Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles

NASA Astrophysics Data System (ADS)

Hu, Xuemin; Chen, Long; Tang, Bo; Cao, Dongpu; He, Haibo

2018-02-01

This paper presents a real-time dynamic path planning method for autonomous driving that avoids both static and moving obstacles. The proposed path planning method determines not only an optimal path, but also the appropriate acceleration and speed for a vehicle. In this method, we first construct a center line from a set of predefined waypoints, which are usually obtained from a lane-level map. A series of path candidates are generated by the arc length and offset to the center line in the s - ρ coordinate system. Then, all of these candidates are converted into Cartesian coordinates. The optimal path is selected considering the total cost of static safety, comfortability, and dynamic safety; meanwhile, the appropriate acceleration and speed for the optimal path are also identified. Various types of roads, including single-lane roads and multi-lane roads with static and moving obstacles, are designed to test the proposed method. The simulation results demonstrate the effectiveness of the proposed method, and indicate its wide practical application to autonomous driving.

Optimised collision avoidance for an ultra-close rendezvous with a failed satellite based on the Gauss pseudospectral method

NASA Astrophysics Data System (ADS)

Chu, Xiaoyu; Zhang, Jingrui; Lu, Shan; Zhang, Yao; Sun, Yue

2016-11-01

This paper presents a trajectory planning algorithm to optimise the collision avoidance of a chasing spacecraft operating in an ultra-close proximity to a failed satellite. The complex configuration and the tumbling motion of the failed satellite are considered. The two-spacecraft rendezvous dynamics are formulated based on the target body frame, and the collision avoidance constraints are detailed, particularly concerning the uncertainties. An optimisation solution of the approaching problem is generated using the Gauss pseudospectral method. A closed-loop control is used to track the optimised trajectory. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms.

Design and performance evaluation of a distributed OFDMA-based MAC protocol for MANETs.

PubMed

Park, Jaesung; Chung, Jiyoung; Lee, Hyungyu; Lee, Jung-Ryun

2014-01-01

In this paper, we propose a distributed MAC protocol for OFDMA-based wireless mobile ad hoc multihop networks, in which the resource reservation and data transmission procedures are operated in a distributed manner. A frame format is designed considering the characteristics of OFDMA that each node can transmit or receive data to or from multiple nodes simultaneously. Under this frame structure, we propose a distributed resource management method including network state estimation and resource reservation processes. We categorize five types of logical errors according to their root causes and show that two of the logical errors are inevitable while three of them are avoided under the proposed distributed MAC protocol. In addition, we provide a systematic method to determine the advertisement period of each node by presenting a clear relation between the accuracy of estimated network states and the signaling overhead. We evaluate the performance of the proposed protocol in respect of the reservation success rate and the success rate of data transmission. Since our method focuses on avoiding logical errors, it could be easily placed on top of the other resource allocation methods focusing on the physical layer issues of the resource management problem and interworked with them.

Method for Predicting Thermal Buckling in Rails

DOT National Transportation Integrated Search

2018-01-01

A method is proposed herein for predicting the onset of thermal buckling in rails in such a way as to provide a means of avoiding this type of potentially devastating failure. The method consists of the development of a thermomechanical model of rail...

Path optimization method for the sign problem

NASA Astrophysics Data System (ADS)

Ohnishi, Akira; Mori, Yuto; Kashiwa, Kouji

2018-03-01

We propose a path optimization method (POM) to evade the sign problem in the Monte-Carlo calculations for complex actions. Among many approaches to the sign problem, the Lefschetz-thimble path-integral method and the complex Langevin method are promising and extensively discussed. In these methods, real field variables are complexified and the integration manifold is determined by the flow equations or stochastically sampled. When we have singular points of the action or multiple critical points near the original integral surface, however, we have a risk to encounter the residual and global sign problems or the singular drift term problem. One of the ways to avoid the singular points is to optimize the integration path which is designed not to hit the singular points of the Boltzmann weight. By specifying the one-dimensional integration-path as z = t +if(t)(f ɛ R) and by optimizing f(t) to enhance the average phase factor, we demonstrate that we can avoid the sign problem in a one-variable toy model for which the complex Langevin method is found to fail. In this proceedings, we propose POM and discuss how we can avoid the sign problem in a toy model. We also discuss the possibility to utilize the neural network to optimize the path.

Model Predictive Control considering Reachable Range of Wheels for Leg / Wheel Mobile Robots

NASA Astrophysics Data System (ADS)

Suzuki, Naito; Nonaka, Kenichiro; Sekiguchi, Kazuma

2016-09-01

Obstacle avoidance is one of the important tasks for mobile robots. In this paper, we study obstacle avoidance control for mobile robots equipped with four legs comprised of three DoF SCARA leg/wheel mechanism, which enables the robot to change its shape adapting to environments. Our previous method achieves obstacle avoidance by model predictive control (MPC) considering obstacle size and lateral wheel positions. However, this method does not ensure existence of joint angles which achieves reference wheel positions calculated by MPC. In this study, we propose a model predictive control considering reachable mobile ranges of wheels positions by combining multiple linear constraints, where each reachable mobile range is approximated as a convex trapezoid. Thus, we achieve to formulate a MPC as a quadratic problem with linear constraints for nonlinear problem of longitudinal and lateral wheel position control. By optimization of MPC, the reference wheel positions are calculated, while each joint angle is determined by inverse kinematics. Considering reachable mobile ranges explicitly, the optimal joint angles are calculated, which enables wheels to reach the reference wheel positions. We verify its advantages by comparing the proposed method with the previous method through numerical simulations.

Scalable parallel elastic-plastic finite element analysis using a quasi-Newton method with a balancing domain decomposition preconditioner

NASA Astrophysics Data System (ADS)

Yusa, Yasunori; Okada, Hiroshi; Yamada, Tomonori; Yoshimura, Shinobu

2018-04-01

A domain decomposition method for large-scale elastic-plastic problems is proposed. The proposed method is based on a quasi-Newton method in conjunction with a balancing domain decomposition preconditioner. The use of a quasi-Newton method overcomes two problems associated with the conventional domain decomposition method based on the Newton-Raphson method: (1) avoidance of a double-loop iteration algorithm, which generally has large computational complexity, and (2) consideration of the local concentration of nonlinear deformation, which is observed in elastic-plastic problems with stress concentration. Moreover, the application of a balancing domain decomposition preconditioner ensures scalability. Using the conventional and proposed domain decomposition methods, several numerical tests, including weak scaling tests, were performed. The convergence performance of the proposed method is comparable to that of the conventional method. In particular, in elastic-plastic analysis, the proposed method exhibits better convergence performance than the conventional method.

Method and System for Air Traffic Rerouting for Airspace Constraint Resolution

NASA Technical Reports Server (NTRS)

Erzberger, Heinz (Inventor); Morando, Alexander R. (Inventor); Sheth, Kapil S. (Inventor); McNally, B. David (Inventor); Clymer, Alexis A. (Inventor); Shih, Fu-tai (Inventor)

2017-01-01

A dynamic constraint avoidance route system automatically analyzes routes of aircraft flying, or to be flown, in or near constraint regions and attempts to find more time and fuel efficient reroutes around current and predicted constraints. The dynamic constraint avoidance route system continuously analyzes all flight routes and provides reroute advisories that are dynamically updated in real time. The dynamic constraint avoidance route system includes a graphical user interface that allows users to visualize, evaluate, modify if necessary, and implement proposed reroutes.

Formation flight and collision avoidance for multiple UAVs based on modified tentacle algorithm in unstructured environments

PubMed Central

2017-01-01

This paper presents a method for formation flight and collision avoidance of multiple UAVs. Due to the shortcomings such as collision avoidance caused by UAV’s high-speed and unstructured environments, this paper proposes a modified tentacle algorithm to ensure the high performance of collision avoidance. Different from the conventional tentacle algorithm which uses inverse derivation, the modified tentacle algorithm rapidly matches the radius of each tentacle and the steering command, ensuring that the data calculation problem in the conventional tentacle algorithm is solved. Meanwhile, both the speed sets and tentacles in one speed set are reduced and reconstructed so as to be applied to multiple UAVs. Instead of path iterative optimization, the paper selects the best tentacle to obtain the UAV collision avoidance path quickly. The simulation results show that the method presented in the paper effectively enhances the performance of flight formation and collision avoidance for multiple high-speed UAVs in unstructured environments. PMID:28763498

A Proposal of Operational Risk Management Method Using FMEA for Drug Manufacturing Computerized System

NASA Astrophysics Data System (ADS)

Takahashi, Masakazu; Nanba, Reiji; Fukue, Yoshinori

This paper proposes operational Risk Management (RM) method using Failure Mode and Effects Analysis (FMEA) for drug manufacturing computerlized system (DMCS). The quality of drug must not be influenced by failures and operational mistakes of DMCS. To avoid such situation, DMCS has to be conducted enough risk assessment and taken precautions. We propose operational RM method using FMEA for DMCS. To propose the method, we gathered and compared the FMEA results of DMCS, and develop a list that contains failure modes, failures and countermeasures. To apply this list, we can conduct RM in design phase, find failures, and conduct countermeasures efficiently. Additionally, we can find some failures that have not been found yet.

A Model for QoS – Aware Wireless Communication in Hospitals

PubMed Central

Alavikia, Zahra; Khadivi, Pejman; Hashemi, Masoud Reza

2012-01-01

In the recent decade, research regarding wireless applications in electronic health (e-Health) services has been increasing. The main benefits of using wireless technologies in e-Health applications are simple communications, fast delivery of medical information, reducing treatment cost and also reducing the medical workers’ error rate. However, using wireless communications in sensitive healthcare environment raises electromagnetic interference (EMI). One of the most effective methods to avoid the EMI problem is power management. To this end, some of methods have been proposed in the literature to reduce EMI effects in health care environments. However, using these methods may result in nonaccurate interference avoidance and also may increase network complexity. To overcome these problems, we introduce two approaches based on per-user location and hospital sectoring for power management in sensitive healthcare environments. Although reducing transmission power could avoid EMI, it causes a number of successful message deliveries to the access point to decrease and, hence, the quality of service requirements cannot be meet. In this paper, we propose the use of relays for decreasing the probability of outage in the aforementioned scenario. Relay placement is the main factor to enjoy the usefulness of relay station benefits in the network and, therefore, we use the genetic algorithm to compute the optimum positions of a fixed number of relays. We have considered delay and maximum blind point coverage as two main criteria in relay station problem. The performance of the proposed method in outage reduction is investigated through simulations. PMID:23493832

A Model for QoS - Aware Wireless Communication in Hospitals.

PubMed

Alavikia, Zahra; Khadivi, Pejman; Hashemi, Masoud Reza

2012-01-01

In the recent decade, research regarding wireless applications in electronic health (e-Health) services has been increasing. The main benefits of using wireless technologies in e-Health applications are simple communications, fast delivery of medical information, reducing treatment cost and also reducing the medical workers' error rate. However, using wireless communications in sensitive healthcare environment raises electromagnetic interference (EMI). One of the most effective methods to avoid the EMI problem is power management. To this end, some of methods have been proposed in the literature to reduce EMI effects in health care environments. However, using these methods may result in nonaccurate interference avoidance and also may increase network complexity. To overcome these problems, we introduce two approaches based on per-user location and hospital sectoring for power management in sensitive healthcare environments. Although reducing transmission power could avoid EMI, it causes a number of successful message deliveries to the access point to decrease and, hence, the quality of service requirements cannot be meet. In this paper, we propose the use of relays for decreasing the probability of outage in the aforementioned scenario. Relay placement is the main factor to enjoy the usefulness of relay station benefits in the network and, therefore, we use the genetic algorithm to compute the optimum positions of a fixed number of relays. We have considered delay and maximum blind point coverage as two main criteria in relay station problem. The performance of the proposed method in outage reduction is investigated through simulations.

Boundary-to-Marker Evidence-Controlled Segmentation and MDL-Based Contour Inference for Overlapping Nuclei.

PubMed

Song, Jie; Xiao, Liang; Lian, Zhichao

2017-03-01

This paper presents a novel method for automated morphology delineation and analysis of cell nuclei in histopathology images. Combining the initial segmentation information and concavity measurement, the proposed method first segments clusters of nuclei into individual pieces, avoiding segmentation errors introduced by the scale-constrained Laplacian-of-Gaussian filtering. After that a nuclear boundary-to-marker evidence computing is introduced to delineate individual objects after the refined segmentation process. The obtained evidence set is then modeled by the periodic B-splines with the minimum description length principle, which achieves a practical compromise between the complexity of the nuclear structure and its coverage of the fluorescence signal to avoid the underfitting and overfitting results. The algorithm is computationally efficient and has been tested on the synthetic database as well as 45 real histopathology images. By comparing the proposed method with several state-of-the-art methods, experimental results show the superior recognition performance of our method and indicate the potential applications of analyzing the intrinsic features of nuclei morphology.

Calibration-independent measurement of complex permittivity of liquids using a coaxial transmission line

NASA Astrophysics Data System (ADS)

Guoxin, Cheng

2015-01-01

In recent years, several calibration-independent transmission/reflection methods have been developed to determine the complex permittivity of liquid materials. However, these methods experience their own respective defects, such as the requirement of multi measurement cells, or the presence of air gap effect. To eliminate these drawbacks, a fast calibration-independent method is proposed in this paper. There are two main advantages of the present method over those in the literature. First, only one measurement cell is required. The cell is measured when it is empty and when it is filled with liquid. This avoids the air gap effect in the approach, in which the structure with two reference ports connected with each other is needed to be measured. Second, it eliminates the effects of uncalibrated coaxial cables, adaptors, and plug sections; systematic errors caused by the experimental setup are avoided by the wave cascading matrix manipulations. Using this method, three dielectric reference liquids, i.e., ethanol, ethanediol, and pure water, and low-loss transformer oil are measured over a wide frequency range to validate the proposed method. Their accuracy is assessed by comparing the results with those obtained from the other well known techniques. It is demonstrated that this proposed method can be used as a robust approach for fast complex permittivity determination of liquid materials.

Morphological rational multi-scale algorithm for color contrast enhancement

NASA Astrophysics Data System (ADS)

Peregrina-Barreto, Hayde; Terol-Villalobos, Iván R.

2010-01-01

Contrast enhancement main goal consists on improving the image visual appearance but also it is used for providing a transformed image in order to segment it. In mathematical morphology several works have been derived from the framework theory for contrast enhancement proposed by Meyer and Serra. However, when working with images with a wide range of scene brightness, as for example when strong highlights and deep shadows appear in the same image, the proposed morphological methods do not allow the enhancement. In this work, a rational multi-scale method, which uses a class of morphological connected filters called filters by reconstruction, is proposed. Granulometry is used by finding the more accurate scales for filters and with the aim of avoiding the use of other little significant scales. The CIE-u'v'Y' space was used to introduce our results since it takes into account the Weber's Law and by avoiding the creation of new colors it permits to modify the luminance values without affecting the hue. The luminance component ('Y) is enhanced separately using the proposed method, next it is used for enhancing the chromatic components (u', v') by means of the center of gravity law of color mixing.

Optical image encryption method based on incoherent imaging and polarized light encoding

NASA Astrophysics Data System (ADS)

Wang, Q.; Xiong, D.; Alfalou, A.; Brosseau, C.

2018-05-01

We propose an incoherent encoding system for image encryption based on a polarized encoding method combined with an incoherent imaging. Incoherent imaging is the core component of this proposal, in which the incoherent point-spread function (PSF) of the imaging system serves as the main key to encode the input intensity distribution thanks to a convolution operation. An array of retarders and polarizers is placed on the input plane of the imaging structure to encrypt the polarized state of light based on Mueller polarization calculus. The proposal makes full use of randomness of polarization parameters and incoherent PSF so that a multidimensional key space is generated to deal with illegal attacks. Mueller polarization calculus and incoherent illumination of imaging structure ensure that only intensity information is manipulated. Another key advantage is that complicated processing and recording related to a complex-valued signal are avoided. The encoded information is just an intensity distribution, which is advantageous for data storage and transition because information expansion accompanying conventional encryption methods is also avoided. The decryption procedure can be performed digitally or using optoelectronic devices. Numerical simulation tests demonstrate the validity of the proposed scheme.

Trade off between variable and fixed size normalization in orthogonal polynomials based iris recognition system.

PubMed

Krishnamoorthi, R; Anna Poorani, G

2016-01-01

Iris normalization is an important stage in any iris biometric, as it has a propensity to trim down the consequences of iris distortion. To indemnify the variation in size of the iris owing to the action of stretching or enlarging the pupil in iris acquisition process and camera to eyeball distance, two normalization schemes has been proposed in this work. In the first method, the iris region of interest is normalized by converting the iris into the variable size rectangular model in order to avoid the under samples near the limbus border. In the second method, the iris region of interest is normalized by converting the iris region into a fixed size rectangular model in order to avoid the dimensional discrepancies between the eye images. The performance of the proposed normalization methods is evaluated with orthogonal polynomials based iris recognition in terms of FAR, FRR, GAR, CRR and EER.

An Unconditionally Stable, Positivity-Preserving Splitting Scheme for Nonlinear Black-Scholes Equation with Transaction Costs

PubMed Central

Guo, Jianqiang; Wang, Wansheng

2014-01-01

This paper deals with the numerical analysis of nonlinear Black-Scholes equation with transaction costs. An unconditionally stable and monotone splitting method, ensuring positive numerical solution and avoiding unstable oscillations, is proposed. This numerical method is based on the LOD-Backward Euler method which allows us to solve the discrete equation explicitly. The numerical results for vanilla call option and for European butterfly spread are provided. It turns out that the proposed scheme is efficient and reliable. PMID:24895653

An unconditionally stable, positivity-preserving splitting scheme for nonlinear Black-Scholes equation with transaction costs.

PubMed

Guo, Jianqiang; Wang, Wansheng

2014-01-01

This paper deals with the numerical analysis of nonlinear Black-Scholes equation with transaction costs. An unconditionally stable and monotone splitting method, ensuring positive numerical solution and avoiding unstable oscillations, is proposed. This numerical method is based on the LOD-Backward Euler method which allows us to solve the discrete equation explicitly. The numerical results for vanilla call option and for European butterfly spread are provided. It turns out that the proposed scheme is efficient and reliable.

Resolving occlusion and segmentation errors in multiple video object tracking

NASA Astrophysics Data System (ADS)

Cheng, Hsu-Yung; Hwang, Jenq-Neng

2009-02-01

In this work, we propose a method to integrate the Kalman filter and adaptive particle sampling for multiple video object tracking. The proposed framework is able to detect occlusion and segmentation error cases and perform adaptive particle sampling for accurate measurement selection. Compared with traditional particle filter based tracking methods, the proposed method generates particles only when necessary. With the concept of adaptive particle sampling, we can avoid degeneracy problem because the sampling position and range are dynamically determined by parameters that are updated by Kalman filters. There is no need to spend time on processing particles with very small weights. The adaptive appearance for the occluded object refers to the prediction results of Kalman filters to determine the region that should be updated and avoids the problem of using inadequate information to update the appearance under occlusion cases. The experimental results have shown that a small number of particles are sufficient to achieve high positioning and scaling accuracy. Also, the employment of adaptive appearance substantially improves the positioning and scaling accuracy on the tracking results.

Morphological rational operator for contrast enhancement.

PubMed

Peregrina-Barreto, Hayde; Herrera-Navarro, Ana M; Morales-Hernández, Luis A; Terol-Villalobos, Iván R

2011-03-01

Contrast enhancement is an important task in image processing that is commonly used as a preprocessing step to improve the images for other tasks such as segmentation. However, some methods for contrast improvement that work well in low-contrast regions affect good contrast regions as well. This occurs due to the fact that some elements may vanish. A method focused on images with different luminance conditions is introduced in the present work. The proposed method is based on morphological transformations by reconstruction and rational operations, which, altogether, allow a more accurate contrast enhancement resulting in regions that are in harmony with their environment. Furthermore, due to the properties of these morphological transformations, the creation of new elements on the image is avoided. The processing is carried out on luminance values in the u'v'Y color space, which avoids the creation of new colors. As a result of the previous considerations, the proposed method keeps the natural color appearance of the image.

Shooting method for solution of boundary-layer flows with massive blowing

NASA Technical Reports Server (NTRS)

Liu, T.-M.; Nachtsheim, P. R.

1973-01-01

A modified, bidirectional shooting method is presented for solving boundary-layer equations under conditions of massive blowing. Unlike the conventional shooting method, which is unstable when the blowing rate increases, the proposed method avoids the unstable direction and is capable of solving complex boundary-layer problems involving mass and energy balance on the surface.

Probability-based hazard avoidance guidance for planetary landing

NASA Astrophysics Data System (ADS)

Yuan, Xu; Yu, Zhengshi; Cui, Pingyuan; Xu, Rui; Zhu, Shengying; Cao, Menglong; Luan, Enjie

2018-03-01

Future landing and sample return missions on planets and small bodies will seek landing sites with high scientific value, which may be located in hazardous terrains. Autonomous landing in such hazardous terrains and highly uncertain planetary environments is particularly challenging. Onboard hazard avoidance ability is indispensable, and the algorithms must be robust to uncertainties. In this paper, a novel probability-based hazard avoidance guidance method is developed for landing in hazardous terrains on planets or small bodies. By regarding the lander state as probabilistic, the proposed guidance algorithm exploits information on the uncertainty of lander position and calculates the probability of collision with each hazard. The collision probability serves as an accurate safety index, which quantifies the impact of uncertainties on the lander safety. Based on the collision probability evaluation, the state uncertainty of the lander is explicitly taken into account in the derivation of the hazard avoidance guidance law, which contributes to enhancing the robustness to the uncertain dynamics of planetary landing. The proposed probability-based method derives fully analytic expressions and does not require off-line trajectory generation. Therefore, it is appropriate for real-time implementation. The performance of the probability-based guidance law is investigated via a set of simulations, and the effectiveness and robustness under uncertainties are demonstrated.

Format conversion between CAD data and GIS data based on ArcGIS

NASA Astrophysics Data System (ADS)

Xie, Qingqing; Wei, Bo; Zhang, Kailin; Wang, Zhichao

2015-12-01

To make full use of the data resources and realize a sharing for the different types of data in different industries, a method of format conversion between CAD data and GIS data based on ArcGIS was proposed. To keep the integrity of the converted data, some key steps to process CAD data before conversion were made in AutoCAD. For examples, deleting unnecessary elements such as title, border and legend avoided the appearance of unnecessary elements after conversion, as layering data again by a national standard avoided the different types of elements to appear in a same layer after conversion. In ArcGIS, converting CAD data to GIS data was executed by the correspondence of graphic element classification between AutoCAD and ArcGIS. In addition, an empty geographic database and feature set was required to create in ArcGIS for storing the text data of CAD data. The experimental results show that the proposed method avoids a large amount of editing work in data conversion and maintains the integrity of spatial data and attribute data between before and after conversion.

Design principles for contamination abatement in scientific satellites.

NASA Technical Reports Server (NTRS)

Naumann, R. J.

1972-01-01

It is shown that deposition of contamination films on satellite optics can be controlled by the following means: isolating critical optical surfaces from the rest of the spacecraft; avoiding or minimizing the use of nonmetallic material, particularly near or in line of sight of optical surfaces; avoiding materials with high vapor pressures; subjecting materials to vacuum baking prior to use, to drive off the volatile outgassing products; keeping the critical surfaces at temperatures above the ambient; avoiding elevated operational temperatures for nonmetallic materials; paying special attention to optics exposed to intense UV-, X-ray, or particular radiation; avoiding water-vapor sources; and directing RCS plumes away from critical surfaces. Methods of controlling particulate contaminants are also proposed.

Handwritten digits recognition using HMM and PSO based on storks

NASA Astrophysics Data System (ADS)

Yan, Liao; Jia, Zhenhong; Yang, Jie; Pang, Shaoning

2010-07-01

A new method for handwritten digits recognition based on hidden markov model (HMM) and particle swarm optimization (PSO) is proposed. This method defined 24 strokes with the sense of directional, to make up for the shortage that is sensitive in choice of stating point in traditional methods, but also reduce the ambiguity caused by shakes. Make use of excellent global convergence of PSO; improving the probability of finding the optimum and avoiding local infinitesimal obviously. Experimental results demonstrate that compared with the traditional methods, the proposed method can make most of the recognition rate of handwritten digits improved.

An extended Lagrangian method

NASA Technical Reports Server (NTRS)

Liou, Meng-Sing

1993-01-01

A unique formulation of describing fluid motion is presented. The method, referred to as 'extended Lagrangian method', is interesting from both theoretical and numerical points of view. The formulation offers accuracy in numerical solution by avoiding numerical diffusion resulting from mixing of fluxes in the Eulerian description. Meanwhile, it also avoids the inaccuracy incurred due to geometry and variable interpolations used by the previous Lagrangian methods. The present method is general and capable of treating subsonic flows as well as supersonic flows. The method proposed in this paper is robust and stable. It automatically adapts to flow features without resorting to clustering, thereby maintaining rather uniform grid spacing throughout and large time step. Moreover, the method is shown to resolve multidimensional discontinuities with a high level of accuracy, similar to that found in 1D problems.

High-accuracy resolver-to-digital conversion via phase locked loop based on PID controller

NASA Astrophysics Data System (ADS)

Li, Yaoling; Wu, Zhong

2018-03-01

The problem of resolver-to-digital conversion (RDC) is transformed into the problem of angle tracking control, and a phase locked loop (PLL) method based on PID controller is proposed in this paper. This controller comprises a typical PI controller plus an incomplete differential which can avoid the amplification of higher-frequency noise components by filtering the phase detection error with a low-pass filter. Compared with conventional ones, the proposed PLL method makes the converter a system of type III and thus the conversion accuracy can be improved. Experimental results demonstrate the effectiveness of the proposed method.

Hue-preserving and saturation-improved color histogram equalization algorithm.

PubMed

Song, Ki Sun; Kang, Hee; Kang, Moon Gi

2016-06-01

In this paper, an algorithm is proposed to improve contrast and saturation without color degradation. The local histogram equalization (HE) method offers better performance than the global HE method, whereas the local HE method sometimes produces undesirable results due to the block-based processing. The proposed contrast-enhancement (CE) algorithm reflects the characteristics of the global HE method in the local HE method to avoid the artifacts, while global and local contrasts are enhanced. There are two ways to apply the proposed CE algorithm to color images. One is luminance processing methods, and the other one is each channel processing methods. However, these ways incur excessive or reduced saturation and color degradation problems. The proposed algorithm solves these problems by using channel adaptive equalization and similarity of ratios between the channels. Experimental results show that the proposed algorithm enhances contrast and saturation while preserving the hue and producing better performance than existing methods in terms of objective evaluation metrics.

Complex Matrix for the Analysis of Sustainable Transformative Learning: An Assessment Methodology of Sustainability Integration in Universities

ERIC Educational Resources Information Center

Palma, Lisiane Celia; Pedrozo, Eugênio Ávila

2015-01-01

Several papers propose analytical methods relating to the inclusion of sustainability in courses and universities. However, as sustainability is a complex subject, methodological proposals on the topic must avoid making disjointed analyses which focus exclusively on curricula or on organisational strategy, as often seen in the literature.…

Obstacle Detection and Avoidance System Based on Monocular Camera and Size Expansion Algorithm for UAVs

PubMed Central

Al-Kaff, Abdulla; García, Fernando; Martín, David; De La Escalera, Arturo; Armingol, José María

2017-01-01

One of the most challenging problems in the domain of autonomous aerial vehicles is the designing of a robust real-time obstacle detection and avoidance system. This problem is complex, especially for the micro and small aerial vehicles, that is due to the Size, Weight and Power (SWaP) constraints. Therefore, using lightweight sensors (i.e., Digital camera) can be the best choice comparing with other sensors; such as laser or radar.For real-time applications, different works are based on stereo cameras in order to obtain a 3D model of the obstacles, or to estimate their depth. Instead, in this paper, a method that mimics the human behavior of detecting the collision state of the approaching obstacles using monocular camera is proposed. The key of the proposed algorithm is to analyze the size changes of the detected feature points, combined with the expansion ratios of the convex hull constructed around the detected feature points from consecutive frames. During the Aerial Vehicle (UAV) motion, the detection algorithm estimates the changes in the size of the area of the approaching obstacles. First, the method detects the feature points of the obstacles, then extracts the obstacles that have the probability of getting close toward the UAV. Secondly, by comparing the area ratio of the obstacle and the position of the UAV, the method decides if the detected obstacle may cause a collision. Finally, by estimating the obstacle 2D position in the image and combining with the tracked waypoints, the UAV performs the avoidance maneuver. The proposed algorithm was evaluated by performing real indoor and outdoor flights, and the obtained results show the accuracy of the proposed algorithm compared with other related works. PMID:28481277

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction

PubMed Central

Lu, Hongyang; Wei, Jingbo; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values. PMID:27110235

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction.

PubMed

Lu, Hongyang; Wei, Jingbo; Liu, Qiegen; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.

Multi-resolution analysis for ear recognition using wavelet features

NASA Astrophysics Data System (ADS)

Shoaib, M.; Basit, A.; Faye, I.

2016-11-01

Security is very important and in order to avoid any physical contact, identification of human when they are moving is necessary. Ear biometric is one of the methods by which a person can be identified using surveillance cameras. Various techniques have been proposed to increase the ear based recognition systems. In this work, a feature extraction method for human ear recognition based on wavelet transforms is proposed. The proposed features are approximation coefficients and specific details of level two after applying various types of wavelet transforms. Different wavelet transforms are applied to find the suitable wavelet. Minimum Euclidean distance is used as a matching criterion. Results achieved by the proposed method are promising and can be used in real time ear recognition system.

Real-time obstacle avoidance using harmonic potential functions

NASA Technical Reports Server (NTRS)

Kim, Jin-Oh; Khosla, Pradeep K.

1992-01-01

This paper presents a new formulation of the artificial potential approach to the obstacle avoidance problem for a mobile robot or a manipulator in a known environment. Previous formulations of artificial potentials for obstacle avoidance have exhibited local minima in a cluttered environment. To build an artificial potential field, harmonic functions that completely eliminate local minima even for a cluttered environment are used. The panel method is employed to represent arbitrarily shaped obstacles and to derive the potential over the whole space. Based on this potential function, an elegant control strategy is proposed for the real-time control of a robot. The harmonic potential, the panel method, and the control strategy are tested with a bar-shaped mobile robot and a three-degree-of-freedom planar redundant manipulator.

Correction of Excessive Precipitation over Steep and High Mountains in a GCM: A Simple Method of Parameterizing the Thermal Effects of Subgrid Topographic Variation

NASA Technical Reports Server (NTRS)

Chao, Winston C.

2015-01-01

The excessive precipitation over steep and high mountains (EPSM) in GCMs and meso-scale models is due to a lack of parameterization of the thermal effects of the subgrid-scale topographic variation. These thermal effects drive subgrid-scale heated slope induced vertical circulations (SHVC). SHVC provide a ventilation effect of removing heat from the boundary layer of resolvable-scale mountain slopes and depositing it higher up. The lack of SHVC parameterization is the cause of EPSM. The author has previously proposed a method of parameterizing SHVC, here termed SHVC.1. Although this has been successful in avoiding EPSM, the drawback of SHVC.1 is that it suppresses convective type precipitation in the regions where it is applied. In this article we propose a new method of parameterizing SHVC, here termed SHVC.2. In SHVC.2 the potential temperature and mixing ratio of the boundary layer are changed when used as input to the cumulus parameterization scheme over mountainous regions. This allows the cumulus parameterization to assume the additional function of SHVC parameterization. SHVC.2 has been tested in NASA Goddard's GEOS-5 GCM. It achieves the primary goal of avoiding EPSM while also avoiding the suppression of convective-type precipitation in regions where it is applied.

Improvement of "Novel Multiparty Quantum Key Agreement Protocol with GHZ States"

NASA Astrophysics Data System (ADS)

Gu, Jun; Hwang, Tzonelih

2017-10-01

Quantum key agreement (QKA) protocol is a method for negotiating a fair and secure key among mutually untrusted participants. Recently, Xu et al. (Quantum Inf. Process. 13:2587-2594, 2014) proposed a multi-party QKA protocol based on Greenberger-Horne-Zeilinger (GHZ) states. However, this study points out that Xu et al.'s protocol cannot provide the fairness property. That is, the last involved participant in the protocol can manipulate the final shared secret key without being detected by the other participants. Moreover, according to Yu et al.'s research (2015), Xu et al.'s protocol cannot avoid the public discussion attack too. To avoid these weaknesses, an improved QKA protocol is proposed.

[GSH fermentation process modeling using entropy-criterion based RBF neural network model].

PubMed

Tan, Zuoping; Wang, Shitong; Deng, Zhaohong; Du, Guocheng

2008-05-01

The prediction accuracy and generalization of GSH fermentation process modeling are often deteriorated by noise existing in the corresponding experimental data. In order to avoid this problem, we present a novel RBF neural network modeling approach based on entropy criterion. It considers the whole distribution structure of the training data set in the parameter learning process compared with the traditional MSE-criterion based parameter learning, and thus effectively avoids the weak generalization and over-learning. Then the proposed approach is applied to the GSH fermentation process modeling. Our results demonstrate that this proposed method has better prediction accuracy, generalization and robustness such that it offers a potential application merit for the GSH fermentation process modeling.

A proposed UAV for indoor patient care.

PubMed

Todd, Catherine; Watfa, Mohamed; El Mouden, Yassine; Sahir, Sana; Ali, Afrah; Niavarani, Ali; Lutfi, Aoun; Copiaco, Abigail; Agarwal, Vaibhavi; Afsari, Kiyan; Johnathon, Chris; Okafor, Onyeka; Ayad, Marina

2015-09-10

Indoor flight, obstacle avoidance and client-server communication of an Unmanned Aerial Vehicle (UAV) raises several unique research challenges. This paper examines current methods and associated technologies adapted within the literature toward autonomous UAV flight, for consideration in a proposed system for indoor healthcare administration with a quadcopter. We introduce Healthbuddy, a unique research initiative towards overcoming challenges associated with indoor navigation, collision detection and avoidance, stability, wireless drone-server communications and automated decision support for patient care in a GPS-denied environment. To address the identified research deficits, a drone-based solution is presented. The solution is preliminary as we develop and refine the suggested algorithms and hardware system to achieve the research objectives.

Modeling error distributions of growth curve models through Bayesian methods.

PubMed

Zhang, Zhiyong

2016-06-01

Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is proposed to flexibly model normal and non-normal data through the explicit specification of the error distributions. A simulation study shows when the distribution of the error is correctly specified, one can avoid the loss in the efficiency of standard error estimates. A real example on the analysis of mathematical ability growth data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 is used to show the application of the proposed methods. Instructions and code on how to conduct growth curve analysis with both normal and non-normal error distributions using the the MCMC procedure of SAS are provided.

An opinion formation based binary optimization approach for feature selection

NASA Astrophysics Data System (ADS)

Hamedmoghadam, Homayoun; Jalili, Mahdi; Yu, Xinghuo

2018-02-01

This paper proposed a novel optimization method based on opinion formation in complex network systems. The proposed optimization technique mimics human-human interaction mechanism based on a mathematical model derived from social sciences. Our method encodes a subset of selected features to the opinion of an artificial agent and simulates the opinion formation process among a population of agents to solve the feature selection problem. The agents interact using an underlying interaction network structure and get into consensus in their opinions, while finding better solutions to the problem. A number of mechanisms are employed to avoid getting trapped in local minima. We compare the performance of the proposed method with a number of classical population-based optimization methods and a state-of-the-art opinion formation based method. Our experiments on a number of high dimensional datasets reveal outperformance of the proposed algorithm over others.

Preconditioned alternating direction method of multipliers for inverse problems with constraints

NASA Astrophysics Data System (ADS)

Jiao, Yuling; Jin, Qinian; Lu, Xiliang; Wang, Weijie

2017-02-01

We propose a preconditioned alternating direction method of multipliers (ADMM) to solve linear inverse problems in Hilbert spaces with constraints, where the feature of the sought solution under a linear transformation is captured by a possibly non-smooth convex function. During each iteration step, our method avoids solving large linear systems by choosing a suitable preconditioning operator. In case the data is given exactly, we prove the convergence of our preconditioned ADMM without assuming the existence of a Lagrange multiplier. In case the data is corrupted by noise, we propose a stopping rule using information on noise level and show that our preconditioned ADMM is a regularization method; we also propose a heuristic rule when the information on noise level is unavailable or unreliable and give its detailed analysis. Numerical examples are presented to test the performance of the proposed method.

Max-margin multiattribute learning with low-rank constraint.

PubMed

Zhang, Qiang; Chen, Lin; Li, Baoxin

2014-07-01

Attribute learning has attracted a lot of interests in recent years for its advantage of being able to model high-level concepts with a compact set of midlevel attributes. Real-world objects often demand multiple attributes for effective modeling. Most existing methods learn attributes independently without explicitly considering their intrinsic relatedness. In this paper, we propose max margin multiattribute learning with low-rank constraint, which learns a set of attributes simultaneously, using only relative ranking of the attributes for the data. By learning all the attributes simultaneously through low-rank constraint, the proposed method is able to capture their intrinsic correlation for improved learning; by requiring only relative ranking, the method avoids restrictive binary labels of attributes that are often assumed by many existing techniques. The proposed method is evaluated on both synthetic data and real visual data including a challenging video data set. Experimental results demonstrate the effectiveness of the proposed method.

UAV formation control design with obstacle avoidance in dynamic three-dimensional environment.

PubMed

Chang, Kai; Xia, Yuanqing; Huang, Kaoli

2016-01-01

This paper considers the artificial potential field method combined with rotational vectors for a general problem of multi-unmanned aerial vehicle (UAV) systems tracking a moving target in dynamic three-dimensional environment. An attractive potential field is generated between the leader and the target. It drives the leader to track the target based on the relative position of them. The other UAVs in the formation are controlled to follow the leader by the attractive control force. The repulsive force affects among the UAVs to avoid collisions and distribute the UAVs evenly on the spherical surface whose center is the leader-UAV. Specific orders or positions of the UAVs are not required. The trajectories of avoidance obstacle can be obtained through two kinds of potential field with rotation vectors. Every UAV can choose the optimal trajectory to avoid the obstacle and reconfigure the formation after passing the obstacle. Simulations study on UAV are presented to demonstrate the effectiveness of proposed method.

An extended Lagrangian method

NASA Technical Reports Server (NTRS)

Liou, Meng-Sing

1992-01-01

A unique formulation of describing fluid motion is presented. The method, referred to as 'extended Lagrangian method', is interesting from both theoretical and numerical points of view. The formulation offers accuracy in numerical solution by avoiding numerical diffusion resulting from mixing of fluxes in the Eulerian description. Meanwhile, it also avoids the inaccuracy incurred due to geometry and variable interpolations used by the previous Lagrangian methods. Unlike the Lagrangian method previously imposed which is valid only for supersonic flows, the present method is general and capable of treating subsonic flows as well as supersonic flows. The method proposed in this paper is robust and stable. It automatically adapts to flow features without resorting to clustering, thereby maintaining rather uniform grid spacing throughout and large time step. Moreover, the method is shown to resolve multi-dimensional discontinuities with a high level of accuracy, similar to that found in one-dimensional problems.

A Chaotic Ordered Hierarchies Consistency Analysis Performance Evaluation Model

NASA Astrophysics Data System (ADS)

Yeh, Wei-Chang

2013-02-01

The Hierarchies Consistency Analysis (HCA) is proposed by Guh in-cooperated along with some case study on a Resort to reinforce the weakness of Analytical Hierarchy Process (AHP). Although the results obtained enabled aid for the Decision Maker to make more reasonable and rational verdicts, the HCA itself is flawed. In this paper, our objective is to indicate the problems of HCA, and then propose a revised method called chaotic ordered HCA (COH in short) which can avoid problems. Since the COH is based upon Guh's method, the Decision Maker establishes decisions in a way similar to that of the original method.

Highlight removal based on the regional-projection fringe projection method

NASA Astrophysics Data System (ADS)

Qi, Zhaoshuai; Wang, Zhao; Huang, Junhui; Xing, Chao; Gao, Jianmin

2018-04-01

In fringe projection profilometry, highlight usually causes the saturation and blooming in captured fringes and reduces the measurement accuracy. To solve the problem, a regional-projection fringe projection (RP-FP) method is proposed. Regional projection patterns (RP patterns) are projected onto the tested object surface to avoid the saturation and blooming. Then, an image inpainting technique is employed to reconstruct the missing phases in the captured RP patterns and a complete surface of the tested object is obtained. Experiments verified the effectiveness of the proposed method. The method can be widely used in industrial inspections and quality controlling in mechanical and manufacturing industries.

Projection-based stabilization of interface Lagrange multipliers in immersogeometric fluid-thin structure interaction analysis, with application to heart valve modeling.

PubMed

Kamensky, David; Evans, John A; Hsu, Ming-Chen; Bazilevs, Yuri

2017-11-01

This paper discusses a method of stabilizing Lagrange multiplier fields used to couple thin immersed shell structures and surrounding fluids. The method retains essential conservation properties by stabilizing only the portion of the constraint orthogonal to a coarse multiplier space. This stabilization can easily be applied within iterative methods or semi-implicit time integrators that avoid directly solving a saddle point problem for the Lagrange multiplier field. Heart valve simulations demonstrate applicability of the proposed method to 3D unsteady simulations. An appendix sketches the relation between the proposed method and a high-order-accurate approach for simpler model problems.

Memory-optimized shift operator alternating direction implicit finite difference time domain method for plasma

NASA Astrophysics Data System (ADS)

Song, Wanjun; Zhang, Hou

2017-11-01

Through introducing the alternating direction implicit (ADI) technique and the memory-optimized algorithm to the shift operator (SO) finite difference time domain (FDTD) method, the memory-optimized SO-ADI FDTD for nonmagnetized collisional plasma is proposed and the corresponding formulae of the proposed method for programming are deduced. In order to further the computational efficiency, the iteration method rather than Gauss elimination method is employed to solve the equation set in the derivation of the formulae. Complicated transformations and convolutions are avoided in the proposed method compared with the Z transforms (ZT) ADI FDTD method and the piecewise linear JE recursive convolution (PLJERC) ADI FDTD method. The numerical dispersion of the SO-ADI FDTD method with different plasma frequencies and electron collision frequencies is analyzed and the appropriate ratio of grid size to the minimum wavelength is given. The accuracy of the proposed method is validated by the reflection coefficient test on a nonmagnetized collisional plasma sheet. The testing results show that the proposed method is advantageous for improving computational efficiency and saving computer memory. The reflection coefficient of a perfect electric conductor (PEC) sheet covered by multilayer plasma and the RCS of the objects coated by plasma are calculated by the proposed method and the simulation results are analyzed.

Intensity-hue-saturation-based image fusion using iterative linear regression

NASA Astrophysics Data System (ADS)

Cetin, Mufit; Tepecik, Abdulkadir

2016-10-01

The image fusion process basically produces a high-resolution image by combining the superior features of a low-resolution spatial image and a high-resolution panchromatic image. Despite its common usage due to its fast computing capability and high sharpening ability, the intensity-hue-saturation (IHS) fusion method may cause some color distortions, especially when a large number of gray value differences exist among the images to be combined. This paper proposes a spatially adaptive IHS (SA-IHS) technique to avoid these distortions by automatically adjusting the exact spatial information to be injected into the multispectral image during the fusion process. The SA-IHS method essentially suppresses the effects of those pixels that cause the spectral distortions by assigning weaker weights to them and avoiding a large number of redundancies on the fused image. The experimental database consists of IKONOS images, and the experimental results both visually and statistically prove the enhancement of the proposed algorithm when compared with the several other IHS-like methods such as IHS, generalized IHS, fast IHS, and generalized adaptive IHS.

An improved wavelet-Galerkin method for dynamic response reconstruction and parameter identification of shear-type frames

NASA Astrophysics Data System (ADS)

Bu, Haifeng; Wang, Dansheng; Zhou, Pin; Zhu, Hongping

2018-04-01

An improved wavelet-Galerkin (IWG) method based on the Daubechies wavelet is proposed for reconstructing the dynamic responses of shear structures. The proposed method flexibly manages wavelet resolution level according to excitation, thereby avoiding the weakness of the wavelet-Galerkin multiresolution analysis (WGMA) method in terms of resolution and the requirement of external excitation. IWG is implemented by this work in certain case studies, involving single- and n-degree-of-freedom frame structures subjected to a determined discrete excitation. Results demonstrate that IWG performs better than WGMA in terms of accuracy and computation efficiency. Furthermore, a new method for parameter identification based on IWG and an optimization algorithm are also developed for shear frame structures, and a simultaneous identification of structural parameters and excitation is implemented. Numerical results demonstrate that the proposed identification method is effective for shear frame structures.

Reconstruction of fluorescence molecular tomography with a cosinoidal level set method.

PubMed

Zhang, Xuanxuan; Cao, Xu; Zhu, Shouping

2017-06-27

Implicit shape-based reconstruction method in fluorescence molecular tomography (FMT) is capable of achieving higher image clarity than image-based reconstruction method. However, the implicit shape method suffers from a low convergence speed and performs unstably due to the utilization of gradient-based optimization methods. Moreover, the implicit shape method requires priori information about the number of targets. A shape-based reconstruction scheme of FMT with a cosinoidal level set method is proposed in this paper. The Heaviside function in the classical implicit shape method is replaced with a cosine function, and then the reconstruction can be accomplished with the Levenberg-Marquardt method rather than gradient-based methods. As a result, the priori information about the number of targets is not required anymore and the choice of step length is avoided. Numerical simulations and phantom experiments were carried out to validate the proposed method. Results of the proposed method show higher contrast to noise ratios and Pearson correlations than the implicit shape method and image-based reconstruction method. Moreover, the number of iterations required in the proposed method is much less than the implicit shape method. The proposed method performs more stably, provides a faster convergence speed than the implicit shape method, and achieves higher image clarity than the image-based reconstruction method.

A Multipurpose Apparatus to Measure Viscosity and Surface Tension of Solutions: The Measurement of the Molecular Cross-Sectional Area of N-Proposal

ERIC Educational Resources Information Center

Xin Zhang; Shouxin Liu; Booxin Li; Na An; Fan Zhang

2004-01-01

A multipurpose apparatus that can be used to measure the viscosity of solution by the Ostwald method and the surface tension of solution by the drop-weight method or by the capillary-rise method is developed. The apparatus is convenient for in-situ preparation of solutions of different concentrations and avoids the error that frothing of the…

Adaptive Discrete Hypergraph Matching.

PubMed

Yan, Junchi; Li, Changsheng; Li, Yin; Cao, Guitao

2018-02-01

This paper addresses the problem of hypergraph matching using higher-order affinity information. We propose a solver that iteratively updates the solution in the discrete domain by linear assignment approximation. The proposed method is guaranteed to converge to a stationary discrete solution and avoids the annealing procedure and ad-hoc post binarization step that are required in several previous methods. Specifically, we start with a simple iterative discrete gradient assignment solver. This solver can be trapped in an -circle sequence under moderate conditions, where is the order of the graph matching problem. We then devise an adaptive relaxation mechanism to jump out this degenerating case and show that the resulting new path will converge to a fixed solution in the discrete domain. The proposed method is tested on both synthetic and real-world benchmarks. The experimental results corroborate the efficacy of our method.

Video markers tracking methods for bike fitting

NASA Astrophysics Data System (ADS)

Rajkiewicz, Piotr; Łepkowska, Katarzyna; Cygan, Szymon

2015-09-01

Sports cycling is becoming increasingly popular over last years. Obtaining and maintaining a proper position on the bike has been shown to be crucial for performance, comfort and injury avoidance. Various techniques of bike fitting are available - from rough settings based on body dimensions to professional services making use of sophisticated equipment and expert knowledge. Modern fitting techniques use mainly joint angles as a criterion of proper position. In this work we examine performance of two proposed methods for dynamic cyclist position assessment based on video data recorded during stationary cycling. Proposed methods are intended for home use, to help amateur cyclist improve their position on the bike, and therefore no professional equipment is used. As a result of data processing, ranges of angles in selected joints are provided. Finally strengths and weaknesses of both proposed methods are discussed.

Structural health monitoring using DOG multi-scale space: an approach for analyzing damage characteristics

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-03-01

Measurement noise is inevitable in practice; thus, it is difficult to identify defects, cracks or damage in a structure while suppressing noise simultaneously. In this work, a novel method is introduced to detect multiple damage in noisy environments. Based on multi-scale space analysis for discrete signals, a method for extracting damage characteristics from the measured displacement mode shape is illustrated. Moreover, the proposed method incorporates a data fusion algorithm to further eliminate measurement noise-based interference. The effectiveness of the method is verified by numerical and experimental methods applied to different structural types. The results demonstrate that there are two advantages to the proposed method. First, damage features are extracted by the difference of the multi-scale representation; this step is taken such that the interference of noise amplification can be avoided. Second, a data fusion technique applied to the proposed method provides a global decision, which retains the damage features while maximally eliminating the uncertainty. Monte Carlo simulations are utilized to validate that the proposed method has a higher accuracy in damage detection.

MO-DE-207A-11: Sparse-View CT Reconstruction Via a Novel Non-Local Means Method

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

Chen, Z; Qi, H; Wu, S

2016-06-15

Purpose: Sparse-view computed tomography (CT) reconstruction is an effective strategy to reduce the radiation dose delivered to patients. Due to its insufficiency of measurements, traditional non-local means (NLM) based reconstruction methods often lead to over-smoothness in image edges. To address this problem, an adaptive NLM reconstruction method based on rotational invariance (RIANLM) is proposed. Methods: The method consists of four steps: 1) Initializing parameters; 2) Algebraic reconstruction technique (ART) reconstruction using raw projection data; 3) Positivity constraint of the image reconstructed by ART; 4) Update reconstructed image by using RIANLM filtering. In RIANLM, a novel similarity metric that is rotationalmore » invariance is proposed and used to calculate the distance between two patches. In this way, any patch with similar structure but different orientation to the reference patch would win a relatively large weight to avoid over-smoothed image. Moreover, the parameter h in RIANLM which controls the decay of the weights is adaptive to avoid over-smoothness, while it in NLM is not adaptive during the whole reconstruction process. The proposed method is named as ART-RIANLM and validated on Shepp-Logan phantom and clinical projection data. Results: In our experiments, the searching neighborhood size is set to 15 by 15 and the similarity window is set to 3 by 3. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, the ART-RIANLM produces higher SNR (35.38dB<24.00dB) and lower MAE (0.0006<0.0023) reconstructed image than ART-NLM. The visual inspection demonstrated that the proposed method could suppress artifacts or noises more effectively and preserve image edges better. Similar results were found for clinical data case. Conclusion: A novel ART-RIANLM method for sparse-view CT reconstruction is presented with superior image. Compared to the conventional ART-NLM method, the SNR and MAE from ART-RIANLM increases 47% and decreases 74%, respectively.« less

Formal Analysis of Extended Well-Clear Boundaries for Unmanned Aircraft

NASA Technical Reports Server (NTRS)

Munoz, Cesar; Narkawicz, Anthony

2016-01-01

This paper concerns the application of formal methods to the definition of a detect and avoid concept for unmanned aircraft systems (UAS). In particular, it illustrates how formal analysis was used to explain and correct unexpected behaviors of the logic that issues alerts when two aircraft are predicted not to be well clear from one another. As a result of this analysis, a recommendation was proposed to, and subsequently adopted by, the US standards organization that defines the minimum operational requirements for the UAS detect and avoid concept.

Utility-preserving anonymization for health data publishing.

PubMed

Lee, Hyukki; Kim, Soohyung; Kim, Jong Wook; Chung, Yon Dohn

2017-07-11

Publishing raw electronic health records (EHRs) may be considered as a breach of the privacy of individuals because they usually contain sensitive information. A common practice for the privacy-preserving data publishing is to anonymize the data before publishing, and thus satisfy privacy models such as k-anonymity. Among various anonymization techniques, generalization is the most commonly used in medical/health data processing. Generalization inevitably causes information loss, and thus, various methods have been proposed to reduce information loss. However, existing generalization-based data anonymization methods cannot avoid excessive information loss and preserve data utility. We propose a utility-preserving anonymization for privacy preserving data publishing (PPDP). To preserve data utility, the proposed method comprises three parts: (1) utility-preserving model, (2) counterfeit record insertion, (3) catalog of the counterfeit records. We also propose an anonymization algorithm using the proposed method. Our anonymization algorithm applies full-domain generalization algorithm. We evaluate our method in comparison with existence method on two aspects, information loss measured through various quality metrics and error rate of analysis result. With all different types of quality metrics, our proposed method show the lower information loss than the existing method. In the real-world EHRs analysis, analysis results show small portion of error between the anonymized data through the proposed method and original data. We propose a new utility-preserving anonymization method and an anonymization algorithm using the proposed method. Through experiments on various datasets, we show that the utility of EHRs anonymized by the proposed method is significantly better than those anonymized by previous approaches.

Mutual information based feature selection for medical image retrieval

NASA Astrophysics Data System (ADS)

Zhi, Lijia; Zhang, Shaomin; Li, Yan

2018-04-01

In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.

Frequency guided methods for demodulation of a single fringe pattern.

PubMed

Wang, Haixia; Kemao, Qian

2009-08-17

Phase demodulation from a single fringe pattern is a challenging task but of interest. A frequency-guided regularized phase tracker and a frequency-guided sequential demodulation method with Levenberg-Marquardt optimization are proposed to demodulate a single fringe pattern. Demodulation path guided by the local frequency from the highest to the lowest is applied in both methods. Since critical points have low local frequency values, they are processed last so that the spurious sign problem caused by these points is avoided. These two methods can be considered as alternatives to the effective fringe follower regularized phase tracker. Demodulation results from one computer-simulated and two experimental fringe patterns using the proposed methods will be demonstrated. (c) 2009 Optical Society of America

Identifying partial topology of complex dynamical networks via a pinning mechanism

NASA Astrophysics Data System (ADS)

Zhu, Shuaibing; Zhou, Jin; Lu, Jun-an

2018-04-01

In this paper, we study the problem of identifying the partial topology of complex dynamical networks via a pinning mechanism. By using the network synchronization theory and the adaptive feedback controlling method, we propose a method which can greatly reduce the number of nodes and observers in the response network. Particularly, this method can also identify the whole topology of complex networks. A theorem is established rigorously, from which some corollaries are also derived in order to make our method more cost-effective. Several numerical examples are provided to verify the effectiveness of the proposed method. In the simulation, an approach is also given to avoid possible identification failure caused by inner synchronization of the drive network.

Autonomous collision avoidance system by combined control of steering and braking using geometrically optimised vehicular trajectory

NASA Astrophysics Data System (ADS)

Hayashi, Ryuzo; Isogai, Juzo; Raksincharoensak, Pongsathorn; Nagai, Masao

2012-01-01

This study proposes an autonomous obstacle avoidance system not only by braking but also by steering, as one of the active safety technologies to prevent traffic accidents. The proposed system prevents the vehicle from colliding with a moving obstacle like a pedestrian jumping out from the roadside. In the proposed system, to avoid the predicted colliding position based on constant-velocity obstacle motion assumption, the avoidance trajectory is derived as connected two identical arcs. The system then controls the vehicle autonomously by the combined control of the braking and steering systems. In this paper, the proposed system is examined by real car experiments and its effectiveness is shown from the results of the experiments.

Recommendations for the Avoidance of Delayed-Onset Muscle Soreness.

ERIC Educational Resources Information Center

Szymanski, David J.

2001-01-01

Describes the possible causes of delayed-onset muscle soreness (DOMS), which include buildup of lactic acid in muscle, increased intracellular calcium concentration, increased intramuscular inflammation, and muscle fiber and connective tissue damage. Proposed methods to reduce DOMS include warming up before exercise and performing repeated bouts…

Recommendation advertising method based on behavior retargeting

NASA Astrophysics Data System (ADS)

Zhao, Yao; YIN, Xin-Chun; CHEN, Zhi-Min

2011-10-01

Online advertising has become an important business in e-commerce. Ad recommended algorithms are the most critical part in recommendation systems. We propose a recommendation advertising method based on behavior retargeting which can avoid leakage click of advertising due to objective reasons and can observe the changes of the user's interest in time. Experiments show that our new method can have a significant effect and can be further to apply to online system.

Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

2018-01-01

Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.

Experimental Method for Characterizing Electrical Steel Sheets in the Normal Direction

PubMed Central

Hihat, Nabil; Lecointe, Jean Philippe; Duchesne, Stephane; Napieralska, Ewa; Belgrand, Thierry

2010-01-01

This paper proposes an experimental method to characterise magnetic laminations in the direction normal to the sheet plane. The principle, which is based on a static excitation to avoid planar eddy currents, is explained and specific test benches are proposed. Measurements of the flux density are made with a sensor moving in and out of an air-gap. A simple analytical model is derived in order to determine the permeability in the normal direction. The experimental results for grain oriented steel sheets are presented and a comparison is provided with values obtained from literature. PMID:22163394

Fetal ECG extraction using independent component analysis by Jade approach

NASA Astrophysics Data System (ADS)

Giraldo-Guzmán, Jader; Contreras-Ortiz, Sonia H.; Lasprilla, Gloria Isabel Bautista; Kotas, Marian

2017-11-01

Fetal ECG monitoring is a useful method to assess the fetus health and detect abnormal conditions. In this paper we propose an approach to extract fetal ECG from abdomen and chest signals using independent component analysis based on the joint approximate diagonalization of eigenmatrices approach. The JADE approach avoids redundancy, what reduces matrix dimension and computational costs. Signals were filtered with a high pass filter to eliminate low frequency noise. Several levels of decomposition were tested until the fetal ECG was recognized in one of the separated sources output. The proposed method shows fast and good performance.

Time-dependent wave splitting and source separation

NASA Astrophysics Data System (ADS)

Grote, Marcus J.; Kray, Marie; Nataf, Frédéric; Assous, Franck

2017-02-01

Starting from classical absorbing boundary conditions, we propose a method for the separation of time-dependent scattered wave fields due to multiple sources or obstacles. In contrast to previous techniques, our method is local in space and time, deterministic, and avoids a priori assumptions on the frequency spectrum of the signal. Numerical examples in two space dimensions illustrate the usefulness of wave splitting for time-dependent scattering problems.

GNSS/Electronic Compass/Road Segment Information Fusion for Vehicle-to-Vehicle Collision Avoidance Application

PubMed Central

Cheng, Qi; Xue, Dabin; Wang, Guanyu; Ochieng, Washington Yotto

2017-01-01

The increasing number of vehicles in modern cities brings the problem of increasing crashes. One of the applications or services of Intelligent Transportation Systems (ITS) conceived to improve safety and reduce congestion is collision avoidance. This safety critical application requires sub-meter level vehicle state estimation accuracy with very high integrity, continuity and availability, to detect an impending collision and issue a warning or intervene in the case that the warning is not heeded. Because of the challenging city environment, to date there is no approved method capable of delivering this high level of performance in vehicle state estimation. In particular, the current Global Navigation Satellite System (GNSS) based collision avoidance systems have the major limitation that the real-time accuracy of dynamic state estimation deteriorates during abrupt acceleration and deceleration situations, compromising the integrity of collision avoidance. Therefore, to provide the Required Navigation Performance (RNP) for collision avoidance, this paper proposes a novel Particle Filter (PF) based model for the integration or fusion of real-time kinematic (RTK) GNSS position solutions with electronic compass and road segment data used in conjunction with an Autoregressive (AR) motion model. The real-time vehicle state estimates are used together with distance based collision avoidance algorithms to predict potential collisions. The algorithms are tested by simulation and in the field representing a low density urban environment. The results show that the proposed algorithm meets the horizontal positioning accuracy requirement for collision avoidance and is superior to positioning accuracy of GNSS only, traditional Constant Velocity (CV) and Constant Acceleration (CA) based motion models, with a significant improvement in the prediction accuracy of potential collision. PMID:29186851

GNSS/Electronic Compass/Road Segment Information Fusion for Vehicle-to-Vehicle Collision Avoidance Application.

PubMed

Sun, Rui; Cheng, Qi; Xue, Dabin; Wang, Guanyu; Ochieng, Washington Yotto

2017-11-25

The increasing number of vehicles in modern cities brings the problem of increasing crashes. One of the applications or services of Intelligent Transportation Systems (ITS) conceived to improve safety and reduce congestion is collision avoidance. This safety critical application requires sub-meter level vehicle state estimation accuracy with very high integrity, continuity and availability, to detect an impending collision and issue a warning or intervene in the case that the warning is not heeded. Because of the challenging city environment, to date there is no approved method capable of delivering this high level of performance in vehicle state estimation. In particular, the current Global Navigation Satellite System (GNSS) based collision avoidance systems have the major limitation that the real-time accuracy of dynamic state estimation deteriorates during abrupt acceleration and deceleration situations, compromising the integrity of collision avoidance. Therefore, to provide the Required Navigation Performance (RNP) for collision avoidance, this paper proposes a novel Particle Filter (PF) based model for the integration or fusion of real-time kinematic (RTK) GNSS position solutions with electronic compass and road segment data used in conjunction with an Autoregressive (AR) motion model. The real-time vehicle state estimates are used together with distance based collision avoidance algorithms to predict potential collisions. The algorithms are tested by simulation and in the field representing a low density urban environment. The results show that the proposed algorithm meets the horizontal positioning accuracy requirement for collision avoidance and is superior to positioning accuracy of GNSS only, traditional Constant Velocity (CV) and Constant Acceleration (CA) based motion models, with a significant improvement in the prediction accuracy of potential collision.

Pediatric fear-avoidance model of chronic pain: Foundation, application and future directions

PubMed Central

Asmundson, Gordon JG; Noel, Melanie; Petter, Mark; Parkerson, Holly A

2012-01-01

The fear-avoidance model of chronic musculoskeletal pain has become an increasingly popular conceptualization of the processes and mechanisms through which acute pain can become chronic. Despite rapidly growing interest and research regarding the influence of fear-avoidance constructs on pain-related disability in children and adolescents, there have been no amendments to the model to account for unique aspects of pediatric chronic pain. A comprehensive understanding of the role of fear-avoidance in pediatric chronic pain necessitates understanding of both child/adolescent and parent factors implicated in its development and maintenance. The primary purpose of the present article is to propose an empirically-based pediatric fear-avoidance model of chronic pain that accounts for both child/adolescent and parent factors as well as their potential interactive effects. To accomplish this goal, the present article will define important fear-avoidance constructs, provide a summary of the general fear-avoidance model and review the growing empirical literature regarding the role of fear-avoidance constructs in pediatric chronic pain. Assessment and treatment options for children with chronic pain will also be described in the context of the proposed pediatric fear-avoidance model of chronic pain. Finally, avenues for future investigation will be proposed. PMID:23248813

Pediatric fear-avoidance model of chronic pain: foundation, application and future directions.

PubMed

Asmundson, Gordon J G; Noel, Melanie; Petter, Mark; Parkerson, Holly A

2012-01-01

The fear-avoidance model of chronic musculoskeletal pain has become an increasingly popular conceptualization of the processes and mechanisms through which acute pain can become chronic. Despite rapidly growing interest and research regarding the influence of fear-avoidance constructs on pain-related disability in children and adolescents, there have been no amendments to the model to account for unique aspects of pediatric chronic pain. A comprehensive understanding of the role of fear-avoidance in pediatric chronic pain necessitates understanding of both child⁄adolescent and parent factors implicated in its development and maintenance. The primary purpose of the present article is to propose an empirically-based pediatric fear-avoidance model of chronic pain that accounts for both child⁄adolescent and parent factors as well as their potential interactive effects. To accomplish this goal, the present article will define important fear-avoidance constructs, provide a summary of the general fear-avoidance model and review the growing empirical literature regarding the role of fear-avoidance constructs in pediatric chronic pain. Assessment and treatment options for children with chronic pain will also be described in the context of the proposed pediatric fear-avoidance model of chronic pain. Finally, avenues for future investigation will be proposed.

State-vector formalism and the Legendre polynomial solution for modelling guided waves in anisotropic plates

NASA Astrophysics Data System (ADS)

Zheng, Mingfang; He, Cunfu; Lu, Yan; Wu, Bin

2018-01-01

We presented a numerical method to solve phase dispersion curve in general anisotropic plates. This approach involves an exact solution to the problem in the form of the Legendre polynomial of multiple integrals, which we substituted into the state-vector formalism. In order to improve the efficiency of the proposed method, we made a special effort to demonstrate the analytical methodology. Furthermore, we analyzed the algebraic symmetries of the matrices in the state-vector formalism for anisotropic plates. The basic feature of the proposed method was the expansion of field quantities by Legendre polynomials. The Legendre polynomial method avoid to solve the transcendental dispersion equation, which can only be solved numerically. This state-vector formalism combined with Legendre polynomial expansion distinguished the adjacent dispersion mode clearly, even when the modes were very close. We then illustrated the theoretical solutions of the dispersion curves by this method for isotropic and anisotropic plates. Finally, we compared the proposed method with the global matrix method (GMM), which shows excellent agreement.

Avoiding Degeneracy in Multidimensional Unfolding by Penalizing on the Coefficient of Variation

ERIC Educational Resources Information Center

Busing, Frank M. T. A.; Groenen, Patrick J. K.; Heiser, Willem J.

2005-01-01

Multidimensional unfolding methods suffer from the degeneracy problem in almost all circumstances. Most degeneracies are easily recognized: the solutions are perfect but trivial, characterized by approximately equal distances between points from different sets. A definition of an absolutely degenerate solution is proposed, which makes clear that…

A multilevel correction adaptive finite element method for Kohn-Sham equation

NASA Astrophysics Data System (ADS)

Hu, Guanghui; Xie, Hehu; Xu, Fei

2018-02-01

In this paper, an adaptive finite element method is proposed for solving Kohn-Sham equation with the multilevel correction technique. In the method, the Kohn-Sham equation is solved on a fixed and appropriately coarse mesh with the finite element method in which the finite element space is kept improving by solving the derived boundary value problems on a series of adaptively and successively refined meshes. A main feature of the method is that solving large scale Kohn-Sham system is avoided effectively, and solving the derived boundary value problems can be handled efficiently by classical methods such as the multigrid method. Hence, the significant acceleration can be obtained on solving Kohn-Sham equation with the proposed multilevel correction technique. The performance of the method is examined by a variety of numerical experiments.

Damage Detection Based on Static Strain Responses Using FBG in a Wind Turbine Blade.

PubMed

Tian, Shaohua; Yang, Zhibo; Chen, Xuefeng; Xie, Yong

2015-08-14

The damage detection of a wind turbine blade enables better operation of the turbines, and provides an early alert to the destroyed events of the blade in order to avoid catastrophic losses. A new non-baseline damage detection method based on the Fiber Bragg grating (FBG) in a wind turbine blade is developed in this paper. Firstly, the Chi-square distribution is proven to be an effective damage-sensitive feature which is adopted as the individual information source for the local decision. In order to obtain the global and optimal decision for the damage detection, the feature information fusion (FIF) method is proposed to fuse and optimize information in above individual information sources, and the damage is detected accurately through of the global decision. Then a 13.2 m wind turbine blade with the distributed strain sensor system is adopted to describe the feasibility of the proposed method, and the strain energy method (SEM) is used to describe the advantage of the proposed method. Finally results show that the proposed method can deliver encouraging results of the damage detection in the wind turbine blade.

Dynamic path planning for mobile robot based on particle swarm optimization

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In the contemporary, robots are used in many fields, such as cleaning, medical treatment, space exploration, disaster relief and so on. The dynamic path planning of robot without collision is becoming more and more the focus of people's attention. A new method of path planning is proposed in this paper. Firstly, the motion space model of the robot is established by using the MAKLINK graph method. Then the A* algorithm is used to get the shortest path from the start point to the end point. Secondly, this paper proposes an effective method to detect and avoid obstacles. When an obstacle is detected on the shortest path, the robot will choose the nearest safety point to move. Moreover, calculate the next point which is nearest to the target. Finally, the particle swarm optimization algorithm is used to optimize the path. The experimental results can prove that the proposed method is more effective.

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.

Efficient depth intraprediction method for H.264/AVC-based three-dimensional video coding

NASA Astrophysics Data System (ADS)

Oh, Kwan-Jung; Oh, Byung Tae

2015-04-01

We present an intracoding method that is applicable to depth map coding in multiview plus depth systems. Our approach combines skip prediction and plane segmentation-based prediction. The proposed depth intraskip prediction uses the estimated direction at both the encoder and decoder, and does not need to encode residual data. Our plane segmentation-based intraprediction divides the current block into biregions, and applies a different prediction scheme for each segmented region. This method avoids incorrect estimations across different regions, resulting in higher prediction accuracy. Simulation results demonstrate that the proposed scheme is superior to H.264/advanced video coding intraprediction and has the ability to improve the subjective rendering quality.

Determination of the state-of-charge in leadacid batteries by means of a reference cell

NASA Astrophysics Data System (ADS)

Armenta, C.

A knowledge of the state-of-charge of any battery is an essential requirement for system energy management and for battery life extension. In photovoltaic power plants and stand-alone photovoltaic installations, a knowledge of the state-of-charge helps one to predict remaining energy, to determine time remaining before battery turndown, and to avoid failures during operation. A reliable method of predicting the state-of-charge will allow reduced installation costs because less reserve capacity is needed to guarantee a reliable energy supply. We propose an on-line method based on simple electrical measurements combined with a new electrolyte agitation technique which avoids systematic control of the battery state-of-charge. The method is very accurate and reduces the standard error in the state-of-charge prediction.

A Wavelet-based Fast Discrimination of Transformer Magnetizing Inrush Current

NASA Astrophysics Data System (ADS)

Kitayama, Masashi

Recently customers who need electricity of higher quality have been installing co-generation facilities. They can avoid voltage sags and other distribution system related disturbances by supplying electricity to important load from their generators. For another example, FRIENDS, highly reliable distribution system using semiconductor switches or storage devices based on power electronics technology, is proposed. These examples illustrates that the request for high reliability in distribution system is increasing. In order to realize these systems, fast relaying algorithms are indispensable. The author proposes a new method of detecting magnetizing inrush current using discrete wavelet transform (DWT). DWT provides the function of detecting discontinuity of current waveform. Inrush current occurs when transformer core becomes saturated. The proposed method detects spikes of DWT components derived from the discontinuity of the current waveform at both the beginning and the end of inrush current. Wavelet thresholding, one of the wavelet-based statistical modeling, was applied to detect the DWT component spikes. The proposed method is verified using experimental data using single-phase transformer and the proposed method is proved to be effective.

Mitigation of Shore Damage Attributed to the Federal Navigation Structures at Port Sanilac Harbor, Michigan.

DTIC Science & Technology

1975-09-01

beach would be more costly tiian the stockpile method of placement considered for the feeder proposal. 5. COMMENTS REQUESTED: The Draft and this...contractual, and methods of detectinq and avoiding pollution to prevent and correct environmental pollution. QUALITY CONTROL 1.34 The contractor (if...Reliahle ;reat ,,kes wave data measured by wave rnauces are nearly nonexistent for statistical t:eatment. An indirect method of develoz’ina wave data is

An adaptive angle-doppler compensation method for airborne bistatic radar based on PAST

NASA Astrophysics Data System (ADS)

Hang, Xu; Jun, Zhao

2018-05-01

Adaptive angle-Doppler compensation method extract the requisite information based on the data itself adaptively, thus avoiding the problem of performance degradation caused by inertia system error. However, this method requires estimation and egiendecomposition of sample covariance matrix, which has a high computational complexity and limits its real-time application. In this paper, an adaptive angle Doppler compensation method based on projection approximation subspace tracking (PAST) is studied. The method uses cyclic iterative processing to quickly estimate the positions of the spectral center of the maximum eigenvector of each range cell, and the computational burden of matrix estimation and eigen-decompositon is avoided, and then the spectral centers of all range cells is overlapped by two dimensional compensation. Simulation results show the proposed method can effectively reduce the no homogeneity of airborne bistatic radar, and its performance is similar to that of egien-decomposition algorithms, but the computation load is obviously reduced and easy to be realized.

A fault tolerant gait for a hexapod robot over uneven terrain.

PubMed

Yang, J M; Kim, J H

2000-01-01

The fault tolerant gait of legged robots in static walking is a gait which maintains its stability against a fault event preventing a leg from having the support state. In this paper, a fault tolerant quadruped gait is proposed for a hexapod traversing uneven terrain with forbidden regions, which do not offer viable footholds but can be stepped over. By comparing performance of straight-line motion and crab walking over even terrain, it is shown that the proposed gait has better mobility and terrain adaptability than previously developed gaits. Based on the proposed gait, we present a method for the generation of the fault tolerant locomotion of a hexapod over uneven terrain with forbidden regions. The proposed method minimizes the number of legs on the ground during walking, and foot adjustment algorithm is used for avoiding steps on forbidden regions. The effectiveness of the proposed strategy over uneven terrain is demonstrated with a computer simulation.

An accurate reactive power control study in virtual flux droop control

NASA Astrophysics Data System (ADS)

Wang, Aimeng; Zhang, Jia

2017-12-01

This paper investigates the problem of reactive power sharing based on virtual flux droop method. Firstly, flux droop control method is derived, where complicated multiple feedback loops and parameter regulation are avoided. Then, the reasons for inaccurate reactive power sharing are theoretically analyzed. Further, a novel reactive power control scheme is proposed which consists of three parts: compensation control, voltage recovery control and flux droop control. Finally, the proposed reactive power control strategy is verified in a simplified microgrid model with two parallel DGs. The simulation results show that the proposed control scheme can achieve accurate reactive power sharing and zero deviation of voltage. Meanwhile, it has some advantages of simple control and excellent dynamic and static performance.

Image dehazing based on non-local saturation

NASA Astrophysics Data System (ADS)

Wang, Linlin; Zhang, Qian; Yang, Deyun; Hou, Yingkun; He, Xiaoting

2018-04-01

In this paper, a method based on non-local saturation algorithm is proposed to avoid block and halo effect for single image dehazing with dark channel prior. First we convert original image from RGB color space into HSV color space with the idea of non-local method. Image saturation is weighted equally by the size of fixed window according to image resolution. Second we utilize the saturation to estimate the atmospheric light value and transmission rate. Then through the function of saturation and transmission, the haze-free image is obtained based on the atmospheric scattering model. Comparing the results of existing methods, our method can restore image color and enhance contrast. We guarantee the proposed method with quantitative and qualitative evaluation respectively. Experiments show the better visual effect with high efficiency.

Gear fatigue crack prognosis using embedded model, gear dynamic model and fracture mechanics

NASA Astrophysics Data System (ADS)

Li, C. James; Lee, Hyungdae

2005-07-01

This paper presents a model-based method that predicts remaining useful life of a gear with a fatigue crack. The method consists of an embedded model to identify gear meshing stiffness from measured gear torsional vibration, an inverse method to estimate crack size from the estimated meshing stiffness; a gear dynamic model to simulate gear meshing dynamics and determine the dynamic load on the cracked tooth; and a fast crack propagation model to forecast the remaining useful life based on the estimated crack size and dynamic load. The fast crack propagation model was established to avoid repeated calculations of FEM and facilitate field deployment of the proposed method. Experimental studies were conducted to validate and demonstrate the feasibility of the proposed method for prognosis of a cracked gear.

Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor.

PubMed

Kikutis, Ramūnas; Stankūnas, Jonas; Rudinskas, Darius; Masiulionis, Tadas

2017-09-28

Current research on Unmanned Aerial Vehicles (UAVs) shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL) simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS) sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically.

Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor

PubMed Central

Kikutis, Ramūnas; Stankūnas, Jonas; Rudinskas, Darius; Masiulionis, Tadas

2017-01-01

Current research on Unmanned Aerial Vehicles (UAVs) shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL) simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS) sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically. PMID:28956839

An Accurate Projector Calibration Method Based on Polynomial Distortion Representation

PubMed Central

Liu, Miao; Sun, Changku; Huang, Shujun; Zhang, Zonghua

2015-01-01

In structure light measurement systems or 3D printing systems, the errors caused by optical distortion of a digital projector always affect the precision performance and cannot be ignored. Existing methods to calibrate the projection distortion rely on calibration plate and photogrammetry, so the calibration performance is largely affected by the quality of the plate and the imaging system. This paper proposes a new projector calibration approach that makes use of photodiodes to directly detect the light emitted from a digital projector. By analyzing the output sequence of the photoelectric module, the pixel coordinates can be accurately obtained by the curve fitting method. A polynomial distortion representation is employed to reduce the residuals of the traditional distortion representation model. Experimental results and performance evaluation show that the proposed calibration method is able to avoid most of the disadvantages in traditional methods and achieves a higher accuracy. This proposed method is also practically applicable to evaluate the geometric optical performance of other optical projection system. PMID:26492247

A consensus reaching model for 2-tuple linguistic multiple attribute group decision making with incomplete weight information

NASA Astrophysics Data System (ADS)

Zhang, Wancheng; Xu, Yejun; Wang, Huimin

2016-01-01

The aim of this paper is to put forward a consensus reaching method for multi-attribute group decision-making (MAGDM) problems with linguistic information, in which the weight information of experts and attributes is unknown. First, some basic concepts and operational laws of 2-tuple linguistic label are introduced. Then, a grey relational analysis method and a maximising deviation method are proposed to calculate the incomplete weight information of experts and attributes respectively. To eliminate the conflict in the group, a weight-updating model is employed to derive the weights of experts based on their contribution to the consensus reaching process. After conflict elimination, the final group preference can be obtained which will give the ranking of the alternatives. The model can effectively avoid information distortion which is occurred regularly in the linguistic information processing. Finally, an illustrative example is given to illustrate the application of the proposed method and comparative analysis with the existing methods are offered to show the advantages of the proposed method.

An attachment-based model of complicated grief including the role of avoidance

PubMed Central

Monk, Timothy; Houck, Patricia; Melhem, Nadine; Frank, Ellen; Reynolds, Charles; Sillowash, Russell

2009-01-01

Introduction Complicated grief is a prolonged grief disorder with elements of a stress response syndrome. We have previously proposed a biobehavioral model showing the pathway to complicated grief. Avoidance is a component that can be difficult to assess and pivotal to treatment. Therefore we developed an avoidance questionnaire to characterize avoidance among patients with CG. Methods We further explain our complicated grief model and provide results of a study of 128 participants in a treatment study of CG who completed a 15-item Grief-related Avoidance Questionnaire (GRAQ). Results of Avoidance Assessment Mean (SD) GRAQ score was 25. 0 ± 12.5 with a range of 0–60. Cronbach's alpha was 0.87 and test re-test correlation was 0.88. Correlation analyses showed good convergent and discriminant validity. Avoidance of reminders of the loss contributed to functional impairment after controlling for other symptoms of complicated grief. Discussion In this paper we extend our previously described attachment-based biobehavioral model of CG. We envision CG as a stress response syndrome that results from failure to integrate information about death of an attachment figure into an effectively functioning secure base schema and/or to effectively re-engage the exploratory system in a world without the deceased. Avoidance is a key element of the model. PMID:17629727

Detection of EEG electrodes in brain volumes.

PubMed

Graffigna, Juan P; Gómez, M Eugenia; Bustos, José J

2010-01-01

This paper presents a method to detect 128 EEG electrodes in image study and to merge with the Nuclear Magnetic Resonance volume for better diagnosis. First we propose three hypotheses to define a specific acquisition protocol in order to recognize the electrodes and to avoid distortions in the image. In the second instance we describe a method for segmenting the electrodes. Finally, registration is performed between volume of the electrodes and NMR.

Aveiro method in reproducing kernel Hilbert spaces under complete dictionary

NASA Astrophysics Data System (ADS)

Mai, Weixiong; Qian, Tao

2017-12-01

Aveiro Method is a sparse representation method in reproducing kernel Hilbert spaces (RKHS) that gives orthogonal projections in linear combinations of reproducing kernels over uniqueness sets. It, however, suffers from determination of uniqueness sets in the underlying RKHS. In fact, in general spaces, uniqueness sets are not easy to be identified, let alone the convergence speed aspect with Aveiro Method. To avoid those difficulties we propose an anew Aveiro Method based on a dictionary and the matching pursuit idea. What we do, in fact, are more: The new Aveiro method will be in relation to the recently proposed, the so called Pre-Orthogonal Greedy Algorithm (P-OGA) involving completion of a given dictionary. The new method is called Aveiro Method Under Complete Dictionary (AMUCD). The complete dictionary consists of all directional derivatives of the underlying reproducing kernels. We show that, under the boundary vanishing condition, bring available for the classical Hardy and Paley-Wiener spaces, the complete dictionary enables an efficient expansion of any given element in the Hilbert space. The proposed method reveals new and advanced aspects in both the Aveiro Method and the greedy algorithm.

A human-machine cooperation route planning method based on improved A* algorithm

NASA Astrophysics Data System (ADS)

Zhang, Zhengsheng; Cai, Chao

2011-12-01

To avoid the limitation of common route planning method to blindly pursue higher Machine Intelligence and autoimmunization, this paper presents a human-machine cooperation route planning method. The proposed method includes a new A* path searing strategy based on dynamic heuristic searching and a human cooperated decision strategy to prune searching area. It can overcome the shortage of A* algorithm to fall into a local long term searching. Experiments showed that this method can quickly plan a feasible route to meet the macro-policy thinking.

Beam-steering efficiency optimization method based on a rapid-search algorithm for liquid crystal optical phased array.

PubMed

Xiao, Feng; Kong, Lingjiang; Chen, Jian

2017-06-01

A rapid-search algorithm to improve the beam-steering efficiency for a liquid crystal optical phased array was proposed and experimentally demonstrated in this paper. This proposed algorithm, in which the value of steering efficiency is taken as the objective function and the controlling voltage codes are considered as the optimization variables, consisted of a detection stage and a construction stage. It optimized the steering efficiency in the detection stage and adjusted its search direction adaptively in the construction stage to avoid getting caught in a wrong search space. Simulations had been conducted to compare the proposed algorithm with the widely used pattern-search algorithm using criteria of convergence rate and optimized efficiency. Beam-steering optimization experiments had been performed to verify the validity of the proposed method.

Robust path planning for flexible needle insertion using Markov decision processes.

PubMed

Tan, Xiaoyu; Yu, Pengqian; Lim, Kah-Bin; Chui, Chee-Kong

2018-05-11

Flexible needle has the potential to accurately navigate to a treatment region in the least invasive manner. We propose a new planning method using Markov decision processes (MDPs) for flexible needle navigation that can perform robust path planning and steering under the circumstance of complex tissue-needle interactions. This method enhances the robustness of flexible needle steering from three different perspectives. First, the method considers the problem caused by soft tissue deformation. The method then resolves the common needle penetration failure caused by patterns of targets, while the last solution addresses the uncertainty issues in flexible needle motion due to complex and unpredictable tissue-needle interaction. Computer simulation and phantom experimental results show that the proposed method can perform robust planning and generate a secure control policy for flexible needle steering. Compared with a traditional method using MDPs, the proposed method achieves higher accuracy and probability of success in avoiding obstacles under complicated and uncertain tissue-needle interactions. Future work will involve experiment with biological tissue in vivo. The proposed robust path planning method can securely steer flexible needle within soft phantom tissues and achieve high adaptability in computer simulation.

A protocol for lifetime energy and environmental impact assessment of building insulation materials

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

Shrestha, Som S., E-mail: shresthass@ornl.gov; Biswas, Kaushik; Desjarlais, Andre O.

This article describes a proposed protocol that is intended to provide a comprehensive list of factors to be considered in evaluating the direct and indirect environmental impacts of building insulation materials, as well as detailed descriptions of standardized calculation methodologies to determine those impacts. The energy and environmental impacts of insulation materials can generally be divided into two categories: (1) direct impact due to the embodied energy of the insulation materials and other factors and (2) indirect or environmental impacts avoided as a result of reduced building energy use due to addition of insulation. Standards and product category rules exist,more » which provide guidelines about the life cycle assessment (LCA) of materials, including building insulation products. However, critical reviews have suggested that these standards fail to provide complete guidance to LCA studies and suffer from ambiguities regarding the determination of the environmental impacts of building insulation and other products. The focus of the assessment protocol described here is to identify all factors that contribute to the total energy and environmental impacts of different building insulation products and, more importantly, provide standardized determination methods that will allow comparison of different insulation material types. Further, the intent is not to replace current LCA standards but to provide a well-defined, easy-to-use comparison method for insulation materials using existing LCA guidelines. - Highlights: • We proposed a protocol to evaluate the environmental impacts of insulation materials. • The protocol considers all life cycle stages of an insulation material. • Both the direct environmental impacts and the indirect impacts are defined. • Standardized calculation methods for the ‘avoided operational energy’ is defined. • Standardized calculation methods for the ‘avoided environmental impact’ is defined.« less

75 FR 72773 - Empowering Consumers to Avoid Bill Shock; Consumer Information and Disclosure

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-26

... require mobile service providers to provide usage alerts and information that will assist consumers in... proposes rules that would require mobile service providers to provide usage alerts, such as voice or text... consumers, including methods such as providing voice or text alerts. In addition, the Commission seeks...

Ethical and Unethical Methods of Plagiarism Prevention in Academic Writing

ERIC Educational Resources Information Center

Bakhtiyari, Kaveh; Salehi, Hadi; Embi, Mohamed Amin; Shakiba, Masoud; Zavvari, Azam; Shahbazi-Moghadam, Masoomeh; Ebrahim, Nader Ale; Mohammadjafari, Marjan

2014-01-01

This paper discusses plagiarism origins, and the ethical solutions to prevent it. It also reviews some unethical approaches, which may be used to decrease the plagiarism rate in academic writings. We propose eight ethical techniques to avoid unconscious and accidental plagiarism in manuscripts without using online systems such as Turnitin and/or…

[Recent developments on the European ban on animal experiments for cosmetics].

PubMed

Ruhdel, I W

2001-01-01

For the second time the European Commission has postponed the sales ban on cosmetics products that have been developed and tested in animal experiments now until 2002. In the meantime the Commission wants to adopt the Seventh Amendment of the EU Cosmetics Directive. In its draft the Commission proposes to scrap the sales ban and replace it with an animal testing ban. This change would avoid possible conflicts with the WTO, however, from the animal welfare point of view would result in animal testing moving into third countries instead of avoiding them. This is because cosmetics products tested on animals outside the EU could be sold in the EU without any restrictions. As a consequence this measure would take the pressure from authorities and industry to further develop and adopt alternative methods. Other proposed measures are not acceptable from the animal welfare point of view, e.g. because they contradict Directive 86/609 and would result in a delay of the application of validated alternative methods. The Deutscher Tierschutzbund therefore still demands an immediate and complete sales ban in connection with an animal testing ban within the EU.

How to avoid unfair discrimination against disabled patients in healthcare resource allocation.

PubMed

Sinclair, Sean

2012-03-01

The paper proposes a new method of researching public opinion for the purposes of valuing the outcomes of healthcare interventions. The issue I address is that, under the quality-adjusted life-year system, disabled patients face a higher cost-effectiveness hurdle than able-bodied patients. This seems inequitable. The author considers the alternative approaches to valuing healthcare interventions that have been proposed, and shows that all of them face the same problem. It is proposed that to value an outcome, instead of researching the general public, the population that is to be targeted with the intervention should be researched.

A Compact Magnetic Field-Based Obstacle Detection and Avoidance System for Miniature Spherical Robots.

PubMed

Wu, Fang; Vibhute, Akash; Soh, Gim Song; Wood, Kristin L; Foong, Shaohui

2017-05-28

Due to their efficient locomotion and natural tolerance to hazardous environments, spherical robots have wide applications in security surveillance, exploration of unknown territory and emergency response. Numerous studies have been conducted on the driving mechanism, motion planning and trajectory tracking methods of spherical robots, yet very limited studies have been conducted regarding the obstacle avoidance capability of spherical robots. Most of the existing spherical robots rely on the "hit and run" technique, which has been argued to be a reasonable strategy because spherical robots have an inherent ability to recover from collisions. Without protruding components, they will not become stuck and can simply roll back after running into bstacles. However, for small scale spherical robots that contain sensitive surveillance sensors and cannot afford to utilize heavy protective shells, the absence of obstacle avoidance solutions would leave the robot at the mercy of potentially dangerous obstacles. In this paper, a compact magnetic field-based obstacle detection and avoidance system has been developed for miniature spherical robots. It utilizes a passive magnetic field so that the system is both compact and power efficient. The proposed system can detect not only the presence, but also the approaching direction of a ferromagnetic obstacle, therefore, an intelligent avoidance behavior can be generated by adapting the trajectory tracking method with the detection information. Design optimization is conducted to enhance the obstacle detection performance and detailed avoidance strategies are devised. Experimental results are also presented for validation purposes.

Stressors and anxiety in dementia caregiving: multiple mediation analysis of rumination, experiential avoidance, and leisure.

PubMed

Romero-Moreno, R; Losada, A; Márquez-González, M; Mausbach, B T

2016-11-01

Despite the robust associations between stressors and anxiety in dementia caregiving, there is a lack of research examining which factors contribute to explain this relationship. This study was designed to test a multiple mediation model of behavioral and psychological symptoms of dementia (BPSD) and anxiety that proposes higher levels of rumination and experiential avoidance and lower levels of leisure satisfaction as potential mediating variables. The sample consisted of 256 family caregivers. In order to test a simultaneously parallel multiple mediation model of the BPSD to anxiety pathway, a PROCESS method was used and bias-corrected and accelerated bootstrapping method was used to test confidence intervals. Higher levels of stressors significantly predicted anxiety. Greater stressors significantly predicted higher levels of rumination and experiential avoidance, and lower levels of leisure satisfaction. These three coping variables significantly predicted anxiety. Finally, rumination, experiential avoidance, and leisure satisfaction significantly mediated the link between stressors and anxiety. The explained variance for the final model was 47.09%. Significant contrasts were found between rumination and leisure satisfaction, with rumination being a significantly higher mediator. The results suggest that caregivers' experiential avoidance, rumination, and leisure satisfaction may function as mechanisms through which BPSD influence on caregivers' anxiety. Training caregivers in reducing their levels of experiential avoidance and rumination by techniques that foster their ability of acceptance of their negative internal experiences, and increase their level of leisure satisfaction, may be helpful to reduce their anxiety symptoms developed by stressors.

Simulating interfering fringe displacements by lateral shifts of a camera for educational purposes

NASA Astrophysics Data System (ADS)

Rivera-Ortega, Uriel

2018-07-01

In this manuscript we propose a simple method to emulate fringe displacements in a fringe pattern, due to the interference of two plane waves, by using lateral shifts of a CMOS detector under the scheme of a Twyman–Green interferometric setup, avoiding unwanted vibrations and the need for specific and expensive devices in order to accomplish the task. The simplicity of the proposed experimental setup allows it to be easily replicated and used for teaching or demonstrative purposes, essentially for undergraduate students.

Inverse Tone Mapping Based upon Retina Response

PubMed Central

Huo, Yongqing; Yang, Fan; Brost, Vincent

2014-01-01

The development of high dynamic range (HDR) display arouses the research of inverse tone mapping methods, which expand dynamic range of the low dynamic range (LDR) image to match that of HDR monitor. This paper proposed a novel physiological approach, which could avoid artifacts occurred in most existing algorithms. Inspired by the property of the human visual system (HVS), this dynamic range expansion scheme performs with a low computational complexity and a limited number of parameters and obtains high-quality HDR results. Comparisons with three recent algorithms in the literature also show that the proposed method reveals more important image details and produces less contrast loss and distortion. PMID:24744678

Estimating travel reduction associated with the use of telemedicine by patients and healthcare professionals: proposal for quantitative synthesis in a systematic review.

PubMed

Wootton, Richard; Bahaadinbeigy, Kambiz; Hailey, David

2011-08-08

A major benefit offered by telemedicine is the avoidance of travel, by patients, their carers and health care professionals. Unfortunately, there is very little published information about the extent of avoided travel. We propose to undertake a systematic review of literature which reports credible data on the reductions in travel associated with the use of telemedicine. The conventional approach to quantitative synthesis of the results from multiple studies is to conduct a meta analysis. However, too much heterogeneity exists between available studies to allow a meaningful meta analysis of the avoided travel when telemedicine is used across all possible settings. We propose instead to consider all credible evidence on avoided travel through telemedicine by fitting a linear model which takes into account the relevant factors in the circumstances of the studies performed. We propose the use of stepwise multiple regression to identify which factors are significant. Our proposed approach is illustrated by the example of teledermatology. In a preliminary review of the literature we found 20 studies in which the percentage of avoided travel through telemedicine could be inferred (a total of 5199 patients). The mean percentage avoided travel reported in the 12 store-and-forward studies was 43%. In the 7 real-time studies and in a single study with a hybrid technique, 70% of the patients avoided travel. A simplified model based on the modality of telemedicine employed (i.e. real-time or store and forward) explained 29% of the variance. The use of store and forward teledermatology alone was associated with 43% of avoided travel. The increase in the proportion of patients who avoided travel (25%) when real-time telemedicine was employed was significant (P = 0.014). Service planners can use this information to weigh up the costs and benefits of the two approaches.

Bootstrap-based methods for estimating standard errors in Cox's regression analyses of clustered event times.

PubMed

Xiao, Yongling; Abrahamowicz, Michal

2010-03-30

We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.

A comparison of Heuristic method and Llewellyn’s rules for identification of redundant constraints

NASA Astrophysics Data System (ADS)

Estiningsih, Y.; Farikhin; Tjahjana, R. H.

2018-03-01

Important techniques in linear programming is modelling and solving practical optimization. Redundant constraints are consider for their effects on general linear programming problems. Identification and reduce redundant constraints are for avoidance of all the calculations associated when solving an associated linear programming problems. Many researchers have been proposed for identification redundant constraints. This paper a compararison of Heuristic method and Llewellyn’s rules for identification of redundant constraints.

The Role of Interpersonal Personality Traits and Reassurance Seeking in Eating Disorder Symptoms and Depressive Symptoms among Women with Bulimia Nervosa

PubMed Central

Mason, Tyler B.; Lavender, Jason M.; Wonderlich, Stephen A.; Crosby, Ross D.; Joiner, Thomas E.; Mitchell, James E.; Crow, Scott J.; Klein, Marjorie H.; Le Grange, Daniel; Bardone-Cone, Anna M.; Peterson, Carol B.

2017-01-01

Introduction The role of interpersonal factors has been proposed in various models of eating disorder (ED) psychopathology and treatment. We examined the independent and interactive contributions of two interpersonal-focused personality traits (i.e., social avoidance and insecure attachment) and reassurance seeking in relation to global ED psychopathology and depressive symptoms among women with bulimia nervosa (BN). Method Participants were 204 adult women with full or subclinical BN who completed a battery of self-report questionnaires. Hierarchical multiple OLS regressions including main effects and interaction terms were used to analyze the data. Results Main effects were found for social avoidance and insecure attachment in association with global ED psychopathology and depressive symptoms. In addition, two-way interactions between social avoidance and reassurance seeking were observed for both global ED psychopathology and depressive symptoms. In general, reassurance seeking strengthened the association between social avoidance and global ED psychopathology and depressive symptoms. Conclusion These results demonstrate the importance of reassurance seeking in psychopathology among women with BN who display personality features characterized by social avoidance. PMID:27234198

The optimal modified variational iteration method for the Lane-Emden equations with Neumann and Robin boundary conditions

NASA Astrophysics Data System (ADS)

Singh, Randhir; Das, Nilima; Kumar, Jitendra

2017-06-01

An effective analytical technique is proposed for the solution of the Lane-Emden equations. The proposed technique is based on the variational iteration method (VIM) and the convergence control parameter h . In order to avoid solving a sequence of nonlinear algebraic or complicated integrals for the derivation of unknown constant, the boundary conditions are used before designing the recursive scheme for solution. The series solutions are found which converges rapidly to the exact solution. Convergence analysis and error bounds are discussed. Accuracy, applicability of the method is examined by solving three singular problems: i) nonlinear Poisson-Boltzmann equation, ii) distribution of heat sources in the human head, iii) second-kind Lane-Emden equation.

Simultaneous separation of copper, cadmium and cobalt from sea-water by co-flotation with octadecylamine and ferric hydroxide as collectors.

PubMed

Cabezon, L M; Caballero, M; Cela, R; Perez-Bustamante, J A

1984-08-01

A method is proposed for the simultaneous quantitative separation of traces ofCu(II), Cd(II) and Co(II) from sea-water samples by means of the co-flotation (adsorbing colloid flotation) technique with ferric hydroxide as co-precipitant and octadecylamine as collector. The experimental parameters have been studied and optimized. The drawbacks arising from the low solubility of octadecylamine and the corresponding sublates in water have been avoided by use of a 6M hydrochloric acid-MIBK-ethanol (1:2:2 v v ) mixture. The results obtained by means of the proposed method have been compared with those given by the usual ammonium pyrrolidine dithiocarbamate/MIBK extraction method.

Determination of Material Strengths by Hydraulic Bulge Test.

PubMed

Wang, Hankui; Xu, Tong; Shou, Binan

2016-12-30

The hydraulic bulge test (HBT) method is proposed to determine material tensile strengths. The basic idea of HBT is similar to the small punch test (SPT), but inspired by the manufacturing process of rupture discs-high-pressure hydraulic oil is used instead of punch to cause specimen deformation. Compared with SPT method, the HBT method can avoid some of influence factors, such as punch dimension, punch material, and the friction between punch and specimen. A calculation procedure that is entirely based on theoretical derivation is proposed for estimate yield strength and ultimate tensile strength. Both conventional tensile tests and hydraulic bulge tests were carried out for several ferrous alloys, and the results showed that hydraulic bulge test results are reliable and accurate.

Multiple object tracking using the shortest path faster association algorithm.

PubMed

Xi, Zhenghao; Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.

Oil Spill Detection in Terma-Side-Looking Airborne Radar Images Using Image Features and Region Segmentation

PubMed Central

Alacid, Beatriz

2018-01-01

This work presents a method for oil-spill detection on Spanish coasts using aerial Side-Looking Airborne Radar (SLAR) images, which are captured using a Terma sensor. The proposed method uses grayscale image processing techniques to identify the dark spots that represent oil slicks on the sea. The approach is based on two steps. First, the noise regions caused by aircraft movements are detected and labeled in order to avoid the detection of false-positives. Second, a segmentation process guided by a map saliency technique is used to detect image regions that represent oil slicks. The results show that the proposed method is an improvement on the previous approaches for this task when employing SLAR images. PMID:29316716

Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

PubMed Central

Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time. PMID:25215322

Rapid optimization of tension distribution for cable-driven parallel manipulators with redundant cables

NASA Astrophysics Data System (ADS)

Ouyang, Bo; Shang, Weiwei

2016-03-01

The solution of tension distributions is infinite for cable-driven parallel manipulators(CDPMs) with redundant cables. A rapid optimization method for determining the optimal tension distribution is presented. The new optimization method is primarily based on the geometry properties of a polyhedron and convex analysis. The computational efficiency of the optimization method is improved by the designed projection algorithm, and a fast algorithm is proposed to determine which two of the lines are intersected at the optimal point. Moreover, a method for avoiding the operating point on the lower tension limit is developed. Simulation experiments are implemented on a six degree-of-freedom(6-DOF) CDPM with eight cables, and the results indicate that the new method is one order of magnitude faster than the standard simplex method. The optimal distribution of tension distribution is thus rapidly established on real-time by the proposed method.

A multistage motion vector processing method for motion-compensated frame interpolation.

PubMed

Huang, Ai- Mei; Nguyen, Truong Q

2008-05-01

In this paper, a novel, low-complexity motion vector processing algorithm at the decoder is proposed for motion-compensated frame interpolation or frame rate up-conversion. We address the problems of having broken edges and deformed structures in an interpolated frame by hierarchically refining motion vectors on different block sizes. Our method explicitly considers the reliability of each received motion vector and has the capability of preserving the structure information. This is achieved by analyzing the distribution of residual energies and effectively merging blocks that have unreliable motion vectors. The motion vector reliability information is also used as a prior knowledge in motion vector refinement using a constrained vector median filter to avoid choosing identical unreliable one. We also propose using chrominance information in our method. Experimental results show that the proposed scheme has better visual quality and is also robust, even in video sequences with complex scenes and fast motion.

A Self-Alignment Algorithm for SINS Based on Gravitational Apparent Motion and Sensor Data Denoising

PubMed Central

Liu, Yiting; Xu, Xiaosu; Liu, Xixiang; Yao, Yiqing; Wu, Liang; Sun, Jin

2015-01-01

Initial alignment is always a key topic and difficult to achieve in an inertial navigation system (INS). In this paper a novel self-initial alignment algorithm is proposed using gravitational apparent motion vectors at three different moments and vector-operation. Simulation and analysis showed that this method easily suffers from the random noise contained in accelerometer measurements which are used to construct apparent motion directly. Aiming to resolve this problem, an online sensor data denoising method based on a Kalman filter is proposed and a novel reconstruction method for apparent motion is designed to avoid the collinearity among vectors participating in the alignment solution. Simulation, turntable tests and vehicle tests indicate that the proposed alignment algorithm can fulfill initial alignment of strapdown INS (SINS) under both static and swinging conditions. The accuracy can either reach or approach the theoretical values determined by sensor precision under static or swinging conditions. PMID:25923932

A tutorial description of an interior point method and its applications to security-constrained economic dispatch

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

Vargas, L.S.; Quintana, V.H.; Vannelli, A.

This paper deals with the use of Successive Linear Programming (SLP) for the solution of the Security-Constrained Economic Dispatch (SCED) problem. The authors tutorially describe an Interior Point Method (IPM) for the solution of Linear Programming (LP) problems, discussing important implementation issues that really make this method far superior to the simplex method. A study of the convergence of the SLP technique and a practical criterion to avoid oscillatory behavior in the iteration process are also proposed. A comparison of the proposed method with an efficient simplex code (MINOS) is carried out by solving SCED problems on two standard IEEEmore » systems. The results show that the interior point technique is reliable, accurate and more than two times faster than the simplex algorithm.« less

Radar-based collision avoidance for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Zhuang, Jia-yuan; Zhang, Lei; Zhao, Shi-qi; Cao, Jian; Wang, Bo; Sun, Han-bing

2016-12-01

Unmanned surface vehicles (USVs) have become a focus of research because of their extensive applications. To ensure safety and reliability and to perform complex tasks autonomously, USVs are required to possess accurate perception of the environment and effective collision avoidance capabilities. To achieve these, investigation into realtime marine radar target detection and autonomous collision avoidance technologies is required, aiming at solving the problems of noise jamming, uneven brightness, target loss, and blind areas in marine radar images. These technologies should also satisfy the requirements of real-time and reliability related to high navigation speeds of USVs. Therefore, this study developed an embedded collision avoidance system based on the marine radar, investigated a highly real-time target detection method which contains adaptive smoothing algorithm and robust segmentation algorithm, developed a stable and reliable dynamic local environment model to ensure the safety of USV navigation, and constructed a collision avoidance algorithm based on velocity obstacle (V-obstacle) which adjusts the USV's heading and speed in real-time. Sea trials results in multi-obstacle avoidance firstly demonstrate the effectiveness and efficiency of the proposed avoidance system, and then verify its great adaptability and relative stability when a USV sailing in a real and complex marine environment. The obtained results will improve the intelligent level of USV and guarantee the safety of USV independent sailing.

Online machining error estimation method of numerical control gear grinding machine tool based on data analysis of internal sensors

NASA Astrophysics Data System (ADS)

Zhao, Fei; Zhang, Chi; Yang, Guilin; Chen, Chinyin

2016-12-01

This paper presents an online estimation method of cutting error by analyzing of internal sensor readings. The internal sensors of numerical control (NC) machine tool are selected to avoid installation problem. The estimation mathematic model of cutting error was proposed to compute the relative position of cutting point and tool center point (TCP) from internal sensor readings based on cutting theory of gear. In order to verify the effectiveness of the proposed model, it was simulated and experimented in gear generating grinding process. The cutting error of gear was estimated and the factors which induce cutting error were analyzed. The simulation and experiments verify that the proposed approach is an efficient way to estimate the cutting error of work-piece during machining process.

Damage Detection Based on Static Strain Responses Using FBG in a Wind Turbine Blade

PubMed Central

Tian, Shaohua; Yang, Zhibo; Chen, Xuefeng; Xie, Yong

2015-01-01

The damage detection of a wind turbine blade enables better operation of the turbines, and provides an early alert to the destroyed events of the blade in order to avoid catastrophic losses. A new non-baseline damage detection method based on the Fiber Bragg grating (FBG) in a wind turbine blade is developed in this paper. Firstly, the Chi-square distribution is proven to be an effective damage-sensitive feature which is adopted as the individual information source for the local decision. In order to obtain the global and optimal decision for the damage detection, the feature information fusion (FIF) method is proposed to fuse and optimize information in above individual information sources, and the damage is detected accurately through of the global decision. Then a 13.2 m wind turbine blade with the distributed strain sensor system is adopted to describe the feasibility of the proposed method, and the strain energy method (SEM) is used to describe the advantage of the proposed method. Finally results show that the proposed method can deliver encouraging results of the damage detection in the wind turbine blade. PMID:26287200

An Operating Method Using Prediction of Photovoltaic Power for a Photovoltaic-Diesel Hybrid Power Generation System

NASA Astrophysics Data System (ADS)

Yamamoto, Shigehiro; Sumi, Kazuyoshi; Nishikawa, Eiichi; Hashimoto, Takeshi

This paper describes a novel operating method using prediction of photovoltaic (PV) power for a photovoltaic-diesel hybrid power generation system. The system is composed of a PV array, a storage battery, a bi-directional inverter and a diesel engine generator (DG). The proposed method enables the system to save fuel consumption by using PV energy effectively, reducing charge and discharge energy of the storage battery, and avoiding low-load operation of the DG. The PV power is simply predicted from a theoretical equation of solar radiation and the observed PV energy for a constant time before the prediction. The amount of fuel consumption of the proposed method is compared with that of other methods by a simulation based on measurement data of the PV power at an actual PV generation system for one year. The simulation results indicate that the amount of fuel consumption of the proposed method is smaller than that of any other methods, and is close to that of the ideal operation of the DG.

Efficient biprediction decision scheme for fast high efficiency video coding encoding

NASA Astrophysics Data System (ADS)

Park, Sang-hyo; Lee, Seung-ho; Jang, Euee S.; Jun, Dongsan; Kang, Jung-Won

2016-11-01

An efficient biprediction decision scheme of high efficiency video coding (HEVC) is proposed for fast-encoding applications. For low-delay video applications, bidirectional prediction can be used to increase compression performance efficiently with previous reference frames. However, at the same time, the computational complexity of the HEVC encoder is significantly increased due to the additional biprediction search. Although a some research has attempted to reduce this complexity, whether the prediction is strongly related to both motion complexity and prediction modes in a coding unit has not yet been investigated. A method that avoids most compression-inefficient search points is proposed so that the computational complexity of the motion estimation process can be dramatically decreased. To determine if biprediction is critical, the proposed method exploits the stochastic correlation of the context of prediction units (PUs): the direction of a PU and the accuracy of a motion vector. Through experimental results, the proposed method showed that the time complexity of biprediction can be reduced to 30% on average, outperforming existing methods in view of encoding time, number of function calls, and memory access.

Error analysis in a stereo vision-based pedestrian detection sensor for collision avoidance applications.

PubMed

Llorca, David F; Sotelo, Miguel A; Parra, Ignacio; Ocaña, Manuel; Bergasa, Luis M

2010-01-01

This paper presents an analytical study of the depth estimation error of a stereo vision-based pedestrian detection sensor for automotive applications such as pedestrian collision avoidance and/or mitigation. The sensor comprises two synchronized and calibrated low-cost cameras. Pedestrians are detected by combining a 3D clustering method with Support Vector Machine-based (SVM) classification. The influence of the sensor parameters in the stereo quantization errors is analyzed in detail providing a point of reference for choosing the sensor setup according to the application requirements. The sensor is then validated in real experiments. Collision avoidance maneuvers by steering are carried out by manual driving. A real time kinematic differential global positioning system (RTK-DGPS) is used to provide ground truth data corresponding to both the pedestrian and the host vehicle locations. The performed field test provided encouraging results and proved the validity of the proposed sensor for being used in the automotive sector towards applications such as autonomous pedestrian collision avoidance.

Error Analysis in a Stereo Vision-Based Pedestrian Detection Sensor for Collision Avoidance Applications

PubMed Central

Llorca, David F.; Sotelo, Miguel A.; Parra, Ignacio; Ocaña, Manuel; Bergasa, Luis M.

2010-01-01

This paper presents an analytical study of the depth estimation error of a stereo vision-based pedestrian detection sensor for automotive applications such as pedestrian collision avoidance and/or mitigation. The sensor comprises two synchronized and calibrated low-cost cameras. Pedestrians are detected by combining a 3D clustering method with Support Vector Machine-based (SVM) classification. The influence of the sensor parameters in the stereo quantization errors is analyzed in detail providing a point of reference for choosing the sensor setup according to the application requirements. The sensor is then validated in real experiments. Collision avoidance maneuvers by steering are carried out by manual driving. A real time kinematic differential global positioning system (RTK-DGPS) is used to provide ground truth data corresponding to both the pedestrian and the host vehicle locations. The performed field test provided encouraging results and proved the validity of the proposed sensor for being used in the automotive sector towards applications such as autonomous pedestrian collision avoidance. PMID:22319323

Towards social autonomous vehicles: Efficient collision avoidance scheme using Richardson's arms race model.

PubMed

Riaz, Faisal; Niazi, Muaz A

2017-01-01

This paper presents the concept of a social autonomous agent to conceptualize such Autonomous Vehicles (AVs), which interacts with other AVs using social manners similar to human behavior. The presented AVs also have the capability of predicting intentions, i.e. mentalizing and copying the actions of each other, i.e. mirroring. Exploratory Agent Based Modeling (EABM) level of the Cognitive Agent Based Computing (CABC) framework has been utilized to design the proposed social agent. Furthermore, to emulate the functionality of mentalizing and mirroring modules of proposed social agent, a tailored mathematical model of the Richardson's arms race model has also been presented. The performance of the proposed social agent has been validated at two levels-firstly it has been simulated using NetLogo, a standard agent-based modeling tool and also, at a practical level using a prototype AV. The simulation results have confirmed that the proposed social agent-based collision avoidance strategy is 78.52% more efficient than Random walk based collision avoidance strategy in congested flock-like topologies. Whereas practical results have confirmed that the proposed scheme can avoid rear end and lateral collisions with the efficiency of 99.876% as compared with the IEEE 802.11n-based existing state of the art mirroring neuron-based collision avoidance scheme.

Towards social autonomous vehicles: Efficient collision avoidance scheme using Richardson’s arms race model

PubMed Central

Niazi, Muaz A.

2017-01-01

This paper presents the concept of a social autonomous agent to conceptualize such Autonomous Vehicles (AVs), which interacts with other AVs using social manners similar to human behavior. The presented AVs also have the capability of predicting intentions, i.e. mentalizing and copying the actions of each other, i.e. mirroring. Exploratory Agent Based Modeling (EABM) level of the Cognitive Agent Based Computing (CABC) framework has been utilized to design the proposed social agent. Furthermore, to emulate the functionality of mentalizing and mirroring modules of proposed social agent, a tailored mathematical model of the Richardson’s arms race model has also been presented. The performance of the proposed social agent has been validated at two levels–firstly it has been simulated using NetLogo, a standard agent-based modeling tool and also, at a practical level using a prototype AV. The simulation results have confirmed that the proposed social agent-based collision avoidance strategy is 78.52% more efficient than Random walk based collision avoidance strategy in congested flock-like topologies. Whereas practical results have confirmed that the proposed scheme can avoid rear end and lateral collisions with the efficiency of 99.876% as compared with the IEEE 802.11n-based existing state of the art mirroring neuron-based collision avoidance scheme. PMID:29040294

Extinction-ratio-independent electrical method for measuring chirp parameters of Mach-Zehnder modulators using frequency-shifted heterodyne.

PubMed

Zhang, Shangjian; Wang, Heng; Zou, Xinhai; Zhang, Yali; Lu, Rongguo; Liu, Yong

2015-06-15

An extinction-ratio-independent electrical method is proposed for measuring chirp parameters of Mach-Zehnder electric-optic intensity modulators based on frequency-shifted optical heterodyne. The method utilizes the electrical spectrum analysis of the heterodyne products between the intensity modulated optical signal and the frequency-shifted optical carrier, and achieves the intrinsic chirp parameters measurement at microwave region with high-frequency resolution and wide-frequency range for the Mach-Zehnder modulator with a finite extinction ratio. Moreover, the proposed method avoids calibrating the responsivity fluctuation of the photodiode in spite of the involved photodetection. Chirp parameters as a function of modulation frequency are experimentally measured and compared to those with the conventional optical spectrum analysis method. Our method enables an extinction-ratio-independent and calibration-free electrical measurement of Mach-Zehnder intensity modulators by using the high-resolution frequency-shifted heterodyne technique.

Flow-gated radial phase-contrast imaging in the presence of weak flow.

PubMed

Peng, Hsu-Hsia; Huang, Teng-Yi; Wang, Fu-Nien; Chung, Hsiao-Wen

2013-01-01

To implement a flow-gating method to acquire phase-contrast (PC) images of carotid arteries without use of an electrocardiography (ECG) signal to synchronize the acquisition of imaging data with pulsatile arterial flow. The flow-gating method was realized through radial scanning and sophisticated post-processing methods including downsampling, complex difference, and correlation analysis to improve the evaluation of flow-gating times in radial phase-contrast scans. Quantitatively comparable results (R = 0.92-0.96, n = 9) of flow-related parameters, including mean velocity, mean flow rate, and flow volume, with conventional ECG-gated imaging demonstrated that the proposed method is highly feasible. The radial flow-gating PC imaging method is applicable in carotid arteries. The proposed flow-gating method can potentially avoid the setting up of ECG-related equipment for brain imaging. This technique has potential use in patients with arrhythmia or weak ECG signals.

Patients Know Best: Qualitative Study on How Families Use Patient-Controlled Personal Health Records

PubMed Central

Schneider, Hanna; Hill, Susan

2016-01-01

Background Self-management technologies, such as patient-controlled electronic health records (PCEHRs), have the potential to help people manage and cope with disease. Objective This study set out to investigate patient families’ lived experiences of working with a PCEHR. Methods We conducted a semistructured qualitative field study with patient families and clinicians at a children’s hospital in the UK that uses a PCEHR (Patients Know Best). All families were managing the health of a child with a serious chronic condition, who was typically under the care of multiple clinicians. As data gathering and analysis progressed, it became clear that while much of the literature assumes that patients are willing and waiting to take more responsibility for and control over their health management (eg, with PCEHRs), only a minority of participants in our study responded in this way. Their experiences with the PCEHR were diverse and strongly shaped by their coping styles. Theory on coping identifies a continuum of coping styles, from approach to avoidance oriented, and proposes that patients’ information needs depend on their style. Results We identified 3 groups of patient families and an outlier, distinguished by their coping style and their PCEHR use. We refer to the outlier as controlling (approach oriented, highly motivated to use PCEHR), and the 3 groups as collaborating (approach oriented, motivated to use PCEHR), cooperating (avoidance oriented, less motivated to use PCEHR), and avoiding (very avoidance oriented, not motivated to use PCEHR). Conclusions The PCEHR met the needs of controller and collaborators better than the needs of cooperators and avoiders. We draw on the Self-Determination Theory to propose ways in which a PCEHR design might better meet the needs of avoidance-oriented users. Further, we highlight the need for families to also relinquish control at times, and propose ways in which PCEHR design might support a better distribution of control, based on effective training, ease of use, comprehensibility of data security mechanisms, timely information provision (recognizing people’s different needs), personalization of use, and easy engagement with clinicians through the PCEHR. PMID:26912201

Intelligent Surveillance Robot with Obstacle Avoidance Capabilities Using Neural Network

PubMed Central

2015-01-01

For specific purpose, vision-based surveillance robot that can be run autonomously and able to acquire images from its dynamic environment is very important, for example, in rescuing disaster victims in Indonesia. In this paper, we propose architecture for intelligent surveillance robot that is able to avoid obstacles using 3 ultrasonic distance sensors based on backpropagation neural network and a camera for face recognition. 2.4 GHz transmitter for transmitting video is used by the operator/user to direct the robot to the desired area. Results show the effectiveness of our method and we evaluate the performance of the system. PMID:26089863

Efficient discovery of risk patterns in medical data.

PubMed

Li, Jiuyong; Fu, Ada Wai-chee; Fahey, Paul

2009-01-01

This paper studies a problem of efficiently discovering risk patterns in medical data. Risk patterns are defined by a statistical metric, relative risk, which has been widely used in epidemiological research. To avoid fruitless search in the complete exploration of risk patterns, we define optimal risk pattern set to exclude superfluous patterns, i.e. complicated patterns with lower relative risk than their corresponding simpler form patterns. We prove that mining optimal risk pattern sets conforms an anti-monotone property that supports an efficient mining algorithm. We propose an efficient algorithm for mining optimal risk pattern sets based on this property. We also propose a hierarchical structure to present discovered patterns for the easy perusal by domain experts. The proposed approach is compared with two well-known rule discovery methods, decision tree and association rule mining approaches on benchmark data sets and applied to a real world application. The proposed method discovers more and better quality risk patterns than a decision tree approach. The decision tree method is not designed for such applications and is inadequate for pattern exploring. The proposed method does not discover a large number of uninteresting superfluous patterns as an association mining approach does. The proposed method is more efficient than an association rule mining method. A real world case study shows that the method reveals some interesting risk patterns to medical practitioners. The proposed method is an efficient approach to explore risk patterns. It quickly identifies cohorts of patients that are vulnerable to a risk outcome from a large data set. The proposed method is useful for exploratory study on large medical data to generate and refine hypotheses. The method is also useful for designing medical surveillance systems.

Naturalness preservation image contrast enhancement via histogram modification

NASA Astrophysics Data System (ADS)

Tian, Qi-Chong; Cohen, Laurent D.

2018-04-01

Contrast enhancement is a technique for enhancing image contrast to obtain better visual quality. Since many existing contrast enhancement algorithms usually produce over-enhanced results, the naturalness preservation is needed to be considered in the framework of image contrast enhancement. This paper proposes a naturalness preservation contrast enhancement method, which adopts the histogram matching to improve the contrast and uses the image quality assessment to automatically select the optimal target histogram. The contrast improvement and the naturalness preservation are both considered in the target histogram, so this method can avoid the over-enhancement problem. In the proposed method, the optimal target histogram is a weighted sum of the original histogram, the uniform histogram, and the Gaussian-shaped histogram. Then the structural metric and the statistical naturalness metric are used to determine the weights of corresponding histograms. At last, the contrast-enhanced image is obtained via matching the optimal target histogram. The experiments demonstrate the proposed method outperforms the compared histogram-based contrast enhancement algorithms.

Singular boundary method for wave propagation analysis in periodic structures

NASA Astrophysics Data System (ADS)

Fu, Zhuojia; Chen, Wen; Wen, Pihua; Zhang, Chuanzeng

2018-07-01

A strong-form boundary collocation method, the singular boundary method (SBM), is developed in this paper for the wave propagation analysis at low and moderate wavenumbers in periodic structures. The SBM is of several advantages including mathematically simple, easy-to-program, meshless with the application of the concept of origin intensity factors in order to eliminate the singularity of the fundamental solutions and avoid the numerical evaluation of the singular integrals in the boundary element method. Due to the periodic behaviors of the structures, the SBM coefficient matrix can be represented as a block Toeplitz matrix. By employing three different fast Toeplitz-matrix solvers, the computational time and storage requirements are significantly reduced in the proposed SBM analysis. To demonstrate the effectiveness of the proposed SBM formulation for wave propagation analysis in periodic structures, several benchmark examples are presented and discussed The proposed SBM results are compared with the analytical solutions, the reference results and the COMSOL software.

Autonomous Landmark Calibration Method for Indoor Localization

PubMed Central

Kim, Jae-Hoon; Kim, Byoung-Seop

2017-01-01

Machine-generated data expansion is a global phenomenon in recent Internet services. The proliferation of mobile communication and smart devices has increased the utilization of machine-generated data significantly. One of the most promising applications of machine-generated data is the estimation of the location of smart devices. The motion sensors integrated into smart devices generate continuous data that can be used to estimate the location of pedestrians in an indoor environment. We focus on the estimation of the accurate location of smart devices by determining the landmarks appropriately for location error calibration. In the motion sensor-based location estimation, the proposed threshold control method determines valid landmarks in real time to avoid the accumulation of errors. A statistical method analyzes the acquired motion sensor data and proposes a valid landmark for every movement of the smart devices. Motion sensor data used in the testbed are collected from the actual measurements taken throughout a commercial building to demonstrate the practical usefulness of the proposed method. PMID:28837071

On the effect of local barrier height in scanning tunneling microscopy: Measurement methods and control implications

NASA Astrophysics Data System (ADS)

Tajaddodianfar, Farid; Moheimani, S. O. Reza; Owen, James; Randall, John N.

2018-01-01

A common cause of tip-sample crashes in a Scanning Tunneling Microscope (STM) operating in constant current mode is the poor performance of its feedback control system. We show that there is a direct link between the Local Barrier Height (LBH) and robustness of the feedback control loop. A method known as the "gap modulation method" was proposed in the early STM studies for estimating the LBH. We show that the obtained measurements are affected by controller parameters and propose an alternative method which we prove to produce LBH measurements independent of the controller dynamics. We use the obtained LBH estimation to continuously update the gains of a STM proportional-integral (PI) controller and show that while tuning the PI gains, the closed-loop system tolerates larger variations of LBH without experiencing instability. We report experimental results, conducted on two STM scanners, to establish the efficiency of the proposed PI tuning approach. Improved feedback stability is believed to help in avoiding the tip/sample crash in STMs.

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

Wang, Xiao; Gao, Wenzhong; Wang, Jianhui

To release the 'hidden inertia' of variable-speed wind turbines for temporary frequency support, a method of torque-limit based inertial control is proposed in this paper. This method aims to improve the frequency support capability considering the maximum torque restriction of a permanent magnet synchronous generator. The advantages of the proposed method are improved frequency nadir (FN) in the event of an under-frequency disturbance; and avoidance of over-deceleration and a second frequency dip during the inertial response. The system frequency response is different, with different slope values in the power-speed plane when the inertial response is performed. The proposed method ismore » evaluated in a modified three-machine, nine-bus system. The simulation results show that there is a trade-off between the recovery time and FN, such that a gradual slope tends to improve the FN and restrict the rate of change of frequency aggressively while causing an extension of the recovery time. These results provide insight into how to properly design such kinds of inertial control strategies for practical applications.« less

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

Wang, Xiao; Gao, Wenzhong; Wang, Jianhui

To release the 'hidden inertia' of variable-speed wind turbines for temporary frequency support, a method of torque-limit-based inertial control is proposed in this paper. This method aims to improve the frequency support capability considering the maximum torque restriction of a permanent magnet synchronous generator. The advantages of the proposed method are improved frequency nadir (FN) in the event of an under-frequency disturbance; and avoidance of over-deceleration and a second frequency dip during the inertial response. The system frequency response is different, with different slope values in the power-speed plane when the inertial response is performed. The proposed method is evaluatedmore » in a modified three-machine, nine-bus system. The simulation results show that there is a trade-off between the recovery time and FN, such that a gradual slope tends to improve the FN and restrict the rate of change of frequency aggressively while causing an extension of the recovery time. These results provide insight into how to properly design such kinds of inertial control strategies for practical applications.« less

Efficient and stable exponential time differencing Runge-Kutta methods for phase field elastic bending energy models

NASA Astrophysics Data System (ADS)

Wang, Xiaoqiang; Ju, Lili; Du, Qiang

2016-07-01

The Willmore flow formulated by phase field dynamics based on the elastic bending energy model has been widely used to describe the shape transformation of biological lipid vesicles. In this paper, we develop and investigate some efficient and stable numerical methods for simulating the unconstrained phase field Willmore dynamics and the phase field Willmore dynamics with fixed volume and surface area constraints. The proposed methods can be high-order accurate and are completely explicit in nature, by combining exponential time differencing Runge-Kutta approximations for time integration with spectral discretizations for spatial operators on regular meshes. We also incorporate novel linear operator splitting techniques into the numerical schemes to improve the discrete energy stability. In order to avoid extra numerical instability brought by use of large penalty parameters in solving the constrained phase field Willmore dynamics problem, a modified augmented Lagrange multiplier approach is proposed and adopted. Various numerical experiments are performed to demonstrate accuracy and stability of the proposed methods.

Adaptive projection intensity adjustment for avoiding saturation in three-dimensional shape measurement

NASA Astrophysics Data System (ADS)

Chen, Chao; Gao, Nan; Wang, Xiangjun; Zhang, Zonghua

2018-03-01

Phase-based fringe projection methods have been commonly used for three-dimensional (3D) measurements. However, image saturation results in incorrect intensities in captured fringe pattern images, leading to phase and measurement errors. Existing solutions are complex. This paper proposes an adaptive projection intensity adjustment method to avoid image saturation and maintain good fringe modulation in measuring objects with a high range of surface reflectivities. The adapted fringe patterns are created using only one prior step of fringe-pattern projection and image capture. First, a set of phase-shifted fringe patterns with maximum projection intensity value of 255 and a uniform gray level pattern are projected onto the surface of an object. The patterns are reflected from and deformed by the object surface and captured by a digital camera. The best projection intensities corresponding to each saturated-pixel clusters are determined by fitting a polynomial function to transform captured intensities to projected intensities. Subsequently, the adapted fringe patterns are constructed using the best projection intensities at projector pixel coordinate. Finally, the adapted fringe patterns are projected for phase recovery and 3D shape calculation. The experimental results demonstrate that the proposed method achieves high measurement accuracy even for objects with a high range of surface reflectivities.

Partial volume correction of brain perfusion estimates using the inherent signal data of time-resolved arterial spin labeling.

PubMed

Ahlgren, André; Wirestam, Ronnie; Petersen, Esben Thade; Ståhlberg, Freddy; Knutsson, Linda

2014-09-01

Quantitative perfusion MRI based on arterial spin labeling (ASL) is hampered by partial volume effects (PVEs), arising due to voxel signal cross-contamination between different compartments. To address this issue, several partial volume correction (PVC) methods have been presented. Most previous methods rely on segmentation of a high-resolution T1 -weighted morphological image volume that is coregistered to the low-resolution ASL data, making the result sensitive to errors in the segmentation and coregistration. In this work, we present a methodology for partial volume estimation and correction, using only low-resolution ASL data acquired with the QUASAR sequence. The methodology consists of a T1 -based segmentation method, with no spatial priors, and a modified PVC method based on linear regression. The presented approach thus avoids prior assumptions about the spatial distribution of brain compartments, while also avoiding coregistration between different image volumes. Simulations based on a digital phantom as well as in vivo measurements in 10 volunteers were used to assess the performance of the proposed segmentation approach. The simulation results indicated that QUASAR data can be used for robust partial volume estimation, and this was confirmed by the in vivo experiments. The proposed PVC method yielded probable perfusion maps, comparable to a reference method based on segmentation of a high-resolution morphological scan. Corrected gray matter (GM) perfusion was 47% higher than uncorrected values, suggesting a significant amount of PVEs in the data. Whereas the reference method failed to completely eliminate the dependence of perfusion estimates on the volume fraction, the novel approach produced GM perfusion values independent of GM volume fraction. The intra-subject coefficient of variation of corrected perfusion values was lowest for the proposed PVC method. As shown in this work, low-resolution partial volume estimation in connection with ASL perfusion estimation is feasible, and provides a promising tool for decoupling perfusion and tissue volume. Copyright © 2014 John Wiley & Sons, Ltd.

A Method for Dynamically Selecting the Best Frequency Hopping Technique in Industrial Wireless Sensor Network Applications

PubMed Central

Fernández de Gorostiza, Erlantz; Mabe, Jon

2018-01-01

Industrial wireless applications often share the communication channel with other wireless technologies and communication protocols. This coexistence produces interferences and transmission errors which require appropriate mechanisms to manage retransmissions. Nevertheless, these mechanisms increase the network latency and overhead due to the retransmissions. Thus, the loss of data packets and the measures to handle them produce an undesirable drop in the QoS and hinder the overall robustness and energy efficiency of the network. Interference avoidance mechanisms, such as frequency hopping techniques, reduce the need for retransmissions due to interferences but they are often tailored to specific scenarios and are not easily adapted to other use cases. On the other hand, the total absence of interference avoidance mechanisms introduces a security risk because the communication channel may be intentionally attacked and interfered with to hinder or totally block it. In this paper we propose a method for supporting the design of communication solutions under dynamic channel interference conditions and we implement dynamic management policies for frequency hopping technique and channel selection at runtime. The method considers several standard frequency hopping techniques and quality metrics, and the quality and status of the available frequency channels to propose the best combined solution to minimize the side effects of interferences. A simulation tool has been developed and used in this work to validate the method. PMID:29473910

Optical coefficient measurements using bulk living tissue by an optical fiber puncture with FOV change

NASA Astrophysics Data System (ADS)

Nakazawa, Haruna; Doi, Marika; Ogawa, Emiyu; Arai, Tsunenori

2018-02-01

To avoid an instability of the optical coefficient measurement using sliced tissue preparation, we proposed the combination of light intensity measurement through an optical fiber puncturing into a bulk tissue varying field of view (FOV) and ray tracing calculation using Monte-Carlo method. The optical coefficients of myocardium such as absorption coefficient μa, scattering coefficient μs, and anisotropic parameter g are used in the myocardium optical propagation. Since optical coefficients obtained using thin sliced tissue could be instable because they are affected by dehydration and intracellular fluid effusion on the sample surface, variety of coefficients have been reported over individual optical differences of living samples. The proposed method which combined the experiment using the bulk tissue with ray tracing calculation were performed. In this method, a 200 μmΦ high-NA silica fiber installed in a 21G needle was punctured up to the bottom of the myocardial bulk tissue over 3 cm in thickness to measure light intensity changing the fiber-tip depth and FOV. We found that the measured attenuation coefficients decreased as the FOV increased. The ray trace calculation represented the same FOV dependence in above mentioned experimental result. We think our particular fiber punctured measurement using bulk tissue varying FOV with Inverse Monte-Carlo method might be useful to obtain the optical coefficients to avoid sample preparation instabilities.

A Method for Dynamically Selecting the Best Frequency Hopping Technique in Industrial Wireless Sensor Network Applications.

PubMed

Fernández de Gorostiza, Erlantz; Berzosa, Jorge; Mabe, Jon; Cortiñas, Roberto

2018-02-23

Industrial wireless applications often share the communication channel with other wireless technologies and communication protocols. This coexistence produces interferences and transmission errors which require appropriate mechanisms to manage retransmissions. Nevertheless, these mechanisms increase the network latency and overhead due to the retransmissions. Thus, the loss of data packets and the measures to handle them produce an undesirable drop in the QoS and hinder the overall robustness and energy efficiency of the network. Interference avoidance mechanisms, such as frequency hopping techniques, reduce the need for retransmissions due to interferences but they are often tailored to specific scenarios and are not easily adapted to other use cases. On the other hand, the total absence of interference avoidance mechanisms introduces a security risk because the communication channel may be intentionally attacked and interfered with to hinder or totally block it. In this paper we propose a method for supporting the design of communication solutions under dynamic channel interference conditions and we implement dynamic management policies for frequency hopping technique and channel selection at runtime. The method considers several standard frequency hopping techniques and quality metrics, and the quality and status of the available frequency channels to propose the best combined solution to minimize the side effects of interferences. A simulation tool has been developed and used in this work to validate the method.

Segmentation of mouse dynamic PET images using a multiphase level set method

NASA Astrophysics Data System (ADS)

Cheng-Liao, Jinxiu; Qi, Jinyi

2010-11-01

Image segmentation plays an important role in medical diagnosis. Here we propose an image segmentation method for four-dimensional mouse dynamic PET images. We consider that voxels inside each organ have similar time activity curves. The use of tracer dynamic information allows us to separate regions that have similar integrated activities in a static image but with different temporal responses. We develop a multiphase level set method that utilizes both the spatial and temporal information in a dynamic PET data set. Different weighting factors are assigned to each image frame based on the noise level and activity difference among organs of interest. We used a weighted absolute difference function in the data matching term to increase the robustness of the estimate and to avoid over-partition of regions with high contrast. We validated the proposed method using computer simulated dynamic PET data, as well as real mouse data from a microPET scanner, and compared the results with those of a dynamic clustering method. The results show that the proposed method results in smoother segments with the less number of misclassified voxels.

Contour detection improved by context-adaptive surround suppression.

PubMed

Sang, Qiang; Cai, Biao; Chen, Hao

2017-01-01

Recently, many image processing applications have taken advantage of a psychophysical and neurophysiological mechanism, called "surround suppression" to extract object contour from a natural scene. However, these traditional methods often adopt a single suppression model and a fixed input parameter called "inhibition level", which needs to be manually specified. To overcome these drawbacks, we propose a novel model, called "context-adaptive surround suppression", which can automatically control the effect of surround suppression according to image local contextual features measured by a surface estimator based on a local linear kernel. Moreover, a dynamic suppression method and its stopping mechanism are introduced to avoid manual intervention. The proposed algorithm is demonstrated and validated by a broad range of experimental results.

Formation Control for Water-Jet USV Based on Bio-Inspired Method

NASA Astrophysics Data System (ADS)

Fu, Ming-yu; Wang, Duan-song; Wang, Cheng-long

2018-03-01

The formation control problem for underactuated unmanned surface vehicles (USVs) is addressed by a distributed strategy based on virtual leader strategy. The control system takes account of disturbance induced by external environment. With the coordinate transformation, the advantage of the proposed scheme is that the control point can be any point of the ship instead of the center of gravity. By introducing bio-inspired model, the formation control problem is addressed with backstepping method. This avoids complicated computation, simplifies the control law, and smoothes the input signals. The system uniform ultimate boundness is proven by Lyapunov stability theory with Young inequality. Simulation results are presented to verify the effectiveness and robust of the proposed controller.

Multiple sound source localization using gammatone auditory filtering and direct sound componence detection

NASA Astrophysics Data System (ADS)

Chen, Huaiyu; Cao, Li

2017-06-01

In order to research multiple sound source localization with room reverberation and background noise, we analyze the shortcomings of traditional broadband MUSIC and ordinary auditory filtering based broadband MUSIC method, then a new broadband MUSIC algorithm with gammatone auditory filtering of frequency component selection control and detection of ascending segment of direct sound componence is proposed. The proposed algorithm controls frequency component within the interested frequency band in multichannel bandpass filter stage. Detecting the direct sound componence of the sound source for suppressing room reverberation interference is also proposed, whose merits are fast calculation and avoiding using more complex de-reverberation processing algorithm. Besides, the pseudo-spectrum of different frequency channels is weighted by their maximum amplitude for every speech frame. Through the simulation and real room reverberation environment experiments, the proposed method has good performance. Dynamic multiple sound source localization experimental results indicate that the average absolute error of azimuth estimated by the proposed algorithm is less and the histogram result has higher angle resolution.

Recognition and defect detection of dot-matrix text via variation-model based learning

NASA Astrophysics Data System (ADS)

Ohyama, Wataru; Suzuki, Koushi; Wakabayashi, Tetsushi

2017-03-01

An algorithm for recognition and defect detection of dot-matrix text printed on products is proposed. Extraction and recognition of dot-matrix text contains several difficulties, which are not involved in standard camera-based OCR, that the appearance of dot-matrix characters is corrupted and broken by illumination, complex texture in the background and other standard characters printed on product packages. We propose a dot-matrix text extraction and recognition method which does not require any user interaction. The method employs detected location of corner points and classification score. The result of evaluation experiment using 250 images shows that recall and precision of extraction are 78.60% and 76.03%, respectively. Recognition accuracy of correctly extracted characters is 94.43%. Detecting printing defect of dot-matrix text is also important in the production scene to avoid illegal productions. We also propose a detection method for printing defect of dot-matrix characters. The method constructs a feature vector of which elements are classification scores of each character class and employs support vector machine to classify four types of printing defect. The detection accuracy of the proposed method is 96.68 %.

Modeling a color-rendering operator for high dynamic range images using a cone-response function

NASA Astrophysics Data System (ADS)

Choi, Ho-Hyoung; Kim, Gi-Seok; Yun, Byoung-Ju

2015-09-01

Tone-mapping operators are the typical algorithms designed to produce visibility and the overall impression of brightness, contrast, and color of high dynamic range (HDR) images on low dynamic range (LDR) display devices. Although several new tone-mapping operators have been proposed in recent years, the results of these operators have not matched those of the psychophysical experiments based on the human visual system. A color-rendering model that is a combination of tone-mapping and cone-response functions using an XYZ tristimulus color space is presented. In the proposed method, the tone-mapping operator produces visibility and the overall impression of brightness, contrast, and color in HDR images when mapped onto relatively LDR devices. The tone-mapping resultant image is obtained using chromatic and achromatic colors to avoid well-known color distortions shown in the conventional methods. The resulting image is then processed with a cone-response function wherein emphasis is placed on human visual perception (HVP). The proposed method covers the mismatch between the actual scene and the rendered image based on HVP. The experimental results show that the proposed method yields an improved color-rendering performance compared to conventional methods.

Robust gaze-steering of an active vision system against errors in the estimated parameters

NASA Astrophysics Data System (ADS)

Han, Youngmo

2015-01-01

Gaze-steering is often used to broaden the viewing range of an active vision system. Gaze-steering procedures are usually based on estimated parameters such as image position, image velocity, depth and camera calibration parameters. However, there may be uncertainties in these estimated parameters because of measurement noise and estimation errors. In this case, robust gaze-steering cannot be guaranteed. To compensate for such problems, this paper proposes a gaze-steering method based on a linear matrix inequality (LMI). In this method, we first propose a proportional derivative (PD) control scheme on the unit sphere that does not use depth parameters. This proposed PD control scheme can avoid uncertainties in the estimated depth and camera calibration parameters, as well as inconveniences in their estimation process, including the use of auxiliary feature points and highly non-linear computation. Furthermore, the control gain of the proposed PD control scheme on the unit sphere is designed using LMI such that the designed control is robust in the presence of uncertainties in the other estimated parameters, such as image position and velocity. Simulation results demonstrate that the proposed method provides a better compensation for uncertainties in the estimated parameters than the contemporary linear method and steers the gaze of the camera more steadily over time than the contemporary non-linear method.

Collision analysis of one kind of chaos-based hash function

NASA Astrophysics Data System (ADS)

Xiao, Di; Peng, Wenbing; Liao, Xiaofeng; Xiang, Tao

2010-02-01

In the last decade, various chaos-based hash functions have been proposed. Nevertheless, the corresponding analyses of them lag far behind. In this Letter, we firstly take a chaos-based hash function proposed very recently in Amin, Faragallah and Abd El-Latif (2009) [11] as a sample to analyze its computational collision problem, and then generalize the construction method of one kind of chaos-based hash function and summarize some attentions to avoid the collision problem. It is beneficial to the hash function design based on chaos in the future.

KEWPIE: A dynamical cascade code for decaying exited compound nuclei

NASA Astrophysics Data System (ADS)

Bouriquet, Bertrand; Abe, Yasuhisa; Boilley, David

2004-05-01

A new dynamical cascade code for decaying hot nuclei is proposed and specially adapted to the synthesis of super-heavy nuclei. For such a case, the interesting channel is of the tiny fraction that will decay through particles emission, thus the code avoids classical Monte-Carlo methods and proposes a new numerical scheme. The time dependence is explicitely taken into account in order to cope with the fact that fission decay rate might not be constant. The code allows to evaluate both statistical and dynamical observables. Results are successfully compared to experimental data.

Analysis of backward error recovery for concurrent processes with recovery blocks

NASA Technical Reports Server (NTRS)

Shin, K. G.; Lee, Y. H.

1982-01-01

Three different methods of implementing recovery blocks (RB's). These are the asynchronous, synchronous, and the pseudo recovery point implementations. Pseudo recovery points so that unbounded rollback may be avoided while maintaining process autonomy are proposed. Probabilistic models for analyzing these three methods under standard assumptions in computer performance analysis, i.e., exponential distributions for related random variables were developed. The interval between two successive recovery lines for asynchronous RB's mean loss in computation power for the synchronized method, and additional overhead and rollback distance in case PRP's are used were estimated.

Fringe order correction for the absolute phase recovered by two selected spatial frequency fringe projections in fringe projection profilometry.

PubMed

Ding, Yi; Peng, Kai; Yu, Miao; Lu, Lei; Zhao, Kun

2017-08-01

The performance of the two selected spatial frequency phase unwrapping methods is limited by a phase error bound beyond which errors will occur in the fringe order leading to a significant error in the recovered absolute phase map. In this paper, we propose a method to detect and correct the wrong fringe orders. Two constraints are introduced during the fringe order determination of two selected spatial frequency phase unwrapping methods. A strategy to detect and correct the wrong fringe orders is also described. Compared with the existing methods, we do not need to estimate the threshold associated with absolute phase values to determine the fringe order error, thus making it more reliable and avoiding the procedure of search in detecting and correcting successive fringe order errors. The effectiveness of the proposed method is validated by the experimental results.

Rapid determination of free fatty acid content in waste deodorizer distillates using single bounce-attenuated total reflectance-FTIR spectroscopy.

PubMed

Naz, Saba; Sherazi, Sayed Tufail Hussain; Talpur, Farah N; Mahesar, Sarfaraz A; Kara, Huseyin

2012-01-01

A simple, rapid, economical, and environmentally friendly analytical method was developed for the quantitative assessment of free fatty acids (FFAs) present in deodorizer distillates and crude oils by single bounce-attenuated total reflectance-FTIR spectroscopy. Partial least squares was applied for the calibration model based on the peak region of the carbonyl group (C=O) from 1726 to 1664 cm(-1) associated with the FFAs. The proposed method totally avoided the use of organic solvents or costly standards and could be applied easily in the oil processing industry. The accuracy of the method was checked by comparison to a conventional standard American Oil Chemists' Society (AOCS) titrimetric procedure, which provided good correlation (R = 0.99980), with an SD of +/- 0.05%. Therefore, the proposed method could be used as an alternate to the AOCS titrimetric method for the quantitative determination of FFAs especially in deodorizer distillates.

A statistically robust EEG re-referencing procedure to mitigate reference effect

PubMed Central

Lepage, Kyle Q.; Kramer, Mark A.; Chu, Catherine J.

2014-01-01

Background The electroencephalogram (EEG) remains the primary tool for diagnosis of abnormal brain activity in clinical neurology and for in vivo recordings of human neurophysiology in neuroscience research. In EEG data acquisition, voltage is measured at positions on the scalp with respect to a reference electrode. When this reference electrode responds to electrical activity or artifact all electrodes are affected. Successful analysis of EEG data often involves re-referencing procedures that modify the recorded traces and seek to minimize the impact of reference electrode activity upon functions of the original EEG recordings. New method We provide a novel, statistically robust procedure that adapts a robust maximum-likelihood type estimator to the problem of reference estimation, reduces the influence of neural activity from the re-referencing operation, and maintains good performance in a wide variety of empirical scenarios. Results The performance of the proposed and existing re-referencing procedures are validated in simulation and with examples of EEG recordings. To facilitate this comparison, channel-to-channel correlations are investigated theoretically and in simulation. Comparison with existing methods The proposed procedure avoids using data contaminated by neural signal and remains unbiased in recording scenarios where physical references, the common average reference (CAR) and the reference estimation standardization technique (REST) are not optimal. Conclusion The proposed procedure is simple, fast, and avoids the potential for substantial bias when analyzing low-density EEG data. PMID:24975291

Spurious cross-frequency amplitude-amplitude coupling in nonstationary, nonlinear signals

NASA Astrophysics Data System (ADS)

Yeh, Chien-Hung; Lo, Men-Tzung; Hu, Kun

2016-07-01

Recent studies of brain activities show that cross-frequency coupling (CFC) plays an important role in memory and learning. Many measures have been proposed to investigate the CFC phenomenon, including the correlation between the amplitude envelopes of two brain waves at different frequencies - cross-frequency amplitude-amplitude coupling (AAC). In this short communication, we describe how nonstationary, nonlinear oscillatory signals may produce spurious cross-frequency AAC. Utilizing the empirical mode decomposition, we also propose a new method for assessment of AAC that can potentially reduce the effects of nonlinearity and nonstationarity and, thus, help to avoid the detection of artificial AACs. We compare the performances of this new method and the traditional Fourier-based AAC method. We also discuss the strategies to identify potential spurious AACs.

A novel segmentation method for uneven lighting image with noise injection based on non-local spatial information and intuitionistic fuzzy entropy

NASA Astrophysics Data System (ADS)

Yu, Haiyan; Fan, Jiulun

2017-12-01

Local thresholding methods for uneven lighting image segmentation always have the limitations that they are very sensitive to noise injection and that the performance relies largely upon the choice of the initial window size. This paper proposes a novel algorithm for segmenting uneven lighting images with strong noise injection based on non-local spatial information and intuitionistic fuzzy theory. We regard an image as a gray wave in three-dimensional space, which is composed of many peaks and troughs, and these peaks and troughs can divide the image into many local sub-regions in different directions. Our algorithm computes the relative characteristic of each pixel located in the corresponding sub-region based on fuzzy membership function and uses it to replace its absolute characteristic (its gray level) to reduce the influence of uneven light on image segmentation. At the same time, the non-local adaptive spatial constraints of pixels are introduced to avoid noise interference with the search of local sub-regions and the computation of local characteristics. Moreover, edge information is also taken into account to avoid false peak and trough labeling. Finally, a global method based on intuitionistic fuzzy entropy is employed on the wave transformation image to obtain the segmented result. Experiments on several test images show that the proposed method has excellent capability of decreasing the influence of uneven illumination on images and noise injection and behaves more robustly than several classical global and local thresholding methods.

A Divergence Median-based Geometric Detector with A Weighted Averaging Filter

NASA Astrophysics Data System (ADS)

Hua, Xiaoqiang; Cheng, Yongqiang; Li, Yubo; Wang, Hongqiang; Qin, Yuliang

2018-01-01

To overcome the performance degradation of the classical fast Fourier transform (FFT)-based constant false alarm rate detector with the limited sample data, a divergence median-based geometric detector on the Riemannian manifold of Heimitian positive definite matrices is proposed in this paper. In particular, an autocorrelation matrix is used to model the correlation of sample data. This method of the modeling can avoid the poor Doppler resolution as well as the energy spread of the Doppler filter banks result from the FFT. Moreover, a weighted averaging filter, conceived from the philosophy of the bilateral filtering in image denoising, is proposed and combined within the geometric detection framework. As the weighted averaging filter acts as the clutter suppression, the performance of the geometric detector is improved. Numerical experiments are given to validate the effectiveness of our proposed method.

W-algebra for solving problems with fuzzy parameters

NASA Astrophysics Data System (ADS)

Shevlyakov, A. O.; Matveev, M. G.

2018-03-01

A method of solving the problems with fuzzy parameters by means of a special algebraic structure is proposed. The structure defines its operations through operations on real numbers, which simplifies its use. It avoids deficiencies limiting applicability of the other known structures. Examples for solution of a quadratic equation, a system of linear equations and a network planning problem are given.

Proposal for a Standard Greenhouse Method for Assessing Soybean Cyst Nematode Resistance in Soybean: SCE08 (Standardized Cyst Evaluation 2008)

USDA-ARS?s Scientific Manuscript database

The soybean cyst nematode (SCN) remains the most economically important pathogen of soybean in North America. Most farmers do not sample for SCN believing instead that the use of SCN-resistant varieties is sufficient to avoid yield losses due to the nematode according to surveys conducted in Illino...

Covariance-based direction-of-arrival estimation of wideband coherent chirp signals via sparse representation.

PubMed

Sha, Zhichao; Liu, Zhengmeng; Huang, Zhitao; Zhou, Yiyu

2013-08-29

This paper addresses the problem of direction-of-arrival (DOA) estimation of multiple wideband coherent chirp signals, and a new method is proposed. The new method is based on signal component analysis of the array output covariance, instead of the complicated time-frequency analysis used in previous literatures, and thus is more compact and effectively avoids possible signal energy loss during the hyper-processes. Moreover, the a priori information of signal number is no longer a necessity for DOA estimation in the new method. Simulation results demonstrate the performance superiority of the new method over previous ones.

Pseudo-color coding method for high-dynamic single-polarization SAR images

NASA Astrophysics Data System (ADS)

Feng, Zicheng; Liu, Xiaolin; Pei, Bingzhi

2018-04-01

A raw synthetic aperture radar (SAR) image usually has a 16-bit or higher bit depth, which cannot be directly visualized on 8-bit displays. In this study, we propose a pseudo-color coding method for high-dynamic singlepolarization SAR images. The method considers the characteristics of both SAR images and human perception. In HSI (hue, saturation and intensity) color space, the method carries out high-dynamic range tone mapping and pseudo-color processing simultaneously in order to avoid loss of details and to improve object identifiability. It is a highly efficient global algorithm.

The safety helmet detection technology and its application to the surveillance system.

PubMed

Wen, Che-Yen

2004-07-01

The Automatic Teller Machine (ATM) plays an important role in the modem economy. It provides a fast and convenient way to process transactions between banks and their customers. Unfortunately, it also provides a convenient way for criminals to get illegal money or use stolen ATM cards to extract money from their victims' accounts. For safety reasons, each ATM has a surveillance system to record customer's face information. However, when criminals use an ATM to withdraw money illegally, they usually hide their faces with something (in Taiwan, criminals usually use safety helmets to block their faces) to avoid the surveillance system recording their face information, which decreases the efficiency of the surveillance system. In this paper, we propose a circle/circular arc detection method based upon the modified Hough transform, and apply it to the detection of safety helmets for the surveillance system of ATMs. Since the safety helmet location will be within the set of the obtainable circles/circular arcs (if any exist), we use geometric features to verify if any safety helmet exists in the set. The proposed method can be used to help the surveillance systems record a customer's face information more precisely. If customers wear safety helmets to block their faces, the system can send a message to remind them to take off their helmets. Besides this, the method can be applied to the surveillance systems of banks by providing an early warning safeguard when any "customer" or "intruder" uses a safety helmet to avoid his/her face information from being recorded by the surveillance system. This will make the surveillance system more useful. Real images are used to analyze the performance of the proposed method.

Hair and bare skin discrimination for laser-assisted hair removal systems.

PubMed

Cayir, Sercan; Yetik, Imam Samil

2017-07-01

Laser-assisted hair removal devices aim to remove body hair permanently. In most cases, these devices irradiate the whole area of the skin with a homogenous power density. Thus, a significant portion of the skin, where hair is not present, is burnt unnecessarily causing health risks. Therefore, methods that can distinguish hair regions automatically would be very helpful avoiding these unnecessary applications of laser. This study proposes a new system of algorithms to detect hair regions with the help of a digital camera. Unlike previous limited number of studies, our methods are very fast allowing for real-time application. Proposed methods are based on certain features derived from histograms of hair and skin regions. We compare our algorithm with competing methods in terms of localization performance and computation time and show that a much faster real-time accurate localization of hair regions is possible with the proposed method. Our results show that the algorithm we have developed is extremely fast (around 45 milliseconds) allowing for real-time application with high accuracy hair localization ( 96.48 %).

Fault diagnosis method based on FFT-RPCA-SVM for Cascaded-Multilevel Inverter.

PubMed

Wang, Tianzhen; Qi, Jie; Xu, Hao; Wang, Yide; Liu, Lei; Gao, Diju

2016-01-01

Thanks to reduced switch stress, high quality of load wave, easy packaging and good extensibility, the cascaded H-bridge multilevel inverter is widely used in wind power system. To guarantee stable operation of system, a new fault diagnosis method, based on Fast Fourier Transform (FFT), Relative Principle Component Analysis (RPCA) and Support Vector Machine (SVM), is proposed for H-bridge multilevel inverter. To avoid the influence of load variation on fault diagnosis, the output voltages of the inverter is chosen as the fault characteristic signals. To shorten the time of diagnosis and improve the diagnostic accuracy, the main features of the fault characteristic signals are extracted by FFT. To further reduce the training time of SVM, the feature vector is reduced based on RPCA that can get a lower dimensional feature space. The fault classifier is constructed via SVM. An experimental prototype of the inverter is built to test the proposed method. Compared to other fault diagnosis methods, the experimental results demonstrate the high accuracy and efficiency of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

[Application of Fourier transform profilometry in 3D-surface reconstruction].

PubMed

Shi, Bi'er; Lu, Kuan; Wang, Yingting; Li, Zhen'an; Bai, Jing

2011-08-01

With the improvement of system frame and reconstruction methods in fluorescent molecules tomography (FMT), the FMT technology has been widely used as an important experimental tool in biomedical research. It is necessary to get the 3D-surface profile of the experimental object as the boundary constraints of FMT reconstruction algorithms. We proposed a new 3D-surface reconstruction method based on Fourier transform profilometry (FTP) method under the blue-purple light condition. The slice images were reconstructed using proper image processing methods, frequency spectrum analysis and filtering. The results of experiment showed that the method properly reconstructed the 3D-surface of objects and has the mm-level accuracy. Compared to other methods, this one is simple and fast. Besides its well-reconstructed, the proposed method could help monitor the behavior of the object during the experiment to ensure the correspondence of the imaging process. Furthermore, the method chooses blue-purple light section as its light source to avoid the interference towards fluorescence imaging.

Fault Analysis of Space Station DC Power Systems-Using Neural Network Adaptive Wavelets to Detect Faults

NASA Technical Reports Server (NTRS)

Momoh, James A.; Wang, Yanchun; Dolce, James L.

1997-01-01

This paper describes the application of neural network adaptive wavelets for fault diagnosis of space station power system. The method combines wavelet transform with neural network by incorporating daughter wavelets into weights. Therefore, the wavelet transform and neural network training procedure become one stage, which avoids the complex computation of wavelet parameters and makes the procedure more straightforward. The simulation results show that the proposed method is very efficient for the identification of fault locations.

Airborne Collision Detection and Avoidance for Small UAS Sense and Avoid Systems

NASA Astrophysics Data System (ADS)

Sahawneh, Laith Rasmi

The increasing demand to integrate unmanned aircraft systems (UAS) into the national airspace is motivated by the rapid growth of the UAS industry, especially small UAS weighing less than 55 pounds. Their use however has been limited by the Federal Aviation Administration regulations due to collision risk they pose, safety and regulatory concerns. Therefore, before civil aviation authorities can approve routine UAS flight operations, UAS must be equipped with sense-and-avoid technology comparable to the see-and-avoid requirements for manned aircraft. The sense-and-avoid problem includes several important aspects including regulatory and system-level requirements, design specifications and performance standards, intruder detecting and tracking, collision risk assessment, and finally path planning and collision avoidance. In this dissertation, our primary focus is on developing an collision detection, risk assessment and avoidance framework that is computationally affordable and suitable to run on-board small UAS. To begin with, we address the minimum sensing range for the sense-and-avoid (SAA) system. We present an approximate close form analytical solution to compute the minimum sensing range to safely avoid an imminent collision. The approach is then demonstrated using a radar sensor prototype that achieves the required minimum sensing range. In the area of collision risk assessment and collision prediction, we present two approaches to estimate the collision risk of an encounter scenario. The first is a deterministic approach similar to those been developed for Traffic Alert and Collision Avoidance (TCAS) in manned aviation. We extend the approach to account for uncertainties of state estimates by deriving an analytic expression to propagate the error variance using Taylor series approximation. To address unanticipated intruders maneuvers, we propose an innovative probabilistic approach to quantify likely intruder trajectories and estimate the probability of collision risk using the uncorrelated encounter model (UEM) developed by MIT Lincoln Laboratory. We evaluate the proposed approach using Monte Carlo simulations and compare the performance with linearly extrapolated collision detection logic. For the path planning and collision avoidance part, we present multiple reactive path planning algorithms. We first propose a collision avoidance algorithm based on a simulated chain that responds to a virtual force field produced by encountering intruders. The key feature of the proposed approach is to model the future motion of both the intruder and the ownship using a chain of waypoints that are equally spaced in time. This timing information is used to continuously re-plan paths that minimize the probability of collision. Second, we present an innovative collision avoidance logic using an ownship centered coordinate system. The technique builds a graph in the local-level frame and uses the Dijkstra's algorithm to find the least cost path. An advantage of this approach is that collision avoidance is inherently a local phenomenon and can be more naturally represented in the local coordinates than the global coordinates. Finally, we propose a two step path planner for ground-based SAA systems. In the first step, an initial suboptimal path is generated using A* search. In the second step, using the A* solution as an initial condition, a chain of unit masses connected by springs and dampers evolves in a simulated force field. The chain is described by a set of ordinary differential equations that is driven by virtual forces to find the steady-state equilibrium. The simulation results show that the proposed approach produces collision-free plans while minimizing the path length. To move towards a deployable system, we apply collision detection and avoidance techniques to a variety of simulation and sensor modalities including camera, radar and ADS-B along with suitable tracking schemes. Keywords: unmanned aircraft system, small UAS, sense and avoid, minimum sensing range, airborne collision detection and avoidance, collision detection, collision risk assessment, collision avoidance, conflict detection, conflict avoidance, path planning.

Coordinated Dynamic Behaviors for Multirobot Systems With Collision Avoidance.

PubMed

Sabattini, Lorenzo; Secchi, Cristian; Fantuzzi, Cesare

2017-12-01

In this paper, we propose a novel methodology for achieving complex dynamic behaviors in multirobot systems. In particular, we consider a multirobot system partitioned into two subgroups: 1) dependent and 2) independent robots. Independent robots are utilized as a control input, and their motion is controlled in such a way that the dependent robots solve a tracking problem, that is following arbitrarily defined setpoint trajectories, in a coordinated manner. The control strategy proposed in this paper explicitly addresses the collision avoidance problem, utilizing a null space-based behavioral approach: this leads to combining, in a non conflicting manner, the tracking control law with a collision avoidance strategy. The combination of these control actions allows the robots to execute their task in a safe way. Avoidance of collisions is formally proven in this paper, and the proposed methodology is validated by means of simulations and experiments on real robots.

Adaptive error covariances estimation methods for ensemble Kalman filters

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

Zhen, Yicun, E-mail: zhen@math.psu.edu; Harlim, John, E-mail: jharlim@psu.edu

2015-08-01

This paper presents a computationally fast algorithm for estimating, both, the system and observation noise covariances of nonlinear dynamics, that can be used in an ensemble Kalman filtering framework. The new method is a modification of Belanger's recursive method, to avoid an expensive computational cost in inverting error covariance matrices of product of innovation processes of different lags when the number of observations becomes large. When we use only product of innovation processes up to one-lag, the computational cost is indeed comparable to a recently proposed method by Berry–Sauer's. However, our method is more flexible since it allows for usingmore » information from product of innovation processes of more than one-lag. Extensive numerical comparisons between the proposed method and both the original Belanger's and Berry–Sauer's schemes are shown in various examples, ranging from low-dimensional linear and nonlinear systems of SDEs and 40-dimensional stochastically forced Lorenz-96 model. Our numerical results suggest that the proposed scheme is as accurate as the original Belanger's scheme on low-dimensional problems and has a wider range of more accurate estimates compared to Berry–Sauer's method on L-96 example.« less

Fast and high-order numerical algorithms for the solution of multidimensional nonlinear fractional Ginzburg-Landau equation

NASA Astrophysics Data System (ADS)

Mohebbi, Akbar

2018-02-01

In this paper we propose two fast and accurate numerical methods for the solution of multidimensional space fractional Ginzburg-Landau equation (FGLE). In the presented methods, to avoid solving a nonlinear system of algebraic equations and to increase the accuracy and efficiency of method, we split the complex problem into simpler sub-problems using the split-step idea. For a homogeneous FGLE, we propose a method which has fourth-order of accuracy in time component and spectral accuracy in space variable and for nonhomogeneous one, we introduce another scheme based on the Crank-Nicolson approach which has second-order of accuracy in time variable. Due to using the Fourier spectral method for fractional Laplacian operator, the resulting schemes are fully diagonal and easy to code. Numerical results are reported in terms of accuracy, computational order and CPU time to demonstrate the accuracy and efficiency of the proposed methods and to compare the results with the analytical solutions. The results show that the present methods are accurate and require low CPU time. It is illustrated that the numerical results are in good agreement with the theoretical ones.

Elitist Binary Wolf Search Algorithm for Heuristic Feature Selection in High-Dimensional Bioinformatics Datasets.

PubMed

Li, Jinyan; Fong, Simon; Wong, Raymond K; Millham, Richard; Wong, Kelvin K L

2017-06-28

Due to the high-dimensional characteristics of dataset, we propose a new method based on the Wolf Search Algorithm (WSA) for optimising the feature selection problem. The proposed approach uses the natural strategy established by Charles Darwin; that is, 'It is not the strongest of the species that survives, but the most adaptable'. This means that in the evolution of a swarm, the elitists are motivated to quickly obtain more and better resources. The memory function helps the proposed method to avoid repeat searches for the worst position in order to enhance the effectiveness of the search, while the binary strategy simplifies the feature selection problem into a similar problem of function optimisation. Furthermore, the wrapper strategy gathers these strengthened wolves with the classifier of extreme learning machine to find a sub-dataset with a reasonable number of features that offers the maximum correctness of global classification models. The experimental results from the six public high-dimensional bioinformatics datasets tested demonstrate that the proposed method can best some of the conventional feature selection methods up to 29% in classification accuracy, and outperform previous WSAs by up to 99.81% in computational time.

A thermodynamically consistent discontinuous Galerkin formulation for interface separation

DOE PAGES

Versino, Daniele; Mourad, Hashem M.; Dávila, Carlos G.; ...

2015-07-31

Our paper describes the formulation of an interface damage model, based on the discontinuous Galerkin (DG) method, for the simulation of failure and crack propagation in laminated structures. The DG formulation avoids common difficulties associated with cohesive elements. Specifically, it does not introduce any artificial interfacial compliance and, in explicit dynamic analysis, it leads to a stable time increment size which is unaffected by the presence of stiff massless interfaces. This proposed method is implemented in a finite element setting. Convergence and accuracy are demonstrated in Mode I and mixed-mode delamination in both static and dynamic analyses. Significantly, numerical resultsmore » obtained using the proposed interface model are found to be independent of the value of the penalty factor that characterizes the DG formulation. By contrast, numerical results obtained using a classical cohesive method are found to be dependent on the cohesive penalty stiffnesses. The proposed approach is shown to yield more accurate predictions pertaining to crack propagation under mixed-mode fracture because of the advantage. Furthermore, in explicit dynamic analysis, the stable time increment size calculated with the proposed method is found to be an order of magnitude larger than the maximum allowable value for classical cohesive elements.« less

Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI.

PubMed

Zhou, Yongxin; Bai, Jing

2007-01-01

A framework that combines atlas registration, fuzzy connectedness (FC) segmentation, and parametric bias field correction (PABIC) is proposed for the automatic segmentation of brain magnetic resonance imaging (MRI). First, the atlas is registered onto the MRI to initialize the following FC segmentation. Original techniques are proposed to estimate necessary initial parameters of FC segmentation. Further, the result of the FC segmentation is utilized to initialize a following PABIC algorithm. Finally, we re-apply the FC technique on the PABIC corrected MRI to get the final segmentation. Thus, we avoid expert human intervention and provide a fully automatic method for brain MRI segmentation. Experiments on both simulated and real MRI images demonstrate the validity of the method, as well as the limitation of the method. Being a fully automatic method, it is expected to find wide applications, such as three-dimensional visualization, radiation therapy planning, and medical database construction.

Random Weighting, Strong Tracking, and Unscented Kalman Filter for Soft Tissue Characterization.

PubMed

Shin, Jaehyun; Zhong, Yongmin; Oetomo, Denny; Gu, Chengfan

2018-05-21

This paper presents a new nonlinear filtering method based on the Hunt-Crossley model for online nonlinear soft tissue characterization. This method overcomes the problem of performance degradation in the unscented Kalman filter due to contact model error. It adopts the concept of Mahalanobis distance to identify contact model error, and further incorporates a scaling factor in predicted state covariance to compensate identified model error. This scaling factor is determined according to the principle of innovation orthogonality to avoid the cumbersome computation of Jacobian matrix, where the random weighting concept is adopted to improve the estimation accuracy of innovation covariance. A master-slave robotic indentation system is developed to validate the performance of the proposed method. Simulation and experimental results as well as comparison analyses demonstrate that the efficacy of the proposed method for online characterization of soft tissue parameters in the presence of contact model error.

A Method for Counting Moving People in Video Surveillance Videos

NASA Astrophysics Data System (ADS)

Conte, Donatello; Foggia, Pasquale; Percannella, Gennaro; Tufano, Francesco; Vento, Mario

2010-12-01

People counting is an important problem in video surveillance applications. This problem has been faced either by trying to detect people in the scene and then counting them or by establishing a mapping between some scene feature and the number of people (avoiding the complex detection problem). This paper presents a novel method, following this second approach, that is based on the use of SURF features and of an [InlineEquation not available: see fulltext.]-SVR regressor provide an estimate of this count. The algorithm takes specifically into account problems due to partial occlusions and to perspective. In the experimental evaluation, the proposed method has been compared with the algorithm by Albiol et al., winner of the PETS 2009 contest on people counting, using the same PETS 2009 database. The provided results confirm that the proposed method yields an improved accuracy, while retaining the robustness of Albiol's algorithm.

Application of 2D graphic representation of protein sequence based on Huffman tree method.

PubMed

Qi, Zhao-Hui; Feng, Jun; Qi, Xiao-Qin; Li, Ling

2012-05-01

Based on Huffman tree method, we propose a new 2D graphic representation of protein sequence. This representation can completely avoid loss of information in the transfer of data from a protein sequence to its graphic representation. The method consists of two parts. One is about the 0-1 codes of 20 amino acids by Huffman tree with amino acid frequency. The amino acid frequency is defined as the statistical number of an amino acid in the analyzed protein sequences. The other is about the 2D graphic representation of protein sequence based on the 0-1 codes. Then the applications of the method on ten ND5 genes and seven Escherichia coli strains are presented in detail. The results show that the proposed model may provide us with some new sights to understand the evolution patterns determined from protein sequences and complete genomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Automatic Train Operation Using Autonomic Prediction of Train Runs

NASA Astrophysics Data System (ADS)

Asuka, Masashi; Kataoka, Kenji; Komaya, Kiyotoshi; Nishida, Syogo

In this paper, we present an automatic train control method adaptable to disturbed train traffic conditions. The proposed method presumes transmission of detected time of a home track clearance to trains approaching to the station by employing equipment of Digital ATC (Automatic Train Control). Using the information, each train controls its acceleration by the method that consists of two approaches. First, by setting a designated restricted speed, the train controls its running time to arrive at the next station in accordance with predicted delay. Second, the train predicts the time at which it will reach the current braking pattern generated by Digital ATC, along with the time when the braking pattern transits ahead. By comparing them, the train correctly chooses the coasting drive mode in advance to avoid deceleration due to the current braking pattern. We evaluated the effectiveness of the proposed method regarding driving conditions, energy consumption and reduction of delays by simulation.

The EM Method in a Probabilistic Wavelet-Based MRI Denoising

PubMed Central

2015-01-01

Human body heat emission and others external causes can interfere in magnetic resonance image acquisition and produce noise. In this kind of images, the noise, when no signal is present, is Rayleigh distributed and its wavelet coefficients can be approximately modeled by a Gaussian distribution. Noiseless magnetic resonance images can be modeled by a Laplacian distribution in the wavelet domain. This paper proposes a new magnetic resonance image denoising method to solve this fact. This method performs shrinkage of wavelet coefficients based on the conditioned probability of being noise or detail. The parameters involved in this filtering approach are calculated by means of the expectation maximization (EM) method, which avoids the need to use an estimator of noise variance. The efficiency of the proposed filter is studied and compared with other important filtering techniques, such as Nowak's, Donoho-Johnstone's, Awate-Whitaker's, and nonlocal means filters, in different 2D and 3D images. PMID:26089959

The EM Method in a Probabilistic Wavelet-Based MRI Denoising.

PubMed

Martin-Fernandez, Marcos; Villullas, Sergio

2015-01-01

Human body heat emission and others external causes can interfere in magnetic resonance image acquisition and produce noise. In this kind of images, the noise, when no signal is present, is Rayleigh distributed and its wavelet coefficients can be approximately modeled by a Gaussian distribution. Noiseless magnetic resonance images can be modeled by a Laplacian distribution in the wavelet domain. This paper proposes a new magnetic resonance image denoising method to solve this fact. This method performs shrinkage of wavelet coefficients based on the conditioned probability of being noise or detail. The parameters involved in this filtering approach are calculated by means of the expectation maximization (EM) method, which avoids the need to use an estimator of noise variance. The efficiency of the proposed filter is studied and compared with other important filtering techniques, such as Nowak's, Donoho-Johnstone's, Awate-Whitaker's, and nonlocal means filters, in different 2D and 3D images.

Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

PubMed

Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

2016-10-05

Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.

Ultrahigh sensitivity refractive index sensor of a D-shaped PCF based on surface plasmon resonance.

PubMed

Wu, JunJun; Li, Shuguang; Wang, Xinyu; Shi, Min; Feng, Xinxing; Liu, Yundong

2018-05-20

We propose a D-shaped photonic crystal fiber (PCF) refractive index sensor with ultrahigh sensitivity and a wide detection range. The gold layer is deposited on the polished surface, avoiding filling or coating inside the air holes of the PCF. The influences of the gold layer thickness and the diameter of the larger air holes are investigated. The sensing characteristics of the proposed sensor are analyzed by the finite element method. The maximum sensitivity can reach 31,000  nm/RIU, and the refractive index detection range is from 1.32 to 1.40. Our proposed PCF has excellent sensing characteristics and is competitive in sensing devices.

A Mixed Integer Linear Programming Approach to Electrical Stimulation Optimization Problems.

PubMed

Abouelseoud, Gehan; Abouelseoud, Yasmine; Shoukry, Amin; Ismail, Nour; Mekky, Jaidaa

2018-02-01

Electrical stimulation optimization is a challenging problem. Even when a single region is targeted for excitation, the problem remains a constrained multi-objective optimization problem. The constrained nature of the problem results from safety concerns while its multi-objectives originate from the requirement that non-targeted regions should remain unaffected. In this paper, we propose a mixed integer linear programming formulation that can successfully address the challenges facing this problem. Moreover, the proposed framework can conclusively check the feasibility of the stimulation goals. This helps researchers to avoid wasting time trying to achieve goals that are impossible under a chosen stimulation setup. The superiority of the proposed framework over alternative methods is demonstrated through simulation examples.

General Framework for Meta-analysis of Rare Variants in Sequencing Association Studies

PubMed Central

Lee, Seunggeun; Teslovich, Tanya M.; Boehnke, Michael; Lin, Xihong

2013-01-01

We propose a general statistical framework for meta-analysis of gene- or region-based multimarker rare variant association tests in sequencing association studies. In genome-wide association studies, single-marker meta-analysis has been widely used to increase statistical power by combining results via regression coefficients and standard errors from different studies. In analysis of rare variants in sequencing studies, region-based multimarker tests are often used to increase power. We propose meta-analysis methods for commonly used gene- or region-based rare variants tests, such as burden tests and variance component tests. Because estimation of regression coefficients of individual rare variants is often unstable or not feasible, the proposed method avoids this difficulty by calculating score statistics instead that only require fitting the null model for each study and then aggregating these score statistics across studies. Our proposed meta-analysis rare variant association tests are conducted based on study-specific summary statistics, specifically score statistics for each variant and between-variant covariance-type (linkage disequilibrium) relationship statistics for each gene or region. The proposed methods are able to incorporate different levels of heterogeneity of genetic effects across studies and are applicable to meta-analysis of multiple ancestry groups. We show that the proposed methods are essentially as powerful as joint analysis by directly pooling individual level genotype data. We conduct extensive simulations to evaluate the performance of our methods by varying levels of heterogeneity across studies, and we apply the proposed methods to meta-analysis of rare variant effects in a multicohort study of the genetics of blood lipid levels. PMID:23768515

Energy Savings in Cellular Networks Based on Space-Time Structure of Traffic Loads

NASA Astrophysics Data System (ADS)

Sun, Jingbo; Wang, Yue; Yuan, Jian; Shan, Xiuming

Since most of energy consumed by the telecommunication infrastructure is due to the Base Transceiver Station (BTS), switching off BTSs when traffic load is low has been recognized as an effective way of saving energy. In this letter, an energy saving scheme is proposed to minimize the number of active BTSs based on the space-time structure of traffic loads as determined by principal component analysis. Compared to existing methods, our approach models traffic loads more accurately, and has a much smaller input size. As it is implemented in an off-line manner, our scheme also avoids excessive communications and computing overheads. Simulation results show that the proposed method has a comparable performance in energy savings.

Reasons and remedies for the agglomeration of multilayered graphene and carbon nanotubes in polymers

PubMed Central

Atif, Rasheed

2016-01-01

Summary One of the main issues in the production of polymer nanocomposites is the dispersion state of filler as multilayered graphene (MLG) and carbon nanotubes (CNTs) tend to agglomerate due to van der Waals forces. The agglomeration can be avoided by using organic solvents, selecting suitable dispersion and production methods, and functionalizing the fillers. Another proposed method is the use of hybrid fillers as synergistic effects can cause an improvement in the dispersion state of the fillers. In this review article, various aspects of each process that can help avoid filler agglomeration and improve dispersion state are discussed in detail. This review article would be helpful for both current and prospective researchers in the field of MLG- and CNT-based polymer nanocomposites to achieve maximum enhancement in mechanical, thermal, and electrical properties of produced polymer nanocomposites. PMID:27826492

A fast referenceless PRFS-based MR thermometry by phase finite difference

NASA Astrophysics Data System (ADS)

Zou, Chao; Shen, Huan; He, Mengyue; Tie, Changjun; Chung, Yiu-Cho; Liu, Xin

2013-08-01

Proton resonance frequency shift-based MR thermometry is a promising temperature monitoring approach for thermotherapy but its accuracy is vulnerable to inter-scan motion. Model-based referenceless thermometry has been proposed to address this problem but phase unwrapping is usually needed before the model fitting process. In this paper, a referenceless MR thermometry method using phase finite difference that avoids the time consuming phase unwrapping procedure is proposed. Unlike the previously proposed phase gradient technique, the use of finite difference in the new method reduces the fitting error resulting from the ringing artifacts associated with phase discontinuity in the calculation of the phase gradient image. The new method takes into account the values at the perimeter of the region of interest because of their direct relevance to the extrapolated baseline phase of the region of interest (where temperature increase takes place). In simulation study, in vivo and ex vivo experiments, the new method has a root-mean-square temperature error of 0.35 °C, 1.02 °C and 1.73 °C compared to 0.83 °C, 2.81 °C, and 3.76 °C from the phase gradient method, respectively. The method also demonstrated a slightly higher, albeit small, temperature accuracy than the original referenceless MR thermometry method. The proposed method is computationally efficient (∼0.1 s per image), making it very suitable for the real time temperature monitoring.

The Organization for Economic Cooperation and Development

DTIC Science & Technology

2010-02-08

experience of OECD members with bilateral treaties, the increasingly sophisticated methods for tax evasion , and the development of new and more complex...new efforts to curtail the use of tax havens for tax avoidance , combined with efforts since the terrorist...addition, on May 4, 2009, President Obama announced a set of proposals to, “crack down on illegal overseas tax evasion , close loopholes, and make it

A dynamic replication management strategy in distributed GIS

NASA Astrophysics Data System (ADS)

Pan, Shaoming; Xiong, Lian; Xu, Zhengquan; Chong, Yanwen; Meng, Qingxiang

2018-03-01

Replication strategy is one of effective solutions to meet the requirement of service response time by preparing data in advance to avoid the delay of reading data from disks. This paper presents a brand-new method to create copies considering the selection of replicas set, the number of copies for each replica and the placement strategy of all copies. First, the popularities of all data are computed considering both the historical access records and the timeliness of the records. Then, replica set can be selected based on their recent popularities. Also, an enhanced Q-value scheme is proposed to assign the number of copies for each replica. Finally, a reasonable copies placement strategy is designed to meet the requirement of load balance. In addition, we present several experiments that compare the proposed method with techniques that use other replication management strategies. The results show that the proposed model has better performance than other algorithms in all respects. Moreover, the experiments based on different parameters also demonstrated the effectiveness and adaptability of the proposed algorithm.

Multi-tasking arbitration and behaviour design for human-interactive robots

NASA Astrophysics Data System (ADS)

Kobayashi, Yuichi; Onishi, Masaki; Hosoe, Shigeyuki; Luo, Zhiwei

2013-05-01

Robots that interact with humans in household environments are required to handle multiple real-time tasks simultaneously, such as carrying objects, collision avoidance and conversation with human. This article presents a design framework for the control and recognition processes to meet these requirements taking into account stochastic human behaviour. The proposed design method first introduces a Petri net for synchronisation of multiple tasks. The Petri net formulation is converted to Markov decision processes and processed in an optimal control framework. Three tasks (safety confirmation, object conveyance and conversation) interact and are expressed by the Petri net. Using the proposed framework, tasks that normally tend to be designed by integrating many if-then rules can be designed in a systematic manner in a state estimation and optimisation framework from the viewpoint of the shortest time optimal control. The proposed arbitration method was verified by simulations and experiments using RI-MAN, which was developed for interactive tasks with humans.

Optical image encryption using triplet of functions

NASA Astrophysics Data System (ADS)

Yatish; Fatima, Areeba; Nishchal, Naveen Kumar

2018-03-01

We propose an image encryption scheme that brings into play a technique using a triplet of functions to manipulate complex-valued functions. Optical cryptosystems using this method are an easier approach toward the ciphertext generation that avoids the use of holographic setup to record phase. The features of this method were shown in the context of double random phase encoding and phase-truncated Fourier transform-based cryptosystems using gyrator transform. In the first step, the complex function is split into two matrices. These matrices are separated, so they contain the real and imaginary parts. In the next step, these two matrices and a random distribution function are acted upon by one of the functions in the triplet. During decryption, the other two functions in the triplet help us retrieve the complex-valued function. The simulation results demonstrate the effectiveness of the proposed idea. To check the robustness of the proposed scheme, attack analyses were carried out.

Enhanced ICP for the Registration of Large-Scale 3D Environment Models: An Experimental Study

PubMed Central

Han, Jianda; Yin, Peng; He, Yuqing; Gu, Feng

2016-01-01

One of the main applications of mobile robots is the large-scale perception of the outdoor environment. One of the main challenges of this application is fusing environmental data obtained by multiple robots, especially heterogeneous robots. This paper proposes an enhanced iterative closest point (ICP) method for the fast and accurate registration of 3D environmental models. First, a hierarchical searching scheme is combined with the octree-based ICP algorithm. Second, an early-warning mechanism is used to perceive the local minimum problem. Third, a heuristic escape scheme based on sampled potential transformation vectors is used to avoid local minima and achieve optimal registration. Experiments involving one unmanned aerial vehicle and one unmanned surface vehicle were conducted to verify the proposed technique. The experimental results were compared with those of normal ICP registration algorithms to demonstrate the superior performance of the proposed method. PMID:26891298

Design of an adaptive super-twisting decoupled terminal sliding mode control scheme for a class of fourth-order systems.

PubMed

Ashtiani Haghighi, Donya; Mobayen, Saleh

2018-04-01

This paper proposes an adaptive super-twisting decoupled terminal sliding mode control technique for a class of fourth-order systems. The adaptive-tuning law eliminates the requirement of the knowledge about the upper bounds of external perturbations. Using the proposed control procedure, the state variables of cart-pole system are converged to decoupled terminal sliding surfaces and their equilibrium points in the finite time. Moreover, via the super-twisting algorithm, the chattering phenomenon is avoided without affecting the control performance. The numerical results demonstrate the high stabilization accuracy and lower performance indices values of the suggested method over the other ones. The simulation results on the cart-pole system as well as experimental validations demonstrate that the proposed control technique exhibits a reasonable performance in comparison with the other methods. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Bio-inspired vision based robot control using featureless estimations of time-to-contact.

PubMed

Zhang, Haijie; Zhao, Jianguo

2017-01-31

Marvelous vision based dynamic behaviors of insects and birds such as perching, landing, and obstacle avoidance have inspired scientists to propose the idea of time-to-contact, which is defined as the time for a moving observer to contact an object or surface if the current velocity is maintained. Since with only a vision sensor, time-to-contact can be directly estimated from consecutive images, it is widely used for a variety of robots to fulfill various tasks such as obstacle avoidance, docking, chasing, perching and landing. However, most of existing methods to estimate the time-to-contact need to extract and track features during the control process, which is time-consuming and cannot be applied to robots with limited computation power. In this paper, we adopt a featureless estimation method, extend this method to more general settings with angular velocities, and improve the estimation results using Kalman filtering. Further, we design an error based controller with gain scheduling strategy to control the motion of mobile robots. Experiments for both estimation and control are conducted using a customized mobile robot platform with low-cost embedded systems. Onboard experimental results demonstrate the effectiveness of the proposed approach, with the robot being controlled to successfully dock in front of a vertical wall. The estimation and control methods presented in this paper can be applied to computation-constrained miniature robots for agile locomotion such as landing, docking, or navigation.

Uncertain decision tree inductive inference

NASA Astrophysics Data System (ADS)

Zarban, L.; Jafari, S.; Fakhrahmad, S. M.

2011-10-01

Induction is the process of reasoning in which general rules are formulated based on limited observations of recurring phenomenal patterns. Decision tree learning is one of the most widely used and practical inductive methods, which represents the results in a tree scheme. Various decision tree algorithms have already been proposed such as CLS, ID3, Assistant C4.5, REPTree and Random Tree. These algorithms suffer from some major shortcomings. In this article, after discussing the main limitations of the existing methods, we introduce a new decision tree induction algorithm, which overcomes all the problems existing in its counterparts. The new method uses bit strings and maintains important information on them. This use of bit strings and logical operation on them causes high speed during the induction process. Therefore, it has several important features: it deals with inconsistencies in data, avoids overfitting and handles uncertainty. We also illustrate more advantages and the new features of the proposed method. The experimental results show the effectiveness of the method in comparison with other methods existing in the literature.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

NASA Astrophysics Data System (ADS)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

An orientation measurement method based on Hall-effect sensors for permanent magnet spherical actuators with 3D magnet array.

PubMed

Yan, Liang; Zhu, Bo; Jiao, Zongxia; Chen, Chin-Yin; Chen, I-Ming

2014-10-24

An orientation measurement method based on Hall-effect sensors is proposed for permanent magnet (PM) spherical actuators with three-dimensional (3D) magnet array. As there is no contact between the measurement system and the rotor, this method could effectively avoid friction torque and additional inertial moment existing in conventional approaches. Curved surface fitting method based on exponential approximation is proposed to formulate the magnetic field distribution in 3D space. The comparison with conventional modeling method shows that it helps to improve the model accuracy. The Hall-effect sensors are distributed around the rotor with PM poles to detect the flux density at different points, and thus the rotor orientation can be computed from the measured results and analytical models. Experiments have been conducted on the developed research prototype of the spherical actuator to validate the accuracy of the analytical equations relating the rotor orientation and the value of magnetic flux density. The experimental results show that the proposed method can measure the rotor orientation precisely, and the measurement accuracy could be improved by the novel 3D magnet array. The study result could be used for real-time motion control of PM spherical actuators.

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

PubMed

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.

Thermodynamically consistent data-driven computational mechanics

NASA Astrophysics Data System (ADS)

González, David; Chinesta, Francisco; Cueto, Elías

2018-05-01

In the paradigm of data-intensive science, automated, unsupervised discovering of governing equations for a given physical phenomenon has attracted a lot of attention in several branches of applied sciences. In this work, we propose a method able to avoid the identification of the constitutive equations of complex systems and rather work in a purely numerical manner by employing experimental data. In sharp contrast to most existing techniques, this method does not rely on the assumption on any particular form for the model (other than some fundamental restrictions placed by classical physics such as the second law of thermodynamics, for instance) nor forces the algorithm to find among a predefined set of operators those whose predictions fit best to the available data. Instead, the method is able to identify both the Hamiltonian (conservative) and dissipative parts of the dynamics while satisfying fundamental laws such as energy conservation or positive production of entropy, for instance. The proposed method is tested against some examples of discrete as well as continuum mechanics, whose accurate results demonstrate the validity of the proposed approach.

Single-camera displacement field correlation method for centrosymmetric 3D dynamic deformation measurement

NASA Astrophysics Data System (ADS)

Zhao, Jiaye; Wen, Huihui; Liu, Zhanwei; Rong, Jili; Xie, Huimin

2018-05-01

Three-dimensional (3D) deformation measurements are a key issue in experimental mechanics. In this paper, a displacement field correlation (DFC) method to measure centrosymmetric 3D dynamic deformation using a single camera is proposed for the first time. When 3D deformation information is collected by a camera at a tilted angle, the measured displacement fields are coupling fields of both the in-plane and out-of-plane displacements. The features of the coupling field are analysed in detail, and a decoupling algorithm based on DFC is proposed. The 3D deformation to be measured can be inverted and reconstructed using only one coupling field. The accuracy of this method was validated by a high-speed impact experiment that simulated an underwater explosion. The experimental results show that the approach proposed in this paper can be used in 3D deformation measurements with higher sensitivity and accuracy, and is especially suitable for high-speed centrosymmetric deformation. In addition, this method avoids the non-synchronisation problem associated with using a pair of high-speed cameras, as is common in 3D dynamic measurements.

Assessment of System Frequency Support Effect of PMSG-WTG Using Torque-Limit-Based Inertial Control

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

Wang, Xiao; Gao, Wenzhong; Wang, Jianhui

2017-02-16

To release the 'hidden inertia' of variable-speed wind turbines for temporary frequency support, a method of torque-limit based inertial control is proposed in this paper. This method aims to improve the frequency support capability considering the maximum torque restriction of a permanent magnet synchronous generator. The advantages of the proposed method are improved frequency nadir (FN) in the event of an under-frequency disturbance; and avoidance of over-deceleration and a second frequency dip during the inertial response. The system frequency response is different, with different slope values in the power-speed plane when the inertial response is performed. The proposed method ismore » evaluated in a modified three-machine, nine-bus system. The simulation results show that there is a trade-off between the recovery time and FN, such that a gradual slope tends to improve the FN and restrict the rate of change of frequency aggressively while causing an extension of the recovery time. These results provide insight into how to properly design such kinds of inertial control strategies for practical applications.« less

Two-Wavelength Multi-Gigahertz Frequency Comb-Based Interferometry for Full-Field Profilometry

NASA Astrophysics Data System (ADS)

Choi, Samuel; Kashiwagi, Ken; Kojima, Shuto; Kasuya, Yosuke; Kurokawa, Takashi

2013-10-01

The multi-gigahertz frequency comb-based interferometer exhibits only the interference amplitude peak without the phase fringes, which can produce a rapid axial scan for full-field profilometry and tomography. Despite huge technical advantages, there remain problems that the interference intensity undulations occurred depending on the interference phase. To avoid such problems, we propose a compensation technique of the interference signals using two frequency combs with slightly varied center wavelengths. The compensated full-field surface profile measurements of cover glass and onion skin were demonstrated experimentally to verify the advantages of the proposed method.

Least square neural network model of the crude oil blending process.

PubMed

Rubio, José de Jesús

2016-06-01

In this paper, the recursive least square algorithm is designed for the big data learning of a feedforward neural network. The proposed method as the combination of the recursive least square and feedforward neural network obtains four advantages over the alone algorithms: it requires less number of regressors, it is fast, it has the learning ability, and it is more compact. Stability, convergence, boundedness of parameters, and local minimum avoidance of the proposed technique are guaranteed. The introduced strategy is applied for the modeling of the crude oil blending process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Speeding up local correlation methods

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

Kats, Daniel

2014-12-28

We present two techniques that can substantially speed up the local correlation methods. The first one allows one to avoid the expensive transformation of the electron-repulsion integrals from atomic orbitals to virtual space. The second one introduces an algorithm for the residual equations in the local perturbative treatment that, in contrast to the standard scheme, does not require holding the amplitudes or residuals in memory. It is shown that even an interpreter-based implementation of the proposed algorithm in the context of local MP2 method is faster and requires less memory than the highly optimized variants of conventional algorithms.

[Treatment of metaphyseal fractures of shin bones by the method of blocking osteosynthesis].

PubMed

Neverov, V A; Khromov, A A; Cherniaev, S N; Egorov, K S; Shebarshov, A L

2008-01-01

The proposed method of reposition and polyaxial stabilization of fragments for intramedullary meallosynthesis of fractures of long tubular bones allows blocking osteosynthesis to be successfully used in treatment of complex metaphyseal fractures of shin bones. It results in strong fixation of the fragments, makes it possible to successfully eliminate residual deformities after introduction of the nail and to avoid the development of them in future under the influence of loading. The method provides early functioning of the interfacing joints, early axial loading, shorter period of disability, the absence of external immobilization.

Safety training priorities

NASA Astrophysics Data System (ADS)

Thompson, N. A.; Ruck, H. W.

1984-04-01

The Air Force is interested in identifying potentially hazardous tasks and prevention of accidents. This effort proposes four methods for determining safety training priorities for job tasks in three enlisted specialties. These methods can be used to design training aimed at avoiding loss of people, time, materials, and money associated with on-the-job accidents. Job tasks performed by airmen were measured using task and job factor ratings. Combining accident reports and job inventories, subject-matter experts identified tasks associated with accidents over a 3-year period. Applying correlational, multiple regression, and cost-benefit analysis, four methods were developed for ordering hazardous tasks to determine safety training priorities.

78 FR 35262 - Detection and Avoidance of Counterfeit Electronic Parts

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-12

... DEPARTMENT OF DEFENSE Defense Acquisition Regulations System [DFARS Case 2012-D055] Detection and Avoidance of Counterfeit Electronic Parts AGENCY: Defense Acquisition Regulations System, Department of... detection and avoidance coverage proposed to be included in the Defense Federal Acquisition Regulation...

A Robust and Fast Method for Sidescan Sonar Image Segmentation Using Nonlocal Despeckling and Active Contour Model.

PubMed

Huo, Guanying; Yang, Simon X; Li, Qingwu; Zhou, Yan

2017-04-01

Sidescan sonar image segmentation is a very important issue in underwater object detection and recognition. In this paper, a robust and fast method for sidescan sonar image segmentation is proposed, which deals with both speckle noise and intensity inhomogeneity that may cause considerable difficulties in image segmentation. The proposed method integrates the nonlocal means-based speckle filtering (NLMSF), coarse segmentation using k -means clustering, and fine segmentation using an improved region-scalable fitting (RSF) model. The NLMSF is used before the segmentation to effectively remove speckle noise while preserving meaningful details such as edges and fine features, which can make the segmentation easier and more accurate. After despeckling, a coarse segmentation is obtained by using k -means clustering, which can reduce the number of iterations. In the fine segmentation, to better deal with possible intensity inhomogeneity, an edge-driven constraint is combined with the RSF model, which can not only accelerate the convergence speed but also avoid trapping into local minima. The proposed method has been successfully applied to both noisy and inhomogeneous sonar images. Experimental and comparative results on real and synthetic sonar images demonstrate that the proposed method is robust against noise and intensity inhomogeneity, and is also fast and accurate.

Lagrangian numerical methods for ocean biogeochemical simulations

NASA Astrophysics Data System (ADS)

Paparella, Francesco; Popolizio, Marina

2018-05-01

We propose two closely-related Lagrangian numerical methods for the simulation of physical processes involving advection, reaction and diffusion. The methods are intended to be used in settings where the flow is nearly incompressible and the Péclet numbers are so high that resolving all the scales of motion is unfeasible. This is commonplace in ocean flows. Our methods consist in augmenting the method of characteristics, which is suitable for advection-reaction problems, with couplings among nearby particles, producing fluxes that mimic diffusion, or unresolved small-scale transport. The methods conserve mass, obey the maximum principle, and allow to tune the strength of the diffusive terms down to zero, while avoiding unwanted numerical dissipation effects.

Enhancement of Satellite Image Compression Using a Hybrid (DWT-DCT) Algorithm

NASA Astrophysics Data System (ADS)

Shihab, Halah Saadoon; Shafie, Suhaidi; Ramli, Abdul Rahman; Ahmad, Fauzan

2017-12-01

Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) image compression techniques have been utilized in most of the earth observation satellites launched during the last few decades. However, these techniques have some issues that should be addressed. The DWT method has proven to be more efficient than DCT for several reasons. Nevertheless, the DCT can be exploited to improve the high-resolution satellite image compression when combined with the DWT technique. Hence, a proposed hybrid (DWT-DCT) method was developed and implemented in the current work, simulating an image compression system on-board on a small remote sensing satellite, with the aim of achieving a higher compression ratio to decrease the onboard data storage and the downlink bandwidth, while avoiding further complex levels of DWT. This method also succeeded in maintaining the reconstructed satellite image quality through replacing the standard forward DWT thresholding and quantization processes with an alternative process that employed the zero-padding technique, which also helped to reduce the processing time of DWT compression. The DCT, DWT and the proposed hybrid methods were implemented individually, for comparison, on three LANDSAT 8 images, using the MATLAB software package. A comparison was also made between the proposed method and three other previously published hybrid methods. The evaluation of all the objective and subjective results indicated the feasibility of using the proposed hybrid (DWT-DCT) method to enhance the image compression process on-board satellites.

Parameter retrieval of chiral metamaterials based on the state-space approach.

PubMed

Zarifi, Davoud; Soleimani, Mohammad; Abdolali, Ali

2013-08-01

This paper deals with the introduction of an approach for the electromagnetic characterization of homogeneous chiral layers. The proposed method is based on the state-space approach and properties of a 4×4 state transition matrix. Based on this, first, the forward problem analysis through the state-space method is reviewed and properties of the state transition matrix of a chiral layer are presented and proved as two theorems. The formulation of a proposed electromagnetic characterization method is then presented. In this method, scattering data for a linearly polarized plane wave incident normally on a homogeneous chiral slab are combined with properties of a state transition matrix and provide a powerful characterization method. The main difference with respect to other well-established retrieval procedures based on the use of the scattering parameters relies on the direct computation of the transfer matrix of the slab as opposed to the conventional calculation of the propagation constant and impedance of the modes supported by the medium. The proposed approach allows avoiding nonlinearity of the problem but requires getting enough equations to fulfill the task which was provided by considering some properties of the state transition matrix. To demonstrate the applicability and validity of the method, the constitutive parameters of two well-known dispersive chiral metamaterial structures at microwave frequencies are retrieved. The results show that the proposed method is robust and reliable.

Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems

PubMed Central

Zainudin, Suhaila; Arif, Shereena M.

2017-01-01

Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5. PMID:28250767

Sector-Based Detection for Hands-Free Speech Enhancement in Cars

NASA Astrophysics Data System (ADS)

Lathoud, Guillaume; Bourgeois, Julien; Freudenberger, Jürgen

2006-12-01

Adaptation control of beamforming interference cancellation techniques is investigated for in-car speech acquisition. Two efficient adaptation control methods are proposed that avoid target cancellation. The "implicit" method varies the step-size continuously, based on the filtered output signal. The "explicit" method decides in a binary manner whether to adapt or not, based on a novel estimate of target and interference energies. It estimates the average delay-sum power within a volume of space, for the same cost as the classical delay-sum. Experiments on real in-car data validate both methods, including a case with[InlineEquation not available: see fulltext.] km/h background road noise.

Traffic sign classification with dataset augmentation and convolutional neural network

NASA Astrophysics Data System (ADS)

Tang, Qing; Kurnianggoro, Laksono; Jo, Kang-Hyun

2018-04-01

This paper presents a method for traffic sign classification using a convolutional neural network (CNN). In this method, firstly we transfer a color image into grayscale, and then normalize it in the range (-1,1) as the preprocessing step. To increase robustness of classification model, we apply a dataset augmentation algorithm and create new images to train the model. To avoid overfitting, we utilize a dropout module before the last fully connection layer. To assess the performance of the proposed method, the German traffic sign recognition benchmark (GTSRB) dataset is utilized. Experimental results show that the method is effective in classifying traffic signs.

Incest avoidance: oedipal and preoedipal, natural and cultural.

PubMed

Paul, Robert A

2010-12-01

Why do most people experience a subjective aversion to the idea of incestuous sexual relations? To help answer this question, recent strands of thinking in both cultural and evolutionary anthropology are considered together with psychoanalytic theories regarding incest avoidance. Coevolutionary theories that propose ways to think about genetic and cultural inheritance as partially independent of each other, evolutionary arguments about the reproductive advantages of incest avoidance, structuralist theory arguing for a kind of incest aversion unrelated to any possible Darwinian selective advantage, and other trends in biosocial research into the origins of the incest avoidance are considered. Finally, a synthesis is proposed that seeks to expand our understanding of the oedipal and preoedipal dynamics of the aversion as these are conceptualized in psychoanalytic theory.

Optimal consensus algorithm integrated with obstacle avoidance

NASA Astrophysics Data System (ADS)

Wang, Jianan; Xin, Ming

2013-01-01

This article proposes a new consensus algorithm for the networked single-integrator systems in an obstacle-laden environment. A novel optimal control approach is utilised to achieve not only multi-agent consensus but also obstacle avoidance capability with minimised control efforts. Three cost functional components are defined to fulfil the respective tasks. In particular, an innovative nonquadratic obstacle avoidance cost function is constructed from an inverse optimal control perspective. The other two components are designed to ensure consensus and constrain the control effort. The asymptotic stability and optimality are proven. In addition, the distributed and analytical optimal control law only requires local information based on the communication topology to guarantee the proposed behaviours, rather than all agents' information. The consensus and obstacle avoidance are validated through simulations.

Proposed modification to avoidance test with Eisenia fetida to assess metal toxicity in agricultural soils affected by mining activities.

PubMed

Delgadillo, Víctor; Verdejo, José; Mondaca, Pedro; Verdugo, Gabriela; Gaete, Hernán; Hodson, Mark E; Neaman, Alexander

2017-06-01

Use of avoidance tests is a quick and cost-effective method of assessing contaminants in soils. One option for assessing earthworm avoidance behavior is a two-section test, which consists of earthworms being given the choice to move between a test soil and a control substrate. For ecological relevance, tested soils should be field-contaminated soils. For practical reasons, artificial soils are commonly used as the control substrate. Interpretation of the test results compromised when the test soil and the artificial substrate differ in their physico-chemical properties other than just contaminants. In this study we identified the physico-chemical properties that influence avoidance response and evaluated the usefulness of adjusting these in the control substrate in order to isolate metal-driven avoidance of field soils by earthworms. A standardized two-section avoidance test with Eisenia fetida was performed on 52 uncontaminated and contaminated (Cu >155mgkg -1 , As >19mgkg -1 ) agricultural soils from the Aconcagua River basin and the Puchuncaví Valley in Chile. Regression analysis indicated that the avoidance response was determined by soil organic matter (OM), electrical conductivity (EC) and total soil Cu. Organic matter content of the artificial substrate was altered by peat additions and EC by NaCl so that these properties matched those of the field soils. The resultant EC 80 for avoidance (indicative of soils of "limited habitat") was 433mg Cu kg -1 (339 - 528mgkg -1 95% confidence intervals). The earthworm avoidance test can be used to assess metal toxicity in field-contaminated soils by adjusting physico-chemical properties (OM and EC) of the artificial control substrate in order to mimic those of the field-collected soil. Copyright © 2017 Elsevier Inc. All rights reserved.

Neuroscience and approach/avoidance personality traits: a two stage (valuation-motivation) approach.

PubMed

Corr, Philip J; McNaughton, Neil

2012-11-01

Many personality theories link specific traits to the sensitivities of the neural systems that control approach and avoidance. But there is no consensus on the nature of these systems. Here we combine recent advances in economics and neuroscience to provide a more solid foundation for a neuroscience of approach/avoidance personality. We propose a two-stage integration of valuation (loss/gain) sensitivities with motivational (approach/avoidance/conflict) sensitivities. Our key conclusions are: (1) that valuation of appetitive and aversive events (e.g. gain and loss as studied by behavioural economists) is an independent perceptual input stage--with the economic phenomenon of loss aversion resulting from greater negative valuation sensitivity compared to positive valuation sensitivity; (2) that valuation of an appetitive stimulus then interacts with a contingency of presentation or omission to generate a motivational 'attractor' or 'repulsor', respectively (vice versa for an aversive stimulus); (3) the resultant behavioural tendencies to approach or avoid have distinct sensitivities to those of the valuation systems; (4) while attractors and repulsors can reinforce new responses they also, more usually, elicit innate or previously conditioned responses and so the perception/valuation-motivation/action complex is best characterised as acting as a 'reinforcer' not a 'reinforcement'; and (5) approach-avoidance conflict must be viewed as activating a third motivation system that is distinct from the basic approach and avoidance systems. We provide examples of methods of assessing each of the constructs within approach-avoidance theories and of linking these constructs to personality measures. We sketch a preliminary five-element reinforcer sensitivity theory (RST-5) as a first step in the integration of existing specific approach-avoidance theories into a coherent neuroscience of personality. Copyright © 2012 Elsevier Ltd. All rights reserved.

A new method to synthesize complicated multi-branched carbon nanotubes with controlled architecture and composition.

PubMed

Wei, Dacheng; Liu, Yunqi; Cao, Lingchao; Fu, Lei; Li, Xianglong; Wang, Yu; Yu, Gui; Zhu, Daoben

2006-02-01

Here we develop a simple method by using flow fluctuation to synthesize arrays of multi-branched carbon nanotubes (CNTs) that are far more complex than those previously reported. The architectures and compositions can be well controlled, thus avoiding any template or additive. A branching mechanism of fluctuation-promoted coalescence of catalyst particles is proposed. This finding will provide a hopeful approach to the goal of CNT-based integrated circuits and be valuable for applying branched junctions in nanoelectronics and producing branched junctions of other materials.

Fuzzy Inference Based Obstacle Avoidance Control of Electric Powered Wheelchair Considering Driving Risk

NASA Astrophysics Data System (ADS)

Kiso, Atsushi; Murakami, Hiroki; Seki, Hirokazu

This paper describes a novel obstacle avoidance control scheme of electric powered wheelchairs for realizing the safe driving in various environments. The “electric powered wheelchair” which generates the driving force by electric motors is expected to be widely used as a mobility support system for elderly people and disabled people; however, the driving performance must be further improved because the number of driving accidents caused by elderly operator's narrow sight and joystick operation errors is increasing. This paper proposes a novel obstacle avoidance control scheme based on fuzzy algorithm to prevent driving accidents. The proposed control system determines the driving direction by fuzzy algorithm based on the information of the joystick operation and distance to obstacles measured by ultrasonic sensors. Fuzzy rules to determine the driving direction are designed surely to avoid passers-by and walls considering the human's intent and driving environments. Some driving experiments on the practical situations show the effectiveness of the proposed control system.

PSD Camera Based Position and Posture Control of Redundant Robot Considering Contact Motion

NASA Astrophysics Data System (ADS)

Oda, Naoki; Kotani, Kentaro

The paper describes a position and posture controller design based on the absolute position by external PSD vision sensor for redundant robot manipulator. The redundancy enables a potential capability to avoid obstacle while continuing given end-effector jobs under contact with middle link of manipulator. Under contact motion, the deformation due to joint torsion obtained by comparing internal and external position sensor, is actively suppressed by internal/external position hybrid controller. The selection matrix of hybrid loop is given by the function of the deformation. And the detected deformation is also utilized in the compliant motion controller for passive obstacle avoidance. The validity of the proposed method is verified by several experimental results of 3link planar redundant manipulator.

The Selection and Placement Method of Materialized Views on Big Data Platform of Equipment Condition Assessment

NASA Astrophysics Data System (ADS)

Ma, Yan; Yao, Jinxia; Gu, Chao; Chen, Yufeng; Yang, Yi; Zou, Lida

2017-05-01

With the formation of electric big data environment, more and more big data analyses emerge. In the complicated data analysis on equipment condition assessment, there exist many join operations, which are time-consuming. In order to save time, the approach of materialized view is usually used. It places part of common and critical join results on external storage and avoids the frequent join operation. In the paper we propose the methods of selecting and placing materialized views to reduce the query time of electric transmission and transformation equipment, and make the profits of service providers maximal. In selection method we design a computation way for the value of non-leaf node based on MVPP structure chart. In placement method we use relevance weights to place the selected materialized views, which help reduce the network transmission time. Our experiments show that the proposed selection and placement methods have a high throughput and good optimization ability of query time for electric transmission and transformation equipment.

75 FR 39541 - Agency Information Collection Activities; Proposed Collection; Comment Request; “The Dairy...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-09

...'s Role in Residue Avoidance Survey'' AGENCY: Food and Drug Administration, HHS. ACTION: Notice... solicits comments on FDA's ``The Dairy Practitioner's Role in Residue Avoidance Survey.'' DATES: Submit... of information technology. ``The Dairy Practitioner's Role in Residue Avoidance Survey'' (OMB Control...

Planning and Assessing Stability Operations: A Proposed Value Focus Thinking Approach

DTIC Science & Technology

2007-03-01

to avoid double -counting of possible consequences. 8... Taxes War Profiteering Arms Smuggling Grey Economy Avoidance of taxes Violation of regulations Smuggling Evasion of economic embargoes... Taxes War Profiteering Arms Smuggling Grey Economy Avoidance of taxes Violation of regulations Smuggling Evasion of economic embargoes

Information Seeking and Avoiding in Health Contexts.

ERIC Educational Resources Information Center

Brashers, Dale E.; Goldsmith, Daena J.; Hsieh, Elaine

2002-01-01

Suggests a research agenda that would provide a basis for proposing normative recommendations for information management in health contexts. Overviews information seeking and avoiding processes. Describes challenges and dilemmas faced by those who seek, avoid, and provide information. Offers research questions derived from a normative agenda for…

ADVANCED SURVEILLANCE OF ENVIROMENTAL RADIATION IN AUTOMATIC NETWORKS.

PubMed

Benito, G; Sáez, J C; Blázquez, J B; Quiñones, J

2018-06-01

The objective of this study is the verification of the operation of a radiation monitoring network conformed by several sensors. The malfunction of a surveillance network has security and economic consequences, which derive from its maintenance and could be avoided with an early detection. The proposed method is based on a kind of multivariate distance, and the verification for the methodology has been tested at CIEMAT's local radiological early warning network.

High-order conservative finite difference GLM-MHD schemes for cell-centered MHD

NASA Astrophysics Data System (ADS)

Mignone, Andrea; Tzeferacos, Petros; Bodo, Gianluigi

2010-08-01

We present and compare third- as well as fifth-order accurate finite difference schemes for the numerical solution of the compressible ideal MHD equations in multiple spatial dimensions. The selected methods lean on four different reconstruction techniques based on recently improved versions of the weighted essentially non-oscillatory (WENO) schemes, monotonicity preserving (MP) schemes as well as slope-limited polynomial reconstruction. The proposed numerical methods are highly accurate in smooth regions of the flow, avoid loss of accuracy in proximity of smooth extrema and provide sharp non-oscillatory transitions at discontinuities. We suggest a numerical formulation based on a cell-centered approach where all of the primary flow variables are discretized at the zone center. The divergence-free condition is enforced by augmenting the MHD equations with a generalized Lagrange multiplier yielding a mixed hyperbolic/parabolic correction, as in Dedner et al. [J. Comput. Phys. 175 (2002) 645-673]. The resulting family of schemes is robust, cost-effective and straightforward to implement. Compared to previous existing approaches, it completely avoids the CPU intensive workload associated with an elliptic divergence cleaning step and the additional complexities required by staggered mesh algorithms. Extensive numerical testing demonstrate the robustness and reliability of the proposed framework for computations involving both smooth and discontinuous features.

The Co-simulation of Humanoid Robot Based on Solidworks, ADAMS and Simulink

NASA Astrophysics Data System (ADS)

Song, Dalei; Zheng, Lidan; Wang, Li; Qi, Weiwei; Li, Yanli

A simulation method of adaptive controller is proposed for the humanoid robot system based on co-simulation of Solidworks, ADAMS and Simulink. A complex mathematical modeling process is avoided by this method, and the real time dynamic simulating function of Simulink would be exerted adequately. This method could be generalized to other complicated control system. This method is adopted to build and analyse the model of humanoid robot. The trajectory tracking and adaptive controller design also proceed based on it. The effect of trajectory tracking is evaluated by fitting-curve theory of least squares method. The anti-interference capability of the robot is improved a lot through comparative analysis.

A weakly-compressible Cartesian grid approach for hydrodynamic flows

NASA Astrophysics Data System (ADS)

Bigay, P.; Oger, G.; Guilcher, P.-M.; Le Touzé, D.

2017-11-01

The present article aims at proposing an original strategy to solve hydrodynamic flows. In introduction, the motivations for this strategy are developed. It aims at modeling viscous and turbulent flows including complex moving geometries, while avoiding meshing constraints. The proposed approach relies on a weakly-compressible formulation of the Navier-Stokes equations. Unlike most hydrodynamic CFD (Computational Fluid Dynamics) solvers usually based on implicit incompressible formulations, a fully-explicit temporal scheme is used. A purely Cartesian grid is adopted for numerical accuracy and algorithmic simplicity purposes. This characteristic allows an easy use of Adaptive Mesh Refinement (AMR) methods embedded within a massively parallel framework. Geometries are automatically immersed within the Cartesian grid with an AMR compatible treatment. The method proposed uses an Immersed Boundary Method (IBM) adapted to the weakly-compressible formalism and imposed smoothly through a regularization function, which stands as another originality of this work. All these features have been implemented within an in-house solver based on this WCCH (Weakly-Compressible Cartesian Hydrodynamic) method which meets the above requirements whilst allowing the use of high-order (> 3) spatial schemes rarely used in existing hydrodynamic solvers. The details of this WCCH method are presented and validated in this article.

Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor

PubMed Central

Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

2016-01-01

Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation. PMID:27649190

Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor.

PubMed

Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

2016-09-15

Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation.

Time-Domain Receiver Function Deconvolution using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Moreira, L. P.

2017-12-01

Receiver Functions (RF) are well know method for crust modelling using passive seismological signals. Many different techniques were developed to calculate the RF traces, applying the deconvolution calculation to radial and vertical seismogram components. A popular method used a spectral division of both components, which requires human intervention to apply the Water Level procedure to avoid instabilities from division by small numbers. One of most used method is an iterative procedure to estimate the RF peaks and applying the convolution with vertical component seismogram, comparing the result with the radial component. This method is suitable for automatic processing, however several RF traces are invalid due to peak estimation failure.In this work it is proposed a deconvolution algorithm using Genetic Algorithm (GA) to estimate the RF peaks. This method is entirely processed in the time domain, avoiding the time-to-frequency calculations (and vice-versa), and totally suitable for automatic processing. Estimated peaks can be used to generate RF traces in a seismogram format for visualization. The RF trace quality is similar for high magnitude events, although there are less failures for RF calculation of smaller events, increasing the overall performance for high number of events per station.

Optical flow estimation on image sequences with differently exposed frames

NASA Astrophysics Data System (ADS)

Bengtsson, Tomas; McKelvey, Tomas; Lindström, Konstantin

2015-09-01

Optical flow (OF) methods are used to estimate dense motion information between consecutive frames in image sequences. In addition to the specific OF estimation method itself, the quality of the input image sequence is of crucial importance to the quality of the resulting flow estimates. For instance, lack of texture in image frames caused by saturation of the camera sensor during exposure can significantly deteriorate the performance. An approach to avoid this negative effect is to use different camera settings when capturing the individual frames. We provide a framework for OF estimation on such sequences that contain differently exposed frames. Information from multiple frames are combined into a total cost functional such that the lack of an active data term for saturated image areas is avoided. Experimental results demonstrate that using alternate camera settings to capture the full dynamic range of an underlying scene can clearly improve the quality of flow estimates. When saturation of image data is significant, the proposed methods show superior performance in terms of lower endpoint errors of the flow vectors compared to a set of baseline methods. Furthermore, we provide some qualitative examples of how and when our method should be used.

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method

PubMed Central

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-01-01

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis. PMID:28029121

Effect of heteroscedasticity treatment in residual error models on model calibration and prediction uncertainty estimation

NASA Astrophysics Data System (ADS)

Sun, Ruochen; Yuan, Huiling; Liu, Xiaoli

2017-11-01

The heteroscedasticity treatment in residual error models directly impacts the model calibration and prediction uncertainty estimation. This study compares three methods to deal with the heteroscedasticity, including the explicit linear modeling (LM) method and nonlinear modeling (NL) method using hyperbolic tangent function, as well as the implicit Box-Cox transformation (BC). Then a combined approach (CA) combining the advantages of both LM and BC methods has been proposed. In conjunction with the first order autoregressive model and the skew exponential power (SEP) distribution, four residual error models are generated, namely LM-SEP, NL-SEP, BC-SEP and CA-SEP, and their corresponding likelihood functions are applied to the Variable Infiltration Capacity (VIC) hydrologic model over the Huaihe River basin, China. Results show that the LM-SEP yields the poorest streamflow predictions with the widest uncertainty band and unrealistic negative flows. The NL and BC methods can better deal with the heteroscedasticity and hence their corresponding predictive performances are improved, yet the negative flows cannot be avoided. The CA-SEP produces the most accurate predictions with the highest reliability and effectively avoids the negative flows, because the CA approach is capable of addressing the complicated heteroscedasticity over the study basin.

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method.

PubMed

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-12-24

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis.

An object tracking method based on guided filter for night fusion image

NASA Astrophysics Data System (ADS)

Qian, Xiaoyan; Wang, Yuedong; Han, Lei

2016-01-01

Online object tracking is a challenging problem as it entails learning an effective model to account for appearance change caused by intrinsic and extrinsic factors. In this paper, we propose a novel online object tracking with guided image filter for accurate and robust night fusion image tracking. Firstly, frame difference is applied to produce the coarse target, which helps to generate observation models. Under the restriction of these models and local source image, guided filter generates sufficient and accurate foreground target. Then accurate boundaries of the target can be extracted from detection results. Finally timely updating for observation models help to avoid tracking shift. Both qualitative and quantitative evaluations on challenging image sequences demonstrate that the proposed tracking algorithm performs favorably against several state-of-art methods.

Sub-aperture switching based ptychographic iterative engine (sasPIE) method for quantitative imaging

NASA Astrophysics Data System (ADS)

Sun, Aihui; Kong, Yan; Jiang, Zhilong; Yu, Wei; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

2018-03-01

Though ptychographic iterative engine (PIE) has been widely adopted in the quantitative micro-imaging with various illuminations as visible light, X-ray and electron beam, the mechanical inaccuracy in the raster scanning of the sample relative to the illumination always degrades the reconstruction quality seriously and makes the resolution reached much lower than that determined by the numerical aperture of the optical system. To overcome this disadvantage, the sub-aperture switching based PIE method is proposed: the mechanical scanning in the common PIE is replaced by the sub-aperture switching, and the reconstruction error related to the positioning inaccuracy is completely avoided. The proposed technique remarkably improves the reconstruction quality, reduces the complexity of the experimental setup and fundamentally accelerates the data acquisition and reconstruction.

Glioma grading using cell nuclei morphologic features in digital pathology images

NASA Astrophysics Data System (ADS)

Reza, Syed M. S.; Iftekharuddin, Khan M.

2016-03-01

This work proposes a computationally efficient cell nuclei morphologic feature analysis technique to characterize the brain gliomas in tissue slide images. In this work, our contributions are two-fold: 1) obtain an optimized cell nuclei segmentation method based on the pros and cons of the existing techniques in literature, 2) extract representative features by k-mean clustering of nuclei morphologic features to include area, perimeter, eccentricity, and major axis length. This clustering based representative feature extraction avoids shortcomings of extensive tile [1] [2] and nuclear score [3] based methods for brain glioma grading in pathology images. Multilayer perceptron (MLP) is used to classify extracted features into two tumor types: glioblastoma multiforme (GBM) and low grade glioma (LGG). Quantitative scores such as precision, recall, and accuracy are obtained using 66 clinical patients' images from The Cancer Genome Atlas (TCGA) [4] dataset. On an average ~94% accuracy from 10 fold crossvalidation confirms the efficacy of the proposed method.

A Noise-Filtered Under-Sampling Scheme for Imbalanced Classification.

PubMed

Kang, Qi; Chen, XiaoShuang; Li, SiSi; Zhou, MengChu

2017-12-01

Under-sampling is a popular data preprocessing method in dealing with class imbalance problems, with the purposes of balancing datasets to achieve a high classification rate and avoiding the bias toward majority class examples. It always uses full minority data in a training dataset. However, some noisy minority examples may reduce the performance of classifiers. In this paper, a new under-sampling scheme is proposed by incorporating a noise filter before executing resampling. In order to verify the efficiency, this scheme is implemented based on four popular under-sampling methods, i.e., Undersampling + Adaboost, RUSBoost, UnderBagging, and EasyEnsemble through benchmarks and significance analysis. Furthermore, this paper also summarizes the relationship between algorithm performance and imbalanced ratio. Experimental results indicate that the proposed scheme can improve the original undersampling-based methods with significance in terms of three popular metrics for imbalanced classification, i.e., the area under the curve, -measure, and -mean.

Measurement of two-photon-absorption spectra through nonlinear fluorescence produced by a line-shaped excitation beam.

PubMed

Hasani, E; Parravicini, J; Tartara, L; Tomaselli, A; Tomassini, D

2018-05-01

We propose an innovative experimental approach to estimate the two-photon absorption (TPA) spectrum of a fluorescent material. Our method develops the standard indirect fluorescence-based method for the TPA measurement by employing a line-shaped excitation beam, generating a line-shaped fluorescence emission. Such a configuration, which requires a relatively high amount of optical power, permits to have a greatly increased fluorescence signal, thus avoiding the photon counterdetection devices usually used in these measurements, and allowing to employ detectors such as charge-coupled device (CCD) cameras. The method is finally tested on a fluorescent isothiocyanate sample, whose TPA spectrum, which is measured with the proposed technique, is compared with the TPA spectra reported in the literature, confirming the validity of our experimental approach. © 2018 The Authors Journal of Microscopy © 2018 Royal Microscopical Society.

Robust bidirectional links for photonic quantum networks

PubMed Central

Xu, Jin-Shi; Yung, Man-Hong; Xu, Xiao-Ye; Tang, Jian-Shun; Li, Chuan-Feng; Guo, Guang-Can

2016-01-01

Optical fibers are widely used as one of the main tools for transmitting not only classical but also quantum information. We propose and report an experimental realization of a promising method for creating robust bidirectional quantum communication links through paired optical polarization-maintaining fibers. Many limitations of existing protocols can be avoided with the proposed method. In particular, the path and polarization degrees of freedom are combined to deterministically create a photonic decoherence-free subspace without the need for any ancillary photon. This method is input state–independent, robust against dephasing noise, postselection-free, and applicable bidirectionally. To rigorously quantify the amount of quantum information transferred, the optical fibers are analyzed with the tools developed in quantum communication theory. These results not only suggest a practical means for protecting quantum information sent through optical quantum networks but also potentially provide a new physical platform for enriching the structure of the quantum communication theory. PMID:26824069

Estimation of uncertainty in tracer gas measurement of air change rates.

PubMed

Iizuka, Atsushi; Okuizumi, Yumiko; Yanagisawa, Yukio

2010-12-01

Simple and economical measurement of air change rates can be achieved with a passive-type tracer gas doser and sampler. However, this is made more complex by the fact many buildings are not a single fully mixed zone. This means many measurements are required to obtain information on ventilation conditions. In this study, we evaluated the uncertainty of tracer gas measurement of air change rate in n completely mixed zones. A single measurement with one tracer gas could be used to simply estimate the air change rate when n = 2. Accurate air change rates could not be obtained for n ≥ 2 due to a lack of information. However, the proposed method can be used to estimate an air change rate with an accuracy of <33%. Using this method, overestimation of air change rate can be avoided. The proposed estimation method will be useful in practical ventilation measurements.

Classical-processing and quantum-processing signal separation methods for qubit uncoupling

NASA Astrophysics Data System (ADS)

Deville, Yannick; Deville, Alain

2012-12-01

The Blind Source Separation problem consists in estimating a set of unknown source signals from their measured combinations. It was only investigated in a non-quantum framework up to now. We propose its first quantum extensions. We thus introduce the Quantum Source Separation field, investigating both its blind and non-blind configurations. More precisely, we show how to retrieve individual quantum bits (qubits) only from the global state resulting from their undesired coupling. We consider cylindrical-symmetry Heisenberg coupling, which e.g. occurs when two electron spins interact through exchange. We first propose several qubit uncoupling methods which typically measure repeatedly the coupled quantum states resulting from individual qubits preparations, and which then statistically process the classical data provided by these measurements. Numerical tests prove the effectiveness of these methods. We then derive a combination of quantum gates for performing qubit uncoupling, thus avoiding repeated qubit preparations and irreversible measurements.

Modified reactive tabu search for the symmetric traveling salesman problems

NASA Astrophysics Data System (ADS)

Lim, Yai-Fung; Hong, Pei-Yee; Ramli, Razamin; Khalid, Ruzelan

2013-09-01

Reactive tabu search (RTS) is an improved method of tabu search (TS) and it dynamically adjusts tabu list size based on how the search is performed. RTS can avoid disadvantage of TS which is in the parameter tuning in tabu list size. In this paper, we proposed a modified RTS approach for solving symmetric traveling salesman problems (TSP). The tabu list size of the proposed algorithm depends on the number of iterations when the solutions do not override the aspiration level to achieve a good balance between diversification and intensification. The proposed algorithm was tested on seven chosen benchmarked problems of symmetric TSP. The performance of the proposed algorithm is compared with that of the TS by using empirical testing, benchmark solution and simple probabilistic analysis in order to validate the quality of solution. The computational results and comparisons show that the proposed algorithm provides a better quality solution than that of the TS.

Mission-based guidance system design for autonomous UAVs

NASA Astrophysics Data System (ADS)

Moon, Jongki

The advantages of UAVs in the aviation arena have led to extensive research activities on autonomous technology of UAVs to achieve specific mission objectives. This thesis mainly focuses on the development of a mission-based guidance system. Among various missions expected for future needs, autonomous formation flight (AFF) and obstacle avoidance within safe operation limits are investigated. In the design of an adaptive guidance system for AFF, the leader information except position is assumed to be unknown to a follower. Thus, the only measured information related to the leader is the line-of-sight (LOS) range and angle. Adding an adaptive element with neural networks into the guidance system provides a capability to effectively handle leader's velocity changes. Therefore, this method can be applied to the AFF control systems that use a passive sensing method. In this thesis, an adaptive velocity command guidance system and an adaptive acceleration command guidance system are developed and presented. Since relative degrees of the LOS range and angle are different depending on the outputs from the guidance system, the architecture of the guidance system changes accordingly. Simulations and flight tests are performed using the Georgia Tech UAV helicopter, the GTMax, to evaluate the proposed guidance systems. The simulation results show that the neural network (NN) based adaptive element can improve the tracking performance by effectively compensating for the effect of unknown dynamics. It has also been shown that the combination of an adaptive velocity command guidance system and the existing GTMax autopilot controller performs better than the combination of an adaptive acceleration command guidance system and the GTMax autopilot controller. The successful flight evaluation using an adaptive velocity command guidance system clearly shows that the adaptive guidance control system is a promising solution for autonomous formation flight of UAVs. In addition, an integrated approach is proposed to resolve the conflict between aggressive maneuvering needed for obstacle avoidance and the constrained maneuvering needed for envelope protection. A time-optimal problem with obstacle and envelope constraints is used for an integrated approach for obstacle avoidance and envelope protection. The Nonlinear trajectory generator (NTG) is used as a real-time optimization solver. The computational complexity arising from the obstacle constraints is reduced by converting the obstacle constraints into a safe waypoint constraint along with an implicit requirement that the horizontal velocity during the avoidance maneuver must be nonnegative. The issue of when to initiate a time-optimal avoidance maneuver is addressed by including a requirement that the vehicle must maintain its original flight path to the maximum extent possible. The simulation evaluations are preformed for the nominal case, the unsafe avoidance solution case, the multiple safe waypoint case, and the unidentified obstacle size case. Artificial values for the load factor limit and the longitudinal flap angle limit are imposed as safe operational boundaries. Also, simulation results for different limit values and different initial flight speed are compared. Simulation results using a nonlinear model of a rotary wing UAV demonstrate the feasibility of the proposed approach for obstacle avoidance with envelope protection.

Efficient Nondomination Level Update Method for Steady-State Evolutionary Multiobjective Optimization.

PubMed

Li, Ke; Deb, Kalyanmoy; Zhang, Qingfu; Zhang, Qiang

2017-09-01

Nondominated sorting (NDS), which divides a population into several nondomination levels (NDLs), is a basic step in many evolutionary multiobjective optimization (EMO) algorithms. It has been widely studied in a generational evolution model, where the environmental selection is performed after generating a whole population of offspring. However, in a steady-state evolution model, where a population is updated right after the generation of a new candidate, the NDS can be extremely time consuming. This is especially severe when the number of objectives and population size become large. In this paper, we propose an efficient NDL update method to reduce the cost for maintaining the NDL structure in steady-state EMO. Instead of performing the NDS from scratch, our method only updates the NDLs of a limited number of solutions by extracting the knowledge from the current NDL structure. Notice that our NDL update method is performed twice at each iteration. One is after the reproduction, the other is after the environmental selection. Extensive experiments fully demonstrate that, comparing to the other five state-of-the-art NDS methods, our proposed method avoids a significant amount of unnecessary comparisons, not only in the synthetic data sets, but also in some real optimization scenarios. Last but not least, we find that our proposed method is also useful for the generational evolution model.

A Predictive Model for Toxicity Effects Assessment of Biotransformed Hepatic Drugs Using Iterative Sampling Method.

PubMed

Tharwat, Alaa; Moemen, Yasmine S; Hassanien, Aboul Ella

2016-12-09

Measuring toxicity is one of the main steps in drug development. Hence, there is a high demand for computational models to predict the toxicity effects of the potential drugs. In this study, we used a dataset, which consists of four toxicity effects:mutagenic, tumorigenic, irritant and reproductive effects. The proposed model consists of three phases. In the first phase, rough set-based methods are used to select the most discriminative features for reducing the classification time and improving the classification performance. Due to the imbalanced class distribution, in the second phase, different sampling methods such as Random Under-Sampling, Random Over-Sampling and Synthetic Minority Oversampling Technique are used to solve the problem of imbalanced datasets. ITerative Sampling (ITS) method is proposed to avoid the limitations of those methods. ITS method has two steps. The first step (sampling step) iteratively modifies the prior distribution of the minority and majority classes. In the second step, a data cleaning method is used to remove the overlapping that is produced from the first step. In the third phase, Bagging classifier is used to classify an unknown drug into toxic or non-toxic. The experimental results proved that the proposed model performed well in classifying the unknown samples according to all toxic effects in the imbalanced datasets.

Determination of trace nickel in hydrogenated cottonseed oil by electrothermal atomic absorption spectrometry after microwave-assisted digestion.

PubMed

Zhang, Gai

2012-01-01

Microwave digestion of hydrogenated cottonseed oil prior to trace nickel determination by electrothermal atomic absorption spectrometry (ETAAS) is proposed here for the first time. Currently, the methods outlined in U.S. Pharmacopeia 28 (USP28) or British Pharmacopeia (BP2003) are recommended as the official methods for analyzing nickel in hydrogenated cottonseed oil. With these methods the samples may be pre-treated by a silica or a platinum crucible. However, the samples were easily tarnished during sample pretreatment when using a silica crucible. In contrast, when using a platinum crucible, hydrogenated cottonseed oil acting as a reducing material may react with the platinum and destroy the crucible. The proposed microwave-assisted digestion avoided tarnishing of sample in the process of sample pretreatment and also reduced the cycle of analysis. The programs of microwave digestion and the parameters of ETAAS were optimized. The accuracy of the proposed method was investigated by analyzing real samples. The results were compared with the ones by pressurized-PTFE-bomb acid digestion and ones obtained by the U.S. Pharmacopeia 28 (USP28) method. The new method involves a relatively rapid matrix destruction technique compared with other present methods for the quantification of metals in oil. © 2011 Institute of Food Technologists®

Motion Planning of Two Stacker Cranes in a Large-Scale Automated Storage/Retrieval System

NASA Astrophysics Data System (ADS)

Kung, Yiheng; Kobayashi, Yoshimasa; Higashi, Toshimitsu; Ota, Jun

We propose a method for reducing the computational time of motion planning for stacker cranes. Most automated storage/retrieval systems (AS/RSs) are only equipped with one stacker crane. However, this is logistically challenging, and greater work efficiency in warehouses, such as those using two stacker cranes, is required. In this paper, a warehouse with two stacker cranes working simultaneously is proposed. Unlike warehouses with only one crane, trajectory planning in those with two cranes is very difficult. Since there are two cranes working together, a proper trajectory must be considered to avoid collision. However, verifying collisions is complicated and requires a considerable amount of computational time. As transport work in AS/RSs occurs randomly, motion planning cannot be conducted in advance. Planning an appropriate trajectory within a restricted duration would be a difficult task. We thereby address the current problem of motion planning requiring extensive calculation time. As a solution, we propose a “free-step” to simplify the procedure of collision verification and reduce the computational time. On the other hand, we proposed a method to reschedule the order of collision verification in order to find an appropriate trajectory in less time. By the proposed method, we reduce the calculation time to less than 1/300 of that achieved in former research.

Structured Kernel Subspace Learning for Autonomous Robot Navigation.

PubMed

Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

2018-02-14

This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

Hypnosis control based on the minimum concentration of anesthetic drug for maintaining appropriate hypnosis.

PubMed

Furutani, Eiko; Nishigaki, Yuki; Kanda, Chiaki; Takeda, Toshihiro; Shirakami, Gotaro

2013-01-01

This paper proposes a novel hypnosis control method using Auditory Evoked Potential Index (aepEX) as a hypnosis index. In order to avoid side effects of an anesthetic drug, it is desirable to reduce the amount of an anesthetic drug during surgery. For this purpose many studies of hypnosis control systems have been done. Most of them use Bispectral Index (BIS), another hypnosis index, but it has problems of dependence on anesthetic drugs and nonsmooth change near some particular values. On the other hand, aepEX has an ability of clear distinction between patient consciousness and unconsciousness and independence of anesthetic drugs. The control method proposed in this paper consists of two elements: estimating the minimum effect-site concentration for maintaining appropriate hypnosis and adjusting infusion rate of an anesthetic drug, propofol, using model predictive control. The minimum effect-site concentration is estimated utilizing the property of aepEX pharmacodynamics. The infusion rate of propofol is adjusted so that effect-site concentration of propofol may be kept near and always above the minimum effect-site concentration. Simulation results of hypnosis control using the proposed method show that the minimum concentration can be estimated appropriately and that the proposed control method can maintain hypnosis adequately and reduce the total infusion amount of propofol.

An Approach to Evaluate Blurriness in Retinal Images with Vitreous Opacity for Cataract Diagnosis

PubMed Central

Xu, Liang

2017-01-01

Cataract is one of the leading causes of blindness in the world's population. A method to evaluate blurriness for cataract diagnosis in retinal images with vitreous opacity is proposed in this paper. Three types of features are extracted, which include pixel number of visible structures, mean contrast between vessels and background, and local standard deviation. To avoid the wrong detection of vitreous opacity as retinal structures, a morphological method is proposed to detect and remove such lesions from retinal visible structure segmentation. Based on the extracted features, a decision tree is trained to classify retinal images into five grades of blurriness. The proposed approach was tested using 1355 clinical retinal images, and the accuracies of two-class classification and five-grade grading compared with that of manual grading are 92.8% and 81.1%, respectively. The kappa value between automatic grading and manual grading is 0.74 in five-grade grading, in which both variance and P value are less than 0.001. Experimental results show that the grading difference between automatic grading and manual grading is all within 1 grade, which is much improvement compared with that of other available methods. The proposed grading method provides a universal measure of cataract severity and can facilitate the decision of cataract surgery. PMID:29065620

An analytical model to design circumferential clasps for laser-sintered removable partial dentures.

PubMed

Alsheghri, Ammar A; Alageel, Omar; Caron, Eric; Ciobanu, Ovidiu; Tamimi, Faleh; Song, Jun

2018-06-21

Clasps of removable partial dentures (RPDs) often suffer from plastic deformation and failure by fatigue; a common complication of RPDs. A new technology for processing metal frameworks for dental prostheses based on laser-sintering, which allows for precise fabrication of clasp geometry, has been recently developed. This study sought to propose a novel method for designing circumferential clasps for laser-sintered RPDs to avoid plastic deformation or fatigue failure. An analytical model for designing clasps with semicircular cross-sections was derived based on mechanics. The Euler-Bernoulli elastic curved beam theory and Castigliano's energy method were used to relate the stress and undercut with the clasp length, cross-sectional radius, alloy properties, tooth type, and retention force. Finite element analysis (FEA) was conducted on a case study and the resultant tensile stress and undercut were compared with the analytical model predictions. Pull-out experiments were conducted on laser-sintered cobalt-chromium (Co-Cr) dental prostheses to validate the analytical model results. The proposed circumferential clasp design model yields results in good agreement with FEA and experiments. The results indicate that Co-Cr circumferential clasps in molars that are 13mm long engaging undercuts of 0.25mm should have a cross-section radius of 1.2mm to provide a retention of 10N and to avoid plastic deformation or fatigue failure. However, shorter circumferential clasps such as those in premolars present high stresses and cannot avoid plastic deformation or fatigue failure. Laser-sintered Co-Cr circumferential clasps in molars are safe, whereas they are susceptible to failure in premolars. Copyright © 2018 The Academy of Dental Materials. Published by Elsevier Inc. All rights reserved.

Efficient realization of 3D joint inversion of seismic and magnetotelluric data with cross gradient structure constraint

NASA Astrophysics Data System (ADS)

Luo, H.; Zhang, H.; Gao, J.

2016-12-01

Seismic and magnetotelluric (MT) imaging methods are generally used to characterize subsurface structures at various scales. The two methods are complementary to each other and the integration of them is helpful for more reliably determining the resistivity and velocity models of the target region. Because of the difficulty in finding empirical relationship between resistivity and velocity parameters, Gallardo and Meju [2003] proposed a joint inversion method enforcing resistivity and velocity models consistent in structure, which is realized by minimizing cross gradients between two models. However, it is extremely challenging to combine two different inversion systems together along with the cross gradient constraints. For this reason, Gallardo [2007] proposed a joint inversion scheme that decouples the seismic and MT inversion systems by iteratively performing seismic and MT inversions as well as cross gradient minimization separately. This scheme avoids the complexity of combining two different systems together but it suffers the issue of balancing between data fitting and structure constraint. In this study, we have developed a new joint inversion scheme that avoids the problem encountered by the scheme of Gallardo [2007]. In the new scheme, seismic and MT inversions are still separately performed but the cross gradient minimization is also constrained by model perturbations from separate inversions. In this way, the new scheme still avoids the complexity of combining two different systems together and at the same time the balance between data fitting and structure consistency constraint can be enforced. We have tested our joint inversion algorithm for both 2D and 3D cases. Synthetic tests show that joint inversion better reconstructed the velocity and resistivity models than separate inversions. Compared to separate inversions, joint inversion can remove artifacts in the resistivity model and can improve the resolution for deeper resistivity structures. We will also show results applying the new joint seismic and MT inversion scheme to southwest China, where several MT profiles are available and earthquakes are very active.

Statistical methods to estimate treatment effects from multichannel electroencephalography (EEG) data in clinical trials.

PubMed

Ma, Junshui; Wang, Shubing; Raubertas, Richard; Svetnik, Vladimir

2010-07-15

With the increasing popularity of using electroencephalography (EEG) to reveal the treatment effect in drug development clinical trials, the vast volume and complex nature of EEG data compose an intriguing, but challenging, topic. In this paper the statistical analysis methods recommended by the EEG community, along with methods frequently used in the published literature, are first reviewed. A straightforward adjustment of the existing methods to handle multichannel EEG data is then introduced. In addition, based on the spatial smoothness property of EEG data, a new category of statistical methods is proposed. The new methods use a linear combination of low-degree spherical harmonic (SPHARM) basis functions to represent a spatially smoothed version of the EEG data on the scalp, which is close to a sphere in shape. In total, seven statistical methods, including both the existing and the newly proposed methods, are applied to two clinical datasets to compare their power to detect a drug effect. Contrary to the EEG community's recommendation, our results suggest that (1) the nonparametric method does not outperform its parametric counterpart; and (2) including baseline data in the analysis does not always improve the statistical power. In addition, our results recommend that (3) simple paired statistical tests should be avoided due to their poor power; and (4) the proposed spatially smoothed methods perform better than their unsmoothed versions. Copyright 2010 Elsevier B.V. All rights reserved.

Automatic and quantitative measurement of collagen gel contraction using model-guided segmentation

NASA Astrophysics Data System (ADS)

Chen, Hsin-Chen; Yang, Tai-Hua; Thoreson, Andrew R.; Zhao, Chunfeng; Amadio, Peter C.; Sun, Yung-Nien; Su, Fong-Chin; An, Kai-Nan

2013-08-01

Quantitative measurement of collagen gel contraction plays a critical role in the field of tissue engineering because it provides spatial-temporal assessment (e.g., changes of gel area and diameter during the contraction process) reflecting the cell behavior and tissue material properties. So far the assessment of collagen gels relies on manual segmentation, which is time-consuming and suffers from serious intra- and inter-observer variability. In this study, we propose an automatic method combining various image processing techniques to resolve these problems. The proposed method first detects the maximal feasible contraction range of circular references (e.g., culture dish) and avoids the interference of irrelevant objects in the given image. Then, a three-step color conversion strategy is applied to normalize and enhance the contrast between the gel and background. We subsequently introduce a deformable circular model which utilizes regional intensity contrast and circular shape constraint to locate the gel boundary. An adaptive weighting scheme was employed to coordinate the model behavior, so that the proposed system can overcome variations of gel boundary appearances at different contraction stages. Two measurements of collagen gels (i.e., area and diameter) can readily be obtained based on the segmentation results. Experimental results, including 120 gel images for accuracy validation, showed high agreement between the proposed method and manual segmentation with an average dice similarity coefficient larger than 0.95. The results also demonstrated obvious improvement in gel contours obtained by the proposed method over two popular, generic segmentation methods.

Sub-second thermoplastic forming of bulk metallic glasses by ultrasonic beating

PubMed Central

Ma, Jiang; Liang, Xiong; Wu, Xiaoyu; Liu, Zhiyuan; Gong, Feng

2015-01-01

The work proposed a novel thermoplastic forming approach–the ultrasonic beating forming (UBF) method for bulk metallic glasses (BMGs) in present work. The rapid forming approach can finish the thermoplastic forming of BMGs in less than one second, avoiding the time-dependent crystallization and oxidation to the most extent. Besides, the UBF is also proved to be competent in the fabrication of structures with the length scale ranging from macro scale to nano scale. Our results propose a novel route for the thermoplastic forming of BMGs and have promising applications in the rapid fabrication of macro to nano scale products and devices. PMID:26644149

Manifold structure preservative for hyperspectral target detection

NASA Astrophysics Data System (ADS)

Imani, Maryam

2018-05-01

A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.

Capitation pricing: Adjusting for prior utilization and physician discretion

PubMed Central

Anderson, Gerard F.; Cantor, Joel C.; Steinberg, Earl P.; Holloway, James

1986-01-01

As the number of Medicare beneficiaries receiving care under at-risk capitation arrangements increases, the method for setting payment rates will come under increasing scrutiny. A number of modifications to the current adjusted average per capita cost (AAPCC) methodology have been proposed, including an adjustment for prior utilization. In this article, we propose use of a utilization adjustment that includes only hospitalizations involving low or moderate physician discretion in the decision to hospitalize. This modification avoids discrimination against capitated systems that prevent certain discretionary admissions. The model also explains more of the variance in per capita expenditures than does the current AAPCC. PMID:10312010

Opto-mechatronics issues in solid immersion lens based near-field recording

NASA Astrophysics Data System (ADS)

Park, No-Cheol; Yoon, Yong-Joong; Lee, Yong-Hyun; Kim, Joong-Gon; Kim, Wan-Chin; Choi, Hyun; Lim, Seungho; Yang, Tae-Man; Choi, Moon-Ho; Yang, Hyunseok; Rhim, Yoon-Chul; Park, Young-Pil

2007-06-01

We analyzed the effects of an external shock on a collision problem in a solid immersion lens (SIL) based near-field recording (NFR) through a shock response analysis and proposed a possible solution to this problem with adopting a protector and safety mode. With this proposed method the collision between SIL and media can be avoided. We showed possible solution for contamination problem in SIL based NFR through a numerical air flow analysis. We also introduced possible solid immersion lens designs to increase the fabrication and assembly tolerances of an optical head with replicated lens. Potentially, these research results could advance NFR technology for commercial product.

A novel adaptive finite time controller for bilateral teleoperation system

NASA Astrophysics Data System (ADS)

Wang, Ziwei; Chen, Zhang; Liang, Bin; Zhang, Bo

2018-03-01

Most bilateral teleoperation researches focus on the system stability within time-delays. However, practical teleoperation tasks require high performances besides system stability, such as convergence rate and accuracy. This paper investigates bilateral teleoperation controller design with transient performances. To ensure the transient performances and system stability simultaneously, an adaptive non-singular fast terminal mode controller is proposed to achieve practical finite-time stability considering system uncertainties and time delays. In addition, a novel switching scheme is introduced, in which way the singularity problem of conventional terminal sliding manifold is avoided. Finally, numerical simulations demonstrate the effectiveness and validity of the proposed method.

Researches on hazard avoidance cameras calibration of Lunar Rover

NASA Astrophysics Data System (ADS)

Li, Chunyan; Wang, Li; Lu, Xin; Chen, Jihua; Fan, Shenghong

2017-11-01

Lunar Lander and Rover of China will be launched in 2013. It will finish the mission targets of lunar soft landing and patrol exploration. Lunar Rover has forward facing stereo camera pair (Hazcams) for hazard avoidance. Hazcams calibration is essential for stereo vision. The Hazcam optics are f-theta fish-eye lenses with a 120°×120° horizontal/vertical field of view (FOV) and a 170° diagonal FOV. They introduce significant distortion in images and the acquired images are quite warped, which makes conventional camera calibration algorithms no longer work well. A photogrammetric calibration method of geometric model for the type of optical fish-eye constructions is investigated in this paper. In the method, Hazcams model is represented by collinearity equations with interior orientation and exterior orientation parameters [1] [2]. For high-precision applications, the accurate calibration model is formulated with the radial symmetric distortion and the decentering distortion as well as parameters to model affinity and shear based on the fisheye deformation model [3] [4]. The proposed method has been applied to the stereo camera calibration system for Lunar Rover.

Statistical CT noise reduction with multiscale decomposition and penalized weighted least squares in the projection domain

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

Tang Shaojie; Tang Xiangyang; School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi 710121

2012-09-15

Purposes: The suppression of noise in x-ray computed tomography (CT) imaging is of clinical relevance for diagnostic image quality and the potential for radiation dose saving. Toward this purpose, statistical noise reduction methods in either the image or projection domain have been proposed, which employ a multiscale decomposition to enhance the performance of noise suppression while maintaining image sharpness. Recognizing the advantages of noise suppression in the projection domain, the authors propose a projection domain multiscale penalized weighted least squares (PWLS) method, in which the angular sampling rate is explicitly taken into consideration to account for the possible variation ofmore » interview sampling rate in advanced clinical or preclinical applications. Methods: The projection domain multiscale PWLS method is derived by converting an isotropic diffusion partial differential equation in the image domain into the projection domain, wherein a multiscale decomposition is carried out. With adoption of the Markov random field or soft thresholding objective function, the projection domain multiscale PWLS method deals with noise at each scale. To compensate for the degradation in image sharpness caused by the projection domain multiscale PWLS method, an edge enhancement is carried out following the noise reduction. The performance of the proposed method is experimentally evaluated and verified using the projection data simulated by computer and acquired by a CT scanner. Results: The preliminary results show that the proposed projection domain multiscale PWLS method outperforms the projection domain single-scale PWLS method and the image domain multiscale anisotropic diffusion method in noise reduction. In addition, the proposed method can preserve image sharpness very well while the occurrence of 'salt-and-pepper' noise and mosaic artifacts can be avoided. Conclusions: Since the interview sampling rate is taken into account in the projection domain multiscale decomposition, the proposed method is anticipated to be useful in advanced clinical and preclinical applications where the interview sampling rate varies.« less

Privacy preservation and information security protection for patients' portable electronic health records.

PubMed

Huang, Lu-Chou; Chu, Huei-Chung; Lien, Chung-Yueh; Hsiao, Chia-Hung; Kao, Tsair

2009-09-01

As patients face the possibility of copying and keeping their electronic health records (EHRs) through portable storage media, they will encounter new risks to the protection of their private information. In this study, we propose a method to preserve the privacy and security of patients' portable medical records in portable storage media to avoid any inappropriate or unintentional disclosure. Following HIPAA guidelines, the method is designed to protect, recover and verify patient's identifiers in portable EHRs. The results of this study show that our methods are effective in ensuring both information security and privacy preservation for patients through portable storage medium.

Automated EEG artifact elimination by applying machine learning algorithms to ICA-based features.

PubMed

Radüntz, Thea; Scouten, Jon; Hochmuth, Olaf; Meffert, Beate

2017-08-01

Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However, evaluating and classifying the calculated independent components (IC) as artifact or EEG is not fully automated at present. In this study, we propose a new approach for automated artifact elimination, which applies machine learning algorithms to ICA-based features. We compared the performance of our classifiers with the visual classification results given by experts. The best result with an accuracy rate of 95% was achieved using features obtained by range filtering of the topoplots and IC power spectra combined with an artificial neural network. Compared with the existing automated solutions, our proposed method is not limited to specific types of artifacts, electrode configurations, or number of EEG channels. The main advantages of the proposed method is that it provides an automatic, reliable, real-time capable, and practical tool, which avoids the need for the time-consuming manual selection of ICs during artifact removal.

Automated EEG artifact elimination by applying machine learning algorithms to ICA-based features

NASA Astrophysics Data System (ADS)

Radüntz, Thea; Scouten, Jon; Hochmuth, Olaf; Meffert, Beate

2017-08-01

Objective. Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However, evaluating and classifying the calculated independent components (IC) as artifact or EEG is not fully automated at present. Approach. In this study, we propose a new approach for automated artifact elimination, which applies machine learning algorithms to ICA-based features. Main results. We compared the performance of our classifiers with the visual classification results given by experts. The best result with an accuracy rate of 95% was achieved using features obtained by range filtering of the topoplots and IC power spectra combined with an artificial neural network. Significance. Compared with the existing automated solutions, our proposed method is not limited to specific types of artifacts, electrode configurations, or number of EEG channels. The main advantages of the proposed method is that it provides an automatic, reliable, real-time capable, and practical tool, which avoids the need for the time-consuming manual selection of ICs during artifact removal.

Analysis and numerical modelling of eddy current damper for vibration problems

NASA Astrophysics Data System (ADS)

Irazu, L.; Elejabarrieta, M. J.

2018-07-01

This work discusses a contactless eddy current damper, which is used to attenuate structural vibration. Eddy currents can remove energy from dynamic systems without any contact and, thus, without adding mass or modifying the rigidity of the structure. An experimental modal analysis of a cantilever beam in the absence of and under a partial magnetic field is conducted in the bandwidth of 01 kHz. The results show that the eddy current phenomenon can attenuate the vibration of the entire structure without modifying the natural frequencies or the mode shapes of the structure itself. In this study, a new inverse method to numerically determine the dynamic properties of the contactless eddy current damper is proposed. The proposed inverse method and the eddy current model based on a lineal viscous force are validated by a practical application. The numerically obtained transfer function correlates with the experimental one, thus showing good agreement in the entire bandwidth of 01 kHz. The proposed method provides an easy and quick tool to model and predict the dynamic behaviour of the contactless eddy current damper, thereby avoiding the use of complex analytical models.

Direct Position Determination of Unknown Signals in the Presence of Multipath Propagation

PubMed Central

Yu, Hongyi

2018-01-01

A novel geolocation architecture, termed “Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)” is proposed in this paper. Existing Direct Position Determination (DPD) methods take advantage of a rather simple channel assumption (line of sight channels with complex path attenuations) and a simplified MUltiple SIgnal Classification (MUSIC) algorithm cost function to avoid the high dimension searching. We point out that the simplified assumption and cost function reduce the positioning accuracy because of the singularity of the array manifold in a multi-path environment. We present a DPD model for unknown signals in the presence of Multi-path Propagation (MP-DPD) in this paper. MP-DPD adds non-negative real path attenuation constraints to avoid the mistake caused by the singularity of the array manifold. The Multi-path Propagation MUSIC (MP-MUSIC) method and the Active Set Algorithm (ASA) are designed to reduce the dimension of searching. A Multi-path Propagation Maximum Likelihood (MP-ML) method is proposed in addition to overcome the limitation of MP-MUSIC in the sense of a time-sensitive application. An iterative algorithm and an approach of initial value setting are given to make the MP-ML time consumption acceptable. Numerical results validate the performances improvement of MP-MUSIC and MP-ML. A closed form of the Cramér–Rao Lower Bound (CRLB) is derived as a benchmark to evaluate the performances of MP-MUSIC and MP-ML. PMID:29562601

Direct Position Determination of Unknown Signals in the Presence of Multipath Propagation.

PubMed

Du, Jianping; Wang, Ding; Yu, Wanting; Yu, Hongyi

2018-03-17

A novel geolocation architecture, termed "Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)" is proposed in this paper. Existing Direct Position Determination (DPD) methods take advantage of a rather simple channel assumption (line of sight channels with complex path attenuations) and a simplified MUltiple SIgnal Classification (MUSIC) algorithm cost function to avoid the high dimension searching. We point out that the simplified assumption and cost function reduce the positioning accuracy because of the singularity of the array manifold in a multi-path environment. We present a DPD model for unknown signals in the presence of Multi-path Propagation (MP-DPD) in this paper. MP-DPD adds non-negative real path attenuation constraints to avoid the mistake caused by the singularity of the array manifold. The Multi-path Propagation MUSIC (MP-MUSIC) method and the Active Set Algorithm (ASA) are designed to reduce the dimension of searching. A Multi-path Propagation Maximum Likelihood (MP-ML) method is proposed in addition to overcome the limitation of MP-MUSIC in the sense of a time-sensitive application. An iterative algorithm and an approach of initial value setting are given to make the MP-ML time consumption acceptable. Numerical results validate the performances improvement of MP-MUSIC and MP-ML. A closed form of the Cramér-Rao Lower Bound (CRLB) is derived as a benchmark to evaluate the performances of MP-MUSIC and MP-ML.

[Methods of statistical analysis in differential diagnostics of the degree of brain glioma anaplasia during preoperative stage].

PubMed

Glavatskiĭ, A Ia; Guzhovskaia, N V; Lysenko, S N; Kulik, A V

2005-12-01

The authors proposed a possible preoperative diagnostics of the degree of supratentorial brain gliom anaplasia using statistical analysis methods. It relies on a complex examination of 934 patients with I-IV degree anaplasias, which had been treated in the Institute of Neurosurgery from 1990 to 2004. The use of statistical analysis methods for differential diagnostics of the degree of brain gliom anaplasia may optimize a diagnostic algorithm, increase reliability of obtained data and in some cases avoid carrying out irrational operative intrusions. Clinically important signs for the use of statistical analysis methods directed to preoperative diagnostics of brain gliom anaplasia have been defined

A proposal for a separative network to evacuate drainage waters and pluvial waters of stagnation in arid zones (Ain Sahra locality, Touggourt, Algeria)

NASA Astrophysics Data System (ADS)

Nettari, Kamel; Boutoutaou, Djamel; Rezagui, Djihed

2018-05-01

Many agglomerations of the Algerian Sahara, are currently affected by a rise of waters of the superficial aquifer. This rise is due to discharges of drainage water and urban wastewater. In addition, the rare stormy rains that occur in these areas cause very high material damage. To avoid this damage, it is essential to propose a separative network to evacuate the drainage andpluvial stagnant waters and propose some adequate solutions to avoid potential flooding.

Risk management algorithm for rear-side collision avoidance using a combined steering torque overlay and differential braking

NASA Astrophysics Data System (ADS)

Lee, Junyung; Yi, Kyongsu; Yoo, Hyunjae; Chong, Hyokjin; Ko, Bongchul

2015-06-01

This paper describes a risk management algorithm for rear-side collision avoidance. The proposed risk management algorithm consists of a supervisor and a coordinator. The supervisor is designed to monitor collision risks between the subject vehicle and approaching vehicle in the adjacent lane. An appropriate criterion of intervention, which satisfies high acceptance to drivers through the consideration of a realistic traffic, has been determined based on the analysis of the kinematics of the vehicles in longitudinal and lateral directions. In order to assist the driver actively and increase driver's safety, a coordinator is designed to combine lateral control using a steering torque overlay by motor-driven power steering and differential braking by vehicle stability control. In order to prevent the collision while limiting actuator's control inputs and vehicle dynamics to safe values for the assurance of the driver's comfort, the Lyapunov theory and linear matrix inequalities based optimisation methods have been used. The proposed risk management algorithm has been evaluated via simulation using CarSim and MATLAB/Simulink.

Supercritical flow past a symmetrical bicircular arc airfoil

NASA Technical Reports Server (NTRS)

Holt, Maurice; Yew, Khoy Chuah

1989-01-01

A numerical scheme is developed for computing steady supercritical flow about symmetrical airfoils, applying it to an ellipse for zero angle of attack. An algorithmic description of this new scheme is presented. Application to a symmetrical bicircular arc airfoil is also proposed. The flow field before the shock is region 1. For transonic flow, singularity can be avoided by integrating the resulting ordinary differential equations away from the body. Region 2 contains the shock which will be located by shock fitting techniques. The shock divides region 2 into supersonic and subsonic regions and there is no singularity problem in this case. The Method of Lines is used in this region and it is advantageous to integrate the resulting ordinary differential equation along the body for shock fitting. Coaxial coordinates have to be used for the bicircular arc airfoil so that boundary values on the airfoil body can be taken with one direction of the coaxial coordinates fixed. To avoid taking boundary values at + or - infinity in the coaxial co-ordinary system, approximate analytical representation of the flow field near the tips of the airfoil is proposed.

Colorimetric characterization of digital cameras with unrestricted capture settings applicable for different illumination circumstances

NASA Astrophysics Data System (ADS)

Fang, Jingyu; Xu, Haisong; Wang, Zhehong; Wu, Xiaomin

2016-05-01

With colorimetric characterization, digital cameras can be used as image-based tristimulus colorimeters for color communication. In order to overcome the restriction of fixed capture settings adopted in the conventional colorimetric characterization procedures, a novel method was proposed considering capture settings. The method calculating colorimetric value of the measured image contains five main steps, including conversion from RGB values to equivalent ones of training settings through factors based on imaging system model so as to build the bridge between different settings, scaling factors involved in preparation steps for transformation mapping to avoid errors resulted from nonlinearity of polynomial mapping for different ranges of illumination levels. The experiment results indicate that the prediction error of the proposed method, which was measured by CIELAB color difference formula, reaches less than 2 CIELAB units under different illumination levels and different correlated color temperatures. This prediction accuracy for different capture settings remains the same level as the conventional method for particular lighting condition.

Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems.

PubMed

Li, Yuan-Xin; Yang, Guang-Hong

2018-04-01

This paper is concerned with the adaptive event-triggered control problem of nonlinear continuous-time systems in strict-feedback form. By using the event-sampled neural network (NN) to approximate the unknown nonlinear function, an adaptive model and an associated event-triggered controller are designed by exploiting the backstepping method. In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated. A positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. The closed-loop stability of the resulting nonlinear impulsive dynamical system is rigorously proved via Lyapunov analysis under an adaptive event sampling condition. In comparing with the traditional adaptive backstepping design with a fixed sample period, the event-triggered method samples the state and updates the NN weights only when it is necessary. Therefore, the number of transmissions can be significantly reduced. Finally, two simulation examples are presented to show the effectiveness of the proposed control method.

Standardization of fixation, processing and staining methods for the central nervous system of vertebrates.

PubMed

Aldana Marcos, H J; Ferrari, C C; Benitez, I; Affanni, J M

1996-12-01

This paper reports the standardization of methods used for processing and embedding various vertebrate brains of different size in paraffin. Other technical details developed for avoiding frequent difficulties arising during laboratory routine are also reported. Some modifications of the Nissl and Klüver-Barrera staining methods are proposed. These modifications include: 1) a Nissl stain solution with a rapid and efficient action with easier differentiation; 2) the use of a cheap microwave oven for the Klüver-Barrera stain. These procedures have the advantage of permitting Nissl and Klüver-Barrera staining of nervous tissue in about five and fifteen minutes respectively. The proposed procedures have been tested in brains obtained from fish, amphibians, reptiles and mammals of different body sizes. They are the result of our long experience in preparing slides for comparative studies. Serial sections of excellent quality were regularly obtained in all the specimens studied. These standardized methods, being simple and quick, are recommended for routine use in neurobiological laboratories.

Sparse alignment for robust tensor learning.

PubMed

Lai, Zhihui; Wong, Wai Keung; Xu, Yong; Zhao, Cairong; Sun, Mingming

2014-10-01

Multilinear/tensor extensions of manifold learning based algorithms have been widely used in computer vision and pattern recognition. This paper first provides a systematic analysis of the multilinear extensions for the most popular methods by using alignment techniques, thereby obtaining a general tensor alignment framework. From this framework, it is easy to show that the manifold learning based tensor learning methods are intrinsically different from the alignment techniques. Based on the alignment framework, a robust tensor learning method called sparse tensor alignment (STA) is then proposed for unsupervised tensor feature extraction. Different from the existing tensor learning methods, L1- and L2-norms are introduced to enhance the robustness in the alignment step of the STA. The advantage of the proposed technique is that the difficulty in selecting the size of the local neighborhood can be avoided in the manifold learning based tensor feature extraction algorithms. Although STA is an unsupervised learning method, the sparsity encodes the discriminative information in the alignment step and provides the robustness of STA. Extensive experiments on the well-known image databases as well as action and hand gesture databases by encoding object images as tensors demonstrate that the proposed STA algorithm gives the most competitive performance when compared with the tensor-based unsupervised learning methods.

An Orientation Measurement Method Based on Hall-effect Sensors for Permanent Magnet Spherical Actuators with 3D Magnet Array

PubMed Central

Yan, Liang; Zhu, Bo; Jiao, Zongxia; Chen, Chin-Yin; Chen, I-Ming

2014-01-01

An orientation measurement method based on Hall-effect sensors is proposed for permanent magnet (PM) spherical actuators with three-dimensional (3D) magnet array. As there is no contact between the measurement system and the rotor, this method could effectively avoid friction torque and additional inertial moment existing in conventional approaches. Curved surface fitting method based on exponential approximation is proposed to formulate the magnetic field distribution in 3D space. The comparison with conventional modeling method shows that it helps to improve the model accuracy. The Hall-effect sensors are distributed around the rotor with PM poles to detect the flux density at different points, and thus the rotor orientation can be computed from the measured results and analytical models. Experiments have been conducted on the developed research prototype of the spherical actuator to validate the accuracy of the analytical equations relating the rotor orientation and the value of magnetic flux density. The experimental results show that the proposed method can measure the rotor orientation precisely, and the measurement accuracy could be improved by the novel 3D magnet array. The study result could be used for real-time motion control of PM spherical actuators. PMID:25342000

Segmentized Clear Channel Assessment for IEEE 802.15.4 Networks.

PubMed

Son, Kyou Jung; Hong, Sung Hyeuck; Moon, Seong-Pil; Chang, Tae Gyu; Cho, Hanjin

2016-06-03

This paper proposed segmentized clear channel assessment (CCA) which increases the performance of IEEE 802.15.4 networks by improving carrier sense multiple access with collision avoidance (CSMA/CA). Improving CSMA/CA is important because the low-power consumption feature and throughput performance of IEEE 802.15.4 are greatly affected by CSMA/CA behavior. To improve the performance of CSMA/CA, this paper focused on increasing the chance to transmit a packet by assessing precise channel status. The previous method used in CCA, which is employed by CSMA/CA, assesses the channel by measuring the energy level of the channel. However, this method shows limited channel assessing behavior, which comes from simple threshold dependent channel busy evaluation. The proposed method solves this limited channel decision problem by dividing CCA into two groups. Two groups of CCA compare their energy levels to get precise channel status. To evaluate the performance of the segmentized CCA method, a Markov chain model has been developed. The validation of analytic results is confirmed by comparing them with simulation results. Additionally, simulation results show the proposed method is improving a maximum 8.76% of throughput and decreasing a maximum 3.9% of the average number of CCAs per packet transmission than the IEEE 802.15.4 CCA method.

Segmentized Clear Channel Assessment for IEEE 802.15.4 Networks

PubMed Central

Son, Kyou Jung; Hong, Sung Hyeuck; Moon, Seong-Pil; Chang, Tae Gyu; Cho, Hanjin

2016-01-01

This paper proposed segmentized clear channel assessment (CCA) which increases the performance of IEEE 802.15.4 networks by improving carrier sense multiple access with collision avoidance (CSMA/CA). Improving CSMA/CA is important because the low-power consumption feature and throughput performance of IEEE 802.15.4 are greatly affected by CSMA/CA behavior. To improve the performance of CSMA/CA, this paper focused on increasing the chance to transmit a packet by assessing precise channel status. The previous method used in CCA, which is employed by CSMA/CA, assesses the channel by measuring the energy level of the channel. However, this method shows limited channel assessing behavior, which comes from simple threshold dependent channel busy evaluation. The proposed method solves this limited channel decision problem by dividing CCA into two groups. Two groups of CCA compare their energy levels to get precise channel status. To evaluate the performance of the segmentized CCA method, a Markov chain model has been developed. The validation of analytic results is confirmed by comparing them with simulation results. Additionally, simulation results show the proposed method is improving a maximum 8.76% of throughput and decreasing a maximum 3.9% of the average number of CCAs per packet transmission than the IEEE 802.15.4 CCA method. PMID:27271626

Topological visual mapping in robotics.

PubMed

Romero, Anna; Cazorla, Miguel

2012-08-01

A key problem in robotics is the construction of a map from its environment. This map could be used in different tasks, like localization, recognition, obstacle avoidance, etc. Besides, the simultaneous location and mapping (SLAM) problem has had a lot of interest in the robotics community. This paper presents a new method for visual mapping, using topological instead of metric information. For that purpose, we propose prior image segmentation into regions in order to group the extracted invariant features in a graph so that each graph defines a single region of the image. Although others methods have been proposed for visual SLAM, our method is complete, in the sense that it makes all the process: it presents a new method for image matching; it defines a way to build the topological map; and it also defines a matching criterion for loop-closing. The matching process will take into account visual features and their structure using the graph transformation matching (GTM) algorithm, which allows us to process the matching and to remove out the outliers. Then, using this image comparison method, we propose an algorithm for constructing topological maps. During the experimentation phase, we will test the robustness of the method and its ability constructing topological maps. We have also introduced new hysteresis behavior in order to solve some problems found building the graph.

Single photon emission computed tomography-guided Cerenkov luminescence tomography

NASA Astrophysics Data System (ADS)

Hu, Zhenhua; Chen, Xueli; Liang, Jimin; Qu, Xiaochao; Chen, Duofang; Yang, Weidong; Wang, Jing; Cao, Feng; Tian, Jie

2012-07-01

Cerenkov luminescence tomography (CLT) has become a valuable tool for preclinical imaging because of its ability of reconstructing the three-dimensional distribution and activity of the radiopharmaceuticals. However, it is still far from a mature technology and suffers from relatively low spatial resolution due to the ill-posed inverse problem for the tomographic reconstruction. In this paper, we presented a single photon emission computed tomography (SPECT)-guided reconstruction method for CLT, in which a priori information of the permissible source region (PSR) from SPECT imaging results was incorporated to effectively reduce the ill-posedness of the inverse reconstruction problem. The performance of the method was first validated with the experimental reconstruction of an adult athymic nude mouse implanted with a Na131I radioactive source and an adult athymic nude mouse received an intravenous tail injection of Na131I. A tissue-mimic phantom based experiment was then conducted to illustrate the ability of the proposed method in resolving double sources. Compared with the traditional PSR strategy in which the PSR was determined by the surface flux distribution, the proposed method obtained much more accurate and encouraging localization and resolution results. Preliminary results showed that the proposed SPECT-guided reconstruction method was insensitive to the regularization methods and ignored the heterogeneity of tissues which can avoid the segmentation procedure of the organs.

Keeping memories at an arm's length: vantage point of trauma memories.

PubMed

Kenny, Lucy M; Bryant, Richard A

2007-08-01

This study investigated the relationship between memory vantage point and avoidance following trauma. Sixty trauma survivors with differing levels of avoidance were interviewed about the vantage point of their memory for trauma, a positive memory, and a neutral memory. Avoidant individuals were more likely to remember their trauma from an observer perspective than individuals with a lower level of avoidance. Avoidance did not influence vantage point for positive or neutral memories. These data support the proposal that adoption of the observer vantage point for trauma memories may serve an avoidant function for people affected by trauma.

Hypoglycemia prediction with subject-specific recursive time-series models.

PubMed

Eren-Oruklu, Meriyan; Cinar, Ali; Quinn, Lauretta

2010-01-01

Avoiding hypoglycemia while keeping glucose within the narrow normoglycemic range (70-120 mg/dl) is a major challenge for patients with type 1 diabetes. Continuous glucose monitors can provide hypoglycemic alarms when the measured glucose decreases below a threshold. However, a better approach is to provide an early alarm that predicts a hypoglycemic episode before it occurs, allowing enough time for the patient to take the necessary precaution to avoid hypoglycemia. We have previously proposed subject-specific recursive models for the prediction of future glucose concentrations and evaluated their prediction performance. In this work, our objective was to evaluate this algorithm further to predict hypoglycemia and provide early hypoglycemic alarms. Three different methods were proposed for alarm decision, where (A) absolute predicted glucose values, (B) cumulative-sum (CUSUM) control chart, and (C) exponentially weighted moving-average (EWMA) control chart were used. Each method was validated using data from the Diabetes Research in Children Network, which consist of measurements from a continuous glucose sensor during an insulin-induced hypoglycemia. Reference serum glucose measurements were used to determine the sensitivity to predict hypoglycemia and the false alarm rate. With the hypoglycemic threshold set to 60 mg/dl, sensitivity of 89, 87.5, and 89% and specificity of 67, 74, and 78% were reported for methods A, B, and C, respectively. Mean values for time to detection were 30 +/- 5.51 (A), 25.8 +/- 6.46 (B), and 27.7 +/- 5.32 (C) minutes. Compared to the absolute value method, both CUSUM and EWMA methods behaved more conservatively before raising an alarm (reduced time to detection), which significantly decreased the false alarm rate and increased the specificity. 2010 Diabetes Technology Society.

Intelligent identification of remnant ridge edges in region west of Yongxing Island, South China Sea

NASA Astrophysics Data System (ADS)

Wang, Weiwei; Guo, Jing; Cai, Guanqiang; Wang, Dawei

2018-02-01

Edge detection enables identification of geomorphologic unit boundaries and thus assists with geomorphical mapping. In this paper, an intelligent edge identification method is proposed and image processing techniques are applied to multi-beam bathymetry data. To accomplish this, a color image is generated by the bathymetry, and a weighted method is used to convert the color image to a gray image. As the quality of the image has a significant influence on edge detection, different filter methods are applied to the gray image for de-noising. The peak signal-to-noise ratio and mean square error are calculated to evaluate which filter method is most appropriate for depth image filtering and the edge is subsequently detected using an image binarization method. Traditional image binarization methods cannot manage the complicated uneven seafloor, and therefore a binarization method is proposed that is based on the difference between image pixel values; the appropriate threshold for image binarization is estimated according to the probability distribution of pixel value differences between two adjacent pixels in horizontal and vertical directions, respectively. Finally, an eight-neighborhood frame is adopted to thin the binary image, connect the intermittent edge, and implement contour extraction. Experimental results show that the method described here can recognize the main boundaries of geomorphologic units. In addition, the proposed automatic edge identification method avoids use of subjective judgment, and reduces time and labor costs.

Branch-Based Centralized Data Collection for Smart Grids Using Wireless Sensor Networks

PubMed Central

Kim, Kwangsoo; Jin, Seong-il

2015-01-01

A smart grid is one of the most important applications in smart cities. In a smart grid, a smart meter acts as a sensor node in a sensor network, and a central device collects power usage from every smart meter. This paper focuses on a centralized data collection problem of how to collect every power usage from every meter without collisions in an environment in which the time synchronization among smart meters is not guaranteed. To solve the problem, we divide a tree that a sensor network constructs into several branches. A conflict-free query schedule is generated based on the branches. Each power usage is collected according to the schedule. The proposed method has important features: shortening query processing time and avoiding collisions between a query and query responses. We evaluate this method using the ns-2 simulator. The experimental results show that this method can achieve both collision avoidance and fast query processing at the same time. The success rate of data collection at a sink node executing this method is 100%. Its running time is about 35 percent faster than that of the round-robin method, and its memory size is reduced to about 10% of that of the depth-first search method. PMID:26007734

Branch-based centralized data collection for smart grids using wireless sensor networks.

PubMed

Kim, Kwangsoo; Jin, Seong-il

2015-05-21

A smart grid is one of the most important applications in smart cities. In a smart grid, a smart meter acts as a sensor node in a sensor network, and a central device collects power usage from every smart meter. This paper focuses on a centralized data collection problem of how to collect every power usage from every meter without collisions in an environment in which the time synchronization among smart meters is not guaranteed. To solve the problem, we divide a tree that a sensor network constructs into several branches. A conflict-free query schedule is generated based on the branches. Each power usage is collected according to the schedule. The proposed method has important features: shortening query processing time and avoiding collisions between a query and query responses. We evaluate this method using the ns-2 simulator. The experimental results show that this method can achieve both collision avoidance and fast query processing at the same time. The success rate of data collection at a sink node executing this method is 100%. Its running time is about 35 percent faster than that of the round-robin method, and its memory size is reduced to about 10% of that of the depth-first search method.

Probabilistic peak detection in CE-LIF for STR DNA typing.

PubMed

Woldegebriel, Michael; van Asten, Arian; Kloosterman, Ate; Vivó-Truyols, Gabriel

2017-07-01

In this work, we present a novel probabilistic peak detection algorithm based on a Bayesian framework for forensic DNA analysis. The proposed method aims at an exhaustive use of raw electropherogram data from a laser-induced fluorescence multi-CE system. As the raw data are informative up to a single data point, the conventional threshold-based approaches discard relevant forensic information early in the data analysis pipeline. Our proposed method assigns a posterior probability reflecting the data point's relevance with respect to peak detection criteria. Peaks of low intensity generated from a truly existing allele can thus constitute evidential value instead of fully discarding them and contemplating a potential allele drop-out. This way of working utilizes the information available within each individual data point and thus avoids making early (binary) decisions on the data analysis that can lead to error propagation. The proposed method was tested and compared to the application of a set threshold as is current practice in forensic STR DNA profiling. The new method was found to yield a significant improvement in the number of alleles identified, regardless of the peak heights and deviation from Gaussian shape. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Lumen-based detection of prostate cancer via convolutional neural networks

NASA Astrophysics Data System (ADS)

Kwak, Jin Tae; Hewitt, Stephen M.

2017-03-01

We present a deep learning approach for detecting prostate cancers. The approach consists of two steps. In the first step, we perform tissue segmentation that identifies lumens within digitized prostate tissue specimen images. Intensity- and texture-based image features are computed at five different scales, and a multiview boosting method is adopted to cooperatively combine the image features from differing scales and to identify lumens. In the second step, we utilize convolutional neural networks (CNN) to automatically extract high-level image features of lumens and to predict cancers. The segmented lumens are rescaled to reduce computational complexity and data augmentation by scaling, rotating, and flipping the rescaled image is applied to avoid overfitting. We evaluate the proposed method using two tissue microarrays (TMA) - TMA1 includes 162 tissue specimens (73 Benign and 89 Cancer) and TMA2 comprises 185 tissue specimens (70 Benign and 115 Cancer). In cross-validation on TMA1, the proposed method achieved an AUC of 0.95 (CI: 0.93-0.98). Trained on TMA1 and tested on TMA2, CNN obtained an AUC of 0.95 (CI: 0.92-0.98). This demonstrates that the proposed method can potentially improve prostate cancer pathology.

Fully coupled simulation of multiple hydraulic fractures to propagate simultaneously from a perforated horizontal wellbore

NASA Astrophysics Data System (ADS)

Zeng, Qinglei; Liu, Zhanli; Wang, Tao; Gao, Yue; Zhuang, Zhuo

2018-02-01

In hydraulic fracturing process in shale rock, multiple fractures perpendicular to a horizontal wellbore are usually driven to propagate simultaneously by the pumping operation. In this paper, a numerical method is developed for the propagation of multiple hydraulic fractures (HFs) by fully coupling the deformation and fracturing of solid formation, fluid flow in fractures, fluid partitioning through a horizontal wellbore and perforation entry loss effect. The extended finite element method (XFEM) is adopted to model arbitrary growth of the fractures. Newton's iteration is proposed to solve these fully coupled nonlinear equations, which is more efficient comparing to the widely adopted fixed-point iteration in the literatures and avoids the need to impose fluid pressure boundary condition when solving flow equations. A secant iterative method based on the stress intensity factor (SIF) is proposed to capture different propagation velocities of multiple fractures. The numerical results are compared with theoretical solutions in literatures to verify the accuracy of the method. The simultaneous propagation of multiple HFs is simulated by the newly proposed algorithm. The coupled influences of propagation regime, stress interaction, wellbore pressure loss and perforation entry loss on simultaneous propagation of multiple HFs are investigated.

Super-resolution fusion of complementary panoramic images based on cross-selection kernel regression interpolation.

PubMed

Chen, Lidong; Basu, Anup; Zhang, Maojun; Wang, Wei; Liu, Yu

2014-03-20

A complementary catadioptric imaging technique was proposed to solve the problem of low and nonuniform resolution in omnidirectional imaging. To enhance this research, our paper focuses on how to generate a high-resolution panoramic image from the captured omnidirectional image. To avoid the interference between the inner and outer images while fusing the two complementary views, a cross-selection kernel regression method is proposed. First, in view of the complementarity of sampling resolution in the tangential and radial directions between the inner and the outer images, respectively, the horizontal gradients in the expected panoramic image are estimated based on the scattered neighboring pixels mapped from the outer, while the vertical gradients are estimated using the inner image. Then, the size and shape of the regression kernel are adaptively steered based on the local gradients. Furthermore, the neighboring pixels in the next interpolation step of kernel regression are also selected based on the comparison between the horizontal and vertical gradients. In simulation and real-image experiments, the proposed method outperforms existing kernel regression methods and our previous wavelet-based fusion method in terms of both visual quality and objective evaluation.

Improved Topographic Mapping Through Multi-Baseline SAR Interferometry with MAP Estimation

NASA Astrophysics Data System (ADS)

Dong, Yuting; Jiang, Houjun; Zhang, Lu; Liao, Mingsheng; Shi, Xuguo

2015-05-01

There is an inherent contradiction between the sensitivity of height measurement and the accuracy of phase unwrapping for SAR interferometry (InSAR) over rough terrain. This contradiction can be resolved by multi-baseline InSAR analysis, which exploits multiple phase observations with different normal baselines to improve phase unwrapping accuracy, or even avoid phase unwrapping. In this paper we propose a maximum a posteriori (MAP) estimation method assisted by SRTM DEM data for multi-baseline InSAR topographic mapping. Based on our method, a data processing flow is established and applied in processing multi-baseline ALOS/PALSAR dataset. The accuracy of resultant DEMs is evaluated by using a standard Chinese national DEM of scale 1:10,000 as reference. The results show that multi-baseline InSAR can improve DEM accuracy compared with single-baseline case. It is noteworthy that phase unwrapping is avoided and the quality of multi-baseline InSAR DEM can meet the DTED-2 standard.

Scatter measurement and correction method for cone-beam CT based on single grating scan

NASA Astrophysics Data System (ADS)

Huang, Kuidong; Shi, Wenlong; Wang, Xinyu; Dong, Yin; Chang, Taoqi; Zhang, Hua; Zhang, Dinghua

2017-06-01

In cone-beam computed tomography (CBCT) systems based on flat-panel detector imaging, the presence of scatter significantly reduces the quality of slices. Based on the concept of collimation, this paper presents a scatter measurement and correction method based on single grating scan. First, according to the characteristics of CBCT imaging, the scan method using single grating and the design requirements of the grating are analyzed and figured out. Second, by analyzing the composition of object projection images and object-and-grating projection images, the processing method for the scatter image at single projection angle is proposed. In addition, to avoid additional scan, this paper proposes an angle interpolation method of scatter images to reduce scan cost. Finally, the experimental results show that the scatter images obtained by this method are accurate and reliable, and the effect of scatter correction is obvious. When the additional object-and-grating projection images are collected and interpolated at intervals of 30 deg, the scatter correction error of slices can still be controlled within 3%.

Learning binary code via PCA of angle projection for image retrieval

NASA Astrophysics Data System (ADS)

Yang, Fumeng; Ye, Zhiqiang; Wei, Xueqi; Wu, Congzhong

2018-01-01

With benefits of low storage costs and high query speeds, binary code representation methods are widely researched for efficiently retrieving large-scale data. In image hashing method, learning hashing function to embed highdimensions feature to Hamming space is a key step for accuracy retrieval. Principal component analysis (PCA) technical is widely used in compact hashing methods, and most these hashing methods adopt PCA projection functions to project the original data into several dimensions of real values, and then each of these projected dimensions is quantized into one bit by thresholding. The variances of different projected dimensions are different, and with real-valued projection produced more quantization error. To avoid the real-valued projection with large quantization error, in this paper we proposed to use Cosine similarity projection for each dimensions, the angle projection can keep the original structure and more compact with the Cosine-valued. We used our method combined the ITQ hashing algorithm, and the extensive experiments on the public CIFAR-10 and Caltech-256 datasets validate the effectiveness of the proposed method.

Development of a Remote Consultation System Using Avatar Technology

NASA Astrophysics Data System (ADS)

Ohnishi, Tatsuya; Yajima, Hiroshi; Sawamoto, Jun

The chance to use the Internet as a communications tool has been increasing, and the consultation businesses for customers at remote places are diversifying in their communication media and forms. In the remote consultation, the lack of non-verbal information is reported as one of the reasons for inefficiency and customer's dissatisfaction compared with the face-to-face consultation. The technique for supplementing non-verbal information with a TV telephone is proposed, and helps to confirm understanding degree or the utterance timing by watching the movement of the face. But the displayed face of the partner causes strong feeling of strain between strangers and the participants also care about background scene displayed on the monitor producing risks in the consultation tasks. In this paper, we propose a remote consultation method that uses avatar technology in the virtual space in order to provide non-verbal information and also avoiding the problem of TV telephone at the same time. The effectiveness of the proposed remote consultation method is confirmed by experiments.

ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.

PubMed

Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2017-07-20

Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.

Positive-negative corresponding normalized ghost imaging based on an adaptive threshold

NASA Astrophysics Data System (ADS)

Li, G. L.; Zhao, Y.; Yang, Z. H.; Liu, X.

2016-11-01

Ghost imaging (GI) technology has attracted increasing attention as a new imaging technique in recent years. However, the signal-to-noise ratio (SNR) of GI with pseudo-thermal light needs to be improved before it meets engineering application demands. We therefore propose a new scheme called positive-negative correspondence normalized GI based on an adaptive threshold (PCNGI-AT) to achieve a good performance with less amount of data. In this work, we use both the advantages of normalized GI (NGI) and positive-negative correspondence GI (P-NCGI). The correctness and feasibility of the scheme were proved in theory before we designed an adaptive threshold selection method, in which the parameter of object signal selection conditions is replaced by the normalizing value. The simulation and experimental results reveal that the SNR of the proposed scheme is better than that of time-correspondence differential GI (TCDGI), avoiding the calculation of the matrix of correlation and reducing the amount of data used. The method proposed will make GI far more practical in engineering applications.

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow.

PubMed

Zhang, Weilong; Guo, Bingxuan; Li, Ming; Liao, Xuan; Li, Wenzhuo

2018-04-16

Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images.

Collision avoidance in TV white spaces: a cross-layer design approach for cognitive radio networks

NASA Astrophysics Data System (ADS)

Foukalas, Fotis; Karetsos, George T.

2015-07-01

One of the most promising applications of cognitive radio networks (CRNs) is the efficient exploitation of TV white spaces (TVWSs) for enhancing the performance of wireless networks. In this paper, we propose a cross-layer design (CLD) of carrier sense multiple access with collision avoidance (CSMA/CA) mechanism at the medium access control (MAC) layer with spectrum sensing (SpSe) at the physical layer, for identifying the occupancy status of TV bands. The proposed CLD relies on a Markov chain model with a state pair containing both the SpSe and the CSMA/CA from which we derive the collision probability and the achievable throughput. Analytical and simulation results are obtained for different collision avoidance and SpSe implementation scenarios by varying the contention window, back off stage and probability of detection. The obtained results depict the achievable throughput under different collision avoidance and SpSe implementation scenarios indicating thereby the performance of collision avoidance in TVWSs-based CRNs.

Method of wavefront tilt correction for optical heterodyne detection systems under strong turbulence

NASA Astrophysics Data System (ADS)

Xiang, Jing-song; Tian, Xin; Pan, Le-chun

2014-07-01

Atmospheric turbulence decreases the heterodyne mixing efficiency of the optical heterodyne detection systems. Wavefront tilt correction is often used to improve the optical heterodyne mixing efficiency. But the performance of traditional centroid tracking tilt correction is poor under strong turbulence conditions. In this paper, a tilt correction method which tracking the peak value of laser spot on focal plane is proposed. Simulation results show that, under strong turbulence conditions, the performance of peak value tracking tilt correction is distinctly better than that of traditional centroid tracking tilt correction method, and the phenomenon of large antenna's performance inferior to small antenna's performance which may be occurred in centroid tracking tilt correction method can also be avoid in peak value tracking tilt correction method.

Shape-based diffeomorphic registration on hippocampal surfaces using Beltrami holomorphic flow.

PubMed

Lui, Lok Ming; Wong, Tsz Wai; Thompson, Paul; Chan, Tony; Gu, Xianfeng; Yau, Shing-Tung

2010-01-01

We develop a new algorithm to automatically register hippocampal (HP) surfaces with complete geometric matching, avoiding the need to manually label landmark features. A good registration depends on a reasonable choice of shape energy that measures the dissimilarity between surfaces. In our work, we first propose a complete shape index using the Beltrami coefficient and curvatures, which measures subtle local differences. The proposed shape energy is zero if and only if two shapes are identical up to a rigid motion. We then seek the best surface registration by minimizing the shape energy. We propose a simple representation of surface diffeomorphisms using Beltrami coefficients, which simplifies the optimization process. We then iteratively minimize the shape energy using the proposed Beltrami Holomorphic flow (BHF) method. Experimental results on 212 HP of normal and diseased (Alzheimer's disease) subjects show our proposed algorithm is effective in registering HP surfaces with complete geometric matching. The proposed shape energy can also capture local shape differences between HP for disease analysis.

A Hierarchical Auction-Based Mechanism for Real-Time Resource Allocation in Cloud Robotic Systems.

PubMed

Wang, Lujia; Liu, Ming; Meng, Max Q-H

2017-02-01

Cloud computing enables users to share computing resources on-demand. The cloud computing framework cannot be directly mapped to cloud robotic systems with ad hoc networks since cloud robotic systems have additional constraints such as limited bandwidth and dynamic structure. However, most multirobotic applications with cooperative control adopt this decentralized approach to avoid a single point of failure. Robots need to continuously update intensive data to execute tasks in a coordinated manner, which implies real-time requirements. Thus, a resource allocation strategy is required, especially in such resource-constrained environments. This paper proposes a hierarchical auction-based mechanism, namely link quality matrix (LQM) auction, which is suitable for ad hoc networks by introducing a link quality indicator. The proposed algorithm produces a fast and robust method that is accurate and scalable. It reduces both global communication and unnecessary repeated computation. The proposed method is designed for firm real-time resource retrieval for physical multirobot systems. A joint surveillance scenario empirically validates the proposed mechanism by assessing several practical metrics. The results show that the proposed LQM auction outperforms state-of-the-art algorithms for resource allocation.

Evidence for an expectancy-based theory of avoidance behaviour.

PubMed

Declercq, Mieke; De Houwer, Jan; Baeyens, Frank

2008-01-01

In most studies on avoidance learning, participants receive an aversive unconditioned stimulus after a warning signal is presented, unless the participant performs a particular response. Lovibond (2006) recently proposed a cognitive theory of avoidance learning, according to which avoidance behaviour is a function of both Pavlovian and instrumental conditioning. In line with this theory, we found that avoidance behaviour was based on an integration of acquired knowledge about, on the one hand, the relation between stimuli and, on the other hand, the relation between behaviour and stimuli.

Adaptive MPC based on MIMO ARX-Laguerre model.

PubMed

Ben Abdelwahed, Imen; Mbarek, Abdelkader; Bouzrara, Kais

2017-03-01

This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A consensus least squares support vector regression (LS-SVR) for analysis of near-infrared spectra of plant samples.

PubMed

Li, Yankun; Shao, Xueguang; Cai, Wensheng

2007-04-15

Consensus modeling of combining the results of multiple independent models to produce a single prediction avoids the instability of single model. Based on the principle of consensus modeling, a consensus least squares support vector regression (LS-SVR) method for calibrating the near-infrared (NIR) spectra was proposed. In the proposed approach, NIR spectra of plant samples were firstly preprocessed using discrete wavelet transform (DWT) for filtering the spectral background and noise, then, consensus LS-SVR technique was used for building the calibration model. With an optimization of the parameters involved in the modeling, a satisfied model was achieved for predicting the content of reducing sugar in plant samples. The predicted results show that consensus LS-SVR model is more robust and reliable than the conventional partial least squares (PLS) and LS-SVR methods.

A novel disturbance-observer based friction compensation scheme for ball and plate system.

PubMed

Wang, Yongkun; Sun, Mingwei; Wang, Zenghui; Liu, Zhongxin; Chen, Zengqiang

2014-03-01

Friction is often ignored when designing a controller for the ball and plate system, which can lead to steady-error and stick-slip phenomena, especially for the small amplitude command. It is difficult to achieve high-precision control performance for the ball and plate system because of its friction. A novel reference compensation strategy is presented to attenuate the aftereffects caused by the friction. To realize this strategy, a linear control law is proposed based on a reduced-order observer. Neither the accurate friction model nor the estimation of specific characteristic parameters is needed in this design. Moreover, the describing function method illustrates that the limit cycle can be avoided. Finally, the comparative mathematical simulations and the practical experiments are used to validate the effectiveness of the proposed method. © 2013 ISA Published by ISA All rights reserved.

Determination of LEDs degradation with entropy generation rate

NASA Astrophysics Data System (ADS)

Cuadras, Angel; Yao, Jiaqiang; Quilez, Marcos

2017-10-01

We propose a method to assess the degradation and aging of light emitting diodes (LEDs) based on irreversible entropy generation rate. We degraded several LEDs and monitored their entropy generation rate ( S ˙ ) in accelerated tests. We compared the thermoelectrical results with the optical light emission evolution during degradation. We find a good relationship between aging and S ˙ (t), because S ˙ is both related to device parameters and optical performance. We propose a threshold of S ˙ (t) as a reliable damage indicator of LED end-of-life that can avoid the need to perform optical measurements to assess optical aging. The method lays beyond the typical statistical laws for lifetime prediction provided by manufacturers. We tested different LED colors and electrical stresses to validate the electrical LED model and we analyzed the degradation mechanisms of the devices.

An artificial neural network controller based on MPSO-BFGS hybrid optimization for spherical flying robot

NASA Astrophysics Data System (ADS)

Liu, Xiaolin; Li, Lanfei; Sun, Hanxu

2017-12-01

Spherical flying robot can perform various tasks in the complex and varied environment to reduce labor costs. However, it is difficult to guarantee the stability of the spherical flying robot in the case of strong coupling and time-varying disturbance. In this paper, an artificial neural network controller (ANNC) based on MPSO-BFGS hybrid optimization algorithm is proposed. The MPSO algorithm is used to optimize the initial weights of the controller to avoid the local optimal solution. The BFGS algorithm is introduced to improve the convergence ability of the network. We use Lyapunov method to analyze the stability of ANNC. The controller is simulated under the condition of nonlinear coupling disturbance. The experimental results show that the proposed controller can obtain the expected value in shoter time compared with the other considered methods.

Swarm-wavelet based extreme learning machine for finger movement classification on transradial amputees.

PubMed

Anam, Khairul; Al-Jumaily, Adel

2014-01-01

The use of a small number of surface electromyography (EMG) channels on the transradial amputee in a myoelectric controller is a big challenge. This paper proposes a pattern recognition system using an extreme learning machine (ELM) optimized by particle swarm optimization (PSO). PSO is mutated by wavelet function to avoid trapped in a local minima. The proposed system is used to classify eleven imagined finger motions on five amputees by using only two EMG channels. The optimal performance of wavelet-PSO was compared to a grid-search method and standard PSO. The experimental results show that the proposed system is the most accurate classifier among other tested classifiers. It could classify 11 finger motions with the average accuracy of about 94 % across five amputees.

Iterative algorithm for joint zero diagonalization with application in blind source separation.

PubMed

Zhang, Wei-Tao; Lou, Shun-Tian

2011-07-01

A new iterative algorithm for the nonunitary joint zero diagonalization of a set of matrices is proposed for blind source separation applications. On one hand, since the zero diagonalizer of the proposed algorithm is constructed iteratively by successive multiplications of an invertible matrix, the singular solutions that occur in the existing nonunitary iterative algorithms are naturally avoided. On the other hand, compared to the algebraic method for joint zero diagonalization, the proposed algorithm requires fewer matrices to be zero diagonalized to yield even better performance. The extension of the algorithm to the complex and nonsquare mixing cases is also addressed. Numerical simulations on both synthetic data and blind source separation using time-frequency distributions illustrate the performance of the algorithm and provide a comparison to the leading joint zero diagonalization schemes.

Fractional-order TV-L2 model for image denoising

NASA Astrophysics Data System (ADS)

Chen, Dali; Sun, Shenshen; Zhang, Congrong; Chen, YangQuan; Xue, Dingyu

2013-10-01

This paper proposes a new fractional order total variation (TV) denoising method, which provides a much more elegant and effective way of treating problems of the algorithm implementation, ill-posed inverse, regularization parameter selection and blocky effect. Two fractional order TV-L2 models are constructed for image denoising. The majorization-minimization (MM) algorithm is used to decompose these two complex fractional TV optimization problems into a set of linear optimization problems which can be solved by the conjugate gradient algorithm. The final adaptive numerical procedure is given. Finally, we report experimental results which show that the proposed methodology avoids the blocky effect and achieves state-of-the-art performance. In addition, two medical image processing experiments are presented to demonstrate the validity of the proposed methodology.

Deficiencies of the cryptography based on multiple-parameter fractional Fourier transform.

PubMed

Ran, Qiwen; Zhang, Haiying; Zhang, Jin; Tan, Liying; Ma, Jing

2009-06-01

Methods of image encryption based on fractional Fourier transform have an incipient flaw in security. We show that the schemes have the deficiency that one group of encryption keys has many groups of keys to decrypt the encrypted image correctly for several reasons. In some schemes, many factors result in the deficiencies, such as the encryption scheme based on multiple-parameter fractional Fourier transform [Opt. Lett.33, 581 (2008)]. A modified method is proposed to avoid all the deficiencies. Security and reliability are greatly improved without increasing the complexity of the encryption process. (c) 2009 Optical Society of America.

25 CFR 900.28 - Is technical assistance available to an Indian tribe or tribal organization to avoid declination...

Code of Federal Regulations, 2012 CFR

2012-04-01

... tribal organization to avoid declination of a proposal? 900.28 Section 900.28 Indians BUREAU OF INDIAN... CONTRACTS UNDER THE INDIAN SELF-DETERMINATION AND EDUCATION ASSISTANCE ACT Declination Procedures § 900.28 Is technical assistance available to an Indian tribe or tribal organization to avoid declination of a...

The Relationship between Bullying Victimization and School Avoidance: An Examination of Direct Associations, Protective Influences, and Aggravating Factors

ERIC Educational Resources Information Center

Hutzell, Kirsten L.; Payne, Allison Ann

2018-01-01

This study examines the impact of bullying victimization on school avoidance by proposing the following hypotheses: (1) Net of other factors, students who have experienced bullying victimization are more likely to engage in school avoidance behaviors; (2) There are protective factors that will decrease this relationship between bullying…

Uncertainty Analysis Based on Sparse Grid Collocation and Quasi-Monte Carlo Sampling with Application in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Zhang, G.; Lu, D.; Ye, M.; Gunzburger, M.

2011-12-01

Markov Chain Monte Carlo (MCMC) methods have been widely used in many fields of uncertainty analysis to estimate the posterior distributions of parameters and credible intervals of predictions in the Bayesian framework. However, in practice, MCMC may be computationally unaffordable due to slow convergence and the excessive number of forward model executions required, especially when the forward model is expensive to compute. Both disadvantages arise from the curse of dimensionality, i.e., the posterior distribution is usually a multivariate function of parameters. Recently, sparse grid method has been demonstrated to be an effective technique for coping with high-dimensional interpolation or integration problems. Thus, in order to accelerate the forward model and avoid the slow convergence of MCMC, we propose a new method for uncertainty analysis based on sparse grid interpolation and quasi-Monte Carlo sampling. First, we construct a polynomial approximation of the forward model in the parameter space by using the sparse grid interpolation. This approximation then defines an accurate surrogate posterior distribution that can be evaluated repeatedly at minimal computational cost. Second, instead of using MCMC, a quasi-Monte Carlo method is applied to draw samples in the parameter space. Then, the desired probability density function of each prediction is approximated by accumulating the posterior density values of all the samples according to the prediction values. Our method has the following advantages: (1) the polynomial approximation of the forward model on the sparse grid provides a very efficient evaluation of the surrogate posterior distribution; (2) the quasi-Monte Carlo method retains the same accuracy in approximating the PDF of predictions but avoids all disadvantages of MCMC. The proposed method is applied to a controlled numerical experiment of groundwater flow modeling. The results show that our method attains the same accuracy much more efficiently than traditional MCMC.

An RBF-FD closest point method for solving PDEs on surfaces

NASA Astrophysics Data System (ADS)

Petras, A.; Ling, L.; Ruuth, S. J.

2018-10-01

Partial differential equations (PDEs) on surfaces appear in many applications throughout the natural and applied sciences. The classical closest point method (Ruuth and Merriman (2008) [17]) is an embedding method for solving PDEs on surfaces using standard finite difference schemes. In this paper, we formulate an explicit closest point method using finite difference schemes derived from radial basis functions (RBF-FD). Unlike the orthogonal gradients method (Piret (2012) [22]), our proposed method uses RBF centers on regular grid nodes. This formulation not only reduces the computational cost but also avoids the ill-conditioning from point clustering on the surface and is more natural to couple with a grid based manifold evolution algorithm (Leung and Zhao (2009) [26]). When compared to the standard finite difference discretization of the closest point method, the proposed method requires a smaller computational domain surrounding the surface, resulting in a decrease in the number of sampling points on the surface. In addition, higher-order schemes can easily be constructed by increasing the number of points in the RBF-FD stencil. Applications to a variety of examples are provided to illustrate the numerical convergence of the method.

Intelligent Local Avoided Collision (iLAC) MAC Protocol for Very High Speed Wireless Network

NASA Astrophysics Data System (ADS)

Hieu, Dinh Chi; Masuda, Akeo; Rabarijaona, Verotiana Hanitriniala; Shimamoto, Shigeru

Future wireless communication systems aim at very high data rates. As the medium access control (MAC) protocol plays the central role in determining the overall performance of the wireless system, designing a suitable MAC protocol is critical to fully exploit the benefit of high speed transmission that the physical layer (PHY) offers. In the latest 802.11n standard [2], the problem of long overhead has been addressed adequately but the issue of excessive colliding transmissions, especially in congested situation, remains untouched. The procedure of setting the backoff value is the heart of the 802.11 distributed coordination function (DCF) to avoid collision in which each station makes its own decision on how to avoid collision in the next transmission. However, collision avoidance is a problem that can not be solved by a single station. In this paper, we introduce a new MAC protocol called Intelligent Local Avoided Collision (iLAC) that redefines individual rationality in choosing the backoff counter value to avoid a colliding transmission. The distinguishing feature of iLAC is that it fundamentally changes this decision making process from collision avoidance to collaborative collision prevention. As a result, stations can avoid colliding transmissions with much greater precision. Analytical solution confirms the validity of this proposal and simulation results show that the proposed algorithm outperforms the conventional algorithms by a large margin.

A possibility of avoiding surface roughness due to insects

NASA Technical Reports Server (NTRS)

Wortmann, F. X.

1984-01-01

Discussion of a method for eliminating turbulence caused by the formation of insect roughness upon the leading edges and fuselage, particularly in aircraft using BLC. The proposed technique foresees the use of elastic surfaces on which insect roughness cannot form. The operational characteristics of highly elastic rubber surface fastened to the wing leading edges and fuselage edges are examined. Some preliminary test results are presented. The technique is seen to be advantageous primarily for short-haul operations.

Precession feature extraction of ballistic missile warhead with high velocity

NASA Astrophysics Data System (ADS)

Sun, Huixia

2018-04-01

This paper establishes the precession model of ballistic missile warhead, and derives the formulas of micro-Doppler frequency induced by the target with precession. In order to obtain micro-Doppler feature of ballistic missile warhead with precession, micro-Doppler bandwidth estimation algorithm, which avoids velocity compensation, is presented based on high-resolution time-frequency transform. The results of computer simulations confirm the effectiveness of the proposed method even with low signal-to-noise ratio.

Microstructure-Based Fatigue Life Prediction Methods for Naval Steel Structures

DTIC Science & Technology

1993-01-30

approach is to work with the lognormal random variable model proposed by Yang et al . [2], which avoids these difficulties. The simplest form of the...I Al - I I 11. and Ti-alloys [ 10- 111 correlate with the elastic modulus only in the continuum growth regime. On the other hand. compilation of...growth. In fact, Eq. (5) implies that microstructure plays no role in the continuum growth regime. Theoretical models of Frost, et al . [35], and

Pose measurement method and experiments for high-speed rolling targets in a wind tunnel.

PubMed

Jia, Zhenyuan; Ma, Xin; Liu, Wei; Lu, Wenbo; Li, Xiao; Chen, Ling; Wang, Zhengqu; Cui, Xiaochun

2014-12-12

High-precision wind tunnel simulation tests play an important role in aircraft design and manufacture. In this study, a high-speed pose vision measurement method is proposed for high-speed and rolling targets in a supersonic wind tunnel. To obtain images with high signal-to-noise ratio and avoid impacts on the aerodynamic shape of the rolling targets, a high-speed image acquisition method based on ultrathin retro-reflection markers is presented. Since markers are small-sized and some of them may be lost when the target is rolling, a novel markers layout with which markers are distributed evenly on the surface is proposed based on a spatial coding method to achieve highly accurate pose information. Additionally, a pose acquisition is carried out according to the mentioned markers layout after removing mismatching points by Case Deletion Diagnostics. Finally, experiments on measuring the pose parameters of high-speed targets in the laboratory and in a supersonic wind tunnel are conducted to verify the feasibility and effectiveness of the proposed method. Experimental results indicate that the position measurement precision is less than 0.16 mm, the pitching and yaw angle precision less than 0.132° and the roll angle precision 0.712°.

New pressure control method of mixed gas in a combined cycle power plant of a steel mill

NASA Astrophysics Data System (ADS)

Xie, Yudong; Wang, Yong

2017-08-01

The enterprise production concept is changing with the development of society. A steel mill requires a combined-cycle power plant, which consists of both a gas turbine and steam turbine. It can recycle energy from the gases that are emitted from coke ovens and blast furnaces during steel production. This plant can decrease the overall energy consumption of the steel mill and reduce pollution to our living environment. To develop a combined-cycle power plant, the pressure in the mixed-gas transmission system must be controlled in the range of 2.30-2.40 MPa. The particularity of the combined-cycle power plant poses a challenge to conventional controllers. In this paper, a composite control method based on the Smith predictor and cascade control was proposed for the pressure control of the mixed gases. This method has a concise structure and can be easily implemented in actual industrial fields. The experiment has been conducted to validate the proposed control method. The experiment illustrates that the proposed method can suppress various disturbances in the gas transmission control system and sustain the pressure of the gas at the desired level, which helps to avoid abnormal shutdowns in the combined-cycle power plant.

On-line tool breakage monitoring of vibration tapping using spindle motor current

NASA Astrophysics Data System (ADS)

Li, Guangjun; Lu, Huimin; Liu, Gang

2008-10-01

Input current of driving motor has been employed successfully as monitoring the cutting state in manufacturing processes for more than a decade. In vibration tapping, however, the method of on-line monitoring motor electric current has not been reported. In this paper, a tap failure prediction method is proposed to monitor the vibration tapping process using the electrical current signal of the spindle motor. The process of vibration tapping is firstly described. Then the relationship between the torque of vibration tapping and the electric current of motor is investigated by theoretic deducing and experimental measurement. According to those results, a monitoring method of tool's breakage is proposed through monitoring the ratio of the current amplitudes during adjacent vibration tapping periods. Finally, a low frequency vibration tapping system with motor current monitoring is built up using a servo motor B-106B and its driver CR06. The proposed method has been demonstrated with experiment data of vibration tapping in titanic alloys. The result of experiments shows that the method, which can avoid the tool breakage and giving a few error alarms when the threshold of amplitude ratio is 1.2 and there is at least 2 times overrun among 50 adjacent periods, is feasible for tool breakage monitoring in the process of vibration tapping small thread holes.

Pose Measurement Method and Experiments for High-Speed Rolling Targets in a Wind Tunnel

PubMed Central

Jia, Zhenyuan; Ma, Xin; Liu, Wei; Lu, Wenbo; Li, Xiao; Chen, Ling; Wang, Zhengqu; Cui, Xiaochun

2014-01-01

High-precision wind tunnel simulation tests play an important role in aircraft design and manufacture. In this study, a high-speed pose vision measurement method is proposed for high-speed and rolling targets in a supersonic wind tunnel. To obtain images with high signal-to-noise ratio and avoid impacts on the aerodynamic shape of the rolling targets, a high-speed image acquisition method based on ultrathin retro-reflection markers is presented. Since markers are small-sized and some of them may be lost when the target is rolling, a novel markers layout with which markers are distributed evenly on the surface is proposed based on a spatial coding method to achieve highly accurate pose information. Additionally, a pose acquisition is carried out according to the mentioned markers layout after removing mismatching points by Case Deletion Diagnostics. Finally, experiments on measuring the pose parameters of high-speed targets in the laboratory and in a supersonic wind tunnel are conducted to verify the feasibility and effectiveness of the proposed method. Experimental results indicate that the position measurement precision is less than 0.16 mm, the pitching and yaw angle precision less than 0.132° and the roll angle precision 0.712°. PMID:25615732

Dynamic Power-Saving Method for Wi-Fi Direct Based IoT Networks Considering Variable-Bit-Rate Video Traffic.

PubMed

Jin, Meihua; Jung, Ji-Young; Lee, Jung-Ryun

2016-10-12

With the arrival of the era of Internet of Things (IoT), Wi-Fi Direct is becoming an emerging wireless technology that allows one to communicate through a direct connection between the mobile devices anytime, anywhere. In Wi-Fi Direct-based IoT networks, all devices are categorized by group of owner (GO) and client. Since portability is emphasized in Wi-Fi Direct devices, it is essential to control the energy consumption of a device very efficiently. In order to avoid unnecessary power consumed by GO, Wi-Fi Direct standard defines two power-saving methods: Opportunistic and Notice of Absence (NoA) power-saving methods. In this paper, we suggest an algorithm to enhance the energy efficiency of Wi-Fi Direct power-saving, considering the characteristics of multimedia video traffic. Proposed algorithm utilizes the statistical distribution for the size of video frames and adjusts the lengths of awake intervals in a beacon interval dynamically. In addition, considering the inter-dependency among video frames, the proposed algorithm ensures that a video frame having high priority is transmitted with higher probability than other frames having low priority. Simulation results show that the proposed method outperforms the traditional NoA method in terms of average delay and energy efficiency.

Dynamic Power-Saving Method for Wi-Fi Direct Based IoT Networks Considering Variable-Bit-Rate Video Traffic

PubMed Central

Jin, Meihua; Jung, Ji-Young; Lee, Jung-Ryun

2016-01-01

With the arrival of the era of Internet of Things (IoT), Wi-Fi Direct is becoming an emerging wireless technology that allows one to communicate through a direct connection between the mobile devices anytime, anywhere. In Wi-Fi Direct-based IoT networks, all devices are categorized by group of owner (GO) and client. Since portability is emphasized in Wi-Fi Direct devices, it is essential to control the energy consumption of a device very efficiently. In order to avoid unnecessary power consumed by GO, Wi-Fi Direct standard defines two power-saving methods: Opportunistic and Notice of Absence (NoA) power-saving methods. In this paper, we suggest an algorithm to enhance the energy efficiency of Wi-Fi Direct power-saving, considering the characteristics of multimedia video traffic. Proposed algorithm utilizes the statistical distribution for the size of video frames and adjusts the lengths of awake intervals in a beacon interval dynamically. In addition, considering the inter-dependency among video frames, the proposed algorithm ensures that a video frame having high priority is transmitted with higher probability than other frames having low priority. Simulation results show that the proposed method outperforms the traditional NoA method in terms of average delay and energy efficiency. PMID:27754315

Modified Mixed Lagrangian-Eulerian Method Based on Numerical Framework of MT3DMS on Cauchy Boundary.

PubMed

Suk, Heejun

2016-07-01

MT3DMS, a modular three-dimensional multispecies transport model, has long been a popular model in the groundwater field for simulating solute transport in the saturated zone. However, the method of characteristics (MOC), modified MOC (MMOC), and hybrid MOC (HMOC) included in MT3DMS did not treat Cauchy boundary conditions in a straightforward or rigorous manner, from a mathematical point of view. The MOC, MMOC, and HMOC regard the Cauchy boundary as a source condition. For the source, MOC, MMOC, and HMOC calculate the Lagrangian concentration by setting it equal to the cell concentration at an old time level. However, the above calculation is an approximate method because it does not involve backward tracking in MMOC and HMOC or allow performing forward tracking at the source cell in MOC. To circumvent this problem, a new scheme is proposed that avoids direct calculation of the Lagrangian concentration on the Cauchy boundary. The proposed method combines the numerical formulations of two different schemes, the finite element method (FEM) and the Eulerian-Lagrangian method (ELM), into one global matrix equation. This study demonstrates the limitation of all MT3DMS schemes, including MOC, MMOC, HMOC, and a third-order total-variation-diminishing (TVD) scheme under Cauchy boundary conditions. By contrast, the proposed method always shows good agreement with the exact solution, regardless of the flow conditions. Finally, the successful application of the proposed method sheds light on the possible flexibility and capability of the MT3DMS to deal with the mass transport problems of all flow regimes. © 2016, National Ground Water Association.

A digital ISO expansion technique for digital cameras

NASA Astrophysics Data System (ADS)

Yoo, Youngjin; Lee, Kangeui; Choe, Wonhee; Park, SungChan; Lee, Seong-Deok; Kim, Chang-Yong

2010-01-01

Market's demands of digital cameras for higher sensitivity capability under low-light conditions are remarkably increasing nowadays. The digital camera market is now a tough race for providing higher ISO capability. In this paper, we explore an approach for increasing maximum ISO capability of digital cameras without changing any structure of an image sensor or CFA. Our method is directly applied to the raw Bayer pattern CFA image to avoid non-linearity characteristics and noise amplification which are usually deteriorated after ISP (Image Signal Processor) of digital cameras. The proposed method fuses multiple short exposed images which are noisy, but less blurred. Our approach is designed to avoid the ghost artifact caused by hand-shaking and object motion. In order to achieve a desired ISO image quality, both low frequency chromatic noise and fine-grain noise that usually appear in high ISO images are removed and then we modify the different layers which are created by a two-scale non-linear decomposition of an image. Once our approach is performed on an input Bayer pattern CFA image, the resultant Bayer image is further processed by ISP to obtain a fully processed RGB image. The performance of our proposed approach is evaluated by comparing SNR (Signal to Noise Ratio), MTF50 (Modulation Transfer Function), color error ~E*ab and visual quality with reference images whose exposure times are properly extended into a variety of target sensitivity.

Students’ Achievement Goals, Learning-Related Emotions and Academic Achievement

PubMed Central

Lüftenegger, Marko; Klug, Julia; Harrer, Katharina; Langer, Marie; Spiel, Christiane; Schober, Barbara

2016-01-01

In the present research, the recently proposed 3 × 2 model of achievement goals is tested and associations with achievement emotions and their joint influence on academic achievement are investigated. The study was conducted with 388 students using the 3 × 2 Achievement Goal Questionnaire including the six proposed goal constructs (task-approach, task-avoidance, self-approach, self-avoidance, other-approach, other-avoidance) and the enjoyment and boredom scales from the Achievement Emotion Questionnaire. Exam grades were used as an indicator of academic achievement. Findings from CFAs provided strong support for the proposed structure of the 3 × 2 achievement goal model. Self-based goals, other-based goals and task-approach goals predicted enjoyment. Task-approach goals negatively predicted boredom. Task-approach and other-approach predicted achievement. The indirect effects of achievement goals through emotion variables on achievement were assessed using bias-corrected bootstrapping. No mediation effects were found. Implications for educational practice are discussed. PMID:27199836

Modeling, Analyzing, and Mitigating Dissonance Between Alerting Systems

NASA Technical Reports Server (NTRS)

Song, Lixia; Kuchar, James K.

2003-01-01

Alerting systems are becoming pervasive in process operations, which may result in the potential for dissonance or conflict in information from different alerting systems that suggests different threat levels and/or actions to resolve hazards. Little is currently available to help in predicting or solving the dissonance problem. This thesis presents a methodology to model and analyze dissonance between alerting systems, providing both a theoretical foundation for understanding dissonance and a practical basis from which specific problems can be addressed. A state-space representation of multiple alerting system operation is generalized that can be tailored across a variety of applications. Based on the representation, two major causes of dissonance are identified: logic differences and sensor error. Additionally, several possible types of dissonance are identified. A mathematical analysis method is developed to identify the conditions for dissonance originating from logic differences. A probabilistic analysis methodology is developed to estimate the probability of dissonance originating from sensor error, and to compare the relative contribution to dissonance of sensor error against the contribution from logic differences. A hybrid model, which describes the dynamic behavior of the process with multiple alerting systems, is developed to identify dangerous dissonance space, from which the process can lead to disaster. Methodologies to avoid or mitigate dissonance are outlined. Two examples are used to demonstrate the application of the methodology. First, a conceptual In-Trail Spacing example is presented. The methodology is applied to identify the conditions for possible dissonance, to identify relative contribution of logic difference and sensor error, and to identify dangerous dissonance space. Several proposed mitigation methods are demonstrated in this example. In the second example, the methodology is applied to address the dissonance problem between two air traffic alert and avoidance systems: the existing Traffic Alert and Collision Avoidance System (TCAS) vs. the proposed Airborne Conflict Management system (ACM). Conditions on ACM resolution maneuvers are identified to avoid dynamic dissonance between TCAS and ACM. Also included in this report is an Appendix written by Lee Winder about recent and continuing work on alerting systems design. The application of Markov Decision Process (MDP) theory to complex alerting problems is discussed and illustrated with an abstract example system.

Protein detection through different platforms of immuno-loop-mediated isothermal amplification

NASA Astrophysics Data System (ADS)

Pourhassan-Moghaddam, Mohammad; Rahmati-Yamchi, Mohammad; Akbarzadeh, Abolfazl; Daraee, Hadis; Nejati-Koshki, Kazem; Hanifehpour, Younes; Joo, Sang Woo

2013-11-01

Different immunoassay-based methods have been devised to detect protein targets. These methods have some challenges that make them inefficient for assaying ultra-low-amounted proteins. ELISA, iPCR, iRCA, and iNASBA are the common immunoassay-based methods of protein detection, each of which has specific and common technical challenges making it necessary to introduce a novel method in order to avoid their problems for detection of target proteins. Here we propose a new method nominated as `immuno-loop-mediated isothermal amplification' or `iLAMP'. This new method is free from the problems of the previous methods and has significant advantages over them. In this paper we also offer various configurations in order to improve the applicability of this method in real-world sample analyses. Important potential applications of this method are stated as well.

Unified method to integrate and blend several, potentially related, sources of information for genetic evaluation.

PubMed

Vandenplas, Jérémie; Colinet, Frederic G; Gengler, Nicolas

2014-09-30

A condition to predict unbiased estimated breeding values by best linear unbiased prediction is to use simultaneously all available data. However, this condition is not often fully met. For example, in dairy cattle, internal (i.e. local) populations lead to evaluations based only on internal records while widely used foreign sires have been selected using internally unavailable external records. In such cases, internal genetic evaluations may be less accurate and biased. Because external records are unavailable, methods were developed to combine external information that summarizes these records, i.e. external estimated breeding values and associated reliabilities, with internal records to improve accuracy of internal genetic evaluations. Two issues of these methods concern double-counting of contributions due to relationships and due to records. These issues could be worse if external information came from several evaluations, at least partially based on the same records, and combined into a single internal evaluation. Based on a Bayesian approach, the aim of this research was to develop a unified method to integrate and blend simultaneously several sources of information into an internal genetic evaluation by avoiding double-counting of contributions due to relationships and due to records. This research resulted in equations that integrate and blend simultaneously several sources of information and avoid double-counting of contributions due to relationships and due to records. The performance of the developed equations was evaluated using simulated and real datasets. The results showed that the developed equations integrated and blended several sources of information well into a genetic evaluation. The developed equations also avoided double-counting of contributions due to relationships and due to records. Furthermore, because all available external sources of information were correctly propagated, relatives of external animals benefited from the integrated information and, therefore, more reliable estimated breeding values were obtained. The proposed unified method integrated and blended several sources of information well into a genetic evaluation by avoiding double-counting of contributions due to relationships and due to records. The unified method can also be extended to other types of situations such as single-step genomic or multi-trait evaluations, combining information across different traits.

Zero-fringe demodulation method based on location-dependent birefringence dispersion in polarized low-coherence interferometry.

PubMed

Wang, Shuang; Liu, Tiegen; Jiang, Junfeng; Liu, Kun; Yin, Jinde; Qin, Zunqi; Zou, Shengliang

2014-04-01

We present a high precision and fast speed demodulation method for a polarized low-coherence interferometer with location-dependent birefringence dispersion. Based on the characteristics of location-dependent birefringence dispersion and five-step phase-shifting technology, the method accurately retrieves the peak position of zero-fringe at the central wavelength, which avoids the fringe order ambiguity. The method processes data only in the spatial domain and reduces the computational load greatly. We successfully demonstrated the effectiveness of the proposed method in an optical fiber Fabry-Perot barometric pressure sensing experiment system. Measurement precision of 0.091 kPa was realized in the pressure range of 160 kPa, and computation time was improved by 10 times compared to the traditional phase-based method that requires Fourier transform operation.

Dictionary learning-based spatiotemporal regularization for 3D dense speckle tracking

NASA Astrophysics Data System (ADS)

Lu, Allen; Zontak, Maria; Parajuli, Nripesh; Stendahl, John C.; Boutagy, Nabil; Eberle, Melissa; O'Donnell, Matthew; Sinusas, Albert J.; Duncan, James S.

2017-03-01

Speckle tracking is a common method for non-rigid tissue motion analysis in 3D echocardiography, where unique texture patterns are tracked through the cardiac cycle. However, poor tracking often occurs due to inherent ultrasound issues, such as image artifacts and speckle decorrelation; thus regularization is required. Various methods, such as optical flow, elastic registration, and block matching techniques have been proposed to track speckle motion. Such methods typically apply spatial and temporal regularization in a separate manner. In this paper, we propose a joint spatiotemporal regularization method based on an adaptive dictionary representation of the dense 3D+time Lagrangian motion field. Sparse dictionaries have good signal adaptive and noise-reduction properties; however, they are prone to quantization errors. Our method takes advantage of the desirable noise suppression, while avoiding the undesirable quantization error. The idea is to enforce regularization only on the poorly tracked trajectories. Specifically, our method 1.) builds data-driven 4-dimensional dictionary of Lagrangian displacements using sparse learning, 2.) automatically identifies poorly tracked trajectories (outliers) based on sparse reconstruction errors, and 3.) performs sparse reconstruction of the outliers only. Our approach can be applied on dense Lagrangian motion fields calculated by any method. We demonstrate the effectiveness of our approach on a baseline block matching speckle tracking and evaluate performance of the proposed algorithm using tracking and strain accuracy analysis.

Magnetic Field Analysis of Lorentz Motors Using a Novel Segmented Magnetic Equivalent Circuit Method

PubMed Central

Qian, Junbing; Chen, Xuedong; Chen, Han; Zeng, Lizhan; Li, Xiaoqing

2013-01-01

A simple and accurate method based on the magnetic equivalent circuit (MEC) model is proposed in this paper to predict magnetic flux density (MFD) distribution of the air-gap in a Lorentz motor (LM). In conventional MEC methods, the permanent magnet (PM) is treated as one common source and all branches of MEC are coupled together to become a MEC network. In our proposed method, every PM flux source is divided into three sub-sections (the outer, the middle and the inner). Thus, the MEC of LM is divided correspondingly into three independent sub-loops. As the size of the middle sub-MEC is small enough, it can be treated as an ideal MEC and solved accurately. Combining with decoupled analysis of outer and inner MECs, MFD distribution in the air-gap can be approximated by a quadratic curve, and the complex calculation of reluctances in MECs can be avoided. The segmented magnetic equivalent circuit (SMEC) method is used to analyze a LM, and its effectiveness is demonstrated by comparison with FEA, conventional MEC and experimental results. PMID:23358368

Spreading to localized targets in complex networks

NASA Astrophysics Data System (ADS)

Sun, Ye; Ma, Long; Zeng, An; Wang, Wen-Xu

2016-12-01

As an important type of dynamics on complex networks, spreading is widely used to model many real processes such as the epidemic contagion and information propagation. One of the most significant research questions in spreading is to rank the spreading ability of nodes in the network. To this end, substantial effort has been made and a variety of effective methods have been proposed. These methods usually define the spreading ability of a node as the number of finally infected nodes given that the spreading is initialized from the node. However, in many real cases such as advertising and news propagation, the spreading only aims to cover a specific group of nodes. Therefore, it is necessary to study the spreading ability of nodes towards localized targets in complex networks. In this paper, we propose a reversed local path algorithm for this problem. Simulation results show that our method outperforms the existing methods in identifying the influential nodes with respect to these localized targets. Moreover, the influential spreaders identified by our method can effectively avoid infecting the non-target nodes in the spreading process.

Ranking Support Vector Machine with Kernel Approximation

PubMed Central

Dou, Yong

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms. PMID:28293256

Ranking Support Vector Machine with Kernel Approximation.

PubMed

Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Guided filter-based fusion method for multiexposure images

NASA Astrophysics Data System (ADS)

Hou, Xinglin; Luo, Haibo; Qi, Feng; Zhou, Peipei

2016-11-01

It is challenging to capture a high-dynamic range (HDR) scene using a low-dynamic range camera. A weighted sum-based image fusion (IF) algorithm is proposed so as to express an HDR scene with a high-quality image. This method mainly includes three parts. First, two image features, i.e., gradients and well-exposedness are measured to estimate the initial weight maps. Second, the initial weight maps are refined by a guided filter, in which the source image is considered as the guidance image. This process could reduce the noise in initial weight maps and preserve more texture consistent with the original images. Finally, the fused image is constructed by a weighted sum of source images in the spatial domain. The main contributions of this method are the estimation of the initial weight maps and the appropriate use of the guided filter-based weight maps refinement. It provides accurate weight maps for IF. Compared to traditional IF methods, this algorithm avoids image segmentation, combination, and the camera response curve calibration. Furthermore, experimental results demonstrate the superiority of the proposed method in both subjective and objective evaluations.

High-Frequency Subband Compressed Sensing MRI Using Quadruplet Sampling

PubMed Central

Sung, Kyunghyun; Hargreaves, Brian A

2013-01-01

Purpose To presents and validates a new method that formalizes a direct link between k-space and wavelet domains to apply separate undersampling and reconstruction for high- and low-spatial-frequency k-space data. Theory and Methods High- and low-spatial-frequency regions are defined in k-space based on the separation of wavelet subbands, and the conventional compressed sensing (CS) problem is transformed into one of localized k-space estimation. To better exploit wavelet-domain sparsity, CS can be used for high-spatial-frequency regions while parallel imaging can be used for low-spatial-frequency regions. Fourier undersampling is also customized to better accommodate each reconstruction method: random undersampling for CS and regular undersampling for parallel imaging. Results Examples using the proposed method demonstrate successful reconstruction of both low-spatial-frequency content and fine structures in high-resolution 3D breast imaging with a net acceleration of 11 to 12. Conclusion The proposed method improves the reconstruction accuracy of high-spatial-frequency signal content and avoids incoherent artifacts in low-spatial-frequency regions. This new formulation also reduces the reconstruction time due to the smaller problem size. PMID:23280540

A multiple distributed representation method based on neural network for biomedical event extraction.

PubMed

Wang, Anran; Wang, Jian; Lin, Hongfei; Zhang, Jianhai; Yang, Zhihao; Xu, Kan

2017-12-20

Biomedical event extraction is one of the most frontier domains in biomedical research. The two main subtasks of biomedical event extraction are trigger identification and arguments detection which can both be considered as classification problems. However, traditional state-of-the-art methods are based on support vector machine (SVM) with massive manually designed one-hot represented features, which require enormous work but lack semantic relation among words. In this paper, we propose a multiple distributed representation method for biomedical event extraction. The method combines context consisting of dependency-based word embedding, and task-based features represented in a distributed way as the input of deep learning models to train deep learning models. Finally, we used softmax classifier to label the example candidates. The experimental results on Multi-Level Event Extraction (MLEE) corpus show higher F-scores of 77.97% in trigger identification and 58.31% in overall compared to the state-of-the-art SVM method. Our distributed representation method for biomedical event extraction avoids the problems of semantic gap and dimension disaster from traditional one-hot representation methods. The promising results demonstrate that our proposed method is effective for biomedical event extraction.

Flip-avoiding interpolating surface registration for skull reconstruction.

PubMed

Xie, Shudong; Leow, Wee Kheng; Lee, Hanjing; Lim, Thiam Chye

2018-03-30

Skull reconstruction is an important and challenging task in craniofacial surgery planning, forensic investigation and anthropological studies. Existing methods typically reconstruct approximating surfaces that regard corresponding points on the target skull as soft constraints, thus incurring non-zero error even for non-defective parts and high overall reconstruction error. This paper proposes a novel geometric reconstruction method that non-rigidly registers an interpolating reference surface that regards corresponding target points as hard constraints, thus achieving low reconstruction error. To overcome the shortcoming of interpolating a surface, a flip-avoiding method is used to detect and exclude conflicting hard constraints that would otherwise cause surface patches to flip and self-intersect. Comprehensive test results show that our method is more accurate and robust than existing skull reconstruction methods. By incorporating symmetry constraints, it can produce more symmetric and normal results than other methods in reconstructing defective skulls with a large number of defects. It is robust against severe outliers such as radiation artifacts in computed tomography due to dental implants. In addition, test results also show that our method outperforms thin-plate spline for model resampling, which enables the active shape model to yield more accurate reconstruction results. As the reconstruction accuracy of defective parts varies with the use of different reference models, we also study the implication of reference model selection for skull reconstruction. Copyright © 2018 John Wiley & Sons, Ltd.

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles

PubMed Central

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently. PMID:28255297

Electromagnetic panel deployment and retraction using the geomagnetic field in LEO satellite missions

NASA Astrophysics Data System (ADS)

Inamori, Takaya; Sugawara, Yoshiki; Satou, Yasutaka

2015-12-01

Increasingly, spacecraft are installed with large-area structures that are extended and deployed post-launch. These extensible structures have been applied in several missions for power generation, thermal radiation, and solar propulsion. Here, we propose a deployment and retraction method using the electromagnetic force generated when the geomagnetic field interacts with electric current flowing on extensible panels. The panels are installed on a satellite in low Earth orbit. Specifically, electrical wires placed on the extensible panels generate magnetic moments, which interfere with the geomagnetic field. The resulting repulsive and retraction forces enable panel deployment and retraction. In the proposed method, a satellite realizes structural deployment using simple electrical wires. Furthermore, the satellite can achieve not only deployment but also retraction for avoiding damage from space debris and for agile attitude maneuvers. Moreover, because the proposed method realizes quasi-static deployment and the retraction of panels by electromagnetic forces, low impulsive force is exerted on fragile panels. The electrical wires can also be used to detect the panel deployment and retraction and generate a large magnetic moment for attitude control. The proposed method was assessed in numerical simulations based on multibody dynamics. Simulation results shows that a small cubic satellite with a wire current of 25 AT deployed 4 panels (20 cm × 20 cm) in 500 s and retracted 4 panels in 100 s.

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles.

PubMed

Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.

Unconstrained and Noninvasive Measurement of Swimming Behavior of Small Fish Based on Ventilatory Signals

NASA Astrophysics Data System (ADS)

Kitayama, Shigehisa; Soh, Zu; Hirano, Akira; Tsuji, Toshio; Takiguchi, Noboru; Ohtake, Hisao

Ventilatory signal is a kind of bioelectric signals reflecting the ventilatory conditions of fish, and has received recent attention as an indicator for assessment of water quality, since breathing is adjusted by the respiratory center according to changes in the underwater environment surrounding the fish. The signals are thus beginning to be used in bioassay systems for water examination. Other than ventilatory conditions, swimming behavior also contains important information for water examination. The conventional bioassay systems, however, only measure either ventilatory signals or swimming behavior. This paper proposes a new unconstrained and noninvasive measurement method that is capable of conducting ventilatory signal measurement and behavioral analysis of fish at the same time. The proposed method estimates the position and the velocity of a fish in free-swimming conditions using power spectrum distribution of measured ventilatory signals from multiple electrodes. This allowed the system to avoid using a camera system which requires light sources. In order to validate estimation accuracy, the position and the velocity estimated by the proposed method were compared to those obtained from video analysis. The results confirmed that the estimated error of the fish positions was within the size of fish, and the correlation coefficient between the velocities was 0.906. The proposed method thus not only can measure the ventilatory signals, but also performs behavioral analysis as accurate as using a video camera.

Reinforcement learning algorithms for robotic navigation in dynamic environments.

PubMed

Yen, Gary G; Hickey, Travis W

2004-04-01

The purpose of this study was to examine improvements to reinforcement learning (RL) algorithms in order to successfully interact within dynamic environments. The scope of the research was that of RL algorithms as applied to robotic navigation. Proposed improvements include: addition of a forgetting mechanism, use of feature based state inputs, and hierarchical structuring of an RL agent. Simulations were performed to evaluate the individual merits and flaws of each proposal, to compare proposed methods to prior established methods, and to compare proposed methods to theoretically optimal solutions. Incorporation of a forgetting mechanism did considerably improve the learning times of RL agents in a dynamic environment. However, direct implementation of a feature-based RL agent did not result in any performance enhancements, as pure feature-based navigation results in a lack of positional awareness, and the inability of the agent to determine the location of the goal state. Inclusion of a hierarchical structure in an RL agent resulted in significantly improved performance, specifically when one layer of the hierarchy included a feature-based agent for obstacle avoidance, and a standard RL agent for global navigation. In summary, the inclusion of a forgetting mechanism, and the use of a hierarchically structured RL agent offer substantially increased performance when compared to traditional RL agents navigating in a dynamic environment.

Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks

NASA Astrophysics Data System (ADS)

Zhu, Shijia; Wang, Yadong

2015-12-01

Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is ‘stationarity’, and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings.

Research on Acceleration Compensation Strategy of Electric Vehicle Based on Fuzzy Control Theory

NASA Astrophysics Data System (ADS)

Zhu, Tianjun; Li, Bin; Zong, Changfu; Wei, Zhicheng

2017-09-01

Nowadays, the driving technology of electric vehicle is developing rapidly. There are many kinds of methods in driving performance control technology. The paper studies the acceleration performance of electric vehicle. Under the premise of energy management, an acceleration power compensation method by fuzzy control theory based on driver intention recognition is proposed, which can meet the driver’s subjective feelings better. It avoids the problem that the pedal opening and power output are single correspondence when the traditional vehicle accelerates. Through the simulation test, this method can significantly improve the performance of acceleration and output torque smoothly in non-emergency acceleration to ensure vehicle comfortable and stable.

A Principled Way of Assessing Visualization Literacy.

PubMed

Boy, Jeremy; Rensink, Ronald A; Bertini, Enrico; Fekete, Jean-Daniel

2014-12-01

We describe a method for assessing the visualization literacy (VL) of a user. Assessing how well people understand visualizations has great value for research (e. g., to avoid confounds), for design (e. g., to best determine the capabilities of an audience), for teaching (e. g., to assess the level of new students), and for recruiting (e. g., to assess the level of interviewees). This paper proposes a method for assessing VL based on Item Response Theory. It describes the design and evaluation of two VL tests for line graphs, and presents the extension of the method to bar charts and scatterplots. Finally, it discusses the reimplementation of these tests for fast, effective, and scalable web-based use.

Exact solitary wave solution for higher order nonlinear Schrodinger equation using He's variational iteration method

NASA Astrophysics Data System (ADS)

Rani, Monika; Bhatti, Harbax S.; Singh, Vikramjeet

2017-11-01

In optical communication, the behavior of the ultrashort pulses of optical solitons can be described through nonlinear Schrodinger equation. This partial differential equation is widely used to contemplate a number of physically important phenomena, including optical shock waves, laser and plasma physics, quantum mechanics, elastic media, etc. The exact analytical solution of (1+n)-dimensional higher order nonlinear Schrodinger equation by He's variational iteration method has been presented. Our proposed solutions are very helpful in studying the solitary wave phenomena and ensure rapid convergent series and avoid round off errors. Different examples with graphical representations have been given to justify the capability of the method.

Counterfactual Consent and the Use of Deception in Research.

PubMed

Wilson, Alan T

2015-09-01

The use of deception for the purposes of research is a widespread practice within many areas of study. If we want to avoid either absolute acceptance or absolute rejection of this practice then we require some method of distinguishing between those uses of deception which are morally acceptable and those which are not. In this article I discuss the concept of counterfactual consent, and propose a related distinction between counterfactual-defeating deception and counterfactual-compatible deception. The aim is to show that this proposed distinction will be useful in furthering the debate regarding the use of deception for the purposes of research. © 2014 The Authors. Bioethics published by John Wiley & Sons Ltd.

Underwater video enhancement using multi-camera super-resolution

NASA Astrophysics Data System (ADS)

Quevedo, E.; Delory, E.; Callicó, G. M.; Tobajas, F.; Sarmiento, R.

2017-12-01

Image spatial resolution is critical in several fields such as medicine, communications or satellite, and underwater applications. While a large variety of techniques for image restoration and enhancement has been proposed in the literature, this paper focuses on a novel Super-Resolution fusion algorithm based on a Multi-Camera environment that permits to enhance the quality of underwater video sequences without significantly increasing computation. In order to compare the quality enhancement, two objective quality metrics have been used: PSNR (Peak Signal-to-Noise Ratio) and the SSIM (Structural SIMilarity) index. Results have shown that the proposed method enhances the objective quality of several underwater sequences, avoiding the appearance of undesirable artifacts, with respect to basic fusion Super-Resolution algorithms.

Adaptive Formation Control of Electrically Driven Nonholonomic Mobile Robots With Limited Information.

PubMed

Bong Seok Park; Jin Bae Park; Yoon Ho Choi

2011-08-01

We present a leader-follower-based adaptive formation control method for electrically driven nonholonomic mobile robots with limited information. First, an adaptive observer is developed under the condition that the velocity measurement is not available. With the proposed adaptive observer, the formation control part is designed to achieve the desired formation and guarantee the collision avoidance. In addition, neural network is employed to compensate the actuator saturation, and the projection algorithm is used to estimate the velocity information of the leader. It is shown, by using the Lyapunov theory, that all errors of the closed-loop system are uniformly ultimately bounded. Simulation results are presented to illustrate the performance of the proposed control system.

A method of inferring collision ratio based on maneuverability of own ship under critical collision conditions

NASA Astrophysics Data System (ADS)

You, Youngjun; Rhee, Key-Pyo; Ahn, Kyoungsoo

2013-06-01

In constructing a collision avoidance system, it is important to determine the time for starting collision avoidance maneuver. Many researchers have attempted to formulate various indices by applying a range of techniques. Among these indices, collision risk obtained by combining Distance to the Closest Point of Approach (DCPA) and Time to the Closest Point of Approach (TCPA) information with fuzzy theory is mostly used. However, the collision risk has a limit, in that membership functions of DCPA and TCPA are empirically determined. In addition, the collision risk is not able to consider several critical collision conditions where the target ship fails to take appropriate actions. It is therefore necessary to design a new concept based on logical approaches. In this paper, a collision ratio is proposed, which is the expected ratio of unavoidable paths to total paths under suitably characterized operation conditions. Total paths are determined by considering categories such as action space and methodology of avoidance. The International Regulations for Preventing Collisions at Sea (1972) and collision avoidance rules (2001) are considered to solve the slower ship's dilemma. Different methods which are based on a constant speed model and simulated speed model are used to calculate the relative positions between own ship and target ship. In the simulated speed model, fuzzy control is applied to determination of command rudder angle. At various encounter situations, the time histories of the collision ratio based on the simulated speed model are compared with those based on the constant speed model.

Bilateral accessory breast tissue of the vulva: a case report introducing a novel labiaplasty technique.

PubMed

Wagner, I Janelle; Damitz, Lynn A; Carey, Erin; Zolnoun, Denniz

2013-05-01

We present the case of a 23-year-old female with bilateral ectopic breast tissue of the vulva, the repair of which necessitated a novel labiaplasty technique. Labiaplasty is becoming an increasingly frequent cosmetic procedure, and the popularity of brief didactic labiaplasty courses has risen in response to consumer demand. There is a paucity of detailed anatomic description of female sensory innervation patterns to the clitoris and surrounding structures. This places patients at risk for denervation of clitoral structures during labiaplasty procedures. Our novel technique proposes a method of individualized patient neurosensory mapping preoperatively, which allows for surgical planning to avoid injury to the sensory branches of the dorsal clitoral nerve. A 23-year-old female presented with bilateral vulvar masses that involved the clitoral complex, which had first become apparent during the second trimester of pregnancy, and failed to resolve in the postpartum period. We describe the preoperative planning and intraoperative approach and dissection to labiaplasty in this patient, which was complex given the size of the masses, and specifically designed to avoid injury to sensory branches of the dorsal clitoral nerve. As labiaplasty becomes more common, it is important to approach labiaplasty patients with a detailed understanding of the sensory innervation of the clitoris and surrounding structures, to avoid nerve injury and resultant sexual dysfunction. Traditional labiaplasty approaches may violate the sensory innervation patterns of the clitoral region, thus causing a sensory loss that affects patient sexual function. Our novel approach to preoperative clitoral nerve sensory mapping provides an alternative method of labiaplasty that may avoid denervation injury.

Improving estimates of genetic maps: a meta-analysis-based approach.

PubMed

Stewart, William C L

2007-07-01

Inaccurate genetic (or linkage) maps can reduce the power to detect linkage, increase type I error, and distort haplotype and relationship inference. To improve the accuracy of existing maps, I propose a meta-analysis-based method that combines independent map estimates into a single estimate of the linkage map. The method uses the variance of each independent map estimate to combine them efficiently, whether the map estimates use the same set of markers or not. As compared with a joint analysis of the pooled genotype data, the proposed method is attractive for three reasons: (1) it has comparable efficiency to the maximum likelihood map estimate when the pooled data are homogeneous; (2) relative to existing map estimation methods, it can have increased efficiency when the pooled data are heterogeneous; and (3) it avoids the practical difficulties of pooling human subjects data. On the basis of simulated data modeled after two real data sets, the proposed method can reduce the sampling variation of linkage maps commonly used in whole-genome linkage scans. Furthermore, when the independent map estimates are also maximum likelihood estimates, the proposed method performs as well as or better than when they are estimated by the program CRIMAP. Since variance estimates of maps may not always be available, I demonstrate the feasibility of three different variance estimators. Overall, the method should prove useful to investigators who need map positions for markers not contained in publicly available maps, and to those who wish to minimize the negative effects of inaccurate maps. Copyright 2007 Wiley-Liss, Inc.

Safety and Convergence Analysis of Intersecting Aircraft Flows Under Decentralized Collision Avoidance

NASA Astrophysics Data System (ADS)

Dallal, Ahmed H.

Safety is an essential requirement for air traffic management and control systems. Aircraft are not allowed to get closer to each other than a specified safety distance, to avoid any conflicts and collisions between aircraft. Forecast analysis predicts a tremendous increase in the number of flights. Subsequently, automated tools are needed to help air traffic controllers resolve air born conflicts. In this dissertation, we consider the problem of conflict resolution of aircraft flows with the assumption that aircraft are flowing through a fixed specified control volume at a constant speed. In this regard, several centralized and decentralized resolution rules have been proposed for path planning and conflict avoidance. For the case of two intersecting flows, we introduce the concept of conflict touches, and a collaborative decentralized conflict resolution rule is then proposed and analyzed for two intersecting flows. The proposed rule is also able to resolved airborne conflicts that resulted from resolving another conflict via the domino effect. We study the safety conditions under the proposed conflict resolution and collision avoidance rule. Then, we use Lyapunov analysis to analytically prove the convergence of conflict resolution dynamics under the proposed rule. The analysis show that, under the proposed conflict resolution rule, the system of intersecting aircraft flows is guaranteed to converge to safe, conflict free, trajectories within a bounded time. Simulations are provided to verify the analytically derived conclusions and study the convergence of the conflict resolution dynamics at different encounter angles. Simulation results show that lateral deviations taken by aircraft in each flow, to resolve conflicts, are bounded, and aircraft converged to safe and conflict free trajectories, within a finite time.

SGM-based seamline determination for urban orthophoto mosaicking

NASA Astrophysics Data System (ADS)

Pang, Shiyan; Sun, Mingwei; Hu, Xiangyun; Zhang, Zuxun

2016-02-01

Mosaicking is a key step in the production of digital orthophoto maps (DOMs), especially for large-scale urban orthophotos. During this step, manual intervention is commonly involved to avoid the case where the seamline crosses obvious objects (e.g., buildings), which causes geometric discontinuities on the DOMs. How to guide the seamline to avoid crossing obvious objects has become a popular topic in the field of photogrammetry and remote sensing. Thus, a new semi-global matching (SGM)-based method to guide seamline determination is proposed for urban orthophoto mosaicking in this study, which can greatly eliminate geometric discontinuities. The approximate epipolar geometry of the orthophoto pairs is first derived and proven, and the approximate epipolar image pair is then generated by rotating the two orthorectified images according to the parallax direction. A SGM algorithm is applied to their overlaps to obtain the corresponding pixel-wise disparity. According to a predefined disparity threshold, the overlap area is identified as the obstacle and non-obstacle areas. For the non-obstacle regions, Hilditch thinning algorithm is used to obtain the skeleton line, followed by Dijkstra's algorithm to search for the optimal path on the skeleton network as the seamline between two orthophotos. A whole seamline network is constructed based on the strip information recorded in flight. In the experimental section, the approximate epipolar geometric theory of the orthophoto is first analyzed and verified, and the effectiveness of the proposed method is then validated by comparing its results with the results of the geometry-based, OrthoVista, and orthoimage elevation synchronous model (OESM)-based methods.

Integrated design of multivariable hydrometric networks using entropy theory with a multiobjective optimization approach

NASA Astrophysics Data System (ADS)

Kim, Y.; Hwang, T.; Vose, J. M.; Martin, K. L.; Band, L. E.

2016-12-01

Obtaining quality hydrologic observations is the first step towards a successful water resources management. While remote sensing techniques have enabled to convert satellite images of the Earth's surface to hydrologic data, the importance of ground-based observations has never been diminished because in-situ data are often highly accurate and can be used to validate remote measurements. The existence of efficient hydrometric networks is becoming more important to obtain as much as information with minimum redundancy. The World Meteorological Organization (WMO) has recommended a guideline for the minimum hydrometric network density based on physiography; however, this guideline is not for the optimum network design but for avoiding serious deficiency from a network. Moreover, all hydrologic variables are interconnected within the hydrologic cycle, while monitoring networks have been designed individually. This study proposes an integrated network design method using entropy theory with a multiobjective optimization approach. In specific, a precipitation and a streamflow networks in a semi-urban watershed in Ontario, Canada were designed simultaneously by maximizing joint entropy, minimizing total correlation, and maximizing conditional entropy of streamflow network given precipitation network. After comparing with the typical individual network designs, the proposed design method would be able to determine more efficient optimal networks by avoiding the redundant stations, in which hydrologic information is transferable. Additionally, four quantization cases were applied in entropy calculations to assess their implications on the station rankings and the optimal networks. The results showed that the selection of quantization method should be considered carefully because the rankings and optimal networks are subject to change accordingly.

Integrated design of multivariable hydrometric networks using entropy theory with a multiobjective optimization approach

NASA Astrophysics Data System (ADS)

Keum, J.; Coulibaly, P. D.

2017-12-01

Obtaining quality hydrologic observations is the first step towards a successful water resources management. While remote sensing techniques have enabled to convert satellite images of the Earth's surface to hydrologic data, the importance of ground-based observations has never been diminished because in-situ data are often highly accurate and can be used to validate remote measurements. The existence of efficient hydrometric networks is becoming more important to obtain as much as information with minimum redundancy. The World Meteorological Organization (WMO) has recommended a guideline for the minimum hydrometric network density based on physiography; however, this guideline is not for the optimum network design but for avoiding serious deficiency from a network. Moreover, all hydrologic variables are interconnected within the hydrologic cycle, while monitoring networks have been designed individually. This study proposes an integrated network design method using entropy theory with a multiobjective optimization approach. In specific, a precipitation and a streamflow networks in a semi-urban watershed in Ontario, Canada were designed simultaneously by maximizing joint entropy, minimizing total correlation, and maximizing conditional entropy of streamflow network given precipitation network. After comparing with the typical individual network designs, the proposed design method would be able to determine more efficient optimal networks by avoiding the redundant stations, in which hydrologic information is transferable. Additionally, four quantization cases were applied in entropy calculations to assess their implications on the station rankings and the optimal networks. The results showed that the selection of quantization method should be considered carefully because the rankings and optimal networks are subject to change accordingly.

An ultrasonic sensor system based on a two-dimensional state method for highway vehicle violation detection applications.

PubMed

Liu, Jun; Han, Jiuqiang; Lv, Hongqiang; Li, Bing

2015-04-16

With the continuing growth of highway construction and vehicle use expansion all over the world, highway vehicle traffic rule violation (TRV) detection has become more and more important so as to avoid traffic accidents and injuries in intelligent transportation systems (ITS) and vehicular ad hoc networks (VANETs). Since very few works have contributed to solve the TRV detection problem by moving vehicle measurements and surveillance devices, this paper develops a novel parallel ultrasonic sensor system that can be used to identify the TRV behavior of a host vehicle in real-time. Then a two-dimensional state method is proposed, utilizing the spacial state and time sequential states from the data of two parallel ultrasonic sensors to detect and count the highway vehicle violations. Finally, the theoretical TRV identification probability is analyzed, and actual experiments are conducted on different highway segments with various driving speeds, which indicates that the identification accuracy of the proposed method can reach about 90.97%.

An Ultrasonic Sensor System Based on a Two-Dimensional State Method for Highway Vehicle Violation Detection Applications

PubMed Central

Liu, Jun; Han, Jiuqiang; Lv, Hongqiang; Li, Bing

2015-01-01

With the continuing growth of highway construction and vehicle use expansion all over the world, highway vehicle traffic rule violation (TRV) detection has become more and more important so as to avoid traffic accidents and injuries in intelligent transportation systems (ITS) and vehicular ad hoc networks (VANETs). Since very few works have contributed to solve the TRV detection problem by moving vehicle measurements and surveillance devices, this paper develops a novel parallel ultrasonic sensor system that can be used to identify the TRV behavior of a host vehicle in real-time. Then a two-dimensional state method is proposed, utilizing the spacial state and time sequential states from the data of two parallel ultrasonic sensors to detect and count the highway vehicle violations. Finally, the theoretical TRV identification probability is analyzed, and actual experiments are conducted on different highway segments with various driving speeds, which indicates that the identification accuracy of the proposed method can reach about 90.97%. PMID:25894940

Image inpainting and super-resolution using non-local recursive deep convolutional network with skip connections

NASA Astrophysics Data System (ADS)

Liu, Miaofeng

2017-07-01

In recent years, deep convolutional neural networks come into use in image inpainting and super-resolution in many fields. Distinct to most of the former methods requiring to know beforehand the local information for corrupted pixels, we propose a 20-depth fully convolutional network to learn an end-to-end mapping a dataset of damaged/ground truth subimage pairs realizing non-local blind inpainting and super-resolution. As there often exist image with huge corruptions or inpainting on a low-resolution image that the existing approaches unable to perform well, we also share parameters in local area of layers to achieve spatial recursion and enlarge the receptive field. To avoid the difficulty of training this deep neural network, skip-connections between symmetric convolutional layers are designed. Experimental results shows that the proposed method outperforms state-of-the-art methods for diverse corrupting and low-resolution conditions, it works excellently when realizing super-resolution and image inpainting simultaneously

Flexible fabrication of biomimetic compound eye array via two-step thermal reflow of simply pre-modeled hierarchic microstructures

NASA Astrophysics Data System (ADS)

Huang, Shengzhou; Li, Mujun; Shen, Lianguan; Qiu, Jinfeng; Zhou, Youquan

2017-06-01

A flexible fabrication method for the biomimetic compound eye (BCE) array is proposed. In this method, a triple-layer sandwich-like coating configuration was introduced, and the required hierarchic microstructures are formed with a simple single-scan exposure in maskless digital lithography. Taking advantage of the difference of glass transition point (Tg) between photoresists of each layer, the pre-formed hierarchic microstructures are in turn reflowed to the curved substrate and the BCE ommatidia in a two-step thermal reflow process. To avoid affecting the spherical substrate formed in the first thermal reflow, a non-contact strategy was proposed in the second reflow process. The measurement results were in good agreement with the designed BCE profiles. Results also showed that the fabricated BCE had good performances in optical test. The presented method is flexible, convenient, low-cost and can easily adapt to the fabrications of other optical elements with hierarchic microstructures.

De-optical-line-terminal hybrid access-aggregation optical network for time-sensitive services based on software-defined networking orchestration

NASA Astrophysics Data System (ADS)

Bai, Wei; Yang, Hui; Xiao, Hongyun; Yu, Ao; He, Linkuan; Zhang, Jie; Li, Zhen; Du, Yi

2017-11-01

With the increase in varieties of services in network, time-sensitive services (TSSs) appear and bring forward an impending need for delay performance. Ultralow-latency communication has become one of the important development goals for many scenarios in the coming 5G era (e.g., robotics and driverless cars). However, the conventional methods, which decrease delay by promoting the available resources and the network transmission speed, have limited effect; a new breakthrough for ultralow-latency communication is necessary. We propose a de-optical-line-terminal (De-OLT) hybrid access-aggregation optical network (DAON) for TSS based on software-defined networking (SDN) orchestration. In this network, low-latency all-optical communication based on optical burst switching can be achieved by removing OLT. For supporting this network and guaranteeing the quality of service for TSSs, we design SDN-driven control method and service provision method. Numerical results demonstrate the proposed DAON promotes network service efficiency and avoids traffic congestion.

Separation of left and right lungs using 3D information of sequential CT images and a guided dynamic programming algorithm

PubMed Central

Park, Sang Cheol; Leader, Joseph Ken; Tan, Jun; Lee, Guee Sang; Kim, Soo Hyung; Na, In Seop; Zheng, Bin

2011-01-01

Objective this article presents a new computerized scheme that aims to accurately and robustly separate left and right lungs on CT examinations. Methods we developed and tested a method to separate the left and right lungs using sequential CT information and a guided dynamic programming algorithm using adaptively and automatically selected start point and end point with especially severe and multiple connections. Results the scheme successfully identified and separated all 827 connections on the total 4034 CT images in an independent testing dataset of CT examinations. The proposed scheme separated multiple connections regardless of their locations, and the guided dynamic programming algorithm reduced the computation time to approximately 4.6% in comparison with the traditional dynamic programming and avoided the permeation of the separation boundary into normal lung tissue. Conclusions The proposed method is able to robustly and accurately disconnect all connections between left and right lungs and the guided dynamic programming algorithm is able to remove redundant processing. PMID:21412104

Statistical analysis on the signals monitoring multiphase flow patterns in pipeline-riser system

NASA Astrophysics Data System (ADS)

Ye, Jing; Guo, Liejin

2013-07-01

The signals monitoring petroleum transmission pipeline in offshore oil industry usually contain abundant information about the multiphase flow on flow assurance which includes the avoidance of most undesirable flow pattern. Therefore, extracting reliable features form these signals to analyze is an alternative way to examine the potential risks to oil platform. This paper is focused on characterizing multiphase flow patterns in pipeline-riser system that is often appeared in offshore oil industry and finding an objective criterion to describe the transition of flow patterns. Statistical analysis on pressure signal at the riser top is proposed, instead of normal prediction method based on inlet and outlet flow conditions which could not be easily determined during most situations. Besides, machine learning method (least square supported vector machine) is also performed to classify automatically the different flow patterns. The experiment results from a small-scale loop show that the proposed method is effective for analyzing the multiphase flow pattern.

Co-Design Method and Wafer-Level Packaging Technique of Thin-Film Flexible Antenna and Silicon CMOS Rectifier Chips for Wireless-Powered Neural Interface Systems.

PubMed

Okabe, Kenji; Jeewan, Horagodage Prabhath; Yamagiwa, Shota; Kawano, Takeshi; Ishida, Makoto; Akita, Ippei

2015-12-16

In this paper, a co-design method and a wafer-level packaging technique of a flexible antenna and a CMOS rectifier chip for use in a small-sized implantable system on the brain surface are proposed. The proposed co-design method optimizes the system architecture, and can help avoid the use of external matching components, resulting in the realization of a small-size system. In addition, the technique employed to assemble a silicon large-scale integration (LSI) chip on the very thin parylene film (5 μm) enables the integration of the rectifier circuits and the flexible antenna (rectenna). In the demonstration of wireless power transmission (WPT), the fabricated flexible rectenna achieved a maximum efficiency of 0.497% with a distance of 3 cm between antennas. In addition, WPT with radio waves allows a misalignment of 185% against antenna size, implying that the misalignment has a less effect on the WPT characteristics compared with electromagnetic induction.

Co-Design Method and Wafer-Level Packaging Technique of Thin-Film Flexible Antenna and Silicon CMOS Rectifier Chips for Wireless-Powered Neural Interface Systems

PubMed Central

Okabe, Kenji; Jeewan, Horagodage Prabhath; Yamagiwa, Shota; Kawano, Takeshi; Ishida, Makoto; Akita, Ippei

2015-01-01

In this paper, a co-design method and a wafer-level packaging technique of a flexible antenna and a CMOS rectifier chip for use in a small-sized implantable system on the brain surface are proposed. The proposed co-design method optimizes the system architecture, and can help avoid the use of external matching components, resulting in the realization of a small-size system. In addition, the technique employed to assemble a silicon large-scale integration (LSI) chip on the very thin parylene film (5 μm) enables the integration of the rectifier circuits and the flexible antenna (rectenna). In the demonstration of wireless power transmission (WPT), the fabricated flexible rectenna achieved a maximum efficiency of 0.497% with a distance of 3 cm between antennas. In addition, WPT with radio waves allows a misalignment of 185% against antenna size, implying that the misalignment has a less effect on the WPT characteristics compared with electromagnetic induction. PMID:26694407

Assessing Feedback in a Mobile Videogame

PubMed Central

Brand, Leah; Beltran, Alicia; Hughes, Sheryl; O'Connor, Teresia; Baranowski, Janice; Nicklas, Theresa; Chen, Tzu-An; Dadabhoy, Hafza R.; Diep, Cassandra S.; Buday, Richard

2016-01-01

Abstract Background: Player feedback is an important part of serious games, although there is no consensus regarding its delivery or optimal content. “Mommio” is a serious game designed to help mothers motivate their preschoolers to eat vegetables. The purpose of this study was to assess optimal format and content of player feedback for use in “Mommio.” Materials and Methods: The current study posed 36 potential “Mommio” gameplay feedback statements to 20 mothers using a Web survey and interview. Mothers were asked about the meaning and helpfulness of each feedback statement. Results: Several themes emerged upon thematic analysis, including identifying an effective alternative in the case of corrective feedback, avoiding vague wording, using succinct and correct grammar, avoiding provocation of guilt, and clearly identifying why players' game choice was correct or incorrect. Conclusions: Guidelines are proposed for future feedback statements. PMID:27058403

Aeromagnetic gradient compensation method for helicopter based on ɛ-support vector regression algorithm

NASA Astrophysics Data System (ADS)

Wu, Peilin; Zhang, Qunying; Fei, Chunjiao; Fang, Guangyou

2017-04-01

Aeromagnetic gradients are typically measured by optically pumped magnetometers mounted on an aircraft. Any aircraft, particularly helicopters, produces significant levels of magnetic interference. Therefore, aeromagnetic compensation is essential, and least square (LS) is the conventional method used for reducing interference levels. However, the LSs approach to solving the aeromagnetic interference model has a few difficulties, one of which is in handling multicollinearity. Therefore, we propose an aeromagnetic gradient compensation method, specifically targeted for helicopter use but applicable on any airborne platform, which is based on the ɛ-support vector regression algorithm. The structural risk minimization criterion intrinsic to the method avoids multicollinearity altogether. Local aeromagnetic anomalies can be retained, and platform-generated fields are suppressed simultaneously by constructing an appropriate loss function and kernel function. The method was tested using an unmanned helicopter and obtained improvement ratios of 12.7 and 3.5 in the vertical and horizontal gradient data, respectively. Both of these values are probably better than those that would have been obtained from the conventional method applied to the same data, had it been possible to do so in a suitable comparative context. The validity of the proposed method is demonstrated by the experimental result.

A fast button surface defects detection method based on convolutional neural network

NASA Astrophysics Data System (ADS)

Liu, Lizhe; Cao, Danhua; Wu, Songlin; Wu, Yubin; Wei, Taoran

2018-01-01

Considering the complexity of the button surface texture and the variety of buttons and defects, we propose a fast visual method for button surface defect detection, based on convolutional neural network (CNN). CNN has the ability to extract the essential features by training, avoiding designing complex feature operators adapted to different kinds of buttons, textures and defects. Firstly, we obtain the normalized button region and then use HOG-SVM method to identify the front and back side of the button. Finally, a convolutional neural network is developed to recognize the defects. Aiming at detecting the subtle defects, we propose a network structure with multiple feature channels input. To deal with the defects of different scales, we take a strategy of multi-scale image block detection. The experimental results show that our method is valid for a variety of buttons and able to recognize all kinds of defects that have occurred, including dent, crack, stain, hole, wrong paint and uneven. The detection rate exceeds 96%, which is much better than traditional methods based on SVM and methods based on template match. Our method can reach the speed of 5 fps on DSP based smart camera with 600 MHz frequency.

Superconvergent second order Cartesian method for solving free boundary problem for invadopodia formation

NASA Astrophysics Data System (ADS)

Gallinato, Olivier; Poignard, Clair

2017-06-01

In this paper, we present a superconvergent second order Cartesian method to solve a free boundary problem with two harmonic phases coupled through the moving interface. The model recently proposed by the authors and colleagues describes the formation of cell protrusions. The moving interface is described by a level set function and is advected at the velocity given by the gradient of the inner phase. The finite differences method proposed in this paper consists of a new stabilized ghost fluid method and second order discretizations for the Laplace operator with the boundary conditions (Dirichlet, Neumann or Robin conditions). Interestingly, the method to solve the harmonic subproblems is superconvergent on two levels, in the sense that the first and second order derivatives of the numerical solutions are obtained with the second order of accuracy, similarly to the solution itself. We exhibit numerical criteria on the data accuracy to get such properties and numerical simulations corroborate these criteria. In addition to these properties, we propose an appropriate extension of the velocity of the level-set to avoid any loss of consistency, and to obtain the second order of accuracy of the complete free boundary problem. Interestingly, we highlight the transmission of the superconvergent properties for the static subproblems and their preservation by the dynamical scheme. Our method is also well suited for quasistatic Hele-Shaw-like or Muskat-like problems.

Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

NASA Astrophysics Data System (ADS)

Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

2017-09-01

With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

A new compound control method for sine-on-random mixed vibration test

NASA Astrophysics Data System (ADS)

Zhang, Buyun; Wang, Ruochen; Zeng, Falin

2017-09-01

Vibration environmental test (VET) is one of the important and effective methods to provide supports for the strength design, reliability and durability test of mechanical products. A new separation control strategy was proposed to apply in multiple-input multiple-output (MIMO) sine on random (SOR) mixed mode vibration test, which is the advanced and intensive test type of VET. As the key problem of the strategy, correlation integral method was applied to separate the mixed signals which included random and sinusoidal components. The feedback control formula of MIMO linear random vibration system was systematically deduced in frequency domain, and Jacobi control algorithm was proposed in view of the elements, such as self-spectrum, coherence, and phase of power spectral density (PSD) matrix. Based on the excessive correction of excitation in sine vibration test, compression factor was introduced to reduce the excitation correction, avoiding the destruction to vibration table or other devices. The two methods were synthesized to be applied in MIMO SOR vibration test system. In the final, verification test system with the vibration of a cantilever beam as the control object was established to verify the reliability and effectiveness of the methods proposed in the paper. The test results show that the exceeding values can be controlled in the tolerance range of references accurately, and the method can supply theory and application supports for mechanical engineering.

Scene-based nonuniformity correction algorithm based on interframe registration.

PubMed

Zuo, Chao; Chen, Qian; Gu, Guohua; Sui, Xiubao

2011-06-01

In this paper, we present a simple and effective scene-based nonuniformity correction (NUC) method for infrared focal plane arrays based on interframe registration. This method estimates the global translation between two adjacent frames and minimizes the mean square error between the two properly registered images to make any two detectors with the same scene produce the same output value. In this way, the accumulation of the registration error can be avoided and the NUC can be achieved. The advantages of the proposed algorithm lie in its low computational complexity and storage requirements and ability to capture temporal drifts in the nonuniformity parameters. The performance of the proposed technique is thoroughly studied with infrared image sequences with simulated nonuniformity and infrared imagery with real nonuniformity. It shows a significantly fast and reliable fixed-pattern noise reduction and obtains an effective frame-by-frame adaptive estimation of each detector's gain and offset.

Spin density and orbital optimization in open shell systems: A rational and computationally efficient proposal

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

Giner, Emmanuel, E-mail: gnrmnl@unife.it; Angeli, Celestino, E-mail: anc@unife.it

2016-03-14

The present work describes a new method to compute accurate spin densities for open shell systems. The proposed approach follows two steps: first, it provides molecular orbitals which correctly take into account the spin delocalization; second, a proper CI treatment allows to account for the spin polarization effect while keeping a restricted formalism and avoiding spin contamination. The main idea of the optimization procedure is based on the orbital relaxation of the various charge transfer determinants responsible for the spin delocalization. The algorithm is tested and compared to other existing methods on a series of organic and inorganic open shellmore » systems. The results reported here show that the new approach (almost black-box) provides accurate spin densities at a reasonable computational cost making it suitable for a systematic study of open shell systems.« less

Recording vocalizations with Bluetooth technology.

PubMed

Gaona-González, Andrés; Santillán-Doherty, Ana María; Arenas-Rosas, Rita Virginia; Muñoz-Delgado, Jairo; Aguillón-Pantaleón, Miguel Angel; Ordoñez-Gómez, José Domingo; Márquez-Arias, Alejandra

2011-06-01

We propose a method for capturing vocalizations that is designed to avoid some of the limiting factors found in traditional bioacoustical methods, such as the impossibility of obtaining continuous long-term registers or analyzing amplitude due to the continuous change of distance between the subject and the position of the recording system. Using Bluetooth technology, vocalizations are captured and transmitted wirelessly into a receiving system without affecting the quality of the signal. The recordings of the proposed system were compared to those obtained as a reference, which were based on the coding of the signal with the so-called pulse-code modulation technique in WAV audio format without any compressing process. The evaluation showed p < .05 for the measured quantitative and qualitative parameters. We also describe how the transmitting system is encapsulated and fixed on the animal and a way to video record a spider monkey's behavior simultaneously with the audio recordings.

A trust region approach with multivariate Padé model for optimal circuit design

NASA Astrophysics Data System (ADS)

Abdel-Malek, Hany L.; Ebid, Shaimaa E. K.; Mohamed, Ahmed S. A.

2017-11-01

Since the optimization process requires a significant number of consecutive function evaluations, it is recommended to replace the function by an easily evaluated approximation model during the optimization process. The model suggested in this article is based on a multivariate Padé approximation. This model is constructed using data points of ?, where ? is the number of parameters. The model is updated over a sequence of trust regions. This model avoids the slow convergence of linear models of ? and has features of quadratic models that need interpolation data points of ?. The proposed approach is tested by applying it to several benchmark problems. Yield optimization using such a direct method is applied to some practical circuit examples. Minimax solution leads to a suitable initial point to carry out the yield optimization process. The yield is optimized by the proposed derivative-free method for active and passive filter examples.

Intelligent vision guide for automatic ventilation grommet insertion into the tympanic membrane.

PubMed

Gao, Wenchao; Tan, Kok Kiong; Liang, Wenyu; Gan, Chee Wee; Lim, Hsueh Yee

2016-03-01

Otitis media with effusion is a worldwide ear disease. The current treatment is to surgically insert a ventilation grommet into the tympanic membrane. A robotic device allowing automatic grommet insertion has been designed in a previous study; however, the part of the membrane where the malleus bone is attached to the inner surface is to be avoided during the insertion process. This paper proposes a synergy of optical flow technique and a gradient vector flow active contours algorithm to achieve an online tracking of the malleus under endoscopic vision, to guide the working channel to move efficiently during the surgery. The proposed method shows a more stable and accurate tracking performance than the current tracking methods in preclinical tests. With satisfactory tracking results, vision guidance of a suitable insertion spot can be provided to the device to perform the surgery in an automatic way. Copyright © 2015 John Wiley & Sons, Ltd.

A support vector machine based control application to the experimental three-tank system.

PubMed

Iplikci, Serdar

2010-07-01

This paper presents a support vector machine (SVM) approach to generalized predictive control (GPC) of multiple-input multiple-output (MIMO) nonlinear systems. The possession of higher generalization potential and at the same time avoidance of getting stuck into the local minima have motivated us to employ SVM algorithms for modeling MIMO systems. Based on the SVM model, detailed and compact formulations for calculating predictions and gradient information, which are used in the computation of the optimal control action, are given in the paper. The proposed MIMO SVM-based GPC method has been verified on an experimental three-tank liquid level control system. Experimental results have shown that the proposed method can handle the control task successfully for different reference trajectories. Moreover, a detailed discussion on data gathering, model selection and effects of the control parameters have been given in this paper. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Segmentation-assisted detection of dirt impairments in archived film sequences.

PubMed

Ren, Jinchang; Vlachos, Theodore

2007-04-01

In this correspondence, a novel segmentation-assisted method for film-dirt detection is proposed. We exploit the fact that film dirt manifests in the spatial domain as a cluster of connected pixels whose intensity differs substantially from that of its neighborhood, and we employ a segmentation-based approach to identify this type of structure. A key feature of our approach is the computation of a measure of confidence attached to detected dirt regions, which can be utilized for performance fine tuning. Another important feature of our algorithm is the avoidance of the computational complexity associated with motion estimation. Our experimental framework benefits from the availability of manually derived as well as objective ground-truth data obtained using infrared scanning. Our results demonstrate that the proposed method compares favorably with standard spatial, temporal, and multistage median-filtering approaches and provides efficient and robust detection for a wide variety of test materials.

Imparting protean behavior to mobile robots accomplishing patrolling tasks in the presence of adversaries.

PubMed

Curiac, Daniel-Ioan; Volosencu, Constantin

2015-10-08

Providing unpredictable trajectories for patrol robots is essential when coping with adversaries. In order to solve this problem we developed an effective approach based on the known protean behavior of individual prey animals-random zig-zag movement. The proposed bio-inspired method modifies the normal robot's path by incorporating sudden and irregular direction changes without jeopardizing the robot's mission. Such a tactic is aimed to confuse the enemy (e.g. a sniper), offering less time to acquire and retain sight alignment and sight picture. This idea is implemented by simulating a series of fictive-temporary obstacles that will randomly appear in the robot's field of view, deceiving the obstacle avoiding mechanism to react. The new general methodology is particularized by using the Arnold's cat map to obtain the timely random appearance and disappearance of the fictive obstacles. The viability of the proposed method is confirmed through an extensive simulation case study.

Thermal modal analysis of novel non-pneumatic mechanical elastic wheel based on FEM and EMA

NASA Astrophysics Data System (ADS)

Zhao, Youqun; Zhu, Mingmin; Lin, Fen; Xiao, Zhen; Li, Haiqing; Deng, Yaoji

2018-01-01

A combination of Finite Element Method (FEM) and Experiment Modal Analysis (EMA) have been employed here to characterize the structural dynamic response of mechanical elastic wheel (ME-Wheel) operating under a specific thermal environment. The influence of high thermal condition on the structural dynamic response of ME-Wheel is investigated. The obtained results indicate that the EMA results are in accordance with those obtained using the proposed Finite Element (FE) model, indicting the high reliability of this FE model applied in analyzing the modal of ME-Wheel working under practical thermal environment. It demonstrates that the structural dynamic response of ME-Wheel operating under a specific thermal condition can be predicted and evaluated using the proposed analysis method, which is beneficial for the dynamic optimization design of the wheel structure to avoid tire temperature related vibration failure and improve safety of tire.

Cost-Sharing of Ecological Construction Based on Trapezoidal Intuitionistic Fuzzy Cooperative Games.

PubMed

Liu, Jiacai; Zhao, Wenjian

2016-11-08

There exist some fuzziness and uncertainty in the process of ecological construction. The aim of this paper is to develop a direct and an effective simplified method for obtaining the cost-sharing scheme when some interested parties form a cooperative coalition to improve the ecological environment of Min River together. Firstly, we propose the solution concept of the least square prenucleolus of cooperative games with coalition values expressed by trapezoidal intuitionistic fuzzy numbers. Then, based on the square of the distance in the numerical value between two trapezoidal intuitionistic fuzzy numbers, we establish a corresponding quadratic programming model to obtain the least square prenucleolus, which can effectively avoid the information distortion and uncertainty enlargement brought about by the subtraction of trapezoidal intuitionistic fuzzy numbers. Finally, we give a numerical example about the cost-sharing of ecological construction in Fujian Province in China to show the validity, applicability, and advantages of the proposed model and method.

An alternative to reduction of surface pressure to sea level

NASA Technical Reports Server (NTRS)

Deardorff, J. W.

1982-01-01

The pitfalls of the present method of reducing surface pressure to sea level are reviewed, and an alternative, adjusted pressure, P, is proposed. P is obtained from solution of a Poisson equation over a continental region, using the simplest boundary condition along the perimeter or coastline where P equals the sea level pressure. The use of P would avoid the empiricisms and disadvantages of pressure reduction to sea level, and would produce surface pressure charts which depict the true geostrophic wind at the surface.

Science communication. Response to Comment on "Quantifying long-term scientific impact".

PubMed

Wang, Dashun; Song, Chaoming; Shen, Hua-Wei; Barabási, Albert-László

2014-07-11

Wang, Mei, and Hicks claim that they observed large mean prediction errors when using our model. We find that their claims are a simple consequence of overfitting, which can be avoided by standard regularization methods. Here, we show that our model provides an effective means to identify papers that may be subject to overfitting, and the model, with or without prior treatment, outperforms the proposed naïve approach. Copyright © 2014, American Association for the Advancement of Science.

Estimation of Skidding Offered by Ackermann Mechanism

NASA Astrophysics Data System (ADS)

Rao, Are Padma; Venkatachalam, Rapur

2016-04-01

Steering for a four wheeler is being provided by Ackermann mechanism. Though it cannot always provide correct steering conditions, it is very popular because of its simple nature. A correct steering would avoid skidding of the tires, and thereby enhance their lives as the wear of the tires is reduced. In this paper it is intended to analyze Ackermann mechanism for its performance. A method of estimating skidding due to improper steering is proposed. Two parameters are identified using which the length of skidding can be estimated.

Quantum Associative Neural Network with Nonlinear Search Algorithm

NASA Astrophysics Data System (ADS)

Zhou, Rigui; Wang, Huian; Wu, Qian; Shi, Yang

2012-03-01

Based on analysis on properties of quantum linear superposition, to overcome the complexity of existing quantum associative memory which was proposed by Ventura, a new storage method for multiply patterns is proposed in this paper by constructing the quantum array with the binary decision diagrams. Also, the adoption of the nonlinear search algorithm increases the pattern recalling speed of this model which has multiply patterns to O( {log2}^{2^{n -t}} ) = O( n - t ) time complexity, where n is the number of quantum bit and t is the quantum information of the t quantum bit. Results of case analysis show that the associative neural network model proposed in this paper based on quantum learning is much better and optimized than other researchers' counterparts both in terms of avoiding the additional qubits or extraordinary initial operators, storing pattern and improving the recalling speed.

Cooperative quantum-behaved particle swarm optimization with dynamic varying search areas and Lévy flight disturbance.

PubMed

Li, Desheng

2014-01-01

This paper proposes a novel variant of cooperative quantum-behaved particle swarm optimization (CQPSO) algorithm with two mechanisms to reduce the search space and avoid the stagnation, called CQPSO-DVSA-LFD. One mechanism is called Dynamic Varying Search Area (DVSA), which takes charge of limiting the ranges of particles' activity into a reduced area. On the other hand, in order to escape the local optima, Lévy flights are used to generate the stochastic disturbance in the movement of particles. To test the performance of CQPSO-DVSA-LFD, numerical experiments are conducted to compare the proposed algorithm with different variants of PSO. According to the experimental results, the proposed method performs better than other variants of PSO on both benchmark test functions and the combinatorial optimization issue, that is, the job-shop scheduling problem.

A scale-invariant change detection method for land use/cover change research

NASA Astrophysics Data System (ADS)

Xing, Jin; Sieber, Renee; Caelli, Terrence

2018-07-01

Land Use/Cover Change (LUCC) detection relies increasingly on comparing remote sensing images with different spatial and spectral scales. Based on scale-invariant image analysis algorithms in computer vision, we propose a scale-invariant LUCC detection method to identify changes from scale heterogeneous images. This method is composed of an entropy-based spatial decomposition, two scale-invariant feature extraction methods, Maximally Stable Extremal Region (MSER) and Scale-Invariant Feature Transformation (SIFT) algorithms, a spatial regression voting method to integrate MSER and SIFT results, a Markov Random Field-based smoothing method, and a support vector machine classification method to assign LUCC labels. We test the scale invariance of our new method with a LUCC case study in Montreal, Canada, 2005-2012. We found that the scale-invariant LUCC detection method provides similar accuracy compared with the resampling-based approach but this method avoids the LUCC distortion incurred by resampling.

Direct application of Padé approximant for solving nonlinear differential equations.

PubMed

Vazquez-Leal, Hector; Benhammouda, Brahim; Filobello-Nino, Uriel; Sarmiento-Reyes, Arturo; Jimenez-Fernandez, Victor Manuel; Garcia-Gervacio, Jose Luis; Huerta-Chua, Jesus; Morales-Mendoza, Luis Javier; Gonzalez-Lee, Mario

2014-01-01

This work presents a direct procedure to apply Padé method to find approximate solutions for nonlinear differential equations. Moreover, we present some cases study showing the strength of the method to generate highly accurate rational approximate solutions compared to other semi-analytical methods. The type of tested nonlinear equations are: a highly nonlinear boundary value problem, a differential-algebraic oscillator problem, and an asymptotic problem. The high accurate handy approximations obtained by the direct application of Padé method shows the high potential if the proposed scheme to approximate a wide variety of problems. What is more, the direct application of the Padé approximant aids to avoid the previous application of an approximative method like Taylor series method, homotopy perturbation method, Adomian Decomposition method, homotopy analysis method, variational iteration method, among others, as tools to obtain a power series solutions to post-treat with the Padé approximant. 34L30.

Trajectory Based Behavior Analysis for User Verification

NASA Astrophysics Data System (ADS)

Pao, Hsing-Kuo; Lin, Hong-Yi; Chen, Kuan-Ta; Fadlil, Junaidillah

Many of our activities on computer need a verification step for authorized access. The goal of verification is to tell apart the true account owner from intruders. We propose a general approach for user verification based on user trajectory inputs. The approach is labor-free for users and is likely to avoid the possible copy or simulation from other non-authorized users or even automatic programs like bots. Our study focuses on finding the hidden patterns embedded in the trajectories produced by account users. We employ a Markov chain model with Gaussian distribution in its transitions to describe the behavior in the trajectory. To distinguish between two trajectories, we propose a novel dissimilarity measure combined with a manifold learnt tuning for catching the pairwise relationship. Based on the pairwise relationship, we plug-in any effective classification or clustering methods for the detection of unauthorized access. The method can also be applied for the task of recognition, predicting the trajectory type without pre-defined identity. Given a trajectory input, the results show that the proposed method can accurately verify the user identity, or suggest whom owns the trajectory if the input identity is not provided.

Tongue Images Classification Based on Constrained High Dispersal Network.

PubMed

Meng, Dan; Cao, Guitao; Duan, Ye; Zhu, Minghua; Tu, Liping; Xu, Dong; Xu, Jiatuo

2017-01-01

Computer aided tongue diagnosis has a great potential to play important roles in traditional Chinese medicine (TCM). However, the majority of the existing tongue image analyses and classification methods are based on the low-level features, which may not provide a holistic view of the tongue. Inspired by deep convolutional neural network (CNN), we propose a novel feature extraction framework called constrained high dispersal neural networks (CHDNet) to extract unbiased features and reduce human labor for tongue diagnosis in TCM. Previous CNN models have mostly focused on learning convolutional filters and adapting weights between them, but these models have two major issues: redundancy and insufficient capability in handling unbalanced sample distribution. We introduce high dispersal and local response normalization operation to address the issue of redundancy. We also add multiscale feature analysis to avoid the problem of sensitivity to deformation. Our proposed CHDNet learns high-level features and provides more classification information during training time, which may result in higher accuracy when predicting testing samples. We tested the proposed method on a set of 267 gastritis patients and a control group of 48 healthy volunteers. Test results show that CHDNet is a promising method in tongue image classification for the TCM study.

Using Hybrid Angle/Distance Information for Distributed Topology Control in Vehicular Sensor Networks

PubMed Central

Huang, Chao-Chi; Chiu, Yang-Hung; Wen, Chih-Yu

2014-01-01

In a vehicular sensor network (VSN), the key design issue is how to organize vehicles effectively, such that the local network topology can be stabilized quickly. In this work, each vehicle with on-board sensors can be considered as a local controller associated with a group of communication members. In order to balance the load among the nodes and govern the local topology change, a group formation scheme using localized criteria is implemented. The proposed distributed topology control method focuses on reducing the rate of group member change and avoiding the unnecessary information exchange. Two major phases are sequentially applied to choose the group members of each vehicle using hybrid angle/distance information. The operation of Phase I is based on the concept of the cone-based method, which can select the desired vehicles quickly. Afterwards, the proposed time-slot method is further applied to stabilize the network topology. Given the network structure in Phase I, a routing scheme is presented in Phase II. The network behaviors are explored through simulation and analysis in a variety of scenarios. The results show that the proposed mechanism is a scalable and effective control framework for VSNs. PMID:25350506

Modeling and analysis of a large deployable antenna structure

NASA Astrophysics Data System (ADS)

Chu, Zhengrong; Deng, Zongquan; Qi, Xiaozhi; Li, Bing

2014-02-01

One kind of large deployable antenna (LDA) structure is proposed by combining a number of basic deployable units in this paper. In order to avoid vibration caused by fast deployment speed of the mechanism, a braking system is used to control the spring-actuated system. Comparisons between the LDA structure and a similar structure used by the large deployable reflector (LDR) indicate that the former has potential for use in antennas with up to 30 m aperture due to its lighter weight. The LDA structure is designed to form a spherical surface found by the least square fitting method so that it can be symmetrical. In this case, the positions of the terminal points in the structure are determined by two principles. A method to calculate the cable network stretched on the LDA structure is developed, which combines the original force density method and the parabolic surface constraint. Genetic algorithm is applied to ensure that each cable reaches a desired tension, which avoids the non-convergence issue effectively. We find that the pattern for the front and rear cable net must be the same when finding the shape of the rear cable net, otherwise anticlastic surface would generate.

The solitary wave solution of coupled Klein-Gordon-Zakharov equations via two different numerical methods

NASA Astrophysics Data System (ADS)

Dehghan, Mehdi; Nikpour, Ahmad

2013-09-01

In this research, we propose two different methods to solve the coupled Klein-Gordon-Zakharov (KGZ) equations: the Differential Quadrature (DQ) and Globally Radial Basis Functions (GRBFs) methods. In the DQ method, the derivative value of a function with respect to a point is directly approximated by a linear combination of all functional values in the global domain. The principal work in this method is the determination of weight coefficients. We use two ways for obtaining these coefficients: cosine expansion (CDQ) and radial basis functions (RBFs-DQ), the former is a mesh-based method and the latter categorizes in the set of meshless methods. Unlike the DQ method, the GRBF method directly substitutes the expression of the function approximation by RBFs into the partial differential equation. The main problem in the GRBFs method is ill-conditioning of the interpolation matrix. Avoiding this problem, we study the bases introduced in Pazouki and Schaback (2011) [44]. Some examples are presented to compare the accuracy and easy implementation of the proposed methods. In numerical examples, we concentrate on Inverse Multiquadric (IMQ) and second-order Thin Plate Spline (TPS) radial basis functions. The variable shape parameter (exponentially and random) strategies are applied in the IMQ function and the results are compared with the constant shape parameter.

TU-G-BRB-01: Continuous Path Optimization for Non-Coplanar Variant SAD IMRT Delivery Using C-Arm Machines.

PubMed

Ruan, D; Dong, P; Low, D; Sheng, K

2012-06-01

To develop and investigate a continuous path optimization methodology to traverse prescribed non-coplanar IMRT beams with variant SADs, by orchestrating the couch and gantry movement with zero-collision, minimal patient motion consequence and machine travel time. We convert the given collision zone definition and the prescribed beam location/angles to a tumor-centric coordinate, and represent the traversing path as a continuous open curve. We proceed to optimize a composite objective function consisting of (1) a strong attraction energy to ensure all prescribed beams are en-route, (2) a penalty for patient-motion inducing couch motion, and (3) a penalty for travel-time inducing overall path-length. Feasibility manifold is defined as complement to collision zone and the optimization is performed with a level set representation evolved with variational flows. The proposed method has been implemented and tested on clinically derived data. In the absence of any existing solutions for the same problem, we validate by: (1) visual inspecting the generated path rendered in the 3D tumor-centric coordinates, and (2) comparing with a traveling-salesman (TSP) solution obtained from relaxing the variant SADs and continuous collision-avoidance requirement. The proposed method has generated delivery paths that are smooth and intuitively appealing. Under relaxed settings, our results outperform the generic TSP solutions and agree with specially tuned versions. We have proposed a novel systematic approach that automatically determines the continuous path to cover non-coplanar, varying SAD IMRT beams. The proposed approach accommodates patient-specific collision zone definition and ensures its avoidance continuously. The differential penalty to couch and gantry motions allows customizable tradeoff between patient geometry stability and delivery efficiency. This development paves the path to achieve safe, accurate and efficient non-coplanar IMRT delivery with the advanced robotic controls in new-generation C-arm systems, enabling practical harvesting of the dose benefit offered by non-coplanar, variant SAD IMRT treatment. © 2012 American Association of Physicists in Medicine.

Missing value imputation for gene expression data by tailored nearest neighbors.

PubMed

Faisal, Shahla; Tutz, Gerhard

2017-04-25

High dimensional data like gene expression and RNA-sequences often contain missing values. The subsequent analysis and results based on these incomplete data can suffer strongly from the presence of these missing values. Several approaches to imputation of missing values in gene expression data have been developed but the task is difficult due to the high dimensionality (number of genes) of the data. Here an imputation procedure is proposed that uses weighted nearest neighbors. Instead of using nearest neighbors defined by a distance that includes all genes the distance is computed for genes that are apt to contribute to the accuracy of imputed values. The method aims at avoiding the curse of dimensionality, which typically occurs if local methods as nearest neighbors are applied in high dimensional settings. The proposed weighted nearest neighbors algorithm is compared to existing missing value imputation techniques like mean imputation, KNNimpute and the recently proposed imputation by random forests. We use RNA-sequence and microarray data from studies on human cancer to compare the performance of the methods. The results from simulations as well as real studies show that the weighted distance procedure can successfully handle missing values for high dimensional data structures where the number of predictors is larger than the number of samples. The method typically outperforms the considered competitors.

Anatomical Calibration through Post-Processing of Standard Motion Tests Data.

PubMed

Kong, Weisheng; Sessa, Salvatore; Zecca, Massimiliano; Takanishi, Atsuo

2016-11-28

The inertial measurement unit is popularly used as a wearable and flexible tool for human motion tracking. Sensor-to-body alignment, or anatomical calibration (AC), is fundamental to improve accuracy and reliability. Current AC methods either require extra movements or are limited to specific joints. In this research, the authors propose a novel method to achieve AC from standard motion tests (such as walking, or sit-to-stand), and compare the results with the AC obtained from specially designed movements. The proposed method uses the limited acceleration range on medial-lateral direction, and applies principal component analysis to estimate the sagittal plane, while the vertical direction is estimated from acceleration during quiet stance. The results show a good correlation between the two sets of IMUs placed on frontal/back and lateral sides of head, trunk and lower limbs. Moreover, repeatability and convergence were verified. The AC obtained from sit-to-stand and walking achieved similar results as the movements specifically designed for upper and lower body AC, respectively, except for the feet. Therefore, the experiments without AC performed can be recovered through post-processing on the walking and sit-to-stand data. Moreover, extra movements for AC can be avoided during the experiment and instead achieved through the proposed method.

Secure Hashing of Dynamic Hand Signatures Using Wavelet-Fourier Compression with BioPhasor Mixing and [InlineEquation not available: see fulltext.] Discretization

NASA Astrophysics Data System (ADS)

Wai Kuan, Yip; Teoh, Andrew B. J.; Ngo, David C. L.

2006-12-01

We introduce a novel method for secure computation of biometric hash on dynamic hand signatures using BioPhasor mixing and[InlineEquation not available: see fulltext.] discretization. The use of BioPhasor as the mixing process provides a one-way transformation that precludes exact recovery of the biometric vector from compromised hashes and stolen tokens. In addition, our user-specific[InlineEquation not available: see fulltext.] discretization acts both as an error correction step as well as a real-to-binary space converter. We also propose a new method of extracting compressed representation of dynamic hand signatures using discrete wavelet transform (DWT) and discrete fourier transform (DFT). Without the conventional use of dynamic time warping, the proposed method avoids storage of user's hand signature template. This is an important consideration for protecting the privacy of the biometric owner. Our results show that the proposed method could produce stable and distinguishable bit strings with equal error rates (EERs) of[InlineEquation not available: see fulltext.] and[InlineEquation not available: see fulltext.] for random and skilled forgeries for stolen token (worst case) scenario, and[InlineEquation not available: see fulltext.] for both forgeries in the genuine token (optimal) scenario.

Study on a Simple Method for Controlling the Engine Output Power of Hybrid Powered Railway Vehicles with Electric Double Layer Capacitors

NASA Astrophysics Data System (ADS)

Okano, Shota; Shibuya, Hiroyuki; Kondo, Keiichiro

This paper presents a simple and energy-saving method for controlling hybrid powered railway vehicles that run on rural non-electrified railway lines and have diesel engine and electrical double layer capacitors (EDLCs). The aim this study is to reduce both the fuel consumption and the capacitance of EDLCs. A basic idea proposed in this paper is that EDLCs supply and absorb the kinetic energy of the vehicle and the engine output compensates supply the energy loss with the vehicle running. Thus, the energy loss is not taken into consideration while expressing the EDLC voltage reference (equation 1); energy loss is considered when the engine is in operating mode. The proposed method is examined by performing numerical simulations for various values of engine operation time, load, and grade section. The results of this study reveal the relationship between the capacitance of the EDLCs and the fuel consumption. Using this proposed control methods, excessive charging of EDLCs can be avoided. The results of this study are expected to expedite the development of energy-saving railway vehicles for the non-electrified lines. Finally, the results of this study increase the possibility of developing hybrid powered railway vehicles.

Physics-Based Image Segmentation Using First Order Statistical Properties and Genetic Algorithm for Inductive Thermography Imaging.

PubMed

Gao, Bin; Li, Xiaoqing; Woo, Wai Lok; Tian, Gui Yun

2018-05-01

Thermographic inspection has been widely applied to non-destructive testing and evaluation with the capabilities of rapid, contactless, and large surface area detection. Image segmentation is considered essential for identifying and sizing defects. To attain a high-level performance, specific physics-based models that describe defects generation and enable the precise extraction of target region are of crucial importance. In this paper, an effective genetic first-order statistical image segmentation algorithm is proposed for quantitative crack detection. The proposed method automatically extracts valuable spatial-temporal patterns from unsupervised feature extraction algorithm and avoids a range of issues associated with human intervention in laborious manual selection of specific thermal video frames for processing. An internal genetic functionality is built into the proposed algorithm to automatically control the segmentation threshold to render enhanced accuracy in sizing the cracks. Eddy current pulsed thermography will be implemented as a platform to demonstrate surface crack detection. Experimental tests and comparisons have been conducted to verify the efficacy of the proposed method. In addition, a global quantitative assessment index F-score has been adopted to objectively evaluate the performance of different segmentation algorithms.

Bifocal computational near eye light field displays and Structure parameters determination scheme for bifocal computational display.

PubMed

Liu, Mali; Lu, Chihao; Li, Haifeng; Liu, Xu

2018-02-19

We propose a bifocal computational near eye light field display (bifocal computational display) and structure parameters determination scheme (SPDS) for bifocal computational display that achieves greater depth of field (DOF), high resolution, accommodation and compact form factor. Using a liquid varifocal lens, two single-focal computational light fields are superimposed to reconstruct a virtual object's light field by time multiplex and avoid the limitation on high refresh rate. By minimizing the deviation between reconstructed light field and original light field, we propose a determination framework to determine the structure parameters of bifocal computational light field display. When applied to different objective to SPDS, it can achieve high average resolution or uniform resolution display over scene depth range. To analyze the advantages and limitation of our proposed method, we have conducted simulations and constructed a simple prototype which comprises a liquid varifocal lens, dual-layer LCDs and a uniform backlight. The results of simulation and experiments with our method show that the proposed system can achieve expected performance well. Owing to the excellent performance of our system, we motivate bifocal computational display and SPDS to contribute to a daily-use and commercial virtual reality display.

Distributed sensor management for space situational awareness via a negotiation game

NASA Astrophysics Data System (ADS)

Jia, Bin; Shen, Dan; Pham, Khanh; Blasch, Erik; Chen, Genshe

2015-05-01

Space situational awareness (SSA) is critical to many space missions serving weather analysis, communications, and navigation. However, the number of sensors used in space situational awareness is limited which hinders collision avoidance prediction, debris assessment, and efficient routing. Hence, it is critical to use such sensor resources efficiently. In addition, it is desired to develop the SSA sensor management algorithm in a distributed manner. In this paper, a distributed sensor management approach using the negotiation game (NG-DSM) is proposed for the SSA. Specifically, the proposed negotiation game is played by each sensor and its neighboring sensors. The bargaining strategies are developed for each sensor based on negotiating for accurately tracking desired targets (e.g., satellite, debris, etc.) . The proposed NG-DSM method is tested in a scenario which includes eight space objects and three different sensor modalities which include a space based optical sensor, a ground radar, or a ground Electro-Optic sensor. The geometric relation between the sensor, the Sun, and the space object is also considered. The simulation results demonstrate the effectiveness of the proposed NG-DSM sensor management methods, which facilitates an application of multiple-sensor multiple-target tracking for space situational awareness.

Efficient reversible data hiding in encrypted image with public key cryptosystem

NASA Astrophysics Data System (ADS)

Xiang, Shijun; Luo, Xinrong

2017-12-01

This paper proposes a new reversible data hiding scheme for encrypted images by using homomorphic and probabilistic properties of Paillier cryptosystem. The proposed method can embed additional data directly into encrypted image without any preprocessing operations on original image. By selecting two pixels as a group for encryption, data hider can retrieve the absolute differences of groups of two pixels by employing a modular multiplicative inverse method. Additional data can be embedded into encrypted image by shifting histogram of the absolute differences by using the homomorphic property in encrypted domain. On the receiver side, legal user can extract the marked histogram in encrypted domain in the same way as data hiding procedure. Then, the hidden data can be extracted from the marked histogram and the encrypted version of original image can be restored by using inverse histogram shifting operations. Besides, the marked absolute differences can be computed after decryption for extraction of additional data and restoration of original image. Compared with previous state-of-the-art works, the proposed scheme can effectively avoid preprocessing operations before encryption and can efficiently embed and extract data in encrypted domain. The experiments on the standard image files also certify the effectiveness of the proposed scheme.

Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations.

PubMed

Ou, Jian; Chen, Yongguang; Zhao, Feng; Liu, Jin; Xiao, Shunping

2017-03-19

The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR). With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.

Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations

PubMed Central

Ou, Jian; Chen, Yongguang; Zhao, Feng; Liu, Jin; Xiao, Shunping

2017-01-01

The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR). With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity. PMID:28335492

BBB disruption with unfocused ultrasound alone-A paradigm shift

NASA Astrophysics Data System (ADS)

Kyle, Al

2012-10-01

One paradigm for ultrasound-enabled blood brain barrier disruption uses image guided focused ultrasound and preformed microbubble agents to enable drug delivery to the brain. We propose an alternative approach: unguided, unfocused ultrasound with no adjunctive agent. Compared with the focused approach, the proposed method affects a larger region of the brain, and is aimed at treatment of regional neurological disease including glioblastoma multiforme (GBM). Avoidance of image guidance and focusing reduces cost for equipment and staff training. Avoidance of adjunctive agents also lowers cost and is enabled by a longer exposure time. Since 2004, our group has worked with two animal models, three investigators in four laboratories to safely deliver five compounds, increasing the concentration of large molecule markers in brain tissue two fold or more. Safety and effectiveness data for four studies have been presented at the Ultrasound Industry Association meetings in 2007 and 2010. This paper describes new safety and effectiveness results for a fifth study. We present evidence of delivery of large molecules - including Avastin-to the brains of a large animal model correlated with acoustic pressure, and summarize the advantages and disadvantages of this novel approach.

Multi-wavelengths digital holography: reconstruction, synthesis and display of holograms using adaptive transformation.

PubMed

Memmolo, P; Finizio, A; Paturzo, M; Ferraro, P; Javidi, B

2012-05-01

A method based on spatial transformations of multiwavelength digital holograms and the correlation matching of their numerical reconstructions is proposed, with the aim to improve superimposition of different color reconstructed images. This method is based on an adaptive affine transform of the hologram that permits management of the physical parameters of numerical reconstruction. In addition, we present a procedure to synthesize a single digital hologram in which three different colors are multiplexed. The optical reconstruction of the synthetic hologram by a spatial light modulator at one wavelength allows us to display all color features of the object, avoiding loss of details.

Path Planning Method in Multi-obstacle Marine Environment

NASA Astrophysics Data System (ADS)

Zhang, Jinpeng; Sun, Hanxv

2017-12-01

In this paper, an improved algorithm for particle swarm optimization is proposed for the application of underwater robot in the complex marine environment. Not only did consider to avoid obstacles when path planning, but also considered the current direction and the size effect on the performance of the robot dynamics. The algorithm uses the trunk binary tree structure to construct the path search space and A * heuristic search method is used in the search space to find a evaluation standard path. Then the particle swarm algorithm to optimize the path by adjusting evaluation function, which makes the underwater robot in the current navigation easier to control, and consume less energy.

A time-domain method for prediction of noise radiated from supersonic rotating sources in a moving medium

NASA Astrophysics Data System (ADS)

Huang, Zhongjie; Siozos-Rousoulis, Leonidas; De Troyer, Tim; Ghorbaniasl, Ghader

2018-02-01

This paper presents a time-domain method for noise prediction of supersonic rotating sources in a moving medium. The proposed approach can be interpreted as an extensive time-domain solution for the convected permeable Ffowcs Williams and Hawkings equation, which is capable of avoiding the Doppler singularity. The solution requires special treatment for construction of the emission surface. The derived formula can explicitly and efficiently account for subsonic uniform constant flow effects on radiated noise. Implementation of the methodology is realized through the Isom thickness noise case and high-speed impulsive noise prediction from helicopter rotors.

A pruning algorithm for Meta-blocking based on cumulative weight

NASA Astrophysics Data System (ADS)

Zhang, Fulin; Gao, Zhipeng; Niu, Kun

2017-08-01

Entity Resolution is an important process in data cleaning and data integration. It usually employs a blocking method to avoid the quadratic complexity work when scales to large data sets. Meta-blocking can perform better in the context of highly heterogeneous information spaces. Yet, its precision and efficiency still have room to improve. In this paper, we present a new pruning algorithm for Meta-Blocking. It can achieve a higher precision than the existing WEP algorithm at a small cost of recall. In addition, can reduce the runtime of the blocking process. We evaluate our proposed method over five real-world data sets.

A stereo-vision hazard-detection algorithm to increase planetary lander autonomy

NASA Astrophysics Data System (ADS)

Woicke, Svenja; Mooij, Erwin

2016-05-01

For future landings on any celestial body, increasing the lander autonomy as well as decreasing risk are primary objectives. Both risk reduction and an increase in autonomy can be achieved by including hazard detection and avoidance in the guidance, navigation, and control loop. One of the main challenges in hazard detection and avoidance is the reconstruction of accurate elevation models, as well as slope and roughness maps. Multiple methods for acquiring the inputs for hazard maps are available. The main distinction can be made between active and passive methods. Passive methods (cameras) have budgetary advantages compared to active sensors (radar, light detection and ranging). However, it is necessary to proof that these methods deliver sufficiently good maps. Therefore, this paper discusses hazard detection using stereo vision. To facilitate a successful landing not more than 1% wrong detections (hazards that are not identified) are allowed. Based on a sensitivity analysis it was found that using a stereo set-up at a baseline of ≤ 2 m is feasible at altitudes of ≤ 200 m defining false positives of less than 1%. It was thus shown that stereo-based hazard detection is an effective means to decrease the landing risk and increase the lander autonomy. In conclusion, the proposed algorithm is a promising candidate for future landers.

An improved algorithm of mask image dodging for aerial image

NASA Astrophysics Data System (ADS)

Zhang, Zuxun; Zou, Songbai; Zuo, Zhiqi

2011-12-01

The technology of Mask image dodging based on Fourier transform is a good algorithm in removing the uneven luminance within a single image. At present, the difference method and the ratio method are the methods in common use, but they both have their own defects .For example, the difference method can keep the brightness uniformity of the whole image, but it is deficient in local contrast; meanwhile the ratio method can work better in local contrast, but sometimes it makes the dark areas of the original image too bright. In order to remove the defects of the two methods effectively, this paper on the basis of research of the two methods proposes a balance solution. Experiments show that the scheme not only can combine the advantages of the difference method and the ratio method, but also can avoid the deficiencies of the two algorithms.

A computer-vision-based rotating speed estimation method for motor bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Wang, Xiaoxian; Guo, Jie; Lu, Siliang; Shen, Changqing; He, Qingbo

2017-06-01

Diagnosis of motor bearing faults under variable speed is a problem. In this study, a new computer-vision-based order tracking method is proposed to address this problem. First, a video recorded by a high-speed camera is analyzed with the speeded-up robust feature extraction and matching algorithm to obtain the instantaneous rotating speed (IRS) of the motor. Subsequently, an audio signal recorded by a microphone is equi-angle resampled for order tracking in accordance with the IRS curve, through which the frequency-domain signal is transferred to an angular-domain one. The envelope order spectrum is then calculated to determine the fault characteristic order, and finally the bearing fault pattern is determined. The effectiveness and robustness of the proposed method are verified with two brushless direct-current motor test rigs, in which two defective bearings and a healthy bearing are tested separately. This study provides a new noninvasive measurement approach that simultaneously avoids the installation of a tachometer and overcomes the disadvantages of tacholess order tracking methods for motor bearing fault diagnosis under variable speed.

Techniques of Acceleration for Association Rule Induction with Pseudo Artificial Life Algorithm

NASA Astrophysics Data System (ADS)

Kanakubo, Masaaki; Hagiwara, Masafumi

Frequent patterns mining is one of the important problems in data mining. Generally, the number of potential rules grows rapidly as the size of database increases. It is therefore hard for a user to extract the association rules. To avoid such a difficulty, we propose a new method for association rule induction with pseudo artificial life approach. The proposed method is to decide whether there exists an item set which contains N or more items in two transactions. If it exists, a series of item sets which are contained in the part of transactions will be recorded. The iteration of this step contributes to the extraction of association rules. It is not necessary to calculate the huge number of candidate rules. In the evaluation test, we compared the extracted association rules using our method with the rules using other algorithms like Apriori algorithm. As a result of the evaluation using huge retail market basket data, our method is approximately 10 and 20 times faster than the Apriori algorithm and many its variants.

LDA merging and splitting with applications to multiagent cooperative learning and system alteration.

PubMed

Pang, Shaoning; Ban, Tao; Kadobayashi, Youki; Kasabov, Nikola K

2012-04-01

To adapt linear discriminant analysis (LDA) to real-world applications, there is a pressing need to equip it with an incremental learning ability to integrate knowledge presented by one-pass data streams, a functionality to join multiple LDA models to make the knowledge sharing between independent learning agents more efficient, and a forgetting functionality to avoid reconstruction of the overall discriminant eigenspace caused by some irregular changes. To this end, we introduce two adaptive LDA learning methods: LDA merging and LDA splitting. These provide the benefits of ability of online learning with one-pass data streams, retained class separability identical to the batch learning method, high efficiency for knowledge sharing due to condensed knowledge representation by the eigenspace model, and more preferable time and storage costs than traditional approaches under common application conditions. These properties are validated by experiments on a benchmark face image data set. By a case study on the application of the proposed method to multiagent cooperative learning and system alternation of a face recognition system, we further clarified the adaptability of the proposed methods to complex dynamic learning tasks.

Fast determination of the spatially distributed photon fluence for light dose evaluation of PDT

NASA Astrophysics Data System (ADS)

Zhao, Kuanxin; Chen, Weiting; Li, Tongxin; Yan, Panpan; Qin, Zhuanping; Zhao, Huijuan

2018-02-01

Photodynamic therapy (PDT) has shown superiorities of noninvasiveness and high-efficiency in the treatment of early-stage skin cancer. Rapid and accurate determination of spatially distributed photon fluence in turbid tissue is essential for the dosimetry evaluation of PDT. It is generally known that photon fluence can be accurately obtained by Monte Carlo (MC) methods, while too much time would be consumed especially for complex light source mode or online real-time dosimetry evaluation of PDT. In this work, a method to rapidly calculate spatially distributed photon fluence in turbid medium is proposed implementing a classical perturbation and iteration theory on mesh Monte Carlo (MMC). In the proposed method, photon fluence can be obtained by superposing a perturbed and iterative solution caused by the defects in turbid medium to an unperturbed solution for the background medium and therefore repetitive MMC simulations can be avoided. To validate the method, a non-melanoma skin cancer model is carried out. The simulation results show the solution of photon fluence can be obtained quickly and correctly by perturbation algorithm.

a Numerical Method for Stability Analysis of Pinned Flexible Mechanisms

NASA Astrophysics Data System (ADS)

Beale, D. G.; Lee, S. W.

1996-05-01

A technique is presented to investigate the stability of mechanisms with pin-jointed flexible members. The method relies on a special floating frame from which elastic link co-ordinates are defined. Energies are easily developed for use in a Lagrange equation formulation, leading to a set of non-linear and mixed ordinary differential-algebraic equations of motion with constraints. Stability and bifurcation analysis is handled using a numerical procedure (generalized co-ordinate partitioning) that avoids the tedious and difficult task of analytically reducing the system of equations to a number equalling the system degrees of freedom. The proposed method was then applied to (1) a slider-crank mechanism with a flexible connecting rod and crank of constant rotational speed, and (2) a four-bar linkage with a flexible coupler with a constant speed crank. In both cases, a single pinned-pinned beam bending mode is employed to develop resonance curves and stability boundaries in the crank length-crank speed parameter plane. Flip and fold bifurcations are common occurrences in both mechanisms. The accuracy of the proposed method was also verified by comparison with previous experimental results [1].

Route visualization using detail lenses.

PubMed

Karnick, Pushpak; Cline, David; Jeschke, Stefan; Razdan, Anshuman; Wonka, Peter

2010-01-01

We present a method designed to address some limitations of typical route map displays of driving directions. The main goal of our system is to generate a printable version of a route map that shows the overview and detail views of the route within a single, consistent visual frame. Our proposed visualization provides a more intuitive spatial context than a simple list of turns. We present a novel multifocus technique to achieve this goal, where the foci are defined by points of interest (POI) along the route. A detail lens that encapsulates the POI at a finer geospatial scale is created for each focus. The lenses are laid out on the map to avoid occlusion with the route and each other, and to optimally utilize the free space around the route. We define a set of layout metrics to evaluate the quality of a lens layout for a given route map visualization. We compare standard lens layout methods to our proposed method and demonstrate the effectiveness of our method in generating aesthetically pleasing layouts. Finally, we perform a user study to evaluate the effectiveness of our layout choices.

A level set-based topology optimization method for simultaneous design of elastic structure and coupled acoustic cavity using a two-phase material model

NASA Astrophysics Data System (ADS)

Noguchi, Yuki; Yamamoto, Takashi; Yamada, Takayuki; Izui, Kazuhiro; Nishiwaki, Shinji

2017-09-01

This papers proposes a level set-based topology optimization method for the simultaneous design of acoustic and structural material distributions. In this study, we develop a two-phase material model that is a mixture of an elastic material and acoustic medium, to represent an elastic structure and an acoustic cavity by controlling a volume fraction parameter. In the proposed model, boundary conditions at the two-phase material boundaries are satisfied naturally, avoiding the need to express these boundaries explicitly. We formulate a topology optimization problem to minimize the sound pressure level using this two-phase material model and a level set-based method that obtains topologies free from grayscales. The topological derivative of the objective functional is approximately derived using a variational approach and the adjoint variable method and is utilized to update the level set function via a time evolutionary reaction-diffusion equation. Several numerical examples present optimal acoustic and structural topologies that minimize the sound pressure generated from a vibrating elastic structure.

Two-dimensional imaging via a narrowband MIMO radar system with two perpendicular linear arrays.

PubMed

Wang, Dang-wei; Ma, Xiao-yan; Su, Yi

2010-05-01

This paper presents a system model and method for the 2-D imaging application via a narrowband multiple-input multiple-output (MIMO) radar system with two perpendicular linear arrays. Furthermore, the imaging formulation for our method is developed through a Fourier integral processing, and the parameters of antenna array including the cross-range resolution, required size, and sampling interval are also examined. Different from the spatial sequential procedure sampling the scattered echoes during multiple snapshot illuminations in inverse synthetic aperture radar (ISAR) imaging, the proposed method utilizes a spatial parallel procedure to sample the scattered echoes during a single snapshot illumination. Consequently, the complex motion compensation in ISAR imaging can be avoided. Moreover, in our array configuration, multiple narrowband spectrum-shared waveforms coded with orthogonal polyphase sequences are employed. The mainlobes of the compressed echoes from the different filter band could be located in the same range bin, and thus, the range alignment in classical ISAR imaging is not necessary. Numerical simulations based on synthetic data are provided for testing our proposed method.

Meta-analysis of alcohol price and income elasticities – with corrections for publication bias

PubMed Central

2013-01-01

Background This paper contributes to the evidence-base on prices and alcohol use by presenting meta-analytic summaries of price and income elasticities for alcohol beverages. The analysis improves on previous meta-analyses by correcting for outliers and publication bias. Methods Adjusting for outliers is important to avoid assigning too much weight to studies with very small standard errors or large effect sizes. Trimmed samples are used for this purpose. Correcting for publication bias is important to avoid giving too much weight to studies that reflect selection by investigators or others involved with publication processes. Cumulative meta-analysis is proposed as a method to avoid or reduce publication bias, resulting in more robust estimates. The literature search obtained 182 primary studies for aggregate alcohol consumption, which exceeds the database used in previous reviews and meta-analyses. Results For individual beverages, corrected price elasticities are smaller (less elastic) by 28-29 percent compared with consensus averages frequently used for alcohol beverages. The average price and income elasticities are: beer, -0.30 and 0.50; wine, -0.45 and 1.00; and spirits, -0.55 and 1.00. For total alcohol, the price elasticity is -0.50 and the income elasticity is 0.60. Conclusions These new results imply that attempts to reduce alcohol consumption through price or tax increases will be less effective or more costly than previously claimed. PMID:23883547

Detecting associated single-nucleotide polymorphisms on the X chromosome in case control genome-wide association studies.

PubMed

Chen, Zhongxue; Ng, Hon Keung Tony; Li, Jing; Liu, Qingzhong; Huang, Hanwen

2017-04-01

In the past decade, hundreds of genome-wide association studies have been conducted to detect the significant single-nucleotide polymorphisms that are associated with certain diseases. However, most of the data from the X chromosome were not analyzed and only a few significant associated single-nucleotide polymorphisms from the X chromosome have been identified from genome-wide association studies. This is mainly due to the lack of powerful statistical tests. In this paper, we propose a novel statistical approach that combines the information of single-nucleotide polymorphisms on the X chromosome from both males and females in an efficient way. The proposed approach avoids the need of making strong assumptions about the underlying genetic models. Our proposed statistical test is a robust method that only makes the assumption that the risk allele is the same for both females and males if the single-nucleotide polymorphism is associated with the disease for both genders. Through simulation study and a real data application, we show that the proposed procedure is robust and have excellent performance compared to existing methods. We expect that many more associated single-nucleotide polymorphisms on the X chromosome will be identified if the proposed approach is applied to current available genome-wide association studies data.

Free-end adaptive nudged elastic band method for locating transition states in minimum energy path calculation.

PubMed

Zhang, Jiayong; Zhang, Hongwu; Ye, Hongfei; Zheng, Yonggang

2016-09-07

A free-end adaptive nudged elastic band (FEA-NEB) method is presented for finding transition states on minimum energy paths, where the energy barrier is very narrow compared to the whole paths. The previously proposed free-end nudged elastic band method may suffer from convergence problems because of the kinks arising on the elastic band if the initial elastic band is far from the minimum energy path and weak springs are adopted. We analyze the origin of the formation of kinks and present an improved free-end algorithm to avoid the convergence problem. Moreover, by coupling the improved free-end algorithm and an adaptive strategy, we develop a FEA-NEB method to accurately locate the transition state with the elastic band cut off repeatedly and the density of images near the transition state increased. Several representative numerical examples, including the dislocation nucleation in a penta-twinned nanowire, the twin boundary migration under a shear stress, and the cross-slip of screw dislocation in face-centered cubic metals, are investigated by using the FEA-NEB method. Numerical results demonstrate both the stability and efficiency of the proposed method.

Efficient multidimensional regularization for Volterra series estimation

NASA Astrophysics Data System (ADS)

Birpoutsoukis, Georgios; Csurcsia, Péter Zoltán; Schoukens, Johan

2018-05-01

This paper presents an efficient nonparametric time domain nonlinear system identification method. It is shown how truncated Volterra series models can be efficiently estimated without the need of long, transient-free measurements. The method is a novel extension of the regularization methods that have been developed for impulse response estimates of linear time invariant systems. To avoid the excessive memory needs in case of long measurements or large number of estimated parameters, a practical gradient-based estimation method is also provided, leading to the same numerical results as the proposed Volterra estimation method. Moreover, the transient effects in the simulated output are removed by a special regularization method based on the novel ideas of transient removal for Linear Time-Varying (LTV) systems. Combining the proposed methodologies, the nonparametric Volterra models of the cascaded water tanks benchmark are presented in this paper. The results for different scenarios varying from a simple Finite Impulse Response (FIR) model to a 3rd degree Volterra series with and without transient removal are compared and studied. It is clear that the obtained models capture the system dynamics when tested on a validation dataset, and their performance is comparable with the white-box (physical) models.

Fluorometric enzymatic assay of L-arginine

NASA Astrophysics Data System (ADS)

Stasyuk, Nataliya; Gayda, Galina; Yepremyan, Hasmik; Stepien, Agnieszka; Gonchar, Mykhailo

2017-01-01

The enzymes of L-arginine (further - Arg) metabolism are promising tools for elaboration of selective methods for quantitative Arg analysis. In our study we propose an enzymatic method for Arg assay based on fluorometric monitoring of ammonia, a final product of Arg splitting by human liver arginase I (further - arginase), isolated from the recombinant yeast strain, and commercial urease. The selective analysis of ammonia (at 415 nm under excitation at 360 nm) is based on reaction with o-phthalaldehyde (OPA) in the presence of sulfite in alkali medium: these conditions permit to avoid the reaction of OPA with any amino acid. A linearity range of the fluorometric arginase-urease-OPA method is from 100 nM to 6 μМ with a limit of detection of 34 nM Arg. The method was used for the quantitative determination of Arg in the pooled sample of blood serum. The obtained results proved to be in a good correlation with the reference enzymatic method and literature data. The proposed arginase-urease-OPA method being sensitive, economical, selective and suitable for both routine and micro-volume formats, can be used in clinical diagnostics for the simultaneous determination of Arg as well as urea and ammonia in serum samples.

Slope angle estimation method based on sparse subspace clustering for probe safe landing

NASA Astrophysics Data System (ADS)

Li, Haibo; Cao, Yunfeng; Ding, Meng; Zhuang, Likui

2018-06-01

To avoid planetary probes landing on steep slopes where they may slip or tip over, a new method of slope angle estimation based on sparse subspace clustering is proposed to improve accuracy. First, a coordinate system is defined and established to describe the measured data of light detection and ranging (LIDAR). Second, this data is processed and expressed with a sparse representation. Third, on this basis, the data is made to cluster to determine which subspace it belongs to. Fourth, eliminating outliers in subspace, the correct data points are used for the fitting planes. Finally, the vectors normal to the planes are obtained using the plane model, and the angle between the normal vectors is obtained through calculation. Based on the geometric relationship, this angle is equal in value to the slope angle. The proposed method was tested in a series of experiments. The experimental results show that this method can effectively estimate the slope angle, can overcome the influence of noise and obtain an exact slope angle. Compared with other methods, this method can minimize the measuring errors and further improve the estimation accuracy of the slope angle.

Single-step reinitialization and extending algorithms for level-set based multi-phase flow simulations

NASA Astrophysics Data System (ADS)

Fu, Lin; Hu, Xiangyu Y.; Adams, Nikolaus A.

2017-12-01

We propose efficient single-step formulations for reinitialization and extending algorithms, which are critical components of level-set based interface-tracking methods. The level-set field is reinitialized with a single-step (non iterative) "forward tracing" algorithm. A minimum set of cells is defined that describes the interface, and reinitialization employs only data from these cells. Fluid states are extrapolated or extended across the interface by a single-step "backward tracing" algorithm. Both algorithms, which are motivated by analogy to ray-tracing, avoid multiple block-boundary data exchanges that are inevitable for iterative reinitialization and extending approaches within a parallel-computing environment. The single-step algorithms are combined with a multi-resolution conservative sharp-interface method and validated by a wide range of benchmark test cases. We demonstrate that the proposed reinitialization method achieves second-order accuracy in conserving the volume of each phase. The interface location is invariant to reapplication of the single-step reinitialization. Generally, we observe smaller absolute errors than for standard iterative reinitialization on the same grid. The computational efficiency is higher than for the standard and typical high-order iterative reinitialization methods. We observe a 2- to 6-times efficiency improvement over the standard method for serial execution. The proposed single-step extending algorithm, which is commonly employed for assigning data to ghost cells with ghost-fluid or conservative interface interaction methods, shows about 10-times efficiency improvement over the standard method while maintaining same accuracy. Despite their simplicity, the proposed algorithms offer an efficient and robust alternative to iterative reinitialization and extending methods for level-set based multi-phase simulations.

Safety of High Speed Guided Ground Transportation Systems: Collision Avoidance and Accident Survivability Volume 4: Proposed Specifications

DOT National Transportation Integrated Search

1993-03-01

This report is the fourth of four volumes concerned with developing safety guidelines and specifications for high-speed : guided ground transportation (HSGGT) collision avoidance and accident survivability. The overall approach taken in this : study ...

An alternative respiratory sounds classification system utilizing artificial neural networks.

PubMed

Oweis, Rami J; Abdulhay, Enas W; Khayal, Amer; Awad, Areen

2015-01-01

Computerized lung sound analysis involves recording lung sound via an electronic device, followed by computer analysis and classification based on specific signal characteristics as non-linearity and nonstationarity caused by air turbulence. An automatic analysis is necessary to avoid dependence on expert skills. This work revolves around exploiting autocorrelation in the feature extraction stage. All process stages were implemented in MATLAB. The classification process was performed comparatively using both artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFIS) toolboxes. The methods have been applied to 10 different respiratory sounds for classification. The ANN was superior to the ANFIS system and returned superior performance parameters. Its accuracy, specificity, and sensitivity were 98.6%, 100%, and 97.8%, respectively. The obtained parameters showed superiority to many recent approaches. The promising proposed method is an efficient fast tool for the intended purpose as manifested in the performance parameters, specifically, accuracy, specificity, and sensitivity. Furthermore, it may be added that utilizing the autocorrelation function in the feature extraction in such applications results in enhanced performance and avoids undesired computation complexities compared to other techniques.

Trajectory optimization for lunar soft landing with complex constraints

NASA Astrophysics Data System (ADS)

Chu, Huiping; Ma, Lin; Wang, Kexin; Shao, Zhijiang; Song, Zhengyu

2017-11-01

A unified trajectory optimization framework with initialization strategies is proposed in this paper for lunar soft landing for various missions with specific requirements. Two main missions of interest are Apollo-like Landing from low lunar orbit and Vertical Takeoff Vertical Landing (a promising mobility method) on the lunar surface. The trajectory optimization is characterized by difficulties arising from discontinuous thrust, multi-phase connections, jump of attitude angle, and obstacles avoidance. Here R-function is applied to deal with the discontinuities of thrust, checkpoint constraints are introduced to connect multiple landing phases, attitude angular rate is designed to get rid of radical changes, and safeguards are imposed to avoid collision with obstacles. The resulting dynamic problems are generally with complex constraints. The unified framework based on Gauss Pseudospectral Method (GPM) and Nonlinear Programming (NLP) solver are designed to solve the problems efficiently. Advanced initialization strategies are developed to enhance both the convergence and computation efficiency. Numerical results demonstrate the adaptability of the framework for various landing missions, and the performance of successful solution of difficult dynamic problems.

Proposal on a sustainable strategy to avoid point source pollution of water with plant protection products.

PubMed

Mestdagh, Inge; Bonicelli, Bernard; Laplana, Ramon; Roettele, Manfred

2009-01-01

Based on the results and lessons learned from the TOPPS project (Training the Operators to prevent Pollution from Point Sources), a proposal on a sustainable strategy to avoid point source pollution from Plant Protection Products (PPPs) was made. Within this TOPPS project (2005-2008), stakeholders were interviewed and research and analysis were done in 6 pilot catchment areas (BE, FR, DE, DK, IT, PL). Next, there was a repeated survey on operators' perception and opinion to measure changes resulting from TOPPS activities and good and bad practices were defined based on the Best Management Practices (risk analysis). Aim of the proposal is to suggest a strategy considering the differences between countries which can be implemented on Member State level in order to avoid PPP pollution of water through point sources. The methodology used for the up-scaLing proposal consists of the analysis of the current situation, a gap analysis, a consistency analysis and organisational structures for implementation. The up-scaling proposal focuses on the behaviour of the operators, on the equipment and infrastructure available with the operators. The proposal defines implementation structures to support correct behaviour through the development and updating of Best Management Practices (BMPs) and through the transfer and the implementation of these BMPs. Next, the proposal also defines requirements for the improvement of equipment and infrastructure based on the defined key factors related to point source pollution. It also contains cost estimates for technical and infrastructure upgrades to comply with BMPs.

Neighborhood Discriminant Hashing for Large-Scale Image Retrieval.

PubMed

Tang, Jinhui; Li, Zechao; Wang, Meng; Zhao, Ruizhen

2015-09-01

With the proliferation of large-scale community-contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample can be inherited from the neighbor samples it selects. The hashing function is expected to be orthogonal to avoid redundancy in the learned hashing bits as much as possible, while an information theoretic regularization is jointly exploited using maximum entropy principle. As a consequence, the learned hashing function is compact and nonredundant among bits, while each bit is highly informative. Extensive experiments are carried out on four publicly available data sets and the comparison results demonstrate the outperforming performance of the proposed NDH method over state-of-the-art hashing techniques.

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow

PubMed Central

Zhang, Weilong; Guo, Bingxuan; Liao, Xuan; Li, Wenzhuo

2018-01-01

Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images. PMID:29659526

A bat algorithm with mutation for UCAV path planning.

PubMed

Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi

2012-01-01

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models.

Prescribed Velocity Gradients for Highly Viscous SPH Fluids with Vorticity Diffusion.

PubMed

Peer, Andreas; Teschner, Matthias

2017-12-01

Working with prescribed velocity gradients is a promising approach to efficiently and robustly simulate highly viscous SPH fluids. Such approaches allow to explicitly and independently process shear rate, spin, and expansion rate. This can be used to, e.g., avoid interferences between pressure and viscosity solvers. Another interesting aspect is the possibility to explicitly process the vorticity, e.g., to preserve the vorticity. In this context, this paper proposes a novel variant of the prescribed-gradient idea that handles vorticity in a physically motivated way. In contrast to a less appropriate vorticity preservation that has been used in a previous approach, vorticity is diffused. The paper illustrates the utility of the vorticity diffusion. Therefore, comparisons of the proposed vorticity diffusion with vorticity preservation and additionally with vorticity damping are presented. The paper further discusses the relation between prescribed velocity gradients and prescribed velocity Laplacians which improves the intuition behind the prescribed-gradient method for highly viscous SPH fluids. Finally, the paper discusses the relation of the proposed method to a physically correct implicit viscosity formulation.

Model reduction method using variable-separation for stochastic saddle point problems

NASA Astrophysics Data System (ADS)

Jiang, Lijian; Li, Qiuqi

2018-02-01

In this paper, we consider a variable-separation (VS) method to solve the stochastic saddle point (SSP) problems. The VS method is applied to obtain the solution in tensor product structure for stochastic partial differential equations (SPDEs) in a mixed formulation. The aim of such a technique is to construct a reduced basis approximation of the solution of the SSP problems. The VS method attempts to get a low rank separated representation of the solution for SSP in a systematic enrichment manner. No iteration is performed at each enrichment step. In order to satisfy the inf-sup condition in the mixed formulation, we enrich the separated terms for the primal system variable at each enrichment step. For the SSP problems by regularization or penalty, we propose a more efficient variable-separation (VS) method, i.e., the variable-separation by penalty method. This can avoid further enrichment of the separated terms in the original mixed formulation. The computation of the variable-separation method decomposes into offline phase and online phase. Sparse low rank tensor approximation method is used to significantly improve the online computation efficiency when the number of separated terms is large. For the applications of SSP problems, we present three numerical examples to illustrate the performance of the proposed methods.

Effective classification of the prevalence of Schistosoma mansoni.

PubMed

Mitchell, Shira A; Pagano, Marcello

2012-12-01

To present an effective classification method based on the prevalence of Schistosoma mansoni in the community. We created decision rules (defined by cut-offs for number of positive slides), which account for imperfect sensitivity, both with a simple adjustment of fixed sensitivity and with a more complex adjustment of changing sensitivity with prevalence. To reduce screening costs while maintaining accuracy, we propose a pooled classification method. To estimate sensitivity, we use the De Vlas model for worm and egg distributions. We compare the proposed method with the standard method to investigate differences in efficiency, measured by number of slides read, and accuracy, measured by probability of correct classification. Modelling varying sensitivity lowers the lower cut-off more significantly than the upper cut-off, correctly classifying regions as moderate rather than lower, thus receiving life-saving treatment. The classification method goes directly to classification on the basis of positive pools, avoiding having to know sensitivity to estimate prevalence. For model parameter values describing worm and egg distributions among children, the pooled method with 25 slides achieves an expected 89.9% probability of correct classification, whereas the standard method with 50 slides achieves 88.7%. Among children, it is more efficient and more accurate to use the pooled method for classification of S. mansoni prevalence than the current standard method. © 2012 Blackwell Publishing Ltd.

A novel method to remove GPR background noise based on the similarity of non-neighboring regions

NASA Astrophysics Data System (ADS)

Montiel-Zafra, V.; Canadas-Quesada, F. J.; Vera-Candeas, P.; Ruiz-Reyes, N.; Rey, J.; Martinez, J.

2017-09-01

Ground penetrating radar (GPR) is a non-destructive technique that has been widely used in many areas of research, such as landmine detection or subsurface anomalies, where it is required to locate targets embedded within a background medium. One of the major challenges in the research of GPR data remains the improvement of the image quality of stone materials by means of detection of true anisotropies since most of the errors are caused by an incorrect interpretation by the users. However, it is complicated due to the interference of the horizontal background noise, e.g., the air-ground interface, that reduces the high-resolution quality of radargrams. Thus, weak or deep anisotropies are often masked by this type of noise. In order to remove the background noise obtained by GPR, this work proposes a novel background removal method assuming that the horizontal noise shows repetitive two-dimensional regions along the movement of the GPR antenna. Specifically, the proposed method, based on the non-local similarity of regions over the distance, computes similarities between different regions of the same depth in order to identify most repetitive regions using a criterion to avoid closer regions. Evaluations are performed using a set of synthetic and real GPR data. Experimental results show that the proposed method obtains promising results compared to the classic background removal techniques and the most recently published background removal methods.

The Sedov Blast Wave as a Radial Piston Verification Test

DOE PAGES

Pederson, Clark; Brown, Bart; Morgan, Nathaniel

2016-06-22

The Sedov blast wave is of great utility as a verification problem for hydrodynamic methods. The typical implementation uses an energized cell of finite dimensions to represent the energy point source. We avoid this approximation by directly finding the effects of the energy source as a boundary condition (BC). Furthermore, the proposed method transforms the Sedov problem into an outward moving radial piston problem with a time-varying velocity. A portion of the mesh adjacent to the origin is removed and the boundaries of this hole are forced with the velocities from the Sedov solution. This verification test is implemented onmore » two types of meshes, and convergence is shown. Our results from the typical initial condition (IC) method and the new BC method are compared.« less

Color Image Enhancement Using Multiscale Retinex Based on Particle Swarm Optimization Method

NASA Astrophysics Data System (ADS)

Matin, F.; Jeong, Y.; Kim, K.; Park, K.

2018-01-01

This paper introduces, a novel method for the image enhancement using multiscale retinex and practical swarm optimization. Multiscale retinex is widely used image enhancement technique which intemperately pertains on parameters such as Gaussian scales, gain and offset, etc. To achieve the privileged effect, the parameters need to be tuned manually according to the image. In order to handle this matter, a developed retinex algorithm based on PSO has been used. The PSO method adjusted the parameters for multiscale retinex with chromaticity preservation (MSRCP) attains better outcome to compare with other existing methods. The experimental result indicates that the proposed algorithm is an efficient one and not only provides true color loyalty in low light conditions but also avoid color distortion at the same time.

An efficient interior-point algorithm with new non-monotone line search filter method for nonlinear constrained programming

NASA Astrophysics Data System (ADS)

Wang, Liwei; Liu, Xinggao; Zhang, Zeyin

2017-02-01

An efficient primal-dual interior-point algorithm using a new non-monotone line search filter method is presented for nonlinear constrained programming, which is widely applied in engineering optimization. The new non-monotone line search technique is introduced to lead to relaxed step acceptance conditions and improved convergence performance. It can also avoid the choice of the upper bound on the memory, which brings obvious disadvantages to traditional techniques. Under mild assumptions, the global convergence of the new non-monotone line search filter method is analysed, and fast local convergence is ensured by second order corrections. The proposed algorithm is applied to the classical alkylation process optimization problem and the results illustrate its effectiveness. Some comprehensive comparisons to existing methods are also presented.

Anterior clinoidectomy using an extradural and intradural 2-step hybrid technique.

PubMed

Tayebi Meybodi, Ali; Lawton, Michael T; Yousef, Sonia; Guo, Xiaoming; González Sánchez, Jose Juan; Tabani, Halima; García, Sergio; Burkhardt, Jan-Karl; Benet, Arnau

2018-02-23

Anterior clinoidectomy is a difficult yet essential technique in skull base surgery. Two main techniques (extradural and intradural) with multiple modifications have been proposed to increase efficiency and avoid complications. In this study, the authors sought to develop a hybrid technique based on localization of the optic strut (OS) to combine the advantages and avoid the disadvantages of both techniques. Ten cadaveric specimens were prepared for surgical simulation. After a standard pterional craniotomy, the anterior clinoid process (ACP) was resected in 2 steps. The segment anterior to the OS was resected extradurally, while the segment posterior to the OS was resected intradurally. The proposed technique was performed in 6 clinical cases to evaluate its safety and efficiency. Anterior clinoidectomy was successfully performed in all cadaveric specimens and all 6 patients by using the proposed technique. The extradural phase enabled early decompression of the optic nerve while avoiding the adjacent internal carotid artery. The OS was drilled intradurally under direct visualization of the adjacent neurovascular structures. The described landmarks were easily identifiable and applicable in the surgically treated patients. No operative complication was encountered. A proposed 2-step hybrid technique combines the advantages of the extradural and intradural techniques while avoiding their disadvantages. This technique allows reduced intradural drilling and subarachnoid bone dust deposition. Moreover, the most critical part of the clinoidectomy-that is, drilling of the OS and removal of the body of the ACP-is left for the intradural phase, when critical neurovascular structures can be directly viewed.

Micro-Doppler Ambiguity Resolution for Wideband Terahertz Radar Using Intra-Pulse Interference

PubMed Central

Yang, Qi; Qin, Yuliang; Deng, Bin; Wang, Hongqiang; You, Peng

2017-01-01

Micro-Doppler, induced by micro-motion of targets, is an important characteristic of target recognition once extracted via parameter estimation methods. However, micro-Doppler is usually too significant to result in ambiguity in the terahertz band because of its relatively high carrier frequency. Thus, a micro-Doppler ambiguity resolution method for wideband terahertz radar using intra-pulse interference is proposed in this paper. The micro-Doppler can be reduced several dozen times its true value to avoid ambiguity through intra-pulse interference processing. The effectiveness of this method is proved by experiments based on a 0.22 THz wideband radar system, and its high estimation precision and excellent noise immunity are verified by Monte Carlo simulation. PMID:28468257

Safe-trajectory optimization and tracking control in ultra-close proximity to a failed satellite

NASA Astrophysics Data System (ADS)

Zhang, Jingrui; Chu, Xiaoyu; Zhang, Yao; Hu, Quan; Zhai, Guang; Li, Yanyan

2018-03-01

This paper presents a trajectory-optimization method for a chaser spacecraft operating in ultra-close proximity to a failed satellite. Based on the combination of active and passive trajectory protection, the constraints in the optimization framework are formulated for collision avoidance and successful docking in the presence of any thruster failure. The constraints are then handled by an adaptive Gauss pseudospectral method, in which the dynamic residuals are used as the metric to determine the distribution of collocation points. A finite-time feedback control is further employed in tracking the optimized trajectory. In particular, the stability and convergence of the controller are proved. Numerical results are given to demonstrate the effectiveness of the proposed methods.

Micro-Doppler Ambiguity Resolution for Wideband Terahertz Radar Using Intra-Pulse Interference.

PubMed

Yang, Qi; Qin, Yuliang; Deng, Bin; Wang, Hongqiang; You, Peng

2017-04-29

Micro-Doppler, induced by micro-motion of targets, is an important characteristic of target recognition once extracted via parameter estimation methods. However, micro-Doppler is usually too significant to result in ambiguity in the terahertz band because of its relatively high carrier frequency. Thus, a micro-Doppler ambiguity resolution method for wideband terahertz radar using intra-pulse interference is proposed in this paper. The micro-Doppler can be reduced several dozen times its true value to avoid ambiguity through intra-pulse interference processing. The effectiveness of this method is proved by experiments based on a 0.22 THz wideband radar system, and its high estimation precision and excellent noise immunity are verified by Monte Carlo simulation.

Testing the statistical compatibility of independent data sets

NASA Astrophysics Data System (ADS)

Maltoni, M.; Schwetz, T.

2003-08-01

We discuss a goodness-of-fit method which tests the compatibility between statistically independent data sets. The method gives sensible results even in cases where the χ2 minima of the individual data sets are very low or when several parameters are fitted to a large number of data points. In particular, it avoids the problem that a possible disagreement between data sets becomes diluted by data points which are insensitive to the crucial parameters. A formal derivation of the probability distribution function for the proposed test statistics is given, based on standard theorems of statistics. The application of the method is illustrated on data from neutrino oscillation experiments, and its complementarity to the standard goodness-of-fit is discussed.

Analysis of nitrites and nitrates in hams and sausages by open-tubular capillary electrochromatography with a nanolatex-coated capillary column.

PubMed

Zhang, Yanhao; Tian, Xiangyu; Guo, Yaxiao; Li, Haibin; Yu, Ajuan; Deng, Zhifen; Sun, Barry Baoguo; Zhang, Shusheng

2014-04-16

In this work, a new open-tubular capillary electrochromatography (OT-CEC) method with the nanolatex-coated column was proposed for the determination of nitrites and nitrates in foodstuffs. The method was simple and repeatable as a result of avoiding the introduction of an electroosmotic flow reverse additive (such as cetyltrimethylammonium chloride) in electrophoretic buffer. The limits of quantitation were 0.89 and 1.05 mg kg⁻¹ for nitrate and nitrite, respectively, whereas the overall recoveries ranged from 94 to 103%. The developed OT-CEC method was successfully applied for 12 samples, and the residue profiles of nitrites and nitrates in hams and sausages were obtained and evaluated.

Safety of high-speed guided ground transportation systems : collision avoidance and accident survivability : volume 4 : proposed specifications

DOT National Transportation Integrated Search

1993-03-01

This report is the fourth of four volumes concerned with developing safety guidelines and specifications for high-speed guided ground transportation (HSGGT) collision avoidance and accident survivability. The overall approach taken in this study is t...

Non-contact data access with direction identification for industrial differential serial bus

NASA Astrophysics Data System (ADS)

Xie, Kai; Li, Xiaoping; Zhang, Hanlu; Yang, Ming; Ye, Yinghao

2013-06-01

We propose a non-contact method for accessing data in industrial differential serial bus applications, which could serve as an effective and safe online testing and diagnosing tool. The data stream and the transmission direction are reconstructed simultaneously from the near-field emanations of a twisted pair, eliminating direct contact with the actual conductors, and avoiding damage to the insulation (only the outer sheathing is removed). A non-contact probe with the ability to sense electric and magnetic fields is presented, as are theories for data reconstruction, direction identification, and a circuit implementation. The prototype was built using inexpensive components and then tested on a standard RS-485 industrial serial bus. Experimental results verified the validity of the proposed scheme.

Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging.

PubMed

Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

2017-11-07

This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

Lane marking detection based on waveform analysis and CNN

NASA Astrophysics Data System (ADS)

Ye, Yang Yang; Chen, Hou Jin; Hao, Xiao Li

2017-06-01

Lane markings detection is a very important part of the ADAS to avoid traffic accidents. In order to obtain accurate lane markings, in this work, a novel and efficient algorithm is proposed, which analyses the waveform generated from the road image after inverse perspective mapping (IPM). The algorithm includes two main stages: the first stage uses an image preprocessing including a CNN to reduce the background and enhance the lane markings. The second stage obtains the waveform of the road image and analyzes the waveform to get lanes. The contribution of this work is that we introduce local and global features of the waveform to detect the lane markings. The results indicate the proposed method is robust in detecting and fitting the lane markings.

Proposal of a method for the evaluation of inaccuracy of home sphygmomanometers.

PubMed

Akpolat, Tekin

2009-10-01

There is no formal protocol for evaluating the individual accuracy of home sphygmomanometers. The aims of this study were to propose a method for achieving accuracy in automated home sphygmomanometers and to test the applicability of the defined method. The purposes of this method were to avoid major inaccuracies and to estimate the optimal circumstance for individual accuracy. The method has three stages and sequential measurement of blood pressure is used. The tested devices were categorized into four groups: accurate, acceptable, inaccurate and very inaccurate (major inaccuracy). The defined method takes approximately 10 min (excluding relaxation time) and was tested on three different occasions. The application of the method has shown that inaccuracy is a common problem among non-tested devices, that validated devices are superior to those that are non-validated or whose validation status is unknown, that major inaccuracy is common, especially in non-tested devices and that validation does not guarantee individual accuracy. A protocol addressing the accuracy of a particular sphygmomanometer in an individual patient is required, and a practical method has been suggested to achieve this. This method can be modified, but the main idea and approach should be preserved unless a better method is proposed. The purchase of validated devices and evaluation of accuracy for the purchased device in an individual patient will improve the monitoring of self-measurement of blood pressure at home. This study addresses device inaccuracy, but errors related to the patient, observer or blood pressure measurement technique should not be underestimated, and strict adherence to the manufacturer's instructions is essential.

Analytical Approaches for Identification and Representation of Critical Protection Systems in Transient Stability Studies

NASA Astrophysics Data System (ADS)

Hedman, Mojdeh Khorsand

After a major disturbance, the power system response is highly dependent on protection schemes and system dynamics. Improving power systems situational awareness requires proper and simultaneous modeling of both protection schemes and dynamic characteristics in power systems analysis tools. Historical information and ex-post analysis of blackouts reaffirm the critical role of protective devices in cascading events, thereby confirming the necessity to represent protective functions in transient stability studies. This dissertation is aimed at studying the importance of representing protective relays in power system dynamic studies. Although modeling all of the protective relays within transient stability studies may result in a better estimation of system behavior, representing, updating, and maintaining the protection system data becomes an insurmountable task. Inappropriate or outdated representation of the relays may result in incorrect assessment of the system behavior. This dissertation presents a systematic method to determine essential relays to be modeled in transient stability studies. The desired approach should identify protective relays that are critical for various operating conditions and contingencies. The results of the transient stability studies confirm that modeling only the identified critical protective relays is sufficient to capture system behavior for various operating conditions and precludes the need to model all of the protective relays. Moreover, this dissertation proposes a method that can be implemented to determine the appropriate location of out-of-step blocking relays. During unstable power swings, a generator or group of generators may accelerate or decelerate leading to voltage depression at the electrical center along with generator tripping. This voltage depression may cause protective relay mis-operation and unintentional separation of the system. In order to avoid unintentional islanding, the potentially mis-operating relays should be blocked from tripping with the use of out-of-step blocking schemes. Blocking these mis-operating relays, combined with an appropriate islanding scheme, help avoid a system wide collapse. The proposed method is tested on data from the Western Electricity Coordinating Council. A triple line outage of the California-Oregon Intertie is studied. The results show that the proposed method is able to successfully identify proper locations of out-of-step blocking scheme.

Evolution of Toxoplasma-PCR methods and practices: a French national survey and proposal for technical guidelines.

PubMed

Roux, Guillaume; Varlet-Marie, Emmanuelle; Bastien, Patrick; Sterkers, Yvon

2018-06-08

The molecular diagnosis of toxoplasmosis lacks standardisation due to the use of numerous methods with variable performance. This diversity of methods also impairs robust performance comparisons between laboratories. The harmonisation of practices by diffusion of technical guidelines is a useful way to improve these performances. The knowledge of methods and practices used for this molecular diagnosis is an essential step to provide guidelines for Toxoplasma-PCR. In the present study, we aimed (i) to describe the methods and practices of Toxoplasma-PCR used by clinical microbiology laboratories in France and (ii) to propose technical guidelines to improve molecular diagnosis of toxoplasmosis. To do so, a yearly self-administered questionnaire-based survey was undertaken in proficient French laboratories from 2008 to 2015, and guidelines were proposed based on the results of those as well as previously published work. This period saw the progressive abandonment of conventional PCR methods, of Toxoplasma-PCR targeting the B1 gene and of the use of two concomitant molecular methods for this diagnosis. The diversity of practices persisted during the study, in spite of the increasing use of commercial kits such as PCR kits, DNA extraction controls and PCR inhibition controls. We also observed a tendency towards the automation of DNA extraction. The evolution of practices did not always go together with an improvement in those, as reported notably by the declining use of Uracil-DNA Glycosylase to avoid carry-over contamination. We here propose technical recommendations which correspond to items explored during the survey, with respect to DNA extraction, Toxoplasma-PCR and good PCR practices. Copyright © 2018 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

Reentry trajectory optimization based on a multistage pseudospectral method.

PubMed

Zhao, Jiang; Zhou, Rui; Jin, Xuelian

2014-01-01

Of the many direct numerical methods, the pseudospectral method serves as an effective tool to solve the reentry trajectory optimization for hypersonic vehicles. However, the traditional pseudospectral method is time-consuming due to large number of discretization points. For the purpose of autonomous and adaptive reentry guidance, the research herein presents a multistage trajectory control strategy based on the pseudospectral method, capable of dealing with the unexpected situations in reentry flight. The strategy typically includes two subproblems: the trajectory estimation and trajectory refining. In each processing stage, the proposed method generates a specified range of trajectory with the transition of the flight state. The full glide trajectory consists of several optimal trajectory sequences. The newly focused geographic constraints in actual flight are discussed thereafter. Numerical examples of free-space flight, target transition flight, and threat avoidance flight are used to show the feasible application of multistage pseudospectral method in reentry trajectory optimization.

Reentry Trajectory Optimization Based on a Multistage Pseudospectral Method

PubMed Central

Zhou, Rui; Jin, Xuelian

2014-01-01

Of the many direct numerical methods, the pseudospectral method serves as an effective tool to solve the reentry trajectory optimization for hypersonic vehicles. However, the traditional pseudospectral method is time-consuming due to large number of discretization points. For the purpose of autonomous and adaptive reentry guidance, the research herein presents a multistage trajectory control strategy based on the pseudospectral method, capable of dealing with the unexpected situations in reentry flight. The strategy typically includes two subproblems: the trajectory estimation and trajectory refining. In each processing stage, the proposed method generates a specified range of trajectory with the transition of the flight state. The full glide trajectory consists of several optimal trajectory sequences. The newly focused geographic constraints in actual flight are discussed thereafter. Numerical examples of free-space flight, target transition flight, and threat avoidance flight are used to show the feasible application of multistage pseudospectral method in reentry trajectory optimization. PMID:24574929

Exploiting Motion Capture to Enhance Avoidance Behaviour in Games

NASA Astrophysics Data System (ADS)

van Basten, Ben J. H.; Jansen, Sander E. M.; Karamouzas, Ioannis

Realistic simulation of interacting virtual characters is essential in computer games, training and simulation applications. The problem is very challenging since people are accustomed to real-world situations and thus, they can easily detect inconsistencies and artifacts in the simulations. Over the past twenty years several models have been proposed for simulating individuals, groups and crowds of characters. However, little effort has been made to actually understand how humans solve interactions and avoid inter-collisions in real-life. In this paper, we exploit motion capture data to gain more insights into human-human interactions. We propose four measures to describe the collision-avoidance behavior. Based on these measures, we extract simple rules that can be applied on top of existing agent and force based approaches, increasing the realism of the resulting simulations.

A fictitious domain approach for the Stokes problem based on the extended finite element method

NASA Astrophysics Data System (ADS)

Court, Sébastien; Fournié, Michel; Lozinski, Alexei

2014-01-01

In the present work, we propose to extend to the Stokes problem a fictitious domain approach inspired by eXtended Finite Element Method and studied for Poisson problem in [Renard]. The method allows computations in domains whose boundaries do not match. A mixed finite element method is used for fluid flow. The interface between the fluid and the structure is localized by a level-set function. Dirichlet boundary conditions are taken into account using Lagrange multiplier. A stabilization term is introduced to improve the approximation of the normal trace of the Cauchy stress tensor at the interface and avoid the inf-sup condition between the spaces for velocity and the Lagrange multiplier. Convergence analysis is given and several numerical tests are performed to illustrate the capabilities of the method.

An improved method to set significance thresholds for β diversity testing in microbial community comparisons.

PubMed

Gülay, Arda; Smets, Barth F

2015-09-01

Exploring the variation in microbial community diversity between locations (β diversity) is a central topic in microbial ecology. Currently, there is no consensus on how to set the significance threshold for β diversity. Here, we describe and quantify the technical components of β diversity, including those associated with the process of subsampling. These components exist for any proposed β diversity measurement procedure. Further, we introduce a strategy to set significance thresholds for β diversity of any group of microbial samples using rarefaction, invoking the notion of a meta-community. The proposed technique was applied to several in silico generated operational taxonomic unit (OTU) libraries and experimental 16S rRNA pyrosequencing libraries. The latter represented microbial communities from different biological rapid sand filters at a full-scale waterworks. We observe that β diversity, after subsampling, is inflated by intra-sample differences; this inflation is avoided in the proposed method. In addition, microbial community evenness (Gini > 0.08) strongly affects all β diversity estimations due to bias associated with rarefaction. Where published methods to test β significance often fail, the proposed meta-community-based estimator is more successful at rejecting insignificant β diversity values. Applying our approach, we reveal the heterogeneous microbial structure of biological rapid sand filters both within and across filters. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Fiber-reinforced materials: finite elements for the treatment of the inextensibility constraint

NASA Astrophysics Data System (ADS)

Auricchio, Ferdinando; Scalet, Giulia; Wriggers, Peter

2017-12-01

The present paper proposes a numerical framework for the analysis of problems involving fiber-reinforced anisotropic materials. Specifically, isotropic linear elastic solids, reinforced by a single family of inextensible fibers, are considered. The kinematic constraint equation of inextensibility in the fiber direction leads to the presence of an undetermined fiber stress in the constitutive equations. To avoid locking-phenomena in the numerical solution due to the presence of the constraint, mixed finite elements based on the Lagrange multiplier, perturbed Lagrangian, and penalty method are proposed. Several boundary-value problems under plane strain conditions are solved and numerical results are compared to analytical solutions, whenever the derivation is possible. The performed simulations allow to assess the performance of the proposed finite elements and to discuss several features of the developed formulations concerning the effective approximation for the displacement and fiber stress fields, mesh convergence, and sensitivity to penalty parameters.

Cooperative Quantum-Behaved Particle Swarm Optimization with Dynamic Varying Search Areas and Lévy Flight Disturbance

PubMed Central

Li, Desheng

2014-01-01

This paper proposes a novel variant of cooperative quantum-behaved particle swarm optimization (CQPSO) algorithm with two mechanisms to reduce the search space and avoid the stagnation, called CQPSO-DVSA-LFD. One mechanism is called Dynamic Varying Search Area (DVSA), which takes charge of limiting the ranges of particles' activity into a reduced area. On the other hand, in order to escape the local optima, Lévy flights are used to generate the stochastic disturbance in the movement of particles. To test the performance of CQPSO-DVSA-LFD, numerical experiments are conducted to compare the proposed algorithm with different variants of PSO. According to the experimental results, the proposed method performs better than other variants of PSO on both benchmark test functions and the combinatorial optimization issue, that is, the job-shop scheduling problem. PMID:24851085

Motorcyclists safety system to avoid rear end collisions based on acoustic signatures

NASA Astrophysics Data System (ADS)

Muzammel, M.; Yusoff, M. Zuki; Malik, A. Saeed; Mohamad Saad, M. Naufal; Meriaudeau, F.

2017-03-01

In many Asian countries, motorcyclists have a higher fatality rate as compared to other vehicles. Among many other factors, rear end collisions are also contributing for these fatalities. Collision detection systems can be useful to minimize these accidents. However, the designing of efficient and cost effective collision detection system for motorcyclist is still a major challenge. In this paper, an acoustic information based, cost effective and efficient collision detection system is proposed for motorcycle applications. The proposed technique uses the Short time Fourier Transform (STFT) to extract the features from the audio signal and Principal component analysis (PCA) has been used to reduce the feature vector length. The reduction of feature length, further increases the performance of this technique. The proposed technique has been tested on self recorded dataset and gives accuracy of 97.87%. We believe that this method can help to reduce a significant number of motorcycle accidents.

A low-cost and portable realization on fringe projection three-dimensional measurement

NASA Astrophysics Data System (ADS)

Xiao, Suzhi; Tao, Wei; Zhao, Hui

2015-12-01

Fringe projection three-dimensional measurement is widely applied in a wide range of industrial application. The traditional fringe projection system has the disadvantages of high expense, big size, and complicated calibration requirements. In this paper we introduce a low-cost and portable realization on three-dimensional measurement with Pico projector. It has the advantages of low cost, compact physical size, and flexible configuration. For the proposed fringe projection system, there is no restriction to camera and projector's relative alignment on parallelism and perpendicularity for installation. Moreover, plane-based calibration method is adopted in this paper that avoids critical requirements on calibration system such as additional gauge block or precise linear z stage. What is more, error sources existing in the proposed system are introduced in this paper. The experimental results demonstrate the feasibility of the proposed low cost and portable fringe projection system.

Mixture model-based clustering and logistic regression for automatic detection of microaneurysms in retinal images

NASA Astrophysics Data System (ADS)

Sánchez, Clara I.; Hornero, Roberto; Mayo, Agustín; García, María

2009-02-01

Diabetic Retinopathy is one of the leading causes of blindness and vision defects in developed countries. An early detection and diagnosis is crucial to avoid visual complication. Microaneurysms are the first ocular signs of the presence of this ocular disease. Their detection is of paramount importance for the development of a computer-aided diagnosis technique which permits a prompt diagnosis of the disease. However, the detection of microaneurysms in retinal images is a difficult task due to the wide variability that these images usually present in screening programs. We propose a statistical approach based on mixture model-based clustering and logistic regression which is robust to the changes in the appearance of retinal fundus images. The method is evaluated on the public database proposed by the Retinal Online Challenge in order to obtain an objective performance measure and to allow a comparative study with other proposed algorithms.

Face Gear Drive with Spur Involute Pinion: Geometry, Generation by a Worm, Stress Analysis

NASA Technical Reports Server (NTRS)

Litvin, Faydor L.; Fuentes, Alfonso; Zanzi, Claudio; Pontiggia, Matteo; Handschuh, Robert F. (Technical Monitor)

2002-01-01

A face gear drive with a spur involute pinion is considered. The generation of the face gear is based on application of a grinding or cutting worm whereas the conventional method of generation is based on application of an involute shaper. An analytical approach is proposed for the determination of: (1) the worm thread surface; (2) avoidance of singularities of the worm thread surface, (air) dressing of the worm; and (3) determination of stresses of the face-gear drive. A computer program for simulation of meshing and contact of the pinion and face-gear has been developed. Correction of machine-tool settings is proposed for reduction of the shift of the bearing contact caused by misalignment. An automatic development of the model of five contacting teeth has been proposed for stress analysis. Numerical examples for illustration of the developed theory are provided.

Recommendations for Sense and Avoid Policy Compliance

NASA Technical Reports Server (NTRS)

2005-01-01

Since unmanned aircraft do not have a human on board, they need to have a sense and avoid capability that provides an "equivalent level of safety" (ELOS) to manned aircraft. The question then becomes - is sense and avoid ELOS for unmanned aircraft adequate to satisfy the requirements of 14 CFR 91.113? Access 5 has proposed a definition of sense and avoid, but the question remains as to whether any sense and avoid system can comply with 14 CFR 91.113 as currently written. The Access 5 definition of sense and avoid ELOS allows for the development of a sense and avoid system for unmanned aircraft that would comply with 14 CFR 91.113. Compliance is based on sensing and avoiding other traffic at an equivalent level of safety for collision avoidance, as manned aircraft. No changes to Part 91 are necessary, with the possible exception of changing "see" to "sense," or obtaining an interpretation from the FAA General Counsel that "sense" is equivalent to "see."

Tabu search and binary particle swarm optimization for feature selection using microarray data.

PubMed

Chuang, Li-Yeh; Yang, Cheng-Huei; Yang, Cheng-Hong

2009-12-01

Gene expression profiles have great potential as a medical diagnosis tool because they represent the state of a cell at the molecular level. In the classification of cancer type research, available training datasets generally have a fairly small sample size compared to the number of genes involved. This fact poses an unprecedented challenge to some classification methodologies due to training data limitations. Therefore, a good selection method for genes relevant for sample classification is needed to improve the predictive accuracy, and to avoid incomprehensibility due to the large number of genes investigated. In this article, we propose to combine tabu search (TS) and binary particle swarm optimization (BPSO) for feature selection. BPSO acts as a local optimizer each time the TS has been run for a single generation. The K-nearest neighbor method with leave-one-out cross-validation and support vector machine with one-versus-rest serve as evaluators of the TS and BPSO. The proposed method is applied and compared to the 11 classification problems taken from the literature. Experimental results show that our method simplifies features effectively and either obtains higher classification accuracy or uses fewer features compared to other feature selection methods.

Resource Isolation Method for Program’S Performance on CMP

NASA Astrophysics Data System (ADS)

Guan, Ti; Liu, Chunxiu; Xu, Zheng; Li, Huicong; Ma, Qiang

2017-10-01

Data center and cloud computing are more popular, which make more benefits for customers and the providers. However, in data center or clusters, commonly there is more than one program running on one server, but programs may interference with each other. The interference may take a little effect, however, the interference may cause serious drop down of performance. In order to avoid the performance interference problem, the mechanism of isolate resource for different programs is a better choice. In this paper we propose a light cost resource isolation method to improve program’s performance. This method uses Cgroups to set the dedicated CPU and memory resource for a program, aiming at to guarantee the program’s performance. There are three engines to realize this method: Program Monitor Engine top program’s resource usage of CPU and memory and transfer the information to Resource Assignment Engine; Resource Assignment Engine calculates the size of CPU and memory resource should be applied for the program; Cgroups Control Engine divide resource by Linux tool Cgroups, and drag program in control group for execution. The experiment result show that making use of the resource isolation method proposed by our paper, program’s performance can be improved.

Low-thrust trajectory optimization of asteroid sample return mission with multiple revolutions and moon gravity assists

NASA Astrophysics Data System (ADS)

Tang, Gao; Jiang, FanHuag; Li, JunFeng

2015-11-01

Near-Earth asteroids have gained a lot of interest and the development in low-thrust propulsion technology makes complex deep space exploration missions possible. A mission from low-Earth orbit using low-thrust electric propulsion system to rendezvous with near-Earth asteroid and bring sample back is investigated. By dividing the mission into five segments, the complex mission is solved separately. Then different methods are used to find optimal trajectories for every segment. Multiple revolutions around the Earth and multiple Moon gravity assists are used to decrease the fuel consumption to escape from the Earth. To avoid possible numerical difficulty of indirect methods, a direct method to parameterize the switching moment and direction of thrust vector is proposed. To maximize the mass of sample, optimal control theory and homotopic approach are applied to find the optimal trajectory. Direct methods of finding proper time to brake the spacecraft using Moon gravity assist are also proposed. Practical techniques including both direct and indirect methods are investigated to optimize trajectories for different segments and they can be easily extended to other missions and more precise dynamic model.

Cost-efficient scheduling of FAST observations

NASA Astrophysics Data System (ADS)

Luo, Qi; Zhao, Laiping; Yu, Ce; Xiao, Jian; Sun, Jizhou; Zhu, Ming; Zhong, Yi

2018-03-01

A cost-efficient schedule for the Five-hundred-meter Aperture Spherical radio Telescope (FAST) requires to maximize the number of observable proposals and the overall scientific priority, and minimize the overall slew-cost generated by telescope shifting, while taking into account the constraints including the astronomical objects visibility, user-defined observable times, avoiding Radio Frequency Interference (RFI). In this contribution, first we solve the problem of maximizing the number of observable proposals and scientific priority by modeling it as a Minimum Cost Maximum Flow (MCMF) problem. The optimal schedule can be found by any MCMF solution algorithm. Then, for minimizing the slew-cost of the generated schedule, we devise a maximally-matchable edges detection-based method to reduce the problem size, and propose a backtracking algorithm to find the perfect matching with minimum slew-cost. Experiments on a real dataset from NASA/IPAC Extragalactic Database (NED) show that, the proposed scheduler can increase the usage of available times with high scientific priority and reduce the slew-cost significantly in a very short time.