Outlier Detection in GNSS Pseudo-Range/Doppler Measurements for Robust Localization

Directory of Open Access Journals (Sweden)

Salim Zair

2016-04-01

Full Text Available In urban areas or space-constrained environments with obstacles, vehicle localization using Global Navigation Satellite System (GNSS data is hindered by Non-Line Of Sight (NLOS and multipath receptions. These phenomena induce faulty data that disrupt the precise localization of the GNSS receiver. In this study, we detect the outliers among the observations, Pseudo-Range (PR and/or Doppler measurements, and we evaluate how discarding them improves the localization. We specify a contrario modeling for GNSS raw data to derive an algorithm that partitions the dataset between inliers and outliers. Then, only the inlier data are considered in the localization process performed either through a classical Particle Filter (PF or a Rao-Blackwellization (RB approach. Both localization algorithms exclusively use GNSS data, but they differ by the way Doppler measurements are processed. An experiment has been performed with a GPS receiver aboard a vehicle. Results show that the proposed algorithms are able to detect the ‘outliers’ in the raw data while being robust to non-Gaussian noise and to intermittent satellite blockage. We compare the performance results achieved either estimating only PR outliers or estimating both PR and Doppler outliers. The best localization is achieved using the RB approach coupled with PR-Doppler outlier estimation.

High Resolution Robust GPS-free Localization for Wireless Sensor Networks and its Applications

KAUST Repository

Mirza, Mohammed

2011-12-12

In this thesis we investigate the problem of robustness and scalability w.r.t. estimating the position of randomly deployed motes/nodes of a Wireless Sensor Network (WSN) without the help of Global Positioning System (GPS) devices. We propose a few applications of range independent localization algorithms that allow the sensors to actively determine their location with high resolution without increasing the complexity of the hardware or any additional device setup. In our first application we try to present a localized and centralized cooperative spectrum sensing using RF sensor networks. This scheme collaboratively sense the spectrum and localize the whole network efficiently and with less difficulty. In second application we try to focus on how efficiently we can localize the nodes, to detect underwater threats, without the use of beacons. In third application we try to focus on 3-Dimensional localization for LTE systems. Our performance evaluation shows that these schemes lead to a significant improvement in localization accuracy compared to the state-of-art range independent localization schemes, without requiring GPS support.

A Practical, Robust and Fast Method for Location Localization in Range-Based Systems.

Science.gov (United States)

Huang, Shiping; Wu, Zhifeng; Misra, Anil

2017-12-11

Location localization technology is used in a number of industrial and civil applications. Real time location localization accuracy is highly dependent on the quality of the distance measurements and efficiency of solving the localization equations. In this paper, we provide a novel approach to solve the nonlinear localization equations efficiently and simultaneously eliminate the bad measurement data in range-based systems. A geometric intersection model was developed to narrow the target search area, where Newton's Method and the Direct Search Method are used to search for the unknown position. Not only does the geometric intersection model offer a small bounded search domain for Newton's Method and the Direct Search Method, but also it can self-correct bad measurement data. The Direct Search Method is useful for the coarse localization or small target search domain, while the Newton's Method can be used for accurate localization. For accurate localization, by utilizing the proposed Modified Newton's Method (MNM), challenges of avoiding the local extrema, singularities, and initial value choice are addressed. The applicability and robustness of the developed method has been demonstrated by experiments with an indoor system.

Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization

Directory of Open Access Journals (Sweden)

Marco A

2006-01-01

Full Text Available Indoor localization systems are undoubtedly of interest in many application fields. Like outdoor systems, they suffer from non-line-of-sight (NLOS errors which hinder their robustness and accuracy. Though many ad hoc techniques have been developed to deal with this problem, unfortunately most of them are not applicable indoors due to the high variability of the environment (movement of furniture and of people, etc.. In this paper, we describe the use of robust regression techniques to detect and reject NLOS measures in a location estimation using multilateration. We show how the least-median-of-squares technique can be used to overcome the effects of NLOS errors, even in environments with little infrastructure, and validate its suitability by comparing it to other methods described in the bibliography. We obtained remarkable results when using it in a real indoor positioning system that works with Bluetooth and ultrasound (BLUPS, even when nearly half the measures suffered from NLOS or other coarse errors.

Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization

Science.gov (United States)

Casas, R.; Marco, A.; Guerrero, J. J.; Falcó, J.

2006-12-01

Indoor localization systems are undoubtedly of interest in many application fields. Like outdoor systems, they suffer from non-line-of-sight (NLOS) errors which hinder their robustness and accuracy. Though many ad hoc techniques have been developed to deal with this problem, unfortunately most of them are not applicable indoors due to the high variability of the environment (movement of furniture and of people, etc.). In this paper, we describe the use of robust regression techniques to detect and reject NLOS measures in a location estimation using multilateration. We show how the least-median-of-squares technique can be used to overcome the effects of NLOS errors, even in environments with little infrastructure, and validate its suitability by comparing it to other methods described in the bibliography. We obtained remarkable results when using it in a real indoor positioning system that works with Bluetooth and ultrasound (BLUPS), even when nearly half the measures suffered from NLOS or other coarse errors.

Robust Floor Determination Algorithm for Indoor Wireless Localization Systems under Reference Node Failure

Directory of Open Access Journals (Sweden)

Kriangkrai Maneerat

2016-01-01

Full Text Available One of the challenging problems for indoor wireless multifloor positioning systems is the presence of reference node (RN failures, which cause the values of received signal strength (RSS to be missed during the online positioning phase of the location fingerprinting technique. This leads to performance degradation in terms of floor accuracy, which in turn affects other localization procedures. This paper presents a robust floor determination algorithm called Robust Mean of Sum-RSS (RMoS, which can accurately determine the floor on which mobile objects are located and can work under either the fault-free scenario or the RN-failure scenarios. The proposed fault tolerance floor algorithm is based on the mean of the summation of the strongest RSSs obtained from the IEEE 802.15.4 Wireless Sensor Networks (WSNs during the online phase. The performance of the proposed algorithm is compared with those of different floor determination algorithms in literature. The experimental results show that the proposed robust floor determination algorithm outperformed the other floor algorithms and can achieve the highest percentage of floor determination accuracy in all scenarios tested. Specifically, the proposed algorithm can achieve greater than 95% correct floor determination under the scenario in which 40% of RNs failed.

A Robust Iris Identification System Based on Wavelet Packet Decomposition and Local Comparisons of the Extracted Signatures

Directory of Open Access Journals (Sweden)

Rossant Florence

2010-01-01

Full Text Available Abstract This paper presents a complete iris identification system including three main stages: iris segmentation, signature extraction, and signature comparison. An accurate and robust pupil and iris segmentation process, taking into account eyelid occlusions, is first detailed and evaluated. Then, an original wavelet-packet-based signature extraction method and a novel identification approach, based on the fusion of local distance measures, are proposed. Performance measurements validating the proposed iris signature and demonstrating the benefit of our local-based signature comparison are provided. Moreover, an exhaustive evaluation of robustness, with regards to the acquisition conditions, attests the high performances and the reliability of our system. Tests have been conducted on two different databases, the well-known CASIA database (V3 and our ISEP database. Finally, a comparison of the performances of our system with the published ones is given and discussed.

Variational and robust density fitting of four-center two-electron integrals in local metrics

Science.gov (United States)

Reine, Simen; Tellgren, Erik; Krapp, Andreas; Kjærgaard, Thomas; Helgaker, Trygve; Jansik, Branislav; Høst, Stinne; Salek, Paweł

2008-09-01

Density fitting is an important method for speeding up quantum-chemical calculations. Linear-scaling developments in Hartree-Fock and density-functional theories have highlighted the need for linear-scaling density-fitting schemes. In this paper, we present a robust variational density-fitting scheme that allows for solving the fitting equations in local metrics instead of the traditional Coulomb metric, as required for linear scaling. Results of fitting four-center two-electron integrals in the overlap and the attenuated Gaussian damped Coulomb metric are presented, and we conclude that density fitting can be performed in local metrics at little loss of chemical accuracy. We further propose to use this theory in linear-scaling density-fitting developments.

Robustness and structure of complex networks

Science.gov (United States)

Shao, Shuai

This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks

Robust non-local effects of ocean heat uptake on radiative feedback and subtropical cloud cover

Science.gov (United States)

Rose, B. E. J.

2016-02-01

moisture. Our results suggest that cloud feedback under transient climate change is partly modulated by ocean heat uptake through robust but non-local atmospheric processes, and has implications on a timescales ranging from inter-annual to multi-centennial.

Robust quantum state engineering through coherent localization in biased-coin quantum walks

Energy Technology Data Exchange (ETDEWEB)

Majury, Helena [Queen' s University, Centre for Secure Information Technologies (CSIT), Belfast (United Kingdom); Queen' s University, Centre for Theoretical Atomic, Molecular and Optical Physics, School of Mathematics and Physics, Belfast (United Kingdom); Boutari, Joelle [University of Oxford, Clarendon Laboratory, Oxford (United Kingdom); O' Sullivan, Elizabeth [Queen' s University, Centre for Secure Information Technologies (CSIT), Belfast (United Kingdom); Ferraro, Alessandro; Paternostro, Mauro [Queen' s University, Centre for Theoretical Atomic, Molecular and Optical Physics, School of Mathematics and Physics, Belfast (United Kingdom)

2018-12-15

We address the performance of a coin-biased quantum walk as a generator for non-classical position states of the walker. We exploit a phenomenon of coherent localization in the position space - resulting from the choice of small values of the coin parameter and assisted by post-selection - to engineer large-size coherent superpositions of position states of the walker. The protocol that we design appears to be remarkably robust against both the actual value taken by the coin parameter and strong dephasing-like noise acting on the spatial degree of freedom. We finally illustrate a possible linear-optics implementation of our proposal, suitable for both bulk and integrated-optics platforms. (orig.)

Exploiting Deep Neural Networks and Head Movements for Robust Binaural Localization of Multiple Sources in Reverberant Environments

DEFF Research Database (Denmark)

Ma, Ning; May, Tobias; Brown, Guy J.

2017-01-01

This paper presents a novel machine-hearing system that exploits deep neural networks (DNNs) and head movements for robust binaural localization of multiple sources in reverberant environments. DNNs are used to learn the relationship between the source azimuth and binaural cues, consisting...... of the complete cross-correlation function (CCF) and interaural level differences (ILDs). In contrast to many previous binaural hearing systems, the proposed approach is not restricted to localization of sound sources in the frontal hemifield. Due to the similarity of binaural cues in the frontal and rear...

Robust Myocardial Motion Tracking for Echocardiography: Variational Framework Integrating Local-to-Global Deformation

Directory of Open Access Journals (Sweden)

Chi Young Ahn

2013-01-01

Full Text Available This paper proposes a robust real-time myocardial border tracking algorithm for echocardiography. Commonly, after an initial contour of LV border is traced at one or two frames from the entire cardiac cycle, LV contour tracking is performed over the remaining frames. Among a variety of tracking techniques, optical flow method is the most widely used for motion estimation of moving objects. However, when echocardiography data is heavily corrupted in some local regions, the errors bring the tracking point out of the endocardial border, resulting in distorted LV contours. This shape distortion often occurs in practice since the data acquisition is affected by ultrasound artifacts, dropouts, or shadowing phenomena of cardiac walls. The proposed method is designed to deal with this shape distortion problem by integrating local optical flow motion and global deformation into a variational framework. The proposed descent method controls the individual tracking points to follow the local motions of a specific speckle pattern, while their overall motions are confined to the global motion constraint being approximately an affine transform of the initial tracking points. Many real experiments show that the proposed method achieves better overall performance than conventional methods.

Robust multi-model control of an autonomous wind power system

Energy Technology Data Exchange (ETDEWEB)

Cutululis, Nicolas Antonio; Hansen, Anca Daniela; Soerensen, Poul [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Ceanga, Emil [' Dunarea de Jos' Univ., Faculty of Electrical Engineering, Galati (Romania)

2006-07-01

This article presents a robust multi-model control structure for a wind power system that uses a variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) connected to a local grid. The control problem consists in maximizing the energy captured from the wind for varying wind speeds. The VSWT-PMSG linearized model analysis reveals the resonant nature of its dynamic at points on the optimal regimes characteristic (ORC). The natural frequency of the system and the damping factor are strongly dependent on the operating point on the ORC. Under these circumstances a robust multi-model control structure is designed. The simulation results prove the viability of the proposed control structure. (Author)

Robust multi-model control of an autonomous wind power system

Science.gov (United States)

Cutululis, Nicolas Antonio; Ceanga, Emil; Hansen, Anca Daniela; Sørensen, Poul

2006-09-01

This article presents a robust multi-model control structure for a wind power system that uses a variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) connected to a local grid. The control problem consists in maximizing the energy captured from the wind for varying wind speeds. The VSWT-PMSG linearized model analysis reveals the resonant nature of its dynamic at points on the optimal regimes characteristic (ORC). The natural frequency of the system and the damping factor are strongly dependent on the operating point on the ORC. Under these circumstances a robust multi-model control structure is designed. The simulation results prove the viability of the proposed control structure. Copyright

A Robust and Efficient Algorithm for Tool Recognition and Localization for Space Station Robot

Directory of Open Access Journals (Sweden)

Lingbo Cheng

2014-12-01

Full Text Available This paper studies a robust target recognition and localization method for a maintenance robot in a space station, and its main goal is to solve the target affine transformation caused by microgravity and the strong reflection and refraction of sunlight and lamplight in the cabin, as well as the occlusion of other objects. In this method, an Affine Scale Invariant Feature Transform (Affine-SIFT algorithm is proposed to extract enough local feature points with a fully affine invariant, and the stable matching point is obtained from the above point for target recognition by the selected Random Sample Consensus (RANSAC algorithm. Then, in order to localize the target, the effective and appropriate 3D grasping scope of the target is defined, and we determine and evaluate the grasping precision with the estimated affine transformation parameters presented in this paper. Finally, the threshold of RANSAC is optimized to enhance the accuracy and efficiency of target recognition and localization, and the scopes of illumination, vision distance and viewpoint angle for robot are evaluated to obtain effective image data by Root-Mean-Square Error (RMSE. An experimental system to simulate the illumination environment in a space station is established. Enough experiments have been carried out, and the experimental results show both the validity of the proposed definition of the grasping scope and the feasibility of the proposed recognition and localization method.

Two-level Robust Measurement Fusion Kalman Filter for Clustering Sensor Networks

Institute of Scientific and Technical Information of China (English)

ZHANG Peng; QI Wen-Juan; DENG Zi-Li

2014-01-01

This paper investigates the distributed fusion Kalman filtering over clustering sensor networks. The sensor network is partitioned as clusters by the nearest neighbor rule and each cluster consists of sensing nodes and cluster-head. Using the minimax robust estimation principle, based on the worst-case conservative system with the conservative upper bounds of noise variances, two-level robust measurement fusion Kalman filter is presented for the clustering sensor network systems with uncertain noise variances. It can significantly reduce the communication load and save energy when the number of sensors is very large. A Lyapunov equation approach for the robustness analysis is presented, by which the robustness of the local and fused Kalman filters is proved. The concept of the robust accuracy is presented, and the robust accuracy relations among the local and fused robust Kalman filters are proved. It is proved that the robust accuracy of the two-level weighted measurement fuser is equal to that of the global centralized robust fuser and is higher than those of each local robust filter and each local weighted measurement fuser. A simulation example shows the correctness and effectiveness of the proposed results.

Consistent and robust determination of border ownership based on asymmetric surrounding contrast.

Science.gov (United States)

Sakai, Ko; Nishimura, Haruka; Shimizu, Ryohei; Kondo, Keiichi

2012-09-01

Determination of the figure region in an image is a fundamental step toward surface construction, shape coding, and object representation. Localized, asymmetric surround modulation, reported neurophysiologically in early-to-intermediate-level visual areas, has been proposed as a mechanism for figure-ground segregation. We investigated, computationally, whether such surround modulation is capable of yielding consistent and robust determination of figure side for various stimuli. Our surround modulation model showed a surprisingly high consistency among pseudorandom block stimuli, with greater consistency for stimuli that yielded higher accuracy of, and shorter reaction times in, human perception. Our analyses revealed that the localized, asymmetric organization of surrounds is crucial in the detection of the contrast imbalance that leads to the determination of the direction of figure with respect to the border. The model also exhibited robustness for gray-scaled natural images, with a mean correct rate of 67%, which was similar to that of figure-side determination in human perception through a small window and of machine-vision algorithms based on local processing. These results suggest a crucial role of surround modulation in the local processing of figure-ground segregation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Robust multiple frequency multiple power localization schemes in the presence of multiple jamming attacks.

Directory of Open Access Journals (Sweden)

Ahmed Abdulqader Hussein

Full Text Available Localization of the wireless sensor network is a vital area acquiring an impressive research concern and called upon to expand more with the rising of its applications. As localization is gaining prominence in wireless sensor network, it is vulnerable to jamming attacks. Jamming attacks disrupt communication opportunity among the sender and receiver and deeply impact the localization process, leading to a huge error of the estimated sensor node position. Therefore, detection and elimination of jamming influence are absolutely indispensable. Range-based techniques especially Received Signal Strength (RSS is facing severe impact of these attacks. This paper proposes algorithms based on Combination Multiple Frequency Multiple Power Localization (C-MFMPL and Step Function Multiple Frequency Multiple Power Localization (SF-MFMPL. The algorithms have been tested in the presence of multiple types of jamming attacks including capture and replay, random and constant jammers over a log normal shadow fading propagation model. In order to overcome the impact of random and constant jammers, the proposed method uses two sets of frequencies shared by the implemented anchor nodes to obtain the averaged RSS readings all over the transmitted frequencies successfully. In addition, three stages of filters have been used to cope with the replayed beacons caused by the capture and replay jammers. In this paper the localization performance of the proposed algorithms for the ideal case which is defined by without the existence of the jamming attack are compared with the case of jamming attacks. The main contribution of this paper is to achieve robust localization performance in the presence of multiple jamming attacks under log normal shadow fading environment with a different simulation conditions and scenarios.

Robust Forecasting of Non-Stationary Time Series

OpenAIRE

Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.

2010-01-01

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable forecasts in the presence of outliers, non-linearity, and heteroscedasticity. In the absence of outliers, the forecasts are only slightly less precise than those based on a localized Least Squares estima...

3D-2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch

Science.gov (United States)

De Silva, T.; Uneri, A.; Ketcha, M. D.; Reaungamornrat, S.; Kleinszig, G.; Vogt, S.; Aygun, N.; Lo, S.-F.; Wolinsky, J.-P.; Siewerdsen, J. H.

2016-04-01

In image-guided spine surgery, robust three-dimensional to two-dimensional (3D-2D) registration of preoperative computed tomography (CT) and intraoperative radiographs can be challenged by the image content mismatch associated with the presence of surgical instrumentation and implants as well as soft-tissue resection or deformation. This work investigates image similarity metrics in 3D-2D registration offering improved robustness against mismatch, thereby improving performance and reducing or eliminating the need for manual masking. The performance of four gradient-based image similarity metrics (gradient information (GI), gradient correlation (GC), gradient information with linear scaling (GS), and gradient orientation (GO)) with a multi-start optimization strategy was evaluated in an institutional review board-approved retrospective clinical study using 51 preoperative CT images and 115 intraoperative mobile radiographs. Registrations were tested with and without polygonal masks as a function of the number of multistarts employed during optimization. Registration accuracy was evaluated in terms of the projection distance error (PDE) and assessment of failure modes (PDE  >  30 mm) that could impede reliable vertebral level localization. With manual polygonal masking and 200 multistarts, the GC and GO metrics exhibited robust performance with 0% gross failures and median PDE  interquartile range (IQR)) and a median runtime of 84 s (plus upwards of 1-2 min for manual masking). Excluding manual polygonal masks and decreasing the number of multistarts to 50 caused the GC-based registration to fail at a rate of  >14% however, GO maintained robustness with a 0% gross failure rate. Overall, the GI, GC, and GS metrics were susceptible to registration errors associated with content mismatch, but GO provided robust registration (median PDE  =  5.5 mm, 2.6 mm IQR) without manual masking and with an improved runtime (29.3 s). The GO metric

Source apportionment of soil heavy metals using robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR) receptor model.

Science.gov (United States)

Qu, Mingkai; Wang, Yan; Huang, Biao; Zhao, Yongcun

2018-06-01

The traditional source apportionment models, such as absolute principal component scores-multiple linear regression (APCS-MLR), are usually susceptible to outliers, which may be widely present in the regional geochemical dataset. Furthermore, the models are merely built on variable space instead of geographical space and thus cannot effectively capture the local spatial characteristics of each source contributions. To overcome the limitations, a new receptor model, robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR), was proposed based on the traditional APCS-MLR model. Then, the new method was applied to the source apportionment of soil metal elements in a region of Wuhan City, China as a case study. Evaluations revealed that: (i) RAPCS-RGWR model had better performance than APCS-MLR model in the identification of the major sources of soil metal elements, and (ii) source contributions estimated by RAPCS-RGWR model were more close to the true soil metal concentrations than that estimated by APCS-MLR model. It is shown that the proposed RAPCS-RGWR model is a more effective source apportionment method than APCS-MLR (i.e., non-robust and global model) in dealing with the regional geochemical dataset. Copyright © 2018 Elsevier B.V. All rights reserved.

Robust Locally Weighted Regression For Ground Surface Extraction In Mobile Laser Scanning 3D Data

Directory of Open Access Journals (Sweden)

A. Nurunnabi

2013-10-01

Full Text Available A new robust way for ground surface extraction from mobile laser scanning 3D point cloud data is proposed in this paper. Fitting polynomials along 2D/3D points is one of the well-known methods for filtering ground points, but it is evident that unorganized point clouds consist of multiple complex structures by nature so it is not suitable for fitting a parametric global model. The aim of this research is to develop and implement an algorithm to classify ground and non-ground points based on statistically robust locally weighted regression which fits a regression surface (line in 2D by fitting without any predefined global functional relation among the variables of interest. Afterwards, the z (elevation-values are robustly down weighted based on the residuals for the fitted points. The new set of down weighted z-values along with x (or y values are used to get a new fit of the (lower surface (line. The process of fitting and down-weighting continues until the difference between two consecutive fits is insignificant. Then the final fit represents the ground level of the given point cloud and the ground surface points can be extracted. The performance of the new method has been demonstrated through vehicle based mobile laser scanning 3D point cloud data from urban areas which include different problematic objects such as short walls, large buildings, electric poles, sign posts and cars. The method has potential in areas like building/construction footprint determination, 3D city modelling, corridor mapping and asset management.

Robust Forecasting of Non-Stationary Time Series

NARCIS (Netherlands)

Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.

2010-01-01

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable

REINA at CLEF 2007 Robust Task

OpenAIRE

Zazo Rodríguez, Ángel Francisco; Figuerola, Carlos G.; Alonso Berrocal, José Luis

2007-01-01

This paper describes our work at CLEF 2007 Robust Task. We have participated in the monolingual (English, French and Portuguese) and the bilingual (English to French) subtask. At CLEF 2006 our research group obtained very good results applying local query expansion using windows of terms in the robust task. This year we have used the same expansion technique, but taking into account some criteria of robustness: MAP, GMAP, MMR, GS@10, P@10, number of failed topics, number of topics bellow 0.1 ...

Robust Object Tracking Using Valid Fragments Selection.

Science.gov (United States)

Zheng, Jin; Li, Bo; Tian, Peng; Luo, Gang

Local features are widely used in visual tracking to improve robustness in cases of partial occlusion, deformation and rotation. This paper proposes a local fragment-based object tracking algorithm. Unlike many existing fragment-based algorithms that allocate the weights to each fragment, this method firstly defines discrimination and uniqueness for local fragment, and builds an automatic pre-selection of useful fragments for tracking. Then, a Harris-SIFT filter is used to choose the current valid fragments, excluding occluded or highly deformed fragments. Based on those valid fragments, fragment-based color histogram provides a structured and effective description for the object. Finally, the object is tracked using a valid fragment template combining the displacement constraint and similarity of each valid fragment. The object template is updated by fusing feature similarity and valid fragments, which is scale-adaptive and robust to partial occlusion. The experimental results show that the proposed algorithm is accurate and robust in challenging scenarios.

3D–2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch

International Nuclear Information System (INIS)

De Silva, T; Ketcha, M D; Siewerdsen, J H; Uneri, A; Reaungamornrat, S; Kleinszig, G; Vogt, S; Aygun, N; Lo, S-F; Wolinsky, J-P

2016-01-01

In image-guided spine surgery, robust three-dimensional to two-dimensional (3D–2D) registration of preoperative computed tomography (CT) and intraoperative radiographs can be challenged by the image content mismatch associated with the presence of surgical instrumentation and implants as well as soft-tissue resection or deformation. This work investigates image similarity metrics in 3D–2D registration offering improved robustness against mismatch, thereby improving performance and reducing or eliminating the need for manual masking. The performance of four gradient-based image similarity metrics (gradient information (GI), gradient correlation (GC), gradient information with linear scaling (GS), and gradient orientation (GO)) with a multi-start optimization strategy was evaluated in an institutional review board-approved retrospective clinical study using 51 preoperative CT images and 115 intraoperative mobile radiographs. Registrations were tested with and without polygonal masks as a function of the number of multistarts employed during optimization. Registration accuracy was evaluated in terms of the projection distance error (PDE) and assessment of failure modes (PDE  >  30 mm) that could impede reliable vertebral level localization. With manual polygonal masking and 200 multistarts, the GC and GO metrics exhibited robust performance with 0% gross failures and median PDE  <  6.4 mm (±4.4 mm interquartile range (IQR)) and a median runtime of 84 s (plus upwards of 1–2 min for manual masking). Excluding manual polygonal masks and decreasing the number of multistarts to 50 caused the GC-based registration to fail at a rate of  >14%; however, GO maintained robustness with a 0% gross failure rate. Overall, the GI, GC, and GS metrics were susceptible to registration errors associated with content mismatch, but GO provided robust registration (median PDE  =  5.5 mm, 2.6 mm IQR) without manual masking and with an improved

Impurity sublattice localization in ZnO revealed by li marker diffusion

DEFF Research Database (Denmark)

Azarov, A.Yu.; Knutsen, K.E.; Neuvonen, P.T.

2013-01-01

Sublattice localization of impurities in compound semiconductors, e.g., ZnO, determines their electronic and optical action. Despite that the impurity position may be envisaged based on charge considerations, the actual localization is often unknown, limiting our understanding of the incorporation...... and possible doping mechanisms. In this study, we demonstrate that the preferential sublattice occupation for a number of impurities in ZnO can be revealed by monitoring Li diffusion. In particular, using ion implantation, the impurity incorporation into the Zn sublattice (holds for, B, Mg, P, Ag, Cd, and Sb...

[Localized purpura revealing vascular prosthetic graft infection].

Science.gov (United States)

Boureau, A S; Lescalie, F; Cassagnau, E; Clairand, R; Connault, J

2013-07-01

Prosthetic graft infection after vascular reconstruction is a rare but serious complication. We report a case of infection occurring late after implantation of an iliofemoral prosthetic vascular graft. The Staphylococcus aureus infection was revealed by vascular purpura localized on the right leg 7 years after implantation of a vascular prosthesis. This case illustrates an uncommonly late clinical manifestation presenting as an acute infection 7 years after the primary operation. In this situation, the presentation differs from early infection, which generally occurs within the first four postoperative months. Diagnosis and treatment remain a difficult challenge because prosthetic graft infection is a potentially life-threatening complication. Morbidity and mortality rates are high. Here we detail specific aspects of the clinical and radiological presentation. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Essential gene disruptions reveal complex relationships between phenotypic robustness, pleiotropy, and fitness

Science.gov (United States)

Bauer, Christopher R; Li, Shuang; Siegal, Mark L

2015-01-01

The concept of robustness in biology has gained much attention recently, but a mechanistic understanding of how genetic networks regulate phenotypic variation has remained elusive. One approach to understand the genetic architecture of variability has been to analyze dispensable gene deletions in model organisms; however, the most important genes cannot be deleted. Here, we have utilized two systems in yeast whereby essential genes have been altered to reduce expression. Using high-throughput microscopy and image analysis, we have characterized a large number of morphological phenotypes, and their associated variation, for the majority of essential genes in yeast. Our results indicate that phenotypic robustness is more highly dependent upon the expression of essential genes than on the presence of dispensable genes. Morphological robustness appears to be a general property of a genotype that is closely related to pleiotropy. While the fitness profile across a range of expression levels is idiosyncratic to each gene, the global pattern indicates that there is a window in which phenotypic variation can be released before fitness effects are observable. PMID:25609648

Designing Phononic Crystals with Wide and Robust Band Gaps

Science.gov (United States)

Jia, Zian; Chen, Yanyu; Yang, Haoxiang; Wang, Lifeng

2018-04-01

Phononic crystals (PnCs) engineered to manipulate and control the propagation of mechanical waves have enabled the design of a range of novel devices, such as waveguides, frequency modulators, and acoustic cloaks, for which wide and robust phononic band gaps are highly preferable. While numerous PnCs have been designed in recent decades, to the best of our knowledge, PnCs that possess simultaneous wide and robust band gaps (to randomness and deformations) have not yet been reported. Here, we demonstrate that by combining the band-gap formation mechanisms of Bragg scattering and local resonances (the latter one is dominating), PnCs with wide and robust phononic band gaps can be established. The robustness of the phononic band gaps are then discussed from two aspects: robustness to geometric randomness (manufacture defects) and robustness to deformations (mechanical stimuli). Analytical formulations further predict the optimal design parameters, and an uncertainty analysis quantifies the randomness effect of each designing parameter. Moreover, we show that the deformation robustness originates from a local resonance-dominant mechanism together with the suppression of structural instability. Importantly, the proposed PnCs require only a small number of layers of elements (three unit cells) to obtain broad, robust, and strong attenuation bands, which offer great potential in designing flexible and deformable phononic devices.

Designing Phononic Crystals with Wide and Robust Band Gaps

Energy Technology Data Exchange (ETDEWEB)

Chen, Yanyu [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jia, Zian [State University of New York at Stony Brook; Yang, Haoxiang [State University of New York at Stony Brook; Wang, Lifeng [State University of New York at Stony Brook

2018-04-16

Phononic crystals (PnCs) engineered to manipulate and control the propagation of mechanical waves have enabled the design of a range of novel devices, such as waveguides, frequency modulators, and acoustic cloaks, for which wide and robust phononic band gaps are highly preferable. While numerous PnCs have been designed in recent decades, to the best of our knowledge, PnCs that possess simultaneous wide and robust band gaps (to randomness and deformations) have not yet been reported. Here, we demonstrate that by combining the band-gap formation mechanisms of Bragg scattering and local resonances (the latter one is dominating), PnCs with wide and robust phononic band gaps can be established. The robustness of the phononic band gaps are then discussed from two aspects: robustness to geometric randomness (manufacture defects) and robustness to deformations (mechanical stimuli). Analytical formulations further predict the optimal design parameters, and an uncertainty analysis quantifies the randomness effect of each designing parameter. Moreover, we show that the deformation robustness originates from a local resonance-dominant mechanism together with the suppression of structural instability. Importantly, the proposed PnCs require only a small number of layers of elements (three unit cells) to obtain broad, robust, and strong attenuation bands, which offer great potential in designing flexible and deformable phononic devices.

REINA at CLEF 2007 Robust Track (2007)

OpenAIRE

Zazo, Ángel F.; G.-Figuerola, Carlos; Alonso-Berrocal, José-Luis

2007-01-01

This paper describes our work at CLEF 2007 Robust Task. We have participated in the monolingual (English, French and Portuguese) and the bilingual (English to French) subtask. At CLEF 2006 our research group obtained very good results applying local query expansion using windows of terms in the robust task. This year we have used the same expansion technique, but taking into account some criteria of robustness: MAP, GMAP, MMR, GS@10, P@10, number of failed topics, number of topics bellow 0.1 ...

Robust Measurement via A Fused Latent and Graphical Item Response Theory Model.

Science.gov (United States)

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

2018-03-12

Item response theory (IRT) plays an important role in psychological and educational measurement. Unlike the classical testing theory, IRT models aggregate the item level information, yielding more accurate measurements. Most IRT models assume local independence, an assumption not likely to be satisfied in practice, especially when the number of items is large. Results in the literature and simulation studies in this paper reveal that misspecifying the local independence assumption may result in inaccurate measurements and differential item functioning. To provide more robust measurements, we propose an integrated approach by adding a graphical component to a multidimensional IRT model that can offset the effect of unknown local dependence. The new model contains a confirmatory latent variable component, which measures the targeted latent traits, and a graphical component, which captures the local dependence. An efficient proximal algorithm is proposed for the parameter estimation and structure learning of the local dependence. This approach can substantially improve the measurement, given no prior information on the local dependence structure. The model can be applied to measure both a unidimensional latent trait and multidimensional latent traits.

Instantaneous, Simple, and Reversible Revealing of Invisible Patterns Encrypted in Robust Hollow Sphere Colloidal Photonic Crystals.

Science.gov (United States)

Zhong, Kuo; Li, Jiaqi; Liu, Liwang; Van Cleuvenbergen, Stijn; Song, Kai; Clays, Koen

2018-05-04

The colors of photonic crystals are based on their periodic crystalline structure. They show clear advantages over conventional chromophores for many applications, mainly due to their anti-photobleaching and responsiveness to stimuli. More specifically, combining colloidal photonic crystals and invisible patterns is important in steganography and watermarking for anticounterfeiting applications. Here a convenient way to imprint robust invisible patterns in colloidal crystals of hollow silica spheres is presented. While these patterns remain invisible under static environmental humidity, even up to near 100% relative humidity, they are unveiled immediately (≈100 ms) and fully reversibly by dynamic humid flow, e.g., human breath. They reveal themselves due to the extreme wettability of the patterned (etched) regions, as confirmed by contact angle measurements. The liquid surface tension threshold to induce wetting (revealing the imprinted invisible images) is evaluated by thermodynamic predictions and subsequently verified by exposure to various vapors with different surface tension. The color of the patterned regions is furthermore independently tuned by vapors with different refractive indices. Such a system can play a key role in applications such as anticounterfeiting, identification, and vapor sensing. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Solving a robust airline crew pairing problem with column generation

NARCIS (Netherlands)

Muter, I.; Birbil, S.I.; Bülbül, K.; Sahin, G.; Yenigün, H.; Tas, D.; Tüzün, D.

2013-01-01

In this study, we solve a robust version of the airline crew pairing problem. Our concept of robustness was partially shaped during our discussions with small local airlines in Turkey which may have to add a set of extra flights into their schedule at short notice during operation. Thus, robustness

Robust extraction of baseline signal of atmospheric trace species using local regression

Science.gov (United States)

Ruckstuhl, A. F.; Henne, S.; Reimann, S.; Steinbacher, M.; Vollmer, M. K.; O'Doherty, S.; Buchmann, B.; Hueglin, C.

2012-11-01

The identification of atmospheric trace species measurements that are representative of well-mixed background air masses is required for monitoring atmospheric composition change at background sites. We present a statistical method based on robust local regression that is well suited for the selection of background measurements and the estimation of associated baseline curves. The bootstrap technique is applied to calculate the uncertainty in the resulting baseline curve. The non-parametric nature of the proposed approach makes it a very flexible data filtering method. Application to carbon monoxide (CO) measured from 1996 to 2009 at the high-alpine site Jungfraujoch (Switzerland, 3580 m a.s.l.), and to measurements of 1,1-difluoroethane (HFC-152a) from Jungfraujoch (2000 to 2009) and Mace Head (Ireland, 1995 to 2009) demonstrates the feasibility and usefulness of the proposed approach. The determined average annual change of CO at Jungfraujoch for the 1996 to 2009 period as estimated from filtered annual mean CO concentrations is -2.2 ± 1.1 ppb yr-1. For comparison, the linear trend of unfiltered CO measurements at Jungfraujoch for this time period is -2.9 ± 1.3 ppb yr-1.

Automatic spinal cord localization, robust to MRI contrasts using global curve optimization.

Science.gov (United States)

Gros, Charley; De Leener, Benjamin; Dupont, Sara M; Martin, Allan R; Fehlings, Michael G; Bakshi, Rohit; Tummala, Subhash; Auclair, Vincent; McLaren, Donald G; Callot, Virginie; Cohen-Adad, Julien; Sdika, Michaël

2018-02-01

During the last two decades, MRI has been increasingly used for providing valuable quantitative information about spinal cord morphometry, such as quantification of the spinal cord atrophy in various diseases. However, despite the significant improvement of MR sequences adapted to the spinal cord, automatic image processing tools for spinal cord MRI data are not yet as developed as for the brain. There is nonetheless great interest in fully automatic and fast processing methods to be able to propose quantitative analysis pipelines on large datasets without user bias. The first step of most of these analysis pipelines is to detect the spinal cord, which is challenging to achieve automatically across the broad range of MRI contrasts, field of view, resolutions and pathologies. In this paper, a fully automated, robust and fast method for detecting the spinal cord centerline on MRI volumes is introduced. The algorithm uses a global optimization scheme that attempts to strike a balance between a probabilistic localization map of the spinal cord center point and the overall spatial consistency of the spinal cord centerline (i.e. the rostro-caudal continuity of the spinal cord). Additionally, a new post-processing feature, which aims to automatically split brain and spine regions is introduced, to be able to detect a consistent spinal cord centerline, independently from the field of view. We present data on the validation of the proposed algorithm, known as "OptiC", from a large dataset involving 20 centers, 4 contrasts (T 2 -weighted n = 287, T 1 -weighted n = 120, T 2 ∗ -weighted n = 307, diffusion-weighted n = 90), 501 subjects including 173 patients with a variety of neurologic diseases. Validation involved the gold-standard centerline coverage, the mean square error between the true and predicted centerlines and the ability to accurately separate brain and spine regions. Overall, OptiC was able to cover 98.77% of the gold-standard centerline, with a

A robust and powerful two-step testing procedure for local ancestry adjusted allelic association analysis in admixed populations.

Science.gov (United States)

Duan, Qing; Xu, Zheng; Raffield, Laura M; Chang, Suhua; Wu, Di; Lange, Ethan M; Reiner, Alex P; Li, Yun

2018-04-01

Genetic association studies in admixed populations allow us to gain deeper understanding of the genetic architecture of human diseases and traits. However, population stratification, complicated linkage disequilibrium (LD) patterns, and the complex interplay of allelic and ancestry effects on phenotypic traits pose challenges in such analyses. These issues may lead to detecting spurious associations and/or result in reduced statistical power. Fortunately, if handled appropriately, these same challenges provide unique opportunities for gene mapping. To address these challenges and to take these opportunities, we propose a robust and powerful two-step testing procedure Local Ancestry Adjusted Allelic (LAAA) association. In the first step, LAAA robustly captures associations due to allelic effect, ancestry effect, and interaction effect, allowing detection of effect heterogeneity across ancestral populations. In the second step, LAAA identifies the source of association, namely allelic, ancestry, or the combination. By jointly modeling allele, local ancestry, and ancestry-specific allelic effects, LAAA is highly powerful in capturing the presence of interaction between ancestry and allele effect. We evaluated the validity and statistical power of LAAA through simulations over a broad spectrum of scenarios. We further illustrated its usefulness by application to the Candidate Gene Association Resource (CARe) African American participants for association with hemoglobin levels. We were able to replicate independent groups' previously identified loci that would have been missed in CARe without joint testing. Moreover, the loci, for which LAAA detected potential effect heterogeneity, were replicated among African Americans from the Women's Health Initiative study. LAAA is freely available at https://yunliweb.its.unc.edu/LAAA. © 2017 WILEY PERIODICALS, INC.

Robust identification and localization of intramedullary nail holes for distal locking using CBCT: a simulation study.

Science.gov (United States)

Kamarianakis, Z; Buliev, I; Pallikarakis, N

2011-05-01

Closed intramedullary nailing is a common technique for treatment of femur and tibia fractures. The most challenging step in this procedure is the precise placement of the lateral screws that stabilize the fragmented bone. The present work concerns the development and the evaluation of a method to accurately identify in the 3D space the axes of the nail hole canals. A limited number of projection images are acquired around the leg with the help of a C-arm. On two of them, the locking hole entries are interactively selected and a rough localization of the hole axes is performed. Perpendicularly to one of them, cone-beam computed tomography (CBCT) reconstructions are produced. The accurate identification and localization of the hole axes are done by an identification of the centers of the nail holes on the tomograms and a further 3D linear regression through principal component analysis (PCA). Various feature-based approaches (RANSAC, least-square fitting, Hough transform) have been compared for best matching the contours and the centers of the holes on the tomograms. The robustness of the suggested method was investigated using simulations. Programming is done in Matlab and C++. Results obtained on synthetic data confirm very good localization accuracy - mean translational error of 0.14 mm (std=0.08 mm) and mean angular error of 0.84° (std=0.35°) at no radiation excess. Successful localization can be further used to guide a surgeon or a robot for correct drilling the bone along the nail openings. Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

A robust frame element with cyclic plasticity and local joint effects

DEFF Research Database (Denmark)

Tidemann, Lasse; Krenk, Steen

2018-01-01

A robust elasto-plastic element is developed for analysis of frame structures. The element consists of a beam member with end joints with properties permitting representation of the effect of section forces in adjoining members, like axial forces. By use of the equilibrium formulation...... is developed, using a mid-step state to obtain representative information about the return path. The element is implemented in a co-rotational large-deformation computer program for frame structures. The formulation is illustrated by application to a couple of typical offshore frame structures, and comparison...... of different representations of the plastic effects illustrates the importance of a robust element with realistic representation of the cyclic plastic mechanisms....

How Robust is Your System Resilience?

Science.gov (United States)

Homayounfar, M.; Muneepeerakul, R.

2017-12-01

Robustness and resilience are concepts in system thinking that have grown in importance and popularity. For many complex social-ecological systems, however, robustness and resilience are difficult to quantify and the connections and trade-offs between them difficult to study. Most studies have either focused on qualitative approaches to discuss their connections or considered only one of them under particular classes of disturbances. In this study, we present an analytical framework to address the linkage between robustness and resilience more systematically. Our analysis is based on a stylized dynamical model that operationalizes a widely used concept framework for social-ecological systems. The model enables us to rigorously define robustness and resilience and consequently investigate their connections. The results reveal the tradeoffs among performance, robustness, and resilience. They also show how the nature of the such tradeoffs varies with the choices of certain policies (e.g., taxation and investment in public infrastructure), internal stresses and external disturbances.

Robust Regression Analysis of GCMS Data Reveals Differential Rewiring of Metabolic Networks in Hepatitis B and C Patients

Directory of Open Access Journals (Sweden)

Cedric Simillion

2017-10-01

Full Text Available About one in 15 of the world’s population is chronically infected with either hepatitis virus B (HBV or C (HCV, with enormous public health consequences. The metabolic alterations caused by these infections have never been directly compared and contrasted. We investigated groups of HBV-positive, HCV-positive, and uninfected healthy controls using gas chromatography-mass spectrometry analyses of their plasma and urine. A robust regression analysis of the metabolite data was conducted to reveal correlations between metabolite pairs. Ten metabolite correlations appeared for HBV plasma and urine, with 18 for HCV plasma and urine, none of which were present in the controls. Metabolic perturbation networks were constructed, which permitted a differential view of the HBV- and HCV-infected liver. HBV hepatitis was consistent with enhanced glucose uptake, glycolysis, and pentose phosphate pathway metabolism, the latter using xylitol and producing threonic acid, which may also be imported by glucose transporters. HCV hepatitis was consistent with impaired glucose uptake, glycolysis, and pentose phosphate pathway metabolism, with the tricarboxylic acid pathway fueled by branched-chain amino acids feeding gluconeogenesis and the hepatocellular loss of glucose, which most probably contributed to hyperglycemia. It is concluded that robust regression analyses can uncover metabolic rewiring in disease states.

Robust extraction of baseline signal of atmospheric trace species using local regression

Directory of Open Access Journals (Sweden)

A. F. Ruckstuhl

2012-11-01

Full Text Available The identification of atmospheric trace species measurements that are representative of well-mixed background air masses is required for monitoring atmospheric composition change at background sites. We present a statistical method based on robust local regression that is well suited for the selection of background measurements and the estimation of associated baseline curves. The bootstrap technique is applied to calculate the uncertainty in the resulting baseline curve. The non-parametric nature of the proposed approach makes it a very flexible data filtering method. Application to carbon monoxide (CO measured from 1996 to 2009 at the high-alpine site Jungfraujoch (Switzerland, 3580 m a.s.l., and to measurements of 1,1-difluoroethane (HFC-152a from Jungfraujoch (2000 to 2009 and Mace Head (Ireland, 1995 to 2009 demonstrates the feasibility and usefulness of the proposed approach.

The determined average annual change of CO at Jungfraujoch for the 1996 to 2009 period as estimated from filtered annual mean CO concentrations is −2.2 ± 1.1 ppb yr⁻¹. For comparison, the linear trend of unfiltered CO measurements at Jungfraujoch for this time period is −2.9 ± 1.3 ppb yr⁻¹.

Robust Sequential Covariance Intersection Fusion Kalman Filtering over Multi-agent Sensor Networks with Measurement Delays and Uncertain Noise Variances

Institute of Scientific and Technical Information of China (English)

QI Wen-Juan; ZHANG Peng; DENG Zi-Li

2014-01-01

This paper deals with the problem of designing robust sequential covariance intersection (SCI) fusion Kalman filter for the clustering multi-agent sensor network system with measurement delays and uncertain noise variances. The sensor network is partitioned into clusters by the nearest neighbor rule. Using the minimax robust estimation principle, based on the worst-case conservative sensor network system with conservative upper bounds of noise variances, and applying the unbiased linear minimum variance (ULMV) optimal estimation rule, we present the two-layer SCI fusion robust steady-state Kalman filter which can reduce communication and computation burdens and save energy sources, and guarantee that the actual filtering error variances have a less-conservative upper-bound. A Lyapunov equation method for robustness analysis is proposed, by which the robustness of the local and fused Kalman filters is proved. The concept of the robust accuracy is presented and the robust accuracy relations of the local and fused robust Kalman filters are proved. It is proved that the robust accuracy of the global SCI fuser is higher than those of the local SCI fusers and the robust accuracies of all SCI fusers are higher than that of each local robust Kalman filter. A simulation example for a tracking system verifies the robustness and robust accuracy relations.

COA based robust output feedback UPFC controller design

Energy Technology Data Exchange (ETDEWEB)

Shayeghi, H., E-mail: hshayeghi@gmail.co [Technical Engineering Department, University of Mohaghegh Ardabili, Ardabil (Iran, Islamic Republic of); Shayanfar, H.A. [Center of Excellence for Power System Automation and Operation, Electrical Engineering Department, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of); Jalilzadeh, S.; Safari, A. [Technical Engineering Department, Zanjan University, Zanjan (Iran, Islamic Republic of)

2010-12-15

In this paper, a novel method for the design of output feedback controller for unified power flow controller (UPFC) using chaotic optimization algorithm (COA) is developed. Chaotic optimization algorithms, which have the features of easy implementation, short execution time and robust mechanisms of escaping from the local optimum, is a promising tool for the engineering applications. The selection of the output feedback gains for the UPFC controllers is converted to an optimization problem with the time domain-based objective function which is solved by a COA based on Lozi map. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed chaotic optimization problem introduces chaos mapping using Lozi map chaotic sequences which increases its convergence rate and resulting precision. To ensure the robustness of the proposed stabilizers, the design process takes into account a wide range of operating conditions and system configurations. The effectiveness of the proposed controller for damping low frequency oscillations is tested and demonstrated through non-linear time-domain simulation and some performance indices studies. The results analysis reveals that the designed COA based output feedback UPFC damping controller has an excellent capability in damping power system low frequency oscillations and enhance greatly the dynamic stability of the power systems.

Robust localized-orbital transferability using the Harris functional

International Nuclear Information System (INIS)

Hierse, W.; Stechel, E.B.

1996-01-01

Replacing diagonalization in a density-functional code by an order-N algorithm does not automatically produce large efficiency gains, at least for system sizes accessible to the current generation of computers. However, both efficiency and conceptual advantages do arise from the transfer of local electronic structure between locally similar, but globally different systems. Order-N methods produce potentially transferable local electronic structure. For practical applications, it is desirable that electronic structure be transferable between subsystems of similar yet somewhat different geometry. We show, in the context of molecular deformations of a simple hydrocarbon system, that this can be accomplished by combining a transfer prescription with the Harris functional. We show proof of principle and discuss the resulting efficiency gains. copyright 1996 The American Physical Society

Robust optimization of the billet for isothermal local loading transitional region of a Ti-alloy rib-web component based on dual-response surface method

Science.gov (United States)

Wei, Ke; Fan, Xiaoguang; Zhan, Mei; Meng, Miao

2018-03-01

Billet optimization can greatly improve the forming quality of the transitional region in the isothermal local loading forming (ILLF) of large-scale Ti-alloy ribweb components. However, the final quality of the transitional region may be deteriorated by uncontrollable factors, such as the manufacturing tolerance of the preforming billet, fluctuation of the stroke length, and friction factor. Thus, a dual-response surface method (RSM)-based robust optimization of the billet was proposed to address the uncontrollable factors in transitional region of the ILLF. Given that the die underfilling and folding defect are two key factors that influence the forming quality of the transitional region, minimizing the mean and standard deviation of the die underfilling rate and avoiding folding defect were defined as the objective function and constraint condition in robust optimization. Then, the cross array design was constructed, a dual-RSM model was established for the mean and standard deviation of the die underfilling rate by considering the size parameters of the billet and uncontrollable factors. Subsequently, an optimum solution was derived to achieve the robust optimization of the billet. A case study on robust optimization was conducted. Good results were attained for improving the die filling and avoiding folding defect, suggesting that the robust optimization of the billet in the transitional region of the ILLF was efficient and reliable.

Robust imaging of localized scatterers using the singular value decomposition and ℓ1 minimization

International Nuclear Information System (INIS)

Chai, A; Moscoso, M; Papanicolaou, G

2013-01-01

We consider narrow band, active array imaging of localized scatterers in a homogeneous medium with and without additive noise. We consider both single and multiple illuminations and study ℓ 1 minimization-based imaging methods. We show that for large arrays, with array diameter comparable to range, and when scatterers are sparse and well separated, ℓ 1 minimization using a single illumination and without additive noise can recover the location and reflectivity of the scatterers exactly. For multiple illuminations, we introduce a hybrid method which combines the singular value decomposition and ℓ 1 minimization. This method can be used when the essential singular vectors of the array response matrix are available. We show that with this hybrid method we can recover the location and reflectivity of the scatterers exactly when there is no noise in the data. Numerical simulations indicate that the hybrid method is, in addition, robust to noise in the data. We also compare the ℓ 1 minimization-based methods with others including Kirchhoff migration, ℓ 2 minimization and multiple signal classification. (paper)

Robust scaling in ecosystems and the meltdown of patch size distributions before extinction

NARCIS (Netherlands)

Kefi, S.; Rietkerk, M.; Roy, M.; Franc, A.; Ruiter, de P.C.; Pascual, M.

2011-01-01

Robust critical systems are characterized by power laws which occur over a broad range of conditions. Their robust behaviour has been explained by local interactions. While such systems could be widespread in nature, their properties are not well understood. Here, we study three robust critical

Robust Huber-based iterated divided difference filtering with application to cooperative localization of autonomous underwater vehicles.

Science.gov (United States)

Gao, Wei; Liu, Yalong; Xu, Bo

2014-12-19

A new algorithm called Huber-based iterated divided difference filtering (HIDDF) is derived and applied to cooperative localization of autonomous underwater vehicles (AUVs) supported by a single surface leader. The position states are estimated using acoustic range measurements relative to the leader, in which some disadvantages such as weak observability, large initial error and contaminated measurements with outliers are inherent. By integrating both merits of iterated divided difference filtering (IDDF) and Huber's M-estimation methodology, the new filtering method could not only achieve more accurate estimation and faster convergence contrast to standard divided difference filtering (DDF) in conditions of weak observability and large initial error, but also exhibit robustness with respect to outlier measurements, for which the standard IDDF would exhibit severe degradation in estimation accuracy. The correctness as well as validity of the algorithm is demonstrated through experiment results.

Incentive-Compatible Robust Line Planning

Science.gov (United States)

Bessas, Apostolos; Kontogiannis, Spyros; Zaroliagis, Christos

The problem of robust line planning requests for a set of origin-destination paths (lines) along with their frequencies in an underlying railway network infrastructure, which are robust to fluctuations of real-time parameters of the solution. In this work, we investigate a variant of robust line planning stemming from recent regulations in the railway sector that introduce competition and free railway markets, and set up a new application scenario: there is a (potentially large) number of line operators that have their lines fixed and operate as competing entities issuing frequency requests, while the management of the infrastructure itself remains the responsibility of a single entity, the network operator. The line operators are typically unwilling to reveal their true incentives, while the network operator strives to ensure a fair (or socially optimal) usage of the infrastructure, e.g., by maximizing the (unknown to him) aggregate incentives of the line operators.

A robust automated left ventricle region of interest localization technique using a cardiac cine MRI atlas

Science.gov (United States)

Ben-Zikri, Yehuda Kfir; Linte, Cristian A.

2016-03-01

Region of interest detection is a precursor to many medical image processing and analysis applications, including segmentation, registration and other image manipulation techniques. The optimal region of interest is often selected manually, based on empirical knowledge and features of the image dataset. However, if inconsistently identified, the selected region of interest may greatly affect the subsequent image analysis or interpretation steps, in turn leading to incomplete assessment during computer-aided diagnosis or incomplete visualization or identification of the surgical targets, if employed in the context of pre-procedural planning or image-guided interventions. Therefore, the need for robust, accurate and computationally efficient region of interest localization techniques is prevalent in many modern computer-assisted diagnosis and therapy applications. Here we propose a fully automated, robust, a priori learning-based approach that provides reliable estimates of the left and right ventricle features from cine cardiac MR images. The proposed approach leverages the temporal frame-to-frame motion extracted across a range of short axis left ventricle slice images with small training set generated from les than 10% of the population. This approach is based on histogram of oriented gradients features weighted by local intensities to first identify an initial region of interest depicting the left and right ventricles that exhibits the greatest extent of cardiac motion. This region is correlated with the homologous region that belongs to the training dataset that best matches the test image using feature vector correlation techniques. Lastly, the optimal left ventricle region of interest of the test image is identified based on the correlation of known ground truth segmentations associated with the training dataset deemed closest to the test image. The proposed approach was tested on a population of 100 patient datasets and was validated against the ground truth

Robust Droop Control of Grid-Connected Inverters

DEFF Research Database (Denmark)

Elkayam, Moria; Kuperman, Alon; Guerrero, Josep M.

2016-01-01

The use of distributed generation in microgrid systems is becoming a popular way to provide a reliable source of electricity to critical loads. Droop control techniques are used in power systems for the synchronization of grid-connected inverters by local measurements of active and reactive powers....... Despite the benefits of distributed generation, the drawback is that large grid-side impedance steps can cause a system to become unstable. A robust control method based on disturbance observer is proposed in this paper. When the proposed robust controller is utilized, closed loop performance remains...

Robust Synchronization of Delayed Chaotic FitzHugh-Nagumo Neurons under External Electrical Stimulation

Directory of Open Access Journals (Sweden)

Muhammad Rehan

2012-01-01

Full Text Available Synchronization of chaotic neurons under external electrical stimulation (EES is studied in order to understand information processing in the brain and to improve the methodologies employed in the treatment of cognitive diseases. This paper investigates the dynamics of uncertain coupled chaotic delayed FitzHugh-Nagumo (FHN neurons under EES for incorporated parametric variations. A global nonlinear control law for synchronization of delayed neurons with known parameters is developed. Based on local and global Lipschitz conditions, knowledge of the bounds on the neuronal states, the Lyapunov-Krasovskii functional, and the L2 gain reduction, a less conservative local robust nonlinear control law is formulated to address the problem of robust asymptotic synchronization of delayed FHN neurons under parametric uncertainties. The proposed local control law guarantees both robust stability and robust performance and provides the L2 bound for uncertainty rejection in the synchronization error dynamics. Separate conditions for single-input and multiple-input control schemes for synchronization of a wide class of FHN systems are provided. The results of the proposed techniques are verified through numerical simulations.

Robust, fast and accurate vision-based localization of a cooperative target used for space robotic arm

Science.gov (United States)

Wen, Zhuoman; Wang, Yanjie; Luo, Jun; Kuijper, Arjan; Di, Nan; Jin, Minghe

2017-07-01

When a space robotic arm deploys a payload, usually the pose between the cooperative target fixed on the payload and the hand-eye camera installed on the arm is calculated in real-time. A high-precision robust visual cooperative target localization method is proposed. Combing a circle, a line and dots as markers, a target that guarantees high detection rates is designed. Given an image, single-pixel-width smooth edges are drawn by a novel linking method. Circles are then quickly extracted using isophotes curvature. Around each circle, a square boundary in a pre-calculated proportion to the circle radius is set. In the boundary, the target is identified if certain numbers of lines exist. Based on the circle, the lines, and the target foreground and background intensities, markers are localized. Finally, the target pose is calculated by the Point-3-Perspective algorithm. The algorithm processes 8 frames per second with the target distance ranging from 0.3m to 1.5 m. It generated high-precision poses of above 97.5% on over 100,000 images regardless of camera background, target pose, illumination and motion blur. At 0.3 m, the rotation and translation errors were less than 0.015° and 0.2 mm. The proposed algorithm is very suitable for real-time visual measurement that requires high precision in aerospace.

Robustness of quantum correlations against linear noise

International Nuclear Information System (INIS)

Guo, Zhihua; Cao, Huaixin; Qu, Shixian

2016-01-01

Relative robustness of quantum correlations (RRoQC) of a bipartite state is firstly introduced relative to a classically correlated state. Robustness of quantum correlations (RoQC) of a bipartite state is then defined as the minimum of RRoQC of the state relative to all classically correlated ones. It is proved that as a function on quantum states, RoQC is nonnegative, lower semi-continuous and neither convex nor concave; especially, it is zero if and only if the state is classically correlated. Thus, RoQC not only quantifies the endurance of quantum correlations of a state against linear noise, but also can be used to distinguish between quantum and classically correlated states. Furthermore, the effects of local quantum channels on the robustness are explored and characterized. (paper)

mRNA-Seq Reveals Novel Molecular Mechanisms and a Robust Fingerprint in Graves' Disease

Science.gov (United States)

Sachidanandam, Ravi; Morshed, Syed; Latif, Rauf; Shi, Ruijin; Davies, Terry F.

2014-01-01

Context: The immune response in autoimmune thyroid disease has been shown to occur primarily within the thyroid gland in which the most abundant antigens can be found. A variety of capture molecules are known to be expressed by thyroid epithelial cells and serve to attract and help retain an intrathyroidal immune infiltrate. Objective: To explore the entire repertoire of expressed genes in human thyroid tissue, we have deep sequenced the transcriptome (referred to as mRNA-Seq). Design and Patients: We applied mRNA-Seq to thyroid tissue from nine patients with Graves' disease subjected to total thyroidectomy and compared the data with 12 samples of normal thyroid tissue obtained from patients having a thyroid nodule removed. The expression for each gene was calculated from the sequencing data by taking the median of the coverage across the length of the gene. The expression levels were quantile normalized and a gene signature was derived from these. Results: On comparison of expression levels in tissues derived from Graves' patients and controls, there was clear evidence for overexpression of the antigen presentation pathway consisting of HLA and associated genes. We also found a robust disease signature and discovered active innate and adaptive immune signaling networks. Conclusions: These data reveal an active immune defense system in Graves' disease, which involves novel molecular mechanisms in its pathogenesis and development. PMID:24971664

Expression-robust 3D face recognition via weighted sparse representation of multi-scale and multi-component local normal patterns

KAUST Repository

Li, Huibin

2014-06-01

In the theory of differential geometry, surface normal, as a first order surface differential quantity, determines the orientation of a surface at each point and contains informative local surface shape information. To fully exploit this kind of information for 3D face recognition (FR), this paper proposes a novel highly discriminative facial shape descriptor, namely multi-scale and multi-component local normal patterns (MSMC-LNP). Given a normalized facial range image, three components of normal vectors are first estimated, leading to three normal component images. Then, each normal component image is encoded locally to local normal patterns (LNP) on different scales. To utilize spatial information of facial shape, each normal component image is divided into several patches, and their LNP histograms are computed and concatenated according to the facial configuration. Finally, each original facial surface is represented by a set of LNP histograms including both global and local cues. Moreover, to make the proposed solution robust to the variations of facial expressions, we propose to learn the weight of each local patch on a given encoding scale and normal component image. Based on the learned weights and the weighted LNP histograms, we formulate a weighted sparse representation-based classifier (W-SRC). In contrast to the overwhelming majority of 3D FR approaches which were only benchmarked on the FRGC v2.0 database, we carried out extensive experiments on the FRGC v2.0, Bosphorus, BU-3DFE and 3D-TEC databases, thus including 3D face data captured in different scenarios through various sensors and depicting in particular different challenges with respect to facial expressions. The experimental results show that the proposed approach consistently achieves competitive rank-one recognition rates on these databases despite their heterogeneous nature, and thereby demonstrates its effectiveness and its generalizability. © 2014 Elsevier B.V.

Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins.

Science.gov (United States)

Loo, Lit-Hsin; Laksameethanasan, Danai; Tung, Yi-Ling

2014-03-01

Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images. PLAST produces human-interpretable protein localization maps that quantitatively describe the similarities in the localization patterns of proteins and major subcellular compartments, without requiring manual assignment or supervised learning of these compartments. Using the budding yeast Saccharomyces cerevisiae as a model system, we show that PLAST is more accurate than existing, qualitative protein localization annotations in identifying known co-localized proteins. Furthermore, we demonstrate that PLAST can reveal protein localization-function relationships that are not obvious from these annotations. First, we identified proteins that have similar localization patterns and participate in closely-related biological processes, but do not necessarily form stable complexes with each other or localize at the same organelles. Second, we found an association between spatial and functional divergences of proteins during evolution. Surprisingly, as proteins with common ancestors evolve, they tend to develop more diverged subcellular localization patterns, but still occupy similar numbers of compartments. This suggests that divergence of protein localization might be more frequently due to the development of more specific localization patterns over ancestral compartments than the occupation of new compartments. PLAST enables systematic and quantitative analyses of protein localization-function relationships, and will be useful to elucidate protein

Development of Robust Behaviour Recognition for an at-Home Biomonitoring Robot with Assistance of Subject Localization and Enhanced Visual Tracking

Science.gov (United States)

Imamoglu, Nevrez; Dorronzoro, Enrique; Wei, Zhixuan; Shi, Huangjun; González, José; Gu, Dongyun; Yu, Wenwei

2014-01-01

Our research is focused on the development of an at-home health care biomonitoring mobile robot for the people in demand. Main task of the robot is to detect and track a designated subject while recognizing his/her activity for analysis and to provide warning in an emergency. In order to push forward the system towards its real application, in this study, we tested the robustness of the robot system with several major environment changes, control parameter changes, and subject variation. First, an improved color tracker was analyzed to find out the limitations and constraints of the robot visual tracking considering the suitable illumination values and tracking distance intervals. Then, regarding subject safety and continuous robot based subject tracking, various control parameters were tested on different layouts in a room. Finally, the main objective of the system is to find out walking activities for different patterns for further analysis. Therefore, we proposed a fast, simple, and person specific new activity recognition model by making full use of localization information, which is robust to partial occlusion. The proposed activity recognition algorithm was tested on different walking patterns with different subjects, and the results showed high recognition accuracy. PMID:25587560

Development of Robust Behaviour Recognition for an at-Home Biomonitoring Robot with Assistance of Subject Localization and Enhanced Visual Tracking

Directory of Open Access Journals (Sweden)

Nevrez Imamoglu

2014-01-01

Full Text Available Our research is focused on the development of an at-home health care biomonitoring mobile robot for the people in demand. Main task of the robot is to detect and track a designated subject while recognizing his/her activity for analysis and to provide warning in an emergency. In order to push forward the system towards its real application, in this study, we tested the robustness of the robot system with several major environment changes, control parameter changes, and subject variation. First, an improved color tracker was analyzed to find out the limitations and constraints of the robot visual tracking considering the suitable illumination values and tracking distance intervals. Then, regarding subject safety and continuous robot based subject tracking, various control parameters were tested on different layouts in a room. Finally, the main objective of the system is to find out walking activities for different patterns for further analysis. Therefore, we proposed a fast, simple, and person specific new activity recognition model by making full use of localization information, which is robust to partial occlusion. The proposed activity recognition algorithm was tested on different walking patterns with different subjects, and the results showed high recognition accuracy.

Development of robust behaviour recognition for an at-home biomonitoring robot with assistance of subject localization and enhanced visual tracking.

Science.gov (United States)

Imamoglu, Nevrez; Dorronzoro, Enrique; Wei, Zhixuan; Shi, Huangjun; Sekine, Masashi; González, José; Gu, Dongyun; Chen, Weidong; Yu, Wenwei

2014-01-01

Our research is focused on the development of an at-home health care biomonitoring mobile robot for the people in demand. Main task of the robot is to detect and track a designated subject while recognizing his/her activity for analysis and to provide warning in an emergency. In order to push forward the system towards its real application, in this study, we tested the robustness of the robot system with several major environment changes, control parameter changes, and subject variation. First, an improved color tracker was analyzed to find out the limitations and constraints of the robot visual tracking considering the suitable illumination values and tracking distance intervals. Then, regarding subject safety and continuous robot based subject tracking, various control parameters were tested on different layouts in a room. Finally, the main objective of the system is to find out walking activities for different patterns for further analysis. Therefore, we proposed a fast, simple, and person specific new activity recognition model by making full use of localization information, which is robust to partial occlusion. The proposed activity recognition algorithm was tested on different walking patterns with different subjects, and the results showed high recognition accuracy.

Robust haptic large distance telemanipulation for ITER

International Nuclear Information System (INIS)

Heck, D.J.F.; Heemskerk, C.J.M.; Koning, J.F.; Abbasi, A.; Nijmeijer, H.

2013-01-01

Highlights: • ITER remote handling maintenance can be controlled safely over a large distance. • Bilateral teleoperation experiments were performed in a local network. • Wave variables make the controller robust against constant communication delays. • Master and slave position synchronization guaranteed by proportional action. -- Abstract: During shutdowns, maintenance crews are expected to work in 24/6 shifts to perform critical remote handling maintenance tasks on the ITER system. In this article, we investigate the possibility to safely perform these haptic maintenance tasks remotely from control stations located anywhere around the world. To guarantee stability in time delayed bilateral teleoperation, the symmetric position tracking controller using wave variables is selected. This algorithm guarantees robustness against communication delays, can eliminate wave reflections and provide position synchronization of the master and slave devices. Experiments have been conducted under realistic local network bandwidth, latency and jitter constraints. They show sufficient transparency even for substantial communication delays

Robust haptic large distance telemanipulation for ITER

Energy Technology Data Exchange (ETDEWEB)

Heck, D.J.F., E-mail: d.j.f.heck@tue.nl [Eindhoven University of Technology, Department of Mechanical Engineering, Eindhoven (Netherlands); Heemskerk, C.J.M.; Koning, J.F. [Heemskerk Innovative Technologies, Sassenheim (Netherlands); Abbasi, A.; Nijmeijer, H. [Eindhoven University of Technology, Department of Mechanical Engineering, Eindhoven (Netherlands)

2013-10-15

Highlights: • ITER remote handling maintenance can be controlled safely over a large distance. • Bilateral teleoperation experiments were performed in a local network. • Wave variables make the controller robust against constant communication delays. • Master and slave position synchronization guaranteed by proportional action. -- Abstract: During shutdowns, maintenance crews are expected to work in 24/6 shifts to perform critical remote handling maintenance tasks on the ITER system. In this article, we investigate the possibility to safely perform these haptic maintenance tasks remotely from control stations located anywhere around the world. To guarantee stability in time delayed bilateral teleoperation, the symmetric position tracking controller using wave variables is selected. This algorithm guarantees robustness against communication delays, can eliminate wave reflections and provide position synchronization of the master and slave devices. Experiments have been conducted under realistic local network bandwidth, latency and jitter constraints. They show sufficient transparency even for substantial communication delays.

Robustness Metrics: Consolidating the multiple approaches to quantify Robustness

DEFF Research Database (Denmark)

Göhler, Simon Moritz; Eifler, Tobias; Howard, Thomas J.

2016-01-01

robustness metrics; 3) Functional expectancy and dispersion robustness metrics; and 4) Probability of conformance robustness metrics. The goal was to give a comprehensive overview of robustness metrics and guidance to scholars and practitioners to understand the different types of robustness metrics...

WE-AB-BRA-01: 3D-2D Image Registration for Target Localization in Spine Surgery: Comparison of Similarity Metrics Against Robustness to Content Mismatch

International Nuclear Information System (INIS)

De Silva, T; Ketcha, M; Siewerdsen, J H; Uneri, A; Reaungamornrat, S; Vogt, S; Kleinszig, G; Lo, S F; Wolinsky, J P; Gokaslan, Z L; Aygun, N

2015-01-01

Purpose: In image-guided spine surgery, mapping 3D preoperative images to 2D intraoperative images via 3D-2D registration can provide valuable assistance in target localization. However, the presence of surgical instrumentation, hardware implants, and soft-tissue resection/displacement causes mismatches in image content, confounding existing registration methods. Manual/semi-automatic methods to mask such extraneous content is time consuming, user-dependent, error prone, and disruptive to clinical workflow. We developed and evaluated 2 novel similarity metrics within a robust registration framework to overcome such challenges in target localization. Methods: An IRB-approved retrospective study in 19 spine surgery patients included 19 preoperative 3D CT images and 50 intraoperative mobile radiographs in cervical, thoracic, and lumbar spine regions. A neuroradiologist provided truth definition of vertebral positions in CT and radiography. 3D-2D registration was performed using the CMA-ES optimizer with 4 gradient-based image similarity metrics: (1) gradient information (GI); (2) gradient correlation (GC); (3) a novel variant referred to as gradient orientation (GO); and (4) a second variant referred to as truncated gradient correlation (TGC). Registration accuracy was evaluated in terms of the projection distance error (PDE) of the vertebral levels. Results: Conventional similarity metrics were susceptible to gross registration error and failure modes associated with the presence of surgical instrumentation: for GI, the median PDE and interquartile range was 33.0±43.6 mm; similarly for GC, PDE = 23.0±92.6 mm respectively. The robust metrics GO and TGC, on the other hand, demonstrated major improvement in PDE (7.6 ±9.4 mm and 8.1± 18.1 mm, respectively) and elimination of gross failure modes. Conclusion: The proposed GO and TGC similarity measures improve registration accuracy and robustness to gross failure in the presence of strong image content mismatch. Such

WE-AB-BRA-01: 3D-2D Image Registration for Target Localization in Spine Surgery: Comparison of Similarity Metrics Against Robustness to Content Mismatch

Energy Technology Data Exchange (ETDEWEB)

De Silva, T; Ketcha, M; Siewerdsen, J H [Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD (United States); Uneri, A; Reaungamornrat, S [Department of Computer Science, Johns Hopkins University, Baltimore, MD (United States); Vogt, S; Kleinszig, G [Siemens Healthcare XP Division, Erlangen, DE (Germany); Lo, S F; Wolinsky, J P; Gokaslan, Z L [Department of Neurosurgery, The Johns Hopkins Hospital, Baltimore, MD (United States); Aygun, N [Department of Raiology and Radiological Sciences, The Johns Hopkins Hospital, Baltimore, MD (United States)

2015-06-15

Purpose: In image-guided spine surgery, mapping 3D preoperative images to 2D intraoperative images via 3D-2D registration can provide valuable assistance in target localization. However, the presence of surgical instrumentation, hardware implants, and soft-tissue resection/displacement causes mismatches in image content, confounding existing registration methods. Manual/semi-automatic methods to mask such extraneous content is time consuming, user-dependent, error prone, and disruptive to clinical workflow. We developed and evaluated 2 novel similarity metrics within a robust registration framework to overcome such challenges in target localization. Methods: An IRB-approved retrospective study in 19 spine surgery patients included 19 preoperative 3D CT images and 50 intraoperative mobile radiographs in cervical, thoracic, and lumbar spine regions. A neuroradiologist provided truth definition of vertebral positions in CT and radiography. 3D-2D registration was performed using the CMA-ES optimizer with 4 gradient-based image similarity metrics: (1) gradient information (GI); (2) gradient correlation (GC); (3) a novel variant referred to as gradient orientation (GO); and (4) a second variant referred to as truncated gradient correlation (TGC). Registration accuracy was evaluated in terms of the projection distance error (PDE) of the vertebral levels. Results: Conventional similarity metrics were susceptible to gross registration error and failure modes associated with the presence of surgical instrumentation: for GI, the median PDE and interquartile range was 33.0±43.6 mm; similarly for GC, PDE = 23.0±92.6 mm respectively. The robust metrics GO and TGC, on the other hand, demonstrated major improvement in PDE (7.6 ±9.4 mm and 8.1± 18.1 mm, respectively) and elimination of gross failure modes. Conclusion: The proposed GO and TGC similarity measures improve registration accuracy and robustness to gross failure in the presence of strong image content mismatch. Such

Data-Driven Neural Network Model for Robust Reconstruction of Automobile Casting

Science.gov (United States)

Lin, Jinhua; Wang, Yanjie; Li, Xin; Wang, Lu

2017-09-01

In computer vision system, it is a challenging task to robustly reconstruct complex 3D geometries of automobile castings. However, 3D scanning data is usually interfered by noises, the scanning resolution is low, these effects normally lead to incomplete matching and drift phenomenon. In order to solve these problems, a data-driven local geometric learning model is proposed to achieve robust reconstruction of automobile casting. In order to relieve the interference of sensor noise and to be compatible with incomplete scanning data, a 3D convolution neural network is established to match the local geometric features of automobile casting. The proposed neural network combines the geometric feature representation with the correlation metric function to robustly match the local correspondence. We use the truncated distance field(TDF) around the key point to represent the 3D surface of casting geometry, so that the model can be directly embedded into the 3D space to learn the geometric feature representation; Finally, the training labels is automatically generated for depth learning based on the existing RGB-D reconstruction algorithm, which accesses to the same global key matching descriptor. The experimental results show that the matching accuracy of our network is 92.2% for automobile castings, the closed loop rate is about 74.0% when the matching tolerance threshold τ is 0.2. The matching descriptors performed well and retained 81.6% matching accuracy at 95% closed loop. For the sparse geometric castings with initial matching failure, the 3D matching object can be reconstructed robustly by training the key descriptors. Our method performs 3D reconstruction robustly for complex automobile castings.

Critical cooperation range to improve spatial network robustness.

Directory of Open Access Journals (Sweden)

Vitor H P Louzada

Full Text Available A robust worldwide air-transportation network (WAN is one that minimizes the number of stranded passengers under a sequence of airport closures. Building on top of this realistic example, here we address how spatial network robustness can profit from cooperation between local actors. We swap a series of links within a certain distance, a cooperation range, while following typical constraints of spatially embedded networks. We find that the network robustness is only improved above a critical cooperation range. Such improvement can be described in the framework of a continuum transition, where the critical exponents depend on the spatial correlation of connected nodes. For the WAN we show that, except for Australia, all continental networks fall into the same universality class. Practical implications of this result are also discussed.

A robust spatial filtering technique for multisource localization and geoacoustic inversion.

Science.gov (United States)

Stotts, S A

2005-07-01

Geoacoustic inversion and source localization using beamformed data from a ship of opportunity has been demonstrated with a bottom-mounted array. An alternative approach, which lies within a class referred to as spatial filtering, transforms element level data into beam data, applies a bearing filter, and transforms back to element level data prior to performing inversions. Automation of this filtering approach is facilitated for broadband applications by restricting the inverse transform to the degrees of freedom of the array, i.e., the effective number of elements, for frequencies near or below the design frequency. A procedure is described for nonuniformly spaced elements that guarantees filter stability well above the design frequency. Monitoring energy conservation with respect to filter output confirms filter stability. Filter performance with both uniformly spaced and nonuniformly spaced array elements is discussed. Vertical (range and depth) and horizontal (range and bearing) ambiguity surfaces are constructed to examine filter performance. Examples that demonstrate this filtering technique with both synthetic data and real data are presented along with comparisons to inversion results using beamformed data. Examinations of cost functions calculated within a simulated annealing algorithm reveal the efficacy of the approach.

An Intercompany Perspective on Biopharmaceutical Drug Product Robustness Studies.

Science.gov (United States)

Morar-Mitrica, Sorina; Adams, Monica L; Crotts, George; Wurth, Christine; Ihnat, Peter M; Tabish, Tanvir; Antochshuk, Valentyn; DiLuzio, Willow; Dix, Daniel B; Fernandez, Jason E; Gupta, Kapil; Fleming, Michael S; He, Bing; Kranz, James K; Liu, Dingjiang; Narasimhan, Chakravarthy; Routhier, Eric; Taylor, Katherine D; Truong, Nobel; Stokes, Elaine S E

2018-02-01

The Biophorum Development Group (BPDG) is an industry-wide consortium enabling networking and sharing of best practices for the development of biopharmaceuticals. To gain a better understanding of current industry approaches for establishing biopharmaceutical drug product (DP) robustness, the BPDG-Formulation Point Share group conducted an intercompany collaboration exercise, which included a bench-marking survey and extensive group discussions around the scope, design, and execution of robustness studies. The results of this industry collaboration revealed several key common themes: (1) overall DP robustness is defined by both the formulation and the manufacturing process robustness; (2) robustness integrates the principles of quality by design (QbD); (3) DP robustness is an important factor in setting critical quality attribute control strategies and commercial specifications; (4) most companies employ robustness studies, along with prior knowledge, risk assessments, and statistics, to develop the DP design space; (5) studies are tailored to commercial development needs and the practices of each company. Three case studies further illustrate how a robustness study design for a biopharmaceutical DP balances experimental complexity, statistical power, scientific understanding, and risk assessment to provide the desired product and process knowledge. The BPDG-Formulation Point Share discusses identified industry challenges with regard to biopharmaceutical DP robustness and presents some recommendations for best practices. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Histomorphometry and cortical robusticity of the adult human femur.

Science.gov (United States)

Miszkiewicz, Justyna Jolanta; Mahoney, Patrick

2018-01-13

Recent quantitative analyses of human bone microanatomy, as well as theoretical models that propose bone microstructure and gross anatomical associations, have started to reveal insights into biological links that may facilitate remodeling processes. However, relationships between bone size and the underlying cortical bone histology remain largely unexplored. The goal of this study is to determine the extent to which static indicators of bone remodeling and vascularity, measured using histomorphometric techniques, relate to femoral midshaft cortical width and robusticity. Using previously published and new quantitative data from 450 adult human male (n = 233) and female (n = 217) femora, we determine if these aspects of femoral size relate to bone microanatomy. Scaling relationships are explored and interpreted within the context of tissue form and function. Analyses revealed that the area and diameter of Haversian canals and secondary osteons, and densities of secondary osteons and osteocyte lacunae from the sub-periosteal region of the posterior midshaft femur cortex were significantly, but not consistently, associated with femoral size. Cortical width and bone robusticity were correlated with osteocyte lacunae density and scaled with positive allometry. Diameter and area of osteons and Haversian canals decreased as the width of cortex and bone robusticity increased, revealing a negative allometric relationship. These results indicate that microscopic products of cortical bone remodeling and vascularity are linked to femur size. Allometric relationships between more robust human femora with thicker cortical bone and histological products of bone remodeling correspond with principles of bone functional adaptation. Future studies may benefit from exploring scaling relationships between bone histomorphometric data and measurements of bone macrostructure.

Design process robustness: A bi-partite network analysis reveals the central importance of people

DEFF Research Database (Denmark)

Piccolo, Sebastiano; Jørgensen, Sune Lehmann; Maier, Anja

2018-01-01

, reducing the risk of rework and delays. Although there has been much progress in modelling and understanding design processes, little is known about the interplay between people and the activities they perform and its influence on design process robustness. To analyse this interplay, we model a large...

Using means-end chain analysis to reveal consumers' motivation for buying local foods: An exploratory study

Directory of Open Access Journals (Sweden)

Poppy Arsil

2016-11-01

Full Text Available This article utilizes and discusses specific aspects of Means-End Chain (MEC analysis for understanding of the motives of Indonesian consumers who are involved in purchasing local foods. The MEC theory is used as a measure of attributes, consequences, and values of locally produced products involving specific aspects of this theory namely laddering methods of administration, content analysis procedure, constructing and interpreting Hierarchy Value Map (HVM. The results of the study indicate that MEC approach is a powerful method to reveal consumer motivation of local foods when associated with the various cultural groupings identified by the study particular between Javanese and Non-Javanese consumers. This study offers a practical implication and source of knowledge for other future studies and policies in term of (a a new approach for understanding the motives behind purchasing local foods for Indonesia consumers, and (b developing new categories of attributes, consequences and values of local foods.

Robust estimation for partially linear models with large-dimensional covariates.

Science.gov (United States)

Zhu, LiPing; Li, RunZe; Cui, HengJian

2013-10-01

We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon-cave regularization method in the robust estimation procedure to select important covariates from the linear component. We establish the consistency for both the linear and the nonlinear components when the covariate dimension diverges at the rate of [Formula: see text], where n is the sample size. We show that the robust estimate of linear component performs asymptotically as well as its oracle counterpart which assumes the baseline function and the unimportant covariates were known a priori. With a consistent estimator of the linear component, we estimate the nonparametric component by a robust local linear regression. It is proved that the robust estimate of nonlinear component performs asymptotically as well as if the linear component were known in advance. Comprehensive simulation studies are carried out and an application is presented to examine the finite-sample performance of the proposed procedures.

Robust digital controllers for uncertain chaotic systems: A digital redesign approach

Energy Technology Data Exchange (ETDEWEB)

Ababneh, Mohammad [Department of Controls, FMC Kongsberg Subsea, FMC Energy Systems, Houston, TX 77067 (United States); Barajas-Ramirez, Juan-Gonzalo [CICESE, Depto. De Electronica y Telecomunicaciones, Ensenada, BC, 22860 (Mexico); Chen Guanrong [Centre for Chaos Control and Synchronization, Department of Electronic Engineering, City University of Hong Kong (China); Shieh, Leang S. [Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204-4005 (United States)

2007-03-15

In this paper, a new and systematic method for designing robust digital controllers for uncertain nonlinear systems with structured uncertainties is presented. In the proposed method, a controller is designed in terms of the optimal linear model representation of the nominal system around each operating point of the trajectory, while the uncertainties are decomposed such that the uncertain nonlinear system can be rewritten as a set of local linear models with disturbed inputs. Applying conventional robust control techniques, continuous-time robust controllers are first designed to eliminate the effects of the uncertainties on the underlying system. Then, a robust digital controller is obtained as the result of a digital redesign of the designed continuous-time robust controller using the state-matching technique. The effectiveness of the proposed controller design method is illustrated through some numerical examples on complex nonlinear systems--chaotic systems.

Effects of methodology and analysis strategy on robustness of pestivirus phylogeny.

Science.gov (United States)

Liu, Lihong; Xia, Hongyan; Baule, Claudia; Belák, Sándor; Wahlberg, Niklas

2010-01-01

Phylogenetic analysis of pestiviruses is a useful tool for classifying novel pestiviruses and for revealing their phylogenetic relationships. In this study, robustness of pestivirus phylogenies has been compared by analyses of the 5'UTR, and complete N(pro) and E2 gene regions separately and combined, performed by four methods: neighbour-joining (NJ), maximum parsimony (MP), maximum likelihood (ML), and Bayesian inference (BI). The strategy of analysing the combined sequence dataset by BI, ML, and MP methods resulted in a single, well-supported tree topology, indicating a reliable and robust pestivirus phylogeny. By contrast, the single-gene analysis strategy resulted in 12 trees of different topologies, revealing different relationships among pestiviruses. These results indicate that the strategies and methodologies are two vital aspects affecting the robustness of the pestivirus phylogeny. The strategy and methodologies outlined in this paper may have a broader application in inferring phylogeny of other RNA viruses.

Robust surface roughness indices and morphological interpretation

Science.gov (United States)

Trevisani, Sebastiano; Rocca, Michele

2016-04-01

Geostatistical-based image/surface texture indices based on variogram (Atkison and Lewis, 2000; Herzfeld and Higginson, 1996; Trevisani et al., 2012) and on its robust variant MAD (median absolute differences, Trevisani and Rocca, 2015) offer powerful tools for the analysis and interpretation of surface morphology (potentially not limited to solid earth). In particular, the proposed robust index (Trevisani and Rocca, 2015) with its implementation based on local kernels permits the derivation of a wide set of robust and customizable geomorphometric indices capable to outline specific aspects of surface texture. The stability of MAD in presence of signal noise and abrupt changes in spatial variability is well suited for the analysis of high-resolution digital terrain models. Moreover, the implementation of MAD by means of a pixel-centered perspective based on local kernels, with some analogies to the local binary pattern approach (Lucieer and Stein, 2005; Ojala et al., 2002), permits to create custom roughness indices capable to outline different aspects of surface roughness (Grohmann et al., 2011; Smith, 2015). In the proposed poster, some potentialities of the new indices in the context of geomorphometry and landscape analysis will be presented. At same time, challenges and future developments related to the proposed indices will be outlined. Atkinson, P.M., Lewis, P., 2000. Geostatistical classification for remote sensing: an introduction. Computers & Geosciences 26, 361-371. Grohmann, C.H., Smith, M.J., Riccomini, C., 2011. Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland. IEEE Transactions on Geoscience and Remote Sensing 49, 1220-1213. Herzfeld, U.C., Higginson, C.A., 1996. Automated geostatistical seafloor classification - Principles, parameters, feature vectors, and discrimination criteria. Computers and Geosciences, 22 (1), pp. 35-52. Lucieer, A., Stein, A., 2005. Texture-based landform segmentation of LiDAR imagery

Robust design optimization using the price of robustness, robust least squares and regularization methods

Science.gov (United States)

Bukhari, Hassan J.

2017-12-01

In this paper a framework for robust optimization of mechanical design problems and process systems that have parametric uncertainty is presented using three different approaches. Robust optimization problems are formulated so that the optimal solution is robust which means it is minimally sensitive to any perturbations in parameters. The first method uses the price of robustness approach which assumes the uncertain parameters to be symmetric and bounded. The robustness for the design can be controlled by limiting the parameters that can perturb.The second method uses the robust least squares method to determine the optimal parameters when data itself is subjected to perturbations instead of the parameters. The last method manages uncertainty by restricting the perturbation on parameters to improve sensitivity similar to Tikhonov regularization. The methods are implemented on two sets of problems; one linear and the other non-linear. This methodology will be compared with a prior method using multiple Monte Carlo simulation runs which shows that the approach being presented in this paper results in better performance.

User and stakeholder involvement for relevant, reliable and robust local-scale climate projections in Norway

Science.gov (United States)

Neby, Simon; Sobolowski, Stefan

2017-04-01

How can users and stakeholders be actively involved with providing input to and using output from local-scale climate projections? How can the scientific community better understand the needs of local actors? And how should communication and cooperation efforts be organized? These are critical questions we aim to answer in a climate services project funded by the Norwegian Research Council (R3: Relevant, Reliable and Robust local-scale climate projections for Norway). The project takes into consideration not only the scientific issues in establishing useful local-scale climate projections, but also addresses the "usability gap" between climate information and decision-making. The lack of effective communication between scientists and user communities often result in outputs and products that are not matched with decision-relevant climate information. In the R3 project, the scientific participants actively engage with a range of users that have quite different information needs: municipalities, infrastructure developers, agriculture, energy producers, insurance companies, and more. In this particular presentation, we present our experiences concerning three specific issues that relate to the stakeholder-science interface: 1) Preferences are not clear-cut and pre-defined. In practice, this means that stakeholders often do not have precise information about their needs, nor precise information about how, where and whether their needs can be voiced. Similarly, science communities tend to presuppose that stakeholders are interested and have well-articulated needs, which is hardly the case. Collectively, that means that there is a need for an approach that guides the articulation and prioritization of preferences in a manner that integrates both scientific and stakeholder perspectives and takes the integrity of both perspectives seriously. 2) Technologies are unclear. Although information may be produced and used, past experiences, trial and error processes and pragmatic

Robust-BD Estimation and Inference for General Partially Linear Models

Directory of Open Access Journals (Sweden)

Chunming Zhang

2017-11-01

Full Text Available The classical quadratic loss for the partially linear model (PLM and the likelihood function for the generalized PLM are not resistant to outliers. This inspires us to propose a class of “robust-Bregman divergence (BD” estimators of both the parametric and nonparametric components in the general partially linear model (GPLM, which allows the distribution of the response variable to be partially specified, without being fully known. Using the local-polynomial function estimation method, we propose a computationally-efficient procedure for obtaining “robust-BD” estimators and establish the consistency and asymptotic normality of the “robust-BD” estimator of the parametric component β o . For inference procedures of β o in the GPLM, we show that the Wald-type test statistic W n constructed from the “robust-BD” estimators is asymptotically distribution free under the null, whereas the likelihood ratio-type test statistic Λ n is not. This provides an insight into the distinction from the asymptotic equivalence (Fan and Huang 2005 between W n and Λ n in the PLM constructed from profile least-squares estimators using the non-robust quadratic loss. Numerical examples illustrate the computational effectiveness of the proposed “robust-BD” estimators and robust Wald-type test in the appearance of outlying observations.

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology

Science.gov (United States)

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental

Identification and robust water level control of horizontal steam generators using quantitative feedback theory

International Nuclear Information System (INIS)

Safarzadeh, O.; Khaki-Sedigh, A.; Shirani, A.S.

2011-01-01

Highlights: → A robust water level controller for steam generators (SGs) is designed based on the Quantitative Feedback Theory. → To design the controller, fairly accurate linear models are identified for the SG. → The designed controller is verified using a developed novel global locally linear neuro-fuzzy model of the SG. → Both of the linear and nonlinear models are based on the SG mathematical thermal-hydraulic model developed using the simulation computer code. → The proposed method is easy to apply and guarantees desired closed loop performance. - Abstract: In this paper, a robust water level control system for the horizontal steam generator (SG) using the quantitative feedback theory (QFT) method is presented. To design a robust QFT controller for the nonlinear uncertain SG, control oriented linear models are identified. Then, the nonlinear system is modeled as an uncertain linear time invariant (LTI) system. The robust designed controller is applied to the nonlinear plant model. This nonlinear model is based on a locally linear neuro-fuzzy (LLNF) model. This model is trained using the locally linear model tree (LOLIMOT) algorithm. Finally, simulation results are employed to show the effectiveness of the designed QFT level controller. It is shown that it will ensure the entire designer's water level closed loop specifications.

Identification and robust water level control of horizontal steam generators using quantitative feedback theory

Energy Technology Data Exchange (ETDEWEB)

Safarzadeh, O., E-mail: O_Safarzadeh@sbu.ac.ir [Shahid Beheshti University, P.O. Box: 19839-63113, Tehran (Iran, Islamic Republic of); Khaki-Sedigh, A. [K. N. Toosi University of Technology, Tehran (Iran, Islamic Republic of); Shirani, A.S. [Shahid Beheshti University, P.O. Box: 19839-63113, Tehran (Iran, Islamic Republic of)

2011-09-15

Highlights: {yields} A robust water level controller for steam generators (SGs) is designed based on the Quantitative Feedback Theory. {yields} To design the controller, fairly accurate linear models are identified for the SG. {yields} The designed controller is verified using a developed novel global locally linear neuro-fuzzy model of the SG. {yields} Both of the linear and nonlinear models are based on the SG mathematical thermal-hydraulic model developed using the simulation computer code. {yields} The proposed method is easy to apply and guarantees desired closed loop performance. - Abstract: In this paper, a robust water level control system for the horizontal steam generator (SG) using the quantitative feedback theory (QFT) method is presented. To design a robust QFT controller for the nonlinear uncertain SG, control oriented linear models are identified. Then, the nonlinear system is modeled as an uncertain linear time invariant (LTI) system. The robust designed controller is applied to the nonlinear plant model. This nonlinear model is based on a locally linear neuro-fuzzy (LLNF) model. This model is trained using the locally linear model tree (LOLIMOT) algorithm. Finally, simulation results are employed to show the effectiveness of the designed QFT level controller. It is shown that it will ensure the entire designer's water level closed loop specifications.

Robust Market Launch Planning for a Multi- Echelon Pharmaceutical Supply Chain

DEFF Research Database (Denmark)

Hansen, Klaus Reinholdt Nyhuus; Grunow, Martin; Gani, Rafiqul

2011-01-01

launching activities after the drug has been approved. In this paper, we present a recourse-based stochastic model, which allows for time phasing the market entries to balance the fluctuating demand with the fixed and periodic production of the active pharmaceutical ingredient. The two major risk elements...... during launch are forecasting inaccuracy and the risk of a required label change from local regulatory authorities. Robust solutions are found by implementing the Robust Optimization framework....

UNIX-based operating systems robustness evaluation

Science.gov (United States)

Chang, Yu-Ming

1996-01-01

Robust operating systems are required for reliable computing. Techniques for robustness evaluation of operating systems not only enhance the understanding of the reliability of computer systems, but also provide valuable feed- back to system designers. This thesis presents results from robustness evaluation experiments on five UNIX-based operating systems, which include Digital Equipment's OSF/l, Hewlett Packard's HP-UX, Sun Microsystems' Solaris and SunOS, and Silicon Graphics' IRIX. Three sets of experiments were performed. The methodology for evaluation tested (1) the exception handling mechanism, (2) system resource management, and (3) system capacity under high workload stress. An exception generator was used to evaluate the exception handling mechanism of the operating systems. Results included exit status of the exception generator and the system state. Resource management techniques used by individual operating systems were tested using programs designed to usurp system resources such as physical memory and process slots. Finally, the workload stress testing evaluated the effect of the workload on system performance by running a synthetic workload and recording the response time of local and remote user requests. Moderate to severe performance degradations were observed on the systems under stress.

Local Political Culture and Use of Local Media: Is There a Relationship?

DEFF Research Database (Denmark)

Hoff, Jens Villiam

this model also turned out to be quite apt in explaining variation in local media use, the citizen role model was at least as good as this model in explaining these variations. Thus, our model of the four citizen roles/four different local cultures seems to be very robust when it comes to explaining...

Image segmentation-based robust feature extraction for color image watermarking

Science.gov (United States)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

Competition improves robustness against loss of information

Directory of Open Access Journals (Sweden)

Arash eKermani Kolankeh

2015-03-01

Full Text Available A substantial number of works aimed at modeling the receptive field properties of the primary visual cortex (V1. Their evaluation criterion is usually the similarity of the model response properties to the recorded responses from biological organisms. However, as several algorithms were able to demonstrate some degree of similarity to biological data based on the existing criteria, we focus on the robustness against loss of information in the form of occlusions as an additional constraint for better understanding the algorithmic level of early vision in the brain. We try to investigate the influence of competition mechanisms on the robustness. Therefore, we compared four methods employing different competition mechanisms, namely, independent component analysis, non-negative matrix factorization with sparseness constraint, predictive coding/biased competition, and a Hebbian neural network with lateral inhibitory connections. Each of those methods is known to be capable of developing receptive fields comparable to those of V1 simple-cells. Since measuring the robustness of methods having simple-cell like receptive fields against occlusion is difficult, we measure the robustness using the classification accuracy on the MNIST hand written digit dataset. For this we trained all methods on the training set of the MNIST hand written digits dataset and tested them on a MNIST test set with different levels of occlusions. We observe that methods which employ competitive mechanisms have higher robustness against loss of information. Also the kind of the competition mechanisms plays an important role in robustness. Global feedback inhibition as employed in predictive coding/biased competition has an advantage compared to local lateral inhibition learned by an anti-Hebb rule.

Analysis of the robustness of network-based disease-gene prioritization methods reveals redundancy in the human interactome and functional diversity of disease-genes.

Directory of Open Access Journals (Sweden)

Emre Guney

Full Text Available Complex biological systems usually pose a trade-off between robustness and fragility where a small number of perturbations can substantially disrupt the system. Although biological systems are robust against changes in many external and internal conditions, even a single mutation can perturb the system substantially, giving rise to a pathophenotype. Recent advances in identifying and analyzing the sequential variations beneath human disorders help to comprehend a systemic view of the mechanisms underlying various disease phenotypes. Network-based disease-gene prioritization methods rank the relevance of genes in a disease under the hypothesis that genes whose proteins interact with each other tend to exhibit similar phenotypes. In this study, we have tested the robustness of several network-based disease-gene prioritization methods with respect to the perturbations of the system using various disease phenotypes from the Online Mendelian Inheritance in Man database. These perturbations have been introduced either in the protein-protein interaction network or in the set of known disease-gene associations. As the network-based disease-gene prioritization methods are based on the connectivity between known disease-gene associations, we have further used these methods to categorize the pathophenotypes with respect to the recoverability of hidden disease-genes. Our results have suggested that, in general, disease-genes are connected through multiple paths in the human interactome. Moreover, even when these paths are disturbed, network-based prioritization can reveal hidden disease-gene associations in some pathophenotypes such as breast cancer, cardiomyopathy, diabetes, leukemia, parkinson disease and obesity to a greater extend compared to the rest of the pathophenotypes tested in this study. Gene Ontology (GO analysis highlighted the role of functional diversity for such diseases.

Perceptual Robust Design

DEFF Research Database (Denmark)

Pedersen, Søren Nygaard

The research presented in this PhD thesis has focused on a perceptual approach to robust design. The results of the research and the original contribution to knowledge is a preliminary framework for understanding, positioning, and applying perceptual robust design. Product quality is a topic...... been presented. Therefore, this study set out to contribute to the understanding and application of perceptual robust design. To achieve this, a state-of-the-art and current practice review was performed. From the review two main research problems were identified. Firstly, a lack of tools...... for perceptual robustness was found to overlap with the optimum for functional robustness and at most approximately 2.2% out of the 14.74% could be ascribed solely to the perceptual robustness optimisation. In conclusion, the thesis have offered a new perspective on robust design by merging robust design...

ER stress-induced protein, VIGG, disturbs plant cation homeostasis, which is correlated with growth retardation and robustness to ER stress

International Nuclear Information System (INIS)

Katoh, Hironori; Fujita, Keiko; Takuhara, Yuki; Ogawa, Atsushi; Suzuki, Shunji

2011-01-01

Highlights: → VIGG is an ER stress-induced protein in plant. → We examine the characteristics of VIGG-overexpressing Arabidopsis plants. → VIGG-overexpressing plants reveal growth retardation and robustness to ER stress. → VIGG disturbs cation homeostasis in plant. -- Abstract: VIGG is a putative endoplasmic reticulum (ER) resident protein induced by virus infection and ER stress, and is correlated with fruit quality in grapevine. The present study was undertaken to determine the biological function of VIGG in grapevine. Experiments using fluorescent protein-VIGG fusion protein demonstrated that VIGG is localized in ER and the ER targeting sequence is in the N-terminus. The overexpression of VIGG in Arabidopsis plant led to growth retardation. The rosette leaves of VIGG-overexpressing plants were smaller than those of the control plants and rolled at 42 days after seeding. VIGG-overexpressing plants revealed robustness to ER stress as well as the low expression of ER stress marker proteins, such as the luminal binding proteins. These characteristics of VIGG-overexpressing plants were supported by a microarray experiment that demonstrated the disruption of genes related to ER stress response and flowering, as well as cation mobility, in the plants. Finally, cation homeostasis in the plants was disturbed by the overexpression of VIGG. Taken together, these results suggest that VIGG may disturb cation homeostasis in plant, which is correlated with the robustness to ER stress and growth retardation.

ER stress-induced protein, VIGG, disturbs plant cation homeostasis, which is correlated with growth retardation and robustness to ER stress

Energy Technology Data Exchange (ETDEWEB)

Katoh, Hironori; Fujita, Keiko; Takuhara, Yuki [Laboratory of Fruit Genetic Engineering, The Institute of Enology and Viticulture, University of Yamanashi, Kofu, Yamanashi 400-0005 (Japan); Ogawa, Atsushi [Department of Biological Production, Akita Prefectural University, Shimosinjyou-nakano 241-438, Akita 010-0195 (Japan); Suzuki, Shunji, E-mail: suzukis@yamanashi.ac.jp [Laboratory of Fruit Genetic Engineering, The Institute of Enology and Viticulture, University of Yamanashi, Kofu, Yamanashi 400-0005 (Japan)

2011-02-18

Highlights: {yields} VIGG is an ER stress-induced protein in plant. {yields} We examine the characteristics of VIGG-overexpressing Arabidopsis plants. {yields} VIGG-overexpressing plants reveal growth retardation and robustness to ER stress. {yields} VIGG disturbs cation homeostasis in plant. -- Abstract: VIGG is a putative endoplasmic reticulum (ER) resident protein induced by virus infection and ER stress, and is correlated with fruit quality in grapevine. The present study was undertaken to determine the biological function of VIGG in grapevine. Experiments using fluorescent protein-VIGG fusion protein demonstrated that VIGG is localized in ER and the ER targeting sequence is in the N-terminus. The overexpression of VIGG in Arabidopsis plant led to growth retardation. The rosette leaves of VIGG-overexpressing plants were smaller than those of the control plants and rolled at 42 days after seeding. VIGG-overexpressing plants revealed robustness to ER stress as well as the low expression of ER stress marker proteins, such as the luminal binding proteins. These characteristics of VIGG-overexpressing plants were supported by a microarray experiment that demonstrated the disruption of genes related to ER stress response and flowering, as well as cation mobility, in the plants. Finally, cation homeostasis in the plants was disturbed by the overexpression of VIGG. Taken together, these results suggest that VIGG may disturb cation homeostasis in plant, which is correlated with the robustness to ER stress and growth retardation.

Superlinearly scalable noise robustness of redundant coupled dynamical systems.

Science.gov (United States)

Kohar, Vivek; Kia, Behnam; Lindner, John F; Ditto, William L

2016-03-01

We illustrate through theory and numerical simulations that redundant coupled dynamical systems can be extremely robust against local noise in comparison to uncoupled dynamical systems evolving in the same noisy environment. Previous studies have shown that the noise robustness of redundant coupled dynamical systems is linearly scalable and deviations due to noise can be minimized by increasing the number of coupled units. Here, we demonstrate that the noise robustness can actually be scaled superlinearly if some conditions are met and very high noise robustness can be realized with very few coupled units. We discuss these conditions and show that this superlinear scalability depends on the nonlinearity of the individual dynamical units. The phenomenon is demonstrated in discrete as well as continuous dynamical systems. This superlinear scalability not only provides us an opportunity to exploit the nonlinearity of physical systems without being bogged down by noise but may also help us in understanding the functional role of coupled redundancy found in many biological systems. Moreover, engineers can exploit superlinear noise suppression by starting a coupled system near (not necessarily at) the appropriate initial condition.

Robustness of pinning a general complex dynamical network

International Nuclear Information System (INIS)

Wang Lei; Sun Youxian

2010-01-01

This Letter studies the robustness problem of pinning a general complex dynamical network toward an assigned synchronous evolution. Several synchronization criteria are presented to guarantee the convergence of the pinning process locally and globally by construction of Lyapunov functions. In particular, if a pinning strategy has been designed for synchronization of a given complex dynamical network, then no matter what uncertainties occur among the pinned nodes, synchronization can still be guaranteed through the pinning. The analytical results show that pinning control has a certain robustness against perturbations on network architecture: adding, deleting and changing the weights of edges. Numerical simulations illustrated by scale-free complex networks verify the theoretical results above-acquired.

Fourier decomposition of spatial localization errors reveals an idiotropic dominance of an internal model of gravity.

Science.gov (United States)

De Sá Teixeira, Nuno Alexandre

2014-12-01

Given its conspicuous nature, gravity has been acknowledged by several research lines as a prime factor in structuring the spatial perception of one's environment. One such line of enquiry has focused on errors in spatial localization aimed at the vanishing location of moving objects - it has been systematically reported that humans mislocalize spatial positions forward, in the direction of motion (representational momentum) and downward in the direction of gravity (representational gravity). Moreover, spatial localization errors were found to evolve dynamically with time in a pattern congruent with an anticipated trajectory (representational trajectory). The present study attempts to ascertain the degree to which vestibular information plays a role in these phenomena. Human observers performed a spatial localization task while tilted to varying degrees and referring to the vanishing locations of targets moving along several directions. A Fourier decomposition of the obtained spatial localization errors revealed that although spatial errors were increased "downward" mainly along the body's longitudinal axis (idiotropic dominance), the degree of misalignment between the latter and physical gravity modulated the time course of the localization responses. This pattern is surmised to reflect increased uncertainty about the internal model when faced with conflicting cues regarding the perceived "downward" direction.

Optic disk localization by a robust fusion method

Science.gov (United States)

Zhang, Jielin; Yin, Fengshou; Wong, Damon W. K.; Liu, Jiang; Baskaran, Mani; Cheng, Ching-Yu; Wong, Tien Yin

2013-02-01

The optic disk localization plays an important role in developing computer-aided diagnosis (CAD) systems for ocular diseases such as glaucoma, diabetic retinopathy and age-related macula degeneration. In this paper, we propose an intelligent fusion of methods for the localization of the optic disk in retinal fundus images. Three different approaches are developed to detect the location of the optic disk separately. The first method is the maximum vessel crossing method, which finds the region with the most number of blood vessel crossing points. The second one is the multichannel thresholding method, targeting the area with the highest intensity. The final method searches the vertical and horizontal region-of-interest separately on the basis of blood vessel structure and neighborhood entropy profile. Finally, these three methods are combined using an intelligent fusion method to improve the overall accuracy. The proposed algorithm was tested on the STARE database and the ORIGAlight database, each consisting of images with various pathologies. The preliminary result on the STARE database can achieve 81.5%, while a higher result of 99% can be obtained for the ORIGAlight database. The proposed method outperforms each individual approach and state-of-the-art method which utilizes an intensity-based approach. The result demonstrates a high potential for this method to be used in retinal CAD systems.

The analysis of image feature robustness using cometcloud

Directory of Open Access Journals (Sweden)

Xin Qi

2012-01-01

Full Text Available The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval.

Sparse alignment for robust tensor learning.

Science.gov (United States)

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.

Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae.

Science.gov (United States)

Jarnuczak, Andrew F; Eyers, Claire E; Schwartz, Jean-Marc; Grant, Christopher M; Hubbard, Simon J

2015-09-01

Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC-based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs. © 2015 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Decentralized formation of random regular graphs for robust multi-agent networks

KAUST Repository

Yazicioglu, A. Yasin; Egerstedt, Magnus; Shamma, Jeff S.

2014-01-01

systems. One family of robust graphs is the random regular graphs. In this paper, we present a locally applicable reconfiguration scheme to build random regular graphs through self-organization. For any connected initial graph, the proposed scheme

Robust Image Analysis of Faces for Genetic Applications

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2010-01-01

Roč. 6, č. 2 (2010), s. 95-102 ISSN 1801-5603 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : object localization * template matching * eye or mouth detection * robust correlation analysis * image denoising Subject RIV: BB - Applied Statistics, Operational Research http://www.ejbi.cz/articles/201012/47/1.html

Plug and Play Robust Distributed Control with Ellipsoidal Parametric Uncertainty System

Directory of Open Access Journals (Sweden)

Hong Wang-jian

2016-01-01

Full Text Available We consider a continuous linear time invariant system with ellipsoidal parametric uncertainty structured into subsystems. Since the design of a local controller uses only information on a subsystem and its neighbours, we combine the plug and play idea and robust distributed control to propose one distributed control strategy for linear system with ellipsoidal parametric uncertainty. Firstly for linear system with ellipsoidal parametric uncertainty, a necessary and sufficient condition for robust state feedback control is proposed by means of linear matrix inequality. If this necessary and sufficient condition is satisfied, this robust state feedback gain matrix can be easily derived to guarantee robust stability and prescribed closed loop performance. Secondly the plug and play idea is introduced in the design process. Finally by one example of aircraft flutter model parameter identification, the efficiency of the proposed control strategy can be easily realized.

Robust Forecasting for Energy Efficiency of Wireless Multimedia Sensor Networks.

Science.gov (United States)

Wang, Xue; Ma, Jun-Jie; Ding, Liang; Bi, Dao-Wei

2007-11-15

An important criterion of wireless sensor network is the energy efficiency inspecified applications. In this wireless multimedia sensor network, the observations arederived from acoustic sensors. Focused on the energy problem of target tracking, this paperproposes a robust forecasting method to enhance the energy efficiency of wirelessmultimedia sensor networks. Target motion information is acquired by acoustic sensornodes while a distributed network with honeycomb configuration is constructed. Thereby,target localization is performed by multiple sensor nodes collaboratively through acousticsignal processing. A novel method, combining autoregressive moving average (ARMA)model and radial basis function networks (RBFNs), is exploited to perform robust targetposition forecasting during target tracking. Then sensor nodes around the target areawakened according to the forecasted target position. With committee decision of sensornodes, target localization is performed in a distributed manner and the uncertainty ofdetection is reduced. Moreover, a sensor-to-observer routing approach of the honeycombmesh network is investigated to solve the data reporting considering the residual energy ofsensor nodes. Target localization and forecasting are implemented in experiments.Meanwhile, sensor node awakening and dynamic routing are evaluated. Experimentalresults verify that energy efficiency of wireless multimedia sensor network is enhanced bythe proposed target tracking method.

A morphing strategy to couple non-local to local continuum mechanics

KAUST Repository

Lubineau, Gilles

2012-06-01

A method for coupling non-local continuum models with long-range central forces to local continuum models is proposed. First, a single unified model that encompasses both local and non-local continuum representations is introduced. This model can be purely non-local, purely local or a hybrid depending on the constitutive parameters. Then, the coupling between the non-local and local descriptions is performed through a transition (morphing) affecting only the constitutive parameters. An important feature is the definition of the morphing functions, which relies on energy equivalence. This approach is useful in large-scale modeling of materials that exhibit strong non-local effects. The computational cost can be reduced while maintaining a reasonable level of accuracy. Efficiency, robustness and basic properties of the approach are discussed using one- and two-dimensional examples. © 2012 Elsevier Ltd.

A morphing strategy to couple non-local to local continuum mechanics

KAUST Repository

Lubineau, Gilles; Azdoud, Yan; Han, Fei; Rey, Christian C.; Askari, Abe H.

2012-01-01

A method for coupling non-local continuum models with long-range central forces to local continuum models is proposed. First, a single unified model that encompasses both local and non-local continuum representations is introduced. This model can be purely non-local, purely local or a hybrid depending on the constitutive parameters. Then, the coupling between the non-local and local descriptions is performed through a transition (morphing) affecting only the constitutive parameters. An important feature is the definition of the morphing functions, which relies on energy equivalence. This approach is useful in large-scale modeling of materials that exhibit strong non-local effects. The computational cost can be reduced while maintaining a reasonable level of accuracy. Efficiency, robustness and basic properties of the approach are discussed using one- and two-dimensional examples. © 2012 Elsevier Ltd.

Using Spread Spectrum Transform for Fast and Robust Simultaneous Measurement in Active Sensors with Multiple Emitters

DEFF Research Database (Denmark)

Harbo, Anders La-Cour; Stoustrup, Jakob

2002-01-01

We present a signal processing algorithm for making robust and simultaneous measurements in an active sensor, which has one or more emitters and a receiver, and which employs some sort of signal processing hardware. Robustness means low sensitivity to time and frequency localized disturbances......-cost active sensors....

Consistent robustness analysis (CRA) identifies biologically relevant properties of regulatory network models.

Science.gov (United States)

Saithong, Treenut; Painter, Kevin J; Millar, Andrew J

2010-12-16

A number of studies have previously demonstrated that "goodness of fit" is insufficient in reliably classifying the credibility of a biological model. Robustness and/or sensitivity analysis is commonly employed as a secondary method for evaluating the suitability of a particular model. The results of such analyses invariably depend on the particular parameter set tested, yet many parameter values for biological models are uncertain. Here, we propose a novel robustness analysis that aims to determine the "common robustness" of the model with multiple, biologically plausible parameter sets, rather than the local robustness for a particular parameter set. Our method is applied to two published models of the Arabidopsis circadian clock (the one-loop [1] and two-loop [2] models). The results reinforce current findings suggesting the greater reliability of the two-loop model and pinpoint the crucial role of TOC1 in the circadian network. Consistent Robustness Analysis can indicate both the relative plausibility of different models and also the critical components and processes controlling each model.

Engineering Amorphous Systems, Using Global-to-Local Compilation

Science.gov (United States)

Nagpal, Radhika

Emerging technologies are making it possible to assemble systems that incorporate myriad of information-processing units at almost no cost: smart materials, selfassembling structures, vast sensor networks, pervasive computing. How does one engineer robust and prespecified global behavior from the local interactions of immense numbers of unreliable parts? We discuss organizing principles and programming methodologies that have emerged from Amorphous Computing research, that allow us to compile a specification of global behavior into a robust program for local behavior.

Robust multivariate analysis

CERN Document Server

J Olive, David

2017-01-01

This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given.  The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory.   The robust techniques  are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis.  A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...

A Robust Wireless Sensor Network Localization Algorithm in Mixed LOS/NLOS Scenario.

Science.gov (United States)

Li, Bing; Cui, Wei; Wang, Bin

2015-09-16

Localization algorithms based on received signal strength indication (RSSI) are widely used in the field of target localization due to its advantages of convenient application and independent from hardware devices. Unfortunately, the RSSI values are susceptible to fluctuate under the influence of non-line-of-sight (NLOS) in indoor space. Existing algorithms often produce unreliable estimated distances, leading to low accuracy and low effectiveness in indoor target localization. Moreover, these approaches require extra prior knowledge about the propagation model. As such, we focus on the problem of localization in mixed LOS/NLOS scenario and propose a novel localization algorithm: Gaussian mixed model based non-metric Multidimensional (GMDS). In GMDS, the RSSI is estimated using a Gaussian mixed model (GMM). The dissimilarity matrix is built to generate relative coordinates of nodes by a multi-dimensional scaling (MDS) approach. Finally, based on the anchor nodes' actual coordinates and target's relative coordinates, the target's actual coordinates can be computed via coordinate transformation. Our algorithm could perform localization estimation well without being provided with prior knowledge. The experimental verification shows that GMDS effectively reduces NLOS error and is of higher accuracy in indoor mixed LOS/NLOS localization and still remains effective when we extend single NLOS to multiple NLOS.

Robustness of Structures

DEFF Research Database (Denmark)

Faber, Michael Havbro; Vrouwenvelder, A.C.W.M.; Sørensen, John Dalsgaard

2011-01-01

In 2005, the Joint Committee on Structural Safety (JCSS) together with Working Commission (WC) 1 of the International Association of Bridge and Structural Engineering (IABSE) organized a workshop on robustness of structures. Two important decisions resulted from this workshop, namely...... ‘COST TU0601: Robustness of Structures’ was initiated in February 2007, aiming to provide a platform for exchanging and promoting research in the area of structural robustness and to provide a basic framework, together with methods, strategies and guidelines enhancing robustness of structures...... the development of a joint European project on structural robustness under the COST (European Cooperation in Science and Technology) programme and the decision to develop a more elaborate document on structural robustness in collaboration between experts from the JCSS and the IABSE. Accordingly, a project titled...

Robust network topologies for generating switch-like cellular responses.

Directory of Open Access Journals (Sweden)

Najaf A Shah

2011-06-01

Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.

Problems of Revenue Generation in Local Government ...

African Journals Online (AJOL)

user

2013-07-07

Jul 7, 2013 ... discernible from budget deficits and paucity of funds for robust economic growth and .... a) Local rates and commission paid to Local Government for assisting in the collection of some ..... Lake Hotel, Enugu. Uhunmwuangho ...

Infrared and visible images registration with adaptable local-global feature integration for rail inspection

Science.gov (United States)

Tang, Chaoqing; Tian, Gui Yun; Chen, Xiaotian; Wu, Jianbo; Li, Kongjing; Meng, Hongying

2017-12-01

Active thermography provides infrared images that contain sub-surface defect information, while visible images only reveal surface information. Mapping infrared information to visible images offers more comprehensive visualization for decision-making in rail inspection. However, the common information for registration is limited due to different modalities in both local and global level. For example, rail track which has low temperature contrast reveals rich details in visible images, but turns blurry in the infrared counterparts. This paper proposes a registration algorithm called Edge-Guided Speeded-Up-Robust-Features (EG-SURF) to address this issue. Rather than sequentially integrating local and global information in matching stage which suffered from buckets effect, this algorithm adaptively integrates local and global information into a descriptor to gather more common information before matching. This adaptability consists of two facets, an adaptable weighting factor between local and global information, and an adaptable main direction accuracy. The local information is extracted using SURF while the global information is represented by shape context from edges. Meanwhile, in shape context generation process, edges are weighted according to local scale and decomposed into bins using a vector decomposition manner to provide more accurate descriptor. The proposed algorithm is qualitatively and quantitatively validated using eddy current pulsed thermography scene in the experiments. In comparison with other algorithms, better performance has been achieved.

Robustness Area Technique Developing Guidelines for Power System Restoration

Directory of Open Access Journals (Sweden)

Paulo Murinelli Pesoti

2017-01-01

Full Text Available This paper proposes a novel energy based technique called the Robustness Area (RA technique that measures power system robustness levels, as a helper for planning Power System Restorations (PSRs. The motivation is on account of the latest blackouts in Brazil, where the local Independent System Operator (ISO encountered difficulties related to circuit disconnections during the restoration. The technique identifies vulnerable and robust buses, pointing out system areas that should be firstly reinforced during PSR, in order to enhance system stability. A Brazilian power system restoration area is used to compare the guidelines adopted by the ISO with a more suitable new plan indicated by the RA tool. Active power and reactive power load margin and standing phase angle show the method efficiency as a result of a well balanced system configuration, enhancing the restoration performance. Time domain simulations for loop closures and severe events also show the positive impact that the proposed tool brings to PSRs.

Different localization patterns of anthocyanin species in the pericarp of black rice revealed by imaging mass spectrometry.

Directory of Open Access Journals (Sweden)

Yukihiro Yoshimura

Full Text Available Black rice (Oryza sativa L. Japonica contains high levels of anthocyanins in the pericarp and is considered an effective health-promoting food. Several studies have identified the molecular species of anthocyanins in black rice, but information about the localization of each anthocyanin species is limited because methodologies for investigating the localization such as determining specific antibodies to anthocyanin, have not yet been developed Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS is a suitable tool for investigating the localization of metabolites. In this study, we identified 7 species of anthocyanin monoglycosides and 2 species of anthocyanin diglycosides in crude extracts from black rice by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS analysis. We also analyzed black rice sections by MALDI-IMS and found 2 additional species of anthocyanin pentosides and revealed different localization patterns of anthocyanin species composed of different sugar moieties. Anthocyanin species composed of a pentose moiety (cyanidin-3-O-pentoside and petunidin-3-O-pentoside were localized in the entire pericarp, whereas anthocyanin species composed of a hexose moiety (cyanidin-3-O-hexoside and peonidin-3-O-hexoside were focally localized in the dorsal pericarp. These results indicate that anthocyanin species composed of different sugar moieties exhibit different localization patterns in the pericarp of black rice. This is the first detailed investigation into the localization of molecular species of anthocyanins by MALDI-IMS.

Invertible chaotic fragile watermarking for robust image authentication

International Nuclear Information System (INIS)

Sidiropoulos, Panagiotis; Nikolaidis, Nikos; Pitas, Ioannis

2009-01-01

Fragile watermarking is a popular method for image authentication. In such schemes, a fragile signal that is sensitive to manipulations is embedded in the image, so that it becomes undetectable after any modification of the original work. Most algorithms focus either on the ability to retrieve the original work after watermark detection (invertibility) or on detecting which image parts have been altered (localization). Furthermore, the majority of fragile watermarking schemes suffer from robustness flaws. We propose a new technique that combines localization and invertibility. Moreover, watermark dependency on the original image and the non-linear watermark embedding procedure guarantees that no malicious attacks will manage to create information leaks.

Robust and efficient walking with spring-like legs

Energy Technology Data Exchange (ETDEWEB)

Rummel, J; Blum, Y; Seyfarth, A, E-mail: juergen.rummel@uni-jena.d, E-mail: andre.seyfarth@uni-jena.d [Lauflabor Locomotion Laboratory, University of Jena, Dornburger Strasse 23, 07743 Jena (Germany)

2010-12-15

The development of bipedal walking robots is inspired by human walking. A way of implementing walking could be performed by mimicking human leg dynamics. A fundamental model, representing human leg dynamics during walking and running, is the bipedal spring-mass model which is the basis for this paper. The aim of this study is the identification of leg parameters leading to a compromise between robustness and energy efficiency in walking. It is found that, compared to asymmetric walking, symmetric walking with flatter angles of attack reveals such a compromise. With increasing leg stiffness, energy efficiency increases continuously. However, robustness is the maximum at moderate leg stiffness and decreases slightly with increasing stiffness. Hence, an adjustable leg compliance would be preferred, which is adaptable to the environment. If the ground is even, a high leg stiffness leads to energy efficient walking. However, if external perturbations are expected, e.g. when the robot walks on uneven terrain, the leg should be softer and the angle of attack flatter. In the case of underactuated robots with constant physical springs, the leg stiffness should be larger than k-tilde = 14 in order to use the most robust gait. Soft legs, however, lack in both robustness and efficiency.

Robust and efficient walking with spring-like legs

International Nuclear Information System (INIS)

Rummel, J; Blum, Y; Seyfarth, A

2010-01-01

The development of bipedal walking robots is inspired by human walking. A way of implementing walking could be performed by mimicking human leg dynamics. A fundamental model, representing human leg dynamics during walking and running, is the bipedal spring-mass model which is the basis for this paper. The aim of this study is the identification of leg parameters leading to a compromise between robustness and energy efficiency in walking. It is found that, compared to asymmetric walking, symmetric walking with flatter angles of attack reveals such a compromise. With increasing leg stiffness, energy efficiency increases continuously. However, robustness is the maximum at moderate leg stiffness and decreases slightly with increasing stiffness. Hence, an adjustable leg compliance would be preferred, which is adaptable to the environment. If the ground is even, a high leg stiffness leads to energy efficient walking. However, if external perturbations are expected, e.g. when the robot walks on uneven terrain, the leg should be softer and the angle of attack flatter. In the case of underactuated robots with constant physical springs, the leg stiffness should be larger than k-tilde = 14 in order to use the most robust gait. Soft legs, however, lack in both robustness and efficiency.

High-Efficiency Colloidal Quantum Dot Photovoltaics via Robust Self-Assembled Monolayers

KAUST Repository

Kim, Gi-Hwan; Garcí a de Arquer, F. Pelayo; Yoon, Yung Jin; Lan, Xinzheng; Liu, Mengxia; Voznyy, Oleksandr; Yang, Zhenyu; Fan, Fengjia; Ip, Alexander H.; Kanjanaboos, Pongsakorn; Hoogland, Sjoerd; Kim, Jin Young; Sargent, Edward H.

2015-01-01

to voltage. With this goal in mind, self-assembled monolayers (SAMs) can be used to modify interface energy levels locally. However, to be effective SAMs must be made robust to treatment using the various solvents and ligands required for to fabricate high

Defining robustness protocols: a method to include and evaluate robustness in clinical plans

International Nuclear Information System (INIS)

McGowan, S E; Albertini, F; Lomax, A J; Thomas, S J

2015-01-01

We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties. (paper)

Defining robustness protocols: a method to include and evaluate robustness in clinical plans

Science.gov (United States)

McGowan, S. E.; Albertini, F.; Thomas, S. J.; Lomax, A. J.

2015-04-01

We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties.

Localization in smart dust sensor networks

NARCIS (Netherlands)

Kilic, Y.; Meijerink, Arjan; Bentum, Marinus Jan

2010-01-01

Our research goal is to design a robust localization system that offers good accuracy even in the harsh indoor and outdoor environments by handling problems in the physical layer. In this respect, localization based on ultra-wide band (UWB) technology with time-based ranging is a good candidate

On projection methods, convergence and robust formulations in topology optimization

DEFF Research Database (Denmark)

Wang, Fengwen; Lazarov, Boyan Stefanov; Sigmund, Ole

2011-01-01

alleviated using various projection methods. In this paper we show that simple projection methods do not ensure local mesh-convergence and propose a modified robust topology optimization formulation based on erosion, intermediate and dilation projections that ensures both global and local mesh-convergence.......Mesh convergence and manufacturability of topology optimized designs have previously mainly been assured using density or sensitivity based filtering techniques. The drawback of these techniques has been gray transition regions between solid and void parts, but this problem has recently been...

Color-SIFT model: a robust and an accurate shot boundary detection algorithm

Science.gov (United States)

Sharmila Kumari, M.; Shekar, B. H.

2010-02-01

In this paper, a new technique called color-SIFT model is devised for shot boundary detection. Unlike scale invariant feature transform model that uses only grayscale information and misses important visual information regarding color, here we have adopted different color planes to extract keypoints which are subsequently used to detect shot boundaries. The basic SIFT model has four stages namely scale-space peak selection, keypoint localization, orientation assignment and keypoint descriptor and all these four stages were employed to extract key descriptors in each color plane. The proposed model works on three different color planes and a fusion has been made to take a decision on number of keypoint matches for shot boundary identification and hence is different from the color global scale invariant feature transform that works on quantized images. In addition, the proposed algorithm possess invariance to linear transformation and robust to occlusion and noisy environment. Experiments have been conducted on the standard TRECVID video database to reveal the performance of the proposed model.

Robust Visual Tracking Using the Bidirectional Scale Estimation

Directory of Open Access Journals (Sweden)

An Zhiyong

2017-01-01

Full Text Available Object tracking with robust scale estimation is a challenging task in computer vision. This paper presents a novel tracking algorithm that learns the translation and scale filters with a complementary scheme. The translation filter is constructed using the ridge regression and multidimensional features. A robust scale filter is constructed by the bidirectional scale estimation, including the forward scale and backward scale. Firstly, we learn the scale filter using the forward tracking information. Then the forward scale and backward scale can be estimated using the respective scale filter. Secondly, a conservative strategy is adopted to compromise the forward and backward scales. Finally, the scale filter is updated based on the final scale estimation. It is effective to update scale filter since the stable scale estimation can improve the performance of scale filter. To reveal the effectiveness of our tracker, experiments are performed on 32 sequences with significant scale variation and on the benchmark dataset with 50 challenging videos. Our results show that the proposed tracker outperforms several state-of-the-art trackers in terms of robustness and accuracy.

Robustness of inflation to inhomogeneous initial conditions

Energy Technology Data Exchange (ETDEWEB)

Clough, Katy; Lim, Eugene A. [Theoretical Particle Physics and Cosmology Group, Physics Department, Kings College London, Strand, London WC2R 2LS (United Kingdom); DiNunno, Brandon S.; Fischler, Willy; Flauger, Raphael; Paban, Sonia, E-mail: katy.clough@kcl.ac.uk, E-mail: eugene.a.lim@gmail.com, E-mail: bsd86@physics.utexas.edu, E-mail: fischler@physics.utexas.edu, E-mail: flauger@physics.utexas.edu, E-mail: paban@physics.utexas.edu [Department of Physics, The University of Texas at Austin, Austin, TX, 78712 (United States)

2017-09-01

We consider the effects of inhomogeneous initial conditions in both the scalar field profile and the extrinsic curvature on different inflationary models. In particular, we compare the robustness of small field inflation to that of large field inflation, using numerical simulations with Einstein gravity in 3+1 dimensions. We find that small field inflation can fail in the presence of subdominant gradient energies, suggesting that it is much less robust to inhomogeneities than large field inflation, which withstands dominant gradient energies. However, we also show that small field inflation can be successful even if some regions of spacetime start out in the region of the potential that does not support inflation. In the large field case, we confirm previous results that inflation is robust if the inflaton occupies the inflationary part of the potential. Furthermore, we show that increasing initial scalar gradients will not form sufficiently massive inflation-ending black holes if the initial hypersurface is approximately flat. Finally, we consider the large field case with a varying extrinsic curvature K , such that some regions are initially collapsing. We find that this may again lead to local black holes, but overall the spacetime remains inflationary if the spacetime is open, which confirms previous theoretical studies.

Methods for robustness programming

NARCIS (Netherlands)

Olieman, N.J.

2008-01-01

Robustness of an object is defined as the probability that an object will have properties as required. Robustness Programming (RP) is a mathematical approach for Robustness estimation and Robustness optimisation. An example in the context of designing a food product, is finding the best composition

Robust design method and thermostatic experiment for multiple piezoelectric vibration absorber system

International Nuclear Information System (INIS)

Nambu, Yohsuke; Takashima, Toshihide; Inagaki, Akiya

2015-01-01

This paper examines the effects of connecting multiplexing shunt circuits composed of inductors and resistors to piezoelectric transducers so as to improve the robustness of a piezoelectric vibration absorber (PVA). PVAs are well known to be effective at suppressing the vibration of an adaptive structure; their weakness is low robustness to changes in the dynamic parameters of the system, including the main structure and the absorber. In the application to space structures, the temperature-dependency of capacitance of piezoelectric ceramics is the factor that causes performance reduction. To improve robustness to the temperature-dependency of the capacitance, this paper proposes a multiple-PVA system that is composed of distributed piezoelectric transducers and several shunt circuits. The optimization problems that determine both the frequencies and the damping ratios of the PVAs are multi-objective problems, which are solved using a real-coded genetic algorithm in this paper. A clamped aluminum beam with four groups of piezoelectric ceramics attached was considered in simulations and experiments. Numerical simulations revealed that the PVA systems designed using the proposed method had tolerance to changes in the capacitances. Furthermore, experiments using a thermostatic bath were conducted to reveal the effectiveness and robustness of the PVA systems. The maximum peaks of the transfer functions of the beam with the open circuit, the single-PVA system, the double-PVA system, and the quadruple-PVA system at 20 °C were 14.3 dB, −6.91 dB, −7.47 dB, and −8.51 dB, respectively. The experimental results also showed that the multiple-PVA system is more robust than a single PVA in a variable temperature environment from −10 °C to 50 °C. In conclusion, the use of multiple PVAs results in an effective, robust vibration control method for adaptive structures. (paper)

Histograms of Oriented 3D Gradients for Fully Automated Fetal Brain Localization and Robust Motion Correction in 3 T Magnetic Resonance Images.

Science.gov (United States)

Serag, Ahmed; Macnaught, Gillian; Denison, Fiona C; Reynolds, Rebecca M; Semple, Scott I; Boardman, James P

2017-01-01

Fetal brain magnetic resonance imaging (MRI) is a rapidly emerging diagnostic imaging tool. However, automated fetal brain localization is one of the biggest obstacles in expediting and fully automating large-scale fetal MRI processing. We propose a method for automatic localization of fetal brain in 3 T MRI when the images are acquired as a stack of 2D slices that are misaligned due to fetal motion. First, the Histogram of Oriented Gradients (HOG) feature descriptor is extended from 2D to 3D images. Then, a sliding window is used to assign a score to all possible windows in an image, depending on the likelihood of it containing a brain, and the window with the highest score is selected. In our evaluation experiments using a leave-one-out cross-validation strategy, we achieved 96% of complete brain localization using a database of 104 MRI scans at gestational ages between 34 and 38 weeks. We carried out comparisons against template matching and random forest based regression methods and the proposed method showed superior performance. We also showed the application of the proposed method in the optimization of fetal motion correction and how it is essential for the reconstruction process. The method is robust and does not rely on any prior knowledge of fetal brain development.

Histograms of Oriented 3D Gradients for Fully Automated Fetal Brain Localization and Robust Motion Correction in 3 T Magnetic Resonance Images

Directory of Open Access Journals (Sweden)

Ahmed Serag

2017-01-01

Full Text Available Fetal brain magnetic resonance imaging (MRI is a rapidly emerging diagnostic imaging tool. However, automated fetal brain localization is one of the biggest obstacles in expediting and fully automating large-scale fetal MRI processing. We propose a method for automatic localization of fetal brain in 3 T MRI when the images are acquired as a stack of 2D slices that are misaligned due to fetal motion. First, the Histogram of Oriented Gradients (HOG feature descriptor is extended from 2D to 3D images. Then, a sliding window is used to assign a score to all possible windows in an image, depending on the likelihood of it containing a brain, and the window with the highest score is selected. In our evaluation experiments using a leave-one-out cross-validation strategy, we achieved 96% of complete brain localization using a database of 104 MRI scans at gestational ages between 34 and 38 weeks. We carried out comparisons against template matching and random forest based regression methods and the proposed method showed superior performance. We also showed the application of the proposed method in the optimization of fetal motion correction and how it is essential for the reconstruction process. The method is robust and does not rely on any prior knowledge of fetal brain development.

SU-F-J-64: Comparison of Dosimetric Robustness Between Proton Therapy and IMRT Plans Following Tumor Regression for Locally Advanced Non-Small Cell Lung Cancer (NSCLC)

Energy Technology Data Exchange (ETDEWEB)

Teng, C; Ainsley, C; Teo, B; Burgdorf, B; Berman, A; Levin, W; Xiao, Y; Lin, L; Simone, C; Solberg, T [University of Pennsylvania, Philadelphia, PA (United States); Janssens, G [IBA, Louvain-la-Neuve (Belgium)

2016-06-15

Purpose: In the light of tumor regression and normal tissue changes, dose distributions can deviate undesirably from what was planned. As a consequence, replanning is sometimes necessary during treatment to ensure continued tumor coverage or to avoid overdosing organs at risk (OARs). Proton plans are generally thought to be less robust than photon plans because of the proton beam’s higher sensitivity to changes in tissue composition, suggesting also a higher likely replanning rate due to tumor regression. The purpose of this study is to compare dosimetric deviations between forward-calculated double scattering (DS) proton plans with IMRT plans upon tumor regression, and assesses their impact on clinical replanning decisions. Methods: Ten consecutive locally advanced NSCLC patients whose tumors shrank > 50% in volume and who received four or more CT scans during radiotherapy were analyzed. All the patients received proton radiotherapy (6660 cGy, 180 cGy/fx). Dosimetric robustness during therapy was characterized by changes in the planning objective metrics as well as by point-by-point root-mean-squared differences for the entire PTV, ITV, and OARs (heart, cord, esophagus, brachial plexus and lungs) DVHs. Results: Sixty-four pairs of DVHs were reviewed by three clinicians, who requested a replanning rate of 16.7% and 18.6% for DS and IMRT plans, respectively, with a high agreement between providers. Robustness of clinical indicators was found to depend on the beam orientation and dose level on the DVH curve. Proton dose increased most in OARs distal to the PTV along the beam path, but these changes were primarily in the mid to low dose levels. In contrast, the variation in IMRT plans occurred primarily in the high dose region. Conclusion: Robustness of clinical indicators depends where on the DVH curves comparisons are made. Similar replanning rates were observed for DS and IMRT plans upon large tumor regression.

Robustness of Structural Systems

DEFF Research Database (Denmark)

Canisius, T.D.G.; Sørensen, John Dalsgaard; Baker, J.W.

2007-01-01

The importance of robustness as a property of structural systems has been recognised following several structural failures, such as that at Ronan Point in 1968,where the consequenceswere deemed unacceptable relative to the initiating damage. A variety of research efforts in the past decades have...... attempted to quantify aspects of robustness such as redundancy and identify design principles that can improve robustness. This paper outlines the progress of recent work by the Joint Committee on Structural Safety (JCSS) to develop comprehensive guidance on assessing and providing robustness in structural...... systems. Guidance is provided regarding the assessment of robustness in a framework that considers potential hazards to the system, vulnerability of system components, and failure consequences. Several proposed methods for quantifying robustness are reviewed, and guidelines for robust design...

Robustness in laying hens

NARCIS (Netherlands)

Star, L.

2008-01-01

The aim of the project ‘The genetics of robustness in laying hens’ was to investigate nature and regulation of robustness in laying hens under sub-optimal conditions and the possibility to increase robustness by using animal breeding without loss of production. At the start of the project, a robust

Robust object tracking combining color and scale invariant features

Science.gov (United States)

Zhang, Shengping; Yao, Hongxun; Gao, Peipei

2010-07-01

Object tracking plays a very important role in many computer vision applications. However its performance will significantly deteriorate due to some challenges in complex scene, such as pose and illumination changes, clustering background and so on. In this paper, we propose a robust object tracking algorithm which exploits both global color and local scale invariant (SIFT) features in a particle filter framework. Due to the expensive computation cost of SIFT features, the proposed tracker adopts a speed-up variation of SIFT, SURF, to extract local features. Specially, the proposed method first finds matching points between the target model and target candidate, than the weight of the corresponding particle based on scale invariant features is computed as the the proportion of matching points of that particle to matching points of all particles, finally the weight of the particle is obtained by combining weights of color and SURF features with a probabilistic way. The experimental results on a variety of challenging videos verify that the proposed method is robust to pose and illumination changes and is significantly superior to the standard particle filter tracker and the mean shift tracker.

Robust short-term memory without synaptic learning.

Directory of Open Access Journals (Sweden)

Samuel Johnson

Full Text Available Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds. The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

Robust short-term memory without synaptic learning.

Science.gov (United States)

Johnson, Samuel; Marro, J; Torres, Joaquín J

2013-01-01

Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

Robust Short-Term Memory without Synaptic Learning

Science.gov (United States)

Johnson, Samuel; Marro, J.; Torres, Joaquín J.

2013-01-01

Short-term memory in the brain cannot in general be explained the way long-term memory can – as a gradual modification of synaptic weights – since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings. PMID:23349664

Non-local means denoising of dynamic PET images.

Directory of Open Access Journals (Sweden)

Joyita Dutta

Full Text Available Dynamic positron emission tomography (PET, which reveals information about both the spatial distribution and temporal kinetics of a radiotracer, enables quantitative interpretation of PET data. Model-based interpretation of dynamic PET images by means of parametric fitting, however, is often a challenging task due to high levels of noise, thus necessitating a denoising step. The objective of this paper is to develop and characterize a denoising framework for dynamic PET based on non-local means (NLM.NLM denoising computes weighted averages of voxel intensities assigning larger weights to voxels that are similar to a given voxel in terms of their local neighborhoods or patches. We introduce three key modifications to tailor the original NLM framework to dynamic PET. Firstly, we derive similarities from less noisy later time points in a typical PET acquisition to denoise the entire time series. Secondly, we use spatiotemporal patches for robust similarity computation. Finally, we use a spatially varying smoothing parameter based on a local variance approximation over each spatiotemporal patch.To assess the performance of our denoising technique, we performed a realistic simulation on a dynamic digital phantom based on the Digimouse atlas. For experimental validation, we denoised [Formula: see text] PET images from a mouse study and a hepatocellular carcinoma patient study. We compared the performance of NLM denoising with four other denoising approaches - Gaussian filtering, PCA, HYPR, and conventional NLM based on spatial patches.The simulation study revealed significant improvement in bias-variance performance achieved using our NLM technique relative to all the other methods. The experimental data analysis revealed that our technique leads to clear improvement in contrast-to-noise ratio in Patlak parametric images generated from denoised preclinical and clinical dynamic images, indicating its ability to preserve image contrast and high

Non-local means denoising of dynamic PET images.

Science.gov (United States)

Dutta, Joyita; Leahy, Richard M; Li, Quanzheng

2013-01-01

Dynamic positron emission tomography (PET), which reveals information about both the spatial distribution and temporal kinetics of a radiotracer, enables quantitative interpretation of PET data. Model-based interpretation of dynamic PET images by means of parametric fitting, however, is often a challenging task due to high levels of noise, thus necessitating a denoising step. The objective of this paper is to develop and characterize a denoising framework for dynamic PET based on non-local means (NLM). NLM denoising computes weighted averages of voxel intensities assigning larger weights to voxels that are similar to a given voxel in terms of their local neighborhoods or patches. We introduce three key modifications to tailor the original NLM framework to dynamic PET. Firstly, we derive similarities from less noisy later time points in a typical PET acquisition to denoise the entire time series. Secondly, we use spatiotemporal patches for robust similarity computation. Finally, we use a spatially varying smoothing parameter based on a local variance approximation over each spatiotemporal patch. To assess the performance of our denoising technique, we performed a realistic simulation on a dynamic digital phantom based on the Digimouse atlas. For experimental validation, we denoised [Formula: see text] PET images from a mouse study and a hepatocellular carcinoma patient study. We compared the performance of NLM denoising with four other denoising approaches - Gaussian filtering, PCA, HYPR, and conventional NLM based on spatial patches. The simulation study revealed significant improvement in bias-variance performance achieved using our NLM technique relative to all the other methods. The experimental data analysis revealed that our technique leads to clear improvement in contrast-to-noise ratio in Patlak parametric images generated from denoised preclinical and clinical dynamic images, indicating its ability to preserve image contrast and high intensity details while

A probabilistic model for robust acoustic localization based on an auditory front-end

NARCIS (Netherlands)

May, T.; Par, van de S.L.J.D.E.; Kohlrausch, A.G.; Boone, M.

2009-01-01

Although extensive research has been done in the field of localization, the degrading effect of reverberation and the presence of multiple sources on localization performance has remained a major issue. The classical approach to localize an acoustic source in the horizontal space is to search for

Robust, Efficient Depth Reconstruction With Hierarchical Confidence-Based Matching.

Science.gov (United States)

Sun, Li; Chen, Ke; Song, Mingli; Tao, Dacheng; Chen, Gang; Chen, Chun

2017-07-01

In recent years, taking photos and capturing videos with mobile devices have become increasingly popular. Emerging applications based on the depth reconstruction technique have been developed, such as Google lens blur. However, depth reconstruction is difficult due to occlusions, non-diffuse surfaces, repetitive patterns, and textureless surfaces, and it has become more difficult due to the unstable image quality and uncontrolled scene condition in the mobile setting. In this paper, we present a novel hierarchical framework with multi-view confidence-based matching for robust, efficient depth reconstruction in uncontrolled scenes. Particularly, the proposed framework combines local cost aggregation with global cost optimization in a complementary manner that increases efficiency and accuracy. A depth map is efficiently obtained in a coarse-to-fine manner by using an image pyramid. Moreover, confidence maps are computed to robustly fuse multi-view matching cues, and to constrain the stereo matching on a finer scale. The proposed framework has been evaluated with challenging indoor and outdoor scenes, and has achieved robust and efficient depth reconstruction.

A Robust Shape Reconstruction Method for Facial Feature Point Detection

Directory of Open Access Journals (Sweden)

Shuqiu Tan

2017-01-01

Full Text Available Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed and applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression and gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction method for the face alignment problems. Instead of a direct regression between the feature space and the shape space, the concept of shape increment reconstruction is introduced. Moreover, a set of coupled overcomplete dictionaries termed the shape increment dictionary and the local appearance dictionary are learned in a regressive manner to select robust features and fit shape increments. Additionally, to make the learned model more generalized, we select the best matched parameter set through extensive validation tests. Experimental results on three public datasets demonstrate that the proposed method achieves a better robustness over the state-of-the-art methods.

Robustness of spin-coupling distributions for perfect quantum state transfer

International Nuclear Information System (INIS)

Zwick, Analia; Alvarez, Gonzalo A.; Stolze, Joachim; Osenda, Omar

2011-01-01

The transmission of quantum information between different parts of a quantum computer is of fundamental importance. Spin chains have been proposed as quantum channels for transferring information. Different configurations for the spin couplings were proposed in order to optimize the transfer. As imperfections in the creation of these specific spin-coupling distributions can never be completely avoided, it is important to find out which systems are optimally suited for information transfer by assessing their robustness against imperfections or disturbances. We analyze different spin coupling distributions of spin chain channels designed for perfect quantum state transfer. In particular, we study the transfer of an initial state from one end of the chain to the other end. We quantify the robustness of different coupling distributions against perturbations and we relate it to the properties of the energy eigenstates and eigenvalues. We find that the localization properties of the systems play an important role for robust quantum state transfer.

Revival and robustness of Bures distance discord under decoherence channels

International Nuclear Information System (INIS)

Shi, Jia-dong; Wang, Dong; Ma, Yang-cheng; Ye, Liu

2016-01-01

In this paper, we demonstrate the revival and robustness of Bures distance discord in comparison with entanglement under local decoherent evolutions. The results show that in depolarizing channel Bures distance discord revives after a dark point of time, while entanglement will damp into death without revival. In addition, in hybrid channel the declining initial condition can enable Bures distance discord to decay more smoothly within a limited time, but speed up the death of entanglement. In this sense, Bures distance discord is typically more robust against decoherence than entanglement. Furthermore, we also provide a geometric interpretation concerning these phenomena. - Highlights: • Bures distance discord is more robust against decoherence than entanglement. • Bures distance discord revives after a dark point of time, while entanglement damps to death. • The initial condition enables Bures distance discord to damp smoothly, but it speeds up the death of entanglement. • A geometric interpretation concerning these phenomena has been provided.

A content-based digital image watermarking scheme resistant to local geometric distortions

International Nuclear Information System (INIS)

Yang, Hong-ying; Chen, Li-li; Wang, Xiang-yang

2011-01-01

Geometric distortion is known as one of the most difficult attacks to resist, as it can desynchronize the location of the watermark and hence cause incorrect watermark detection. Geometric distortion can be decomposed into two classes: global affine transforms and local geometric distortions. Most countermeasures proposed in the literature only address the problem of global affine transforms. It is a challenging problem to design a robust image watermarking scheme against local geometric distortions. In this paper, we propose a new content-based digital image watermarking scheme with good visual quality and reasonable resistance against local geometric distortions. Firstly, the robust feature points, which can survive various common image processing and global affine transforms, are extracted by using a multi-scale SIFT (scale invariant feature transform) detector. Then, the affine covariant local feature regions (LFRs) are constructed adaptively according to the feature scale and local invariant centroid. Finally, the digital watermark is embedded into the affine covariant LFRs by modulating the magnitudes of discrete Fourier transform (DFT) coefficients. By binding the watermark with the affine covariant LFRs, the watermark detection can be done without synchronization error. Experimental results show that the proposed image watermarking is not only invisible and robust against common image processing operations such as sharpening, noise addition, and JPEG compression, etc, but also robust against global affine transforms and local geometric distortions

Supervised linear dimensionality reduction with robust margins for object recognition

Science.gov (United States)

Dornaika, F.; Assoum, A.

2013-01-01

Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.

Tensor voting for robust color edge detection

OpenAIRE

Moreno, Rodrigo; García, Miguel Ángel; Puig, Domenec

2014-01-01

The final publication is available at Springer via http://dx.doi.org/10.1007/978-94-007-7584-8_9 This chapter proposes two robust color edge detection methods based on tensor voting. The first method is a direct adaptation of the classical tensor voting to color images where tensors are initialized with either the gradient or the local color structure tensor. The second method is based on an extension of tensor voting in which the encoding and voting processes are specifically tailored to ...

Robust linear registration of CT images using random regression forests

Science.gov (United States)

Konukoglu, Ender; Criminisi, Antonio; Pathak, Sayan; Robertson, Duncan; White, Steve; Haynor, David; Siddiqui, Khan

2011-03-01

Global linear registration is a necessary first step for many different tasks in medical image analysis. Comparing longitudinal studies1, cross-modality fusion2, and many other applications depend heavily on the success of the automatic registration. The robustness and efficiency of this step is crucial as it affects all subsequent operations. Most common techniques cast the linear registration problem as the minimization of a global energy function based on the image intensities. Although these algorithms have proved useful, their robustness in fully automated scenarios is still an open question. In fact, the optimization step often gets caught in local minima yielding unsatisfactory results. Recent algorithms constrain the space of registration parameters by exploiting implicit or explicit organ segmentations, thus increasing robustness4,5. In this work we propose a novel robust algorithm for automatic global linear image registration. Our method uses random regression forests to estimate posterior probability distributions for the locations of anatomical structures - represented as axis aligned bounding boxes6. These posterior distributions are later integrated in a global linear registration algorithm. The biggest advantage of our algorithm is that it does not require pre-defined segmentations or regions. Yet it yields robust registration results. We compare the robustness of our algorithm with that of the state of the art Elastix toolbox7. Validation is performed via 1464 pair-wise registrations in a database of very diverse 3D CT images. We show that our method decreases the "failure" rate of the global linear registration from 12.5% (Elastix) to only 1.9%.

Machine learning meliorates computing and robustness in discrete combinatorial optimization problems.

Directory of Open Access Journals (Sweden)

Fushing Hsieh

2016-11-01

Full Text Available Discrete combinatorial optimization problems in real world are typically defined via an ensemble of potentially high dimensional measurements pertaining to all subjects of a system under study. We point out that such a data ensemble in fact embeds with system's information content that is not directly used in defining the combinatorial optimization problems. Can machine learning algorithms extract such information content and make combinatorial optimizing tasks more efficient? Would such algorithmic computations bring new perspectives into this classic topic of Applied Mathematics and Theoretical Computer Science? We show that answers to both questions are positive. One key reason is due to permutation invariance. That is, the data ensemble of subjects' measurement vectors is permutation invariant when it is represented through a subject-vs-measurement matrix. An unsupervised machine learning algorithm, called Data Mechanics (DM, is applied to find optimal permutations on row and column axes such that the permuted matrix reveals coupled deterministic and stochastic structures as the system's information content. The deterministic structures are shown to facilitate geometry-based divide-and-conquer scheme that helps optimizing task, while stochastic structures are used to generate an ensemble of mimicries retaining the deterministic structures, and then reveal the robustness pertaining to the original version of optimal solution. Two simulated systems, Assignment problem and Traveling Salesman problem, are considered. Beyond demonstrating computational advantages and intrinsic robustness in the two systems, we propose brand new robust optimal solutions. We believe such robust versions of optimal solutions are potentially more realistic and practical in real world settings.

An elementary quantum network using robust nuclear spin qubits in diamond

Science.gov (United States)

Kalb, Norbert; Reiserer, Andreas; Humphreys, Peter; Blok, Machiel; van Bemmelen, Koen; Twitchen, Daniel; Markham, Matthew; Taminiau, Tim; Hanson, Ronald

Quantum registers containing multiple robust qubits can form the nodes of future quantum networks for computation and communication. Information storage within such nodes must be resilient to any type of local operation. Here we demonstrate multiple robust memories by employing five nuclear spins adjacent to a nitrogen-vacancy defect centre in diamond. We characterize the storage of quantum superpositions and their resilience to entangling attempts with the electron spin of the defect centre. The storage fidelity is found to be limited by the probabilistic electron spin reset after failed entangling attempts. Control over multiple memories is then utilized to encode states in decoherence protected subspaces with increased robustness. Furthermore we demonstrate memory control in two optically linked network nodes and characterize the storage capabilities of both memories in terms of the process fidelity with the identity. These results pave the way towards multi-qubit quantum algorithms in a remote network setting.

Cell array-based intracellular localization screening reveals novel functional features of human chromosome 21 proteins

Directory of Open Access Journals (Sweden)

Kahlem Pascal

2006-06-01

Full Text Available Abstract Background Trisomy of human chromosome 21 (Chr21 results in Down's syndrome, a complex developmental and neurodegenerative disease. Molecular analysis of Down's syndrome, however, poses a particular challenge, because the aneuploid region of Chr21 contains many genes of unknown function. Subcellular localization of human Chr21 proteins may contribute to further understanding of the functions and regulatory mechanisms of the genes that code for these proteins. Following this idea, we used a transfected-cell array technique to perform a rapid and cost-effective analysis of the intracellular distribution of Chr 21 proteins. Results We chose 89 genes that were distributed over the majority of 21q, ranging from RBM11 (14.5 Mb to MCM3AP (46.6 Mb, with part of them expressed aberrantly in the Down's syndrome mouse model. Open reading frames of these genes were cloned into a mammalian expression vector with an amino-terminal His6 tag. All of the constructs were arrayed on glass slides and reverse transfected into HEK293T cells for protein expression. Co-localization detection using a set of organelle markers was carried out for each Chr21 protein. Here, we report the subcellular localization properties of 52 proteins. For 34 of these proteins, their localization is described for the first time. Furthermore, the alteration in cell morphology and growth as a result of protein over-expression for claudin-8 and claudin-14 genes has been characterized. Conclusion The cell array-based protein expression and detection approach is a cost-effective platform for large-scale functional analyses, including protein subcellular localization and cell phenotype screening. The results from this study reveal novel functional features of human Chr21 proteins, which should contribute to further understanding of the molecular pathology of Down's syndrome.

Robust Growth Determinants

OpenAIRE

Doppelhofer, Gernot; Weeks, Melvyn

2011-01-01

This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsi- monious mixture modeling that allows for fat-tailed errors compared to the normal benchmark case. Applying robust model averaging to growth determinants, the paper finds that eight out of eighteen variables found to be significantly related to economic growth ...

Transient Localization in Shallow Water Environments

National Research Council Canada - National Science Library

Brune, Joachim

1998-01-01

.... Measures of robustness to be examined include the size of the localization footprint on the ambiguity surface and the peak-to-sidelobe levels in the presence of environmental mismatch and noise...

Symmetry-Free, p-Robust Equilibrated Error Indication for the hp-Version of the FEMin Nearly Incompressible Linear Elasticity

OpenAIRE

Dörsek, Philipp; Melenk, Jens M.

2017-01-01

We consider the extension of the p-robust equilibrated error estimator due to Braess, Pillwein and Schöberl to linear elasticity. We derive a formulation where the local mixed auxiliary problems do not require symmetry of the stresses. The resulting error estimator is p-robust, and the reliability estimate is also robust in the incompressible limit if quadratics are included in the approximation space. Extensions to other systems of linear second-order partial differential equations are discu...

A robust image watermarking in contourlet transform domain

Science.gov (United States)

Sharma, Rajat; Gupta, Abhishek Kumar; Singh, Deepak; Verma, Vivek Singh; Bhardwaj, Anuj

2017-10-01

A lot of work has been done in the field of image watermarking to overcome the problems of rightful ownership, copyright protection etc. In order to provide a robust solution of such issues, the authors propose a hybrid approach that involves contourlet, lifting wavelet, and discrete cosine transform. The first level coefficients of the original image which are obtained using contourlet transform are further decomposed using one level lifting wavelet transform. After that, these coefficients are modified using discrete cosine transform. Whereas, second level subband of contourlet transform coefficients are used to obtain block wise modification parameter based on edge detection and entropy calculations. Watermark bits are embedded by quantizing the discrete cosine transform coefficient blocks obtained using HL sub-band of first level lifting wavelet transform coefficients. The experimental results reveal that the proposed scheme has high robustness and imperceptibility.

Robust Adaptive Speed Control of Induction Motor Drives

DEFF Research Database (Denmark)

Bidstrup, N.

This thesis concerns speed control of current vector controlled induction motor drives (CVC drives). The CVC drive is an existing prototype drive developed by Danfoss A/S, Transmission Division. Practical tests have revealed that the open loop dynamical properties of the CVC drive are highly......, (LS) identification and generalized predictive control (GPC) has been implemented and tested on the CVC drive. Allthough GPC is a robust control method, it was not possible to maintain specified controller performance in the entire operating range. This was the main reason for investigating truly...... and measurement noise in general, were the major reasons for the drifting parameters. Two approaches was proposed to robustify MASTR2 against the output noise. The first approach consists of filtering the output. Output filtering had a significant effect in simulations, but the robustness against the output noise...

Adaptive integral robust control and application to electromechanical servo systems.

Science.gov (United States)

Deng, Wenxiang; Yao, Jianyong

2017-03-01

This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A robust method for estimating motorbike count based on visual information learning

Science.gov (United States)

Huynh, Kien C.; Thai, Dung N.; Le, Sach T.; Thoai, Nam; Hamamoto, Kazuhiko

2015-03-01

Estimating the number of vehicles in traffic videos is an important and challenging task in traffic surveillance, especially with a high level of occlusions between vehicles, e.g.,in crowded urban area with people and/or motorbikes. In such the condition, the problem of separating individual vehicles from foreground silhouettes often requires complicated computation [1][2][3]. Thus, the counting problem is gradually shifted into drawing statistical inferences of target objects density from their shape [4], local features [5], etc. Those researches indicate a correlation between local features and the number of target objects. However, they are inadequate to construct an accurate model for vehicles density estimation. In this paper, we present a reliable method that is robust to illumination changes and partial affine transformations. It can achieve high accuracy in case of occlusions. Firstly, local features are extracted from images of the scene using Speed-Up Robust Features (SURF) method. For each image, a global feature vector is computed using a Bag-of-Words model which is constructed from the local features above. Finally, a mapping between the extracted global feature vectors and their labels (the number of motorbikes) is learned. That mapping provides us a strong prediction model for estimating the number of motorbikes in new images. The experimental results show that our proposed method can achieve a better accuracy in comparison to others.

Robustness of Greenberger-Horne-Zeilinger and W states for teleportation in external environments

Energy Technology Data Exchange (ETDEWEB)

Hu Mingliang, E-mail: mingliang0301@163.co [School of Science, Xi' an University of Posts and Telecommunications, Xi' an 710061 (China)

2011-01-31

By solving analytically a master equation in the Lindblad form, we study quantum teleportation of the one-qubit state under the influence of different surrounding environments, and compared the robustness between Greenberger-Horne-Zeilinger (GHZ) and W states in terms of their teleportation capacity. The results revealed that when subject to zero temperature environment, the GHZ state is always more robust than the W state, while the reverse situation occurs when the channel is subject to infinite temperature or dephasing environment.

Robustness of Greenberger-Horne-Zeilinger and W states for teleportation in external environments

International Nuclear Information System (INIS)

Hu Mingliang

2011-01-01

By solving analytically a master equation in the Lindblad form, we study quantum teleportation of the one-qubit state under the influence of different surrounding environments, and compared the robustness between Greenberger-Horne-Zeilinger (GHZ) and W states in terms of their teleportation capacity. The results revealed that when subject to zero temperature environment, the GHZ state is always more robust than the W state, while the reverse situation occurs when the channel is subject to infinite temperature or dephasing environment.

LSAH: a fast and efficient local surface feature for point cloud registration

Science.gov (United States)

Lu, Rongrong; Zhu, Feng; Wu, Qingxiao; Kong, Yanzi

2018-04-01

Point cloud registration is a fundamental task in high level three dimensional applications. Noise, uneven point density and varying point cloud resolutions are the three main challenges for point cloud registration. In this paper, we design a robust and compact local surface descriptor called Local Surface Angles Histogram (LSAH) and propose an effectively coarse to fine algorithm for point cloud registration. The LSAH descriptor is formed by concatenating five normalized sub-histograms into one histogram. The five sub-histograms are created by accumulating a different type of angle from a local surface patch respectively. The experimental results show that our LSAH is more robust to uneven point density and point cloud resolutions than four state-of-the-art local descriptors in terms of feature matching. Moreover, we tested our LSAH based coarse to fine algorithm for point cloud registration. The experimental results demonstrate that our algorithm is robust and efficient as well.

Robustness of structures

DEFF Research Database (Denmark)

Vrouwenvelder, T.; Sørensen, John Dalsgaard

2009-01-01

After the collapse of the World Trade Centre towers in 2001 and a number of collapses of structural systems in the beginning of the century, robustness of structural systems has gained renewed interest. Despite many significant theoretical, methodical and technological advances, structural...... of robustness for structural design such requirements are not substantiated in more detail, nor have the engineering profession been able to agree on an interpretation of robustness which facilitates for its uantification. A European COST action TU 601 on ‘Robustness of structures' has started in 2007...... by a group of members of the CSS. This paper describes the ongoing work in this action, with emphasis on the development of a theoretical and risk based quantification and optimization procedure on the one side and a practical pre-normative guideline on the other....

PET functional volume delineation: a robustness and repeatability study

International Nuclear Information System (INIS)

Hatt, Mathieu; Cheze-le Rest, Catherine; Albarghach, Nidal; Pradier, Olivier; Visvikis, Dimitris

2011-01-01

Current state-of-the-art algorithms for functional uptake volume segmentation in PET imaging consist of threshold-based approaches, whose parameters often require specific optimization for a given scanner and associated reconstruction algorithms. Different advanced image segmentation approaches previously proposed and extensively validated, such as among others fuzzy C-means (FCM) clustering, or fuzzy locally adaptive bayesian (FLAB) algorithm have the potential to improve the robustness of functional uptake volume measurements. The objective of this study was to investigate robustness and repeatability with respect to various scanner models, reconstruction algorithms and acquisition conditions. Robustness was evaluated using a series of IEC phantom acquisitions carried out on different PET/CT scanners (Philips Gemini and Gemini Time-of-Flight, Siemens Biograph and GE Discovery LS) with their associated reconstruction algorithms (RAMLA, TF MLEM, OSEM). A range of acquisition parameters (contrast, duration) and reconstruction parameters (voxel size) were considered for each scanner model, and the repeatability of each method was evaluated on simulated and clinical tumours and compared to manual delineation. For all the scanner models, acquisition parameters and reconstruction algorithms considered, the FLAB algorithm demonstrated higher robustness in delineation of the spheres with low mean errors (10%) and variability (5%), with respect to threshold-based methodologies and FCM. The repeatability provided by all segmentation algorithms considered was very high with a negligible variability of <5% in comparison to that associated with manual delineation (5-35%). The use of advanced image segmentation algorithms may not only allow high accuracy as previously demonstrated, but also provide a robust and repeatable tool to aid physicians as an initial guess in determining functional volumes in PET. (orig.)

Decentralized formation of random regular graphs for robust multi-agent networks

KAUST Repository

Yazicioglu, A. Yasin

2014-12-15

Multi-agent networks are often modeled via interaction graphs, where the nodes represent the agents and the edges denote direct interactions between the corresponding agents. Interaction graphs have significant impact on the robustness of networked systems. One family of robust graphs is the random regular graphs. In this paper, we present a locally applicable reconfiguration scheme to build random regular graphs through self-organization. For any connected initial graph, the proposed scheme maintains connectivity and the average degree while minimizing the degree differences and randomizing the links. As such, if the average degree of the initial graph is an integer, then connected regular graphs are realized uniformly at random as time goes to infinity.

Robustness of Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

2008-01-01

This paper describes the background of the robustness requirements implemented in the Danish Code of Practice for Safety of Structures and in the Danish National Annex to the Eurocode 0, see (DS-INF 146, 2003), (DS 409, 2006), (EN 1990 DK NA, 2007) and (Sørensen and Christensen, 2006). More...... frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new structures essential....... According to Danish design rules robustness shall be documented for all structures in high consequence class. The design procedure to document sufficient robustness consists of: 1) Review of loads and possible failure modes / scenarios and determination of acceptable collapse extent; 2) Review...

Quantum dot-based local field imaging reveals plasmon-based interferometric logic in silver nanowire networks.

Science.gov (United States)

Wei, Hong; Li, Zhipeng; Tian, Xiaorui; Wang, Zhuoxian; Cong, Fengzi; Liu, Ning; Zhang, Shunping; Nordlander, Peter; Halas, Naomi J; Xu, Hongxing

2011-02-09

We show that the local electric field distribution of propagating plasmons along silver nanowires can be imaged by coating the nanowires with a layer of quantum dots, held off the surface of the nanowire by a nanoscale dielectric spacer layer. In simple networks of silver nanowires with two optical inputs, control of the optical polarization and phase of the input fields directs the guided waves to a specific nanowire output. The QD-luminescent images of these structures reveal that a complete family of phase-dependent, interferometric logic functions can be performed on these simple networks. These results show the potential for plasmonic waveguides to support compact interferometric logic operations.

Dynamics robustness of cascading systems.

Directory of Open Access Journals (Sweden)

Jonathan T Young

2017-03-01

Full Text Available A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1 Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2 Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it

Robust Ensemble Filtering and Its Relation to Covariance Inflation in the Ensemble Kalman Filter

KAUST Repository

Luo, Xiaodong

2011-12-01

A robust ensemble filtering scheme based on the H∞ filtering theory is proposed. The optimal H∞ filter is derived by minimizing the supremum (or maximum) of a predefined cost function, a criterion different from the minimum variance used in the Kalman filter. By design, the H∞ filter is more robust than the Kalman filter, in the sense that the estimation error in the H∞ filter in general has a finite growth rate with respect to the uncertainties in assimilation, except for a special case that corresponds to the Kalman filter. The original form of the H∞ filter contains global constraints in time, which may be inconvenient for sequential data assimilation problems. Therefore a variant is introduced that solves some time-local constraints instead, and hence it is called the time-local H∞ filter (TLHF). By analogy to the ensemble Kalman filter (EnKF), the concept of ensemble time-local H∞ filter (EnTLHF) is also proposed. The general form of the EnTLHF is outlined, and some of its special cases are discussed. In particular, it is shown that an EnKF with certain covariance inflation is essentially an EnTLHF. In this sense, the EnTLHF provides a general framework for conducting covariance inflation in the EnKF-based methods. Some numerical examples are used to assess the relative robustness of the TLHF–EnTLHF in comparison with the corresponding KF–EnKF method.

Robust and distributed hypothesis testing

CERN Document Server

Gül, Gökhan

2017-01-01

This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the boo...

Robustness Property of Robust-BD Wald-Type Test for Varying-Dimensional General Linear Models

Directory of Open Access Journals (Sweden)

Xiao Guo

2018-03-01

Full Text Available An important issue for robust inference is to examine the stability of the asymptotic level and power of the test statistic in the presence of contaminated data. Most existing results are derived in finite-dimensional settings with some particular choices of loss functions. This paper re-examines this issue by allowing for a diverging number of parameters combined with a broader array of robust error measures, called “robust- BD ”, for the class of “general linear models”. Under regularity conditions, we derive the influence function of the robust- BD parameter estimator and demonstrate that the robust- BD Wald-type test enjoys the robustness of validity and efficiency asymptotically. Specifically, the asymptotic level of the test is stable under a small amount of contamination of the null hypothesis, whereas the asymptotic power is large enough under a contaminated distribution in a neighborhood of the contiguous alternatives, thus lending supports to the utility of the proposed robust- BD Wald-type test.

Robustness of intratumour 18F-FDG PET uptake heterogeneity quantification for therapy response prediction in oesophageal carcinoma

International Nuclear Information System (INIS)

Hatt, Mathieu; Tixier, Florent; Visvikis, Dimitris; Cheze Le Rest, Catherine; Pradier, Olivier

2013-01-01

Intratumour uptake heterogeneity in PET quantified in terms of textural features for response to therapy has been investigated in several studies, including assessment of their robustness for reconstruction and physiological reproducibility. However, there has been no thorough assessment of the potential impact of preprocessing steps on the resulting quantification and its predictive value. The goal of this work was to assess the robustness of PET heterogeneity in textural features for delineation of functional volumes and partial volume correction (PVC). This retrospective analysis included 50 patients with oesophageal cancer. PVC of each PET image was performed. Tumour volumes were determined using fixed and adaptive thresholding, and the fuzzy locally adaptive Bayesian algorithm, and heterogeneity was quantified using local and regional textural features. Differences in the absolute values of the image-derived parameters considered were assessed using Bland-Altman analysis. The impact on their predictive value for the identification of patient nonresponders was assessed by comparing areas under the receiver operating characteristic curves. Heterogeneity parameters were more dependent on delineation than on PVC. The parameters most sensitive to delineation and PVC were regional ones (intensity variability and size zone variability), whereas local parameters such as entropy and homogeneity were the most robust. Despite the large differences in absolute values obtained from different delineation methods or after PVC, these differences did not necessarily translate into a significant impact on their predictive value. Parameters such as entropy, homogeneity, dissimilarity (for local heterogeneity characterization) and zone percentage (for regional characterization) should be preferred. This selection is based on a demonstrated high differentiation power in terms of predicting response, as well as a significant robustness with respect to the delineation method used

Event-triggered decentralized robust model predictive control for constrained large-scale interconnected systems

Directory of Open Access Journals (Sweden)

Ling Lu

2016-12-01

Full Text Available This paper considers the problem of event-triggered decentralized model predictive control (MPC for constrained large-scale linear systems subject to additive bounded disturbances. The constraint tightening method is utilized to formulate the MPC optimization problem. The local predictive control law for each subsystem is determined aperiodically by relevant triggering rule which allows a considerable reduction of the computational load. And then, the robust feasibility and closed-loop stability are proved and it is shown that every subsystem state will be driven into a robust invariant set. Finally, the effectiveness of the proposed approach is illustrated via numerical simulations.

Adaptive ACMS: A robust localized Approximated Component Mode Synthesis Method

OpenAIRE

Madureira, Alexandre L.; Sarkis, Marcus

2017-01-01

We consider finite element methods of multiscale type to approximate solutions for two-dimensional symmetric elliptic partial differential equations with heterogeneous $L^\\infty$ coefficients. The methods are of Galerkin type and follows the Variational Multiscale and Localized Orthogonal Decomposition--LOD approaches in the sense that it decouples spaces into multiscale and fine subspaces. In a first method, the multiscale basis functions are obtained by mapping coarse basis functions, based...

Robustness Beamforming Algorithms

Directory of Open Access Journals (Sweden)

Sajad Dehghani

2014-04-01

Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.

On the prediction of ductile fracture by void coalescence and strain localization

Science.gov (United States)

Luo, Tuo; Gao, Xiaosheng

2018-04-01

This paper presents a unit cell model based on the observation that ductile fracture occurs when plastic flow is localized in a band. The unit cell consists of three void containing material units stacked in the direction normal to the localization plane. Localization takes place in the middle material unit while the two outer units undergo elastic recovery after failure occurs. Thus a failure criterion is established as when the macroscopic effective strain of the outer material units reaches the maximum value. Analyses are conducted to demonstrate the effect of the voids existing outside the localization band. Comparisons of the present model with several previous models suggest that the present model is not only easy to implement in finite element analysis but also more suitable to robustly determine the failure strain. A series of unit cell analyses are conducted for various macroscopic stress triaxialities and Lode parameters. The analysis results confirm that for a fixed Lode parameter, the failure strain decreases exponentially with the stress triaxiality and for a given stress triaxiality, it increases as the stress state approaches the generalized tension and generalized compression. The analysis results also reveal the effect of the stress state on the deformed void shape within and near the localization band.

Local ecological knowledge and scientific data reveal overexploitation by multigear artisanal fisheries in the southwestern Atlantic.

Directory of Open Access Journals (Sweden)

Mariana G Bender

Full Text Available In the last decades, a number of studies based on historical records revealed the diversity loss in the oceans and human-induced changes to marine ecosystems. These studies have improved our understanding of the human impacts in the oceans. They also drew attention to the shifting baseline syndrome and the importance of assessing appropriate sources of data in order to build the most reliable environmental baseline. Here we amassed information from artisanal fishermen's local ecological knowledge, fisheries landing data and underwater visual census to assess the decline of fish species in Southeastern Brazil. Interviews with 214 fishermen from line, beach seine and spearfishing revealed a sharp decline in abundance of the bluefish Pomatomus saltatrix, the groupers Epinephelus marginatus, Mycteroperca acutirostris, M. bonaci and M. microlepis, and large parrotfishes in the past six decades. Fisheries landing data from a 16-year period support the decline of bluefish as pointed by fishermen's local knowledge, while underwater visual census campaigns show reductions in groupers' abundance and a sharp population decline of the Brazilian endemic parrotfish Scarus trispinosus. Despite the marked decline of these fisheries, younger and less experienced fishermen recognized fewer species as overexploited and fishing sites as depleted than older and more experienced fishermen, indicating the occurrence of the shifting baseline syndrome. Here we show both the decline of multigear fisheries catches - combining anecdotal and scientific data - as well as changes in environmental perceptions over generations of fishermen. Managing ocean resources requires looking into the past, and into traditional knowledge, bringing historical baselines to the present and improving public awareness.

Uniform competency-based local feature extraction for remote sensing images

Science.gov (United States)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

Robustness-Based Simplification of 2D Steady and Unsteady Vector Fields

KAUST Repository

Skraba, Primoz

2015-08-01

© 2015 IEEE. Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification techniques based on the topological skeleton successively remove pairs of critical points connected by separatrices, using distance or area-based relevance measures. These methods rely on the stable extraction of the topological skeleton, which can be difficult due to instability in numerical integration, especially when processing highly rotational flows. In this paper, we propose a novel simplification scheme derived from the recently introduced topological notion of robustness which enables the pruning of sets of critical points according to a quantitative measure of their stability, that is, the minimum amount of vector field perturbation required to remove them. This leads to a hierarchical simplification scheme that encodes flow magnitude in its perturbation metric. Our novel simplification algorithm is based on degree theory and has minimal boundary restrictions. Finally, we provide an implementation under the piecewise-linear setting and apply it to both synthetic and real-world datasets. We show local and complete hierarchical simplifications for steady as well as unsteady vector fields.

Robustness-Based Simplification of 2D Steady and Unsteady Vector Fields.

Science.gov (United States)

Skraba, Primoz; Bei Wang; Guoning Chen; Rosen, Paul

2015-08-01

Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification techniques based on the topological skeleton successively remove pairs of critical points connected by separatrices, using distance or area-based relevance measures. These methods rely on the stable extraction of the topological skeleton, which can be difficult due to instability in numerical integration, especially when processing highly rotational flows. In this paper, we propose a novel simplification scheme derived from the recently introduced topological notion of robustness which enables the pruning of sets of critical points according to a quantitative measure of their stability, that is, the minimum amount of vector field perturbation required to remove them. This leads to a hierarchical simplification scheme that encodes flow magnitude in its perturbation metric. Our novel simplification algorithm is based on degree theory and has minimal boundary restrictions. Finally, we provide an implementation under the piecewise-linear setting and apply it to both synthetic and real-world datasets. We show local and complete hierarchical simplifications for steady as well as unsteady vector fields.

Robustness-Based Simplification of 2D Steady and Unsteady Vector Fields

KAUST Repository

Skraba, Primoz; Wang, Bei; Chen, Guoning; Rosen, Paul

2015-01-01

© 2015 IEEE. Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification techniques based on the topological skeleton successively remove pairs of critical points connected by separatrices, using distance or area-based relevance measures. These methods rely on the stable extraction of the topological skeleton, which can be difficult due to instability in numerical integration, especially when processing highly rotational flows. In this paper, we propose a novel simplification scheme derived from the recently introduced topological notion of robustness which enables the pruning of sets of critical points according to a quantitative measure of their stability, that is, the minimum amount of vector field perturbation required to remove them. This leads to a hierarchical simplification scheme that encodes flow magnitude in its perturbation metric. Our novel simplification algorithm is based on degree theory and has minimal boundary restrictions. Finally, we provide an implementation under the piecewise-linear setting and apply it to both synthetic and real-world datasets. We show local and complete hierarchical simplifications for steady as well as unsteady vector fields.

Robustness Analyses of Timber Structures

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Hald, Frederik

2013-01-01

The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many mo...... with respect to robustness of timber structures and will discuss the consequences of such robustness issues related to the future development of timber structures.......The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many...... modern building codes consider the need for the robustness of structures and provide strategies and methods to obtain robustness. Therefore, a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper summaries issues...

Robust Networked Control Scheme for Distributed Secondary Control of Islanded MicroGrids

DEFF Research Database (Denmark)

Shafiee, Qobad; Stefanovic, Cedomir; Dragicevic, Tomislav

2014-01-01

Distributed secondary control (DSC) is a new approach for microgrids (MGs) by which the frequency, voltage and power can be regulated by using only local unit controllers. Such a solution is necessary for anticipated scenarios that have an increased number of distributed generators (DGs) within...... the MG. Due to the constrained traffic pattern required by the secondary control, it is viable to implement a dedicated local area communication functionality among the local controllers. This paper presents a new, wireless-based robust communication algorithm for the DSC of MGs. The algorithm tightly...... couples the communication and the control functionality, such that the transmission errors are absorbed through an averaging operation performed in each local controller, resulting in a very high reliability. Furthermore, transmissions from each DG are periodic and prescheduled broadcasts, and in this way...

Influence of Different Coupling Modes on the Robustness of Smart Grid under Targeted Attack

Directory of Open Access Journals (Sweden)

WenJie Kang

2018-05-01

Full Text Available Many previous works only focused on the cascading failure of global coupling of one-to-one structures in interdependent networks, but the local coupling of dual coupling structures has rarely been studied due to its complex structure. This will result in a serious consequence that many conclusions of the one-to-one structure may be incorrect in the dual coupling network and do not apply to the smart grid. Therefore, it is very necessary to subdivide the dual coupling link into a top-down coupling link and a bottom-up coupling link in order to study their influence on network robustness by combining with different coupling modes. Additionally, the power flow of the power grid can cause the load of a failed node to be allocated to its neighboring nodes and trigger a new round of load distribution when the load of these nodes exceeds their capacity. This means that the robustness of smart grids may be affected by four factors, i.e., load redistribution, local coupling, dual coupling link and coupling mode; however, the research on the influence of those factors on the network robustness is missing. In this paper, firstly, we construct the smart grid as a two-layer network with a dual coupling link and divide the power grid and communication network into many subnets based on the geographical location of their nodes. Secondly, we define node importance ( N I as an evaluation index to access the impact of nodes on the cyber or physical network and propose three types of coupling modes based on N I of nodes in the cyber and physical subnets, i.e., Assortative Coupling in Subnets (ACIS, Disassortative Coupling in Subnets (DCIS, and Random Coupling in Subnets (RCIS. Thirdly, a cascading failure model is proposed for studying the effect of local coupling of dual coupling link in combination with ACIS, DCIS, and RCIS on the robustness of the smart grid against a targeted attack, and the survival rate of functional nodes is used to assess the robustness of

Influence of Different Coupling Modes on the Robustness of Smart Grid under Targeted Attack.

Science.gov (United States)

Kang, WenJie; Hu, Gang; Zhu, PeiDong; Liu, Qiang; Hang, Zhi; Liu, Xin

2018-05-24

Many previous works only focused on the cascading failure of global coupling of one-to-one structures in interdependent networks, but the local coupling of dual coupling structures has rarely been studied due to its complex structure. This will result in a serious consequence that many conclusions of the one-to-one structure may be incorrect in the dual coupling network and do not apply to the smart grid. Therefore, it is very necessary to subdivide the dual coupling link into a top-down coupling link and a bottom-up coupling link in order to study their influence on network robustness by combining with different coupling modes. Additionally, the power flow of the power grid can cause the load of a failed node to be allocated to its neighboring nodes and trigger a new round of load distribution when the load of these nodes exceeds their capacity. This means that the robustness of smart grids may be affected by four factors, i.e., load redistribution, local coupling, dual coupling link and coupling mode; however, the research on the influence of those factors on the network robustness is missing. In this paper, firstly, we construct the smart grid as a two-layer network with a dual coupling link and divide the power grid and communication network into many subnets based on the geographical location of their nodes. Secondly, we define node importance ( N I ) as an evaluation index to access the impact of nodes on the cyber or physical network and propose three types of coupling modes based on N I of nodes in the cyber and physical subnets, i.e., Assortative Coupling in Subnets (ACIS), Disassortative Coupling in Subnets (DCIS), and Random Coupling in Subnets (RCIS). Thirdly, a cascading failure model is proposed for studying the effect of local coupling of dual coupling link in combination with ACIS, DCIS, and RCIS on the robustness of the smart grid against a targeted attack, and the survival rate of functional nodes is used to assess the robustness of the smart grid

Bayesian-based localization in inhomogeneous transmission media

DEFF Research Database (Denmark)

Nadimi, E. S.; Blanes-Vidal, V.; Johansen, P. M.

2013-01-01

In this paper, we propose a novel robust probabilistic approach based on the Bayesian inference using received-signal-strength (RSS) measurements with varying path-loss exponent. We derived the probability density function (pdf) of the distance between any two sensors in the network with heteroge......In this paper, we propose a novel robust probabilistic approach based on the Bayesian inference using received-signal-strength (RSS) measurements with varying path-loss exponent. We derived the probability density function (pdf) of the distance between any two sensors in the network...... with heterogeneous transmission medium as a function of the given RSS measurements and the characteristics of the heterogeneous medium. The results of this study show that the localization mean square error (MSE) of the Bayesian-based method outperformed all other existing localization approaches. © 2013 ACM....

Stochastic Mesocortical Dynamics and Robustness of Working Memory during Delay-Period.

Directory of Open Access Journals (Sweden)

Melissa Reneaux

Full Text Available The role of prefronto-mesoprefrontal system in the dopaminergic modulation of working memory during delayed response tasks is well-known. Recently, a dynamical model of the closed-loop mesocortical circuit has been proposed which employs a deterministic framework to elucidate the system's behavior in a qualitative manner. Under natural conditions, noise emanating from various sources affects the circuit's functioning to a great extent. Accordingly in the present study, we reformulate the model into a stochastic framework and investigate its steady state properties in the presence of constant background noise during delay-period. From the steady state distribution, global potential landscape and signal-to-noise ratio are obtained which help in defining robustness of the circuit dynamics. This provides insight into the robustness of working memory during delay-period against its disruption due to background noise. The findings reveal that the global profile of circuit's robustness is predominantly governed by the level of D1 receptor activity and high D1 receptor stimulation favors the working memory-associated sustained-firing state over the spontaneous-activity state of the system. Moreover, the circuit's robustness is further fine-tuned by the levels of excitatory and inhibitory activities in a way such that the robustness of sustained-firing state exhibits an inverted-U shaped profile with respect to D1 receptor stimulation. It is predicted that the most robust working memory is formed possibly at a subtle ratio of the excitatory and inhibitory activities achieved at a critical level of D1 receptor stimulation. The study also paves a way to understand various cognitive deficits observed in old-age, acute stress and schizophrenia and suggests possible mechanistic routes to the working memory impairments based on the circuit's robustness profile.

Stochastic Mesocortical Dynamics and Robustness of Working Memory during Delay-Period.

Science.gov (United States)

Reneaux, Melissa; Gupta, Rahul; Karmeshu

2015-01-01

The role of prefronto-mesoprefrontal system in the dopaminergic modulation of working memory during delayed response tasks is well-known. Recently, a dynamical model of the closed-loop mesocortical circuit has been proposed which employs a deterministic framework to elucidate the system's behavior in a qualitative manner. Under natural conditions, noise emanating from various sources affects the circuit's functioning to a great extent. Accordingly in the present study, we reformulate the model into a stochastic framework and investigate its steady state properties in the presence of constant background noise during delay-period. From the steady state distribution, global potential landscape and signal-to-noise ratio are obtained which help in defining robustness of the circuit dynamics. This provides insight into the robustness of working memory during delay-period against its disruption due to background noise. The findings reveal that the global profile of circuit's robustness is predominantly governed by the level of D1 receptor activity and high D1 receptor stimulation favors the working memory-associated sustained-firing state over the spontaneous-activity state of the system. Moreover, the circuit's robustness is further fine-tuned by the levels of excitatory and inhibitory activities in a way such that the robustness of sustained-firing state exhibits an inverted-U shaped profile with respect to D1 receptor stimulation. It is predicted that the most robust working memory is formed possibly at a subtle ratio of the excitatory and inhibitory activities achieved at a critical level of D1 receptor stimulation. The study also paves a way to understand various cognitive deficits observed in old-age, acute stress and schizophrenia and suggests possible mechanistic routes to the working memory impairments based on the circuit's robustness profile.

Using local symmetry for landmark selection

OpenAIRE

Kootstra, Geert; de Jong, Sjoerd; Schomaker, Lambert R. B.

2009-01-01

Most visual Simultaneous Localization And Mapping (SLAM) methods use interest points as landmarks in their maps of the environment. Often the interest points are detected using contrast features, for instance those of the Scale Invariant Feature Transform (SIFT). The SIFT interest points, however, have problems with stability, and noise robustness. Taking our inspiration from human vision, we therefore propose the use of local symmetry to select interest points. Our method, the MUlti-scale Sy...

Attack robustness and centrality of complex networks.

Directory of Open Access Journals (Sweden)

Swami Iyer

Full Text Available Many complex systems can be described by networks, in which the constituent components are represented by vertices and the connections between the components are represented by edges between the corresponding vertices. A fundamental issue concerning complex networked systems is the robustness of the overall system to the failure of its constituent parts. Since the degree to which a networked system continues to function, as its component parts are degraded, typically depends on the integrity of the underlying network, the question of system robustness can be addressed by analyzing how the network structure changes as vertices are removed. Previous work has considered how the structure of complex networks change as vertices are removed uniformly at random, in decreasing order of their degree, or in decreasing order of their betweenness centrality. Here we extend these studies by investigating the effect on network structure of targeting vertices for removal based on a wider range of non-local measures of potential importance than simply degree or betweenness. We consider the effect of such targeted vertex removal on model networks with different degree distributions, clustering coefficients and assortativity coefficients, and for a variety of empirical networks.

International Conference on Robust Statistics

CERN Document Server

Filzmoser, Peter; Gather, Ursula; Rousseeuw, Peter

2003-01-01

Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.

Robustness of intratumour {sup 18}F-FDG PET uptake heterogeneity quantification for therapy response prediction in oesophageal carcinoma

Energy Technology Data Exchange (ETDEWEB)

Hatt, Mathieu; Tixier, Florent; Visvikis, Dimitris [CHRU Morvan, INSERM, UMR 1101, LaTIM, Brest (France); Cheze Le Rest, Catherine [CHU Miletrie, Nuclear Medicine, Poitiers (France); Pradier, Olivier [CHRU Morvan, Radiotherapy, Brest (France)

2013-10-15

Intratumour uptake heterogeneity in PET quantified in terms of textural features for response to therapy has been investigated in several studies, including assessment of their robustness for reconstruction and physiological reproducibility. However, there has been no thorough assessment of the potential impact of preprocessing steps on the resulting quantification and its predictive value. The goal of this work was to assess the robustness of PET heterogeneity in textural features for delineation of functional volumes and partial volume correction (PVC). This retrospective analysis included 50 patients with oesophageal cancer. PVC of each PET image was performed. Tumour volumes were determined using fixed and adaptive thresholding, and the fuzzy locally adaptive Bayesian algorithm, and heterogeneity was quantified using local and regional textural features. Differences in the absolute values of the image-derived parameters considered were assessed using Bland-Altman analysis. The impact on their predictive value for the identification of patient nonresponders was assessed by comparing areas under the receiver operating characteristic curves. Heterogeneity parameters were more dependent on delineation than on PVC. The parameters most sensitive to delineation and PVC were regional ones (intensity variability and size zone variability), whereas local parameters such as entropy and homogeneity were the most robust. Despite the large differences in absolute values obtained from different delineation methods or after PVC, these differences did not necessarily translate into a significant impact on their predictive value. Parameters such as entropy, homogeneity, dissimilarity (for local heterogeneity characterization) and zone percentage (for regional characterization) should be preferred. This selection is based on a demonstrated high differentiation power in terms of predicting response, as well as a significant robustness with respect to the delineation method used

Multiplex social ecological network analysis reveals how social changes affect community robustness more than resource depletion.

Science.gov (United States)

Baggio, Jacopo A; BurnSilver, Shauna B; Arenas, Alex; Magdanz, James S; Kofinas, Gary P; De Domenico, Manlio

2016-11-29

Network analysis provides a powerful tool to analyze complex influences of social and ecological structures on community and household dynamics. Most network studies of social-ecological systems use simple, undirected, unweighted networks. We analyze multiplex, directed, and weighted networks of subsistence food flows collected in three small indigenous communities in Arctic Alaska potentially facing substantial economic and ecological changes. Our analysis of plausible future scenarios suggests that changes to social relations and key households have greater effects on community robustness than changes to specific wild food resources.

Magnetization measurements reveal the local shear stiffness of hydrogels probed by ferromagnetic nanorods

Energy Technology Data Exchange (ETDEWEB)

Bender, P., E-mail: nano@p-bender.de; Tschöpe, A., E-mail: antsch@mx.uni-saarland.de; Birringer, R., E-mail: r.birringer@nano.uni-saarland.de

2014-12-15

The local mechanical coupling of ferromagnetic nanorods in hydrogels was characterized by magnetization measurements. Nickel nanorods were synthesized by the AAO-template method and embedded in gelatine hydrogels with mechanically soft or hard matrix properties determined by the gelatine weight fraction. By applying a homogeneous magnetic field during gelation the nanorods were aligned along the field resulting in uniaxially textured ferrogels. The magnetization curves of the soft ferrogel exhibited not only important similarities but also characteristic differences as compared to the hard ferrogel. The hystereses measured in a field parallel to the texture axis were almost identical for both samples indicating effective coupling of the nanorods with the polymer network. By contrast, measurements in a magnetic field perpendicular to the texture axis revealed a much higher initial susceptibility of the soft as compared to the hard ferrogel. This difference was attributed to the additional rotation of the nanorods allowed by the reduced shear modulus in the soft ferrogel matrix. Two methods for data analysis were presented which enabled us to determine the shear modulus of the gelatine matrix which was interpreted as a local rather than macroscopic quantity in consideration of the nanoscale of the probe particles. - Highlights: • Nanorods are embedded as magnetic probes in gelatine gels. • Elastic rotation of the rods can be induced by applying a homogeneous magnetic field. • Rod rotation has significant influence on the magnetization curves. • Two methods are presented to estimate the shear modulus of the matrix from the magnetization curves.

Robust Scientists

DEFF Research Database (Denmark)

Gorm Hansen, Birgitte

their core i nterests, 2) developing a selfsupply of industry interests by becoming entrepreneurs and thus creating their own compliant industry partner and 3) balancing resources within a larger collective of researchers, thus countering changes in the influx of funding caused by shifts in political...... knowledge", Danish research policy seems to have helped develop politically and economically "robust scientists". Scientific robustness is acquired by way of three strategies: 1) tasting and discriminating between resources so as to avoid funding that erodes academic profiles and push scientists away from...

swLORETA: a novel approach to robust source localization and synchronization tomography

International Nuclear Information System (INIS)

Palmero-Soler, Ernesto; Dolan, Kevin; Hadamschek, Volker; Tass, Peter A

2007-01-01

Standardized low-resolution brain electromagnetic tomography (sLORETA) is a widely used technique for source localization. However, this technique still has some limitations, especially under realistic noisy conditions and in the case of deep sources. To overcome these problems, we present here swLORETA, an improved version of sLORETA, obtained by incorporating a singular value decomposition-based lead field weighting. We show that the precision of the source localization can further be improved by a tomographic phase synchronization analysis based on swLORETA. The phase synchronization analysis turns out to be superior to a standard linear coherence analysis, since the latter cannot distinguish between real phase locking and signal mixing

Once for All: A Novel Robust System for Co-expression of Multiple Chimeric Fluorescent Fusion Proteins in Plants

Directory of Open Access Journals (Sweden)

Guitao Zhong

2017-06-01

Full Text Available Chimeric fluorescent fusion proteins have been employed as a powerful tool to reveal the subcellular localizations and dynamics of proteins in living cells. Co-expression of a fluorescent fusion protein with well-known organelle markers in the same cell is especially useful in revealing its spatial and temporal functions of the protein in question. However, the conventional methods for co-expressing multiple fluorescent tagged proteins in plants have the drawbacks of low expression efficiency, variations in the expression level and time-consuming genetic crossing. Here, we have developed a novel robust system that allows for high-efficient co-expression of multiple chimeric fluorescent fusion proteins in plants in a time-saving fashion. This system takes advantage of employing a single expression vector which consists of multiple semi-independent expressing cassettes for the protein co-expression thereby overcoming the limitations of using multiple independent expressing plasmids. In addition, it is a highly manipulable DNA assembly system, in which modification and recombination of DNA molecules are easily achieved through an optimized one-step assembly reaction. By employing this effective system, we demonstrated that co-expression of two chimeric fluorescent fusion reporter proteins of vacuolar sorting receptor and secretory carrier membrane protein gave rise to their perspective subcellular localizations in plants via both transient expression and stable transformation. Thus, we believed that this technical advance represents a promising approach for multi-color-protein co-expression in plant cells.

Ways of making-sense: Local gamma synchronization reveals differences between semantic processing induced by music and language.

Science.gov (United States)

Barraza, Paulo; Chavez, Mario; Rodríguez, Eugenio

2016-01-01

Similar to linguistic stimuli, music can also prime the meaning of a subsequent word. However, it is so far unknown what is the brain dynamics underlying the semantic priming effect induced by music, and its relation to language. To elucidate these issues, we compare the brain oscillatory response to visual words that have been semantically primed either by a musical excerpt or by an auditory sentence. We found that semantic violation between music-word pairs triggers a classical ERP N400, and induces a sustained increase of long-distance theta phase synchrony, along with a transient increase of local gamma activity. Similar results were observed after linguistic semantic violation except for gamma activity, which increased after semantic congruence between sentence-word pairs. Our findings indicate that local gamma activity is a neural marker that signals different ways of semantic processing between music and language, revealing the dynamic and self-organized nature of the semantic processing. Copyright © 2015 Elsevier Inc. All rights reserved.

Robust Trust in Expert Testimony

Directory of Open Access Journals (Sweden)

Christian Dahlman

2015-05-01

Full Text Available The standard of proof in criminal trials should require that the evidence presented by the prosecution is robust. This requirement of robustness says that it must be unlikely that additional information would change the probability that the defendant is guilty. Robustness is difficult for a judge to estimate, as it requires the judge to assess the possible effect of information that the he or she does not have. This article is concerned with expert witnesses and proposes a method for reviewing the robustness of expert testimony. According to the proposed method, the robustness of expert testimony is estimated with regard to competence, motivation, external strength, internal strength and relevance. The danger of trusting non-robust expert testimony is illustrated with an analysis of the Thomas Quick Case, a Swedish legal scandal where a patient at a mental institution was wrongfully convicted for eight murders.

Robustness Analysis of Timber Truss Structure

DEFF Research Database (Denmark)

Rajčić, Vlatka; Čizmar, Dean; Kirkegaard, Poul Henning

2010-01-01

The present paper discusses robustness of structures in general and the robustness requirements given in the codes. Robustness of timber structures is also an issues as this is closely related to Working group 3 (Robustness of systems) of the COST E55 project. Finally, an example of a robustness...... evaluation of a widespan timber truss structure is presented. This structure was built few years ago near Zagreb and has a span of 45m. Reliability analysis of the main members and the system is conducted and based on this a robustness analysis is preformed....

Qualitative Robustness in Estimation

Directory of Open Access Journals (Sweden)

Mohammed Nasser

2012-07-01

Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif";} Qualitative robustness, influence function, and breakdown point are three main concepts to judge an estimator from the viewpoint of robust estimation. It is important as well as interesting to study relation among them. This article attempts to present the concept of qualitative robustness as forwarded by first proponents and its later development. It illustrates intricacies of qualitative robustness and its relation with consistency, and also tries to remove commonly believed misunderstandings about relation between influence function and qualitative robustness citing some examples from literature and providing a new counter-example. At the end it places a useful finite and a simulated version of   qualitative robustness index (QRI. In order to assess the performance of the proposed measures, we have compared fifteen estimators of correlation coefficient using simulated as well as real data sets.

Robust controller for synchronous generator with local load via VSC

Energy Technology Data Exchange (ETDEWEB)

Cabrera-Vazquez, J. [Universidad de Guadalajara, Centro Universitario de Ciencias Exactas e Ingenierias, Departamento de Electronica, Av. Revolucion No. 1500, Modulo ' ' O' ' , Apdo. Postal 44840, Guadalajara Jalisco (Mexico); Loukianov, Alexander G.; Canedo, Jose M. [Centro de Investigacion y de Estudios Avanzados del IPN, Apdo. Postal 31-438, Plaza La Luna, C. P. 44550, Guadalajara, Jalisco (Mexico); Utkin, Vadim I. [Department of Electrical Engineering, The Ohio-State University, Columbus, OH 43210-1272 (United States)

2007-05-15

The objective of this paper is to design a nonlinear observer-based excitation controller for power system comprising a single synchronous generator connected to an infinite bus with local load. The controller proposed is based on the using first singular perturbation systems concepts and then Sliding Mode Control technique combining with Block Control Principle. To reduce ''chattering'' a nonlinear observer with estimation of the mechanical torque and rotor fluxes is designed. This combined approach enables to compensate the inherent nonlinearities of the generator and to reject external disturbances. (author)

Robustness in econometrics

CERN Document Server

Sriboonchitta, Songsak; Huynh, Van-Nam

2017-01-01

This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.

Robust Programming by Example

OpenAIRE

Bishop , Matt; Elliott , Chip

2011-01-01

Part 2: WISE 7; International audience; Robust programming lies at the heart of the type of coding called “secure programming”. Yet it is rarely taught in academia. More commonly, the focus is on how to avoid creating well-known vulnerabilities. While important, that misses the point: a well-structured, robust program should anticipate where problems might arise and compensate for them. This paper discusses one view of robust programming and gives an example of how it may be taught.

Robust Reliability or reliable robustness? - Integrated consideration of robustness and reliability aspects

DEFF Research Database (Denmark)

Kemmler, S.; Eifler, Tobias; Bertsche, B.

2015-01-01

products are and vice versa. For a comprehensive understanding and to use existing synergies between both domains, this paper discusses the basic principles of Reliability- and Robust Design theory. The development of a comprehensive model will enable an integrated consideration of both domains...

Swarm: robust and fast clustering method for amplicon-based studies

Science.gov (United States)

Rognes, Torbjørn; Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

2014-01-01

Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units. PMID:25276506

Swarm: robust and fast clustering method for amplicon-based studies

Directory of Open Access Journals (Sweden)

Frédéric Mahé

2014-09-01

Full Text Available Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units.

Robust emotion recognition using spectral and prosodic features

CERN Document Server

Rao, K Sreenivasa

2013-01-01

In this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner. The authors also delve into the complementary evidences obtained from excitation source, vocal tract system and prosodic features for the purpose of enhancing emotion recognition performance. Features based on speaking rate characteristics are explored with the help of multi-stage and hybrid models for further improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus.

Architecture and robustness tradeoffs in speed-scaled queues with application to energy management

Science.gov (United States)

Dinh, Tuan V.; Andrew, Lachlan L. H.; Nazarathy, Yoni

2014-08-01

We consider single-pass, lossless, queueing systems at steady-state subject to Poisson job arrivals at an unknown rate. Service rates are allowed to depend on the number of jobs in the system, up to a fixed maximum, and power consumption is an increasing function of speed. The goal is to control the state dependent service rates such that both energy consumption and delay are kept low. We consider a linear combination of the mean job delay and energy consumption as the performance measure. We examine both the 'architecture' of the system, which we define as a specification of the number of speeds that the system can choose from, and the 'design' of the system, which we define as the actual speeds available. Previous work has illustrated that when the arrival rate is precisely known, there is little benefit in introducing complex (multi-speed) architectures, yet in view of parameter uncertainty, allowing a variable number of speeds improves robustness. We quantify the tradeoffs of architecture specification with respect to robustness, analysing both global robustness and a newly defined measure which we call local robustness.

Atomically manufactured nickel-silicon quantum dots displaying robust resonant tunneling and negative differential resistance

Science.gov (United States)

Cheng, Jian-Yih; Fisher, Brandon L.; Guisinger, Nathan P.; Lilley, Carmen M.

2017-12-01

Providing a spin-free host material in the development of quantum information technology has made silicon a very interesting and desirable material for qubit design. Much of the work and experimental progress has focused on isolated phosphorous atoms. In this article, we report on the exploration of Ni-Si clusters that are atomically manufactured via self-assembly from the bottom-up and behave as isolated quantum dots. These small quantum dot structures are probed at the atomic-scale with scanning tunneling microscopy and spectroscopy, revealing robust resonance through discrete quantized energy levels within the Ni-Si clusters. The resonance energy is reproducible and the peak spacing of the quantum dot structures increases as the number of atoms in the cluster decrease. Probing these quantum dot structures on degenerately doped silicon results in the observation of negative differential resistance in both I-V and dI/dV spectra. At higher surface coverage of nickel, a well-known √19 surface modification is observed and is essentially a tightly packed array of the clusters. Spatial conductance maps reveal variations in the local density of states that suggest the clusters are influencing the electronic properties of their neighbors. All of these results are extremely encouraging towards the utilization of metal modified silicon surfaces to advance or complement existing quantum information technology.

Aerodynamic robustness in owl-inspired leading-edge serrations: a computational wind-gust model.

Science.gov (United States)

Rao, Chen; Liu, Hao

2018-06-08

Owls are a master to achieve silent flight in gliding and flapping flights under natural turbulent environments owing to their unique wing morphologies. While the leading-edge serrations are recently revealed, as a passive flow control micro-device, to play a crucial role in aerodynamic force production and sound suppression [25], the characteristics of wind-gust rejection associated with leading-edge serrations remain unclear. Here we address a large-eddy simulation (LES)-based study of aerodynamic robustness in owl-inspired leading-edge serrations, which is conducted with clean and serrated wing models through mimicking wind-gusts under a longitudinal fluctuation in free-stream inflow and a lateral fluctuation in pitch angle over a broad range of angles of attack (AoAs) over 0° ≤ Φ ≤ 20°. Our results show that the leading-edge serration-based passive flow control mechanisms associated with laminar-turbulent transition work effectively under fluctuated inflow and wing pitch, indicating that the leading-edge serrations are of potential gust fluctuation rejection or robustness in aerodynamic performance. Moreover, it is revealed that the tradeoff between turbulent flow control (i.e., aero-acoustic suppression) and force production in the serrated model holds independently to the wind-gust environments: poor at lower AoAs but capable of achieving equivalent aerodynamic performance at higher AoAs > 15o compared to the clean model. Our results reveal that the owl-inspired leading-edge serrations can be a robust micro-device for aero-acoustic control coping with unsteady and complex wind environments in biomimetic rotor designs for various fluid machineries. © 2018 IOP Publishing Ltd.

Robust

DEFF Research Database (Denmark)

2017-01-01

‘Robust – Reflections on Resilient Architecture’, is a scientific publication following the conference of the same name in November of 2017. Researches and PhD-Fellows, associated with the Masters programme: Cultural Heritage, Transformation and Restoration (Transformation), at The Royal Danish...

Robust multi-objective control of hybrid renewable microgeneration systems with energy storage

International Nuclear Information System (INIS)

Allison, John

2017-01-01

Highlights: • A hybrid energy system of micro-CHP, solar PV, and battery storage is presented. • Possible to exploit synergy of systems to fulfil the thermal and electrical demands. • Can control to minimise the interaction with the local electrical network. • Three different control approaches were compared. • The nonlinear inversion-based control strategy exhibits optimum performance. - Abstract: Microgeneration technologies are positioned to address future building energy efficiency requirements and facilitate the integration of renewables into buildings to ensure a sustainable, energy-secure future. This paper explores the development of a robust multi-input multi-output (MIMO) controller applicable to the control of hybrid renewable microgeneration systems with the objective of minimising the electrical grid utilisation of a building while fulfilling the thermal demands. The controller employs the inverse dynamics of the building, servicing systems, and energy storage with a robust control methodology. These inverse dynamics provides the control system with knowledge of the complex cause and effect relationships between the system, the controlled inputs, and the external disturbances, while an outer-loop control ensures robust, stable control in the presence of modelling deficiencies/uncertainty and unknown disturbances. Variable structure control compensates for the physical limitations of the systems whereby the control strategy employed switches depending on the current utilisation and availability of the energy supplies. Preliminary results presented for a system consisting of a micro-CHP unit, solar PV, and battery storage indicate that the control strategy is effective in minimising the interaction with the local electrical network and maximising the utilisation of the available renewable energy.

Is MoS2 a robust material for 2D electronics?

International Nuclear Information System (INIS)

Lorenz, Tommy; Joswig, Jan-Ole; Seifert, Gotthard; Ghorbani-Asl, Mahdi; Heine, Thomas

2014-01-01

A nanoindentation computer experiment has been carried out by means of Born–Oppenheimer molecular-dynamics simulations employing the density-functional based tight-binding method. A free-standing MoS 2 sheet, fixed at a circular support, was indented by a stiff, sharp tip. During this process, the strain on the nanolayer is locally different, with maximum values in the vicinity of the tip. All studied electronic properties—the band gap, the projected density of states, the atomic charges and the quantum conductance through the layer—vary only slightly before they change significantly when the MoS 2 sheet finally is pierced. After strong local deformation due to the indentation process, the electronic conductance in our model still is 80% of its original value. Thus, the electronic structure of single-layer MoS 2 is rather robust upon local deformation. (paper)

Robustness in Railway Operations (RobustRailS)

DEFF Research Database (Denmark)

Jensen, Jens Parbo; Nielsen, Otto Anker

This study considers the problem of enhancing railway timetable robustness without adding slack time, hence increasing the travel time. The approach integrates a transit assignment model to assess how passengers adapt their behaviour whenever operations are changed. First, the approach considers...

A robust multivariate long run analysis of European electricity prices

OpenAIRE

Bruno Bosco; Lucia Parisio; Matteo Pelagatti; Fabio Baldi

2007-01-01

This paper analyses the interdependencies existing in wholesale electricity prices in six major European countries. The results of our robust multivariate long run dynamic analysis reveal the presence of four highly integrated central European markets (France, Germany, the Netherlands and Austria). The trend shared by these four electricity markets appears to be common also to gas prices, but not to oil prices. The existence of long term dynamics among electricity prices and between electrici...

Metabolic Flux Analysis of Shewanella spp. Reveals Evolutionary Robustness in Central Carbon Metabolism

Energy Technology Data Exchange (ETDEWEB)

Tang, Yinjie J.; Martin, Hector Garcia; Dehal, Paramvir S.; Deutschbauer, Adam; Llora, Xavier; Meadows, Adam; Arkin, Adam; Keasling, Jay D.

2009-08-19

Shewanella spp. are a group of facultative anaerobic bacteria widely distributed in marine and fresh-water environments. In this study, we profiled the central metabolic fluxes of eight recently sequenced Shewanella species grown under the same condition in minimal med-ium with [3-13C] lactate. Although the tested Shewanella species had slightly different growth rates (0.23-0.29 h31) and produced different amounts of acetate and pyruvate during early exponential growth (pseudo-steady state), the relative intracellular metabolic flux distributions were remarkably similar. This result indicates that Shewanella species share similar regulation in regard to central carbon metabolic fluxes under steady growth conditions: the maintenance of metabolic robustness is not only evident in a single species under genetic perturbations (Fischer and Sauer, 2005; Nat Genet 37(6):636-640), but also observed through evolutionary related microbial species. This remarkable conservation of relative flux profiles through phylogenetic differences prompts us to introduce the concept of metabotype as an alternative scheme to classify microbial fluxomics. On the other hand, Shewanella spp. display flexibility in the relative flux profiles when switching their metabolism from consuming lactate to consuming pyruvate and acetate.

Robust transient stabilisation problem for a synchronous generator in a power network

Science.gov (United States)

Verrelli, C. M.; Damm, G.

2010-04-01

The robust transient stabilisation problem (with stability proof€) of a synchronous generator in an uncertain power network with transfer conductances is rigorously formulated and solved. The generator angular speed and electrical power are required to be kept close, when mechanical and electrical perturbations occur, to the synchronous speed and mechanical input power, respectively, while the generator terminal voltage is to be regulated, when perturbations are removed, to its pre-fault reference constant value. A robust adaptive nonlinear feedback control algorithm is designed on the basis of a third-order model of the synchronous machine: only two system parameters (synchronous machine damping and inertia constants) along with upper and lower bounds on the remaining uncertain ones are supposed to be known. The conditions to be satisfied by the remote network dynamics for guaranteeing ℒ2 and ℒ∞ robustness and asymptotic relative speed and voltage regulation to zero are weaker than those required by the single machine-infinite bus approximation: dynamic interactions between the local deviations of the generator states from the corresponding equilibrium values and the remote generators states are allowed.

An analytical hierarchical model explaining the robustness and flaw-tolerance of the interlocking barb-barbule structure of bird feathers

Science.gov (United States)

Chen, Qiang; Gorb, Stanislav; Kovalev, Alexander; Li, Zhiyong; Pugno, Nicola

2016-10-01

Feathers can fulfill their aerodynamic function only if the pennaceous vane forms an airfoil stabilized by robust interlocking between barbules. Thus, revealing the robustness of the interlocking mechanical behavior of the barbules is very important to understand the function and long-term resilience of bird feathers. This paper, basing on the small- and large-beam deflection solutions, presents a hierarchical mechanical model for deriving the critical delamination conditions of the interlocking barbules between two adjacent barbs in bird feathers. The results indicate a high robustness and flaw-tolerant design of the structure. This work contributes to the understanding of the mechanical behavior of the robust interlocking barb-barbule structure of the bird feather, and provides a basis for design of feather-inspired materials with robust interlocking mechanism, such as advanced bio-inspired micro-zipping devices.

Robust Real-Time Tracking for Visual Surveillance

Directory of Open Access Journals (Sweden)

Aguilera Josep

2007-01-01

Full Text Available This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i motion detection using a layered background model, (ii object tracking based on local appearance, (iii hierarchical object recognition, and (iv fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed.

Local appearance features for robust MRI brain structure segmentation across scanning protocols

DEFF Research Database (Denmark)

Achterberg, H.C.; Poot, Dirk H. J.; van der Lijn, Fedde

2013-01-01

Segmentation of brain structures in magnetic resonance images is an important task in neuro image analysis. Several papers on this topic have shown the benefit of supervised classification based on local appearance features, often combined with atlas-based approaches. These methods require...... a representative annotated training set and therefore often do not perform well if the target image is acquired on a different scanner or with a different acquisition protocol than the training images. Assuming that the appearance of the brain is determined by the underlying brain tissue distribution...... with substantially different imaging protocols and on different scanners. While a combination of conventional appearance features trained on data from a different scanner with multiatlas segmentation performed poorly with an average Dice overlap of 0.698, the local appearance model based on the new acquisition...

PRESSURE EQUILIBRIUM BETWEEN THE LOCAL INTERSTELLAR CLOUDS AND THE LOCAL HOT BUBBLE

Energy Technology Data Exchange (ETDEWEB)

Snowden, S. L.; Chiao, M.; Collier, M. R.; Porter, F. S.; Thomas, N. E. [NASA/Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Cravens, T.; Robertson, I. P. [Department of Physics and Astronomy, University of Kansas, 1251 Wescoe Hall Drive, Lawrence, KS 66045 (United States); Galeazzi, M.; Uprety, Y.; Ursino, E. [Department of Physics, University of Miami, 1320 Campo Sano Drive, Coral Gables, FL 33146 (United States); Koutroumpa, D. [Université Versailles St-Quentin, Sorbonne Universités, UPMC Univ. Paris 06, CNRS/INSU, LATMOS-IPSL, 11 Boulevard d' Alembert, F-78280 Guyancourt (France); Kuntz, K. D. [The Henry A. Rowland Department of Physics and Astronomy, The Johns Hopkins University, Baltimore, MD 21218 (United States); Lallement, R.; Puspitarini, L. [GEPI, Observatoire de Paris, CNRS UMR8111, Université Paris Diderot, 5 Place Jules Janssen, F-92190 Meudon (France); Lepri, S. T. [University of Michigan, 2455 Hayward Street, Ann Arbor, MI 48109 (United States); McCammon, D.; Morgan, K. [Department of Physics, University of Wisconsin, 1150 University Avenue, Madison, WI 53706 (United States); Walsh, B. M., E-mail: steven.l.snowden@nasa.gov [Space Sciences Laboratory, 7 Gauss Way, Berkeley, CA 94720 (United States)

2014-08-10

Three recent results related to the heliosphere and the local interstellar medium (ISM) have provided an improved insight into the distribution and conditions of material in the solar neighborhood. These are the measurement of the magnetic field outside of the heliosphere by Voyager 1, the improved mapping of the three-dimensional structure of neutral material surrounding the Local Cavity using extensive ISM absorption line and reddening data, and a sounding rocket flight which observed the heliospheric helium focusing cone in X-rays and provided a robust estimate of the contribution of solar wind charge exchange emission to the ROSAT All-Sky Survey 1/4 keV band data. Combining these disparate results, we show that the thermal pressure of the plasma in the Local Hot Bubble (LHB) is P/k = 10, 700 cm{sup –3} K. If the LHB is relatively free of a global magnetic field, it can easily be in pressure (thermal plus magnetic field) equilibrium with the local interstellar clouds, eliminating a long-standing discrepancy in models of the local ISM.

High-Efficiency Colloidal Quantum Dot Photovoltaics via Robust Self-Assembled Monolayers

KAUST Repository

Kim, Gi-Hwan

2015-11-11

© 2015 American Chemical Society. The optoelectronic tunability offered by colloidal quantum dots (CQDs) is attractive for photovoltaic applications but demands proper band alignment at electrodes for efficient charge extraction at minimal cost to voltage. With this goal in mind, self-assembled monolayers (SAMs) can be used to modify interface energy levels locally. However, to be effective SAMs must be made robust to treatment using the various solvents and ligands required for to fabricate high quality CQD solids. We report robust self-assembled monolayers (R-SAMs) that enable us to increase the efficiency of CQD photovoltaics. Only by developing a process for secure anchoring of aromatic SAMs, aided by deposition of the SAMs in a water-free deposition environment, were we able to provide an interface modification that was robust against the ensuing chemical treatments needed in the fabrication of CQD solids. The energy alignment at the rectifying interface was tailored by tuning the R-SAM for optimal alignment relative to the CQD quantum-confined electron energy levels. This resulted in a CQD PV record power conversion efficiency (PCE) of 10.7% with enhanced reproducibility relative to controls.

Robust statistical methods with R

CERN Document Server

Jureckova, Jana

2005-01-01

Robust statistical methods were developed to supplement the classical procedures when the data violate classical assumptions. They are ideally suited to applied research across a broad spectrum of study, yet most books on the subject are narrowly focused, overly theoretical, or simply outdated. Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on practical application.The authors work from underlying mathematical tools to implementation, paying special attention to the computational aspects. They cover the whole range of robust methods, including differentiable statistical functions, distance of measures, influence functions, and asymptotic distributions, in a rigorous yet approachable manner. Highlighting hands-on problem solving, many examples and computational algorithms using the R software supplement the discussion. The book examines the characteristics of robustness, estimators of real parameter, large sample properties, and goodness-of-fit tests. It...

Robust Manufacturing Control

CERN Document Server

2013-01-01

This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest developments and new ideas focusing on robust manufacturing control for global networks. Today, Global Production Networks (i.e. the nexus of interconnected material and information flows through which products and services are manufactured, assembled and distributed) are confronted with and expected to adapt to: sudden and unpredictable large-scale changes of important parameters which are occurring more and more frequently, event propagation in networks with high degree of interconnectivity which leads to unforeseen fluctuations, and non-equilibrium states which increasingly characterize daily business. These multi-scale changes deeply influence logistic target achievement and call for robust planning and control ...

Constrained Local UniversE Simulations: a Local Group factory

Science.gov (United States)

Carlesi, Edoardo; Sorce, Jenny G.; Hoffman, Yehuda; Gottlöber, Stefan; Yepes, Gustavo; Libeskind, Noam I.; Pilipenko, Sergey V.; Knebe, Alexander; Courtois, Hélène; Tully, R. Brent; Steinmetz, Matthias

2016-05-01

Near-field cosmology is practised by studying the Local Group (LG) and its neighbourhood. This paper describes a framework for simulating the `near field' on the computer. Assuming the Λ cold dark matter (ΛCDM) model as a prior and applying the Bayesian tools of the Wiener filter and constrained realizations of Gaussian fields to the Cosmicflows-2 (CF2) survey of peculiar velocities, constrained simulations of our cosmic environment are performed. The aim of these simulations is to reproduce the LG and its local environment. Our main result is that the LG is likely a robust outcome of the ΛCDMscenario when subjected to the constraint derived from CF2 data, emerging in an environment akin to the observed one. Three levels of criteria are used to define the simulated LGs. At the base level, pairs of haloes must obey specific isolation, mass and separation criteria. At the second level, the orbital angular momentum and energy are constrained, and on the third one the phase of the orbit is constrained. Out of the 300 constrained simulations, 146 LGs obey the first set of criteria, 51 the second and 6 the third. The robustness of our LG `factory' enables the construction of a large ensemble of simulated LGs. Suitable candidates for high-resolution hydrodynamical simulations of the LG can be drawn from this ensemble, which can be used to perform comprehensive studies of the formation of the LG.

Robust passive control for Internet-based switching systems with time-delay

Energy Technology Data Exchange (ETDEWEB)

Guan Zhihong [Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China); Zhang Hao [Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China)], E-mail: ehao79@163.com; Yang Shuanghua [Department of Computer Science, Loughborough University, Loughborough LE11 3TU (United Kingdom)

2008-04-15

In this paper, based on remote control and local control strategy, a class of hybrid multi-rate control models with time-delay and switching controllers are formulated and the problem of robust passive control for this discrete system is investigated. By Lyapunov-Krasovskii function and applying it to a descriptor model transformation some new sufficient conditions in form of LMIs are derived. A numerical example is given to illustrate the effectiveness of the theoretical result.

Robustness - theoretical framework

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Rizzuto, Enrico; Faber, Michael H.

2010-01-01

More frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new struct...... of this fact sheet is to describe a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines....

Compressed multi-block local binary pattern for object tracking

Science.gov (United States)

Li, Tianwen; Gao, Yun; Zhao, Lei; Zhou, Hao

2018-04-01

Both robustness and real-time are very important for the application of object tracking under a real environment. The focused trackers based on deep learning are difficult to satisfy with the real-time of tracking. Compressive sensing provided a technical support for real-time tracking. In this paper, an object can be tracked via a multi-block local binary pattern feature. The feature vector was extracted based on the multi-block local binary pattern feature, which was compressed via a sparse random Gaussian matrix as the measurement matrix. The experiments showed that the proposed tracker ran in real-time and outperformed the existed compressive trackers based on Haar-like feature on many challenging video sequences in terms of accuracy and robustness.

Robustness Assessment of Spatial Timber Structures

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning

2012-01-01

Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures many modern buildi...... to robustness of spatial timber structures and will discuss the consequences of such robustness issues related to the future development of timber structures.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures many modern building...... codes consider the need for robustness of structures and provide strategies and methods to obtain robustness. Therefore a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper summaries issues with respect...

A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear Optimization

Science.gov (United States)

Li, Zukui; Ding, Ran; Floudas, Christodoulos A.

2011-01-01

Robust counterpart optimization techniques for linear optimization and mixed integer linear optimization problems are studied in this paper. Different uncertainty sets, including those studied in literature (i.e., interval set; combined interval and ellipsoidal set; combined interval and polyhedral set) and new ones (i.e., adjustable box; pure ellipsoidal; pure polyhedral; combined interval, ellipsoidal, and polyhedral set) are studied in this work and their geometric relationship is discussed. For uncertainty in the left hand side, right hand side, and objective function of the optimization problems, robust counterpart optimization formulations induced by those different uncertainty sets are derived. Numerical studies are performed to compare the solutions of the robust counterpart optimization models and applications in refinery production planning and batch process scheduling problem are presented. PMID:21935263

A novel fragile X syndrome mutation reveals a conserved role for the carboxy-terminus in FMRP localization and function.

Science.gov (United States)

Okray, Zeynep; de Esch, Celine E F; Van Esch, Hilde; Devriendt, Koen; Claeys, Annelies; Yan, Jiekun; Verbeeck, Jelle; Froyen, Guy; Willemsen, Rob; de Vrij, Femke M S; Hassan, Bassem A

2015-04-01

Loss of function of the FMR1 gene leads to fragile X syndrome (FXS), the most common form of intellectual disability. The loss of FMR1 function is usually caused by epigenetic silencing of the FMR1 promoter leading to expansion and subsequent methylation of a CGG repeat in the 5' untranslated region. Very few coding sequence variations have been experimentally characterized and shown to be causal to the disease. Here, we describe a novel FMR1 mutation and reveal an unexpected nuclear export function for the C-terminus of FMRP. We screened a cohort of patients with typical FXS symptoms who tested negative for CGG repeat expansion in the FMR1 locus. In one patient, we identified a guanine insertion in FMR1 exon 15. This mutation alters the open reading frame creating a short novel C-terminal sequence, followed by a stop codon. We find that this novel peptide encodes a functional nuclear localization signal (NLS) targeting the patient FMRP to the nucleolus in human cells. We also reveal an evolutionarily conserved nuclear export function associated with the endogenous C-terminus of FMRP. In vivo analyses in Drosophila demonstrate that a patient-mimetic mutation alters the localization and function of Dfmrp in neurons, leading to neomorphic neuronal phenotypes. © 2015 The Authors. Published under the terms of the CC BY 4.0 license.

Expression robust 3D face recognition via mesh-based histograms of multiple order surface differential quantities

KAUST Repository

Li, Huibin

2011-09-01

This paper presents a mesh-based approach for 3D face recognition using a novel local shape descriptor and a SIFT-like matching process. Both maximum and minimum curvatures estimated in the 3D Gaussian scale space are employed to detect salient points. To comprehensively characterize 3D facial surfaces and their variations, we calculate weighted statistical distributions of multiple order surface differential quantities, including histogram of mesh gradient (HoG), histogram of shape index (HoS) and histogram of gradient of shape index (HoGS) within a local neighborhood of each salient point. The subsequent matching step then robustly associates corresponding points of two facial surfaces, leading to much more matched points between different scans of a same person than the ones of different persons. Experimental results on the Bosphorus dataset highlight the effectiveness of the proposed method and its robustness to facial expression variations. © 2011 IEEE.

Robust 3D–2D image registration: application to spine interventions and vertebral labeling in the presence of anatomical deformation

International Nuclear Information System (INIS)

Otake, Yoshito; Wang, Adam S; Webster Stayman, J; Siewerdsen, Jeffrey H; Uneri, Ali; Kleinszig, Gerhard; Vogt, Sebastian; Khanna, A Jay; Gokaslan, Ziya L

2013-01-01

We present a framework for robustly estimating registration between a 3D volume image and a 2D projection image and evaluate its precision and robustness in spine interventions for vertebral localization in the presence of anatomical deformation. The framework employs a normalized gradient information similarity metric and multi-start covariance matrix adaptation evolution strategy optimization with local-restarts, which provided improved robustness against deformation and content mismatch. The parallelized implementation allowed orders-of-magnitude acceleration in computation time and improved the robustness of registration via multi-start global optimization. Experiments involved a cadaver specimen and two CT datasets (supine and prone) and 36 C-arm fluoroscopy images acquired with the specimen in four positions (supine, prone, supine with lordosis, prone with kyphosis), three regions (thoracic, abdominal, and lumbar), and three levels of geometric magnification (1.7, 2.0, 2.4). Registration accuracy was evaluated in terms of projection distance error (PDE) between the estimated and true target points in the projection image, including 14 400 random trials (200 trials on the 72 registration scenarios) with initialization error up to ±200 mm and ±10°. The resulting median PDE was better than 0.1 mm in all cases, depending somewhat on the resolution of input CT and fluoroscopy images. The cadaver experiments illustrated the tradeoff between robustness and computation time, yielding a success rate of 99.993% in vertebral labeling (with ‘success’ defined as PDE <5 mm) using 1,718 664 ± 96 582 function evaluations computed in 54.0 ± 3.5 s on a mid-range GPU (nVidia, GeForce GTX690). Parameters yielding a faster search (e.g., fewer multi-starts) reduced robustness under conditions of large deformation and poor initialization (99.535% success for the same data registered in 13.1 s), but given good initialization (e.g., ±5 mm, assuming a robust

Robust 3D–2D image registration: application to spine interventions and vertebral labeling in the presence of anatomical deformation

Energy Technology Data Exchange (ETDEWEB)

Otake, Yoshito; Wang, Adam S; Webster Stayman, J; Siewerdsen, Jeffrey H [Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD (United States); Uneri, Ali [Department of Computer Science, Johns Hopkins University, Baltimore MD (United States); Kleinszig, Gerhard; Vogt, Sebastian [Siemens Healthcare, Erlangen (Germany); Khanna, A Jay [Department of Orthopaedic Surgery, Johns Hopkins University, Baltimore MD (United States); Gokaslan, Ziya L, E-mail: jeff.siewerdsen@jhu.edu [Department of Neurosurgery, Johns Hopkins University, Baltimore MD (United States)

2013-12-07

We present a framework for robustly estimating registration between a 3D volume image and a 2D projection image and evaluate its precision and robustness in spine interventions for vertebral localization in the presence of anatomical deformation. The framework employs a normalized gradient information similarity metric and multi-start covariance matrix adaptation evolution strategy optimization with local-restarts, which provided improved robustness against deformation and content mismatch. The parallelized implementation allowed orders-of-magnitude acceleration in computation time and improved the robustness of registration via multi-start global optimization. Experiments involved a cadaver specimen and two CT datasets (supine and prone) and 36 C-arm fluoroscopy images acquired with the specimen in four positions (supine, prone, supine with lordosis, prone with kyphosis), three regions (thoracic, abdominal, and lumbar), and three levels of geometric magnification (1.7, 2.0, 2.4). Registration accuracy was evaluated in terms of projection distance error (PDE) between the estimated and true target points in the projection image, including 14 400 random trials (200 trials on the 72 registration scenarios) with initialization error up to ±200 mm and ±10°. The resulting median PDE was better than 0.1 mm in all cases, depending somewhat on the resolution of input CT and fluoroscopy images. The cadaver experiments illustrated the tradeoff between robustness and computation time, yielding a success rate of 99.993% in vertebral labeling (with ‘success’ defined as PDE <5 mm) using 1,718 664 ± 96 582 function evaluations computed in 54.0 ± 3.5 s on a mid-range GPU (nVidia, GeForce GTX690). Parameters yielding a faster search (e.g., fewer multi-starts) reduced robustness under conditions of large deformation and poor initialization (99.535% success for the same data registered in 13.1 s), but given good initialization (e.g., ±5 mm, assuming a robust

Robust procedures in chemometrics

DEFF Research Database (Denmark)

Kotwa, Ewelina

properties of the analysed data. The broad theoretical background of robust procedures was given as a very useful supplement to the classical methods, and a new tool, based on robust PCA, aiming at identifying Rayleigh and Raman scatters in excitation-mission (EEM) data was developed. The results show...

Robust canonical correlations: A comparative study

OpenAIRE

Branco, JA; Croux, Christophe; Filzmoser, P; Oliveira, MR

2005-01-01

Several approaches for robust canonical correlation analysis will be presented and discussed. A first method is based on the definition of canonical correlation analysis as looking for linear combinations of two sets of variables having maximal (robust) correlation. A second method is based on alternating robust regressions. These methods axe discussed in detail and compared with the more traditional approach to robust canonical correlation via covariance matrix estimates. A simulation study ...

Robust surface registration using N-points approximate congruent sets

Directory of Open Access Journals (Sweden)

Yao Jian

2011-01-01

Full Text Available Abstract Scans acquired by 3D sensors are typically represented in a local coordinate system. When multiple scans, taken from different locations, represent the same scene these must be registered to a common reference frame. We propose a fast and robust registration approach to automatically align two scans by finding two sets of N-points, that are approximately congruent under rigid transformation and leading to a good estimate of the transformation between their corresponding point clouds. Given two scans, our algorithm randomly searches for the best sets of congruent groups of points using a RANSAC-based approach. To successfully and reliably align two scans when there is only a small overlap, we improve the basic RANSAC random selection step by employing a weight function that approximates the probability of each pair of points in one scan to match one pair in the other. The search time to find pairs of congruent sets of N-points is greatly reduced by employing a fast search codebook based on both binary and multi-dimensional lookup tables. Moreover, we introduce a novel indicator of the overlapping region quality which is used to verify the estimated rigid transformation and to improve the alignment robustness. Our framework is general enough to incorporate and efficiently combine different point descriptors derived from geometric and texture-based feature points or scene geometrical characteristics. We also present a method to improve the matching effectiveness of texture feature descriptors by extracting them from an atlas of rectified images recovered from the scan reflectance image. Our algorithm is robust with respect to different sampling densities and also resilient to noise and outliers. We demonstrate its robustness and efficiency on several challenging scan datasets with varying degree of noise, outliers, extent of overlap, acquired from indoor and outdoor scenarios.

A block matching-based registration algorithm for localization of locally advanced lung tumors

Energy Technology Data Exchange (ETDEWEB)

Robertson, Scott P.; Weiss, Elisabeth; Hugo, Geoffrey D., E-mail: gdhugo@vcu.edu [Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, 23298 (United States)

2014-04-15

Purpose: To implement and evaluate a block matching-based registration (BMR) algorithm for locally advanced lung tumor localization during image-guided radiotherapy. Methods: Small (1 cm{sup 3}), nonoverlapping image subvolumes (“blocks”) were automatically identified on the planning image to cover the tumor surface using a measure of the local intensity gradient. Blocks were independently and automatically registered to the on-treatment image using a rigid transform. To improve speed and robustness, registrations were performed iteratively from coarse to fine image resolution. At each resolution, all block displacements having a near-maximum similarity score were stored. From this list, a single displacement vector for each block was iteratively selected which maximized the consistency of displacement vectors across immediately neighboring blocks. These selected displacements were regularized using a median filter before proceeding to registrations at finer image resolutions. After evaluating all image resolutions, the global rigid transform of the on-treatment image was computed using a Procrustes analysis, providing the couch shift for patient setup correction. This algorithm was evaluated for 18 locally advanced lung cancer patients, each with 4–7 weekly on-treatment computed tomography scans having physician-delineated gross tumor volumes. Volume overlap (VO) and border displacement errors (BDE) were calculated relative to the nominal physician-identified targets to establish residual error after registration. Results: Implementation of multiresolution registration improved block matching accuracy by 39% compared to registration using only the full resolution images. By also considering multiple potential displacements per block, initial errors were reduced by 65%. Using the final implementation of the BMR algorithm, VO was significantly improved from 77% ± 21% (range: 0%–100%) in the initial bony alignment to 91% ± 8% (range: 56%–100%;p < 0

A block matching-based registration algorithm for localization of locally advanced lung tumors

International Nuclear Information System (INIS)

Robertson, Scott P.; Weiss, Elisabeth; Hugo, Geoffrey D.

2014-01-01

Purpose: To implement and evaluate a block matching-based registration (BMR) algorithm for locally advanced lung tumor localization during image-guided radiotherapy. Methods: Small (1 cm 3 ), nonoverlapping image subvolumes (“blocks”) were automatically identified on the planning image to cover the tumor surface using a measure of the local intensity gradient. Blocks were independently and automatically registered to the on-treatment image using a rigid transform. To improve speed and robustness, registrations were performed iteratively from coarse to fine image resolution. At each resolution, all block displacements having a near-maximum similarity score were stored. From this list, a single displacement vector for each block was iteratively selected which maximized the consistency of displacement vectors across immediately neighboring blocks. These selected displacements were regularized using a median filter before proceeding to registrations at finer image resolutions. After evaluating all image resolutions, the global rigid transform of the on-treatment image was computed using a Procrustes analysis, providing the couch shift for patient setup correction. This algorithm was evaluated for 18 locally advanced lung cancer patients, each with 4–7 weekly on-treatment computed tomography scans having physician-delineated gross tumor volumes. Volume overlap (VO) and border displacement errors (BDE) were calculated relative to the nominal physician-identified targets to establish residual error after registration. Results: Implementation of multiresolution registration improved block matching accuracy by 39% compared to registration using only the full resolution images. By also considering multiple potential displacements per block, initial errors were reduced by 65%. Using the final implementation of the BMR algorithm, VO was significantly improved from 77% ± 21% (range: 0%–100%) in the initial bony alignment to 91% ± 8% (range: 56%–100%;p < 0.001). Left

Illumination robust face recognition using spatial adaptive shadow compensation based on face intensity prior

Science.gov (United States)

Hsieh, Cheng-Ta; Huang, Kae-Horng; Lee, Chang-Hsing; Han, Chin-Chuan; Fan, Kuo-Chin

2017-12-01

Robust face recognition under illumination variations is an important and challenging task in a face recognition system, particularly for face recognition in the wild. In this paper, a face image preprocessing approach, called spatial adaptive shadow compensation (SASC), is proposed to eliminate shadows in the face image due to different lighting directions. First, spatial adaptive histogram equalization (SAHE), which uses face intensity prior model, is proposed to enhance the contrast of each local face region without generating visible noises in smooth face areas. Adaptive shadow compensation (ASC), which performs shadow compensation in each local image block, is then used to produce a wellcompensated face image appropriate for face feature extraction and recognition. Finally, null-space linear discriminant analysis (NLDA) is employed to extract discriminant features from SASC compensated images. Experiments performed on the Yale B, Yale B extended, and CMU PIE face databases have shown that the proposed SASC always yields the best face recognition accuracy. That is, SASC is more robust to face recognition under illumination variations than other shadow compensation approaches.

Written-in conductive patterns on robust graphene oxide biopaper by electrochemical microstamping.

Science.gov (United States)

Hu, Kesong; Tolentino, Lorenzo S; Kulkarni, Dhaval D; Ye, Chunhong; Kumar, Satish; Tsukruk, Vladimir V

2013-12-16

The silk road: By employing silk fibroin as a binder between graphene oxide films and aluminum foil for a facile, highly localized reduction process, conductive paper is reinvented. The flexible, robust biographene papers have high toughness and electrical conductivity. This electrochemical written-in approach is readily applicable for the fabrication of conductive patterned papers with complex circuitries. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gabor Weber Local Descriptor for Bovine Iris Recognition

OpenAIRE

Sun, Shengnan; Zhao, Lindu; Yang, Shicai

2013-01-01

Iris recognition is a robust biometric technology. This paper proposes a novel local descriptor for bovine iris recognition, named Gabor Weber local descriptor (GWLD). We first compute the Gabor magnitude maps for the input bovine iris image, and then calculate the differential excitation and orientation for each pixel over each Gabor magnitude map. After that, we use these differential excitations and orientations to construct the GWLD histogram representation. Finally, histogram intersectio...

Nonlinear decentralized robust governor control for hydroturbine-generator sets in multi-machine power systems

Energy Technology Data Exchange (ETDEWEB)

Qiang Lu; Yusong Sun; Yuanzhang Sun [Tsinghua University, Beijing (China). Dept. of Electrical Engineering; Felix F Wu; Yixin Ni [University of Hong Kong (China). Dept. of Electrical and Electronic Engineering; Yokoyama, Akihiko [University of Tokyo (Japan). Dept. of Electrical Engineering; Goto, Masuo; Konishi, Hiroo [Hitachi Ltd., Tokyo (Japan). Power System Div.

2004-06-01

A novel nonlinear decentralized robust governor control for hydroturbine-generator sets in multi-machine power systems is suggested in this paper. The nonelastic water hammer effect and disturbances are considered in the modeling. The advanced differential geometry theory, nonlinear robust control theory and the dynamic feedback method are combined to solve the problem. The nonlinear decentralized robust control law for the speed governor of hydroturbine-generators has been derived. The input signals to the proposed controller are all local measurements and independent to the system parameters. The derived control law guarantees the integrated system stability with disturbance attenuation, which is significant to the real power system application. Computer tests on an 8-machine, 36-bus power system show clearly the effectiveness of the new control strategy in transient stability enhancement and disturbance attenuation. The computer test results based on the suggested controller are compared favorably with those based on the conventional linear governor control. (author)

Detection of heart beats in multimodal data: a robust beat-to-beat interval estimation approach.

Science.gov (United States)

Antink, Christoph Hoog; Brüser, Christoph; Leonhardt, Steffen

2015-08-01

The heart rate and its variability play a vital role in the continuous monitoring of patients, especially in the critical care unit. They are commonly derived automatically from the electrocardiogram as the interval between consecutive heart beat. While their identification by QRS-complexes is straightforward under ideal conditions, the exact localization can be a challenging task if the signal is severely contaminated with noise and artifacts. At the same time, other signals directly related to cardiac activity are often available. In this multi-sensor scenario, methods of multimodal sensor-fusion allow the exploitation of redundancies to increase the accuracy and robustness of beat detection.In this paper, an algorithm for the robust detection of heart beats in multimodal data is presented. Classic peak-detection is augmented by robust multi-channel, multimodal interval estimation to eliminate false detections and insert missing beats. This approach yielded a score of 90.70 and was thus ranked third place in the PhysioNet/Computing in Cardiology Challenge 2014: Robust Detection of Heart Beats in Muthmodal Data follow-up analysis.In the future, the robust beat-to-beat interval estimator may directly be used for the automated processing of multimodal patient data for applications such as diagnosis support and intelligent alarming.

Optogenetic Activation of the Sensorimotor Cortex Reveals "Local Inhibitory and Global Excitatory" Inputs to the Basal Ganglia.

Science.gov (United States)

Ozaki, Mitsunori; Sano, Hiromi; Sato, Shigeki; Ogura, Mitsuhiro; Mushiake, Hajime; Chiken, Satomi; Nakao, Naoyuki; Nambu, Atsushi

2017-12-01

To understand how information from different cortical areas is integrated and processed through the cortico-basal ganglia pathways, we used optogenetics to systematically stimulate the sensorimotor cortex and examined basal ganglia activity. We utilized Thy1-ChR2-YFP transgenic mice, in which channelrhodopsin 2 is robustly expressed in layer V pyramidal neurons. We applied light spots to the sensorimotor cortex in a grid pattern and examined neuronal responses in the globus pallidus (GP) and entopeduncular nucleus (EPN), which are the relay and output nuclei of the basal ganglia, respectively. Light stimulation typically induced a triphasic response composed of early excitation, inhibition, and late excitation in GP/EPN neurons. Other response patterns lacking 1 or 2 of the components were also observed. The distribution of the cortical sites whose stimulation induced a triphasic response was confined, whereas stimulation of the large surrounding areas induced early and late excitation without inhibition. Our results suggest that cortical inputs to the GP/EPN are organized in a "local inhibitory and global excitatory" manner. Such organization seems to be the neuronal basis for information processing through the cortico-basal ganglia pathways, that is, releasing and terminating necessary information at an appropriate timing, while simultaneously suppressing other unnecessary information. © The Author 2017. Published by Oxford University Press.

Efficient and robust model-to-image alignment using 3D scale-invariant features.

Science.gov (United States)

Toews, Matthew; Wells, William M

2013-04-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.

Radioresistance of intermediate TCR cells and their localization in the body of mice revealed by irradiation

International Nuclear Information System (INIS)

Kimura, Motohiko; Watanabe, Hisami; Ohtsuka, Kazuo; Iiai, Tsuneo; Tsuchida, Masanori; Sato, Shotaro; Abo, Toru

1993-01-01

Extrathymic generation of T cells in the liver and in the intestine was recently demonstrated. We investigated herein whether such T cells, especially those in the liver, are present in other organs of mice. This investigation is possible employing our recently introduced method with which even a minor proportion of extrathymic, intermediate T-cell receptor (TCR) cells in organs other than the liver can be identified. Intermediate TCR cells expressed higher levels of IL-2Rβ and lymphocyte function-associated antigen-1 (LFA-1) than bright TCR cells (i.e., T cells of thymic origin) as revealed by two-color staining. Although intermediate TCR cells were present at a small proportion in the spleen and thymus, they predominated in these organs after irradiation (9 Gy) and bone marrow reconstitution, or after low dose irradiation (6 Gy). This was due to that intermediate TCR cells were relatively radioresistant, whereas bright TCR cells were radiosensitive. Microscopic observation and immunochemical staining showed that intermediate TCR cells in the spleen localized in the red pulp and those in the thymus localized in the medulla. These intermediate TCR cells displayed a large light scatter, similar to such cells in the liver. The present results suggest that intermediate TCR cells may proliferate at multiple sites in the body. (author)

Robust plasmonic substrates

DEFF Research Database (Denmark)

Kostiučenko, Oksana; Fiutowski, Jacek; Tamulevicius, Tomas

2014-01-01

Robustness is a key issue for the applications of plasmonic substrates such as tip-enhanced Raman spectroscopy, surface-enhanced spectroscopies, enhanced optical biosensing, optical and optoelectronic plasmonic nanosensors and others. A novel approach for the fabrication of robust plasmonic...... substrates is presented, which relies on the coverage of gold nanostructures with diamond-like carbon (DLC) thin films of thicknesses 25, 55 and 105 nm. DLC thin films were grown by direct hydrocarbon ion beam deposition. In order to find the optimum balance between optical and mechanical properties...

A robust standard deviation control chart

NARCIS (Netherlands)

Schoonhoven, M.; Does, R.J.M.M.

2012-01-01

This article studies the robustness of Phase I estimators for the standard deviation control chart. A Phase I estimator should be efficient in the absence of contaminations and resistant to disturbances. Most of the robust estimators proposed in the literature are robust against either diffuse

A Hybrid Interval-Robust Optimization Model for Water Quality Management.

Science.gov (United States)

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-05-01

In water quality management problems, uncertainties may exist in many system components and pollution-related processes ( i.e. , random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval-robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements.

A Hybrid Interval–Robust Optimization Model for Water Quality Management

Science.gov (United States)

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-01-01

Abstract In water quality management problems, uncertainties may exist in many system components and pollution-related processes (i.e., random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval–robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements. PMID:23922495

Robust neural network with applications to credit portfolio data analysis.

Science.gov (United States)

Feng, Yijia; Li, Runze; Sudjianto, Agus; Zhang, Yiyun

2010-01-01

In this article, we study nonparametric conditional quantile estimation via neural network structure. We proposed an estimation method that combines quantile regression and neural network (robust neural network, RNN). It provides good smoothing performance in the presence of outliers and can be used to construct prediction bands. A Majorization-Minimization (MM) algorithm was developed for optimization. Monte Carlo simulation study is conducted to assess the performance of RNN. Comparison with other nonparametric regression methods (e.g., local linear regression and regression splines) in real data application demonstrate the advantage of the newly proposed procedure.

DNA markers reveal genetic structure and localized diversity of ...

African Journals Online (AJOL)

uqhdesma

2016-10-12

Oct 12, 2016 ... STRUCTURE analysis revealed 4 clusters of genetically ..... 10000 cycles and 50000 Markov Chain Monte Carlo (MCMC) iterations and 10 replicate runs performed for each K value to ..... WL, Lee M, Porter K (2000). Genetic ...

Robust sampling-sourced numerical retrieval algorithm for optical energy loss function based on log–log mesh optimization and local monotonicity preserving Steffen spline

Energy Technology Data Exchange (ETDEWEB)

Maglevanny, I.I., E-mail: sianko@list.ru [Volgograd State Social Pedagogical University, 27 Lenin Avenue, Volgograd 400131 (Russian Federation); Smolar, V.A. [Volgograd State Technical University, 28 Lenin Avenue, Volgograd 400131 (Russian Federation)

2016-01-15

We introduce a new technique of interpolation of the energy-loss function (ELF) in solids sampled by empirical optical spectra. Finding appropriate interpolation methods for ELFs poses several challenges. The sampled ELFs are usually very heterogeneous, can originate from various sources thus so called “data gaps” can appear, and significant discontinuities and multiple high outliers can be present. As a result an interpolation based on those data may not perform well at predicting reasonable physical results. Reliable interpolation tools, suitable for ELF applications, should therefore satisfy several important demands: accuracy and predictive power, robustness and computational efficiency, and ease of use. We examined the effect on the fitting quality due to different interpolation schemes with emphasis on ELF mesh optimization procedures and we argue that the optimal fitting should be based on preliminary log–log scaling data transforms by which the non-uniformity of sampled data distribution may be considerably reduced. The transformed data are then interpolated by local monotonicity preserving Steffen spline. The result is a piece-wise smooth fitting curve with continuous first-order derivatives that passes through all data points without spurious oscillations. Local extrema can occur only at grid points where they are given by the data, but not in between two adjacent grid points. It is found that proposed technique gives the most accurate results and also that its computational time is short. Thus, it is feasible using this simple method to address practical problems associated with interaction between a bulk material and a moving electron. A compact C++ implementation of our algorithm is also presented.

Robust sampling-sourced numerical retrieval algorithm for optical energy loss function based on log–log mesh optimization and local monotonicity preserving Steffen spline

International Nuclear Information System (INIS)

Maglevanny, I.I.; Smolar, V.A.

2016-01-01

We introduce a new technique of interpolation of the energy-loss function (ELF) in solids sampled by empirical optical spectra. Finding appropriate interpolation methods for ELFs poses several challenges. The sampled ELFs are usually very heterogeneous, can originate from various sources thus so called “data gaps” can appear, and significant discontinuities and multiple high outliers can be present. As a result an interpolation based on those data may not perform well at predicting reasonable physical results. Reliable interpolation tools, suitable for ELF applications, should therefore satisfy several important demands: accuracy and predictive power, robustness and computational efficiency, and ease of use. We examined the effect on the fitting quality due to different interpolation schemes with emphasis on ELF mesh optimization procedures and we argue that the optimal fitting should be based on preliminary log–log scaling data transforms by which the non-uniformity of sampled data distribution may be considerably reduced. The transformed data are then interpolated by local monotonicity preserving Steffen spline. The result is a piece-wise smooth fitting curve with continuous first-order derivatives that passes through all data points without spurious oscillations. Local extrema can occur only at grid points where they are given by the data, but not in between two adjacent grid points. It is found that proposed technique gives the most accurate results and also that its computational time is short. Thus, it is feasible using this simple method to address practical problems associated with interaction between a bulk material and a moving electron. A compact C++ implementation of our algorithm is also presented.

Robustness: confronting lessons from physics and biology.

Science.gov (United States)

Lesne, Annick

2008-11-01

The term robustness is encountered in very different scientific fields, from engineering and control theory to dynamical systems to biology. The main question addressed herein is whether the notion of robustness and its correlates (stability, resilience, self-organisation) developed in physics are relevant to biology, or whether specific extensions and novel frameworks are required to account for the robustness properties of living systems. To clarify this issue, the different meanings covered by this unique term are discussed; it is argued that they crucially depend on the kind of perturbations that a robust system should by definition withstand. Possible mechanisms underlying robust behaviours are examined, either encountered in all natural systems (symmetries, conservation laws, dynamic stability) or specific to biological systems (feedbacks and regulatory networks). Special attention is devoted to the (sometimes counterintuitive) interrelations between robustness and noise. A distinction between dynamic selection and natural selection in the establishment of a robust behaviour is underlined. It is finally argued that nested notions of robustness, relevant to different time scales and different levels of organisation, allow one to reconcile the seemingly contradictory requirements for robustness and adaptability in living systems.

Formation of Robust Multi-Agent Networks through Self-Organizing Random Regular Graphs

KAUST Repository

Yasin Yazicioǧlu, A.; Egerstedt, Magnus; Shamma, Jeff S.

2015-01-01

Multi-Agent networks are often modeled as interaction graphs, where the nodes represent the agents and the edges denote some direct interactions. The robustness of a multi-Agent network to perturbations such as failures, noise, or malicious attacks largely depends on the corresponding graph. In many applications, networks are desired to have well-connected interaction graphs with relatively small number of links. One family of such graphs is the random regular graphs. In this paper, we present a decentralized scheme for transforming any connected interaction graph with a possibly non-integer average degree of k into a connected random m-regular graph for some m ϵ [k+k ] 2. Accordingly, the agents improve the robustness of the network while maintaining a similar number of links as the initial configuration by locally adding or removing some edges. © 2015 IEEE.

Formation of Robust Multi-Agent Networks through Self-Organizing Random Regular Graphs

KAUST Repository

Yasin Yazicioǧlu, A.

2015-11-25

Multi-Agent networks are often modeled as interaction graphs, where the nodes represent the agents and the edges denote some direct interactions. The robustness of a multi-Agent network to perturbations such as failures, noise, or malicious attacks largely depends on the corresponding graph. In many applications, networks are desired to have well-connected interaction graphs with relatively small number of links. One family of such graphs is the random regular graphs. In this paper, we present a decentralized scheme for transforming any connected interaction graph with a possibly non-integer average degree of k into a connected random m-regular graph for some m ϵ [k+k ] 2. Accordingly, the agents improve the robustness of the network while maintaining a similar number of links as the initial configuration by locally adding or removing some edges. © 2015 IEEE.

Application of robust fuzzy control in power control of nuclear reactor

International Nuclear Information System (INIS)

Liu Lei; Luan Xiuchun; Jin Guangyuan; Yu Tao; Rao Su

2013-01-01

Robust-fuzzy controller based on T-S fuzzy model was designed for real-time controlling of nuclear reactor power and adapting to the load changing of power grid. Local controller was designed by means of state feedback technique, and the global controller was designed by parallel distributed compensation (PDC) method. The result of solving linear matrix inequalities (LMI) proves that this controller is stable. The simulation shows that the nuclear power can be well controlled in three typical conditions by this controller. (authors)

Biometric feature embedding using robust steganography technique

Science.gov (United States)

Rashid, Rasber D.; Sellahewa, Harin; Jassim, Sabah A.

2013-05-01

This paper is concerned with robust steganographic techniques to hide and communicate biometric data in mobile media objects like images, over open networks. More specifically, the aim is to embed binarised features extracted using discrete wavelet transforms and local binary patterns of face images as a secret message in an image. The need for such techniques can arise in law enforcement, forensics, counter terrorism, internet/mobile banking and border control. What differentiates this problem from normal information hiding techniques is the added requirement that there should be minimal effect on face recognition accuracy. We propose an LSB-Witness embedding technique in which the secret message is already present in the LSB plane but instead of changing the cover image LSB values, the second LSB plane will be changed to stand as a witness/informer to the receiver during message recovery. Although this approach may affect the stego quality, it is eliminating the weakness of traditional LSB schemes that is exploited by steganalysis techniques for LSB, such as PoV and RS steganalysis, to detect the existence of secrete message. Experimental results show that the proposed method is robust against PoV and RS attacks compared to other variants of LSB. We also discussed variants of this approach and determine capacity requirements for embedding face biometric feature vectors while maintain accuracy of face recognition.

Integrated analysis of multiple data sources reveals modular structure of biological networks

International Nuclear Information System (INIS)

Lu Hongchao; Shi Baochen; Wu Gaowei; Zhang Yong; Zhu Xiaopeng; Zhang Zhihua; Liu Changning; Zhao, Yi; Wu Tao; Wang Jie; Chen Runsheng

2006-01-01

It has been a challenging task to integrate high-throughput data into investigations of the systematic and dynamic organization of biological networks. Here, we presented a simple hierarchical clustering algorithm that goes a long way to achieve this aim. Our method effectively reveals the modular structure of the yeast protein-protein interaction network and distinguishes protein complexes from functional modules by integrating high-throughput protein-protein interaction data with the added subcellular localization and expression profile data. Furthermore, we take advantage of the detected modules to provide a reliably functional context for the uncharacterized components within modules. On the other hand, the integration of various protein-protein association information makes our method robust to false-positives, especially for derived protein complexes. More importantly, this simple method can be extended naturally to other types of data fusion and provides a framework for the study of more comprehensive properties of the biological network and other forms of complex networks

Assessing a robust ensemble-based Kalman filter for efficient ecosystem data assimilation of the Cretan Sea

KAUST Repository

Triantafyllou, George N.; Hoteit, Ibrahim; Luo, Xiaodong; Tsiaras, Kostas P.; Petihakis, George

2013-01-01

An application of an ensemble-based robust filter for data assimilation into an ecosystem model of the Cretan Sea is presented and discussed. The ecosystem model comprises two on-line coupled sub-models: the Princeton Ocean Model (POM) and the European Regional Seas Ecosystem Model (ERSEM). The filtering scheme is based on the Singular Evolutive Interpolated Kalman (SEIK) filter which is implemented with a time-local H∞ filtering strategy to enhance robustness and performances during periods of strong ecosystem variability. Assimilation experiments in the Cretan Sea indicate that robustness can be achieved in the SEIK filter by introducing an adaptive inflation scheme of the modes of the filter error covariance matrix. Twin-experiments are performed to evaluate the performance of the assimilation system and to study the benefits of using robust filtering in an ensemble filtering framework. Pseudo-observations of surface chlorophyll, extracted from a model reference run, were assimilated every two days. Simulation results suggest that the adaptive inflation scheme significantly improves the behavior of the SEIK filter during periods of strong ecosystem variability. © 2012 Elsevier B.V.

Assessing a robust ensemble-based Kalman filter for efficient ecosystem data assimilation of the Cretan Sea

KAUST Repository

Triantafyllou, George N.

2013-09-01

An application of an ensemble-based robust filter for data assimilation into an ecosystem model of the Cretan Sea is presented and discussed. The ecosystem model comprises two on-line coupled sub-models: the Princeton Ocean Model (POM) and the European Regional Seas Ecosystem Model (ERSEM). The filtering scheme is based on the Singular Evolutive Interpolated Kalman (SEIK) filter which is implemented with a time-local H∞ filtering strategy to enhance robustness and performances during periods of strong ecosystem variability. Assimilation experiments in the Cretan Sea indicate that robustness can be achieved in the SEIK filter by introducing an adaptive inflation scheme of the modes of the filter error covariance matrix. Twin-experiments are performed to evaluate the performance of the assimilation system and to study the benefits of using robust filtering in an ensemble filtering framework. Pseudo-observations of surface chlorophyll, extracted from a model reference run, were assimilated every two days. Simulation results suggest that the adaptive inflation scheme significantly improves the behavior of the SEIK filter during periods of strong ecosystem variability. © 2012 Elsevier B.V.

A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty

Directory of Open Access Journals (Sweden)

Maryam Rahafrooz

2016-09-01

Full Text Available In this paper, a novel multi-objective robust possibilistic programming model is proposed, which simultaneously considers maximizing the distributive justice in relief distribution, minimizing the risk of relief distribution, and minimizing the total logistics costs. To effectively cope with the uncertainties of the after-disaster environment, the uncertain parameters of the proposed model are considered in the form of fuzzy trapezoidal numbers. The proposed model not only considers relief commodities priority and demand points priority in relief distribution, but also considers the difference between the pre-disaster and post-disaster supply abilities of the suppliers. In order to solve the proposed model, the LP-metric and the improved augmented ε-constraint methods are used. Second, a set of test problems are designed to evaluate the effectiveness of the proposed robust model against its equivalent deterministic form, which reveales the capabilities of the robust model. Finally, to illustrate the performance of the proposed robust model, a seismic region of northwestern Iran (East Azerbaijan is selected as a case study to model its relief logistics in the face of future earthquakes. This investigation indicates the usefulness of the proposed model in the field of crisis.

Impact of self-healing capability on network robustness

Science.gov (United States)

Shang, Yilun

2015-04-01

A wide spectrum of real-life systems ranging from neurons to botnets display spontaneous recovery ability. Using the generating function formalism applied to static uncorrelated random networks with arbitrary degree distributions, the microscopic mechanism underlying the depreciation-recovery process is characterized and the effect of varying self-healing capability on network robustness is revealed. It is found that the self-healing capability of nodes has a profound impact on the phase transition in the emergence of percolating clusters, and that salient difference exists in upholding network integrity under random failures and intentional attacks. The results provide a theoretical framework for quantitatively understanding the self-healing phenomenon in varied complex systems.

Infinitely robust order and local order-parameter tulips in Apollonian networks with quenched disorder

Science.gov (United States)

Kaplan, C. Nadir; Hinczewski, Michael; Berker, A. Nihat

2009-06-01

For a variety of quenched random spin systems on an Apollonian network, including ferromagnetic and antiferromagnetic bond percolation and the Ising spin glass, we find the persistence of ordered phases up to infinite temperature over the entire range of disorder. We develop a renormalization-group technique that yields highly detailed information, including the exact distributions of local magnetizations and local spin-glass order parameters, which turn out to exhibit, as function of temperature, complex and distinctive tulip patterns.

Robust AIC with High Breakdown Scale Estimate

Directory of Open Access Journals (Sweden)

Shokrya Saleh

2014-01-01

Full Text Available Akaike Information Criterion (AIC based on least squares (LS regression minimizes the sum of the squared residuals; LS is sensitive to outlier observations. Alternative criterion, which is less sensitive to outlying observation, has been proposed; examples are robust AIC (RAIC, robust Mallows Cp (RCp, and robust Bayesian information criterion (RBIC. In this paper, we propose a robust AIC by replacing the scale estimate with a high breakdown point estimate of scale. The robustness of the proposed methods is studied through its influence function. We show that, the proposed robust AIC is effective in selecting accurate models in the presence of outliers and high leverage points, through simulated and real data examples.

Methodology in robust and nonparametric statistics

CERN Document Server

Jurecková, Jana; Picek, Jan

2012-01-01

Introduction and SynopsisIntroductionSynopsisPreliminariesIntroductionInference in Linear ModelsRobustness ConceptsRobust and Minimax Estimation of LocationClippings from Probability and Asymptotic TheoryProblemsRobust Estimation of Location and RegressionIntroductionM-EstimatorsL-EstimatorsR-EstimatorsMinimum Distance and Pitman EstimatorsDifferentiable Statistical FunctionsProblemsAsymptotic Representations for L-Estimators

Histone Variant HTZ1 Shows Extensive Epistasis with, but Does Not Increase Robustness to, New Mutations

Science.gov (United States)

Richardson, Joshua B.; Uppendahl, Locke D.; Traficante, Maria K.; Levy, Sasha F.; Siegal, Mark L.

2013-01-01

Biological systems produce phenotypes that appear to be robust to perturbation by mutations and environmental variation. Prior studies identified genes that, when impaired, reveal previously cryptic genetic variation. This result is typically interpreted as evidence that the disrupted gene normally increases robustness to mutations, as such robustness would allow cryptic variants to accumulate. However, revelation of cryptic genetic variation is not necessarily evidence that a mutationally robust state has been made less robust. Demonstrating a difference in robustness requires comparing the ability of each state (with the gene perturbed or intact) to suppress the effects of new mutations. Previous studies used strains in which the existing genetic variation had been filtered by selection. Here, we use mutation accumulation (MA) lines that have experienced minimal selection, to test the ability of histone H2A.Z (HTZ1) to increase robustness to mutations in the yeast Saccharomyces cerevisiae. HTZ1, a regulator of chromatin structure and gene expression, represents a class of genes implicated in mutational robustness. It had previously been shown to increase robustness of yeast cell morphology to fluctuations in the external or internal microenvironment. We measured morphological variation within and among 79 MA lines with and without HTZ1. Analysis of within-line variation confirms that HTZ1 increases microenvironmental robustness. Analysis of between-line variation shows the morphological effects of eliminating HTZ1 to be highly dependent on the line, which implies that HTZ1 interacts with mutations that have accumulated in the lines. However, lines without HTZ1 are, as a group, not more phenotypically diverse than lines with HTZ1 present. The presence of HTZ1, therefore, does not confer greater robustness to mutations than its absence. Our results provide experimental evidence that revelation of cryptic genetic variation cannot be assumed to be caused by loss of

Histone variant HTZ1 shows extensive epistasis with, but does not increase robustness to, new mutations.

Directory of Open Access Journals (Sweden)

Joshua B Richardson

Full Text Available Biological systems produce phenotypes that appear to be robust to perturbation by mutations and environmental variation. Prior studies identified genes that, when impaired, reveal previously cryptic genetic variation. This result is typically interpreted as evidence that the disrupted gene normally increases robustness to mutations, as such robustness would allow cryptic variants to accumulate. However, revelation of cryptic genetic variation is not necessarily evidence that a mutationally robust state has been made less robust. Demonstrating a difference in robustness requires comparing the ability of each state (with the gene perturbed or intact to suppress the effects of new mutations. Previous studies used strains in which the existing genetic variation had been filtered by selection. Here, we use mutation accumulation (MA lines that have experienced minimal selection, to test the ability of histone H2A.Z (HTZ1 to increase robustness to mutations in the yeast Saccharomyces cerevisiae. HTZ1, a regulator of chromatin structure and gene expression, represents a class of genes implicated in mutational robustness. It had previously been shown to increase robustness of yeast cell morphology to fluctuations in the external or internal microenvironment. We measured morphological variation within and among 79 MA lines with and without HTZ1. Analysis of within-line variation confirms that HTZ1 increases microenvironmental robustness. Analysis of between-line variation shows the morphological effects of eliminating HTZ1 to be highly dependent on the line, which implies that HTZ1 interacts with mutations that have accumulated in the lines. However, lines without HTZ1 are, as a group, not more phenotypically diverse than lines with HTZ1 present. The presence of HTZ1, therefore, does not confer greater robustness to mutations than its absence. Our results provide experimental evidence that revelation of cryptic genetic variation cannot be assumed to be

Measuring streetscape complexity based on the statistics of local contrast and spatial frequency.

Directory of Open Access Journals (Sweden)

André Cavalcante

Full Text Available Streetscapes are basic urban elements which play a major role in the livability of a city. The visual complexity of streetscapes is known to influence how people behave in such built spaces. However, how and which characteristics of a visual scene influence our perception of complexity have yet to be fully understood. This study proposes a method to evaluate the complexity perceived in streetscapes based on the statistics of local contrast and spatial frequency. Here, 74 streetscape images from four cities, including daytime and nighttime scenes, were ranked for complexity by 40 participants. Image processing was then used to locally segment contrast and spatial frequency in the streetscapes. The statistics of these characteristics were extracted and later combined to form a single objective measure. The direct use of statistics revealed structural or morphological patterns in streetscapes related to the perception of complexity. Furthermore, in comparison to conventional measures of visual complexity, the proposed objective measure exhibits a higher correlation with the opinion of the participants. Also, the performance of this method is more robust regarding different time scenarios.

Robust Approaches to Forecasting

OpenAIRE

Jennifer Castle; David Hendry; Michael P. Clements

2014-01-01

We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods ar...

Robust media processing on programmable power-constrained systems

Science.gov (United States)

McVeigh, Jeff

2005-03-01

To achieve consumer-level quality, media systems must process continuous streams of audio and video data while maintaining exacting tolerances on sampling rate, jitter, synchronization, and latency. While it is relatively straightforward to design fixed-function hardware implementations to satisfy worst-case conditions, there is a growing trend to utilize programmable multi-tasking solutions for media applications. The flexibility of these systems enables support for multiple current and future media formats, which can reduce design costs and time-to-market. This paper provides practical engineering solutions to achieve robust media processing on such systems, with specific attention given to power-constrained platforms. The techniques covered in this article utilize the fundamental concepts of algorithm and software optimization, software/hardware partitioning, stream buffering, hierarchical prioritization, and system resource and power management. A novel enhancement to dynamically adjust processor voltage and frequency based on buffer fullness to reduce system power consumption is examined in detail. The application of these techniques is provided in a case study of a portable video player implementation based on a general-purpose processor running a non real-time operating system that achieves robust playback of synchronized H.264 video and MP3 audio from local storage and streaming over 802.11.

Theoretical Framework for Robustness Evaluation

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

2011-01-01

This paper presents a theoretical framework for evaluation of robustness of structural systems, incl. bridges and buildings. Typically modern structural design codes require that ‘the consequence of damages to structures should not be disproportional to the causes of the damages’. However, although...... the importance of robustness for structural design is widely recognized the code requirements are not specified in detail, which makes the practical use difficult. This paper describes a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines...

Robust portfolio selection under norm uncertainty

Directory of Open Access Journals (Sweden)

Lei Wang

2016-06-01

Full Text Available Abstract In this paper, we consider the robust portfolio selection problem which has a data uncertainty described by the ( p , w $(p,w$ -norm in the objective function. We show that the robust formulation of this problem is equivalent to a linear optimization problem. Moreover, we present some numerical results concerning our robust portfolio selection problem.

Robust state feedback controller design of STATCOM using chaotic optimization algorithm

Directory of Open Access Journals (Sweden)

Safari Amin

2010-01-01

Full Text Available In this paper, a new design technique for the design of robust state feedback controller for static synchronous compensator (STATCOM using Chaotic Optimization Algorithm (COA is presented. The design is formulated as an optimization problem which is solved by the COA. Since chaotic planning enjoys reliability, ergodicity and stochastic feature, the proposed technique presents chaos mapping using Lozi map chaotic sequences which increases its convergence rate. To ensure the robustness of the proposed damping controller, the design process takes into account a wide range of operating conditions and system configurations. The simulation results reveal that the proposed controller has an excellent capability in damping power system low frequency oscillations and enhances greatly the dynamic stability of the power systems. Moreover, the system performance analysis under different operating conditions shows that the phase based controller is superior compare to the magnitude based controller.

Robustness Recipes for Minimax Robust Optimization in Intensity Modulated Proton Therapy for Oropharyngeal Cancer Patients

Energy Technology Data Exchange (ETDEWEB)

Voort, Sebastian van der [Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam (Netherlands); Section of Nuclear Energy and Radiation Applications, Department of Radiation, Science and Technology, Delft University of Technology, Delft (Netherlands); Water, Steven van de [Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam (Netherlands); Perkó, Zoltán [Section of Nuclear Energy and Radiation Applications, Department of Radiation, Science and Technology, Delft University of Technology, Delft (Netherlands); Heijmen, Ben [Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam (Netherlands); Lathouwers, Danny [Section of Nuclear Energy and Radiation Applications, Department of Radiation, Science and Technology, Delft University of Technology, Delft (Netherlands); Hoogeman, Mischa, E-mail: m.hoogeman@erasmusmc.nl [Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam (Netherlands)

2016-05-01

Purpose: We aimed to derive a “robustness recipe” giving the range robustness (RR) and setup robustness (SR) settings (ie, the error values) that ensure adequate clinical target volume (CTV) coverage in oropharyngeal cancer patients for given gaussian distributions of systematic setup, random setup, and range errors (characterized by standard deviations of Σ, σ, and ρ, respectively) when used in minimax worst-case robust intensity modulated proton therapy (IMPT) optimization. Methods and Materials: For the analysis, contoured computed tomography (CT) scans of 9 unilateral and 9 bilateral patients were used. An IMPT plan was considered robust if, for at least 98% of the simulated fractionated treatments, 98% of the CTV received 95% or more of the prescribed dose. For fast assessment of the CTV coverage for given error distributions (ie, different values of Σ, σ, and ρ), polynomial chaos methods were used. Separate recipes were derived for the unilateral and bilateral cases using one patient from each group, and all 18 patients were included in the validation of the recipes. Results: Treatment plans for bilateral cases are intrinsically more robust than those for unilateral cases. The required RR only depends on the ρ, and SR can be fitted by second-order polynomials in Σ and σ. The formulas for the derived robustness recipes are as follows: Unilateral patients need SR = −0.15Σ{sup 2} + 0.27σ{sup 2} + 1.85Σ − 0.06σ + 1.22 and RR=3% for ρ = 1% and ρ = 2%; bilateral patients need SR = −0.07Σ{sup 2} + 0.19σ{sup 2} + 1.34Σ − 0.07σ + 1.17 and RR=3% and 4% for ρ = 1% and 2%, respectively. For the recipe validation, 2 plans were generated for each of the 18 patients corresponding to Σ = σ = 1.5 mm and ρ = 0% and 2%. Thirty-four plans had adequate CTV coverage in 98% or more of the simulated fractionated treatments; the remaining 2 had adequate coverage in 97.8% and 97.9%. Conclusions: Robustness recipes were derived that can

A novel binary shape context for 3D local surface description

Science.gov (United States)

Dong, Zhen; Yang, Bisheng; Liu, Yuan; Liang, Fuxun; Li, Bijun; Zang, Yufu

2017-08-01

3D local surface description is now at the core of many computer vision technologies, such as 3D object recognition, intelligent driving, and 3D model reconstruction. However, most of the existing 3D feature descriptors still suffer from low descriptiveness, weak robustness, and inefficiency in both time and memory. To overcome these challenges, this paper presents a robust and descriptive 3D Binary Shape Context (BSC) descriptor with high efficiency in both time and memory. First, a novel BSC descriptor is generated for 3D local surface description, and the performance of the BSC descriptor under different settings of its parameters is analyzed. Next, the descriptiveness, robustness, and efficiency in both time and memory of the BSC descriptor are evaluated and compared to those of several state-of-the-art 3D feature descriptors. Finally, the performance of the BSC descriptor for 3D object recognition is also evaluated on a number of popular benchmark datasets, and an urban-scene dataset is collected by a terrestrial laser scanner system. Comprehensive experiments demonstrate that the proposed BSC descriptor obtained high descriptiveness, strong robustness, and high efficiency in both time and memory and achieved high recognition rates of 94.8%, 94.1% and 82.1% on the considered UWA, Queen, and WHU datasets, respectively.

Gabor Weber Local Descriptor for Bovine Iris Recognition

Directory of Open Access Journals (Sweden)

Shengnan Sun

2013-01-01

Full Text Available Iris recognition is a robust biometric technology. This paper proposes a novel local descriptor for bovine iris recognition, named Gabor Weber local descriptor (GWLD. We first compute the Gabor magnitude maps for the input bovine iris image, and then calculate the differential excitation and orientation for each pixel over each Gabor magnitude map. After that, we use these differential excitations and orientations to construct the GWLD histogram representation. Finally, histogram intersection is adopted to measure the similarity between different GWLD histograms. The experimental results on the SEU bovine iris database verify the representation power of our proposed local descriptor.

Robust Proton Pencil Beam Scanning Treatment Planning for Rectal Cancer Radiation Therapy

International Nuclear Information System (INIS)

Blanco Kiely, Janid Patricia; White, Benjamin M.

2016-01-01

Purpose: To investigate, in a treatment plan design and robustness study, whether proton pencil beam scanning (PBS) has the potential to offer advantages, relative to interfraction uncertainties, over photon volumetric modulated arc therapy (VMAT) in a locally advanced rectal cancer patient population. Methods and Materials: Ten patients received a planning CT scan, followed by an average of 4 weekly offline CT verification CT scans, which were rigidly co-registered to the planning CT. Clinical PBS plans were generated on the planning CT, using a single-field uniform-dose technique with single-posterior and parallel-opposed (LAT) fields geometries. The VMAT plans were generated on the planning CT using 2 6-MV, 220° coplanar arcs. Clinical plans were forward-calculated on verification CTs to assess robustness relative to anatomic changes. Setup errors were assessed by forward-calculating clinical plans with a ±5-mm (left–right, anterior–posterior, superior–inferior) isocenter shift on the planning CT. Differences in clinical target volume and organ at risk dose–volume histogram (DHV) indicators between plans were tested for significance using an appropriate Wilcoxon test (P<.05). Results: Dosimetrically, PBS plans were statistically different from VMAT plans, showing greater organ at risk sparing. However, the bladder was statistically identical among LAT and VMAT plans. The clinical target volume coverage was statistically identical among all plans. The robustness test found that all DVH indicators for PBS and VMAT plans were robust, except the LAT's genitalia (V5, V35). The verification CT plans showed that all DVH indicators were robust. Conclusions: Pencil beam scanning plans were found to be as robust as VMAT plans relative to interfractional changes during treatment when posterior beam angles and appropriate range margins are used. Pencil beam scanning dosimetric gains in the bowel (V15, V20) over VMAT suggest that using PBS to treat rectal cancer

Robust Proton Pencil Beam Scanning Treatment Planning for Rectal Cancer Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Blanco Kiely, Janid Patricia, E-mail: jkiely@sas.upenn.edu; White, Benjamin M.

2016-05-01

Purpose: To investigate, in a treatment plan design and robustness study, whether proton pencil beam scanning (PBS) has the potential to offer advantages, relative to interfraction uncertainties, over photon volumetric modulated arc therapy (VMAT) in a locally advanced rectal cancer patient population. Methods and Materials: Ten patients received a planning CT scan, followed by an average of 4 weekly offline CT verification CT scans, which were rigidly co-registered to the planning CT. Clinical PBS plans were generated on the planning CT, using a single-field uniform-dose technique with single-posterior and parallel-opposed (LAT) fields geometries. The VMAT plans were generated on the planning CT using 2 6-MV, 220° coplanar arcs. Clinical plans were forward-calculated on verification CTs to assess robustness relative to anatomic changes. Setup errors were assessed by forward-calculating clinical plans with a ±5-mm (left–right, anterior–posterior, superior–inferior) isocenter shift on the planning CT. Differences in clinical target volume and organ at risk dose–volume histogram (DHV) indicators between plans were tested for significance using an appropriate Wilcoxon test (P<.05). Results: Dosimetrically, PBS plans were statistically different from VMAT plans, showing greater organ at risk sparing. However, the bladder was statistically identical among LAT and VMAT plans. The clinical target volume coverage was statistically identical among all plans. The robustness test found that all DVH indicators for PBS and VMAT plans were robust, except the LAT's genitalia (V5, V35). The verification CT plans showed that all DVH indicators were robust. Conclusions: Pencil beam scanning plans were found to be as robust as VMAT plans relative to interfractional changes during treatment when posterior beam angles and appropriate range margins are used. Pencil beam scanning dosimetric gains in the bowel (V15, V20) over VMAT suggest that using PBS to treat rectal

Implicit Active Contours Driven by Local and Global Image Fitting Energy for Image Segmentation and Target Localization

Directory of Open Access Journals (Sweden)

Xiaosheng Yu

2013-01-01

Full Text Available We propose a novel active contour model in a variational level set formulation for image segmentation and target localization. We combine a local image fitting term and a global image fitting term to drive the contour evolution. Our model can efficiently segment the images with intensity inhomogeneity with the contour starting anywhere in the image. In its numerical implementation, an efficient numerical schema is used to ensure sufficient numerical accuracy. We validated its effectiveness in numerous synthetic images and real images, and the promising experimental results show its advantages in terms of accuracy, efficiency, and robustness.

Robust Frequency Invariant Beamforming with Low Sidelobe for Speech Enhancement

Science.gov (United States)

Zhu, Yiting; Pan, Xiang

2018-01-01

Frequency invariant beamformers (FIBs) are widely used in speech enhancement and source localization. There are two traditional optimization methods for FIB design. The first one is convex optimization, which is simple but the frequency invariant characteristic of the beam pattern is poor with respect to frequency band of five octaves. The least squares (LS) approach using spatial response variation (SRV) constraint is another optimization method. Although, it can provide good frequency invariant property, it usually couldn’t be used in speech enhancement for its lack of weight norm constraint which is related to the robustness of a beamformer. In this paper, a robust wideband beamforming method with a constant beamwidth is proposed. The frequency invariant beam pattern is achieved by resolving an optimization problem of the SRV constraint to cover speech frequency band. With the control of sidelobe level, it is available for the frequency invariant beamformer (FIB) to prevent distortion of interference from the undesirable direction. The approach is completed in time-domain by placing tapped delay lines(TDL) and finite impulse response (FIR) filter at the output of each sensor which is more convenient than the Frost processor. By invoking the weight norm constraint, the robustness of the beamformer is further improved against random errors. Experiment results show that the proposed method has a constant beamwidth and almost the same white noise gain as traditional delay-and-sum (DAS) beamformer.

A theoretical and practical contribution to supply chain robustness:developing a schema for robustness in dyads

OpenAIRE

Durach, Christian F.

2016-01-01

Published in print by Universitätsverlag der TU Berlin, ISBN 978-3-7983-2812-9 (ISSN 1865-3170) This doctoral thesis develops four individual research studies on supply chain robustness. The overall goal of these studies is to develop a conceptual framework of supply chain robustness by consolidating current literature in the field, and, drawing on that framework, to construct a schema of determinants that facilitate robustness in buyer-supplier relationships. This research is motivated by...

Estimating organic, local, and other price premiums in the Hawaii fluid milk market.

Science.gov (United States)

Loke, Matthew K; Xu, Xun; Leung, PingSun

2015-04-01

With retail scanner data, we applied hedonic price modeling to explore price premiums for organic, local, and other product attributes of fluid milk in Hawaii. Within the context of revealed preference, this analysis of organic and local attributes, under a single unified framework, is significant, as research in this area is deficient in the existing literature. This paper finds both organic and local attributes delivered price premiums over imported, conventional, whole fluid milk. However, the estimated price premium for organic milk (24.6%) is significantly lower than findings in the existing literature. Likewise, the price premium for the local attribute is estimated at 17.4%, again substantially lower compared with an earlier, stated preference study in Hawaii. Beyond that, we estimated a robust price premium of 19.7% for nutritional benefits claimed. The magnitude of this estimated coefficient reinforces the notion that nutrition information on food is deemed beneficial and valuable. Finally, package size measures the influence of product weight. With each larger package size, the estimate led to a corresponding larger price discount. This result is consistent with the practice of weight discounting that retailers usually offer with fresh packaged food. Additionally, we estimated a fairly high Armington elasticity of substitution, which suggests a relatively high degree of substitution between local and imported fluid milk when their relative price changes. Overall, this study establishes price premiums for organic, local, and nutrition benefits claimed for fluid milk in Hawaii. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Position-Invariant Robust Features for Long-Term Recognition of Dynamic Outdoor Scenes

Science.gov (United States)

Kawewong, Aram; Tangruamsub, Sirinart; Hasegawa, Osamu

A novel Position-Invariant Robust Feature, designated as PIRF, is presented to address the problem of highly dynamic scene recognition. The PIRF is obtained by identifying existing local features (i.e. SIFT) that have a wide baseline visibility within a place (one place contains more than one sequential images). These wide-baseline visible features are then represented as a single PIRF, which is computed as an average of all descriptors associated with the PIRF. Particularly, PIRFs are robust against highly dynamical changes in scene: a single PIRF can be matched correctly against many features from many dynamical images. This paper also describes an approach to using these features for scene recognition. Recognition proceeds by matching an individual PIRF to a set of features from test images, with subsequent majority voting to identify a place with the highest matched PIRF. The PIRF system is trained and tested on 2000+ outdoor omnidirectional images and on COLD datasets. Despite its simplicity, PIRF offers a markedly better rate of recognition for dynamic outdoor scenes (ca. 90%) than the use of other features. Additionally, a robot navigation system based on PIRF (PIRF-Nav) can outperform other incremental topological mapping methods in terms of time (70% less) and memory. The number of PIRFs can be reduced further to reduce the time while retaining high accuracy, which makes it suitable for long-term recognition and localization.

Robust Pose Estimation using the SwissRanger SR-3000 Camera

DEFF Research Database (Denmark)

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

2007-01-01

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

Robust control design with MATLAB

CERN Document Server

Gu, Da-Wei; Konstantinov, Mihail M

2013-01-01

Robust Control Design with MATLAB® (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples from teaching-laboratory experiments, such as a two-wheeled, self-balancing robot, to complex systems like a flexible-link manipulator are given detailed presentation. All of these exercises are conducted using MATLAB® Robust Control Toolbox 3, Control System Toolbox and Simulink®. By sharing their experiences in industrial cases with minimum recourse to complicated theories and formulae, the authors convey essential ideas and useful insights into robust industrial control systems design using major H-infinity optimization and related methods allowing readers quickly to move on with their own challenges. The hands-on tutorial style of this text rests on an abundance of examples and features for the second edition: ·        rewritten and simplified presentation of theoretical and meth...

Robust Portfolio Optimization Using Pseudodistances

Science.gov (United States)

2015-01-01

The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature. PMID:26468948

Robust Portfolio Optimization Using Pseudodistances.

Science.gov (United States)

Toma, Aida; Leoni-Aubin, Samuela

2015-01-01

The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature.

International Conference on Robust Statistics 2015

CERN Document Server

Basu, Ayanendranath; Filzmoser, Peter; Mukherjee, Diganta

2016-01-01

This book offers a collection of recent contributions and emerging ideas in the areas of robust statistics presented at the International Conference on Robust Statistics 2015 (ICORS 2015) held in Kolkata during 12–16 January, 2015. The book explores the applicability of robust methods in other non-traditional areas which includes the use of new techniques such as skew and mixture of skew distributions, scaled Bregman divergences, and multilevel functional data methods; application areas being circular data models and prediction of mortality and life expectancy. The contributions are of both theoretical as well as applied in nature. Robust statistics is a relatively young branch of statistical sciences that is rapidly emerging as the bedrock of statistical analysis in the 21st century due to its flexible nature and wide scope. Robust statistics supports the application of parametric and other inference techniques over a broader domain than the strictly interpreted model scenarios employed in classical statis...

Robust T1-weighted structural brain imaging and morphometry at 7T using MP2RAGE.

Directory of Open Access Journals (Sweden)

Kieran R O'Brien

Full Text Available PURPOSE: To suppress the noise, by sacrificing some of the signal homogeneity for numerical stability, in uniform T1 weighted (T1w images obtained with the magnetization prepared 2 rapid gradient echoes sequence (MP2RAGE and to compare the clinical utility of these robust T1w images against the uniform T1w images. MATERIALS AND METHODS: 8 healthy subjects (29.0 ± 4.1 years; 6 Male, who provided written consent, underwent two scan sessions within a 24 hour period on a 7T head-only scanner. The uniform and robust T1w image volumes were calculated inline on the scanner. Two experienced radiologists qualitatively rated the images for: general image quality; 7T specific artefacts; and, local structure definition. Voxel-based and volume-based morphometry packages were used to compare the segmentation quality between the uniform and robust images. Statistical differences were evaluated by using a positive sided Wilcoxon rank test. RESULTS: The robust image suppresses background noise inside and outside the skull. The inhomogeneity introduced was ranked as mild. The robust image was significantly ranked higher than the uniform image for both observers (observer 1/2, p-value = 0.0006/0.0004. In particular, an improved delineation of the pituitary gland, cerebellar lobes was observed in the robust versus uniform T1w image. The reproducibility of the segmentation results between repeat scans improved (p-value = 0.0004 from an average volumetric difference across structures of ≈ 6.6% to ≈ 2.4% for the uniform image and robust T1w image respectively. CONCLUSIONS: The robust T1w image enables MP2RAGE to produce, clinically familiar T1w images, in addition to T1 maps, which can be readily used in uniform morphometry packages.

Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields

KAUST Repository

Wang, B.

2013-06-01

Analyzing critical points and their temporal evolutions plays a crucial role in understanding the behavior of vector fields. A key challenge is to quantify the stability of critical points: more stable points may represent more important phenomena or vice versa. The topological notion of robustness is a tool which allows us to quantify rigorously the stability of each critical point. Intuitively, the robustness of a critical point is the minimum amount of perturbation necessary to cancel it within a local neighborhood, measured under an appropriate metric. In this paper, we introduce a new analysis and visualization framework which enables interactive exploration of robustness of critical points for both stationary and time-varying 2D vector fields. This framework allows the end-users, for the first time, to investigate how the stability of a critical point evolves over time. We show that this depends heavily on the global properties of the vector field and that structural changes can correspond to interesting behavior. We demonstrate the practicality of our theories and techniques on several datasets involving combustion and oceanic eddy simulations and obtain some key insights regarding their stable and unstable features. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields

KAUST Repository

Wang, B.; Rosen, P.; Skraba, P.; Bhatia, H.; Pascucci, V.

2013-01-01

Analyzing critical points and their temporal evolutions plays a crucial role in understanding the behavior of vector fields. A key challenge is to quantify the stability of critical points: more stable points may represent more important phenomena or vice versa. The topological notion of robustness is a tool which allows us to quantify rigorously the stability of each critical point. Intuitively, the robustness of a critical point is the minimum amount of perturbation necessary to cancel it within a local neighborhood, measured under an appropriate metric. In this paper, we introduce a new analysis and visualization framework which enables interactive exploration of robustness of critical points for both stationary and time-varying 2D vector fields. This framework allows the end-users, for the first time, to investigate how the stability of a critical point evolves over time. We show that this depends heavily on the global properties of the vector field and that structural changes can correspond to interesting behavior. We demonstrate the practicality of our theories and techniques on several datasets involving combustion and oceanic eddy simulations and obtain some key insights regarding their stable and unstable features. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

Robustness of IPTV business models

NARCIS (Netherlands)

Bouwman, H.; Zhengjia, M.; Duin, P. van der; Limonard, S.

2008-01-01

The final stage in the STOF method is an evaluation of the robustness of the design, for which the method provides some guidelines. For many innovative services, the future holds numerous uncertainties, which makes evaluating the robustness of a business model a difficult task. In this chapter, we

Robust Design Impact Metrics: Measuring the effect of implementing and using Robust Design

DEFF Research Database (Denmark)

Ebro, Martin; Olesen, Jesper; Howard, Thomas J.

2014-01-01

Measuring the performance of an organisation’s product development process can be challenging due to the limited use of metrics in R&D. An organisation considering whether to use Robust Design as an integrated part of their development process may find it difficult to define whether it is relevant......, and afterwards measure the effect of having implemented it. This publication identifies and evaluates Robust Design-related metrics and finds that 2 metrics are especially useful: 1) Relative amount of R&D Resources spent after Design Verification and 2) Number of ‘change notes’ after Design Verification....... The metrics have been applied in a case company to test the assumptions made during the evaluation. It is concluded that the metrics are useful and relevant, but further work is necessary to make a proper overview and categorisation of different types of robustness related metrics....

Robust loss functions for boosting.

Science.gov (United States)

Kanamori, Takafumi; Takenouchi, Takashi; Eguchi, Shinto; Murata, Noboru

2007-08-01

Boosting is known as a gradient descent algorithm over loss functions. It is often pointed out that the typical boosting algorithm, Adaboost, is highly affected by outliers. In this letter, loss functions for robust boosting are studied. Based on the concept of robust statistics, we propose a transformation of loss functions that makes boosting algorithms robust against extreme outliers. Next, the truncation of loss functions is applied to contamination models that describe the occurrence of mislabels near decision boundaries. Numerical experiments illustrate that the proposed loss functions derived from the contamination models are useful for handling highly noisy data in comparison with other loss functions.

Robustness of airline route networks

Science.gov (United States)

Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David

2016-03-01

Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.

Error Control in Distributed Node Self-Localization

Directory of Open Access Journals (Sweden)

Ying Zhang

2008-03-01

Full Text Available Location information of nodes in an ad hoc sensor network is essential to many tasks such as routing, cooperative sensing, and service delivery. Distributed node self-localization is lightweight and requires little communication overhead, but often suffers from the adverse effects of error propagation. Unlike other localization papers which focus on designing elaborate localization algorithms, this paper takes a different perspective, focusing on the error propagation problem, addressing questions such as where localization error comes from and how it propagates from node to node. To prevent error from propagating and accumulating, we develop an error-control mechanism based on characterization of node uncertainties and discrimination between neighboring nodes. The error-control mechanism uses only local knowledge and is fully decentralized. Simulation results have shown that the active selection strategy significantly mitigates the effect of error propagation for both range and directional sensors. It greatly improves localization accuracy and robustness.

Robust control for a biaxial servo with time delay system based on adaptive tuning technique.

Science.gov (United States)

Chen, Tien-Chi; Yu, Chih-Hsien

2009-07-01

A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new network based cross-coupled control and adaptive tuning techniques are used together to cancel out the skew error. The conventional fixed gain PID cross-coupled controller (CCC) is replaced with the adaptive cross-coupled controller (ACCC) in the proposed control scheme to maintain biaxial servo system synchronization motion. Adaptive-tuning PID (APID) position and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. A delay-time compensator (DTC) with an adaptive controller was augmented to set the time delay element, effectively moving it outside the closed loop, enhancing the stability of the robust controlled system. This scheme provides strong robustness with respect to uncertain dynamics and disturbances. The simulation and experimental results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.

Multimodel Robust Control for Hydraulic Turbine

OpenAIRE

Osuský, Jakub; Števo, Stanislav

2014-01-01

The paper deals with the multimodel and robust control system design and their combination based on M-Δ structure. Controller design will be done in the frequency domain with nominal performance specified by phase margin. Hydraulic turbine model is analyzed as system with unstructured uncertainty, and robust stability condition is included in controller design. Multimodel and robust control approaches are presented in detail on hydraulic turbine model. Control design approaches are compared a...

Robust spike sorting of retinal ganglion cells tuned to spot stimuli.

Science.gov (United States)

Ghahari, Alireza; Badea, Tudor C

2016-08-01

We propose an automatic spike sorting approach for the data recorded from a microelectrode array during visual stimulation of wild type retinas with tiled spot stimuli. The approach first detects individual spikes per electrode by their signature local minima. With the mixture probability distribution of the local minima estimated afterwards, it applies a minimum-squared-error clustering algorithm to sort the spikes into different clusters. A template waveform for each cluster per electrode is defined, and a number of reliability tests are performed on it and its corresponding spikes. Finally, a divisive hierarchical clustering algorithm is used to deal with the correlated templates per cluster type across all the electrodes. According to the measures of performance of the spike sorting approach, it is robust even in the cases of recordings with low signal-to-noise ratio.

Detecting measurement-induced relative-position localization

International Nuclear Information System (INIS)

Knott, P A; Sindt, J; Dunningham, J A

2013-01-01

The theory of decoherence explains how classicality emerges from an underlying quantum reality. An additional interpretation to this has been proposed in which scattering events induce the localization of relative observables (Rau et al 2003 Science 301 1081). An interesting consequence of this process is that it involves the build-up of certain robust entanglements between the observables being localized. To date the weakness of this interpretation has been the lack of a clear experimental signature that allows it to be tested. Here we provide a simple experimentally accessible scheme that enables just that. We also discuss a Bayesian technique that could, in principle, allow experiments to confirm the localization to any desired degree of accuracy and we present precision requirements that are achievable with current experiments. Finally, we extend the scheme from its initial one dimensional proof of principle to the more real world scenario of three dimensional localization. (paper)

Robustness of Linear Systems towards Multi-Dissipative Pertubations

DEFF Research Database (Denmark)

Thygesen, Uffe Høgsbro; Poulsen, Niels Kjølstad

1997-01-01

We consider the question of robust stability of a linear time invariant plant subject to dynamic perturbations, which are dissipative in the sense of Willems with respect to several quadratic supply rates. For instance, parasitic dynamics are often both small gain and passive. We reduce several...... robustness analysis questions to linear matrix inequalities: robust stability, robust H2 performance and robust performance in presence of disturbances with finite signal-to-noise ratios...

Pixel-level multisensor image fusion based on matrix completion and robust principal component analysis

Science.gov (United States)

Wang, Zhuozheng; Deller, J. R.; Fleet, Blair D.

2016-01-01

Acquired digital images are often corrupted by a lack of camera focus, faulty illumination, or missing data. An algorithm is presented for fusion of multiple corrupted images of a scene using the lifting wavelet transform. The method employs adaptive fusion arithmetic based on matrix completion and self-adaptive regional variance estimation. Characteristics of the wavelet coefficients are used to adaptively select fusion rules. Robust principal component analysis is applied to low-frequency image components, and regional variance estimation is applied to high-frequency components. Experiments reveal that the method is effective for multifocus, visible-light, and infrared image fusion. Compared with traditional algorithms, the new algorithm not only increases the amount of preserved information and clarity but also improves robustness.

Robust performance results for discrete-time systems

Directory of Open Access Journals (Sweden)

Mahmoud Magdi S.

1997-01-01

Full Text Available The problems of robust performance and feedback control synthesis for a class of linear discrete-time systems with time-varying parametric uncertainties are addressed in this paper. The uncertainties are bound and have a linear matrix fractional form. Based on the concept of strongly robust H ∞ -performance criterion, results of robust stability and performance are developed and expressed in easily computable linear matrix inequalities. Synthesis of robust feedback controllers is carried out for several system models of interest.

Bilinear Regularized Locality Preserving Learning on Riemannian Graph for Motor Imagery BCI.

Science.gov (United States)

Xie, Xiaofeng; Yu, Zhu Liang; Gu, Zhenghui; Zhang, Jun; Cen, Ling; Li, Yuanqing

2018-03-01

In off-line training of motor imagery-based brain-computer interfaces (BCIs), to enhance the generalization performance of the learned classifier, the local information contained in test data could be used to improve the performance of motor imagery as well. Further considering that the covariance matrices of electroencephalogram (EEG) signal lie on Riemannian manifold, in this paper, we construct a Riemannian graph to incorporate the information of training and test data into processing. The adjacency and weight in Riemannian graph are determined by the geodesic distance of Riemannian manifold. Then, a new graph embedding algorithm, called bilinear regularized locality preserving (BRLP), is derived upon the Riemannian graph for addressing the problems of high dimensionality frequently arising in BCIs. With a proposed regularization term encoding prior information of EEG channels, the BRLP could obtain more robust performance. Finally, an efficient classification algorithm based on extreme learning machine is proposed to perform on the tangent space of learned embedding. Experimental evaluations on the BCI competition and in-house data sets reveal that the proposed algorithms could obtain significantly higher performance than many competition algorithms after using same filter process.

Robust adaptive synchronization of general dynamical networks ...

Indian Academy of Sciences (India)

Home; Journals; Pramana – Journal of Physics; Volume 86; Issue 6. Robust ... A robust adaptive synchronization scheme for these general complex networks with multiple delays and uncertainties is established and raised by employing the robust adaptive control principle and the Lyapunov stability theory. We choose ...

Robust synthesis for real-time systems

DEFF Research Database (Denmark)

Larsen, Kim Guldstrand; Legay, Axel; Traonouez, Luois-Marie

2014-01-01

Specification theories for real-time systems allow reasoning about interfaces and their implementation models, using a set of operators that includes satisfaction, refinement, logical and parallel composition. To make such theories applicable throughout the entire design process from an abstract...... of introducing small perturbations into formal models. We address this problem of robust implementations in timed specification theories. We first consider a fixed perturbation and study the robustness of timed specifications with respect to the operators of the theory. To this end we synthesize robust...... specification to an implementation, we need to reason about the possibility to effectively implement the theoretical specifications on physical systems, despite their limited precision. In the literature, this implementation problem has been linked to the robustness problem that analyzes the consequences...

Robustness of edge states in topological quantum dots against global electric field

Science.gov (United States)

Qu, Jin-Xian; Zhang, Shu-Hui; Liu, Ding-Yang; Wang, Ping; Yang, Wen

2017-07-01

The topological insulator has attracted increasing attention as a new state of quantum matter featured by the symmetry-protected edge states. Although the qualitative robustness of the edge states against local perturbations has been well established, it is not clear how these topological edge states respond quantitatively to a global perturbation. Here, we study the response of topological edge states in a HgTe quantum dot to an external in-plane electric field—a paradigmatic global perturbation in solid-state environments. We find that the stability of the topological edge state could be larger than that of the ground bulk state by several orders of magnitudes. This robustness may be verified by standard transport measurements in the Coulomb blockage regime. Our work may pave the way towards utilizing these topological edge states as stable memory devices for charge and/or spin information and stable emitter of single terahertz photons or entangled terahertz photon pairs for quantum communication.

Local facet approximation for image stitching

Science.gov (United States)

Li, Jing; Lai, Shiming; Liu, Yu; Wang, Zhengming; Zhang, Maojun

2018-01-01

Image stitching aims at eliminating multiview parallax and generating a seamless panorama given a set of input images. This paper proposes a local adaptive stitching method, which could achieve both accurate and robust image alignments across the whole panorama. A transformation estimation model is introduced by approximating the scene as a combination of neighboring facets. Then, the local adaptive stitching field is constructed using a series of linear systems of the facet parameters, which enables the parallax handling in three-dimensional space. We also provide a concise but effective global projectivity preserving technique that smoothly varies the transformations from local adaptive to global planar. The proposed model is capable of stitching both normal images and fisheye images. The efficiency of our method is quantitatively demonstrated in the comparative experiments on several challenging cases.

Automated detection of microaneurysms using robust blob descriptors

Science.gov (United States)

Adal, K.; Ali, S.; Sidibé, D.; Karnowski, T.; Chaum, E.; Mériaudeau, F.

2013-03-01

Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fundus images. Then, Hessian-based candidate selection algorithm is applied to extract image regions which are more likely to be MAs. For each candidate region, robust low-level blob descriptors such as Speeded Up Robust Features (SURF) and Intensity Normalized Radon Transform are extracted to characterize candidate MA regions. The combined features are then classified using SVM which has been trained using ten manually annotated training images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. Preliminary results show the competitiveness of the proposed candidate selection techniques against state-of-the art methods as well as the promising future for the proposed descriptors to be used in the localization of MAs from fundus images.

Short-circuit current density imaging of crystalline silicon solar cells via lock-in thermography: Robustness and simplifications

International Nuclear Information System (INIS)

Fertig, Fabian; Greulich, Johannes; Rein, Stefan

2014-01-01

Spatially resolved determination of solar cell parameters is beneficial for loss analysis and optimization of conversion efficiency. One key parameter that has been challenging to access by an imaging technique on solar cell level is short-circuit current density. This work discusses the robustness of a recently suggested approach to determine short-circuit current density spatially resolved based on a series of lock-in thermography images and options for a simplified image acquisition procedure. For an accurate result, one or two emissivity-corrected illuminated lock-in thermography images and one dark lock-in thermography image have to be recorded. The dark lock-in thermography image can be omitted if local shunts are negligible. Furthermore, it is shown that omitting the correction of lock-in thermography images for local emissivity variations only leads to minor distortions for standard silicon solar cells. Hence, adequate acquisition of one image only is sufficient to generate a meaningful map of short-circuit current density. Beyond that, this work illustrates the underlying physics of the recently proposed method and demonstrates its robustness concerning varying excitation conditions and locally increased series resistance. Experimentally gained short-circuit current density images are validated for monochromatic illumination in comparison to the reference method of light-beam induced current

A Novel Evolutionary Algorithm for Designing Robust Analog Filters

Directory of Open Access Journals (Sweden)

Shaobo Li

2018-03-01

Full Text Available Designing robust circuits that withstand environmental perturbation and device degradation is critical for many applications. Traditional robust circuit design is mainly done by tuning parameters to improve system robustness. However, the topological structure of a system may set a limit on the robustness achievable through parameter tuning. This paper proposes a new evolutionary algorithm for robust design that exploits the open-ended topological search capability of genetic programming (GP coupled with bond graph modeling. We applied our GP-based robust design (GPRD algorithm to evolve robust lowpass and highpass analog filters. Compared with a traditional robust design approach based on a state-of-the-art real-parameter genetic algorithm (GA, our GPRD algorithm with a fitness criterion rewarding robustness, with respect to parameter perturbations, can evolve more robust filters than what was achieved through parameter tuning alone. We also find that inappropriate GA tuning may mislead the search process and that multiple-simulation and perturbed fitness evaluation methods for evolving robustness have complementary behaviors with no absolute advantage of one over the other.

Robust and fast license plate detection based on the fusion of color and edge feature

Science.gov (United States)

Cai, De; Shi, Zhonghan; Liu, Jin; Hu, Chuanping; Mei, Lin; Qi, Li

2014-11-01

Extracting a license plate is an important stage in automatic vehicle identification. The degradation of images and the computation intense make this task difficult. In this paper, a robust and fast license plate detection based on the fusion of color and edge feature is proposed. Based on the dichromatic reflection model, two new color ratios computed from the RGB color model are introduced and proved to be two color invariants. The global color feature extracted by the new color invariants improves the method's robustness. The local Sobel edge feature guarantees the method's accuracy. In the experiment, the detection performance is good. The detection results show that this paper's method is robust to the illumination, object geometry and the disturbance around the license plates. The method can also detect license plates when the color of the car body is the same as the color of the plates. The processing time for image size of 1000x1000 by pixels is nearly 0.2s. Based on the comparison, the performance of the new ratios is comparable to the common used HSI color model.

The Variation Management Framework (VMF) for Robust Design

DEFF Research Database (Denmark)

Howard, Thomas J.; Ebro, Martin; Eifler, Tobias

2014-01-01

Robust Design is an approach to reduce the effects of variation. There are numerous tools,methods and models associated with robust design, however, there is both a lack of a processmodel formalising the step of a robust design process and a framework tying the models together.In this paper we pr...... in the market place and identifies areaswhere action can be taken against variation. An additional benefit of the framework is that itmakes the link between visual/sensory/perceptual robustness, product robustness, and productionvariation (Six Sigma)....

Measure of robustness for complex networks

Science.gov (United States)

Youssef, Mina Nabil

Critical infrastructures are repeatedly attacked by external triggers causing tremendous amount of damages. Any infrastructure can be studied using the powerful theory of complex networks. A complex network is composed of extremely large number of different elements that exchange commodities providing significant services. The main functions of complex networks can be damaged by different types of attacks and failures that degrade the network performance. These attacks and failures are considered as disturbing dynamics, such as the spread of viruses in computer networks, the spread of epidemics in social networks, and the cascading failures in power grids. Depending on the network structure and the attack strength, every network differently suffers damages and performance degradation. Hence, quantifying the robustness of complex networks becomes an essential task. In this dissertation, new metrics are introduced to measure the robustness of technological and social networks with respect to the spread of epidemics, and the robustness of power grids with respect to cascading failures. First, we introduce a new metric called the Viral Conductance (VCSIS ) to assess the robustness of networks with respect to the spread of epidemics that are modeled through the susceptible/infected/susceptible (SIS) epidemic approach. In contrast to assessing the robustness of networks based on a classical metric, the epidemic threshold, the new metric integrates the fraction of infected nodes at steady state for all possible effective infection strengths. Through examples, VCSIS provides more insights about the robustness of networks than the epidemic threshold. In addition, both the paradoxical robustness of Barabasi-Albert preferential attachment networks and the effect of the topology on the steady state infection are studied, to show the importance of quantifying the robustness of networks. Second, a new metric VCSIR is introduced to assess the robustness of networks with respect

Robust tumor morphometry in multispectral fluorescence microscopy

Science.gov (United States)

Tabesh, Ali; Vengrenyuk, Yevgen; Teverovskiy, Mikhail; Khan, Faisal M.; Sapir, Marina; Powell, Douglas; Mesa-Tejada, Ricardo; Donovan, Michael J.; Fernandez, Gerardo

2009-02-01

Morphological and architectural characteristics of primary tissue compartments, such as epithelial nuclei (EN) and cytoplasm, provide important cues for cancer diagnosis, prognosis, and therapeutic response prediction. We propose two feature sets for the robust quantification of these characteristics in multiplex immunofluorescence (IF) microscopy images of prostate biopsy specimens. To enable feature extraction, EN and cytoplasm regions were first segmented from the IF images. Then, feature sets consisting of the characteristics of the minimum spanning tree (MST) connecting the EN and the fractal dimension (FD) of gland boundaries were obtained from the segmented compartments. We demonstrated the utility of the proposed features in prostate cancer recurrence prediction on a multi-institution cohort of 1027 patients. Univariate analysis revealed that both FD and one of the MST features were highly effective for predicting cancer recurrence (p <= 0.0001). In multivariate analysis, an MST feature was selected for a model incorporating clinical and image features. The model achieved a concordance index (CI) of 0.73 on the validation set, which was significantly higher than the CI of 0.69 for the standard multivariate model based solely on clinical features currently used in clinical practice (p < 0.0001). The contributions of this work are twofold. First, it is the first demonstration of the utility of the proposed features in morphometric analysis of IF images. Second, this is the largest scale study of the efficacy and robustness of the proposed features in prostate cancer prognosis.

Robust recognition via information theoretic learning

CERN Document Server

He, Ran; Yuan, Xiaotong; Wang, Liang

2014-01-01

This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy.The?authors?resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency,?the brief?introduces the additive and multip

Robust methods for multivariate data analysis A1

DEFF Research Database (Denmark)

Frosch, Stina; Von Frese, J.; Bro, Rasmus

2005-01-01

Outliers may hamper proper classical multivariate analysis, and lead to incorrect conclusions. To remedy the problem of outliers, robust methods are developed in statistics and chemometrics. Robust methods reduce or remove the effect of outlying data points and allow the ?good? data to primarily...... determine the result. This article reviews the most commonly used robust multivariate regression and exploratory methods that have appeared since 1996 in the field of chemometrics. Special emphasis is put on the robust versions of chemometric standard tools like PCA and PLS and the corresponding robust...

Robustness Evaluation of Timber Structures

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard

2009-01-01

Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure....

Ins-Robust Primitive Words

OpenAIRE

Srivastava, Amit Kumar; Kapoor, Kalpesh

2017-01-01

Let Q be the set of primitive words over a finite alphabet with at least two symbols. We characterize a class of primitive words, Q_I, referred to as ins-robust primitive words, which remain primitive on insertion of any letter from the alphabet and present some properties that characterizes words in the set Q_I. It is shown that the language Q_I is dense. We prove that the language of primitive words that are not ins-robust is not context-free. We also present a linear time algorithm to reco...

Robust Sound Localization: An Application of an Auditory Perception System for a Humanoid Robot

National Research Council Canada - National Science Library

Irie, Robert E

1995-01-01

.... This thesis presents an integrated auditory system for a humanoid robot, currently under development, that will, among other things, learn to localize normal, everyday sounds in a realistic environment...

Local-scale models reveal ecological niche variability in amphibian and reptile communities from two contrasting biogeographic regions

Directory of Open Access Journals (Sweden)

Alberto Muñoz

2016-10-01

Full Text Available Ecological Niche Models (ENMs are widely used to describe how environmental factors influence species distribution. Modelling at a local scale, compared to a large scale within a high environmental gradient, can improve our understanding of ecological species niches. The main goal of this study is to assess and compare the contribution of environmental variables to amphibian and reptile ENMs in two Spanish national parks located in contrasting biogeographic regions, i.e., the Mediterranean and the Atlantic area. The ENMs were built with maximum entropy modelling using 11 environmental variables in each territory. The contributions of these variables to the models were analysed and classified using various statistical procedures (Mann–Whitney U tests, Principal Components Analysis and General Linear Models. Distance to the hydrological network was consistently the most relevant variable for both parks and taxonomic classes. Topographic variables (i.e., slope and altitude were the second most predictive variables, followed by climatic variables. Differences in variable contribution were observed between parks and taxonomic classes. Variables related to water availability had the larger contribution to the models in the Mediterranean park, while topography variables were decisive in the Atlantic park. Specific response curves to environmental variables were in accordance with the biogeographic affinity of species (Mediterranean and non-Mediterranean species and taxonomy (amphibians and reptiles. Interestingly, these results were observed for species located in both parks, particularly those situated at their range limits. Our findings show that ecological niche models built at local scale reveal differences in habitat preferences within a wide environmental gradient. Therefore, modelling at local scales rather than assuming large-scale models could be preferable for the establishment of conservation strategies for herptile species in natural

Local-scale models reveal ecological niche variability in amphibian and reptile communities from two contrasting biogeographic regions

Science.gov (United States)

Santos, Xavier; Felicísimo, Ángel M.

2016-01-01

Ecological Niche Models (ENMs) are widely used to describe how environmental factors influence species distribution. Modelling at a local scale, compared to a large scale within a high environmental gradient, can improve our understanding of ecological species niches. The main goal of this study is to assess and compare the contribution of environmental variables to amphibian and reptile ENMs in two Spanish national parks located in contrasting biogeographic regions, i.e., the Mediterranean and the Atlantic area. The ENMs were built with maximum entropy modelling using 11 environmental variables in each territory. The contributions of these variables to the models were analysed and classified using various statistical procedures (Mann–Whitney U tests, Principal Components Analysis and General Linear Models). Distance to the hydrological network was consistently the most relevant variable for both parks and taxonomic classes. Topographic variables (i.e., slope and altitude) were the second most predictive variables, followed by climatic variables. Differences in variable contribution were observed between parks and taxonomic classes. Variables related to water availability had the larger contribution to the models in the Mediterranean park, while topography variables were decisive in the Atlantic park. Specific response curves to environmental variables were in accordance with the biogeographic affinity of species (Mediterranean and non-Mediterranean species) and taxonomy (amphibians and reptiles). Interestingly, these results were observed for species located in both parks, particularly those situated at their range limits. Our findings show that ecological niche models built at local scale reveal differences in habitat preferences within a wide environmental gradient. Therefore, modelling at local scales rather than assuming large-scale models could be preferable for the establishment of conservation strategies for herptile species in natural parks. PMID

A Survey on Robustness in Railway Planning

DEFF Research Database (Denmark)

Lusby, Richard Martin; Larsen, Jesper; Bull, Simon Henry

2018-01-01

Planning problems in passenger railway range from long term strategic decision making to the detailed planning of operations.Operations research methods have played an increasing role in this planning process. However, recently more attention has been given to considerations of robustness...... in the quality of solutions to individual planning problems, and of operations in general. Robustness in general is the capacity for some system to absorb or resist changes. In the context of railway robustness it is often taken to be the capacity for operations to continue at some level when faced...... with a disruption such as delay or failure. This has resulted in more attention given to the inclusion of robustness measures and objectives in individual planning problems, and to the providing of tools to ensure operations continue under disrupted situations. In this paper we survey the literature on robustness...

A robust interpretation of duration calculus

DEFF Research Database (Denmark)

Franzle, M.; Hansen, Michael Reichhardt

2005-01-01

We transfer the concept of robust interpretation from arithmetic first-order theories to metric-time temporal logics. The idea is that the interpretation of a formula is robust iff its truth value does not change under small variation of the constants in the formula. Exemplifying this on Duration...... Calculus (DC), our findings are that the robust interpretation of DC is equivalent to a multi-valued interpretation that uses the real numbers as semantic domain and assigns Lipschitz-continuous interpretations to all operators of DC. Furthermore, this continuity permits approximation between discrete...

Design Robust Controller for Rotary Kiln

Directory of Open Access Journals (Sweden)

Omar D. Hernández-Arboleda

2013-11-01

Full Text Available This paper presents the design of a robust controller for a rotary kiln. The designed controller is a combination of a fractional PID and linear quadratic regulator (LQR, these are not used to control the kiln until now, in addition robustness criteria are evaluated (gain margin, phase margin, strength gain, rejecting high frequency noise and sensitivity applied to the entire model (controller-plant, obtaining good results with a frequency range of 0.020 to 90 rad/s, which contributes to the robustness of the system.

Danish Requirements for Robustness of Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Christensen, H. H.

2006-01-01

. This paper describes the background of the revised robustness requirements implemented in the Danish Code of Practice for Safety of Structures in 2003 [1, 2, 3]. According to the Danish design rules robustness shall be documented for all structures where consequences of failure are serious. This paper...... describes the background of the design procedure in the Danish codes, which shall be followed in order to document sufficient robustness in the following steps: Step 1: review of loads and possible failure modes/scenarios and determination of acceptable collapse extent. Step 2: review of the structural...

A Denoising Based Autoassociative Model for Robust Sensor Monitoring in Nuclear Power Plants

Directory of Open Access Journals (Sweden)

Ahmad Shaheryar

2016-01-01

Full Text Available Sensors health monitoring is essentially important for reliable functioning of safety-critical chemical and nuclear power plants. Autoassociative neural network (AANN based empirical sensor models have widely been reported for sensor calibration monitoring. However, such ill-posed data driven models may result in poor generalization and robustness. To address above-mentioned issues, several regularization heuristics such as training with jitter, weight decay, and cross-validation are suggested in literature. Apart from these regularization heuristics, traditional error gradient based supervised learning algorithms for multilayered AANN models are highly susceptible of being trapped in local optimum. In order to address poor regularization and robust learning issues, here, we propose a denoised autoassociative sensor model (DAASM based on deep learning framework. Proposed DAASM model comprises multiple hidden layers which are pretrained greedily in an unsupervised fashion under denoising autoencoder architecture. In order to improve robustness, dropout heuristic and domain specific data corruption processes are exercised during unsupervised pretraining phase. The proposed sensor model is trained and tested on sensor data from a PWR type nuclear power plant. Accuracy, autosensitivity, spillover, and sequential probability ratio test (SPRT based fault detectability metrics are used for performance assessment and comparison with extensively reported five-layer AANN model by Kramer.

Robust lyapunov controller for uncertain systems

KAUST Repository

Laleg-Kirati, Taous-Meriem; Elmetennani, Shahrazed

2017-01-01

Various examples of systems and methods are provided for Lyapunov control for uncertain systems. In one example, a system includes a process plant and a robust Lyapunov controller configured to control an input of the process plant. The robust

Towards structural controllability of local-world networks

International Nuclear Information System (INIS)

Sun, Shiwen; Ma, Yilin; Wu, Yafang; Wang, Li; Xia, Chengyi

2016-01-01

Controlling complex networks is of vital importance in science and engineering. Meanwhile, local-world effect is an important ingredient which should be taken into consideration in the complete description of real-world complex systems. In this letter, structural controllability of a class of local-world networks is investigated. Through extensive numerical simulations, firstly, effects of local world size M and network size N on structural controllability are examined. For local-world networks with sparse topological configuration, compared to network size, local-world size can induce stronger influence on controllability, however, for dense networks, controllability is greatly affected by network size and local-world effect can be neglected. Secondly, relationships between controllability and topological properties are analyzed. Lastly, the robustness of local-world networks under targeted attacks regarding structural controllability is discussed. These results can help to deepen the understanding of structural complexity and connectivity patterns of complex systems. - Highlights: • Structural controllability of a class of local-world networks is investigated. • For sparse local-world networks, compared to network size, local-world size can bring stronger influence on controllability. • For dense networks, controllability is greatly affected by network size and the effect of local-world size can be neglected. • Structural controllability against targeted node attacks is discussed.

Towards structural controllability of local-world networks

Energy Technology Data Exchange (ETDEWEB)

Sun, Shiwen, E-mail: sunsw80@126.com [Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384 (China); Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of Education, Tianjin 300384 (China); Ma, Yilin; Wu, Yafang; Wang, Li; Xia, Chengyi [Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384 (China); Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of Education, Tianjin 300384 (China)

2016-05-20

Controlling complex networks is of vital importance in science and engineering. Meanwhile, local-world effect is an important ingredient which should be taken into consideration in the complete description of real-world complex systems. In this letter, structural controllability of a class of local-world networks is investigated. Through extensive numerical simulations, firstly, effects of local world size M and network size N on structural controllability are examined. For local-world networks with sparse topological configuration, compared to network size, local-world size can induce stronger influence on controllability, however, for dense networks, controllability is greatly affected by network size and local-world effect can be neglected. Secondly, relationships between controllability and topological properties are analyzed. Lastly, the robustness of local-world networks under targeted attacks regarding structural controllability is discussed. These results can help to deepen the understanding of structural complexity and connectivity patterns of complex systems. - Highlights: • Structural controllability of a class of local-world networks is investigated. • For sparse local-world networks, compared to network size, local-world size can bring stronger influence on controllability. • For dense networks, controllability is greatly affected by network size and the effect of local-world size can be neglected. • Structural controllability against targeted node attacks is discussed.

Improving Robustness against Environmental Sounds for Directing Attention of Social Robots

DEFF Research Database (Denmark)

Thomsen, Nicolai Bæk; Tan, Zheng-Hua; Lindberg, Børge

2015-01-01

This paper presents a multi-modal system for finding out where to direct the attention of a social robot in a dialog scenario, which is robust against environmental sounds (door slamming, phone ringing etc.) and short speech segments. The method is based on combining voice activity detection (VAD......) and sound source localization (SSL) and furthermore apply post-processing to SSL to filter out short sounds. The system is tested against a baseline system in four different real-world experiments, where different sounds are used as interfering sounds. The results are promising and show a clear improvement....

Robust Adaptive Thresholder For Document Scanning Applications

Science.gov (United States)

Hsing, To R.

1982-12-01

In document scanning applications, thresholding is used to obtain binary data from a scanner. However, due to: (1) a wide range of different color backgrounds; (2) density variations of printed text information; and (3) the shading effect caused by the optical systems, the use of adaptive thresholding to enhance the useful information is highly desired. This paper describes a new robust adaptive thresholder for obtaining valid binary images. It is basically a memory type algorithm which can dynamically update the black and white reference level to optimize a local adaptive threshold function. The results of high image quality from different types of simulate test patterns can be obtained by this algorithm. The software algorithm is described and experiment results are present to describe the procedures. Results also show that the techniques described here can be used for real-time signal processing in the varied applications.

Robustness Analysis of Typologies of Reciprocal Timber Structures

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Parigi, Dario

2013-01-01

to the future development of typologies of reciprocal timber structures. The paper concludes that these kinds of structures can have a potential as long span timber structures in real projects if they are carefully designed with respect to the overall robustness strategies.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures many modern building...... codes consider the need for robustness in structures and provides strategies and methods to obtain robustness. Therefore a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper outlines robustness issues related...

2D Vector Field Simplification Based on Robustness

KAUST Repository

Skraba, Primoz

2014-03-01

Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification techniques based on the topological skeleton successively remove pairs of critical points connected by separatrices, using distance or area-based relevance measures. These methods rely on the stable extraction of the topological skeleton, which can be difficult due to instability in numerical integration, especially when processing highly rotational flows. These geometric metrics do not consider the flow magnitude, an important physical property of the flow. In this paper, we propose a novel simplification scheme derived from the recently introduced topological notion of robustness, which provides a complementary view on flow structure compared to the traditional topological-skeleton-based approaches. Robustness enables the pruning of sets of critical points according to a quantitative measure of their stability, that is, the minimum amount of vector field perturbation required to remove them. This leads to a hierarchical simplification scheme that encodes flow magnitude in its perturbation metric. Our novel simplification algorithm is based on degree theory, has fewer boundary restrictions, and so can handle more general cases. Finally, we provide an implementation under the piecewise-linear setting and apply it to both synthetic and real-world datasets. © 2014 IEEE.

Robust Weak Chimeras in Oscillator Networks with Delayed Linear and Quadratic Interactions

Science.gov (United States)

Bick, Christian; Sebek, Michael; Kiss, István Z.

2017-10-01

We present an approach to generate chimera dynamics (localized frequency synchrony) in oscillator networks with two populations of (at least) two elements using a general method based on a delayed interaction with linear and quadratic terms. The coupling design yields robust chimeras through a phase-model-based design of the delay and the ratio of linear and quadratic components of the interactions. We demonstrate the method in the Brusselator model and experiments with electrochemical oscillators. The technique opens the way to directly bridge chimera dynamics in phase models and real-world oscillator networks.

An H(∞) control approach to robust learning of feedforward neural networks.

Science.gov (United States)

Jing, Xingjian

2011-09-01

A novel H(∞) robust control approach is proposed in this study to deal with the learning problems of feedforward neural networks (FNNs). The analysis and design of a desired weight update law for the FNN is transformed into a robust controller design problem for a discrete dynamic system in terms of the estimation error. The drawbacks of some existing learning algorithms can therefore be revealed, especially for the case that the output data is fast changing with respect to the input or the output data is corrupted by noise. Based on this approach, the optimal learning parameters can be found by utilizing the linear matrix inequality (LMI) optimization techniques to achieve a predefined H(∞) "noise" attenuation level. Several existing BP-type algorithms are shown to be special cases of the new H(∞)-learning algorithm. Theoretical analysis and several examples are provided to show the advantages of the new method. Copyright © 2011 Elsevier Ltd. All rights reserved.

The cellular robustness by genetic redundancy in budding yeast.

Directory of Open Access Journals (Sweden)

Jingjing Li

2010-11-01

Full Text Available The frequent dispensability of duplicated genes in budding yeast is heralded as a hallmark of genetic robustness contributed by genetic redundancy. However, theoretical predictions suggest such backup by redundancy is evolutionarily unstable, and the extent of genetic robustness contributed from redundancy remains controversial. It is anticipated that, to achieve mutual buffering, the duplicated paralogs must at least share some functional overlap. However, counter-intuitively, several recent studies reported little functional redundancy between these buffering duplicates. The large yeast genetic interactions released recently allowed us to address these issues on a genome-wide scale. We herein characterized the synthetic genetic interactions for ∼500 pairs of yeast duplicated genes originated from either whole-genome duplication (WGD or small-scale duplication (SSD events. We established that functional redundancy between duplicates is a pre-requisite and thus is highly predictive of their backup capacity. This observation was particularly pronounced with the use of a newly introduced metric in scoring functional overlap between paralogs on the basis of gene ontology annotations. Even though mutual buffering was observed to be prevalent among duplicated genes, we showed that the observed backup capacity is largely an evolutionarily transient state. The loss of backup capacity generally follows a neutral mode, with the buffering strength decreasing in proportion to divergence time, and the vast majority of the paralogs have already lost their backup capacity. These observations validated previous theoretic predictions about instability of genetic redundancy. However, departing from the general neutral mode, intriguingly, our analysis revealed the presence of natural selection in stabilizing functional overlap between SSD pairs. These selected pairs, both WGD and SSD, tend to have decelerated functional evolution, have higher propensities of co

Compaction bands in shale revealed through digital volume correlation of time-resolved X-ray tomography scans

Science.gov (United States)

McBeck, J.; Kobchenko, M.; Hall, S.; Tudisco, E.; Cordonnier, B.; Renard, F.

2017-12-01

Previous studies have identified compaction bands primarily within sandstones, and in fewer instances, within other porous rocks and sediments. Using Digital Volume Correlation (DVC) of X-ray microtomography scans, we find evidence of localized zones of high axial contraction that form tabular structures sub-perpendicular to maximum compression, σ1, in Green River shale. To capture in situ strain localization throughout loading, two shale cores were deformed in the HADES triaxial deformation apparatus installed on the X-ray microtomography beamline ID19 at the European Synchrotron Radiation Facility. In these experiments, we increase σ1 in increments of two MPa, with constant confining pressure (20 MPa), until the sample fails in macroscopic shear. After each stress step, a 3D image of the sample inside the rig is acquired at a voxel resolution of 6.5 μm. The evolution of lower density regions within 3D reconstructions of linear attenuation coefficients reveal the development of fractures that fail with some opening. If a fracture produces negligible dilation, it may remain undetected in image segmentation of the reconstructions. We use the DVC software TomoWarp2 to identify undetected fractures and capture the 3D incremental displacement field between each successive pair of microtomography scans acquired in each experiment. The corresponding strain fields reveal localized bands of high axial contraction that host minimal shear strain, and thus match the kinematic definition of compaction bands. The bands develop sub-perpendicular to σ1 in the two samples in which pre-existing bedding laminations were oriented parallel and perpendicular to σ1. As the shales deform plastically toward macroscopic shear failure, the number of bands and axial contraction within the bands increase, while the spacing between the bands decreases. Compaction band development accelerates the rate of overall axial contraction, increasing the mean axial contraction throughout the sample

Robust Sound Localization: An Application of an Auditory Perception System for a Humanoid Robot

National Research Council Canada - National Science Library

Irie, Robert E

1995-01-01

Localizing sounds with different frequency and time domain characteristics in a dynamic listening environment is a challenging task that has not been explored in the field of robotics as much as other perceptual tasks...

A Robust Localization, Slip Estimation, and Compensation System for WMR in the Indoor Environments

Directory of Open Access Journals (Sweden)

Zakir Ullah

2018-05-01

Full Text Available A novel approach is proposed for the path tracking of a Wheeled Mobile Robot (WMR in the presence of an unknown lateral slip. Much of the existing work has assumed pure rolling conditions between the wheel and ground. Under the pure rolling conditions, the wheels of a WMR are supposed to roll without slipping. Complex wheel-ground interactions, acceleration and steering system noise are the factors which cause WMR wheel slip. A basic research problem in this context is localization and slip estimation of WMR from a stream of noisy sensors data when the robot is moving on a slippery surface, or moving at a high speed. DecaWave based ranging system and Particle Filter (PF are good candidates to estimate the location of WMR indoors and outdoors. Unfortunately, wheel-slip of WMR limits the ultimate performance that can be achieved by real-world implementation of the PF, because location estimation systems typically partially rely on the robot heading. A small error in the WMR heading leads to a large error in location estimation of the PF because of its cumulative nature. In order to enhance the tracking and localization performance of the PF in the environments where the main reason for an error in the PF location estimation is angular noise, two methods were used for heading estimation of the WMR (1: Reinforcement Learning (RL and (2: Location-based Heading Estimation (LHE. Trilateration is applied to DecaWave based ranging system for calculating the probable location of WMR, this noisy location along with PF current mean is used to estimate the WMR heading by using the above two methods. Beside the WMR location calculation, DecaWave based ranging system is also used to update the PF weights. The localization and tracking performance of the PF is significantly improved through incorporating heading error in localization by applying RL and LHE. Desired trajectory information is then used to develop an algorithm for extracting the lateral slip along

Robustness of Long Span Reciprocal Timber Structures

DEFF Research Database (Denmark)

Balfroid, Nathalie; Kirkegaard, Poul Henning

2011-01-01

engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper makes a discussion of such robustness issues related to the future development of reciprocal timber structures. The paper concludes that these kind of structures can have...... a potential as long span timber structures in real projects if they are carefully designed with respect to the overall robustness strategies.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. The interest has also been facilitated due to recently severe structural failures...

Application of a new dual localization-affinity purification tag reveals novel aspects of protein kinase biology in Aspergillus nidulans.

Science.gov (United States)

De Souza, Colin P; Hashmi, Shahr B; Osmani, Aysha H; Osmani, Stephen A

2014-01-01

Filamentous fungi occupy critical environmental niches and have numerous beneficial industrial applications but devastating effects as pathogens and agents of food spoilage. As regulators of essentially all biological processes protein kinases have been intensively studied but how they regulate the often unique biology of filamentous fungi is not completely understood. Significant understanding of filamentous fungal biology has come from the study of the model organism Aspergillus nidulans using a combination of molecular genetics, biochemistry, cell biology and genomic approaches. Here we describe dual localization-affinity purification (DLAP) tags enabling endogenous N or C-terminal protein tagging for localization and biochemical studies in A. nidulans. To establish DLAP tag utility we endogenously tagged 17 protein kinases for analysis by live cell imaging and affinity purification. Proteomic analysis of purifications by mass spectrometry confirmed association of the CotA and NimXCdk1 kinases with known binding partners and verified a predicted interaction of the SldABub1/R1 spindle assembly checkpoint kinase with SldBBub3. We demonstrate that the single TOR kinase of A. nidulans locates to vacuoles and vesicles, suggesting that the function of endomembranes as major TOR cellular hubs is conserved in filamentous fungi. Comparative analysis revealed 7 kinases with mitotic specific locations including An-Cdc7 which unexpectedly located to mitotic spindle pole bodies (SPBs), the first such localization described for this family of DNA replication kinases. We show that the SepH septation kinase locates to SPBs specifically in the basal region of apical cells in a biphasic manner during mitosis and again during septation. This results in gradients of SepH between G1 SPBs which shift along hyphae as each septum forms. We propose that SepH regulates the septation initiation network (SIN) specifically at SPBs in the basal region of G1 cells and that localized gradients

Experimental investigation of the robustness against noise for different Bell-type inequalities in three-qubit Greenberger-Horne-Zeilinger states

International Nuclear Information System (INIS)

Lu Huaixin; Zhao Jiaqiang; Cao Lianzhen; Wang Xiaoqin

2011-01-01

There are different families of inequalities that can be used to characterize the entanglement of multiqubit entangled states by the violation of quantum mechanics prediction versus local realism prediction. In a noisy environment, the violation of different inequalities distinguishes a direct from a noise-free environment. That is, each inequality has a different robustness against noise. We investigate theoretically and experimentally this proposition with the Mermin inequality, Bell inequality, and Svetlichny inequality using three-qubit GHZ states for different levels of noise. Our purpose is to determine which one of the inequalities is more robust against noise and thus more suitable to characterize entanglement of states. Our results show that the Mermin inequality is the most robust against stronger noise and is, thus, more suitable for characterizing the entanglement of three-qubit GHZ states in a noisy environment.

Experimental investigation of the robustness against noise for different Bell-type inequalities in three-qubit Greenberger-Horne-Zeilinger states

Energy Technology Data Exchange (ETDEWEB)

Lu Huaixin; Zhao Jiaqiang; Cao Lianzhen; Wang Xiaoqin [Department of Physics and Electronic Science, Weifang University, Weifang, Shandong 261061 (China)

2011-10-15

There are different families of inequalities that can be used to characterize the entanglement of multiqubit entangled states by the violation of quantum mechanics prediction versus local realism prediction. In a noisy environment, the violation of different inequalities distinguishes a direct from a noise-free environment. That is, each inequality has a different robustness against noise. We investigate theoretically and experimentally this proposition with the Mermin inequality, Bell inequality, and Svetlichny inequality using three-qubit GHZ states for different levels of noise. Our purpose is to determine which one of the inequalities is more robust against noise and thus more suitable to characterize entanglement of states. Our results show that the Mermin inequality is the most robust against stronger noise and is, thus, more suitable for characterizing the entanglement of three-qubit GHZ states in a noisy environment.

Interferometric probes of many-body localization.

Science.gov (United States)

Serbyn, M; Knap, M; Gopalakrishnan, S; Papić, Z; Yao, N Y; Laumann, C R; Abanin, D A; Lukin, M D; Demler, E A

2014-10-03

We propose a method for detecting many-body localization (MBL) in disordered spin systems. The method involves pulsed coherent spin manipulations that probe the dephasing of a given spin due to its entanglement with a set of distant spins. It allows one to distinguish the MBL phase from a noninteracting localized phase and a delocalized phase. In particular, we show that for a properly chosen pulse sequence the MBL phase exhibits a characteristic power-law decay reflecting its slow growth of entanglement. We find that this power-law decay is robust with respect to thermal and disorder averaging, provide numerical simulations supporting our results, and discuss possible experimental realizations in solid-state and cold-atom systems.

Nonlinear robust hierarchical control for nonlinear uncertain systems

Directory of Open Access Journals (Sweden)

Leonessa Alexander

1999-01-01

Full Text Available A nonlinear robust control-system design framework predicated on a hierarchical switching controller architecture parameterized over a set of moving nominal system equilibria is developed. Specifically, using equilibria-dependent Lyapunov functions, a hierarchical nonlinear robust control strategy is developed that robustly stabilizes a given nonlinear system over a prescribed range of system uncertainty by robustly stabilizing a collection of nonlinear controlled uncertain subsystems. The robust switching nonlinear controller architecture is designed based on a generalized (lower semicontinuous Lyapunov function obtained by minimizing a potential function over a given switching set induced by the parameterized nominal system equilibria. The proposed framework robustly stabilizes a compact positively invariant set of a given nonlinear uncertain dynamical system with structured parametric uncertainty. Finally, the efficacy of the proposed approach is demonstrated on a jet engine propulsion control problem with uncertain pressure-flow map data.

The importance of robust design methodology

DEFF Research Database (Denmark)

Eifler, Tobias; Howard, Thomas J.

2018-01-01

infamous recalls in automotive history, that of the GM ignition switch, from the perspective of Robust Design. It is investigated if available Robust Design methods such as sensitivity analysis, tolerance stack-ups, design clarity, etc. would have been suitable to account for the performance variation...

Security and robustness for collaborative monitors

NARCIS (Netherlands)

Testerink, Bas; Bulling, Nils; Dastani, Mehdi

2016-01-01

Decentralized monitors can be subject to robustness and security risks. Robustness risks include attacks on the monitor’s infrastructure in order to disable parts of its functionality. Security risks include attacks that try to extract information from the monitor and thereby possibly leak sensitive

Local food and tourism

DEFF Research Database (Denmark)

Boesen, Morten; Sundbo, Donna; Sundbo, Jon

2017-01-01

This article investigates the question: Why local food networks succeed or fail in collaborating with local tourism actors to create more tourism based on local food? The article focuses on entrepreneurial local food networks and their collaboration with local tourism actors. Emphasis...... is on the actions and attitude logics of local food networks and tourism actors, and whether their respective logics fit as a factor to explain why or why not development of local food concepts lead to increased local tourism. Six local food networks and their collaboration with local tourism actors are studied...... by using observation supplemented with other qualitative methods. Analysis of these networks reveals that successful collaboration is characterised by the food networks and tourism actors having at least one logic in common. The fitting logics that lead to success are primarily celebrity and civic logics...

Correlated network of networks enhances robustness against catastrophic failures.

Science.gov (United States)

Min, Byungjoon; Zheng, Muhua

2018-01-01

Networks in nature rarely function in isolation but instead interact with one another with a form of a network of networks (NoN). A network of networks with interdependency between distinct networks contains instability of abrupt collapse related to the global rule of activation. As a remedy of the collapse instability, here we investigate a model of correlated NoN. We find that the collapse instability can be removed when hubs provide the majority of interconnections and interconnections are convergent between hubs. Thus, our study identifies a stable structure of correlated NoN against catastrophic failures. Our result further suggests a plausible way to enhance network robustness by manipulating connection patterns, along with other methods such as controlling the state of node based on a local rule.

Robust statistics and geochemical data analysis

International Nuclear Information System (INIS)

Di, Z.

1987-01-01

Advantages of robust procedures over ordinary least-squares procedures in geochemical data analysis is demonstrated using NURE data from the Hot Springs Quadrangle, South Dakota, USA. Robust principal components analysis with 5% multivariate trimming successfully guarded the analysis against perturbations by outliers and increased the number of interpretable factors. Regression with SINE estimates significantly increased the goodness-of-fit of the regression and improved the correspondence of delineated anomalies with known uranium prospects. Because of the ubiquitous existence of outliers in geochemical data, robust statistical procedures are suggested as routine procedures to replace ordinary least-squares procedures

Towards distortion-free robust image authentication

International Nuclear Information System (INIS)

Coltuc, D

2007-01-01

This paper investigates a general framework for distortion-free robust image authentication by multiple marking. First, by robust watermarking a subsampled version of image edges is embedded. Then, by reversible watermarking the information needed to recover the original image is inserted, too. The hiding capacity of the reversible watermarking is the essential requirement for this approach. Thus in case of no attacks not only image is authenticated but also the original is exactly recovered. In case of attacks, reversibility is lost, but image can still be authenticated. Preliminary results providing very good robustness against JPEG compression are presented

On the robustness of Herlihy's hierarchy

Science.gov (United States)

Jayanti, Prasad

1993-01-01

A wait-free hierarchy maps object types to levels in Z(+) U (infinity) and has the following property: if a type T is at level N, and T' is an arbitrary type, then there is a wait-free implementation of an object of type T', for N processes, using only registers and objects of type T. The infinite hierarchy defined by Herlihy is an example of a wait-free hierarchy. A wait-free hierarchy is robust if it has the following property: if T is at level N, and S is a finite set of types belonging to levels N - 1 or lower, then there is no wait-free implementation of an object of type T, for N processes, using any number and any combination of objects belonging to the types in S. Robustness implies that there are no clever ways of combining weak shared objects to obtain stronger ones. Contrary to what many researchers believe, we prove that Herlihy's hierarchy is not robust. We then define some natural variants of Herlihy's hierarchy, which are also infinite wait-free hierarchies. With the exception of one, which is still open, these are not robust either. We conclude with the open question of whether non-trivial robust wait-free hierarchies exist.

Information theory perspective on network robustness

International Nuclear Information System (INIS)

Schieber, Tiago A.; Carpi, Laura; Frery, Alejandro C.; Rosso, Osvaldo A.; Pardalos, Panos M.; Ravetti, Martín G.

2016-01-01

A crucial challenge in network theory is the study of the robustness of a network when facing a sequence of failures. In this work, we propose a dynamical definition of network robustness based on Information Theory, that considers measurements of the structural changes caused by failures of the network's components. Failures are defined here as a temporal process defined in a sequence. Robustness is then evaluated by measuring dissimilarities between topologies after each time step of the sequence, providing a dynamical information about the topological damage. We thoroughly analyze the efficiency of the method in capturing small perturbations by considering different probability distributions on networks. In particular, we find that distributions based on distances are more consistent in capturing network structural deviations, as better reflect the consequences of the failures. Theoretical examples and real networks are used to study the performance of this methodology. - Highlights: • A novel methodology to measure the robustness of a network to component failure or targeted attacks is proposed. • The use of the network's distance PDF allows a precise analysis. • The method provides a dynamic robustness profile showing the response of the topology to each failure event. • The measure is capable to detect network's critical elements.

Replication and robustness in developmental research.

Science.gov (United States)

Duncan, Greg J; Engel, Mimi; Claessens, Amy; Dowsett, Chantelle J

2014-11-01

Replications and robustness checks are key elements of the scientific method and a staple in many disciplines. However, leading journals in developmental psychology rarely include explicit replications of prior research conducted by different investigators, and few require authors to establish in their articles or online appendices that their key results are robust across estimation methods, data sets, and demographic subgroups. This article makes the case for prioritizing both explicit replications and, especially, within-study robustness checks in developmental psychology. It provides evidence on variation in effect sizes in developmental studies and documents strikingly different replication and robustness-checking practices in a sample of journals in developmental psychology and a sister behavioral science-applied economics. Our goal is not to show that any one behavioral science has a monopoly on best practices, but rather to show how journals from a related discipline address vital concerns of replication and generalizability shared by all social and behavioral sciences. We provide recommendations for promoting graduate training in replication and robustness-checking methods and for editorial policies that encourage these practices. Although some of our recommendations may shift the form and substance of developmental research articles, we argue that they would generate considerable scientific benefits for the field. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

IMF–METALLICITY: A TIGHT LOCAL RELATION REVEALED BY THE CALIFA SURVEY

International Nuclear Information System (INIS)

Martín-Navarro, Ignacio; Vazdekis, Alexandre; Falcón-Barroso, Jesús; La Barbera, Francesco; Lyubenova, Mariya; Trager, S. C.; Ven, Glenn van de; Ferreras, Ignacio; Sánchez, S. F.; García-Benito, R.; Mendoza, M. A.; Mast, D.; Sánchez-Blázquez, P.

2015-01-01

Variations in the stellar initial mass function (IMF) have been invoked to explain the spectroscopic and dynamical properties of early-type galaxies (ETGs). However, no observations have yet been able to disentangle the physical driver. We analyze here a sample of 24 ETGs drawn from the CALIFA survey, deriving in a homogeneous way their stellar population and kinematic properties. We find that the local IMF is tightly related to the local metallicity, becoming more bottom-heavy toward metal-rich populations. Our result, combined with the galaxy mass–metallicity relation, naturally explains previous claims of a galaxy mass–IMF relation, derived from non-IFU spectra. If we assume that—within the star formation environment of ETGs—metallicity is the main driver of IMF variations, a significant revision of the interpretation of galaxy evolution observables is necessary

Primal and dual approaches to adjustable robust optimization

NARCIS (Netherlands)

de Ruiter, Frans

2018-01-01

Robust optimization has become an important paradigm to deal with optimization under uncertainty. Adjustable robust optimization is an extension that deals with multistage problems. This thesis starts with a short but comprehensive introduction to adjustable robust optimization. Then the two

Reliability-Based Robustness Analysis for a Croatian Sports Hall

DEFF Research Database (Denmark)

Čizmar, Dean; Kirkegaard, Poul Henning; Sørensen, John Dalsgaard

2011-01-01

This paper presents a probabilistic approach for structural robustness assessment for a timber structure built a few years ago. The robustness analysis is based on a structural reliability based framework for robustness and a simplified mechanical system modelling of a timber truss system....... A complex timber structure with a large number of failure modes is modelled with only a few dominant failure modes. First, a component based robustness analysis is performed based on the reliability indices of the remaining elements after the removal of selected critical elements. The robustness...... is expressed and evaluated by a robustness index. Next, the robustness is assessed using system reliability indices where the probabilistic failure model is modelled by a series system of parallel systems....

A robust statistical estimation (RoSE) algorithm jointly recovers the 3D location and intensity of single molecules accurately and precisely

Science.gov (United States)

Mazidi, Hesam; Nehorai, Arye; Lew, Matthew D.

2018-02-01

In single-molecule (SM) super-resolution microscopy, the complexity of a biological structure, high molecular density, and a low signal-to-background ratio (SBR) may lead to imaging artifacts without a robust localization algorithm. Moreover, engineered point spread functions (PSFs) for 3D imaging pose difficulties due to their intricate features. We develop a Robust Statistical Estimation algorithm, called RoSE, that enables joint estimation of the 3D location and photon counts of SMs accurately and precisely using various PSFs under conditions of high molecular density and low SBR.

Design principles for robust oscillatory behavior.

Science.gov (United States)

Castillo-Hair, Sebastian M; Villota, Elizabeth R; Coronado, Alberto M

2015-09-01

Oscillatory responses are ubiquitous in regulatory networks of living organisms, a fact that has led to extensive efforts to study and replicate the circuits involved. However, to date, design principles that underlie the robustness of natural oscillators are not completely known. Here we study a three-component enzymatic network model in order to determine the topological requirements for robust oscillation. First, by simulating every possible topological arrangement and varying their parameter values, we demonstrate that robust oscillators can be obtained by augmenting the number of both negative feedback loops and positive autoregulations while maintaining an appropriate balance of positive and negative interactions. We then identify network motifs, whose presence in more complex topologies is a necessary condition for obtaining oscillatory responses. Finally, we pinpoint a series of simple architectural patterns that progressively render more robust oscillators. Together, these findings can help in the design of more reliable synthetic biomolecular networks and may also have implications in the understanding of other oscillatory systems.

Infrared target recognition based on improved joint local ternary pattern

Science.gov (United States)

Sun, Junding; Wu, Xiaosheng

2016-05-01

This paper presents a simple, efficient, yet robust approach, named joint orthogonal combination of local ternary pattern, for automatic forward-looking infrared target recognition. It gives more advantages to describe the macroscopic textures and microscopic textures by fusing variety of scales than the traditional LBP-based methods. In addition, it can effectively reduce the feature dimensionality. Further, the rotation invariant and uniform scheme, the robust LTP, and soft concave-convex partition are introduced to enhance its discriminative power. Experimental results demonstrate that the proposed method can achieve competitive results compared with the state-of-the-art methods.

Robustness of Distance-to-Default

DEFF Research Database (Denmark)

Jessen, Cathrine; Lando, David

2013-01-01

Distance-to-default is a remarkably robust measure for ranking firms according to their risk of default. The ranking seems to work despite the fact that the Merton model from which the measure is derived produces default probabilities that are far too small when applied to real data. We use...... simulations to investigate the robustness of the distance-to-default measure to different model specifications. Overall we find distance-to-default to be robust to a number of deviations from the simple Merton model that involve different asset value dynamics and different default triggering mechanisms....... A notable exception is a model with stochastic volatility of assets. In this case both the ranking of firms and the estimated default probabilities using distance-to-default perform significantly worse. We therefore propose a volatility adjustment of the distance-to-default measure, that significantly...

Robustness of digital artist authentication

DEFF Research Database (Denmark)

Jacobsen, Robert; Nielsen, Morten

In many cases it is possible to determine the authenticity of a painting from digital reproductions of the paintings; this has been demonstrated for a variety of artists and with different approaches. Common to all these methods in digital artist authentication is that the potential of the method...... is in focus, while the robustness has not been considered, i.e. the degree to which the data collection process influences the decision of the method. However, in order for an authentication method to be successful in practice, it needs to be robust to plausible error sources from the data collection....... In this paper we investigate the robustness of the newly proposed authenticity method introduced by the authors based on second generation multiresolution analysis. This is done by modelling a number of realistic factors that can occur in the data collection....

Visual-based simultaneous localization and mapping and global positioning system correction for geo-localization of a mobile robot

International Nuclear Information System (INIS)

Berrabah, Sid Ahmed; Baudoin, Yvan; Sahli, Hichem

2011-01-01

This paper introduces an approach combining visual-based simultaneous localization and mapping (V-SLAM) and global positioning system (GPS) correction for accurate multi-sensor localization of an outdoor mobile robot in geo-referenced maps. The proposed framework combines two extended Kalman filters (EKF); the first one, referred to as the integration filter, is dedicated to the improvement of the GPS localization based on data from an inertial navigation system and wheels' encoders. The second EKF implements the V-SLAM process. The linear and angular velocities in the dynamic model of the V-SLAM EKF filter are given by the GPS/INS/Encoders integration filter. On the other hand, the output of the V-SLAM EKF filter is used to update the dynamics estimation in the integration filter and therefore the geo-referenced localization. This solution increases the accuracy and the robustness of the positioning during GPS outage and allows SLAM in less featured environments

Adaptive Critic Nonlinear Robust Control: A Survey.

Science.gov (United States)

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

A Robust Controller Structure for Pico-Satellite Applications

DEFF Research Database (Denmark)

Kragelund, Martin Nygaard; Green, Martin; Kristensen, Mads

This paper describes the development of a robust controller structure for use in pico-satellite missions. The structure relies on unknown disturbance estimation and use of robust control theory to implement a system that is robust to both unmodeled disturbances and parameter uncertainties. As one...

Uncertainty Modeling and Robust Output Feedback Control of Nonlinear Discrete Systems: A Mathematical Programming Approach

Directory of Open Access Journals (Sweden)

Olav Slupphaug

2001-01-01

Full Text Available We present a mathematical programming approach to robust control of nonlinear systems with uncertain, possibly time-varying, parameters. The uncertain system is given by different local affine parameter dependent models in different parts of the state space. It is shown how this representation can be obtained from a nonlinear uncertain system by solving a set of continuous linear semi-infinite programming problems, and how each of these problems can be solved as a (finite series of ordinary linear programs. Additionally, the system representation includes control- and state constraints. The controller design method is derived from Lyapunov stability arguments and utilizes an affine parameter dependent quadratic Lyapunov function. The controller has a piecewise affine output feedback structure, and the design amounts to finding a feasible solution to a set of linear matrix inequalities combined with one spectral radius constraint on the product of two positive definite matrices. A local solution approach to this nonconvex feasibility problem is proposed. Complexity of the design method and some special cases such as state- feedback are discussed. Finally, an application of the results is given by proposing an on-line computationally feasible algorithm for constrained nonlinear state- feedback model predictive control with robust stability.

DC Algorithm for Extended Robust Support Vector Machine.

Science.gov (United States)

Fujiwara, Shuhei; Takeda, Akiko; Kanamori, Takafumi

2017-05-01

Nonconvex variants of support vector machines (SVMs) have been developed for various purposes. For example, robust SVMs attain robustness to outliers by using a nonconvex loss function, while extended [Formula: see text]-SVM (E[Formula: see text]-SVM) extends the range of the hyperparameter by introducing a nonconvex constraint. Here, we consider an extended robust support vector machine (ER-SVM), a robust variant of E[Formula: see text]-SVM. ER-SVM combines two types of nonconvexity from robust SVMs and E[Formula: see text]-SVM. Because of the two nonconvexities, the existing algorithm we proposed needs to be divided into two parts depending on whether the hyperparameter value is in the extended range or not. The algorithm also heuristically solves the nonconvex problem in the extended range. In this letter, we propose a new, efficient algorithm for ER-SVM. The algorithm deals with two types of nonconvexity while never entailing more computations than either E[Formula: see text]-SVM or robust SVM, and it finds a critical point of ER-SVM. Furthermore, we show that ER-SVM includes the existing robust SVMs as special cases. Numerical experiments confirm the effectiveness of integrating the two nonconvexities.

Robust reflective ghost imaging against different partially polarized thermal light

Science.gov (United States)

Li, Hong-Guo; Wang, Yan; Zhang, Rui-Xue; Zhang, De-Jian; Liu, Hong-Chao; Li, Zong-Guo; Xiong, Jun

2018-03-01

We theoretically study the influence of degree of polarization (DOP) of thermal light on the contrast-to-noise ratio (CNR) of the reflective ghost imaging (RGI), which is a novel and indirect imaging modality. An expression for the CNR of RGI with partially polarized thermal light is carefully derived, which suggests a weak dependence of CNR on the DOP, especially when the ratio of the object size to the speckle size of thermal light has a large value. Different from conventional imaging approaches, our work reveals that RGI is much more robust against the DOP of the light source, which thereby has advantages in practical applications, such as remote sensing.

Citizen Science into Action - Robust Data with Affordable Technologies for Flood Risks Management in the Himalayas

Science.gov (United States)

Pandeya, B.; Uprety, M.; Paul, J. D.; Dugar, S.; Buytaert, W.

2017-12-01

With a robust and affordable monitoring system, a wealth of hydrological data can be generated which is fundamental to predict flood risks more accurately. Since the Himalayan region is characterized by data deficiency and unpredictable hydrological behaviour, a locally based participatory monitoring system is a necessity to deal with frequently occurring flooding incidents. A gap in hydrological data is the main bottleneck for establishing any effective flood early warning system. Therefore, an alternative and affordable technical solution can only overcome the situation and support flood risks management activities in the region. In coordination with local people, government authorities and NGOs, we have established a citizen science monitoring system, in which we tested two types of low-cost sensors, ultrasound and LiDAR, in the Karnali river basin of Nepal. The results confirm the robustness of sensor data when compared to conventional radar system based monitoring data. Additionally, our findings also confirmed that the ultrasound sensors are only useful to small rivers whereas the LiDAR sensors are suitable to large river basins with highly variable local climatic conditions. Since the collected sensor data can be directly used in operational flood early warning system in the basin, an opportunity has been created for integrating both affordable technology and citizen science into existing hydrological monitoring practice. Finally, a successful integration could become a testament for upscaling the practice and building flood risk resilient communities in the region.

Robustness-related issues in speaker recognition

CERN Document Server

Zheng, Thomas Fang

2017-01-01

This book presents an overview of speaker recognition technologies with an emphasis on dealing with robustness issues. Firstly, the book gives an overview of speaker recognition, such as the basic system framework, categories under different criteria, performance evaluation and its development history. Secondly, with regard to robustness issues, the book presents three categories, including environment-related issues, speaker-related issues and application-oriented issues. For each category, the book describes the current hot topics, existing technologies, and potential research focuses in the future. The book is a useful reference book and self-learning guide for early researchers working in the field of robust speech recognition.

Robustness, efficiency, and optimality in the Fenna-Matthews-Olson photosynthetic pigment-protein complex

Energy Technology Data Exchange (ETDEWEB)

Baker, Lewis A.; Habershon, Scott, E-mail: S.Habershon@warwick.ac.uk [Department of Chemistry and Centre for Scientific Computing, University of Warwick, Coventry CV4 7AL (United Kingdom)

2015-09-14

Pigment-protein complexes (PPCs) play a central role in facilitating excitation energy transfer (EET) from light-harvesting antenna complexes to reaction centres in photosynthetic systems; understanding molecular organisation in these biological networks is key to developing better artificial light-harvesting systems. In this article, we combine quantum-mechanical simulations and a network-based picture of transport to investigate how chromophore organization and protein environment in PPCs impacts on EET efficiency and robustness. In a prototypical PPC model, the Fenna-Matthews-Olson (FMO) complex, we consider the impact on EET efficiency of both disrupting the chromophore network and changing the influence of (local and global) environmental dephasing. Surprisingly, we find a large degree of resilience to changes in both chromophore network and protein environmental dephasing, the extent of which is greater than previously observed; for example, FMO maintains EET when 50% of the constituent chromophores are removed, or when environmental dephasing fluctuations vary over two orders-of-magnitude relative to the in vivo system. We also highlight the fact that the influence of local dephasing can be strongly dependent on the characteristics of the EET network and the initial excitation; for example, initial excitations resulting in rapid coherent decay are generally insensitive to the environment, whereas the incoherent population decay observed following excitation at weakly coupled chromophores demonstrates a more pronounced dependence on dephasing rate as a result of the greater possibility of local exciton trapping. Finally, we show that the FMO electronic Hamiltonian is not particularly optimised for EET; instead, it is just one of many possible chromophore organisations which demonstrate a good level of EET transport efficiency following excitation at different chromophores. Overall, these robustness and efficiency characteristics are attributed to the highly

Robustness, efficiency, and optimality in the Fenna-Matthews-Olson photosynthetic pigment-protein complex

International Nuclear Information System (INIS)

Baker, Lewis A.; Habershon, Scott

2015-01-01

Pigment-protein complexes (PPCs) play a central role in facilitating excitation energy transfer (EET) from light-harvesting antenna complexes to reaction centres in photosynthetic systems; understanding molecular organisation in these biological networks is key to developing better artificial light-harvesting systems. In this article, we combine quantum-mechanical simulations and a network-based picture of transport to investigate how chromophore organization and protein environment in PPCs impacts on EET efficiency and robustness. In a prototypical PPC model, the Fenna-Matthews-Olson (FMO) complex, we consider the impact on EET efficiency of both disrupting the chromophore network and changing the influence of (local and global) environmental dephasing. Surprisingly, we find a large degree of resilience to changes in both chromophore network and protein environmental dephasing, the extent of which is greater than previously observed; for example, FMO maintains EET when 50% of the constituent chromophores are removed, or when environmental dephasing fluctuations vary over two orders-of-magnitude relative to the in vivo system. We also highlight the fact that the influence of local dephasing can be strongly dependent on the characteristics of the EET network and the initial excitation; for example, initial excitations resulting in rapid coherent decay are generally insensitive to the environment, whereas the incoherent population decay observed following excitation at weakly coupled chromophores demonstrates a more pronounced dependence on dephasing rate as a result of the greater possibility of local exciton trapping. Finally, we show that the FMO electronic Hamiltonian is not particularly optimised for EET; instead, it is just one of many possible chromophore organisations which demonstrate a good level of EET transport efficiency following excitation at different chromophores. Overall, these robustness and efficiency characteristics are attributed to the highly

Robust Self Tuning Controllers

DEFF Research Database (Denmark)

Poulsen, Niels Kjølstad

1985-01-01

The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...... has several operation modes and a detector for controlling the mode. A special self tuning controller has been developed to regulate plant with changing time delay.......The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...

On the robustness of EC-PC spike detection method for online neural recording.

Science.gov (United States)

Zhou, Yin; Wu, Tong; Rastegarnia, Amir; Guan, Cuntai; Keefer, Edward; Yang, Zhi

2014-09-30

Online spike detection is an important step to compress neural data and perform real-time neural information decoding. An unsupervised, automatic, yet robust signal processing is strongly desired, thus it can support a wide range of applications. We have developed a novel spike detection algorithm called "exponential component-polynomial component" (EC-PC) spike detection. We firstly evaluate the robustness of the EC-PC spike detector under different firing rates and SNRs. Secondly, we show that the detection Precision can be quantitatively derived without requiring additional user input parameters. We have realized the algorithm (including training) into a 0.13 μm CMOS chip, where an unsupervised, nonparametric operation has been demonstrated. Both simulated data and real data are used to evaluate the method under different firing rates (FRs), SNRs. The results show that the EC-PC spike detector is the most robust in comparison with some popular detectors. Moreover, the EC-PC detector can track changes in the background noise due to the ability to re-estimate the neural data distribution. Both real and synthesized data have been used for testing the proposed algorithm in comparison with other methods, including the absolute thresholding detector (AT), median absolute deviation detector (MAD), nonlinear energy operator detector (NEO), and continuous wavelet detector (CWD). Comparative testing results reveals that the EP-PC detection algorithm performs better than the other algorithms regardless of recording conditions. The EC-PC spike detector can be considered as an unsupervised and robust online spike detection. It is also suitable for hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

Robustness analysis of chiller sequencing control

International Nuclear Information System (INIS)

Liao, Yundan; Sun, Yongjun; Huang, Gongsheng

2015-01-01

Highlights: • Uncertainties with chiller sequencing control were systematically quantified. • Robustness of chiller sequencing control was systematically analyzed. • Different sequencing control strategies were sensitive to different uncertainties. • A numerical method was developed for easy selection of chiller sequencing control. - Abstract: Multiple-chiller plant is commonly employed in the heating, ventilating and air-conditioning system to increase operational feasibility and energy-efficiency under part load condition. In a multiple-chiller plant, chiller sequencing control plays a key role in achieving overall energy efficiency while not sacrifices the cooling sufficiency for indoor thermal comfort. Various sequencing control strategies have been developed and implemented in practice. Based on the observation that (i) uncertainty, which cannot be avoided in chiller sequencing control, has a significant impact on the control performance and may cause the control fail to achieve the expected control and/or energy performance; and (ii) in current literature few studies have systematically addressed this issue, this paper therefore presents a study on robustness analysis of chiller sequencing control in order to understand the robustness of various chiller sequencing control strategies under different types of uncertainty. Based on the robustness analysis, a simple and applicable method is developed to select the most robust control strategy for a given chiller plant in the presence of uncertainties, which will be verified using case studies

Phase-Field Relaxation of Topology Optimization with Local Stress Constraints

DEFF Research Database (Denmark)

Stainko, Roman; Burger, Martin

2006-01-01

inequality constraints. We discretize the problem by finite elements and solve the arising finite-dimensional programming problems by a primal-dual interior point method. Numerical experiments for problems with local stress constraints based on different criteria indicate the success and robustness......We introduce a new relaxation scheme for structural topology optimization problems with local stress constraints based on a phase-field method. In the basic formulation we have a PDE-constrained optimization problem, where the finite element and design analysis are solved simultaneously...

Robust linearized image reconstruction for multifrequency EIT of the breast.

Science.gov (United States)

Boverman, Gregory; Kao, Tzu-Jen; Kulkarni, Rujuta; Kim, Bong Seok; Isaacson, David; Saulnier, Gary J; Newell, Jonathan C

2008-10-01

Electrical impedance tomography (EIT) is a developing imaging modality that is beginning to show promise for detecting and characterizing tumors in the breast. At Rensselaer Polytechnic Institute, we have developed a combined EIT-tomosynthesis system that allows for the coregistered and simultaneous analysis of the breast using EIT and X-ray imaging. A significant challenge in EIT is the design of computationally efficient image reconstruction algorithms which are robust to various forms of model mismatch. Specifically, we have implemented a scaling procedure that is robust to the presence of a thin highly-resistive layer of skin at the boundary of the breast and we have developed an algorithm to detect and exclude from the image reconstruction electrodes that are in poor contact with the breast. In our initial clinical studies, it has been difficult to ensure that all electrodes make adequate contact with the breast, and thus procedures for the use of data sets containing poorly contacting electrodes are particularly important. We also present a novel, efficient method to compute the Jacobian matrix for our linearized image reconstruction algorithm by reducing the computation of the sensitivity for each voxel to a quadratic form. Initial clinical results are presented, showing the potential of our algorithms to detect and localize breast tumors.

Attractive ellipsoids in robust control

CERN Document Server

Poznyak, Alexander; Azhmyakov, Vadim

2014-01-01

This monograph introduces a newly developed robust-control design technique for a wide class of continuous-time dynamical systems called the “attractive ellipsoid method.” Along with a coherent introduction to the proposed control design and related topics, the monograph studies nonlinear affine control systems in the presence of uncertainty and presents a constructive and easily implementable control strategy that guarantees certain stability properties. The authors discuss linear-style feedback control synthesis in the context of the above-mentioned systems. The development and physical implementation of high-performance robust-feedback controllers that work in the absence of complete information is addressed, with numerous examples to illustrate how to apply the attractive ellipsoid method to mechanical and electromechanical systems. While theorems are proved systematically, the emphasis is on understanding and applying the theory to real-world situations. Attractive Ellipsoids in Robust Control will a...

Advances in robust fractional control

CERN Document Server

Padula, Fabrizio

2015-01-01

This monograph presents design methodologies for (robust) fractional control systems. It shows the reader how to take advantage of the superior flexibility of fractional control systems compared with integer-order systems in achieving more challenging control requirements. There is a high degree of current interest in fractional systems and fractional control arising from both academia and industry and readers from both milieux are catered to in the text. Different design approaches having in common a trade-off between robustness and performance of the control system are considered explicitly. The text generalizes methodologies, techniques and theoretical results that have been successfully applied in classical (integer) control to the fractional case. The first part of Advances in Robust Fractional Control is the more industrially-oriented. It focuses on the design of fractional controllers for integer processes. In particular, it considers fractional-order proportional-integral-derivative controllers, becau...

Forecasting exchange rates: a robust regression approach

OpenAIRE

Preminger, Arie; Franck, Raphael

2005-01-01

The least squares estimation method as well as other ordinary estimation method for regression models can be severely affected by a small number of outliers, thus providing poor out-of-sample forecasts. This paper suggests a robust regression approach, based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by outliers. A robust linear autoregressive (RAR) and a robust neural network (RNN) models are estimated to study the predictabil...

Robust-yet-fragile nature of interdependent networks

Science.gov (United States)

Tan, Fei; Xia, Yongxiang; Wei, Zhi

2015-05-01

Interdependent networks have been shown to be extremely vulnerable based on the percolation model. Parshani et al. [Europhys. Lett. 92, 68002 (2010), 10.1209/0295-5075/92/68002] further indicated that the more intersimilar networks are, the more robust they are to random failures. When traffic load is considered, how do the coupling patterns impact cascading failures in interdependent networks? This question has been largely unexplored until now. In this paper, we address this question by investigating the robustness of interdependent Erdös-Rényi random graphs and Barabási-Albert scale-free networks under either random failures or intentional attacks. It is found that interdependent Erdös-Rényi random graphs are robust yet fragile under either random failures or intentional attacks. Interdependent Barabási-Albert scale-free networks, however, are only robust yet fragile under random failures but fragile under intentional attacks. We further analyze the interdependent communication network and power grid and achieve similar results. These results advance our understanding of how interdependency shapes network robustness.

Model Robust Calibration: Method and Application to Electronically-Scanned Pressure Transducers

Science.gov (United States)

Walker, Eric L.; Starnes, B. Alden; Birch, Jeffery B.; Mays, James E.

2010-01-01

This article presents the application of a recently developed statistical regression method to the controlled instrument calibration problem. The statistical method of Model Robust Regression (MRR), developed by Mays, Birch, and Starnes, is shown to improve instrument calibration by reducing the reliance of the calibration on a predetermined parametric (e.g. polynomial, exponential, logarithmic) model. This is accomplished by allowing fits from the predetermined parametric model to be augmented by a certain portion of a fit to the residuals from the initial regression using a nonparametric (locally parametric) regression technique. The method is demonstrated for the absolute scale calibration of silicon-based pressure transducers.

A robust classic.

Science.gov (United States)

Kutzner, Florian; Vogel, Tobias; Freytag, Peter; Fiedler, Klaus

2011-01-01

In the present research, we argue for the robustness of illusory correlations (ICs, Hamilton & Gifford, 1976) regarding two boundary conditions suggested in previous research. First, we argue that ICs are maintained under extended experience. Using simulations, we derive conflicting predictions. Whereas noise-based accounts predict ICs to be maintained (Fielder, 2000; Smith, 1991), a prominent account based on discrepancy-reducing feedback learning predicts ICs to disappear (Van Rooy et al., 2003). An experiment involving 320 observations with majority and minority members supports the claim that ICs are maintained. Second, we show that actively using the stereotype to make predictions that are met with reward and punishment does not eliminate the bias. In addition, participants' operant reactions afford a novel online measure of ICs. In sum, our findings highlight the robustness of ICs that can be explained as a result of unbiased but noisy learning.

Localized modes in optics of photonic liquid crystals with local anisotropy of absorption

Energy Technology Data Exchange (ETDEWEB)

Belyakov, V. A., E-mail: bel1937@mail.ru, E-mail: bel@landau.ac.ru [Russian Academy of Science, Landau Institute for Theoretical Physics (Russian Federation); Semenov, S. V. [National Research Center “Kurchatov Institute,” (Russian Federation)

2016-05-15

The localized optical modes in spiral photonic liquid crystals are theoretically studied for the certainty at the example of chiral liquid crystals (CLCs) for the case of CLC with an anisotropic local absorption. The model adopted here (absence of dielectric interfaces in the structures under investigation) makes it possible to get rid of mixing of polarizations on the surfaces of the CLC layer and of the defect structure and to reduce the corresponding equations to only the equations for light with polarization diffracting in the CLC. The dispersion equations determining connection of the edge mode (EM) and defect mode (DM) frequencies with the CLC layer parameters (anisotropy of local absorption, CLC order parameter) and other parameters of the DMS are obtained. Analytic expressions for the transmission and reflection coefficients of CLC layer and DMS for the case of CLC with an anisotropic local absorption are presented and analyzed. It is shown that the CLC layers with locally anisotropic absorption reduce the EM and DM lifetimes (and increase the lasing threshold) in the way different from the case of CLC with an isotropic local absorption. Due to the Borrmann effect revealing of which is different at the opposite stop-band edges in the case of CLC layers with an anisotropic local absorption the EM life-times for the EM frequencies at the opposite stop-bands edges may be significantly different. The options of experimental observations of the theoretically revealed phenomena are briefly discussed.

The behavioral economics of social anxiety disorder reveal a robust effect for interpersonal traits.

Science.gov (United States)

Rodebaugh, Thomas L; Tonge, Natasha A; Weisman, Jaclyn S; Lim, Michelle H; Fernandez, Katya C; Bogdan, Ryan

2017-08-01

Recent evidence suggests that reduced generosity among individuals with social anxiety disorder (SAD) in behavioral economic tasks may result from constraint in changing behavior according to interpersonal contingencies. That is, people with SAD may be slower to be more generous when the situation warrants. Conversely, more global effects on generosity may be related to interpersonal vindictiveness, a dimension only somewhat related to SAD. A total of 133 participants, 73 with the generalized form of SAD, completed self-report instruments and a behavioral economic task with simulated interpersonal (friend, romantic partner, stranger) interactions. In a separate visit, friends (n = 88) also came to the lab and rated participants on vindictiveness. Interpersonal vindictiveness was associated with reduced initial and overall giving to simulated friends. SAD predicted a lack of increased giving to a simulated friend, and attenuated an increase in giving to simulated known versus unknown players compared to participants without SAD. Friend-reported vindictiveness predicted in the same direction as diagnosis. However, the findings for SAD were less robust than those for vindictiveness. SAD is perhaps weakly related to behavioral constraint in economic tasks that simulate interpersonal interactions, whereas vindictiveness is strongly related to lower overall generosity as well as (via friend report) behavioral constraint. Further study is needed to better characterize the construct of vindictiveness. Our findings dovetail with the suggestion that SAD is related to impairment in the proposed affiliation and attachment system, but further suggest that direct study of that system may be more fruitful than focusing on disorders. Copyright © 2017 Elsevier Ltd. All rights reserved.

An experiment of a 3D real-time robust visual odometry for intelligent vehicles

OpenAIRE

Rodriguez Florez , Sergio Alberto; Fremont , Vincent; Bonnifait , Philippe

2009-01-01

International audience; Vision systems are nowadays very promising for many on-board vehicles perception functionalities, like obstacles detection/recognition and ego-localization. In this paper, we present a 3D visual odometric method that uses a stereo-vision system to estimate the 3D ego-motion of a vehicle in outdoor road conditions. In order to run in real-time, the studied technique is sparse meaning that it makes use of feature points that are tracked during several frames. A robust sc...

Comparing Four Instructional Techniques for Promoting Robust Knowledge

Science.gov (United States)

Richey, J. Elizabeth; Nokes-Malach, Timothy J.

2015-01-01

Robust knowledge serves as a common instructional target in academic settings. Past research identifying characteristics of experts' knowledge across many domains can help clarify the features of robust knowledge as well as ways of assessing it. We review the expertise literature and identify three key features of robust knowledge (deep,…

Robust inference in sample selection models

KAUST Repository

Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio

2015-01-01

The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman's two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

Robust inference in sample selection models

KAUST Repository

Zhelonkin, Mikhail

2015-11-20

The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman\\'s two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

MULTI-TEMPORAL AND MULTI-SENSOR IMAGE MATCHING BASED ON LOCAL FREQUENCY INFORMATION

Directory of Open Access Journals (Sweden)

X. Liu

2012-08-01

Full Text Available Image Matching is often one of the first tasks in many Photogrammetry and Remote Sensing applications. This paper presents an efficient approach to automated multi-temporal and multi-sensor image matching based on local frequency information. Two new independent image representations, Local Average Phase (LAP and Local Weighted Amplitude (LWA, are presented to emphasize the common scene information, while suppressing the non-common illumination and sensor-dependent information. In order to get the two representations, local frequency information is firstly obtained from Log-Gabor wavelet transformation, which is similar to that of the human visual system; then the outputs of odd and even symmetric filters are used to construct the LAP and LWA. The LAP and LWA emphasize on the phase and amplitude information respectively. As these two representations are both derivative-free and threshold-free, they are robust to noise and can keep as much of the image details as possible. A new Compositional Similarity Measure (CSM is also presented to combine the LAP and LWA with the same weight for measuring the similarity of multi-temporal and multi-sensor images. The CSM can make the LAP and LWA compensate for each other and can make full use of the amplitude and phase of local frequency information. In many image matching applications, the template is usually selected without consideration of its matching robustness and accuracy. In order to overcome this problem, a local best matching point detection is presented to detect the best matching template. In the detection method, we employ self-similarity analysis to identify the template with the highest matching robustness and accuracy. Experimental results using some real images and simulation images demonstrate that the presented approach is effective for matching image pairs with significant scene and illumination changes and that it has advantages over other state-of-the-art approaches, which include: the

Robust methods for data reduction

CERN Document Server

Farcomeni, Alessio

2015-01-01

Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy

Robust synchronization of master-slave chaotic systems using approximate model: An experimental study.

Science.gov (United States)

Ahmed, Hafiz; Salgado, Ivan; Ríos, Héctor

2018-02-01

Robust synchronization of master slave chaotic systems are considered in this work. First an approximate model of the error system is obtained using the ultra-local model concept. Then a Continuous Singular Terminal Sliding-Mode (CSTSM) Controller is designed for the purpose of synchronization. The proposed approach is output feedback-based and uses fixed-time higher order sliding-mode (HOSM) differentiator for state estimation. Numerical simulation and experimental results are given to show the effectiveness of the proposed technique. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Science.gov (United States)

Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun

2014-01-01

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Directory of Open Access Journals (Sweden)

Jianzhong Wang

Full Text Available Recently, Sparse Representation-based Classification (SRC has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW demonstrate the effectiveness of LCJDSRC.

Robust surgery loading

NARCIS (Netherlands)

Hans, Elias W.; Wullink, Gerhard; van Houdenhoven, Mark; Kazemier, Geert

2008-01-01

We consider the robust surgery loading problem for a hospital’s operating theatre department, which concerns assigning surgeries and sufficient planned slack to operating room days. The objective is to maximize capacity utilization and minimize the risk of overtime, and thus cancelled patients. This

Increasing average period lengths by switching of robust chaos maps in finite precision

Science.gov (United States)

Nagaraj, N.; Shastry, M. C.; Vaidya, P. G.

2008-12-01

Grebogi, Ott and Yorke (Phys. Rev. A 38, 1988) have investigated the effect of finite precision on average period length of chaotic maps. They showed that the average length of periodic orbits (T) of a dynamical system scales as a function of computer precision (ɛ) and the correlation dimension (d) of the chaotic attractor: T ˜ɛ-d/2. In this work, we are concerned with increasing the average period length which is desirable for chaotic cryptography applications. Our experiments reveal that random and chaotic switching of deterministic chaotic dynamical systems yield higher average length of periodic orbits as compared to simple sequential switching or absence of switching. To illustrate the application of switching, a novel generalization of the Logistic map that exhibits Robust Chaos (absence of attracting periodic orbits) is first introduced. We then propose a pseudo-random number generator based on chaotic switching between Robust Chaos maps which is found to successfully pass stringent statistical tests of randomness.

Robust policy choice under Calvo and Rotemberg pricing

OpenAIRE

Sienknecht, Sebastian

2012-01-01

This paper examines the robustness of welfare-based policy choices across the nonlinear Calvo and Rotemberg pricing assumptions. Comparisons between simple interest rate rules turn out to be robust and independent of the price dispersion inherent in the Calvo setting. This robustness is violated if there is a policy alternative that controls for price dispersion.

Completed Local Ternary Pattern for Rotation Invariant Texture Classification

Directory of Open Access Journals (Sweden)

Taha H. Rassem

2014-01-01

Full Text Available Despite the fact that the two texture descriptors, the completed modeling of Local Binary Pattern (CLBP and the Completed Local Binary Count (CLBC, have achieved a remarkable accuracy for invariant rotation texture classification, they inherit some Local Binary Pattern (LBP drawbacks. The LBP is sensitive to noise, and different patterns of LBP may be classified into the same class that reduces its discriminating property. Although, the Local Ternary Pattern (LTP is proposed to be more robust to noise than LBP, however, the latter’s weakness may appear with the LTP as well as with LBP. In this paper, a novel completed modeling of the Local Ternary Pattern (LTP operator is proposed to overcome both LBP drawbacks, and an associated completed Local Ternary Pattern (CLTP scheme is developed for rotation invariant texture classification. The experimental results using four different texture databases show that the proposed CLTP achieved an impressive classification accuracy as compared to the CLBP and CLBC descriptors.

Risk, Robustness and Water Resources Planning Under Uncertainty

Science.gov (United States)

Borgomeo, Edoardo; Mortazavi-Naeini, Mohammad; Hall, Jim W.; Guillod, Benoit P.

2018-03-01

Risk-based water resources planning is based on the premise that water managers should invest up to the point where the marginal benefit of risk reduction equals the marginal cost of achieving that benefit. However, this cost-benefit approach may not guarantee robustness under uncertain future conditions, for instance under climatic changes. In this paper, we expand risk-based decision analysis to explore possible ways of enhancing robustness in engineered water resources systems under different risk attitudes. Risk is measured as the expected annual cost of water use restrictions, while robustness is interpreted in the decision-theoretic sense as the ability of a water resource system to maintain performance—expressed as a tolerable risk of water use restrictions—under a wide range of possible future conditions. Linking risk attitudes with robustness allows stakeholders to explicitly trade-off incremental increases in robustness with investment costs for a given level of risk. We illustrate the framework through a case study of London's water supply system using state-of-the -art regional climate simulations to inform the estimation of risk and robustness.

TAO-robust backpropagation learning algorithm.

Science.gov (United States)

Pernía-Espinoza, Alpha V; Ordieres-Meré, Joaquín B; Martínez-de-Pisón, Francisco J; González-Marcos, Ana

2005-03-01

In several fields, as industrial modelling, multilayer feedforward neural networks are often used as universal function approximations. These supervised neural networks are commonly trained by a traditional backpropagation learning format, which minimises the mean squared error (mse) of the training data. However, in the presence of corrupted data (outliers) this training scheme may produce wrong models. We combine the benefits of the non-linear regression model tau-estimates [introduced by Tabatabai, M. A. Argyros, I. K. Robust Estimation and testing for general nonlinear regression models. Applied Mathematics and Computation. 58 (1993) 85-101] with the backpropagation algorithm to produce the TAO-robust learning algorithm, in order to deal with the problems of modelling with outliers. The cost function of this approach has a bounded influence function given by the weighted average of two psi functions, one corresponding to a very robust estimate and the other to a highly efficient estimate. The advantages of the proposed algorithm are studied with an example.

Robustness of holonomic quantum gates

International Nuclear Information System (INIS)

Solinas, P.; Zanardi, P.; Zanghi, N.

2005-01-01

Full text: If the driving field fluctuates during the quantum evolution this produces errors in the applied operator. The holonomic (and geometrical) quantum gates are believed to be robust against some kind of noise. Because of the geometrical dependence of the holonomic operators can be robust against this kind of noise; in fact if the fluctuations are fast enough they cancel out leaving the final operator unchanged. I present the numerical studies of holonomic quantum gates subject to this parametric noise, the fidelity of the noise and ideal evolution is calculated for different noise correlation times. The holonomic quantum gates seem robust not only for fast fluctuating fields but also for slow fluctuating fields. These results can be explained as due to the geometrical feature of the holonomic operator: for fast fluctuating fields the fluctuations are canceled out, for slow fluctuating fields the fluctuations do not perturb the loop in the parameter space. (author)

Robust estimation and hypothesis testing

CERN Document Server

Tiku, Moti L

2004-01-01

In statistical theory and practice, a certain distribution is usually assumed and then optimal solutions sought. Since deviations from an assumed distribution are very common, one cannot feel comfortable with assuming a particular distribution and believing it to be exactly correct. That brings the robustness issue in focus. In this book, we have given statistical procedures which are robust to plausible deviations from an assumed mode. The method of modified maximum likelihood estimation is used in formulating these procedures. The modified maximum likelihood estimators are explicit functions of sample observations and are easy to compute. They are asymptotically fully efficient and are as efficient as the maximum likelihood estimators for small sample sizes. The maximum likelihood estimators have computational problems and are, therefore, elusive. A broad range of topics are covered in this book. Solutions are given which are easy to implement and are efficient. The solutions are also robust to data anomali...

Localization of Cladosporium fulvum hydrophobins reveals a role for HCf-6 in adhesion

DEFF Research Database (Denmark)

Lacroix, Hélène; Whiteford, James; Spanu, Pietro D

2008-01-01

for establishing hydrophobin localization during growth in culture and in plants. In this paper we localize HCf-2, -3, -4 and -5 and compare the data to our previous observations for HCf-1 and -6. In culture, HCf-1, -2, -3 and 4 localize to conidia and also appear on aerial hyphae. HCf-4 is unique...... in that it appears on submerged hyphae. HCf-5 expression is tightly regulated and appears on aerial hyphae early on during growth. Only HCf-1, -3 and -6 were observed during infection; HCf-3 appears on both conidia and emerging germ tubes. We also show that HCf-6 is secreted and coats surfaces under and around...... growing hyphae and demonstrate the effect of deleting HCf-6 on the adhesion of germinating C. fulvum conidia to glass slides....

Enhancing robustness of multiparty quantum correlations using weak measurement

International Nuclear Information System (INIS)

Singh, Uttam; Mishra, Utkarsh; Dhar, Himadri Shekhar

2014-01-01

Multipartite quantum correlations are important resources for the development of quantum information and computation protocols. However, the resourcefulness of multipartite quantum correlations in practical settings is limited by its fragility under decoherence due to environmental interactions. Though there exist protocols to protect bipartite entanglement under decoherence, the implementation of such protocols for multipartite quantum correlations has not been sufficiently explored. Here, we study the effect of local amplitude damping channel on the generalized Greenberger–Horne–Zeilinger state, and use a protocol of optimal reversal quantum weak measurement to protect the multipartite quantum correlations. We observe that the weak measurement reversal protocol enhances the robustness of multipartite quantum correlations. Further it increases the critical damping value that corresponds to entanglement sudden death. To emphasize the efficacy of the technique in protection of multipartite quantum correlation, we investigate two proximately related quantum communication tasks, namely, quantum teleportation in a one sender, many receivers setting and multiparty quantum information splitting, through a local amplitude damping channel. We observe an increase in the average fidelity of both the quantum communication tasks under the weak measurement reversal protocol. The method may prove beneficial, for combating external interactions, in other quantum information tasks using multipartite resources. - Highlights: • Extension of weak measurement reversal scheme to protect multiparty quantum correlations. • Protection of multiparty quantum correlation under local amplitude damping noise. • Enhanced fidelity of quantum teleportation in one sender and many receivers setting. • Enhanced fidelity of quantum information splitting protocol

Enhancing robustness of multiparty quantum correlations using weak measurement

Energy Technology Data Exchange (ETDEWEB)

Singh, Uttam, E-mail: uttamsingh@hri.res.in [Quantum Information and Computation Group, Harish-Chandra Research Institute, Chhatnag Road, Jhunsi, Allahabad 211 019 (India); Mishra, Utkarsh, E-mail: utkarsh@hri.res.in [Quantum Information and Computation Group, Harish-Chandra Research Institute, Chhatnag Road, Jhunsi, Allahabad 211 019 (India); Dhar, Himadri Shekhar, E-mail: dhar.himadri@gmail.com [School of Physical Sciences, Jawaharlal Nehru University, New Delhi 110067 (India)

2014-11-15

Multipartite quantum correlations are important resources for the development of quantum information and computation protocols. However, the resourcefulness of multipartite quantum correlations in practical settings is limited by its fragility under decoherence due to environmental interactions. Though there exist protocols to protect bipartite entanglement under decoherence, the implementation of such protocols for multipartite quantum correlations has not been sufficiently explored. Here, we study the effect of local amplitude damping channel on the generalized Greenberger–Horne–Zeilinger state, and use a protocol of optimal reversal quantum weak measurement to protect the multipartite quantum correlations. We observe that the weak measurement reversal protocol enhances the robustness of multipartite quantum correlations. Further it increases the critical damping value that corresponds to entanglement sudden death. To emphasize the efficacy of the technique in protection of multipartite quantum correlation, we investigate two proximately related quantum communication tasks, namely, quantum teleportation in a one sender, many receivers setting and multiparty quantum information splitting, through a local amplitude damping channel. We observe an increase in the average fidelity of both the quantum communication tasks under the weak measurement reversal protocol. The method may prove beneficial, for combating external interactions, in other quantum information tasks using multipartite resources. - Highlights: • Extension of weak measurement reversal scheme to protect multiparty quantum correlations. • Protection of multiparty quantum correlation under local amplitude damping noise. • Enhanced fidelity of quantum teleportation in one sender and many receivers setting. • Enhanced fidelity of quantum information splitting protocol.

A comparative analysis of global and local processing of hierarchical visual stimuli in young children (Homo sapiens) and monkeys (Cebus apella).

Science.gov (United States)

De Lillo, Carlo; Spinozzi, Giovanna; Truppa, Valentina; Naylor, Donna M

2005-05-01

Results obtained with preschool children (Homo sapiens) were compared with results previously obtained from capuchin monkeys (Cebus apella) in matching-to-sample tasks featuring hierarchical visual stimuli. In Experiment 1, monkeys, in contrast with children, showed an advantage in matching the stimuli on the basis of their local features. These results were replicated in a 2nd experiment in which control trials enabled the authors to rule out that children used spurious cues to solve the matching task. In a 3rd experiment featuring conditions in which the density of the stimuli was manipulated, monkeys' accuracy in the processing of the global shape of the stimuli was negatively affected by the separation of the local elements, whereas children's performance was robust across testing conditions. Children's response latencies revealed a global precedence in the 2nd and 3rd experiments. These results show differences in the processing of hierarchical stimuli by humans and monkeys that emerge early during childhood. 2005 APA, all rights reserved

Robust Structured Control Design via LMI Optimization

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Stoustrup, Jakob

2011-01-01

This paper presents a new procedure for discrete-time robust structured control design. Parameter-dependent nonconvex conditions for stabilizable and induced L2-norm performance controllers are solved by an iterative linear matrix inequalities (LMI) optimization. A wide class of controller...... structures including decentralized of any order, fixed-order dynamic output feedback, static output feedback can be designed robust to polytopic uncertainties. Stability is proven by a parameter-dependent Lyapunov function. Numerical examples on robust stability margins shows that the proposed procedure can...

Structure-aware Local Sparse Coding for Visual Tracking

KAUST Repository

Qi, Yuankai

2018-01-24

Sparse coding has been applied to visual tracking and related vision problems with demonstrated success in recent years. Existing tracking methods based on local sparse coding sample patches from a target candidate and sparsely encode these using a dictionary consisting of patches sampled from target template images. The discriminative strength of existing methods based on local sparse coding is limited as spatial structure constraints among the template patches are not exploited. To address this problem, we propose a structure-aware local sparse coding algorithm which encodes a target candidate using templates with both global and local sparsity constraints. For robust tracking, we show local regions of a candidate region should be encoded only with the corresponding local regions of the target templates that are the most similar from the global view. Thus, a more precise and discriminative sparse representation is obtained to account for appearance changes. To alleviate the issues with tracking drifts, we design an effective template update scheme. Extensive experiments on challenging image sequences demonstrate the effectiveness of the proposed algorithm against numerous stateof- the-art methods.

Epigenomic Co-localization and Co-evolution Reveal a Key Role for 5hmC as a Communication Hub in the Chromatin Network of ESCs

Directory of Open Access Journals (Sweden)

David Juan

2016-02-01

Full Text Available Summary: Epigenetic communication through histone and cytosine modifications is essential for gene regulation and cell identity. Here, we propose a framework that is based on a chromatin communication model to get insight on the function of epigenetic modifications in ESCs. The epigenetic communication network was inferred from genome-wide location data plus extensive manual annotation. Notably, we found that 5-hydroxymethylcytosine (5hmC is the most-influential hub of this network, connecting DNA demethylation to nucleosome remodeling complexes and to key transcription factors of pluripotency. Moreover, an evolutionary analysis revealed a central role of 5hmC in the co-evolution of chromatin-related proteins. Further analysis of regions where 5hmC co-localizes with specific interactors shows that each interaction points to chromatin remodeling, stemness, differentiation, or metabolism. Our results highlight the importance of cytosine modifications in the epigenetic communication of ESCs. : 5-hydroxymethylcytosine (5hmC plays a key role in the epigenomic communication network of embryonic stem cells. Juan et al. build a communication network based in co-localization of epigenomic data and literature. The analysis of the network and its components reveals that proteins reading and editing 5hmC co-evolve and serve as links between diverse molecular processes.

The Crane Robust Control

Directory of Open Access Journals (Sweden)

Marek Hicar

2004-01-01

Full Text Available The article is about a control design for complete structure of the crane: crab, bridge and crane uplift.The most important unknown parameters for simulations are burden weight and length of hanging rope. We will use robustcontrol for crab and bridge control to ensure adaptivity for burden weight and rope length. Robust control will be designed for current control of the crab and bridge, necessary is to know the range of unknown parameters. Whole robust will be splitto subintervals and after correct identification of unknown parameters the most suitable robust controllers will be chosen.The most important condition at the crab and bridge motion is avoiding from burden swinging in the final position. Crab and bridge drive is designed by asynchronous motor fed from frequency converter. We will use crane uplift with burden weightobserver in combination for uplift, crab and bridge drive with cooperation of their parameters: burden weight, rope length and crab and bridge position. Controllers are designed by state control method. We will use preferably a disturbance observerwhich will identify burden weight as a disturbance. The system will be working in both modes at empty hook as well asat maximum load: burden uplifting and dropping down.

Robust synchronization control scheme of a population of nonlinear stochastic synthetic genetic oscillators under intrinsic and extrinsic molecular noise via quorum sensing.

Science.gov (United States)

Chen, Bor-Sen; Hsu, Chih-Yuan

2012-10-26

Collective rhythms of gene regulatory networks have been a subject of considerable interest for biologists and theoreticians, in particular the synchronization of dynamic cells mediated by intercellular communication. Synchronization of a population of synthetic genetic oscillators is an important design in practical applications, because such a population distributed over different host cells needs to exploit molecular phenomena simultaneously in order to emerge a biological phenomenon. However, this synchronization may be corrupted by intrinsic kinetic parameter fluctuations and extrinsic environmental molecular noise. Therefore, robust synchronization is an important design topic in nonlinear stochastic coupled synthetic genetic oscillators with intrinsic kinetic parameter fluctuations and extrinsic molecular noise. Initially, the condition for robust synchronization of synthetic genetic oscillators was derived based on Hamilton Jacobi inequality (HJI). We found that if the synchronization robustness can confer enough intrinsic robustness to tolerate intrinsic parameter fluctuation and extrinsic robustness to filter the environmental noise, then robust synchronization of coupled synthetic genetic oscillators is guaranteed. If the synchronization robustness of a population of nonlinear stochastic coupled synthetic genetic oscillators distributed over different host cells could not be maintained, then robust synchronization could be enhanced by external control input through quorum sensing molecules. In order to simplify the analysis and design of robust synchronization of nonlinear stochastic synthetic genetic oscillators, the fuzzy interpolation method was employed to interpolate several local linear stochastic coupled systems to approximate the nonlinear stochastic coupled system so that the HJI-based synchronization design problem could be replaced by a simple linear matrix inequality (LMI)-based design problem, which could be solved with the help of LMI

An Design of HF-Band RFID System with Multiple Readers and Passive Tags for Indoor Mobile Robot Self-Localization

Directory of Open Access Journals (Sweden)

Jian Mi

2016-07-01

Full Text Available Radio frequency identification (RFID technology has already been explored for efficient self-localization of indoor mobile robots. A mobile robot equipped with RFID readers detects passive RFID tags installed on the floor in order to locate itself. The Monte-Carlo localization (MCL method enables the localization of a mobile robot equipped with an RFID system with reasonable accuracy, sufficient robustness and low computational cost. The arrangements of RFID readers and tags and the size of antennas are important design parameters for realizing accurate and robust self-localization using a low-cost RFID system. The design of a likelihood model of RFID tag detection is also crucial for the accurate self-localization. This paper presents a novel design and arrangement of RFID readers and tags for indoor mobile robot self-localization. First, by considering small-sized and large-sized antennas of an RFID reader, we show how the design of the likelihood model affects the accuracy of self-localization. We also design a novel likelihood model by taking into consideration the characteristics of the communication range of an RFID system with a large antenna. Second, we propose a novel arrangement of RFID tags with eight RFID readers, which results in the RFID system configuration requiring much fewer readers and tags while retaining reasonable accuracy of self-localization. We verify the performances of MCL-based self-localization realized using the high-frequency (HF-band RFID system with eight RFID readers and a lower density of RFID tags installed on the floor based on MCL in simulated and real environments. The results of simulations and real environment experiments demonstrate that our proposed low-cost HF-band RFID system realizes accurate and robust self-localization of an indoor mobile robot.

Towards Robust Face Recognition from Video

International Nuclear Information System (INIS)

Price, JR

2001-01-01

A novel, template-based method for face recognition is presented. The goals of the proposed method are to integrate multiple observations for improved robustness and to provide auxiliary confidence data for subsequent use in an automated video surveillance system. The proposed framework consists of a parallel system of classifiers, referred to as observers, where each observer is trained on one face region. The observer outputs are combined to yield the final recognition result. Three of the four confounding factors-expression, illumination, and decoration-are specifically addressed in this paper. The extension of the proposed approach to address the fourth confounding factor-pose-is straightforward and well supported in previous work. A further contribution of the proposed approach is the computation of a revealing confidence measure. This confidence measure will aid the subsequent application of the proposed method to video surveillance scenarios. Results are reported for a database comprising 676 images of 160 subjects under a variety of challenging circumstances. These results indicate significant performance improvements over previous methods and demonstrate the usefulness of the confidence data

Robust structural optimization using Gauss-type quadrature formula

International Nuclear Information System (INIS)

Lee, Sang Hoon; Seo, Ki Seog; Chen, Shikui; Chen, Wei

2009-01-01

In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the Tensor Product Quadrature (TPQ) formula and the Univariate Dimension Reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.

Robust structural optimization using Gauss-type quadrature formula

Energy Technology Data Exchange (ETDEWEB)

Lee, Sang Hoon; Seo, Ki Seog [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Chen, Shikui; Chen, Wei [Northwestern University, Illinois (United States)

2009-07-01

In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the Tensor Product Quadrature (TPQ) formula and the Univariate Dimension Reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.

Robust Structural Optimization Using Gauss-type Quadrature Formula

Energy Technology Data Exchange (ETDEWEB)

Lee, Sang Hoon; Seo, Ki Seog; Chen, Shikui; Chen, Wei [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2009-08-15

In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the tensor product quadrature (TPQ) formula and the univariate dimension reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.

Robust Structural Optimization Using Gauss-type Quadrature Formula

International Nuclear Information System (INIS)

Lee, Sang Hoon; Seo, Ki Seog; Chen, Shikui; Chen, Wei

2009-01-01

In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the tensor product quadrature (TPQ) formula and the univariate dimension reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty

Perspective: Evolution and detection of genetic robustness

NARCIS (Netherlands)

Visser, de J.A.G.M.; Hermisson, J.; Wagner, G.P.; Ancel Meyers, L.; Bagheri-Chaichian, H.; Blanchard, J.L.; Chao, L.; Cheverud, J.M.; Elena, S.F.; Fontana, W.; Gibson, G.; Hansen, T.F.; Krakauer, D.; Lewontin, R.C.; Ofria, C.; Rice, S.H.; Dassow, von G.; Wagner, A.; Whitlock, M.C.

2003-01-01

Robustness is the invariance of phenotypes in the face of perturbation. The robustness of phenotypes appears at various levels of biological organization, including gene expression, protein folding, metabolic flux, physiological homeostasis, development, and even organismal fitness. The mechanisms

Emergence of robustness in networks of networks

Science.gov (United States)

Roth, Kevin; Morone, Flaviano; Min, Byungjoon; Makse, Hernán A.

2017-06-01

A model of interdependent networks of networks (NONs) was introduced recently [Proc. Natl. Acad. Sci. (USA) 114, 3849 (2017), 10.1073/pnas.1620808114] in the context of brain activation to identify the neural collective influencers in the brain NON. Here we investigate the emergence of robustness in such a model, and we develop an approach to derive an exact expression for the random percolation transition in Erdös-Rényi NONs of this kind. Analytical calculations are in agreement with numerical simulations, and highlight the robustness of the NON against random node failures, which thus presents a new robust universality class of NONs. The key aspect of this robust NON model is that a node can be activated even if it does not belong to the giant mutually connected component, thus allowing the NON to be built from below the percolation threshold, which is not possible in previous models of interdependent networks. Interestingly, the phase diagram of the model unveils particular patterns of interconnectivity for which the NON is most vulnerable, thereby marking the boundary above which the robustness of the system improves with increasing dependency connections.

Hiding the weakness: structural robustness using origami design

Science.gov (United States)

Liu, Bin; Santangelo, Christian; Cohen, Itai

2015-03-01

A non-deformable structure is typically associated with infinitely stiff materials that resist distortion. In this work, we designed a structure with a region that will not deform even though it is made of arbitrarily compliant materials. More specifically, we show that a foldable sheet with a circular hole in the middle can be deformed externally with the internal geometry of the hole unaffected. Instead of strengthening the local stiffness, we fine tune the crease patterns so that all the soft modes that can potentially deform the internal geometry are not accessible through strain on the external boundary. The inner structure is thus protected by the topological mechanics, based on the detailed geometry of how the vertices in the foldable sheet are connected. In this way, we isolate the structural robustness from the mechanical properties of the materials, which introduces an extra degree of freedom for structural design.

Framework for Robustness Assessment of Timber Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

2011-01-01

This paper presents a theoretical framework for the design and analysis of robustness of timber structures. This is actualized by a more4 frequent use of advanced types of timber structures with limited redundancy and serious consequences in the case of failure. Combined with increased requirements...... to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new structures essential. Further, the collapse of the Ballerup Super Arena, the bad Reichenhall Ice-Arena and a number of other structural systems during the last 10 years has...... increased the interest in robustness. Typically, modern structural design codes require that ‘the consequence of damages to structures should not be disproportional to the causes of the damages’. However, although the importance of robustness for structural design is widely recognized, the code requirements...

UTV Expansion Pack: Special-Purpose Rank-Revealing Algorithms

DEFF Research Database (Denmark)

Fierro, Ricardo D.; Hansen, Per Christian

2005-01-01

This collection of Matlab 7.0 software supplements and complements the package UTV Tools from 1999, and includes implementations of special-purpose rank-revealing algorithms developed since the publication of the original package. We provide algorithms for computing and modifying symmetric rank-r...... values of a sparse or structured matrix. These new algorithms have applications in signal processing, optimization and LSI information retrieval.......This collection of Matlab 7.0 software supplements and complements the package UTV Tools from 1999, and includes implementations of special-purpose rank-revealing algorithms developed since the publication of the original package. We provide algorithms for computing and modifying symmetric rank......-revealing VSV decompositions, we expand the algorithms for the ULLV decomposition of a matrix pair to handle interference-type problems with a rank-deficient covariance matrix, and we provide a robust and reliable Lanczos algorithm which - despite its simplicity - is able to capture all the dominant singular...

Robust Exponential Synchronization for a Class of Master-Slave Distributed Parameter Systems with Spatially Variable Coefficients and Nonlinear Perturbation

Directory of Open Access Journals (Sweden)

Chengdong Yang

2015-01-01

Full Text Available This paper addresses the exponential synchronization problem of a class of master-slave distributed parameter systems (DPSs with spatially variable coefficients and spatiotemporally variable nonlinear perturbation, modeled by a couple of semilinear parabolic partial differential equations (PDEs. With a locally Lipschitz constraint, the perturbation is a continuous function of time, space, and system state. Firstly, a sufficient condition for the robust exponential synchronization of the unforced semilinear master-slave PDE systems is investigated for all admissible nonlinear perturbations. Secondly, a robust distributed proportional-spatial derivative (P-sD state feedback controller is desired such that the closed-loop master-slave PDE systems achieve exponential synchronization. Using Lyapunov’s direct method and the technique of integration by parts, the main results of this paper are presented in terms of spatial differential linear matrix inequalities (SDLMIs. Finally, two numerical examples are provided to show the effectiveness of the proposed methods applied to the robust exponential synchronization problem of master-slave PDE systems with nonlinear perturbation.

Robust economic optimization and environmental policy analysis for microgrid planning: An application to Taichung Industrial Park, Taiwan

International Nuclear Information System (INIS)

Yu, Nan; Kang, Jin-Su; Chang, Chung-Chuan; Lee, Tai-Yong; Lee, Dong-Yup

2016-01-01

This study aims to provide economical and environmentally friendly solutions for a microgrid system with distributed energy resources in the design stage, considering multiple uncertainties during operation and conflicting interests among diverse microgrid stakeholders. For the purpose, we develop a multi-objective optimization model for robust microgrid planning, on the basis of an economic robustness measure, i.e. the worst-case cost among possible scenarios, to reduce the variability among scenario costs caused by uncertainties. The efficacy of the model is successfully demonstrated by applying it to Taichung Industrial Park in Taiwan, an industrial complex, where significant amount of greenhouse gases are emitted. Our findings show that the most robust solution, but the highest cost, mainly includes 45% (26.8 MW) of gas engine and 47% (28 MW) of photovoltaic panel with the highest system capacity (59 MW). Further analyses reveal the environmental benefits from the significant reduction of the expected annual CO_2 emission and carbon tax by about half of the current utility facilities in the region. In conclusion, the developed model provides an efficient decision-making tool for robust microgrid planning at the preliminary stage. - Highlights: • Developed robust economic and environmental optimization model for microgrid planning. • Provided Pareto optimal planning solutions for Taichung Industrial Park, Taiwan. • Suggested microgrid configuration with significant economic and environmental benefits. • Identified gas engine and photovoltaic panel as two promising energy sources.

Local Anesthesia at ST36 to Reveal Responding Brain Areas to deqi

Directory of Open Access Journals (Sweden)

Ling-min Jin

2014-01-01

Full Text Available Background. Development of non-deqi control is still a challenge. This study aims to set up a potential approach to non-deqi control by using lidocaine anesthesia at ST36. Methods. Forty healthy volunteers were recruited and they received two fMRI scans. One was accompanied with manual acupuncture at ST36 (DQ group, and another was associated with both local anesthesia and manual acupuncture at the same acupoint (LA group. Results. Comparing to DQ group, more than 90 percent deqi sensations were reduced by local anesthesia in LA group. The mainly activated regions in DQ group were bilateral IFG, S1, primary motor cortex, IPL, thalamus, insula, claustrum, cingulate gyrus, putamen, superior temporal gyrus, and cerebellum. Surprisingly only cerebellum showed significant activation in LA group. Compared to the two groups, bilateral S1, insula, ipsilateral IFG, IPL, claustrum, and contralateral ACC were remarkably activated. Conclusions. Local anesthesia at ST36 is able to block most of the deqi feelings and inhibit brain responses to deqi, which would be developed into a potential approach for non-deqi control. Bilateral S1, insula, ipsilateral IFG, IPL, claustrum, and contralateral ACC might be the key brain regions responding to deqi.

Robust energy-absorbing compensators for the ACTEX II test article

Science.gov (United States)

Blaurock, Carl A.; Miller, David W.; Nye, Ted

1995-05-01

The paper addresses the problem of satellite solar panel vibration. A multi-layer vibration control scheme is investigated using a flight test article. Key issues in the active control portion are presented in the paper. The paper discusses the primary control design drivers, which are the time variations in modal frequencies due to configuration and thermal changes. A local control design approach is investigated, but found to be unworkable due to sensor/actuator non-collocation. An alternate design process uses linear robust control techniques, by describing the modal shifts as uncertainties. Multiple modal design, alpha- shifted multiple model, and a feedthrough compensation scheme are examined. Ground and simulation tests demonstrate that the resulting controllers provide significant vibration reduction in the presence of expected system variations.

A kinematic approach for efficient and robust simulation of the cardiac beating motion.

Directory of Open Access Journals (Sweden)

Takashi Ijiri

Full Text Available Computer simulation techniques for cardiac beating motions potentially have many applications and a broad audience. However, most existing methods require enormous computational costs and often show unstable behavior for extreme parameter sets, which interrupts smooth simulation study and make it difficult to apply them to interactive applications. To address this issue, we present an efficient and robust framework for simulating the cardiac beating motion. The global cardiac motion is generated by the accumulation of local myocardial fiber contractions. We compute such local-to-global deformations using a kinematic approach; we divide a heart mesh model into overlapping local regions, contract them independently according to fiber orientation, and compute a global shape that satisfies contracted shapes of all local regions as much as possible. A comparison between our method and a physics-based method showed that our method can generate motion very close to that of a physics-based simulation. Our kinematic method has high controllability; the simulated ventricle-wall-contraction speed can be easily adjusted to that of a real heart by controlling local contraction timing. We demonstrate that our method achieves a highly realistic beating motion of a whole heart in real time on a consumer-level computer. Our method provides an important step to bridge a gap between cardiac simulations and interactive applications.

A Robust Design Applicability Model

DEFF Research Database (Denmark)

Ebro, Martin; Lars, Krogstie; Howard, Thomas J.

2015-01-01

to be applicable in organisations assigning a high importance to one or more factors that are known to be impacted by RD, while also experiencing a high level of occurrence of this factor. The RDAM supplements existing maturity models and metrics to provide a comprehensive set of data to support management......This paper introduces a model for assessing the applicability of Robust Design (RD) in a project or organisation. The intention of the Robust Design Applicability Model (RDAM) is to provide support for decisions by engineering management considering the relevant level of RD activities...

Performance Evaluation of Localization Accuracy for a Log-Normal Shadow Fading Wireless Sensor Network under Physical Barrier Attacks.

Science.gov (United States)

Hussein, Ahmed Abdulqader; Rahman, Tharek A; Leow, Chee Yen

2015-12-04

Localization is an apparent aspect of a wireless sensor network, which is the focus of much interesting research. One of the severe conditions that needs to be taken into consideration is localizing a mobile target through a dispersed sensor network in the presence of physical barrier attacks. These attacks confuse the localization process and cause location estimation errors. Range-based methods, like the received signal strength indication (RSSI), face the major influence of this kind of attack. This paper proposes a solution based on a combination of multi-frequency multi-power localization (C-MFMPL) and step function multi-frequency multi-power localization (SF-MFMPL), including the fingerprint matching technique and lateration, to provide a robust and accurate localization technique. In addition, this paper proposes a grid coloring algorithm to detect the signal hole map in the network, which refers to the attack-prone regions, in order to carry out corrective actions. The simulation results show the enhancement and robustness of RSS localization performance in the face of log normal shadow fading effects, besides the presence of physical barrier attacks, through detecting, filtering and eliminating the effect of these attacks.

Performance Evaluation of Localization Accuracy for a Log-Normal Shadow Fading Wireless Sensor Network under Physical Barrier Attacks

Science.gov (United States)

Abdulqader Hussein, Ahmed; Rahman, Tharek A.; Leow, Chee Yen

2015-01-01

Localization is an apparent aspect of a wireless sensor network, which is the focus of much interesting research. One of the severe conditions that needs to be taken into consideration is localizing a mobile target through a dispersed sensor network in the presence of physical barrier attacks. These attacks confuse the localization process and cause location estimation errors. Range-based methods, like the received signal strength indication (RSSI), face the major influence of this kind of attack. This paper proposes a solution based on a combination of multi-frequency multi-power localization (C-MFMPL) and step function multi-frequency multi-power localization (SF-MFMPL), including the fingerprint matching technique and lateration, to provide a robust and accurate localization technique. In addition, this paper proposes a grid coloring algorithm to detect the signal hole map in the network, which refers to the attack-prone regions, in order to carry out corrective actions. The simulation results show the enhancement and robustness of RSS localization performance in the face of log normal shadow fading effects, besides the presence of physical barrier attacks, through detecting, filtering and eliminating the effect of these attacks. PMID:26690159

Robust Stacking-Independent Ultrafast Charge Transfer in MoS2/WS2 Bilayers.

Science.gov (United States)

Ji, Ziheng; Hong, Hao; Zhang, Jin; Zhang, Qi; Huang, Wei; Cao, Ting; Qiao, Ruixi; Liu, Can; Liang, Jing; Jin, Chuanhong; Jiao, Liying; Shi, Kebin; Meng, Sheng; Liu, Kaihui

2017-12-26

Van der Waals-coupled two-dimensional (2D) heterostructures have attracted great attention recently due to their high potential in the next-generation photodetectors and solar cells. The understanding of charge-transfer process between adjacent atomic layers is the key to design optimal devices as it directly determines the fundamental response speed and photon-electron conversion efficiency. However, general belief and theoretical studies have shown that the charge transfer behavior depends sensitively on interlayer configurations, which is difficult to control accurately, bringing great uncertainties in device designing. Here we investigate the ultrafast dynamics of interlayer charge transfer in a prototype heterostructure, the MoS 2 /WS 2 bilayer with various stacking configurations, by optical two-color ultrafast pump-probe spectroscopy. Surprisingly, we found that the charge transfer is robust against varying interlayer twist angles and interlayer coupling strength, in time scale of ∼90 fs. Our observation, together with atomic-resolved transmission electron characterization and time-dependent density functional theory simulations, reveals that the robust ultrafast charge transfer is attributed to the heterogeneous interlayer stretching/sliding, which provides additional channels for efficient charge transfer previously unknown. Our results elucidate the origin of transfer rate robustness against interlayer stacking configurations in optical devices based on 2D heterostructures, facilitating their applications in ultrafast and high-efficient optoelectronic and photovoltaic devices in the near future.

Modeling and analyzing cascading dynamics of the Internet based on local congestion information

Science.gov (United States)

Zhu, Qian; Nie, Jianlong; Zhu, Zhiliang; Yu, Hai; Xue, Yang

2018-06-01

Cascading failure has already become one of the vital issues in network science. By considering realistic network operational settings, we propose the congestion function to represent the congested extent of node and construct a local congestion-aware routing strategy with a tunable parameter. We investigate the cascading failures on the Internet triggered by deliberate attacks. Simulation results show that the tunable parameter has an optimal value that makes the network achieve a maximum level of robustness. The robustness of the network has a positive correlation with tolerance parameter, but it has a negative correlation with the packets generation rate. In addition, there exists a threshold of the attacking proportion of nodes that makes the network achieve the lowest robustness. Moreover, by introducing the concept of time delay for information transmission on the Internet, we found that an increase of the time delay will decrease the robustness of the network rapidly. The findings of the paper will be useful for enhancing the robustness of the Internet in the future.

SU-E-T-625: Robustness Evaluation and Robust Optimization of IMPT Plans Based on Per-Voxel Standard Deviation of Dose Distributions.

Science.gov (United States)

Liu, W; Mohan, R

2012-06-01

Proton dose distributions, IMPT in particular, are highly sensitive to setup and range uncertainties. We report a novel method, based on per-voxel standard deviation (SD) of dose distributions, to evaluate the robustness of proton plans and to robustly optimize IMPT plans to render them less sensitive to uncertainties. For each optimization iteration, nine dose distributions are computed - the nominal one, and one each for ± setup uncertainties along x, y and z axes and for ± range uncertainty. SD of dose in each voxel is used to create SD-volume histogram (SVH) for each structure. SVH may be considered a quantitative representation of the robustness of the dose distribution. For optimization, the desired robustness may be specified in terms of an SD-volume (SV) constraint on the CTV and incorporated as a term in the objective function. Results of optimization with and without this constraint were compared in terms of plan optimality and robustness using the so called'worst case' dose distributions; which are obtained by assigning the lowest among the nine doses to each voxel in the clinical target volume (CTV) and the highest to normal tissue voxels outside the CTV. The SVH curve and the area under it for each structure were used as quantitative measures of robustness. Penalty parameter of SV constraint may be varied to control the tradeoff between robustness and plan optimality. We applied these methods to one case each of H&N and lung. In both cases, we found that imposing SV constraint improved plan robustness but at the cost of normal tissue sparing. SVH-based optimization and evaluation is an effective tool for robustness evaluation and robust optimization of IMPT plans. Studies need to be conducted to test the methods for larger cohorts of patients and for other sites. This research is supported by National Cancer Institute (NCI) grant P01CA021239, the University Cancer Foundation via the Institutional Research Grant program at the University of Texas MD

Localization from Visual Landmarks on a Free-Flying Robot

Science.gov (United States)

Coltin, Brian; Fusco, Jesse; Moratto, Zack; Alexandrov, Oleg; Nakamura, Robert

2016-01-01

We present the localization approach for Astrobee, a new free-flying robot designed to navigate autonomously on the International Space Station (ISS). Astrobee will accommodate a variety of payloads and enable guest scientists to run experiments in zero-g, as well as assist astronauts and ground controllers. Astrobee will replace the SPHERES robots which currently operate on the ISS, whose use of fixed ultrasonic beacons for localization limits them to work in a 2 meter cube. Astrobee localizes with monocular vision and an IMU, without any environmental modifications. Visual features detected on a pre-built map, optical flow information, and IMU readings are all integrated into an extended Kalman filter (EKF) to estimate the robot pose. We introduce several modifications to the filter to make it more robust to noise, and extensively evaluate the localization algorithm.

Neural networks, cellular automata, and robust approach applications for vertex localization in the opera target tracker detector

International Nuclear Information System (INIS)

Dmitrievskij, S.G.; Gornushkin, Yu.A.; Ososkov, G.A.

2005-01-01

A neural-network (NN) approach for neutrino interaction vertex reconstruction in the OPERA experiment with the help of the Target Tracker (TT) detector is described. A feed-forward NN with the standard back propagation option is used. The energy functional minimization of the network is performed by the method of conjugate gradients. Data preprocessing by means of cellular automaton algorithm is performed. The Hough transform is applied for muon track determination and the robust fitting method is used for shower axis reconstruction. A comparison of the proposed approach with earlier studies, based on the use of the neural network package SNNS, shows their similar performance. The further development of the approach is underway

Robust Portfolio Optimization using CAPM Approach

Directory of Open Access Journals (Sweden)

mohsen gharakhani

2013-08-01

Full Text Available In this paper, a new robust model of multi-period portfolio problem has been developed. One of the key concerns in any asset allocation problem is how to cope with uncertainty about future returns. There are some approaches in the literature for this purpose including stochastic programming and robust optimization. Applying these techniques to multi-period portfolio problem may increase the problem size in a way that the resulting model is intractable. In this paper, a novel approach has been proposed to formulate multi-period portfolio problem as an uncertain linear program assuming that asset return follows the single-index factor model. Robust optimization technique has been also used to solve the problem. In order to evaluate the performance of the proposed model, a numerical example has been applied using simulated data.

Parametric uncertainty modeling for robust control

DEFF Research Database (Denmark)

Rasmussen, K.H.; Jørgensen, Sten Bay

1999-01-01

The dynamic behaviour of a non-linear process can often be approximated with a time-varying linear model. In the presented methodology the dynamics is modeled non-conservatively as parametric uncertainty in linear lime invariant models. The obtained uncertainty description makes it possible...... to perform robustness analysis on a control system using the structured singular value. The idea behind the proposed method is to fit a rational function to the parameter variation. The parameter variation can then be expressed as a linear fractional transformation (LFT), It is discussed how the proposed...... point changes. It is shown that a diagonal PI control structure provides robust performance towards variations in feed flow rate or feed concentrations. However including both liquid and vapor flow delays robust performance specifications cannot be satisfied with this simple diagonal control structure...

Predator-prey interaction reveals local effects of high-altitude insect migration

Science.gov (United States)

High-altitude nocturnal insect migrations represent significant pulses of resources, yet are difficult to study and poorly understood. Predator-prey interactions, specifically migratory moth consumption by high-flying bats, potentially reveal flows of migratory insects across a landscape. In North...

Robust estimation of seismic coda shape

Science.gov (United States)

Nikkilä, Mikko; Polishchuk, Valentin; Krasnoshchekov, Dmitry

2014-04-01

We present a new method for estimation of seismic coda shape. It falls into the same class of methods as non-parametric shape reconstruction with the use of neural network techniques where data are split into a training and validation data sets. We particularly pursue the well-known problem of image reconstruction formulated in this case as shape isolation in the presence of a broadly defined noise. This combined approach is enabled by the intrinsic feature of seismogram which can be divided objectively into a pre-signal seismic noise with lack of the target shape, and the remainder that contains scattered waveforms compounding the coda shape. In short, we separately apply shape restoration procedure to pre-signal seismic noise and the event record, which provides successful delineation of the coda shape in the form of a smooth almost non-oscillating function of time. The new algorithm uses a recently developed generalization of classical computational-geometry tool of α-shape. The generalization essentially yields robust shape estimation by ignoring locally a number of points treated as extreme values, noise or non-relevant data. Our algorithm is conceptually simple and enables the desired or pre-determined level of shape detail, constrainable by an arbitrary data fit criteria. The proposed tool for coda shape delineation provides an alternative to moving averaging and/or other smoothing techniques frequently used for this purpose. The new algorithm is illustrated with an application to the problem of estimating the coda duration after a local event. The obtained relation coefficient between coda duration and epicentral distance is consistent with the earlier findings in the region of interest.

In Silico Design of Robust Bolalipid Membranes

NARCIS (Netherlands)

Bulacu, Monica; Periole, Xavier; Marrink, Siewert J.; Périole, Xavier

The robustness of microorganisms used in industrial fermentations is essential for the efficiency and yield of the production process. A viable tool to increase the robustness is through engineering of the cell membrane and especially by incorporating lipids from species that survive under harsh

Extending the Scope of Robust Quadratic Optimization

NARCIS (Netherlands)

Marandi, Ahmadreza; Ben-Tal, A.; den Hertog, Dick; Melenberg, Bertrand

In this paper, we derive tractable reformulations of the robust counterparts of convex quadratic and conic quadratic constraints with concave uncertainties for a broad range of uncertainty sets. For quadratic constraints with convex uncertainty, it is well-known that the robust counterpart is, in

Applying Robust Design in an Industrial Context

DEFF Research Database (Denmark)

Christensen, Martin Ebro

mechanical architectures. Furthermore a set of 15 robust design principles for reducing the variation in functional performance is compiled in a format directly supporting the work of the design engineer. With these foundational methods in place, the existing tools, methods and KPIs of Robust Design...

Efficient reanalysis techniques for robust topology optimization

DEFF Research Database (Denmark)

Amir, Oded; Sigmund, Ole; Lazarov, Boyan Stefanov

2012-01-01

efficient robust topology optimization procedures based on reanalysis techniques. The approach is demonstrated on two compliant mechanism design problems where robust design is achieved by employing either a worst case formulation or a stochastic formulation. It is shown that the time spent on finite...

ATMAD: robust image analysis for Automatic Tissue MicroArray De-arraying.

Science.gov (United States)

Nguyen, Hoai Nam; Paveau, Vincent; Cauchois, Cyril; Kervrann, Charles

2018-04-19

Over the last two decades, an innovative technology called Tissue Microarray (TMA), which combines multi-tissue and DNA microarray concepts, has been widely used in the field of histology. It consists of a collection of several (up to 1000 or more) tissue samples that are assembled onto a single support - typically a glass slide - according to a design grid (array) layout, in order to allow multiplex analysis by treating numerous samples under identical and standardized conditions. However, during the TMA manufacturing process, the sample positions can be highly distorted from the design grid due to the imprecision when assembling tissue samples and the deformation of the embedding waxes. Consequently, these distortions may lead to severe errors of (histological) assay results when the sample identities are mismatched between the design and its manufactured output. The development of a robust method for de-arraying TMA, which localizes and matches TMA samples with their design grid, is therefore crucial to overcome the bottleneck of this prominent technology. In this paper, we propose an Automatic, fast and robust TMA De-arraying (ATMAD) approach dedicated to images acquired with brightfield and fluorescence microscopes (or scanners). First, tissue samples are localized in the large image by applying a locally adaptive thresholding on the isotropic wavelet transform of the input TMA image. To reduce false detections, a parametric shape model is considered for segmenting ellipse-shaped objects at each detected position. Segmented objects that do not meet the size and the roundness criteria are discarded from the list of tissue samples before being matched with the design grid. Sample matching is performed by estimating the TMA grid deformation under the thin-plate model. Finally, thanks to the estimated deformation, the true tissue samples that were preliminary rejected in the early image processing step are recognized by running a second segmentation step. We

Robust Learning Control Design for Quantum Unitary Transformations.

Science.gov (United States)

Wu, Chengzhi; Qi, Bo; Chen, Chunlin; Dong, Daoyi

2017-12-01

Robust control design for quantum unitary transformations has been recognized as a fundamental and challenging task in the development of quantum information processing due to unavoidable decoherence or operational errors in the experimental implementation of quantum operations. In this paper, we extend the systematic methodology of sampling-based learning control (SLC) approach with a gradient flow algorithm for the design of robust quantum unitary transformations. The SLC approach first uses a "training" process to find an optimal control strategy robust against certain ranges of uncertainties. Then a number of randomly selected samples are tested and the performance is evaluated according to their average fidelity. The approach is applied to three typical examples of robust quantum transformation problems including robust quantum transformations in a three-level quantum system, in a superconducting quantum circuit, and in a spin chain system. Numerical results demonstrate the effectiveness of the SLC approach and show its potential applications in various implementation of quantum unitary transformations.

An Overview of the Adaptive Robust DFT

Directory of Open Access Journals (Sweden)

Djurović Igor

2010-01-01

Full Text Available Abstract This paper overviews basic principles and applications of the robust DFT (RDFT approach, which is used for robust processing of frequency-modulated (FM signals embedded in non-Gaussian heavy-tailed noise. In particular, we concentrate on the spectral analysis and filtering of signals corrupted by impulsive distortions using adaptive and nonadaptive robust estimators. Several adaptive estimators of location parameter are considered, and it is shown that their application is preferable with respect to non-adaptive counterparts. This fact is demonstrated by efficiency comparison of adaptive and nonadaptive RDFT methods for different noise environments.

RFMix: A Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference

Science.gov (United States)

Maples, Brian K.; Gravel, Simon; Kenny, Eimear E.; Bustamante, Carlos D.

2013-01-01

Local-ancestry inference is an important step in the genetic analysis of fully sequenced human genomes. Current methods can only detect continental-level ancestry (i.e., European versus African versus Asian) accurately even when using millions of markers. Here, we present RFMix, a powerful discriminative modeling approach that is faster (∼30×) and more accurate than existing methods. We accomplish this by using a conditional random field parameterized by random forests trained on reference panels. RFMix is capable of learning from the admixed samples themselves to boost performance and autocorrect phasing errors. RFMix shows high sensitivity and specificity in simulated Hispanics/Latinos and African Americans and admixed Europeans, Africans, and Asians. Finally, we demonstrate that African Americans in HapMap contain modest (but nonzero) levels of Native American ancestry (∼0.4%). PMID:23910464

Distributed Robust Optimization in Networked System.

Science.gov (United States)

Wang, Shengnan; Li, Chunguang

2016-10-11

In this paper, we consider a distributed robust optimization (DRO) problem, where multiple agents in a networked system cooperatively minimize a global convex objective function with respect to a global variable under the global constraints. The objective function can be represented by a sum of local objective functions. The global constraints contain some uncertain parameters which are partially known, and can be characterized by some inequality constraints. After problem transformation, we adopt the Lagrangian primal-dual method to solve this problem. We prove that the primal and dual optimal solutions of the problem are restricted in some specific sets, and we give a method to construct these sets. Then, we propose a DRO algorithm to find the primal-dual optimal solutions of the Lagrangian function, which consists of a subgradient step, a projection step, and a diffusion step, and in the projection step of the algorithm, the optimized variables are projected onto the specific sets to guarantee the boundedness of the subgradients. Convergence analysis and numerical simulations verifying the performance of the proposed algorithm are then provided. Further, for nonconvex DRO problem, the corresponding approach and algorithm framework are also provided.

Evolution favors protein mutational robustness in sufficiently large populations

Directory of Open Access Journals (Sweden)

Venturelli Ophelia S

2007-07-01

Full Text Available Abstract Background An important question is whether evolution favors properties such as mutational robustness or evolvability that do not directly benefit any individual, but can influence the course of future evolution. Functionally similar proteins can differ substantially in their robustness to mutations and capacity to evolve new functions, but it has remained unclear whether any of these differences might be due to evolutionary selection for these properties. Results Here we use laboratory experiments to demonstrate that evolution favors protein mutational robustness if the evolving population is sufficiently large. We neutrally evolve cytochrome P450 proteins under identical selection pressures and mutation rates in populations of different sizes, and show that proteins from the larger and thus more polymorphic population tend towards higher mutational robustness. Proteins from the larger population also evolve greater stability, a biophysical property that is known to enhance both mutational robustness and evolvability. The excess mutational robustness and stability is well described by mathematical theory, and can be quantitatively related to the way that the proteins occupy their neutral network. Conclusion Our work is the first experimental demonstration of the general tendency of evolution to favor mutational robustness and protein stability in highly polymorphic populations. We suggest that this phenomenon could contribute to the mutational robustness and evolvability of viruses and bacteria that exist in large populations.

Feedforward/feedback control synthesis for performance and robustness

Science.gov (United States)

Wie, Bong; Liu, Qiang

1990-01-01

Both feedforward and feedback control approaches for uncertain dynamical systems are investigated. The control design objective is to achieve a fast settling time (high performance) and robustness (insensitivity) to plant modeling uncertainty. Preshapong of an ideal, time-optimal control input using a 'tapped-delay' filter is shown to provide a rapid maneuver with robust performance. A robust, non-minimum-phase feedback controller is synthesized with particular emphasis on its proper implementation for a non-zero set-point control problem. The proposed feedforward/feedback control approach is robust for a certain class of uncertain dynamical systems, since the control input command computed for a given desired output does not depend on the plant parameters.

PARAMETER COORDINATION AND ROBUST OPTIMIZATION FOR MULTIDISCIPLINARY DESIGN