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The Extended Electromotive Force(EEMF) has a high potential because that the model enables position estimation by utilizing not only electromotive force but also saliency of inductance. In particular, the EEMF consists of two components, excited by rotor speed and high-frequency signal injection. The characteristic of EEMF excited by speed has been proposed sufficiently. This paper describes analysis of robustness of parameter error in two types of Extended Electromotive Force (EEMF) exited by high frequency signal injection for position sensorless control. Finally, formula evaluation indicates that each EEMF model has different robustness of parameter error.

Static branch parameter errors existing in power system model have seriously affected the accuracy of state estimation and the practical level of other applications. In order to identify the parameter errors, the paper proposed a method using PSO to optimize and identify error parameter of power network based on local state estimation. According to make state estimation in the local area which included the suspicious branch parameters, making the suspicious branch parameters as optimization variables, and the objective function is formed to make the Weighted-Sum Squared Residual minimum. Then use the particle swarm algorithm (PSO) to optimize the objective function so as to obtain the optimal parameters of the current conditions. The effectiveness of the proposed algorithm is verified by the IEEE-118 node model and the actual system.

It is inevitable that the mechanical part has error when machining. To increasing the machining precision and decreasing the shape and position error, error compensation is one way. The geometry error parameter is necessary when the error compensation model is founded and the compensation data is calculated. The common measuring and identifying methods are introduced in this article. Their mathematic models and solutions are listed and their merits and drawbacks are compared. This method has been applied in CNC error compensation and the effect is advisable.

During the construction control in order to better control the elevation, the need for sensitivity analysis of the design parameters, the sensitivity analysis of design parameter adjustment principle, so as to adjust the measured deflection and deflection calculation error of judgment, and for the cross section should be the main design parameters of stress sensitivity. This method can identify accurately fast parameter error during the bridge construction, and ensure the smooth and long construction Liang Qiao. To provide reference for construction control of this kind of bridge deflection.

The Lagrange multiplier-based method is an effective network parameter error identification method. However, two full matrices with high-dimensions are involved in the calculation procedure; these create huge computational burdens for large-scale power systems. To solve this problem, a fast solution is proposed in this paper, where special treatment techniques for full matrices are used to dramatically improve the calculation efficiency. A practical parameter error identification program has been developed and used in many electric power control centers. In this paper, the results for test systems and on-site applications are given, which show that the proposed approach is very efficient.

This study investigates organic consumers’ preferences for local production of apples. The analysis is based on a choice experiment among 637 Danish consumers used in combination with a principal component analysis of a set of opinion questions. The principal component analysis identifies two components of questions. Component 1 concerns benefits related to organic products while component 2 relates to positive features of locally produced products. When the components are included in analysis of data from the choice experiment a random parameter error component model suggests that respondents who recognize the benefits of organic products have relatively high preferences for both organically and locally produced apples. Respondents who, on the other hand, recognize the benefits of locally produced products have high preferences for domestically and locally produced apples but not for organic apples.

In this letter, a fast network parameter error correction scheme is proposed based on recent findings on parameter error identification. Compared to the widely applied augmented state estimation approach, it is computationally very efficient and numerically stable, and requires very modest coding effort. Simulation results in the New England power system show that it produces reliable results in the presence of both strongly correlated errors and Gaussian measurement noise.

This paper investigates the problem of network parameter error detection and identification in power systems. Recently, a parameter error identification method which is based on Lagrange multipliers corresponding to a single measurement scan has been developed. This paper provides an improvement of this method via the use of multiple measurement scans which increases the local redundancy at no additional cost. This leads to identification of errors which could otherwise not be identified. The paper presents a detailed analysis of the limitations of the single scan method and also shows the relationship between the number of scans, the normalized Lagrange multipliers and the normalized residuals. The presented method is easy to implement since estimation of different scans can be executed independent of each other by using an existing state estimation program. Simulations on IEEE 14-, 30-, and 118-bus systems are provided to illustrate the proposed approach of parameter error identification.

In order to improve the prediction accuracy of stock index, eliminate of the blindness of parameters selection for support vector machine, a stock index prediction method combined the genetic simulated annealing algorithm (GASA) which integrated the parallel search of genetic algorithm with the probabilistic sudden jumping characteristics of simulated annealing algorithm, with support vector machine (SVM) is proposed. Using daily data of Shanghai stock index opening quotation which is normalization processed, the stock index prediction model based on GASA-SVM is established. Optimal parameter error penalty parameter c=1 and Gaussian kernel parameter g=1.625 are obtained. Compared the result with GA-SVM prediction model, the comparative analysis shows that GASA-SVM(MSE= 0.000191111) model prediction capabilities are superior to GA-SVM(MSE=0.000018825) prediction model. It can provide valuable references for the investors.

Recently, sensorless controls, which eliminate position and speed sensor in a permanent magnet synchronous motor drive, have been much studied. Most sensorless control algorithms are based on the back-EMF and speed estimations which are obtained from the voltage equations. Therefore, the sensorless control performance is largely affected by the parameter errors of a motor. This paper investigates a novel adaptive control with the parameter error compensation for the speed sensorless control of a permanent magnet synchronous motor. The proposed parameter estimation is obtained from the d-axis current error between the real and estimated currents. The proposed algorithm is verified through the simulation and experimentation.

Previous work on parameter error identification based on normalized Lagrange multipliers has shown that the errors in parameters of branches constituting single- or double-edge cutsets could not be detected or identified without incorporating phasor measurements. In order to address this deficiency, a computationally efficient algorithm has been developed to identify all such cutsets and documented in a recent paper. This paper builds on that work and formulates a strategic phasor measurement placement problem whose objective is to ensure detectability and identifiability of all network parameters in a given system. A practical solution is developed for this problem and simulation results for IEEE 14-, 30- and 57-bus test systems are provided to illustrate its implementation.

In this paper, the role of constant optimal forcing (COF) in correcting forecast models was numerically studied using the well-known Lorenz 63 model. The results show that when we only consider model error caused by parameter error, which also changes with the development of state variables in a numerical model, the impact of such model error on forecast uncertainties can be offset by superimposing COF on the tendency equations in the numerical model. The COF can also offset the impact of model error caused by stochastic processes. In reality, the forecast results of numerical models are simultaneously influenced by parameter uncertainty and stochastic process as well as their interactions. Our results indicate that COF is also able to significantly offset the impact of such hybrid model error on forecast results. In summary, although the variation in the model error due to physical process is time-dependent, the superimposition of COF on the numerical model is an effective approach to reducing the influence of model error on forecast results. Therefore, the COF method may be an effective approach to correcting numerical models and thus improving the forecast capability of models.

A novel adaptive identification framework is proposed for sinusoidal signals to estimate all unknown parameters (i.e. offset, amplitude, frequency and phase). The proposed identification is independent of any observer/predictor design and thus can be implemented in a simplified manner. The adaptive laws are driven by appropriate parameter error information derived by applying filter operations on the output measurements. Globally exponential convergence of the parameter estimation is proved. The proposed idea is further extended for multi-sinusoid signals and verified in terms of simulations.

The paper discusses the optimization technology and algorithm features in the hydraulic system simulation. It presents the realization in the package. Detailed description of the principle and development is shown, focused on parameter optimization by parameter error integration and genetic algorithm which are realized in the optimization module. The application is an example of hydraulic system of injection molding machine which showed the efficiency and capacity of the module. The comparison between curves of simulation and experiment indicated the achievements, to find optimized hydraulic parameters efficiently and quickly so as to shorten the design cycle.

It was previously shown that normalized Lagrange multipliers in state estimation could be effectively used for network parameter error detection and identification. However, it was also observed that there could exist a number of “insensitive” normalized Lagrange multipliers corresponding to certain parameters which might lead to detection failure. This paper derives the relationship between Lagrange multipliers and parameter errors and explains the reasons behind detection failures. Furthermore, it facilitates the identification of insensitive normalized Lagrange multipliers. These results are then used to clarify the significance of incorporating multiple measurement scans as a way of avoiding detection failure and to derive a new approach for estimating the necessary number of scans to guarantee parameter error detection. Simulation results using the IEEE 14-bus system are presented to verify the proposed solution.

The Normalized Lagrange Multiplier (NLM) method was shown to be useful in network parameter error detection, but suffered from occasional failure in certain cases. This paper exploits the advantages of PMUs and proposes a solution to the detection failure issue. The relationship between NLMs and parameter errors is first derived then used to identify insensitive NLMs which account for the issue of missing parameter error. Subsequently, a PMU placement strategy is proposed to improve the performance of the NLM method. Simulation results in the IEEE 14-bus test system show that the increased redundancy and accuracy gained by the incorporation of PMUs significantly facilitate the detection of parameter errors which was not possible by using only SCADA measurements.

In order to improve the accuracy performance of a six degree-of-freedom (DOF) redundantly actuated parallel mechanism (RAPM), a self-calibration method based on sensor redundancy is presented. The kinematic model of the RAPM is built and its 44 identifiable parameters are determined by QR decomposition of the identification matrix. Consequently, the self-calibration algorithm is formulated and the least-squares method is used to correct kinematic parameters. A guideline for selection of measurement configurations is presented. Numerical simulations are performed to confirm the validity of the proposed calibration algorithm. Simulation results show that the average parameter error of 2.23 mm is reduced to 0.12 mm, and the position and orientation accuracy of the platform can reach 0.05 mm and 0.16 mrad after calibration.

Adaptive control has recently been extended to bilateral teleoperators to synchronize the local and remote positions and velocities. However, precise parameter estimation has not been achieved via conventional adaptations. In this paper, we propose an modified adaptive control method for teleoperation systems by introducing a new adaptive law, which uses the parameter error as new leakage terms. Consequently, we prove that the position and velocity synchronization and the parameter estimation can be achieved simultaneously. It is found that the parameter estimation convergence can help to improve the motion synchronization. Simulation results validate the feasibility and efficacy of the proposed method.

Conditions for boundedness and convergence of the output error and the parameter error for various Caputo's fractional order adaptive schemes based on the steepest descent method are derived in this paper. To this aim, the concept of sufficiently exciting signals is introduced, characterized and related to the concept of persistently exciting signals used in the integer order case. An application is designed in adaptive indirect control of integer order systems using fractional equations to adjust parameters. This application is illustrated for a pole placement adaptive problem. Advantages of using fractional adjustment in control adaptive schemes are experimentally obtained.

Rigid registration is an important step in 3D scanning and modeling of manufactured objects that are generally composed of a combination of basic geometric primitives such as planes, spheres, cylinders, etc. In this paper, an efficient and robust method is proposed to align two basic geometric primitives. The transformation between two primitives is found by minimizing the parameter error between primitive correspondences. The approach applies an interior-point method and a new objective function to achieve good results. Compared to previous primitive-based alignment approach proposed by Rabbani et al. (Rabbani et al., 2007), the presented approach achieves better results in terms of convergence and accuracy. Finally, the proposed method is used in various applications such as data completion and primitive-based registration for quality control and inspection.

Machine spiral bevel gear tooth surface will be associated with the machine error in the event of a failure, the mathematical model with the use of the new method of calculation error based on better understanding of spiral bevel gears, the error theory and the law of error flank tooth surfaces calculated. And the Machine Tool and Tool error parameter adjustment errors can be introduced into the study of the influence of different error understand the correlation between the sizes of the error value to provide guidance and basis for the production and processing.

The analysis of amplified stress interaction in cortical bone is relatively new since most previous research have neglected the error parameter of fracture without realizing the accuracy of prediction has been violated, numerically. Indeed, the related analytical and empirical formulation for stress interaction analysis for example Kachanov theory is relatively accurate for very specific case. Thus, an approach that would produce less error for better prediction is paramount. The crack interaction parameter using the stress singularity element is one of alternative approach. This simulation is based on the changes of stress amplification in different crack intervals. Stress amplification in a solid, with the existence of crack is the amount of load that exhibits onto the solid perpendicularly. This research aims is to simulate stress amplification induced by crack interaction in cortical bone. Hence, the average error of the numerical method has been discussed and validated.

Image restoration plays an important role in transportation applications. This paper studies a motion blurred image processing method, which has good recovery effect. In this method, first the wiener filter is used for image restoration. Then, based on the error parameter analysis, the parameters of point spread function are estimated, and the noise parameter is estimated by using the probability and statistics method. Furthermore, the ringing effect is processed by using the smooth boundary method. Finally, experimental results show that the proposed method can restore the motion blurred images effectively and has strong robustness for the noise.

BACKGROUND: When using a target-controlled infusion of propofol to produce sedation, the operator assumes that the individual patient's pharmacokinetic parameters match those in the control system so that the specified effect-site target is achieved, and that the specified target is appropriate for the individual patient's sensitivity. These inaccuracies cascade, and this produces error in the desired level of sedation, termed "target error." To address this issue, we designed a control system that incorporates the operator's observation of loss of responsiveness to determine patient sensitivity. Our hypothesis was that this control system would reduce the impact of pharmacokinetic parameter error and uncertainty in sensitivity on the system's target error. METHODS: A novel control system was implemented that produces a slow transition in the probability of loss of responsiveness, providing the operator with greater resolution to observe the time of this transition. The system uses the time of this transition to infer the effect-site concentration associated with loss of responsiveness, and the infusion sequence necessary to maintain this concentration. We used computer simulation to generate a population of 10,000 patients with randomly distributed pharmacokinetic parameters and sensitivity to propofol, and compared the target error of our system with that of a target-controlled infusion system targeting the effect-site concentration associated with 50% probability of loss of responsiveness. RESULTS: Our system exhibited a target error of -0.75% ± 8.96%, compared with 0% ± 27.6% for target-controlled infusion, reducing the variability in achieving the specified target by a factor of 3.1 compared with target-controlled infusion, which was significant at P < 0.0001. CONCLUSIONS: Our system reduces the impact of biological variability by including the operator in the control loop. The utility of this approach in clinical practice will require further evaluation.

Property testing is concerned with constant-time algorithms for deciding whether a given object satisfies a predetermined property or is far from satisfying it. In this paper, we consider testing properties related to the connectivity of two vertices in sparse graphs. We present one-sided error testers for (s,t)-disconnectivity with query complexity 2^O^(^1^/^@e^) for digraphs and O(1/@e^2) for graphs, where @e is an error parameter. Furthermore, we show that these algorithms are the best possible in view of query complexity, i.e., we give matching lower bounds for two-sided error testers for both cases. We also give a constant-time algorithm for testing the (s,t)-disconnectivity of a directed bounded-degree hypergraph, which can be used to test the satisfiability of Horn SAT.

In the field of tourism forecasting, the application of time-varying parameters has been successful in forecasting arrivals taking into account the changing behaviour of tourists. This article uses quarterly data to forecast intercontinental tourism demand for a long-haul, developing destination (South Africa) by applying time-varying parameters (TVP) to single equation estimates, and comparing these with vector autoregressive results. Ex-ante forecasts are done for tourist arrivals from various continents, and forecasting accuracy is evaluated by determining the Mean Absolute Percentage Error (MAPE), the Mean Absolute Deviation/Mean ratio (MAD/mean), the percentage Root Mean Square Error (RMSE) and Theil's inequality coefficient. The results show that TVP do not always outperform other forecasting techniques.

Within the framework of the Zebiak–Cane model, the approach of conditional nonlinear optimal perturbation (CNOP) is used to study the effect of model parameter errors on El Niño–Southern Oscillation (ENSO) predictability. The optimal model parameter errors are obtained within a reasonable error bound (i.e., CNOP-P errors), which have the largest effect on the results of El Niño predictions. The resultant prediction errors were investigated in depth. The CNOP-P errors do not cause a noticeable prediction error of the sea surface temperature anomaly averaged over the Niño-3 region and do not show an obvious season-dependent evolution of the prediction errors. Consequently, the CNOP-P errors do not cause a significant spring predictability barrier (SPB) for El Niño events. In contrast, the initial errors that have the largest effect on the results of the predictions (i.e., the CNOP-I errors) show a season-dependent evolution, with the largest error increase in spring, and also cause a large prediction error, thereby generating a significant SPB. The initial errors play a more important role than the parameter errors in generating a significant SPB for El Niño events. To further validate this result, the authors investigated the situation in which CNOP-I and CNOP-P errors are simultaneously superimposed in the model, which may be a more credible approach because the initial errors and model parameter errors coexist under realistic predictions. The combined mode of CNOP-I and CNOP-P errors shows a similar season-dependent evolution to that of CNOP-I errors and yields a large prediction error, thereby inducing a significant SPB. The inference, therefore, is that initial errors play a more important role than model parameter errors in generating a significant SPB for El Niño predictions of the Zebiak–Cane model. This result helps to clarify the roles of the initial error and parameter error in the development of an SPB, and highlights the role of initial errors, which demonstrates that the SPB could be markedly reduced by improving the initial conditions. The results provide a theoretical basis for improving data assimilation in ENSO predictions.

Given a text T=T[1 ₀ n] and a circular pattern P=P[1 ₀ m], the circular pattern matching (CPM) problem is to find all occurrences of P in T. We present the first algorithm that exploits suffix links to solve the exact CPM (ECPM) problem in O(n log |Σ|) time and O(n) space, where Σ is the symbol alphabet. Then, we present a q-gram-based algorithm for the approximate CPM (ACPM) problem using the idea of bidirectional edit distance. Our algorithm finds all k-approximate occurrences of P in T. We then extend each algorithm to solve the all-against-all variant of the CPM problem for both exact and k-approximate matches. Although the CPM problem has been studied since the 1980s, this is the first attempt on the all-against-all variant, without using a trivial application of standard CPM algorithms. Given a database S=S1$1S2$2 ₀ SZ$Z of Z sequences, our algorithms solve the all-against-all ACPM problem in O(kmaN) time on average and O(kmmN2) worst case, where k is the error parameter, N=∑i=1Z(|Si|+1), ma=N/Z and mm=maxi=1,2,₀ Z{|Si|}. Space complexity is O(N). These can be compared with the O(N2malog ma) average and O(N3log mm) worst case time required by the best available ACPM algorithm.

This article analyses the dynamic evolution of capital mobility in eight Organization for Economic Co-operation and Development (OECD) countries over the period 1850 to 1992. We estimate an error-correction model of saving and investment that allows to distinguish between short- and long-run capital mobility. The parameters of the error-correction model are allowed to be time-vary ing and are estimated using the Kalman filter and maximum likelihood technique. We find that both short- and long-run capital mobility was very high at the end of the nineteenth century but since then decreased in most countries. However, the magnitude of changes in long-run capital mobility is very small while the absolute change of short-run capital mobility is substantial.

Some analytical results concerning PI controller tuning based on integrator plus time delay models are worked out and presented. A method for obtaining PI controller parameters, Kp=alpha/(k*tau), and, Ti=beta*tau, which ensures a given prescribed maximum time delay error, dtau_max, to time delay, tau, ratio parameter delta=dau_max/tau, is presented. The corner stone in this method, is a method product parameter, c=alpha*beta. Analytical relations between the PI controller parameters, Ti, and, Kp, and the time delay error parameter, delta, is presented, and we propose the setting, beta=c/a*(delta+1), and, alpha=a/(delta+1), which gives, Ti=c/a*(delta+1)*tau, and Kp=a/((delta+1)*k*tau), where the parameter, a, is constant in the method product parameter, c=alpha*beta. It also turns out that the integral time, Ti, is linear in, delta, and the proportional gain, Kp, inversely proportional to, delta+1. For the original Ziegler Nichols (ZN) method this parameter is approximately, c=2.38, and the presented method may e.g., be used to obtain new modified ZN parameters with increased robustness margins, also documented in the paper.

As a tool of complex shape, the manufacturing error of hobs can be classed into three kinds: the datum level error, the tooth thickness error and the parameter error of helicoidal surface. The parameter error of helicoidal surface, which is composed of tooth error and helix error, is the most importance among them. For precision of hob and convenience of measurement, several individual errors are instead of the helix error. How to set reasonable individual errors to guarantee the helix error within tolerance, the relationship between them in gear hob measurements is analyzed, and the approach to decompose the helix error into individual error has been discussed in the paper. On the basis of above theory, a high precision mode can be easily established using the soft ware.

For the high-resolution airborne synthetic aperture radar (SAR) stereo geolocation application, the final geolocation accuracy is influenced by various error parameter sources. In this paper, an airborne SAR stereo geolocation parameter error model, involving the parameter errors derived from the navigation system on the flight platform, has been put forward. Moreover, a kind of near-direct method for modeling and sensitivity analysis of navigation parameter errors is also given. This method directly uses the ground reference to calculate the covariance matrix relationship between the parameter errors and the eventual geolocation errors for ground target points. In addition, utilizing true flight track parameters’ errors, this paper gave a verification of the method and a corresponding sensitivity analysis for airborne SAR stereo geolocation model and proved its efficiency.

Using PET, brain areas representing the use of a well‐learned tool (chopsticks) were investigated in 10 normal common users. The experimental task was to hold the tool in their right hand and use it to pick up and transport a small pin from a table. Data for the same task performed using only the fingers were also obtained as a control. The results showed an extensive overlap in activated areas with and without the use of the tool. The tool‐use prehension, compared to the finger prehension, was associated with higher activities in the caudal‐ventral premotor, dorsal premotor, superior parietal, posterior intraparietal, middle temporal gyrus, and primary sensory, occipital cortices, and the cerebellum. These are thus considered to be the human cortical and subcortical substrates representing the use of the tool studied. The activity of the posterior intraparietal area was negatively correlated with the number of drops of the pin, whereas occipital activity was positively correlated with the same error parameter. The caudal‐ventral premotor and posterior intraparietal areas are together known to be involved in tool use‐related modulation in peripersonal space. The correlation results suggest that this modulation depends on the level of performance. The coactivated left middle temporal gyrus further suggests that familiarity with a tool as well as the knowledge about its usage plays a role in peripersonal space modulation. Superior parietal activation, along with occipital activation, indicates the involvement of visual‐spatial attention in the tool use, possibly reflecting the effect of interaction between the prehension (task) and the tool. Hum Brain Mapp 2009. © 2009 Wiley‐Liss, Inc.

We present the regression models for determining the total excess air ratio αΣ and gas temperature Tg* upstream of the high-pressure turbine formed on the basis of the engine parameter values that are regularly measured. The sensitivity of the regression models presented to the sensor and instrumentation precision is studied. The errors of measuring and calculating αΣ and Tg* in different altitude-speed engine operation conditions are shown.

This paper proposes a position sensorless drive system combined with on-line parameter identification for an interior permanent magnet synchronous motor. The accuracy of the position estimation can be improved by the proposed system, in which the motor parameters used for the position estimation are identified according to the operating conditions. First, the influence of the parameter error on the estimation position error is examined from the simulation and experimental results. Next, the characteristics of the sensorless drive system and the performance of parameter identification are shown. The experimental results show that the proposed system can achieve more accurate position estimation than the drive system without the parameter identification for all operating conditions.

Methods for power network parameter estimation and correction are discussed in this paper. A sequential-type method for real-time processing of network parameters is proposed. The method exploits the information contained in the measurement residuals to estimate a better network parameter; it uses a linearized sensitivity model to relate the measurement residuals to the parameter error. The proposed method has been coded in FORTRAN using several short-cuts and has been thoroughly tested in the estimation of transformer ratios in the Belgian HV system.

Currently, no optimal curriculum exists for the Fundamentals of Laparoscopic Surgery (FLS) manual skills training program. The objective was to create a proficiency-based training curriculum that would allow both successful completion of the FLS manual skills exam and improved performance in the operating room. Two experienced laparoscopic surgeons performed 5 consecutive repetitions of all 5 FLS tasks. The mean performance times for both subjects were determined. Error parameters for each task were also recorded and used to establish a maximum allowable error parameter for each task. These data were used to create both error- and time-based proficiency levels for each task based on the importance of the task and the amount of resources consumed when practicing the task. This type of objective proficiency level was determined for each of the 5 FLS tasks. We have developed a proficiency-based training curriculum for the psychomotor skills portion of FLS. Work is under way to evaluate and validate this curricular design.

A sensorless driving method of brushless DC motors (BLDCM) using neural networks has been studied in this paper. Considering the nonlinear characteristics and the parameter error of the modeling, neural networks are introduced to estimate the electromotive force (EMF). The results of simulation and experiment using offline trained neural networks show that the proposed method is useful. In addition, the robustness about the parameters is discussed. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 162(4): 64–71, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20240

This paper deals with an influence of parameter error to be included in a coordinate transformation which transforms a nonholonomic driftless system into a canonical form called “Chained Form”. The considered driftless systems are classified according to this influence, and investigated the possibility whether the system is able to regulate by already proposed control method. Finally adaptive control method within the framework of Time State Control Form for one of the classified system with an unknown system parameter which is difficult to regulate is proposed.

The paper proposes a robust three-view matching method to produce quasi-dense 3D points in multi-view stereo. In order to overcome the limitations of traditional wide baseline match propagation methods, the proposed method simultaneously models illumination variations and perspective distortions in images, and performs an effective affine parameter error detection and rectification mechanism in the process of match propagation. Experiments show the proposed method can effectively enhance the stability and robustness of match propagation, and achieve better performance in both accuracy and quantity of the quasi-dense 3D points.

In this paper it is proposed an approach to detect, identify and correct series and shunt branch parameter errors of a transmission line using a geometrical view. Firstly it is tested if any of the measurement equations have a gross error using the J(x) index, but with the measurement error as the objective function. Next, to conclude for transmission line i-j parameter error, the corresponding measurements associated to that line should have the Composed Normalized Error CNE i-j superior to the chosen threshold value. Also, the error will spread to the measurements of the neighborhood. The correction in the parameter is made using the corresponding measurement CNE. The proposed approach uses only one measurement snapshot. Using the geometrical view, two kinds of topological errors are analyzed: (i) very large parameter errors; (ii) short circuit of a line. To test the procedure efficiency the IEEE 39-bus network will be used.

Teste de propriedades em grafos consiste no estudo de algoritmos aleatórios sublineares que determinam se um grafo $G$ de entrada com $n$ vértices satisfaz uma dada propriedade ou se é necessário adicionar ou remover mais do que $\\epsilon{n \\choose 2}$ arestas para fazer $G$ satisfazê-la, para algum parâmetro $\\epsilon$ de erro fixo. Uma propriedade de grafos $P$ é dita testável se, para todo $\\epsilon > 0$, existe um tal algoritmo para $P$ cujo tempo de execução é independente de $n$. Um dos resultados de maior importância nesta área, provado por Alon e Shapira, afirma que toda propriedade hereditária de grafos é testável. Neste trabalho, apresentamos resultados análogos para torneios --- grafos completos nos quais são dadas orientações para cada aresta. Graph property testing is the study of randomized sublinear algorithms which decide if an input graph $G$ with $n$ vertices satisfies a given property or if it is necessary to add or remove more than $\\epsilon{n \\choose 2}$ edges to make $G$ satisfy it, for some fixed error parameter $\\epsilon$ . A graph property $P$ is called testable if, for every $\\epsilon > 0$, there is such an algorithm for $P$ whose run time is independent of $n$. One of the most important results in this area is due to Alon and Shapira, who showed that every hereditary graph property is testable. In this work, we show analogous results for tournaments --- complete graphs in which every edge is given an orientation.