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In d - Scattered Set we are given an (edge-weighted) graph and are asked to select at least k vertices, so that the distance between any pair is at least d , thus generalizing Independent Set . We provide upper and lower bounds on the complexity of this problem with respect to various standard graph parameters. In particular, we show the following: • For any d ≥ 2 , an O ∗ ( d tw ) -time algorithm, where tw is the treewidth of the input graph and a tight SETH-based lower bound matching this algorithm’s performance. These generalize known results for Independent Set . • d - Scattered Set is W[1]-hard parameterized by vertex cover (for edge-weighted graphs), or feedback vertex set (for unweighted graphs), even if k is an additional parameter. • A single-exponential algorithm parameterized by vertex cover for unweighted graphs, complementing the above-mentioned hardness. • A 2 O ( td 2 ) -time algorithm parameterized by tree-depth ( td ), as well as a matching ETH-based lower bound, both for unweighted graphs. We complement these mostly negative results by providing an FPT approximation scheme parameterized by treewidth. In particular, we give an algorithm which, for any error parameter ϵ > 0 , runs in time O ∗ ( ( tw ∕ ϵ ) O ( tw ) ) and returns a d ∕ ( 1 + ϵ ) -scattered set of size k , if a d -scattered set of the same size exists.

The critical power (CP) and maximal lactate steady state (MLSS) are operational surrogates of the maximal metabolic steady state (MMSS). However, their concordance and their agreement with MMSS remains variable likely due to methodological factors. PURPOSE To compare the concordance between CP and MLSS estimated by various models and criteria and their agreement with MMSS. METHODS After a ramp-test, ten recreationally active males performed four-to-five severe-intensity constant-power output (PO) trials to estimate CP, and three-to-four constant-PO trials to determine MLSS and identify MMSS. CP was computed using the 3-parameter hyperbolic (CP3-hyp), 2-parameter hyperbolic (CP2-hyp), linear (CPlin), and inverse of time (CP1/Tlim) models. In addition, the model with lowest combined parameter error identified the "best-fit" CP (CPbest-fit). MLSS was determined as an increase in blood lactate concentration ≤ 1 mM during constant-PO cycling from the 5th (MLSS10-30), 10th (MLSS10-30), 15th (MLSS15-30), 20th (MLSS20-30), or 25th (MLSS25-30) to 30th minute. MMSS was identified as the greatest PO associated with the highest submaximal steady state V[Combining Dot Above]O2 (MV[Combining Dot Above]O2ss). RESULTS Concordance between the various CP and MLSS estimates was greatest when MLSS was identified as MLSS15-30, MLSS20-30, and MLSS25-30. The PO at MV[Combining Dot Above]O2ss was 243 ± 43 W. Of the various CP models and MLSS criteria, CP2-hyp (244 ± 46 W) and CPlin (248 ± 46 W) and MLSS15-30 and MLSS20-30 (both 245 ± 46 W), respectively displayed, on average, the greatest agreement with MV[Combining Dot Above]O2ss. Nevertheless, all CP models and MLSS criteria demonstrated some degree of inaccuracies with respect to MV[Combining Dot Above]O2ss. CONCLUSIONS Differences between CP and MLSS can be reconciled with optimal methods of determination. When estimating MMSS, from CP the error margin of the model-estimate should be considered. For MLSS, MLSS15-30 and MLSS20-30 demonstrated the highest degree of accuracy.

The aim of the study is research of the influence of the sampling interval on the precision of the parameter estimations of a dual-mass DC electromechanical system (DMDCEMS) via Symlet wavelet. Four options are discussed in which the same wavelet function and time of observation are used and only the sampling period is different. The system parameters are evaluated. The relative output error and the summary relative parameter error are also obtained. The results are compared and analyzed.

Our main contribution is a general framework to design efficient polynomial time approximation schemes (EPTAS) for fundamental classes of stochastic combinatorial optimization problems. Given an error parameter $\epsilon>0$, such algorithmic schemes attain a $(1+\epsilon)$-approximation in only $t(\epsilon)\cdot poly(n)$ time, where $t(\cdot)$ is some function that depends only on $\epsilon$. Technically speaking, our approach relies on presenting tailor-made reductions to a newly-introduced multi-dimensional extension of the Santa Claus problem [Bansal-Sviridenko, STOC'06]. Even though the single-dimensional problem is already known to be APX-Hard, we prove that an EPTAS can be designed under certain structural assumptions, which hold for our applications. To demonstrate the versatility of our framework, we obtain an EPTAS for the adaptive ProbeMax problem as well as for its non-adaptive counterpart; in both cases, state-of-the-art approximability results have been inefficient polynomial time approximation schemes (PTAS) [Chen et al., NIPS'16; Fu et al., ICALP'18]. Turning our attention to selection-stopping settings, we further derive an EPTAS for the Free-Order Prophets problem [Agrawal et al., EC'20] and for its cost-driven generalization, Pandora's Box with Commitment [Fu et al., ICALP'18]. These results improve on known PTASes for their adaptive variants, and constitute the first non-trivial approximations in the non-adaptive setting., Comment: 33 pages

For GSTAR models, the least squares estimation method is commonly used since errors are assumed be uncorrelated. However, this method is not appropriate when errors are correlated, either in time or spatially. For these cases, the generalized least squares (GLS) method can be applied. GLS is more powerful since it has an error parameter that can act as a controller of the model to produce an efficient estimator. In this study, R Software was used to estimate GSTAR parameters. The resulted model was applied to real data, i.e. the monthly tea production of five plantations in West Java, Indonesia. The best model for forecasting was the GSTAR(1;1) model with temporally correlated error assumption.

To realize the error parameter estimation of strap-down inertial navigation system (SINS) and improve the navigation accuracy for aircraft, a hybrid improved restricted Boltzmann machine BP neural network (IRBM-BPNN) approach, which combines restricted Boltzmann machine (RBM) and BP neural network (BPNN), is proposed to forecast the inertial measurement unit (IMU) instrument errors and initial alignment errors of SINS. Firstly, the error generation mechanism of SINS is analyzed, and initial alignment error model and IMU instrument error model are established. Secondly, an unsupervised RBM method is introduced to initialize BPNN to improve the forecast performance of the neural network. The RBM-BPNN model is constructed through the information fusion of SINS/GPS/CNS integrated navigation system by using the sum of position deviation, the sum of velocity deviation and the sum of attitude deviation as the inputs and by using the error parameters of SINS as the outputs. The RBM-BPNN structure is improved to enhance its forecast accuracy, and the pulse signal is increased as the input of the neural network. Finally, we conduct simulation experiments to forecast and compensate the error parameters of the proposed IRBM-BPNN method. Simulation results show that the artificial neural network method is feasible and effective in forecasting SINS error parameters, and the forecast accuracy of SINS error parameters can be effectively improved by combining RBM and BPNN methods and improving the neural network structure. The proposed IRBM-BPNN method has the optimal forecast accuracy of SINS error parameters and navigation accuracy of aircraft compared with the radial basis function neural network method and BPNN method.

Synthetic aperture radar (SAR) has a good ability to detect the microwave scattering characteristics of the target and has a good capability of slant range Doppler positioning. Using multi-view SAR images in combination with image matching and positioning equations, the 3D position of the target can be obtained. In the past, multi-view 3D reconstruction mainly used side-looking images with parallel trajectories but different incident angles. That method is not universal for different configurations and lacks analysis of the relationship between solution and parameter error. This study aims at the problem of multi-view SAR 3D reconstruction. The authors establish general 3D reconstruction equations that can be used for non-parallel track and non-side-looking and the solution method is deduced. Based on this, an analysis method of error sensitivity is proposed and the dependence relationship between the reconstruction error and configuration, velocity, position, and slant range is analysed. The correctness of this method is verified by simulation experiments, which provides guidance for selection of configuration and sensor accuracy when applying 3D reconstruction.

For critical engine parts, such as crankshafts, fatigue strength is one of the most important parameters in the design and manufacturing stage. In previous work, fatigue limit loads of the crankshafts with different structural features were predicted based on different theories of critical distance (TCDs). The results showed that the definition of the TCD had an obvious impact on the accuracy of such predictions. This paper, first the critical distance was determined based on the limit stress distribution of a given crankshaft and the definition of the approach. Then, the fatigue limit load of another crankshaft was predicted based on the parameters obtained in the previous step. Finally, corresponding experimental verification and model parameter error influence analysis were conducted to evaluate the accuracies of the predictions. The results showed that for the modified indirect-defined TCD (ITCD), the predictions based on the line and point methods were approximately equal, and the parameter errors had an obvious impact on the predictions. However, for the direct-defined TCD (DTCD), the critical line approach had much better accuracy than the critical point approach, and the DTCD was much less sensitive to the model parameter errors than the ITCD approach, therefore, the DTCD approach is much more suitable for actual engineering applications.

A Crimp Force Monitor (CFM) is equipment for detecting crimp errors by analyzing crimp signals obtained from force and strain sensors. The analysis is commonly performed by aligning a measured crimp signal with a reference signal and comparing their difference. Current analysis methods often suffer from wrong alignments that result in false negative detections. This paper presents a new crimp signal analysis method in CFM. First, a falling edge alignment is proposed that matches falling edges of the measured and the reference signals by minimizing the absolute difference summation. Second, a signal parameter error is introduced to evaluate the crimp quality difference between the measured signal and the reference. For calculating the signal parameter error, part of a signal is identified and divided into several regions to maximize the signal parameter errors. Experiments showed that the proposed method can improve the signal alignment and accurately detect bad crimps especially with the strain sensor.

In the field of high-risk observation, the nodes in Wireless Sensor Network (WSN) are distributed randomly. The result from sensing becomes meaningless if it is not known from where the originating node is. Therefore, a sensor node positioning scheme, known as the localization scheme, is required. The localization scheme consists of distance estimation and position computing. Thus, this resear ch used connectivity as distance estimation within range free algorithm DV-Hop and Amorphous, and then trilateral algorithm for computing the position. Besides that, distance estimation using the connectivity between nodes is not needed for the additional hardware ranging as required by a range-based localization scheme. In this research compared the localization algorithm based on range free localization, which are DV-Hop algorithm and Amorphous algorithm. The simulation result shows that the amorphous alg orithm have achieved 13.60% and 24.538% lower than dv-hop algorithm for each parameter error localization and energy consumption. On node density variations, dv-hop algorithm gained a localization error that is 26.95% lower than amorphous algorithm, but for energy consumption parameter, amorphous gained 14.227% lower than dv-hop algorithm. In the communication range variation scenario, dv-hop algorithm gained a localization error that is50.282% lower than amorphous. However, for energy consumption parameter, amorphous algorithm gained 12.35%. lower than dv-hop algorithm.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

We consider the related notions of two-prover and of relativistic commitment schemes. In recent work, Lunghi et al. proposed a new relativistic commitment scheme with a multi-round sustain phase that enables to keep the binding property alive as long as the sustain phase is running. They prove security of their scheme against classical attacks; however, the proven bound on the error parameter is very weak: it blows up doubly exponentially in the number of rounds. In this work, we give a new analysis of the multi-round scheme of Lunghi et al., and we show a linear growth of the error parameter instead (also considering classical attacks only). Our analysis is based on a new and rather general composition theorem for two-prover commitment schemes. The proof of our composition theorem is based on a better understanding of the binding property of two-prover commitments that we provide in the form of new definitions and relations among them. These new insights are certainly of independent interest and are likely to be useful in other contexts as well. Finally, our work gives rise to several interesting open problems, for instance extending our results to the quantum setting, where the dishonest provers are allowed to perform measurements on an entangled quantum state in order to try to break the binding property., Comment: Independently and concurrently, Chakraborty, Chailloux, and Leverrier proved a similar bound on the Lunghi et al. scheme (https://arxiv.org/abs/1507.00239) with respect to a weaker notion of security. The latest revision also contains a tightness result similar to the one by Bricout and Chailloux (https://arxiv.org/abs/1608.03820), but with a different proof and a slightly better constant term

In PBN flight procedure design, in order to ensure the design quality, we need to evaluation the error of route parameters. Actual test is a good way, but it often requires large amounts of human, financial and other resources. In this paper, we use ArcGIS which has powerful data analysis function to assess the route parameter error, by comparative analysis of reverser's data and design data. The results show that the error assessment methods and conclusions of the final assessment of the actual test error coincide, the method can be used to evaluation the error of route parameters in PBN flight procedure design.

We propose some PAC like settings for a learning problem of a sub-class of linear languages, and show its polynomial time learnability in each of our settings. Here, the sub-class of linear languages is newly defined, and it includes the class of regular languages and the class of even linear languages. We show a polynomial time learning algorithm in either of the following settings with a fixed but unknown probability distribution for examples.(1) The first case is when the learner can use randomly drawn examples, membership queries, and a set of representative samples.(2) The second case is when the learner can use randomly drawn examples, membership queries, and both of the size of a grammar which can generate the target language and d. Where d is the probability such that the rarest rule in the target grammar occurs in the derivation of a randomly drawn example. In each case, for the target language Lt, the hypothesis Lhsatisfies thatPr[P(Lh Δ Lt) ≤ e] ≥ 1 - δ for the error parameter 0 < e ≤ 1 and the confidential parameter 0 < δ ≤ 1.

These In this paper, the control of the pneumatic actuator using Dahlin algorithm is proposed. Dahlin algorithm has problem which cause a steady-state error by an input-side disturbance for an integrator plant with time delay. In addition, it has problem which not ensure follow-up to a response model by parameter error of controller. To solve these problems, we introduce discrete-time IMC and iterative least squares technique. Our proposed method can remove a steady-state error caused by an input-side disturbance for an integrator plant with time delay by introducing discrete-time IMC and ensure follow-up to a response model by introducing iterative least squares technique. In the simulation, it is shown that the proposed method has a superior performance for an integrator plant with time delay. Furthermore, by applying the proposed method to a pneumatic actuator, the effectiveness of the method is examined and confirmed.

We present two new algorithms for solving the {\em All Pairs Shortest Paths} (APSP) problem for weighted directed graphs. Both algorithms use fast matrix multiplication algorithms. The first algorithm solves the APSP problem for weighted directed graphs in which the edge weights are integers of small absolute value in $\Ot(n^{2+\mu})$ time, where $\mu$ satisfies the equation $\omega(1,\mu,1)=1+2\mu$ and $\omega(1,\mu,1)$ is the exponent of the multiplication of an $n\times n^\mu$ matrix by an $n^\mu \times n$ matrix. Currently, the best available bounds on $\omega(1,\mu,1)$, obtained by Coppersmith, imply that $\mu0$ is an error parameter and W is the largest edge weight in the graph, after the edge weights are scaled so that the smallest non-zero edge weight in the graph is 1. It returns estimates of all the distances in the graph with a stretch of at most $1+\eps$. Corresponding paths can also be found efficiently., Comment: 27 pages, 19 figures, a preliminary version appeared in FOCS'98 under a slightly different title

This paper shows that an arbitrary Gaussian pure state can be deterministically generated in a dissipative open system that has quasi-local interactions between the subsystems and couples to surrounding environment in a local manner. A quasi-local interaction, which means that the interaction occurs among only a few subsystems, is a crucial requirement for practical engineering of a dissipative system. The key idea is that, first, an auxiliary system having local interaction with environment is prepared, and then that auxiliary system is coupled to the underlying target system via a set of two-body Hamiltonians in such a way that a desired pure state is generated. Moreover, we show that, even with a simple single-mode auxiliary system, deterministic generation of an arbitrary approximate Gaussian cluster state is possible, by devising an appropriate switching scheme. Lastly, we discuss in a specific example how much a dissipation-induced pure Gaussian state can be perturbed by decoherence and parameter error., Comment: 11 pages, 6 figures

In this paper we present first ever error-free, asynchronous broadcast (called as A-cast) and Byzantine Agreement (called as ABA) protocols with optimal communication complexity and fault tolerance. Our protocols are multi-valued, meaning that they deal with l bit input and achieve communication complexity of ${\mathcal O}(n\ell)$ bits for large enough l for a set of n≥3t+1 parties in which at most t can be Byzantine corrupted. Previously, Patra and Rangan (Latincrypt'10, ICITS'11) reported multi-valued, communication optimal A-cast and ABA protocols that are only probabilistically correct. Following all the previous works on multi-valued protocols, we too follow reduction-based approach for our protocols, meaning that our protocols are designed given existing A-cast and ABA protocols for small message (possibly for single bit). Our reductions invoke less or equal number of instances of protocols for single bit in comparison to the reductions of Patra and Rangan. Furthermore, our reductions run in constant expected time, in contrast to ${\mathcal O}(n)$ of Patra and Rangan (ICITS'11). Also our reductions are much simpler and more elegant than their reductions. By adapting our techniques from asynchronous settings, we present new error-free, communication optimal reduction-based protocols for broadcast (BC) and Byzantine Agreement (BA) in synchronous settings that are constant-round and call for only $\mathcal O(n^2)$ instances of protocols for single bit. Prior to this, communication optimality has been achieved by Fitzi and Hirt (PODC'06) who proposed probabilistically correct multi-valued BC and BA protocols with constant-round and ${\mathcal O}(n(n+\kappa))$ (κ is the error parameter) invocations to the single bit protocols. Recently, Liang and Vaidya (PODC'11) achieved the same without error probability. However, their reduction calls for round complexity and number of instances that are function of the message size, ${\mathcal O}(\sqrt{\ell} + n^2)$ and ${\mathcal O}(n^2\sqrt{\ell} + n^4)$ , respectively where l=Ω(n6).

Universal curves and approximate formulas for the elements of the track parameter error matrix are derived for homogeneous tracking detectors in the continuous measurement limit.

Given a stable L\'{e}vy process $X=(X_t)_{0\le t\le T}$ of index $\alpha\in(1,2)$ with no negative jumps, and letting $S_t=\sup_{0\le s\le t}X_s$ denote its running supremum for $t\in [0,T]$, we consider the optimal prediction problem \[V=\inf_{0\le\tau\le T}\mathsf{E}(S_T-X_{\tau})^p,\] where the infimum is taken over all stopping times $\tau$ of $X$, and the error parameter $p\in(1,\alpha)$ is given and fixed. Reducing the optimal prediction problem to a fractional free-boundary problem of Riemann--Liouville type, and finding an explicit solution to the latter, we show that there exists $\alpha_*\in(1,2)$ (equal to 1.57 approximately) and a strictly increasing function $p_*:(\alpha_*,2)\rightarrow(1,2)$ satisfying $p_*(\alpha_*+)=1$, $p_*(2-)=2$ and $p_*(\alpha), Comment: Published in at http://dx.doi.org/10.1214/10-AOP598 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org)

Any error of network parameters affects the value of the measurement residuals calculated in state estimation. Explicit mathematical expressions relating the residuals to the parameter errors are derived. A two-step approach is proposed for parameter error estimation. The first step is to estimate a bias vector which combines the effects of parameter errors and the state of the system. A least-square approach using the measurement residuals calculated in each state estimation run is proposed for the first step. After several state estimation runs, a sequence of such bias vectors is obtained. The second step is to estimate the parameter errors from the sequence of bias vectors. A recursive least-square estimation method is proposed for this step. Theoretical and computational issues of the proposed method are addressed. Test results are presented. >

In the context of big HST surveys, we present extensive and well tested image simulations to derive the survey detection completeness. We elaborate on the reliability of 2D galaxy fitting codes (GALFIT and GIM2D), which are widely used for morphological galaxy classification (especially for galaxies at high redshift), but are rarely tested thoroughly. While both codes perform similarly well on bright, big galaxies in these surveys, we find that GALFIT is more robust on faint and small galaxies, especially when used in the context of GALAPAGOS, a script that automates the fitting process successfully. Furthermore, we show that both codes underestimate the true parameter error bars severely. Whereas a Sérsic index cut is not an ideal tool to distinguish between early- and late-type galaxies it is widely used as such. We will point out potential complications in using such a simple automated cut. [1] © 2008 American Institute of Physics.