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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.

本論文では、フィードバック制御による平面宇宙ロボットの姿勢制御問題を取り扱う。非ホロノミック拘束をもつ宇宙ロボットの姿勢をフィードバックにより制御する研究としては、これまでに直線経路に基づく不変マニフォールドを利用した手法が提案されている。ここでは、より一般的な経路に基づくマニフォールドを利用することで、フィードバック制御系の特性を改善する。具体的には、マニフォールドまでの漸近収束性、収束速度、パラメター誤差に対するロバスト性について検討する。, This paper deals with feedback control strategy for attitude reorientation of a planar space robot. While the previous work for attitude reorientation proposes to utilize an invariant manifold designed by a straight line trajectory toward the desired configuration, the present study designs invariant manifolds for general trajectories. By using the proposed manifolds, asymptotic convergence to an invariant manifold can be proved analytically, and convergence speed and robustness for parametric errors of the space robot are improved., 資料番号: AA0063480046

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.

One of the longest standing open questions in adaptive control concerns the correctness of the stability claim of the un–normalized model reference scheme proposed by R. V. Monopoli in 1974. Although provably correct solutions to the problem now abound, in particular, it is well–know that adding a normalization to Monopoli’s original scheme ensures global convergence, it is interesting to know whether this technique– driven modification is really necessary or only required to complete the stability proof in the absence of more elaborate arguments. In this paper we construct a counterexample that provides a definite—unfortunately, negative—answer to the claim. Instrumental for the establishment of this result is a technical lemma that shows that, under some conditions on the regressor that may appear in Monopoli’s scheme, the parameter error freezes as the adaptation gain goes to infinity. On the lighter side, we also prove that the counterexample can be “fixed”, in the sense of achieving semiglobal stability, adjusting some tuning parameters.

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

×n matrix A with entries between say −1 and 1, and an error parameter e between 0 and 1, we find a matrix D (implicitly) which is the sum of \(\) simple rank 1 matrices so that the sum of entries of any submatrix (among the \(\)) of (A−D) is at most emn in absolute value. Our algorithm takes time dependent only on e and the allowed probability of failure (not on m, n).

The well-known recursive least-squares (RLS) algorithm experiences overshoot in the norm of the parameter error vector temporarily during the initialisation stage when the initial value of the input autocorrelation matrix is chosen very small. We have had no guide to choose a suitable initial value of the input autocorrelation matrix in order to cause the RLS algorithm not to fluctuate during the initialisation phase. In this paper, deriving the bound of parameter error norm square, we give a useful guide to choose the initial value in order to avoid the initial overshoot in the RLS algorithm. Besides, we show that what are the crucial factors of the overshoot phenomena. The ratio of the initial value to the input power should be chosen according to the signal-to-noise ratio of the system and the order of the filter. We present various simulation results to validate our analysis.

In practical computation of the discrete best uniform approximation, we usually only get “near best” (i.e., with the “e-near alteration property”) approximation. We need to estimate the error between the (unknown) best approximation and the achieved approximation. In this paper we estimate the parameter error by means of the generalized strong unicity constants.

Recently a practical and efficient off-line approach for network branch parameter (series and shunt admittances) errors detection, identification and correction was developed. In comparison with other methodologies already proposed for branch parameters validation, the novel features of this off-line approach are the identification procedure of suspicious branches and the way the augmented state-parameter estimation problem is solved. Several simulation results (with IEEE bus systems) have demonstrated the high correctness and reliability of that off-line approach to deal with single and multiple parameter errors in adjacent (those having a terminal bus in common) and non-adjacent branches. Moreover the approach was also demonstrated on tests performed on the Hydro-Quebec Trans-Energie networks. One of these tests shows that approach enables the validation of series and shunt admittances of parallel transmission lines with series compensation. However, that offline approach does not have the desired property of distinguishing between bad data (bad analog measurements) and branch parameter errors. This paper presents a simple yet effective improvement by creating new indexes that enable the distinction between bad data and branch parameter errors, even when both appear simultaneously. Simulation results have sown the effectiveness of including the new indexes in that off-line approach.

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 a conversation between multiple speakers, each person participates in the speech at different times. Therefore the active speakers in each speech segment are unknown. However, identifying the voice activity (VA) of the speakers of interest is required for adaptive beamforming techniques such as minimum variance distortionless response beamforming and the adaptive blocking beamforming (AB). Considering two speakers, this paper addresses a voice activity classification (VAC) problem that focuses on identifying the active speaker(s) in each speech segment. The proposed method is based on a new concept, the beamformer-output-ratio (BOR). This value is calculated from the outputs of two different beamformers steering at two speakers. The first part of the paper introduces the definition of BOR, the VAC method using BOR and simulation results. The simulations are based on real recordings and show a high classification accuracy. In the second part of the paper, the theoretical results of the BOR of the delay-and-sum (DS) beamforming are presented, including BOR formula derived in different environments and its behaviour in relation to parameter errors. Refereed/Peer-reviewed

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.

The variable precision covering rough set model is promoted by extending the range of error parameter in this paper. Some properties of the promoted variable precision covering rough set model are discussed. Furthermore, we get some meaningful conclusion by means of researching on the power effect of covering variable precision approximation operators for the promoted variable precision covering rough set model.

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)

This paper reports the results of a study of an error parameter, m, which has been proposed as a measure for determining the effects on accuracy of the basic assumptions upon which TLM modelling of diffusion and heat flow has been founded. The nature of the m parameter is studied in detail by using a two-dimensional thermal diffusion problem. The use of m in the implementation of automatic timestepping is discussed in a practical three-dimensional engineering problem.

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. >

Mining frequent itemsets over online data streams, where the new data arrive and the old data will be removed with high speed, is a challenge for the computational complexity. Existing approximate mining algorithms suffer from explosive computational complexity when decreasing the error parameter, ∈, which is used to control the mining accuracy. We propose a new approximate mining algorithm using an approximate frequent itemset tree (abbreviated as AFI-tree), called AFI algorithm, to mine approximate frequent itemsets over online data streams. The AFI-tree based on prefix tree maintains only frequent itemsets, so the number of nodes in the tree is very small. All the infrequent child nodes of any frequent node are pruned and the maximal support of the pruned nodes is estimated to detect new frequent itemsets. In order to guarantee the mining accuracy, when the estimated maximal support of the pruned nodes is a bit more than the minimum support, their supports will be re-computed and the frequent nodes among them will be inserted into the AFI-tree. Experimental results show that the AFI algorithm consumes much less memory space than existing algorithms, and runs much faster than existing algorithms in most occasions.

This paper combines with Kafang’s engineering practice of Xinshan mining area, makes crater tests, and then determines the blasting parameters under experimental conditions. Train the key stakeholders blasting parameters both at home and abroad based on the BP artificial neural network (ANN) model. On the basis that the best charge depth is 1.09m which under the experimental conditions of blasting crater test. Conduct optimizing calculation of blasting parameters by using EasyNN-plus software. Through a comprehensive analysis of optimization ways and parameter error, recommend blasting parameters under experimental conditions: charge depth L=1.09m, the best crater radius Rj=0.77-0.79m, the best crater volume Vj=0.5-0.6m3, and explosive consumption 1.0-1.1kg/t.

We investigate the problem of finding frequent patterns in a continuous stream of transactions. It is recognized that the approximate solutions are usually sufficient and many existing literature explicitly trade off accuracy for speed where the quality of the final approximate counts are governed by an error parameter, i¾?. However, the quantification of i¾?is never simple. By setting a small i¾?, we achieve good accuracy but suffer in terms of efficiency. A bigger i¾?improves the efficiency but seriously degrades the mining accuracy. To alleviate this problem, we offer an alternative which allows user to customize a set of error bounds based on his requirement. Our experimental studies show that the proposed algorithm has high precision, requires less memory and consumes less CPU time.

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.

Inverse problems in geophysics are usually ill-posed, in such a way that regularization is one possibility to have more stable solutions. The quality of the regularized solution however depends on the appropriate selection of the regularization parameter λ . One now popular tool for the selection of λ is the so-called L-curve, reintroduced in the literature of inverse problems by Hansen in the 1990’s. L-curve may sometimes provide a non-optimal λ for imaging, so that in the present work we compare three methodologies for the selection of λ . The first one is the λ provided by the Hansen’s toolbox. The second is the visual inspection of the L-curve built by us, and the third one is the critical point of the L-curve first derivative, which is, in general, equivalent to the inflection point, or the L-curve’s knee. This point is the appropriate compensation between the x axis which is the data parameter error, and the y axis, which represents the amount of regularization. Extensive simulations with synthetic data in traveltime tomography leaded us to the conclusion that all three methodologies are feasible, although we noticed that for the zero order regularization, with noisy data, visual inspection and first derivative methodologies provided the best results.

In this paper, the quantization error and parameters of the single-lens prism-based stereovision system are studied in detail. Each image captured using this system can be divided into two subimages on the left and right, and these subimages are generated by two virtual cameras that are produced by the biprism. This stereovision system is equivalent to the conventional two-camera system and the two subimages captured have disparity that can be used to reconstruct the 3D scene. The relative range error of this system is studied with respect to the system parameters, which gives us a better way to quantify the range resolution of the system and enables the selection of system parameters to become easier.

A novel error parameter analysis approach for synthesis of an artificial transmission line (ATL) from the ABCD parameters of a uniform transmission line section is presented. An MMIC ATL delay line with 180deg phase shift is synthesized to demonstrate this approach. The MMIC is fabricated using a conventional GaAs process and test results are validated with those of the simulated results.

The following sections are included:IntroductionWays of Fitting the Data to the Set of TheoriesError SpecificationsDescribing True PreferencesThe ExperimentsAnalyzing the ResultsCorrecting for Degrees of FreedomFull and Overfull CorrectionCP Errors in the Complete Ranking ExperimentPreference Functionals FittedResultsConclusionsAcknowledgementsReferences

One of the longest standing open questions in adaptive control concerns the correctness of the stability claim of the un-normalized model reference scheme proposed by Monopoli in 1974. Although provably correct solutions to the problem now abound, in particular, it is well known that adding a normalization to Monopoli's original scheme ensures global convergence, it is interesting to know whether this technique-driven modification is really necessary or only required to complete the stability proof in the absence of more elaborate arguments. In this note, we construct a counterexample that provides a definite-unfortunately, negative-answer to the claim. Instrumental for the establishment of this result is a technical lemma that shows that, under some conditions on the regressor that may appear in Monopoli's scheme, the parameter error freezes as the adaptation gain goes to infinity. On the lighter side, we also prove that Monopoli's scheme is semiglobally stable, underscoring the relevance of this important contribution.

The adaptive control of feedback linearizable discrete-time systems is studied. The nonlinearities in the system are linear combinations of known nonlinear functions. Although the unknown parameters appear linearly, the convergence result obtained is not global. The maximum allowable parameter error depends on the system characteristics and on the initial system states. Simulations show that the system diverges when the initial parameter error is too large.

*† Standard sequential loop closure design based on Evans root migration concepts is a well accepted, insightful and effective technique for meeting nominal performance objectives and traditional gain-phase stability margin requirements. Unfortunately, assessment of closedloop variations resulting from parameter error is a post-process, implying an iterative design-assess-redesign procedure is necessary if variations are found unacceptable. Further, the modern parameter uncertainty assessment framework is often inconsistent, both quantitatively and qualitatively, with the redesign task. Specifically, the parameter uncertainty assessment variables are not readily apparent in the sequential loop design framework, and these variables provide little guidance for the redesign strategy. Therefore, expanding the root migration sequential loop design methodology to directly incorporate the parameter uncertainty framework is explored. A sequential loop closure design procedure is enhanced to include closed-loop transfer function polynomials as a function of parameter uncertainty in such away that allows uncertainty root locus plots to be carried along in successive design steps. This graphical information facilitates insight into key closed-loop poles and zeros and system variables that influence parameter robustness properties. The engineer can evaluate and tune traditional stability and performance metrics simultaneously with newer parameter uncertainty metrics at each design step leading to the final overall multivariable control system.

Some influencing factors on the parameter estimation of satellite interference location is discussed in this paper. For every factor, quantitative analysis was carried out to show the influence on the parameter estimation. The analyses concerning the parameter error are backed up with an estimation experiment using actual signals relayed by two satellites.

We show that s-term DNF formulas can be learned under the uniform distribution in quasi-polynomial time with statistical queries of tolerance Ω(e/s). The tolerance improves on the known tolerance Ω(e2/s) and is optimal with respect to its dependence on the error parameter e. We further consider the related model of learning with proper distance queries and show that DNF formulas can be learned under the uniform distribution with quasi-polynomial queries, where the hypotheses are DNF formulas of polynomial size. Finally we consider the class of majorities over DNF formulas and provide polynomially related upper and lower bounds for the number of distance queries required to learn this class.

We investigate the required redshift accuracy of type Ia supernova and cluster number-count surveys in order for the redshift uncertainties not to contribute appreciably to the dark energy parameter error budget. For the SNAP supernova experiment, we find that, without the assistance of ground-based measurements, individual supernova redshifts would need to be determined to about 0.002 or better, which is a challenging but feasible requirement for a low-resolution spectrograph. However, we find that accurate redshifts for z1) clusters., Submitted to ApJ. Gaussianity assumption for observables fully justified. Photo-z's for SNe discussed

The CSG’s physical performance is decided by its structural parameters, such as width of grating stair, height of grating stair, and the shape of stair edge. Consideration of the practical fabrication process, an error model of CSG’s structure is built to express the relationship between CSG’s performance and its structural parameters. In this model, each structural parameter of CSG is expressed as a variable, and the structural parameter error induced by fabrication process is expressed as minute disturb of relative variable. Through analysis and simulation, we obtained a general estimation standard for the structural parameter errors of CSG, which provides a theoretical direction for CSG’s fabrication and usage.

The development of the XCS Learning Classifier System [26] has produced a stable implementation, able to consistently identify the accurate and optimally general population of classifiers mapping a given reward landscape [15,16,29]. XCS is particularly powerful within direct-reward environments, and notably within problems suitable for commercial application [3]. The application of XCS within delayed reward environments has also shown promise, although early investigations were within enviroments with a comparatively short delay to reward (e.g. [28, 19]). Subsequent systematic investigation [19,20,1,2] have suggested that XCS has difficulty accurately mapping and exploiting even simple environments with moderate reward delays. This paper summarises these results and presents new results that identify some limits and their implications. A modification to the error computation within XCS is introduced that allows the minimum error parameter to be applied relative to the magnitude of the payoff to each classifier. First results demonstrate that this modification enables XCS to successfully map longer delayed-reward enviroments.

A new adaptation algorithm is presented for adaptive control of robot manipulators. The passivity property of the proposed algorithm is first established, then the stability is proved based on the passivity properties of the plant and those of the proposed algorithm. Because of the use of the past information and averaging effect, this algorithm gives a smoother tracking and parameter error in the presence of disturbances, and a parameter convergence under a weaker excitation condition. Computer simulations are presented to illustrate this effect. >

An identification method for dynamic models of robots that improves on the sequential estimation method of Mayeda, K. Osuka and A. Kangawa (1984) is proposed. This method has the following advantages over the sequential estimation method: the parameter error propagation is reduced, because parameters directly estimated from the data are used instead of parameters indirectly calculated; and analysis calculation for identification is reduced, because at most four degrees of freedom of the robot to be identified are considered. The method is applied to a 6 d.o.f. direct drive robot. >

This article deals with the algorithm of measurement and design of probe sensors of conductivity for determination of parameters of plasma and melt of the heat-protecting antenna material within the framework of solving the problem of maintenance of steady communication with a satellite on a flight descent segment. The problem of the measured parameter error is considered separately.

Following publication of the paper, the authors have detected a parameter error in the Eq. (5) which was used for estimating greenhouse eference evapotranspiration (ET0). The equation of FAO 56 Penman–Monteith method with a fixed aerodynamic resistance of 295 s m−1 hould be: ET0 = 0.408 (Rn − G) + 628 T+273 (es − ea) (5) + 1.24 The ET0 value used in the paper was correct. There were some errors in publication process. No further changes were required in the Results” and “Discussion and Conclusions” sections of the paper. The authors would like to apologise for any inconvenience caused.

We model a load using an artificial neural network (ANN) to improve an on-wafer line-reflect-match (LRM) calibration of a vector network analyzer (VNA). The ANN is trained with measurement data obtained from a thru-reflect-line (TRL) calibration. The accuracy of the LRM calibration using the ANN-modeled load compares favorably to a benchmark multiline TRL calibration with an average worst-case scattering parameter error bound of 0.017 over a 40-GHz bandwidth.

A short-coding error parameter (SCEP) that provides a bound on the average probability of decoding error for codes with length shorter than the memory length is presented. It is shown that this bound is tighter than the bound based on the conventional cutoff rate and that the SCEP is independent of the channel's memory length, provided the codeword length is shorter than the memory length. >

Many parameters influence the quality of machined parts on five-axis machine tools. One important family of parameters are the geometric inaccuracies in the relative location of the machine axes. A method is proposed which uses a telescoping magnetic ball bar to identify these error sources. The methodology is applied to position independent geometric error parameters such as joint misalignments, angular offset and axes separation. Simulation results support the effectiveness of the approach.

The extent to which errors in predicting body segment parameters (SP) influence biomechanical analysis of human motion is unclear. Therefore, the current study quantitatively evaluated the differences in SP estimates using literature predictive functions and computed the effect of SP variation on the kinetic output of walking. For a group of 15 young males, significant differences (P0. 05) were observed between SP estimates for the leg and thigh using the literature predictive functions, with mass and moment of inertial values differing by more than 40%. Using kinematic and ground reaction force data collected for each subject while walking, inverse dynamic analysis was performed iteratively to compute hip forces and moments while simultaneously varying SP values over nine intervals within +/-40% of a baseline value. SP variations were found to significantly affect (P0.05) most of the kinetic estimates produced, particularly those taken during the swing phase. However, the magnitude of these effects was generally less than 1% of body weight. The data from the current study allows researchers to estimate the errors in kinetic measures due to SP variation. The results also indicate that the accuracy of SP prediction should be of concern in biomechanical research particularly for open chain and high acceleration activities. Further study is necessary to identify the importance of SP variation on other motion skills.

This paper presents a new automation algorithm for parameter commissioning of AC motors, which is based upon the method using the characteristics of the controller and Walsh function analysis. By investigating the distortion of controller output resulting from parameter error and evaluating through Walsh function analysis, the proposed adaptation process can achieve the commissioning of AC motors automatically. In this paper, a waveform distortion index (WDI) according to type of AC motors and their parameters are decided. To prove the effectiveness of the proposed automatic parameter commissioning algorithm to real industrial fields experimental verifications are achieved.

Background The role of pharmacokinetic modelling is important in the development of new formulations. Some of these models are related to a particular dosage form, others are similar to models that have already been developed. Intranasal (IN) administration can be an example of a dosage form with a specific pharmacokinetic model, especially when it is applied to create a systemic effect. Purpose To design a pharmacokinetic model that adequately describes a dual absorption profile of the concentration-time curve for intranasal administration. Materials and Methods A strategy to predict dual absorption was developed to describe the pharmacokinetics of an intranasal administration (model1 and model2). A programme for fitting and simulation was developed (SIMLAB). Midazolam nasal spray was used as an example for this model. To validate the final pharmacokinetic model, Monte Carlo simulations were performed. Results We had trouble fitting the observations to a single one-compartment dual absorption model. In many cases a flip-flop condition occurred in which the fitted absorption rate was lower than the estimated elimination rate, and the elimination rate showed an unrealistic value. To prevent this flip-flop condition, we used the absorption parameters from the associated observations. We developed the following model: the model superposes two one-compartment absorption models where the dose is split up over the two compartment inputs and the concentration-time curves are separated by using different lag-times (t0). Monte Carlo simulations resulted in a plasma concentration-time profile, indicating the median concentration and the 5th–95th percentile ranges. Biphasic profiles were observed starting at a parameter error of 15%, increasing to 13.6% of biphasic profiles at a parameter error of 50%. When increasing the difference between a parameter in Model 1 and Model 2, the contribution of t0 to creating a local minimum exceeded the contribution of ka. The AUC of the measured and estimated curve was 201.6 µg/L*h and 201.3 µg/L*h, respectively. Conclusions The model developed is able to fit concentration-time curves showing individual dual absorption curves adequately. No conflict of interest.

Purpose: The purpose of this study is to evaluate delivery parameter errors (DPEs) and their impact on clinical dose variation with the Varian RapidArc technique. Methods: The dynalog files of 16 head-and-neck patients were retrospectively analyzed to characterize three RapidArc DPEs: dose MU, gantry angle, and MLC gap errors. A total of 64 reconstructed plans were created by creating four variants of each of the original 16 plans (three with the DPEs applied individually and one with the three DPEs combined). These reconstructed plans were compared to the original plans to evaluate the impact of the DPEs on the clinical dose distribution. Results: The mean dose MU, gantry angle, and MLC gap error for all patients were 0.00 ± 0.00 MU, −0.36 ± 0.03°, and 0.00 ± 0.01 mm, respectively. The DPEs had no obvious dosimetric impact on any of the studied dosimetric endpoints except the parotid dose. The gantry angle error, MLC gap error, and combined DPEs changed the parotid Dmean (mean dose) and parotid V30 (volume receiving at least 30 Gy) by 1%–2%. Conclusions: It is feasible to use dose distributions reconstructed from dynalog file data as a quality assurance tool. The dose MU, gantry angle, and MLC errors have only minor effects on the accuracy of the delivered dose.

We present a new approach to adaptive nonlinear control based on a complete controller-identifier separation which has long been a goal in adaptive system design. Our controllers guarantee certain input/state stability properties with respect to the parameter error % MathType!MTEF!2!1!+- % feaagaart1ev2aaatCvAUfKttLearuqr1ngBPrgarmWu51MyVXgatC % vAUfeBSjuyZL2yd9gzLbvyNv2CaeHbd9wDYLwzYbItLDharyavP1wz % ZbItLDhis9wBH5garqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbb % L8F4rqqrFfpeea0xe9Lq-Jc9vqaqpepm0xbba9pwe9Q8fs0-yqaqpe % pae9pg0FirpepeKkFr0xfr-xfr-xb9adbaqaaeGaciGaaiaabeqaam % aaeaqbaaGcbiqaca0fcuaH4oqCgaacaaaa!3CEC! \[ \tilde \theta \] and its derivative % MathType!MTEF!2!1!+- % feaagaart1ev2aaatCvAUfKttLearuqr1ngBPrgarmWu51MyVXgatC % vAUfeBSjuyZL2yd9gzLbvyNv2CaeHbd9wDYLwzYbItLDharyavP1wz % ZbItLDhis9wBH5garqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbb % L8F4rqqrFfpeea0xe9Lq-Jc9vqaqpepm0xbba9pwe9Q8fs0-yqaqpe % pae9pg0FirpepeKkFr0xfr-xfr-xb9adbaqaaeGaciGaaiaabeqaam % aaeaqbaaGcbiqaca0fcuaH4oqCgaacgaGaaaaa!3CF4! \[ \dot \tilde \theta \] as inputs. The parameter identifiers, in turn, guarantee % MathType!MTEF!2!1!+- % feaagaart1ev2aaatCvAUfKttLearuqr1ngBPrgarmWu51MyVXgatC % vAUfeBSjuyZL2yd9gzLbvyNv2CaeHbd9wDYLwzYbItLDharyavP1wz % ZbItLDhis9wBH5garqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbb % L8F4rqqrFfpeea0xe9Lq-Jc9vqaqpepm0xbba9pwe9Q8fs0-yqaqpe % pae9pg0FirpepeKkFr0xfr-xfr-xb9adbaqaaeGaciGaaiaabeqaam % aaeaqbaaGcbiGacWefca0fcuaH4oqCgaacaiabgIGioprr1ngBPrwt % HrhAXaqehuuDJXwAKbstHrhAG8KBLbacgaGae8NeHWKaeyOhIukaaa!4AD4! \[ \tilde \theta \in \mathcal{L}\infty \] , and either % MathType!MTEF!2!1!+- % feaagaart1ev2aaatCvAUfKttLearuqr1ngBPrgarmWu51MyVXgatC % vAUfeBSjuyZL2yd9gzLbvyNv2CaeHbd9wDYLwzYbItLDharyavP1wz % ZbItLDhis9wBH5garqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbb % L8F4rqqrFfpeea0xe9Lq-Jc9vqaqpepm0xbba9pwe9Q8fs0-yqaqpe % pae9pg0FirpepeKkFr0xfr-xfr-xb9adbaqaaeGaciGaaiaabeqaam % aaeaqbaaGcbiGacWefca0fcuaH4oqCgaacgaGaaiabgIGioprr1ngB % PrwtHrhAXaqehuuDJXwAKbstHrhAG8KBLbacgaGae8NeHWKaeyOhIu % kaaa!4ADC! \[ \dot \tilde \theta \in \mathcal{L}\infty \] or % MathType!MTEF!2!1!+- % feaagaart1ev2aaatCvAUfKttLearuqr1ngBPrgarmWu51MyVXgatC % vAUfeBSjuyZL2yd9gzLbvyNv2CaeHbd9wDYLwzYbItLDharyavP1wz % ZbItLDhis9wBH5garqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbb % L8F4rqqrFfpeea0xe9Lq-Jc9vqaqpepm0xbba9pwe9Q8fs0-yqaqpe % pae9pg0FirpepeKkFr0xfr-xfr-xb9adbaqaaeGaciGaaiaabeqaam % aaeaqbaaGcbiGacWefca0fcuaH4oqCgaacgaGaaiabgIGioprr1ngB % PrwtHrhAXaqehuuDJXwAKbstHrhAG8KBLbacgaGae8NeHW0aaSbaaS % qaaiabikdaYaqabaaaaa!4A89! \[ \dot \tilde \theta \in \mathcal{L}_2 \] or both. This estimation-based approach encompases two families of schemes: swapping-based and observer-based. Swapping-based schemes allow the use of a wide variety of update laws — gradient and least-squares, normalized and unnormalized. Observer-based schemes use parameter identifiers of lower dynamic order. All these schemes achieve systematic improvement of transient performance.

An online degradation model is presented, in which is avoided the error in parameter degradation accelerated test, which is caused by temperature shock during parameter measurement. Through the measurement with avoiding the error parameter, the parameter degradation model can be more accurate. To demonstrate the application of the method, a kind of mature product, 3CG120, is tested in a temperature range of 150230 ℃ under online process-stress. Then the error of lifetime is obtained by utilizing the online model to be about 6.5%, much less than that of the old model (23.2%).