929 resultados para Dahlberg error


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"Appendix (p.203-292) Rules of the United States Circuit court of appeals for the Ninth circuit. Revised rules for the Supreme Court of the United States, under act of February 13, 1925, as amended June 7, 1926. Requirements respecting petitions for writs of certiorari under the act of February 13, 1925. Jurisdictional act of February 13, 1925, as amended April 3, 1926. Sections 24 and 25 of the Bankruptcy act, as amended May 28, 1926, effective August 28, 1926."

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Dizziness and/or unsteadiness are common symptoms of chronic whiplash-associated disorders. This study aimed to report the characteristics of these symptoms and determine whether there was any relationship to cervical joint position error. Joint position error, the accuracy to return to the natural head posture following extension and rotation, was measured in 102 subjects with persistent whiplash-associated disorder and 44 control subjects. Whiplash subjects completed a neck pain index and answered questions about the characteristics of dizziness. The results indicated that subjects with whiplash-associated disorders had significantly greater joint position errors than control subjects. Within the whiplash group, those with dizziness had greater joint position errors than those without dizziness following rotation (rotation (R) 4.5degrees (0.3) vs 2.9degrees (0.4); rotation (L) 3.9degrees (0.3) vs 2.8degrees (0.4) respectively) and a higher neck pain index (55.3% (1.4) vs 43.1% (1.8)). Characteristics of the dizziness were consistent for those reported for a cervical cause but no characteristics could predict the magnitude of joint position error. Cervical mechanoreceptor dysfunction is a likely cause of dizziness in whiplash-associated disorder.

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The reliability of measurement refers to unsystematic error in observed responses. Investigations of the prevalence of random error in stated estimates of willingness to pay (WTP) are important to an understanding of why tests of validity in CV can fail. However, published reliability studies have tended to adopt empirical methods that have practical and conceptual limitations when applied to WTP responses. This contention is supported in a review of contingent valuation reliability studies that demonstrate important limitations of existing approaches to WTP reliability. It is argued that empirical assessments of the reliability of contingent values may be better dealt with by using multiple indicators to measure the latent WTP distribution. This latent variable approach is demonstrated with data obtained from a WTP study for stormwater pollution abatement. Attitude variables were employed as a way of assessing the reliability of open-ended WTP (with benchmarked payment cards) for stormwater pollution abatement. The results indicated that participants' decisions to pay were reliably measured, but not the magnitude of the WTP bids. This finding highlights the need to better discern what is actually being measured in VVTP studies, (C) 2003 Elsevier B.V. All rights reserved.

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The use of presence/absence data in wildlife management and biological surveys is widespread. There is a growing interest in quantifying the sources of error associated with these data. We show that false-negative errors (failure to record a species when in fact it is present) can have a significant impact on statistical estimation of habitat models using simulated data. Then we introduce an extension of logistic modeling, the zero-inflated binomial (ZIB) model that permits the estimation of the rate of false-negative errors and the correction of estimates of the probability of occurrence for false-negative errors by using repeated. visits to the same site. Our simulations show that even relatively low rates of false negatives bias statistical estimates of habitat effects. The method with three repeated visits eliminates the bias, but estimates are relatively imprecise. Six repeated visits improve precision of estimates to levels comparable to that achieved with conventional statistics in the absence of false-negative errors In general, when error rates are less than or equal to50% greater efficiency is gained by adding more sites, whereas when error rates are >50% it is better to increase the number of repeated visits. We highlight the flexibility of the method with three case studies, clearly demonstrating the effect of false-negative errors for a range of commonly used survey methods.

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A quantum circuit implementing 5-qubit quantum-error correction on a linear-nearest-neighbor architecture is described. The canonical decomposition is used to construct fast and simple gates that incorporate the necessary swap operations allowing the circuit to achieve the same depth as the current least depth circuit. Simulations of the circuit's performance when subjected to discrete and continuous errors are presented. The relationship between the error rate of a physical qubit and that of a logical qubit is investigated with emphasis on determining the concatenated error correction threshold.

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We describe a scheme for quantum-error correction that employs feedback and weak measurement rather than the standard tools of projective measurement and fast controlled unitary gates. The advantage of this scheme over previous protocols [for example, Ahn Phys. Rev. A 65, 042301 (2001)], is that it requires little side processing while remaining robust to measurement inefficiency, and is therefore considerably more practical. We evaluate the performance of our scheme by simulating the correction of bit flips. We also consider implementation in a solid-state quantum-computation architecture and estimate the maximal error rate that could be corrected with current technology.

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We demonstrate a quantum error correction scheme that protects against accidental measurement, using a parity encoding where the logical state of a single qubit is encoded into two physical qubits using a nondeterministic photonic controlled-NOT gate. For the single qubit input states vertical bar 0 >, vertical bar 1 >, vertical bar 0 > +/- vertical bar 1 >, and vertical bar 0 > +/- i vertical bar 1 > our encoder produces the appropriate two-qubit encoded state with an average fidelity of 0.88 +/- 0.03 and the single qubit decoded states have an average fidelity of 0.93 +/- 0.05 with the original state. We are able to decode the two-qubit state (up to a bit flip) by performing a measurement on one of the qubits in the logical basis; we find that the 64 one-qubit decoded states arising from 16 real and imaginary single-qubit superposition inputs have an average fidelity of 0.96 +/- 0.03.

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We describe an implementation of quantum error correction that operates continuously in time and requires no active interventions such as measurements or gates. The mechanism for carrying away the entropy introduced by errors is a cooling procedure. We evaluate the effectiveness of the scheme by simulation, and remark on its connections to some recently proposed error prevention procedures.

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Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

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A framework for developing marketing category management decision support systems (DSS) based upon the Bayesian Vector Autoregressive (BVAR) model is extended. Since the BVAR model is vulnerable to permanent and temporary shifts in purchasing patterns over time, a form that can correct for the shifts and still provide the other advantages of the BVAR is a Bayesian Vector Error-Correction Model (BVECM). We present the mechanics of extending the DSS to move from a BVAR model to the BVECM model for the category management problem. Several additional iterative steps are required in the DSS to allow the decision maker to arrive at the best forecast possible. The revised marketing DSS framework and model fitting procedures are described. Validation is conducted on a sample problem.

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Operator quantum error correction is a recently developed theory that provides a generalized and unified framework for active error correction and passive error avoiding schemes. In this Letter, we describe these codes using the stabilizer formalism. This is achieved by adding a gauge group to stabilizer codes that defines an equivalence class between encoded states. Gauge transformations leave the encoded information unchanged; their effect is absorbed by virtual gauge qubits that do not carry useful information. We illustrate the construction by identifying a gauge symmetry in Shor's 9-qubit code that allows us to remove 3 of its 8 stabilizer generators, leading to a simpler decoding procedure and a wider class of logical operations without affecting its essential properties. This opens the path to possible improvements of the error threshold of fault-tolerant quantum computing.

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This letter presents an analytical model for evaluating the Bit Error Rate (BER) of a Direct Sequence Code Division Multiple Access (DS-CDMA) system, with M-ary orthogonal modulation and noncoherent detection, employing an array antenna operating in a Nakagami fading environment. An expression of the Signal to Interference plus Noise Ratio (SINR) at the output of the receiver is derived, which allows the BER to be evaluated using a closed form expression. The analytical model is validated by comparing the obtained results with simulation results.

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Very few empirically validated interventions for improving metacognitive skills (i.e., self-awareness and self-regulation) and functional outcomes have been reported. This single-case experimental study presents JM, a 36-year-old man with a very severe traumatic brain injury (TBI) who demonstrated long-term awareness deficits. Treatment at four years post-injury involved a metacognitive contextual intervention based on a conceptualization of neuro-cognitive, psychological, and socio-environmental factors contributing to his awareness deficits. The 16-week intervention targeted error awareness and self-correction in two real life settings: (a) cooking at home: and (b) volunteer work. Outcome measures included behavioral observation of error behavior and standardized awareness measures. Relative to baseline performance in the cooking setting, JM demonstrated a 44% reduction in error frequency and increased self-correction. Although no spontaneous generalization was evident in the volunteer work setting, specific training in this environment led to a 39% decrease in errors. JM later gained paid employment and received brief metacognitive training in his work environment. JM's global self-knowledge of deficits assessed by self-report was unchanged after the program. Overall, the study provides preliminary support for a metacognitive contextual approach to improve error awareness and functional Outcome in real life settings.