Target/error overlap in jargonaphasia:the case for a one-source model, lexical and non-lexical summation, and the special status of correct responses

We present three jargonaphasic patients who made phonological errors in naming, repetition and reading. We analyse target/response overlap using statistical models to answer three questions: 1) Is there a single phonological source for errors or two sources, one for target-related errors and a separate source for abstruse errors? 2) Can correct responses be predicted by the same distribution used to predict errors or do they show a completion boost (CB)? 3) Is non-lexical and lexical information summed during reading and repetition? The answers were clear. 1) Abstruse errors did not require a separate distribution created by failure to access word forms. Abstruse and target-related errors were the endpoints of a single overlap distribution. 2) Correct responses required a special factor, e.g., a CB or lexical/phonological feedback, to preserve their integrity. 3) Reading and repetition required separate lexical and non-lexical contributions that were combined at output.

A Generalized Quasi-Likelihood Estimator for Nonstationary Stochastic Processes−Asymptotic Properties and Examples

2010 Mathematics Subject Classification: 62F12, 62M05, 62M09, 62M10, 60G42.

Large and Moderate Deviations Principles for Recursive Kernel Estimator of a Multivariate Density and its Partial Derivatives

2000 Mathematics Subject Classification: 62G07, 60F10.

Comparison of numerical bit error rate estimation methods in 112Gbs QPSK CO-OFDM transmission

We demonstrate an accurate BER estimation method for QPSK CO-OFDM transmission based on the probability density function of the received QPSK symbols. Using a 112Gbs QPSK CO-OFDM transmission as an example, we show that this method offers the most accurate estimate of the system's performance in comparison with other known approaches.

Intraoperative prediction of refractive error using a prototype surgical aberrometer

Purpose: To ascertain the agreement level between intra-operative refraction using a prototype surgical Hartmann-Shack aberrometer and subjective refraction a month later. Methods: Fifty-four consecutive patients had their pseudophakic refractive measured with the aberrometer intra-operatively at the end of their cataract surgery. A masked optometrist performed subjective refraction 4 weeks later. The two sets of data were then analysed for correlation. Results: The mean spherical equivalent was −0.14 ± 0.37 D (Range: −1.41 to +1.72 D) with the prototype aberrometer and −0.34 ± 0.32 (−1.64 to +1.88 D) with subjective refraction. The measurements positively correlated to a very high degree (r =+0.81, p < 0.01). In 84.3% of cases the two measurements were within 0.50D of each other. Conclusion: The aberrometer can verify the aimed refractive status of the eye intraoperatively to avoid a refractive surprise. The aberrometer is a useful tool for real time assessment of the ocular refractive status.

Pairwise comparison matrices and the error-free property of the decision maker

Pairwise comparison is a popular assessment method either for deriving criteria-weights or for evaluating alternatives according to a given criterion. In real-world applications consistency of the comparisons rarely happens: intransitivity can occur. The aim of the paper is to discuss the relationship between the consistency of the decision maker—described with the error-free property—and the consistency of the pairwise comparison matrix (PCM). The concept of error-free matrix is used to demonstrate that consistency of the PCM is not a sufficient condition of the error-free property of the decision maker. Informed and uninformed decision makers are defined. In the first stage of an assessment method a consistent or near-consistent matrix should be achieved: detecting, measuring and improving consistency are part of any procedure with both types of decision makers. In the second stage additional information are needed to reveal the decision maker’s real preferences. Interactive questioning procedures are recommended to reach that goal.

A válság mint negatív információ és bizonytalansági tényező. A válság hatása az egy részvényre jutó nyereség-előrejelzésekre (The financial crisis as negative information and a factor of uncertainty. Analysing the EPS forecasting error in Hungary and Austria)

A szerző a 2008-ban kezdődött gazdasági világválság hatását vizsgálja az egy részvényre jutó nyereség előrejelzésének hibájára. Számos publikáció bizonyította, hogy az elemzők a tényértékeknél szisztematikusan kedvezőbb tervértéket adnak meg az egy részvényre jutó előrejelzéseikben. Más vizsgálatok azt igazolták, hogy az egy részvényre jutó előrejelzési hiba bizonytalan környezetben növekszik, míg arra is számos bizonyítékot lehet találni, hogy a negatív hírek hatását az elemzők alulsúlyozzák. A gazdasági világválság miatt az elemzőknek számtalan negatív hírt kellett figyelembe venniük az előrejelzések készítésekor, továbbá a válság az egész gazdaságban jelentősen növelte a bizonytalanságot. A szerző azt vizsgálja, hogy miként hatott a gazdasági világválság az egy részvényre jutó nyereség- előrejelzés hibájára, megkülönböztetve azt az időszakot, amíg a válság negatív hír volt, attól, amikor már hatásaként jelentősen megnőtt a bizonytalanság. _____ The author investigated the impact of the financial crisis that started in 2008 on the forecasting error for earnings per share. There is plentiful evidence from the 1980s that analysts give systematically more favourable values in their earnings per share (EPS) forecasts than reality, i.e. they are generally optimistic. Other investigations have supported the idea that the EPS forecasting error is greater under uncertain environmental circumstances, while other researchers prove that the analysts under-react to the negative information in their forecasts. The financial crisis brought a myriad of negative information for analysts to consider in such forecasts, while also increasing the level of uncertainty for the entire economy. The article investigates the impact of the financial crisis on the EPS forecasting error, distinguishing the period when the crisis gave merely negative information, from the one when its effect of uncertainty was significantly increased over the entire economy.

Estimation of global systematic risk for securities listed in multiple markets

The market model is the most frequently estimated model in financial economics and has proven extremely useful in the estimation of systematic risk. In this era of rapid globalization of financial markets there has been a substantial increase in cross listings of stocks in foreign and regional capital markets. As many as a third to a half of the stocks in some major exchanges are foreign listed. The multiple listings of stocks has major implications for the estimation of systematic risk. The traditiona1 method of estimating the market model by using data from only one market will lead to misleading estimates of beta. This study demonstrates that the estimator for systematic risk and the methodology itself changes when stocks are listed in multiple markets. General expressions are developed to obtain the estimator of global beta under a variety of assumptions about the error terms of the market models for different capital markets. The assumptions pertain both to the volatilities of the abnormal returns in each market, and to the relationship between the markets. ^ Explicit expressions are derived for the estimation of global systematic risk beta when the returns are homoscedastic and also under different heteroscedastic conditions both within and/or between markets. These results for the estimation of global beta are further extended when return generating process follows an autoregressive scheme.^

Methodology to create cost estimation models for engineer-to-order operations

This research addresses the problem of cost estimation for product development in engineer-to-order (ETO) operations. An ETO operation starts the product development process with a product specification and ends with delivery of a rather complicated, highly customized product. ETO operations are practiced in various industries such as engineering tooling, factory plants, industrial boilers, pressure vessels, shipbuilding, bridges and buildings. ETO views each product as a delivery item in an industrial project and needs to make an accurate estimation of its development cost at the bidding and/or planning stage before any design or manufacturing activity starts. ^ Many ETO practitioners rely on an ad hoc approach to cost estimation, with use of past projects as reference, adapting them to the new requirements. This process is often carried out on a case-by-case basis and in a non-procedural fashion, thus limiting its applicability to other industry domains and transferability to other estimators. In addition to being time consuming, this approach usually does not lead to an accurate cost estimate, which varies from 30% to 50%. ^ This research proposes a generic cost modeling methodology for application in ETO operations across various industry domains. Using the proposed methodology, a cost estimator will be able to develop a cost estimation model for use in a chosen ETO industry in a more expeditious, systematic and accurate manner. ^ The development of the proposed methodology was carried out by following the meta-methodology as outlined by Thomann. Deploying the methodology, cost estimation models were created in two industry domains (building construction and the steel milling equipment manufacturing). The models are then applied to real cases; the cost estimates are significantly more accurate than the actual estimates, with mean absolute error rate of 17.3%. ^ This research fills an important need of quick and accurate cost estimation across various ETO industries. It differs from existing approaches to the problem in that a methodology is developed for use to quickly customize a cost estimation model for a chosen application domain. In addition to more accurate estimation, the major contributions are in its transferability to other users and applicability to different ETO operations. ^

Mitigating congestion by integrating time forecasting and realtime information aggregation in cellular networks

An iterative travel time forecasting scheme, named the Advanced Multilane Prediction based Real-time Fastest Path (AMPRFP) algorithm, is presented in this dissertation. This scheme is derived from the conventional kernel estimator based prediction model by the association of real-time nonlinear impacts that caused by neighboring arcs’ traffic patterns with the historical traffic behaviors. The AMPRFP algorithm is evaluated by prediction of the travel time of congested arcs in the urban area of Jacksonville City. Experiment results illustrate that the proposed scheme is able to significantly reduce both the relative mean error (RME) and the root-mean-squared error (RMSE) of the predicted travel time. To obtain high quality real-time traffic information, which is essential to the performance of the AMPRFP algorithm, a data clean scheme enhanced empirical learning (DCSEEL) algorithm is also introduced. This novel method investigates the correlation between distance and direction in the geometrical map, which is not considered in existing fingerprint localization methods. Specifically, empirical learning methods are applied to minimize the error that exists in the estimated distance. A direction filter is developed to clean joints that have negative influence to the localization accuracy. Synthetic experiments in urban, suburban and rural environments are designed to evaluate the performance of DCSEEL algorithm in determining the cellular probe’s position. The results show that the cellular probe’s localization accuracy can be notably improved by the DCSEEL algorithm. Additionally, a new fast correlation technique for overcoming the time efficiency problem of the existing correlation algorithm based floating car data (FCD) technique is developed. The matching process is transformed into a 1-dimensional (1-D) curve matching problem and the Fast Normalized Cross-Correlation (FNCC) algorithm is introduced to supersede the Pearson product Moment Correlation Co-efficient (PMCC) algorithm in order to achieve the real-time requirement of the FCD method. The fast correlation technique shows a significant improvement in reducing the computational cost without affecting the accuracy of the matching process.

Effects of Dehydration on Balance as Measured by the Balance Error Scoring System

The purpose of this study was to identify the effects of active dehydration on balance in euthermic individuals employing the Balance Error Scoring System (BESS). The results indicate that dehydration significantly negatively affects balance.

Pairing Repeated Reading and Systematic Error Correction: Impact on Fluency of 18 Year Old Students on a Small Caribbean Island

This study investigates the impact of a combined treatment of Systematic Error Correction and Repeated Reading on reading rate and errors for 18 year olds with undiagnosed reading difficulties on a Caribbean Island. In addition to direct daily measures of reading accuracy, the Reading Self Perception Scale was administered to determine whether the intervention was associated with changes in the way the student perceives himself as a reader.

Effects of worked examples and algebra problem -solving skill on error and cognitive load

This study determined the levels of algebra problem solving skill at which worked examples promoted learning of further problem solving skill and reduction of cognitive load in college developmental algebra students. Problem solving skill was objectively measured as error production; cognitive load was subjectively measured as perceived mental effort. ^ Sixty-three Ss were pretested, received homework of worked examples or mass problem solving, and posttested. Univarate ANCOVA (covariate = previous grade) were performed on the practice and posttest data. The factors used in the analysis were practice strategy (worked examples vs. mass problem solving) and algebra problem solving skill (low vs. moderate vs. high). Students in the practice phase who studied worked examples exhibited (a) fewer errors and reduced cognitive load, at moderate skill; (b) neither fewer errors nor reduced cognitive load, at low skill; and (c) only reduced cognitive load, at high skill. In the posttest, only cognitive load was reduced. ^ The results suggested that worked examples be emphasized for developmental students with moderate problem solving skill. Areas for further research were discussed. ^

Analysis of Students’ Misconceptions and Error Patterns in Mathematics: The Case of Fractions

This study analyzed three fifth grade students’ misconceptions and error patterns when working with equivalence, addition and subtraction of fractions. The findings revealed that students used both conceptual and procedural knowledge to solve the problems. They used pictures, gave examples, and made connections to other mathematical concepts and to daily life topics. Error patterns found include using addition and subtraction of numerators and denominators, and finding the greatest common factor.

Comparison of Some Improved Estimators for Linear Regression Model under Different Conditions

Multiple linear regression model plays a key role in statistical inference and it has extensive applications in business, environmental, physical and social sciences. Multicollinearity has been a considerable problem in multiple regression analysis. When the regressor variables are multicollinear, it becomes difficult to make precise statistical inferences about the regression coefficients. There are some statistical methods that can be used, which are discussed in this thesis are ridge regression, Liu, two parameter biased and LASSO estimators. Firstly, an analytical comparison on the basis of risk was made among ridge, Liu and LASSO estimators under orthonormal regression model. I found that LASSO dominates least squares, ridge and Liu estimators over a significant portion of the parameter space for large dimension. Secondly, a simulation study was conducted to compare performance of ridge, Liu and two parameter biased estimator by their mean squared error criterion. I found that two parameter biased estimator performs better than its corresponding ridge regression estimator. Overall, Liu estimator performs better than both ridge and two parameter biased estimator.