Static and Dynamic Error Correction of a Computer-Aided Mechanical Navigation Linkage for Arthroscopic Hip Surgery

While beneficially decreasing the necessary incision size, arthroscopic hip surgery increases the surgical complexity due to loss of joint visibility. To ease such difficulty, a computer-aided mechanical navigation system was developed to present the location of the surgical tool relative to the patient¿s hip joint. A preliminary study reduced the position error of the tracking linkage with limited static testing trials. In this study, a correction method, including a rotational correction factor and a length correction function, was developed through more in-depth static testing. The developed correction method was then applied to additional static and dynamic testing trials to evaluate its effectiveness. For static testing, the position error decreased from an average of 0.384 inches to 0.153 inches, with an error reduction of 60.5%. Three parameters utilized to quantify error reduction of dynamic testing did not show consistent results. The vertex coordinates achieved 29.4% of error reduction, yet with large variation in the upper vertex. The triangular area error was reduced by 5.37%, however inconsistent among all five dynamic trials. Error of vertex angles increased, indicating a shape torsion using the developed correction method. While the established correction method effectively and consistently reduced position error in static testing, it did not present consistent results in dynamic trials. More dynamic paramters should be explored to quantify error reduction of dynamic testing, and more in-depth dynamic testing methodology should be conducted to further improve the accuracy of the computer-aided nagivation system.

Choques de oferta e política monetária na economia brasileira: Uma análise do impacto dos preços das commodities na inflação entre 2002 e 2014

Há mais de uma década o controle dos níveis de preço na economia brasileira é realizado dentro do escopo do Regime de Metas de Inflação, que utiliza modelos macroeconômicos como instrumentos para guiar as tomadas de decisões sobre política monetária. Após um período de relativo êxito (2006 - 2009), nos últimos anos apesar dos esforços das autoridades monetárias na aplicação das políticas de contenção da inflação, seguindo os mandamentos do regime de metas, esta tem se mostrado resistente, provocando um debate em torno de fatores que podem estar ocasionando tal comportamento. Na literatura internacional, alguns trabalhos têm creditado aos choques de oferta, especialmente aos desencadeados pela variação dos preços das commodities, uma participação significativa na inflação, principalmente em economias onde os produtos primários figuram como maioria na pauta exportadora. Na literatura nacional, já existem alguns trabalhos que apontam nesta mesma direção. Sendo assim, buscou-se, como objetivo principal para o presente estudo, avaliar como os choques de oferta, mais especificamente os choques originados pelos preços das commodities, têm impactado na inflação brasileira e como e com que eficiência a política monetária do país tem reagido. Para tanto, foi estimado um modelo semiestrutural contendo uma curva de Phillips, uma curva IS e duas versões da Função de Reação do Banco Central, de modo a verificar como as decisões de política monetária são tomadas. O método de estimação empregado foi o de Autorregressão Vetorial com Correção de Erro (VEC) na sua versão estrutural, que permite uma avaliação dinâmica das relações de interdependência entre as variáveis do modelo proposto. Por meio da estimação da curva de Phillips foi possível observar que os choques de oferta, tanto das commodities como da produtividade do trabalho e do câmbio, não impactam a inflação imediatamente, porém sua relevância é crescente ao longo do tempo chegando a prevalecer sobre o efeito autorregressivo (indexação) verificado. Estes choques também se apresentaram importantes para o comportamento da expectativa de inflação, produzindo assim, uma indicação de que seus impactos tendem a se espalhar pelos demais setores da economia. Através dos resultados da curva IS constatou-se a forte inter-relação entre o hiato do produto e a taxa de juros, o que indica que a política monetária, por meio da fixação de tal taxa, influencia fortemente a demanda agregada. Já por meio da estimação da primeira função de reação, foi possível perceber que há uma relação contemporânea relevante entre o desvio da expectativa de inflação em relação à meta e a taxa Selic, ao passo que a relação contemporânea do hiato do produto sobre a taxa Selic se mostrou pequena. Por fim, os resultados obtidos com a segunda função de reação, confirmaram que as autoridades monetárias reagem mais fortemente aos sinais inflacionários da economia do que às movimentações que acontecem na atividade econômica e mostraram que uma elevação nos preços das commodities, em si, não provoca diretamente um aumento na taxa básica de juros da economia.

Quantum-error correction on linear-nearest-neighbor qubit arrays

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.

Continuous quantum error correction by cooling

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.

Stabilizer formalism for operator quantum error correction

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.

Operator quantum error correction

This paper is an expanded and more detailed version of the work [1] in which the Operator Quantum Error Correction formalism was introduced. This is a new scheme for the error correction of quantum operations that incorporates the known techniques - i.e. the standard error correction model, the method of decoherence-free subspaces, and the noiseless subsystem method - as special cases, and relies on a generalized mathematical framework for noiseless subsystems that applies to arbitrary quantum operations. We also discuss a number of examples and introduce the notion of unitarily noiseless subsystems.

An econometric analysis of international tourism demand in Hong Kong : a cointegration and error correction approach

The purpose of this study is to develop econometric models to better understand the economic factors affecting inbound tourist flows from each of six origin countries that contribute to Hong Kong’s international tourism demand. To this end, we test alternative cointegration and error correction approaches to examine the economic determinants of tourist flows to Hong Kong, and to produce accurate econometric forecasts of inbound tourism demand. Our empirical findings show that permanent income is the most significant determinant of tourism demand in all models. The variables of own price, weighted substitute prices, trade volume, the share price index (as an indicator of changes in wealth in origin countries), and a dummy variable representing the Beijing incident (1989) are also found to be important determinants for some origin countries. The average long-run income and own price elasticity was measured at 2.66 and – 1.02, respectively. It was hypothesised that permanent income is a better explanatory variable of long-haul tourism demand than current income. A novel approach (grid search process) has been used to empirically derive the weights to be attached to the lagged income variable for estimating permanent income. The results indicate that permanent income, estimated with empirically determined relatively small weighting factors, was capable of producing better results than the current income variable in explaining long-haul tourism demand. This finding suggests that the use of current income in previous empirical tourism demand studies may have produced inaccurate results. The share price index, as a measure of wealth, was also found to be significant in two models. Studies of tourism demand rarely include wealth as an explanatory forecasting long-haul tourism demand. However, finding a satisfactory proxy for wealth common to different countries is problematic. This study indicates with the ECM (Error Correction Models) based on the Engle-Granger (1987) approach produce more accurate forecasts than ECM based on Pesaran and Shin (1998) and Johansen (1988, 1991, 1995) approaches for all of the long-haul markets and Japan. Overall, ECM produce better forecasts than the OLS, ARIMA and NAÏVE models, indicating the superiority of the application of a cointegration approach for tourism demand forecasting. The results show that permanent income is the most important explanatory variable for tourism demand from all countries but there are substantial variations between countries with the long-run elasticity ranging between 1.1 for the U.S. and 5.3 for U.K. Price is the next most important variable with the long-run elasticities ranging between -0.8 for Japan and -1.3 for Germany and short-run elasticities ranging between – 0.14 for Germany and -0.7 for Taiwan. The fastest growing market is Mainland China. The findings have implications for policies and strategies on investment, marketing promotion and pricing.

Pricing-to-market using EGARCH-error correction model

In this paper, the authors use an exponential generalized autoregressive conditional heteroscedastic (EGARCH) error-correction model (ECM), that is, EGARCH-ECM, to estimate the pass-through effects of foreign exchange (FX) rates and producers’ prices for 20 U.K. export sectors. The long-run adjustment of export prices to FX rates and producers’ prices is within the range of -1.02% (for the Textiles sector) and -17.22% (for the Meat sector). The contemporaneous pricing-to-market (PTM) coefficient is within the range of -72.84% (for the Fuels sector) and -8.05% (for the Textiles sector). Short-run FX rate pass-through is not complete even after several months. Rolling EGARCH-ECMs show that the short and long-run effects of FX rate and producers’ prices fluctuate substantially as are asymmetry and volatility estimates before equilibrium is achieved.

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.

Development of error correction techniques for nitrate-N load estimation models

Excess nutrient loads carried by streams and rivers are a great concern for environmental resource managers. In agricultural regions, excess loads are transported downstream to receiving water bodies, potentially causing algal blooms, which could lead to numerous ecological problems. To better understand nutrient load transport, and to develop appropriate water management plans, it is important to have accurate estimates of annual nutrient loads. This study used a Monte Carlo sub-sampling method and error-corrected statistical models to estimate annual nitrate-N loads from two watersheds in central Illinois. The performance of three load estimation methods (the seven-parameter log-linear model, the ratio estimator, and the flow-weighted averaging estimator) applied at one-, two-, four-, six-, and eight-week sampling frequencies were compared. Five error correction techniques; the existing composite method, and four new error correction techniques developed in this study; were applied to each combination of sampling frequency and load estimation method. On average, the most accurate error reduction technique, (proportional rectangular) resulted in 15% and 30% more accurate load estimates when compared to the most accurate uncorrected load estimation method (ratio estimator) for the two watersheds. Using error correction methods, it is possible to design more cost-effective monitoring plans by achieving the same load estimation accuracy with fewer observations. Finally, the optimum combinations of monitoring threshold and sampling frequency that minimizes the number of samples required to achieve specified levels of accuracy in load estimation were determined. For one- to three-weeks sampling frequencies, combined threshold/fixed-interval monitoring approaches produced the best outcomes, while fixed-interval-only approaches produced the most accurate results for four- to eight-weeks sampling frequencies.

Quantum error correction with the IBM quantum experience

Mentre si svolgono operazioni su dei qubit, possono avvenire vari errori, modificando così l’informazione da essi contenuta. La Quantum Error Correction costruisce algoritmi che permettono di tollerare questi errori e proteggere l’informazione che si sta elaborando. Questa tesi si focalizza sui codici a 3 qubit, che possono correggere un errore di tipo bit-flip o un errore di tipo phase-flip. Più precisamente, all’interno di questi algoritmi, l’attenzione è posta sulla procedura di encoding, che punta a proteggere meglio dagli errori l’informazione contenuta da un qubit, e la syndrome measurement, che specifica su quale qubit è avvenuto un errore senza alterare lo stato del sistema. Inoltre, sfruttando la procedura della syndrome measurement, è stata stimata la probabilità di errore di tipo bit-flip e phase-flip su un qubit attraverso l’utilizzo della IBM quantum experience.

Fertility and female work force participation in Bangladesh: Causality and cointegration

This paper examines the causal links between fertility and female labor force participation in Bangladesh over the period 1974-2000 by specifying a bivariate and several trivariate models in a vector error correction framework. The three trivariate models alternatively include average age at first marriage for females, per capita GDP and infant mortality rate, which control for the effects of other socio-economic factors on fertility and female labor force participation. All the specified models indicate an inverse long-run relationship between fertility and female labor force participation. While the bivariate model also indicates bidirectional causality, the multivariate models confirm only a unidirectional causality – from labor force participation to fertility. Further, per capita GDP and infant mortality rate appear to Granger-cause both fertility and female labor force participation.

Evaluation of dynamic pass-through of carbon prices into electricity prices – a cointegrated VECM analysis

This paper addresses the impact of the CO2 opportunity cost on the wholesale electricity price in the context of the Iberian electricity market (MIBEL), namely on the Portuguese system, for the period corresponding to the Phase II of the European Union Emission Trading Scheme (EU ETS). In the econometric analysis a vector error correction model (VECM) is specified to estimate both long–run equilibrium relations and short–run interactions between the electricity price and the fuel (natural gas and coal) and carbon prices. The model is estimated using daily spot market prices and the four commodities prices are jointly modelled as endogenous variables. Moreover, a set of exogenous variables is incorporated in order to account for the electricity demand conditions (temperature) and the electricity generation mix (quantity of electricity traded according the technology used). The outcomes for the Portuguese electricity system suggest that the dynamic pass–through of carbon prices into electricity prices is strongly significant and a long–run elasticity was estimated (equilibrium relation) that is aligned with studies that have been conducted for other markets.