973 resultados para cost prediction
Resumo:
We predict here from first-principle calculations that finite-length (n,0) single walled carbon nanotubes (SWCNTs) with H-termination at the open ends displaying antiferromagnetic coupling when n is greater than 6. An opposite local gating effect of the spin states, i.e., half metallicity, is found under the influence of an external electric field along the direction of tube axis. Remarkably, boron doping of unpassivated SWCNTs at both zigzag edges is found to favor a ferromagnetic ground state, with the B-doped tubes displaying half-metallic behavior even in the absence of an electric field. Aside of the intrinsic interest of these results, an important avenue for development of CNT-based spintronic is suggested.
Resumo:
Recent literature has focused on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility models can largely improve VaR prediction, especially for emerging markets where jumps play a stronger role than those in developed markets.
Resumo:
Mortality and cost outcomes of elderly intensive care unit (ICU) trauma patients were characterised in a retrospective cohort study from an Australian tertiary ICU. Trauma patients admitted between January 2000 and December 2005 were grouped into three major age categories: aged ≥65 years admitted into ICU (n=272); aged ≥65 years admitted into general ward (n=610) and aged <65 years admitted into ICU (n=1617). Hospital mortality predictors were characterised as odds ratios (OR) using logistic regression. The impact of predictor variables on (log) total hospital-stay costs was determined using least squares regression. An alternate treatment-effects regression model estimated the mortality cost-effect as an endogenous variable. Mortality predictors (P ≤0.0001, comparator: ICU ≥65 years, ventilated) were: ICU <65 not-ventilated (OR 0.014); ICU <65 ventilated (OR 0.090); ICU age ≥65 not-ventilated (OR 0.061) and ward ≥65 (OR 0.086); increasing injury severity score and increased Charlson comorbidity index of 1 and 2, compared with zero (OR 2.21 [1.40 to 3.48] and OR 2.57 [1.45 to 4.55]). The raw mean daily ICU and hospital costs in A$ 2005 (US$) for age <65 and ≥65 to ICU, and ≥65 to the ward were; for year 2000: ICU, $2717 (1462) and $2777 (1494); hospital, $1837 (988) and $1590 (855); ward $933 (502); for year 2005: ICU, $3202 (2393) and $3086 (2307); hospital, $1938 (1449) and $1914 (1431); ward $1180 (882). Cost increments were predicted by age ≥65 and ICU admission, increasing injury severity score, mechanical ventilation, Charlson comorbidity index increments and hospital survival. Mortalitycost-effect was estimated at -63% by least squares regression and -82% by treatment-effects regression model. Patient demographic factors, injury severity and its consequences predict both cost and survival in trauma. The cost mortality effect was biased upwards by conventional least squares regression estimation.
Resumo:
The ability to steer business operations in alignment with the true origins of costs, and to be informed about this on a real-time basis, allows businesses to increase profitability. In most organisations however, high-level cost-based managerial decisions are still being made separately from process-related operational decisions. In this paper, we describe how process-related decisions at the operational level can be guided by cost considerations and how these cost-informed decision rules can be supported by a workflow management system. The paper presents the conceptual framework together with data requirements and technical challenges that need to be addressed to realise cost-informed workflow execution. The feasibility of our approach is demonstrated using a prototype implementation in the YAWL workflow environment.
Resumo:
The Action Lecture program is an innovative teaching method run in some nursery and primary schools in Paris and designed to improve pupils’ literacy. We report the results of an evaluation of this program. We describe the experimental protocol that was built to estimate the program’s impact on several types of indicators. Data were processed following a Differences-in-Differences (DID) method. Then we use the estimation of the impact on academic achievement to conduct a cost-effectiveness analysis and take a reduction of the class size program as a benchmark. The results are positive for the Action Lecture program.
Resumo:
Background Falls are one of the most frequently occurring adverse events that impact upon the recovery of older hospital inpatients. Falls can threaten both immediate and longer-term health and independence. There is need to identify cost-effective means for preventing falls in hospitals. Hospital-based falls prevention interventions tested in randomized trials have not yet been subjected to economic evaluation. Methods Incremental cost-effectiveness analysis was undertaken from the health service provider perspective, over the period of hospitalization (time horizon) using the Australian Dollar (A$) at 2008 values. Analyses were based on data from a randomized trial among n = 1,206 acute and rehabilitation inpatients. Decision tree modeling with three-way sensitivity analyses were conducted using burden of disease estimates developed from trial data and previous research. The intervention was a multimedia patient education program provided with trained health professional follow-up shown to reduce falls among cognitively intact hospital patients. Results The short-term cost to a health service of one cognitively intact patient being a faller could be as high as A$14,591 (2008). The education program cost A$526 (2008) to prevent one cognitively intact patient becoming a faller and A$294 (2008) to prevent one fall based on primary trial data. These estimates were unstable due to high variability in the hospital costs accrued by individual patients involved in the trial. There was a 52% probability the complete program was both more effective and less costly (from the health service perspective) than providing usual care alone. Decision tree modeling sensitivity analyses identified that when provided in real life contexts, the program would be both more effective in preventing falls among cognitively intact inpatients and cost saving where the proportion of these patients who would otherwise fall under usual care conditions is at least 4.0%. Conclusions This economic evaluation was designed to assist health care providers decide in what circumstances this intervention should be provided. If the proportion of cognitively intact patients falling on a ward under usual care conditions is 4% or greater, then provision of the complete program in addition to usual care will likely both prevent falls and reduce costs for a health service.
Resumo:
This paper proposes a practical prediction procedure for vertical displacement of a Rotarywing Unmanned Aerial Vehicle (RUAV) landing deck in the presence of stochastic sea state disturbances. A proper time series model tending to capture characteristics of the dynamic relationship between an observer and a landing deck is constructed, with model orders determined by a novel principle based on Bayes Information Criterion (BIC) and coefficients identified using the Forgetting Factor Recursive Least Square (FFRLS) method. In addition, a fast-converging online multi-step predictor is developed, which can be implemented more rapidly than the Auto-Regressive (AR) predictor as it requires less memory allocations when updating coefficients. Simulation results demonstrate that the proposed prediction approach exhibits satisfactory prediction performance, making it suitable for integration into ship-helicopter approach and landing guidance systems in consideration of computational capacity of the flight computer.
Resumo:
In this paper, we present a monocular vision based autonomous navigation system for Micro Aerial Vehicles (MAVs) in GPS-denied environments. The major drawback of monocular systems is that the depth scale of the scene can not be determined without prior knowledge or other sensors. To address this problem, we minimize a cost function consisting of a drift-free altitude measurement and up-to-scale position estimate obtained using the visual sensor. We evaluate the scale estimator, state estimator and controller performance by comparing with ground truth data acquired using a motion capture system. All resources including source code, tutorial documentation and system models are available online.
Resumo:
This paper describes a risk model for estimating the likelihood of collisions at low-exposure railway level crossings, demonstrating the effect that differences in safety integrity can have on the likelihood of a collision. The model facilitates the comparison of safety benefits between level crossings with passive controls (stop or give-way signs) and level crossings that have been hypothetically upgraded with conventional or low-cost warning devices. The scenario presented illustrates how treatment of a cross-section of level crossings with low cost devices can provide a greater safety benefit compared to treatment with conventional warning devices for the same budget.
Resumo:
Genomic DNA obtained from patient whole blood samples is a key element for genomic research. Advantages and disadvantages, in terms of time-efficiency, cost-effectiveness and laboratory requirements, of procedures available to isolate nucleic acids need to be considered before choosing any particular method. These characteristics have not been fully evaluated for some laboratory techniques, such as the salting out method for DNA extraction, which has been excluded from comparison in different studies published to date. We compared three different protocols (a traditional salting out method, a modified salting out method and a commercially available kit method) to determine the most cost-effective and time-efficient method to extract DNA. We extracted genomic DNA from whole blood samples obtained from breast cancer patient volunteers and compared the results of the product obtained in terms of quantity (concentration of DNA extracted and DNA obtained per ml of blood used) and quality (260/280 ratio and polymerase chain reaction product amplification) of the obtained yield. On average, all three methods showed no statistically significant differences between the final result, but when we accounted for time and cost derived for each method, they showed very significant differences. The modified salting out method resulted in a seven- and twofold reduction in cost compared to the commercial kit and traditional salting out method, respectively and reduced time from 3 days to 1 hour compared to the traditional salting out method. This highlights a modified salting out method as a suitable choice to be used in laboratories and research centres, particularly when dealing with a large number of samples.
Resumo:
Background/Aim Hamstring strain injuries (HSIs) have remained the most prevalent injury in the Australian football league (AFL) over the past 21 regular seasons. The impact of HSIs in sport is often expressed as regular season games missed due to injury. However the financial cost of athletes missing games due to injury has not been investigated. The aim of this report is to estimate the financial cost of games missed due to HSIs in the AFL. Method Data was collected using publically available information from the AFL’s injury report and the official AFL annual report for the past 10 competitive AFL seasons. Average athlete salary and injury epidemiology data was used to determine the average yearly financial cost of HSIs for AFL clubs and the average financial cost of a single HSI over this time period. Results Across the observed period, average yearly financial cost of HSIs per club increased by 71% compared to a 43% increase in average yearly athlete salary. Over the same time period the average financial cost of a single HSI increased by 56% from $25,603 in 2003 to $40,021 in 2012, despite little change in HSI rates during the period. Conclusion The observed increased financial cost of HSIs was ultimately explained by the failure of teams to decrease HSI rates, but coupled with increases in athlete salaries over the past 10 season. The information presented in this report will highlight the financial cost of HSIs and other sporting injuries, raising greater awareness and the need for further funding for research into injury prevention strategies to maximise economical return for investment in athletes.
Resumo:
A method for prediction of the radiation pattern of N strongly coupled antennas with mismatched sources is presented. The method facilitates fast and accurate design of compact arrays. The prediction is based on the measured N-port S parameters of the coupled antennas and the N active element patterns measured in a 50 ω environment. By introducing equivalent power sources, the radiation pattern with excitation by sources with arbitrary impedances and various decoupling and matching networks (DMN) can be accurately predicted without the need for additional measurements. Two experiments were carried out for verification: pattern prediction for parasitic antennas with different loads and for antennas with DMN. The difference between measured and predicted patterns was within 1 to 2 dB.
Resumo:
Objectives Early childhood caries is a highly destructive dental disease which is compounded by the need for young children to be treated under general anaesthesia. In Australia, there are long waiting periods for treatment at public hospitals. In this paper, we examined the costs and patient outcomes of a prevention programme for early childhood caries to assess its value for government services. Design Cost-effectiveness analysis using a Markov model. Setting Public dental patients in a low socioeconomic, socially disadvantaged area in the State of Queensland, Australia. Participants Children aged 6 months to 6 years received either a telephone prevention programme or usual care. Primary and secondary outcome measures A mathematical model was used to assess caries incidence and public dental treatment costs for a cohort of children. Healthcare costs, treatment probabilities and caries incidence were modelled from 6 months to 6 years of age based on trial data from mothers and their children who received either a telephone prevention programme or usual care. Sensitivity analyses were used to assess the robustness of the findings to uncertainty in the model estimates. Results By age 6 years, the telephone intervention programme had prevented an estimated 43 carious teeth and saved £69 984 in healthcare costs per 100 children. The results were sensitive to the cost of general anaesthesia (cost-savings range £36 043–£97 298) and the incidence of caries in the prevention group (cost-savings range £59 496–£83 368) and usual care (cost-savings range £46 833–£93 328), but there were cost savings in all scenarios. Conclusions A telephone intervention that aims to prevent early childhood caries is likely to generate considerable and immediate patient benefits and cost savings to the public dental health service in disadvantaged communities.
Resumo:
Travel time prediction has long been the topic of transportation research. But most relevant prediction models in the literature are limited to motorways. Travel time prediction on arterial networks is challenging due to involving traffic signals and significant variability of individual vehicle travel time. The limited availability of traffic data from arterial networks makes travel time prediction even more challenging. Recently, there has been significant interest of exploiting Bluetooth data for travel time estimation. This research analysed the real travel time data collected by the Brisbane City Council using the Bluetooth technology on arterials. Databases, including experienced average daily travel time are created and classified for approximately 8 months. Thereafter, based on data characteristics, Seasonal Auto Regressive Integrated Moving Average (SARIMA) modelling is applied on the database for short-term travel time prediction. The SARMIA model not only takes the previous continuous lags into account, but also uses the values from the same time of previous days for travel time prediction. This is carried out by defining a seasonality coefficient which improves the accuracy of travel time prediction in linear models. The accuracy, robustness and transferability of the model are evaluated through comparing the real and predicted values on three sites within Brisbane network. The results contain the detailed validation for different prediction horizons (5 min to 90 minutes). The model performance is evaluated mainly on congested periods and compared to the naive technique of considering the historical average.