A Comparison of Anchor-Item Designs for the Concurrent Calibration of Large Banks of Likert-Type Items

Current interest in measuring quality of life is generating interest in the construction of computerized adaptive tests (CATs) with Likert-type items. Calibration of an item bank for use in CAT requires collecting responses to a large number of candidate items. However, the number is usually too large to administer to each subject in the calibration sample. The concurrent anchor-item design solves this problem by splitting the items into separate subtests, with some common items across subtests; then administering each subtest to a different sample; and finally running estimation algorithms once on the aggregated data array, from which a substantial number of responses are then missing. Although the use of anchor-item designs is widespread, the consequences of several configuration decisions on the accuracy of parameter estimates have never been studied in the polytomous case. The present study addresses this question by simulation, comparing the outcomes of several alternatives on the configuration of the anchor-item design. The factors defining variants of the anchor-item design are (a) subtest size, (b) balance of common and unique items per subtest, (c) characteristics of the common items, and (d) criteria for the distribution of unique items across subtests. The results of this study indicate that maximizing accuracy in item parameter recovery requires subtests of the largest possible number of items and the smallest possible number of common items; the characteristics of the common items and the criterion for distribution of unique items do not affect accuracy.

Cervical cancer precursors and hormonal contraceptive use in HIV-positive women: application of a causal model and semi-parametric estimation methods.

OBJECTIVE: To demonstrate the application of causal inference methods to observational data in the obstetrics and gynecology field, particularly causal modeling and semi-parametric estimation. BACKGROUND: Human immunodeficiency virus (HIV)-positive women are at increased risk for cervical cancer and its treatable precursors. Determining whether potential risk factors such as hormonal contraception are true causes is critical for informing public health strategies as longevity increases among HIV-positive women in developing countries. METHODS: We developed a causal model of the factors related to combined oral contraceptive (COC) use and cervical intraepithelial neoplasia 2 or greater (CIN2+) and modified the model to fit the observed data, drawn from women in a cervical cancer screening program at HIV clinics in Kenya. Assumptions required for substantiation of a causal relationship were assessed. We estimated the population-level association using semi-parametric methods: g-computation, inverse probability of treatment weighting, and targeted maximum likelihood estimation. RESULTS: We identified 2 plausible causal paths from COC use to CIN2+: via HPV infection and via increased disease progression. Study data enabled estimation of the latter only with strong assumptions of no unmeasured confounding. Of 2,519 women under 50 screened per protocol, 219 (8.7%) were diagnosed with CIN2+. Marginal modeling suggested a 2.9% (95% confidence interval 0.1%, 6.9%) increase in prevalence of CIN2+ if all women under 50 were exposed to COC; the significance of this association was sensitive to method of estimation and exposure misclassification. CONCLUSION: Use of causal modeling enabled clear representation of the causal relationship of interest and the assumptions required to estimate that relationship from the observed data. Semi-parametric estimation methods provided flexibility and reduced reliance on correct model form. Although selected results suggest an increased prevalence of CIN2+ associated with COC, evidence is insufficient to conclude causality. Priority areas for future studies to better satisfy causal criteria are identified.

A review of the accuracy and utility of motion sensors to measure physical activity of frail older hospitalised patients.

The purpose of this review was to examine the utility and accuracy of commercially available motion sensors to measure step-count and time spent upright in frail older hospitalized patients. A database search (CINAHL and PubMed, 2004–2014) and a further hand search of papers’ references yielded 24 validation studies meeting the inclusion criteria. Fifteen motion sensors (eight pedometers, six accelerometers, and one sensor systems) have been tested in older adults. Only three have been tested in hospital patients, two of which detected postures and postural changes accurately, but none estimated step-count accurately. Only one motion sensor remained accurate at speeds typical of frail older hospitalized patients, but it has yet to be tested in this cohort. Time spent upright can be accurately measured in the hospital, but further validation studies are required to determine which, if any, motion sensor can accurately measure step-count.

Eyewitness Memory: Balancing the Accuracy, Precision, and Quantity of Information through Metacognitive Monitoring and Control

Historically, memory has been evaluated by examining how much is remembered, however a more recent conception of memory focuses on the accuracy of memories. When using this accuracy-oriented conception of memory, unlike with the quantity-oriented approach, memory does not always deteriorate over time. A possible explanation for this seemingly surprising finding lies in the metacognitive processes of monitoring and control. Use of these processes allows people to withhold responses of which they are unsure, or to adjust the precision of responses to a level that is broad enough to be correct. The ability to accurately report memories has implications for investigators who interview witnesses to crimes, and those who evaluate witness testimony. This research examined the amount of information provided, accuracy, and precision of responses provided during immediate and delayed interviews about a videotaped mock crime. The interview format was manipulated such that a single free narrative response was elicited, or a series of either yes/no or cued questions were asked. Instructions provided by the interviewer indicated to the participants that they should either stress being informative, or being accurate. The interviews were then transcribed and scored. Results indicate that accuracy rates remained stable and high after a one week delay. Compared to those interviewed immediately, after a delay participants provided less information and responses that were less precise. Participants in the free narrative condition were the most accurate. Participants in the cued questions condition provided the most precise responses. Participants in the yes/no questions condition were most likely to say “I don’t know”. The results indicate that people are able to monitor their memories and modify their reports to maintain high accuracy. When control over precision was not possible, such as in the yes/no condition, people said “I don’t know” to maintain accuracy. However when withholding responses and adjusting precision were both possible, people utilized both methods. It seems that concerns that memories reported after a long retention interval might be inaccurate are unfounded.

Estimate of the (R)USLE rainfall erosivity factor from monthly precipitation data in mainland Spain

The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (R-factor) of the (R)USLE model in areas without good temporal data coverage. In mainland Spain, the Nature Conservation Institute (ICONA) determined the R-factor at few selected pluviographs, so simple estimates of the R-factor are definitely of great interest. The objectives of this study were: (1) to identify a readily available estimate of the R-factor for mainland Spain; (2) to discuss the applicability of a single (global) estimate based on analysis of regional results; (3) to evaluate the effect of record length on estimate precision and accuracy; and (4) to validate an available regression model developed by ICONA. Four estimators based on monthly precipitation were computed at 74 rainfall stations throughout mainland Spain. The regression analysis conducted at a global level clearly showed that modified Fournier index (MFI) ranked first among all assessed indexes. Applicability of this preliminary global model across mainland Spain was evaluated by analyzing regression results obtained at a regional level. It was found that three contiguous regions of eastern Spain (Catalonia, Valencian Community and Murcia) could have a different rainfall erosivity pattern, so a new regression analysis was conducted by dividing mainland Spain into two areas: Eastern Spain and plateau-lowland area. A comparative analysis concluded that the bi-areal regression model based on MFI for a 10-year record length provided a simple, precise and accurate estimate of the R-factor in mainland Spain. Finally, validation of the regression model proposed by ICONA showed that R-ICONA index overpredicted the R-factor by approximately 19%.

Feature-based camera pose estimation

The estimating of the relative orientation and position of a camera is one of the integral topics in the field of computer vision. The accuracy of a certain Finnish technology company’s traffic sign inventory and localization process can be improved by utilizing the aforementioned concept. The company’s localization process uses video data produced by a vehicle installed camera. The accuracy of estimated traffic sign locations depends on the relative orientation between the camera and the vehicle. This thesis proposes a computer vision based software solution which can estimate a camera’s orientation relative to the movement direction of the vehicle by utilizing video data. The task was solved by using feature-based methods and open source software. When using simulated data sets, the camera orientation estimates had an absolute error of 0.31 degrees on average. The software solution can be integrated to be a part of the traffic sign localization pipeline of the company in question.

Rational Function Interpolation of Electromagnetic Transfer Functions of High-Speed Interconnect Systems from Discrete Time-Domain and Frequency-Domain Data

We present new methodologies to generate rational function approximations of broadband electromagnetic responses of linear and passive networks of high-speed interconnects, and to construct SPICE-compatible, equivalent circuit representations of the generated rational functions. These new methodologies are driven by the desire to improve the computational efficiency of the rational function fitting process, and to ensure enhanced accuracy of the generated rational function interpolation and its equivalent circuit representation. Toward this goal, we propose two new methodologies for rational function approximation of high-speed interconnect network responses. The first one relies on the use of both time-domain and frequency-domain data, obtained either through measurement or numerical simulation, to generate a rational function representation that extrapolates the input, early-time transient response data to late-time response while at the same time providing a means to both interpolate and extrapolate the used frequency-domain data. The aforementioned hybrid methodology can be considered as a generalization of the frequency-domain rational function fitting utilizing frequency-domain response data only, and the time-domain rational function fitting utilizing transient response data only. In this context, a guideline is proposed for estimating the order of the rational function approximation from transient data. The availability of such an estimate expedites the time-domain rational function fitting process. The second approach relies on the extraction of the delay associated with causal electromagnetic responses of interconnect systems to provide for a more stable rational function process utilizing a lower-order rational function interpolation. A distinctive feature of the proposed methodology is its utilization of scattering parameters. For both methodologies, the approach of fitting the electromagnetic network matrix one element at a time is applied. It is shown that, with regard to the computational cost of the rational function fitting process, such an element-by-element rational function fitting is more advantageous than full matrix fitting for systems with a large number of ports. Despite the disadvantage that different sets of poles are used in the rational function of different elements in the network matrix, such an approach provides for improved accuracy in the fitting of network matrices of systems characterized by both strongly coupled and weakly coupled ports. Finally, in order to provide a means for enforcing passivity in the adopted element-by-element rational function fitting approach, the methodology for passivity enforcement via quadratic programming is modified appropriately for this purpose and demonstrated in the context of element-by-element rational function fitting of the admittance matrix of an electromagnetic multiport.

Validation of single photon absorptiometry for on-farm measurement of density and mineral content of tail bone in cattle

A validation study examined the accuracy of a purpose-built single photon absorptiometry (SPA) instrument for making on-farm in vivo measurements of bone mineral density (BMD) in tail bones of cattle. In vivo measurements were made at the proximal end of the ninth coccygeal vertebra (Cy9) in steers of two age groups (each n = 10) in adequate or low phosphorus status. The tails of the steers were then resected and the BMD of the Cy9 bone was measured in the laboratory with SPA on the resected tails and then with established laboratory procedures on defleshed bone. Specific gravity and ash density were measured on the isolated Cy9 vertebrae and on 5-mm2 dorso-ventral cores of bone cut from each defleshed Cy9. Calculated BMD determined by SPA required a measure of tail bone thickness and this was estimated as a fraction of total tail thickness. Actual tail bone thickness was also measured on the isolated Cy9 vertebrae. The accuracy of measurement of BMD by SPA was evaluated by comparison with the ash density of the bone cores measured in the laboratory. In vivo SPA measurements of BMD were closely correlated with laboratory measurements of core ash density (r = 0.92). Ash density and specific gravity of cores, and all SPA measures of BMD, were affected by phosphorus status of the steers, but the effect of steer age was only significant (P < 0.05) for steers in adequate phosphorus status. The accuracy of SPA to determine BMD of tail bone may be improved by reducing error associated with in vivo estimation of tail bone thickness, and also by adjusting for displacement of soft tissue by bone mineral. In conclusion a purpose-built SPA instrument could be used to make on-farm sequential non-invasive in vivo measurements of the BMD of tailbone in cattle with accuracy acceptable for many animal studies.

Thermal Tracking and Estimation for Microprocessors

Due to increasing integration density and operating frequency of today's high performance processors, the temperature of a typical chip can easily exceed 100 degrees Celsius. However, the runtime thermal state of a chip is very hard to predict and manage due to the random nature in computing workloads, as well as the process, voltage and ambient temperature variability (together called PVT variability). The uneven nature (both in time and space) of the heat dissipation of the chip could lead to severe reliability issues and error-prone chip behavior (e.g. timing errors). Many dynamic power/thermal management techniques have been proposed to address this issue such as dynamic voltage and frequency scaling (DVFS), clock gating and etc. However, most of such techniques require accurate knowledge of the runtime thermal state of the chip to make efficient and effective control decisions. In this work we address the problem of tracking and managing the temperature of microprocessors which include the following sub-problems: (1) how to design an efficient sensor-based thermal tracking system on a given design that could provide accurate real-time temperature feedback; (2) what statistical techniques could be used to estimate the full-chip thermal profile based on very limited (and possibly noise-corrupted) sensor observations; (3) how do we adapt to changes in the underlying system's behavior, since such changes could impact the accuracy of our thermal estimation. The thermal tracking methodology proposed in this work is enabled by on-chip sensors which are already implemented in many modern processors. We first investigate the underlying relationship between heat distribution and power consumption, then we introduce an accurate thermal model for the chip system. Based on this model, we characterize the temperature correlation that exists among different chip modules and explore statistical approaches (such as those based on Kalman filter) that could utilize such correlation to estimate the accurate chip-level thermal profiles in real time. Such estimation is performed based on limited sensor information because sensors are usually resource constrained and noise-corrupted. We also took a further step to extend the standard Kalman filter approach to account for (1) nonlinear effects such as leakage-temperature interdependency and (2) varying statistical characteristics in the underlying system model. The proposed thermal tracking infrastructure and estimation algorithms could consistently generate accurate thermal estimates even when the system is switching among workloads that have very distinct characteristics. Through experiments, our approaches have demonstrated promising results with much higher accuracy compared to existing approaches. Such results can be used to ensure thermal reliability and improve the effectiveness of dynamic thermal management techniques.

Efficient split eld FDTD analysis of third-order nonlinear materials in two-dimensionally periodic media

In this work the split-field finite-difference time-domain method (SF-FDTD) has been extended for the analysis of two-dimensionally periodic structures with third-order nonlinear media. The accuracy of the method is verified by comparisons with the nonlinear Fourier Modal Method (FMM). Once the formalism has been validated, examples of one- and two-dimensional nonlinear gratings are analysed. Regarding the 2D case, the shifting in resonant waveguides is corroborated. Here, not only the scalar Kerr effect is considered, the tensorial nature of the third-order nonlinear susceptibility is also included. The consideration of nonlinear materials in this kind of devices permits to design tunable devices such as variable band filters. However, the third-order nonlinear susceptibility is usually small and high intensities are needed in order to trigger the nonlinear effect. Here, a one-dimensional CBG is analysed in both linear and nonlinear regime and the shifting of the resonance peaks in both TE and TM are achieved numerically. The application of a numerical method based on the finite- difference time-domain method permits to analyse this issue from the time domain, thus bistability curves are also computed by means of the numerical method. These curves show how the nonlinear effect modifies the properties of the structure as a function of variable input pump field. When taking the nonlinear behaviour into account, the estimation of the electric field components becomes more challenging. In this paper, we present a set of acceleration strategies based on parallel software and hardware solutions.

Lineup identification accuracy: the effects of alcohol, target presence, confidence ratings, and response time

Despite the intoxication of many eyewitnesses at crime scenes, only four published studies to date have investigated the effects of alcohol intoxication on eyewitness identification performance. While one found intoxication significantly increased false identification rates from target absent showups, three found no such effect using the more traditional lineup procedure. The present study sought to further explore the effects of alcohol intoxication on identification performance and examine whether accurate decisions from intoxicated witnesses could be postdicted by confidence and response times. One hundred and twenty participants engaged in a study examining the effects of intoxication (control, placebo, and mild intoxication) and target presence on identification performance. Participants viewed a simultaneous lineup one week after watching a mock crime video of a man attempting to steal cars. Ethanol intoxication (0.6 ml/kg) was found to make no significant difference to identification accuracy and such identifications from intoxicated individuals were made no less confidently or slowly than those from sober witnesses. These results are discussed with respect to the previous research examining intoxicated witness identification accuracy and the misconceptions the criminal justice system holds about the accuracy of such witnesses.

Quasi-a priori truncation error estimation in the DGSEM

In this paper we show how to accurately perform a quasi-a priori estimation of the truncation error of steady-state solutions computed by a discontinuous Galerkin spectral element method. We estimate the spatial truncation error using the ?-estimation procedure. While most works in the literature rely on fully time-converged solutions on grids with different spacing to perform the estimation, we use non time-converged solutions on one grid with different polynomial orders. The quasi-a priori approach estimates the error while the residual of the time-iterative method is not negligible. Furthermore, the method permits one to decouple the surface and the volume contributions of the truncation error, and provides information about the anisotropy of the solution as well as its rate of convergence in polynomial order. First, we focus on the analysis of one dimensional scalar conservation laws to examine the accuracy of the estimate. Then, we extend the analysis to two dimensional problems. We demonstrate that this quasi-a priori approach yields a spectrally accurate estimate of the truncation error.

Improvement of accuracy in a free bending test for material characterization

The effect of secondary (anticlastic) curvature and the stress state on the measurement of material properties in a free bending test is studied in order to improve the accuracy of the test. Experiments and numerical analysis are conducted on a medium strength 304L stainless steel and high strength dual-phase steels, DP780 and DP1000. The dependence of the secondary curvature on sample geometry is analysed and correction factors are introduced to improve the accuracy of the calculation of material properties when using plane strain or uniaxial stress two-dimensional assumptions. A free bending test procedure is proposed to characterize material behaviour close to yield. This will allow the quick and simple analysis of material properties for bending-dominated forming processes such as roll forming.

The creation and evaluation of novel canine training aids for cocaine using molecularly encapsulated sol-gel polymers and an investigation of canine field accuracy

Biological detectors, such as canines, are valuable tools used for the rapid identification of illicit materials. However, recent increased scrutiny over the reliability, field accuracy, and the capabilities of each detection canine is currently being evaluated in the legal system. For example, the Supreme Court case, State of Florida v. Harris, discussed the need for continuous monitoring of canine abilities, thresholds, and search capabilities. As a result, the fallibility of canines for detection was brought to light, as well as a need for further research and understanding of canine detection. This study is two-fold, as it looks to not only create new training aids for canines that can be manipulated for dissipation control, but also investigates canine field accuracy to objects with similar odors to illicit materials. ^ It was the goal of this research to improve upon current canine training aid mimics. Sol-gel polymer training aids, imprinted with the active odor of cocaine, were developed. This novel training aid improved upon the longevity of currently existing training aids, while also provided a way to manipulate the polymer network to alter the dissipation rate of the imprinted active odors. The manipulation of the polymer network could allow handlers to control the abundance of odors presented to their canines, familiarizing themselves to their canine’s capabilities and thresholds, thereby increasing the canines’ strength in court.^ The field accuracy of detection canines was recently called into question during the Supreme Court case, State of Florida v. Jardines, where it was argued that if cocaine’s active odor, methyl benzoate, was found to be produced by the popular landscaping flower, snapdragons, canines will false alert to said flowers. Therefore, snapdragon flowers were grown and tested both in the laboratory and in the field to determine the odors produced by snapdragon flowers; the persistence of these odors once flowers have been cut; and whether detection canines will alert to both growing and cut flowers during a blind search scenario. Results revealed that although methyl benzoate is produced by snapdragon flowers, certified narcotics detection canines can distinguish cocaine’s odor profile from that of snapdragon flowers and will not alert.^

Assessment of resting energy expenditure in pediatric mitochondrial diseases with indirect calorimetry

Mitochondrial diseases (MD) are the most frequent inborn errors of metabolism. In affected tissues, MD can alter cellular oxygen consumption rate leading to potential decreases in whole-body resting energy expenditure (REE), but data on pediatric children are absent. We determined, using indirect calorimetry (IC), whole-body oxygen consumption (VO2), carbon dioxide production (VCO2), respiratory quotient (RQ) and REE in pediatric patients with MD and healthy controls. Another goal was to assess the accuracy of available predictive equations for REE estimation in this patient population. IC data were obtained under fasting and resting conditions in 20 MD patients and 27 age and gender-matched healthy peers. We determined the agreement between REE measured with IC and REE estimated with Schofield weight and FAO/WHO/UNU equations. Mean values of VO2, VCO2 (mL·min-1·kg-1) or RQ did not differ significantly between patients and controls (P = 0.085, P = 0.055 and P = 0.626 respectively). Accordingly, no significant differences (P = 0.086) were found for REE (kcal·day-1 kg-1) either. On the other hand, although we found no significant differences between IC-measured REE and Schofield or FAO/WHO/UNU-estimated REE, Bland-Altman analysis revealed wide limits of agreement and there were some important individual differences between IC and equation-derived REE. VO2, VCO2, RQ and REE are not significantly altered in pediatric patients with MD compared with healthy controls. The energy demands of pediatric patients with MD should be determined based on IC data in order to provide the best possible personalized nutritional management for these children.