Unreliable Measurements Research Articles

Ring Difference Filter for Fast and Noise Robust Depth from Focus.

Depth from focus (DfF) is a method of estimating the depth of a scene by using information acquired through changes in the focus of a camera. Within the DfF framework of, the focus measure (FM) forms the foundation which determines the accuracy of the output. With the results from the FM, the role of a DfF pipeline is to determine and recalculate unreliable measurements while enhancing those that are reliable. In this paper, we propose a new FM, which we call the "ring difference filter" (RDF), that can more accurately and robustly measure focus. FMs can usually be categorized as confident local methods or noise robust non-local methods. The RDF's unique ring-and-disk structure allows it to have the advantages of both local and non-local FMs. We then describe an efficient pipeline that utilizes the RDF's properties. Part of this pipeline is our proposed RDF-based cost aggregation method, which is able to robustly refine the initial results in the presence of image noise. Our method is able to reproduce results that are on par with or even better than those of state-of-the-art methods, while spending less time in computation.

Relative Afferent Pupillary Defect Screening Through Transfer Learning.

Abnormalities in pupillary light reflex can indicate optic nerve disorders that may lead to permanent visual loss if not diagnosed in an early stage. In this study, we focus on relative afferent pupillary defect (RAPD), which is based on the difference between the reactions of the eyes when they are exposed to light stimuli. Incumbent RAPD assessment methods are based on subjective practices that can lead to unreliable measurements. To eliminate subjectivity and obtain reliable measurements, we introduced an automated framework to detect RAPD. For validation, we conducted a clinical study with lab-on-a-headset, which can perform automated light reflex test. In addition to benchmarking handcrafted algorithms, we proposed a transfer learning-based approach that transformed a deep learning-based generic object recognition algorithm into a pupil detector. Based on the conducted experiments, proposed algorithm RAPDNet can achieve a sensitivity and a specificity of 90.6% over 64 test cases in a balanced set, which corresponds to an AUC of 0.929 in ROC analysis. According to our benchmark with three handcrafted algorithms and nine performance metrics, RAPDNet outperforms all other algorithms in every performance category.

Edge fracture instability in sheared complex fluids: Onset criterion and possible mitigation strategy

We perform a detailed theoretical study of the edge fracture instability, which commonly destabilizes the fluid-air interface during strong shear flows of entangled polymeric fluids, leading to unreliable rheological measurements. By means of direct nonlinear simulations, we map out phase diagrams showing the degree of edge fracture in the plane of the surface tension of the fluid-air interface and the imposed shear rate, within the Giesekus and Johnson–Segalman models, for different values of the nonlinear constitutive parameters that determine the dependencies on the shear rate of the shear and normal stresses. The threshold for the onset of edge fracture is shown to be relatively robust against variations in the wetting angle where the fluid-air interface meets the hard walls of the flow cell, whereas the nonlinear dynamics depend strongly on the wetting angle. We perform a linear stability calculation to derive an exact analytical expression for the onset of edge fracture, expressed in terms of the shear-rate derivative of the second normal stress difference, the shear-rate derivative of the shear stress (sometimes called the tangent viscosity), the jump in the shear stress across the interface between the fluid and the outside air, the surface tension of that interface, and the rheometer gap size. (The shear stress to which we refer is σxy with x^ being the flow direction and y^ being the flow-gradient direction. The interface normal is in the vorticity direction z^.) Full agreement between our analytical calculation and nonlinear simulations is demonstrated. We also elucidate in detail the mechanism of edge fracture and finally suggest a new way in which it might be mitigated in experimental practice. We also suggest that, by containing the second normal stress difference, our criterion for the onset of edge fracture may be used as a means to determine that quantity experimentally. Some of the results in this paper were first announced in an earlier letter [E. J. Hemingway, H. Kusumaatmaja, and S. M. Fielding, Phys. Rev. Lett. 119, 028006 (2017)]. The present paper provides additional simulation results, calculational details of the linear stability analysis, and more detailed discussion of the significance and limitations of our findings.

Multi-Phase Flow Metering in Offshore Oil and Gas Transportation Pipelines: Trends and Perspectives.

Multi-phase flow meters are of huge importance to the offshore oil and gas industry. Unreliable measurements can lead to many disadvantages and even wrong decision-making. It is especially important for mature reservoirs as the gas volume fraction and water cut is increasing during the lifetime of a well. Hence, it is essential to accurately monitor the multi-phase flow of oil, water and gas inside the transportation pipelines. The objective of this review paper is to present the current trends and technologies within multi-phase flow measurements and to introduce the most promising methods based on parameters such as accuracy, footprint, safety, maintenance and calibration. Typical meters, such as tomography, gamma densitometry and virtual flow meters are described and compared based on their performance with respect to multi-phase flow measurements. Both experimental prototypes and commercial solutions are presented and evaluated. For a non-intrusive, non-invasive and inexpensive meter solution, this review paper predicts a progress for virtual flow meters in the near future. The application of multi-phase flows meters are expected to further expand in the future as fields are maturing, thus, efficient utilization of existing fields are in focus, to decide if a field is still financially profitable.

SAT-022 Improving The Diagnosis, Treatment, And Prevention Of Diseases Through Accurate And Reliable Laboratory Measurements With CDC Clinical Standardization Programs

Laboratory measurements are critical for the correct diagnosis and treatment of patients as well as in the investigation of diseases, such as cardiovascular disease, hypogonadism, bone-related diseases, infertility, and certain cancers. Inaccurate and unreliable measurements can lead to the misclassification of patients and incorrect treatment. In CDC Clinical Standardization Programs (CDC CSP), accuracy, precision, and other analytical parameters are assessed against performance goals defined by clinical and medical organizations. CDC offers two approaches to improve the accuracy and reliability of laboratory measurements. The first approach focuses on calibration and annual certification of commercial assays and laboratory developed tests (LDTs). This approach is used in [1] CDC Hormone Standardization (CDC HoSt) Program for total testosterone (TT) and estradiol (E2), [2] Vitamin D Standardization-Certification Program (CDC VDSCP) and [3] Cardiovascular Disease Biomarker Standardization Programs for total cholesterol (TC), total glycerides (TG), HDL-cholesterol (HDL-C), and LDL-cholesterol (LDL-C). Free thyroxine (fT4) will also be available in late 2019. The second approach monitors the accuracy and imprecision of measurements performed routinely in patient care, public health, and research. This approach is focused on the accuracy and consistency of laboratory tests in the hand of end-users. CDC has implemented this approach in the Lipid Standardization Program (CDC LSP) for TC, TG, HDL-C, apolipoprotein AI and B, and CDC Accuracy-based Monitoring (CDC AMP) Program for TT and 25OHD. CDC AMP for E2 will be available for enrollment in late 2019. CDC CSP have improved the accuracy of participating laboratories. Among-laboratory bias decreased from 16.5% in 2007 to 2.8% in 2017 for TT and 54.8% in 2012 to 13.9% in 2017 for E2. Similar improvements have been observed for 25OHD, with a decrease in among-laboratory bias from 13.9% in 2012 to 5.2% in 2016 at 30 nmol/L (vitamin D deficiency) and 12.3% in 2012 to 3.0% in 2016 at 50 nmol/L (vitamin D insufficiency). CDC CSP efforts have helped maintain analytical performance over time. For example, data collected over the past 10 years from CDC LSP indicate that the majority of TC measurements, performed in research and patient care, are consistently within the recommended bias limits of +3%. CDC continues to address new clinical and public health needs by adding new analytes, such as free testosterone, sex hormone binding globulin (SHBG), fT4, parathyroid hormone (PTH), and glucose. CDC CSP also support projects with establishing reference ranges, creating population data using national surveys, and conducting special research studies. CDC CSP are supported by and collaborate with key stakeholders such as the Partnership for the Accurate Testing of Hormones (PATH) and affiliated organizations, including the Endocrine Society.

Delayed Blood Processing Leads to Rapid Deterioration in the Measurement of the Neutrophil Respiratory Burst by the Dihydrorhodamine-123 Reduction Assay.

Neutrophils ex vivo in whole blood specimens are widely understood to decay rapidly when compared to other leukocytes, requiring assessment of neutrophil activity to be performed shortly after blood collection. There is a disparity in evidence for decay rates in measurements and recommended time-frames for assaying neutrophil parameters in particular assays following blood collection. We, therefore, evaluated the decline in the neutrophil respiratory burst, typically screened for assessing congenital NADPH oxidase defects, over a shorter time-course than previously published experiments. The neutrophil respiratory burst was assessed by flow cytometric detection of DHR-123 oxidation to rhodamine-123 (Rho123), following stimulation of neutrophils by phorbol myristate acetate (PMA), in heparinized healthy donor blood specimens immediately following venipuncture, and then at 3 and 5 h later with ambient temperature or refrigerated specimen storage. A consistent time-dependent decline in the Rho123 fluorescence of PMA-stimulated neutrophils was detected in the healthy donor specimens, indicating a decay in respiratory burst activity. Neutrophil oxidative indexes calculated for half of the specimens at 3 and 5 h of age, fell below our normal laboratory lower limit. We also found that Rho123 histograms of PMA-stimulated neutrophils from stored healthy donor specimens have a risk of misinterpretation due to mimicking the appearance of histograms from carriers of CGD and other NADPH oxidase defects. Refrigeration of specimens did not significantly minimize decay. DHR assay of the neutrophil respiratory burst from blood specimens at 3 h post-venipuncture and beyond can generate unreliable clinical measurements due to decay. © 2019 International Clinical Cytometry Society.

Integrated geologic, geophysical, and petrophysical data to construct full field geologic model of Cambrian-Ordovician and Upper Cretaceous reservoir formations, Central Western Sirte Basin, Libya

The Cambrian-Ordovician and Upper Cretaceous formations, which are the main oil-producing formations in the central Sirte Basin, are structurally complex. The lateral and vertical heterogeneity of the reservoir formations is not well-understood, which negatively affects the performance of the reservoirs. We constructed efficient full-field static models that incorporate the lateral and vertical variation of those reservoir formations by integrating geologic and geophysical data. We determined lithology and reservoir properties by selecting appropriate petrophysical techniques that suit the available well data and overcome issues with unreliable well-log measurements. In the process of building structural models, defining and mapping the base of the Cambrian-Ordovician Gargaf Formation was very challenging because wells did not penetrate the basal formation, and the quality of the seismic data decreases with depth. Therefore, we applied techniques of adding isochore maps of the overlying Upper Cretaceous of the Bahi and Waha Formations to map basal contact and determine the thickness of the Gargaf Formation for the first time in the area. The constructed isochore maps showed the thickness variation and the distributions of the Bahi and Waha Formations and explained the influence of Gargaf paleotopography and faults on them. The fault models combined with facies and property models suggested an interconnection among the three main reservoirs. They also indicated that the quality of the Waha reservoir enhances as the lithology varies from limestones to calcareous sandstones, whereas the quality of the Gargaf reservoir was primarily controlled by fractures. The total estimate of the original oil in place with the largest contribution of hydrocarbon volume from the Waha Formation was [Formula: see text] stock tank barrel. The created model with a fine-scale geocellular covering an area of [Formula: see text] is unique to the study area and it can be updated and refined at any time with new data production and drilling activities.

Comparison of the 18F-FDG avidity at PET of benign and malignant pure ground-glass opacities: a paradox?

To determine if pure ground-glass opacities (GGOs) and the subgroup of ground-glass nodules (GGNs) typically demonstrate higher 2-[18F]-fluoro-2-deoxy-d-glucose (18F-FDG) uptake at positron-emission tomography (PET) when benign than when malignant. Informed consent was waived for this institutional review board (IRB)-approved, Health Insurance Portability and Accountability Act (HIPAA) compliant, retrospective study. A review of all 1,864 combined PET/computed tomography (CT) examinations performed in 2011 on a single system to identify pure GGOs with mean diameter ≥1 cm yielded 166 GGOs. Two blinded subspecialty-trained thoracic radiologists independently assessed GGO size, morphology, attenuation, and location on CT. A blinded nuclear radiologist procured the SUVmax for each GGO. Final diagnosis of malignancy (n=21) was made based on histopathology or upon increased size and attenuation; a final diagnosis of benignity (n=106) was made if GGO resolved, was new within 3 months, evolved in a manner consistent with pulmonary fibrosis, or was stable for ≥60 months; 29 were indeterminate and were excluded, along with 10 cases with unreliable SUVmax measurements, yielding 127 GGOs, of which 68 were GGNs, in 76 patients. The SUVmax was significantly higher in benign than malignant GGOs (p=0.0017) and in the GGN subgroup (p=0.03). A threshold SUVmax >1.5 for GGOs, including GGNs, assured benignity in this cohort. Benign GGOs and the benign GGN subgroup demonstrated significantly higher FDG uptake at PET than malignant GGOs/GGNs. Awareness of this finding may prevent misinterpretation of highly 18FDG-avid pure GGOs/GGNs as definitively malignant, which could lead to unnecessary thoracic surgery and its associated risks.

Technical performance of shear wave elastography for measuring liver stiffness in pediatric and adolescent patients: a systematic review and meta-analysis

To assess the technical performance (proportion of technical failure and unreliable measurements) of shear wave elastography (SWE) for assessing liver stiffness in pediatric and adolescent patients. We searched Ovid-MEDLINE and EMBASE databases for eligible studies and selected original articles investigating transient elastography (TE), point shear wave elastography (pSWE), or two-dimensional SWE (2D-SWE) for measuring liver stiffness in pediatric and adolescent patients. A quantitative synthesis of studies reporting technical failures and/or unreliable measurements of TE, pSWE, or 2D-SWE is presented. Meta-analytic pooling was conducted using the random effects model. Meta-regression analysis was conducted to explore potential causes of heterogeneity. Forty of 69 studies (58%) provided technical performance information. Technical failure data were reported in 3 TE, 6 pSWE, and 8 2D-SWE studies. Unreliable measurement data were provided in 21 TE, 4 pSWE, and 1 2D-SWE study. The pooled proportion of unreliable measurements of TE was 12.1%. Meta-regression analysis showed that the study population size and readers' blinding to pathologic results affected the study's heterogeneity. The pooled proportions of technical failure during pSWE and 2D-SWE were 4.1% and 2.2%, respectively, demonstrating no significant difference between the techniques. We reviewed the technical performance of SWE, especially the rate of unreliable measurements from TE studies and rates of technical failure from pSWE and 2D-SWE studies. Considering the importance of technical performance for clinical validation of SWE, numbers of and reasons for technical failure and unreliable measurements should be reported in future studies. Further efforts are necessary to standardize SWE reliability criteria. • Most TE studies reported rate of unreliable measurements, whereas pSWE and 2D-SWE studies were likely to report rates of technical failure. • The pooled proportion of unreliable measurements of TE was 12.1%. • The pooled proportions of technical failure during pSWE and 2D-SWE were 4.1% and 2.2%, respectively, demonstrating no significant difference between the techniques.

Technical Performance of Two-Dimensional Shear Wave Elastography for Measuring Liver Stiffness: A Systematic Review and Meta-Analysis.

ObjectiveTo assess the technical performance of two-dimensional shear wave elastography (2D-SWE) for measuring liver stiffness.Materials and MethodsThe Ovid-MEDLINE and EMBASE databases were searched for studies reporting the technical performance of 2D-SWE, including concerns with technical failures, unreliable measurements, interobserver reliability, and/or intraobserver reliability, published until June 30, 2018. The pooled proportion of technical failure and unreliable measurements was calculated using meta-analytic pooling via the random-effects model and inverse variance method for calculating weights. Subgroup analyses were performed to explore potential causes of heterogeneity. The pooled intraclass correlation coefficients (ICCs) for interobserver and intraobserver reliability were calculated using the Hedges-Olkin method with Fisher's Z transformation of the correlation coefficient.ResultsThe search yielded 34 articles. From 20 2D-SWE studies including 6196 patients, the pooled proportion of technical failure was 2.3% (95% confidence interval [CI], 1.3–3.9%). The pooled proportion of unreliable measurements from 20 studies including 6961 patients was 7.5% (95% CI, 4.7–11.7%). In the subgroup analyses, studies conducting more than three measurements showed fewer unreliable measurements than did those with three measurements or less, but no intergroup difference was found in technical failure. The pooled ICCs for interobserver reliability (from 10 studies including 517 patients) and intraobserver reliability (from 7 studies including 679 patients) were 0.87 (95% CI, 0.82–0.90) and 0.93 (95% CI, 0.89–0.95), respectively, suggesting good to excellent reliability.Conclusion2D-SWE shows good technical performance for assessing liver stiffness, with high technical success and reliability. Future studies should establish the quality criteria and optimal number of measurements.

The Impact of Field Measurements and Data-Handling Procedures on Carbonate- and Sulfide-Scale Prediction

Summary Carbonate and sulfide scales are directly coupled together and differ from other inorganic scales because they are intimately linked to the in-situ concentrations of carbon dioxide (CO2) and hydrogen sulfide (H2S), which influence the local pH and availability of reactive species. The CO2 in aqueous solutions has the most significant effect on the system pH, on the solution content of bicarbonate ion (HCO3–), and on the final alkalinity. However, the presence of H2S in the system also has a direct and important effect on the total-system alkalinity. When calcium carbonate deposition occurs in a depressurized aqueous fluid, the amount of scale (CaCO3) that forms depends on the initial (prescaling) solution alkalinity. Thus, the occurrence and severity of carbonate scale are linked to both the solution carbonate system (CO2/HCO3–/CO32–) and the sulfide system (H2S/HS–/S2–). In previous publications, we have described a rigorous work flow (step-by-step procedure) to accurately predict carbonate- and sulfide-scaling profiles from reservoir to separator using commonly available field data (Verri et al. 2017a). Although, with perfect data, the work flow is rigorous [i.e., it will correctly predict the types and amounts of scale that can occur in some carbonate systems (e.g., CaCO3, FeCO3, FeS)], the numerical results produced are, of course, subject to errors of different types. In this paper, we identify and describe three key categories of data and procedures that must be correctly gathered and used to obtain accurate carbonate- and sulfide-scale predictions: These relate to field measurements, data-handling procedures, choice of software, model equations, and parameters. Moreover, in this work, the impact of unreliable field measurements on the final carbonate and sulfide scaling profiles is estimated, with a specific focus on gas- and water-chemistry errors. By varying important parameters such as Ca2+ concentration and gas-phase CO2 and H2S, it is possible to assess the impact that errors in these measurements have on the final scale-prediction profiles. Because of the closely coupled nature of the carbonate and sulfide systems, it is essential to consider “groups” of variables that change together.

МЕТОД ПОСТРОЕНИЯ РЕЛЬЕФА ДНА ДЛЯ ЗАКРЫТОГО ВОДОЕМА ИЗ ПРОИЗВОЛЬНО РАСПРЕДЕЛЕННЫХ ТОЧЕЧНЫХ ДАННЫХ ИЗМЕРЕНИЙ

Numerical simulation of circulation and internal waves in a basin requires the knowledge of bottom topography, defined as a continuous and continuously differentiable field (un¬less there are known features of the relief to justify the opposite), which is, unfortunately, not always available with sufficient resolution and coverage. In this article we review ex¬isting techniques for producing regularly gridded field from scattered bathymetry data - in our case raw field data measured by a boat equipped with an echo sounder and GPS - and propose a new one, which we believe is the most optimal for this situation. The technique essentially goes along the line of approach of Sandwell (1987) using Green functions to construct biharmonic spline interpolation, which we augment by adding coastline and in-troduce special preprocessing of measured data to identify and eliminate (by averaging out) potentially contradictory and unreliable measurements which may cause spurious oscillations of biharmonic spline.

Estimating network structure from unreliable measurements

Most empirical studies of networks assume that the network data we are given represent a complete and accurate picture of the nodes and edges in the system of interest, but in real-world situations this is rarely the case. More often the data only specify the network structure imperfectly -- like data in essentially every other area of empirical science, network data are prone to measurement error and noise. At the same time, the data may be richer than simple network measurements, incorporating multiple measurements, weights, lengths or strengths of edges, node or edge labels, or annotations of various kinds. Here we develop a general method for making estimates of network structure and properties using any form of network data, simple or complex, when the data are unreliable, and give example applications to a selection of social and biological networks.

A Clinical Trial with Combined Transcranial Direct Current Stimulation and Attentional Bias Modification in Alcohol-Dependent Patients.

BackgroundModifying attentional processes with attentional bias modification (ABM) might be a relevant add‐on to treatment in addiction. This study investigated whether influencing cortical plasticity with transcranial direct current stimulation (tDCS) could increase training effects. tDCS could also help alcohol‐dependent patients to overcome craving and reduce relapse, independent of training. These approaches were combined to investigate effects in the treatment of alcoholism.MethodsNinety‐eight patients (analytical sample = 83) were randomly assigned to 4 groups in a 2‐by‐2 factorial design. Patients received 4 sessions of ABM (control or real training) combined with 2 mA tDCS (active: 20 minutes or sham: 30 seconds) over the left dorsolateral prefrontal cortex. Alcohol bias and craving were assessed, and treatment outcome was measured as relapse after 1 year.ResultsAttentional bias scores indicated that during the training only the group with active tDCS and real ABM displayed an overall avoidance bias (p < 0.05). From pre‐ to postassessment, there were no main or interaction effects of tDCS and ABM on the bias scores, craving, or relapse (p > 0.2). However, effects on relapse after active tDCS were in the expected direction.ConclusionsThere was no evidence of a beneficial effect of tDCS or ABM or the combination. Whether the absence of effect was due to issues with the outcome measurements (e.g., lack of craving, high dropout, and unreliable measurements) or aspects of the intervention should be further investigated.

Event-triggered diffusion estimation for asynchronous sensor networks with unreliable measurements

This article aims at investigating the event-triggered (ET) distributed estimation problem for asynchronous sensor networks with randomly occurred unreliable measurements. We propose two ET mechanisms to schedule data transmissions in this paper. One ET mechanism based on dual-criterion is proposed to schedule the transmissions of measurements and avoid the interferences from unreliable measurements. The other ET mechanism is proposed to schedule the transmissions of local estimates. The connotative information in aforementioned ET mechanisms is exploited for taking full use of available information. Then, we provide the corresponding event-triggered asynchronous diffusion estimator based on the diffusion filtering scheme. In the proposed method, a sensor first generates a local estimate by utilizing available information of asynchronous measurements in each estimation period. Then it fuses available information of asynchronous local estimates to generate a fused estimate. Results of simulations in different cases and experiment in an optical-electronic detection network verify the validity and feasibility of the proposed method.

Target capture and station keeping of fixed speed vehicles without self-location information

Target capture and station keeping problems for an autonomous vehicle agent have been studied in the literature for the cases where the position of the agent can be measured. Station keeping refers to moving the agent to a target whose distances are predefined from a set of beacons that can be stations or other agents. Here we study the target capture and station keeping problems for a nonholonomic vehicle agent that does not know its location and can measure only distances to the target (to the beacons for station keeping). This sensing limitation corresponds to consideration of unavailability of GPS and odometry in practical UAV settings. For each of the target capture and station keeping problems, we propose a control algorithm that uses only agent-target (agent-beacon for station keeping) range and range rate information. We show the stability and convergence properties of our control algorithms. We verified the performance of our control algorithms by simulations and real time experiments on a ground robot. Our algorithms captured the target in finite time in the experiments. Therefore, our algorithms are efficient in scenarios where GPS is unavailable or target identification by vision algorithms is unreliable but continuous agent-target range measurements are available.

Optimal distributed Kalman filtering fusion for multirate multisensor dynamic systems with correlated noise and unreliable measurements

An optimal distributed fusion estimation problem is concerned in this study for a kind of linear dynamic multirate sensors systems with correlated noise and stochastic unreliable measurements. The system is formulated at the finest scale with multiple sensors at different scales observing a common target independently with different sampling rates. The noise between different sensors is relevant, moreover, is also correlated with the system noise. The authors derive the local state estimation algorithms under the circumstance of total reliable measurements and stochastic unreliable measurements occur occasions, and the optimal distributed Kalman filter fusion algorithm, respectively. The authors provide a simulation example to illustrate the effectiveness and feasibility of the proposed algorithm.

Robust AOA based acoustic source localization method with unreliable measurements

Abstract The performance degradation problem of the angle of arrival (AOA)-based acoustic localization methods in the presence of unreliable bearing measurements (outliers) is addressed in this paper. Two typical M-estimators based on Tukey and Huber functions are applied to tackle the problem. Both functions are solved by the iterative reweighted nonlinear least squares (IRNLS) method. Considering the Huber function is convex in nature, it is specifically utilized to mitigate the influence of large residuals on pseudolinear estimator (PLE) by convex optimization. To make the IRNLS method more feasible to use, an approximate relationship between the outlier probability and the bound parameter is provided. The robustness and effectiveness of the proposed methods are clearly demonstrated through a series of simulation results in the presence of various unreliable measurements.

Correspondence between retinotopic cortical mapping and conventional functional and morphological assessment of retinal disease

PurposeThe present study describes retinotopic mapping of the primary visual cortex using functional MRI (fMRI) in patients with retinal disease. It addresses the relationship between fMRI data and data obtained...

Specific Features of Constructing a Dual-Mode GNSS Gyrocompass as a Tightly-Coupled Integrated System

A task of constructing a tightly-coupled inertial satellite integrated system under the conditions of limited visibility is considered in terms of solving both orientation and navigation problems. To determine the orientation parameters of a moving object, a dual-mode GNSS gyrocompass is implemented, which comprises a gimballess inertial measurement unit (IMU) on fiber-optic gyros (FOG), and two-antenna receiving equipment (RE) of global navigation satellite system (GNSS). Algorithms and errors of a GNSS gyrocompass with antenna baseline at the level of wavelength of carrier frequency and satellite receivers with external reference oscillator are studied. At that, the IMU with the antenna module of GNSS RE operates in reversible modulation rotation mode. A specific feature of this system is that a GNSS gyrocompass can be constructed while observing at least one navigation satellite of GPS or GLONASS; moreover, it has an autonomous operation mode which implements an AHRS scheme and position dead-reckoning based on the IMU and log data in absence of signals from the navigation satellite. The ambiguity of phase measurements and unreliable measurements are removed by referring to the IMU data when forming differential measurements in the integrated system at the level of the first differences of phases. The results of desktop analysis of bed testing data for a prototype system with a GNSS gyrocompass Orion-M (designed by CSRI Elektropribor) comprising GNSS receiving units 2K-363E-62 (RIRV JSC) and FOG-based inertial unit VG 910 (Fizoptika JSC) are presented in the paper.