ProScan Automated Profilogram Reduction System, MLR-94-7, 1994

Kansas State University, with funding from the Kansas Department of Transportation (KDOT), has developed a computerized reduction system for profilograms produced by mechanical profilographs. The commercial version of the system (ProScan (trademark)) is marketed by Devore Systems, Inc. The system consists of an IBM Compatible PC 486SX33 computer or better, Epson LQ-570 printer, a Logitech Scanman 32 hand scanner system, a paper transport unit, and the ProScan software. The Scanner is not adaptable to IBM computers with the micro channel architecture. The Iowa DOT Transportation Centers could realize the following advantages by using ProScan: (1) Save about 5 to 8 staff hours of reduction and reporting time per Transportation Center per week for a Materials Technician 3 or 4 (the time savings would come during the busiest part of the season); (2) Reduce errors in reduction, transfer, and typing of profile values; (3) Increase the accuracy of the monitor results; and (4) Allow rapid evaluation of contractor traces when tolerance limits between monitor and certified results are exceeded.

Statistical Analysis of Highway Needs Condition Data: Manual vs. Automated, TR-494

This project examines similarities and differences between the automated condition data collected on and off county paved roads and the manual condition data collected by Iowa Department of Transportation (DOT) staff in 2000 and 2001. Also, the researchers will provide staff support to the advisory committee in exploring other options to the highway need process. The results show that the automated condition data can be used in a converted highway needs process with no major differences between the two methods. Even though the foundation rating difference was significant, the foundation rating weighting factor in HWYNEEDS is minimal and should not have a major impact. In terms of RUTF formula based distribution, the results clearly show the superiority of the condition-based analysis compared to the non-condition based. That correlation can be further enhanced by adding more distress variables to the analysis.

Automated identification of minimal myocardial motion for improved image quality on MR angiography at 3 T

OBJECTIVE: Imaging during a period of minimal myocardial motion is of paramount importance for coronary MR angiography (MRA). The objective of our study was to evaluate the utility of FREEZE, a custom-built automated tool for the identification of the period of minimal myocardial motion, in both a moving phantom at 1.5 T and 10 healthy adults (nine men, one woman; mean age, 24.9 years; age range, 21-32 years) at 3 T. CONCLUSION: Quantitative analysis of the moving phantom showed that dimension measurements approached those obtained in the static phantom when using FREEZE. In vitro, vessel sharpness, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were significantly improved when coronary MRA was performed during the software-prescribed period of minimal myocardial motion (p < 0.05). Consistent with these objective findings, image quality assessments by consensus review also improved significantly when using the automated prescription of the period of minimal myocardial motion. The use of FREEZE improves image quality of coronary MRA. Simultaneously, operator dependence can be minimized while the ease of use is improved.

Multicenter study of a new fully automated HBsAg screening assay with enhanced sensitivity for the detection of HBV mutants.

In a multicenter study a new, fully automated Roche Diagnostics Elecsys HBsAg II screening assay with improved sensitivity to HBsAg mutant detection was compared to well-established HBsAg tests: AxSYM HBsAg V2 (Abbott), Architect HBsAg (Abbott), Advia Centaur HBsAg (Bayer) Enzygnost HBsAg 5.0 (Dade-Behring), and Vitros Eci HBsAg (Ortho). A total of 16 seroconversion panels, samples of 60 HBsAg native mutants, and 31 HBsAg recombinant mutants, dilution series of NIBSC and PEI standards, 156 HBV positive samples comprising genotypes A to G, 686 preselected HBsAg positive samples from different stages of infection, 3,593 samples from daily routine, and 6,360 unselected blood donations were tested to evaluate the analytical and clinical sensitivity, the detection of mutants, and the specificity of the new assay. Elecsys HBsAg II showed a statistically significant better sensitivity in seroconversion panels to the compared tests. Fifty-seven out of 60 native mutants and all recombinant mutants were found positive. Among 156 HBV samples with different genotypes and 696 preselected HBsAg positive samples Elecsys HBsAg II achieved a sensitivity of 100%. The lower detection limit for NIBSC standard was calculated to be 0.025 IU/ml and for the PEI standards ad and ay it was <0.001 and <0.005 U/ml, respectively. Within 2,724 daily routine specimens and 6.360 unselected blood donations Elecsys HBsAg II showed a specificity of 99.97 and 99.88%, respectively. In conclusion the new Elecsys HBsAg II shows a high sensitivity for the detection of all stages of HBV infection and HBsAg mutants paired together with a high specificity in blood donors, daily routine samples, and potentially interfering sera.

Automated Traffic/Truck Weight Monitoring Equipment (Weigh-in-Motion), HR-282, 1988

This report documents work undertaken in the demonstration of a low-cost Automatic Weight and Classification System (AWACS). An AWACS procurement specification and details of the results of the project are also included. The intent of the project is to support and encourage transferring research knowledge to state and local agencies and manufacturers through field demonstrations. Presently available, Weigh-in-Motion and Classification Systems are typically too expensive to permit the wide deployment necessary to obtain representative vehicle data. Piezo electric technology has been used in the United Kingdom and Europe and is believed to be the basic element in a low-cost AWACS. Low-cost systems have been installed at two sites, one in Portland Cement Concrete (PCC) pavement in Iowa and the other in Asphaltic Cement Concrete (ACC) pavement in Minnesota to provide experience with both types of pavement. The systems provide axle weights, gross vehicle weight, axle spacing, vehicle classification, vehicle speed, vehicle count, and time of arrival. In addition, system self-calibration and a method to predict contact tire pressure is included in the system design. The study has shown that in the PCC pavement, the AWACS is capable of meeting the needs of state and federal highway agencies, producing accuracies comparable to many current commercial WIM devices. This is being achieved at a procurement cost of substantially less than currently available equipment. In the ACC pavement the accuracies were less than those observed in the PCC pavement which is concluded to result from a low pavement rigidity at this site. Further work is needed to assess the AWACS performance at a range of sites in ACC pavements.

The Effectiveness of Iowa's Automated Red Light Running Enforcement Programs, 2007

The Federal Highway Administration estimates that red light running causes more than 100,000 crashes and 1,000 fatalities annually and results in an estimated economic loss of over $14 billion per year in the United States. In Iowa alone, a statewide analysis of red light running crashes, using crash data from 2001 to 2006, indicates that an average of 1,682 red light running crashes occur at signalized intersections every year. As a result, red light running poses a significant safety issue for communities. Communities rarely have the resources to place additional law enforcement in the field to combat the problem and they are increasingly using automated red light running camera-enforcement systems at signalized intersections. In Iowa, three communities currently use camera enforcement since 2004. These communities include Davenport, Council Bluffs, and Clive. As communities across the United States attempt to address red light running, a number of communities have implemented red light running camera enforcement programs. This report examines the red light running programs in Iowa and summarizes results of analyses to evaluate the effectiveness of such cameras.

Automated Lesion Detection-Based Symptome Mapping In Patients With Sensory Deficits

The human brain is the most complex structure known. With its high number of cells, number of connections and number of pathways it is the source of every thought in the world. It consumes 25% of our oxygen and suffers very fast from a disruption of its supply. An acute event, like a stroke, results in rapid dysfunction referable to the affected area. A few minutes without oxygen and neuronal cells die and subsequently degenerate. Changes in the brains incoming blood flow alternate the anatomy and physiology of the brain. All stroke events leave behind a brain tissue lesion. To rapidly react and improve the prediction of outcome in stroke patients, accurate lesion detection and reliable lesion-based function correlation would be very helpful. With a number of neuroimaging and clinical data of cerebral injured patients this study aims to investigate correlations of structural lesion locations with sensory functions.

A fast automated screening method for the detection of blood transfusion in sports.

Currently, there is no simple direct screening method for the misuse of blood transfusions in sports. In this study, we investigated whether the measurement of iron in EDTA-plasma can serve as biomarker for such purpose. Our results revealed an increase of the plasma iron level up to 25-fold 6 h after blood re-infusion. The variable remained elevated 10-fold one day after the procedure. A specificity of 100% and a sensitivity of 93% were obtained with a proposed threshold at 45 µg/dL of plasma iron. Therefore, our test could be used as a simple, cost effective biomarker for the screening for blood transfusion misuse in sports. Copyright © 2014 John Wiley & Sons, Ltd.

Review of Automated Vehicle Technology: Policy and Implementation Implications; Version 1.0; RB28-015, 2016

This report provides recommendations for the state of Iowa over the next five years in regards to automated vehicle policy development. These administrative, planning, legal, and community strategy recommendations for government agencies include: • Encouraging automation by preparing government agencies, infrastructure, leveraging procurement, and advocating for safety mandates • Adjusting long range planning processes by identifying and incorporating a wide range of new automation scenarios • Beginning to analyze and, as necessary, clarify existing law as it apples to automated driving • Auditing existing law • Enforcing existing laws • Ensuring vehicle owners and operators bear the true cost of driving • Embracing flexibility by giving agencies the statutory authority to achieve regulatory goals through different means, allowing them to make small-scale exemptions to statutory regimes and clarifying their enforcement discretion • Thinking locally and preparing publicly • Sharing the steps being taken to promote (as well as to anticipate and regulate) automated driving • Instituting public education about automated vehicle technologies.

Transjugular liver biopsy: prospective evaluation of the angle formed between the hepatic veins and the vena cava main axis and modification of a semi-automated biopsy device in cases of an unfavorable angle.

In cases of transjugular liver biopsies, the venous angle formed between the chosen hepatic vein and the vena cava main axis in a frontal plane can be large, leading to technical difficulties. In a prospective study including 139 consecutive patients who underwent transjugular liver biopsy using the Quick-Core biopsy set, the mean venous angle was equal to 49.6 degrees. For 21.1% of the patients, two attempts at hepatic venous catheterization failed because the venous angle was too large, with a mean of 69.7 degrees. In all of these patients, manual reshaping of the distal curvature of the stiffening metallic cannula, by forming a new mean angle equal to 48 degrees , allowed successful completion of the procedure in less than 10 min.

A new early and automated MRI-based predictor of motor improvement after stroke.

OBJECTIVES: In this study, we investigated the structural plasticity of the contralesional motor network in ischemic stroke patients using diffusion magnetic resonance imaging (MRI) and explored a model that combines a MRI-based metric of contralesional network integrity and clinical data to predict functional outcome at 6 months after stroke. METHODS: MRI and clinical examinations were performed in 12 patients in the acute phase, at 1 and 6 months after stroke. Twelve age- and gender-matched controls underwent 2 MRIs 1 month apart. Structural remodeling after stroke was assessed using diffusion MRI with an automated measurement of generalized fractional anisotropy (GFA), which was calculated along connections between contralesional cortical motor areas. The predictive model of poststroke functional outcome was computed using a linear regression of acute GFA measures and the clinical assessment. RESULTS: GFA changes in the contralesional motor tracts were found in all patients and differed significantly from controls (0.001 ≤ p < 0.05). GFA changes in intrahemispheric and interhemispheric motor tracts correlated with age (p ≤ 0.01); those in intrahemispheric motor tracts correlated strongly with clinical scores and stroke sizes (p ≤ 0.001). GFA measured in the acute phase together with a routine motor score and age were a strong predictor of motor outcome at 6 months (r(2) = 0.96, p = 0.0002). CONCLUSION: These findings represent a proof of principle that contralesional diffusion MRI measures may provide reliable information for personalized rehabilitation planning after ischemic motor stroke. Neurology® 2012;79:39-46.

Automated segmentation of multiple red blood cells with digital holographic microscopy.

We present a method to automatically segment red blood cells (RBCs) visualized by digital holographic microscopy (DHM), which is based on the marker-controlled watershed algorithm. Quantitative phase images of RBCs can be obtained by using off-axis DHM along to provide some important information about each RBC, including size, shape, volume, hemoglobin content, etc. The most important process of segmentation based on marker-controlled watershed is to perform an accurate localization of internal and external markers. Here, we first obtain the binary image via Otsu algorithm. Then, we apply morphological operations to the binary image to get the internal markers. We then apply the distance transform algorithm combined with the watershed algorithm to generate external markers based on internal markers. Finally, combining the internal and external markers, we modify the original gradient image and apply the watershed algorithm. By appropriately identifying the internal and external markers, the problems of oversegmentation and undersegmentation are avoided. Furthermore, the internal and external parts of the RBCs phase image can also be segmented by using the marker-controlled watershed combined with our method, which can identify the internal and external markers appropriately. Our experimental results show that the proposed method achieves good performance in terms of segmenting RBCs and could thus be helpful when combined with an automated classification of RBCs.

ML estimator and hybrid beamformer for multipath and interference mitigation in GNSS receivers

This paper addresses the estimation of the code-phase(pseudorange) and the carrier-phase of the direct signal received from a direct-sequence spread-spectrum satellite transmitter. Thesignal is received by an antenna array in a scenario with interferenceand multipath propagation. These two effects are generallythe limiting error sources in most high-precision positioning applications.A new estimator of the code- and carrier-phases is derivedby using a simplified signal model and the maximum likelihood(ML) principle. The simplified model consists essentially ofgathering all signals, except for the direct one, in a component withunknown spatial correlation. The estimator exploits the knowledgeof the direction-of-arrival of the direct signal and is much simplerthan other estimators derived under more detailed signal models.Moreover, we present an iterative algorithm, that is adequate for apractical implementation and explores an interesting link betweenthe ML estimator and a hybrid beamformer. The mean squarederror and bias of the new estimator are computed for a numberof scenarios and compared with those of other methods. The presentedestimator and the hybrid beamforming outperform the existingtechniques of comparable complexity and attains, in manysituations, the Cramér–Rao lower bound of the problem at hand.