Vision-based real-time position control of a semi-automated system for robot-assisted joint fracture surgery.

PubMed

Dagnino, Giulio; Georgilas, Ioannis; Tarassoli, Payam; Atkins, Roger; Dogramadzi, Sanja

2016-03-01

Joint fracture surgery quality can be improved by robotic system with high-accuracy and high-repeatability fracture fragment manipulation. A new real-time vision-based system for fragment manipulation during robot-assisted fracture surgery was developed and tested. The control strategy was accomplished by merging fast open-loop control with vision-based control. This two-phase process is designed to eliminate the open-loop positioning errors by closing the control loop using visual feedback provided by an optical tracking system. Evaluation of the control system accuracy was performed using robot positioning trials, and fracture reduction accuracy was tested in trials on ex vivo porcine model. The system resulted in high fracture reduction reliability with a reduction accuracy of 0.09 mm (translations) and of [Formula: see text] (rotations), maximum observed errors in the order of 0.12 mm (translations) and of [Formula: see text] (rotations), and a reduction repeatability of 0.02 mm and [Formula: see text]. The proposed vision-based system was shown to be effective and suitable for real joint fracture surgical procedures, contributing a potential improvement of their quality.

The Accuracy of Integrated [18F] Fluorodeoxyglucose-Positron Emission Tomography/Computed Tomography in Detection of Pelvic and Para-aortic Nodal Metastasis in Patients with High Risk Endometrial Cancer

PubMed Central

Gholkar, Nikhil Shirish; Saha, Subhas Chandra; Prasad, GRV; Bhattacharya, Anish; Srinivasan, Radhika; Suri, Vanita

2014-01-01

Lymph nodal (LN) metastasis is the most important prognostic factor in high-risk endometrial cancer. However, the benefit of routine lymphadenectomy in endometrial cancer is controversial. This study was conducted to assess the accuracy of [18F] fluorodeoxyglucose-positron emission tomography/computed tomography ([18F] FDG-PET/CT) in detection of pelvic and para-aortic nodal metastases in high-risk endometrial cancer. 20 patients with high-risk endometrial carcinoma underwent [18F] FDG-PET/CT followed by total abdominal hysterectomy, bilateral salpingo-oophorectomy and systematic pelvic lymphadenectomy with or without para-aortic lymphadenectomy. The findings on histopathology were compared with [18F] FDG-PET/CT findings to calculate the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of [18F] FDG-PET/CT. The pelvic nodal findings were analyzed on a patient and nodal chain based criteria. The para-aortic nodal findings were reported separately. Histopathology documented nodal involvement in two patients (10%). For detection of pelvic nodes, on a patient based analysis, [18F] FDG-PET/CT had a sensitivity of 100%, specificity of 61.11%, PPV of 22.22%, NPV of 100% and accuracy of 65% and on a nodal chain based analysis, [18F] FDG-PET/CT had a sensitivity of 100%, specificity of 80%, PPV of 20%, NPV of 100%, and accuracy of 80.95%. For detection of para-aortic nodes, [18F] FDG-PET/CT had sensitivity of 100%, specificity of 66.67%, PPV of 20%, NPV of 100%, and accuracy of 69.23%. Although [18F] FDG-PET/CT has high sensitivity for detection of LN metastasis in endometrial carcinoma, it had moderate accuracy and high false positivity. However, the high NPV is important in selecting patients in whom lymphadenectomy may be omitted. PMID:25538488

Improving transmembrane protein consensus topology prediction using inter-helical interaction.

PubMed

Wang, Han; Zhang, Chao; Shi, Xiaohu; Zhang, Li; Zhou, You

2012-11-01

Alpha helix transmembrane proteins (αTMPs) represent roughly 30% of all open reading frames (ORFs) in a typical genome and are involved in many critical biological processes. Due to the special physicochemical properties, it is hard to crystallize and obtain high resolution structures experimentally, thus, sequence-based topology prediction is highly desirable for the study of transmembrane proteins (TMPs), both in structure prediction and function prediction. Various model-based topology prediction methods have been developed, but the accuracy of those individual predictors remain poor due to the limitation of the methods or the features they used. Thus, the consensus topology prediction method becomes practical for high accuracy applications by combining the advances of the individual predictors. Here, based on the observation that inter-helical interactions are commonly found within the transmembrane helixes (TMHs) and strongly indicate the existence of them, we present a novel consensus topology prediction method for αTMPs, CNTOP, which incorporates four top leading individual topology predictors, and further improves the prediction accuracy by using the predicted inter-helical interactions. The method achieved 87% prediction accuracy based on a benchmark dataset and 78% accuracy based on a non-redundant dataset which is composed of polytopic αTMPs. Our method derives the highest topology accuracy than any other individual predictors and consensus predictors, at the same time, the TMHs are more accurately predicted in their length and locations, where both the false positives (FPs) and the false negatives (FNs) decreased dramatically. The CNTOP is available at: http://ccst.jlu.edu.cn/JCSB/cntop/CNTOP.html. Copyright © 2012 Elsevier B.V. All rights reserved.

Improvement of Gaofen-3 Absolute Positioning Accuracy Based on Cross-Calibration

PubMed Central

Deng, Mingjun; Li, Jiansong

2017-01-01

The Chinese Gaofen-3 (GF-3) mission was launched in August 2016, equipped with a full polarimetric synthetic aperture radar (SAR) sensor in the C-band, with a resolution of up to 1 m. The absolute positioning accuracy of GF-3 is of great importance, and in-orbit geometric calibration is a key technology for improving absolute positioning accuracy. Conventional geometric calibration is used to accurately calibrate the geometric calibration parameters of the image (internal delay and azimuth shifts) using high-precision ground control data, which are highly dependent on the control data of the calibration field, but it remains costly and labor-intensive to monitor changes in GF-3’s geometric calibration parameters. Based on the positioning consistency constraint of the conjugate points, this study presents a geometric cross-calibration method for the rapid and accurate calibration of GF-3. The proposed method can accurately calibrate geometric calibration parameters without using corner reflectors and high-precision digital elevation models, thus improving absolute positioning accuracy of the GF-3 image. GF-3 images from multiple regions were collected to verify the absolute positioning accuracy after cross-calibration. The results show that this method can achieve a calibration accuracy as high as that achieved by the conventional field calibration method. PMID:29240675

Precise Orbit Determination for ALOS

NASA Technical Reports Server (NTRS)

Nakamura, Ryo; Nakamura, Shinichi; Kudo, Nobuo; Katagiri, Seiji

2007-01-01

The Advanced Land Observing Satellite (ALOS) has been developed to contribute to the fields of mapping, precise regional land coverage observation, disaster monitoring, and resource surveying. Because the mounted sensors need high geometrical accuracy, precise orbit determination for ALOS is essential for satisfying the mission objectives. So ALOS mounts a GPS receiver and a Laser Reflector (LR) for Satellite Laser Ranging (SLR). This paper deals with the precise orbit determination experiments for ALOS using Global and High Accuracy Trajectory determination System (GUTS) and the evaluation of the orbit determination accuracy by SLR data. The results show that, even though the GPS receiver loses lock of GPS signals more frequently than expected, GPS-based orbit is consistent with SLR-based orbit. And considering the 1 sigma error, orbit determination accuracy of a few decimeters (peak-to-peak) was achieved.

An oscillation-free flow solver based on flux reconstruction

NASA Astrophysics Data System (ADS)

Aguerre, Horacio J.; Pairetti, Cesar I.; Venier, Cesar M.; Márquez Damián, Santiago; Nigro, Norberto M.

2018-07-01

In this paper, a segregated algorithm is proposed to suppress high-frequency oscillations in the velocity field for incompressible flows. In this context, a new velocity formula based on a reconstruction of face fluxes is defined eliminating high-frequency errors. In analogy to the Rhie-Chow interpolation, this approach is equivalent to including a flux-based pressure gradient with a velocity diffusion in the momentum equation. In order to guarantee second-order accuracy of the numerical solver, a set of conditions are defined for the reconstruction operator. To arrive at the final formulation, an outlook over the state of the art regarding velocity reconstruction procedures is presented comparing them through an error analysis. A new operator is then obtained by means of a flux difference minimization satisfying the required spatial accuracy. The accuracy of the new algorithm is analyzed by performing mesh convergence studies for unsteady Navier-Stokes problems with analytical solutions. The stabilization properties of the solver are then tested in a problem where spurious numerical oscillations arise for the velocity field. The results show a remarkable performance of the proposed technique eliminating high-frequency errors without losing accuracy.

An analytical model with flexible accuracy for deep submicron DCVSL cells

NASA Astrophysics Data System (ADS)

Valiollahi, Sepideh; Ardeshir, Gholamreza

2018-07-01

Differential cascoded voltage switch logic (DCVSL) cells are among the best candidates of circuit designers for a wide range of applications due to advantages such as low input capacitance, high switching speed, small area and noise-immunity; nevertheless, a proper model has not yet been developed to analyse them. This paper analyses deep submicron DCVSL cells based on a flexible accuracy-simplicity trade-off including the following key features: (1) the model is capable of producing closed-form expressions with an acceptable accuracy; (2) model equations can be solved numerically to offer higher accuracy; (3) the short-circuit currents occurring in high-low/low-high transitions are accounted in analysis and (4) the changes in the operating modes of transistors during transitions together with an efficient submicron I-V model, which incorporates the most important non-ideal short-channel effects, are considered. The accuracy of the proposed model is validated in IBM 0.13 µm CMOS technology through comparisons with the accurate physically based BSIM3 model. The maximum error caused by analytical solutions is below 10%, while this amount is below 7% for numerical solutions.

Recent developments in heterodyne laser interferometry at Harbin Institute of Technology

NASA Astrophysics Data System (ADS)

Hu, P. C.; Tan, J. B. B.; Yang, H. X. X.; Fu, H. J. J.; Wang, Q.

2013-01-01

In order to fulfill the requirements for high-resolution and high-precision heterodyne interferometric technologies and instruments, the laser interferometry group of HIT has developed some novel techniques for high-resolution and high-precision heterodyne interferometers, such as high accuracy laser frequency stabilization, dynamic sub-nanometer resolution phase interpolation and dynamic nonlinearity measurement. Based on a novel lock point correction method and an asymmetric thermal structure, the frequency stabilized laser achieves a long term stability of 1.2×10-8, and it can be steadily stabilized even in the air flowing up to 1 m/s. In order to achieve dynamic sub-nanometer resolution of laser heterodyne interferometers, a novel phase interpolation method based on digital delay line is proposed. Experimental results show that, the proposed 0.62 nm, phase interpolator built with a 64 multiple PLL and an 8-tap digital delay line achieves a static accuracy better than 0.31nm and a dynamic accuracy better than 0.62 nm over the velocity ranging from -2 m/s to 2 m/s. Meanwhile, an accuracy beam polarization measuring setup is proposed to check and ensure the light's polarization state of the dual frequency laser head, and a dynamic optical nonlinearity measuring setup is built to measure the optical nonlinearity of the heterodyne system accurately and quickly. Analysis and experimental results show that, the beam polarization measuring setup can achieve an accuracy of 0.03° in ellipticity angles and an accuracy of 0.04° in the non-orthogonality angle respectively, and the optical nonlinearity measuring setup can achieve an accuracy of 0.13°.

A New Filtering and Smoothing Algorithm for Railway Track Surveying Based on Landmark and IMU/Odometer

PubMed Central

Jiang, Qingan; Wu, Wenqi; Jiang, Mingming; Li, Yun

2017-01-01

High-accuracy railway track surveying is essential for railway construction and maintenance. The traditional approaches based on total station equipment are not efficient enough since high precision surveying frequently needs static measurements. This paper proposes a new filtering and smoothing algorithm based on the IMU/odometer and landmarks integration for the railway track surveying. In order to overcome the difficulty of estimating too many error parameters with too few landmark observations, a new model with completely observable error states is established by combining error terms of the system. Based on covariance analysis, the analytical relationship between the railway track surveying accuracy requirements and equivalent gyro drifts including bias instability and random walk noise are established. Experiment results show that the accuracy of the new filtering and smoothing algorithm for railway track surveying can reach 1 mm (1σ) when using a Ring Laser Gyroscope (RLG)-based Inertial Measurement Unit (IMU) with gyro bias instability of 0.03°/h and random walk noise of 0.005°/h while control points of the track control network (CPIII) position observations are provided by the optical total station in about every 60 m interval. The proposed approach can satisfy at the same time the demands of high accuracy and work efficiency for railway track surveying. PMID:28629191

Generating high-accuracy urban distribution map for short-term change monitoring based on convolutional neural network by utilizing SAR imagery

NASA Astrophysics Data System (ADS)

Iino, Shota; Ito, Riho; Doi, Kento; Imaizumi, Tomoyuki; Hikosaka, Shuhei

2017-10-01

In the developing countries, urban areas are expanding rapidly. With the rapid developments, a short term monitoring of urban changes is important. A constant observation and creation of urban distribution map of high accuracy and without noise pollution are the key issues for the short term monitoring. SAR satellites are highly suitable for day or night and regardless of atmospheric weather condition observations for this type of study. The current study highlights the methodology of generating high-accuracy urban distribution maps derived from the SAR satellite imagery based on Convolutional Neural Network (CNN), which showed the outstanding results for image classification. Several improvements on SAR polarization combinations and dataset construction were performed for increasing the accuracy. As an additional data, Digital Surface Model (DSM), which are useful to classify land cover, were added to improve the accuracy. From the obtained result, high-accuracy urban distribution map satisfying the quality for short-term monitoring was generated. For the evaluation, urban changes were extracted by taking the difference of urban distribution maps. The change analysis with time series of imageries revealed the locations of urban change areas for short-term. Comparisons with optical satellites were performed for validating the results. Finally, analysis of the urban changes combining X-band, L-band and C-band SAR satellites was attempted to increase the opportunity of acquiring satellite imageries. Further analysis will be conducted as future work of the present study

Object-Based Random Forest Classification of Land Cover from Remotely Sensed Imagery for Industrial and Mining Reclamation

NASA Astrophysics Data System (ADS)

Chen, Y.; Luo, M.; Xu, L.; Zhou, X.; Ren, J.; Zhou, J.

2018-04-01

The RF method based on grid-search parameter optimization could achieve a classification accuracy of 88.16 % in the classification of images with multiple feature variables. This classification accuracy was higher than that of SVM and ANN under the same feature variables. In terms of efficiency, the RF classification method performs better than SVM and ANN, it is more capable of handling multidimensional feature variables. The RF method combined with object-based analysis approach could highlight the classification accuracy further. The multiresolution segmentation approach on the basis of ESP scale parameter optimization was used for obtaining six scales to execute image segmentation, when the segmentation scale was 49, the classification accuracy reached the highest value of 89.58 %. The classification accuracy of object-based RF classification was 1.42 % higher than that of pixel-based classification (88.16 %), and the classification accuracy was further improved. Therefore, the RF classification method combined with object-based analysis approach could achieve relatively high accuracy in the classification and extraction of land use information for industrial and mining reclamation areas. Moreover, the interpretation of remotely sensed imagery using the proposed method could provide technical support and theoretical reference for remotely sensed monitoring land reclamation.

Fuzzy PID control algorithm based on PSO and application in BLDC motor

NASA Astrophysics Data System (ADS)

Lin, Sen; Wang, Guanglong

2017-06-01

A fuzzy PID control algorithm is studied based on improved particle swarm optimization (PSO) to perform Brushless DC (BLDC) motor control which has high accuracy, good anti-jamming capability and steady state accuracy compared with traditional PID control. The mathematical and simulation model is established for BLDC motor by simulink software, and the speed loop of the fuzzy PID controller is designed. The simulation results show that the fuzzy PID control algorithm based on PSO has higher stability, high control precision and faster dynamic response speed.

A neural network approach to cloud classification

NASA Technical Reports Server (NTRS)

Lee, Jonathan; Weger, Ronald C.; Sengupta, Sailes K.; Welch, Ronald M.

1990-01-01

It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery achieves an overall cloud identification accuracy of 93 percent. Cirrus can be distinguished from boundary layer cloudiness with an accuracy of 96 percent, without the use of an infrared channel. Stratocumulus is retrieved with an accuracy of 92 percent, cumulus at 90 percent. The use of the neural network does not improve cirrus classification accuracy. Rather, its main effect is in the improved separation between stratocumulus and cumulus cloudiness. While most cloud classification algorithms rely on linear parametric schemes, the present study is based on a nonlinear, nonparametric four-layer neural network approach. A three-layer neural network architecture, the nonparametric K-nearest neighbor approach, and the linear stepwise discriminant analysis procedure are compared. A significant finding is that significantly higher accuracies are attained with the nonparametric approaches using only 20 percent of the database as training data, compared to 67 percent of the database in the linear approach.

Towards SSVEP-based, portable, responsive Brain-Computer Interface.

PubMed

Kaczmarek, Piotr; Salomon, Pawel

2015-08-01

A Brain-Computer Interface in motion control application requires high system responsiveness and accuracy. SSVEP interface consisted of 2-8 stimuli and 2 channel EEG amplifier was presented in this paper. The observed stimulus is recognized based on a canonical correlation calculated in 1 second window, ensuring high interface responsiveness. A threshold classifier with hysteresis (T-H) was proposed for recognition purposes. Obtained results suggest that T-H classifier enables to significantly increase classifier performance (resulting in accuracy of 76%, while maintaining average false positive detection rate of stimulus different then observed one between 2-13%, depending on stimulus frequency). It was shown that the parameters of T-H classifier, maximizing true positive rate, can be estimated by gradient-based search since the single maximum was observed. Moreover the preliminary results, performed on a test group (N=4), suggest that for T-H classifier exists a certain set of parameters for which the system accuracy is similar to accuracy obtained for user-trained classifier.

Curriculum-Based Measurement of Reading Growth: Weekly versus Intermittent Progress Monitoring

ERIC Educational Resources Information Center

Jenkins, Joseph; Schulze, Margaret; Marti, Allison; Harbaugh, Allen G.

2017-01-01

We examined the idea that leaner schedules of progress monitoring (PM) can lighten assessment demands without undermining decision-making accuracy. Using curriculum-based measurement of reading, we compared effects on decision accuracy of 5 intermittent PM schedules relative to that of every-week PM. For participating students with high-incidence…

High accuracy in short ISS missions

NASA Astrophysics Data System (ADS)

Rüeger, J. M.

1986-06-01

Traditionally Inertial Surveying Systems ( ISS) are used for missions of 30 km to 100 km length. Today, a new type of ISS application is emanating from an increased need for survey control densification in urban areas often in connection with land information systems or cadastral surveys. The accuracy requirements of urban surveys are usually high. The loss in accuracy caused by the coordinate transfer between IMU and ground marks is investigated and an offsetting system based on electronic tacheometers is proposed. An offsetting system based on a Hewlett-Packard HP 3820A electronic tacheometer has been tested in Sydney (Australia) in connection with a vehicle mounted LITTON Auto-Surveyor System II. On missions over 750 m ( 8 stations, 25 minutes duration, 3.5 minute ZUPT intervals, mean offset distances 9 metres) accuracies of 37 mm (one sigma) in position and 8 mm in elevation were achieved. Some improvements to the LITTON Auto-Surveyor System II are suggested which would improve the accuracies even further.

Accuracy of computer-aided diagnosis based on narrow-band imaging endocytoscopy for diagnosing colorectal lesions: comparison with experts.

PubMed

Misawa, Masashi; Kudo, Shin-Ei; Mori, Yuichi; Takeda, Kenichi; Maeda, Yasuharu; Kataoka, Shinichi; Nakamura, Hiroki; Kudo, Toyoki; Wakamura, Kunihiko; Hayashi, Takemasa; Katagiri, Atsushi; Baba, Toshiyuki; Ishida, Fumio; Inoue, Haruhiro; Nimura, Yukitaka; Oda, Msahiro; Mori, Kensaku

2017-05-01

Real-time characterization of colorectal lesions during colonoscopy is important for reducing medical costs, given that the need for a pathological diagnosis can be omitted if the accuracy of the diagnostic modality is sufficiently high. However, it is sometimes difficult for community-based gastroenterologists to achieve the required level of diagnostic accuracy. In this regard, we developed a computer-aided diagnosis (CAD) system based on endocytoscopy (EC) to evaluate cellular, glandular, and vessel structure atypia in vivo. The purpose of this study was to compare the diagnostic ability and efficacy of this CAD system with the performances of human expert and trainee endoscopists. We developed a CAD system based on EC with narrow-band imaging that allowed microvascular evaluation without dye (ECV-CAD). The CAD algorithm was programmed based on texture analysis and provided a two-class diagnosis of neoplastic or non-neoplastic, with probabilities. We validated the diagnostic ability of the ECV-CAD system using 173 randomly selected EC images (49 non-neoplasms, 124 neoplasms). The images were evaluated by the CAD and by four expert endoscopists and three trainees. The diagnostic accuracies for distinguishing between neoplasms and non-neoplasms were calculated. ECV-CAD had higher overall diagnostic accuracy than trainees (87.8 vs 63.4%; [Formula: see text]), but similar to experts (87.8 vs 84.2%; [Formula: see text]). With regard to high-confidence cases, the overall accuracy of ECV-CAD was also higher than trainees (93.5 vs 71.7%; [Formula: see text]) and comparable to experts (93.5 vs 90.8%; [Formula: see text]). ECV-CAD showed better diagnostic accuracy than trainee endoscopists and was comparable to that of experts. ECV-CAD could thus be a powerful decision-making tool for less-experienced endoscopists.

The effect of stimulus strength on the speed and accuracy of a perceptual decision.

PubMed

Palmer, John; Huk, Alexander C; Shadlen, Michael N

2005-05-02

Both the speed and the accuracy of a perceptual judgment depend on the strength of the sensory stimulation. When stimulus strength is high, accuracy is high and response time is fast; when stimulus strength is low, accuracy is low and response time is slow. Although the psychometric function is well established as a tool for analyzing the relationship between accuracy and stimulus strength, the corresponding chronometric function for the relationship between response time and stimulus strength has not received as much consideration. In this article, we describe a theory of perceptual decision making based on a diffusion model. In it, a decision is based on the additive accumulation of sensory evidence over time to a bound. Combined with simple scaling assumptions, the proportional-rate and power-rate diffusion models predict simple analytic expressions for both the chronometric and psychometric functions. In a series of psychophysical experiments, we show that this theory accounts for response time and accuracy as a function of both stimulus strength and speed-accuracy instructions. In particular, the results demonstrate a close coupling between response time and accuracy. The theory is also shown to subsume the predictions of Piéron's Law, a power function dependence of response time on stimulus strength. The theory's analytic chronometric function allows one to extend theories of accuracy to response time.

Classification of large-scale fundus image data sets: a cloud-computing framework.

PubMed

Roychowdhury, Sohini

2016-08-01

Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized method that finds optimal image-based feature sets that reduce computational time complexity while maximizing overall classification accuracy for detection of diabetic retinopathy (DR). First, region-based and pixel-based features are extracted from fundus images for classification of DR lesions and vessel-like structures. Next, feature ranking strategies are used to distinguish the optimal classification feature sets. DR lesion and vessel classification accuracies are computed using the boosted decision tree and decision forest classifiers in the Microsoft Azure Machine Learning Studio platform, respectively. For images from the DIARETDB1 data set, 40 of its highest-ranked features are used to classify four DR lesion types with an average classification accuracy of 90.1% in 792 seconds. Also, for classification of red lesion regions and hemorrhages from microaneurysms, accuracies of 85% and 72% are observed, respectively. For images from STARE data set, 40 high-ranked features can classify minor blood vessels with an accuracy of 83.5% in 326 seconds. Such cloud-based fundus image analysis systems can significantly enhance the borderline classification performances in automated screening systems.

Automatic multi-organ segmentation using learning-based segmentation and level set optimization.

PubMed

Kohlberger, Timo; Sofka, Michal; Zhang, Jingdan; Birkbeck, Neil; Wetzl, Jens; Kaftan, Jens; Declerck, Jérôme; Zhou, S Kevin

2011-01-01

We present a novel generic segmentation system for the fully automatic multi-organ segmentation from CT medical images. Thereby we combine the advantages of learning-based approaches on point cloud-based shape representation, such a speed, robustness, point correspondences, with those of PDE-optimization-based level set approaches, such as high accuracy and the straightforward prevention of segment overlaps. In a benchmark on 10-100 annotated datasets for the liver, the lungs, and the kidneys we show that the proposed system yields segmentation accuracies of 1.17-2.89 mm average surface errors. Thereby the level set segmentation (which is initialized by the learning-based segmentations) contributes with an 20%-40% increase in accuracy.

A novel method for accurate needle-tip identification in trans-rectal ultrasound-based high-dose-rate prostate brachytherapy.

PubMed

Zheng, Dandan; Todor, Dorin A

2011-01-01

In real-time trans-rectal ultrasound (TRUS)-based high-dose-rate prostate brachytherapy, the accurate identification of needle-tip position is critical for treatment planning and delivery. Currently, needle-tip identification on ultrasound images can be subject to large uncertainty and errors because of ultrasound image quality and imaging artifacts. To address this problem, we developed a method based on physical measurements with simple and practical implementation to improve the accuracy and robustness of needle-tip identification. Our method uses measurements of the residual needle length and an off-line pre-established coordinate transformation factor, to calculate the needle-tip position on the TRUS images. The transformation factor was established through a one-time systematic set of measurements of the probe and template holder positions, applicable to all patients. To compare the accuracy and robustness of the proposed method and the conventional method (ultrasound detection), based on the gold-standard X-ray fluoroscopy, extensive measurements were conducted in water and gel phantoms. In water phantom, our method showed an average tip-detection accuracy of 0.7 mm compared with 1.6 mm of the conventional method. In gel phantom (more realistic and tissue-like), our method maintained its level of accuracy while the uncertainty of the conventional method was 3.4mm on average with maximum values of over 10mm because of imaging artifacts. A novel method based on simple physical measurements was developed to accurately detect the needle-tip position for TRUS-based high-dose-rate prostate brachytherapy. The method demonstrated much improved accuracy and robustness over the conventional method. Copyright © 2011 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Explicit area-based accuracy assessment for mangrove tree crown delineation using Geographic Object-Based Image Analysis (GEOBIA)

NASA Astrophysics Data System (ADS)

Kamal, Muhammad; Johansen, Kasper

2017-10-01

Effective mangrove management requires spatially explicit information of mangrove tree crown map as a basis for ecosystem diversity study and health assessment. Accuracy assessment is an integral part of any mapping activities to measure the effectiveness of the classification approach. In geographic object-based image analysis (GEOBIA) the assessment of the geometric accuracy (shape, symmetry and location) of the created image objects from image segmentation is required. In this study we used an explicit area-based accuracy assessment to measure the degree of similarity between the results of the classification and reference data from different aspects, including overall quality (OQ), user's accuracy (UA), producer's accuracy (PA) and overall accuracy (OA). We developed a rule set to delineate the mangrove tree crown using WorldView-2 pan-sharpened image. The reference map was obtained by visual delineation of the mangrove tree crowns boundaries form a very high-spatial resolution aerial photograph (7.5cm pixel size). Ten random points with a 10 m radius circular buffer were created to calculate the area-based accuracy assessment. The resulting circular polygons were used to clip both the classified image objects and reference map for area comparisons. In this case, the area-based accuracy assessment resulted 64% and 68% for the OQ and OA, respectively. The overall quality of the calculation results shows the class-related area accuracy; which is the area of correctly classified as tree crowns was 64% out of the total area of tree crowns. On the other hand, the overall accuracy of 68% was calculated as the percentage of all correctly classified classes (tree crowns and canopy gaps) in comparison to the total class area (an entire image). Overall, the area-based accuracy assessment was simple to implement and easy to interpret. It also shows explicitly the omission and commission error variations of object boundary delineation with colour coded polygons.

Calorimetric method for determination of {sup 51}Cr neutrino source activity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Veretenkin, E. P., E-mail: veretenk@inr.ru; Gavrin, V. N.; Danshin, S. N.

Experimental study of nonstandard neutrino properties using high-intensity artificial neutrino sources requires the activity of the sources to be determined with high accuracy. In the BEST project, a calorimetric system for measurement of the activity of high-intensity (a few MCi) neutrino sources based on {sup 51}Cr with an accuracy of 0.5–1% is created. In the paper, the main factors affecting the accuracy of determining the neutrino source activity are discussed. The calorimetric system design and the calibration results using a thermal simulator of the source are presented.

a New Approach for Accuracy Improvement of Pulsed LIDAR Remote Sensing Data

NASA Astrophysics Data System (ADS)

Zhou, G.; Huang, W.; Zhou, X.; He, C.; Li, X.; Huang, Y.; Zhang, L.

2018-05-01

In remote sensing applications, the accuracy of time interval measurement is one of the most important parameters that affect the quality of pulsed lidar data. The traditional time interval measurement technique has the disadvantages of low measurement accuracy, complicated circuit structure and large error. A high-precision time interval data cannot be obtained in these traditional methods. In order to obtain higher quality of remote sensing cloud images based on the time interval measurement, a higher accuracy time interval measurement method is proposed. The method is based on charging the capacitance and sampling the change of capacitor voltage at the same time. Firstly, the approximate model of the capacitance voltage curve in the time of flight of pulse is fitted based on the sampled data. Then, the whole charging time is obtained with the fitting function. In this method, only a high-speed A/D sampler and capacitor are required in a single receiving channel, and the collected data is processed directly in the main control unit. The experimental results show that the proposed method can get error less than 3 ps. Compared with other methods, the proposed method improves the time interval accuracy by at least 20 %.

A study on low-cost, high-accuracy, and real-time stereo vision algorithms for UAV power line inspection

NASA Astrophysics Data System (ADS)

Wang, Hongyu; Zhang, Baomin; Zhao, Xun; Li, Cong; Lu, Cunyue

2018-04-01

Conventional stereo vision algorithms suffer from high levels of hardware resource utilization due to algorithm complexity, or poor levels of accuracy caused by inadequacies in the matching algorithm. To address these issues, we have proposed a stereo range-finding technique that produces an excellent balance between cost, matching accuracy and real-time performance, for power line inspection using UAV. This was achieved through the introduction of a special image preprocessing algorithm and a weighted local stereo matching algorithm, as well as the design of a corresponding hardware architecture. Stereo vision systems based on this technique have a lower level of resource usage and also a higher level of matching accuracy following hardware acceleration. To validate the effectiveness of our technique, a stereo vision system based on our improved algorithms were implemented using the Spartan 6 FPGA. In comparative experiments, it was shown that the system using the improved algorithms outperformed the system based on the unimproved algorithms, in terms of resource utilization and matching accuracy. In particular, Block RAM usage was reduced by 19%, and the improved system was also able to output range-finding data in real time.

Parallelism measurement for base plate of standard artifact with multiple tactile approaches

NASA Astrophysics Data System (ADS)

Ye, Xiuling; Zhao, Yan; Wang, Yiwen; Wang, Zhong; Fu, Luhua; Liu, Changjie

2018-01-01

Nowadays, as workpieces become more precise and more specialized which results in more sophisticated structures and higher accuracy for the artifacts, higher requirements have been put forward for measuring accuracy and measuring methods. As an important method to obtain the size of workpieces, coordinate measuring machine (CMM) has been widely used in many industries. In order to achieve the calibration of a self-developed CMM, it is found that the parallelism of the base plate used for fixing the standard artifact is an important factor which affects the measurement accuracy in the process of studying self-made high-precision standard artifact. And aimed to measure the parallelism of the base plate, by using the existing high-precision CMM, gauge blocks, dial gauge and marble platform with the tactile approach, three methods for parallelism measurement of workpieces are employed, and comparisons are made within the measurement results. The results of experiments show that the final accuracy of all the three methods is able to reach micron level and meets the measurement requirements. Simultaneously, these three approaches are suitable for different measurement conditions which provide a basis for rapid and high-precision measurement under different equipment conditions.

Rater Accuracy and Training Group Effects in Expert- and Supervisor-Based Monitoring Systems

ERIC Educational Resources Information Center

Baird, Jo-Anne; Meadows, Michelle; Leckie, George; Caro, Daniel

2017-01-01

This study evaluated rater accuracy with rater-monitoring data from high stakes examinations in England. Rater accuracy was estimated with cross-classified multilevel modelling. The data included face-to-face training and monitoring of 567 raters in 110 teams, across 22 examinations, giving a total of 5500 data points. Two rater-monitoring systems…

Experimental study of low-cost fiber optic distributed temperature sensor system performance

NASA Astrophysics Data System (ADS)

Dashkov, Michael V.; Zharkov, Alexander D.

2016-03-01

The distributed control of temperature is an actual task for various application such as oil & gas fields, high-voltage power lines, fire alarm systems etc. The most perspective are optical fiber distributed temperature sensors (DTS). They have advantages on accuracy, resolution and range, but have a high cost. Nevertheless, for some application the accuracy of measurement and localization aren't so important as cost. The results of an experimental study of low-cost Raman based DTS based on standard OTDR are represented.

Innovative use of global navigation satellite systems for flight inspection

NASA Astrophysics Data System (ADS)

Kim, Eui-Ho

The International Civil Aviation Organization (ICAO) mandates flight inspection in every country to provide safety during flight operations. Among many criteria of flight inspection, airborne inspection of Instrument Landing Systems (ILS) is very important because the ILS is the primary landing guidance system worldwide. During flight inspection of the ILS, accuracy in ILS landing guidance is checked by using a Flight Inspection System (FIS). Therefore, a flight inspection system must have high accuracy in its positioning capability to detect any deviation so that accurate guidance of the ILS can be maintained. Currently, there are two Automated Flight Inspection Systems (AFIS). One is called Inertial-based AFIS, and the other one is called Differential GPS-based (DGPS-based) AFIS. The Inertial-based AFIS enables efficient flight inspection procedures, but its drawback is high cost because it requires a navigation-grade Inertial Navigation System (INS). On the other hand, the DGPS-based AFIS has relatively low cost, but flight inspection procedures require landing and setting up a reference receiver. Most countries use either one of the systems based on their own preferences. There are around 1200 ILS in the U.S., and each ILS must be inspected every 6 to 9 months. Therefore, it is important to manage the airborne inspection of the ILS in a very efficient manner. For this reason, the Federal Aviation Administration (FAA) mainly uses the Inertial-based AFIS, which has better efficiency than the DGPS-based AFIS in spite of its high cost. Obviously, the FAA spends tremendous resources on flight inspection. This thesis investigates the value of GPS and the FAA's augmentation to GPS for civil aviation called the Wide Area Augmentation System (or WAAS) for flight inspection. Because standard GPS or WAAS position outputs cannot meet the required accuracy for flight inspection, in this thesis, various algorithms are developed to improve the positioning ability of Flight Inspection Systems (FIS) by using GPS and WAAS in novel manners. The algorithms include Adaptive Carrier Smoothing (ACS), optimizing WAAS accuracy and stability, and reference point-based precise relative positioning for real-time and near-real-time applications. The developed systems are WAAS-aided FIS, WAAS-based FIS, and stand-alone GPS-based FIS. These systems offer both high efficiency and low cost, and they have different advantages over one another in terms of accuracy, integrity, and worldwide availability. The performance of each system is tested with experimental flight test data and shown to have accuracy that is sufficient for flight inspection and superior to the current Inertial-based AFIS.

Systematic Calibration for Ultra-High Accuracy Inertial Measurement Units.

PubMed

Cai, Qingzhong; Yang, Gongliu; Song, Ningfang; Liu, Yiliang

2016-06-22

An inertial navigation system (INS) has been widely used in challenging GPS environments. With the rapid development of modern physics, an atomic gyroscope will come into use in the near future with a predicted accuracy of 5 × 10(-6)°/h or better. However, existing calibration methods and devices can not satisfy the accuracy requirements of future ultra-high accuracy inertial sensors. In this paper, an improved calibration model is established by introducing gyro g-sensitivity errors, accelerometer cross-coupling errors and lever arm errors. A systematic calibration method is proposed based on a 51-state Kalman filter and smoother. Simulation results show that the proposed calibration method can realize the estimation of all the parameters using a common dual-axis turntable. Laboratory and sailing tests prove that the position accuracy in a five-day inertial navigation can be improved about 8% by the proposed calibration method. The accuracy can be improved at least 20% when the position accuracy of the atomic gyro INS can reach a level of 0.1 nautical miles/5 d. Compared with the existing calibration methods, the proposed method, with more error sources and high order small error parameters calibrated for ultra-high accuracy inertial measurement units (IMUs) using common turntables, has a great application potential in future atomic gyro INSs.

Recollection is a continuous process: implications for dual-process theories of recognition memory.

PubMed

Mickes, Laura; Wais, Peter E; Wixted, John T

2009-04-01

Dual-process theory, which holds that recognition decisions can be based on recollection or familiarity, has long seemed incompatible with signal detection theory, which holds that recognition decisions are based on a singular, continuous memory-strength variable. Formal dual-process models typically regard familiarity as a continuous process (i.e., familiarity comes in degrees), but they construe recollection as a categorical process (i.e., recollection either occurs or does not occur). A continuous process is characterized by a graded relationship between confidence and accuracy, whereas a categorical process is characterized by a binary relationship such that high confidence is associated with high accuracy but all lower degrees of confidence are associated with chance accuracy. Using a source-memory procedure, we found that the relationship between confidence and source-recollection accuracy was graded. Because recollection, like familiarity, is a continuous process, dual-process theory is more compatible with signal detection theory than previously thought.

The research of adaptive-exposure on spot-detecting camera in ATP system

NASA Astrophysics Data System (ADS)

Qian, Feng; Jia, Jian-jun; Zhang, Liang; Wang, Jian-Yu

2013-08-01

High precision acquisition, tracking, pointing (ATP) system is one of the key techniques of laser communication. The spot-detecting camera is used to detect the direction of beacon in laser communication link, so that it can get the position information of communication terminal for ATP system. The positioning accuracy of camera decides the capability of laser communication system directly. So the spot-detecting camera in satellite-to-earth laser communication ATP systems needs high precision on target detection. The positioning accuracy of cameras should be better than +/-1μ rad . The spot-detecting cameras usually adopt centroid algorithm to get the position information of light spot on detectors. When the intensity of beacon is moderate, calculation results of centroid algorithm will be precise. But the intensity of beacon changes greatly during communication for distance, atmospheric scintillation, weather etc. The output signal of detector will be insufficient when the camera underexposes to beacon because of low light intensity. On the other hand, the output signal of detector will be saturated when the camera overexposes to beacon because of high light intensity. The calculation accuracy of centroid algorithm becomes worse if the spot-detecting camera underexposes or overexposes, and then the positioning accuracy of camera will be reduced obviously. In order to improve the accuracy, space-based cameras should regulate exposure time in real time according to light intensity. The algorithm of adaptive-exposure technique for spot-detecting camera based on metal-oxide-semiconductor (CMOS) detector is analyzed. According to analytic results, a CMOS camera in space-based laser communication system is described, which utilizes the algorithm of adaptive-exposure to adapting exposure time. Test results from imaging experiment system formed verify the design. Experimental results prove that this design can restrain the reduction of positioning accuracy for the change of light intensity. So the camera can keep stable and high positioning accuracy during communication.

Accuracy of Handheld Blood Glucose Meters at High Altitude

PubMed Central

de Vries, Suzanna T.; Fokkert, Marion J.; Dikkeschei, Bert D.; Rienks, Rienk; Bilo, Karin M.; Bilo, Henk J. G.

2010-01-01

Background Due to increasing numbers of people with diabetes taking part in extreme sports (e.g., high-altitude trekking), reliable handheld blood glucose meters (BGMs) are necessary. Accurate blood glucose measurement under extreme conditions is paramount for safe recreation at altitude. Prior studies reported bias in blood glucose measurements using different BGMs at high altitude. We hypothesized that glucose-oxidase based BGMs are more influenced by the lower atmospheric oxygen pressure at altitude than glucose dehydrogenase based BGMs. Methodology/Principal Findings Glucose measurements at simulated altitude of nine BGMs (six glucose dehydrogenase and three glucose oxidase BGMs) were compared to glucose measurement on a similar BGM at sea level and to a laboratory glucose reference method. Venous blood samples of four different glucose levels were used. Moreover, two glucose oxidase and two glucose dehydrogenase based BGMs were evaluated at different altitudes on Mount Kilimanjaro. Accuracy criteria were set at a bias <15% from reference glucose (when >6.5 mmol/L) and <1 mmol/L from reference glucose (when <6.5 mmol/L). No significant difference was observed between measurements at simulated altitude and sea level for either glucose oxidase based BGMs or glucose dehydrogenase based BGMs as a group phenomenon. Two GDH based BGMs did not meet set performance criteria. Most BGMs are generally overestimating true glucose concentration at high altitude. Conclusion At simulated high altitude all tested BGMs, including glucose oxidase based BGMs, did not show influence of low atmospheric oxygen pressure. All BGMs, except for two GDH based BGMs, performed within predefined criteria. At true high altitude one GDH based BGM had best precision and accuracy. PMID:21103399

Secondary Ion Mass Spectrometers (SIMS) for calcium isotope measurements as an application to biological samples

NASA Astrophysics Data System (ADS)

Craven, S. M.; Hoenigman, J. R.; Moddeman, W. E.

1981-11-01

The potential use of secondary ion mass spectroscopy (SIMS) to analyze biological samples for calcium isotopes is discussed. Comparison of UTI and Extranuclear based quadrupole systems is made on the basis of the analysis of CaO and calcium metal. The Extranuclear quadrupole based system is superior in resolution and sensitivity to the UTI system and is recommended. For determination of calcium isotopes to within an accuracy of a few percent a high resolution quadrupole, such as the Extranuclear, and signal averaging capability are required. Charge neutralization will be mandated for calcium oxide, calcium nitrate, or calcium oxalate. SIMS is not capable of the high precision and high accuracy results possible by thermal ionization methods, but where faster analysis is desirable with an accuracy of a few percent, SIMS is a viable alternative.

[Analysis on accuracy and influencing factors of oral fluid-based rapid HIV self-testing among men who have sex with men].

PubMed

Li, Youfang; Wang, Yumiao; Zhang, Renzhong; Wang, Jue; Li, Zhiqing; Wang, Ling; Pan, Songfeng; Yang, Yanling; Ma, Yanling; Jia, Manhong

2016-01-01

To understood the accuracy of oral fluid-based rapid HIV self-testing among men who have sex with men (MSM) and related factors. Survey was conducted among MSM selected through non-probability sampling to evaluate the quality of their rapid HIV self-testing, and related information was analyzed. The most MSM were aged 21-30 years (57.0%). Among them, 45.7% had educational level of college or above, 78.5% were unmarried, 59.3% were casual laborers. The overall accuracy rate of oral fluid based self-testing was 95.0%, the handling of"inserting test paper into tube as indicated by arrow on it"had the highest accuracy rate (98.0%), and the handling of"gently upsetting tube for 3 times"had lowest accuracy rate (65.0%); Chi-square analysis showed that educational level, no touch with middle part of test paper, whether reading the instruction carefully, whether understanding the instruction and inserting test paper into tube as indicated by the arrow on it were associated with the accuracy of oral fluid-based rapid HIV self-testing, (P<0.05). Multivariate logistic regression analysis indicated that educational level, no touch with middle part of test paper and understanding instructions were associated with the accuracy of oral fluid-based rapid HIV self-testing. The accuracy of oral fluid-based rapid HIV self-testing was high among MSM, the accuracy varied with the educational level of the MSM. Touch with the middle part of test paper or not and understanding the instructions or not might influence the accuracy of the self-testing.

Semi-Lagrangian particle methods for high-dimensional Vlasov-Poisson systems

NASA Astrophysics Data System (ADS)

Cottet, Georges-Henri

2018-07-01

This paper deals with the implementation of high order semi-Lagrangian particle methods to handle high dimensional Vlasov-Poisson systems. It is based on recent developments in the numerical analysis of particle methods and the paper focuses on specific algorithmic features to handle large dimensions. The methods are tested with uniform particle distributions in particular against a recent multi-resolution wavelet based method on a 4D plasma instability case and a 6D gravitational case. Conservation properties, accuracy and computational costs are monitored. The excellent accuracy/cost trade-off shown by the method opens new perspective for accurate simulations of high dimensional kinetic equations by particle methods.

Model-based RSA of a femoral hip stem using surface and geometrical shape models.

PubMed

Kaptein, Bart L; Valstar, Edward R; Spoor, Cees W; Stoel, Berend C; Rozing, Piet M

2006-07-01

Roentgen stereophotogrammetry (RSA) is a highly accurate three-dimensional measuring technique for assessing micromotion of orthopaedic implants. A drawback is that markers have to be attached to the implant. Model-based techniques have been developed to prevent using special marked implants. We compared two model-based RSA methods with standard marker-based RSA techniques. The first model-based RSA method used surface models, and the second method used elementary geometrical shape (EGS) models. We used a commercially available stem to perform experiments with a phantom as well as reanalysis of patient RSA radiographs. The data from the phantom experiment indicated the accuracy and precision of the elementary geometrical shape model-based RSA method is equal to marker-based RSA. For model-based RSA using surface models, the accuracy is equal to the accuracy of marker-based RSA, but its precision is worse. We found no difference in accuracy and precision between the two model-based RSA techniques in clinical data. For this particular hip stem, EGS model-based RSA is a good alternative for marker-based RSA.

Image Mosaicking Approach for a Double-Camera System in the GaoFen2 Optical Remote Sensing Satellite Based on the Big Virtual Camera.

PubMed

Cheng, Yufeng; Jin, Shuying; Wang, Mi; Zhu, Ying; Dong, Zhipeng

2017-06-20

The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy.

Modelling and Experiment Based on a Navigation System for a Cranio-Maxillofacial Surgical Robot.

PubMed

Duan, Xingguang; Gao, Liang; Wang, Yonggui; Li, Jianxi; Li, Haoyuan; Guo, Yanjun

2018-01-01

In view of the characteristics of high risk and high accuracy in cranio-maxillofacial surgery, we present a novel surgical robot system that can be used in a variety of surgeries. The surgical robot system can assist surgeons in completing biopsy of skull base lesions, radiofrequency thermocoagulation of the trigeminal ganglion, and radioactive particle implantation of skull base malignant tumors. This paper focuses on modelling and experimental analyses of the robot system based on navigation technology. Firstly, the transformation relationship between the subsystems is realized based on the quaternion and the iterative closest point registration algorithm. The hand-eye coordination model based on optical navigation is established to control the end effector of the robot moving to the target position along the planning path. The closed-loop control method, "kinematics + optics" hybrid motion control method, is presented to improve the positioning accuracy of the system. Secondly, the accuracy of the system model was tested by model experiments. And the feasibility of the closed-loop control method was verified by comparing the positioning accuracy before and after the application of the method. Finally, the skull model experiments were performed to evaluate the function of the surgical robot system. The results validate its feasibility and are consistent with the preoperative surgical planning.

Modelling and Experiment Based on a Navigation System for a Cranio-Maxillofacial Surgical Robot

PubMed Central

Duan, Xingguang; Gao, Liang; Li, Jianxi; Li, Haoyuan; Guo, Yanjun

2018-01-01

In view of the characteristics of high risk and high accuracy in cranio-maxillofacial surgery, we present a novel surgical robot system that can be used in a variety of surgeries. The surgical robot system can assist surgeons in completing biopsy of skull base lesions, radiofrequency thermocoagulation of the trigeminal ganglion, and radioactive particle implantation of skull base malignant tumors. This paper focuses on modelling and experimental analyses of the robot system based on navigation technology. Firstly, the transformation relationship between the subsystems is realized based on the quaternion and the iterative closest point registration algorithm. The hand-eye coordination model based on optical navigation is established to control the end effector of the robot moving to the target position along the planning path. The closed-loop control method, “kinematics + optics” hybrid motion control method, is presented to improve the positioning accuracy of the system. Secondly, the accuracy of the system model was tested by model experiments. And the feasibility of the closed-loop control method was verified by comparing the positioning accuracy before and after the application of the method. Finally, the skull model experiments were performed to evaluate the function of the surgical robot system. The results validate its feasibility and are consistent with the preoperative surgical planning. PMID:29599948

Parallel Reaction Monitoring: A Targeted Experiment Performed Using High Resolution and High Mass Accuracy Mass Spectrometry

PubMed Central

Rauniyar, Navin

2015-01-01

The parallel reaction monitoring (PRM) assay has emerged as an alternative method of targeted quantification. The PRM assay is performed in a high resolution and high mass accuracy mode on a mass spectrometer. This review presents the features that make PRM a highly specific and selective method for targeted quantification using quadrupole-Orbitrap hybrid instruments. In addition, this review discusses the label-based and label-free methods of quantification that can be performed with the targeted approach. PMID:26633379

Improving the accuracy of k-nearest neighbor using local mean based and distance weight

NASA Astrophysics Data System (ADS)

Syaliman, K. U.; Nababan, E. B.; Sitompul, O. S.

2018-03-01

In k-nearest neighbor (kNN), the determination of classes for new data is normally performed by a simple majority vote system, which may ignore the similarities among data, as well as allowing the occurrence of a double majority class that can lead to misclassification. In this research, we propose an approach to resolve the majority vote issues by calculating the distance weight using a combination of local mean based k-nearest neighbor (LMKNN) and distance weight k-nearest neighbor (DWKNN). The accuracy of results is compared to the accuracy acquired from the original k-NN method using several datasets from the UCI Machine Learning repository, Kaggle and Keel, such as ionosphare, iris, voice genre, lower back pain, and thyroid. In addition, the proposed method is also tested using real data from a public senior high school in city of Tualang, Indonesia. Results shows that the combination of LMKNN and DWKNN was able to increase the classification accuracy of kNN, whereby the average accuracy on test data is 2.45% with the highest increase in accuracy of 3.71% occurring on the lower back pain symptoms dataset. For the real data, the increase in accuracy is obtained as high as 5.16%.

A Rapid Coordinate Transformation Method Applied in Industrial Robot Calibration Based on Characteristic Line Coincidence.

PubMed

Liu, Bailing; Zhang, Fumin; Qu, Xinghua; Shi, Xiaojia

2016-02-18

Coordinate transformation plays an indispensable role in industrial measurements, including photogrammetry, geodesy, laser 3-D measurement and robotics. The widely applied methods of coordinate transformation are generally based on solving the equations of point clouds. Despite the high accuracy, this might result in no solution due to the use of ill conditioned matrices. In this paper, a novel coordinate transformation method is proposed, not based on the equation solution but based on the geometric transformation. We construct characteristic lines to represent the coordinate systems. According to the space geometry relation, the characteristic line scan is made to coincide by a series of rotations and translations. The transformation matrix can be obtained using matrix transformation theory. Experiments are designed to compare the proposed method with other methods. The results show that the proposed method has the same high accuracy, but the operation is more convenient and flexible. A multi-sensor combined measurement system is also presented to improve the position accuracy of a robot with the calibration of the robot kinematic parameters. Experimental verification shows that the position accuracy of robot manipulator is improved by 45.8% with the proposed method and robot calibration.

A Rapid Coordinate Transformation Method Applied in Industrial Robot Calibration Based on Characteristic Line Coincidence

PubMed Central

Liu, Bailing; Zhang, Fumin; Qu, Xinghua; Shi, Xiaojia

2016-01-01

Coordinate transformation plays an indispensable role in industrial measurements, including photogrammetry, geodesy, laser 3-D measurement and robotics. The widely applied methods of coordinate transformation are generally based on solving the equations of point clouds. Despite the high accuracy, this might result in no solution due to the use of ill conditioned matrices. In this paper, a novel coordinate transformation method is proposed, not based on the equation solution but based on the geometric transformation. We construct characteristic lines to represent the coordinate systems. According to the space geometry relation, the characteristic line scan is made to coincide by a series of rotations and translations. The transformation matrix can be obtained using matrix transformation theory. Experiments are designed to compare the proposed method with other methods. The results show that the proposed method has the same high accuracy, but the operation is more convenient and flexible. A multi-sensor combined measurement system is also presented to improve the position accuracy of a robot with the calibration of the robot kinematic parameters. Experimental verification shows that the position accuracy of robot manipulator is improved by 45.8% with the proposed method and robot calibration. PMID:26901203

Evaluating the accuracy of SHAPE-directed RNA secondary structure predictions

PubMed Central

Sükösd, Zsuzsanna; Swenson, M. Shel; Kjems, Jørgen; Heitsch, Christine E.

2013-01-01

Recent advances in RNA structure determination include using data from high-throughput probing experiments to improve thermodynamic prediction accuracy. We evaluate the extent and nature of improvements in data-directed predictions for a diverse set of 16S/18S ribosomal sequences using a stochastic model of experimental SHAPE data. The average accuracy for 1000 data-directed predictions always improves over the original minimum free energy (MFE) structure. However, the amount of improvement varies with the sequence, exhibiting a correlation with MFE accuracy. Further analysis of this correlation shows that accurate MFE base pairs are typically preserved in a data-directed prediction, whereas inaccurate ones are not. Thus, the positive predictive value of common base pairs is consistently higher than the directed prediction accuracy. Finally, we confirm sequence dependencies in the directability of thermodynamic predictions and investigate the potential for greater accuracy improvements in the worst performing test sequence. PMID:23325843

Atropos: specific, sensitive, and speedy trimming of sequencing reads.

PubMed

Didion, John P; Martin, Marcel; Collins, Francis S

2017-01-01

A key step in the transformation of raw sequencing reads into biological insights is the trimming of adapter sequences and low-quality bases. Read trimming has been shown to increase the quality and reliability while decreasing the computational requirements of downstream analyses. Many read trimming software tools are available; however, no tool simultaneously provides the accuracy, computational efficiency, and feature set required to handle the types and volumes of data generated in modern sequencing-based experiments. Here we introduce Atropos and show that it trims reads with high sensitivity and specificity while maintaining leading-edge speed. Compared to other state-of-the-art read trimming tools, Atropos achieves significant increases in trimming accuracy while remaining competitive in execution times. Furthermore, Atropos maintains high accuracy even when trimming data with elevated rates of sequencing errors. The accuracy, high performance, and broad feature set offered by Atropos makes it an appropriate choice for the pre-processing of Illumina, ABI SOLiD, and other current-generation short-read sequencing datasets. Atropos is open source and free software written in Python (3.3+) and available at https://github.com/jdidion/atropos.

Atropos: specific, sensitive, and speedy trimming of sequencing reads

PubMed Central

Collins, Francis S.

2017-01-01

A key step in the transformation of raw sequencing reads into biological insights is the trimming of adapter sequences and low-quality bases. Read trimming has been shown to increase the quality and reliability while decreasing the computational requirements of downstream analyses. Many read trimming software tools are available; however, no tool simultaneously provides the accuracy, computational efficiency, and feature set required to handle the types and volumes of data generated in modern sequencing-based experiments. Here we introduce Atropos and show that it trims reads with high sensitivity and specificity while maintaining leading-edge speed. Compared to other state-of-the-art read trimming tools, Atropos achieves significant increases in trimming accuracy while remaining competitive in execution times. Furthermore, Atropos maintains high accuracy even when trimming data with elevated rates of sequencing errors. The accuracy, high performance, and broad feature set offered by Atropos makes it an appropriate choice for the pre-processing of Illumina, ABI SOLiD, and other current-generation short-read sequencing datasets. Atropos is open source and free software written in Python (3.3+) and available at https://github.com/jdidion/atropos. PMID:28875074

Cadastral Database Positional Accuracy Improvement

NASA Astrophysics Data System (ADS)

Hashim, N. M.; Omar, A. H.; Ramli, S. N. M.; Omar, K. M.; Din, N.

2017-10-01

Positional Accuracy Improvement (PAI) is the refining process of the geometry feature in a geospatial dataset to improve its actual position. This actual position relates to the absolute position in specific coordinate system and the relation to the neighborhood features. With the growth of spatial based technology especially Geographical Information System (GIS) and Global Navigation Satellite System (GNSS), the PAI campaign is inevitable especially to the legacy cadastral database. Integration of legacy dataset and higher accuracy dataset like GNSS observation is a potential solution for improving the legacy dataset. However, by merely integrating both datasets will lead to a distortion of the relative geometry. The improved dataset should be further treated to minimize inherent errors and fitting to the new accurate dataset. The main focus of this study is to describe a method of angular based Least Square Adjustment (LSA) for PAI process of legacy dataset. The existing high accuracy dataset known as National Digital Cadastral Database (NDCDB) is then used as bench mark to validate the results. It was found that the propose technique is highly possible for positional accuracy improvement of legacy spatial datasets.

Vertical Accuracy Evaluation of Aster GDEM2 Over a Mountainous Area Based on Uav Photogrammetry

NASA Astrophysics Data System (ADS)

Liang, Y.; Qu, Y.; Guo, D.; Cui, T.

2018-05-01

Global digital elevation models (GDEM) provide elementary information on heights of the Earth's surface and objects on the ground. GDEMs have become an important data source for a range of applications. The vertical accuracy of a GDEM is critical for its applications. Nowadays UAVs has been widely used for large-scale surveying and mapping. Compared with traditional surveying techniques, UAV photogrammetry are more convenient and more cost-effective. UAV photogrammetry produces the DEM of the survey area with high accuracy and high spatial resolution. As a result, DEMs resulted from UAV photogrammetry can be used for a more detailed and accurate evaluation of the GDEM product. This study investigates the vertical accuracy (in terms of elevation accuracy and systematic errors) of the ASTER GDEM Version 2 dataset over a complex terrain based on UAV photogrammetry. Experimental results show that the elevation errors of ASTER GDEM2 are in normal distribution and the systematic error is quite small. The accuracy of the ASTER GDEM2 coincides well with that reported by the ASTER validation team. The accuracy in the research area is negatively correlated to both the slope of the terrain and the number of stereo observations. This study also evaluates the vertical accuracy of the up-sampled ASTER GDEM2. Experimental results show that the accuracy of the up-sampled ASTER GDEM2 data in the research area is not significantly reduced by the complexity of the terrain. The fine-grained accuracy evaluation of the ASTER GDEM2 is informative for the GDEM-supported UAV photogrammetric applications.

1-D grating based SPR biosensor for the detection of lung cancer biomarkers using Vroman effect

NASA Astrophysics Data System (ADS)

Teotia, Pradeep Kumar; Kaler, R. S.

2018-01-01

Grating based surface plasmon resonance waveguide biosensor have been reported for the detection of lung cancer biomarkers using Vroman effect. The proposed grating based multilayered biosensor is designed with high detection accuracy for Epidermal growth factor receptor (EGFR) and also analysed to show high detection accuracy with acceptable sensitivity for both cancer biomarkers. The introduction of periodic grating with multilayer metals generates a good resonance that make it possible for early detection of cancerous cells. Using finite difference time domain method, it is observed wavelength of biosensor get red-shifted on variations of the refractive index due to the presence of both the cancerous bio-markers. The reported detection accuracy and sensitivity of proposed biosensor is quite acceptable for both lung cancer biomarkers i.e. Carcinoembryonic antigen (CEA) and Epidermal growth factor receptor (EGFR) which further offer us label free early detection of lung cancer using these biomarkers.

Secondary ion mass spectrometers (SIMS) for calcium isotope measurements as an application to biological samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Craven, S.M.; Hoenigman, J.R.; Moddeman, W.E.

1981-11-20

The potential use of secondary ion mass spectroscopy (SIMS) to analyze biological samples for calcium isotopes is discussed. Comparison of UTI and Extranuclear based quadrupole systems is made on the basis of the analysis of CaO and calcium metal. The Extranuclear quadrupole based system is superior in resolution and sensitivity to the UTI system and is recommended. For determination of calcium isotopes to within an accuracy of a few percent a high resolution quadrupole, such as the Extranuclear, and signal averaging capability are required. Charge neutralization will be mandated for calcium oxide, calcium nitrate, or calcium oxalate. SIMS is notmore » capable of the high precision and high accuracy results possible by thermal ionization methods, but where faster analysis is desirable with an accuracy of a few percent, SIMS is a viable alternative.« less

Validating continuous digital light processing (cDLP) additive manufacturing accuracy and tissue engineering utility of a dye-initiator package.

PubMed

Wallace, Jonathan; Wang, Martha O; Thompson, Paul; Busso, Mallory; Belle, Vaijayantee; Mammoser, Nicole; Kim, Kyobum; Fisher, John P; Siblani, Ali; Xu, Yueshuo; Welter, Jean F; Lennon, Donald P; Sun, Jiayang; Caplan, Arnold I; Dean, David

2014-03-01

This study tested the accuracy of tissue engineering scaffold rendering via the continuous digital light processing (cDLP) light-based additive manufacturing technology. High accuracy (i.e., <50 µm) allows the designed performance of features relevant to three scale spaces: cell-scaffold, scaffold-tissue, and tissue-organ interactions. The biodegradable polymer poly (propylene fumarate) was used to render highly accurate scaffolds through the use of a dye-initiator package, TiO2 and bis (2,4,6-trimethylbenzoyl)phenylphosphine oxide. This dye-initiator package facilitates high accuracy in the Z dimension. Linear, round, and right-angle features were measured to gauge accuracy. Most features showed accuracies between 5.4-15% of the design. However, one feature, an 800 µm diameter circular pore, exhibited a 35.7% average reduction of patency. Light scattered in the x, y directions by the dye may have reduced this feature's accuracy. Our new fine-grained understanding of accuracy could be used to make further improvements by including corrections in the scaffold design software. Successful cell attachment occurred with both canine and human mesenchymal stem cells (MSCs). Highly accurate cDLP scaffold rendering is critical to the design of scaffolds that both guide bone regeneration and that fully resorb. Scaffold resorption must occur for regenerated bone to be remodeled and, thereby, achieve optimal strength.

An accurate online calibration system based on combined clamp-shape coil for high voltage electronic current transformers.

PubMed

Li, Zhen-hua; Li, Hong-bin; Zhang, Zhi

2013-07-01

Electronic transformers are widely used in power systems because of their wide bandwidth and good transient performance. However, as an emerging technology, the failure rate of electronic transformers is higher than that of traditional transformers. As a result, the calibration period needs to be shortened. Traditional calibration methods require the power of transmission line be cut off, which results in complicated operation and power off loss. This paper proposes an online calibration system which can calibrate electronic current transformers without power off. In this work, the high accuracy standard current transformer and online operation method are the key techniques. Based on the clamp-shape iron-core coil and clamp-shape air-core coil, a combined clamp-shape coil is designed as the standard current transformer. By analyzing the output characteristics of the two coils, the combined clamp-shape coil can achieve verification of the accuracy. So the accuracy of the online calibration system can be guaranteed. Moreover, by employing the earth potential working method and using two insulating rods to connect the combined clamp-shape coil to the high voltage bus, the operation becomes simple and safe. Tests in China National Center for High Voltage Measurement and field experiments show that the proposed system has a high accuracy of up to 0.05 class.

Individual Patient Diagnosis of AD and FTD via High-Dimensional Pattern Classification of MRI

PubMed Central

Davatzikos, C.; Resnick, S. M.; Wu, X.; Parmpi, P.; Clark, C. M.

2008-01-01

The purpose of this study is to determine the diagnostic accuracy of MRI-based high-dimensional pattern classification in differentiating between patients with Alzheimer’s Disease (AD), Frontotemporal Dementia (FTD), and healthy controls, on an individual patient basis. MRI scans of 37 patients with AD and 37 age-matched cognitively normal elderly individuals, as well as 12 patients with FTD and 12 age-matched cognitively normal elderly individuals, were analyzed using voxel-based analysis and high-dimensional pattern classification. Diagnostic sensitivity and specificity of spatial patterns of regional brain atrophy found to be characteristic of AD and FTD were determined via cross-validation and via split-sample methods. Complex spatial patterns of relatively reduced brain volumes were identified, including temporal, orbitofrontal, parietal and cingulate regions, which were predominantly characteristic of either AD or FTD. These patterns provided 100% diagnostic accuracy, when used to separate AD or FTD from healthy controls. The ability to correctly distinguish AD from FTD averaged 84.3%. All estimates of diagnostic accuracy were determined via cross-validation. In conclusion, AD- and FTD-specific patterns of brain atrophy can be detected with high accuracy using high-dimensional pattern classification of MRI scans obtained in a typical clinical setting. PMID:18474436

Accuracy evaluation of 3D lidar data from small UAV

NASA Astrophysics Data System (ADS)

Tulldahl, H. M.; Bissmarck, Fredrik; Larsson, Hâkan; Grönwall, Christina; Tolt, Gustav

2015-10-01

A UAV (Unmanned Aerial Vehicle) with an integrated lidar can be an efficient system for collection of high-resolution and accurate three-dimensional (3D) data. In this paper we evaluate the accuracy of a system consisting of a lidar sensor on a small UAV. High geometric accuracy in the produced point cloud is a fundamental qualification for detection and recognition of objects in a single-flight dataset as well as for change detection using two or several data collections over the same scene. Our work presented here has two purposes: first to relate the point cloud accuracy to data processing parameters and second, to examine the influence on accuracy from the UAV platform parameters. In our work, the accuracy is numerically quantified as local surface smoothness on planar surfaces, and as distance and relative height accuracy using data from a terrestrial laser scanner as reference. The UAV lidar system used is the Velodyne HDL-32E lidar on a multirotor UAV with a total weight of 7 kg. For processing of data into a geographically referenced point cloud, positioning and orientation of the lidar sensor is based on inertial navigation system (INS) data combined with lidar data. The combination of INS and lidar data is achieved in a dynamic calibration process that minimizes the navigation errors in six degrees of freedom, namely the errors of the absolute position (x, y, z) and the orientation (pitch, roll, yaw) measured by GPS/INS. Our results show that low-cost and light-weight MEMS based (microelectromechanical systems) INS equipment with a dynamic calibration process can obtain significantly improved accuracy compared to processing based solely on INS data.

On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP.

PubMed

Winkler, Irene; Debener, Stefan; Müller, Klaus-Robert; Tangermann, Michael

2015-01-01

Standard artifact removal methods for electroencephalographic (EEG) signals are either based on Independent Component Analysis (ICA) or they regress out ocular activity measured at electrooculogram (EOG) channels. Successful ICA-based artifact reduction relies on suitable pre-processing. Here we systematically evaluate the effects of high-pass filtering at different frequencies. Offline analyses were based on event-related potential data from 21 participants performing a standard auditory oddball task and an automatic artifactual component classifier method (MARA). As a pre-processing step for ICA, high-pass filtering between 1-2 Hz consistently produced good results in terms of signal-to-noise ratio (SNR), single-trial classification accuracy and the percentage of `near-dipolar' ICA components. Relative to no artifact reduction, ICA-based artifact removal significantly improved SNR and classification accuracy. This was not the case for a regression-based approach to remove EOG artifacts.

Detecting exact breakpoints of deletions with diversity in hepatitis B viral genomic DNA from next-generation sequencing data.

PubMed

Cheng, Ji-Hong; Liu, Wen-Chun; Chang, Ting-Tsung; Hsieh, Sun-Yuan; Tseng, Vincent S

2017-10-01

Many studies have suggested that deletions of Hepatitis B Viral (HBV) are associated with the development of progressive liver diseases, even ultimately resulting in hepatocellular carcinoma (HCC). Among the methods for detecting deletions from next-generation sequencing (NGS) data, few methods considered the characteristics of virus, such as high evolution rates and high divergence among the different HBV genomes. Sequencing high divergence HBV genome sequences using the NGS technology outputs millions of reads. Thus, detecting exact breakpoints of deletions from these big and complex data incurs very high computational cost. We proposed a novel analytical method named VirDelect (Virus Deletion Detect), which uses split read alignment base to detect exact breakpoint and diversity variable to consider high divergence in single-end reads data, such that the computational cost can be reduced without losing accuracy. We use four simulated reads datasets and two real pair-end reads datasets of HBV genome sequence to verify VirDelect accuracy by score functions. The experimental results show that VirDelect outperforms the state-of-the-art method Pindel in terms of accuracy score for all simulated datasets and VirDelect had only two base errors even in real datasets. VirDelect is also shown to deliver high accuracy in analyzing the single-end read data as well as pair-end data. VirDelect can serve as an effective and efficient bioinformatics tool for physiologists with high accuracy and efficient performance and applicable to further analysis with characteristics similar to HBV on genome length and high divergence. The software program of VirDelect can be downloaded at https://sourceforge.net/projects/virdelect/. Copyright © 2017. Published by Elsevier Inc.

Normed kernel function-based fuzzy possibilistic C-means (NKFPCM) algorithm for high-dimensional breast cancer database classification with feature selection is based on Laplacian Score

NASA Astrophysics Data System (ADS)

Lestari, A. W.; Rustam, Z.

2017-07-01

In the last decade, breast cancer has become the focus of world attention as this disease is one of the primary leading cause of death for women. Therefore, it is necessary to have the correct precautions and treatment. In previous studies, Fuzzy Kennel K-Medoid algorithm has been used for multi-class data. This paper proposes an algorithm to classify the high dimensional data of breast cancer using Fuzzy Possibilistic C-means (FPCM) and a new method based on clustering analysis using Normed Kernel Function-Based Fuzzy Possibilistic C-Means (NKFPCM). The objective of this paper is to obtain the best accuracy in classification of breast cancer data. In order to improve the accuracy of the two methods, the features candidates are evaluated using feature selection, where Laplacian Score is used. The results show the comparison accuracy and running time of FPCM and NKFPCM with and without feature selection.

Recent advances in laser triangulation-based measurement of airfoil surfaces

NASA Astrophysics Data System (ADS)

Hageniers, Omer L.

1995-01-01

The measurement of aircraft jet engine turbine and compressor blades requires a high degree of accuracy. This paper will address the development and performance attributes of a noncontact electro-optical gaging system specifically designed to meet the airfoil dimensional measurement requirements inherent in turbine and compressor blade manufacture and repair. The system described consists of the following key components: a high accuracy, dual channel, laser based optical sensor, a four degree of freedom mechanical manipulator system and a computer based operator interface. Measurement modes of the system include point by point data gathering at rates up to 3 points per second and an 'on-the-fly' mode where points can be gathered at data rates up to 20 points per second at surface scanning speeds of up to 1 inch per second. Overall system accuracy is +/- 0.0005 inches in a configuration that is useable in the blade manufacturing area. The systems ability to input design data from CAD data bases and output measurement data in a CAD compatible data format is discussed.

Influence of Waveform Characteristics on LiDAR Ranging Accuracy and Precision

PubMed Central

Yang, Bingwei; Xie, Xinhao; Li, Duan

2018-01-01

Time of flight (TOF) based light detection and ranging (LiDAR) is a technology for calculating distance between start/stop signals of time of flight. In lab-built LiDAR, two ranging systems for measuring flying time between start/stop signals include time-to-digital converter (TDC) that counts time between trigger signals and analog-to-digital converter (ADC) that processes the sampled start/stop pulses waveform for time estimation. We study the influence of waveform characteristics on range accuracy and precision of two kinds of ranging system. Comparing waveform based ranging (WR) with analog discrete return system based ranging (AR), a peak detection method (WR-PK) shows the best ranging performance because of less execution time, high ranging accuracy, and stable precision. Based on a novel statistic mathematical method maximal information coefficient (MIC), WR-PK precision has a high linear relationship with the received pulse width standard deviation. Thus keeping the received pulse width of measuring a constant distance as stable as possible can improve ranging precision. PMID:29642639

Radiometric calibration of hyper-spectral imaging spectrometer based on optimizing multi-spectral band selection

NASA Astrophysics Data System (ADS)

Sun, Li-wei; Ye, Xin; Fang, Wei; He, Zhen-lei; Yi, Xiao-long; Wang, Yu-peng

2017-11-01

Hyper-spectral imaging spectrometer has high spatial and spectral resolution. Its radiometric calibration needs the knowledge of the sources used with high spectral resolution. In order to satisfy the requirement of source, an on-orbit radiometric calibration method is designed in this paper. This chain is based on the spectral inversion accuracy of the calibration light source. We compile the genetic algorithm progress which is used to optimize the channel design of the transfer radiometer and consider the degradation of the halogen lamp, thus realizing the high accuracy inversion of spectral curve in the whole working time. The experimental results show the average root mean squared error is 0.396%, the maximum root mean squared error is 0.448%, and the relative errors at all wavelengths are within 1% in the spectral range from 500 nm to 900 nm during 100 h operating time. The design lays a foundation for the high accuracy calibration of imaging spectrometer.

Vibration extraction based on fast NCC algorithm and high-speed camera.

PubMed

Lei, Xiujun; Jin, Yi; Guo, Jie; Zhu, Chang'an

2015-09-20

In this study, a high-speed camera system is developed to complete the vibration measurement in real time and to overcome the mass introduced by conventional contact measurements. The proposed system consists of a notebook computer and a high-speed camera which can capture the images as many as 1000 frames per second. In order to process the captured images in the computer, the normalized cross-correlation (NCC) template tracking algorithm with subpixel accuracy is introduced. Additionally, a modified local search algorithm based on the NCC is proposed to reduce the computation time and to increase efficiency significantly. The modified algorithm can rapidly accomplish one displacement extraction 10 times faster than the traditional template matching without installing any target panel onto the structures. Two experiments were carried out under laboratory and outdoor conditions to validate the accuracy and efficiency of the system performance in practice. The results demonstrated the high accuracy and efficiency of the camera system in extracting vibrating signals.

A Framework Based on Reference Data with Superordinate Accuracy for the Quality Analysis of Terrestrial Laser Scanning-Based Multi-Sensor-Systems.

PubMed

Stenz, Ulrich; Hartmann, Jens; Paffenholz, Jens-André; Neumann, Ingo

2017-08-16

Terrestrial laser scanning (TLS) is an efficient solution to collect large-scale data. The efficiency can be increased by combining TLS with additional sensors in a TLS-based multi-sensor-system (MSS). The uncertainty of scanned points is not homogenous and depends on many different influencing factors. These include the sensor properties, referencing, scan geometry (e.g., distance and angle of incidence), environmental conditions (e.g., atmospheric conditions) and the scanned object (e.g., material, color and reflectance, etc.). The paper presents methods, infrastructure and results for the validation of the suitability of TLS and TLS-based MSS. Main aspects are the backward modelling of the uncertainty on the basis of reference data (e.g., point clouds) with superordinate accuracy and the appropriation of a suitable environment/infrastructure (e.g., the calibration process of the targets for the registration of laser scanner and laser tracker data in a common coordinate system with high accuracy) In this context superordinate accuracy means that the accuracy of the acquired reference data is better by a factor of 10 than the data of the validated TLS and TLS-based MSS. These aspects play an important role in engineering geodesy, where the aimed accuracy lies in a range of a few mm or less.

A Novel Multi-Aperture Based Sun Sensor Based on a Fast Multi-Point MEANSHIFT (FMMS) Algorithm

PubMed Central

You, Zheng; Sun, Jian; Xing, Fei; Zhang, Gao-Fei

2011-01-01

With the current increased widespread interest in the development and applications of micro/nanosatellites, it was found that we needed to design a small high accuracy satellite attitude determination system, because the star trackers widely used in large satellites are large and heavy, and therefore not suitable for installation on micro/nanosatellites. A Sun sensor + magnetometer is proven to be a better alternative, but the conventional sun sensor has low accuracy, and cannot meet the requirements of the attitude determination systems of micro/nanosatellites, so the development of a small high accuracy sun sensor with high reliability is very significant. This paper presents a multi-aperture based sun sensor, which is composed of a micro-electro-mechanical system (MEMS) mask with 36 apertures and an active pixels sensor (APS) CMOS placed below the mask at a certain distance. A novel fast multi-point MEANSHIFT (FMMS) algorithm is proposed to improve the accuracy and reliability, the two key performance features, of an APS sun sensor. When the sunlight illuminates the sensor, a sun spot array image is formed on the APS detector. Then the sun angles can be derived by analyzing the aperture image location on the detector via the FMMS algorithm. With this system, the centroid accuracy of the sun image can reach 0.01 pixels, without increasing the weight and power consumption, even when some missing apertures and bad pixels appear on the detector due to aging of the devices and operation in a harsh space environment, while the pointing accuracy of the single-aperture sun sensor using the conventional correlation algorithm is only 0.05 pixels. PMID:22163770

Robust vehicle detection under various environments to realize road traffic flow surveillance using an infrared thermal camera.

PubMed

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2015-01-01

To realize road traffic flow surveillance under various environments which contain poor visibility conditions, we have already proposed two vehicle detection methods using thermal images taken with an infrared thermal camera. The first method uses pattern recognition for the windshields and their surroundings to detect vehicles. However, the first method decreases the vehicle detection accuracy in winter season. To maintain high vehicle detection accuracy in all seasons, we developed the second method. The second method uses tires' thermal energy reflection areas on a road as the detection targets. The second method did not achieve high detection accuracy for vehicles on left-hand and right-hand lanes except for two center-lanes. Therefore, we have developed a new method based on the second method to increase the vehicle detection accuracy. This paper proposes the new method and shows that the detection accuracy for vehicles on all lanes is 92.1%. Therefore, by combining the first method and the new method, high vehicle detection accuracies are maintained under various environments, and road traffic flow surveillance can be realized.

Robust Vehicle Detection under Various Environments to Realize Road Traffic Flow Surveillance Using an Infrared Thermal Camera

PubMed Central

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2015-01-01

To realize road traffic flow surveillance under various environments which contain poor visibility conditions, we have already proposed two vehicle detection methods using thermal images taken with an infrared thermal camera. The first method uses pattern recognition for the windshields and their surroundings to detect vehicles. However, the first method decreases the vehicle detection accuracy in winter season. To maintain high vehicle detection accuracy in all seasons, we developed the second method. The second method uses tires' thermal energy reflection areas on a road as the detection targets. The second method did not achieve high detection accuracy for vehicles on left-hand and right-hand lanes except for two center-lanes. Therefore, we have developed a new method based on the second method to increase the vehicle detection accuracy. This paper proposes the new method and shows that the detection accuracy for vehicles on all lanes is 92.1%. Therefore, by combining the first method and the new method, high vehicle detection accuracies are maintained under various environments, and road traffic flow surveillance can be realized. PMID:25763384

Variation of Static-PPP Positioning Accuracy Using GPS-Single Frequency Observations (Aswan, Egypt)

NASA Astrophysics Data System (ADS)

Farah, Ashraf

2017-06-01

Precise Point Positioning (PPP) is a technique used for position computation with a high accuracy using only one GNSS receiver. It depends on highly accurate satellite position and clock data rather than broadcast ephemeries. PPP precision varies based on positioning technique (static or kinematic), observations type (single or dual frequency) and the duration of collected observations. PPP-(dual frequency receivers) offers comparable accuracy to differential GPS. PPP-single frequency receivers has many applications such as infrastructure, hydrography and precision agriculture. PPP using low cost GPS single-frequency receivers is an area of great interest for millions of users in developing countries such as Egypt. This research presents a study for the variability of single frequency static GPS-PPP precision based on different observation durations.

From 16-bit to high-accuracy IDCT approximation: fruits of single architecture affliation

NASA Astrophysics Data System (ADS)

Liu, Lijie; Tran, Trac D.; Topiwala, Pankaj

2007-09-01

In this paper, we demonstrate an effective unified framework for high-accuracy approximation of the irrational co-effcient floating-point IDCT by a single integer-coeffcient fixed-point architecture. Our framework is based on a modified version of the Loeffler's sparse DCT factorization, and the IDCT architecture is constructed via a cascade of dyadic lifting steps and butterflies. We illustrate that simply varying the accuracy of the approximating parameters yields a large family of standard-compliant IDCTs, from rare 16-bit approximations catering to portable computing to ultra-high-accuracy 32-bit versions that virtually eliminate any drifting effect when pairing with the 64-bit floating-point IDCT at the encoder. Drifting performances of the proposed IDCTs along with existing popular IDCT algorithms in H.263+, MPEG-2 and MPEG-4 are also demonstrated.

Genomic selection accuracies within and between environments and small breeding groups in white spruce.

PubMed

Beaulieu, Jean; Doerksen, Trevor K; MacKay, John; Rainville, André; Bousquet, Jean

2014-12-02

Genomic selection (GS) may improve selection response over conventional pedigree-based selection if markers capture more detailed information than pedigrees in recently domesticated tree species and/or make it more cost effective. Genomic prediction accuracies using 1748 trees and 6932 SNPs representative of as many distinct gene loci were determined for growth and wood traits in white spruce, within and between environments and breeding groups (BG), each with an effective size of Ne ≈ 20. Marker subsets were also tested. Model fits and/or cross-validation (CV) prediction accuracies for ridge regression (RR) and the least absolute shrinkage and selection operator models approached those of pedigree-based models. With strong relatedness between CV sets, prediction accuracies for RR within environment and BG were high for wood (r = 0.71-0.79) and moderately high for growth (r = 0.52-0.69) traits, in line with trends in heritabilities. For both classes of traits, these accuracies achieved between 83% and 92% of those obtained with phenotypes and pedigree information. Prediction into untested environments remained moderately high for wood (r ≥ 0.61) but dropped significantly for growth (r ≥ 0.24) traits, emphasizing the need to phenotype in all test environments and model genotype-by-environment interactions for growth traits. Removing relatedness between CV sets sharply decreased prediction accuracies for all traits and subpopulations, falling near zero between BGs with no known shared ancestry. For marker subsets, similar patterns were observed but with lower prediction accuracies. Given the need for high relatedness between CV sets to obtain good prediction accuracies, we recommend to build GS models for prediction within the same breeding population only. Breeding groups could be merged to build genomic prediction models as long as the total effective population size does not exceed 50 individuals in order to obtain high prediction accuracy such as that obtained in the present study. A number of markers limited to a few hundred would not negatively impact prediction accuracies, but these could decrease more rapidly over generations. The most promising short-term approach for genomic selection would likely be the selection of superior individuals within large full-sib families vegetatively propagated to implement multiclonal forestry.

SU-F-J-95: Impact of Shape Complexity On the Accuracy of Gradient-Based PET Volume Delineation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dance, M; Wu, G; Gao, Y

2016-06-15

Purpose: Explore correlation of tumor complexity shape with PET target volume accuracy when delineated with gradient-based segmentation tool. Methods: A total of 24 clinically realistic digital PET Monte Carlo (MC) phantoms of NSCLC were used in the study. The phantom simulated 29 thoracic lesions (lung primary and mediastinal lymph nodes) of varying size, shape, location, and {sup 18}F-FDG activity. A program was developed to calculate a curvature vector along the outline and the standard deviation of this vector was used as a metric to quantify a shape’s “complexity score”. This complexity score was calculated for standard geometric shapes and MC-generatedmore » target volumes in PET phantom images. All lesions were contoured using a commercially available gradient-based segmentation tool and the differences in volume from the MC-generated volumes were calculated as the measure of the accuracy of segmentation. Results: The average absolute percent difference in volumes between the MC-volumes and gradient-based volumes was 11% (0.4%–48.4%). The complexity score showed strong correlation with standard geometric shapes. However, no relationship was found between the complexity score and the accuracy of segmentation by gradient-based tool on MC simulated tumors (R{sup 2} = 0.156). When the lesions were grouped into primary lung lesions and mediastinal/mediastinal adjacent lesions, the average absolute percent difference in volumes were 6% and 29%, respectively. The former group is more isolated and the latter is more surround by tissues with relatively high SUV background. Conclusion: The complexity shape of NSCLC lesions has little effect on the accuracy of the gradient-based segmentation method and thus is not a good predictor of uncertainty in target volume delineation. Location of lesion within a relatively high SUV background may play a more significant role in the accuracy of gradient-based segmentation.« less

SVM classifier on chip for melanoma detection.

PubMed

Afifi, Shereen; GholamHosseini, Hamid; Sinha, Roopak

2017-07-01

Support Vector Machine (SVM) is a common classifier used for efficient classification with high accuracy. SVM shows high accuracy for classifying melanoma (skin cancer) clinical images within computer-aided diagnosis systems used by skin cancer specialists to detect melanoma early and save lives. We aim to develop a medical low-cost handheld device that runs a real-time embedded SVM-based diagnosis system for use in primary care for early detection of melanoma. In this paper, an optimized SVM classifier is implemented onto a recent FPGA platform using the latest design methodology to be embedded into the proposed device for realizing online efficient melanoma detection on a single system on chip/device. The hardware implementation results demonstrate a high classification accuracy of 97.9% and a significant acceleration factor of 26 from equivalent software implementation on an embedded processor, with 34% of resources utilization and 2 watts for power consumption. Consequently, the implemented system meets crucial embedded systems constraints of high performance and low cost, resources utilization and power consumption, while achieving high classification accuracy.

Accuracy of a hexapod parallel robot kinematics based external fixator.

PubMed

Faschingbauer, Maximilian; Heuer, Hinrich J D; Seide, Klaus; Wendlandt, Robert; Münch, Matthias; Jürgens, Christian; Kirchner, Rainer

2015-12-01

Different hexapod-based external fixators are increasingly used to treat bone deformities and fractures. Accuracy has not been measured sufficiently for all models. An infrared tracking system was applied to measure positioning maneuvers with a motorized Precision Hexapod® fixator, detecting three-dimensional positions of reflective balls mounted in an L-arrangement on the fixator, simulating bone directions. By omitting one dimension of the coordinates, projections were simulated as if measured on standard radiographs. Accuracy was calculated as the absolute difference between targeted and measured positioning values. In 149 positioning maneuvers, the median values for positioning accuracy of translations and rotations (torsions/angulations) were below 0.3 mm and 0.2° with quartiles ranging from -0.5 mm to 0.5 mm and -1.0° to 0.9°, respectively. The experimental setup was found to be precise and reliable. It can be applied to compare different hexapod-based fixators. Accuracy of the investigated hexapod system was high. Copyright © 2014 John Wiley & Sons, Ltd.

Investigation of Portevin-Le Chatelier effect in 5456 Al-based alloy using digital image correlation

NASA Astrophysics Data System (ADS)

Cheng, Teng; Xu, Xiaohai; Cai, Yulong; Fu, Shihua; Gao, Yue; Su, Yong; Zhang, Yong; Zhang, Qingchuan

2015-02-01

A variety of experimental methods have been proposed for Portevin-Le Chatelier (PLC) effect. They mainly focused on the in-plane deformation. In order to achieve the high-accuracy measurement, three-dimensional digital image correlation (3D-DIC) was employed in this work to investigate the PLC effect in 5456 Al-based alloy. The temporal and spatial evolutions of deformation in the full field of specimen surface were observed. The large deformation of localized necking was determined experimentally. The distributions of out-of-plane displacement over the loading procedure were also obtained. Furthermore, a comparison of measurement accuracy between two-dimensional digital image correlation (2D-DIC) and 3D-DIC was also performed. Due to the theoretical restriction, the measurement accuracy of 2D-DIC decreases with the increase of deformation. A maximum discrepancy of about 20% with 3D-DIC was observed in this work. Therefore, 3D-DIC is actually more essential for the high-accuracy investigation of PLC effect.

Supervised segmentation of microelectrode recording artifacts using power spectral density.

PubMed

Bakstein, Eduard; Schneider, Jakub; Sieger, Tomas; Novak, Daniel; Wild, Jiri; Jech, Robert

2015-08-01

Appropriate detection of clean signal segments in extracellular microelectrode recordings (MER) is vital for maintaining high signal-to-noise ratio in MER studies. Existing alternatives to manual signal inspection are based on unsupervised change-point detection. We present a method of supervised MER artifact classification, based on power spectral density (PSD) and evaluate its performance on a database of 95 labelled MER signals. The proposed method yielded test-set accuracy of 90%, which was close to the accuracy of annotation (94%). The unsupervised methods achieved accuracy of about 77% on both training and testing data.

Decomposed multidimensional control grid interpolation for common consumer electronic image processing applications

NASA Astrophysics Data System (ADS)

Zwart, Christine M.; Venkatesan, Ragav; Frakes, David H.

2012-10-01

Interpolation is an essential and broadly employed function of signal processing. Accordingly, considerable development has focused on advancing interpolation algorithms toward optimal accuracy. Such development has motivated a clear shift in the state-of-the art from classical interpolation to more intelligent and resourceful approaches, registration-based interpolation for example. As a natural result, many of the most accurate current algorithms are highly complex, specific, and computationally demanding. However, the diverse hardware destinations for interpolation algorithms present unique constraints that often preclude use of the most accurate available options. For example, while computationally demanding interpolators may be suitable for highly equipped image processing platforms (e.g., computer workstations and clusters), only more efficient interpolators may be practical for less well equipped platforms (e.g., smartphones and tablet computers). The latter examples of consumer electronics present a design tradeoff in this regard: high accuracy interpolation benefits the consumer experience but computing capabilities are limited. It follows that interpolators with favorable combinations of accuracy and efficiency are of great practical value to the consumer electronics industry. We address multidimensional interpolation-based image processing problems that are common to consumer electronic devices through a decomposition approach. The multidimensional problems are first broken down into multiple, independent, one-dimensional (1-D) interpolation steps that are then executed with a newly modified registration-based one-dimensional control grid interpolator. The proposed approach, decomposed multidimensional control grid interpolation (DMCGI), combines the accuracy of registration-based interpolation with the simplicity, flexibility, and computational efficiency of a 1-D interpolation framework. Results demonstrate that DMCGI provides improved interpolation accuracy (and other benefits) in image resizing, color sample demosaicing, and video deinterlacing applications, at a computational cost that is manageable or reduced in comparison to popular alternatives.

A Novel Multi-Digital Camera System Based on Tilt-Shift Photography Technology

PubMed Central

Sun, Tao; Fang, Jun-yong; Zhao, Dong; Liu, Xue; Tong, Qing-xi

2015-01-01

Multi-digital camera systems (MDCS) are constantly being improved to meet the increasing requirement of high-resolution spatial data. This study identifies the insufficiencies of traditional MDCSs and proposes a new category MDCS based on tilt-shift photography to improve ability of the MDCS to acquire high-accuracy spatial data. A prototype system, including two or four tilt-shift cameras (TSC, camera model: Nikon D90), is developed to validate the feasibility and correctness of proposed MDCS. Similar to the cameras of traditional MDCSs, calibration is also essential for TSC of new MDCS. The study constructs indoor control fields and proposes appropriate calibration methods for TSC, including digital distortion model (DDM) approach and two-step calibrated strategy. The characteristics of TSC are analyzed in detail via a calibration experiment; for example, the edge distortion of TSC. Finally, the ability of the new MDCS to acquire high-accuracy spatial data is verified through flight experiments. The results of flight experiments illustrate that geo-position accuracy of prototype system achieves 0.3 m at a flight height of 800 m, and spatial resolution of 0.15 m. In addition, results of the comparison between the traditional (MADC II) and proposed MDCS demonstrate that the latter (0.3 m) provides spatial data with higher accuracy than the former (only 0.6 m) under the same conditions. We also take the attitude that using higher accuracy TSC in the new MDCS should further improve the accuracy of the photogrammetry senior product. PMID:25835187

A novel multi-digital camera system based on tilt-shift photography technology.

PubMed

Sun, Tao; Fang, Jun-Yong; Zhao, Dong; Liu, Xue; Tong, Qing-Xi

2015-03-31

Multi-digital camera systems (MDCS) are constantly being improved to meet the increasing requirement of high-resolution spatial data. This study identifies the insufficiencies of traditional MDCSs and proposes a new category MDCS based on tilt-shift photography to improve ability of the MDCS to acquire high-accuracy spatial data. A prototype system, including two or four tilt-shift cameras (TSC, camera model: Nikon D90), is developed to validate the feasibility and correctness of proposed MDCS. Similar to the cameras of traditional MDCSs, calibration is also essential for TSC of new MDCS. The study constructs indoor control fields and proposes appropriate calibration methods for TSC, including digital distortion model (DDM) approach and two-step calibrated strategy. The characteristics of TSC are analyzed in detail via a calibration experiment; for example, the edge distortion of TSC. Finally, the ability of the new MDCS to acquire high-accuracy spatial data is verified through flight experiments. The results of flight experiments illustrate that geo-position accuracy of prototype system achieves 0.3 m at a flight height of 800 m, and spatial resolution of 0.15 m. In addition, results of the comparison between the traditional (MADC II) and proposed MDCS demonstrate that the latter (0.3 m) provides spatial data with higher accuracy than the former (only 0.6 m) under the same conditions. We also take the attitude that using higher accuracy TSC in the new MDCS should further improve the accuracy of the photogrammetry senior product.

Combining High Spatial Resolution Optical and LIDAR Data for Object-Based Image Classification

NASA Astrophysics Data System (ADS)

Li, R.; Zhang, T.; Geng, R.; Wang, L.

2018-04-01

In order to classify high spatial resolution images more accurately, in this research, a hierarchical rule-based object-based classification framework was developed based on a high-resolution image with airborne Light Detection and Ranging (LiDAR) data. The eCognition software is employed to conduct the whole process. In detail, firstly, the FBSP optimizer (Fuzzy-based Segmentation Parameter) is used to obtain the optimal scale parameters for different land cover types. Then, using the segmented regions as basic units, the classification rules for various land cover types are established according to the spectral, morphological and texture features extracted from the optical images, and the height feature from LiDAR respectively. Thirdly, the object classification results are evaluated by using the confusion matrix, overall accuracy and Kappa coefficients. As a result, a method using the combination of an aerial image and the airborne Lidar data shows higher accuracy.

Determining dynamical parameters of the Milky Way Galaxy based on high-accuracy radio astrometry

NASA Astrophysics Data System (ADS)

Honma, Mareki; Nagayama, Takumi; Sakai, Nobuyuki

2015-08-01

In this paper we evaluate how the dynamical structure of the Galaxy can be constrained by high-accuracy VLBI (Very Long Baseline Interferometry) astrometry such as VERA (VLBI Exploration of Radio Astrometry). We generate simulated samples of maser sources which follow the gas motion caused by a spiral or bar potential, with their distribution similar to those currently observed with VERA and VLBA (Very Long Baseline Array). We apply the Markov chain Monte Carlo analyses to the simulated sample sources to determine the dynamical parameter of the models. We show that one can successfully determine the initial model parameters if astrometric results are obtained for a few hundred sources with currently achieved astrometric accuracy. If astrometric data are available from 500 sources, the expected accuracy of R0 and Θ0 is ˜ 1% or higher, and parameters related to the spiral structure can be constrained by an error of 10% or with higher accuracy. We also show that the parameter determination accuracy is basically independent of the locations of resonances such as corotation and/or inner/outer Lindblad resonances. We also discuss the possibility of model selection based on the Bayesian information criterion (BIC), and demonstrate that BIC can be used to discriminate different dynamical models of the Galaxy.

Self-powered microneedle-based biosensors for pain-free high-accuracy measurement of glycaemia in interstitial fluid.

PubMed

Strambini, L M; Longo, A; Scarano, S; Prescimone, T; Palchetti, I; Minunni, M; Giannessi, D; Barillaro, G

2015-04-15

In this work a novel self-powered microneedle-based transdermal biosensor for pain-free high-accuracy real-time measurement of glycaemia in interstitial fluid (ISF) is reported. The proposed transdermal biosensor makes use of an array of silicon-dioxide hollow microneedles that are about one order of magnitude both smaller (borehole down to 4µm) and more densely-packed (up to 1×10(6)needles/cm(2)) than state-of-the-art microneedles used for biosensing so far. This allows self-powered (i.e. pump-free) uptake of ISF to be carried out with high efficacy and reliability in a few seconds (uptake rate up to 1µl/s) by exploiting capillarity in the microneedles. By coupling the microneedles operating under capillary-action with an enzymatic glucose biosensor integrated on the back-side of the needle-chip, glucose measurements are performed with high accuracy (±20% of the actual glucose level for 96% of measures) and reproducibility (coefficient of variation 8.56%) in real-time (30s) over the range 0-630mg/dl, thus significantly improving microneedle-based biosensor performance with respect to the state-of-the-art. Copyright © 2014 Elsevier B.V. All rights reserved.

The role of feedback contingency in perceptual category learning.

PubMed

Ashby, F Gregory; Vucovich, Lauren E

2016-11-01

Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how feedback contingency affects category learning, and current theories assign little or no importance to this variable. Two experiments examined the effects of contingency degradation on rule-based and information-integration category learning. In rule-based tasks, optimal accuracy is possible with a simple explicit rule, whereas optimal accuracy in information-integration tasks requires integrating information from 2 or more incommensurable perceptual dimensions. In both experiments, participants each learned rule-based or information-integration categories under either high or low levels of feedback contingency. The exact same stimuli were used in all 4 conditions, and optimal accuracy was identical in every condition. Learning was good in both high-contingency conditions, but most participants showed little or no evidence of learning in either low-contingency condition. Possible causes of these effects, as well as their theoretical implications, are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The Role of Feedback Contingency in Perceptual Category Learning

PubMed Central

Ashby, F. Gregory; Vucovich, Lauren E.

2016-01-01

Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how feedback contingency affects category learning, and current theories assign little or no importance to this variable. Two experiments examined the effects of contingency degradation on rule-based and information-integration category learning. In rule-based tasks, optimal accuracy is possible with a simple explicit rule, whereas optimal accuracy in information-integration tasks requires integrating information from two or more incommensurable perceptual dimensions. In both experiments, participants each learned rule-based or information-integration categories under either high or low levels of feedback contingency. The exact same stimuli were used in all four conditions and optimal accuracy was identical in every condition. Learning was good in both high-contingency conditions, but most participants showed little or no evidence of learning in either low-contingency condition. Possible causes of these effects are discussed, as well as their theoretical implications. PMID:27149393

Thematic Accuracy Assessment of the 2011 National Land ...

EPA Pesticide Factsheets

Accuracy assessment is a standard protocol of National Land Cover Database (NLCD) mapping. Here we report agreement statistics between map and reference labels for NLCD 2011, which includes land cover for ca. 2001, ca. 2006, and ca. 2011. The two main objectives were assessment of agreement between map and reference labels for the three, single-date NLCD land cover products at Level II and Level I of the classification hierarchy, and agreement for 17 land cover change reporting themes based on Level I classes (e.g., forest loss; forest gain; forest, no change) for three change periods (2001–2006, 2006–2011, and 2001–2011). The single-date overall accuracies were 82%, 83%, and 83% at Level II and 88%, 89%, and 89% at Level I for 2011, 2006, and 2001, respectively. Many class-specific user's accuracies met or exceeded a previously established nominal accuracy benchmark of 85%. Overall accuracies for 2006 and 2001 land cover components of NLCD 2011 were approximately 4% higher (at Level II and Level I) than the overall accuracies for the same components of NLCD 2006. The high Level I overall, user's, and producer's accuracies for the single-date eras in NLCD 2011 did not translate into high class-specific user's and producer's accuracies for many of the 17 change reporting themes. User's accuracies were high for the no change reporting themes, commonly exceeding 85%, but were typically much lower for the reporting themes that represented change. Only forest l

Characterization and delineation of caribou habitat on Unimak Island using remote sensing techniques

NASA Astrophysics Data System (ADS)

Atkinson, Brain M.

The assessment of herbivore habitat quality is traditionally based on quantifying the forages available to the animal across their home range through ground-based techniques. While these methods are highly accurate, they can be time-consuming and highly expensive, especially for herbivores that occupy vast spatial landscapes. The Unimak Island caribou herd has been decreasing in the last decade at rates that have prompted discussion of management intervention. Frequent inclement weather in this region of Alaska has provided for little opportunity to study the caribou forage habitat on Unimak Island. The overall objectives of this study were two-fold 1) to assess the feasibility of using high-resolution color and near-infrared aerial imagery to map the forage distribution of caribou habitat on Unimak Island and 2) to assess the use of a new high-resolution multispectral satellite imagery platform, RapidEye, and use of the "red-edge" spectral band on vegetation classification accuracy. Maximum likelihood classification algorithms were used to create land cover maps in aerial and satellite imagery. Accuracy assessments and transformed divergence values were produced to assess vegetative spectral information and classification accuracy. By using RapidEye and aerial digital imagery in a hierarchical supervised classification technique, we were able to produce a high resolution land cover map of Unimak Island. We obtained overall accuracy rates of 71.4 percent which are comparable to other land cover maps using RapidEye imagery. The "red-edge" spectral band included in the RapidEye imagery provides additional spectral information that allows for a more accurate overall classification, raising overall accuracy 5.2 percent.

Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression.

PubMed

Kim, Soyeon; Baladandayuthapani, Veerabhadran; Lee, J Jack

2017-06-01

In personalized medicine, biomarkers are used to select therapies with the highest likelihood of success based on an individual patient's biomarker/genomic profile. Two goals are to choose important biomarkers that accurately predict treatment outcomes and to cull unimportant biomarkers to reduce the cost of biological and clinical verifications. These goals are challenging due to the high dimensionality of genomic data. Variable selection methods based on penalized regression (e.g., the lasso and elastic net) have yielded promising results. However, selecting the right amount of penalization is critical to simultaneously achieving these two goals. Standard approaches based on cross-validation (CV) typically provide high prediction accuracy with high true positive rates but at the cost of too many false positives. Alternatively, stability selection (SS) controls the number of false positives, but at the cost of yielding too few true positives. To circumvent these issues, we propose prediction-oriented marker selection (PROMISE), which combines SS with CV to conflate the advantages of both methods. Our application of PROMISE with the lasso and elastic net in data analysis shows that, compared to CV, PROMISE produces sparse solutions, few false positives, and small type I + type II error, and maintains good prediction accuracy, with a marginal decrease in the true positive rates. Compared to SS, PROMISE offers better prediction accuracy and true positive rates. In summary, PROMISE can be applied in many fields to select regularization parameters when the goals are to minimize false positives and maximize prediction accuracy.

Topography-based analysis of Hurricane Katrina inundation of New Orleans: Chapter 3G in Science and the storms-the USGS response to the hurricanes of 2005

USGS Publications Warehouse

Gesch, Dean

2007-01-01

The ready availability of high-resolution, high-accuracy elevation data proved valuable for development of topographybased products to determine rough estimates of the inundation of New Orleans, La., from Hurricane Katrina. Because of its high level of spatial detail and vertical accuracy of elevation measurements, light detection and ranging (lidar) remote sensing is an excellent mapping technology for use in low-relief hurricane-prone coastal areas.

Potential accuracy of translation estimation between radar and optical images

NASA Astrophysics Data System (ADS)

Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

2015-10-01

This paper investigates the potential accuracy achievable for optical to radar image registration by area-based approach. The analysis is carried out mainly based on the Cramér-Rao Lower Bound (CRLB) on translation estimation accuracy previously proposed by the authors and called CRLBfBm. This bound is now modified to take into account radar image speckle noise properties: spatial correlation and signal-dependency. The newly derived theoretical bound is fed with noise and texture parameters estimated for the co-registered pair of optical Landsat 8 and radar SIR-C images. It is found that difficulty of optical to radar image registration stems more from speckle noise influence than from dissimilarity of the considered kinds of images. At finer scales (and higher speckle noise level), probability of finding control fragments (CF) suitable for registration is low (1% or less) but overall number of such fragments is high thanks to image size. Conversely, at the coarse scale, where speckle noise level is reduced, probability of finding CFs suitable for registration can be as high as 40%, but overall number of such CFs is lower. Thus, the study confirms and supports area-based multiresolution approach for optical to radar registration where coarse scales are used for fast registration "lock" and finer scales for reaching higher registration accuracy. The CRLBfBm is found inaccurate for the main scale due to intensive speckle noise influence. For other scales, the validity of the CRLBfBm bound is confirmed by calculating statistical efficiency of area-based registration method based on normalized correlation coefficient (NCC) measure that takes high values of about 25%.

Scalable Photogrammetric Motion Capture System "mosca": Development and Application

NASA Astrophysics Data System (ADS)

Knyaz, V. A.

2015-05-01

Wide variety of applications (from industrial to entertainment) has a need for reliable and accurate 3D information about motion of an object and its parts. Very often the process of movement is rather fast as in cases of vehicle movement, sport biomechanics, animation of cartoon characters. Motion capture systems based on different physical principles are used for these purposes. The great potential for obtaining high accuracy and high degree of automation has vision-based system due to progress in image processing and analysis. Scalable inexpensive motion capture system is developed as a convenient and flexible tool for solving various tasks requiring 3D motion analysis. It is based on photogrammetric techniques of 3D measurements and provides high speed image acquisition, high accuracy of 3D measurements and highly automated processing of captured data. Depending on the application the system can be easily modified for different working areas from 100 mm to 10 m. The developed motion capture system uses from 2 to 4 technical vision cameras for video sequences of object motion acquisition. All cameras work in synchronization mode at frame rate up to 100 frames per second under the control of personal computer providing the possibility for accurate calculation of 3D coordinates of interest points. The system was used for a set of different applications fields and demonstrated high accuracy and high level of automation.

A Technique for Real-Time Ionospheric Ranging Error Correction Based On Radar Dual-Frequency Detection

NASA Astrophysics Data System (ADS)

Lyu, Jiang-Tao; Zhou, Chen

2017-12-01

Ionospheric refraction is one of the principal error sources for limiting the accuracy of radar systems for space target detection. High-accuracy measurement of the ionospheric electron density along the propagation path of radar wave is the most important procedure for the ionospheric refraction correction. Traditionally, the ionospheric model and the ionospheric detection instruments, like ionosonde or GPS receivers, are employed for obtaining the electron density. However, both methods are not capable of satisfying the requirements of correction accuracy for the advanced space target radar system. In this study, we propose a novel technique for ionospheric refraction correction based on radar dual-frequency detection. Radar target range measurements at two adjacent frequencies are utilized for calculating the electron density integral exactly along the propagation path of the radar wave, which can generate accurate ionospheric range correction. The implementation of radar dual-frequency detection is validated by a P band radar located in midlatitude China. The experimental results present that the accuracy of this novel technique is more accurate than the traditional ionospheric model correction. The technique proposed in this study is very promising for the high-accuracy radar detection and tracking of objects in geospace.

Accuracy and safety of ward based pleural ultrasound in the Australian healthcare system.

PubMed

Hammerschlag, Gary; Denton, Matthew; Wallbridge, Peter; Irving, Louis; Hew, Mark; Steinfort, Daniel

2017-04-01

Ultrasound has been shown to improve the accuracy and safety of pleural procedures. Studies to date have been performed in large, specialized units, where pleural procedures are performed by a small number of highly specialized physicians. There are no studies examining the safety and accuracy of ultrasound in the Australian healthcare system where procedures are performed by junior doctors with a high staff turnover. We performed a retrospective review of the ultrasound database in the Respiratory Department at the Royal Melbourne Hospital to determine accuracy and complications associated pleural procedures. A total of 357 ultrasounds were performed between October 2010 and June 2013. Accuracy of pleural procedures was 350 of 356 (98.3%). Aspiration of pleural fluid was successful in 121 of 126 (96%) of patients. Two (0.9%) patients required chest tube insertion for management of pneumothorax. There were no recorded pleural infections, haemorrhage or viscera puncture. Ward-based ultrasound for pleural procedures is safe and accurate when performed by appropriately trained and supported junior medical officers. Our findings support this model of pleural service care in the Australian healthcare system. © 2016 Asian Pacific Society of Respirology.

Indoor positioning algorithm combined with angular vibration compensation and the trust region technique based on received signal strength-visible light communication

NASA Astrophysics Data System (ADS)

Wang, Jin; Li, Haoxu; Zhang, Xiaofeng; Wu, Rangzhong

2017-05-01

Indoor positioning using visible light communication has become a topic of intensive research in recent years. Because the normal of the receiver always deviates from that of the transmitter in application, the positioning systems which require that the normal of the receiver be aligned with that of the transmitter have large positioning errors. Some algorithms take the angular vibrations into account; nevertheless, these positioning algorithms cannot meet the requirement of high accuracy or low complexity. A visible light positioning algorithm combined with angular vibration compensation is proposed. The angle information from the accelerometer or other angle acquisition devices is used to calculate the angle of incidence even when the receiver is not horizontal. Meanwhile, a received signal strength technique with high accuracy is employed to determine the location. Moreover, an eight-light-emitting-diode (LED) system model is provided to improve the accuracy. The simulation results show that the proposed system can achieve a low positioning error with low complexity, and the eight-LED system exhibits improved performance. Furthermore, trust region-based positioning is proposed to determine three-dimensional locations and achieves high accuracy in both the horizontal and the vertical components.

Object-Based Arctic Sea Ice Feature Extraction through High Spatial Resolution Aerial photos

NASA Astrophysics Data System (ADS)

Miao, X.; Xie, H.

2015-12-01

High resolution aerial photographs used to detect and classify sea ice features can provide accurate physical parameters to refine, validate, and improve climate models. However, manually delineating sea ice features, such as melt ponds, submerged ice, water, ice/snow, and pressure ridges, is time-consuming and labor-intensive. An object-based classification algorithm is developed to automatically extract sea ice features efficiently from aerial photographs taken during the Chinese National Arctic Research Expedition in summer 2010 (CHINARE 2010) in the MIZ near the Alaska coast. The algorithm includes four steps: (1) the image segmentation groups the neighboring pixels into objects based on the similarity of spectral and textural information; (2) the random forest classifier distinguishes four general classes: water, general submerged ice (GSI, including melt ponds and submerged ice), shadow, and ice/snow; (3) the polygon neighbor analysis separates melt ponds and submerged ice based on spatial relationship; and (4) pressure ridge features are extracted from shadow based on local illumination geometry. The producer's accuracy of 90.8% and user's accuracy of 91.8% are achieved for melt pond detection, and shadow shows a user's accuracy of 88.9% and producer's accuracies of 91.4%. Finally, pond density, pond fraction, ice floes, mean ice concentration, average ridge height, ridge profile, and ridge frequency are extracted from batch processing of aerial photos, and their uncertainties are estimated.

Certified ion implantation fluence by high accuracy RBS.

PubMed

Colaux, Julien L; Jeynes, Chris; Heasman, Keith C; Gwilliam, Russell M

2015-05-07

From measurements over the last two years we have demonstrated that the charge collection system based on Faraday cups can robustly give near-1% absolute implantation fluence accuracy for our electrostatically scanned 200 kV Danfysik ion implanter, using four-point-probe mapping with a demonstrated accuracy of 2%, and accurate Rutherford backscattering spectrometry (RBS) of test implants from our quality assurance programme. The RBS is traceable to the certified reference material IRMM-ERM-EG001/BAM-L001, and involves convenient calibrations both of the electronic gain of the spectrometry system (at about 0.1% accuracy) and of the RBS beam energy (at 0.06% accuracy). We demonstrate that accurate RBS is a definitive method to determine quantity of material. It is therefore useful for certifying high quality reference standards, and is also extensible to other kinds of samples such as thin self-supporting films of pure elements. The more powerful technique of Total-IBA may inherit the accuracy of RBS.

Mapping Vegetation Community Types in a Highly-Disturbed Landscape: Integrating Hiearchical Object-Based Image Analysis with Digital Surface Models

NASA Astrophysics Data System (ADS)

Snavely, Rachel A.

Focusing on the semi-arid and highly disturbed landscape of San Clemente Island, California, this research tests the effectiveness of incorporating a hierarchal object-based image analysis (OBIA) approach with high-spatial resolution imagery and light detection and range (LiDAR) derived canopy height surfaces for mapping vegetation communities. The study is part of a large-scale research effort conducted by researchers at San Diego State University's (SDSU) Center for Earth Systems Analysis Research (CESAR) and Soil Ecology and Restoration Group (SERG), to develop an updated vegetation community map which will support both conservation and management decisions on Naval Auxiliary Landing Field (NALF) San Clemente Island. Trimble's eCognition Developer software was used to develop and generate vegetation community maps for two study sites, with and without vegetation height data as input. Overall and class-specific accuracies were calculated and compared across the two classifications. The highest overall accuracy (approximately 80%) was observed with the classification integrating airborne visible and near infrared imagery having very high spatial resolution with a LiDAR derived canopy height model. Accuracies for individual vegetation classes differed between both classification methods, but were highest when incorporating the LiDAR digital surface data. The addition of a canopy height model, however, yielded little difference in classification accuracies for areas of very dense shrub cover. Overall, the results show the utility of the OBIA approach for mapping vegetation with high spatial resolution imagery, and emphasizes the advantage of both multi-scale analysis and digital surface data for accuracy characterizing highly disturbed landscapes. The integrated imagery and digital canopy height model approach presented both advantages and limitations, which have to be considered prior to its operational use in mapping vegetation communities.

High accuracy demodulation for twin-grating based sensor network with hybrid TDM/FDM

NASA Astrophysics Data System (ADS)

Ai, Fan; Sun, Qizhen; Cheng, Jianwei; Luo, Yiyang; Yan, Zhijun; Liu, Deming

2017-04-01

We demonstrate a high accuracy demodulation platform with a tunable Fabry-Perot filter (TFF) for twin-grating based fiber optic sensing network with hybrid TDM/FDM. The hybrid TDM/FDM scheme can improve the spatial resolution to centimeter but increases the requirement of high spectrum resolution. To realize the demodulation of the complex twin-grating spectrum, we adopt the TFF demodulation method and compensate the environmental temperature change and nonlinear effect through calibration FBGs. The performance of the demodulation module is tested by a temperature experiment. Spectrum resolution of 1pm is realized with precision of 2.5pm while the environmental temperature of TFF changes 9.3°C.

The Accuracy of Adult Narrative Reports of Developmental Trajectories

ERIC Educational Resources Information Center

Cohen, Patricia; Kasen, Stephanie; Bifulco, Antonia; Andrews, Howard; Gordon, Kathy

2005-01-01

This methodological investigation examines the accuracy of narrative-based scaled ratings covering several post high school years. Guided narratives by young adults described developmentally relevant behaviour and context for each month between ages 17 and the mid-20s. "Prospective" narratives covered shorter time periods in three interviews…

Rigorous accuracy assessment for 3D reconstruction using time-series Dual Fluoroscopy (DF) image pairs

NASA Astrophysics Data System (ADS)

Al-Durgham, Kaleel; Lichti, Derek D.; Kuntze, Gregor; Ronsky, Janet

2017-06-01

High-speed biplanar videoradiography, or clinically referred to as dual fluoroscopy (DF), imaging systems are being used increasingly for skeletal kinematics analysis. Typically, a DF system comprises two X-ray sources, two image intensifiers and two high-speed video cameras. The combination of these elements provides time-series image pairs of articulating bones of a joint, which permits the measurement of bony rotation and translation in 3D at high temporal resolution (e.g., 120-250 Hz). Assessment of the accuracy of 3D measurements derived from DF imaging has been the subject of recent research efforts by several groups, however with methodological limitations. This paper presents a novel and simple accuracy assessment procedure based on using precise photogrammetric tools. We address the fundamental photogrammetry principles for the accuracy evaluation of an imaging system. Bundle adjustment with selfcalibration is used for the estimation of the system parameters. The bundle adjustment calibration uses an appropriate sensor model and applies free-network constraints and relative orientation stability constraints for a precise estimation of the system parameters. A photogrammetric intersection of time-series image pairs is used for the 3D reconstruction of a rotating planar object. A point-based registration method is used to combine the 3D coordinates from the intersection and independently surveyed coordinates. The final DF accuracy measure is reported as the distance between 3D coordinates from image intersection and the independently surveyed coordinates. The accuracy assessment procedure is designed to evaluate the accuracy over the full DF image format and a wide range of object rotation. Experiment of reconstruction of a rotating planar object reported an average positional error of 0.44 +/- 0.2 mm in the derived 3D coordinates (minimum 0.05 and maximum 1.2 mm).

Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited.

PubMed

Thomas, Cibu; Ye, Frank Q; Irfanoglu, M Okan; Modi, Pooja; Saleem, Kadharbatcha S; Leopold, David A; Pierpaoli, Carlo

2014-11-18

Tractography based on diffusion-weighted MRI (DWI) is widely used for mapping the structural connections of the human brain. Its accuracy is known to be limited by technical factors affecting in vivo data acquisition, such as noise, artifacts, and data undersampling resulting from scan time constraints. It generally is assumed that improvements in data quality and implementation of sophisticated tractography methods will lead to increasingly accurate maps of human anatomical connections. However, assessing the anatomical accuracy of DWI tractography is difficult because of the lack of independent knowledge of the true anatomical connections in humans. Here we investigate the future prospects of DWI-based connectional imaging by applying advanced tractography methods to an ex vivo DWI dataset of the macaque brain. The results of different tractography methods were compared with maps of known axonal projections from previous tracer studies in the macaque. Despite the exceptional quality of the DWI data, none of the methods demonstrated high anatomical accuracy. The methods that showed the highest sensitivity showed the lowest specificity, and vice versa. Additionally, anatomical accuracy was highly dependent upon parameters of the tractography algorithm, with different optimal values for mapping different pathways. These results suggest that there is an inherent limitation in determining long-range anatomical projections based on voxel-averaged estimates of local fiber orientation obtained from DWI data that is unlikely to be overcome by improvements in data acquisition and analysis alone.

A Vehicular Mobile Standard Instrument for Field Verification of Traffic Speed Meters Based on Dual-Antenna Doppler Radar Sensor

PubMed Central

Du, Lei; Sun, Qiao; Cai, Changqing; Bai, Jie; Fan, Zhe; Zhang, Yue

2018-01-01

Traffic speed meters are important legal measuring instruments specially used for traffic speed enforcement and must be tested and verified in the field every year using a vehicular mobile standard speed-measuring instrument to ensure speed-measuring performances. The non-contact optical speed sensor and the GPS speed sensor are the two most common types of standard speed-measuring instruments. The non-contact optical speed sensor requires extremely high installation accuracy, and its speed-measuring error is nonlinear and uncorrectable. The speed-measuring accuracy of the GPS speed sensor is rapidly reduced if the amount of received satellites is insufficient enough, which often occurs in urban high-rise regions, tunnels, and mountainous regions. In this paper, a new standard speed-measuring instrument using a dual-antenna Doppler radar sensor is proposed based on a tradeoff between the installation accuracy requirement and the usage region limitation, which has no specified requirements for its mounting distance and no limitation on usage regions and can automatically compensate for the effect of an inclined installation angle on its speed-measuring accuracy. Theoretical model analysis, simulated speed measurement results, and field experimental results compared with a GPS speed sensor with high accuracy showed that the dual-antenna Doppler radar sensor is effective and reliable as a new standard speed-measuring instrument. PMID:29621142

A Vehicular Mobile Standard Instrument for Field Verification of Traffic Speed Meters Based on Dual-Antenna Doppler Radar Sensor.

PubMed

Du, Lei; Sun, Qiao; Cai, Changqing; Bai, Jie; Fan, Zhe; Zhang, Yue

2018-04-05

Traffic speed meters are important legal measuring instruments specially used for traffic speed enforcement and must be tested and verified in the field every year using a vehicular mobile standard speed-measuring instrument to ensure speed-measuring performances. The non-contact optical speed sensor and the GPS speed sensor are the two most common types of standard speed-measuring instruments. The non-contact optical speed sensor requires extremely high installation accuracy, and its speed-measuring error is nonlinear and uncorrectable. The speed-measuring accuracy of the GPS speed sensor is rapidly reduced if the amount of received satellites is insufficient enough, which often occurs in urban high-rise regions, tunnels, and mountainous regions. In this paper, a new standard speed-measuring instrument using a dual-antenna Doppler radar sensor is proposed based on a tradeoff between the installation accuracy requirement and the usage region limitation, which has no specified requirements for its mounting distance and no limitation on usage regions and can automatically compensate for the effect of an inclined installation angle on its speed-measuring accuracy. Theoretical model analysis, simulated speed measurement results, and field experimental results compared with a GPS speed sensor with high accuracy showed that the dual-antenna Doppler radar sensor is effective and reliable as a new standard speed-measuring instrument.

A Framework Based on Reference Data with Superordinate Accuracy for the Quality Analysis of Terrestrial Laser Scanning-Based Multi-Sensor-Systems

PubMed Central

Stenz, Ulrich; Neumann, Ingo

2017-01-01

Terrestrial laser scanning (TLS) is an efficient solution to collect large-scale data. The efficiency can be increased by combining TLS with additional sensors in a TLS-based multi-sensor-system (MSS). The uncertainty of scanned points is not homogenous and depends on many different influencing factors. These include the sensor properties, referencing, scan geometry (e.g., distance and angle of incidence), environmental conditions (e.g., atmospheric conditions) and the scanned object (e.g., material, color and reflectance, etc.). The paper presents methods, infrastructure and results for the validation of the suitability of TLS and TLS-based MSS. Main aspects are the backward modelling of the uncertainty on the basis of reference data (e.g., point clouds) with superordinate accuracy and the appropriation of a suitable environment/infrastructure (e.g., the calibration process of the targets for the registration of laser scanner and laser tracker data in a common coordinate system with high accuracy) In this context superordinate accuracy means that the accuracy of the acquired reference data is better by a factor of 10 than the data of the validated TLS and TLS-based MSS. These aspects play an important role in engineering geodesy, where the aimed accuracy lies in a range of a few mm or less. PMID:28812998

Vegetation classification of Coffea on Hawaii Island using WorldView-2 satellite imagery

NASA Astrophysics Data System (ADS)

Gaertner, Julie; Genovese, Vanessa Brooks; Potter, Christopher; Sewake, Kelvin; Manoukis, Nicholas C.

2017-10-01

Coffee is an important crop in tropical regions of the world; about 125 million people depend on coffee agriculture for their livelihoods. Understanding the spatial extent of coffee fields is useful for management and control of coffee pests such as Hypothenemus hampei and other pests that use coffee fruit as a host for immature stages such as the Mediterranean fruit fly, for economic planning, and for following changes in coffee agroecosystems over time. We present two methods for detecting Coffea arabica fields using remote sensing and geospatial technologies on WorldView-2 high-resolution spectral data of the Kona region of Hawaii Island. The first method, a pixel-based method using a maximum likelihood algorithm, attained 72% producer accuracy and 69% user accuracy (68% overall accuracy) based on analysis of 104 ground truth testing polygons. The second method, an object-based image analysis (OBIA) method, considered both spectral and textural information and improved accuracy, resulting in 76% producer accuracy and 94% user accuracy (81% overall accuracy) for the same testing areas. We conclude that the OBIA method is useful for detecting coffee fields grown in the open and use it to estimate the distribution of about 1050 hectares under coffee agriculture in the Kona region in 2012.

Accuracy of estimation of genomic breeding values in pigs using low-density genotypes and imputation.

PubMed

Badke, Yvonne M; Bates, Ronald O; Ernst, Catherine W; Fix, Justin; Steibel, Juan P

2014-04-16

Genomic selection has the potential to increase genetic progress. Genotype imputation of high-density single-nucleotide polymorphism (SNP) genotypes can improve the cost efficiency of genomic breeding value (GEBV) prediction for pig breeding. Consequently, the objectives of this work were to: (1) estimate accuracy of genomic evaluation and GEBV for three traits in a Yorkshire population and (2) quantify the loss of accuracy of genomic evaluation and GEBV when genotypes were imputed under two scenarios: a high-cost, high-accuracy scenario in which only selection candidates were imputed from a low-density platform and a low-cost, low-accuracy scenario in which all animals were imputed using a small reference panel of haplotypes. Phenotypes and genotypes obtained with the PorcineSNP60 BeadChip were available for 983 Yorkshire boars. Genotypes of selection candidates were masked and imputed using tagSNP in the GeneSeek Genomic Profiler (10K). Imputation was performed with BEAGLE using 128 or 1800 haplotypes as reference panels. GEBV were obtained through an animal-centric ridge regression model using de-regressed breeding values as response variables. Accuracy of genomic evaluation was estimated as the correlation between estimated breeding values and GEBV in a 10-fold cross validation design. Accuracy of genomic evaluation using observed genotypes was high for all traits (0.65-0.68). Using genotypes imputed from a large reference panel (accuracy: R(2) = 0.95) for genomic evaluation did not significantly decrease accuracy, whereas a scenario with genotypes imputed from a small reference panel (R(2) = 0.88) did show a significant decrease in accuracy. Genomic evaluation based on imputed genotypes in selection candidates can be implemented at a fraction of the cost of a genomic evaluation using observed genotypes and still yield virtually the same accuracy. On the other side, using a very small reference panel of haplotypes to impute training animals and candidates for selection results in lower accuracy of genomic evaluation.

Research on Modeling of Propeller in a Turboprop Engine

NASA Astrophysics Data System (ADS)

Huang, Jiaqin; Huang, Xianghua; Zhang, Tianhong

2015-05-01

In the simulation of engine-propeller integrated control system for a turboprop aircraft, a real-time propeller model with high-accuracy is required. A study is conducted to compare the real-time and precision performance of propeller models based on strip theory and lifting surface theory. The emphasis in modeling by strip theory is focused on three points as follows: First, FLUENT is adopted to calculate the lift and drag coefficients of the propeller. Next, a method to calculate the induced velocity which occurs in the ground rig test is presented. Finally, an approximate method is proposed to obtain the downwash angle of the propeller when the conventional algorithm has no solution. An advanced approximation of the velocities induced by helical horseshoe vortices is applied in the model based on lifting surface theory. This approximate method will reduce computing time and remain good accuracy. Comparison between the two modeling techniques shows that the model based on strip theory which owns more advantage on both real-time and high-accuracy can meet the requirement.

High accuracy electronic material level sensor

DOEpatents

McEwan, T.E.

1997-03-11

The High Accuracy Electronic Material Level Sensor (electronic dipstick) is a sensor based on time domain reflectometry (TDR) of very short electrical pulses. Pulses are propagated along a transmission line or guide wire that is partially immersed in the material being measured; a launcher plate is positioned at the beginning of the guide wire. Reflected pulses are produced at the material interface due to the change in dielectric constant. The time difference of the reflections at the launcher plate and at the material interface are used to determine the material level. Improved performance is obtained by the incorporation of: (1) a high accuracy time base that is referenced to a quartz crystal, (2) an ultrawideband directional sampler to allow operation without an interconnect cable between the electronics module and the guide wire, (3) constant fraction discriminators (CFDs) that allow accurate measurements regardless of material dielectric constants, and reduce or eliminate errors induced by triple-transit or ``ghost`` reflections on the interconnect cable. These improvements make the dipstick accurate to better than 0.1%. 4 figs.

High accuracy electronic material level sensor

DOEpatents

McEwan, Thomas E.

1997-01-01

The High Accuracy Electronic Material Level Sensor (electronic dipstick) is a sensor based on time domain reflectometry (TDR) of very short electrical pulses. Pulses are propagated along a transmission line or guide wire that is partially immersed in the material being measured; a launcher plate is positioned at the beginning of the guide wire. Reflected pulses are produced at the material interface due to the change in dielectric constant. The time difference of the reflections at the launcher plate and at the material interface are used to determine the material level. Improved performance is obtained by the incorporation of: 1) a high accuracy time base that is referenced to a quartz crystal, 2) an ultrawideband directional sampler to allow operation without an interconnect cable between the electronics module and the guide wire, 3) constant fraction discriminators (CFDs) that allow accurate measurements regardless of material dielectric constants, and reduce or eliminate errors induced by triple-transit or "ghost" reflections on the interconnect cable. These improvements make the dipstick accurate to better than 0.1%.

An implicit spatial and high-order temporal finite difference scheme for 2D acoustic modelling

NASA Astrophysics Data System (ADS)

Wang, Enjiang; Liu, Yang

2018-01-01

The finite difference (FD) method exhibits great superiority over other numerical methods due to its easy implementation and small computational requirement. We propose an effective FD method, characterised by implicit spatial and high-order temporal schemes, to reduce both the temporal and spatial dispersions simultaneously. For the temporal derivative, apart from the conventional second-order FD approximation, a special rhombus FD scheme is included to reach high-order accuracy in time. Compared with the Lax-Wendroff FD scheme, this scheme can achieve nearly the same temporal accuracy but requires less floating-point operation times and thus less computational cost when the same operator length is adopted. For the spatial derivatives, we adopt the implicit FD scheme to improve the spatial accuracy. Apart from the existing Taylor series expansion-based FD coefficients, we derive the least square optimisation based implicit spatial FD coefficients. Dispersion analysis and modelling examples demonstrate that, our proposed method can effectively decrease both the temporal and spatial dispersions, thus can provide more accurate wavefields.

A Classification of Remote Sensing Image Based on Improved Compound Kernels of Svm

NASA Astrophysics Data System (ADS)

Zhao, Jianing; Gao, Wanlin; Liu, Zili; Mou, Guifen; Lu, Lin; Yu, Lina

The accuracy of RS classification based on SVM which is developed from statistical learning theory is high under small number of train samples, which results in satisfaction of classification on RS using SVM methods. The traditional RS classification method combines visual interpretation with computer classification. The accuracy of the RS classification, however, is improved a lot based on SVM method, because it saves much labor and time which is used to interpret images and collect training samples. Kernel functions play an important part in the SVM algorithm. It uses improved compound kernel function and therefore has a higher accuracy of classification on RS images. Moreover, compound kernel improves the generalization and learning ability of the kernel.

A family of high-order gas-kinetic schemes and its comparison with Riemann solver based high-order methods

NASA Astrophysics Data System (ADS)

Ji, Xing; Zhao, Fengxiang; Shyy, Wei; Xu, Kun

2018-03-01

Most high order computational fluid dynamics (CFD) methods for compressible flows are based on Riemann solver for the flux evaluation and Runge-Kutta (RK) time stepping technique for temporal accuracy. The advantage of this kind of space-time separation approach is the easy implementation and stability enhancement by introducing more middle stages. However, the nth-order time accuracy needs no less than n stages for the RK method, which can be very time and memory consuming due to the reconstruction at each stage for a high order method. On the other hand, the multi-stage multi-derivative (MSMD) method can be used to achieve the same order of time accuracy using less middle stages with the use of the time derivatives of the flux function. For traditional Riemann solver based CFD methods, the lack of time derivatives in the flux function prevents its direct implementation of the MSMD method. However, the gas kinetic scheme (GKS) provides such a time accurate evolution model. By combining the second-order or third-order GKS flux functions with the MSMD technique, a family of high order gas kinetic methods can be constructed. As an extension of the previous 2-stage 4th-order GKS, the 5th-order schemes with 2 and 3 stages will be developed in this paper. Based on the same 5th-order WENO reconstruction, the performance of gas kinetic schemes from the 2nd- to the 5th-order time accurate methods will be evaluated. The results show that the 5th-order scheme can achieve the theoretical order of accuracy for the Euler equations, and present accurate Navier-Stokes solutions as well due to the coupling of inviscid and viscous terms in the GKS formulation. In comparison with Riemann solver based 5th-order RK method, the high order GKS has advantages in terms of efficiency, accuracy, and robustness, for all test cases. The 4th- and 5th-order GKS have the same robustness as the 2nd-order scheme for the capturing of discontinuous solutions. The current high order MSMD GKS is a multi-dimensional scheme with incorporation of both normal and tangential spatial derivatives of flow variables at a cell interface in the flux evaluation. The scheme can be extended straightforwardly to viscous flow computation in unstructured mesh. It provides a promising direction for the development of high-order CFD methods for the computation of complex flows, such as turbulence and acoustics with shock interactions.

High-Precision Attitude Estimation Method of Star Sensors and Gyro Based on Complementary Filter and Unscented Kalman Filter

NASA Astrophysics Data System (ADS)

Guo, C.; Tong, X.; Liu, S.; Liu, S.; Lu, X.; Chen, P.; Jin, Y.; Xie, H.

2017-07-01

Determining the attitude of satellite at the time of imaging then establishing the mathematical relationship between image points and ground points is essential in high-resolution remote sensing image mapping. Star tracker is insensitive to the high frequency attitude variation due to the measure noise and satellite jitter, but the low frequency attitude motion can be determined with high accuracy. Gyro, as a short-term reference to the satellite's attitude, is sensitive to high frequency attitude change, but due to the existence of gyro drift and integral error, the attitude determination error increases with time. Based on the opposite noise frequency characteristics of two kinds of attitude sensors, this paper proposes an on-orbit attitude estimation method of star sensors and gyro based on Complementary Filter (CF) and Unscented Kalman Filter (UKF). In this study, the principle and implementation of the proposed method are described. First, gyro attitude quaternions are acquired based on the attitude kinematics equation. An attitude information fusion method is then introduced, which applies high-pass filtering and low-pass filtering to the gyro and star tracker, respectively. Second, the attitude fusion data based on CF are introduced as the observed values of UKF system in the process of measurement updating. The accuracy and effectiveness of the method are validated based on the simulated sensors attitude data. The obtained results indicate that the proposed method can suppress the gyro drift and measure noise of attitude sensors, improving the accuracy of the attitude determination significantly, comparing with the simulated on-orbit attitude and the attitude estimation results of the UKF defined by the same simulation parameters.

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision

PubMed Central

Ender, Andreas; Mehl, Albert

2014-01-01

Reference scanners are used in dental medicine to verify a lot of procedures. The main interest is to verify impression methods as they serve as a base for dental restorations. The current limitation of many reference scanners is the lack of accuracy scanning large objects like full dental arches, or the limited possibility to assess detailed tooth surfaces. A new reference scanner, based on focus variation scanning technique, was evaluated with regards to highest local and general accuracy. A specific scanning protocol was tested to scan original tooth surface from dental impressions. Also, different model materials were verified. The results showed a high scanning accuracy of the reference scanner with a mean deviation of 5.3 ± 1.1 µm for trueness and 1.6 ± 0.6 µm for precision in case of full arch scans. Current dental impression methods showed much higher deviations (trueness: 20.4 ± 2.2 µm, precision: 12.5 ± 2.5 µm) than the internal scanning accuracy of the reference scanner. Smaller objects like single tooth surface can be scanned with an even higher accuracy, enabling the system to assess erosive and abrasive tooth surface loss. The reference scanner can be used to measure differences for a lot of dental research fields. The different magnification levels combined with a high local and general accuracy can be used to assess changes of single teeth or restorations up to full arch changes. PMID:24836007

Kalman approach to accuracy management for interoperable heterogeneous model abstraction within an HLA-compliant simulation

NASA Astrophysics Data System (ADS)

Leskiw, Donald M.; Zhau, Junmei

2000-06-01

This paper reports on results from an ongoing project to develop methodologies for representing and managing multiple, concurrent levels of detail and enabling high performance computing using parallel arrays within distributed object-based simulation frameworks. At this time we present the methodology for representing and managing multiple, concurrent levels of detail and modeling accuracy by using a representation based on the Kalman approach for estimation. The Kalman System Model equations are used to represent model accuracy, Kalman Measurement Model equations provide transformations between heterogeneous levels of detail, and interoperability among disparate abstractions is provided using a form of the Kalman Update equations.

A fuzzy pattern matching method based on graph kernel for lithography hotspot detection

NASA Astrophysics Data System (ADS)

Nitta, Izumi; Kanazawa, Yuzi; Ishida, Tsutomu; Banno, Koji

2017-03-01

In advanced technology nodes, lithography hotspot detection has become one of the most significant issues in design for manufacturability. Recently, machine learning based lithography hotspot detection has been widely investigated, but it has trade-off between detection accuracy and false alarm. To apply machine learning based technique to the physical verification phase, designers require minimizing undetected hotspots to avoid yield degradation. They also need a ranking of similar known patterns with a detected hotspot to prioritize layout pattern to be corrected. To achieve high detection accuracy and to prioritize detected hotspots, we propose a novel lithography hotspot detection method using Delaunay triangulation and graph kernel based machine learning. Delaunay triangulation extracts features of hotspot patterns where polygons locate irregularly and closely one another, and graph kernel expresses inner structure of graphs. Additionally, our method provides similarity between two patterns and creates a list of similar training patterns with a detected hotspot. Experiments results on ICCAD 2012 benchmarks show that our method achieves high accuracy with allowable range of false alarm. We also show the ranking of the similar known patterns with a detected hotspot.

Accuracy Improvement in Magnetic Field Modeling for an Axisymmetric Electromagnet

NASA Technical Reports Server (NTRS)

Ilin, Andrew V.; Chang-Diaz, Franklin R.; Gurieva, Yana L.; Il,in, Valery P.

2000-01-01

This paper examines the accuracy and calculation speed for the magnetic field computation in an axisymmetric electromagnet. Different numerical techniques, based on an adaptive nonuniform grid, high order finite difference approximations, and semi-analitical calculation of boundary conditions are considered. These techniques are being applied to the modeling of the Variable Specific Impulse Magnetoplasma Rocket. For high-accuracy calculations, a fourth-order scheme offers dramatic advantages over a second order scheme. For complex physical configurations of interest in plasma propulsion, a second-order scheme with nonuniform mesh gives the best results. Also, the relative advantages of various methods are described when the speed of computation is an important consideration.

Analysis of energy-based algorithms for RNA secondary structure prediction

PubMed Central

2012-01-01

Background RNA molecules play critical roles in the cells of organisms, including roles in gene regulation, catalysis, and synthesis of proteins. Since RNA function depends in large part on its folded structures, much effort has been invested in developing accurate methods for prediction of RNA secondary structure from the base sequence. Minimum free energy (MFE) predictions are widely used, based on nearest neighbor thermodynamic parameters of Mathews, Turner et al. or those of Andronescu et al. Some recently proposed alternatives that leverage partition function calculations find the structure with maximum expected accuracy (MEA) or pseudo-expected accuracy (pseudo-MEA) methods. Advances in prediction methods are typically benchmarked using sensitivity, positive predictive value and their harmonic mean, namely F-measure, on datasets of known reference structures. Since such benchmarks document progress in improving accuracy of computational prediction methods, it is important to understand how measures of accuracy vary as a function of the reference datasets and whether advances in algorithms or thermodynamic parameters yield statistically significant improvements. Our work advances such understanding for the MFE and (pseudo-)MEA-based methods, with respect to the latest datasets and energy parameters. Results We present three main findings. First, using the bootstrap percentile method, we show that the average F-measure accuracy of the MFE and (pseudo-)MEA-based algorithms, as measured on our largest datasets with over 2000 RNAs from diverse families, is a reliable estimate (within a 2% range with high confidence) of the accuracy of a population of RNA molecules represented by this set. However, average accuracy on smaller classes of RNAs such as a class of 89 Group I introns used previously in benchmarking algorithm accuracy is not reliable enough to draw meaningful conclusions about the relative merits of the MFE and MEA-based algorithms. Second, on our large datasets, the algorithm with best overall accuracy is a pseudo MEA-based algorithm of Hamada et al. that uses a generalized centroid estimator of base pairs. However, between MFE and other MEA-based methods, there is no clear winner in the sense that the relative accuracy of the MFE versus MEA-based algorithms changes depending on the underlying energy parameters. Third, of the four parameter sets we considered, the best accuracy for the MFE-, MEA-based, and pseudo-MEA-based methods is 0.686, 0.680, and 0.711, respectively (on a scale from 0 to 1 with 1 meaning perfect structure predictions) and is obtained with a thermodynamic parameter set obtained by Andronescu et al. called BL* (named after the Boltzmann likelihood method by which the parameters were derived). Conclusions Large datasets should be used to obtain reliable measures of the accuracy of RNA structure prediction algorithms, and average accuracies on specific classes (such as Group I introns and Transfer RNAs) should be interpreted with caution, considering the relatively small size of currently available datasets for such classes. The accuracy of the MEA-based methods is significantly higher when using the BL* parameter set of Andronescu et al. than when using the parameters of Mathews and Turner, and there is no significant difference between the accuracy of MEA-based methods and MFE when using the BL* parameters. The pseudo-MEA-based method of Hamada et al. with the BL* parameter set significantly outperforms all other MFE and MEA-based algorithms on our large data sets. PMID:22296803

Analysis of energy-based algorithms for RNA secondary structure prediction.

PubMed

Hajiaghayi, Monir; Condon, Anne; Hoos, Holger H

2012-02-01

RNA molecules play critical roles in the cells of organisms, including roles in gene regulation, catalysis, and synthesis of proteins. Since RNA function depends in large part on its folded structures, much effort has been invested in developing accurate methods for prediction of RNA secondary structure from the base sequence. Minimum free energy (MFE) predictions are widely used, based on nearest neighbor thermodynamic parameters of Mathews, Turner et al. or those of Andronescu et al. Some recently proposed alternatives that leverage partition function calculations find the structure with maximum expected accuracy (MEA) or pseudo-expected accuracy (pseudo-MEA) methods. Advances in prediction methods are typically benchmarked using sensitivity, positive predictive value and their harmonic mean, namely F-measure, on datasets of known reference structures. Since such benchmarks document progress in improving accuracy of computational prediction methods, it is important to understand how measures of accuracy vary as a function of the reference datasets and whether advances in algorithms or thermodynamic parameters yield statistically significant improvements. Our work advances such understanding for the MFE and (pseudo-)MEA-based methods, with respect to the latest datasets and energy parameters. We present three main findings. First, using the bootstrap percentile method, we show that the average F-measure accuracy of the MFE and (pseudo-)MEA-based algorithms, as measured on our largest datasets with over 2000 RNAs from diverse families, is a reliable estimate (within a 2% range with high confidence) of the accuracy of a population of RNA molecules represented by this set. However, average accuracy on smaller classes of RNAs such as a class of 89 Group I introns used previously in benchmarking algorithm accuracy is not reliable enough to draw meaningful conclusions about the relative merits of the MFE and MEA-based algorithms. Second, on our large datasets, the algorithm with best overall accuracy is a pseudo MEA-based algorithm of Hamada et al. that uses a generalized centroid estimator of base pairs. However, between MFE and other MEA-based methods, there is no clear winner in the sense that the relative accuracy of the MFE versus MEA-based algorithms changes depending on the underlying energy parameters. Third, of the four parameter sets we considered, the best accuracy for the MFE-, MEA-based, and pseudo-MEA-based methods is 0.686, 0.680, and 0.711, respectively (on a scale from 0 to 1 with 1 meaning perfect structure predictions) and is obtained with a thermodynamic parameter set obtained by Andronescu et al. called BL* (named after the Boltzmann likelihood method by which the parameters were derived). Large datasets should be used to obtain reliable measures of the accuracy of RNA structure prediction algorithms, and average accuracies on specific classes (such as Group I introns and Transfer RNAs) should be interpreted with caution, considering the relatively small size of currently available datasets for such classes. The accuracy of the MEA-based methods is significantly higher when using the BL* parameter set of Andronescu et al. than when using the parameters of Mathews and Turner, and there is no significant difference between the accuracy of MEA-based methods and MFE when using the BL* parameters. The pseudo-MEA-based method of Hamada et al. with the BL* parameter set significantly outperforms all other MFE and MEA-based algorithms on our large data sets.

An object-based image analysis approach for aquaculture ponds precise mapping and monitoring: a case study of Tam Giang-Cau Hai Lagoon, Vietnam.

PubMed

Virdis, Salvatore Gonario Pasquale

2014-01-01

Monitoring and mapping shrimp farms, including their impact on land cover and land use, is critical to the sustainable management and planning of coastal zones. In this work, a methodology was proposed to set up a cost-effective and reproducible procedure that made use of satellite remote sensing, object-based classification approach, and open-source software for mapping aquaculture areas with high planimetric and thematic accuracy between 2005 and 2008. The analysis focused on two characteristic areas of interest of the Tam Giang-Cau Hai Lagoon (in central Vietnam), which have similar farming systems to other coastal aquaculture worldwide: the first was primarily characterised by locally referred "low tide" shrimp ponds, which are partially submerged areas; the second by earthed shrimp ponds, locally referred to as "high tide" ponds, which are non-submerged areas on the lagoon coast. The approach was based on the region-growing segmentation of high- and very high-resolution panchromatic images, SPOT5 and Worldview-1, and the unsupervised clustering classifier ISOSEG embedded on SPRING non-commercial software. The results, the accuracy of which was tested with a field-based aquaculture inventory, showed that in favourable situations (high tide shrimp ponds), the classification results provided high rates of accuracy (>95 %) through a fully automatic object-based classification. In unfavourable situations (low tide shrimp ponds), the performance degraded due to the low contrast between the water and the pond embankments. In these situations, the automatic results were improved by manual delineation of the embankments. Worldview-1 necessarily showed better thematic accuracy, and precise maps have been realised at a scale of up to 1:2,000. However, SPOT5 provided comparable results in terms of number of correctly classified ponds, but less accurate results in terms of the precision of mapped features. The procedure also demonstrated high degrees of reproducibility because it was applied to images with different spatial resolutions in an area that, during the investigated period, did not experience significant land cover changes.

Fourier analysis for hydrostatic pressure sensing in a polarization-maintaining photonic crystal fiber.

PubMed

Childs, Paul; Wong, Allan C L; Fu, H Y; Liao, Yanbiao; Tam, Hwayaw; Lu, Chao; Wai, P K A

2010-12-20

We measured the hydrostatic pressure dependence of the birefringence and birefringent dispersion of a Sagnac interferometric sensor incorporating a length of highly birefringent photonic crystal fiber using Fourier analysis. Sensitivity of both the phase and chirp spectra to hydrostatic pressure is demonstrated. Using this analysis, phase-based measurements showed a good linearity with an effective sensitivity of 9.45 nm/MPa and an accuracy of ±7.8 kPa using wavelength-encoded data and an effective sensitivity of -55.7 cm(-1)/MPa and an accuracy of ±4.4 kPa using wavenumber-encoded data. Chirp-based measurements, though nonlinear in response, showed an improvement in accuracy at certain pressure ranges with an accuracy of ±5.5 kPa for the full range of measured pressures using wavelength-encoded data and dropping to within ±2.5 kPa in the range of 0.17 to 0.4 MPa using wavenumber-encoded data. Improvements of the accuracy demonstrated the usefulness of implementing chirp-based analysis for sensing purposes.

FPGA-Based Smart Sensor for Online Displacement Measurements Using a Heterodyne Interferometer

PubMed Central

Vera-Salas, Luis Alberto; Moreno-Tapia, Sandra Veronica; Garcia-Perez, Arturo; de Jesus Romero-Troncoso, Rene; Osornio-Rios, Roque Alfredo; Serroukh, Ibrahim; Cabal-Yepez, Eduardo

2011-01-01

The measurement of small displacements on the nanometric scale demands metrological systems of high accuracy and precision. In this context, interferometer-based displacement measurements have become the main tools used for traceable dimensional metrology. The different industrial applications in which small displacement measurements are employed requires the use of online measurements, high speed processes, open architecture control systems, as well as good adaptability to specific process conditions. The main contribution of this work is the development of a smart sensor for large displacement measurement based on phase measurement which achieves high accuracy and resolution, designed to be used with a commercial heterodyne interferometer. The system is based on a low-cost Field Programmable Gate Array (FPGA) allowing the integration of several functions in a single portable device. This system is optimal for high speed applications where online measurement is needed and the reconfigurability feature allows the addition of different modules for error compensation, as might be required by a specific application. PMID:22164040

Accuracy of Rhenium-188 SPECT/CT activity quantification for applications in radionuclide therapy using clinical reconstruction methods.

PubMed

Esquinas, Pedro L; Uribe, Carlos F; Gonzalez, M; Rodríguez-Rodríguez, Cristina; Häfeli, Urs O; Celler, Anna

2017-07-20

The main applications of 188 Re in radionuclide therapies include trans-arterial liver radioembolization and palliation of painful bone-metastases. In order to optimize 188 Re therapies, the accurate determination of radiation dose delivered to tumors and organs at risk is required. Single photon emission computed tomography (SPECT) can be used to perform such dosimetry calculations. However, the accuracy of dosimetry estimates strongly depends on the accuracy of activity quantification in 188 Re images. In this study, we performed a series of phantom experiments aiming to investigate the accuracy of activity quantification for 188 Re SPECT using high-energy and medium-energy collimators. Objects of different shapes and sizes were scanned in Air, non-radioactive water (Cold-water) and water with activity (Hot-water). The ordered subset expectation maximization algorithm with clinically available corrections (CT-based attenuation, triple-energy window (TEW) scatter and resolution recovery was used). For high activities, the dead-time corrections were applied. The accuracy of activity quantification was evaluated using the ratio of the reconstructed activity in each object to this object's true activity. Each object's activity was determined with three segmentation methods: a 1% fixed threshold (for cold background), a 40% fixed threshold and a CT-based segmentation. Additionally, the activity recovered in the entire phantom, as well as the average activity concentration of the phantom background were compared to their true values. Finally, Monte-Carlo simulations of a commercial [Formula: see text]-camera were performed to investigate the accuracy of the TEW method. Good quantification accuracy (errors  <10%) was achieved for the entire phantom, the hot-background activity concentration and for objects in cold background segmented with a 1% threshold. However, the accuracy of activity quantification for objects segmented with 40% threshold or CT-based methods decreased (errors  >15%), mostly due to partial-volume effects. The Monte-Carlo simulations confirmed that TEW-scatter correction applied to 188 Re, although practical, yields only approximate estimates of the true scatter.

Accuracy assessment of high frequency 3D ultrasound for digital impression-taking of prepared teeth

NASA Astrophysics Data System (ADS)

Heger, Stefan; Vollborn, Thorsten; Tinschert, Joachim; Wolfart, Stefan; Radermacher, Klaus

2013-03-01

Silicone based impression-taking of prepared teeth followed by plaster casting is well-established but potentially less reliable, error-prone and inefficient, particularly in combination with emerging techniques like computer aided design and manufacturing (CAD/CAM) of dental prosthesis. Intra-oral optical scanners for digital impression-taking have been introduced but until now some drawbacks still exist. Because optical waves can hardly penetrate liquids or soft-tissues, sub-gingival preparations still need to be uncovered invasively prior to scanning. High frequency ultrasound (HFUS) based micro-scanning has been recently investigated as an alternative to optical intra-oral scanning. Ultrasound is less sensitive against oral fluids and in principal able to penetrate gingiva without invasively exposing of sub-gingival preparations. Nevertheless, spatial resolution as well as digitization accuracy of an ultrasound based micro-scanning system remains a critical parameter because the ultrasound wavelength in water-like media such as gingiva is typically smaller than that of optical waves. In this contribution, the in-vitro accuracy of ultrasound based micro-scanning for tooth geometry reconstruction is being investigated and compared to its extra-oral optical counterpart. In order to increase the spatial resolution of the system, 2nd harmonic frequencies from a mechanically driven focused single element transducer were separated and corresponding 3D surface models were calculated for both fundamentals and 2nd harmonics. Measurements on phantoms, model teeth and human teeth were carried out for evaluation of spatial resolution and surface detection accuracy. Comparison of optical and ultrasound digital impression taking indicate that, in terms of accuracy, ultrasound based tooth digitization can be an alternative for optical impression-taking.

3D anisotropic modeling and identification for airborne EM systems based on the spectral-element method

NASA Astrophysics Data System (ADS)

Huang, Xin; Yin, Chang-Chun; Cao, Xiao-Yue; Liu, Yun-He; Zhang, Bo; Cai, Jing

2017-09-01

The airborne electromagnetic (AEM) method has a high sampling rate and survey flexibility. However, traditional numerical modeling approaches must use high-resolution physical grids to guarantee modeling accuracy, especially for complex geological structures such as anisotropic earth. This can lead to huge computational costs. To solve this problem, we propose a spectral-element (SE) method for 3D AEM anisotropic modeling, which combines the advantages of spectral and finite-element methods. Thus, the SE method has accuracy as high as that of the spectral method and the ability to model complex geology inherited from the finite-element method. The SE method can improve the modeling accuracy within discrete grids and reduce the dependence of modeling results on the grids. This helps achieve high-accuracy anisotropic AEM modeling. We first introduced a rotating tensor of anisotropic conductivity to Maxwell's equations and described the electrical field via SE basis functions based on GLL interpolation polynomials. We used the Galerkin weighted residual method to establish the linear equation system for the SE method, and we took a vertical magnetic dipole as the transmission source for our AEM modeling. We then applied fourth-order SE calculations with coarse physical grids to check the accuracy of our modeling results against a 1D semi-analytical solution for an anisotropic half-space model and verified the high accuracy of the SE. Moreover, we conducted AEM modeling for different anisotropic 3D abnormal bodies using two physical grid scales and three orders of SE to obtain the convergence conditions for different anisotropic abnormal bodies. Finally, we studied the identification of anisotropy for single anisotropic abnormal bodies, anisotropic surrounding rock, and single anisotropic abnormal body embedded in an anisotropic surrounding rock. This approach will play a key role in the inversion and interpretation of AEM data collected in regions with anisotropic geology.

Highly accurate symplectic element based on two variational principles

NASA Astrophysics Data System (ADS)

Qing, Guanghui; Tian, Jia

2018-02-01

For the stability requirement of numerical resultants, the mathematical theory of classical mixed methods are relatively complex. However, generalized mixed methods are automatically stable, and their building process is simple and straightforward. In this paper, based on the seminal idea of the generalized mixed methods, a simple, stable, and highly accurate 8-node noncompatible symplectic element (NCSE8) was developed by the combination of the modified Hellinger-Reissner mixed variational principle and the minimum energy principle. To ensure the accuracy of in-plane stress results, a simultaneous equation approach was also suggested. Numerical experimentation shows that the accuracy of stress results of NCSE8 are nearly the same as that of displacement methods, and they are in good agreement with the exact solutions when the mesh is relatively fine. NCSE8 has advantages of the clearing concept, easy calculation by a finite element computer program, higher accuracy and wide applicability for various linear elasticity compressible and nearly incompressible material problems. It is possible that NCSE8 becomes even more advantageous for the fracture problems due to its better accuracy of stresses.

Development of an integrated sub-picometric SWIFTS-based wavelength meter

NASA Astrophysics Data System (ADS)

Duchemin, Céline; Thomas, Fabrice; Martin, Bruno; Morino, Eric; Puget, Renaud; Oliveres, Robin; Bonneville, Christophe; Gonthiez, Thierry; Valognes, Nicolas

2017-02-01

SWIFTSTM technology has been known for over five years to offer compact and high-resolution laser spectrum analyzers. The increase of wavelength monitoring demand with even better accuracy and resolution has pushed the development of a wavelength meter based on SWIFTSTM technology, named LW-10. As a reminder, SWIFTSTM principle consists in a waveguide in which a stationary wave is created, sampled and read out by a linear image sensor array. Due to its inherent properties (non-uniform subsampling) and aliasing signal (as presented in Shannon-Nyquist criterion), the system offers short spectral window bandwidths thus needs an a priori on the working wavelength and thermal monitoring. Although SWIFTSTM-based devices are barely sensitive to atmospheric pressure, temperature control is a key factor to master both high accuracy and wavelength meter resolution. Temperature control went from passive (temperature probing only) to active control (Peltier thermoelectric cooler) with milli-degree accuracy. The software part consists in dropping the Fourier-like transform, for a least-squares method directly on the interference pattern. Moreover, the consideration of the system's chromatic behavior provides a "signature" for automated wavelength detection and discrimination. This SWIFTSTM-based new device - LW-10 - shows outstanding results in terms of absolute accuracy, wavelength meter resolution as well as calibration robustness within a compact device, compared to other existing technologies. On the 630 - 1100 nm range, the final device configuration allows pulsed or CW lasers monitoring with 20 MHz resolution and 200 MHz absolute accuracy. Non-exhaustive applications include tunable laser control and frequency locking experiments

Global investigations of the satellite-based Fugro OmniSTAR HP service

NASA Astrophysics Data System (ADS)

Pflugmacher, Andreas; Heister, Hansbert; Heunecke, Otto

2009-12-01

OmniSTAR is one of the world's leading suppliers of satellite-based augmentation services for onshore and offshore GNSS applications. OmniSTAR currently offers three services: VBS, HP and XP. OmniSTAR VBS is the code-based service, suitable for sub-metre positioning accuracy. The HP and XP services provide sub-decimetre accuracy, with the HP service based on a precise differential methodology and the XP service uses precise absolute positioning. The sub-decimetre HP and XP services both have distinctive convergence behaviour, and the positioning task is essentially a time-dependent process during which the accuracy of the estimated coordinates continuously improves over time. To validate the capabilities of the OmniSTAR services, and in particular the HP (High Performance) service, globally distributed measurement campaigns were performed. The results of these investigations confirm that the HP service satisfies its high accuracy specification, but only after a sufficient initialisation phase. Two kinds of disturbances can handicap HP operation: lack of GNSS observations and outages of the augmentation signal. The most serious kind of disturbance is the former. Within a few seconds the achieved convergence level is completely lost. Outages in the reception of augmentation data merely affect the relevant period of the outage - the accuracy during the outage is degraded. Only longer interruptions lead to a loss of the HP solution. When HP convergence is lost, the HP process has to be re-initialized. If there are known points (so-called “seed points”) available, a shortened “kick-start”-initialization is possible. With the aid of seed points it only takes a few minutes to restore convergence.

SPHINX--an algorithm for taxonomic binning of metagenomic sequences.

PubMed

Mohammed, Monzoorul Haque; Ghosh, Tarini Shankar; Singh, Nitin Kumar; Mande, Sharmila S

2011-01-01

Compared with composition-based binning algorithms, the binning accuracy and specificity of alignment-based binning algorithms is significantly higher. However, being alignment-based, the latter class of algorithms require enormous amount of time and computing resources for binning huge metagenomic datasets. The motivation was to develop a binning approach that can analyze metagenomic datasets as rapidly as composition-based approaches, but nevertheless has the accuracy and specificity of alignment-based algorithms. This article describes a hybrid binning approach (SPHINX) that achieves high binning efficiency by utilizing the principles of both 'composition'- and 'alignment'-based binning algorithms. Validation results with simulated sequence datasets indicate that SPHINX is able to analyze metagenomic sequences as rapidly as composition-based algorithms. Furthermore, the binning efficiency (in terms of accuracy and specificity of assignments) of SPHINX is observed to be comparable with results obtained using alignment-based algorithms. A web server for the SPHINX algorithm is available at http://metagenomics.atc.tcs.com/SPHINX/.

Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel.

PubMed

Mitt, Mario; Kals, Mart; Pärn, Kalle; Gabriel, Stacey B; Lander, Eric S; Palotie, Aarno; Ripatti, Samuli; Morris, Andrew P; Metspalu, Andres; Esko, Tõnu; Mägi, Reedik; Palta, Priit

2017-06-01

Genetic imputation is a cost-efficient way to improve the power and resolution of genome-wide association (GWA) studies. Current publicly accessible imputation reference panels accurately predict genotypes for common variants with minor allele frequency (MAF)≥5% and low-frequency variants (0.5≤MAF<5%) across diverse populations, but the imputation of rare variation (MAF<0.5%) is still rather limited. In the current study, we evaluate imputation accuracy achieved with reference panels from diverse populations with a population-specific high-coverage (30 ×) whole-genome sequencing (WGS) based reference panel, comprising of 2244 Estonian individuals (0.25% of adult Estonians). Although the Estonian-specific panel contains fewer haplotypes and variants, the imputation confidence and accuracy of imputed low-frequency and rare variants was significantly higher. The results indicate the utility of population-specific reference panels for human genetic studies.

Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel

PubMed Central

Mitt, Mario; Kals, Mart; Pärn, Kalle; Gabriel, Stacey B; Lander, Eric S; Palotie, Aarno; Ripatti, Samuli; Morris, Andrew P; Metspalu, Andres; Esko, Tõnu; Mägi, Reedik; Palta, Priit

2017-01-01

Genetic imputation is a cost-efficient way to improve the power and resolution of genome-wide association (GWA) studies. Current publicly accessible imputation reference panels accurately predict genotypes for common variants with minor allele frequency (MAF)≥5% and low-frequency variants (0.5≤MAF<5%) across diverse populations, but the imputation of rare variation (MAF<0.5%) is still rather limited. In the current study, we evaluate imputation accuracy achieved with reference panels from diverse populations with a population-specific high-coverage (30 ×) whole-genome sequencing (WGS) based reference panel, comprising of 2244 Estonian individuals (0.25% of adult Estonians). Although the Estonian-specific panel contains fewer haplotypes and variants, the imputation confidence and accuracy of imputed low-frequency and rare variants was significantly higher. The results indicate the utility of population-specific reference panels for human genetic studies. PMID:28401899

Discontinuity Detection in the Shield Metal Arc Welding Process

PubMed Central

Cocota, José Alberto Naves; Garcia, Gabriel Carvalho; da Costa, Adilson Rodrigues; de Lima, Milton Sérgio Fernandes; Rocha, Filipe Augusto Santos; Freitas, Gustavo Medeiros

2017-01-01

This work proposes a new methodology for the detection of discontinuities in the weld bead applied in Shielded Metal Arc Welding (SMAW) processes. The detection system is based on two sensors—a microphone and piezoelectric—that acquire acoustic emissions generated during the welding. The feature vectors extracted from the sensor dataset are used to construct classifier models. The approaches based on Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers are able to identify with a high accuracy the three proposed weld bead classes: desirable weld bead, shrinkage cavity and burn through discontinuities. Experimental results illustrate the system’s high accuracy, greater than 90% for each class. A novel Hierarchical Support Vector Machine (HSVM) structure is proposed to make feasible the use of this system in industrial environments. This approach presented 96.6% overall accuracy. Given the simplicity of the equipment involved, this system can be applied in the metal transformation industries. PMID:28489045

Discontinuity Detection in the Shield Metal Arc Welding Process.

PubMed

Cocota, José Alberto Naves; Garcia, Gabriel Carvalho; da Costa, Adilson Rodrigues; de Lima, Milton Sérgio Fernandes; Rocha, Filipe Augusto Santos; Freitas, Gustavo Medeiros

2017-05-10

This work proposes a new methodology for the detection of discontinuities in the weld bead applied in Shielded Metal Arc Welding (SMAW) processes. The detection system is based on two sensors-a microphone and piezoelectric-that acquire acoustic emissions generated during the welding. The feature vectors extracted from the sensor dataset are used to construct classifier models. The approaches based on Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers are able to identify with a high accuracy the three proposed weld bead classes: desirable weld bead, shrinkage cavity and burn through discontinuities. Experimental results illustrate the system's high accuracy, greater than 90% for each class. A novel Hierarchical Support Vector Machine (HSVM) structure is proposed to make feasible the use of this system in industrial environments. This approach presented 96.6% overall accuracy. Given the simplicity of the equipment involved, this system can be applied in the metal transformation industries.

High accuracy digital aging monitor based on PLL-VCO circuit

NASA Astrophysics Data System (ADS)

Yuejun, Zhang; Zhidi, Jiang; Pengjun, Wang; Xuelong, Zhang

2015-01-01

As the manufacturing process is scaled down to the nanoscale, the aging phenomenon significantly affects the reliability and lifetime of integrated circuits. Consequently, the precise measurement of digital CMOS aging is a key aspect of nanoscale aging tolerant circuit design. This paper proposes a high accuracy digital aging monitor using phase-locked loop and voltage-controlled oscillator (PLL-VCO) circuit. The proposed monitor eliminates the circuit self-aging effect for the characteristic of PLL, whose frequency has no relationship with circuit aging phenomenon. The PLL-VCO monitor is implemented in TSMC low power 65 nm CMOS technology, and its area occupies 303.28 × 298.94 μm2. After accelerating aging tests, the experimental results show that PLL-VCO monitor improves accuracy about high temperature by 2.4% and high voltage by 18.7%.

An Adaptive Failure Detector Based on Quality of Service in Peer-to-Peer Networks

PubMed Central

Dong, Jian; Ren, Xiao; Zuo, Decheng; Liu, Hongwei

2014-01-01

The failure detector is one of the fundamental components that maintain high availability of Peer-to-Peer (P2P) networks. Under different network conditions, the adaptive failure detector based on quality of service (QoS) can achieve the detection time and accuracy required by upper applications with lower detection overhead. In P2P systems, complexity of network and high churn lead to high message loss rate. To reduce the impact on detection accuracy, baseline detection strategy based on retransmission mechanism has been employed widely in many P2P applications; however, Chen's classic adaptive model cannot describe this kind of detection strategy. In order to provide an efficient service of failure detection in P2P systems, this paper establishes a novel QoS evaluation model for the baseline detection strategy. The relationship between the detection period and the QoS is discussed and on this basis, an adaptive failure detector (B-AFD) is proposed, which can meet the quantitative QoS metrics under changing network environment. Meanwhile, it is observed from the experimental analysis that B-AFD achieves better detection accuracy and time with lower detection overhead compared to the traditional baseline strategy and the adaptive detectors based on Chen's model. Moreover, B-AFD has better adaptability to P2P network. PMID:25198005

Thematic accuracy assessment of the 2011 National Land Cover Database (NLCD)

USGS Publications Warehouse

Wickham, James; Stehman, Stephen V.; Gass, Leila; Dewitz, Jon; Sorenson, Daniel G.; Granneman, Brian J.; Poss, Richard V.; Baer, Lori Anne

2017-01-01

Accuracy assessment is a standard protocol of National Land Cover Database (NLCD) mapping. Here we report agreement statistics between map and reference labels for NLCD 2011, which includes land cover for ca. 2001, ca. 2006, and ca. 2011. The two main objectives were assessment of agreement between map and reference labels for the three, single-date NLCD land cover products at Level II and Level I of the classification hierarchy, and agreement for 17 land cover change reporting themes based on Level I classes (e.g., forest loss; forest gain; forest, no change) for three change periods (2001–2006, 2006–2011, and 2001–2011). The single-date overall accuracies were 82%, 83%, and 83% at Level II and 88%, 89%, and 89% at Level I for 2011, 2006, and 2001, respectively. Many class-specific user's accuracies met or exceeded a previously established nominal accuracy benchmark of 85%. Overall accuracies for 2006 and 2001 land cover components of NLCD 2011 were approximately 4% higher (at Level II and Level I) than the overall accuracies for the same components of NLCD 2006. The high Level I overall, user's, and producer's accuracies for the single-date eras in NLCD 2011 did not translate into high class-specific user's and producer's accuracies for many of the 17 change reporting themes. User's accuracies were high for the no change reporting themes, commonly exceeding 85%, but were typically much lower for the reporting themes that represented change. Only forest loss, forest gain, and urban gain had user's accuracies that exceeded 70%. Lower user's accuracies for the other change reporting themes may be attributable to the difficulty in determining the context of grass (e.g., open urban, grassland, agriculture) and between the components of the forest-shrubland-grassland gradient at either the mapping phase, reference label assignment phase, or both. NLCD 2011 user's accuracies for forest loss, forest gain, and urban gain compare favorably with results from other land cover change accuracy assessments.

Wind velocity measurement accuracy with highly stable 12 mJ/pulse high repetition rate CO2 laser master oscillator power amplifier

NASA Technical Reports Server (NTRS)

Bilbro, James W.; Johnson, Steven C.; Rothermel, Jeffry

1987-01-01

A coherent CO2 lidar operating in a master oscillator power amplifier configuration (MOPA) is described for both ground-based and airborne operation. Representative data taken from measurements against stationary targets in both the ground-based and airborne configurations are shown for the evaluation of the frequency stability of the system. Examples of data are also given which show the results of anomalous system operation. Overall results demonstrate that velocity measurements can be performed consistently to an accuracy of + or - 0.5 m/s and in some cases + or - 0.1 m/s.

Adaptive optics based non-null interferometry for optical free form surfaces test

NASA Astrophysics Data System (ADS)

Zhang, Lei; Zhou, Sheng; Li, Jingsong; Yu, Benli

2018-03-01

An adaptive optics based non-null interferometry (ANI) is proposed for optical free form surfaces testing, in which an open-loop deformable mirror (DM) is employed as a reflective compensator, to compensate various low-order aberrations flexibly. The residual wavefront aberration is treated by the multi-configuration ray tracing (MCRT) algorithm. The MCRT algorithm based on the simultaneous ray tracing for multiple system models, in which each model has different DM surface deformation. With the MCRT algorithm, the final figure error can be extracted together with the surface misalignment aberration correction after the initial system calibration. The flexible test for free form surface is achieved with high accuracy, without auxiliary device for DM deformation monitoring. Experiments proving the feasibility, repeatability and high accuracy of the ANI were carried out to test a bi-conic surface and a paraboloidal surface, with a high stable ALPAOTM DM88. The accuracy of the final test result of the paraboloidal surface was better than 1/20 Μ PV value. It is a successful attempt in research of flexible optical free form surface metrology and would have enormous potential in future application with the development of the DM technology.

High resolution mapping of development in the wildland-urban interface using object based image extraction.

PubMed

Caggiano, Michael D; Tinkham, Wade T; Hoffman, Chad; Cheng, Antony S; Hawbaker, Todd J

2016-10-01

The wildland-urban interface (WUI), the area where human development encroaches on undeveloped land, is expanding throughout the western United States resulting in increased wildfire risk to homes and communities. Although census based mapping efforts have provided insights into the pattern of development and expansion of the WUI at regional and national scales, these approaches do not provide sufficient detail for fine-scale fire and emergency management planning, which requires maps of individual building locations. Although fine-scale maps of the WUI have been developed, they are often limited in their spatial extent, have unknown accuracies and biases, and are costly to update over time. In this paper we assess a semi-automated Object Based Image Analysis (OBIA) approach that utilizes 4-band multispectral National Aerial Image Program (NAIP) imagery for the detection of individual buildings within the WUI. We evaluate this approach by comparing the accuracy and overall quality of extracted buildings to a building footprint control dataset. In addition, we assessed the effects of buffer distance, topographic conditions, and building characteristics on the accuracy and quality of building extraction. The overall accuracy and quality of our approach was positively related to buffer distance, with accuracies ranging from 50 to 95% for buffer distances from 0 to 100 m. Our results also indicate that building detection was sensitive to building size, with smaller outbuildings (footprints less than 75 m 2 ) having detection rates below 80% and larger residential buildings having detection rates above 90%. These findings demonstrate that this approach can successfully identify buildings in the WUI in diverse landscapes while achieving high accuracies at buffer distances appropriate for most fire management applications while overcoming cost and time constraints associated with traditional approaches. This study is unique in that it evaluates the ability of an OBIA approach to extract highly detailed data on building locations in a WUI setting.

High resolution mapping of development in the wildland-urban interface using object based image extraction

USGS Publications Warehouse

Caggiano, Michael D.; Tinkham, Wade T.; Hoffman, Chad; Cheng, Antony S.; Hawbaker, Todd J.

2016-01-01

The wildland-urban interface (WUI), the area where human development encroaches on undeveloped land, is expanding throughout the western United States resulting in increased wildfire risk to homes and communities. Although census based mapping efforts have provided insights into the pattern of development and expansion of the WUI at regional and national scales, these approaches do not provide sufficient detail for fine-scale fire and emergency management planning, which requires maps of individual building locations. Although fine-scale maps of the WUI have been developed, they are often limited in their spatial extent, have unknown accuracies and biases, and are costly to update over time. In this paper we assess a semi-automated Object Based Image Analysis (OBIA) approach that utilizes 4-band multispectral National Aerial Image Program (NAIP) imagery for the detection of individual buildings within the WUI. We evaluate this approach by comparing the accuracy and overall quality of extracted buildings to a building footprint control dataset. In addition, we assessed the effects of buffer distance, topographic conditions, and building characteristics on the accuracy and quality of building extraction. The overall accuracy and quality of our approach was positively related to buffer distance, with accuracies ranging from 50 to 95% for buffer distances from 0 to 100 m. Our results also indicate that building detection was sensitive to building size, with smaller outbuildings (footprints less than 75 m2) having detection rates below 80% and larger residential buildings having detection rates above 90%. These findings demonstrate that this approach can successfully identify buildings in the WUI in diverse landscapes while achieving high accuracies at buffer distances appropriate for most fire management applications while overcoming cost and time constraints associated with traditional approaches. This study is unique in that it evaluates the ability of an OBIA approach to extract highly detailed data on building locations in a WUI setting.

Automatic Generation of High Quality DSM Based on IRS-P5 Cartosat-1 Stereo Data

NASA Astrophysics Data System (ADS)

d'Angelo, Pablo; Uttenthaler, Andreas; Carl, Sebastian; Barner, Frithjof; Reinartz, Peter

2010-12-01

IRS-P5 Cartosat-1 high resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on IRS-P5 Cartosat-1 imagery is presented, with an emphasis on automated processing and product quality. The proposed system processes IRS-P5 level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The described method uses an RPC correction based on DSM alignment instead of using reference images with a lower lateral accuracy, this results in improved geolocation of the DSMs and orthoimages. Following RPC correction, highly detailed DSMs with 5 m grid spacing are derived using Semiglobal Matching. The proposed method is part of an operational Cartosat-1 processor for the generation of a high resolution DSM. Evaluation of 18 scenes against independent ground truth measurements indicates a mean lateral error (CE90) of 6.7 meters and a mean vertical accuracy (LE90) of 5.1 meters.

Mediterranean Land Use and Land Cover Classification Assessment Using High Spatial Resolution Data

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Boteva, Silvena

2016-10-01

Landscape fragmentation is noticeably practiced in Mediterranean regions and imposes substantial complications in several satellite image classification methods. To some extent, high spatial resolution data were able to overcome such complications. For better classification performances in Land Use Land Cover (LULC) mapping, the current research adopts different classification methods comparison for LULC mapping using Sentinel-2 satellite as a source of high spatial resolution. Both of pixel-based and an object-based classification algorithms were assessed; the pixel-based approach employs Maximum Likelihood (ML), Artificial Neural Network (ANN) algorithms, Support Vector Machine (SVM), and, the object-based classification uses the Nearest Neighbour (NN) classifier. Stratified Masking Process (SMP) that integrates a ranking process within the classes based on spectral fluctuation of the sum of the training and testing sites was implemented. An analysis of the overall and individual accuracy of the classification results of all four methods reveals that the SVM classifier was the most efficient overall by distinguishing most of the classes with the highest accuracy. NN succeeded to deal with artificial surface classes in general while agriculture area classes, and forest and semi-natural area classes were segregated successfully with SVM. Furthermore, a comparative analysis indicates that the conventional classification method yielded better accuracy results than the SMP method overall with both classifiers used, ML and SVM.

Overlay accuracy on a flexible web with a roll printing process based on a roll-to-roll system.

PubMed

Chang, Jaehyuk; Lee, Sunggun; Lee, Ki Beom; Lee, Seungjun; Cho, Young Tae; Seo, Jungwoo; Lee, Sukwon; Jo, Gugrae; Lee, Ki-yong; Kong, Hyang-Shik; Kwon, Sin

2015-05-01

For high-quality flexible devices from printing processes based on Roll-to-Roll (R2R) systems, overlay alignment during the patterning of each functional layer poses a major challenge. The reason is because flexible substrates have a relatively low stiffness compared with rigid substrates, and they are easily deformed during web handling in the R2R system. To achieve a high overlay accuracy for a flexible substrate, it is important not only to develop web handling modules (such as web guiding, tension control, winding, and unwinding) and a precise printing tool but also to control the synchronization of each unit in the total system. A R2R web handling system and reverse offset printing process were developed in this work, and an overlay between the 1st and 2nd layers of ±5μm on a 500 mm-wide film was achieved at a σ level of 2.4 and 2.8 (x and y directions, respectively) in a continuous R2R printing process. This paper presents the components and mechanisms used in reverse offset printing based on a R2R system and the printing results including positioning accuracy and overlay alignment accuracy.

Parametric diagnosis of the adaptive gas path in the automatic control system of the aircraft engine

NASA Astrophysics Data System (ADS)

Kuznetsova, T. A.

2017-01-01

The paper dwells on the adaptive multimode mathematical model of the gas-turbine aircraft engine (GTE) embedded in the automatic control system (ACS). The mathematical model is based on the throttle performances, and is characterized by high accuracy of engine parameters identification in stationary and dynamic modes. The proposed on-board engine model is the state space linearized low-level simulation. The engine health is identified by the influence of the coefficient matrix. The influence coefficient is determined by the GTE high-level mathematical model based on measurements of gas-dynamic parameters. In the automatic control algorithm, the sum of squares of the deviation between the parameters of the mathematical model and real GTE is minimized. The proposed mathematical model is effectively used for gas path defects detecting in on-line GTE health monitoring. The accuracy of the on-board mathematical model embedded in ACS determines the quality of adaptive control and reliability of the engine. To improve the accuracy of identification solutions and sustainability provision, the numerical method of Monte Carlo was used. The parametric diagnostic algorithm based on the LPτ - sequence was developed and tested. Analysis of the results suggests that the application of the developed algorithms allows achieving higher identification accuracy and reliability than similar models used in practice.

System Design, Calibration and Performance Analysis of a Novel 360° Stereo Panoramic Mobile Mapping System

NASA Astrophysics Data System (ADS)

Blaser, S.; Nebiker, S.; Cavegn, S.

2017-05-01

Image-based mobile mapping systems enable the efficient acquisition of georeferenced image sequences, which can later be exploited in cloud-based 3D geoinformation services. In order to provide a 360° coverage with accurate 3D measuring capabilities, we present a novel 360° stereo panoramic camera configuration. By using two 360° panorama cameras tilted forward and backward in combination with conventional forward and backward looking stereo camera systems, we achieve a full 360° multi-stereo coverage. We furthermore developed a fully operational new mobile mapping system based on our proposed approach, which fulfils our high accuracy requirements. We successfully implemented a rigorous sensor and system calibration procedure, which allows calibrating all stereo systems with a superior accuracy compared to that of previous work. Our study delivered absolute 3D point accuracies in the range of 4 to 6 cm and relative accuracies of 3D distances in the range of 1 to 3 cm. These results were achieved in a challenging urban area. Furthermore, we automatically reconstructed a 3D city model of our study area by employing all captured and georeferenced mobile mapping imagery. The result is a very high detailed and almost complete 3D city model of the street environment.

An Efficient Neural-Network-Based Microseismic Monitoring Platform for Hydraulic Fracture on an Edge Computing Architecture.

PubMed

Zhang, Xiaopu; Lin, Jun; Chen, Zubin; Sun, Feng; Zhu, Xi; Fang, Gengfa

2018-06-05

Microseismic monitoring is one of the most critical technologies for hydraulic fracturing in oil and gas production. To detect events in an accurate and efficient way, there are two major challenges. One challenge is how to achieve high accuracy due to a poor signal-to-noise ratio (SNR). The other one is concerned with real-time data transmission. Taking these challenges into consideration, an edge-computing-based platform, namely Edge-to-Center LearnReduce, is presented in this work. The platform consists of a data center with many edge components. At the data center, a neural network model combined with convolutional neural network (CNN) and long short-term memory (LSTM) is designed and this model is trained by using previously obtained data. Once the model is fully trained, it is sent to edge components for events detection and data reduction. At each edge component, a probabilistic inference is added to the neural network model to improve its accuracy. Finally, the reduced data is delivered to the data center. Based on experiment results, a high detection accuracy (over 96%) with less transmitted data (about 90%) was achieved by using the proposed approach on a microseismic monitoring system. These results show that the platform can simultaneously improve the accuracy and efficiency of microseismic monitoring.

Implementation of High Time Delay Accuracy of Ultrasonic Phased Array Based on Interpolation CIC Filter

PubMed Central

Liu, Peilu; Li, Xinghua; Li, Haopeng; Su, Zhikun; Zhang, Hongxu

2017-01-01

In order to improve the accuracy of ultrasonic phased array focusing time delay, analyzing the original interpolation Cascade-Integrator-Comb (CIC) filter, an 8× interpolation CIC filter parallel algorithm was proposed, so that interpolation and multichannel decomposition can simultaneously process. Moreover, we summarized the general formula of arbitrary multiple interpolation CIC filter parallel algorithm and established an ultrasonic phased array focusing time delay system based on 8× interpolation CIC filter parallel algorithm. Improving the algorithmic structure, 12.5% of addition and 29.2% of multiplication was reduced, meanwhile the speed of computation is still very fast. Considering the existing problems of the CIC filter, we compensated the CIC filter; the compensated CIC filter’s pass band is flatter, the transition band becomes steep, and the stop band attenuation increases. Finally, we verified the feasibility of this algorithm on Field Programming Gate Array (FPGA). In the case of system clock is 125 MHz, after 8× interpolation filtering and decomposition, time delay accuracy of the defect echo becomes 1 ns. Simulation and experimental results both show that the algorithm we proposed has strong feasibility. Because of the fast calculation, small computational amount and high resolution, this algorithm is especially suitable for applications with high time delay accuracy and fast detection. PMID:29023385

Implementation of High Time Delay Accuracy of Ultrasonic Phased Array Based on Interpolation CIC Filter.

PubMed

Liu, Peilu; Li, Xinghua; Li, Haopeng; Su, Zhikun; Zhang, Hongxu

2017-10-12

In order to improve the accuracy of ultrasonic phased array focusing time delay, analyzing the original interpolation Cascade-Integrator-Comb (CIC) filter, an 8× interpolation CIC filter parallel algorithm was proposed, so that interpolation and multichannel decomposition can simultaneously process. Moreover, we summarized the general formula of arbitrary multiple interpolation CIC filter parallel algorithm and established an ultrasonic phased array focusing time delay system based on 8× interpolation CIC filter parallel algorithm. Improving the algorithmic structure, 12.5% of addition and 29.2% of multiplication was reduced, meanwhile the speed of computation is still very fast. Considering the existing problems of the CIC filter, we compensated the CIC filter; the compensated CIC filter's pass band is flatter, the transition band becomes steep, and the stop band attenuation increases. Finally, we verified the feasibility of this algorithm on Field Programming Gate Array (FPGA). In the case of system clock is 125 MHz, after 8× interpolation filtering and decomposition, time delay accuracy of the defect echo becomes 1 ns. Simulation and experimental results both show that the algorithm we proposed has strong feasibility. Because of the fast calculation, small computational amount and high resolution, this algorithm is especially suitable for applications with high time delay accuracy and fast detection.

Online virtual isocenter based radiation field targeting for high performance small animal microirradiation

NASA Astrophysics Data System (ADS)

Stewart, James M. P.; Ansell, Steve; Lindsay, Patricia E.; Jaffray, David A.

2015-12-01

Advances in precision microirradiators for small animal radiation oncology studies have provided the framework for novel translational radiobiological studies. Such systems target radiation fields at the scale required for small animal investigations, typically through a combination of on-board computed tomography image guidance and fixed, interchangeable collimators. Robust targeting accuracy of these radiation fields remains challenging, particularly at the millimetre scale field sizes achievable by the majority of microirradiators. Consistent and reproducible targeting accuracy is further hindered as collimators are removed and inserted during a typical experimental workflow. This investigation quantified this targeting uncertainty and developed an online method based on a virtual treatment isocenter to actively ensure high performance targeting accuracy for all radiation field sizes. The results indicated that the two-dimensional field placement uncertainty was as high as 1.16 mm at isocenter, with simulations suggesting this error could be reduced to 0.20 mm using the online correction method. End-to-end targeting analysis of a ball bearing target on radiochromic film sections showed an improved targeting accuracy with the three-dimensional vector targeting error across six different collimators reduced from 0.56+/- 0.05 mm (mean  ±  SD) to 0.05+/- 0.05 mm for an isotropic imaging voxel size of 0.1 mm.

Research on navigation of satellite constellation based on an asynchronous observation model using X-ray pulsar

NASA Astrophysics Data System (ADS)

Guo, Pengbin; Sun, Jian; Hu, Shuling; Xue, Ju

2018-02-01

Pulsar navigation is a promising navigation method for high-altitude orbit space tasks or deep space exploration. At present, an important reason for restricting the development of pulsar navigation is that navigation accuracy is not high due to the slow update of the measurements. In order to improve the accuracy of pulsar navigation, an asynchronous observation model which can improve the update rate of the measurements is proposed on the basis of satellite constellation which has a broad space for development because of its visibility and reliability. The simulation results show that the asynchronous observation model improves the positioning accuracy by 31.48% and velocity accuracy by 24.75% than that of the synchronous observation model. With the new Doppler effects compensation method in the asynchronous observation model proposed in this paper, the positioning accuracy is improved by 32.27%, and the velocity accuracy is improved by 34.07% than that of the traditional method. The simulation results show that without considering the clock error will result in a filtering divergence.

Evaluation of a Moderate Resolution, Satellite-Based Impervious Surface Map Using an Independent, High-Resolution Validation Dataset

EPA Science Inventory

Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data ...

Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness

PubMed Central

Li, Jin; Tran, Maggie; Siwabessy, Justy

2016-01-01

Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and caution should be taken when applying filter FS methods in selecting predictive models. PMID:26890307

Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness.

PubMed

Li, Jin; Tran, Maggie; Siwabessy, Justy

2016-01-01

Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia's marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to 'small p and large n' problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and caution should be taken when applying filter FS methods in selecting predictive models.

Evaluation of various mental task combinations for near-infrared spectroscopy-based brain-computer interfaces

NASA Astrophysics Data System (ADS)

Hwang, Han-Jeong; Lim, Jeong-Hwan; Kim, Do-Won; Im, Chang-Hwan

2014-07-01

A number of recent studies have demonstrated that near-infrared spectroscopy (NIRS) is a promising neuroimaging modality for brain-computer interfaces (BCIs). So far, most NIRS-based BCI studies have focused on enhancing the accuracy of the classification of different mental tasks. In the present study, we evaluated the performances of a variety of mental task combinations in order to determine the mental task pairs that are best suited for customized NIRS-based BCIs. To this end, we recorded event-related hemodynamic responses while seven participants performed eight different mental tasks. Classification accuracies were then estimated for all possible pairs of the eight mental tasks (C=28). Based on this analysis, mental task combinations with relatively high classification accuracies frequently included the following three mental tasks: "mental multiplication," "mental rotation," and "right-hand motor imagery." Specifically, mental task combinations consisting of two of these three mental tasks showed the highest mean classification accuracies. It is expected that our results will be a useful reference to reduce the time needed for preliminary tests when discovering individual-specific mental task combinations.

A Novel Energy-Efficient Approach for Human Activity Recognition.

PubMed

Zheng, Lingxiang; Wu, Dihong; Ruan, Xiaoyang; Weng, Shaolin; Peng, Ao; Tang, Biyu; Lu, Hai; Shi, Haibin; Zheng, Huiru

2017-09-08

In this paper, we propose a novel energy-efficient approach for mobile activity recognition system (ARS) to detect human activities. The proposed energy-efficient ARS, using low sampling rates, can achieve high recognition accuracy and low energy consumption. A novel classifier that integrates hierarchical support vector machine and context-based classification (HSVMCC) is presented to achieve a high accuracy of activity recognition when the sampling rate is less than the activity frequency, i.e., the Nyquist sampling theorem is not satisfied. We tested the proposed energy-efficient approach with the data collected from 20 volunteers (14 males and six females) and the average recognition accuracy of around 96.0% was achieved. Results show that using a low sampling rate of 1Hz can save 17.3% and 59.6% of energy compared with the sampling rates of 5 Hz and 50 Hz. The proposed low sampling rate approach can greatly reduce the power consumption while maintaining high activity recognition accuracy. The composition of power consumption in online ARS is also investigated in this paper.

High Accuracy Monocular SFM and Scale Correction for Autonomous Driving.

PubMed

Song, Shiyu; Chandraker, Manmohan; Guest, Clark C

2016-04-01

We present a real-time monocular visual odometry system that achieves high accuracy in real-world autonomous driving applications. First, we demonstrate robust monocular SFM that exploits multithreading to handle driving scenes with large motions and rapidly changing imagery. To correct for scale drift, we use known height of the camera from the ground plane. Our second contribution is a novel data-driven mechanism for cue combination that allows highly accurate ground plane estimation by adapting observation covariances of multiple cues, such as sparse feature matching and dense inter-frame stereo, based on their relative confidences inferred from visual data on a per-frame basis. Finally, we demonstrate extensive benchmark performance and comparisons on the challenging KITTI dataset, achieving accuracy comparable to stereo and exceeding prior monocular systems. Our SFM system is optimized to output pose within 50 ms in the worst case, while average case operation is over 30 fps. Our framework also significantly boosts the accuracy of applications like object localization that rely on the ground plane.

Evaluation of mechanical accuracy for couch‐based tracking system (CBTS)

PubMed Central

Lee, Suk; Chang, Kyung‐Hwan; Shim, Jand Bo; Cao, Yuanjie; Lee, Chang Ki; Cho, Sam Ju; Yang, Dae Sik; Park, Young Je; Yoon, Won Seob

2012-01-01

This study evaluated the mechanical accuracy of an in‐house–developed couch‐based tracking system (CBTS) according to respiration data. The overall delay time of the CBTS was calculated, and the accuracy, reproducibility, and loading effect of the CBTS were evaluated according to the sinusoidal waveform and various respiratory motion data of real patients with and without a volunteer weighing 75 kg. The root mean square (rms) error of the accuracy, the reproducibility, and the sagging measurements were calculated for the three axes (X, Y, and Z directions) of the CBTS. The overall delay time of the CBTS was 0.251 sec. The accuracy and reproducibility in the Z direction in real patient data were poor, as indicated by high rms errors. The results of the loading effect were within 1.0 mm in all directions. This novel CBTS has the potential for clinical application for tumor tracking in radiation therapy. PACS number: 87.55.ne PMID:23149775

Analysis of parameters for technological equipment of parallel kinematics based on rods of variable length for processing accuracy assurance

NASA Astrophysics Data System (ADS)

Koltsov, A. G.; Shamutdinov, A. H.; Blokhin, D. A.; Krivonos, E. V.

2018-01-01

A new classification of parallel kinematics mechanisms on symmetry coefficient, being proportional to mechanism stiffness and accuracy of the processing product using the technological equipment under study, is proposed. A new version of the Stewart platform with a high symmetry coefficient is presented for analysis. The workspace of the mechanism under study is described, this space being a complex solid figure. The workspace end points are reached by the center of the mobile platform which moves in parallel related to the base plate. Parameters affecting the processing accuracy, namely the static and dynamic stiffness, natural vibration frequencies are determined. The capability assessment of the mechanism operation under various loads, taking into account resonance phenomena at different points of the workspace, was conducted. The study proved that stiffness and therefore, processing accuracy with the use of the above mentioned mechanisms are comparable with the stiffness and accuracy of medium-sized series-produced machines.

Preliminary navigation accuracy analysis for the TDRSS Onboard Navigation System (TONS) experiment on EP/EUVE

NASA Technical Reports Server (NTRS)

Gramling, C. J.; Long, A. C.; Lee, T.; Ottenstein, N. A.; Samii, M. V.

1991-01-01

A Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (TONS) is currently being developed by NASA to provide a high accuracy autonomous navigation capability for users of TDRSS and its successor, the Advanced TDRSS (ATDRSS). The fully autonomous user onboard navigation system will support orbit determination, time determination, and frequency determination, based on observation of a continuously available, unscheduled navigation beacon signal. A TONS experiment will be performed in conjunction with the Explorer Platform (EP) Extreme Ultraviolet Explorer (EUVE) mission to flight quality TONS Block 1. An overview is presented of TONS and a preliminary analysis of the navigation accuracy anticipated for the TONS experiment. Descriptions of the TONS experiment and the associated navigation objectives, as well as a description of the onboard navigation algorithms, are provided. The accuracy of the selected algorithms is evaluated based on the processing of realistic simulated TDRSS one way forward link Doppler measurements. The analysis process is discussed and the associated navigation accuracy results are presented.

Determining the accuracy of maximum likelihood parameter estimates with colored residuals

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.; Klein, Vladislav

1994-01-01

An important part of building high fidelity mathematical models based on measured data is calculating the accuracy associated with statistical estimates of the model parameters. Indeed, without some idea of the accuracy of parameter estimates, the estimates themselves have limited value. In this work, an expression based on theoretical analysis was developed to properly compute parameter accuracy measures for maximum likelihood estimates with colored residuals. This result is important because experience from the analysis of measured data reveals that the residuals from maximum likelihood estimation are almost always colored. The calculations involved can be appended to conventional maximum likelihood estimation algorithms. Simulated data runs were used to show that the parameter accuracy measures computed with this technique accurately reflect the quality of the parameter estimates from maximum likelihood estimation without the need for analysis of the output residuals in the frequency domain or heuristically determined multiplication factors. The result is general, although the application studied here is maximum likelihood estimation of aerodynamic model parameters from flight test data.

Dustfall Effect on Hyperspectral Inversion of Chlorophyll Content - a Laboratory Experiment

NASA Astrophysics Data System (ADS)

Chen, Yuteng; Ma, Baodong; Li, Xuexin; Zhang, Song; Wu, Lixin

2018-04-01

Dust pollution is serious in many areas of China. It is of great significance to estimate chlorophyll content of vegetation accurately by hyperspectral remote sensing for assessing the vegetation growth status and monitoring the ecological environment in dusty areas. By using selected vegetation indices including Medium Resolution Imaging Spectrometer Terrestrial Chlorophyll Index (MTCI) Double Difference Index (DD) and Red Edge Position Index (REP), chlorophyll inversion models were built to study the accuracy of hyperspectral inversion of chlorophyll content based on a laboratory experiment. The results show that: (1) REP exponential model has the most stable accuracy for inversion of chlorophyll content in dusty environment. When dustfall amount is less than 80 g/m2, the inversion accuracy based on REP is stable with the variation of dustfall amount. When dustfall amount is greater than 80 g/m2, the inversion accuracy is slightly fluctuation. (2) Inversion accuracy of DD is worst among three models. (3) MTCI logarithm model has high inversion accuracy when dustfall amount is less than 80 g/m2; When dustfall amount is greater than 80 g/m2, inversion accuracy decreases regularly and inversion accuracy of modified MTCI (mMTCI) increases significantly. The results provide experimental basis and theoretical reference for hyperspectral remote sensing inversion of chlorophyll content.

The Combination of Micro Diaphragm Pumps and Flow Sensors for Single Stroke Based Liquid Flow Control

PubMed Central

Jenke, Christoph; Pallejà Rubio, Jaume; Kibler, Sebastian; Häfner, Johannes; Richter, Martin; Kutter, Christoph

2017-01-01

With the combination of micropumps and flow sensors, highly accurate and secure closed-loop controlled micro dosing systems for liquids are possible. Implementing a single stroke based control mode with piezoelectrically driven micro diaphragm pumps can provide a solution for dosing of volumes down to nanoliters or variable average flow rates in the range of nL/min to μL/min. However, sensor technologies feature a yet undetermined accuracy for measuring highly pulsatile micropump flow. Two miniaturizable in-line sensor types providing electrical readout—differential pressure based flow sensors and thermal calorimetric flow sensors—are evaluated for their suitability of combining them with mircopumps. Single stroke based calibration of the sensors was carried out with a new method, comparing displacement volumes and sensor flow volumes. Limitations of accuracy and performance for single stroke based flow control are described. Results showed that besides particle robustness of sensors, controlling resistive and capacitive damping are key aspects for setting up reproducible and reliable liquid dosing systems. Depending on the required average flow or defined volume, dosing systems with an accuracy of better than 5% for the differential pressure based sensor and better than 6.5% for the thermal calorimeter were achieved. PMID:28368344

Developing Local Oral Reading Fluency Cut Scores for Predicting High-Stakes Test Performance

ERIC Educational Resources Information Center

Grapin, Sally L.; Kranzler, John H.; Waldron, Nancy; Joyce-Beaulieu, Diana; Algina, James

2017-01-01

This study evaluated the classification accuracy of a second grade oral reading fluency curriculum-based measure (R-CBM) in predicting third grade state test performance. It also compared the long-term classification accuracy of local and publisher-recommended R-CBM cut scores. Participants were 266 students who were divided into a calibration…

Multi-task Gaussian process for imputing missing data in multi-trait and multi-environment trials.

PubMed

Hori, Tomoaki; Montcho, David; Agbangla, Clement; Ebana, Kaworu; Futakuchi, Koichi; Iwata, Hiroyoshi

2016-11-01

A method based on a multi-task Gaussian process using self-measuring similarity gave increased accuracy for imputing missing phenotypic data in multi-trait and multi-environment trials. Multi-environmental trial (MET) data often encounter the problem of missing data. Accurate imputation of missing data makes subsequent analysis more effective and the results easier to understand. Moreover, accurate imputation may help to reduce the cost of phenotyping for thinned-out lines tested in METs. METs are generally performed for multiple traits that are correlated to each other. Correlation among traits can be useful information for imputation, but single-trait-based methods cannot utilize information shared by traits that are correlated. In this paper, we propose imputation methods based on a multi-task Gaussian process (MTGP) using self-measuring similarity kernels reflecting relationships among traits, genotypes, and environments. This framework allows us to use genetic correlation among multi-trait multi-environment data and also to combine MET data and marker genotype data. We compared the accuracy of three MTGP methods and iterative regularized PCA using rice MET data. Two scenarios for the generation of missing data at various missing rates were considered. The MTGP performed a better imputation accuracy than regularized PCA, especially at high missing rates. Under the 'uniform' scenario, in which missing data arise randomly, inclusion of marker genotype data in the imputation increased the imputation accuracy at high missing rates. Under the 'fiber' scenario, in which missing data arise in all traits for some combinations between genotypes and environments, the inclusion of marker genotype data decreased the imputation accuracy for most traits while increasing the accuracy in a few traits remarkably. The proposed methods will be useful for solving the missing data problem in MET data.

Mapping seabed sediments: Comparison of manual, geostatistical, object-based image analysis and machine learning approaches

NASA Astrophysics Data System (ADS)

Diesing, Markus; Green, Sophie L.; Stephens, David; Lark, R. Murray; Stewart, Heather A.; Dove, Dayton

2014-08-01

Marine spatial planning and conservation need underpinning with sufficiently detailed and accurate seabed substrate and habitat maps. Although multibeam echosounders enable us to map the seabed with high resolution and spatial accuracy, there is still a lack of fit-for-purpose seabed maps. This is due to the high costs involved in carrying out systematic seabed mapping programmes and the fact that the development of validated, repeatable, quantitative and objective methods of swath acoustic data interpretation is still in its infancy. We compared a wide spectrum of approaches including manual interpretation, geostatistics, object-based image analysis and machine-learning to gain further insights into the accuracy and comparability of acoustic data interpretation approaches based on multibeam echosounder data (bathymetry, backscatter and derivatives) and seabed samples with the aim to derive seabed substrate maps. Sample data were split into a training and validation data set to allow us to carry out an accuracy assessment. Overall thematic classification accuracy ranged from 67% to 76% and Cohen's kappa varied between 0.34 and 0.52. However, these differences were not statistically significant at the 5% level. Misclassifications were mainly associated with uncommon classes, which were rarely sampled. Map outputs were between 68% and 87% identical. To improve classification accuracy in seabed mapping, we suggest that more studies on the effects of factors affecting the classification performance as well as comparative studies testing the performance of different approaches need to be carried out with a view to developing guidelines for selecting an appropriate method for a given dataset. In the meantime, classification accuracy might be improved by combining different techniques to hybrid approaches and multi-method ensembles.

Land cover in Upper Egypt assessed using regional and global land cover products derived from MODIS imagery.

PubMed

Fuller, Douglas O; Parenti, Michael S; Gad, Adel M; Beier, John C

2012-01-01

Irrigation along the Nile River has resulted in dramatic changes in the biophysical environment of Upper Egypt. In this study we used a combination of MODIS 250 m NDVI data and Landsat imagery to identify areas that changed from 2001-2008 as a result of irrigation and water-level fluctuations in the Nile River and nearby water bodies. We used two different methods of time series analysis -- principal components (PCA) and harmonic decomposition (HD), applied to the MODIS 250 m NDVI images to derive simple three-class land cover maps and then assessed their accuracy using a set of reference polygons derived from 30 m Landsat 5 and 7 imagery. We analyzed our MODIS 250 m maps against a new MODIS global land cover product (MOD12Q1 collection 5) to assess whether regionally specific mapping approaches are superior to a standard global product. Results showed that the accuracy of the PCA-based product was greater than the accuracy of either the HD or MOD12Q1 products for the years 2001, 2003, and 2008. However, the accuracy of the PCA product was only slightly better than the MOD12Q1 for 2001 and 2003. Overall, the results suggest that our PCA-based approach produces a high level of user and producer accuracies, although the MOD12Q1 product also showed consistently high accuracy. Overlay of 2001-2008 PCA-based maps showed a net increase of 12 129 ha of irrigated vegetation, with the largest increase found from 2006-2008 around the Districts of Edfu and Kom Ombo. This result was unexpected in light of ambitious government plans to develop 336 000 ha of irrigated agriculture around the Toshka Lakes.

Automatic extraction of plots from geo-registered UAS imagery of crop fields with complex planting schemes

NASA Astrophysics Data System (ADS)

Hearst, Anthony A.

Complex planting schemes are common in experimental crop fields and can make it difficult to extract plots of interest from high-resolution imagery of the fields gathered by Unmanned Aircraft Systems (UAS). This prevents UAS imagery from being applied in High-Throughput Precision Phenotyping and other areas of agricultural research. If the imagery is accurately geo-registered, then it may be possible to extract plots from the imagery based on their map coordinates. To test this approach, a UAS was used to acquire visual imagery of 5 ha of soybean fields containing 6.0 m2 plots in a complex planting scheme. Sixteen artificial targets were setup in the fields before flights and different spatial configurations of 0 to 6 targets were used as Ground Control Points (GCPs) for geo-registration, resulting in a total of 175 geo-registered image mosaics with a broad range of geo-registration accuracies. Geo-registration accuracy was quantified based on the horizontal Root Mean Squared Error (RMSE) of targets used as checkpoints. Twenty test plots were extracted from the geo-registered imagery. Plot extraction accuracy was quantified based on the percentage of the desired plot area that was extracted. It was found that using 4 GCPs along the perimeter of the field minimized the horizontal RMSE and enabled a plot extraction accuracy of at least 70%, with a mean plot extraction accuracy of 92%. Future work will focus on further enhancing the plot extraction accuracy through additional image processing techniques so that it becomes sufficiently accurate for all practical purposes in agricultural research and potentially other areas of research.

Experimental studies of high-accuracy RFID localization with channel impairments

NASA Astrophysics Data System (ADS)

Pauls, Eric; Zhang, Yimin D.

2015-05-01

Radio frequency identification (RFID) systems present an incredibly cost-effective and easy-to-implement solution to close-range localization. One of the important applications of a passive RFID system is to determine the reader position through multilateration based on the estimated distances between the reader and multiple distributed reference tags obtained from, e.g., the received signal strength indicator (RSSI) readings. In practice, the achievable accuracy of passive RFID reader localization suffers from many factors, such as the distorted RSSI reading due to channel impairments in terms of the susceptibility to reader antenna patterns and multipath propagation. Previous studies have shown that the accuracy of passive RFID localization can be significantly improved by properly modeling and compensating for such channel impairments. The objective of this paper is to report experimental study results that validate the effectiveness of such approaches for high-accuracy RFID localization. We also examine a number of practical issues arising in the underlying problem that limit the accuracy of reader-tag distance measurements and, therefore, the estimated reader localization. These issues include the variations in tag radiation characteristics for similar tags, effects of tag orientations, and reader RSS quantization and measurement errors. As such, this paper reveals valuable insights of the issues and solutions toward achieving high-accuracy passive RFID localization.

A design of optical modulation system with pixel-level modulation accuracy

NASA Astrophysics Data System (ADS)

Zheng, Shiwei; Qu, Xinghua; Feng, Wei; Liang, Baoqiu

2018-01-01

Vision measurement has been widely used in the field of dimensional measurement and surface metrology. However, traditional methods of vision measurement have many limits such as low dynamic range and poor reconfigurability. The optical modulation system before image formation has the advantage of high dynamic range, high accuracy and more flexibility, and the modulation accuracy is the key parameter which determines the accuracy and effectiveness of optical modulation system. In this paper, an optical modulation system with pixel level accuracy is designed and built based on multi-points reflective imaging theory and digital micromirror device (DMD). The system consisted of digital micromirror device, CCD camera and lens. Firstly we achieved accurate pixel-to-pixel correspondence between the DMD mirrors and the CCD pixels by moire fringe and an image processing of sampling and interpolation. Then we built three coordinate systems and calculated the mathematic relationship between the coordinate of digital micro-mirror and CCD pixels using a checkerboard pattern. A verification experiment proves that the correspondence error is less than 0.5 pixel. The results show that the modulation accuracy of system meets the requirements of modulation. Furthermore, the high reflecting edge of a metal circular piece can be detected using the system, which proves the effectiveness of the optical modulation system.

A novel redundant INS based on triple rotary inertial measurement units

NASA Astrophysics Data System (ADS)

Chen, Gang; Li, Kui; Wang, Wei; Li, Peng

2016-10-01

Accuracy and reliability are two key performances of inertial navigation system (INS). Rotation modulation (RM) can attenuate the bias of inertial sensors and make it possible for INS to achieve higher navigation accuracy with lower-class sensors. Therefore, the conflict between the accuracy and cost of INS can be eased. Traditional system redundancy and recently researched sensor redundancy are two primary means to improve the reliability of INS. However, how to make the best use of the redundant information from redundant sensors hasn’t been studied adequately, especially in rotational INS. This paper proposed a novel triple rotary unit strapdown inertial navigation system (TRUSINS), which combines RM and sensor redundancy design to enhance the accuracy and reliability of rotational INS. Each rotary unit independently rotates to modulate the errors of two gyros and two accelerometers. Three units can provide double sets of measurements along all three axes of body frame to constitute a couple of INSs which make TRUSINS redundant. Experiments and simulations based on a prototype which is made up of six fiber-optic gyros with drift stability of 0.05° h-1 show that TRUSINS can achieve positioning accuracy of about 0.256 n mile h-1, which is ten times better than that of a normal non-rotational INS with the same level inertial sensors. The theoretical analysis and the experimental results show that due to the advantage of the innovative structure, the designed fault detection and isolation (FDI) strategy can tolerate six sensor faults at most, and is proved to be effective and practical. Therefore, TRUSINS is particularly suitable and highly beneficial for the applications where high accuracy and high reliability is required.

Fusion and Gaussian mixture based classifiers for SONAR data

NASA Astrophysics Data System (ADS)

Kotari, Vikas; Chang, KC

2011-06-01

Underwater mines are inexpensive and highly effective weapons. They are difficult to detect and classify. Hence detection and classification of underwater mines is essential for the safety of naval vessels. This necessitates a formulation of highly efficient classifiers and detection techniques. Current techniques primarily focus on signals from one source. Data fusion is known to increase the accuracy of detection and classification. In this paper, we formulated a fusion-based classifier and a Gaussian mixture model (GMM) based classifier for classification of underwater mines. The emphasis has been on sound navigation and ranging (SONAR) signals due to their extensive use in current naval operations. The classifiers have been tested on real SONAR data obtained from University of California Irvine (UCI) repository. The performance of both GMM based classifier and fusion based classifier clearly demonstrate their superior classification accuracy over conventional single source cases and validate our approach.

Development of an embedded instrument for autofocus and polarization alignment of polarization maintaining fiber

NASA Astrophysics Data System (ADS)

Feng, Di; Fang, Qimeng; Huang, Huaibo; Zhao, Zhengqi; Song, Ningfang

2017-12-01

The development and implementation of a practical instrument based on an embedded technique for autofocus and polarization alignment of polarization maintaining fiber is presented. For focusing efficiency and stability, an image-based focusing algorithm fully considering the image definition evaluation and the focusing search strategy was used to accomplish autofocus. For improving the alignment accuracy, various image-based algorithms of alignment detection were developed with high calculation speed and strong robustness. The instrument can be operated as a standalone device with real-time processing and convenience operations. The hardware construction, software interface, and image-based algorithms of main modules are described. Additionally, several image simulation experiments were also carried out to analyze the accuracy of the above alignment detection algorithms. Both the simulation results and experiment results indicate that the instrument can achieve the accuracy of polarization alignment <±0.1 deg.

Research of Face Recognition with Fisher Linear Discriminant

NASA Astrophysics Data System (ADS)

Rahim, R.; Afriliansyah, T.; Winata, H.; Nofriansyah, D.; Ratnadewi; Aryza, S.

2018-01-01

Face identification systems are developing rapidly, and these developments drive the advancement of biometric-based identification systems that have high accuracy. However, to develop a good face recognition system and to have high accuracy is something that’s hard to find. Human faces have diverse expressions and attribute changes such as eyeglasses, mustache, beard and others. Fisher Linear Discriminant (FLD) is a class-specific method that distinguishes facial image images into classes and also creates distance between classes and intra classes so as to produce better classification.

Modeling hemodynamics in intracranial aneurysms: Comparing accuracy of CFD solvers based on finite element and finite volume schemes.

PubMed

Botti, Lorenzo; Paliwal, Nikhil; Conti, Pierangelo; Antiga, Luca; Meng, Hui

2018-06-01

Image-based computational fluid dynamics (CFD) has shown potential to aid in the clinical management of intracranial aneurysms (IAs) but its adoption in the clinical practice has been missing, partially due to lack of accuracy assessment and sensitivity analysis. To numerically solve the flow-governing equations CFD solvers generally rely on two spatial discretization schemes: Finite Volume (FV) and Finite Element (FE). Since increasingly accurate numerical solutions are obtained by different means, accuracies and computational costs of FV and FE formulations cannot be compared directly. To this end, in this study we benchmark two representative CFD solvers in simulating flow in a patient-specific IA model: (1) ANSYS Fluent, a commercial FV-based solver and (2) VMTKLab multidGetto, a discontinuous Galerkin (dG) FE-based solver. The FV solver's accuracy is improved by increasing the spatial mesh resolution (134k, 1.1m, 8.6m and 68.5m tetrahedral element meshes). The dGFE solver accuracy is increased by increasing the degree of polynomials (first, second, third and fourth degree) on the base 134k tetrahedral element mesh. Solutions from best FV and dGFE approximations are used as baseline for error quantification. On average, velocity errors for second-best approximations are approximately 1cm/s for a [0,125]cm/s velocity magnitude field. Results show that high-order dGFE provide better accuracy per degree of freedom but worse accuracy per Jacobian non-zero entry as compared to FV. Cross-comparison of velocity errors demonstrates asymptotic convergence of both solvers to the same numerical solution. Nevertheless, the discrepancy between under-resolved velocity fields suggests that mesh independence is reached following different paths. This article is protected by copyright. All rights reserved.

High-accurate optical vector analysis based on optical single-sideband modulation

NASA Astrophysics Data System (ADS)

Xue, Min; Pan, Shilong

2016-11-01

Most of the efforts devoted to the area of optical communications were on the improvement of the optical spectral efficiency. Varies innovative optical devices are thus developed to finely manipulate the optical spectrum. Knowing the spectral responses of these devices, including the magnitude, phase and polarization responses, is of great importance for their fabrication and application. To achieve high-resolution characterization, optical vector analyzers (OVAs) based on optical single-sideband (OSSB) modulation have been proposed and developed. Benefiting from the mature and highresolution microwave technologies, the OSSB-based OVA can potentially achieve a resolution of sub-Hz. However, the accuracy is restricted by the measurement errors induced by the unwanted first-order sideband and the high-order sidebands in the OSSB signal, since electrical-to-optical conversion and optical-to-electrical conversion are essentially required to achieve high-resolution frequency sweeping and extract the magnitude and phase information in the electrical domain. Recently, great efforts have been devoted to improve the accuracy of the OSSB-based OVA. In this paper, the influence of the unwanted-sideband induced measurement errors and techniques for implementing high-accurate OSSB-based OVAs are discussed.

Fluorescence-based methods for detecting caries lesions: systematic review, meta-analysis and sources of heterogeneity.

PubMed

Gimenez, Thais; Braga, Mariana Minatel; Raggio, Daniela Procida; Deery, Chris; Ricketts, David N; Mendes, Fausto Medeiros

2013-01-01

Fluorescence-based methods have been proposed to aid caries lesion detection. Summarizing and analysing findings of studies about fluorescence-based methods could clarify their real benefits. We aimed to perform a comprehensive systematic review and meta-analysis to evaluate the accuracy of fluorescence-based methods in detecting caries lesions. Two independent reviewers searched PubMed, Embase and Scopus through June 2012 to identify papers/articles published. Other sources were checked to identify non-published literature. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS AND DIAGNOSTIC METHODS: The eligibility criteria were studies that: (1) have assessed the accuracy of fluorescence-based methods of detecting caries lesions on occlusal, approximal or smooth surfaces, in both primary or permanent human teeth, in the laboratory or clinical setting; (2) have used a reference standard; and (3) have reported sufficient data relating to the sample size and the accuracy of methods. A diagnostic 2×2 table was extracted from included studies to calculate the pooled sensitivity, specificity and overall accuracy parameters (Diagnostic Odds Ratio and Summary Receiver-Operating curve). The analyses were performed separately for each method and different characteristics of the studies. The quality of the studies and heterogeneity were also evaluated. Seventy five studies met the inclusion criteria from the 434 articles initially identified. The search of the grey or non-published literature did not identify any further studies. In general, the analysis demonstrated that the fluorescence-based method tend to have similar accuracy for all types of teeth, dental surfaces or settings. There was a trend of better performance of fluorescence methods in detecting more advanced caries lesions. We also observed moderate to high heterogeneity and evidenced publication bias. Fluorescence-based devices have similar overall performance; however, better accuracy in detecting more advanced caries lesions has been observed.

Working memory capacity and task goals modulate error-related ERPs.

PubMed

Coleman, James R; Watson, Jason M; Strayer, David L

2018-03-01

The present study investigated individual differences in information processing following errant behavior. Participants were initially classified as high or as low working memory capacity using the Operation Span Task. In a subsequent session, they then performed a high congruency version of the flanker task under both speed and accuracy stress. We recorded ERPs and behavioral measures of accuracy and response time in the flanker task with a primary focus on processing following an error. The error-related negativity was larger for the high working memory capacity group than for the low working memory capacity group. The positivity following an error (Pe) was modulated to a greater extent by speed-accuracy instruction for the high working memory capacity group than for the low working memory capacity group. These data help to explicate the neural bases of individual differences in working memory capacity and cognitive control. © 2017 Society for Psychophysiological Research.

An Improved Method of AGM for High Precision Geolocation of SAR Images

NASA Astrophysics Data System (ADS)

Zhou, G.; He, C.; Yue, T.; Huang, W.; Huang, Y.; Li, X.; Chen, Y.

2018-05-01

In order to take full advantage of SAR images, it is necessary to obtain the high precision location of the image. During the geometric correction process of images, to ensure the accuracy of image geometric correction and extract the effective mapping information from the images, precise image geolocation is important. This paper presents an improved analytical geolocation method (IAGM) that determine the high precision geolocation of each pixel in a digital SAR image. This method is based on analytical geolocation method (AGM) proposed by X. K. Yuan aiming at realizing the solution of RD model. Tests will be conducted using RADARSAT-2 SAR image. Comparing the predicted feature geolocation with the position as determined by high precision orthophoto, results indicate an accuracy of 50m is attainable with this method. Error sources will be analyzed and some recommendations about improving image location accuracy in future spaceborne SAR's will be given.

A noncontact RF-based respiratory sensor: results of a clinical trial.

PubMed

Madsen, Spence; Baczuk, Jordan; Thorup, Kurt; Barton, Richard; Patwari, Neal; Langell, John T

2016-06-01

Respiratory rate (RR) is a critical vital signs monitored in health care setting. Current monitors suffer from sensor-contact failure, inaccurate data, and limited patient mobility. There is a critical need for an accurate and reliable and noncontact system to monitor RR. We developed a contact-free radio frequency (RF)-based system that measures movement using WiFi signal diffraction, which is converted into interpretable data using a Fourier transform. Here, we investigate the system's ability to measure fine movements associated with human respiration. Testing was conducted on subjects using visual cue, fixed-tempo instruction to breath at standard RRs. Blinded instruction-based RRs were compared to RF-acquired data to determine measurement accuracy. The RF-based technology was studied on postoperative ventilator-dependent patients. Blinded ventilator capnographic RR data were collected for each patient and compared to RF-acquired data to determine measurement accuracy. Respiratory rate data collected from 10 subjects breathing at a fixed RR (14, 16, 18, or 20) demonstrated 95.5% measurement accuracy between the patient's actual rate and that measured by our RF technology. Ten patients were enrolled into the clinical trial. Blinded ventilator capnographic RR data were compared to RF-based acquired data. The RF-based data showed 88.8% measurement accuracy with ventilator capnography. Initial clinical pilot trials with our contact-free RF-based monitoring system demonstrate a high degree of RR measurement accuracy when compared to capnographic data. Based on these results, we believe RF-based systems present a promising noninvasive, inexpensive, and accurate tool for continuous RR monitoring. Copyright © 2016 Elsevier Inc. All rights reserved.

High order GPS base station support for Rhode Island

DOT National Transportation Integrated Search

2001-09-01

The University of Rhode Island (URI) upgraded its Global Positioning System (GPS) Base Station to provide round-the-clock Internet access to survey-grade (+/- 2 cm accuracy) reference files using a web-based data distribution system. In August 2000, ...

Potential and limits to unravel the genetic architecture and predict the variation of Fusarium head blight resistance in European winter wheat (Triticum aestivum L.).

PubMed

Jiang, Y; Zhao, Y; Rodemann, B; Plieske, J; Kollers, S; Korzun, V; Ebmeyer, E; Argillier, O; Hinze, M; Ling, J; Röder, M S; Ganal, M W; Mette, M F; Reif, J C

2015-03-01

Genome-wide mapping approaches in diverse populations are powerful tools to unravel the genetic architecture of complex traits. The main goals of our study were to investigate the potential and limits to unravel the genetic architecture and to identify the factors determining the accuracy of prediction of the genotypic variation of Fusarium head blight (FHB) resistance in wheat (Triticum aestivum L.) based on data collected with a diverse panel of 372 European varieties. The wheat lines were phenotyped in multi-location field trials for FHB resistance and genotyped with 782 simple sequence repeat (SSR) markers, and 9k and 90k single-nucleotide polymorphism (SNP) arrays. We applied genome-wide association mapping in combination with fivefold cross-validations and observed surprisingly high accuracies of prediction for marker-assisted selection based on the detected quantitative trait loci (QTLs). Using a random sample of markers not selected for marker-trait associations revealed only a slight decrease in prediction accuracy compared with marker-based selection exploiting the QTL information. The same picture was confirmed in a simulation study, suggesting that relatedness is a main driver of the accuracy of prediction in marker-assisted selection of FHB resistance. When the accuracy of prediction of three genomic selection models was contrasted for the three marker data sets, no significant differences in accuracies among marker platforms and genomic selection models were observed. Marker density impacted the accuracy of prediction only marginally. Consequently, genomic selection of FHB resistance can be implemented most cost-efficiently based on low- to medium-density SNP arrays.

Model-based phase-shifting interferometer

NASA Astrophysics Data System (ADS)

Liu, Dong; Zhang, Lei; Shi, Tu; Yang, Yongying; Chong, Shiyao; Miao, Liang; Huang, Wei; Shen, Yibing; Bai, Jian

2015-10-01

A model-based phase-shifting interferometer (MPI) is developed, in which a novel calculation technique is proposed instead of the traditional complicated system structure, to achieve versatile, high precision and quantitative surface tests. In the MPI, the partial null lens (PNL) is employed to implement the non-null test. With some alternative PNLs, similar as the transmission spheres in ZYGO interferometers, the MPI provides a flexible test for general spherical and aspherical surfaces. Based on modern computer modeling technique, a reverse iterative optimizing construction (ROR) method is employed for the retrace error correction of non-null test, as well as figure error reconstruction. A self-compiled ray-tracing program is set up for the accurate system modeling and reverse ray tracing. The surface figure error then can be easily extracted from the wavefront data in forms of Zernike polynomials by the ROR method. Experiments of the spherical and aspherical tests are presented to validate the flexibility and accuracy. The test results are compared with those of Zygo interferometer (null tests), which demonstrates the high accuracy of the MPI. With such accuracy and flexibility, the MPI would possess large potential in modern optical shop testing.

Navier-Stokes simulations of slender axisymmetric shapes in supersonic, turbulent flow

NASA Astrophysics Data System (ADS)

Moran, Kenneth J.; Beran, Philip S.

1994-07-01

Computational fluid dynamics is used to study flows about slender, axisymmetric bodies at very high speeds. Numerical experiments are conducted to simulate a broad range of flight conditions. Mach number is varied from 1.5 to 8 and Reynolds number is varied from 1 X 10(exp 6)/m to 10(exp 8)/m. The primary objective is to develop and validate a computational and methodology for the accurate simulation of a wide variety of flow structures. Accurate results are obtained for detached bow shocks, recompression shocks, corner-point expansions, base-flow recirculations, and turbulent boundary layers. Accuracy is assessed through comparison with theory and experimental data; computed surface pressure, shock structure, base-flow structure, and velocity profiles are within measurement accuracy throughout the range of conditions tested. The methodology is both practical and general: general in its applicability, and practicaal in its performance. To achieve high accuracy, modifications to previously reported techniques are implemented in the scheme. These modifications improve computed results in the vicinity of symmetry lines and in the base flow region, including the turbulent wake.

Two laboratory methods for the calibration of GPS speed meters

NASA Astrophysics Data System (ADS)

Bai, Yin; Sun, Qiao; Du, Lei; Yu, Mei; Bai, Jie

2015-01-01

The set-ups of two calibration systems are presented to investigate calibration methods of GPS speed meters. The GPS speed meter calibrated is a special type of high accuracy speed meter for vehicles which uses Doppler demodulation of GPS signals to calculate the measured speed of a moving target. Three experiments are performed: including simulated calibration, field-test signal replay calibration, and in-field test comparison with an optical speed meter. The experiments are conducted at specific speeds in the range of 40-180 km h-1 with the same GPS speed meter as the device under calibration. The evaluation of measurement results validates both methods for calibrating GPS speed meters. The relative deviations between the measurement results of the GPS-based high accuracy speed meter and those of the optical speed meter are analyzed, and the equivalent uncertainty of the comparison is evaluated. The comparison results justify the utilization of GPS speed meters as reference equipment if no fewer than seven satellites are available. This study contributes to the widespread use of GPS-based high accuracy speed meters as legal reference equipment in traffic speed metrology.

ECG Sensor Card with Evolving RBP Algorithms for Human Verification.

PubMed

Tseng, Kuo-Kun; Huang, Huang-Nan; Zeng, Fufu; Tu, Shu-Yi

2015-08-21

It is known that cardiac and respiratory rhythms in electrocardiograms (ECGs) are highly nonlinear and non-stationary. As a result, most traditional time-domain algorithms are inadequate for characterizing the complex dynamics of the ECG. This paper proposes a new ECG sensor card and a statistical-based ECG algorithm, with the aid of a reduced binary pattern (RBP), with the aim of achieving faster ECG human identity recognition with high accuracy. The proposed algorithm has one advantage that previous ECG algorithms lack-the waveform complex information and de-noising preprocessing can be bypassed; therefore, it is more suitable for non-stationary ECG signals. Experimental results tested on two public ECG databases (MIT-BIH) from MIT University confirm that the proposed scheme is feasible with excellent accuracy, low complexity, and speedy processing. To be more specific, the advanced RBP algorithm achieves high accuracy in human identity recognition and is executed at least nine times faster than previous algorithms. Moreover, based on the test results from a long-term ECG database, the evolving RBP algorithm also demonstrates superior capability in handling long-term and non-stationary ECG signals.

High-accuracy 3D measurement system based on multi-view and structured light

NASA Astrophysics Data System (ADS)

Li, Mingyue; Weng, Dongdong; Li, Yufeng; Zhang, Longbin; Zhou, Haiyun

2013-12-01

3D surface reconstruction is one of the most important topics in Spatial Augmented Reality (SAR). Using structured light is a simple and rapid method to reconstruct the objects. In order to improve the precision of 3D reconstruction, we present a high-accuracy multi-view 3D measurement system based on Gray-code and Phase-shift. We use a camera and a light projector that casts structured light patterns on the objects. In this system, we use only one camera to take photos on the left and right sides of the object respectively. In addition, we use VisualSFM to process the relationships between each perspective, so the camera calibration can be omitted and the positions to place the camera are no longer limited. We also set appropriate exposure time to make the scenes covered by gray-code patterns more recognizable. All of the points above make the reconstruction more precise. We took experiments on different kinds of objects, and a large number of experimental results verify the feasibility and high accuracy of the system.

[Research on partial least squares for determination of impurities in the presence of high concentration of matrix by ICP-AES].

PubMed

Wang, Yan-peng; Gong, Qi; Yu, Sheng-rong; Liu, You-yan

2012-04-01

A method for detecting trace impurities in high concentration matrix by ICP-AES based on partial least squares (PLS) was established. The research showed that PLS could effectively correct the interference caused by high level of matrix concentration error and could withstand higher concentrations of matrix than multicomponent spectral fitting (MSF). When the mass ratios of matrix to impurities were from 1 000 : 1 to 20 000 : 1, the recoveries of standard addition were between 95% and 105% by PLS. For the system in which interference effect has nonlinear correlation with the matrix concentrations, the prediction accuracy of normal PLS method was poor, but it can be improved greatly by using LIN-PPLS, which was based on matrix transformation of sample concentration. The contents of Co, Pb and Ga in stream sediment (GBW07312) were detected by MSF, PLS and LIN-PPLS respectively. The results showed that the prediction accuracy of LIN-PPLS was better than PLS, and the prediction accuracy of PLS was better than MSF.

GNSS/Electronic Compass/Road Segment Information Fusion for Vehicle-to-Vehicle Collision Avoidance Application

PubMed Central

Cheng, Qi; Xue, Dabin; Wang, Guanyu; Ochieng, Washington Yotto

2017-01-01

The increasing number of vehicles in modern cities brings the problem of increasing crashes. One of the applications or services of Intelligent Transportation Systems (ITS) conceived to improve safety and reduce congestion is collision avoidance. This safety critical application requires sub-meter level vehicle state estimation accuracy with very high integrity, continuity and availability, to detect an impending collision and issue a warning or intervene in the case that the warning is not heeded. Because of the challenging city environment, to date there is no approved method capable of delivering this high level of performance in vehicle state estimation. In particular, the current Global Navigation Satellite System (GNSS) based collision avoidance systems have the major limitation that the real-time accuracy of dynamic state estimation deteriorates during abrupt acceleration and deceleration situations, compromising the integrity of collision avoidance. Therefore, to provide the Required Navigation Performance (RNP) for collision avoidance, this paper proposes a novel Particle Filter (PF) based model for the integration or fusion of real-time kinematic (RTK) GNSS position solutions with electronic compass and road segment data used in conjunction with an Autoregressive (AR) motion model. The real-time vehicle state estimates are used together with distance based collision avoidance algorithms to predict potential collisions. The algorithms are tested by simulation and in the field representing a low density urban environment. The results show that the proposed algorithm meets the horizontal positioning accuracy requirement for collision avoidance and is superior to positioning accuracy of GNSS only, traditional Constant Velocity (CV) and Constant Acceleration (CA) based motion models, with a significant improvement in the prediction accuracy of potential collision. PMID:29186851

GNSS/Electronic Compass/Road Segment Information Fusion for Vehicle-to-Vehicle Collision Avoidance Application.

PubMed

Sun, Rui; Cheng, Qi; Xue, Dabin; Wang, Guanyu; Ochieng, Washington Yotto

2017-11-25

The increasing number of vehicles in modern cities brings the problem of increasing crashes. One of the applications or services of Intelligent Transportation Systems (ITS) conceived to improve safety and reduce congestion is collision avoidance. This safety critical application requires sub-meter level vehicle state estimation accuracy with very high integrity, continuity and availability, to detect an impending collision and issue a warning or intervene in the case that the warning is not heeded. Because of the challenging city environment, to date there is no approved method capable of delivering this high level of performance in vehicle state estimation. In particular, the current Global Navigation Satellite System (GNSS) based collision avoidance systems have the major limitation that the real-time accuracy of dynamic state estimation deteriorates during abrupt acceleration and deceleration situations, compromising the integrity of collision avoidance. Therefore, to provide the Required Navigation Performance (RNP) for collision avoidance, this paper proposes a novel Particle Filter (PF) based model for the integration or fusion of real-time kinematic (RTK) GNSS position solutions with electronic compass and road segment data used in conjunction with an Autoregressive (AR) motion model. The real-time vehicle state estimates are used together with distance based collision avoidance algorithms to predict potential collisions. The algorithms are tested by simulation and in the field representing a low density urban environment. The results show that the proposed algorithm meets the horizontal positioning accuracy requirement for collision avoidance and is superior to positioning accuracy of GNSS only, traditional Constant Velocity (CV) and Constant Acceleration (CA) based motion models, with a significant improvement in the prediction accuracy of potential collision.

High accuracy transit photometry of the planet OGLE-TR-113b with a new deconvolution-based method

NASA Astrophysics Data System (ADS)

Gillon, M.; Pont, F.; Moutou, C.; Bouchy, F.; Courbin, F.; Sohy, S.; Magain, P.

2006-11-01

A high accuracy photometry algorithm is needed to take full advantage of the potential of the transit method for the characterization of exoplanets, especially in deep crowded fields. It has to reduce to the lowest possible level the negative influence of systematic effects on the photometric accuracy. It should also be able to cope with a high level of crowding and with large-scale variations of the spatial resolution from one image to another. A recent deconvolution-based photometry algorithm fulfills all these requirements, and it also increases the resolution of astronomical images, which is an important advantage for the detection of blends and the discrimination of false positives in transit photometry. We made some changes to this algorithm to optimize it for transit photometry and used it to reduce NTT/SUSI2 observations of two transits of OGLE-TR-113b. This reduction has led to two very high precision transit light curves with a low level of systematic residuals, used together with former photometric and spectroscopic measurements to derive new stellar and planetary parameters in excellent agreement with previous ones, but significantly more precise.

Diagnostic accuracy of a noninvasive hepatic ultrasound score for non-alcoholic fatty liver disease (NAFLD) in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

PubMed

Goulart, Alessandra Carvalho; Oliveira, Ilka Regina Souza de; Alencar, Airlane Pereira; Santos, Maira Solange Camara dos; Santos, Itamar Souza; Martines, Brenda Margatho Ramos; Meireles, Danilo Peron; Martines, João Augusto dos Santos; Misciagna, Giovanni; Benseñor, Isabela Martins; Lotufo, Paulo Andrade

2015-01-01

Noninvasive strategies for evaluating non-alcoholic fatty liver disease (NAFLD) have been investigated over the last few decades. Our aim was to evaluate the diagnostic accuracy of a new hepatic ultrasound score for NAFLD in the ELSA-Brasil study. Diagnostic accuracy study conducted in the ELSA center, in the hospital of a public university. Among the 15,105 participants of the ELSA study who were evaluated for NAFLD, 195 individuals were included in this sub-study. Hepatic ultrasound was performed (deep beam attenuation, hepatorenal index and anteroposterior diameter of the right hepatic lobe) and compared with the hepatic steatosis findings from 64-channel high-resolution computed tomography (CT). We also evaluated two clinical indices relating to NAFLD: the fatty liver index (FLI) and the hepatic steatosis index (HSI). Among the 195 participants, the NAFLD frequency was 34.4%. High body mass index, high waist circumference, diabetes and hypertriglyceridemia were associated with high hepatic attenuation and large anteroposterior diameter of the right hepatic lobe, but not with the hepatorenal index. The hepatic ultrasound score, based on hepatic attenuation and the anteroposterior diameter of the right hepatic lobe, presented the best performance for NAFLD screening at the cutoff point ≥ 1 point; sensitivity: 85.1%; specificity: 73.4%; accuracy: 79.3%; and area under the curve (AUC 0.85; 95% confidence interval, CI: 0.78-0.91)]. FLI and HSI presented lower performance (AUC 0.76; 95% CI: 0.69-0.83) than CT. The hepatic ultrasound score based on hepatic attenuation and the anteroposterior diameter of the right hepatic lobe has good reproducibility and accuracy for NAFLD screening.

Reproducibility of UAV-based earth surface topography based on structure-from-motion algorithms.

NASA Astrophysics Data System (ADS)

Clapuyt, François; Vanacker, Veerle; Van Oost, Kristof

2014-05-01

A representation of the earth surface at very high spatial resolution is crucial to accurately map small geomorphic landforms with high precision. Very high resolution digital surface models (DSM) can then be used to quantify changes in earth surface topography over time, based on differencing of DSMs taken at various moments in time. However, it is compulsory to have both high accuracy for each topographic representation and consistency between measurements over time, as DSM differencing automatically leads to error propagation. This study investigates the reproducibility of reconstructions of earth surface topography based on structure-from-motion (SFM) algorithms. To this end, we equipped an eight-propeller drone with a standard reflex camera. This equipment can easily be deployed in the field, as it is a lightweight, low-cost system in comparison with classic aerial photo surveys and terrestrial or airborne LiDAR scanning. Four sets of aerial photographs were created for one test field. The sets of airphotos differ in focal length, and viewing angles, i.e. nadir view and ground-level view. In addition, the importance of the accuracy of ground control points for the construction of a georeferenced point cloud was assessed using two different GPS devices with horizontal accuracy at resp. the sub-meter and sub-decimeter level. Airphoto datasets were processed with SFM algorithm and the resulting point clouds were georeferenced. Then, the surface representations were compared with each other to assess the reproducibility of the earth surface topography. Finally, consistency between independent datasets is discussed.

Fault detection and isolation of high temperature proton exchange membrane fuel cell stack under the influence of degradation

NASA Astrophysics Data System (ADS)

Jeppesen, Christian; Araya, Samuel Simon; Sahlin, Simon Lennart; Thomas, Sobi; Andreasen, Søren Juhl; Kær, Søren Knudsen

2017-08-01

This study proposes a data-drive impedance-based methodology for fault detection and isolation of low and high cathode stoichiometry, high CO concentration in the anode gas, high methanol vapour concentrations in the anode gas and low anode stoichiometry, for high temperature PEM fuel cells. The fault detection and isolation algorithm is based on an artificial neural network classifier, which uses three extracted features as input. Two of the proposed features are based on angles in the impedance spectrum, and are therefore relative to specific points, and shown to be independent of degradation, contrary to other available feature extraction methods in the literature. The experimental data is based on a 35 day experiment, where 2010 unique electrochemical impedance spectroscopy measurements were recorded. The test of the algorithm resulted in a good detectability of the faults, except for high methanol vapour concentration in the anode gas fault, which was found to be difficult to distinguish from a normal operational data. The achieved accuracy for faults related to CO pollution, anode- and cathode stoichiometry is 100% success rate. Overall global accuracy on the test data is 94.6%.

Development of a data-processing method based on Bayesian k-means clustering to discriminate aneugens and clastogens in a high-content micronucleus assay.

PubMed

Huang, Z H; Li, N; Rao, K F; Liu, C T; Huang, Y; Ma, M; Wang, Z J

2018-03-01

Genotoxicants can be identified as aneugens and clastogens through a micronucleus (MN) assay. The current high-content screening-based MN assays usually discriminate an aneugen from a clastogen based on only one parameter, such as the MN size, intensity, or morphology, which yields low accuracies (70-84%) because each of these parameters may contribute to the results. Therefore, the development of an algorithm that can synthesize high-dimensionality data to attain comparative results is important. To improve the automation and accuracy of detection using the current parameter-based mode of action (MoA), the MN MoA signatures of 20 chemicals were systematically recruited in this study to develop an algorithm. The results of the algorithm showed very good agreement (93.58%) between the prediction and reality, indicating that the proposed algorithm is a validated analytical platform for the rapid and objective acquisition of genotoxic MoA messages.

Star Tracker Based ATP System Conceptual Design and Pointing Accuracy Estimation

NASA Technical Reports Server (NTRS)

Orfiz, Gerardo G.; Lee, Shinhak

2006-01-01

A star tracker based beaconless (a.k.a. non-cooperative beacon) acquisition, tracking and pointing concept for precisely pointing an optical communication beam is presented as an innovative approach to extend the range of high bandwidth (> 100 Mbps) deep space optical communication links throughout the solar system and to remove the need for a ground based high power laser as a beacon source. The basic approach for executing the ATP functions involves the use of stars as the reference sources from which the attitude knowledge is obtained and combined with high bandwidth gyroscopes for propagating the pointing knowledge to the beam pointing mechanism. Details of the conceptual design are presented including selection of an orthogonal telescope configuration and the introduction of an optical metering scheme to reduce misalignment error. Also, estimates are presented that demonstrate that aiming of the communications beam to the Earth based receive terminal can be achieved with a total system pointing accuracy of better than 850 nanoradians (3 sigma) from anywhere in the solar system.

Diagnostic accuracy of tablet-based software for the detection of concussion.

PubMed

Yang, Suosuo; Flores, Benjamin; Magal, Rotem; Harris, Kyrsti; Gross, Jonathan; Ewbank, Amy; Davenport, Sasha; Ormachea, Pablo; Nasser, Waleed; Le, Weidong; Peacock, W Frank; Katz, Yael; Eagleman, David M

2017-01-01

Despite the high prevalence of traumatic brain injuries (TBI), there are few rapid and straightforward tests to improve its assessment. To this end, we developed a tablet-based software battery ("BrainCheck") for concussion detection that is well suited to sports, emergency department, and clinical settings. This article is a study of the diagnostic accuracy of BrainCheck. We administered BrainCheck to 30 TBI patients and 30 pain-matched controls at a hospital Emergency Department (ED), and 538 healthy individuals at 10 control test sites. We compared the results of the tablet-based assessment against physician diagnoses derived from brain scans, clinical examination, and the SCAT3 test, a traditional measure of TBI. We found consistent distributions of normative data and high test-retest reliability. Based on these assessments, we defined a composite score that distinguishes TBI from non-TBI individuals with high sensitivity (83%) and specificity (87%). We conclude that our testing application provides a rapid, portable testing method for TBI.

Error tolerance analysis of wave diagnostic based on coherent modulation imaging in high power laser system

NASA Astrophysics Data System (ADS)

Pan, Xingchen; Liu, Cheng; Zhu, Jianqiang

2018-02-01

Coherent modulation imaging providing fast convergence speed and high resolution with single diffraction pattern is a promising technique to satisfy the urgent demands for on-line multiple parameter diagnostics with single setup in high power laser facilities (HPLF). However, the influence of noise on the final calculated parameters concerned has not been investigated yet. According to a series of simulations with twenty different sampling beams generated based on the practical parameters and performance of HPLF, the quantitative analysis based on statistical results was first investigated after considering five different error sources. We found the background noise of detector and high quantization error will seriously affect the final accuracy and different parameters have different sensitivity to different noise sources. The simulation results and the corresponding analysis provide the potential directions to further improve the final accuracy of parameter diagnostics which is critically important to its formal applications in the daily routines of HPLF.

The ship edge feature detection based on high and low threshold for remote sensing image

NASA Astrophysics Data System (ADS)

Li, Xuan; Li, Shengyang

2018-05-01

In this paper, a method based on high and low threshold is proposed to detect the ship edge feature due to the low accuracy rate caused by the noise. Analyze the relationship between human vision system and the target features, and to determine the ship target by detecting the edge feature. Firstly, using the second-order differential method to enhance the quality of image; Secondly, to improvement the edge operator, we introduction of high and low threshold contrast to enhancement image edge and non-edge points, and the edge as the foreground image, non-edge as a background image using image segmentation to achieve edge detection, and remove the false edges; Finally, the edge features are described based on the result of edge features detection, and determine the ship target. The experimental results show that the proposed method can effectively reduce the number of false edges in edge detection, and has the high accuracy of remote sensing ship edge detection.

Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data

PubMed Central

Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

2016-01-01

Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting. PMID:27667901

Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data.

PubMed

Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

2015-08-01

Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting.

MUSCLE: multiple sequence alignment with high accuracy and high throughput.

PubMed

Edgar, Robert C

2004-01-01

We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

Automated novel high-accuracy miniaturized positioning system for use in analytical instrumentation

NASA Astrophysics Data System (ADS)

Siomos, Konstadinos; Kaliakatsos, John; Apostolakis, Manolis; Lianakis, John; Duenow, Peter

1996-01-01

The development of three-dimensional automotive devices (micro-robots) for applications in analytical instrumentation, clinical chemical diagnostics and advanced laser optics, depends strongly on the ability of such a device: firstly to be positioned with high accuracy, reliability, and automatically, by means of user friendly interface techniques; secondly to be compact; and thirdly to operate under vacuum conditions, free of most of the problems connected with conventional micropositioners using stepping-motor gear techniques. The objective of this paper is to develop and construct a mechanically compact computer-based micropositioning system for coordinated motion in the X-Y-Z directions with: (1) a positioning accuracy of less than 1 micrometer, (the accuracy of the end-position of the system is controlled by a hard/software assembly using a self-constructed optical encoder); (2) a heat-free propulsion mechanism for vacuum operation; and (3) synchronized X-Y motion.

Influence of part orientation on the geometric accuracy in robot-based incremental sheet metal forming

NASA Astrophysics Data System (ADS)

Störkle, Denis Daniel; Seim, Patrick; Thyssen, Lars; Kuhlenkötter, Bernd

2016-10-01

This article describes new developments in an incremental, robot-based sheet metal forming process (`Roboforming') for the production of sheet metal components for small lot sizes and prototypes. The dieless kinematic-based generation of the shape is implemented by means of two industrial robots, which are interconnected to a cooperating robot system. Compared to other incremental sheet metal forming (ISF) machines, this system offers high geometrical form flexibility without the need of any part-dependent tools. The industrial application of ISF is still limited by certain constraints, e.g. the low geometrical accuracy. Responding to these constraints, the authors present the influence of the part orientation and the forming sequence on the geometric accuracy. Their influence is illustrated with the help of various experimental results shown and interpreted within this article.

The accuracy of an electromagnetic navigation system in lateral skull base approaches.

PubMed

Komune, Noritaka; Matsushima, Ken; Matsuo, Satoshi; Safavi-Abbasi, Sam; Matsumoto, Nozomu; Rhoton, Albert L

2017-02-01

Image-guided optical tracking systems are being used with increased frequency in lateral skull base surgery. Recently, electromagnetic tracking systems have become available for use in this region. However, the clinical accuracy of the electromagnetic tracking system has not been examined in lateral skull base surgery. This study evaluates the accuracy of electromagnetic navigation in lateral skull base surgery. Cadaveric and radiographic study. Twenty cadaveric temporal bones were dissected in a surgical setting under a commercially available, electromagnetic surgical navigation system. The target registration error (TRE) was measured at 28 surgical landmarks during and after performing the standard translabyrinthine and middle cranial fossa surgical approaches to the internal acoustic canal. In addition, three demonstrative procedures that necessitate navigation with high accuracy were performed; that is, canalostomy of the superior semicircular canal from the middle cranial fossa, 1 cochleostomy from the middle cranial fossa, 2 and infralabyrinthine approach to the petrous apex. 3 RESULTS: Eleven of 17 (65%) of the targets in the translabyrinthine approach and five of 11 (45%) of the targets in the middle fossa approach could be identified in the navigation system with TRE of less than 0.5 mm. Three accuracy-dependent procedures were completed without anatomical injury of important anatomical structures. The electromagnetic navigation system had sufficient accuracy to be used in the surgical setting. It was possible to perform complex procedures in the lateral skull base under the guidance of the electromagnetically tracked navigation system. N/A. Laryngoscope, 2016 127:450-459, 2017. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Earth observation data based rapid flood-extent modelling for tsunami-devastated coastal areas

NASA Astrophysics Data System (ADS)

Hese, Sören; Heyer, Thomas

2016-04-01

Earth observation (EO)-based mapping and analysis of natural hazards plays a critical role in various aspects of post-disaster aid management. Spatial very high-resolution Earth observation data provide important information for managing post-tsunami activities on devastated land and monitoring re-cultivation and reconstruction. The automatic and fast use of high-resolution EO data for rapid mapping is, however, complicated by high spectral variability in densely populated urban areas and unpredictable textural and spectral land-surface changes. The present paper presents the results of the SENDAI project, which developed an automatic post-tsunami flood-extent modelling concept using RapidEye multispectral satellite data and ASTER Global Digital Elevation Model Version 2 (GDEM V2) data of the eastern coast of Japan (captured after the Tohoku earthquake). In this paper, the authors developed both a bathtub-modelling approach and a cost-distance approach, and integrated the roughness parameters of different land-use types to increase the accuracy of flood-extent modelling. Overall, the accuracy of the developed models reached 87-92%, depending on the analysed test site. The flood-modelling approach was explained and results were compared with published approaches. We came to the conclusion that the cost-factor-based approach reaches accuracy comparable to published results from hydrological modelling. However the proposed cost-factor approach is based on a much simpler dataset, which is available globally.

Kinematic-PPP using Single/Dual Frequency Observations from (GPS, GLONASS and GPS/GLONASS) Constellations for Hydrography

NASA Astrophysics Data System (ADS)

Farah, Ashraf

2018-03-01

Global Positioning System (GPS) technology is ideally suited for inshore and offshore positioning because of its high accuracy and the short observation time required for a position fix. Precise point positioning (PPP) is a technique used for position computation with a high accuracy using a single GNSS receiver. It relies on highly accurate satellite position and clock data that can be acquired from different sources such as the International GNSS Service (IGS). PPP precision varies based on positioning technique (static or kinematic), observations type (single or dual frequency) and the duration of observations among other factors. PPP offers comparable accuracy to differential GPS with safe in cost and time. For many years, PPP users depended on GPS (American system) which considered the solely reliable system. GLONASS's contribution in PPP techniques was limited due to fail in maintaining full constellation. Yet, GLONASS limited observations could be integrated into GPS-based PPP to improve availability and precision. As GLONASS reached its full constellation early 2013, there is a wide interest in PPP systems based on GLONASS only and independent of GPS. This paper investigates the performance of kinematic PPP solution for the hydrographic applications in the Nile river (Aswan, Egypt) based on GPS, GLONASS and GPS/GLONASS constellations. The study investigates also the effect of using two different observation types; single-frequency and dual frequency observations from the tested constellations.

a New Approach for Subway Tunnel Deformation Monitoring: High-Resolution Terrestrial Laser Scanning

NASA Astrophysics Data System (ADS)

Li, J.; Wan, Y.; Gao, X.

2012-07-01

With the improvement of the accuracy and efficiency of laser scanning technology, high-resolution terrestrial laser scanning (TLS) technology can obtain high precise points-cloud and density distribution and can be applied to high-precision deformation monitoring of subway tunnels and high-speed railway bridges and other fields. In this paper, a new approach using a points-cloud segmentation method based on vectors of neighbor points and surface fitting method based on moving least squares was proposed and applied to subway tunnel deformation monitoring in Tianjin combined with a new high-resolution terrestrial laser scanner (Riegl VZ-400). There were three main procedures. Firstly, a points-cloud consisted of several scanning was registered by linearized iterative least squares approach to improve the accuracy of registration, and several control points were acquired by total stations (TS) and then adjusted. Secondly, the registered points-cloud was resampled and segmented based on vectors of neighbor points to select suitable points. Thirdly, the selected points were used to fit the subway tunnel surface with moving least squares algorithm. Then a series of parallel sections obtained from temporal series of fitting tunnel surfaces were compared to analysis the deformation. Finally, the results of the approach in z direction were compared with the fiber optical displacement sensor approach and the results in x, y directions were compared with TS respectively, and comparison results showed the accuracy errors of x, y, z directions were respectively about 1.5 mm, 2 mm, 1 mm. Therefore the new approach using high-resolution TLS can meet the demand of subway tunnel deformation monitoring.

Information extraction with object based support vector machines and vegetation indices

NASA Astrophysics Data System (ADS)

Ustuner, Mustafa; Abdikan, Saygin; Balik Sanli, Fusun

2016-07-01

Information extraction through remote sensing data is important for policy and decision makers as extracted information provide base layers for many application of real world. Classification of remotely sensed data is the one of the most common methods of extracting information however it is still a challenging issue because several factors are affecting the accuracy of the classification. Resolution of the imagery, number and homogeneity of land cover classes, purity of training data and characteristic of adopted classifiers are just some of these challenging factors. Object based image classification has some superiority than pixel based classification for high resolution images since it uses geometry and structure information besides spectral information. Vegetation indices are also commonly used for the classification process since it provides additional spectral information for vegetation, forestry and agricultural areas. In this study, the impacts of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) on the classification accuracy of RapidEye imagery were investigated. Object based Support Vector Machines were implemented for the classification of crop types for the study area located in Aegean region of Turkey. Results demonstrated that the incorporation of NDRE increase the classification accuracy from 79,96% to 86,80% as overall accuracy, however NDVI decrease the classification accuracy from 79,96% to 78,90%. Moreover it is proven than object based classification with RapidEye data give promising results for crop type mapping and analysis.

An Investigation of the Accuracy of Alternative Methods of True Score Estimation in High-Stakes Mixed-Format Examinations.

ERIC Educational Resources Information Center

Klinger, Don A.; Rogers, W. Todd

2003-01-01

The estimation accuracy of procedures based on classical test score theory and item response theory (generalized partial credit model) were compared for examinations consisting of multiple-choice and extended-response items. Analysis of British Columbia Scholarship Examination results found an error rate of about 10 percent for both methods, with…

The Short-Term and Long-Term Effects of AWE Feedback on ESL Students' Development of Grammatical Accuracy

ERIC Educational Resources Information Center

Li, Zhi; Feng, Hui-Hsien; Saricaoglu, Aysel

2017-01-01

This classroom-based study employs a mixed-methods approach to exploring both short-term and long-term effects of Criterion feedback on ESL students' development of grammatical accuracy. The results of multilevel growth modeling indicate that Criterion feedback helps students in both intermediate-high and advanced-low levels reduce errors in eight…

Direct Detection Doppler Lidar for Spaceborne Wind Measurement

NASA Technical Reports Server (NTRS)

Korb, C. Laurence; Flesia, Cristina

1999-01-01

The theory of double edge lidar techniques for measuring the atmospheric wind using aerosol and molecular backscatter is described. Two high spectral resolution filters with opposite slopes are located about the laser frequency for the aerosol based measurement or in the wings of the Rayleigh - Brillouin profile for the molecular measurement. This doubles the signal change per unit Doppler shift and improves the measurement accuracy by nearly a factor of 2 relative to the single edge technique. For the aerosol based measurement, the use of two high resolution edge filters reduces the effects of background, Rayleigh scattering, by as much as an order of magnitude and substantially improves the measurement accuracy. Also, we describe a method that allows the Rayleigh and aerosol components of the signal to be independently determined. A measurement accuracy of 1.2 m/s can be obtained for a signal level of 1000 detected photons which corresponds to signal levels in the boundary layer. For the molecular based measurement, we describe the use of a crossover region where the sensitivity of a molecular and aerosol-based measurement are equal. This desensitizes the molecular measurement to the effects of aerosol scattering and greatly simplifies the measurement. Simulations using a conical scanning spaceborne lidar at 355 nm give an accuracy of 2-3 m/s for altitudes of 2-15 km for a 1 km vertical resolution, a satellite altitude of 400 km, and a 200 km x 200 km spatial.

On-Ground Processing of Yaogan-24 Remote Sensing Satellite Attitude Data and Verification Using Geometric Field Calibration

PubMed Central

Wang, Mi; Fan, Chengcheng; Yang, Bo; Jin, Shuying; Pan, Jun

2016-01-01

Satellite attitude accuracy is an important factor affecting the geometric processing accuracy of high-resolution optical satellite imagery. To address the problem whereby the accuracy of the Yaogan-24 remote sensing satellite’s on-board attitude data processing is not high enough and thus cannot meet its image geometry processing requirements, we developed an approach involving on-ground attitude data processing and digital orthophoto (DOM) and the digital elevation model (DEM) verification of a geometric calibration field. The approach focuses on three modules: on-ground processing based on bidirectional filter, overall weighted smoothing and fitting, and evaluation in the geometric calibration field. Our experimental results demonstrate that the proposed on-ground processing method is both robust and feasible, which ensures the reliability of the observation data quality, convergence and stability of the parameter estimation model. In addition, both the Euler angle and quaternion could be used to build a mathematical fitting model, while the orthogonal polynomial fitting model is more suitable for modeling the attitude parameter. Furthermore, compared to the image geometric processing results based on on-board attitude data, the image uncontrolled and relative geometric positioning result accuracy can be increased by about 50%. PMID:27483287

Improving risk prediction accuracy for new soldiers in the U.S. Army by adding self-report survey data to administrative data.

PubMed

Bernecker, Samantha L; Rosellini, Anthony J; Nock, Matthew K; Chiu, Wai Tat; Gutierrez, Peter M; Hwang, Irving; Joiner, Thomas E; Naifeh, James A; Sampson, Nancy A; Zaslavsky, Alan M; Stein, Murray B; Ursano, Robert J; Kessler, Ronald C

2018-04-03

High rates of mental disorders, suicidality, and interpersonal violence early in the military career have raised interest in implementing preventive interventions with high-risk new enlistees. The Army Study to Assess Risk and Resilience in Servicemembers (STARRS) developed risk-targeting systems for these outcomes based on machine learning methods using administrative data predictors. However, administrative data omit many risk factors, raising the question whether risk targeting could be improved by adding self-report survey data to prediction models. If so, the Army may gain from routinely administering surveys that assess additional risk factors. The STARRS New Soldier Survey was administered to 21,790 Regular Army soldiers who agreed to have survey data linked to administrative records. As reported previously, machine learning models using administrative data as predictors found that small proportions of high-risk soldiers accounted for high proportions of negative outcomes. Other machine learning models using self-report survey data as predictors were developed previously for three of these outcomes: major physical violence and sexual violence perpetration among men and sexual violence victimization among women. Here we examined the extent to which this survey information increases prediction accuracy, over models based solely on administrative data, for those three outcomes. We used discrete-time survival analysis to estimate a series of models predicting first occurrence, assessing how model fit improved and concentration of risk increased when adding the predicted risk score based on survey data to the predicted risk score based on administrative data. The addition of survey data improved prediction significantly for all outcomes. In the most extreme case, the percentage of reported sexual violence victimization among the 5% of female soldiers with highest predicted risk increased from 17.5% using only administrative predictors to 29.4% adding survey predictors, a 67.9% proportional increase in prediction accuracy. Other proportional increases in concentration of risk ranged from 4.8% to 49.5% (median = 26.0%). Data from an ongoing New Soldier Survey could substantially improve accuracy of risk models compared to models based exclusively on administrative predictors. Depending upon the characteristics of interventions used, the increase in targeting accuracy from survey data might offset survey administration costs.

Evaluation of portable CT scanners for otologic image-guided surgery

PubMed Central

Balachandran, Ramya; Schurzig, Daniel; Fitzpatrick, J Michael; Labadie, Robert F

2011-01-01

Purpose Portable CT scanners are beneficial for diagnosis in the intensive care unit, emergency room, and operating room. Portable fixed-base versus translating-base CT systems were evaluated for otologic image-guided surgical (IGS) applications based on geometric accuracy and utility for percutaneous cochlear implantation. Methods Five cadaveric skulls were fitted with fiducial markers and scanned using both a translating-base, 8-slice CT scanner (CereTom®) and a fixed-base, flat-panel, volume-CT (fpVCT) scanner (Xoran xCAT®). Images were analyzed for: (a) subjective quality (i.e. noise), (b) consistency of attenuation measurements (Hounsfield units) across similar tissue, and (c) geometric accuracy of fiducial marker positions. The utility of these scanners in clinical IGS cases was tested. Results Five cadaveric specimens were scanned using each of the scanners. The translating-base, 8-slice CT scanner had spatially consistent Hounsfield units, and the image quality was subjectively good. However, because of movement variations during scanning, the geometric accuracy of fiducial marker positions was low. The fixed-base, fpVCT system had high spatial resolution, but the images were noisy and had spatially inconsistent attenuation measurements; while the geometric representation of the fiducial markers was highly accurate. Conclusion Two types of portable CT scanners were evaluated for otologic IGS. The translating-base, 8-slice CT scanner provided better image quality than a fixed-base, fpVCT scanner. However, the inherent error in three-dimensional spatial relationships by the translating-based system makes it suboptimal for otologic IGS use. PMID:21779768

Comparing ordinary kriging and inverse distance weighting for soil as pollution in Beijing.

PubMed

Qiao, Pengwei; Lei, Mei; Yang, Sucai; Yang, Jun; Guo, Guanghui; Zhou, Xiaoyong

2018-06-01

Spatial interpolation method is the basis of soil heavy metal pollution assessment and remediation. The existing evaluation index for interpolation accuracy did not combine with actual situation. The selection of interpolation methods needs to be based on specific research purposes and research object characteristics. In this paper, As pollution in soils of Beijing was taken as an example. The prediction accuracy of ordinary kriging (OK) and inverse distance weighted (IDW) were evaluated based on the cross validation results and spatial distribution characteristics of influencing factors. The results showed that, under the condition of specific spatial correlation, the cross validation results of OK and IDW for every soil point and the prediction accuracy of spatial distribution trend are similar. But the prediction accuracy of OK for the maximum and minimum is less than IDW, while the number of high pollution areas identified by OK are less than IDW. It is difficult to identify the high pollution areas fully by OK, which shows that the smoothing effect of OK is obvious. In addition, with increasing of the spatial correlation of As concentration, the cross validation error of OK and IDW decreases, and the high pollution area identified by OK is approaching the result of IDW, which can identify the high pollution areas more comprehensively. However, because the semivariogram constructed by OK interpolation method is more subjective and requires larger number of soil samples, IDW is more suitable for spatial prediction of heavy metal pollution in soils.

Nucleic Acid-Based Approaches for Detection of Viral Hepatitis

PubMed Central

Behzadi, Payam; Ranjbar, Reza; Alavian, Seyed Moayed

2014-01-01

Context: To determining suitable nucleic acid diagnostics for individual viral hepatitis agent, an extensive search using related keywords was done in major medical library and data were collected, categorized, and summarized in different sections. Results: Various types of molecular biology tools can be used to detect and quantify viral genomic elements and analyze the sequences. These molecular assays are proper technologies for rapidly detecting viral agents with high accuracy, high sensitivity, and high specificity. Nonetheless, the application of each diagnostic method is completely dependent on viral agent. Conclusions: Despite rapidity, automation, accuracy, cost-effectiveness, high sensitivity, and high specificity of molecular techniques, each type of molecular technology has its own advantages and disadvantages. PMID:25789132

Accuracy of patient-specific guided glenoid baseplate positioning for reverse shoulder arthroplasty.

PubMed

Levy, Jonathan C; Everding, Nathan G; Frankle, Mark A; Keppler, Louis J

2014-10-01

The accuracy of reproducing a surgical plan during shoulder arthroplasty is improved by computer assistance. Intraoperative navigation, however, is challenged by increased surgical time and additional technically difficult steps. Patient-matched instrumentation has the potential to reproduce a similar degree of accuracy without the need for additional surgical steps. The purpose of this study was to examine the accuracy of patient-specific planning and a patient-specific drill guide for glenoid baseplate placement in reverse shoulder arthroplasty. A patient-specific glenoid baseplate drill guide for reverse shoulder arthroplasty was produced for 14 cadaveric shoulders based on a plan developed by a virtual preoperative 3-dimensional planning system using thin-cut computed tomography images. Using this patient-specific guide, high-volume shoulder surgeons exposed the glenoid through a deltopectoral approach and drilled the bicortical pathway defined by the guide. The trajectory of the drill path was compared with the virtual preoperative planned position using similar thin-cut computed tomography images to define accuracy. The drill pathway defined by the patient-matched guide was found to be highly accurate when compared with the preoperative surgical plan. The translational accuracy was 1.2 ± 0.7 mm. The accuracy of inferior tilt was 1.2° ± 1.2°. The accuracy of glenoid version was 2.6° ± 1.7°. The use of patient-specific glenoid baseplate guides is highly accurate in reproducing a virtual 3-dimensional preoperative plan. This technique delivers the accuracy observed using computerized navigation without any additional surgical steps or technical challenges. Copyright © 2014 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Digital tomosynthesis (DTS) with a Circular X-ray tube: Its image reconstruction based on total-variation minimization and the image characteristics

NASA Astrophysics Data System (ADS)

Park, Y. O.; Hong, D. K.; Cho, H. S.; Je, U. K.; Oh, J. E.; Lee, M. S.; Kim, H. J.; Lee, S. H.; Jang, W. S.; Cho, H. M.; Choi, S. I.; Koo, Y. S.

2013-09-01

In this paper, we introduce an effective imaging system for digital tomosynthesis (DTS) with a circular X-ray tube, the so-called circular-DTS (CDTS) system, and its image reconstruction algorithm based on the total-variation (TV) minimization method for low-dose, high-accuracy X-ray imaging. Here, the X-ray tube is equipped with a series of cathodes distributed around a rotating anode, and the detector remains stationary throughout the image acquisition. We considered a TV-based reconstruction algorithm that exploited the sparsity of the image with substantially high image accuracy. We implemented the algorithm for the CDTS geometry and successfully reconstructed images of high accuracy. The image characteristics were investigated quantitatively by using some figures of merit, including the universal-quality index (UQI) and the depth resolution. For selected tomographic angles of 20, 40, and 60°, the corresponding UQI values in the tomographic view were estimated to be about 0.94, 0.97, and 0.98, and the depth resolutions were about 4.6, 3.1, and 1.2 voxels in full width at half maximum (FWHM), respectively. We expect the proposed method to be applicable to developing a next-generation dental or breast X-ray imaging system.

Effects of a risk-based online mammography intervention on accuracy of perceived risk and mammography intentions.

PubMed

Seitz, Holli H; Gibson, Laura; Skubisz, Christine; Forquer, Heather; Mello, Susan; Schapira, Marilyn M; Armstrong, Katrina; Cappella, Joseph N

2016-10-01

This experiment tested the effects of an individualized risk-based online mammography decision intervention. The intervention employs exemplification theory and the Elaboration Likelihood Model of persuasion to improve the match between breast cancer risk and mammography intentions. 2918 women ages 35-49 were stratified into two levels of 10-year breast cancer risk (<1.5%; ≥1.5%) then randomly assigned to one of eight conditions: two comparison conditions and six risk-based intervention conditions that varied according to a 2 (amount of content: brief vs. extended) x 3 (format: expository vs. untailored exemplar [example case] vs. tailored exemplar) design. Outcomes included mammography intentions and accuracy of perceived breast cancer risk. Risk-based intervention conditions improved the match between objective risk estimates and perceived risk, especially for high-numeracy women with a 10-year breast cancer risk ≤1.5%. For women with a risk≤1.5%, exemplars improved accuracy of perceived risk and all risk-based interventions increased intentions to wait until age 50 to screen. A risk-based mammography intervention improved accuracy of perceived risk and the match between objective risk estimates and mammography intentions. Interventions could be applied in online or clinical settings to help women understand risk and make mammography decisions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Effects of a Risk-based Online Mammography Intervention on Accuracy of Perceived Risk and Mammography Intentions

PubMed Central

Seitz, Holli H.; Gibson, Laura; Skubisz, Christine; Forquer, Heather; Mello, Susan; Schapira, Marilyn M.; Armstrong, Katrina; Cappella, Joseph N.

2016-01-01

Objective This experiment tested the effects of an individualized risk-based online mammography decision intervention. The intervention employs exemplification theory and the Elaboration Likelihood Model of persuasion to improve the match between breast cancer risk and mammography intentions. Methods 2,918 women ages 35-49 were stratified into two levels of 10-year breast cancer risk (< 1.5%; ≥ 1.5%) then randomly assigned to one of eight conditions: two comparison conditions and six risk-based intervention conditions that varied according to a 2 (amount of content: brief vs. extended) × 3 (format: expository vs. untailored exemplar [example case] vs. tailored exemplar) design. Outcomes included mammography intentions and accuracy of perceived breast cancer risk. Results Risk-based intervention conditions improved the match between objective risk estimates and perceived risk, especially for high-numeracy women with a 10-year breast cancer risk <1.5%. For women with a risk < 1.5%, exemplars improved accuracy of perceived risk and all risk-based interventions increased intentions to wait until age 50 to screen. Conclusion A risk-based mammography intervention improved accuracy of perceived risk and the match between objective risk estimates and mammography intentions. Practice Implications Interventions could be applied in online or clinical settings to help women understand risk and make mammography decisions. PMID:27178707

High accuracy operon prediction method based on STRING database scores.

PubMed

Taboada, Blanca; Verde, Cristina; Merino, Enrique

2010-07-01

We present a simple and highly accurate computational method for operon prediction, based on intergenic distances and functional relationships between the protein products of contiguous genes, as defined by STRING database (Jensen,L.J., Kuhn,M., Stark,M., Chaffron,S., Creevey,C., Muller,J., Doerks,T., Julien,P., Roth,A., Simonovic,M. et al. (2009) STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res., 37, D412-D416). These two parameters were used to train a neural network on a subset of experimentally characterized Escherichia coli and Bacillus subtilis operons. Our predictive model was successfully tested on the set of experimentally defined operons in E. coli and B. subtilis, with accuracies of 94.6 and 93.3%, respectively. As far as we know, these are the highest accuracies ever obtained for predicting bacterial operons. Furthermore, in order to evaluate the predictable accuracy of our model when using an organism's data set for the training procedure, and a different organism's data set for testing, we repeated the E. coli operon prediction analysis using a neural network trained with B. subtilis data, and a B. subtilis analysis using a neural network trained with E. coli data. Even for these cases, the accuracies reached with our method were outstandingly high, 91.5 and 93%, respectively. These results show the potential use of our method for accurately predicting the operons of any other organism. Our operon predictions for fully-sequenced genomes are available at http://operons.ibt.unam.mx/OperonPredictor/.

Identifying High-Rate Flows Based on Sequential Sampling

NASA Astrophysics Data System (ADS)

Zhang, Yu; Fang, Binxing; Luo, Hao

We consider the problem of fast identification of high-rate flows in backbone links with possibly millions of flows. Accurate identification of high-rate flows is important for active queue management, traffic measurement and network security such as detection of distributed denial of service attacks. It is difficult to directly identify high-rate flows in backbone links because tracking the possible millions of flows needs correspondingly large high speed memories. To reduce the measurement overhead, the deterministic 1-out-of-k sampling technique is adopted which is also implemented in Cisco routers (NetFlow). Ideally, a high-rate flow identification method should have short identification time, low memory cost and processing cost. Most importantly, it should be able to specify the identification accuracy. We develop two such methods. The first method is based on fixed sample size test (FSST) which is able to identify high-rate flows with user-specified identification accuracy. However, since FSST has to record every sampled flow during the measurement period, it is not memory efficient. Therefore the second novel method based on truncated sequential probability ratio test (TSPRT) is proposed. Through sequential sampling, TSPRT is able to remove the low-rate flows and identify the high-rate flows at the early stage which can reduce the memory cost and identification time respectively. According to the way to determine the parameters in TSPRT, two versions of TSPRT are proposed: TSPRT-M which is suitable when low memory cost is preferred and TSPRT-T which is suitable when short identification time is preferred. The experimental results show that TSPRT requires less memory and identification time in identifying high-rate flows while satisfying the accuracy requirement as compared to previously proposed methods.

Precision and accuracy of manual water-level measurements taken in the Yucca Mountain area, Nye County, Nevada, 1988-90

USGS Publications Warehouse

Boucher, M.S.

1994-01-01

Water-level measurements have been made in deep boreholes in the Yucca Mountain area, Nye County, Nevada, since 1983 in support of the U.S. Department of Energy's Yucca Mountain Project, which is an evaluation of the area to determine its suitability as a potential storage area for high-level nuclear waste. Water-level measurements were taken either manually, using various water-level measuring equipment such as steel tapes, or they were taken continuously, using automated data recorders and pressure transducers. This report presents precision range and accuracy data established for manual water-level measurements taken in the Yucca Mountain area, 1988-90. Precision and accuracy ranges were determined for all phases of the water-level measuring process, and overall accuracy ranges are presented. Precision ranges were determined for three steel tapes using a total of 462 data points. Mean precision ranges of these three tapes ranged from 0.014 foot to 0.026 foot. A mean precision range of 0.093 foot was calculated for the multiconductor cable, using 72 data points. Mean accuracy values were calculated on the basis of calibrations of the steel tapes and the multiconductor cable against a reference steel tape. The mean accuracy values of the steel tapes ranged from 0.053 foot, based on three data points to 0.078, foot based on six data points. The mean accuracy of the multiconductor cable was O. 15 foot, based on six data points. Overall accuracy of the water-level measurements was calculated by taking the square root of the sum of the squares of the individual accuracy values. Overall accuracy was calculated to be 0.36 foot for water-level measurements taken with steel tapes, without accounting for the inaccuracy of borehole deviations from vertical. An overall accuracy of 0.36 foot for measurements made with steel tapes is considered satisfactory for this project.

Optimization of the scan protocols for CT-based material extraction in small animal PET/CT studies

NASA Astrophysics Data System (ADS)

Yang, Ching-Ching; Yu, Jhih-An; Yang, Bang-Hung; Wu, Tung-Hsin

2013-12-01

We investigated the effects of scan protocols on CT-based material extraction to minimize radiation dose while maintaining sufficient image information in small animal studies. The phantom simulation experiments were performed with the high dose (HD), medium dose (MD) and low dose (LD) protocols at 50, 70 and 80 kVp with varying mA s. The reconstructed CT images were segmented based on Hounsfield unit (HU)-physical density (ρ) calibration curves and the dual-energy CT-based (DECT) method. Compared to the (HU;ρ) method performed on CT images acquired with the 80 kVp HD protocol, a 2-fold improvement in segmentation accuracy and a 7.5-fold reduction in radiation dose were observed when the DECT method was performed on CT images acquired with the 50/80 kVp LD protocol, showing the possibility to reduce radiation dose while achieving high segmentation accuracy.

Significant improvement in one-dimensional cursor control using Laplacian electroencephalography over electroencephalography

NASA Astrophysics Data System (ADS)

Boudria, Yacine; Feltane, Amal; Besio, Walter

2014-06-01

Objective. Brain-computer interfaces (BCIs) based on electroencephalography (EEG) have been shown to accurately detect mental activities, but the acquisition of high levels of control require extensive user training. Furthermore, EEG has low signal-to-noise ratio and low spatial resolution. The objective of the present study was to compare the accuracy between two types of BCIs during the first recording session. EEG and tripolar concentric ring electrode (TCRE) EEG (tEEG) brain signals were recorded and used to control one-dimensional cursor movements. Approach. Eight human subjects were asked to imagine either ‘left’ or ‘right’ hand movement during one recording session to control the computer cursor using TCRE and disc electrodes. Main results. The obtained results show a significant improvement in accuracies using TCREs (44%-100%) compared to disc electrodes (30%-86%). Significance. This study developed the first tEEG-based BCI system for real-time one-dimensional cursor movements and showed high accuracies with little training.

Optical Fiber On-Line Detection System for Non-Touch Monitoring Roller Shape

NASA Astrophysics Data System (ADS)

Guo, Y.; Wang, Y. T.

2006-10-01

Basing on the principle of reflective displacement fiber-optic sensor, a high accuracy non-touch on-line optical fiber measurement system for roller shape is presented. The principle and composition of the detection system and the operation process are expatiated also. By using a novel probe of three optical fibers in equal transverse space, the effects of fluctuations in the light source, reflective changing of target surface and the intensity losses in the fiber lines are automatically compensated. Meantime, an optical fiber sensor model of correcting static error based on BP artificial neural network (ANN) is set up. Also by using interpolation method and value filtering to process the signals, effectively reduce the influence of random noise and the vibration of the roller bearing. So enhance the accuracy and resolution remarkably. Experiment proves that the accuracy of the system reach to the demand of practical production process, it provides a new method for the high speed, accurate and automatic on line detection of the mill roller shape.

Research of autonomous celestial navigation based on new measurement model of stellar refraction

NASA Astrophysics Data System (ADS)

Yu, Cong; Tian, Hong; Zhang, Hui; Xu, Bo

2014-09-01

Autonomous celestial navigation based on stellar refraction has attracted widespread attention for its high accuracy and full autonomy．In this navigation method, establishment of accurate stellar refraction measurement model is the fundament and key issue to achieve high accuracy navigation. However, the existing measurement models are limited due to the uncertainty of atmospheric parameters. Temperature, pressure and other factors which affect the stellar refraction within the height of earth's stratosphere are researched, and the varying model of atmosphere with altitude is derived on the basis of standard atmospheric data. Furthermore, a novel measurement model of stellar refraction in a continuous range of altitudes from 20 km to 50 km is produced by modifying the fixed altitude (25 km) measurement model, and equation of state with the orbit perturbations is established, then a simulation is performed using the improved Extended Kalman Filter. The results show that the new model improves the navigation accuracy, which has a certain practical application value.

High altitude atmospheric modeling

NASA Technical Reports Server (NTRS)

Hedin, Alan E.

1988-01-01

Five empirical models were compared with 13 data sets, including both atmospheric drag-based data and mass spectrometer data. The most recently published model, MSIS-86, was found to be the best model overall with an accuracy around 15 percent. The excellent overall agreement of the mass spectrometer-based MSIS models with the drag data, including both the older data from orbital decay and the newer accelerometer data, suggests that the absolute calibration of the (ensemble of) mass spectrometers and the assumed drag coefficient in the atomic oxygen regime are consistent to 5 percent. This study illustrates a number of reasons for the current accuracy limit such as calibration accuracy and unmodeled trends. Nevertheless, the largest variations in total density in the thermosphere are accounted for, to a very high degree, by existing models. The greatest potential for improvements is in areas where we still have insufficient data (like the lower thermosphere or exosphere), where there are disagreements in technique (such as the exosphere) which can be resolved, or wherever generally more accurate measurements become available.

Fuzzy difference-of-Gaussian-based iris recognition method for noisy iris images

NASA Astrophysics Data System (ADS)

Kang, Byung Jun; Park, Kang Ryoung; Yoo, Jang-Hee; Moon, Kiyoung

2010-06-01

Iris recognition is used for information security with a high confidence level because it shows outstanding recognition accuracy by using human iris patterns with high degrees of freedom. However, iris recognition accuracy can be reduced by noisy iris images with optical and motion blurring. We propose a new iris recognition method based on the fuzzy difference-of-Gaussian (DOG) for noisy iris images. This study is novel in three ways compared to previous works: (1) The proposed method extracts iris feature values using the DOG method, which is robust to local variations of illumination and shows fine texture information, including various frequency components. (2) When determining iris binary codes, image noises that cause the quantization error of the feature values are reduced with the fuzzy membership function. (3) The optimal parameters of the DOG filter and the fuzzy membership function are determined in terms of iris recognition accuracy. Experimental results showed that the performance of the proposed method was better than that of previous methods for noisy iris images.

Accuracy Improvement Capability of Advanced Projectile Based on Course Correction Fuze Concept

PubMed Central

Elsaadany, Ahmed; Wen-jun, Yi

2014-01-01

Improvement in terminal accuracy is an important objective for future artillery projectiles. Generally it is often associated with range extension. Various concepts and modifications are proposed to correct the range and drift of artillery projectile like course correction fuze. The course correction fuze concepts could provide an attractive and cost-effective solution for munitions accuracy improvement. In this paper, the trajectory correction has been obtained using two kinds of course correction modules, one is devoted to range correction (drag ring brake) and the second is devoted to drift correction (canard based-correction fuze). The course correction modules have been characterized by aerodynamic computations and flight dynamic investigations in order to analyze the effects on deflection of the projectile aerodynamic parameters. The simulation results show that the impact accuracy of a conventional projectile using these course correction modules can be improved. The drag ring brake is found to be highly capable for range correction. The deploying of the drag brake in early stage of trajectory results in large range correction. The correction occasion time can be predefined depending on required correction of range. On the other hand, the canard based-correction fuze is found to have a higher effect on the projectile drift by modifying its roll rate. In addition, the canard extension induces a high-frequency incidence angle as canards reciprocate at the roll motion. PMID:25097873

Accuracy improvement capability of advanced projectile based on course correction fuze concept.

PubMed

Elsaadany, Ahmed; Wen-jun, Yi

2014-01-01

Improvement in terminal accuracy is an important objective for future artillery projectiles. Generally it is often associated with range extension. Various concepts and modifications are proposed to correct the range and drift of artillery projectile like course correction fuze. The course correction fuze concepts could provide an attractive and cost-effective solution for munitions accuracy improvement. In this paper, the trajectory correction has been obtained using two kinds of course correction modules, one is devoted to range correction (drag ring brake) and the second is devoted to drift correction (canard based-correction fuze). The course correction modules have been characterized by aerodynamic computations and flight dynamic investigations in order to analyze the effects on deflection of the projectile aerodynamic parameters. The simulation results show that the impact accuracy of a conventional projectile using these course correction modules can be improved. The drag ring brake is found to be highly capable for range correction. The deploying of the drag brake in early stage of trajectory results in large range correction. The correction occasion time can be predefined depending on required correction of range. On the other hand, the canard based-correction fuze is found to have a higher effect on the projectile drift by modifying its roll rate. In addition, the canard extension induces a high-frequency incidence angle as canards reciprocate at the roll motion.

Application of magnetic resonance imaging in diagnosis of Uterus Cervical Carcinoma.

PubMed

Peng, Jidong; Wang, Weiqiang; Zeng, Daohui

2017-01-01

Effective treatment of Uterus Cervical Carcinoma (UCC) rely heavily on the precise pre-surgical staging. The conventional International Federation of Gynecology and Obstetrics (FIGO) system based on clinical examination is being applied worldwide for UCC staging. Yet its performance just appears passable. Thus, this study aims to investigate the value of applying Magnetic Resonance Imaging (MRI) with clinical examination in staging of UCC. A retrospective dataset involving 164 patients diagnosed with UCC was enrolled in this study. The mean age of this study population was 46.1 years (range, 28-#x2013;75 years). All patients underwent operations and UCC types were confirmed by pathological examinations. The tumor stages were determined by two experienced Gynecologist independently based on FIGO examinations and MRI. The diagnostic results were also compared with the post-operative pathologic reports. Statistical data analysis on diagnostic performance was then done and reported. The study results showed that the overall accuracy of applying MRI in UCC staging was 82.32%, while using FIGO staging method, the staging accuracy was 59.15%. MRI is suitable to evaluate tumor extent with high accuracy, and it can offer more objective information for the diagnosis and staging of UCC. Compared with clinical examinations based on FIGO, MRI illustrated relatively high accuracy in evaluating UCC staging, and is worthwhile to be recommended in future clinical practice.

Design of a prototype position actuator for the primary mirror segments of the European Extremely Large Telescope

NASA Astrophysics Data System (ADS)

Jiménez, A.; Morante, E.; Viera, T.; Núñez, M.; Reyes, M.

2010-07-01

European Extremely Large Telescope (E-ELT) based in 984 primary mirror segments achieving required optical performance; they must position relatively to adjacent segments with relative nanometer accuracy. CESA designed M1 Position Actuators (PACT) to comply with demanding performance requirements of EELT. Three PACT are located under each segment controlling three out of the plane degrees of freedom (tip, tilt, piston). To achieve a high linear accuracy in long operational displacements, PACT uses two stages in series. First stage based on Voice Coil Actuator (VCA) to achieve high accuracies in very short travel ranges, while second stage based on Brushless DC Motor (BLDC) provides large stroke ranges and allows positioning the first stage closer to the demanded position. A BLDC motor is used achieving a continuous smoothly movement compared to sudden jumps of a stepper. A gear box attached to the motor allows a high reduction of power consumption and provides a great challenge for sizing. PACT space envelope was reduced by means of two flat springs fixed to VCA. Its main characteristic is a low linear axial stiffness. To achieve best performance for PACT, sensors have been included in both stages. A rotary encoder is included in BLDC stage to close position/velocity control loop. An incremental optical encoder measures PACT travel range with relative nanometer accuracy and used to close the position loop of the whole actuator movement. For this purpose, four different optical sensors with different gratings will be evaluated. Control strategy show different internal closed loops that work together to achieve required performance.

Is multiple-sequence alignment required for accurate inference of phylogeny?

PubMed

Höhl, Michael; Ragan, Mark A

2007-04-01

The process of inferring phylogenetic trees from molecular sequences almost always starts with a multiple alignment of these sequences but can also be based on methods that do not involve multiple sequence alignment. Very little is known about the accuracy with which such alignment-free methods recover the correct phylogeny or about the potential for increasing their accuracy. We conducted a large-scale comparison of ten alignment-free methods, among them one new approach that does not calculate distances and a faster variant of our pattern-based approach; all distance-based alignment-free methods are freely available from http://www.bioinformatics.org.au (as Python package decaf+py). We show that most methods exhibit a higher overall reconstruction accuracy in the presence of high among-site rate variation. Under all conditions that we considered, variants of the pattern-based approach were significantly better than the other alignment-free methods. The new pattern-based variant achieved a speed-up of an order of magnitude in the distance calculation step, accompanied by a small loss of tree reconstruction accuracy. A method of Bayesian inference from k-mers did not improve on classical alignment-free (and distance-based) methods but may still offer other advantages due to its Bayesian nature. We found the optimal word length k of word-based methods to be stable across various data sets, and we provide parameter ranges for two different alphabets. The influence of these alphabets was analyzed to reveal a trade-off in reconstruction accuracy between long and short branches. We have mapped the phylogenetic accuracy for many alignment-free methods, among them several recently introduced ones, and increased our understanding of their behavior in response to biologically important parameters. In all experiments, the pattern-based approach emerged as superior, at the expense of higher resource consumption. Nonetheless, no alignment-free method that we examined recovers the correct phylogeny as accurately as does an approach based on maximum-likelihood distance estimates of multiply aligned sequences.

Effect of time discretization of the imaging process on the accuracy of trajectory estimation in fluorescence microscopy

PubMed Central

Wong, Yau; Chao, Jerry; Lin, Zhiping; Ober, Raimund J.

2014-01-01

In fluorescence microscopy, high-speed imaging is often necessary for the proper visualization and analysis of fast subcellular dynamics. Here, we examine how the speed of image acquisition affects the accuracy with which parameters such as the starting position and speed of a microscopic non-stationary fluorescent object can be estimated from the resulting image sequence. Specifically, we use a Fisher information-based performance bound to investigate the detector-dependent effect of frame rate on the accuracy of parameter estimation. We demonstrate that when a charge-coupled device detector is used, the estimation accuracy deteriorates as the frame rate increases beyond a point where the detector’s readout noise begins to overwhelm the low number of photons detected in each frame. In contrast, we show that when an electron-multiplying charge-coupled device (EMCCD) detector is used, the estimation accuracy improves with increasing frame rate. In fact, at high frame rates where the low number of photons detected in each frame renders the fluorescent object difficult to detect visually, imaging with an EMCCD detector represents a natural implementation of the Ultrahigh Accuracy Imaging Modality, and enables estimation with an accuracy approaching that which is attainable only when a hypothetical noiseless detector is used. PMID:25321248

Block Adjustment and Image Matching of WORLDVIEW-3 Stereo Pairs and Accuracy Evaluation

NASA Astrophysics Data System (ADS)

Zuo, C.; Xiao, X.; Hou, Q.; Li, B.

2018-05-01

WorldView-3, as a high-resolution commercial earth observation satellite, which is launched by Digital Global, provides panchromatic imagery of 0.31 m resolution. The positioning accuracy is less than 3.5 meter CE90 without ground control, which can use for large scale topographic mapping. This paper presented the block adjustment for WorldView-3 based on RPC model and achieved the accuracy of 1 : 2000 scale topographic mapping with few control points. On the base of stereo orientation result, this paper applied two kinds of image matching algorithm for DSM extraction: LQM and SGM. Finally, this paper compared the accuracy of the point cloud generated by the two image matching methods with the reference data which was acquired by an airborne laser scanner. The results showed that the RPC adjustment model of WorldView-3 image with small number of GCPs could satisfy the requirement of Chinese Surveying and Mapping regulations for 1 : 2000 scale topographic maps. And the point cloud result obtained through WorldView-3 stereo image matching had higher elevation accuracy, the RMS error of elevation for bare ground area is 0.45 m, while for buildings the accuracy can almost reach 1 meter.

Higher-order triangular spectral element method with optimized cubature points for seismic wavefield modeling

NASA Astrophysics Data System (ADS)

Liu, Youshan; Teng, Jiwen; Xu, Tao; Badal, José

2017-05-01

The mass-lumped method avoids the cost of inverting the mass matrix and simultaneously maintains spatial accuracy by adopting additional interior integration points, known as cubature points. To date, such points are only known analytically in tensor domains, such as quadrilateral or hexahedral elements. Thus, the diagonal-mass-matrix spectral element method (SEM) in non-tensor domains always relies on numerically computed interpolation points or quadrature points. However, only the cubature points for degrees 1 to 6 are known, which is the reason that we have developed a p-norm-based optimization algorithm to obtain higher-order cubature points. In this way, we obtain and tabulate new cubature points with all positive integration weights for degrees 7 to 9. The dispersion analysis illustrates that the dispersion relation determined from the new optimized cubature points is comparable to that of the mass and stiffness matrices obtained by exact integration. Simultaneously, the Lebesgue constant for the new optimized cubature points indicates its surprisingly good interpolation properties. As a result, such points provide both good interpolation properties and integration accuracy. The Courant-Friedrichs-Lewy (CFL) numbers are tabulated for the conventional Fekete-based triangular spectral element (TSEM), the TSEM with exact integration, and the optimized cubature-based TSEM (OTSEM). A complementary study demonstrates the spectral convergence of the OTSEM. A numerical example conducted on a half-space model demonstrates that the OTSEM improves the accuracy by approximately one order of magnitude compared to the conventional Fekete-based TSEM. In particular, the accuracy of the 7th-order OTSEM is even higher than that of the 14th-order Fekete-based TSEM. Furthermore, the OTSEM produces a result that can compete in accuracy with the quadrilateral SEM (QSEM). The high accuracy of the OTSEM is also tested with a non-flat topography model. In terms of computational efficiency, the OTSEM is more efficient than the Fekete-based TSEM, although it is slightly costlier than the QSEM when a comparable numerical accuracy is required.

Assessing the dependence of sensitivity and specificity on prevalence in meta-analysis

PubMed Central

Li, Jialiang; Fine, Jason P.

2011-01-01

We consider modeling the dependence of sensitivity and specificity on the disease prevalence in diagnostic accuracy studies. Many meta-analyses compare test accuracy across studies and fail to incorporate the possible connection between the accuracy measures and the prevalence. We propose a Pearson type correlation coefficient and an estimating equation–based regression framework to help understand such a practical dependence. The results we derive may then be used to better interpret the results from meta-analyses. In the biomedical examples analyzed in this paper, the diagnostic accuracy of biomarkers are shown to be associated with prevalence, providing insights into the utility of these biomarkers in low- and high-prevalence populations. PMID:21525421

Rolling bearing fault diagnosis based on information fusion using Dempster-Shafer evidence theory

NASA Astrophysics Data System (ADS)

Pei, Di; Yue, Jianhai; Jiao, Jing

2017-10-01

This paper presents a fault diagnosis method for rolling bearing based on information fusion. Acceleration sensors are arranged at different position to get bearing vibration data as diagnostic evidence. The Dempster-Shafer (D-S) evidence theory is used to fuse multi-sensor data to improve diagnostic accuracy. The efficiency of the proposed method is demonstrated by the high speed train transmission test bench. The results of experiment show that the proposed method in this paper improves the rolling bearing fault diagnosis accuracy compared with traditional signal analysis methods.

Reputation-Based Secure Sensor Localization in Wireless Sensor Networks

PubMed Central

He, Jingsha; Xu, Jing; Zhu, Xingye; Zhang, Yuqiang; Zhang, Ting; Fu, Wanqing

2014-01-01

Location information of sensor nodes in wireless sensor networks (WSNs) is very important, for it makes information that is collected and reported by the sensor nodes spatially meaningful for applications. Since most current sensor localization schemes rely on location information that is provided by beacon nodes for the regular sensor nodes to locate themselves, the accuracy of localization depends on the accuracy of location information from the beacon nodes. Therefore, the security and reliability of the beacon nodes become critical in the localization of regular sensor nodes. In this paper, we propose a reputation-based security scheme for sensor localization to improve the security and the accuracy of sensor localization in hostile or untrusted environments. In our proposed scheme, the reputation of each beacon node is evaluated based on a reputation evaluation model so that regular sensor nodes can get credible location information from highly reputable beacon nodes to accomplish localization. We also perform a set of simulation experiments to demonstrate the effectiveness of the proposed reputation-based security scheme. And our simulation results show that the proposed security scheme can enhance the security and, hence, improve the accuracy of sensor localization in hostile or untrusted environments. PMID:24982940

High-Resolution Surface Reconstruction from Imagery for Close Range Cultural Heritage Applications

NASA Astrophysics Data System (ADS)

Wenzel, K.; Abdel-Wahab, M.; Cefalu, A.; Fritsch, D.

2012-07-01

The recording of high resolution point clouds with sub-mm resolution is a demanding and cost intensive task, especially with current equipment like handheld laser scanners. We present an image based approached, where techniques of image matching and dense surface reconstruction are combined with a compact and affordable rig of off-the-shelf industry cameras. Such cameras provide high spatial resolution with low radiometric noise, which enables a one-shot solution and thus an efficient data acquisition while satisfying high accuracy requirements. However, the largest drawback of image based solutions is often the acquisition of surfaces with low texture where the image matching process might fail. Thus, an additional structured light projector is employed, represented here by the pseudo-random pattern projector of the Microsoft Kinect. Its strong infrared-laser projects speckles of different sizes. By using dense image matching techniques on the acquired images, a 3D point can be derived for almost each pixel. The use of multiple cameras enables the acquisition of a high resolution point cloud with high accuracy for each shot. For the proposed system up to 3.5 Mio. 3D points with sub-mm accuracy can be derived per shot. The registration of multiple shots is performed by Structure and Motion reconstruction techniques, where feature points are used to derive the camera positions and rotations automatically without initial information.

An Improved BLE Indoor Localization with Kalman-Based Fusion: An Experimental Study

PubMed Central

Röbesaat, Jenny; Zhang, Peilin; Abdelaal, Mohamed; Theel, Oliver

2017-01-01

Indoor positioning has grasped great attention in recent years. A number of efforts have been exerted to achieve high positioning accuracy. However, there exists no technology that proves its efficacy in various situations. In this paper, we propose a novel positioning method based on fusing trilateration and dead reckoning. We employ Kalman filtering as a position fusion algorithm. Moreover, we adopt an Android device with Bluetooth Low Energy modules as the communication platform to avoid excessive energy consumption and to improve the stability of the received signal strength. To further improve the positioning accuracy, we take the environmental context information into account while generating the position fixes. Extensive experiments in a testbed are conducted to examine the performance of three approaches: trilateration, dead reckoning and the fusion method. Additionally, the influence of the knowledge of the environmental context is also examined. Finally, our proposed fusion method outperforms both trilateration and dead reckoning in terms of accuracy: experimental results show that the Kalman-based fusion, for our settings, achieves a positioning accuracy of less than one meter. PMID:28445421

Detection and mapping the spatial distribution of bracken fern weeds using the Landsat 8 OLI new generation sensor

NASA Astrophysics Data System (ADS)

Matongera, Trylee Nyasha; Mutanga, Onisimo; Dube, Timothy; Sibanda, Mbulisi

2017-05-01

Bracken fern is an invasive plant that presents serious environmental, ecological and economic problems around the world. An understanding of the spatial distribution of bracken fern weeds is therefore essential for providing appropriate management strategies at both local and regional scales. The aim of this study was to assess the utility of the freely available medium resolution Landsat 8 OLI sensor in the detection and mapping of bracken fern at the Cathedral Peak, South Africa. To achieve this objective, the results obtained from Landsat 8 OLI were compared with those derived using the costly, high spatial resolution WorldView-2 imagery. Since previous studies have already successfully mapped bracken fern using high spatial resolution WorldView-2 image, the comparison was done to investigate the magnitude of difference in accuracy between the two sensors in relation to their acquisition costs. To evaluate the performance of Landsat 8 OLI in discriminating bracken fern compared to that of Worldview-2, we tested the utility of (i) spectral bands; (ii) derived vegetation indices as well as (iii) the combination of spectral bands and vegetation indices based on discriminant analysis classification algorithm. After resampling the training and testing data and reclassifying several times (n = 100) based on the combined data sets, the overall accuracies for both Landsat 8 and WorldView-2 were tested for significant differences based on Mann-Whitney U test. The results showed that the integration of the spectral bands and derived vegetation indices yielded the best overall classification accuracy (80.08% and 87.80% for Landsat 8 OLI and WorldView-2 respectively). Additionally, the use of derived vegetation indices as a standalone data set produced the weakest overall accuracy results of 62.14% and 82.11% for both the Landsat 8 OLI and WorldView-2 images. There were significant differences {U (100) = 569.5, z = -10.8242, p < 0.01} between the classification accuracies derived based on Landsat OLI 8 and those derived using WorldView-2 sensor. Although there were significant differences between Landsat and WorldView-2 accuracies, the magnitude of variation (9%) between the two sensors was within an acceptable range. Therefore, the findings of this study demonstrated that the recently launched Landsat 8 OLI multispectral sensor provides valuable information that could aid in the long term continuous monitoring and formulation of effective bracken fern management with acceptable accuracies that are comparable to those obtained from the high resolution WorldView-2 commercial sensor.

Delineating Beach and Dune Morphology from Massive Terrestrial Laser Scanning Data Using the Generic Mapping Tools

NASA Astrophysics Data System (ADS)

Zhou, X.; Wang, G.; Yan, B.; Kearns, T.

2016-12-01

Terrestrial laser scanning (TLS) techniques have been proven to be efficient tools to collect three-dimensional high-density and high-accuracy point clouds for coastal research and resource management. However, the processing and presenting of massive TLS data is always a challenge for research when targeting a large area with high-resolution. This article introduces a workflow using shell-scripting techniques to chain together tools from the Generic Mapping Tools (GMT), Geographic Resources Analysis Support System (GRASS), and other command-based open-source utilities for automating TLS data processing. TLS point clouds acquired in the beach and dune area near Freeport, Texas in May 2015 were used for the case study. Shell scripts for rotating the coordinate system, removing anomalous points, assessing data quality, generating high-accuracy bare-earth DEMs, and quantifying beach and sand dune features (shoreline, cross-dune section, dune ridge, toe, and volume) are presented in this article. According to this investigation, the accuracy of the laser measurements (distance from the scanner to the targets) is within a couple of centimeters. However, the positional accuracy of TLS points with respect to a global coordinate system is about 5 cm, which is dominated by the accuracy of GPS solutions for obtaining the positions of the scanner and reflector. The accuracy of TLS-derived bare-earth DEM is primarily determined by the size of grid cells and roughness of the terrain surface for the case study. A DEM with grid cells of 4m x 1m (shoreline by cross-shore) provides a suitable spatial resolution and accuracy for deriving major beach and dune features.

Using high-order polynomial basis in 3-D EM forward modeling based on volume integral equation method

NASA Astrophysics Data System (ADS)

Kruglyakov, Mikhail; Kuvshinov, Alexey

2018-05-01

3-D interpretation of electromagnetic (EM) data of different origin and scale becomes a common practice worldwide. However, 3-D EM numerical simulations (modeling)—a key part of any 3-D EM data analysis—with realistic levels of complexity, accuracy and spatial detail still remains challenging from the computational point of view. We present a novel, efficient 3-D numerical solver based on a volume integral equation (IE) method. The efficiency is achieved by using a high-order polynomial (HOP) basis instead of the zero-order (piecewise constant) basis that is invoked in all routinely used IE-based solvers. We demonstrate that usage of the HOP basis allows us to decrease substantially the number of unknowns (preserving the same accuracy), with corresponding speed increase and memory saving.

Bridge Displacement Monitoring Method Based on Laser Projection-Sensing Technology

PubMed Central

Zhao, Xuefeng; Liu, Hao; Yu, Yan; Xu, Xiaodong; Hu, Weitong; Li, Mingchu; Ou, Jingping

2015-01-01

Bridge displacement is the most basic evaluation index of the health status of a bridge structure. The existing measurement methods for bridge displacement basically fail to realize long-term and real-time dynamic monitoring of bridge structures, because of the low degree of automation and the insufficient precision, causing bottlenecks and restriction. To solve this problem, we proposed a bridge displacement monitoring system based on laser projection-sensing technology. First, the laser spot recognition method was studied. Second, the software for the displacement monitoring system was developed. Finally, a series of experiments using this system were conducted, and the results show that such a system has high measurement accuracy and speed. We aim to develop a low-cost, high-accuracy and long-term monitoring method for bridge displacement based on these preliminary efforts. PMID:25871716

Fuzzy Temporal Logic Based Railway Passenger Flow Forecast Model

PubMed Central

Dou, Fei; Jia, Limin; Wang, Li; Xu, Jie; Huang, Yakun

2014-01-01

Passenger flow forecast is of essential importance to the organization of railway transportation and is one of the most important basics for the decision-making on transportation pattern and train operation planning. Passenger flow of high-speed railway features the quasi-periodic variations in a short time and complex nonlinear fluctuation because of existence of many influencing factors. In this study, a fuzzy temporal logic based passenger flow forecast model (FTLPFFM) is presented based on fuzzy logic relationship recognition techniques that predicts the short-term passenger flow for high-speed railway, and the forecast accuracy is also significantly improved. An applied case that uses the real-world data illustrates the precision and accuracy of FTLPFFM. For this applied case, the proposed model performs better than the k-nearest neighbor (KNN) and autoregressive integrated moving average (ARIMA) models. PMID:25431586

Good Practices for Learning to Recognize Actions Using FV and VLAD.

PubMed

Wu, Jianxin; Zhang, Yu; Lin, Weiyao

2016-12-01

High dimensional representations such as Fisher vectors (FV) and vectors of locally aggregated descriptors (VLAD) have shown state-of-the-art accuracy for action recognition in videos. The high dimensionality, on the other hand, also causes computational difficulties when scaling up to large-scale video data. This paper makes three lines of contributions to learning to recognize actions using high dimensional representations. First, we reviewed several existing techniques that improve upon FV or VLAD in image classification, and performed extensive empirical evaluations to assess their applicability for action recognition. Our analyses of these empirical results show that normality and bimodality are essential to achieve high accuracy. Second, we proposed a new pooling strategy for VLAD and three simple, efficient, and effective transformations for both FV and VLAD. Both proposed methods have shown higher accuracy than the original FV/VLAD method in extensive evaluations. Third, we proposed and evaluated new feature selection and compression methods for the FV and VLAD representations. This strategy uses only 4% of the storage of the original representation, but achieves comparable or even higher accuracy. Based on these contributions, we recommend a set of good practices for action recognition in videos for practitioners in this field.

Classifier ensemble construction with rotation forest to improve medical diagnosis performance of machine learning algorithms.

PubMed

Ozcift, Akin; Gulten, Arif

2011-12-01

Improving accuracies of machine learning algorithms is vital in designing high performance computer-aided diagnosis (CADx) systems. Researches have shown that a base classifier performance might be enhanced by ensemble classification strategies. In this study, we construct rotation forest (RF) ensemble classifiers of 30 machine learning algorithms to evaluate their classification performances using Parkinson's, diabetes and heart diseases from literature. While making experiments, first the feature dimension of three datasets is reduced using correlation based feature selection (CFS) algorithm. Second, classification performances of 30 machine learning algorithms are calculated for three datasets. Third, 30 classifier ensembles are constructed based on RF algorithm to assess performances of respective classifiers with the same disease data. All the experiments are carried out with leave-one-out validation strategy and the performances of the 60 algorithms are evaluated using three metrics; classification accuracy (ACC), kappa error (KE) and area under the receiver operating characteristic (ROC) curve (AUC). Base classifiers succeeded 72.15%, 77.52% and 84.43% average accuracies for diabetes, heart and Parkinson's datasets, respectively. As for RF classifier ensembles, they produced average accuracies of 74.47%, 80.49% and 87.13% for respective diseases. RF, a newly proposed classifier ensemble algorithm, might be used to improve accuracy of miscellaneous machine learning algorithms to design advanced CADx systems. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A Novel Energy-Efficient Approach for Human Activity Recognition

PubMed Central

Zheng, Lingxiang; Wu, Dihong; Ruan, Xiaoyang; Weng, Shaolin; Tang, Biyu; Lu, Hai; Shi, Haibin

2017-01-01

In this paper, we propose a novel energy-efficient approach for mobile activity recognition system (ARS) to detect human activities. The proposed energy-efficient ARS, using low sampling rates, can achieve high recognition accuracy and low energy consumption. A novel classifier that integrates hierarchical support vector machine and context-based classification (HSVMCC) is presented to achieve a high accuracy of activity recognition when the sampling rate is less than the activity frequency, i.e., the Nyquist sampling theorem is not satisfied. We tested the proposed energy-efficient approach with the data collected from 20 volunteers (14 males and six females) and the average recognition accuracy of around 96.0% was achieved. Results show that using a low sampling rate of 1Hz can save 17.3% and 59.6% of energy compared with the sampling rates of 5 Hz and 50 Hz. The proposed low sampling rate approach can greatly reduce the power consumption while maintaining high activity recognition accuracy. The composition of power consumption in online ARS is also investigated in this paper. PMID:28885560

Optical System Error Analysis and Calibration Method of High-Accuracy Star Trackers

PubMed Central

Sun, Ting; Xing, Fei; You, Zheng

2013-01-01

The star tracker is a high-accuracy attitude measurement device widely used in spacecraft. Its performance depends largely on the precision of the optical system parameters. Therefore, the analysis of the optical system parameter errors and a precise calibration model are crucial to the accuracy of the star tracker. Research in this field is relatively lacking a systematic and universal analysis up to now. This paper proposes in detail an approach for the synthetic error analysis of the star tracker, without the complicated theoretical derivation. This approach can determine the error propagation relationship of the star tracker, and can build intuitively and systematically an error model. The analysis results can be used as a foundation and a guide for the optical design, calibration, and compensation of the star tracker. A calibration experiment is designed and conducted. Excellent calibration results are achieved based on the calibration model. To summarize, the error analysis approach and the calibration method are proved to be adequate and precise, and could provide an important guarantee for the design, manufacture, and measurement of high-accuracy star trackers. PMID:23567527

The interaction between vocabulary size and phonotactic probability effects on children's production accuracy and fluency in nonword repetition.

PubMed

Edwards, Jan; Beckman, Mary E; Munson, Benjamin

2004-04-01

Adults' performance on a variety of tasks suggests that phonological processing of nonwords is grounded in generalizations about sublexical patterns over all known words. A small body of research suggests that children's phonological acquisition is similarly based on generalizations over the lexicon. To test this account, production accuracy and fluency were examined in nonword repetitions by 104 children and 22 adults. Stimuli were 22 pairs of nonwords, in which one nonword contained a low-frequency or unattested two-phoneme sequence and the other contained a high-frequency sequence. For a subset of these nonword pairs, segment durations were measured. The same sound was produced with a longer duration (less fluently) when it appeared in a low-frequency sequence, as compared to a high-frequency sequence. Low-frequency sequences were also repeated with lower accuracy than high-frequency sequences. Moreover, children with smaller vocabularies showed a larger influence of frequency on accuracy than children with larger vocabularies. Taken together, these results provide support for a model of phonological acquisition in which knowledge of sublexical units emerges from generalizations made over lexical items.

Generalized Centroid Estimators in Bioinformatics

PubMed Central

Hamada, Michiaki; Kiryu, Hisanori; Iwasaki, Wataru; Asai, Kiyoshi

2011-01-01

In a number of estimation problems in bioinformatics, accuracy measures of the target problem are usually given, and it is important to design estimators that are suitable to those accuracy measures. However, there is often a discrepancy between an employed estimator and a given accuracy measure of the problem. In this study, we introduce a general class of efficient estimators for estimation problems on high-dimensional binary spaces, which represent many fundamental problems in bioinformatics. Theoretical analysis reveals that the proposed estimators generally fit with commonly-used accuracy measures (e.g. sensitivity, PPV, MCC and F-score) as well as it can be computed efficiently in many cases, and cover a wide range of problems in bioinformatics from the viewpoint of the principle of maximum expected accuracy (MEA). It is also shown that some important algorithms in bioinformatics can be interpreted in a unified manner. Not only the concept presented in this paper gives a useful framework to design MEA-based estimators but also it is highly extendable and sheds new light on many problems in bioinformatics. PMID:21365017

A noncontact laser technique for circular contouring accuracy measurement

NASA Astrophysics Data System (ADS)

Wang, Charles; Griffin, Bob

2001-02-01

The worldwide competition in manufacturing frequently requires the high-speed machine tools to deliver contouring accuracy in the order of a few micrometers, while moving at relatively high feed rates. Traditional test equipment is rather limited in its capability to measure contours of small radius at high speed. Described here is a new noncontact laser measurement technique for the test of circular contouring accuracy. This technique is based on a single-aperture laser Doppler displacement meter with a flat mirror as the target. It is of a noncontact type with the ability to vary the circular path radius continuously at data rates of up to 1000 Hz. Using this instrument, the actual radius, feed rate, velocity, and acceleration profiles can also be determined. The basic theory of operation, the hardware setup, the data collection, the data processing, and the error budget are discussed.

Temporal regularization of ultrasound-based liver motion estimation for image-guided radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

O’Shea, Tuathan P., E-mail: tuathan.oshea@icr.ac.uk; Bamber, Jeffrey C.; Harris, Emma J.

Purpose: Ultrasound-based motion estimation is an expanding subfield of image-guided radiation therapy. Although ultrasound can detect tissue motion that is a fraction of a millimeter, its accuracy is variable. For controlling linear accelerator tracking and gating, ultrasound motion estimates must remain highly accurate throughout the imaging sequence. This study presents a temporal regularization method for correlation-based template matching which aims to improve the accuracy of motion estimates. Methods: Liver ultrasound sequences (15–23 Hz imaging rate, 2.5–5.5 min length) from ten healthy volunteers under free breathing were used. Anatomical features (blood vessels) in each sequence were manually annotated for comparison withmore » normalized cross-correlation based template matching. Five sequences from a Siemens Acuson™ scanner were used for algorithm development (training set). Results from incremental tracking (IT) were compared with a temporal regularization method, which included a highly specific similarity metric and state observer, known as the α–β filter/similarity threshold (ABST). A further five sequences from an Elekta Clarity™ system were used for validation, without alteration of the tracking algorithm (validation set). Results: Overall, the ABST method produced marked improvements in vessel tracking accuracy. For the training set, the mean and 95th percentile (95%) errors (defined as the difference from manual annotations) were 1.6 and 1.4 mm, respectively (compared to 6.2 and 9.1 mm, respectively, for IT). For each sequence, the use of the state observer leads to improvement in the 95% error. For the validation set, the mean and 95% errors for the ABST method were 0.8 and 1.5 mm, respectively. Conclusions: Ultrasound-based motion estimation has potential to monitor liver translation over long time periods with high accuracy. Nonrigid motion (strain) and the quality of the ultrasound data are likely to have an impact on tracking performance. A future study will investigate spatial uniformity of motion and its effect on the motion estimation errors.« less

An evaluation of a UAV guidance system with consumer grade GPS receivers

NASA Astrophysics Data System (ADS)

Rosenberg, Abigail Stella

Remote sensing has been demonstrated an important tool in agricultural and natural resource management and research applications, however there are limitations that exist with traditional platforms (i.e., hand held sensors, linear moves, vehicle mounted, airplanes, remotely piloted vehicles (RPVs), unmanned aerial vehicles (UAVs) and satellites). Rapid technological advances in electronics, computers, software applications, and the aerospace industry have dramatically reduced the cost and increased the availability of remote sensing technologies. Remote sensing imagery vary in spectral, spatial, and temporal resolutions and are available from numerous providers. Appendix A presented results of a test project that acquired high-resolution aerial photography with a RPV to map the boundary of a 0.42 km2 fire area. The project mapped the boundaries of the fire area from a mosaic of the aerial images collected and compared this with ground-based measurements. The project achieved a 92.4% correlation between the aerial assessment and the ground truth data. Appendix B used multi-objective analysis to quantitatively assess the tradeoffs between different sensor platform attributes to identify the best overall technology. Experts were surveyed to identify the best overall technology at three different pixel sizes. Appendix C evaluated the positional accuracy of a relatively low cost UAV designed for high resolution remote sensing of small areas in order to determine the positional accuracy of sensor readings. The study evaluated the accuracy and uncertainty of a UAV flight route with respect to the programmed waypoints and of the UAV's GPS position, respectively. In addition, the potential displacement of sensor data was evaluated based on (1) GPS measurements on board the aircraft and (2) the autopilot's circuit board with 3-axis gyros and accelerometers (i.e., roll, pitch, and yaw). The accuracies were estimated based on a 95% confidence interval or similar methods. The accuracy achieved in the second and third manuscripts demonstrates that reasonably priced, high resolution remote sensing via RPVs and UAVs is practical for agriculture and natural resource professionals.

Post-processing for improving hyperspectral anomaly detection accuracy

NASA Astrophysics Data System (ADS)

Wu, Jee-Cheng; Jiang, Chi-Ming; Huang, Chen-Liang

2015-10-01

Anomaly detection is an important topic in the exploitation of hyperspectral data. Based on the Reed-Xiaoli (RX) detector and a morphology operator, this research proposes a novel technique for improving the accuracy of hyperspectral anomaly detection. Firstly, the RX-based detector is used to process a given input scene. Then, a post-processing scheme using morphology operator is employed to detect those pixels around high-scoring anomaly pixels. Tests were conducted using two real hyperspectral images with ground truth information and the results based on receiver operating characteristic curves, illustrated that the proposed method reduced the false alarm rates of the RXbased detector.

Property evaluations of hydrocarbon fuels under supercritical conditions based on cubic equation of state

NASA Astrophysics Data System (ADS)

Li, Haohan; Wu, Yong; Zeng, Xiaojun; Wang, Xiaohan; Zhao, Daiqing

2017-06-01

Thermophysical properties, such as density, specific heat, viscosity and thermal conductivity, vary sharply near critical point. To evaluate these properties of hydrocarbons accurately is crucial to the further research of fuel system. Comparison was made by the calculating program based on four widely used equations of state (EoS), and results indicated that calculations based on the Peng-Robinson (PR) equation of state achieve better prediction accuracy among the four equations of state. Due to the small computational amount and high accuracy, the evaluation method proposed in this paper can be implemented into practical application for the design of fuel system.

Optimizing digital elevation models (DEMs) accuracy for planning and design of mobile communication networks

NASA Astrophysics Data System (ADS)

Hassan, Mahmoud A.

2004-02-01

Digital elevation models (DEMs) are important tools in the planning, design and maintenance of mobile communication networks. This research paper proposes a method for generating high accuracy DEMs based on SPOT satellite 1A stereo pair images, ground control points (GCP) and Erdas OrthoBASE Pro image processing software. DEMs with 0.2911 m mean error were achieved for the hilly and heavily populated city of Amman. The generated DEM was used to design a mobile communication network resulted in a minimum number of radio base transceiver stations, maximum number of covered regions and less than 2% of dead zones.

SoRS: Social recommendation using global rating reputation and local rating similarity

NASA Astrophysics Data System (ADS)

Qian, Fulan; Zhao, Shu; Tang, Jie; Zhang, Yanping

2016-11-01

Recommendation is an important and also challenging problem in online social networks. It needs to consider not only users' personalized interests, but also social relations between users. Indeed, in practice, users are often inclined to accept recommendations from friends or opinion leaders (users with high reputations). In this paper, we present a novel recommendation framework, social recommendation using global rating reputation and local rating similarity, which combine user reputation and social similarity based on ratings. User reputation can be obtained by iteratively calculating the correlation of historical ratings of user and intrinsic qualities of items. We view the user reputation as the user's global influence and the similarity based on rating of social relation as the user's local influence, introduce it in the basic social recommender model. Thus users with high reputation have a strong influence on the others, and on the other hand, the effect of a user with low reputation has been weakened. The recommendation accuracy of proposed framework can be improved by effectively removing nature noise because of less rigorous user ratings and strengthening the effect of user influence with high reputation. We also improve the similarity based on ratings by avoiding the high similarity with the less common ratings between friends. We evaluate our approach on three datasets including Movielens, Epinions and Douban. Empirical results demonstrate that proposed framework achieves significant improvements on recommendation accuracy. User reputation and local similarity which are both based on ratings have a lot of helpful in improvement of prediction accuracy. The reputation also can help to improve the recommendation precision with the small training sets.

Quantitative modeling of the accuracy in registering preoperative patient-specific anatomic models into left atrial cardiac ablation procedures

PubMed Central

Rettmann, Maryam E.; Holmes, David R.; Kwartowitz, David M.; Gunawan, Mia; Johnson, Susan B.; Camp, Jon J.; Cameron, Bruce M.; Dalegrave, Charles; Kolasa, Mark W.; Packer, Douglas L.; Robb, Richard A.

2014-01-01

Purpose: In cardiac ablation therapy, accurate anatomic guidance is necessary to create effective tissue lesions for elimination of left atrial fibrillation. While fluoroscopy, ultrasound, and electroanatomic maps are important guidance tools, they lack information regarding detailed patient anatomy which can be obtained from high resolution imaging techniques. For this reason, there has been significant effort in incorporating detailed, patient-specific models generated from preoperative imaging datasets into the procedure. Both clinical and animal studies have investigated registration and targeting accuracy when using preoperative models; however, the effect of various error sources on registration accuracy has not been quantitatively evaluated. Methods: Data from phantom, canine, and patient studies are used to model and evaluate registration accuracy. In the phantom studies, data are collected using a magnetically tracked catheter on a static phantom model. Monte Carlo simulation studies were run to evaluate both baseline errors as well as the effect of different sources of error that would be present in a dynamic in vivo setting. Error is simulated by varying the variance parameters on the landmark fiducial, physical target, and surface point locations in the phantom simulation studies. In vivo validation studies were undertaken in six canines in which metal clips were placed in the left atrium to serve as ground truth points. A small clinical evaluation was completed in three patients. Landmark-based and combined landmark and surface-based registration algorithms were evaluated in all studies. In the phantom and canine studies, both target registration error and point-to-surface error are used to assess accuracy. In the patient studies, no ground truth is available and registration accuracy is quantified using point-to-surface error only. Results: The phantom simulation studies demonstrated that combined landmark and surface-based registration improved landmark-only registration provided the noise in the surface points is not excessively high. Increased variability on the landmark fiducials resulted in increased registration errors; however, refinement of the initial landmark registration by the surface-based algorithm can compensate for small initial misalignments. The surface-based registration algorithm is quite robust to noise on the surface points and continues to improve landmark registration even at high levels of noise on the surface points. Both the canine and patient studies also demonstrate that combined landmark and surface registration has lower errors than landmark registration alone. Conclusions: In this work, we describe a model for evaluating the impact of noise variability on the input parameters of a registration algorithm in the context of cardiac ablation therapy. The model can be used to predict both registration error as well as assess which inputs have the largest effect on registration accuracy. PMID:24506630

Quantitative modeling of the accuracy in registering preoperative patient-specific anatomic models into left atrial cardiac ablation procedures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rettmann, Maryam E., E-mail: rettmann.maryam@mayo.edu; Holmes, David R.; Camp, Jon J.

2014-02-15

Purpose: In cardiac ablation therapy, accurate anatomic guidance is necessary to create effective tissue lesions for elimination of left atrial fibrillation. While fluoroscopy, ultrasound, and electroanatomic maps are important guidance tools, they lack information regarding detailed patient anatomy which can be obtained from high resolution imaging techniques. For this reason, there has been significant effort in incorporating detailed, patient-specific models generated from preoperative imaging datasets into the procedure. Both clinical and animal studies have investigated registration and targeting accuracy when using preoperative models; however, the effect of various error sources on registration accuracy has not been quantitatively evaluated. Methods: Datamore » from phantom, canine, and patient studies are used to model and evaluate registration accuracy. In the phantom studies, data are collected using a magnetically tracked catheter on a static phantom model. Monte Carlo simulation studies were run to evaluate both baseline errors as well as the effect of different sources of error that would be present in a dynamicin vivo setting. Error is simulated by varying the variance parameters on the landmark fiducial, physical target, and surface point locations in the phantom simulation studies. In vivo validation studies were undertaken in six canines in which metal clips were placed in the left atrium to serve as ground truth points. A small clinical evaluation was completed in three patients. Landmark-based and combined landmark and surface-based registration algorithms were evaluated in all studies. In the phantom and canine studies, both target registration error and point-to-surface error are used to assess accuracy. In the patient studies, no ground truth is available and registration accuracy is quantified using point-to-surface error only. Results: The phantom simulation studies demonstrated that combined landmark and surface-based registration improved landmark-only registration provided the noise in the surface points is not excessively high. Increased variability on the landmark fiducials resulted in increased registration errors; however, refinement of the initial landmark registration by the surface-based algorithm can compensate for small initial misalignments. The surface-based registration algorithm is quite robust to noise on the surface points and continues to improve landmark registration even at high levels of noise on the surface points. Both the canine and patient studies also demonstrate that combined landmark and surface registration has lower errors than landmark registration alone. Conclusions: In this work, we describe a model for evaluating the impact of noise variability on the input parameters of a registration algorithm in the context of cardiac ablation therapy. The model can be used to predict both registration error as well as assess which inputs have the largest effect on registration accuracy.« less

High frequency, high time resolution time-to-digital converter employing passive resonating circuits.

PubMed

Ripamonti, Giancarlo; Abba, Andrea; Geraci, Angelo

2010-05-01

A method for measuring time intervals accurate to the picosecond range is based on phase measurements of oscillating waveforms synchronous with their beginning and/or end. The oscillation is generated by triggering an LC resonant circuit, whose capacitance is precharged. By using high Q resonators and a final active quenching of the oscillation, it is possible to conjugate high time resolution and a small measurement time, which allows a high measurement rate. Methods for fast analysis of the data are considered and discussed with reference to computing resource requirements, speed, and accuracy. Experimental tests show the feasibility of the method and a time accuracy better than 4 ps rms. Methods aimed at further reducing hardware resources are finally discussed.

Controlling an avatar by thought using real-time fMRI

NASA Astrophysics Data System (ADS)

Cohen, Ori; Koppel, Moshe; Malach, Rafael; Friedman, Doron

2014-06-01

Objective. We have developed a brain-computer interface (BCI) system based on real-time functional magnetic resonance imaging (fMRI) with virtual reality feedback. The advantage of fMRI is the relatively high spatial resolution and the coverage of the whole brain; thus we expect that it may be used to explore novel BCI strategies, based on new types of mental activities. However, fMRI suffers from a low temporal resolution and an inherent delay, since it is based on a hemodynamic response rather than electrical signals. Thus, our objective in this paper was to explore whether subjects could perform a BCI task in a virtual environment using our system, and how their performance was affected by the delay. Approach. The subjects controlled an avatar by left-hand, right-hand and leg motion or imagery. The BCI classification is based on locating the regions of interest (ROIs) related with each of the motor classes, and selecting the ROI with maximum average values online. The subjects performed a cue-based task and a free-choice task, and the analysis includes evaluation of the performance as well as subjective reports. Main results. Six subjects performed the task with high accuracy when allowed to move their fingers and toes, and three subjects achieved high accuracy using imagery alone. In the cue-based task the accuracy was highest 8-12 s after the trigger, whereas in the free-choice task the subjects performed best when the feedback was provided 6 s after the trigger. Significance. We show that subjects are able to perform a navigation task in a virtual environment using an fMRI-based BCI, despite the hemodynamic delay. The same approach can be extended to other mental tasks and other brain areas.

Diagnostic potential of Raman spectroscopy in Barrett's esophagus

NASA Astrophysics Data System (ADS)

Wong Kee Song, Louis-Michel; Molckovsky, Andrea; Wang, Kenneth K.; Burgart, Lawrence J.; Dolenko, Brion; Somorjai, Rajmund L.; Wilson, Brian C.

2005-04-01

Patients with Barrett's esophagus (BE) undergo periodic endoscopic surveillance with random biopsies in an effort to detect dysplastic or early cancerous lesions. Surveillance may be enhanced by near-infrared Raman spectroscopy (NIRS), which has the potential to identify endoscopically-occult dysplastic lesions within the Barrett's segment and allow for targeted biopsies. The aim of this study was to assess the diagnostic performance of NIRS for identifying dysplastic lesions in BE in vivo. Raman spectra (Pexc=70 mW; t=5 s) were collected from Barrett's mucosa at endoscopy using a custom-built NIRS system (λexc=785 nm) equipped with a filtered fiber-optic probe. Each probed site was biopsied for matching histological diagnosis as assessed by an expert pathologist. Diagnostic algorithms were developed using genetic algorithm-based feature selection and linear discriminant analysis, and classification was performed on all spectra with a bootstrap-based cross-validation scheme. The analysis comprised 192 samples (112 non-dysplastic, 54 low-grade dysplasia and 26 high-grade dysplasia/early adenocarcinoma) from 65 patients. Compared with histology, NIRS differentiated dysplastic from non-dysplastic Barrett's samples with 86% sensitivity, 88% specificity and 87% accuracy. NIRS identified 'high-risk' lesions (high-grade dysplasia/early adenocarcinoma) with 88% sensitivity, 89% specificity and 89% accuracy. In the present study, NIRS classified Barrett's epithelia with high and clinically-useful diagnostic accuracy.

Brain tumour classification and abnormality detection using neuro-fuzzy technique and Otsu thresholding.

PubMed

Renjith, Arokia; Manjula, P; Mohan Kumar, P

2015-01-01

Brain tumour is one of the main causes for an increase in transience among children and adults. This paper proposes an improved method based on Magnetic Resonance Imaging (MRI) brain image classification and image segmentation approach. Automated classification is encouraged by the need of high accuracy when dealing with a human life. The detection of the brain tumour is a challenging problem, due to high diversity in tumour appearance and ambiguous tumour boundaries. MRI images are chosen for detection of brain tumours, as they are used in soft tissue determinations. First of all, image pre-processing is used to enhance the image quality. Second, dual-tree complex wavelet transform multi-scale decomposition is used to analyse texture of an image. Feature extraction extracts features from an image using gray-level co-occurrence matrix (GLCM). Then, the Neuro-Fuzzy technique is used to classify the stages of brain tumour as benign, malignant or normal based on texture features. Finally, tumour location is detected using Otsu thresholding. The classifier performance is evaluated based on classification accuracies. The simulated results show that the proposed classifier provides better accuracy than previous method.

A Novel Sensor System for Measuring Wheel Loads of Vehicles on Highways

PubMed Central

Zhang, Wenbin; Suo, Chunguang; Wang, Qi

2008-01-01

With the development of the highway transportation and business trade, vehicle Weigh-In-Motion (WIM) technology has become a key technology for measuring traffic loads. In this paper a novel WIM system based on monitoring of pavement strain responses in rigid pavement was investigated. In this WIM system multiple low cost, light weight, small volume and high accuracy embedded concrete strain sensors were used as WIM sensors to measure rigid pavement strain responses. In order to verify the feasibility of the method, a system prototype based on multiple sensors was designed and deployed on a relatively busy freeway. Field calibration and tests were performed with known two-axle truck wheel loads and the measurement errors were calculated based on the static weights measured with a static weighbridge. This enables the weights of other vehicles to be calculated from the calibration constant. Calibration and test results for individual sensors or three-sensor fusions are both provided. Repeatability, sources of error, and weight accuracy are discussed. Successful results showed that the proposed method was feasible and proven to have a high accuracy. Furthermore, a sample mean approach using multiple fused individual sensors could provide better performance compared to individual sensors. PMID:27873952

Emergency positioning system accuracy with infrared LEDs in high-security facilities

NASA Astrophysics Data System (ADS)

Knoch, Sierra N.; Nelson, Charles; Walker, Owens

2017-05-01

Instantaneous personnel location presents a challenge in Department of Defense applications where high levels of security restrict real-time tracking of crew members. During emergency situations, command and control requires immediate accountability of all personnel. Current radio frequency (RF) based indoor positioning systems can be unsuitable due to RF leakage and electromagnetic interference with sensitively calibrated machinery on variable platforms like ships, submarines and high-security facilities. Infrared light provide a possible solution to this problem. This paper proposes and evaluates an indoor line-of-sight positioning system that is comprised of IR and high-sensitivity CMOS camera receivers. In this system the movement of the LEDs is captured by the camera, uploaded and analyzed; the highest point of power is located and plotted to create a blueprint of crewmember location. Results provided evaluate accuracy as a function of both wavelength and environmental conditions. Research will further evaluate the accuracy of the LED transmitter and CMOS camera receiver system. Transmissions in both the 780 and 850nm IR are analyzed.

A high-order vertex-based central ENO finite-volume scheme for three-dimensional compressible flows

DOE PAGES

Charest, Marc R.J.; Canfield, Thomas R.; Morgan, Nathaniel R.; ...

2015-03-11

High-order discretization methods offer the potential to reduce the computational cost associated with modeling compressible flows. However, it is difficult to obtain accurate high-order discretizations of conservation laws that do not produce spurious oscillations near discontinuities, especially on multi-dimensional unstructured meshes. A novel, high-order, central essentially non-oscillatory (CENO) finite-volume method that does not have these difficulties is proposed for tetrahedral meshes. The proposed unstructured method is vertex-based, which differs from existing cell-based CENO formulations, and uses a hybrid reconstruction procedure that switches between two different solution representations. It applies a high-order k-exact reconstruction in smooth regions and a limited linearmore » reconstruction when discontinuities are encountered. Both reconstructions use a single, central stencil for all variables, making the application of CENO to arbitrary unstructured meshes relatively straightforward. The new approach was applied to the conservation equations governing compressible flows and assessed in terms of accuracy and computational cost. For all problems considered, which included various function reconstructions and idealized flows, CENO demonstrated excellent reliability and robustness. Up to fifth-order accuracy was achieved in smooth regions and essentially non-oscillatory solutions were obtained near discontinuities. The high-order schemes were also more computationally efficient for high-accuracy solutions, i.e., they took less wall time than the lower-order schemes to achieve a desired level of error. In one particular case, it took a factor of 24 less wall-time to obtain a given level of error with the fourth-order CENO scheme than to obtain the same error with the second-order scheme.« less

Compound activity prediction using models of binding pockets or ligand properties in 3D

PubMed Central

Kufareva, Irina; Chen, Yu-Chen; Ilatovskiy, Andrey V.; Abagyan, Ruben

2014-01-01

Transient interactions of endogenous and exogenous small molecules with flexible binding sites in proteins or macromolecular assemblies play a critical role in all biological processes. Current advances in high-resolution protein structure determination, database development, and docking methodology make it possible to design three-dimensional models for prediction of such interactions with increasing accuracy and specificity. Using the data collected in the Pocketome encyclopedia, we here provide an overview of two types of the three-dimensional ligand activity models, pocket-based and ligand property-based, for two important classes of proteins, nuclear and G-protein coupled receptors. For half the targets, the pocket models discriminate actives from property matched decoys with acceptable accuracy (the area under ROC curve, AUC, exceeding 84%) and for about one fifth of the targets with high accuracy (AUC > 95%). The 3D ligand property field models performed better than 95% in half of the cases. The high performance models can already become a basis of activity predictions for new chemicals. Family-wide benchmarking of the models highlights strengths of both approaches and helps identify their inherent bottlenecks and challenges. PMID:23116466

Algorithmic Classification of Five Characteristic Types of Paraphasias.

PubMed

Fergadiotis, Gerasimos; Gorman, Kyle; Bedrick, Steven

2016-12-01

This study was intended to evaluate a series of algorithms developed to perform automatic classification of paraphasic errors (formal, semantic, mixed, neologistic, and unrelated errors). We analyzed 7,111 paraphasias from the Moss Aphasia Psycholinguistics Project Database (Mirman et al., 2010) and evaluated the classification accuracy of 3 automated tools. First, we used frequency norms from the SUBTLEXus database (Brysbaert & New, 2009) to differentiate nonword errors and real-word productions. Then we implemented a phonological-similarity algorithm to identify phonologically related real-word errors. Last, we assessed the performance of a semantic-similarity criterion that was based on word2vec (Mikolov, Yih, & Zweig, 2013). Overall, the algorithmic classification replicated human scoring for the major categories of paraphasias studied with high accuracy. The tool that was based on the SUBTLEXus frequency norms was more than 97% accurate in making lexicality judgments. The phonological-similarity criterion was approximately 91% accurate, and the overall classification accuracy of the semantic classifier ranged from 86% to 90%. Overall, the results highlight the potential of tools from the field of natural language processing for the development of highly reliable, cost-effective diagnostic tools suitable for collecting high-quality measurement data for research and clinical purposes.

Micro-assembly of three-dimensional rotary MEMS mirrors

NASA Astrophysics Data System (ADS)

Wang, Lidai; Mills, James K.; Cleghorn, William L.

2009-02-01

We present a novel approach to construct three-dimensional rotary micro-mirrors, which are fundamental components to build 1×N or N×M optical switching systems. A rotary micro-mirror consists of two microparts: a rotary micro-motor and a micro-mirror. Both of the two microparts are fabricated with PolyMUMPs, a surface micromachining process. A sequential robotic microassembly process is developed to join the two microparts together to construct a threedimensional device. In order to achieve high positioning accuracy and a strong mechanical connection, the micro-mirror is joined to the micro-motor using an adhesive mechanical fastener. The mechanical fastener has self-alignment ability and provides a temporary joint between the two microparts. The adhesive bonding can create a strong permanent connection, which does not require extra supporting plates for the micro-mirror. A hybrid manipulation strategy, which includes pick-and-place and pushing-based manipulations, is utilized to manipulation the micro-mirror. The pick-andplace manipulation has the ability to globally position the micro-mirror in six degrees of freedom. The pushing-based manipulation can achieve high positioning accuracy. This microassembly approach has great flexibility and high accuracy; furthermore, it does not require extra supporting plates, which greatly simplifies the assembly process.

A robust method of computing finite difference coefficients based on Vandermonde matrix

NASA Astrophysics Data System (ADS)

Zhang, Yijie; Gao, Jinghuai; Peng, Jigen; Han, Weimin

2018-05-01

When the finite difference (FD) method is employed to simulate the wave propagation, high-order FD method is preferred in order to achieve better accuracy. However, if the order of FD scheme is high enough, the coefficient matrix of the formula for calculating finite difference coefficients is close to be singular. In this case, when the FD coefficients are computed by matrix inverse operator of MATLAB, inaccuracy can be produced. In order to overcome this problem, we have suggested an algorithm based on Vandermonde matrix in this paper. After specified mathematical transformation, the coefficient matrix is transformed into a Vandermonde matrix. Then the FD coefficients of high-order FD method can be computed by the algorithm of Vandermonde matrix, which prevents the inverse of the singular matrix. The dispersion analysis and numerical results of a homogeneous elastic model and a geophysical model of oil and gas reservoir demonstrate that the algorithm based on Vandermonde matrix has better accuracy compared with matrix inverse operator of MATLAB.

Ultrahigh-order Maxwell solver with extreme scalability for electromagnetic PIC simulations of plasmas

NASA Astrophysics Data System (ADS)

Vincenti, Henri; Vay, Jean-Luc

2018-07-01

The advent of massively parallel supercomputers, with their distributed-memory technology using many processing units, has favored the development of highly-scalable local low-order solvers at the expense of harder-to-scale global very high-order spectral methods. Indeed, FFT-based methods, which were very popular on shared memory computers, have been largely replaced by finite-difference (FD) methods for the solution of many problems, including plasmas simulations with electromagnetic Particle-In-Cell methods. For some problems, such as the modeling of so-called "plasma mirrors" for the generation of high-energy particles and ultra-short radiations, we have shown that the inaccuracies of standard FD-based PIC methods prevent the modeling on present supercomputers at sufficient accuracy. We demonstrate here that a new method, based on the use of local FFTs, enables ultrahigh-order accuracy with unprecedented scalability, and thus for the first time the accurate modeling of plasma mirrors in 3D.

Instrument for evaluation of sedentary lifestyle in patients with high blood pressure.

PubMed

Lopes, Marcos Venícios de Oliveira; da Silva, Viviane Martins; de Araujo, Thelma Leite; Guedes, Nirla Gomes; Martins, Larissa Castelo Guedes; Teixeira, Iane Ximenes

2015-01-01

this article describes the diagnostic accuracy of the International Physical Activity Questionnaire to identify the nursing diagnosis of sedentary lifestyle. a diagnostic accuracy study was developed with 240 individuals with established high blood pressure. The analysis of diagnostic accuracy was based on measures of sensitivity, specificity, predictive values, likelihood ratios, efficiency, diagnostic odds ratio, Youden index, and area under the receiver-operating characteristic curve. statistical differences between genders were observed for activities of moderate intensity and for total physical activity. Age was negatively correlated with activities of moderate intensity and total physical activity. the analysis of area under the receiver-operating characteristic curve for moderate intensity activities, walking, and total physical activity showed that the International Physical Activity Questionnaire present moderate capacity to correctly classify individuals with and without sedentary lifestyle.

Real-Time Optical Biopsy of Colon Polyps With Narrow Band Imaging in Community Practice Does Not Yet Meet Key Thresholds for Clinical Decisions

PubMed Central

LADABAUM, URI; FIORITTO, ANN; MITANI, AYA; DESAI, MANISHA; KIM, JANE P.; REX, DOUGLAS K.; IMPERIALE, THOMAS; GUNARATNAM, NARESH

2017-01-01

BACKGROUND & AIMS Accurate optical analysis of colorectal polyps (optical biopsy) could prevent unnecessary polypectomies or allow a “resect and discard” strategy with surveillance intervals determined based on the results of the optical biopsy; this could be less expensive than histopathologic analysis of polyps. We prospectively evaluated real-time optical biopsy analysis of polyps with narrow band imaging (NBI) by community-based gastroenterologists. METHODS We first analyzed a computerized module to train gastroenterologists (N = 13) in optical biopsy skills using photographs of polyps. Then we evaluated a practice-based learning program for these gastroenterologists (n = 12) that included real-time optical analysis of polyps in vivo, comparison of optical biopsy predictions to histopathologic analysis, and ongoing feedback on performance. RESULTS Twelve of 13 subjects identified adenomas with >90% accuracy at the end of the computer study, and 3 of 12 subjects did so with accuracy ≥90% in the in vivo study. Learning curves showed considerable variation among batches of polyps. For diminutive rectosigmoid polyps assessed with high confidence at the end of the study, adenomas were identified with mean (95% confidence interval [CI]) accuracy, sensitivity, specificity, and negative predictive values of 81% (73%–89%), 85% (74%–96%), 78% (66%–92%), and 91% (86%–97%), respectively. The adjusted odds ratio for high confidence as a predictor of accuracy was 1.8 (95% CI, 1.3–2.5). The agreement between surveillance recommendations informed by high-confidence NBI analysis of diminutive polyps and results from histopathologic analysis of all polyps was 80% (95% CI, 77%–82%). CONCLUSIONS In an evaluation of real-time optical biopsy analysis of polyps with NBI, only 25% of gastroenterologists assessed polyps with ≥90% accuracy. The negative predictive value for identification of adenomas, but not the surveillance interval agreement, met the American Society for Gastrointestinal Endoscopy–recommended thresholds for optical biopsy. Better results in community practice must be achieved before NBI-based optical biopsy methods can be used routinely to evaluate polyps; ClinicalTrials.gov number, NCT01638091. PMID:23041328

TU-H-CAMPUS-JeP3-02: Automated Dose Accumulation and Dose Accuracy Assessment for Online Or Offline Adaptive Replanning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, G; Ahunbay, E; Li, X

Purpose: With introduction of high-quality treatment imaging during radiation therapy (RT) delivery, e.g., MR-Linac, adaptive replanning of either online or offline becomes appealing. Dose accumulation of delivered fractions, a prerequisite for the adaptive replanning, can be cumbersome and inaccurate. The purpose of this work is to develop an automated process to accumulate daily doses and to assess the dose accumulation accuracy voxel-by-voxel for adaptive replanning. Methods: The process includes the following main steps: 1) reconstructing daily dose for each delivered fraction with a treatment planning system (Monaco, Elekta) based on the daily images using machine delivery log file and consideringmore » patient repositioning if applicable, 2) overlaying the daily dose to the planning image based on deformable image registering (DIR) (ADMIRE, Elekta), 3) assessing voxel dose deformation accuracy based on deformation field using predetermined criteria, and 4) outputting accumulated dose and dose-accuracy volume histograms and parameters. Daily CTs acquired using a CT-on-rails during routine CT-guided RT for sample patients with head and neck and prostate cancers were used to test the process. Results: Daily and accumulated doses (dose-volume histograms, etc) along with their accuracies (dose-accuracy volume histogram) can be robustly generated using the proposed process. The test data for a head and neck cancer case shows that the gross tumor volume decreased by 20% towards the end of treatment course, and the parotid gland mean dose increased by 10%. Such information would trigger adaptive replanning for the subsequent fractions. The voxel-based accuracy in the accumulated dose showed that errors in accumulated dose near rigid structures were small. Conclusion: A procedure as well as necessary tools to automatically accumulate daily dose and assess dose accumulation accuracy is developed and is useful for adaptive replanning. Partially supported by Elekta, Inc.« less

Automatic segmentation of invasive breast carcinomas from dynamic contrast-enhanced MRI using time series analysis.

PubMed

Jayender, Jagadaeesan; Chikarmane, Sona; Jolesz, Ferenc A; Gombos, Eva

2014-08-01

To accurately segment invasive ductal carcinomas (IDCs) from dynamic contrast-enhanced MRI (DCE-MRI) using time series analysis based on linear dynamic system (LDS) modeling. Quantitative segmentation methods based on black-box modeling and pharmacokinetic modeling are highly dependent on imaging pulse sequence, timing of bolus injection, arterial input function, imaging noise, and fitting algorithms. We modeled the underlying dynamics of the tumor by an LDS and used the system parameters to segment the carcinoma on the DCE-MRI. Twenty-four patients with biopsy-proven IDCs were analyzed. The lesions segmented by the algorithm were compared with an expert radiologist's segmentation and the output of a commercial software, CADstream. The results are quantified in terms of the accuracy and sensitivity of detecting the lesion and the amount of overlap, measured in terms of the Dice similarity coefficient (DSC). The segmentation algorithm detected the tumor with 90% accuracy and 100% sensitivity when compared with the radiologist's segmentation and 82.1% accuracy and 100% sensitivity when compared with the CADstream output. The overlap of the algorithm output with the radiologist's segmentation and CADstream output, computed in terms of the DSC was 0.77 and 0.72, respectively. The algorithm also shows robust stability to imaging noise. Simulated imaging noise with zero mean and standard deviation equal to 25% of the base signal intensity was added to the DCE-MRI series. The amount of overlap between the tumor maps generated by the LDS-based algorithm from the noisy and original DCE-MRI was DSC = 0.95. The time-series analysis based segmentation algorithm provides high accuracy and sensitivity in delineating the regions of enhanced perfusion corresponding to tumor from DCE-MRI. © 2013 Wiley Periodicals, Inc.

Automatic Segmentation of Invasive Breast Carcinomas from DCE-MRI using Time Series Analysis

PubMed Central

Jayender, Jagadaeesan; Chikarmane, Sona; Jolesz, Ferenc A.; Gombos, Eva

2013-01-01

Purpose Quantitative segmentation methods based on black-box modeling and pharmacokinetic modeling are highly dependent on imaging pulse sequence, timing of bolus injection, arterial input function, imaging noise and fitting algorithms. To accurately segment invasive ductal carcinomas (IDCs) from dynamic contrast enhanced MRI (DCE-MRI) using time series analysis based on linear dynamic system (LDS) modeling. Methods We modeled the underlying dynamics of the tumor by a LDS and use the system parameters to segment the carcinoma on the DCE-MRI. Twenty-four patients with biopsy-proven IDCs were analyzed. The lesions segmented by the algorithm were compared with an expert radiologist’s segmentation and the output of a commercial software, CADstream. The results are quantified in terms of the accuracy and sensitivity of detecting the lesion and the amount of overlap, measured in terms of the Dice similarity coefficient (DSC). Results The segmentation algorithm detected the tumor with 90% accuracy and 100% sensitivity when compared to the radiologist’s segmentation and 82.1% accuracy and 100% sensitivity when compared to the CADstream output. The overlap of the algorithm output with the radiologist’s segmentation and CADstream output, computed in terms of the DSC was 0.77 and 0.72 respectively. The algorithm also shows robust stability to imaging noise. Simulated imaging noise with zero mean and standard deviation equal to 25% of the base signal intensity was added to the DCE-MRI series. The amount of overlap between the tumor maps generated by the LDS-based algorithm from the noisy and original DCE-MRI was DSC=0.95. Conclusion The time-series analysis based segmentation algorithm provides high accuracy and sensitivity in delineating the regions of enhanced perfusion corresponding to tumor from DCE-MRI. PMID:24115175

A Novel Gravity Compensation Method for High Precision Free-INS Based on “Extreme Learning Machine”

PubMed Central

Zhou, Xiao; Yang, Gongliu; Cai, Qingzhong; Wang, Jing

2016-01-01

In recent years, with the emergency of high precision inertial sensors (accelerometers and gyros), gravity compensation has become a major source influencing the navigation accuracy in inertial navigation systems (INS), especially for high-precision INS. This paper presents preliminary results concerning the effect of gravity disturbance on INS. Meanwhile, this paper proposes a novel gravity compensation method for high-precision INS, which estimates the gravity disturbance on the track using the extreme learning machine (ELM) method based on measured gravity data on the geoid and processes the gravity disturbance to the height where INS has an upward continuation, then compensates the obtained gravity disturbance into the error equations of INS to restrain the INS error propagation. The estimation accuracy of the gravity disturbance data is verified by numerical tests. The root mean square error (RMSE) of the ELM estimation method can be improved by 23% and 44% compared with the bilinear interpolation method in plain and mountain areas, respectively. To further validate the proposed gravity compensation method, field experiments with an experimental vehicle were carried out in two regions. Test 1 was carried out in a plain area and Test 2 in a mountain area. The field experiment results also prove that the proposed gravity compensation method can significantly improve the positioning accuracy. During the 2-h field experiments, the positioning accuracy can be improved by 13% and 29% respectively, in Tests 1 and 2, when the navigation scheme is compensated by the proposed gravity compensation method. PMID:27916856

Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat

PubMed Central

Rutkoski, Jessica; Poland, Jesse; Mondal, Suchismita; Autrique, Enrique; Pérez, Lorena González; Crossa, José; Reynolds, Matthew; Singh, Ravi

2016-01-01

Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal or remote sensing could be useful for improving pedigree and genomic prediction model accuracies for traits not yet possible to phenotype directly. We tested if using aerial measurements of canopy temperature, and green and red normalized difference vegetation index as secondary traits in pedigree and genomic best linear unbiased prediction models could increase accuracy for grain yield in wheat, Triticum aestivum L., using 557 lines in five environments. Secondary traits on training and test sets, and grain yield on the training set were modeled as multivariate, and compared to univariate models with grain yield on the training set only. Cross validation accuracies were estimated within and across-environment, with and without replication, and with and without correcting for days to heading. We observed that, within environment, with unreplicated secondary trait data, and without correcting for days to heading, secondary traits increased accuracies for grain yield by 56% in pedigree, and 70% in genomic prediction models, on average. Secondary traits increased accuracy slightly more when replicated, and considerably less when models corrected for days to heading. In across-environment prediction, trends were similar but less consistent. These results show that secondary traits measured in high-throughput could be used in pedigree and genomic prediction to improve accuracy. This approach could improve selection in wheat during early stages if validated in early-generation breeding plots. PMID:27402362

A Subspace Pursuit–based Iterative Greedy Hierarchical Solution to the Neuromagnetic Inverse Problem

PubMed Central

Babadi, Behtash; Obregon-Henao, Gabriel; Lamus, Camilo; Hämäläinen, Matti S.; Brown, Emery N.; Purdon, Patrick L.

2013-01-01

Magnetoencephalography (MEG) is an important non-invasive method for studying activity within the human brain. Source localization methods can be used to estimate spatiotemporal activity from MEG measurements with high temporal resolution, but the spatial resolution of these estimates is poor due to the ill-posed nature of the MEG inverse problem. Recent developments in source localization methodology have emphasized temporal as well as spatial constraints to improve source localization accuracy, but these methods can be computationally intense. Solutions emphasizing spatial sparsity hold tremendous promise, since the underlying neurophysiological processes generating MEG signals are often sparse in nature, whether in the form of focal sources, or distributed sources representing large-scale functional networks. Recent developments in the theory of compressed sensing (CS) provide a rigorous framework to estimate signals with sparse structure. In particular, a class of CS algorithms referred to as greedy pursuit algorithms can provide both high recovery accuracy and low computational complexity. Greedy pursuit algorithms are difficult to apply directly to the MEG inverse problem because of the high-dimensional structure of the MEG source space and the high spatial correlation in MEG measurements. In this paper, we develop a novel greedy pursuit algorithm for sparse MEG source localization that overcomes these fundamental problems. This algorithm, which we refer to as the Subspace Pursuit-based Iterative Greedy Hierarchical (SPIGH) inverse solution, exhibits very low computational complexity while achieving very high localization accuracy. We evaluate the performance of the proposed algorithm using comprehensive simulations, as well as the analysis of human MEG data during spontaneous brain activity and somatosensory stimuli. These studies reveal substantial performance gains provided by the SPIGH algorithm in terms of computational complexity, localization accuracy, and robustness. PMID:24055554

Evaluation of the Horizontal and Vertical Accuracy of GNSS Survey Observations from a Real-Time Network

NASA Astrophysics Data System (ADS)

Allahyari, M.; Olsen, M. J.; Gillins, D. T.; Dennis, M. L.

2016-12-01

Many current surveying standards in the United States require several long-duration, static Global Navigation Satellite System (GNSS) observations to derive high-accuracy geodetic coordinates. However, over the past decade, many entities have established real-time GNSS networks (RTNs), which could reduce the field time for establishing geodetic control from hours to minutes. To evaluate the accuracy of RTN GNSS observations, data collected from two National Geodetic Survey (NGS) surveys in South Carolina and Oregon were studied. The objectives were to: 1) determine the accuracy of a real-time observation as a function of duration; 2) examine the influence of including GLONASS (Russia's version of GPS); 3) compare results using a single base to the full RTN network solution; and 4) assess the effect of baseline length on accuracy. In South Carolina, 360 observations ranging from 5 to 600 seconds were collected on 20 passive marks using RTN and single-base solutions, both with GPS+GLONASS and GPS-only. In Oregon, 18 passive marks were observed from 5 to 900 seconds using GPS-only with the RTN, and with GPS+GLONASS and GPS-only from a single-base. To develop "truth" coordinates, at least 30 hours of static GPS data were also collected on all marks. Each static survey session was post-processed in OPUS-Projects, and the resulting vectors were used to build survey networks that were least-squares adjusted using the NGS software ADJUST. The resulting coordinates provided the basis for evaluating the accuracy of the real-time observations. Results from this study indicate great potential in the use of RTNs for accurate derivation of geodetic coordinates. Both case studies showed an optimal observation duration of 180 seconds. RTN data tended to be more accurate and consistent than single-base data, and GLONASS slightly improved accuracy. A key benefit of GLONASS was the ability to obtain more fixed solutions at longer baseline lengths than single-base solutions.

A real-time freehand ultrasound calibration system with automatic accuracy feedback and control.

PubMed

Chen, Thomas Kuiran; Thurston, Adrian D; Ellis, Randy E; Abolmaesumi, Purang

2009-01-01

This article describes a fully automatic, real-time, freehand ultrasound calibration system. The system was designed to be simple and sterilizable, intended for operating-room usage. The calibration system employed an automatic-error-retrieval and accuracy-control mechanism based on a set of ground-truth data. Extensive validations were conducted on a data set of 10,000 images in 50 independent calibration trials to thoroughly investigate the accuracy, robustness, and performance of the calibration system. On average, the calibration accuracy (measured in three-dimensional reconstruction error against a known ground truth) of all 50 trials was 0.66 mm. In addition, the calibration errors converged to submillimeter in 98% of all trials within 12.5 s on average. Overall, the calibration system was able to consistently, efficiently and robustly achieve high calibration accuracy with real-time performance.

A Practical Torque Estimation Method for Interior Permanent Magnet Synchronous Machine in Electric Vehicles.

PubMed

Wu, Zhihong; Lu, Ke; Zhu, Yuan

2015-01-01

The torque output accuracy of the IPMSM in electric vehicles using a state of the art MTPA strategy highly depends on the accuracy of machine parameters, thus, a torque estimation method is necessary for the safety of the vehicle. In this paper, a torque estimation method based on flux estimator with a modified low pass filter is presented. Moreover, by taking into account the non-ideal characteristic of the inverter, the torque estimation accuracy is improved significantly. The effectiveness of the proposed method is demonstrated through MATLAB/Simulink simulation and experiment.

A Practical Torque Estimation Method for Interior Permanent Magnet Synchronous Machine in Electric Vehicles

PubMed Central

Zhu, Yuan

2015-01-01

The torque output accuracy of the IPMSM in electric vehicles using a state of the art MTPA strategy highly depends on the accuracy of machine parameters, thus, a torque estimation method is necessary for the safety of the vehicle. In this paper, a torque estimation method based on flux estimator with a modified low pass filter is presented. Moreover, by taking into account the non-ideal characteristic of the inverter, the torque estimation accuracy is improved significantly. The effectiveness of the proposed method is demonstrated through MATLAB/Simulink simulation and experiment. PMID:26114557

Application of Linear Discriminant Analysis in Dimensionality Reduction for Hand Motion Classification

NASA Astrophysics Data System (ADS)

Phinyomark, A.; Hu, H.; Phukpattaranont, P.; Limsakul, C.

2012-01-01

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high dimensionality, it is commonplace to apply a processing step that transforms the data to a space of significantly lower dimensions with only a limited loss of useful information. Linear discriminant analysis (LDA) has been successfully applied as an EMG feature projection method. Recently, a number of extended LDA-based algorithms have been proposed, which are more competitive in terms of both classification accuracy and computational costs/times with classical LDA. This paper presents the findings of a comparative study of classical LDA and five extended LDA methods. From a quantitative comparison based on seven multi-feature sets, three extended LDA-based algorithms, consisting of uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis, produce better class separability when compared with a baseline system (without feature projection), principle component analysis (PCA), and classical LDA. Based on a 7-dimension time domain and time-scale feature vectors, these methods achieved respectively 95.2% and 93.2% classification accuracy by using a linear discriminant classifier.

Integrated Georeferencing of Stereo Image Sequences Captured with a Stereovision Mobile Mapping System - Approaches and Practical Results

NASA Astrophysics Data System (ADS)

Eugster, H.; Huber, F.; Nebiker, S.; Gisi, A.

2012-07-01

Stereovision based mobile mapping systems enable the efficient capturing of directly georeferenced stereo pairs. With today's camera and onboard storage technologies imagery can be captured at high data rates resulting in dense stereo sequences. These georeferenced stereo sequences provide a highly detailed and accurate digital representation of the roadside environment which builds the foundation for a wide range of 3d mapping applications and image-based geo web-services. Georeferenced stereo images are ideally suited for the 3d mapping of street furniture and visible infrastructure objects, pavement inspection, asset management tasks or image based change detection. As in most mobile mapping systems, the georeferencing of the mapping sensors and observations - in our case of the imaging sensors - normally relies on direct georeferencing based on INS/GNSS navigation sensors. However, in urban canyons the achievable direct georeferencing accuracy of the dynamically captured stereo image sequences is often insufficient or at least degraded. Furthermore, many of the mentioned application scenarios require homogeneous georeferencing accuracy within a local reference frame over the entire mapping perimeter. To achieve these demands georeferencing approaches are presented and cost efficient workflows are discussed which allows validating and updating the INS/GNSS based trajectory with independently estimated positions in cases of prolonged GNSS signal outages in order to increase the georeferencing accuracy up to the project requirements.

A highly accurate symmetric optical flow based high-dimensional nonlinear spatial normalization of brain images.

PubMed

Wen, Ying; Hou, Lili; He, Lianghua; Peterson, Bradley S; Xu, Dongrong

2015-05-01

Spatial normalization plays a key role in voxel-based analyses of brain images. We propose a highly accurate algorithm for high-dimensional spatial normalization of brain images based on the technique of symmetric optical flow. We first construct a three dimension optical model with the consistency assumption of intensity and consistency of the gradient of intensity under a constraint of discontinuity-preserving spatio-temporal smoothness. Then, an efficient inverse consistency optical flow is proposed with aims of higher registration accuracy, where the flow is naturally symmetric. By employing a hierarchical strategy ranging from coarse to fine scales of resolution and a method of Euler-Lagrange numerical analysis, our algorithm is capable of registering brain images data. Experiments using both simulated and real datasets demonstrated that the accuracy of our algorithm is not only better than that of those traditional optical flow algorithms, but also comparable to other registration methods used extensively in the medical imaging community. Moreover, our registration algorithm is fully automated, requiring a very limited number of parameters and no manual intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

3D Higher Order Modeling in the BEM/FEM Hybrid Formulation

NASA Technical Reports Server (NTRS)

Fink, P. W.; Wilton, D. R.

2000-01-01

Higher order divergence- and curl-conforming bases have been shown to provide significant benefits, in both convergence rate and accuracy, in the 2D hybrid finite element/boundary element formulation (P. Fink and D. Wilton, National Radio Science Meeting, Boulder, CO, Jan. 2000). A critical issue in achieving the potential for accuracy of the approach is the accurate evaluation of all matrix elements. These involve products of high order polynomials and, in some instances, singular Green's functions. In the 2D formulation, the use of a generalized Gaussian quadrature method was found to greatly facilitate the computation and to improve the accuracy of the boundary integral equation self-terms. In this paper, a 3D, hybrid electric field formulation employing higher order bases and higher order elements is presented. The improvements in convergence rate and accuracy, compared to those resulting from lower order modeling, are established. Techniques developed to facilitate the computation of the boundary integral self-terms are also shown to improve the accuracy of these terms. Finally, simple preconditioning techniques are used in conjunction with iterative solution procedures to solve the resulting linear system efficiently. In order to handle the boundary integral singularities in the 3D formulation, the parent element- either a triangle or rectangle-is subdivided into a set of sub-triangles with a common vertex at the singularity. The contribution to the integral from each of the sub-triangles is computed using the Duffy transformation to remove the singularity. This method is shown to greatly facilitate t'pe self-term computation when the bases are of higher order. In addition, the sub-triangles can be further divided to achieve near arbitrary accuracy in the self-term computation. An efficient method for subdividing the parent element is presented. The accuracy obtained using higher order bases is compared to that obtained using lower order bases when the number of unknowns is approximately equal. Also, convergence rates obtained using higher order bases are compared to those obtained with lower order bases for selected sample

Multi-Autonomous Ground-robotic International Challenge (MAGIC) 2010

DTIC Science & Technology

2010-12-14

SLAM technique since this setup, having a LIDAR with long-range high-accuracy measurement capability, allows accurate localization and mapping more...achieve the accuracy of 25cm due to the use of multi-dimensional information. OGM is, similarly to SLAM , carried out by using LIDAR data. The OGM...a result of the development and implementation of the hybrid feature-based/scan-matching Simultaneous Localization and Mapping ( SLAM ) technique, the

Integrative Chemical-Biological Read-Across Approach for Chemical Hazard Classification

PubMed Central

Low, Yen; Sedykh, Alexander; Fourches, Denis; Golbraikh, Alexander; Whelan, Maurice; Rusyn, Ivan; Tropsha, Alexander

2013-01-01

Traditional read-across approaches typically rely on the chemical similarity principle to predict chemical toxicity; however, the accuracy of such predictions is often inadequate due to the underlying complex mechanisms of toxicity. Here we report on the development of a hazard classification and visualization method that draws upon both chemical structural similarity and comparisons of biological responses to chemicals measured in multiple short-term assays (”biological” similarity). The Chemical-Biological Read-Across (CBRA) approach infers each compound's toxicity from those of both chemical and biological analogs whose similarities are determined by the Tanimoto coefficient. Classification accuracy of CBRA was compared to that of classical RA and other methods using chemical descriptors alone, or in combination with biological data. Different types of adverse effects (hepatotoxicity, hepatocarcinogenicity, mutagenicity, and acute lethality) were classified using several biological data types (gene expression profiling and cytotoxicity screening). CBRA-based hazard classification exhibited consistently high external classification accuracy and applicability to diverse chemicals. Transparency of the CBRA approach is aided by the use of radial plots that show the relative contribution of analogous chemical and biological neighbors. Identification of both chemical and biological features that give rise to the high accuracy of CBRA-based toxicity prediction facilitates mechanistic interpretation of the models. PMID:23848138

Otitis Media Diagnosis for Developing Countries Using Tympanic Membrane Image-Analysis.

PubMed

Myburgh, Hermanus C; van Zijl, Willemien H; Swanepoel, DeWet; Hellström, Sten; Laurent, Claude

2016-03-01

Otitis media is one of the most common childhood diseases worldwide, but because of lack of doctors and health personnel in developing countries it is often misdiagnosed or not diagnosed at all. This may lead to serious, and life-threatening complications. There is, thus a need for an automated computer based image-analyzing system that could assist in making accurate otitis media diagnoses anywhere. A method for automated diagnosis of otitis media is proposed. The method uses image-processing techniques to classify otitis media. The system is trained using high quality pre-assessed images of tympanic membranes, captured by digital video-otoscopes, and classifies undiagnosed images into five otitis media categories based on predefined signs. Several verification tests analyzed the classification capability of the method. An accuracy of 80.6% was achieved for images taken with commercial video-otoscopes, while an accuracy of 78.7% was achieved for images captured on-site with a low cost custom-made video-otoscope. The high accuracy of the proposed otitis media classification system compares well with the classification accuracy of general practitioners and pediatricians (~64% to 80%) using traditional otoscopes, and therefore holds promise for the future in making automated diagnosis of otitis media in medically underserved populations.

Sensitivity and accuracy of high-throughput metabarcoding methods for early detection of invasive fish species

NASA Astrophysics Data System (ADS)

Hatzenbuhler, Chelsea; Kelly, John R.; Martinson, John; Okum, Sara; Pilgrim, Erik

2017-04-01

High-throughput DNA metabarcoding has gained recognition as a potentially powerful tool for biomonitoring, including early detection of aquatic invasive species (AIS). DNA based techniques are advancing, but our understanding of the limits to detection for metabarcoding complex samples is inadequate. For detecting AIS at an early stage of invasion when the species is rare, accuracy at low detection limits is key. To evaluate the utility of metabarcoding in future fish community monitoring programs, we conducted several experiments to determine the sensitivity and accuracy of routine metabarcoding methods. Experimental mixes used larval fish tissue from multiple “common” species spiked with varying proportions of tissue from an additional “rare” species. Pyrosequencing of genetic marker, COI (cytochrome c oxidase subunit I) and subsequent sequence data analysis provided experimental evidence of low-level detection of the target “rare” species at biomass percentages as low as 0.02% of total sample biomass. Limits to detection varied interspecifically and were susceptible to amplification bias. Moreover, results showed some data processing methods can skew sequence-based biodiversity measurements from corresponding relative biomass abundances and increase false absences. We suggest caution in interpreting presence/absence and relative abundance in larval fish assemblages until metabarcoding methods are optimized for accuracy and precision.

Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic.

PubMed

Wang, Ming; Long, Qi

2016-09-01

Prediction models for disease risk and prognosis play an important role in biomedical research, and evaluating their predictive accuracy in the presence of censored data is of substantial interest. The standard concordance (c) statistic has been extended to provide a summary measure of predictive accuracy for survival models. Motivated by a prostate cancer study, we address several issues associated with evaluating survival prediction models based on c-statistic with a focus on estimators using the technique of inverse probability of censoring weighting (IPCW). Compared to the existing work, we provide complete results on the asymptotic properties of the IPCW estimators under the assumption of coarsening at random (CAR), and propose a sensitivity analysis under the mechanism of noncoarsening at random (NCAR). In addition, we extend the IPCW approach as well as the sensitivity analysis to high-dimensional settings. The predictive accuracy of prediction models for cancer recurrence after prostatectomy is assessed by applying the proposed approaches. We find that the estimated predictive accuracy for the models in consideration is sensitive to NCAR assumption, and thus identify the best predictive model. Finally, we further evaluate the performance of the proposed methods in both settings of low-dimensional and high-dimensional data under CAR and NCAR through simulations. © 2016, The International Biometric Society.

Otitis Media Diagnosis for Developing Countries Using Tympanic Membrane Image-Analysis

PubMed Central

Myburgh, Hermanus C.; van Zijl, Willemien H.; Swanepoel, DeWet; Hellström, Sten; Laurent, Claude

2016-01-01

Background Otitis media is one of the most common childhood diseases worldwide, but because of lack of doctors and health personnel in developing countries it is often misdiagnosed or not diagnosed at all. This may lead to serious, and life-threatening complications. There is, thus a need for an automated computer based image-analyzing system that could assist in making accurate otitis media diagnoses anywhere. Methods A method for automated diagnosis of otitis media is proposed. The method uses image-processing techniques to classify otitis media. The system is trained using high quality pre-assessed images of tympanic membranes, captured by digital video-otoscopes, and classifies undiagnosed images into five otitis media categories based on predefined signs. Several verification tests analyzed the classification capability of the method. Findings An accuracy of 80.6% was achieved for images taken with commercial video-otoscopes, while an accuracy of 78.7% was achieved for images captured on-site with a low cost custom-made video-otoscope. Interpretation The high accuracy of the proposed otitis media classification system compares well with the classification accuracy of general practitioners and pediatricians (~ 64% to 80%) using traditional otoscopes, and therefore holds promise for the future in making automated diagnosis of otitis media in medically underserved populations. PMID:27077122

Experimental comparison of landmark-based methods for 3D elastic registration of pre- and postoperative liver CT data

NASA Astrophysics Data System (ADS)

Lange, Thomas; Wörz, Stefan; Rohr, Karl; Schlag, Peter M.

2009-02-01

The qualitative and quantitative comparison of pre- and postoperative image data is an important possibility to validate surgical procedures, in particular, if computer assisted planning and/or navigation is performed. Due to deformations after surgery, partially caused by the removal of tissue, a non-rigid registration scheme is a prerequisite for a precise comparison. Interactive landmark-based schemes are a suitable approach, if high accuracy and reliability is difficult to achieve by automatic registration approaches. Incorporation of a priori knowledge about the anatomical structures to be registered may help to reduce interaction time and improve accuracy. Concerning pre- and postoperative CT data of oncological liver resections the intrahepatic vessels are suitable anatomical structures. In addition to using branching landmarks for registration, we here introduce quasi landmarks at vessel segments with high localization precision perpendicular to the vessels and low precision along the vessels. A comparison of interpolating thin-plate splines (TPS), interpolating Gaussian elastic body splines (GEBS) and approximating GEBS on landmarks at vessel branchings as well as approximating GEBS on the introduced vessel segment landmarks is performed. It turns out that the segment landmarks provide registration accuracies as good as branching landmarks and can improve accuracy if combined with branching landmarks. For a low number of landmarks segment landmarks are even superior.

Motion-sensor fusion-based gesture recognition and its VLSI architecture design for mobile devices

NASA Astrophysics Data System (ADS)

Zhu, Wenping; Liu, Leibo; Yin, Shouyi; Hu, Siqi; Tang, Eugene Y.; Wei, Shaojun

2014-05-01

With the rapid proliferation of smartphones and tablets, various embedded sensors are incorporated into these platforms to enable multimodal human-computer interfaces. Gesture recognition, as an intuitive interaction approach, has been extensively explored in the mobile computing community. However, most gesture recognition implementations by now are all user-dependent and only rely on accelerometer. In order to achieve competitive accuracy, users are required to hold the devices in predefined manner during the operation. In this paper, a high-accuracy human gesture recognition system is proposed based on multiple motion sensor fusion. Furthermore, to reduce the energy overhead resulted from frequent sensor sampling and data processing, a high energy-efficient VLSI architecture implemented on a Xilinx Virtex-5 FPGA board is also proposed. Compared with the pure software implementation, approximately 45 times speed-up is achieved while operating at 20 MHz. The experiments show that the average accuracy for 10 gestures achieves 93.98% for user-independent case and 96.14% for user-dependent case when subjects hold the device randomly during completing the specified gestures. Although a few percent lower than the conventional best result, it still provides competitive accuracy acceptable for practical usage. Most importantly, the proposed system allows users to hold the device randomly during operating the predefined gestures, which substantially enhances the user experience.

Wavefront Sensing for WFIRST with a Linear Optical Model

NASA Technical Reports Server (NTRS)

Jurling, Alden S.; Content, David A.

2012-01-01

In this paper we develop methods to use a linear optical model to capture the field dependence of wavefront aberrations in a nonlinear optimization-based phase retrieval algorithm for image-based wavefront sensing. The linear optical model is generated from a ray trace model of the system and allows the system state to be described in terms of mechanical alignment parameters rather than wavefront coefficients. This approach allows joint optimization over images taken at different field points and does not require separate convergence of phase retrieval at individual field points. Because the algorithm exploits field diversity, multiple defocused images per field point are not required for robustness. Furthermore, because it is possible to simultaneously fit images of many stars over the field, it is not necessary to use a fixed defocus to achieve adequate signal-to-noise ratio despite having images with high dynamic range. This allows high performance wavefront sensing using in-focus science data. We applied this technique in a simulation model based on the Wide Field Infrared Survey Telescope (WFIRST) Intermediate Design Reference Mission (IDRM) imager using a linear optical model with 25 field points. We demonstrate sub-thousandth-wave wavefront sensing accuracy in the presence of noise and moderate undersampling for both monochromatic and polychromatic images using 25 high-SNR target stars. Using these high-quality wavefront sensing results, we are able to generate upsampled point-spread functions (PSFs) and use them to determine PSF ellipticity to high accuracy in order to reduce the systematic impact of aberrations on the accuracy of galactic ellipticity determination for weak-lensing science.

Brain-Computer Interface Based on Generation of Visual Images

PubMed Central

Bobrov, Pavel; Frolov, Alexander; Cantor, Charles; Fedulova, Irina; Bakhnyan, Mikhail; Zhavoronkov, Alexander

2011-01-01

This paper examines the task of recognizing EEG patterns that correspond to performing three mental tasks: relaxation and imagining of two types of pictures: faces and houses. The experiments were performed using two EEG headsets: BrainProducts ActiCap and Emotiv EPOC. The Emotiv headset becomes widely used in consumer BCI application allowing for conducting large-scale EEG experiments in the future. Since classification accuracy significantly exceeded the level of random classification during the first three days of the experiment with EPOC headset, a control experiment was performed on the fourth day using ActiCap. The control experiment has shown that utilization of high-quality research equipment can enhance classification accuracy (up to 68% in some subjects) and that the accuracy is independent of the presence of EEG artifacts related to blinking and eye movement. This study also shows that computationally-inexpensive Bayesian classifier based on covariance matrix analysis yields similar classification accuracy in this problem as a more sophisticated Multi-class Common Spatial Patterns (MCSP) classifier. PMID:21695206

Distributed wavefront reconstruction with SABRE for real-time large scale adaptive optics control

NASA Astrophysics Data System (ADS)

Brunner, Elisabeth; de Visser, Cornelis C.; Verhaegen, Michel

2014-08-01

We present advances on Spline based ABerration REconstruction (SABRE) from (Shack-)Hartmann (SH) wavefront measurements for large-scale adaptive optics systems. SABRE locally models the wavefront with simplex B-spline basis functions on triangular partitions which are defined on the SH subaperture array. This approach allows high accuracy through the possible use of nonlinear basis functions and great adaptability to any wavefront sensor and pupil geometry. The main contribution of this paper is a distributed wavefront reconstruction method, D-SABRE, which is a 2 stage procedure based on decomposing the sensor domain into sub-domains each supporting a local SABRE model. D-SABRE greatly decreases the computational complexity of the method and removes the need for centralized reconstruction while obtaining a reconstruction accuracy for simulated E-ELT turbulences within 1% of the global method's accuracy. Further, a generalization of the methodology is proposed making direct use of SH intensity measurements which leads to an improved accuracy of the reconstruction compared to centroid algorithms using spatial gradients.

Spatial Classification of Orchards and Vineyards with High Spatial Resolution Panchromatic Imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warner, Timothy; Steinmaus, Karen L.

2005-02-01

New high resolution single spectral band imagery offers the capability to conduct image classifications based on spatial patterns in imagery. A classification algorithm based on autocorrelation patterns was developed to automatically extract orchards and vineyards from satellite imagery. The algorithm was tested on IKONOS imagery over Granger, WA, which resulted in a classification accuracy of 95%.

The large discretization step method for time-dependent partial differential equations

NASA Technical Reports Server (NTRS)

Haras, Zigo; Taasan, Shlomo

1995-01-01

A new method for the acceleration of linear and nonlinear time dependent calculations is presented. It is based on the Large Discretization Step (LDS) approximation, defined in this work, which employs an extended system of low accuracy schemes to approximate a high accuracy discrete approximation to a time dependent differential operator. Error bounds on such approximations are derived. These approximations are efficiently implemented in the LDS methods for linear and nonlinear hyperbolic equations, presented here. In these algorithms the high and low accuracy schemes are interpreted as the same discretization of a time dependent operator on fine and coarse grids, respectively. Thus, a system of correction terms and corresponding equations are derived and solved on the coarse grid to yield the fine grid accuracy. These terms are initialized by visiting the fine grid once in many coarse grid time steps. The resulting methods are very general, simple to implement and may be used to accelerate many existing time marching schemes.

Revisiting the Least-squares Procedure for Gradient Reconstruction on Unstructured Meshes

NASA Technical Reports Server (NTRS)

Mavriplis, Dimitri J.; Thomas, James L. (Technical Monitor)

2003-01-01

The accuracy of the least-squares technique for gradient reconstruction on unstructured meshes is examined. While least-squares techniques produce accurate results on arbitrary isotropic unstructured meshes, serious difficulties exist for highly stretched meshes in the presence of surface curvature. In these situations, gradients are typically under-estimated by up to an order of magnitude. For vertex-based discretizations on triangular and quadrilateral meshes, and cell-centered discretizations on quadrilateral meshes, accuracy can be recovered using an inverse distance weighting in the least-squares construction. For cell-centered discretizations on triangles, both the unweighted and weighted least-squares constructions fail to provide suitable gradient estimates for highly stretched curved meshes. Good overall flow solution accuracy can be retained in spite of poor gradient estimates, due to the presence of flow alignment in exactly the same regions where the poor gradient accuracy is observed. However, the use of entropy fixes has the potential for generating large but subtle discretization errors.

Precision measurement of refractive index of air based on laser synthetic wavelength interferometry with Edlén equation estimation.

PubMed

Yan, Liping; Chen, Benyong; Zhang, Enzheng; Zhang, Shihua; Yang, Ye

2015-08-01

A novel method for the precision measurement of refractive index of air (n(air)) based on the combining of the laser synthetic wavelength interferometry with the Edlén equation estimation is proposed. First, a n(air_e) is calculated from the modified Edlén equation according to environmental parameters measured by low precision sensors with an uncertainty of 10(-6). Second, a unique integral fringe number N corresponding to n(air) is determined based on the calculated n(air_e). Then, a fractional fringe ε corresponding to n(air) with high accuracy can be obtained according to the principle of fringe subdivision of laser synthetic wavelength interferometry. Finally, high accurate measurement of n(air) is achieved according to the determined fringes N and ε. The merit of the proposed method is that it not only solves the problem of the measurement accuracy of n(air) being limited by the accuracies of environmental sensors, but also avoids adopting complicated vacuum pumping to measure the integral fringe N in the method of conventional laser interferometry. To verify the feasibility of the proposed method, comparison experiments with Edlén equations in short time and in long time were performed. Experimental results show that the measurement accuracy of n(air) is better than 2.5 × 10(-8) in short time tests and 6.2 × 10(-8) in long time tests.

Towards equation of state of dark energy from quasar monitoring: Reverberation strategy

NASA Astrophysics Data System (ADS)

Czerny, B.; Hryniewicz, K.; Maity, I.; Schwarzenberg-Czerny, A.; Życki, P. T.; Bilicki, M.

2013-08-01

Context. High-redshift quasars can be used to constrain the equation of state of dark energy. They can serve as a complementary tool to supernovae Type Ia, especially at z > 1. Aims: The method is based on the determination of the size of the broad line region (BLR) from the emission line delay, the determination of the absolute monochromatic luminosity either from the observed statistical relation or from a model of the formation of the BLR, and the determination of the observed monochromatic flux from photometry. This allows the luminosity distance to a quasar to be obtained, independently from its redshift. The accuracy of the measurements is, however, a key issue. Methods: We modeled the expected accuracy of the measurements by creating artificial quasar monochromatic lightcurves and responses from the BLR under various assumptions about the variability of a quasar, BLR extension, distribution of the measurements in time, accuracy of the measurements, and the intrinsic line variability. Results: We show that the five-year monitoring of a single quasar based on the Mg II line should give an accuracy of 0.06-0.32 mag in the distance modulus which will allow new constraints to be put on the expansion rate of the Universe at high redshifts. Successful monitoring of higher redshift quasars based on C IV lines requires proper selection of the objects to avoid sources with much higher levels of the intrinsic variability of C IV compared to Mg II.

Accuracy assessment for a multi-parameter optical calliper in on line automotive applications

NASA Astrophysics Data System (ADS)

D'Emilia, G.; Di Gasbarro, D.; Gaspari, A.; Natale, E.

2017-08-01

In this work, a methodological approach based on the evaluation of the measurement uncertainty is applied to an experimental test case, related to the automotive sector. The uncertainty model for different measurement procedures of a high-accuracy optical gauge is discussed in order to individuate the best measuring performances of the system for on-line applications and when the measurement requirements are becoming more stringent. In particular, with reference to the industrial production and control strategies of high-performing turbochargers, two uncertainty models are proposed, discussed and compared, to be used by the optical calliper. Models are based on an integrated approach between measurement methods and production best practices to emphasize their mutual coherence. The paper shows the possible advantages deriving from the considerations that the measurement uncertainty modelling provides, in order to keep control of the uncertainty propagation on all the indirect measurements useful for production statistical control, on which basing further improvements.

Portable smartphone based quantitative phase microscope

NASA Astrophysics Data System (ADS)

Meng, Xin; Tian, Xiaolin; Yu, Wei; Kong, Yan; Jiang, Zhilong; Liu, Fei; Xue, Liang; Liu, Cheng; Wang, Shouyu

2018-01-01

To realize portable device with high contrast imaging capability, we designed a quantitative phase microscope using transport of intensity equation method based on a smartphone. The whole system employs an objective and an eyepiece as imaging system and a cost-effective LED as illumination source. A 3-D printed cradle is used to align these components. Images of different focal planes are captured by manual focusing, followed by calculation of sample phase via a self-developed Android application. To validate its accuracy, we first tested the device by measuring a random phase plate with known phases, and then red blood cell smear, Pap smear, broad bean epidermis sections and monocot root were also measured to show its performance. Owing to its advantages as accuracy, high-contrast, cost-effective and portability, the portable smartphone based quantitative phase microscope is a promising tool which can be future adopted in remote healthcare and medical diagnosis.

Accuracy and Calibration of High Explosive Thermodynamic Equations of State

NASA Astrophysics Data System (ADS)

Baker, Ernest L.; Capellos, Christos; Stiel, Leonard I.; Pincay, Jack

2010-10-01

The Jones-Wilkins-Lee-Baker (JWLB) equation of state (EOS) was developed to more accurately describe overdriven detonation while maintaining an accurate description of high explosive products expansion work output. The increased mathematical complexity of the JWLB high explosive equations of state provides increased accuracy for practical problems of interest. Increased numbers of parameters are often justified based on improved physics descriptions but can also mean increased calibration complexity. A generalized extent of aluminum reaction Jones-Wilkins-Lee (JWL)-based EOS was developed in order to more accurately describe the observed behavior of aluminized explosives detonation products expansion. A calibration method was developed to describe the unreacted, partially reacted, and completely reacted explosive using nonlinear optimization. A reasonable calibration of a generalized extent of aluminum reaction JWLB EOS as a function of aluminum reaction fraction has not yet been achieved due to the increased mathematical complexity of the JWLB form.

[An optical-fiber-sensor-based spectrophotometer for soil non-metallic nutrient determination].

PubMed

He, Dong-xian; Hu, Juan-xiu; Lu, Shao-kun; He, Hou-yong

2012-01-01

In order to achieve rapid, convenient and efficient soil nutrient determination in soil testing and fertilizer recommendation, a portable optical-fiber-sensor-based spectrophotometer including immersed fiber sensor, flat field holographic concave grating, and diode array detector was developed for soil non-metallic nutrient determination. According to national standard of ultraviolet and visible spectrophotometer with JJG 178-2007, the wavelength accuracy and repeatability, baseline stability, transmittance accuracy and repeatability measured by the prototype instrument were satisfied with the national standard of III level; minimum spectral bandwidth, noise and excursion, and stray light were satisfied with the national standard of IV level. Significant linear relationships with slope of closing to 1 were found between the soil available nutrient contents including soil nitrate nitrogen, ammonia nitrogen, available phosphorus, available sulfur, available boron, and organic matter measured by the prototype instrument compared with that measured by two commercial single-beam-based and dual-beam-based spectrophotometers. No significant differences were revealed from the above comparison data. Therefore, the optical-fiber-sensor-based spectrophotometer can be used for rapid soil non-metallic nutrient determination with a high accuracy.

High resolution microendoscopy for classification of colorectal polyps.

PubMed

Chang, S S; Shukla, R; Polydorides, A D; Vila, P M; Lee, M; Han, H; Kedia, P; Lewis, J; Gonzalez, S; Kim, M K; Harpaz, N; Godbold, J; Richards-Kortum, R; Anandasabapathy, S

2013-07-01

It can be difficult to distinguish adenomas from benign polyps during routine colonoscopy. High resolution microendoscopy (HRME) is a novel method for imaging colorectal mucosa with subcellular detail. HRME criteria for the classification of colorectal neoplasia have not been previously described. Study goals were to develop criteria to characterize HRME images of colorectal mucosa (normal, hyperplastic polyps, adenomas, cancer) and to determine the accuracy and interobserver variability for the discrimination of neoplastic from non-neoplastic polyps when these criteria were applied by novice and expert microendoscopists. Two expert pathologists created consensus HRME image criteria using images from 68 patients with polyps who had undergone colonoscopy plus HRME. Using these criteria, HRME expert and novice microendoscopists were shown a set of training images and then tested to determine accuracy and interobserver variability. Expert microendoscopists identified neoplasia with sensitivity, specificity, and accuracy of 67 % (95 % confidence interval [CI] 58 % - 75 %), 97 % (94 % - 100 %), and 87 %, respectively. Nonexperts achieved sensitivity, specificity, and accuracy of 73 % (66 % - 80 %), 91 % (80 % - 100 %), and 85 %, respectively. Overall, neoplasia were identified with sensitivity 70 % (65 % - 76 %), specificity 94 % (87 % - 100 %), and accuracy 85 %. Kappa values were: experts 0.86; nonexperts 0.72; and overall 0.78. Using the new criteria, observers achieved high specificity and substantial interobserver agreement for distinguishing benign polyps from neoplasia. Increased expertise in HRME imaging improves accuracy. This low-cost microendoscopic platform may be an alternative to confocal microendoscopy in lower-resource or community-based settings.

Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP

NASA Astrophysics Data System (ADS)

Jain, Sankalp; Grandits, Melanie; Richter, Lars; Ecker, Gerhard F.

2017-06-01

The bile salt export pump (BSEP) actively transports conjugated monovalent bile acids from the hepatocytes into the bile. This facilitates the formation of micelles and promotes digestion and absorption of dietary fat. Inhibition of BSEP leads to decreased bile flow and accumulation of cytotoxic bile salts in the liver. A number of compounds have been identified to interact with BSEP, which results in drug-induced cholestasis or liver injury. Therefore, in silico approaches for flagging compounds as potential BSEP inhibitors would be of high value in the early stage of the drug discovery pipeline. Up to now, due to the lack of a high-resolution X-ray structure of BSEP, in silico based identification of BSEP inhibitors focused on ligand-based approaches. In this study, we provide a homology model for BSEP, developed using the corrected mouse P-glycoprotein structure (PDB ID: 4M1M). Subsequently, the model was used for docking-based classification of a set of 1212 compounds (405 BSEP inhibitors, 807 non-inhibitors). Using the scoring function ChemScore, a prediction accuracy of 81% on the training set and 73% on two external test sets could be obtained. In addition, the applicability domain of the models was assessed based on Euclidean distance. Further, analysis of the protein-ligand interaction fingerprints revealed certain functional group-amino acid residue interactions that could play a key role for ligand binding. Though ligand-based models, due to their high speed and accuracy, remain the method of choice for classification of BSEP inhibitors, structure-assisted docking models demonstrate reasonably good prediction accuracies while additionally providing information about putative protein-ligand interactions.

Coarse-to-fine markerless gait analysis based on PCA and Gauss-Laguerre decomposition

NASA Astrophysics Data System (ADS)

Goffredo, Michela; Schmid, Maurizio; Conforto, Silvia; Carli, Marco; Neri, Alessandro; D'Alessio, Tommaso

2005-04-01

Human movement analysis is generally performed through the utilization of marker-based systems, which allow reconstructing, with high levels of accuracy, the trajectories of markers allocated on specific points of the human body. Marker based systems, however, show some drawbacks that can be overcome by the use of video systems applying markerless techniques. In this paper, a specifically designed computer vision technique for the detection and tracking of relevant body points is presented. It is based on the Gauss-Laguerre Decomposition, and a Principal Component Analysis Technique (PCA) is used to circumscribe the region of interest. Results obtained on both synthetic and experimental tests provide significant reduction of the computational costs, with no significant reduction of the tracking accuracy.

High temperature current mirror amplifier

DOEpatents

Patterson, III, Raymond B.

1984-05-22

A high temperature current mirror amplifier having biasing means in the transdiode connection of the input transistor for producing a voltage to maintain the base-collector junction reversed-biased and a current means for maintaining a current through the biasing means at high temperatures so that the base-collector junction of the input transistor remained reversed-biased. For accuracy, a second current mirror is provided with a biasing means and current means on the input leg.

The Utility and Validity of Kinematic GPS Positioning for the Geosar Airborne Terrain Mapping Radar System

NASA Technical Reports Server (NTRS)

Freedman, Adam; Hensley, Scott; Chapin, Elaine; Kroger, Peter; Hussain, Mushtaq; Allred, Bruce

1999-01-01

GeoSAR is an airborne, interferometric Synthetic Aperture Radar (IFSAR) system for terrain mapping, currently under development by a consortium including NASA's Jet Propulsion Laboratory (JPL), Calgis, Inc., a California mapping sciences company, and the California Department of Conservation (CaIDOC), with funding provided by the U.S. Army Corps of Engineers Topographic Engineering Center (TEC) and the U.S. Defense Advanced Research Projects Agency (DARPA). IFSAR data processing requires high-accuracy platform position and attitude knowledge. On 9 GeoSAR, these are provided by one or two Honeywell Embedded GPS Inertial Navigation Units (EGI) and an Ashtech Z12 GPS receiver. The EGIs provide real-time high-accuracy attitude and moderate-accuracy position data, while the Ashtech data, post-processed differentially with data from a nearby ground station using Ashtech PNAV software, provide high-accuracy differential GPS positions. These data are optimally combined using a Kalman filter within the GeoSAR motion measurement software, and the resultant position and orientation information are used to process the dual frequency (X-band and P-band) radar data to generate high-accuracy, high -resolution terrain imagery and digital elevation models (DEMs). GeoSAR requirements specify sub-meter level planimetric and vertical accuracies for the resultant DEMS. To achieve this, platform positioning errors well below one meter are needed. The goal of GeoSAR is to obtain 25 cm or better 3-D positions from the GPS systems on board the aircraft. By imaging a set of known point target corner-cube reflectors, the GeoSAR system can be calibrated. This calibration process yields the true position of the aircraft with an uncertainty of 20- 50 cm. This process thus allows an independent assessment of the accuracy of our GPS-based positioning systems. We will present an overview of the GeoSAR motion measurement system, focusing on the use of GPS and the blending of position data from the various systems. We will present the results of our calibration studies that relate to the accuracy the GPS positioning. We will discuss the effects these positioning, errors have on the resultant DEM products and imagery.

Regression Analysis of Optical Coherence Tomography Disc Variables for Glaucoma Diagnosis.

PubMed

Richter, Grace M; Zhang, Xinbo; Tan, Ou; Francis, Brian A; Chopra, Vikas; Greenfield, David S; Varma, Rohit; Schuman, Joel S; Huang, David

2016-08-01

To report diagnostic accuracy of optical coherence tomography (OCT) disc variables using both time-domain (TD) and Fourier-domain (FD) OCT, and to improve the use of OCT disc variable measurements for glaucoma diagnosis through regression analyses that adjust for optic disc size and axial length-based magnification error. Observational, cross-sectional. In total, 180 normal eyes of 112 participants and 180 eyes of 138 participants with perimetric glaucoma from the Advanced Imaging for Glaucoma Study. Diagnostic variables evaluated from TD-OCT and FD-OCT were: disc area, rim area, rim volume, optic nerve head volume, vertical cup-to-disc ratio (CDR), and horizontal CDR. These were compared with overall retinal nerve fiber layer thickness and ganglion cell complex. Regression analyses were performed that corrected for optic disc size and axial length. Area-under-receiver-operating curves (AUROC) were used to assess diagnostic accuracy before and after the adjustments. An index based on multiple logistic regression that combined optic disc variables with axial length was also explored with the aim of improving diagnostic accuracy of disc variables. Comparison of diagnostic accuracy of disc variables, as measured by AUROC. The unadjusted disc variables with the highest diagnostic accuracies were: rim volume for TD-OCT (AUROC=0.864) and vertical CDR (AUROC=0.874) for FD-OCT. Magnification correction significantly worsened diagnostic accuracy for rim variables, and while optic disc size adjustments partially restored diagnostic accuracy, the adjusted AUROCs were still lower. Axial length adjustments to disc variables in the form of multiple logistic regression indices led to a slight but insignificant improvement in diagnostic accuracy. Our various regression approaches were not able to significantly improve disc-based OCT glaucoma diagnosis. However, disc rim area and vertical CDR had very high diagnostic accuracy, and these disc variables can serve to complement additional OCT measurements for diagnosis of glaucoma.

Pairagon: a highly accurate, HMM-based cDNA-to-genome aligner.

PubMed

Lu, David V; Brown, Randall H; Arumugam, Manimozhiyan; Brent, Michael R

2009-07-01

The most accurate way to determine the intron-exon structures in a genome is to align spliced cDNA sequences to the genome. Thus, cDNA-to-genome alignment programs are a key component of most annotation pipelines. The scoring system used to choose the best alignment is a primary determinant of alignment accuracy, while heuristics that prevent consideration of certain alignments are a primary determinant of runtime and memory usage. Both accuracy and speed are important considerations in choosing an alignment algorithm, but scoring systems have received much less attention than heuristics. We present Pairagon, a pair hidden Markov model based cDNA-to-genome alignment program, as the most accurate aligner for sequences with high- and low-identity levels. We conducted a series of experiments testing alignment accuracy with varying sequence identity. We first created 'perfect' simulated cDNA sequences by splicing the sequences of exons in the reference genome sequences of fly and human. The complete reference genome sequences were then mutated to various degrees using a realistic mutation simulator and the perfect cDNAs were aligned to them using Pairagon and 12 other aligners. To validate these results with natural sequences, we performed cross-species alignment using orthologous transcripts from human, mouse and rat. We found that aligner accuracy is heavily dependent on sequence identity. For sequences with 100% identity, Pairagon achieved accuracy levels of >99.6%, with one quarter of the errors of any other aligner. Furthermore, for human/mouse alignments, which are only 85% identical, Pairagon achieved 87% accuracy, higher than any other aligner. Pairagon source and executables are freely available at http://mblab.wustl.edu/software/pairagon/

An energy efficient and high speed architecture for convolution computing based on binary resistive random access memory

NASA Astrophysics Data System (ADS)

Liu, Chen; Han, Runze; Zhou, Zheng; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng

2018-04-01

In this work we present a novel convolution computing architecture based on metal oxide resistive random access memory (RRAM) to process the image data stored in the RRAM arrays. The proposed image storage architecture shows performances of better speed-device consumption efficiency compared with the previous kernel storage architecture. Further we improve the architecture for a high accuracy and low power computing by utilizing the binary storage and the series resistor. For a 28 × 28 image and 10 kernels with a size of 3 × 3, compared with the previous kernel storage approach, the newly proposed architecture shows excellent performances including: 1) almost 100% accuracy within 20% LRS variation and 90% HRS variation; 2) more than 67 times speed boost; 3) 71.4% energy saving.

Efficient airport detection using region-based fully convolutional neural networks

NASA Astrophysics Data System (ADS)

Xin, Peng; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Lv, Chao

2018-04-01

This paper presents a model for airport detection using region-based fully convolutional neural networks. To achieve fast detection with high accuracy, we shared the conv layers between the region proposal procedure and the airport detection procedure and used graphics processing units (GPUs) to speed up the training and testing time. For lack of labeled data, we transferred the convolutional layers of ZF net pretrained by ImageNet to initialize the shared convolutional layers, then we retrained the model using the alternating optimization training strategy. The proposed model has been tested on an airport dataset consisting of 600 images. Experiments show that the proposed method can distinguish airports in our dataset from similar background scenes almost real-time with high accuracy, which is much better than traditional methods.

Accuracy and Reliability of Emergency Department Triage Using the Emergency Severity Index: An International Multicenter Assessment.

PubMed

Mistry, Binoy; Stewart De Ramirez, Sarah; Kelen, Gabor; Schmitz, Paulo S K; Balhara, Kamna S; Levin, Scott; Martinez, Diego; Psoter, Kevin; Anton, Xavier; Hinson, Jeremiah S

2018-05-01

We assess accuracy and variability of triage score assignment by emergency department (ED) nurses using the Emergency Severity Index (ESI) in 3 countries. In accordance with previous reports and clinical observation, we hypothesize low accuracy and high variability across all sites. This cross-sectional multicenter study enrolled 87 ESI-trained nurses from EDs in Brazil, the United Arab Emirates, and the United States. Standardized triage scenarios published by the Agency for Healthcare Research and Quality (AHRQ) were used. Accuracy was defined by concordance with the AHRQ key and calculated as percentages. Accuracy comparisons were made with one-way ANOVA and paired t test. Interrater reliability was measured with Krippendorff's α. Subanalyses based on nursing experience and triage scenario type were also performed. Mean accuracy pooled across all sites and scenarios was 59.2% (95% confidence interval [CI] 56.4% to 62.0%) and interrater reliability was modest (α=.730; 95% CI .692 to .767). There was no difference in overall accuracy between sites or according to nurse experience. Medium-acuity scenarios were scored with greater accuracy (76.4%; 95% CI 72.6% to 80.3%) than high- or low-acuity cases (44.1%, 95% CI 39.3% to 49.0% and 54%, 95% CI 49.9% to 58.2%), and adult scenarios were scored with greater accuracy than pediatric ones (66.2%, 95% CI 62.9% to 69.7% versus 46.9%, 95% CI 43.4% to 50.3%). In this multinational study, concordance of nurse-assigned ESI score with reference standard was universally poor and variability was high. Although the ESI is the most popular ED triage tool in the United States and is increasingly used worldwide, our findings point to a need for more reliable ED triage tools. Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Grid refinement in Cartesian coordinates for groundwater flow models using the divergence theorem and Taylor's series.

PubMed

Mansour, M M; Spink, A E F

2013-01-01

Grid refinement is introduced in a numerical groundwater model to increase the accuracy of the solution over local areas without compromising the run time of the model. Numerical methods developed for grid refinement suffered certain drawbacks, for example, deficiencies in the implemented interpolation technique; the non-reciprocity in head calculations or flow calculations; lack of accuracy resulting from high truncation errors, and numerical problems resulting from the construction of elongated meshes. A refinement scheme based on the divergence theorem and Taylor's expansions is presented in this article. This scheme is based on the work of De Marsily (1986) but includes more terms of the Taylor's series to improve the numerical solution. In this scheme, flow reciprocity is maintained and high order of refinement was achievable. The new numerical method is applied to simulate groundwater flows in homogeneous and heterogeneous confined aquifers. It produced results with acceptable degrees of accuracy. This method shows the potential for its application to solving groundwater heads over nested meshes with irregular shapes. © 2012, British Geological Survey © NERC 2012. Ground Water © 2012, National GroundWater Association.

Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

NASA Astrophysics Data System (ADS)

Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

2010-02-01

Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

A Low Complexity System Based on Multiple Weighted Decision Trees for Indoor Localization

PubMed Central

Sánchez-Rodríguez, David; Hernández-Morera, Pablo; Quinteiro, José Ma.; Alonso-González, Itziar

2015-01-01

Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity. The localization system is built using a dataset from sensor fusion, which combines the strength of radio signals from different wireless local area network access points and device orientation information from a digital compass built-in mobile device, so that extra sensors are unnecessary. Experimental results indicate that the proposed system leads to substantial improvements on computational complexity over the widely-used traditional fingerprinting methods, and it has a better accuracy than they have. PMID:26110413

hp-Adaptive time integration based on the BDF for viscous flows

NASA Astrophysics Data System (ADS)

Hay, A.; Etienne, S.; Pelletier, D.; Garon, A.

2015-06-01

This paper presents a procedure based on the Backward Differentiation Formulas of order 1 to 5 to obtain efficient time integration of the incompressible Navier-Stokes equations. The adaptive algorithm performs both stepsize and order selections to control respectively the solution accuracy and the computational efficiency of the time integration process. The stepsize selection (h-adaptivity) is based on a local error estimate and an error controller to guarantee that the numerical solution accuracy is within a user prescribed tolerance. The order selection (p-adaptivity) relies on the idea that low-accuracy solutions can be computed efficiently by low order time integrators while accurate solutions require high order time integrators to keep computational time low. The selection is based on a stability test that detects growing numerical noise and deems a method of order p stable if there is no method of lower order that delivers the same solution accuracy for a larger stepsize. Hence, it guarantees both that (1) the used method of integration operates inside of its stability region and (2) the time integration procedure is computationally efficient. The proposed time integration procedure also features a time-step rejection and quarantine mechanisms, a modified Newton method with a predictor and dense output techniques to compute solution at off-step points.

Cryo-EM image alignment based on nonuniform fast Fourier transform.

PubMed

Yang, Zhengfan; Penczek, Pawel A

2008-08-01

In single particle analysis, two-dimensional (2-D) alignment is a fundamental step intended to put into register various particle projections of biological macromolecules collected at the electron microscope. The efficiency and quality of three-dimensional (3-D) structure reconstruction largely depends on the computational speed and alignment accuracy of this crucial step. In order to improve the performance of alignment, we introduce a new method that takes advantage of the highly accurate interpolation scheme based on the gridding method, a version of the nonuniform fast Fourier transform, and utilizes a multi-dimensional optimization algorithm for the refinement of the orientation parameters. Using simulated data, we demonstrate that by using less than half of the sample points and taking twice the runtime, our new 2-D alignment method achieves dramatically better alignment accuracy than that based on quadratic interpolation. We also apply our method to image to volume registration, the key step in the single particle EM structure refinement protocol. We find that in this case the accuracy of the method not only surpasses the accuracy of the commonly used real-space implementation, but results are achieved in much shorter time, making gridding-based alignment a perfect candidate for efficient structure determination in single particle analysis.

Cryo-EM Image Alignment Based on Nonuniform Fast Fourier Transform

PubMed Central

Yang, Zhengfan; Penczek, Pawel A.

2008-01-01

In single particle analysis, two-dimensional (2-D) alignment is a fundamental step intended to put into register various particle projections of biological macromolecules collected at the electron microscope. The efficiency and quality of three-dimensional (3-D) structure reconstruction largely depends on the computational speed and alignment accuracy of this crucial step. In order to improve the performance of alignment, we introduce a new method that takes advantage of the highly accurate interpolation scheme based on the gridding method, a version of the nonuniform Fast Fourier Transform, and utilizes a multi-dimensional optimization algorithm for the refinement of the orientation parameters. Using simulated data, we demonstrate that by using less than half of the sample points and taking twice the runtime, our new 2-D alignment method achieves dramatically better alignment accuracy than that based on quadratic interpolation. We also apply our method to image to volume registration, the key step in the single particle EM structure refinement protocol. We find that in this case the accuracy of the method not only surpasses the accuracy of the commonly used real-space implementation, but results are achieved in much shorter time, making gridding-based alignment a perfect candidate for efficient structure determination in single particle analysis. PMID:18499351

A Very High Order, Adaptable MESA Implementation for Aeroacoustic Computations

NASA Technical Reports Server (NTRS)

Dydson, Roger W.; Goodrich, John W.

2000-01-01

Since computational efficiency and wave resolution scale with accuracy, the ideal would be infinitely high accuracy for problems with widely varying wavelength scales. Currently, many of the computational aeroacoustics methods are limited to 4th order accurate Runge-Kutta methods in time which limits their resolution and efficiency. However, a new procedure for implementing the Modified Expansion Solution Approximation (MESA) schemes, based upon Hermitian divided differences, is presented which extends the effective accuracy of the MESA schemes to 57th order in space and time when using 128 bit floating point precision. This new approach has the advantages of reducing round-off error, being easy to program. and is more computationally efficient when compared to previous approaches. Its accuracy is limited only by the floating point hardware. The advantages of this new approach are demonstrated by solving the linearized Euler equations in an open bi-periodic domain. A 500th order MESA scheme can now be created in seconds, making these schemes ideally suited for the next generation of high performance 256-bit (double quadruple) or higher precision computers. This ease of creation makes it possible to adapt the algorithm to the mesh in time instead of its converse: this is ideal for resolving varying wavelength scales which occur in noise generation simulations. And finally, the sources of round-off error which effect the very high order methods are examined and remedies provided that effectively increase the accuracy of the MESA schemes while using current computer technology.

SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes.

PubMed

Pruesse, Elmar; Peplies, Jörg; Glöckner, Frank Oliver

2012-07-15

In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements. In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. Alignment of up to 500 sequences using the latest SILVA SSU/LSU Ref datasets as reference MSA is offered at http://www.arb-silva.de/aligner. This page also links to Linux binaries, user manual and tutorial. SINA is made available under a personal use license.

Carrier-phase multipath corrections for GPS-based satellite attitude determination

NASA Technical Reports Server (NTRS)

Axelrad, A.; Reichert, P.

2001-01-01

This paper demonstrates the high degree of spatial repeatability of these errors for a spacecraft environment and describes a correction technique, termed the sky map method, which exploits the spatial correlation to correct measurements and improve the accuracy of GPS-based attitude solutions.

Exploring Proficiency-Based vs. Performance-Based Items with Elicited Imitation Assessment

ERIC Educational Resources Information Center

Cox, Troy L.; Bown, Jennifer; Burdis, Jacob

2015-01-01

This study investigates the effect of proficiency- vs. performance-based elicited imitation (EI) assessment. EI requires test-takers to repeat sentences in the target language. The accuracy at which test-takers are able to repeat sentences highly correlates with test-takers' language proficiency. However, in EI, the factors that render an item…

Research on light rail electric load forecasting based on ARMA model

NASA Astrophysics Data System (ADS)

Huang, Yifan

2018-04-01

The article compares a variety of time series models and combines the characteristics of power load forecasting. Then, a light load forecasting model based on ARMA model is established. Based on this model, a light rail system is forecasted. The prediction results show that the accuracy of the model prediction is high.

Improved spring model-based collaborative indoor visible light positioning

NASA Astrophysics Data System (ADS)

Luo, Zhijie; Zhang, WeiNan; Zhou, GuoFu

2016-06-01

Gaining accuracy with indoor positioning of individuals is important as many location-based services rely on the user's current position to provide them with useful services. Many researchers have studied indoor positioning techniques based on WiFi and Bluetooth. However, they have disadvantages such as low accuracy or high cost. In this paper, we propose an indoor positioning system in which visible light radiated from light-emitting diodes is used to locate the position of receivers. Compared with existing methods using light-emitting diode light, we present a high-precision and simple implementation collaborative indoor visible light positioning system based on an improved spring model. We first estimate coordinate position information using the visible light positioning system, and then use the spring model to correct positioning errors. The system can be employed easily because it does not require additional sensors and the occlusion problem of visible light would be alleviated. We also describe simulation experiments, which confirm the feasibility of our proposed method.

Coarse cluster enhancing collaborative recommendation for social network systems

NASA Astrophysics Data System (ADS)

Zhao, Yao-Dong; Cai, Shi-Min; Tang, Ming; Shang, Min-Sheng

2017-10-01

Traditional collaborative filtering based recommender systems for social network systems bring very high demands on time complexity due to computing similarities of all pairs of users via resource usages and annotation actions, which thus strongly suppresses recommending speed. In this paper, to overcome this drawback, we propose a novel approach, namely coarse cluster that partitions similar users and associated items at a high speed to enhance user-based collaborative filtering, and then develop a fast collaborative user model for the social tagging systems. The experimental results based on Delicious dataset show that the proposed model is able to dramatically reduce the processing time cost greater than 90 % and relatively improve the accuracy in comparison with the ordinary user-based collaborative filtering, and is robust for the initial parameter. Most importantly, the proposed model can be conveniently extended by introducing more users' information (e.g., profiles) and practically applied for the large-scale social network systems to enhance the recommending speed without accuracy loss.

Traffic Sign Recognition with Invariance to Lighting in Dual-Focal Active Camera System

NASA Astrophysics Data System (ADS)

Gu, Yanlei; Panahpour Tehrani, Mehrdad; Yendo, Tomohiro; Fujii, Toshiaki; Tanimoto, Masayuki

In this paper, we present an automatic vision-based traffic sign recognition system, which can detect and classify traffic signs at long distance under different lighting conditions. To realize this purpose, the traffic sign recognition is developed in an originally proposed dual-focal active camera system. In this system, a telephoto camera is equipped as an assistant of a wide angle camera. The telephoto camera can capture a high accuracy image for an object of interest in the view field of the wide angle camera. The image from the telephoto camera provides enough information for recognition when the accuracy of traffic sign is low from the wide angle camera. In the proposed system, the traffic sign detection and classification are processed separately for different images from the wide angle camera and telephoto camera. Besides, in order to detect traffic sign from complex background in different lighting conditions, we propose a type of color transformation which is invariant to light changing. This color transformation is conducted to highlight the pattern of traffic signs by reducing the complexity of background. Based on the color transformation, a multi-resolution detector with cascade mode is trained and used to locate traffic signs at low resolution in the image from the wide angle camera. After detection, the system actively captures a high accuracy image of each detected traffic sign by controlling the direction and exposure time of the telephoto camera based on the information from the wide angle camera. Moreover, in classification, a hierarchical classifier is constructed and used to recognize the detected traffic signs in the high accuracy image from the telephoto camera. Finally, based on the proposed system, a set of experiments in the domain of traffic sign recognition is presented. The experimental results demonstrate that the proposed system can effectively recognize traffic signs at low resolution in different lighting conditions.

Bioassays for TSH Receptor Autoantibodies, from FRTL-5 Cells to TSH Receptor-LH/CG Receptor Chimeras: The Contribution of Leonard D. Kohn.

PubMed

Giuliani, Cesidio; Saji, Motoyasu; Bucci, Ines; Napolitano, Giorgio

2016-01-01

Since the discovery 60 years ago of the "long-acting thyroid stimulator" by Adams and Purves, great progress has been made in the detection of thyroid-stimulating hormone (TSH) receptor (TSHR) autoantibodies (TRAbs) in Graves' disease. Today, commercial assays are available that can detect TRAbs with high accuracy and provide diagnostic and prognostic evaluation of patients with Graves' disease. The present review focuses on the development of TRAbs bioassays, and particularly on the role that Leonard D. Kohn had in this. Indeed, 30 years ago, the Kohn group developed a bioassay based on the use of FRTL-5 cells that was characterized by high reproducibility, feasibility, and diagnostic accuracy. Using this FRTL-5 bioassay, Kohn and his colleagues were the first to develop monoclonal antibodies (moAbs) against the TSHR. Furthermore, they demonstrated the multifaceted functional nature of TRAbs in patients with Graves' disease, with the identification of stimulating and blocking TRAbs, and even antibodies that activated pathways other than cAMP. After the cloning of the TSHR, the Kohn laboratory constructed human TSHR-rat luteinizing hormone/chorionic gonadotropin receptor chimeras. This paved the way to a new bioassay based on the use of non-thyroid cells transfected with the Mc4 chimera. The new Mc4 bioassay is characterized by high diagnostic and prognostic accuracy, greater than for other assays. The availability of a commercial kit based on the Mc4 chimera is spreading the use of this assay worldwide, indicating its benefits for these patients with Graves' disease. This review also describes the main contributions made by other researchers in TSHR molecular biology and TRAbs assay, especially with the development of highly potent moAbs. A comparison of the diagnostic accuracies of the main TRAbs assays, as both immunoassays and bioassays, is also provided.

Bioassays for TSH Receptor Autoantibodies, from FRTL-5 Cells to TSH Receptor–LH/CG Receptor Chimeras: The Contribution of Leonard D. Kohn

PubMed Central

Giuliani, Cesidio; Saji, Motoyasu; Bucci, Ines; Napolitano, Giorgio

2016-01-01

Since the discovery 60 years ago of the “long-acting thyroid stimulator” by Adams and Purves, great progress has been made in the detection of thyroid-stimulating hormone (TSH) receptor (TSHR) autoantibodies (TRAbs) in Graves’ disease. Today, commercial assays are available that can detect TRAbs with high accuracy and provide diagnostic and prognostic evaluation of patients with Graves’ disease. The present review focuses on the development of TRAbs bioassays, and particularly on the role that Leonard D. Kohn had in this. Indeed, 30 years ago, the Kohn group developed a bioassay based on the use of FRTL-5 cells that was characterized by high reproducibility, feasibility, and diagnostic accuracy. Using this FRTL-5 bioassay, Kohn and his colleagues were the first to develop monoclonal antibodies (moAbs) against the TSHR. Furthermore, they demonstrated the multifaceted functional nature of TRAbs in patients with Graves’ disease, with the identification of stimulating and blocking TRAbs, and even antibodies that activated pathways other than cAMP. After the cloning of the TSHR, the Kohn laboratory constructed human TSHR–rat luteinizing hormone/chorionic gonadotropin receptor chimeras. This paved the way to a new bioassay based on the use of non-thyroid cells transfected with the Mc4 chimera. The new Mc4 bioassay is characterized by high diagnostic and prognostic accuracy, greater than for other assays. The availability of a commercial kit based on the Mc4 chimera is spreading the use of this assay worldwide, indicating its benefits for these patients with Graves’ disease. This review also describes the main contributions made by other researchers in TSHR molecular biology and TRAbs assay, especially with the development of highly potent moAbs. A comparison of the diagnostic accuracies of the main TRAbs assays, as both immunoassays and bioassays, is also provided. PMID:27504107

Accuracy of reading liquid based cytology slides using the ThinPrep Imager compared with conventional cytology: prospective study

PubMed Central

d'Assuncao, Jefferson; Irwig, Les; Macaskill, Petra; Chan, Siew F; Richards, Adele; Farnsworth, Annabelle

2007-01-01

Objective To compare the accuracy of liquid based cytology using the computerised ThinPrep Imager with that of manually read conventional cytology. Design Prospective study. Setting Pathology laboratory in Sydney, Australia. Participants 55 164 split sample pairs (liquid based sample collected after conventional sample from one collection) from consecutive samples of women choosing both types of cytology and whose specimens were examined between August 2004 and June 2005. Main outcome measures Primary outcome was accuracy of slides for detecting squamous lesions. Secondary outcomes were rate of unsatisfactory slides, distribution of squamous cytological classifications, and accuracy of detecting glandular lesions. Results Fewer unsatisfactory slides were found for imager read cytology than for conventional cytology (1.8% v 3.1%; P<0.001). More slides were classified as abnormal by imager read cytology (7.4% v 6.0% overall and 2.8% v 2.2% for cervical intraepithelial neoplasia of grade 1 or higher). Among 550 patients in whom imager read cytology was cervical intraepithelial neoplasia grade 1 or higher and conventional cytology was less severe than grade 1, 133 of 380 biopsy samples taken were high grade histology. Among 294 patients in whom imager read cytology was less severe than cervical intraepithelial neoplasia grade 1 and conventional cytology was grade 1 or higher, 62 of 210 biopsy samples taken were high grade histology. Imager read cytology therefore detected 71 more cases of high grade histology than did conventional cytology, resulting from 170 more biopsies. Similar results were found when one pathologist reread the slides, masked to cytology results. Conclusion The ThinPrep Imager detects 1.29 more cases of histological high grade squamous disease per 1000 women screened than conventional cytology, with cervical intraepithelial neoplasia grade 1 as the threshold for referral to colposcopy. More imager read slides than conventional slides were satisfactory for examination and more contained low grade cytological abnormalities. PMID:17604301

Speed, Dissipation, and Accuracy in Early T-cell Recognition

NASA Astrophysics Data System (ADS)

Cui, Wenping; Mehta, Pankaj

In the immune system, T cells can perform self-foreign discrimination with great foreign ligand sensitivity, high decision speed and low energy cost. There is significant evidence T-cells achieve such great performance with a mechanism: kinetic proofreading(KPR). KPR-based mechanisms actively consume energy to increase the specificity of T-cell recognition. An important theoretical question arises: how to understand trade-offs and fundamental limits on accuracy, speed, and dissipation (energy consumption). Recent theoretical work suggests that it is always possible to reduce the the error of KPR-based mechanisms by waiting longer and/or consuming more energy. Surprisingly, we find that this is not the case and that there actually exists an optimal point in the speed-energy-accuracy plane for KPR and its generalizations. This work was supported by NIH R35 and Simons MMLS Grant.

GPS-based tracking system for TOPEX orbit determination

NASA Technical Reports Server (NTRS)

Melbourne, W. G.

1984-01-01

A tracking system concept is discussed that is based on the utilization of the constellation of Navstar satellites in the Global Positioning System (GPS). The concept involves simultaneous and continuous metric tracking of the signals from all visible Navstar satellites by approximately six globally distributed ground terminals and by the TOPEX spacecraft at 1300-km altitude. Error studies indicate that this system could be capable of obtaining decimeter position accuracies and, most importantly, around 5 cm in the radial component which is key to exploiting the full accuracy potential of the altimetric measurements for ocean topography. Topics covered include: background of the GPS, the precision mode for utilization of the system, past JPL research for using the GPS in precision applications, the present tracking system concept for high accuracy satellite positioning, and results from a proof-of-concept demonstration.

Accuracy of Estimating Highly Eccentric Binary Black Hole Parameters with Gravitational-wave Detections

NASA Astrophysics Data System (ADS)

Gondán, László; Kocsis, Bence; Raffai, Péter; Frei, Zsolt

2018-03-01

Mergers of stellar-mass black holes on highly eccentric orbits are among the targets for ground-based gravitational-wave detectors, including LIGO, VIRGO, and KAGRA. These sources may commonly form through gravitational-wave emission in high-velocity dispersion systems or through the secular Kozai–Lidov mechanism in triple systems. Gravitational waves carry information about the binaries’ orbital parameters and source location. Using the Fisher matrix technique, we determine the measurement accuracy with which the LIGO–VIRGO–KAGRA network could measure the source parameters of eccentric binaries using a matched filtering search of the repeated burst and eccentric inspiral phases of the waveform. We account for general relativistic precession and the evolution of the orbital eccentricity and frequency during the inspiral. We find that the signal-to-noise ratio and the parameter measurement accuracy may be significantly higher for eccentric sources than for circular sources. This increase is sensitive to the initial pericenter distance, the initial eccentricity, and the component masses. For instance, compared to a 30 {M}ȯ –30 {M}ȯ non-spinning circular binary, the chirp mass and sky-localization accuracy can improve by a factor of ∼129 (38) and ∼2 (11) for an initially highly eccentric binary assuming an initial pericenter distance of 20 M tot (10 M tot).

Inventory and analysis of natural vegetation and related resources from space and high altitude photography

NASA Technical Reports Server (NTRS)

Poulton, C. E.; Faulkner, D. P.; Johnson, J. R.; Mouat, D. A.; Schrumpf, B. J.

1971-01-01

A high altitude photomosaic resource map of Site 29 was produced which provided an opportunity to test photo interpretation accuracy of natural vegetation resource features when mapped at a small (1:133,400) scale. Helicopter reconnaissance over 144 previously selected test points revealed a highly adequate level of photo interpretation accuracy. In general, the reasons for errors could be accounted for. The same photomosaic resource map enabled construction of interpretive land use overlays. Based on features of the landscape, including natural vegetation types, judgements for land use suitability were made and have been presented for two types of potential land use. These two, agriculture and urbanization, represent potential land use conflicts.

a Band Selection Method for High Precision Registration of Hyperspectral Image

NASA Astrophysics Data System (ADS)

Yang, H.; Li, X.

2018-04-01

During the registration of hyperspectral images and high spatial resolution images, too much bands in a hyperspectral image make it difficult to select bands with good registration performance. Terrible bands are possible to reduce matching speed and accuracy. To solve this problem, an algorithm based on Cram'er-Rao lower bound theory is proposed to select good matching bands in this paper. The algorithm applies the Cram'er-Rao lower bound theory to the study of registration accuracy, and selects good matching bands by CRLB parameters. Experiments show that the algorithm in this paper can choose good matching bands and provide better data for the registration of hyperspectral image and high spatial resolution image.

Graph-based signal integration for high-throughput phenotyping

PubMed Central

2012-01-01

Background Electronic Health Records aggregated in Clinical Data Warehouses (CDWs) promise to revolutionize Comparative Effectiveness Research and suggest new avenues of research. However, the effectiveness of CDWs is diminished by the lack of properly labeled data. We present a novel approach that integrates knowledge from the CDW, the biomedical literature, and the Unified Medical Language System (UMLS) to perform high-throughput phenotyping. In this paper, we automatically construct a graphical knowledge model and then use it to phenotype breast cancer patients. We compare the performance of this approach to using MetaMap when labeling records. Results MetaMap's overall accuracy at identifying breast cancer patients was 51.1% (n=428); recall=85.4%, precision=26.2%, and F1=40.1%. Our unsupervised graph-based high-throughput phenotyping had accuracy of 84.1%; recall=46.3%, precision=61.2%, and F1=52.8%. Conclusions We conclude that our approach is a promising alternative for unsupervised high-throughput phenotyping. PMID:23320851

High-Accuracy Measurements of Total Column Water Vapor From the Orbiting Carbon Observatory-2

NASA Technical Reports Server (NTRS)

Nelson, Robert R.; Crisp, David; Ott, Lesley E.; O'Dell, Christopher W.

2016-01-01

Accurate knowledge of the distribution of water vapor in Earth's atmosphere is of critical importance to both weather and climate studies. Here we report on measurements of total column water vapor (TCWV) from hyperspectral observations of near-infrared reflected sunlight over land and ocean surfaces from the Orbiting Carbon Observatory-2 (OCO-2). These measurements are an ancillary product of the retrieval algorithm used to measure atmospheric carbon dioxide concentrations, with information coming from three highly resolved spectral bands. Comparisons to high-accuracy validation data, including ground-based GPS and microwave radiometer data, demonstrate that OCO-2 TCWV measurements have maximum root-mean-square deviations of 0.9-1.3mm. Our results indicate that OCO-2 is the first space-based sensor to accurately and precisely measure the two most important greenhouse gases, water vapor and carbon dioxide, at high spatial resolution [1.3 x 2.3 km(exp. 2)] and that OCO-2 TCWV measurements may be useful in improving numerical weather predictions and reanalysis products.

Maneuver Recovery Analysis for the Magnetospheric Multiscale Mission

NASA Technical Reports Server (NTRS)

Gramling, Cheryl; Carpenter, Russell; Volle, Michael; Lee, Taesul; Long, Anne

2007-01-01

The use of spacecraft formations creates new and more demanding requirements for orbit determination accuracy. In addition to absolute navigation requirements, there are typically relative navigation requirements that are based on the size or shape of the formation. The difficulty in meeting these requirements is related to the relative dynamics of the spacecraft orbits and the frequency of the formation maintenance maneuvers. This paper examines the effects of bi-weekly formation maintenance maneuvers on the absolute and relative orbit determination accuracy for the four-spacecraft Magnetospheric Multiscale (MMS) formation. Results are presented from high fidelity simulations that include the effects of realistic orbit determination errors in the maneuver planning process. Solutions are determined using a high accuracy extended Kalman filter designed for onboard navigation. Three different solutions are examined, considering the effects of process noise and measurement rate on the solutions.

Design and test of a hybrid foot force sensing and GPS system for richer user mobility activity recognition.

PubMed

Zhang, Zelun; Poslad, Stefan

2013-11-01

Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capability, i.e., they cannot recognise both human posture (during travelling) and transportation mode simultaneously, and a relatively high computational complexity. Here, a new GPS and Foot-Force (GPS + FF) sensor method is proposed to overcome these challenges that leverages a set of wearable FF sensors in combination with GPS, e.g., in a mobile phone. User mobility activities that can be recognised include both daily user postures and common transportation modes: sitting, standing, walking, cycling, bus passenger, car passenger (including private cars and taxis) and car driver. The novelty of this work is that our approach provides a more comprehensive recognition capability in terms of reliably recognising both human posture and transportation mode simultaneously during travel. In addition, by comparing the new GPS + FF method with both an ACC method (62% accuracy) and a GPS + ACC based method (70% accuracy) as baseline methods, it obtains a higher accuracy (95%) with less computational complexity, when tested on a dataset obtained from ten individuals.

A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery.

PubMed

Huang, Huasheng; Deng, Jizhong; Lan, Yubin; Yang, Aqing; Deng, Xiaoling; Zhang, Lei

2018-01-01

Appropriate Site Specific Weed Management (SSWM) is crucial to ensure the crop yields. Within SSWM of large-scale area, remote sensing is a key technology to provide accurate weed distribution information. Compared with satellite and piloted aircraft remote sensing, unmanned aerial vehicle (UAV) is capable of capturing high spatial resolution imagery, which will provide more detailed information for weed mapping. The objective of this paper is to generate an accurate weed cover map based on UAV imagery. The UAV RGB imagery was collected in 2017 October over the rice field located in South China. The Fully Convolutional Network (FCN) method was proposed for weed mapping of the collected imagery. Transfer learning was used to improve generalization capability, and skip architecture was applied to increase the prediction accuracy. After that, the performance of FCN architecture was compared with Patch_based CNN algorithm and Pixel_based CNN method. Experimental results showed that our FCN method outperformed others, both in terms of accuracy and efficiency. The overall accuracy of the FCN approach was up to 0.935 and the accuracy for weed recognition was 0.883, which means that this algorithm is capable of generating accurate weed cover maps for the evaluated UAV imagery.

Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain-computer interface: three-class classification of rest, right-, and left-hand motor execution.

PubMed

Trakoolwilaiwan, Thanawin; Behboodi, Bahareh; Lee, Jaeseok; Kim, Kyungsoo; Choi, Ji-Woong

2018-01-01

The aim of this work is to develop an effective brain-computer interface (BCI) method based on functional near-infrared spectroscopy (fNIRS). In order to improve the performance of the BCI system in terms of accuracy, the ability to discriminate features from input signals and proper classification are desired. Previous studies have mainly extracted features from the signal manually, but proper features need to be selected carefully. To avoid performance degradation caused by manual feature selection, we applied convolutional neural networks (CNNs) as the automatic feature extractor and classifier for fNIRS-based BCI. In this study, the hemodynamic responses evoked by performing rest, right-, and left-hand motor execution tasks were measured on eight healthy subjects to compare performances. Our CNN-based method provided improvements in classification accuracy over conventional methods employing the most commonly used features of mean, peak, slope, variance, kurtosis, and skewness, classified by support vector machine (SVM) and artificial neural network (ANN). Specifically, up to 6.49% and 3.33% improvement in classification accuracy was achieved by CNN compared with SVM and ANN, respectively.

Intelligent Diagnostic Assistant for Complicated Skin Diseases through C5's Algorithm.

PubMed

Jeddi, Fatemeh Rangraz; Arabfard, Masoud; Kermany, Zahra Arab

2017-09-01

Intelligent Diagnostic Assistant can be used for complicated diagnosis of skin diseases, which are among the most common causes of disability. The aim of this study was to design and implement a computerized intelligent diagnostic assistant for complicated skin diseases through C5's Algorithm. An applied-developmental study was done in 2015. Knowledge base was developed based on interviews with dermatologists through questionnaires and checklists. Knowledge representation was obtained from the train data in the database using Excel Microsoft Office. Clementine Software and C5's Algorithms were applied to draw the decision tree. Analysis of test accuracy was performed based on rules extracted using inference chains. The rules extracted from the decision tree were entered into the CLIPS programming environment and the intelligent diagnostic assistant was designed then. The rules were defined using forward chaining inference technique and were entered into Clips programming environment as RULE. The accuracy and error rates obtained in the training phase from the decision tree were 99.56% and 0.44%, respectively. The accuracy of the decision tree was 98% and the error was 2% in the test phase. Intelligent diagnostic assistant can be used as a reliable system with high accuracy, sensitivity, specificity, and agreement.

Three-dimensional sensing methodology combining stereo vision and phase-measuring profilometry based on dynamic programming

NASA Astrophysics Data System (ADS)

Lee, Hyunki; Kim, Min Young; Moon, Jeon Il

2017-12-01

Phase measuring profilometry and moiré methodology have been widely applied to the three-dimensional shape measurement of target objects, because of their high measuring speed and accuracy. However, these methods suffer from inherent limitations called a correspondence problem, or 2π-ambiguity problem. Although a kind of sensing method to combine well-known stereo vision and phase measuring profilometry (PMP) technique simultaneously has been developed to overcome this problem, it still requires definite improvement for sensing speed and measurement accuracy. We propose a dynamic programming-based stereo PMP method to acquire more reliable depth information and in a relatively small time period. The proposed method efficiently fuses information from two stereo sensors in terms of phase and intensity simultaneously based on a newly defined cost function of dynamic programming. In addition, the important parameters are analyzed at the view point of the 2π-ambiguity problem and measurement accuracy. To analyze the influence of important hardware and software parameters related to the measurement performance and to verify its efficiency, accuracy, and sensing speed, a series of experimental tests were performed with various objects and sensor configurations.

Activity Recognition for Personal Time Management

NASA Astrophysics Data System (ADS)

Prekopcsák, Zoltán; Soha, Sugárka; Henk, Tamás; Gáspár-Papanek, Csaba

We describe an accelerometer based activity recognition system for mobile phones with a special focus on personal time management. We compare several data mining algorithms for the automatic recognition task in the case of single user and multiuser scenario, and improve accuracy with heuristics and advanced data mining methods. The results show that daily activities can be recognized with high accuracy and the integration with the RescueTime software can give good insights for personal time management.

Grazing Incidence Optics for X-rays Interferometry

NASA Technical Reports Server (NTRS)

Shipley, Ann; Zissa, David; Cash, Webster; Joy, Marshall

1999-01-01

Grazing incidence mirror parameters and constraints for x-ray interferometry are described. We present interferometer system tolerances and ray trace results used to define mirror surface accuracy requirements. Mirror material, surface figure, roughness, and geometry are evaluated based on analysis results. We also discuss mirror mount design constraints, finite element analysis, environmental issues, and solutions. Challenges associated with quantifying high accuracy mirror surface quality are addressed and test results are compared with theoretical predictions.

Secure Fingerprint Identification of High Accuracy

DTIC Science & Technology

2014-01-01

secure ) solution of complexity O(n3) based on Gaussian elimination. When it is applied to biometrics X and Y with mX and mY minutiae, respectively...collections of biometric data in use today include, for example, fingerprint, face, and iris images collected by the US Department of Homeland Security ...work we focus on fingerprint data due to popularity and good accuracy of this type of biometry. We formulate the problem of private, or secure , finger

Spectroscopy of H3+ based on a new high-accuracy global potential energy surface.

PubMed

Polyansky, Oleg L; Alijah, Alexander; Zobov, Nikolai F; Mizus, Irina I; Ovsyannikov, Roman I; Tennyson, Jonathan; Lodi, Lorenzo; Szidarovszky, Tamás; Császár, Attila G

2012-11-13

The molecular ion H(3)(+) is the simplest polyatomic and poly-electronic molecular system, and its spectrum constitutes an important benchmark for which precise answers can be obtained ab initio from the equations of quantum mechanics. Significant progress in the computation of the ro-vibrational spectrum of H(3)(+) is discussed. A new, global potential energy surface (PES) based on ab initio points computed with an average accuracy of 0.01 cm(-1) relative to the non-relativistic limit has recently been constructed. An analytical representation of these points is provided, exhibiting a standard deviation of 0.097 cm(-1). Problems with earlier fits are discussed. The new PES is used for the computation of transition frequencies. Recently measured lines at visible wavelengths combined with previously determined infrared ro-vibrational data show that an accuracy of the order of 0.1 cm(-1) is achieved by these computations. In order to achieve this degree of accuracy, relativistic, adiabatic and non-adiabatic effects must be properly accounted for. The accuracy of these calculations facilitates the reassignment of some measured lines, further reducing the standard deviation between experiment and theory.

Developing collaborative classifiers using an expert-based model

USGS Publications Warehouse

Mountrakis, G.; Watts, R.; Luo, L.; Wang, Jingyuan

2009-01-01

This paper presents a hierarchical, multi-stage adaptive strategy for image classification. We iteratively apply various classification methods (e.g., decision trees, neural networks), identify regions of parametric and geographic space where accuracy is low, and in these regions, test and apply alternate methods repeating the process until the entire image is classified. Currently, classifiers are evaluated through human input using an expert-based system; therefore, this paper acts as the proof of concept for collaborative classifiers. Because we decompose the problem into smaller, more manageable sub-tasks, our classification exhibits increased flexibility compared to existing methods since classification methods are tailored to the idiosyncrasies of specific regions. A major benefit of our approach is its scalability and collaborative support since selected low-accuracy classifiers can be easily replaced with others without affecting classification accuracy in high accuracy areas. At each stage, we develop spatially explicit accuracy metrics that provide straightforward assessment of results by non-experts and point to areas that need algorithmic improvement or ancillary data. Our approach is demonstrated in the task of detecting impervious surface areas, an important indicator for human-induced alterations to the environment, using a 2001 Landsat scene from Las Vegas, Nevada. ?? 2009 American Society for Photogrammetry and Remote Sensing.

Recalibration of the Klales et al. (2012) method of sexing the human innominate for Mexican populations.

PubMed

Gómez-Valdés, Jorge A; Menéndez Garmendia, Antinea; García-Barzola, Lizbeth; Sánchez-Mejorada, Gabriela; Karam, Carlos; Baraybar, José Pablo; Klales, Alexandra

2017-03-01

The aim of this study was to test the accuracy of the Klales et al. (2012) equation for sex estimation in contemporary Mexican population. Our investigation was carried out on a sample of 203 left innominates of identified adult skeletons from the UNAM-Collection and the Santa María Xigui Cemetery, in Central Mexico. The Klales' original equation produces a sex bias in sex estimation against males (86-92% accuracy versus 100% accuracy in females). Based on these results, the Klales et al. (2012) method was recalibrated for a new cutt-of-point for sex estimation in contemporary Mexican populations. The results show cross-validated classification accuracy rates as high as 100% after recalibrating the original logistic regression equation. Recalibration improved classification accuracy and eliminated sex bias. This new formula will improve sex estimation for Mexican contemporary populations. © 2017 Wiley Periodicals, Inc.

Factors Influencing Science Content Accuracy in Elementary Inquiry Science Lessons

NASA Astrophysics Data System (ADS)

Nowicki, Barbara L.; Sullivan-Watts, Barbara; Shim, Minsuk K.; Young, Betty; Pockalny, Robert

2013-06-01

Elementary teachers face increasing demands to engage children in authentic science process and argument while simultaneously preparing them with knowledge of science facts, vocabulary, and concepts. This reform is particularly challenging due to concerns that elementary teachers lack adequate science background to teach science accurately. This study examined 81 in-classroom inquiry science lessons for preservice education majors and their cooperating teachers to determine the accuracy of the science content delivered in elementary classrooms. Our results showed that 74 % of experienced teachers and 50 % of student teachers presented science lessons with greater than 90 % accuracy. Eleven of the 81 lessons (9 preservice, 2 cooperating teachers) failed to deliver accurate science content to the class. Science content accuracy was highly correlated with the use of kit-based resources supported with professional development, a preference for teaching science, and grade level. There was no correlation between the accuracy of science content and some common measures of teacher content knowledge (i.e., number of college science courses, science grades, or scores on a general science content test). Our study concluded that when provided with high quality curricular materials and targeted professional development, elementary teachers learn needed science content and present it accurately to their students.

Accuracy of Binary Black Hole waveforms for Advanced LIGO searches

NASA Astrophysics Data System (ADS)

Kumar, Prayush; Barkett, Kevin; Bhagwat, Swetha; Chu, Tony; Fong, Heather; Brown, Duncan; Pfeiffer, Harald; Scheel, Mark; Szilagyi, Bela

2015-04-01

Coalescing binaries of compact objects are flagship sources for the first direct detection of gravitational waves with LIGO-Virgo observatories. Matched-filtering based detection searches aimed at binaries of black holes will use aligned spin waveforms as filters, and their efficiency hinges on the accuracy of the underlying waveform models. A number of gravitational waveform models are available in literature, e.g. the Effective-One-Body, Phenomenological, and traditional post-Newtonian ones. While Numerical Relativity (NR) simulations provide for the most accurate modeling of gravitational radiation from compact binaries, their computational cost limits their application in large scale searches. In this talk we assess the accuracy of waveform models in two regions of parameter space, which have only been explored cursorily in the past: the high mass-ratio regime as well as the comparable mass-ratio + high spin regime.s Using the SpEC code, six q = 7 simulations with aligned-spins and lasting 60 orbits, and tens of q ∈ [1,3] simulations with high black hole spins were performed. We use them to study the accuracy and intrinsic parameter biases of different waveform families, and assess their viability for Advanced LIGO searches.

Impaired gas exchange: accuracy of defining characteristics in children with acute respiratory infection1

PubMed Central

Pascoal, Lívia Maia; Lopes, Marcos Venícios de Oliveira; Chaves, Daniel Bruno Resende; Beltrão, Beatriz Amorim; da Silva, Viviane Martins; Monteiro, Flávia Paula Magalhães

2015-01-01

OBJECTIVE: to analyze the accuracy of the defining characteristics of the Impaired gas exchange nursing diagnosis in children with acute respiratory infection. METHOD: open prospective cohort study conducted with 136 children monitored for a consecutive period of at least six days and not more than ten days. An instrument based on the defining characteristics of the Impaired gas exchange diagnosis and on literature addressing pulmonary assessment was used to collect data. The accuracy means of all the defining characteristics under study were computed. RESULTS: the Impaired gas exchange diagnosis was present in 42.6% of the children in the first assessment. Hypoxemia was the characteristic that presented the best measures of accuracy. Abnormal breathing presented high sensitivity, while restlessness, cyanosis, and abnormal skin color showed high specificity. All the characteristics presented negative predictive values of 70% and cyanosis stood out by its high positive predictive value. CONCLUSION: hypoxemia was the defining characteristic that presented the best predictive ability to determine Impaired gas exchange. Studies of this nature enable nurses to minimize variability in clinical situations presented by the patient and to identify more precisely the nursing diagnosis that represents the patient's true clinical condition. PMID:26155010

Urban Modelling Performance of Next Generation SAR Missions

NASA Astrophysics Data System (ADS)

Sefercik, U. G.; Yastikli, N.; Atalay, C.

2017-09-01

In synthetic aperture radar (SAR) technology, urban mapping and modelling have become possible with revolutionary missions TerraSAR-X (TSX) and Cosmo-SkyMed (CSK) since 2007. These satellites offer 1m spatial resolution in high-resolution spotlight imaging mode and capable for high quality digital surface model (DSM) acquisition for urban areas utilizing interferometric SAR (InSAR) technology. With the advantage of independent generation from seasonal weather conditions, TSX and CSK DSMs are much in demand by scientific users. The performance of SAR DSMs is influenced by the distortions such as layover, foreshortening, shadow and double-bounce depend up on imaging geometry. In this study, the potential of DSMs derived from convenient 1m high-resolution spotlight (HS) InSAR pairs of CSK and TSX is validated by model-to-model absolute and relative accuracy estimations in an urban area. For the verification, an airborne laser scanning (ALS) DSM of the study area was used as the reference model. Results demonstrated that TSX and CSK urban DSMs are compatible in open, built-up and forest land forms with the absolute accuracy of 8-10 m. The relative accuracies based on the coherence of neighbouring pixels are superior to absolute accuracies both for CSK and TSX.

An optimal implicit staggered-grid finite-difference scheme based on the modified Taylor-series expansion with minimax approximation method for elastic modeling

NASA Astrophysics Data System (ADS)

Yang, Lei; Yan, Hongyong; Liu, Hong

2017-03-01

Implicit staggered-grid finite-difference (ISFD) scheme is competitive for its great accuracy and stability, whereas its coefficients are conventionally determined by the Taylor-series expansion (TE) method, leading to a loss in numerical precision. In this paper, we modify the TE method using the minimax approximation (MA), and propose a new optimal ISFD scheme based on the modified TE (MTE) with MA method. The new ISFD scheme takes the advantage of the TE method that guarantees great accuracy at small wavenumbers, and keeps the property of the MA method that keeps the numerical errors within a limited bound at the same time. Thus, it leads to great accuracy for numerical solution of the wave equations. We derive the optimal ISFD coefficients by applying the new method to the construction of the objective function, and using a Remez algorithm to minimize its maximum. Numerical analysis is made in comparison with the conventional TE-based ISFD scheme, indicating that the MTE-based ISFD scheme with appropriate parameters can widen the wavenumber range with high accuracy, and achieve greater precision than the conventional ISFD scheme. The numerical modeling results also demonstrate that the MTE-based ISFD scheme performs well in elastic wave simulation, and is more efficient than the conventional ISFD scheme for elastic modeling.

PASTA for Proteins.

PubMed

Collins, Kodi; Warnow, Tandy

2018-06-19

PASTA is a multiple sequence method that uses divide-and-conquer plus iteration to enable base alignment methods to scale with high accuracy to large sequence datasets. By default, PASTA included MAFFT L-INS-i; our new extension of PASTA enables the use of MAFFT G-INS-i, MAFFT Homologs, CONTRAlign, and ProbCons. We analyzed the performance of each base method and PASTA using these base methods on 224 datasets from BAliBASE 4 with at least 50 sequences. We show that PASTA enables the most accurate base methods to scale to larger datasets at reduced computational effort, and generally improves alignment and tree accuracy on the largest BAliBASE datasets. PASTA is available at https://github.com/kodicollins/pasta and has also been integrated into the original PASTA repository at https://github.com/smirarab/pasta. Supplementary data are available at Bioinformatics online.

Classification method, spectral diversity, band combination and accuracy assessment evaluation for urban feature detection

NASA Astrophysics Data System (ADS)

Erener, A.

2013-04-01

Automatic extraction of urban features from high resolution satellite images is one of the main applications in remote sensing. It is useful for wide scale applications, namely: urban planning, urban mapping, disaster management, GIS (geographic information systems) updating, and military target detection. One common approach to detecting urban features from high resolution images is to use automatic classification methods. This paper has four main objectives with respect to detecting buildings. The first objective is to compare the performance of the most notable supervised classification algorithms, including the maximum likelihood classifier (MLC) and the support vector machine (SVM). In this experiment the primary consideration is the impact of kernel configuration on the performance of the SVM. The second objective of the study is to explore the suitability of integrating additional bands, namely first principal component (1st PC) and the intensity image, for original data for multi classification approaches. The performance evaluation of classification results is done using two different accuracy assessment methods: pixel based and object based approaches, which reflect the third aim of the study. The objective here is to demonstrate the differences in the evaluation of accuracies of classification methods. Considering consistency, the same set of ground truth data which is produced by labeling the building boundaries in the GIS environment is used for accuracy assessment. Lastly, the fourth aim is to experimentally evaluate variation in the accuracy of classifiers for six different real situations in order to identify the impact of spatial and spectral diversity on results. The method is applied to Quickbird images for various urban complexity levels, extending from simple to complex urban patterns. The simple surface type includes a regular urban area with low density and systematic buildings with brick rooftops. The complex surface type involves almost all kinds of challenges, such as high dense build up areas, regions with bare soil, and small and large buildings with different rooftops, such as concrete, brick, and metal. Using the pixel based accuracy assessment it was shown that the percent building detection (PBD) and quality percent (QP) of the MLC and SVM depend on the complexity and texture variation of the region. Generally, PBD values range between 70% and 90% for the MLC and SVM, respectively. No substantial improvements were observed when the SVM and MLC classifications were developed by the addition of more variables, instead of the use of only four bands. In the evaluation of object based accuracy assessment, it was demonstrated that while MLC and SVM provide higher rates of correct detection, they also provide higher rates of false alarms.

Automatic Extraction of Small Spatial Plots from Geo-Registered UAS Imagery

NASA Astrophysics Data System (ADS)

Cherkauer, Keith; Hearst, Anthony

2015-04-01

Accurate extraction of spatial plots from high-resolution imagery acquired by Unmanned Aircraft Systems (UAS), is a prerequisite for accurate assessment of experimental plots in many geoscience fields. If the imagery is correctly geo-registered, then it may be possible to accurately extract plots from the imagery based on their map coordinates. To test this approach, a UAS was used to acquire visual imagery of 5 ha of soybean fields containing 6.0 m2 plots in a complex planting scheme. Sixteen artificial targets were setup in the fields before flights and different spatial configurations of 0 to 6 targets were used as Ground Control Points (GCPs) for geo-registration, resulting in a total of 175 geo-registered image mosaics with a broad range of geo-registration accuracies. Geo-registration accuracy was quantified based on the horizontal Root Mean Squared Error (RMSE) of targets used as checkpoints. Twenty test plots were extracted from the geo-registered imagery. Plot extraction accuracy was quantified based on the percentage of the desired plot area that was extracted. It was found that using 4 GCPs along the perimeter of the field minimized the horizontal RMSE and enabled a plot extraction accuracy of at least 70%, with a mean plot extraction accuracy of 92%. The methods developed are suitable for work in many fields where replicates across time and space are necessary to quantify variability.

An accurate online calibration system based on combined clamp-shape coil for high voltage electronic current transformers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Zhen-hua; Li, Hong-bin; Zhang, Zhi

Electronic transformers are widely used in power systems because of their wide bandwidth and good transient performance. However, as an emerging technology, the failure rate of electronic transformers is higher than that of traditional transformers. As a result, the calibration period needs to be shortened. Traditional calibration methods require the power of transmission line be cut off, which results in complicated operation and power off loss. This paper proposes an online calibration system which can calibrate electronic current transformers without power off. In this work, the high accuracy standard current transformer and online operation method are the key techniques. Basedmore » on the clamp-shape iron-core coil and clamp-shape air-core coil, a combined clamp-shape coil is designed as the standard current transformer. By analyzing the output characteristics of the two coils, the combined clamp-shape coil can achieve verification of the accuracy. So the accuracy of the online calibration system can be guaranteed. Moreover, by employing the earth potential working method and using two insulating rods to connect the combined clamp-shape coil to the high voltage bus, the operation becomes simple and safe. Tests in China National Center for High Voltage Measurement and field experiments show that the proposed system has a high accuracy of up to 0.05 class.« less

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

NASA Technical Reports Server (NTRS)

Xiong, Jun; Thenkabail, Prasad S.; Tilton, James C.; Gumma, Murali K.; Teluguntla, Pardhasaradhi; Oliphant, Adam; Congalton, Russell G.; Yadav, Kamini; Gorelick, Noel

2017-01-01

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Evaluation of the Aurora Application Shade Measurement Accuracy

DOE Office of Scientific and Technical Information (OSTI.GOV)

2015-12-01

Aurora is an integrated, Web-based application that helps solar installers perform sales, engineering design, and financial analysis. One of Aurora's key features is its high-resolution remote shading analysis.

Object-based land cover classification based on fusion of multifrequency SAR data and THAICHOTE optical imagery

NASA Astrophysics Data System (ADS)

Sukawattanavijit, Chanika; Srestasathiern, Panu

2017-10-01

Land Use and Land Cover (LULC) information are significant to observe and evaluate environmental change. LULC classification applying remotely sensed data is a technique popularly employed on a global and local dimension particularly, in urban areas which have diverse land cover types. These are essential components of the urban terrain and ecosystem. In the present, object-based image analysis (OBIA) is becoming widely popular for land cover classification using the high-resolution image. COSMO-SkyMed SAR data was fused with THAICHOTE (namely, THEOS: Thailand Earth Observation Satellite) optical data for land cover classification using object-based. This paper indicates a comparison between object-based and pixel-based approaches in image fusion. The per-pixel method, support vector machines (SVM) was implemented to the fused image based on Principal Component Analysis (PCA). For the objectbased classification was applied to the fused images to separate land cover classes by using nearest neighbor (NN) classifier. Finally, the accuracy assessment was employed by comparing with the classification of land cover mapping generated from fused image dataset and THAICHOTE image. The object-based data fused COSMO-SkyMed with THAICHOTE images demonstrated the best classification accuracies, well over 85%. As the results, an object-based data fusion provides higher land cover classification accuracy than per-pixel data fusion.

Wall-based measurement features provides an improved IVUS coronary artery risk assessment when fused with plaque texture-based features during machine learning paradigm.

PubMed

Banchhor, Sumit K; Londhe, Narendra D; Araki, Tadashi; Saba, Luca; Radeva, Petia; Laird, John R; Suri, Jasjit S

2017-12-01

Planning of percutaneous interventional procedures involves a pre-screening and risk stratification of the coronary artery disease. Current screening tools use stand-alone plaque texture-based features and therefore lack the ability to stratify the risk. This IRB approved study presents a novel strategy for coronary artery disease risk stratification using an amalgamation of IVUS plaque texture-based and wall-based measurement features. Due to common genetic plaque makeup, carotid plaque burden was chosen as a gold standard for risk labels during training-phase of machine learning (ML) paradigm. Cross-validation protocol was adopted to compute the accuracy of the ML framework. A set of 59 plaque texture-based features was padded with six wall-based measurement features to show the improvement in stratification accuracy. The ML system was executed using principle component analysis-based framework for dimensionality reduction and uses support vector machine classifier for training and testing-phases. The ML system produced a stratification accuracy of 91.28%, demonstrating an improvement of 5.69% when wall-based measurement features were combined with plaque texture-based features. The fused system showed an improvement in mean sensitivity, specificity, positive predictive value, and area under the curve by: 6.39%, 4.59%, 3.31% and 5.48%, respectively when compared to the stand-alone system. While meeting the stability criteria of 5%, the ML system also showed a high average feature retaining power and mean reliability of 89.32% and 98.24%, respectively. The ML system showed an improvement in risk stratification accuracy when the wall-based measurement features were fused with the plaque texture-based features. Copyright © 2017 Elsevier Ltd. All rights reserved.

Urban Land Cover/use Change Detection Using High Resolution SPOT 5 and SPOT 6 Images and Urban Atlas Nomenclature

NASA Astrophysics Data System (ADS)

Akay, S. S.; Sertel, E.

2016-06-01

Urban land cover/use changes like urbanization and urban sprawl have been impacting the urban ecosystems significantly therefore determination of urban land cover/use changes is an important task to understand trends and status of urban ecosystems, to support urban planning and to aid decision-making for urban-based projects. High resolution satellite images could be used to accurately, periodically and quickly map urban land cover/use and their changes by time. This paper aims to determine urban land cover/use changes in Gaziantep city centre between 2010 and 2105 using object based images analysis and high resolution SPOT 5 and SPOT 6 images. 2.5 m SPOT 5 image obtained in 5th of June 2010 and 1.5 m SPOT 6 image obtained in 7th of July 2015 were used in this research to precisely determine land changes in five-year period. In addition to satellite images, various ancillary data namely Normalized Difference Vegetation Index (NDVI), Difference Water Index (NDWI) maps, cadastral maps, OpenStreetMaps, road maps and Land Cover maps, were integrated into the classification process to produce high accuracy urban land cover/use maps for these two years. Both images were geometrically corrected to fulfil the 1/10,000 scale geometric accuracy. Decision tree based object oriented classification was applied to identify twenty different urban land cover/use classes defined in European Urban Atlas project. Not only satellite images and satellite image-derived indices but also different thematic maps were integrated into decision tree analysis to create rule sets for accurate mapping of each class. Rule sets of each satellite image for the object based classification involves spectral, spatial and geometric parameter to automatically produce urban map of the city centre region. Total area of each class per related year and their changes in five-year period were determined and change trend in terms of class transformation were presented. Classification accuracy assessment was conducted by creating a confusion matrix to illustrate the thematic accuracy of each class.

Research on Knowledge-Based Optimization Method of Indoor Location Based on Low Energy Bluetooth

NASA Astrophysics Data System (ADS)

Li, C.; Li, G.; Deng, Y.; Wang, T.; Kang, Z.

2017-09-01

With the rapid development of LBS (Location-based Service), the demand for commercialization of indoor location has been increasing, but its technology is not perfect. Currently, the accuracy of indoor location, the complexity of the algorithm, and the cost of positioning are hard to be simultaneously considered and it is still restricting the determination and application of mainstream positioning technology. Therefore, this paper proposes a method of knowledge-based optimization of indoor location based on low energy Bluetooth. The main steps include: 1) The establishment and application of a priori and posterior knowledge base. 2) Primary selection of signal source. 3) Elimination of positioning gross error. 4) Accumulation of positioning knowledge. The experimental results show that the proposed algorithm can eliminate the signal source of outliers and improve the accuracy of single point positioning in the simulation data. The proposed scheme is a dynamic knowledge accumulation rather than a single positioning process. The scheme adopts cheap equipment and provides a new idea for the theory and method of indoor positioning. Moreover, the performance of the high accuracy positioning results in the simulation data shows that the scheme has a certain application value in the commercial promotion.

Extrapolation-Based References Improve Motion and Eddy-Current Correction of High B-Value DWI Data: Application in Parkinson's Disease Dementia.

PubMed

Nilsson, Markus; Szczepankiewicz, Filip; van Westen, Danielle; Hansson, Oskar

2015-01-01

Conventional motion and eddy-current correction, where each diffusion-weighted volume is registered to a non diffusion-weighted reference, suffers from poor accuracy for high b-value data. An alternative approach is to extrapolate reference volumes from low b-value data. We aim to compare the performance of conventional and extrapolation-based correction of diffusional kurtosis imaging (DKI) data, and to demonstrate the impact of the correction approach on group comparison studies. DKI was performed in patients with Parkinson's disease dementia (PDD), and healthy age-matched controls, using b-values of up to 2750 s/mm2. The accuracy of conventional and extrapolation-based correction methods was investigated. Parameters from DTI and DKI were compared between patients and controls in the cingulum and the anterior thalamic projection tract. Conventional correction resulted in systematic registration errors for high b-value data. The extrapolation-based methods did not exhibit such errors, yielding more accurate tractography and up to 50% lower standard deviation in DKI metrics. Statistically significant differences were found between patients and controls when using the extrapolation-based motion correction that were not detected when using the conventional method. We recommend that conventional motion and eddy-current correction should be abandoned for high b-value data in favour of more accurate methods using extrapolation-based references.

High temperature current mirror amplifier

DOEpatents

Patterson, R.B. III.

1984-05-22

Disclosed is a high temperature current mirror amplifier having biasing means in the transdiode connection of the input transistor for producing a voltage to maintain the base-collector junction reversed-biased and a current means for maintaining a current through the biasing means at high temperatures so that the base-collector junction of the input transistor remained reversed-biased. For accuracy, a second current mirror is provided with a biasing means and current means on the input leg. 2 figs.

Contextual information influences diagnosis accuracy and decision making in simulated emergency medicine emergencies.

PubMed

McRobert, Allistair Paul; Causer, Joe; Vassiliadis, John; Watterson, Leonie; Kwan, James; Williams, Mark A

2013-06-01

It is well documented that adaptations in cognitive processes with increasing skill levels support decision making in multiple domains. We examined skill-based differences in cognitive processes in emergency medicine physicians, and whether performance was significantly influenced by the removal of contextual information related to a patient's medical history. Skilled (n=9) and less skilled (n=9) emergency medicine physicians responded to high-fidelity simulated scenarios under high- and low-context information conditions. Skilled physicians demonstrated higher diagnostic accuracy irrespective of condition, and were less affected by the removal of context-specific information compared with less skilled physicians. The skilled physicians generated more options, and selected better quality options during diagnostic reasoning compared with less skilled counterparts. These cognitive processes were active irrespective of the level of context-specific information presented, although high-context information enhanced understanding of the patients' symptoms resulting in higher diagnostic accuracy. Our findings have implications for scenario design and the manipulation of contextual information during simulation training.

Feasibility of a GNSS-Probe for Creating Digital Maps of High Accuracy and Integrity

NASA Astrophysics Data System (ADS)

Vartziotis, Dimitris; Poulis, Alkis; Minogiannis, Alexandros; Siozos, Panayiotis; Goudas, Iraklis; Samson, Jaron; Tossaint, Michel

The “ROADSCANNER” project addresses the need for increased accuracy and integrity Digital Maps (DM) utilizing the latest developments in GNSS, in order to provide the required datasets for novel applications, such as navigation based Safety Applications, Advanced Driver Assistance Systems (ADAS) and Digital Automotive Simulations. The activity covered in the current paper is the feasibility study, preliminary tests, initial product design and development plan for an EGNOS enabled vehicle probe. The vehicle probe will be used for generating high accuracy, high integrity and ADAS compatible digital maps of roads, employing a multiple passes methodology supported by sophisticated refinement algorithms. Furthermore, the vehicle probe will be equipped with pavement scanning and other data fusion equipment, in order to produce 3D road surface models compatible with standards of road-tire simulation applications. The project was assigned to NIKI Ltd under the 1st Call for Ideas in the frame of the ESA - Greece Task Force.

Assessment of flat rolling theories for the use in a model-based controller for high-precision rolling applications

NASA Astrophysics Data System (ADS)

Stockert, Sven; Wehr, Matthias; Lohmar, Johannes; Abel, Dirk; Hirt, Gerhard

2017-10-01

In the electrical and medical industries the trend towards further miniaturization of devices is accompanied by the demand for smaller manufacturing tolerances. Such industries use a plentitude of small and narrow cold rolled metal strips with high thickness accuracy. Conventional rolling mills can hardly achieve further improvement of these tolerances. However, a model-based controller in combination with an additional piezoelectric actuator for high dynamic roll adjustment is expected to enable the production of the required metal strips with a thickness tolerance of +/-1 µm. The model-based controller has to be based on a rolling theory which can describe the rolling process very accurately. Additionally, the required computing time has to be low in order to predict the rolling process in real-time. In this work, four rolling theories from literature with different levels of complexity are tested for their suitability for the predictive controller. Rolling theories of von Kármán, Siebel, Bland & Ford and Alexander are implemented in Matlab and afterwards transferred to the real-time computer used for the controller. The prediction accuracy of these theories is validated using rolling trials with different thickness reduction and a comparison to the calculated results. Furthermore, the required computing time on the real-time computer is measured. Adequate results according the prediction accuracy can be achieved with the rolling theories developed by Bland & Ford and Alexander. A comparison of the computing time of those two theories reveals that Alexander's theory exceeds the sample rate of 1 kHz of the real-time computer.

Design of a real-time system of moving ship tracking on-board based on FPGA in remote sensing images

NASA Astrophysics Data System (ADS)

Yang, Tie-jun; Zhang, Shen; Zhou, Guo-qing; Jiang, Chuan-xian

2015-12-01

With the broad attention of countries in the areas of sea transportation and trade safety, the requirements of efficiency and accuracy of moving ship tracking are becoming higher. Therefore, a systematic design of moving ship tracking onboard based on FPGA is proposed, which uses the Adaptive Inter Frame Difference (AIFD) method to track a ship with different speed. For the Frame Difference method (FD) is simple but the amount of computation is very large, it is suitable for the use of FPGA to implement in parallel. But Frame Intervals (FIs) of the traditional FD method are fixed, and in remote sensing images, a ship looks very small (depicted by only dozens of pixels) and moves slowly. By applying invariant FIs, the accuracy of FD for moving ship tracking is not satisfactory and the calculation is highly redundant. So we use the adaptation of FD based on adaptive extraction of key frames for moving ship tracking. A FPGA development board of Xilinx Kintex-7 series is used for simulation. The experiments show that compared with the traditional FD method, the proposed one can achieve higher accuracy of moving ship tracking, and can meet the requirement of real-time tracking in high image resolution.

A High Precision Approach to Calibrate a Structured Light Vision Sensor in a Robot-Based Three-Dimensional Measurement System.

PubMed

Wu, Defeng; Chen, Tianfei; Li, Aiguo

2016-08-30

A robot-based three-dimensional (3D) measurement system is presented. In the presented system, a structured light vision sensor is mounted on the arm of an industrial robot. Measurement accuracy is one of the most important aspects of any 3D measurement system. To improve the measuring accuracy of the structured light vision sensor, a novel sensor calibration approach is proposed to improve the calibration accuracy. The approach is based on a number of fixed concentric circles manufactured in a calibration target. The concentric circle is employed to determine the real projected centres of the circles. Then, a calibration point generation procedure is used with the help of the calibrated robot. When enough calibration points are ready, the radial alignment constraint (RAC) method is adopted to calibrate the camera model. A multilayer perceptron neural network (MLPNN) is then employed to identify the calibration residuals after the application of the RAC method. Therefore, the hybrid pinhole model and the MLPNN are used to represent the real camera model. Using a standard ball to validate the effectiveness of the presented technique, the experimental results demonstrate that the proposed novel calibration approach can achieve a highly accurate model of the structured light vision sensor.

Dependence of Adaptive Cross-correlation Algorithm Performance on the Extended Scene Image Quality

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2008-01-01

Recently, we reported an adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels between two extended-scene sub-images captured by a Shack-Hartmann wavefront sensor. It determines the positions of all extended-scene image cells relative to a reference cell in the same frame using an FFT-based iterative image-shifting algorithm. It works with both point-source spot images as well as extended scene images. We have demonstrated previously based on some measured images that the ACC algorithm can determine image shifts with as high an accuracy as 0.01 pixel for shifts as large 3 pixels, and yield similar results for both point source spot images and extended scene images. The shift estimate accuracy of the ACC algorithm depends on illumination level, background, and scene content in addition to the amount of the shift between two image cells. In this paper we investigate how the performance of the ACC algorithm depends on the quality and the frequency content of extended scene images captured by a Shack-Hatmann camera. We also compare the performance of the ACC algorithm with those of several other approaches, and introduce a failsafe criterion for the ACC algorithm-based extended scene Shack-Hatmann sensors.

Object Based Image Analysis Combining High Spatial Resolution Imagery and Laser Point Clouds for Urban Land Cover

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and analysis of a broad range of object features available. High resolution imagery, Lidar dataset and parcel map can be widely used for classification as information carriers. Therefore, refinement of objects classification is made possible for the urban land cover. The paper presents an approach to object based image analysis (OBIA) combing high spatial resolution imagery and airborne Lidar point clouds. The advanced workflow for urban land cover is designed with four components. Firstly, colour-infrared TrueOrtho photo and laser point clouds were pre-processed to derive the parcel map of water bodies and nDSM respectively. Secondly, image objects are created via multi-resolution image segmentation integrating scale parameter, the colour and shape properties with compactness criterion. Image can be subdivided into separate object regions. Thirdly, image objects classification is performed on the basis of segmentation and a rule set of knowledge decision tree. These objects imagery are classified into six classes such as water bodies, low vegetation/grass, tree, low building, high building and road. Finally, in order to assess the validity of the classification results for six classes, accuracy assessment is performed through comparing randomly distributed reference points of TrueOrtho imagery with the classification results, forming the confusion matrix and calculating overall accuracy and Kappa coefficient. The study area focuses on test site Vaihingen/Enz and a patch of test datasets comes from the benchmark of ISPRS WG III/4 test project. The classification results show higher overall accuracy for most types of urban land cover. Overall accuracy is 89.5% and Kappa coefficient equals to 0.865. The OBIA approach provides an effective and convenient way to combine high resolution imagery and Lidar ancillary data for classification of urban land cover.

ICan: An Optimized Ion-Current-Based Quantification Procedure with Enhanced Quantitative Accuracy and Sensitivity in Biomarker Discovery

PubMed Central

2015-01-01

The rapidly expanding availability of high-resolution mass spectrometry has substantially enhanced the ion-current-based relative quantification techniques. Despite the increasing interest in ion-current-based methods, quantitative sensitivity, accuracy, and false discovery rate remain the major concerns; consequently, comprehensive evaluation and development in these regards are urgently needed. Here we describe an integrated, new procedure for data normalization and protein ratio estimation, termed ICan, for improved ion-current-based analysis of data generated by high-resolution mass spectrometry (MS). ICan achieved significantly better accuracy and precision, and lower false-positive rate for discovering altered proteins, over current popular pipelines. A spiked-in experiment was used to evaluate the performance of ICan to detect small changes. In this study E. coli extracts were spiked with moderate-abundance proteins from human plasma (MAP, enriched by IgY14-SuperMix procedure) at two different levels to set a small change of 1.5-fold. Forty-five (92%, with an average ratio of 1.71 ± 0.13) of 49 identified MAP protein (i.e., the true positives) and none of the reference proteins (1.0-fold) were determined as significantly altered proteins, with cutoff thresholds of ≥1.3-fold change and p ≤ 0.05. This is the first study to evaluate and prove competitive performance of the ion-current-based approach for assigning significance to proteins with small changes. By comparison, other methods showed remarkably inferior performance. ICan can be broadly applicable to reliable and sensitive proteomic survey of multiple biological samples with the use of high-resolution MS. Moreover, many key features evaluated and optimized here such as normalization, protein ratio determination, and statistical analyses are also valuable for data analysis by isotope-labeling methods. PMID:25285707

Reuse of imputed data in microarray analysis increases imputation efficiency

PubMed Central

Kim, Ki-Yeol; Kim, Byoung-Jin; Yi, Gwan-Su

2004-01-01

Background The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked. Results We developed a new cluster-based imputation method called sequential K-nearest neighbor (SKNN) method. This imputes the missing values sequentially from the gene having least missing values, and uses the imputed values for the later imputation. Although it uses the imputed values, the efficiency of this new method is greatly improved in its accuracy and computational complexity over the conventional KNN-based method and other methods based on maximum likelihood estimation. The performance of SKNN was in particular higher than other imputation methods for the data with high missing rates and large number of experiments. Application of Expectation Maximization (EM) to the SKNN method improved the accuracy, but increased computational time proportional to the number of iterations. The Multiple Imputation (MI) method, which is well known but not applied previously to microarray data, showed a similarly high accuracy as the SKNN method, with slightly higher dependency on the types of data sets. Conclusions Sequential reuse of imputed data in KNN-based imputation greatly increases the efficiency of imputation. The SKNN method should be practically useful to save the data of some microarray experiments which have high amounts of missing entries. The SKNN method generates reliable imputed values which can be used for further cluster-based analysis of microarray data. PMID:15504240

Prediction of drug synergy in cancer using ensemble-based machine learning techniques

NASA Astrophysics Data System (ADS)

Singh, Harpreet; Rana, Prashant Singh; Singh, Urvinder

2018-04-01

Drug synergy prediction plays a significant role in the medical field for inhibiting specific cancer agents. It can be developed as a pre-processing tool for therapeutic successes. Examination of different drug-drug interaction can be done by drug synergy score. It needs efficient regression-based machine learning approaches to minimize the prediction errors. Numerous machine learning techniques such as neural networks, support vector machines, random forests, LASSO, Elastic Nets, etc., have been used in the past to realize requirement as mentioned above. However, these techniques individually do not provide significant accuracy in drug synergy score. Therefore, the primary objective of this paper is to design a neuro-fuzzy-based ensembling approach. To achieve this, nine well-known machine learning techniques have been implemented by considering the drug synergy data. Based on the accuracy of each model, four techniques with high accuracy are selected to develop ensemble-based machine learning model. These models are Random forest, Fuzzy Rules Using Genetic Cooperative-Competitive Learning method (GFS.GCCL), Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Dynamic Evolving Neural-Fuzzy Inference System method (DENFIS). Ensembling is achieved by evaluating the biased weighted aggregation (i.e. adding more weights to the model with a higher prediction score) of predicted data by selected models. The proposed and existing machine learning techniques have been evaluated on drug synergy score data. The comparative analysis reveals that the proposed method outperforms others in terms of accuracy, root mean square error and coefficient of correlation.

Assessing the accuracy of the International Classification of Diseases codes to identify abusive head trauma: a feasibility study.

PubMed

Berger, Rachel P; Parks, Sharyn; Fromkin, Janet; Rubin, Pamela; Pecora, Peter J

2015-04-01

To assess the accuracy of an International Classification of Diseases (ICD) code-based operational case definition for abusive head trauma (AHT). Subjects were children <5 years of age evaluated for AHT by a hospital-based Child Protection Team (CPT) at a tertiary care paediatric hospital with a completely electronic medical record (EMR) system. Subjects were designated as non-AHT traumatic brain injury (TBI) or AHT based on whether the CPT determined that the injuries were due to AHT. The sensitivity and specificity of the ICD-based definition were calculated. There were 223 children evaluated for AHT: 117 AHT and 106 non-AHT TBI. The sensitivity and specificity of the ICD-based operational case definition were 92% (95% CI 85.8 to 96.2) and 96% (95% CI 92.3 to 99.7), respectively. All errors in sensitivity and three of the four specificity errors were due to coder error; one specificity error was a physician error. In a paediatric tertiary care hospital with an EMR system, the accuracy of an ICD-based case definition for AHT was high. Additional studies are needed to assess the accuracy of this definition in all types of hospitals in which children with AHT are cared for. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

De novo assembly of highly polymorphic metagenomic data using in situ generated reference sequences and a novel BLAST-based assembly pipeline.

PubMed

Lin, You-Yu; Hsieh, Chia-Hung; Chen, Jiun-Hong; Lu, Xuemei; Kao, Jia-Horng; Chen, Pei-Jer; Chen, Ding-Shinn; Wang, Hurng-Yi

2017-04-26

The accuracy of metagenomic assembly is usually compromised by high levels of polymorphism due to divergent reads from the same genomic region recognized as different loci when sequenced and assembled together. A viral quasispecies is a group of abundant and diversified genetically related viruses found in a single carrier. Current mainstream assembly methods, such as Velvet and SOAPdenovo, were not originally intended for the assembly of such metagenomics data, and therefore demands for new methods to provide accurate and informative assembly results for metagenomic data. In this study, we present a hybrid method for assembling highly polymorphic data combining the partial de novo-reference assembly (PDR) strategy and the BLAST-based assembly pipeline (BBAP). The PDR strategy generates in situ reference sequences through de novo assembly of a randomly extracted partial data set which is subsequently used for the reference assembly for the full data set. BBAP employs a greedy algorithm to assemble polymorphic reads. We used 12 hepatitis B virus quasispecies NGS data sets from a previous study to assess and compare the performance of both PDR and BBAP. Analyses suggest the high polymorphism of a full metagenomic data set leads to fragmentized de novo assembly results, whereas the biased or limited representation of external reference sequences included fewer reads into the assembly with lower assembly accuracy and variation sensitivity. In comparison, the PDR generated in situ reference sequence incorporated more reads into the final PDR assembly of the full metagenomics data set along with greater accuracy and higher variation sensitivity. BBAP assembly results also suggest higher assembly efficiency and accuracy compared to other assembly methods. Additionally, BBAP assembly recovered HBV structural variants that were not observed amongst assembly results of other methods. Together, PDR/BBAP assembly results were significantly better than other compared methods. Both PDR and BBAP independently increased the assembly efficiency and accuracy of highly polymorphic data, and assembly performances were further improved when used together. BBAP also provides nucleotide frequency information. Together, PDR and BBAP provide powerful tools for metagenomic data studies.

Constructing better classifier ensemble based on weighted accuracy and diversity measure.

PubMed

Zeng, Xiaodong; Wong, Derek F; Chao, Lidia S

2014-01-01

A weighted accuracy and diversity (WAD) method is presented, a novel measure used to evaluate the quality of the classifier ensemble, assisting in the ensemble selection task. The proposed measure is motivated by a commonly accepted hypothesis; that is, a robust classifier ensemble should not only be accurate but also different from every other member. In fact, accuracy and diversity are mutual restraint factors; that is, an ensemble with high accuracy may have low diversity, and an overly diverse ensemble may negatively affect accuracy. This study proposes a method to find the balance between accuracy and diversity that enhances the predictive ability of an ensemble for unknown data. The quality assessment for an ensemble is performed such that the final score is achieved by computing the harmonic mean of accuracy and diversity, where two weight parameters are used to balance them. The measure is compared to two representative measures, Kappa-Error and GenDiv, and two threshold measures that consider only accuracy or diversity, with two heuristic search algorithms, genetic algorithm, and forward hill-climbing algorithm, in ensemble selection tasks performed on 15 UCI benchmark datasets. The empirical results demonstrate that the WAD measure is superior to others in most cases.

Constructing Better Classifier Ensemble Based on Weighted Accuracy and Diversity Measure

PubMed Central

Chao, Lidia S.

2014-01-01

A weighted accuracy and diversity (WAD) method is presented, a novel measure used to evaluate the quality of the classifier ensemble, assisting in the ensemble selection task. The proposed measure is motivated by a commonly accepted hypothesis; that is, a robust classifier ensemble should not only be accurate but also different from every other member. In fact, accuracy and diversity are mutual restraint factors; that is, an ensemble with high accuracy may have low diversity, and an overly diverse ensemble may negatively affect accuracy. This study proposes a method to find the balance between accuracy and diversity that enhances the predictive ability of an ensemble for unknown data. The quality assessment for an ensemble is performed such that the final score is achieved by computing the harmonic mean of accuracy and diversity, where two weight parameters are used to balance them. The measure is compared to two representative measures, Kappa-Error and GenDiv, and two threshold measures that consider only accuracy or diversity, with two heuristic search algorithms, genetic algorithm, and forward hill-climbing algorithm, in ensemble selection tasks performed on 15 UCI benchmark datasets. The empirical results demonstrate that the WAD measure is superior to others in most cases. PMID:24672402

Accuracy of genetic code translation and its orthogonal corruption by aminoglycosides and Mg2+ ions.

PubMed

Zhang, Jingji; Pavlov, Michael Y; Ehrenberg, Måns

2018-02-16

We studied the effects of aminoglycosides and changing Mg2+ ion concentration on the accuracy of initial codon selection by aminoacyl-tRNA in ternary complex with elongation factor Tu and GTP (T3) on mRNA programmed ribosomes. Aminoglycosides decrease the accuracy by changing the equilibrium constants of 'monitoring bases' A1492, A1493 and G530 in 16S rRNA in favor of their 'activated' state by large, aminoglycoside-specific factors, which are the same for cognate and near-cognate codons. Increasing Mg2+ concentration decreases the accuracy by slowing dissociation of T3 from its initial codon- and aminoglycoside-independent binding state on the ribosome. The distinct accuracy-corrupting mechanisms for aminoglycosides and Mg2+ ions prompted us to re-interpret previous biochemical experiments and functional implications of existing high resolution ribosome structures. We estimate the upper thermodynamic limit to the accuracy, the 'intrinsic selectivity' of the ribosome. We conclude that aminoglycosides do not alter the intrinsic selectivity but reduce the fraction of it that is expressed as the accuracy of initial selection. We suggest that induced fit increases the accuracy and speed of codon reading at unaltered intrinsic selectivity of the ribosome.

Direct Sensor Orientation of a Land-Based Mobile Mapping System

PubMed Central

Rau, Jiann-Yeou; Habib, Ayman F.; Kersting, Ana P.; Chiang, Kai-Wei; Bang, Ki-In; Tseng, Yi-Hsing; Li, Yu-Hua

2011-01-01

A land-based mobile mapping system (MMS) is flexible and useful for the acquisition of road environment geospatial information. It integrates a set of imaging sensors and a position and orientation system (POS). The positioning quality of such systems is highly dependent on the accuracy of the utilized POS. This limitation is the major drawback due to the elevated cost associated with high-end GPS/INS units, particularly the inertial system. The potential accuracy of the direct sensor orientation depends on the architecture and quality of the GPS/INS integration process as well as the validity of the system calibration (i.e., calibration of the individual sensors as well as the system mounting parameters). In this paper, a novel single-step procedure using integrated sensor orientation with relative orientation constraint for the estimation of the mounting parameters is introduced. A comparative analysis between the proposed single-step and the traditional two-step procedure is carried out. Moreover, the estimated mounting parameters using the different methods are used in a direct geo-referencing procedure to evaluate their performance and the feasibility of the implemented system. Experimental results show that the proposed system using single-step system calibration method can achieve high 3D positioning accuracy. PMID:22164015

Detecting the Water-soluble Chloride Distribution of Cement Paste in a High-precision Way.

PubMed

Chang, Honglei; Mu, Song

2017-11-21

To improve the accuracy of the chloride distribution along the depth of cement paste under cyclic wet-dry conditions, a new method is proposed to obtain a high-precision chloride profile. Firstly, paste specimens are molded, cured, and exposed to cyclic wet-dry conditions. Then, powder samples at different specimen depths are grinded when the exposure age is reached. Finally, the water-soluble chloride content is detected using a silver nitrate titration method, and chloride profiles are plotted. The key to improving the accuracy of the chloride distribution along the depth is to exclude the error in the powderization, which is the most critical step for testing the distribution of chloride. Based on the above concept, the grinding method in this protocol can be used to grind powder samples automatically layer by layer from the surface inward, and it should be noted that a very thin grinding thickness (less than 0.5 mm) with a minimum error less than 0.04 mm can be obtained. The chloride profile obtained by this method better reflects the chloride distribution in specimens, which helps researchers to capture the distribution features that are often overlooked. Furthermore, this method can be applied to studies in the field of cement-based materials, which require high chloride distribution accuracy.

Computer aided manual validation of mass spectrometry-based proteomic data.

PubMed

Curran, Timothy G; Bryson, Bryan D; Reigelhaupt, Michael; Johnson, Hannah; White, Forest M

2013-06-15

Advances in mass spectrometry-based proteomic technologies have increased the speed of analysis and the depth provided by a single analysis. Computational tools to evaluate the accuracy of peptide identifications from these high-throughput analyses have not kept pace with technological advances; currently the most common quality evaluation methods are based on statistical analysis of the likelihood of false positive identifications in large-scale data sets. While helpful, these calculations do not consider the accuracy of each identification, thus creating a precarious situation for biologists relying on the data to inform experimental design. Manual validation is the gold standard approach to confirm accuracy of database identifications, but is extremely time-intensive. To palliate the increasing time required to manually validate large proteomic datasets, we provide computer aided manual validation software (CAMV) to expedite the process. Relevant spectra are collected, catalogued, and pre-labeled, allowing users to efficiently judge the quality of each identification and summarize applicable quantitative information. CAMV significantly reduces the burden associated with manual validation and will hopefully encourage broader adoption of manual validation in mass spectrometry-based proteomics. Copyright © 2013 Elsevier Inc. All rights reserved.

Systematic assessment of survey scan and MS2-based abundance strategies for label-free quantitative proteomics using high-resolution MS data.

PubMed

Tu, Chengjian; Li, Jun; Sheng, Quanhu; Zhang, Ming; Qu, Jun

2014-04-04

Survey-scan-based label-free method have shown no compelling benefit over fragment ion (MS2)-based approaches when low-resolution mass spectrometry (MS) was used, the growing prevalence of high-resolution analyzers may have changed the game. This necessitates an updated, comparative investigation of these approaches for data acquired by high-resolution MS. Here, we compared survey scan-based (ion current, IC) and MS2-based abundance features including spectral-count (SpC) and MS2 total-ion-current (MS2-TIC), for quantitative analysis using various high-resolution LC/MS data sets. Key discoveries include: (i) study with seven different biological data sets revealed only IC achieved high reproducibility for lower-abundance proteins; (ii) evaluation with 5-replicate analyses of a yeast sample showed IC provided much higher quantitative precision and lower missing data; (iii) IC, SpC, and MS2-TIC all showed good quantitative linearity (R(2) > 0.99) over a >1000-fold concentration range; (iv) both MS2-TIC and IC showed good linear response to various protein loading amounts but not SpC; (v) quantification using a well-characterized CPTAC data set showed that IC exhibited markedly higher quantitative accuracy, higher sensitivity, and lower false-positives/false-negatives than both SpC and MS2-TIC. Therefore, IC achieved an overall superior performance than the MS2-based strategies in terms of reproducibility, missing data, quantitative dynamic range, quantitative accuracy, and biomarker discovery.

Systematic Assessment of Survey Scan and MS2-Based Abundance Strategies for Label-Free Quantitative Proteomics Using High-Resolution MS Data

PubMed Central

2015-01-01

Survey-scan-based label-free method have shown no compelling benefit over fragment ion (MS2)-based approaches when low-resolution mass spectrometry (MS) was used, the growing prevalence of high-resolution analyzers may have changed the game. This necessitates an updated, comparative investigation of these approaches for data acquired by high-resolution MS. Here, we compared survey scan-based (ion current, IC) and MS2-based abundance features including spectral-count (SpC) and MS2 total-ion-current (MS2-TIC), for quantitative analysis using various high-resolution LC/MS data sets. Key discoveries include: (i) study with seven different biological data sets revealed only IC achieved high reproducibility for lower-abundance proteins; (ii) evaluation with 5-replicate analyses of a yeast sample showed IC provided much higher quantitative precision and lower missing data; (iii) IC, SpC, and MS2-TIC all showed good quantitative linearity (R2 > 0.99) over a >1000-fold concentration range; (iv) both MS2-TIC and IC showed good linear response to various protein loading amounts but not SpC; (v) quantification using a well-characterized CPTAC data set showed that IC exhibited markedly higher quantitative accuracy, higher sensitivity, and lower false-positives/false-negatives than both SpC and MS2-TIC. Therefore, IC achieved an overall superior performance than the MS2-based strategies in terms of reproducibility, missing data, quantitative dynamic range, quantitative accuracy, and biomarker discovery. PMID:24635752

Smearing model and restoration of star image under conditions of variable angular velocity and long exposure time.

PubMed

Sun, Ting; Xing, Fei; You, Zheng; Wang, Xiaochu; Li, Bin

2014-03-10

The star tracker is one of the most promising attitude measurement devices widely used in spacecraft for its high accuracy. High dynamic performance is becoming its major restriction, and requires immediate focus and promotion. A star image restoration approach based on the motion degradation model of variable angular velocity is proposed in this paper. This method can overcome the problem of energy dispersion and signal to noise ratio (SNR) decrease resulting from the smearing of the star spot, thus preventing failed extraction and decreased star centroid accuracy. Simulations and laboratory experiments are conducted to verify the proposed methods. The restoration results demonstrate that the described method can recover the star spot from a long motion trail to the shape of Gaussian distribution under the conditions of variable angular velocity and long exposure time. The energy of the star spot can be concentrated to ensure high SNR and high position accuracy. These features are crucial to the subsequent star extraction and the whole performance of the star tracker.

Comparison of Phase-Based 3D Near-Field Source Localization Techniques for UHF RFID.

PubMed

Parr, Andreas; Miesen, Robert; Vossiek, Martin

2016-06-25

In this paper, we present multiple techniques for phase-based narrowband backscatter tag localization in three-dimensional space with planar antenna arrays or synthetic apertures. Beamformer and MUSIC localization algorithms, known from near-field source localization and direction-of-arrival estimation, are applied to the 3D backscatter scenario and their performance in terms of localization accuracy is evaluated. We discuss the impact of different transceiver modes known from the literature, which evaluate different send and receive antenna path combinations for a single localization, as in multiple input multiple output (MIMO) systems. Furthermore, we propose a new Singledimensional-MIMO (S-MIMO) transceiver mode, which is especially suited for use with mobile robot systems. Monte-Carlo simulations based on a realistic multipath error model ensure spatial correlation of the simulated signals, and serve to critically appraise the accuracies of the different localization approaches. A synthetic uniform rectangular array created by a robotic arm is used to evaluate selected localization techniques. We use an Ultra High Frequency (UHF) Radiofrequency Identification (RFID) setup to compare measurements with the theory and simulation. The results show how a mean localization accuracy of less than 30 cm can be reached in an indoor environment. Further simulations demonstrate how the distance between aperture and tag affects the localization accuracy and how the size and grid spacing of the rectangular array need to be adapted to improve the localization accuracy down to orders of magnitude in the centimeter range, and to maximize array efficiency in terms of localization accuracy per number of elements.

3D micro-mapping: Towards assessing the quality of crowdsourcing to support 3D point cloud analysis

NASA Astrophysics Data System (ADS)

Herfort, Benjamin; Höfle, Bernhard; Klonner, Carolin

2018-03-01

In this paper, we propose a method to crowdsource the task of complex three-dimensional information extraction from 3D point clouds. We design web-based 3D micro tasks tailored to assess segmented LiDAR point clouds of urban trees and investigate the quality of the approach in an empirical user study. Our results for three different experiments with increasing complexity indicate that a single crowdsourcing task can be solved in a very short time of less than five seconds on average. Furthermore, the results of our empirical case study reveal that the accuracy, sensitivity and precision of 3D crowdsourcing are high for most information extraction problems. For our first experiment (binary classification with single answer) we obtain an accuracy of 91%, a sensitivity of 95% and a precision of 92%. For the more complex tasks of the second Experiment 2 (multiple answer classification) the accuracy ranges from 65% to 99% depending on the label class. Regarding the third experiment - the determination of the crown base height of individual trees - our study highlights that crowdsourcing can be a tool to obtain values with even higher accuracy in comparison to an automated computer-based approach. Finally, we found out that the accuracy of the crowdsourced results for all experiments is hardly influenced by characteristics of the input point cloud data and of the users. Importantly, the results' accuracy can be estimated using agreement among volunteers as an intrinsic indicator, which makes a broad application of 3D micro-mapping very promising.

Low-Cost 3-D Flow Estimation of Blood With Clutter.

PubMed

Wei, Siyuan; Yang, Ming; Zhou, Jian; Sampson, Richard; Kripfgans, Oliver D; Fowlkes, J Brian; Wenisch, Thomas F; Chakrabarti, Chaitali

2017-05-01

Volumetric flow rate estimation is an important ultrasound medical imaging modality that is used for diagnosing cardiovascular diseases. Flow rates are obtained by integrating velocity estimates over a cross-sectional plane. Speckle tracking is a promising approach that overcomes the angle dependency of traditional Doppler methods, but suffers from poor lateral resolution. Recent work improves lateral velocity estimation accuracy by reconstructing a synthetic lateral phase (SLP) signal. However, the estimation accuracy of such approaches is compromised by the presence of clutter. Eigen-based clutter filtering has been shown to be effective in removing the clutter signal; but it is computationally expensive, precluding its use at high volume rates. In this paper, we propose low-complexity schemes for both velocity estimation and clutter filtering. We use a two-tiered motion estimation scheme to combine the low complexity sum-of-absolute-difference and SLP methods to achieve subpixel lateral accuracy. We reduce the complexity of eigen-based clutter filtering by processing in subgroups and replacing singular value decomposition with less compute-intensive power iteration and subspace iteration methods. Finally, to improve flow rate estimation accuracy, we use kernel power weighting when integrating the velocity estimates. We evaluate our method for fast- and slow-moving clutter for beam-to-flow angles of 90° and 60° using Field II simulations, demonstrating high estimation accuracy across scenarios. For instance, for a beam-to-flow angle of 90° and fast-moving clutter, our estimation method provides a bias of -8.8% and standard deviation of 3.1% relative to the actual flow rate.

Very high resolution aerial films

NASA Astrophysics Data System (ADS)

Becker, Rolf

1986-11-01

The use of very high resolution aerial films in aerial photography is evaluated. Commonly used panchromatic, color, and CIR films and their high resolution equivalents are compared. Based on practical experience and systematic investigations, the very high image quality and improved height accuracy that can be achieved using these films are demonstrated. Advantages to be gained from this improvement and operational restrictions encountered when using high resolution film are discussed.

Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling

PubMed Central

Bricher, Phillippa K.; Lucieer, Arko; Shaw, Justine; Terauds, Aleks; Bergstrom, Dana M.

2013-01-01

Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6–96.3%, κ = 0.849–0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments. PMID:23940805

ShinyGPAS: interactive genomic prediction accuracy simulator based on deterministic formulas.

PubMed

Morota, Gota

2017-12-20

Deterministic formulas for the accuracy of genomic predictions highlight the relationships among prediction accuracy and potential factors influencing prediction accuracy prior to performing computationally intensive cross-validation. Visualizing such deterministic formulas in an interactive manner may lead to a better understanding of how genetic factors control prediction accuracy. The software to simulate deterministic formulas for genomic prediction accuracy was implemented in R and encapsulated as a web-based Shiny application. Shiny genomic prediction accuracy simulator (ShinyGPAS) simulates various deterministic formulas and delivers dynamic scatter plots of prediction accuracy versus genetic factors impacting prediction accuracy, while requiring only mouse navigation in a web browser. ShinyGPAS is available at: https://chikudaisei.shinyapps.io/shinygpas/ . ShinyGPAS is a shiny-based interactive genomic prediction accuracy simulator using deterministic formulas. It can be used for interactively exploring potential factors that influence prediction accuracy in genome-enabled prediction, simulating achievable prediction accuracy prior to genotyping individuals, or supporting in-class teaching. ShinyGPAS is open source software and it is hosted online as a freely available web-based resource with an intuitive graphical user interface.

The development of retrosynthetic glycan libraries to profile and classify the human serum N-linked glycome.

PubMed

Kronewitter, Scott R; An, Hyun Joo; de Leoz, Maria Lorna; Lebrilla, Carlito B; Miyamoto, Suzanne; Leiserowitz, Gary S

2009-06-01

Annotation of the human serum N-linked glycome is a formidable challenge but is necessary for disease marker discovery. A new theoretical glycan library was constructed and proposed to provide all possible glycan compositions in serum. It was developed based on established glycobiology and retrosynthetic state-transition networks. We find that at least 331 compositions are possible in the serum N-linked glycome. By pairing the theoretical glycan mass library with a high mass accuracy and high-resolution MS, human serum glycans were effectively profiled. Correct isotopic envelope deconvolution to monoisotopic masses and the high mass accuracy instruments drastically reduced the amount of false composition assignments. The high throughput capacity enabled by this library permitted the rapid glycan profiling of large control populations. With the use of the library, a human serum glycan mass profile was developed from 46 healthy individuals. This paper presents a theoretical N-linked glycan mass library that was used for accurate high-throughput human serum glycan profiling. Rapid methods for evaluating a patient's glycome are instrumental for studying glycan-based markers.

High-speed demodulation of weak fiber Bragg gratings based on microwave photonics and chromatic dispersion

NASA Astrophysics Data System (ADS)

Zhou, Lei; Li, Zhengying; Xiang, Na; Bao, Xiaoyi

2018-06-01

A high speed quasi-distributed demodulation method based on the microwave photonics and the chromatic dispersion effect is designed and implemented for weak fiber Bragg gratings (FBGs). Due to the effect of dispersion compensation fiber (DCF), FBG wavelength shift leads to the change of the difference frequency signal at the mixer. With the way of crossing microwave sweep cycle, all wavelengths of cascade FBGs can be high speed obtained by measuring the frequencies change. Moreover, through the introduction of Chirp-Z and Hanning window algorithm, the analysis of difference frequency signal is achieved very well. By adopting the single-peak filter as a reference, the length disturbance of DCF caused by temperature can be also eliminated. Therefore, the accuracy of this novel method is greatly improved, and high speed demodulation of FBGs can easily realize. The feasibility and performance are experimentally demonstrated using 105 FBGs with 0.1% reflectivity, 1 m spatial interval. Results show that each grating can be distinguished well, and the demodulation rate is as high as 40 kHz, the accuracy is about 8 pm.

Artificial neural network modeling using clinical and knowledge independent variables predicts salt intake reduction behavior

PubMed Central

Isma’eel, Hussain A.; Sakr, George E.; Almedawar, Mohamad M.; Fathallah, Jihan; Garabedian, Torkom; Eddine, Savo Bou Zein

2015-01-01

Background High dietary salt intake is directly linked to hypertension and cardiovascular diseases (CVDs). Predicting behaviors regarding salt intake habits is vital to guide interventions and increase their effectiveness. We aim to compare the accuracy of an artificial neural network (ANN) based tool that predicts behavior from key knowledge questions along with clinical data in a high cardiovascular risk cohort relative to the least square models (LSM) method. Methods We collected knowledge, attitude and behavior data on 115 patients. A behavior score was calculated to classify patients’ behavior towards reducing salt intake. Accuracy comparison between ANN and regression analysis was calculated using the bootstrap technique with 200 iterations. Results Starting from a 69-item questionnaire, a reduced model was developed and included eight knowledge items found to result in the highest accuracy of 62% CI (58-67%). The best prediction accuracy in the full and reduced models was attained by ANN at 66% and 62%, respectively, compared to full and reduced LSM at 40% and 34%, respectively. The average relative increase in accuracy over all in the full and reduced models is 82% and 102%, respectively. Conclusions Using ANN modeling, we can predict salt reduction behaviors with 66% accuracy. The statistical model has been implemented in an online calculator and can be used in clinics to estimate the patient’s behavior. This will help implementation in future research to further prove clinical utility of this tool to guide therapeutic salt reduction interventions in high cardiovascular risk individuals. PMID:26090333

Online absolute pose compensation and steering control of industrial robot based on six degrees of freedom laser measurement

NASA Astrophysics Data System (ADS)

Yang, Juqing; Wang, Dayong; Fan, Baixing; Dong, Dengfeng; Zhou, Weihu

2017-03-01

In-situ intelligent manufacturing for large-volume equipment requires industrial robots with absolute high-accuracy positioning and orientation steering control. Conventional robots mainly employ an offline calibration technology to identify and compensate key robotic parameters. However, the dynamic and static parameters of a robot change nonlinearly. It is not possible to acquire a robot's actual parameters and control the absolute pose of the robot with a high accuracy within a large workspace by offline calibration in real-time. This study proposes a real-time online absolute pose steering control method for an industrial robot based on six degrees of freedom laser tracking measurement, which adopts comprehensive compensation and correction of differential movement variables. First, the pose steering control system and robot kinematics error model are constructed, and then the pose error compensation mechanism and algorithm are introduced in detail. By accurately achieving the position and orientation of the robot end-tool, mapping the computed Jacobian matrix of the joint variable and correcting the joint variable, the real-time online absolute pose compensation for an industrial robot is accurately implemented in simulations and experimental tests. The average positioning error is 0.048 mm and orientation accuracy is better than 0.01 deg. The results demonstrate that the proposed method is feasible, and the online absolute accuracy of a robot is sufficiently enhanced.

Accuracy of DSM based on digital aerial image matching. (Polish Title: Dokładność NMPT tworzonego metodą automatycznego dopasowania cyfrowych zdjęć lotniczych)

NASA Astrophysics Data System (ADS)

Kubalska, J. L.; Preuss, R.

2013-12-01

Digital Surface Models (DSM) are used in GIS data bases as single product more often. They are also necessary to create other products such as3D city models, true-ortho and object-oriented classification. This article presents results of DSM generation for classification of vegetation in urban areas. Source data allowed producing DSM with using of image matching method and ALS data. The creation of DSM from digital images, obtained by Ultra Cam-D digital Vexcel camera, was carried out in Match-T by INPHO. This program optimizes the configuration of images matching process, which ensures high accuracy and minimize gap areas. The analysis of the accuracy of this process was made by comparison of DSM generated in Match-T with DSM generated from ALS data. Because of further purpose of generated DSM it was decided to create model in GRID structure with cell size of 1 m. With this parameter differential model from both DSMs was also built that allowed determining the relative accuracy of the compared models. The analysis indicates that the generation of DSM with multi-image matching method is competitive for the same surface model creation from ALS data. Thus, when digital images with high overlap are available, the additional registration of ALS data seems to be unnecessary.

EEG-based classification of imaginary left and right foot movements using beta rebound.

PubMed

Hashimoto, Yasunari; Ushiba, Junichi

2013-11-01

The purpose of this study was to investigate cortical lateralization of event-related (de)synchronization during left and right foot motor imagery tasks and to determine classification accuracy of the two imaginary movements in a brain-computer interface (BCI) paradigm. We recorded 31-channel scalp electroencephalograms (EEGs) from nine healthy subjects during brisk imagery tasks of left and right foot movements. EEG was analyzed with time-frequency maps and topographies, and the accuracy rate of classification between left and right foot movements was calculated. Beta rebound at the end of imagination (increase of EEG beta rhythm amplitude) was identified from the two EEGs derived from the right-shift and left-shift bipolar pairs at the vertex. This process enabled discrimination between right or left foot imagery at a high accuracy rate (maximum 81.6% in single trial analysis). These data suggest that foot motor imagery has potential to elicit left-right differences in EEG, while BCI using the unilateral foot imagery can achieve high classification accuracy, similar to ordinary BCI, based on hand motor imagery. By combining conventional discrimination techniques, the left-right discrimination of unilateral foot motor imagery provides a novel BCI system that could control a foot neuroprosthesis or a robotic foot. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Poster — Thur Eve — 40: Automated Quality Assurance for Remote-Afterloading High Dose Rate Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Anthony; Ravi, Ananth

2014-08-15

High dose rate (HDR) remote afterloading brachytherapy involves sending a small, high-activity radioactive source attached to a cable to different positions within a hollow applicator implanted in the patient. It is critical that the source position within the applicator and the dwell time of the source are accurate. Daily quality assurance (QA) tests of the positional and dwell time accuracy are essential to ensure that the accuracy of the remote afterloader is not compromised prior to patient treatment. Our centre has developed an automated, video-based QA system for HDR brachytherapy that is dramatically superior to existing diode or film QAmore » solutions in terms of cost, objectivity, positional accuracy, with additional functionalities such as being able to determine source dwell time and transit time of the source. In our system, a video is taken of the brachytherapy source as it is sent out through a position check ruler, with the source visible through a clear window. Using a proprietary image analysis algorithm, the source position is determined with respect to time as it moves to different positions along the check ruler. The total material cost of the video-based system was under $20, consisting of a commercial webcam and adjustable stand. The accuracy of the position measurement is ±0.2 mm, and the time resolution is 30 msec. Additionally, our system is capable of robustly verifying the source transit time and velocity (a test required by the AAPM and CPQR recommendations), which is currently difficult to perform accurately.« less

Modification and fixed-point analysis of a Kalman filter for orientation estimation based on 9D inertial measurement unit data.

PubMed

Brückner, Hans-Peter; Spindeldreier, Christian; Blume, Holger

2013-01-01

A common approach for high accuracy sensor fusion based on 9D inertial measurement unit data is Kalman filtering. State of the art floating-point filter algorithms differ in their computational complexity nevertheless, real-time operation on a low-power microcontroller at high sampling rates is not possible. This work presents algorithmic modifications to reduce the computational demands of a two-step minimum order Kalman filter. Furthermore, the required bit-width of a fixed-point filter version is explored. For evaluation real-world data captured using an Xsens MTx inertial sensor is used. Changes in computational latency and orientation estimation accuracy due to the proposed algorithmic modifications and fixed-point number representation are evaluated in detail on a variety of processing platforms enabling on-board processing on wearable sensor platforms.

Comparison of 3d Reconstruction Services and Terrestrial Laser Scanning for Cultural Heritage Documentation

NASA Astrophysics Data System (ADS)

Rasztovits, S.; Dorninger, P.

2013-07-01

Terrestrial Laser Scanning (TLS) is an established method to reconstruct the geometrical surface of given objects. Current systems allow for fast and efficient determination of 3D models with high accuracy and richness in detail. Alternatively, 3D reconstruction services are using images to reconstruct the surface of an object. While the instrumental expenses for laser scanning systems are high, upcoming free software services as well as open source software packages enable the generation of 3D models using digital consumer cameras. In addition, processing TLS data still requires an experienced user while recent web-services operate completely automatically. An indisputable advantage of image based 3D modeling is its implicit capability for model texturing. However, the achievable accuracy and resolution of the 3D models is lower than those of laser scanning data. Within this contribution, we investigate the results of automated web-services for image based 3D model generation with respect to a TLS reference model. For this, a copper sculpture was acquired using a laser scanner and using image series of different digital cameras. Two different webservices, namely Arc3D and AutoDesk 123D Catch were used to process the image data. The geometric accuracy was compared for the entire model and for some highly structured details. The results are presented and interpreted based on difference models. Finally, an economical comparison of the generation of the models is given considering the interactive and processing time costs.

Handheld Reflective Foil Emissometer with 0.007 Absolute Accuracy at 0.05

NASA Astrophysics Data System (ADS)

van der Ham, E. W. M.; Ballico, M. J.

2014-07-01

The development and performance of a handheld emissometer for the measurement of the emissivity of highly reflective metallic foils used for the insulation of domestic and commercial buildings are described. Reflective roofing insulation based on a thin coating of metal on a more robust substrate is very widely used in hotter climates to reduce the radiant heat transfer between the ceiling and roof in commercial and residential buildings. The required normal emissivity of these foils is generally below 0.05, so stray reflected ambient infrared radiation (IR) makes traditional reflectance-based measurements of emissivity very difficult to achieve with the required accuracy. Many manufacturers apply additional coatings onto the metallic foil to reduce visible glare during installation on a roof, and to provide protection to the thin reflective layer; however, this layer can also substantially increase the IR emissivity. The system as developed at the National Measurement Institute, Australia (NMIA) is based on the principle of measurement of the modulation in thermal infrared radiation, as the sample is thermally modulated by hot and cold air streams. A commercial infrared to band radiation thermometer with a highly specialized stray and reflected radiation shroud attachment is used as the detector system, allowing for convenient handheld field measurements. The performance and accuracy of the system have been compared with NMIA's reference emissometer systems for a number of typical material samples, demonstrating its capability to measure the absolute thermal emissivity of these very highly reflective foils with an uncertainty of better than.

AERONET Version 3 Release: Providing Significant Improvements for Multi-Decadal Global Aerosol Database and Near Real-Time Validation

NASA Technical Reports Server (NTRS)

Holben, Brent; Slutsker, Ilya; Giles, David; Eck, Thomas; Smirnov, Alexander; Sinyuk, Aliaksandr; Schafer, Joel; Sorokin, Mikhail; Rodriguez, Jon; Kraft, Jason;

Quantitative multi-pinhole small-animal SPECT: uniform versus non-uniform Chang attenuation correction.

PubMed

Wu, C; de Jong, J R; Gratama van Andel, H A; van der Have, F; Vastenhouw, B; Laverman, P; Boerman, O C; Dierckx, R A J O; Beekman, F J

2011-09-21

Attenuation of photon flux on trajectories between the source and pinhole apertures affects the quantitative accuracy of reconstructed single-photon emission computed tomography (SPECT) images. We propose a Chang-based non-uniform attenuation correction (NUA-CT) for small-animal SPECT/CT with focusing pinhole collimation, and compare the quantitative accuracy with uniform Chang correction based on (i) body outlines extracted from x-ray CT (UA-CT) and (ii) on hand drawn body contours on the images obtained with three integrated optical cameras (UA-BC). Measurements in phantoms and rats containing known activities of isotopes were conducted for evaluation. In (125)I, (201)Tl, (99m)Tc and (111)In phantom experiments, average relative errors comparing to the gold standards measured in a dose calibrator were reduced to 5.5%, 6.8%, 4.9% and 2.8%, respectively, with NUA-CT. In animal studies, these errors were 2.1%, 3.3%, 2.0% and 2.0%, respectively. Differences in accuracy on average between results of NUA-CT, UA-CT and UA-BC were less than 2.3% in phantom studies and 3.1% in animal studies except for (125)I (3.6% and 5.1%, respectively). All methods tested provide reasonable attenuation correction and result in high quantitative accuracy. NUA-CT shows superior accuracy except for (125)I, where other factors may have more impact on the quantitative accuracy than the selected attenuation correction.

Reweighted mass center based object-oriented sparse subspace clustering for hyperspectral images

NASA Astrophysics Data System (ADS)

Zhai, Han; Zhang, Hongyan; Zhang, Liangpei; Li, Pingxiang

2016-10-01

Considering the inevitable obstacles faced by the pixel-based clustering methods, such as salt-and-pepper noise, high computational complexity, and the lack of spatial information, a reweighted mass center based object-oriented sparse subspace clustering (RMC-OOSSC) algorithm for hyperspectral images (HSIs) is proposed. First, the mean-shift segmentation method is utilized to oversegment the HSI to obtain meaningful objects. Second, a distance reweighted mass center learning model is presented to extract the representative and discriminative features for each object. Third, assuming that all the objects are sampled from a union of subspaces, it is natural to apply the SSC algorithm to the HSI. Faced with the high correlation among the hyperspectral objects, a weighting scheme is adopted to ensure that the highly correlated objects are preferred in the procedure of sparse representation, to reduce the representation errors. Two widely used hyperspectral datasets were utilized to test the performance of the proposed RMC-OOSSC algorithm, obtaining high clustering accuracies (overall accuracy) of 71.98% and 89.57%, respectively. The experimental results show that the proposed method clearly improves the clustering performance with respect to the other state-of-the-art clustering methods, and it significantly reduces the computational time.

High-accuracy resolver-to-digital conversion via phase locked loop based on PID controller

NASA Astrophysics Data System (ADS)

Li, Yaoling; Wu, Zhong

2018-03-01

The problem of resolver-to-digital conversion (RDC) is transformed into the problem of angle tracking control, and a phase locked loop (PLL) method based on PID controller is proposed in this paper. This controller comprises a typical PI controller plus an incomplete differential which can avoid the amplification of higher-frequency noise components by filtering the phase detection error with a low-pass filter. Compared with conventional ones, the proposed PLL method makes the converter a system of type III and thus the conversion accuracy can be improved. Experimental results demonstrate the effectiveness of the proposed method.

Uav-Based 3d Urban Environment Monitoring

NASA Astrophysics Data System (ADS)

Boonpook, Wuttichai; Tan, Yumin; Liu, Huaqing; Zhao, Binbin; He, Lingfeng

2018-04-01

Unmanned Aerial Vehicle (UAV) based remote sensing can be used to make three-dimensions (3D) mapping with great flexibility, besides the ability to provide high resolution images. In this paper we propose a quick-change detection method on UAV images by combining altitude from Digital Surface Model (DSM) and texture analysis from images. Cases of UAV images with and without georeferencing are both considered. Research results show that the accuracy of change detection can be enhanced with georeferencing procedure, and the accuracy and precision of change detection on UAV images which are collected both vertically and obliquely but without georeferencing also have a good performance.

FPGA-based fused smart-sensor for tool-wear area quantitative estimation in CNC machine inserts.

PubMed

Trejo-Hernandez, Miguel; Osornio-Rios, Roque Alfredo; de Jesus Romero-Troncoso, Rene; Rodriguez-Donate, Carlos; Dominguez-Gonzalez, Aurelio; Herrera-Ruiz, Gilberto

2010-01-01

Manufacturing processes are of great relevance nowadays, when there is a constant claim for better productivity with high quality at low cost. The contribution of this work is the development of a fused smart-sensor, based on FPGA to improve the online quantitative estimation of flank-wear area in CNC machine inserts from the information provided by two primary sensors: the monitoring current output of a servoamplifier, and a 3-axis accelerometer. Results from experimentation show that the fusion of both parameters makes it possible to obtain three times better accuracy when compared with the accuracy obtained from current and vibration signals, individually used.

Low cycle fatigue numerical estimation of a high pressure turbine disc for the AL-31F jet engine

NASA Astrophysics Data System (ADS)

Spodniak, Miroslav; Klimko, Marek; Hocko, Marián; Žitek, Pavel

This article deals with the description of an approximate numerical estimation approach of a low cycle fatigue of a high pressure turbine disc for the AL-31F turbofan jet engine. The numerical estimation is based on the finite element method carried out in the SolidWorks software. The low cycle fatigue assessment of a high pressure turbine disc was carried out on the basis of dimensional, shape and material disc characteristics, which are available for the particular high pressure engine turbine. The method described here enables relatively fast setting of economically feasible low cycle fatigue of the assessed high pressure turbine disc using a commercially available software. The numerical estimation of accuracy of a low cycle fatigue depends on the accuracy of required input data for the particular investigated object.

Developing a weighted measure of speech sound accuracy.

PubMed

Preston, Jonathan L; Ramsdell, Heather L; Oller, D Kimbrough; Edwards, Mary Louise; Tobin, Stephen J

2011-02-01

To develop a system for numerically quantifying a speaker's phonetic accuracy through transcription-based measures. With a focus on normal and disordered speech in children, the authors describe a system for differentially weighting speech sound errors on the basis of various levels of phonetic accuracy using a Weighted Speech Sound Accuracy (WSSA) score. The authors then evaluate the reliability and validity of this measure. Phonetic transcriptions were analyzed from several samples of child speech, including preschoolers and young adolescents with and without speech sound disorders and typically developing toddlers. The new measure of phonetic accuracy was validated against existing measures, was used to discriminate typical and disordered speech production, and was evaluated to examine sensitivity to changes in phonetic accuracy over time. Reliability between transcribers and consistency of scores among different word sets and testing points are compared. Initial psychometric data indicate that WSSA scores correlate with other measures of phonetic accuracy as well as listeners' judgments of the severity of a child's speech disorder. The measure separates children with and without speech sound disorders and captures growth in phonetic accuracy in toddlers' speech over time. The measure correlates highly across transcribers, word lists, and testing points. Results provide preliminary support for the WSSA as a valid and reliable measure of phonetic accuracy in children's speech.

Diode‐based transmission detector for IMRT delivery monitoring: a validation study

PubMed Central

Li, Taoran; Wu, Q. Jackie; Matzen, Thomas; Yin, Fang‐Fang

2016-01-01

The purpose of this work was to evaluate the potential of a new transmission detector for real‐time quality assurance of dynamic‐MLC‐based radiotherapy. The accuracy of detecting dose variation and static/dynamic MLC position deviations was measured, as well as the impact of the device on the radiation field (surface dose, transmission). Measured dose variations agreed with the known variations within 0.3%. The measurement of static and dynamic MLC position deviations matched the known deviations with high accuracy (0.7–1.2 mm). The absorption of the device was minimal (∼ 1%). The increased surface dose was small (1%–9%) but, when added to existing collimator scatter effects could become significant at large field sizes (≥30×30 cm2). Overall the accuracy and speed of the device show good potential for real‐time quality assurance. PACS number(s): 87.55.Qr PMID:27685115

Design of all-weather celestial navigation system

NASA Astrophysics Data System (ADS)

Sun, Hongchi; Mu, Rongjun; Du, Huajun; Wu, Peng

2018-03-01

In order to realize autonomous navigation in the atmosphere, an all-weather celestial navigation system is designed. The research of celestial navigation system include discrimination method of comentropy and the adaptive navigation algorithm based on the P value. The discrimination method of comentropy is studied to realize the independent switching of two celestial navigation modes, starlight and radio. Finally, an adaptive filtering algorithm based on P value is proposed, which can greatly improve the disturbance rejection capability of the system. The experimental results show that the accuracy of the three axis attitude is better than 10″, and it can work all weather. In perturbation environment, the position accuracy of the integrated navigation system can be increased 20% comparing with the traditional method. It basically meets the requirements of the all-weather celestial navigation system, and it has the ability of stability, reliability, high accuracy and strong anti-interference.

Airborne and ground based lidar measurements of the atmospheric pressure profile

NASA Technical Reports Server (NTRS)

Korb, C. Laurence; Schwemmer, Geary K.; Dombrowski, Mark; Weng, Chi Y.

1989-01-01

The first high accuracy remote measurements of the atmospheric pressure profile have been made. The measurements were made with a differential absorption lidar system that utilizes tunable alexandrite lasers. The absorption in the trough between two lines in the oxygen A-band near 760 nm was used for probing the atmosphere. Measurements of the two-dimensional structure of the pressure field were made in the troposphere from an aircraft looking down. Also, measurements of the one-dimensional structure were made from the ground looking up. Typical pressure accuracies for the aircraft measurements were 1.5-2 mbar with a 30-m vertical resolution and a 100-shot average (20 s), which corresponds to a 2-km horizontal resolution. Typical accuracies for the upward viewing ground based measurements were 2.0 mbar for a 30-m resolution and a 100-shot average.

Tuberculosis disease diagnosis using artificial immune recognition system.

PubMed

Shamshirband, Shahaboddin; Hessam, Somayeh; Javidnia, Hossein; Amiribesheli, Mohsen; Vahdat, Shaghayegh; Petković, Dalibor; Gani, Abdullah; Kiah, Miss Laiha Mat

2014-01-01

There is a high risk of tuberculosis (TB) disease diagnosis among conventional methods. This study is aimed at diagnosing TB using hybrid machine learning approaches. Patient epicrisis reports obtained from the Pasteur Laboratory in the north of Iran were used. All 175 samples have twenty features. The features are classified based on incorporating a fuzzy logic controller and artificial immune recognition system. The features are normalized through a fuzzy rule based on a labeling system. The labeled features are categorized into normal and tuberculosis classes using the Artificial Immune Recognition Algorithm. Overall, the highest classification accuracy reached was for the 0.8 learning rate (α) values. The artificial immune recognition system (AIRS) classification approaches using fuzzy logic also yielded better diagnosis results in terms of detection accuracy compared to other empirical methods. Classification accuracy was 99.14%, sensitivity 87.00%, and specificity 86.12%.

Error analysis and correction of lever-type stylus profilometer based on Nelder-Mead Simplex method

NASA Astrophysics Data System (ADS)

Hu, Chunbing; Chang, Suping; Li, Bo; Wang, Junwei; Zhang, Zhongyu

2017-10-01

Due to the high measurement accuracy and wide range of applications, lever-type stylus profilometry is commonly used in industrial research areas. However, the error caused by the lever structure has a great influence on the profile measurement, thus this paper analyzes the error of high-precision large-range lever-type stylus profilometry. The errors are corrected by the Nelder-Mead Simplex method, and the results are verified by the spherical surface calibration. It can be seen that this method can effectively reduce the measurement error and improve the accuracy of the stylus profilometry in large-scale measurement.

Advanced turboprop noise prediction based on recent theoretical results

NASA Technical Reports Server (NTRS)

Farassat, F.; Padula, S. L.; Dunn, M. H.

1987-01-01

The development of a high speed propeller noise prediction code at Langley Research Center is described. The code utilizes two recent acoustic formulations in the time domain for subsonic and supersonic sources. The structure and capabilities of the code are discussed. Grid size study for accuracy and speed of execution on a computer is also presented. The code is tested against an earlier Langley code. Considerable increase in accuracy and speed of execution are observed. Some examples of noise prediction of a high speed propeller for which acoustic test data are available are given. A brisk derivation of formulations used is given in an appendix.

Importance of Personalized Health-Care Models: A Case Study in Activity Recognition.

PubMed

Zdravevski, Eftim; Lameski, Petre; Trajkovik, Vladimir; Pombo, Nuno; Garcia, Nuno

2018-01-01

Novel information and communication technologies create possibilities to change the future of health care. Ambient Assisted Living (AAL) is seen as a promising supplement of the current care models. The main goal of AAL solutions is to apply ambient intelligence technologies to enable elderly people to continue to live in their preferred environments. Applying trained models from health data is challenging because the personalized environments could differ significantly than the ones which provided training data. This paper investigates the effects on activity recognition accuracy using single accelerometer of personalized models compared to models built on general population. In addition, we propose a collaborative filtering based approach which provides balance between fully personalized models and generic models. The results show that the accuracy could be improved to 95% with fully personalized models, and up to 91.6% with collaborative filtering based models, which is significantly better than common models that exhibit accuracy of 85.1%. The collaborative filtering approach seems to provide highly personalized models with substantial accuracy, while overcoming the cold start problem that is common for fully personalized models.

High-order asynchrony-tolerant finite difference schemes for partial differential equations

NASA Astrophysics Data System (ADS)

Aditya, Konduri; Donzis, Diego A.

2017-12-01

Synchronizations of processing elements (PEs) in massively parallel simulations, which arise due to communication or load imbalances between PEs, significantly affect the scalability of scientific applications. We have recently proposed a method based on finite-difference schemes to solve partial differential equations in an asynchronous fashion - synchronization between PEs is relaxed at a mathematical level. While standard schemes can maintain their stability in the presence of asynchrony, their accuracy is drastically affected. In this work, we present a general methodology to derive asynchrony-tolerant (AT) finite difference schemes of arbitrary order of accuracy, which can maintain their accuracy when synchronizations are relaxed. We show that there are several choices available in selecting a stencil to derive these schemes and discuss their effect on numerical and computational performance. We provide a simple classification of schemes based on the stencil and derive schemes that are representative of different classes. Their numerical error is rigorously analyzed within a statistical framework to obtain the overall accuracy of the solution. Results from numerical experiments are used to validate the performance of the schemes.

HEp-2 cell image classification method based on very deep convolutional networks with small datasets

NASA Astrophysics Data System (ADS)

Lu, Mengchi; Gao, Long; Guo, Xifeng; Liu, Qiang; Yin, Jianping

2017-07-01

Human Epithelial-2 (HEp-2) cell images staining patterns classification have been widely used to identify autoimmune diseases by the anti-Nuclear antibodies (ANA) test in the Indirect Immunofluorescence (IIF) protocol. Because manual test is time consuming, subjective and labor intensive, image-based Computer Aided Diagnosis (CAD) systems for HEp-2 cell classification are developing. However, methods proposed recently are mostly manual features extraction with low accuracy. Besides, the scale of available benchmark datasets is small, which does not exactly suitable for using deep learning methods. This issue will influence the accuracy of cell classification directly even after data augmentation. To address these issues, this paper presents a high accuracy automatic HEp-2 cell classification method with small datasets, by utilizing very deep convolutional networks (VGGNet). Specifically, the proposed method consists of three main phases, namely image preprocessing, feature extraction and classification. Moreover, an improved VGGNet is presented to address the challenges of small-scale datasets. Experimental results over two benchmark datasets demonstrate that the proposed method achieves superior performance in terms of accuracy compared with existing methods.

Genome sequencing in microfabricated high-density picolitre reactors.

PubMed

Margulies, Marcel; Egholm, Michael; Altman, William E; Attiya, Said; Bader, Joel S; Bemben, Lisa A; Berka, Jan; Braverman, Michael S; Chen, Yi-Ju; Chen, Zhoutao; Dewell, Scott B; Du, Lei; Fierro, Joseph M; Gomes, Xavier V; Godwin, Brian C; He, Wen; Helgesen, Scott; Ho, Chun Heen; Ho, Chun He; Irzyk, Gerard P; Jando, Szilveszter C; Alenquer, Maria L I; Jarvie, Thomas P; Jirage, Kshama B; Kim, Jong-Bum; Knight, James R; Lanza, Janna R; Leamon, John H; Lefkowitz, Steven M; Lei, Ming; Li, Jing; Lohman, Kenton L; Lu, Hong; Makhijani, Vinod B; McDade, Keith E; McKenna, Michael P; Myers, Eugene W; Nickerson, Elizabeth; Nobile, John R; Plant, Ramona; Puc, Bernard P; Ronan, Michael T; Roth, George T; Sarkis, Gary J; Simons, Jan Fredrik; Simpson, John W; Srinivasan, Maithreyan; Tartaro, Karrie R; Tomasz, Alexander; Vogt, Kari A; Volkmer, Greg A; Wang, Shally H; Wang, Yong; Weiner, Michael P; Yu, Pengguang; Begley, Richard F; Rothberg, Jonathan M

2005-09-15

The proliferation of large-scale DNA-sequencing projects in recent years has driven a search for alternative methods to reduce time and cost. Here we describe a scalable, highly parallel sequencing system with raw throughput significantly greater than that of state-of-the-art capillary electrophoresis instruments. The apparatus uses a novel fibre-optic slide of individual wells and is able to sequence 25 million bases, at 99% or better accuracy, in one four-hour run. To achieve an approximately 100-fold increase in throughput over current Sanger sequencing technology, we have developed an emulsion method for DNA amplification and an instrument for sequencing by synthesis using a pyrosequencing protocol optimized for solid support and picolitre-scale volumes. Here we show the utility, throughput, accuracy and robustness of this system by shotgun sequencing and de novo assembly of the Mycoplasma genitalium genome with 96% coverage at 99.96% accuracy in one run of the machine.

Small arms mini-fire control system: fiber-optic barrel deflection sensor

NASA Astrophysics Data System (ADS)

Rajic, S.; Datskos, P.; Lawrence, W.; Marlar, T.; Quinton, B.

2012-06-01

Traditionally the methods to increase firearms accuracy, particularly at distance, have concentrated on barrel isolation (free floating) and substantial barrel wall thickening to gain rigidity. This barrel stiffening technique did not completely eliminate barrel movement but the problem was significantly reduced to allow a noticeable accuracy enhancement. This process, although highly successful, came at a very high weight penalty. Obviously the goal would be to lighten the barrel (firearm), yet achieve even greater accuracy. Thus, if lightweight barrels could ultimately be compensated for both their static and dynamic mechanical perturbations, the result would be very accurate, yet significantly lighter weight, weapons. We discuss our development of a barrel reference sensor system that is designed to accomplish this ambitious goal. Our optical fiber-based sensor monitors the barrel muzzle position and autonomously compensates for any induced perturbations. The reticle is electronically adjusted in position to compensate for the induced barrel deviation in real time.

Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery.

PubMed

Belgiu, Mariana; Dr Guţ, Lucian

2014-10-01

Although multiresolution segmentation (MRS) is a powerful technique for dealing with very high resolution imagery, some of the image objects that it generates do not match the geometries of the target objects, which reduces the classification accuracy. MRS can, however, be guided to produce results that approach the desired object geometry using either supervised or unsupervised approaches. Although some studies have suggested that a supervised approach is preferable, there has been no comparative evaluation of these two approaches. Therefore, in this study, we have compared supervised and unsupervised approaches to MRS. One supervised and two unsupervised segmentation methods were tested on three areas using QuickBird and WorldView-2 satellite imagery. The results were assessed using both segmentation evaluation methods and an accuracy assessment of the resulting building classifications. Thus, differences in the geometries of the image objects and in the potential to achieve satisfactory thematic accuracies were evaluated. The two approaches yielded remarkably similar classification results, with overall accuracies ranging from 82% to 86%. The performance of one of the unsupervised methods was unexpectedly similar to that of the supervised method; they identified almost identical scale parameters as being optimal for segmenting buildings, resulting in very similar geometries for the resulting image objects. The second unsupervised method produced very different image objects from the supervised method, but their classification accuracies were still very similar. The latter result was unexpected because, contrary to previously published findings, it suggests a high degree of independence between the segmentation results and classification accuracy. The results of this study have two important implications. The first is that object-based image analysis can be automated without sacrificing classification accuracy, and the second is that the previously accepted idea that classification is dependent on segmentation is challenged by our unexpected results, casting doubt on the value of pursuing 'optimal segmentation'. Our results rather suggest that as long as under-segmentation remains at acceptable levels, imperfections in segmentation can be ruled out, so that a high level of classification accuracy can still be achieved.

A Random Forest-based ensemble method for activity recognition.

PubMed

Feng, Zengtao; Mo, Lingfei; Li, Meng

2015-01-01

This paper presents a multi-sensor ensemble approach to human physical activity (PA) recognition, using random forest. We designed an ensemble learning algorithm, which integrates several independent Random Forest classifiers based on different sensor feature sets to build a more stable, more accurate and faster classifier for human activity recognition. To evaluate the algorithm, PA data collected from the PAMAP (Physical Activity Monitoring for Aging People), which is a standard, publicly available database, was utilized to train and test. The experimental results show that the algorithm is able to correctly recognize 19 PA types with an accuracy of 93.44%, while the training is faster than others. The ensemble classifier system based on the RF (Random Forest) algorithm can achieve high recognition accuracy and fast calculation.

Quantitative differential phase contrast imaging at high resolution with radially asymmetric illumination.

PubMed

Lin, Yu-Zi; Huang, Kuang-Yuh; Luo, Yuan

2018-06-15

Half-circle illumination-based differential phase contrast (DPC) microscopy has been utilized to recover phase images through a pair of images along multiple axes. Recently, the half-circle based DPC using 12-axis measurements significantly provides a circularly symmetric phase transfer function to improve accuracy for more stable phase recovery. Instead of using half-circle-based DPC, we propose a new scheme of DPC under radially asymmetric illumination to achieve circularly symmetric phase transfer function and enhance the accuracy of phase recovery in a more stable and efficient fashion. We present the design, implementation, and experimental image data demonstrating the ability of our method to obtain quantitative phase images of microspheres, as well as live fibroblast cell samples.

THTM: A template matching algorithm based on HOG descriptor and two-stage matching

NASA Astrophysics Data System (ADS)

Jiang, Yuanjie; Ruan, Li; Xiao, Limin; Liu, Xi; Yuan, Feng; Wang, Haitao

2018-04-01

We propose a novel method for template matching named THTM - a template matching algorithm based on HOG (histogram of gradient) and two-stage matching. We rely on the fast construction of HOG and the two-stage matching that jointly lead to a high accuracy approach for matching. TMTM give enough attention on HOG and creatively propose a twice-stage matching while traditional method only matches once. Our contribution is to apply HOG to template matching successfully and present two-stage matching, which is prominent to improve the matching accuracy based on HOG descriptor. We analyze key features of THTM and perform compared to other commonly used alternatives on a challenging real-world datasets. Experiments show that our method outperforms the comparison method.

Out-of-Focus Projector Calibration Method with Distortion Correction on the Projection Plane in the Structured Light Three-Dimensional Measurement System.

PubMed

Zhang, Jiarui; Zhang, Yingjie; Chen, Bo

2017-12-20

The three-dimensional measurement system with a binary defocusing technique is widely applied in diverse fields. The measurement accuracy is mainly determined by out-of-focus projector calibration accuracy. In this paper, a high-precision out-of-focus projector calibration method that is based on distortion correction on the projection plane and nonlinear optimization algorithm is proposed. To this end, the paper experimentally presents the principle that the projector has noticeable distortions outside its focus plane. In terms of this principle, the proposed method uses a high-order radial and tangential lens distortion representation on the projection plane to correct the calibration residuals caused by projection distortion. The final accuracy parameters of out-of-focus projector were obtained using a nonlinear optimization algorithm with good initial values, which were provided by coarsely calibrating the parameters of the out-of-focus projector on the focal and projection planes. Finally, the experimental results demonstrated that the proposed method can accuracy calibrate an out-of-focus projector, regardless of the amount of defocusing.

Use of topographic and climatological models in a geographical data base to improve Landsat MSS classification for Olympic National Park

NASA Technical Reports Server (NTRS)

Cibula, William G.; Nyquist, Maurice O.

1987-01-01

An unsupervised computer classification of vegetation/landcover of Olympic National Park and surrounding environs was initially carried out using four bands of Landsat MSS data. The primary objective of the project was to derive a level of landcover classifications useful for park management applications while maintaining an acceptably high level of classification accuracy. Initially, nine generalized vegetation/landcover classes were derived. Overall classification accuracy was 91.7 percent. In an attempt to refine the level of classification, a geographic information system (GIS) approach was employed. Topographic data and watershed boundaries (inferred precipitation/temperature) data were registered with the Landsat MSS data. The resultant boolean operations yielded 21 vegetation/landcover classes while maintaining the same level of classification accuracy. The final classification provided much better identification and location of the major forest types within the park at the same high level of accuracy, and these met the project objective. This classification could now become inputs into a GIS system to help provide answers to park management coupled with other ancillary data programs such as fire management.

Effects of high altitude and exercise on marksmanship.

PubMed

Tharion, W J; Hoyt, R W; Marlowe, B E; Cymerman, A

1992-02-01

The effects of exercise and high altitude (3,700 m to 4,300 m) on marksmanship accuracy and sighting time were quantified in 16 experienced marksmen. Subjects dry-fired a disabled rifle equipped with a laser-based system from a free-standing position. The 2.3-cm circular target was at a distance of 5 m. Marksmanship was assessed under the following conditions: 1) at rest at sea level; 2) immediately after a 21-km run/walk ascent from 1,800 m to 4,300 m elevation; 3) at rest during days 1 to 3 at altitude; 4) at rest during days 14 to 16 at altitude; and 5) immediately after a second ascent after 17 d at altitude. Exercise reduced marksmanship accuracy (p less than 0.05) but did not affect sighting time. Acute altitude exposure reduced marksmanship accuracy, and decreased sighting time (p less than 0.05). However, after residence at altitude, accuracy and sighting time at rest returned to sea level values. Exercise and acute altitude exposure had similar but independent detrimental effects on marksmanship.

Accuracy, Sensitivity and Specificity of Fine Needle Aspiration Biopsy for Salivary Gland Tumors: A Retrospective Study from 2006 to 2011

PubMed

Silva, William P P; Stramandinoli-Zanicotti, Roberta T; Schussel, Juliana L; Ramos, Gyl H A; Ioshi, Sergio O; Sassi, Laurindo M

2016-11-01

Objective: This article concerns evaluation of the sensitivity, specificity and accuracy of FNAB for pre-surgical diagnosis of benign and malignant lesions of major and minor salivary glands of patients treated in the Department of Head and Neck Surgery of Erasto Gartner Hospital. Methods: This retrospective study analyzed medical records from January 2006 to December 2011 from patients with salivary gland lesions who underwent preoperative FNAB and, after surgical excision of the lesion, histopathological examination. Results: The study had a cohort of 130 cases, but 34 cases (26.2%) were considered unsatisfactory regarding cytology analyses. Based on the data, sensitivity was 66.7% (6/9), specificity was 81.6% (71/87), accuracy was 80.2% (77/96), the positive predictive value was 66,7% (6/9) and the negative predictive value was 81.6% (71/87). Conclusion: Despite the high rate of inadequate samples obtained in the FNAB in this study the technique offers high specificity, accuracy and acceptable sensitivity. Creative Commons Attribution License

Identification of Biomolecular Building Blocks by Recognition Tunneling: Stride towards Nanopore Sequencing of Biomolecules

NASA Astrophysics Data System (ADS)

Sen, Suman

DNA, RNA and Protein are three pivotal biomolecules in human and other organisms, playing decisive roles in functionality, appearance, diseases development and other physiological phenomena. Hence, sequencing of these biomolecules acquires the prime interest in the scientific community. Single molecular identification of their building blocks can be done by a technique called Recognition Tunneling (RT) based on Scanning Tunneling Microscope (STM). A single layer of specially designed recognition molecule is attached to the STM electrodes, which trap the targeted molecules (DNA nucleoside monophosphates, RNA nucleoside monophosphates or amino acids) inside the STM nanogap. Depending on their different binding interactions with the recognition molecules, the analyte molecules generate stochastic signal trains accommodating their "electronic fingerprints". Signal features are used to detect the molecules using a machine learning algorithm and different molecules can be identified with significantly high accuracy. This, in turn, paves the way for rapid, economical nanopore sequencing platform, overcoming the drawbacks of Next Generation Sequencing (NGS) techniques. To read DNA nucleotides with high accuracy in an STM tunnel junction a series of nitrogen-based heterocycles were designed and examined to check their capabilities to interact with naturally occurring DNA nucleotides by hydrogen bonding in the tunnel junction. These recognition molecules are Benzimidazole, Imidazole, Triazole and Pyrrole. Benzimidazole proved to be best among them showing DNA nucleotide classification accuracy close to 99%. Also, Imidazole reader can read an abasic monophosphate (AP), a product from depurination or depyrimidination that occurs 10,000 times per human cell per day. In another study, I have investigated a new universal reader, 1-(2-mercaptoethyl)pyrene (Pyrene reader) based on stacking interactions, which should be more specific to the canonical DNA nucleosides. In addition, Pyrene reader showed higher DNA base-calling accuracy compare to Imidazole reader, the workhorse in our previous projects. In my other projects, various amino acids and RNA nucleoside monophosphates were also classified with significantly high accuracy using RT. Twenty naturally occurring amino acids and various RNA nucleosides (four canonical and two modified) were successfully identified. Thus, we envision nanopore sequencing biomolecules using Recognition Tunneling (RT) that should provide comprehensive betterment over current technologies in terms of time, chemical and instrumental cost and capability of de novo sequencing.

Accuracy Assessment of a Complex Building 3d Model Reconstructed from Images Acquired with a Low-Cost Uas

NASA Astrophysics Data System (ADS)

Oniga, E.; Chirilă, C.; Stătescu, F.

2017-02-01

Nowadays, Unmanned Aerial Systems (UASs) are a wide used technique for acquisition in order to create buildings 3D models, providing the acquisition of a high number of images at very high resolution or video sequences, in a very short time. Since low-cost UASs are preferred, the accuracy of a building 3D model created using this platforms must be evaluated. To achieve results, the dean's office building from the Faculty of "Hydrotechnical Engineering, Geodesy and Environmental Engineering" of Iasi, Romania, has been chosen, which is a complex shape building with the roof formed of two hyperbolic paraboloids. Seven points were placed on the ground around the building, three of them being used as GCPs, while the remaining four as Check points (CPs) for accuracy assessment. Additionally, the coordinates of 10 natural CPs representing the building characteristic points were measured with a Leica TCR 405 total station. The building 3D model was created as a point cloud which was automatically generated based on digital images acquired with the low-cost UASs, using the image matching algorithm and different software like 3DF Zephyr, Visual SfM, PhotoModeler Scanner and Drone2Map for ArcGIS. Except for the PhotoModeler Scanner software, the interior and exterior orientation parameters were determined simultaneously by solving a self-calibrating bundle adjustment. Based on the UAS point clouds, automatically generated by using the above mentioned software and GNSS data respectively, the parameters of the east side hyperbolic paraboloid were calculated using the least squares method and a statistical blunder detection. Then, in order to assess the accuracy of the building 3D model, several comparisons were made for the facades and the roof with reference data, considered with minimum errors: TLS mesh for the facades and GNSS mesh for the roof. Finally, the front facade of the building was created in 3D based on its characteristic points using the PhotoModeler Scanner software, resulting a CAD (Computer Aided Design) model. The results showed the high potential of using low-cost UASs for building 3D model creation and if the building 3D model is created based on its characteristic points the accuracy is significantly improved.

Read-only high accuracy volume holographic optical correlator

NASA Astrophysics Data System (ADS)

Zhao, Tian; Li, Jingming; Cao, Liangcai; He, Qingsheng; Jin, Guofan

2011-10-01

A read-only volume holographic correlator (VHC) is proposed. After the recording of all of the correlation database pages by angular multiplexing, a stand-alone read-only high accuracy VHC will be separated from the VHC recording facilities which include the high-power laser and the angular multiplexing system. The stand-alone VHC has its own low power readout laser and very compact and simple structure. Since there are two lasers that are employed for recording and readout, respectively, the optical alignment tolerance of the laser illumination on the SLM is very sensitive. The twodimensional angular tolerance is analyzed based on the theoretical model of the volume holographic correlator. The experimental demonstration of the proposed read-only VHC is introduced and discussed.

High throughput single cell counting in droplet-based microfluidics.

PubMed

Lu, Heng; Caen, Ouriel; Vrignon, Jeremy; Zonta, Eleonora; El Harrak, Zakaria; Nizard, Philippe; Baret, Jean-Christophe; Taly, Valérie

2017-05-02

Droplet-based microfluidics is extensively and increasingly used for high-throughput single-cell studies. However, the accuracy of the cell counting method directly impacts the robustness of such studies. We describe here a simple and precise method to accurately count a large number of adherent and non-adherent human cells as well as bacteria. Our microfluidic hemocytometer provides statistically relevant data on large populations of cells at a high-throughput, used to characterize cell encapsulation and cell viability during incubation in droplets.

Cadastral Positioning Accuracy Improvement: a Case Study in Malaysia

NASA Astrophysics Data System (ADS)

Hashim, N. M.; Omar, A. H.; Omar, K. M.; Abdullah, N. M.; Yatim, M. H. M.

2016-09-01

Cadastral map is a parcel-based information which is specifically designed to define the limitation of boundaries. In Malaysia, the cadastral map is under authority of the Department of Surveying and Mapping Malaysia (DSMM). With the growth of spatial based technology especially Geographical Information System (GIS), DSMM decided to modernize and reform its cadastral legacy datasets by generating an accurate digital based representation of cadastral parcels. These legacy databases usually are derived from paper parcel maps known as certified plan. The cadastral modernization will result in the new cadastral database no longer being based on single and static parcel paper maps, but on a global digital map. Despite the strict process of the cadastral modernization, this reform has raised unexpected queries that remain essential to be addressed. The main focus of this study is to review the issues that have been generated by this transition. The transformed cadastral database should be additionally treated to minimize inherent errors and to fit them to the new satellite based coordinate system with high positional accuracy. This review result will be applied as a foundation for investigation to study the systematic and effectiveness method for Positional Accuracy Improvement (PAI) in cadastral database modernization.

Molecular Isotopic Distribution Analysis (MIDAs) with Adjustable Mass Accuracy

NASA Astrophysics Data System (ADS)

Alves, Gelio; Ogurtsov, Aleksey Y.; Yu, Yi-Kuo

2014-01-01

In this paper, we present Molecular Isotopic Distribution Analysis (MIDAs), a new software tool designed to compute molecular isotopic distributions with adjustable accuracies. MIDAs offers two algorithms, one polynomial-based and one Fourier-transform-based, both of which compute molecular isotopic distributions accurately and efficiently. The polynomial-based algorithm contains few novel aspects, whereas the Fourier-transform-based algorithm consists mainly of improvements to other existing Fourier-transform-based algorithms. We have benchmarked the performance of the two algorithms implemented in MIDAs with that of eight software packages (BRAIN, Emass, Mercury, Mercury5, NeutronCluster, Qmass, JFC, IC) using a consensus set of benchmark molecules. Under the proposed evaluation criteria, MIDAs's algorithms, JFC, and Emass compute with comparable accuracy the coarse-grained (low-resolution) isotopic distributions and are more accurate than the other software packages. For fine-grained isotopic distributions, we compared IC, MIDAs's polynomial algorithm, and MIDAs's Fourier transform algorithm. Among the three, IC and MIDAs's polynomial algorithm compute isotopic distributions that better resemble their corresponding exact fine-grained (high-resolution) isotopic distributions. MIDAs can be accessed freely through a user-friendly web-interface at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/midas/index.html.

Molecular Isotopic Distribution Analysis (MIDAs) with adjustable mass accuracy.

PubMed

Alves, Gelio; Ogurtsov, Aleksey Y; Yu, Yi-Kuo

2014-01-01

In this paper, we present Molecular Isotopic Distribution Analysis (MIDAs), a new software tool designed to compute molecular isotopic distributions with adjustable accuracies. MIDAs offers two algorithms, one polynomial-based and one Fourier-transform-based, both of which compute molecular isotopic distributions accurately and efficiently. The polynomial-based algorithm contains few novel aspects, whereas the Fourier-transform-based algorithm consists mainly of improvements to other existing Fourier-transform-based algorithms. We have benchmarked the performance of the two algorithms implemented in MIDAs with that of eight software packages (BRAIN, Emass, Mercury, Mercury5, NeutronCluster, Qmass, JFC, IC) using a consensus set of benchmark molecules. Under the proposed evaluation criteria, MIDAs's algorithms, JFC, and Emass compute with comparable accuracy the coarse-grained (low-resolution) isotopic distributions and are more accurate than the other software packages. For fine-grained isotopic distributions, we compared IC, MIDAs's polynomial algorithm, and MIDAs's Fourier transform algorithm. Among the three, IC and MIDAs's polynomial algorithm compute isotopic distributions that better resemble their corresponding exact fine-grained (high-resolution) isotopic distributions. MIDAs can be accessed freely through a user-friendly web-interface at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/midas/index.html.

From Panoramic Photos to a Low-Cost Photogrammetric Workflow for Cultural Heritage 3d Documentation

NASA Astrophysics Data System (ADS)

D'Annibale, E.; Tassetti, A. N.; Malinverni, E. S.

2013-07-01

The research aims to optimize a workflow of architecture documentation: starting from panoramic photos, tackling available instruments and technologies to propose an integrated, quick and low-cost solution of Virtual Architecture. The broader research background shows how to use spherical panoramic images for the architectural metric survey. The input data (oriented panoramic photos), the level of reliability and Image-based Modeling methods constitute an integrated and flexible 3D reconstruction approach: from the professional survey of cultural heritage to its communication in virtual museum. The proposed work results from the integration and implementation of different techniques (Multi-Image Spherical Photogrammetry, Structure from Motion, Imagebased Modeling) with the aim to achieve high metric accuracy and photorealistic performance. Different documentation chances are possible within the proposed workflow: from the virtual navigation of spherical panoramas to complex solutions of simulation and virtual reconstruction. VR tools make for the integration of different technologies and the development of new solutions for virtual navigation. Image-based Modeling techniques allow 3D model reconstruction with photo realistic and high-resolution texture. High resolution of panoramic photo and algorithms of panorama orientation and photogrammetric restitution vouch high accuracy and high-resolution texture. Automated techniques and their following integration are subject of this research. Data, advisably processed and integrated, provide different levels of analysis and virtual reconstruction joining the photogrammetric accuracy to the photorealistic performance of the shaped surfaces. Lastly, a new solution of virtual navigation is tested. Inside the same environment, it proposes the chance to interact with high resolution oriented spherical panorama and 3D reconstructed model at once.

When Interference Helps: Increasing Executive Load to Facilitate Deception Detection in the Concealed Information Test

PubMed Central

Visu-Petra, George; Varga, Mihai; Miclea, Mircea; Visu-Petra, Laura

2013-01-01

The possibility to enhance the detection efficiency of the Concealed Information Test (CIT) by increasing executive load was investigated, using an interference design. After learning and executing a mock crime scenario, subjects underwent three deception detection tests: an RT-based CIT, an RT-based CIT plus a concurrent memory task (CITMem), and an RT-based CIT plus a concurrent set-shifting task (CITShift). The concealed information effect, consisting in increased RT and lower response accuracy for probe items compared to irrelevant items, was evidenced across all three conditions. The group analyses indicated a larger difference between RTs to probe and irrelevant items in the dual-task conditions, but this difference was not translated in a significantly increased detection efficiency at an individual level. Signal detection parameters based on the comparison with a simulated innocent group showed accurate discrimination for all conditions. Overall response accuracy on the CITMem was highest and the difference between response accuracy to probes and irrelevants was smallest in this condition. Accuracy on the concurrent tasks (Mem and Shift) was high, and responses on these tasks were significantly influenced by CIT stimulus type (probes vs. irrelevants). The findings are interpreted in relation to the cognitive load/dual-task interference literature, generating important insights for research on the involvement of executive functions in deceptive behavior. PMID:23543918

Multimodal navigated skull base tumor resection using image-based vascular and cranial nerve segmentation: A prospective pilot study

PubMed Central

Dolati, Parviz; Gokoglu, Abdulkerim; Eichberg, Daniel; Zamani, Amir; Golby, Alexandra; Al-Mefty, Ossama

2015-01-01

Background: Skull base tumors frequently encase or invade adjacent normal neurovascular structures. For this reason, optimal tumor resection with incomplete knowledge of patient anatomy remains a challenge. Methods: To determine the accuracy and utility of image-based preoperative segmentation in skull base tumor resections, we performed a prospective study. Ten patients with skull base tumors underwent preoperative 3T magnetic resonance imaging, which included thin section three-dimensional (3D) space T2, 3D time of flight, and magnetization-prepared rapid acquisition gradient echo sequences. Imaging sequences were loaded in the neuronavigation system for segmentation and preoperative planning. Five different neurovascular landmarks were identified in each case and measured for accuracy using the neuronavigation system. Each segmented neurovascular element was validated by manual placement of the navigation probe, and errors of localization were measured. Results: Strong correspondence between image-based segmentation and microscopic view was found at the surface of the tumor and tumor-normal brain interfaces in all cases. The accuracy of the measurements was 0.45 ± 0.21 mm (mean ± standard deviation). This information reassured the surgeon and prevented vascular injury intraoperatively. Preoperative segmentation of the related cranial nerves was possible in 80% of cases and helped the surgeon localize involved cranial nerves in all cases. Conclusion: Image-based preoperative vascular and neural element segmentation with 3D reconstruction is highly informative preoperatively and could increase the vigilance of neurosurgeons for preventing neurovascular injury during skull base surgeries. Additionally, the accuracy found in this study is superior to previously reported measurements. This novel preliminary study is encouraging for future validation with larger numbers of patients. PMID:26674155

Multimodal navigated skull base tumor resection using image-based vascular and cranial nerve segmentation: A prospective pilot study.

PubMed

Dolati, Parviz; Gokoglu, Abdulkerim; Eichberg, Daniel; Zamani, Amir; Golby, Alexandra; Al-Mefty, Ossama

2015-01-01

Skull base tumors frequently encase or invade adjacent normal neurovascular structures. For this reason, optimal tumor resection with incomplete knowledge of patient anatomy remains a challenge. To determine the accuracy and utility of image-based preoperative segmentation in skull base tumor resections, we performed a prospective study. Ten patients with skull base tumors underwent preoperative 3T magnetic resonance imaging, which included thin section three-dimensional (3D) space T2, 3D time of flight, and magnetization-prepared rapid acquisition gradient echo sequences. Imaging sequences were loaded in the neuronavigation system for segmentation and preoperative planning. Five different neurovascular landmarks were identified in each case and measured for accuracy using the neuronavigation system. Each segmented neurovascular element was validated by manual placement of the navigation probe, and errors of localization were measured. Strong correspondence between image-based segmentation and microscopic view was found at the surface of the tumor and tumor-normal brain interfaces in all cases. The accuracy of the measurements was 0.45 ± 0.21 mm (mean ± standard deviation). This information reassured the surgeon and prevented vascular injury intraoperatively. Preoperative segmentation of the related cranial nerves was possible in 80% of cases and helped the surgeon localize involved cranial nerves in all cases. Image-based preoperative vascular and neural element segmentation with 3D reconstruction is highly informative preoperatively and could increase the vigilance of neurosurgeons for preventing neurovascular injury during skull base surgeries. Additionally, the accuracy found in this study is superior to previously reported measurements. This novel preliminary study is encouraging for future validation with larger numbers of patients.

Spacecraft attitude determination accuracy from mission experience

NASA Technical Reports Server (NTRS)

Brasoveanu, D.; Hashmall, J.

1994-01-01

This paper summarizes a compilation of attitude determination accuracies attained by a number of satellites supported by the Goddard Space Flight Center Flight Dynamics Facility. The compilation is designed to assist future mission planners in choosing and placing attitude hardware and selecting the attitude determination algorithms needed to achieve given accuracy requirements. The major goal of the compilation is to indicate realistic accuracies achievable using a given sensor complement based on mission experience. It is expected that the use of actual spacecraft experience will make the study especially useful for mission design. A general description of factors influencing spacecraft attitude accuracy is presented. These factors include determination algorithms, inertial reference unit characteristics, and error sources that can affect measurement accuracy. Possible techniques for mitigating errors are also included. Brief mission descriptions are presented with the attitude accuracies attained, grouped by the sensor pairs used in attitude determination. The accuracies for inactive missions represent a compendium of missions report results, and those for active missions represent measurements of attitude residuals. Both three-axis and spin stabilized missions are included. Special emphasis is given to high-accuracy sensor pairs, such as two fixed-head star trackers (FHST's) and fine Sun sensor plus FHST. Brief descriptions of sensor design and mode of operation are included. Also included are brief mission descriptions and plots summarizing the attitude accuracy attained using various sensor complements.

Adaptive optics using a MEMS deformable mirror for a segmented mirror telescope

NASA Astrophysics Data System (ADS)

Miyamura, Norihide

2017-09-01

For small satellite remote sensing missions, a large aperture telescope more than 400mm is required to realize less than 1m GSD observations. However, it is difficult or expensive to realize the large aperture telescope using a monolithic primary mirror with high surface accuracy. A segmented mirror telescope should be studied especially for small satellite missions. Generally, not only high accuracy of optical surface but also high accuracy of optical alignment is required for large aperture telescopes. For segmented mirror telescopes, the alignment is more difficult and more important. For conventional systems, the optical alignment is adjusted before launch to achieve desired imaging performance. However, it is difficult to adjust the alignment for large sized optics in high accuracy. Furthermore, thermal environment in orbit and vibration in a launch vehicle cause the misalignments of the optics. We are developing an adaptive optics system using a MEMS deformable mirror for an earth observing remote sensing sensor. An image based adaptive optics system compensates the misalignments and wavefront aberrations of optical elements using the deformable mirror by feedback of observed images. We propose the control algorithm of the deformable mirror for a segmented mirror telescope by using of observed image. The numerical simulation results and experimental results show that misalignment and wavefront aberration of the segmented mirror telescope are corrected and image quality is improved.

An experimental apparatus for diffraction-limited soft x-ray nano-focusing

NASA Astrophysics Data System (ADS)

Merthe, Daniel J.; Goldberg, Kenneth A.; Yashchuk, Valeriy V.; Yuan, Sheng; McKinney, Wayne R.; Celestre, Richard; Mochi, Iacopo; Macdougall, James; Morrison, Gregory Y.; Rakawa, Senajith B.; Anderson, Erik; Smith, Brian V.; Domning, Edward E.; Warwick, Tony; Padmore, Howard

2011-09-01

Realizing the experimental potential of high-brightness, next generation synchrotron and free-electron laser light sources requires the development of reflecting x-ray optics capable of wavefront preservation and high-resolution nano-focusing. At the Advanced Light Source (ALS) beamline 5.3.1, we are developing broadly applicable, high-accuracy, in situ, at-wavelength wavefront measurement techniques to surpass 100-nrad slope measurement accuracy for diffraction-limited Kirkpatrick-Baez (KB) mirrors. The at-wavelength methodology we are developing relies on a series of wavefront-sensing tests with increasing accuracy and sensitivity, including scanning-slit Hartmann tests, grating-based lateral shearing interferometry, and quantitative knife-edge testing. We describe the original experimental techniques and alignment methodology that have enabled us to optimally set a bendable KB mirror to achieve a focused, FWHM spot size of 150 nm, with 1 nm (1.24 keV) photons at 3.7 mrad numerical aperture. The predictions of wavefront measurement are confirmed by the knife-edge testing. The side-profiled elliptically bent mirror used in these one-dimensional focusing experiments was originally designed for a much different glancing angle and conjugate distances. Visible-light long-trace profilometry was used to pre-align the mirror before installation at the beamline. This work demonstrates that high-accuracy, at-wavelength wavefront-slope feedback can be used to optimize the pitch, roll, and mirror-bending forces in situ, using procedures that are deterministic and repeatable.

Instantaneous Real-Time Kinematic Decimeter-Level Positioning with BeiDou Triple-Frequency Signals over Medium Baselines.

PubMed

He, Xiyang; Zhang, Xiaohong; Tang, Long; Liu, Wanke

2015-12-22

Many applications, such as marine navigation, land vehicles location, etc., require real time precise positioning under medium or long baseline conditions. In this contribution, we develop a model of real-time kinematic decimeter-level positioning with BeiDou Navigation Satellite System (BDS) triple-frequency signals over medium distances. The ambiguities of two extra-wide-lane (EWL) combinations are fixed first, and then a wide lane (WL) combination is reformed based on the two EWL combinations for positioning. Theoretical analysis and empirical analysis is given of the ambiguity fixing rate and the positioning accuracy of the presented method. The results indicate that the ambiguity fixing rate can be up to more than 98% when using BDS medium baseline observations, which is much higher than that of dual-frequency Hatch-Melbourne-Wübbena (HMW) method. As for positioning accuracy, decimeter level accuracy can be achieved with this method, which is comparable to that of carrier-smoothed code differential positioning method. Signal interruption simulation experiment indicates that the proposed method can realize fast high-precision positioning whereas the carrier-smoothed code differential positioning method needs several hundreds of seconds for obtaining high precision results. We can conclude that a relatively high accuracy and high fixing rate can be achieved for triple-frequency WL method with single-epoch observations, displaying significant advantage comparing to traditional carrier-smoothed code differential positioning method.

A Multitemporal, Multisensor Approach to Mapping the Canadian Boreal Forest

NASA Astrophysics Data System (ADS)

Reith, Ernest

The main anthropogenic source of CO2 emissions is the combustion of fossil fuels, while the clearing and burning of forests contribute significant amounts as well. Vegetation represents a major reservoir for terrestrial carbon stocks, and improving our ability to inventory vegetation will enhance our understanding of the impacts of land cover and climate change on carbon stocks and fluxes. These relationships may be an indication of a series of troubling biosphere-atmospheric feedback mechanisms that need to be better understood and modeled. Valuable land cover information can be provided to the global climate change modeling community using advanced remote sensing capabilities such as Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR). Individually and synergistically, data were successfully used to characterize the complex nature of the Canadian boreal forest land cover types. The multiple endmember spectral mixture analysis process was applied against seasonal AVIRIS data to produce species-level vegetated land cover maps of two study sites in the Canadian boreal forest: Old Black Spruce (OBS) and Old Jack Pine (OJP). The highest overall accuracy was assessed to be at least 66% accurate to the available reference map, providing evidence that high-quality, species-level land cover mapping of the Canadian boreal forest is achievable at accuracy levels greater than other previous research efforts in the region. Backscatter information from multichannel, polarimetric SAR utilizing a binary decision tree-based classification technique methodology was moderately successfully applied to AIRSAR to produce maps of the boreal land cover types at both sites, with overall accuracies at least 59%. A process, centered around noise whitening and principal component analysis features of the minimum noise fraction transform, was implemented to leverage synergies contained within spatially coregistered multitemporal and multisensor AVIRIS and AIRSAR data sets to successfully produce high-accuracy boreal forest land cover maps. Overall land cover map accuracies of 78% and 72% were assessed for OJP and OBS sites, respectively, for either seasonal or multitemporal data sets. High individual land cover accuracies appeared to be independent of site, season, or multisensor combination in the minimum-noise fraction-based approach.

Design and numerical analysis of highly sensitive Au-MoS2-graphene based hybrid surface plasmon resonance biosensor

NASA Astrophysics Data System (ADS)

Rahman, M. Saifur; Anower, Md. Shamim; Hasan, Md. Rabiul; Hossain, Md. Biplob; Haque, Md. Ismail

2017-08-01

We demonstrate a highly sensitive Au-MoS2-Graphene based hybrid surface plasmon resonance (SPR) biosensor for the detection of DNA hybridization. The performance parameters of the proposed sensor are investigated in terms of sensitivity, detection accuracy and quality factor at operating wavelength of 633 nm. We observed in the numerical study that sensitivity can be greatly increased by adding MoS2 layer in the middle of a Graphene-on-Au layer. It is shown that by using single layer of MoS2 in between gold and graphene layer, the proposed biosensor exhibits simultaneously high sensitivity of 87.8 deg/RIU, high detection accuracy of 1.28 and quality factor of 17.56 with gold layer thickness of 50 nm. This increased performance is due to the absorption ability and optical characteristics of graphene biomolecules and high fluorescence quenching ability of MoS2. On the basis of changing in SPR angle and minimum reflectance, the proposed sensor can sense nucleotides bonding happened between double-stranded DNA (dsDNA) helix structures. Therefore, this sensor can successfully detect the hybridization of target DNAs to the probe DNAs pre-immobilized on the Au-MoS2-Graphene hybrid with capability of distinguishing single-base mismatch.

VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability.

PubMed

Feng, Lichen; Li, Zunchao; Wang, Yuanfa

2018-02-01

Portable automatic seizure detection system is very convenient for epilepsy patients to carry. In order to make the system on-chip trainable with high efficiency and attain high detection accuracy, this paper presents a very large scale integration (VLSI) design based on the nonlinear support vector machine (SVM). The proposed design mainly consists of a feature extraction (FE) module and an SVM module. The FE module performs the three-level Daubechies discrete wavelet transform to fit the physiological bands of the electroencephalogram (EEG) signal and extracts the time-frequency domain features reflecting the nonstationary signal properties. The SVM module integrates the modified sequential minimal optimization algorithm with the table-driven-based Gaussian kernel to enable efficient on-chip learning. The presented design is verified on an Altera Cyclone II field-programmable gate array and tested using the two publicly available EEG datasets. Experiment results show that the designed VLSI system improves the detection accuracy and training efficiency.

Gaze-independent brain-computer interfaces based on covert attention and feature attention

NASA Astrophysics Data System (ADS)

Treder, M. S.; Schmidt, N. M.; Blankertz, B.

2011-10-01

There is evidence that conventional visual brain-computer interfaces (BCIs) based on event-related potentials cannot be operated efficiently when eye movements are not allowed. To overcome this limitation, the aim of this study was to develop a visual speller that does not require eye movements. Three different variants of a two-stage visual speller based on covert spatial attention and non-spatial feature attention (i.e. attention to colour and form) were tested in an online experiment with 13 healthy participants. All participants achieved highly accurate BCI control. They could select one out of thirty symbols (chance level 3.3%) with mean accuracies of 88%-97% for the different spellers. The best results were obtained for a speller that was operated using non-spatial feature attention only. These results show that, using feature attention, it is possible to realize high-accuracy, fast-paced visual spellers that have a large vocabulary and are independent of eye gaze.

Efficient L1 regularization-based reconstruction for fluorescent molecular tomography using restarted nonlinear conjugate gradient.

PubMed

Shi, Junwei; Zhang, Bin; Liu, Fei; Luo, Jianwen; Bai, Jing

2013-09-15

For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.

An Improved Ensemble Learning Method for Classifying High-Dimensional and Imbalanced Biomedicine Data.

PubMed

Yu, Hualong; Ni, Jun

2014-01-01

Training classifiers on skewed data can be technically challenging tasks, especially if the data is high-dimensional simultaneously, the tasks can become more difficult. In biomedicine field, skewed data type often appears. In this study, we try to deal with this problem by combining asymmetric bagging ensemble classifier (asBagging) that has been presented in previous work and an improved random subspace (RS) generation strategy that is called feature subspace (FSS). Specifically, FSS is a novel method to promote the balance level between accuracy and diversity of base classifiers in asBagging. In view of the strong generalization capability of support vector machine (SVM), we adopt it to be base classifier. Extensive experiments on four benchmark biomedicine data sets indicate that the proposed ensemble learning method outperforms many baseline approaches in terms of Accuracy, F-measure, G-mean and AUC evaluation criterions, thus it can be regarded as an effective and efficient tool to deal with high-dimensional and imbalanced biomedical data.

Based on the CSI regional segmentation indoor localization algorithm

NASA Astrophysics Data System (ADS)

Zeng, Xi; Lin, Wei; Lan, Jingwei

2017-08-01

To solve the problem of high cost and low accuracy, the method of Channel State Information (CSI) regional segmentation are proposed in the indoor positioning. Because Channel State Information (CSI) stability, and effective against multipath effect, we used the Channel State Information (CSI) to segment location area. The method Acquisition CSI the influence of different link to pinpoint the location of the area. Then the method can improve the accuracy of positioning, and reduce the cost of the fingerprint localization algorithm.

Video-Based Intervention in Teaching Fraction Problem-Solving to Students with Autism Spectrum Disorder.

PubMed

Yakubova, Gulnoza; Hughes, Elizabeth M; Hornberger, Erin

2015-09-01

The purpose of this study was to determine the effectiveness of a point-of-view video modeling intervention to teach mathematics problem-solving when working on word problems involving subtracting mixed fractions with uncommon denominators. Using a multiple-probe across students design of single-case methodology, three high school students with ASD completed the study. All three students demonstrated greater accuracy in solving fraction word problems and maintained accuracy levels at a 1-week follow-up.

Performance of a Method to Standardize Breast Ultrasound Interpretation Using Image Processing and Case-Based Reasoning

NASA Astrophysics Data System (ADS)

André, M. P.; Galperin, M.; Berry, A.; Ojeda-Fournier, H.; O'Boyle, M.; Olson, L.; Comstock, C.; Taylor, A.; Ledgerwood, M.

Our computer-aided diagnostic (CADx) tool uses advanced image processing and artificial intelligence to analyze findings on breast sonography images. The goal is to standardize reporting of such findings using well-defined descriptors and to improve accuracy and reproducibility of interpretation of breast ultrasound by radiologists. This study examined several factors that may impact accuracy and reproducibility of the CADx software, which proved to be highly accurate and stabile over several operating conditions.

Velocity precision measurements using laser Doppler anemometry

NASA Astrophysics Data System (ADS)

Dopheide, D.; Taux, G.; Narjes, L.

1985-07-01

A Laser Doppler Anemometer (LDA) was calibrated to determine its applicability to high pressure measurements (up to 10 bars) for industrial purposes. The measurement procedure with LDA and the experimental computerized layouts are presented. The calibration procedure is based on absolute accuracy of Doppler frequency and calibration of interference strip intervals. A four-quadrant detector allows comparison of the interference strip distance measurements and computer profiles. Further development of LDA is recommended to increase accuracy (0.1% inaccuracy) and to apply the method industrially.

Remote sensing of atmospheric aerosols with the SPEX spectropolarimeter

NASA Astrophysics Data System (ADS)

van Harten, G.; Rietjens, J.; Smit, M.; Snik, F.; Keller, C. U.; di Noia, A.; Hasekamp, O.; Vonk, J.; Volten, H.

2013-12-01

Characterizing atmospheric aerosols is key to understanding their influence on climate through their direct and indirect radiative forcing. This requires long-term global coverage, at high spatial (~km) and temporal (~days) resolution, which can only be provided by satellite remote sensing. Aerosol load and properties such as particle size, shape and chemical composition can be derived from multi-wavelength radiance and polarization measurements of sunlight that is scattered by the Earth's atmosphere at different angles. The required polarimetric accuracy of ~10^(-3) is very challenging, particularly since the instrument is located on a rapidly moving platform. Our Spectropolarimeter for Planetary EXploration (SPEX) is based on a novel, snapshot spectral modulator, with the intrinsic ability to measure polarization at high accuracy. It exhibits minimal instrumental polarization and is completely solid-state and passive. An athermal set of birefringent crystals in front of an analyzer encodes the incoming linear polarization into a sinusoidal modulation in the intensity spectrum. Moreover, a dual beam implementation yields redundancy that allows for a mutual correction in both the spectrally and spatially modulated data to increase the measurement accuracy. A partially polarized calibration stimulus has been developed, consisting of a carefully depolarized source followed by tilted glass plates to induce polarization in a controlled way. Preliminary calibration measurements show an accuracy of SPEX of well below 10^(-3), with a sensitivity limit of 2*10^(-4). We demonstrate the potential of the SPEX concept by presenting retrievals of aerosol properties based on clear sky measurements using a prototype satellite instrument and a dedicated ground-based SPEX. The retrieval algorithm, originally designed for POLDER data, performs iterative fitting of aerosol properties and surface albedo, where the initial guess is provided by a look-up table. The retrieved aerosol properties, including aerosol optical thickness, single scattering albedo, size distribution and complex refractive index, will be compared with the on-site AERONET sun-photometer, lidar, particle counter and sizer, and PM10 and PM2.5 monitoring instruments. Retrievals of the aerosol layer height based on polarization measurements in the O2A absorption band will be compared with lidar profiles. Furthermore, the possibility of enhancing the retrieval accuracy by replacing the look-up table with a neural network based initial guess will be discussed, using retrievals from simulated ground-based data.

CLARREO Pathfinder Mission to ISS: Demonstrating Greatly Increased Accuracy for Reflected Solar Space Based Observations: Calibration and Intercalibration

NASA Astrophysics Data System (ADS)

Wielicki, B. A.

2016-12-01

The CLARREO (Climate Absolute Radiance and Refractivity) Pathfinder mission is a new mission started by NASA in 2016. CLARREO Pathfinder will fly a new generation of high accuracy reflected solar spectrometer in orbit on the Inernational Space Station (ISS) to demonstrate the ability to increase accuracy of reflected solar observations from space by a factor of 3 to 20. The spectrometer will use the sun and moon as calibration sources with a baseline objective of 0.3% (1 sigma) reflectance calibration uncertainty for the contiguous spectrum from 350nm to 2300nm, covering over 95% of the Earth's reflected solar spectrum. Spectral sampling is 3nm with resolution of 6nm. The spectrometer is mounted on a 2-axis gimbal enabling a new ability to use the same optical path to view the sun, moon, and Earth. Planned launch is 2020 with at least 1 year on orbit to demonstrate the new capability. The mission will also demonstrate the ability to use the new spectrometer as a reference transfer spectrometer in orbit to achieve intercalibration of reflected solar instruments to within 0.3% (1 sigma) using space, time, spectral, and angle matched observations across the full scan width of remote sensing instruments. Intercalibration to 0.3% will be demonstrated across the full scan width of the NASA CERES broadband radiometer and the NOAA VIIRS imager reflected solar spectral channels. This mission will demonstrate reflected solar intercalibration across the full swath width as opposed to current nadir only intercalibration used by GSICS (Global Space Based InterCalibration System). Intercalibration will include a new capability to determine scan angle dependence of polarization sensitivity of instruments like VIIRS. The high accuracy goals of this mission are driven primarily by the accuracy required to more rapidly and accurately observe climate change signals such as cloud feedback (see Wielicki et al. 2013 Bulletin of the American Meteorological Society). The new high accuracy and intercalibration capability will also be very useful for serving as a reference calibrator for constellations of operational instruments in Geostationary or Low Earth Orbit (e.g. land resource imagers, ocean color, cloud imagers). The higher accuracy will enable operational sensors to more effectively serve as climate change sensors.

Two-axis tracking solar collector mechanism

DOEpatents

Johnson, Kenneth C.

1992-01-01

This invention is a novel solar tracking mechanism incorporating a number of practical features that give it superior environmental resilience and exceptional tracking accuracy. The mechanism comprises a lightweight space-frame assembly supporting an array of point-focus Fresnel lenses in a two-axis tracking structure. The system is enclosed under a glass cover which isolates it from environmental exposure and enhances tracking accuracy by eliminating wind loading. Tracking accuracy is also enhanced by the system's broad-based tracking support. The system's primary intended application would be to focus highly concentrated sunlight into optical fibers for transmission to core building illumination zones, and the system may also have potential for photovoltaic or photothermal solar energy conversion.

Two-axis tracking solar collector mechanism

DOEpatents

Johnson, Kenneth C.

1990-01-01

This invention is a novel solar tracking mechanism incorporating a number of practical features that give it superior environmental resilience and exceptional tracking accuracy. The mechanism comprises a lightweight space-frame assembly supporting an array of point-focus Fresnel lenses in a two-axis tracking structure. The system is enclosed under a glass cover which isolates it from environmental exposure and enhances tracking accuracy by eliminating wind loading. Tracking accuracy is also enhanced by the system's broad-based tracking support. The system's primary intended application would be to focus highly concentrated sunlight into optical fibers for transmission to core building illumination zones, and the system may also have potential for photovoltaic or photothermal solar energy conversion.

An evaluation of information retrieval accuracy with simulated OCR output

DOE Office of Scientific and Technical Information (OSTI.GOV)

Croft, W.B.; Harding, S.M.; Taghva, K.

Optical Character Recognition (OCR) is a critical part of many text-based applications. Although some commercial systems use the output from OCR devices to index documents without editing, there is very little quantitative data on the impact of OCR errors on the accuracy of a text retrieval system. Because of the difficulty of constructing test collections to obtain this data, we have carried out evaluation using simulated OCR output on a variety of databases. The results show that high quality OCR devices have little effect on the accuracy of retrieval, but low quality devices used with databases of short documents canmore » result in significant degradation.« less

Two-axis tracking solar collector mechanism

DOEpatents

Johnson, K.C.

1992-12-08

This invention is a novel solar tracking mechanism incorporating a number of practical features that give it superior environmental resilience and exceptional tracking accuracy. The mechanism comprises a lightweight space-frame assembly supporting an array of point-focus Fresnel lenses in a two-axis tracking structure. The system is enclosed under a glass cover which isolates it from environmental exposure and enhances tracking accuracy by eliminating wind loading. Tracking accuracy is also enhanced by the system's broad-based tracking support. The system's primary intended application would be to focus highly concentrated sunlight into optical fibers for transmission to core building illumination zones, and the system may also have potential for photovoltaic or photothermal solar energy conversion. 16 figs.

PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

NASA Astrophysics Data System (ADS)

Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.

2018-03-01

Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.

Automatic disease diagnosis using optimised weightless neural networks for low-power wearable devices

PubMed Central

Edla, Damodar Reddy; Kuppili, Venkatanareshbabu; Dharavath, Ramesh; Beechu, Nareshkumar Reddy

2017-01-01

Low-power wearable devices for disease diagnosis are used at anytime and anywhere. These are non-invasive and pain-free for the better quality of life. However, these devices are resource constrained in terms of memory and processing capability. Memory constraint allows these devices to store a limited number of patterns and processing constraint provides delayed response. It is a challenging task to design a robust classification system under above constraints with high accuracy. In this Letter, to resolve this problem, a novel architecture for weightless neural networks (WNNs) has been proposed. It uses variable sized random access memories to optimise the memory usage and a modified binary TRIE data structure for reducing the test time. In addition, a bio-inspired-based genetic algorithm has been employed to improve the accuracy. The proposed architecture is experimented on various disease datasets using its software and hardware realisations. The experimental results prove that the proposed architecture achieves better performance in terms of accuracy, memory saving and test time as compared to standard WNNs. It also outperforms in terms of accuracy as compared to conventional neural network-based classifiers. The proposed architecture is a powerful part of most of the low-power wearable devices for the solution of memory, accuracy and time issues. PMID:28868148

Solving the stability-accuracy-diversity dilemma of recommender systems

NASA Astrophysics Data System (ADS)

Hou, Lei; Liu, Kecheng; Liu, Jianguo; Zhang, Runtong

2017-02-01

Recommender systems are of great significance in predicting the potential interesting items based on the target user's historical selections. However, the recommendation list for a specific user has been found changing vastly when the system changes, due to the unstable quantification of item similarities, which is defined as the recommendation stability problem. To improve the similarity stability and recommendation stability is crucial for the user experience enhancement and the better understanding of user interests. While the stability as well as accuracy of recommendation could be guaranteed by recommending only popular items, studies have been addressing the necessity of diversity which requires the system to recommend unpopular items. By ranking the similarities in terms of stability and considering only the most stable ones, we present a top- n-stability method based on the Heat Conduction algorithm (denoted as TNS-HC henceforth) for solving the stability-accuracy-diversity dilemma. Experiments on four benchmark data sets indicate that the TNS-HC algorithm could significantly improve the recommendation stability and accuracy simultaneously and still retain the high-diversity nature of the Heat Conduction algorithm. Furthermore, we compare the performance of the TNS-HC algorithm with a number of benchmark recommendation algorithms. The result suggests that the TNS-HC algorithm is more efficient in solving the stability-accuracy-diversity triple dilemma of recommender systems.

Diagnostic accuracy of liver fibrosis based on red cell distribution width (RDW) to platelet ratio with fibroscan in chronic hepatitis B

NASA Astrophysics Data System (ADS)

Sembiring, J.; Jones, F.

2018-03-01

Red cell Distribution Width (RDW) and platelet ratio (RPR) can predict liver fibrosis and cirrhosis in chronic hepatitis B with relatively high accuracy. RPR was superior to other non-invasive methods to predict liver fibrosis, such as AST and ALT ratio, AST and platelet ratio Index and FIB-4. The aim of this study was to assess diagnostic accuracy liver fibrosis by using RDW and platelets ratio in chronic hepatitis B patients based on compared with Fibroscan. This cross-sectional study was conducted at Adam Malik Hospital from January-June 2015. We examine 34 patients hepatitis B chronic, screen RDW, platelet, and fibroscan. Data were statistically analyzed. The result RPR with ROC procedure has an accuracy of 72.3% (95% CI: 84.1% - 97%). In this study, the RPR had a moderate ability to predict fibrosis degree (p = 0.029 with AUC> 70%). The cutoff value RPR was 0.0591, sensitivity and spesificity were 71.4% and 60%, Positive Prediction Value (PPV) was 55.6% and Negative Predictions Value (NPV) was 75%, positive likelihood ratio was 1.79 and negative likelihood ratio was 0.48. RPR have the ability to predict the degree of liver fibrosis in chronic hepatitis B patients with moderate accuracy.

Fine-resolution repeat topographic surveying of dryland landscapes using UAS-based structure-from-motion photogrammetry: Assessing accuracy and precision against traditional ground-based erosion measurements

USGS Publications Warehouse

Gillian, Jeffrey K.; Karl, Jason W.; Elaksher, Ahmed; Duniway, Michael C.

2017-01-01

Structure-from-motion (SfM) photogrammetry from unmanned aerial system (UAS) imagery is an emerging tool for repeat topographic surveying of dryland erosion. These methods are particularly appealing due to the ability to cover large landscapes compared to field methods and at reduced costs and finer spatial resolution compared to airborne laser scanning. Accuracy and precision of high-resolution digital terrain models (DTMs) derived from UAS imagery have been explored in many studies, typically by comparing image coordinates to surveyed check points or LiDAR datasets. In addition to traditional check points, this study compared 5 cm resolution DTMs derived from fixed-wing UAS imagery with a traditional ground-based method of measuring soil surface change called erosion bridges. We assessed accuracy by comparing the elevation values between DTMs and erosion bridges along thirty topographic transects each 6.1 m long. Comparisons occurred at two points in time (June 2014, February 2015) which enabled us to assess vertical accuracy with 3314 data points and vertical precision (i.e., repeatability) with 1657 data points. We found strong vertical agreement (accuracy) between the methods (RMSE 2.9 and 3.2 cm in June 2014 and February 2015, respectively) and high vertical precision for the DTMs (RMSE 2.8 cm). Our results from comparing SfM-generated DTMs to check points, and strong agreement with erosion bridge measurements suggests repeat UAS imagery and SfM processing could replace erosion bridges for a more synoptic landscape assessment of shifting soil surfaces for some studies. However, while collecting the UAS imagery and generating the SfM DTMs for this study was faster than collecting erosion bridge measurements, technical challenges related to the need for ground control networks and image processing requirements must be addressed before this technique could be applied effectively to large landscapes.

The effect of stimulus intensity on response time and accuracy in dynamic, temporally constrained environments.

PubMed

Causer, J; McRobert, A P; Williams, A M

2013-10-01

The ability to make accurate judgments and execute effective skilled movements under severe temporal constraints are fundamental to elite performance in a number of domains including sport, military combat, law enforcement, and medicine. In two experiments, we examine the effect of stimulus strength on response time and accuracy in a temporally constrained, real-world, decision-making task. Specifically, we examine the effect of low stimulus intensity (black) and high stimulus intensity (sequin) uniform designs, worn by teammates, to determine the effect of stimulus strength on the ability of soccer players to make rapid and accurate responses. In both field- and laboratory-based scenarios, professional soccer players viewed developing patterns of play and were required to make a penetrative pass to an attacking player. Significant differences in response accuracy between uniform designs were reported in laboratory- and field-based experiments. Response accuracy was significantly higher in the sequin compared with the black uniform condition. Response times only differed between uniform designs in the laboratory-based experiment. These findings extend the literature into a real-world environment and have significant implications for the design of clothing wear in a number of domains. © 2012 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Technical Note: A respiratory monitoring and processing system based on computer vision: prototype and proof of principle.

PubMed

Leduc, Nicolas; Atallah, Vincent; Escarmant, Patrick; Vinh-Hung, Vincent

2016-09-08

Monitoring and controlling respiratory motion is a challenge for the accuracy and safety of therapeutic irradiation of thoracic tumors. Various commercial systems based on the monitoring of internal or external surrogates have been developed but remain costly. In this article we describe and validate Madibreast, an in-house-made respiratory monitoring and processing device based on optical tracking of external markers. We designed an optical apparatus to ensure real-time submillimetric image resolution at 4 m. Using OpenCv libraries, we optically tracked high-contrast markers set on patients' breasts. Validation of spatial and time accuracy was performed on a mechanical phantom and on human breast. Madibreast was able to track motion of markers up to a 5 cm/s speed, at a frame rate of 30 fps, with submillimetric accuracy on mechanical phantom and human breasts. Latency was below 100 ms. Concomitant monitoring of three different locations on the breast showed discrepancies in axial motion up to 4 mm for deep-breathing patterns. This low-cost, computer-vision system for real-time motion monitoring of the irradiation of breast cancer patients showed submillimetric accuracy and acceptable latency. It allowed the authors to highlight differences in surface motion that may be correlated to tumor motion.v. © 2016 The Authors.

Study design requirements for RNA sequencing-based breast cancer diagnostics.

PubMed

Mer, Arvind Singh; Klevebring, Daniel; Grönberg, Henrik; Rantalainen, Mattias

2016-02-01

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.

Measuring Blood Glucose Concentrations in Photometric Glucometers Requiring Very Small Sample Volumes.

PubMed

Demitri, Nevine; Zoubir, Abdelhak M

2017-01-01

Glucometers present an important self-monitoring tool for diabetes patients and, therefore, must exhibit high accuracy as well as good usability features. Based on an invasive photometric measurement principle that drastically reduces the volume of the blood sample needed from the patient, we present a framework that is capable of dealing with small blood samples, while maintaining the required accuracy. The framework consists of two major parts: 1) image segmentation; and 2) convergence detection. Step 1 is based on iterative mode-seeking methods to estimate the intensity value of the region of interest. We present several variations of these methods and give theoretical proofs of their convergence. Our approach is able to deal with changes in the number and position of clusters without any prior knowledge. Furthermore, we propose a method based on sparse approximation to decrease the computational load, while maintaining accuracy. Step 2 is achieved by employing temporal tracking and prediction, herewith decreasing the measurement time, and, thus, improving usability. Our framework is tested on several real datasets with different characteristics. We show that we are able to estimate the underlying glucose concentration from much smaller blood samples than is currently state of the art with sufficient accuracy according to the most recent ISO standards and reduce measurement time significantly compared to state-of-the-art methods.

Design and Test of a Hybrid Foot Force Sensing and GPS System for Richer User Mobility Activity Recognition

PubMed Central

Zhang, Zelun; Poslad, Stefan

2013-01-01

Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capability, i.e., they cannot recognise both human posture (during travelling) and transportation mode simultaneously, and a relatively high computational complexity. Here, a new GPS and Foot-Force (GPS + FF) sensor method is proposed to overcome these challenges that leverages a set of wearable FF sensors in combination with GPS, e.g., in a mobile phone. User mobility activities that can be recognised include both daily user postures and common transportation modes: sitting, standing, walking, cycling, bus passenger, car passenger (including private cars and taxis) and car driver. The novelty of this work is that our approach provides a more comprehensive recognition capability in terms of reliably recognising both human posture and transportation mode simultaneously during travel. In addition, by comparing the new GPS + FF method with both an ACC method (62% accuracy) and a GPS + ACC based method (70% accuracy) as baseline methods, it obtains a higher accuracy (95%) with less computational complexity, when tested on a dataset obtained from ten individuals. PMID:24189333

Static bending deflection and free vibration analysis of moderate thick symmetric laminated plates using multidimensional wave digital filters

NASA Astrophysics Data System (ADS)

Tseng, Chien-Hsun

2018-06-01

This paper aims to develop a multidimensional wave digital filtering network for predicting static and dynamic behaviors of composite laminate based on the FSDT. The resultant network is, thus, an integrated platform that can perform not only the free vibration but also the bending deflection of moderate thick symmetric laminated plates with low plate side-to-thickness ratios (< = 20). Safeguarded by the Courant-Friedrichs-Levy stability condition with the least restriction in terms of optimization technique, the present method offers numerically high accuracy, stability and efficiency to proceed a wide range of modulus ratios for the FSDT laminated plates. Instead of using a constant shear correction factor (SCF) with a limited numerical accuracy for the bending deflection, an optimum SCF is particularly sought by looking for a minimum ratio of change in the transverse shear energy. This way, it can predict as good results in terms of accuracy for certain cases of bending deflection. Extensive simulation results carried out for the prediction of maximum bending deflection have demonstratively proven that the present method outperforms those based on the higher-order shear deformation and layerwise plate theories. To the best of our knowledge, this is the first work that shows an optimal selection of SCF can significantly increase the accuracy of FSDT-based laminates especially compared to the higher order theory disclaiming any correction. The highest accuracy of overall solution is compared to the 3D elasticity equilibrium one.

Training sample selection based on self-training for liver cirrhosis classification using ultrasound images

NASA Astrophysics Data System (ADS)

Fujita, Yusuke; Mitani, Yoshihiro; Hamamoto, Yoshihiko; Segawa, Makoto; Terai, Shuji; Sakaida, Isao

2017-03-01

Ultrasound imaging is a popular and non-invasive tool used in the diagnoses of liver disease. Cirrhosis is a chronic liver disease and it can advance to liver cancer. Early detection and appropriate treatment are crucial to prevent liver cancer. However, ultrasound image analysis is very challenging, because of the low signal-to-noise ratio of ultrasound images. To achieve the higher classification performance, selection of training regions of interest (ROIs) is very important that effect to classification accuracy. The purpose of our study is cirrhosis detection with high accuracy using liver ultrasound images. In our previous works, training ROI selection by MILBoost and multiple-ROI classification based on the product rule had been proposed, to achieve high classification performance. In this article, we propose self-training method to select training ROIs effectively. Evaluation experiments were performed to evaluate effect of self-training, using manually selected ROIs and also automatically selected ROIs. Experimental results show that self-training for manually selected ROIs achieved higher classification performance than other approaches, including our conventional methods. The manually ROI definition and sample selection are important to improve classification accuracy in cirrhosis detection using ultrasound images.

Multispectral image fusion for illumination-invariant palmprint recognition

PubMed Central

Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied. PMID:28558064

Multispectral image fusion for illumination-invariant palmprint recognition.

PubMed

Lu, Longbin; Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied.

High-precision positioning system of four-quadrant detector based on the database query

NASA Astrophysics Data System (ADS)

Zhang, Xin; Deng, Xiao-guo; Su, Xiu-qin; Zheng, Xiao-qiang

2015-02-01

The fine pointing mechanism of the Acquisition, Pointing and Tracking (APT) system in free space laser communication usually use four-quadrant detector (QD) to point and track the laser beam accurately. The positioning precision of QD is one of the key factors of the pointing accuracy to APT system. A positioning system is designed based on FPGA and DSP in this paper, which can realize the sampling of AD, the positioning algorithm and the control of the fast swing mirror. We analyze the positioning error of facular center calculated by universal algorithm when the facular energy obeys Gauss distribution from the working principle of QD. A database is built by calculation and simulation with MatLab software, in which the facular center calculated by universal algorithm is corresponded with the facular center of Gaussian beam, and the database is stored in two pieces of E2PROM as the external memory of DSP. The facular center of Gaussian beam is inquiry in the database on the basis of the facular center calculated by universal algorithm in DSP. The experiment results show that the positioning accuracy of the high-precision positioning system is much better than the positioning accuracy calculated by universal algorithm.