Blurred image restoration using knife-edge function and optimal window Wiener filtering.

PubMed

Wang, Min; Zhou, Shudao; Yan, Wei

2018-01-01

Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects.

Blurred image restoration using knife-edge function and optimal window Wiener filtering

PubMed Central

Zhou, Shudao; Yan, Wei

2018-01-01

Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects. PMID:29377950

Single-view phase retrieval of an extended sample by exploiting edge detection and sparsity

DOE PAGES

Tripathi, Ashish; McNulty, Ian; Munson, Todd; ...

2016-10-14

We propose a new approach to robustly retrieve the exit wave of an extended sample from its coherent diffraction pattern by exploiting sparsity of the sample's edges. This approach enables imaging of an extended sample with a single view, without ptychography. We introduce nonlinear optimization methods that promote sparsity, and we derive update rules to robustly recover the sample's exit wave. We test these methods on simulated samples by varying the sparsity of the edge-detected representation of the exit wave. Finally, our tests illustrate the strengths and limitations of the proposed method in imaging extended samples.

Edge guided image reconstruction in linear scan CT by weighted alternating direction TV minimization.

PubMed

Cai, Ailong; Wang, Linyuan; Zhang, Hanming; Yan, Bin; Li, Lei; Xi, Xiaoqi; Li, Jianxin

2014-01-01

Linear scan computed tomography (CT) is a promising imaging configuration with high scanning efficiency while the data set is under-sampled and angularly limited for which high quality image reconstruction is challenging. In this work, an edge guided total variation minimization reconstruction (EGTVM) algorithm is developed in dealing with this problem. The proposed method is modeled on the combination of total variation (TV) regularization and iterative edge detection strategy. In the proposed method, the edge weights of intermediate reconstructions are incorporated into the TV objective function. The optimization is efficiently solved by applying alternating direction method of multipliers. A prudential and conservative edge detection strategy proposed in this paper can obtain the true edges while restricting the errors within an acceptable degree. Based on the comparison on both simulation studies and real CT data set reconstructions, EGTVM provides comparable or even better quality compared to the non-edge guided reconstruction and adaptive steepest descent-projection onto convex sets method. With the utilization of weighted alternating direction TV minimization and edge detection, EGTVM achieves fast and robust convergence and reconstructs high quality image when applied in linear scan CT with under-sampled data set.

Image enhancement of real-time television to benefit the visually impaired.

PubMed

Wolffsohn, James S; Mukhopadhyay, Ditipriya; Rubinstein, Martin

2007-09-01

To examine the use of real-time, generic edge detection, image processing techniques to enhance the television viewing of the visually impaired. Prospective, clinical experimental study. One hundred and two sequential visually impaired (average age 73.8 +/- 14.8 years; 59% female) in a single center optimized a dynamic television image with respect to edge detection filter (Prewitt, Sobel, or the two combined), color (red, green, blue, or white), and intensity (one to 15 times) of the overlaid edges. They then rated the original television footage compared with a black-and-white image displaying the edges detected and the original television image with the detected edges overlaid in the chosen color and at the intensity selected. Footage of news, an advertisement, and the end of program credits were subjectively assessed in a random order. A Prewitt filter was preferred (44%) compared with the Sobel filter (27%) or a combination of the two (28%). Green and white were equally popular for displaying the detected edges (32%), with blue (22%) and red (14%) less so. The average preferred edge intensity was 3.5 +/- 1.7 times. The image-enhanced television was significantly preferred to the original (P < .001), which in turn was preferred to viewing the detected edges alone (P < .001) for each of the footage clips. Preference was not dependent on the condition causing visual impairment. Seventy percent were definitely willing to buy a set-top box that could achieve these effects for a reasonable price. Simple generic edge detection image enhancement options can be performed on television in real-time and significantly enhance the viewing of the visually impaired.

Combined optimization of image-gathering and image-processing systems for scene feature detection

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Arduini, Robert F.; Samms, Richard W.

1987-01-01

The relationship between the image gathering and image processing systems for minimum mean squared error estimation of scene characteristics is investigated. A stochastic optimization problem is formulated where the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled and noisy image data. An analytical solution for the optimal characteristic image processor is developed. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristic is scene restoration. Optimal edge detection is investigated using the Laplacian operator x G as the desired characteristic, where G is a two dimensional Gaussian distribution function. It is shown that the optimal edge detector compensates for the blurring introduced by the image gathering optics, and notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition. The optimal image gathering optical transfer function is also investigated and the results of a sensitivity analysis are shown.

The optimization of edge and line detectors for forest image analysis

Treesearch

Zhiling Long; Joseph Picone; Victor A. Rudis

2000-01-01

Automated image analysis for forestry applications is becoming increasingly important with the rapid evolution of satellite and land-based remote imaging industries. Features derived from line information play a very important role in analyses of such images. Many edge and line detection algorithms have been proposed but few, if any, comprehensive studies exist that...

Parallel Hough Transform-Based Straight Line Detection and Its FPGA Implementation in Embedded Vision

PubMed Central

Lu, Xiaofeng; Song, Li; Shen, Sumin; He, Kang; Yu, Songyu; Ling, Nam

2013-01-01

Hough Transform has been widely used for straight line detection in low-definition and still images, but it suffers from execution time and resource requirements. Field Programmable Gate Arrays (FPGA) provide a competitive alternative for hardware acceleration to reap tremendous computing performance. In this paper, we propose a novel parallel Hough Transform (PHT) and FPGA architecture-associated framework for real-time straight line detection in high-definition videos. A resource-optimized Canny edge detection method with enhanced non-maximum suppression conditions is presented to suppress most possible false edges and obtain more accurate candidate edge pixels for subsequent accelerated computation. Then, a novel PHT algorithm exploiting spatial angle-level parallelism is proposed to upgrade computational accuracy by improving the minimum computational step. Moreover, the FPGA based multi-level pipelined PHT architecture optimized by spatial parallelism ensures real-time computation for 1,024 × 768 resolution videos without any off-chip memory consumption. This framework is evaluated on ALTERA DE2-115 FPGA evaluation platform at a maximum frequency of 200 MHz, and it can calculate straight line parameters in 15.59 ms on the average for one frame. Qualitative and quantitative evaluation results have validated the system performance regarding data throughput, memory bandwidth, resource, speed and robustness. PMID:23867746

Parallel Hough Transform-based straight line detection and its FPGA implementation in embedded vision.

PubMed

Lu, Xiaofeng; Song, Li; Shen, Sumin; He, Kang; Yu, Songyu; Ling, Nam

2013-07-17

Hough Transform has been widely used for straight line detection in low-definition and still images, but it suffers from execution time and resource requirements. Field Programmable Gate Arrays (FPGA) provide a competitive alternative for hardware acceleration to reap tremendous computing performance. In this paper, we propose a novel parallel Hough Transform (PHT) and FPGA architecture-associated framework for real-time straight line detection in high-definition videos. A resource-optimized Canny edge detection method with enhanced non-maximum suppression conditions is presented to suppress most possible false edges and obtain more accurate candidate edge pixels for subsequent accelerated computation. Then, a novel PHT algorithm exploiting spatial angle-level parallelism is proposed to upgrade computational accuracy by improving the minimum computational step. Moreover, the FPGA based multi-level pipelined PHT architecture optimized by spatial parallelism ensures real-time computation for 1,024 × 768 resolution videos without any off-chip memory consumption. This framework is evaluated on ALTERA DE2-115 FPGA evaluation platform at a maximum frequency of 200 MHz, and it can calculate straight line parameters in 15.59 ms on the average for one frame. Qualitative and quantitative evaluation results have validated the system performance regarding data throughput, memory bandwidth, resource, speed and robustness.

Optimization of oligonucleotide arrays and RNA amplification protocols for analysis of transcript structure and alternative splicing.

PubMed

Castle, John; Garrett-Engele, Phil; Armour, Christopher D; Duenwald, Sven J; Loerch, Patrick M; Meyer, Michael R; Schadt, Eric E; Stoughton, Roland; Parrish, Mark L; Shoemaker, Daniel D; Johnson, Jason M

2003-01-01

Microarrays offer a high-resolution means for monitoring pre-mRNA splicing on a genomic scale. We have developed a novel, unbiased amplification protocol that permits labeling of entire transcripts. Also, hybridization conditions, probe characteristics, and analysis algorithms were optimized for detection of exons, exon-intron edges, and exon junctions. These optimized protocols can be used to detect small variations and isoform mixtures, map the tissue specificity of known human alternative isoforms, and provide a robust, scalable platform for high-throughput discovery of alternative splicing.

Optimization of oligonucleotide arrays and RNA amplification protocols for analysis of transcript structure and alternative splicing

PubMed Central

Castle, John; Garrett-Engele, Phil; Armour, Christopher D; Duenwald, Sven J; Loerch, Patrick M; Meyer, Michael R; Schadt, Eric E; Stoughton, Roland; Parrish, Mark L; Shoemaker, Daniel D; Johnson, Jason M

2003-01-01

Microarrays offer a high-resolution means for monitoring pre-mRNA splicing on a genomic scale. We have developed a novel, unbiased amplification protocol that permits labeling of entire transcripts. Also, hybridization conditions, probe characteristics, and analysis algorithms were optimized for detection of exons, exon-intron edges, and exon junctions. These optimized protocols can be used to detect small variations and isoform mixtures, map the tissue specificity of known human alternative isoforms, and provide a robust, scalable platform for high-throughput discovery of alternative splicing. PMID:14519201

Experimental study on the crack detection with optimized spatial wavelet analysis and windowing

NASA Astrophysics Data System (ADS)

Ghanbari Mardasi, Amir; Wu, Nan; Wu, Christine

2018-05-01

In this paper, a high sensitive crack detection is experimentally realized and presented on a beam under certain deflection by optimizing spatial wavelet analysis. Due to the crack existence in the beam structure, a perturbation/slop singularity is induced in the deflection profile. Spatial wavelet transformation works as a magnifier to amplify the small perturbation signal at the crack location to detect and localize the damage. The profile of a deflected aluminum cantilever beam is obtained for both intact and cracked beams by a high resolution laser profile sensor. Gabor wavelet transformation is applied on the subtraction of intact and cracked data sets. To improve detection sensitivity, scale factor in spatial wavelet transformation and the transformation repeat times are optimized. Furthermore, to detect the possible crack close to the measurement boundaries, wavelet transformation edge effect, which induces large values of wavelet coefficient around the measurement boundaries, is efficiently reduced by introducing different windowing functions. The result shows that a small crack with depth of less than 10% of the beam height can be localized with a clear perturbation. Moreover, the perturbation caused by a crack at 0.85 mm away from one end of the measurement range, which is covered by wavelet transform edge effect, emerges by applying proper window functions.

Detecting Faults in Southern California using Computer-Vision Techniques and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) Interferometry

NASA Astrophysics Data System (ADS)

Barba, M.; Rains, C.; von Dassow, W.; Parker, J. W.; Glasscoe, M. T.

2013-12-01

Knowing the location and behavior of active faults is essential for earthquake hazard assessment and disaster response. In Interferometric Synthetic Aperture Radar (InSAR) images, faults are revealed as linear discontinuities. Currently, interferograms are manually inspected to locate faults. During the summer of 2013, the NASA-JPL DEVELOP California Disasters team contributed to the development of a method to expedite fault detection in California using remote-sensing technology. The team utilized InSAR images created from polarimetric L-band data from NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) project. A computer-vision technique known as 'edge-detection' was used to automate the fault-identification process. We tested and refined an edge-detection algorithm under development through NASA's Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) project. To optimize the algorithm we used both UAVSAR interferograms and synthetic interferograms generated through Disloc, a web-based modeling program available through NASA's QuakeSim project. The edge-detection algorithm detected seismic, aseismic, and co-seismic slip along faults that were identified and compared with databases of known fault systems. Our optimization process was the first step toward integration of the edge-detection code into E-DECIDER to provide decision support for earthquake preparation and disaster management. E-DECIDER partners that will use the edge-detection code include the California Earthquake Clearinghouse and the US Department of Homeland Security through delivery of products using the Unified Incident Command and Decision Support (UICDS) service. Through these partnerships, researchers, earthquake disaster response teams, and policy-makers will be able to use this new methodology to examine the details of ground and fault motions for moderate to large earthquakes. Following an earthquake, the newly discovered faults can be paired with infrastructure overlays, allowing emergency response teams to identify sites that may have been exposed to damage. The faults will also be incorporated into a database for future integration into fault models and earthquake simulations, improving future earthquake hazard assessment. As new faults are mapped, they will further understanding of the complex fault systems and earthquake hazards within the seismically dynamic state of California.

Information theoretic analysis of edge detection in visual communication

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2010-08-01

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the artifacts introduced into the process by the image gathering process. However, experiments show that the image gathering process profoundly impacts the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. In this paper, we perform an end-to-end information theory based system analysis to assess edge detection methods. We evaluate the performance of the different algorithms as a function of the characteristics of the scene, and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge detection algorithm is regarded to have high performance only if the information rate from the scene to the edge approaches the maximum possible. This goal can be achieved only by jointly optimizing all processes. People generally use subjective judgment to compare different edge detection methods. There is not a common tool that can be used to evaluate the performance of the different algorithms, and to give people a guide for selecting the best algorithm for a given system or scene. Our information-theoretic assessment becomes this new tool to which allows us to compare the different edge detection operators in a common environment.

First Order Statistics of Speckle around a Scatterer Volume Density Edge and Edge Detection in Ultrasound Images.

NASA Astrophysics Data System (ADS)

Li, Yue

1990-01-01

Ultrasonic imaging plays an important role in medical imaging. But the images exhibit a granular structure, commonly known as speckle. The speckle tends to mask the presence of low-contrast lesions and reduces the ability of a human observer to resolve fine details. Our interest in this research is to examine the problem of edge detection and come up with methods for improving the visualization of organ boundaries and tissue inhomogeneity edges. An edge in an image can be formed either by acoustic impedance change or by scatterer volume density change (or both). The echo produced from these two kinds of edges has different properties. In this work, it has been proved that the echo from a scatterer volume density edge is the Hilbert transform of the echo from a rough impedance boundary (except for a constant) under certain conditions. This result can be used for choosing the correct signal to transmit to optimize the performance of edge detectors and characterizing an edge. The signal to noise ratio of the echo produced by a scatterer volume density edge is also obtained. It is found that: (1) By transmitting a signal with high bandwidth ratio and low center frequency, one can obtain a higher signal to noise ratio. (2) For large area edges, the farther the transducer is from the edge, the larger is the signal to noise ratio. But for small area edges, the nearer the transducer is to the edge, the larger is the signal to noise ratio. These results enable us to maximize the signal to noise ratio by adjusting these parameters. (3) The signal to noise ratio is not only related to the ratio of scatterer volume densities at the edge, but also related to the absolute value of scatterer volume densities. Some of these results have been proved through simulation and experiment. Different edge detection methods have been used to detect simulated scatterer volume density edges to compare their performance. A so-called interlaced array method has been developed for speckle reduction in the images formed by synthetic aperture focussing technique, and experiments have been done to evaluate its performance.

Information theoretic analysis of linear shift-invariant edge-detection operators

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2012-06-01

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the influences by the image gathering process. However, experiments show that the image gathering process has a profound impact on the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. We perform an end-to-end information theory based system analysis to assess linear shift-invariant edge-detection algorithms. We evaluate the performance of the different algorithms as a function of the characteristics of the scene and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge-detection algorithm is regarded as having high performance only if the information rate from the scene to the edge image approaches its maximum possible. This goal can be achieved only by jointly optimizing all processes. Our information-theoretic assessment provides a new tool that allows us to compare different linear shift-invariant edge detectors in a common environment.

Network Community Detection based on the Physarum-inspired Computational Framework.

PubMed

Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili

2016-12-13

Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.

Optimization of entanglement witnesses

NASA Astrophysics Data System (ADS)

Lewenstein, M.; Kraus, B.; Cirac, J. I.; Horodecki, P.

2000-11-01

An entanglement witness (EW) is an operator that allows the detection of entangled states. We give necessary and sufficient conditions for such operators to be optimal, i.e., to detect entangled states in an optimal way. We show how to optimize general EW, and then we particularize our results to the nondecomposable ones; the latter are those that can detect positive partial transpose entangled states (PPTES's). We also present a method to systematically construct and optimize this last class of operators based on the existence of ``edge'' PPTES's, i.e., states that violate the range separability criterion [Phys. Lett. A 232, 333 (1997)] in an extreme manner. This method also permits a systematic construction of nondecomposable positive maps (PM's). Our results lead to a sufficient condition for entanglement in terms of nondecomposable EW's and PM's. Finally, we illustrate our results by constructing optimal EW acting on H=C2⊗C4. The corresponding PM's constitute examples of PM's with minimal ``qubit'' domains, or-equivalently-minimal Hermitian conjugate codomains.

Edge geometry effects on resonance response of electroplated cylindrical Ni/PZT/Ni magnetoelectric composites

NASA Astrophysics Data System (ADS)

Yakubov, Vladislav; Xu, Lirong; Volinsky, Alex A.; Qiao, Lijie; Pan, De'an

2017-08-01

Trilayer Ni/PZT/Ni cylindrical magnetoelectric (ME) composites were prepared by electrodeposition, a process, which creates sub-millimeter raised edges due to current concentration near sharp points. The ME response in both axial and vertical modes was measured with the edges, with only outer edges removed, and with both outer and inner edges removed. The ME voltage coefficient improved at resonance by 40% and 147% without the edges in the vertical and axial modes, respectively. The observed improvements in three different samples were only present at the ME resonance and no changes were detected outside of the ME resonance. Mechanical quality factor at resonance also improved with no effect on the resonant frequency. Experimentally demonstrated minor geometry changes resulted in substantial ME improvement at resonant frequency. This study demonstrates device performance optimization. The observed effects have been attributed to improved vibrations in terms of decreased damping coefficient and enhanced vibration amplitude at resonance.

Spatial heterogeneity of type I error for local cluster detection tests

PubMed Central

2014-01-01

Background Just as power, type I error of cluster detection tests (CDTs) should be spatially assessed. Indeed, CDTs’ type I error and power have both a spatial component as CDTs both detect and locate clusters. In the case of type I error, the spatial distribution of wrongly detected clusters (WDCs) can be particularly affected by edge effect. This simulation study aims to describe the spatial distribution of WDCs and to confirm and quantify the presence of edge effect. Methods A simulation of 40 000 datasets has been performed under the null hypothesis of risk homogeneity. The simulation design used realistic parameters from survey data on birth defects, and in particular, two baseline risks. The simulated datasets were analyzed using the Kulldorff’s spatial scan as a commonly used test whose behavior is otherwise well known. To describe the spatial distribution of type I error, we defined the participation rate for each spatial unit of the region. We used this indicator in a new statistical test proposed to confirm, as well as quantify, the edge effect. Results The predefined type I error of 5% was respected for both baseline risks. Results showed strong edge effect in participation rates, with a descending gradient from center to edge, and WDCs more often centrally situated. Conclusions In routine analysis of real data, clusters on the edge of the region should be carefully considered as they rarely occur when there is no cluster. Further work is needed to combine results from power studies with this work in order to optimize CDTs performance. PMID:24885343

Edge printability: techniques used to evaluate and improve extreme wafer edge printability

NASA Astrophysics Data System (ADS)

Roberts, Bill; Demmert, Cort; Jekauc, Igor; Tiffany, Jason P.

2004-05-01

The economics of semiconductor manufacturing have forced process engineers to develop techniques to increase wafer yield. Improvements in process controls and uniformities in all areas of the fab have reduced film thickness variations at the very edge of the wafer surface. This improved uniformity has provided the opportunity to consider decreasing edge exclusions, and now the outermost extents of the wafer must be considered in the yield model and expectations. These changes have increased the requirements on lithography to improve wafer edge printability in areas that previously were not even coated. This has taxed all software and hardware components used in defining the optical focal plane at the wafer edge. We have explored techniques to determine the capabilities of extreme wafer edge printability and the components of the systems that influence this printability. We will present current capabilities and new detection techniques and the influence that the individual hardware and software components have on edge printability. We will show effects of focus sensor designs, wafer layout, utilization of dummy edge fields, the use of non-zero overlay targets and chemical/optical edge bead optimization.

Online Community Detection for Large Complex Networks

PubMed Central

Pan, Gang; Zhang, Wangsheng; Wu, Zhaohui; Li, Shijian

2014-01-01

Complex networks describe a wide range of systems in nature and society. To understand complex networks, it is crucial to investigate their community structure. In this paper, we develop an online community detection algorithm with linear time complexity for large complex networks. Our algorithm processes a network edge by edge in the order that the network is fed to the algorithm. If a new edge is added, it just updates the existing community structure in constant time, and does not need to re-compute the whole network. Therefore, it can efficiently process large networks in real time. Our algorithm optimizes expected modularity instead of modularity at each step to avoid poor performance. The experiments are carried out using 11 public data sets, and are measured by two criteria, modularity and NMI (Normalized Mutual Information). The results show that our algorithm's running time is less than the commonly used Louvain algorithm while it gives competitive performance. PMID:25061683

Text, photo, and line extraction in scanned documents

NASA Astrophysics Data System (ADS)

Erkilinc, M. Sezer; Jaber, Mustafa; Saber, Eli; Bauer, Peter; Depalov, Dejan

2012-07-01

We propose a page layout analysis algorithm to classify a scanned document into different regions such as text, photo, or strong lines. The proposed scheme consists of five modules. The first module performs several image preprocessing techniques such as image scaling, filtering, color space conversion, and gamma correction to enhance the scanned image quality and reduce the computation time in later stages. Text detection is applied in the second module wherein wavelet transform and run-length encoding are employed to generate and validate text regions, respectively. The third module uses a Markov random field based block-wise segmentation that employs a basis vector projection technique with maximum a posteriori probability optimization to detect photo regions. In the fourth module, methods for edge detection, edge linking, line-segment fitting, and Hough transform are utilized to detect strong edges and lines. In the last module, the resultant text, photo, and edge maps are combined to generate a page layout map using K-Means clustering. The proposed algorithm has been tested on several hundred documents that contain simple and complex page layout structures and contents such as articles, magazines, business cards, dictionaries, and newsletters, and compared against state-of-the-art page-segmentation techniques with benchmark performance. The results indicate that our methodology achieves an average of ˜89% classification accuracy in text, photo, and background regions.

Visual information processing II; Proceedings of the Meeting, Orlando, FL, Apr. 14-16, 1993

NASA Technical Reports Server (NTRS)

Huck, Friedrich O. (Editor); Juday, Richard D. (Editor)

1993-01-01

Various papers on visual information processing are presented. Individual topics addressed include: aliasing as noise, satellite image processing using a hammering neural network, edge-detetion method using visual perception, adaptive vector median filters, design of a reading test for low-vision image warping, spatial transformation architectures, automatic image-enhancement method, redundancy reduction in image coding, lossless gray-scale image compression by predictive GDF, information efficiency in visual communication, optimizing JPEG quantization matrices for different applications, use of forward error correction to maintain image fidelity, effect of peanoscanning on image compression. Also discussed are: computer vision for autonomous robotics in space, optical processor for zero-crossing edge detection, fractal-based image edge detection, simulation of the neon spreading effect by bandpass filtering, wavelet transform (WT) on parallel SIMD architectures, nonseparable 2D wavelet image representation, adaptive image halftoning based on WT, wavelet analysis of global warming, use of the WT for signal detection, perfect reconstruction two-channel rational filter banks, N-wavelet coding for pattern classification, simulation of image of natural objects, number-theoretic coding for iconic systems.

Optimization of Visual Information Presentation for Visual Prosthesis.

PubMed

Guo, Fei; Yang, Yuan; Gao, Yong

2018-01-01

Visual prosthesis applying electrical stimulation to restore visual function for the blind has promising prospects. However, due to the low resolution, limited visual field, and the low dynamic range of the visual perception, huge loss of information occurred when presenting daily scenes. The ability of object recognition in real-life scenarios is severely restricted for prosthetic users. To overcome the limitations, optimizing the visual information in the simulated prosthetic vision has been the focus of research. This paper proposes two image processing strategies based on a salient object detection technique. The two processing strategies enable the prosthetic implants to focus on the object of interest and suppress the background clutter. Psychophysical experiments show that techniques such as foreground zooming with background clutter removal and foreground edge detection with background reduction have positive impacts on the task of object recognition in simulated prosthetic vision. By using edge detection and zooming technique, the two processing strategies significantly improve the recognition accuracy of objects. We can conclude that the visual prosthesis using our proposed strategy can assist the blind to improve their ability to recognize objects. The results will provide effective solutions for the further development of visual prosthesis.

Optimization of Visual Information Presentation for Visual Prosthesis

PubMed Central

Gao, Yong

2018-01-01

Visual prosthesis applying electrical stimulation to restore visual function for the blind has promising prospects. However, due to the low resolution, limited visual field, and the low dynamic range of the visual perception, huge loss of information occurred when presenting daily scenes. The ability of object recognition in real-life scenarios is severely restricted for prosthetic users. To overcome the limitations, optimizing the visual information in the simulated prosthetic vision has been the focus of research. This paper proposes two image processing strategies based on a salient object detection technique. The two processing strategies enable the prosthetic implants to focus on the object of interest and suppress the background clutter. Psychophysical experiments show that techniques such as foreground zooming with background clutter removal and foreground edge detection with background reduction have positive impacts on the task of object recognition in simulated prosthetic vision. By using edge detection and zooming technique, the two processing strategies significantly improve the recognition accuracy of objects. We can conclude that the visual prosthesis using our proposed strategy can assist the blind to improve their ability to recognize objects. The results will provide effective solutions for the further development of visual prosthesis. PMID:29731769

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

Tripathi, Ashish; McNulty, Ian; Munson, Todd

We propose a new approach to robustly retrieve the exit wave of an extended sample from its coherent diffraction pattern by exploiting sparsity of the sample's edges. This approach enables imaging of an extended sample with a single view, without ptychography. We introduce nonlinear optimization methods that promote sparsity, and we derive update rules to robustly recover the sample's exit wave. We test these methods on simulated samples by varying the sparsity of the edge-detected representation of the exit wave. Finally, our tests illustrate the strengths and limitations of the proposed method in imaging extended samples.

Network community-detection enhancement by proper weighting

NASA Astrophysics Data System (ADS)

Khadivi, Alireza; Ajdari Rad, Ali; Hasler, Martin

2011-04-01

In this paper, we show how proper assignment of weights to the edges of a complex network can enhance the detection of communities and how it can circumvent the resolution limit and the extreme degeneracy problems associated with modularity. Our general weighting scheme takes advantage of graph theoretic measures and it introduces two heuristics for tuning its parameters. We use this weighting as a preprocessing step for the greedy modularity optimization algorithm of Newman to improve its performance. The result of the experiments of our approach on computer-generated and real-world data networks confirm that the proposed approach not only mitigates the problems of modularity but also improves the modularity optimization.

Deep convolutional networks for automated detection of posterior-element fractures on spine CT

NASA Astrophysics Data System (ADS)

Roth, Holger R.; Wang, Yinong; Yao, Jianhua; Lu, Le; Burns, Joseph E.; Summers, Ronald M.

2016-03-01

Injuries of the spine, and its posterior elements in particular, are a common occurrence in trauma patients, with potentially devastating consequences. Computer-aided detection (CADe) could assist in the detection and classification of spine fractures. Furthermore, CAD could help assess the stability and chronicity of fractures, as well as facilitate research into optimization of treatment paradigms. In this work, we apply deep convolutional networks (ConvNets) for the automated detection of posterior element fractures of the spine. First, the vertebra bodies of the spine with its posterior elements are segmented in spine CT using multi-atlas label fusion. Then, edge maps of the posterior elements are computed. These edge maps serve as candidate regions for predicting a set of probabilities for fractures along the image edges using ConvNets in a 2.5D fashion (three orthogonal patches in axial, coronal and sagittal planes). We explore three different methods for training the ConvNet using 2.5D patches along the edge maps of `positive', i.e. fractured posterior-elements and `negative', i.e. non-fractured elements. An experienced radiologist retrospectively marked the location of 55 displaced posterior-element fractures in 18 trauma patients. We randomly split the data into training and testing cases. In testing, we achieve an area-under-the-curve of 0.857. This corresponds to 71% or 81% sensitivities at 5 or 10 false-positives per patient, respectively. Analysis of our set of trauma patients demonstrates the feasibility of detecting posterior-element fractures in spine CT images using computer vision techniques such as deep convolutional networks.

Rigid shape matching by segmentation averaging.

PubMed

Wang, Hongzhi; Oliensis, John

2010-04-01

We use segmentations to match images by shape. The new matching technique does not require point-to-point edge correspondence and is robust to small shape variations and spatial shifts. To address the unreliability of segmentations computed bottom-up, we give a closed form approximation to an average over all segmentations. Our method has many extensions, yielding new algorithms for tracking, object detection, segmentation, and edge-preserving smoothing. For segmentation, instead of a maximum a posteriori approach, we compute the "central" segmentation minimizing the average distance to all segmentations of an image. For smoothing, instead of smoothing images based on local structures, we smooth based on the global optimal image structures. Our methods for segmentation, smoothing, and object detection perform competitively, and we also show promising results in shape-based tracking.

Multi-exponential analysis of magnitude MR images using a quantitative multispectral edge-preserving filter.

PubMed

Bonny, Jean Marie; Boespflug-Tanguly, Odile; Zanca, Michel; Renou, Jean Pierre

2003-03-01

A solution for discrete multi-exponential analysis of T(2) relaxation decay curves obtained in current multi-echo imaging protocol conditions is described. We propose a preprocessing step to improve the signal-to-noise ratio and thus lower the signal-to-noise ratio threshold from which a high percentage of true multi-exponential detection is detected. It consists of a multispectral nonlinear edge-preserving filter that takes into account the signal-dependent Rician distribution of noise affecting magnitude MR images. Discrete multi-exponential decomposition, which requires no a priori knowledge, is performed by a non-linear least-squares procedure initialized with estimates obtained from a total least-squares linear prediction algorithm. This approach was validated and optimized experimentally on simulated data sets of normal human brains.

Injection current minimization of InAs/InGaAs quantum dot laser by optimization of its active region and reflectivity of laser cavity edges

NASA Astrophysics Data System (ADS)

Korenev, V. V.; Savelyev, A. V.; Zhukov, A. E.; Maximov, M. V.

2015-11-01

The ways to optimize key parameters of active region and edge reflectivity of edge- emitting semiconductor quantum dot laser are provided. It is shown that in the case of optimal cavity length and sufficiently large dispersion lasing spectrum of a given width can be obtained at injection current up to an order of magnitude lower in comparison to non-optimized sample. The influence of internal loss and edge reflection is also studied in details.

Extensions of algebraic image operators: An approach to model-based vision

NASA Technical Reports Server (NTRS)

Lerner, Bao-Ting; Morelli, Michael V.

1990-01-01

Researchers extend their previous research on a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets. Addition and multiplication are defined for the set of all grey-level images, which can then be described as polynomials of two variables. Utilizing this new algebraic structure, researchers devised an innovative, efficient edge detection scheme. An accurate method for deriving gradient component information from this edge detector is presented. Based upon this new edge detection system researchers developed a robust method for linear feature extraction by combining the techniques of a Hough transform and a line follower. The major advantage of this feature extractor is its general, object-independent nature. Target attributes, such as line segment lengths, intersections, angles of intersection, and endpoints are derived by the feature extraction algorithm and employed during model matching. The algebraic operators are global operations which are easily reconfigured to operate on any size or shape region. This provides a natural platform from which to pursue dynamic scene analysis. A method for optimizing the linear feature extractor which capitalizes on the spatially reconfiguration nature of the edge detector/gradient component operator is discussed.

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.

Page layout analysis and classification for complex scanned documents

NASA Astrophysics Data System (ADS)

Erkilinc, M. Sezer; Jaber, Mustafa; Saber, Eli; Bauer, Peter; Depalov, Dejan

2011-09-01

A framework for region/zone classification in color and gray-scale scanned documents is proposed in this paper. The algorithm includes modules for extracting text, photo, and strong edge/line regions. Firstly, a text detection module which is based on wavelet analysis and Run Length Encoding (RLE) technique is employed. Local and global energy maps in high frequency bands of the wavelet domain are generated and used as initial text maps. Further analysis using RLE yields a final text map. The second module is developed to detect image/photo and pictorial regions in the input document. A block-based classifier using basis vector projections is employed to identify photo candidate regions. Then, a final photo map is obtained by applying probabilistic model based on Markov random field (MRF) based maximum a posteriori (MAP) optimization with iterated conditional mode (ICM). The final module detects lines and strong edges using Hough transform and edge-linkages analysis, respectively. The text, photo, and strong edge/line maps are combined to generate a page layout classification of the scanned target document. Experimental results and objective evaluation show that the proposed technique has a very effective performance on variety of simple and complex scanned document types obtained from MediaTeam Oulu document database. The proposed page layout classifier can be used in systems for efficient document storage, content based document retrieval, optical character recognition, mobile phone imagery, and augmented reality.

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images

PubMed Central

Wang, Yuliang; Zhang, Zaicheng; Wang, Huimin; Bi, Shusheng

2015-01-01

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells. PMID:26066315

LROC assessment of non-linear filtering methods in Ga-67 SPECT imaging

NASA Astrophysics Data System (ADS)

De Clercq, Stijn; Staelens, Steven; De Beenhouwer, Jan; D'Asseler, Yves; Lemahieu, Ignace

2006-03-01

In emission tomography, iterative reconstruction is usually followed by a linear smoothing filter to make such images more appropriate for visual inspection and diagnosis by a physician. This will result in a global blurring of the images, smoothing across edges and possibly discarding valuable image information for detection tasks. The purpose of this study is to investigate which possible advantages a non-linear, edge-preserving postfilter could have on lesion detection in Ga-67 SPECT imaging. Image quality can be defined based on the task that has to be performed on the image. This study used LROC observer studies based on a dataset created by CPU-intensive Gate Monte Carlo simulations of a voxelized digital phantom. The filters considered in this study were a linear Gaussian filter, a bilateral filter, the Perona-Malik anisotropic diffusion filter and the Catte filtering scheme. The 3D MCAT software phantom was used to simulate the distribution of Ga-67 citrate in the abdomen. Tumor-present cases had a 1-cm diameter tumor randomly placed near the edges of the anatomical boundaries of the kidneys, bone, liver and spleen. Our data set was generated out of a single noisy background simulation using the bootstrap method, to significantly reduce the simulation time and to allow for a larger observer data set. Lesions were simulated separately and added to the background afterwards. These were then reconstructed with an iterative approach, using a sufficiently large number of MLEM iterations to establish convergence. The output of a numerical observer was used in a simplex optimization method to estimate an optimal set of parameters for each postfilter. No significant improvement was found for using edge-preserving filtering techniques over standard linear Gaussian filtering.

Swarm Intelligence for Optimizing Hybridized Smoothing Filter in Image Edge Enhancement

NASA Astrophysics Data System (ADS)

Rao, B. Tirumala; Dehuri, S.; Dileep, M.; Vindhya, A.

In this modern era, image transmission and processing plays a major role. It would be impossible to retrieve information from satellite and medical images without the help of image processing techniques. Edge enhancement is an image processing step that enhances the edge contrast of an image or video in an attempt to improve its acutance. Edges are the representations of the discontinuities of image intensity functions. For processing these discontinuities in an image, a good edge enhancement technique is essential. The proposed work uses a new idea for edge enhancement using hybridized smoothening filters and we introduce a promising technique of obtaining best hybrid filter using swarm algorithms (Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)) to search for an optimal sequence of filters from among a set of rather simple, representative image processing filters. This paper deals with the analysis of the swarm intelligence techniques through the combination of hybrid filters generated by these algorithms for image edge enhancement.

CNNEDGEPOT: CNN based edge detection of 2D near surface potential field data

NASA Astrophysics Data System (ADS)

Aydogan, D.

2012-09-01

All anomalies are important in the interpretation of gravity and magnetic data because they indicate some important structural features. One of the advantages of using gravity or magnetic data for searching contacts is to be detected buried structures whose signs could not be seen on the surface. In this paper, a general view of the cellular neural network (CNN) method with a large scale nonlinear circuit is presented focusing on its image processing applications. The proposed CNN model is used consecutively in order to extract body and body edges. The algorithm is a stochastic image processing method based on close neighborhood relationship of the cells and optimization of A, B and I matrices entitled as cloning template operators. Setting up a CNN (continues time cellular neural network (CTCNN) or discrete time cellular neural network (DTCNN)) for a particular task needs a proper selection of cloning templates which determine the dynamics of the method. The proposed algorithm is used for image enhancement and edge detection. The proposed method is applied on synthetic and field data generated for edge detection of near-surface geological bodies that mask each other in various depths and dimensions. The program named as CNNEDGEPOT is a set of functions written in MATLAB software. The GUI helps the user to easily change all the required CNN model parameters. A visual evaluation of the outputs due to DTCNN and CTCNN are carried out and the results are compared with each other. These examples demonstrate that in detecting the geological features the CNN model can be used for visual interpretation of near surface gravity or magnetic anomaly maps.

Edge detection and localization with edge pattern analysis and inflection characterization

NASA Astrophysics Data System (ADS)

Jiang, Bo

2012-05-01

In general edges are considered to be abrupt changes or discontinuities in two dimensional image signal intensity distributions. The accuracy of front-end edge detection methods in image processing impacts the eventual success of higher level pattern analysis downstream. To generalize edge detectors designed from a simple ideal step function model to real distortions in natural images, research on one dimensional edge pattern analysis to improve the accuracy of edge detection and localization proposes an edge detection algorithm, which is composed by three basic edge patterns, such as ramp, impulse, and step. After mathematical analysis, general rules for edge representation based upon the classification of edge types into three categories-ramp, impulse, and step (RIS) are developed to reduce detection and localization errors, especially reducing "double edge" effect that is one important drawback to the derivative method. But, when applying one dimensional edge pattern in two dimensional image processing, a new issue is naturally raised that the edge detector should correct marking inflections or junctions of edges. Research on human visual perception of objects and information theory pointed out that a pattern lexicon of "inflection micro-patterns" has larger information than a straight line. Also, research on scene perception gave an idea that contours have larger information are more important factor to determine the success of scene categorization. Therefore, inflections or junctions are extremely useful features, whose accurate description and reconstruction are significant in solving correspondence problems in computer vision. Therefore, aside from adoption of edge pattern analysis, inflection or junction characterization is also utilized to extend traditional derivative edge detection algorithm. Experiments were conducted to test my propositions about edge detection and localization accuracy improvements. The results support the idea that these edge detection method improvements are effective in enhancing the accuracy of edge detection and localization.

Edge detection - Image-plane versus digital processing

NASA Technical Reports Server (NTRS)

Huck, Friedrich O.; Fales, Carl L.; Park, Stephen K.; Triplett, Judith A.

1987-01-01

To optimize edge detection with the familiar Laplacian-of-Gaussian operator, it has become common to implement this operator with a large digital convolution mask followed by some interpolation of the processed data to determine the zero crossings that locate edges. It is generally recognized that this large mask causes substantial blurring of fine detail. It is shown that the spatial detail can be improved by a factor of about four with either the Wiener-Laplacian-of-Gaussian filter or an image-plane processor. The Wiener-Laplacian-of-Gaussian filter minimizes the image-gathering degradations if the scene statistics are at least approximately known and also serves as an interpolator to determine the desired zero crossings directly. The image-plane processor forms the Laplacian-of-Gaussian response by properly combining the optical design of the image-gathering system with a minimal three-by-three lateral-inhibitory processing mask. This approach, which is suggested by Marr's model of early processing in human vision, also reduces data processing by about two orders of magnitude and data transmission by up to an order of magnitude.

2007 Beyond SBIR Phase II: Bringing Technology Edge to the Warfighter

DTIC Science & Technology

2007-08-23

Systems Trade-Off Analysis and Optimization Verification and Validation On-Board Diagnostics and Self - healing Security and Anti-Tampering Rapid...verification; Safety and reliability analysis of flight and mission critical systems On-Board Diagnostics and Self - Healing Model-based monitoring and... self - healing On-board diagnostics and self - healing ; Autonomic computing; Network intrusion detection and prevention Anti-Tampering and Trust

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1985-01-01

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Experimental and Numerical Optimization of a High-Lift System to Improve Low-Speed Performance, Stability, and Control of an Arrow-Wing Supersonic Transport

NASA Technical Reports Server (NTRS)

Hahne, David E.; Glaab, Louis J.

1999-01-01

An investigation was performed to evaluate leading-and trailing-edge flap deflections for optimal aerodynamic performance of a High-Speed Civil Transport concept during takeoff and approach-to-landing conditions. The configuration used for this study was designed by the Douglas Aircraft Company during the 1970's. A 0.1-scale model of this configuration was tested in the Langley 30- by 60-Foot Tunnel with both the original leading-edge flap system and a new leading-edge flap system, which was designed with modem computational flow analysis and optimization tools. Leading-and trailing-edge flap deflections were generated for the original and modified leading-edge flap systems with the computational flow analysis and optimization tools. Although wind tunnel data indicated improvements in aerodynamic performance for the analytically derived flap deflections for both leading-edge flap systems, perturbations of the analytically derived leading-edge flap deflections yielded significant additional improvements in aerodynamic performance. In addition to the aerodynamic performance optimization testing, stability and control data were also obtained. An evaluation of the crosswind landing capability of the aircraft configuration revealed that insufficient lateral control existed as a result of high levels of lateral stability. Deflection of the leading-and trailing-edge flaps improved the crosswind landing capability of the vehicle considerably; however, additional improvements are required.

Power spectrum weighted edge analysis for straight edge detection in images

NASA Astrophysics Data System (ADS)

Karvir, Hrishikesh V.; Skipper, Julie A.

2007-04-01

Most man-made objects provide characteristic straight line edges and, therefore, edge extraction is a commonly used target detection tool. However, noisy images often yield broken edges that lead to missed detections, and extraneous edges that may contribute to false target detections. We present a sliding-block approach for target detection using weighted power spectral analysis. In general, straight line edges appearing at a given frequency are represented as a peak in the Fourier domain at a radius corresponding to that frequency, and a direction corresponding to the orientation of the edges in the spatial domain. Knowing the edge width and spacing between the edges, a band-pass filter is designed to extract the Fourier peaks corresponding to the target edges and suppress image noise. These peaks are then detected by amplitude thresholding. The frequency band width and the subsequent spatial filter mask size are variable parameters to facilitate detection of target objects of different sizes under known imaging geometries. Many military objects, such as trucks, tanks and missile launchers, produce definite signatures with parallel lines and the algorithm proves to be ideal for detecting such objects. Moreover, shadow-casting objects generally provide sharp edges and are readily detected. The block operation procedure offers advantages of significant reduction in noise influence, improved edge detection, faster processing speed and versatility to detect diverse objects of different sizes in the image. With Scud missile launcher replicas as target objects, the method has been successfully tested on terrain board test images under different backgrounds, illumination and imaging geometries with cameras of differing spatial resolution and bit-depth.

Resource Costs Give Optimization the Edge

Treesearch

C.M. Eddins

1996-01-01

To optimize or not to optimize - that is the question practically every sawmill has considered at some time or another. Edger and trimmer optimization is a particularly hot topic, as these are among the most wasteful areas of the sawmill because trimmer and edger operators traditionally tend to over edge or trim. By its very definition, optimizing equipment seeks to...

Practical Study for the Properties of Hueckel Edge Detection Operator

NASA Astrophysics Data System (ADS)

Jabbar, Hameed M. Abdul; Hatem, Amal J.; Ameer, Inbethaq M. A. Abdul

2018-05-01

The first practical study for the Hueckel edge detection operator was presented in this research, where it is tested on standard step edge set images. A number of criteria were adopted to evaluate its practical performance, which is the accuracy in detecting the edges direction, the error in the edges location (dislocation), edges width, the calculated edge goodness criterion and the consumed execution time. These criteria were studied with the edge direction and the used disk radius of the Hueckel edge detection operator. Important notes were recorded for the performance of this operator depending on the direction of the edge and/or with the radius of the used disk. There is a variation in the performance of the operator in terms of precision in detecting of the edges direction and position. A discussion was presented for the all criteria adopted in the research.

Surface Hold Advisor Using Critical Sections

NASA Technical Reports Server (NTRS)

Law, Caleb Hoi Kei (Inventor); Hsiao, Thomas Kun-Lung (Inventor); Mittler, Nathan C. (Inventor); Couluris, George J. (Inventor)

2013-01-01

The Surface Hold Advisor Using Critical Sections is a system and method for providing hold advisories to surface controllers to prevent gridlock and resolve crossing and merging conflicts among vehicles traversing a vertex-edge graph representing a surface traffic network on an airport surface. The Advisor performs pair-wise comparisons of current position and projected path of each vehicle with other surface vehicles to detect conflicts, determine critical sections, and provide hold advisories to traffic controllers recommending vehicles stop at entry points to protected zones around identified critical sections. A critical section defines a segment of the vertex-edge graph where vehicles are in crossing or merging or opposite direction gridlock contention. The Advisor detects critical sections without reference to scheduled, projected or required times along assigned vehicle paths, and generates hold advisories to prevent conflicts without requiring network path direction-of-movement rules and without requiring rerouting, rescheduling or other network optimization solutions.

Research on improved edge extraction algorithm of rectangular piece

NASA Astrophysics Data System (ADS)

He, Yi-Bin; Zeng, Ya-Jun; Chen, Han-Xin; Xiao, San-Xia; Wang, Yan-Wei; Huang, Si-Yu

Traditional edge detection operators such as Prewitt operator, LOG operator and Canny operator, etc. cannot meet the requirements of the modern industrial measurement. This paper proposes a kind of image edge detection algorithm based on improved morphological gradient. It can be detect the image using structural elements, which deals with the characteristic information of the image directly. Choosing different shapes and sizes of structural elements to use together, the ideal image edge information can be detected. The experimental result shows that the algorithm can well extract image edge with noise, which is clearer, and has more detailed edges compared with the previous edge detection algorithm.

Edge detection based on computational ghost imaging with structured illuminations

NASA Astrophysics Data System (ADS)

Yuan, Sheng; Xiang, Dong; Liu, Xuemei; Zhou, Xin; Bing, Pibin

2018-03-01

Edge detection is one of the most important tools to recognize the features of an object. In this paper, we propose an optical edge detection method based on computational ghost imaging (CGI) with structured illuminations which are generated by an interference system. The structured intensity patterns are designed to make the edge of an object be directly imaged from detected data in CGI. This edge detection method can extract the boundaries for both binary and grayscale objects in any direction at one time. We also numerically test the influence of distance deviations in the interference system on edge extraction, i.e., the tolerance of the optical edge detection system to distance deviation. Hopefully, it may provide a guideline for scholars to build an experimental system.

Object detection via eye tracking and fringe restraint

NASA Astrophysics Data System (ADS)

Pan, Fei; Zhang, Hanming; Zeng, Ying; Tong, Li; Yan, Bin

2017-07-01

Object detection is a computer vision problem which caught a large amount of attention. But the candidate boundingboxes extracted from only image features may end up with false-detection due to the semantic gap between the top-down and the bottom up information. In this paper, we propose a novel method for generating object bounding-boxes proposals using the combination of eye fixation point, saliency detection and edges. The new method obtains a fixation orientated Gaussian map, optimizes the map through single-layer cellular automata, and derives bounding-boxes from the optimized map on three levels. Then we score the boxes by combining all the information above, and choose the box with the highest score to be the final box. We perform an evaluation of our method by comparing with previous state-ofthe art approaches on the challenging POET datasets, the images of which are chosen from PASCAL VOC 2012. Our method outperforms them on small scale objects while comparable to them in general.

A robust sub-pixel edge detection method of infrared image based on tremor-based retinal receptive field model

NASA Astrophysics Data System (ADS)

Gao, Kun; Yang, Hu; Chen, Xiaomei; Ni, Guoqiang

2008-03-01

Because of complex thermal objects in an infrared image, the prevalent image edge detection operators are often suitable for a certain scene and extract too wide edges sometimes. From a biological point of view, the image edge detection operators work reliably when assuming a convolution-based receptive field architecture. A DoG (Difference-of- Gaussians) model filter based on ON-center retinal ganglion cell receptive field architecture with artificial eye tremors introduced is proposed for the image contour detection. Aiming at the blurred edges of an infrared image, the subsequent orthogonal polynomial interpolation and sub-pixel level edge detection in rough edge pixel neighborhood is adopted to locate the foregoing rough edges in sub-pixel level. Numerical simulations show that this method can locate the target edge accurately and robustly.

Influence of optimized leading-edge deflection and geometric anhedral on the low-speed aerodynamic characteristics of a low-aspect-ratio highly swept arrow-wing configuration. [langley 7 by 10 foot tunnel

NASA Technical Reports Server (NTRS)

Coe, P. L., Jr.; Huffman, J. K.

1979-01-01

An investigation conducted in the Langley 7 by 10 foot tunnel to determine the influence of an optimized leading-edge deflection on the low speed aerodynamic performance of a configuration with a low aspect ratio, highly swept wing. The sensitivity of the lateral stability derivative to geometric anhedral was also studied. The optimized leading edge deflection was developed by aligning the leading edge with the incoming flow along the entire span. Owing to spanwise variation of unwash, the resulting optimized leading edge was a smooth, continuously warped surface for which the deflection varied from 16 deg at the side of body to 50 deg at the wing tip. For the particular configuration studied, levels of leading-edge suction on the order of 90 percent were achieved. The results of tests conducted to determine the sensitivity of the lateral stability derivative to geometric anhedral indicate values which are in reasonable agreement with estimates provided by simple vortex-lattice theories.

White blood cell segmentation by circle detection using electromagnetism-like optimization.

PubMed

Cuevas, Erik; Oliva, Diego; Díaz, Margarita; Zaldivar, Daniel; Pérez-Cisneros, Marco; Pajares, Gonzalo

2013-01-01

Medical imaging is a relevant field of application of image processing algorithms. In particular, the analysis of white blood cell (WBC) images has engaged researchers from fields of medicine and computer vision alike. Since WBCs can be approximated by a quasicircular form, a circular detector algorithm may be successfully applied. This paper presents an algorithm for the automatic detection of white blood cells embedded into complicated and cluttered smear images that considers the complete process as a circle detection problem. The approach is based on a nature-inspired technique called the electromagnetism-like optimization (EMO) algorithm which is a heuristic method that follows electromagnetism principles for solving complex optimization problems. The proposed approach uses an objective function which measures the resemblance of a candidate circle to an actual WBC. Guided by the values of such objective function, the set of encoded candidate circles are evolved by using EMO, so that they can fit into the actual blood cells contained in the edge map of the image. Experimental results from blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique regarding detection, robustness, and stability.

White Blood Cell Segmentation by Circle Detection Using Electromagnetism-Like Optimization

PubMed Central

Oliva, Diego; Díaz, Margarita; Zaldivar, Daniel; Pérez-Cisneros, Marco; Pajares, Gonzalo

2013-01-01

Medical imaging is a relevant field of application of image processing algorithms. In particular, the analysis of white blood cell (WBC) images has engaged researchers from fields of medicine and computer vision alike. Since WBCs can be approximated by a quasicircular form, a circular detector algorithm may be successfully applied. This paper presents an algorithm for the automatic detection of white blood cells embedded into complicated and cluttered smear images that considers the complete process as a circle detection problem. The approach is based on a nature-inspired technique called the electromagnetism-like optimization (EMO) algorithm which is a heuristic method that follows electromagnetism principles for solving complex optimization problems. The proposed approach uses an objective function which measures the resemblance of a candidate circle to an actual WBC. Guided by the values of such objective function, the set of encoded candidate circles are evolved by using EMO, so that they can fit into the actual blood cells contained in the edge map of the image. Experimental results from blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique regarding detection, robustness, and stability. PMID:23476713

An improved dehazing algorithm of aerial high-definition image

NASA Astrophysics Data System (ADS)

Jiang, Wentao; Ji, Ming; Huang, Xiying; Wang, Chao; Yang, Yizhou; Li, Tao; Wang, Jiaoying; Zhang, Ying

2016-01-01

For unmanned aerial vehicle(UAV) images, the sensor can not get high quality images due to fog and haze weather. To solve this problem, An improved dehazing algorithm of aerial high-definition image is proposed. Based on the model of dark channel prior, the new algorithm firstly extracts the edges from crude estimated transmission map and expands the extracted edges. Then according to the expended edges, the algorithm sets a threshold value to divide the crude estimated transmission map into different areas and makes different guided filter on the different areas compute the optimized transmission map. The experimental results demonstrate that the performance of the proposed algorithm is substantially the same as the one based on dark channel prior and guided filter. The average computation time of the new algorithm is around 40% of the one as well as the detection ability of UAV image is improved effectively in fog and haze weather.

Three-dimensional unstructured grid refinement and optimization using edge-swapping

NASA Technical Reports Server (NTRS)

Gandhi, Amar; Barth, Timothy

1993-01-01

This paper presents a three-dimensional (3-D) 'edge-swapping method based on local transformations. This method extends Lawson's edge-swapping algorithm into 3-D. The 3-D edge-swapping algorithm is employed for the purpose of refining and optimizing unstructured meshes according to arbitrary mesh-quality measures. Several criteria including Delaunay triangulations are examined. Extensions from two to three dimensions of several known properties of Delaunay triangulations are also discussed.

A threshold selection method based on edge preserving

NASA Astrophysics Data System (ADS)

Lou, Liantang; Dan, Wei; Chen, Jiaqi

2015-12-01

A method of automatic threshold selection for image segmentation is presented. An optimal threshold is selected in order to preserve edge of image perfectly in image segmentation. The shortcoming of Otsu's method based on gray-level histograms is analyzed. The edge energy function of bivariate continuous function is expressed as the line integral while the edge energy function of image is simulated by discretizing the integral. An optimal threshold method by maximizing the edge energy function is given. Several experimental results are also presented to compare with the Otsu's method.

Two-Dimensional Edge Detection by Guided Mode Resonant Metasurface

NASA Astrophysics Data System (ADS)

Saba, Amirhossein; Tavakol, Mohammad Reza; Karimi-Khoozani, Parisa; Khavasi, Amin

2018-05-01

In this letter, a new approach to perform edge detection is presented using an all-dielectric CMOS-compatible metasurface. The design is based on guided-mode resonance which provides a high quality factor resonance to make the edge detection experimentally realizable. The proposed structure that is easy to fabricate, can be exploited for detection of edges in two dimensions due to its symmetry. Also, the trade-off between gain and resolution of edge detection is discussed which can be adjusted by appropriate design parameters. The proposed edge detector has also the potential to be used in ultrafast analog computing and image processing.

Applications of 3D-EDGE Detection for ALS Point Cloud

NASA Astrophysics Data System (ADS)

Ni, H.; Lin, X. G.; Zhang, J. X.

2017-09-01

Edge detection has been one of the major issues in the field of remote sensing and photogrammetry. With the fast development of sensor technology of laser scanning system, dense point clouds have become increasingly common. Precious 3D-edges are able to be detected from these point clouds and a great deal of edge or feature line extraction methods have been proposed. Among these methods, an easy-to-use 3D-edge detection method, AGPN (Analyzing Geometric Properties of Neighborhoods), has been proposed. The AGPN method detects edges based on the analysis of geometric properties of a query point's neighbourhood. The AGPN method detects two kinds of 3D-edges, including boundary elements and fold edges, and it has many applications. This paper presents three applications of AGPN, i.e., 3D line segment extraction, ground points filtering, and ground breakline extraction. Experiments show that the utilization of AGPN method gives a straightforward solution to these applications.

Novel method for edge detection of retinal vessels based on the model of the retinal vascular network and mathematical morphology

NASA Astrophysics Data System (ADS)

Xu, Lei; Zheng, Xiaoxiang; Zhang, Hengyi; Yu, Yajun

1998-09-01

Accurate edge detection of retinal vessels is a prerequisite for quantitative analysis of subtle morphological changes of retinal vessels under different pathological conditions. A novel method for edge detection of retinal vessels is presented in this paper. Methods: (1) Wavelet-based image preprocessing. (2) The signed edge detection algorithm and mathematical morphological operation are applied to get the approximate regions that contain retinal vessels. (3) By convolving the preprocessed image with a LoG operator only on the detected approximate regions of retinal vessels, followed by edges refining, clear edge maps of the retinal vessels are fast obtained. Results: A detailed performance evaluation together with the existing techniques is given to demonstrate the strong features of our method. Conclusions: True edge locations of retinal vessels can be fast detected with continuous structures of retinal vessels, less non- vessel segments left and insensitivity to noise. The method is also suitable for other application fields such as road edge detection.

Real-time 3D reconstruction of road curvature in far look-ahead distance from analysis of image sequences

NASA Astrophysics Data System (ADS)

Behringer, Reinhold

1995-12-01

A system for visual road recognition in far look-ahead distance, implemented in the autonomous road vehicle VaMP (a passenger car), is described. Visual cues of a road in a video image are the bright lane markings and the edges formed at the road borders. In a distance of more than 100 m, the most relevant road cue is the homogeneous road area, limited by the two border edges. These cues can be detected by the image processing module KRONOS applying edge detection techniques and areal 2D segmentation based on resolution triangles (analogous to a resolution pyramid). An estimation process performs an update of a state vector, which describes spatial road shape and vehicle orientation relative to the road. This state vector is estimated every 40 ms by exploiting knowledge about the vehicle movement (spatio-temporal model of vehicle dynamics) and the road design rules (clothoidal segments). Kalman filter techniques are applied to obtain an optimal estimate of the state vector by evaluating the measurements of the road border positions in the image sequence taken by a set of CCD cameras. The road consists of segments with piecewise constant curvature parameters. The borders between these segments can be detected by applying methods which have been developed for detection of discontinuities during time-discrete measurements. The road recognition system has been tested in autonomous rides with VaMP on public Autobahnen in real traffic at speeds up to 130 km/h.

Detectability Thresholds and Optimal Algorithms for Community Structure in Dynamic Networks

NASA Astrophysics Data System (ADS)

Ghasemian, Amir; Zhang, Pan; Clauset, Aaron; Moore, Cristopher; Peel, Leto

2016-07-01

The detection of communities within a dynamic network is a common means for obtaining a coarse-grained view of a complex system and for investigating its underlying processes. While a number of methods have been proposed in the machine learning and physics literature, we lack a theoretical analysis of their strengths and weaknesses, or of the ultimate limits on when communities can be detected. Here, we study the fundamental limits of detecting community structure in dynamic networks. Specifically, we analyze the limits of detectability for a dynamic stochastic block model where nodes change their community memberships over time, but where edges are generated independently at each time step. Using the cavity method, we derive a precise detectability threshold as a function of the rate of change and the strength of the communities. Below this sharp threshold, we claim that no efficient algorithm can identify the communities better than chance. We then give two algorithms that are optimal in the sense that they succeed all the way down to this threshold. The first uses belief propagation, which gives asymptotically optimal accuracy, and the second is a fast spectral clustering algorithm, based on linearizing the belief propagation equations. These results extend our understanding of the limits of community detection in an important direction, and introduce new mathematical tools for similar extensions to networks with other types of auxiliary information.

A Study of Deep CNN-Based Classification of Open and Closed Eyes Using a Visible Light Camera Sensor.

PubMed

Kim, Ki Wan; Hong, Hyung Gil; Nam, Gi Pyo; Park, Kang Ryoung

2017-06-30

The necessity for the classification of open and closed eyes is increasing in various fields, including analysis of eye fatigue in 3D TVs, analysis of the psychological states of test subjects, and eye status tracking-based driver drowsiness detection. Previous studies have used various methods to distinguish between open and closed eyes, such as classifiers based on the features obtained from image binarization, edge operators, or texture analysis. However, when it comes to eye images with different lighting conditions and resolutions, it can be difficult to find an optimal threshold for image binarization or optimal filters for edge and texture extraction. In order to address this issue, we propose a method to classify open and closed eye images with different conditions, acquired by a visible light camera, using a deep residual convolutional neural network. After conducting performance analysis on both self-collected and open databases, we have determined that the classification accuracy of the proposed method is superior to that of existing methods.

Modeling of direct detection Doppler wind lidar. I. The edge technique.

PubMed

McKay, J A

1998-09-20

Analytic models, based on a convolution of a Fabry-Perot etalon transfer function with a Gaussian spectral source, are developed for the shot-noise-limited measurement precision of Doppler wind lidars based on the edge filter technique by use of either molecular or aerosol atmospheric backscatter. The Rayleigh backscatter formulation yields a map of theoretical sensitivity versus etalon parameters, permitting design optimization and showing that the optimal system will have a Doppler measurement uncertainty no better than approximately 2.4 times that of a perfect, lossless receiver. An extension of the models to include the effect of limited etalon aperture leads to a condition for the minimum aperture required to match light collection optics. It is shown that, depending on the choice of operating point, the etalon aperture finesse must be 4-15 to avoid degradation of measurement precision. A convenient, closed-form expression for the measurement precision is obtained for spectrally narrow backscatter and is shown to be useful for backscatter that is spectrally broad as well. The models are extended to include extrinsic noise, such as solar background or the Rayleigh background on an aerosol Doppler lidar. A comparison of the model predictions with experiment has not yet been possible, but a comparison with detailed instrument modeling by McGill and Spinhirne shows satisfactory agreement. The models derived here will be more conveniently implemented than McGill and Spinhirne's and more readily permit physical insights to the optimization and limitations of the double-edge technique.

Optimum Edging and Trimming of Hardwood Lumber

Treesearch

Carmen Regalado; D. Earl Kline; Philip A. Araman

1992-01-01

Before the adoption of an automated system for optimizing edging and trimming in hardwood mills, the performance of present manual systems must be evaluated to provide a basis for comparison. a study was made in which lumber values recovered in actual hardwood operations were compared to the output of a computer-based procedure for edging and trimming optimization. The...

Finding Statistically Significant Communities in Networks

PubMed Central

Lancichinetti, Andrea; Radicchi, Filippo; Ramasco, José J.; Fortunato, Santo

2011-01-01

Community structure is one of the main structural features of networks, revealing both their internal organization and the similarity of their elementary units. Despite the large variety of methods proposed to detect communities in graphs, there is a big need for multi-purpose techniques, able to handle different types of datasets and the subtleties of community structure. In this paper we present OSLOM (Order Statistics Local Optimization Method), the first method capable to detect clusters in networks accounting for edge directions, edge weights, overlapping communities, hierarchies and community dynamics. It is based on the local optimization of a fitness function expressing the statistical significance of clusters with respect to random fluctuations, which is estimated with tools of Extreme and Order Statistics. OSLOM can be used alone or as a refinement procedure of partitions/covers delivered by other techniques. We have also implemented sequential algorithms combining OSLOM with other fast techniques, so that the community structure of very large networks can be uncovered. Our method has a comparable performance as the best existing algorithms on artificial benchmark graphs. Several applications on real networks are shown as well. OSLOM is implemented in a freely available software (http://www.oslom.org), and we believe it will be a valuable tool in the analysis of networks. PMID:21559480

A threshold-based fixed predictor for JPEG-LS image compression

NASA Astrophysics Data System (ADS)

Deng, Lihua; Huang, Zhenghua; Yao, Shoukui

2018-03-01

In JPEG-LS, fixed predictor based on median edge detector (MED) only detect horizontal and vertical edges, and thus produces large prediction errors in the locality of diagonal edges. In this paper, we propose a threshold-based edge detection scheme for the fixed predictor. The proposed scheme can detect not only the horizontal and vertical edges, but also diagonal edges. For some certain thresholds, the proposed scheme can be simplified to other existing schemes. So, it can also be regarded as the integration of these existing schemes. For a suitable threshold, the accuracy of horizontal and vertical edges detection is higher than the existing median edge detection in JPEG-LS. Thus, the proposed fixed predictor outperforms the existing JPEG-LS predictors for all images tested, while the complexity of the overall algorithm is maintained at a similar level.

Efficient method of image edge detection based on FSVM

NASA Astrophysics Data System (ADS)

Cai, Aiping; Xiong, Xiaomei

2013-07-01

For efficient object cover edge detection in digital images, this paper studied traditional methods and algorithm based on SVM. It analyzed Canny edge detection algorithm existed some pseudo-edge and poor anti-noise capability. In order to provide a reliable edge extraction method, propose a new detection algorithm based on FSVM. Which contains several steps: first, trains classify sample and gives the different membership function to different samples. Then, a new training sample is formed by increase the punishment some wrong sub-sample, and use the new FSVM classification model for train and test them. Finally the edges are extracted of the object image by using the model. Experimental result shows that good edge detection image will be obtained and adding noise experiments results show that this method has good anti-noise.

Ultrafast two-dimensional lithium beam emission spectroscopy diagnostic on the EAST tokamak

NASA Astrophysics Data System (ADS)

Zoletnik, S.; Hu, G. H.; Tál, B.; Dunai, D.; Anda, G.; Asztalos, O.; Pokol, G. I.; Kálvin, S.; Németh, J.; Krizsanóczi, T.

2018-06-01

A diagnostic instrument is described for the Experimental Advanced Superconducting Tokamak (EAST) for the measurement of the edge plasma electron density profile and plasma turbulence properties. An accelerated neutral lithium beam is injected into the tokamak and the Doppler shifted 670.8 nm light emission of the Li2p-2s transition is detected. A novel compact setup is used, where the beam injection and observation take place from the same equatorial diagnostic port and radial-poloidal resolution is achieved with microsecond time resolution. The observation direction is optimized in order to achieve a sufficient Doppler shift of the beam light to be able to separate from the strong edge lithium line emission on this lithium coated device. A 250 kHz beam chopping technique is also demonstrated for the removal of background light. First results show the capability of measuring turbulence and its poloidal flow velocity in the scrape-off layer and edge region and the resolution of details of transient phenomena like edge localized modes with few microsecond time resolution.

SU-E-I-76: Optimizing Imaging Parameters for a Novel Radiographic Imaging System for the Detection of Corrosion in Aluminum Aircraft Structures.

PubMed

Hammonds, J; Price, R; Donnelly, E; Pickens, D

2012-06-01

A laboratory-based phase-contrast radiography/tomosynthesis imaging system previously (Med. Phys. Vol. 38, 2353 May 2011) for improved detection of low-contrast soft-tissue masses was used to evaluate the sensitivity for detecting the presence of thin layers of corrosion on aluminum aircraft structures. The evaluation utilized a test object of aluminum (2.5 inch × 2.5 inch × 1/8 inch) on which different geometric patterns of 0.0038 inch thick anodized aluminum oxide was deposited. A circular area of radius 1 inch centered on the phantom's midpoint was milled to an approximate thickness of 0.022 inches. The x-ray source used for this investigation was a dual focal spot, tungsten anode x-ray tube. The focal used during the investigation has a nominal size of 0.010 mm. The active area of the imager is 17.1 cm × 23.9 cm (2016 × 2816 pixels) with a pixel pitch of 0.085 mm. X-ray tube voltages ranged from 20-40 kVp and source- to-object and object-to-image distances were varied from 20-100 cm. Performance of the phase-contrast mode was compared to conventional absorption-based radiography using contrast ratio and contrast-to-noise ratios (C/N). Phase-contrast performance was based on edge-enhancement index (EEI) and the edge-enhancement-to-noise (EE/N) ratio. for absorption-based radiography, the best C/N ratio was observed at the lowest kVp value (20 kVp). The optimum sampling angle for tomosynthesis was +/- 8 degrees. Comparing C/N to EE/N demonstrated the phase-contrast techniques improve the conspicuity of the oxide layer edges. This work provides the optimal parameters that a radiographic imaging system would need to differentiate the two different compounds of aluminum. Subcontractee from Positron Systems Inc. (Boise, Idaho) through United States Air Force grant (AF083-225). © 2012 American Association of Physicists in Medicine.

Does the optimal position of the acetabular fragment should be within the radiological normal range for all developmental dysplasia of the hip? A patient-specific finite element analysis.

PubMed

Wang, Xuyi; Peng, Jianping; Li, De; Zhang, Linlin; Wang, Hui; Jiang, Leisheng; Chen, Xiaodong

2016-10-04

The success of Bernese periacetabular osteotomy depends significantly on how extent the acetabular fragment can be corrected to its optimal position. This study was undertaken to investigate whether correcting the acetabular fragment into the so-called radiological "normal" range is the best choice for all developmental dysplasia of the hip with different severities of dysplasia from the biomechanical view? If not, is there any correlation between the biomechanically optimal position of the acetabular fragment and the severity of dysplasia? Four finite element models with different severities of dysplasia were developed. The virtual periacetabular osteotomy was performed with the acetabular fragment rotated anterolaterally to incremental center-edge angles; then, the contact area and pressure and von Mises stress in the cartilage were calculated at different correction angles. The optimal position of the acetabular fragment for patients 1, 2, and 3 was when the acetabular fragment rotated 17° laterally (with the lateral center-edge angle of 36° and anterior center-edge angle of 58°; both were slightly larger than the "normal" range), 25° laterally following further 5° anterior rotation (with the lateral center-edge angle of 31° and anterior center-edge angle of 51°; both were within the "normal" range), and 30° laterally following further 10° anterior rotation (with the lateral center-edge angle of 25° and anterior center-edge angle of 40°; both were less than the "normal" range), respectively. The optimal corrective position of the acetabular fragment is severity dependent rather than within the radiological "normal" range for developmental dysplasia of the hip. We prudently proposed that the optimal correction center-edge angle of mild, moderate, and severe developmental dysplasia of the hip is slightly larger than the "normal" range, within the "normal" range, and less than the lower limit of the "normal" range, respectively.

Optimal acetabular component orientation estimated using edge-loading and impingement risk in patients with metal-on-metal hip resurfacing arthroplasty.

PubMed

Mellon, Stephen J; Grammatopoulos, George; Andersen, Michael S; Pandit, Hemant G; Gill, Harinderjit S; Murray, David W

2015-01-21

Edge-loading in patients with metal-on-metal resurfaced hips can cause high serum metal ion levels, the development of soft-tissue reactions local to the joint called pseudotumours and ultimately, failure of the implant. Primary edge-loading is where contact between the femoral and acetabular components occurs at the edge/rim of the acetabular component whereas impingement of the femoral neck on the acetabular component's edge causes secondary or contrecoup edge-loading. Although the relationship between the orientation of the acetabular component and primary edge-loading has been identified, the contribution of acetabular component orientation to impingement and secondary edge-loading is less clear. Our aim was to estimate the optimal acetabular component orientation for 16 metal-on-metal hip resurfacing arthroplasty (MoMHRA) subjects with known serum metal ion levels. Data from motion analysis, subject-specific musculoskeletal modelling and Computed Tomography (CT) measurements were used to calculate the dynamic contact patch to rim (CPR) distance and impingement risk for 3416 different acetabular component orientations during gait, sit-to-stand, stair descent and static standing. For each subject, safe zones free from impingement and edge-loading (CPR <10%) were defined and, consequently, an optimal acetabular component orientation was determined (mean inclination 39.7° (SD 6.6°) mean anteversion 14.9° (SD 9.0°)). The results of this study suggest that the optimal acetabular component orientation can be determined from a patient's motion and anatomy. However, 'safe' zones of acetabular component orientation associated with reduced risk of dislocation and pseudotumour are also associated with a reduced risk of edge-loading and impingement. Copyright © 2014 Elsevier Ltd. All rights reserved.

[Image processing applying in analysis of motion features of cultured cardiac myocyte in rat].

PubMed

Teng, Qizhi; He, Xiaohai; Luo, Daisheng; Wang, Zhengrong; Zhou, Beiyi; Yuan, Zhirun; Tao, Dachang

2007-02-01

Study of mechanism of medicine actions, by quantitative analysis of cultured cardiac myocyte, is one of the cutting edge researches in myocyte dynamics and molecular biology. The characteristics of cardiac myocyte auto-beating without external stimulation make the research sense. Research of the morphology and cardiac myocyte motion using image analysis can reveal the fundamental mechanism of medical actions, increase the accuracy of medicine filtering, and design the optimal formula of medicine for best medical treatments. A system of hardware and software has been built with complete sets of functions including living cardiac myocyte image acquisition, image processing, motion image analysis, and image recognition. In this paper, theories and approaches are introduced for analysis of living cardiac myocyte motion images and implementing quantitative analysis of cardiac myocyte features. A motion estimation algorithm is used for motion vector detection of particular points and amplitude and frequency detection of a cardiac myocyte. Beatings of cardiac myocytes are sometimes very small. In such case, it is difficult to detect the motion vectors from the particular points in a time sequence of images. For this reason, an image correlation theory is employed to detect the beating frequencies. Active contour algorithm in terms of energy function is proposed to approximate the boundary and detect the changes of edge of myocyte.

A new method of edge detection for object recognition

USGS Publications Warehouse

Maddox, Brian G.; Rhew, Benjamin

2004-01-01

Traditional edge detection systems function by returning every edge in an input image. This can result in a large amount of clutter and make certain vectorization algorithms less accurate. Accuracy problems can then have a large impact on automated object recognition systems that depend on edge information. A new method of directed edge detection can be used to limit the number of edges returned based on a particular feature. This results in a cleaner image that is easier for vectorization. Vectorized edges from this process could then feed an object recognition system where the edge data would also contain information as to what type of feature it bordered.

Reduction of wafer-edge overlay errors using advanced correction models, optimized for minimal metrology requirements

NASA Astrophysics Data System (ADS)

Kim, Min-Suk; Won, Hwa-Yeon; Jeong, Jong-Mun; Böcker, Paul; Vergaij-Huizer, Lydia; Kupers, Michiel; Jovanović, Milenko; Sochal, Inez; Ryan, Kevin; Sun, Kyu-Tae; Lim, Young-Wan; Byun, Jin-Moo; Kim, Gwang-Gon; Suh, Jung-Joon

2016-03-01

In order to optimize yield in DRAM semiconductor manufacturing for 2x nodes and beyond, the (processing induced) overlay fingerprint towards the edge of the wafer needs to be reduced. Traditionally, this is achieved by acquiring denser overlay metrology at the edge of the wafer, to feed field-by-field corrections. Although field-by-field corrections can be effective in reducing localized overlay errors, the requirement for dense metrology to determine the corrections can become a limiting factor due to a significant increase of metrology time and cost. In this study, a more cost-effective solution has been found in extending the regular correction model with an edge-specific component. This new overlay correction model can be driven by an optimized, sparser sampling especially at the wafer edge area, and also allows for a reduction of noise propagation. Lithography correction potential has been maximized, with significantly less metrology needs. Evaluations have been performed, demonstrating the benefit of edge models in terms of on-product overlay performance, as well as cell based overlay performance based on metrology-to-cell matching improvements. Performance can be increased compared to POR modeling and sampling, which can contribute to (overlay based) yield improvement. Based on advanced modeling including edge components, metrology requirements have been optimized, enabling integrated metrology which drives down overall metrology fab footprint and lithography cycle time.

Holistic, model-based optimization of edge leveling as an enabler for lithographic focus control: application to a memory use case

NASA Astrophysics Data System (ADS)

Hasan, T.; Kang, Y.-S.; Kim, Y.-J.; Park, S.-J.; Jang, S.-Y.; Hu, K.-Y.; Koop, E. J.; Hinnen, P. C.; Voncken, M. M. A. J.

2016-03-01

Advancement of the next generation technology nodes and emerging memory devices demand tighter lithographic focus control. Although the leveling performance of the latest-generation scanners is state of the art, challenges remain at the wafer edge due to large process variations. There are several customer configurable leveling control options available in ASML scanners, some of which are application specific in their scope of leveling improvement. In this paper, we assess the usability of leveling non-correctable error models to identify yield limiting edge dies. We introduce a novel dies-inspec based holistic methodology for leveling optimization to guide tool users in selecting an optimal configuration of leveling options. Significant focus gain, and consequently yield gain, can be achieved with this integrated approach. The Samsung site in Hwaseong observed an improved edge focus performance in a production of a mid-end memory product layer running on an ASML NXT 1960 system. 50% improvement in focus and a 1.5%p gain in edge yield were measured with the optimized configurations.

Dual Transition Edge Sensor Bolometer for Enhanced Dynamic Range

NASA Technical Reports Server (NTRS)

Chervenak, J. A.; Benford, D. J.; Moseley, S. H.; Irwin, K. D.

2004-01-01

Broadband surveys at the millimeter and submillimeter wavelengths will require bolometers that can reach new limits of sensitivity and also operate under high background conditions. To address this need, we present results on a dual transition edge sensor (TES) device with two operating modes: one for low background, ultrasensitive detection and one for high background, enhanced dynamic range detection. The device consists of a detector element with two transition temperatures (T(sub c)) of 0.25 and 0.51 K located on the same micromachined, thermally isolated membrane structure. It can be biased on either transition, and features phonon-limited noise performance at the lower T(sub c). We measure noise performance on the lower transition 7 x 10(exp -18) W/rt(Hz) and the bias power on the upper transition of 12.5 pW, giving a factor of 10 enhancement of the dynamic range for the device. We discuss the biasable range of this type of device and present a design concept to optimize utility of the device.

On the distribution of saliency.

PubMed

Berengolts, Alexander; Lindenbaum, Michael

2006-12-01

Detecting salient structures is a basic task in perceptual organization. Saliency algorithms typically mark edge-points with some saliency measure, which grows with the length and smoothness of the curve on which these edge-points lie. Here, we propose a modified saliency estimation mechanism that is based on probabilistically specified grouping cues and on curve length distributions. In this framework, the Shashua and Ullman saliency mechanism may be interpreted as a process for detecting the curve with maximal expected length. Generalized types of saliency naturally follow. We propose several specific generalizations (e.g., gray-level-based saliency) and rigorously derive the limitations on generalized saliency types. We then carry out a probabilistic analysis of expected length saliencies. Using ergodicity and asymptotic analysis, we derive the saliency distributions associated with the main curves and with the rest of the image. We then extend this analysis to finite-length curves. Using the derived distributions, we derive the optimal threshold on the saliency for discriminating between figure and background and bound the saliency-based figure-from-ground performance.

The circuit of polychromator for Experimental Advanced Superconducting Tokamak edge Thomson scattering diagnostic.

PubMed

Zang, Qing; Hsieh, C L; Zhao, Junyu; Chen, Hui; Li, Fengjuan

2013-09-01

The detector circuit is the core component of filter polychromator which is used for scattering light analysis in Thomson scattering diagnostic, and is responsible for the precision and stability of a system. High signal-to-noise and stability are primary requirements for the diagnostic. Recently, an upgraded detector circuit for weak light detecting in Experimental Advanced Superconducting Tokamak (EAST) edge Thomson scattering system has been designed, which can be used for the measurement of large electron temperature (T(e)) gradient and low electron density (n(e)). In this new circuit, a thermoelectric-cooled avalanche photodiode with the aid circuit is involved for increasing stability and enhancing signal-to-noise ratio (SNR), especially the circuit will never be influenced by ambient temperature. These features are expected to improve the accuracy of EAST Thomson diagnostic dramatically. Related mechanical construction of the circuit is redesigned as well for heat-sinking and installation. All parameters are optimized, and SNR is dramatically improved. The number of minimum detectable photons is only 10.

A simplified implementation of edge detection in MATLAB is faster and more sensitive than fast fourier transform for actin fiber alignment quantification.

PubMed

Kemeny, Steven Frank; Clyne, Alisa Morss

2011-04-01

Fiber alignment plays a critical role in the structure and function of cells and tissues. While fiber alignment quantification is important to experimental analysis and several different methods for quantifying fiber alignment exist, many studies focus on qualitative rather than quantitative analysis perhaps due to the complexity of current fiber alignment methods. Speed and sensitivity were compared in edge detection and fast Fourier transform (FFT) for measuring actin fiber alignment in cells exposed to shear stress. While edge detection using matrix multiplication was consistently more sensitive than FFT, image processing time was significantly longer. However, when MATLAB functions were used to implement edge detection, MATLAB's efficient element-by-element calculations and fast filtering techniques reduced computation cost 100 times compared to the matrix multiplication edge detection method. The new computation time was comparable to the FFT method, and MATLAB edge detection produced well-distributed fiber angle distributions that statistically distinguished aligned and unaligned fibers in half as many sample images. When the FFT sensitivity was improved by dividing images into smaller subsections, processing time grew larger than the time required for MATLAB edge detection. Implementation of edge detection in MATLAB is simpler, faster, and more sensitive than FFT for fiber alignment quantification.

Using evolutionary computation to optimize an SVM used in detecting buried objects in FLIR imagery

NASA Astrophysics Data System (ADS)

Paino, Alex; Popescu, Mihail; Keller, James M.; Stone, Kevin

2013-06-01

In this paper we describe an approach for optimizing the parameters of a Support Vector Machine (SVM) as part of an algorithm used to detect buried objects in forward looking infrared (FLIR) imagery captured by a camera installed on a moving vehicle. The overall algorithm consists of a spot-finding procedure (to look for potential targets) followed by the extraction of several features from the neighborhood of each spot. The features include local binary pattern (LBP) and histogram of oriented gradients (HOG) as these are good at detecting texture classes. Finally, we project and sum each hit into UTM space along with its confidence value (obtained from the SVM), producing a confidence map for ROC analysis. In this work, we use an Evolutionary Computation Algorithm (ECA) to optimize various parameters involved in the system, such as the combination of features used, parameters on the Canny edge detector, the SVM kernel, and various HOG and LBP parameters. To validate our approach, we compare results obtained from an SVM using parameters obtained through our ECA technique with those previously selected by hand through several iterations of "guess and check".

Information theoretic analysis of canny edge detection in visual communication

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2011-06-01

In general edge detection evaluation, the edge detectors are examined, analyzed, and compared either visually or with a metric for specific an application. This analysis is usually independent of the characteristics of the image-gathering, transmission and display processes that do impact the quality of the acquired image and thus, the resulting edge image. We propose a new information theoretic analysis of edge detection that unites the different components of the visual communication channel and assesses edge detection algorithms in an integrated manner based on Shannon's information theory. The edge detection algorithm here is considered to achieve high performance only if the information rate from the scene to the edge approaches the maximum possible. Thus, by setting initial conditions of the visual communication system as constant, different edge detection algorithms could be evaluated. This analysis is normally limited to linear shift-invariant filters so in order to examine the Canny edge operator in our proposed system, we need to estimate its "power spectral density" (PSD). Since the Canny operator is non-linear and shift variant, we perform the estimation for a set of different system environment conditions using simulations. In our paper we will first introduce the PSD of the Canny operator for a range of system parameters. Then, using the estimated PSD, we will assess the Canny operator using information theoretic analysis. The information-theoretic metric is also used to compare the performance of the Canny operator with other edge-detection operators. This also provides a simple tool for selecting appropriate edgedetection algorithms based on system parameters, and for adjusting their parameters to maximize information throughput.

BP fusion model for the detection of oil spills on the sea by remote sensing

NASA Astrophysics Data System (ADS)

Chen, Weiwei; An, Jubai; Zhang, Hande; Lin, Bin

2003-06-01

Oil spills are very serious marine pollution in many countries. In order to detect and identify the oil-spilled on the sea by remote sensor, scientists have to conduct a research work on the remote sensing image. As to the detection of oil spills on the sea, edge detection is an important technology in image processing. There are many algorithms of edge detection developed for image processing. These edge detection algorithms always have their own advantages and disadvantages in the image processing. Based on the primary requirements of edge detection of the oil spills" image on the sea, computation time and detection accuracy, we developed a fusion model. The model employed a BP neural net to fuse the detection results of simple operators. The reason we selected BP neural net as the fusion technology is that the relation between simple operators" result of edge gray level and the image"s true edge gray level is nonlinear, while BP neural net is good at solving the nonlinear identification problem. Therefore in this paper we trained a BP neural net by some oil spill images, then applied the BP fusion model on the edge detection of other oil spill images and obtained a good result. In this paper the detection result of some gradient operators and Laplacian operator are also compared with the result of BP fusion model to analysis the fusion effect. At last the paper pointed out that the fusion model has higher accuracy and higher speed in the processing oil spill image"s edge detection.

Effect of interaction strength on robustness of controlling edge dynamics in complex networks

NASA Astrophysics Data System (ADS)

Pang, Shao-Peng; Hao, Fei

2018-05-01

Robustness plays a critical role in the controllability of complex networks to withstand failures and perturbations. Recent advances in the edge controllability show that the interaction strength among edges plays a more important role than network structure. Therefore, we focus on the effect of interaction strength on the robustness of edge controllability. Using three categories of all edges to quantify the robustness, we develop a universal framework to evaluate and analyze the robustness in complex networks with arbitrary structures and interaction strengths. Applying our framework to a large number of model and real-world networks, we find that the interaction strength is a dominant factor for the robustness in undirected networks. Meanwhile, the strongest robustness and the optimal edge controllability in undirected networks can be achieved simultaneously. Different from the case of undirected networks, the robustness in directed networks is determined jointly by the interaction strength and the network's degree distribution. Moreover, a stronger robustness is usually associated with a larger number of driver nodes required to maintain full control in directed networks. This prompts us to provide an optimization method by adjusting the interaction strength to optimize the robustness of edge controllability.

First demonstration of 10 keV-width energy-discrimination K-edge radiography using a cadmium-telluride X-ray camera with a tungsten-target tube

NASA Astrophysics Data System (ADS)

Watanabe, Manabu; Sato, Eiichi; Abderyim, Purkhet; Abudurexiti, Abulajiang; Hagiwara, Osahiko; Matsukiyo, Hiroshi; Osawa, Akihiro; Enomoto, Toshiyuki; Nagao, Jiro; Sato, Shigehiro; Ogawa, Akira; Onagawa, Jun

2011-05-01

Energy-discrimination X-ray camera is useful to perform monochromatic radiography using polychromatic X-rays. This X-ray camera was developed to carry out K-edge radiography using cerium and gadolinium-based contrast media. In this camera, objects are irradiated by a cone beam from a tungsten-target X-ray generator, and penetrating X-ray photons are detected by a cadmium-telluride detector with amplifiers. Both optimal photon-energy level and energy width are selected using a multichannel analyzer, and the photon number is counted by a counter card. Radiography was performed by the detector scanning using an x- y stage driven by a two-stage controller, and radiograms were shown on a personal computer monitor. In radiography, tube voltage and current were 90 kV and 5.8 μA, respectively, and the X-ray intensity was 0.61 μGy/s at 1.0 m from the X-ray source. The K-edge energies of cerium and gadolinium are 40.3 and 50.3 keV, respectively, and 10 keV-width enhanced K-edge radiography was performed using X-ray photons with energies just beyond K-edge energies of cerium and gadolinium. Thus, cerium K-edge radiography was carried out using X-ray photons with an energy range from 40.3 to 50. 3 keV, and gadolinium K-edge radiography was accomplished utilizing photon energies ranging from 50.3 to 60.3 keV.

Synthetic Minority Oversampling Technique and Fractal Dimension for Identifying Multiple Sclerosis

NASA Astrophysics Data System (ADS)

Zhang, Yu-Dong; Zhang, Yin; Phillips, Preetha; Dong, Zhengchao; Wang, Shuihua

Multiple sclerosis (MS) is a severe brain disease. Early detection can provide timely treatment. Fractal dimension can provide statistical index of pattern changes with scale at a given brain image. In this study, our team used susceptibility weighted imaging technique to obtain 676 MS slices and 880 healthy slices. We used synthetic minority oversampling technique to process the unbalanced dataset. Then, we used Canny edge detector to extract distinguishing edges. The Minkowski-Bouligand dimension was a fractal dimension estimation method and used to extract features from edges. Single hidden layer neural network was used as the classifier. Finally, we proposed a three-segment representation biogeography-based optimization to train the classifier. Our method achieved a sensitivity of 97.78±1.29%, a specificity of 97.82±1.60% and an accuracy of 97.80±1.40%. The proposed method is superior to seven state-of-the-art methods in terms of sensitivity and accuracy.

Detection and labeling ribs on expiration chest radiographs

NASA Astrophysics Data System (ADS)

Park, Mira; Jin, Jesse S.; Wilson, Laurence S.

2003-06-01

Typically, inspiration is preferred when xraying the lungs. The x-ray technologist will ask a patient to be still and to take a deep breath and to hold it. This not only reduces the possibility of a blurred image but also enhances the quality of the image since air-filled lungs are easier to see on x-ray film. However, inspiration causes low density in the inner part of lung field. That means that ribs in the inner part of lung field have lower density than the other parts nearer to the border of the lung field. That is why edge detection algorithms often fail to detect ribs. Therefore to make rib edges clear we try to produce an expiration lung field using a 'hemi-elliptical cavity.' Based on the expiration lung field, we extract the rib edges using canny edge detector and a new connectivity method, called '4 way with 10-neighbors connectivity' to detect clavicle and rib edge candidates. Once the edge candidates are formed, our system selects the best candidates using knowledge-based constraints such as a gradient, length and location. The edges can be paired and labeled as superior rib edge and inferior rib edge. Then the system uses the clavicle, which is obtained in a same method for the rib edge detection, as a landmark to label all detected ribs.

Optimization of cascading failure on complex network based on NNIA

NASA Astrophysics Data System (ADS)

Zhu, Qian; Zhu, Zhiliang; Qi, Yi; Yu, Hai; Xu, Yanjie

2018-07-01

Recently, the robustness of networks under cascading failure has attracted extensive attention. Different from previous studies, we concentrate on how to improve the robustness of the networks from the perspective of intelligent optimization. We establish two multi-objective optimization models that comprehensively consider the operational cost of the edges in the networks and the robustness of the networks. The NNIA (Non-dominated Neighbor Immune Algorithm) is applied to solve the optimization models. We finished simulations of the Barabási-Albert (BA) network and Erdös-Rényi (ER) network. In the solutions, we find the edges that can facilitate the propagation of cascading failure and the edges that can suppress the propagation of cascading failure. From the conclusions, we take optimal protection measures to weaken the damage caused by cascading failures. We also consider actual situations of operational cost feasibility of the edges. People can make a more practical choice based on the operational cost. Our work will be helpful in the design of highly robust networks or improvement of the robustness of networks in the future.

Current LWIR HSI Remote Sensing Activities at Defence R&D Canada - Valcartier

DTIC Science & Technology

2009-10-01

measures the IR radiation from a target scene which is optically combined onto a single detector out-of-phase with the IR radiation from a corresponding...Hyper-Cam-LW. The MODDIFS project involves the development of a leading edge infrared ( IR ) hyperspectral sensor optimized for the standoff detection...essentially offer the optical subtraction capability of the CATSI system but at high-spatial resolution using an MCT focal plane array of 8484

Tripartite community structure in social bookmarking data

NASA Astrophysics Data System (ADS)

Neubauer, Nicolas; Obermayer, Klaus

2011-12-01

Community detection is a branch of network analysis concerned with identifying strongly connected subnetworks. Social bookmarking sites aggregate datasets of often hundreds of millions of triples (document, user, and tag), which, when interpreted as edges of a graph, give rise to special networks called 3-partite, 3-uniform hypergraphs. We identify challenges and opportunities of generalizing community detection and in particular modularity optimization to these structures. Two methods for community detection are introduced that preserve the hypergraph's special structure to different degrees. Their performance is compared on synthetic datasets, showing the benefits of structure preservation. Furthermore, a tool for interactive exploration of the community detection results is introduced and applied to examples from real datasets. We find additional evidence for the importance of structure preservation and, more generally, demonstrate how tripartite community detection can help understand the structure of social bookmarking data.

A Study of Deep CNN-Based Classification of Open and Closed Eyes Using a Visible Light Camera Sensor

PubMed Central

Kim, Ki Wan; Hong, Hyung Gil; Nam, Gi Pyo; Park, Kang Ryoung

2017-01-01

The necessity for the classification of open and closed eyes is increasing in various fields, including analysis of eye fatigue in 3D TVs, analysis of the psychological states of test subjects, and eye status tracking-based driver drowsiness detection. Previous studies have used various methods to distinguish between open and closed eyes, such as classifiers based on the features obtained from image binarization, edge operators, or texture analysis. However, when it comes to eye images with different lighting conditions and resolutions, it can be difficult to find an optimal threshold for image binarization or optimal filters for edge and texture extraction. In order to address this issue, we propose a method to classify open and closed eye images with different conditions, acquired by a visible light camera, using a deep residual convolutional neural network. After conducting performance analysis on both self-collected and open databases, we have determined that the classification accuracy of the proposed method is superior to that of existing methods. PMID:28665361

System and method for automated object detection in an image

DOEpatents

Kenyon, Garrett T.; Brumby, Steven P.; George, John S.; Paiton, Dylan M.; Schultz, Peter F.

2015-10-06

A contour/shape detection model may use relatively simple and efficient kernels to detect target edges in an object within an image or video. A co-occurrence probability may be calculated for two or more edge features in an image or video using an object definition. Edge features may be differentiated between in response to measured contextual support, and prominent edge features may be extracted based on the measured contextual support. The object may then be identified based on the extracted prominent edge features.

The crack detection algorithm of pavement image based on edge information

NASA Astrophysics Data System (ADS)

Yang, Chunde; Geng, Mingyue

2018-05-01

As the images of pavement cracks are affected by a large amount of complicated noises, such as uneven illumination and water stains, the detected cracks are discontinuous and the main body information at the edge of the cracks is easily lost. In order to solve the problem, a crack detection algorithm in pavement image based on edge information is proposed. Firstly, the image is pre-processed by the nonlinear gray-scale transform function and reconstruction filter to enhance the linear characteristic of the crack. At the same time, an adaptive thresholding method is designed to coarsely extract the cracks edge according to the gray-scale gradient feature and obtain the crack gradient information map. Secondly, the candidate edge points are obtained according to the gradient information, and the edge is detected based on the single pixel percolation processing, which is improved by using the local difference between pixels in the fixed region. Finally, complete crack is obtained by filling the crack edge. Experimental results show that the proposed method can accurately detect pavement cracks and preserve edge information.

Meta-Analysis of the Detection of Plant Pigment Concentrations Using Hyperspectral Remotely Sensed Data

PubMed Central

Huang, Jingfeng; Wei, Chen; Zhang, Yao; Blackburn, George Alan; Wang, Xiuzhen; Wei, Chuanwen; Wang, Jing

2015-01-01

Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550–560nm) and red edge (680–750nm) regions; chlorophyll b on the red, (630–660nm), red edge (670–710nm) and the near-infrared (800–810nm); carotenoids on the 500–580nm region; and anthocyanins on the green (550–560nm), red edge (700–710nm) and near-infrared (780–790nm). For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a. PMID:26356842

Optimal graph search segmentation using arc-weighted graph for simultaneous surface detection of bladder and prostate.

PubMed

Song, Qi; Wu, Xiaodong; Liu, Yunlong; Smith, Mark; Buatti, John; Sonka, Milan

2009-01-01

We present a novel method for globally optimal surface segmentation of multiple mutually interacting objects, incorporating both edge and shape knowledge in a 3-D graph-theoretic approach. Hard surface interacting constraints are enforced in the interacting regions, preserving the geometric relationship of those partially interacting surfaces. The soft smoothness a priori shape compliance is introduced into the energy functional to provide shape guidance. The globally optimal surfaces can be simultaneously achieved by solving a maximum flow problem based on an arc-weighted graph representation. Representing the segmentation problem in an arc-weighted graph, one can incorporate a wider spectrum of constraints into the formulation, thus increasing segmentation accuracy and robustness in volumetric image data. To the best of our knowledge, our method is the first attempt to introduce the arc-weighted graph representation into the graph-searching approach for simultaneous segmentation of multiple partially interacting objects, which admits a globally optimal solution in a low-order polynomial time. Our new approach was applied to the simultaneous surface detection of bladder and prostate. The result was quite encouraging in spite of the low saliency of the bladder and prostate in CT images.

Wavelet Fusion for Concealed Object Detection Using Passive Millimeter Wave Sequence Images

NASA Astrophysics Data System (ADS)

Chen, Y.; Pang, L.; Liu, H.; Xu, X.

2018-04-01

PMMW imaging system can create interpretable imagery on the objects concealed under clothing, which gives the great advantage to the security check system. Paper addresses wavelet fusion to detect concealed objects using passive millimeter wave (PMMW) sequence images. According to PMMW real-time imager acquired image characteristics and storage methods firstly, using the sum of squared difference (SSD) as the image-related parameters to screen the sequence images. Secondly, the selected images are optimized using wavelet fusion algorithm. Finally, the concealed objects are detected by mean filter, threshold segmentation and edge detection. The experimental results show that this method improves the detection effect of concealed objects by selecting the most relevant images from PMMW sequence images and using wavelet fusion to enhance the information of the concealed objects. The method can be effectively applied to human body concealed object detection in millimeter wave video.

Image edge detection based tool condition monitoring with morphological component analysis.

PubMed

Yu, Xiaolong; Lin, Xin; Dai, Yiquan; Zhu, Kunpeng

2017-07-01

The measurement and monitoring of tool condition are keys to the product precision in the automated manufacturing. To meet the need, this study proposes a novel tool wear monitoring approach based on the monitored image edge detection. Image edge detection has been a fundamental tool to obtain features of images. This approach extracts the tool edge with morphological component analysis. Through the decomposition of original tool wear image, the approach reduces the influence of texture and noise for edge measurement. Based on the target image sparse representation and edge detection, the approach could accurately extract the tool wear edge with continuous and complete contour, and is convenient in charactering tool conditions. Compared to the celebrated algorithms developed in the literature, this approach improves the integrity and connectivity of edges, and the results have shown that it achieves better geometry accuracy and lower error rate in the estimation of tool conditions. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Edge control in CNC polishing, paper 2: simulation and validation of tool influence functions on edges.

PubMed

Li, Hongyu; Walker, David; Yu, Guoyu; Sayle, Andrew; Messelink, Wilhelmus; Evans, Rob; Beaucamp, Anthony

2013-01-14

Edge mis-figure is regarded as one of the most difficult technical issues for manufacturing the segments of extremely large telescopes, which can dominate key aspects of performance. A novel edge-control technique has been developed, based on 'Precessions' polishing technique and for which accurate and stable edge tool influence functions (TIFs) are crucial. In the first paper in this series [D. Walker Opt. Express 20, 19787-19798 (2012)], multiple parameters were experimentally optimized using an extended set of experiments. The first purpose of this new work is to 'short circuit' this procedure through modeling. This also gives the prospect of optimizing local (as distinct from global) polishing for edge mis-figure, now under separate development. This paper presents a model that can predict edge TIFs based on surface-speed profiles and pressure distributions over the polishing spot at the edge of the part, the latter calculated by finite element analysis and verified by direct force measurement. This paper also presents a hybrid-measurement method for edge TIFs to verify the simulation results. Experimental and simulation results show good agreement.

Optimization of the K-edge imaging for vulnerable plaques using gold nanoparticles and energy-resolved photon counting detectors: a simulation study

PubMed Central

Alivov, Yahya; Baturin, Pavlo; Le, Huy Q.; Ducote, Justin; Molloi, Sabee

2014-01-01

We investigated the effect of different imaging parameters such as dose, beam energy, energy resolution, and number of energy bins on image quality of K-edge spectral computed tomography (CT) of gold nanoparticles (GNP) accumulated in an atherosclerotic plaque. Maximum likelihood technique was employed to estimate the concentration of GNP, which served as a targeted intravenous contrast material intended to detect the degree of plaque's inflammation. The simulations studies used a single slice parallel beam CT geometry with an X-ray beam energy ranging between 50 and 140 kVp. The synthetic phantoms included small (3 cm in diameter) cylinder and chest (33x24 cm2) phantom, where both phantoms contained tissue, calcium, and gold. In the simulation studies GNP quantification and background (calcium and tissue) suppression task were pursued. The X-ray detection sensor was represented by an energy resolved photon counting detector (e.g., CdZnTe) with adjustable energy bins. Both ideal and more realistic (12% FWHM energy resolution) implementations of photon counting detector were simulated. The simulations were performed for the CdZnTe detector with pixel pitch of 0.5-1 mm, which corresponds to the performance without significant charge sharing and cross-talk effects. The Rose model was employed to estimate the minimum detectable concentration of GNPs. A figure of merit (FOM) was used to optimize the X-ray beam energy (kVp) to achieve the highest signal-to-noise ratio (SNR) with respect to patient dose. As a result, the successful identification of gold and background suppression was demonstrated. The highest FOM was observed at 125 kVp X-ray beam energy. The minimum detectable GNP concentration was determined to be approximately 1.06 μmol/mL (0.21 mg/mL) for an ideal detector and about 2.5 μmol/mL (0.49 mg/mL) for more realistic (12% FWHM) detector. The studies show the optimal imaging parameters at lowest patient dose using an energy resolved photon counting detector to image GNP in an atherosclerotic plaque. PMID:24334301

Dynamic-thresholding level set: a novel computer-aided volumetry method for liver tumors in hepatic CT images

NASA Astrophysics Data System (ADS)

Cai, Wenli; Yoshida, Hiroyuki; Harris, Gordon J.

2007-03-01

Measurement of the volume of focal liver tumors, called liver tumor volumetry, is indispensable for assessing the growth of tumors and for monitoring the response of tumors to oncology treatments. Traditional edge models, such as the maximum gradient and zero-crossing methods, often fail to detect the accurate boundary of a fuzzy object such as a liver tumor. As a result, the computerized volumetry based on these edge models tends to differ from manual segmentation results performed by physicians. In this study, we developed a novel computerized volumetry method for fuzzy objects, called dynamic-thresholding level set (DT level set). An optimal threshold value computed from a histogram tends to shift, relative to the theoretical threshold value obtained from a normal distribution model, toward a smaller region in the histogram. We thus designed a mobile shell structure, called a propagating shell, which is a thick region encompassing the level set front. The optimal threshold calculated from the histogram of the shell drives the level set front toward the boundary of a liver tumor. When the volume ratio between the object and the background in the shell approaches one, the optimal threshold value best fits the theoretical threshold value and the shell stops propagating. Application of the DT level set to 26 hepatic CT cases with 63 biopsy-confirmed hepatocellular carcinomas (HCCs) and metastases showed that the computer measured volumes were highly correlated with those of tumors measured manually by physicians. Our preliminary results showed that DT level set was effective and accurate in estimating the volumes of liver tumors detected in hepatic CT images.

Design optimization using adjoint of Long-time LES for the trailing edge of a transonic turbine vane

NASA Astrophysics Data System (ADS)

Talnikar, Chaitanya; Wang, Qiqi

2017-11-01

Adjoint-based design optimization methods have been applied to low-fidelity simulation methods like Reynolds Averaged Navier-Stokes (RANS) and are useful for designing fluid machinery components. But to reliably capture the complex flow phenomena involved in turbomachinery, high fidelity simulations like large eddy simulation (LES) are required. Unfortunately due to the chaotic dynamics of turbulence, the unsteady adjoint method for LES diverges and produces incorrect gradients. Using a viscosity stabilized unsteady adjoint method developed for LES, the gradient can be obtained with reasonable accuracy. In this paper, design of the trailing edge of a gas turbine inlet guide vane is performed with the objective to reduce stagnation pressure loss and heat transfer over the surface of the vane. Slight changes in the shape of trailing edge can significantly impact these quantities by altering the boundary layer development process and separation points. The trailing edge is parameterized using a linear combination of 5 convex designs. Bayesian optimization is used as a global optimizer with the objective function evaluated from the LES and gradients obtained using the viscosity adjoint method. Results from the optimization, performed on the supercomputer Mira, are presented.

Enhanced Detectability of Community Structure in Multilayer Networks through Layer Aggregation.

PubMed

Taylor, Dane; Shai, Saray; Stanley, Natalie; Mucha, Peter J

2016-06-03

Many systems are naturally represented by a multilayer network in which edges exist in multiple layers that encode different, but potentially related, types of interactions, and it is important to understand limitations on the detectability of community structure in these networks. Using random matrix theory, we analyze detectability limitations for multilayer (specifically, multiplex) stochastic block models (SBMs) in which L layers are derived from a common SBM. We study the effect of layer aggregation on detectability for several aggregation methods, including summation of the layers' adjacency matrices for which we show the detectability limit vanishes as O(L^{-1/2}) with increasing number of layers, L. Importantly, we find a similar scaling behavior when the summation is thresholded at an optimal value, providing insight into the common-but not well understood-practice of thresholding pairwise-interaction data to obtain sparse network representations.

The circuit of polychromator for Experimental Advanced Superconducting Tokamak edge Thomson scattering diagnostic

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

Zang, Qing; Zhao, Junyu; Chen, Hui

2013-09-15

The detector circuit is the core component of filter polychromator which is used for scattering light analysis in Thomson scattering diagnostic, and is responsible for the precision and stability of a system. High signal-to-noise and stability are primary requirements for the diagnostic. Recently, an upgraded detector circuit for weak light detecting in Experimental Advanced Superconducting Tokamak (EAST) edge Thomson scattering system has been designed, which can be used for the measurement of large electron temperature (T{sub e}) gradient and low electron density (n{sub e}). In this new circuit, a thermoelectric-cooled avalanche photodiode with the aid circuit is involved for increasingmore » stability and enhancing signal-to-noise ratio (SNR), especially the circuit will never be influenced by ambient temperature. These features are expected to improve the accuracy of EAST Thomson diagnostic dramatically. Related mechanical construction of the circuit is redesigned as well for heat-sinking and installation. All parameters are optimized, and SNR is dramatically improved. The number of minimum detectable photons is only 10.« less

Electron-beam lithography with character projection exposure for throughput enhancement with line-edge quality optimization

NASA Astrophysics Data System (ADS)

Ikeno, Rimon; Maruyama, Satoshi; Mita, Yoshio; Ikeda, Makoto; Asada, Kunihiro

2016-03-01

Among various electron-beam lithography (EBL) techniques, variable-shaped beam (VSB) and character projection (CP) methods have attracted many EBL users for their high-throughput feature, but they are considered to be more suited to small-featured VLSI fabrication with regularly-arranged layouts like standard-cell logics and memory arrays. On the other hand, non-VLSI applications like photonics, MEMS, MOEMS, and so on, have not been fully utilized the benefit of CP method due to their wide variety of layout patterns. In addition, the stepwise edge shapes by VSB method often causes intolerable edge roughness to degrade device characteristics from its intended performance with smooth edges. We proposed an overall EBL methodology applicable to wade-variety of EBL applications utilizing VSB and CP methods. Its key idea is in our layout data conversion algorithm that decomposes curved or oblique edges of arbitrary layout patterns into CP shots. We expect significant reduction in EB shot count with a CP-bordered exposure data compared to the corresponding VSB-alone conversion result. Several CP conversion parameters are used to optimize EB exposure throughput, edge quality, and resultant device characteristics. We demonstrated out methodology using the leading-edge VSB/CP EBL tool, ADVANTEST F7000S-VD02, with high resolution Hydrogen Silsesquioxane (HSQ) resist. Through our experiments of curved and oblique edge lithography under various data conversion conditions, we learned correspondence of the conversion parameters to the resultant edge roughness and other conditions. They will be utilized as the fundamental data for further enhancement of our EBL strategy for optimized EB exposure.

Divertor target shape optimization in realistic edge plasma geometry

NASA Astrophysics Data System (ADS)

Dekeyser, W.; Reiter, D.; Baelmans, M.

2014-07-01

Tokamak divertor design for next-step fusion reactors heavily relies on numerical simulations of the plasma edge. Currently, the design process is mainly done in a forward approach, where the designer is strongly guided by his experience and physical intuition in proposing divertor shapes, which are then thoroughly assessed by numerical computations. On the other hand, automated design methods based on optimization have proven very successful in the related field of aerodynamic design. By recasting design objectives and constraints into the framework of a mathematical optimization problem, efficient forward-adjoint based algorithms can be used to automatically compute the divertor shape which performs the best with respect to the selected edge plasma model and design criteria. In the past years, we have extended these methods to automated divertor target shape design, using somewhat simplified edge plasma models and geometries. In this paper, we build on and extend previous work to apply these shape optimization methods for the first time in more realistic, single null edge plasma and divertor geometry, as commonly used in current divertor design studies. In a case study with JET-like parameters, we show that the so-called one-shot method is very effective is solving divertor target design problems. Furthermore, by detailed shape sensitivity analysis we demonstrate that the development of the method already at the present state provides physically plausible trends, allowing to achieve a divertor design with an almost perfectly uniform power load for our particular choice of edge plasma model and design criteria.

Gas turbine bucket wall thickness control

DOEpatents

Stathopoulos, Dimitrios; Xu, Liming; Lewis, Doyle C.

2002-01-01

A core for use in casting a turbine bucket including serpentine cooling passages is divided into two pieces including a leading edge core section and a trailing edge core section. Wall thicknesses at the leading edge and the trailing edge of the turbine bucket can be controlled independent of each other by separately positioning the leading edge core section and the trailing edge core section in the casting die. The controlled leading and trailing edge thicknesses can thus be optimized for efficient cooling, resulting in more efficient turbine operation.

Edge Detection Based On the Characteristic of Primary Visual Cortex Cells

NASA Astrophysics Data System (ADS)

Zhu, M. M.; Xu, Y. L.; Ma, H. Q.

2018-01-01

Aiming at the problem that it is difficult to balance the accuracy of edge detection and anti-noise performance, and referring to the dynamic and static perceptions of the primary visual cortex (V1) cells, a V1 cell model is established to perform edge detection. A spatiotemporal filter is adopted to simulate the receptive field of V1 simple cells, the model V1 cell is obtained after integrating the responses of simple cells by half-wave rectification and normalization, Then the natural image edge is detected by using static perception of V1 cells. The simulation results show that, the V1 model can basically fit the biological data and has the universality of biology. What’s more, compared with other edge detection operators, the proposed model is more effective and has better robustness

Using new edges for anomaly detection in computer networks

DOEpatents

Neil, Joshua Charles

2017-07-04

Creation of new edges in a network may be used as an indication of a potential attack on the network. Historical data of a frequency with which nodes in a network create and receive new edges may be analyzed. Baseline models of behavior among the edges in the network may be established based on the analysis of the historical data. A new edge that deviates from a respective baseline model by more than a predetermined threshold during a time window may be detected. The new edge may be flagged as potentially anomalous when the deviation from the respective baseline model is detected. Probabilities for both new and existing edges may be obtained for all edges in a path or other subgraph. The probabilities may then be combined to obtain a score for the path or other subgraph. A threshold may be obtained by calculating an empirical distribution of the scores under historical conditions.

Using new edges for anomaly detection in computer networks

DOEpatents

Neil, Joshua Charles

2015-05-19

Creation of new edges in a network may be used as an indication of a potential attack on the network. Historical data of a frequency with which nodes in a network create and receive new edges may be analyzed. Baseline models of behavior among the edges in the network may be established based on the analysis of the historical data. A new edge that deviates from a respective baseline model by more than a predetermined threshold during a time window may be detected. The new edge may be flagged as potentially anomalous when the deviation from the respective baseline model is detected. Probabilities for both new and existing edges may be obtained for all edges in a path or other subgraph. The probabilities may then be combined to obtain a score for the path or other subgraph. A threshold may be obtained by calculating an empirical distribution of the scores under historical conditions.

Anti-impulse-noise Edge Detection via Anisotropic Morphological Directional Derivatives.

PubMed

Shui, Peng-Lang; Wang, Fu-Ping

2017-07-13

Traditional differential-based edge detection suffers from abrupt degradation in performance when images are corrupted by impulse noises. The morphological operators such as the median filters and weighted median filters possess the intrinsic ability to counteract impulse noise. In this paper, by combining the biwindow configuration with weighted median filters, anisotropic morphological directional derivatives (AMDD) robust to impulse noise are proposed to measure the local grayscale variation around a pixel. For ideal step edges, the AMDD spatial response and directional representation are derived. The characteristics and edge resolution of two kinds of typical biwindows are analyzed thoroughly. In terms of the AMDD spatial response and directional representation of ideal step edges, the spatial matched filter is used to extract the edge strength map (ESM) from the AMDDs of an image. The spatial and directional matched filters are used to extract the edge direction map (EDM). Embedding the extracted ESM and EDM into the standard route of the differential-based edge detection, an anti-impulse-noise AMDD-based edge detector is constructed. It is compared with the existing state-of-the-art detectors on a recognized image dataset for edge detection evaluation. The results show that it attains competitive performance in noise-free and Gaussian noise cases and the best performance in impulse noise cases.

Penalization of aperture complexity in inversely planned volumetric modulated arc therapy

PubMed Central

Younge, Kelly C.; Matuszak, Martha M.; Moran, Jean M.; McShan, Daniel L.; Fraass, Benedick A.; Roberts, Donald A.

2012-01-01

Purpose: Apertures obtained during volumetric modulated arc therapy (VMAT) planning can be small and irregular, resulting in dosimetric inaccuracies during delivery. Our purpose is to develop and integrate an aperture-regularization objective function into the optimization process for VMAT, and to quantify the impact of using this objective function on dose delivery accuracy and optimized dose distributions. Methods: An aperture-based metric (“edge penalty”) was developed that penalizes complex aperture shapes based on the ratio of MLC side edge length and aperture area. To assess the utility of the metric, VMAT plans were created for example paraspinal, brain, and liver SBRT cases with and without incorporating the edge penalty in the cost function. To investigate the dose calculation accuracy, Gafchromic EBT2 film was used to measure the 15 highest weighted apertures individually and as a composite from each of two paraspinal plans: one with and one without the edge penalty applied. Films were analyzed using a triple-channel nonuniformity correction and measurements were compared directly to calculations. Results: Apertures generated with the edge penalty were larger, more regularly shaped and required up to 30% fewer monitor units than those created without the edge penalty. Dose volume histogram analysis showed that the changes in doses to targets, organs at risk, and normal tissues were negligible. Edge penalty apertures that were measured with film for the paraspinal plan showed a notable decrease in the number of pixels disagreeing with calculation by more than 10%. For a 5% dose passing criterion, the number of pixels passing in the composite dose distributions for the non-edge penalty and edge penalty plans were 52% and 96%, respectively. Employing gamma with 3% dose/1 mm distance criteria resulted in a 79.5% (without penalty)/95.4% (with penalty) pass rate for the two plans. Gradient compensation of 3%/1 mm resulted in 83.3%/96.2% pass rates. Conclusions: The use of the edge penalty during optimization has the potential to markedly improve dose delivery accuracy for VMAT plans while still maintaining high quality optimized dose distributions. The penalty regularizes aperture shape and improves delivery efficiency. PMID:23127107

Real-time edge-enhanced optical correlator

NASA Technical Reports Server (NTRS)

Liu, Tsuen-Hsi (Inventor); Cheng, Li-Jen (Inventor)

1992-01-01

Edge enhancement of an input image by four-wave mixing a first write beam with a second write beam in a photorefractive crystal, GaAs, was achieved for VanderLugt optical correlation with an edge enhanced reference image by optimizing the power ratio of a second write beam to the first write beam (70:1) and optimizing the power ratio of a read beam, which carries the reference image to the first write beam (100:701). Liquid crystal TV panels are employed as spatial light modulators to change the input and reference images in real time.

Robust design of multiple trailing edge flaps for helicopter vibration reduction: A multi-objective bat algorithm approach

NASA Astrophysics Data System (ADS)

Mallick, Rajnish; Ganguli, Ranjan; Seetharama Bhat, M.

2015-09-01

The objective of this study is to determine an optimal trailing edge flap configuration and flap location to achieve minimum hub vibration levels and flap actuation power simultaneously. An aeroelastic analysis of a soft in-plane four-bladed rotor is performed in conjunction with optimal control. A second-order polynomial response surface based on an orthogonal array (OA) with 3-level design describes both the objectives adequately. Two new orthogonal arrays called MGB2P-OA and MGB4P-OA are proposed to generate nonlinear response surfaces with all interaction terms for two and four parameters, respectively. A multi-objective bat algorithm (MOBA) approach is used to obtain the optimal design point for the mutually conflicting objectives. MOBA is a recently developed nature-inspired metaheuristic optimization algorithm that is based on the echolocation behaviour of bats. It is found that MOBA inspired Pareto optimal trailing edge flap design reduces vibration levels by 73% and flap actuation power by 27% in comparison with the baseline design.

Morphing Wings: A Study Using High-Fidelity Aerodynamic Shape Optimization

NASA Astrophysics Data System (ADS)

Curiale, Nathanael J.

With the aviation industry under pressure to reduce fuel consumption, morphing wings have the capacity to improve aircraft performance, thereby making a significant contribution to reversing climate change. Through high-fidelity aerodynamic shape optimization, various forms of morphing wings are assessed for a hypothetical regional-class aircraft. The framework used solves the Reynolds-averaged Navier-Stokes equations and utilizes a gradient-based optimization algorithm. Baseline geometries are developed through multipoint optimization, where the average drag coefficient is minimized over a range of flight conditions with additional dive constraints. Morphing optimizations are then performed, beginning with these baseline shapes. Five distinct types of morphing are investigated and compared. Overall, a theoretical fully adaptable wing produces roughly a 2% improvement in average performance, whereas trailing-edge morphing with a 27-point multipoint baseline results in just over a 1% improvement in average performance. Trailing-edge morphing proves to be more beneficial than leading-edge morphing, upper-surface morphing, and a conventional flap.

Energy discriminating x-ray camera utilizing a cadmium telluride detector

NASA Astrophysics Data System (ADS)

Sato, Eiichi; Purkhet, Abderyim; Matsukiyo, Hiroshi; Osawa, Akihiro; Enomoto, Toshiyuki; Wantanabe, Manabu; Nagao, Jiro; Nomiya, Seiichiro; Hitomi, Keitaro; Tanaka, Etsuro; Kawai, Toshiaki; Sato, Shigehiro; Ogawa, Akira; Onagawa, Jun

2009-07-01

An energy-discriminating x-ray camera is useful for performing monochromatic radiography using polychromatic x rays. This x-ray camera was developed to carry out K-edge radiography using iodine-based contrast media. In this camera, objects are exposed by a cone beam from a cerium x-ray generator, and penetrating x-ray photons are detected by a cadmium telluride detector with an amplifier unit. The optimal x-ray photon energy and the energy width are selected out using a multichannel analyzer, and the photon number is counted by a counter card. Radiography was performed by the detector scanning using an x-y stage driven by a two-stage controller, and radiograms obtained by energy discriminating are shown on a personal computer monitor. In radiography, the tube voltage and current were 60 kV and 36 μA, respectively, and the x-ray intensity was 4.7 μGy/s. Cerium K-series characteristic x rays are absorbed effectively by iodine-based contrast media, and iodine K-edge radiography was performed using x rays with energies just beyond iodine K-edge energy 33.2 keV.

A radiation detector design mitigating problems related to sawed edges

NASA Astrophysics Data System (ADS)

Aurola, A.; Marochkin, V.; Tuuva, T.

2014-12-01

In pixelated silicon radiation detectors that are utilized for the detection of UV, visible, and in particular Near Infra-Red (NIR) light it is desirable to utilize a relatively thick fully depleted Back-Side Illuminated (BSI) detector design providing 100% Fill Factor (FF), low Cross-Talk (CT), and high Quantum Efficiency (QE). The optimal thickness of such detectors is typically less than 300μm and above 40μm and thus it is more or less mandatory to thin the detector wafer from the backside after the front side of the detector has been processed and before a conductive layer is formed on the backside. A TAIKO thinning process is optimal for such a thickness range since neither a support substrate on the front side nor lithographic steps on the backside are required. The conductive backside layer should, however, be homogenous throughout the wafer and it should be biased from the front side of the detector. In order to provide good QE for blue and UV light the conductive backside layer should be of opposite doping type than the substrate. The problem with a homogeneous backside layer being of opposite doping type than the substrate is that a lot of leakage current is typically generated at the sawed chip edges, which may increase the dark noise and the power consumption. These problems are substantially mitigated with a proposed detector edge arrangement which 2D simulation results are presented in this paper.

An optimized knife-edge method for on-orbit MTF estimation of optical sensors using powell parameter fitting

NASA Astrophysics Data System (ADS)

Han, Lu; Gao, Kun; Gong, Chen; Zhu, Zhenyu; Guo, Yue

2017-08-01

On-orbit Modulation Transfer Function (MTF) is an important indicator to evaluate the performance of the optical remote sensors in a satellite. There are many methods to estimate MTF, such as pinhole method, slit method and so on. Among them, knife-edge method is quite efficient, easy-to-use and recommended in ISO12233 standard for the wholefrequency MTF curve acquisition. However, the accuracy of the algorithm is affected by Edge Spread Function (ESF) fitting accuracy significantly, which limits the range of application. So in this paper, an optimized knife-edge method using Powell algorithm is proposed to improve the ESF fitting precision. Fermi function model is the most popular ESF fitting model, yet it is vulnerable to the initial values of the parameters. Considering the characteristics of simple and fast convergence, Powell algorithm is applied to fit the accurate parameters adaptively with the insensitivity to the initial parameters. Numerical simulation results reveal the accuracy and robustness of the optimized algorithm under different SNR, edge direction and leaning angles conditions. Experimental results using images of the camera in ZY-3 satellite show that this method is more accurate than the standard knife-edge method of ISO12233 in MTF estimation.

Cell edge detection in JPEG2000 wavelet domain - analysis on sigmoid function edge model.

PubMed

Punys, Vytenis; Maknickas, Ramunas

2011-01-01

Big virtual microscopy images (80K x 60K pixels and larger) are usually stored using the JPEG2000 image compression scheme. Diagnostic quantification, based on image analysis, might be faster if performed on compressed data (approx. 20 times less the original amount), representing the coefficients of the wavelet transform. The analysis of possible edge detection without reverse wavelet transform is presented in the paper. Two edge detection methods, suitable for JPEG2000 bi-orthogonal wavelets, are proposed. The methods are adjusted according calculated parameters of sigmoid edge model. The results of model analysis indicate more suitable method for given bi-orthogonal wavelet.

A Semi-Automatic Method for Image Analysis of Edge Dynamics in Living Cells

PubMed Central

Huang, Lawrence; Helmke, Brian P.

2011-01-01

Spatial asymmetry of actin edge ruffling contributes to the process of cell polarization and directional migration, but mechanisms by which external cues control actin polymerization near cell edges remain unclear. We designed a quantitative image analysis strategy to measure the spatiotemporal distribution of actin edge ruffling. Time-lapse images of endothelial cells (ECs) expressing mRFP-actin were segmented using an active contour method. In intensity line profiles oriented normal to the cell edge, peak detection identified the angular distribution of polymerized actin within 1 µm of the cell edge, which was localized to lamellipodia and edge ruffles. Edge features associated with filopodia and peripheral stress fibers were removed. Circular statistical analysis enabled detection of cell polarity, indicated by a unimodal distribution of edge ruffles. To demonstrate the approach, we detected a rapid, nondirectional increase in edge ruffling in serum-stimulated ECs and a change in constitutive ruffling orientation in quiescent, nonpolarized ECs. Error analysis using simulated test images demonstrate robustness of the method to variations in image noise levels, edge ruffle arc length, and edge intensity gradient. These quantitative measurements of edge ruffling dynamics enable investigation at the cellular length scale of the underlying molecular mechanisms regulating actin assembly and cell polarization. PMID:21643526

Improvement and implementation for Canny edge detection algorithm

NASA Astrophysics Data System (ADS)

Yang, Tao; Qiu, Yue-hong

2015-07-01

Edge detection is necessary for image segmentation and pattern recognition. In this paper, an improved Canny edge detection approach is proposed due to the defect of traditional algorithm. A modified bilateral filter with a compensation function based on pixel intensity similarity judgment was used to smooth image instead of Gaussian filter, which could preserve edge feature and remove noise effectively. In order to solve the problems of sensitivity to the noise in gradient calculating, the algorithm used 4 directions gradient templates. Finally, Otsu algorithm adaptively obtain the dual-threshold. All of the algorithm simulated with OpenCV 2.4.0 library in the environments of vs2010, and through the experimental analysis, the improved algorithm has been proved to detect edge details more effectively and with more adaptability.

Optimization of Second Fault Detection Thresholds to Maximize Mission POS

NASA Technical Reports Server (NTRS)

Anzalone, Evan

2018-01-01

In order to support manned spaceflight safety requirements, the Space Launch System (SLS) has defined program-level requirements for key systems to ensure successful operation under single fault conditions. To accommodate this with regards to Navigation, the SLS utilizes an internally redundant Inertial Navigation System (INS) with built-in capability to detect, isolate, and recover from first failure conditions and still maintain adherence to performance requirements. The unit utilizes multiple hardware- and software-level techniques to enable detection, isolation, and recovery from these events in terms of its built-in Fault Detection, Isolation, and Recovery (FDIR) algorithms. Successful operation is defined in terms of sufficient navigation accuracy at insertion while operating under worst case single sensor outages (gyroscope and accelerometer faults at launch). In addition to first fault detection and recovery, the SLS program has also levied requirements relating to the capability of the INS to detect a second fault, tracking any unacceptable uncertainty in knowledge of the vehicle's state. This detection functionality is required in order to feed abort analysis and ensure crew safety. Increases in navigation state error and sensor faults can drive the vehicle outside of its operational as-designed environments and outside of its performance envelope causing loss of mission, or worse, loss of crew. The criteria for operation under second faults allows for a larger set of achievable missions in terms of potential fault conditions, due to the INS operating at the edge of its capability. As this performance is defined and controlled at the vehicle level, it allows for the use of system level margins to increase probability of mission success on the operational edges of the design space. Due to the implications of the vehicle response to abort conditions (such as a potentially failed INS), it is important to consider a wide range of failure scenarios in terms of both magnitude and time. As such, the Navigation team is taking advantage of the INS's capability to schedule and change fault detection thresholds in flight. These values are optimized along a nominal trajectory in order to maximize probability of mission success, and reducing the probability of false positives (defined as when the INS would report a second fault condition resulting in loss of mission, but the vehicle would still meet insertion requirements within system-level margins). This paper will describe an optimization approach using Genetic Algorithms to tune the threshold parameters to maximize vehicle resilience to second fault events as a function of potential fault magnitude and time of fault over an ascent mission profile. The analysis approach, and performance assessment of the results will be presented to demonstrate the applicability of this process to second fault detection to maximize mission probability of success.

Supporting the Maritime Information Dominance: Optimizing Tactical Network for Biometric Data Sharing in Maritime Interdiction Operations

DTIC Science & Technology

2015-03-01

information dominance in the maritime domain by optimizing tactical mobile ad hoc network (MANET) systems for wireless sharing of biometric data in maritime interdiction operations (MIO). Current methods for sharing biometric data in MIO are unnecessarily slow and do not leverage wireless networks at the tactical edge to maximize information dominance . Field experiments allow students to test wireless MANETs at the tactical edge. Analysis is focused on determining optimal MANET design and implementation. It considers various implementations with

Towards predictive diagnosis and management of rotator cuff disease: using curvelet transform for edge detection and segmentation of tissue

NASA Astrophysics Data System (ADS)

Pai Raikar, Vipul; Kwartowitz, David M.

2016-04-01

Degradation and injury of the rotator cuff is one of the most common diseases of the shoulder among the general population. In orthopedic injuries, rotator cuff disease is only second to back pain in terms of overall reduced quality of life for patients. Clinically, this disease is managed via pain and activity assessment and diagnostic imaging using ultrasound and MRI. Ultrasound has been shown to have good accuracy for identification and measurement of rotator cuff tears. In our previous work, we have developed novel, real-time techniques to biomechanically assess the condition of the rotator cuff based on Musculoskeletal Ultrasound. Of the rotator cuff tissues, supraspinatus is the first that sees degradation and is the most commonly affected. In our work, one of the challenges lies in effectively segmenting and characterizing the supraspinatus. We are exploring the possibility of using curvelet transform for improving techniques to segment tissue in ultrasound. Curvelets have been shown to give optimal multi-scale representation of edges in images. They are designed to represent edges and singularities along curves in images which makes them an attractive proposition for use in ultrasound segmentation. In this work, we present a novel approach to the possibility of using curvelet transforms for automatic edge and feature extraction for the supraspinatus.

Content-based unconstrained color logo and trademark retrieval with color edge gradient co-occurrence histograms

NASA Astrophysics Data System (ADS)

Phan, Raymond; Androutsos, Dimitrios

2008-01-01

In this paper, we present a logo and trademark retrieval system for unconstrained color image databases that extends the Color Edge Co-occurrence Histogram (CECH) object detection scheme. We introduce more accurate information to the CECH, by virtue of incorporating color edge detection using vector order statistics. This produces a more accurate representation of edges in color images, in comparison to the simple color pixel difference classification of edges as seen in the CECH. Our proposed method is thus reliant on edge gradient information, and as such, we call this the Color Edge Gradient Co-occurrence Histogram (CEGCH). We use this as the main mechanism for our unconstrained color logo and trademark retrieval scheme. Results illustrate that the proposed retrieval system retrieves logos and trademarks with good accuracy, and outperforms the CECH object detection scheme with higher precision and recall.

Implementation of sobel method to detect the seed rubber plant leaves

NASA Astrophysics Data System (ADS)

Suyanto; Munte, J.

2018-03-01

This research was conducted to develop a system that can identify and recognize the type of rubber tree based on the pattern of leaves of the plant. The steps research are started with the identification of the image data acquisition, image processing, image edge detection and identification method template matching. Edge detection is using Sobel edge detection. Pattern recognition would detect image as input and compared with other images in a database called templates. Experiments carried out in one phase, identification of the leaf edge, using a rubber plant leaf image 14 are superior and 5 for each type of test images (clones) of the plant. From the experimental results obtained by the recognition rate of 91.79%.

An Adaptive Immune Genetic Algorithm for Edge Detection

NASA Astrophysics Data System (ADS)

Li, Ying; Bai, Bendu; Zhang, Yanning

An adaptive immune genetic algorithm (AIGA) based on cost minimization technique method for edge detection is proposed. The proposed AIGA recommends the use of adaptive probabilities of crossover, mutation and immune operation, and a geometric annealing schedule in immune operator to realize the twin goals of maintaining diversity in the population and sustaining the fast convergence rate in solving the complex problems such as edge detection. Furthermore, AIGA can effectively exploit some prior knowledge and information of the local edge structure in the edge image to make vaccines, which results in much better local search ability of AIGA than that of the canonical genetic algorithm. Experimental results on gray-scale images show the proposed algorithm perform well in terms of quality of the final edge image, rate of convergence and robustness to noise.

Long-range, noncoherent laser Doppler velocimeter.

PubMed

Bloom, S H; Kremer, R; Searcy, P A; Rivers, M; Menders, J; Korevaar, E

1991-11-15

An experimental demonstration of a long-range, noncoherent laser Doppler velocimeter (LDV) is presented. The LDV detects incoming Doppler-shifted signal photons by using the sharp spectral absorption features in atomic or molecular vapors. The edge of the absorption feature is used to convert changes in frequency to large changes in transmission. Preliminary measurements of wind velocity using seeded aerosols showed that the LDV results agreed with mechanical anemometer measurements to within the accuracy of the LDV measurements. With optimization the LDV will provide accurate range-resolved and vibration-tolerant wind-speed measurements at large distances.

An acoustofluidic micromixer based on oscillating sidewall sharp-edges.

PubMed

Huang, Po-Hsun; Xie, Yuliang; Ahmed, Daniel; Rufo, Joseph; Nama, Nitesh; Chen, Yuchao; Chan, Chung Yu; Huang, Tony Jun

2013-10-07

Rapid and homogeneous mixing inside a microfluidic channel is demonstrated via the acoustic streaming phenomenon induced by the oscillation of sidewall sharp-edges. By optimizing the design of the sharp-edges, excellent mixing performance and fast mixing speed can be achieved in a simple device, making our sharp-edge-based acoustic micromixer a promising candidate for a wide variety of applications.

A model for managing edge effects in harvest scheduling using spatial optimization

Treesearch

Kai L. Ross; Sándor F. Tóth

2016-01-01

Actively managed forest stands can create new forest edges. If left unchecked over time and across space, forest operations such as clear-cuts can create complex networks of forest edges. Newly created edges alter the landscape and can affect many environmental factors. These altered environmental factors have a variety of impacts on forest growth and structure and can...

Automated divertor target design by adjoint shape sensitivity analysis and a one-shot method

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

Dekeyser, W., E-mail: Wouter.Dekeyser@kuleuven.be; Reiter, D.; Baelmans, M.

As magnetic confinement fusion progresses towards the development of first reactor-scale devices, computational tokamak divertor design is a topic of high priority. Presently, edge plasma codes are used in a forward approach, where magnetic field and divertor geometry are manually adjusted to meet design requirements. Due to the complex edge plasma flows and large number of design variables, this method is computationally very demanding. On the other hand, efficient optimization-based design strategies have been developed in computational aerodynamics and fluid mechanics. Such an optimization approach to divertor target shape design is elaborated in the present paper. A general formulation ofmore » the design problems is given, and conditions characterizing the optimal designs are formulated. Using a continuous adjoint framework, design sensitivities can be computed at a cost of only two edge plasma simulations, independent of the number of design variables. Furthermore, by using a one-shot method the entire optimization problem can be solved at an equivalent cost of only a few forward simulations. The methodology is applied to target shape design for uniform power load, in simplified edge plasma geometry.« less

Contour Tracking with a Spatio-Temporal Intensity Moment.

PubMed

Demi, Marcello

2016-06-01

Standard edge detection operators such as the Laplacian of Gaussian and the gradient of Gaussian can be used to track contours in image sequences. When using edge operators, a contour, which is determined on a frame of the sequence, is simply used as a starting contour to locate the nearest contour on the subsequent frame. However, the strategy used to look for the nearest edge points may not work when tracking contours of non isolated gray level discontinuities. In these cases, strategies derived from the optical flow equation, which look for similar gray level distributions, appear to be more appropriate since these can work with a lower frame rate than that needed for strategies based on pure edge detection operators. However, an optical flow strategy tends to propagate the localization errors through the sequence and an additional edge detection procedure is essential to compensate for such a drawback. In this paper a spatio-temporal intensity moment is proposed which integrates the two basic functions of edge detection and tracking.

A novel orthoimage mosaic method using the weighted A* algorithm for UAV imagery

NASA Astrophysics Data System (ADS)

Zheng, Maoteng; Zhou, Shunping; Xiong, Xiaodong; Zhu, Junfeng

2017-12-01

A weighted A* algorithm is proposed to select optimal seam-lines in orthoimage mosaic for UAV (Unmanned Aircraft Vehicle) imagery. The whole workflow includes four steps: the initial seam-line network is firstly generated by standard Voronoi Diagram algorithm; an edge diagram is then detected based on DSM (Digital Surface Model) data; the vertices (conjunction nodes) of initial network are relocated since some of them are on the high objects (buildings, trees and other artificial structures); and, the initial seam-lines are finally refined using the weighted A* algorithm based on the edge diagram and the relocated vertices. The method was tested with two real UAV datasets. Preliminary results show that the proposed method produces acceptable mosaic images in both the urban and mountainous areas, and is better than the result of the state-of-the-art methods on the datasets.

Method and apparatus for detecting flaws and defects in heat seals

NASA Technical Reports Server (NTRS)

Rai, Kula R. (Inventor); Lew, Thomas M. (Inventor); Sinclair, Robert B. (Inventor)

1993-01-01

Flaws and defects in heat seals formed between sheets of translucent film are identified by optically examining consecutive lateral sections of the seal along the seal length. Each lateral seal section is illuminated and an optical sensor array detects the intensity of light transmitted through the seal section for the purpose of detecting and locating edges in the heat seal. A line profile for each consecutive seal section is derived having an amplitude proportional to the change in light intensity across the seal section. Instances in the derived line profile where the amplitude is greater than a threshold level indicate the detection of a seal edge. The detected edges in each derived line profile are then compared to a preset profile edge standard to identify the existence of a flaw or defect.

Edge-directed inference for microaneurysms detection in digital fundus images

NASA Astrophysics Data System (ADS)

Huang, Ke; Yan, Michelle; Aviyente, Selin

2007-03-01

Microaneurysms (MAs) detection is a critical step in diabetic retinopathy screening, since MAs are the earliest visible warning of potential future problems. A variety of algorithms have been proposed for MAs detection in mass screening. Different methods have been proposed for MAs detection. The core technology for most of existing methods is based on a directional mathematical morphological operation called "Top-Hat" filter that requires multiple filtering operations at each pixel. Background structure, uneven illumination and noise often cause confusion between MAs and some non-MA structures and limits the applicability of the filter. In this paper, a novel detection framework based on edge directed inference is proposed for MAs detection. The candidate MA regions are first delineated from the edge map of a fundus image. Features measuring shape, brightness and contrast are extracted for each candidate MA region to better exclude false detection from true MAs. Algorithmic analysis and empirical evaluation reveal that the proposed edge directed inference outperforms the "Top-Hat" based algorithm in both detection accuracy and computational speed.

Learning to predict where human gaze is using quaternion DCT based regional saliency detection

NASA Astrophysics Data System (ADS)

Li, Ting; Xu, Yi; Zhang, Chongyang

2014-09-01

Many current visual attention approaches used semantic features to accurately capture human gaze. However, these approaches demand high computational cost and can hardly be applied to daily use. Recently, some quaternion-based saliency detection models, such as PQFT (phase spectrum of Quaternion Fourier Transform), QDCT (Quaternion Discrete Cosine Transform), have been proposed to meet real-time requirement of human gaze tracking tasks. However, current saliency detection methods used global PQFT and QDCT to locate jump edges of the input, which can hardly detect the object boundaries accurately. To address the problem, we improved QDCT-based saliency detection model by introducing superpixel-wised regional saliency detection mechanism. The local smoothness of saliency value distribution is emphasized to distinguish noises of background from salient regions. Our algorithm called saliency confidence can distinguish the patches belonging to the salient object and those of the background. It decides whether the image patches belong to the same region. When an image patch belongs to a region consisting of other salient patches, this patch should be salient as well. Therefore, we use saliency confidence map to get background weight and foreground weight to do the optimization on saliency map obtained by QDCT. The optimization is accomplished by least square method. The optimization approach we proposed unifies local and global saliency by combination of QDCT and measuring the similarity between each image superpixel. We evaluate our model on four commonly-used datasets (Toronto, MIT, OSIE and ASD) using standard precision-recall curves (PR curves), the mean absolute error (MAE) and area under curve (AUC) measures. In comparison with most state-of-art models, our approach can achieve higher consistency with human perception without training. It can get accurate human gaze even in cluttered background. Furthermore, it achieves better compromise between speed and accuracy.

Optimization of the blade trailing edge geometric parameters for a small scale ORC turbine

NASA Astrophysics Data System (ADS)

Zhang, L.; Zhuge, W. L.; Peng, J.; Liu, S. J.; Zhang, Y. J.

2013-12-01

In general, the method proposed by Whitfield and Baines is adopted for the turbine preliminary design. In this design procedure for the turbine blade trailing edge geometry, two assumptions (ideal gas and zero discharge swirl) and two experience values (WR and γ) are used to get the three blade trailing edge geometric parameters: relative exit flow angle β6, the exit tip radius R6t and hub radius R6h for the purpose of maximizing the rotor total-to-static isentropic efficiency. The method above is established based on the experience and results of testing using air as working fluid, so it does not provide a mathematical optimal solution to instruct the optimization of geometry parameters and consider the real gas effects of the organic, working fluid which must be taken into consideration for the ORC turbine design procedure. In this paper, a new preliminary design and optimization method is established for the purpose of reducing the exit kinetic energy loss to improve the turbine efficiency ηts, and the blade trailing edge geometric parameters for a small scale ORC turbine with working fluid R123 are optimized based on this method. The mathematical optimal solution to minimize the exit kinetic energy is deduced, which can be used to design and optimize the exit shroud/hub radius and exit blade angle. And then, the influence of blade trailing edge geometric parameters on turbine efficiency ηts are analysed and the optimal working ranges of these parameters for the equations are recommended in consideration of working fluid R123. This method is used to modify an existing ORC turbine exit kinetic energy loss from 11.7% to 7%, which indicates the effectiveness of the method. However, the internal passage loss increases from 7.9% to 9.4%, so the only way to consider the influence of geometric parameters on internal passage loss is to give the empirical ranges of these parameters, such as the recommended ranges that the value of γ is at 0.3 to 0.4, and the value of τ is at 0.5 to 0.6.

Processing Images of Craters for Spacecraft Navigation

NASA Technical Reports Server (NTRS)

Cheng, Yang; Johnson, Andrew E.; Matthies, Larry H.

2009-01-01

A crater-detection algorithm has been conceived to enable automation of what, heretofore, have been manual processes for utilizing images of craters on a celestial body as landmarks for navigating a spacecraft flying near or landing on that body. The images are acquired by an electronic camera aboard the spacecraft, then digitized, then processed by the algorithm, which consists mainly of the following steps: 1. Edges in an image detected and placed in a database. 2. Crater rim edges are selected from the edge database. 3. Edges that belong to the same crater are grouped together. 4. An ellipse is fitted to each group of crater edges. 5. Ellipses are refined directly in the image domain to reduce errors introduced in the detection of edges and fitting of ellipses. 6. The quality of each detected crater is evaluated. It is planned to utilize this algorithm as the basis of a computer program for automated, real-time, onboard processing of crater-image data. Experimental studies have led to the conclusion that this algorithm is capable of a detection rate >93 percent, a false-alarm rate <5 percent, a geometric error <0.5 pixel, and a position error <0.3 pixel.

Alpha-ray detection with a MgB 2 transition edge sensor

NASA Astrophysics Data System (ADS)

Okayasu, S.; Katagiri, M.; Hojou, K.; Morii, Y.; Miki, S.; Shimakage, H.; Wang, Z.; Ishida, T.

2008-09-01

We have been investigating for neutron detection with the MgB 2 transition edge sensor (TES). For the purpose, we have been developing a low noise measurement system for the detection. To confirm the performance of the detecting sensor, alpha ray detection from an americium-241 ( 241Am) alpha-ray source was achieved. A short microfabricated sample with 10 μm length and 1 μm width is used to improve the S/N ratio. The detection is achieved under a constant current condition in the range between 1 and 6 μA bias current, and the resistivity changes at the sample due to the alpha ray irradiation is detected just on the transition edge.

Optimal perturbations of a finite-width mixing layer near the trailing edge

NASA Astrophysics Data System (ADS)

Gumbart, James C.; Rabchuk, James

2002-03-01

The trailing edge of a surface separating two fluid flows can act as an efficient receptor for acoustic or other disturbances. The incident wave energy is converted by a linear mechanism into incipient flow instabilities which lead further downstream to the transition to turbulence. Understanding this process is essential for analyzing feedback loops and other resonances which can cause unwanted structural vibrations in the surface material or directed acoustic emissions from the mixing region. Previously, the modes of instability in a finite-width mixing layer near the trailing edge were studied as a function of frequency by assuming that vorticity was continually being introduced into the flow at the trailing edge by the forcing field. It was found that the initial amplitude of the growing instability mode was a sharply decreasing function of forcing frequency, and that the initial amplitude was a minimum for the frequency at which the rate of instability growth was a maximum^1. This result has led to a study of the adjoint equation for the perturbation stream function, whose eigensolutions are known to be associated with the optimal perturbation field for the frequency of forcing leading to the greatest instability growth downstream. We have obtained these solutions for a piecewise linear velocity profile near the trailing edge using group-theoretic techniques and have shown that they are indeed optimal. We have also analyzed the nature of the physical forcing field that might produce these optimal perturbations. ^1 Rabchuk, J.A., July 2000, Physics of Fluids.

Optimization of K-edge imaging for vulnerable plaques using gold nanoparticles and energy resolved photon counting detectors: a simulation study.

PubMed

Alivov, Yahya; Baturin, Pavlo; Le, Huy Q; Ducote, Justin; Molloi, Sabee

2014-01-06

We investigated the effect of different imaging parameters, such as dose, beam energy, energy resolution and the number of energy bins, on the image quality of K-edge spectral computed tomography (CT) of gold nanoparticles (GNP) accumulated in an atherosclerotic plaque. A maximum likelihood technique was employed to estimate the concentration of GNP, which served as a targeted intravenous contrast material intended to detect the degree of the plaque's inflammation. The simulation studies used a single-slice parallel beam CT geometry with an x-ray beam energy ranging between 50 and 140 kVp. The synthetic phantoms included small (3 cm in diameter) cylinder and chest (33 × 24 cm(2)) phantoms, where both phantoms contained tissue, calcium and gold. In the simulation studies, GNP quantification and background (calcium and tissue) suppression tasks were pursued. The x-ray detection sensor was represented by an energy resolved photon counting detector (e.g., CdZnTe) with adjustable energy bins. Both ideal and more realistic (12% full width at half maximum (FWHM) energy resolution) implementations of the photon counting detector were simulated. The simulations were performed for the CdZnTe detector with a pixel pitch of 0.5-1 mm, which corresponds to a performance without significant charge sharing and cross-talk effects. The Rose model was employed to estimate the minimum detectable concentration of GNPs. A figure of merit (FOM) was used to optimize the x-ray beam energy (kVp) to achieve the highest signal-to-noise ratio with respect to the patient dose. As a result, the successful identification of gold and background suppression was demonstrated. The highest FOM was observed at the 125 kVp x-ray beam energy. The minimum detectable GNP concentration was determined to be approximately 1.06 µmol mL(-1) (0.21 mg mL(-1)) for an ideal detector and about 2.5 µmol mL(-1) (0.49 mg mL(-1)) for a more realistic (12% FWHM) detector. The studies show the optimal imaging parameters at the lowest patient dose using an energy resolved photon counting detector to image GNP in an atherosclerotic plaque.

Feasibility of spectral CT imaging for the detection of liver lesions with gold-based contrast agents - A simulation study.

PubMed

Müllner, Marie; Schlattl, Helmut; Hoeschen, Christoph; Dietrich, Olaf

2015-12-01

To demonstrate the feasibility of gold-specific spectral CT imaging for the detection of liver lesions in humans at low concentrations of gold as targeted contrast agent. A Monte Carlo simulation study of spectral CT imaging with a photon-counting and energy-resolving detector (with 6 energy bins) was performed in a realistic phantom of the human abdomen. The detector energy thresholds were optimized for the detection of gold. The simulation results were reconstructed with the K-edge imaging algorithm; the reconstructed gold-specific images were filtered and evaluated with respect to signal-to-noise ratio and contrast-to-noise ratio (CNR). The simulations demonstrate the feasibility of spectral CT with CNRs of the specific gold signal between 2.7 and 4.8 after bilateral filtering. Using the optimized bin thresholds increases the CNRs of the lesions by up to 23% compared to bin thresholds described in former studies. Gold is a promising new CT contrast agent for spectral CT in humans; minimum tissue mass fractions of 0.2 wt% of gold are required for sufficient image contrast. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Remote Sensing of Mars: Detection of Impact Craters on the Mars Global Surveyor DTM by Integrating Edge- and Region-Based Algorithms

NASA Astrophysics Data System (ADS)

Athanassas, C. D.; Vaiopoulos, A.; Kolokoussis, P.; Argialas, D.

2018-03-01

This study integrates two different computer vision approaches, namely the circular Hough transform (CHT) and the determinant of Hessian (DoH), to detect automatically the largest number possible of craters of any size on the digital terrain model (DTM) generated by the Mars Global Surveyor mission. Specifically, application of the standard version of CHT to the DTM captured a great number of craters with diameter smaller than 50 km only, failing to capture larger craters. On the other hand, DoH was successful in detecting craters that were undetected by CHT, but its performance was deterred by the irregularity of the topographic surface encompassed: strongly undulated and inclined (trended) topographies hindered crater detection. When run on a de-trended DTM (and keeping the topology unaltered) DoH scored higher. Current results, although not optimal, encourage combined use of CHT and DoH for routine crater detection undertakings.

Detection and Length Estimation of Linear Scratch on Solid Surfaces Using an Angle Constrained Ant Colony Technique

NASA Astrophysics Data System (ADS)

Pal, Siddharth; Basak, Aniruddha; Das, Swagatam

In many manufacturing areas the detection of surface defects is one of the most important processes in quality control. Currently in order to detect small scratches on solid surfaces most of the industries working on material manufacturing rely on visual inspection primarily. In this article we propose a hybrid computational intelligence technique to automatically detect a linear scratch from a solid surface and estimate its length (in pixel unit) simultaneously. The approach is based on a swarm intelligence algorithm called Ant Colony Optimization (ACO) and image preprocessing with Wiener and Sobel filters as well as the Canny edge detector. The ACO algorithm is mostly used to compensate for the broken parts of the scratch. Our experimental results confirm that the proposed technique can be used for detecting scratches from noisy and degraded images, even when it is very difficult for conventional image processing to distinguish the scratch area from its background.

Sparse targets in hydroacoustic surveys: Balancing quantity and quality of in situ target strength data

USGS Publications Warehouse

DuFour, Mark R.; Mayer, Christine M.; Kocovsky, Patrick; Qian, Song; Warner, David M.; Kraus, Richard T.; Vandergoot, Christopher

2017-01-01

Hydroacoustic sampling of low-density fish in shallow water can lead to low sample sizes of naturally variable target strength (TS) estimates, resulting in both sparse and variable data. Increasing maximum beam compensation (BC) beyond conventional values (i.e., 3 dB beam width) can recover more targets during data analysis; however, data quality decreases near the acoustic beam edges. We identified the optimal balance between data quantity and quality with increasing BC using a standard sphere calibration, and we quantified the effect of BC on fish track variability, size structure, and density estimates of Lake Erie walleye (Sander vitreus). Standard sphere mean TS estimates were consistent with theoretical values (−39.6 dB) up to 18-dB BC, while estimates decreased at greater BC values. Natural sources (i.e., residual and mean TS) dominated total fish track variation, while contributions from measurement related error (i.e., number of single echo detections (SEDs) and BC) were proportionally low. Increasing BC led to more fish encounters and SEDs per fish, while stability in size structure and density were observed at intermediate values (e.g., 18 dB). Detection of medium to large fish (i.e., age-2+ walleye) benefited most from increasing BC, as proportional changes in size structure and density were greatest in these size categories. Therefore, when TS data are sparse and variable, increasing BC to an optimal value (here 18 dB) will maximize the TS data quantity while limiting lower-quality data near the beam edges.

Simulation and Optimization of an Airfoil with Leading Edge Slat

NASA Astrophysics Data System (ADS)

Schramm, Matthias; Stoevesandt, Bernhard; Peinke, Joachim

2016-09-01

A gradient-based optimization is used in order to improve the shape of a leading edge slat upstream of a DU 91-W2-250 airfoil. The simulations are performed by solving the Reynolds-Averaged Navier-Stokes equations (RANS) using the open source CFD code OpenFOAM. Gradients are computed via the adjoint approach, which is suitable to deal with many design parameters, but keeping the computational costs low. The implementation is verified by comparing the gradients from the adjoint method with gradients obtained by finite differences for a NACA 0012 airfoil. The simulations of the leading edge slat are validated against measurements from the acoustic wind tunnel of Oldenburg University at a Reynolds number of Re = 6 • 105. The shape of the slat is optimized using the adjoint approach resulting in a drag reduction of 2%. Although the optimization is done for Re = 6 • 105, the improvements also hold for a higher Reynolds number of Re = 7.9 • 106, which is more realistic at modern wind turbines.

High-Fidelity Aerostructural Design Optimization of Transport Aircraft with Continuous Morphing Trailing Edge Technology

NASA Astrophysics Data System (ADS)

Burdette, David A., Jr.

Adaptive morphing trailing edge technology offers the potential to decrease the fuel burn of transonic commercial transport aircraft by allowing wings to dynamically adjust to changing flight conditions. Current configurations allow flap and aileron droop; however, this approach provides limited degrees of freedom and increased drag produced by gaps in the wing's surface. Leading members in the aeronautics community including NASA, AFRL, Boeing, and a number of academic institutions have extensively researched morphing technology for its potential to improve aircraft efficiency. With modern computational tools it is possible to accurately and efficiently model aircraft configurations in order to quantify the efficiency improvements offered by mor- phing technology. Coupled high-fidelity aerodynamic and structural solvers provide the capability to model and thoroughly understand the nuanced trade-offs involved in aircraft design. This capability is important for a detailed study of the capabilities of morphing trailing edge technology. Gradient-based multidisciplinary design opti- mization provides the ability to efficiently traverse design spaces and optimize the trade-offs associated with the design. This thesis presents a number of optimization studies comparing optimized config- urations with and without morphing trailing edge devices. The baseline configuration used throughout this work is the NASA Common Research Model. The first opti- mization comparison considers the optimal fuel burn predicted by the Breguet range equation at a single cruise point. This initial singlepoint optimization comparison demonstrated a limited fuel burn savings of less than 1%. Given the effectiveness of the passive aeroelastic tailoring in the optimized non-morphing wing, the singlepoint optimization offered limited potential for morphing technology to provide any bene- fit. To provide a more appropriate comparison, a number of multipoint optimizations were performed. With a 3-point stencil, the morphing wing burned 2.53% less fuel than its optimized non-morphing counterpart. Expanding further to a 7-point stencil, the morphing wing used 5.04% less fuel. Additional studies demonstrate that the size of the morphing device can be reduced without sizable performance reductions, and that as aircraft wings' aspect ratios increase, the effectiveness of morphing trailing edge devices increases. The final set of studies in this thesis consider mission analy- sis, including climb, multi-altitude cruise, and descent. These mission analyses were performed with a number of surrogate models, trained with O(100) optimizations. These optimizations demonstrated fuel burn reductions as large as 5% at off-design conditions. The fuel burn predicted by the mission analysis was up to 2.7% lower for the morphing wing compared to the conventional configuration.

Semantic Image Segmentation with Contextual Hierarchical Models.

PubMed

Seyedhosseini, Mojtaba; Tasdizen, Tolga

2016-05-01

Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).

Ultrasound-Guided Bar Edge Labeling in the Perioperative Assessment of Nuss Bar Removal.

PubMed

Incerti, Filippo; Bertocchini, Alessia; Ghionzoli, Marco; Messineo, Antonio

2017-12-01

Nuss bar removal after minimally invasive repair of pectus excavatum in patients where bar ends are not palpable, can be a challenging procedure for the surgeon; a blind dissection toward the bar edges may lead to intercostal vessels or deep intercostal muscle injuries. In this article, we describe a fast, repeatable, low-cost technique to detect bar edge and stabilizers. A perioperative scan is performed by means of a portable ultrasonograph a few minutes before the operation. The bar edge stabilizer is detected as a hyperechogenic image with a concentric crescent while the bar edge is detected as a hyperechogenic dashed line with net edges. The scan is performed, and the actual projection on the skin of the metal plaque bulk is then labeled on the patient's chest by an ink marker. We believe that this method may improve morbidity, operative time, and consequently, hospitalization length and costs.

Active edge control in the precessions polishing process for manufacturing large mirror segments

NASA Astrophysics Data System (ADS)

Li, Hongyu; Zhang, Wei; Walker, David; Yu, Gouyo

2014-09-01

The segmentation of the primary mirror is the only promising solution for building the next generation of ground telescopes. However, manufacturing segmented mirrors presents its own challenges. The edge mis-figure impacts directly on the telescope's scientific output. The `Edge effect' significantly dominates the polishing precision. Therefore, the edge control is regarded as one of the most difficult technical issues in the segment production that needs to be addressed urgently. This paper reports an active edge control technique for the mirror segments fabrication using the Precession's polishing technique. The strategy in this technique requires that the large spot be selected on the bulk area for fast polishing, and the small spot is used for edge figuring. This can be performed by tool lift and optimizing the dell time to compensate for non-uniform material removal at the edge zone. This requires accurate and stable edge tool influence functions. To obtain the full tool influence function at the edge, we have demonstrated in previous work a novel hybrid-measurement method which uses both simultaneous phase interferometry and profilometry. In this paper, the edge effect under `Bonnet tool' polishing is investigated. The pressure distribution is analyzed by means of finite element analysis (FEA). According to the `Preston' equation, the shape of the edge tool influence functions is predicted. With this help, the multiple process parameters at the edge zone are optimized. This is demonstrated on a 200mm crosscorners hexagonal part with a result of PV less than 200nm for entire surface.

Edge detection techniques for iris recognition system

NASA Astrophysics Data System (ADS)

Tania, U. T.; Motakabber, S. M. A.; Ibrahimy, M. I.

2013-12-01

Nowadays security and authentication are the major parts of our daily life. Iris is one of the most reliable organ or part of human body which can be used for identification and authentication purpose. To develop an iris authentication algorithm for personal identification, this paper examines two edge detection techniques for iris recognition system. Between the Sobel and the Canny edge detection techniques, the experimental result shows that the Canny's technique has better ability to detect points in a digital image where image gray level changes even at slow rate.

Delaunay Refinement Mesh Generation

DTIC Science & Technology

1997-05-18

edge is locally Delaunay; thus, by Lemma 3, every edge is Delaunay. Theorem 5 Let V be a set of three or more vertices in the plane that are not all...this document. Delaunay triangulations are valuable in part because they have the following optimality properties. Theorem 6 Among all triangulations of...no locally Delaunay edges. By Theorem 5, a triangulation with no locally Delaunay edges is the Delaunay triangulation. The property of max-min

Vegetation's red edge: a possible spectroscopic biosignature of extraterrestrial plants.

PubMed

Seager, S; Turner, E L; Schafer, J; Ford, E B

2005-06-01

Earth's deciduous plants have a sharp order-of-magnitude increase in leaf reflectance between approximately 700 and 750 nm wavelength. This strong reflectance of Earth's vegetation suggests that surface biosignatures with sharp spectral features might be detectable in the spectrum of scattered light from a spatially unresolved extrasolar terrestrial planet. We assess the potential of Earth's step-function-like spectroscopic feature, referred to as the "red edge," as a tool for astrobiology. We review the basic characteristics and physical origin of the red edge and summarize its use in astronomy: early spectroscopic efforts to search for vegetation on Mars and recent reports of detection of the red edge in the spectrum of Earthshine (i.e., the spatially integrated scattered light spectrum of Earth). We present Earthshine observations from Apache Point Observatory (New Mexico) to emphasize that time variability is key to detecting weak surface biosignatures such as the vegetation red edge. We briefly discuss the evolutionary advantages of vegetation's red edge reflectance, and speculate that while extraterrestrial "light-harvesting organisms" have no compelling reason to display the exact same red edge feature as terrestrial vegetation, they might have similar spectroscopic features at different wavelengths than terrestrial vegetation. This implies that future terrestrial-planet-characterizing space missions should obtain data that allow time-varying, sharp spectral features at unknown wavelengths to be identified. We caution that some mineral reflectance edges are similar in slope and strength to vegetation's red edge (albeit at different wavelengths); if an extrasolar planet reflectance edge is detected care must be taken with its interpretation.

Edge Detection Method Based on Neural Networks for COMS MI Images

NASA Astrophysics Data System (ADS)

Lee, Jin-Ho; Park, Eun-Bin; Woo, Sun-Hee

2016-12-01

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

Edge detection of optical subaperture image based on improved differential box-counting method

NASA Astrophysics Data System (ADS)

Li, Yi; Hui, Mei; Liu, Ming; Dong, Liquan; Kong, Lingqin; Zhao, Yuejin

2018-01-01

Optical synthetic aperture imaging technology is an effective approach to improve imaging resolution. Compared with monolithic mirror system, the image of optical synthetic aperture system is often more complex at the edge, and as a result of the existence of gap between segments, which makes stitching becomes a difficult problem. So it is necessary to extract the edge of subaperture image for achieving effective stitching. Fractal dimension as a measure feature can describe image surface texture characteristics, which provides a new approach for edge detection. In our research, an improved differential box-counting method is used to calculate fractal dimension of image, then the obtained fractal dimension is mapped to grayscale image to detect edges. Compared with original differential box-counting method, this method has two improvements as follows: by modifying the box-counting mechanism, a box with a fixed height is replaced by a box with adaptive height, which solves the problem of over-counting the number of boxes covering image intensity surface; an image reconstruction method based on super-resolution convolutional neural network is used to enlarge small size image, which can solve the problem that fractal dimension can't be calculated accurately under the small size image, and this method may well maintain scale invariability of fractal dimension. The experimental results show that the proposed algorithm can effectively eliminate noise and has a lower false detection rate compared with the traditional edge detection algorithms. In addition, this algorithm can maintain the integrity and continuity of image edge in the case of retaining important edge information.

Edge detection for optical synthetic aperture based on deep neural network

NASA Astrophysics Data System (ADS)

Tan, Wenjie; Hui, Mei; Liu, Ming; Kong, Lingqin; Dong, Liquan; Zhao, Yuejin

2017-09-01

Synthetic aperture optics systems can meet the demands of the next-generation space telescopes being lighter, larger and foldable. However, the boundaries of segmented aperture systems are much more complex than that of the whole aperture. More edge regions mean more imaging edge pixels, which are often mixed and discretized. In order to achieve high-resolution imaging, it is necessary to identify the gaps between the sub-apertures and the edges of the projected fringes. In this work, we introduced the algorithm of Deep Neural Network into the edge detection of optical synthetic aperture imaging. According to the detection needs, we constructed image sets by experiments and simulations. Based on MatConvNet, a toolbox of MATLAB, we ran the neural network, trained it on training image set and tested its performance on validation set. The training was stopped when the test error on validation set stopped declining. As an input image is given, each intra-neighbor area around the pixel is taken into the network, and scanned pixel by pixel with the trained multi-hidden layers. The network outputs make a judgment on whether the center of the input block is on edge of fringes. We experimented with various pre-processing and post-processing techniques to reveal their influence on edge detection performance. Compared with the traditional algorithms or their improvements, our method makes decision on a much larger intra-neighbor, and is more global and comprehensive. Experiments on more than 2,000 images are also given to prove that our method outperforms classical algorithms in optical images-based edge detection.

Researches on Position Detection for Vacuum Switch Electrode

NASA Astrophysics Data System (ADS)

Dong, Huajun; Guo, Yingjie; Li, Jie; Kong, Yihan

2018-03-01

Form and transformation character of vacuum arc is important influencing factor on the vacuum switch performance, and the dynamic separations of electrode is the chief effecting factor on the transformation of vacuum arcs forms. Consequently, how to detect the position of electrode to calculate the separations in the arcs image is of great significance. However, gray level distribution of vacuum arcs image isn’t even, the gray level of burning arcs is high, but the gray level of electrode is low, meanwhile, the forms of vacuum arcs changes sharply, the problems above restrict electrode position detection precisely. In this paper, algorithm of detecting electrode position base on vacuum arcs image was proposed. The digital image processing technology was used in vacuum switch arcs image analysis, the upper edge and lower edge were detected respectively, then linear fitting was done using the result of edge detection, the fitting result was the position of electrode, thus, accurate position detection of electrode was realized. From the experimental results, we can see that: algorithm described in this paper detected upper and lower edge of arcs successfully and the position of electrode was obtained through calculation.

Direct Detection Doppler Lidar for Spaceborne Wind Measurement

NASA Technical Reports Server (NTRS)

Korb, C. Laurence; Flesia, Cristina

1999-01-01

Aerosol and molecular based versions of the double-edge technique can be used for direct detection Doppler lidar spaceborne wind measurement. The edge technique utilizes the edge of a high spectral resolution filter for high accuracy wind measurement using direct detection lidar. The signal is split between an edge filter channel and a broadband energy monitor channel. The energy monitor channel is used for signal normalization. The edge measurement is made as a differential frequency measurement between the outgoing laser signal and the atmospheric backscattered return for each pulse. As a result the measurement is insensitive to laser and edge filter frequency jitter and drift at a level less than a few parts in 10(exp 10). We have developed double edge versions of the edge technique for aerosol and molecular-based lidar measurement of the wind. Aerosol-based wind measurements have been made at Goddard Space Flight Center and molecular-based wind measurements at the University of Geneva. We have demonstrated atmospheric measurements using these techniques for altitudes from 1 to more than 10 km. Measurement accuracies of better than 1.25 m/s have been obtained with integration times from 5 to 30 seconds. The measurements can be scaled to space and agree, within a factor of two, with satellite-based simulations of performance based on Poisson statistics. The theory of the double edge aerosol technique is described by a generalized formulation which substantially extends the capabilities of the edge technique. It uses two edges with opposite slopes located about the laser frequency at approximately the half-width of each edge filter. This doubles the signal change for a given Doppler shift and yields a factor of 1.6 improvement in the measurement accuracy compared to the single edge technique. The use of two high resolution edge filters substantially reduces the effects of Rayleigh scattering on the measurement, as much as order of magnitude, and allows the signal to noise ratio to be substantially improved in areas of low aerosol backscatter. We describe a method that allows the Rayleigh and aerosol components of the signal to be independently determined using the two edge channels and an energy monitor channel. The effects of Rayleigh scattering may then subtracted from the measurement and we show that the correction process does not significantly increase the measurement noise for Rayleigh to aerosol ratios up to 10. We show that for small Doppler shifts a measurement accuracy of 0.4 m/s can be obtained for 5000 detected photon, 1.2 m/s for 1000 detected photons, and 3.7 m/s for 50 detected photons for a Rayleigh to aerosol ratio of 5. Methods for increasing the dynamic range of the aerosol-based system to more than +/- 100 m/s are given.

The Impact of the Implementation of Edge Detection Methods on the Accuracy of Automatic Voltage Reading

NASA Astrophysics Data System (ADS)

Sidor, Kamil; Szlachta, Anna

2017-04-01

The article presents the impact of the edge detection method in the image analysis on the reading accuracy of the measured value. In order to ensure the automatic reading of the measured value by an analog meter, a standard webcam and the LabVIEW programme were applied. NI Vision Development tools were used. The Hough transform was used to detect the indicator. The programme output was compared during the application of several methods of edge detection. Those included: the Prewitt operator, the Roberts cross, the Sobel operator and the Canny edge detector. The image analysis was made for an analog meter indicator with the above-mentioned methods, and the results of that analysis were compared with each other and presented.

Real-time value optimization of edging and trimming operations for rough, green hardwood lumber

Treesearch

Daniel L. Schmoldt; Hang Song; Philip A. Araman

2001-01-01

For edging/trimming operations in hardwood sawmills, an operator examines both sides—or just the waney-edged side—of each board, and makes a quick assessment of grade potential. The operator then decides where to edge and/or trim the board to achieve the intended grade and, presumably, maximum value. However, human operators can only achieve lumber values that are 62-...

Remote estimation of canopy nitrogen content in winter wheat using airborne hyperspectral reflectance measurements

NASA Astrophysics Data System (ADS)

Zhou, Xianfeng; Huang, Wenjiang; Kong, Weiping; Ye, Huichun; Luo, Juhua; Chen, Pengfei

2016-11-01

Timely and accurate assessment of canopy nitrogen content (CNC) provides valuable insight into rapid and real-time nitrogen status monitoring in crops. A semi-empirical approach based on spectral index was extensively used for nitrogen content estimation. However, in many cases, due to specific vegetation types or local conditions, the applicability and robustness of established spectral indices for nitrogen retrieval were limited. The objective of this study was to investigate the optimal spectral index for winter wheat (Triticum aestivum L.) CNC estimation using Pushbroom Hyperspectral Imager (PHI) airborne hyperspectral data. Data collected from two different field experiments that were conducted during the major growth stages of winter wheat in 2002 and 2003 were used. Our results showed that a significant linear relationship existed between nitrogen and chlorophyll content at the canopy level, and it was not affected by cultivars, growing conditions and nutritional status of winter wheat. Nevertheless, it varied with growth stages. Periods around heading stage mainly worsened the relationship and CNC estimation, and CNC assessment for growth stages before and after heading could improve CNC retrieval accuracy to some extent. CNC assessment with PHI airborne hyperspectra suggested that spectral indices based on red-edge band including narrowband and broadband CIred-edge, NDVI-like and ND705 showed convincing results in CNC retrieval. NDVI-like and ND705 were sensitive to detect CNC changes less than 5 g/m2, narrowband and broadband CIred-edge were sensitive to a wide range of CNC variations. Further evaluation of CNC retrieval using field measured hyperspectra indicated that NDVI-like was robust and exhibited the highest accuracy in CNC assessment, and spectral indices (CIred-edge and CIgreen) that established on narrow or broad bands showed no obvious difference in CNC assessment. Overall, our study suggested that NDVI-like was the optimal indicator for winter wheat CNC retrieval.

Robustness of mission plans for unmanned aircraft

NASA Astrophysics Data System (ADS)

Niendorf, Moritz

This thesis studies the robustness of optimal mission plans for unmanned aircraft. Mission planning typically involves tactical planning and path planning. Tactical planning refers to task scheduling and in multi aircraft scenarios also includes establishing a communication topology. Path planning refers to computing a feasible and collision-free trajectory. For a prototypical mission planning problem, the traveling salesman problem on a weighted graph, the robustness of an optimal tour is analyzed with respect to changes to the edge costs. Specifically, the stability region of an optimal tour is obtained, i.e., the set of all edge cost perturbations for which that tour is optimal. The exact stability region of solutions to variants of the traveling salesman problems is obtained from a linear programming relaxation of an auxiliary problem. Edge cost tolerances and edge criticalities are derived from the stability region. For Euclidean traveling salesman problems, robustness with respect to perturbations to vertex locations is considered and safe radii and vertex criticalities are introduced. For weighted-sum multi-objective problems, stability regions with respect to changes in the objectives, weights, and simultaneous changes are given. Most critical weight perturbations are derived. Computing exact stability regions is intractable for large instances. Therefore, tractable approximations are desirable. The stability region of solutions to relaxations of the traveling salesman problem give under approximations and sets of tours give over approximations. The application of these results to the two-neighborhood and the minimum 1-tree relaxation are discussed. Bounds on edge cost tolerances and approximate criticalities are obtainable likewise. A minimum spanning tree is an optimal communication topology for minimizing the cumulative transmission power in multi aircraft missions. The stability region of a minimum spanning tree is given and tolerances, stability balls, and criticalities are derived. This analysis is extended to Euclidean minimum spanning trees. This thesis aims at enabling increased mission performance by providing means of assessing the robustness and optimality of a mission and methods for identifying critical elements. Examples of the application to mission planning in contested environments, cargo aircraft mission planning, multi-objective mission planning, and planning optimal communication topologies for teams of unmanned aircraft are given.

Modeling the Performance of Direct-Detection Doppler Lidar Systems in Real Atmospheres

NASA Technical Reports Server (NTRS)

McGill, Matthew J.; Hart, William D.; McKay, Jack A.; Spinhirne, James D.

1999-01-01

Previous modeling of the performance of spaceborne direct-detection Doppler lidar systems has assumed extremely idealized atmospheric models. Here we develop a technique for modeling the performance of these systems in a more realistic atmosphere, based on actual airborne lidar observations. The resulting atmospheric model contains cloud and aerosol variability that is absent in other simulations of spaceborne Doppler lidar instruments. To produce a realistic simulation of daytime performance, we include solar radiance values that are based on actual measurements and are allowed to vary as the viewing scene changes. Simulations are performed for two types of direct-detection Doppler lidar systems: the double-edge and the multi-channel techniques. Both systems were optimized to measure winds from Rayleigh backscatter at 355 nm. Simulations show that the measurement uncertainty during daytime is degraded by only about 10-20% compared to nighttime performance, provided a proper solar filter is included in the instrument design.

Modeling the performance of direct-detection Doppler lidar systems including cloud and solar background variability.

PubMed

McGill, M J; Hart, W D; McKay, J A; Spinhirne, J D

1999-10-20

Previous modeling of the performance of spaceborne direct-detection Doppler lidar systems assumed extremely idealized atmospheric models. Here we develop a technique for modeling the performance of these systems in a more realistic atmosphere, based on actual airborne lidar observations. The resulting atmospheric model contains cloud and aerosol variability that is absent in other simulations of spaceborne Doppler lidar instruments. To produce a realistic simulation of daytime performance, we include solar radiance values that are based on actual measurements and are allowed to vary as the viewing scene changes. Simulations are performed for two types of direct-detection Doppler lidar system: the double-edge and the multichannel techniques. Both systems were optimized to measure winds from Rayleigh backscatter at 355 nm. Simulations show that the measurement uncertainty during daytime is degraded by only approximately 10-20% compared with nighttime performance, provided that a proper solar filter is included in the instrument design.

A study on obstacle detection method of the frontal view using a camera on highway

NASA Astrophysics Data System (ADS)

Nguyen, Van-Quang; Park, Jeonghyeon; Seo, Changjun; Kim, Heungseob; Boo, Kwangsuck

2018-03-01

In this work, we introduce an approach to detect vehicles for driver assistance, or warning system. For driver assistance system, it must detect both lanes (left and right side lane), and discover vehicles ahead of the test vehicle. Therefore, in this study, we use a camera, it is installed on the windscreen of the test vehicle. Images from the camera are used to detect three lanes, and detect multiple vehicles. In lane detection, line detection and vanishing point estimation are used. For the vehicle detection, we combine the horizontal and vertical edge detection, the horizontal edge is used to detect the vehicle candidates, and then the vertical edge detection is used to verify the vehicle candidates. The proposed algorithm works with of 480 × 640 image frame resolution. The system was tested on the highway in Korea.

Comparison of edge detection techniques for M7 subtype Leukemic cell in terms of noise filters and threshold value

NASA Astrophysics Data System (ADS)

Salam, Afifah Salmi Abdul; Isa, Mohd. Nazrin Md.; Ahmad, Muhammad Imran; Che Ismail, Rizalafande

2017-11-01

This paper will focus on the study and identifying various threshold values for two commonly used edge detection techniques, which are Sobel and Canny Edge detection. The idea is to determine which values are apt in giving accurate results in identifying a particular leukemic cell. In addition, evaluating suitability of edge detectors are also essential as feature extraction of the cell depends greatly on image segmentation (edge detection). Firstly, an image of M7 subtype of Acute Myelocytic Leukemia (AML) is chosen due to its diagnosing which were found lacking. Next, for an enhancement in image quality, noise filters are applied. Hence, by comparing images with no filter, median and average filter, useful information can be acquired. Each threshold value is fixed with value 0, 0.25 and 0.5. From the investigation found, without any filter, Canny with a threshold value of 0.5 yields the best result.

Wrinkling reduction of membrane structure by trimming edges

NASA Astrophysics Data System (ADS)

Liu, Mingjun; Huang, Jin; Liu, Mingyue

2017-05-01

Thin membranes have negligible bending stiffness, compressive stresses inevitably lead to wrinkling. Therefore, it is important to keep the surface of membrane structures flat in order to guarantee high precision. Edge-trimming is an effective method to passively diminish wrinkles, however a key difficulty in this process is the determination of the optimal trimming level. In this paper, regular polygonal membrane structures subjected to equal radial forces were analyzed, and a new stress field distribution model for arc-edge square membrane structure was proposed to predict the optimal trimming level. This model is simple and applicable to any polygonal membrane structures. Comparison among the results of the finite element analysis, and the experimental and analytical results showed that the proposed model accurately described the stress field distribution and guaranteed that there are no wrinkles appear inside the effective inscribed circle region for the optimal trimming level.

The Edge Detectors Suitable for Retinal OCT Image Segmentation

PubMed Central

Yang, Jing; Gao, Qian; Zhou, Sheng

2017-01-01

Retinal layer thickness measurement offers important information for reliable diagnosis of retinal diseases and for the evaluation of disease development and medical treatment responses. This task critically depends on the accurate edge detection of the retinal layers in OCT images. Here, we intended to search for the most suitable edge detectors for the retinal OCT image segmentation task. The three most promising edge detection algorithms were identified in the related literature: Canny edge detector, the two-pass method, and the EdgeFlow technique. The quantitative evaluation results show that the two-pass method outperforms consistently the Canny detector and the EdgeFlow technique in delineating the retinal layer boundaries in the OCT images. In addition, the mean localization deviation metrics show that the two-pass method caused the smallest edge shifting problem. These findings suggest that the two-pass method is the best among the three algorithms for detecting retinal layer boundaries. The overall better performance of Canny and two-pass methods over EdgeFlow technique implies that the OCT images contain more intensity gradient information than texture changes along the retinal layer boundaries. The results will guide our future efforts in the quantitative analysis of retinal OCT images for the effective use of OCT technologies in the field of ophthalmology. PMID:29065594

Topology optimization for three-dimensional electromagnetic waves using an edge element-based finite-element method.

PubMed

Deng, Yongbo; Korvink, Jan G

2016-05-01

This paper develops a topology optimization procedure for three-dimensional electromagnetic waves with an edge element-based finite-element method. In contrast to the two-dimensional case, three-dimensional electromagnetic waves must include an additional divergence-free condition for the field variables. The edge element-based finite-element method is used to both discretize the wave equations and enforce the divergence-free condition. For wave propagation described in terms of the magnetic field in the widely used class of non-magnetic materials, the divergence-free condition is imposed on the magnetic field. This naturally leads to a nodal topology optimization method. When wave propagation is described using the electric field, the divergence-free condition must be imposed on the electric displacement. In this case, the material in the design domain is assumed to be piecewise homogeneous to impose the divergence-free condition on the electric field. This results in an element-wise topology optimization algorithm. The topology optimization problems are regularized using a Helmholtz filter and a threshold projection method and are analysed using a continuous adjoint method. In order to ensure the applicability of the filter in the element-wise topology optimization version, a regularization method is presented to project the nodal into an element-wise physical density variable.

Topology optimization for three-dimensional electromagnetic waves using an edge element-based finite-element method

PubMed Central

Korvink, Jan G.

2016-01-01

This paper develops a topology optimization procedure for three-dimensional electromagnetic waves with an edge element-based finite-element method. In contrast to the two-dimensional case, three-dimensional electromagnetic waves must include an additional divergence-free condition for the field variables. The edge element-based finite-element method is used to both discretize the wave equations and enforce the divergence-free condition. For wave propagation described in terms of the magnetic field in the widely used class of non-magnetic materials, the divergence-free condition is imposed on the magnetic field. This naturally leads to a nodal topology optimization method. When wave propagation is described using the electric field, the divergence-free condition must be imposed on the electric displacement. In this case, the material in the design domain is assumed to be piecewise homogeneous to impose the divergence-free condition on the electric field. This results in an element-wise topology optimization algorithm. The topology optimization problems are regularized using a Helmholtz filter and a threshold projection method and are analysed using a continuous adjoint method. In order to ensure the applicability of the filter in the element-wise topology optimization version, a regularization method is presented to project the nodal into an element-wise physical density variable. PMID:27279766

Wing-section optimization for supersonic viscous flow

NASA Technical Reports Server (NTRS)

Item, Cem C.; Baysal, Oktay (Editor)

1995-01-01

To improve the shape of a supersonic wing, an automated method that also includes higher fidelity to the flow physics is desirable. With this impetus, an aerodynamic optimization methodology incorporating thin-layer Navier-Stokes equations and sensitivity analysis had been previously developed. Prior to embarking upon the wind design task, the present investigation concentrated on testing the feasibility of the methodology, and the identification of adequate problem formulations, by defining two-dimensional, cost-effective test cases. Starting with two distinctly different initial airfoils, two independent shape optimizations resulted in shapes with similar features: slightly cambered, parabolic profiles with sharp leading- and trailing-edges. Secondly, the normal section to the subsonic portion of the leading edge, which had a high normal angle-of-attack, was considered. The optimization resulted in a shape with twist and camber which eliminated the adverse pressure gradient, hence, exploiting the leading-edge thrust. The wing section shapes obtained in all the test cases had the features predicted by previous studies. Therefore, it was concluded that the flowfield analyses and sensitivity coefficients were computed and fed to the present gradient-based optimizer correctly. Also, as a result of the present two-dimensional study, suggestions were made for the problem formulations which should contribute to an effective wing shape optimization.

Image processing system and method for recognizing and removing shadows from the image of a monitored scene

DOEpatents

Osbourn, Gordon C.

1996-01-01

The shadow contrast sensitivity of the human vision system is simulated by configuring information obtained from an image sensor so that the information may be evaluated with multiple pixel widths in order to produce a machine vision system able to distinguish between shadow edges and abrupt object edges. A second difference of the image intensity for each line of the image is developed and this second difference is used to screen out high frequency noise contributions from the final edge detection signals. These edge detection signals are constructed from first differences of the image intensity where the screening conditions are satisfied. The positional coincidence of oppositely signed maxima in the first difference signal taken from the right and the second difference signal taken from the left is used to detect the presence of an object edge. Alternatively, the effective number of responding operators (ENRO) may be utilized to determine the presence of object edges.

Automatic comic page image understanding based on edge segment analysis

NASA Astrophysics Data System (ADS)

Liu, Dong; Wang, Yongtao; Tang, Zhi; Li, Luyuan; Gao, Liangcai

2013-12-01

Comic page image understanding aims to analyse the layout of the comic page images by detecting the storyboards and identifying the reading order automatically. It is the key technique to produce the digital comic documents suitable for reading on mobile devices. In this paper, we propose a novel comic page image understanding method based on edge segment analysis. First, we propose an efficient edge point chaining method to extract Canny edge segments (i.e., contiguous chains of Canny edge points) from the input comic page image; second, we propose a top-down scheme to detect line segments within each obtained edge segment; third, we develop a novel method to detect the storyboards by selecting the border lines and further identify the reading order of these storyboards. The proposed method is performed on a data set consisting of 2000 comic page images from ten printed comic series. The experimental results demonstrate that the proposed method achieves satisfactory results on different comics and outperforms the existing methods.

An Iris Segmentation Algorithm based on Edge Orientation for Off-angle Iris Recognition

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

Karakaya, Mahmut; Barstow, Del R; Santos-Villalobos, Hector J

Iris recognition is known as one of the most accurate and reliable biometrics. However, the accuracy of iris recognition systems depends on the quality of data capture and is negatively affected by several factors such as angle, occlusion, and dilation. In this paper, we present a segmentation algorithm for off-angle iris images that uses edge detection, edge elimination, edge classification, and ellipse fitting techniques. In our approach, we first detect all candidate edges in the iris image by using the canny edge detector; this collection contains edges from the iris and pupil boundaries as well as eyelash, eyelids, iris texturemore » etc. Edge orientation is used to eliminate the edges that cannot be part of the iris or pupil. Then, we classify the remaining edge points into two sets as pupil edges and iris edges. Finally, we randomly generate subsets of iris and pupil edge points, fit ellipses for each subset, select ellipses with similar parameters, and average to form the resultant ellipses. Based on the results from real experiments, the proposed method shows effectiveness in segmentation for off-angle iris images.« less

Detecting the Edge of the Tongue: A Tutorial

ERIC Educational Resources Information Center

Iskarous, Khalil

2005-01-01

The goal of this paper is to provide a tutorial introduction to the topic of edge detection of the tongue from ultrasound scans for researchers in speech science and phonetics. The method introduced here is Active Contours (also called snakes), a method for searching for an edge, assuming that it is a smooth curve in the image data. The advantage…

Vehicle tracking using fuzzy-based vehicle detection window with adaptive parameters

NASA Astrophysics Data System (ADS)

Chitsobhuk, Orachat; Kasemsiri, Watjanapong; Glomglome, Sorayut; Lapamonpinyo, Pipatphon

2018-04-01

In this paper, fuzzy-based vehicle tracking system is proposed. The proposed system consists of two main processes: vehicle detection and vehicle tracking. In the first process, the Gradient-based Adaptive Threshold Estimation (GATE) algorithm is adopted to provide the suitable threshold value for the sobel edge detection. The estimated threshold can be adapted to the changes of diverse illumination conditions throughout the day. This leads to greater vehicle detection performance compared to a fixed user's defined threshold. In the second process, this paper proposes the novel vehicle tracking algorithms namely Fuzzy-based Vehicle Analysis (FBA) in order to reduce the false estimation of the vehicle tracking caused by uneven edges of the large vehicles and vehicle changing lanes. The proposed FBA algorithm employs the average edge density and the Horizontal Moving Edge Detection (HMED) algorithm to alleviate those problems by adopting fuzzy rule-based algorithms to rectify the vehicle tracking. The experimental results demonstrate that the proposed system provides the high accuracy of vehicle detection about 98.22%. In addition, it also offers the low false detection rates about 3.92%.

A Stochastic Approach to Path Planning in the Weighted-Region Problem

DTIC Science & Technology

1991-03-01

polynomial time. However, the polyhedrons in this three-dimensional obstacle-avoidance problem are all obstacles (i.e. travel is not permitted within...them). Therefore, optimal paths tend to avoid their vertices, and settle into closest approach tangents across polyhedron edges. So, in a sense...intersection update map database with new vertex for this edge 3. IF (C1 > D) and (C2 > D) THEN edge intersects ellipse at two points OR edge is

Shearlet-based edge detection: flame fronts and tidal flats

NASA Astrophysics Data System (ADS)

King, Emily J.; Reisenhofer, Rafael; Kiefer, Johannes; Lim, Wang-Q.; Li, Zhen; Heygster, Georg

2015-09-01

Shearlets are wavelet-like systems which are better suited for handling geometric features in multi-dimensional data than traditional wavelets. A novel method for edge and line detection which is in the spirit of phase congruency but is based on a complex shearlet transform will be presented. This approach to detection yields an approximate tangent direction of detected discontinuities as a byproduct of the computation, which then yields local curvature estimates. Two applications of the edge detection method will be discussed. First, the tracking and classification of flame fronts is a critical component of research in technical thermodynamics. Quite often, the flame fronts are transient or weak and the images are noisy. The standard methods used in the field for the detection of flame fronts do not handle such data well. Fortunately, using the shearlet-based edge measure yields good results as well as an accurate approximation of local curvature. Furthermore, a modification of the method will yield line detection, which is important for certain imaging modalities. Second, the Wadden tidal flats are a biodiverse region along the North Sea coast. One approach to surveying the delicate region and tracking the topographical changes is to use pre-existing Synthetic Aperture Radar (SAR) images. Unfortunately, SAR data suffers from multiplicative noise as well as sensitivity to environmental factors. The first large-scale mapping project of that type showed good results but only with a tremendous amount of manual interaction because there are many edges in the data which are not boundaries of the tidal flats but are edges of features like fields or islands. Preliminary results will be presented.

Development and Characterization of Embedded Sensory Particles Using Multi-Scale 3D Digital Image Correlation

NASA Technical Reports Server (NTRS)

Cornell, Stephen R.; Leser, William P.; Hochhalter, Jacob D.; Newman, John A.; Hartl, Darren J.

2014-01-01

A method for detecting fatigue cracks has been explored at NASA Langley Research Center. Microscopic NiTi shape memory alloy (sensory) particles were embedded in a 7050 aluminum alloy matrix to detect the presence of fatigue cracks. Cracks exhibit an elevated stress field near their tip inducing a martensitic phase transformation in nearby sensory particles. Detectable levels of acoustic energy are emitted upon particle phase transformation such that the existence and location of fatigue cracks can be detected. To test this concept, a fatigue crack was grown in a mode-I single-edge notch fatigue crack growth specimen containing sensory particles. As the crack approached the sensory particles, measurements of particle strain, matrix-particle debonding, and phase transformation behavior of the sensory particles were performed. Full-field deformation measurements were performed using a novel multi-scale optical 3D digital image correlation (DIC) system. This information will be used in a finite element-based study to determine optimal sensory material behavior and density.

Detection of exudates in fundus images using a Markovian segmentation model.

PubMed

Harangi, Balazs; Hajdu, Andras

2014-01-01

Diabetic retinopathy (DR) is one of the most common causing of vision loss in developed countries. In early stage of DR, some signs like exudates appear in the retinal images. An automatic screening system must be capable to detect these signs properly so that the treatment of the patients may begin in time. The appearance of exudates shows a rich variety regarding their shape and size making automatic detection more challenging. We propose a way for the automatic segmentation of exudates consisting of a candidate extraction step followed by exact contour detection and region-wise classification. More specifically, we extract possible exudate candidates using grayscale morphology and their proper shape is determined by a Markovian segmentation model considering edge information. Finally, we label the candidates as true or false ones by an optimally adjusted SVM classifier. For testing purposes, we considered the publicly available database DiaretDB1, where the proposed method outperformed several state-of-the-art exudate detectors.

Stability of Solutions to Classes of Traveling Salesman Problems.

PubMed

Niendorf, Moritz; Kabamba, Pierre T; Girard, Anouck R

2016-04-01

By performing stability analysis on an optimal tour for problems belonging to classes of the traveling salesman problem (TSP), this paper derives margins of optimality for a solution with respect to disturbances in the problem data. Specifically, we consider the asymmetric sequence-dependent TSP, where the sequence dependence is driven by the dynamics of a stack. This is a generalization of the symmetric non sequence-dependent version of the TSP. Furthermore, we also consider the symmetric sequence-dependent variant and the asymmetric non sequence-dependent variant. Amongst others these problems have applications in logistics and unmanned aircraft mission planning. Changing external conditions such as traffic or weather may alter task costs, which can render an initially optimal itinerary suboptimal. Instead of optimizing the itinerary every time task costs change, stability criteria allow for fast evaluation of whether itineraries remain optimal. This paper develops a method to compute stability regions for the best tour in a set of tours for the symmetric TSP and extends the results to the asymmetric problem as well as their sequence-dependent counterparts. As the TSP is NP-hard, heuristic methods are frequently used to solve it. The presented approach is also applicable to analyze stability regions for a tour obtained through application of the k -opt heuristic with respect to the k -neighborhood. A dimensionless criticality metric for edges is proposed, such that a high criticality of an edge indicates that the optimal tour is more susceptible to cost changes in that edge. Multiple examples demonstrate the application of the developed stability computation method as well as the edge criticality measure that facilitates an intuitive assessment of instances of the TSP.

A novel cloning template designing method by using an artificial bee colony algorithm for edge detection of CNN based imaging sensors.

PubMed

Parmaksızoğlu, Selami; Alçı, Mustafa

2011-01-01

Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods.

A Novel Cloning Template Designing Method by Using an Artificial Bee Colony Algorithm for Edge Detection of CNN Based Imaging Sensors

PubMed Central

Parmaksızoğlu, Selami; Alçı, Mustafa

2011-01-01

Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods. PMID:22163903

Fpga based hardware synthesis for automatic segmentation of retinal blood vessels in diabetic retinopathy images.

PubMed

Sivakamasundari, J; Kavitha, G; Sujatha, C M; Ramakrishnan, S

2014-01-01

Diabetic Retinopathy (DR) is a disorder that affects the structure of retinal blood vessels due to long-standing diabetes mellitus. Real-Time mass screening system for DR is vital for timely diagnosis and periodic screening to prevent the patient from severe visual loss. Human retinal fundus images are widely used for an automated segmentation of blood vessel and diagnosis of various blood vessel disorders. In this work, an attempt has been made to perform hardware synthesis of Kirsch template based edge detection for segmentation of blood vessels. This method is implemented using LabVIEW software and is synthesized in field programmable gate array board to yield results in real-time application. The segmentation of blood vessels using Kirsch based edge detection is compared with other edge detection methods such as Sobel, Prewitt and Canny. The texture features such as energy, entropy, contrast, mean, homogeneity and structural feature namely ratio of vessel to vessel free area are obtained from the segmented images. The performance of segmentation is analysed in terms of sensitivity, specificity and accuracy. It is observed from the results that the Kirsch based edge detection technique segmented the edges of blood vessels better than other edge detection techniques. The ratio of vessel to vessel free area classified the normal and DR affected retinal images more significantly than other texture based features. FPGA based hardware synthesis of Kirsch edge detection method is able to differentiate normal and diseased images with high specificity (93%). This automated segmentation of retinal blood vessels system could be used in computer-assisted diagnosis for diabetic retinopathy screening in real-time application.

Shape optimization for aerodynamic efficiency and low observability

NASA Technical Reports Server (NTRS)

Vinh, Hoang; Van Dam, C. P.; Dwyer, Harry A.

1993-01-01

Field methods based on the finite-difference approximations of the time-domain Maxwell's equations and the potential-flow equation have been developed to solve the multidisciplinary problem of airfoil shaping for aerodynamic efficiency and low radar cross section (RCS). A parametric study and an optimization study employing the two analysis methods are presented to illustrate their combined capabilities. The parametric study shows that for frontal radar illumination, the RCS of an airfoil is independent of the chordwise location of maximum thickness but depends strongly on the maximum thickness, leading-edge radius, and leadingedge shape. In addition, this study shows that the RCS of an airfoil can be reduced without significant effects on its transonic aerodynamic efficiency by reducing the leading-edge radius and/or modifying the shape of the leading edge. The optimization study involves the minimization of wave drag for a non-lifting, symmetrical airfoil with constraints on the airfoil maximum thickness and monostatic RCS. This optimization study shows that the two analysis methods can be used effectively to design aerodynamically efficient airfoils with certain desired RCS characteristics.

Computational wing optimization and comparisons with experiment for a semi-span wing model

NASA Technical Reports Server (NTRS)

Waggoner, E. G.; Haney, H. P.; Ballhaus, W. F.

1978-01-01

A computational wing optimization procedure was developed and verified by an experimental investigation of a semi-span variable camber wing model in the NASA Ames Research Center 14 foot transonic wind tunnel. The Bailey-Ballhaus transonic potential flow analysis and Woodward-Carmichael linear theory codes were linked to Vanderplaats constrained minimization routine to optimize model configurations at several subsonic and transonic design points. The 35 deg swept wing is characterized by multi-segmented leading and trailing edge flaps whose hinge lines are swept relative to the leading and trailing edges of the wing. By varying deflection angles of the flap segments, camber and twist distribution can be optimized for different design conditions. Results indicate that numerical optimization can be both an effective and efficient design tool. The optimized configurations had as good or better lift to drag ratios at the design points as the best designs previously tested during an extensive parametric study.

Optically Unraveling the Edge Chirality-Dependent Band Structure and Plasmon Damping in Graphene Edges.

PubMed

Duan, Jiahua; Chen, Runkun; Cheng, Yuan; Yang, Tianzhong; Zhai, Feng; Dai, Qing; Chen, Jianing

2018-05-01

The nontrivial topological origin and pseudospinorial character of electron wavefunctions make edge states possess unusual electronic properties. Twenty years ago, the tight-binding model calculation predicted that zigzag termination of 2D sheets of carbon atoms have peculiar edge states, which show potential application in spintronics and modern information technologies. Although scanning probe microscopy is employed to capture this phenomenon, the experimental demonstration of its optical response remains challenging. Here, the propagating graphene plasmon provides an edge-selective polaritonic probe to directly detect and control the electronic edge state at ambient condition. Compared with armchair, the edge-band structure in the bandgap gives rise to additional optical absorption and strongly absorbed rim at zigzag edge. Furthermore, the optical conductivity is reconstructed and the anisotropic plasmon damping in graphene systems is revealed. The reported approach paves the way for detecting edge-specific phenomena in other van der Waals materials and topological insulators. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structurally efficient inflatable protective device

DOEpatents

Nelsen, James M.; Whinery, Larry D.; Gwinn, Kenneth W.; McBride, Donald D.; Luna, Daniel A.; Holder, Joseph P.; Bliton, Richard J.

1997-01-01

An apparatus and method for making a low cost, self-venting, inflatable protective cushion of simple and structurally efficient design with a shape and construction that optimizes the cushion's ability to withstand inflation pressures and impact when deployed which includes a sheet defined by at least one fold line and a plurality of flap portions, each flap portion having a base edge corresponding to a fold line and at least two side edges each extending outwardly from a base edge and ultimately converging to meet each other, the flap portions being folded at the fold line(s) and being joined at corresponding side edges to define an inflatable chamber. The inflatable protective cushion and method for making same may further include a lightweight, low permeability, fabric that optimizes the cushion's ability to withstand inflation pressures and impact when deployed and minimizes the packed volume of the cushion when stored.

Structurally efficient inflatable protective device

DOEpatents

Nelsen, J.M.; Whinery, L.D.; Gwinn, K.W.; McBride, D.D.; Luna, D.A.; Holder, J.P.; Bliton, R.J.

1997-03-04

An apparatus and method are disclosed for making a low cost, self-venting, inflatable protective cushion of simple and structurally efficient design with a shape and construction that optimizes the cushion`s ability to withstand inflation pressures and impact when deployed which includes a sheet defined by at least one fold line and a plurality of flap portions, each flap portion having a base edge corresponding to a fold line and at least two side edges each extending outwardly from a base edge and ultimately converging to meet each other, the flap portions being folded at the fold line(s) and being joined at corresponding side edges to define an inflatable chamber. The inflatable protective cushion and method for making same may further include a lightweight, low permeability, fabric that optimizes the cushion`s ability to withstand inflation pressures and impact when deployed and minimizes the packed volume of the cushion when stored. 22 figs.

Structurally efficient inflatable protective device

DOEpatents

Nelsen, J.M.; Whinery, L.D.; Gwinn, K.W.; McBride, D.D.; Luna, D.A.; Holder, J.P.; Bliton, R.J.

1996-01-09

An apparatus and method are disclosed for making a low cost, self-venting, inflatable protective cushion of simple and structurally efficient design with a shape and construction that optimizes the cushion`s ability to withstand inflation pressures and impact when deployed which includes a sheet defined by at least one fold line and a plurality of flap portions, each flap portion having a base edge corresponding to a fold line and at least two side edges each extending outwardly from a base edge and ultimately converging to meet each other, the flap portions being folded at the fold line(s) and being joined at corresponding side edges to define an inflatable chamber. The inflatable protective cushion and method for making same may further include a lightweight, low permeability, fabric that optimizes the cushion`s ability to withstand inflation pressures and impact when deployed and minimizes the packed volume of the cushion when stored. 22 figs.

Structurally efficient inflatable protective device

DOEpatents

Nelsen, James M.; Whinery, Larry D.; Gwinn, Kenneth W.; McBride, Donald D.; Luna, Daniel A.; Holder, Joseph P.; Bliton, Richard J.

1996-01-01

An apparatus and method for making a low cost, self-venting, inflatable protective cushion of simple and structurally efficient design with a shape and construction that optimizes the cushion's ability to withstand inflation pressures and impact when deployed which includes a sheet defined by at least one fold line and a plurality of flap portions, each flap portion having a base edge corresponding to a fold line and at least two side edges each extending outwardly from a base edge and ultimately converging to meet each other, the flap portions being folded at the fold line(s) and being Joined at corresponding side edges to define an inflatable chamber. The inflatable protective cushion and method for making same may further include a lightweight, low permeability, fabric that optimizes the cushion's ability to withstand inflation pressures and impact when deployed and minimizes the packed volume of the cushion when stored.

Structurally efficient inflatable protective device

DOEpatents

Nelsen, James M.; Whinery, Larry D.; Gwinn, Kenneth W.; McBride, Donald D.; Luna, Daniel A.; Holder, Joseph P.; Bliton, Richard J.

1996-01-01

An apparatus and method for making a low cost, self-venting, inflatable protective cushion of simple and structurally efficient design with a shape and construction that optimizes the cushion's ability to withstand inflation pressures and impact when deployed which includes a sheet defined by at least one fold line and a plurality of flap portions, each flap portion having a base edge corresponding to a fold line and at least two side edges each extending outwardly from a base edge and ultimately converging to meet each other, the flap portions being folded at the fold line(s) and being joined at corresponding side edges to define an inflatable chamber. The inflatable protective cushion and method for making same may further include a lightweight, low permeability, fabric that optimizes the cushion's ability to withstand inflation pressures and impact when deployed and minimizes the packed volume of the cushion when stored.

Line-edge quality optimization of electron beam resist for high-throughput character projection exposure utilizing atomic force microscope analysis

NASA Astrophysics Data System (ADS)

Ikeno, Rimon; Mita, Yoshio; Asada, Kunihiro

2017-04-01

High-throughput electron-beam lithography (EBL) by character projection (CP) and variable-shaped beam (VSB) methods is a promising technique for low-to-medium volume device fabrication with regularly arranged layouts, such as standard-cell logics and memory arrays. However, non-VLSI applications like MEMS and MOEMS may not fully utilize the benefits of CP method due to their wide variety of layout figures including curved and oblique edges. In addition, the stepwise shapes that appear on such irregular edges by VSB exposure often result in intolerable edge roughness, which may degrade performances of the fabricated devices. In our former study, we proposed a general EBL methodology for such applications utilizing a combination of CP and VSB methods, and demonstrated its capabilities in electron beam (EB) shot reduction and edge-quality improvement by using a leading-edge EB exposure tool, ADVANTEST F7000S-VD02, and high-resolution Hydrogen Silsesquioxane resist. Both scanning electron microscope and atomic force microscope observations were used to analyze quality of the resist edge profiles to determine the influence of the control parameters used in the exposure-data preparation process. In this study, we carried out detailed analysis of the captured edge profiles utilizing Fourier analysis, and successfully distinguish the systematic undulation by the exposed CP character profiles from random roughness components. Such capability of precise edge-roughness analysis is useful to our EBL methodology to maintain both the line-edge quality and the exposure throughput by optimizing the control parameters in the layout data conversion.

Subpixel edge estimation with lens aberrations compensation based on the iterative image approximation for high-precision thermal expansion measurements of solids

NASA Astrophysics Data System (ADS)

Inochkin, F. M.; Kruglov, S. K.; Bronshtein, I. G.; Kompan, T. A.; Kondratjev, S. V.; Korenev, A. S.; Pukhov, N. F.

2017-06-01

A new method for precise subpixel edge estimation is presented. The principle of the method is the iterative image approximation in 2D with subpixel accuracy until the appropriate simulated is found, matching the simulated and acquired images. A numerical image model is presented consisting of three parts: an edge model, object and background brightness distribution model, lens aberrations model including diffraction. The optimal values of model parameters are determined by means of conjugate-gradient numerical optimization of a merit function corresponding to the L2 distance between acquired and simulated images. Computationally-effective procedure for the merit function calculation along with sufficient gradient approximation is described. Subpixel-accuracy image simulation is performed in a Fourier domain with theoretically unlimited precision of edge points location. The method is capable of compensating lens aberrations and obtaining the edge information with increased resolution. Experimental method verification with digital micromirror device applied to physically simulate an object with known edge geometry is shown. Experimental results for various high-temperature materials within the temperature range of 1000°C..2400°C are presented.

Adaptive sampling in behavioral surveys.

PubMed

Thompson, S K

1997-01-01

Studies of populations such as drug users encounter difficulties because the members of the populations are rare, hidden, or hard to reach. Conventionally designed large-scale surveys detect relatively few members of the populations so that estimates of population characteristics have high uncertainty. Ethnographic studies, on the other hand, reach suitable numbers of individuals only through the use of link-tracing, chain referral, or snowball sampling procedures that often leave the investigators unable to make inferences from their sample to the hidden population as a whole. In adaptive sampling, the procedure for selecting people or other units to be in the sample depends on variables of interest observed during the survey, so the design adapts to the population as encountered. For example, when self-reported drug use is found among members of the sample, sampling effort may be increased in nearby areas. Types of adaptive sampling designs include ordinary sequential sampling, adaptive allocation in stratified sampling, adaptive cluster sampling, and optimal model-based designs. Graph sampling refers to situations with nodes (for example, people) connected by edges (such as social links or geographic proximity). An initial sample of nodes or edges is selected and edges are subsequently followed to bring other nodes into the sample. Graph sampling designs include network sampling, snowball sampling, link-tracing, chain referral, and adaptive cluster sampling. A graph sampling design is adaptive if the decision to include linked nodes depends on variables of interest observed on nodes already in the sample. Adjustment methods for nonsampling errors such as imperfect detection of drug users in the sample apply to adaptive as well as conventional designs.

Measurement of pattern roughness and local size variation using CD-SEM: current status

NASA Astrophysics Data System (ADS)

Fukuda, Hiroshi; Kawasaki, Takahiro; Kawada, Hiroki; Sakai, Kei; Kato, Takashi; Yamaguchi, Satoru; Ikota, Masami; Momonoi, Yoshinori

2018-03-01

Measurement of line edge roughness (LER) is discussed from four aspects: edge detection, PSD prediction, sampling strategy, and noise mitigation, and general guidelines and practical solutions for LER measurement today are introduced. Advanced edge detection algorithms such as wave-matching method are shown effective for robustly detecting edges from low SNR images, while conventional algorithm with weak filtering is still effective in suppressing SEM noise and aliasing. Advanced PSD prediction method such as multi-taper method is effective in suppressing sampling noise within a line edge to analyze, while number of lines is still required for suppressing line to line variation. Two types of SEM noise mitigation methods, "apparent noise floor" subtraction method and LER-noise decomposition using regression analysis are verified to successfully mitigate SEM noise from PSD curves. These results are extended to LCDU measurement to clarify the impact of SEM noise and sampling noise on LCDU.

Natural history of optical coherence tomography-detected non-flow-limiting edge dissections following drug-eluting stent implantation.

PubMed

Radu, Maria D; Räber, Lorenz; Heo, Jungho; Gogas, Bill D; Jørgensen, Erik; Kelbæk, Henning; Muramatsu, Takashi; Farooq, Vasim; Helqvist, Steffen; Garcia-Garcia, Hector M; Windecker, Stephan; Saunamäki, Kari; Serruys, Patrick W

2014-01-22

Angiographic evidence of edge dissections has been associated with a risk of early stent thrombosis. Optical coherence tomography (OCT) is a high-resolution technology detecting a greater number of edge dissections--particularly non-flow-limiting--compared to angiography. Their natural history and clinical implications remain unclear. The objectives of the present study were to assess the morphology, healing response, and clinical outcomes of OCT-detected edge dissections using serial OCT imaging at baseline and at one year following drug-eluting stent (DES) implantation. Edge dissections were defined as disruptions of the luminal surface in the 5 mm segments proximal and distal to the stent, and categorised as flaps, cavities, double-lumen dissections or fissures. Qualitative and quantitative OCT analyses were performed every 0.5 mm at baseline and one year, and clinical outcomes were assessed. Sixty-three lesions (57 patients) were studied with OCT at baseline and one-year follow-up. Twenty-two non-flow-limiting edge dissections in 21 lesions (20 patients) were identified by OCT; only two (9%) were angiographically visible. Flaps were found in 96% of cases. The median longitudinal dissection length was 2.9 mm (interquartile range [IQR] 1.6-4.2 mm), whereas the circumferential and axial extensions amounted to 1.2 mm (IQR: 0.9-1.7 mm) and 0.6 mm (IQR: 0.4-0.7 mm), respectively. Dissections extended into the media and adventitia in seven (33%) and four (20%) cases, respectively. Eighteen (82%) OCT-detected edge dissections were also evaluated with intravascular ultrasound which identified nine (50%) of these OCT-detected dissections. No stent thrombosis or target lesion revascularisation occurred up to one year. At follow-up, 20 (90%) edge dissections were completely healed on OCT. The two cases exhibiting persistent dissection had the longest flaps (2.81 mm and 2.42 mm) at baseline. OCT-detected edge dissections which are angiographically silent in the majority of cases are not associated with acute stent thrombosis or restenosis up to one-year follow-up.

Image reconstruction for x-ray K-edge imaging with a photon counting detector

NASA Astrophysics Data System (ADS)

Meng, Bo; Cong, Wenxiang; Xi, Yan; Wang, Ge

2014-09-01

Contrast agents with high-Z elements have K-absorption edges which significantly change X-ray attenuation coefficients. The K-edge characteristics is different for various kinds of contrast agents, which offers opportunities for material decomposition in biomedical applications. In this paper, we propose a new K-edge imaging method, which not only quantifies a distribution of a contrast agent but also provides an optimized contrast ratio. Our numerical simulation tests demonstrate the feasibility and merits of the proposed methodology.

High Precision Edge Detection Algorithm for Mechanical Parts

NASA Astrophysics Data System (ADS)

Duan, Zhenyun; Wang, Ning; Fu, Jingshun; Zhao, Wenhui; Duan, Boqiang; Zhao, Jungui

2018-04-01

High precision and high efficiency measurement is becoming an imperative requirement for a lot of mechanical parts. So in this study, a subpixel-level edge detection algorithm based on the Gaussian integral model is proposed. For this purpose, the step edge normal section line Gaussian integral model of the backlight image is constructed, combined with the point spread function and the single step model. Then gray value of discrete points on the normal section line of pixel edge is calculated by surface interpolation, and the coordinate as well as gray information affected by noise is fitted in accordance with the Gaussian integral model. Therefore, a precise location of a subpixel edge was determined by searching the mean point. Finally, a gear tooth was measured by M&M3525 gear measurement center to verify the proposed algorithm. The theoretical analysis and experimental results show that the local edge fluctuation is reduced effectively by the proposed method in comparison with the existing subpixel edge detection algorithms. The subpixel edge location accuracy and computation speed are improved. And the maximum error of gear tooth profile total deviation is 1.9 μm compared with measurement result with gear measurement center. It indicates that the method has high reliability to meet the requirement of high precision measurement.

Compliant flow designs for optimum lift control of wind turbine rotors

NASA Astrophysics Data System (ADS)

Williams, Theodore J. H.

An optimization approach was formulated to determine geometric designs that are most compliant to flow control devices. Single dielectric barrier discharge (SDBD) plasma actuators are used in the flow control design optimization as they are able to be incorporated into CFD simulations. An adjoint formulation was derived in order to have a numerically efficient way of calculating the shape derivatives on the surface of the geometric design. The design of a wind turbine blade retrofit for the JIMP 25kW wind turbine at Notre Dame is used to motivate analyses that utilize the optimization approach. The CFD simulations of the existing wind turbine blade were validated against wind tunnel testing. A one-parameter optimization was performed in order to design a trailing edge addition for the current wind turbine blade. The trailing edge addition was designed to meet a desired lift target while maximizing the lift-to-drag ratio. This analysis was performed at seven radial locations on the wind turbine blade. The new trailing edge retrofits were able to achieve the lift target for the outboard radial locations. The designed geometry has been fabricated and is currently being validated on a full-scale turbine and it is predicted to have an increase in annual energy production of 4.30%. The design of a trailing edge retrofit that includes the use of a SDBD plasma actuator was performed using a two-parameter optimization. The objective of this analysis was to meet the lift target and maximize the controllability of the design. The controllability is defined as the difference in lift between plasma on and plasma off cases. A trailing edge retrofit with the plasma actuator located on the pressure side was able to achieve the target passive lift increase while using plasma flow control to reduce the lift to below the original design. This design resulted in a highly compliant flow.

Wear Detection of Drill Bit by Image-based Technique

NASA Astrophysics Data System (ADS)

Sukeri, Maziyah; Zulhilmi Paiz Ismadi, Mohd; Rahim Othman, Abdul; Kamaruddin, Shahrul

2018-03-01

Image processing for computer vision function plays an essential aspect in the manufacturing industries for the tool condition monitoring. This study proposes a dependable direct measurement method to measure the tool wear using image-based analysis. Segmentation and thresholding technique were used as the means to filter and convert the colour image to binary datasets. Then, the edge detection method was applied to characterize the edge of the drill bit. By using cross-correlation method, the edges of original and worn drill bits were correlated to each other. Cross-correlation graphs were able to detect the difference of the worn edge despite small difference between the graphs. Future development will focus on quantifying the worn profile as well as enhancing the sensitivity of the technique.

Algorithm for parametric community detection in networks.

PubMed

Bettinelli, Andrea; Hansen, Pierre; Liberti, Leo

2012-07-01

Modularity maximization is extensively used to detect communities in complex networks. It has been shown, however, that this method suffers from a resolution limit: Small communities may be undetectable in the presence of larger ones even if they are very dense. To alleviate this defect, various modifications of the modularity function have been proposed as well as multiresolution methods. In this paper we systematically study a simple model (proposed by Pons and Latapy [Theor. Comput. Sci. 412, 892 (2011)] and similar to the parametric model of Reichardt and Bornholdt [Phys. Rev. E 74, 016110 (2006)]) with a single parameter α that balances the fraction of within community edges and the expected fraction of edges according to the configuration model. An exact algorithm is proposed to find optimal solutions for all values of α as well as the corresponding successive intervals of α values for which they are optimal. This algorithm relies upon a routine for exact modularity maximization and is limited to moderate size instances. An agglomerative hierarchical heuristic is therefore proposed to address parametric modularity detection in large networks. At each iteration the smallest value of α for which it is worthwhile to merge two communities of the current partition is found. Then merging is performed and the data are updated accordingly. An implementation is proposed with the same time and space complexity as the well-known Clauset-Newman-Moore (CNM) heuristic [Phys. Rev. E 70, 066111 (2004)]. Experimental results on artificial and real world problems show that (i) communities are detected by both exact and heuristic methods for all values of the parameter α; (ii) the dendrogram summarizing the results of the heuristic method provides a useful tool for substantive analysis, as illustrated particularly on a Les Misérables data set; (iii) the difference between the parametric modularity values given by the exact method and those given by the heuristic is moderate; (iv) the heuristic version of the proposed parametric method, viewed as a modularity maximization tool, gives better results than the CNM heuristic for large instances.

Quality optimized medical image information hiding algorithm that employs edge detection and data coding.

PubMed

Al-Dmour, Hayat; Al-Ani, Ahmed

2016-04-01

The present work has the goal of developing a secure medical imaging information system based on a combined steganography and cryptography technique. It attempts to securely embed patient's confidential information into his/her medical images. The proposed information security scheme conceals coded Electronic Patient Records (EPRs) into medical images in order to protect the EPRs' confidentiality without affecting the image quality and particularly the Region of Interest (ROI), which is essential for diagnosis. The secret EPR data is converted into ciphertext using private symmetric encryption method. Since the Human Visual System (HVS) is less sensitive to alterations in sharp regions compared to uniform regions, a simple edge detection method has been introduced to identify and embed in edge pixels, which will lead to an improved stego image quality. In order to increase the embedding capacity, the algorithm embeds variable number of bits (up to 3) in edge pixels based on the strength of edges. Moreover, to increase the efficiency, two message coding mechanisms have been utilized to enhance the ±1 steganography. The first one, which is based on Hamming code, is simple and fast, while the other which is known as the Syndrome Trellis Code (STC), is more sophisticated as it attempts to find a stego image that is close to the cover image through minimizing the embedding impact. The proposed steganography algorithm embeds the secret data bits into the Region of Non Interest (RONI), where due to its importance; the ROI is preserved from modifications. The experimental results demonstrate that the proposed method can embed large amount of secret data without leaving a noticeable distortion in the output image. The effectiveness of the proposed algorithm is also proven using one of the efficient steganalysis techniques. The proposed medical imaging information system proved to be capable of concealing EPR data and producing imperceptible stego images with minimal embedding distortions compared to other existing methods. In order to refrain from introducing any modifications to the ROI, the proposed system only utilizes the Region of Non Interest (RONI) in embedding the EPR data. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

People efficiently explore the solution space of the computationally intractable traveling salesman problem to find near-optimal tours.

PubMed

Acuña, Daniel E; Parada, Víctor

2010-07-29

Humans need to solve computationally intractable problems such as visual search, categorization, and simultaneous learning and acting, yet an increasing body of evidence suggests that their solutions to instantiations of these problems are near optimal. Computational complexity advances an explanation to this apparent paradox: (1) only a small portion of instances of such problems are actually hard, and (2) successful heuristics exploit structural properties of the typical instance to selectively improve parts that are likely to be sub-optimal. We hypothesize that these two ideas largely account for the good performance of humans on computationally hard problems. We tested part of this hypothesis by studying the solutions of 28 participants to 28 instances of the Euclidean Traveling Salesman Problem (TSP). Participants were provided feedback on the cost of their solutions and were allowed unlimited solution attempts (trials). We found a significant improvement between the first and last trials and that solutions are significantly different from random tours that follow the convex hull and do not have self-crossings. More importantly, we found that participants modified their current better solutions in such a way that edges belonging to the optimal solution ("good" edges) were significantly more likely to stay than other edges ("bad" edges), a hallmark of structural exploitation. We found, however, that more trials harmed the participants' ability to tell good from bad edges, suggesting that after too many trials the participants "ran out of ideas." In sum, we provide the first demonstration of significant performance improvement on the TSP under repetition and feedback and evidence that human problem-solving may exploit the structure of hard problems paralleling behavior of state-of-the-art heuristics.

People Efficiently Explore the Solution Space of the Computationally Intractable Traveling Salesman Problem to Find Near-Optimal Tours

PubMed Central

Acuña, Daniel E.; Parada, Víctor

2010-01-01

Humans need to solve computationally intractable problems such as visual search, categorization, and simultaneous learning and acting, yet an increasing body of evidence suggests that their solutions to instantiations of these problems are near optimal. Computational complexity advances an explanation to this apparent paradox: (1) only a small portion of instances of such problems are actually hard, and (2) successful heuristics exploit structural properties of the typical instance to selectively improve parts that are likely to be sub-optimal. We hypothesize that these two ideas largely account for the good performance of humans on computationally hard problems. We tested part of this hypothesis by studying the solutions of 28 participants to 28 instances of the Euclidean Traveling Salesman Problem (TSP). Participants were provided feedback on the cost of their solutions and were allowed unlimited solution attempts (trials). We found a significant improvement between the first and last trials and that solutions are significantly different from random tours that follow the convex hull and do not have self-crossings. More importantly, we found that participants modified their current better solutions in such a way that edges belonging to the optimal solution (“good” edges) were significantly more likely to stay than other edges (“bad” edges), a hallmark of structural exploitation. We found, however, that more trials harmed the participants' ability to tell good from bad edges, suggesting that after too many trials the participants “ran out of ideas.” In sum, we provide the first demonstration of significant performance improvement on the TSP under repetition and feedback and evidence that human problem-solving may exploit the structure of hard problems paralleling behavior of state-of-the-art heuristics. PMID:20686597

Accurately estimating PSF with straight lines detected by Hough transform

NASA Astrophysics Data System (ADS)

Wang, Ruichen; Xu, Liangpeng; Fan, Chunxiao; Li, Yong

2018-04-01

This paper presents an approach to estimating point spread function (PSF) from low resolution (LR) images. Existing techniques usually rely on accurate detection of ending points of the profile normal to edges. In practice however, it is often a great challenge to accurately localize profiles of edges from a LR image, which hence leads to a poor PSF estimation of the lens taking the LR image. For precisely estimating the PSF, this paper proposes firstly estimating a 1-D PSF kernel with straight lines, and then robustly obtaining the 2-D PSF from the 1-D kernel by least squares techniques and random sample consensus. Canny operator is applied to the LR image for obtaining edges and then Hough transform is utilized to extract straight lines of all orientations. Estimating 1-D PSF kernel with straight lines effectively alleviates the influence of the inaccurate edge detection on PSF estimation. The proposed method is investigated on both natural and synthetic images for estimating PSF. Experimental results show that the proposed method outperforms the state-ofthe- art and does not rely on accurate edge detection.

Adaptive local thresholding for robust nucleus segmentation utilizing shape priors

NASA Astrophysics Data System (ADS)

Wang, Xiuzhong; Srinivas, Chukka

2016-03-01

This paper describes a novel local thresholding method for foreground detection. First, a Canny edge detection method is used for initial edge detection. Then, tensor voting is applied on the initial edge pixels, using a nonsymmetric tensor field tailored to encode prior information about nucleus size, shape, and intensity spatial distribution. Tensor analysis is then performed to generate the saliency image and, based on that, the refined edge. Next, the image domain is divided into blocks. In each block, at least one foreground and one background pixel are sampled for each refined edge pixel. The saliency weighted foreground histogram and background histogram are then created. These two histograms are used to calculate a threshold by minimizing the background and foreground pixel classification error. The block-wise thresholds are then used to generate the threshold for each pixel via interpolation. Finally, the foreground is obtained by comparing the original image with the threshold image. The effective use of prior information, combined with robust techniques, results in far more reliable foreground detection, which leads to robust nucleus segmentation.

Reflection symmetry detection using locally affine invariant edge correspondence.

PubMed

Wang, Zhaozhong; Tang, Zesheng; Zhang, Xiao

2015-04-01

Reflection symmetry detection receives increasing attentions in recent years. The state-of-the-art algorithms mainly use the matching of intensity-based features (such as the SIFT) within a single image to find symmetry axes. This paper proposes a novel approach by establishing the correspondence of locally affine invariant edge-based features, which are superior to the intensity based in the aspects that it is insensitive to illumination variations, and applicable to textureless objects. The locally affine invariance is achieved by simple linear algebra for efficient and robust computations, making the algorithm suitable for detections under object distortions like perspective projection. Commonly used edge detectors and a voting process are, respectively, used before and after the edge description and matching steps to form a complete reflection detection pipeline. Experiments are performed using synthetic and real-world images with both multiple and single reflection symmetry axis. The test results are compared with existing algorithms to validate the proposed method.

Interactions between Soil Habitat and Geographic Range Location Affect Plant Fitness

PubMed Central

Stanton-Geddes, John; Shaw, Ruth G.; Tiffin, Peter

2012-01-01

Populations are often found on different habitats at different geographic locations. This habitat shift may be due to biased dispersal, physiological tolerances or biotic interactions. To explore how fitness of the native plant Chamaecrista fasciculata depends on habitat within, at and beyond its range edge, we planted seeds from five populations in two soil substrates at these geographic locations. We found that with reduced competition, lifetime fitness was always greater or equivalent in one habitat type, loam soils, though early-season survival was greater on sand soils. At the range edge, natural populations are typically found on sand soil habitats, which are also less competitive environments. Early-season survival and fitness differed among source populations, and when transplanted beyond the range edge, range edge populations had greater fitness than interior populations. Our results indicate that even when the optimal soil substrate for a species does not change with geographic range location, the realized niche of a species may be restricted to sub-optimal habitats at the range edge because of the combined effects of differences in abiotic and biotic effects (e.g. competitors) between substrates. PMID:22615745

Numerical optimization of three-dimensional coils for NSTX-U

DOE PAGES

Lazerson, S. A.; Park, J. -K.; Logan, N.; ...

2015-09-03

A tool for the calculation of optimal three-dimensional (3D) perturbative magnetic fields in tokamaks has been developed. The IPECOPT code builds upon the stellarator optimization code STELLOPT to allow for optimization of linear ideal magnetohydrodynamic perturbed equilibrium (IPEC). This tool has been applied to NSTX-U equilibria, addressing which fields are the most effective at driving NTV torques. The NTV torque calculation is performed by the PENT code. Optimization of the normal field spectrum shows that fields with n = 1 character can drive a large core torque. It is also shown that fields with n = 3 features are capablemore » of driving edge torque and some core torque. Coil current optimization (using the planned in-vessel and existing RWM coils) on NSTX-U suggest the planned coils set is adequate for core and edge torque control. In conclusion, comparison between error field correction experiments on DIII-D and the optimizer show good agreement.« less

Human emotion detector based on genetic algorithm using lip features

NASA Astrophysics Data System (ADS)

Brown, Terrence; Fetanat, Gholamreza; Homaifar, Abdollah; Tsou, Brian; Mendoza-Schrock, Olga

2010-04-01

We predicted human emotion using a Genetic Algorithm (GA) based lip feature extractor from facial images to classify all seven universal emotions of fear, happiness, dislike, surprise, anger, sadness and neutrality. First, we isolated the mouth from the input images using special methods, such as Region of Interest (ROI) acquisition, grayscaling, histogram equalization, filtering, and edge detection. Next, the GA determined the optimal or near optimal ellipse parameters that circumvent and separate the mouth into upper and lower lips. The two ellipses then went through fitness calculation and were followed by training using a database of Japanese women's faces expressing all seven emotions. Finally, our proposed algorithm was tested using a published database consisting of emotions from several persons. The final results were then presented in confusion matrices. Our results showed an accuracy that varies from 20% to 60% for each of the seven emotions. The errors were mainly due to inaccuracies in the classification, and also due to the different expressions in the given emotion database. Detailed analysis of these errors pointed to the limitation of detecting emotion based on the lip features alone. Similar work [1] has been done in the literature for emotion detection in only one person, we have successfully extended our GA based solution to include several subjects.

A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories.

PubMed

Yang, Wei; Ai, Tinghua; Lu, Wei

2018-04-19

Crowdsourcing trajectory data is an important approach for accessing and updating road information. In this paper, we present a novel approach for extracting road boundary information from crowdsourcing vehicle traces based on Delaunay triangulation (DT). First, an optimization and interpolation method is proposed to filter abnormal trace segments from raw global positioning system (GPS) traces and interpolate the optimization segments adaptively to ensure there are enough tracking points. Second, constructing the DT and the Voronoi diagram within interpolated tracking lines to calculate road boundary descriptors using the area of Voronoi cell and the length of triangle edge. Then, the road boundary detection model is established integrating the boundary descriptors and trajectory movement features (e.g., direction) by DT. Third, using the boundary detection model to detect road boundary from the DT constructed by trajectory lines, and a regional growing method based on seed polygons is proposed to extract the road boundary. Experiments were conducted using the GPS traces of taxis in Beijing, China, and the results show that the proposed method is suitable for extracting the road boundary from low-frequency GPS traces, multi-type road structures, and different time intervals. Compared with two existing methods, the automatically extracted boundary information was proved to be of higher quality.

A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories

PubMed Central

Yang, Wei

2018-01-01

Crowdsourcing trajectory data is an important approach for accessing and updating road information. In this paper, we present a novel approach for extracting road boundary information from crowdsourcing vehicle traces based on Delaunay triangulation (DT). First, an optimization and interpolation method is proposed to filter abnormal trace segments from raw global positioning system (GPS) traces and interpolate the optimization segments adaptively to ensure there are enough tracking points. Second, constructing the DT and the Voronoi diagram within interpolated tracking lines to calculate road boundary descriptors using the area of Voronoi cell and the length of triangle edge. Then, the road boundary detection model is established integrating the boundary descriptors and trajectory movement features (e.g., direction) by DT. Third, using the boundary detection model to detect road boundary from the DT constructed by trajectory lines, and a regional growing method based on seed polygons is proposed to extract the road boundary. Experiments were conducted using the GPS traces of taxis in Beijing, China, and the results show that the proposed method is suitable for extracting the road boundary from low-frequency GPS traces, multi-type road structures, and different time intervals. Compared with two existing methods, the automatically extracted boundary information was proved to be of higher quality. PMID:29671792

The Effect of Aerodynamic Evaluators on the Multi-Objective Optimization of Flatback Airfoils

NASA Astrophysics Data System (ADS)

Miller, M.; Slew, K. Lee; Matida, E.

2016-09-01

With the long lengths of today's wind turbine rotor blades, there is a need to reduce the mass, thereby requiring stiffer airfoils, while maintaining the aerodynamic efficiency of the airfoils, particularly in the inboard region of the blade where structural demands are highest. Using a genetic algorithm, the multi-objective aero-structural optimization of 30% thick flatback airfoils was systematically performed for a variety of aerodynamic evaluators such as lift-to-drag ratio (Cl/Cd), torque (Ct), and torque-to-thrust ratio (Ct/Cn) to determine their influence on airfoil shape and performance. The airfoil optimized for Ct possessed a 4.8% thick trailing-edge, and a rather blunt leading-edge region which creates high levels of lift and correspondingly, drag. It's ability to maintain similar levels of lift and drag under forced transition conditions proved it's insensitivity to roughness. The airfoil optimized for Cl/Cd displayed relatively poor insensitivity to roughness due to the rather aft-located free transition points. The Ct/Cn optimized airfoil was found to have a very similar shape to that of the Cl/Cd airfoil, with a slightly more blunt leading-edge which aided in providing higher levels of lift and moderate insensitivity to roughness. The influence of the chosen aerodynamic evaluator under the specified conditions and constraints in the optimization of wind turbine airfoils is shown to have a direct impact on the airfoil shape and performance.

An acoustofluidic micromixer based on oscillating sidewall sharp-edges†

PubMed Central

Huang, Po-Hsun; Xie, Yuliang; Ahmed, Daniel; Rufo, Joseph; Nama, Nitesh; Chen, Yuchao; Chan, Chung Yu; Huang, Tony Jun

2014-01-01

Rapid and homogeneous mixing inside a microfluidic channel is demonstrated via the acoustic streaming phenomenon induced by the oscillation of sidewall sharp-edges. By optimizing the design of the sharp-edges, excellent mixing performance and fast mixing speed can be achieved in a simple device, making our sharp-edge-based acoustic micromixer a promising candidate for a wide variety of applications. PMID:23896797

Impact of MBE deposition conditions on InAs/GaInSb superlattices for very long wavelength infrared detection

NASA Astrophysics Data System (ADS)

Brown, G. J.; Haugan, H. J.; Mahalingam, K.; Grazulis, L.; Elhamri, S.

2015-01-01

The objective of this work is to establish molecular beam epitaxy (MBE) growth processes that can produce high quality InAs/GaInSb superlattice (SL) materials specifically tailored for very long wavelength infrared (VLWIR) detection. To accomplish this goal, several series of MBE growth optimization studies, using a SL structure of 47.0 Å InAs/21.5 Å Ga0.75In0.25Sb, were performed to refine the MBE growth process and optimize growth parameters. Experimental results demonstrated that our "slow" MBE growth process can consistently produce an energy gap near 50 meV. This is an important factor in narrow band gap SLs. However, there are other growth factors that also impact the electrical and optical properties of the SL materials. The SL layers are particularly sensitive to the anion incorporation condition formed during the surface reconstruction process. Since antisite defects are potentially responsible for the inherent residual carrier concentrations and short carrier lifetimes, the optimization of anion incorporation conditions, by manipulating anion fluxes, anion species, and deposition temperature, was systematically studied. Optimization results are reported in the context of comparative studies on the influence of the growth temperature on the crystal structural quality and surface roughness performed under a designed set of deposition conditions. The optimized SL samples produced an overall strong photoresponse signal with a relatively sharp band edge that is essential for developing VLWIR detectors. A quantitative analysis of the lattice strain, performed at the atomic scale by aberration corrected transmission electron microscopy, provided valuable information about the strain distribution at the GaInSb-on-InAs interface and in the InAs layers, which was important for optimizing the anion conditions.

Local extinction and turnover rates at the edge and interior of species' ranges

USGS Publications Warehouse

Doherty, P.F.; Boulinier, T.; James., D.

2003-01-01

One hypothesis for the maintenance of the edge of a species' range suggests that more central (and abundant) populations are relatively stable and edge populations are less stable with increased local extinction and turnover rates. To date, estimates of such metrics are equivocal due to design and analysis flaws. Apparent increased estimates of extinction and turnover rates at the edge of range, versus the interior, could be a function of decreased detection probabilities alone, and not of a biological process. We estimated extinction and turnover rates for species at the interiors and edges of their ranges using an approach which incorporates potential heterogeneity in species detection probabilities. Extinction rates were higher at the edges (0.17 ?? 0.03 []) than in the interiors (0.04 ?? 0.01), as was turnover. Without taking the probability of detection into account these differences would be artificially magnified. Knowledge of extinction and turnover rates is essential in furthering our understanding of range dynamics, and in directing conservation efforts. This study further illustrates the practical application of methods proposed recently for estimating extinction rates and other community dynamic parameters.

Local extinction and turnover rates at the edge and interior of species' ranges

USGS Publications Warehouse

Doherty, P.F.; Boulinier, T.; Nichols, J.D.

2003-01-01

One hypothesis for the maintenance of the edge of a species' range suggests that more central (and abundant) populations are relatively stable and edge populations are less stable with increased local extinction and turnover rates. To date, estimates of such metrics are equivocal due to design and analysis flaws. Apparent increased estimates of extinction and turnover rates at the edge of range, versus the interior, could be a function of decreased detection probabilities alone, and not of a biological process. We estimated extinction and turnover rates for species at the interiors and edges of their ranges using an approach which incorporates potential heterogeneity in species detection probabilities. Extinction rates were higher at the edges (0.17 ' 0.03 [SE]) than in the interiors (0.04 ' 0.01), as was turnover. Without taking the probability of detection into account these differences would be artificially magnified. Knowledge of extinction and turnover rates is essential in furthering our understanding of range dynamics, and in directing conservation efforts. This study further illustrates the practical application of methods proposed recently for estimating extinction rates and other community dynamic parameters.

Habitat edges have weak effects on duck nest survival at local spatial scales

USGS Publications Warehouse

Raquel, Amelia J; Ringelman, Kevin M.; Ackerman, Joshua T.; Eadie, John M.

2015-01-01

Edge effects on nesting success have been documented in breeding birds in a variety of contexts, but there is still uncertainty in how edge type and spatial scale determine the magnitude and detectability of edge effects. Habitat edges are often viewed as predator corridors that surround or penetrate core habitat and increase the risk of predation for nearby nests. We studied the effects of three different types of potential predator corridors (main perimeter roads, field boundaries, and ATV trails within fields) on waterfowl nest survival in California. We measured the distance from duck nests to the nearest edge of each type, and used distance as a covariate in a logistic exposure analysis of nest survival. We found only weak evidence for edge effects due to predation. The best supported model of nest survival included all three distance categories, and while all coefficient estimates were positive (indicating that survival increased with distance from edge), 85% coefficient confidence intervals approached or bounded zero indicating an overall weak effect of habitat edges on nest success. We suggest that given the configuration of edges at our site, there may be few areas far enough from hard edges to be considered ‘core’ habitat, making edge effects on nest survival particularly difficult to detect.

A new edge detection algorithm based on Canny idea

NASA Astrophysics Data System (ADS)

Feng, Yingke; Zhang, Jinmin; Wang, Siming

2017-10-01

The traditional Canny algorithm has poor self-adaptability threshold, and it is more sensitive to noise. In order to overcome these drawbacks, this paper proposed a new edge detection method based on Canny algorithm. Firstly, the media filtering and filtering based on the method of Euclidean distance are adopted to process it; secondly using the Frei-chen algorithm to calculate gradient amplitude; finally, using the Otsu algorithm to calculate partial gradient amplitude operation to get images of thresholds value, then find the average of all thresholds that had been calculated, half of the average is high threshold value, and the half of the high threshold value is low threshold value. Experiment results show that this new method can effectively suppress noise disturbance, keep the edge information, and also improve the edge detection accuracy.

Statistical wiring of thalamic receptive fields optimizes spatial sampling of the retinal image

PubMed Central

Wang, Xin; Sommer, Friedrich T.; Hirsch, Judith A.

2014-01-01

Summary It is widely assumed that mosaics of retinal ganglion cells establish the optimal representation of visual space. However, relay cells in the visual thalamus often receive convergent input from several retinal afferents and, in cat, outnumber ganglion cells. To explore how the thalamus transforms the retinal image, we built a model of the retinothalamic circuit using experimental data and simple wiring rules. The model shows how the thalamus might form a resampled map of visual space with the potential to facilitate detection of stimulus position in the presence of sensor noise. Bayesian decoding conducted with the model provides support for this scenario. Despite its benefits, however, resampling introduces image blur, thus impairing edge perception. Whole-cell recordings obtained in vivo suggest that this problem is mitigated by arrangements of excitation and inhibition within the receptive field that effectively boost contrast borders, much like strategies used in digital image processing. PMID:24559681

Design, testing, and damage tolerance study of bonded stiffened composite wing cover panels

NASA Technical Reports Server (NTRS)

Madan, Ram C.; Sutton, Jason O.

1988-01-01

Results are presented from the application of damage tolerance criteria for composite panels to multistringer composite wing cover panels developed under NASA's Composite Transport Wing Technology Development contract. This conceptual wing design integrated aeroelastic stiffness constraints with an enhanced damage tolerance material system, in order to yield optimized producibility and structural performance. Damage tolerance was demonstrated in a test program using full-sized cover panel subcomponents; panel skins were impacted at midbay between stiffeners, directly over a stiffener, and over the stiffener flange edge. None of the impacts produced visible damage. NASTRAN analyses were performed to simulate NDI-detected invisible damage.

Highly Uniform 150 mm Diameter Multichroic Polarimeter Array Deployed for CMB Detection

NASA Technical Reports Server (NTRS)

Ho, Shuay-Pwu Patty; Austermann, Jason; Beall, James A.; Choi, Steve K.; Cothard, Nicholas F.; Crowley, Kevin; Datta, Rahul; Devlin, Mark J.; Duff, Shannon M.; Wollack, Edward J.

2016-01-01

The Advanced Atacama Cosmology Telescope Polarimeter is an upgraded receiver for the Atacama Cosmology Telescope, which has begun making measurements of the small angular scale polarization anisotropies in the Cosmic Microwave Background using the first of four new multichroic superconducting detector arrays. Here, we review all details of the optimization and characterization of this first array, which features 2012 AlMn transition edge sensor bolometers operating at 150 and 230 GHz. We present critical temperatures, thermal conductivities,saturation powers, time constants, and sensitivities for the array. The results show high uniformity across the 150 mm wafer and good performance in the field.

BFL: a node and edge betweenness based fast layout algorithm for large scale networks

PubMed Central

Hashimoto, Tatsunori B; Nagasaki, Masao; Kojima, Kaname; Miyano, Satoru

2009-01-01

Background Network visualization would serve as a useful first step for analysis. However, current graph layout algorithms for biological pathways are insensitive to biologically important information, e.g. subcellular localization, biological node and graph attributes, or/and not available for large scale networks, e.g. more than 10000 elements. Results To overcome these problems, we propose the use of a biologically important graph metric, betweenness, a measure of network flow. This metric is highly correlated with many biological phenomena such as lethality and clusters. We devise a new fast parallel algorithm calculating betweenness to minimize the preprocessing cost. Using this metric, we also invent a node and edge betweenness based fast layout algorithm (BFL). BFL places the high-betweenness nodes to optimal positions and allows the low-betweenness nodes to reach suboptimal positions. Furthermore, BFL reduces the runtime by combining a sequential insertion algorim with betweenness. For a graph with n nodes, this approach reduces the expected runtime of the algorithm to O(n2) when considering edge crossings, and to O(n log n) when considering only density and edge lengths. Conclusion Our BFL algorithm is compared against fast graph layout algorithms and approaches requiring intensive optimizations. For gene networks, we show that our algorithm is faster than all layout algorithms tested while providing readability on par with intensive optimization algorithms. We achieve a 1.4 second runtime for a graph with 4000 nodes and 12000 edges on a standard desktop computer. PMID:19146673

Enhancing Community Detection By Affinity-based Edge Weighting Scheme

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

Yoo, Andy; Sanders, Geoffrey; Henson, Van

Community detection refers to an important graph analytics problem of finding a set of densely-connected subgraphs in a graph and has gained a great deal of interest recently. The performance of current community detection algorithms is limited by an inherent constraint of unweighted graphs that offer very little information on their internal community structures. In this paper, we propose a new scheme to address this issue that weights the edges in a given graph based on recently proposed vertex affinity. The vertex affinity quantifies the proximity between two vertices in terms of their clustering strength, and therefore, it is idealmore » for graph analytics applications such as community detection. We also demonstrate that the affinity-based edge weighting scheme can improve the performance of community detection algorithms significantly.« less

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

Balakrishnan, S.; Sankaranarayanan, R.

Nonlocal two-qubit gates are geometrically represented by tetrahedron known as Weyl chamber within which perfect entanglers form a polyhedron. We identify that all edges of the Weyl chamber and polyhedron are formed by single parametric gates. Nonlocal attributes of these edges are characterized using entangling power and local invariants. In particular, SWAP{sup -{alpha}} family of gates with 0{<=}{alpha}{<=}1 constitutes one edge of the Weyl chamber with SWAP{sup -1/2} being the only perfect entangler. Finally, optimal constructions of controlled-NOT using SWAP{sup -1/2} gate and gates belong to three edges of the polyhedron are presented.

The edge detection method of the infrared imagery of the laser spot

NASA Astrophysics Data System (ADS)

Che, Jinxi; Zhang, Jinchun; Li, Zhongmin

2016-01-01

In the jamming effectiveness experiments, in which the thermal infrared imager was interfered by the CO2 Laser, in order to evaluate the jamming effect of the thermal infrared imager by the CO2 Laser, it was needed to analyses the obtained infrared imagery of laser spot. Because the laser spot pictures obtained from the thermal infrared imager are irregular, the edge detection is an important process. The image edge is one of the most basic characteristics of the image, and it contains most of the information of the image. Generally, because of the thermal balance effect, the partly temperature of objective is no quite difference; therefore the infrared imagery's ability of reflecting the local detail of object is obvious week. At the same time, when the information of heat distribution of the thermal imagery was combined with the basic information of target, such as the object size, the relative position of field of view, shape and outline, and so on, the information just has more value. Hence, it is an important step for making image processing to extract the objective edge of the infrared imagery. Meanwhile it is an important part of image processing procedure and it is the premise of many subsequent processing. So as to extract outline information of the target from the original thermal imagery, and overcome the disadvantage, such as the low image contrast of the image and serious noise interference, and so on, the edge of thermal imagery needs detecting and processing. The principles of the Roberts, Sobel, Prewitt and Canny operator were analyzed, and then they were used to making edge detection on the thermal imageries of laser spot, which were obtained from the jamming effect experiments of CO2 laser jamming the thermal infrared imager. On the basis of the detection result, their performances were compared. At the end, the characteristics of the operators were summarized, which provide reference for the choice of edge detection operators in thermal imagery processing in future.

SAR-based change detection using hypothesis testing and Markov random field modelling

NASA Astrophysics Data System (ADS)

Cao, W.; Martinis, S.

2015-04-01

The objective of this study is to automatically detect changed areas caused by natural disasters from bi-temporal co-registered and calibrated TerraSAR-X data. The technique in this paper consists of two steps: Firstly, an automatic coarse detection step is applied based on a statistical hypothesis test for initializing the classification. The original analytical formula as proposed in the constant false alarm rate (CFAR) edge detector is reviewed and rewritten in a compact form of the incomplete beta function, which is a builtin routine in commercial scientific software such as MATLAB and IDL. Secondly, a post-classification step is introduced to optimize the noisy classification result in the previous step. Generally, an optimization problem can be formulated as a Markov random field (MRF) on which the quality of a classification is measured by an energy function. The optimal classification based on the MRF is related to the lowest energy value. Previous studies provide methods for the optimization problem using MRFs, such as the iterated conditional modes (ICM) algorithm. Recently, a novel algorithm was presented based on graph-cut theory. This method transforms a MRF to an equivalent graph and solves the optimization problem by a max-flow/min-cut algorithm on the graph. In this study this graph-cut algorithm is applied iteratively to improve the coarse classification. At each iteration the parameters of the energy function for the current classification are set by the logarithmic probability density function (PDF). The relevant parameters are estimated by the method of logarithmic cumulants (MoLC). Experiments are performed using two flood events in Germany and Australia in 2011 and a forest fire on La Palma in 2009 using pre- and post-event TerraSAR-X data. The results show convincing coarse classifications and considerable improvement by the graph-cut post-classification step.

Safer passenger car front shapes for pedestrians: A computational approach to reduce overall pedestrian injury risk in realistic impact scenarios.

PubMed

Li, Guibing; Yang, Jikuang; Simms, Ciaran

2017-03-01

Vehicle front shape has a significant influence on pedestrian injuries and the optimal design for overall pedestrian protection remains an elusive goal, especially considering the variability of vehicle-to-pedestrian accident scenarios. Therefore this study aims to develop and evaluate an efficient framework for vehicle front shape optimization for pedestrian protection accounting for the broad range of real world impact scenarios and their distributions in recent accident data. Firstly, a framework for vehicle front shape optimization for pedestrian protection was developed based on coupling of multi-body simulations and a genetic algorithm. This framework was then applied for optimizing passenger car front shape for pedestrian protection, and its predictions were evaluated using accident data and kinematic analyses. The results indicate that the optimization shows a good convergence and predictions of the optimization framework are corroborated when compared to the available accident data, and the optimization framework can distinguish 'good' and 'poor' vehicle front shapes for pedestrian safety. Thus, it is feasible and reliable to use the optimization framework for vehicle front shape optimization for reducing overall pedestrian injury risk. The results also show the importance of considering the broad range of impact scenarios in vehicle front shape optimization. A safe passenger car for overall pedestrian protection should have a wide and flat bumper (covering pedestrians' legs from the lower leg up to the shaft of the upper leg with generally even contacts), a bonnet leading edge height around 750mm, a short bonnet (<800mm) with a shallow or steep angle (either >17° or <12°) and a shallow windscreen (≤30°). Sensitivity studies based on simulations at the population level indicate that the demands for a safe passenger car front shape for head and leg protection are generally consistent, but partially conflict with pelvis protection. In particular, both head and leg injury risk increase with increasing bumper lower height and depth, and decrease with increasing bonnet leading edge height, while pelvis injury risk increases with increasing bonnet leading edge height. However, the effects of bonnet leading edge height and windscreen design on head injury risk are complex and require further analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Robust approach to ocular fundus image analysis

NASA Astrophysics Data System (ADS)

Tascini, Guido; Passerini, Giorgio; Puliti, Paolo; Zingaretti, Primo

1993-07-01

The analysis of morphological and structural modifications of retinal blood vessels plays an important role both to establish the presence of some systemic diseases as hypertension and diabetes and to study their course. The paper describes a robust set of techniques developed to quantitatively evaluate morphometric aspects of the ocular fundus vascular and micro vascular network. They are defined: (1) the concept of 'Local Direction of a vessel' (LD); (2) a special form of edge detection, named Signed Edge Detection (SED), which uses LD to choose the convolution kernel in the edge detection process and is able to distinguish between the left or the right vessel edge; (3) an iterative tracking (IT) method. The developed techniques use intensively both LD and SED in: (a) the automatic detection of number, position and size of blood vessels departing from the optical papilla; (b) the tracking of body and edges of the vessels; (c) the recognition of vessel branches and crossings; (d) the extraction of a set of features as blood vessel length and average diameter, arteries and arterioles tortuosity, crossing position and angle between two vessels. The algorithms, implemented in C language, have an execution time depending on the complexity of the currently processed vascular network.

Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

2018-04-01

In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

Finite-size effect on the dynamic and sensing performances of graphene resonators: the role of edge stress.

PubMed

Kim, Chang-Wan; Dai, Mai Duc; Eom, Kilho

2016-01-01

We have studied the finite-size effect on the dynamic behavior of graphene resonators and their applications in atomic mass detection using a continuum elastic model such as modified plate theory. In particular, we developed a model based on von Karman plate theory with including the edge stress, which arises from the imbalance between the coordination numbers of bulk atoms and edge atoms of graphene. It is shown that as the size of a graphene resonator decreases, the edge stress depending on the edge structure of a graphene resonator plays a critical role on both its dynamic and sensing performances. We found that the resonance behavior of graphene can be tuned not only through edge stress but also through nonlinear vibration, and that the detection sensitivity of a graphene resonator can be controlled by using the edge stress. Our study sheds light on the important role of the finite-size effect in the effective design of graphene resonators for their mass sensing applications.

Task-Driven Orbit Design and Implementation on a Robotic C-Arm System for Cone-Beam CT.

PubMed

Ouadah, S; Jacobson, M; Stayman, J W; Ehtiati, T; Weiss, C; Siewerdsen, J H

2017-03-01

This work applies task-driven optimization to the design of non-circular orbits that maximize imaging performance for a particular imaging task. First implementation of task-driven imaging on a clinical robotic C-arm system is demonstrated, and a framework for orbit calculation is described and evaluated. We implemented a task-driven imaging framework to optimize orbit parameters that maximize detectability index d '. This framework utilizes a specified Fourier domain task function and an analytical model for system spatial resolution and noise. Two experiments were conducted to test the framework. First, a simple task was considered consisting of frequencies lying entirely on the f z -axis (e.g., discrimination of structures oriented parallel to the central axial plane), and a "circle + arc" orbit was incorporated into the framework as a means to improve sampling of these frequencies, and thereby increase task-based detectability. The orbit was implemented on a robotic C-arm (Artis Zeego, Siemens Healthcare). A second task considered visualization of a cochlear implant simulated within a head phantom, with spatial frequency response emphasizing high-frequency content in the ( f y , f z ) plane of the cochlea. An optimal orbit was computed using the task-driven framework, and the resulting image was compared to that for a circular orbit. For the f z -axis task, the circle + arc orbit was shown to increase d ' by a factor of 1.20, with an improvement of 0.71 mm in a 3D edge-spread measurement for edges located far from the central plane and a decrease in streak artifacts compared to a circular orbit. For the cochlear implant task, the resulting orbit favored complementary views of high tilt angles in a 360° orbit, and d ' was increased by a factor of 1.83. This work shows that a prospective definition of imaging task can be used to optimize source-detector orbit and improve imaging performance. The method was implemented for execution of non-circular, task-driven orbits on a clinical robotic C-arm system. The framework is sufficiently general to include both acquisition parameters (e.g., orbit, kV, and mA selection) and reconstruction parameters (e.g., a spatially varying regularizer).

Task-driven orbit design and implementation on a robotic C-arm system for cone-beam CT

NASA Astrophysics Data System (ADS)

Ouadah, S.; Jacobson, M.; Stayman, J. W.; Ehtiati, T.; Weiss, C.; Siewerdsen, J. H.

2017-03-01

Purpose: This work applies task-driven optimization to the design of non-circular orbits that maximize imaging performance for a particular imaging task. First implementation of task-driven imaging on a clinical robotic C-arm system is demonstrated, and a framework for orbit calculation is described and evaluated. Methods: We implemented a task-driven imaging framework to optimize orbit parameters that maximize detectability index d'. This framework utilizes a specified Fourier domain task function and an analytical model for system spatial resolution and noise. Two experiments were conducted to test the framework. First, a simple task was considered consisting of frequencies lying entirely on the fz-axis (e.g., discrimination of structures oriented parallel to the central axial plane), and a "circle + arc" orbit was incorporated into the framework as a means to improve sampling of these frequencies, and thereby increase task-based detectability. The orbit was implemented on a robotic C-arm (Artis Zeego, Siemens Healthcare). A second task considered visualization of a cochlear implant simulated within a head phantom, with spatial frequency response emphasizing high-frequency content in the (fy, fz) plane of the cochlea. An optimal orbit was computed using the task-driven framework, and the resulting image was compared to that for a circular orbit. Results: For the fz-axis task, the circle + arc orbit was shown to increase d' by a factor of 1.20, with an improvement of 0.71 mm in a 3D edge-spread measurement for edges located far from the central plane and a decrease in streak artifacts compared to a circular orbit. For the cochlear implant task, the resulting orbit favored complementary views of high tilt angles in a 360° orbit, and d' was increased by a factor of 1.83. Conclusions: This work shows that a prospective definition of imaging task can be used to optimize source-detector orbit and improve imaging performance. The method was implemented for execution of non-circular, task-driven orbits on a clinical robotic C-arm system. The framework is sufficiently general to include both acquisition parameters (e.g., orbit, kV, and mA selection) and reconstruction parameters (e.g., a spatially varying regularizer).

A novel algorithm for osteoarthritis detection in Hough domain

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sabyasachi; Poria, Nilanjan; Chakraborty, Rajanya; Pratiher, Sawon; Mukherjee, Sukanya; Panigrahi, Prasanta K.

2018-02-01

Background subtraction of knee MRI images has been performed, followed by edge detection through canny edge detector. In order to avoid the discontinuities among edges, Daubechies-4 (Db-4) discrete wavelet transform (DWT) methodology is applied for the smoothening of edges identified through canny edge detector. The approximation coefficients of Db-4, having highest energy is selected to get rid of discontinuities in edges. Hough transform is then applied to find imperfect knee locations, as a function of distance (r) and angle (θ). The final outcome of the linear Hough transform is a two-dimensional array i.e., the accumulator space (r, θ) where one dimension of this matrix is the quantized angle θ and the other dimension is the quantized distance r. A novel algorithm has been suggested such that any deviation from the healthy knee bone structure for diseases like osteoarthritis can clearly be depicted on the accumulator space.

77 FR 33125 - Airworthiness Directives; Bombardier, Inc. Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-05

... along the wing leading edge and the inboard end rib of the wing leading edge due to insufficient clearance. This proposed AD would require inspecting the wire harness along the leading edge for chafing... to detect and correct chafing damage to the wire harness along the wing leading edge which, if not...

Development of a fully automatic scheme for detection of masses in whole breast ultrasound images.

PubMed

Ikedo, Yuji; Fukuoka, Daisuke; Hara, Takeshi; Fujita, Hiroshi; Takada, Etsuo; Endo, Tokiko; Morita, Takako

2007-11-01

Ultrasonography has been used for breast cancer screening in Japan. Screening using a conventional hand-held probe is operator dependent and thus it is possible that some areas of the breast may not be scanned. To overcome such problems, a mechanical whole breast ultrasound (US) scanner has been proposed and developed for screening purposes. However, another issue is that radiologists might tire while interpreting all images in a large-volume screening; this increases the likelihood that masses may remain undetected. Therefore, the aim of this study is to develop a fully automatic scheme for the detection of masses in whole breast US images in order to assist the interpretations of radiologists and potentially improve the screening accuracy. The authors database comprised 109 whole breast US imagoes, which include 36 masses (16 malignant masses, 5 fibroadenomas, and 15 cysts). A whole breast US image with 84 slice images (interval between two slice images: 2 mm) was obtained by the ASU-1004 US scanner (ALOKA Co., Ltd., Japan). The feature based on the edge directions in each slice and a method for subtracting between the slice images were used for the detection of masses in the authors proposed scheme. The Canny edge detector was applied to detect edges in US images; these edges were classified as near-vertical edges or near-horizontal edges using a morphological method. The positions of mass candidates were located using the near-vertical edges as a cue. Then, the located positions were segmented by the watershed algorithm and mass candidate regions were detected using the segmented regions and the low-density regions extracted by the slice subtraction method. For the removal of false positives (FPs), rule-based schemes and a quadratic discriminant analysis were applied for the distribution between masses and FPs. As a result, the sensitivity of the authors scheme for the detection of masses was 80.6% (29/36) with 3.8 FPs per whole breast image. The authors scheme for a computer-aided detection may be useful in improving the screening performance and efficiency.

Natural and artificial spectral edges in exoplanets

NASA Astrophysics Data System (ADS)

Lingam, Manasvi; Loeb, Abraham

2017-09-01

Technological civilizations may rely upon large-scale photovoltaic arrays to harness energy from their host star. Photovoltaic materials, such as silicon, possess distinctive spectral features, including an 'artificial edge' that is characteristically shifted in wavelength shortwards of the 'red edge' of vegetation. Future observations of reflected light from exoplanets would be able to detect both natural and artificial edges photometrically, if a significant fraction of the planet's surface is covered by vegetation or photovoltaic arrays, respectively. The stellar energy thus tapped can be utilized for terraforming activities by transferring heat and light from the day side to the night side on tidally locked exoplanets, thereby producing detectable artefacts.

Three-dimensional contour edge detection algorithm

NASA Astrophysics Data System (ADS)

Wang, Yizhou; Ong, Sim Heng; Kassim, Ashraf A.; Foong, Kelvin W. C.

2000-06-01

This paper presents a novel algorithm for automatically extracting 3D contour edges, which are points of maximum surface curvature in a surface range image. The 3D image data are represented as a surface polygon mesh. The algorithm transforms the range data, obtained by scanning a dental plaster cast, into a 2D gray scale image by linearly converting the z-value of each vertex to a gray value. The Canny operator is applied to the median-filtered image to obtain the edge pixels and their orientations. A vertex in the 3D object corresponding to the detected edge pixel and its neighbors in the direction of the edge gradient are further analyzed with respect to their n-curvatures to extract the real 3D contour edges. This algorithm provides a fast method of reducing and sorting the unwieldy data inherent in the surface mesh representation. It employs powerful 2D algorithms to extract features from the transformed 3D models and refers to the 3D model for further analysis of selected data. This approach substantially reduces the computational burden without losing accuracy. It is also easily extended to detect 3D landmarks and other geometrical features, thus making it applicable to a wide range of applications.

Reducing radiation dose by application of optimized low-energy x-ray filters to K-edge imaging with a photon counting detector.

PubMed

Choi, Yu-Na; Lee, Seungwan; Kim, Hee-Joung

2016-01-21

K-edge imaging with photon counting x-ray detectors (PCXDs) can improve image quality compared with conventional energy integrating detectors. However, low-energy x-ray photons below the K-edge absorption energy of a target material do not contribute to image formation in the K-edge imaging and are likely to be completely absorbed by an object. In this study, we applied x-ray filters to the K-edge imaging with a PCXD based on cadmium zinc telluride for reducing radiation dose induced by low-energy x-ray photons. We used aluminum (Al) filters with different thicknesses as the low-energy x-ray filters and implemented the iodine K-edge imaging with an energy bin of 34-48 keV at the tube voltages of 50, 70 and 90 kVp. The effects of the low-energy x-ray filters on the K-edge imaging were investigated with respect to signal-difference-to-noise ratio (SDNR), entrance surface air kerma (ESAK) and figure of merit (FOM). The highest value of SDNR was observed in the K-edge imaging with a 2 mm Al filter, and the SDNR decreased as a function of the filter thicknesses. Compared to the K-edge imaging with a 2 mm Al filter, the ESAK was reduced by 66%, 48% and 39% in the K-edge imaging with a 12 mm Al filter for 50 kVp, 70 kVp and 90 kVp, respectively. The FOM values, which took into account the ESAK and SDNR, were maximized for 8, 6 to 8 and 4 mm Al filters at 50 kVp, 70 kVp and 90 kVp, respectively. We concluded that the use of an optimal low-energy filter thickness, which was determined by maximizing the FOM, could significantly reduce radiation dose while maintaining image quality in the K-edge imaging with the PCXD.

Detection of fractional solitons in quantum spin Hall systems

NASA Astrophysics Data System (ADS)

Fleckenstein, C.; Traverso Ziani, N.; Trauzettel, B.

2018-03-01

We propose two experimental setups that allow for the implementation and the detection of fractional solitons of the Goldstone-Wilczek type. The first setup is based on two magnetic barriers at the edge of a quantum spin Hall system for generating the fractional soliton. If then a quantum point contact is created with the other edge, the linear conductance shows evidence of the fractional soliton. The second setup consists of a single magnetic barrier covering both edges and implementing a long quantum point contact. In this case, the fractional soliton can unambiguously be detected as a dip in the conductance without the need to control the magnetization of the barrier.

Global Radius of Curvature Estimation and Control System for Segmented Mirrors

NASA Technical Reports Server (NTRS)

Rakoczy, John M. (Inventor)

2006-01-01

An apparatus controls positions of plural mirror segments in a segmented mirror with an edge sensor system and a controller. Current mirror segment edge sensor measurements and edge sensor reference measurements are compared with calculated edge sensor bias measurements representing a global radius of curvature. Accumulated prior actuator commands output from an edge sensor control unit are combined with an estimator matrix to form the edge sensor bias measurements. An optimal control matrix unit then accumulates the plurality of edge sensor error signals calculated by the summation unit and outputs the corresponding plurality of actuator commands. The plural mirror actuators respond to the actuator commands by moving respective positions of the mixor segments. A predetermined number of boundary conditions, corresponding to a plurality of hexagonal mirror locations, are removed to afford mathematical matrix calculation.

Optimization of a Scintillator for the Measurement of Positrons from Trapped, Polarized 37K

NASA Astrophysics Data System (ADS)

France, Erin; Melconian, Dan

2011-10-01

Precision beta decay experiments can be used to test the Standard Model via their value of correlation parameters. The TRINAT Collaboration is performing such an experiment using a source of polarized 37K from a magneto optical trap. The momentum of an emitted positron will be detected using a Silicon strip detector backed by a plastic scintillator. The goal of my research was to optimize the readout of the scintillator by testing different experimental setups. The front face and sides of the scintillator and light guide were wrapped with various reflective materials to find which maximized the light output. We found that one layer of Teflon tape on the front face with a loose wrapping of 3M-ESR (Enhanced Spectral Reflector) on the sides was optimal. We then tested the position dependence of this detector by moving a collimated source of betas across the front face, showing only a (5.9 +/- 0.5)% reduction in light collection at the edge compared to the center. The product of this work will be used in the upcoming TRINAT experiment measuring the beta asymmetry of 37K.

Entangled states in the role of witnesses

NASA Astrophysics Data System (ADS)

Wang, Bang-Hai

2018-05-01

Quantum entanglement lies at the heart of quantum mechanics and quantum information processing. In this work, we show a framework where entangled states play the role of witnesses. We extend the notion of entanglement witnesses, developing a hierarchy of witnesses for classes of observables. This hierarchy captures the fact that entangled states act as witnesses for detecting entanglement witnesses and separable states act as witnesses for the set of non-block-positive Hermitian operators. Indeed, more hierarchies of witnesses exist. We introduce the concept of finer and optimal entangled states. These definitions not only give an unambiguous and non-numeric quantification of entanglement and an alternative perspective on edge states but also answer the open question of what the remainder of the best separable approximation of a density matrix is. Furthermore, we classify all entangled states into disjoint families with optimal entangled states at its heart. This implies that we can focus only on the study of a typical family with optimal entangled states at its core when we investigate entangled states. Our framework also assembles many seemingly different findings with simple arguments that do not require lengthy calculations.

Optimizing Radiometric Fidelity to Enhance Aerial Image Change Detection Utilizing Digital Single Lens Reflex (DSLR) Cameras

NASA Astrophysics Data System (ADS)

Kerr, Andrew D.

Determining optimal imaging settings and best practices related to the capture of aerial imagery using consumer-grade digital single lens reflex (DSLR) cameras, should enable remote sensing scientists to generate consistent, high quality, and low cost image data sets. Radiometric optimization, image fidelity, image capture consistency and repeatability were evaluated in the context of detailed image-based change detection. The impetus for this research is in part, a dearth of relevant, contemporary literature, on the utilization of consumer grade DSLR cameras for remote sensing, and the best practices associated with their use. The main radiometric control settings on a DSLR camera, EV (Exposure Value), WB (White Balance), light metering, ISO, and aperture (f-stop), are variables that were altered and controlled over the course of several image capture missions. These variables were compared for their effects on dynamic range, intra-frame brightness variation, visual acuity, temporal consistency, and the detectability of simulated cracks placed in the images. This testing was conducted from a terrestrial, rather than an airborne collection platform, due to the large number of images per collection, and the desire to minimize inter-image misregistration. The results point to a range of slightly underexposed image exposure values as preferable for change detection and noise minimization fidelity. The makeup of the scene, the sensor, and aerial platform, influence the selection of the aperture and shutter speed which along with other variables, allow for estimation of the apparent image motion (AIM) motion blur in the resulting images. The importance of the image edges in the image application, will in part dictate the lowest usable f-stop, and allow the user to select a more optimal shutter speed and ISO. The single most important camera capture variable is exposure bias (EV), with a full dynamic range, wide distribution of DN values, and high visual contrast and acuity occurring around -0.7 to -0.3EV exposure bias. The ideal values for sensor gain, was found to be ISO 100, with ISO 200 a less desirable. This study offers researchers a better understanding of the effects of camera capture settings on RSI pairs and their influence on image-based change detection.

Algorithm for Automated Detection of Edges of Clouds

NASA Technical Reports Server (NTRS)

Ward, Jennifer G.; Merceret, Francis J.

2006-01-01

An algorithm processes cloud-physics data gathered in situ by an aircraft, along with reflectivity data gathered by ground-based radar, to determine whether the aircraft is inside or outside a cloud at a given time. A cloud edge is deemed to be detected when the in/out state changes, subject to a hysteresis constraint. Such determinations are important in continuing research on relationships among lightning, electric charges in clouds, and decay of electric fields with distance from cloud edges.

A novel organophosphorus hydrolase-based biosensor using mesoporous carbons and carbon black for the detection of organophosphate nerve agents.

PubMed

Lee, Joon Hwan; Park, Jae Yeon; Min, Kyoungseon; Cha, Hyung Joon; Choi, Suk Soon; Yoo, Young Je

2010-03-15

To detect organophosphate chemicals, which are used both as pesticides and as nerve agents, a novel biosensor based on organophosphorus hydrolase was developed. By using mesoporous carbon (MC) and carbon black (CB) as an anodic layer, the sensitivity of the sensor to p-nitrophenol (PNP), which is the product of the organophosphorus hydrolase reaction, was greatly improved. The MC/CB/glass carbon (GC) layer exhibited an enhanced amperometric response relative to a carbon nanotube (CNT)-modified electrode because it promoted electron transfer of enzymatically generated phenolic compounds (p-nitrophenol). The well-ordered nanopores, many edge-plane-like defective sites (EDSs), and high surface area of the MC resulted in increased sensitivity, and allowed for nanomolar-range detection of the analyte paraoxon. Thus, MCs are suitable for use in real-time biosensors. Under the optimized experimental conditions, the biosensor had a detection limit of 0.12 microM (36 ppb) and a sensitivity of 198 nA/microM for paraoxon. (c) 2009 Elsevier B.V. All rights reserved.

Research and Development Trend of Shape Control for Cold Rolling Strip

NASA Astrophysics Data System (ADS)

Wang, Dong-Cheng; Liu, Hong-Min; Liu, Jun

2017-09-01

Shape is an important quality index of cold rolling strip. Up to now, many problems in the shape control domain have not been solved satisfactorily, and a review on the research progress in the shape control domain can help to seek new breakthrough directions. In the past 10 years, researches and applications of shape control models, shape control means, shape detection technology, and shape control system have achieved significant progress. In the aspect of shape control models, the researches in the past improve the accuracy, speed and robustness of the models. The intelligentization of shape control models should be strengthened in the future. In the aspect of the shape control means, the researches in the past focus on the roll optimization, mill type selection, process optimization, local strip shape control, edge drop control, and so on. In the future, more attention should be paid to the coordination control of both strip shape and other quality indexes, and the refinement of control objective should be strengthened. In the aspects of shape detection technology and shape control system, some new types of shape detection meters and shape control systems are developed and have successfully industrial applications. In the future, the standardization of shape detection technology and shape control system should be promoted to solve the problem of compatibility. In general, the four expected development trends of shape control for cold rolling strip in the future are intelligentization, coordination, refinement, and standardization. The proposed research provides new breakthrough directions for improving shape quality.

Hybrid Optimization of Object-Based Classification in High-Resolution Images Using Continous ANT Colony Algorithm with Emphasis on Building Detection

NASA Astrophysics Data System (ADS)

Tamimi, E.; Ebadi, H.; Kiani, A.

2017-09-01

Automatic building detection from High Spatial Resolution (HSR) images is one of the most important issues in Remote Sensing (RS). Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM) classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO) algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF) classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object). These showed the superiority of the proposed method in terms of time and accuracy.

Optimal Shape of a Gamma-ray Collimator: single vs double knife edge

NASA Astrophysics Data System (ADS)

Metz, Albert; Hogenbirk, Alfred

2017-09-01

Gamma-ray collimators in nuclear waste scanners are used for selecting a narrow vertical segment in activity measurements of waste vessels. The system that is used by NRG uses tapered slit collimators of both the single and double knife edge type. The properties of these collimators were investigated by means of Monte Carlo simulations. We found that single knife edge collimators are highly preferable for a conservative estimate of the activity of the waste vessels. These collimators show much less dependence on the angle of incidence of the radiation than double knife edge collimators. This conclusion also applies to cylindrical collimators of the single knife edge type, that are generally used in medical imaging spectroscopy.

Real-time line-width measurements: a new feature for reticle inspection systems

NASA Astrophysics Data System (ADS)

Eran, Yair; Greenberg, Gad; Joseph, Amnon; Lustig, Cornel; Mizrahi, Eyal

1997-07-01

The significance of line width control in mask production has become greater with the lessening of defect size. There are two conventional methods used for controlling line widths dimensions which employed in the manufacturing of masks for sub micron devices. These two methods are the critical dimensions (CD) measurement and the detection of edge defects. Achieving reliable and accurate control of line width errors is one of the most challenging tasks in mask production. Neither of the two methods cited above (namely CD measurement and the detection of edge defects) guarantees the detection of line width errors with good sensitivity over the whole mask area. This stems from the fact that CD measurement provides only statistical data on the mask features whereas applying edge defect detection method checks defects on each edge by itself, and does not supply information on the combined result of error detection on two adjacent edges. For example, a combination of a small edge defect together with a CD non- uniformity which are both within the allowed tolerance, may yield a significant line width error, which will not be detected using the conventional methods (see figure 1). A new approach for the detection of line width errors which overcomes this difficulty is presented. Based on this approach, a new sensitive line width error detector was developed and added to Orbot's RT-8000 die-to-database reticle inspection system. This innovative detector operates continuously during the mask inspection process and scans (inspects) the entire area of the reticle for line width errors. The detection is based on a comparison of measured line width that are taken on both the design database and the scanned image of the reticle. In section 2, the motivation for developing this new detector is presented. The section covers an analysis of various defect types, which are difficult to detect using conventional edge detection methods or, alternatively, CD measurements. In section 3, the basic concept of the new approach is introduced together with a description of the new detector and its characteristics. In section 4, the calibration process that took place in order to achieve reliable and repeatable line width measurements is presented. The description of an experiments conducted in order to evaluate the sensitivity of the new detector is given in section 5, followed by a report of the results of this evaluation. The conclusions are presented in section 6.

Topological transitions in continuously deformed photonic crystals

NASA Astrophysics Data System (ADS)

Zhu, Xuan; Wang, Hai-Xiao; Xu, Changqing; Lai, Yun; Jiang, Jian-Hua; John, Sajeev

2018-02-01

We demonstrate that multiple topological transitions can occur, with high sensitivity, by continuous change of the geometry of a simple two-dimensional dielectric-frame photonic crystal consisting of circular air holes. By changing the radii of the holes and/or the distance between them, multiple transitions between normal and topological photonic band gaps (PBGs) can appear. The time-reversal symmetric topological PBGs resemble the quantum spin Hall insulator of electrons and have two counterpropagating edge states. We search for optimal topological transitions, i.e., sharp transitions sensitive to the geometry, and optimal topological PBGs, i.e., large PBGs with a clean spectrum of edge states. Such optimizations reveal that dielectric-frame photonic crystals are promising for optical sensors and unidirectional waveguides.

Markov random field model-based edge-directed image interpolation.

PubMed

Li, Min; Nguyen, Truong Q

2008-07-01

This paper presents an edge-directed image interpolation algorithm. In the proposed algorithm, the edge directions are implicitly estimated with a statistical-based approach. In opposite to explicit edge directions, the local edge directions are indicated by length-16 weighting vectors. Implicitly, the weighting vectors are used to formulate geometric regularity (GR) constraint (smoothness along edges and sharpness across edges) and the GR constraint is imposed on the interpolated image through the Markov random field (MRF) model. Furthermore, under the maximum a posteriori-MRF framework, the desired interpolated image corresponds to the minimal energy state of a 2-D random field given the low-resolution image. Simulated annealing methods are used to search for the minimal energy state from the state space. To lower the computational complexity of MRF, a single-pass implementation is designed, which performs nearly as well as the iterative optimization. Simulation results show that the proposed MRF model-based edge-directed interpolation method produces edges with strong geometric regularity. Compared to traditional methods and other edge-directed interpolation methods, the proposed method improves the subjective quality of the interpolated edges while maintaining a high PSNR level.

Edge-based correlation image registration for multispectral imaging

DOEpatents

Nandy, Prabal [Albuquerque, NM

2009-11-17

Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

Mortality after percutaneous edge-to-edge mitral valve repair: a contemporary review.

PubMed

Kortlandt, Friso A; de Beenhouwer, Thomas; Swaans, Martin J; Post, Marco C; van der Heyden, Jan A S; Eefting, Frank D; Rensing, Benno J W M

2016-04-01

Percutaneous edge-to-edge mitral valve (MV) repair is a relatively new treatment option for mitral regurgitation (MR). After the feasibility and safety having been proved in low-surgical-risk patients, the use of this procedure has shifted more to the treatment of high-risk patients. With the absence of randomized controlled trials (RCT) for this particular subgroup, observational studies try to add evidence to the safety aspect of this procedure. These also provide short- and mid-term mortality figures. Several mortality predictors have been identified, which may help the optimal selection of patients who will benefit most from this technique. In this article we provide an overview of the literature about mortality and its predictors in patients treated with the percutaneous edge-to-edge device.

A synthetic genetic edge detection program.

PubMed

Tabor, Jeffrey J; Salis, Howard M; Simpson, Zachary Booth; Chevalier, Aaron A; Levskaya, Anselm; Marcotte, Edward M; Voigt, Christopher A; Ellington, Andrew D

2009-06-26

Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E. coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.

A Synthetic Genetic Edge Detection Program

PubMed Central

Tabor, Jeffrey J.; Salis, Howard; Simpson, Zachary B.; Chevalier, Aaron A.; Levskaya, Anselm; Marcotte, Edward M.; Voigt, Christopher A.; Ellington, Andrew D.

2009-01-01

Summary Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E.coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks. PMID:19563759

Intelligent identification of remnant ridge edges in region west of Yongxing Island, South China Sea

NASA Astrophysics Data System (ADS)

Wang, Weiwei; Guo, Jing; Cai, Guanqiang; Wang, Dawei

2018-02-01

Edge detection enables identification of geomorphologic unit boundaries and thus assists with geomorphical mapping. In this paper, an intelligent edge identification method is proposed and image processing techniques are applied to multi-beam bathymetry data. To accomplish this, a color image is generated by the bathymetry, and a weighted method is used to convert the color image to a gray image. As the quality of the image has a significant influence on edge detection, different filter methods are applied to the gray image for de-noising. The peak signal-to-noise ratio and mean square error are calculated to evaluate which filter method is most appropriate for depth image filtering and the edge is subsequently detected using an image binarization method. Traditional image binarization methods cannot manage the complicated uneven seafloor, and therefore a binarization method is proposed that is based on the difference between image pixel values; the appropriate threshold for image binarization is estimated according to the probability distribution of pixel value differences between two adjacent pixels in horizontal and vertical directions, respectively. Finally, an eight-neighborhood frame is adopted to thin the binary image, connect the intermittent edge, and implement contour extraction. Experimental results show that the method described here can recognize the main boundaries of geomorphologic units. In addition, the proposed automatic edge identification method avoids use of subjective judgment, and reduces time and labor costs.

Optimization of the poro-serrated trailing edges for airfoil broadband noise reduction.

PubMed

Chong, Tze Pei; Dubois, Elisa

2016-08-01

This paper reports an aeroacoustic investigation of a NACA0012 airfoil with a number of poro-serrated trailing edge devices that contain porous materials of various air flow resistances at the gaps between adjacent members of the serrated-sawtooth trailing edge. The main objective of this work is to determine whether multiple-mechanisms on the broadband noise reduction can co-exist on a poro-serrated trailing edge. When the sawtooth gaps are filled with porous material of low-flow resistivity, the vortex shedding tone at low-frequency could not be completely suppressed at high-velocity, but a reasonably good broadband noise reduction can be achieved at high-frequency. When the sawtooth gaps are filled with porous material of very high-flow resistivity, no vortex shedding tone is present, but the serration effect on the broadband noise reduction becomes less effective. An optimal choice of the flow resistivity for a poro-serrated configuration has been identified, where it can surpass the conventional serrated trailing edge of the same geometry by achieving a further 1.5 dB reduction in the broadband noise while completely suppressing the vortex shedding tone. A weakened turbulent boundary layer noise scattering at the poro-serrated trailing edge is reflected by the lower-turbulence intensity at the near wake centreline across the whole spanwise wavelength of the sawtooth.

Information filtering via weighted heat conduction algorithm

NASA Astrophysics Data System (ADS)

Liu, Jian-Guo; Guo, Qiang; Zhang, Yi-Cheng

2011-06-01

In this paper, by taking into account effects of the user and object correlations on a heat conduction (HC) algorithm, a weighted heat conduction (WHC) algorithm is presented. We argue that the edge weight of the user-object bipartite network should be embedded into the HC algorithm to measure the object similarity. The numerical results indicate that both the accuracy and diversity could be improved greatly compared with the standard HC algorithm and the optimal values reached simultaneously. On the Movielens and Netflix datasets, the algorithmic accuracy, measured by the average ranking score, can be improved by 39.7% and 56.1% in the optimal case, respectively, and the diversity could reach 0.9587 and 0.9317 when the recommendation list equals to 5. Further statistical analysis indicates that, in the optimal case, the distributions of the edge weight are changed to the Poisson form, which may be the reason why HC algorithm performance could be improved. This work highlights the effect of edge weight on a personalized recommendation study, which maybe an important factor affecting personalized recommendation performance.

Optimal network modification for spectral radius dependent phase transitions

NASA Astrophysics Data System (ADS)

Rosen, Yonatan; Kirsch, Lior; Louzoun, Yoram

2016-09-01

The dynamics of contact processes on networks is often determined by the spectral radius of the networks adjacency matrices. A decrease of the spectral radius can prevent the outbreak of an epidemic, or impact the synchronization among systems of coupled oscillators. The spectral radius is thus tightly linked to network dynamics and function. As such, finding the minimal change in network structure necessary to reach the intended spectral radius is important theoretically and practically. Given contemporary big data resources such as large scale communication or social networks, this problem should be solved with a low runtime complexity. We introduce a novel method for the minimal decrease in weights of edges required to reach a given spectral radius. The problem is formulated as a convex optimization problem, where a global optimum is guaranteed. The method can be easily adjusted to an efficient discrete removal of edges. We introduce a variant of the method which finds optimal decrease with a focus on weights of vertices. The proposed algorithm is exceptionally scalable, solving the problem for real networks of tens of millions of edges in a short time.

A tight upper bound for quadratic knapsack problems in grid-based wind farm layout optimization

NASA Astrophysics Data System (ADS)

Quan, Ning; Kim, Harrison M.

2018-03-01

The 0-1 quadratic knapsack problem (QKP) in wind farm layout optimization models possible turbine locations as nodes, and power loss due to wake effects between pairs of turbines as edges in a complete graph. The goal is to select up to a certain number of turbine locations such that the sum of selected node and edge coefficients is maximized. Finding the optimal solution to the QKP is difficult in general, but it is possible to obtain a tight upper bound on the QKP's optimal value which facilitates the use of heuristics to solve QKPs by giving a good estimate of the optimality gap of any feasible solution. This article applies an upper bound method that is especially well-suited to QKPs in wind farm layout optimization due to certain features of the formulation that reduce the computational complexity of calculating the upper bound. The usefulness of the upper bound was demonstrated by assessing the performance of the greedy algorithm for solving QKPs in wind farm layout optimization. The results show that the greedy algorithm produces good solutions within 4% of the optimal value for small to medium sized problems considered in this article.

Spatial vision processes: From the optical image to the symbolic structures of contour information

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.

1988-01-01

The significance of machine and natural vision is discussed together with the need for a general approach to image acquisition and processing aimed at recognition. An exploratory scheme is proposed which encompasses the definition of spatial primitives, intrinsic image properties and sampling, 2-D edge detection at the smallest scale, the construction of spatial primitives from edges, and the isolation of contour information from textural information. Concepts drawn from or suggested by natural vision at both perceptual and physiological levels are relied upon heavily to guide the development of the overall scheme. The scheme is intended to provide a larger context in which to place the emerging technology of detector array focal-plane processors. The approach differs from many recent efforts in edge detection and image coding by emphasizing smallest scale edge detection as a foundation for multi-scale symbolic processing while diminishing somewhat the importance of image convolutions with multi-scale edge operators. Cursory treatments of information theory illustrate that the direct application of this theory to structural information in images could not be realized.

Segmentation of blurred objects using wavelet transform: application to x-ray images

NASA Astrophysics Data System (ADS)

Barat, Cecile S.; Ducottet, Christophe; Bilgot, Anne; Desbat, Laurent

2004-02-01

First, we present a wavelet-based algorithm for edge detection and characterization, which is an adaptation of Mallat and Hwang"s method. This algorithm relies on a modelization of contours as smoothed singularities of three particular types (transitions, peaks and lines). On the one hand, it allows to detect and locate edges at an adapted scale. On the other hand, it is able to identify the type of each detected edge point and to measure its amplitude and smoothing size. The latter parameters represent respectively the contrast and the smoothness level of the edge point. Second, we explain that this method has been integrated in a 3D bone surface reconstruction algorithm designed for computer-assisted and minimal invasive orthopaedic surgery. In order to decrease the dose to the patient and to obtain rapidly a 3D image, we propose to identify a bone shape from few X-ray projections by using statistical shape models registered to segmented X-ray projections. We apply this approach to pedicle screw insertion (scoliosis, fractures...) where ten to forty percent of the screws are known to be misplaced. In this context, the proposed edge detection algorithm allows to overcome the major problem of vertebrae segmentation in the X-ray images.

An automated approach to magnetic divertor configuration design

NASA Astrophysics Data System (ADS)

Blommaert, M.; Dekeyser, W.; Baelmans, M.; Gauger, N. R.; Reiter, D.

2015-01-01

Automated methods based on optimization can greatly assist computational engineering design in many areas. In this paper an optimization approach to the magnetic design of a nuclear fusion reactor divertor is proposed and applied to a tokamak edge magnetic configuration in a first feasibility study. The approach is based on reduced models for magnetic field and plasma edge, which are integrated with a grid generator into one sensitivity code. The design objective chosen here for demonstrative purposes is to spread the divertor target heat load as much as possible over the entire target area. Constraints on the separatrix position are introduced to eliminate physically irrelevant magnetic field configurations during the optimization cycle. A gradient projection method is used to ensure stable cost function evaluations during optimization. The concept is applied to a configuration with typical Joint European Torus (JET) parameters and it automatically provides plausible configurations with reduced heat load.

TRO-2D - A code for rational transonic aerodynamic optimization

NASA Technical Reports Server (NTRS)

Davis, W. H., Jr.

1985-01-01

Features and sample applications of the transonic rational optimization (TRO-2D) code are outlined. TRO-2D includes the airfoil analysis code FLO-36, the CONMIN optimization code and a rational approach to defining aero-function shapes for geometry modification. The program is part of an effort to develop an aerodynamically smart optimizer that will simplify and shorten the design process. The user has a selection of drag minimization and associated minimum lift, moment, and the pressure distribution, a choice among 14 resident aero-function shapes, and options on aerodynamic and geometric constraints. Design variables such as the angle of attack, leading edge radius and camber, shock strength and movement, supersonic pressure plateau control, etc., are discussed. The results of calculations of a reduced leading edge camber transonic airfoil and an airfoil with a natural laminar flow are provided, showing that only four design variables need be specified to obtain satisfactory results.

High accuracy position method based on computer vision and error analysis

NASA Astrophysics Data System (ADS)

Chen, Shihao; Shi, Zhongke

2003-09-01

The study of high accuracy position system is becoming the hotspot in the field of autocontrol. And positioning is one of the most researched tasks in vision system. So we decide to solve the object locating by using the image processing method. This paper describes a new method of high accuracy positioning method through vision system. In the proposed method, an edge-detection filter is designed for a certain running condition. Here, the filter contains two mainly parts: one is image-processing module, this module is to implement edge detection, it contains of multi-level threshold self-adapting segmentation, edge-detection and edge filter; the other one is object-locating module, it is to point out the location of each object in high accurate, and it is made up of medium-filtering and curve-fitting. This paper gives some analysis error for the method to prove the feasibility of vision in position detecting. Finally, to verify the availability of the method, an example of positioning worktable, which is using the proposed method, is given at the end of the paper. Results show that the method can accurately detect the position of measured object and identify object attitude.

Automatic airline baggage counting using 3D image segmentation

NASA Astrophysics Data System (ADS)

Yin, Deyu; Gao, Qingji; Luo, Qijun

2017-06-01

The baggage number needs to be checked automatically during baggage self-check-in. A fast airline baggage counting method is proposed in this paper using image segmentation based on height map which is projected by scanned baggage 3D point cloud. There is height drop in actual edge of baggage so that it can be detected by the edge detection operator. And then closed edge chains are formed from edge lines that is linked by morphological processing. Finally, the number of connected regions segmented by closed chains is taken as the baggage number. Multi-bag experiment that is performed on the condition of different placement modes proves the validity of the method.

The Superior-Edge-of-the-Knee Incision Method in Lymphaticovenular Anastomosis for Lower Extremity Lymphedema.

PubMed

Seki, Yukio; Yamamoto, Takumi; Yoshimatsu, Hidehiko; Hayashi, Akitatsu; Kurazono, Arito; Mori, Masanori; Kato, Yoichi; Koshima, Isao

2015-11-01

Lymphatic vessel diameter and lymph flow are important for accurate anastomosis and effective lymph-to-venous flow in lymphaticovenular anastomosis. The authors developed a reliable method, the superioredge-of-the-knee incision method, for detecting and making the best use of high-flow lymphatic vessels in the distal medial thigh between the deep and superficial fascia, where movement of the knee, combined with compression between these fascial layers, theoretically results in upward propulsion of lymphatic fluid. Intraoperative detection of large lymphatic vessels and of venous reflux and postoperative lymphedematous volume reduction were compared between 15 patients in whom lymphaticovenular anastomoses with the superior-edge-of-the-knee incision method were undergone and 15 in whom conventional lymphaticovenular anastomoses were undergone. Lymphaticovenular anastomosis at the thigh yielded 30 anastomoses in the superior-edge-of-the-knee incision group and 32 anastomoses in the non-superior-edge-of-the-knee incision group. Large lymphatic vessels were more frequently found in the superior-edge-of-the-knee incision group than in the non-superior-edge-of-the-knee incision group (60.0 percent versus 18.8 percent; p = 0.002). Venous reflux occurred less frequently in the superior-edge-of-the-knee incision group than in the non-superior-edge-of-the-knee incision group (10.0 percent versus 65.6 percent; p < 0.001). Reduction of the lower extremity lymphedema index was significantly greater in the superior-edge-of-the-knee incision group than in the non-superior-edge-of-the-knee incision group (24.427 ± 12.400 versus 0.032 ± 20.535; p < 0.001). The superior-edge-of-the-knee incision method facilitates detection and use of large, high-flow lymphatic vessels in the distal medial thigh, both of which are important for optimum therapeutic effects in patients with lower extremity lymphedema. Therapeutic, III.

An analytically-based method for predicting the noise generated by the interaction between turbulence and a serrated leading edge

NASA Astrophysics Data System (ADS)

Mathews, J. R.; Peake, N.

2018-05-01

This paper considers the interaction of turbulence with a serrated leading edge. We investigate the noise produced by an aerofoil moving through a turbulent perturbation to uniform flow by considering the scattered pressure from the leading edge. We model the aerofoil as an infinite half plane with a leading edge serration, and develop an analytical model using a Green's function based upon the work of Howe. This allows us to consider both deterministic eddies and synthetic turbulence interacting with the leading edge. We show that it is possible to reduce the noise by using a serrated leading edge compared with a straight edge, but the optimal noise-reducing choice of serration is hard to predict due to the complex interaction. We also consider the effect of angle of attack, and find that in general the serrations are less effective at higher angles of attack.

Content modification attacks on consensus seeking multi-agent system with double-integrator dynamics.

PubMed

Dong, Yimeng; Gupta, Nirupam; Chopra, Nikhil

2016-11-01

In this paper, vulnerability of a distributed consensus seeking multi-agent system (MAS) with double-integrator dynamics against edge-bound content modification cyber attacks is studied. In particular, we define a specific edge-bound content modification cyber attack called malignant content modification attack (MCoMA), which results in unbounded growth of an appropriately defined group disagreement vector. Properties of MCoMA are utilized to design detection and mitigation algorithms so as to impart resilience in the considered MAS against MCoMA. Additionally, the proposed detection mechanism is extended to detect the general edge-bound content modification attacks (not just MCoMA). Finally, the efficacies of the proposed results are illustrated through numerical simulations.

Content modification attacks on consensus seeking multi-agent system with double-integrator dynamics

NASA Astrophysics Data System (ADS)

Dong, Yimeng; Gupta, Nirupam; Chopra, Nikhil

2016-11-01

In this paper, vulnerability of a distributed consensus seeking multi-agent system (MAS) with double-integrator dynamics against edge-bound content modification cyber attacks is studied. In particular, we define a specific edge-bound content modification cyber attack called malignant content modification attack (MCoMA), which results in unbounded growth of an appropriately defined group disagreement vector. Properties of MCoMA are utilized to design detection and mitigation algorithms so as to impart resilience in the considered MAS against MCoMA. Additionally, the proposed detection mechanism is extended to detect the general edge-bound content modification attacks (not just MCoMA). Finally, the efficacies of the proposed results are illustrated through numerical simulations.

An approach for traffic prohibition sign detection

NASA Astrophysics Data System (ADS)

Li, Qingquan; Xu, Dihong; Li, Bijun; Zeng, Zhe

2006-10-01

This paper presents an off-line traffic prohibition sign detection approach, whose core is based on combination with the color feature of traffic prohibition signs, shape feature and degree of circularity. Matlab-Image-processing toolbox is used for this purpose. In order to reduce the computational cost, a pre-processing of the image is applied before the core. Then, we employ the obvious redness attribute of prohibition signs to coarsely eliminate the non-redness image in the input data. Again, a edge-detection operator, Canny edge detector, is applied to extract the potential edge. Finally, Degree of circularity is used to verdict the traffic prohibition sign. Experimental results show that our systems offer satisfactory performance.

Linear array optical edge sensor

NASA Technical Reports Server (NTRS)

Bejczy, Antal K. (Inventor); Primus, Howard C. (Inventor)

1987-01-01

A series of independent parallel pairs of light emitting and detecting diodes for a linear pixel array, which is laterally positioned over an edge-like discontinuity in a workpiece to be scanned, is disclosed. These independent pairs of light emitters and detectors sense along intersecting pairs of separate optical axes. A discontinuity, such as an edge in the sensed workpiece, reflects a detectable difference in the amount of light from that discontinuity in comparison to the amount of light that is reflected on either side of the discontinuity. A sequentially sychronized clamping and sampling circuit detects that difference as an electrical signal which is recovered by circuitry that exhibits an improved signal-to-noise capability for the system.

Numerical Approach for Goaf-Side Entry Layout and Yield Pillar Design in Fractured Ground Conditions

NASA Astrophysics Data System (ADS)

Jiang, Lishuai; Zhang, Peipeng; Chen, Lianjun; Hao, Zhen; Sainoki, Atsushi; Mitri, Hani S.; Wang, Qingbiao

2017-11-01

Entry driven along goaf-side (EDG), which is the development of an entry of the next longwall panel along the goaf-side and the isolation of the entry from the goaf with a small-width yield pillar, has been widely employed in China over the past several decades . The width of such a yield pillar has a crucial effect on EDG layout in terms of the ground control, isolation effect and resource recovery rate. Based on a case study, this paper presents an approach for evaluating, designing and optimizing EDG and yield pillar by considering the results from numerical simulations and field practice. To rigorously analyze the ground stability, the numerical study begins with the simulation of goaf-side stress and ground conditions. Four global models with identical conditions, except for the width of the yield pillar, are built, and the effect of pillar width on ground stability is investigated by comparing aspects of stress distribution, failure propagation, and displacement evolution during the entire service life of the entry. Based on simulation results, the isolation effect of the pillar acquired from field practice is also considered. The suggested optimal yield pillar design is validated using a field test in the same mine. Thus, the presented numerical approach provides references and can be utilized for the evaluation, design and optimization of EDG and yield pillars under similar geological and geotechnical circumstances.

A hyperspectral image optimizing method based on sub-pixel MTF analysis

NASA Astrophysics Data System (ADS)

Wang, Yun; Li, Kai; Wang, Jinqiang; Zhu, Yajie

2015-04-01

Hyperspectral imaging is used to collect tens or hundreds of images continuously divided across electromagnetic spectrum so that the details under different wavelengths could be represented. A popular hyperspectral imaging methods uses a tunable optical band-pass filter settled in front of the focal plane to acquire images of different wavelengths. In order to alleviate the influence of chromatic aberration in some segments in a hyperspectral series, in this paper, a hyperspectral optimizing method uses sub-pixel MTF to evaluate image blurring quality was provided. This method acquired the edge feature in the target window by means of the line spread function (LSF) to calculate the reliable position of the edge feature, then the evaluation grid in each line was interpolated by the real pixel value based on its relative position to the optimal edge and the sub-pixel MTF was used to analyze the image in frequency domain, by which MTF calculation dimension was increased. The sub-pixel MTF evaluation was reliable, since no image rotation and pixel value estimation was needed, and no artificial information was introduced. With theoretical analysis, the method proposed in this paper is reliable and efficient when evaluation the common images with edges of small tilt angle in real scene. It also provided a direction for the following hyperspectral image blurring evaluation and the real-time focal plane adjustment in real time in related imaging system.

Sub-surface defects detection of by using active thermography and advanced image edge detection

NASA Astrophysics Data System (ADS)

Tse, Peter W.; Wang, Gaochao

2017-05-01

Active or pulsed thermography is a popular non-destructive testing (NDT) tool for inspecting the integrity and anomaly of industrial equipment. One of the recent research trends in using active thermography is to automate the process in detecting hidden defects. As of today, human effort has still been using to adjust the temperature intensity of the thermo camera in order to visually observe the difference in cooling rates caused by a normal target as compared to that by a sub-surface crack exists inside the target. To avoid the tedious human-visual inspection and minimize human induced error, this paper reports the design of an automatic method that is capable of detecting subsurface defects. The method used the technique of active thermography, edge detection in machine vision and smart algorithm. An infrared thermo-camera was used to capture a series of temporal pictures after slightly heating up the inspected target by flash lamps. Then the Canny edge detector was employed to automatically extract the defect related images from the captured pictures. The captured temporal pictures were preprocessed by a packet of Canny edge detector and then a smart algorithm was used to reconstruct the whole sequences of image signals. During the processes, noise and irrelevant backgrounds exist in the pictures were removed. Consequently, the contrast of the edges of defective areas had been highlighted. The designed automatic method was verified by real pipe specimens that contains sub-surface cracks. After applying such smart method, the edges of cracks can be revealed visually without the need of using manual adjustment on the setting of thermo-camera. With the help of this automatic method, the tedious process in manually adjusting the colour contract and the pixel intensity in order to reveal defects can be avoided.

Detection of latent fingerprints using high-resolution 3D confocal microscopy in non-planar acquisition scenarios

NASA Astrophysics Data System (ADS)

Kirst, Stefan; Vielhauer, Claus

2015-03-01

In digitized forensics the support of investigators in any manner is one of the main goals. Using conservative lifting methods, the detection of traces is done manually. For non-destructive contactless methods, the necessity for detecting traces is obvious for further biometric analysis. High resolutional 3D confocal laser scanning microscopy (CLSM) grants the possibility for a detection by segmentation approach with improved detection results. Optimal scan results with CLSM are achieved on surfaces orthogonal to the sensor, which is not always possible due to environmental circumstances or the surface's shape. This introduces additional noise, outliers and a lack of contrast, making a detection of traces even harder. Prior work showed the possibility of determining angle-independent classification models for the detection of latent fingerprints (LFP). Enhancing this approach, we introduce a larger feature space containing a variety of statistical-, roughness-, color-, edge-directivity-, histogram-, Gabor-, gradient- and Tamura features based on raw data and gray-level co-occurrence matrices (GLCM) using high resolutional data. Our test set consists of eight different surfaces for the detection of LFP in four different acquisition angles with a total of 1920 single scans. For each surface and angles in steps of 10, we capture samples from five donors to introduce variance by a variety of sweat compositions and application influences such as pressure or differences in ridge thickness. By analyzing the present test set with our approach, we intend to determine angle- and substrate-dependent classification models to determine optimal surface specific acquisition setups and also classification models for a general detection purpose for both, angles and substrates. The results on overall models with classification rates up to 75.15% (kappa 0.50) already show a positive tendency regarding the usability of the proposed methods for LFP detection on varying surfaces in non-planar scenarios.

Low-noise heterodyne receiver for electron cyclotron emission imaging and microwave imaging reflectometry

NASA Astrophysics Data System (ADS)

Tobias, B.; Domier, C. W.; Luhmann, N. C.; Luo, C.; Mamidanna, M.; Phan, T.; Pham, A.-V.; Wang, Y.

2016-11-01

The critical component enabling electron cyclotron emission imaging (ECEI) and microwave imaging reflectometry (MIR) to resolve 2D and 3D electron temperature and density perturbations is the heterodyne imaging array that collects and downconverts radiated emission and/or reflected signals (50-150 GHz) to an intermediate frequency (IF) band (e.g. 0.1-18 GHz) that can be transmitted by a shielded coaxial cable for further filtering and detection. New circuitry has been developed for this task, integrating gallium arsenide (GaAs) monolithic microwave integrated circuits (MMICs) mounted on a liquid crystal polymer (LCP) substrate. The improved topology significantly increases electromagnetic shielding from out-of-band interference, leads to 10× improvement in the signal-to-noise ratio, and dramatic cost savings through integration. The current design, optimized for reflectometry and edge radiometry on mid-sized tokamaks, has demonstrated >20 dB conversion gain in upper V-band (60-75 GHz). Implementation of the circuit in a multi-channel electron cyclotron emission imaging (ECEI) array will improve the diagnosis of edge-localized modes and fluctuations of the high-confinement, or H-mode, pedestal.

Low-noise heterodyne receiver for electron cyclotron emission imaging and microwave imaging reflectometry.

PubMed

Tobias, B; Domier, C W; Luhmann, N C; Luo, C; Mamidanna, M; Phan, T; Pham, A-V; Wang, Y

2016-11-01

The critical component enabling electron cyclotron emission imaging (ECEI) and microwave imaging reflectometry (MIR) to resolve 2D and 3D electron temperature and density perturbations is the heterodyne imaging array that collects and downconverts radiated emission and/or reflected signals (50-150 GHz) to an intermediate frequency (IF) band (e.g. 0.1-18 GHz) that can be transmitted by a shielded coaxial cable for further filtering and detection. New circuitry has been developed for this task, integrating gallium arsenide (GaAs) monolithic microwave integrated circuits (MMICs) mounted on a liquid crystal polymer (LCP) substrate. The improved topology significantly increases electromagnetic shielding from out-of-band interference, leads to 10× improvement in the signal-to-noise ratio, and dramatic cost savings through integration. The current design, optimized for reflectometry and edge radiometry on mid-sized tokamaks, has demonstrated >20 dB conversion gain in upper V-band (60-75 GHz). Implementation of the circuit in a multi-channel electron cyclotron emission imaging (ECEI) array will improve the diagnosis of edge-localized modes and fluctuations of the high-confinement, or H-mode, pedestal.

Cascaded systems analysis of noise and detectability in dual-energy cone-beam CT

PubMed Central

Gang, Grace J.; Zbijewski, Wojciech; Webster Stayman, J.; Siewerdsen, Jeffrey H.

2012-01-01

Purpose: Dual-energy computed tomography and dual-energy cone-beam computed tomography (DE-CBCT) are promising modalities for applications ranging from vascular to breast, renal, hepatic, and musculoskeletal imaging. Accordingly, the optimization of imaging techniques for such applications would benefit significantly from a general theoretical description of image quality that properly incorporates factors of acquisition, reconstruction, and tissue decomposition in DE tomography. This work reports a cascaded systems analysis model that includes the Poisson statistics of x rays (quantum noise), detector model (flat-panel detectors), anatomical background, image reconstruction (filtered backprojection), DE decomposition (weighted subtraction), and simple observer models to yield a task-based framework for DE technique optimization. Methods: The theoretical framework extends previous modeling of DE projection radiography and CBCT. Signal and noise transfer characteristics are propagated through physical and mathematical stages of image formation and reconstruction. Dual-energy decomposition was modeled according to weighted subtraction of low- and high-energy images to yield the 3D DE noise-power spectrum (NPS) and noise-equivalent quanta (NEQ), which, in combination with observer models and the imaging task, yields the dual-energy detectability index (d′). Model calculations were validated with NPS and NEQ measurements from an experimental imaging bench simulating the geometry of a dedicated musculoskeletal extremities scanner. Imaging techniques, including kVp pair and dose allocation, were optimized using d′ as an objective function for three example imaging tasks: (1) kidney stone discrimination; (2) iodine vs bone in a uniform, soft-tissue background; and (3) soft tissue tumor detection on power-law anatomical background. Results: Theoretical calculations of DE NPS and NEQ demonstrated good agreement with experimental measurements over a broad range of imaging conditions. Optimization results suggest a lower fraction of total dose imparted by the low-energy acquisition, a finding consistent with previous literature. The selection of optimal kVp pair reveals the combined effect of both quantum noise and contrast in the kidney stone discrimination and soft-tissue tumor detection tasks, whereas the K-edge effect of iodine was the dominant factor in determining kVp pairs in the iodine vs bone task. The soft-tissue tumor task illustrated the benefit of dual-energy imaging in eliminating anatomical background noise and improving detectability beyond that achievable by single-energy scans. Conclusions: This work established a task-based theoretical framework that is predictive of DE image quality. The model can be utilized in optimizing a broad range of parameters in image acquisition, reconstruction, and decomposition, providing a useful tool for maximizing DE-CBCT image quality and reducing dose. PMID:22894440

Doppler lidar wind measurement with the edge technique

NASA Technical Reports Server (NTRS)

Korb, C. Laurence; Gentry, Bruce M.

1992-01-01

The edge technique is a new and powerful method for measuring small frequency shifts. Range resolved lidar measurements of winds can be made with high accuracy and high vertical resolution using the edge technique to measure the Doppler shift of an atmospheric backscattered signal from a pulsed laser. The edge technique can be used at near-infrared or visible wavelengths using well developed solid state lasers and detectors with various edge filters. In the edge technique, the laser frequency is located on the steep slope of the spectral response function of a high resolution optical filter. Due to the steep slope of the edge, very small frequency shifts cause large changes in measured signal. The frequency of the outgoing laser pulse is determined by measuring its location on the edge of the filter. This is accomplished by sending a small portion of the beam to the edge detection setup where the incoming light is split into two channels - an edge filter and an energy monitor channel. The energy monitor signal is used to normalize the edge filter signal for magnitude. The laser return backscattered from the atmosphere is collected by a telescope and directed through the edge detection setup to determine its frequency (location on the edge) in a similar manner for each range element. The Doppler shift, and thus the wind, is determined from a differential measurement of the frequency of the outgoing laser pulse and the frequency of the laser return backscattered from the atmosphere. We have conducted simulations of the performance of an edge lidar system using an injection seeded pulsed Nd:YAG laser at 1.06 microns. The central fringe of a Fabry-Perot etalon is used as a high resolution edge filter to measure the shift of the aerosol return.

Active edge maps for medical image registration

NASA Astrophysics Data System (ADS)

Kerwin, William; Yuan, Chun

2001-07-01

Applying edge detection prior to performing image registration yields several advantages over raw intensity- based registration. Advantages include the ability to register multicontrast or multimodality images, immunity to intensity variations, and the potential for computationally efficient algorithms. In this work, a common framework for edge-based image registration is formulated as an adaptation of snakes used in boundary detection. Called active edge maps, the new formulation finds a one-to-one transformation T(x) that maps points in a source image to corresponding locations in a target image using an energy minimization approach. The energy consists of an image component that is small when edge features are well matched in the two images, and an internal term that restricts T(x) to allowable configurations. The active edge map formulation is illustrated here with a specific example developed for affine registration of carotid artery magnetic resonance images. In this example, edges are identified using a magnitude of gradient operator, image energy is determined using a Gaussian weighted distance function, and the internal energy includes separate, adjustable components that control volume preservation and rigidity.

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.

Image-Data Compression Using Edge-Optimizing Algorithm for WFA Inference.

ERIC Educational Resources Information Center

Culik, Karel II; Kari, Jarkko

1994-01-01

Presents an inference algorithm that produces a weighted finite automata (WFA), in particular, the grayness functions of graytone images. Image-data compression results based on the new inference algorithm produces a WFA with a relatively small number of edges. Image-data compression results alone and in combination with wavelets are discussed.…

Miniaturization and Optimization of Nanoscale Resonant Oscillators

DTIC Science & Technology

2013-09-07

carried out over a range of core sizes. Using a double 4-f imaging system in conjunction with a pump filter ( Semrock RazorEdge long wavelength pass...Using a double 4-f imaging system in conjunction with a pump filter ( Semrock RazorEdge long wavelength pass), the samples are imaged onto either an

Online Mapping and Perception Algorithms for Multi-robot Teams Operating in Urban Environments

DTIC Science & Technology

2015-01-01

each method on a 2.53 GHz Intel i5 laptop. All our algorithms are hand-optimized, implemented in Java and single threaded. To determine which algorithm...approach would be to label all the pixels in the image with an x, y, z point. However, the angular resolution of the camera is finer than that of the...edge criterion. That is, each edge is either present or absent. In [42], edge existence is further screened by a fixed threshold for angular

Edge detection based on adaptive threshold b-spline wavelet for optical sub-aperture measuring

NASA Astrophysics Data System (ADS)

Zhang, Shiqi; Hui, Mei; Liu, Ming; Zhao, Zhu; Dong, Liquan; Liu, Xiaohua; Zhao, Yuejin

2015-08-01

In the research of optical synthetic aperture imaging system, phase congruency is the main problem and it is necessary to detect sub-aperture phase. The edge of the sub-aperture system is more complex than that in the traditional optical imaging system. And with the existence of steep slope for large-aperture optical component, interference fringe may be quite dense when interference imaging. Deep phase gradient may cause a loss of phase information. Therefore, it's urgent to search for an efficient edge detection method. Wavelet analysis as a powerful tool is widely used in the fields of image processing. Based on its properties of multi-scale transform, edge region is detected with high precision in small scale. Longing with the increase of scale, noise is reduced in contrary. So it has a certain suppression effect on noise. Otherwise, adaptive threshold method which sets different thresholds in various regions can detect edge points from noise. Firstly, fringe pattern is obtained and cubic b-spline wavelet is adopted as the smoothing function. After the multi-scale wavelet decomposition of the whole image, we figure out the local modulus maxima in gradient directions. However, it also contains noise, and thus adaptive threshold method is used to select the modulus maxima. The point which greater than threshold value is boundary point. Finally, we use corrosion and expansion deal with the resulting image to get the consecutive boundary of image.

Graph Design via Convex Optimization: Online and Distributed Perspectives

NASA Astrophysics Data System (ADS)

Meng, De

Network and graph have long been natural abstraction of relations in a variety of applications, e.g. transportation, power system, social network, communication, electrical circuit, etc. As a large number of computation and optimization problems are naturally defined on graphs, graph structures not only enable important properties of these problems, but also leads to highly efficient distributed and online algorithms. For example, graph separability enables the parallelism for computation and operation as well as limits the size of local problems. More interestingly, graphs can be defined and constructed in order to take best advantage of those problem properties. This dissertation focuses on graph structure and design in newly proposed optimization problems, which establish a bridge between graph properties and optimization problem properties. We first study a new optimization problem called Geodesic Distance Maximization Problem (GDMP). Given a graph with fixed edge weights, finding the shortest path, also known as the geodesic, between two nodes is a well-studied network flow problem. We introduce the Geodesic Distance Maximization Problem (GDMP): the problem of finding the edge weights that maximize the length of the geodesic subject to convex constraints on the weights. We show that GDMP is a convex optimization problem for a wide class of flow costs, and provide a physical interpretation using the dual. We present applications of the GDMP in various fields, including optical lens design, network interdiction, and resource allocation in the control of forest fires. We develop an Alternating Direction Method of Multipliers (ADMM) by exploiting specific problem structures to solve large-scale GDMP, and demonstrate its effectiveness in numerical examples. We then turn our attention to distributed optimization on graph with only local communication. Distributed optimization arises in a variety of applications, e.g. distributed tracking and localization, estimation problems in sensor networks, multi-agent coordination. Distributed optimization aims to optimize a global objective function formed by summation of coupled local functions over a graph via only local communication and computation. We developed a weighted proximal ADMM for distributed optimization using graph structure. This fully distributed, single-loop algorithm allows simultaneous updates and can be viewed as a generalization of existing algorithms. More importantly, we achieve faster convergence by jointly designing graph weights and algorithm parameters. Finally, we propose a new problem on networks called Online Network Formation Problem: starting with a base graph and a set of candidate edges, at each round of the game, player one first chooses a candidate edge and reveals it to player two, then player two decides whether to accept it; player two can only accept limited number of edges and make online decisions with the goal to achieve the best properties of the synthesized network. The network properties considered include the number of spanning trees, algebraic connectivity and total effective resistance. These network formation games arise in a variety of cooperative multiagent systems. We propose a primal-dual algorithm framework for the general online network formation game, and analyze the algorithm performance by the competitive ratio and regret.

Spin-transfer-torque efficiency enhanced by edge-damage of perpendicular magnetic random access memories

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

Song, Kyungmi; Lee, Kyung-Jin, E-mail: kj-lee@korea.ac.kr; Department of Materials Science and Engineering, Korea University, Seoul 136-713

2015-08-07

We numerically investigate the effect of magnetic and electrical damages at the edge of a perpendicular magnetic random access memory (MRAM) cell on the spin-transfer-torque (STT) efficiency that is defined by the ratio of thermal stability factor to switching current. We find that the switching mode of an edge-damaged cell is different from that of an undamaged cell, which results in a sizable reduction in the switching current. Together with a marginal reduction of the thermal stability factor of an edge-damaged cell, this feature makes the STT efficiency large. Our results suggest that a precise edge control is viable formore » the optimization of STT-MRAM.« less

Real time optical edge enhancement using a Hughes liquid crystal light valve

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1989-01-01

The discovery of an edge enhancement effect in using a Hughes CdS liquid crystal light valve (LCLV) is reported. An edge-enhanced version of the input writing image can be directly obtained by operating the LCLV at a lower bias frequency and bias voltage. Experimental conditions in which this edge enhancement effect can be optimized are described. Experimental results show that the SNR of the readout image using this technique is superior to that obtained using high-pass filtering. The repeatability of this effect is confirmed by obtaining an edge enhancement result using two different Hughes LCLVs. The applicability of this effect to improve discrimination capability in optical pattern recognition is addressed. The results show that the Hughes LCLV can be used in both continuous tone and edge-enhancing modes by simply adjusting its bias conditions.

Optimizing the 3D-reconstruction technique for serial block-face scanning electron microscopy.

PubMed

Wernitznig, Stefan; Sele, Mariella; Urschler, Martin; Zankel, Armin; Pölt, Peter; Rind, F Claire; Leitinger, Gerd

2016-05-01

Elucidating the anatomy of neuronal circuits and localizing the synaptic connections between neurons, can give us important insights in how the neuronal circuits work. We are using serial block-face scanning electron microscopy (SBEM) to investigate the anatomy of a collision detection circuit including the Lobula Giant Movement Detector (LGMD) neuron in the locust, Locusta migratoria. For this, thousands of serial electron micrographs are produced that allow us to trace the neuronal branching pattern. The reconstruction of neurons was previously done manually by drawing cell outlines of each cell in each image separately. This approach was very time consuming and troublesome. To make the process more efficient a new interactive software was developed. It uses the contrast between the neuron under investigation and its surrounding for semi-automatic segmentation. For segmentation the user sets starting regions manually and the algorithm automatically selects a volume within the neuron until the edges corresponding to the neuronal outline are reached. Internally the algorithm optimizes a 3D active contour segmentation model formulated as a cost function taking the SEM image edges into account. This reduced the reconstruction time, while staying close to the manual reference segmentation result. Our algorithm is easy to use for a fast segmentation process, unlike previous methods it does not require image training nor an extended computing capacity. Our semi-automatic segmentation algorithm led to a dramatic reduction in processing time for the 3D-reconstruction of identified neurons. Copyright © 2016 Elsevier B.V. All rights reserved.

A PKC-MARCKS-PI3K regulatory module links Ca2+ and PIP3 signals at the leading edge of polarized macrophages.

PubMed

Ziemba, Brian P; Falke, Joseph J

2018-01-01

The leukocyte chemosensory pathway detects attractant gradients and directs cell migration to sites of inflammation, infection, tissue damage, and carcinogenesis. Previous studies have revealed that local Ca2+ and PIP3 signals at the leading edge of polarized leukocytes play central roles in positive feedback loop essential to cell polarization and chemotaxis. These prior studies showed that stimulation of the leading edge Ca2+ signal can strongly activate PI3K, thereby triggering a larger PIP3 signal, but did not elucidate the mechanistic link between Ca2+ and PIP3 signaling. A hypothesis explaining this link emerged, postulating that Ca2+-activated PKC displaces the MARCKS protein from plasma membrane PIP2, thereby releasing sequestered PIP2 to serve as the target and substrate lipid of PI3K in PIP3 production. In vitro single molecule studies of the reconstituted pathway on lipid bilayers demonstrated the feasibility of this PKC-MARCKS-PI3K regulatory module linking Ca2+ and PIP3 signals in the reconstituted system. The present study tests the model predictions in live macrophages by quantifying the effects of: (a) two pathway activators-PDGF and ATP that stimulate chemoreceptors and Ca2+ influx, respectively; and (b) three pathway inhibitors-wortmannin, EGTA, and Go6976 that inhibit PI3K, Ca2+ influx, and PKC, respectively; on (c) four leading edge activity sensors-AKT-PH-mRFP, CKAR, MARCKSp-mRFP, and leading edge area that report on PIP3 density, PKC activity, MARCKS membrane binding, and leading edge expansion/contraction, respectively. The results provide additional evidence that PKC and PI3K are both essential elements of the leading edge positive feedback loop, and strongly support the existence of a PKC-MARCKS-PI3K regulatory module linking the leading edge Ca2+ and PIP3 signals. As predicted, activators stimulate leading edge PKC activity, displacement of MARCKS from the leading edge membrane and increased leading edge PIP3 levels, while inhibitors trigger the opposite effects. Comparison of the findings for the ameboid chemotaxis of leukocytes with recently published findings for the mesenchymal chemotaxis of fibroblasts suggests that some features of the emerging leukocyte leading edge core pathway (PLC-DAG-Ca2+-PKC-MARCKS-PIP2-PI3K-PIP3) may well be shared by all chemotaxing eukaryotic cells, while other elements of the leukocyte pathway may be specialized features of these highly optimized, professional gradient-seeking cells. More broadly, the findings suggest a molecular mechanism for the strong links between phospho-MARCKS and many human cancers.

A PKC-MARCKS-PI3K regulatory module links Ca2+ and PIP3 signals at the leading edge of polarized macrophages

PubMed Central

Ziemba, Brian P.

2018-01-01

The leukocyte chemosensory pathway detects attractant gradients and directs cell migration to sites of inflammation, infection, tissue damage, and carcinogenesis. Previous studies have revealed that local Ca2+ and PIP3 signals at the leading edge of polarized leukocytes play central roles in positive feedback loop essential to cell polarization and chemotaxis. These prior studies showed that stimulation of the leading edge Ca2+ signal can strongly activate PI3K, thereby triggering a larger PIP3 signal, but did not elucidate the mechanistic link between Ca2+ and PIP3 signaling. A hypothesis explaining this link emerged, postulating that Ca2+-activated PKC displaces the MARCKS protein from plasma membrane PIP2, thereby releasing sequestered PIP2 to serve as the target and substrate lipid of PI3K in PIP3 production. In vitro single molecule studies of the reconstituted pathway on lipid bilayers demonstrated the feasibility of this PKC-MARCKS-PI3K regulatory module linking Ca2+ and PIP3 signals in the reconstituted system. The present study tests the model predictions in live macrophages by quantifying the effects of: (a) two pathway activators—PDGF and ATP that stimulate chemoreceptors and Ca2+ influx, respectively; and (b) three pathway inhibitors—wortmannin, EGTA, and Go6976 that inhibit PI3K, Ca2+ influx, and PKC, respectively; on (c) four leading edge activity sensors—AKT-PH-mRFP, CKAR, MARCKSp-mRFP, and leading edge area that report on PIP3 density, PKC activity, MARCKS membrane binding, and leading edge expansion/contraction, respectively. The results provide additional evidence that PKC and PI3K are both essential elements of the leading edge positive feedback loop, and strongly support the existence of a PKC-MARCKS-PI3K regulatory module linking the leading edge Ca2+ and PIP3 signals. As predicted, activators stimulate leading edge PKC activity, displacement of MARCKS from the leading edge membrane and increased leading edge PIP3 levels, while inhibitors trigger the opposite effects. Comparison of the findings for the ameboid chemotaxis of leukocytes with recently published findings for the mesenchymal chemotaxis of fibroblasts suggests that some features of the emerging leukocyte leading edge core pathway (PLC-DAG-Ca2+-PKC-MARCKS-PIP2-PI3K-PIP3) may well be shared by all chemotaxing eukaryotic cells, while other elements of the leukocyte pathway may be specialized features of these highly optimized, professional gradient-seeking cells. More broadly, the findings suggest a molecular mechanism for the strong links between phospho-MARCKS and many human cancers. PMID:29715315

Estimated Benefits of Variable-Geometry Wing Camber Control for Transport Aircraft

NASA Technical Reports Server (NTRS)

Bolonkin, Alexander; Gilyard, Glenn B.

1999-01-01

Analytical benefits of variable-camber capability on subsonic transport aircraft are explored. Using aerodynamic performance models, including drag as a function of deflection angle for control surfaces of interest, optimal performance benefits of variable camber are calculated. Results demonstrate that if all wing trailing-edge surfaces are available for optimization, drag can be significantly reduced at most points within the flight envelope. The optimization approach developed and illustrated for flight uses variable camber for optimization of aerodynamic efficiency (maximizing the lift-to-drag ratio). Most transport aircraft have significant latent capability in this area. Wing camber control that can affect performance optimization for transport aircraft includes symmetric use of ailerons and flaps. In this paper, drag characteristics for aileron and flap deflections are computed based on analytical and wind-tunnel data. All calculations based on predictions for the subject aircraft and the optimal surface deflection are obtained by simple interpolation for given conditions. An algorithm is also presented for computation of optimal surface deflection for given conditions. Benefits of variable camber for a transport configuration using a simple trailing-edge control surface system can approach more than 10 percent, especially for nonstandard flight conditions. In the cruise regime, the benefit is 1-3 percent.

WINGDES2 - WING DESIGN AND ANALYSIS CODE

NASA Technical Reports Server (NTRS)

Carlson, H. W.

1994-01-01

This program provides a wing design algorithm based on modified linear theory which takes into account the effects of attainable leading-edge thrust. A primary objective of the WINGDES2 approach is the generation of a camber surface as mild as possible to produce drag levels comparable to those attainable with full theoretical leading-edge thrust. WINGDES2 provides both an analysis and a design capability and is applicable to both subsonic and supersonic flow. The optimization can be carried out for designated wing portions such as leading and trailing edge areas for the design of mission-adaptive surfaces, or for an entire planform such as a supersonic transport wing. This program replaces an earlier wing design code, LAR-13315, designated WINGDES. WINGDES2 incorporates modifications to improve numerical accuracy and provides additional capabilities. A means of accounting for the presence of interference pressure fields from airplane components other than the wing and a direct process for selection of flap surfaces to approach the performance levels of the optimized wing surfaces are included. An increased storage capacity allows better numerical representation of those configurations that have small chord leading-edge or trailing-edge design areas. WINGDES2 determines an optimum combination of a series of candidate surfaces rather than the more commonly used candidate loadings. The objective of the design is the recovery of unrealized theoretical leading-edge thrust of the input flat surface by shaping of the design surface to create a distributed thrust and thus minimize drag. The input consists of airfoil section thickness data, leading and trailing edge planform geometry, and operational parameters such as Mach number, Reynolds number, and design lift coefficient. Output includes optimized camber surface ordinates, pressure coefficient distributions, and theoretical aerodynamic characteristics. WINGDES2 is written in FORTRAN V for batch execution and has been implemented on a CDC CYBER computer operating under NOS 2.7.1 with a central memory requirement of approximately 344K (octal) of 60 bit words. This program was developed in 1984, and last updated in 1990. CDC and CYBER are trademarks of Control Data Corporation.

Effect of leading-edge load constraints on the design and performance of supersonic wings

NASA Technical Reports Server (NTRS)

Darden, C. M.

1985-01-01

A theoretical and experimental investigation was conducted to assess the effect of leading-edge load constraints on supersonic wing design and performance. In the effort to delay flow separation and the formation of leading-edge vortices, two constrained, linear-theory optimization approaches were used to limit the loadings on the leading edge of a variable-sweep planform design. Experimental force and moment tests were made on two constrained camber wings, a flat uncambered wing, and an optimum design with no constraints. Results indicate that vortex strength and separation regions were mildest on the severely and moderately constrained wings.

Percutaneous Tricuspid Valve Regurgitation Repair With the MitraClip Device Using an Edge-to-Edge Bicuspidization Technique.

PubMed

Gafoor, Sameer; Petrescu, O Madalina; Lehr, Eric J; Puls, Charles; Zhang, Ming; Petersen, John L; Olsen, John V; Penev, Irina; Agrawal, Mayank; Sharma, Rahul; Barnhart, Glenn

2017-03-01

Patients who present with both severe mitral and tricuspid regurgitation who are symptomatic despite optimal medical therapy and at prohibitive risk for surgery pose a significant therapeutic challenge. The MitraClip device (Abbott Vascular) is approved for percutaneous mitral valve repair in high-risk and non-operative patients, and has also been used for tricuspid valve repair. Imaging support for percutaneous edge-to-edge tricuspid valve repair has not been reported and is a vital part of the procedure. Here, we present a periprocedural imaging strategy for percutaneous tricuspid valve repair with the MitraClip device using a bicuspidization technique.

Electrically tunable spin filtering for electron tunneling between spin-resolved quantum Hall edge states and a quantum dot

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

Kiyama, H., E-mail: kiyama@meso.t.u-tokyo.ac.jp; Fujita, T.; Teraoka, S.

2014-06-30

Spin filtering with electrically tunable efficiency is achieved for electron tunneling between a quantum dot and spin-resolved quantum Hall edge states by locally gating the two-dimensional electron gas (2DEG) leads near the tunnel junction to the dot. The local gating can change the potential gradient in the 2DEG and consequently the edge state separation. We use this technique to electrically control the ratio of the dot–edge state tunnel coupling between opposite spins and finally increase spin filtering efficiency up to 91%, the highest ever reported, by optimizing the local gating.

Optimization studies of the ITER low field side reflectometer.

PubMed

Diem, S J; Wilgen, J B; Bigelow, T S; Hanson, G R; Harvey, R W; Smirnov, A P

2010-10-01

Microwave reflectometry will be used on ITER to measure the electron density profile, density fluctuations due to MHD/turbulence, edge localized mode (ELM) density transients, and as an L-H transition monitor. The ITER low field side reflectometer system will measure both core and edge quantities using multiple antenna arrays spanning frequency ranges of 15-155 GHz for the O-mode system and 55-220 GHz for the X-mode system. Optimization studies using the GENRAY ray-tracing code have been done for edge and core measurements. The reflectometer launchers will utilize the HE11 mode launched from circular corrugated waveguide. The launched beams are assumed to be Gaussian with a beam waist diameter of 0.643 times the waveguide diameter. Optimum launcher size and placement are investigated by computing the antenna coupling between launchers, assuming the launched and received beams have a Gaussian beam pattern.

Project HyBuJET

NASA Technical Reports Server (NTRS)

Ramsay, Tom; Collet, Bill; Igar, Karyn; Kendall, Dewayne; Miklosovic, Dave; Reuss, Robyn; Ringer, Mark; Scheidt, Tony

1990-01-01

A conceptual Hypersonic Business Jet (HyBuJet) was examined. The main areas of concentration include: aerodynamics, propulsion, stability and control, mission profile, and atmospheric heating. In order to optimize for cruise conditions, a waverider configuration was chosen for the high lift drag ratio and low wave drag. The leading edge and lower surface of a waverider was mapped out from a known flow field and optimized for cruising at Mach 6 and at high altitudes. The shockwave generated by a waverider remains attached along the entire leading edge, allowing for a larger compression along the lower surface. Three turbofan ramjets were chosen as the propulsion of the aircraft due to the combination of good subsonic performance along with high speed propulsive capabilities. A combination of liquid silicon convective cooling for the leading edges with a highly radiative outer skin material was chosen to reduce the atmospheric heating to acceptable level.

Generation algorithm of craniofacial structure contour in cephalometric images

NASA Astrophysics Data System (ADS)

Mondal, Tanmoy; Jain, Ashish; Sardana, H. K.

2010-02-01

Anatomical structure tracing on cephalograms is a significant way to obtain cephalometric analysis. Computerized cephalometric analysis involves both manual and automatic approaches. The manual approach is limited in accuracy and repeatability. In this paper we have attempted to develop and test a novel method for automatic localization of craniofacial structure based on the detected edges on the region of interest. According to the grey scale feature at the different region of the cephalometric images, an algorithm for obtaining tissue contour is put forward. Using edge detection with specific threshold an improved bidirectional contour tracing approach is proposed by an interactive selection of the starting edge pixels, the tracking process searches repetitively for an edge pixel at the neighborhood of previously searched edge pixel to segment images, and then craniofacial structures are obtained. The effectiveness of the algorithm is demonstrated by the preliminary experimental results obtained with the proposed method.

Sampled-data consensus in switching networks of integrators based on edge events

NASA Astrophysics Data System (ADS)

Xiao, Feng; Meng, Xiangyu; Chen, Tongwen

2015-02-01

This paper investigates the event-driven sampled-data consensus in switching networks of multiple integrators and studies both the bidirectional interaction and leader-following passive reaction topologies in a unified framework. In these topologies, each information link is modelled by an edge of the information graph and assigned a sequence of edge events, which activate the mutual data sampling and controller updates of the two linked agents. Two kinds of edge-event-detecting rules are proposed for the general asynchronous data-sampling case and the synchronous periodic event-detecting case. They are implemented in a distributed fashion, and their effectiveness in reducing communication costs and solving consensus problems under a jointly connected topology condition is shown by both theoretical analysis and simulation examples.

Range image segmentation using Zernike moment-based generalized edge detector

NASA Technical Reports Server (NTRS)

Ghosal, S.; Mehrotra, R.

1992-01-01

The authors proposed a novel Zernike moment-based generalized step edge detection method which can be used for segmenting range and intensity images. A generalized step edge detector is developed to identify different kinds of edges in range images. These edge maps are thinned and linked to provide final segmentation. A generalized edge is modeled in terms of five parameters: orientation, two slopes, one step jump at the location of the edge, and the background gray level. Two complex and two real Zernike moment-based masks are required to determine all these parameters of the edge model. Theoretical noise analysis is performed to show that these operators are quite noise tolerant. Experimental results are included to demonstrate edge-based segmentation technique.

Real-time edge tracking using a tactile sensor

NASA Technical Reports Server (NTRS)

Berger, Alan D.; Volpe, Richard; Khosla, Pradeep K.

1989-01-01

Object recognition through the use of input from multiple sensors is an important aspect of an autonomous manipulation system. In tactile object recognition, it is necessary to determine the location and orientation of object edges and surfaces. A controller is proposed that utilizes a tactile sensor in the feedback loop of a manipulator to track along edges. In the control system, the data from the tactile sensor is first processed to find edges. The parameters of these edges are then used to generate a control signal to a hybrid controller. Theory is presented for tactile edge detection and an edge tracking controller. In addition, experimental verification of the edge tracking controller is presented.

Optimization of edge state velocity in the integer quantum Hall regime

NASA Astrophysics Data System (ADS)

Sahasrabudhe, H.; Novakovic, B.; Nakamura, J.; Fallahi, S.; Povolotskyi, M.; Klimeck, G.; Rahman, R.; Manfra, M. J.

2018-02-01

Observation of interference in the quantum Hall regime may be hampered by a small edge state velocity due to finite phase coherence time. Therefore designing two quantum point contact (QPCs) interferometers having a high edge state velocity is desirable. Here we present a new simulation method for designing heterostructures with high edge state velocity by realistically modeling edge states near QPCs in the integer quantum Hall effect (IQHE) regime. Using this simulation method, we also predict the filling factor at the center of QPCs and their conductance at different gate voltages. The 3D Schrödinger equation is split into 1D and 2D parts. Quasi-1D Schrödinger and Poisson equations are solved self-consistently in the IQHE regime to obtain the potential profile, and quantum transport is used to solve for the edge state wave functions. The velocity of edge states is found to be /B , where is the expectation value of the electric field for the edge state. Anisotropically etched trench gated heterostructures with double-sided delta doping have the highest edge state velocity among the structures considered.

78 FR 52419 - Airworthiness Directives; The Boeing Company Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-23

... trailing edge flap area that qualify as structural significant items (SSIs). This AD requires revising the... detect and correct fatigue cracking of the wing trailing edge structure, which could result in... within the wing trailing edge flap area that qualify as structural significant items (SSI). We are...

A Program to Improve the Triangulated Surface Mesh Quality Along Aircraft Component Intersections

NASA Technical Reports Server (NTRS)

Cliff, Susan E.

2005-01-01

A computer program has been developed for improving the quality of unstructured triangulated surface meshes in the vicinity of component intersections. The method relies solely on point removal and edge swapping for improving the triangulations. It can be applied to any lifting surface component such as a wing, canard or horizontal tail component intersected with a fuselage, or it can be applied to a pylon that is intersected with a wing, fuselage or nacelle. The lifting surfaces or pylon are assumed to be aligned in the axial direction with closed trailing edges. The method currently maintains salient edges only at leading and trailing edges of the wing or pylon component. This method should work well for any shape of fuselage that is free of salient edges at the intersection. The method has been successfully demonstrated on a total of 125 different test cases that include both blunt and sharp wing leading edges. The code is targeted for use in the automated environment of numerical optimization where geometric perturbations to individual components can be critical to the aerodynamic performance of a vehicle. Histograms of triangle aspect ratios are reported to assess the quality of the triangles attached to the intersection curves before and after application of the program. Large improvements to the quality of the triangulations were obtained for the 125 test cases; the quality was sufficient for use with an automated tetrahedral mesh generation program that is used as part of an aerodynamic shape optimization method.

A graph signal filtering-based approach for detection of different edge types on airborne lidar data

NASA Astrophysics Data System (ADS)

Bayram, Eda; Vural, Elif; Alatan, Aydin

2017-10-01

Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the detection of the boundaries of an object or scene captured by LiDAR. Our approach is motivated by edge detection techniques in vision research and it is established on graph signal filtering which is an exciting and promising field of signal processing for irregular data types. Due to the convenient applicability of graph signal processing tools on unstructured point clouds, we achieve the detection of the edge points directly on 3D data by using a graph representation that is constructed exclusively to answer the requirements of the application. Moreover, considering the elevation data as the (graph) signal, we leverage aerial characteristic of the airborne LiDAR data. The proposed method can be employed both for discovering the jump edges on a segmentation problem and for exploring the crease edges on a LiDAR object on a reconstruction/modeling problem, by only adjusting the filter characteristics.

Image processing techniques for noise removal, enhancement and segmentation of cartilage OCT images

NASA Astrophysics Data System (ADS)

Rogowska, Jadwiga; Brezinski, Mark E.

2002-02-01

Osteoarthritis, whose hallmark is the progressive loss of joint cartilage, is a major cause of morbidity worldwide. Recently, optical coherence tomography (OCT) has demonstrated considerable promise for the assessment of articular cartilage. Among the most important parameters to be assessed is cartilage width. However, detection of the bone cartilage interface is critical for the assessment of cartilage width. At present, the quantitative evaluations of cartilage thickness are being done using manual tracing of cartilage-bone borders. Since data is being obtained near video rate with OCT, automated identification of the bone-cartilage interface is critical. In order to automate the process of boundary detection on OCT images, there is a need for developing new image processing techniques. In this paper we describe the image processing techniques for speckle removal, image enhancement and segmentation of cartilage OCT images. In particular, this paper focuses on rabbit cartilage since this is an important animal model for testing both chondroprotective agents and cartilage repair techniques. In this study, a variety of techniques were examined. Ultimately, by combining an adaptive filtering technique with edge detection (vertical gradient, Sobel edge detection), cartilage edges can be detected. The procedure requires several steps and can be automated. Once the cartilage edges are outlined, the cartilage thickness can be measured.

Optimization of Blended Wing Body Composite Panels Using Both NASTRAN and Genetic Algorithm

NASA Technical Reports Server (NTRS)

Lovejoy, Andrew E.

2006-01-01

The blended wing body (BWB) is a concept that has been investigated for improving the performance of transport aircraft. A trade study was conducted by evaluating four regions from a BWB design characterized by three fuselage bays and a 400,000 lb. gross take-off weight (GTW). This report describes the structural optimization of these regions via computational analysis and compares them to the baseline designs of the same construction. The identified regions were simplified for use in the optimization. The regions were represented by flat panels having appropriate classical boundary conditions and uniform force resultants along the panel edges. Panel-edge tractions and internal pressure values applied during the study were those determined by nonlinear NASTRAN analyses. Only one load case was considered in the optimization analysis for each panel region. Optimization was accomplished using both NASTRAN solution 200 and Genetic Algorithm (GA), with constraints imposed on stress, buckling, and minimum thicknesses. The NASTRAN optimization analyses often resulted in infeasible solutions due to violation of the constraints, whereas the GA enforced satisfaction of the constraints and, therefore, always ensured a feasible solution. However, both optimization methods encountered difficulties when the number of design variables was increased. In general, the optimized panels weighed less than the comparable baseline panels.

Localization of tumors in various organs, using edge detection algorithms

NASA Astrophysics Data System (ADS)

López Vélez, Felipe

2015-09-01

The edge of an image is a set of points organized in a curved line, where in each of these points the brightness of the image changes abruptly, or has discontinuities, in order to find these edges there will be five different mathematical methods to be used and later on compared with its peers, this is with the aim of finding which of the methods is the one that can find the edges of any given image. In this paper these five methods will be used for medical purposes in order to find which one is capable of finding the edges of a scanned image more accurately than the others. The problem consists in analyzing the following two biomedicals images. One of them represents a brain tumor and the other one a liver tumor. These images will be analyzed with the help of the five methods described and the results will be compared in order to determine the best method to be used. It was decided to use different algorithms of edge detection in order to obtain the results shown below; Bessel algorithm, Morse algorithm, Hermite algorithm, Weibull algorithm and Sobel algorithm. After analyzing the appliance of each of the methods to both images it's impossible to determine the most accurate method for tumor detection due to the fact that in each case the best method changed, i.e., for the brain tumor image it can be noticed that the Morse method was the best at finding the edges of the image but for the liver tumor image it was the Hermite method. Making further observations it is found that Hermite and Morse have for these two cases the lowest standard deviations, concluding that these two are the most accurate method to find the edges in analysis of biomedical images.

Optimization of transition edge sensor arrays for cosmic microwave background observations with the south pole telescope

DOE PAGES

Ding, Junjia; Ade, P. A. R.; Anderson, A. J.; ...

2016-12-15

In this study, we describe the optimization of transition-edge-sensor (TES) detector arrays for the thirdgeneration camera for the South PoleTelescope.The camera,which contains ~16 000 detectors, will make high-angular-resolution maps of the temperature and polarization of the cosmic microwave background. Our key results are scatter in the transition temperature of Ti/Au TESs is reduced by fabricating the TESs on a thin Ti(5 nm)/Au(5 nm) buffer layer and the thermal conductivity of the legs that support our detector islands is dominated by the SiOx dielectric in the microstrip transmission lines that run along

Optimal placement of trailing-edge flaps for helicopter vibration reduction using response surface methods

NASA Astrophysics Data System (ADS)

Viswamurthy, S. R.; Ganguli, Ranjan

2007-03-01

This study aims to determine optimal locations of dual trailing-edge flaps to achieve minimum hub vibration levels in a helicopter, while incurring low penalty in terms of required trailing-edge flap control power. An aeroelastic analysis based on finite elements in space and time is used in conjunction with an optimal control algorithm to determine the flap time history for vibration minimization. The reduced hub vibration levels and required flap control power (due to flap motion) are the two objectives considered in this study and the flap locations along the blade are the design variables. It is found that second order polynomial response surfaces based on the central composite design of the theory of design of experiments describe both objectives adequately. Numerical studies for a four-bladed hingeless rotor show that both objectives are more sensitive to outboard flap location compared to the inboard flap location by an order of magnitude. Optimization results show a disjoint Pareto surface between the two objectives. Two interesting design points are obtained. The first design gives 77 percent vibration reduction from baseline conditions (no flap motion) with a 7 percent increase in flap power compared to the initial design. The second design yields 70 percent reduction in hub vibration with a 27 percent reduction in flap power from the initial design.

Enhanced Component Performance Study: Emergency Diesel Generators 1998–2014

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

Schroeder, John Alton

2015-11-01

This report presents an enhanced performance evaluation of emergency diesel generators (EDGs) at U.S. commercial nuclear power plants. This report evaluates component performance over time using (1) Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES) data from 1998 through 2014 and (2) maintenance unavailability (UA) performance data from Mitigating Systems Performance Index (MSPI) Basis Document data from 2002 through 2014. The objective is to show estimates of current failure probabilities and rates related to EDGs, trend these data on an annual basis, determine if the current data are consistent with the probability distributions currently recommended for use inmore » NRC probabilistic risk assessments, show how the reliability data differ for different EDG manufacturers and for EDGs with different ratings; and summarize the subcomponents, causes, detection methods, and recovery associated with each EDG failure mode. Engineering analyses were performed with respect to time period and failure mode without regard to the actual number of EDGs at each plant. The factors analyzed are: sub-component, failure cause, detection method, recovery, manufacturer, and EDG rating. Six trends with varying degrees of statistical significance were identified in the data.« less

Optimized optical devices for edge-coupling-enabled silicon photonics platform

NASA Astrophysics Data System (ADS)

Png, Ching Eng; Ang, Thomas Y. L.; Ong, Jun Rong; Lim, Soon Thor; Sahin, Ezgi; Chen, G. F. R.; Tan, D. T. H.; Guo, Tina X.; Wang, Hong

2018-02-01

We present a library of high-performance passive and active silicon photonic devices at the C-band that is specifically designed and optimized for edge-coupling-enabled silicon photonics platform. These devices meet the broadband (100 nm), low-loss (< 2dB per device), high speed (>= 25 Gb/s), and polarization diversity requirements (TE and TM polarization extinction ratio <= 25 dB) for optical communication applications. Ultra-low loss edge couplers, broadband directional couplers, high-extinction ratio polarization beam splitters (PBSs), and high-speed modulators are some of the devices within our library. In particular, we have designed and fabricated inverse taper fiber-to-waveguide edge couplers of tip widths ranging from 120 nm to 200 nm, and we obtained a low coupling loss of 1.80+/-0.28 dB for 160 nm tip width. To achieve polarization diversity operation for inverse tapers, we have experimentally realized different designs of polarization beam splitters (PBS). Our optimized PBS has a measured extinction ratio of <= 25 dB for both the quasiTE modes, and quasi-TM modes. Additionally, a broadband (100 nm) directional coupler with a 50/50 power splitting ratio was experimentally realized on a small footprint of 20×3 μm2 . Last but not least, high-speed silicon modulators with a range of carrier doping concentrations and offset of the PN junction can be used to optimise the modulation efficiency, and insertion losses for operation at 25 GHz.

An Automated Cloud-edge Detection Algorithm Using Cloud Physics and Radar Data

NASA Technical Reports Server (NTRS)

Ward, Jennifer G.; Merceret, Francis J.; Grainger, Cedric A.

2003-01-01

An automated cloud edge detection algorithm was developed and extensively tested. The algorithm uses in-situ cloud physics data measured by a research aircraft coupled with ground-based weather radar measurements to determine whether the aircraft is in or out of cloud. Cloud edges are determined when the in/out state changes, subject to a hysteresis constraint. The hysteresis constraint prevents isolated transient cloud puffs or data dropouts from being identified as cloud boundaries. The algorithm was verified by detailed manual examination of the data set in comparison to the results from application of the automated algorithm.

High Speed Edge Detection

NASA Technical Reports Server (NTRS)

Prokop, Norman F (Inventor)

2016-01-01

Analog circuits for detecting edges in pixel arrays are disclosed. A comparator may be configured to receive an all pass signal and a low pass signal for a pixel intensity in an array of pixels. A latch may be configured to receive a counter signal and a latching signal from the comparator. The comparator may be configured to send the latching signal to the latch when the all pass signal is below the low pass signal minus an offset. The latch may be configured to hold a last negative edge location when the latching signal is received from the comparator.

High Speed Edge Detection

NASA Technical Reports Server (NTRS)

Prokop, Norman F (Inventor)

2015-01-01

Analog circuits for detecting edges in pixel arrays are disclosed. A comparator may be configured to receive an all pass signal and a low pass signal for a pixel intensity in an array of pixels. A latch may be configured to receive a counter signal and a latching signal from the comparator. The comparator may be configured to send the latching signal to the latch when the all pass signal is below the low pass signal minus an offset. The latch may be configured to hold a last negative edge location when the latching signal is received from the comparator.

On the possibility to detect multipolar order in URu 2 Si 2 by the electric quadrupolar transition of resonant elastic x-ray scattering

DOE PAGES

Wang, Y. L.; Fabbris, G.; Meyers, D.; ...

2017-08-30

Resonant elastic x-ray scattering is a powerful technique for measuring multipolar order parameters. In this paper, we theoretically and experimentally study the possibility of using this technique to detect the proposed multipolar order parameters in URu 2 Si 2 at the U- L 3 edge with the electric quadrupolar transition. Based on an atomic model, we calculate the azimuthal dependence of the quadrupolar transition at the U- L 3 edge. Our results illustrate the potential of this technique for distinguishing different multipolar order parameters. We then perform experiments on ultraclean single crystals of URu 2 Si 2 at the U-more » L 3 edge to search for the predicted signal, but do not detect any indications of multipolar moments within the experimental uncertainty. We also theoretically estimate the orders of magnitude of the cross section and the expected count rate of the quadrupolar transition and compare them to the dipolar transitions at the U- M 4 and U- L 3 edges, clarifying the difficulty in detecting higher order multipolar order parameters in URu 2 Si 2 in the current experimental setup.« less

Study on the effect of the runner design parameters on 50 MW Francis hydro turbine model performance

NASA Astrophysics Data System (ADS)

Shrestha, Ujjwal; Chen, Zhenmu; Choi, Young-Do

2018-06-01

Francis hydro turbine is the dominant turbine in the hydropower generation. Francis turbine has been installed at most 60% of the hydropower in the world at present. Although the basic design for the Francis turbine has various method regarding the specific speed. The runner meridional shape varies with different specific speed. Despite having, the basic design but there is still some room for the optimization. In this study 50 MW, Francis hydro turbine with specific speed 323 m-kW was designed and considered for the optimization. The various parameter as runner meridional shape (curve profile of hub, shroud, leading edge and trailing edge), blade angle and its distribution, blade thickness, runner inlet width that has been considered for the optimization of the runner for enhancement of the performance.

Improved Abutting Edges For Welding In Keyhole Mode

NASA Technical Reports Server (NTRS)

Harwing, Dennis D.; Sanders, John M.

1994-01-01

Welds of better quality made, and/or heat input reduced. Improved shapes devised for abutting edges of metal pieces to be joined by plasma arc welding in keyhole mode, in which gas jet maintains molten hole ("keyhole") completely through thickness of weld joint. Edges of metal pieces to be welded together machined to provide required combination gap and shaped, thin sections. Shapes and dimensions chosen to optimize weld in various respects; e.g., to enhance penetration of keyhole or reduce heat input to produce joint of given thickness.

Edge detection, cosmic strings and the south pole telescope

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

Stewart, Andrew; Brandenberger, Robert, E-mail: stewarta@physics.mcgill.ca, E-mail: rhb@physics.mcgill.ca

2009-02-15

We develop a method of constraining the cosmic string tension G{mu} which uses the Canny edge detection algorithm as a means of searching CMB temperature maps for the signature of the Kaiser-Stebbins effect. We test the potential of this method using high resolution, simulated CMB temperature maps. By modeling the future output from the South Pole Telescope project (including anticipated instrumental noise), we find that cosmic strings with G{mu} > 5.5 Multiplication-Sign 10{sup -8} could be detected.

In vitro chloramphenicol detection in a Haemophilus influenza model using an aptamer-polymer based electrochemical biosensor.

PubMed

Yadav, Saurabh K; Agrawal, Bharati; Chandra, Pranjal; Goyal, Rajendra N

2014-05-15

A sensitive and selective electrochemical biosensor is developed for the determination of chloramphenicol (CAP) exploring its direct electron transfer processes in in-vitro model and pharmaceutical samples. This biosensor exploits a selective binding of CAP with aptamer, immobilized onto the poly-(4-amino-3-hydroxynapthalene sulfonic acid) (p-AHNSA) modified edge plane pyrolytic graphite. The electrochemical reduction of CAP was observed in a well-defined peak. A quartz crystal microbalance (QCM) study is performed to confirm the interaction between the polymer film and the aptamer. Cyclic voltammetry (CV) and square wave voltammetry (SWV) were used to detect CAP. The in-vitro CAP detection is performed using the bacterial strain of Haemophilus influenza. A significant accumulation of CAP by the drug sensitive H. influenza strain is observed for the first time in this study using a biosensor. Various parameters affecting the CAP detection in standard solution and in in vitro detection are optimized. The detection of CAP is linear in the range of 0.1-2500 nM with the detection limit and sensitivity of 0.02 nM and 0.102 µA/nM, respectively. CAP is also detected in the presence of other common antibiotics and proteins present in the real sample matrix, and negligible interference is observed. Copyright © 2013 Elsevier B.V. All rights reserved.

Leading edge gypsy moth population dynamics

Treesearch

M. R. Carter; F. W. Ravlin; M. L. McManus

1991-01-01

Leading edge gypsy moth populations have been the focus of several intervention programs (MDIPM, AIPM). Knowledge of gypsy moth population dynamics in leading edge area is crucial for effective management. Populations in these areas tend to reach outbreak levels (noticeable defoliation) within three to four years after egg masses are first detected. Pheromone traps...

Lasing in optimized two-dimensional iron-nail-shaped rod photonic crystals

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

Kwon, Soon-Yong; Moon, Seul-Ki; Yang, Jin-Kyu, E-mail: jinkyuyang@kongju.ac.kr

2016-03-15

We demonstrated lasing at the Γ-point band-edge (BE) modes in optimized two-dimensional iron-nail-shaped rod photonic crystals by optical pulse pumping at room temperature. As the radius of the rod increased quadratically toward the edge of the pattern, the quality factor of the Γ-point BE mode increased up to three times, and the modal volume decreased to 56% compared with the values of the original Γ-point BE mode because of the reduction of the optical loss in the horizontal direction. Single-mode lasing from an optimized iron-nail-shaped rod array with an InGaAsP multiple quantum well embedded in the nail heads was observedmore » at a low threshold pump power of 160 μW. Real-image-based numerical simulations showed that the lasing actions originated from the optimized Γ-point BE mode and agreed well with the measurement results, including the lasing polarization, wavelength, and near-field image.« less

Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach.

PubMed

Abd El Aziz, Mohamed; Selim, I M; Xiong, Shengwu

2017-06-30

This paper presents a new approach for the automatic detection of galaxy morphology from datasets based on an image-retrieval approach. Currently, there are several classification methods proposed to detect galaxy types within an image. However, in some situations, the aim is not only to determine the type of galaxy within the queried image, but also to determine the most similar images for query image. Therefore, this paper proposes an image-retrieval method to detect the type of galaxies within an image and return with the most similar image. The proposed method consists of two stages, in the first stage, a set of features is extracted based on shape, color and texture descriptors, then a binary sine cosine algorithm selects the most relevant features. In the second stage, the similarity between the features of the queried galaxy image and the features of other galaxy images is computed. Our experiments were performed using the EFIGI catalogue, which contains about 5000 galaxies images with different types (edge-on spiral, spiral, elliptical and irregular). We demonstrate that our proposed approach has better performance compared with the particle swarm optimization (PSO) and genetic algorithm (GA) methods.

Contrast-guided image interpolation.

PubMed

Wei, Zhe; Ma, Kai-Kuang

2013-11-01

In this paper a contrast-guided image interpolation method is proposed that incorporates contrast information into the image interpolation process. Given the image under interpolation, four binary contrast-guided decision maps (CDMs) are generated and used to guide the interpolation filtering through two sequential stages: 1) the 45(°) and 135(°) CDMs for interpolating the diagonal pixels and 2) the 0(°) and 90(°) CDMs for interpolating the row and column pixels. After applying edge detection to the input image, the generation of a CDM lies in evaluating those nearby non-edge pixels of each detected edge for re-classifying them possibly as edge pixels. This decision is realized by solving two generalized diffusion equations over the computed directional variation (DV) fields using a derived numerical approach to diffuse or spread the contrast boundaries or edges, respectively. The amount of diffusion or spreading is proportional to the amount of local contrast measured at each detected edge. The diffused DV fields are then thresholded for yielding the binary CDMs, respectively. Therefore, the decision bands with variable widths will be created on each CDM. The two CDMs generated in each stage will be exploited as the guidance maps to conduct the interpolation process: for each declared edge pixel on the CDM, a 1-D directional filtering will be applied to estimate its associated to-be-interpolated pixel along the direction as indicated by the respective CDM; otherwise, a 2-D directionless or isotropic filtering will be used instead to estimate the associated missing pixels for each declared non-edge pixel. Extensive simulation results have clearly shown that the proposed contrast-guided image interpolation is superior to other state-of-the-art edge-guided image interpolation methods. In addition, the computational complexity is relatively low when compared with existing methods; hence, it is fairly attractive for real-time image applications.

Field emission from optimized structure of carbon nanotube field emitter array

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

Chouhan, V., E-mail: vchouhan@post.kek.jp, E-mail: vijaychouhan84@gmail.com; Noguchi, T.; Kato, S.

The authors report a detail study on the emission properties of field emitter array (FEA) of micro-circular emitters of multiwall carbon nanotubes (CNTs). The FEAs were fabricated on patterned substrates prepared with an array of circular titanium (Ti) islands on titanium nitride coated tantalum substrates. CNTs were rooted into these Ti islands to prepare an array of circular emitters. The circular emitters were prepared in different diameters and pitches in order to optimize their structure for acquiring a high emission current. The pitch was varied from 0 to 600 μm, while a diameter of circular emitters was kept constant to bemore » 50 μm in order to optimize a pitch. For diameter optimization, a diameter was changed from 50 to 200 μm while keeping a constant edge-to-edge distance of 150 μm between the circular emitters. The FEA with a diameter of 50 μm and a pitch of 120 μm was found to be the best to achieve an emission current of 47 mA corresponding to an effective current density of 30.5 A/cm{sup 2} at 7 V/μm. The excellent emission current was attributed to good quality of CNT rooting into the substrate and optimized FEA structure, which provided a high electric field on a whole circular emitter of 50 μm and the best combination of the strong edge effect and CNT coverage. The experimental results were confirmed with computer simulation.« less

Value of Defect Information in Automated Hardwood Edger and Trimmer Systems

Treesearch

Carmen Regalado; D. Earl Kline; Philip A. Araman

1992-01-01

Due to the limited capability of board defect scanners, not all defect information required to make the best edging and trimming decision can be scanned for use in an automated system. The objective of the study presented in this paper was to evaluate the lumber value obtainable from edging and trimming optimization using varying levels of defect information as input....

Optimization of Process Parameters of Edge Robotic Deburring with Force Control

NASA Astrophysics Data System (ADS)

Burghardt, A.; Szybicki, D.; Kurc, K.; Muszyńska, M.

2016-12-01

The issues addressed in the paper present a part of the scientific research conducted within the framework of the automation of the aircraft engine part manufacturing processes. The results of the research presented in the article provided information in which tolerances while using a robotic control station with the option of force control we can make edge deburring.

Automated macromolecular crystal detection system and method

DOEpatents

Christian, Allen T [Tracy, CA; Segelke, Brent [San Ramon, CA; Rupp, Bernard [Livermore, CA; Toppani, Dominique [Fontainebleau, FR

2007-06-05

An automated macromolecular method and system for detecting crystals in two-dimensional images, such as light microscopy images obtained from an array of crystallization screens. Edges are detected from the images by identifying local maxima of a phase congruency-based function associated with each image. The detected edges are segmented into discrete line segments, which are subsequently geometrically evaluated with respect to each other to identify any crystal-like qualities such as, for example, parallel lines, facing each other, similarity in length, and relative proximity. And from the evaluation a determination is made as to whether crystals are present in each image.

Detection and display of acoustic window for guiding and training cardiac ultrasound users

NASA Astrophysics Data System (ADS)

Huang, Sheng-Wen; Radulescu, Emil; Wang, Shougang; Thiele, Karl; Prater, David; Maxwell, Douglas; Rafter, Patrick; Dupuy, Clement; Drysdale, Jeremy; Erkamp, Ramon

2014-03-01

Successful ultrasound data collection strongly relies on the skills of the operator. Among different scans, echocardiography is especially challenging as the heart is surrounded by ribs and lung tissue. Less experienced users might acquire compromised images because of suboptimal hand-eye coordination and less awareness of artifacts. Clearly, there is a need for a tool that can guide and train less experienced users to position the probe optimally. We propose to help users with hand-eye coordination by displaying lines overlaid on B-mode images. The lines indicate the edges of blockages (e.g., ribs) and are updated in real time according to movement of the probe relative to the blockages. They provide information about how probe positioning can be improved. To distinguish between blockage and acoustic window, we use coherence, an indicator of channel data similarity after applying focusing delays. Specialized beamforming was developed to estimate coherence. Image processing is applied to coherence maps to detect unblocked beams and the angle of the lines for display. We built a demonstrator based on a Philips iE33 scanner, from which beamsummed RF data and video output are transferred to a workstation for processing. The detected lines are overlaid on B-mode images and fed back to the scanner display to provide users real-time guidance. Using such information in addition to B-mode images, users will be able to quickly find a suitable acoustic window for optimal image quality, and improve their skill.

Reproducibility of aortic intima-media thickness in infants using edge-detection software and manual caliper measurements.

PubMed

McCloskey, Kate; Ponsonby, Anne-Louise; Carlin, John B; Jachno, Kim; Cheung, Michael; Skilton, Michael R; Koleff, Jane; Vuillermin, Peter; Burgner, David

2014-06-03

Aortic intima-media thickness measured by transabdominal ultrasound (aIMT) is an intermediate phenotype of cardiovascular risk. We aimed to (1) investigate the reproducibility of aIMT in a population-derived cohort of infants; (2) establish the distribution of aIMT in early infancy; (3) compare measurement by edge-detection software to that by manual sonographic calipers; and (4) assess the effect of individual and environmental variables on image quality. Participants were term infants recruited to a population-derived birth cohort study. Transabdominal ultrasound was performed at six weeks of age by one of two trained operators. Thirty participants had ultrasounds performed by both operators on the same day. Data were collected on environmental (infant sleeping, presence of a sibling, use of sucrose, timing during study visit) and individual (post-conception age, weight, gender) variables. Two readers assessed image quality and measured aIMT by edge-detection software and a subset by manual sonographic calipers. Measurements were repeated by the same reader and between readers to obtain intra-observer and inter-observer reliability. Aortic IMT was measured successfully using edge-detection in 814 infants, and 290 of these infants also had aIMT measured using manual sonographic calipers. The intra-reader intra-class correlation (ICC) (n = 20) was 0.90 (95% CI 0.76, 0.96), mean difference 1.5 μm (95% LOA -39, 59). The between reader ICC using edge-detection (n = 20) was 0.92 (95% CI 0.82, 0.97) mean difference 2 μm (95% LOA -45.0, 49.0) and with manual caliper measurement (n = 290) the ICC was 0.84 (95% CI 0.80, 0.87) mean difference 5 μm (95% LOA -51.8, 61.8). Edge-detection measurements were greater than those from manual sonographic calipers (mean aIMT 618 μm (50) versus mean aIMT 563 μm (49) respectively; p < 0.001, mean difference 44 μm, 95% LOA -54, 142). With the exception of infant crying (p = 0.001), no associations were observed between individual and environmental variables and image quality. In a population-derived cohort of term infants, aIMT measurement has a high level of intra and inter-reader reproducibility. Measurement of aIMT using edge-detection software gives higher inter-reader ICC than manual sonographic calipers. Image quality is not substantially affected by individual and environmental factors.

Robust design optimization method for centrifugal impellers under surface roughness uncertainties due to blade fouling

NASA Astrophysics Data System (ADS)

Ju, Yaping; Zhang, Chuhua

2016-03-01

Blade fouling has been proved to be a great threat to compressor performance in operating stage. The current researches on fouling-induced performance degradations of centrifugal compressors are based mainly on simplified roughness models without taking into account the realistic factors such as spatial non-uniformity and randomness of the fouling-induced surface roughness. Moreover, little attention has been paid to the robust design optimization of centrifugal compressor impellers with considerations of blade fouling. In this paper, a multi-objective robust design optimization method is developed for centrifugal impellers under surface roughness uncertainties due to blade fouling. A three-dimensional surface roughness map is proposed to describe the nonuniformity and randomness of realistic fouling accumulations on blades. To lower computational cost in robust design optimization, the support vector regression (SVR) metamodel is combined with the Monte Carlo simulation (MCS) method to conduct the uncertainty analysis of fouled impeller performance. The analyzed results show that the critical fouled region associated with impeller performance degradations lies at the leading edge of blade tip. The SVR metamodel has been proved to be an efficient and accurate means in the detection of impeller performance variations caused by roughness uncertainties. After design optimization, the robust optimal design is found to be more efficient and less sensitive to fouling uncertainties while maintaining good impeller performance in the clean condition. This research proposes a systematic design optimization method for centrifugal compressors with considerations of blade fouling, providing a practical guidance to the design of advanced centrifugal compressors.

Factors affecting volume calculation with single photon emission tomography (SPECT) method

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

Liu, T.H.; Lee, K.H.; Chen, D.C.P.

1985-05-01

Several factors may influence the calculation of absolute volumes (VL) from SPECT images. The effect of these factors must be established to optimize the technique. The authors investigated the following on the VL calculations: % of background (BG) subtraction, reconstruction filters, sample activity, angular sampling and edge detection methods. Transaxial images of a liver-trunk phantom filled with Tc-99m from 1 to 3 ..mu..Ci/cc were obtained in 64x64 matrix with a Siemens Rota Camera and MDS computer. Different reconstruction filters including Hanning 20,32, 64 and Butterworth 20, 32 were used. Angular samplings were performed in 3 and 6 degree increments. ROI'smore » were drawn manually and with an automatic edge detection program around the image after BG subtraction. VL's were calculated by multiplying the number of pixels within the ROI by the slice thickness and the x- and y- calibrations of each pixel. One or 2 pixel per slice thickness was applied in the calculation. An inverse correlation was found between the calculated VL and the % of BG subtraction (r=0.99 for 1,2,3 ..mu..Ci/cc activity). Based on the authors' linear regression analysis, the correct liver VL was measured with about 53% BG subtraction. The reconstruction filters, slice thickness and angular sampling had only minor effects on the calculated phantom volumes. Detection of the ROI automatically by the computer was not as accurate as the manual method. The authors conclude that the % of BG subtraction appears to be the most important factor affecting the VL calculation. With good quality control and appropriate reconstruction factors, correct VL calculations can be achieved with SPECT.« less

Superpixel edges for boundary detection

DOEpatents

Moya, Mary M.; Koch, Mark W.

2016-07-12

Various embodiments presented herein relate to identifying one or more edges in a synthetic aperture radar (SAR) image comprising a plurality of superpixels. Superpixels sharing an edge (or boundary) can be identified and one or more properties of the shared superpixels can be compared to determine whether the superpixels form the same or two different features. Where the superpixels form the same feature the edge is identified as an internal edge. Where the superpixels form two different features, the edge is identified as an external edge. Based upon classification of the superpixels, the external edge can be further determined to form part of a roof, wall, etc. The superpixels can be formed from a speckle-reduced SAR image product formed from a registered stack of SAR images, which is further segmented into a plurality of superpixels. The edge identification process is applied to the SAR image comprising the superpixels and edges.

An enhanced narrow-band imaging method for the microvessel detection

NASA Astrophysics Data System (ADS)

Yu, Feng; Song, Enmin; Liu, Hong; Wan, Youming; Zhu, Jun; Hung, Chih-Cheng

2018-02-01

A medical endoscope system combined with the narrow-band imaging (NBI), has been shown to be a superior diagnostic tool for early cancer detection. The NBI can reveal the morphologic changes of microvessels in the superficial cancer. In order to improve the conspicuousness of microvessel texture, we propose an enhanced NBI method to improve the conspicuousness of endoscopic images. To obtain the more conspicuous narrow-band images, we use the edge operator to extract the edge information of the narrow-band blue and green images, and give a weight to the extracted edges. Then, the weighted edges are fused with the narrow-band blue and green images. Finally, the displayed endoscopic images are reconstructed with the enhanced narrow-band images. In addition, we evaluate the performance of enhanced narrow-band images with different edge operators. Experimental results indicate that the Sobel and Canny operators achieve the best performance of all. Compared with traditional NBI method of Olympus company, our proposed method has more conspicuous texture of microvessel.

Molybdenum X-Ray Absorption Edges from 200 – 20,000 eV, The Benefits of Soft X-Ray Spectroscopy for Chemical Speciation

PubMed Central

George, Simon J.; Drury, Owen B.; Fu, Juxia; Friedrich, Stephan; Doonan, Christian J.; George, Graham N.; White, Jonathan M.; Young, Charles G.; Cramer, Stephen P.

2009-01-01

We have surveyed the chemical utility of the near-edge structure of molybdenum x-ray absorption edges from the hard x-ray K-edge at 20,000 eV down to the soft x-ray M4,5-edges at ~230 eV. We compared, for each edge, the spectra of two tetrahedral anions, MoO4 and MoS42-. We used three criteria for assessing near-edge structure of each edge: (i) the ratio of the observed chemical shift between MoO42- and MoS42- and the linewidth, (ii) the chemical information from analysis of the near-edge structure and (iii) the ease of measurement using fluorescence detection. Not surprisingly, the K-edge was by far the easiest to measure, but it contained the least information. The L2,3-edges, although harder to measure, had benefits with regard to selection rules and chemical speciation in that they had both a greater chemical shift as well as detailed lineshapes which could be theoretically analyzed in terms of Mo ligand field, symmetry, and covalency. The soft x-ray M2,3-edges were perhaps the least useful, in that they were difficult to measure using fluorescence detection and had very similar information content to the corresponding L2,3-edges. Interestingly, the soft x-ray, low energy (~230 eV) M4,5-edges had greatest potential chemical sensitivity and using our high resolution superconducting tunnel junction (STJ) fluorescence detector they appear to be straightforward to measure. The spectra were amenable to analysis using both the TT-multiplet approach and FEFF. The results using FEFF indicate that the sharp near-edge peaks arise from 3d → 5p transitions, while the broad edge structure has predominately 3d → 4f character. A proper understanding of the dependence of these soft x-ray spectra on ligand field and site geometry is necessary before a complete assessment of the utility of the Mo M4,5-edges can be made. This work includes crystallographic characterization of sodium tetrathiomolybdate. PMID:19041140

The SKED: speckle knife edge detector

NASA Astrophysics Data System (ADS)

Sharpies, S. D.; Light, R. A.; Achamfuo-Yeboah, S. O.; Clark, M.; Somekh, M. G.

2014-06-01

The knife edge detector—also known as optical beam deflection—is a simple and robust method of detecting ultrasonic waves using a laser. It is particularly suitable for detection of high frequency surface acoustic waves as the response is proportional to variation of the local tilt of the surface. In the case of a specular reflection of the incident laser beam from a smooth surface, any lateral movement of the reflected beam caused by the ultrasonic waves is easily detected by a pair of photodiodes. The major disadvantage of the knife edge detector is that it does not cope well with optically rough surfaces, those that give a speckled reflection. The optical speckles from a rough surface adversely affect the efficiency of the knife edge detector, because 'dark' speckles move synchronously with 'bright' speckles, and their contributions to the ultrasonic signal cancel each other out. We have developed a new self-adapting sensor which can cope with the optical speckles reflected from a rough surface. It is inelegantly called the SKED—speckle knife edge detector—and like its smooth surface namesake it is simple, cheap, compact, and robust. We describe the theory of its operation, and present preliminary experimental results validating the overall concept and the operation of the prototype device.

Iris segmentation using an edge detector based on fuzzy sets theory and cellular learning automata.

PubMed

Ghanizadeh, Afshin; Abarghouei, Amir Atapour; Sinaie, Saman; Saad, Puteh; Shamsuddin, Siti Mariyam

2011-07-01

Iris-based biometric systems identify individuals based on the characteristics of their iris, since they are proven to remain unique for a long time. An iris recognition system includes four phases, the most important of which is preprocessing in which the iris segmentation is performed. The accuracy of an iris biometric system critically depends on the segmentation system. In this paper, an iris segmentation system using edge detection techniques and Hough transforms is presented. The newly proposed edge detection system enhances the performance of the segmentation in a way that it performs much more efficiently than the other conventional iris segmentation methods.

Effect of temporal pulse shaping on the reduction of laser weld defects in a Pd-Ag-Sn dental alloy.

PubMed

Bertrand, C; Poulon-Quintin, A

2011-03-01

To describe the influence of pulse shaping on the behavior of a palladium-based dental alloy during laser welding and to show how its choice is effective to promote good weld quality. Single spots, weld beads and welds with 80% overlapping were performed on Pd-Ag-Sn cast plates. A pulsed Nd:Yag laser was used with a specific welding procedure using all the possibilities for pulse-shaping: (1) the square pulse shape as the default setting, (2) a rising edge slope for gradual heating, (3) a falling edge slope to slow the cooling and (4) a combination of a rising and falling edges called bridge shape. The optimization of the pulse shape is supposed to enhance weldability and produce defect-free welds (cracks, pores…) Vickers microhardness measurements were made on cross sections of the welds. A correlation between laser welding parameters and microstructure evolution was found. Hot cracking and internal porosities were systematically detected when using rapid cooling. The presence of these types of defects was significantly reduced with the slow cooling of the molten pool. The best weld quality was obtained with the use of the bridge shape. The use of a slow cooling ramp is the only way to significantly reduce the presence of typical defects within the welds for this Pd-based alloy studied. Copyright © 2010 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Adaptive Gaze Strategies for Locomotion with Constricted Visual Field

PubMed Central

Authié, Colas N.; Berthoz, Alain; Sahel, José-Alain; Safran, Avinoam B.

2017-01-01

In retinitis pigmentosa (RP), loss of peripheral visual field accounts for most difficulties encountered in visuo-motor coordination during locomotion. The purpose of this study was to accurately assess the impact of peripheral visual field loss on gaze strategies during locomotion, and identify compensatory mechanisms. Nine RP subjects presenting a central visual field limited to 10–25° in diameter, and nine healthy subjects were asked to walk in one of three directions—straight ahead to a visual target, leftward and rightward through a door frame, with or without obstacle on the way. Whole body kinematics were recorded by motion capture, and gaze direction in space was reconstructed using an eye-tracker. Changes in gaze strategies were identified in RP subjects, including extensive exploration prior to walking, frequent fixations of the ground (even knowing no obstacle was present), of door edges, essentially of the proximal one, of obstacle edge/corner, and alternating door edges fixations when approaching the door. This was associated with more frequent, sometimes larger rapid-eye-movements, larger movements, and forward tilting of the head. Despite the visual handicap, the trajectory geometry was identical between groups, with a small decrease in walking speed in RPs. These findings identify the adaptive changes in sensory-motor coordination, in order to ensure visual awareness of the surrounding, detect changes in spatial configuration, collect information for self-motion, update the postural reference frame, and update egocentric distances to environmental objects. They are of crucial importance for the design of optimized rehabilitation procedures. PMID:28798674

XAFSmass: a program for calculating the optimal mass of XAFS samples

NASA Astrophysics Data System (ADS)

Klementiev, K.; Chernikov, R.

2016-05-01

We present a new implementation of the XAFSmass program that calculates the optimal mass of XAFS samples. It has several improvements as compared to the old Windows based program XAFSmass: 1) it is truly platform independent, as provided by Python language, 2) it has an improved parser of chemical formulas that enables parentheses and nested inclusion-to-matrix weight percentages. The program calculates the absorption edge height given the total optical thickness, operates with differently determined sample amounts (mass, pressure, density or sample area) depending on the aggregate state of the sample and solves the inverse problem of finding the elemental composition given the experimental absorption edge jump and the chemical formula.

Photon counting x-ray imaging with K-edge filtered x-rays: A simulation study.

PubMed

Atak, Haluk; Shikhaliev, Polad M

2016-03-01

In photon counting (PC) x-ray imaging and computed tomography (CT), the broad x-ray spectrum can be split into two parts using an x-ray filter with appropriate K-edge energy, which can improve material decomposition. Recent experimental study has demonstrated substantial improvement in material decomposition with PC CT when K-edge filtered x-rays were used. The purpose of the current work was to conduct further investigations of the K-edge filtration method using comprehensive simulation studies. The study was performed in the following aspects: (1) optimization of the K-edge filter for a particular imaging configuration, (2) effects of the K-edge filter parameters on material decomposition, (3) trade-off between the energy bin separation, tube load, and beam quality with K-edge filter, (4) image quality of general (unsubtracted) images when a K-edge filter is used to improve dual energy (DE) subtracted images, and (5) improvements with K-edge filtered x-rays when PC detector has limited energy resolution. The PC x-ray images of soft tissue phantoms with 15 and 30 cm thicknesses including iodine, CaCO3, and soft tissue contrast materials, were simulated. The signal to noise ratio (SNR) of the contrast elements was determined in general and material-decomposed images using K-edge filters with different atomic numbers and thicknesses. The effect of the filter atomic number and filter thickness on energy separation factor and SNR was determined. The boundary conditions for the tube load and halfvalue layer were determined when the K-edge filters are used. The material-decomposed images were also simulated using PC detector with limited energy resolution, and improvements with K-edge filtered x-rays were quantified. The K-edge filters with atomic numbers from 56 to 71 and K-edge energies 37.4-63.4 keV, respectively, can be used for tube voltages from 60 to 150 kVp, respectively. For a particular tube voltage of 120 kVp, the Gd and Ho were the optimal filter materials to achieve highest SNR. For a particular K-edge filter of Gd and tube voltage of 120 kVp, the filter thickness 0.6 mm provided maximum SNR for considered imaging applications. While K-edge filtration improved SNR of CaCO3 and iodine by 41% and 36%, respectively, in DE subtracted images, it did not deteriorate SNR in general images. For x-ray imaging with nonideal PC detector, the positive effect of the K-edge filter was increased when FWHM energy resolution was degraded, and maximum improvement was at 60% FWHM. This study has shown that K-edge filtered x-rays can provide substantial improvements of material selective PC x-ray and CT imaging for nearly all imaging applications using 60-150 kVp tube voltages. Potential limitations such as tube load, beam hardening, and availability of filter material were shown to not be critical.

Optimization of Pockels electric field in transverse modulated optical voltage sensor

NASA Astrophysics Data System (ADS)

Huang, Yifan; Xu, Qifeng; Chen, Kun-Long; Zhou, Jie

2018-05-01

This paper investigates the possibilities of optimizing the Pockels electric field in a transverse modulated optical voltage sensor with a spherical electrode structure. The simulations show that due to the edge effect and the electric field concentrations and distortions, the electric field distributions in the crystal are non-uniform. In this case, a tiny variation in the light path leads to an integral error of more than 0.5%. Moreover, a 2D model cannot effectively represent the edge effect, so a 3D model is employed to optimize the electric field distributions. Furthermore, a new method to attach a quartz crystal to the electro-optic crystal along the electric field direction is proposed to improve the non-uniformity of the electric field. The integral error is reduced therefore from 0.5% to 0.015% and less. The proposed method is simple, practical and effective, and it has been validated by numerical simulations and experimental tests.

Breast mass segmentation in mammography using plane fitting and dynamic programming.

PubMed

Song, Enmin; Jiang, Luan; Jin, Renchao; Zhang, Lin; Yuan, Yuan; Li, Qiang

2009-07-01

Segmentation is an important and challenging task in a computer-aided diagnosis (CAD) system. Accurate segmentation could improve the accuracy in lesion detection and characterization. The objective of this study is to develop and test a new segmentation method that aims at improving the performance level of breast mass segmentation in mammography, which could be used to provide accurate features for classification. This automated segmentation method consists of two main steps and combines the edge gradient, the pixel intensity, as well as the shape characteristics of the lesions to achieve good segmentation results. First, a plane fitting method was applied to a background-trend corrected region-of-interest (ROI) of a mass to obtain the edge candidate points. Second, dynamic programming technique was used to find the "optimal" contour of the mass from the edge candidate points. Area-based similarity measures based on the radiologist's manually marked annotation and the segmented region were employed as criteria to evaluate the performance level of the segmentation method. With the evaluation criteria, the new method was compared with 1) the dynamic programming method developed by Timp and Karssemeijer, and 2) the normalized cut segmentation method, based on 337 ROIs extracted from a publicly available image database. The experimental results indicate that our segmentation method can achieve a higher performance level than the other two methods, and the improvements in segmentation performance level were statistically significant. For instance, the mean overlap percentage for the new algorithm was 0.71, whereas those for Timp's dynamic programming method and the normalized cut segmentation method were 0.63 (P < .001) and 0.61 (P < .001), respectively. We developed a new segmentation method by use of plane fitting and dynamic programming, which achieved a relatively high performance level. The new segmentation method would be useful for improving the accuracy of computerized detection and classification of breast cancer in mammography.

Simulation of pattern and defect detection in periodic amplitude and phase structures using photorefractive four-wave mixing

NASA Astrophysics Data System (ADS)

Nehmetallah, Georges; Banerjee, Partha; Khoury, Jed

2015-03-01

The nonlinearity inherent in four-wave mixing in photorefractive (PR) materials is used for adaptive filtering. Examples include script enhancement on a periodic pattern, scratch and defect cluster enhancement, periodic pattern dislocation enhancement, etc. through intensity filtering image manipulation. Organic PR materials have large space-bandwidth product, which makes them useful in adaptive filtering techniques in quality control systems. For instance, in the case of edge enhancement, phase conjugation via four-wave mixing suppresses the low spatial frequencies of the Fourier spectrum of an aperiodic image and consequently leads to image edge enhancement. In this work, we model, numerically verify, and simulate the performance of a four wave mixing setup used for edge, defect and pattern detection in periodic amplitude and phase structures. The results show that this technique successfully detects the slightest defects clearly even with no enhancement. This technique should facilitate improvements in applications such as image display sharpness utilizing edge enhancement, production line defect inspection of fabrics, textiles, e-beam lithography masks, surface inspection, and materials characterization.

Detection of metal stress in boreal forest species using the 0.67-micron chlorophyll absorption band

NASA Technical Reports Server (NTRS)

Singhroy, Vernon H.; Kruse, Fred A.

1991-01-01

Several recent studies have shown that a shift of the red-edge inflection near 0.70 micron in vegetation reflectance spectra is an indicator of metal stress, partially attributable to changes in chlorophyll concentration. This 'red-edge shift', however, is difficult to detect and has been reported both toward longer (red) and shorter (blue) wavelengths. Our work demonstrates that direct measurement of the depth and width of the chlorophyll absorption band at 0.67 micron using digital feature extraction and absorption band characterization procedures developed for the analysis of mineral spectra is a more consistent indicator of metal stress. Additionally, the magnitude of these parameters is generally greater than that of the red edge shift and thus should be more amenable to detection and mapping using field and aircraft spectrometers.

Innovative Design and Performance Evaluation of Bionic Imprinting Toothed Wheel.

PubMed

Zhang, Zhihong; Wang, Xiaoyang; Tong, Jin; Stephen, Carr

2018-01-01

A highly efficient soil-burrowing dung beetle possesses an intricate outer contour curve on its foreleg end-tooth. This study was carried out based on evidence that this special outer contour curve has the potential of reducing soil penetration resistance and could enhance soil-burrowing efficiency. A toothed wheel is a typical agricultural implement for soil imprinting, to increase its working efficiency; the approach of the bionic geometrical structure was utilized to optimize the innovative shape of imprinting toothed wheel. Characteristics in the dung beetle's foreleg end-tooth were extracted and studied by the edge detection technique. Then, this special outer contour curve was modeled by a nine-order polynomial function and used for the innovative design of imprinting the tooth's cutting edge. Both the conventional and bionic teeth were manufactured, and traction tests in a soil bin were conducted. Taking required draft force and volume of imprinted microbasin as the evaluating indexes, operating efficiency and quality of different toothed wheels were compared and investigated. Results indicate that compared with the conventional toothed wheel, a bionic toothed wheel possesses a better forward resistance reduction property against soil and, meanwhile, can enhance the quality of soil imprinting by increasing the volume of the created micro-basin.

Automated reconstruction of standing posture panoramas from multi-sector long limb x-ray images

NASA Astrophysics Data System (ADS)

Miller, Linzey; Trier, Caroline; Ben-Zikri, Yehuda K.; Linte, Cristian A.

2016-03-01

Due to the digital X-ray imaging system's limited field of view, several individual sector images are required to capture the posture of an individual in standing position. These images are then "stitched together" to reconstruct the standing posture. We have created an image processing application that automates the stitching, therefore minimizing user input, optimizing workflow, and reducing human error. The application begins with pre-processing the input images by removing artifacts, filtering out isolated noisy regions, and amplifying a seamless bone edge. The resulting binary images are then registered together using a rigid-body intensity based registration algorithm. The identified registration transformations are then used to map the original sector images into the panorama image. Our method focuses primarily on the use of the anatomical content of the images to generate the panoramas as opposed to using external markers employed to aid with the alignment process. Currently, results show robust edge detection prior to registration and we have tested our approach by comparing the resulting automatically-stitched panoramas to the manually stitched panoramas in terms of registration parameters, target registration error of homologous markers, and the homogeneity of the digitally subtracted automatically- and manually-stitched images using 26 patient datasets.

Low-noise heterodyne receiver for electron cyclotron emission imaging and microwave imaging reflectometry

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

Tobias, B., E-mail: bjtobias@pppl.gov; Domier, C. W.; Luhmann, N. C.

2016-11-15

The critical component enabling electron cyclotron emission imaging (ECEI) and microwave imaging reflectometry (MIR) to resolve 2D and 3D electron temperature and density perturbations is the heterodyne imaging array that collects and downconverts radiated emission and/or reflected signals (50–150 GHz) to an intermediate frequency (IF) band (e.g. 0.1–18 GHz) that can be transmitted by a shielded coaxial cable for further filtering and detection. New circuitry has been developed for this task, integrating gallium arsenide (GaAs) monolithic microwave integrated circuits (MMICs) mounted on a liquid crystal polymer (LCP) substrate. The improved topology significantly increases electromagnetic shielding from out-of-band interference, leads tomore » 10× improvement in the signal-to-noise ratio, and dramatic cost savings through integration. The current design, optimized for reflectometry and edge radiometry on mid-sized tokamaks, has demonstrated >20 dB conversion gain in upper V-band (60-75 GHz). Implementation of the circuit in a multi-channel electron cyclotron emission imaging (ECEI) array will improve the diagnosis of edge-localized modes and fluctuations of the high-confinement, or H-mode, pedestal.« less

Low-noise heterodyne receiver for electron cyclotron emission imaging and microwave imaging reflectometry

DOE PAGES

Tobias, B.; Domier, C. W.; Luhmann, Jr., N. C.; ...

2016-07-25

The critical component enabling electron cyclotron emission imaging (ECEI) and microwave imaging reflectometry (MIR) to resolve 2D and 3D electron temperature and density perturbations is the heterodyne imaging array that collects and downconverts radiated emission and/or reflected signals (50-150 GHz) to an intermediate frequency (IF) band (e.g. 0.1-18 GHz) that can be transmitted by a shielded coaxial cable for further filtering and detection. New circuitry has been developed for this task, integrating gallium arsenide (GaAs) monolithic microwave integrated circuits (MMICs) mounted on a liquid crystal polymer (LCP) substrate. The improved topology significantly increases electromagnetic shielding from out-of-band interference, leads tomore » 10x improvement in the signal-to-noise ratio, and dramatic cost savings through integration. The current design, optimized for reflectometry and edge radiometry on mid-sized tokamaks, has demonstrated >20 dB conversion gain in upper V-band (60-75 GHz). As a result, implementation of the circuit in a multi-channel electron cyclotron emission imaging (ECEI) array will improve the diagnosis of edge-localized modes and fluctuations of the high-confinement, or H-mode, pedestal.« less

A combined spectral and object-based approach to transparent cloud removal in an operational setting for Landsat ETM+

NASA Astrophysics Data System (ADS)

Watmough, Gary R.; Atkinson, Peter M.; Hutton, Craig W.

2011-04-01

The automated cloud cover assessment (ACCA) algorithm has provided automated estimates of cloud cover for the Landsat ETM+ mission since 2001. However, due to the lack of a band around 1.375 μm, cloud edges and transparent clouds such as cirrus cannot be detected. Use of Landsat ETM+ imagery for terrestrial land analysis is further hampered by the relatively long revisit period due to a nadir only viewing sensor. In this study, the ACCA threshold parameters were altered to minimise omission errors in the cloud masks. Object-based analysis was used to reduce the commission errors from the extended cloud filters. The method resulted in the removal of optically thin cirrus cloud and cloud edges which are often missed by other methods in sub-tropical areas. Although not fully automated, the principles of the method developed here provide an opportunity for using otherwise sub-optimal or completely unusable Landsat ETM+ imagery for operational applications. Where specific images are required for particular research goals the method can be used to remove cloud and transparent cloud helping to reduce bias in subsequent land cover classifications.

Curriculum on the Edge of Survival: How Schools Fail to Prepare Students for Membership in a Democracy

ERIC Educational Resources Information Center

Heller, Daniel

2007-01-01

Typically, school curriculum has been viewed through the lens of preparation for the workplace or higher education--both worthy objectives. However, this is not the only lens, and perhaps not even the most powerful one to use, if the goal is to optimize the educational system. "Curriculum on the Edge of Survival" attempts to define basic aspects…

Strain measurement in semiconductor heterostructures by scanning transmission electron microscopy.

PubMed

Müller, Knut; Rosenauer, Andreas; Schowalter, Marco; Zweck, Josef; Fritz, Rafael; Volz, Kerstin

2012-10-01

This article deals with the measurement of strain in semiconductor heterostructures from convergent beam electron diffraction patterns. In particular, three different algorithms in the field of (circular) pattern recognition are presented that are able to detect diffracted disc positions accurately, from which the strain in growth direction is calculated. Although the three approaches are very different as one is based on edge detection, one on rotational averages, and one on cross correlation with masks, it is found that identical strain profiles result for an In x Ga1-x N y As1-y /GaAs heterostructure consisting of five compressively and tensile strained layers. We achieve a precision of strain measurements of 7-9·10-4 and a spatial resolution of 0.5-0.7 nm over the whole width of the layer stack which was 350 nm. Being already very applicable to strain measurements in contemporary nanostructures, we additionally suggest future hardware and software designs optimized for fast and direct acquisition of strain distributions, motivated by the present studies.

Observation of EHO in NSTX and Theoretical Study of its Active Control Using HHFW Antenna

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

J.-K. Park, et. al.

2013-01-14

Two important topics in the tokamak ELM control, using the non-axisymmetric (3D) magnetic perturbations, are studied in NSTX and combined envisioning ELM control in the future NSTX-U operation: Experimental observations of the edge harmonic oscillation in NSTX (not necessarily the same as EHOs in DIII-D), and theoretical study of its external drive using the high harmonic fast wave (HHFW) antenna as a 3D field coil. Edge harmonic oscillations were observed particularly well in NSTX ELM-free operation with low n core modes, with various diagnostics confirming n = 4 ~ 6 edge-localized and coherent oscillations in 2 ~ 8kHz frequency range.more » These oscillations seem to have a favored operational window in rotational shear, similarly to EHOs in DIII-D QH modes . However, in NSTX, they are not observed to provide particle or impurity control, possibly due to their weak amplitudes, of a few mm displacements, as measured by reflectometry. The external drive of these modes has been proposed in NSTX, by utilizing audio-frequency currents in the HHFW antenna straps. Analysis shows that the HHFW straps can be optimized to maximize n = 4 ~ 6 while minimizing n = 1 ~ 3. Also, IPEC calculations show that the optimized configuration with only 1kAt current can produce comparable or larger displacements than the observed internal modes. If this optimized external drive can be constructively combined, or further resonated with the internal modes, the edge harmonic oscillations in NSTX may be able to produce sufficient particle control to modify ELMs.« less

Preparation of edge states by shaking boundaries

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

Shi, Z.C.; Center for Quantum Sciences and School of Physics, Northeast Normal University, Changchun 130024; Hou, S.C.

2016-10-15

Preparing topological states of quantum matter, such as edge states, is one of the most important directions in condensed matter physics. In this work, we present a proposal to prepare edge states in Aubry–André–Harper (AAH) model with open boundaries, which takes advantage of Lyapunov control to design operations. We show that edge states can be obtained with almost arbitrary initial states. A numerical optimalization for the control is performed and the dependence of control process on the system size is discussed. The merit of this proposal is that the shaking exerts only on the boundaries of the model. As amore » by-product, a topological entangled state is achieved by elaborately designing the shaking scheme.« less

Wisps in the outer edge of the Keeler Gap

NASA Astrophysics Data System (ADS)

Tiscareno, M. S.; Arnault, E. G.

2014-12-01

The outer part of Saturn's A ring contains five sharp edges: the inner and outer edges of the Encke Gap and of the Keeler Gap (which contain the moons Pan and Daphnis, respectively), and the outer edge of the A ring itself. Four of these five edges are characterized by structure at moderate to high spatial frequencies, with amplitudes ranging from 2 to 30 km (Tiscareno et al. 2005, DPS). Only the outer edge of the Keeler Gap is reasonably smooth in appearance (Tiscareno et al. 2005, DPS), with occultations indicating residuals less than 1 km upon a possibly non-zero eccentricity (R.G. French, personal communication, 2014). Superposed upon the relatively smooth outer edge of the Keeler Gap are a system of "wisps," which appear to be ring material protruding inward into the gap, usually with a sharp trailing edge and a smooth gradation back to the background edge location on the leading side (Porco et al. 2005, Science). The radial amplitude of wisps is usually 0.5 to 1 km, and their azimuthal extent is approximately a degree of longitude (~2400 km). Wisps are likely caused by an interplay between Daphnis (and perhaps other moons) and embedded moonlets within the ring, though the details remain unclear. We will present a catalogue of wisp detections in Cassini images. We carry out repeated gaussian fits of the radial edge location in order to characterize edge structure (see Figure, which compares our fitted edge to the figure presented by Porco et al. 2005) and visually scan those fitted edges in order to detect wisps. With extensive coverage in longitude and in time, we will report on how wisps evolve and move, both within an orbit period and on longer timescales. We will also report on the frequency and interpretation of wisps that deviate from the standard morphology. We will discuss the implications of our results for the origin and nature of wisps, and for the larger picture of how masses interact within Saturn's rings.

Lunar-edge based on-orbit modulation transfer function (MTF) measurement

NASA Astrophysics Data System (ADS)

Cheng, Ying; Yi, Hongwei; Liu, Xinlong

2017-10-01

Modulation transfer function (MTF) is an important parameter for image quality evaluation of on-orbit optical image systems. Various methods have been proposed to determine the MTF of an imaging system which are based on images containing point, pulse and edge features. In this paper, the edge of the moon can be used as a high contrast target to measure on-orbit MTF of image systems based on knife-edge methods. The proposed method is an extension of the ISO 12233 Slanted-edge Spatial Frequency Response test, except that the shape of the edge is a circular arc instead of a straight line. In order to get more accurate edge locations and then obtain a more authentic edge spread function (ESF), we choose circular fitting method based on least square to fit lunar edge in sub-pixel edge detection process. At last, simulation results show that the MTF value at Nyquist frequency calculated using our lunar edge method is reliable and accurate with error less than 2% comparing with theoretical MTF value.

Avalanche and edge-of-chaos criticality do not necessarily co-occur in neural networks.

PubMed

Kanders, Karlis; Lorimer, Tom; Stoop, Ruedi

2017-04-01

There are indications that for optimizing neural computation, neural networks may operate at criticality. Previous approaches have used distinct fingerprints of criticality, leaving open the question whether the different notions would necessarily reflect different aspects of one and the same instance of criticality, or whether they could potentially refer to distinct instances of criticality. In this work, we choose avalanche criticality and edge-of-chaos criticality and demonstrate for a recurrent spiking neural network that avalanche criticality does not necessarily entrain dynamical edge-of-chaos criticality. This suggests that the different fingerprints may pertain to distinct phenomena.

Avalanche and edge-of-chaos criticality do not necessarily co-occur in neural networks

NASA Astrophysics Data System (ADS)

Kanders, Karlis; Lorimer, Tom; Stoop, Ruedi

2017-04-01

There are indications that for optimizing neural computation, neural networks may operate at criticality. Previous approaches have used distinct fingerprints of criticality, leaving open the question whether the different notions would necessarily reflect different aspects of one and the same instance of criticality, or whether they could potentially refer to distinct instances of criticality. In this work, we choose avalanche criticality and edge-of-chaos criticality and demonstrate for a recurrent spiking neural network that avalanche criticality does not necessarily entrain dynamical edge-of-chaos criticality. This suggests that the different fingerprints may pertain to distinct phenomena.

Investigation of statistical iterative reconstruction for dedicated breast CT

PubMed Central

Makeev, Andrey; Glick, Stephen J.

2013-01-01

Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images were compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue. Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters. Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially improved performance (by a factor of greater than 10) compared to FBP. The hyperbolic prior was also observed to be superior to the TV norm. A few of the best-performing parameter pairs for the PML method also demonstrated superior performance for various radiation doses. In fact, using PML with certain parameter values results in better images, acquired using 2 mGy dose, than FBP-reconstructed images acquired using 6 mGy dose. Conclusions: A range of optimal free parameters for the PML algorithm with hyperbolic and TV norm-based potentials is presented for the microcalcification detection task, in dedicated breast CT. The reported values can be used as starting values of the free parameters, when SIR techniques are used for image reconstruction. Significant improvement in image quality can be achieved by using PML with optimal combination of parameters, as compared to FBP. Importantly, these results suggest improved detection of microcalcifications can be obtained by using PML with lower radiation dose to the patient, than using FBP with higher dose. PMID:23927318

78 FR 66859 - Airworthiness Directives; the Boeing Company Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-07

... airplanes. This proposed AD was prompted by reports of bearing damage at certain trailing edge (TE) flap... certain trailing edge (TE) flap support rib assemblies. We are issuing this AD to detect and correct...

Image registration with uncertainty analysis

DOEpatents

Simonson, Katherine M [Cedar Crest, NM

2011-03-22

In an image registration method, edges are detected in a first image and a second image. A percentage of edge pixels in a subset of the second image that are also edges in the first image shifted by a translation is calculated. A best registration point is calculated based on a maximum percentage of edges matched. In a predefined search region, all registration points other than the best registration point are identified that are not significantly worse than the best registration point according to a predetermined statistical criterion.

Development of Long-Pulse Heating and Current Drive Actuators and Operational Techniques Compatible with a High-Z Divertor and First Wall

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

Wang, Guiding

Accurate measurement of the edge electron density profile is essential to optimizing antenna coupling and assessment of impurity contamination in studying long-pulse plasma heating and current drive in fusion devices. Measurement of the edge density profile has been demonstrated on the US fusion devices such as C-Mod, DIII-D, and TFTR amongst many devices, and has been used for RF loading and impurity modeling calculations for many years. University of Science and Technology of China (USTC) has recently installed a density profile reflectometer system on the EAST fusion device at the Institute of Plasma Physics, Chinese Academy of Sciences in Chinamore » based on the University of California Los Angeles (UCLA)-designed reflectometer system on the DIII-D fusion device at General Atomics Company in San Diego, California. UCLA has been working with USTC to optimize the existing microwave antenna, waveguide system, microwave electronics, and data analysis to produce reliable edge density profiles. During the past budget year, progress has been made in all three major areas: effort to achieve reliable system operations under various EAST operational conditions, effort to optimize system performance, and effort to provide quality density profiles into EAST’s database routinely.« less

Fast global image smoothing based on weighted least squares.

PubMed

Min, Dongbo; Choi, Sunghwan; Lu, Jiangbo; Ham, Bumsub; Sohn, Kwanghoon; Do, Minh N

2014-12-01

This paper presents an efficient technique for performing a spatially inhomogeneous edge-preserving image smoothing, called fast global smoother. Focusing on sparse Laplacian matrices consisting of a data term and a prior term (typically defined using four or eight neighbors for 2D image), our approach efficiently solves such global objective functions. In particular, we approximate the solution of the memory-and computation-intensive large linear system, defined over a d-dimensional spatial domain, by solving a sequence of 1D subsystems. Our separable implementation enables applying a linear-time tridiagonal matrix algorithm to solve d three-point Laplacian matrices iteratively. Our approach combines the best of two paradigms, i.e., efficient edge-preserving filters and optimization-based smoothing. Our method has a comparable runtime to the fast edge-preserving filters, but its global optimization formulation overcomes many limitations of the local filtering approaches. Our method also achieves high-quality results as the state-of-the-art optimization-based techniques, but runs ∼10-30 times faster. Besides, considering the flexibility in defining an objective function, we further propose generalized fast algorithms that perform Lγ norm smoothing (0 < γ < 2) and support an aggregated (robust) data term for handling imprecise data constraints. We demonstrate the effectiveness and efficiency of our techniques in a range of image processing and computer graphics applications.

Comparison of Bayesian clustering and edge detection methods for inferring boundaries in landscape genetics

USGS Publications Warehouse

Safner, T.; Miller, M.P.; McRae, B.H.; Fortin, M.-J.; Manel, S.

2011-01-01

Recently, techniques available for identifying clusters of individuals or boundaries between clusters using genetic data from natural populations have expanded rapidly. Consequently, there is a need to evaluate these different techniques. We used spatially-explicit simulation models to compare three spatial Bayesian clustering programs and two edge detection methods. Spatially-structured populations were simulated where a continuous population was subdivided by barriers. We evaluated the ability of each method to correctly identify boundary locations while varying: (i) time after divergence, (ii) strength of isolation by distance, (iii) level of genetic diversity, and (iv) amount of gene flow across barriers. To further evaluate the methods' effectiveness to detect genetic clusters in natural populations, we used previously published data on North American pumas and a European shrub. Our results show that with simulated and empirical data, the Bayesian spatial clustering algorithms outperformed direct edge detection methods. All methods incorrectly detected boundaries in the presence of strong patterns of isolation by distance. Based on this finding, we support the application of Bayesian spatial clustering algorithms for boundary detection in empirical datasets, with necessary tests for the influence of isolation by distance. ?? 2011 by the authors; licensee MDPI, Basel, Switzerland.

Comparative Study of Speckle Filtering Methods in PolSAR Radar Images

NASA Astrophysics Data System (ADS)

Boutarfa, S.; Bouchemakh, L.; Smara, Y.

2015-04-01

Images acquired by polarimetric SAR (PolSAR) radar systems are characterized by the presence of a noise called speckle. This noise has a multiplicative nature, corrupts both the amplitude and phase images, which complicates data interpretation, degrades segmentation performance and reduces the detectability of targets. Hence, the need to preprocess the images by adapted filtering methods before analysis.In this paper, we present a comparative study of implemented methods for reducing speckle in PolSAR images. These developed filters are: refined Lee filter based on the estimation of the minimum mean square error MMSE, improved Sigma filter with detection of strong scatterers based on the calculation of the coherency matrix to detect the different scatterers in order to preserve the polarization signature and maintain structures that are necessary for image interpretation, filtering by stationary wavelet transform SWT using multi-scale edge detection and the technique for improving the wavelet coefficients called SSC (sum of squared coefficients), and Turbo filter which is a combination between two complementary filters the refined Lee filter and the wavelet transform SWT. One filter can boost up the results of the other.The originality of our work is based on the application of these methods to several types of images: amplitude, intensity and complex, from a satellite or an airborne radar, and on the optimization of wavelet filtering by adding a parameter in the calculation of the threshold. This parameter will control the filtering effect and get a good compromise between smoothing homogeneous areas and preserving linear structures.The methods are applied to the fully polarimetric RADARSAT-2 images (HH, HV, VH, VV) acquired on Algiers, Algeria, in C-band and to the three polarimetric E-SAR images (HH, HV, VV) acquired on Oberpfaffenhofen area located in Munich, Germany, in P-band.To evaluate the performance of each filter, we used the following criteria: smoothing homogeneous areas, preserving edges and polarimetric information.Experimental results are included to illustrate the different implemented methods.

In-Operando Spatial Imaging of Edge Termination Electric Fields in GaN Vertical p-n Junction Diodes

DOE PAGES

Leonard, Francois; Dickerson, J. R.; King, M. P.; ...

2016-05-03

Control of electric fields with edge terminations is critical to maximize the performance of high-power electronic devices. We proposed a variety of edge termination designs which makes the optimization of such designs challenging due to many parameters that impact their effectiveness. And while modeling has recently allowed new insight into the detailed workings of edge terminations, the experimental verification of the design effectiveness is usually done through indirect means, such as the impact on breakdown voltages. In this letter, we use scanning photocurrent microscopy to spatially map the electric fields in vertical GaN p-n junction diodes in operando. We alsomore » reveal the complex behavior of seemingly simple edge termination designs, and show how the device breakdown voltage correlates with the electric field behavior. Modeling suggests that an incomplete compensation of the p-type layer in the edge termination creates a bilayer structure that leads to these effects, with variations that significantly impact the breakdown voltage.« less

Active Control of Separation From the Flap of a Supercritical Airfoil

NASA Technical Reports Server (NTRS)

Melton, La Tunia Pack; Yao, Chung-Sheng; Seifert, Avi

2003-01-01

Active flow control in the form of periodic zero-mass-flux excitation was applied at several regions on the leading edge and trailing edge flaps of a simplified high-lift system t o delay flow separation. The NASA Energy Efficient Transport (EET) supercritical airfoil was equipped with a 15% chord simply hinged leading edge flap and a 25% chord simply hinged trailing edge flap. Detailed flow features were measured in an attempt to identify optimal actuator placement. The measurements included steady and unsteady model and tunnel wall pressures, wake surveys, arrays of surface hot-films, flow visualization, and particle image velocimetry (PIV). The current paper describes the application of active separation control at several locations on the deflected trailing edge flap. High frequency (F(+) approx.= 10) and low frequency amplitude modulation (F(+)AM approx.= 1) of the high frequency excitation were used for control. Preliminary efforts to combine leading and trailing edge flap excitations are also reported.

Intelligent model-based OPC

NASA Astrophysics Data System (ADS)

Huang, W. C.; Lai, C. M.; Luo, B.; Tsai, C. K.; Chih, M. H.; Lai, C. W.; Kuo, C. C.; Liu, R. G.; Lin, H. T.

2006-03-01

Optical proximity correction is the technique of pre-distorting mask layouts so that the printed patterns are as close to the desired shapes as possible. For model-based optical proximity correction, a lithographic model to predict the edge position (contour) of patterns on the wafer after lithographic processing is needed. Generally, segmentation of edges is performed prior to the correction. Pattern edges are dissected into several small segments with corresponding target points. During the correction, the edges are moved back and forth from the initial drawn position, assisted by the lithographic model, to finally settle on the proper positions. When the correction converges, the intensity predicted by the model in every target points hits the model-specific threshold value. Several iterations are required to achieve the convergence and the computation time increases with the increase of the required iterations. An artificial neural network is an information-processing paradigm inspired by biological nervous systems, such as how the brain processes information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. A neural network can be a powerful data-modeling tool that is able to capture and represent complex input/output relationships. The network can accurately predict the behavior of a system via the learning procedure. A radial basis function network, a variant of artificial neural network, is an efficient function approximator. In this paper, a radial basis function network was used to build a mapping from the segment characteristics to the edge shift from the drawn position. This network can provide a good initial guess for each segment that OPC has carried out. The good initial guess reduces the required iterations. Consequently, cycle time can be shortened effectively. The optimization of the radial basis function network for this system was practiced by genetic algorithm, which is an artificially intelligent optimization method with a high probability to obtain global optimization. From preliminary results, the required iterations were reduced from 5 to 2 for a simple dumbbell-shape layout.

Geometric Effects on the Amplification of First Mode Instability Waves

NASA Technical Reports Server (NTRS)

Kirk, Lindsay C.; Candler, Graham V.

2013-01-01

The effects of geometric changes on the amplification of first mode instability waves in an external supersonic boundary layer were investigated using numerical techniques. Boundary layer stability was analyzed at Mach 6 conditions similar to freestream conditions obtained in quiet ground test facilities so that results obtained in this study may be applied to future test article design to measure first mode instability waves. The DAKOTA optimization software package was used to optimize an axisymmetric geometry to maximize the amplification of the waves at first mode frequencies as computed by the 2D STABL hypersonic boundary layer stability analysis tool. First, geometric parameters such as nose radius, cone half angle, vehicle length, and surface curvature were examined separately to determine the individual effects on the first mode amplification. Finally, all geometric parameters were allowed to vary to produce a shape optimized to maximize the amplification of first mode instability waves while minimizing the amplification of second mode instability waves. Since first mode waves are known to be most unstable in the form of oblique wave, the geometries were optimized using a broad range of wave frequencies as well as a wide range of oblique wave angles to determine the geometry that most amplifies the first mode waves. Since first mode waves are seen most often in flows with low Mach numbers at the edge of the boundary layer, the edge Mach number for each geometry was recorded to determine any relationship between edge Mach number and the stability of first mode waves. Results indicate that an axisymmetric cone with a sharp nose and a slight flare at the aft end under the Mach 6 freestream conditions used here will lower the Mach number at the edge of the boundary layer to less than 4, and the corresponding stability analysis showed maximum first mode N factors of 3.

Nonaxisymmetric modelling in BOUT++; toward global edge fluid turbulence in stellarators

NASA Astrophysics Data System (ADS)

Shanahan, Brendan; Hill, Peter; Dudson, Ben

2016-10-01

As Wendelstein 7-X has been optimized for neoclassical transport, turbulent transport could potentially become comparable to neoclassical losses. Furthermore, the imminent installation of an island divertor merits global edge modelling to determine heat flux profiles and the efficacy of the system. Currently, however, nonaxisymmetric edge plasma modelling is limited to either steady state (non-turbulent) transport modelling, or computationally expensive gyrokinetics. The implementation of the Flux Coordinate Independent (FCI) approach to parallel derivatives has allowed the extension of the BOUT++ edge fluid turbulence framework to nonaxisymmetric geometries. Here we first investigate the implementation of the FCI method in BOUT++ by modelling diffusion equations in nonaxisymmetric geometries with and without boundary interaction, and quantify the inherent error. We then present the results of non-turbulent transport modelling and compare with analytical theory. The ongoing extension of BOUT++ to nonaxisymmetric configurations, and the prospects of stellarator edge fluid turbulence simulations will be discussed.

Band-edge positions in G W : Effects of starting point and self-consistency

NASA Astrophysics Data System (ADS)

Chen, Wei; Pasquarello, Alfredo

2014-10-01

We study the effect of starting point and self-consistency within G W on the band-edge positions of semiconductors and insulators. Compared to calculations based on a semilocal starting point, the use of a hybrid-functional starting point shows a larger quasiparticle correction for both band-edge states. When the self-consistent treatment is employed, the band-gap opening is found to result mostly from a shift of the valence-band edge. Within the non-self-consistent methods, we analyse the performance of empirical and nonempirical schemes in which the starting point is optimally tuned. We further assess the accuracy of the band-edge positions through the calculation of ionization potentials of surfaces. The ionization potentials for most systems are reasonably well described by one-shot calculations. However, in the case of TiO2, we find that the use of self-consistency is critical to obtain a good agreement with experiment.

Fabrication of sapphire-based high performance step-edge HTS Josephson junctions and SQUIDs and their application to scanning SQUID microscopy

NASA Astrophysics Data System (ADS)

Ming, Bin

Josephson junctions are at the heart of any superconductor device applications. A SQUID (Superconducting Quantum Interference Device), which consists of two Josephson junctions, is by far the most important example. Unfortunately, in the case of high-Tc superconductors (HTS), the quest for a robust, flexible, and high performance junction technology is yet far from the end. Currently, the only proven method to make HTS junctions is the SrTiO3(STO)-based bicrystal technology. In this thesis we concentrate on the fabrication of YBCO step-edge junctions and SQUIDs on sapphire. The step-edge method provides complete control of device locations and facilitates sophisticated, high-density layout. We select CeO2 as the buffer layer, as the key step to make device quality YBCO thin films on sapphire. With an "overhang" shadow mask produced by a novel photolithography technique, a steep step edge was fabricated on the CeO2 buffer layer by Ar+ ion milling with optimized parameters for minimum ion beam divergence. The step angle was determined to be in excess of 80° by atomic force microscopy (AFM). Josephson junctions patterned from those step edges exhibited resistively shunted junction (RSJ) like current-voltage characteristics. IcR n values in the 200--500 mV range were measured at 77K. Shapiro steps were observed under microwave irradiation, reflecting the true Josephson nature of those junctions. The magnetic field dependence of the junction Ic indicates a uniform current distribution. These results suggest that all fabrication processes are well controlled and the step edge is relatively straight and free of microstructural defects. The SQUIDs made from the same process exhibit large voltage modulation in a varying magnetic field. At 77K, our sapphire-based step-edge SQUID has a low white noise level at 3muphi0/ Hz , as compared to typically >10muphi0/ Hz from the best bicrystal STO SQUIDS. Our effort at device fabrication is chiefly motivated by the scanning SQUID microscopy (SSM) application. A scanning SQUID microscope is a non-contact, non-destructive imaging tool that can resolve weak currents beneath the sample surface by detecting their magnetic fields. Our low-noise sapphire-based step-edge SQUIDs should be particularly suitable for such an application. An earlier effort to make SNS trench junctions using focused ion beam (FIB) is reviewed in a separate chapter. (Abstract shortened by UMI.)

MuSCoWERT: multi-scale consistence of weighted edge Radon transform for horizon detection in maritime images.

PubMed

Prasad, Dilip K; Rajan, Deepu; Rachmawati, Lily; Rajabally, Eshan; Quek, Chai

2016-12-01

This paper addresses the problem of horizon detection, a fundamental process in numerous object detection algorithms, in a maritime environment. The maritime environment is characterized by the absence of fixed features, the presence of numerous linear features in dynamically changing objects and background and constantly varying illumination, rendering the typically simple problem of detecting the horizon a challenging one. We present a novel method called multi-scale consistence of weighted edge Radon transform, abbreviated as MuSCoWERT. It detects the long linear features consistent over multiple scales using multi-scale median filtering of the image followed by Radon transform on a weighted edge map and computing the histogram of the detected linear features. We show that MuSCoWERT has excellent performance, better than seven other contemporary methods, for 84 challenging maritime videos, containing over 33,000 frames, and captured using visible range and near-infrared range sensors mounted onboard, onshore, or on floating buoys. It has a median error of about 2 pixels (less than 0.2%) from the center of the actual horizon and a median angular error of less than 0.4 deg. We are also sharing a new challenging horizon detection dataset of 65 videos of visible, infrared cameras for onshore and onboard ship camera placement.

Threshold-adaptive canny operator based on cross-zero points

NASA Astrophysics Data System (ADS)

Liu, Boqi; Zhang, Xiuhua; Hong, Hanyu

2018-03-01

Canny edge detection[1] is a technique to extract useful structural information from different vision objects and dramatically reduce the amount of data to be processed. It has been widely applied in various computer vision systems. There are two thresholds have to be settled before the edge is segregated from background. Usually, by the experience of developers, two static values are set as the thresholds[2]. In this paper, a novel automatic thresholding method is proposed. The relation between the thresholds and Cross-zero Points is analyzed, and an interpolation function is deduced to determine the thresholds. Comprehensive experimental results demonstrate the effectiveness of proposed method and advantageous for stable edge detection at changing illumination.

Wisps in the outer edge of the Keeler Gap

NASA Astrophysics Data System (ADS)

Tiscareno, Matthew S.; Arnault, Ethan G.

2015-11-01

Superposed upon the relatively smooth outer edge of the Keeler Gap are a system of "wisps," which appear to be ring material protruding inward into the gap, usually with a sharp trailing edge and a smooth gradation back to the background edge location on the leading side (Porco et al. 2005, Science). The radial amplitude of wisps is usually 0.5 to 1 km, and their azimuthal extent is approximately a degree of longitude (~2400 km). Wisps are likely caused by an interplay between Daphnis (and perhaps other moons) and embedded moonlets within the ring, though the details remain unclear.Aside from the wisps, the Keeler Gap outer edge is the only one of the five sharp edges in the outer part of Saturn's A ring that is reasonably smooth in appearance (Tiscareno et al. 2005, DPS), with occultations indicating residuals less than 1 km upon a possibly non-zero eccentricity (R.G. French, personal communication, 2014). The other four (the inner and outer edges of the Encke Gap, the inner edge of the Keeler Gap, and the outer edge of the A ring itself) are characterized by wavy structure at moderate to high spatial frequencies, with amplitudes ranging from 2 to 30 km (Tiscareno et al. 2005, DPS).We will present a catalogue of wisp detections in Cassini images. We carry out repeated gaussian fits of the radial edge location in order to characterize edge structure and visually scan those fitted edges in order to detect wisps. With extensive coverage in longitude and in time, we will report on how wisps evolve and move, both within an orbit period and on longer timescales. We will also report on the frequency and interpretation of wisps that deviate from the standard morphology. We will discuss the implications of our results for the origin and nature of wisps, and for the larger picture of how masses interact within Saturn's rings.

Comparison of birds detected from roadside and off-road point counts in the Shenandoah National Park

USGS Publications Warehouse

Keller, C.M.E.; Fuller, M.R.; Ralph, C. John; Sauer, John R.; Droege, Sam

1995-01-01

Roadside point counts are generally used for large surveys to increase the number of samples. We examined differences in species detected from roadside versus off-road (200-m and 400-ha) point counts in the Shenandoah National Park. We also compared the list of species detected in the first 3 minutes to those detected in 10 minutes for potential species biases. Results from 81 paired roadside and off-road counts indicated that roadside counts had higher numbers of several edge species but did not have lower numbers of nonedge forest species. More individuals and species were detected from roadside points because of this increase in edge species. Sixty-five percent of the species detected in 10 minutes were recorded in the first 3 minutes.

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

Li, Dengwang; Wang, Jie; Kapp, Daniel S.

Purpose: The aim of this work is to develop a robust algorithm for accurate segmentation of liver with special attention paid to the problems with fuzzy edges and tumor. Methods: 200 CT images were collected from radiotherapy treatment planning system. 150 datasets are selected as the panel data for shape dictionary and parameters estimation. The remaining 50 datasets were used as test images. In our study liver segmentation was formulated as optimization process of implicit function. The liver region was optimized via local and global optimization during iterations. Our method consists five steps: 1)The livers from the panel data weremore » segmented manually by physicians, and then We estimated the parameters of GMM (Gaussian mixture model) and MRF (Markov random field). Shape dictionary was built by utilizing the 3D liver shapes. 2)The outlines of chest and abdomen were located according to rib structure in the input images, and the liver region was initialized based on GMM. 3)The liver shape for each 2D slice was adjusted using MRF within the neighborhood of liver edge for local optimization. 4)The 3D liver shape was corrected by employing SSR (sparse shape representation) based on liver shape dictionary for global optimization. Furthermore, H-PSO(Hybrid Particle Swarm Optimization) was employed to solve the SSR equation. 5)The corrected 3D liver was divided into 2D slices as input data of the third step. The iteration was repeated within the local optimization and global optimization until it satisfied the suspension conditions (maximum iterations and changing rate). Results: The experiments indicated that our method performed well even for the CT images with fuzzy edge and tumors. Comparing with physician delineated results, the segmentation accuracy with the 50 test datasets (VOE, volume overlap percentage) was on average 91%–95%. Conclusion: The proposed automatic segmentation method provides a sensible technique for segmentation of CT images. This work is supported by NIH/NIBIB (1R01-EB016777), National Natural Science Foundation of China (No.61471226 and No.61201441), Research funding from Shandong Province (No.BS2012DX038 and No.J12LN23), and Research funding from Jinan City (No.201401221 and No.20120109)« less

X-Ray Phase Imaging for Breast Cancer Detection

DTIC Science & Technology

2011-09-01

the inline phase contrast imaging has good potential of greatly enhanc - ing the detection sensitivity and reducing radiation doses involved in the...the edge- enhancement generated by phase- contrast is generally useful for imaging the wrap, however, such edge- enhancements may lead interpretation...Kotre and I. P. Birch, “Phase contrast enhancement of x-ray mam- mography: A design study,” Phys. Med. Biol. 44, 2853–2866 (1999). 6F. Arfelli et al

Curriculum on the Edge of Survival: How Schools Fail to Prepare Students for Membership in a Democracy. 2nd Edition

ERIC Educational Resources Information Center

Heller, Daniel

2012-01-01

Typically, school curriculum has been viewed through the lens of preparation for the workplace or higher education, both worthy objectives. However, this is not the only lens, and perhaps not even the most powerful one to use, if the goal is to optimize the educational system. "Curriculum on the Edge of Survival, 2nd Edition," attempts to define…

In silico simulation of liver crack detection using ultrasonic shear wave imaging.

PubMed

Nie, Erwei; Yu, Jiao; Dutta, Debaditya; Zhu, Yanying

2018-05-16

Liver trauma is an important source of morbidity and mortality worldwide. A timely detection and precise evaluation of traumatic liver injury and the bleeding site is necessary. There is a need to develop better imaging modalities of hepatic injuries to increase the sensitivity of ultrasonic imaging techniques for sites of hemorrhage caused by cracks. In this study, we conduct an in silico simulation of liver crack detection and delineation using an ultrasonic shear wave imaging (USWI) based method. We simulate the generation and propagation of the shear wave in a liver tissue medium having a crack using COMSOL. Ultrasound radio frequency (RF) signal synthesis and the two-dimensional speckle tracking algorithm are applied to simulate USWI in a medium with randomly distributed scatterers. Crack detection is performed using the directional filter and the edge detection algorithm rather than the conventional inversion algorithm. Cracks with varied sizes and locations are studied with our method and the crack localization results are compared with the given crack. Our pilot simulation study shows that, by using USWI combined with a directional filter cum edge detection technique, the near-end edge of the crack can be detected in all the three cracks that we studied. The detection errors are within 5%. For a crack of 1.6 mm thickness, little shear wave can pass through it and the far-end edge of the crack cannot be detected. The detected crack lengths using USWI are all slightly shorter than the actual crack length. The robustness of our method in detecting a straight crack, a curved crack and a subtle crack of 0.5 mm thickness is demonstrated. In this paper, we simulate the use of a USWI based method for the detection and delineation of the crack in liver. The in silico simulation helps to improve understanding and interpretation of USWI measurements in a physical scattered liver medium with a crack. This pilot study provides a basis for improved insights in future crack detection studies in a tissue phantom or liver.

Optimization of a resazurin-based microplate assay for large-scale compound screenings against Klebsiella pneumoniae.

PubMed

Kim, Hyung Jun; Jang, Soojin

2018-01-01

A new resazurin-based assay was evaluated and optimized using a microplate (384-well) format for high-throughput screening of antibacterial molecules against Klebsiella pneumoniae . Growth of the bacteria in 384-well plates was more effectively measured and had a > sixfold higher signal-to-background ratio using the resazurin-based assay compared with absorbance measurements at 600 nm. Determination of minimum inhibitory concentrations of the antibiotics revealed that the optimized assay quantitatively measured antibacterial activity of various antibiotics. An edge effect observed in the initial assay was significantly reduced using a 1-h incubation of the bacteria-containing plates at room temperature. There was an approximately 10% decrease in signal variability between the edge and the middle wells along with improvement in the assay robustness ( Z ' = 0.99). This optimized resazurin-based assay is an efficient, inexpensive, and robust assay that can quantitatively measure antibacterial activity using a high-throughput screening system to assess a large number of compounds for discovery of new antibiotics against K. pneumoniae .

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Flight-Test Results

NASA Technical Reports Server (NTRS)

Brown, Nelson Andrew; Schaefer, Jacob Robert

2013-01-01

A peak-seeking control algorithm for real-time trim optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control algorithm is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are used for optimization of fuel flow. Results from six research flights are presented herein. The optimization algorithm found a trim configuration that required approximately 3 percent less fuel flow than the baseline trim at the same flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These results show that the algorithm has good performance in a relevant environment.

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Flight-test Results

NASA Technical Reports Server (NTRS)

Brown, Nelson Andrew; Schaefer, Jacob Robert

2013-01-01

A peak-seeking control algorithm for real-time trim optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control algorithm is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are used for optimization of fuel flow. Results from six research flights are presented herein. The optimization algorithm found a trim configuration that required approximately 3 percent less fuel flow than the baseline trim at the same flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These results show that the algorithm has good performance in a relevant environment.

Peak Seeking Control for Reduced Fuel Consumption with Preliminary Flight Test Results

NASA Technical Reports Server (NTRS)

Brown, Nelson

2012-01-01

The Environmentally Responsible Aviation project seeks to accomplish the simultaneous reduction of fuel burn, noise, and emissions. A project at NASA Dryden Flight Research Center is contributing to ERAs goals by exploring the practical application of real-time trim configuration optimization for enhanced performance and reduced fuel consumption. This peak-seeking control approach is based on Newton-Raphson algorithm using a time-varying Kalman filter to estimate the gradient of the performance function. In real-time operation, deflection of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of a modified F-18 are directly optimized, and the horizontal stabilators and angle of attack are indirectly optimized. Preliminary results from three research flights are presented herein. The optimization system found a trim configuration that required approximately 3.5% less fuel flow than the baseline trim at the given flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These preliminary results show the algorithm has good performance and is expected to show similar results at other flight conditions and aircraft configurations.

Computer vision, camouflage breaking and countershading

PubMed Central

Tankus, Ariel; Yeshurun, Yehezkel

2008-01-01

Camouflage is frequently used in the animal kingdom in order to conceal oneself from visual detection or surveillance. Many camouflage techniques are based on masking the familiar contours and texture of the subject by superposition of multiple edges on top of it. This work presents an operator, Darg, for the detection of three-dimensional smooth convex (or, equivalently, concave) objects. It can be used to detect curved objects on a relatively flat background, regardless of image edges, contours and texture. We show that a typical camouflage found in some animal species seems to be a ‘countermeasure’ taken against detection that might be based on our method. Detection by Darg is shown to be very robust, from both theoretical considerations and practical examples of real-life images. PMID:18990669

Numerical optimization of three-dimensional coils for NSTX-U

NASA Astrophysics Data System (ADS)

Lazerson, S. A.; Park, J.-K.; Logan, N.; Boozer, A.

2015-10-01

A tool for the calculation of optimal three-dimensional (3D) perturbative magnetic fields in tokamaks has been developed. The IPECOPT code builds upon the stellarator optimization code STELLOPT to allow for optimization of linear ideal magnetohydrodynamic perturbed equilibrium (IPEC). This tool has been applied to NSTX-U equilibria, addressing which fields are the most effective at driving NTV torques. The NTV torque calculation is performed by the PENT code. Optimization of the normal field spectrum shows that fields with n  =  1 character can drive a large core torque. It is also shown that fields with n  =  3 features are capable of driving edge torque and some core torque. Coil current optimization (using the planned in-vessel and existing RWM coils) on NSTX-U suggest the planned coils set is adequate for core and edge torque control. Comparison between error field correction experiments on DIII-D and the optimizer show good agreement. Notice: This manuscript has been authored by Princeton University under Contract Number DE-AC02-09CH11466 with the U.S. Department of Energy. The publisher, by accepting the article for publication acknowledges, that the United States Government retains a non-exclusive,paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

Assessment of AVIRIS data from vegetated sites in the Owens Valley, California

NASA Technical Reports Server (NTRS)

Rock, B. N.; Elvidge, Christopher D.; Defeo, N. J.

1988-01-01

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were acquired from the Bishop, CA area, located at the northern end of the Owens Valley, on July 30, 1987. Radiometrically-corrected AVIRIS data were flat-field corrected, and spectral curves produced and analyzed for pixels taken from both native and cultivated vegetation sites, using the JPS SPAM software program and PC-based spreadsheet programs. Analyses focussed on the chlorophyll well and red edge portions of the spectral curves. Results include the following: AVIRIS spectral data are acquired at sufficient spectral resolution to allow detection of blue shifts of both the chlorophyll well and red edge in moisture-stressed vegetation when compared with non-stressed vegetation; a normalization of selected parameters (chlorophyll well and near infrared shoulder) may be used to emphasize the shift in red edge position; and the presence of the red edge in AVIRIS spectral curves may be useful in detecting small amounts (20 to 30 pct cover) of semi-arid and arid vegetation ground cover. A discussion of possible causes of AVIRIS red edge shifts in respsonse to stress is presented.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

PubMed

Villaverde, Monica; Perez, David; Moreno, Felix

2015-11-17

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Strain-Dependent Edge Structures in MoS2 Layers.

PubMed

Tinoco, Miguel; Maduro, Luigi; Masaki, Mukai; Okunishi, Eiji; Conesa-Boj, Sonia

2017-11-08

Edge structures are low-dimensional defects unavoidable in layered materials of the transition metal dichalcogenides (TMD) family. Among the various types of such structures, the armchair (AC) and zigzag (ZZ) edge types are the most common. It has been predicted that the presence of intrinsic strain localized along these edges structures can have direct implications for the customization of their electronic properties. However, pinning down the relation between local structure and electronic properties at these edges is challenging. Here, we quantify the local strain field that arises at the edges of MoS 2 flakes by combining aberration-corrected transmission electron microscopy (TEM) with the geometrical-phase analysis (GPA) method. We also provide further insight on the possible effects of such edge strain on the resulting electronic behavior by means of electron energy loss spectroscopy (EELS) measurements. Our results reveal that the two-dominant edge structures, ZZ and AC, induce the formation of different amounts of localized strain fields. We also show that by varying the free edge curvature from concave to convex, compressive strain turns into tensile strain. These results pave the way toward the customization of edge structures in MoS 2 , which can be used to engineer the properties of layered materials and thus contribute to the optimization of the next generation of atomic-scale electronic devices built upon them.

The Double Edge Technique for Doppler lidar wind measurement

NASA Technical Reports Server (NTRS)

Korb, C. Laurence; Gentry, Bruce M.; Li, S. Xingfu; Flesia, Cristina; Chen, Huailin; Mathur, S.

1998-01-01

The edge technique utilizes the edge of a high spectral resolution filter for high accuracy wind measurement using direct detection lidar. The signal is split between an edge filter channel and a broadband energy monitor channel. The energy monitor channel is used for signal normalization. The edge measurement is made as a differential frequency measurement between the outgoing laser signal and the atmospheric backscattered return for each pulse. As a result, the measurement is insensitive to laser and edge filter frequency jitter and drift at a level less than a few parts in 10(exp 10). We will discuss the methodology of the technique in detail, present a broad range of simulation results, and provide preprints of a journal article currently in press.

Effects of dwell time of excitation waveform on meniscus movements for a tubular piezoelectric print-head: experiments and model

NASA Astrophysics Data System (ADS)

Chang, Jiaqing; Liu, Yaxin; Huang, Bo

2017-07-01

In inkjet applications, it is normal to search for an optimal drive waveform when dispensing a fresh fluid or adjusting a newly fabricated print-head. To test trial waveforms with different dwell times, a camera and a strobe light were used to image the protruding or retracting liquid tongues without ejecting any droplets. An edge detection method was used to calculate the lengths of the liquid tongues to draw the meniscus movement curves. The meniscus movement is determined by the time-domain response of the acoustic pressure at the nozzle of the print-head. Starting at the inverse piezoelectric effect, a mathematical model which considers the liquid viscosity in acoustic propagation is constructed to study the acoustic pressure response at the nozzle of the print-head. The liquid viscosity retards the propagation speed and dampens the harmonic amplitude. The pressure response, which is the combined effect of the acoustic pressures generated during the rising time and the falling time and after their propagations and reflections, explains the meniscus movements well. Finally, the optimal dwell time for droplet ejections is discussed.

A geometrically based method for automated radiosurgery planning.

PubMed

Wagner, T H; Yi, T; Meeks, S L; Bova, F J; Brechner, B L; Chen, Y; Buatti, J M; Friedman, W A; Foote, K D; Bouchet, L G

2000-12-01

A geometrically based method of multiple isocenter linear accelerator radiosurgery treatment planning optimization was developed, based on a target's solid shape. Our method uses an edge detection process to determine the optimal sphere packing arrangement with which to cover the planning target. The sphere packing arrangement is converted into a radiosurgery treatment plan by substituting the isocenter locations and collimator sizes for the spheres. This method is demonstrated on a set of 5 irregularly shaped phantom targets, as well as a set of 10 clinical example cases ranging from simple to very complex in planning difficulty. Using a prototype implementation of the method and standard dosimetric radiosurgery treatment planning tools, feasible treatment plans were developed for each target. The treatment plans generated for the phantom targets showed excellent dose conformity and acceptable dose homogeneity within the target volume. The algorithm was able to generate a radiosurgery plan conforming to the Radiation Therapy Oncology Group (RTOG) guidelines on radiosurgery for every clinical and phantom target examined. This automated planning method can serve as a valuable tool to assist treatment planners in rapidly and consistently designing conformal multiple isocenter radiosurgery treatment plans.

Analog "neuronal" networks in early vision.

PubMed Central

Koch, C; Marroquin, J; Yuille, A

1986-01-01

Many problems in early vision can be formulated in terms of minimizing a cost function. Examples are shape from shading, edge detection, motion analysis, structure from motion, and surface interpolation. As shown by Poggio and Koch [Poggio, T. & Koch, C. (1985) Proc. R. Soc. London, Ser. B 226, 303-323], quadratic variational problems, an important subset of early vision tasks, can be "solved" by linear, analog electrical, or chemical networks. However, in the presence of discontinuities, the cost function is nonquadratic, raising the question of designing efficient algorithms for computing the optimal solution. Recently, Hopfield and Tank [Hopfield, J. J. & Tank, D. W. (1985) Biol. Cybern. 52, 141-152] have shown that networks of nonlinear analog "neurons" can be effective in computing the solution of optimization problems. We show how these networks can be generalized to solve the nonconvex energy functionals of early vision. We illustrate this approach by implementing a specific analog network, solving the problem of reconstructing a smooth surface from sparse data while preserving its discontinuities. These results suggest a novel computational strategy for solving early vision problems in both biological and real-time artificial vision systems. PMID:3459172

Image steganography based on 2k correction and coherent bit length

NASA Astrophysics Data System (ADS)

Sun, Shuliang; Guo, Yongning

2014-10-01

In this paper, a novel algorithm is proposed. Firstly, the edge of cover image is detected with Canny operator and secret data is embedded in edge pixels. Sorting method is used to randomize the edge pixels in order to enhance security. Coherent bit length L is determined by relevant edge pixels. Finally, the method of 2k correction is applied to achieve better imperceptibility in stego image. The experiment shows that the proposed method is better than LSB-3 and Jae-Gil Yu's in PSNR and capacity.

Fast Edge Detection and Segmentation of Terrestrial Laser Scans Through Normal Variation Analysis

NASA Astrophysics Data System (ADS)

Che, E.; Olsen, M. J.

2017-09-01

Terrestrial Laser Scanning (TLS) utilizes light detection and ranging (lidar) to effectively and efficiently acquire point cloud data for a wide variety of applications. Segmentation is a common procedure of post-processing to group the point cloud into a number of clusters to simplify the data for the sequential modelling and analysis needed for most applications. This paper presents a novel method to rapidly segment TLS data based on edge detection and region growing. First, by computing the projected incidence angles and performing the normal variation analysis, the silhouette edges and intersection edges are separated from the smooth surfaces. Then a modified region growing algorithm groups the points lying on the same smooth surface. The proposed method efficiently exploits the gridded scan pattern utilized during acquisition of TLS data from most sensors and takes advantage of parallel programming to process approximately 1 million points per second. Moreover, the proposed segmentation does not require estimation of the normal at each point, which limits the errors in normal estimation propagating to segmentation. Both an indoor and outdoor scene are used for an experiment to demonstrate and discuss the effectiveness and robustness of the proposed segmentation method.

Structure-adaptive CBCT reconstruction using weighted total variation and Hessian penalties

PubMed Central

Shi, Qi; Sun, Nanbo; Sun, Tao; Wang, Jing; Tan, Shan

2016-01-01

The exposure of normal tissues to high radiation during cone-beam CT (CBCT) imaging increases the risk of cancer and genetic defects. Statistical iterative algorithms with the total variation (TV) penalty have been widely used for low dose CBCT reconstruction, with state-of-the-art performance in suppressing noise and preserving edges. However, TV is a first-order penalty and sometimes leads to the so-called staircase effect, particularly over regions with smooth intensity transition in the reconstruction images. A second-order penalty known as the Hessian penalty was recently used to replace TV to suppress the staircase effect in CBCT reconstruction at the cost of slightly blurring object edges. In this study, we proposed a new penalty, the TV-H, which combines TV and Hessian penalties for CBCT reconstruction in a structure-adaptive way. The TV-H penalty automatically differentiates the edges, gradual transition and uniform local regions within an image using the voxel gradient, and adaptively weights TV and Hessian according to the local image structures in the reconstruction process. Our proposed penalty retains the benefits of TV, including noise suppression and edge preservation. It also maintains the structures in regions with gradual intensity transition more successfully. A majorization-minimization (MM) approach was designed to optimize the objective energy function constructed with the TV-H penalty. The MM approach employed a quadratic upper bound of the original objective function, and the original optimization problem was changed to a series of quadratic optimization problems, which could be efficiently solved using the Gauss-Seidel update strategy. We tested the reconstruction algorithm on two simulated digital phantoms and two physical phantoms. Our experiments indicated that the TV-H penalty visually and quantitatively outperformed both TV and Hessian penalties. PMID:27699100

Structure-adaptive CBCT reconstruction using weighted total variation and Hessian penalties.

PubMed

Shi, Qi; Sun, Nanbo; Sun, Tao; Wang, Jing; Tan, Shan

2016-09-01

The exposure of normal tissues to high radiation during cone-beam CT (CBCT) imaging increases the risk of cancer and genetic defects. Statistical iterative algorithms with the total variation (TV) penalty have been widely used for low dose CBCT reconstruction, with state-of-the-art performance in suppressing noise and preserving edges. However, TV is a first-order penalty and sometimes leads to the so-called staircase effect, particularly over regions with smooth intensity transition in the reconstruction images. A second-order penalty known as the Hessian penalty was recently used to replace TV to suppress the staircase effect in CBCT reconstruction at the cost of slightly blurring object edges. In this study, we proposed a new penalty, the TV-H, which combines TV and Hessian penalties for CBCT reconstruction in a structure-adaptive way. The TV-H penalty automatically differentiates the edges, gradual transition and uniform local regions within an image using the voxel gradient, and adaptively weights TV and Hessian according to the local image structures in the reconstruction process. Our proposed penalty retains the benefits of TV, including noise suppression and edge preservation. It also maintains the structures in regions with gradual intensity transition more successfully. A majorization-minimization (MM) approach was designed to optimize the objective energy function constructed with the TV-H penalty. The MM approach employed a quadratic upper bound of the original objective function, and the original optimization problem was changed to a series of quadratic optimization problems, which could be efficiently solved using the Gauss-Seidel update strategy. We tested the reconstruction algorithm on two simulated digital phantoms and two physical phantoms. Our experiments indicated that the TV-H penalty visually and quantitatively outperformed both TV and Hessian penalties.

Identification of jasmine flower (Jasminum sp.) based on the shape of the flower using sobel edge and k-nearest neighbour

NASA Astrophysics Data System (ADS)

Qur’ania, A.; Sarinah, I.

2018-03-01

People often wrong in knowing the type of jasmine by just looking at the white color of the jasmine, while not all white flowers including jasmine and not all jasmine flowers have white. There is a jasmine that is yellow and there is a jasmine that is white and purple.The aim of this research is to identify Jasmine flower (Jasminum sp.) based on the shape of the flower image-based using Sobel edge detection and k-Nearest Neighbor. Edge detection is used to detect the type of flower from the flower shape. Edge detection aims to improve the appearance of the border of a digital image. While k-Nearest Neighbor method is used to classify the classification of test objects into classes that have neighbouring properties closest to the object of training. The data used in this study are three types of jasmine namely jasmine white (Jasminum sambac), jasmine gambir (Jasminum pubescens), and jasmine japan (Pseuderanthemum reticulatum). Testing of jasmine flower image resized 50 × 50 pixels, 100 × 100 pixels, 150 × 150 pixels yields an accuracy of 84%. Tests on distance values of the k-NN method with spacing 5, 10 and 15 resulted in different accuracy rates for 5 and 10 closest distances yielding the same accuracy rate of 84%, for the 15 shortest distance resulted in a small accuracy of 65.2%.

Bayesian segmentation of atrium wall using globally-optimal graph cuts on 3D meshes.

PubMed

Veni, Gopalkrishna; Fu, Zhisong; Awate, Suyash P; Whitaker, Ross T

2013-01-01

Efficient segmentation of the left atrium (LA) wall from delayed enhancement MRI is challenging due to inconsistent contrast, combined with noise, and high variation in atrial shape and size. We present a surface-detection method that is capable of extracting the atrial wall by computing an optimal a-posteriori estimate. This estimation is done on a set of nested meshes, constructed from an ensemble of segmented training images, and graph cuts on an associated multi-column, proper-ordered graph. The graph/mesh is a part of a template/model that has an associated set of learned intensity features. When this mesh is overlaid onto a test image, it produces a set of costs which lead to an optimal segmentation. The 3D mesh has an associated weighted, directed multi-column graph with edges that encode smoothness and inter-surface penalties. Unlike previous graph-cut methods that impose hard constraints on the surface properties, the proposed method follows from a Bayesian formulation resulting in soft penalties on spatial variation of the cuts through the mesh. The novelty of this method also lies in the construction of proper-ordered graphs on complex shapes for choosing among distinct classes of base shapes for automatic LA segmentation. We evaluate the proposed segmentation framework on simulated and clinical cardiac MRI.

An algorithm for automatic parameter adjustment for brain extraction in BrainSuite

NASA Astrophysics Data System (ADS)

Rajagopal, Gautham; Joshi, Anand A.; Leahy, Richard M.

2017-02-01

Brain Extraction (classification of brain and non-brain tissue) of MRI brain images is a crucial pre-processing step necessary for imaging-based anatomical studies of the human brain. Several automated methods and software tools are available for performing this task, but differences in MR image parameters (pulse sequence, resolution) and instrumentand subject-dependent noise and artefacts affect the performance of these automated methods. We describe and evaluate a method that automatically adapts the default parameters of the Brain Surface Extraction (BSE) algorithm to optimize a cost function chosen to reflect accurate brain extraction. BSE uses a combination of anisotropic filtering, Marr-Hildreth edge detection, and binary morphology for brain extraction. Our algorithm automatically adapts four parameters associated with these steps to maximize the brain surface area to volume ratio. We evaluate the method on a total of 109 brain volumes with ground truth brain masks generated by an expert user. A quantitative evaluation of the performance of the proposed algorithm showed an improvement in the mean (s.d.) Dice coefficient from 0.8969 (0.0376) for default parameters to 0.9509 (0.0504) for the optimized case. These results indicate that automatic parameter optimization can result in significant improvements in definition of the brain mask.

Layout optimization of DRAM cells using rigorous simulation model for NTD

NASA Astrophysics Data System (ADS)

Jeon, Jinhyuck; Kim, Shinyoung; Park, Chanha; Yang, Hyunjo; Yim, Donggyu; Kuechler, Bernd; Zimmermann, Rainer; Muelders, Thomas; Klostermann, Ulrich; Schmoeller, Thomas; Do, Mun-hoe; Choi, Jung-Hoe

2014-03-01

DRAM chip space is mainly determined by the size of the memory cell array patterns which consist of periodic memory cell features and edges of the periodic array. Resolution Enhancement Techniques (RET) are used to optimize the periodic pattern process performance. Computational Lithography such as source mask optimization (SMO) to find the optimal off axis illumination and optical proximity correction (OPC) combined with model based SRAF placement are applied to print patterns on target. For 20nm Memory Cell optimization we see challenges that demand additional tool competence for layout optimization. The first challenge is a memory core pattern of brick-wall type with a k1 of 0.28, so it allows only two spectral beams to interfere. We will show how to analytically derive the only valid geometrically limited source. Another consequence of two-beam interference limitation is a "super stable" core pattern, with the advantage of high depth of focus (DoF) but also low sensitivity to proximity corrections or changes of contact aspect ratio. This makes an array edge correction very difficult. The edge can be the most critical pattern since it forms the transition from the very stable regime of periodic patterns to non-periodic periphery, so it combines the most critical pitch and highest susceptibility to defocus. Above challenge makes the layout correction to a complex optimization task demanding a layout optimization that finds a solution with optimal process stability taking into account DoF, exposure dose latitude (EL), mask error enhancement factor (MEEF) and mask manufacturability constraints. This can only be achieved by simultaneously considering all criteria while placing and sizing SRAFs and main mask features. The second challenge is the use of a negative tone development (NTD) type resist, which has a strong resist effect and is difficult to characterize experimentally due to negative resist profile taper angles that perturb CD at bottom characterization by scanning electron microscope (SEM) measurements. High resist impact and difficult model data acquisition demand for a simulation model that hat is capable of extrapolating reliably beyond its calibration dataset. We use rigorous simulation models to provide that predictive performance. We have discussed the need of a rigorous mask optimization process for DRAM contact cell layout yielding mask layouts that are optimal in process performance, mask manufacturability and accuracy. In this paper, we have shown the step by step process from analytical illumination source derivation, a NTD and application tailored model calibration to layout optimization such as OPC and SRAF placement. Finally the work has been verified with simulation and experimental results on wafer.

On the Design of Smart Parking Networks in the Smart Cities: An Optimal Sensor Placement Model

PubMed Central

Bagula, Antoine; Castelli, Lorenzo; Zennaro, Marco

2015-01-01

Smart parking is a typical IoT application that can benefit from advances in sensor, actuator and RFID technologies to provide many services to its users and parking owners of a smart city. This paper considers a smart parking infrastructure where sensors are laid down on the parking spots to detect car presence and RFID readers are embedded into parking gates to identify cars and help in the billing of the smart parking. Both types of devices are endowed with wired and wireless communication capabilities for reporting to a gateway where the situation recognition is performed. The sensor devices are tasked to play one of the three roles: (1) slave sensor nodes located on the parking spot to detect car presence/absence; (2) master nodes located at one of the edges of a parking lot to detect presence and collect the sensor readings from the slave nodes; and (3) repeater sensor nodes, also called “anchor” nodes, located strategically at specific locations in the parking lot to increase the coverage and connectivity of the wireless sensor network. While slave and master nodes are placed based on geographic constraints, the optimal placement of the relay/anchor sensor nodes in smart parking is an important parameter upon which the cost and efficiency of the parking system depends. We formulate the optimal placement of sensors in smart parking as an integer linear programming multi-objective problem optimizing the sensor network engineering efficiency in terms of coverage and lifetime maximization, as well as its economic gain in terms of the number of sensors deployed for a specific coverage and lifetime. We propose an exact solution to the node placement problem using single-step and two-step solutions implemented in the Mosel language based on the Xpress-MPsuite of libraries. Experimental results reveal the relative efficiency of the single-step compared to the two-step model on different performance parameters. These results are consolidated by simulation results, which reveal that our solution outperforms a random placement in terms of both energy consumption, delay and throughput achieved by a smart parking network. PMID:26134104

On the Design of Smart Parking Networks in the Smart Cities: An Optimal Sensor Placement Model.

PubMed

Bagula, Antoine; Castelli, Lorenzo; Zennaro, Marco

2015-06-30

Smart parking is a typical IoT application that can benefit from advances in sensor, actuator and RFID technologies to provide many services to its users and parking owners of a smart city. This paper considers a smart parking infrastructure where sensors are laid down on the parking spots to detect car presence and RFID readers are embedded into parking gates to identify cars and help in the billing of the smart parking. Both types of devices are endowed with wired and wireless communication capabilities for reporting to a gateway where the situation recognition is performed. The sensor devices are tasked to play one of the three roles: (1) slave sensor nodes located on the parking spot to detect car presence/absence; (2) master nodes located at one of the edges of a parking lot to detect presence and collect the sensor readings from the slave nodes; and (3) repeater sensor nodes, also called "anchor" nodes, located strategically at specific locations in the parking lot to increase the coverage and connectivity of the wireless sensor network. While slave and master nodes are placed based on geographic constraints, the optimal placement of the relay/anchor sensor nodes in smart parking is an important parameter upon which the cost and efficiency of the parking system depends. We formulate the optimal placement of sensors in smart parking as an integer linear programming multi-objective problem optimizing the sensor network engineering efficiency in terms of coverage and lifetime maximization, as well as its economic gain in terms of the number of sensors deployed for a specific coverage and lifetime. We propose an exact solution to the node placement problem using single-step and two-step solutions implemented in the Mosel language based on the Xpress-MPsuite of libraries. Experimental results reveal the relative efficiency of the single-step compared to the two-step model on different performance parameters. These results are consolidated by simulation results, which reveal that our solution outperforms a random placement in terms of both energy consumption, delay and throughput achieved by a smart parking network.

Feature extraction and classification of clouds in high resolution panchromatic satellite imagery

NASA Astrophysics Data System (ADS)

Sharghi, Elan

The development of sophisticated remote sensing sensors is rapidly increasing, and the vast amount of satellite imagery collected is too much to be analyzed manually by a human image analyst. It has become necessary for a tool to be developed to automate the job of an image analyst. This tool would need to intelligently detect and classify objects of interest through computer vision algorithms. Existing software called the Rapid Image Exploitation Resource (RAPIER®) was designed by engineers at Space and Naval Warfare Systems Center Pacific (SSC PAC) to perform exactly this function. This software automatically searches for anomalies in the ocean and reports the detections as a possible ship object. However, if the image contains a high percentage of cloud coverage, a high number of false positives are triggered by the clouds. The focus of this thesis is to explore various feature extraction and classification methods to accurately distinguish clouds from ship objects. An examination of a texture analysis method, line detection using the Hough transform, and edge detection using wavelets are explored as possible feature extraction methods. The features are then supplied to a K-Nearest Neighbors (KNN) or Support Vector Machine (SVM) classifier. Parameter options for these classifiers are explored and the optimal parameters are determined.

Dual Energy Method for Breast Imaging: A Simulation Study.

PubMed

Koukou, V; Martini, N; Michail, C; Sotiropoulou, P; Fountzoula, C; Kalyvas, N; Kandarakis, I; Nikiforidis, G; Fountos, G

2015-01-01

Dual energy methods can suppress the contrast between adipose and glandular tissues in the breast and therefore enhance the visibility of calcifications. In this study, a dual energy method based on analytical modeling was developed for the detection of minimum microcalcification thickness. To this aim, a modified radiographic X-ray unit was considered, in order to overcome the limited kVp range of mammographic units used in previous DE studies, combined with a high resolution CMOS sensor (pixel size of 22.5 μm) for improved resolution. Various filter materials were examined based on their K-absorption edge. Hydroxyapatite (HAp) was used to simulate microcalcifications. The contrast to noise ratio (CNR tc ) of the subtracted images was calculated for both monoenergetic and polyenergetic X-ray beams. The optimum monoenergetic pair was 23/58 keV for the low and high energy, respectively, resulting in a minimum detectable microcalcification thickness of 100 μm. In the polyenergetic X-ray study, the optimal spectral combination was 40/70 kVp filtered with 100 μm cadmium and 1000 μm copper, respectively. In this case, the minimum detectable microcalcification thickness was 150 μm. The proposed dual energy method provides improved microcalcification detectability in breast imaging with mean glandular dose values within acceptable levels.

Dual Energy Method for Breast Imaging: A Simulation Study

PubMed Central

2015-01-01

Dual energy methods can suppress the contrast between adipose and glandular tissues in the breast and therefore enhance the visibility of calcifications. In this study, a dual energy method based on analytical modeling was developed for the detection of minimum microcalcification thickness. To this aim, a modified radiographic X-ray unit was considered, in order to overcome the limited kVp range of mammographic units used in previous DE studies, combined with a high resolution CMOS sensor (pixel size of 22.5 μm) for improved resolution. Various filter materials were examined based on their K-absorption edge. Hydroxyapatite (HAp) was used to simulate microcalcifications. The contrast to noise ratio (CNRtc) of the subtracted images was calculated for both monoenergetic and polyenergetic X-ray beams. The optimum monoenergetic pair was 23/58 keV for the low and high energy, respectively, resulting in a minimum detectable microcalcification thickness of 100 μm. In the polyenergetic X-ray study, the optimal spectral combination was 40/70 kVp filtered with 100 μm cadmium and 1000 μm copper, respectively. In this case, the minimum detectable microcalcification thickness was 150 μm. The proposed dual energy method provides improved microcalcification detectability in breast imaging with mean glandular dose values within acceptable levels. PMID:26246848

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

Mihailescu, Lucian

This disclosure provides systems, methods, and apparatus related to ion beam therapy. In one aspect, a system includes a position sensitive detector and a collimator. The position sensitive detector configured to detect gamma rays generated by an ion beam interacting with a target. The collimator is positioned between the target and the position sensitive detector. The collimator includes a plurality of knife-edge slits, with a first knife-edge slit intersecting with a second knife-edge slit.

Detection of radon emission at the edges of lunar maria with the Apollo alpha-particle spectrometer

NASA Technical Reports Server (NTRS)

Gorenstein, P.; Golub, L.; Bjorkholm, P.

1974-01-01

The distribution of radioactive polonium-210, a decay product of radon-222, shows enhanced concentrations at the edges of lunar maria. Enhancements are seen at the edges of Mare Fecunditatis, Mare Crisium, Mare Smythii, Mare Tranquillitatis, Mare Nubium, Mare Cognitum, and Oceanus Procellarum. The observation is indicative of the transient emission of radon gas from the perimeters of lunar maria.

Detection of radon emission at the edges of lunar maria with the apollo alpha-particle spectrometer

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

Gorenstein, P.; Golub, L.; Bjorkholm, P.

1974-02-01

The distribution of radioactive /sup 210/Po, a decay product of /sup 222/ Rn, shows enhanced concentrations at the edges of lunar maria. Enhancements are seen at the edges of Mare Fecunditatis, Mare Crisium, Mare Smythii, Mare Tranquillitatis, Mare Nubium, Mare Cognitum, and Oceanus Procellarum. The observation is indicative of the transient emission of radon gas from the perimeters of lunar maria. (auth)

Integration of adaptive guided filtering, deep feature learning, and edge-detection techniques for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Wan, Xiaoqing; Zhao, Chunhui; Gao, Bing

2017-11-01

The integration of an edge-preserving filtering technique in the classification of a hyperspectral image (HSI) has been proven effective in enhancing classification performance. This paper proposes an ensemble strategy for HSI classification using an edge-preserving filter along with a deep learning model and edge detection. First, an adaptive guided filter is applied to the original HSI to reduce the noise in degraded images and to extract powerful spectral-spatial features. Second, the extracted features are fed as input to a stacked sparse autoencoder to adaptively exploit more invariant and deep feature representations; then, a random forest classifier is applied to fine-tune the entire pretrained network and determine the classification output. Third, a Prewitt compass operator is further performed on the HSI to extract the edges of the first principal component after dimension reduction. Moreover, the regional growth rule is applied to the resulting edge logical image to determine the local region for each unlabeled pixel. Finally, the categories of the corresponding neighborhood samples are determined in the original classification map; then, the major voting mechanism is implemented to generate the final output. Extensive experiments proved that the proposed method achieves competitive performance compared with several traditional approaches.

Antigens in electron-dense granules from Entamoeba histolytica as possible markers for pathogenicity.

PubMed Central

Muñoz, M L; Lamoyi, E; León, G; Tovar, R; Pérez-García, J; De La Torre, M; Murueta, E; Bernal, R M

1990-01-01

In vitro interaction of Entamoeba histolytica with collagen induces intracellular formation and release of electron-dense granules (EDG) and stimulation of collagenolytic activity. Purified EDG contain 1.66 U of collagenase per mg of protein. Thus, EDG may participate in tissue destruction during invasive amebiasis. Monoclonal antibodies (MAbs) L1.1 and L7.1 reacted specifically with EDG in enzyme-linked immunosorbent assay (ELISA) and immunofluorescence and immunoelectron microscopy. MAb L7.1 immunoprecipitated three polypeptides with molecular weights of 95,000, 68,000, and 28,000 from lysates of biosynthetically labeled E. histolytica. Both MAbs recognized the pathogenic E. histolytica axenic strains HM1:IMSS, HM38:IMSS, and HK-9 but failed to react in ELISA with Entamoeba moshkovskii, Entamoeba invadens, and E. histolytica-like Laredo. In addition, MAb L7.1 reacted with one E. histolytica isolate from a symptomatic patient but did not react with four of five isolates from asymptomatic patients. EDG antigens were detected by a MAb L7.1-based ELISA in E. histolytica-containing fecal samples from symptomatic, but not asymptomatic, individuals. These results suggest that the EDG antigen detected with MAb L7.1 may be differentially expressed in pathogenic and nonpathogenic E. histolytica. Images PMID:2174899

Optimizing the Router Configurations within a Nominal Air Force Base

DTIC Science & Technology

2009-09-01

cardinality of V, and the size of G is the cardinality of E. For the purposes of this thesis, the vertices represent individual pieces of...edges with cardinality smaller than k leaves a connected graph. Given a connected graph G, if there is an edge e in G such that its removal results in...CDR Michael Herrera Naval Postgraduate School Monterey, California 4. Ray Elliott Naval Postgraduate School Monterey, California 5. Craig

Modeling Skill Growth and Decay in Edge Organizations: Near-Optimizing Knowledge and Power Flows (Phase Two)

DTIC Science & Technology

2006-06-01

cost to hold it. With respect to knowledge inventory, each policy exhibits both desirable and undesirable traits. JIT seeks to accrue knowledge...Management approach. Introduction and Motivation Edge organizations [1] can only achieve their putative effectiveness through the...EOQ) and cost analysis, as well as inventory doctrines of Just-In-Case (JIC), Just-In-Time ( JIT ), and make vs. buy decisions, we examined knowledge

Laser Truss Sensor for Segmented Telescope Phasing

NASA Technical Reports Server (NTRS)

Liu, Duncan T.; Lay, Oliver P.; Azizi, Alireza; Erlig, Herman; Dorsky, Leonard I.; Asbury, Cheryl G.; Zhao, Feng

2011-01-01

A paper describes the laser truss sensor (LTS) for detecting piston motion between two adjacent telescope segment edges. LTS is formed by two point-to-point laser metrology gauges in a crossed geometry. A high-resolution (<30 nm) LTS can be implemented with existing laser metrology gauges. The distance change between the reference plane and the target plane is measured as a function of the phase change between the reference and target beams. To ease the bandwidth requirements for phase detection electronics (or phase meter), homodyne or heterodyne detection techniques have been used. The phase of the target beam also changes with the refractive index of air, which changes with the air pressure, temperature, and humidity. This error can be minimized by enclosing the metrology beams in baffles. For longer-term (weeks) tracking at the micron level accuracy, the same gauge can be operated in the absolute metrology mode with an accuracy of microns; to implement absolute metrology, two laser frequencies will be used on the same gauge. Absolute metrology using heterodyne laser gauges is a demonstrated technology. Complexity of laser source fiber distribution can be optimized using the range-gated metrology (RGM) approach.

Acoustic Emission Detection of Impact Damage on Space Shuttle Structures

NASA Technical Reports Server (NTRS)

Prosser, William H.; Gorman, Michael R.; Madaras, Eric I.

2004-01-01

The loss of the Space Shuttle Columbia as a result of impact damage from foam debris during ascent has led NASA to investigate the feasibility of on-board impact detection technologies. AE sensing has been utilized to monitor a wide variety of impact conditions on Space Shuttle components ranging from insulating foam and ablator materials, and ice at ascent velocities to simulated hypervelocity micrometeoroid and orbital debris impacts. Impact testing has been performed on both reinforced carbon composite leading edge materials as well as Shuttle tile materials on representative aluminum wing structures. Results of these impact tests will be presented with a focus on the acoustic emission sensor responses to these impact conditions. These tests have demonstrated the potential of employing an on-board Shuttle impact detection system. We will describe the present plans for implementation of an initial, very low frequency acoustic impact sensing system using pre-existing flight qualified hardware. The details of an accompanying flight measurement system to assess the Shuttle s acoustic background noise environment as a function of frequency will be described. The background noise assessment is being performed to optimize the frequency range of sensing for a planned future upgrade to the initial impact sensing system.

Photocurrent enhancement of graphene photodetectors by photon tunneling of light into surface plasmons

NASA Astrophysics Data System (ADS)

Maleki, Alireza; Cumming, Benjamin P.; Gu, Min; Downes, James E.; Coutts, David W.; Dawes, Judith M.

2017-10-01

We demonstrate that surface plasmon resonances excited by photon tunneling through an adjacent dielectric medium enhance the photocurrent detected by a graphene photodetector. The device is created by overlaying a graphene sheet over an etched gap in a gold film deposited on glass. The detected photocurrents are compared for five different excitation wavelengths, ranging from {λ }0=570 {{nm}} to {λ }0=730 {{nm}}. Although the device is not optimized, the photocurrent excited with incident p-polarized light (which excites resonant surface plasmons) is significantly amplified in comparison with that for s-polarized light (without surface plasmon resonances). We observe that the photocurrent is greater for shorter wavelengths (for both s- and p-polarizations) with increased photothermal current. Position-dependent Raman spectroscopic analysis of the optically-excited graphene photodetector indicates the presence of charge carriers in the graphene near the metallic edge. In addition, we show that the polarity of the photocurrent reverses across the gap as the incident light spot moves across the gap. Graphene-based photodetectors offer a simple architecture which can be fabricated on dielectric waveguides to exploit the plasmonic photocurrent enhancement of the evanescent field. Applications for these devices include photodetection, optical sensing and direct plasmonic detection.

Bio-Inspired Control of Roughness and Trailing Edge Noise

NASA Astrophysics Data System (ADS)

Clark, Ian Andrew

Noise from fluid flow over rough surfaces is an important consideration in the design and performance of certain vehicles with high surface-area-to-perimeter ratios. A new method of noise control based on the anatomy of owls is developed and consists of fabric or fibrous canopies suspended above the surface. The method is tested experimentally and is found to reduce the total far-field noise emitted by the surface. The treatment also is found to reduce the magnitude of pressure fluctuations felt by the underlying surface by up to three orders of magnitude. Experimental investigations into the effects of geometric parameters of the canopies lead to an optimized design which maximizes noise reduction. The results obtained during the canopy experiment inspired a separate new device for the reduction of trailing edge noise. This type of noise is generated by flow past the wing of an aircraft or the blades of a wind turbine, and is a source of annoyance for those in surrounding communities. The newly developed treatment consists of small fins, or "finlets," placed near the trailing edge of an airfoil. The treatment is tested experimentally at near-full-scale conditions and is found to reduce the magnitude of far-field noise by up to 10 dB. Geometric parameters of the finlets are tested to determine the optimal size and spacing of the finlets to maximize noise reduction. Follow-up computational and experimental studies reveal the fluid mechanics behind the noise reduction by showing that the finlets produce a velocity deficit in the flow near the trailing edge and limit the magnitude and spanwise correlation lengthscale of turbulence near the trailing edge, factors which determine the magnitude of far-field noise. In a final experiment, the finlets are applied to a marine propeller and are found to reduce not only trailing edge noise, but also noise caused by the bluntness of the trailing edge. The results of this experiment show the potential usefulness of finlets to reduce noise from rotating systems, such as fans or propellers, as well as from structures which feature blunt trailing edges.

Effects of Density and Impurity on Edge Localized Modes in Tokamaks

NASA Astrophysics Data System (ADS)

Zhu, Ping

2017-10-01

Plasma density and impurity concentration are believed to be two of the key elements governing the edge tokamak plasma conditions. Optimal levels of plasma density and impurity concentration in the edge region have been searched for in order to achieve the desired fusion gain and divertor heat/particle load mitigation. However, how plasma density or impurity would affect the edge pedestal stability may have not been well known. Our recent MHD theory modeling and simulations using the NIMROD code have found novel effects of density and impurity on the dynamics of edge-localized modes (ELMs) in tokamaks. First, previous MHD analyses often predict merely a weak stabilizing effect of toroidal flow on ELMs in experimentally relevant regimes. We find that the stabilizing effects on the high- n ELMs from toroidal flow can be significantly enhanced with the increased edge plasma density. Here n denotes the toroidal mode number. Second, the stabilizing effects of the enhanced edge resistivity due to lithium-conditioning on the low- n ELMs in the high confinement (H-mode) discharges in NSTX have been identified. Linear stability analysis of the experimentally constrained equilibrium suggests that the change in the equilibrium plasma density and pressure profiles alone due to lithium-conditioning may not be sufficient for a complete suppression of the low- n ELMs. The enhanced resistivity due to the increased effective electric charge number Zeff after lithium-conditioning provides additional stabilization of the low- n ELMs. These new effects revealed in our theory analyses may help further understand recent ELM experiments and suggest new control schemes for ELM suppression and mitigation in future experiments. They may also pose additional constraints on the optimal levels of plasma density and impurity concentration in the edge region for H-mode tokamak operation. Supported by National Magnetic Confinement Fusion Science Program of China Grants 2014GB124002 and 2015GB101004, the 100 Talent Program of the Chinese Academy of Sciences, and U.S. Department of Energy Grants DE-FG02-86ER53218 and DE-FC02-08ER54975.

Brain's tumor image processing using shearlet transform

NASA Astrophysics Data System (ADS)

Cadena, Luis; Espinosa, Nikolai; Cadena, Franklin; Korneeva, Anna; Kruglyakov, Alexey; Legalov, Alexander; Romanenko, Alexey; Zotin, Alexander

2017-09-01

Brain tumor detection is well known research area for medical and computer scientists. In last decades there has been much research done on tumor detection, segmentation, and classification. Medical imaging plays a central role in the diagnosis of brain tumors and nowadays uses methods non-invasive, high-resolution techniques, especially magnetic resonance imaging and computed tomography scans. Edge detection is a fundamental tool in image processing, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image has discontinuities. Shearlets is the most successful frameworks for the efficient representation of multidimensional data, capturing edges and other anisotropic features which frequently dominate multidimensional phenomena. The paper proposes an improved brain tumor detection method by automatically detecting tumor location in MR images, its features are extracted by new shearlet transform.

Cutting Edge Technologies Presentation: An Overview of Developing Sensor Technology Directions and Possible Barriers to New Technology Implementation

NASA Technical Reports Server (NTRS)

Hunter, Gary W.

2007-01-01

The aerospace industry requires the development of a range of chemical sensor technologies for such applications as leak detection, emission monitoring, fuel leak detection, environmental monitoring, and fire detection. A range of chemical sensors are being developed based on micromachining and microfabrication technology to fabricate microsensors with minimal size, weight, and power consumption; and the use of nanomaterials and structures to develop sensors with improved stability combined with higher sensitivity, However, individual sensors are limited in the amount of information that they can provide in environments that contain multiple chemical species. Thus, sensor arrays are being developed to address detection needs in such multi-species environments. These technologies and technical approaches have direct relevance to breath monitoring for clinical applications. This presentation gives an overview of developing cutting-edge sensor technology and possible barriers to new technology implementation. This includes lessons learned from previous microsensor development, recent work in development of a breath monitoring system, and future directions in the implementation of cutting edge sensor technology.

Glue detection based on teaching points constraint and tracking model of pixel convolution

NASA Astrophysics Data System (ADS)

Geng, Lei; Ma, Xiao; Xiao, Zhitao; Wang, Wen

2018-01-01

On-line glue detection based on machine version is significant for rust protection and strengthening in car production. Shadow stripes caused by reflect light and unevenness of inside front cover of car reduce the accuracy of glue detection. In this paper, we propose an effective algorithm to distinguish the edges of the glue and shadow stripes. Teaching points are utilized to calculate slope between the two adjacent points. Then a tracking model based on pixel convolution along motion direction is designed to segment several local rectangular regions using distance. The distance is the height of rectangular region. The pixel convolution along the motion direction is proposed to extract edges of gules in local rectangular region. A dataset with different illumination and complexity shape stripes are used to evaluate proposed method, which include 500 thousand images captured from the camera of glue gun machine. Experimental results demonstrate that the proposed method can detect the edges of glue accurately. The shadow stripes are distinguished and removed effectively. Our method achieves the 99.9% accuracies for the image dataset.

High-Speed Edge-Detecting Line Scan Smart Camera

NASA Technical Reports Server (NTRS)

Prokop, Norman F.

2012-01-01

A high-speed edge-detecting line scan smart camera was developed. The camera is designed to operate as a component in a NASA Glenn Research Center developed inlet shock detection system. The inlet shock is detected by projecting a laser sheet through the airflow. The shock within the airflow is the densest part and refracts the laser sheet the most in its vicinity, leaving a dark spot or shadowgraph. These spots show up as a dip or negative peak within the pixel intensity profile of an image of the projected laser sheet. The smart camera acquires and processes in real-time the linear image containing the shock shadowgraph and outputting the shock location. Previously a high-speed camera and personal computer would perform the image capture and processing to determine the shock location. This innovation consists of a linear image sensor, analog signal processing circuit, and a digital circuit that provides a numerical digital output of the shock or negative edge location. The smart camera is capable of capturing and processing linear images at over 1,000 frames per second. The edges are identified as numeric pixel values within the linear array of pixels, and the edge location information can be sent out from the circuit in a variety of ways, such as by using a microcontroller and onboard or external digital interface to include serial data such as RS-232/485, USB, Ethernet, or CAN BUS; parallel digital data; or an analog signal. The smart camera system can be integrated into a small package with a relatively small number of parts, reducing size and increasing reliability over the previous imaging system..

A fast method to emulate an iterative POCS image reconstruction algorithm.

PubMed

Zeng, Gengsheng L

2017-10-01

Iterative image reconstruction algorithms are commonly used to optimize an objective function, especially when the objective function is nonquadratic. Generally speaking, the iterative algorithms are computationally inefficient. This paper presents a fast algorithm that has one backprojection and no forward projection. This paper derives a new method to solve an optimization problem. The nonquadratic constraint, for example, an edge-preserving denoising constraint is implemented as a nonlinear filter. The algorithm is derived based on the POCS (projections onto projections onto convex sets) approach. A windowed FBP (filtered backprojection) algorithm enforces the data fidelity. An iterative procedure, divided into segments, enforces edge-enhancement denoising. Each segment performs nonlinear filtering. The derived iterative algorithm is computationally efficient. It contains only one backprojection and no forward projection. Low-dose CT data are used for algorithm feasibility studies. The nonlinearity is implemented as an edge-enhancing noise-smoothing filter. The patient studies results demonstrate its effectiveness in processing low-dose x ray CT data. This fast algorithm can be used to replace many iterative algorithms. © 2017 American Association of Physicists in Medicine.

Multi-agent fare optimization model of two modes problem and its analysis based on edge of chaos

NASA Astrophysics Data System (ADS)

Li, Xue-yan; Li, Xue-mei; Li, Xue-wei; Qiu, He-ting

2017-03-01

This paper proposes a new framework of fare optimization & game model for studying the competition between two travel modes (high speed railway and civil aviation) in which passengers' group behavior is taken into consideration. The small-world network is introduced to construct the multi-agent model of passengers' travel mode choice. The cumulative prospect theory is adopted to depict passengers' bounded rationality, the heterogeneity of passengers' reference point is depicted using the idea of group emotion computing. The conceptions of "Langton parameter" and "evolution entropy" in the theory of "edge of chaos" are introduced to create passengers' "decision coefficient" and "evolution entropy of travel mode choice" which are used to quantify passengers' group behavior. The numerical simulation and the analysis of passengers' behavior show that (1) the new model inherits the features of traditional model well and the idea of self-organizing traffic flow evolution fully embodies passengers' bounded rationality, (2) compared with the traditional model (logit model), when passengers are in the "edge of chaos" state, the total profit of the transportation system is higher.

In-flight edge response measurements for high-spatial-resolution remote sensing systems

NASA Astrophysics Data System (ADS)

Blonski, Slawomir; Pagnutti, Mary A.; Ryan, Robert; Zanoni, Vickie

2002-09-01

In-flight measurements of spatial resolution were conducted as part of the NASA Scientific Data Purchase Verification and Validation process. Characterization included remote sensing image products with ground sample distance of 1 meter or less, such as those acquired with the panchromatic imager onboard the IKONOS satellite and the airborne ADAR System 5500 multispectral instrument. Final image products were used to evaluate the effects of both the image acquisition system and image post-processing. Spatial resolution was characterized by full width at half maximum of an edge-response-derived line spread function. The edge responses were analyzed using the tilted-edge technique that overcomes the spatial sampling limitations of the digital imaging systems. As an enhancement to existing algorithms, the slope of the edge response and the orientation of the edge target were determined by a single computational process. Adjacent black and white square panels, either painted on a flat surface or deployed as tarps, formed the ground-based edge targets used in the tests. Orientation of the deployable tarps was optimized beforehand, based on simulations of the imaging system. The effects of such factors as acquisition geometry, temporal variability, Modulation Transfer Function compensation, and ground sample distance on spatial resolution were investigated.

Patterning control strategies for minimum edge placement error in logic devices

NASA Astrophysics Data System (ADS)

Mulkens, Jan; Hanna, Michael; Slachter, Bram; Tel, Wim; Kubis, Michael; Maslow, Mark; Spence, Chris; Timoshkov, Vadim

2017-03-01

In this paper we discuss the edge placement error (EPE) for multi-patterning semiconductor manufacturing. In a multi-patterning scheme the creation of the final pattern is the result of a sequence of lithography and etching steps, and consequently the contour of the final pattern contains error sources of the different process steps. We describe the fidelity of the final pattern in terms of EPE, which is defined as the relative displacement of the edges of two features from their intended target position. We discuss our holistic patterning optimization approach to understand and minimize the EPE of the final pattern. As an experimental test vehicle we use the 7-nm logic device patterning process flow as developed by IMEC. This patterning process is based on Self-Aligned-Quadruple-Patterning (SAQP) using ArF lithography, combined with line cut exposures using EUV lithography. The computational metrology method to determine EPE is explained. It will be shown that ArF to EUV overlay, CDU from the individual process steps, and local CD and placement of the individual pattern features, are the important contributors. Based on the error budget, we developed an optimization strategy for each individual step and for the final pattern. Solutions include overlay and CD metrology based on angle resolved scatterometry, scanner actuator control to enable high order overlay corrections and computational lithography optimization to minimize imaging induced pattern placement errors of devices and metrology targets.

Magnetotransport Properties of Graphene Nanoribbons with Zigzag Edges

NASA Astrophysics Data System (ADS)

Wu, Shuang; Liu, Bing; Shen, Cheng; Li, Si; Huang, Xiaochun; Lu, Xiaobo; Chen, Peng; Wang, Guole; Wang, Duoming; Liao, Mengzhou; Zhang, Jing; Zhang, Tingting; Wang, Shuopei; Yang, Wei; Yang, Rong; Shi, Dongxia; Watanabe, Kenji; Taniguchi, Takashi; Yao, Yugui; Wang, Weihua; Zhang, Guangyu

2018-05-01

The determination of the electronic structure by edge geometry is unique to graphene. In theory, an evanescent nonchiral edge state is predicted at the zigzag edges of graphene. Up to now, the approach used to study zigzag-edged graphene has mostly been limited to scanning tunneling microscopy. The transport properties have not been revealed. Recent advances in hydrogen plasma-assisted "top-down" fabrication of zigzag-edged graphene nanoribbons (Z-GNRs) have allowed us to investigate edge-related transport properties. In this Letter, we report the magnetotransport properties of Z-GNRs down to ˜70 nm wide on an h -BN substrate. In the quantum Hall effect regime, a prominent conductance peak is observed at Landau ν =0 , which is absent in GNRs with nonzigzag edges. The conductance peak persists under perpendicular magnetic fields and low temperatures. At a zero magnetic field, a nonlocal voltage signal, evidenced by edge conduction, is detected. These prominent transport features are closely related to the observable density of states at the hydrogen-etched zigzag edge of graphene probed by scanning tunneling spectroscopy, which qualitatively matches the theoretically predicted electronic structure for zigzag-edged graphene. Our study gives important insights for the design of new edge-related electronic devices.

Edge-SIFT: discriminative binary descriptor for scalable partial-duplicate mobile search.

PubMed

Zhang, Shiliang; Tian, Qi; Lu, Ke; Huang, Qingming; Gao, Wen

2013-07-01

As the basis of large-scale partial duplicate visual search on mobile devices, image local descriptor is expected to be discriminative, efficient, and compact. Our study shows that the popularly used histogram-based descriptors, such as scale invariant feature transform (SIFT) are not optimal for this task. This is mainly because histogram representation is relatively expensive to compute on mobile platforms and loses significant spatial clues, which are important for improving discriminative power and matching near-duplicate image patches. To address these issues, we propose to extract a novel binary local descriptor named Edge-SIFT from the binary edge maps of scale- and orientation-normalized image patches. By preserving both locations and orientations of edges and compressing the sparse binary edge maps with a boosting strategy, the final Edge-SIFT shows strong discriminative power with compact representation. Furthermore, we propose a fast similarity measurement and an indexing framework with flexible online verification. Hence, the Edge-SIFT allows an accurate and efficient image search and is ideal for computation sensitive scenarios such as a mobile image search. Experiments on a large-scale dataset manifest that the Edge-SIFT shows superior retrieval accuracy to Oriented BRIEF (ORB) and is superior to SIFT in the aspects of retrieval precision, efficiency, compactness, and transmission cost.

Chordwise implementation of pneumatic artificial muscles to actuate a trailing edge flap

NASA Astrophysics Data System (ADS)

Vocke, R. D., III; Kothera, C. S.; Wereley, N. M.

2018-07-01

This work describes the theoretical design and experimental validation of a rotorcraft-specific trailing edge flap powered by pneumatic artificial muscle actuators. The actuators in this work are co-located outboard on the rotor blade with the flap and arranged with a chordwise orientation where diameter and length restrictions can severely limit the operating range of the system. Techniques for addressing this configuration, such as introducing a bias contraction and mechanism optimization, are discussed and a numerical optimization is performed for an actuation system sized for implementation on a medium utility helicopter rotor. The optimized design achieves ±10° of deflection at 1/rev, and maintains at least ±2° half peak-to-peak deflection out to 10/rev, indicating that the system has the actuation authority and bandwidth necessary for both primary control and vibration/noise reduction. Portions of this paper were presented at the AHS 70th Annual Forum, Montréal, Québec, Canada, May 20–22, 2014.

Peak-Seeking Control For Reduced Fuel Consumption: Flight-Test Results For The Full-Scale Advanced Systems Testbed FA-18 Airplane

NASA Technical Reports Server (NTRS)

Brown, Nelson

2013-01-01

A peak-seeking control algorithm for real-time trim optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control algorithm is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane are used for optimization of fuel flow. Results from six research flights are presented herein. The optimization algorithm found a trim configuration that required approximately 3 percent less fuel flow than the baseline trim at the same flight condition. This presentation also focuses on the design of the flight experiment and the practical challenges of conducting the experiment.

Reconstructing Buildings with Discontinuities and Roof Overhangs from Oblique Aerial Imagery

NASA Astrophysics Data System (ADS)

Frommholz, D.; Linkiewicz, M.; Meissner, H.; Dahlke, D.

2017-05-01

This paper proposes a two-stage method for the reconstruction of city buildings with discontinuities and roof overhangs from oriented nadir and oblique aerial images. To model the structures the input data is transformed into a dense point cloud, segmented and filtered with a modified marching cubes algorithm to reduce the positional noise. Assuming a monolithic building the remaining vertices are initially projected onto a 2D grid and passed to RANSAC-based regression and topology analysis to geometrically determine finite wall, ground and roof planes. If this should fail due to the presence of discontinuities the regression will be repeated on a 3D level by traversing voxels within the regularly subdivided bounding box of the building point set. For each cube a planar piece of the current surface is approximated and expanded. The resulting segments get mutually intersected yielding both topological and geometrical nodes and edges. These entities will be eliminated if their distance-based affiliation to the defining point sets is violated leaving a consistent building hull including its structural breaks. To add the roof overhangs the computed polygonal meshes are projected onto the digital surface model derived from the point cloud. Their shapes are offset equally along the edge normals with subpixel accuracy by detecting the zero-crossings of the second-order directional derivative in the gradient direction of the height bitmap and translated back into world space to become a component of the building. As soon as the reconstructed objects are finished the aerial images are further used to generate a compact texture atlas for visualization purposes. An optimized atlas bitmap is generated that allows perspectivecorrect multi-source texture mapping without prior rectification involving a partially parallel placement algorithm. Moreover, the texture atlases undergo object-based image analysis (OBIA) to detect window areas which get reintegrated into the building models. To evaluate the performance of the proposed method a proof-of-concept test on sample structures obtained from real-world data of Heligoland/Germany has been conducted. It revealed good reconstruction accuracy in comparison to the cadastral map, a speed-up in texture atlas optimization and visually attractive render results.

Automated mapping of linear dunefield morphometric parameters from remotely-sensed data

NASA Astrophysics Data System (ADS)

Telfer, M. W.; Fyfe, R. M.; Lewin, S.

2015-12-01

Linear dunes are among the world's most common desert dune types, and typically occur in dunefields arranged in remarkably organized patterns extending over hundreds of kilometers. The causes of the patterns, formed by dunes merging, bifurcating and terminating, are still poorly understood, although it is widely accepted that they are emergent properties of the complex system of interactions between the boundary layer and an often-vegetated erodible substrate. Where such dunefields are vegetated, they are typically used as extensive rangeland, yet it is evident that many currently stabilized dunefields have been reactivated repeatedly during the late Quaternary. It has been suggested that dunefield patterning and the temporal evolution of dunefields are related, and thus there is considerable interest in better understanding the boundary conditions controlling dune patterning, especially given the possibility of reactivation of currently-stabilized dunefields under 21st century climate change. However, the time-consuming process of manual dune mapping has hampered attempts at quantitative description of dunefield patterning. This study aims to develop and test methods for delineating linear dune trendlines automatically from freely-available remotely sensed datasets. The highest resolution free global topographic data presently available (Aster GDEM v2) proved to be of marginal use, as the topographic expression of the dunes is of the same order as the vertical precision of the dataset (∼10 m), but in regions with relatively simple patterning it defined dune trends adequately. Analysis of spectral data (panchromatic Landsat 8 data) proved more promising in five of the six test sites, and despite poor panchromatic signal/noise ratios for the sixth site, the reflectance in the deep blue/violet (Landsat 8 Band 1) offers an alternative method of delineating dune pattern. A new edge detection algorithm (LInear Dune Optimized edge detection; LIDO) is proposed, based on Sobel operators with directional filtering and topologically-constrained recursion to optimize the inclusion of marginal zones. The method offers the potential for rapid quantitative mapping of linear dunefield patterning, providing validation data for modeling studies, and offering for the first time the ability to readily remap dunefields to assess dune reorganization at the dunefield scale.

3D early embryogenesis image filtering by nonlinear partial differential equations.

PubMed

Krivá, Z; Mikula, K; Peyriéras, N; Rizzi, B; Sarti, A; Stasová, O

2010-08-01

We present nonlinear diffusion equations, numerical schemes to solve them and their application for filtering 3D images obtained from laser scanning microscopy (LSM) of living zebrafish embryos, with a goal to identify the optimal filtering method and its parameters. In the large scale applications dealing with analysis of 3D+time embryogenesis images, an important objective is a correct detection of the number and position of cell nuclei yielding the spatio-temporal cell lineage tree of embryogenesis. The filtering is the first and necessary step of the image analysis chain and must lead to correct results, removing the noise, sharpening the nuclei edges and correcting the acquisition errors related to spuriously connected subregions. In this paper we study such properties for the regularized Perona-Malik model and for the generalized mean curvature flow equations in the level-set formulation. A comparison with other nonlinear diffusion filters, like tensor anisotropic diffusion and Beltrami flow, is also included. All numerical schemes are based on the same discretization principles, i.e. finite volume method in space and semi-implicit scheme in time, for solving nonlinear partial differential equations. These numerical schemes are unconditionally stable, fast and naturally parallelizable. The filtering results are evaluated and compared first using the Mean Hausdorff distance between a gold standard and different isosurfaces of original and filtered data. Then, the number of isosurface connected components in a region of interest (ROI) detected in original and after the filtering is compared with the corresponding correct number of nuclei in the gold standard. Such analysis proves the robustness and reliability of the edge preserving nonlinear diffusion filtering for this type of data and lead to finding the optimal filtering parameters for the studied models and numerical schemes. Further comparisons consist in ability of splitting the very close objects which are artificially connected due to acquisition error intrinsically linked to physics of LSM. In all studied aspects it turned out that the nonlinear diffusion filter which is called geodesic mean curvature flow (GMCF) has the best performance. Copyright 2010 Elsevier B.V. All rights reserved.

An analytical design procedure for the determination of effective leading edge extensions on thick delta wings

NASA Technical Reports Server (NTRS)

Ghaffari, F.; Chaturvedi, S. K.

1984-01-01

An analytical design procedure for leading edge extensions (LEE) was developed for thick delta wings. This LEE device is designed to be mounted to a wing along the pseudo-stagnation stream surface associated with the attached flow design lift coefficient of greater than zero. The intended purpose of this device is to improve the aerodynamic performance of high subsonic and low supersonic aircraft at incidences above that of attached flow design lift coefficient, by using a vortex system emanating along the leading edges of the device. The low pressure associated with these vortices would act on the LEE upper surface and the forward facing area at the wing leading edges, providing an additional lift and effective leading edge thrust recovery. The first application of this technique was to a thick, round edged, twisted and cambered wing of approximately triangular planform having a sweep of 58 deg and aspect ratio of 2.30. The panel aerodynamics and vortex lattice method with suction analogy computer codes were employed to determine the pseudo-stagnation stream surface and an optimized LEE planform shape.

Edge-defect induced spin-dependent Seebeck effect and spin figure of merit in graphene nanoribbons.

PubMed

Liu, Qing-Bo; Wu, Dan-Dan; Fu, Hua-Hua

2017-10-11

By using the first-principle calculations combined with the non-equilibrium Green's function approach, we have studied spin caloritronic properties of graphene nanoribbons (GNRs) with different edge defects. The theoretical results show that the edge-defected GNRs with sawtooth shapes can exhibit spin-dependent currents with opposite flowing directions by applying temperature gradients, indicating the occurrence of the spin-dependent Seebeck effect (SDSE). The edge defects bring about two opposite effects on the thermal spin currents: the enhancement of the symmetry of thermal spin-dependent currents, which contributes to the realization of pure thermal spin currents, and the decreasing of the spin thermoelectric conversion efficiency of the devices. It is fortunate that applying a gate voltage is an efficient route to optimize these two opposite spin thermoelectric properties towards realistic device applications. Moreover, due to the existence of spin-splitting band gaps, the edge-defected GNRs can be designed as spin-dependent Seebeck diodes and rectifiers, indicating that the edge-defected GNRs are potential candidates for room-temperature spin caloritronic devices.

Maximizing algebraic connectivity in air transportation networks

NASA Astrophysics Data System (ADS)

Wei, Peng

In air transportation networks the robustness of a network regarding node and link failures is a key factor for its design. An experiment based on the real air transportation network is performed to show that the algebraic connectivity is a good measure for network robustness. Three optimization problems of algebraic connectivity maximization are then formulated in order to find the most robust network design under different constraints. The algebraic connectivity maximization problem with flight routes addition or deletion is first formulated. Three methods to optimize and analyze the network algebraic connectivity are proposed. The Modified Greedy Perturbation Algorithm (MGP) provides a sub-optimal solution in a fast iterative manner. The Weighted Tabu Search (WTS) is designed to offer a near optimal solution with longer running time. The relaxed semi-definite programming (SDP) is used to set a performance upper bound and three rounding techniques are discussed to find the feasible solution. The simulation results present the trade-off among the three methods. The case study on two air transportation networks of Virgin America and Southwest Airlines show that the developed methods can be applied in real world large scale networks. The algebraic connectivity maximization problem is extended by adding the leg number constraint, which considers the traveler's tolerance for the total connecting stops. The Binary Semi-Definite Programming (BSDP) with cutting plane method provides the optimal solution. The tabu search and 2-opt search heuristics can find the optimal solution in small scale networks and the near optimal solution in large scale networks. The third algebraic connectivity maximization problem with operating cost constraint is formulated. When the total operating cost budget is given, the number of the edges to be added is not fixed. Each edge weight needs to be calculated instead of being pre-determined. It is illustrated that the edge addition and the weight assignment can not be studied separately for the problem with operating cost constraint. Therefore a relaxed SDP method with golden section search is developed to solve both at the same time. The cluster decomposition is utilized to solve large scale networks.

Edge magnetism of Heisenberg model on honeycomb lattice.

PubMed

Huang, Wen-Min; Hikihara, Toshiya; Lee, Yen-Chen; Lin, Hsiu-Hau

2017-03-07

Edge magnetism in graphene sparks intense theoretical and experimental interests. In the previous study, we demonstrated the existence of collective excitations at the zigzag edge of the honeycomb lattice with long-ranged Néel order. By employing the Schwinger-boson approach, we show that the edge magnons remain robust even when the long-ranged order is destroyed by spin fluctuations. Furthermore, in the effective field-theory limit, the dynamics of the edge magnon is captured by the one-dimensional relativistic Klein-Gordon equation. It is intriguing that the boundary field theory for the edge magnon is tied up with its bulk counterpart. By performing density-matrix renormalization group calculations, we show that the robustness may be attributed to the closeness between the ground state and the Néel state. The existence of edge magnon is not limited to the honeycomb structure, as demonstrated in the rotated-square lattice with zigzag edges as well. The universal behavior indicates that the edge magnons may attribute to the uncompensated edges and can be detected in many two-dimensional materials.

Three-dimensional structure of wind turbine wakes as measured by scanning lidar

NASA Astrophysics Data System (ADS)

Bodini, Nicola; Zardi, Dino; Lundquist, Julie K.

2017-08-01

The lower wind speeds and increased turbulence that are characteristic of turbine wakes have considerable consequences on large wind farms: turbines located downwind generate less power and experience increased turbulent loads. The structures of wakes and their downwind impacts are sensitive to wind speed and atmospheric variability. Wake characterization can provide important insights for turbine layout optimization in view of decreasing the cost of wind energy. The CWEX-13 field campaign, which took place between June and September 2013 in a wind farm in Iowa, was designed to explore the interaction of multiple wakes in a range of atmospheric stability conditions. Based on lidar wind measurements, we extend, present, and apply a quantitative algorithm to assess wake parameters such as the velocity deficits, the size of the wake boundaries, and the location of the wake centerlines. We focus on wakes from a row of four turbines at the leading edge of the wind farm to explore variations between wakes from the edge of the row (outer wakes) and those from turbines in the center of the row (inner wakes). Using multiple horizontal scans at different elevations, a three-dimensional structure of wakes from the row of turbines can be created. Wakes erode very quickly during unstable conditions and can in fact be detected primarily in stable conditions in the conditions measured here. During stable conditions, important differences emerge between the wakes of inner turbines and the wakes of outer turbines. Further, the strong wind veer associated with stable conditions results in a stretching of the wake structures, and this stretching manifests differently for inner and outer wakes. These insights can be incorporated into low-order wake models for wind farm layout optimization or for wind power forecasting.

Three-dimensional structure of wind turbine wakes as measured by scanning lidar

DOE PAGES

Bodini, Nicola; Zardi, Dino; Lundquist, Julie K.

2017-08-14

The lower wind speeds and increased turbulence that are characteristic of turbine wakes have considerable consequences on large wind farms: turbines located downwind generate less power and experience increased turbulent loads. The structures of wakes and their downwind impacts are sensitive to wind speed and atmospheric variability. Wake characterization can provide important insights for turbine layout optimization in view of decreasing the cost of wind energy. The CWEX-13 field campaign, which took place between June and September 2013 in a wind farm in Iowa, was designed to explore the interaction of multiple wakes in a range of atmospheric stability conditions.more » Based on lidar wind measurements, we extend, present, and apply a quantitative algorithm to assess wake parameters such as the velocity deficits, the size of the wake boundaries, and the location of the wake centerlines. We focus on wakes from a row of four turbines at the leading edge of the wind farm to explore variations between wakes from the edge of the row (outer wakes) and those from turbines in the center of the row (inner wakes). Using multiple horizontal scans at different elevations, a three-dimensional structure of wakes from the row of turbines can be created. Wakes erode very quickly during unstable conditions and can in fact be detected primarily in stable conditions in the conditions measured here. During stable conditions, important differences emerge between the wakes of inner turbines and the wakes of outer turbines. Further, the strong wind veer associated with stable conditions results in a stretching of the wake structures, and this stretching manifests differently for inner and outer wakes. As a result, these insights can be incorporated into low-order wake models for wind farm layout optimization or for wind power forecasting.« less

Three-dimensional structure of wind turbine wakes as measured by scanning lidar

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

Bodini, Nicola; Zardi, Dino; Lundquist, Julie K.

The lower wind speeds and increased turbulence that are characteristic of turbine wakes have considerable consequences on large wind farms: turbines located downwind generate less power and experience increased turbulent loads. The structures of wakes and their downwind impacts are sensitive to wind speed and atmospheric variability. Wake characterization can provide important insights for turbine layout optimization in view of decreasing the cost of wind energy. The CWEX-13 field campaign, which took place between June and September 2013 in a wind farm in Iowa, was designed to explore the interaction of multiple wakes in a range of atmospheric stability conditions.more » Based on lidar wind measurements, we extend, present, and apply a quantitative algorithm to assess wake parameters such as the velocity deficits, the size of the wake boundaries, and the location of the wake centerlines. We focus on wakes from a row of four turbines at the leading edge of the wind farm to explore variations between wakes from the edge of the row (outer wakes) and those from turbines in the center of the row (inner wakes). Using multiple horizontal scans at different elevations, a three-dimensional structure of wakes from the row of turbines can be created. Wakes erode very quickly during unstable conditions and can in fact be detected primarily in stable conditions in the conditions measured here. During stable conditions, important differences emerge between the wakes of inner turbines and the wakes of outer turbines. Further, the strong wind veer associated with stable conditions results in a stretching of the wake structures, and this stretching manifests differently for inner and outer wakes. As a result, these insights can be incorporated into low-order wake models for wind farm layout optimization or for wind power forecasting.« less

Edge Detection,

DTIC Science & Technology

1985-09-01

PROJECT. T ASK0 Artificial Inteligence Laboratory AREA It WORK UNIT NUMBERS V 545 Technology Square ( Cambridge, HA 02139 I I* CONTOOL1LIN@4OFFICE NAME...ARD-A1t62 62 EDGE DETECTION(U) NASSACNUSETTS INST OF TECH CAMBRIDGE 1/1 ARTIFICIAL INTELLIGENCE LAB E C HILDRETH SEP 85 AI-M-8 N99SI4-8S-C-6595...used to carry out this analysis. cce~iO a N) ’.~" D LI’BL. P p ------------ Sj. t i MASSACHUSETTS INSTITUTE OF TECHNOLOGY i ARTIFICIAL INTELLIGENCE

Appearance-Based Vision and the Automatic Generation of Object Recognition Programs

DTIC Science & Technology

1992-07-01

q u a groued into equivalence clases with respect o visible featms; the equivalence classes me called alpecu. A recognitio smuegy is generated from...illustates th concept. pge 9 Table 1: Summary o fSnsors Samr Vertex Edge Face Active/ Passive Edge detector line, passive Shape-fzm-shading - r passive...example of the detectability computation for a liht-stripe range finder is shown zn Fqgur 2. Figure 2: Detectability of a face for a light-stripe range

Near band edge photoluminescence of ZnO nanowires: Optimization via surface engineering

NASA Astrophysics Data System (ADS)

Yan, Danhua; Zhang, Wenrui; Cen, Jiajie; Stavitski, Eli; Sadowski, Jerzy T.; Vescovo, Elio; Walter, Andrew; Attenkofer, Klaus; Stacchiola, Darío J.; Liu, Mingzhao

2017-12-01

Zinc oxide (ZnO) nanowire arrays have potential applications for various devices such as ultra-violet light emitting diodes and lasers, where photoluminescence of intense near band edge emission without defect emissions is usually desired. Here, we demonstrate, counter-intuitively, that the near band edge emission may become dominant by introducing certain surface defects to ZnO nanowires via surface engineering. Specifically, near band edge emission (NBE) is effectively enhanced after a low pressure O2 plasma treatment that sputters off surface oxygen species to produce a reduced and oxygen vacancy-rich surface. The effect is attributed to the lowered surface valence band maximum of the reduced ZnO surface that creates an accumulative band bending, which screens the photo-generated minority carriers (holes) from reaching or being trapped by the surface defects.

Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors

PubMed Central

Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin

2018-01-01

Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison. PMID:29614028

Near band edge photoluminescence of ZnO nanowires: Optimization via surface engineering

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

Yan, Danhua; Zhang, Wenrui; Cen, Jiajie

Zinc oxide (ZnO) nanowire arrays have potential applications for various devices including ultra-violet light emitting diodes and lasers, where photoluminescence of intense near band edge emission without defect emissions is usually desired. Here, we demonstrate, counter-intuitively, that the near band edge emission may become dominant by introducing certain surface defects to ZnO nanowires via surface engineering. Specifically, near band edge emission (NBE) is effectively enhanced after a low pressure O 2 plasma treatment that sputters off surface oxygen species to produce a reduced and oxygen vacancy-rich surface. The effect is attributed to the lowered surface valence band maximum of themore » reduced ZnO surface that creates an accumulative band bending, which screens the photo-generated minority carriers (holes) from reaching or being trapped by the surface defects.« less

Near band edge photoluminescence of ZnO nanowires: Optimization via surface engineering

DOE PAGES

Yan, Danhua; Zhang, Wenrui; Cen, Jiajie; ...

2017-12-04

Zinc oxide (ZnO) nanowire arrays have potential applications for various devices including ultra-violet light emitting diodes and lasers, where photoluminescence of intense near band edge emission without defect emissions is usually desired. Here, we demonstrate, counter-intuitively, that the near band edge emission may become dominant by introducing certain surface defects to ZnO nanowires via surface engineering. Specifically, near band edge emission (NBE) is effectively enhanced after a low pressure O 2 plasma treatment that sputters off surface oxygen species to produce a reduced and oxygen vacancy-rich surface. The effect is attributed to the lowered surface valence band maximum of themore » reduced ZnO surface that creates an accumulative band bending, which screens the photo-generated minority carriers (holes) from reaching or being trapped by the surface defects.« less

Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors.

PubMed

Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin

2018-04-03

Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison.

Feature extraction algorithm for space targets based on fractal theory

NASA Astrophysics Data System (ADS)

Tian, Balin; Yuan, Jianping; Yue, Xiaokui; Ning, Xin

2007-11-01

In order to offer a potential for extending the life of satellites and reducing the launch and operating costs, satellite servicing including conducting repairs, upgrading and refueling spacecraft on-orbit become much more frequently. Future space operations can be more economically and reliably executed using machine vision systems, which can meet real time and tracking reliability requirements for image tracking of space surveillance system. Machine vision was applied to the research of relative pose for spacecrafts, the feature extraction algorithm was the basis of relative pose. In this paper fractal geometry based edge extraction algorithm which can be used in determining and tracking the relative pose of an observed satellite during proximity operations in machine vision system was presented. The method gets the gray-level image distributed by fractal dimension used the Differential Box-Counting (DBC) approach of the fractal theory to restrain the noise. After this, we detect the consecutive edge using Mathematical Morphology. The validity of the proposed method is examined by processing and analyzing images of space targets. The edge extraction method not only extracts the outline of the target, but also keeps the inner details. Meanwhile, edge extraction is only processed in moving area to reduce computation greatly. Simulation results compared edge detection using the method which presented by us with other detection methods. The results indicate that the presented algorithm is a valid method to solve the problems of relative pose for spacecrafts.

Eb&D: A new clustering approach for signed social networks based on both edge-betweenness centrality and density of subgraphs

NASA Astrophysics Data System (ADS)

Qi, Xingqin; Song, Huimin; Wu, Jianliang; Fuller, Edgar; Luo, Rong; Zhang, Cun-Quan

2017-09-01

Clustering algorithms for unsigned social networks which have only positive edges have been studied intensively. However, when a network has like/dislike, love/hate, respect/disrespect, or trust/distrust relationships, unsigned social networks with only positive edges are inadequate. Thus we model such kind of networks as signed networks which can have both negative and positive edges. Detecting the cluster structures of signed networks is much harder than for unsigned networks, because it not only requires that positive edges within clusters are as many as possible, but also requires that negative edges between clusters are as many as possible. Currently, we have few clustering algorithms for signed networks, and most of them requires the number of final clusters as an input while it is actually hard to predict beforehand. In this paper, we will propose a novel clustering algorithm called Eb &D for signed networks, where both the betweenness of edges and the density of subgraphs are used to detect cluster structures. A hierarchically nested system will be constructed to illustrate the inclusion relationships of clusters. To show the validity and efficiency of Eb &D, we test it on several classical social networks and also hundreds of synthetic data sets, and all obtain better results compared with other methods. The biggest advantage of Eb &D compared with other methods is that the number of clusters do not need to be known prior.

Generation and detection of edge magnetoplasmons in a quantum Hall system using a photoconductive switch

NASA Astrophysics Data System (ADS)

Lin, Chaojing; Morita, Kyosuke; Muraki, Koji; Fujisawa, Toshimasa

2018-04-01

Edge magnetoplasmons (EMPs) are unidirectional charge density waves travelling in an edge channel of a two-dimensional electron gas in the quantum Hall regime. We present both generation and detection schemes with a photoconductive switch (PCS) for EMPs. Here, the conductance of the PCS is modulated by irradiation with a laser beam, whose amplitude can be modulated by an external signal. When the PCS is used as a generator, the electrical current from the PCS is injected into the edge channel to excite EMPs. When the PCS is used as a detector, the electronic potential induced by EMPs is applied to the PCS with a modulated laser beam so as to constitute a phase-sensitive measurement. For both experiments, we confirm that the time of flight for the EMPs increases with the magnetic field in agreement with the EMP characteristics. Combination of the two schemes would be useful in investigating and utilizing EMPs at higher frequencies.

Generation of phase edge singularities by coplanar three-beam interference and their detection.

PubMed

Patorski, Krzysztof; Sluzewski, Lukasz; Trusiak, Maciej; Pokorski, Krzysztof

2017-02-06

In recent years singular optics has gained considerable attention in science and technology. Up to now optical vortices (phase point dislocations) have been of main interest. This paper presents the first general analysis of formation of phase edge singularities by coplanar three-beam interference. They can be generated, for example, by three-slit interference or self-imaging in the Fresnel diffraction field of a sinusoidal grating. We derive a general condition for the ratio of amplitudes of interfering beams resulting in phase edge dislocations, lateral separation of dislocations depends on this ratio as well. Analytically derived properties are corroborated by numerical and experimental studies. We develop a simple, robust, common path optical self-imaging configuration aided by a coherent tilted reference wave and spatial filtering. Finally, we propose an automatic fringe pattern analysis technique for detecting phase edge dislocations, based on the continuous wavelet transform. Presented studies open new possibilities for developing grating based sensing techniques for precision metrology of very small phase differences.

Operator-coached machine vision for space telerobotics

NASA Technical Reports Server (NTRS)

Bon, Bruce; Wilcox, Brian; Litwin, Todd; Gennery, Donald B.

1991-01-01

A prototype system for interactive object modeling has been developed and tested. The goal of this effort has been to create a system which would demonstrate the feasibility of high interactive operator-coached machine vision in a realistic task environment, and to provide a testbed for experimentation with various modes of operator interaction. The purpose for such a system is to use human perception where machine vision is difficult, i.e., to segment the scene into objects and to designate their features, and to use machine vision to overcome limitations of human perception, i.e., for accurate measurement of object geometry. The system captures and displays video images from a number of cameras, allows the operator to designate a polyhedral object one edge at a time by moving a 3-D cursor within these images, performs a least-squares fit of the designated edges to edge data detected with a modified Sobel operator, and combines the edges thus detected to form a wire-frame object model that matches the Sobel data.

Distributed Scene Analysis For Autonomous Road Vehicle Guidance

NASA Astrophysics Data System (ADS)

Mysliwetz, Birger D.; Dickmanns, E. D.

1987-01-01

An efficient distributed processing scheme has been developed for visual road boundary tracking by 'VaMoRs', a testbed vehicle for autonomous mobility and computer vision. Ongoing work described here is directed to improving the robustness of the road boundary detection process in the presence of shadows, ill-defined edges and other disturbing real world effects. The system structure and the techniques applied for real-time scene analysis are presented along with experimental results. All subfunctions of road boundary detection for vehicle guidance, such as edge extraction, feature aggregation and camera pointing control, are executed in parallel by an onboard multiprocessor system. On the image processing level local oriented edge extraction is performed in multiple 'windows', tighly controlled from a hierarchically higher, modelbased level. The interpretation process involving a geometric road model and the observer's relative position to the road boundaries is capable of coping with ambiguity in measurement data. By using only selected measurements to update the model parameters even high noise levels can be dealt with and misleading edges be rejected.

Optimum Material Composition for Minimizing the Stress Intensity Factor of Edge Crack in Thick-Walled FGM Circular Pipes Under Thermomechanical Loading

NASA Astrophysics Data System (ADS)

Sekine, Hideki; Yoshida, Kimiaki

This paper deals with the optimization problem of material composition for minimizing the stress intensity factor of radial edge crack in thick-walled functionally graded material (FGM) circular pipes under steady-state thermomechanical loading. Homogenizing the FGM circular pipes by simulating the inhomogeneity of thermal conductivity by a distribution of equivalent eigentemperature gradient and the inhomogeneity of Young's modulus and Poisson's ratio by a distribution of equivalent eigenstrain, we present an approximation method to obtain the stress intensity factor of radial edge crack in the FGM circular pipes. The optimum material composition for minimizing the stress intensity factor of radial edge crack is determined using a nonlinear mathematical programming method. Numerical results obtained for a thick-walled TiC/Al2O3 FGM circular pipe reveal that it is possible to decrease remarkably the stress intensity factor of radial edge crack by setting the optimum material composition profile.

Tuning colloidal quantum dot band edge positions through solution-phase surface chemistry modification

DOE PAGES

Kroupa, Daniel M.; Vörös, Márton; Brawand, Nicholas P.; ...

2017-05-16

Band edge positions of semiconductors determine their functionality in many optoelectronic applications such as photovoltaics, photoelectrochemical cells and light emitting diodes. Here we show that band edge positions of lead sulfide (PbS) colloidal semiconductor nanocrystals, specifically quantum dots (QDs), can be tuned over 2.0 eV through surface chemistry modification. We achieved this remarkable control through the development of simple, robust and scalable solution-phase ligand exchange methods, which completely replace native ligands with functionalized cinnamate ligands, allowing for well-defined, highly tunable chemical systems. By combining experiments and ab initio simulations, we establish clear relationships between QD surface chemistry and the bandmore » edge positions of ligand/QD hybrid systems. We find that in addition to ligand dipole, inter-QD ligand shell inter-digitization contributes to the band edge shifts. As a result, we expect that our established relationships and principles can help guide future optimization of functional organic/inorganic hybrid nanostructures for diverse optoelectronic applications.« less

Tuning colloidal quantum dot band edge positions through solution-phase surface chemistry modification

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

Kroupa, Daniel M.; Vörös, Márton; Brawand, Nicholas P.

Band edge positions of semiconductors determine their functionality in many optoelectronic applications such as photovoltaics, photoelectrochemical cells and light emitting diodes. Here we show that band edge positions of lead sulfide (PbS) colloidal semiconductor nanocrystals, specifically quantum dots (QDs), can be tuned over 2.0 eV through surface chemistry modification. We achieved this remarkable control through the development of simple, robust and scalable solution-phase ligand exchange methods, which completely replace native ligands with functionalized cinnamate ligands, allowing for well-defined, highly tunable chemical systems. By combining experiments and ab initio simulations, we establish clear relationships between QD surface chemistry and the bandmore » edge positions of ligand/QD hybrid systems. We find that in addition to ligand dipole, inter-QD ligand shell inter-digitization contributes to the band edge shifts. As a result, we expect that our established relationships and principles can help guide future optimization of functional organic/inorganic hybrid nanostructures for diverse optoelectronic applications.« less

Tuning colloidal quantum dot band edge positions through solution-phase surface chemistry modification

PubMed Central

Kroupa, Daniel M.; Vörös, Márton; Brawand, Nicholas P.; McNichols, Brett W.; Miller, Elisa M.; Gu, Jing; Nozik, Arthur J.; Sellinger, Alan; Galli, Giulia; Beard, Matthew C.

2017-01-01

Band edge positions of semiconductors determine their functionality in many optoelectronic applications such as photovoltaics, photoelectrochemical cells and light emitting diodes. Here we show that band edge positions of lead sulfide (PbS) colloidal semiconductor nanocrystals, specifically quantum dots (QDs), can be tuned over 2.0 eV through surface chemistry modification. We achieved this remarkable control through the development of simple, robust and scalable solution-phase ligand exchange methods, which completely replace native ligands with functionalized cinnamate ligands, allowing for well-defined, highly tunable chemical systems. By combining experiments and ab initio simulations, we establish clear relationships between QD surface chemistry and the band edge positions of ligand/QD hybrid systems. We find that in addition to ligand dipole, inter-QD ligand shell inter-digitization contributes to the band edge shifts. We expect that our established relationships and principles can help guide future optimization of functional organic/inorganic hybrid nanostructures for diverse optoelectronic applications. PMID:28508866

Tuning colloidal quantum dot band edge positions through solution-phase surface chemistry modification

NASA Astrophysics Data System (ADS)

Kroupa, Daniel M.; Vörös, Márton; Brawand, Nicholas P.; McNichols, Brett W.; Miller, Elisa M.; Gu, Jing; Nozik, Arthur J.; Sellinger, Alan; Galli, Giulia; Beard, Matthew C.

2017-05-01

Band edge positions of semiconductors determine their functionality in many optoelectronic applications such as photovoltaics, photoelectrochemical cells and light emitting diodes. Here we show that band edge positions of lead sulfide (PbS) colloidal semiconductor nanocrystals, specifically quantum dots (QDs), can be tuned over 2.0 eV through surface chemistry modification. We achieved this remarkable control through the development of simple, robust and scalable solution-phase ligand exchange methods, which completely replace native ligands with functionalized cinnamate ligands, allowing for well-defined, highly tunable chemical systems. By combining experiments and ab initio simulations, we establish clear relationships between QD surface chemistry and the band edge positions of ligand/QD hybrid systems. We find that in addition to ligand dipole, inter-QD ligand shell inter-digitization contributes to the band edge shifts. We expect that our established relationships and principles can help guide future optimization of functional organic/inorganic hybrid nanostructures for diverse optoelectronic applications.

Rimmed and edge thickened Stodola shaped flywheel

DOEpatents

Kulkarni, S.V.; Stone, R.G.

1983-10-11

A flywheel is described that is useful for energy storage in a hybrid vehicle automotive power system or in some stationary applications. The flywheel has a body composed of essentially planar isotropic high strength material. The flywheel body is enclosed by a rim of circumferentially wound fiber embedded in resin. The rim promotes flywheel safety and survivability. The flywheel has a truncated and edge thickened Stodola shape designed to optimize system mass and energy storage capability. 6 figs.

Rimmed and edge thickened stodola shaped flywheel. [Patent application

DOEpatents

Kulkarni, S.V.; Stone, R.G.

1980-09-24

A flywheel is described that is useful for energy storage in a hybrid vehicle automotive power system or in some stationary applications. The flywheel has a body composed of essentially planar isotropic high strength material. The flywheel body is enclosed by a rim of circumferentially wound fiber embedded in resin. The rim promotes flywheel safety and survivability. The flywheel has a truncated and edge thickened Stodola shape designed to optimize system mass and energy storage capability.

Role of helical edge modes in the chiral quantum anomalous Hall state.

PubMed

Mani, Arjun; Benjamin, Colin

2018-01-22

Although indications are that a single chiral quantum anomalous Hall(QAH) edge mode might have been experimentally detected. There have been very many recent experiments which conjecture that a chiral QAH edge mode always materializes along with a pair of quasi-helical quantum spin Hall (QSH) edge modes. In this work we deal with a substantial 'What If?' question- in case the QSH edge modes, from which these QAH edge modes evolve, are not topologically-protected then the QAH edge modes wont be topologically-protected too and thus unfit for use in any applications. Further, as a corollary one can also ask if the topological-protection of QSH edge modes does not carry over during the evolution process to QAH edge modes then again our 'What if?' scenario becomes apparent. The 'how' of the resolution of this 'What if?' conundrum is the main objective of our work. We show in similar set-ups affected by disorder and inelastic scattering, transport via trivial QAH edge mode leads to quantization of Hall resistance and not that via topological QAH edge modes. This perhaps begs a substantial reinterpretation of those experiments which purported to find signatures of chiral(topological) QAH edge modes albeit in conjunction with quasi helical QSH edge modes.

Structural Health Monitoring Analysis for the Orbiter Wing Leading Edge

NASA Technical Reports Server (NTRS)

Yap, Keng C.

2010-01-01

This viewgraph presentation reviews Structural Health Monitoring Analysis for the Orbiter Wing Leading Edge. The Wing Leading Edge Impact Detection System (WLE IDS) and the Impact Analysis Process are also described to monitor WLE debris threats. The contents include: 1) Risk Management via SHM; 2) Hardware Overview; 3) Instrumentation; 4) Sensor Configuration; 5) Debris Hazard Monitoring; 6) Ascent Response Summary; 7) Response Signal; 8) Distribution of Flight Indications; 9) Probabilistic Risk Analysis (PRA); 10) Model Correlation; 11) Impact Tests; 12) Wing Leading Edge Modeling; 13) Ascent Debris PRA Results; and 14) MM/OD PRA Results.

Image Edge Extraction via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A. (Inventor); Klinko, Steve (Inventor)

2008-01-01

A computer-based technique for detecting edges in gray level digital images employs fuzzy reasoning to analyze whether each pixel in an image is likely on an edge. The image is analyzed on a pixel-by-pixel basis by analyzing gradient levels of pixels in a square window surrounding the pixel being analyzed. An edge path passing through the pixel having the greatest intensity gradient is used as input to a fuzzy membership function, which employs fuzzy singletons and inference rules to assigns a new gray level value to the pixel that is related to the pixel's edginess degree.

Linear landmark extraction in SAR images with application to augmented integrity aero-navigation: an overview to a novel processing chain

NASA Astrophysics Data System (ADS)

Fabbrini, L.; Messina, M.; Greco, M.; Pinelli, G.

2011-10-01

In the context of augmented integrity Inertial Navigation System (INS), recent technological developments have been focusing on landmark extraction from high-resolution synthetic aperture radar (SAR) images in order to retrieve aircraft position and attitude. The article puts forward a processing chain that can automatically detect linear landmarks on highresolution synthetic aperture radar (SAR) images and can be successfully exploited also in the context of augmented integrity INS. The processing chain uses constant false alarm rate (CFAR) edge detectors as the first step of the whole processing procedure. Our studies confirm that the ratio of averages (RoA) edge detector detects object boundaries more effectively than Student T-test and Wilcoxon-Mann-Whitney (WMW) test. Nevertheless, all these statistical edge detectors are sensitive to violation of the assumptions which underlie their theory. In addition to presenting a solution to the previous problem, we put forward a new post-processing algorithm useful to remove the main false alarms, to select the most probable edge position, to reconstruct broken edges and finally to vectorize them. SAR images from the "MSTAR clutter" dataset were used to prove the effectiveness of the proposed algorithms.

Automated Cloud Observation for Ground Telescope Optimization

NASA Astrophysics Data System (ADS)

Lane, B.; Jeffries, M. W., Jr.; Therien, W.; Nguyen, H.

As the number of man-made objects placed in space each year increases with advancements in commercial, academic and industry, the number of objects required to be detected, tracked, and characterized continues to grow at an exponential rate. Commercial companies, such as ExoAnalytic Solutions, have deployed ground based sensors to maintain track custody of these objects. For the ExoAnalytic Global Telescope Network (EGTN), observation of such objects are collected at the rate of over 10 million unique observations per month (as of September 2017). Currently, the EGTN does not optimally collect data on nights with significant cloud levels. However, a majority of these nights prove to be partially cloudy providing clear portions in the sky for EGTN sensors to observe. It proves useful for a telescope to utilize these clear areas to continue resident space object (RSO) observation. By dynamically updating the tasking with the varying cloud positions, the number of observations could potentially increase dramatically due to increased persistence, cadence, and revisit. This paper will discuss the recent algorithms being implemented within the EGTN, including the motivation, need, and general design. The use of automated image processing as well as various edge detection methods, including Canny, Sobel, and Marching Squares, on real-time large FOV images of the sky enhance the tasking and scheduling of a ground based telescope is discussed in Section 2. Implementations of these algorithms on single and expanding to multiple telescopes, will be explored. Results of applying these algorithms to the EGTN in real-time and comparison to non-optimized EGTN tasking is presented in Section 3. Finally, in Section 4 we explore future work in applying these throughout the EGTN as well as other optical telescopes.

Comparison of parameters of modern cooled and uncooled thermal cameras

NASA Astrophysics Data System (ADS)

Bareła, Jarosław; Kastek, Mariusz; Firmanty, Krzysztof; Krupiński, Michał

2017-10-01

During the design of a system employing thermal cameras one always faces a problem of choosing the camera types best suited for the task. In many cases such a choice is far from optimal one, and there are several reasons for that. System designers often favor tried and tested solution they are used to. They do not follow the latest developments in the field of infrared technology and sometimes their choices are based on prejudice and not on facts. The paper presents the results of measurements of basic parameters of MWIR and LWIR thermal cameras, carried out in a specialized testing laboratory. The measured parameters are decisive in terms of image quality generated by thermal cameras. All measurements were conducted according to current procedures and standards. However the camera settings were not optimized for a specific test conditions or parameter measurements. Instead the real settings used in normal camera operations were applied to obtain realistic camera performance figures. For example there were significant differences between measured values of noise parameters and catalogue data provided by manufacturers, due to the application of edge detection filters to increase detection and recognition ranges. The purpose of this paper is to provide help in choosing the optimal thermal camera for particular application, answering the question whether to opt for cheaper microbolometer device or apply slightly better (in terms of specifications) yet more expensive cooled unit. Measurements and analysis were performed by qualified personnel with several dozen years of experience in both designing and testing of thermal camera systems with both cooled and uncooled focal plane arrays. Cameras of similar array sizes and optics were compared, and for each tested group the best performing devices were selected.

Investigation of statistical iterative reconstruction for dedicated breast CT

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

Makeev, Andrey; Glick, Stephen J.

2013-08-15

Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images weremore » compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue.Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters.Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially improved performance (by a factor of greater than 10) compared to FBP. The hyperbolic prior was also observed to be superior to the TV norm. A few of the best-performing parameter pairs for the PML method also demonstrated superior performance for various radiation doses. In fact, using PML with certain parameter values results in better images, acquired using 2 mGy dose, than FBP-reconstructed images acquired using 6 mGy dose.Conclusions: A range of optimal free parameters for the PML algorithm with hyperbolic and TV norm-based potentials is presented for the microcalcification detection task, in dedicated breast CT. The reported values can be used as starting values of the free parameters, when SIR techniques are used for image reconstruction. Significant improvement in image quality can be achieved by using PML with optimal combination of parameters, as compared to FBP. Importantly, these results suggest improved detection of microcalcifications can be obtained by using PML with lower radiation dose to the patient, than using FBP with higher dose.« less

Probing Anisotropic Surface Properties of Molybdenite by Direct Force Measurements.

PubMed

Lu, Zhenzhen; Liu, Qingxia; Xu, Zhenghe; Zeng, Hongbo

2015-10-27

Probing anisotropic surface properties of layer-type mineral is fundamentally important in understanding its surface charge and wettability for a variety of applications. In this study, the surface properties of the face and the edge surfaces of natural molybdenite (MoS2) were investigated by direct surface force measurements using atomic force microscope (AFM). The interaction forces between the AFM tip (Si3N4) and face or edge surface of molybdenite were measured in 10 mM NaCl solutions at various pHs. The force profiles were well-fitted with classical DLVO (Derjaguin-Landau-Verwey-Overbeek) theory to determine the surface potentials of the face and the edge surfaces of molybdenite. The surface potentials of both the face and edge surfaces become more negative with increasing pH. At neutral and alkaline conditions, the edge surface exhibits more negative surface potential than the face surface, which is possibly due to molybdate and hydromolybdate ions on the edge surface. The point of zero charge (PZC) of the edge surface was determined around pH 3 while PZC of the face surface was not observed in the range of pH 3-11. The interaction forces between octadecyltrichlorosilane-treated AFM tip (OTS-tip) and face or edge surface of molybdenite were also measured at various pHs to study the wettability of molybdenite surfaces. An attractive force between the OTS-tip and the face surface was detected. The force profiles were well-fitted by considering DLVO forces and additional hydrophobic force. Our results suggest the hydrophobic feature of the face surface of molybdenite. In contrast, no attractive force between the OTS-tip and the edge surface was detected. This is the first study in directly measuring surface charge and wettability of the pristine face and edge surfaces of molybdenite through surface force measurements.

Application of Time-Frequency Domain Transform to Three-Dimensional Interpolation of Medical Images.

PubMed

Lv, Shengqing; Chen, Yimin; Li, Zeyu; Lu, Jiahui; Gao, Mingke; Lu, Rongrong

2017-11-01

Medical image three-dimensional (3D) interpolation is an important means to improve the image effect in 3D reconstruction. In image processing, the time-frequency domain transform is an efficient method. In this article, several time-frequency domain transform methods are applied and compared in 3D interpolation. And a Sobel edge detection and 3D matching interpolation method based on wavelet transform is proposed. We combine wavelet transform, traditional matching interpolation methods, and Sobel edge detection together in our algorithm. What is more, the characteristics of wavelet transform and Sobel operator are used. They deal with the sub-images of wavelet decomposition separately. Sobel edge detection 3D matching interpolation method is used in low-frequency sub-images under the circumstances of ensuring high frequency undistorted. Through wavelet reconstruction, it can get the target interpolation image. In this article, we make 3D interpolation of the real computed tomography (CT) images. Compared with other interpolation methods, our proposed method is verified to be effective and superior.

Edge detection

NASA Astrophysics Data System (ADS)

Hildreth, E. C.

1985-09-01

For both biological systems and machines, vision begins with a large and unwieldly array of measurements of the amount of light reflected from surfaces in the environment. The goal of vision is to recover physical properties of objects in the scene such as the location of object boundaries and the structure, color and texture of object surfaces, from the two-dimensional image that is projected onto the eye or camera. This goal is not achieved in a single step: vision proceeds in stages, with each stage producing increasingly more useful descriptions of the image and then the scene. The first clues about the physical properties of the scene are provided by the changes of intensity in the image. The importance of intensity changes and edges in early visual processing has led to extensive research on their detection, description and use, both in computer and biological vision systems. This article reviews some of the theory that underlies the detection of edges, and the methods used to carry out this analysis.

Computer simulation and evaluation of edge detection algorithms and their application to automatic path selection

NASA Technical Reports Server (NTRS)

Longendorfer, B. A.

1976-01-01

The construction of an autonomous roving vehicle requires the development of complex data-acquisition and processing systems, which determine the path along which the vehicle travels. Thus, a vehicle must possess algorithms which can (1) reliably detect obstacles by processing sensor data, (2) maintain a constantly updated model of its surroundings, and (3) direct its immediate actions to further a long range plan. The first function consisted of obstacle recognition. Obstacles may be identified by the use of edge detection techniques. Therefore, the Kalman Filter was implemented as part of a large scale computer simulation of the Mars Rover. The second function consisted of modeling the environment. The obstacle must be reconstructed from its edges, and the vast amount of data must be organized in a readily retrievable form. Therefore, a Terrain Modeller was developed which assembled and maintained a rectangular grid map of the planet. The third function consisted of directing the vehicle's actions.

Using fuzzy fractal features of digital images for the material surface analisys

NASA Astrophysics Data System (ADS)

Privezentsev, D. G.; Zhiznyakov, A. L.; Astafiev, A. V.; Pugin, E. V.

2018-01-01

Edge detection is an important task in image processing. There are a lot of approaches in this area: Sobel, Canny operators and others. One of the perspective techniques in image processing is the use of fuzzy logic and fuzzy sets theory. They allow us to increase processing quality by representing information in its fuzzy form. Most of the existing fuzzy image processing methods switch to fuzzy sets on very late stages, so this leads to some useful information loss. In this paper, a novel method of edge detection based on fuzzy image representation and fuzzy pixels is proposed. With this approach, we convert the image to fuzzy form on the first step. Different approaches to this conversion are described. Several membership functions for fuzzy pixel description and requirements for their form and view are given. A novel approach to edge detection based on Sobel operator and fuzzy image representation is proposed. Experimental testing of developed method was performed on remote sensing images.

Performance evaluation of canny edge detection on a tiled multicore architecture

NASA Astrophysics Data System (ADS)

Brethorst, Andrew Z.; Desai, Nehal; Enright, Douglas P.; Scrofano, Ronald

2011-01-01

In the last few years, a variety of multicore architectures have been used to parallelize image processing applications. In this paper, we focus on assessing the parallel speed-ups of different Canny edge detection parallelization strategies on the Tile64, a tiled multicore architecture developed by the Tilera Corporation. Included in these strategies are different ways Canny edge detection can be parallelized, as well as differences in data management. The two parallelization strategies examined were loop-level parallelism and domain decomposition. Loop-level parallelism is achieved through the use of OpenMP,1 and it is capable of parallelization across the range of values over which a loop iterates. Domain decomposition is the process of breaking down an image into subimages, where each subimage is processed independently, in parallel. The results of the two strategies show that for the same number of threads, programmer implemented, domain decomposition exhibits higher speed-ups than the compiler managed, loop-level parallelism implemented with OpenMP.

Quantitative analysis of the plain radiographic appearance of nonossifying fibroma.

PubMed

Friedland, J A; Reinus, W R; Fisher, A J; Wilson, A J

1995-08-01

To quantitate radiographic features that distinguish the plain radiographic appearance of nonossifying fibroma (NOF) from other solitary lesions of bone. Seven hundred nine cases of focal bone lesions, including 34 NOFs, were analyzed according to demographic, anatomic, and plain radiographic features. Vector analysis of groups of features was performed to determine those that are most sensitive and specific for the appearance of NOF in contrast to other lesions in the data base. The radiographic appearance of NOFs was most consistently a medullary based (97%), lytic lesion (100%) with geographic bone destruction (100%), marginal sclerosis (97%), and well-defined edges (94%). A statistically significant number of lesions were located in the distal aspect of long bones. Unicameral bone cyst shared the most radiographic features with the NOF. Vector analysis showed a large degree of overlap between NOF and other lesions such as aneurysmal bone cyst, chondromyxoid fibroma, and eosinophilic granuloma. The description that optimized sensitivity and prevalence for detection of NOF is a medullary based, ovoid lesion in the distal or proximal portions of a long bone with well-defined edges, a partial or complete rind of sclerosis, and absence of fallen fragment, periosteal reaction, and cortical disruption. The radiographic appearance of NOF is relatively nonspecific but, using vector analysis, can be better elucidated over current textbook descriptions.

Innovative Design and Performance Evaluation of Bionic Imprinting Toothed Wheel

PubMed Central

Wang, Xiaoyang; Tong, Jin; Stephen, Carr

2018-01-01

A highly efficient soil-burrowing dung beetle possesses an intricate outer contour curve on its foreleg end-tooth. This study was carried out based on evidence that this special outer contour curve has the potential of reducing soil penetration resistance and could enhance soil-burrowing efficiency. A toothed wheel is a typical agricultural implement for soil imprinting, to increase its working efficiency; the approach of the bionic geometrical structure was utilized to optimize the innovative shape of imprinting toothed wheel. Characteristics in the dung beetle's foreleg end-tooth were extracted and studied by the edge detection technique. Then, this special outer contour curve was modeled by a nine-order polynomial function and used for the innovative design of imprinting the tooth's cutting edge. Both the conventional and bionic teeth were manufactured, and traction tests in a soil bin were conducted. Taking required draft force and volume of imprinted microbasin as the evaluating indexes, operating efficiency and quality of different toothed wheels were compared and investigated. Results indicate that compared with the conventional toothed wheel, a bionic toothed wheel possesses a better forward resistance reduction property against soil and, meanwhile, can enhance the quality of soil imprinting by increasing the volume of the created micro-basin. PMID:29515651

Investigation of Energy-Dispersive X-ray Computed Tomography System with CdTe Scan Detector and Comparing-Differentiator and Its Application to Gadolinium K-Edge Imaging

NASA Astrophysics Data System (ADS)

Chiba, Hiraku; Sato, Yuichi; Sato, Eiichi; Maeda, Tomoko; Matsushita, Ryo; Yanbe, Yutaka; Hagiwara, Osahiko; Matsukiyo, Hiroshi; Osawa, Akihiro; Enomoto, Toshiyuki; Watanabe, Manabu; Kusachi, Shinya; Sato, Shigehiro; Ogawa, Akira; Onagawa, Jun

2012-10-01

An energy-dispersive (ED) X-ray computed tomography (CT) system is useful for carrying out monochromatic imaging by selecting optimal energy photons. CT is performed by repeated linear scans and rotations of an object. X-ray photons from the object are detected by the cadmium telluride (CdTe) detector, and event pulses of X-ray photons are produced using charge-sensitive and shaping amplifiers. The lower photon energy is determined by a comparator, and the maximum photon energy of 70 keV corresponds to the tube voltage. Logical pulses from the comparator are counted by a counter card through a differentiator to reduce pulse width and rise time. In the ED-CT system, tube voltage and current were 70 kV and 0.30 mA, respectively, and X-ray intensity was 18.2 µGy/s at 1.0 m from the source at a tube voltage of 70 kV. Demonstration of gadolinium K-edge CT for cancer diagnosis was carried out by selecting photons with energies ranging from 50.4 to 70 keV, and photon-count energy subtraction imaging from 30 to 50.3 keV was also performed.