Determination of formal redox potentials in aqueous solution of copper(II) complexes with ligands having nitrogen and oxygen donor atoms and comparison with their EPR and UV-Vis spectral features.

PubMed

Tabbì, Giovanni; Giuffrida, Alessandro; Bonomo, Raffaele P

2013-11-01

Formal redox potentials in aqueous solution were determined for copper(II) complexes with ligands having oxygen and nitrogen as donor atoms. All the chosen copper(II) complexes have well-known stereochemistries (pseudo-octahedral, square planar, square-based pyramidal, trigonal bipyramidal or tetrahedral) as witnessed by their reported spectroscopic, EPR and UV-visible (UV-Vis) features, so that a rough correlation between the measured redox potential and the typical geometrical arrangement of the copper(II) complex could be established. Negative values have been obtained for copper(II) complexes in tetragonally elongated pseudo-octahedral geometries, when measured against Ag/AgCl reference electrode. Copper(II) complexes in tetrahedral environments (or flattened tetrahedral geometries) show positive redox potential values. There is a region, always in the field of negative redox potentials which groups the copper(II) complexes exhibiting square-based pyramidal arrangements. Therefore, it is suggested that a measurement of the formal redox potential could be of great help, when some ambiguities might appear in the interpretation of spectroscopic (EPR and UV-Vis) data. Unfortunately, when the comparison is made between copper(II) complexes in square-based pyramidal geometries and those in square planar environments (or a pseudo-octahedral) a little perturbed by an equatorial tetrahedral distortion, their redox potentials could fall in the same intermediate region. In this case spectroscopic data have to be handled with great care in order to have an answer about a copper complex geometrical characteristics. © 2013.

A probabilistic approach to segmentation and classification of neoplasia in uterine cervix images using color and geometric features

NASA Astrophysics Data System (ADS)

Srinivasan, Yeshwanth; Hernes, Dana; Tulpule, Bhakti; Yang, Shuyu; Guo, Jiangling; Mitra, Sunanda; Yagneswaran, Sriraja; Nutter, Brian; Jeronimo, Jose; Phillips, Benny; Long, Rodney; Ferris, Daron

2005-04-01

Automated segmentation and classification of diagnostic markers in medical imagery are challenging tasks. Numerous algorithms for segmentation and classification based on statistical approaches of varying complexity are found in the literature. However, the design of an efficient and automated algorithm for precise classification of desired diagnostic markers is extremely image-specific. The National Library of Medicine (NLM), in collaboration with the National Cancer Institute (NCI), is creating an archive of 60,000 digitized color images of the uterine cervix. NLM is developing tools for the analysis and dissemination of these images over the Web for the study of visual features correlated with precancerous neoplasia and cancer. To enable indexing of images of the cervix, it is essential to develop algorithms for the segmentation of regions of interest, such as acetowhitened regions, and automatic identification and classification of regions exhibiting mosaicism and punctation. Success of such algorithms depends, primarily, on the selection of relevant features representing the region of interest. We present color and geometric features based statistical classification and segmentation algorithms yielding excellent identification of the regions of interest. The distinct classification of the mosaic regions from the non-mosaic ones has been obtained by clustering multiple geometric and color features of the segmented sections using various morphological and statistical approaches. Such automated classification methodologies will facilitate content-based image retrieval from the digital archive of uterine cervix and have the potential of developing an image based screening tool for cervical cancer.

Facial expression identification using 3D geometric features from Microsoft Kinect device

NASA Astrophysics Data System (ADS)

Han, Dongxu; Al Jawad, Naseer; Du, Hongbo

2016-05-01

Facial expression identification is an important part of face recognition and closely related to emotion detection from face images. Various solutions have been proposed in the past using different types of cameras and features. Microsoft Kinect device has been widely used for multimedia interactions. More recently, the device has been increasingly deployed for supporting scientific investigations. This paper explores the effectiveness of using the device in identifying emotional facial expressions such as surprise, smile, sad, etc. and evaluates the usefulness of 3D data points on a face mesh structure obtained from the Kinect device. We present a distance-based geometric feature component that is derived from the distances between points on the face mesh and selected reference points in a single frame. The feature components extracted across a sequence of frames starting and ending by neutral emotion represent a whole expression. The feature vector eliminates the need for complex face orientation correction, simplifying the feature extraction process and making it more efficient. We applied the kNN classifier that exploits a feature component based similarity measure following the principle of dynamic time warping to determine the closest neighbors. Preliminary tests on a small scale database of different facial expressions show promises of the newly developed features and the usefulness of the Kinect device in facial expression identification.

Approximate Joint Diagonalization and Geometric Mean of Symmetric Positive Definite Matrices

PubMed Central

Congedo, Marco; Afsari, Bijan; Barachant, Alexandre; Moakher, Maher

2015-01-01

We explore the connection between two problems that have arisen independently in the signal processing and related fields: the estimation of the geometric mean of a set of symmetric positive definite (SPD) matrices and their approximate joint diagonalization (AJD). Today there is a considerable interest in estimating the geometric mean of a SPD matrix set in the manifold of SPD matrices endowed with the Fisher information metric. The resulting mean has several important invariance properties and has proven very useful in diverse engineering applications such as biomedical and image data processing. While for two SPD matrices the mean has an algebraic closed form solution, for a set of more than two SPD matrices it can only be estimated by iterative algorithms. However, none of the existing iterative algorithms feature at the same time fast convergence, low computational complexity per iteration and guarantee of convergence. For this reason, recently other definitions of geometric mean based on symmetric divergence measures, such as the Bhattacharyya divergence, have been considered. The resulting means, although possibly useful in practice, do not satisfy all desirable invariance properties. In this paper we consider geometric means of covariance matrices estimated on high-dimensional time-series, assuming that the data is generated according to an instantaneous mixing model, which is very common in signal processing. We show that in these circumstances we can approximate the Fisher information geometric mean by employing an efficient AJD algorithm. Our approximation is in general much closer to the Fisher information geometric mean as compared to its competitors and verifies many invariance properties. Furthermore, convergence is guaranteed, the computational complexity is low and the convergence rate is quadratic. The accuracy of this new geometric mean approximation is demonstrated by means of simulations. PMID:25919667

iGRaND: an invariant frame for RGBD sensor feature detection and descriptor extraction with applications

NASA Astrophysics Data System (ADS)

Willis, Andrew R.; Brink, Kevin M.

2016-06-01

This article describes a new 3D RGBD image feature, referred to as iGRaND, for use in real-time systems that use these sensors for tracking, motion capture, or robotic vision applications. iGRaND features use a novel local reference frame derived from the image gradient and depth normal (hence iGRaND) that is invariant to scale and viewpoint for Lambertian surfaces. Using this reference frame, Euclidean invariant feature components are computed at keypoints which fuse local geometric shape information with surface appearance information. The performance of the feature for real-time odometry is analyzed and its computational complexity and accuracy is compared with leading alternative 3D features.

Visualisation of urban airborne laser scanning data with occlusion images

NASA Astrophysics Data System (ADS)

Hinks, Tommy; Carr, Hamish; Gharibi, Hamid; Laefer, Debra F.

2015-06-01

Airborne Laser Scanning (ALS) was introduced to provide rapid, high resolution scans of landforms for computational processing. More recently, ALS has been adapted for scanning urban areas. The greater complexity of urban scenes necessitates the development of novel methods to exploit urban ALS to best advantage. This paper presents occlusion images: a novel technique that exploits the geometric complexity of the urban environment to improve visualisation of small details for better feature recognition. The algorithm is based on an inversion of traditional occlusion techniques.

Designing perturbative metamaterials from discrete models.

PubMed

Matlack, Kathryn H; Serra-Garcia, Marc; Palermo, Antonio; Huber, Sebastian D; Daraio, Chiara

2018-04-01

Identifying material geometries that lead to metamaterials with desired functionalities presents a challenge for the field. Discrete, or reduced-order, models provide a concise description of complex phenomena, such as negative refraction, or topological surface states; therefore, the combination of geometric building blocks to replicate discrete models presenting the desired features represents a promising approach. However, there is no reliable way to solve such an inverse problem. Here, we introduce 'perturbative metamaterials', a class of metamaterials consisting of weakly interacting unit cells. The weak interaction allows us to associate each element of the discrete model with individual geometric features of the metamaterial, thereby enabling a systematic design process. We demonstrate our approach by designing two-dimensional elastic metamaterials that realize Veselago lenses, zero-dispersion bands and topological surface phonons. While our selected examples are within the mechanical domain, the same design principle can be applied to acoustic, thermal and photonic metamaterials composed of weakly interacting unit cells.

Rapid Prototyping Technology for Manufacturing GTE Turbine Blades

NASA Astrophysics Data System (ADS)

Balyakin, A. V.; Dobryshkina, E. M.; Vdovin, R. A.; Alekseev, V. P.

2018-03-01

The conventional approach to manufacturing turbine blades by investment casting is expensive and time-consuming, as it takes a lot of time to make geometrically precise and complex wax patterns. Turbine blade manufacturing in pilot production can be sped up by accelerating the casting process while keeping the geometric precision of the final product. This paper compares the rapid prototyping method (casting the wax pattern composition into elastic silicone molds) to the conventional technology. Analysis of the size precision of blade casts shows that silicon-mold casting features sufficient geometric precision. Thus, this method for making wax patterns can be a cost-efficient solution for small-batch or pilot production of turbine blades for gas-turbine units (GTU) and gas-turbine engines (GTE). The paper demonstrates how additive technology and thermographic analysis can speed up the cooling of wax patterns in silicone molds. This is possible at an optimal temperature and solidification time, which make the process more cost-efficient while keeping the geometric quality of the final product.

Patient-Specific Simulation of Cardiac Blood Flow From High-Resolution Computed Tomography.

PubMed

Lantz, Jonas; Henriksson, Lilian; Persson, Anders; Karlsson, Matts; Ebbers, Tino

2016-12-01

Cardiac hemodynamics can be computed from medical imaging data, and results could potentially aid in cardiac diagnosis and treatment optimization. However, simulations are often based on simplified geometries, ignoring features such as papillary muscles and trabeculae due to their complex shape, limitations in image acquisitions, and challenges in computational modeling. This severely hampers the use of computational fluid dynamics in clinical practice. The overall aim of this study was to develop a novel numerical framework that incorporated these geometrical features. The model included the left atrium, ventricle, ascending aorta, and heart valves. The framework used image registration to obtain patient-specific wall motion, automatic remeshing to handle topological changes due to the complex trabeculae motion, and a fast interpolation routine to obtain intermediate meshes during the simulations. Velocity fields and residence time were evaluated, and they indicated that papillary muscles and trabeculae strongly interacted with the blood, which could not be observed in a simplified model. The framework resulted in a model with outstanding geometrical detail, demonstrating the feasibility as well as the importance of a framework that is capable of simulating blood flow in physiologically realistic hearts.

Integration of Error Compensation of Coordinate Measuring Machines into Feature Measurement: Part I—Model Development

PubMed Central

Calvo, Roque; D’Amato, Roberto; Gómez, Emilio; Domingo, Rosario

2016-01-01

The development of an error compensation model for coordinate measuring machines (CMMs) and its integration into feature measurement is presented. CMMs are widespread and dependable instruments in industry and laboratories for dimensional measurement. From the tip probe sensor to the machine display, there is a complex transformation of probed point coordinates through the geometrical feature model that makes the assessment of accuracy and uncertainty measurement results difficult. Therefore, error compensation is not standardized, conversely to other simpler instruments. Detailed coordinate error compensation models are generally based on CMM as a rigid-body and it requires a detailed mapping of the CMM’s behavior. In this paper a new model type of error compensation is proposed. It evaluates the error from the vectorial composition of length error by axis and its integration into the geometrical measurement model. The non-explained variability by the model is incorporated into the uncertainty budget. Model parameters are analyzed and linked to the geometrical errors and uncertainty of CMM response. Next, the outstanding measurement models of flatness, angle, and roundness are developed. The proposed models are useful for measurement improvement with easy integration into CMM signal processing, in particular in industrial environments where built-in solutions are sought. A battery of implementation tests are presented in Part II, where the experimental endorsement of the model is included. PMID:27690052

Orienting in virtual environments: How are surface features and environmental geometry weighted in an orientation task?

PubMed

Kelly, Debbie M; Bischof, Walter F

2008-10-01

We investigated how human adults orient in enclosed virtual environments, when discrete landmark information is not available and participants have to rely on geometric and featural information on the environmental surfaces. In contrast to earlier studies, where, for women, the featural information from discrete landmarks overshadowed the encoding of the geometric information, Experiment 1 showed that when featural information is conjoined with the environmental surfaces, men and women encoded both types of information. Experiment 2 showed that, although both types of information are encoded, performance in locating a goal position is better if it is close to a geometrically or featurally distinct location. Furthermore, although features are relied upon more strongly than geometry, initial experience with an environment influences the relative weighting of featural and geometric cues. Taken together, these results show that human adults use a flexible strategy for encoding spatial information.

A shape-based segmentation method for mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen

2013-07-01

Segmentation of mobile laser point clouds of urban scenes into objects is an important step for post-processing (e.g., interpretation) of point clouds. Point clouds of urban scenes contain numerous objects with significant size variability, complex and incomplete structures, and holes or variable point densities, raising great challenges for the segmentation of mobile laser point clouds. This paper addresses these challenges by proposing a shape-based segmentation method. The proposed method first calculates the optimal neighborhood size of each point to derive the geometric features associated with it, and then classifies the point clouds according to geometric features using support vector machines (SVMs). Second, a set of rules are defined to segment the classified point clouds, and a similarity criterion for segments is proposed to overcome over-segmentation. Finally, the segmentation output is merged based on topological connectivity into a meaningful geometrical abstraction. The proposed method has been tested on point clouds of two urban scenes obtained by different mobile laser scanners. The results show that the proposed method segments large-scale mobile laser point clouds with good accuracy and computationally effective time cost, and that it segments pole-like objects particularly well.

Impact of roadway geometric features on crash severity on rural two-lane highways.

PubMed

Haghighi, Nima; Liu, Xiaoyue Cathy; Zhang, Guohui; Porter, Richard J

2018-02-01

This study examines the impact of a wide range of roadway geometric features on the severity outcomes of crashes occurred on rural two-lane highways. We argue that crash data have a hierarchical structure which needs to be addressed in modeling procedure. Moreover, most of previous studies ignored the impact of geometric features on crash types when developing crash severity models. We hypothesis that geometric features are more likely to determine crash type, and crash type together with other occupant, environmental and vehicle characteristics determine crash severity outcome. This paper presents an application of multilevel models to successfully capture both hierarchical structure of crash data and indirect impact of geometric features on crash severity. Using data collected in Illinois from 2007 to 2009, multilevel ordered logit model is developed to quantify the impact of geometric features and environmental conditions on crash severity outcome. Analysis results revealed that there is a significant variation in severity outcomes of crashes occurred across segments which verifies the presence of hierarchical structure. Lower risk of severe crashes is found to be associated with the presence of 10-ft lane and/or narrow shoulders, lower roadside hazard rate, higher driveway density, longer barrier length, and shorter barrier offset. The developed multilevel model offers greater consistency with data generating mechanism and can be utilized to evaluate safety effects of geometric design improvement projects. Published by Elsevier Ltd.

[Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

PubMed

Li, Jing; Hong, Wenxue

2014-12-01

The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method.

Advanced computer-aided design for bone tissue-engineering scaffolds.

PubMed

Ramin, E; Harris, R A

2009-04-01

The design of scaffolds with an intricate and controlled internal structure represents a challenge for tissue engineering. Several scaffold-manufacturing techniques allow the creation of complex architectures but with little or no control over the main features of the channel network such as the size, shape, and interconnectivity of each individual channel, resulting in intricate but random structures. The combined use of computer-aided design (CAD) systems and layer-manufacturing techniques allows a high degree of control over these parameters with few limitations in terms of achievable complexity. However, the design of complex and intricate networks of channels required in CAD is extremely time-consuming since manually modelling hundreds of different geometrical elements, all with different parameters, may require several days to design individual scaffold structures. An automated design methodology is proposed by this research to overcome these limitations. This approach involves the investigation of novel software algorithms, which are able to interact with a conventional CAD program and permit the automated design of several geometrical elements, each with a different size and shape. In this work, the variability of the parameters required to define each geometry has been set as random, but any other distribution could have been adopted. This methodology has been used to design five cubic scaffolds with interconnected pore channels that range from 200 to 800 microm in diameter, each with an increased complexity of the internal geometrical arrangement. A clinical case study, consisting of an integration of one of these geometries with a craniofacial implant, is then presented.

Self-interference digital holography with a geometric-phase hologram lens.

PubMed

Choi, KiHong; Yim, Junkyu; Yoo, Seunghwi; Min, Sung-Wook

2017-10-01

Self-interference digital holography (SIDH) is actively studied because the hologram acquisition under the incoherent illumination condition is available. The key component in this system is wavefront modulating optics, which modulates an incoming object wave into two different wavefront curvatures. In this Letter, the geometric-phase hologram lens is introduced in the SIDH system to perform as a polarization-sensitive wavefront modulator and a single-path beam splitter. This special optics has several features, such as high transparency, a modulation efficiency up to 99%, a thinness of a few millimeters, and a flat structure. The demonstration system is devised, and the numerical reconstruction results from an acquired complex hologram are presented.

Mobile visual object identification: from SIFT-BoF-RANSAC to Sketchprint

NASA Astrophysics Data System (ADS)

Voloshynovskiy, Sviatoslav; Diephuis, Maurits; Holotyak, Taras

2015-03-01

Mobile object identification based on its visual features find many applications in the interaction with physical objects and security. Discriminative and robust content representation plays a central role in object and content identification. Complex post-processing methods are used to compress descriptors and their geometrical information, aggregate them into more compact and discriminative representations and finally re-rank the results based on the similarity geometries of descriptors. Unfortunately, most of the existing descriptors are not very robust and discriminative once applied to the various contend such as real images, text or noise-like microstructures next to requiring at least 500-1'000 descriptors per image for reliable identification. At the same time, the geometric re-ranking procedures are still too complex to be applied to the numerous candidates obtained from the feature similarity based search only. This restricts that list of candidates to be less than 1'000 which obviously causes a higher probability of miss. In addition, the security and privacy of content representation has become a hot research topic in multimedia and security communities. In this paper, we introduce a new framework for non- local content representation based on SketchPrint descriptors. It extends the properties of local descriptors to a more informative and discriminative, yet geometrically invariant content representation. In particular it allows images to be compactly represented by 100 SketchPrint descriptors without being fully dependent on re-ranking methods. We consider several use cases, applying SketchPrint descriptors to natural images, text documents, packages and micro-structures and compare them with the traditional local descriptors.

Facades structure detection by geometric moment

NASA Astrophysics Data System (ADS)

Jiang, Diqiong; Chen, Hui; Song, Rui; Meng, Lei

2017-06-01

This paper proposes a novel method for extracting facades structure from real-world pictures by using local geometric moment. Compared with existing methods, the proposed method has advantages of easy-to-implement, low computational cost, and robustness to noises, such as uneven illumination, shadow, and shade from other objects. Besides, our method is faster and has a lower space complexity, making it feasible for mobile devices and the situation where real-time data processing is required. Specifically, a facades structure modal is first proposed to support the use of our special noise reduction method, which is based on a self-adapt local threshold with Gaussian weighted average for image binarization processing and the feature of the facades structure. Next, we divide the picture of the building into many individual areas, each of which represents a door or a window in the picture. Subsequently we calculate the geometric moment and centroid for each individual area, for identifying those collinear ones based on the feature vectors, each of which is thereafter replaced with a line. Finally, we comprehensively analyze all the geometric moment and centroid to find out the facades structure of the building. We compare our result with other methods and especially report the result from the pictures taken in bad environmental conditions. Our system is designed for two application, i.e, the reconstruction of facades based on higher resolution ground-based on imagery, and the positional system based on recognize the urban building.

Computed Tomography Inspection and Analysis for Additive Manufacturing Components

NASA Technical Reports Server (NTRS)

Beshears, Ronald D.

2017-01-01

Computed tomography (CT) inspection was performed on test articles additively manufactured from metallic materials. Metallic AM and machined wrought alloy test articles with programmed flaws and geometric features were inspected using a 2-megavolt linear accelerator based CT system. Performance of CT inspection on identically configured wrought and AM components and programmed flaws was assessed to determine the impact of additive manufacturing on inspectability of objects with complex geometries.

Efficient Feature Extraction and Likelihood Fusion for Vehicle Tracking in Low Frame Rate Airborne Video

DTIC Science & Technology

2010-07-01

imagery, persistent sensor array I. Introduction New device fabrication technologies and heterogeneous embedded processors have led to the emergence of a...geometric occlusions between target and sensor , motion blur, urban scene complexity, and high data volumes. In practical terms the targets are small...distributed airborne narrow-field-of-view video sensor networks. Airborne camera arrays combined with com- putational photography techniques enable the

Ducting arrangement for cooling a gas turbine structure

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

Lee, Ching-Pang; Morrison, Jay A.

2015-07-21

A ducting arrangement (10) for a can annular gas turbine engine, including: a duct (12, 14) disposed between a combustor (16) and a first row of turbine blades and defining a hot gas path (30) therein, the duct (12, 14) having raised geometric features (54) incorporated into an outer surface (80); and a flow sleeve (72) defining a cooling flow path (84) between an inner surface (78) of the flow sleeve (72) and the duct outer surface (80). After a cooling fluid (86) traverses a relatively upstream raised geometric feature (90), the inner surface (78) of the flow sleeve (72)more » is effective to direct the cooling fluid (86) toward a landing (94) separating the relatively upstream raised geometric feature (90) from a relatively downstream raised geometric feature (94).« less

Transmission properties of a single metallic slit: from the subwavelength regime to the geometrical-optics limit.

PubMed

Bravo-Abad, J; Martín-Moreno, L; García-Vidal, F J

2004-02-01

In this work we explore the transmission properties of a single slit in a metallic screen. We analyze the dependence of these properties on both slit width and angle of incident radiation. We study in detail the crossover between the subwavelength regime and the geometrical-optics limit. In the subwavelength regime, resonant transmission linked to the excitation of waveguide resonances is analyzed. Linewidth of these resonances and their associated electric-field intensities are controlled by just the width of the slit. More complex transmission spectra appear when the wavelength of light is comparable to the slit width. Rapid oscillations associated with the emergence of different propagating modes inside the slit are the main features appearing in this regime.

An Energy-Based Approach for Detection and Characterization of Subtle Entities Within Laser Scanning Point-Clouds

NASA Astrophysics Data System (ADS)

Arav, Reuma; Filin, Sagi

2016-06-01

Airborne laser scans present an optimal tool to describe geomorphological features in natural environments. However, a challenge arises in the detection of such phenomena, as they are embedded in the topography, tend to blend into their surroundings and leave only a subtle signature within the data. Most object-recognition studies address mainly urban environments and follow a general pipeline where the data are partitioned into segments with uniform properties. These approaches are restricted to man-made domain and are capable to handle limited features that answer a well-defined geometric form. As natural environments present a more complex set of features, the common interpretation of the data is still manual at large. In this paper, we propose a data-aware detection scheme, unbound to specific domains or shapes. We define the recognition question as an energy optimization problem, solved by variational means. Our approach, based on the level-set method, characterizes geometrically local surfaces within the data, and uses these characteristics as potential field for minimization. The main advantage here is that it allows topological changes of the evolving curves, such as merging and breaking. We demonstrate the proposed methodology on the detection of collapse sinkholes.

Computer-aided diagnosis for phase-contrast X-ray computed tomography: quantitative characterization of human patellar cartilage with high-dimensional geometric features.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Glaser, Christian; Wismüller, Axel

2014-02-01

Phase-contrast computed tomography (PCI-CT) has shown tremendous potential as an imaging modality for visualizing human cartilage with high spatial resolution. Previous studies have demonstrated the ability of PCI-CT to visualize (1) structural details of the human patellar cartilage matrix and (2) changes to chondrocyte organization induced by osteoarthritis. This study investigates the use of high-dimensional geometric features in characterizing such chondrocyte patterns in the presence or absence of osteoarthritic damage. Geometrical features derived from the scaling index method (SIM) and statistical features derived from gray-level co-occurrence matrices were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic curve (AUC). SIM-derived geometrical features exhibited the best classification performance (AUC, 0.95 ± 0.06) and were most robust to changes in ROI size. These results suggest that such geometrical features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix in an automated and non-subjective manner, while also enabling classification of cartilage as healthy or osteoarthritic with high accuracy. Such features could potentially serve as imaging markers for evaluating osteoarthritis progression and its response to different therapeutic intervention strategies.

Complex quantum network geometries: Evolution and phase transitions

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra; Rahmede, Christoph; Wu, Zhihao

2015-08-01

Networks are topological and geometric structures used to describe systems as different as the Internet, the brain, or the quantum structure of space-time. Here we define complex quantum network geometries, describing the underlying structure of growing simplicial 2-complexes, i.e., simplicial complexes formed by triangles. These networks are geometric networks with energies of the links that grow according to a nonequilibrium dynamics. The evolution in time of the geometric networks is a classical evolution describing a given path of a path integral defining the evolution of quantum network states. The quantum network states are characterized by quantum occupation numbers that can be mapped, respectively, to the nodes, links, and triangles incident to each link of the network. We call the geometric networks describing the evolution of quantum network states the quantum geometric networks. The quantum geometric networks have many properties common to complex networks, including small-world property, high clustering coefficient, high modularity, and scale-free degree distribution. Moreover, they can be distinguished between the Fermi-Dirac network and the Bose-Einstein network obeying, respectively, the Fermi-Dirac and Bose-Einstein statistics. We show that these networks can undergo structural phase transitions where the geometrical properties of the networks change drastically. Finally, we comment on the relation between quantum complex network geometries, spin networks, and triangulations.

Complex quantum network geometries: Evolution and phase transitions.

PubMed

Bianconi, Ginestra; Rahmede, Christoph; Wu, Zhihao

2015-08-01

Networks are topological and geometric structures used to describe systems as different as the Internet, the brain, or the quantum structure of space-time. Here we define complex quantum network geometries, describing the underlying structure of growing simplicial 2-complexes, i.e., simplicial complexes formed by triangles. These networks are geometric networks with energies of the links that grow according to a nonequilibrium dynamics. The evolution in time of the geometric networks is a classical evolution describing a given path of a path integral defining the evolution of quantum network states. The quantum network states are characterized by quantum occupation numbers that can be mapped, respectively, to the nodes, links, and triangles incident to each link of the network. We call the geometric networks describing the evolution of quantum network states the quantum geometric networks. The quantum geometric networks have many properties common to complex networks, including small-world property, high clustering coefficient, high modularity, and scale-free degree distribution. Moreover, they can be distinguished between the Fermi-Dirac network and the Bose-Einstein network obeying, respectively, the Fermi-Dirac and Bose-Einstein statistics. We show that these networks can undergo structural phase transitions where the geometrical properties of the networks change drastically. Finally, we comment on the relation between quantum complex network geometries, spin networks, and triangulations.

Identification of different coordination geometries by XAFS in copper(II) complexes with trimesic acid

NASA Astrophysics Data System (ADS)

Gaur, A.; Klysubun, W.; Soni, Balram; Shrivastava, B. D.; Prasad, J.; Srivastava, K.

2016-10-01

X-ray absorption spectroscopy (XAS) is very useful in revealing the information about geometric and electronic structure of a transition-metal absorber and thus commonly used for determination of metal-ligand coordination. But XAFS analysis becomes difficult if differently coordinated metal centers are present in a system. In the present investigation, existence of distinct coordination geometries around metal centres have been studied by XAFS in a series of trimesic acid Cu(II) complexes. The complexes studied are: Cu3(tma)2(im)6 8H2O (1), Cu3(tma)2(mim)6 17H2O (2), Cu3(tma)2(tmen)3 8.5H2O (3), Cu3(tma) (pmd)3 6H2O (ClO4)3 (4) and Cu3(tma)2 3H2O (5). These complexes have not only Cu metal centres with different coordination but in complexes 1-3, there are multiple coordination geometries present around Cu centres. Using XANES spectra, different coordination geometries present in these complexes have been identified. The variation observed in the pre-edge features and edge features have been correlated with the distortion of the specific coordination environment around Cu centres in the complexes. XANES spectra have been calculated for the distinct metal centres present in the complexes by employing ab-initio calculations. These individual spectra have been used to resolve the spectral contribution of the Cu centres to the particular XANES features exhibited by the experimental spectra of the multinuclear complexes. Also, the variation in the 4p density of states have been calculated for the different Cu centres and then correlated with the features originated from corresponding coordination of Cu. Thus, these spectral features have been successfully utilized to detect the presence of the discrete metal centres in a system. The inferences about the coordination geometry have been supported by EXAFS analysis which has been used to determine the structural parameters for these complexes.

Individual differences in using geometric and featural cues to maintain spatial orientation: cue quantity and cue ambiguity are more important than cue type.

PubMed

Kelly, Jonathan W; McNamara, Timothy P; Bodenheimer, Bobby; Carr, Thomas H; Rieser, John J

2009-02-01

Two experiments explored the role of environmental cues in maintaining spatial orientation (sense of self-location and direction) during locomotion. Of particular interest was the importance of geometric cues (provided by environmental surfaces) and featural cues (nongeometric properties provided by striped walls) in maintaining spatial orientation. Participants performed a spatial updating task within virtual environments containing geometric or featural cues that were ambiguous or unambiguous indicators of self-location and direction. Cue type (geometric or featural) did not affect performance, but the number and ambiguity of environmental cues did. Gender differences, interpreted as a proxy for individual differences in spatial ability and/or experience, highlight the interaction between cue quantity and ambiguity. When environmental cues were ambiguous, men stayed oriented with either one or two cues, whereas women stayed oriented only with two. When environmental cues were unambiguous, women stayed oriented with one cue.

Principles of quasi-equivalence and Euclidean geometry govern the assembly of cubic and dodecahedral cores of pyruvate dehydrogenase complexes.

PubMed

Izard, T; Aevarsson, A; Allen, M D; Westphal, A H; Perham, R N; de Kok, A; Hol, W G

1999-02-16

The pyruvate dehydrogenase multienzyme complex (Mr of 5-10 million) is assembled around a structural core formed of multiple copies of dihydrolipoyl acetyltransferase (E2p), which exhibits the shape of either a cube or a dodecahedron, depending on the source. The crystal structures of the 60-meric dihydrolipoyl acyltransferase cores of Bacillus stearothermophilus and Enterococcus faecalis pyruvate dehydrogenase complexes were determined and revealed a remarkably hollow dodecahedron with an outer diameter of approximately 237 A, 12 large openings of approximately 52 A diameter across the fivefold axes, and an inner cavity with a diameter of approximately 118 A. Comparison of cubic and dodecahedral E2p assemblies shows that combining the principles of quasi-equivalence formulated by Caspar and Klug [Caspar, D. L. & Klug, A. (1962) Cold Spring Harbor Symp. Quant. Biol. 27, 1-4] with strict Euclidean geometric considerations results in predictions of the major features of the E2p dodecahedron matching the observed features almost exactly.

Contribution of low-temperature single-molecule techniques to structural issues of pigment–protein complexes from photosynthetic purple bacteria

PubMed Central

Löhner, Alexander; Cogdell, Richard

2018-01-01

As the electronic energies of the chromophores in a pigment–protein complex are imposed by the geometrical structure of the protein, this allows the spectral information obtained to be compared with predictions derived from structural models. Thereby, the single-molecule approach is particularly suited for the elucidation of specific, distinctive spectral features that are key for a particular model structure, and that would not be observable in ensemble-averaged spectra due to the heterogeneity of the biological objects. In this concise review, we illustrate with the example of the light-harvesting complexes from photosynthetic purple bacteria how results from low-temperature single-molecule spectroscopy can be used to discriminate between different structural models. Thereby the low-temperature approach provides two advantages: (i) owing to the negligible photobleaching, very long observation times become possible, and more importantly, (ii) at cryogenic temperatures, vibrational degrees of freedom are frozen out, leading to sharper spectral features and in turn to better resolved spectra. PMID:29321265

Genotypic Complexity of Fisher’s Geometric Model

PubMed Central

Hwang, Sungmin; Park, Su-Chan; Krug, Joachim

2017-01-01

Fisher’s geometric model was originally introduced to argue that complex adaptations must occur in small steps because of pleiotropic constraints. When supplemented with the assumption of additivity of mutational effects on phenotypic traits, it provides a simple mechanism for the emergence of genotypic epistasis from the nonlinear mapping of phenotypes to fitness. Of particular interest is the occurrence of reciprocal sign epistasis, which is a necessary condition for multipeaked genotypic fitness landscapes. Here we compute the probability that a pair of randomly chosen mutations interacts sign epistatically, which is found to decrease with increasing phenotypic dimension n, and varies nonmonotonically with the distance from the phenotypic optimum. We then derive expressions for the mean number of fitness maxima in genotypic landscapes comprised of all combinations of L random mutations. This number increases exponentially with L, and the corresponding growth rate is used as a measure of the complexity of the landscape. The dependence of the complexity on the model parameters is found to be surprisingly rich, and three distinct phases characterized by different landscape structures are identified. Our analysis shows that the phenotypic dimension, which is often referred to as phenotypic complexity, does not generally correlate with the complexity of fitness landscapes and that even organisms with a single phenotypic trait can have complex landscapes. Our results further inform the interpretation of experiments where the parameters of Fisher’s model have been inferred from data, and help to elucidate which features of empirical fitness landscapes can be described by this model. PMID:28450460

Folding and Fracturing of Rocks: the background

NASA Astrophysics Data System (ADS)

Ramsay, John G.

2017-04-01

This book was generated by structural geology teaching classes at Imperial College. I was appointed lecturer during 1957 and worked together with Dr Gilbert Wilson teaching basic structural geology at B.Sc level. I became convinced that the subject, being essentially based on geometric field observations, required a firm mathematical basis for its future development. In particular it seemed to me to require a very sound understanding of stress and strain. My field experience suggested that a knowledge of two- and three-demensional strain was critical in understanding natural tectonic processes. I found a rich confirmation for this in early publications of deformed fossils, oolitic limestones and spotted slates made by several geologists around the beginning of the 20th century (Sorby, Philips, Haughton, Harker) often using surprisingly sophisticated mathematical methods. These methods were discussed and elaborated in Folding and Fracturing of Rocks in a practical way. The geometric features of folds were related to folding mechanisms and the fold related small scale structures such as cleavage, schistosity and lineation explained in terms of rock strain. My work in the Scottish Highlands had shown just how repeated fold superposition could produce very complex geometric features, while further work in other localities suggested that such geometric complications are common in many orogenic zones. From the development of structural geological studies over the past decades it seems that the readers of this book have found many of the ideas set out are still of practical application. The mapping of these outcrop-scale structures should be emphasised in all field studies because they can be seen as ''fingerprints'' of regional scale tectonic processes. My own understanding of structural geology has been inspired by field work and I am of the opinion that future progress in understanding will be likewise based on careful observation and measurement of the features of naturally deformed rocks mathematically analysed using the concepts of three-dimensional continuum mechanics.

Modelling turbulent boundary layer flow over fractal-like multiscale terrain using large-eddy simulations and analytical tools.

PubMed

Yang, X I A; Meneveau, C

2017-04-13

In recent years, there has been growing interest in large-eddy simulation (LES) modelling of atmospheric boundary layers interacting with arrays of wind turbines on complex terrain. However, such terrain typically contains geometric features and roughness elements reaching down to small scales that typically cannot be resolved numerically. Thus subgrid-scale models for the unresolved features of the bottom roughness are needed for LES. Such knowledge is also required to model the effects of the ground surface 'underneath' a wind farm. Here we adapt a dynamic approach to determine subgrid-scale roughness parametrizations and apply it for the case of rough surfaces composed of cuboidal elements with broad size distributions, containing many scales. We first investigate the flow response to ground roughness of a few scales. LES with the dynamic roughness model which accounts for the drag of unresolved roughness is shown to provide resolution-independent results for the mean velocity distribution. Moreover, we develop an analytical roughness model that accounts for the sheltering effects of large-scale on small-scale roughness elements. Taking into account the shading effect, constraints from fundamental conservation laws, and assumptions of geometric self-similarity, the analytical roughness model is shown to provide analytical predictions that agree well with roughness parameters determined from LES.This article is part of the themed issue 'Wind energy in complex terrains'. © 2017 The Author(s).

Comparison of Point Matching Techniques for Road Network Matching

NASA Astrophysics Data System (ADS)

Hackeloeer, A.; Klasing, K.; Krisp, J. M.; Meng, L.

2013-05-01

Map conflation investigates the unique identification of geographical entities across different maps depicting the same geographic region. It involves a matching process which aims to find commonalities between geographic features. A specific subdomain of conflation called Road Network Matching establishes correspondences between road networks of different maps on multiple layers of abstraction, ranging from elementary point locations to high-level structures such as road segments or even subgraphs derived from the induced graph of a road network. The process of identifying points located on different maps by means of geometrical, topological and semantical information is called point matching. This paper provides an overview of various techniques for point matching, which is a fundamental requirement for subsequent matching steps focusing on complex high-level entities in geospatial networks. Common point matching approaches as well as certain combinations of these are described, classified and evaluated. Furthermore, a novel similarity metric called the Exact Angular Index is introduced, which considers both topological and geometrical aspects. The results offer a basis for further research on a bottom-up matching process for complex map features, which must rely upon findings derived from suitable point matching algorithms. In the context of Road Network Matching, reliable point matches provide an immediate starting point for finding matches between line segments describing the geometry and topology of road networks, which may in turn be used for performing a structural high-level matching on the network level.

Automated real-time search and analysis algorithms for a non-contact 3D profiling system

NASA Astrophysics Data System (ADS)

Haynes, Mark; Wu, Chih-Hang John; Beck, B. Terry; Peterman, Robert J.

2013-04-01

The purpose of this research is to develop a new means of identifying and extracting geometrical feature statistics from a non-contact precision-measurement 3D profilometer. Autonomous algorithms have been developed to search through large-scale Cartesian point clouds to identify and extract geometrical features. These algorithms are developed with the intent of providing real-time production quality control of cold-rolled steel wires. The steel wires in question are prestressing steel reinforcement wires for concrete members. The geometry of the wire is critical in the performance of the overall concrete structure. For this research a custom 3D non-contact profilometry system has been developed that utilizes laser displacement sensors for submicron resolution surface profiling. Optimizations in the control and sensory system allow for data points to be collected at up to an approximate 400,000 points per second. In order to achieve geometrical feature extraction and tolerancing with this large volume of data, the algorithms employed are optimized for parsing large data quantities. The methods used provide a unique means of maintaining high resolution data of the surface profiles while keeping algorithm running times within practical bounds for industrial application. By a combination of regional sampling, iterative search, spatial filtering, frequency filtering, spatial clustering, and template matching a robust feature identification method has been developed. These algorithms provide an autonomous means of verifying tolerances in geometrical features. The key method of identifying the features is through a combination of downhill simplex and geometrical feature templates. By performing downhill simplex through several procedural programming layers of different search and filtering techniques, very specific geometrical features can be identified within the point cloud and analyzed for proper tolerancing. Being able to perform this quality control in real time provides significant opportunities in cost savings in both equipment protection and waste minimization.

Infrared Spectroscopic Imaging for Prostate Pathology Practice

DTIC Science & Technology

2011-04-01

features – geometric properties of epithelial cells/nuclei and lumens – that are quantified based on H&E stained images as well as FT-IR images of...the samples. By restricting the features used to geometric measures, we sought to mimic the pattern recognition process employed by human experts, and...relatively dark and can be modeled as small elliptical areas in the stained images. This geometrical model is often confounded as multiple nuclei can be

A diagram retrieval method with multi-label learning

NASA Astrophysics Data System (ADS)

Fu, Songping; Lu, Xiaoqing; Liu, Lu; Qu, Jingwei; Tang, Zhi

2015-01-01

In recent years, the retrieval of plane geometry figures (PGFs) has attracted increasing attention in the fields of mathematics education and computer science. However, the high cost of matching complex PGF features leads to the low efficiency of most retrieval systems. This paper proposes an indirect classification method based on multi-label learning, which improves retrieval efficiency by reducing the scope of compare operation from the whole database to small candidate groups. Label correlations among PGFs are taken into account for the multi-label classification task. The primitive feature selection for multi-label learning and the feature description of visual geometric elements are conducted individually to match similar PGFs. The experiment results show the competitive performance of the proposed method compared with existing PGF retrieval methods in terms of both time consumption and retrieval quality.

Volumetric quantitative characterization of human patellar cartilage with topological and geometrical features on phase-contrast X-ray computed tomography.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Wismüller, Axel

2015-11-01

Phase-contrast X-ray computed tomography (PCI-CT) has attracted significant interest in recent years for its ability to provide significantly improved image contrast in low absorbing materials such as soft biological tissue. In the research context of cartilage imaging, previous studies have demonstrated the ability of PCI-CT to visualize structural details of human patellar cartilage matrix and capture changes to chondrocyte organization induced by osteoarthritis. This study evaluates the use of geometrical and topological features for volumetric characterization of such chondrocyte patterns in the presence (or absence) of osteoarthritic damage. Geometrical features derived from the scaling index method (SIM) and topological features derived from Minkowski Functionals were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These features were subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver operating characteristic curve (AUC). Our results show that the classification performance of SIM-derived geometrical features (AUC: 0.90 ± 0.09) is significantly better than Minkowski Functionals volume (AUC: 0.54 ± 0.02), surface (AUC: 0.72 ± 0.06), mean breadth (AUC: 0.74 ± 0.06) and Euler characteristic (AUC: 0.78 ± 0.04) (p < 10(-4)). These results suggest that such geometrical features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix in an automated manner, while also enabling classification of cartilage as healthy or osteoarthritic with high accuracy. Such features could potentially serve as diagnostic imaging markers for evaluating osteoarthritis progression and its response to different therapeutic intervention strategies.

Phase contrast imaging X-ray computed tomography: quantitative characterization of human patellar cartilage matrix with topological and geometrical features

NASA Astrophysics Data System (ADS)

Nagarajan, Mahesh B.; Coan, Paola; Huber, Markus B.; Diemoz, Paul C.; Wismüller, Axel

2014-03-01

Current assessment of cartilage is primarily based on identification of indirect markers such as joint space narrowing and increased subchondral bone density on x-ray images. In this context, phase contrast CT imaging (PCI-CT) has recently emerged as a novel imaging technique that allows a direct examination of chondrocyte patterns and their correlation to osteoarthritis through visualization of cartilage soft tissue. This study investigates the use of topological and geometrical approaches for characterizing chondrocyte patterns in the radial zone of the knee cartilage matrix in the presence and absence of osteoarthritic damage. For this purpose, topological features derived from Minkowski Functionals and geometric features derived from the Scaling Index Method (SIM) were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of healthy and osteoarthritic specimens of human patellar cartilage. The extracted features were then used in a machine learning task involving support vector regression to classify ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The best classification performance was observed with high-dimensional geometrical feature vectors derived from SIM (0.95 ± 0.06) which outperformed all Minkowski Functionals (p < 0.001). These results suggest that such quantitative analysis of chondrocyte patterns in human patellar cartilage matrix involving SIM-derived geometrical features can distinguish between healthy and osteoarthritic tissue with high accuracy.

Trajectory analysis via a geometric feature space approach

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

Rintoul, Mark D.; Wilson, Andrew T.

This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally,more » these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.« less

Trajectory analysis via a geometric feature space approach

DOE PAGES

Rintoul, Mark D.; Wilson, Andrew T.

2015-10-05

This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally,more » these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.« less

Neutrino Mixing and the Double Tetrahedral Group

NASA Astrophysics Data System (ADS)

Bentov, Yoni; Zee, A.

2013-11-01

In the spirit of a previous study of the tetrahedral group T ≃A4, we discuss a minimalist scheme to derive the neutrino mixing matrix using the double tetrahedral group T‧, the double cover of T. The new features are three distinct two-dimensional representations and complex Clebsch-Gordan coefficients, which can result in a geometric source of CP violation in the neutrino mass matrix. In an appendix, we derive explicitly the relevant group theory for the tetrahedral group T and its double cover T‧.

Multiscale Cues Drive Collective Cell Migration

NASA Astrophysics Data System (ADS)

Nam, Ki-Hwan; Kim, Peter; Wood, David K.; Kwon, Sunghoon; Provenzano, Paolo P.; Kim, Deok-Ho

2016-07-01

To investigate complex biophysical relationships driving directed cell migration, we developed a biomimetic platform that allows perturbation of microscale geometric constraints with concomitant nanoscale contact guidance architectures. This permits us to elucidate the influence, and parse out the relative contribution, of multiscale features, and define how these physical inputs are jointly processed with oncogenic signaling. We demonstrate that collective cell migration is profoundly enhanced by the addition of contract guidance cues when not otherwise constrained. However, while nanoscale cues promoted migration in all cases, microscale directed migration cues are dominant as the geometric constraint narrows, a behavior that is well explained by stochastic diffusion anisotropy modeling. Further, oncogene activation (i.e. mutant PIK3CA) resulted in profoundly increased migration where extracellular multiscale directed migration cues and intrinsic signaling synergistically conspire to greatly outperform normal cells or any extracellular guidance cues in isolation.

Performance Evaluation of Various STL File Mesh Refining Algorithms Applied for FDM-RP Process

NASA Astrophysics Data System (ADS)

Ledalla, Siva Rama Krishna; Tirupathi, Balaji; Sriram, Venkatesh

2018-06-01

Layered manufacturing machines use the stereolithography (STL) file to build parts. When a curved surface is converted from a computer aided design (CAD) file to STL, it results in a geometrical distortion and chordal error. Parts manufactured with this file, might not satisfy geometric dimensioning and tolerance requirements due to approximated geometry. Current algorithms built in CAD packages have export options to globally reduce this distortion, which leads to an increase in the file size and pre-processing time. In this work, different mesh subdivision algorithms are applied on STL file of a complex geometric features using MeshLab software. The mesh subdivision algorithms considered in this work are modified butterfly subdivision technique, loops sub division technique and general triangular midpoint sub division technique. A comparative study is made with respect to volume and the build time using the above techniques. It is found that triangular midpoint sub division algorithm is more suitable for the geometry under consideration. Only the wheel cap part is then manufactured on Stratasys MOJO FDM machine. The surface roughness of the part is measured on Talysurf surface roughness tester.

Algebraic reasoning for the enhancement of data-driven building reconstructions

NASA Astrophysics Data System (ADS)

Meidow, Jochen; Hammer, Horst

2016-04-01

Data-driven approaches for the reconstruction of buildings feature the flexibility needed to capture objects of arbitrary shape. To recognize man-made structures, geometric relations such as orthogonality or parallelism have to be detected. These constraints are typically formulated as sets of multivariate polynomials. For the enforcement of the constraints within an adjustment process, a set of independent and consistent geometric constraints has to be determined. Gröbner bases are an ideal tool to identify such sets exactly. A complete workflow for geometric reasoning is presented to obtain boundary representations of solids based on given point clouds. The constraints are formulated in homogeneous coordinates, which results in simple polynomials suitable for the successful derivation of Gröbner bases for algebraic reasoning. Strategies for the reduction of the algebraical complexity are presented. To enforce the constraints, an adjustment model is introduced, which is able to cope with homogeneous coordinates along with their singular covariance matrices. The feasibility and the potential of the approach are demonstrated by the analysis of a real data set.

Young Children's Use of Features to Reorient Is More than Just Associative: Further Evidence against a Modular View of Spatial Processing

ERIC Educational Resources Information Center

Newcombe, Nora S.; Ratliff, Kristin R.; Shallcross, Wendy L.; Twyman, Alexandra D.

2010-01-01

Proponents of a geometric module have argued that instances of young children's use of features as well as geometry to reorient can be explained by a two-stage process. In this model, only the first stage is a true reorientation, accomplished by using geometric information alone; features are considered in a second stage using association (Lee,…

Propagation, cascades, and agreement dynamics in complex communication and social networks

NASA Astrophysics Data System (ADS)

Lu, Qiming

Many modern and important technological, social, information and infrastructure systems can be viewed as complex systems with a large number of interacting components. Models of complex networks and dynamical interactions, as well as their applications are of fundamental interests in many aspects. Here, several stylized models of multiplex propagation and opinion dynamics are investigated on complex and empirical social networks. We first investigate cascade dynamics in threshold-controlled (multiplex) propagation on random geometric networks. We find that such local dynamics can serve as an efficient, robust, and reliable prototypical activation protocol in sensor networks in responding to various alarm scenarios. We also consider the same dynamics on a modified network by adding a few long-range communication links, resulting in a small-world network. We find that such construction can further enhance and optimize the speed of the network's response, while keeping energy consumption at a manageable level. We also investigate a prototypical agent-based model, the Naming Game, on two-dimensional random geometric networks. The Naming Game [A. Baronchelli et al., J. Stat. Mech.: Theory Exp. (2006) P06014.] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the Naming Games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially-embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case. When applying the model of Naming Game on empirical social networks, this stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.

Geometric modeling of subcellular structures, organelles, and multiprotein complexes

PubMed Central

Feng, Xin; Xia, Kelin; Tong, Yiying; Wei, Guo-Wei

2013-01-01

SUMMARY Recently, the structure, function, stability, and dynamics of subcellular structures, organelles, and multi-protein complexes have emerged as a leading interest in structural biology. Geometric modeling not only provides visualizations of shapes for large biomolecular complexes but also fills the gap between structural information and theoretical modeling, and enables the understanding of function, stability, and dynamics. This paper introduces a suite of computational tools for volumetric data processing, information extraction, surface mesh rendering, geometric measurement, and curvature estimation of biomolecular complexes. Particular emphasis is given to the modeling of cryo-electron microscopy data. Lagrangian-triangle meshes are employed for the surface presentation. On the basis of this representation, algorithms are developed for surface area and surface-enclosed volume calculation, and curvature estimation. Methods for volumetric meshing have also been presented. Because the technological development in computer science and mathematics has led to multiple choices at each stage of the geometric modeling, we discuss the rationales in the design and selection of various algorithms. Analytical models are designed to test the computational accuracy and convergence of proposed algorithms. Finally, we select a set of six cryo-electron microscopy data representing typical subcellular complexes to demonstrate the efficacy of the proposed algorithms in handling biomolecular surfaces and explore their capability of geometric characterization of binding targets. This paper offers a comprehensive protocol for the geometric modeling of subcellular structures, organelles, and multiprotein complexes. PMID:23212797

Iris-based medical analysis by geometric deformation features.

PubMed

Ma, Lin; Zhang, D; Li, Naimin; Cai, Yan; Zuo, Wangmeng; Wang, Kuanguan

2013-01-01

Iris analysis studies the relationship between human health and changes in the anatomy of the iris. Apart from the fact that iris recognition focuses on modeling the overall structure of the iris, iris diagnosis emphasizes the detecting and analyzing of local variations in the characteristics of irises. This paper focuses on studying the geometrical structure changes in irises that are caused by gastrointestinal diseases, and on measuring the observable deformations in the geometrical structures of irises that are related to roundness, diameter and other geometric forms of the pupil and the collarette. Pupil and collarette based features are defined and extracted. A series of experiments are implemented on our experimental pathological iris database, including manual clustering of both normal and pathological iris images, manual classification by non-specialists, manual classification by individuals with a medical background, classification ability verification for the proposed features, and disease recognition by applying the proposed features. The results prove the effectiveness and clinical diagnostic significance of the proposed features and a reliable recognition performance for automatic disease diagnosis. Our research results offer a novel systematic perspective for iridology studies and promote the progress of both theoretical and practical work in iris diagnosis.

Multi-scale clustering by building a robust and self correcting ultrametric topology on data points.

PubMed

Fushing, Hsieh; Wang, Hui; Vanderwaal, Kimberly; McCowan, Brenda; Koehl, Patrice

2013-01-01

The advent of high-throughput technologies and the concurrent advances in information sciences have led to an explosion in size and complexity of the data sets collected in biological sciences. The biggest challenge today is to assimilate this wealth of information into a conceptual framework that will help us decipher biological functions. A large and complex collection of data, usually called a data cloud, naturally embeds multi-scale characteristics and features, generically termed geometry. Understanding this geometry is the foundation for extracting knowledge from data. We have developed a new methodology, called data cloud geometry-tree (DCG-tree), to resolve this challenge. This new procedure has two main features that are keys to its success. Firstly, it derives from the empirical similarity measurements a hierarchy of clustering configurations that captures the geometric structure of the data. This hierarchy is then transformed into an ultrametric space, which is then represented via an ultrametric tree or a Parisi matrix. Secondly, it has a built-in mechanism for self-correcting clustering membership across different tree levels. We have compared the trees generated with this new algorithm to equivalent trees derived with the standard Hierarchical Clustering method on simulated as well as real data clouds from fMRI brain connectivity studies, cancer genomics, giraffe social networks, and Lewis Carroll's Doublets network. In each of these cases, we have shown that the DCG trees are more robust and less sensitive to measurement errors, and that they provide a better quantification of the multi-scale geometric structures of the data. As such, DCG-tree is an effective tool for analyzing complex biological data sets.

Goldfish (Carassius auratus) matching geometric and featural cues: a reinterpretation of some of the data of Vargas, López, Salas, and Thinus-Blanc (2004).

PubMed

Cheng, Ken

2005-11-01

Vargas, López, Salas, and Thinus-Blanc showed that goldfish (Carassius auratus) can use both geometric and featural cues in relocating a target corner in a rectangular enclosure. When featural cues (arrangement of striped walls) were put in conflict with geometric cues, results differed according to target location during training. Vargas, López, et al. explained the results of their cue conflict in terms of 2 different strategies: mapping and cue guidance. I provide an alternative, more parsimonious interpretation in which the same strategy of attempting to match as many cues as possible applies to both cases. ((c) 2005 APA, all rights reserved).

Dynamic facial expression recognition based on geometric and texture features

NASA Astrophysics Data System (ADS)

Li, Ming; Wang, Zengfu

2018-04-01

Recently, dynamic facial expression recognition in videos has attracted growing attention. In this paper, we propose a novel dynamic facial expression recognition method by using geometric and texture features. In our system, the facial landmark movements and texture variations upon pairwise images are used to perform the dynamic facial expression recognition tasks. For one facial expression sequence, pairwise images are created between the first frame and each of its subsequent frames. Integration of both geometric and texture features further enhances the representation of the facial expressions. Finally, Support Vector Machine is used for facial expression recognition. Experiments conducted on the extended Cohn-Kanade database show that our proposed method can achieve a competitive performance with other methods.

Using Geometry-Based Metrics as Part of Fitness-for-Purpose Evaluations of 3D City Models

NASA Astrophysics Data System (ADS)

Wong, K.; Ellul, C.

2016-10-01

Three-dimensional geospatial information is being increasingly used in a range of tasks beyond visualisation. 3D datasets, however, are often being produced without exact specifications and at mixed levels of geometric complexity. This leads to variations within the models' geometric and semantic complexity as well as the degree of deviation from the corresponding real world objects. Existing descriptors and measures of 3D data such as CityGML's level of detail are perhaps only partially sufficient in communicating data quality and fitness-for-purpose. This study investigates whether alternative, automated, geometry-based metrics describing the variation of complexity within 3D datasets could provide additional relevant information as part of a process of fitness-for-purpose evaluation. The metrics include: mean vertex/edge/face counts per building; vertex/face ratio; minimum 2D footprint area and; minimum feature length. Each metric was tested on six 3D city models from international locations. The results show that geometry-based metrics can provide additional information on 3D city models as part of fitness-for-purpose evaluations. The metrics, while they cannot be used in isolation, may provide a complement to enhance existing data descriptors if backed up with local knowledge, where possible.

Evaluating molecular cobalt complexes for the conversion of N2 to NH3.

PubMed

Del Castillo, Trevor J; Thompson, Niklas B; Suess, Daniel L M; Ung, Gaël; Peters, Jonas C

2015-10-05

Well-defined molecular catalysts for the reduction of N2 to NH3 with protons and electrons remain very rare despite decades of interest and are currently limited to systems featuring molybdenum or iron. This report details the synthesis of a molecular cobalt complex that generates superstoichiometric yields of NH3 (>200% NH3 per Co-N2 precursor) via the direct reduction of N2 with protons and electrons. While the NH3 yields reported herein are modest by comparison to those of previously described iron and molybdenum systems, they intimate that other metals are likely to be viable as molecular N2 reduction catalysts. Additionally, a comparison of the featured tris(phosphine)borane Co-N2 complex with structurally related Co-N2 and Fe-N2 species shows how remarkably sensitive the N2 reduction performance of potential precatalysts is. These studies enable consideration of the structural and electronic effects that are likely relevant to N2 conversion activity, including the π basicity, charge state, and geometric flexibility.

Robust pattern decoding in shape-coded structured light

NASA Astrophysics Data System (ADS)

Tang, Suming; Zhang, Xu; Song, Zhan; Song, Lifang; Zeng, Hai

2017-09-01

Decoding is a challenging and complex problem in a coded structured light system. In this paper, a robust pattern decoding method is proposed for the shape-coded structured light in which the pattern is designed as grid shape with embedded geometrical shapes. In our decoding method, advancements are made at three steps. First, a multi-template feature detection algorithm is introduced to detect the feature point which is the intersection of each two orthogonal grid-lines. Second, pattern element identification is modelled as a supervised classification problem and the deep neural network technique is applied for the accurate classification of pattern elements. Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions. Third, an error correction mechanism based on epipolar constraint, coplanarity constraint and topological constraint is presented to reduce the false matches. In the experiments, several complex objects including human hand are chosen to test the accuracy and robustness of the proposed method. The experimental results show that our decoding method not only has high decoding accuracy, but also owns strong robustness to surface color and complex textures.

Reorienting in Images of a Three-Dimensional Environment

ERIC Educational Resources Information Center

Kelly, Debbie M.; Bischof, Walter F.

2005-01-01

Adult humans searched for a hidden goal in images depicting 3-dimensional rooms. Images contained either featural cues, geometric cues, or both, which could be used to determine the correct location of the goal. In Experiment 1, participants learned to use featural and geometric information equally well. However, men and women showed significant…

Modeling and analysis of the chip formation and transient cutting force during elliptical vibration cutting process

NASA Astrophysics Data System (ADS)

Lin, Jieqiong; Guan, Liang; Lu, Mingming; Han, Jinguo; Kan, Yudi

2017-12-01

In traditional diamond cutting, the cutting force is usually large and it will affect tool life and machining quality. Elliptical vibration cutting (EVC) as one of the ultra-precision machining technologies has a lot of advantages, such as reduces cutting force, extend tool life and so on. It's difficult to predict the transient cutting force of EVC due to its unique elliptical motion trajectory. Study on chip formation will helpfully to predict cutting force. The geometric feature of chip has important effects on cutting force, however, few scholars have studied the chip formation. In order to investigate the time-varying cutting force of EVC, the geometric feature model of chip is established based on analysis of chip formation, and the effects of cutting parameters on the geometric feature of chip are analyzed. To predict transient force quickly and effectively, the geometric feature of chip is introduced into the cutting force model. The calculated results show that the error between the predicted cutting force in this paper and that in the literature is less than 2%, which proves its feasibility.

Quench dynamics of the three-dimensional U(1) complex field theory: Geometric and scaling characterizations of the vortex tangle.

PubMed

Kobayashi, Michikazu; Cugliandolo, Leticia F

2016-12-01

We present a detailed study of the equilibrium properties and stochastic dynamic evolution of the U(1)-invariant relativistic complex field theory in three dimensions. This model has been used to describe, in various limits, properties of relativistic bosons at finite chemical potential, type II superconductors, magnetic materials, and aspects of cosmology. We characterize the thermodynamic second-order phase transition in different ways. We study the equilibrium vortex configurations and their statistical and geometrical properties in equilibrium at all temperatures. We show that at very high temperature the statistics of the filaments is the one of fully packed loop models. We identify the temperature, within the ordered phase, at which the number density of vortex lengths falls off algebraically and we associate it to a geometric percolation transition that we characterize in various ways. We measure the fractal properties of the vortex tangle at this threshold. Next, we perform infinite rate quenches from equilibrium in the disordered phase, across the thermodynamic critical point, and deep into the ordered phase. We show that three time regimes can be distinguished: a first approach toward a state that, within numerical accuracy, shares many features with the one at the percolation threshold; a later coarsening process that does not alter, at sufficiently low temperature, the fractal properties of the long vortex loops; and a final approach to equilibrium. These features are independent of the reconnection rule used to build the vortex lines. In each of these regimes we identify the various length scales of the vortices in the system. We also study the scaling properties of the ordering process and the progressive annihilation of topological defects and we prove that the time-dependence of the time-evolving vortex tangle can be described within the dynamic scaling framework.

Geometrically robust image watermarking by sector-shaped partitioning of geometric-invariant regions.

PubMed

Tian, Huawei; Zhao, Yao; Ni, Rongrong; Cao, Gang

2009-11-23

In a feature-based geometrically robust watermarking system, it is a challenging task to detect geometric-invariant regions (GIRs) which can survive a broad range of image processing operations. Instead of commonly used Harris detector or Mexican hat wavelet method, a more robust corner detector named multi-scale curvature product (MSCP) is adopted to extract salient features in this paper. Based on such features, disk-like GIRs are found, which consists of three steps. First, robust edge contours are extracted. Then, MSCP is utilized to detect the centers for GIRs. Third, the characteristic scale selection is performed to calculate the radius of each GIR. A novel sector-shaped partitioning method for the GIRs is designed, which can divide a GIR into several sector discs with the help of the most important corner (MIC). The watermark message is then embedded bit by bit in each sector by using Quantization Index Modulation (QIM). The GIRs and the divided sector discs are invariant to geometric transforms, so the watermarking method inherently has high robustness against geometric attacks. Experimental results show that the scheme has a better robustness against various image processing operations including common processing attacks, affine transforms, cropping, and random bending attack (RBA) than the previous approaches.

One-Dimensional Chirality: Strong Optical Activity in Epsilon-Near-Zero Metamaterials.

PubMed

Rizza, Carlo; Di Falco, Andrea; Scalora, Michael; Ciattoni, Alessandro

2015-07-31

We suggest that electromagnetic chirality, generally displayed by 3D or 2D complex chiral structures, can occur in 1D patterned composites whose components are achiral. This feature is highly unexpected in a 1D system which is geometrically achiral since its mirror image can always be superposed onto it by a 180 deg rotation. We analytically evaluate from first principles the bianisotropic response of multilayered metamaterials and we show that the chiral tensor is not vanishing if the system is geometrically one-dimensional chiral; i.e., its mirror image cannot be superposed onto it by using translations without resorting to rotations. As a signature of 1D chirality, we show that 1D chiral metamaterials support optical activity and we prove that this phenomenon undergoes a dramatic nonresonant enhancement in the epsilon-near-zero regime where the magnetoelectric coupling can become dominant in the constitutive relations.

Generalized Toda theory from six dimensions and the conifold

NASA Astrophysics Data System (ADS)

van Leuven, Sam; Oling, Gerben

2017-12-01

Recently, a physical derivation of the Alday-Gaiotto-Tachikawa correspondence has been put forward. A crucial role is played by the complex Chern-Simons theory arising in the 3d-3d correspondence, whose boundary modes lead to Toda theory on a Riemann surface. We explore several features of this derivation and subsequently argue that it can be extended to a generalization of the AGT correspondence. The latter involves codimension two defects in six dimensions that wrap the Riemann surface. We use a purely geometrical description of these defects and find that the generalized AGT setup can be modeled in a pole region using generalized conifolds. Furthermore, we argue that the ordinary conifold clarifies several features of the derivation of the original AGT correspondence.

UWB tomosynthesis of objects in mediums with metal inclusions

NASA Astrophysics Data System (ADS)

Yakubov, V. P.; Shipilov, S. E.; Sukhanov, D. Ya; Minin, I. V.; Minin, O. V.

2017-08-01

Radiowave tomography of dielectric objects containing metal inclusions is a rather complex problem, since the scattering of waves by dielectric inhomogeneities occurs against the background of substantially stronger reflections from metal parts, even if they are geometrically small. The arising features of obtaining a tomogram in such conditions, including overcoming of disguising by reinforcing ribbons and the appearance of locational shadows at different depths, are discussed in the paper. Herewith principled importance to achieve high focusing of UWB radiation by tomosynthesis is noted on the basis of direct experimental data.

Engineering Design of Safe Automobile Front Strut Tower Brace with Predetermined Destruction

NASA Astrophysics Data System (ADS)

Mironenko, R. Ye; Balaev, E. Yu; Blednova, Zh M.

2018-03-01

This paper shows the developed design of an automobile front strut tower brace instantly breakable on reaching a predetermined value impact load, which allows the impact load not to be transferred to the opposite strut. An automobile front strut tower brace with the directed destruction V-shaped element using the SolidWorks and SolidWorks Simulations software complex was developed, designed and analyzed. The obtained data were confirmed experimentally. By changing geometric features of the V-shaped element, it is possible to change the impact load value required for its destruction.

Low-angle normal faulting and isostatic response in the Gulf of Suez: Evidence from seismic interpretation and geometric reconstruction

NASA Technical Reports Server (NTRS)

Perry, S. K.; Schamel, S.

1985-01-01

Tectonic extension within continental crust creates a variety of major features best classed as extensional orogens. These features have come under increasing attention in recent years, with the welding of field observation and theoretical concepts. Most recent advances have come from the Basin and Range Province of the southwestern United States and from the North Sea. Application of these geometric and isostatic concepts, in combination with seismic interpretation, to the southern Gulf of Suez, an active extensional orogen, allows generation of detailed structural maps and geometrically balanced sections which suggest a regional structural model. Geometric models which should prove to be a valuable adjunct to numerical and thermal models for the rifting process are discussed.

Assessing the contributions of surface waves and complex rays to far-field Mie scattering by use of the Debye series

NASA Technical Reports Server (NTRS)

Hovenac, Edward A.; Lock, James A.

1991-01-01

The contributions of complex rays and the secondary radiation shed by surface waves to scattering by a dielectric sphere are calculated in the context of the Debye series expansion of the Mie scattering amplitudes. Also, the contributions of geometrical rays are reviewed and compared with the Debye series. Interference effects between surface waves, complex waves, and geometrical waves are calculated, and the possibility of observing these interference effects is discussed. Experimental data supporting the observation of a surface wave-geometrical pattern is presented.

Geometric and Algebraic Approaches in the Concept of Complex Numbers

ERIC Educational Resources Information Center

Panaoura, A.; Elia, I.; Gagatsis, A.; Giatilis, G.-P.

2006-01-01

This study explores pupils' performance and processes in tasks involving equations and inequalities of complex numbers requiring conversions from a geometric representation to an algebraic representation and conversions in the reverse direction, and also in complex numbers problem solving. Data were collected from 95 pupils of the final grade from…

Development of the local magnification method for quantitative evaluation of endoscope geometric distortion

NASA Astrophysics Data System (ADS)

Wang, Quanzeng; Cheng, Wei-Chung; Suresh, Nitin; Hua, Hong

2016-05-01

With improved diagnostic capabilities and complex optical designs, endoscopic technologies are advancing. As one of the several important optical performance characteristics, geometric distortion can negatively affect size estimation and feature identification related diagnosis. Therefore, a quantitative and simple distortion evaluation method is imperative for both the endoscopic industry and the medical device regulatory agent. However, no such method is available yet. While the image correction techniques are rather mature, they heavily depend on computational power to process multidimensional image data based on complex mathematical model, i.e., difficult to understand. Some commonly used distortion evaluation methods, such as the picture height distortion (DPH) or radial distortion (DRAD), are either too simple to accurately describe the distortion or subject to the error of deriving a reference image. We developed the basic local magnification (ML) method to evaluate endoscope distortion. Based on the method, we also developed ways to calculate DPH and DRAD. The method overcomes the aforementioned limitations, has clear physical meaning in the whole field of view, and can facilitate lesion size estimation during diagnosis. Most importantly, the method can facilitate endoscopic technology to market and potentially be adopted in an international endoscope standard.

Potentiation and Overshadowing of Shape by Wall Color in a Kite-Shaped Maze Using Rats in a Foraging Task

ERIC Educational Resources Information Center

Cole, Mark R.; Gibson, Laura; Pollack, Adam; Yates, Lynsey

2011-01-01

The interaction between redundant geometric and featural cues in open field search tasks has been examined widely with results that are not always consistent. Cheng (1986) found evidence that when searching for food in rectangular environments, rats used the geometrical characteristics of the environment rather than local featural cues, suggesting…

Geometric correction of satellite data using curvilinear features and virtual control points

NASA Technical Reports Server (NTRS)

Algazi, V. R.; Ford, G. E.; Meyer, D. I.

1979-01-01

A simple, yet effective procedure for the geometric correction of partial Landsat scenes is described. The procedure is based on the acquisition of actual and virtual control points from the line printer output of enhanced curvilinear features. The accuracy of this method compares favorably with that of the conventional approach in which an interactive image display system is employed.

Computer-aided diagnosis of mammographic masses using geometric verification-based image retrieval

NASA Astrophysics Data System (ADS)

Li, Qingliang; Shi, Weili; Yang, Huamin; Zhang, Huimao; Li, Guoxin; Chen, Tao; Mori, Kensaku; Jiang, Zhengang

2017-03-01

Computer-Aided Diagnosis of masses in mammograms is an important indicator of breast cancer. The use of retrieval systems in breast examination is increasing gradually. In this respect, the method of exploiting the vocabulary tree framework and the inverted file in the mammographic masse retrieval have been proved high accuracy and excellent scalability. However it just considered the features in each image as a visual word and had ignored the spatial configurations of features. It greatly affect the retrieval performance. To overcome this drawback, we introduce the geometric verification method to retrieval in mammographic masses. First of all, we obtain corresponding match features based on the vocabulary tree framework and the inverted file. After that, we grasps the main point of local similarity characteristic of deformations in the local regions by constructing the circle regions of corresponding pairs. Meanwhile we segment the circle to express the geometric relationship of local matches in the area and generate the spatial encoding strictly. Finally we judge whether the matched features are correct or not, based on verifying the all spatial encoding are whether satisfied the geometric consistency. Experiments show the promising results of our approach.

Synoptic evaluation of scale-dependent metrics for hydrographic line feature geometry

USGS Publications Warehouse

Stanislawski, Larry V.; Buttenfield, Barbara P.; Raposo, Paulo; Cameron, Madeline; Falgout, Jeff T.

2015-01-01

Methods of acquisition and feature simplification for vector feature data impact cartographic representations and scientific investigations of these data, and are therefore important considerations for geographic information science (Haunert and Sester 2008). After initial collection, linear features may be simplified to reduce excessive detail or to furnish a reduced-scale version of the features through cartographic generalization (Regnauld and McMaster 2008, Stanislawski et al. 2014). A variety of algorithms exist to simplify linear cartographic features, and all of the methods affect the positional accuracy of the features (Shahriari and Tao 2002, Regnauld and McMaster 2008, Stanislawski et al. 2012). In general, simplification operations are controlled by one or more tolerance parameters that limit the amount of positional change the operation can make to features. Using a single tolerance value can have varying levels of positional change on features; depending on local shape, texture, or geometric characteristics of the original features (McMaster and Shea 1992, Shahriari and Tao 2002, Buttenfield et al. 2010). Consequently, numerous researchers have advocated calibration of simplification parameters to control quantifiable properties of resulting changes to the features (Li and Openshaw 1990, Raposo 2013, Tobler 1988, Veregin 2000, and Buttenfield, 1986, 1989).This research identifies relations between local topographic conditions and geometric characteristics of linear features that are available in the National Hydrography Dataset (NHD). The NHD is a comprehensive vector dataset of surface 18 th ICA Workshop on Generalisation and Multiple Representation, Rio de Janiero, Brazil 2015 2 water features within the United States that is maintained by the U.S. Geological Survey (USGS). In this paper, geometric characteristics of cartographic representations for natural stream and river features are summarized for subbasin watersheds within entire regions of the conterminous United States and compared to topographic metrics. A concurrent processing workflow is implemented using a Linux high-performance computing cluster to simultaneously process multiple subbasins, and thereby complete the work in a fraction of the time required for a single-process environment. In addition, similar metrics are generated for several levels of simplification of the hydrographic features to quantify the effects of simplification over the various landscape conditions. Objectives of this exploratory investigation are to quantify geometric characteristics of linear hydrographic features over the various terrain conditions within the conterminous United States and thereby illuminate relations between stream geomorphological conditions and cartographic representation. The synoptic view of these characteristics over regional watersheds that is afforded through concurrent processing, in conjunction with terrain conditions, may reveal patterns for classifying cartographic stream features into stream geomorphological classes. Furthermore, the synoptic measurement of the amount of change in geometric characteristics caused by the several levels of simplification can enable estimation of tolerance values that appropriately control simplification-induced geometric change of the cartographic features within the various geomorphological classes in the country. Hence, these empirically derived rules or relations could help generate multiscale-representations of features through automated generalization that adequately maintain surface drainage variations and patterns reflective of the natural stream geomorphological conditions across the country.

A new technique for solving puzzles.

PubMed

Makridis, Michael; Papamarkos, Nikos

2010-06-01

This paper proposes a new technique for solving jigsaw puzzles. The novelty of the proposed technique is that it provides an automatic jigsaw puzzle solution without any initial restriction about the shape of pieces, the number of neighbor pieces, etc. The proposed technique uses both curve- and color-matching similarity features. A recurrent procedure is applied, which compares and merges puzzle pieces in pairs, until the original puzzle image is reformed. Geometrical and color features are extracted on the characteristic points (CPs) of the puzzle pieces. CPs, which can be considered as high curvature points, are detected by a rotationally invariant corner detection algorithm. The features which are associated with color are provided by applying a color reduction technique using the Kohonen self-organized feature map. Finally, a postprocessing stage checks and corrects the relative position between puzzle pieces to improve the quality of the resulting image. Experimental results prove the efficiency of the proposed technique, which can be further extended to deal with even more complex jigsaw puzzle problems.

Mathematics and morphogenesis of cities: A geometrical approach

NASA Astrophysics Data System (ADS)

Courtat, Thomas; Gloaguen, Catherine; Douady, Stephane

2011-03-01

Cities are living organisms. They are out of equilibrium, open systems that never stop developing and sometimes die. The local geography can be compared to a shell constraining its development. In brief, a city’s current layout is a step in a running morphogenesis process. Thus cities display a huge diversity of shapes and none of the traditional models, from random graphs, complex networks theory, or stochastic geometry, takes into account the geometrical, functional, and dynamical aspects of a city in the same framework. We present here a global mathematical model dedicated to cities that permits describing, manipulating, and explaining cities’ overall shape and layout of their street systems. This street-based framework conciliates the topological and geometrical sides of the problem. From the static analysis of several French towns (topology of first and second order, anisotropy, streets scaling) we make the hypothesis that the development of a city follows a logic of division or extension of space. We propose a dynamical model that mimics this logic and that, from simple general rules and a few parameters, succeeds in generating a large diversity of cities and in reproducing the general features the static analysis has pointed out.

Effect of Morphologic Features of Neurons on the Extracellular Electric Potential: A Simulation Study Using Cable Theory and Electro-Quasi-Static Equations.

PubMed

Bestel, R; Appali, R; van Rienen, U; Thielemann, C

2017-11-01

Microelectrode arrays serve as an indispensable tool in electro-physiological research to study the electrical activity of neural cells, enabling measurements of single cell as well as network communication analysis. Recent experimental studies have reported that the neuronal geometry has an influence on electrical signaling and extracellular recordings. However, the corresponding mechanisms are not yet fully understood and require further investigation. Allowing systematic parameter studies, computational modeling provides the opportunity to examine the underlying effects that influence extracellular potentials. In this letter, we present an in silico single cell model to analyze the effect of geometrical variability on the extracellular electric potentials. We describe finite element models of a single neuron with varying geometric complexity in three-dimensional space. The electric potential generation of the neuron is modeled using Hodgkin-Huxley equations. The signal propagation is described with electro-quasi-static equations, and results are compared with corresponding cable equation descriptions. Our results show that both the geometric dimensions and the distribution of ion channels of a neuron are critical factors that significantly influence both the amplitude and shape of extracellular potentials.

Complex Ordered Patterns in Mechanical Instability Induced Geometrically Frustrated Triangular Cellular Structures

NASA Astrophysics Data System (ADS)

Kang, Sung Hoon; Shan, Sicong; Košmrlj, Andrej; Noorduin, Wim L.; Shian, Samuel; Weaver, James C.; Clarke, David R.; Bertoldi, Katia

2014-03-01

Geometrical frustration arises when a local order cannot propagate throughout the space because of geometrical constraints. This phenomenon plays a major role in many systems leading to disordered ground-state configurations. Here, we report a theoretical and experimental study on the behavior of buckling-induced geometrically frustrated triangular cellular structures. To our surprise, we find that buckling induces complex ordered patterns which can be tuned by controlling the porosity of the structures. Our analysis reveals that the connected geometry of the cellular structure plays a crucial role in the generation of ordered states in this frustrated system.

Improving Visibility of Stereo-Radiographic Spine Reconstruction with Geometric Inferences.

PubMed

Kumar, Sampath; Nayak, K Prabhakar; Hareesha, K S

2016-04-01

Complex deformities of the spine, like scoliosis, are evaluated more precisely using stereo-radiographic 3D reconstruction techniques. Primarily, it uses six stereo-corresponding points available on the vertebral body for the 3D reconstruction of each vertebra. The wireframe structure obtained in this process has poor visualization, hence difficult to diagnose. In this paper, a novel method is proposed to improve the visibility of this wireframe structure using a deformation of a generic spine model in accordance with the 3D-reconstructed corresponding points. Then, the geometric inferences like vertebral orientations are automatically extracted from the radiographs to improve the visibility of the 3D model. Biplanar radiographs are acquired from five scoliotic subjects on a specifically designed calibration bench. The stereo-corresponding point reconstruction method is used to build six-point wireframe vertebral structures and thus the entire spine model. Using the 3D spine midline and automatically extracted vertebral orientation features, a more realistic 3D spine model is generated. To validate the method, the 3D spine model is back-projected on biplanar radiographs and the error difference is computed. Though, this difference is within the error limits available in the literature, the proposed work is simple and economical. The proposed method does not require more corresponding points and image features to improve the visibility of the model. Hence, it reduces the computational complexity. Expensive 3D digitizer and vertebral CT scan models are also excluded from this study. Thus, the visibility of stereo-corresponding point reconstruction is improved to obtain a low-cost spine model for a better diagnosis of spinal deformities.

Methods of treating complex space vehicle geometry for charged particle radiation transport

NASA Technical Reports Server (NTRS)

Hill, C. W.

1973-01-01

Current methods of treating complex geometry models for space radiation transport calculations are reviewed. The geometric techniques used in three computer codes are outlined. Evaluations of geometric capability and speed are provided for these codes. Although no code development work is included several suggestions for significantly improving complex geometry codes are offered.

Cross-domain latent space projection for person re-identification

NASA Astrophysics Data System (ADS)

Pu, Nan; Wu, Song; Qian, Li; Xiao, Guoqiang

2018-04-01

In this paper, we research the problem of person re-identification and propose a cross-domain latent space projection (CDLSP) method to address the problems of the absence or insufficient labeled data in the target domain. Under the assumption that the visual features in the source domain and target domain share the similar geometric structure, we transform the visual features from source domain and target domain to a common latent space by optimizing the object function defined in the manifold alignment method. Moreover, the proposed object function takes into account the specific knowledge in the re-id with the aim to improve the performance of re-id under complex situations. Extensive experiments conducted on four benchmark datasets show the proposed CDLSP outperforms or is competitive with stateof- the-art methods for person re-identification.

Design for Additive Bio-Manufacturing: From Patient-Specific Medical Devices to Rationally Designed Meta-Biomaterials.

PubMed

Zadpoor, Amir A

2017-07-25

Recent advances in additive manufacturing (AM) techniques in terms of accuracy, reliability, the range of processable materials, and commercial availability have made them promising candidates for production of functional parts including those used in the biomedical industry. The complexity-for-free feature offered by AM means that very complex designs become feasible to manufacture, while batch-size-indifference enables fabrication of fully patient-specific medical devices. Design for AM (DfAM) approaches aim to fully utilize those features for development of medical devices with substantially enhanced performance and biomaterials with unprecedented combinations of favorable properties that originate from complex geometrical designs at the micro-scale. This paper reviews the most important approaches in DfAM particularly those applicable to additive bio-manufacturing including image-based design pipelines, parametric and non-parametric designs, metamaterials, rational and computationally enabled design, topology optimization, and bio-inspired design. Areas with limited research have been identified and suggestions have been made for future research. The paper concludes with a brief discussion on the practical aspects of DfAM and the potential of combining AM with subtractive and formative manufacturing processes in so-called hybrid manufacturing processes.

Design for Additive Bio-Manufacturing: From Patient-Specific Medical Devices to Rationally Designed Meta-Biomaterials

PubMed Central

Zadpoor, Amir A.

2017-01-01

Recent advances in additive manufacturing (AM) techniques in terms of accuracy, reliability, the range of processable materials, and commercial availability have made them promising candidates for production of functional parts including those used in the biomedical industry. The complexity-for-free feature offered by AM means that very complex designs become feasible to manufacture, while batch-size-indifference enables fabrication of fully patient-specific medical devices. Design for AM (DfAM) approaches aim to fully utilize those features for development of medical devices with substantially enhanced performance and biomaterials with unprecedented combinations of favorable properties that originate from complex geometrical designs at the micro-scale. This paper reviews the most important approaches in DfAM particularly those applicable to additive bio-manufacturing including image-based design pipelines, parametric and non-parametric designs, metamaterials, rational and computationally enabled design, topology optimization, and bio-inspired design. Areas with limited research have been identified and suggestions have been made for future research. The paper concludes with a brief discussion on the practical aspects of DfAM and the potential of combining AM with subtractive and formative manufacturing processes in so-called hybrid manufacturing processes. PMID:28757572

The tarsal-metatarsal complex of caviomorph rodents: Anatomy and functional-adaptive analysis.

PubMed

Candela, Adriana M; Muñoz, Nahuel A; García-Esponda, César M

2017-06-01

Caviomorph rodents represent a major adaptive radiation of Neotropical mammals. They occupy a variety of ecological niches, which is also reflected in their wide array of locomotor behaviors. It is expected that this radiation would be mirrored by an equivalent disparity of tarsal-metatarsal morphology. Here, the tarsal-metatarsal complex of Erethizontidae, Cuniculidae, Dasyproctidae, Caviidae, Chinchillidae, Octodontidae, Ctenomyidae, and Echimyidae was examined, in order to evaluate its anatomical variation and functional-adaptive relevance in relation to locomotor behaviors. A qualitative study in functional morphology and a geometric morphometric analysis were performed. We recognized two distinct tarsal-metatarsal patterns that represent the extremes of anatomical variation in the foot. The first, typically present in arboreal species, is characterized by features that facilitate movements at different levels of the tarsal-metatarsal complex. The second pattern, typically present in cursorial caviomorphs, has a set of features that act to stabilize the joints, improve the interlocking of the tarsal bones, and restrict movements to the parasagittal plane. The morphological disparity recognized in this study seems to result from specific locomotor adaptations to climb, dig, run, jump and swim, as well as phylogenetic effects within and among the groups studies. © 2017 Wiley Periodicals, Inc.

Influence of minor geometric features on Stirling pulse tube cryocooler performance

NASA Astrophysics Data System (ADS)

Fang, T.; Spoor, P. S.; Ghiaasiaan, S. M.; Perrella, M.

2017-12-01

Minor geometric features and imperfections are commonly introduced into the basic design of multi-component systems to simplify or reduce the manufacturing expense. In this work, the cooling performance of a Stirling type cryocooler was tested in different driving powers, cold-end temperatures and inclination angles. A series of Computational Fluid Dynamics (CFD) simulations based on a prototypical cold tip was carried out. Detailed CFD model predictions were compared with the experiment and were used to investigate the impact of such apparently minor geometric imperfections on the performance of Stirling type pulse tube cryocoolers. Predictions of cooling performance and gravity orientation sensitivity were compared with experimental results obtained with the cryocooler prototypes. The results indicate that minor geometry features in the cold tip assembly can have considerable negative effects on the gravity orientation sensitivity of a pulse tube cryocooler.

3D fault curvature and fractal roughness: Insights for rupture dynamics and ground motions using a Discontinous Galerkin method

NASA Astrophysics Data System (ADS)

Ulrich, Thomas; Gabriel, Alice-Agnes

2017-04-01

Natural fault geometries are subject to a large degree of uncertainty. Their geometrical structure is not directly observable and may only be inferred from surface traces, or geophysical measurements. Most studies aiming at assessing the potential seismic hazard of natural faults rely on idealised shaped models, based on observable large-scale features. Yet, real faults are wavy at all scales, their geometric features presenting similar statistical properties from the micro to the regional scale. Dynamic rupture simulations aim to capture the observed complexity of earthquake sources and ground-motions. From a numerical point of view, incorporating rough faults in such simulations is challenging - it requires optimised codes able to run efficiently on high-performance computers and simultaneously handle complex geometries. Physics-based rupture dynamics hosted by rough faults appear to be much closer to source models inverted from observation in terms of complexity. Moreover, the simulated ground-motions present many similarities with observed ground-motions records. Thus, such simulations may foster our understanding of earthquake source processes, and help deriving more accurate seismic hazard estimates. In this presentation, the software package SeisSol (www.seissol.org), based on an ADER-Discontinuous Galerkin scheme, is used to solve the spontaneous dynamic earthquake rupture problem. The usage of tetrahedral unstructured meshes naturally allows for complicated fault geometries. However, SeisSol's high-order discretisation in time and space is not particularly suited for small-scale fault roughness. We will demonstrate modelling conditions under which SeisSol resolves rupture dynamics on rough faults accurately. The strong impact of the geometric gradient of the fault surface on the rupture process is then shown in 3D simulations. Following, the benefits of explicitly modelling fault curvature and roughness, in distinction to prescribing heterogeneous initial stress conditions on a planar fault, is demonstrated. Furthermore, we show that rupture extend, rupture front coherency and rupture speed are highly dependent on the initial amplitude of stress acting on the fault, defined by the normalized prestress factor R, the ratio of the potential stress drop over the breakdown stress drop. The effects of fault complexity are particularly pronounced for lower R. By low-pass filtering a rough fault at several cut-off wavelengths, we then try to capture rupture complexity using a simplified fault geometry. We find that equivalent source dynamics can only be obtained using a scarcely filtered fault associated with a reduced stress level. To investigate the wavelength-dependent roughness effect, the fault geometry is bandpass-filtered over several spectral ranges. We show that geometric fluctuations cause rupture velocity fluctuations of similar length scale. The impact of fault geometry is especially pronounced when the rupture front velocity is near supershear. Roughness fluctuations significantly smaller than the rupture front characteristic dimension (cohesive zone size) affect only macroscopic rupture properties, thus, posing a minimum length scale limiting the required resolution of 3D fault complexity. Lastly, the effect of fault curvature and roughness on the simulated ground-motions is assessed. Despite employing a simple linear slip weakening friction law, the simulated ground-motions compare well with estimates from ground motions prediction equations, even at relatively high frequencies.

The geometrical structure of quantum theory as a natural generalization of information geometry

NASA Astrophysics Data System (ADS)

Reginatto, Marcel

2015-01-01

Quantum mechanics has a rich geometrical structure which allows for a geometrical formulation of the theory. This formalism was introduced by Kibble and later developed by a number of other authors. The usual approach has been to start from the standard description of quantum mechanics and identify the relevant geometrical features that can be used for the reformulation of the theory. Here this procedure is inverted: the geometrical structure of quantum theory is derived from information geometry, a geometrical structure that may be considered more fundamental, and the Hilbert space of the standard formulation of quantum mechanics is constructed using geometrical quantities. This suggests that quantum theory has its roots in information geometry.

An Iterative Closest Points Algorithm for Registration of 3D Laser Scanner Point Clouds with Geometric Features.

PubMed

He, Ying; Liang, Bin; Yang, Jun; Li, Shunzhi; He, Jin

2017-08-11

The Iterative Closest Points (ICP) algorithm is the mainstream algorithm used in the process of accurate registration of 3D point cloud data. The algorithm requires a proper initial value and the approximate registration of two point clouds to prevent the algorithm from falling into local extremes, but in the actual point cloud matching process, it is difficult to ensure compliance with this requirement. In this paper, we proposed the ICP algorithm based on point cloud features (GF-ICP). This method uses the geometrical features of the point cloud to be registered, such as curvature, surface normal and point cloud density, to search for the correspondence relationships between two point clouds and introduces the geometric features into the error function to realize the accurate registration of two point clouds. The experimental results showed that the algorithm can improve the convergence speed and the interval of convergence without setting a proper initial value.

An Iterative Closest Points Algorithm for Registration of 3D Laser Scanner Point Clouds with Geometric Features

PubMed Central

Liang, Bin; Yang, Jun; Li, Shunzhi; He, Jin

2017-01-01

The Iterative Closest Points (ICP) algorithm is the mainstream algorithm used in the process of accurate registration of 3D point cloud data. The algorithm requires a proper initial value and the approximate registration of two point clouds to prevent the algorithm from falling into local extremes, but in the actual point cloud matching process, it is difficult to ensure compliance with this requirement. In this paper, we proposed the ICP algorithm based on point cloud features (GF-ICP). This method uses the geometrical features of the point cloud to be registered, such as curvature, surface normal and point cloud density, to search for the correspondence relationships between two point clouds and introduces the geometric features into the error function to realize the accurate registration of two point clouds. The experimental results showed that the algorithm can improve the convergence speed and the interval of convergence without setting a proper initial value. PMID:28800096

Extracting insights from the shape of complex data using topology

PubMed Central

Lum, P. Y.; Singh, G.; Lehman, A.; Ishkanov, T.; Vejdemo-Johansson, M.; Alagappan, M.; Carlsson, J.; Carlsson, G.

2013-01-01

This paper applies topological methods to study complex high dimensional data sets by extracting shapes (patterns) and obtaining insights about them. Our method combines the best features of existing standard methodologies such as principal component and cluster analyses to provide a geometric representation of complex data sets. Through this hybrid method, we often find subgroups in data sets that traditional methodologies fail to find. Our method also permits the analysis of individual data sets as well as the analysis of relationships between related data sets. We illustrate the use of our method by applying it to three very different kinds of data, namely gene expression from breast tumors, voting data from the United States House of Representatives and player performance data from the NBA, in each case finding stratifications of the data which are more refined than those produced by standard methods. PMID:23393618

Extracting insights from the shape of complex data using topology.

PubMed

Lum, P Y; Singh, G; Lehman, A; Ishkanov, T; Vejdemo-Johansson, M; Alagappan, M; Carlsson, J; Carlsson, G

2013-01-01

This paper applies topological methods to study complex high dimensional data sets by extracting shapes (patterns) and obtaining insights about them. Our method combines the best features of existing standard methodologies such as principal component and cluster analyses to provide a geometric representation of complex data sets. Through this hybrid method, we often find subgroups in data sets that traditional methodologies fail to find. Our method also permits the analysis of individual data sets as well as the analysis of relationships between related data sets. We illustrate the use of our method by applying it to three very different kinds of data, namely gene expression from breast tumors, voting data from the United States House of Representatives and player performance data from the NBA, in each case finding stratifications of the data which are more refined than those produced by standard methods.

QWT: Retrospective and New Applications

NASA Astrophysics Data System (ADS)

Xu, Yi; Yang, Xiaokang; Song, Li; Traversoni, Leonardo; Lu, Wei

Quaternion wavelet transform (QWT) achieves much attention in recent years as a new image analysis tool. In most cases, it is an extension of the real wavelet transform and complex wavelet transform (CWT) by using the quaternion algebra and the 2D Hilbert transform of filter theory, where analytic signal representation is desirable to retrieve phase-magnitude description of intrinsically 2D geometric structures in a grayscale image. In the context of color image processing, however, it is adapted to analyze the image pattern and color information as a whole unit by mapping sequential color pixels to a quaternion-valued vector signal. This paper provides a retrospective of QWT and investigates its potential use in the domain of image registration, image fusion, and color image recognition. It is indicated that it is important for QWT to induce the mechanism of adaptive scale representation of geometric features, which is further clarified through two application instances of uncalibrated stereo matching and optical flow estimation. Moreover, quaternionic phase congruency model is defined based on analytic signal representation so as to operate as an invariant feature detector for image registration. To achieve better localization of edges and textures in image fusion task, we incorporate directional filter bank (DFB) into the quaternion wavelet decomposition scheme to greatly enhance the direction selectivity and anisotropy of QWT. Finally, the strong potential use of QWT in color image recognition is materialized in a chromatic face recognition system by establishing invariant color features. Extensive experimental results are presented to highlight the exciting properties of QWT.

Exploring Eucladoceros ecomorphology using geometric morphometrics.

PubMed

Curran, Sabrina C

2015-01-01

An increasingly common method for reconstructing paleoenvironmental parameters of hominin sites is ecological functional morphology (ecomorphology). This study provides a geometric morphometric study of cervid rearlimb morphology as it relates to phylogeny, size, and ecomorphology. These methods are then applied to an extinct Pleistocene cervid, Eucladoceros, which is found in some of the earliest hominin-occupied sites in Eurasia. Variation in cervid postcranial functional morphology associated with different habitats can be summarized as trade-offs between joint stability versus mobility and rapid movement versus power-generation. Cervids in open habitats emphasize limb stability to avoid joint dislocation during rapid flight from predators. Closed-adapted cervids require more joint mobility to rapidly switch directions in complex habitats. Two skeletal features (of the tibia and calcaneus) have significant phylogenetic signals, while two (the femur and third phalanx) do not. Additionally, morphology of two of these features (tibia and third phalanx) were correlated with body size. For the tibial analysis (but not the third phalanx) this correlation was ameliorated when phylogeny was taken into account. Eucladoceros specimens from France and Romania fall on the more open side of the habitat continuum, a result that is at odds with reconstructions of their diet as browsers, suggesting that they may have had a behavioral regime unlike any extant cervid. © 2014 Wiley Periodicals, Inc.

Movement Timing and Invariance Arise from Several Geometries

PubMed Central

Bennequin, Daniel; Fuchs, Ronit; Berthoz, Alain; Flash, Tamar

2009-01-01

Human movements show several prominent features; movement duration is nearly independent of movement size (the isochrony principle), instantaneous speed depends on movement curvature (captured by the 2/3 power law), and complex movements are composed of simpler elements (movement compositionality). No existing theory can successfully account for all of these features, and the nature of the underlying motion primitives is still unknown. Also unknown is how the brain selects movement duration. Here we present a new theory of movement timing based on geometrical invariance. We propose that movement duration and compositionality arise from cooperation among Euclidian, equi-affine and full affine geometries. Each geometry posses a canonical measure of distance along curves, an invariant arc-length parameter. We suggest that for continuous movements, the actual movement duration reflects a particular tensorial mixture of these canonical parameters. Near geometrical singularities, specific combinations are selected to compensate for time expansion or compression in individual parameters. The theory was mathematically formulated using Cartan's moving frame method. Its predictions were tested on three data sets: drawings of elliptical curves, locomotion and drawing trajectories of complex figural forms (cloverleaves, lemniscates and limaçons, with varying ratios between the sizes of the large versus the small loops). Our theory accounted well for the kinematic and temporal features of these movements, in most cases better than the constrained Minimum Jerk model, even when taking into account the number of estimated free parameters. During both drawing and locomotion equi-affine geometry was the most dominant geometry, with affine geometry second most important during drawing; Euclidian geometry was second most important during locomotion. We further discuss the implications of this theory: the origin of the dominance of equi-affine geometry, the possibility that the brain uses different mixtures of these geometries to encode movement duration and speed, and the ontogeny of such representations. PMID:19593380

Capabilities overview of the MORET 5 Monte Carlo code

NASA Astrophysics Data System (ADS)

Cochet, B.; Jinaphanh, A.; Heulers, L.; Jacquet, O.

2014-06-01

The MORET code is a simulation tool that solves the transport equation for neutrons using the Monte Carlo method. It allows users to model complex three-dimensional geometrical configurations, describe the materials, define their own tallies in order to analyse the results. The MORET code has been initially designed to perform calculations for criticality safety assessments. New features has been introduced in the MORET 5 code to expand its use for reactor applications. This paper presents an overview of the MORET 5 code capabilities, going through the description of materials, the geometry modelling, the transport simulation and the definition of the outputs.

Self-assembly of a [Ni8] carbonate cube incorporating four μ4-carbonato linkers through fixation of atmospheric CO2 by ligated [Ni2] complexes.

PubMed

Ghosh, Aloke Kumar; Pait, Moumita; Shatruk, Michael; Bertolasi, Valerio; Ray, Debashis

2014-02-07

The communication reports the synthesis, characterization, and magnetic behavior of a novel μ4-carbonato supported and imidazole capped ligated nickel cage [Ni8(μ-H2bpmp)4(μ4-CO3)4(ImH)8](NO3)4·2H2O (1) through self-assembly of ligand bound ferromagnetic Ni2 building blocks. Structural analysis indicates newer geometrical features for the coordination cage formation and dominant interdimer antiferromagnetic coupling resulting in a diamagnetic ground state.

Visualizing the Arithmetic of Complex Numbers

ERIC Educational Resources Information Center

Soto-Johnson, Hortensia

2014-01-01

The Common Core State Standards Initiative stresses the importance of developing a geometric and algebraic understanding of complex numbers in their different forms (i.e., Cartesian, polar and exponential). Unfortunately, most high school textbooks do not offer such explanations much less exercises that encourage students to bridge geometric and…

Reliability of vascular geometry factors derived from clinical MRA

NASA Astrophysics Data System (ADS)

Bijari, Payam B.; Antiga, Luca; Steinman, David A.

2009-02-01

Recent work from our group has demonstrated that the amount of disturbed flow at the carotid bifurcation, believed to be a local risk factor for carotid atherosclerosis, can be predicted from luminal geometric factors. The next step along the way to a large-scale retrospective or prospective imaging study of such local risk factors for atherosclerosis is to investigate whether these geometric features are reproducible and accurate from routine 3D contrast-enhanced magnetic resonance angiography (CEMRA) using a fast and practical method of extraction. Motivated by this fact, we examined the reproducibility of multiple geometric features that are believed important in atherosclerosis risk assessment. We reconstructed three-dimensional carotid bifurcations from 15 clinical study participants who had previously undergone baseline and repeat CEMRA acquisitions. Certain geometric factors were extracted and compared between the baseline and the repeat scan. As the spatial resolution of the CEMRA data was noticeably coarse and anisotropic, we also investigated whether this might affect the measurement of the same geometric risk factors by simulating the CEMRA acquisition for 15 normal carotid bifurcations previously acquired at high resolution. Our results show that the extracted geometric factors are reproducible and faithful, with intra-subject uncertainties well below inter-subject variabilities. More importantly, these geometric risk factors can be extracted consistently and quickly for potential use as disturbed flow predictors.

Structure and reactivity of a mononuclear gold(II) complex

NASA Astrophysics Data System (ADS)

Preiß, Sebastian; Förster, Christoph; Otto, Sven; Bauer, Matthias; Müller, Patrick; Hinderberger, Dariush; Hashemi Haeri, Haleh; Carella, Luca; Heinze, Katja

2017-12-01

Mononuclear gold(II) complexes are very rare labile species. Transient gold(II) species have been suggested in homogeneous catalysis and in medical applications, but their geometric and electronic structures have remained essentially unexplored: even fundamental data, such as the ionic radius of gold(II), are unknown. Now, an unprecedentedly stable neutral gold(II) complex of a porphyrin derivative has been isolated, and its structural and spectroscopic features determined. The gold atom adopts a 2+2 coordination mode in between those of gold(III) (four-coordinate square planar) and gold(I) (two-coordinate linear), owing to a second-order Jahn-Teller distortion enabled by the relativistically lowered 6s orbital of gold. The reactivity of this gold(II) complex towards dioxygen, nitrosobenzene and acids is discussed. This study provides insight on the ionic radius of gold(II), and allows it to be placed within the homologous series of nd9 Cu/Ag/Au divalent ions and the 5d8/9/10 Pt/Au/Hg 'relativistic' triad in the periodic table.

Protein-protein docking using region-based 3D Zernike descriptors

PubMed Central

2009-01-01

Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods. PMID:20003235

Protein-protein docking using region-based 3D Zernike descriptors.

PubMed

Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke

2009-12-09

Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD < or = 2.5 A) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.

The geometrical structure of quantum theory as a natural generalization of information geometry

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

Reginatto, Marcel

2015-01-13

Quantum mechanics has a rich geometrical structure which allows for a geometrical formulation of the theory. This formalism was introduced by Kibble and later developed by a number of other authors. The usual approach has been to start from the standard description of quantum mechanics and identify the relevant geometrical features that can be used for the reformulation of the theory. Here this procedure is inverted: the geometrical structure of quantum theory is derived from information geometry, a geometrical structure that may be considered more fundamental, and the Hilbert space of the standard formulation of quantum mechanics is constructed usingmore » geometrical quantities. This suggests that quantum theory has its roots in information geometry.« less

A nonuniform popularity-similarity optimization (nPSO) model to efficiently generate realistic complex networks with communities

NASA Astrophysics Data System (ADS)

Muscoloni, Alessandro; Vittorio Cannistraci, Carlo

2018-05-01

The investigation of the hidden metric space behind complex network topologies is a fervid topic in current network science and the hyperbolic space is one of the most studied, because it seems associated to the structural organization of many real complex systems. The popularity-similarity-optimization (PSO) model simulates how random geometric graphs grow in the hyperbolic space, generating realistic networks with clustering, small-worldness, scale-freeness and rich-clubness. However, it misses to reproduce an important feature of real complex networks, which is the community organization. The geometrical-preferential-attachment (GPA) model was recently developed in order to confer to the PSO also a soft community structure, which is obtained by forcing different angular regions of the hyperbolic disk to have a variable level of attractiveness. However, the number and size of the communities cannot be explicitly controlled in the GPA, which is a clear limitation for real applications. Here, we introduce the nonuniform PSO (nPSO) model. Differently from GPA, the nPSO generates synthetic networks in the hyperbolic space where heterogeneous angular node attractiveness is forced by sampling the angular coordinates from a tailored nonuniform probability distribution (for instance a mixture of Gaussians). The nPSO differs from GPA in other three aspects: it allows one to explicitly fix the number and size of communities; it allows one to tune their mixing property by means of the network temperature; it is efficient to generate networks with high clustering. Several tests on the detectability of the community structure in nPSO synthetic networks and wide investigations on their structural properties confirm that the nPSO is a valid and efficient model to generate realistic complex networks with communities.

Sparse approximation of currents for statistics on curves and surfaces.

PubMed

Durrleman, Stanley; Pennec, Xavier; Trouvé, Alain; Ayache, Nicholas

2008-01-01

Computing, processing, visualizing statistics on shapes like curves or surfaces is a real challenge with many applications ranging from medical image analysis to computational geometry. Modelling such geometrical primitives with currents avoids feature-based approach as well as point-correspondence method. This framework has been proved to be powerful to register brain surfaces or to measure geometrical invariants. However, if the state-of-the-art methods perform efficiently pairwise registrations, new numerical schemes are required to process groupwise statistics due to an increasing complexity when the size of the database is growing. Statistics such as mean and principal modes of a set of shapes often have a heavy and highly redundant representation. We propose therefore to find an adapted basis on which mean and principal modes have a sparse decomposition. Besides the computational improvement, this sparse representation offers a way to visualize and interpret statistics on currents. Experiments show the relevance of the approach on 34 sets of 70 sulcal lines and on 50 sets of 10 meshes of deep brain structures.

Augmented Topological Descriptors of Pore Networks for Material Science.

PubMed

Ushizima, D; Morozov, D; Weber, G H; Bianchi, A G C; Sethian, J A; Bethel, E W

2012-12-01

One potential solution to reduce the concentration of carbon dioxide in the atmosphere is the geologic storage of captured CO2 in underground rock formations, also known as carbon sequestration. There is ongoing research to guarantee that this process is both efficient and safe. We describe tools that provide measurements of media porosity, and permeability estimates, including visualization of pore structures. Existing standard algorithms make limited use of geometric information in calculating permeability of complex microstructures. This quantity is important for the analysis of biomineralization, a subsurface process that can affect physical properties of porous media. This paper introduces geometric and topological descriptors that enhance the estimation of material permeability. Our analysis framework includes the processing of experimental data, segmentation, and feature extraction and making novel use of multiscale topological analysis to quantify maximum flow through porous networks. We illustrate our results using synchrotron-based X-ray computed microtomography of glass beads during biomineralization. We also benchmark the proposed algorithms using simulated data sets modeling jammed packed bead beds of a monodispersive material.

Similarity-based Regularized Latent Feature Model for Link Prediction in Bipartite Networks.

PubMed

Wang, Wenjun; Chen, Xue; Jiao, Pengfei; Jin, Di

2017-12-05

Link prediction is an attractive research topic in the field of data mining and has significant applications in improving performance of recommendation system and exploring evolving mechanisms of the complex networks. A variety of complex systems in real world should be abstractly represented as bipartite networks, in which there are two types of nodes and no links connect nodes of the same type. In this paper, we propose a framework for link prediction in bipartite networks by combining the similarity based structure and the latent feature model from a new perspective. The framework is called Similarity Regularized Nonnegative Matrix Factorization (SRNMF), which explicitly takes the local characteristics into consideration and encodes the geometrical information of the networks by constructing a similarity based matrix. We also develop an iterative scheme to solve the objective function based on gradient descent. Extensive experiments on a variety of real world bipartite networks show that the proposed framework of link prediction has a more competitive, preferable and stable performance in comparison with the state-of-art methods.

Geometry-based pressure drop prediction in mildly diseased human coronary arteries.

PubMed

Schrauwen, J T C; Wentzel, J J; van der Steen, A F W; Gijsen, F J H

2014-06-03

Pressure drop (△p) estimations in human coronary arteries have several important applications, including determination of appropriate boundary conditions for CFD and estimation of fractional flow reserve (FFR). In this study a △p prediction was made based on geometrical features derived from patient-specific imaging data. Twenty-two mildly diseased human coronary arteries were imaged with computed tomography and intravascular ultrasound. Each artery was modelled in three consecutive steps: from straight to tapered, to stenosed, to curved model. CFD was performed to compute the additional △p in each model under steady flow for a wide range of Reynolds numbers. The correlations between the added geometrical complexity and additional △p were used to compute a predicted △p. This predicted △p based on geometry was compared to CFD results. The mean △p calculated with CFD was 855±666Pa. Tapering and curvature added significantly to the total △p, accounting for 31.4±19.0% and 18.0±10.9% respectively at Re=250. Using tapering angle, maximum area stenosis and angularity of the centerline, we were able to generate a good estimate for the predicted △p with a low mean but high standard deviation: average error of 41.1±287.8Pa at Re=250. Furthermore, the predicted △p was used to accurately estimate FFR (r=0.93). The effect of the geometric features was determined and the pressure drop in mildly diseased human coronary arteries was predicted quickly based solely on geometry. This pressure drop estimation could serve as a boundary condition in CFD to model the impact of distal epicardial vessels. Copyright © 2014 Elsevier Ltd. All rights reserved.

Robust recognition of degraded machine-printed characters using complementary similarity measure and error-correction learning

NASA Astrophysics Data System (ADS)

Hagita, Norihiro; Sawaki, Minako

1995-03-01

Most conventional methods in character recognition extract geometrical features such as stroke direction, connectivity of strokes, etc., and compare them with reference patterns in a stored dictionary. Unfortunately, geometrical features are easily degraded by blurs, stains and the graphical background designs used in Japanese newspaper headlines. This noise must be removed before recognition commences, but no preprocessing method is completely accurate. This paper proposes a method for recognizing degraded characters and characters printed on graphical background designs. This method is based on the binary image feature method and uses binary images as features. A new similarity measure, called the complementary similarity measure, is used as a discriminant function. It compares the similarity and dissimilarity of binary patterns with reference dictionary patterns. Experiments are conducted using the standard character database ETL-2 which consists of machine-printed Kanji, Hiragana, Katakana, alphanumeric, an special characters. The results show that this method is much more robust against noise than the conventional geometrical feature method. It also achieves high recognition rates of over 92% for characters with textured foregrounds, over 98% for characters with textured backgrounds, over 98% for outline fonts, and over 99% for reverse contrast characters.

Complex Mapping of Aerofoils--A Different Perspective

ERIC Educational Resources Information Center

Matthews, Miccal T.

2012-01-01

In this article an application of conformal mapping to aerofoil theory is studied from a geometric and calculus point of view. The problem is suitable for undergraduate teaching in terms of a project or extended piece of work, and brings together the concepts of geometric mapping, parametric equations, complex numbers and calculus. The Joukowski…

Complexity of Geometric Inductive Reasoning Tasks: Contribution to the Understanding of Fluid Intelligence.

ERIC Educational Resources Information Center

Primi, Ricardo

2002-01-01

Created two geometric inductive reasoning matrix tests by manipulating four sources of complexity orthogonally. Results for 313 undergraduates show that fluid intelligence is most strongly associated with the part of the central executive component of working memory that is related to controlled attention processing and selective encoding. (SLD)

Is language necessary for human spatial reorientation? Reconsidering evidence from dual task paradigms.

PubMed

Ratliff, Kristin R; Newcombe, Nora S

2008-03-01

Being able to reorient to the spatial environment after disorientation is a basic adaptive challenge. There is clear evidence that reorientation uses geometric information about the shape of the surrounding space. However, there has been controversy concerning whether use of geometry is a modular function, and whether use of features is dependent on human language. A key argument for the role of language comes from shadowing findings where adults engaged in a linguistic task during reorientation ignored a colored wall feature and only used geometric information to reorient [Hermer-Vazquez, L., Spelke, E., & Katsnelson, A. (1999). Sources of flexibility in human cognition: Dual task studies of space and language. Cognitive Psychology, 39, 3-36]. We report three studies showing: (a) that the results of Hermer-Vazques et al. [Hermer-Vazquez, L., Spelke, E., & Katsnelson, A. (1999). Sources of flexibility in human cognition: Dual task studies of space and language. Cognitive Psychology, 39, 3-36] are obtained in incidental learning but not with explicit instructions, (b) that a spatial task impedes use of features at least as much as a verbal shadowing task, and (c) that neither secondary task impedes use of features in a room larger than that used by Hermer-Vazquez et al. These results suggest that language is not necessary for successful use of features in reorientation. In fact, whether or not there is an encapsulated geometric module is currently unsettled. The current findings support an alternative to modularity; the adaptive combination view hypothesizes that geometric and featural information are utilized in varying degrees, dependent upon the certainty and variance with which the two kinds of information are encoded, along with their salience and perceived usefulness.

Advanced Techniques for Ultrasonic Imaging in the Presence of Material and Geometrical Complexity

NASA Astrophysics Data System (ADS)

Brath, Alexander Joseph

The complexity of modern engineering systems is increasing in several ways: advances in materials science are leading to the design of materials which are optimized for material strength, conductivity, temperature resistance etc., leading to complex material microstructure; the combination of additive manufacturing and shape optimization algorithms are leading to components with incredibly intricate geometrical complexity; and engineering systems are being designed to operate at larger scales in ever harsher environments. As a result, at the same time that there is an increasing need for reliable and accurate defect detection and monitoring capabilities, many of the currently available non-destructive evaluation techniques are rendered ineffective by this increasing material and geometrical complexity. This thesis addresses the challenges posed by inspection and monitoring problems in complex engineering systems with a three-part approach. In order to address material complexities, a model of wavefront propagation in anisotropic materials is developed, along with efficient numerical techniques to solve for the wavefront propagation in inhomogeneous, anisotropic material. Since material and geometrical complexities significantly affect the ability of ultrasonic energy to penetrate into the specimen, measurement configurations are tailored to specific applications which utilize arrays of either piezoelectric (PZT) or electromagnetic acoustic transducers (EMAT). These measurement configurations include novel array architectures as well as the exploration of ice as an acoustic coupling medium. Imaging algorithms which were previously developed for isotropic materials with simple geometry are adapted to utilize the more powerful wavefront propagation model and novel measurement configurations.

SU-F-T-304: Complex Multi-PTV Treatment Evaluation Using a Remotely Processed 3D Gel Dosimeter

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

Hoisak, J; Dragojevic, I; Sutlief, S

Purpose: A new 3D gel dosimeter (ClearView™, Modus Medical Systems) was investigated for use as a QA tool for stereotactic radiosurgery (SRS) plans exhibiting high dose gradients and spatially separated treatment targets. The unique feature of this gel dosimeter is the remote processing service provided by Modus Medical Systems. Methods: The gel dosimeters were filled in either 10 cm diameter or 15 cm diameter clear plastic jars. The jars were then shipped in ice-cooled containers to our department for irradiation. Clinical SRS plans for treatment of multiple metastases and plans with simulated concave structures were applied to a CT scanmore » of the gel dosimeter. The gel was irradiated in treatment position using modulated arcs and then returned in the cooled container for processing. The 3D gel dose was compared to the DICOM-RT dose from the treatment plan to assess dosimetric and geometric agreement. Results: There was no discernible difference between the planned and measured dose for dose gradients as high as 10%/mm, which was the highest gradient we evaluated. Geometric agreement for distant metastases separated by 6 cm was within 1.5 mm. Among three identically irradiated gels using a plan intended for nine metastases, the 3%/3mm gamma passing rate was 84.5% with a range of 14.7%, measured over the entire volume of the dosimeter. Regions of larger gamma values correlated with geometric offsets between the planned and measured data. Conclusion: The gel dosimeter exhibits the dosimetric and geometric characteristics necessary for 3D evaluation of treatment plan deliverability. The range of observed gamma passing rates suggests a high sensitivity to geometric registration. With proper management of geometric registration between planned and measured data, this service should enable a radiation oncology department to use 3D dosimetry in end-to-end testing or patient plan delivery QA without the expense of an in-house processing system.« less

Detection of Chorus Elements and other Wave Signatures Using Geometric Computational Techniques in the Van Allen radiation belts

NASA Astrophysics Data System (ADS)

Sengupta, A.; Kletzing, C.; Howk, R.; Kurth, W. S.

2017-12-01

An important goal of the Van Allen Probes mission is to understand wave particle interactions that can energize relativistic electron in the Earth's Van Allen radiation belts. The EMFISIS instrumentation suite provides measurements of wave electric and magnetic fields of wave features such as chorus that participate in these interactions. Geometric signal processing discovers structural relationships, e.g. connectivity across ridge-like features in chorus elements to reveal properties such as dominant angles of the element (frequency sweep rate) and integrated power along the a given chorus element. These techniques disambiguate these wave features against background hiss-like chorus. This enables autonomous discovery of chorus elements across the large volumes of EMFISIS data. At the scale of individual or overlapping chorus elements, topological pattern recognition techniques enable interpretation of chorus microstructure by discovering connectivity and other geometric features within the wave signature of a single chorus element or between overlapping chorus elements. Thus chorus wave features can be quantified and studied at multiple scales of spectral geometry using geometric signal processing techniques. We present recently developed computational techniques that exploit spectral geometry of chorus elements and whistlers to enable large-scale automated discovery, detection and statistical analysis of these events over EMFISIS data. Specifically, we present different case studies across a diverse portfolio of chorus elements and discuss the performance of our algorithms regarding precision of detection as well as interpretation of chorus microstructure. We also provide large-scale statistical analysis on the distribution of dominant sweep rates and other properties of the detected chorus elements.

On the appropriate feature for general SAR image registration

NASA Astrophysics Data System (ADS)

Li, Dong; Zhang, Yunhua

2012-09-01

An investigation to the appropriate feature for SAR image registration is conducted. The commonly-used features such as tie points, Harris corner, the scale invariant feature transform (SIFT), and the speeded up robust feature (SURF) are comprehensively evaluated in terms of several criteria such as the geometrical invariance of feature, the extraction speed, the localization accuracy, the geometrical invariance of descriptor, the matching speed, the robustness to decorrelation, and the flexibility to image speckling. It is shown that SURF outperforms others. It is particularly indicated that SURF has good flexibility to image speckling because the Fast-Hessian detector of SURF has a potential relation with the refined Lee filter. It is recommended to perform SURF on the oversampled image with unaltered sampling step so as to improve the subpixel registration accuracy and speckle immunity. Thus SURF is more appropriate and competent for general SAR image registration.

Seventeen-Coordinate Actinide Helium Complexes.

PubMed

Kaltsoyannis, Nikolas

2017-06-12

The geometries and electronic structures of molecular ions featuring He atoms complexed to actinide cations are explored computationally using density functional and coupled cluster theories. A new record coordination number is established, as AcHe 17 3+ , ThHe 17 4+ , and PaHe 17 4+ are all found to be true geometric minima, with the He atoms clearly located in the first shell around the actinide. Analysis of AcHe n 3+ (n=1-17) using the quantum theory of atoms in molecules (QTAIM) confirms these systems as having closed shell, charge-induced dipole bonding. Excellent correlations (R 2 >0.95) are found between QTAIM metrics (bond critical point electron densities and delocalization indices) and the average Ac-He distances, and also with the incremental He binding energies. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characterization and analysis of Porous, Brittle solid structures by X-ray micro computed tomography

NASA Astrophysics Data System (ADS)

Lin, C. L.; Videla, A. R.; Yu, Q.; Miller, J. D.

2010-12-01

The internal structure of porous, brittle solid structures, such as porous rock, foam metal and wallboard, is extremely complex. For example, in the case of wallboard, the air bubble size and the thickness/composition of the wall structure are spatial parameters that vary significantly and influence mechanical, thermal, and acoustical properties. In this regard, the complex geometry and the internal texture of material, such as wallboard, is characterized and analyzed in 3-D using cone beam x-ray micro computed tomography. Geometrical features of the porous brittle structure are quantitatively analyzed based on calibration of the x-ray linear attenuation coefficient, use of a 3-D watershed algorithm, and use of a 3-D skeletonization procedure. Several examples of the 3-D analysis for porous, wallboard structures are presented and the results discussed.

Research on complex 3D tree modeling based on L-system

NASA Astrophysics Data System (ADS)

Gang, Chen; Bin, Chen; Yuming, Liu; Hui, Li

2018-03-01

L-system as a fractal iterative system could simulate complex geometric patterns. Based on the field observation data of trees and knowledge of forestry experts, this paper extracted modeling constraint rules and obtained an L-system rules set. Using the self-developed L-system modeling software the L-system rule set was parsed to generate complex tree 3d models.The results showed that the geometrical modeling method based on l-system could be used to describe the morphological structure of complex trees and generate 3D tree models.

Efficient 3D geometric and Zernike moments computation from unstructured surface meshes.

PubMed

Pozo, José María; Villa-Uriol, Maria-Cruz; Frangi, Alejandro F

2011-03-01

This paper introduces and evaluates a fast exact algorithm and a series of faster approximate algorithms for the computation of 3D geometric moments from an unstructured surface mesh of triangles. Being based on the object surface reduces the computational complexity of these algorithms with respect to volumetric grid-based algorithms. In contrast, it can only be applied for the computation of geometric moments of homogeneous objects. This advantage and restriction is shared with other proposed algorithms based on the object boundary. The proposed exact algorithm reduces the computational complexity for computing geometric moments up to order N with respect to previously proposed exact algorithms, from N(9) to N(6). The approximate series algorithm appears as a power series on the rate between triangle size and object size, which can be truncated at any desired degree. The higher the number and quality of the triangles, the better the approximation. This approximate algorithm reduces the computational complexity to N(3). In addition, the paper introduces a fast algorithm for the computation of 3D Zernike moments from the computed geometric moments, with a computational complexity N(4), while the previously proposed algorithm is of order N(6). The error introduced by the proposed approximate algorithms is evaluated in different shapes and the cost-benefit ratio in terms of error, and computational time is analyzed for different moment orders.

Ultrasound finite element simulation sensitivity to anisotropic titanium microstructures

NASA Astrophysics Data System (ADS)

Freed, Shaun; Blackshire, James L.; Na, Jeong K.

2016-02-01

Analytical wave models are inadequate to describe complex metallic microstructure interactions especially for near field anisotropic property effects and through geometric features smaller than the wavelength. In contrast, finite element ultrasound simulations inherently capture microstructure influences due to their reliance on material definitions rather than wave descriptions. To better understand and quantify heterogeneous crystal orientation effects to ultrasonic wave propagation, a finite element modeling case study has been performed with anisotropic titanium grain structures. A parameterized model has been developed utilizing anisotropic spheres within a bulk material. The resulting wave parameters are analyzed as functions of both wavelength and sphere to bulk crystal mismatch angle.

High-performance computing in image registration

NASA Astrophysics Data System (ADS)

Zanin, Michele; Remondino, Fabio; Dalla Mura, Mauro

2012-10-01

Thanks to the recent technological advances, a large variety of image data is at our disposal with variable geometric, radiometric and temporal resolution. In many applications the processing of such images needs high performance computing techniques in order to deliver timely responses e.g. for rapid decisions or real-time actions. Thus, parallel or distributed computing methods, Digital Signal Processor (DSP) architectures, Graphical Processing Unit (GPU) programming and Field-Programmable Gate Array (FPGA) devices have become essential tools for the challenging issue of processing large amount of geo-data. The article focuses on the processing and registration of large datasets of terrestrial and aerial images for 3D reconstruction, diagnostic purposes and monitoring of the environment. For the image alignment procedure, sets of corresponding feature points need to be automatically extracted in order to successively compute the geometric transformation that aligns the data. The feature extraction and matching are ones of the most computationally demanding operations in the processing chain thus, a great degree of automation and speed is mandatory. The details of the implemented operations (named LARES) exploiting parallel architectures and GPU are thus presented. The innovative aspects of the implementation are (i) the effectiveness on a large variety of unorganized and complex datasets, (ii) capability to work with high-resolution images and (iii) the speed of the computations. Examples and comparisons with standard CPU processing are also reported and commented.

Matching Real and Synthetic Panoramic Images Using a Variant of Geometric Hashing

NASA Astrophysics Data System (ADS)

Li-Chee-Ming, J.; Armenakis, C.

2017-05-01

This work demonstrates an approach to automatically initialize a visual model-based tracker, and recover from lost tracking, without prior camera pose information. These approaches are commonly referred to as tracking-by-detection. Previous tracking-by-detection techniques used either fiducials (i.e. landmarks or markers) or the object's texture. The main contribution of this work is the development of a tracking-by-detection algorithm that is based solely on natural geometric features. A variant of geometric hashing, a model-to-image registration algorithm, is proposed that searches for a matching panoramic image from a database of synthetic panoramic images captured in a 3D virtual environment. The approach identifies corresponding features between the matched panoramic images. The corresponding features are to be used in a photogrammetric space resection to estimate the camera pose. The experiments apply this algorithm to initialize a model-based tracker in an indoor environment using the 3D CAD model of the building.

The Use of Video-Tacheometric Technology for Documenting and Analysing Geometric Features of Objects

NASA Astrophysics Data System (ADS)

Woźniak, Marek; Świerczyńska, Ewa; Jastrzębski, Sławomir

2015-12-01

This paper analyzes selected aspects of the use of video-tacheometric technology for inventorying and documenting geometric features of objects. Data was collected with the use of the video-tacheometer Topcon Image Station IS-3 and the professional camera Canon EOS 5D Mark II. During the field work and the development of data the following experiments have been performed: multiple determination of the camera interior orientation parameters and distortion parameters of five lenses with different focal lengths, reflectorless measurements of profiles for the elevation and inventory of decorative surface wall of the building of Warsaw Ballet School. During the research the process of acquiring and integrating video-tacheometric data was analysed as well as the process of combining "point cloud" acquired by using video-tacheometer in the scanning process with independent photographs taken by a digital camera. On the basis of tests performed, utility of the use of video-tacheometric technology in geodetic surveys of geometrical features of buildings has been established.

The geometric nature of weights in real complex networks

NASA Astrophysics Data System (ADS)

Allard, Antoine; Serrano, M. Ángeles; García-Pérez, Guillermo; Boguñá, Marián

2017-01-01

The topology of many real complex networks has been conjectured to be embedded in hidden metric spaces, where distances between nodes encode their likelihood of being connected. Besides of providing a natural geometrical interpretation of their complex topologies, this hypothesis yields the recipe for sustainable Internet's routing protocols, sheds light on the hierarchical organization of biochemical pathways in cells, and allows for a rich characterization of the evolution of international trade. Here we present empirical evidence that this geometric interpretation also applies to the weighted organization of real complex networks. We introduce a very general and versatile model and use it to quantify the level of coupling between their topology, their weights and an underlying metric space. Our model accurately reproduces both their topology and their weights, and our results suggest that the formation of connections and the assignment of their magnitude are ruled by different processes.

Segmentation and texture analysis of structural biomarkers using neighborhood-clustering-based level set in MRI of the schizophrenic brain.

PubMed

Latha, Manohar; Kavitha, Ganesan

2018-02-03

Schizophrenia (SZ) is a psychiatric disorder that especially affects individuals during their adolescence. There is a need to study the subanatomical regions of SZ brain on magnetic resonance images (MRI) based on morphometry. In this work, an attempt was made to analyze alterations in structure and texture patterns in images of the SZ brain using the level-set method and Laws texture features. T1-weighted MRI of the brain from Center of Biomedical Research Excellence (COBRE) database were considered for analysis. Segmentation was carried out using the level-set method. Geometrical and Laws texture features were extracted from the segmented brain stem, corpus callosum, cerebellum, and ventricle regions to analyze pattern changes in SZ. The level-set method segmented multiple brain regions, with higher similarity and correlation values compared with an optimized method. The geometric features obtained from regions of the corpus callosum and ventricle showed significant variation (p < 0.00001) between normal and SZ brain. Laws texture feature identified a heterogeneous appearance in the brain stem, corpus callosum and ventricular regions, and features from the brain stem were correlated with Positive and Negative Syndrome Scale (PANSS) score (p < 0.005). A framework of geometric and Laws texture features obtained from brain subregions can be used as a supplement for diagnosis of psychiatric disorders.

Simulation of Robot Kinematics Using Interactive Computer Graphics.

ERIC Educational Resources Information Center

Leu, M. C.; Mahajan, R.

1984-01-01

Development of a robot simulation program based on geometric transformation softwares available in most computer graphics systems and program features are described. The program can be extended to simulate robots coordinating with external devices (such as tools, fixtures, conveyors) using geometric transformations to describe the…

Down syndrome detection from facial photographs using machine learning techniques

NASA Astrophysics Data System (ADS)

Zhao, Qian; Rosenbaum, Kenneth; Sze, Raymond; Zand, Dina; Summar, Marshall; Linguraru, Marius George

2013-02-01

Down syndrome is the most commonly occurring chromosomal condition; one in every 691 babies in United States is born with it. Patients with Down syndrome have an increased risk for heart defects, respiratory and hearing problems and the early detection of the syndrome is fundamental for managing the disease. Clinically, facial appearance is an important indicator in diagnosing Down syndrome and it paves the way for computer-aided diagnosis based on facial image analysis. In this study, we propose a novel method to detect Down syndrome using photography for computer-assisted image-based facial dysmorphology. Geometric features based on facial anatomical landmarks, local texture features based on the Contourlet transform and local binary pattern are investigated to represent facial characteristics. Then a support vector machine classifier is used to discriminate normal and abnormal cases; accuracy, precision and recall are used to evaluate the method. The comparison among the geometric, local texture and combined features was performed using the leave-one-out validation. Our method achieved 97.92% accuracy with high precision and recall for the combined features; the detection results were higher than using only geometric or texture features. The promising results indicate that our method has the potential for automated assessment for Down syndrome from simple, noninvasive imaging data.

Haptic exploration of fingertip-sized geometric features using a multimodal tactile sensor

NASA Astrophysics Data System (ADS)

Ponce Wong, Ruben D.; Hellman, Randall B.; Santos, Veronica J.

2014-06-01

Haptic perception remains a grand challenge for artificial hands. Dexterous manipulators could be enhanced by "haptic intelligence" that enables identification of objects and their features via touch alone. Haptic perception of local shape would be useful when vision is obstructed or when proprioceptive feedback is inadequate, as observed in this study. In this work, a robot hand outfitted with a deformable, bladder-type, multimodal tactile sensor was used to replay four human-inspired haptic "exploratory procedures" on fingertip-sized geometric features. The geometric features varied by type (bump, pit), curvature (planar, conical, spherical), and footprint dimension (1.25 - 20 mm). Tactile signals generated by active fingertip motions were used to extract key parameters for use as inputs to supervised learning models. A support vector classifier estimated order of curvature while support vector regression models estimated footprint dimension once curvature had been estimated. A distal-proximal stroke (along the long axis of the finger) enabled estimation of order of curvature with an accuracy of 97%. Best-performing, curvature-specific, support vector regression models yielded R2 values of at least 0.95. While a radial-ulnar stroke (along the short axis of the finger) was most helpful for estimating feature type and size for planar features, a rolling motion was most helpful for conical and spherical features. The ability to haptically perceive local shape could be used to advance robot autonomy and provide haptic feedback to human teleoperators of devices ranging from bomb defusal robots to neuroprostheses.

Streaks, multiplets, and holes: High-resolution spatio-temporal behavior of Parkfield seismicity

USGS Publications Warehouse

Waldhauser, F.; Ellsworth, W.L.; Schaff, D.P.; Cole, A.

2004-01-01

Double-difference locations of ???8000 earthquakes from 1969-2002 on the Parkfield section of the San Andreas Fault reveal detailed fault structures and seismicity that is, although complex, highly organized in both space and time. Distinctive features of the seismicity include: 1) multiple recurrence of earthquakes of the same size at precisely the same location on the fault (multiplets), implying frictional or geometric controls on their location and size; 2) sub-horizontal alignments of hypocenters along the fault plane (streaks), suggestive of rheological transitions within the fault zone and/or stress concentrations between locked and creeping areas; 3) regions devoid of microearthquakes with typical dimensions of 1-5 km (holes), one of which contains the M6 1966 Parkfield earthquake hypocenter. These features represent long lived structures that persist through many cycles of individual event. Copyright 2004 by the American Geophysical Union.

A Coordination Chemistry Approach to Fine-Tune the Physicochemical Parameters of Lanthanide Complexes Relevant to Medical Applications.

PubMed

Le Fur, Mariane; Molnár, Enikő; Beyler, Maryline; Kálmán, Ferenc K; Fougère, Olivier; Esteban-Gómez, David; Rousseaux, Olivier; Tripier, Raphaël; Tircsó, Gyula; Platas-Iglesias, Carlos

2018-03-02

The geometric features of two pyclen-based ligands possessing identical donor atoms but different site organization have a profound impact in their complexation properties toward lanthanide ions. The ligand containing two acetate groups and a picolinate arm arranged in a symmetrical fashion (L1) forms a Gd 3+ complex being two orders of magnitude less stable than its dissymmetric analogue GdL2. Besides, GdL1 experiences a much faster dissociation following the acid-catalyzed mechanism than GdL2. On the contrary, GdL1 exhibits a lower exchange rate of the coordinated water molecule compared to GdL2. These very different properties are related to different strengths of the Gd-ligand bonds associated to steric effects, which hinder the coordination of a water molecule in GdL2 and the binding of acetate groups in GdL1. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Geometric interpretations for resonances of plasmonic nanoparticles

NASA Astrophysics Data System (ADS)

Liu, Wei; Oulton, Rupert F.; Kivshar, Yuri S.

2015-07-01

The field of plasmonics can be roughly categorized into two branches: surface plasmon polaritons (SPPs) propagating in waveguides and localized surface plasmons (LSPs) supported by scattering particles. Investigations along these two directions usually employ different approaches, resulting in more or less a dogma that the two branches progress almost independently of each other, with few interactions. Here in this work we interpret LSPs from a Bohr model based geometric perspective relying on SPPs, thus establishing a connection between these two sub-fields. Besides the clear explanations of conventional scattering features of plasmonic nanoparticles, based on this geometric model we further demonstrate other anomalous scattering features (higher order modes supported at lower frequencies, and blueshift of the resonance with increasing particle sizes) and multiple electric resonances of the same order supported at different frequencies, which have been revealed to originate from backward SPP modes and multiple dispersion bands supported in the corresponding plasmonic waveguides, respectively. Inspired by this geometric model, it is also shown that, through solely geometric tuning, the absorption of each LSP resonance can be maximized to reach the single channel absorption limit, provided that the scattering and absorption rates are tuned to be equal.

Length measurement and spatial orientation reconstruction of single nanowires.

PubMed

Prestopino, Giuseppe; Orsini, Andrea; Falconi, Christian; Bietti, Sergio; Verona-Rinati, Gianluca; Caselli, Federica; Bisegna, Paolo

2018-06-27

The accurate determination of the geometrical features of quasi one-dimensional nanostructures is mandatory for reducing errors and improving repeatability in the estimation of a number of geometry-dependent properties in nanotechnology. In this paper a method for the reconstruction of length and spatial orientation of single nanowires is presented. Those quantities are calculated from a sequence of scanning electron microscope images taken at different tilt angles using a simple 3D geometric model. The proposed method is evaluated on a collection of scanning electron microscope images of single GaAs nanowires. It is validated through the reconstruction of known geometric features of a standard reference calibration pattern. An overall uncertainty of about 1% in the estimated length of the nanowires is achieved. © 2018 IOP Publishing Ltd.

High Resolution SAR Imaging Employing Geometric Features for Extracting Seismic Damage of Buildings

NASA Astrophysics Data System (ADS)

Cui, L. P.; Wang, X. P.; Dou, A. X.; Ding, X.

2018-04-01

Synthetic Aperture Radar (SAR) image is relatively easy to acquire but difficult for interpretation. This paper probes how to identify seismic damage of building using geometric features of SAR. The SAR imaging geometric features of buildings, such as the high intensity layover, bright line induced by double bounce backscattering and dark shadow is analysed, and show obvious differences texture features of homogeneity, similarity and entropy in combinatorial imaging geometric regions between the un-collapsed and collapsed buildings in airborne SAR images acquired in Yushu city damaged by 2010 Ms7.1 Yushu, Qinghai, China earthquake, which implicates a potential capability to discriminate collapsed and un-collapsed buildings from SAR image. Study also shows that the proportion of highlight (layover & bright line) area (HA) is related to the seismic damage degree, thus a SAR image damage index (SARDI), which related to the ratio of HA to the building occupation are of building in a street block (SA), is proposed. While HA is identified through feature extraction with high-pass and low-pass filtering of SAR image in frequency domain. A partial region with 58 natural street blocks in the Yushu City are selected as study area. Then according to the above method, HA is extracted, SARDI is then calculated and further classified into 3 classes. The results show effective through validation check with seismic damage classes interpreted artificially from post-earthquake airborne high resolution optical image, which shows total classification accuracy 89.3 %, Kappa coefficient 0.79 and identical to the practical seismic damage distribution. The results are also compared and discussed with the building damage identified from SAR image available by other authors.

Simplified and refined finite element approaches for determining stresses and internal forces in geometrically nonlinear structural analysis

NASA Technical Reports Server (NTRS)

Robinson, J. C.

1979-01-01

Two methods for determining stresses and internal forces in geometrically nonlinear structural analysis are presented. The simplified approach uses the mid-deformed structural position to evaluate strains when rigid body rotation is present. The important feature of this approach is that it can easily be used with a general-purpose finite-element computer program. The refined approach uses element intrinsic or corotational coordinates and a geometric transformation to determine element strains from joint displacements. Results are presented which demonstrate the capabilities of these potentially useful approaches for geometrically nonlinear structural analysis.

Iron-dextran complex: geometrical structure and magneto-optical features.

PubMed

Graczykowski, Bartłomiej; Dobek, Andrzej

2011-11-15

Molecular mass of the iron-dextran complex (M(w)=1133 kDa), diameter of its particles (∼8.3 nm) and the content of iron ions in the complex core (N(Fe)=6360) were determined by static light scattering, measurements of refractive index increment and the Cotton-Mouton effect in solution. The known number of iron ions permitted the calculation of the permanent magnetic dipole moment value to be μ(Fe)=3.17×10(-18) erg Oe(-1) and the determination of anisotropy of linear magneto-optical polarizabilities components as Δχ=9.2×10(-21) cm(3). Knowing both values and the value of the mean linear optical polarizability α=7.3×10(-20) cm(3), it was possible to show that the total measured CM effect was due to the reorientation of the permanent and the induced magnetic dipole moments of the complex. Analysis of the measured magneto-optical birefringence indicated very small optical anisotropy of linear optical polarizability components, κ(α), which suggested a homogeneous structure of particles of spherical symmetry. Copyright © 2011 Elsevier Inc. All rights reserved.

On the properties of microsolvated molecules in the ground (S0) and excited (S1) states: The anisole-ammonia 1:1 complex

NASA Astrophysics Data System (ADS)

Biczysko, Malgorzata; Piani, Giovanni; Pasquini, Massimiliano; Schiccheri, Nicola; Pietraperzia, Giangaetano; Becucci, Maurizio; Pavone, Michele; Barone, Vincenzo

2007-10-01

State-of-the-art spectroscopic and theoretical methods have been exploited in a joint effort to elucidate the subtle features of the structure and the energetics of the anisole-ammonia 1:1 complex, a prototype of microsolvation processes. Resonance enhanced multiphoton ionization and laser-induced fluorescence spectra are discussed and compared to high-level first-principles theoretical models, based on density functional, many body second order perturbation, and coupled cluster theories. In the most stable nonplanar structure of the complex, the ammonia interacts with the delocalized π electron density of the anisole ring: hydrogen bonding and dispersive forces provide a comparable stabilization energy in the ground state, whereas in the excited state the dispersion term is negligible because of electron density transfer from the oxygen to the aromatic ring. Ground and excited state geometrical parameters deduced from experimental data and computed by quantum mechanical methods are in very good agreement and allow us to unambiguously determine the molecular structure of the anisole-ammonia complex.

Encoding geometric and non-geometric information: a study with evolved agents.

PubMed

Ponticorvo, Michela; Miglino, Orazio

2010-01-01

Vertebrate species use geometric information and non-geometric or featural cues to orient. Under some circumstances, when both geometric and non-geometric information are available, the geometric information overwhelms non-geometric cues (geometric primacy). In other cases, we observe the inverse tendency or the successful integration of both cues. In past years, modular explanations have been proposed for the geometric primacy: geometric and non-geometric information are processed separately, with the geometry module playing a dominant role. The modularity issue is related to the recent debate on the encoding of geometric information: is it innate or does it depend on environmental experience? In order to get insight into the mechanisms that cause the wide variety of behaviors observed in nature, we used Artificial Life experiments. We demonstrated that agents trained mainly with a single class of information oriented efficiently when they were exposed to one class of information (geometric or non-geometric). When they were tested in environments that contained both classes of information, they displayed a primacy for the information that they had experienced more during their training phase. Encoding and processing geometric and non-geometric information was run in a single cognitive neuro-representation. These findings represent a theoretical proof that the exposure frequency to different spatial information during a learning/adaptive history could produce agents with no modular neuro-cognitive systems that are able to process different types of spatial information and display various orientation behaviors (geometric primacy, non-geometric primacy, no primacy at all).

How Can Students Generalize Examples? Focusing on the Generalizing Geometric Properties

ERIC Educational Resources Information Center

Park, JinHyeong; Kim, Dong-Won

2017-01-01

The purpose of this study is to determine the progression of exemplifying and example generalization by students. We investigated whether example generalization occurs by analyzing collected data by identifying whether students recognize, describe, and define general features of geometric examples. We also investigate how example generalization…

Model-assisted development of a laminography inspection system

NASA Astrophysics Data System (ADS)

Grandin, R.; Gray, J.

2012-05-01

Traditional computed tomography (CT) is an effective method of determining the internal structure of an object through non-destructive means; however, inspection of certain objects, such as those with planar geometrics or with limited access, requires an alternate approach. An alternative is laminography and has been the focus of a number of researchers in the past decade for both medical and industrial inspections. Many research efforts rely on geometrically-simple analytical models, such as the Shepp-Logan phantom, for the development of their algorithms. Recent work at the Center for Non-Destructive Evaluation makes extensive use of a forward model, XRSIM, to study artifacts arising from the reconstruction method, the effects of complex geometries and known issues such as high density features on the laminography reconstruction process. The use of a model provides full knowledge of all aspects of the geometry and provides a means to quantitatively evaluate the impact of methods designed to reduce artifacts generated by the reconstruction methods or that are result of the part geometry. We will illustrate the use of forward simulations to quantitatively assess reconstruction algorithm development and artifact reduction.

Effects of human dynamics on epidemic spreading in Côte d'Ivoire

NASA Astrophysics Data System (ADS)

Li, Ruiqi; Wang, Wenxu; Di, Zengru

2017-02-01

Understanding and predicting outbreaks of contagious diseases are crucial to the development of society and public health, especially for underdeveloped countries. However, challenging problems are encountered because of complex epidemic spreading dynamics influenced by spatial structure and human dynamics (including both human mobility and human interaction intensity). We propose a systematical model to depict nationwide epidemic spreading in Côte d'Ivoire, which integrates multiple factors, such as human mobility, human interaction intensity, and demographic features. We provide insights to aid in modeling and predicting the epidemic spreading process by data-driven simulation and theoretical analysis, which is otherwise beyond the scope of local evaluation and geometrical views. We show that the requirement that the average local basic reproductive number to be greater than unity is not necessary for outbreaks of epidemics. The observed spreading phenomenon can be roughly explained as a heterogeneous diffusion-reaction process by redefining mobility distance according to the human mobility volume between nodes, which is beyond the geometrical viewpoint. However, the heterogeneity of human dynamics still poses challenges to precise prediction.

Interfacial B-site atomic configuration in polar (111) and non-polar (001) SrIrO3/SrTiO3 heterostructures

NASA Astrophysics Data System (ADS)

Anderson, T. J.; Zhou, H.; Xie, L.; Podkaminer, J. P.; Patzner, J. J.; Ryu, S.; Pan, X. Q.; Eom, C. B.

2017-09-01

The precise control of interfacial atomic arrangement in ABO3 perovskite heterostructures is paramount, particularly in cases where the subsequent electronic properties of the material exhibit geometrical preferences along polar crystallographic directions that feature inevitably complex surface reconstructions. Here, we present the B-site interfacial structure in polar (111) and non-polar (001) SrIrO3/SrTiO3 interfaces. The heterostructures were examined using scanning transmission electron microscopy and synchrotron-based coherent Bragg rod analysis. Our results reveal the preference of B-site intermixing across the (111) interface due to the polarity-compensated SrTiO3 substrate surface prior to growth. By comparison, the intermixing at the non-polar (001) interface is negligible. This finding suggests that the intermixing may be necessary to mitigate epitaxy along heavily reconstructed and non-stoichiometric (111) perovskite surfaces. Furthermore, this preferential B-site configuration could allow the geometric design of the interfacial perovskite structure and chemistry to selectively engineer the correlated electronic states of the B-site d-orbital.

A topological study of gravity free-surface waves generated by bluff bodies using the method of steepest descents

PubMed Central

2016-01-01

The standard analytical approach for studying steady gravity free-surface waves generated by a moving body often relies upon a linearization of the physical geometry, where the body is considered asymptotically small in one or several of its dimensions. In this paper, a methodology that avoids any such geometrical simplification is presented for the case of steady-state flows at low speeds. The approach is made possible through a reduction of the water-wave equations to a complex-valued integral equation that can be studied using the method of steepest descents. The main result is a theory that establishes a correspondence between different bluff-bodied free-surface flow configurations, with the topology of the Riemann surface formed by the steepest descent paths. Then, when a geometrical feature of the body is modified, a corresponding change to the Riemann surface is observed, and the resultant effects to the water waves can be derived. This visual procedure is demonstrated for the case of two-dimensional free-surface flow past a surface-piercing ship and over an angled step in a channel. PMID:27493559

PCSYS: The optimal design integration system picture drawing system with hidden line algorithm capability for aerospace vehicle configurations

NASA Technical Reports Server (NTRS)

Hague, D. S.; Vanderburg, J. D.

1977-01-01

A vehicle geometric definition based upon quadrilateral surface elements to produce realistic pictures of an aerospace vehicle. The PCSYS programs can be used to visually check geometric data input, monitor geometric perturbations, and to visualize the complex spatial inter-relationships between the internal and external vehicle components. PCSYS has two major component programs. The between program, IMAGE, draws a complex aerospace vehicle pictorial representation based on either an approximate but rapid hidden line algorithm or without any hidden line algorithm. The second program, HIDDEN, draws a vehicle representation using an accurate but time consuming hidden line algorithm.

MD simulations of papillomavirus DNA-E2 protein complexes hints at a protein structural code for DNA deformation.

PubMed

Falconi, M; Oteri, F; Eliseo, T; Cicero, D O; Desideri, A

2008-08-01

The structural dynamics of the DNA binding domains of the human papillomavirus strain 16 and the bovine papillomavirus strain 1, complexed with their DNA targets, has been investigated by modeling, molecular dynamics simulations, and nuclear magnetic resonance analysis. The simulations underline different dynamical features of the protein scaffolds and a different mechanical interaction of the two proteins with DNA. The two protein structures, although very similar, show differences in the relative mobility of secondary structure elements. Protein structural analyses, principal component analysis, and geometrical and energetic DNA analyses indicate that the two transcription factors utilize a different strategy in DNA recognition and deformation. Results show that the protein indirect DNA readout is not only addressable to the DNA molecule flexibility but it is finely tuned by the mechanical and dynamical properties of the protein scaffold involved in the interaction.

Seizures induced by music.

PubMed

Ogunyemi, A O; Breen, H

1993-01-01

Musicogenic epilepsy is a rare disorder. Much remains to be learned about the electroclinical features. This report describes a patient who has been followed at our institution for 17 years, and was investigated with long-term telemetered simultaneous video-EEG recordings. She began to have seizures at the age of 10 years. She experienced complex partial seizures, often preceded by elementary auditory hallucination and complex auditory illusion. The seizures occurred in relation to singing, listening to music or thinking about music. She also had occasional generalized tonic clonic seizures during sleep. There was no significant antecedent history. The family history was negative for epilepsy. The physical examination was unremarkable. CT and MRI scans of the brain were normal. During long-term simultaneous video-EEG recordings, clinical and electrographic seizure activities were recorded in association with singing and listening to music. Mathematical calculation, copying or viewing geometric patterns and playing the game of chess failed to evoke seizures.

On designing low pressure loss working spaces for a planar Stirling micromachine

NASA Astrophysics Data System (ADS)

Hachey, M.-A.; Léveillé, É.; Fréchette, L. G.; Formosa, F.

2015-12-01

In this paper, research was undertaken with the objective to design low pressure loss working spaces for a Stirling cycle micro heat engine operating from low temperature waste heat. This planar free-piston heat engine is anticipated to operate at the kHz level with mm3 displacement. Given the resonant nature of the free-piston configuration, the complexity of its working gas’ flow geometry and its projected high operating frequency, flow analysis is relatively complex. Design considerations were thus based on fast prototyping and experimentation. Results show that geometrical features, such as a sharp 90° corner between the regenerator and working spaces, are strong contributors to pressure losses. This research culminated into a promising revised working space configuration for engine start-up, as it considerably reduced total pressure losses, more than 80% at Re = 700, from the original design.

PANTHER. Trajectory Analysis

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

Rintoul, Mark Daniel; Wilson, Andrew T.; Valicka, Christopher G.

We want to organize a body of trajectories in order to identify, search for, classify and predict behavior among objects such as aircraft and ships. Existing compari- son functions such as the Fr'echet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as total distance traveled and distance be- tween start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally, these features can generallymore » be mapped easily to behaviors of interest to humans that are searching large databases. Most of these geometric features are invariant under rigid transformation. We demonstrate the use of different subsets of these features to iden- tify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories, predict destination and apply unsupervised machine learning algorithms.« less

P09.62 Towards individualized survival prediction in glioblastoma patients using machine learning methods

PubMed Central

Vera, L.; Pérez-Beteta, J.; Molina, D.; Borrás, J. M.; Benavides, M.; Barcia, J. A.; Velásquez, C.; Albillo, D.; Lara, P.; Pérez-García, V. M.

2017-01-01

Abstract Introduction: Machine learning methods are integrated in clinical research studies due to their strong capability to discover parameters having a high information content and their predictive combined potential. Several studies have been developed using glioblastoma patient’s imaging data. Many of them have focused on including large numbers of variables, mostly two-dimensional textural features and/or genomic data, regardless of their meaning or potential clinical relevance. Materials and methods: 193 glioblastoma patients were included in the study. Preoperative 3D magnetic resonance images were collected and semi-automatically segmented using an in-house software. After segmentation, a database of 90 parameters including geometrical and textural image-based measures together with patients’ clinical data (including age, survival, type of treatment, etc.) was constructed. The criterion for including variables in the study was that they had either shown individual impact on survival in single or multivariate analyses or have a precise clinical or geometrical meaning. These variables were used to perform several machine learning experiments. In a first set of computational cross-validation experiments based on regression trees, those attributes showing the highest information measures were extracted. In the second phase, more sophisticated learning methods were employed in order to validate the potential of the previous variables predicting survival. Concretely support vector machines, neural networks and sparse grid methods were used. Results: Variables showing high information measure in the first phase provided the best prediction results in the second phase. Specifically, patient age, Stupp regimen and a geometrical measure related with the irregularity of contrast-enhancing areas were the variables showing the highest information measure in the first stage. For the second phase, the combinations of patient age and Stupp regimen together with one tumor geometrical measure and one tumor heterogeneity feature reached the best quality prediction. Conclusions: Advanced machine learning methods identified the parameters with the highest information measure and survival predictive potential. The uninformed machine learning methods identified a novel feature measure with direct impact on survival. Used in combination with other previously known variables multi-indexes can be defined that can help in tumor characterization and prognosis prediction. Recent advances on the definition of those multi-indexes will be reported in the conference. Funding: James S. Mc. Donnell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer [Collaborative award 220020450 and planning grant 220020420], MINECO/FEDER [MTM2015-71200-R], JCCM [PEII-2014-031-P].

The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers.

PubMed

Amalric, Marie; Wang, Liping; Pica, Pierre; Figueira, Santiago; Sigman, Mariano; Dehaene, Stanislas

2017-01-01

During language processing, humans form complex embedded representations from sequential inputs. Here, we ask whether a "geometrical language" with recursive embedding also underlies the human ability to encode sequences of spatial locations. We introduce a novel paradigm in which subjects are exposed to a sequence of spatial locations on an octagon, and are asked to predict future locations. The sequences vary in complexity according to a well-defined language comprising elementary primitives and recursive rules. A detailed analysis of error patterns indicates that primitives of symmetry and rotation are spontaneously detected and used by adults, preschoolers, and adult members of an indigene group in the Amazon, the Munduruku, who have a restricted numerical and geometrical lexicon and limited access to schooling. Furthermore, subjects readily combine these geometrical primitives into hierarchically organized expressions. By evaluating a large set of such combinations, we obtained a first view of the language needed to account for the representation of visuospatial sequences in humans, and conclude that they encode visuospatial sequences by minimizing the complexity of the structured expressions that capture them.

The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers

PubMed Central

Amalric, Marie; Wang, Liping; Figueira, Santiago; Sigman, Mariano; Dehaene, Stanislas

2017-01-01

During language processing, humans form complex embedded representations from sequential inputs. Here, we ask whether a “geometrical language” with recursive embedding also underlies the human ability to encode sequences of spatial locations. We introduce a novel paradigm in which subjects are exposed to a sequence of spatial locations on an octagon, and are asked to predict future locations. The sequences vary in complexity according to a well-defined language comprising elementary primitives and recursive rules. A detailed analysis of error patterns indicates that primitives of symmetry and rotation are spontaneously detected and used by adults, preschoolers, and adult members of an indigene group in the Amazon, the Munduruku, who have a restricted numerical and geometrical lexicon and limited access to schooling. Furthermore, subjects readily combine these geometrical primitives into hierarchically organized expressions. By evaluating a large set of such combinations, we obtained a first view of the language needed to account for the representation of visuospatial sequences in humans, and conclude that they encode visuospatial sequences by minimizing the complexity of the structured expressions that capture them. PMID:28125595

Computer modeling of electromagnetic problems using the geometrical theory of diffraction

NASA Technical Reports Server (NTRS)

Burnside, W. D.

1976-01-01

Some applications of the geometrical theory of diffraction (GTD), a high frequency ray optical solution to electromagnetic problems, are presented. GTD extends geometric optics, which does not take into account the diffractions occurring at edges, vertices, and various other discontinuities. Diffraction solutions, analysis of basic structures, construction of more complex structures, and coupling using GTD are discussed.

A study on axial and torsional resonant mode matching for a mechanical system with complex nonlinear geometries

NASA Astrophysics Data System (ADS)

Watson, Brett; Yeo, Leslie; Friend, James

2010-06-01

Making use of mechanical resonance has many benefits for the design of microscale devices. A key to successfully incorporating this phenomenon in the design of a device is to understand how the resonant frequencies of interest are affected by changes to the geometric parameters of the design. For simple geometric shapes, this is quite easy, but for complex nonlinear designs, it becomes significantly more complex. In this paper, two novel modeling techniques are demonstrated to extract the axial and torsional resonant frequencies of a complex nonlinear geometry. The first decomposes the complex geometry into easy to model components, while the second uses scaling techniques combined with the finite element method. Both models overcome problems associated with using current analytical methods as design tools, and enable a full investigation of how changes in the geometric parameters affect the resonant frequencies of interest. The benefit of such models is then demonstrated through their use in the design of a prototype piezoelectric ultrasonic resonant micromotor which has improved performance characteristics over previous prototypes.

Infrared Spectroscopic Imaging for Prostate Pathology Practice

DTIC Science & Technology

2010-03-01

lassification a lgorithm u ses mo rphological f eatures – geometric pr operties of epithelial cells/nuclei and lumens – that are quantified based on H&E stained...images as well as FT-IR images of the samples. By restricting the features used to geometric measures, we sought to m imic t he pa ttern r...be modeled as small elliptical areas in the stained images. This geometrical model is often confounded as multiple nuclei can be so close as to ap

Evolution of Geometric Sensitivity Derivatives from Computer Aided Design Models

NASA Technical Reports Server (NTRS)

Jones, William T.; Lazzara, David; Haimes, Robert

2010-01-01

The generation of design parameter sensitivity derivatives is required for gradient-based optimization. Such sensitivity derivatives are elusive at best when working with geometry defined within the solid modeling context of Computer-Aided Design (CAD) systems. Solid modeling CAD systems are often proprietary and always complex, thereby necessitating ad hoc procedures to infer parameter sensitivity. A new perspective is presented that makes direct use of the hierarchical associativity of CAD features to trace their evolution and thereby track design parameter sensitivity. In contrast to ad hoc methods, this method provides a more concise procedure following the model design intent and determining the sensitivity of CAD geometry directly to its respective defining parameters.

Dynamic feature analysis of vector-based images for neuropsychological testing

NASA Astrophysics Data System (ADS)

Smith, Stephen L.; Cervantes, Basilio R.

1998-07-01

The dynamic properties of human motor activities, such as those observed in the course of drawing simple geometric shapes, are considerably more complex and often more informative than the goal to be achieved; in this case a static line drawing. This paper demonstrates how these dynamic properties may be used to provide a means of assessing a patient's visuo-spatial ability -- an important component of neuropsychological testing. The work described here provides a quantitative assessment of visuo-spatial ability, whilst preserving the conventional test environment. Results will be presented for a clinical population of long-term haemodialysis patients and test population comprises three groups of children (1) 7-8 years, (2) 9-10 years and (3) 11-12 years, all of which have no known neurological dysfunction. Ten new dynamic measurements extracted from patient responses in conjunction with one static feature deduced from earlier work describe a patient's visuo-spatial ability in a quantitative manner with sensitivity not previously attainable. The dynamic feature measurements in isolation provide a unique means of tracking a patient's approach to motor activities and could prove useful in monitoring a child' visuo-motor development.

Feeling form: the neural basis of haptic shape perception.

PubMed

Yau, Jeffrey M; Kim, Sung Soo; Thakur, Pramodsingh H; Bensmaia, Sliman J

2016-02-01

The tactile perception of the shape of objects critically guides our ability to interact with them. In this review, we describe how shape information is processed as it ascends the somatosensory neuraxis of primates. At the somatosensory periphery, spatial form is represented in the spatial patterns of activation evoked across populations of mechanoreceptive afferents. In the cerebral cortex, neurons respond selectively to particular spatial features, like orientation and curvature. While feature selectivity of neurons in the earlier processing stages can be understood in terms of linear receptive field models, higher order somatosensory neurons exhibit nonlinear response properties that result in tuning for more complex geometrical features. In fact, tactile shape processing bears remarkable analogies to its visual counterpart and the two may rely on shared neural circuitry. Furthermore, one of the unique aspects of primate somatosensation is that it contains a deformable sensory sheet. Because the relative positions of cutaneous mechanoreceptors depend on the conformation of the hand, the haptic perception of three-dimensional objects requires the integration of cutaneous and proprioceptive signals, an integration that is observed throughout somatosensory cortex. Copyright © 2016 the American Physiological Society.

Geometric characterization and simulation of planar layered elastomeric fibrous biomaterials

PubMed Central

Carleton, James B.; D'Amore, Antonio; Feaver, Kristen R.; Rodin, Gregory J.; Sacks, Michael S.

2014-01-01

Many important biomaterials are composed of multiple layers of networked fibers. While there is a growing interest in modeling and simulation of the mechanical response of these biomaterials, a theoretical foundation for such simulations has yet to be firmly established. Moreover, correctly identifying and matching key geometric features is a critically important first step for performing reliable mechanical simulations. The present work addresses these issues in two ways. First, using methods of geometric probability we develop theoretical estimates for the mean linear and areal fiber intersection densities for two-dimensional fibrous networks. These densities are expressed in terms of the fiber density and the orientation distribution function, both of which are relatively easy-to-measure properties. Secondly, we develop a random walk algorithm for geometric simulation of two-dimensional fibrous networks which can accurately reproduce the prescribed fiber density and orientation distribution function. Furthermore, the linear and areal fiber intersection densities obtained with the algorithm are in agreement with the theoretical estimates. Both theoretical and computational results are compared with those obtained by post-processing of SEM images of actual scaffolds. These comparisons reveal difficulties inherent to resolving fine details of multilayered fibrous networks. The methods provided herein can provide a rational means to define and generate key geometric features from experimentally measured or prescribed scaffold structural data. PMID:25311685

Histopathological Image Classification using Discriminative Feature-oriented Dictionary Learning

PubMed Central

Vu, Tiep Huu; Mousavi, Hojjat Seyed; Monga, Vishal; Rao, Ganesh; Rao, UK Arvind

2016-01-01

In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structures. In this paper, we propose an automatic feature discovery framework via learning class-specific dictionaries and present a low-complexity method for classification and disease grading in histopathology. Essentially, our Discriminative Feature-oriented Dictionary Learning (DFDL) method learns class-specific dictionaries such that under a sparsity constraint, the learned dictionaries allow representing a new image sample parsimoniously via the dictionary corresponding to the class identity of the sample. At the same time, the dictionary is designed to be poorly capable of representing samples from other classes. Experiments on three challenging real-world image databases: 1) histopathological images of intraductal breast lesions, 2) mammalian kidney, lung and spleen images provided by the Animal Diagnostics Lab (ADL) at Pennsylvania State University, and 3) brain tumor images from The Cancer Genome Atlas (TCGA) database, reveal the merits of our proposal over state-of-the-art alternatives. Moreover, we demonstrate that DFDL exhibits a more graceful decay in classification accuracy against the number of training images which is highly desirable in practice where generous training is often not available. PMID:26513781

Geometrical modelling of textile reinforcements

NASA Technical Reports Server (NTRS)

Pastore, Christopher M.; Birger, Alexander B.; Clyburn, Eugene

1995-01-01

The mechanical properties of textile composites are dictated by the arrangement of yarns contained with the material. Thus to develop a comprehensive understanding of the performance of these materials, it is necessary to develop a geometrical model of the fabric structure. This task is quite complex, as the fabric is made form highly flexible yarn systems which experience a certain degree of compressability. Furthermore there are tremendous forces acting on the fabric during densification typically resulting in yarn displacement and misorientation. The objective of this work is to develop a methodology for characterizing the geometry of yarns within a fabric structure including experimental techniques for evaluating these models. Furthermore, some applications of these geometric results to mechanical prediction models are demonstrated. Although more costly than its predecessors, the present analysis is based on the detailed architecture developed by one of the authors and his colleagues and accounts for many of the geometric complexities that other analyses ignore.

Comprehensive Evaluation of Fast-Response, Reynolds-Averaged Navier–Stokes, and Large-Eddy Simulation Methods Against High-Spatial-Resolution Wind-Tunnel Data in Step-Down Street Canyons

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

Hayati, Arash Nemati; Stoll, Rob; Kim, J. J.

Three computational fluid dynamics (CFD) methods with different levels of flow-physics modelling are comprehensively evaluated against high-spatial-resolution wind-tunnel velocity data from step-down street canyons (i.e., a short building downwind of a tall building). The first method is a semi-empirical fast-response approach using the Quick Urban Industrial Complex (QUIC-URB) model. The second method solves the Reynolds-averaged Navier–Stokes (RANS) equations, and the third one utilizes a fully-coupled fluid-structure interaction large-eddy simulation (LES) model with a grid-turbulence inflow generator. Unlike typical point-by-point evaluation comparisons, here the entire two-dimensional wind-tunnel dataset is used to evaluate the dynamics of dominant flow topological features in themore » street canyon. Each CFD method is scrutinized for several geometric configurations by varying the downwind-to-upwind building-height ratio (H d/H u) and street canyon-width to building-width aspect ratio (S / W) for inflow winds perpendicular to the upwind building front face. Disparities between the numerical results and experimental data are quantified in terms of their ability to capture flow topological features for different geometric configurations. Ultimately, all three methods qualitatively predict the primary flow topological features, including a saddle point and a primary vortex. But, the secondary flow topological features, namely an in-canyon separation point and secondary vortices, are only well represented by the LES method despite its failure for taller downwind building cases. Misrepresentation of flow-regime transitions, exaggeration of the coherence of recirculation zones and wake fields, and overestimation of downwards vertical velocity into the canyon are the main defects in QUIC-URB, RANS and LES results, respectively. All three methods underestimate the updrafts and, surprisingly, QUIC-URB outperforms RANS for the streamwise velocity component, while RANS is superior to QUIC-URB for the vertical velocity component in the street canyon.« less

Comprehensive Evaluation of Fast-Response, Reynolds-Averaged Navier–Stokes, and Large-Eddy Simulation Methods Against High-Spatial-Resolution Wind-Tunnel Data in Step-Down Street Canyons

DOE PAGES

Hayati, Arash Nemati; Stoll, Rob; Kim, J. J.; ...

2017-05-18

Three computational fluid dynamics (CFD) methods with different levels of flow-physics modelling are comprehensively evaluated against high-spatial-resolution wind-tunnel velocity data from step-down street canyons (i.e., a short building downwind of a tall building). The first method is a semi-empirical fast-response approach using the Quick Urban Industrial Complex (QUIC-URB) model. The second method solves the Reynolds-averaged Navier–Stokes (RANS) equations, and the third one utilizes a fully-coupled fluid-structure interaction large-eddy simulation (LES) model with a grid-turbulence inflow generator. Unlike typical point-by-point evaluation comparisons, here the entire two-dimensional wind-tunnel dataset is used to evaluate the dynamics of dominant flow topological features in themore » street canyon. Each CFD method is scrutinized for several geometric configurations by varying the downwind-to-upwind building-height ratio (H d/H u) and street canyon-width to building-width aspect ratio (S / W) for inflow winds perpendicular to the upwind building front face. Disparities between the numerical results and experimental data are quantified in terms of their ability to capture flow topological features for different geometric configurations. Ultimately, all three methods qualitatively predict the primary flow topological features, including a saddle point and a primary vortex. But, the secondary flow topological features, namely an in-canyon separation point and secondary vortices, are only well represented by the LES method despite its failure for taller downwind building cases. Misrepresentation of flow-regime transitions, exaggeration of the coherence of recirculation zones and wake fields, and overestimation of downwards vertical velocity into the canyon are the main defects in QUIC-URB, RANS and LES results, respectively. All three methods underestimate the updrafts and, surprisingly, QUIC-URB outperforms RANS for the streamwise velocity component, while RANS is superior to QUIC-URB for the vertical velocity component in the street canyon.« less

Comprehensive Evaluation of Fast-Response, Reynolds-Averaged Navier-Stokes, and Large-Eddy Simulation Methods Against High-Spatial-Resolution Wind-Tunnel Data in Step-Down Street Canyons

NASA Astrophysics Data System (ADS)

Hayati, Arash Nemati; Stoll, Rob; Kim, J. J.; Harman, Todd; Nelson, Matthew A.; Brown, Michael J.; Pardyjak, Eric R.

2017-08-01

Three computational fluid dynamics (CFD) methods with different levels of flow-physics modelling are comprehensively evaluated against high-spatial-resolution wind-tunnel velocity data from step-down street canyons (i.e., a short building downwind of a tall building). The first method is a semi-empirical fast-response approach using the Quick Urban Industrial Complex (QUIC-URB) model. The second method solves the Reynolds-averaged Navier-Stokes (RANS) equations, and the third one utilizes a fully-coupled fluid-structure interaction large-eddy simulation (LES) model with a grid-turbulence inflow generator. Unlike typical point-by-point evaluation comparisons, here the entire two-dimensional wind-tunnel dataset is used to evaluate the dynamics of dominant flow topological features in the street canyon. Each CFD method is scrutinized for several geometric configurations by varying the downwind-to-upwind building-height ratio (H_d/H_u) and street canyon-width to building-width aspect ratio ( S / W) for inflow winds perpendicular to the upwind building front face. Disparities between the numerical results and experimental data are quantified in terms of their ability to capture flow topological features for different geometric configurations. Overall, all three methods qualitatively predict the primary flow topological features, including a saddle point and a primary vortex. However, the secondary flow topological features, namely an in-canyon separation point and secondary vortices, are only well represented by the LES method despite its failure for taller downwind building cases. Misrepresentation of flow-regime transitions, exaggeration of the coherence of recirculation zones and wake fields, and overestimation of downwards vertical velocity into the canyon are the main defects in QUIC-URB, RANS and LES results, respectively. All three methods underestimate the updrafts and, surprisingly, QUIC-URB outperforms RANS for the streamwise velocity component, while RANS is superior to QUIC-URB for the vertical velocity component in the street canyon.

Automated landmarking and geometric characterization of the carotid siphon.

PubMed

Bogunović, Hrvoje; Pozo, José María; Cárdenes, Rubén; Villa-Uriol, María Cruz; Blanc, Raphaël; Piotin, Michel; Frangi, Alejandro F

2012-05-01

The geometry of the carotid siphon has a large variability between subjects, which has prompted its study as a potential geometric risk factor for the onset of vascular pathologies on and off the internal carotid artery (ICA). In this work, we present a methodology for an objective and extensive geometric characterization of carotid siphon parameterized by a set of anatomical landmarks. We introduce a complete and automated characterization pipeline. Starting from the segmentation of vasculature from angiographic image and its centerline extraction, we first identify ICA by characterizing vessel tree bifurcations and training a support vector machine classifier to detect ICA terminal bifurcation. On ICA centerline curve, we detect anatomical landmarks of carotid siphon by modeling it as a sequence of four bends and selecting their centers and interfaces between them. Bends are detected from the trajectory of the curvature vector expressed in the parallel transport frame of the curve. Finally, using the detected landmarks, we characterize the geometry in two complementary ways. First, with a set of local and global geometric features, known to affect hemodynamics. Second, using large deformation diffeomorphic metric curve mapping (LDDMCM) to quantify pairwise shape similarity. We processed 96 images acquired with 3D rotational angiography. ICA identification had a cross-validation success rate of 99%. Automated landmarking was validated by computing limits of agreement with the reference taken to be the locations of the manually placed landmarks averaged across multiple observers. For all but one landmark, either the bias was not statistically significant or the variability was within 50% of the inter-observer one. The subsequently computed values of geometric features and LDDMCM were commensurate to the ones obtained with manual landmarking. The characterization based on pair-wise LDDMCM proved better in classifying the carotid siphon shape classes than the one based on geometric features. The proposed characterization provides a rich description of geometry and is ready to be applied in the search for geometric risk factors of the carotid siphon. Copyright © 2012 Elsevier B.V. All rights reserved.

Modeling Geometric-Temporal Context With Directional Pyramid Co-Occurrence for Action Recognition.

PubMed

Yuan, Chunfeng; Li, Xi; Hu, Weiming; Ling, Haibin; Maybank, Stephen J

2014-02-01

In this paper, we present a new geometric-temporal representation for visual action recognition based on local spatio-temporal features. First, we propose a modified covariance descriptor under the log-Euclidean Riemannian metric to represent the spatio-temporal cuboids detected in the video sequences. Compared with previously proposed covariance descriptors, our descriptor can be measured and clustered in Euclidian space. Second, to capture the geometric-temporal contextual information, we construct a directional pyramid co-occurrence matrix (DPCM) to describe the spatio-temporal distribution of the vector-quantized local feature descriptors extracted from a video. DPCM characterizes the co-occurrence statistics of local features as well as the spatio-temporal positional relationships among the concurrent features. These statistics provide strong descriptive power for action recognition. To use DPCM for action recognition, we propose a directional pyramid co-occurrence matching kernel to measure the similarity of videos. The proposed method achieves the state-of-the-art performance and improves on the recognition performance of the bag-of-visual-words (BOVWs) models by a large margin on six public data sets. For example, on the KTH data set, it achieves 98.78% accuracy while the BOVW approach only achieves 88.06%. On both Weizmann and UCF CIL data sets, the highest possible accuracy of 100% is achieved.

Solute transport by flow yields geometric shocks in shape evolution

NASA Astrophysics Data System (ADS)

Huang, Jinzi (Mac); Davies Wykes, Megan; Hajjar, George; Ristroph, Leif; Shelley, Michael

2017-11-01

Geological processes such as erosion and dissolution of surfaces often lead to striking shapes with strikingly sharp features. We present observations of such features forming in dissolution under gravity. In our experiment, a dissolving body with initially smooth surface evolves into an increasingly sharp needle shape. A mathematical model of its shape dynamics, derived from a boundary layer theory, predicts that a geometric shock forms at the tip of dissolved body, with the tip curvature becoming infinite in finite time. We further discuss the model's application to similar processes, such as flow driven erosion which can yield corners.

Cross-Cutting Relationships

NASA Technical Reports Server (NTRS)

2003-01-01

[figure removed for brevity, see original site]

Released 25 August 2003

The several linear cross-cutting grabens and collapse features observed in this THEMIS image illustrate the relative timing of a series of complex geologic processes as more recent events produce features that overlap and intersect older ones. Some impact craters are observed to be cut grabens, suggesting an older impact event compared to impact craters that appear fresh and unmodified.

Image information: VIS instrument. Latitude 14.1, Longitude 236.3 East (123.7 West). 19 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Fisher's geometrical model emerges as a property of complex integrated phenotypic networks.

PubMed

Martin, Guillaume

2014-05-01

Models relating phenotype space to fitness (phenotype-fitness landscapes) have seen important developments recently. They can roughly be divided into mechanistic models (e.g., metabolic networks) and more heuristic models like Fisher's geometrical model. Each has its own drawbacks, but both yield testable predictions on how the context (genomic background or environment) affects the distribution of mutation effects on fitness and thus adaptation. Both have received some empirical validation. This article aims at bridging the gap between these approaches. A derivation of the Fisher model "from first principles" is proposed, where the basic assumptions emerge from a more general model, inspired by mechanistic networks. I start from a general phenotypic network relating unspecified phenotypic traits and fitness. A limited set of qualitative assumptions is then imposed, mostly corresponding to known features of phenotypic networks: a large set of traits is pleiotropically affected by mutations and determines a much smaller set of traits under optimizing selection. Otherwise, the model remains fairly general regarding the phenotypic processes involved or the distribution of mutation effects affecting the network. A statistical treatment and a local approximation close to a fitness optimum yield a landscape that is effectively the isotropic Fisher model or its extension with a single dominant phenotypic direction. The fit of the resulting alternative distributions is illustrated in an empirical data set. These results bear implications on the validity of Fisher's model's assumptions and on which features of mutation fitness effects may vary (or not) across genomic or environmental contexts.

Non-Newtonian fluid flow in 2D fracture networks

NASA Astrophysics Data System (ADS)

Zou, L.; Håkansson, U.; Cvetkovic, V.

2017-12-01

Modeling of non-Newtonian fluid (e.g., drilling fluids and cement grouts) flow in fractured rocks is of interest in many geophysical and industrial practices, such as drilling operations, enhanced oil recovery and rock grouting. In fractured rock masses, the flow paths are dominated by fractures, which are often represented as discrete fracture networks (DFN). In the literature, many studies have been devoted to Newtonian fluid (e.g., groundwater) flow in fractured rock using the DFN concept, but few works are dedicated to non-Newtonian fluids.In this study, a generalized flow equation for common non-Newtonian fluids (such as Bingham, power-law and Herschel-Bulkley) in a single fracture is obtained from the analytical solutions for non-Newtonian fluid discharge between smooth parallel plates. Using Monte Carlo sampling based on site characterization data for the distribution of geometrical features (e.g., density, length, aperture and orientations) in crystalline fractured rock, a two dimensional (2D) DFN model is constructed for generic flow simulations. Due to complex properties of non-Newtonian fluids, the relationship between fluid discharge and the pressure gradient is nonlinear. A Galerkin finite element method solver is developed to iteratively solve the obtained nonlinear governing equations for the 2D DFN model. Using DFN realizations, simulation results for different geometrical distributions of the fracture network and different non-Newtonian fluid properties are presented to illustrate the spatial discharge distributions. The impact of geometrical structures and the fluid properties on the non-Newtonian fluid flow in 2D DFN is examined statistically. The results generally show that modeling non-Newtonian fluid flow in fractured rock as a DFN is feasible, and that the discharge distribution may be significantly affected by the geometrical structures as well as by the fluid constitutive properties.

Non a Priori Automatic Discovery of 3D Chemical Patterns: Application to Mutagenicity.

PubMed

Rabatel, Julien; Fannes, Thomas; Lepailleur, Alban; Le Goff, Jérémie; Crémilleux, Bruno; Ramon, Jan; Bureau, Ronan; Cuissart, Bertrand

2017-10-01

This article introduces a new type of structural fragment called a geometrical pattern. Such geometrical patterns are defined as molecular graphs that include a labelling of atoms together with constraints on interatomic distances. The discovery of geometrical patterns in a chemical dataset relies on the induction of multiple decision trees combined in random forests. Each computational step corresponds to a refinement of a preceding set of constraints, extending a previous geometrical pattern. This paper focuses on the mutagenicity of chemicals via the definition of structural alerts in relation with these geometrical patterns. It follows an experimental assessment of the main geometrical patterns to show how they can efficiently originate the definition of a chemical feature related to a chemical function or a chemical property. Geometrical patterns have provided a valuable and innovative approach to bring new pieces of information for discovering and assessing structural characteristics in relation to a particular biological phenotype. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

On the critical or geometrical nature of the observed scaling laws associated with the fracture and faulting processes

NASA Astrophysics Data System (ADS)

Potirakis, Stelios M.; Kopanas, John; Antonopoulos, George; Nomicos, Constantinos; Eftaxias, Konstantinos

2015-04-01

One of the largest controversial issues of the materials science community is the interpretation of scaling laws associated with the fracture and faulting processes. Especially, an important open question is whether the spatial and temporal complexity of earthquakes and fault structures, above all the interpretation of the observed scaling laws, emerge from geometrical and material built-in heterogeneities or from the critical behavior inherent to the nonlinear equations governing the earthquake dynamics. Crack propagation is the basic mechanism of material's failure. A number of laboratory studies carried out on a wide range of materials have revealed the existence of EMEs during fracture experiments, while these emissions are ranging in a wide frequency spectrum, i.e., from the kHz to the MHz bands. A crucial feature observed on the laboratory scale is that the MHz EME systematically precedes the corresponding kHz one. The aforementioned crucial feature is observed in geophysical scale, as well. The remarkable asynchronous appearance of these two EMEs both on the laboratory and the geophysical scale implies that they refer to different final stages of faulting process. Accumulated laboratory, theoretical and numerical evidence supports the hypothesis that the MHz EME is emitted during the fracture of process of heterogeneous medium surrounding the family of strong entities (asperities) distributed along the fault sustaining the system. The kHz EME is attributed to the family of asperities themselves. We argue in terms of the fracture induced pre-seismic MHz-kHz EMEs that the scaling laws associated with the fracture of heterogeneous materials emerge from the critical behavior inherent to the nonlinear equations governing their dynamics (second-order phase transition), while the scaling laws associated with the fracture of family of asperities have geometric nature, namely, are rooted in the fractal nature of the population of asperities.

Geometric multigrid to accelerate the solution of the quasi-static electric field problem by tetrahedral finite elements.

PubMed

Hollaus, K; Weiss, B; Magele, Ch; Hutten, H

2004-02-01

The acceleration of the solution of the quasi-static electric field problem considering anisotropic complex conductivity simulated by tetrahedral finite elements of first order is investigated by geometric multigrid.

Some basic results on the sets of sequences with geometric calculus

NASA Astrophysics Data System (ADS)

Türkmen, Cengiz; Başar, Feyzi

2012-08-01

As an alternative to the classical calculus, Grossman and Katz [Non-Newtonian Calculus, Lee Press, Pigeon Cove, Massachusetts, 1972] introduced the non-Newtonian calculus consisting of the branches of geometric, anageometric and bigeometric calculus. Following Grossman and Katz, we construct the field C(G) of geometric complex numbers and the concept of geometric metric. Also we give the triangle and Minkowski's inequalities in the sense of geometric calculus. Later we respectively define the sets w(G), ℓ∞(G), c(G), c0(G) and ℓp(G) of all, bounded, convergent, null and p-absolutely summable sequences, in the sense of geometric calculus and show that each of the set forms a complete vector space on the field C(G).

Geometric phase of mixed states for three-level open systems

NASA Astrophysics Data System (ADS)

Jiang, Yanyan; Ji, Y. H.; Xu, Hualan; Hu, Li-Yun; Wang, Z. S.; Chen, Z. Q.; Guo, L. P.

2010-12-01

Geometric phase of mixed state for three-level open system is defined by establishing in connecting density matrix with nonunit vector ray in a three-dimensional complex Hilbert space. Because the geometric phase depends only on the smooth curve on this space, it is formulated entirely in terms of geometric structures. Under the limiting of pure state, our approach is in agreement with the Berry phase, Pantcharatnam phase, and Aharonov and Anandan phase. We find that, furthermore, the Berry phase of mixed state correlated to population inversions of three-level open system.

Residual Shuffling Convolutional Neural Networks for Deep Semantic Image Segmentation Using Multi-Modal Data

NASA Astrophysics Data System (ADS)

Chen, K.; Weinmann, M.; Gao, X.; Yan, M.; Hinz, S.; Jutzi, B.; Weinmann, M.

2018-05-01

In this paper, we address the deep semantic segmentation of aerial imagery based on multi-modal data. Given multi-modal data composed of true orthophotos and the corresponding Digital Surface Models (DSMs), we extract a variety of hand-crafted radiometric and geometric features which are provided separately and in different combinations as input to a modern deep learning framework. The latter is represented by a Residual Shuffling Convolutional Neural Network (RSCNN) combining the characteristics of a Residual Network with the advantages of atrous convolution and a shuffling operator to achieve a dense semantic labeling. Via performance evaluation on a benchmark dataset, we analyze the value of different feature sets for the semantic segmentation task. The derived results reveal that the use of radiometric features yields better classification results than the use of geometric features for the considered dataset. Furthermore, the consideration of data on both modalities leads to an improvement of the classification results. However, the derived results also indicate that the use of all defined features is less favorable than the use of selected features. Consequently, data representations derived via feature extraction and feature selection techniques still provide a gain if used as the basis for deep semantic segmentation.

Quantitative 3-D Imaging, Segmentation and Feature Extraction of the Respiratory System in Small Mammals for Computational Biophysics Simulations

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

Trease, Lynn L.; Trease, Harold E.; Fowler, John

2007-03-15

One of the critical steps toward performing computational biology simulations, using mesh based integration methods, is in using topologically faithful geometry derived from experimental digital image data as the basis for generating the computational meshes. Digital image data representations contain both the topology of the geometric features and experimental field data distributions. The geometric features that need to be captured from the digital image data are three-dimensional, therefore the process and tools we have developed work with volumetric image data represented as data-cubes. This allows us to take advantage of 2D curvature information during the segmentation and feature extraction process.more » The process is basically: 1) segmenting to isolate and enhance the contrast of the features that we wish to extract and reconstruct, 2) extracting the geometry of the features in an isosurfacing technique, and 3) building the computational mesh using the extracted feature geometry. “Quantitative” image reconstruction and feature extraction is done for the purpose of generating computational meshes, not just for producing graphics "screen" quality images. For example, the surface geometry that we extract must represent a closed water-tight surface.« less

Multiscale unfolding of real networks by geometric renormalization

NASA Astrophysics Data System (ADS)

García-Pérez, Guillermo; Boguñá, Marián; Serrano, M. Ángeles

2018-06-01

Symmetries in physical theories denote invariance under some transformation, such as self-similarity under a change of scale. The renormalization group provides a powerful framework to study these symmetries, leading to a better understanding of the universal properties of phase transitions. However, the small-world property of complex networks complicates application of the renormalization group by introducing correlations between coexisting scales. Here, we provide a framework for the investigation of complex networks at different resolutions. The approach is based on geometric representations, which have been shown to sustain network navigability and to reveal the mechanisms that govern network structure and evolution. We define a geometric renormalization group for networks by embedding them into an underlying hidden metric space. We find that real scale-free networks show geometric scaling under this renormalization group transformation. We unfold the networks in a self-similar multilayer shell that distinguishes the coexisting scales and their interactions. This in turn offers a basis for exploring critical phenomena and universality in complex networks. It also affords us immediate practical applications, including high-fidelity smaller-scale replicas of large networks and a multiscale navigation protocol in hyperbolic space, which betters those on single layers.

3D facial expression recognition using maximum relevance minimum redundancy geometrical features

NASA Astrophysics Data System (ADS)

Rabiu, Habibu; Saripan, M. Iqbal; Mashohor, Syamsiah; Marhaban, Mohd Hamiruce

2012-12-01

In recent years, facial expression recognition (FER) has become an attractive research area, which besides the fundamental challenges, it poses, finds application in areas, such as human-computer interaction, clinical psychology, lie detection, pain assessment, and neurology. Generally the approaches to FER consist of three main steps: face detection, feature extraction and expression recognition. The recognition accuracy of FER hinges immensely on the relevance of the selected features in representing the target expressions. In this article, we present a person and gender independent 3D facial expression recognition method, using maximum relevance minimum redundancy geometrical features. The aim is to detect a compact set of features that sufficiently represents the most discriminative features between the target classes. Multi-class one-against-one SVM classifier was employed to recognize the seven facial expressions; neutral, happy, sad, angry, fear, disgust, and surprise. The average recognition accuracy of 92.2% was recorded. Furthermore, inter database homogeneity was investigated between two independent databases the BU-3DFE and UPM-3DFE the results showed a strong homogeneity between the two databases.

Iron(II) complexes of new hexadentate 1,1,1-tris-(iminomethyl)ethane podands, and their 7-methyl-1,3,5-triazaadamantane rearrangement products.

PubMed

Diener, Sara A; Santoro, Amedeo; Kilner, Colin A; Loughrey, Jonathan J; Halcrow, Malcolm A

2012-04-07

New iron(II) podand complexes have been prepared, by condensation of 2-(aminomethyl)-2-methyl-1,3-diaminopropane with 3 equiv of a heterocyclic aldehyde in the presence of hydrated Fe[BF(4)](2) or Fe[ClO(4)](2) as templates. The 2-(aminomethyl)-2-methyl-1,3-diaminopropane is prepared in situ by deprotonation of its trihydrochloride salt. The chloride must be removed from these reactions by precipitation with silver, to avoid the formation of the alternative 2,4,6-trisubstituted-7-methyl-1,3,5-triazaadamantane condensation products, or their FeCl(2) adducts. The crystal structures of two 2,4,6-tri(pyridyl)-7-methyl-1,3,5-triazaadamantane-containing species are presented, and contain two different geometric isomers of this tricyclic ring with three equatorial, or two equatorial and one axial, pyridyl substituents. Both structures feature strong C-HX (X = Cl or F) hydrogen bonding from the aminal C-H groups in the triazaadamantane ring. Five iron(II) podand complexes were successfully obtained, all of which contain low-spin iron centres.

Identification of literary movements using complex networks to represent texts

NASA Astrophysics Data System (ADS)

Amancio, Diego Raphael; Oliveira, Osvaldo N., Jr.; da Fontoura Costa, Luciano

2012-04-01

The use of statistical methods to analyze large databases of text has been useful in unveiling patterns of human behavior and establishing historical links between cultures and languages. In this study, we identified literary movements by treating books published from 1590 to 1922 as complex networks, whose metrics were analyzed with multivariate techniques to generate six clusters of books. The latter correspond to time periods coinciding with relevant literary movements over the last five centuries. The most important factor contributing to the distinctions between different literary styles was the average shortest path length, in particular the asymmetry of its distribution. Furthermore, over time there has emerged a trend toward larger average shortest path lengths, which is correlated with increased syntactic complexity, and a more uniform use of the words reflected in a smaller power-law coefficient for the distribution of word frequency. Changes in literary style were also found to be driven by opposition to earlier writing styles, as revealed by the analysis performed with geometrical concepts. The approaches adopted here are generic and may be extended to analyze a number of features of languages and cultures.

Seeing mathematics: perceptual experience and brain activity in acquired synesthesia.

PubMed

Brogaard, Berit; Vanni, Simo; Silvanto, Juha

2013-01-01

We studied the patient JP who has exceptional abilities to draw complex geometrical images by hand and a form of acquired synesthesia for mathematical formulas and objects, which he perceives as geometrical figures. JP sees all smooth curvatures as discrete lines, similarly regardless of scale. We carried out two preliminary investigations to establish the perceptual nature of synesthetic experience and to investigate the neural basis of this phenomenon. In a functional magnetic resonance imaging (fMRI) study, image-inducing formulas produced larger fMRI responses than non-image inducing formulas in the left temporal, parietal and frontal lobes. Thus our main finding is that the activation associated with his experience of complex geometrical images emerging from mathematical formulas is restricted to the left hemisphere.

An adaptive moving finite volume scheme for modeling flood inundation over dry and complex topography

NASA Astrophysics Data System (ADS)

Zhou, Feng; Chen, Guoxian; Huang, Yuefei; Yang, Jerry Zhijian; Feng, Hui

2013-04-01

A new geometrical conservative interpolation on unstructured meshes is developed for preserving still water equilibrium and positivity of water depth at each iteration of mesh movement, leading to an adaptive moving finite volume (AMFV) scheme for modeling flood inundation over dry and complex topography. Unlike traditional schemes involving position-fixed meshes, the iteration process of the AFMV scheme moves a fewer number of the meshes adaptively in response to flow variables calculated in prior solutions and then simulates their posterior values on the new meshes. At each time step of the simulation, the AMFV scheme consists of three parts: an adaptive mesh movement to shift the vertices position, a geometrical conservative interpolation to remap the flow variables by summing the total mass over old meshes to avoid the generation of spurious waves, and a partial differential equations(PDEs) discretization to update the flow variables for a new time step. Five different test cases are presented to verify the computational advantages of the proposed scheme over nonadaptive methods. The results reveal three attractive features: (i) the AMFV scheme could preserve still water equilibrium and positivity of water depth within both mesh movement and PDE discretization steps; (ii) it improved the shock-capturing capability for handling topographic source terms and wet-dry interfaces by moving triangular meshes to approximate the spatial distribution of time-variant flood processes; (iii) it was able to solve the shallow water equations with a relatively higher accuracy and spatial-resolution with a lower computational cost.

Practical Implementation of Semi-Automated As-Built Bim Creation for Complex Indoor Environments

NASA Astrophysics Data System (ADS)

Yoon, S.; Jung, J.; Heo, J.

2015-05-01

In recent days, for efficient management and operation of existing buildings, the importance of as-built BIM is emphasized in AEC/FM domain. However, fully automated as-built BIM creation is a tough issue since newly-constructed buildings are becoming more complex. To manage this problem, our research group has developed a semi-automated approach, focusing on productive 3D as-built BIM creation for complex indoor environments. In order to test its feasibility for a variety of complex indoor environments, we applied the developed approach to model the `Charlotte stairs' in Lotte World Mall, Korea. The approach includes 4 main phases: data acquisition, data pre-processing, geometric drawing, and as-built BIM creation. In the data acquisition phase, due to its complex structure, we moved the scanner location several times to obtain the entire point clouds of the test site. After which, data pre-processing phase entailing point-cloud registration, noise removal, and coordinate transformation was followed. The 3D geometric drawing was created using the RANSAC-based plane detection and boundary tracing methods. Finally, in order to create a semantically-rich BIM, the geometric drawing was imported into the commercial BIM software. The final as-built BIM confirmed that the feasibility of the proposed approach in the complex indoor environment.

A trap potential model investigation of the optical activity induced in dye-DNA intercalation complexes

NASA Astrophysics Data System (ADS)

Kamiya, Mamoru

1988-02-01

The fundamental features of the optical activity induced in dye-DNA intercalation complexes are studied by application of the trap potential model which is useful to evaluate the induced rotational strength without reference to detailed geometrical information about the intercalation complexes. The specific effect of the potential depth upon the induced optical activity is explained in terms of the relative magnitudes of the wave-phase and helix-phase variations in the path of an electron moving on a restricted helical segment just like an exciton trapped around the dye intercalation site. The parallel and perpendicular components of the induced rotational strength well reflect basic properties of the helicity effects about the longitudinal and tangential axes of the DNA helical cylinder. The trap potential model is applied to optimize the potential parameters so as to reproduce the ionic strength effect upon the optical activity induced to proflavine-DNA intercalation complexes. From relationships between the optimized potential parameters and ionic strengths, it is inferred that increase in the ionic strength contributes to the optical activity induced by the nearest-neighbour interaction between intercalated proflavine and DNA base pairs.

Research on the laser transmission characteristics simulation and comprehensive test in complex channel environment

NASA Astrophysics Data System (ADS)

Fu, Qiang; Liu, Jianhua; Wang, Xiaoman; Jiang, Huilin; Liu, Zhi

2014-12-01

The laser transmission characteristics affected in the complex channel environment, which limits the performance of laser equipment and engineering application severely. The article aim at the influence of laser transmission in atmospheric and seawater channels, summarizes the foreign researching work of the simulation and comprehensive test regarding to the laser transmission characteristics in complex environment. And researched the theory of atmospheric turbulence effect, water attenuation features, and put forward the corresponding theoretical model. And researched the simulate technology of atmospheric channel and sea water channel, put forward the analog device plan, adopt the similar theory of flowing to simulate the atmosphere turbulence .When the flowing has the same condition of geometric limits including the same Reynolds, they must be similar to each other in the motivation despite of the difference in the size, speed, and intrinsic quality. On this basis, set up a device for complex channel simulation and comprehensive testing, the overall design of the structure of the device, Hot and Cold Air Convection Simulation of Atmospheric Turbulence, mainly consists of cell body, heating systems, cooling systems, automatic control system. he simulator provides platform and method for the basic research of laser transmission characteristics in the domestic.

Peripheral Faulting of Eden Patera: Potential Evidence in Support of a New Volcanic Construct on Mars

NASA Astrophysics Data System (ADS)

Harlow, J.

2016-12-01

Arabia Terra's (AT) pock-marked topography in the expansive upland region of Mars Northern Hemisphere has been assumed to be the result of impact crater bombardment. However, examination of several craters by researchers revealed morphologies inconsistent with neighboring craters of similar size and age. These 'craters' share features with terrestrial super-eruption calderas, and are considered a new volcanic construct on Mars called `plains-style' caldera complexes. Eden Patera (EP), located on the northern boundary of AT is a reference type for these calderas. EP lacks well-preserved impact crater morphologies, including a decreasing depth to diameter ratio. Conversely, Eden shares geomorphological attributes with terrestrial caldera complexes such as Valles Caldera (New Mexico): arcuate caldera walls, concentric fracturing/faulting, flat-topped benches, irregular geometric circumferences, etc. This study focuses on peripheral fractures surrounding EP to provide further evidence of calderas within the AT region. Scaled balloon experiments mimicking terrestrial caldera analogs have showcased fracturing/faulting patterns and relationships of caldera systems. These experiments show: 1) radial fracturing (perpendicular to caldera rim) upon inflation, 2) concentric faulting (parallel to sub-parallel to caldera rim) during evacuation, and 3) intersecting radial and concentric peripheral faulting from resurgence. Utilizing Mars Reconnaissance Orbiter Context Camera (CTX) imagery, peripheral fracturing is analyzed using GIS to study variations in peripheral fracture geometries relative to the caldera rim. Visually, concentric fractures dominate within 20 km, radial fractures prevail between 20 and 50 km, followed by gradation into randomly oriented and highly angular intersections in the fretted terrain region. Rose diagrams of orientation relative to north expose uniformly oriented mean regional stresses, but do not illuminate localized caldera stresses. Further examination of orientation relative to caldera rim reveals expected orientations of ±30° on rose diagrams, taking into account the geometric nature of concentric faulting. These results establish a quantitative geometric system to differentiate localized from regional faulting surrounding Eden Patera.

Triggered Snap-Through of Bistable Shells

NASA Astrophysics Data System (ADS)

Cai, Yijie; Huang, Shicheng; Trase, Ian; Hu, Nan; Chen, Zi

Elastic bistable shells are common structures in nature and engineering, such as the lobes of the Venus flytrap or the surface of a toy jumping poppers. Despite their ubiquity, the parameters that control the bistability of such structures are not well understood. In this study, we explore how the geometrical features of radially symmetric elastic shells affect the shape and potential energy of a shell's stable states, and how to tune certain parameters in order to generate a snap-through transition from a convex semi-stable state to concave stable state. We fabricated a series of elastic shells with varying geometric parameters out of silicone rubber and measured the resulting potential energy in the semi-stable state. Finite element simulations were also conducted in order to determine the deformation and stress in the shells during snap-through. It was found that the energy of the semi-stable state is controlled by only two geometric parameters and a dimensionless ratio. We also noted two distinct transitions during snap-through, one between monostability and semi-bistability (the state a popper toy is in before it snaps-through and jumps), and a second transition between semi-bistability and true bistability. This work shows that it is possible to use a set of simple parameters to tailor the energy landscape of an elastic shell in order to generate complex trigger motions for their potential use in smart applications. Z.C. acknowledge support from Society in Science-Branco Weiss Fellowship, administered by ETH Zurich.

Geometric characterization and simulation of planar layered elastomeric fibrous biomaterials

DOE PAGES

Carleton, James B.; D’Amore, Antonio; Feaver, Kristen R.; ...

2014-10-13

Many important biomaterials are composed of multiple layers of networked fibers. While there is a growing interest in modeling and simulation of the mechanical response of these biomaterials, a theoretical foundation for such simulations has yet to be firmly established. Moreover, correctly identifying and matching key geometric features is a critically important first step for performing reliable mechanical simulations. This paper addresses these issues in two ways. First, using methods of geometric probability, we develop theoretical estimates for the mean linear and areal fiber intersection densities for 2-D fibrous networks. These densities are expressed in terms of the fiber densitymore » and the orientation distribution function, both of which are relatively easy-to-measure properties. Secondly, we develop a random walk algorithm for geometric simulation of 2-D fibrous networks which can accurately reproduce the prescribed fiber density and orientation distribution function. Furthermore, the linear and areal fiber intersection densities obtained with the algorithm are in agreement with the theoretical estimates. Both theoretical and computational results are compared with those obtained by post-processing of scanning electron microscope images of actual scaffolds. These comparisons reveal difficulties inherent to resolving fine details of multilayered fibrous networks. Finally, the methods provided herein can provide a rational means to define and generate key geometric features from experimentally measured or prescribed scaffold structural data.« less

Spacetime encodings. II. Pictures of integrability

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

Brink, Jeandrew

I visually explore the features of geodesic orbits in arbitrary stationary axisymmetric vacuum (SAV) spacetimes that are constructed from a complex Ernst potential. Some of the geometric features of integrable and chaotic orbits are highlighted. The geodesic problem for these SAV spacetimes is rewritten as a 2 degree of freedom problem and the connection between current ideas in dynamical systems and the study of two manifolds sought. The relationship between the Hamilton-Jacobi equations, canonical transformations, constants of motion, and Killing tensors are commented on. Wherever possible I illustrate the concepts by means of examples from general relativity. This investigation ismore » designed to build the readers' intuition about how integrability arises, and to summarize some of the known facts about 2 degree of freedom systems. Evidence is given, in the form of an orbit-crossing structure, that geodesics in SAV spacetimes might admit a fourth constant of motion that is quartic in momentum (by contrast with Kerr spacetime, where Carter's fourth constant is quadratic)« less

[Three dimensional mathematical model of tooth for finite element analysis].

PubMed

Puskar, Tatjana; Vasiljević, Darko; Marković, Dubravka; Jevremović, Danimir; Pantelić, Dejan; Savić-Sević, Svetlana; Murić, Branka

2010-01-01

The mathematical model of the abutment tooth is the starting point of the finite element analysis of stress and deformation of dental structures. The simplest and easiest way is to form a model according to the literature data of dimensions and morphological characteristics of teeth. Our method is based on forming 3D models using standard geometrical forms (objects) in programmes for solid modeling. Forming the mathematical model of abutment of the second upper premolar for finite element analysis of stress and deformation of dental structures. The abutment tooth has a form of a complex geometric object. It is suitable for modeling in programs for solid modeling SolidWorks. After analysing the literature data about the morphological characteristics of teeth, we started the modeling dividing the tooth (complex geometric body) into simple geometric bodies (cylinder, cone, pyramid,...). Connecting simple geometric bodies together or substricting bodies from the basic body, we formed complex geometric body, tooth. The model is then transferred into Abaqus, a computational programme for finite element analysis. Transferring the data was done by standard file format for transferring 3D models ACIS SAT. Using the programme for solid modeling SolidWorks, we developed three models of abutment of the second maxillary premolar: the model of the intact abutment, the model of the endodontically treated tooth with two remaining cavity walls and the model of the endodontically treated tooth with two remaining walls and inserted post. Mathematical models of the abutment made according to the literature data are very similar with the real abutment and the simplifications are minimal. These models enable calculations of stress and deformation of the dental structures. The finite element analysis provides useful information in understanding biomechanical problems and gives guidance for clinical research.

Geological and Structural Patterns on Titan Enhanced Through Cassini's SAR PCA and High-Resolution Radiometry

NASA Astrophysics Data System (ADS)

Paganelli, F.; Schubert, G.; Lopes, R. M. C.; Malaska, M.; Le Gall, A. A.; Kirk, R. L.

2016-12-01

The current SAR data coverage on Titan encompasses several areas in which multiple radar passes are present and overlapping, providing additional information to aid the interpretation of geological and structural features. We exploit the different combinations of look direction and variable incidence angle to examine Cassini Synthetic Aperture RADAR (SAR) data using the Principal Component Analysis (PCA) technique and high-resolution radiometry, as a tool to aid in the interpretation of geological and structural features. Look direction and variable incidence angle is of particular importance in the analysis of variance in the images, which aid in the perception and identification of geological and structural features, as extensively demonstrated in Earth and planetary examples. The PCA enhancement technique uses projected non-ortho-rectified SAR imagery in order to maintain the inherent differences in scattering and geometric properties due to the different look directions, while enhancing the geometry of surface features. The PC2 component provides a stereo view of the areas in which complex surface features and structural patterns can be enhanced and outlined. We focus on several areas of interest, in older and recently acquired flybys, in which evidence of geological and structural features can be enhanced and outlined in the PC1 and PC2 components. Results of this technique provide enhanced geometry and insights into the interpretation of the observed geological and structural features, thus allowing a better understanding towards the geology and tectonics on Titan.

Improved Remapping Processor For Digital Imagery

NASA Technical Reports Server (NTRS)

Fisher, Timothy E.

1991-01-01

Proposed digital image processor improved version of Programmable Remapper, which performs geometric and radiometric transformations on digital images. Features include overlapping and variably sized preimages. Overcomes some of limitations of image-warping circuit boards implementing only those geometric tranformations expressible in terms of polynomials of limited order. Also overcomes limitations of existing Programmable Remapper and made to perform transformations at video rate.

Selection of the best features for leukocytes classification in blood smear microscopic images

NASA Astrophysics Data System (ADS)

Sarrafzadeh, Omid; Rabbani, Hossein; Talebi, Ardeshir; Banaem, Hossein Usefi

2014-03-01

Automatic differential counting of leukocytes provides invaluable information to pathologist for diagnosis and treatment of many diseases. The main objective of this paper is to detect leukocytes from a blood smear microscopic image and classify them into their types: Neutrophil, Eosinophil, Basophil, Lymphocyte and Monocyte using features that pathologists consider to differentiate leukocytes. Features contain color, geometric and texture features. Colors of nucleus and cytoplasm vary among the leukocytes. Lymphocytes have single, large, round or oval and Monocytes have singular convoluted shape nucleus. Nucleus of Eosinophils is divided into 2 segments and nucleus of Neutrophils into 2 to 5 segments. Lymphocytes often have no granules, Monocytes have tiny granules, Neutrophils have fine granules and Eosinophils have large granules in cytoplasm. Six color features is extracted from both nucleus and cytoplasm, 6 geometric features only from nucleus and 6 statistical features and 7 moment invariants features only from cytoplasm of leukocytes. These features are fed to support vector machine (SVM) classifiers with one to one architecture. The results obtained by applying the proposed method on blood smear microscopic image of 10 patients including 149 white blood cells (WBCs) indicate that correct rate for all classifiers are above 93% which is in a higher level in comparison with previous literatures.

Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers

NASA Astrophysics Data System (ADS)

Weinmann, Martin; Jutzi, Boris; Hinz, Stefan; Mallet, Clément

2015-07-01

3D scene analysis in terms of automatically assigning 3D points a respective semantic label has become a topic of great importance in photogrammetry, remote sensing, computer vision and robotics. In this paper, we address the issue of how to increase the distinctiveness of geometric features and select the most relevant ones among these for 3D scene analysis. We present a new, fully automated and versatile framework composed of four components: (i) neighborhood selection, (ii) feature extraction, (iii) feature selection and (iv) classification. For each component, we consider a variety of approaches which allow applicability in terms of simplicity, efficiency and reproducibility, so that end-users can easily apply the different components and do not require expert knowledge in the respective domains. In a detailed evaluation involving 7 neighborhood definitions, 21 geometric features, 7 approaches for feature selection, 10 classifiers and 2 benchmark datasets, we demonstrate that the selection of optimal neighborhoods for individual 3D points significantly improves the results of 3D scene analysis. Additionally, we show that the selection of adequate feature subsets may even further increase the quality of the derived results while significantly reducing both processing time and memory consumption.

D Reconstruction-Reverse Engineering - Digital Fabrication of the Egyptian Palermo Stone Using by Smartphone and Light Structured Scanner

NASA Astrophysics Data System (ADS)

Di Paola, F.; Inzerillo, L.

2018-05-01

This paper presents a pipeline that has been developed to acquire a shape with particular features both under the geometric and radiometric aspects. In fact, the challenge was to build a 3D model of the black Stone of Palermo, where the oldest Egyptian history was printed with the use of hieroglyphs. The dark colour of the material and the superficiality of the hieroglyphs' groove have made the acquisition process very complex to the point of having to experiment with a pipeline that allows the structured light scanner not to lose the homologous points in the 3D alignment phase. For the texture reconstruction we used a last generation smartphone.

Analytical study of sandwich structures using Euler-Bernoulli beam equation

NASA Astrophysics Data System (ADS)

Xue, Hui; Khawaja, H.

2017-01-01

This paper presents an analytical study of sandwich structures. In this study, the Euler-Bernoulli beam equation is solved analytically for a four-point bending problem. Appropriate initial and boundary conditions are specified to enclose the problem. In addition, the balance coefficient is calculated and the Rule of Mixtures is applied. The focus of this study is to determine the effective material properties and geometric features such as the moment of inertia of a sandwich beam. The effective parameters help in the development of a generic analytical correlation for complex sandwich structures from the perspective of four-point bending calculations. The main outcomes of these analytical calculations are the lateral displacements and longitudinal stresses for each particular material in the sandwich structure.

Velocity Measurements in Nasal Cavities by Means of Stereoscopic Piv - Preliminary Tests

NASA Astrophysics Data System (ADS)

Cozzi, Fabio; Felisati, Giovanni; Quadrio, Maurizio

2017-08-01

The prediction of detailed flow patterns in human nasal cavities using computational fluid dynamics (CFD) can provide essential information on the potential relationship between patient-specific geometrical characteristics of the nasal anatomy and health problems, and ultimately led to improved surgery. The complex flow structure and the intricate geometry of the nasal cavities make achieving such goals a challenge for CFD specialists. The need for experimental data to validate and improve the numerical simulations is particularly crucial. To this aim an experimental set-up based on Stereo PIV and a silicon phantom of nasal cavities have been designed and realized at Politecnico di Milano. This work describes the main features and challenges of the set-up along with some preliminary results.

The Data Transfer Kit: A geometric rendezvous-based tool for multiphysics data transfer

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

Slattery, S. R.; Wilson, P. P. H.; Pawlowski, R. P.

2013-07-01

The Data Transfer Kit (DTK) is a software library designed to provide parallel data transfer services for arbitrary physics components based on the concept of geometric rendezvous. The rendezvous algorithm provides a means to geometrically correlate two geometric domains that may be arbitrarily decomposed in a parallel simulation. By repartitioning both domains such that they have the same geometric domain on each parallel process, efficient and load balanced search operations and data transfer can be performed at a desirable algorithmic time complexity with low communication overhead relative to other types of mapping algorithms. With the increased development efforts in multiphysicsmore » simulation and other multiple mesh and geometry problems, generating parallel topology maps for transferring fields and other data between geometric domains is a common operation. The algorithms used to generate parallel topology maps based on the concept of geometric rendezvous as implemented in DTK are described with an example using a conjugate heat transfer calculation and thermal coupling with a neutronics code. In addition, we provide the results of initial scaling studies performed on the Jaguar Cray XK6 system at Oak Ridge National Laboratory for a worse-case-scenario problem in terms of algorithmic complexity that shows good scaling on 0(1 x 104) cores for topology map generation and excellent scaling on 0(1 x 105) cores for the data transfer operation with meshes of O(1 x 109) elements. (authors)« less

An engineering, multiscale constitutive model for fiber-forming collagen in tension.

PubMed

Annovazzi, Lorella; Genna, Francesco

2010-01-01

This work proposes a nonlinear constitutive model for a single collagen fiber. Fiber-forming collagen can exhibit different hierarchies of basic units, called fascicles, bundles, fibrils, microfibrils, and so forth, down to the molecular (tropocollagen) level. Exploiting the fact that at each hierarchy level the microstructure can be seen, at least approximately, as that of a wavy, or crimped, extensible cable, the proposed stress-strain model considers a given number of levels, each of which contributes to the overall mechanical behavior according to its own geometrical features (crimp, or waviness), as well as to the basic mechanical properties of the tropocollagen. The crimp features at all levels are assumed to be random variables, whose statistical integration furnishes a stress-strain curve for a collagen fiber. The soundness of this model-the first, to the Authors' knowledge, to treat a single collagen fiber as a microstructured nonlinear structural element-is checked by its application to collagen fibers for which experimental results are available: rat tail tendon, periodontal ligament, and engineered ones. Here, no attempt is made to obtain a stress-strain law for generic collagenous tissues, which exhibit specific features, often much more complex than those of a single fiber. However, it is trivial to observe that the availability of a sound, microstructurally based constitutive law for a single collagen fiber (but applicable at any sub-level, or to any other material with a similar microstructure) is essential for assembling complex constitutive models for any collagenous fibrous tissue.

Functional constraints on tooth morphology in carnivorous mammals

PubMed Central

2012-01-01

Background The range of potential morphologies resulting from evolution is limited by complex interacting processes, ranging from development to function. Quantifying these interactions is important for understanding adaptation and convergent evolution. Using three-dimensional reconstructions of carnivoran and dasyuromorph tooth rows, we compared statistical models of the relationship between tooth row shape and the opposing tooth row, a static feature, as well as measures of mandibular motion during chewing (occlusion), which are kinetic features. This is a new approach to quantifying functional integration because we use measures of movement and displacement, such as the amount the mandible translates laterally during occlusion, as opposed to conventional morphological measures, such as mandible length and geometric landmarks. By sampling two distantly related groups of ecologically similar mammals, we study carnivorous mammals in general rather than a specific group of mammals. Results Statistical model comparisons demonstrate that the best performing models always include some measure of mandibular motion, indicating that functional and statistical models of tooth shape as purely a function of the opposing tooth row are too simple and that increased model complexity provides a better understanding of tooth form. The predictors of the best performing models always included the opposing tooth row shape and a relative linear measure of mandibular motion. Conclusions Our results provide quantitative support of long-standing hypotheses of tooth row shape as being influenced by mandibular motion in addition to the opposing tooth row. Additionally, this study illustrates the utility and necessity of including kinetic features in analyses of morphological integration. PMID:22899809

Interface projection techniques for fluid-structure interaction modeling with moving-mesh methods

NASA Astrophysics Data System (ADS)

Tezduyar, Tayfun E.; Sathe, Sunil; Pausewang, Jason; Schwaab, Matthew; Christopher, Jason; Crabtree, Jason

2008-12-01

The stabilized space-time fluid-structure interaction (SSTFSI) technique developed by the Team for Advanced Flow Simulation and Modeling (T★AFSM) was applied to a number of 3D examples, including arterial fluid mechanics and parachute aerodynamics. Here we focus on the interface projection techniques that were developed as supplementary methods targeting the computational challenges associated with the geometric complexities of the fluid-structure interface. Although these supplementary techniques were developed in conjunction with the SSTFSI method and in the context of air-fabric interactions, they can also be used in conjunction with other moving-mesh methods, such as the Arbitrary Lagrangian-Eulerian (ALE) method, and in the context of other classes of FSI applications. The supplementary techniques currently consist of using split nodal values for pressure at the edges of the fabric and incompatible meshes at the air-fabric interfaces, the FSI Geometric Smoothing Technique (FSI-GST), and the Homogenized Modeling of Geometric Porosity (HMGP). Using split nodal values for pressure at the edges and incompatible meshes at the interfaces stabilizes the structural response at the edges of the membrane used in modeling the fabric. With the FSI-GST, the fluid mechanics mesh is sheltered from the consequences of the geometric complexity of the structure. With the HMGP, we bypass the intractable complexities of the geometric porosity by approximating it with an “equivalent”, locally-varying fabric porosity. As test cases demonstrating how the interface projection techniques work, we compute the air-fabric interactions of windsocks, sails and ringsail parachutes.

Non-rigid Reconstruction of Casting Process with Temperature Feature

NASA Astrophysics Data System (ADS)

Lin, Jinhua; Wang, Yanjie; Li, Xin; Wang, Ying; Wang, Lu

2017-09-01

Off-line reconstruction of rigid scene has made a great progress in the past decade. However, the on-line reconstruction of non-rigid scene is still a very challenging task. The casting process is a non-rigid reconstruction problem, it is a high-dynamic molding process lacking of geometric features. In order to reconstruct the casting process robustly, an on-line fusion strategy is proposed for dynamic reconstruction of casting process. Firstly, the geometric and flowing feature of casting are parameterized in manner of TSDF (truncated signed distance field) which is a volumetric block, parameterized casting guarantees real-time tracking and optimal deformation of casting process. Secondly, data structure of the volume grid is extended to have temperature value, the temperature interpolation function is build to generate the temperature of each voxel. This data structure allows for dynamic tracking of temperature of casting during deformation stages. Then, the sparse RGB features is extracted from casting scene to search correspondence between geometric representation and depth constraint. The extracted color data guarantees robust tracking of flowing motion of casting. Finally, the optimal deformation of the target space is transformed into a nonlinear regular variational optimization problem. This optimization step achieves smooth and optimal deformation of casting process. The experimental results show that the proposed method can reconstruct the casting process robustly and reduce drift in the process of non-rigid reconstruction of casting.

a New Paradigm for Matching - and Aerial Images

NASA Astrophysics Data System (ADS)

Koch, T.; Zhuo, X.; Reinartz, P.; Fraundorfer, F.

2016-06-01

This paper investigates the performance of SIFT-based image matching regarding large differences in image scaling and rotation, as this is usually the case when trying to match images captured from UAVs and airplanes. This task represents an essential step for image registration and 3d-reconstruction applications. Various real world examples presented in this paper show that SIFT, as well as A-SIFT perform poorly or even fail in this matching scenario. Even if the scale difference in the images is known and eliminated beforehand, the matching performance suffers from too few feature point detections, ambiguous feature point orientations and rejection of many correct matches when applying the ratio-test afterwards. Therefore, a new feature matching method is provided that overcomes these problems and offers thousands of matches by a novel feature point detection strategy, applying a one-to-many matching scheme and substitute the ratio-test by adding geometric constraints to achieve geometric correct matches at repetitive image regions. This method is designed for matching almost nadir-directed images with low scene depth, as this is typical in UAV and aerial image matching scenarios. We tested the proposed method on different real world image pairs. While standard SIFT failed for most of the datasets, plenty of geometrical correct matches could be found using our approach. Comparing the estimated fundamental matrices and homographies with ground-truth solutions, mean errors of few pixels can be achieved.

Geometric Structure-Preserving Discretization Schemes for Nonlinear Elasticity

DTIC Science & Technology

2015-08-13

conditions. 15.  SUBJECT TERMS geometric theory for nonlinear elasticity, discrete exterior calculus 16.  SECURITY CLASSIFICATION OF: 17.  LIMITATION...associated Laplacian. We use the general theory for approximation of Hilbert complexes and the finite element exterior calculus and introduce some stable mixed

Pragmatic geometric model evaluation

NASA Astrophysics Data System (ADS)

Pamer, Robert

2015-04-01

Quantification of subsurface model reliability is mathematically and technically demanding as there are many different sources of uncertainty and some of the factors can be assessed merely in a subjective way. For many practical applications in industry or risk assessment (e. g. geothermal drilling) a quantitative estimation of possible geometric variations in depth unit is preferred over relative numbers because of cost calculations for different scenarios. The talk gives an overview of several factors that affect the geometry of structural subsurface models that are based upon typical geological survey organization (GSO) data like geological maps, borehole data and conceptually driven construction of subsurface elements (e. g. fault network). Within the context of the trans-European project "GeoMol" uncertainty analysis has to be very pragmatic also because of different data rights, data policies and modelling software between the project partners. In a case study a two-step evaluation methodology for geometric subsurface model uncertainty is being developed. In a first step several models of the same volume of interest have been calculated by omitting successively more and more input data types (seismic constraints, fault network, outcrop data). The positions of the various horizon surfaces are then compared. The procedure is equivalent to comparing data of various levels of detail and therefore structural complexity. This gives a measure of the structural significance of each data set in space and as a consequence areas of geometric complexity are identified. These areas are usually very data sensitive hence geometric variability in between individual data points in these areas is higher than in areas of low structural complexity. Instead of calculating a multitude of different models by varying some input data or parameters as it is done by Monte-Carlo-simulations, the aim of the second step of the evaluation procedure (which is part of the ongoing work) is to calculate basically two model variations that can be seen as geometric extremes of all available input data. This does not lead to a probability distribution for the spatial position of geometric elements but it defines zones of major (or minor resp.) geometric variations due to data uncertainty. Both model evaluations are then analyzed together to give ranges of possible model outcomes in metric units.

Real-Time Correction By Optical Tracking with Integrated Geometric Distortion Correction for Reducing Motion Artifacts in fMRI

NASA Astrophysics Data System (ADS)

Rotenberg, David J.

Artifacts caused by head motion are a substantial source of error in fMRI that limits its use in neuroscience research and clinical settings. Real-time scan-plane correction by optical tracking has been shown to correct slice misalignment and non-linear spin-history artifacts, however residual artifacts due to dynamic magnetic field non-uniformity may remain in the data. A recently developed correction technique, PLACE, can correct for absolute geometric distortion using the complex image data from two EPI images, with slightly shifted k-space trajectories. We present a correction approach that integrates PLACE into a real-time scan-plane update system by optical tracking, applied to a tissue-equivalent phantom undergoing complex motion and an fMRI finger tapping experiment with overt head motion to induce dynamic field non-uniformity. Experiments suggest that including volume by volume geometric distortion correction by PLACE can suppress dynamic geometric distortion artifacts in a phantom and in vivo and provide more robust activation maps.

Formulation of dynamical theory of X-ray diffraction for perfect crystals in the Laue case using the Riemann surface.

PubMed

Saka, Takashi

2016-05-01

The dynamical theory for perfect crystals in the Laue case was reformulated using the Riemann surface, as used in complex analysis. In the two-beam approximation, each branch of the dispersion surface is specified by one sheet of the Riemann surface. The characteristic features of the dispersion surface are analytically revealed using four parameters, which are the real and imaginary parts of two quantities specifying the degree of departure from the exact Bragg condition and the reflection strength. By representing these parameters on complex planes, these characteristics can be graphically depicted on the Riemann surface. In the conventional case, the absorption is small and the real part of the reflection strength is large, so the formulation is the same as the traditional analysis. However, when the real part of the reflection strength is small or zero, the two branches of the dispersion surface cross, and the dispersion relationship becomes similar to that of the Bragg case. This is because the geometrical relationships among the parameters are similar in both cases. The present analytical method is generally applicable, irrespective of the magnitudes of the parameters. Furthermore, the present method analytically revealed many characteristic features of the dispersion surface and will be quite instructive for further numerical calculations of rocking curves.

Orienting in Virtual Environments: How Are Surface Features and Environmental Geometry Weighted in an Orientation Task?

ERIC Educational Resources Information Center

Kelly, Debbie M.; Bischof, Walter F.

2008-01-01

We investigated how human adults orient in enclosed virtual environments, when discrete landmark information is not available and participants have to rely on geometric and featural information on the environmental surfaces. In contrast to earlier studies, where, for women, the featural information from discrete landmarks overshadowed the encoding…

An Integrative Object-Based Image Analysis Workflow for Uav Images

NASA Astrophysics Data System (ADS)

Yu, Huai; Yan, Tianheng; Yang, Wen; Zheng, Hong

2016-06-01

In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA). More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT) representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC). Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya'an earthquake demonstrate the effectiveness and efficiency of our proposed method.

Strong dependence of rain-induced lidar depolarization on the illumination angle: experimental evidence and geometrical-optics interpretation.

PubMed

Roy, G; Bissonnette, L R

2001-09-20

Backscatter and depolarization lidar measurements from clouds and precipitation are reported as functions of the elevation angle of the pointing lidar direction. We recorded the data by scanning the lidar beam (Nd:YAG) at a constant angular speed of ~3.5 degrees /s while operating at a repetition rate of 10 Hz. We show that in rain there is an evident and at times spectacular dependence on the elevation angle. That dependence appears to be sensitive to raindrop size. We have developed a three-dimensional polarization-dependent ray-tracing algorithm to calculate the backscatter and the depolarization ratio by large nonspherical droplets. We have applied it to raindrop shapes derived from existing static and dynamic (oscillating) models. We show that many of the observed complex backscatter and depolarization features can be interpreted to a good extent by geometrical optics. These results suggest that there is a definite need for more extensive calculations of the scattering phase matrix elements for large deformed raindrops as functions of the direction of illumination. Obvious applications are retrieval of information on the liquid-solid phase of precipitation and on the size and the vibration state of raindrops.

Xpatch prediction improvements to support multiple ATR applications

NASA Astrophysics Data System (ADS)

Andersh, Dennis J.; Lee, Shung W.; Moore, John T.; Sullivan, Douglas P.; Hughes, Jeff A.; Ling, Hao

1998-08-01

This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time-domain signature sand synthetic aperture radar (SAR) images of realistic 3D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, IGES curved surfaces, or solid geometries.The computer code, Xpatch, based on the shooting-and-bouncing-ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. Xpatch computers the first- bounce physical optics (PO) plus the physical theory of diffraction (PTD) contributions. Xpatch calculates the multi-bounce ray contributions by using geometric optics and PO for complex vehicles with materials. It has been found that the multi-bounce calculations, the radar return in typically 10 to 15 dB too low. Examples of predicted range profiles, SAR, imagery, and RCS for several different geometries are compared with measured data to demonstrate the quality of the predictions. Recent enhancements to Xpatch include improvements for millimeter wave applications and hybridization with finite element method for small geometric features and augmentation of additional IGES entities to support trimmed and untrimmed surfaces.

Analytic Expression of Geometric Discord in Arbitrary Mixture of any Two Bi-qubit Product Pure States

NASA Astrophysics Data System (ADS)

Xie, Chuan-Mei; Liu, Yi-Min; Xing, Hang; Zhang, Zhan-Jun

2015-04-01

Quantum correlations in a family of states comprising any mixture of a pair of arbitrary bi-qubit product pure states are studied by employing geometric discord [Phys. Rev. Lett. 105 (2010) 190502] as the quantifier. First, the inherent symmetry in the family of states about local unitary transformations is revealed. Then, the analytic expression of geometric discords in the states is worked out. Some concrete discussions and analyses on the captured geometric discords are made so that their distinct features are exposed. It is found that, the more averagely the two bi-qubit product states are mixed, the bigger geometric discord the mixed state owns. Moreover, the monotonic relationships of geometric discord with different parameters are revealed. Supported by the National Natural Science Foundation of China (NNSFC) under Grant Nos. 11375011 and 11372122, the Natural Science Foundation of Anhui Province under Grant No. 1408085MA12, and the 211 Project of Anhui University

Polarization ellipse and Stokes parameters in geometric algebra.

PubMed

Santos, Adler G; Sugon, Quirino M; McNamara, Daniel J

2012-01-01

In this paper, we use geometric algebra to describe the polarization ellipse and Stokes parameters. We show that a solution to Maxwell's equation is a product of a complex basis vector in Jackson and a linear combination of plane wave functions. We convert both the amplitudes and the wave function arguments from complex scalars to complex vectors. This conversion allows us to separate the electric field vector and the imaginary magnetic field vector, because exponentials of imaginary scalars convert vectors to imaginary vectors and vice versa, while exponentials of imaginary vectors only rotate the vector or imaginary vector they are multiplied to. We convert this expression for polarized light into two other representations: the Cartesian representation and the rotated ellipse representation. We compute the conversion relations among the representation parameters and their corresponding Stokes parameters. And finally, we propose a set of geometric relations between the electric and magnetic fields that satisfy an equation similar to the Poincaré sphere equation.

Analysis of geometric moments as features for firearm identification.

PubMed

Md Ghani, Nor Azura; Liong, Choong-Yeun; Jemain, Abdul Aziz

2010-05-20

The task of identifying firearms from forensic ballistics specimens is exacting in crime investigation since the last two decades. Every firearm, regardless of its size, make and model, has its own unique 'fingerprint'. These fingerprints transfer when a firearm is fired to the fired bullet and cartridge case. The components that are involved in producing these unique characteristics are the firing chamber, breech face, firing pin, ejector, extractor and the rifling of the barrel. These unique characteristics are the critical features in identifying firearms. It allows investigators to decide on which particular firearm that has fired the bullet. Traditionally the comparison of ballistic evidence has been a tedious and time-consuming process requiring highly skilled examiners. Therefore, the main objective of this study is the extraction and identification of suitable features from firing pin impression of cartridge case images for firearm recognition. Some previous studies have shown that firing pin impression of cartridge case is one of the most important characteristics used for identifying an individual firearm. In this study, data are gathered using 747 cartridge case images captured from five different pistols of type 9mm Parabellum Vektor SP1, made in South Africa. All the images of the cartridge cases are then segmented into three regions, forming three different set of images, i.e. firing pin impression image, centre of firing pin impression image and ring of firing pin impression image. Then geometric moments up to the sixth order were generated from each part of the images to form a set of numerical features. These 48 features were found to be significantly different using the MANOVA test. This high dimension of features is then reduced into only 11 significant features using correlation analysis. Classification results using cross-validation under discriminant analysis show that 96.7% of the images were classified correctly. These results demonstrate the value of geometric moments technique for producing a set of numerical features, based on which the identification of firearms are made.

Electromagnetic backscattering by corner reflectors

NASA Technical Reports Server (NTRS)

Balanis, C. A.; Griesser, T.

1986-01-01

The Geometrical Theory of Diffraction (GTD), which supplements Geometric Optics (GO), and the Physical Theory of Diffraction (PTD), which supplements Physical Optics (PO), are used to predict the backscatter cross sections of dihedral corner reflectors which have right, obtuse, or acute included angles. These theories allow individual backscattering mechanisms of the dihedral corner reflectors to be identified and provide good agreement with experimental results in the azimuthal plane. The advantages and disadvantages of the geometrical and physical theories are discussed in terms of their accuracy, usefulness, and complexity. Numerous comparisons of analytical results with experimental data are presented. While physical optics alone is more accurate and more useful than geometrical optics alone, the combination of geometrical optics and geometrical diffraction seems to out perform physical optics and physical diffraction when compared with experimental data, especially for acute angle dihedral corner reflectors.

Geometric Heat Engines Featuring Power that Grows with Efficiency.

PubMed

Raz, O; Subaşı, Y; Pugatch, R

2016-04-22

Thermodynamics places a limit on the efficiency of heat engines, but not on their output power or on how the power and efficiency change with the engine's cycle time. In this Letter, we develop a geometrical description of the power and efficiency as a function of the cycle time, applicable to an important class of heat engine models. This geometrical description is used to design engine protocols that attain both the maximal power and maximal efficiency at the fast driving limit. Furthermore, using this method, we also prove that no protocol can exactly attain the Carnot efficiency at nonzero power.

Towards an information geometric characterization/classification of complex systems. I. Use of generalized entropies

NASA Astrophysics Data System (ADS)

Ghikas, Demetris P. K.; Oikonomou, Fotios D.

2018-04-01

Using the generalized entropies which depend on two parameters we propose a set of quantitative characteristics derived from the Information Geometry based on these entropies. Our aim, at this stage, is to construct first some fundamental geometric objects which will be used in the development of our geometrical framework. We first establish the existence of a two-parameter family of probability distributions. Then using this family we derive the associated metric and we state a generalized Cramer-Rao Inequality. This gives a first two-parameter classification of complex systems. Finally computing the scalar curvature of the information manifold we obtain a further discrimination of the corresponding classes. Our analysis is based on the two-parameter family of generalized entropies of Hanel and Thurner (2011).

Comparative study of palm print authentication system using geometric features

NASA Astrophysics Data System (ADS)

Shreyas, Kamath K. M.; Rajeev, Srijith; Panetta, Karen; Agaian, Sos S.

2017-05-01

Biometrics, particularly palm print authentication has been a stimulating research area due to its abundance of features. Stable features and effective matching are the most crucial steps for an authentication system. In conventional palm print authentication systems, matching is based on flexion creases, friction ridges, and minutiae points. Currently, contactless palm print imaging is an emerging technology. However, they tend to involve fluctuations in the image quality and texture loss due to factors such as varying illumination conditions, occlusions, noise, pose, and ghosting. These variations decrease the performance of the authentication systems. Furthermore, real-time palm print authentication in large databases continue to be a challenging task. In order to effectively solve these problems, features which are invariant to these anomalies are required. This paper proposes a robust palm print matching framework by making a comparative study of different local geometric features such as Difference-of-Gaussian, Hessian, Hessian-Laplace, Harris-Laplace, and Multiscale Harris for feature detection. These detectors are coupled with Scale Invariant Feature Transformation (SIFT) descriptor to describe the identified features. Additionally, a two-stage refinement process is carried out to obtain the best stable matches. Computer simulations demonstrate that the accuracy of the system has increased effectively with an EER of 0.86% when Harris-Laplace detector is used on IITD database.

Complexity and approximability for a problem of intersecting of proximity graphs with minimum number of equal disks

NASA Astrophysics Data System (ADS)

Kobylkin, Konstantin

2016-10-01

Computational complexity and approximability are studied for the problem of intersecting of a set of straight line segments with the smallest cardinality set of disks of fixed radii r > 0 where the set of segments forms straight line embedding of possibly non-planar geometric graph. This problem arises in physical network security analysis for telecommunication, wireless and road networks represented by specific geometric graphs defined by Euclidean distances between their vertices (proximity graphs). It can be formulated in a form of known Hitting Set problem over a set of Euclidean r-neighbourhoods of segments. Being of interest computational complexity and approximability of Hitting Set over so structured sets of geometric objects did not get much focus in the literature. Strong NP-hardness of the problem is reported over special classes of proximity graphs namely of Delaunay triangulations, some of their connected subgraphs, half-θ6 graphs and non-planar unit disk graphs as well as APX-hardness is given for non-planar geometric graphs at different scales of r with respect to the longest graph edge length. Simple constant factor approximation algorithm is presented for the case where r is at the same scale as the longest edge length.

Characterization and Biomimcry of Avian Nanostructured Tissues

DTIC Science & Technology

2016-01-19

keratin cortex (Maia et al. 2011) at the outer edge of barbs from TEM images. Geometric morphometrics of barb shape Digitized images of the barb thin...morphological measurements (all P > 0.05; Figure 4C; Table S2). Gloss and Barb Geometric Morphometrics Matte and glossy barbs differed significantly in...barbs and lack of multiple, clear anatomically homologous features, traditional landmark based morphometric techniques (Bookstein, 1982) would be

Analytical close-form solutions to the elastic fields of solids with dislocations and surface stress

NASA Astrophysics Data System (ADS)

Ye, Wei; Paliwal, Bhasker; Ougazzaden, Abdallah; Cherkaoui, Mohammed

2013-07-01

The concept of eigenstrain is adopted to derive a general analytical framework to solve the elastic field for 3D anisotropic solids with general defects by considering the surface stress. The formulation shows the elastic constants and geometrical features of the surface play an important role in determining the elastic fields of the solid. As an application, the analytical close-form solutions to the stress fields of an infinite isotropic circular nanowire are obtained. The stress fields are compared with the classical solutions and those of complex variable method. The stress fields from this work demonstrate the impact from the surface stress when the size of the nanowire shrinks but becomes negligible in macroscopic scale. Compared with the power series solutions of complex variable method, the analytical solutions in this work provide a better platform and they are more flexible in various applications. More importantly, the proposed analytical framework profoundly improves the studies of general 3D anisotropic materials with surface effects.

Graph Curvature for Differentiating Cancer Networks

PubMed Central

Sandhu, Romeil; Georgiou, Tryphon; Reznik, Ed; Zhu, Liangjia; Kolesov, Ivan; Senbabaoglu, Yasin; Tannenbaum, Allen

2015-01-01

Cellular interactions can be modeled as complex dynamical systems represented by weighted graphs. The functionality of such networks, including measures of robustness, reliability, performance, and efficiency, are intrinsically tied to the topology and geometry of the underlying graph. Utilizing recently proposed geometric notions of curvature on weighted graphs, we investigate the features of gene co-expression networks derived from large-scale genomic studies of cancer. We find that the curvature of these networks reliably distinguishes between cancer and normal samples, with cancer networks exhibiting higher curvature than their normal counterparts. We establish a quantitative relationship between our findings and prior investigations of network entropy. Furthermore, we demonstrate how our approach yields additional, non-trivial pair-wise (i.e. gene-gene) interactions which may be disrupted in cancer samples. The mathematical formulation of our approach yields an exact solution to calculating pair-wise changes in curvature which was computationally infeasible using prior methods. As such, our findings lay the foundation for an analytical approach to studying complex biological networks. PMID:26169480

Polarization-independent broadband meta-holograms via polarization-dependent nanoholes.

PubMed

Zhang, Xiaohu; Li, Xiong; Jin, Jinjin; Pu, Mingbo; Ma, Xiaoliang; Luo, Jun; Guo, Yinghui; Wang, Changtao; Luo, Xiangang

2018-05-17

Composed of ultrathin metal or dielectric nanostructures, metasurfaces can manipulate the phase, amplitude and polarization of electromagnetic waves at a subwavelength scale, which is promising for flat optical devices. In general, metasurfaces composed of space-variant anisotropic units are sensitive to the incident polarization due to the inherent polarization dependent geometric phase. Here, we implement polarization-independent broadband metasurface holograms constructed by polarization-dependent anisotropic elliptical nanoholes by elaborate design of complex amplitude holograms. The fabricated meta-hologram exhibits a polarization insensitive feature with an acceptable image quality. We verify the feasibility of the design algorithm for three-dimensional (3D) meta-holograms with simulation and the feasibility for two-dimensional (2D) meta-holograms is experimentally demonstrated at a broadband wavelength range from 405 nm to 632.8 nm. The effective polarization-independent broadband complex wavefront control with anisotropic elliptical nanoholes proposed in this paper greatly promotes the practical applications of the metasurface in technologies associated with wavefront manipulation, such as flat lens, colorful holographic displays and optical storage.

THE ROLE OF THE HIPPOCAMPUS IN OBJECT DISCRIMINATION BASED ON VISUAL FEATURES.

PubMed

Levcik, David; Nekovarova, Tereza; Antosova, Eliska; Stuchlik, Ales; Klement, Daniel

2018-06-07

The role of rodent hippocampus has been intensively studied in different cognitive tasks. However, its role in discrimination of objects remains controversial due to conflicting findings. We tested whether the number and type of features available for the identification of objects might affect the strategy (hippocampal-independent vs. hippocampal-dependent) that rats adopt to solve object discrimination tasks. We trained rats to discriminate 2D visual objects presented on a computer screen. The objects were defined either by their shape only or by multiple-features (a combination of filling pattern and brightness in addition to the shape). Our data showed that objects displayed as simple geometric shapes are not discriminated by trained rats after their hippocampi had been bilaterally inactivated by the GABA A -agonist muscimol. On the other hand, objects containing a specific combination of non-geometric features in addition to the shape are discriminated even without the hippocampus. Our results suggest that the involvement of the hippocampus in visual object discrimination depends on the abundance of object's features. Copyright © 2018. Published by Elsevier Inc.

Effects of lung disease on the three-dimensional structure and air flow pattern in the human airway tree

NASA Astrophysics Data System (ADS)

van de Moortele, Tristan; Nemes, Andras; Wendt, Christine; Coletti, Filippo

2016-11-01

The morphological features of the airway tree directly affect the air flow features during breathing, which determines the gas exchange and inhaled particle transport. Lung disease, Chronic Obstructive Pulmonary Disease (COPD) in this study, affects the structural features of the lungs, which in turn negatively affects the air flow through the airways. Here bronchial tree air volume geometries are segmented from Computed Tomography (CT) scans of healthy and diseased subjects. Geometrical analysis of the airway centerlines and corresponding cross-sectional areas provide insight into the specific effects of COPD on the airway structure. These geometries are also used to 3D print anatomically accurate, patient specific flow models. Three-component, three-dimensional velocity fields within these models are acquired using Magnetic Resonance Imaging (MRI). The three-dimensional flow fields provide insight into the change in flow patterns and features. Additionally, particle trajectories are determined using the velocity fields, to identify the fate of therapeutic and harmful inhaled aerosols. Correlation between disease-specific and patient-specific anatomical features with dysfunctional airflow patterns can be achieved by combining geometrical and flow analysis.

Identification and evaluation of the cost-effectiveness of highway design features to reduce nonrecurrent congestion.

DOT National Transportation Integrated Search

2014-01-01

This research report presents the findings on the identification and evaluation of the use of highway geometric design features on freeways to reduce nonrecurrent congestion and improve travel time reliability. General guidance is provided on the ran...

Efficient processing of fluorescence images using directional multiscale representations.

PubMed

Labate, D; Laezza, F; Negi, P; Ozcan, B; Papadakis, M

2014-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data.

Efficient processing of fluorescence images using directional multiscale representations

PubMed Central

Labate, D.; Laezza, F.; Negi, P.; Ozcan, B.; Papadakis, M.

2017-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data. PMID:28804225

Medical Image Fusion Based on Feature Extraction and Sparse Representation

PubMed Central

Wei, Gao; Zongxi, Song

2017-01-01

As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information. SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. The decision map is added to the normal sparse representation based method to improve the speed of the algorithm. Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images. The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods. PMID:28321246

Predicting DNA binding proteins using support vector machine with hybrid fractal features.

PubMed

Niu, Xiao-Hui; Hu, Xue-Hai; Shi, Feng; Xia, Jing-Bo

2014-02-21

DNA-binding proteins play a vitally important role in many biological processes. Prediction of DNA-binding proteins from amino acid sequence is a significant but not fairly resolved scientific problem. Chaos game representation (CGR) investigates the patterns hidden in protein sequences, and visually reveals previously unknown structure. Fractal dimensions (FD) are good tools to measure sizes of complex, highly irregular geometric objects. In order to extract the intrinsic correlation with DNA-binding property from protein sequences, CGR algorithm, fractal dimension and amino acid composition are applied to formulate the numerical features of protein samples in this paper. Seven groups of features are extracted, which can be computed directly from the primary sequence, and each group is evaluated by the 10-fold cross-validation test and Jackknife test. Comparing the results of numerical experiments, the group of amino acid composition and fractal dimension (21-dimension vector) gets the best result, the average accuracy is 81.82% and average Matthew's correlation coefficient (MCC) is 0.6017. This resulting predictor is also compared with existing method DNA-Prot and shows better performances. © 2013 The Authors. Published by Elsevier Ltd All rights reserved.

Decompositions of the polyhedral product functor with applications to moment-angle complexes and related spaces

PubMed Central

Bahri, A.; Bendersky, M.; Cohen, F. R.; Gitler, S.

2009-01-01

This article gives a natural decomposition of the suspension of a generalized moment-angle complex or partial product space which arises as the polyhedral product functor described below. The introduction and application of the smash product moment-angle complex provides a precise identification of the stable homotopy type of the values of the polyhedral product functor. One direct consequence is an analysis of the associated cohomology. For the special case of the complements of certain subspace arrangements, the geometrical decomposition implies the homological decomposition in earlier work of others as described below. Because the splitting is geometric, an analogous homological decomposition for a generalized moment-angle complex applies for any homology theory. Implied, therefore, is a decomposition for the Stanley–Reisner ring of a finite simplicial complex, and natural generalizations. PMID:19620727

Decompositions of the polyhedral product functor with applications to moment-angle complexes and related spaces.

PubMed

Bahri, A; Bendersky, M; Cohen, F R; Gitler, S

2009-07-28

This article gives a natural decomposition of the suspension of a generalized moment-angle complex or partial product space which arises as the polyhedral product functor described below. The introduction and application of the smash product moment-angle complex provides a precise identification of the stable homotopy type of the values of the polyhedral product functor. One direct consequence is an analysis of the associated cohomology. For the special case of the complements of certain subspace arrangements, the geometrical decomposition implies the homological decomposition in earlier work of others as described below. Because the splitting is geometric, an analogous homological decomposition for a generalized moment-angle complex applies for any homology theory. Implied, therefore, is a decomposition for the Stanley-Reisner ring of a finite simplicial complex, and natural generalizations.

Universal properties of knotted polymer rings.

PubMed

Baiesi, M; Orlandini, E

2012-09-01

By performing Monte Carlo sampling of N-steps self-avoiding polygons embedded on different Bravais lattices we explore the robustness of universality in the entropic, metric, and geometrical properties of knotted polymer rings. In particular, by simulating polygons with N up to 10(5) we furnish a sharp estimate of the asymptotic values of the knot probability ratios and show their independence on the lattice type. This universal feature was previously suggested, although with different estimates of the asymptotic values. In addition, we show that the scaling behavior of the mean-squared radius of gyration of polygons depends on their knot type only through its correction to scaling. Finally, as a measure of the geometrical self-entanglement of the self-avoiding polygons we consider the standard deviation of the writhe distribution and estimate its power-law behavior in the large N limit. The estimates of the power exponent do depend neither on the lattice nor on the knot type, strongly supporting an extension of the universality property to some features of the geometrical entanglement.

Structural and mechanical features of the order-disorder transition in experimental hard-sphere packings

NASA Astrophysics Data System (ADS)

Hanifpour, M.; Francois, N.; Robins, V.; Kingston, A.; Vaez Allaei, S. M.; Saadatfar, M.

2015-06-01

Here we present an experimental and numerical investigation on the grain-scale geometrical and mechanical properties of partially crystallized structures made of macroscopic frictional grains. Crystallization is inevitable in arrangements of monosized hard spheres with packing densities exceeding Bernal's limiting density ϕBernal≈0.64 . We study packings of monosized hard spheres whose density spans over a wide range (0.59 <ϕ <0.72 ) . These experiments harness x-ray computed tomography, three-dimensional image analysis, and numerical simulations to access precisely the geometry and the 3D structure of internal forces within the sphere packings. We show that clear geometrical transitions coincide with modifications of the mechanical backbone of the packing both at the grain and global scale. Notably, two transitions are identified at ϕBernal≈0.64 and ϕc≈0.68 . These results provide insights on how geometrical and mechanical features at the grain scale conspire to yield partially crystallized structures that are mechanically stable.

The geometric preference subtype in ASD: identifying a consistent, early-emerging phenomenon through eye tracking.

PubMed

Moore, Adrienne; Wozniak, Madeline; Yousef, Andrew; Barnes, Cindy Carter; Cha, Debra; Courchesne, Eric; Pierce, Karen

2018-01-01

The wide range of ability and disability in ASD creates a need for tools that parse the phenotypic heterogeneity into meaningful subtypes. Using eye tracking, our past studies revealed that when presented with social and geometric images, a subset of ASD toddlers preferred viewing geometric images, and these toddlers also had greater symptom severity than ASD toddlers with greater social attention. This study tests whether this "GeoPref test" effect would generalize across different social stimuli. Two hundred and twenty-seven toddlers (76 ASD) watched a 90-s video, the Complex Social GeoPref test, of dynamic geometric images paired with social images of children interacting and moving. Proportion of visual fixation time and number of saccades per second to both images were calculated. To allow for cross-paradigm comparisons, a subset of 126 toddlers also participated in the original GeoPref test. Measures of cognitive and social functioning (MSEL, ADOS, VABS) were collected and related to eye tracking data. To examine utility as a diagnostic indicator to detect ASD toddlers, validation statistics (e.g., sensitivity, specificity, ROC, AUC) were calculated for the Complex Social GeoPref test alone and when combined with the original GeoPref test. ASD toddlers spent a significantly greater amount of time viewing geometric images than any other diagnostic group. Fixation patterns from ASD toddlers who participated in both tests revealed a significant correlation, supporting the idea that these tests identify a phenotypically meaningful ASD subgroup. Combined use of both original and Complex Social GeoPref tests identified a subgroup of about 1 in 3 ASD toddlers from the "GeoPref" subtype (sensitivity 35%, specificity 94%, AUC 0.75.) Replicating our previous studies, more time looking at geometric images was associated with significantly greater ADOS symptom severity. Regardless of the complexity of the social images used (low in the original GeoPref test vs high in the new Complex Social GeoPref test), eye tracking of toddlers can accurately identify a specific ASD "GeoPref" subtype with elevated symptom severity. The GeoPref tests are predictive of ASD at the individual subject level and thus potentially useful for various clinical applications (e.g., early identification, prognosis, or development of subtype-specific treatments).

Constraining geostatistical models with hydrological data to improve prediction realism

NASA Astrophysics Data System (ADS)

Demyanov, V.; Rojas, T.; Christie, M.; Arnold, D.

2012-04-01

Geostatistical models reproduce spatial correlation based on the available on site data and more general concepts about the modelled patters, e.g. training images. One of the problem of modelling natural systems with geostatistics is in maintaining realism spatial features and so they agree with the physical processes in nature. Tuning the model parameters to the data may lead to geostatistical realisations with unrealistic spatial patterns, which would still honour the data. Such model would result in poor predictions, even though although fit the available data well. Conditioning the model to a wider range of relevant data provide a remedy that avoid producing unrealistic features in spatial models. For instance, there are vast amounts of information about the geometries of river channels that can be used in describing fluvial environment. Relations between the geometrical channel characteristics (width, depth, wave length, amplitude, etc.) are complex and non-parametric and are exhibit a great deal of uncertainty, which is important to propagate rigorously into the predictive model. These relations can be described within a Bayesian approach as multi-dimensional prior probability distributions. We propose a way to constrain multi-point statistics models with intelligent priors obtained from analysing a vast collection of contemporary river patterns based on previously published works. We applied machine learning techniques, namely neural networks and support vector machines, to extract multivariate non-parametric relations between geometrical characteristics of fluvial channels from the available data. An example demonstrates how ensuring geological realism helps to deliver more reliable prediction of a subsurface oil reservoir in a fluvial depositional environment.

Geometric Demonstration of the Fundamental Theorems of the Calculus

ERIC Educational Resources Information Center

Sauerheber, Richard D.

2010-01-01

After the monumental discovery of the fundamental theorems of the calculus nearly 350 years ago, it became possible to answer extremely complex questions regarding the natural world. Here, a straightforward yet profound demonstration, employing geometrically symmetric functions, describes the validity of the general power rules for integration and…

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

Milani, Gabriele, E-mail: milani@stru.polimi.it, E-mail: gabriele.milani@polimi.it; Valente, Marco

This study presents some FE results regarding the behavior under horizontal loads of eight existing masonry towers located in the North-East of Italy. The towers, albeit unique for geometric and architectural features, show some affinities which justify a comparative analysis, as for instance the location and the similar masonry material. Their structural behavior under horizontal loads is therefore influenced by geometrical issues, such as slenderness, walls thickness, perforations, irregularities, presence of internal vaults, etc., all features which may be responsible for a peculiar output. The geometry of the towers is deduced from both existing available documentation and in-situ surveys. Onmore » the basis of such geometrical data, a detailed 3D realistic mesh is conceived, with a point by point characterization of each single geometric element. The FE models are analysed under seismic loads acting along geometric axes of the plan section, both under non-linear static (pushover) and non-linear dynamic excitation assumptions. A damage-plasticity material model exhibiting softening in both tension and compression, already available in the commercial code Abaqus, is used for masonry. Pushover analyses are performed with both G1 and G2 horizontal loads distribution, according to Italian code requirements, along X+/− and Y+/− directions. Non-linear dynamic analyses are performed along both X and Y directions with a real accelerogram scaled to different peak ground accelerations. Some few results are presented in this paper. It is found that the results obtained with pushover analyses reasonably well fit expensive non-linear dynamic simulations, with a slightly less conservative trend.« less

Probability density cloud as a geometrical tool to describe statistics of scattered light.

PubMed

Yaitskova, Natalia

2017-04-01

First-order statistics of scattered light is described using the representation of the probability density cloud, which visualizes a two-dimensional distribution for complex amplitude. The geometric parameters of the cloud are studied in detail and are connected to the statistical properties of phase. The moment-generating function for intensity is obtained in a closed form through these parameters. An example of exponentially modified normal distribution is provided to illustrate the functioning of this geometrical approach.

Quantification of thrombus formation in malapposed coronary stents deployed in vitro through imaging analysis.

PubMed

Brown, Jonathan; O'Brien, Caroline C; Lopes, Augusto C; Kolandaivelu, Kumaran; Edelman, Elazer R

2018-04-11

Stent thrombosis is a major complication of coronary stent and scaffold intervention. While often unanticipated and lethal, its incidence is low making mechanistic examination difficult through clinical investigation alone. Thus, throughout the technological advancement of these devices, experimental models have been indispensable in furthering our understanding of device safety and efficacy. As we refine model systems to gain deeper insight into adverse events, it is equally important that we continue to refine our measurement methods. We used digital signal processing in an established flow loop model to investigate local flow effects due to geometric stent features and ultimately its relationship to thrombus formation. A new metric of clot distribution on each microCT slice termed normalized clot ratio was defined to quantify this distribution. Three under expanded coronary bare-metal stents were run in a flow loop model to induce clotting. Samples were then scanned in a MicroCT machine and digital signal processing methods applied to analyze geometric stent conformation and spatial clot formation. Results indicated that geometric stent features play a significant role in clotting patterns, specifically at a frequency of 0.6225 Hz corresponding to a geometric distance of 1.606 mm. The magnitude-squared coherence between geometric features and clot distribution was greater than 0.4 in all samples. In stents with poor wall apposition, ranging from 0.27 mm to 0.64 mm maximum malapposition (model of real-world heterogeneity), clots were found to have formed in between stent struts rather than directly adjacent to struts. This early work shows how the combination of tools in the areas of image processing and signal analysis can advance the resolution at which we are able to define thrombotic mechanisms in in vitro models, and ultimately, gain further insight into clinical performance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Apparatus for checking dimensions of workpieces

DOEpatents

Possati, Mario; Golinelli, Guido

1992-01-01

An apparatus for checking features of workpieces with rotational symmetry defining a geometrical axis, which includes a base, rest devices fixed to the base for supporting the workpiece with the geometrical axis horizontally arranged, and a support structure coupled to the base for rotation about a horizontal axis. A counterweight and sensor are coupled to the support structure and movable with the support structure from a rest position, allowing loading of the workpiece to be checked onto the rest devices to a working position where the sensor is brought into cooperation with the workpiece. The axis of rotation of the support structure is arranged below the axis of the workpiece, in correspondence to a vertical geometrical plane passing through the workpiece geometric axis when the workpiece is positioned on the rest devices.

Free-form geometric modeling by integrating parametric and implicit PDEs.

PubMed

Du, Haixia; Qin, Hong

2007-01-01

Parametric PDE techniques, which use partial differential equations (PDEs) defined over a 2D or 3D parametric domain to model graphical objects and processes, can unify geometric attributes and functional constraints of the models. PDEs can also model implicit shapes defined by level sets of scalar intensity fields. In this paper, we present an approach that integrates parametric and implicit trivariate PDEs to define geometric solid models containing both geometric information and intensity distribution subject to flexible boundary conditions. The integrated formulation of second-order or fourth-order elliptic PDEs permits designers to manipulate PDE objects of complex geometry and/or arbitrary topology through direct sculpting and free-form modeling. We developed a PDE-based geometric modeling system for shape design and manipulation of PDE objects. The integration of implicit PDEs with parametric geometry offers more general and arbitrary shape blending and free-form modeling for objects with intensity attributes than pure geometric models.

Not so Complex: Iteration in the Complex Plane

ERIC Educational Resources Information Center

O'Dell, Robin S.

2014-01-01

The simple process of iteration can produce complex and beautiful figures. In this article, Robin O'Dell presents a set of tasks requiring students to use the geometric interpretation of complex number multiplication to construct linear iteration rules. When the outputs are plotted in the complex plane, the graphs trace pleasing designs…

Advanced Interactive Display Formats for Terminal Area Traffic Control

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Shaviv, G. E.

1999-01-01

This research project deals with an on-line dynamic method for automated viewing parameter management in perspective displays. Perspective images are optimized such that a human observer will perceive relevant spatial geometrical features with minimal errors. In order to compute the errors at which observers reconstruct spatial features from perspective images, a visual spatial-perception model was formulated. The model was employed as the basis of an optimization scheme aimed at seeking the optimal projection parameter setting. These ideas are implemented in the context of an air traffic control (ATC) application. A concept, referred to as an active display system, was developed. This system uses heuristic rules to identify relevant geometrical features of the three-dimensional air traffic situation. Agile, on-line optimization was achieved by a specially developed and custom-tailored genetic algorithm (GA), which was to deal with the multi-modal characteristics of the objective function and exploit its time-evolving nature.

Internal Gravity Waves: Generation and Breaking Mechanisms by Laboratory Experiments

NASA Astrophysics Data System (ADS)

la Forgia, Giovanni; Adduce, Claudia; Falcini, Federico

2016-04-01

Internal gravity waves (IGWs), occurring within estuaries and the coastal oceans, are manifest as large amplitude undulations of the pycnocline. IGWs propagating horizontally in a two layer stratified fluid are studied. The breaking of an IGW of depression shoaling upon a uniformly sloping boundary is investigated experimentally. Breaking dynamics beneath the shoaling waves causes both mixing and wave-induced near-bottom vortices suspending and redistributing the bed material. Laboratory experiments are conducted in a Perspex tank through the standard lock-release method, following the technique described in Sutherland et al. (2013). Each experiment is analysed and the instantaneous pycnocline position is measured, in order to obtain both geometric and kinematic features of the IGW: amplitude, wavelength and celerity. IGWs main features depend on the geometrical parameters that define the initial experimental setting: the density difference between the layers, the total depth, the layers depth ratio, the aspect ratio, and the displacement between the pycnoclines. Relations between IGWs geometric and kinematic features and the initial setting parameters are analysed. The approach of the IGWs toward a uniform slope is investigated in the present experiments. Depending on wave and slope characteristics, different breaking and mixing processes are observed. Sediments are sprinkled on the slope to visualize boundary layer separation in order to analyze the suspension e redistribution mechanisms due to the wave breaking.

A study on the effects of temperature and substrate structure on the templated two-phase film growth via a hybrid model

NASA Astrophysics Data System (ADS)

Lu, Xiao; Li, Jia; Zhu, Jian-Gang; Laughlin, David E.; Zhu, Jingxi

2018-06-01

Templated growth of two-phase thin films can achieve desirably ordered microstructures. In such cases, the microstructure of the growing films follows the topography of the template. By combining the Potts model Monte Carlo simulation and the "level set" method, an attempt was previously made to understand the physical mechanism behind the templated growth process. In the current work, this model is further used to study the effect of two parameters within the templated growth scenario, namely, the temperature and the geometric features of the template. The microstructure of the thin film grown with different lattice temperatures and domes is analyzed. It is found that within a moderate temperature range, the effect of geometric features took control of the ordering of the microstructure by its influence on the surface energy gradient. Interestingly, within this temperature range, as the temperature is increased, an ordered microstructure forms on a template without the optimal geometric features, which seems to be a result of competition between the kinetics and the thermodynamics during deposition. However, when the temperature was either above or below this temperature range, the template provided no guide to the whole deposition so that no ordered microstructure formed.

Application of complex geometrical optics to determination of thermal, transport, and optical parameters of thin films by the photothermal beam deflection technique.

PubMed

Korte, Dorota; Franko, Mladen

2015-01-01

In this work, complex geometrical optics is, for what we believe is the first time, applied instead of geometrical or wave optics to describe the probe beam interaction with the field of the thermal wave in photothermal beam deflection (photothermal deflection spectroscopy) experiments on thin films. On the basis of this approach the thermal (thermal diffusivity and conductivity), optical (energy band gap), and transport (carrier lifetime) parameters of the semiconductor thin films (pure TiO2, N- and C-doped TiO2, or TiO2/SiO2 composites deposited on a glass or aluminum support) were determined with better accuracy and simultaneously during one measurement. The results are in good agreement with results obtained by the use of other methods and reported in the literature.

Game Building with Complex-Valued Functions

ERIC Educational Resources Information Center

Dittman, Marki; Soto-Johnson, Hortensia; Dickinson, Scott; Harr, Tim

2017-01-01

In this paper, we describe how we integrated complex analysis into the second semester of a geometry course designed for preservice secondary mathematics teachers. As part of this inquiry-based course, the preservice teachers incorporated their geometric understanding of the arithmetic of complex numbers and complex-valued functions to create a…

Geometrical tile design for complex neighborhoods.

PubMed

Czeizler, Eugen; Kari, Lila

2009-01-01

Recent research has showed that tile systems are one of the most suitable theoretical frameworks for the spatial study and modeling of self-assembly processes, such as the formation of DNA and protein oligomeric structures. A Wang tile is a unit square, with glues on its edges, attaching to other tiles and forming larger and larger structures. Although quite intuitive, the idea of glues placed on the edges of a tile is not always natural for simulating the interactions occurring in some real systems. For example, when considering protein self-assembly, the shape of a protein is the main determinant of its functions and its interactions with other proteins. Our goal is to use geometric tiles, i.e., square tiles with geometrical protrusions on their edges, for simulating tiled paths (zippers) with complex neighborhoods, by ribbons of geometric tiles with simple, local neighborhoods. This paper is a step toward solving the general case of an arbitrary neighborhood, by proposing geometric tile designs that solve the case of a "tall" von Neumann neighborhood, the case of the f-shaped neighborhood, and the case of a 3 x 5 "filled" rectangular neighborhood. The techniques can be combined and generalized to solve the problem in the case of any neighborhood, centered at the tile of reference, and included in a 3 x (2k + 1) rectangle.

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

Ruan, D; Shao, W; Low, D

Purpose: To evaluate and test the hypothesis that plan quality may be systematically affected by treatment delivery techniques and target-tocritical structure geometric relationship in radiotherapy for brain tumor. Methods: Thirty-four consecutive brain tumor patients treated between 2011–2014 were analyzed. Among this cohort, 10 were planned with 3DCRT, 11 with RadipArc, and 13 with helical IMRT on TomoTherapy. The selected dosimetric endpoints (i.e., PTV V100, maximum brainstem/chiasm/ optic nerve doses) were considered as a vector in a highdimensional space. A Pareto analysis was performed to identify the subset of Pareto-efficient plans.The geometric relationships, specifically the overlapping volume and centroid-of-mass distance betweenmore » each critical structure to the PTV were extracted as potential geometric features. The classification-tree analyses were repeated using these geometric features with and without the treatment modality as an additional categorical predictor. In both scenarios, the dominant features to prognosticate the Pareto membership were identified and the tree structures to provide optimal inference were recorded. The classification performance was further analyzed to determine the role of treatment modality in affecting plan quality. Results: Seven Pareto-efficient plans were identified based on dosimetric endpoints (3 from 3DCRT, 3 from RapicArc, 1 from Tomo), which implies that the evaluated treatment modality may have a minor influence on plan quality. Classification trees with/without the treatment modality as a predictor both achieved accuracy of 88.2%: with 100% sensitivity and 87.1% specificity for the former, and 66.7% sensitivity and 96.0% specificity for the latter. The coincidence of accuracy from both analyses further indicates no-to-weak dependence of plan quality on treatment modality. Both analyses have identified the brainstem to PTV distance as the primary predictive feature for Pareto-efficiency. Conclusion: Pareto evaluation and classification-tree analyses have indicated that plan quality depends strongly on geometry for brain tumor, specifically PTV-tobrain-stem-distance but minimally on treatment modality.« less

Device-Free Localization via an Extreme Learning Machine with Parameterized Geometrical Feature Extraction.

PubMed

Zhang, Jie; Xiao, Wendong; Zhang, Sen; Huang, Shoudong

2017-04-17

Device-free localization (DFL) is becoming one of the new technologies in wireless localization field, due to its advantage that the target to be localized does not need to be attached to any electronic device. In the radio-frequency (RF) DFL system, radio transmitters (RTs) and radio receivers (RXs) are used to sense the target collaboratively, and the location of the target can be estimated by fusing the changes of the received signal strength (RSS) measurements associated with the wireless links. In this paper, we will propose an extreme learning machine (ELM) approach for DFL, to improve the efficiency and the accuracy of the localization algorithm. Different from the conventional machine learning approaches for wireless localization, in which the above differential RSS measurements are trivially used as the only input features, we introduce the parameterized geometrical representation for an affected link, which consists of its geometrical intercepts and differential RSS measurement. Parameterized geometrical feature extraction (PGFE) is performed for the affected links and the features are used as the inputs of ELM. The proposed PGFE-ELM for DFL is trained in the offline phase and performed for real-time localization in the online phase, where the estimated location of the target is obtained through the created ELM. PGFE-ELM has the advantages that the affected links used by ELM in the online phase can be different from those used for training in the offline phase, and can be more robust to deal with the uncertain combination of the detectable wireless links. Experimental results show that the proposed PGFE-ELM can improve the localization accuracy and learning speed significantly compared with a number of the existing machine learning and DFL approaches, including the weighted K-nearest neighbor (WKNN), support vector machine (SVM), back propagation neural network (BPNN), as well as the well-known radio tomographic imaging (RTI) DFL approach.

Device-Free Localization via an Extreme Learning Machine with Parameterized Geometrical Feature Extraction

PubMed Central

Zhang, Jie; Xiao, Wendong; Zhang, Sen; Huang, Shoudong

2017-01-01

Device-free localization (DFL) is becoming one of the new technologies in wireless localization field, due to its advantage that the target to be localized does not need to be attached to any electronic device. In the radio-frequency (RF) DFL system, radio transmitters (RTs) and radio receivers (RXs) are used to sense the target collaboratively, and the location of the target can be estimated by fusing the changes of the received signal strength (RSS) measurements associated with the wireless links. In this paper, we will propose an extreme learning machine (ELM) approach for DFL, to improve the efficiency and the accuracy of the localization algorithm. Different from the conventional machine learning approaches for wireless localization, in which the above differential RSS measurements are trivially used as the only input features, we introduce the parameterized geometrical representation for an affected link, which consists of its geometrical intercepts and differential RSS measurement. Parameterized geometrical feature extraction (PGFE) is performed for the affected links and the features are used as the inputs of ELM. The proposed PGFE-ELM for DFL is trained in the offline phase and performed for real-time localization in the online phase, where the estimated location of the target is obtained through the created ELM. PGFE-ELM has the advantages that the affected links used by ELM in the online phase can be different from those used for training in the offline phase, and can be more robust to deal with the uncertain combination of the detectable wireless links. Experimental results show that the proposed PGFE-ELM can improve the localization accuracy and learning speed significantly compared with a number of the existing machine learning and DFL approaches, including the weighted K-nearest neighbor (WKNN), support vector machine (SVM), back propagation neural network (BPNN), as well as the well-known radio tomographic imaging (RTI) DFL approach. PMID:28420187

Experimental realization of universal geometric quantum gates with solid-state spins.

PubMed

Zu, C; Wang, W-B; He, L; Zhang, W-G; Dai, C-Y; Wang, F; Duan, L-M

2014-10-02

Experimental realization of a universal set of quantum logic gates is the central requirement for the implementation of a quantum computer. In an 'all-geometric' approach to quantum computation, the quantum gates are implemented using Berry phases and their non-Abelian extensions, holonomies, from geometric transformation of quantum states in the Hilbert space. Apart from its fundamental interest and rich mathematical structure, the geometric approach has some built-in noise-resilience features. On the experimental side, geometric phases and holonomies have been observed in thermal ensembles of liquid molecules using nuclear magnetic resonance; however, such systems are known to be non-scalable for the purposes of quantum computing. There are proposals to implement geometric quantum computation in scalable experimental platforms such as trapped ions, superconducting quantum bits and quantum dots, and a recent experiment has realized geometric single-bit gates in a superconducting system. Here we report the experimental realization of a universal set of geometric quantum gates using the solid-state spins of diamond nitrogen-vacancy centres. These diamond defects provide a scalable experimental platform with the potential for room-temperature quantum computing, which has attracted strong interest in recent years. Our experiment shows that all-geometric and potentially robust quantum computation can be realized with solid-state spin quantum bits, making use of recent advances in the coherent control of this system.

The geometric framework for nutrition reveals interactions between protein and carbohydrate during larval growth in honey bees

USDA-ARS?s Scientific Manuscript database

In holometabolous insects, larval nutrition affects adult body size, a life history trait with a profound influence on performance and fitness. Individual nutritional components of larval diet are often complex and may interact with one another, necessitating the use of a geometric framework for und...

Clifford support vector machines for classification, regression, and recurrence.

PubMed

Bayro-Corrochano, Eduardo Jose; Arana-Daniel, Nancy

2010-11-01

This paper introduces the Clifford support vector machines (CSVM) as a generalization of the real and complex-valued support vector machines using the Clifford geometric algebra. In this framework, we handle the design of kernels involving the Clifford or geometric product. In this approach, one redefines the optimization variables as multivectors. This allows us to have a multivector as output. Therefore, we can represent multiple classes according to the dimension of the geometric algebra in which we work. We show that one can apply CSVM for classification and regression and also to build a recurrent CSVM. The CSVM is an attractive approach for the multiple input multiple output processing of high-dimensional geometric entities. We carried out comparisons between CSVM and the current approaches to solve multiclass classification and regression. We also study the performance of the recurrent CSVM with experiments involving time series. The authors believe that this paper can be of great use for researchers and practitioners interested in multiclass hypercomplex computing, particularly for applications in complex and quaternion signal and image processing, satellite control, neurocomputation, pattern recognition, computer vision, augmented virtual reality, robotics, and humanoids.

Integration of Geomatics Techniques for Digitizing Highly Relevant Geological and Cultural Heritage Sites: the Case of San Leo (italy)

NASA Astrophysics Data System (ADS)

Girelli, V. A.; Borgatti, L.; Dellapasqua, M.; Mandanici, E.; Spreafico, M. C.; Tini, M. A.; Bitelli, G.

2017-08-01

The research activities described in this contribution were carried out at San Leo (Italy). The town is located on the top of a quadrangular rock slab affected by a complex system of fractures and has a wealth of cultural heritage, as evidenced by the UNESCO's nomination. The management of this fragile set requires a comprehensive system of geometrical information to analyse and preserve all the geological and cultural features. In this perspective, the latest Geomatics techniques were used to perform some detailed surveys and to manage the great amount of acquired geometrical knowledge of both natural (the cliff) and historical heritage. All the data were also georeferenced in a unique reference system. In particular, high accurate terrestrial laser scanner surveys were performed for the whole cliff, in order to obtain a dense point cloud useful for a large number of geological studies, among others the analyses of the last rockslide by comparing pre- and post-event data. Moreover, the geometrical representation of the historical centre was performed using different approaches, in order to generate an accurate DTM and DSM of the site. For these purposes, a large scale numerical map was used, integrating the data with GNSS and laser surveys of the area. Finally, many surveys were performed with different approaches on some of the most relevant monuments of the town. In fact, these surveys were performed by terrestrial laser scanner, light structured scanner and photogrammetry, the last mainly applied with the Structure from Motion approach.

Modeling Slab-Slab Interactions: Dynamics of Outward Dipping Double-Sided Subduction Systems

NASA Astrophysics Data System (ADS)

Király, Ágnes; Holt, Adam F.; Funiciello, Francesca; Faccenna, Claudio; Capitanio, Fabio A.

2018-03-01

Slab-slab interaction is a characteristic feature of tectonically complex areas. Outward dipping double-sided subduction is one of these complex cases, which has several examples on Earth, most notably the Molucca Sea and Adriatic Sea. This study focuses on developing a framework for linking plate kinematics and slab interactions in an outward dipping subduction geometry. We used analog and numerical models to better understand the underlying subduction dynamics. Compared to a single subduction model, double-sided subduction exhibits more time-dependent and vigorous toroidal flow cells that are elongated (i.e., not circular). Because both the Molucca and Adriatic Sea exhibit an asymmetric subduction configuration, we also examine the role that asymmetry plays in the dynamics of outward dipping double-sided subduction. We introduce asymmetry in two ways; with variable initial depths for the two slabs ("geometric" asymmetry), and with variable buoyancy within the subducting plate ("mechanical" asymmetry). Relative to the symmetric case, we probe how asymmetry affects the overall slab kinematics, whether asymmetric behavior intensifies or equilibrates as subduction proceeds. While initial geometric asymmetry disappears once the slabs are anchored to the 660 km discontinuity, the mechanical asymmetry can cause more permanent differences between the two subduction zones. In the most extreme case, the partly continental slab stops subducting due to the unequal slab pull force. The results show that the slab-slab interaction is most effective when the two trenches are closer than 10-8 cm in the laboratory, which is 600-480 km when scaled to the Earth.

A novel automated spike sorting algorithm with adaptable feature extraction.

PubMed

Bestel, Robert; Daus, Andreas W; Thielemann, Christiane

2012-10-15

To study the electrophysiological properties of neuronal networks, in vitro studies based on microelectrode arrays have become a viable tool for analysis. Although in constant progress, a challenging task still remains in this area: the development of an efficient spike sorting algorithm that allows an accurate signal analysis at the single-cell level. Most sorting algorithms currently available only extract a specific feature type, such as the principal components or Wavelet coefficients of the measured spike signals in order to separate different spike shapes generated by different neurons. However, due to the great variety in the obtained spike shapes, the derivation of an optimal feature set is still a very complex issue that current algorithms struggle with. To address this problem, we propose a novel algorithm that (i) extracts a variety of geometric, Wavelet and principal component-based features and (ii) automatically derives a feature subset, most suitable for sorting an individual set of spike signals. Thus, there is a new approach that evaluates the probability distribution of the obtained spike features and consequently determines the candidates most suitable for the actual spike sorting. These candidates can be formed into an individually adjusted set of spike features, allowing a separation of the various shapes present in the obtained neuronal signal by a subsequent expectation maximisation clustering algorithm. Test results with simulated data files and data obtained from chick embryonic neurons cultured on microelectrode arrays showed an excellent classification result, indicating the superior performance of the described algorithm approach. Copyright © 2012 Elsevier B.V. All rights reserved.

A laser-based vision system for weld quality inspection.

PubMed

Huang, Wei; Kovacevic, Radovan

2011-01-01

Welding is a very complex process in which the final weld quality can be affected by many process parameters. In order to inspect the weld quality and detect the presence of various weld defects, different methods and systems are studied and developed. In this paper, a laser-based vision system is developed for non-destructive weld quality inspection. The vision sensor is designed based on the principle of laser triangulation. By processing the images acquired from the vision sensor, the geometrical features of the weld can be obtained. Through the visual analysis of the acquired 3D profiles of the weld, the presences as well as the positions and sizes of the weld defects can be accurately identified and therefore, the non-destructive weld quality inspection can be achieved.

Contour fractal analysis of grains

NASA Astrophysics Data System (ADS)

Guida, Giulia; Casini, Francesca; Viggiani, Giulia MB

2017-06-01

Fractal analysis has been shown to be useful in image processing to characterise the shape and the grey-scale complexity in different applications spanning from electronic to medical engineering (e.g. [1]). Fractal analysis consists of several methods to assign a dimension and other fractal characteristics to a dataset describing geometric objects. Limited studies have been conducted on the application of fractal analysis to the classification of the shape characteristics of soil grains. The main objective of the work described in this paper is to obtain, from the results of systematic fractal analysis of artificial simple shapes, the characterization of the particle morphology at different scales. The long term objective of the research is to link the microscopic features of granular media with the mechanical behaviour observed in the laboratory and in situ.

A Laser-Based Vision System for Weld Quality Inspection

PubMed Central

Huang, Wei; Kovacevic, Radovan

2011-01-01

Welding is a very complex process in which the final weld quality can be affected by many process parameters. In order to inspect the weld quality and detect the presence of various weld defects, different methods and systems are studied and developed. In this paper, a laser-based vision system is developed for non-destructive weld quality inspection. The vision sensor is designed based on the principle of laser triangulation. By processing the images acquired from the vision sensor, the geometrical features of the weld can be obtained. Through the visual analysis of the acquired 3D profiles of the weld, the presences as well as the positions and sizes of the weld defects can be accurately identified and therefore, the non-destructive weld quality inspection can be achieved. PMID:22344308

X-ray absorption spectroscopic studies of mononuclear non-heme iron enzymes

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

Westre, Tami E.

Fe-K-edge X-ray absorption spectroscopy (XAS) has been used to investigate the electronic and geometric structure of the iron active site in non-heme iron enzymes. A new theoretical extended X-ray absorption fine structure (EXAFS) analysis approach, called GNXAS, has been tested on data for iron model complexes to evaluate the utility and reliability of this new technique, especially with respect to the effects of multiple-scattering. In addition, a detailed analysis of the 1s→3d pre-edge feature has been developed as a tool for investigating the oxidation state, spin state, and geometry of iron sites. Edge and EXAFS analyses have then been appliedmore » to the study of non-heme iron enzyme active sites.« less

Computer-Aided Diagnosis of Solid Breast Lesions Using an Ultrasonic Multi-Feature Analysis Procedure

DTIC Science & Technology

2011-01-01

areas. We quantified morphometric features by geometric and fractal analysis of traced lesion boundaries. Although no single parameter can reliably...These include acoustic descriptors (“echogenicity,” “heterogeneity,” “shadowing”) and morphometric descriptors (“area,” “aspect ratio,” “border...quantitative descriptors; some morphometric features (such as border irregularity) also were particularly effective in lesion classification. Our

A semi-analytical description of protein folding that incorporates detailed geometrical information

PubMed Central

Suzuki, Yoko; Noel, Jeffrey K.; Onuchic, José N.

2011-01-01

Much has been done to study the interplay between geometric and energetic effects on the protein folding energy landscape. Numerical techniques such as molecular dynamics simulations are able to maintain a precise geometrical representation of the protein. Analytical approaches, however, often focus on the energetic aspects of folding, including geometrical information only in an average way. Here, we investigate a semi-analytical expression of folding that explicitly includes geometrical effects. We consider a Hamiltonian corresponding to a Gaussian filament with structure-based interactions. The model captures local features of protein folding often averaged over by mean-field theories, for example, loop contact formation and excluded volume. We explore the thermodynamics and folding mechanisms of beta-hairpin and alpha-helical structures as functions of temperature and Q, the fraction of native contacts formed. Excluded volume is shown to be an important component of a protein Hamiltonian, since it both dominates the cooperativity of the folding transition and alters folding mechanisms. Understanding geometrical effects in analytical formulae will help illuminate the consequences of the approximations required for the study of larger proteins. PMID:21721664

"Soft docking": matching of molecular surface cubes.

PubMed

Jiang, F; Kim, S H

1991-05-05

Molecular recognition is achieved through the complementarity of molecular surface structures and energetics with, most commonly, associated minor conformational changes. This complementarity can take many forms: charge-charge interaction, hydrogen bonding, van der Waals' interaction, and the size and shape of surfaces. We describe a method that exploits these features to predict the sites of interactions between two cognate molecules given their three-dimensional structures. We have developed a "cube representation" of molecular surface and volume which enables us not only to design a simple algorithm for a six-dimensional search but also to allow implicitly the effects of the conformational changes caused by complex formation. The present molecular docking procedure may be divided into two stages. The first is the selection of a population of complexes by geometric "soft docking", in which surface structures of two interacting molecules are matched with each other, allowing minor conformational changes implicitly, on the basis of complementarity in size and shape, close packing, and the absence of steric hindrance. The second is a screening process to identify a subpopulation with many favorable energetic interactions between the buried surface areas. Once the size of the subpopulation is small, one may further screen to find the correct complex based on other criteria or constraints obtained from biochemical, genetic, and theoretical studies, including visual inspection. We have tested the present method in two ways. First is a control test in which we docked the components of a molecular complex of known crystal structure available in the Protein Data Bank (PDB). Two molecular complexes were used: (1) a ternary complex of dihydrofolate reductase, NADPH and methotrexate (3DFR in PDB) and (2) a binary complex of trypsin and trypsin inhibitor (2PTC in PDB). The components of each complex were taken apart at an arbitrary relative orientation and then docked together again. The results show that the geometric docking alone is sufficient to determine the correct docking solutions in these ideal cases, and that the cube representation of the molecules does not degrade the docking process in the search for the correct solution. The second is the more realistic experiment in which we docked the crystal structures of uncomplexed molecules and then compared the structures of docked complexes with the crystal structures of the corresponding complexes. This is to test the capability of our method in accommodating the effects of the conformational changes in the binding sites of the molecules in docking.(ABSTRACT TRUNCATED AT 400 WORDS)

Multi-Scale Voxel Segmentation for Terrestrial Lidar Data within Marshes

NASA Astrophysics Data System (ADS)

Nguyen, C. T.; Starek, M. J.; Tissot, P.; Gibeaut, J. C.

2016-12-01

The resilience of marshes to a rising sea is dependent on their elevation response. Terrestrial laser scanning (TLS) is a detailed topographic approach for accurate, dense surface measurement with high potential for monitoring of marsh surface elevation response. The dense point cloud provides a 3D representation of the surface, which includes both terrain and non-terrain objects. Extraction of topographic information requires filtering of the data into like-groups or classes, therefore, methods must be incorporated to identify structure in the data prior to creation of an end product. A voxel representation of three-dimensional space provides quantitative visualization and analysis for pattern recognition. The objectives of this study are threefold: 1) apply a multi-scale voxel approach to effectively extract geometric features from the TLS point cloud data, 2) investigate the utility of K-means and Self Organizing Map (SOM) clustering algorithms for segmentation, and 3) utilize a variety of validity indices to measure the quality of the result. TLS data were collected at a marsh site along the central Texas Gulf Coast using a Riegl VZ 400 TLS. The site consists of both exposed and vegetated surface regions. To characterize structure of the point cloud, octree segmentation is applied to create a tree data structure of voxels containing the points. The flexibility of voxels in size and point density makes this algorithm a promising candidate to locally extract statistical and geometric features of the terrain including surface normal and curvature. The characteristics of the voxel itself such as the volume and point density are also computed and assigned to each point as are laser pulse characteristics. The features extracted from the voxelization are then used as input for clustering of the points using the K-means and SOM clustering algorithms. Optimal number of clusters are then determined based on evaluation of cluster separability criterions. Results for different combinations of the feature space vector and differences between K-means and SOM clustering will be presented. The developed method provides a novel approach for compressing TLS scene complexity in marshes, such as for vegetation biomass studies or erosion monitoring.

Framework of collagen type I - vasoactive vessels structuring invariant geometric attractor in cancer tissues: insight into biological magnetic field.

PubMed

Díaz, Jairo A; Murillo, Mauricio F; Jaramillo, Natalia A

2009-01-01

In a previous research, we have described and documented self-assembly of geometric triangular chiral hexagon crystal-like complex organizations (GTCHC) in human pathological tissues. This article documents and gathers insights into the magnetic field in cancer tissues and also how it generates an invariant functional geometric attractor constituted for collider partners in their entangled environment. The need to identify this hierarquic attractor was born out of the concern to understand how the vascular net of these complexes are organized, and to determine if the spiral vascular subpatterns observed adjacent to GTCHC complexes and their assembly are interrelational. The study focuses on cancer tissues and all the macroscopic and microscopic material in which GTCHC complexes are identified, which have been overlooked so far, and are rigorously revised. This revision follows the same parameters that were established in the initial phase of the investigation, but with a new item: the visualization and documentation of external dorsal serous vascular bed areas in spatial correlation with the localization of GTCHC complexes inside the tumors. Following the standard of the electro-optical collision model, we were able to reproduce and replicate collider patterns, that is, pairs of left and right hand spin-spiraled subpatterns, associated with the orientation of the spinning process that can be an expansion or contraction disposition of light particles. Agreement between this model and tumor data is surprisingly close; electromagnetic spiral patterns generated were identical at the spiral vascular arrangement in connection with GTCHC complexes in malignant tumors. These findings suggest that the framework of collagen type 1 - vasoactive vessels that structure geometric attractors in cancer tissues with invariant morphology sets generate collider partners in their magnetic domain with opposite biological behavior. If these principles are incorporated into nanomaterial, biomedical devices, and engineered tissues, new therapeutic strategies could be developed for cancer treatment.

Versatility and Invariance in the Evolution of Homologous Heteromeric Interfaces

PubMed Central

Andreani, Jessica; Faure, Guilhem; Guerois, Raphaël

2012-01-01

Evolutionary pressures act on protein complex interfaces so that they preserve their complementarity. Nonetheless, the elementary interactions which compose the interface are highly versatile throughout evolution. Understanding and characterizing interface plasticity across evolution is a fundamental issue which could provide new insights into protein-protein interaction prediction. Using a database of 1,024 couples of close and remote heteromeric structural interologs, we studied protein-protein interactions from a structural and evolutionary point of view. We systematically and quantitatively analyzed the conservation of different types of interface contacts. Our study highlights astonishing plasticity regarding polar contacts at complex interfaces. It also reveals that up to a quarter of the residues switch out of the interface when comparing two homologous complexes. Despite such versatility, we identify two important interface descriptors which correlate with an increased conservation in the evolution of interfaces: apolar patches and contacts surrounding anchor residues. These observations hold true even when restricting the dataset to transiently formed complexes. We show that a combination of six features related either to sequence or to geometric properties of interfaces can be used to rank positions likely to share similar contacts between two interologs. Altogether, our analysis provides important tracks for extracting meaningful information from multiple sequence alignments of conserved binding partners and for discriminating near-native interfaces using evolutionary information. PMID:22952442

3dRPC: a web server for 3D RNA-protein structure prediction.

PubMed

Huang, Yangyu; Li, Haotian; Xiao, Yi

2018-04-01

RNA-protein interactions occur in many biological processes. To understand the mechanism of these interactions one needs to know three-dimensional (3D) structures of RNA-protein complexes. 3dRPC is an algorithm for prediction of 3D RNA-protein complex structures and consists of a docking algorithm RPDOCK and a scoring function 3dRPC-Score. RPDOCK is used to sample possible complex conformations of an RNA and a protein by calculating the geometric and electrostatic complementarities and stacking interactions at the RNA-protein interface according to the features of atom packing of the interface. 3dRPC-Score is a knowledge-based potential that uses the conformations of nucleotide-amino-acid pairs as statistical variables and that is used to choose the near-native complex-conformations obtained from the docking method above. Recently, we built a web server for 3dRPC. The users can easily use 3dRPC without installing it locally. RNA and protein structures in PDB (Protein Data Bank) format are the only needed input files. It can also incorporate the information of interface residues or residue-pairs obtained from experiments or theoretical predictions to improve the prediction. The address of 3dRPC web server is http://biophy.hust.edu.cn/3dRPC. yxiao@hust.edu.cn.

Chain-Wise Generalization of Road Networks Using Model Selection

NASA Astrophysics Data System (ADS)

Bulatov, D.; Wenzel, S.; Häufel, G.; Meidow, J.

2017-05-01

Streets are essential entities of urban terrain and their automatized extraction from airborne sensor data is cumbersome because of a complex interplay of geometric, topological and semantic aspects. Given a binary image, representing the road class, centerlines of road segments are extracted by means of skeletonization. The focus of this paper lies in a well-reasoned representation of these segments by means of geometric primitives, such as straight line segments as well as circle and ellipse arcs. We propose the fusion of raw segments based on similarity criteria; the output of this process are the so-called chains which better match to the intuitive perception of what a street is. Further, we propose a two-step approach for chain-wise generalization. First, the chain is pre-segmented using circlePeucker and finally, model selection is used to decide whether two neighboring segments should be fused to a new geometric entity. Thereby, we consider both variance-covariance analysis of residuals and model complexity. The results on a complex data-set with many traffic roundabouts indicate the benefits of the proposed procedure.

Luminescent and thermochromic properties of tellurium(IV) halide complexes with cesium

NASA Astrophysics Data System (ADS)

Sedakova, T. V.; Mirochnik, A. G.

2016-02-01

The spectral-luminescent and thermochromic properties of complex compounds of the composition Cs2TeHal6 (Hal = Cl, Br, I) are studied. The interrelation between the geometric structure and spectral-luminescent properties is studied using the example on complex compounds of tellurium(IV) halides with cesium. The Stokes shift and the luminescence intensity of Te(IV) ions with island octahedral coordination are found to depend on the position of the A band in the luminescence excitation spectra, the diffuse reflection, and the energy of the luminescent 3 P 1 → 1 S 0 transition of the tellurium(IV) ion. The maximum luminescence intensity and the minimum Stokes shift at 77 and 300 K are observed for Cs2TeCl6. The geometrical and electronic factors responsible for luminescence intensification in Te(IV) complexes under study are analyzed.

An Introduction to Geometric Algebra with some Preliminary Thoughts on the Geometric Meaning of Quantum Mechanics

NASA Astrophysics Data System (ADS)

Horn, Martin Erik

2014-10-01

It is still a great riddle to me why Wolfgang Pauli and P.A.M. Dirac had not fully grasped the meaning of their own mathematical constructions. They invented magnificent, fantastic and very important mathematical features of modern physics, but they only delivered half of the interpretations of their own inventions. Of course, Pauli matrices and Dirac matrices represent operators, which Pauli and Dirac discussed in length. But this is only part of the true meaning behind them, as the non-commutative ideas of Grassmann, Clifford, Hamilton and Cartan allow a second, very far reaching interpretation of Pauli and Dirac matrices. An introduction to this alternative interpretation will be discussed. Some applications of this view on Pauli and Dirac matrices are given, e.g. a geometric algebra picture of the plane wave solution of the Maxwell equation, a geometric algebra picture of special relativity, a toy model of SU(3) symmetry, and some only very preliminary thoughts about a possible geometric meaning of quantum mechanics.

A computational framework to characterize and compare the geometry of coronary networks.

PubMed

Bulant, C A; Blanco, P J; Lima, T P; Assunção, A N; Liberato, G; Parga, J R; Ávila, L F R; Pereira, A C; Feijóo, R A; Lemos, P A

2017-03-01

This work presents a computational framework to perform a systematic and comprehensive assessment of the morphometry of coronary arteries from in vivo medical images. The methodology embraces image segmentation, arterial vessel representation, characterization and comparison, data storage, and finally analysis. Validation is performed using a sample of 48 patients. Data mining of morphometric information of several coronary arteries is presented. Results agree to medical reports in terms of basic geometric and anatomical variables. Concerning geometric descriptors, inter-artery and intra-artery correlations are studied. Data reported here can be useful for the construction and setup of blood flow models of the coronary circulation. Finally, as an application example, similarity criterion to assess vasculature likelihood based on geometric features is presented and used to test geometric similarity among sibling patients. Results indicate that likelihood, measured through geometric descriptors, is stronger between siblings compared with non-relative patients. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

GeoBuilder: a geometric algorithm visualization and debugging system for 2D and 3D geometric computing.

PubMed

Wei, Jyh-Da; Tsai, Ming-Hung; Lee, Gen-Cher; Huang, Jeng-Hung; Lee, Der-Tsai

2009-01-01

Algorithm visualization is a unique research topic that integrates engineering skills such as computer graphics, system programming, database management, computer networks, etc., to facilitate algorithmic researchers in testing their ideas, demonstrating new findings, and teaching algorithm design in the classroom. Within the broad applications of algorithm visualization, there still remain performance issues that deserve further research, e.g., system portability, collaboration capability, and animation effect in 3D environments. Using modern technologies of Java programming, we develop an algorithm visualization and debugging system, dubbed GeoBuilder, for geometric computing. The GeoBuilder system features Java's promising portability, engagement of collaboration in algorithm development, and automatic camera positioning for tracking 3D geometric objects. In this paper, we describe the design of the GeoBuilder system and demonstrate its applications.

Biomaterial design for specific cellular interactions: Role of surface functionalization and geometric features

NASA Astrophysics Data System (ADS)

Kolhar, Poornima

The areas of drug delivery and tissue engineering have experienced extraordinary growth in recent years with the application of engineering principles and their potential to support and improve the field of medicine. The tremendous progress in nanotechnology and biotechnology has lead to this explosion of research and development in biomedical applications. Biomaterials can now be engineered at a nanoscale and their specific interactions with the biological tissues can be modulated. Various design parameters are being established and researched for design of drug-delivery carriers and scaffolds to be implanted into humans. Nanoparticles made from versatile biomaterial can deliver both small-molecule drugs and various classes of bio-macromolecules, such as proteins and oligonucleotides. Similarly in the field of tissue engineering, current approaches emphasize nanoscale control of cell behavior by mimicking the natural extracellular matrix (ECM) unlike, traditional scaffolds. Drug delivery and tissue engineering are closely connected fields and both of these applications require materials with exceptional physical, chemical, biological, and biomechanical properties to provide superior therapy. In the current study the surface functionalization and the geometric features of the biomaterials has been explored. In particular, a synthetic surface for culture of human embryonic stem cells has been developed, demonstrating the importance of surface functionalization in maintaining the pluripotency of hESCs. In the second study, the geometric features of the drug delivery carriers are investigated and the polymeric nanoneedles mediated cellular permeabilization and direct cytoplasmic delivery is reported. In the third study, the combined effect of surface functionalization and geometric modification of carriers for vascular targeting is enunciated. These studies illustrate how the biomaterials can be designed to achieve various cellular behaviors and control the interactions with cells in vivo .

High-order graph matching based feature selection for Alzheimer's disease identification.

PubMed

Liu, Feng; Suk, Heung-Il; Wee, Chong-Yaw; Chen, Huafu; Shen, Dinggang

2013-01-01

One of the main limitations of l1-norm feature selection is that it focuses on estimating the target vector for each sample individually without considering relations with other samples. However, it's believed that the geometrical relation among target vectors in the training set may provide useful information, and it would be natural to expect that the predicted vectors have similar geometric relations as the target vectors. To overcome these limitations, we formulate this as a graph-matching feature selection problem between a predicted graph and a target graph. In the predicted graph a node is represented by predicted vector that may describe regional gray matter volume or cortical thickness features, and in the target graph a node is represented by target vector that include class label and clinical scores. In particular, we devise new regularization terms in sparse representation to impose high-order graph matching between the target vectors and the predicted ones. Finally, the selected regional gray matter volume and cortical thickness features are fused in kernel space for classification. Using the ADNI dataset, we evaluate the effectiveness of the proposed method and obtain the accuracies of 92.17% and 81.57% in AD and MCI classification, respectively.

Incoherent optical generalized Hough transform: pattern recognition and feature extraction applications

NASA Astrophysics Data System (ADS)

Fernández, Ariel; Ferrari, José A.

2017-05-01

Pattern recognition and feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital-only methods. We explore an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a pupil mask implemented on a high-contrast spatial light modulator for orientation/shape variation of the template. Real-time can also be achieved. In addition, by thresholding of the GHT and optically inverse transforming, the previously detected features of interest can be extracted.

iFER: facial expression recognition using automatically selected geometric eye and eyebrow features

NASA Astrophysics Data System (ADS)

Oztel, Ismail; Yolcu, Gozde; Oz, Cemil; Kazan, Serap; Bunyak, Filiz

2018-03-01

Facial expressions have an important role in interpersonal communications and estimation of emotional states or intentions. Automatic recognition of facial expressions has led to many practical applications and became one of the important topics in computer vision. We present a facial expression recognition system that relies on geometry-based features extracted from eye and eyebrow regions of the face. The proposed system detects keypoints on frontal face images and forms a feature set using geometric relationships among groups of detected keypoints. Obtained feature set is refined and reduced using the sequential forward selection (SFS) algorithm and fed to a support vector machine classifier to recognize five facial expression classes. The proposed system, iFER (eye-eyebrow only facial expression recognition), is robust to lower face occlusions that may be caused by beards, mustaches, scarves, etc. and lower face motion during speech production. Preliminary experiments on benchmark datasets produced promising results outperforming previous facial expression recognition studies using partial face features, and comparable results to studies using whole face information, only slightly lower by ˜ 2.5 % compared to the best whole face facial recognition system while using only ˜ 1 / 3 of the facial region.

Geometric Integration of Hybrid Correspondences for RGB-D Unidirectional Tracking

PubMed Central

Tang, Shengjun; Chen, Wu; Wang, Weixi; Li, Xiaoming; Li, Wenbin; Huang, Zhengdong; Hu, Han; Guo, Renzhong

2018-01-01

Traditionally, visual-based RGB-D SLAM systems only use correspondences with valid depth values for camera tracking, thus ignoring the regions without 3D information. Due to the strict limitation on measurement distance and view angle, such systems adopt only short-range constraints which may introduce larger drift errors during long-distance unidirectional tracking. In this paper, we propose a novel geometric integration method that makes use of both 2D and 3D correspondences for RGB-D tracking. Our method handles the problem by exploring visual features both when depth information is available and when it is unknown. The system comprises two parts: coarse pose tracking with 3D correspondences, and geometric integration with hybrid correspondences. First, the coarse pose tracking generates the initial camera pose using 3D correspondences with frame-by-frame registration. The initial camera poses are then used as inputs for the geometric integration model, along with 3D correspondences, 2D-3D correspondences and 2D correspondences identified from frame pairs. The initial 3D location of the correspondence is determined in two ways, from depth image and by using the initial poses to triangulate. The model improves the camera poses and decreases drift error during long-distance RGB-D tracking iteratively. Experiments were conducted using data sequences collected by commercial Structure Sensors. The results verify that the geometric integration of hybrid correspondences effectively decreases the drift error and improves mapping accuracy. Furthermore, the model enables a comparative and synergistic use of datasets, including both 2D and 3D features. PMID:29723974

Geometric Integration of Hybrid Correspondences for RGB-D Unidirectional Tracking.

PubMed

Tang, Shengjun; Chen, Wu; Wang, Weixi; Li, Xiaoming; Darwish, Walid; Li, Wenbin; Huang, Zhengdong; Hu, Han; Guo, Renzhong

2018-05-01

Traditionally, visual-based RGB-D SLAM systems only use correspondences with valid depth values for camera tracking, thus ignoring the regions without 3D information. Due to the strict limitation on measurement distance and view angle, such systems adopt only short-range constraints which may introduce larger drift errors during long-distance unidirectional tracking. In this paper, we propose a novel geometric integration method that makes use of both 2D and 3D correspondences for RGB-D tracking. Our method handles the problem by exploring visual features both when depth information is available and when it is unknown. The system comprises two parts: coarse pose tracking with 3D correspondences, and geometric integration with hybrid correspondences. First, the coarse pose tracking generates the initial camera pose using 3D correspondences with frame-by-frame registration. The initial camera poses are then used as inputs for the geometric integration model, along with 3D correspondences, 2D-3D correspondences and 2D correspondences identified from frame pairs. The initial 3D location of the correspondence is determined in two ways, from depth image and by using the initial poses to triangulate. The model improves the camera poses and decreases drift error during long-distance RGB-D tracking iteratively. Experiments were conducted using data sequences collected by commercial Structure Sensors. The results verify that the geometric integration of hybrid correspondences effectively decreases the drift error and improves mapping accuracy. Furthermore, the model enables a comparative and synergistic use of datasets, including both 2D and 3D features.

A geometric modeler based on a dual-geometry representation polyhedra and rational b-splines

NASA Technical Reports Server (NTRS)

Klosterman, A. L.

1984-01-01

For speed and data base reasons, solid geometric modeling of large complex practical systems is usually approximated by a polyhedra representation. Precise parametric surface and implicit algebraic modelers are available but it is not yet practical to model the same level of system complexity with these precise modelers. In response to this contrast the GEOMOD geometric modeling system was built so that a polyhedra abstraction of the geometry would be available for interactive modeling without losing the precise definition of the geometry. Part of the reason that polyhedra modelers are effective is that all bounded surfaces can be represented in a single canonical format (i.e., sets of planar polygons). This permits a very simple and compact data structure. Nonuniform rational B-splines are currently the best representation to describe a very large class of geometry precisely with one canonical format. The specific capabilities of the modeler are described.

Retinal Connectomics: Towards Complete, Accurate Networks

PubMed Central

Marc, Robert E.; Jones, Bryan W.; Watt, Carl B.; Anderson, James R.; Sigulinsky, Crystal; Lauritzen, Scott

2013-01-01

Connectomics is a strategy for mapping complex neural networks based on high-speed automated electron optical imaging, computational assembly of neural data volumes, web-based navigational tools to explore 1012–1015 byte (terabyte to petabyte) image volumes, and annotation and markup tools to convert images into rich networks with cellular metadata. These collections of network data and associated metadata, analyzed using tools from graph theory and classification theory, can be merged with classical systems theory, giving a more completely parameterized view of how biologic information processing systems are implemented in retina and brain. Networks have two separable features: topology and connection attributes. The first findings from connectomics strongly validate the idea that the topologies complete retinal networks are far more complex than the simple schematics that emerged from classical anatomy. In particular, connectomics has permitted an aggressive refactoring of the retinal inner plexiform layer, demonstrating that network function cannot be simply inferred from stratification; exposing the complex geometric rules for inserting different cells into a shared network; revealing unexpected bidirectional signaling pathways between mammalian rod and cone systems; documenting selective feedforward systems, novel candidate signaling architectures, new coupling motifs, and the highly complex architecture of the mammalian AII amacrine cell. This is but the beginning, as the underlying principles of connectomics are readily transferrable to non-neural cell complexes and provide new contexts for assessing intercellular communication. PMID:24016532

Theoretical studies on the electronic structure and spectroscopic properties of transition metals bis(dipyrrinate)s

NASA Astrophysics Data System (ADS)

Ksenofontov, Alexander A.; Guseva, Galina B.; Antina, Elena V.

2016-10-01

Density functional theory (DFT) and Time-dependent density functional theory (TD- DFT) computations have been used to reveal structural, molecular, electronic and spectral-luminescent parameters and features of several homoleptic transition metals bis(dipyrrine) complexes. The influence of complexing agent and ligand nature on the regularities in geometric, spectral-luminescent properties, kinetic and thermal stability changes in the [M2L2] complexes series were studied. Special attention is paid to the influence of the solvating media (PCM/TD-B3LYP/Def2-SVP) on changing spectral-luminescent properties of d-metals bis(dipyrrinate)s. The interpretation of the dependence between spectral-luminescent properties of the complexes and HOMO-LUMO (highest occupied molecular orbital and lowest unoccupied molecular orbital) energy gap's width was given. It was shown that the regularities in changing the helicates' quantum yield depending on the nature of complexing agent, ligand and solvent properties, obtained from quantum-chemical calculations, are in the agreement with our previously obtained experimental data. Thus, structural and spectral-luminescent characteristics of new [M2L2] luminophors can be evaluated with high reliability, and good forecast prospects for their use as fluorescent dyes for optical devices can be made in terms of the results of theoretical studies (B3LYP/Def2-SVP and TD-B3LYP/Def2-SVP).

The molten glass sewing machine

PubMed Central

Inamura, Chikara; Lizardo, Daniel; Franchin, Giorgia; Stern, Michael; Houk, Peter; Oxman, Neri

2017-01-01

We present a fluid-instability-based approach for digitally fabricating geometrically complex uniformly sized structures in molten glass. Formed by mathematically defined and physically characterized instability patterns, such structures are produced via the additive manufacturing of optically transparent glass, and result from the coiling of an extruded glass thread. We propose a minimal geometrical model—and a methodology—to reliably control the morphology of patterns, so that these building blocks can be assembled into larger structures with tailored functionally and optically tunable properties. This article is part of the themed issue ‘Patterning through instabilities in complex media: theory and applications’. PMID:28373379

Mechanical assembly of complex, 3D mesostructures from releasable multilayers of advanced materials.

PubMed

Yan, Zheng; Zhang, Fan; Liu, Fei; Han, Mengdi; Ou, Dapeng; Liu, Yuhao; Lin, Qing; Guo, Xuelin; Fu, Haoran; Xie, Zhaoqian; Gao, Mingye; Huang, Yuming; Kim, JungHwan; Qiu, Yitao; Nan, Kewang; Kim, Jeonghyun; Gutruf, Philipp; Luo, Hongying; Zhao, An; Hwang, Keh-Chih; Huang, Yonggang; Zhang, Yihui; Rogers, John A

2016-09-01

Capabilities for assembly of three-dimensional (3D) micro/nanostructures in advanced materials have important implications across a broad range of application areas, reaching nearly every class of microsystem technology. Approaches that rely on the controlled, compressive buckling of 2D precursors are promising because of their demonstrated compatibility with the most sophisticated planar technologies, where materials include inorganic semiconductors, polymers, metals, and various heterogeneous combinations, spanning length scales from submicrometer to centimeter dimensions. We introduce a set of fabrication techniques and design concepts that bypass certain constraints set by the underlying physics and geometrical properties of the assembly processes associated with the original versions of these methods. In particular, the use of releasable, multilayer 2D precursors provides access to complex 3D topologies, including dense architectures with nested layouts, controlled points of entanglement, and other previously unobtainable layouts. Furthermore, the simultaneous, coordinated assembly of additional structures can enhance the structural stability and drive the motion of extended features in these systems. The resulting 3D mesostructures, demonstrated in a diverse set of more than 40 different examples with feature sizes from micrometers to centimeters, offer unique possibilities in device design. A 3D spiral inductor for near-field communication represents an example where these ideas enable enhanced quality ( Q ) factors and broader working angles compared to those of conventional 2D counterparts.

Mechanical assembly of complex, 3D mesostructures from releasable multilayers of advanced materials

PubMed Central

Yan, Zheng; Zhang, Fan; Liu, Fei; Han, Mengdi; Ou, Dapeng; Liu, Yuhao; Lin, Qing; Guo, Xuelin; Fu, Haoran; Xie, Zhaoqian; Gao, Mingye; Huang, Yuming; Kim, JungHwan; Qiu, Yitao; Nan, Kewang; Kim, Jeonghyun; Gutruf, Philipp; Luo, Hongying; Zhao, An; Hwang, Keh-Chih; Huang, Yonggang; Zhang, Yihui; Rogers, John A.

2016-01-01

Capabilities for assembly of three-dimensional (3D) micro/nanostructures in advanced materials have important implications across a broad range of application areas, reaching nearly every class of microsystem technology. Approaches that rely on the controlled, compressive buckling of 2D precursors are promising because of their demonstrated compatibility with the most sophisticated planar technologies, where materials include inorganic semiconductors, polymers, metals, and various heterogeneous combinations, spanning length scales from submicrometer to centimeter dimensions. We introduce a set of fabrication techniques and design concepts that bypass certain constraints set by the underlying physics and geometrical properties of the assembly processes associated with the original versions of these methods. In particular, the use of releasable, multilayer 2D precursors provides access to complex 3D topologies, including dense architectures with nested layouts, controlled points of entanglement, and other previously unobtainable layouts. Furthermore, the simultaneous, coordinated assembly of additional structures can enhance the structural stability and drive the motion of extended features in these systems. The resulting 3D mesostructures, demonstrated in a diverse set of more than 40 different examples with feature sizes from micrometers to centimeters, offer unique possibilities in device design. A 3D spiral inductor for near-field communication represents an example where these ideas enable enhanced quality (Q) factors and broader working angles compared to those of conventional 2D counterparts. PMID:27679820

A Modified Kinematic Model of Neutral and Ionized Gas in Galactic Center

NASA Astrophysics Data System (ADS)

Krishnarao, Dhanesh; Benjamin, Robert A.; Haffner, L. Matthew

2018-01-01

Gas near the center of the Milky Way is very complex across all phases (cold, warm, neutral, ionized, atomic, molecular, etc.) and shows strong observational evidence for warping, lopsided orientations and strongly non-circular kinematics. Historically, the kinematic complexities were modeled with many discrete features involved with expulsive phenomena near Galactic Center. However, much of the observed emission can be explained with a single unified and smooth density structure when geometrical and perspective effects are accounted for. Here we present a new model for a tilted, elliptical disk of gas within the inner 2 kpc of Galactic center based on the series of models following Burton & Liszt (1978 - 1992, Papers I- V). Machine learning techniques such as the Histogram of Oriented Gradients image correlation statistic are used to optimize the geometry and kinematics of neutral and ionized gas in 3D observational space (position,position, velocity). The model successfully predicts emission from neutral gas as seen by HI (Hi4Pi) and explains anomalous ionized gas features in H-Alpha emission (Wisconsin H-Alpha Mapper) and UV absorption lines (Hubble Space Telescope - Space Telescope Imaging Spectrograph). The modeled distribution of this tilted gas disk along with its kinematics of elliptical x1 orbits can reveal new insight about the Galactic Bar, star formation, and high-velocity gas near Galactic Center and its relation with the Fermi Bubble.

Mechanical assembly of complex, 3D mesostructures from releasable multilayers of advanced materials

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

Yan, Zheng; Zhang, Fan; Liu, Fei

Capabilities for assembly of three-dimensional (3D) micro/nanostructures in advanced materials have important implications across a broad range of application areas, reaching nearly every class of microsystem technology. Approaches that rely on the controlled, compressive buckling of 2D precursors are promising because of their demonstrated compatibility with the most sophisticated planar technologies, where materials include inorganic semiconductors, polymers, metals, and various heterogeneous combinations, spanning length scales from submicrometer to centimeter dimensions. We introduce a set of fabrication techniques and design concepts that bypass certain constraints set by the underlying physics and geometrical properties of the assembly processes associated with the originalmore » versions of these methods. In particular, the use of releasable, multilayer 2D precursors provides access to complex 3D topologies, including dense architectures with nested layouts, controlled points of entanglement, and other previously unobtainable layouts. Furthermore, the simultaneous, coordinated assembly of additional structures can enhance the structural stability and drive the motion of extended features in these systems. The resulting 3D mesostructures, demonstrated in a diverse set of more than 40 different examples with feature sizes from micrometers to centimeters, offer unique possibilities in device design. In conclusion, a 3D spiral inductor for near-field communication represents an example where these ideas enable enhanced quality ( Q) factors and broader working angles compared to those of conventional 2D counterparts.« less

Mechanical assembly of complex, 3D mesostructures from releasable multilayers of advanced materials

DOE PAGES

Yan, Zheng; Zhang, Fan; Liu, Fei; ...

2016-09-23

Capabilities for assembly of three-dimensional (3D) micro/nanostructures in advanced materials have important implications across a broad range of application areas, reaching nearly every class of microsystem technology. Approaches that rely on the controlled, compressive buckling of 2D precursors are promising because of their demonstrated compatibility with the most sophisticated planar technologies, where materials include inorganic semiconductors, polymers, metals, and various heterogeneous combinations, spanning length scales from submicrometer to centimeter dimensions. We introduce a set of fabrication techniques and design concepts that bypass certain constraints set by the underlying physics and geometrical properties of the assembly processes associated with the originalmore » versions of these methods. In particular, the use of releasable, multilayer 2D precursors provides access to complex 3D topologies, including dense architectures with nested layouts, controlled points of entanglement, and other previously unobtainable layouts. Furthermore, the simultaneous, coordinated assembly of additional structures can enhance the structural stability and drive the motion of extended features in these systems. The resulting 3D mesostructures, demonstrated in a diverse set of more than 40 different examples with feature sizes from micrometers to centimeters, offer unique possibilities in device design. In conclusion, a 3D spiral inductor for near-field communication represents an example where these ideas enable enhanced quality ( Q) factors and broader working angles compared to those of conventional 2D counterparts.« less

A fully-coupled discontinuous Galerkin spectral element method for two-phase flow in petroleum reservoirs

NASA Astrophysics Data System (ADS)

Taneja, Ankur; Higdon, Jonathan

2018-01-01

A high-order spectral element discontinuous Galerkin method is presented for simulating immiscible two-phase flow in petroleum reservoirs. The governing equations involve a coupled system of strongly nonlinear partial differential equations for the pressure and fluid saturation in the reservoir. A fully implicit method is used with a high-order accurate time integration using an implicit Rosenbrock method. Numerical tests give the first demonstration of high order hp spatial convergence results for multiphase flow in petroleum reservoirs with industry standard relative permeability models. High order convergence is shown formally for spectral elements with up to 8th order polynomials for both homogeneous and heterogeneous permeability fields. Numerical results are presented for multiphase fluid flow in heterogeneous reservoirs with complex geometric or geologic features using up to 11th order polynomials. Robust, stable simulations are presented for heterogeneous geologic features, including globally heterogeneous permeability fields, anisotropic permeability tensors, broad regions of low-permeability, high-permeability channels, thin shale barriers and thin high-permeability fractures. A major result of this paper is the demonstration that the resolution of the high order spectral element method may be exploited to achieve accurate results utilizing a simple cartesian mesh for non-conforming geological features. Eliminating the need to mesh to the boundaries of geological features greatly simplifies the workflow for petroleum engineers testing multiple scenarios in the face of uncertainty in the subsurface geology.

Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images.

PubMed

Al-Khafaji, Suhad Lateef; Jun Zhou; Zia, Ali; Liew, Alan Wee-Chung

2018-02-01

Spectral-spatial feature extraction is an important task in hyperspectral image processing. In this paper we propose a novel method to extract distinctive invariant features from hyperspectral images for registration of hyperspectral images with different spectral conditions. Spectral condition means images are captured with different incident lights, viewing angles, or using different hyperspectral cameras. In addition, spectral condition includes images of objects with the same shape but different materials. This method, which is named spectral-spatial scale invariant feature transform (SS-SIFT), explores both spectral and spatial dimensions simultaneously to extract spectral and geometric transformation invariant features. Similar to the classic SIFT algorithm, SS-SIFT consists of keypoint detection and descriptor construction steps. Keypoints are extracted from spectral-spatial scale space and are detected from extrema after 3D difference of Gaussian is applied to the data cube. Two descriptors are proposed for each keypoint by exploring the distribution of spectral-spatial gradient magnitude in its local 3D neighborhood. The effectiveness of the SS-SIFT approach is validated on images collected in different light conditions, different geometric projections, and using two hyperspectral cameras with different spectral wavelength ranges and resolutions. The experimental results show that our method generates robust invariant features for spectral-spatial image matching.

4U 1626-67 as Seen by Suzaku Before and After the 2008 Torque Reversal

NASA Technical Reports Server (NTRS)

Camero-Arranz, A.; Pottschmidt, K.; Finger, M. H.; Ikhsanov, N. R.; Wilson-Hodge, C. A.; Marcu, D. M.

2012-01-01

Aims. The accretion-powered pulsar 4U 1626-67 experienced a new torque reversal at the beginning of 2008, after about 18 years of steadily spinning down. The main goal of the present work is to study this recent torque reversal that occurred in 2008 February. Methods. We present a spectral analysis of this source using two pointed observations performed by Suzaku in 2006 March and in 2010 September. Results. We confirm with Suzaku the presence of a strong emission-line complex centered on 1 keV, with the strongest line being the hydrogen-like Ne Lya at 1.025(3) keV. We were able to resolve this complex with up to seven emission lines. A dramatic increase of the intensity of the Ne Lya line after the 2008 torque reversal occurred, with the equivalent width of this line reaching almost the same value measured by ASCA in 1993. We also report on the detection of a cyclotron line feature centered at approximately 37 keV. In spite of the fact that an increase of the X-ray luminosity (0.5-100keV) of a factor of approximately 2.8 occurred between these two observations, no significant change in the energy of the cyclotron line feature was observed. However, the intensity of the approximately 1 keV line complex increased by an overall factor of approximately 8. Conclusions. Our results favor a scenario in which the neutron star in 4U 1626-67 accretes material from a geometrically thin disk during both the spin-up and spin-down phases.

High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV) Technology

PubMed Central

Torres-Sánchez, Jorge; López-Granados, Francisca; Serrano, Nicolás; Arquero, Octavio; Peña, José M.

2015-01-01

The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees as geometric solids, which produce inconsistent results. As an alternative, this work presents an innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: 1) generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV) technology and 2) use of object-based image analysis techniques. Our UAV-based procedure produced successful results both in single-tree and in tree-row plantations, reporting up to 97% accuracy on area quantification and minimal deviations compared to in-field estimations of tree heights and crown volumes. The maps generated could be used to understand the linkages between tree grown and field-related factors or to optimize crop management operations in the context of precision agriculture with relevant agro-environmental implications. PMID:26107174

High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV) Technology.

PubMed

Torres-Sánchez, Jorge; López-Granados, Francisca; Serrano, Nicolás; Arquero, Octavio; Peña, José M

2015-01-01

The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees as geometric solids, which produce inconsistent results. As an alternative, this work presents an innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: 1) generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV) technology and 2) use of object-based image analysis techniques. Our UAV-based procedure produced successful results both in single-tree and in tree-row plantations, reporting up to 97% accuracy on area quantification and minimal deviations compared to in-field estimations of tree heights and crown volumes. The maps generated could be used to understand the linkages between tree grown and field-related factors or to optimize crop management operations in the context of precision agriculture with relevant agro-environmental implications.

Delineation and geometric modeling of road networks

NASA Astrophysics Data System (ADS)

Poullis, Charalambos; You, Suya

In this work we present a novel vision-based system for automatic detection and extraction of complex road networks from various sensor resources such as aerial photographs, satellite images, and LiDAR. Uniquely, the proposed system is an integrated solution that merges the power of perceptual grouping theory (Gabor filtering, tensor voting) and optimized segmentation techniques (global optimization using graph-cuts) into a unified framework to address the challenging problems of geospatial feature detection and classification. Firstly, the local precision of the Gabor filters is combined with the global context of the tensor voting to produce accurate classification of the geospatial features. In addition, the tensorial representation used for the encoding of the data eliminates the need for any thresholds, therefore removing any data dependencies. Secondly, a novel orientation-based segmentation is presented which incorporates the classification of the perceptual grouping, and results in segmentations with better defined boundaries and continuous linear segments. Finally, a set of gaussian-based filters are applied to automatically extract centerline information (magnitude, width and orientation). This information is then used for creating road segments and transforming them to their polygonal representations.

Modeling ultrasound propagation through material of increasing geometrical complexity.

PubMed

Odabaee, Maryam; Odabaee, Mostafa; Pelekanos, Matthew; Leinenga, Gerhard; Götz, Jürgen

2018-06-01

Ultrasound is increasingly being recognized as a neuromodulatory and therapeutic tool, inducing a broad range of bio-effects in the tissue of experimental animals and humans. To achieve these effects in a predictable manner in the human brain, the thick cancellous skull presents a problem, causing attenuation. In order to overcome this challenge, as a first step, the acoustic properties of a set of simple bone-modeling resin samples that displayed an increasing geometrical complexity (increasing step sizes) were analyzed. Using two Non-Destructive Testing (NDT) transducers, we found that Wiener deconvolution predicted the Ultrasound Acoustic Response (UAR) and attenuation caused by the samples. However, whereas the UAR of samples with step sizes larger than the wavelength could be accurately estimated, the prediction was not accurate when the sample had a smaller step size. Furthermore, a Finite Element Analysis (FEA) performed in ANSYS determined that the scattering and refraction of sound waves was significantly higher in complex samples with smaller step sizes compared to simple samples with a larger step size. Together, this reveals an interaction of frequency and geometrical complexity in predicting the UAR and attenuation. These findings could in future be applied to poro-visco-elastic materials that better model the human skull. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Microstructure-sensitive small fatigue crack growth assessment. Effect of strain ratio multiaxial strain state and geometric discontinuities

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

Castelluccio, Gustavo M.; McDowell, David L.

Fatigue crack initiation in the high cycle fatigue regime is strongly influenced by microstructural features. Research efforts have usually focused on predicting fatigue resistance against crack incubation without considering the early fatigue crack growth after encountering the first grain boundary. However, a significant fraction of the variability of the total fatigue life can be attributed to growth of small cracks as they encounter the first few grain boundaries, rather than crack formation within the first grain. Our paper builds on the framework previously developed by the authors to assess microstructure-sensitive small fatigue crack formation and early growth under complex loadingmore » conditions. Moreover, the scheme employs finite element simulations that explicitly render grains and crystallographic directions along with simulation of microstructurally small fatigue crack growth from grain to grain. The methodology employs a crystal plasticity algorithm in ABAQUS that was previously calibrated to study fatigue crack initiation in RR1000 Ni-base superalloy. Our work present simulations with non-zero applied mean strains and geometric discontinuities that were not previously considered for calibration. Results exhibit trends similar to those found in experiments for multiple metallic materials, conveying a consistent physical description of fatigue damage phenomena.« less

Origin of hyperbolicity in brain-to-brain coordination networks

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka; Andjelković, Miroslav; Šuvakov, Milovan

2018-02-01

Hyperbolicity or negative curvature of complex networks is the intrinsic geometric proximity of nodes in the graph metric space, which implies an improved network function. Here, we investigate hidden combinatorial geometries in brain-to-brain coordination networks arising through social communications. The networks originate from correlations among EEG signals previously recorded during spoken communications comprising of 14 individuals with 24 speaker-listener pairs. We find that the corresponding networks are delta-hyperbolic with delta_max=1 and the graph diameter D=3 in each brain. While the emergent hyperbolicity in the two-brain networks satisfies delta_max/D/2 < 1 and can be attributed to the topology of the subgraph formed around the cross-brains linking channels. We identify these subgraphs in each studied two-brain network and decompose their structure into simple geometric descriptors (triangles, tetrahedra and cliques of higher orders) that contribute to hyperbolicity. Considering topologies that exceed two separate brain networks as a measure of coordination synergy between the brains, we identify different neuronal correlation patterns ranging from weak coordination to super-brain structure. These topology features are in qualitative agreement with the listener’s self-reported ratings of own experience and quality of the speaker, suggesting that studies of the cross-brain connector networks can reveal new insight into the neural mechanisms underlying human social behavior.

Enhanced Seismic Imaging of Turbidite Deposits in Chicontepec Basin, Mexico

NASA Astrophysics Data System (ADS)

Chavez-Perez, S.; Vargas-Meleza, L.

2007-05-01

We test, as postprocessing tools, a combination of migration deconvolution and geometric attributes to attack the complex problems of reflector resolution and detection in migrated seismic volumes. Migration deconvolution has been empirically shown to be an effective approach for enhancing the illumination of migrated images, which are blurred versions of the subsurface reflectivity distribution, by decreasing imaging artifacts, improving spatial resolution, and alleviating acquisition footprint problems. We utilize migration deconvolution as a means to improve the quality and resolution of 3D prestack time migrated results from Chicontepec basin, Mexico, a very relevant portion of the producing onshore sector of Pemex, the Mexican petroleum company. Seismic data covers the Agua Fria, Coapechaca, and Tajin fields. It exhibits acquisition footprint problems, migration artifacts and a severe lack of resolution in the target area, where turbidite deposits need to be characterized between major erosional surfaces. Vertical resolution is about 35 m and the main hydrocarbon plays are turbidite beds no more than 60 m thick. We also employ geometric attributes (e.g., coherent energy and curvature), computed after migration deconvolution, to detect and map out depositional features, and help design development wells in the area. Results of this workflow show imaging enhancement and allow us to identify meandering channels and individual sand bodies, previously undistinguishable in the original seismic migrated images.

Optical versus tactile geometry measurement: alternatives or counterparts

NASA Astrophysics Data System (ADS)

Lehmann, Peter

2003-05-01

This contribution deals with measuring strategies and methods for the determination of several geometrical features, covering the surface micro-topography and the form of mechanical objects. The measuring principles used in optical surface metrology include optical focusing profilers, confocal point measuring and areal measuring sensors as well as interferometrical principles such as white light interferometry and speckle techniques. In comparison with stylus instruments optical techniques provide certain advantages such as a fast data acquisition, in-process applicability or contactless measurement. However, the frequency response characteristics of optical and tactile measurement differ significantly. In addition, optical sensors are commonly more influenced by critical geometrical conditions and optical properties of an object. For precise form measurement mechanical instruments dominate till now. One reason for this may be, that commonly the complete 360 degrees geometry of the measuring object has to be analyzed. Another point is that optical principles such as form measuring interferometry fail in cases of complex object geometry or rougher object surfaces. Other methods, e.g. fringe projection or digital holography, till now do not meet the accuracy demands of precision engineered workpieces. Hence, a combination of mechanical concepts and optical sensors represents an interesting potential for current and future measuring tasks, which require high accuracy and maximum flexibility.

Microstructure-sensitive small fatigue crack growth assessment. Effect of strain ratio multiaxial strain state and geometric discontinuities

DOE PAGES

Castelluccio, Gustavo M.; McDowell, David L.

2015-09-16

Fatigue crack initiation in the high cycle fatigue regime is strongly influenced by microstructural features. Research efforts have usually focused on predicting fatigue resistance against crack incubation without considering the early fatigue crack growth after encountering the first grain boundary. However, a significant fraction of the variability of the total fatigue life can be attributed to growth of small cracks as they encounter the first few grain boundaries, rather than crack formation within the first grain. Our paper builds on the framework previously developed by the authors to assess microstructure-sensitive small fatigue crack formation and early growth under complex loadingmore » conditions. Moreover, the scheme employs finite element simulations that explicitly render grains and crystallographic directions along with simulation of microstructurally small fatigue crack growth from grain to grain. The methodology employs a crystal plasticity algorithm in ABAQUS that was previously calibrated to study fatigue crack initiation in RR1000 Ni-base superalloy. Our work present simulations with non-zero applied mean strains and geometric discontinuities that were not previously considered for calibration. Results exhibit trends similar to those found in experiments for multiple metallic materials, conveying a consistent physical description of fatigue damage phenomena.« less

Rigorous diffraction analysis using geometrical theory of diffraction for future mask technology

NASA Astrophysics Data System (ADS)

Chua, Gek S.; Tay, Cho J.; Quan, Chenggen; Lin, Qunying

2004-05-01

Advanced lithographic techniques such as phase shift masks (PSM) and optical proximity correction (OPC) result in a more complex mask design and technology. In contrast to the binary masks, which have only transparent and nontransparent regions, phase shift masks also take into consideration transparent features with a different optical thickness and a modified phase of the transmitted light. PSM are well-known to show prominent diffraction effects, which cannot be described by the assumption of an infinitely thin mask (Kirchhoff approach) that is used in many commercial photolithography simulators. A correct prediction of sidelobe printability, process windows and linearity of OPC masks require the application of rigorous diffraction theory. The problem of aerial image intensity imbalance through focus with alternating Phase Shift Masks (altPSMs) is performed and compared between a time-domain finite-difference (TDFD) algorithm (TEMPEST) and Geometrical theory of diffraction (GTD). Using GTD, with the solution to the canonical problems, we obtained a relationship between the edge on the mask and the disturbance in image space. The main interest is to develop useful formulations that can be readily applied to solve rigorous diffraction for future mask technology. Analysis of rigorous diffraction effects for altPSMs using GTD approach will be discussed.

Protein 3D Structure and Electron Microscopy Map Retrieval Using 3D-SURFER2.0 and EM-SURFER.

PubMed

Han, Xusi; Wei, Qing; Kihara, Daisuke

2017-12-08

With the rapid growth in the number of solved protein structures stored in the Protein Data Bank (PDB) and the Electron Microscopy Data Bank (EMDB), it is essential to develop tools to perform real-time structure similarity searches against the entire structure database. Since conventional structure alignment methods need to sample different orientations of proteins in the three-dimensional space, they are time consuming and unsuitable for rapid, real-time database searches. To this end, we have developed 3D-SURFER and EM-SURFER, which utilize 3D Zernike descriptors (3DZD) to conduct high-throughput protein structure comparison, visualization, and analysis. Taking an atomic structure or an electron microscopy map of a protein or a protein complex as input, the 3DZD of a query protein is computed and compared with the 3DZD of all other proteins in PDB or EMDB. In addition, local geometrical characteristics of a query protein can be analyzed using VisGrid and LIGSITE CSC in 3D-SURFER. This article describes how to use 3D-SURFER and EM-SURFER to carry out protein surface shape similarity searches, local geometric feature analysis, and interpretation of the search results. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Haralick textural features on T2 -weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer.

PubMed

Gnep, Khémara; Fargeas, Auréline; Gutiérrez-Carvajal, Ricardo E; Commandeur, Frédéric; Mathieu, Romain; Ospina, Juan D; Rolland, Yan; Rohou, Tanguy; Vincendeau, Sébastien; Hatt, Mathieu; Acosta, Oscar; de Crevoisier, Renaud

2017-01-01

To explore the association between magnetic resonance imaging (MRI), including Haralick textural features, and biochemical recurrence following prostate cancer radiotherapy. In all, 74 patients with peripheral zone localized prostate adenocarcinoma underwent pretreatment 3.0T MRI before external beam radiotherapy. Median follow-up of 47 months revealed 11 patients with biochemical recurrence. Prostate tumors were segmented on T 2 -weighted sequences (T 2 -w) and contours were propagated onto the coregistered apparent diffusion coefficient (ADC) images. We extracted 140 image features from normalized T 2 -w and ADC images corresponding to first-order (n = 6), gradient-based (n = 4), and second-order Haralick textural features (n = 130). Four geometrical features (tumor diameter, perimeter, area, and volume) were also computed. Correlations between Gleason score and MRI features were assessed. Cox regression analysis and random survival forests (RSF) were performed to assess the association between MRI features and biochemical recurrence. Three T 2 -w and one ADC Haralick textural features were significantly correlated with Gleason score (P < 0.05). Twenty-eight T 2 -w Haralick features and all four geometrical features were significantly associated with biochemical recurrence (P < 0.05). The most relevant features were Haralick features T 2 -w contrast, T 2 -w difference variance, ADC median, along with tumor volume and tumor area (C-index from 0.76 to 0.82; P < 0.05). By combining these most powerful features in an RSF model, the obtained C-index was 0.90. T 2 -w Haralick features appear to be strongly associated with biochemical recurrence following prostate cancer radiotherapy. 3 J. Magn. Reson. Imaging 2017;45:103-117. © 2016 International Society for Magnetic Resonance in Medicine.

Integrating dimension reduction and out-of-sample extension in automated classification of ex vivo human patellar cartilage on phase contrast X-ray computed tomography.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Wismüller, Axel

2015-01-01

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns.

Experimental limits on the fidelity of adiabatic geometric phase gates in a single solid-state spin qubit

DOE PAGES

Zhang, Kai; Nusran, N. M.; Slezak, B. R.; ...

2016-05-17

While it is often thought that the geometric phase is less sensitive to fluctuations in the control fields, a very general feature of adiabatic Hamiltonians is the unavoidable dynamic phase that accompanies the geometric phase. The effect of control field noise during adiabatic geometric quantum gate operations has not been probed experimentally, especially in the canonical spin qubit system that is of interest for quantum information. We present measurement of the Berry phase and carry out adiabatic geometric phase gate in a single solid-state spin qubit associated with the nitrogen-vacancy center in diamond. We manipulate the spin qubit geometrically bymore » careful application of microwave radiation that creates an effective rotating magnetic field, and observe the resulting Berry phase signal via spin echo interferometry. Our results show that control field noise at frequencies higher than the spin echo clock frequency causes decay of the quantum phase, and degrades the fidelity of the geometric phase gate to the classical threshold after a few (~10) operations. This occurs in spite of the geometric nature of the state preparation, due to unavoidable dynamic contributions. In conclusion, we have carried out systematic analysis and numerical simulations to study the effects of the control field noise and imperfect driving waveforms on the quantum phase gate.« less

Experimental limits on the fidelity of adiabatic geometric phase gates in a single solid-state spin qubit

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

Zhang, Kai; Nusran, N. M.; Slezak, B. R.

While it is often thought that the geometric phase is less sensitive to fluctuations in the control fields, a very general feature of adiabatic Hamiltonians is the unavoidable dynamic phase that accompanies the geometric phase. The effect of control field noise during adiabatic geometric quantum gate operations has not been probed experimentally, especially in the canonical spin qubit system that is of interest for quantum information. We present measurement of the Berry phase and carry out adiabatic geometric phase gate in a single solid-state spin qubit associated with the nitrogen-vacancy center in diamond. We manipulate the spin qubit geometrically bymore » careful application of microwave radiation that creates an effective rotating magnetic field, and observe the resulting Berry phase signal via spin echo interferometry. Our results show that control field noise at frequencies higher than the spin echo clock frequency causes decay of the quantum phase, and degrades the fidelity of the geometric phase gate to the classical threshold after a few (~10) operations. This occurs in spite of the geometric nature of the state preparation, due to unavoidable dynamic contributions. In conclusion, we have carried out systematic analysis and numerical simulations to study the effects of the control field noise and imperfect driving waveforms on the quantum phase gate.« less

Functional aspects of metatarsal head shape in humans, apes, and Old World monkeys.

PubMed

Fernández, Peter J; Almécija, Sergio; Patel, Biren A; Orr, Caley M; Tocheri, Matthew W; Jungers, William L

2015-09-01

Modern human metatarsal heads are typically described as "dorsally domed," mediolaterally wide, and dorsally flat. Despite the apparent functional importance of these features in forefoot stability during bipedalism, the distinctiveness of this morphology has not been quantitatively evaluated within a broad comparative framework. In order to use these features to reconstruct fossil hominin locomotor behaviors with any confidence, their connection to human bipedalism should be validated through a comparative analysis of other primates with different locomotor behaviors and foot postures, including species with biomechanical demands potentially similar to those of bipedalism (e.g., terrestrial digitigrady). This study explores shape variation in the distal metatarsus among humans and other extant catarrhines using three-dimensional geometric morphometrics (3 DGM). Shape differences among species in metatarsal head morphology are well captured by the first two principal components of Procrustes shape coordinates, and these two components summarize most of the variance related to "dorsal doming" and "dorsal expansion." Multivariate statistical tests reveal significant differences among clades in overall shape, and humans are reliably distinguishable from other species by aspects of shape related to a greater degree of dorsal doming. Within quadrupeds, terrestrial species also trend toward more domed metatarsal heads, but not to the extent seen in humans. Certain aspects of distal metatarsus shape are likely related to habitual dorsiflexion of the metatarsophalangeal joints, but the total morphological pattern seen in humans is distinct. These comparative results indicate that this geometric morphometric approach is useful to characterize the complexity of metatarsal head morphology and will help clarify its relationship with function in fossil primates, including early hominins. Published by Elsevier Ltd.

2D and 3D characterization of pore defects in die cast AM60

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

Yang, Zhuofei; CanmetMATERIALS, 183 Longwood Road South, Hamilton L8P 0A5, Ontario Canada; Maurey, Alexandre

2016-04-15

The widespread application of die castings can be hampered due to the potential of large scale porosity to act as nucleation sites for fracture and fatigue. It is therefore important to develop robust approaches to the characterization of porosity providing parameters that can be linked to the material's mechanical properties. We have tackled this problem in a study of the AM60 die cast Mg alloy, using samples extracted from a prototype shock tower. A quantitative characterization of porosity has been undertaken, analyzing porosity in both 2D (using classical metallographic methods) and in 3D (using X-ray computed tomography (XCT)). Metallographic characterizationmore » results show that shrinkage pores and small gas pores can be distinguished based on their distinct geometrical features. Shrinkage pores are irregular with multiple arms, resulting in a form factor less than 0.4. In contrast, gas pores are generally more circular in shape yielding form factors larger than 0.6. XCT provides deeper insight into the shape of pores, although this understanding is limited by the resolution obtainable by laboratory based XCT. It also shows how 2D sectioning can produce artefacts as single complex pores are sectioned into multiple small pores. - Highlights: • Mg (e.g. AM60) die castings may contain large scale porosity that act as nucleation sites for fracture and fatigue • Quantitative characterization of porosity metallography (2D) and X-ray tomography (3D) is used • Shrinkage pores and small gas pores can be distinguished based on their distinct geometrical features. • Shrinkage pores are irregular giving a form factor < 0.4; gas pores are rounder with form factors > 0.6 • XCT enables pore visualization, although limited by the resolution obtainable by laboratory based XCT.« less

Geometric and potential dynamics interpretation of the optic ring resonator bistability

NASA Astrophysics Data System (ADS)

Chiangga, S.; Chittha, T.; Frank, T. D.

2015-07-01

The optical bistability is a fundamental nonlinear feature of the ring resonator. A geometric and potential dynamics interpretation of the bistability is given. Accordingly, the bistability of the nonlinear system is shown to be a consequence of geometric laws of vector calculus describing the resonator ring. In contrast, the so-called transcendental relations that have been obtained in the literature in order to describe the optical wave are interpreted in terms of potential dynamical systems. The proposed novel interpretation provides new insights into the nature of the ring resonator optical bistability. The fundamental work by Rukhlenko, Premaratne and Agrawal (2010) as well as a more recent study by Chiangga, Pitakwongsaporn, Frank and Yupapin (2013) are considered.

Geometry, packing, and evolutionary paths to increased multicellular size

NASA Astrophysics Data System (ADS)

Jacobeen, Shane; Graba, Elyes C.; Brandys, Colin G.; Day, Thomas C.; Ratcliff, William C.; Yunker, Peter J.

2018-05-01

The evolutionary transition to multicellularity transformed life on earth, heralding the evolution of large, complex organisms. Recent experiments demonstrated that laboratory-evolved multicellular "snowflake yeast" readily overcome the physical barriers that limit cluster size by modifying cellular geometry [Jacobeen et al., Nat. Phys. 14, 286 (2018), 10.1038/s41567-017-0002-y]. However, it is unclear why this route to large size is observed, rather than an evolved increase in intercellular bond strength. Here, we use a geometric model of the snowflake yeast growth form to examine the geometric efficiency of increasing size by modifying geometry and bond strength. We find that changing geometry is a far more efficient route to large size than evolving increased intercellular adhesion. In fact, increasing cellular aspect ratio is on average ˜13 times more effective than increasing bond strength at increasing the number of cells in a cluster. Modifying other geometric parameters, such as the geometric arrangement of mother and daughter cells, also had larger effects on cluster size than increasing bond strength. Simulations reveal that as cells reproduce, internal stress in the cluster increases rapidly; thus, increasing bond strength provides diminishing returns in cluster size. Conversely, as cells become more elongated, cellular packing density within the cluster decreases, which substantially decreases the rate of internal stress accumulation. This suggests that geometrically imposed physical constraints may have been a key early selective force guiding the emergence of multicellular complexity.

Geometrical Tile Design for Complex Neighborhoods

PubMed Central

Czeizler, Eugen; Kari, Lila

2009-01-01

Recent research has showed that tile systems are one of the most suitable theoretical frameworks for the spatial study and modeling of self-assembly processes, such as the formation of DNA and protein oligomeric structures. A Wang tile is a unit square, with glues on its edges, attaching to other tiles and forming larger and larger structures. Although quite intuitive, the idea of glues placed on the edges of a tile is not always natural for simulating the interactions occurring in some real systems. For example, when considering protein self-assembly, the shape of a protein is the main determinant of its functions and its interactions with other proteins. Our goal is to use geometric tiles, i.e., square tiles with geometrical protrusions on their edges, for simulating tiled paths (zippers) with complex neighborhoods, by ribbons of geometric tiles with simple, local neighborhoods. This paper is a step toward solving the general case of an arbitrary neighborhood, by proposing geometric tile designs that solve the case of a “tall” von Neumann neighborhood, the case of the f-shaped neighborhood, and the case of a 3 × 5 “filled” rectangular neighborhood. The techniques can be combined and generalized to solve the problem in the case of any neighborhood, centered at the tile of reference, and included in a 3 × (2k + 1) rectangle. PMID:19956398

Foliar and woody materials discriminated using terrestrial LiDAR in a mixed natural forest

NASA Astrophysics Data System (ADS)

Zhu, Xi; Skidmore, Andrew K.; Darvishzadeh, Roshanak; Niemann, K. Olaf; Liu, Jing; Shi, Yifang; Wang, Tiejun

2018-02-01

Separation of foliar and woody materials using remotely sensed data is crucial for the accurate estimation of leaf area index (LAI) and woody biomass across forest stands. In this paper, we present a new method to accurately separate foliar and woody materials using terrestrial LiDAR point clouds obtained from ten test sites in a mixed forest in Bavarian Forest National Park, Germany. Firstly, we applied and compared an adaptive radius near-neighbor search algorithm with a fixed radius near-neighbor search method in order to obtain both radiometric and geometric features derived from terrestrial LiDAR point clouds. Secondly, we used a random forest machine learning algorithm to classify foliar and woody materials and examined the impact of understory and slope on the classification accuracy. An average overall accuracy of 84.4% (Kappa = 0.75) was achieved across all experimental plots. The adaptive radius near-neighbor search method outperformed the fixed radius near-neighbor search method. The classification accuracy was significantly higher when the combination of both radiometric and geometric features was utilized. The analysis showed that increasing slope and understory coverage had a significant negative effect on the overall classification accuracy. Our results suggest that the utilization of the adaptive radius near-neighbor search method coupling both radiometric and geometric features has the potential to accurately discriminate foliar and woody materials from terrestrial LiDAR data in a mixed natural forest.

Combination of optically measured coordinates and displacements for quantitative investigation of complex objects

NASA Astrophysics Data System (ADS)

Andrae, Peter; Beeck, Manfred-Andreas; Jueptner, Werner P. O.; Nadeborn, Werner; Osten, Wolfgang

1996-09-01

Holographic interferometry makes it possible to measure high precision displacement data in the range of the wavelength of the used laser light. However, the determination of 3D- displacement vectors of objects with complex surfaces requires the measurement of 3D-object coordinates not only to consider local sensitivities but to distinguish between in-plane deformation, i.e. strains, and out-of-plane components, i.e. shears, too. To this purpose both the surface displacement and coordinates have to be combined and it is advantageous to make the data available for CAE- systems. The object surface has to be approximated analytically from the measured point cloud to generate a surface mesh. The displacement vectors can be assigned to the nodes of this surface mesh for visualization of the deformation of the object under test. They also can be compared to the results of FEM-calculations or can be used as boundary conditions for further numerical investigations. Here the 3D-object coordinates are measured in a separate topometric set-up using a modified fringe projection technique to acquire absolute phase values and a sophisticated geometrical model to map these phase data onto coordinates precisely. The determination of 3D-displacement vectors requires the measurement of several interference phase distributions for at least three independent sensitivity directions depending on the observation and illumination directions as well as the 3D-position of each measuring point. These geometric quantities have to be transformed into a reference coordinate system of the interferometric set-up in order to calculate the geometric matrix. The necessary transformation can be realized by means of a detection of object features in both data sets and a subsequent determination of the external camera orientation. This paper presents a consistent solution for the measurement and combination of shape and displacement data including their transformation into simulation systems. The described procedure will be demonstrated on an automotive component. Thus more accurate and effective measurement techniques make it possible to bring experimental and numerical displacement analysis closer.

Geometric Triangular Chiral Hexagon Crystal-Like Complexes Organization in Pathological Tissues Biological Collision Order

PubMed Central

Díaz, Jairo A.; Jaramillo, Natalia A.; Murillo, Mauricio F.

2007-01-01

The present study describes and documents self-assembly of geometric triangular chiral hexagon crystal like complex organizations (GTCHC) in human pathological tissues.The authors have found this architectural geometric expression at macroscopic and microscopic levels mainly in cancer processes. This study is based essentially on macroscopic and histopathologic analyses of 3000 surgical specimens: 2600 inflammatory lesions and 400 malignant tumours. Geometric complexes identified photographically at macroscopic level were located in the gross surgical specimen, and these areas were carefully dissected. Samples were taken to carry out histologic analysis. Based on the hypothesis of a collision genesis mechanism and because it is difficult to carry out an appropriate methodological observation in biological systems, the authors designed a model base on other dynamic systems to obtain indirect information in which a strong white flash wave light discharge, generated by an electronic device, hits over the lines of electrical conductance structured in helicoidal pattern. In their experimental model, the authors were able to reproduce and to predict polarity, chirality, helicoid geometry, triangular and hexagonal clusters through electromagnetic sequential collisions. They determined that similar events among constituents of extracelular matrix which drive and produce piezoelectric activity are responsible for the genesis of GTCHC complexes in pathological tissues. This research suggests that molecular crystals represented by triangular chiral hexagons derived from a collision-attraction event against collagen type I fibrils emerge at microscopic and macroscopic scales presenting a lateral assembly of each side of hypertrophy helicoid fibers, that represent energy flow in cooperative hierarchically chiral electromagnetic interaction in pathological tissues and arises as a geometry of the equilibrium in perturbed biological systems. Further interdisciplinary studies must be carried out to reproduce, manipulate and amplify their activity and probably use them as a base to develop new therapeutic strategies in cancer. PMID:18074008

An Experiment on Isomerism in Metal-Amino Acid Complexes.

ERIC Educational Resources Information Center

Harrison, R. Graeme; Nolan, Kevin B.

1982-01-01

Background information, laboratory procedures, and discussion of results are provided for syntheses of cobalt (III) complexes, I-III, illustrating three possible bonding modes of glycine to a metal ion (the complex cations II and III being linkage/geometric isomers). Includes spectrophotometric and potentiometric methods to distinguish among the…

Ab initio molecular orbital calculations on the associated complexes of lithium cyanide with ammonia

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

Mohandas, P.; Shivaglal, M.C.; Chandrasekhar, J.

Ab initio molecular orbital (MO) calculations with the 3-21G and 6-31G basis sets are carried out on a series of complexes of NH{sub 3} with Li{sup +}, C{triple_bond}N{sup -}, LiCN, and its isomer LiNC. The BSSE-corrected interaction energies, geometrical parameters, internal force constants, and harmonic vibrational frequencies are evaluated for 15 species. Complexes with trifurcated (C{sub 3v}) structures are calculated to be saddle points on the potential energy surfaces and have one imaginary frequency each. Calculated energies, geometrical parameters, internal force constants, and harmonic vibrational frequencies of the various species considered are discussed in terms of the nature of associationmore » of LiCN with ammonia. The vibrational frequencies of the relevant complexed species are compared with the experimental frequencies reported earlier for solutions of lithium cyanide in liquid ammonia. 40 refs., 1 fig., 4 tabs.« less

Laplace-Beltrami Eigenvalues and Topological Features of Eigenfunctions for Statistical Shape Analysis

PubMed Central

Reuter, Martin; Wolter, Franz-Erich; Shenton, Martha; Niethammer, Marc

2009-01-01

This paper proposes the use of the surface based Laplace-Beltrami and the volumetric Laplace eigenvalues and -functions as shape descriptors for the comparison and analysis of shapes. These spectral measures are isometry invariant and therefore allow for shape comparisons with minimal shape pre-processing. In particular, no registration, mapping, or remeshing is necessary. The discriminatory power of the 2D surface and 3D solid methods is demonstrated on a population of female caudate nuclei (a subcortical gray matter structure of the brain, involved in memory function, emotion processing, and learning) of normal control subjects and of subjects with schizotypal personality disorder. The behavior and properties of the Laplace-Beltrami eigenvalues and -functions are discussed extensively for both the Dirichlet and Neumann boundary condition showing advantages of the Neumann vs. the Dirichlet spectra in 3D. Furthermore, topological analyses employing the Morse-Smale complex (on the surfaces) and the Reeb graph (in the solids) are performed on selected eigenfunctions, yielding shape descriptors, that are capable of localizing geometric properties and detecting shape differences by indirectly registering topological features such as critical points, level sets and integral lines of the gradient field across subjects. The use of these topological features of the Laplace-Beltrami eigenfunctions in 2D and 3D for statistical shape analysis is novel. PMID:20161035

Geometric properties-dependent neural synchrony modulated by extracellular subthreshold electric field

NASA Astrophysics Data System (ADS)

Wei, Xile; Si, Kaili; Yi, Guosheng; Wang, Jiang; Lu, Meili

2016-07-01

In this paper, we use a reduced two-compartment neuron model to investigate the interaction between extracellular subthreshold electric field and synchrony in small world networks. It is observed that network synchronization is closely related to the strength of electric field and geometric properties of the two-compartment model. Specifically, increasing the electric field induces a gradual improvement in network synchrony, while increasing the geometric factor results in an abrupt decrease in synchronization of network. In addition, increasing electric field can make the network become synchronous from asynchronous when the geometric parameter is set to a given value. Furthermore, it is demonstrated that network synchrony can also be affected by the firing frequency and dynamical bifurcation feature of single neuron. These results highlight the effect of weak field on network synchrony from the view of biophysical model, which may contribute to further understanding the effect of electric field on network activity.

Modeling species-abundance relationships in multi-species collections

USGS Publications Warehouse

Peng, S.; Yin, Z.; Ren, H.; Guo, Q.

2003-01-01

Species-abundance relationship is one of the most fundamental aspects of community ecology. Since Motomura first developed the geometric series model to describe the feature of community structure, ecologists have developed many other models to fit the species-abundance data in communities. These models can be classified into empirical and theoretical ones, including (1) statistical models, i.e., negative binomial distribution (and its extension), log-series distribution (and its extension), geometric distribution, lognormal distribution, Poisson-lognormal distribution, (2) niche models, i.e., geometric series, broken stick, overlapping niche, particulate niche, random assortment, dominance pre-emption, dominance decay, random fraction, weighted random fraction, composite niche, Zipf or Zipf-Mandelbrot model, and (3) dynamic models describing community dynamics and restrictive function of environment on community. These models have different characteristics and fit species-abundance data in various communities or collections. Among them, log-series distribution, lognormal distribution, geometric series, and broken stick model have been most widely used.

Vision-Based UAV Flight Control and Obstacle Avoidance

DTIC Science & Technology

2006-01-01

denoted it by Vb = (Vb1, Vb2 , Vb3). Fig. 2 shows the block diagram of the proposed vision-based motion analysis and obstacle avoidance system. We denote...structure analysis often involve computation- intensive computer vision tasks, such as feature extraction and geometric modeling. Computation-intensive...First, we extract a set of features from each block. 2) Second, we compute the distance between these two sets of features. In conventional motion

System and Method for Modeling the Flow Performance Features of an Object

NASA Technical Reports Server (NTRS)

Jorgensen, Charles (Inventor); Ross, James (Inventor)

1997-01-01

The method and apparatus includes a neural network for generating a model of an object in a wind tunnel from performance data on the object. The network is trained from test input signals (e.g., leading edge flap position, trailing edge flap position, angle of attack, and other geometric configurations, and power settings) and test output signals (e.g., lift, drag, pitching moment, or other performance features). In one embodiment, the neural network training method employs a modified Levenberg-Marquardt optimization technique. The model can be generated 'real time' as wind tunnel testing proceeds. Once trained, the model is used to estimate performance features associated with the aircraft given geometric configuration and/or power setting input. The invention can also be applied in other similar static flow modeling applications in aerodynamics, hydrodynamics, fluid dynamics, and other such disciplines. For example, the static testing of cars, sails, and foils, propellers, keels, rudders, turbines, fins, and the like, in a wind tunnel, water trough, or other flowing medium.

Using Temporal Covariance of Motion and Geometric Features via Boosting for Human Fall Detection.

PubMed

Ali, Syed Farooq; Khan, Reamsha; Mahmood, Arif; Hassan, Malik Tahir; Jeon, And Moongu

2018-06-12

Fall induced damages are serious incidences for aged as well as young persons. A real-time automatic and accurate fall detection system can play a vital role in timely medication care which will ultimately help to decrease the damages and complications. In this paper, we propose a fast and more accurate real-time system which can detect people falling in videos captured by surveillance cameras. Novel temporal and spatial variance-based features are proposed which comprise the discriminatory motion, geometric orientation and location of the person. These features are used along with ensemble learning strategy of boosting with J48 and Adaboost classifiers. Experiments have been conducted on publicly available standard datasets including Multiple Cameras Fall ( with 2 classes and 3 classes ) and UR Fall Detection achieving percentage accuracies of 99.2, 99.25 and 99.0, respectively. Comparisons with nine state-of-the-art methods demonstrate the effectiveness of the proposed approach on both datasets.

Constraint-based stereo matching

NASA Technical Reports Server (NTRS)

Kuan, D. T.

1987-01-01

The major difficulty in stereo vision is the correspondence problem that requires matching features in two stereo images. Researchers describe a constraint-based stereo matching technique using local geometric constraints among edge segments to limit the search space and to resolve matching ambiguity. Edge segments are used as image features for stereo matching. Epipolar constraint and individual edge properties are used to determine possible initial matches between edge segments in a stereo image pair. Local edge geometric attributes such as continuity, junction structure, and edge neighborhood relations are used as constraints to guide the stereo matching process. The result is a locally consistent set of edge segment correspondences between stereo images. These locally consistent matches are used to generate higher-level hypotheses on extended edge segments and junctions to form more global contexts to achieve global consistency.

The Use of a Parametric Feature Based CAD System to Teach Introductory Engineering Graphics.

ERIC Educational Resources Information Center

Howell, Steven K.

1995-01-01

Describes the use of a parametric-feature-based computer-aided design (CAD) System, AutoCAD Designer, in teaching concepts of three dimensional geometrical modeling and design. Allows engineering graphics to go beyond the role of documentation and communication and allows an engineer to actually build a virtual prototype of a design idea and…

Virtual environments for scene of crime reconstruction and analysis

NASA Astrophysics Data System (ADS)

Howard, Toby L. J.; Murta, Alan D.; Gibson, Simon

2000-02-01

This paper describes research conducted in collaboration with Greater Manchester Police (UK), to evalute the utility of Virtual Environments for scene of crime analysis, forensic investigation, and law enforcement briefing and training. We present an illustrated case study of the construction of a high-fidelity virtual environment, intended to match a particular real-life crime scene as closely as possible. We describe and evaluate the combination of several approaches including: the use of the Manchester Scene Description Language for constructing complex geometrical models; the application of a radiosity rendering algorithm with several novel features based on human perceptual consideration; texture extraction from forensic photography; and experiments with interactive walkthroughs and large-screen stereoscopic display of the virtual environment implemented using the MAVERIK system. We also discuss the potential applications of Virtual Environment techniques in the Law Enforcement and Forensic communities.

High performance interactive graphics for shower reconstruction in HPC, the DELPHI barrel electromagnetic calorimeter

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

Stanescu, C.

1990-08-01

Complex software for shower reconstruction in DELPHI barrel electromagnetic calorimeter which deals, for each event, with great amounts of information, due to the high spatial resolution of this detector, needs powerful verification tools. An interactive graphics program, running on high performance graphics display system Whizzard 7555 from Megatek, was developed to display the logical steps in showers and their axes reconstruction. The program allows both operations on the image in real-time (rotation, translation and zoom) and the use of non-geometrical criteria to modify it (as the use of energy) thresholds for the representation of the elements that compound the showersmore » (or of the associated lego plots). For this purpose graphics objects associated to user parameters were defined. Instancing and modelling features of the native graphics library were extensively used.« less

Free-vibration acoustic resonance of a nonlinear elastic bar

NASA Astrophysics Data System (ADS)

Tarumi, Ryuichi; Oshita, Yoshihito

2011-02-01

Free-vibration acoustic resonance of a one-dimensional nonlinear elastic bar was investigated by direct analysis in the calculus of variations. The Lagrangian density of the bar includes a cubic term of the deformation gradient, which is responsible for both geometric and constitutive nonlinearities. By expanding the deformation function into a complex Fourier series, we derived the action integral in an analytic form and evaluated its stationary conditions numerically with the Ritz method for the first three resonant vibration modes. This revealed that the bar shows the following prominent nonlinear features: (i) amplitude dependence of the resonance frequency; (ii) symmetry breaking in the vibration pattern; and (iii) excitation of the high-frequency mode around nodal-like points. Stability of the resonant vibrations was also addressed in terms of a convex condition on the strain energy density.

A machine for the preliminary investigation of design features influencing the wear behaviour of knee prostheses.

PubMed

McGloughlin, T M; Murphy, D M; Kavanagh, A G

2004-01-01

Degradation of tibial inserts in vivo has been found to be multifactorial in nature, resulting in a complex interaction of many variables. A range of kinematic conditions occurs at the tibio-femoral interface, giving rise to various degrees of rolling and sliding at this interface. The movement of the tibio-femoral contact point may be an influential factor in the overall wear of ultra-high molecular weight polyethylene (UHMWPE) tibial components. As part of this study a three-station wear-test machine was designed and built to investigate the influence of rolling and sliding on the wear behaviour of specific design aspects of contemporary knee prostheses. Using the machine, it is possible to monitor the effect of various slide roll ratios on the performance of contemporary bearing designs from a geometrical and materials perspective.

An improved version of NCOREL: A computer program for 3-D nonlinear supersonic potential flow computations

NASA Technical Reports Server (NTRS)

Siclari, Michael J.

1988-01-01

A computer code called NCOREL (for Nonconical Relaxation) has been developed to solve for supersonic full potential flows over complex geometries. The method first solves for the conical at the apex and then marches downstream in a spherical coordinate system. Implicit relaxation techniques are used to numerically solve the full potential equation at each subsequent crossflow plane. Many improvements have been made to the original code including more reliable numerics for computing wing-body flows with multiple embedded shocks, inlet flow through simulation, wake model and entropy corrections. Line relaxation or approximate factorization schemes are optionally available. Improved internal grid generation using analytic conformal mappings, supported by a simple geometric Harris wave drag input that was originally developed for panel methods and internal geometry package are some of the new features.

Combining Statistical and Geometric Features for Colonic Polyp Detection in CTC Based on Multiple Kernel Learning

PubMed Central

Wang, Shijun; Yao, Jianhua; Petrick, Nicholas; Summers, Ronald M.

2010-01-01

Colon cancer is the second leading cause of cancer-related deaths in the United States. Computed tomographic colonography (CTC) combined with a computer aided detection system provides a feasible approach for improving colonic polyps detection and increasing the use of CTC for colon cancer screening. To distinguish true polyps from false positives, various features extracted from polyp candidates have been proposed. Most of these traditional features try to capture the shape information of polyp candidates or neighborhood knowledge about the surrounding structures (fold, colon wall, etc.). In this paper, we propose a new set of shape descriptors for polyp candidates based on statistical curvature information. These features called histograms of curvature features are rotation, translation and scale invariant and can be treated as complementing existing feature set. Then in order to make full use of the traditional geometric features (defined as group A) and the new statistical features (group B) which are highly heterogeneous, we employed a multiple kernel learning method based on semi-definite programming to learn an optimized classification kernel from the two groups of features. We conducted leave-one-patient-out test on a CTC dataset which contained scans from 66 patients. Experimental results show that a support vector machine (SVM) based on the combined feature set and the semi-definite optimization kernel achieved higher FROC performance compared to SVMs using the two groups of features separately. At a false positive per scan rate of 5, the sensitivity of the SVM using the combined features improved from 0.77 (Group A) and 0.73 (Group B) to 0.83 (p ≤ 0.01). PMID:20953299

Assessing future vent opening locations at the Somma-Vesuvio volcanic complex: 1. A new information geodatabase with uncertainty characterizations

NASA Astrophysics Data System (ADS)

Tadini, A.; Bisson, M.; Neri, A.; Cioni, R.; Bevilacqua, A.; Aspinall, W. P.

2017-06-01

This study presents new and revised data sets about the spatial distribution of past volcanic vents, eruptive fissures, and regional/local structures of the Somma-Vesuvio volcanic system (Italy). The innovative features of the study are the identification and quantification of important sources of uncertainty affecting interpretations of the data sets. In this regard, the spatial uncertainty of each feature is modeled by an uncertainty area, i.e., a geometric element typically represented by a polygon drawn around points or lines. The new data sets have been assembled as an updatable geodatabase that integrates and complements existing databases for Somma-Vesuvio. The data are organized into 4 data sets and stored as 11 feature classes (points and lines for feature locations and polygons for the associated uncertainty areas), totaling more than 1700 elements. More specifically, volcanic vent and eruptive fissure elements are subdivided into feature classes according to their associated eruptive styles: (i) Plinian and sub-Plinian eruptions (i.e., large- or medium-scale explosive activity); (ii) violent Strombolian and continuous ash emission eruptions (i.e., small-scale explosive activity); and (iii) effusive eruptions (including eruptions from both parasitic vents and eruptive fissures). Regional and local structures (i.e., deep faults) are represented as linear feature classes. To support interpretation of the eruption data, additional data sets are provided for Somma-Vesuvio geological units and caldera morphological features. In the companion paper, the data presented here, and the associated uncertainties, are used to develop a first vent opening probability map for the Somma-Vesuvio caldera, with specific attention focused on large or medium explosive events.

Manifold regularized multitask learning for semi-supervised multilabel image classification.

PubMed

Luo, Yong; Tao, Dacheng; Geng, Bo; Xu, Chao; Maybank, Stephen J

2013-02-01

It is a significant challenge to classify images with multiple labels by using only a small number of labeled samples. One option is to learn a binary classifier for each label and use manifold regularization to improve the classification performance by exploring the underlying geometric structure of the data distribution. However, such an approach does not perform well in practice when images from multiple concepts are represented by high-dimensional visual features. Thus, manifold regularization is insufficient to control the model complexity. In this paper, we propose a manifold regularized multitask learning (MRMTL) algorithm. MRMTL learns a discriminative subspace shared by multiple classification tasks by exploiting the common structure of these tasks. It effectively controls the model complexity because different tasks limit one another's search volume, and the manifold regularization ensures that the functions in the shared hypothesis space are smooth along the data manifold. We conduct extensive experiments, on the PASCAL VOC'07 dataset with 20 classes and the MIR dataset with 38 classes, by comparing MRMTL with popular image classification algorithms. The results suggest that MRMTL is effective for image classification.

Dynamic ruptures on faults of complex geometry: insights from numerical simulations, from large-scale curvature to small-scale fractal roughness

NASA Astrophysics Data System (ADS)

Ulrich, T.; Gabriel, A. A.

2016-12-01

The geometry of faults is subject to a large degree of uncertainty. As buried structures being not directly observable, their complex shapes may only be inferred from surface traces, if available, or through geophysical methods, such as reflection seismology. As a consequence, most studies aiming at assessing the potential hazard of faults rely on idealized fault models, based on observable large-scale features. Yet, real faults are known to be wavy at all scales, their geometric features presenting similar statistical properties from the micro to the regional scale. The influence of roughness on the earthquake rupture process is currently a driving topic in the computational seismology community. From the numerical point of view, rough faults problems are challenging problems that require optimized codes able to run efficiently on high-performance computing infrastructure and simultaneously handle complex geometries. Physically, simulated ruptures hosted by rough faults appear to be much closer to source models inverted from observation in terms of complexity. Incorporating fault geometry on all scales may thus be crucial to model realistic earthquake source processes and to estimate more accurately seismic hazard. In this study, we use the software package SeisSol, based on an ADER-Discontinuous Galerkin scheme, to run our numerical simulations. SeisSol allows solving the spontaneous dynamic earthquake rupture problem and the wave propagation problem with high-order accuracy in space and time efficiently on large-scale machines. In this study, the influence of fault roughness on dynamic rupture style (e.g. onset of supershear transition, rupture front coherence, propagation of self-healing pulses, etc) at different length scales is investigated by analyzing ruptures on faults of varying roughness spectral content. In particular, we investigate the existence of a minimum roughness length scale in terms of rupture inherent length scales below which the rupture ceases to be sensible. Finally, the effect of fault geometry on ground-motions, in the near-field, is considered. Our simulations feature a classical linear slip weakening on the fault and a viscoplastic constitutive model off the fault. The benefits of using a more elaborate fast velocity-weakening friction law will also be considered.

Geometry of modified release formulations during dissolution--influence on performance of dosage forms with diclofenac sodium.

PubMed

Dorożyński, Przemysław; Kulinowski, Piotr; Jamróz, Witold; Juszczyk, Ewelina

2014-12-30

The objectives of the work included: presentation of magnetic resonance imaging (MRI) and fractal analysis based approach to comparison of dosage forms of different composition, structure, and assessment of the influence of the compositional factors i.e., matrix type, excipients etc., on properties and performance of the dosage form during drug dissolution. The work presents the first attempt to compare MRI data obtained for tablet formulations of different composition and characterized by distinct differences in hydration and drug dissolution mechanisms. The main difficulty, in such a case stems from differences in hydration behavior and tablet's geometry i.e., swelling, cracking, capping etc. A novel approach to characterization of matrix systems i.e., quantification of changes of geometrical complexity of the matrix shape during drug dissolution has been developed. Using three chosen commercial modified release tablet formulations with diclofenac sodium we present the method of parameterization of their geometrical complexity on the base of fractal analysis. The main result of the study is the correlation between the hydrating tablet behavior and drug dissolution - the increase of geometrical complexity expressed as fractal dimension relates to the increased variability of drug dissolution results. Copyright © 2014 Elsevier B.V. All rights reserved.

Estimating the volume of glacial ice on Mars: Geographic and geometric constraints on concentric crater fill, lineated valley fill, and lobate debris aprons along the Martian dichotomy boundary

NASA Astrophysics Data System (ADS)

Fassett, C.; Levy, J.; Head, J.

2013-09-01

Landforms inferred to have formed from glacial processes are abundant on Mars and include features such as concentric crater fill (CCF), lobate debris aprons (LDA), and lineated valley fill (LVF). Here, we present new mapping of the spatial extent of these landforms derived from CTX and THEMIS VIS image data, and new geometric constraints on the volume of glaciogenic fill material present in concentric crater fill deposits.

Assembly of objects with not fully predefined shapes

NASA Technical Reports Server (NTRS)

Arlotti, M. A.; Dimartino, V.

1989-01-01

An assembly problem in a non-deterministic environment, i.e., where parts to be assembled have unknown shape, size and location, is described. The only knowledge used by the robot to perform the assembly operation is given by a connectivity rule and geometrical constraints concerning parts. Once a set of geometrical features of parts has been extracted by a vision system, applying such a rule allows the dtermination of the composition sequence. A suitable sensory apparatus allows the control the whole operation.

Geometric morphometric analysis of allometric variation in the mandibular morphology of the hominids of Atapuerca, Sima de los Huesos site.

PubMed

Rosas, Antonio; Bastir, Markus

2004-06-01

Allometry is an important factor of morphological integration that contributes to the organization of the phenotype and its variation. Variation in the allometric shape of the mandible is particularly important in hominid evolution because the mandible carries important taxonomic traits. Some of these traits are known to covary with size, particularly the retromolar space, symphyseal curvature, and position of the mental foramen. The mandible is a well studied system in the context of the evolutionary development of complex morphological structures because it is composed of different developmental units that are integrated within a single bone. In the present study, we investigated the allometric variation of two important developmental units that are separated by the inferior nerve (a branch of CN V3). We tested the null hypothesis that there would be no difference in allometric variation between the two components. Procrustes-based geometric morphometrics of 20 two-dimensional (2D) landmarks were analyzed by multivariate regressions of shape on size in samples from 121 humans, 48 chimpanzees, and 50 gorillas (all recent specimens), eight fossil hominids from Atapuerca, Sima de los Huesos (AT-SH), and 17 Neandertals. The findings show that in all of the examined species, there was significantly greater allometric variation in the supra-nerve unit than in the infra-nerve unit. The formation of the retromolar space exhibited an allometric relationship with the supra-nerve unit in all of the species studied. The formation of the chin-like morphology is an "apodynamic" feature of the infra-nerve unit in the AT-SH hominids. The results of this study support the hypothesis that allometry contributes to the organization of variation in complex morphological structures. Copyright 2004 Wiley-Liss, Inc.

A comprehensive pipeline for multi-resolution modeling of the mitral valve: Validation, computational efficiency, and predictive capability.

PubMed

Drach, Andrew; Khalighi, Amir H; Sacks, Michael S

2018-02-01

Multiple studies have demonstrated that the pathological geometries unique to each patient can affect the durability of mitral valve (MV) repairs. While computational modeling of the MV is a promising approach to improve the surgical outcomes, the complex MV geometry precludes use of simplified models. Moreover, the lack of complete in vivo geometric information presents significant challenges in the development of patient-specific computational models. There is thus a need to determine the level of detail necessary for predictive MV models. To address this issue, we have developed a novel pipeline for building attribute-rich computational models of MV with varying fidelity directly from the in vitro imaging data. The approach combines high-resolution geometric information from loaded and unloaded states to achieve a high level of anatomic detail, followed by mapping and parametric embedding of tissue attributes to build a high-resolution, attribute-rich computational models. Subsequent lower resolution models were then developed and evaluated by comparing the displacements and surface strains to those extracted from the imaging data. We then identified the critical levels of fidelity for building predictive MV models in the dilated and repaired states. We demonstrated that a model with a feature size of about 5 mm and mesh size of about 1 mm was sufficient to predict the overall MV shape, stress, and strain distributions with high accuracy. However, we also noted that more detailed models were found to be needed to simulate microstructural events. We conclude that the developed pipeline enables sufficiently complex models for biomechanical simulations of MV in normal, dilated, repaired states. Copyright © 2017 John Wiley & Sons, Ltd.

Recognizing visual focus of attention from head pose in natural meetings.

PubMed

Ba, Sileye O; Odobez, Jean-Marc

2009-02-01

We address the problem of recognizing the visual focus of attention (VFOA) of meeting participants based on their head pose. To this end, the head pose observations are modeled using a Gaussian mixture model (GMM) or a hidden Markov model (HMM) whose hidden states correspond to the VFOA. The novelties of this paper are threefold. First, contrary to previous studies on the topic, in our setup, the potential VFOA of a person is not restricted to other participants only. It includes environmental targets as well (a table and a projection screen), which increases the complexity of the task, with more VFOA targets spread in the pan as well as tilt gaze space. Second, we propose a geometric model to set the GMM or HMM parameters by exploiting results from cognitive science on saccadic eye motion, which allows the prediction of the head pose given a gaze target. Third, an unsupervised parameter adaptation step not using any labeled data is proposed, which accounts for the specific gazing behavior of each participant. Using a publicly available corpus of eight meetings featuring four persons, we analyze the above methods by evaluating, through objective performance measures, the recognition of the VFOA from head pose information obtained either using a magnetic sensor device or a vision-based tracking system. The results clearly show that in such complex but realistic situations, the VFOA recognition performance is highly dependent on how well the visual targets are separated for a given meeting participant. In addition, the results show that the use of a geometric model with unsupervised adaptation achieves better results than the use of training data to set the HMM parameters.

Fast non-Abelian geometric gates via transitionless quantum driving.

PubMed

Zhang, J; Kyaw, Thi Ha; Tong, D M; Sjöqvist, Erik; Kwek, Leong-Chuan

2015-12-21

A practical quantum computer must be capable of performing high fidelity quantum gates on a set of quantum bits (qubits). In the presence of noise, the realization of such gates poses daunting challenges. Geometric phases, which possess intrinsic noise-tolerant features, hold the promise for performing robust quantum computation. In particular, quantum holonomies, i.e., non-Abelian geometric phases, naturally lead to universal quantum computation due to their non-commutativity. Although quantum gates based on adiabatic holonomies have already been proposed, the slow evolution eventually compromises qubit coherence and computational power. Here, we propose a general approach to speed up an implementation of adiabatic holonomic gates by using transitionless driving techniques and show how such a universal set of fast geometric quantum gates in a superconducting circuit architecture can be obtained in an all-geometric approach. Compared with standard non-adiabatic holonomic quantum computation, the holonomies obtained in our approach tends asymptotically to those of the adiabatic approach in the long run-time limit and thus might open up a new horizon for realizing a practical quantum computer.

Fast non-Abelian geometric gates via transitionless quantum driving

PubMed Central

Zhang, J.; Kyaw, Thi Ha; Tong, D. M.; Sjöqvist, Erik; Kwek, Leong-Chuan

2015-01-01

A practical quantum computer must be capable of performing high fidelity quantum gates on a set of quantum bits (qubits). In the presence of noise, the realization of such gates poses daunting challenges. Geometric phases, which possess intrinsic noise-tolerant features, hold the promise for performing robust quantum computation. In particular, quantum holonomies, i.e., non-Abelian geometric phases, naturally lead to universal quantum computation due to their non-commutativity. Although quantum gates based on adiabatic holonomies have already been proposed, the slow evolution eventually compromises qubit coherence and computational power. Here, we propose a general approach to speed up an implementation of adiabatic holonomic gates by using transitionless driving techniques and show how such a universal set of fast geometric quantum gates in a superconducting circuit architecture can be obtained in an all-geometric approach. Compared with standard non-adiabatic holonomic quantum computation, the holonomies obtained in our approach tends asymptotically to those of the adiabatic approach in the long run-time limit and thus might open up a new horizon for realizing a practical quantum computer. PMID:26687580

The Delicate Balance of Preorganisation and Adaptability in Multiply Bonded Host-Guest Complexes.

PubMed

von Krbek, Larissa K S; Achazi, Andreas J; Schoder, Stefan; Gaedke, Marius; Biberger, Tobias; Paulus, Beate; Schalley, Christoph A

2017-02-24

Rigidity and preorganisation are believed to be required for high affinity in multiply bonded supramolecular complexes as they help reduce the entropic penalty of the binding event. This comes at the price that such rigid complexes are sensitive to small geometric mismatches. In marked contrast, nature uses more flexible building blocks. Thus, one might consider putting the rigidity/high-affinity notion to the test. Multivalent crown/ammonium complexes are ideal for this purpose as the monovalent interaction is well understood. A series of divalent complexes with different spacer lengths and rigidities has thus been analysed to correlate chelate cooperativities and spacer properties. Too long spacers reduce chelate cooperativity compared to exactly matching ones. However, in contrast to expectation, flexible guests bind with chelate cooperativities clearly exceeding those of rigid structures. Flexible spacers adapt to small geometric host-guest mismatches. Spacer-spacer interactions help overcome the entropic penalty of conformational fixation during binding and a delicate balance of preorganisation and adaptability is at play in multivalent complexes. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Global Geometric Properties of Martian Impact Craters: A Preliminary Assessment Using Mars Orbiter Laser Altimeter (MOLA)

NASA Technical Reports Server (NTRS)

Garvin, J. B.; Sakimoto, S. E. H.; Schnetzler, C.; Frawley, J. J.

1999-01-01

Impact craters on Mars have been used to provide fundamental insights into the properties of the martian crust, the role of volatiles, the relative age of the surface, and on the physics of impact cratering in the Solar System. Before the three-dimensional information provided by the Mars Orbiter Laser Altimeter (MOLA) instrument which is currently operating in Mars orbit aboard the Mars Global Surveyor (MGS), impact features were characterized morphologically using orbital images from Mariner 9 and Viking. Fresh-appearing craters were identified and measurements of their geometric properties were derived from various image-based methods. MOLA measurements can now provide a global sample of topographic cross-sections of martian impact features as small as approx. 2 km in diameter, to basin-scale features. We have previously examined MOLA cross-sections of Northern Hemisphere and North Polar Region impact features, but were unable to consider the global characteristics of these ubiquitous landforms. Here we present our preliminary assessment of the geometric properties of a globally-distributed sample of martian impact craters, most of which were sampled during the initial stages of the MGS mapping mission (i.e., the first 600 orbits). Our aim is to develop a framework for reconsidering theories concerning impact cratering in the martian environment. This first global analysis is focused upon topographically-fresh impact craters, defined here on the basis of MOLA topographic profiles that cross the central cavities of craters that can be observed in Viking-based MDIM global image mosaics. We have considered crater depths, rim heights, ejecta topologies, cross-sectional "shapes", and simple physical models for ejecta emplacement. To date (May, 1999), we have measured the geometric properties of over 1300 impact craters in the 2 to 350 km diameter size interval. A large fraction of these measured craters were sampled with cavity-center cross-sections during the first two months of MGS mapping. Many of these craters are included in Nadine Barlow's Catalogue of Martian Impact Craters, although we have treated simple craters smaller than about 7 km in greater detail than all previous investigations. Additional information is contained in the original extended abstract.

Integrating Dimension Reduction and Out-of-Sample Extension in Automated Classification of Ex Vivo Human Patellar Cartilage on Phase Contrast X-Ray Computed Tomography

PubMed Central

Nagarajan, Mahesh B.; Coan, Paola; Huber, Markus B.; Diemoz, Paul C.; Wismüller, Axel

2015-01-01

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns. PMID:25710875

A new unified framework for the early detection of the progression to diabetic retinopathy from fundus images.

PubMed

Leontidis, Georgios

2017-11-01

Human retina is a diverse and important tissue, vastly studied for various retinal and other diseases. Diabetic retinopathy (DR), a leading cause of blindness, is one of them. This work proposes a novel and complete framework for the accurate and robust extraction and analysis of a series of retinal vascular geometric features. It focuses on studying the registered bifurcations in successive years of progression from diabetes (no DR) to DR, in order to identify the vascular alterations. Retinal fundus images are utilised, and multiple experimental designs are employed. The framework includes various steps, such as image registration and segmentation, extraction of features, statistical analysis and classification models. Linear mixed models are utilised for making the statistical inferences, alongside the elastic-net logistic regression, boruta algorithm, and regularised random forests for the feature selection and classification phases, in order to evaluate the discriminative potential of the investigated features and also build classification models. A number of geometric features, such as the central retinal artery and vein equivalents, are found to differ significantly across the experiments and also have good discriminative potential. The classification systems yield promising results with the area under the curve values ranging from 0.821 to 0.968, across the four different investigated combinations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of organs' shapes with geometric and Zernike 3D moments.

PubMed

Broggio, D; Moignier, A; Ben Brahim, K; Gardumi, A; Grandgirard, N; Pierrat, N; Chea, M; Derreumaux, S; Desbrée, A; Boisserie, G; Aubert, B; Mazeron, J-J; Franck, D

2013-09-01

The morphological similarity of organs is studied with feature vectors based on geometric and Zernike 3D moments. It is particularly investigated if outliers and average models can be identified. For this purpose, the relative proximity to the mean feature vector is defined, principal coordinate and clustering analyses are also performed. To study the consistency and usefulness of this approach, 17 livers and 76 hearts voxel models from several sources are considered. In the liver case, models with similar morphological feature are identified. For the limited amount of studied cases, the liver of the ICRP male voxel model is identified as a better surrogate than the female one. For hearts, the clustering analysis shows that three heart shapes represent about 80% of the morphological variations. The relative proximity and clustering analysis rather consistently identify outliers and average models. For the two cases, identification of outliers and surrogate of average models is rather robust. However, deeper classification of morphological feature is subject to caution and can only be performed after cross analysis of at least two kinds of feature vectors. Finally, the Zernike moments contain all the information needed to re-construct the studied objects and thus appear as a promising tool to derive statistical organ shapes. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A Novel Face-on-Face Contact Method for Nonlinear Solid Mechanics

NASA Astrophysics Data System (ADS)

Wopschall, Steven Robert

The implicit solution to contact problems in nonlinear solid mechanics poses many difficulties. Traditional node-to-segment methods may suffer from locking and experience contact force chatter in the presence of sliding. More recent developments include mortar based methods, which resolve local contact interactions over face-pairs and feature a kinematic constraint in integral form that smoothes contact behavior, especially in the presence of sliding. These methods have been shown to perform well in the presence of geometric nonlinearities and are demonstratively more robust than node-to-segment methods. These methods are typically biased, however, interpolating contact tractions and gap equations on a designated non-mortar face, which leads to an asymmetry in the formulation. Another challenge is constraint enforcement. The general selection of the active set of constraints is brought with difficulty, often leading to non-physical solutions and easily resulting in missed face-pair interactions. Details on reliable constraint enforcement methods are lacking in the greater contact literature. This work presents an unbiased contact formulation utilizing a median-plane methodology. Up to linear polynomials are used for the discrete pressure representation and integral gap constraints are enforced using a novel subcycling procedure. This procedure reliably determines the active set of contact constraints leading to physical and kinematically admissible solutions void of heuristics and user action. The contact method presented herein successfully solves difficult quasi-static contact problems in the implicit computational setting. These problems feature finite deformations, material nonlinearity, and complex interface geometries, all of which are challenging characteristics for contact implementations and constraint enforcement algorithms. The subcycling procedure is a key feature of this method, handling active constraint selection for complex interfaces and mesh geometries.

Low-Rank Discriminant Embedding for Multiview Learning.

PubMed

Li, Jingjing; Wu, Yue; Zhao, Jidong; Lu, Ke

2017-11-01

This paper focuses on the specific problem of multiview learning where samples have the same feature set but different probability distributions, e.g., different viewpoints or different modalities. Since samples lying in different distributions cannot be compared directly, this paper aims to learn a latent subspace shared by multiple views assuming that the input views are generated from this latent subspace. Previous approaches usually learn the common subspace by either maximizing the empirical likelihood, or preserving the geometric structure. However, considering the complementarity between the two objectives, this paper proposes a novel approach, named low-rank discriminant embedding (LRDE), for multiview learning by taking full advantage of both sides. By further considering the duality between data points and features of multiview scene, i.e., data points can be grouped based on their distribution on features, while features can be grouped based on their distribution on the data points, LRDE not only deploys low-rank constraints on both sample level and feature level to dig out the shared factors across different views, but also preserves geometric information in both the ambient sample space and the embedding feature space by designing a novel graph structure under the framework of graph embedding. Finally, LRDE jointly optimizes low-rank representation and graph embedding in a unified framework. Comprehensive experiments in both multiview manner and pairwise manner demonstrate that LRDE performs much better than previous approaches proposed in recent literatures.

Geometrical approach to tumor growth.

PubMed

Escudero, Carlos

2006-08-01

Tumor growth has a number of features in common with a physical process known as molecular beam epitaxy. Both growth processes are characterized by the constraint of growth development to the body border, and surface diffusion of cells and particles at the growing edge. However, tumor growth implies an approximate spherical symmetry that makes necessary a geometrical treatment of the growth equations. The basic model was introduced in a former paper [C. Escudero, Phys. Rev. E 73, 020902(R) (2006)], and in the present work we extend our analysis and try to shed light on the possible geometrical principles that drive tumor growth. We present two-dimensional models that reproduce the experimental observations, and analyze the unexplored three-dimensional case, for which interesting conclusions on tumor growth are derived.

The ancient art of laying rope

NASA Astrophysics Data System (ADS)

Bohr, J.; Olsen, K.

2011-03-01

We describe a geometrical property of helical structures and show how it accounts for the early art of rope-making. Helices have a maximum number of rotations that can be added to them — and it is shown that this is a geometrical feature, not a material property. This geometrical insight explains why nearly identically appearing ropes can be made from very different materials and it is also the reason behind the unyielding nature of ropes. Maximally rotated strands behave as zero-twist structures. Hence, under strain they neither rotate in one direction nor in the other. The necessity for the rope to be stretched while being laid, known from Egyptian tomb scenes, follows straightforwardly, as does the function of the top, an old tool for laying ropes.

The Place of Mathematics.

ERIC Educational Resources Information Center

Brinkworth, Peter; Scott, Paul

2000-01-01

Discusses the geometric features of a building called the Alhambra in a city in the southernmost region of Australia called Granada. Describes plane patterns and analyzes those patterns while focusing on the plane symmetry. (ASK)

Macro-level safety analysis of pedestrian crashes in Shanghai, China.

PubMed

Wang, Xuesong; Yang, Junguang; Lee, Chris; Ji, Zhuoran; You, Shikai

2016-11-01

Pedestrian safety has become one of the most important issues in the field of traffic safety. This study aims at investigating the association between pedestrian crash frequency and various predictor variables including roadway, socio-economic, and land-use features. The relationships were modeled using the data from 263 Traffic Analysis Zones (TAZs) within the urban area of Shanghai - the largest city in China. Since spatial correlation exists among the zonal-level data, Bayesian Conditional Autoregressive (CAR) models with seven different spatial weight features (i.e. (a) 0-1 first order, adjacency-based, (b) common boundary-length-based, (c) geometric centroid-distance-based, (d) crash-weighted centroid-distance-based, (e) land use type, adjacency-based, (f) land use intensity, adjacency-based, and (g) geometric centroid-distance-order) were developed to characterize the spatial correlations among TAZs. Model results indicated that the geometric centroid-distance-order spatial weight feature, which was introduced in macro-level safety analysis for the first time, outperformed all the other spatial weight features. Population was used as the surrogate for pedestrian exposure, and had a positive effect on pedestrian crashes. Other significant factors included length of major arterials, length of minor arterials, road density, average intersection spacing, percentage of 3-legged intersections, and area of TAZ. Pedestrian crashes were higher in TAZs with medium land use intensity than in TAZs with low and high land use intensity. Thus, higher priority should be given to TAZs with medium land use intensity to improve pedestrian safety. Overall, these findings can help transportation planners and managers understand the characteristics of pedestrian crashes and improve pedestrian safety. Copyright © 2016 Elsevier Ltd. All rights reserved.

Matching Aerial Images to 3D Building Models Using Context-Based Geometric Hashing

PubMed Central

Jung, Jaewook; Sohn, Gunho; Bang, Kiin; Wichmann, Andreas; Armenakis, Costas; Kada, Martin

2016-01-01

A city is a dynamic entity, which environment is continuously changing over time. Accordingly, its virtual city models also need to be regularly updated to support accurate model-based decisions for various applications, including urban planning, emergency response and autonomous navigation. A concept of continuous city modeling is to progressively reconstruct city models by accommodating their changes recognized in spatio-temporal domain, while preserving unchanged structures. A first critical step for continuous city modeling is to coherently register remotely sensed data taken at different epochs with existing building models. This paper presents a new model-to-image registration method using a context-based geometric hashing (CGH) method to align a single image with existing 3D building models. This model-to-image registration process consists of three steps: (1) feature extraction; (2) similarity measure; and matching, and (3) estimating exterior orientation parameters (EOPs) of a single image. For feature extraction, we propose two types of matching cues: edged corner features representing the saliency of building corner points with associated edges, and contextual relations among the edged corner features within an individual roof. A set of matched corners are found with given proximity measure through geometric hashing, and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on collinearity equations. The result shows that acceptable accuracy of EOPs of a single image can be achievable using the proposed registration approach as an alternative to a labor-intensive manual registration process. PMID:27338410

A stochastic-geometric model of soil variation in Pleistocene patterned ground

NASA Astrophysics Data System (ADS)

Lark, Murray; Meerschman, Eef; Van Meirvenne, Marc

2013-04-01

In this paper we examine the spatial variability of soil in parent material with complex spatial structure which arises from complex non-linear geomorphic processes. We show that this variability can be better-modelled by a stochastic-geometric model than by a standard Gaussian random field. The benefits of the new model are seen in the reproduction of features of the target variable which influence processes like water movement and pollutant dispersal. Complex non-linear processes in the soil give rise to properties with non-Gaussian distributions. Even under a transformation to approximate marginal normality, such variables may have a more complex spatial structure than the Gaussian random field model of geostatistics can accommodate. In particular the extent to which extreme values of the variable are connected in spatially coherent regions may be misrepresented. As a result, for example, geostatistical simulation generally fails to reproduce the pathways for preferential flow in an environment where coarse infill of former fluvial channels or coarse alluvium of braided streams creates pathways for rapid movement of water. Multiple point geostatistics has been developed to deal with this problem. Multiple point methods proceed by sampling from a set of training images which can be assumed to reproduce the non-Gaussian behaviour of the target variable. The challenge is to identify appropriate sources of such images. In this paper we consider a mode of soil variation in which the soil varies continuously, exhibiting short-range lateral trends induced by local effects of the factors of soil formation which vary across the region of interest in an unpredictable way. The trends in soil variation are therefore only apparent locally, and the soil variation at regional scale appears random. We propose a stochastic-geometric model for this mode of soil variation called the Continuous Local Trend (CLT) model. We consider a case study of soil formed in relict patterned ground with pronounced lateral textural variations arising from the presence of infilled ice-wedges of Pleistocene origin. We show how knowledge of the pedogenetic processes in this environment, along with some simple descriptive statistics, can be used to select and fit a CLT model for the apparent electrical conductivity (ECa) of the soil. We use the model to simulate realizations of the CLT process, and compare these with realizations of a fitted Gaussian random field. We show how statistics that summarize the spatial coherence of regions with small values of ECa, which are expected to have coarse texture and so larger saturated hydraulic conductivity, are better reproduced by the CLT model than by the Gaussian random field. This suggests that the CLT model could be used to generate an unlimited supply of training images to allow multiple point geostatistical simulation or prediction of this or similar variables.

Influence of stochastic geometric imperfections on the load-carrying behaviour of thin-walled structures using constrained random fields

NASA Astrophysics Data System (ADS)

Lauterbach, S.; Fina, M.; Wagner, W.

2018-04-01

Since structural engineering requires highly developed and optimized structures, the thickness dependency is one of the most controversially debated topics. This paper deals with stability analysis of lightweight thin structures combined with arbitrary geometrical imperfections. Generally known design guidelines only consider imperfections for simple shapes and loading, whereas for complex structures the lower-bound design philosophy still holds. Herein, uncertainties are considered with an empirical knockdown factor representing a lower bound of existing measurements. To fully understand and predict expected bearable loads, numerical investigations are essential, including geometrical imperfections. These are implemented into a stand-alone program code with a stochastic approach to compute random fields as geometric imperfections that are applied to nodes of the finite element mesh of selected structural examples. The stochastic approach uses the Karhunen-Loève expansion for the random field discretization. For this approach, the so-called correlation length l_c controls the random field in a powerful way. This parameter has a major influence on the buckling shape, and also on the stability load. First, the impact of the correlation length is studied for simple structures. Second, since most structures for engineering devices are more complex and combined structures, these are intensively discussed with the focus on constrained random fields for e.g. flange-web-intersections. Specific constraints for those random fields are pointed out with regard to the finite element model. Further, geometrical imperfections vanish where the structure is supported.

Performance improvement of ERP-based brain-computer interface via varied geometric patterns.

PubMed

Ma, Zheng; Qiu, Tianshuang

2017-12-01

Recently, many studies have been focusing on optimizing the stimulus of an event-related potential (ERP)-based brain-computer interface (BCI). However, little is known about the effectiveness when increasing the stimulus unpredictability. We investigated a new stimulus type of varied geometric pattern where both complexity and unpredictability of the stimulus are increased. The proposed and classical paradigms were compared in within-subject experiments with 16 healthy participants. Results showed that the BCI performance was significantly improved for the proposed paradigm, with an average online written symbol rate increasing by 138% comparing with that of the classical paradigm. Amplitudes of primary ERP components, such as N1, P2a, P2b, N2, were also found to be significantly enhanced with the proposed paradigm. In this paper, a novel ERP BCI paradigm with a new stimulus type of varied geometric pattern is proposed. By jointly increasing the complexity and unpredictability of the stimulus, the performance of an ERP BCI could be considerably improved.

Registration methods for nonblind watermark detection in digital cinema applications

NASA Astrophysics Data System (ADS)

Nguyen, Philippe; Balter, Raphaele; Montfort, Nicolas; Baudry, Severine

2003-06-01

Digital watermarking may be used to enforce copyright protection of digital cinema, by embedding in each projected movie an unique identifier (fingerprint). By identifying the source of illegal copies, watermarking will thus incite movie theatre managers to enforce copyright protection, in particular by preventing people from coming in with a handy cam. We propose here a non-blind watermark method to improve the watermark detection on very impaired sequences. We first present a study on the picture impairments caused by the projection on a screen, then acquisition with a handy cam. We show that images undergo geometric deformations, which are fully described by a projective geometry model. The sequence also undergoes spatial and temporal luminance variation. Based on this study and on the impairments models which follow, we propose a method to match the retrieved sequence to the original one. First, temporal registration is performed by comparing the average luminance variation on both sequences. To compensate for geometric transformations, we used paired points from both sequences, obtained by applying a feature points detector. The matching of the feature points then enables to retrieve the geometric transform parameters. Tests show that the watermark retrieval on rectified sequences is greatly improved.

Cognitive object recognition system (CORS)

NASA Astrophysics Data System (ADS)

Raju, Chaitanya; Varadarajan, Karthik Mahesh; Krishnamurthi, Niyant; Xu, Shuli; Biederman, Irving; Kelley, Troy

2010-04-01

We have developed a framework, Cognitive Object Recognition System (CORS), inspired by current neurocomputational models and psychophysical research in which multiple recognition algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based algorithms) are integrated to provide a comprehensive solution to object recognition and landmarking. Objects are defined as a combination of geons, corresponding to their simple parts, and the relations among the parts. However, those objects that are not easily decomposable into geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The unique interaction between these algorithms is a novel approach that combines the effectiveness of both algorithms and takes us closer to a generalized approach to object recognition. CORS allows recognition of objects through a larger range of poses using geometric primitives and performs well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon composition of an object allows image understanding and reasoning even with novel objects. With reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied environments. Feasibility of the CORS system was demonstrated with real stereo images captured from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans and other relevant landmarks in the indoor environment.

A mechanistic insight into the mechanical role of the stratum corneum during stretching and compression of the skin.

PubMed

Leyva-Mendivil, Maria F; Page, Anton; Bressloff, Neil W; Limbert, Georges

2015-09-01

The study of skin biophysics has largely been driven by consumer goods, biomedical and cosmetic industries which aim to design products that efficiently interact with the skin and/or modify its biophysical properties for health or cosmetic benefits. The skin is a hierarchical biological structure featuring several layers with their own distinct geometry and mechanical properties. Up to now, no computational models of the skin have simultaneously accounted for these geometrical and material characteristics to study their complex biomechanical interactions under particular macroscopic deformation modes. The goal of this study was, therefore, to develop a robust methodology combining histological sections of human skin, image-processing and finite element techniques to address fundamental questions about skin mechanics and, more particularly, about how macroscopic strains are transmitted and modulated through the epidermis and dermis. The work hypothesis was that, as skin deforms under macroscopic loads, the stratum corneum does not experience significant strains but rather folds/unfolds during skin extension/compression. A sample of fresh human mid-back skin was processed for wax histology. Sections were stained and photographed by optical microscopy. The multiple images were stitched together to produce a larger region of interest and segmented to extract the geometry of the stratum corneum, viable epidermis and dermis. From the segmented structures a 2D finite element mesh of the skin composite model was created and geometrically non-linear plane-strain finite element analyses were conducted to study the sensitivity of the model to variations in mechanical properties. The hybrid experimental-computational methodology has offered valuable insights into the simulated mechanics of the skin, and that of the stratum corneum in particular, by providing qualitative and quantitative information on strain magnitude and distribution. Through a complex non-linear interplay, the geometry and mechanical characteristics of the skin layers (and their relative balance), play a critical role in conditioning the skin mechanical response to macroscopic in-plane compression and extension. Topographical features of the skin surface such as furrows were shown to act as an efficient means to deflect, convert and redistribute strain-and so stress-within the stratum corneum, viable epidermis and dermis. Strain reduction and amplification phenomena were also observed and quantified. Despite the small thickness of the stratum corneum, its Young׳s modulus has a significant effect not only on the strain magnitude and directions within the stratum corneum layer but also on those of the underlying layers. This effect is reflected in the deformed shape of the skin surface in simulated compression and extension and is intrinsically linked to the rather complex geometrical characteristics of each skin layer. Moreover, if the Young׳s modulus of the viable epidermis is assumed to be reduced by a factor 12, the area of skin folding is likely to increase under skin compression. These results should be considered in the light of published computational models of the skin which, up to now, have ignored these characteristics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Recognition of Simple 3D Geometrical Objects under Partial Occlusion

NASA Astrophysics Data System (ADS)

Barchunova, Alexandra; Sommer, Gerald

In this paper we present a novel procedure for contour-based recognition of partially occluded three-dimensional objects. In our approach we use images of real and rendered objects whose contours have been deformed by a restricted change of the viewpoint. The preparatory part consists of contour extraction, preprocessing, local structure analysis and feature extraction. The main part deals with an extended construction and functionality of the classifier ensemble Adaptive Occlusion Classifier (AOC). It relies on a hierarchical fragmenting algorithm to perform a local structure analysis which is essential when dealing with occlusions. In the experimental part of this paper we present classification results for five classes of simple geometrical figures: prism, cylinder, half cylinder, a cube, and a bridge. We compare classification results for three classical feature extractors: Fourier descriptors, pseudo Zernike and Zernike moments.

Geometric facial comparisons in speed-check photographs.

PubMed

Buck, Ursula; Naether, Silvio; Kreutz, Kerstin; Thali, Michael

2011-11-01

In many cases, it is not possible to call the motorists to account for their considerable excess in speeding, because they deny being the driver on the speed-check photograph. An anthropological comparison of facial features using a photo-to-photo comparison can be very difficult depending on the quality of the photographs. One difficulty of that analysis method is that the comparison photographs of the presumed driver are taken with a different camera or camera lens and from a different angle than for the speed-check photo. To take a comparison photograph with exactly the same camera setup is almost impossible. Therefore, only an imprecise comparison of the individual facial features is possible. The geometry and position of each facial feature, for example the distances between the eyes or the positions of the ears, etc., cannot be taken into consideration. We applied a new method using 3D laser scanning, optical surface digitalization, and photogrammetric calculation of the speed-check photo, which enables a geometric comparison. Thus, the influence of the focal length and the distortion of the objective lens are eliminated and the precise position and the viewing direction of the speed-check camera are calculated. Even in cases of low-quality images or when the face of the driver is partly hidden, good results are delivered using this method. This new method, Geometric Comparison, is evaluated and validated in a prepared study which is described in this article.

Safety modeling of urban arterials in Shanghai, China.

PubMed

Wang, Xuesong; Fan, Tianxiang; Chen, Ming; Deng, Bing; Wu, Bing; Tremont, Paul

2015-10-01

Traffic safety on urban arterials is influenced by several key variables including geometric design features, land use, traffic volume, and travel speeds. This paper is an exploratory study of the relationship of these variables to safety. It uses a comparatively new method of measuring speeds by extracting GPS data from taxis operating on Shanghai's urban network. This GPS derived speed data, hereafter called Floating Car Data (FCD) was used to calculate average speeds during peak and off-peak hours, and was acquired from samples of 15,000+ taxis traveling on 176 segments over 18 major arterials in central Shanghai. Geometric design features of these arterials and surrounding land use characteristics were obtained by field investigation, and crash data was obtained from police reports. Bayesian inference using four different models, Poisson-lognormal (PLN), PLN with Maximum Likelihood priors (PLN-ML), hierarchical PLN (HPLN), and HPLN with Maximum Likelihood priors (HPLN-ML), was used to estimate crash frequencies. Results showed the HPLN-ML models had the best goodness-of-fit and efficiency, and models with ML priors yielded estimates with the lowest standard errors. Crash frequencies increased with increases in traffic volume. Higher average speeds were associated with higher crash frequencies during peak periods, but not during off-peak periods. Several geometric design features including average segment length of arterial, number of lanes, presence of non-motorized lanes, number of access points, and commercial land use, were positively related to crash frequencies. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Geometric View of Complex Trigonometric Functions

ERIC Educational Resources Information Center

Hammack, Richard

2007-01-01

Given that the sine and cosine functions of a real variable can be interpreted as the coordinates of points on the unit circle, the author of this article asks whether there is something similar for complex variables, and shows that indeed there is.

Advanced metrology by offline SEM data processing

NASA Astrophysics Data System (ADS)

Lakcher, Amine; Schneider, Loïc.; Le-Gratiet, Bertrand; Ducoté, Julien; Farys, Vincent; Besacier, Maxime

2017-06-01

Today's technology nodes contain more and more complex designs bringing increasing challenges to chip manufacturing process steps. It is necessary to have an efficient metrology to assess process variability of these complex patterns and thus extract relevant data to generate process aware design rules and to improve OPC models. Today process variability is mostly addressed through the analysis of in-line monitoring features which are often designed to support robust measurements and as a consequence are not always very representative of critical design rules. CD-SEM is the main CD metrology technique used in chip manufacturing process but it is challenged when it comes to measure metrics like tip to tip, tip to line, areas or necking in high quantity and with robustness. CD-SEM images contain a lot of information that is not always used in metrology. Suppliers have provided tools that allow engineers to extract the SEM contours of their features and to convert them into a GDS. Contours can be seen as the signature of the shape as it contains all the dimensional data. Thus the methodology is to use the CD-SEM to take high quality images then generate SEM contours and create a data base out of them. Contours are used to feed an offline metrology tool that will process them to extract different metrics. It was shown in two previous papers that it is possible to perform complex measurements on hotspots at different process steps (lithography, etch, copper CMP) by using SEM contours with an in-house offline metrology tool. In the current paper, the methodology presented previously will be expanded to improve its robustness and combined with the use of phylogeny to classify the SEM images according to their geometrical proximities.

A multiple-point geostatistical approach to quantifying uncertainty for flow and transport simulation in geologically complex environments

NASA Astrophysics Data System (ADS)

Cronkite-Ratcliff, C.; Phelps, G. A.; Boucher, A.

2011-12-01

In many geologic settings, the pathways of groundwater flow are controlled by geologic heterogeneities which have complex geometries. Models of these geologic heterogeneities, and consequently, their effects on the simulated pathways of groundwater flow, are characterized by uncertainty. Multiple-point geostatistics, which uses a training image to represent complex geometric descriptions of geologic heterogeneity, provides a stochastic approach to the analysis of geologic uncertainty. Incorporating multiple-point geostatistics into numerical models provides a way to extend this analysis to the effects of geologic uncertainty on the results of flow simulations. We present two case studies to demonstrate the application of multiple-point geostatistics to numerical flow simulation in complex geologic settings with both static and dynamic conditioning data. Both cases involve the development of a training image from a complex geometric description of the geologic environment. Geologic heterogeneity is modeled stochastically by generating multiple equally-probable realizations, all consistent with the training image. Numerical flow simulation for each stochastic realization provides the basis for analyzing the effects of geologic uncertainty on simulated hydraulic response. The first case study is a hypothetical geologic scenario developed using data from the alluvial deposits in Yucca Flat, Nevada. The SNESIM algorithm is used to stochastically model geologic heterogeneity conditioned to the mapped surface geology as well as vertical drill-hole data. Numerical simulation of groundwater flow and contaminant transport through geologic models produces a distribution of hydraulic responses and contaminant concentration results. From this distribution of results, the probability of exceeding a given contaminant concentration threshold can be used as an indicator of uncertainty about the location of the contaminant plume boundary. The second case study considers a characteristic lava-flow aquifer system in Pahute Mesa, Nevada. A 3D training image is developed by using object-based simulation of parametric shapes to represent the key morphologic features of rhyolite lava flows embedded within ash-flow tuffs. In addition to vertical drill-hole data, transient pressure head data from aquifer tests can be used to constrain the stochastic model outcomes. The use of both static and dynamic conditioning data allows the identification of potential geologic structures that control hydraulic response. These case studies demonstrate the flexibility of the multiple-point geostatistics approach for considering multiple types of data and for developing sophisticated models of geologic heterogeneities that can be incorporated into numerical flow simulations.

Adaptive multi-resolution 3D Hartree-Fock-Bogoliubov solver for nuclear structure

NASA Astrophysics Data System (ADS)

Pei, J. C.; Fann, G. I.; Harrison, R. J.; Nazarewicz, W.; Shi, Yue; Thornton, S.

2014-08-01

Background: Complex many-body systems, such as triaxial and reflection-asymmetric nuclei, weakly bound halo states, cluster configurations, nuclear fragments produced in heavy-ion fusion reactions, cold Fermi gases, and pasta phases in neutron star crust, are all characterized by large sizes and complex topologies in which many geometrical symmetries characteristic of ground-state configurations are broken. A tool of choice to study such complex forms of matter is an adaptive multi-resolution wavelet analysis. This method has generated much excitement since it provides a common framework linking many diversified methodologies across different fields, including signal processing, data compression, harmonic analysis and operator theory, fractals, and quantum field theory. Purpose: To describe complex superfluid many-fermion systems, we introduce an adaptive pseudospectral method for solving self-consistent equations of nuclear density functional theory in three dimensions, without symmetry restrictions. Methods: The numerical method is based on the multi-resolution and computational harmonic analysis techniques with a multi-wavelet basis. The application of state-of-the-art parallel programming techniques include sophisticated object-oriented templates which parse the high-level code into distributed parallel tasks with a multi-thread task queue scheduler for each multi-core node. The internode communications are asynchronous. The algorithm is variational and is capable of solving coupled complex-geometric systems of equations adaptively, with functional and boundary constraints, in a finite spatial domain of very large size, limited by existing parallel computer memory. For smooth functions, user-defined finite precision is guaranteed. Results: The new adaptive multi-resolution Hartree-Fock-Bogoliubov (HFB) solver madness-hfb is benchmarked against a two-dimensional coordinate-space solver hfb-ax that is based on the B-spline technique and a three-dimensional solver hfodd that is based on the harmonic-oscillator basis expansion. Several examples are considered, including the self-consistent HFB problem for spin-polarized trapped cold fermions and the Skyrme-Hartree-Fock (+BCS) problem for triaxial deformed nuclei. Conclusions: The new madness-hfb framework has many attractive features when applied to nuclear and atomic problems involving many-particle superfluid systems. Of particular interest are weakly bound nuclear configurations close to particle drip lines, strongly elongated and dinuclear configurations such as those present in fission and heavy-ion fusion, and exotic pasta phases that appear in neutron star crust.

The Transition from Complex Crater to Peak-Ring Basin on the Moon: New Observations from the Lunar Orbiter Laser Altimeter (LOLA) Instrument

NASA Technical Reports Server (NTRS)

Baker, David M. H.; Head, James W.; Fassett, Caleb I.; Kadish, Seth J.; Smith, Dave E.; Zuber, Maria T.; Neumann, Gregory A.

2012-01-01

Impact craters on planetary bodies transition with increasing size from simple, to complex, to peak-ring basins and finally to multi-ring basins. Important to understanding the relationship between complex craters with central peaks and multi-ring basins is the analysis of protobasins (exhibiting a rim crest and interior ring plus a central peak) and peak-ring basins (exhibiting a rim crest and an interior ring). New data have permitted improved portrayal and classification of these transitional features on the Moon. We used new 128 pixel/degree gridded topographic data from the Lunar Orbiter Laser Altimeter (LOLA) instrument onboard the Lunar Reconnaissance Orbiter, combined with image mosaics, to conduct a survey of craters >50 km in diameter on the Moon and to update the existing catalogs of lunar peak-ring basins and protobasins. Our updated catalog includes 17 peak-ring basins (rim-crest diameters range from 207 km to 582 km, geometric mean = 343 km) and 3 protobasins (137-170 km, geometric mean = 157 km). Several basins inferred to be multi-ring basins in prior studies (Apollo, Moscoviense, Grimaldi, Freundlich-Sharonov, Coulomb-Sarton, and Korolev) are now classified as peak-ring basins due to their similarities with lunar peak-ring basin morphologies and absence of definitive topographic ring structures greater than two in number. We also include in our catalog 23 craters exhibiting small ring-like clusters of peaks (50-205 km, geometric mean = 81 km); one (Humboldt) exhibits a rim-crest diameter and an interior morphology that may be uniquely transitional to the process of forming peak rings. Comparisons of the predictions of models for the formation of peak-ring basins with the characteristics of the new basin catalog for the Moon suggest that formation and modification of an interior melt cavity and nonlinear scaling of impact melt volume with crater diameter provide important controls on the development of peak rings. In particular, a power-law model of growth of an interior melt cavity with increasing crater diameter is consistent with power-law fits to the peak-ring basin data for the Moon and Mercury. We suggest that the relationship between the depth of melting and depth of the transient cavity offers a plausible control on the onset diameter and subsequent development of peak-ring basins and also multi-ring basins, which is consistent with both planetary gravitational acceleration and mean impact velocity being important in determining the onset of basin morphological forms on the terrestrial planets.

Looking at faces from different angles: Europeans fixate different features in Asian and Caucasian faces.

PubMed

Brielmann, Aenne A; Bülthoff, Isabelle; Armann, Regine

2014-07-01

Race categorization of faces is a fast and automatic process and is known to affect further face processing profoundly and at earliest stages. Whether processing of own- and other-race faces might rely on different facial cues, as indicated by diverging viewing behavior, is much under debate. We therefore aimed to investigate two open questions in our study: (1) Do observers consider information from distinct facial features informative for race categorization or do they prefer to gain global face information by fixating the geometrical center of the face? (2) Does the fixation pattern, or, if facial features are considered relevant, do these features differ between own- and other-race faces? We used eye tracking to test where European observers look when viewing Asian and Caucasian faces in a race categorization task. Importantly, in order to disentangle centrally located fixations from those towards individual facial features, we presented faces in frontal, half-profile and profile views. We found that observers showed no general bias towards looking at the geometrical center of faces, but rather directed their first fixations towards distinct facial features, regardless of face race. However, participants looked at the eyes more often in Caucasian faces than in Asian faces, and there were significantly more fixations to the nose for Asian compared to Caucasian faces. Thus, observers rely on information from distinct facial features rather than facial information gained by centrally fixating the face. To what extent specific features are looked at is determined by the face's race. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Graphical Representation of Complex Solutions of the Quadratic Equation in the "xy" Plane

ERIC Educational Resources Information Center

McDonald, Todd

2006-01-01

This paper presents a visual representation of complex solutions of quadratic equations in the xy plane. Rather than moving to the complex plane, students are able to experience a geometric interpretation of the solutions in the xy plane. I am also working on these types of representations with higher order polynomials with some success.

Robot Acting on Moving Bodies (RAMBO): Interaction with tumbling objects

NASA Technical Reports Server (NTRS)

Davis, Larry S.; Dementhon, Daniel; Bestul, Thor; Ziavras, Sotirios; Srinivasan, H. V.; Siddalingaiah, Madhu; Harwood, David

1989-01-01

Interaction with tumbling objects will become more common as human activities in space expand. Attempting to interact with a large complex object translating and rotating in space, a human operator using only his visual and mental capacities may not be able to estimate the object motion, plan actions or control those actions. A robot system (RAMBO) equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a tumbling object, is being developed. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations rearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enhancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using dynamic interpolations between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

How effective are geometric morphometric techniques for assessing functional shape variation? An example from the great ape temporomandibular joint.

PubMed

Terhune, Claire E

2013-08-01

Functional shape analyses have long relied on the use of shape ratios to test biomechanical hypotheses. This method is powerful because of the ease with which results are interpreted, but these techniques fall short in quantifying complex morphologies that may not have a strong biomechanical foundation but may still be functionally informative. In contrast, geometric morphometric methods are continually being adopted for quantifying complex shapes, but they tend to prove inadequate in functional analyses because they have little foundation in an explicit biomechanical framework. The goal of this study was to evaluate the intersection of these two methods using the great ape temporomandibular joint as a case study. Three-dimensional coordinates of glenoid fossa and mandibular condyle shape were collected using a Microscribe digitizer. Linear distances extracted from these landmarks were analyzed using a series of one-way ANOVAs; further, the landmark configurations were analyzed using geometric morphometric techniques. Results suggest that the two methods are broadly similar, although the geometric morphometric data allow for the identification of shape differences among taxa that were not immediately apparent in the univariate analyses. Furthermore, this study suggests several new approaches for translating these shape data into a biomechanical context by adjusting the data using a biomechanically relevant variable. Copyright © 2013 Wiley Periodicals, Inc.

Geometric state space uncertainty as a new type of uncertainty addressing disparity in ';emergent properties' between real and modeled systems

NASA Astrophysics Data System (ADS)

Montero, J. T.; Lintz, H. E.; Sharp, D.

2013-12-01

Do emergent properties that result from models of complex systems match emergent properties from real systems? This question targets a type of uncertainty that we argue requires more attention in system modeling and validation efforts. We define an ';emergent property' to be an attribute or behavior of a modeled or real system that can be surprising or unpredictable and result from complex interactions among the components of a system. For example, thresholds are common across diverse systems and scales and can represent emergent system behavior that is difficult to predict. Thresholds or other types of emergent system behavior can be characterized by their geometry in state space (where state space is the space containing the set of all states of a dynamic system). One way to expedite our growing mechanistic understanding of how emergent properties emerge from complex systems is to compare the geometry of surfaces in state space between real and modeled systems. Here, we present an index (threshold strength) that can quantify a geometric attribute of a surface in state space. We operationally define threshold strength as how strongly a surface in state space resembles a step or an abrupt transition between two system states. First, we validated the index for application in greater than three dimensions of state space using simulated data. Then, we demonstrated application of the index in measuring geometric state space uncertainty between a real system and a deterministic, modeled system. In particular, we looked at geometric space uncertainty between climate behavior in 20th century and modeled climate behavior simulated by global climate models (GCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5). Surfaces from the climate models came from running the models over the same domain as the real data. We also created response surfaces from a real, climate data based on an empirical model that produces a geometric surface of predicted values in state space. We used a kernel regression method designed to capture the geometry of real data pattern without imposing shape assumptions a priori on the data; this kernel regression method is known as Non-parametric Multiplicative Regression (NPMR). We found that quantifying and comparing a geometric attribute in more than three dimensions of state space can discern whether the emergent nature of complex interactions in modeled systems matches that of real systems. Further, this method has potentially wider application in contexts where searching for abrupt change or ';action' in any hyperspace is desired.

Tracking and imaging humans on heterogeneous infrared sensor arrays for law enforcement applications

NASA Astrophysics Data System (ADS)

Feller, Steven D.; Zheng, Y.; Cull, Evan; Brady, David J.

2002-08-01

We present a plan for the integration of geometric constraints in the source, sensor and analysis levels of sensor networks. The goal of geometric analysis is to reduce the dimensionality and complexity of distributed sensor data analysis so as to achieve real-time recognition and response to significant events. Application scenarios include biometric tracking of individuals, counting and analysis of individuals in groups of humans and distributed sentient environments. We are particularly interested in using this approach to provide networks of low cost point detectors, such as infrared motion detectors, with complex imaging capabilities. By extending the capabilities of simple sensors, we expect to reduce the cost of perimeter and site security applications.

Non-stoquastic Hamiltonians in quantum annealing via geometric phases

NASA Astrophysics Data System (ADS)

Vinci, Walter; Lidar, Daniel A.

2017-09-01

We argue that a complete description of quantum annealing implemented with continuous variables must take into account the non-adiabatic Aharonov-Anandan geometric phase that arises when the system Hamiltonian changes during the anneal. We show that this geometric effect leads to the appearance of non-stoquasticity in the effective quantum Ising Hamiltonians that are typically used to describe quantum annealing with flux qubits. We explicitly demonstrate the effect of this geometric non-stoquasticity when quantum annealing is performed with a system of one and two coupled flux qubits. The realization of non-stoquastic Hamiltonians has important implications from a computational complexity perspective, since it is believed that in many cases quantum annealing with stoquastic Hamiltonians can be efficiently simulated via classical algorithms such as Quantum Monte Carlo. It is well known that the direct implementation of non-stoquastic Hamiltonians with flux qubits is particularly challenging. Our results suggest an alternative path for the implementation of non-stoquasticity via geometric phases that can be exploited for computational purposes.

Geometric phase topology in weak measurement

NASA Astrophysics Data System (ADS)

Samlan, C. T.; Viswanathan, Nirmal K.

2017-12-01

The geometric phase visualization proposed by Bhandari (R Bhandari 1997 Phys. Rep. 281 1-64) in the ellipticity-ellipse orientation basis of the polarization ellipse of light is implemented to understand the geometric aspects of weak measurement. The weak interaction of a pre-selected state, acheived via spin-Hall effect of light (SHEL), results in a spread in the polarization ellipticity (η) or ellipse orientation (χ) depending on the resulting spatial or angular shift, respectively. The post-selection leads to the projection of the η spread in the complementary χ basis results in the appearance of a geometric phase with helical phase topology in the η - χ parameter space. By representing the weak measurement on the Poincaré sphere and using Jones calculus, the complex weak value and the geometric phase topology are obtained. This deeper understanding of the weak measurement process enabled us to explore the techniques’ capabilities maximally, as demonstrated via SHEL in two examples—external reflection at glass-air interface and transmission through a tilted half-wave plate.

Tailoring optical complex field with spiral blade plasmonic vortex lens

PubMed Central

Rui, Guanghao; Zhan, Qiwen; Cui, Yiping

2015-01-01

Optical complex fields have attracted increasing interests because of the novel effects and phenomena arising from the spatially inhomogeneous state of polarizations and optical singularities of the light beam. In this work, we propose a spiral blade plasmonic vortex lens (SBPVL) that offers unique opportunities to manipulate these novel fields. The strong interaction between the SBPVL and the optical complex fields enable the synthesis of highly tunable plasmonic vortex. Through theoretical derivations and numerical simulations we demonstrated that the characteristics of the plasmonic vortex are determined by the angular momentum (AM) of the light, and the geometrical topological charge of the SBPVL, which is govern by the nonlinear superposition of the pitch and the number of blade element. In addition, it is also shown that by adjusting the geometric parameters, SBPVL can be utilized to focus and manipulate optical complex field with fractional AM. This miniature plasmonic device may find potential applications in optical trapping, optical data storage and many other related fields. PMID:26335894

Phase Helps Find Geometrically Optimal Gaits

NASA Astrophysics Data System (ADS)

Revzen, Shai; Hatton, Ross

Geometric motion planning describes motions of animals and machines governed by g ˙ = gA (q) q ˙ - a connection A (.) relating shape q and shape velocity q ˙ to body frame velocity g-1 g ˙ ∈ se (3) . Measuring the entire connection over a multidimensional q is often unfeasible with current experimental methods. We show how using a phase estimator can make tractable measuring the local structure of the connection surrounding a periodic motion q (φ) driven by a phase φ ∈S1 . This approach reduces the complexity of the estimation problem by a factor of dimq . The results suggest that phase estimation can be combined with geometric optimization into an iterative gait optimization algorithm usable on experimental systems, or alternatively, to allow the geometric optimality of an observed gait to be detected. ARO W911NF-14-1-0573, NSF 1462555.

Omitted variable bias in crash reduction factors.

DOT National Transportation Integrated Search

2015-09-01

Transportation planners and traffic engineers are increasingly turning to crash reduction factors to evaluate changes in road : geometric and design features in order to reduce crashes. Crash reduction factors are typically estimated based on segment...

Digital hologram transformations for RGB color holographic display with independent image magnification and translation in 3D.

PubMed

Makowski, Piotr L; Zaperty, Weronika; Kozacki, Tomasz

2018-01-01

A new framework for in-plane transformations of digital holograms (DHs) is proposed, which provides improved control over basic geometrical features of holographic images reconstructed optically in full color. The method is based on a Fourier hologram equivalent of the adaptive affine transformation technique [Opt. Express18, 8806 (2010)OPEXFF1094-408710.1364/OE.18.008806]. The solution includes four elementary geometrical transformations that can be performed independently on a full-color 3D image reconstructed from an RGB hologram: (i) transverse magnification; (ii) axial translation with minimized distortion; (iii) transverse translation; and (iv) viewing angle rotation. The independent character of transformations (i) and (ii) constitutes the main result of the work and plays a double role: (1) it simplifies synchronization of color components of the RGB image in the presence of mismatch between capture and display parameters; (2) provides improved control over position and size of the projected image, particularly the axial position, which opens new possibilities for efficient animation of holographic content. The approximate character of the operations (i) and (ii) is examined both analytically and experimentally using an RGB circular holographic display system. Additionally, a complex animation built from a single wide-aperture RGB Fourier hologram is presented to demonstrate full capabilities of the developed toolset.

Actual Romanian research in post-newtonian dynamics

NASA Astrophysics Data System (ADS)

Mioc, V.; Stavinschi, M.

2007-05-01

We survey the recent Romanian results in the study of the two-body problem in post-Newtonian fields. Such a field is characterized, in general, by a potential of the form U(q)=|q|^{-1}+ something (small, but not compulsorily). We distinguish some classes of post-Newtonian models: relativistic (Schwarzschild, Fock, Einstein PN, Reissner-Nordström, Schwarzschild - de Sitter, etc.) and nonrelativistic (Manev, Mücket-Treder, Seeliger, gravito-elastic, etc.). Generalized models (the zonal-satellite problem, quasihomogeneous fields), as well as special cases (anisotropic Manev-type and Schwarzschild-type models, Popovici or Popovici-Manev photogravitational problem), were also tackled. The methods used in such studies are various: analytical (using mainly the theory of perturbations, but also other theories: functions of complex variable, variational calculus, etc.), geometric (qualitative approach of the theory of dynamical systems), and numerical (especially using the Poincaré-section technique). The areas of interest and the general results obtained focus on: exact or approximate analytical solutions; characteristics of local flows (especially at limit situations: collision and escape); quasiperiodic and periodic orbits; equilibria; symmetries; chaoticity; geometric description of the global flow (and physical interpretation of the phase-space structure). We emphasize some special features, which cannot be met within the Newtonian framework: black-hole effect, oscillatory collisions, radial librations, bounded orbits for nonnegative energy, existence of unstable circular motion (or unstable rest), symmetric periodic orbits within anisotropic models, etc.

The shape of the hominoid proximal femur: a geometric morphometric analysis

PubMed Central

Harmon, Elizabeth H

2007-01-01

As part of the hip joint, the proximal femur is an integral locomotor component. Although a link between locomotion and the morphology of some aspects of the proximal femur has been identified, inclusive shapes of this element have not been compared among behaviourally heterogeneous hominoids. Previous analyses have partitioned complex proximal femoral morphology into discrete features (e.g. head, neck, greater trochanter) to facilitate conventional linear measurements. In this study, three-dimensional geometric morphometrics are used to examine the shape of the proximal femur in hominoids to determine whether femoral shape co-varies with locomotor category. Fourteen landmarks are recorded on adult femora of Homo, Pan, Gorilla, Pongo and Hylobates. Generalized Procrustes analysis (GPA) is used to adjust for position, orientation and scale among landmark configurations. Principal components analysis is used to collapse and compare variation in residuals from GPA, and thin-plate spline analysis is used to visualize shape change among taxa. The results indicate that knucklewalking African apes are similar to one another in femoral shape, whereas the more suspensory Asian apes diverge from the African ape pattern. The shape of the human and orangutan proximal femur converge, a result that is best explained in terms of the distinct requirements for locomotion in each group. These findings suggest that the shape of the proximal femur is brought about primarily by locomotor behaviour. PMID:17310545

Facial Orientation and Facial Shape in Extant Great Apes: A Geometric Morphometric Analysis of Covariation

PubMed Central

Neaux, Dimitri; Guy, Franck; Gilissen, Emmanuel; Coudyzer, Walter; Vignaud, Patrick; Ducrocq, Stéphane

2013-01-01

The organization of the bony face is complex, its morphology being influenced in part by the rest of the cranium. Characterizing the facial morphological variation and craniofacial covariation patterns in extant hominids is fundamental to the understanding of their evolutionary history. Numerous studies on hominid facial shape have proposed hypotheses concerning the relationship between the anterior facial shape, facial block orientation and basicranial flexion. In this study we test these hypotheses in a sample of adult specimens belonging to three extant hominid genera (Homo, Pan and Gorilla). Intraspecific variation and covariation patterns are analyzed using geometric morphometric methods and multivariate statistics, such as partial least squared on three-dimensional landmarks coordinates. Our results indicate significant intraspecific covariation between facial shape, facial block orientation and basicranial flexion. Hominids share similar characteristics in the relationship between anterior facial shape and facial block orientation. Modern humans exhibit a specific pattern in the covariation between anterior facial shape and basicranial flexion. This peculiar feature underscores the role of modern humans' highly-flexed basicranium in the overall integration of the cranium. Furthermore, our results are consistent with the hypothesis of a relationship between the reduction of the value of the cranial base angle and a downward rotation of the facial block in modern humans, and to a lesser extent in chimpanzees. PMID:23441232

The Design of Case Products’ Shape Form Information Database Based on NURBS Surface

NASA Astrophysics Data System (ADS)

Liu, Xing; Liu, Guo-zhong; Xu, Nuo-qi; Zhang, Wei-she

2017-07-01

In order to improve the computer design of product shape design,applying the Non-uniform Rational B-splines(NURBS) of curves and surfaces surface to the representation of the product shape helps designers to design the product effectively.On the basis of the typical product image contour extraction and using Pro/Engineer(Pro/E) to extract the geometric feature of scanning mold,in order to structure the information data base system of value point,control point and node vector parameter information,this paper put forward a unified expression method of using NURBS curves and surfaces to describe products’ geometric shape and using matrix laboratory(MATLAB) to simulate when products have the same or similar function.A case study of electric vehicle’s front cover illustrates the access process of geometric shape information of case product in this paper.This method can not only greatly reduce the capacity of information debate,but also improve the effectiveness of computer aided geometric innovation modeling.

On a common circle: natural scenes and Gestalt rules.

PubMed

Sigman, M; Cecchi, G A; Gilbert, C D; Magnasco, M O

2001-02-13

To understand how the human visual system analyzes images, it is essential to know the structure of the visual environment. In particular, natural images display consistent statistical properties that distinguish them from random luminance distributions. We have studied the geometric regularities of oriented elements (edges or line segments) present in an ensemble of visual scenes, asking how much information the presence of a segment in a particular location of the visual scene carries about the presence of a second segment at different relative positions and orientations. We observed strong long-range correlations in the distribution of oriented segments that extend over the whole visual field. We further show that a very simple geometric rule, cocircularity, predicts the arrangement of segments in natural scenes, and that different geometrical arrangements show relevant differences in their scaling properties. Our results show similarities to geometric features of previous physiological and psychophysical studies. We discuss the implications of these findings for theories of early vision.

Geometric Bioinspired Networks for Recognition of 2-D and 3-D Low-Level Structures and Transformations.

PubMed

Bayro-Corrochano, Eduardo; Vazquez-Santacruz, Eduardo; Moya-Sanchez, Eduardo; Castillo-Munis, Efrain

2016-10-01

This paper presents the design of radial basis function geometric bioinspired networks and their applications. Until now, the design of neural networks has been inspired by the biological models of neural networks but mostly using vector calculus and linear algebra. However, these designs have never shown the role of geometric computing. The question is how biological neural networks handle complex geometric representations involving Lie group operations like rotations. Even though the actual artificial neural networks are biologically inspired, they are just models which cannot reproduce a plausible biological process. Until now researchers have not shown how, using these models, one can incorporate them into the processing of geometric computing. Here, for the first time in the artificial neural networks domain, we address this issue by designing a kind of geometric RBF using the geometric algebra framework. As a result, using our artificial networks, we show how geometric computing can be carried out by the artificial neural networks. Such geometric neural networks have a great potential in robot vision. This is the most important aspect of this contribution to propose artificial geometric neural networks for challenging tasks in perception and action. In our experimental analysis, we show the applicability of our geometric designs, and present interesting experiments using 2-D data of real images and 3-D screw axis data. In general, our models should be used to process different types of inputs, such as visual cues, touch (texture, elasticity, temperature), taste, and sound. One important task of a perception-action system is to fuse a variety of cues coming from the environment and relate them via a sensor-motor manifold with motor modules to carry out diverse reasoned actions.

Non-destructive inspection of polymer composite products

NASA Astrophysics Data System (ADS)

Anoshkin, A. N.; Sal'nikov, A. F.; Osokin, V. M.; Tretyakov, A. A.; Luzin, G. S.; Potrakhov, N. N.; Bessonov, V. B.

2018-02-01

The paper considers the main types of defects encountered in products made of polymer composite materials for aviation use. The analysis of existing methods of nondestructive testing is carried out, features of their application are considered taking into account design features, geometrical parameters and internal structure of objects of inspection. The advantages and disadvantages of the considered methods of nondestructive testing used in industrial production are shown.

CT Image Sequence Analysis for Object Recognition - A Rule-Based 3-D Computer Vision System

Treesearch

Dongping Zhu; Richard W. Conners; Daniel L. Schmoldt; Philip A. Araman

1991-01-01

Research is now underway to create a vision system for hardwood log inspection using a knowledge-based approach. In this paper, we present a rule-based, 3-D vision system for locating and identifying wood defects using topological, geometric, and statistical attributes. A number of different features can be derived from the 3-D input scenes. These features and evidence...

Encounter Models for the Littoral Regions of the National Airspace System

DTIC Science & Technology

2010-09-15

Jeff Richardson, Steven Schimmelpfennig, Richard Whitlock, Lt. Han Saydam, Lt. Tanuxay Keooudom, James Evans, TSgt. Christopher Cosper, Lt. Luke Marron...24 17 Correlated geometric feature comparison. 25 A- l Aircraft vertical rate in uncorrelated encounters. 31 A-2 Uncorrelated continuous feature...in correlated encounters. 35 B- l Approach angle (/3) and bearing (x) definition. 39 C- l Horizontal plane encounter initialization. 42 C-2

Analysis of 3D OCT images for diagnosis of skin tumors

NASA Astrophysics Data System (ADS)

Raupov, Dmitry S.; Myakinin, Oleg O.; Bratchenko, Ivan A.; Zakharov, Valery P.; Khramov, Alexander G.

2018-04-01

Skin cancer is one of the fastest growing type of cancer. It represents the most commonly diagnosed malignancy, surpassing lung, breast, colorectal and prostate cancer. So, diagnostics for different types of skin cancer on early stages is a very high challenge for medicine industry. New optical imaging techniques have been developed in order to improve diagnostics precision. Optical coherence tomography (OCT) is based on low-coherence interferometry to detect the intensity of backscattered infrared light from biological tissues by measuring the optical path length. OCT provides the advantage of real-time, in vivo, low-cost imaging of suspicious lesions without having to proceed directly to a tissue biopsy. The post-processing techniques can be used for improving the precision of diagnostics and providing solutions to overcome limitations for OCT. Image processing can include noise filtration and evaluation of textural, geometric, morphological, spectral, statistic and other features. The main idea of this investigation is using information received from multiple analyze on 2D- and 3D-OCT images for skin tumors differentiating. At first, we tested the computer algorithm on OCT data hypercubes and separated B- and C-scans. Combination of 2D and 3D data give us an opportunity to receive common information about tumor (geometric and morphological characteristics) and use more powerful algorithms for features evaluation (fractal and textural) on these separated scans. These groups of features provide closer connection to classical wide-used ABCDE criteria (Asymmetry, Border irregularity, Color, Diameter, Evolution). We used a set of features consisting of fractal dimension, Haralick's, Gabor's, Tamura's, Markov random fields, geometric features and many others. We could note about good results on the test sets in differentiation between BCC and Nevus, MM and Healthy Skin. We received dividing MM from Healthy Skin with sensitivity more 90% and specificity more 92% (168 B-scans from 8 species) by using three Haralick's features like Contrast, Correlation and Energy. The results are very promising to be tested for new cases and new bigger sets of OCT images.

Structural analyses of the JPL Mars Pathfinder impact

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

Gwinn, K.W.

1994-12-31

The purpose of this paper is to demonstrate that finite element analysis can be used in the design process for high performance fabric structures. These structures exhibit extreme geometric nonlinearity; specifically, the contact and interaction of fabric surfaces with the large deformation which necessarily results from membrane structures introduces great complexity to analyses of this type. All of these features are demonstrated here in the analysis of the Jet Propulsion Laboratory (JPL) Mars Pathfinder impact onto Mars. This lander system uses airbags to envelope the lander experiment package, protecting it with large deformation upon contact. Results from the analysis showmore » the stress in the fabric airbags, forces in the internal tendon support system, forces in the latches and hinges which allow the lander to deploy after impact, and deceleration of the lander components. All of these results provide the JPL engineers with design guidance for the success of this novel lander system.« less

Structural analyses of the JPL Mars Pathfinder impact

NASA Astrophysics Data System (ADS)

Gwinn, Kenneth W.

The purpose of this paper is to demonstrate that finite element analysis can be used in the design process for high performance fabric structures. These structures exhibit extreme geometric nonlinearity; specifically, the contact and interaction of fabric surfaces with the large deformation which necessarily results from membrane structures introduces great complexity to analyses of this type. All of these features are demonstrated here in the analysis of the Jet Propulsion Laboratory (JPL) Mars Pathfinder impact onto Mars. This lander system uses airbags to envelope the lander experiment package, protecting it with large deformation upon contact. Results from the analysis show the stress in the fabric airbags, forces in the internal tendon support system, forces in the latches and hinges which allow the lander to deploy after impact, and deceleration of the lander components. All of these results provide the JPL engineers with design guidance for the success of this novel lander system.

A Persistent Feature of Multiple Scattering of Waves in the Time-Domain: A Tutorial

NASA Technical Reports Server (NTRS)

Lock, James A.; Mishchenko, Michael I.

2015-01-01

The equations for frequency-domain multiple scattering are derived for a scalar or electromagnetic plane wave incident on a collection of particles at known positions, and in the time-domain for a plane wave pulse incident on the same collection of particles. The calculation is carried out for five different combinations of wave types and particle types of increasing geometrical complexity. The results are used to illustrate and discuss a number of physical and mathematical characteristics of multiple scattering in the frequency- and time-domains. We argue that frequency-domain multiple scattering is a purely mathematical construct since there is no temporal sequencing information in the frequency-domain equations and since the multi-particle path information can be dispelled by writing the equations in another mathematical form. However, multiple scattering becomes a definite physical phenomenon in the time-domain when the collection of particles is illuminated by an appropriately short localized pulse.

Thin sheets achieve optimal wrapping of liquids

NASA Astrophysics Data System (ADS)

Paulsen, Joseph; Démery, Vincent; Davidovitch, Benny; Santangelo, Christian; Russell, Thomas; Menon, Narayanan

2015-03-01

A liquid drop can wrap itself in a sheet using capillary forces [Py et al., PRL 98, 2007]. However, the efficiency of ``capillary origami'' at covering the surface of a drop is hampered by the mechanical cost of bending the sheet. Thinner sheets deform more readily by forming small-scale wrinkles and stress-focussing patterns, but it is unclear how coverage efficiency competes with mechanical cost as thickness is decreased, and what wrapping shapes will emerge. We place a thin (~ 100 nm) polymer film on a drop whose volume is gradually decreased so that the sheet covers an increasing fraction of its surface. The sheet exhibits a complex sequence of axisymmetric and polygonal partially- and fully- wrapped shapes. Remarkably, the progression appears independent of mechanical properties. The gross shape, which neglects small-scale features, is correctly predicted by a simple geometric approach wherein the exposed area is minimized. Thus, simply using a thin enough sheet results in maximal coverage.

Generalized elastica patterns in a curved rotating Hele-Shaw cell

NASA Astrophysics Data System (ADS)

Brandão, Rodolfo; Miranda, José A.

2017-08-01

We study a family of generalized elasticalike equilibrium shapes that arise at the interface separating two fluids in a curved rotating Hele-Shaw cell. This family of stationary interface solutions consists of shapes that balance the competing capillary and centrifugal forces in such a curved flow environment. We investigate how the emerging interfacial patterns are impacted by changes in the geometric properties of the curved Hele-Shaw cell. A vortex-sheet formalism is used to calculate the two-fluid interface curvature, and a gallery of possible shapes is provided to highlight a number of peculiar morphological features. A linear perturbation theory is employed to show that the most prominent aspects of these complex stationary patterns can be fairly well reproduced by the interplay of just two interfacial modes. The connection of these dominant modes to the geometry of the curved cell, as well as to the fluid dynamic properties of the flow, is discussed.

On dependency properties of the ISIs generated by a two-compartmental neuronal model.

PubMed

Benedetto, Elisa; Sacerdote, Laura

2013-02-01

One-dimensional leaky integrate and fire neuronal models describe interspike intervals (ISIs) of a neuron as a renewal process and disregarding the neuron geometry. Many multi-compartment models account for the geometrical features of the neuron but are too complex for their mathematical tractability. Leaky integrate and fire two-compartment models seem a good compromise between mathematical tractability and an improved realism. They indeed allow to relax the renewal hypothesis, typical of one-dimensional models, without introducing too strong mathematical difficulties. Here, we pursue the analysis of the two-compartment model studied by Lansky and Rodriguez (Phys D 132:267-286, 1999), aiming of introducing some specific mathematical results used together with simulation techniques. With the aid of these methods, we investigate dependency properties of ISIs for different values of the model parameters. We show that an increase of the input increases the strength of the dependence between successive ISIs.

TIGER: A user-friendly interactive grid generation system for complicated turbomachinery and axis-symmetric configurations

NASA Technical Reports Server (NTRS)

Shih, Ming H.; Soni, Bharat K.

1993-01-01

The issue of time efficiency in grid generation is addressed by developing a user friendly graphical interface for interactive/automatic construction of structured grids around complex turbomachinery/axis-symmetric configurations. The accuracy of geometry modeling and its fidelity is accomplished by adapting the nonuniform rational b-spline (NURBS) representation. A customized interactive grid generation code, TIGER, has been developed to facilitate the grid generation process for complicated internal, external, and internal-external turbomachinery fields simulations. The FORMS Library is utilized to build user-friendly graphical interface. The algorithm allows a user to redistribute grid points interactively on curves/surfaces using NURBS formulation with accurate geometric definition. TIGER's features include multiblock, multiduct/shroud, multiblade row, uneven blade count, and patched/overlapping block interfaces. It has been applied to generate grids for various complicated turbomachinery geometries, as well as rocket and missile configurations.

Distributed bearing fault diagnosis based on vibration analysis

NASA Astrophysics Data System (ADS)

Dolenc, Boštjan; Boškoski, Pavle; Juričić, Đani

2016-01-01

Distributed bearing faults appear under various circumstances, for example due to electroerosion or the progression of localized faults. Bearings with distributed faults tend to generate more complex vibration patterns than those with localized faults. Despite the frequent occurrence of such faults, their diagnosis has attracted limited attention. This paper examines a method for the diagnosis of distributed bearing faults employing vibration analysis. The vibrational patterns generated are modeled by incorporating the geometrical imperfections of the bearing components. Comparing envelope spectra of vibration signals shows that one can distinguish between localized and distributed faults. Furthermore, a diagnostic procedure for the detection of distributed faults is proposed. This is evaluated on several bearings with naturally born distributed faults, which are compared with fault-free bearings and bearings with localized faults. It is shown experimentally that features extracted from vibrations in fault-free, localized and distributed fault conditions form clearly separable clusters, thus enabling diagnosis.

A class of hybrid finite element methods for electromagnetics: A review

NASA Technical Reports Server (NTRS)

Volakis, J. L.; Chatterjee, A.; Gong, J.

1993-01-01

Integral equation methods have generally been the workhorse for antenna and scattering computations. In the case of antennas, they continue to be the prominent computational approach, but for scattering applications the requirement for large-scale computations has turned researchers' attention to near neighbor methods such as the finite element method, which has low O(N) storage requirements and is readily adaptable in modeling complex geometrical features and material inhomogeneities. In this paper, we review three hybrid finite element methods for simulating composite scatterers, conformal microstrip antennas, and finite periodic arrays. Specifically, we discuss the finite element method and its application to electromagnetic problems when combined with the boundary integral, absorbing boundary conditions, and artificial absorbers for terminating the mesh. Particular attention is given to large-scale simulations, methods, and solvers for achieving low memory requirements and code performance on parallel computing architectures.

Visual display aid for orbital maneuvering - Design considerations

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Ellis, Stephen R.

1993-01-01

This paper describes the development of an interactive proximity operations planning system that allows on-site planning of fuel-efficient multiburn maneuvers in a potential multispacecraft environment. Although this display system most directly assists planning by providing visual feedback to aid visualization of the trajectories and constraints, its most significant features include: (1) the use of an 'inverse dynamics' algorithm that removes control nonlinearities facing the operator, and (2) a trajectory planning technique that separates, through a 'geometric spreadsheet', the normally coupled complex problems of planning orbital maneuvers and allows solution by an iterative sequence of simple independent actions. The visual feedback of trajectory shapes and operational constraints, provided by user-transparent and continuously active background computations, allows the operator to make fast, iterative design changes that rapidly converge to fuel-efficient solutions. The planning tool provides an example of operator-assisted optimization of nonlinear cost functions.

Review of FD-TD numerical modeling of electromagnetic wave scattering and radar cross section

NASA Technical Reports Server (NTRS)

Taflove, Allen; Umashankar, Korada R.

1989-01-01

Applications of the finite-difference time-domain (FD-TD) method for numerical modeling of electromagnetic wave interactions with structures are reviewed, concentrating on scattering and radar cross section (RCS). A number of two- and three-dimensional examples of FD-TD modeling of scattering and penetration are provided. The objects modeled range in nature from simple geometric shapes to extremely complex aerospace and biological systems. Rigorous analytical or experimental validatons are provided for the canonical shapes, and it is shown that FD-TD predictive data for near fields and RCS are in excellent agreement with the benchmark data. It is concluded that with continuing advances in FD-TD modeling theory for target features relevant to the RCS problems and in vector and concurrent supercomputer technology, it is likely that FD-TD numerical modeling will occupy an important place in RCS technology in the 1990s and beyond.

Depth estimation of laser glass drilling based on optical differential measurements of acoustic response

NASA Astrophysics Data System (ADS)

Gorodesky, Niv; Ozana, Nisan; Berg, Yuval; Dolev, Omer; Danan, Yossef; Kotler, Zvi; Zalevsky, Zeev

2016-09-01

We present the first steps of a device suitable for characterization of complex 3D micro-structures. This method is based on an optical approach allowing extraction and separation of high frequency ultrasonic sound waves induced to the analyzed samples. Rapid, non-destructive characterization of 3D micro-structures are limited in terms of geometrical features and optical properties of the sample. We suggest a method which is based on temporal tracking of secondary speckle patterns generated when illuminating a sample with a laser probe while applying known periodic vibration using an ultrasound transmitter. In this paper we investigated lasers drilled through glass vias. The large aspect ratios of the vias possess a challenge for traditional microscopy techniques in analyzing depth and taper profiles of the vias. The correlation of the amplitude vibrations to the vias depths is experimentally demonstrated.

Ion beam sputtering of Ag - Angular and energetic distributions of sputtered and scattered particles

NASA Astrophysics Data System (ADS)

Feder, René; Bundesmann, Carsten; Neumann, Horst; Rauschenbach, Bernd

2013-12-01

Ion beam sputter deposition (IBD) provides intrinsic features which influence the properties of the growing film, because ion properties and geometrical process conditions generate different energy and spatial distribution of the sputtered and scattered particles. A vacuum deposition chamber is set up to measure the energy and spatial distribution of secondary particles produced by ion beam sputtering of different target materials under variation of geometrical parameters (incidence angle of primary ions and emission angle of secondary particles) and of primary ion beam parameters (ion species and energies).

Generalized Born-Oppenheimer treatment of Jahn-Teller systems in Hilbert spaces of arbitrary dimension: theory and application to a three-state model potential.

PubMed

Varandas, A J C; Sarkar, B

2011-05-14

Generalized Born-Oppenheimer equations including the geometrical phase effect are derived for three- and four-fold electronic manifolds in Jahn-Teller systems near the degeneracy seam. The method is readily extendable to N-fold systems of arbitrary dimension. An application is reported for a model threefold system, and the results are compared with Born-Oppenheimer (geometrical phase ignored), extended Born-Oppenheimer, and coupled three-state calculations. The theory shows unprecedented simplicity while depicting all features of more elaborated ones.

Optimal Information Extraction of Laser Scanning Dataset by Scale-Adaptive Reduction

NASA Astrophysics Data System (ADS)

Zang, Y.; Yang, B.

2018-04-01

3D laser technology is widely used to collocate the surface information of object. For various applications, we need to extract a good perceptual quality point cloud from the scanned points. To solve the problem, most of existing methods extract important points based on a fixed scale. However, geometric features of 3D object come from various geometric scales. We propose a multi-scale construction method based on radial basis function. For each scale, important points are extracted from the point cloud based on their importance. We apply a perception metric Just-Noticeable-Difference to measure degradation of each geometric scale. Finally, scale-adaptive optimal information extraction is realized. Experiments are undertaken to evaluate the effective of the proposed method, suggesting a reliable solution for optimal information extraction of object.

Complex nonlinear dynamics in the limit of weak coupling of a system of microcantilevers connected by a geometrically nonlinear tunable nanomembrane.

PubMed

Jeong, Bongwon; Cho, Hanna; Keum, Hohyun; Kim, Seok; Michael McFarland, D; Bergman, Lawrence A; King, William P; Vakakis, Alexander F

2014-11-21

Intentional utilization of geometric nonlinearity in micro/nanomechanical resonators provides a breakthrough to overcome the narrow bandwidth limitation of linear dynamic systems. In past works, implementation of intentional geometric nonlinearity to an otherwise linear nano/micromechanical resonator has been successfully achieved by local modification of the system through nonlinear attachments of nanoscale size, such as nanotubes and nanowires. However, the conventional fabrication method involving manual integration of nanoscale components produced a low yield rate in these systems. In the present work, we employed a transfer-printing assembly technique to reliably integrate a silicon nanomembrane as a nonlinear coupling component onto a linear dynamic system with two discrete microcantilevers. The dynamics of the developed system was modeled analytically and investigated experimentally as the coupling strength was finely tuned via FIB post-processing. The transition from the linear to the nonlinear dynamic regime with gradual change in the coupling strength was experimentally studied. In addition, we observed for the weakly coupled system that oscillation was asynchronous in the vicinity of the resonance, thus exhibiting a nonlinear complex mode. We conjectured that the emergence of this nonlinear complex mode could be attributed to the nonlinear damping arising from the attached nanomembrane.

Groups of adjacent contour segments for object detection.

PubMed

Ferrari, V; Fevrier, L; Jurie, F; Schmid, C

2008-01-01

We present a family of scale-invariant local shape features formed by chains of k connected, roughly straight contour segments (kAS), and their use for object class detection. kAS are able to cleanly encode pure fragments of an object boundary, without including nearby clutter. Moreover, they offer an attractive compromise between information content and repeatability, and encompass a wide variety of local shape structures. We also define a translation and scale invariant descriptor encoding the geometric configuration of the segments within a kAS, making kAS easy to reuse in other frameworks, for example as a replacement or addition to interest points. Software for detecting and describing kAS is released on lear.inrialpes.fr/software. We demonstrate the high performance of kAS within a simple but powerful sliding-window object detection scheme. Through extensive evaluations, involving eight diverse object classes and more than 1400 images, we 1) study the evolution of performance as the degree of feature complexity k varies and determine the best degree; 2) show that kAS substantially outperform interest points for detecting shape-based classes; 3) compare our object detector to the recent, state-of-the-art system by Dalal and Triggs [4].

A simplified lumped model for the optimization of post-buckled beam architecture wideband generator

NASA Astrophysics Data System (ADS)

Liu, Weiqun; Formosa, Fabien; Badel, Adrien; Hu, Guangdi

2017-11-01

Buckled beams structures are a classical kind of bistable energy harvesters which attract more and more interests because of their capability to scavenge energy over a large frequency band in comparison with linear generator. The usual modeling approach uses the Galerkin mode discretization method with relatively high complexity, while the simplification with a single-mode solution lacks accuracy. It stems on the optimization of the energy potential features to finally define the physical and geometrical parameters. Therefore, in this paper, a simple lumped model is proposed with explicit relationship between the potential shape and parameters to allow efficient design of bistable beams based generator. The accuracy of the approximation model is studied with the effectiveness of application analyzed. Moreover, an important fact, that the bending stiffness has little influence on the potential shape with low buckling level and the sectional area determined, is found. This feature extends the applicable range of the model by utilizing the design of high moment of inertia. Numerical investigations demonstrate that the proposed model is a simple and reliable tool for design. An optimization example of using the proposed model is demonstrated with satisfactory performance.

Neomorphosis and heterochrony of skull shape in dog domestication.

PubMed

Geiger, Madeleine; Evin, Allowen; Sánchez-Villagra, Marcelo R; Gascho, Dominic; Mainini, Cornelia; Zollikofer, Christoph P E

2017-10-18

The overall similarity of the skull shape of some dog breeds with that of juvenile wolves begs the question if and how ontogenetic changes such as paedomorphosis (evolutionary juvenilisation) played a role in domestication. Here we test for changes in patterns of development and growth during dog domestication. We present the first geometric morphometric study using ontogenetic series of dog and wolf crania, and samples of dogs with relatively ancestral morphology and from different time periods. We show that patterns of juvenile-to-adult morphological change are largely similar in wolves and domestic dogs, but differ in two ways. First, dog skulls show unique (neomorphic) features already shortly after birth, and these features persist throughout postnatal ontogeny. Second, at any given age, juvenile dogs exhibit skull shapes that resemble those of consistently younger wolves, even in dog breeds that do not exhibit a 'juvenilized' morphology as adults. These patterns exemplify the complex nature of evolutionary changes during dog domestication: the cranial morphology of adult dogs cannot simply be explained as either neomorphic or paedomorphic. The key to our understanding of dog domestication may lie in a closer comparative examination of developmental phases.

Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images

NASA Astrophysics Data System (ADS)

Alshehhi, Rasha; Marpu, Prashanth Reddy

2017-04-01

Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.

Alternate approach for calculating hardness based on residual indentation depth: Comparison with experiments

NASA Astrophysics Data System (ADS)

Ananthakrishna, G.; K, Srikanth

2018-03-01

It is well known that plastic deformation is a highly nonlinear dissipative irreversible phenomenon of considerable complexity. As a consequence, little progress has been made in modeling some well-known size-dependent properties of plastic deformation, for instance, calculating hardness as a function of indentation depth independently. Here, we devise a method of calculating hardness by calculating the residual indentation depth and then calculate the hardness as the ratio of the load to the residual imprint area. Recognizing the fact that dislocations are the basic defects controlling the plastic component of the indentation depth, we set up a system of coupled nonlinear time evolution equations for the mobile, forest, and geometrically necessary dislocation densities. Within our approach, we consider the geometrically necessary dislocations to be immobile since they contribute to additional hardness. The model includes dislocation multiplication, storage, and recovery mechanisms. The growth of the geometrically necessary dislocation density is controlled by the number of loops that can be activated under the contact area and the mean strain gradient. The equations are then coupled to the load rate equation. Our approach has the ability to adopt experimental parameters such as the indentation rates, the geometrical parameters defining the Berkovich indenter, including the nominal tip radius. The residual indentation depth is obtained by integrating the Orowan expression for the plastic strain rate, which is then used to calculate the hardness. Consistent with the experimental observations, the increasing hardness with decreasing indentation depth in our model arises from limited dislocation sources at small indentation depths and therefore avoids divergence in the limit of small depths reported in the Nix-Gao model. We demonstrate that for a range of parameter values that physically represent different materials, the model predicts the three characteristic features of hardness, namely, increase in the hardness with decreasing indentation depth, and the linear relation between the square of the hardness and the inverse of the indentation depth, for all but 150 nm, deviating for smaller depths. In addition, we also show that it is straightforward to obtain optimized parameter values that give good fit to the hardness data for polycrystalline cold worked copper and single crystals of silver.

Application of Fourier analysis to multispectral/spatial recognition

NASA Technical Reports Server (NTRS)

Hornung, R. J.; Smith, J. A.

1973-01-01

One approach for investigating spectral response from materials is to consider spatial features of the response. This might be accomplished by considering the Fourier spectrum of the spatial response. The Fourier Transform may be used in a one-dimensional to multidimensional analysis of more than one channel of data. The two-dimensional transform represents the Fraunhofer diffraction pattern of the image in optics and has certain invariant features. Physically the diffraction pattern contains spatial features which are possibly unique to a given configuration or classification type. Different sampling strategies may be used to either enhance geometrical differences or extract additional features.

A statistical shape modelling framework to extract 3D shape biomarkers from medical imaging data: assessing arch morphology of repaired coarctation of the aorta.

PubMed

Bruse, Jan L; McLeod, Kristin; Biglino, Giovanni; Ntsinjana, Hopewell N; Capelli, Claudio; Hsia, Tain-Yen; Sermesant, Maxime; Pennec, Xavier; Taylor, Andrew M; Schievano, Silvia

2016-05-31

Medical image analysis in clinical practice is commonly carried out on 2D image data, without fully exploiting the detailed 3D anatomical information that is provided by modern non-invasive medical imaging techniques. In this paper, a statistical shape analysis method is presented, which enables the extraction of 3D anatomical shape features from cardiovascular magnetic resonance (CMR) image data, with no need for manual landmarking. The method was applied to repaired aortic coarctation arches that present complex shapes, with the aim of capturing shape features as biomarkers of potential functional relevance. The method is presented from the user-perspective and is evaluated by comparing results with traditional morphometric measurements. Steps required to set up the statistical shape modelling analyses, from pre-processing of the CMR images to parameter setting and strategies to account for size differences and outliers, are described in detail. The anatomical mean shape of 20 aortic arches post-aortic coarctation repair (CoA) was computed based on surface models reconstructed from CMR data. By analysing transformations that deform the mean shape towards each of the individual patient's anatomy, shape patterns related to differences in body surface area (BSA) and ejection fraction (EF) were extracted. The resulting shape vectors, describing shape features in 3D, were compared with traditionally measured 2D and 3D morphometric parameters. The computed 3D mean shape was close to population mean values of geometric shape descriptors and visually integrated characteristic shape features associated with our population of CoA shapes. After removing size effects due to differences in body surface area (BSA) between patients, distinct 3D shape features of the aortic arch correlated significantly with EF (r = 0.521, p = .022) and were well in agreement with trends as shown by traditional shape descriptors. The suggested method has the potential to discover previously unknown 3D shape biomarkers from medical imaging data. Thus, it could contribute to improving diagnosis and risk stratification in complex cardiac disease.

Constrained Multipoint Aerodynamic Shape Optimization Using an Adjoint Formulation and Parallel Computers

NASA Technical Reports Server (NTRS)

Reuther, James; Jameson, Antony; Alonso, Juan Jose; Rimlinger, Mark J.; Saunders, David

1997-01-01

An aerodynamic shape optimization method that treats the design of complex aircraft configurations subject to high fidelity computational fluid dynamics (CFD), geometric constraints and multiple design points is described. The design process will be greatly accelerated through the use of both control theory and distributed memory computer architectures. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods. The resulting problem is implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on a higher order CFD method. In order to facilitate the integration of these high fidelity CFD approaches into future multi-disciplinary optimization (NW) applications, new methods must be developed which are capable of simultaneously addressing complex geometries, multiple objective functions, and geometric design constraints. In our earlier studies, we coupled the adjoint based design formulations with unconstrained optimization algorithms and showed that the approach was effective for the aerodynamic design of airfoils, wings, wing-bodies, and complex aircraft configurations. In many of the results presented in these earlier works, geometric constraints were satisfied either by a projection into feasible space or by posing the design space parameterization such that it automatically satisfied constraints. Furthermore, with the exception of reference 9 where the second author initially explored the use of multipoint design in conjunction with adjoint formulations, our earlier works have focused on single point design efforts. Here we demonstrate that the same methodology may be extended to treat complete configuration designs subject to multiple design points and geometric constraints. Examples are presented for both transonic and supersonic configurations ranging from wing alone designs to complex configuration designs involving wing, fuselage, nacelles and pylons.

Differential Geometry Based Multiscale Models

PubMed Central

Wei, Guo-Wei

2010-01-01

Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that are coupled to generalized Navier–Stokes equations for fluid dynamics, Newton's equation for molecular dynamics, and potential and surface driving geometric flows for the micro-macro interface. For excessively large aqueous macromolecular complexes in chemistry and biology, we further develop differential geometry based multiscale fluid-electro-elastic models to replace the expensive molecular dynamics description with an alternative elasticity formulation. PMID:20169418

Interhemispheric Resource Sharing: Decreasing Benefits with Increasing Processing Efficiency

ERIC Educational Resources Information Center

Maertens, M.; Pollmann, S.

2005-01-01

Visual matches are sometimes faster when stimuli are presented across visual hemifields, compared to within-field matching. Using a cued geometric figure matching task, we investigated the influence of computational complexity vs. processing efficiency on this bilateral distribution advantage (BDA). Computational complexity was manipulated by…

Heterobimetallic complexes with redox-active mesoionic carbenes as metalloligands: electrochemical properties, electronic structures and catalysis.

PubMed

Hettmanczyk, Lara; Manck, Sinja; Hoyer, Carolin; Hohloch, Stephan; Sarkar, Biprajit

2015-07-11

A mesoionic carbene with a ferrocene backbone is used as a metalloligand to generate the first example of their Fe-Au heterobimetallic complexes. The details of geometric and electronic structures in different redox states and preliminary catalytic results are presented.

Complex lasso: new entangled motifs in proteins

NASA Astrophysics Data System (ADS)

Niemyska, Wanda; Dabrowski-Tumanski, Pawel; Kadlof, Michal; Haglund, Ellinor; Sułkowski, Piotr; Sulkowska, Joanna I.

2016-11-01

We identify new entangled motifs in proteins that we call complex lassos. Lassos arise in proteins with disulfide bridges (or in proteins with amide linkages), when termini of a protein backbone pierce through an auxiliary surface of minimal area, spanned on a covalent loop. We find that as much as 18% of all proteins with disulfide bridges in a non-redundant subset of PDB form complex lassos, and classify them into six distinct geometric classes, one of which resembles supercoiling known from DNA. Based on biological classification of proteins we find that lassos are much more common in viruses, plants and fungi than in other kingdoms of life. We also discuss how changes in the oxidation/reduction potential may affect the function of proteins with lassos. Lassos and associated surfaces of minimal area provide new, interesting and possessing many potential applications geometric characteristics not only of proteins, but also of other biomolecules.

A restricted Steiner tree problem is solved by Geometric Method II

NASA Astrophysics Data System (ADS)

Lin, Dazhi; Zhang, Youlin; Lu, Xiaoxu

2013-03-01

The minimum Steiner tree problem has wide application background, such as transportation system, communication network, pipeline design and VISL, etc. It is unfortunately that the computational complexity of the problem is NP-hard. People are common to find some special problems to consider. In this paper, we first put forward a restricted Steiner tree problem, which the fixed vertices are in the same side of one line L and we find a vertex on L such the length of the tree is minimal. By the definition and the complexity of the Steiner tree problem, we know that the complexity of this problem is also Np-complete. In the part one, we have considered there are two fixed vertices to find the restricted Steiner tree problem. Naturally, we consider there are three fixed vertices to find the restricted Steiner tree problem. And we also use the geometric method to solve such the problem.

Micro-navigation in complex periodic environments

NASA Astrophysics Data System (ADS)

Chamolly, Alexander; Ishikawa, Takuji; Lauga, Eric

2017-11-01

Natural and artificial small-scale swimmers may often self-propel in environments subject to complex geometrical constraints. While most past theoretical work on low-Reynolds number locomotion addressed idealised geometrical situations, not much is known on the motion of swimmers in heterogeneous environments. We investigate theoretically and numerically the behaviour of a single spherical micro-swimmer located in an infinite, periodic body-centred cubic lattice consisting of rigid inert spheres of the same size as the swimmer. We uncover a surprising and complex phase diagram of qualitatively different trajectories depending on the lattice packing density and swimming actuation strength. These results are then rationalised using hydrodynamic theory. In particular we show that the far-field nature of the swimmer (pusher vs. puller) governs the behaviour even at high volume fractions. ERC Grant PhyMeBa (682754, EL); JSPS Grant-in-Aid for Scientific Research (A) (17H00853, TI).

Fatigue Magnification Factors of Arc-Soft-Toe Bracket Joints

NASA Astrophysics Data System (ADS)

Fu, Qiang; Li, Huajun; Wang, Hongqing; Wang, Shuqing; Li, Dejiang; Li, Qun; Fang, Hui

2018-06-01

Arc-soft-toe bracket (ASTB), as a joint structure in the marine structure, is the hot spot with significant stress concentration, therefore, fatigue behavior of ASTBs is an important point of concern in their design. Since macroscopic geometric factors obviously influence the stress flaws in joints, the shapes and sizes of ASTBs should represent the stress distribution around cracks in the hot spots. In this paper, we introduce a geometric magnification factor for reflecting the macroscopic geometric effects of ASTB crack features and construct a 3D finite element model to simulate the distribution of stress intensity factor (SIF) at the crack endings. Sensitivity analyses with respect to the geometric ratio H t / L b , R/ L b , L t / L b are performed, and the relations between the geometric factor and these parameters are presented. A set of parametric equations with respect to the geometric magnification factor is obtained using a curve fitting technique. A nonlinear relationship exists between the SIF and the ratio of ASTB arm to toe length. When the ratio of ASTB arm to toe length reaches a marginal value, the SIF of crack at the ASTB toe is not influenced by ASTB geometric parameters. In addition, the arc shape of the ASTB slope edge can transform the stress flowing path, which significantly affects the SIF at the ASTB toe. A proper method to reduce stress concentration is setting a slope edge arc size equal to the ASTB arm length.

Spatial Relation Predicates in Topographic Feature Semantics

USGS Publications Warehouse

Varanka, Dalia E.; Caro, Holly K.

2013-01-01

Topographic data are designed and widely used for base maps of diverse applications, yet the power of these information sources largely relies on the interpretive skills of map readers and relational database expert users once the data are in map or geographic information system (GIS) form. Advances in geospatial semantic technology offer data model alternatives for explicating concepts and articulating complex data queries and statements. To understand and enrich the vocabulary of topographic feature properties for semantic technology, English language spatial relation predicates were analyzed in three standard topographic feature glossaries. The analytical approach drew from disciplinary concepts in geography, linguistics, and information science. Five major classes of spatial relation predicates were identified from the analysis; representations for most of these are not widely available. The classes are: part-whole (which are commonly modeled throughout semantic and linked-data networks), geometric, processes, human intention, and spatial prepositions. These are commonly found in the ‘real world’ and support the environmental science basis for digital topographical mapping. The spatial relation concepts are based on sets of relation terms presented in this chapter, though these lists are not prescriptive or exhaustive. The results of this study make explicit the concepts forming a broad set of spatial relation expressions, which in turn form the basis for expanding the range of possible queries for topographical data analysis and mapping.

Mixing geometric and radiometric features for change classification

NASA Astrophysics Data System (ADS)

Fournier, Alexandre; Descombes, Xavier; Zerubia, Josiane

2008-02-01

Most basic change detection algorithms use a pixel-based approach. Whereas such approach is quite well defined for monitoring important area changes (such as urban growth monitoring) in low resolution images, an object based approach seems more relevant when the change detection is specifically aimed toward targets (such as small buildings and vehicles). In this paper, we present an approach that mixes radiometric and geometric features to qualify the changed zones. The goal is to establish bounds (appearance, disappearance, substitution ...) between the detected changes and the underlying objects. We proceed by first clustering the change map (containing each pixel bitemporal radiosity) in different classes using the entropy-kmeans algorithm. Assuming that most man-made objects have a polygonal shape, a polygonal approximation algorithm is then used in order to characterize the resulting zone shapes. Hence allowing us to refine the primary rough classification, by integrating the polygon orientations in the state space. Tests are currently conducted on Quickbird data.

Specific feature of magnetooptical images of stray fields of magnets of various geometrical shapes

NASA Astrophysics Data System (ADS)

Ivanov, V. E.; Koveshnikov, A. V.; Andreev, S. V.

2017-08-01

Specific features of magnetooptical images (MOIs) of stray fields near the faces of prismatic hard magnetic elements have been studied. Attention has primarily been focused on MOIs of fields near faces oriented perpendicular to the magnetic moment of hard magnetic elements. With regard to the polar sensitivity, MOIs have practically uniform brightness and geometrically they coincide with the figures of the bases of the elements. With regard to longitudinal sensitivity, MOIs consist of several sectors, the number of which is determined by the number of angles of the image. Each angle is divided by the bisectrix into two sectors of different brightnesses; therefore, the MOI of a triangular magnet consists of three sectors. A rectangle consists of four sectors separated by the bisectrices of the interior angles. In all types of figures, these lines converge at the center of the figure and form a singular point of the source or sink type.

SIFT optimization and automation for matching images from multiple temporal sources

NASA Astrophysics Data System (ADS)

Castillo-Carrión, Sebastián; Guerrero-Ginel, José-Emilio

2017-05-01

Scale Invariant Feature Transformation (SIFT) was applied to extract tie-points from multiple source images. Although SIFT is reported to perform reliably under widely different radiometric and geometric conditions, using the default input parameters resulted in too few points being found. We found that the best solution was to focus on large features as these are more robust and not prone to scene changes over time, which constitutes a first approach to the automation of processes using mapping applications such as geometric correction, creation of orthophotos and 3D models generation. The optimization of five key SIFT parameters is proposed as a way of increasing the number of correct matches; the performance of SIFT is explored in different images and parameter values, finding optimization values which are corroborated using different validation imagery. The results show that the optimization model improves the performance of SIFT in correlating multitemporal images captured from different sources.

Identifying the distinct features of geometric structures for hole trapping to generate radicals on rutile TiO₂(110) in photooxidation using density functional theory calculations with hybrid functional.

PubMed

Wang, Dong; Wang, Haifeng; Hu, P

2015-01-21

Using density functional theory calculations with HSE 06 functional, we obtained the structures of spin-polarized radicals on rutile TiO2(110), which is crucial to understand the photooxidation at the atomic level, and further calculate the thermodynamic stabilities of these radicals. By analyzing the results, we identify the structural features for hole trapping in the system, and reveal the mutual effects among the geometric structures, the energy levels of trapped hole states and their hole trapping capacities. Furthermore, the results from HSE 06 functional are compared to those from DFT + U and the stability trend of radicals against the number of slabs is tested. The effect of trapped holes on two important steps of the oxygen evolution reaction, i.e. water dissociation and the oxygen removal, is investigated and discussed.

Unification of the family of Garrison-Wright's phases.

PubMed

Cui, Xiao-Dong; Zheng, Yujun

2014-07-24

Inspired by Garrison and Wight's seminal work on complex-valued geometric phases, we generalize the concept of Pancharatnam's "in-phase" in interferometry and further develop a theoretical framework for unification of the abelian geometric phases for a biorthogonal quantum system modeled by a parameterized or time-dependent nonhermitian hamiltonian with a finite and nondegenerate instantaneous spectrum, that is, the family of Garrison-Wright's phases, which will no longer be confined in the adiabatic and nonadiabatic cyclic cases. Besides, we employ a typical example, Bethe-Lamb model, to illustrate how to apply our theory to obtain an explicit result for the Garrison-Wright's noncyclic geometric phase, and also to present its potential applications in quantum computation and information.

Gauge Gravity and Electroweak Theory

NASA Astrophysics Data System (ADS)

Hestenes, David

2008-09-01

Reformulation of the Dirac equation in terms of the real Spacetime Algebra (STA) reveals hidden geometric structure, including a geometric role for the unit imaginary as generator of rotations in a spacelike plane. The STA and the real Dirac equation play essential roles in a new Gauge Theory Gravity (GTG) version of General Relativity (GR). Besides clarifying the conceptual foundations of GR and facilitating complex computations, GTG opens up new possibilities for a unified gauge theory of gravity and quantum mechanics, including spacetime geometry of electroweak interactions. The Weinberg-Salam model fits perfectly into this geometric framework, and a promising variant that replaces chiral states with Majorana states is formulated to incorporate zitterbewegung in electron states.

Structure of complexes between aluminum chloride and other chlorides, 2: Alkali-(chloroaluminates). Gaseous complexes

NASA Technical Reports Server (NTRS)

Hargittai, M.

1980-01-01

The structural chemistry of complexes between aluminum chloride and other metal chlorides is important both for practice and theory. Condensed-phase as well as vapor-phase complexes are of interest. Structural information on such complexes is reviewed. The first emphasis is given to the molten state because of its practical importance. Aluminum chloride forms volatile complexes with other metal chlorides and these vapor-phase complexes are dealt with in the second part. Finally, the variations in molecular shape and geometrical parameters are summarized.

Influence of muscle-tendon complex geometrical parameters on modeling passive stretch behavior with the Discrete Element Method.

PubMed

Roux, A; Laporte, S; Lecompte, J; Gras, L-L; Iordanoff, I

2016-01-25

The muscle-tendon complex (MTC) is a multi-scale, anisotropic, non-homogeneous structure. It is composed of fascicles, gathered together in a conjunctive aponeurosis. Fibers are oriented into the MTC with a pennation angle. Many MTC models use the Finite Element Method (FEM) to simulate the behavior of the MTC as a hyper-viscoelastic material. The Discrete Element Method (DEM) could be adapted to model fibrous materials, such as the MTC. DEM could capture the complex behavior of a material with a simple discretization scheme and help in understanding the influence of the orientation of fibers on the MTC׳s behavior. The aims of this study were to model the MTC in DEM at the macroscopic scale and to obtain the force/displacement curve during a non-destructive passive tensile test. Another aim was to highlight the influence of the geometrical parameters of the MTC on the global mechanical behavior. A geometrical construction of the MTC was done using discrete element linked by springs. Young׳s modulus values of the MTC׳s components were retrieved from the literature to model the microscopic stiffness of each spring. Alignment and re-orientation of all of the muscle׳s fibers with the tensile axis were observed numerically. The hyper-elastic behavior of the MTC was pointed out. The structure׳s effects, added to the geometrical parameters, highlight the MTC׳s mechanical behavior. It is also highlighted by the heterogeneity of the strain of the MTC׳s components. DEM seems to be a promising method to model the hyper-elastic macroscopic behavior of the MTC with simple elastic microscopic elements. Copyright © 2015 Elsevier Ltd. All rights reserved.

Relationship between extent and complexity of coronary artery disease and different left ventricular geometric patterns in patients with coronary artery disease and hypertension

PubMed Central

Uçar, Hakan; Gür, Mustafa; Börekçi, Abdürrezzak; Yıldırım, Arafat; Baykan, Ahmet Oytun; Kalkan, Gülhan Yüksel; Koç, Mevlüt; Şeker, Taner; Coşkun, Mehmet; Şen, Ömer; Çaylı, Murat

2015-01-01

Objective: The relationship between severity of coronary artery disease (CAD) and left ventricler (LV) hypertrophy in hypertensive patients is well known. However, the association between the extent and complexity of CAD assessed with SYNTAX score (SS) and different LV geometric patterns has not been investigated. We aimed to investigate the association between SYNTAX score and different LV geometric patterns in hypertensive patients. Methods: The study had been made in our clinic between January 2013 and August 2013. We studied 251 CAD patients who had hypertension and who underwent coronary angiography (147 males, 104 females; mean age 61.61±9.9 years). Coronary angiography was performed based on clinical indications. SS was determined in all patients. Echocardiographic examination was performed in all subjects. Four different geometric patterns were determined in patients according to LV mass index (LVMI) and relative wall thickness (RWT) (Groups: NG-normal geometry, CR-concentric remodeling, EH-eccentric hypertrophy, and CH-concentric hypertrophy). Biochemical markers were measured in all participants. Results: The highest SS values were observed in the CH group compared with the NG, CR, and EH groups (p<0.05 for all). Also, the SS values of the EH group were higher than in the NG and CR groups (p<0.05 for all). Multivariate linear regression analysis showed that SS was independently associated with LV geometry (β=0.316, p=0.001), as well as age (β=0.163, p=0.007) and diabetes (β=-0.134, p=0.022). Conclusion: SYNTAX score is independently related with LV geometry in hypertensive patients. This result shows that LV remodeling is parallel to the increase in the extent and complexity of CAD in our study patients. PMID:25592099

APPROACHES TO GEOMETRIC DATA ANALYSIS ON BIG AREA ADDITIVELY MANUFACTURED (BAAM) PARTS

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

Dreifus, Gregory D; Ally, Nadya R; Post, Brian K

The promise of additive manufacturing is that a user can design and print complex geometries that are very difficult, if not impossible, to machine. The capabilities of 3D printing are restricted by a number of factors, including properties of the build material, time constraints, and geometric design restrictions. In this paper, a thorough accounting and study of the geometric restrictions that exist in the current iteration of additive manufacturing (AM) fused deposition modeling (FDM) technologies are discussed. Offline and online methodologies for collecting data sets for qualitative analysis of large scale AM, in particular Oak Ridge National Laboratory s (ORNL)more » big area additive manufacturing (BAAM) system, are summarized. In doing so, a survey of tools for designers and software developers is provided. In particular, strategies in which geometric data can be used as training sets for smarter AM technologies in the future are explained as well.« less

Software systems for modeling articulated figures

NASA Technical Reports Server (NTRS)

Phillips, Cary B.

1989-01-01

Research in computer animation and simulation of human task performance requires sophisticated geometric modeling and user interface tools. The software for a research environment should present the programmer with a powerful but flexible substrate of facilities for displaying and manipulating geometric objects, yet insure that future tools have a consistent and friendly user interface. Jack is a system which provides a flexible and extensible programmer and user interface for displaying and manipulating complex geometric figures, particularly human figures in a 3D working environment. It is a basic software framework for high-performance Silicon Graphics IRIS workstations for modeling and manipulating geometric objects in a general but powerful way. It provides a consistent and user-friendly interface across various applications in computer animation and simulation of human task performance. Currently, Jack provides input and control for applications including lighting specification and image rendering, anthropometric modeling, figure positioning, inverse kinematics, dynamic simulation, and keyframe animation.

Geometry Helps to Compare Persistence Diagrams

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

Kerber, Michael; Morozov, Dmitriy; Nigmetov, Arnur

2015-11-16

Exploiting geometric structure to improve the asymptotic complexity of discrete assignment problems is a well-studied subject. In contrast, the practical advantages of using geometry for such problems have not been explored. We implement geometric variants of the Hopcroft--Karp algorithm for bottleneck matching (based on previous work by Efrat el al.), and of the auction algorithm by Bertsekas for Wasserstein distance computation. Both implementations use k-d trees to replace a linear scan with a geometric proximity query. Our interest in this problem stems from the desire to compute distances between persistence diagrams, a problem that comes up frequently in topological datamore » analysis. We show that our geometric matching algorithms lead to a substantial performance gain, both in running time and in memory consumption, over their purely combinatorial counterparts. Moreover, our implementation significantly outperforms the only other implementation available for comparing persistence diagrams.« less

MECH: Algorithms and Tools for Automated Assessment of Potential Attack Locations

DTIC Science & Technology

2015-10-06

conscious and subconscious processing of the geometric structure of the local terrain, sight lines to prominent or useful terrain features, proximity...This intuition or instinct is the outcome of an unconscious or subconscious integration of available facts and impressions. Thus, in the search...adjacency. Even so, we inevitably introduce a bias between events and non-event road locations when calculating the route visibility features. 63

Geometric distortions affect face recognition in chimpanzees (Pan troglodytes) and monkeys (Macaca mulatta).

PubMed

Taubert, Jessica; Parr, Lisa A

2011-01-01

All primates can recognize faces and do so by analyzing the subtle variation that exists between faces. Through a series of three experiments, we attempted to clarify the nature of second-order information processing in nonhuman primates. Experiment one showed that both chimpanzees (Pan troglodytes) and rhesus monkeys (Macaca mulatta) tolerate geometric distortions along the vertical axis, suggesting that information about absolute position of features does not contribute to accurate face recognition. Chimpanzees differed from monkeys, however, in that they were more sensitive to distortions along the horizontal axis, suggesting that when building a global representation of facial identity, horizontal relations between features are more diagnostic of identity than vertical relations. Two further experiments were performed to determine whether the monkeys were simply less sensitive to horizontal relations compared to chimpanzees or were instead relying on local features. The results of these experiments confirm that monkeys can utilize a holistic strategy when discriminating between faces regardless of familiarity. In contrast, our data show that chimpanzees, like humans, use a combination of holistic and local features when the faces are unfamiliar, but primarily holistic information when the faces become familiar. We argue that our comparative approach to the study of face recognition reveals the impact that individual experience and social organization has on visual cognition.

Imperfectly geometric shapes of nanograting structures as solar absorbers with superior performance for solar cells.

PubMed

Nguyen-Huu, Nghia; Cada, Michael; Pištora, Jaromír

2014-03-10

The expectation of perfectly geometric shapes of subwavelength grating (SWG) structures such as smoothness of sidewalls and sharp corners and nonexistence of grating defects is not realistic due to micro/nanofabrication processes. This work numerically investigates optical properties of an optimal solar absorber comprising a single-layered silicon (Si) SWG deposited on a finite Si substrate, with a careful consideration given to effects of various types of its imperfect geometry. The absorptance spectra of the solar absorber with different geometric shapes, namely, the grating with attached nanometer-sized features at the top and bottom of sidewalls and periodic defects within four and ten grating periods are investigated comprehensively. It is found that the grating with attached features at the bottom absorbs more energy than both the one at the top and the perfect grating. In addition, it is shown that the grating with defects in each fourth period exhibits the highest average absorptance (91%) compared with that of the grating having defects in each tenth period (89%), the grating with attached features (89%), and the perfect one (86%). Moreover, the results indicate that the absorptance spectrum of the imperfect structures is insensitive to angles of incidence. Furthermore, the absorptance enhancement is clearly demonstrated by computing magnetic field, energy density, and Poynting vector distributions. The results presented in this study prove that imperfect geometries of the nanograting structure display a higher absorptance than the perfect one, and provide such a practical guideline for nanofabrication capabilities necessary to be considered by structure designers.

Understanding magnetotransport signatures in networks of connected permalloy nanowires

NASA Astrophysics Data System (ADS)

Le, B. L.; Park, J.; Sklenar, J.; Chern, G.-W.; Nisoli, C.; Watts, J. D.; Manno, M.; Rench, D. W.; Samarth, N.; Leighton, C.; Schiffer, P.

2017-02-01

The change in electrical resistance associated with the application of an external magnetic field is known as the magnetoresistance (MR). The measured MR is quite complex in the class of connected networks of single-domain ferromagnetic nanowires, known as "artificial spin ice," due to the geometrically induced collective behavior of the nanowire moments. We have conducted a thorough experimental study of the MR of a connected honeycomb artificial spin ice, and we present a simulation methodology for understanding the detailed behavior of this complex correlated magnetic system. Our results demonstrate that the behavior, even at low magnetic fields, can be well described only by including significant contributions from the vertices at which the legs meet, opening the door to new geometrically induced MR phenomena.

High-fidelity meshes from tissue samples for diffusion MRI simulations.

PubMed

Panagiotaki, Eleftheria; Hall, Matt G; Zhang, Hui; Siow, Bernard; Lythgoe, Mark F; Alexander, Daniel C

2010-01-01

This paper presents a method for constructing detailed geometric models of tissue microstructure for synthesizing realistic diffusion MRI data. We construct three-dimensional mesh models from confocal microscopy image stacks using the marching cubes algorithm. Random-walk simulations within the resulting meshes provide synthetic diffusion MRI measurements. Experiments optimise simulation parameters and complexity of the meshes to achieve accuracy and reproducibility while minimizing computation time. Finally we assess the quality of the synthesized data from the mesh models by comparison with scanner data as well as synthetic data from simple geometric models and simplified meshes that vary only in two dimensions. The results support the extra complexity of the three-dimensional mesh compared to simpler models although sensitivity to the mesh resolution is quite robust.

A low-complexity geometric bilateration method for localization in Wireless Sensor Networks and its comparison with Least-Squares methods.

PubMed

Cota-Ruiz, Juan; Rosiles, Jose-Gerardo; Sifuentes, Ernesto; Rivas-Perea, Pablo

2012-01-01

This research presents a distributed and formula-based bilateration algorithm that can be used to provide initial set of locations. In this scheme each node uses distance estimates to anchors to solve a set of circle-circle intersection (CCI) problems, solved through a purely geometric formulation. The resulting CCIs are processed to pick those that cluster together and then take the average to produce an initial node location. The algorithm is compared in terms of accuracy and computational complexity with a Least-Squares localization algorithm, based on the Levenberg-Marquardt methodology. Results in accuracy vs. computational performance show that the bilateration algorithm is competitive compared with well known optimized localization algorithms.

A New Quaternion-Based Kalman Filter for Real-Time Attitude Estimation Using the Two-Step Geometrically-Intuitive Correction Algorithm.

PubMed

Feng, Kaiqiang; Li, Jie; Zhang, Xiaoming; Shen, Chong; Bi, Yu; Zheng, Tao; Liu, Jun

2017-09-19

In order to reduce the computational complexity, and improve the pitch/roll estimation accuracy of the low-cost attitude heading reference system (AHRS) under conditions of magnetic-distortion, a novel linear Kalman filter, suitable for nonlinear attitude estimation, is proposed in this paper. The new algorithm is the combination of two-step geometrically-intuitive correction (TGIC) and the Kalman filter. In the proposed algorithm, the sequential two-step geometrically-intuitive correction scheme is used to make the current estimation of pitch/roll immune to magnetic distortion. Meanwhile, the TGIC produces a computed quaternion input for the Kalman filter, which avoids the linearization error of measurement equations and reduces the computational complexity. Several experiments have been carried out to validate the performance of the filter design. The results demonstrate that the mean time consumption and the root mean square error (RMSE) of pitch/roll estimation under magnetic disturbances are reduced by 45.9% and 33.8%, respectively, when compared with a standard filter. In addition, the proposed filter is applicable for attitude estimation under various dynamic conditions.

A New Quaternion-Based Kalman Filter for Real-Time Attitude Estimation Using the Two-Step Geometrically-Intuitive Correction Algorithm

PubMed Central

Feng, Kaiqiang; Li, Jie; Zhang, Xiaoming; Shen, Chong; Bi, Yu; Zheng, Tao; Liu, Jun

2017-01-01

In order to reduce the computational complexity, and improve the pitch/roll estimation accuracy of the low-cost attitude heading reference system (AHRS) under conditions of magnetic-distortion, a novel linear Kalman filter, suitable for nonlinear attitude estimation, is proposed in this paper. The new algorithm is the combination of two-step geometrically-intuitive correction (TGIC) and the Kalman filter. In the proposed algorithm, the sequential two-step geometrically-intuitive correction scheme is used to make the current estimation of pitch/roll immune to magnetic distortion. Meanwhile, the TGIC produces a computed quaternion input for the Kalman filter, which avoids the linearization error of measurement equations and reduces the computational complexity. Several experiments have been carried out to validate the performance of the filter design. The results demonstrate that the mean time consumption and the root mean square error (RMSE) of pitch/roll estimation under magnetic disturbances are reduced by 45.9% and 33.8%, respectively, when compared with a standard filter. In addition, the proposed filter is applicable for attitude estimation under various dynamic conditions. PMID:28925979

A new concept of feature-based gauge for coordinate measuring arm evaluation

NASA Astrophysics Data System (ADS)

Cuesta, E.; González-Madruga, D.; Alvarez, B. J.; Barreiro, J.

2014-06-01

Articulated arm coordinate measuring machines (AACMM or CMA) have conquered a market share in the actual dimensional metrology field, overall when their role implies the inspection of geometrical and dimensional tolerances in an accurate 3D environment for medium-size parts. However, the unavoidable fact of AACMM manual operation constrains its reliability to a great extent, avoiding rigorous evaluation and casting doubt upon the usefulness of external calibration. In this research, a dimensional gauge especially aimed at AACMM evaluation has been developed. Furthermore, the operator skill will be revealed through the use of this gauge. A set of geometrical features, some of them oriented to evaluate the operator and others the equipment, have been collected for the gauge. The proposed evaluation methodology clearly distinguishes between dimensional and geometrical tolerances (with or without datum references), whereas actual verification standards only consider the former. Next, quality indicators deduced from the measurement results are proposed in order to compare AACMM versus coordinate measuring machine (CMM) performance, assuming that CMM possess the maximum accuracy that AACMM could reach, because CMM combines maximum contact accuracy with minimum operator influence. As a result, AACMM evaluation time could be significantly reduced since this gauge allows us to perform a customized evaluation of only those specific tolerances of interest to the user.

Influence of the geometric configuration of accretion flow on the black hole spin dependence of relativistic acoustic geometry

NASA Astrophysics Data System (ADS)

Tarafdar, Pratik; Das, Tapas K.

Linear perturbation of general relativistic accretion of low angular momentum hydrodynamic fluid onto a Kerr black hole leads to the formation of curved acoustic geometry embedded within the background flow. Characteristic features of such sonic geometry depend on the black hole spin. Such dependence can be probed by studying the correlation of the acoustic surface gravity κ with the Kerr parameter a. The κ-a relationship further gets influenced by the geometric configuration of the accretion flow structure. In this work, such influence has been studied for multitransonic shocked accretion where linear perturbation of general relativistic flow profile leads to the formation of two analogue black hole-type horizons formed at the sonic points and one analogue white hole-type horizon which is formed at the shock location producing divergent acoustic surface gravity. Dependence of the κ-a relationship on the geometric configuration has also been studied for monotransonic accretion, over the entire span of the Kerr parameter including retrograde flow. For accreting astrophysical black holes, the present work thus investigates how the salient features of the embedded relativistic sonic geometry may be determined not only by the background spacetime, but also by the flow configuration of the embedding matter.

Space-time evolution of a growth fold (Betic Cordillera, Spain). Evidences from 3D geometrical modelling

NASA Astrophysics Data System (ADS)

Martin-Rojas, Ivan; Alfaro, Pedro; Estévez, Antonio

2014-05-01

We present a study that encompasses several software tools (iGIS©, ArcGIS©, Autocad©, etc.) and data (geological mapping, high resolution digital topographic data, high resolution aerial photographs, etc.) to create a detailed 3D geometric model of an active fault propagation growth fold. This 3D model clearly shows structural features of the analysed fold, as well as growth relationships and sedimentary patterns. The results obtained permit us to discuss the kinematics and structural evolution of the fold and the fault in time and space. The study fault propagation fold is the Crevillente syncline. This fold represents the northern limit of the Bajo Segura Basin, an intermontane basin in the Eastern Betic Cordillera (SE Spain) developed from upper Miocene on. 3D features of the Crevillente syncline, including growth pattern, indicate that limb rotation and, consequently, fault activity was higher during Messinian than during Tortonian; consequently, fault activity was also higher. From Pliocene on our data point that limb rotation and fault activity steadies or probably decreases. This in time evolution of the Crevillente syncline is not the same all along the structure; actually the 3D geometric model indicates that observed lateral heterogeneity is related to along strike variation of fault displacement.

[Visual Texture Agnosia in Humans].

PubMed

Suzuki, Kyoko

2015-06-01

Visual object recognition requires the processing of both geometric and surface properties. Patients with occipital lesions may have visual agnosia, which is impairment in the recognition and identification of visually presented objects primarily through their geometric features. An analogous condition involving the failure to recognize an object by its texture may exist, which can be called visual texture agnosia. Here we present two cases with visual texture agnosia. Case 1 had left homonymous hemianopia and right upper quadrantanopia, along with achromatopsia, prosopagnosia, and texture agnosia, because of damage to his left ventromedial occipitotemporal cortex and right lateral occipito-temporo-parietal cortex due to multiple cerebral embolisms. Although he showed difficulty matching and naming textures of real materials, he could readily name visually presented objects by their contours. Case 2 had right lower quadrantanopia, along with impairment in stereopsis and recognition of texture in 2D images, because of subcortical hemorrhage in the left occipitotemporal region. He failed to recognize shapes based on texture information, whereas shape recognition based on contours was well preserved. Our findings, along with those of three reported cases with texture agnosia, indicate that there are separate channels for processing texture, color, and geometric features, and that the regions around the left collateral sulcus are crucial for texture processing.

Shape-optimization of round-to-slot holes for improving film cooling effectiveness on a flat surface

NASA Astrophysics Data System (ADS)

Huang, Ying; Zhang, Jing-zhou; Wang, Chun-hua

2018-01-01

Single-objective optimization for improving adiabatic film cooling effectiveness is performed for single row of round-to-slot film cooling holes on a flat surface by using CFD analysis and surrogate approximation methods. Among the main geometric parameters, dimensionless hole-to-hole pitch (P/d) and slot length-to-diameter (l/d) are fixed as 2.4 and 2 respectively, and the other parameters (hole height-to-diameter ratio, slot width-to-diameter and inclination angle) are chosen as the design variables. Given a wide range of possible geometric variables, the geometric optimization of round-to-slot holes is carried out under two typical blowing ratios of M = 0.5 and M = 1.5 by selecting a spatially-averaged adiabatic film cooling effectiveness between x/d = 2 and x/d = 12 as the objective function to be maximized. Radial basis function neural network is applied for constructing the surrogate model and then the optimal design point is searched by a genetic algorithm. It is revealed that the optimal round-to-slot hole is of converging feature under a low blowing ratio but of diffusing feature under a high blowing ratio. Further, the influence principle of optimal round-to-slot geometry on film cooling performance is illustrated according to the detailed flow and thermal behaviors.

Shape-optimization of round-to-slot holes for improving film cooling effectiveness on a flat surface

NASA Astrophysics Data System (ADS)

Huang, Ying; Zhang, Jing-zhou; Wang, Chun-hua

2018-06-01

Single-objective optimization for improving adiabatic film cooling effectiveness is performed for single row of round-to-slot film cooling holes on a flat surface by using CFD analysis and surrogate approximation methods. Among the main geometric parameters, dimensionless hole-to-hole pitch ( P/ d) and slot length-to-diameter ( l/ d) are fixed as 2.4 and 2 respectively, and the other parameters (hole height-to-diameter ratio, slot width-to-diameter and inclination angle) are chosen as the design variables. Given a wide range of possible geometric variables, the geometric optimization of round-to-slot holes is carried out under two typical blowing ratios of M = 0.5 and M = 1.5 by selecting a spatially-averaged adiabatic film cooling effectiveness between x/ d = 2 and x/ d = 12 as the objective function to be maximized. Radial basis function neural network is applied for constructing the surrogate model and then the optimal design point is searched by a genetic algorithm. It is revealed that the optimal round-to-slot hole is of converging feature under a low blowing ratio but of diffusing feature under a high blowing ratio. Further, the influence principle of optimal round-to-slot geometry on film cooling performance is illustrated according to the detailed flow and thermal behaviors.

Alternative design consistency rating methods for two-lane rural highways

DOT National Transportation Integrated Search

2000-08-01

Design consistency refers to the conformance of a highway's geometry with driver expectancy. Drivers make fewer errors in the vicinity of geometric features that conform with their expectations. Techniques to evaluate the consistency of a design docu...

A Radial Age Gradient in the Geometrically Thick Disk of the Milky Way

NASA Astrophysics Data System (ADS)

Martig, Marie; Minchev, Ivan; Ness, Melissa; Fouesneau, Morgan; Rix, Hans-Walter

2016-11-01

In the Milky Way, the thick disk can be defined using individual stellar abundances, kinematics, or age, or geometrically, as stars high above the midplane. In nearby galaxies, where only a geometric definition can be used, thick disks appear to have large radial scale lengths, and their red colors suggest that they are uniformly old. The Milky Way’s geometrically thick disk is also radially extended, but it is far from chemically uniform: α-enhanced stars are confined within the inner Galaxy. In simulated galaxies, where old stars are centrally concentrated, geometrically thick disks are radially extended, too. Younger stellar populations flare in the simulated disks’ outer regions, bringing those stars high above the midplane. The resulting geometrically thick disks therefore show a radial age gradient, from old in their central regions to younger in their outskirts. Based on our age estimates for a large sample of giant stars in the APOGEE survey, we can now test this scenario for the Milky Way. We find that the geometrically defined thick disk in the Milky Way has indeed a strong radial age gradient: the median age for red clump stars goes from ∼9 Gyr in the inner disk to 5 Gyr in the outer disk. We propose that at least some nearby galaxies could also have thick disks that are not uniformly old, and that geometrically thick disks might be complex structures resulting from different formation mechanisms in their inner and outer parts.

Magneto-thermo-elastokinetics of geometrically nonlinear laminated composite plates. Part 2: vibration and wave propagation

NASA Technical Reports Server (NTRS)

Qin, Zhanming; Hasanyan, Davresh; Librescu, Liviu; Ambur, Damodar R.

2005-01-01

In Part 1 of this paper, the governing equations of geometrically nonlinear, anisotropic composite plates incorporating magneto-thermo-elastic effects have been derived. In order to gain insight into the implications of a number of geometrical and physical features of the system. three special cases are investigated: (i) free vibration of a plate strip immersed in a transversal magnetic field; (ii) free vibration of the plate strip immersed in an axial magnetic field; (iii) magneto-elastic wave propagations of an infinite plate. Within each of these cases, a prescribed uniform thermal field is considered. Special coupling characteristics between the magnetic and elastic fields are put into evidence. Extensive numerical investigations are conducted and pertinent conclusions which highlight the various effects induced by the magneto-elastic couplings and the finite electroconductivity, are outlined.

Mechanical Characterization of Partially Crystallized Sphere Packings

NASA Astrophysics Data System (ADS)

Hanifpour, M.; Francois, N.; Vaez Allaei, S. M.; Senden, T.; Saadatfar, M.

2014-10-01

We study grain-scale mechanical and geometrical features of partially crystallized packings of frictional spheres, produced experimentally by a vibrational protocol. By combining x-ray computed tomography, 3D image analysis, and discrete element method simulations, we have access to the 3D structure of internal forces. We investigate how the network of mechanical contacts and intergranular forces change when the packing structure evolves from amorphous to near perfect crystalline arrangements. We compare the behavior of the geometrical neighbors (quasicontracts) of a grain to the evolution of the mechanical contacts. The mechanical coordination number Zm is a key parameter characterizing the crystallization onset. The high fluctuation level of Zm and of the force distribution in highly crystallized packings reveals that a geometrically ordered structure still possesses a highly random mechanical backbone similar to that of amorphous packings.

Carbene-aerogen bonds: an ab initio study

NASA Astrophysics Data System (ADS)

Esrafili, Mehdi D.; Sabouri, Ayda

2017-04-01

Through the use of ab initio calculations, the possibility of formation of σ-hole interaction between ZO3 (Z = Ar, Kr and Xe) and carbene species is investigated. Since singlet carbenes show a negative electrostatic potential on their divalent carbon atom, they can favourably interact with the positive electrostatic potential generated by the σ-hole of Z atom of ZO3. The characteristic of this interaction, termed as 'carbene-aerogen' bond, is analysed in terms of geometric, interaction energies and electronic features. The energy decomposition analysis indicates that for all complexes analysed here, the electrostatic energy is more negative than the polarisation or dispersion energy term. According to the electron density analysis, some partial covalent character can be ascribed to XeṡṡṡC interactions. In addition, the carbene-aerogen bond exhibits cooperative effects with the HṡṡṡO hydrogen-bonding interaction in ternary complexes where both interactions coexist. For a given carbene, the amount of these cooperative effects increases with the size of the Z atom. The results obtained in this work may be helpful for the extension and future application of σ-hole intermolecular interactions as well as coordination chemistry.

Polydopamine-based concentric nanoshells with programmable architectures and plasmonic properties.

PubMed

Choi, Chun Kit K; Zhuo, Xiaolu; Chiu, Yee Ting Elaine; Yang, Hongrong; Wang, Jianfang; Choi, Chung Hang Jonathan

2017-11-09

Nanoshells, classically comprising gold as the metallic component and silica as the dielectric material, are important for fundamental studies in nanoplasmonics. They also empower a myriad of applications, including sensing, energy harvesting, and cancer therapy. Yet, laborious preparation precludes the development of next-generation nanoshells with structural complexity, compositional diversity, and tailorable plasmonic behaviors. This work presents an efficient approach to the bottom-up assembly of concentric nanoshells. By employing polydopamine as the dielectric material and exploiting its intrinsic adhesiveness and pH-tunable surface charge, the growth of each shell only takes 3-4 hours at room temperature. A series of polydopamine-based concentric nanoshells with programmable nanogap thickness, elemental composition (gold and silver), and geometrical configuration (number of layers) is prepared, followed by extensive structural characterization. Four of the silver-containing nanostructures are newly reported. Systematic investigations into the plasmonic properties of concentric nanoshells as a function of their structural parameters further reveal multiple Fano resonances and local-field "hot spots", infrequently reported plasmonic features for individual nanostructures fabricated using bottom-up wet chemistry. These results establish materials design rules for engineering complex plasmon-based systems originating from the integration of multiple plasmonic elements into defined locations within a compact nanostructure.

Structural analysis using thrust-fault hanging-wall sequence diagrams: Ogden duplex, Wasatch Range, Utah

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

Schirmer, T.W.

1988-05-01

Detailed mapping and cross-section traverses provide the control for structural analysis and geometric modeling of the Ogden duplex, a complex thrust system exposed in the Wasatch Mountains, east of Ogden, Utah. The structures consist of east-dipping folded thrust faults, basement-cored horses, lateral ramps and folds, and tear faults. The sequence of thrusting determined by means of lateral overlap of horses, thrust-splay relationships, and a top-to-bottom piggyback development is Willard thrust, Ogden thrust, Weber thrust, and Taylor thrust. Major decollement zones occur in the Cambrian shales and limestones. The Tintic Quartzite is the marker for determining gross geometries of horses. Thismore » exposed duplex serves as a good model to illustrate the method of constructing a hanging-wall sequence diagram - a series of longitudinal cross sections that move forward in time and space, and show how a thrust system formed as it moved updip over various footwall ramps. A hanging wall sequence diagram also shows the complex lateral variations in a thrust system and helps to locate lateral ramps, lateral folds, tear faults, and other features not shown on dip-oriented cross sections. 8 figures.« less

Manifold angles, the concept of self-similarity, and angle-enhanced bifurcation diagrams

PubMed Central

Beims, Marcus W.; Gallas, Jason A. C.

2016-01-01

Chaos and regularity are routinely discriminated by using Lyapunov exponents distilled from the norm of orthogonalized Lyapunov vectors, propagated during the temporal evolution of the dynamics. Such exponents are mean-field-like averages that, for each degree of freedom, squeeze the whole temporal evolution complexity into just a single number. However, Lyapunov vectors also contain a step-by-step record of what exactly happens with the angles between stable and unstable manifolds during the whole evolution, a big-data information permanently erased by repeated orthogonalizations. Here, we study changes of angles between invariant subspaces as observed during temporal evolution of Hénon’s system. Such angles are calculated numerically and analytically and used to characterize self-similarity of a chaotic attractor. In addition, we show how standard tools of dynamical systems may be angle-enhanced by dressing them with informations not difficult to extract. Such angle-enhanced tools reveal unexpected and practical facts that are described in detail. For instance, we present a video showing an angle-enhanced bifurcation diagram that exposes from several perspectives the complex geometrical features underlying the attractors. We believe such findings to be generic for extended classes of systems. PMID:26732416

Manifold angles, the concept of self-similarity, and angle-enhanced bifurcation diagrams

NASA Astrophysics Data System (ADS)

Beims, Marcus W.; Gallas, Jason A. C.

2016-01-01

Chaos and regularity are routinely discriminated by using Lyapunov exponents distilled from the norm of orthogonalized Lyapunov vectors, propagated during the temporal evolution of the dynamics. Such exponents are mean-field-like averages that, for each degree of freedom, squeeze the whole temporal evolution complexity into just a single number. However, Lyapunov vectors also contain a step-by-step record of what exactly happens with the angles between stable and unstable manifolds during the whole evolution, a big-data information permanently erased by repeated orthogonalizations. Here, we study changes of angles between invariant subspaces as observed during temporal evolution of Hénon’s system. Such angles are calculated numerically and analytically and used to characterize self-similarity of a chaotic attractor. In addition, we show how standard tools of dynamical systems may be angle-enhanced by dressing them with informations not difficult to extract. Such angle-enhanced tools reveal unexpected and practical facts that are described in detail. For instance, we present a video showing an angle-enhanced bifurcation diagram that exposes from several perspectives the complex geometrical features underlying the attractors. We believe such findings to be generic for extended classes of systems.

Automated quadrilateral surface discretization method and apparatus usable to generate mesh in a finite element analysis system

DOEpatents

Blacker, Teddy D.

1994-01-01

An automatic quadrilateral surface discretization method and apparatus is provided for automatically discretizing a geometric region without decomposing the region. The automated quadrilateral surface discretization method and apparatus automatically generates a mesh of all quadrilateral elements which is particularly useful in finite element analysis. The generated mesh of all quadrilateral elements is boundary sensitive, orientation insensitive and has few irregular nodes on the boundary. A permanent boundary of the geometric region is input and rows are iteratively layered toward the interior of the geometric region. Also, an exterior permanent boundary and an interior permanent boundary for a geometric region may be input and the rows are iteratively layered inward from the exterior boundary in a first counter clockwise direction while the rows are iteratively layered from the interior permanent boundary toward the exterior of the region in a second clockwise direction. As a result, a high quality mesh for an arbitrary geometry may be generated with a technique that is robust and fast for complex geometric regions and extreme mesh gradations.

Mathematical figures.

PubMed

Fara, Patricia

2009-06-01

Renaissance philosophers believed that God had created a harmonious cosmos bonded together mathematically. This intellectual approach was also embraced by some artists, who incorporated complex numerical and geometrical symbolism within their portraits.

Rhombus-shaped tetranuclear [Ln4] complexes [Ln = Dy(III) and Ho(III)]: synthesis, structure, and SMM behavior.

PubMed

Chandrasekhar, Vadapalli; Hossain, Sakiat; Das, Sourav; Biswas, Sourav; Sutter, Jean-Pascal

2013-06-03

The reaction of a new hexadentate Schiff base hydrazide ligand (LH3) with rare earth(III) chloride salts in the presence of triethylamine as the base afforded two planar tetranuclear neutral complexes: [{(LH)2Dy4}(μ2-O)4](H2O)8·2CH3OH·8H2O (1) and [{(LH)2Ho4}(μ2-O)4](H2O)8·6CH3OH·4H2O (2). These neutral complexes possess a structure in which all of the lanthanide ions and the donor atoms of the ligand remain in a perfect plane. Each doubly deprotonated ligand holds two Ln(III) ions in its two distinct chelating coordination pockets to form [LH(Ln)2](4+) units. Two such units are connected by four [μ2-O](2-) ligands to form a planar tetranuclear assembly with an Ln(III)4 core that possesses a rhombus-shaped structure. Detailed static and dynamic magnetic analysis of 1 and 2 revealed single-molecule magnet (SMM) behavior for complex 1. A peculiar feature of the χM" versus temperature curve is that two peaks that are frequency-dependent are revealed, indicating the occurrence of two relaxation processes that lead to two energy barriers (16.8 and 54.2 K) and time constants (τ0 = 1.4 × 10(-6) s, τ0 = 7.2 × 10(-7) s). This was related to the presence of two distinct geometrical sites for Dy(III) in complex 1.

Thermal imitators with single directional invisibility

NASA Astrophysics Data System (ADS)

Wang, Ruizhe; Xu, Liujun; Huang, Jiping

2017-12-01

Thermal metamaterials have been intensively studied during the past years to achieve the long-standing dream of invisibility, illusion, and other inconceivable thermal phenomena. However, many thermal metamaterials can only exhibit omnidirectional thermal response, which take on the distinct feature of geometrical isotropy. In this work, we theoretically design and experimentally fabricate a pair of thermal imitators by applying geometrical anisotropy provided by elliptical/ellipsoidal particles and layered structures. This pair of thermal imitators possesses thermal invisibility in one direction, while having thermal opacity in other directions. This work may open a gate in designing direction-dependent thermal metamaterials.

Recent transformations in the high-Arctic glacier landsystem Hørbyebreen, Svalbard.

NASA Astrophysics Data System (ADS)

Ewertowski, Marek; Evans, David; Roberts, David; Tomczyk, Aleksandra

2016-04-01

The Hørbyebreen is a polythermal valley glacier in the Petuniabukta area, central part of Spitsbergen. Since the end of the Little Ice Age, a debris-free glacier margin retreated by more than 3 km exposing complex landform assemblages including ice-cored moraines, flutes, eskers and geometric ridge networks. Glacier recession and landforms' development in the terrestrial parts of the foreland were quantified using time-series of orthophotos and digital elevation models (generated based on 1961, 1990, 2009 aerial photographs) and high resolution satellite images from 2013. Additionally, detailed analyses of a case study area were performed based on unmanned aerial vehicle (UAV) imagery (3 cm resolution) captured in 2014. A time-series of 1:5,000 geomorphological maps of the whole foreland, together with 1:300 map of a sample area of complex geometric ridge networks and results of sedimentological analysis, enable us to assess the evolution of glacial landform assemblages. The two main areas of the Hørbyebreen foreland were identified as: (1) the outer moraine ridge and (2) the inner zone between the contemporary ice edge and the outer moraine ridge. The outer moraine ridge was relatively stable and subject to mainly vertical transformation between 1960 and 2009. The most prominent changes were observed within the inner zone. In 1960 it was covered by glacier ice, whereas in 2009 this area exhibited a wide range of subglacial and englacial landforms, including a network of rectilinear ridges which we interpret as crevasse infills created by the injection of pressurized englacial meltwater. Other prominent features in this zone include controlled moraine, indicative of sub-marginal debris entrainment by the polythermal snout, and complex esker network. This landform assemblage is diagnostic of a variable process-form regime in which the glacial geomorphology of polythermal conditions is supplemented with surge signatures and therefore is likely to be the most representative landsystem model for terrestrial-terminating Svalbard glaciers. The research was founded by Polish National Science Centre (project granted by decision number DEC-2011/01/D/ST10/06494).

Gauge freedom in observables and Landsberg's nonadiabatic geometric phase: Pumping spectroscopy of interacting open quantum systems

NASA Astrophysics Data System (ADS)

Pluecker, T.; Wegewijs, M. R.; Splettstoesser, J.

2017-04-01

We set up a general density-operator approach to geometric steady-state pumping through slowly driven open quantum systems. This approach applies to strongly interacting systems that are weakly coupled to multiple reservoirs at high temperature, illustrated by an Anderson quantum dot. Pumping gives rise to a nonadiabatic geometric phase that can be described by a framework originally developed for classical dissipative systems by Landsberg. This geometric phase is accumulated by the transported observable (charge, spin, energy) and not by the quantum state. It thus differs radically from the adiabatic Berry-Simon phase, even when generalizing it to mixed states, following Sarandy and Lidar. As a key feature, our geometric formulation of pumping stays close to a direct physical intuition (i) by tying gauge transformations to calibration of the meter registering the transported observable and (ii) by deriving a geometric connection from a driving-frequency expansion of the current. Furthermore, our approach provides a systematic and efficient way to compute the geometric pumping of various observables, including charge, spin, energy, and heat. These insights seem to be generalizable beyond the present paper's working assumptions (e.g., Born-Markov limit) to more general open-system evolutions involving memory and strong-coupling effects due to low-temperature reservoirs as well. Our geometric curvature formula reveals a general experimental scheme for performing geometric transport spectroscopy that enhances standard nonlinear spectroscopies based on measurements for static parameters. We indicate measurement strategies for separating the useful geometric pumping contribution to transport from nongeometric effects. A large part of the paper is devoted to an explicit comparison with the Sinitsyn-Nemenmann full-counting-statistics (FCS) approach to geometric pumping, restricting attention to the first moments of the pumped observable. Covering all key aspects, gauge freedom, pumping connection, curvature, and gap condition, we argue that our approach is physically more transparent and, importantly, simpler for practical calculations. In particular, this comparison allows us to clarify how in the FCS approach an "adiabatic" approximation leads to a manifestly nonadiabatic result involving a finite retardation time of the response to parameter driving.

Eye-tracking Reveals Abnormal Visual Preference for Geometric Images as an Early Biomarker of an ASD Subtype Associated with Increased Symptom Severity

PubMed Central

Pierce, Karen; Marinero, Steven; Hazin, Roxana; McKenna, Benjamin; Barnes, Cynthia Carter; Malige, Ajith

2015-01-01

Background Clinically and biologically, ASD is heterogeneous. Unusual patterns of visual preference as indexed by eye-tracking are hallmarks, yet whether they can be used to define an early biomarker of ASD as a whole, or leveraged to define a subtype is unclear. To begin to examine this issue, large cohorts are required. Methods A sample of 334 toddlers from 6 distinct groups (115 ASD, 20 ASD-Features, 57 DD, 53 Other, 64 TD, and 25 Typ SIB) participated. Toddlers watched a movie containing both geometric and social images. Fixation duration and number of saccades within each AOI and validation statistics for this independent sample computed. Next, to maximize power, data from our previous study (N=110) was added totaling 444 subjects. A subset of toddlers repeated the eye-tracking procedure. Results As in the original study, a subset of toddlers with ASD fixated on geometric images greater than 69%. Using this cutoff, sensitivity for ASD was 21%, specificity 98%, and PPV 86%. Toddlers with ASD who strongly preferred geometric images had (a) worse cognitive, language, and social skills relative to toddlers with ASD who strongly preferred social images and (b) fewer saccades when viewing geometric images. Unaffected siblings of ASD probands did not show evidence of heightened preference for geometric images. Test-retest reliability was good. Examination of age effects suggest that this test may not be appropriate with children > 4 years. Conclusions Enhanced visual preference for geometric repetition may be an early developmental biomarker of an ASD subtype with more severe symptoms. PMID:25981170

Applying instructional design practices to evaluate and improve the roadway characteristics inventory (RCI) training curriculum : [summary].

DOT National Transportation Integrated Search

2010-01-01

The Roadway Characteristics Inventory (RCI) is one of FDOTs largest databases, including over 2 million records. The RCI contains data for several hundred features and characteristics representing geometric, operational, and administrative data re...

Finite element analysis of the Wolf Creek multispan curved girder bridge.

DOT National Transportation Integrated Search

2008-01-01

The use of curved girder bridges in highway construction has grown steadily during the last 40 years. Today, roughly 25% of newly constructed bridges have a curved alignment. Curved girder bridges have numerous complicating geometric features that di...

Intelligent services for discovery of complex geospatial features from remote sensing imagery

NASA Astrophysics Data System (ADS)

Yue, Peng; Di, Liping; Wei, Yaxing; Han, Weiguo

2013-09-01

Remote sensing imagery has been commonly used by intelligence analysts to discover geospatial features, including complex ones. The overwhelming volume of routine image acquisition requires automated methods or systems for feature discovery instead of manual image interpretation. The methods of extraction of elementary ground features such as buildings and roads from remote sensing imagery have been studied extensively. The discovery of complex geospatial features, however, is still rather understudied. A complex feature, such as a Weapon of Mass Destruction (WMD) proliferation facility, is spatially composed of elementary features (e.g., buildings for hosting fuel concentration machines, cooling towers, transportation roads, and fences). Such spatial semantics, together with thematic semantics of feature types, can be used to discover complex geospatial features. This paper proposes a workflow-based approach for discovery of complex geospatial features that uses geospatial semantics and services. The elementary features extracted from imagery are archived in distributed Web Feature Services (WFSs) and discoverable from a catalogue service. Using spatial semantics among elementary features and thematic semantics among feature types, workflow-based service chains can be constructed to locate semantically-related complex features in imagery. The workflows are reusable and can provide on-demand discovery of complex features in a distributed environment.

Automated feature detection and identification in digital point-ordered signals

DOEpatents

Oppenlander, Jane E.; Loomis, Kent C.; Brudnoy, David M.; Levy, Arthur J.

1998-01-01

A computer-based automated method to detect and identify features in digital point-ordered signals. The method is used for processing of non-destructive test signals, such as eddy current signals obtained from calibration standards. The signals are first automatically processed to remove noise and to determine a baseline. Next, features are detected in the signals using mathematical morphology filters. Finally, verification of the features is made using an expert system of pattern recognition methods and geometric criteria. The method has the advantage that standard features can be, located without prior knowledge of the number or sequence of the features. Further advantages are that standard features can be differentiated from irrelevant signal features such as noise, and detected features are automatically verified by parameters extracted from the signals. The method proceeds fully automatically without initial operator set-up and without subjective operator feature judgement.

Shape complexes: the intersection of label orderings and star convexity constraints in continuous max-flow medical image segmentation

PubMed Central

Baxter, John S. H.; Inoue, Jiro; Drangova, Maria; Peters, Terry M.

2016-01-01

Abstract. Optimization-based segmentation approaches deriving from discrete graph-cuts and continuous max-flow have become increasingly nuanced, allowing for topological and geometric constraints on the resulting segmentation while retaining global optimality. However, these two considerations, topological and geometric, have yet to be combined in a unified manner. The concept of “shape complexes,” which combine geodesic star convexity with extendable continuous max-flow solvers, is presented. These shape complexes allow more complicated shapes to be created through the use of multiple labels and super-labels, with geodesic star convexity governed by a topological ordering. These problems can be optimized using extendable continuous max-flow solvers. Previous approaches required computationally expensive coordinate system warping, which are ill-defined and ambiguous in the general case. These shape complexes are demonstrated in a set of synthetic images as well as vessel segmentation in ultrasound, valve segmentation in ultrasound, and atrial wall segmentation from contrast-enhanced CT. Shape complexes represent an extendable tool alongside other continuous max-flow methods that may be suitable for a wide range of medical image segmentation problems. PMID:28018937

Protein-induced geometric constraints and charge transfer in bacteriochlorophyll-histidine complexes in LH2.

PubMed

Wawrzyniak, Piotr K; Alia, A; Schaap, Roland G; Heemskerk, Mattijs M; de Groot, Huub J M; Buda, Francesco

2008-12-14

Bacteriochlorophyll-histidine complexes are ubiquitous in nature and are essential structural motifs supporting the conversion of solar energy into chemically useful compounds in a wide range of photosynthesis processes. A systematic density functional theory study of the NMR chemical shifts for histidine and for bacteriochlorophyll-a-histidine complexes in the light-harvesting complex II (LH2) is performed using the BLYP functional in combination with the 6-311++G(d,p) basis set. The computed chemical shift patterns are consistent with available experimental data for positive and neutral(tau) (N(tau) protonated) crystalline histidines. The results for the bacteriochlorophyll-a-histidine complexes in LH2 provide evidence that the protein environment is stabilizing the histidine close to the Mg ion, thereby inducing a large charge transfer of approximately 0.5 electronic equivalent. Due to this protein-induced geometric constraint, the Mg-coordinated histidine in LH2 appears to be in a frustrated state very different from the formal neutral(pi) (N(pi) protonated) form. This finding could be important for the understanding of basic functional mechanisms involved in tuning the electronic properties and exciton coupling in LH2.

Testing convergent and parallel adaptations in talpids humeral mechanical performance by means of geometric morphometrics and finite element analysis.

PubMed

Piras, P; Sansalone, G; Teresi, L; Kotsakis, T; Colangelo, P; Loy, A

2012-07-01

The shape and mechanical performance in Talpidae humeri were studied by means of Geometric Morphometrics and Finite Element Analysis, including both extinct and extant taxa. The aim of this study was to test whether the ability to dig, quantified by humerus mechanical performance, was characterized by convergent or parallel adaptations in different clades of complex tunnel digger within Talpidae, that is, Talpinae+Condylura (monophyletic) and some complex tunnel diggers not belonging to this clade. Our results suggest that the pattern underlying Talpidae humerus evolution is evolutionary parallelism. However, this insight changed to true convergence when we tested an alternative phylogeny based on molecular data, with Condylura moved to a more basal phylogenetic position. Shape and performance analyses, as well as specific comparative methods, provided strong evidence that the ability to dig complex tunnels reached a functional optimum in distantly related taxa. This was also confirmed by the lower phenotypic variance in complex tunnel digger taxa, compared to non-complex tunnel diggers. Evolutionary rates of phenotypic change showed a smooth deceleration in correspondence with the most recent common ancestor of the Talpinae+Condylura clade. Copyright © 2012 Wiley Periodicals, Inc.

Generation of unstructured grids and Euler solutions for complex geometries

NASA Technical Reports Server (NTRS)

Loehner, Rainald; Parikh, Paresh; Salas, Manuel D.

1989-01-01

Algorithms are described for the generation and adaptation of unstructured grids in two and three dimensions, as well as Euler solvers for unstructured grids. The main purpose is to demonstrate how unstructured grids may be employed advantageously for the economic simulation of both geometrically as well as physically complex flow fields.

Recoding Numerics to Geometrics for Complex Discrimination Tasks; A Feasibility Study of Coding Strategy.

ERIC Educational Resources Information Center

Simpkins, John D.

Processing complex multivariate information effectively when relational properties of information sub-groups are ambiguous is difficult for man and man-machine systems. However, the information processing task is made easier through code study, cybernetic planning, and accurate display mechanisms. An exploratory laboratory study designed for the…

Plane Transformations in a Complex Setting II: Isometries

ERIC Educational Resources Information Center

Dana-Picard, Thierry

2007-01-01

This paper is the second part of a study of plane transformations using a complex setting. The first part was devoted to homotheties and translations, now attention is turned towards plane isometries. The group theoretic properties of plane isometries are easy to derive and images of classical geometrical objects by these transformations are…

Plane Transformations in a Complex Setting III: Similarities

ERIC Educational Resources Information Center

Dana-Picard, Thierry

2009-01-01

This is the third part of a study of plane transformations described in a complex setting. After the study of homotheties, translations, rotations and reflections, we proceed now to the study of plane similarities, either direct or inverse. Their group theoretical properties are described, and their action on classical geometrical objects is…

Automated identification and geometrical features extraction of individual trees from Mobile Laser Scanning data in Budapest

NASA Astrophysics Data System (ADS)

Koma, Zsófia; Székely, Balázs; Folly-Ritvay, Zoltán; Skobrák, Ferenc; Koenig, Kristina; Höfle, Bernhard

2016-04-01

Mobile Laser Scanning (MLS) is an evolving operational measurement technique for urban environment providing large amounts of high resolution information about trees, street features, pole-like objects on the street sides or near to motorways. In this study we investigate a robust segmentation method to extract the individual trees automatically in order to build an object-based tree database system. We focused on the large urban parks in Budapest (Margitsziget and Városliget; KARESZ project) which contained large diversity of different kind of tree species. The MLS data contained high density point cloud data with 1-8 cm mean absolute accuracy 80-100 meter distance from streets. The robust segmentation method contained following steps: The ground points are determined first. As a second step cylinders are fitted in vertical slice 1-1.5 meter relative height above ground, which is used to determine the potential location of each single trees trunk and cylinder-like object. Finally, residual values are calculated as deviation of each point from a vertically expanded fitted cylinder; these residual values are used to separate cylinder-like object from individual trees. After successful parameterization, the model parameters and the corresponding residual values of the fitted object are extracted and imported into the tree database. Additionally, geometric features are calculated for each segmented individual tree like crown base, crown width, crown length, diameter of trunk, volume of the individual trees. In case of incompletely scanned trees, the extraction of geometric features is based on fitted circles. The result of the study is a tree database containing detailed information about urban trees, which can be a valuable dataset for ecologist, city planners, planting and mapping purposes. Furthermore, the established database will be the initial point for classification trees into single species. MLS data used in this project had been measured in the framework of KARESZ project for whole Budapest. BSz contributed as an Alexander von Humboldt Research Fellow.

Wafer-scale single-crystal perovskite patterned thin films based on geometrically-confined lateral crystal growth

PubMed Central

Lee, Lynn; Baek, Jangmi; Park, Kyung Sun; Lee, Yong-EunKoo; Shrestha, Nabeen K.; Sung, Myung M.

2017-01-01

We report a facile roll-printing method, geometrically confined lateral crystal growth, for the fabrication of large-scale, single-crystal CH3NH3PbI3 perovskite thin films. Geometrically confined lateral crystal growth is based on transfer of a perovskite ink solution via a patterned rolling mould to a heated substrate, where the solution crystallizes instantly with the immediate evaporation of the solvent. The striking feature of this method is that the instant crystallization of the feeding solution under geometrical confinement leads to the unidirectional lateral growth of single-crystal perovskites. Here, we fabricated single-crystal perovskites in the form of a patterned thin film (3 × 3 inch) with a high carrier mobility of 45.64 cm2 V−1 s−1. We also used these single-crystal perovskite thin films to construct solar cells with a lateral configuration. Their active-area power conversion efficiency shows a highest value of 4.83%, which exceeds the literature efficiency values of lateral perovskite solar cells. PMID:28691697

Naming games in two-dimensional and small-world-connected random geometric networks.

PubMed

Lu, Qiming; Korniss, G; Szymanski, B K

2008-01-01

We investigate a prototypical agent-based model, the naming game, on two-dimensional random geometric networks. The naming game [Baronchelli, J. Stat. Mech.: Theory Exp. (2006) P06014] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the naming games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case.

Structure, function and evolution of the gas exchangers: comparative perspectives

PubMed Central

Maina, JN

2002-01-01

Over the evolutionary continuum, animals have faced similar fundamental challenges of acquiring molecular oxygen for aerobic metabolism. Under limitations and constraints imposed by factors such as phylogeny, behaviour, body size and environment, they have responded differently in founding optimal respiratory structures. A quintessence of the aphorism that ‘necessity is the mother of invention’, gas exchangers have been inaugurated through stiff cost–benefit analyses that have evoked transaction of trade-offs and compromises. Cogent structural–functional correlations occur in constructions of gas exchangers: within and between taxa, morphological complexity and respiratory efficiency increase with metabolic capacities and oxygen needs. Highly active, small endotherms have relatively better-refined gas exchangers compared with large, inactive ectotherms. Respiratory structures have developed from the plain cell membrane of the primeval prokaryotic unicells to complex multifunctional ones ofthe modern Metazoa. Regarding the respiratory medium used to extract oxygen from, animal life has had only two choices – water or air – within the biological range of temperature and pressure the only naturally occurring respirable fluids. In rarer cases, certain animalshave adapted to using both media. Gills (evaginated gas exchangers) are the primordial respiratory organs: they are the archetypal water breathing organs. Lungs (invaginated gas exchangers) are the model air breathing organs. Bimodal (transitional) breathers occupy the water–air interface. Presentation and exposure of external (water/air) and internal (haemolymph/blood) respiratory media, features determined by geometric arrangement of the conduits, are important features for gas exchange efficiency: counter-current, cross-current, uniform pool and infinite pool designs have variably developed. PMID:12430953

Structural, Spectroscopic, and Electrochemical Properties of Nonheme Fe(II)-Hydroquinonate Complexes: Synthetic Models of Hydroquinone Dioxygenases

PubMed Central

Baum, Amanda E.; Park, Heaweon; Wang, Denan; Lindeman, Sergey V.; Fiedler, Adam T.

2012-01-01

Using the tris(3,5-diphenylpyrazol-1-yl)borate (Ph2Tp) supporting ligand, a series of mono- and dinuclear ferrous complexes containing hydroquinonate (HQate) ligands have been prepared and structurally characterized with X-ray crystallography. The monoiron(II) complexes serve as faithful mimics of the substrate-bound form of hydroquinone dioxygenases (HQDOs) – a family of nonheme Fe enzymes that catalyze the oxidative cleavage of 1,4-dihydroxybenzene units. Reflecting the variety of HQDO substrates, the synthetic complexes feature both mono- and bidentate HQate ligands. The bidentate HQates cleanly provide five-coordinate, high-spin Fe(II) complexes with the general formula [Fe(Ph2Tp)(HLX)] (1X), where HLX is a HQate(1-) ligand substituted at the 2-position with a benzimidazolyl (1A), acetyl (1B and 1C), or methoxy (1D) group. In contrast, the monodentate ligand 2,6-dimethylhydroquinone (H2LF) exhibited a greater tendency to bridge between two Fe(II) centers, resulting in formation of [Fe2(Ph2Tp)2(μ-LF)(MeCN)] [2F(MeCN)]. However, addition of one equivalent of “free” pyrazole (Ph2pz) ligand provided the mononuclear complex, [Fe(Ph2Tp)(HLF)(Ph2pz)] [1F(Ph2pz)], which is stabilized by an intramolecular hydrogen bond between the HLF and Ph2pz donors. Complex 1F(Ph2pz) represents the first crystallographically-characterized example of a monoiron complex bound to an untethered HQate ligand. The geometric and electronic structures of the Fe/HQate complexes were further probed with spectroscopic (UV-vis absorption, 1H NMR) and electrochemical methods. Cyclic voltammograms of complexes in the 1X series revealed an Fe-based oxidation between 0 and −300 mV (vs. Fc+/0), in addition to irreversible oxidation(s) of the HQate ligand at higher potentials. The one-electron oxidized species (1Xox) were examined with UV-vis absorption and electron paramagnetic resonance (EPR) spectroscopies. PMID:22930005

Investigating large-scale secondary circulations within impact crater topographies in a refractive index-matched facility

NASA Astrophysics Data System (ADS)

Blois, Gianluca; Kim, Taehoon; Bristow, Nathan; Day, Mackenzie; Kocurek, Gary; Anderson, William; Christensen, Kenneth

2017-11-01

Impact craters, common large-scale topographic features on the surface of Mars, are circular depressions delimited by a sharp ridge. A variety of crater fill morphologies exist, suggesting that complex intracrater circulations affect their evolution. Some large craters (diameter >10 km), particularly at mid latitudes on Mars, exhibit a central mound surrounded by circular moat. Foremost among these examples is Gale crater, landing site of NASA's Curiosity rover, since large-scale climatic processes early in in the history of Mars are preserved in the stratigraphic record of the inner mound. Investigating the intracrater flow produced by large scale winds aloft Mars craters is key to a number of important scientific issues including ongoing research on Mars paleo-environmental reconstruction and the planning of future missions (these results must be viewed in conjunction with the affects of radial katabatibc flows, the importance of which is already established in preceding studies). In this work we consider a number of crater shapes inspired by Gale morphology, including idealized craters. Access to the flow field within such geometrically complex topography is achieved herein using a refractive index matched approach. Instantaneous velocity maps, using both planar and volumetric PIV techniques, are presented to elucidate complex three-dimensional flow within the crater. In addition, first- and second-order statistics will be discussed in the context of wind-driven (aeolian) excavation of crater fill.

Physical Modeling of Flow Over Gale Crater, Mars: Laboratory Measurements of Basin Secondary Circulations

NASA Astrophysics Data System (ADS)

Bristow, N.; Blois, G.; Kim, T.; Anderson, W.; Day, M. D.; Kocurek, G.; Christensen, K. T.

2017-12-01

Impact craters, common large-scale topographic features on the surface of Mars, are circular depressions delimited by a sharp ridge. A variety of crater fill morphologies exist, suggesting that complex intracrater circulations affect their evolution. Some large craters (diameter > 10 km), particularly at mid latitudes on Mars, exhibit a central mound surrounded by circular moat. Foremost among these examples is Gale crater, landing site of NASA's Curiosity rover, since large-scale climatic processes early in in the history of Mars are preserved in the stratigraphic record of the inner mound. Investigating the intracrater flow produced by large scale winds aloft Mars craters is key to a number of important scientific issues including ongoing research on Mars paleo-environmental reconstruction and the planning of future missions (these results must be viewed in conjunction with the affects of radial katabatibc flows, the importance of which is already established in preceding studies). In this work we consider a number of crater shapes inspired by Gale morphology, including idealized craters. Access to the flow field within such geometrically complex topography is achieved herein using a refractive index matched approach. Instantaneous velocity maps, using both planar and volumetric PIV techniques, are presented to elucidate complex three-dimensional flow within the crater. In addition, first- and second-order statistics will be discussed in the context of wind-driven (aeolian) excavation of crater fill.

Sci-Vis Framework

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

Arthur Bleeker, PNNL

2015-03-11

SVF is a full featured OpenGL 3d framework that allows for rapid creation of complex visualizations. The SVF framework handles much of the lifecycle and complex tasks required for a 3d visualization. Unlike a game framework SVF was designed to use fewer resources, work well in a windowed environment, and only render when necessary. The scene also takes advantage of multiple threads to free up the UI thread as much as possible. Shapes (actors) in the scene are created by adding or removing functionality (through support objects) during runtime. This allows a highly flexible and dynamic means of creating highlymore » complex actors without the code complexity (it also helps overcome the lack of multiple inheritance in Java.) All classes are highly customizable and there are abstract classes which are intended to be subclassed to allow a developer to create more complex and highly performant actors. There are multiple demos included in the framework to help the developer get started and shows off nearly all of the functionality. Some simple shapes (actors) are already created for you such as text, bordered text, radial text, text area, complex paths, NURBS paths, cube, disk, grid, plane, geometric shapes, and volumetric area. It also comes with various camera types for viewing that can be dragged, zoomed, and rotated. Picking or selecting items in the scene can be accomplished in various ways depending on your needs (raycasting or color picking.) The framework currently has functionality for tooltips, animation, actor pools, color gradients, 2d physics, text, 1d/2d/3d textures, children, blending, clipping planes, view frustum culling, custom shaders, and custom actor states« less

Reaction landscape of a pentadentate N5-ligated Mn(II) complex with O2˙- and H2O2 includes conversion of a peroxomanganese(III) adduct to a bis(μ-oxo)dimanganese(III,IV) species.

PubMed

Leto, Domenick F; Chattopadhyay, Swarup; Day, Victor W; Jackson, Timothy A

2013-09-28

Herein we describe the chemical reactivity of the mononuclear [Mn(II)(N4py)(OTf)](OTf) (1) complex with hydrogen peroxide and superoxide. Treatment of 1 with one equivalent superoxide at -40 °C in MeCN formed the peroxomanganese(III) adduct, [Mn(III)(O2)(N4py)](+) (2) in ~30% yield. Complex 2 decayed over time and the formation of the bis(μ-oxo)dimanganese(III,IV) complex, [Mn(III)Mn(IV)(μ-O)2(N4py)2](3+) (3) was observed. When 2 was formed in higher yields (~60%) using excess superoxide, the [Mn(III)(O2)(N4py)](+) species thermally decayed to Mn(II) species and 3 was formed in no greater than 10% yield. Treatment of [Mn(III)(O2)(N4py)](+) with 1 resulted in the formation of 3 in ~90% yield, relative to the concentration of [Mn(III)(O2)(N4py)](+). This reaction mimics the observed chemistry of Mn-ribonucleotide reductase, as it features the conversion of two Mn(II) species to an oxo-bridged Mn(III)Mn(IV) compound using O2(-) as oxidant. Complex 3 was independently prepared through treatment of 1 with H2O2 and base at -40 °C. The geometric and electronic structures of 3 were probed using electronic absorption, electron paramagnetic resonance (EPR), magnetic circular dichroism (MCD), variable-temperature, variable-field MCD (VTVH-MCD), and X-ray absorption (XAS) spectroscopies. Complex 3 was structurally characterized by X-ray diffraction (XRD), which revealed the N4py ligand bound in an unusual tetradentate fashion.