Parallel Segments Research Articles

Rapid fully automatic segmentation of subcortical brain structures by shape-constrained surface adaptation.

This work presents a novel approach for the rapid segmentation of clinically relevant subcortical brain structures in T1-weighted MRI by utilizing a shape-constrained deformable surface model. In contrast to other approaches for segmenting brain structures, its design allows for parallel segmentation of individual brain structures within a flexible and robust hierarchical framework such that accurate adaptation and volume computation can be achieved within a minute of processing time. Furthermore, adaptation is driven by local and not global contrast, potentially relaxing requirements with respect to preprocessing steps such as bias-field correction. Detailed evaluation experiments on more than 1000 subjects, including comparisons to FSL FIRST and FreeSurfer as well as a clinical assessment, demonstrate high accuracy and test-retest consistency of the presented segmentation approach, leading, for example, to an average segmentation error of less than 0.5mm. The presented approach might be useful in both, research as well as clinical routine, for automated segmentation and volume quantification of subcortical brain structures in order to increase confidence in the diagnosis of neuro-degenerative disorders, such as Alzheimer's disease, Parkinson's disease, Multiple Sclerosis, or clinical applications for other neurologic and psychiatric diseases.

Large-scale genomic prediction using singular value decomposition of the genotype matrix

BackgroundFor marker effect models and genomic animal models, computational requirements increase with the number of loci and the number of genotyped individuals, respectively. In the latter case, the inverse genomic relationship matrix (GRM) is typically needed, which is computationally demanding to compute for large datasets. Thus, there is a great need for dimensionality-reduction methods that can analyze massive genomic data. For this purpose, we developed reduced-dimension singular value decomposition (SVD) based models for genomic prediction.MethodsFast SVD is performed by analyzing different chromosomes/genome segments in parallel and/or by restricting SVD to a limited core of genotyped individuals, producing chromosome- or segment-specific principal components (PC). Given a limited effective population size, nearly all the genetic variation can be effectively captured by a limited number of PC. Genomic prediction can then be performed either by PC ridge regression (PCRR) or by genomic animal models using an inverse GRM computed from the chosen PC (PCIG). In the latter case, computation of the inverse GRM will be feasible for any number of genotyped individuals and can be readily produced row- or element-wise.ResultsUsing simulated data, we show that PCRR and PCIG models, using chromosome-wise SVD of a core sample of individuals, are appropriate for genomic prediction in a larger population, and results in virtually identical predicted breeding values as the original full-dimension genomic model (r = 1.000). Compared with other algorithms (e.g. algorithm for proven and young animals, APY), the (chromosome-wise SVD-based) PCRR and PCIG models were more robust to size of the core sample, giving nearly identical results even down to 500 core individuals. The method was also successfully tested on a large multi-breed dataset.ConclusionsSVD can be used for dimensionality reduction of large genomic datasets. After SVD, genomic prediction using dense genomic data and many genotyped individuals can be done in a computationally efficient manner. Using this method, the resulting genomic estimated breeding values were virtually identical to those computed from a full-dimension genomic model.

Implementation of the parallel mean shift-based image segmentation algorithm on a GPU cluster

ABSTRACTThe mean shift image segmentation algorithm is very computation-intensive. To address the need to deal with a large number of remote sensing (RS) image segmentations in real-world applications, this study has investigated the parallelization of the mean shift algorithm on a single graphics processing unit (GPU) and a task-scheduling method with message passing interface (MPI)+OpenCL programming model on a GPU cluster platform. This paper presents the test results of the parallel mean shift image segmentation algorithm on Shelob, a GPU cluster platform at Louisiana State University, with different datasets and parameters. The experimental results show that the proposed parallel algorithm can achieve good speedups with different configurations and RS data and can provide an effective solution for RS image processing on a GPU cluster.

The Role of Coseismic Coulomb Stress Changes in Shaping the Hard Link Between Normal Fault Segments

AbstractThe mechanism and evolution of fault linkage is important in the growth and development of large faults. Here we investigate the role of coseismic stress changes in shaping the hard links between parallel normal fault segments (or faults), by comparing numerical models of the Coulomb stress change from simulated earthquakes on two en echelon fault segments to natural observations of hard‐linked fault geometry. We consider three simplified linking fault geometries: (1) fault bend, (2) breached relay ramp, and (3) strike‐slip transform fault. We consider scenarios where either one or both segments rupture and vary the distance between segment tips. Fault bends and breached relay ramps are favored where segments underlap or when the strike‐perpendicular distance between overlapping segments is less than 20% of their total length, matching all 14 documented examples. Transform fault linkage geometries are preferred when overlapping segments are laterally offset at larger distances. Few transform faults exist in continental extensional settings, and our model suggests that propagating faults or fault segments may first link through fault bends or breached ramps before reaching sufficient overlap for a transform fault to develop. Our results suggest that Coulomb stresses arising from multisegment ruptures or repeated earthquakes are consistent with natural observations of the geometry of hard links between parallel normal fault segments.

Structural setting and kinematics of Nubian fault system, SE Western Desert, Egypt: An example of multi-reactivated intraplate strike-slip faults

Detailed surface geological mapping and subsurface seismic interpretation have been integrated to unravel the structural style and kinematic history of the Nubian Fault System (NFS). The NFS consists of several E-W Principal Deformation Zones (PDZs) (e.g. Kalabsha fault). Each PDZ is defined by spectacular E-W, WNW and ENE dextral strike-slip faults, NNE sinistral strike-slip faults, NE to ENE folds, and NNW normal faults. Each fault zone has typical self-similar strike-slip architecture comprising multi-scale fault segments. Several multi-scale uplifts and basins were developed at the step-over zones between parallel strike-slip fault segments as a result of local extension or contraction. The NNE faults consist of right-stepping sinistral strike-slip fault segments (e.g. Sin El Kiddab fault). The NNE sinistral faults extend for long distances ranging from 30 to 100 kms and cut one or two E-W PDZs.Two nearly perpendicular strike-slip tectonic regimes are recognized in the NFS; an inactive E-W Late Cretaceous - Early Cenozoic dextral transpression and an active NNE sinistral shear.

Radial sample load distribution under overload conditions: Analytical scale columns

ABSTRACTThe homogeneity of the sample load across the radial cross section of analytical scale columns was determined when operating under overload conditions. The study was performed using active flow technology columns operating in parallel segmentation mode. The outlet segmentation ratio was varied to enable different volume fractions of mobile phase, and thus sample, to elute from the peripheral and central flow regions of the column. The amount of solute exiting the peripheral and radial central exit ports was determined as a function of the flow segmentation ratio. The experimental data using an analytical scale column with dimensions, 100 × 4.6 mm, indicated that the sample load distribution was essentially uniform as a function of the column radial cross section.

Design Criteria in Sizing Phase-Change RF Switches

This paper presents design criteria for four-terminal phase-change (PC) RF switches as a function of their dimensions, (heater width, RF gap, and barrier thickness), materials, and connection topology. Reducing heater width is shown to reduce switch actuation power, with this reduction ultimately being limited by the maximum allowed heater current density, as set by projected reliability. Narrower RF gaps are shown to increase switch cut-off frequency $F_{\mathrm {CO}}$ , because they decrease on-state resistance more than they increase off-state capacitance. The balance of this increased $F_{\mathrm {CO}}$ versus the estimated reduction in power handling as the RF gap shrinks is quantified. Barrier layers of AlN thicker than 200 nm are shown to be sufficient to electrically decouple the switch from the heater trace. Coupling to heater pads can also be significant unless pad sizes are reduced as in a monolithically integrated switch. Finally, it is demonstrated that division of the switch into multiple parallel segments is a viable approach for lowering the heater actuation voltage for CMOS integration. A 12.5% increase in $C_{\mathrm{\scriptscriptstyle OFF}}$ (~1.5 fF) was observed and 35% increase in actuation power at temperature was needed in a two-segment parallel switch, as compared to a single segment switch.

Single-Stage Buck-Derived LED Driver With Improved Efficiency and Power Factor Using Current Path Control Switches

This paper proposes a single-stage light-emitting diode (LED) driver based on an inverted buck topology, using current path control switches. The proposed circuit consists of a control circuit, a bridge diode, and an inverted buck converter with multiple switches connected to the LED segments in parallel. Whereas the typical buck LED driver operates with a fixed LED forward voltage, the proposed driver operates with a variable LED forward voltage, according to the input voltage level. Because of this capability to adjust the LED forward voltage, it can reduce the current ripple and the switching frequency with a small inductance value. In addition, it enables operation with LED lamps of a wide voltage range, while simultaneously achieving small dead-angles. The detailed operation principles are described, and the design considerations for the proposed driver are discussed. The proposed driver circuit and control operation are verified experimentally using a 7 W hardware prototype with four LED segments. The obtained experimental results show that under a 110 Vrms input voltage, the proposed driver achieves a power factor of 0.94 with a small dead-angle and an efficiency of 94%.

Diversity Coding in Two-Connected Networks

In this paper, we propose a new proactive recovery scheme against single edge failures for unicast connections in transport networks. The new scheme is a generalization of diversity coding where the source data AB are split into two parts A and B and three data flows A, B, and their exclusive OR (XOR) A⊕B are sent along the network between the source and the destination node of the connection. By ensuring that two data flows out of the three always operate even if a single edge fails, the source data can be instantaneously recovered at the destination node. In contrast with diversity coding, we do not require the three data flows to be routed along three disjoint paths; however, in our scheme, a data flow is allowed to split into two parallel segments and later merge back. Thus, our generalized diversity coding (GDC) scheme can be used in sparse but still two-connected network topologies. Our proof improves an earlier result of network coding, by using purely graph theoretical tool set instead of algebraic argument. In particular, we show that when the source data are divided into two parts, robust intra-session network coding against single edge failures is always possible without any in-network algebraic operation. We present linear-time robust code construction algorithms for this practical special case in minimal coding graphs. We further characterize this question, and show that by increasing the number of edge failures and source data parts, we lose these desired properties.

Real-time enhancement of sparse 3D maps using a parallel segmentation scheme based on superpixels

In this work, we focus on the problem of feature-based 3D mapping of environments with large textureless regions, which generates sparse 3D maps that may not represent well the mapped scene. To deal with this problem, based on our previous work (Cruz Martinez et al. in 2016 IEEE international symposium on mixed and augmented reality (ISMAR) adjunct proceedings, IEEE, 2016), we propose to enhance sparse 3D maps by using a superpixel-based segmentation with the aim of generating denser 3D maps of the scene in real time. Superpixels are middle-level features, which represent similar regions in an image, which can be connected in order to segment textureless areas. We propose a graphics processor unit architecture for (1) superpixel extraction considering chromatic and depth information, (2) superpixel-based segmentation, generation of connectivity matrix to compute the connected components algorithm and (3) mapping of segmented regions to 3D points. We use the ORB-SLAM system (Mur-Artal et al. in IEEE Trans Robot 31(5):1147–1163, 2015) to generate a sparse 3D map and to project the textureless segments onto it at 27 frames per second. We assessed our approach in terms of segmentation and map quality. Regarding the latter, covered area by the generated map, depth accuracy, and computational performance are reported.

Modelling side to side intestinal anastomosis.

Side-to-side intestinal anastomosis is a surgical procedure where an incision is performed between two parallel segments of gut and then they are sutured together. The purpose of this paper is to investigate if the standard surgical practice diameter used in anastomosis leads to undesirable closed circulatory flows which may be harmful to the gut tissue. A finite element model for the chyme flow in a side by side anastomosis with realistic user configurable parameters is developed and solved in a wide range of situations. We analyze the flow crossing the anastomosis, the normalized pressure difference in the gut section and the streamlines that show the presence or absence of closed flow regions for a set of surgically feasible anastomosis diameter values. In contrast with the findings of simpler analytical models, closed flows do not appear in any of these cases. The study shows that the current standard surgical practice where the anastomosis diameter is similar to the gut diameter does not lead to undesirable effects predicted by some simple analytical models.

Extracting Parallel Paragraphs from Common Crawl

Abstract Most of the current methods for mining parallel texts from the web assume that web pages of web sites share same structure across languages. We believe that there still exists a non-negligible amount of parallel data spread across sources not satisfying this assumption. We propose an approach based on a combination of bivec (a bilingual extension of word2vec) and locality-sensitive hashing which allows us to efficiently identify pairs of parallel segments located anywhere on pages of a given web domain, regardless their structure. We validate our method on realigning segments from a large parallel corpus. Another experiment with real-world data provided by Common Crawl Foundation confirms that our solution scales to hundreds of terabytes large set of web-crawled data.

Generating Topographic Map Data from Classification Results

The use of classification results as topographic map data requires cartographic enhancement and checking of the geometric accuracy. Urban areas are of special interest. The conversion of the classification result into topographic map data of high thematic and geometric quality is subject of this contribution. After reviewing the existing literature on this topic, a methodology is presented. The extraction of point clouds belonging to line segments is solved by the Hough transform. The mathematics for deriving polygons of orthogonal, parallel and general line segments by least squares adjustment is presented. A unique solution for polylines, where the Hough parameters are optimized, is also given. By means of two data sets land cover maps of six classes were produced and then enhanced by the proposed method. The classification used the decision tree method applying a variety of attributes including object heights derived from imagery. The cartographic enhancement is carried out with two different levels of quality. The user’s accuracies for the classes “impervious surface” and “building” were above 85% in the “Level 1” map of Example 1. The geometric accuracy of building corners at the “Level 2” maps is assessed by means of reference data derived from ortho-images. The obtained root mean square errors (RMSE) of the generated coordinates (x, y) were RMSEx = 1.2 m and RMSEy = 0.7 m (Example 1) and RMSEx = 0.8 m and RMSEy = 1.0 m (Example 2) using 31 and 62 check points, respectively. All processing for Level 1 (raster data) could be carried out with a high degree of automation. Level 2 maps (vector data) were compiled for the classes “building” and “road and parking lot”. For urban areas with numerous classes and of large size, universal algorithms are necessary to produce vector data fully automatically. The recent progress in sensors and machine learning methods will support the generation of topographic map data of high thematic and geometric accuracy.

Impurity screening and stability of Fermi arcs against Coulomb and magnetic scattering in a Weyl monopnictide

We present a quasiparticle interference study of clean and Mn surface-doped TaAs, a prototypical Weyl semimetal, to test the screening properties as well as the stability of Fermi arcs against Coulomb and magnetic scattering. Contrary to topological insulators, the impurities are effectively screened in Weyl semimetals. The adatoms significantly enhance the strength of the signal such that theoretical predictions on the potential impact of Fermi arcs can be unambiguously scrutinized. Our analysis reveals the existence of three extremely short, previously unknown scattering vectors. Comparison with theory traces them back to scattering events between large parallel segments of spin-split trivial states, strongly limiting their coherence. In sharp contrast to previous work [R. Batabyal et al., Sci. Adv. 2, e1600709 (2016)], where similar but weaker subtle modulations were interpreted as evidence of quasiparticle interference originating from Femi arcs, we can safely exclude this being the case. Overall, our results indicate that intra- as well as inter-Fermi arc scattering are strongly suppressed and may explain why-in spite of their complex multiband structure-transport measurements show signatures of topological states in Weyl monopnictides.

Joint Reconstruction and Segmentation of 7T-like MR Images from 3T MRI Based on Cascaded Convolutional Neural Networks.

7T MRI scanner provides MR images with higher resolution and better contrast than 3T MR scanners. This helps many medical analysis tasks, including tissue segmentation. However, currently there is a very limited number of 7T MRI scanners worldwide. This motivates us to propose a novel image post-processing framework that can jointly generate high-resolution 7T-like images and their corresponding high-quality 7T-like tissue segmentation maps, solely from the routine 3T MR images. Our proposed framework comprises two parallel components, namely (1) reconstruction and (2) segmentation. The reconstruction component includes the multi-step cascaded convolutional neural networks (CNNs) that map the input 3T MR image to a 7T-like MR image, in terms of both resolution and contrast. Similarly, the segmentation component involves another paralleled cascaded CNNs, with a different architecture, to generate high-quality segmentation maps. These cascaded feedbacks between the two designed paralleled CNNs allow both tasks to mutually benefit from each another when learning the respective reconstruction and segmentation mappings. For evaluation, we have tested our framework on 15 subjects (with paired 3T and 7T images) using a leave-one-out cross-validation. The experimental results show that our estimated 7T-like images have richer anatomical details and better segmentation results, compared to the 3T MRI. Furthermore, our method also achieved better results in both reconstruction and segmentation tasks, compared to the state-of-the-art methods.

Autonomous Recognition System for Barcode Detection in Complex Scenes

Linear barcode technology has been widely used in our common life, such as in logistics, retailed products and many other applications. Many researches and smart applications focus on how to decode the barcode so that it is difficult to locate precisely when the background becomes very complex. Moreover, many smart apps need human interaction to make sure the detected region is in a correct position of the screen. This paper presents an effective approach to locate the barcodes in real-time without manual disturbing. Basic morphological operations and Parallel Line Segment Detector (P-LSD) are applied to achieve the legal block of barcodes. Our method has been evaluated by a standard database and the experimental results show that our approach is more robuster than other earlier methods.

Parallel fragments : Measuring their impact on translation performance

Lack of parallel corpora have diverted the direction of research towards exploring other arenas to fill in the dearth. Comparable corpora have proved to be a valuable resource in this regard. Interestingly other than the parallel sentences extracted from comparable corpora, parallel phrase fragments have also proved to be beneficial for statistical machine translation. We present a novel approach based on an efficient framework for parallel fragment extraction from comparable corpora. Using the fragments as additional corpus for translation, we are able to obtain an improvement of 0.88 and 0.89 BLEU points on test data for Arabic–English and French–English systems respectively. We have also conducted a detailed analysis of impact of fragments extracted from related vs non-related corpus. A comparison of impact of parallel fragments vs. parallel sentences is also presented highlighting the significance of parallel segments for statistical machine translation. The article concludes with a crude comparative analysis of our approach with an existing fragment extraction technique at various stages of the fragment extraction pipeline.

Context-Aware Fusion of RGB and Thermal Imagery for Traffic Monitoring.

In order to enable a robust 24-h monitoring of traffic under changing environmental conditions, it is beneficial to observe the traffic scene using several sensors, preferably from different modalities. To fully benefit from multi-modal sensor output, however, one must fuse the data. This paper introduces a new approach for fusing color RGB and thermal video streams by using not only the information from the videos themselves, but also the available contextual information of a scene. The contextual information is used to judge the quality of a particular modality and guides the fusion of two parallel segmentation pipelines of the RGB and thermal video streams. The potential of the proposed context-aware fusion is demonstrated by extensive tests of quantitative and qualitative characteristics on existing and novel video datasets and benchmarked against competing approaches to multi-modal fusion.

Color‐Temperature Tuning and Control of Trichromatic White Light Emission from a Multisegment ZnCdSSe Heterostructure Nanosheet

Tuning and control of color temperature of trichromatic white light emission is demonstrated for the first time from a single ZnCdSSe nanosheet realized by a novel growth method using chemical vapor deposition (CVD). The nanosheets have thicknesses in the range of 60–350 nm and lateral dimensions of tens of micrometers. These nanosheet structures with three or more parallel segments are able to emit the three primary colors of light from a monolithic body and the combination of the emitted light appears as white. Due to temperature dependence of the alloy composition and the spatial profile of the temperature in the CVD chamber, alloy compositions and the widths of individual segments can be controlled by the substrate locations and the growth time, respectively. Such control determines the emission color and relative intensity of each segment, thus resulting in the tuning of the color temperature of the white light, or in the realization of any visible colors. Trichromatic white light emission is demonstrated with the correlated color temperature covering an extensive range from 2700 to 14 400 K using various growth parameters. In addition, a dynamic tuning of colors and color temperature is demonstrated by sweeping a pump beam across a single nanosheet.

Harbor Detection in Polarimetric SAR Images Based on the Characteristics of Parallel Curves

This letter proposes a harbor detection method by extracting specific paralleled contours of harbors in polarimetric synthetic aperture radar (SAR) images. First, land and sea are partitioned by the region-based level set segmentation algorithm which is applied to the extraction of the volume scattering component. Then, parallel curves are modeled by a series of parallel line segments. They are detected by finding out and connecting paralleled line segments given certain criteria. The detected parallel curves are merged according to a distance measurement so that the harbor contour is finally detected. RADARSAT-2 polarimetric SAR data covering an area in Singapore are used to test the harbor detection method. Experimental results show that the method improves sea–land segmentation accuracy and extracts all parallel curves along the coast correctly. The method enables an accurate detection of harbors.