Parallel Segments Research Articles

Middle school students’ reasoning with regards to parallelism and perpendicularity of line segments

This study investigates middle school students’ reasoning about parallelism and perpendicularity of two line segments. Data were collected from 83 middle school students through an identification task consisting of various examples and non-examples of the parallelism and perpendicularity of two line segments. One-to-one interviews were also conducted with fifteen students to support students’ written reasons. The results indicated that middle school students identify parallel/perpendicular line segments by using three types of reasoning: visual reasoning, attribute reasoning, and language-based reasoning. With the influence of the concept images shaped by prototypical and intuitive examples and linguistic factors, some students either focused on non-critical attributes of the concepts as the critical ones or omitted critical attributes of the concepts. Hence, they either identified examples of parallel line segments and perpendicular line segments as non-examples or considered non-examples of the concepts as examples.

A Low Temperature Coefficient Time-to-Digital Converter with 1.3 ps Resolution Implemented in a 28 nm FPGA.

Time-to-digital converter (TDC) is the key technology to realize accurate time delay measurement in high-precision optical fiber time-frequency transmission and synchronization, optical sensing and many scientific applications. The performance of FPGA-TDC based on the carry chain is sensitive to the operating temperature. This paper presents a parallel multichain cross segmentation method, without multitime measurements, which merges multichain into an equivalent chain, achieving low temperature coefficient and maintaining high precision. The equivalent chain breaks the limit of the intrinsic cell delay of a single carry chain, improves the precision and reduces the impact of temperature variation significantly. A two-channel TDC based on parallel multichain cross segmentation method is implemented in a 28 nm fabrication process Kintex-7 FPGA. The results show that the performance of TDC is improved with the increase of the number of chains. The 10-chain TDC with 1.3 ps resolution, 4.6 ps single-shot precision performs much better than the plain TDC with 11.4 ps resolution, 8.7 ps single-shot precision. The resolution is stable with 0.0002 ps/°C temperature coefficient under an operating temperature range from 25 °C to 70 °C. Moreover, the proposed method reduces the complexity of the circuit and the resource usage.

Early Ordovician Seleneceme (Trilobita) in Ziyang Fauna, South China

ABSTRACT Ziyang Fauna is a significant early Ordovician Floian fossil Lagerstätte, recovered from blackish-grey mud limestone and calcareous mudstone of possible slope facies in the Yangtze platform in Ziyang County, Shaanxi Province, China, distinguished by predominate trilobites, accompanied with graptolites, brachiopods, arthropods and some trace fossils. It is marked by high abundance of exceptionally preserved Seleneceme (Trilobita). Two trilobite species named Caputrotundum bashanense and C. ziyangensis, are reassigned here to Seleneceme based on a detailed study of more than one hundred well-preserved specimens. The taxonomic generic and ontogeny characters of Seleneceme are as follows: cephalon semicircular in outline, with axial spine and genal spines; without eye lobes; glabella subcircular in outline, with deep longitudinal glabellar furrows; thorax and pygidium with much parallel segments. The morphological variation during ontogeny of Seleneceme is characterised by the gradual increase of the length/width ratio (L/W) of the body, but with a constant width/length ratio (W/L) of the cephalon, and also a faster growth rate in the pygidium than in the thorax.

Towards an early diagnosis of Alzheimer disease: a precise and parallel image segmentation approach via derived hybrid cross entropy thresholding method

Towards an early diagnosis of Alzheimer disease: a precise and parallel image segmentation approach via derived hybrid cross entropy thresholding method

Worst-Case Response Time Analysis of Multitype DAG Tasks Based on Reconstruction

With the wide application of heterogeneous multi-core processor real-time systems, the existing analysis methods of worst-case response time (WCRT) overestimate the blocking information among tasks, resulting in a rather pessimistic estimation. To improve the accuracy of the WCRT, we propose a reconstruction-based WCRT analysis method for multi-type directed acyclic graph (DAG) tasks scheduling algorithm(RMDS). The RMDS algorithm comprises the following steps: First, we unitize all task nodes in the multi-type DAG task; Then, we use key factors as task priorities to schedule tasks and reconstruct the DAG task model into a parallel node segment model; Finally, we estimate the WCRT of multi-type DAG tasks according to the parallel node segment model to assess task schedulability. To verify the performance of our algorithm, we compared it with traditional algorithms. RDMS showed an acceptance rate 6.13% higher and its overall performance increased by 25.95% in comparison with traditional algorithms.

A Benchmark Sentinel-1 SAR Dataset for Airport Detection

Airports are important targets in both military and civilian tasks. Synthetic aperture radar (SAR) based airport detection has received increasing attention in recent years. However, due to the high cost of the SAR imaging and annotation process, there is no publicly available SAR dataset for airport detection, which leads to the fact that deep learning methods have not been applied to airport detection and no unified evaluation benchmark for traditional methods. To provide a benchmark for airport detection studies in SAR images, a large SAR airport dataset (SAD) is presented in this paper. It contains 624 SAR images from Sentinel 1B, covering 104 instances of airports with different scales, orientations and shapes, which can realistically reflect the real world. Experiments with four deep learning-based methods and three traditional methods on this dataset demonstrate its effectiveness and challenge. It serves for the development of state-of-the-art airport detection algorithms or other related tasks. In addition, we found that airport runways in SAR images always have some parallel line segments. Inspired by this, the fusion of deep features and line segments is achieved by designing a line segment detector branch, which further improves the accuracy of airport detection.

A parallel 3D image segmentation method for Coronary CT Angiography

Coronary artery (CA) disease is one of the major cardiovascular diseases that has been proved to be the leading cause of human death in world. In this paper, a 3D image segmentation algorithm based on Lattice Boltzmann (LB) is proposed for 3D CA segmentation. After investigating the behavior of Boundary Treatment schemes, a non-equilibrium extrapolation scheme is applied to keep the stability of the computation, and reduce the frequency of the re-initialization. The denoising and clipping method are also proposed for the segmentation refining. The segmentation result shows our LB model for 3D CAD segmentation is effective. More importantly, the LB model has natural parallelism. Our model can run on massively parallel architectures, ranging from inexpensive embedded FPGAs and DSPs up to GPUs.

Maxillary and Orbital Floor Reconstruction with Parallel Segments of the Fibula Free Flap: A Technical Note.

The fibula free flap (FFF) is considered a gold standard for maxillary reconstructions, and in the last few decades, this flap has been widely used for mandibular defects, with a range of modifications, which have allowed the improvement and greater success. The reconstructions of the maxilla and midface are less reported than mandibular reconstructions, despite the remarkable evolution over the years. In the reconstruction of type IIIa maxillary defects using FFF, some authors report that it may not provide enough height to support the orbit in class 3 and 4 defects. Others also encountered several difficulties, mainly in modeling fibular bone (FB) for the zygomatic-maxilla complex reconstruction and orbital floor, due to the difficulty in rotating the soft tissues, pedicle, orientation of the (FB) segments. To show this new technique presents another option for maxillary reconstruction with a FFF in type IIIa defects. After harvesting FFF in the standard fashion, differentiated osteotomies, modeling, and arrangement of the fibular bone segments are performed. This new technique presented has the advantage of requiring only one flap, promoting the resolution of the technical difficulties previously reported.

Quantifying tidal expiratory flow limitation using a vector-based analysis technique

Objective. Tidal expiratory flow limitation (EFLT) is commonly identified by tidal breaths exceeding the forced vital capacity (FVC) loop. This technique, known as the Hyatt method, is limited by the difficulties in defining the FVC and tidal flow-volume (TV) loops. The vector-based analysis (VBA) technique described and piloted in this manuscript identifies and quantifies EFLT as tidal breaths that conform to the contour of the FVC loop. Approach. The FVC and TV loops are interpolated to generate uniformly spaced plots. VBA is performed to determine the smallest vector difference between each point on the FVC and TV curves, termed the flow reserve vector (FRV). From the FVC point yielding the lowest FRV, the tangential angles of the FVC and TV segments are recorded. If the TV and FVC loops become parallel, the difference between the tangential angles tends towards zero. We infer EFLT as parallel TV and FVC segments where the FRV is < 0.1 and the tangential angle is within ±18 degrees for ≥5% of TV. EFLT is quantified by the percent of TV loop fulfilling these criteria. We compared the presence and degree of EFLT at rest and during peak exercise using the Hyatt method and our VBA technique in 25 healthy subjects and 20 subjects with moderate-severe airflow obstruction. Main results. Compared to the Hyatt method, our VBA technique reported a significantly lower degree of EFLT in healthy subjects during peak exercise, and in obstructed subjects at rest and during peak exercise. In contrast to the Hyatt method, our VBA technique re-classified five subjects (one in the healthy group and four in the obstructed group) as demonstrating EFLT. Significance. Our VBA technique provides an alternative approach to determine and quantify EFLT which may reduce the overestimation of the degree EFLT and more accurately identify subjects experiencing EFLT.

Parallel region growing of half-tone images based on selected average brightness of the area along the growth route

The problem of parallel segmentation of halftone images by brightness for implementation on the basis of programmable logic integrated circuits is considered. Segmentation divides an image into regions formed from pixels with approximately the same brightness, and is a computationally complex operation due to multiple checks of the value of each pixel for the possibility of joining an adjacent region. To speed up segmentation, parallel algorithms for growing areas have been developed, in which processing begins from the neighborhoods of preselected initial growth pixels. The condition of joining an adjacent pixel to an area takes into account the average brightness of the area to limit the variance of its pixel values. Therefore, when each new pixel is added to the area, its average brightness is recalculated. This leads to high time complexity. In some parallel algorithms, the sample mean is calculated in a small window, which makes it possible to slightly reduce the time complexity when matching the window size with the segment sizes. To significantly reduce the temporal complexity, the article proposes a model for the parallel growth of image regions based on a simplified condition for joining adjacent pixels to a region, taking into account the sample average value of the region's brightness along the growth route connecting the boundary pixel of the region and the initial growth pixel through a sequence of pixels used to attach the considered boundary pixel to area. A significant decrease in the temporal complexity of the proposed model of parallel growing of image regions in comparison with the known models is achieved due to a slight increase in the spatial complexity.

Fast, precise, and shape-flexible registration of wavefronts

A fast and precise algorithm for wavefront reconstruction by the registration of wavefront segments is presented. If the wavefront exceeds the sensor aperture or the dynamic range of the sensor, a Shack-Hartmann sensor can measure only segments of an optical wavefront. The algorithm registers the wavefront segments in parallel, where they are simultaneously transformed to minimize their overlap mismatch for precise reconstruction of the entire wavefront. The original nonlinear optimization problem is approximated by a convex optimization problem that can be solved more efficiently. A simulation-based analysis of the algorithm and a comparison to a previously proposed parallel registration (PR) algorithm as well as to the iterative closest point (ICP) algorithm are presented. It is shown that despite measurement noise, the algorithm can precisely register plane as well as divergent wavefronts with root mean square registration errors smaller than 10 nm. Particularly for the divergent wavefront, this enables a reduction of the registration error by a factor of up to 750 as compared to the established algorithms. Analysis and comparison to the ICP and PR algorithm also show that the computation time of the proposed algorithm can be from one to three orders of magnitude smaller.

An Online Map Matching Algorithm Based on Second-Order Hidden Markov Model

Map matching is a key preprocess of trajectory data which recently have become a major data source for various transport applications and location-based services. In this paper, an online map matching algorithm based on the second-order hidden Markov model (HMM) is proposed for processing trajectory data in complex urban road networks such as parallel road segments and various road intersections. Several factors such as driver’s travel preference, network topology, road level, and vehicle heading are well considered. An extended Viterbi algorithm and a self-adaptive sliding window mechanism are adopted to solve the map matching problem efficiently. To demonstrate the effectiveness of the proposed algorithm, a case study is carried out using a massive taxi trajectory dataset in Nanjing, China. Case study results show that the accuracy of the proposed algorithm outperforms the baseline algorithm built on the first-order HMM in various testing experiments.

Analysis and modelling of rampart line antennas

A new, efficient, and accurate analytical model is introduced for estimating the beam direction of rampart line antennas with microstrip radiators that can change beam direction with feeding frequency. The model takes its origins from 1-D array theory, in which the bends represent the radiating elements, and the interconnecting lines represent the phase shifters. A mathematical expression accounting for the equivalent length of the bends for the correct estimation of the distance between the radiators is introduced. The model was tested for various substrate relative permittivity values ranging from 2.9 to 6.45. This model can be used for arbitrary rampart line configurations by providing the equivalent dipole direction, depending on the orientation of the bends. An alternative geometry was proposed to reduce the coupling between the parallel line segments. A prototype operating in a bandwidth of 1 GHz around 7.8 GHz was realized on a Rogers RO4350B high-frequency laminate with a thickness of 1.524 mm. Both the radiation pattern and the reflection coefficient were measured and show a good agreement with the proposed analytical model and commercial full-wave simulation tool results.

Mathematically optimized trajectory for terrestrial close-range photogrammetric 3D reconstruction of forest stands

Terrestrial close-range photogrammetry offers a low-cost method of three-dimensional (3D) reconstruction of forest stands that provides automatically processable 3D data that can be used to evaluate inventory parameters of forest stands and individual trees. However, fundamental methodological problems in image acquisition and processing remain. This study enhances the methodology of photogrammetric Structure from Motion reconstruction of forest stands by determining the best photographer's trajectory for image acquisition. The study comprises 1) mathematical optimization of the route in a square grid using integer programming, 2) evaluation of point clouds derived from sequences of real photographs, simulating different trajectories, and 3) verification on real trajectories. In a forest research plot, we established a 1 m square grid of 625 (i.e., 25 × 25) photographic positions, and at each position, we captured 16 photographs in uniformly spaced directions. We adopted real tree positions and diameters, and the coordinates of the photographic positions, including orientation angles of captured images, were recorded. We then formulated an integer programming optimization model to find the most efficient trajectory that provided coverage of all sides of all trees with sufficient counts of images. Subsequently, we used the 10,000 captured images to produce image subsets simulating image sequences acquired during the photographer's movement along 84 different systematic trajectories of seven patterns based on either parallel lines or concentric orbits. 3D point clouds derived from the simulated image sequences were evaluated for their suitability for automatic tree detection and estimation of diameters at breast height. The results of the integer programming model indicated that the optimal trajectory consisted of parallel line segments if the camera is pointed forward – in the travel direction, or concentric orbits if the camera is pointed to a side – perpendicular to the travel direction. With point clouds derived from the images of the simulated trajectories, the best diameter estimates on automatically detected trees were achieved with trajectories consisting of parallel lines in two perpendicular directions where each line was passed in both opposite directions. For efficient image acquisition, resulting in point clouds of reasonable quality with low counts of images, a trajectory consisting of concentric orbits, including the plot perimeter with the camera pointed towards the plot center, proved to be the best. Results of simulated trajectories were verified with the photogrammetric reconstruction of the forest stand based on real trajectories for six patterns. The mathematical optimization was consistent with the results of the experiment, which indicated that mathematical optimization may represent a valid tool for planning trajectories for photogrammetric 3D reconstruction of scenes in general.

A Strategy of Parallel Seed-Based Image Segmentation Algorithms for Handling Massive Image Tiles over the Spark Platform

The volume of remote sensing images continues to grow as image sources become more diversified and with increasing spatial and spectral resolution. The handling of such large-volume datasets, which exceed available CPU memory, in a timely and efficient manner is becoming a challenge for single machines. The distributed cluster provides an effective solution with strong calculation power. There has been an increasing number of big data technologies that have been adopted to deal with large images using mature parallel technology. However, since most commercial big data platforms are not specifically developed for the remote sensing field, two main issues exist in processing large images with big data platforms using a distributed cluster. On the one hand, the quantities and categories of official algorithms used to process remote sensing images in big data platforms are limited compared to large amounts of sequential algorithms. On the other hand, the sequential algorithms employed directly to process large images in parallel over a distributed cluster may lead to incomplete objects in the tile edges and the generation of large communication volumes at the shuffle stage. It is, therefore, necessary to explore the distributed strategy and adapt the sequential algorithms over the distributed cluster. In this research, we employed two seed-based image segmentation algorithms to construct a distributed strategy based on the Spark platform. The proposed strategy focuses on modifying the incomplete objects by processing border areas and reducing the communication volume to a reasonable size by limiting the auxiliary bands and the buffer size to a small range during the shuffle stage. We calculated the F-measure and execution time to evaluate the accuracy and execution efficiency. The statistical data reveal that both segmentation algorithms maintained high accuracy, as achieved in the reference image segmented in the sequential way. Moreover, generally the strategy took less execution time compared to significantly larger auxiliary bands and buffer sizes. The proposed strategy can modify incomplete objects, with execution time being twice as fast as the strategies that do not employ communication volume reduction in the distributed cluster.

Airport Detection-Based Cosaliency on Remote Sensing Images

This paper proposes a contour extraction model based on cosaliency detection for remote sensing image airport detection and improves the traditional line segmentation detection (LSD) algorithm to make it more suitable for the goal of this paper. Our model consists of two parts, a cosaliency detection module and a contour extraction module. In the first part, the cosaliency detection module mainly uses the network framework of Visual Geometry Group-19 (VGG-19) to obtain the result maps of the interimage comparison and the intraimage consistency, and then the two result maps are multiplied pixel by pixel to obtain the cosaliency mask. In the second part, the contour extraction module uses superpixel segmentation and parallel line segment detection (PLSD) to refine the airport contour and runway information to obtain the preprocessed result map, and then we merge the result of cosaliency detection with the preprocessed result to obtain the final airport contour. We compared the model proposed in this article with four commonly used methods. The experimental results show that the accuracy of the model is 15% higher than that of the target detection result based on the saliency model, and the accuracy of the active contour model based on the saliency analysis is improved by 1%. This shows that the model proposed in this paper can extract a contour that closely matches the actual target.

A Parallel Backbone Networks Structure for Scene Text Detection

Text detection in complex scenes is very hard realize by the diversification of text distribution, direction, and typesetting. This paper proposes one scene text detection method with end-to-end structure with parallel backbone network and region segmentation. With multiple deformable convolutions and extracting features of multi-dimensional text regions, multiple candidate regions of different sizes are generated and corresponding states are further given. Experiments show that compared with baseline, this method can further adapt to the problem that the different shapes and angles of the target in the image lead to the decrease of accuracy.

Analyzing and Building an Advertising Image of the Library through User Interviews

Over the past decades, advertising for the library has become a mandatory part of the activity, but the approach to its creation is largely based on accepted stereotypes that express the most common ideas about the properties of such a complex phenomenon as the target audience of the library. Advertising can be expressed through an advertising image that contains not only objective but also subjective information; it uses associations, metaphors, emotions, visualization of something that has a generalizing character, i. e. a layer of implicit information is added to the exact data and read automatically. One of the problems of creating an advertising image may be that there are contradictions between the perception of the person who creates an advertising based on a stereotype and its recipient. The article reflects the experience of the State Public Scientific Technological Library of the Siberian Branch of the Russian Academy of Sciences (SPSTL SB RAS) in the study of two groups — “Event visitors” and “Readers”. The study involved 326 people (254 visitors to mass events and 72 readers of the SPSTL SB RAS). The author tested the method of semi-formalized interview to get relevant information for better understanding the audience’s motivation and desires. It is assumed to use pre-made plan with a list of mandatory questions, while using general wording and their variations, “close to the text”, and observing the general logic in their sequence.The author analyses the data on distribution of users in both groups (“Event visitors” and “Readers”) by the age categories and employment areas; frequency of library visits; frequency of references to forms of work that are called in demand and found interesting in both groups; frequency of references to preferred information channels. The article presents the main positions for creating an advertising image of the library. The author shows the expediency of using the semi-formalized interview method to adjust the advertising image of the library and the campaign to promote events, resources and services based on it, both for individual groups and for several segments in parallel, if the library’s event or service does not have a specific addressee. The article reveals the method of work that can be applied in the analysis of the advertising image for other libraries.

Liveable streets in Shanghai: Definition, characteristics and design

This monograph focuses on the concept of ‘liveable streets’ in China, which has been overlooked in the existing literature. This research has firstly developed an analytical framework with a hierarchy of liveability qualities, factors, and specific indicators for Shanghai. The framework was initially informed by the literature and then refined through questionnaires and interviews with urban development professionals in China (n = 107). Interviews with residents (n = 242) on residential streets were also conducted. The research applied and tested the framework’s usefulness in practice on fifteen selected street segments. Some street segments are rooted in the Chinese tradition, while others showcase strong international influences. According to their historical-morphological characteristics, the selected streets are categorised as S, M, L, XL, and XXL streets. Each category includes three parallel street segments that carry different volumes of vehicular traffic. The study reveals many physical and functional characteristics of streets that are conducive to vibrant social life, particularly manifested in the S and M streets in Shanghai. The analytical framework developed through this research informs a localised definition of liveable streets. Among six definitory liveability qualities, ‘social interaction’ and ‘sense of belonging’, reinforced by ‘local economic activities’ are specific to Shanghai and distinct from the Western context. The three other qualities include a ‘local humanised environment’, ‘facilities and mixed-uses’, and ‘safety’, which are also vital for liveable streets in Chinese cities. This research sheds light on contextualising liveability qualities and informs the design and planning of liveable streets in China.

Charge density wave and weak Kondo effect in a Dirac semimetal CeSbTe

Using angle-resolved photoemission spectroscopy (ARPES) and low-energy electron diffraction (LEED), together with density-functional theory (DFT) calculation, we report the formation of charge density wave (CDW) and its interplay with the Kondo effect and topological states in CeSbTe. The observed Fermi surface (FS) exhibits parallel segments that can be well connected by the observed CDW ordering vector, indicating that the CDW order is driven by the electron-phonon coupling (EPC) as a result of the nested FS. The CDW gap is large (∼0.3 eV) and momentum-dependent, which naturally explains the robust CDW order up to high temperatures. The gap opening leads to a reduced density of states (DOS) near the Fermi level (EF), which correspondingly suppresses the many-body Kondo effect, leading to very localized 4f electrons at 20 K and above. The topological Dirac cone at the X point is found to remain gapless inside the CDW phase. Our results provide evidence for the competition between CDW and the Kondo effect in a Kondo lattice system. The robust CDW order in CeSbTe and related compounds provide an opportunity to search for the long-sought-after axionic insulator.