Hybrid Mapping Research Articles

Fixed points of generalized hybrid mappings in 2-uniformly convex hyperbolic metric spaces

Fixed points of generalized hybrid mappings in 2-uniformly convex hyperbolic metric spaces

OGI-SLAM2: A Hybrid Map SLAM Framework Grounded in Inertial-Based SLAM

Indoor localization using mobile sensors has gained momentum lately. However, indoor pedestrian localization with low-cost IMU has not been practically applied, and the main challenge is that it is difficult for low-cost IMU to obtain high-precision localization performance over a long period of time. In this paper, we propose a multi-source fusion indoor pedestrian autonomous localization framework combining landmark maps and occupancy grid maps. Combining the ideas of optimization and occupancy grid map-based inertial SLAM algorithm(OGI-SLAM), we maintain the short- and medium-term localization accuracy with OGI-SLAM, and achieve long-term localization accuracy improvement with keypoint maps. Without prior knowledge of the map, we use user motion features and environmental features to extract keypoints in the trajectory and construct keypoint descriptors. Combining the uncertainty of system location and the similarity of environmental features, we propose a keypoint extraction and association method to solve the problem of inaccurate particle filtering loop closing with low-cost IMU. In addition, a two-step trajectory optimization method is proposed, which uses bundle adjustment to correct the positioning error of keypoints and models the error correction of common points between keypoints as affine transformation, avoiding the large matrix inversion operation in the optimization process. Simulations and field trial evaluations show that the system is able to achieve a maximum positioning accuracy of 1.64 meters with low-performance IMU on board, representing a 57% maximum improvement in positioning accuracy compared to OGI-SLAM. This highlights the promise of OGI-SLAM2 as an unconventional indoor positioning method.

Weak convergence theorems for symmetric generalized hybrid mappings and equilibrium problems

<p style='text-indent:20px;'>In this paper, we introduce three new iterative methods for finding a common point of the set of fixed points of a symmetric generalized hybrid mapping and the set of solutions of an equilibrium problem in a real Hilbert space. Each method can be considered as an combination of Ishikawa's process with the proximal point algorithm, the extragradient algorithm with or without linesearch. Under certain conditions on parameters, the iteration sequences generated by the proposed methods are proved to be weakly convergent to a solution of the problem. These results extend the previous results given in the literature. A numerical example is also provided to illustrate the proposed algorithms.</p>

Fixed Point Theorems for Pemetaan Nonexpansive, Nonspreading, and Hybrid Mappings in Hilbert Space.

A Firmly nonexpansive mapping is a map which is closely related to equilibrium problems Nonexpansive, nonspreading, and hybrid mappings are nonlinear mappings in Hilbert spaces. In this paper, we show the existence of a fixed point of nonexpansive, nonspreading, and hybrid mappings in Hilbert space using The Banach limit.

Image Watermarking Based on Chaos Encryption with Hybrid Mapping and Grey Wolf Optimizer

Image Watermarking Based on Chaos Encryption with Hybrid Mapping and Grey Wolf Optimizer

Weak and Strong Convergence Theorems for Common Attractive Points of Widely More Generalized Hybrid Mappings in Hilbert Spaces

In this work, we study iterative methods for the approximation of common attractive points of two widely more generalized hybrid mappings in Hilbert spaces and obtain weak and strong convergence theorems without assuming the closedness for the domain. A numerical example supporting our main result is also presented. As a consequence, our main results can be applied to solving a common fixed point problem.

Complexity in a Hybrid van der Pol System

In this work, we study, from a numerical point of view, the dynamics of a specific hybrid map which is that of the kicked van der Pol system. The dynamics of this system is generated by a two-stage procedure: the first stage is the time-[Formula: see text] map of the vector field associated with the van der Pol equation, and the second stage is a translation. We propose a numerical method for computing local (un)stable manifolds of a given fixed point, which leads to high order polynomial parameterization of the embedding. Such a representation of the dynamics on the manifold is obtained in terms of a simple conjugacy relation and by constructing two contracting operators. We illustrate our techniques by plotting (for specific values of the parameters) both stable and unstable manifolds displaying homoclinic intersection. Furthermore, our numerical study reveals the presence of a strange attractor included in the closure of the unstable manifold of the fixed point.

Domain-specific Hybrid Mapping for Energy-efficient Baseband Processing in Wireless Networks

Advancing telecommunication standards continuously push for larger bandwidths, lower latencies, and faster data rates. The receiver baseband unit not only has to deal with a huge number of users expecting connectivity but also with a high workload heterogeneity. As a consequence of the required flexibility, baseband processing has seen a trend towards software implementations in cloud Radio Access Networks (cRANs). The flexibility gained from software implementation comes at the price of impoverished energy efficiency. This paper addresses the trade-off between flexibility and efficiency by proposing a domain-specific hybrid mapping algorithm. Hybrid mapping is an established approach from the model-based design of embedded systems that allows us to retain flexibility while targeting heterogeneous hardware. Depending on the current workload, the runtime system selects the most energy-efficient mapping configuration without violating timing constraints. We leverage the structure of baseband processing, and refine the scheduling methodology, to enable efficient mapping of 100s of tasks at the millisecond granularity, improving upon state-of-the-art hybrid approaches. We validate our approach on an Odroid XU4 and virtual platforms with application-specific accelerators on an open-source prototype. On different LTE workloads, our hybrid approach shows significant improvements both at design time and at runtime. At design-time, mappings of similar quality to those obtained by state-of-the-art methods are generated around four orders of magnitude faster. At runtime, multi-application schedules are computed 37.7% faster than the state-of-the-art without compromising on the quality.

Cytogenomic analysis unveils mixed molecular evolution and recurrent chromosomal rearrangements shaping the multigene families on Schistocerca grasshopper genomes.

Multigene families are essential components of eukaryotic genomes and play key roles either structurally and functionally. Their modes of evolution remain elusive even in the era of genomics, because multiple multigene family sequences coexist in genomes, particularly in large repetitive genomes. Here, we investigate how the multigene families 18S rDNA, U2 snDNA, and H3 histone evolved in 10 species of Schistocerca grasshoppers with very large and repeat-enriched genomes. Using sequenced genomes and fluorescence in situ hybridization mapping, we find substantial differences between species, including the number of chromosomal clusters, changes in sequence abundance and nucleotide composition, pseudogenization, and association with transposable elements (TEs). The intragenomic analysis of Schistocerca gregaria using long-read sequencing and genome assembly unveils conservation for H3 histone and recurrent pseudogenization for 18S rDNA and U2 snDNA, likely promoted by association with TEs and sequence truncation. Remarkably, TEs were frequently associated with truncated copies, were also among the most abundant in the genome, and revealed signatures of recent activity. Our findings suggest a combined effect of concerted and birth-and-death models driving the evolution of multigene families in Schistocerca over the last 8 million years, and the occurrence of intra- and interchromosomal rearrangements shaping their chromosomal distribution. Despite the conserved karyotype in Schistocerca, our analysis highlights the extensive reorganization of repetitive DNAs in Schistocerca, contributing to the advance of comparative genomics for this important grasshopper genus.

Exploiting In-Hand Knowledge in Hybrid Joint-Cartesian Mapping for Anthropomorphic Robotic Hands

Replication of human hand motions on anthropomorphic robotic hands is typically treated in literature as the combination of two sub-problems: the measurement of human hand motions, and the mapping of such motions on the robotic hand. In this letter we focus on the second one. Different approaches have been proposed to deal with this problem, but none of them preserves both master finger shapes and fingertip positions on the robotic hand, i.e. ensuring predictability and natural motion for the teleoperator. In this article, we propose a novel hybrid approach that combines both joint and Cartesian mappings in a single solution. In particular, we exploit the a priori, in-hand information related to the areas of the workspace in which thumb and finger fingertips can get in contact. This allows to define, for each finger, a zone of transition from joint to Cartesian mapping. As a consequence, both hand shape during volar grasps and correctness of the fingertip positions for precision grasps are preserved, despite the master-slave kinematic dissimilarities. The proposed hybrid mapping is presented and experimentally evaluated both in simulation and with a real slave anthropomorphic robotic hand.

Some common fixed-point theorems for a pair of p-hybrid mappings via common limit range property in G-metric space

This paper aims to prove common fixed point theorems for a pair of hybrid and p-hybrid mappings via common limit range property in G-metric space setting. The
 theorems proved here will generalise the results due to Nashine et al. [35], Karapinar et al. [23, 24] from metric space notion to G-metric space and that of Mustafa et
 al.[30] using (CLRf ) property concept in G-metric space, and many others in this setting. We also provided an illustrative example to validate the results.

Aspects of Atlas Mapping for Analysis of Energy Infrastructure in Different Regions

he paper addresses the visualization and systematization of cartographic material for analyzing energy infrastructure in various world regions. It discusses the technology (architecture) for building maps based on the concept of atlas mapping. An interface was developed for the construction of interactive maps and navigation in any section of the world atlas - from the level of world continents to a detailed map of any region within the country. We have constructed and stored contour maps of all countries of the world in the database of the computing geo-information system (СGIS). CGIS allows constructing hybrid maps, which contain vector and raster map layers with the energy infrastructure overlaid on them in the selected territory. An algorithm was constructed to search for energy objects and administrative entities in any country or region of the world. The atlases built by CGIS are used at Melentiev Energy Systems Institute (MESI) of the Siberian Branch of the Russian Academy of Sciences to plot the solutions obtained with the optimization model ORIRES (which reflects the optimal operation of the interconnected power systems in different scenarios) on a map of a selected area or region.

Hybrid MAP and PIC Detection for OTFS Modulation

Orthogonal time frequency space (OTFS) modulation has attracted substantial attention recently due to its great potential of providing reliable communications in high-mobility scenarios. In this article, we propose a novel hybrid signal detection algorithm for OTFS modulation. Based on the system model, we first derive the near-optimal <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">symbol-wise</i> maximum <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a posteriori</i> (MAP) detection algorithm for OTFS modulation. Then, in order to reduce the detection complexity, we propose a partitioning rule that separates the related received symbols into two subsets for detecting each transmitted symbol, according to the corresponding path gains. According to the partitioning rule, we design the hybrid detection algorithm to exploit the power discrepancy of each subset, where the MAP detection is applied to the subset with larger channel gains, while the parallel interference cancellation (PIC) detection is applied to the subset with smaller channel gains. We also provide the error performance analysis of the proposed hybrid detection algorithm. Simulation results show that the proposed hybrid detection algorithm can not only approach the performance of the near-optimal <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">symbol-wise</i> MAP algorithms, but also offer a substantial performance gain compared with existing algorithms.

AR-Based Navigation Using RGB-D Camera and Hybrid Map

Current pedestrian navigation applications have been developed for the smartphone platform and guide users on a 2D top view map. The Augmented Reality (AR)-based navigation from the first-person view could provide a new experience for pedestrians compared to the current navigation. This research proposes a marker free system for AR-based indoor navigation. The proposed system adopts the RGB-D camera to observe the surrounding environment and builds a point cloud map using Simultaneous Localization and Mapping (SLAM) technology. After that, a hybrid map is developed by integrating the point cloud map and a floor map. Finally, positioning and navigation are performed on the proposed hybrid map. In order to visualize the augmented navigation information on the real scene seamlessly, this research proposes an orientation error correction method to improve the correctness of navigation. The experimental results indicated that the proposed system could provide first-person view navigation with satisfactory performance. In addition, compared to the baseline without any error correction, the navigation system with the orientation error correction method achieved significantly better performance. The proposed system is developed for the smart glasses and can be used as a touring tool.

Simulation of average monthly ozone exposure concentrations in China: A temporal and spatial estimation method

BackgroundOzone has adverse effects on human health, it is necessary to obtain the refined ozone exposure concentration. At present, most of existing ozone exposure research is based on ground air quality monitoring station (MS) which gather urban area information only. It is diffcult to estimate the ozone in the areas where MSs are scarce. ObjectiveBy combining accurate but uneven data of outdoor ozone exposure concentrations based on MSs and unbiased coverage data based on RS in China, we can improve the accuracy of simulation of average monthly ozone exposure concentrations in monitor-free area. Since ozone concentrations are usually low at night, ozone exposure is assessed during the day (e.g., 10:00–18:00). MethodsWe proposed a space–time geostatistical kriging interpolation based on the composite space/time mean trend model (CSTM) to predict ozone exposure in mainland China, having obtained a refined ozone exposure concentration interpolation map from an MS. We verified the accuracy of the interpolation results and remote sensing (RS) data, while simultaneously determining the distance threshold (according to the data accuracy) to improve the accuracy of the hybrid map. ResultsWe used a refined smoothing filter to reduce the influence of spatial and seasonal trends on ozone concentration. We found a cutoff separation distance of 175 km at which the two data showed an equal estimation accuracy, and the estimation result was fused with RS data through the distance threshold. Finally, The multi-source data with the best accuracy were fused to obtain the refined map. In China, ozone exposure concentration mainly gathers in the northern and eastern regions as well as part of the central mainland. ConclusionsRS data can be used to characterize ground ozone exposure concentrations when 24th-layer data and MS data for monitoring ozone exposure concentrations are combined to estimate temporal and spatial ozone exposure in China. Ozone exposure in China can be explored further to provide suggestions for human health and regional economic development.

A Monocular Visual Odometry Method Based on Virtual-Real Hybrid Map in Low-Texture Outdoor Environment.

With the extensive application of robots, such as unmanned aerial vehicle (UAV) in exploring unknown environments, visual odometry (VO) algorithms have played an increasingly important role. The environments are diverse, not always textured, or low-textured with insufficient features, making them challenging for mainstream VO. However, for low-texture environment, due to the structural characteristics of man-made scene, the lines are usually abundant. In this paper, we propose a virtual-real hybrid map based monocular visual odometry algorithm. The core idea is that we reprocess line segment features to generate the virtual intersection matching points, which can be used to build the virtual map. Introducing virtual map can improve the stability of the visual odometry algorithm in low-texture environment. Specifically, we first combine unparallel matched line segments to generate virtual intersection matching points, then, based on the virtual intersection matching points, we triangulate to get a virtual map, combined with the real map built upon the ordinary point features to form a virtual-real hybrid 3D map. Finally, using the hybrid map, the continuous camera pose estimation can be solved. Extensive experimental results have demonstrated the robustness and effectiveness of the proposed method in various low-texture scenes.

The assembly of caprine Y chromosome sequence reveals a unique paternal phylogenetic pattern and improves our understanding of the origin of domestic goat.

The mammalian Y chromosome offers a unique perspective on the male reproduction and paternal evolutionary histories. However, further understanding of the Y chromosome biology for most mammals is hindered by the lack of a Y chromosome assembly. This study presents an integrated in silico strategy for identifying and assembling the goat Y‐linked scaffolds using existing data. A total of 11.5 Mb Y‐linked sequences were clustered into 33 scaffolds, and 187 protein‐coding genes were annotated. We also identified high abundance of repetitive elements. A 5.84 Mb subset was further ordered into an assembly with the evidence from the goat radiation hybrid map (RH map). The existing whole‐genome resequencing data of 96 goats (worldwide distribution) were utilized to exploit the paternal relationships among bezoars and domestic goats. Goat paternal lineages were clearly divided into two clades (Y1 and Y2), predating the goat domestication. Demographic history analyses indicated that maternal lineages experienced a bottleneck effect around 2,000 YBP (years before present), after which goats belonging to the A haplogroup spread worldwide from the Near East. As opposed to this, paternal lineages experienced a population decline around the 10,000 YBP. The evidence from the Y chromosome suggests that male goats were not affected by the A haplogroup worldwide transmission, which implies sexually unbalanced contribution to the goat trade and population expansion in post‐Neolithic period.

High-resolution mapping of the Mov-1 locus in wheat by combining radiation hybrid (RH) and recombination-based mapping approaches.

This work reports a quick method that integrates RH mapping and genetic mapping to map the dominant Mov-1 locus to a 1.1-Mb physical interval with a small number of candidate genes. Bread wheat is an important crop for global human population. Identification of genes and alleles controlling agronomic traits is essential toward sustainably increasing crop production. The unique multi-ovary (MOV) trait in wheat holds potential for improving yields and is characterized by the formation of 2-3 grains per spikelet. The genetic basis of the multi-ovary trait is known to be monogenic and dominant in nature. Its precise mapping and functional characterization is critical to utilizing this trait in a feasible manner. Previous mapping efforts of the locus controlling multiple ovary/pistil formation in the hexaploid wheat have failed to produce a consensus for a particular chromosome. We describe a mapping strategy integrating radiation hybrid mapping and high-resolution genetic mapping to locate the chromosomal position of the Mov-1 locus in hexaploid wheat. We used RH mapping approach using a panel of 188 lines to map the Mov-1 locus in the terminal part of long arm of wheat chromosome 2D with a map resolution of 1.67Mb/cR1500. Then using a genetic population of MOV × Synthetic wheat of F2 lines, we delineated the Mov-1 locus to a 1.1-Mb physical region with a small number of candidate genes. This demonstrates the value of this integrated strategy to mapping dominant genes in wheat.

Mean convergence theorems using hybrid methods to find common fixed points for noncommutative nonlinear mappings in Hilbert spaces

This paper considers approximation methods to find common fixed points for two general nonlinear mappings that contain generalized hybrid mappings or normally 2-generalized hybrid mappings. First, we combine Nakajo and Takahashi’s hybrid method with a mean iteration method and prove three strong convergence theorems that approximate common fixed points for nonlinear mappings. We then develop Takahashi, Takeuchi and Kubota’s shrinking projection method and prove three strong convergence theorems. Nonlinear mappings are not necessarily continuous or commutative.

Qualitative Methods and Hybrid Maps for Spatial Perception with an Example of Security Perception

The security/insecurity of our cities has become the subject of public debate in recent years. The individual intuitions about security or insecurity can vary with age, gender, social background, personal constitution and previous positive or negative experiences. They are also constantly (re)produced, as perceptions of space are individual and selective. Noting these variations, materialised factors also play a major role, e.g., recessed house entrances, dense or high hedges, poor orientation options, dark places, etc. Attributing meaning to these materialised factors, real constructs are formed which create positive or negative narratives about certain (urban) spaces, influencing the actual use and design of urban spaces. To investigate the importance attached to certain spaces, qualitative methods are required for examining socio-spatial situations, perceptual processes and attribution. Using different methods in an explorative and in-depth descriptive research phase, such as expert interviews, user observations, surveys on go-alongs, participatory mapping with detailed information on structural and spatial locations, the advantages and disadvantages of method selection are presented. Berlin’s Alexanderplatz was used as a case study area to determine perceptions of security in urban areas. We confirmed that despite variations, certain subjective perceptions concerning visibility, brightness, and audibility are collective. Additionally, hybrid maps are used to explain how subjective perceptions of space, combined with 3D graphics, can alert architects and city planners to uncertainty among users of public space.