General Mapping Research Articles

A Machine-Learning Approach to Generalisation of GIS Data

The automation of map generalisation in this study involves an expert system approach that consists of four main components including knowledge acquisition, an inference engine, knowledge representation and a user interface. The acquired knowledge was then utilised to build a knowledge-based solution: a ‘Generalisation Expert System’ (GES) developed in Java, Python and C programming environments for the delivery of generalised geographical features. Its capabilities are demonstrated in a case study through generalising several line and polyline databases over the study area in Canberra, Australia. The cartographic and GIS software communities will benefit from this study through access to a set of tools, guidelines and protocols that incorporate a standardised cartographic generalisation methodology. The results of the trials utilising GES were analysed: a series of generalisation routines were performed to assess the quality of simplification results for different spatial layers. Cartometric measures such as the total length and number of line or polyline segments were used as indices of generalisation to quantify generalisation performance for the target small scale. For example, there are 101,228 segments in 1:250,000 scale and 9,491 segments in 1:500,000 scale contours over the study area. This requires a reduction in the complexity and the density of elevation data. Changes in the representation of contour features at 1:250,000 and 1:500,000 scales as a result of generalisation were quantified. Outputs from map derivation have been analysed applying the Radical Law, this determines the retained number of objects for a given scale change and the number of objects of the original source map. Testing demonstrated that the implemented algorithms in GES are able to extract characteristic vertices on the original entity lines and polylines (e.g. for roads) while excluding non-characteristic lines and polylines to reduce irrelevant computation. This study has demonstrated reasonable improvements in Vertex Reduction, Classification and Merge, Enhanced Douglas-Peucker and Douglas-Peucker-Peschier algorithms. The test results show that GES generalises line features accurately while still maintaining their geometric relations. Existing generalisation software requires advanced technical skills from users; GES however, has a basic and user friendly Graphical User Interface (GUI) which is an advantage to users with basic technical skills and understanding of spatial data management. Changes to geographic parameters should be updated in multi-scale maps and spatial databases in near real-time. GES can be developed as a potential tool for generalising large-scale maps into smaller scales, and creating maps of different themes across a variety of scales. Test results have also demonstrated that the methodology developed improves the efficiency of line and polyline generalisation. This study aims to contribute to generalisation system design and the production of a clear framework for users. Experiments presented in this book can be applied to real world problems such as the generalisation of road networks and area features using GES. Future research should be directed towards developing web mapping platforms with generalisation functionality at varying scales.

General Higher-Order Lipschitz Mappings

In this paper, we introduce a new class of mappings and investigate their fixed point property. In the first direction, we prove a fixed point theorem for general higher-order contraction mappings in a given metric space and finally prove an approximate fixed point property for general higher-order nonexpansive mappings in a Banach space.

Modeling of pollutants from artisanal refining of crude oil in Port Harcourt: A case study of Eagle Island

Air sampling was carried out on the research area (Eagle Island) using both experimental and Gaussian dispersion model. A DM 106(particulate mass monitor) was applied to deduce the concentrations of suspended particulate matters (PM 1, PM 2.5, PM 10). Also, concentrations of pollutants (NO2, VOCs, SO2) were obtained using an Aerqual 300 device, while temperature, humidity, wind speed and wind direction were measured using Portable extech 45156 weather station and compass with experimental values obtained for two days (morning and night). Thus, these experimental concentration values obtained was plotted showing level of concentration at different locations (distances). In addition, Gaussian dispersion model was used to predict pollution concentration at various distances to ascertain the level of pollution within the research study area. Modeled results obtained was compared with experimental values to evaluate deviations, and a GIS based model (ARCGIS) was used to determine the general mapping of the research study area with dispersion of pollutants from source to distance up to 1000m depicted.

New species of Arctiocossus Felder, 1874 (Lepidoptera, Cossidae: Cossinae) from Republic of South Africa

The article describes a new species, Arctiocossus strohlei Yakovlev, sp. n. (Lepidoptera, Cossidae: Cossinae) from Republic of South Africa (Free State Province). The catalog of the genus is provided, the general distributional map is given. The article has 6 illustrations.

A new method to compute periodic orbits in general symplectic maps

The search of high-order periodic orbits has been typically restricted to problems with symmetries that help to reduce the dimension of the search space. Well-known examples include reversible maps with symmetry lines. The present work proposes a new method to compute high-order periodic orbits in twist maps without the use of symmetries. The method is a combination of the parameterization method in Fourier space and a Newton–Gauss multiple shooting scheme. The parameterization method has been successfully used in the past to compute quasi-periodic invariant circles. However, this is the first time that this method is used in the context of periodic orbits. Numerical examples are presented showing the accuracy and efficiency of the proposed method. The method is also applied to verify the renormalization prediction of the residues’ convergence at criticality (extensively studied in reversible maps) in the relatively unexplored case of maps without symmetries.

Distributed Online Caching for High-Definition Maps in Autonomous Driving Systems

This letter investigates online high-definition (HD) map caching for autonomous driving in vehicular networks when vehicles' requests and trajectories are unknown in advance. We first introduce a general HD map model that divides each HD map into different sub-maps to accommodate different driving functionalities. Then we introduce a service model for road side units (RSUs) by considering both the freshness of the dynamic sub-maps that are locally saved at each vehicle and the retrieving cost of sub-maps that are not cached at RSUs but must be needed for high-level driving control. After that, we propose a distributed multi-agent multi-armed bandit (MAMAB) algorithm for each RSU to learn its own cache strategy independently for maximizing the accumulated cache utility over a finite time horizon. Simulation results are provided to validate the effectiveness of our proposed algorithm.

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.

Base Station and Passive Reflectors Placement for Urban mmWave Networks

The use of millimeter-wave (mmWave) bands in 5G networks introduces a new set of challenges to network planning. Vulnerability to blockages and high path loss at mmWave frequencies require careful planning of the network to achieve a desired service quality. In this paper, we propose a novel 3D geometry-based framework for deploying mmWave base stations (gNBs) in urban environments by considering first-order reflection effects. We also provide a solution for the optimum deployment of passive metallic reflectors (PMRs) to extend radio coverage to non-line-of-sight (NLoS) areas. In particular, we perform visibility analysis to find the direct and indirect visibility regions, and using these, we derive a geometry-and-blockage-aided path loss model . We then formulate the network planning problem as two independent optimization problems, placement of gNB(s) and PMRs, to maximize the coverage area, minimize the deployment cost, and maintain a desired quality-of-service level. We test the efficacy of our proposed approach using a generic map and compare our simulation results with the ray tracing solution. Our simulation results show that considering the first-order reflections in planning the mmWave network helps reduce the number of PMRs required to cover the NLoS area. Moreover, the gNB placement aided with PMRs require fewer gNBs to cover the same area, which in turn reduces the deployment cost.

General Mapping Between Complex Spatial and Temporal Frequencies by Analytical Continuation

This article introduces a general technique for intermapping the complex spatial frequency (or propagation constant) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\gamma =\alpha +j\beta $ </tex-math></inline-formula> and the temporal frequency <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\omega = \omega _{\text {r}}+j\omega _{\text {i}}$ </tex-math></inline-formula> of arbitrary electromagnetic media and structures. This technique is based on the analytic property of complex functions that describe physical phenomena; it invokes the analytic continuity theorem to assert the unicity of the mapping function and builds this function from known data within a restricted domain of its analyticity by curve fitting to a generic polynomial expansion. It is not only applicable to canonical problems admitting an analytical solution but also to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">general</i> medium or structure problems, from eigen- or driven-mode full-wave simulation results. The proposed technique is demonstrated for several systems, namely, an unbounded lossy medium, a dielectric-filled rectangular waveguide, a periodically loaded transmission line, a 1-D photonic crystal, and a series-fed patch (SFP) leaky-wave antenna (LWA), and it is validated either by analytical results or by full-wave simulated results.

Topological Transversality Coincidence Theory for Multivalued Maps with Selections in a Given Class

Abstract This paper presents the topological transversality coincidence theorem for general multivalued maps who have selections in a given class of maps.

Practicum based learning in the material “understanding the basics of mapping” in geography subject high school

This article explains the experience in implementing practicum-based learning, especially in making maps, in geography Subject Grade X High School in Banda Aceh. It provides an overview of the application of practicum-based learning on map (cartography), which can be referred to by high school geography teachers, especially in Chapter 3.2. “Understanding the basics of mapping, remote sensing, and geographic information systems (GIS)”. This was a literature review that is following the experience of the application of practicum-based learning that we have done in subject schools. The application of practicum-based learning based on maps was done by general practicum based; Grouping, Preparing Materials, Understanding Step Activity, Working Project, and Sharing/Confirm Result. The learning was six themes: (1) copying map data into new maps manually, (2) lettering and completing map attributes, (3) manually counting area on the map, (4) Zoom in and out of the map, (5) Make a Map of the Globe, and (6) Overlays the Map Manually. Copying maps and lettering maps makes students understand about the data and attributes of general maps and understand the elements on the map. Students learn to make grid boxes and calculate the area with map scale make them do basic for calculating the area with pixels digitally. Making maps of a globe directly teaches them the principle of drawing the earth into a flat. Overlapping maps makes students understand the basics of map functions and determine information on it.

Mind the Gap! On the Discursive Construction of Collective Political Identities

This article explores, from a theoretical perspective, the dynamics underlying the discursive construction of collective identities within the political domain. Specifically, it: (1) presents a general mapping of political sphere studies carried out from a semiotic perspective; (2) attempts to bridge different paradigms within the semiotic tradition; and (3) establishes a dialogue between political theory and semiotics through the analysis of certain ideas belonging to the former whose semiotic nature has not yet been adequately examined, even if they are of a discursive nature. The article pays particular attention to the role that the ‘political gap’ – i.e., the space of indetermination between the various collective political identities that compete against each other in the ‘contest over meaning’ of politics – plays in the discursive construction of those identities. Arguing from a constructivist premise, establishing relational differences is a constitutive feature of the meaning-making, dynamic, and gaps between collective identities, a necessary precondition for their discursive emergence and the political sphere’s existence.

NURBS-based geometries: A mapping approach for virtual serendipity elements

A NURBS-based serendipity virtual element method for general (arbitrary) element shapes is outlined in this work. The low-order VEM ansatz function is now extended towards higher-order formulation. In comparison with the already existing serendipity VEM, a general mapping scheme is developed within this contribution allowing to deviate from the assumption of straight edges of virtual elements. A number of numerical examples illustrates the robustness and accuracy of the new mapping methodology. The results are very promising and underline the advantages of the formulations for dealing with arbitrary geometries.

Hull Shape Design Optimization with Parameter Space and Model Reductions, and Self-Learning Mesh Morphing

In the field of parametric partial differential equations, shape optimization represents a challenging problem due to the required computational resources. In this contribution, a data-driven framework involving multiple reduction techniques is proposed to reduce such computational burden. Proper orthogonal decomposition (POD) and active subspace genetic algorithm (ASGA) are applied for a dimensional reduction of the original (high fidelity) model and for an efficient genetic optimization based on active subspace property. The parameterization of the shape is applied directly to the computational mesh, propagating the generic deformation map applied to the surface (of the object to optimize) to the mesh nodes using a radial basis function (RBF) interpolation. Thus, topology and quality of the original mesh are preserved, enabling application of POD-based reduced order modeling techniques, and avoiding the necessity of additional meshing steps. Model order reduction is performed coupling POD and Gaussian process regression (GPR) in a data-driven fashion. The framework is validated on a benchmark ship.

Studying Political Communities in VK.com with Network Analysis

The study explores politicized virtual communities of Russia in the VK.com within the social network analysis approach. The paper focuses on the VK since it is the largest social networking service in Russia. The authors aim to draw a general map of virtual communities in the VK which are politically engaged and represent all political ideologies in Russia. The data were collected with help of the VK API in 2019. Based on the specially designed algorithm, the authors have collected a sample of 115 politicized communities. The paper presents a critical analysis of the implementation of data sampling and crawling. The authors argue that this study includes all significant virtual communities from a full range of ideologically and politically oriented discussion groups to institutionalized political actors such as political parties and government agencies, including groups of leading Russian mass media. The authors apply the Gephi network analysis and visualization software package, a leading social network analysis software, to produce a map of the political virtual communities in Russia. The study indicates that virtual communities of mass media and the institutionalized communities, such as political parties or government institutions, have concentrated at the core of the graph. At the same time, discussion groups about ideologies were in the periphery of the graph.

Impact of ICD-9-CM to ICD-10-CM coding transition on trauma hospitalization trends among young adults in 12 states

BackgroundWe aimed to estimate the impact of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding transition on traumatic injury-related hospitalization trends among young adults across a geographically and demographically diverse group of U.S. states.MethodsInterrupted time series analyses were conducted using statewide inpatient databases from 12 states and including traumatic injury-related hospitalizations in adults aged 19–44 years in 2011–2017. Segmented regression models were used to estimate the impact of the October 2015 coding transition on external cause of injury (ECOI) completeness (percentage of hospitalizations with a documented ECOI code) and on population-level rates of injury-related hospitalizations by nature, intent, mechanism, and severity of injury.ResultsThe transition to ICD-10-CM was associated with a drop in ECOI completion in the transition month (− 3.7%; P < .0001), but there was no significant change in the positive trend in ECOI completion from the pre- to post-transition periods. There were significant increases post-transition in the measured rates of hospitalization for traumatic brain injury (TBI), unintentional injury, mild injury (injury severity score (ISS) < 9), and injuries caused by drowning, firearms, machinery, other pedestrian, suffocation, and unspecified mechanism. Conversely, there were significant decreases in October 2015 in the rates of hospitalization for assault, injuries of undetermined intent, injuries of moderate severity (ISS 9–15), and injuries caused by fire/burn, other pedal cyclist, other transportation, natural/environmental, and other specified mechanism. A significant increase in the percentage of hospitalizations classified as resulting from severe injury (ISS > 15) was observed when the general equivalence mapping maximum severity method for converting ICD-10-CM codes to ICD-9-CM codes was used. State-specific results for the outcomes of ECOI completion and TBI-related hospitalization rates are provided in an online supplement.ConclusionsThe U.S. transition from ICD-9-CM to ICD-10-CM coding led to a significant decrease in ECOI completion and several significant changes in measured rates of injury-related hospitalizations by injury intent, mechanism, nature, and severity. The results of this study can inform the design and analysis of future traumatic injury-related health services research studies that use both ICD-9-CM and ICD-10-CM coded data.Level of evidenceII (Interrupted Time Series)

The MinimumBreak algorithm applied to a series of road turns

Cartographic generalization is the process of small-scale map production from large-scale maps. When the size of the map is reduced, the objects present in the latter can conflict with each other. There may be overlapping of objects, coalesced roads, or imperceptibility problems. Generalization solves these problems through algorithms. However, the generalization is not yet automated due to the lack of algorithms. In this article, a new algorithm for processing turn series on a road to correct the coalescence is investigated. Tests as well as comparisons with existing algorithms are going to be conducted. This research has proven to be beneficial to the field of cartography as there is a lack of algorithms treating complex series of turns when producing a map. The samples used for the study are winding mountainous roads from Algeria, China, Norway, Switzerland, and France.

Two-Dimensional Memristive Hyperchaotic Maps and Application in Secure Communication

Continuous memristor has been widely used in chaotic oscillating circuits and neuromorphic computing systems. However, discrete memristor and its coupling discrete map have not been noticed yet. This article presents a discrete memristor and constructs a general two-dimensional memristive map model by coupling the discrete memristor with an existing discrete map. The pinched hysteresis loops of the discrete memristor are demonstrated. Four examples of memristive discrete maps are provided and their coupling strength-relied and memristor initial-boosted complex dynamics are investigated using numerical measures. The evaluation results manifest that the discrete memristor can enhance the chaos complexity and its coupling maps can generate hyperchaos. Particularly, the hyperchaotic sequences can nondestructively be controlled by memristor initial state and the initial-controlled hyperchaos is robust, which is applicable to many chaos-based applications. Additionally, we develop a hardware platform to implement the memristive maps and acquire the four-channel hyperchaotic sequences. We also apply the memristive maps to the application of secure communication and the experiments show that the memristive maps display better performance than some existing discrete maps.

Transformation Cloaking in Elastic Plates

In this paper we formulate the problem of elastodynamic transformation cloaking for Kirchhoff-Love plates and elastic plates with both the in-plane and out-of-plane displacements. A cloaking transformation maps the boundary-value problem of an isotropic and homogeneous elastic plate (virtual problem) to that of an anisotropic and inhomogeneous elastic plate with a hole surrounded by a cloak that is to be designed (physical problem). For Kirchhoff-Love plates, the (out-of-plane) governing equations of the virtual plate is transformed to those of the physical plate up to an unknown scalar field. In doing so, one finds the initial stress and the initial tangential body force for the physical plate, along with a set of constraints that we call cloaking compatibility equations. These constraints involve the cloaking transformation, the unknown scalar field, and the elastic constants of the virtual plate. It is noted that the cloaking map needs to satisfy certain conditions on the outer boundary of the cloak and the surface of the hole. In particular, the cloaking map needs to fix the outer boundary of the cloak up to the third order. Assuming a generic radial cloaking map, we show that cloaking a circular hole in Kirchoff-Love plates is not possible; the cloaking compatibility equations and the boundary conditions that the cloaking map needs to satisfy are the obstruction to cloaking. Next, relaxing the pure bending assumption, the transformation cloaking problem of an elastic plate in the presence of in-plane and out-of-plane displacements is formulated. In this case, there are two sets of governing equations that need to be simultaneously transformed under the cloaking map. We show that cloaking a circular hole is not possible for a general radial cloaking map; the cloaking compatibility equations and the boundary conditions that the cloaking map needs to satisfy obstruct cloaking.

GeoSparkViz: a cluster computing system for visualizing massive-scale geospatial data

In the last decade, geospatial data which is extracted from GPS traces and satellites image has become ubiquitous. GeoVisual analytics, abbr. GeoViz, is the science of analytical reasoning assisted by geospatial map interfaces. GeoViz involves two phases: (1) spatial data processing: that loads spatial data and executes spatial queries to return the set of spatial objects to be visualized. (2) Map visualization: that applies a map visualization effect, e.g., Heatmap, on the spatial objects produced in the first phase. Existing GeoViz system architectures decouple these two phases, which lose the opportunity to co-optimize the data processing and map visualization phases in the same cluster. To remedy this, the paper presents GeoSparkViz, a full-fledged system that allows the user to load, process, integrate and execute GeoViz tasks on spatial data at scale. GeoSparkViz extends a state-of-the-art distributed data management system to provide native support for general geospatial map visualization. The system encapsulates the main steps of the map visualization process, e.g., pixelize spatial objects, pixel aggregation, and map tile rendering into a set of massively parallelized map building operators. This allows the system to co-optimize the spatial query operators and map building operators side by side. GeoSparkViz is also equipped with a GeoViz-aware spatial partitioning operator that achieves load balancing for GeoViz workloads among all nodes in the cluster. Experiments based on an implementation in Spark show that GeoSparkViz achieves up to an order of magnitude less data-to-visualization time than its counterparts when running visual analytics tasks over large-scale spatial data extracted from the NYC taxi dataset and OpenStreetMaps.