Map Symbols Research Articles

An Efficient, Platform-Independent Map Rendering Framework for Mobile Augmented Reality

With the extensive application of big spatial data and the emergence of spatial computing, augmented reality (AR) map rendering has attracted significant attention. A common issue in existing solutions is that AR-GIS systems rely on different platform-specific graphics libraries on different operating systems, and rendering implementations can vary across various platforms. This causes performance degradation and rendering styles that are not consistent across environments. However, high-performance rendering consistency across devices is critical in AR-GIS, especially for edge collaborative computing. In this paper, we present a high-performance, platform-independent AR-GIS rendering engine; the augmented reality universal graphics library (AUGL) engine. A unified cross-platform interface is proposed to preserve AR-GIS rendering style consistency across platforms. High-performance AR-GIS map symbol drawing models are defined and implemented based on a unified algorithm interface. We also develop a pre-caching strategy, optimized spatial-index querying, and a GPU-accelerated vector drawing algorithm that minimizes IO latency throughout the rendering process. Comparisons to existing AR-GIS visualization engines indicate that the performance of the AUGL engine is two times higher than that of the AR-GIS rendering engine on the Android, iOS, and Vuforia platforms. The drawing efficiency for vector polygons is improved significantly. The rendering performance is more than three times better than the average performances of existing Android and iOS systems.

Online emergency mapping based on disaster scenario and data integration

ABSTRACT Emergency mapping is a task that requires abundant professional knowledge and complex operations, especially in high timeliness demands in disaster scenarios. The operation of the conventional cartographic system based on GIS in the desktop environment is complicated and requires operators to have strong professional skills, while the network environment provides low-cost, unified geographical data services and easy-to-use operation without using any specific software. In this paper, we propose an online emergency mapping framework, which is a novel idea for rapid mapping and combining multi-source heterogeneous disaster data with cartographer knowledge. Through a disaster scenario model for emergency mapping, the corresponding relationship between scenarios and map groups can be understood. Through disaster data integration, knowledge rules, mapping templates, map symbol engines, and a simple wizard, an emergency response map can be rapidly produced. With the support of the techniques mentioned above, a prototype system is developed to verify the efficiency and validity of the framework. The results demonstrate that a framework that can effectively assist decision makers in displaying the present situation clearly and accurately has high practical value. The study also provides a novel perspective for shortening the mapping cycle in emergencies.

Evaluating the effectiveness and efficiency of risk communication for maps depicting the hazard of COVID-19.

COVID‐19 maps convey hazard and risk information to the public, which play an important role in the risk communication for individual protection. The aim of this study is to improve the effectiveness and efficiency of communicating the specific risk of COVID‐19 maps. By testing 71 subjects from Wuhan, China, this study explored how color schemes (cool, warm, and mixed colors) and data presentation forms (choropleth maps, graduated symbol maps) influence visual cognition patterns, risk perception, comprehension, and subjective satisfaction. The results indicated that the warm scheme (yellow/red) has significant strengths in visual cognition and understanding, and the choropleth map (vs. the graduated symbol map) has significant strengths in risk expression. On subjective satisfaction, the combination of the mixed scheme (blue/yellow/red) and the choropleth map scored highest mean value. These results have implications for enhancing the focused functions of COVID‐19 maps that fit different terms: in the early and medium terms of disease transmission, choropleth maps with warm or cool colors should be considered as a priority design for their better risk perception. When the epidemic conditions are on the upturn, a better reading experience combination of choropleth maps with mixed colors can be considered.

Poincaré–Birkhoff–Witt isomorphisms and Kapranov dg-manifolds

We prove that to every inclusion A↪L of Lie algebroids over the same base manifold M corresponds a Kapranov dg-manifold structure on A[1]⊕L/A, which is canonical up to isomorphism. As a consequence, Γ(Λ•A∨⊗L/A) carries a canonical L∞[1] algebra structure whose unary bracket is the Chevalley–Eilenberg differential dA∇Bott corresponding to the Bott representation of A on L/A and whose binary bracket is a cocycle representative of the Atiyah class of the Lie pair (L,A). To this end, we construct explicit isomorphisms of C∞(M)-coalgebras Γ(S(L/A))→∼U(L)U(L)Γ(A), which we elect to call Poincaré–Birkhoff–Witt maps. These maps admit a recursive characterization that allows for explicit computations. They generalize both the classical symmetrization map S(g)→U(g) of Lie theory and (the inverse of) the complete symbol map for differential operators. Finally, we prove that the Kapranov dg-manifold A[1]⊕L/A is linearizable if and only if the Atiyah class of the Lie pair (L,A) vanishes.

On Syntomic Complexes with Modulus for Semi-stable Reduction Cases

In this paper, we define a syntomic complex for modulus pair $(X,D)$, where $X$ is a regular semi-stable family and $D$ is an effective Cartier divisor on $X$ and we compute its cohomology sheaves. We construct a symbol map for this syntomic complex for modulus pair $(X,D)$ and investigate its cokernel by computing its cohomology sheaves. To compute the structure of the cohomology sheaves of syntomic complex with modulus, we define some filtrations on it.

Mapping Bodies, Designing Feminist Icons

Bodies are nuanced, fluid, and political—often combining forms of intersecting and experiential identities. Nevertheless, bodies are frequently missing from maps altogether or, when they are included on maps, they are reduced to points, lines, and polygons. Focusing on iconography, I explore the depiction of bodies in map symbolization through a feminist lens. I apply a feminist semiotic analysis to thirty-eight Maki icons to problematize the ways in which bodies are depicted, abstracted, or erased. I analyze icon symbolization, particularly the presence/absence of bodily forms, the presence/absence of an embodied object, and the icons’ iconicity. My feminist analysis reveals the underlying silences, defaults, and power dynamics within the Maki icon set. I call mapmakers to rethink the depictions of bodies in icons—and the role of “universal” icon sets, more broadly—through a feminist lens. I offer design opportunities as a starting point for such an endeavor.

Exploring basic numerical capacities in children with difficulties in simple arithmetical achievement

Introduction: Current cognitive theories suggest that mathematical learning disabilities may be caused by a dysfunction in the ability to represent non-symbolic numerosity (non-symbolic skills), by impairments in the ability to associate symbolic numerical representations with the underlying analogic non-numerical magnitude representation (symbolic and numerical mapping skills), or by a combination of both deficits. The aim of this study was to contrast the number sense hypothesis and the access deficit hypothesis, to identify the possible origin of the varying degrees of arithmetical difficulties. Method: We compared the performance of children with very low arithmetic achievement (VLA), children with low arithmetical achievement (LA), and typically achieving peers (TA), in non-symbolic, symbolic and numerical mapping tasks. Intellectual capacity and working memory were also evaluated as control variables. The sample comprised 85 Chilean children (3rd to 6th grades) from the Public General Education System. Data were included in several covariance analyses to identify potentially different behavioural profiles between groups. Results: The results showed deficits in both non-symbolic numerosity processing and number-magnitude mapping skills in children with VLA, whereas children with LA exhibited deficits in numerical mapping tasks only. Conclusions: These findings support the hypothesis of impaired non-symbolic numerical representations as the cognitive foundation of severe arithmetical difficulties. Low arithmetical achievement, in contrast, seems to be better explained by defective numerical mapping skills, which fits the access deficit hypothesis. The results presented here provide new evidence regarding the cognitive mechanisms underlying the different behavioural profiles identified in children with varying degrees of arithmetical difficulties.

High-Order Modulation Based on Deep Neural Network for Physical-Layer Network Coding

Physical-layer network coding (PNC) is an effective technique for enhancing wireless network throughput. Recently, it has been demonstrated that convolutional autoencoders effectively works in point-to-point communication systems, but their application to wireless relay networks is scarcely explored. In this letter, we propose a convolutional autoencoder for PNC in a two-way relay channel. The constellation mapping and demapping of symbols at each node are determined adaptively through a deep learning technique, such that the bit error rate performance is improved for high-order modulation. Simulation results verify the advantages of the proposed scheme over the conventional PNC scheme for various modulation types.

Huffman-Coded Sphere Shaping for Extended-Reach Single-Span Links

Huffman-coded sphere shaping (HCSS) is an algorithm for finite-length probabilistic constellation shaping, which provides nearly optimal energy efficiency at low implementation complexity. In this paper, we experimentally study the nonlinear performance of HCSS employing dual-polarization 64-ary quadrature amplitude modulation (DP-64QAM) in an extended-reach single-span link comprising 200 km of standard single-mode fiber (SSMF). We investigate the effects of shaping sequence length, dimensionality of symbol mapping, and shaping rate. We determine that the naive approach of Maxwell–Boltzmann distribution matching — which is optimal in the additive white Gaussian noise channel — provides a maximum achievable information rate (AIR) gain of 0.18 bits/4D-symbol with respect to uniform signaling at optimum launch power in the infinite length regime. Conversely, HCSS can achieve a gain of 0.37 bits/4D-symbol over uniform signaling using amplitude sequence length of 32, which may be implemented without multiplications, using integer comparison and addition operations only. Coded system performance, with a net data rate of approximately 425 Gb/s for both shaped and uniform inputs, is also analyzed.

Kanban Systems in the Context of the Enterprise Systems

Companies are under increasing pressure from customers, competitors, limited resources, etc. These conditions oblige companies to permanently improve their organizational structure and the activities of all system’s flows. The paper analyses the types of Kanban systems, in the broader context of the enterprise systems. The most important reference architectures were analysed (with the emphasis on the modules dedicated to flow description) and the standards that allow the activity modelling of a manufacturing enterprises. Starting from this context, the paper describes three models of Kanban systems that are specific to companies with different information systems development. Models are: Push production with withdrawal Kanban; Pull production with withdrawal Kanban and production Kanban triggered by Kanban board; Pull production with withdrawal Kanban and production Kanban triggered by the dispatch to the customers. The models are graphically described using Value Stream Map (VMS) symbols. These models are useful in the development and improvement of production flows.

Опыт подеревной инвентаризации и картографирования городских зеленых насаждений общего пользования

The article presents the results of research in the field of mapping the ecological state of city trees. Public green spaces are subject to constant and intense anthropogenic impact, which necessitates prompt and thorough monitoring and control of their state. However, the current methodology for the inventory of public green spaces is methodologically outdated long ago and does not take into account the modern techniques of remote sensing and GIS technologies in the field of obtaining information about natural objects. The article substantiates a new approach, which consists in using freely distributed remote sensing data to obtain information about the location and main ecological characteristics of trees that are part of urban public greening. A schematic diagram of the inventory of public green spaces using Earth remote sensing materials is presented. Requirements for map symbols used on digital maps of public green spaces are formulated. The symbols developed taking into account the existing system of symbols for large-scale topographic maps are given. The advantages and disadvantages of the developed system, and the corrections made to it, are noted. Fragments of created digital maps of public green spaces are presented. The landscaping of streets and highways in Novosibisk and Yakutsk and a park in Novosibirsk were assessed and mapped. The spatial position of city trees and the main types of disturbance in their condition (the presence of multi-stems, dead stems and branches, damaged crowns, etc.) were determined. The results showed the consistency of the proposed approach for operational environmental assessment and mapping of linear green spaces. When studying and mapping areal urban plantings, it is advisable to provide for an additional survey with the help of unmanned aerial vehicles to control thickened tall vegetation. Thus, the proposed approach minimizes field surveys of the territory, which significantly saves time and costs for an inventory of public green spaces.

基于不同约束条件的地图符号定义的数学定义

基于不同约束条件的地图符号定义的数学定义

Throughput Enhancement for the Joint Radar-Communication Systems Based on Cognitive Closed-Loop Design

The majority of the current dual function radar-communication (DFRC) systems are producing only an angle-dependent transmit beampattern (BP) and imposing a constraint for the communication receiver to be present within the sidelobe (SL) directions to decode the transmitted information. In this paper, an efficient angle-range dependent DFRC system is proposed using frequency diverse array (FDA)-multiple-input multiple-output (MIMO) configuration. We developed a closed-loop design that improves the tracking task of the system and permits a cognitive selection for an optimum signaling strategy towards the intended communication receiver during each scan. We used two information embedding schemes, a proposed amplitude phase shift keying (APSK) and phase-shift keying (PSK), that utilize either the magnitude ratios and/or phase shifts between the radar waveform pairs towards the communication direction. Hence, the communication link is maintained and the system throughput is enhanced. The simulation results verify that the communication performance is enhanced in terms of low symbol error rate (SER), secure information transmission, and increased throughput, while for radar applications the performance is improved in terms of target detection and parameter estimation. It also showed that the proposed symbol mapping APSK scheme provides a high data rate transmission compared to the existing SL-based information embedding schemes while preserving a low bit error rate (BER). Besides, the Cramer-Rao lower bounds (CRLB) for range and angle estimation and the signal-to-interference-noise ratio (SINR) for the proposed DFRC system are analyzed.

Using different mapping techniques and GIS programs in the analysis and visualisation of mental maps

Abstract The paper presents the review of mapping techniques applied in research using mental maps. The review covers both evaluative and structural mapping. The choice of a method is influenced by the level of freedom given to the respondents while creating sketch maps. It is also highly affected by the area of a given region, scale used in the research and limitations of mapping techniques in GIS software. For large scale maps created in GIS software, it is possible to use quantitative methods, i.e. proportional symbol maps or quantitative signature symbols. Using multiple complementary mapping techniques allows to draw the most comprehensive conclusions in the analyses of perception of a given space in the society.

Galois symbol maps for abelian varieties over a $p$-adic field

We study the Galois symbol map associated to the multiplicative group and an abelian variety which has good ordinary reduction over a $p$-adic field. As a byproduct, one can calculate the “class group” in the sense of the class field theory for curves ove

Hybrid Approach for Solving the Q3AP

Metaheuristics algorithms are competitive methods for solving assignment problems. This paper reports on nature inspired algorithms approach which is the particle swarm optimization (PSO) method hybrid with a local search (LS) algorithm for solving the quadratic three-dimensional assignment problem (Q3AP) where population-based metaheuristics like PSO or GA failed to solve. Q3AP is one of the combinatorial problems proven to be NP-Hard. It is an extension of the quadratic assignment problem (QAP). Solving the Q3AP consists of finding an optimal symbol mapping over two vectors, whereas solving the QAP consists of finding an optimal symbol mapping over one vector only. The authors tested the proposed hybrid algorithm on many instances where some of them haven't been used in the previous works for solving Q3AP. The results show that compared with the PSO algorithm and the genetic algorithm (GA), the proposed hybrid PSO-ILS(TS) algorithm is promising for finding the optimal/best known solution.

Model and Verification of Medical English Machine Translation Based on Optimized Generalized Likelihood Ratio Algorithm

Phrase identification plays an important role in medical English machine translation. However, the phrases in medical English are complicated in internal structure and semantic relationship, which hinders the identification of machine translation and thus affects the accuracy of translation results. With the aim of breaking through the bottleneck of machine translation in medical field, this paper designed a machine translation model based on the optimized generalized likelihood ratio (GLR) algorithm. Specifically, the model in question established a medical phrase corpus of 250,000 English and 280,000 Chinese words, applied the symbol mapping function to the identification of the phrase’s part of speech, and employed the syntactic function of the multioutput analysis table structure to correct the structural ambiguity in the identification of the part of speech, eventually obtaining the final identification result. According to the comprehensive verification, the translation model employing the optimized GLR algorithm was seen to improve the speed, accuracy, and update performance of machine translation and was seen to be more suitable for machine translation in medical field, therefore providing a new perspective for the employment of medical machine translation.

Crime mapping features

In this paper tools, organization and tactics of crime mapping are analyzed. The directions of application of mapping for maintenance of public safety and order, in criminal intelligence process, etc. are outlined. The domestic experience of mapping is briefly analyzed. The main goals that are achieved with the use of mapping are defined. Features of visualization of criminogenic cells are revealed. Pin mapping features (when points which symbolize a certain event are placed on the map on the corresponding coordinates) are outlined. Kernel density mapping is described, which makes it much easier to detect criminogenic foci, as hot-spot maps clearly reflect the concentration of certain events in the region. A method of mapping using proportional symbol mapping is disclosed when the increase in the size of the symbol denoting a point on the map is proportional to the increase in the number of events or other parameters at these coordinates. The building of geographical profiles of criminals is briefly described. The theoretical basis of mapping for the prediction of crimes is outlined. Prediction strategies based on equations and machine calculations and actuarial strategies based on expertise and clinical strategy are analyzed. Considerations are given to the appropriateness of applying appropriate strategies in different countries. The phenomenon of near repeat patterns is studied. Some software solutions for the implementation of the tasks of mapping criminal manifestations and the use of artificial intelligence systems for this purpose are described. Examples are given. It is noted that the use of cartography to prevent and predict crimes in Ukraine is in its infancy. Some solutions are proposed that could improve the situation in the field of crime mapping in Ukraine.

Form Follows Content: An Empirical Study on Symbol-Content (In)Congruences in Thematic Maps

Through signs and symbols, maps represent geographic space in a generalized and abstracted way. Cartographic research is, therefore, concerned with establishing a mutually shared set of signs and semiotic rules to communicate geospatial information successfully. While cartographers generally strive for cognitively congruent maps, empirical research has only started to explore the different facets and levels of correspondences between external cartographic representations and processes of human cognition. This research, therefore, draws attention to the principle of contextual congruence to study the correspondences between shape symbols and different geospatial content. An empirical study was carried out to explore the (in)congruence of cartographic point symbols with respect to positive, neutral, and negative geospatial topics in monothematic maps. In an online survey, 72 thematic maps (i.e., 12 map topics × 6 symbols) were evaluated by 116 participants in a between-groups design. The point symbols comprised five symmetric shapes (i.e., Circle, Triangle, Square, Rhomb, Star) and one Asymmetric Star shape. The study revealed detailed symbol-content congruences for each map topic as well as on an aggregated level, i.e., by positive, neutral, and negative topic clusters. Asymmetric Star symbols generally showed to be highly incongruent with positive and neutral topics, while highly congruent with negative map topics. Symmetric shapes, on the other hand, emerged to be of high congruence with positive and neutral map topics, whilst incongruent with negative topics. As the meaning of point symbols showed to be susceptible to context, the findings lead to the conclusion that cognitively congruent maps require profound context-specific considerations when designing and employing map symbols.

Sufi Symbol as Gap, Metaphor as Clue

Abstract This article introduces an approach to analyzing the way in which figurative language interfaces with cognitive, cultural, and spiritual experience in the symbols employed by the Sufis to express their love of God. It relies on the Cognitive Linguistic Approach to reveal the relationship between the Sufis’ thoughts about God, secular language of love, and the idea of divine love. Through a case study analysis of the symbols of love in Ibn ʿArabī’s poetry, the two chief undertakings here are: first, to argue that thoughts and feelings of human love inspired the Sufis to express their ideas about their experience of divine love through secular symbols that create gaps of indeterminacy in their poems, and second, to explain, using Conceptual Metaphor Theory, how these gaps can be closed through mappings of the Sufi symbols, as parts of the target domain of divine love, onto the source domain of secular love.