Automated Mapping System Research Articles

Orientation precision of TEM-based orientation mapping techniques

Automatic orientation mapping is an important addition to standard capabilities of conventional transmission electron microscopy (TEM) as it facilitates investigation of crystalline materials. A number of different such mapping systems have been implemented. One of their crucial characteristics is the orientation resolution. The precision in determination of orientations and misorientations reached in practice by TEM-based automatic mapping systems is the main subject of the paper. The analysis is focused on two methods: first, using spot diffraction patterns and 'template matching', and second, using Kikuchi patterns and detection of reflections. In simple terms, for typical mapping conditions, their precisions in orientation determination with the confidence of 95% are, respectively, 1.1 ° and 0.3 °. The results are illustrated by example maps of cellular structure in deformed Al, the case for which high orientation sensitivity matters. For more direct comparison, a novel approach to mapping is used: the same patterns are solved by each of the two methods. Proceeding from a classification of the mapping systems, the obtained results may serve as indicators of precisions of other TEM-based orientation mapping methods. The findings are of significance for selection of methods adequate to investigated materials.

Mapping ideas from cyberspace to realspace: visualizing the spatial context of keywords from web page search results

We introduce a new method for visualizing and analyzing information landscapes of ideas and events posted on public web pages through customized web-search engines and keywords. This research integrates GIScience and web-search engines to track and analyze public web pages and their web contents with associated spatial relationships. Web pages searched by clusters of keywords were mapped with real-world coordinates (by geolocating their Internet Protocol addresses). The resulting maps represent web information landscapes consisting of hundreds of populated web pages searched by selected keywords. By creating a Spatial Web Automatic Reasoning and Mapping System prototype, researchers can visualize the spread of web pages associated with specific keywords, concepts, ideas, or news over time and space. These maps may reveal important spatial relationships and spatial context associated with selected keywords. This approach may provide a new research direction for geographers to study the diffusion of human thought and ideas. A better understanding of the spatial and temporal dynamics of the ‘collective thinking of human beings’ over the Internet may help us understand various innovation diffusion processes, human behaviors, and social movements around the world.

Validation of a novel algorithm for quantification of the percentage of signal fractionation in atrial fibrillation

Catheter ablation for paroxysmal atrial fibrillation (AF) is rapidly becoming a standard practice. There is literature to support that catheter ablation of persistent AF requires additional 'substrate modification'. In clinical practice, operators rely on automated fractionation maps created by three-dimensional anatomic mapping systems to rapidly assess complex 'fractionated' signals (CFAE). These systems use differing algorithms to automate the process. The agreement between operators and contemporary algorithms has not been examined. We sought to assess the agreement between operators and a novel method of quantification calculating percentage fractionation (PF). Expert opinion on 80 atrial electrogram 4 s signals of varying levels of activity were gathered and pooled for comparison. Twelve independent experts visually quantified the signal fractionation and offered a threshold level for ablation. We developed an algorithm to find sites with high continuous electrical activity, or high PF. Correlation between experts and PF was 0.78 [P < 0.01, 95% confidence interval (CI) (0.68-0.86)]. Receiver operating characteristics curve sensitivity and specificity for PF were 0.7727 and 0.8103 at the optimal cut-off point of 58.45 PF with area under curve 0.89 CI (0.80-0.99). The PF statistic represents a more robust and intuitive measure to represent fractionated atrial activity; importantly it demonstrates excellent agreement with expert users and presents a new standard for algorithm assessment. Use of a PF statistic should be considered in automated mapping systems.

Comparing interactive and automated mapping systems for supporting fisheries enforcement activities—a case study on vessel monitoring systems (VMS)

The conservation of wild fisheries resources in the face of an ever-increasing world demand for seafood requires the use of a number of management tools, including no-take zones, and gear, species, and temporal restrictions. One way of enforcing some of these regulations is through the use of Vessel Monitoring System (VMS) data that provides enforcement officers with the position of fishing vessels in the management area. The increasing volume of movement data collected using VMS calls for new methods that could help analysts extract useful knowledge from these large data sets. Various approaches have been proposed for visualizing and exploring movement data and detecting patterns within these data, but those approaches have generally not been tested in a real-world context or compared together, making their actual usability and utility unclear. This paper describes, compares, and assesses three such approaches in the context of fisheries enforcement: an existing system used for fisheries enforcement operations in Canada (VUE), a novel Hybrid Spatio-temporal Filtering (HSF) system developed by the authors, and an automated Behavioural Change Point Analysis (BCPA) system. A field trial was conducted with experienced fisheries enforcement officers to compare and contrast the benefits and drawbacks of the three approaches. While all three presented advantages and disadvantages, the interactivity of VUE and HSF were identified as desirable features, as they provide analysts with more control over the data, while allowing flexible data exploration. BCPA, while providing an automated approach to the data analysis, was pointed out as being too much of a “black box”, causing unease among the experts who require a level of transparency similar to that of legally admissible evidence. In the end, the experts suggested that the best approach would be to merge the analytical power of their existing VUE system with the exploratory power of the HSF system. This study provides insight into the value of using interactive mapping and filtering approaches in support of data analysis in the context of fisheries enforcement.

Design and Realization of Automatic Mapping System for Borehole Data

Drawing geologic maps (profile\plane\column map) are high-workload and low-accuracy task. Based on a series of research on previous study, system architecture, database and key algorithm, an auto-mapping system has been developed by interacting with MS SQL database, the framework of MAPGIS and visual programming tools. The actual-measured data in ZhiJiaDi district, Shanxi Province, China is chosen as a case study to demonstrate the validity and capability of the system. The test results compared with the manual-mapping one in GEMD method shows that the key algorithm are reliable, and this new system not only provide a user friendly interface, but also have the ability to satisfy requirement on the geologic maps with high accuracy, efficiency and conveniences.The geologic maps (profile\plane\column map) are the most basic forms of expression for the geological content, which play an important role in guidance of geological exploration, metallogenic prediction and decision-making [1]. In China, various maps are manually drawn in MAPGIS platform according to the paper map provided by the geologists, which results in large workload, complicated process and inaccuracy. It seriously affects the quality of work for computing of resources amount, metallogenic prediction and mine design, etc. Therefore, research on a new automatic mapping system which is convenient, efficient and accurate becomes the urgent need for domestic mineral system.

Design Modeling and Solving Implementation for Product Conceptual Design in Quality Function Deployment

Considering the process of research in conceptual design, a framework model of Function-Behaviour-structure was put forward, and QFD was an effective tool for function conversion. Then a mixed solving technology combining case-based reasoning and behaviour solving reasoning was discussed to achieve design mapping. Finally, an automatic synthesis mapping system was developed and the conceptual design of clam collector was given as an example. Application results demonstrated that the proposed method was feasible.

Cartographic Support for the 2010 Decennial Census of the United States

As this article is published, the U.S. Census Bureau is completing work for the twenty third decennial census of the United States. Once again, the MAF/TIGER system served as the geospatial infrastructure supporting numerous census operations and data collection, tabulation, and dissemination activities. From data collection to data dissemination we trace the recent activities of the 2010 Decennial Census of the United States to illustrate the role maps and geospatial data play in an increasing variety of public and private sector activities across the nation. To ensure a successful 2010 Census, millions of maps had to be created. This article will give an overview of the automated mapping system designed to create these maps. This includes a discussion about associated software needed and the variety of map types that were developed. Finally, future map production and geospatial activities at the Census Bureau will be discussed.

Towards ontology alignment of e-business standards using OWL and F-logic

In this paper a mapping of Core Components specification based e-business standards to an ontology is presented and a framework for ontology alignment based on F-logic is proposed. The well accepted Web Ontology Language (OWL) is used for ontology development. In order to preserve the existing hierarchy of the standards, an emphasis is put on the mapping of Core Components elements to specific constructs in OWL. The main purpose of developing an e-business standards ontology is to create a foundation for an automated mapping system that would be able to convert concepts from various standards in an independent fashion. The practical applicability and verification of the presented mappings is tested on the mapping of Universal Business Language version 2.0 and Cross Industry Invoice version 2.0 to OWL. Additionally we propose a 4-rules class alignment technique which is formalised in F-logic a deductive object-oriented rule-based language for ontology management.

학술논문의 참고문헌 자동매핑 방법에 관한 연구

With the advanced learning and the diversity of topics, researchers on each area keenly feel the need of precise and a quick discovery of required information at any time. This study presents a way of constructing the automatic mapping system that can compare and analyze duplicated data and that describes the result by building an effective reference extraction method and another way of correcting the wrong form of used Chinese characters with Traditional Korean Medicine dictionary. With this innovation, data duplication on references and Chinese characters errors can be fixed. Under the situation that a number of references of newly published papers that can continuously be extracted.

ONTOGRATE: TOWARDS AUTOMATIC INTEGRATION FOR RELATIONAL DATABASES AND THE SEMANTIC WEB THROUGH AN ONTOLOGY-BASED FRAMEWORK

Integrating existing relational databases with ontology-based systems is among the important research problems for the Semantic Web. We have designed a comprehensive framework called OntoGrate which combines a highly automatic mapping system, a logic inference engine, and several syntax wrappers that inter-operate with consistent semantics to answer ontology-based queries using the data from heterogeneous databases. There are several major contributions of our OntoGrate research: (i) we designed an ontology-based framework that provides a unified semantics for mapping discovery and query translation by transforming database schemas to Semantic Web ontologies; (ii) we developed a highly automatic ontology mapping system which leverages object reconciliation and multi-relational data mining techniques; (iii) we developed an inference-based query translation algorithm and several syntax wrappers which can translate queries and answers between relational databases and the Semantic Web. The testing results of our implemented OntoGrate system in different domains show that the large amount of data in relational databases can be directly utilized for answering Semantic Web queries rather than first converting all relational data into RDF or OWL.

Studies on high order mode of bell-shaped prototype cavities**Supported by Science and Technology Commission of Shanghai Municipality (026505027, 036505011)

Aluminium and copper prototype cavities were designed to study higher order modes (HOM). An automatic field mapping system was developed with LabVIEW to measure the radiofrequency (RF) characteristics, such as resonant frequency, Q-value, shunt impedance and electromagnetic field distribution of the higher-order modes in a model RF cavity. Two kinds of the bell-shaped cavities were measured using the field mapping system, their frequencies are 1.5 GHz and 800 MHz respectively. The fields' distributions of the monopole modes and dipole modes, as well the R/Q values, were measured.

Autonomous vision-based robotic exploration and mapping using hybrid maps and particle filters

This paper addresses the problem of exploring and mapping an unknown environment using a robot equipped with a stereo vision sensor. The main contribution of our work is a fully automatic mapping system that operates without the use of active range sensors (such as laser or sonic transducers), can operate on-line and can consistently produce accurate maps of large-scale environments. Our approach implements a Rao-Blackwellised particle filter (RBPF) to solve the simultaneous localization and mapping problem and uses efficient data structures for real-time data association, mapping, and spatial reasoning. We employ a hybrid map representation that infers 3D point landmarks from image features to achieve precise localization, coupled with occupancy grids for safe navigation. We demonstrate two exploration approaches, one based on a greedy strategy and one based on an iteratively deepening strategy. This paper describes our framework and implementation, and presents our exploration method, and experimental results illustrating the functionality of the system.

Designing and Implementing Software Components for an Automated Mapping System

This paper summarizes a research project that examined the usefulness of Object-oriented Programming (OOP) and the Unified Modelling Language (UML) in producing well-designed software. This leads to cost effective implementation of new automated mapping tools as they emerge. In this project, software for an automated mapping system was designed, implemented, and successfully tested. The system consists of the following subsystems: 1) image acquisition, 2) positioning, 3) image point referencing, 4) spatial object extraction, and, 5) visualization. This paper addresses parts of this work (the first 3 subsystems) in order to demonstrate the flexibility of this approach to software design.

Applications of the Near-Field Techniques in EMC Investigations

A completely automatic near-field mapping system has been developed within the Research Institute for Electronic Embedded Systems (IRSEEM) in order to determine the electromagnetic field created by electronic systems and components. This test bench uses a 3-D positioning system of the probe to make accurate measurements. This paper presents some applications of the near-field techniques in EMC investigations. In the first part, near-field measurements are used to locate precisely the electromagnetic sources of a limiter device. In the second part, we present an equivalent model of the radiated emission of an integrated circuit. In the last part, the near-field test bench is used to characterize faults in a cable.

An application of Spartan spatial random fields in environmental mapping: focus on automatic mapping capabilities

This paper investigates the potential of Spartan spatial random fields (SSRFs) in real-time mapping applications. The data set that we study focuses on the distribution of daily gamma dose rates over part of Germany. Our goal is to determine a Spartan spatial model from the data, and then use it to generate “predictive” maps of the radioactivity. In the SSRF framework, the spatial dependence is determined from sample functions that focus on short-range correlations. A recently formulated SSRF predictor is used to derive isolevel contour maps of the dose rates. The SSRF predictor is explicit. Moreover, the adjustments that it requires by the user are reduced compared to classical geostatistical methods. These features present clear advantages for an automatic mapping system. The performance of the SSRF predictor is evaluated by means of various cross-validation measures. The values of the performance measures are similar to those obtained by classical geostatistical methods. Application of the SSRF method to data that simulate a radioactivity release scenario is also discussed. Hot spots are detected and removed using a heuristic method. The extreme values that appear in the path of the simulated plume are not captured by the currently used Spartan spatial model. Modeling of the processes leading to extreme values can enhance the predictive capabilities of the spatial model, by incorporating physical information.

Towards generic real-time mapping algorithms for environmental monitoring and emergency detection

Real-time analysis of data reported by environmental monitoring networks poses a number of challenges, one of which is the conversion of point measurements of phenomena that display some spatial dependence into maps. This is the case for the many variables that cannot be monitored efficiently over large regions by satellites. Environmental pollutants, radiation levels, rainfall fields and seismic activity are but a few of these variables that are usually interpolated for the production of maps. These maps will then further serve as an essential support for decision-making. Ideally, in order to allow real-time assessments and minimize human intervention in case of hazards and emergencies that are frequently linked to the above mentioned variables (e.g. air pollution peaks, nuclear accidents, flash-floods, earthquakes), these maps should be established in near real time and thus automatically. The ability of real-time mapping systems running in the routine mode to be able to cope with extreme events is not straightforward, and few systems are today used automatically for both monitoring the environment and triggering early warnings in case of necessity. Alternatively, adopting a decision-centered view of environmental monitoring and mapping systems allows us to re-formulate their final objective as a classification problem that consists of discriminating routine against emergency conditions, or background information against outliers. It is the purpose of this paper to give an overview of the main challenges for developing and evaluating automatic mapping systems for critical environmental variables, as well as to discuss steps toward the development of generic real-time mapping algorithms.

Automatic mapping in emergency: a geostatistical perspective

In the case of a severe nuclear accident, radionuclides may be released into the atmosphere and contaminate large areas. Radiological maps are obtained after converting local measurements into continuous information in space. Ideally, the mapping process should be fully automatic and provide information in real time. This paper is presenting the results obtained from two statistical exercises that addressed the issue of automating the spatial interpolation step both in routine and emergency situations. The first exercise addressed mainly the current state-of-the-art of spatial interpolation and explored the impact of human factors on the results obtained. The second exercise was dealing specifically with the automation issue. To further address the response of these mapping algorithms in emergency situations, simulated data have also been used to explore the impact of extreme values on the process. It is shown that, independently of the choice of algorithms, many obstacles still remain before we can rely on fully automatic mapping systems in emergency situations, especially during the early and critical stages of an accident when measurements on the contamination are sparse.

Unmanned Helicopter borne 3D Mapping System based on Multi-Sensor Integration

In this research, we propose an automatic 3D mapping system based on multi-sensor integration that is a combination of IMU (FOG), GPS, laser scanner and digital camera. An automatic mapping means that direct geo-referencing is achieved automatically without any ground control points, which accurately measures ground coordinate values. 3D model is reconstructed by laser scanner as 3D point cloud data, while texture is acquired by digital camera from the same platform simultaneously. The accurate trajectory of the platform with attitude changes is determined through the integration of GPS/IMU and digital camera. All the measurement tools are loaded on the unmanned helicopter, RPH2, which is made by Fuji Heavy Industries Ltd. A method of 3D mapping by integrating all the sensors from an unmanned helicopter is focused in this paper.

An integrated system for automatic road mapping from high-resolution multi-spectral satellite imagery by information fusion

Here we present an integrated system for automatic mapping of urban and suburban roads from high-resolution satellite imagery. Road extraction strategies can be enriched and improved by multi-source data fusion. Fusion can occur by combining road extraction results from different image sources, or by applying multiple detectors to a single source image and then fusing the multi-detector road extraction results. Our proposed system models roads differently for urban vs. suburban environments. In suburban areas, roads are modeled as curvilinear and homogeneous regions with nearly constant width. Roads are extracted by integrating the output of two road detectors followed by a road tracker. The first detector is based on fine-scale image segmentation and grouping where road centerlines are identified and extracted using shape and structure information from the segments. This detector generates a very reliable road extraction but is incomplete as many road segments are not captured. A multi-scale curvilinear structure detector based on differential geometry is used as a complementary detector. This detector utilizes a fuzzy decision algorithm based on a 1D road profile model. The final suburban road centerlines are generated by integrating the results from the two detectors using an optimum path search algorithm. In many dense urban areas in the US, road networks are composed primarily of straight lines that form a grid structure. Here we use directional morphological filtering to mask out dark and bright structures shorter than a city block. We then use a spatial signature weighted Hough transform to generate a road grid hypothesis. The modified Hough transform incorporates spatial information derived from surrounding image pixels and can be applied to multi-spectral images. Each piece of the hypothesized road grid is then verified using homogeneity, shape, and vegetation information from the local surrounding area. Missing pieces of the road network are added using a road tracker based on profile matching. The integrated road extraction system based on the fusion of multi-detector results is tested using IKONOS multi-spectral imagery of the City of Columbia, Missouri. Evaluation of the extracted road networks using representative test sites show completeness values that range between 70% and 86% and correctness values that range between 70% and 92%.

An Automated System for Multi-Scale Vegetation Mapping

The geographical distribution of vegetation is commonly represented on maps. However, some map users require very detailed information down to species at individual levels, while others are satisfied with generalized data on a class or community. Representation of vegetation data at different levels of abstraction is required to satisfy the requirements of different applications. It is desirable to have an automated mapping system so that smaller-scale representations of vegetation data can be derived efficiently from larger-scale representation. This article presents the design philosophy of a prototype automated system for vegetation mapping using geo-information technology. We devised a user interface based on an extension of existing ArcMap applications with the integration of ArcObjects and Visual Basic customization. The Vegetation Mapping System (VMS) is developed with five windows of user interface: the raw data and code pages for source map data input, and the classification, tolerance, and scale pages for output at a user-desired scale. This system avoids the frequent problem of revising vegetation databases at different scales. It is different from other general mapping systems in that vegetation characteristics and spatial pattern are taken into consideration.