The inclusion of landmarks within navigation systems: industry requirements

Research has shown that the usability, safety and acceptability of navigation systems can be enhanced by the use of landmarks within guidance instructions. ‘Landmarks’, refer to buildings, street furniture and built aspects of the environment. The REGIONAL project aims to enable the inclusion of landmarks within future navigation systems by gaining a thorough understanding of the driver requirements for this information and the commercial enablers and barriers to their inclusion within databases, navigation software and end products. This deliverable tackles the latter issue of the requirements of industry

Applications of Virtual Reality

Information Technology is growing rapidly. With the birth of high-resolution graphics, high-speed computing and user interaction devices Virtual Reality has emerged as a major new technology in the mid 90es, last century. Virtual Reality technology is currently used in a broad range of applications. The best known are games, movies, simulations, therapy. From a manufacturing standpoint, there are some attractive applications including training, education, collaborative work and learning. This book provides an up-to-date discussion of the current research in Virtual Reality and its applications. It describes the current Virtual Reality state-of-the-art and points out many areas where there is still work to be done. We have chosen certain areas to cover in this book, which we believe will have potential significant impact on Virtual Reality and its applications. This book provides a definitive resource for wide variety of people including academicians, designers, developers, educators, engineers, practitioners, researchers, and graduate students

Seamless connectivity:investigating implementation challenges of multibroker MQTT platform for smart environmental monitoring

Abstract. This thesis explores the performance and efficiency of MQTT-based infrastructure Internet of Things (IoT) sensor networks for smart environment. The study focuses on the impact of network latency and broker switching in distributed multi-broker MQTT platforms. The research involves three case studies: a cloud-based multi-broker deployment, a Local Area Network (LAN)-based multi-broker deployment, and a multi-layer LAN network-based multi-broker deployment. The research is guided by three objectives: quantifying and analyzing the latency of multi-broker MQTT platforms; investigating the benefits of distributed brokers for edge users; and assessing the impact of switching latency at applications. This thesis ultimately seeks to answer three key questions related to network and switching latency, the merits of distributed brokers, and the influence of switching latency on the reliability of end-user applications

Retrieving Landmark Salience Based on Wikipedia: An Integrated Ranking Model

Landmarks are important for assisting in wayfinding and navigation and for enriching user experience. Although many user-generated geotagged sources exist, landmark entities are still mostly retrieved from authoritative geographic sources. Wikipedia, the world’s largest free encyclopedia, stores geotagged information on many geospatial entities, including a very large and well-founded volume of landmark information. However, not all Wikipedia geotagged landmark entities can be considered valuable and instructive. This research introduces an integrated ranking model for mining landmarks from Wikipedia predicated on estimating and weighting their salience. Other than location, the model is based on the entries’ category and attributed data. Preliminary ranking is formulated on the basis of three spatial descriptors associated with landmark salience, namely permanence, visibility, and uniqueness. This ranking is integrated with a score derived from a set of numerical attributes that are associated with public interest in the Wikipedia page―including the number of redirects and the date of the latest edit. The methodology is comparatively evaluated for various areas in different cities. Results show that the developed integrated ranking model is robust in identifying landmark salience, paving the way for incorporation of Wikipedia’s content into navigation systems

Functionality-Driven Musculature Retargeting

We present a novel retargeting algorithm that transfers the musculature of a reference anatomical model to new bodies with different sizes, body proportions, muscle capability, and joint range of motion while preserving the functionality of the original musculature as closely as possible. The geometric configuration and physiological parameters of musculotendon units are estimated and optimized to adapt to new bodies. The range of motion around joints is estimated from a motion capture dataset and edited further for individual models. The retargeted model is simulation-ready, so we can physically simulate muscle-actuated motor skills with the model. Our system is capable of generating a wide variety of anatomical bodies that can be simulated to walk, run, jump and dance while maintaining balance under gravity. We will also demonstrate the construction of individualized musculoskeletal models from bi-planar X-ray images and medical examinations.Comment: 15 pages, 20 figure

A skewness-aware matrix factorization approach for mesh-structured cloud services

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Online cloud services need to fulfill clients' requests scalably and fast. State-of-the-art cloud services are increasingly deployed as a distributed service mesh. Service to service communication is frequent in the mesh. Unfortunately, problematic events may occur between any pair of nodes in the mesh, therefore, it is vital to maximize the network visibility. A state-of-the-art approach is to model pairwise RTTs based on a latent factor model represented as a low-rank matrix factorization. A latent factor corresponds to a rank-1 component in the factorization model, and is shared by all node pairs. However, different node pairs usually experience a skewed set of hidden factors, which should be fully considered in the model. In this paper, we propose a skewness-aware matrix factorization method named SMF. We decompose the matrix factorization into basic units of rank-one latent factors, and progressively combine rank-one factors for different node pairs. We present a unifying framework to automatically and adaptively select the rank-one factors for each node pair, which not only preserves the low rankness of the matrix model, but also adapts to skewed network latency distributions. Over real-world RTT data sets, SMF significantly improves the relative error by a factor of 0.2 x to 10 x, converges fast and stably, and compactly captures fine-grained local and global network latency structures.Peer ReviewedPostprint (author's final draft

Evaluation of Morphed Human Body Models for Diverse Occupant Safety Analysis

Female, obese, and elderly occupants are at increased risk of injury in vehicle accidents. Human Body Models (HBMs) are used to represent the human anatomy and to study injury mechanisms in mathematical crash test simulations. HBM morphing methods can adjust the anatomical geometry of existing HBMs, enabling HBMs to represent the diverse occupant population, beyond the traditionally considered body sizes.The aims of this thesis were to define and select a diverse population of occupants. Thereafter, select an HBM morphing tool for morphing of the SAFER HBM to individuals in this population; Finally, this population of morphed HBMs was to be validated.The defined target population to be represented by HBMs in occupant injury risk evaluations included individuals of both sexes. The selection was based on occupant injury risks and biomechanical risk factors. The male and female sub-populations include individuals of a wide range of statures and weights and ages from 20 to 80 years. A sample of 27 female and 27 males were selected as the initial population.The parametric HBM morphing tool, developed by University of Michigan Transportation Research Institute, was selected for morphing the SAFER HBM. Sled test results from individual male and female Post Mortem Human Subjects (PMHSs) of a wide range of body sizes were used for validation of morphed HBMs. The SAFER HBM was parametrically morphed to each individual PMHS. Predictions from both morphed and the baseline SAFER HBM were collected in reconstructions of the PMHS tests. HBM kinematics, chest deflections and interaction forces were compared to corresponding test results using CORA cross-correlation rating. Comparison of morphed and baseline HBM results showed that correlation rating was not consistently improved for morphed HBMs. For large, obese, and small female subjects in frontal impacts, and in lateral impacts, morphed HBMs were stiffer than the corresponding PMHSs. \ua0To improve morphed SAFER HBM predictions for diverse occupants, future work will identify and mitigate the sources of the stiff responses through model updates. Sex and age dependent biomechanical properties, as available in literature will be included. Biofidelity criteria for morphed HBMs will be defined and with morphed HBMs meeting these criteria, protective principles increasing the protection of all occupants will be investigated

Advanced Geolocation Techniques and Geopolitical Integration for a Resilient Internet Infrastructure

Governments and institutions are alarmed by the number of recent incidents that have compromised the confidentiality, availability, and integrity of critical infrastructure and services, and exposed the fragility of the Internet architecture. BGP offers limited performance and security mechanisms to protect the integrity of exchanged routing information and to provide authentication and authorisation of the advertised IP address space. Instead, each AS operator implicitly trusts that the routing information exchanged through BGP is accurate. As a result, the Internet backbone is potentially exposed. To better inform BGP administrators when choosing their routing paths, this thesis seeks to improve and advance current geolocation techniques, integrating geopolitical considerations into IP routing and introducing new IPv4 and IPv6 tools. By examining three distinct but interrelated aspects - improving current IP geolocation methods - enabling data routing for end users and network administrators - introducing a new IPv6 method of IP geolocation - this research aims to contribute to a more secure, efficient, and geographically aware Internet infrastructure. The thesis begins with an investigation of current techniques for geolocating hosts using passive, active, and hybrid methods. This is followed by a survey of the fundamental problems that IP geolocation techniques must address. The survey points to the obvious difficulties in using Delay-Distance models and suggests that the use of Return-Trip Times can lead to highly misleading results. The thesis builds on this current work by introducing new procedures and methodologies to create fine-grained multilayer maps of the structure of the Internet. Next, the thesis explores the additional benefits that IPv6 can bring to IP geolocation. IPv6 introduces a significant evolution in the area of Internet Protocols which resolves many of the issues with the limitations of IPv4 and provides an improved framework for the future of the Internet. The concept of extension headers is a feature that enhances the IPv6 protocol’s flexibility and functionality, and it is key among these advancements. The thesis conceptualises the design of a new IPv6 extension header, which aims to incorporate a geopolitical dimension into each data packet, optionally allowing network paths to be dynamically adjusted based on country codes of transit networks. The thesis builds on this tool by developing a new IPv6 tool to map network infrastructure, aiming to surpass current methodologies in accuracy, comprehensiveness, and utility. The tool provides a more precise and comprehensive mapping of the network’s topology, including geolocation data and peer connections of network nodes. The thesis discusses how we can build on these foundational tools by combining them to produce new fault-finding techniques and a robust network analysis methodology. These methods and tools will benefit BGP administrators by informing them of better routing decisions, helping to avoid possible single points of failure, and enhancing overall network resilience. Finally, we discuss some limitations of the proposed approach and summarise some next steps needed towards accurate and complete Internet infrastructure ma

DYNAMICS OF COLLABORATIVE NAVIGATION AND APPLYING DATA DRIVEN METHODS TO IMPROVE PEDESTRIAN NAVIGATION INSTRUCTIONS AT DECISION POINTS FOR PEOPLE OF VARYING SPATIAL APTITUDES

Cognitive Geography seeks to understand individual decision-making variations based on fundamental cognitive differences between people of varying spatial aptitudes. Understanding fundamental behavioral discrepancies among individuals is an important step to improve navigation algorithms and the overall travel experience. Contemporary navigation aids, although helpful in providing turn-by-turn directions, lack important capabilities to distinguish decision points for their features and importance. Existing systems lack the ability to generate landmark or decision point based instructions using real-time or crowd sourced data. Systems cannot customize personalized instructions for individuals based on inherent spatial ability, travel history, or situations. This dissertation presents a novel experimental setup to examine simultaneous wayfinding behavior for people of varying spatial abilities. This study reveals discrepancies in the information processing, landmark preference and spatial information communication among groups possessing differing abilities. Empirical data is used to validate computational salience techniques that endeavor to predict the difficulty of decision point use from the structure of the routes. Outlink score and outflux score, two meta-algorithms that derive secondary scores from existing metrics of network analysis, are explored. These two algorithms approximate human cognitive variation in navigation by analyzing neighboring and directional effect properties of decision point nodes within a routing network. The results are validated by a human wayfinding experiment, results show that these metrics generally improve the prediction of errors. In addition, a model of personalized weighting for users\u27 characteristics is derived from a SVMrank machine learning method. Such a system can effectively rank decision point difficulty based on user behavior and derive weighted models for navigators that reflect their individual tendencies. The weights reflect certain characteristics of groups. Such models can serve as personal travel profiles, and potentially be used to complement sense-of-direction surveys in classifying wayfinders. A prototype with augmented instructions for pedestrian navigation is created and tested, with particular focus on investigating how augmented instructions at particular decision points affect spatial learning. The results demonstrate that survey knowledge acquisition is improved for people with low spatial ability while decreased for people of high spatial ability. Finally, contributions are summarized, conclusions are provided, and future implications are discussed