Shortest path and vehicle trajectory aided map-matching for low frequency GPS data

Map-matching algorithms that utilise road segment connectivity along with other data (i.e.position, speed and heading) in the process of map-matching are normally suitable for high frequency (1 Hz or higher) positioning data from GPS. While applying such map-matching algorithms to low frequency data (such as data from a fleet of private cars, buses or light duty vehicles or smartphones), the performance of these algorithms reduces to in the region of 70% in terms of correct link identification, especially in urban and sub-urban road networks. This level of performance may be insufficient for some real-time Intelligent Transport System (ITS) applications and services such as estimating link travel time and speed from low frequency GPS data. Therefore, this paper develops a new weight-based shortest path and vehicle trajectory aided map-matching (stMM) algorithm that enhances the map-matching of low frequency positioning data on a road map. The well-known A* search algorithm is employed to derive the shortest path between two points while taking into account both link connectivity and turn restrictions at junctions. In the developed stMM algorithm, two additional weights related to the shortest path and vehicle trajectory are considered: one shortest path-based weight is related to the distance along the shortest path and the distance along the vehicle trajectory, while the other is associated with the heading difference of the vehicle trajectory. The developed stMM algorithm is tested using a series of real-world datasets of varying frequencies (i.e. 1 s, 5 s, 30 s, 60 s sampling intervals). A high-accuracy integrated navigation system (a high-grade inertial navigation system and a carrier-phase GPS receiver) is used to measure the accuracy of the developed algorithm. The results suggest that the algorithm identifies 98.9% of the links correctly for every 30 s GPS data. Omitting the information from the shortest path and vehicle trajectory, the accuracy of the algorithm reduces to about 73% in terms of correct link identification. The algorithm can process on average 50 positioning fixes per second making it suitable for real-time ITS applications and services.

Maintaining our rage: Inside Australia's longest-running music video program

This research presents an insider's account of rage, Australia's longest-running music video program. The research's significance is that there has been scarce scholarly analysis of this idiosyncratic ABC program, despite its longevity and uniqueness. The thesis takes a reflective and reflexive narrative journey across rage's decades, presenting the accounts of the program makers, aided by the perspective of an embedded researcher, the program's former Series Producer. This work addresses the rage research gap and contributes to the scholarly discussion on music video and its contexts, the ABC, public service broadcasting, creative labour, and the cultural sense-making of television producers.

Genetics of path lengths in brain connectivity networks: HARDI-based maps in 457 adults

Brain connectivity analyses are increasingly popular for investigating organization. Many connectivity measures including path lengths are generally defined as the number of nodes traversed to connect a node in a graph to the others. Despite its name, path length is purely topological, and does not take into account the physical length of the connections. The distance of the trajectory may also be highly relevant, but is typically overlooked in connectivity analyses. Here we combined genotyping, anatomical MRI and HARDI to understand how our genes influence the cortical connections, using whole-brain tractography. We defined a new measure, based on Dijkstra's algorithm, to compute path lengths for tracts connecting pairs of cortical regions. We compiled these measures into matrices where elements represent the physical distance traveled along tracts. We then analyzed a large cohort of healthy twins and show that our path length measure is reliable, heritable, and influenced even in young adults by the Alzheimer's risk gene, CLU.

The path less travelled: Vertical circulation spaces in apartment buildings in the subtropics

This paper presents data on residents’ use of common stairways and lifts (vertical circulation spaces) in multi-storey apartment buildings (MSABs) in Brisbane, Australia. Vertical movement is a defining aspect of multi-storey living and the energy consumed by lifts contributes significantly to the energy budget of the typical MSAB. The purpose is to investigate whether a reappraisal of vertical circulation design, through the lens of residents’ requirements, might contribute to energy reductions in this building type. Data was gathered on a theoretical sample of MSAB ranging from five decades old to very recent schemes. 90 residents were surveyed about their day-to-day experiences of circulation and access systems. The results showed that residents mainly chose to use the stairs for convenience and exercise. Building management regimes that limited residents’ access to collective spaces were the main impediment to discretionary stair use. Only two buildings did not have fully enclosed stairwells and these had the highest stair usage, suggesting that stair design, and building governance are two areas that might be worthy of attention. The more that circulation design is focussed on limiting access, the less opportunities there are for personal choice, incidental social interaction and casual surveillance of collective spaces. The more that design of vertical circulation spaces in MSAB meets residents’ needs the less likely they are to be reliant on continuous energy supply for normal functioning.

The path towards greening the Malaysian construction industry

Construction industry contributes significantly to environmental degradation, and governments in many countries which are endeavouring to address the situation. Malaysia is no exception. This paper examines the path towards green construction project delivery in Malaysia, focusing on current green policies and initiatives by governments. The historical waves in Malaysian approaches to tackling environmental issues are described, starting from the early 20th century, through the 1990s to the present, and the influence of these approaches on construction practices is analysed. Based on the findings of policy review, essential green construction practices aimed at mitigating the adverse effects of construction activities on the environment in Malaysia were identified. This paper paves the way for future studies in construction and sustainability in Malaysia, especially for the Southeast Asian region where sustainability practices are urgently needed.

The transcriptome of the bowhead whale Balaena mysticetus reveals adaptations of the longest‐lived mammal

Mammals vary dramatically in lifespan, by at least two-orders of magnitude, but the molecular basis for this difference remains largely unknown. The bowhead whale Balaena mysticetus is the longest-lived mammal known, with an estimated maximal lifespan in excess of two hundred years. It is also one of the two largest animals and the most cold-adapted baleen whale species. Here, we report the first genome-wide gene expression analyses of the bowhead whale, based on the de novo assembly of its transcriptome. Bowhead whale or cetacean-specific changes in gene expression were identified in the liver, kidney and heart, and complemented with analyses of positively selected genes. Changes associated with altered insulin signaling and other gene expression patterns could help explain the remarkable longevity of bowhead whales as well as their adaptation to a lipid-rich diet. The data also reveal parallels in candidate longevity adaptations of the bowhead whale, naked mole rat and Brandt's bat. The bowhead whale transcriptome is a valuable resource for the study of this remarkable animal, including the evolution of longevity and its important correlates such as resistance to cancer and other diseases.

LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

Path algebra for mobile robots

In this paper, we introduce a path algebra well suited for navigation in environments that can be abstracted as topological graphs. From this path algebra, we derive algorithms to reduce routes in such environments. The routes are reduced in the sense that they are shorter (contain fewer edges), but still connect the endpoints of the initial routes. Contrary to planning methods descended from Disjktra’s Shortest Path Algorithm like D , the navigation methods derived from our path algebra do not require any graph representation. We prove that the reduced routes are optimal when the graphs are without cycles. In the case of graphs with cycles, we prove that whatever the length of the initial route, the length of the reduced route is bounded by a constant that only depends on the structure of the environment.

Singularity-free path planning for the Stewart platform manipulator

This paper addresses the problem of singularity-free path planning for the six-degree-of-freedom parallel manipulator known as the Stewart platform manipulator. Unlike serial manipulators, the Stewart platform possesses singular configurations within the workspace where the manipulator is uncontrollable. An algorithm has been developed to construct continuous paths within the workspace of the manipulator by avoiding singularities and ill-conditioning. Given two end-poses of the manipulator, the algorithm finds out safe (well-conditioned) via points and plans a continuous path from the initial pose to the final one. When the two end-poses belong to different branches and no singularity-free path is possible, the algorithm indicates the impossibility of a valid path. A numerical example has also been presented as illustration of the path planning strategy.

Study of texture evolution in metastable beta-Ti alloy as a function of strain path and its effect on alpha transformation texture

Texture evolution in a low cost beta titanium alloy was studied for different modes of rolling and heat treatments. The alloy was cold rolled by unidirectional and multi-step cross rolling. The cold rolled material was either aged directly or recrystallized and then aged. The evolution of texture in alpha and beta phases were studied. The rolling texture of beta phase that is characterized by the gamma fiber is stronger for MSCR than UDR; while the trend is reversed on recrystallization. The mode of rolling affects alpha transformation texture on aging with smaller alpha lath size and stronger alpha texture in UDR than in MSCR. The defect structure in beta phase influences the evolution of a texture on aging. A stronger defect structure in beta phase leads to variant selection with the rolled samples showing fewer variants than the recrystallized samples.

A critical evaluation of literature on robot path planning in dynamic environment

Robot Path Planning (RPP) in dynamic environments is a search problem based on the examination of collision-free paths in the presence of dynamic and static obstacles. Many techniques have been developed to solve this problem. Trapping in a local minima and maintaining a Real-Time performance are known as the two most important challenges that these techniques face to solve such problem. This study presents a comprehensive survey of the various techniques that have been proposed in this domain. As part of this survey, we include a classification of the approaches and identify their methods.

Ant Colony Optimization Algorithms for Shortest Path Problems

We propose four variants of recently proposed multi-timescale algorithm in [1] for ant colony optimization and study their application on a multi-stage shortest path problem. We study the performance of the various algorithms in this framework. We observe, that one of the variants consistently outperforms the algorithm [1].

Access path query language for relational database systems

Database management systems offer a very reliable and attractive data organization for fast and economical information storage and processing for diverse applications. It is much more important that the information should be easily accessible to users with varied backgrounds, professional as well as casual, through a suitable data sublanguage. The language adopted here (APPLE) is one such language for relational database systems and is completely nonprocedural and well suited to users with minimum or no programming background. This is supported by an access path model which permits the user to formulate completely nonprocedural queries expressed solely in terms of attribute names. The data description language (DDL) and data manipulation language (DML) features of APPLE are also discussed. The underlying relational database has been implemented with the help of the DATATRIEVE-11 utility for record and domain definition which is available on the PDP-11/35. The package is coded in Pascal and MACRO-11. Further, most of the limitations of the DATATRIEVE-11 utility have been eliminated in the interface package.

Comment on path integration of a quadratic action with a generalized memory

Using the promeasure technique, we give an alternative evaluation of a path integral corresponding to a quadratic action with a generalized memory.

Exact evaluation of Gaussian path integrals involving non-local potentials

An exact expression for the calculation of gaussian path integrals involving non-local potentials is given. Its utility is demonstrated by using it to evaluate a path integral arising in the study of an electron gas in a random potential.