Identifying weak linear features with the "coalescing shortest path image transform"

The detection of line-like features in images finds many applications in microanalysis. Actin fibers, microtubules, neurites, pilis, DNA, and other biological structures all come up as tenuous curved lines in microscopy images. A reliable tracing method that preserves the integrity and details of these structures is particularly important for quantitative analyses. We have developed a new image transform called the "Coalescing Shortest Path Image Transform" with very encouraging properties. Our scheme efficiently combines information from an extensive collection of shortest paths in the image to delineate even very weak linear features. © Copyright Microscopy Society of America 2011.

Tubule detection in testis images using boundary weighting and circular shortest path

In studies of germ cell transplantation, measureing tubule diameters and counting cells from different populations using antibodies as markers are very important. Manual measurement of tubule sizes and cell counts is a tedious and sanity grinding work. In this paper, we propose a new boundary weighting based tubule detection method. We first enhance the linear features of the input image and detect the approximate centers of tubules. Next, a boundary weighting transform is applied to the polar transformed image of each tubule region and a circular shortest path is used for the boundary detection. Then, ellipse fitting is carried out for tubule selection and measurement. The algorithm has been tested on a dataset consisting of 20 images, each having about 20 tubules. Experiments show that the detection results of our algorithm are very close to the results obtained manually. © 2013 IEEE.

Convergence-guaranteed time-varying RRT path planning for profiling floats in 4-Dimensional flow

This paper presents an extension to the Rapidly-exploring Random Tree (RRT) algorithm applied to autonomous, drifting underwater vehicles. The proposed algorithm is able to plan paths that guarantee convergence in the presence of time-varying ocean dynamics. The method utilizes 4-Dimensional, ocean model prediction data as an evolving basis for expanding the tree from the start location to the goal. The performance of the proposed method is validated through Monte-Carlo simulations. Results illustrate the importance of the temporal variance in path execution, and demonstrate the convergence guarantee of the proposed methods.

Autonomous vehicle path planning for persistence monitoring under uncertainty using Gaussian based Markov decision process

One of the main challenges facing online and offline path planners is the uncertainty in the magnitude and direction of the environmental energy because it is dynamic, changeable with time, and hard to forecast. This thesis develops an artificial intelligence for a mobile robot to learn from historical or forecasted data of environmental energy available in the area of interest which will help for a persistence monitoring under uncertainty using the developed algorithm.

Automotive modal lock-in: The role of path dependence and large socio-economic regimes in market failure

This paper addresses less recognised factors which influence the diffusion of a particular technology. While an innovation’s attributes and performance are paramount, many fail because of external factors which favour an alternative. This paper, with theoretic input from diffusion, lock-in and path-dependency, presents a qualitative study of external factors that influenced the evolution of transportation in USA. This historical account reveals how one technology and its emergent systems become dominant while other choices are overridden by socio-political, economic and technological interests which include not just the manufacturing and service industries associated with the automobile but also government and market stakeholders. Termed here as a large socio-economic regime (LSER),its power in ensuring lock-in and continued path-dependency is shown to pass through three stages, weakening eventually as awareness improves. The study extends to transport trends in China, Korea, Indonesia and Malaysia and they all show the dominant role of an LSER. As transportation policy is increasingly accountable to address both demand and environmental concerns and innovators search for solutions, this paper presents important knowledge for innovators, marketers and policy makers for commercial and societal reasons, especially when negative externalities associated with an incumbent transportation technology may lead to market failure.

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.

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.

Optimum position of steel outrigger system for high rise composite buildings subjected to wind loads

The responses of composite buildings under wind loads clearly become more critical as the building becomes taller, less stiff and more lightweight. When the composite building increases in height, the stiffness of the structure becomes more important factor and introduction to belt truss and outrigger system is often used to provide sufficient lateral stiffness to the structure. Most of the research works to date is limited to reinforced concrete building with outrigger system of concrete structure, simple building plan layout, single height of a building, one direction wind and single level of outrigger arrangement. There is a scarcity in research works about the effective position of outrigger level on composite buildings under lateral wind loadings when the building plan layout, height and outrigger arrangement are varied. The aim of this paper is to determine the optimum location of steel belt and outrigger systems by using different arrangement of single and double level outrigger for different size, shape and height of composite building. In this study a comprehensive finite element modelling of composite building prototypes is carried out, with three different layouts (Rectangular, Octagonal and L shaped) and for three different storey (28, 42 and 57-storey). Models are analysed for dynamic cyclonic wind loads with various combination of steel belt and outrigger bracings. It is concluded that the effectiveness of the single and double level steel belt and outrigger bracing are varied based on their positions for different size, shape and height of composite building.

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.

New microscale vertically oriented organic photovoltaics cells

We initially look at the changing energy environment and how that can have a dramatic change on the potential of alternative energies, in particular those of organic photovoltaicvs (OPV) cells. In looking at OPV's we also address the aspects of where we are with the current art and why we may not be getting the best from our materials. In doing so, we propose the idea of changing how we build organic photovoltaics by addressing the best method to contain light within the devices. Our initial effort is in addressing how these microscale optical concentrators work in the form of optical fibers in terms of absorption. We have derived a mathematical method which takes account of the input angle of light to achieve optimum absorption. However, in doing so we also address the complex issue how the changing refractive indices in a multilayer device can alter how we input the light. We have found that by knowing the materials refractive index our model takes into account the incident plane, meridonal plane, cross sectional are and path length to ensure optical angular input. Secondly, we also address the practicalities of making such vertical structures the greater issue of changing light intensity incident on a solar cell and how that aspects alters how we view the performance of organic solar cells.

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.

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.