E-business impacts for urban freight: results from an Australian study

E-Business is expected to dramatically change the way business is conducted internationally, nationally, within states and at the local area level. Moreover, these changes are very likely to happen well within the planning time frames required for provision of transport infrastructure and services. E-business is defined as including e-commerce, either between Businesses to Business (B2B) or Business to Customers (B2C), and the adoption of electronic technology within businesses. This paper presents some results from a study commissioned by the Australian National Transport Secretariat (NTS) to assist Australian business and government pro-actively address the transport issues arising from e-business. The resulting working papers will be used to establish a research framework for identifying policy and planning levers to maximize benefits to Australia from national and global e-business activity. The study sought to investigate three principal questions on e-business impacts: how will the transport task change; what will be affected; and how can the transport system respond? Current literature suggests that growth in e-business stems from the combined existence of market demand, suitable enabling technology, and skills and familiarity in management/users/ industry/government. The results of the study suggest that e-business will have implications for urban freight including higher levels of demand for goods and services, increased requirements for logistics distribution, changes in location preferences and improved transport network performance

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

Economic Valuation of Oceanographic Forecasting Services: A Cost-Benefit Exercise

This paper provides an assessment of the economic value of the oceanographic services provided by the Mediterranean operational forecasting system, MFSTEP. The main purpose of this exploratory study is to carry out a cost-benefit analysis for different development scenarios, by comparing the costs associated with the project implementation with the private benefits that arise from delivering its products on the market. As far as the costs are concerned, a total cost assessment has been performed by identifying, classifying and estimating the wide range of inputs that have been allocated both to the project development and maintenance. Against this context, a cost questionnaire has been designed and administered to all MFSTEP partners. In addition, the study focuses on an end-users analysis in order to examine end-users’ attitudes and interests for the forecasting products, their needs and satisfaction. As before, we make the use of a survey. Finally, this questionnaire is characterized by exploring the use of the contingent valuation approach so as to address and estimate the private benefits derived from the provision of the MFSTEP products. Estimation results show that the mean willingness to pay for accessing the forecasting products amounts to 65 euro per download. Cost-benefit analysis reveals that, from a market perspective relying on the profit maximisation, a total of 163 downloads per day are required for total maintenance costs recovery, whereas 90 downloads per day are required to recover personnel maintenance costs. Finally, 33 downloads per day are required so as to recover durable equipment maintenance costs.Cost-Benefit Analysis, Contingent Valuation, Survey Design, Willingness to Pay, Cost Assessment, Observing and Modelling Oceanographic System

Reproducible Econometric Research. A Critical Review of the State of the Art.

Recent software developments are reviewed from the vantage point of reproducible econometric research. We argue that the emergence of new tools, particularly in the open-source community, have greatly eased the burden of documenting and archiving both empirical and simulation work in econometrics. Some of these tools are highlighted in the discussion of three small replication exercises.Series: Research Report Series / Department of Statistics and Mathematic

Performance evaluation of a distributed integrative architecture for robotics

The eld of robotics employs a vast amount of coupled sub-systems. These need to interact cooperatively and concurrently in order to yield the desired results. Some hybrid algorithms also require intensive cooperative interactions internally. The architecture proposed lends it- self amenable to problem domains that require rigorous calculations that are usually impeded by the capacity of a single machine, and incompatibility issues between software computing elements. Implementations are abstracted away from the physical hardware for ease of de- velopment and competition in simulation leagues. Monolithic developments are complex, and the desire for decoupled architectures arises. Decoupling also lowers the threshold for using distributed and parallel resources. The ability to re-use and re-combine components on de- mand, therefore is essential, while maintaining the necessary degree of interaction. For this reason we propose to build software components on top of a Service Oriented Architecture (SOA) using Web Services. An additional bene t is platform independence regarding both the operating system and the implementation language. The robot soccer platform as well as the associated simulation leagues are the target domain for the development. Furthermore are machine vision and remote process control related portions of the architecture currently in development and testing for industrial environments. We provide numerical data based on the Python frameworks ZSI and SOAPpy undermining the suitability of this approach for the eld of robotics. Response times of signi cantly less than 50 ms even for fully interpreted, dynamic languages provides hard information showing the feasibility of Web Services based SOAs even in time critical robotic applications

DeepPicar: A Low-cost Deep Neural Network-based Autonomous Car

We present DeepPicar, a low-cost deep neural network based autonomous car platform. DeepPicar is a small scale replication of a real self-driving car called DAVE-2 by NVIDIA. DAVE-2 uses a deep convolutional neural network (CNN), which takes images from a front-facing camera as input and produces car steering angles as output. DeepPicar uses the same network architecture---9 layers, 27 million connections and 250K parameters---and can drive itself in real-time using a web camera and a Raspberry Pi 3 quad-core platform. Using DeepPicar, we analyze the Pi 3's computing capabilities to support end-to-end deep learning based real-time control of autonomous vehicles. We also systematically compare other contemporary embedded computing platforms using the DeepPicar's CNN-based real-time control workload. We find that all tested platforms, including the Pi 3, are capable of supporting the CNN-based real-time control, from 20 Hz up to 100 Hz, depending on hardware platform. However, we find that shared resource contention remains an important issue that must be considered in applying CNN models on shared memory based embedded computing platforms; we observe up to 11.6X execution time increase in the CNN based control loop due to shared resource contention. To protect the CNN workload, we also evaluate state-of-the-art cache partitioning and memory bandwidth throttling techniques on the Pi 3. We find that cache partitioning is ineffective, while memory bandwidth throttling is an effective solution.Comment: To be published as a conference paper at RTCSA 201

Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

A Communication Monitor for Wireless Sensor Networks Based on Software Defined Radio

Link quality estimation of reliability-crucial wireless sensor networks (WSNs) is often limited by the observability and testability of single-chip radio transceivers. The estimation is often based on collection of packer-level statistics, including packet reception rate, or vendor-specific registers, such as CC2420's Received Signal Strength Indicator (RSSI) and Link Quality Indicator (LQI). The speed or accuracy of such metrics limits the performance of reliability mechanisms built in wireless sensor networks. To improve link quality estimation in WSNs, we designed a powerful wireless communication monitor based on Software Defined Radio (SDR). We studied the relations between three implemented link quality metrics and packet reception rate under different channel conditions. Based on a comparison of the metrics' relative advantages, we proposed using a combination of them for fast and accurate estimation of a sensor network link