Performance profiling for predictive train schedules

In this article an alternate sensitivity analysis is proposed for train schedules. It characterises the schedules robustness or lack thereof and provides unique profiles of performance for different sources of delay and for different values of delay. An approach like this is necessary because train schedules are only a prediction of what will actually happen. They can perform poorly with respect to a variety of performance metrics, when deviations and other delays occur, if for instance they can even be implemented, and as originally intended. The information provided by this analytical approach is beneficial because it can be used as part of a proactive scheduling approach to alter a schedule in advance or to identify suitable courses of action for specific “bad behaviour”. Furthermore this information may be used to quantify the cost of delay. The effect of sectional running time (SRT) deviations and additional dwell time in particular were quantified for three railway schedule performance measures. The key features of this approach were demonstrated in a case study.

BOSTER : an efficient algorithm for mining frequent unordered induced subtrees

Extracting frequent subtrees from the tree structured data has important applications in Web mining. In this paper, we introduce a novel canonical form for rooted labelled unordered trees called the balanced-optimal-search canonical form (BOCF) that can handle the isomorphism problem efficiently. Using BOCF, we define a tree structure guided scheme based enumeration approach that systematically enumerates only the valid subtrees. Finally, we present the balanced optimal search tree miner (BOSTER) algorithm based on BOCF and the proposed enumeration approach, for finding frequent induced subtrees from a database of labelled rooted unordered trees. Experiments on the real datasets compare the efficiency of BOSTER over the two state-of-the-art algorithms for mining induced unordered subtrees, HybridTreeMiner and UNI3. The results are encouraging.

BEST : an efficient algorithm for mining frequent unordered embedded subtrees

This paper presents an algorithm for mining unordered embedded subtrees using the balanced-optimal-search canonical form (BOCF). A tree structure guided scheme based enumeration approach is defined using BOCF for systematically enumerating the valid subtrees only. Based on this canonical form and enumeration technique, the balanced optimal search embedded subtree mining algorithm (BEST) is introduced for mining embedded subtrees from a database of labelled rooted unordered trees. The extensive experiments on both synthetic and real datasets demonstrate the efficiency of BEST over the two state-of-the-art algorithms for mining embedded unordered subtrees, SLEUTH and U3.

Key Concepts in Crime and Society

This book is an introduction to key issues in the area of crime as it connects to society. The book is divided into three parts: Understanding Crime and Criminality: introduces topics such as the social construction of crime and deviance, social control, the fear of crime, poverty and exclusion, white collar crime, victims of crime, race/gender and crime. Types of Crime and Criminality: explores examples including human trafficking, sex work, drug crime, environmental crime, cyber crime, war crime, terrorism, and interpersonal violence. Responses to Crime: looks at areas such as crime and the media, policing, moral panics, deterrence, prisons and rehabilitation.

Synonymization of key pest species within the Bactrocera dorsalis species complex (Diptera: Tephritidae): Taxonomic changes based on a review of 20 years of integrative morphological, molecular, cytogenetic, behavioural and chemoecological data

Bactrocera papayae Drew & Hancock, Bactrocera philippinensis Drew & Hancock, Bactrocera carambolae Drew & Hancock, and Bactrocera invadens Drew, Tsuruta & White are four horticultural pest tephritid fruit fly species that are highly similar, morphologically and genetically, to the destructive pest, the Oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae). This similarity has rendered the discovery of reliable diagnostic characters problematic, which, in view of the economic importance of these taxa and the international trade implications, has resulted in ongoing difficulties for many areas of plant protection and food security. Consequently, a major international collaborative and integrated multidisciplinary research effort was initiated in 2009 to build upon existing literature with the specific aim of resolving biological species limits among B. papayae, B. philippinensis, B. carambolae, B. invadens and B. dorsalis to overcome constraints to pest management and international trade. Bactrocera philippinensis has recently been synonymized with B. papayae as a result of this initiative and this review corroborates that finding; however, the other names remain in use. While consistent characters have been found to reliably distinguish B. carambolae from B. dorsalis, B. invadens and B. papayae, no such characters have been found to differentiate the latter three putative species. We conclude that B. carambolae is a valid species and that the remaining taxa, B. dorsalis, B. invadens and B. papayae, represent the same species. Thus, we consider B. dorsalis (Hendel) as the senior synonym of B. papayae Drew and Hancock syn.n. and B. invadens Drew, Tsuruta & White syn.n. A redescription of B. dorsalis is provided. Given the agricultural importance of B. dorsalis, this taxonomic decision will have significant global plant biosecurity implications, affecting pest management, quarantine, international trade, postharvest treatment and basic research. Throughout the paper, we emphasize the value of independent and multidisciplinary tools in delimiting species, particularly in complicated cases involving morphologically cryptic taxa.

Beyond the Producer/Consumer Divide : Key Principles of Produsage and Opportunities for Innovation

Though popular, concepts such as Toffler's 'prosumer' (1970; 1980; 1990) are inherently limited in their ability to accurately describe the makeup and dynamics of current co-creative environments, from fundamentally non-profit initiatives like the Wikipedia to user-industry partnerships that engage in crowdsourcing and the development of collective intelligence. Instead, the success or failure of such projects can be understood best if the traditional producer/consumer divide is dissolved, allowing for the emergence of the produser (Bruns, 2008). A close investigation of leading spaces for produsage makes it possible to extract the key principles which underpin and guide such content co-creation, and to identify how innovative pro-am partnerships between commercial entities and user communities might be structured in order to maximise the benefits that both sides will be able to draw from such collaboration. This chapter will outline these principles, and point to successes and failures in applying them to pro- am initiatives.

An open pit multistage mine production scheduling model for drilling, blasting and excavating operations

This paper proposes a new multi-resource multi-stage scheduling problem for optimising the open-pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints have been considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times of equipment; equipment-assignment-dependent operation times of blocks; distances between each pair of blocks; due windows of blocks; material properties of blocks; swell factors of blocks; and slope requirements of blocks. It is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level. The model also provides an intelligent decision support tool to account for the availability and usage of equipment units for drilling, blasting and excavating stages.

Defining a ‘democratic elite’ : key media in the battle for social responsibility

This paper offers a definition of elite media arguing their content focus will sufficiently meet social responsibility needs of democracy. Its assumptions come from the Finkelstein and Leveson Inquiries and regulatory British Royal Charter (2013). These provide guidelines on how media outlets meet ‘social responsibility’ standards, e.g. press has a ‘responsibility to be fair and accurate’ (Finkelstein); ethical press will feel a responsibility to ‘hold power to account’ (Leveson); news media ‘will be held strictly accountable’ (RC). The paper invokes the British principle of media opting-in to observe standards, and so serve the democracy. It will give examples from existing media, and consider social responsibility of media more generally. Obvious cases of ‘quality’ media: public broadcasters, e.g. BBC, Al-Jazeera, and ‘quality’ press, e.g. NYT, Süddeutscher Zeitung, but also community broadcasters, specialised magazines, news agencies, distinctive web logs, and others. Where providing commentary, these abjure gratuitous opinion -- meeting a standard of reasoned, informational and fair. Funding is almost a definer, many such services supported by the state, private trusts, public institutions or volunteering by staff. Literature supporting discussion on elite media will include their identity as primarily committed to a public good, e.g. the ‘Public Value Test’, Moe and Donders (2011); with reference also to recent literature on developing public service media. Within its limits the paper will treat social media as participants among all media, including elite, and as a parallel dimension of mass communication founded on inter-activity. Elite media will fulfil the need for social responsibility, firstly by providing one space, a ‘plenary’ for debate. Second is the notion of building public recognition of elite media as trustworthy. Third is the fact that elite media together are a large sector with resources to sustain social cohesion and debate; notwithstanding pressure on funds, and impacts of digital transformation undermining employment in media more than in most industries.

Key influences on cycling for transport

Over recent years, the health, transport and environment sectors have been increasingly focused on the promotion of transport cycling. From a health perspective, transport cycling is recognised as a beneficial form of physical activity as it can be easily integrated into daily living, is done at an intensity that confers health benefits, and is associated with reductions in mortality and morbidity [1]. From a safety perspective, the risk of a serious cycling injury decreases as cycling increases [2] as having more cyclists on roads increases motor vehicle drivers’ awareness of cyclists and in turn makes cycling safer. Whereas cycling for recreation is the fourth most commonly reported physical activity among Australian adults [3], transport cycling is an underutilised travel mode. Approximately 1.3% of journeys to work in Australia are made by bicycle [4]. This low prevalence is mirrored in the UK and the US, but not in some European countries like the Netherlands and Denmark, where over 18% and 26%, respectively, of all journeys are made by bicycle [5]. In the past decade, concerted efforts have been made by Australian state and local governments to increase cycling rates [6]. Notably, Melbourne, Sydney and Brisbane have implemented policies, increased bicycle commuting infrastructure, and offered information and promotion programs to encourage commuter cycling [6,7]. Governments have also developed comprehensive longterm plans for guiding future cycling strategies, using lessons learned from around the world in developing successful cycling policy and promotion [6,7]. Changes in transport cycling rates in inner cities since these efforts have been implemented are encouraging. In Sydney, census data indicate an 83% increase in the number of people using a bicycle for commuting between 2001 and 2011 [8]. Counts of bicycles being ridden along major cycling commuter routes indicate increases in weekday morning cycling trips in Brisbane (63% increase from 2004 to 2010) [7] and in Melbourne (a 43% increase from 2006 to 2008) [9]. However, bicycle mode share to work has changed little: for example, between 2001 and 2011, it decreased slightly from 1.6% to 1.3% in Brisbane [10,11]. Researchers have been investigating factors that may be contributing to low rates of cycling for transport, to inform future policy and programming to encourage transport cycling. The aim of this paper is to overview our work to date in this area of research in Queensland.

Pollen image classification using the classifynder system: Algorithm comparison and a case study on New Zealand honey

We describe an investigation into how Massey University’s Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University’s pollen reference collection (2,890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set.We additionally work through a real world case study where we assess the ability of the system to determine the pollen make-up of samples of New Zealand honey. In addition to the Classifynder’s native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples.

A communication model and partitioning algorithm for streaming applications for an embedded MPSoC

Energy efficient embedded computing enables new application scenarios in mobile devices like software-defined radio and video processing. The hierarchical multiprocessor considered in this work may contain dozens or hundreds of resource efficient VLIW CPUs. Programming this number of CPU cores is a complex task requiring compiler support. The stream programming paradigm provides beneficial properties that help to support automatic partitioning. This work describes a compiler for streaming applications targeting the self-build hierarchical CoreVA-MPSoC multiprocessor platform. The compiler is supported by a programming model that is tailored to fit the streaming programming paradigm. We present a novel simulated-annealing (SA) based partitioning algorithm, called Smart SA. The overall speedup of Smart SA is 12.84 for an MPSoC with 16 CPU cores compared to a single CPU implementation. Comparison with a state of the art partitioning algorithm shows an average performance improvement of 34.07%.

An efficient forward-backward algorithm to MSDEPP including batteries and voltage control devices

Electric distribution networks are now in the era of transition from passive to active distribution networks with the integration of energy storage devices. Optimal usage of batteries and voltage control devices along with other upgrades in network needs a distribution expansion planning (DEP) considering inter-temporal dependencies of stages. This paper presents an efficient approach for solving multi-stage distribution expansion planning problems (MSDEPP) based on a forward-backward approach considering energy storage devices such as batteries and voltage control devices such as voltage regulators and capacitors. The proposed algorithm is compared with three other techniques including full dynamic, forward fill-in, backward pull-out from the point of view of their precision and their computational efficiency. The simulation results for the IEEE 13 bus network show the proposed pseudo-dynamic forward-backward approach presents good efficiency in precision and time of optimization.