Dragline automation

Draglines are used extensively for overburden stripping in Australian open cut coal mines. This paper outlines the design of a computer control system to implement an automated swing cycle on a production dragline. Subsystems and sensors have been developed to satisfy the constraints imposed by the task, the harsh operating environment and the mines production requirements.

On Visual Detection of Highly-occluded Objects for Harvesting Automation in Horticulture

Developing accurate and reliable crop detection algorithms is an important step for harvesting automation in horticulture. This paper presents a novel approach to visual detection of highly-occluded fruits. We use a conditional random field (CRF) on multi-spectral image data (colour and Near-Infrared Reflectance, NIR) to model two classes: crop and background. To describe these two classes, we explore a range of visual-texture features including local binary pattern, histogram of oriented gradients, and learn auto-encoder features. The pro-posed methods are evaluated using hand-labelled images from a dataset captured on a commercial capsicum farm. Experimental results are presented, and performance is evaluated in terms of the Area Under the Curve (AUC) of the precision-recall curves.Our current results achieve a maximum performance of 0.81AUC when combining all of the texture features in conjunction with colour information.

Location of concentrators in a computer communication network: a stochastic automation search method

The following problem is considered. Given the locations of the Central Processing Unit (ar;the terminals which have to communicate with it, to determine the number and locations of the concentrators and to assign the terminals to the concentrators in such a way that the total cost is minimized. There is alao a fixed cost associated with each concentrator. There is ail upper limit to the number of terminals which can be connected to a concentrator. The terminals can be connected directly to the CPU also In this paper it is assumed that the concentrators can bo located anywhere in the area A containing the CPU and the terminals. Then this becomes a multimodal optimization problem. In the proposed algorithm a stochastic automaton is used as a search device to locate the minimum of the multimodal cost function . The proposed algorithm involves the following. The area A containing the CPU and the terminals is divided into an arbitrary number of regions (say K). An approximate value for the number of concentrators is assumed (say m). The optimum number is determined by iteration later The m concentrators can be assigned to the K regions in (mk) ways (m > K) or (km) ways (K>m).(All possible assignments are feasible, i.e. a region can contain 0,1,…, to concentrators). Each possible assignment is assumed to represent a state of the stochastic variable structure automaton. To start with, all the states are assigned equal probabilities. At each stage of the search the automaton visits a state according to the current probability distribution. At each visit the automaton selects a 'point' inside that state with uniform probability. The cost associated with that point is calculated and the average cost of that state is updated. Then the probabilities of all the states are updated. The probabilities are taken to bo inversely proportional to the average cost of the states After a certain number of searches the search probabilities become stationary and the automaton visits a particular state again and again. Then the automaton is said to have converged to that state Then by conducting a local gradient search within that state the exact locations of the concentrators are determined This algorithm was applied to a set of test problems and the results were compared with those given by Cooper's (1964, 1967) EAC algorithm and on the average it was found that the proposed algorithm performs better.

Documenting the inevitable: Voting behaviour at the 2013 Australian election

This chapter uses data from the 2013 Australian Election Study (AES), conducted by Clive Bean, Ian McAllister, Juliet Pietsch and Rachel Gibson (Bean et al. 2014) to investigate political attitudes and voting behaviour in the election. The study was funded by the Australian Research Council and involved a national survey of political attitudes and behaviour using a self-completion questionnaire mailed to respondents on the day before the 7 September election. The sample was a systematic random sample of enrolled voters throughout Australia, drawn by the Australian Electoral Commission. Respondents were given the option of returning the completed questionnaire by reply-paid mail or completing the survey online. Non-respondents were sent several follow-up mailings and the final sample size was 3955, representing a response rate of 34 per cent. The data were weighted to reflect population parameters for gender, age, state and vote.

A Simple Hysteretic Energy Harvesting Method for Nonneutral AC Switches in Load Automation

This paper presents a simple hysteretic method to obtain the energy required to operate the gate-drive, sensors, and other circuits within nonneutral ac switches intended for use in load automated buildings. The proposed method features a switch-mode low part-count self-powered MOSFET ac switch that achieves efficiency and load current THD figures comparable to those of an externally gate-driven switch built using similar MOSFETS. The fundamental operation of the method is explained in detail, followed by the modifications required for practical implementation. Certain design rules that allow the method to accommodate a wide range of single-phase loads from 10 VA to 1 kVA are discussed, along with an efficiency enhancement feature based on inherent MOSFET characteristics. The limitations and side effects of the method are also mentioned according to their levels of severity. Finally, experimental results obtained using a prototype sensor switch are presented, along with a performance comparison of the prototype with an externally gate-driven MOSFET switch.

Home-Automation System

Nuestro proyecto trata de obtener un sistema centralizado para el manejo y monitorización de un conjunto de aparatos eléctricos del hogar, tales como luces, cámaras, sensores, y otros aparatos mediante una aplicación para dispositivos móviles Android. También se facilita una herramienta web para administrar dichos aparatos. Nuestro sistema da soporte al manejo individual y manual de estos aparatos, por ejemplo encender una lámpara, así como la posibilidad de incluir programas que se ejecuten a una determinada hora, y con una determinada recurrencia. Por ejemplo, se puede programar el encendido de una luz todos los días a las 20:00. Además, también se pueden crear reglas que, dado una determinada situación, realicen una serie de acciones. Por ejemplo, si se detecta que la luminosidad baja de cierto valor (detectado mediante un sensor de luz), se encienda una lámpara. Para conseguir esto se ha realizado una aplicación centralizada, a modo de servidor, que se comunica con los aparatos eléctricos mediante diferentes protocolos de comunicación, así como con el dispositivo móvil Android, y una aplicación web administrativa, a través de un portal de servicios web.

Designing High Performance Factory Automation Applications on Top of DDS

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