A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm

During the past few decades, developing efficient methods to solve dynamic facility layout problems has been focused on significantly by practitioners and researchers. More specifically meta-heuristic algorithms, especially genetic algorithm, have been proven to be increasingly helpful to generate sub-optimal solutions for large-scale dynamic facility layout problems. Nevertheless, the uncertainty of the manufacturing factors in addition to the scale of the layout problem calls for a mixed genetic algorithm–robust approach that could provide a single unlimited layout design. The present research aims to devise a customized permutation-based robust genetic algorithm in dynamic manufacturing environments that is expected to be generating a unique robust layout for all the manufacturing periods. The numerical outcomes of the proposed robust genetic algorithm indicate significant cost improvements compared to the conventional genetic algorithm methods and a selective number of other heuristic and meta-heuristic techniques.

Learning Temporal Alignment Uncertainty for Efficient Event Detection

In this paper we tackle the problem of efficient video event detection. We argue that linear detection functions should be preferred in this regard due to their scalability and efficiency during estimation and evaluation. A popular approach in this regard is to represent a sequence using a bag of words (BOW) representation due to its: (i) fixed dimensionality irrespective of the sequence length, and (ii) its ability to compactly model the statistics in the sequence. A drawback to the BOW representation, however, is the intrinsic destruction of the temporal ordering information. In this paper we propose a new representation that leverages the uncertainty in relative temporal alignments between pairs of sequences while not destroying temporal ordering. Our representation, like BOW, is of a fixed dimensionality making it easily integrated with a linear detection function. Extensive experiments on CK+, 6DMG, and UvA-NEMO databases show significant performance improvements across both isolated and continuous event detection tasks.

Repeatable Condition-Invariant Visual Odometry for Sequence-Based Place Recognition

This paper describes a vision-only system for place recognition in environments that are tra- versed at different times of day, when chang- ing conditions drastically affect visual appear- ance, and at different speeds, where places aren’t visited at a consistent linear rate. The ma- jor contribution is the removal of wheel-based odometry from the previously presented algo- rithm (SMART), allowing the technique to op- erate on any camera-based device; in our case a mobile phone. While we show that the di- rect application of visual odometry to our night- time datasets does not achieve a level of perfor- mance typically needed, the VO requirements of SMART are orthogonal to typical usage: firstly only the magnitude of the velocity is required, and secondly the calculated velocity signal only needs to be repeatable in any one part of the environment over day and night cycles, but not necessarily globally consistent. Our results show that the smoothing effect of motion constraints is highly beneficial for achieving a locally consis- tent, lighting-independent velocity estimate. We also show that the advantage of our patch-based technique used previously for frame recogni- tion, surprisingly, does not transfer to VO, where SIFT demonstrates equally good performance. Nevertheless, we present the SMART system us- ing only vision, which performs sequence-base place recognition in extreme low-light condi- tions where standard 6-DOF VO fails and that improves place recognition performance over odometry-less benchmarks, approaching that of wheel odometry.

Enhancing human action recognition with region proposals

Deep convolutional network models have dominated recent work in human action recognition as well as image classification. However, these methods are often unduly influenced by the image background, learning and exploiting the presence of cues in typical computer vision datasets. For unbiased robotics applications, the degree of variation and novelty in action backgrounds is far greater than in computer vision datasets. To address this challenge, we propose an “action region proposal” method that, informed by optical flow, extracts image regions likely to contain actions for input into the network both during training and testing. In a range of experiments, we demonstrate that manually segmenting the background is not enough; but through active action region proposals during training and testing, state-of-the-art or better performance can be achieved on individual spatial and temporal video components. Finally, we show by focusing attention through action region proposals, we can further improve upon the existing state-of-the-art in spatio-temporally fused action recognition performance.

The con-stitutional re-cognition (s)cam-pain: The campaign for the hidden recognition of first nations peoples' racial inferiority

The constitutional recognition campaign has received party-wide support and its efforts have been promoted by Prime Minister Tony Abbott as being something that would ‘complete our Constitution.’ The broader rhetoric surrounding this campaign suggests that it will result in a just, albeit delayed, recognition of indigenous peoples in the Australian legal system. However, beneath the surface of this seemingly benevolent gesture, is a reaffirmation of the colonial subordination and erasure of the several hundred original nations’ peoples and ways of being.

Shifting the Focus. Incorporating knowledge about Aboriginal engineering into main stream content

BACKGROUND OR CONTEXT The concept of 'Aboriginal engineering' has had little exposure in conventional engineering education programs, despite more than 40,000 years of active human engagement with the diverse Australian environment. The work reported in this paper began with the premise that Indigenous Student Support Through Indigenous Perspectives Embedded in Engineering Curricula (Goldfinch, et al 2013) would provide a clear and replicable means of encouraging Aboriginal teenagers to consider a career in engineering. Although that remains a key outcome of this OLT project, the direction taken by the research had led to additional insights and perspectives that have wide implications for engineering education more generally. There has only been passing reference to the achievements of Aboriginal engineering in current texts, and the very absence of such references was a prompt to explore further as our work developed. PURPOSE OR GOAL Project goals focused on curriculum-based change, including development of a model for inclusive teaching spaces, and study units employing key features of the model. As work progressed we found we needed to understand more about the principles and practices informing the development of pre-contact Aboriginal engineering strategies for sustaining life and society within the landscape of this often harsh continent. We also found ourselves being asked 'what engineering did Aboriginal cultures have?' Finding that there are no easy-to- access answers, we began researching the question, while continuing to engage with specific curriculum trials. APPROACH Stakeholders in the project had been identified as engineering educators, potential Aboriginal students and Aboriginal communities local to Universities involved in the project. We realised, early on, that at least one more group was involved - all the non-Aboriginal students in engineering classes. This realisation, coupled with recognition of the need to understand Aboriginal engineering as a set of viable, long term practices, altered the focus of our efforts. Rather than focusing primarily on finding ways to attract Aboriginal engineering students, the shift has been towards evolving ways of including knowledge about Aboriginal practices and principles in relevant engineering content. DISCUSSION This paper introduces the model resulting from the work of this project, explores its potential influence on engineering curriculum development and reports on implementation strategies. The model is a static representation of a dynamic and cyclic approach to engaging with Aboriginal engineering through contact with local communities in regard to building knowledge about the social beliefs underlying Aboriginal engineering principles and practices. Ways to engage engineering educators, students and the wider community are evolving through the continuing work of the project team and will be reported in more detail in the paper. RECOMMENDATIONS/IMPLICATIONS/CONCLUSION While engineering may be considered by some to be agnostic in regard to culture and social issues, the work of this project is drawing attention to the importance of including such issues into curriculum materials at a number of levels of complexity. The paper will introduce and explore the central concepts of the research completed to date, as well as suggesting ways in which engineering educators can extend their knowledge and understanding of Aboriginal engineering principles in the context of their own specialisations.

Modeling dynamic demand response using Monte Carlo simulation and interval mathematics for boundary estimation

With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.

Correction factors for dynamic state estimation of aggregated generators

This paper presents an approach for dynamic state estimation of aggregated generators by introducing a new correction factor for equivalent inter-area power flows. The spread of generators from the center of inertia of each area is summarized by the correction term α on the equivalent power flow between the areas and is applied to the identification and estimation process. A nonlinear time varying Kalman filter is applied to estimate the equivalent angles and velocities of coherent areas by reducing the effect of local modes on the estimated states. The approach is simulated on two test systems and the results show the effect of the correction factor and the performance of the state estimation by estimating the inter-area dynamics of the system.

PMU measurement based dynamic load modeling using SVC devices in online environment

Online dynamic load modeling has become possible with the availability of Static Voltage Compensator (SVC) and Phasor Measurement Unit (PMU) devices. The power of the load response to the small random bounded voltage fluctuations caused from SVC can be measured by PMU for modelling purposes. The aim of this paper is to illustrate the capability of identifying an aggregated load model from high voltage substation level in the online environment. The induction motor is used as the main test subject since it contributes the majority of the dynamic loads. A test system representing simple electromechanical generator model serving dynamic loads through the transmission network is used to verify the proposed method. Also, dynamic load with multiple induction motors are modeled to achieve a better realistic load representation.

Dynamic Bayesian network inferencing for non-homogeneous complex systems

Dynamic Bayesian Networks (DBNs) provide a versatile platform for predicting and analysing the behaviour of complex systems. As such, they are well suited to the prediction of complex ecosystem population trajectories under anthropogenic disturbances such as the dredging of marine seagrass ecosystems. However, DBNs assume a homogeneous Markov chain whereas a key characteristics of complex ecosystems is the presence of feedback loops, path dependencies and regime changes whereby the behaviour of the system can vary based on past states. This paper develops a method based on the small world structure of complex systems networks to modularise a non-homogeneous DBN and enable the computation of posterior marginal probabilities given evidence in forwards inference. It also provides an approach for an approximate solution for backwards inference as convergence is not guaranteed for a path dependent system. When applied to the seagrass dredging problem, the incorporation of path dependency can implement conditional absorption and allows release from the zero state in line with environmental and ecological observations. As dredging has a marked global impact on seagrass and other marine ecosystems of high environmental and economic value, using such a complex systems model to develop practical ways to meet the needs of conservation and industry through enhancing resistance and/or recovery is of paramount importance.

Recognition and enforcement in cross-border insolvency law: A proposal for judicial gap-filling

This Article analyzes the recognition and enforcement of cross-border insolvency judgments from the United States, United Kingdom, and Australia to determine whether the UNCITRAL Model Law’s goal of modified universalism is currently being practiced, and subjects the Model Law to analysis through the lens of international relations theories to elaborate a way forward. We posit that courts could use the express language of the Model Law text to confer recognition and enforcement of foreign insolvency judgments. The adoption of our proposal will reduce costs, maximize recovery for creditors, and ensure predictability for all parties.

Activity recognition using binary tree SVM

This paper presents an effective classification method based on Support Vector Machines (SVM) in the context of activity recognition. Local features that capture both spatial and temporal information in activity videos have made significant progress recently. Efficient and effective features, feature representation and classification plays a crucial role in activity recognition. For classification, SVMs are popularly used because of their simplicity and efficiency; however the common multi-class SVM approaches applied suffer from limitations including having easily confused classes and been computationally inefficient. We propose using a binary tree SVM to address the shortcomings of multi-class SVMs in activity recognition. We proposed constructing a binary tree using Gaussian Mixture Models (GMM), where activities are repeatedly allocated to subnodes until every new created node contains only one activity. Then, for each internal node a separate SVM is learned to classify activities, which significantly reduces the training time and increases the speed of testing compared to popular the `one-against-the-rest' multi-class SVM classifier. Experiments carried out on the challenging and complex Hollywood dataset demonstrates comparable performance over the baseline bag-of-features method.

The open access advantage for researchers: Reflections on experience and challenges

This paper focuses on the advantages of Open Access, (OA) particularly from the point of view of individual researchers, research centres and disciplines, and institutions. The advantage described by the phrase “OA advantage”, is multifaceted. The experience of Queensland University of Technology in Australia in pioneering OA as preferred practice in an institution with a growing research profile and energy, has seen evidence of the OA advantage develop in the experience of our researchers. The University has witnessed the development of practical evidence about improved recognition and impact, and this has occurred in the context of sector wide activity and policy where fresh approaches and leadership will result in even greater rewards for researchers whose outputs are “in the open”.

Organizational competencies and dynamic Accounting Information System capability: Impact on AIS processes and firm performance

Accounting information systems (AIS) capture and process accounting data and provide valuable information for decision-makers. However, in a rapidly changing environment, continual management of the AIS is necessary for organizations to optimise performance outcomes. We suggest that building a dynamic AIS capability enables accounting process and organizational performance. Using the dynamic capabilities framework (Teece 2007) we propose that a dynamic AIS capability can be developed through the synergy of three competencies: a flexible AIS, having a complementary business intelligence system and accounting professionals with IT technical competency. Using survey data, we find evidence of a positive association between a dynamic AIS capability, accounting process performance, and overall firm performance. The results suggest that developing a dynamic AIS resource can add value to an organization. This study provides guidance for organizations looking to leverage the performance outcomes of their AIS environment.

A review on exploring the behavior of multi-layer composite structures under dynamic loading

This paper reviews the recent research progress on multi-layer composite structures composed of variety of materials. The utilization of multi-layer composite system is found to be common in metal structures and pavement systems. The layer of composite structure designed to encounter heavy dynamic energy should have sufficient ductility to counteract the intensity of energy. Therefore, the selection of materials and enhancement of interface bonding become crucial and both are discussed in this paper. The failure modes have also been explored in conjunction with stresses at failures and inferred solutions are also revealed. The paper attempts to reveal all technical facts on multi-layer composite structure in a broad field.