Consumer phase identification in a three phase unbalanced LV distribution network

A new technique is presented for automatically identifying the phase connection of domestic customers. Voltage information from a reference three phase house is correlated with voltage information from other customer electricity meters on the same network to determine the highest probability phase connection. The techniques are purely based upon a time series of electrical voltage measurements taken by the household smart meters and no additional equipment is required. The method is demonstrated using real smart meter datasets to correctly identify the phase connections of 75 consumers on a low voltage distribution feeder.

Isolation of microvascular endothelial cells from cadaveric corneal limbus

Limbal microvascular endothelial cells (L-MVEC) contribute to formation of the corneal-limbal stem cell niche and to neovascularization of diseased and injuries corneas. Nevertheless, despite these important roles in corneal health and disease, few attempts have been made to isolate L-MVEC with the view to studying their biology in vitro. We therefore explored the feasibility of generating primary cultures of L-MVEC from cadaveric human tissue. We commenced our study by evaluating growth conditions (MesenCult-XF system) that have been previously found to be associated with expression of the endothelial cell surface marker thrombomodulin/CD141, in crude cultures established from collagenase-digests of limbal stroma. The potential presence of L-MVEC in these cultures was examined by flow cytometry using a more specific marker for vascular endothelial cells, CD31/PECAM-1. These studies demonstrated that the presence of CD141 in crude cultures established using the MesenCult-XF system is unrelated to L-MVEC. Thus we subsequently explored the use of magnetic assisted cell sorting (MACS) for CD31 as a tool for generating cultures of L-MVEC, in conjunction with more traditional endothelial cell growth conditions. These conditions consisted of gelatin-coated tissue culture plastic and MCDB-131 medium supplemented with fetal bovine serum (10% v/v), D-glucose (10 mg/mL), epidermal growth factor (10 ng/mL), heparin (50 μg/mL), hydrocortisone (1 μg/mL) and basic fibroblast growth factor (10 ng/mL). Our studies revealed that use of endothelial growth conditions are insufficient to generate significant numbers of L-MVEC in primary cultures established from cadaveric corneal stroma. Nevertheless, through use of positive-MACS selection for CD31 we were able to routinely observe L-MVEC in cultures derived from collagenase-digests of limbal stroma. The presence of L-MVEC in these cultures was confirmed by immunostaining for von Willebrand factor (vWF) and by ingestion of acetylated low-density lipoprotein. Moreover, the vWF+ cells formed aligned cell-to-cell ‘trains’ when grown on Geltrex™. The purity of L-MVEC cultures was found to be unrelated to tissue donor age (32 to 80 years) or duration in eye bank corneal preservation medium prior to use (3 to 10 days in Optisol) (using multiple regression test). Optimal purity of L-MVEC cultures was achieved through use of two rounds of positive-MACS selection for CD31 (mean ± s.e.m, 65.0 ± 20.8%; p<0.05). We propose that human L-MVEC cultures generated through these techniques, in conjunction with other cell types, will provide a useful tool for exploring the mechanisms of blood vessel cell growth in vitro.

Convolutional Neural Network-based place recognition

Recently Convolutional Neural Networks (CNNs) have been shown to achieve state-of-the-art performance on various classification tasks. In this paper, we present for the first time a place recognition technique based on CNN models, by combining the powerful features learnt by CNNs with a spatial and sequential filter. Applying the system to a 70 km benchmark place recognition dataset we achieve a 75% increase in recall at 100% precision, significantly outperforming all previous state of the art techniques. We also conduct a comprehensive performance comparison of the utility of features from all 21 layers for place recognition, both for the benchmark dataset and for a second dataset with more significant viewpoint changes.

A hybrid quality function deployment and cybernetic analytic network process model for project manager selection

Identifying appropriate decision criteria and making optimal decisions in a structured way is a complex process. This paper presents an approach for doing this in the form of a hybrid Quality Function Deployment (QFD) and Cybernetic Analytic Network Process (CANP) model for project manager selection. This involves the use of QFD to translate the owner's project management expectations into selection criteria and the CANP to weight the expectations and selection criteria. The supermatrix approach then prioritises the candidates with respect to the overall decision-making goal. A case study is used to demonstrate the use of the model in selecting a renovation project manager. This involves the development of 18 selection criteria in response to the owner's three main expectations of time, cost and quality.

Facebook for adults ? A longitudinal study of MBA student’s use of an enterprise social network for collaborative learning

The rapid pace of social media means that our understanding of the way in which it facilitates the learning process continues to lag. The findings of a longitudinal study of an executive MBA cohort over the period of eight months in their use of the social media application is presented. Over time the ownership and use of the Yammer site shifted to become student driven and facilitated. The motivations behind the site’s use, perceived advantages and disadvantages and changes in usage patterns are documented. The case provides a useful insight into the way in which students used this technology to facilitate their learning goals and how patterns of behaviour changed in response to the changing needs of the cohort.

A Hybrid Queue-based Bayesian Network framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an R2 goodness of fit of 0.9994 and 0.9982 respectively over a 10 h test period. The utility of the framework is demonstrated on a number of usage scenarios including causal analysis and ‘what-if’ analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

A supervisory load-leveling approach to improve the voltage profile in distribution network

This paper suggests a supervisory control for storage units to provide load leveling in distribution networks. This approach coordinates storage units to charge during high generation and discharge during peak load times, while utilized to improve the network voltage profile indirectly. The aim of this control strategy is to establish power sharing on a pro rata basis for storage units. As a case study, a practical distribution network with 30 buses is simulated and the results are provided.

Estimating the impact of reduced inertia on frequency stability due to large-scale wind penetration in Australian electricity network

Large-scale integration of non-inertial generators such as wind farms will create frequency stability issues due to reduced system inertia. Inertia based frequency stability study is important to predict the performance of power system with increased level of renewables. This paper focuses on the impact large-scale wind penetration on frequency stability of the Australian Power Network. MATLAB simulink is used to develop a frequency based dynamic model utilizing the network data from a simplified 14-generator Australian power system. The loss of generation is modeled as the active power disturbance and minimum inertia required to maintain the frequency stability is determined for five-area power system.

The application of social network analysis in the construction industry of Hong Kong

The Hong Kong construction industry is currently facing ageing problem and labour shortage. There are opportunities for employing ethnic minority construction workers to join this hazardous industry. These ethnic minority workers are prone to accidents due to communication barriers. Safety communication is playing an important role for avoiding the accidents on construction sites. However, the ethnic minority workers are not very fluent in the local language and facing safety communication problems while working with local workers. Social network analysis (SNA), being an effective tool to identify the safety communication flow on the construction site, is used to attain the measures of safety communication like centrality, density and betweenness within the ethnic minorities and local workers, and to generate sociograms that visually represent communication pattern within the effective and ineffective safety networks. The aim of this paper is to present the application of SNA for improving the safety communication of ethnic minorities in the construction industry of Hong Kong. The paper provides the theoretical background of SNA approaches for the data collection and analysis using the software UCINET and NetDraw, to determine the predominant safety communication network structure and pattern of ethnic minorities on site.

Social network resilience following organisational change

This paper presents two key findings from a longitudinal study examining the dynamics of social networks during organisational change. One, the degree to which users seek new sources of information while adapting to the change. Two, the degree to which social networks display structural resilience when undergoing significant structural and technological change. Users reported an increase in advice ties post-implementation, however a proportionally higher increase in ties within their work group compared to the wider network was identified. The results also supported the supposition that while IT driven change may initially disrupt social networks some networks possess a high degree of resilience, with key players reasserting their original positions of influence following the initial phase of change related disruption.