Characterising an ECG signal using statistical modelling : a feasibility study

For clinical use, in electrocardiogram (ECG) signal analysis it is important to detect not only the centre of the P wave, the QRS complex and the T wave, but also the time intervals, such as the ST segment. Much research focused entirely on qrs complex detection, via methods such as wavelet transforms, spline fitting and neural networks. However, drawbacks include the false classification of a severe noise spike as a QRS complex, possibly requiring manual editing, or the omission of information contained in other regions of the ECG signal. While some attempts were made to develop algorithms to detect additional signal characteristics, such as P and T waves, the reported success rates are subject to change from person-to-person and beat-to-beat. To address this variability we propose the use of Markov-chain Monte Carlo statistical modelling to extract the key features of an ECG signal and we report on a feasibility study to investigate the utility of the approach. The modelling approach is examined with reference to a realistic computer generated ECG signal, where details such as wave morphology and noise levels are variable.

Development of a Remote Sensing Core Curriculum submitted for the sessions on educational initiatives in Geoscience and Remote Sensing

A Remote Sensing Core Curriculum (RSCC) development project is currently underway. This project is being conducted under the auspices of the National Center for Geographic Information and Analysis (NCGIA). RSCC is an outgrowth of the NCGIA GIS Core Curriculum project. It grew out of discussions begun at NCGIA, Initiative 12 (I-12): 'Integration of Remote Sensing and Geographic Information Systems'. This curriculum development project focuses on providing professors, teachers and instructors in undergraduate and graduate institutions with course materials from experts in specific subject matter for areas use in the class room.

Remote sensing utility expansion through Earth Portal internet browser

A modular, graphic-oriented Internet browser has been developed to enable non-technical client access to a literal spinning world of information and remotely sensed. The Earth Portal (www.earthportal.net) uses the ManyOne browser (www.manyone.net) to provide engaging point and click views of the Earth fully tessellated with remotely sensed imagery and geospatial data. The ManyOne browser technology use Mozilla with embedded plugins to apply multiple 3-D graphics engines, e.g. ArcGlobe or GeoFusion, that directly link with the open-systems architecture of the geo-spatial infrastructure. This innovation allows for rendering of satellite imagery directly over the Earth's surface and requires no technical training by the web user. Effective use of this global distribution system for the remote sensing community requires a minimal compliance with protocols and standards that have been promoted by NSDI and other open-systems standards organizations.

High penetration of rooftop photovoltaic cells in low voltage distribution networks : voltage imbalance and improvement

Installation of domestic rooftop photovoltaic cells (PVs) is increasing due to feed–in tariff and motivation driven by environmental concerns. Even though the increase in the PV installation is gradual, their locations and ratings are often random. Therefore, such single–phase bi–directional power flow caused by the residential customers can have adverse effect on the voltage imbalance of a three–phase distribution network. In this chapter, a voltage imbalance sensitivity analysis and stochastic evaluation are carried out based on the ratings and locations of single–phase grid–connected rooftop PVs in a residential low voltage distribution network. The stochastic evaluation, based on Monte Carlo method, predicts a failure index of non–standard voltage imbalance in the network in presence of PVs. Later, the application of series and parallel custom power devices are investigated to improve voltage imbalance problem in these feeders. In this regard, first, the effectiveness of these two custom power devices is demonstrated vis–à–vis the voltage imbalance reduction in feeders containing rooftop PVs. Their effectiveness is investigated from the installation location and rating points of view. Later, a Monte Carlo based stochastic analysis is utilized to investigate their efficacy for different uncertainties of load and PV rating and location in the network. This is followed by demonstrating the dynamic feasibility and stability issues of applying these devices in the network.

THE quest for alpha : can artificial neural networks help?

The application of artificial neural networks (ANN) in finance is relatively new area of research. We employed ANNs that used both fundamental and technical inputs to predict future prices of widely held Australian stocks and used these predicted prices for stock portfolio selection over a 10-year period (2001-2011). We found that the ANNs generally do well in predicting the direction of stock price movements. The stock portfolios selected by the ANNs with median accuracy are able to generate positive alpha over the 10-year period. More importantly, we found that a portfolio based on randomly selected network configuration had zero chance of resulting in a significantly negative alpha but a 27% chance of yielding a significantly positive alpha. This is in stark contrast to the findings of the research on mutual fund performance where active fund managers with negative alphas outnumber those with positive alphas.

Critical analysis of spam prevention techniques

E-mail spam has remained a scourge and menacing nuisance for users, internet and network service operators and providers, in spite of the anti-spam techniques available; and spammers are relentlessly circumventing these anti-spam techniques embedded or installed in form of software products on both client and server sides of both fixed and mobile devices to their advantage. This continuous evasion degrades the capabilities of these anti-spam techniques as none of them provides a comprehensive reliable solution to the problem posed by spam and spammers. Major problem for instance arises when these anti-spam techniques misjudge or misclassify legitimate emails as spam (false positive); or fail to deliver or block spam on the SMTP server (false negative); and the spam passes-on to the receiver, and yet this server from where it originates does not notice or even have an auto alert service to indicate that the spam it was designed to prevent has slipped and moved on to the receiver’s SMTP server; and the receiver’s SMTP server still fail to stop the spam from reaching user’s device and with no auto alert mechanism to inform itself of this inability; thus causing a staggering cost in loss of time, effort and finance. This paper takes a comparative literature overview of some of these anti-spam techniques, especially the filtering technological endorsements designed to prevent spam, their merits and demerits to entrench their capability enhancements, as well as evaluative analytical recommendations that will be subject to further research.

Introduction to the special issue on next generation network architectures, protocols, theory, systems and applications

This special issue of Networking Science focuses on Next Generation Network (NGN) that enables the deployment of access independent services over converged fixed and mobile networks. NGN is a packet-based network and uses the Internet protocol (IP) to transport the various types of traffic (voice, video, data and signalling). NGN facilitates easy adoption of distributed computing applications by providing high speed connectivity in a converged networked environment. It also makes end user devices and applications highly intelligent and efficient by empowering them with programmability and remote configuration options. However, there are a number of important challenges in provisioning next generation network technologies in a converged communication environment. Some preliminary challenges include those that relate to QoS, switching and routing, management and control, and security which must be addressed on an urgent or emergency basis. The consideration of architectural issues in the design and pro- vision of secure services for NGN deserves special attention and hence is the main theme of this special issue.

An algebraic approach for determination of DG parameters to support voltage profiles in radial distribution networks

Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of Distributed Generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. This paper addresses the issue of improving the network voltage profile in distribution systems by installing a DG of the most suitable size, at a suitable location. An analytical approach is developed based on algebraic equations for uniformly distributed loads to determine the optimal operation, size and location of the DG in order to achieve required levels of network voltage. The developed method is simple to use for conceptual design and analysis of distribution system expansion with a DG and suitable for a quick estimation of DG parameters (such as optimal operating angle, size and location of a DG system) in a radial network. A practical network is used to verify the proposed technique and test results are presented.

Optimising offsets and bandwidths in vehicle traffic networks

Bandwidths and offsets are important components in vehicle traffic control strategies. This article proposes new methods for quantifying and selecting them. Bandwidth is the amount of green time available for vehicles to travel through adjacent intersections without the requirement to stop at the second traffic light. The offset is the difference between the starting-time of ``green'' periods at two adjacent intersections, along a given route. The core ideas in this article were developed during the 2013 Maths and Industry Study Group in Brisbane, Australia. Analytical expressions for computing bandwidth, as a function of offset, are developed. An optimisation model, for selecting offsets across an arterial, is proposed. Arterial roads were focussed upon, as bandwidth and offset have a greater impact on these types of road as opposed to a full traffic network. A generic optimisation-simulation approach is also proposed to refine an initial starting solution, according to a specified metric. A metric that reflects the number of stops, and the distance between stops, is proposed to explicitly reduce the dissatisfaction of road users, and to implicitly reduce fuel consumption and emissions. Conceptually the optimisation-simulation approach is superior as it handles real-life complexities and is a global optimisation approach. The models and equations in this article can be used in road planning and traffic control.

At home on the outstation : barriers to home Internet in remote Indigenous communities

Indigenous Australians living in remote areas have little access to the Internet and make little use of it. This article investigates the various dimensions of Internet take-up in remote Indigenous communities in Australia and considers the implications for broadband policy. It focuses specifically on the circumstances and experiences of three remote Indigenous communities in central Australia. Residents in these communities provided significant insight into the social, economic and cultural aspects of communications access and use. This evidence is used to examine the drivers and barriers to home Internet for remote Indigenous communities and to discuss a complex set of issues, including: the dynamics of remote living, economic priorities, cultural engagement with technology, and the characteristics of domestic life in remote Indigenous communities.

Out of their minds: legal theory in neural networks

This paper examines the use of connectionism (neural networks) in modelling legal reasoning. I discuss how the implementations of neural networks have failed to account for legal theoretical perspectives on adjudication. I criticise the use of neural networks in law, not because connectionism is inherently unsuitable in law, but rather because it has been done so poorly to date. The paper reviews a number of legal theories which provide a grounding for the use of neural networks in law. It then examines some implementations undertaken in law and criticises their legal theoretical naïvete. It then presents a lessons from the implementations which researchers must bear in mind if they wish to build neural networks which are justified by legal theories.

Privacy by design for social networks

This research has established a new privacy framework, privacy model, and privacy architecture to create more transparent privacy for social networking users. The architecture is designed into three levels: Business, Data, and Technology, which is based on The Open Group Architecture Framework (TOGAF®). This framework and architecture provides a novel platform for investigating privacy in Social Networks (SNs). This approach mitigates many current SN privacy issues, and leads to a more controlled form of privacy assessment. Ultimately, more privacy will encourage more connections between people across SN services.