The state-of-the-art in personalized recommender systems for social networking

With the explosion of Web 2.0 application such as blogs, social and professional networks, and various other types of social media, the rich online information and various new sources of knowledge flood users and hence pose a great challenge in terms of information overload. It is critical to use intelligent agent software systems to assist users in finding the right information from an abundance of Web data. Recommender systems can help users deal with information overload problem efficiently by suggesting items (e.g., information and products) that match users’ personal interests. The recommender technology has been successfully employed in many applications such as recommending films, music, books, etc. The purpose of this report is to give an overview of existing technologies for building personalized recommender systems in social networking environment, to propose a research direction for addressing user profiling and cold start problems by exploiting user-generated content newly available in Web 2.0.

On the impact of the "linguistic turn" on research in information systems

The linguistic turn within philosophy has recently gained increased attention within social sciences. It can be seen as an attempt to investigate traditional philosophical problems by analysing the linguistic expressions used for these investigations. More generally, the phenomenon of language itself must be considered because of its (constitutional) impact on the investigation of phenomena in social sciences. In order to understand the consequences of the linguistic turn, its origins in philosophy are important and will be discussed. Within social sciences the linguistic turn already had significant impact. As an example, we will therefore discuss what directions the linguistic turn enabled for organizational analysis. Information Systems as a discipline must face the consequences of the linguistic turn as well. We will discuss how the linguistic framework introduced impacts the development of knowledge management and that of managerial and organizational support systems. This example shows what different perspectives the linguistic turn can provide for investigations within Information Systems. In addition, we will briefly outline the impact of the linguistic turn with respect to methodologies in Information Systems research.

Benefiting white noise in developing feedforward active noise control systems

In many applications of active noise control (ANC), an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to adjust the secondary path estimation. Comparative simulation results shown in this paper indicate effectiveness of the proposed method.

Novel channel tracking and equalization methods in MU-MIMO-OFDM systems

The methodology undertaken, the channel model and the system model created for developing a novel adaptive equalization method and a novel channel tracking method for uplink of MU-MIMO-OFDM systems is presented in this paper. The results show that the channel tracking method works with 97% accuracy, while the training-based initial channel estimation method shows poor performance in estimating the actual channel comparatively.

Measurement, modelling and capacity analysis for novel, fixed multi-user single-antenna MIMO-OFDM system, in rural environments

High-speed broadband internet access is widely recognised as a catalyst to social and economic development. However, the provision of broadband Internet services with the existing solutions to rural population, scattered over an extensive geographical area, remains both an economic and technical challenge. As a feasible solution, the Commonwealth Scientific and Industrial Research Organization (CSIRO) proposed a highly spectrally efficient, innovative and cost-effective fixed wireless broadband access technology, which uses analogue TV frequency spectrum and Multi-User MIMO (MUMIMO) technology with Orthogonal-Frequency-Division-Multiplexing (OFDM). MIMO systems have emerged as a promising solution for the increasing demand of higher data rates, better quality of service, and higher network capacity. However, the performance of MIMO systems can be significantly affected by different types of propagation environments e.g., indoor, outdoor urban, or outdoor rural and operating frequencies. For instance, large spectral efficiencies associated with MIMO systems, which assume a rich scattering environment in urban environments, may not be valid for all propagation environments, such as outdoor rural environments, due to the presence of less scatterer densities. Since this is the first time a MU-MIMO-OFDM fixed broadband wireless access solution is deployed in a rural environment, questions from both theoretical and practical standpoints arise; For example, what capacity gains are available for the proposed solution under realistic rural propagation conditions?. Currently, no comprehensive channel measurement and capacity analysis results are available for MU-MIMO-OFDM fixed broadband wireless access systems which employ large scale multiple antennas at the Access Point (AP) and analogue TV frequency spectrum in rural environments. Moreover, according to the literature, no deterministic MU-MIMO channel models exist that define rural wireless channels by accounting for terrain effects. This thesis fills the aforementioned knowledge gaps with channel measurements, channel modeling and comprehensive capacity analysis for MU-MIMO-OFDM fixed wireless broadband access systems in rural environments. For the first time, channel measurements were conducted in a rural farmland near Smithton, Tasmania using CSIRO's broadband wireless access solution. A novel deterministic MU-MIMO-OFDM channel model, which can be used for accurate performance prediction of rural MUMIMO channels with dominant Line-of-Sight (LoS) paths, was developed under this research. Results show that the proposed solution can achieve 43.7 bits/s/Hz at a Signal-to- Noise Ratio (SNR) of 20 dB in rural environments. Based on channel measurement results, this thesis verifies that the deterministic channel model accurately predicts channel capacity in rural environments with a Root Mean Square (RMS) error of 0.18 bits/s/Hz. Moreover, this study presents a comprehensive capacity analysis of rural MU-MIMOOFDM channels using experimental, simulated and theoretical models. Based on the validated deterministic model, further investigations on channel capacity and the eects of capacity variation, with different user distribution angles (θ) around the AP, were analysed. For instance, when SNR = 20dB, the capacity increases from 15.5 bits/s/Hz to 43.7 bits/s/Hz as θ increases from 10° to 360°. Strategies to mitigate these capacity degradation effects are also presented by employing a suitable user grouping method. Outcomes of this thesis have already been used by CSIRO scientists to determine optimum user distribution angles around the AP, and are of great significance for researchers and MU-MUMO-OFDM system developers to understand the advantages and potential capacity gains of MU-MIMO systems in rural environments. Also, results of this study are useful to further improve the performance of MU-MIMO-OFDM systems in rural environments. Ultimately, this knowledge contribution will be useful in delivering efficient, cost-effective high-speed wireless broadband systems that are tailor-made for rural environments, thus, improving the quality of life and economic prosperity of rural populations.

A basis for instrusion detection in distributed systems using kernel-level data tainting

This project was a step forward in developing intrusion detection systems in distributed environments such as web services. It investigates a new approach of detection based on so-called "taint-marking" techniques and introduces a theoretical framework along with its implementation in the Linux kernel.

Prediction and proactivity in real-time interactive music systems

We advocate for the use of predictive techniques in interactive computer music systems. We suggest that the inclusion of prediction can assist in the design of proactive rather than reactive computational performance partners. We summarize the significant role prediction plays in human musical decisions, and the only modest use of prediction in interactive music systems to date. After describing how we are working toward employing predictive processes in our own metacreation software we reflect on future extensions to these approaches.

Role of electromechanical wave propagation in power systems

In a large interconnected power system, disturbances initiated by a fault or other events cause acceleration in the generator rotors with respect to their synchronous reference frame. This acceleration of rotors can be described by two different dynamic phenomena, as shown in existing literature. One of the phenomena is simultaneous acceleration and the other is electromechanical wave propagation, which is characterized by travelling waves in terms of a wave equation. This paper demonstrates that depending on the structure of the system, the exhibited dynamic response will be dominated by one phenomenon or the other or a mixture of both. Two system structures of choice are examined, with each structure exemplifying each phenomenon present to different degrees in their dynamic responses. Prediction of dominance of either dynamic phenomenon in a particular system can be determined by taking into account the relative sizes of the values of its reduced admittance matrix.

A novel real time pricing scheme for demand response in residential distribution systems

Price based technique is one way to handle increase in peak demand and deal with voltage violations in residential distribution systems. This paper proposes an improved real time pricing scheme for residential customers with demand response option. Smart meters and in-home display units are used to broadcast the price and appropriate load adjustment signals. Customers are given an opportunity to respond to the signals and adjust the loads. This scheme helps distribution companies to deal with overloading problems and voltage issues in a more efficient way. Also, variations in wholesale electricity prices are passed on to electricity customers to take collective measure to reduce network peak demand. It is ensured that both customers and utility are benefitted by this scheme.

Systematic evaluation of GoSoapBox in tertiary education : a student response system for improving learning experiences and outcomes

There is currently a wide range of research into the recent introduction of student response systems in higher education and tertiary settings (Banks 2006; Kay and Le Sange, 2009; Beatty and Gerace 2009; Lantz 2010; Sprague and Dahl 2009). However, most of this pedagogical literature has generated ‘how to’ approaches regarding the use of ‘clickers’, keypads, and similar response technologies. There are currently no systematic reviews on the effectiveness of ‘GoSoapBox’ – a more recent, and increasingly popular student response system – for its capacity to enhance critical thinking, and achieve sustained learning outcomes. With rapid developments in teaching and learning technologies across all undergraduate disciplines, there is a need to obtain comprehensive, evidence-based advice on these types of technologies, their uses, and overall efficacy. This paper addresses this current gap in knowledge. Our teaching team, in an undergraduate Sociology and Public Health unit at the Queensland University of Technology (QUT), introduced GoSoapBox as a mechanism for discussing controversial topics, such as sexuality, gender, economics, religion, and politics during lectures, and to take opinion polls on social and cultural issues affecting human health. We also used this new teaching technology to allow students to interact with each other during class – both on both social and academic topics – and to generate discussions and debates during lectures. The paper reports on a data-driven study into how this interactive online tool worked to improve engagement and the quality of academic work produced by students. This paper will firstly, cover the recent literature reviewing student response systems in tertiary settings. Secondly, it will outline the theoretical framework used to generate this pedagogical research. In keeping with the social and collaborative features of Web 2.0 technologies, Bandura’s Social Learning Theory (SLT) will be applied here to investigate the effectiveness of GoSoapBox as an online tool for improving learning experiences and the quality of academic output by students. Bandura has emphasised the Internet as a tool for ‘self-controlled learning’ (Bandura 2001), as it provides the education sector with an opportunity to reconceptualise the relationship between learning and thinking (Glassman & Kang 2011). Thirdly, we describe the methods used to implement the use of GoSoapBox in our lectures and tutorials, and which aspects of the technology we drew on for learning purposes, as well as the methods for obtaining feedback from the students about the effectiveness or otherwise of this tool. Fourthly, we report cover findings from an examination of all student/staff activity on GoSoapBox as well as reports from students about the benefits and limitations of it as a learning aid. We then display a theoretical model that is produced via an iterative analytical process between SLT and our data analysis for use by academics and teachers across the undergraduate curriculum. The model has implications for all teachers considering the use of student response systems to improve the learning experiences of their students. Finally, we consider some of the negative aspects of GoSoapBox as a learning aid.

Cross-layer design for traffic management in wireless networked control systems

Wireless networked control systems (WNCSs) have been increasingly deployed in industrial applications. As they require timely data packet transmissions, it is difficult to make efficient use of the limited channel resources, particularly in contention based wireless networks in the layered network architecture. Aiming to maintain the WNCSs under critical real-time traffic condition at which the WNCSs marginally meet the real-time requirements, a cross-layer design (CLD) approach is presented in this paper to adaptively adjust the control period to achieve improved channel utilization while still maintaining effective and timely packet transmissions. The effectiveness of the proposed approach is demonstrated through simulation studies.

Optimal distributed generation placement in radial distribution systems

Distributed generation (DG) resources are commonly used in the electric systems to obtain minimum line losses, as one of the benefits of DG, in radial distribution systems. Studies have shown the importance of appropriate selection of location and size of DGs. This paper proposes an analytical method for solving optimal distributed generation placement (ODGP) problem to minimize line losses in radial distribution systems using loss sensitivity factor (LSF) based on bus-injection to branch-current (BIBC) matrix. The proposed method is formulated and tested on 12 and 34 bus radial distribution systems. The classical grid search algorithm based on successive load flows is employed to validate the results. The main advantages of the proposed method as compared with the other conventional methods are the robustness and no need to calculate and invert large admittance or Jacobian matrices. Therefore, the simulation time and the amount of computer memory, required for processing data especially for the large systems, decreases.

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.

Using a smartphone application for customer-centric banking

The banking industry is under pressure. In order to compete, banks should adapt to concentrating on the specific customer needs, following an outside-in perspective. This paper presents the design of a business model for banks that considers this development by providing flexible and comprehensive support for retail banking clients. It is demonstrated that the identification of customer processes and the consequent alignment of banking services to those processes implies great potential to increase customer retention in banking. It will be shown that information technology – especially smartphones – can serve as an interface between customer and suppliers to enable an alignment of offerings to customer processes. This approach enables the integration of banks into their customers’ lifestyle, creating emotional value added, improving the personal relationship and the customers’ affiliation with the bank. The paper presents the design of such a customer-process-centric smartphone application and derives success factors for implementation.

Tensor-based item recommendation using probabilistic ranking in social tagging systems

A common problem with the use of tensor modeling in generating quality recommendations for large datasets is scalability. In this paper, we propose the Tensor-based Recommendation using Probabilistic Ranking method that generates the reconstructed tensor using block-striped parallel matrix multiplication and then probabilistically calculates the preferences of user to rank the recommended items. Empirical analysis on two real-world datasets shows that the proposed method is scalable for large tensor datasets and is able to outperform the benchmarking methods in terms of accuracy.