Predictive compensation for variable network delays and packet losses in networked control systems

Networked control systems (NCSs) offer many advantages over conventional control; however, they also demonstrate challenging problems such as network-induced delay and packet losses. This paper proposes an approach of predictive compensation for simultaneous network-induced delays and packet losses. Different from the majority of existing NCS control methods, the proposed approach addresses co-design of both network and controller. It also alleviates the requirements of precise process models and full understanding of NCS network dynamics. For a series of possible sensor-to-actuator delays, the controller computes a series of corresponding redundant control values. Then, it sends out those control values in a single packet to the actuator. Once receiving the control packet, the actuator measures the actual sensor-to-actuator delay and computes the control signals from the control packet. When packet dropout occurs, the actuator utilizes past control packets to generate an appropriate control signal. The effectiveness of the approach is demonstrated through examples.

Social network analysis of an online dating network

Online social networks can be found everywhere from chatting websites like MSN, blogs such as MySpace to social media such as YouTube and second life. Among them, there is one interesting type of online social networks, online dating network that is growing fast. This paper analyzes an online dating network from social network analysis point of view. Observations are made and results are obtained in order to suggest a better recommendation system for people-to-people networks.

Complexity, evolution, and the structure of demand

This chapter argues that evolutionary economics should be founded upon complex systems theory rather than neo-Darwinian analogies concerning natural selection, which focus on supply side considerations and competition amongst firms and technologies. It suggests that conceptions such as production and consumption functions should be replaced by network representations, in which the preferences or, more correctly, the aspirations of consumers are fundamental and, as such, the primary drivers of economic growth. Technological innovation is viewed as a process that is intermediate between these aspirational networks, and the organizational networks in which goods and services are produced. Consumer knowledge becomes at least as important as producer knowledge in determining how economic value is generated. It becomes clear that the stability afforded by connective systems of rules is essential for economic flexibility to exist, but that too many rules result in inert and structurally unstable states. In contrast, too few rules result in a more stable state, but at a low level of ordered complexity. Economic evolution from this perspective is explored using random and scale free network representations of complex systems.

Using strategic movement to calibrate a neural compass : a spiking network for tracking head direction in rats and robots

The head direction (HD) system in mammals contains neurons that fire to represent the direction the animal is facing in its environment. The ability of these cells to reliably track head direction even after the removal of external sensory cues implies that the HD system is calibrated to function effectively using just internal (proprioceptive and vestibular) inputs. Rat pups and other infant mammals display stereotypical warm-up movements prior to locomotion in novel environments, and similar warm-up movements are seen in adult mammals with certain brain lesion-induced motor impairments. In this study we propose that synaptic learning mechanisms, in conjunction with appropriate movement strategies based on warm-up movements, can calibrate the HD system so that it functions effectively even in darkness. To examine the link between physical embodiment and neural control, and to determine that the system is robust to real-world phenomena, we implemented the synaptic mechanisms in a spiking neural network and tested it on a mobile robot platform. Results show that the combination of the synaptic learning mechanisms and warm-up movements are able to reliably calibrate the HD system so that it accurately tracks real-world head direction, and that calibration breaks down in systematic ways if certain movements are omitted. This work confirms that targeted, embodied behaviour can be used to calibrate neural systems, demonstrates that ‘grounding’ of modeled biological processes in the real world can reveal underlying functional principles (supporting the importance of robotics to biology), and proposes a functional role for stereotypical behaviours seen in infant mammals and those animals with certain motor deficits. We conjecture that these calibration principles may extend to the calibration of other neural systems involved in motion tracking and the representation of space, such as grid cells in entorhinal cortex.

A descriptive approach for power system stability and security assessment

Power system dynamic analysis and security assessment are becoming more significant today due to increases in size and complexity from restructuring, emerging new uncertainties, integration of renewable energy sources, distributed generation, and micro grids. Precise modelling of all contributed elements/devices, understanding interactions in detail, and observing hidden dynamics using existing analysis tools/theorems are difficult, and even impossible. In this chapter, the power system is considered as a continuum and the propagated electomechanical waves initiated by faults and other random events are studied to provide a new scheme for stability investigation of a large dimensional system. For this purpose, the measured electrical indices (such as rotor angle and bus voltage) following a fault in different points among the network are used, and the behaviour of the propagated waves through the lines, nodes, and buses is analyzed. The impact of weak transmission links on a progressive electromechanical wave using energy function concept is addressed. It is also emphasized that determining severity of a disturbance/contingency accurately, without considering the related electromechanical waves, hidden dynamics, and their properties is not secure enough. Considering these phenomena takes heavy and time consuming calculation, which is not suitable for online stability assessment problems. However, using a continuum model for a power system reduces the burden of complex calculations

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

Leveraging the network information for evaluating answer quality in a collaborative question answering portal

Collaborative question answering (cQA) portals such as Yahoo! Answers allow users as askers or answer authors to communicate, and exchange information through the asking and answering of questions in the network. In their current set-up, answers to a question are arranged in chronological order. For effective information retrieval, it will be advantageous to have the users’ answers ranked according to their quality. This paper proposes a novel approach of evaluating and ranking the users’answers and recommending the top-n quality answers to information seekers. The proposed approach is based on a user-reputation method which assigns a score to an answer reflecting its answer author’s reputation level in the network. The proposed approach is evaluated on a dataset collected from a live cQA, namely, Yahoo! Answers. To compare the results obtained by the non-content-based user-reputation method, experiments were also conducted with several content-based methods that assign a score to an answer reflecting its content quality. Various combinations of non-content and content-based scores were also used in comparing results. Empirical analysis shows that the proposed method is able to rank the users’ answers and recommend the top-n answers with good accuracy. Results of the proposed method outperform the content-based methods, various combinations, and the results obtained by the popular link analysis method, HITS.

Influence of rainfall and catchment characteristics on urban stormwater quality

This thesis presents the outcomes of a comprehensive research study undertaken to investigate the influence of rainfall and catchment characteristics on urban stormwater quality. The knowledge created is expected to contribute to a greater understanding of urban stormwater quality and thereby enhance the design of stormwater quality treatment systems. The research study was undertaken based on selected urban catchments in Gold Coast, Australia. The research methodology included field investigations, laboratory testing, computer modelling and data analysis. Both univariate and multivariate data analysis techniques were used to investigate the influence of rainfall and catchment characteristics on urban stormwater quality. The rainfall characteristics investigated included average rainfall intensity and rainfall duration whilst catchment characteristics included land use, impervious area percentage, urban form and pervious area location. The catchment scale data for the analysis was obtained from four residential catchments, including rainfall-runoff records, drainage network data, stormwater quality data and land use and land cover data. Pollutants build-up samples were collected from twelve road surfaces in residential, commercial and industrial land use areas. The relationships between rainfall characteristics, catchment characteristics and urban stormwater quality were investigated based on residential catchments and then extended to other land uses. Based on the influence rainfall characteristics exert on urban stormwater quality, rainfall events can be classified into three different types, namely, high average intensity-short duration (Type 1), high average intensity-long duration (Type 2) and low average intensity-long duration (Type 3). This provides an innovative approach to conventional modelling which does not commonly relate stormwater quality to rainfall characteristics. Additionally, it was found that the threshold intensity for pollutant wash-off from urban catchments is much less than for rural catchments. High average intensity-short duration rainfall events are cumulatively responsible for the generation of a major fraction of the annual pollutants load compared to the other rainfall event types. Additionally, rainfall events less than 1 year ARI such as 6- month ARI should be considered for treatment design as they generate a significant fraction of the annual runoff volume and by implication a significant fraction of the pollutants load. This implies that stormwater treatment designs based on larger rainfall events would not be feasible in the context of cost-effectiveness, efficiency in treatment performance and possible savings in land area needed. This also suggests that the simulation of long-term continuous rainfall events for stormwater treatment design may not be needed and that event based simulations would be adequate. The investigations into the relationship between catchment characteristics and urban stormwater quality found that other than conventional catchment characteristics such as land use and impervious area percentage, other catchment characteristics such as urban form and pervious area location also play important roles in influencing urban stormwater quality. These outcomes point to the fact that the conventional modelling approach in the design of stormwater quality treatment systems which is commonly based on land use and impervious area percentage would be inadequate. It was also noted that the small uniformly urbanised areas within a larger mixed catchment produce relatively lower variations in stormwater quality and as expected lower runoff volume with the opposite being the case for large mixed use urbanised catchments. Therefore, a decentralised approach to water quality treatment would be more effective rather than an "end-of-pipe" approach. The investigation of pollutants build-up on different land uses showed that pollutant build-up characteristics vary even within the same land use. Therefore, the conventional approach in stormwater quality modelling, which is based solely on land use, may prove to be inappropriate. Industrial land use has relatively higher variability in maximum pollutant build-up, build-up rate and particle size distribution than the other two land uses. However, commercial and residential land uses had relatively higher variations of nutrients and organic carbon build-up. Additionally, it was found that particle size distribution had a relatively higher variability for all three land uses compared to the other build-up parameters. The high variability in particle size distribution for all land uses illustrate the dissimilarities associated with the fine and coarse particle size fractions even within the same land use and hence the variations in stormwater quality in relation to pollutants adsorbing to different sizes of particles.

The development of a conceptual framework for a district 4-Year Pavement Management Plan, implementation of network-level project screening process

The Texas Department of Transportation (TxDOT) is concerned about the widening gap between preservation needs and available funding. Funding levels are not adequate to meet the preservation needs of the roadway network; therefore projects listed in the 4-Year Pavement Management Plan must be ranked to determine which projects should be funded now and which can be postponed until a later year. Currently, each district uses locally developed methods to prioritize projects. These ranking methods have relied on less formal qualitative assessments based on engineers’ subjective judgment. It is important for TxDOT to have a 4-Year Pavement Management Plan that uses a transparent, rational project ranking process. The objective of this study is to develop a conceptual framework that describes the development of the 4-Year Pavement Management Plan. It can be largely divided into three Steps; 1) Network-Level project screening process, 2) Project-Level project ranking process, and 3) Economic Analysis. A rational pavement management procedure and a project ranking method accepted by districts and the TxDOT administration will maximize efficiency in budget allocations and will potentially help improve pavement condition. As a part of the implementation of the 4-Year Pavement Management Plan, the Network-Level Project Screening (NLPS) tool including the candidate project identification algorithm and the preliminary project ranking matrix was developed. The NLPS has been used by the Austin District Pavement Engineer (DPE) to evaluate PMIS (Pavement Management Information System) data and to prepare a preliminary list of candidate projects for further evaluation.

Tunable decoupling and matching network for diversity enhancement of closely spaced antennas

A tunable decoupling and matching network (DMN) for a closely spaced two-element antenna array is presented. The DMN achieves perfect matching for the eigenmodes of the array and thus simultaneously isolates and matches the system ports while keeping the circuit small. Arrays of closely spaced wire and microstrip monopole pairs are used to demonstrate the proposed DMN. It is found that monopoles with different lengths can be used for the design frequency by using this DMN, which increases the design flexibility. This property also enables frequency tuning using the DMN only without having to change the length of the antennas. The proposed DMN uses only one varactor to achieve a tuning range of 18.8% with both return loss and isolation better than 10-dB when the spacing between the antenna is 0.05λ. When the spacing increases to 0.1λ, the simulated tuning range is more than 60%.

Integrating electrical vehicles to demand side response scheme in Queensland Australia

Depleting fossil fuel resources and increased accumulation of greenhouse gas emissions are increasingly making electrical vehicles (EV) attractive option for the transportation sector. However uncontrolled random charging and discharging of EVs may aggravate the problems of an already stressed system during the peak demand and cause voltage problems during low demand. This paper develops a demand side response scheme for properly integrating EVs in the Electrical Network. The scheme enacted upon information on electricity market conditions regularly released by the Australian Energy Market Operator (AEMO) on the internet. The scheme adopts Internet relays and solid state switches to cycle charging and discharging of EVs. Due to the pending time-of-use and real-price programs, financial benefits will represent driving incentives to consumers to implement the scheme. A wide-scale dissemination of the scheme is expected to mitigate excessive peaks on the electrical network with all associated technical, economic and social benefits.

Optimising a coal rail network under capacity constraints

This research deals with an innovative methodology for optimising the coal train scheduling problem. Based on our previously published work, generic solution techniques are developed by utilising a “toolbox” of standard well-solved standard scheduling problems. According to our analysis, the coal train scheduling problem can be basically modelled a Blocking Parallel-Machine Job-Shop Scheduling (BPMJSS) problem with some minor constraints. To construct the feasible train schedules, an innovative constructive algorithm called the SLEK algorithm is proposed. To optimise the train schedule, a three-stage hybrid algorithm called the SLEK-BIH-TS algorithm is developed based on the definition of a sophisticated neighbourhood structure under the mechanism of the Best-Insertion-Heuristic (BIH) algorithm and Tabu Search (TS) metaheuristic algorithm. A case study is performed for optimising a complex real-world coal rail system in Australia. A method to calculate the lower bound of the makespan is proposed to evaluate results. The results indicate that the proposed methodology is promising to find the optimal or near-optimal feasible train timetables of a coal rail system under network and terminal capacity constraints.

Produsage: a closer look at continuing developments

The concept of produsage developed from the realisation that new language was needed to describe the new phenomena emerging from the intersection of Web 2.0, user-generated content, and social media since the early years of the new millennium. When hundreds, thousands, maybe tens of thousands of participants utilise online platforms to collaborate in the development and continuous improvement of a wide variety of content – from software to informational resources to creative works –, and when this work takes place through a series of more or less unplanned, ad hoc, almost random cooperative encounters, then to describe these processes using terms which were developed during the industrial revolution no longer makes much sense. When – exactly because what takes place here is no longer a form of production in any conventional sense of the word – the outcomes of these massively distributed collaborations appear in the form of constantly changing, permanently mutable bodies of work which are owned at once by everyone and no-one, by the community of contributors as a whole but by none of them as individuals, then to conceptualise them as fixed and complete products in the industrial meaning of the term is missing the point. When what results from these efforts is of a quality (in both depth and breadth) that enables it to substitute for, replace, and even undermine the business model of long-established industrial products, even though precariously it relies on volunteer contributions, and when their volunteering efforts make it possible for some contributors to find semi- or fully professional employment in their field, then conventional industrial logic is put on its head.

Service delivery framework : an architectural strategy for next-generation service delivery in business network

The next-generation of service-oriented architecture (SOA) needs to scale for flexible service consumption, beyond organizational and application boundaries, into communities, ecosystems and business networks. In wider and, ultimately, global settings, new capabilities are needed so that business partners can efficiently and reliably enable, adapt and expose services. Those services can then be discovered, ordered, consumed, metered and paid for, through new applications and opportunities, driven by third-parties in the global “village”. This trend is already underway, in different ways, through different early adopter market segments. This paper proposes an architectural strategy for the provisioning and delivery of services in communities, ecosystems and business networks – a Service Delivery Framework (SDF). The SDF is intended to support multiple industries and deployments where a SOA platform is needed for collaborating partners and diverse consumers. Specifically, it is envisaged that the SDF allows providers to publish their services into network directories so that they can be repurposed, traded and consumed, and leveraging network utilities like B2B gateways and cloud hosting. To support these different facets of service delivery, the SDF extends the conventional service provider, service broker and service consumer of the Web Services Architecture to include service gateway, service hoster, service aggregator and service channel maker.