Stochastic simulation for spatial modelling of dynamic process in a living cell

One of the fundamental motivations underlying computational cell biology is to gain insight into the complicated dynamical processes taking place, for example, on the plasma membrane or in the cytosol of a cell. These processes are often so complicated that purely temporal mathematical models cannot adequately capture the complex chemical kinetics and transport processes of, for example, proteins or vesicles. On the other hand, spatial models such as Monte Carlo approaches can have very large computational overheads. This chapter gives an overview of the state of the art in the development of stochastic simulation techniques for the spatial modelling of dynamic processes in a living cell.

Dynamic texture reconstruction from sparse codes for unusual event detection in crowded scenes

Unusual event detection in crowded scenes remains challenging because of the diversity of events and noise. In this paper, we present a novel approach for unusual event detection via sparse reconstruction of dynamic textures over an overcomplete basis set, with the dynamic texture described by local binary patterns from three orthogonal planes (LBPTOP). The overcomplete basis set is learnt from the training data where only the normal items observed. In the detection process, given a new observation, we compute the sparse coefficients using the Dantzig Selector algorithm which was proposed in the literature of compressed sensing. Then the reconstruction errors are computed, based on which we detect the abnormal items. Our application can be used to detect both local and global abnormal events. We evaluate our algorithm on UCSD Abnormality Datasets for local anomaly detection, which is shown to outperform current state-of-the-art approaches, and we also get promising results for rapid escape detection using the PETS2009 dataset.

Planning of distribution networks for medium voltage and low voltage

Determination of the placement and rating of transformers and feeders are the main objective of the basic distribution network planning. The bus voltage and the feeder current are two constraints which should be maintained within their standard range. The distribution network planning is hardened when the planning area is located far from the sources of power generation and the infrastructure. This is mainly as a consequence of the voltage drop, line loss and system reliability. Long distance to supply loads causes a significant amount of voltage drop across the distribution lines. Capacitors and Voltage Regulators (VRs) can be installed to decrease the voltage drop. This long distance also increases the probability of occurrence of a failure. This high probability leads the network reliability to be low. Cross-Connections (CC) and Distributed Generators (DGs) are devices which can be employed for improving system reliability. Another main factor which should be considered in planning of distribution networks (in both rural and urban areas) is load growth. For supporting this factor, transformers and feeders are conventionally upgraded which applies a large cost. Installation of DGs and capacitors in a distribution network can alleviate this issue while the other benefits are gained. In this research, a comprehensive planning is presented for the distribution networks. Since the distribution network is composed of low and medium voltage networks, both are included in this procedure. However, the main focus of this research is on the medium voltage network planning. The main objective is to minimize the investment cost, the line loss, and the reliability indices for a study timeframe and to support load growth. The investment cost is related to the distribution network elements such as the transformers, feeders, capacitors, VRs, CCs, and DGs. The voltage drop and the feeder current as the constraints are maintained within their standard range. In addition to minimizing the reliability and line loss costs, the planned network should support a continual growth of loads, which is an essential concern in planning distribution networks. In this thesis, a novel segmentation-based strategy is proposed for including this factor. Using this strategy, the computation time is significantly reduced compared with the exhaustive search method as the accuracy is still acceptable. In addition to being applicable for considering the load growth, this strategy is appropriate for inclusion of practical load characteristic (dynamic), as demonstrated in this thesis. The allocation and sizing problem has a discrete nature with several local minima. This highlights the importance of selecting a proper optimization method. Modified discrete particle swarm optimization as a heuristic method is introduced in this research to solve this complex planning problem. Discrete nonlinear programming and genetic algorithm as an analytical and a heuristic method respectively are also applied to this problem to evaluate the proposed optimization method.

A study of abrasive water jet characteristics by CFD simulation

Computational fluid dynamics (CFD) models for ultrahigh velocity waterjets and abrasive waterjets (AWJs) are established using the Fluent 6 flow solver. Jet dynamic characteristics for the flow downstream from a very fine nozzle are then simulated under steady state, turbulent, two-phase and three-phase flow conditions. Water and particle velocities in a jet are obtained under different input and boundary conditions to provide an insight into the jet characteristics and a fundamental understanding of the kerf formation process in AWJ cutting. For the range of downstream distances considered, the results indicate that a jet is characterised by an initial rapid decay of the axial velocity at the jet centre while the cross-sectional flow evolves towards a top-hat profile downstream.

A multidisciplinary examination of fast bowling talent development in cricket

Research on expertise, talent identification and development has tended to be mono-disciplinary, typically adopting geno-centric or environmentalist positions, with an overriding focus on operational issues. In this thesis, the validity of dualist positions on sport expertise is evaluated. It is argued that, to advance understanding of expertise and talent development, a shift towards a multidisciplinary and integrative science focus is necessary, along with the development of a comprehensive multidisciplinary theoretical rationale. Dynamical systems theory is utilised as a multidisciplinary theoretical rationale for the succession of studies, capturing how multiple interacting constraints can shape the development of expert performers. Phase I of the research examines experiential knowledge of coaches and players on the development of fast bowling talent utilising qualitative research methodology. It provides insights into the developmental histories of expert fast bowlers, as well as coaching philosophies on the constraints of fast bowling expertise. Results suggest talent development programmes should eschew the notion of common optimal performance models and emphasize the individual nature of pathways to expertise. Coaching and talent development programmes should identify the range of interacting constraints that impinge on the performance potential of individual athletes, rather than evaluating current performance on physical tests referenced to group norms. Phase II of this research comprises three further studies that investigate several of the key components identified as important for fast bowling expertise, talent identification and development extrapolated from Phase I of this research. This multidisciplinary programme of work involves a comprehensive analysis of fast bowling performance in a cross-section of the Cricket Australia high performance pathways, from the junior, emerging and national elite fast bowling squads. Briefly, differences were found in trunk kinematics associated with the generation of ball speed across the three groups. These differences in release mechanics indicated the functional adaptations in movement patterns as bowlers’ physical and anatomical characteristics changed during maturation. Second to the generation of ball speed, the ability to produce a range of delivery types was highlighted as a key component of expertise in the qualitative phase. The ability of athletes to produce consistent results on different surfaces and in different environments has drawn attention to the challenge of measuring consistency and flexibility in skill assessments. Examination of fast bowlers in Phase II demonstrated that national bowlers can make adjustments to the accuracy of subsequent deliveries during performance of a cricket bowling skills test, and perform a range of delivery types with increased accuracy and consistency. Finally, variability in selected delivery stride ground reaction force components in fast bowling revealed the degenerate nature of this complex multi-articular skill where the same performance outcome can be achieved with unique movement strategies. Utilising qualitative and quantitative methodologies to examine fast bowling expertise, the importance of degeneracy and adaptability in fast bowling has been highlighted alongside learning design that promotes dynamic learning environments.

Towards a model of dynamic capabilities in innovation-based competitive strategy : insights from project-oriented service firms

With the growing significance of services in most developed economies, there is an increased interest in the role of service innovation in service firm competitive strategy. Despite growing literature on service innovation, it remains fragmented reflecting the need for a model that captures key antecedents driving the service innovation-based competitive advantage process. Building on extant literature and using thirteen in-depth interviews with CEOs of project-oriented service firms, this paper presents a model of innovation-based competitive advantage. The emergent model suggests that entrepreneurial service firms pursuing innovation carefully select and use dynamic capabilities that enable them to achieve greater innovation and sustained competitive advantage. Our findings indicate that firms purposefully use create, extend and modify processes to build and nurture key dynamic capabilities. The paper presents a set of theoretical propositions to guide future research. Implications for theory and practice are discussed. Finally, directions for future research are outlined.

Preliminary study on bridge health prediction using Dynamic Objective Oriented Bayesian Network (DOOBN)

The availability of bridges is crucial to people’s daily life and national economy. Bridge health prediction plays an important role in bridge management because maintenance optimization is implemented based on prediction results of bridge deterioration. Conventional bridge deterioration models can be categorised into two groups, namely condition states models and structural reliability models. Optimal maintenance strategy should be carried out based on both condition states and structural reliability of a bridge. However, none of existing deterioration models considers both condition states and structural reliability. This study thus proposes a Dynamic Objective Oriented Bayesian Network (DOOBN) based method to overcome the limitations of the existing methods. This methodology has the ability to act upon as a flexible unifying tool, which can integrate a variety of approaches and information for better bridge deterioration prediction. Two demonstrative case studies are conducted to preliminarily justify the feasibility of the methodology

How long is a tweet? Mapping dynamic conversation networks on Twitter using Gawk and Gephi

Twitter is now well established as the world’s second most important social media platform, after Facebook. Its 140-character updates are designed for brief messaging, and its network structures are kept relatively flat and simple: messages from users are either public and visible to all (even to unregistered visitors using the Twitter website), or private and visible only to approved ‘followers’ of the sender; there are no more complex definitions of degrees of connection (family, friends, friends of friends) as they are available in other social networks. Over time, Twitter users have developed simple, but effective mechanisms for working around these limitations: ‘#hashtags’, which enable the manual or automatic collation of all tweets containing the same #hashtag, as well allowing users to subscribe to content feeds that contain only those tweets which feature specific #hashtags; and ‘@replies’, which allow senders to direct public messages even to users whom they do not already follow. This paper documents a methodology for extracting public Twitter activity data around specific #hashtags, and for processing these data in order to analyse and visualize the @reply networks existing between participating users – both overall, as a static network, and over time, to highlight the dynamic structure of @reply conversations. Such visualizations enable us to highlight the shifting roles played by individual participants, as well as the response of the overall #hashtag community to new stimuli – such as the entry of new participants or the availability of new information. Over longer timeframes, it is also possible to identify different phases in the overall discussion, or the formation of distinct clusters of preferentially interacting participants.

Evaluation of modal analysis techniques using physical models to detect osseointegration of implants in transfemoral amputees

Non-invasive vibration analysis has been used extensively to monitor the progression of dental implant healing and stabilization. It is now being considered as a method to monitor femoral implants in transfemoral amputees. This paper evaluates two modal analysis excitation methods and investigates their capabilities in detecting changes at the interface between the implant and the bone that occur during osseointegration. Excitation of bone-implant physical models with the electromagnetic shaker provided higher coherence values and a greater number of modes over the same frequency range when compared to the impact hammer. Differences were detected in the natural frequencies and fundamental mode shape of the model when the fit of the implant was altered in the bone. The ability to detect changes in the model dynamic properties demonstrates the potential of modal analysis in this application and warrants further investigation.

Fundamentals of process integration

Technologies and languages for integrated processes are a relatively recent innovation. Over that period many divergent waves of innovation have transformed process integration. Like sockets and distributed objects, early workflow systems ordered programming interfaces that connected the process modelling layer to any middleware. BPM systems emerged later, connecting the modelling world to middleware through components. While BPM systems increased ease of use (modelling convenience), long-standing and complex interactions involving many process instances remained di±cult to model. Enterprise Service Buses (ESBs), followed, connecting process models to heterogeneous forms of middleware. ESBs, however, generally forced modellers to choose a particular underlying middleware and to stick to it, despite their ability to connect with many forms of middleware. Furthermore ESBs encourage process integrations to be modelled on their own, logically separate from the process model. This can lead to the inability to reason about long standing conversations at the process layer. Technologies and languages for process integration generally lack formality. This has led to arbitrariness in the underlying language building blocks. Conceptual holes exist in a range of technologies and languages for process integration and this can lead to customer dissatisfaction and failure to bring integration projects to reach their potential. Standards for process integration share similar fundamental flaws to languages and technologies. Standards are also in direct competition with other standards causing a lack of clarity. Thus the area of greatest risk in a BPM project remains process integration, despite major advancements in the technology base. This research examines some fundamental aspects of communication middleware and how these fundamental building blocks of integration can be brought to the process modelling layer in a technology agnostic manner. This way process modelling can be conceptually complete without becoming stuck in a particular middleware technology. Coloured Petri nets are used to define a formal semantics for the fundamental aspects of communication middleware. They provide the means to define and model the dynamic aspects of various integration middleware. Process integration patterns are used as a tool to codify common problems to be solved. Object Role Modelling is a formal modelling technique that was used to define the syntax of a proposed process integration language. This thesis provides several contributions to the field of process integration. It proposes a framework defining the key notions of integration middleware. This framework provides a conceptual foundation upon which a process integration language could be built. The thesis defines an architecture that allows various forms of middleware to be aggregated and reasoned about at the process layer. This thesis provides a comprehensive set of process integration patterns. These constitute a benchmark for the kinds of problems a process integration language must support. The thesis proposes a process integration modelling language and a partial implementation that is able to enact the language. A process integration pilot project in a German hospital is brie°y described at the end of the thesis. The pilot is based on ideas in this thesis.

Load modelling : induction motors

Modelling the power systems load is a challenge since the load level and composition varies with time. An accurate load model is important because there is a substantial component of load dynamics in the frequency range relevant to system stability. The composition of loads need to be charaterised because the time constants of composite loads affect the damping contributions of the loads to power system oscillations, and their effects vary with the time of the day, depending on the mix of motors loads. This chapter has two main objectives: 1) describe the load modelling in small signal using on-line measurements; and 2) present a new approach to develop models that reflect the load response to large disturbances. Small signal load characterisation based on on-line measurements allows predicting the composition of load with improved accuracy compared with post-mortem or classical load models. Rather than a generic dynamic model for small signal modelling of the load, an explicit induction motor is used so the performance for larger disturbances can be more reliably inferred. The relation between power and frequency/voltage can be explicitly formulated and the contribution of induction motors extracted. One of the main features of this work is the induction motor component can be associated to nominal powers or equivalent motors

Metaheuristics for minimizing the makespan of the dynamic shop scheduling problem

For the shop scheduling problems such as flow-shop, job-shop, open-shop, mixed-shop, and group-shop, most research focuses on optimizing the makespan under static conditions and does not take into consideration dynamic disturbances such as machine breakdown and new job arrivals. We regard the shop scheduling problem under static conditions as the static shop scheduling problem, while the shop scheduling problem with dynamic disturbances as the dynamic shop scheduling problem. In this paper, we analyze the characteristics of the dynamic shop scheduling problem when machine breakdown and new job arrivals occur, and present a framework to model the dynamic shop scheduling problem as a static group-shop-type scheduling problem. Using the proposed framework, we apply a metaheuristic proposed for solving the static shop scheduling problem to a number of dynamic shop scheduling benchmark problems. The results show that the metaheuristic methodology which has been successfully applied to the static shop scheduling problems can also be applied to solve the dynamic shop scheduling problem efficiently.