Probability distributed time delays: integrating spatial effects into temporal models

Background In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive. Results We present a method that incorporates spatial information by means of tailored, probability distributed time-delays. These distributions can be directly obtained by single in silico or a suitable set of in vitro experiments and are subsequently fed into a delay stochastic simulation algorithm (DSSA), achieving a good compromise between computational costs and a much more accurate representation of spatial processes such as molecular diffusion and translocation between cell compartments. Additionally, we present a novel alternative approach based on delay differential equations (DDE) that can be used in scenarios of high molecular concentrations and low noise propagation. Conclusions Our proposed methodologies accurately capture and incorporate certain spatial processes into temporal stochastic and deterministic simulations, increasing their accuracy at low computational costs. This is of particular importance given that time spans of cellular processes are generally larger (possibly by several orders of magnitude) than those achievable by current spatially-resolved stochastic simulators. Hence, our methodology allows users to explore cellular scenarios under the effects of diffusion and stochasticity in time spans that were, until now, simply unfeasible. Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated by the corresponding Master Equations and presented elsewhere.

Enabling USDL by tools

Fundamental tooling is required in order to apply USDL in practical settings. This chapter discusses three fundamental types of tools for USDL. First, USDL editors have been developed for expert and casual users, respectively. Second, several USDL repositories have been built to allow editors accessing and storing USDL descriptions. Third, our generic USDL marketplace allows providers to describe their services once and potentially trade them anywhere. In addition, the iosyncrasies of service trading as opposed to the simpler case of product trading. The chapter also presents several deployment scenarios of such tools to foster individual value chains and support new business models across organizational boundaries. We close the chapter with an application of USDL in the context of service engineering.

A microscopic simulation model to estimate Bus Rapid Transit (BRT) station service capacity with mixed stopping and non-stopping bus operation

Bus Rapid Transit (BRT) station is the interface between passenger and service. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses maneuvering into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. However, some systems include operation where express buses pass the critical station, resulting in a proportion of non stopping buses. It is important to understand the operation of the critical busway station under this type of operation, as it affects busway line capacity. This study uses micro simulation to treat the BRT station operation and to analyze the relationship between station Limit state bus capacity (B_ls), Total Bus Capacity (B_ttl). First, the simulation model is developed for Limit state scenario and then a mathematical model is defined, calibrated for a specified range of controlled scenarios of mean and coefficient of variation of dwell time. Thereafter, the proposed B_ls model is extended to consider non stopping buses and B_ttlmodel is defined. The proposed models provides better understanding to the BRT line capacity and is useful for transit authorities for designing better BRT operation.

Damage diagnosis for complex steel truss bridges using multi-layer genetic algorithm

Considerate amount of research has proposed optimization-based approaches employing various vibration parameters for structural damage diagnosis. The damage detection by these methods is in fact a result of updating the analytical structural model in line with the current physical model. The feasibility of these approaches has been proven. But most of the verification has been done on simple structures, such as beams or plates. In the application on a complex structure, like steel truss bridges, a traditional optimization process will cost massive computational resources and lengthy convergence. This study presents a multi-layer genetic algorithm (ML-GA) to overcome the problem. Unlike the tedious convergence process in a conventional damage optimization process, in each layer, the proposed algorithm divides the GA’s population into groups with a less number of damage candidates; then, the converged population in each group evolves as an initial population of the next layer, where the groups merge to larger groups. In a damage detection process featuring ML-GA, as parallel computation can be implemented, the optimization performance and computational efficiency can be enhanced. In order to assess the proposed algorithm, the modal strain energy correlation (MSEC) has been considered as the objective function. Several damage scenarios of a complex steel truss bridge’s finite element model have been employed to evaluate the effectiveness and performance of ML-GA, against a conventional GA. In both single- and multiple damage scenarios, the analytical and experimental study shows that the MSEC index has achieved excellent damage indication and efficiency using the proposed ML-GA, whereas the conventional GA only converges at a local solution.

A microscopic simulation model to estimate bus rapid transit station bus capacity

The Bus Rapid Transit (BRT) station is the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses maneuvering into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on BRT line capacity. This study uses microscopic traffic simulation modeling to treat the BRT station operation and to analyze the relationship between station bus capacity and BRT line bus capacity. First, the simulation model is developed for the limit state scenario and then a statistical model is defined and calibrated for a specified range of controlled scenarios of dwell time characteristics. A field survey was conducted to verify the parameters such as dwell time, clearance time and coefficient of variation of dwell time to obtain relevant station bus capacity. The proposed model for BRT bus capacity provides a better understanding of BRT line capacity and is useful to transit authorities in BRT planning, design and operation.

Modeling Bus Rapid Transit station bus queuing for Bus Rapid Transit station bus operation analysis

Stations on Bus Rapid Transit (BRT) lines ordinarily control line capacity because they act as bottlenecks. At stations with passing lanes, congestion may occur when buses maneuvering into and out of the platform stopping lane interfere with bus flow, or when a queue of buses forms upstream of the station blocking inflow. We contend that, as bus inflow to the station area approaches capacity, queuing will become excessive in a manner similar to operation of a minor movement on an unsignalized intersection. This analogy is used to treat BRT station operation and to analyze the relationship between station queuing and capacity. In the first of three stages, we conducted microscopic simulation modeling to study and analyze operating characteristics of the station under near steady state conditions through output variables of capacity, degree of saturation and queuing. A mathematical model was then developed to estimate the relationship between average queue and degree of saturation and calibrated for a specified range of controlled scenarios of mean and coefficient of variation of dwell time. Finally, simulation results were calibrated and validated.

Demonstrating accountable-eHealth systems

The security and privacy of patient information is one of the biggest hindrances to the wide adoption of eHealth systems. For eHealth systems to be successful they must provide protection for patients’ privacy while ensuring healthcare professionals are able to access the information necessary to provide appropriate care. Accountable-eHealth systems are a proposed solution to these potentially competing concerns by enforcing appropriate use and after-the-fact accountability measures. We have developed a Web-based prototype to demonstrate scenarios of how both appropriate and inappropriate use of patient information would be handled in an Accountable-eHealth system.

Cryptography in the cloud : advances and challenges

Cloud computing is a currently developing revolution in information technology that is disturbing the way that individuals and corporate entities operate while enabling new distributed services that have not existed before. At the foundation of cloud computing is the broader concept of converged infrastructure and shared services. Security is often said to be a major concern of users considering migration to cloud computing. This article examines some of these security concerns and surveys recent research efforts in cryptography to provide new technical mechanisms suitable for the new scenarios of cloud computing. We consider techniques such as homomorphic encryption, searchable encryption, proofs of storage, and proofs of location. These techniques allow cloud computing users to benefit from cloud server processing capabilities while keeping their data encrypted; and to check independently the integrity and location of their data. Overall we are interested in how users may be able to maintain and verify their own security without having to rely on the trust of the cloud provider.

Modelling the water, energy and economic nexus

The mining industry faces three long term strategic risks in relation to its water and energy use: 1) securing enough water and energy to meet increased production; 2) reducing water use, energy consumption and emissions due to social, environmental and economic pressures; and 3) understanding the links between water and energy, so that an improvement in one area does not create an adverse effect in another. This project helps the industry analyse these risks by creating a hierarchical systems model (HSM) that represents the water and energy interactions on a sub-site, site and regional scales; which is coupled with a flexible risk framework. The HSM consists of: components that represent sources of water and energy; activities that use water and energy and off-site destinations of water and produced emissions. It can also represent more complex components on a site, with inbuilt examples including tailings dams and water treatment plants. The HSM also allows multiple sites and other infrastructure to be connected together to explore regional water and energy interactions. By representing water and energy as a single interconnected system the HSM can explore tradeoffs and synergies. For example, on a synthetic case study, which represents a typical site, simulations suggested that while a synergy in terms of water use and energy use could be made when chemical additives were used to enhance dust suppression, there were trade-offs when either thickened tailings or dry processing were used. On a regional scale, the HSM was used to simulate various scenarios, including: mines only withdrawing water when needed; achieving economics-of-scale through use of a single centralised treatment plant rather than smaller decentralised treatment plants; and capturing of fugitive emissions for energy generation. The HSM also includes an integrated risk framework for interpreting model output, so that onsite and off-site impacts of various water and energy management strategies can be compared in a managerial context. The case studies in this report explored company, social and environmental risks for scenarios of regional water scarcity, unregulated saline discharge, and the use of plantation forestry to offset carbon emissions. The HSM was able to represent the non-linear causal relationship at the regional scale, such as the forestry scheme offsetting a small percentage of carbon emissions but causing severe regional water shortages. The HSM software developed in this project will be released as an open source tool to allow industry personnel to easily and inexpensively quantify and explore the links between water use, energy use, and carbon emissions. The tool can be easily adapted to represent specific sites or regions. Case studies conducted in this project highlighted the potential complexity of these links between water, energy, and carbon emissions, as well as the significance of the cumulative effects of these links over time. A deeper understanding of these links is vital for the mining industry in order to progress to more sustainable operations, and the HSM provides an accessible, robust framework for investigating these links.

100 futures now : designing sustainable futures

This presentation tells the story of an initiative in middle schooling at Kelvin Grove State College that begins in the Art studios, but reaches out to other disciplines and approaches, and to community and industry partners. It is inspired by the potential of 'future thinking' to become a compelling focus in contemporary art and design. Ethically it espouses a simple premise": every student in our classrooms now has a stake in creating livable, democratic and creative futures. Every student has the potential to be an active force in making that future. "100 Futures Now" is a project that envisages creative and imaginative students working in collaboration with artists and designers to visualize amazing futures and communicate their vision through art and design. "100 Futures Now" is one in a series of innovative curriculum initiatives at Kelvin Grove State College designed to build sustainable practice in arts education with the support of partners in industry and universities and with resident artists and designers. The model blends elements of art and design methodology to focus on the critical and creative thinking skills prioritised in ACARA and 21st century curriculum. The organisers are developing a sustainable model for working with resident artists that goes beyond a single arts intervention or extension/enrichment experience. In this model artists and designers are collaborators in the design of learning experiences that support future programs. This model also looks to transfer the benefits of residencies to the wider school community (in this case to middle schooling curriculum) and to teachers in other curriculum areas, and not exclusively to the immediate target group. In "100 Futures Now", story-making is the engine that powers the creative process. For this reason the program uses a series of imaginative scenarios, including those of speculative fiction and science, as departure points for inquiry, and applies the methodologies of arts and design practice to explore and express student story telling and story making. The story-making responses of student teams will naturally be expressed multimodally through visual art, design artifacts, installation, performance and digital works. The project’s focus on narratives and its modes of communication (performance/installation) are inspired by the work of experimental contemporary design practices and the speculative scenarios of U.K. based designers Anthony Dunne and Fiona Raby. Thanks to the support of an Arts Queensland Artist-in -Residence grant in 2014, resident artists and designers who work with a diversity of ideas and approaches ranging over science, bio-ethics, biodiversity, behavior and ethics, ambient sound, urbanism, food, and wearable design, will work with middle school students as catalysts for deeper thinking and creative action. All these rich fields for future speculation will become triggers for team inquiry into the deeper connections between the past, the present, and future challenges such as climate, waste, energy, sustainability and resilience. These imagined futures will form the platform for a critical, sustainability/design futures approach that will involve questioning assumptions and empowering students as agents rather than consumers of change.

Analyzing busway station potential capacity under mixed stopping and non-stopping operation

Busway stations are the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses manoeuvring into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on busway capacity. This study uses microscopic simulation to treat the busway station operation and to analyse the relationship between station potential capacity where all buses stop, and Mixed Potential Capacity where there is a mixture of stopping and non-stopping buses. First, the micro simulation technique is used to analyze the All Stopping Buses (ASB) scenario and then statistical model is tuned and calibrated for a specified range of controlled scenarios of dwell time characteristics Subsequently, a mathematical model is developed for Mixed Stopping Buses (MSB) Potential Capacity by introducing different proportions of express (or non-stopping) buses. The proposed models for a busway station bus capacity provide a better understanding of operation and are useful to transit agencies in busway planning, design and operation.

Analysing busway station capacity under mixed stopping and non-stopping operation

Busway stations are the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses manoeuvring into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on busway capacity. This study uses microscopic simulation to treat the busway station operation and to analyse the relationship between station potential capacity where all buses stop, and Mixed Potential Capacity where there is a mixture of stopping and non-stopping buses. First, the micro simulation technique is used to analyze the All Stopping Buses (ASB) scenario and then statistical model is tuned and calibrated for a specified range of controlled scenarios of dwell time characteristics Subsequently, a mathematical model is developed for Mixed Stopping Buses (MSB) Potential Capacity by introducing different proportions of express (or non-stopping) buses. The proposed models for a busway station bus capacity provide a better understanding of operation and are useful to transit agencies in busway planning, design and operation.

Modelling the BRT station capacity and queuing for all stopping busway operation

Stations on Bus Rapid Transit (BRT) lines ordinarily control line capacity because they act as bottlenecks. At stations with passing lanes, congestion may occur when buses maneuvering into and out of the platform stopping lane interfere with bus flow, or when a queue of buses forms upstream of the station blocking inflow. We contend that, as bus inflow to the station area approaches capacity, queuing will become excessive in a manner similar to operation of a minor movement on an unsignalized intersection. This analogy was used to treat BRT station operation and to analyze the relationship between station queuing and capacity. We conducted microscopic simulation to study and analyze operating characteristics of the station under near steady state conditions through output variables of capacity, degree of saturation and queuing. In the first of two stages, a mathematical model was developed for all stopping buses potential capacity with bus to bus interference and the model was validated. Secondly, a mathematical model was developed to estimate the relationship between average queue and degree of saturation and calibrated for a specified range of controlled scenarios of mean and coefficient of variation of dwell time.

A framework for freeway incident modeling and traffic re-routing

This paper proposes an analytical Incident Traffic Management framework for freeway incident modeling and traffic re-routing. The proposed framework incorporates an econometric incident duration model and a traffic re-routing optimization module. The incident duration model is used to estimate the expected duration of the incident and thus determine the planning horizon for the re-routing module. The re-routing module is a CTM-based Single Destination System Optimal Dynamic Traffic Assignment model that generates optimal real-time strategies of re-routing freeway traffic to its adjacent arterial network during incidents. The proposed framework has been applied to a case study network including a freeway and its adjacent arterial network in South East Queensland, Australia. The results from different scenarios of freeway demand and incident blockage extent have been analyzed and advantages of the proposed framework are demonstrated.

Enriching architectural design education through interactive displays and local community engagement

Designers have a social responsibility to deal with the needs, issues, and problems that their clients and communities are confronted with. Students of design require opportunities to reflect on their role as social facilitators to develop an attitude towards community engagement through different phases and aspects of their careers. However, current design courses are challenged by compressed timeframes and fragmented scenarios of different academic requirements that do not actively teach community engagement. This paper outlines a participatory and technological approach that was employed to address these issues within the teaching of Architecture and Urban Design at the Queensland University of Technology, Brisbane, Australia. A multi-phase community based research project with actual stakeholders was implemented over a two-year period. Approximately 150 students in the final year of the Bachelor of Design-Architecture; 10 students in the Master of Architecture and 15 students in the Master of Design-Urban Design have informed and influenced each others’ learning through the teaching and research nexus facilitated by this project. The technical approach was implemented in form of a bespoke digital platform that supported the display and discussion of digital media on a series of interactive touch walls. The platform allowed students to easily upload their final designs onto large interactive surfaces, where visitors could explore the media and provide comments. Through the use of this technical platform and the introduction of neogeography, students have been able to broaden their level of interaction and support their learning experience through external structured and unstructured feedback from the local community. Students have not only been exposed to community representatives, but they also have been working in parallel on a specific case study providing each other, across different years and courses, material for reflection and data to structure their design activities.