A methodology for object identification and tracking in construction based on spatial modeling and image matching techniques

Understanding the motion characteristics of on-site objects is desirable for the analysis of construction work zones, especially in problems related to safety and productivity studies. This article presents a methodology for rapid object identification and tracking. The proposed methodology contains algorithms for spatial modeling and image matching. A high-frame-rate range sensor was utilized for spatial data acquisition. The experimental results indicated that an occupancy grid spatial modeling algorithm could quickly build a suitable work zone model from the acquired data. The results also showed that an image matching algorithm is able to find the most similar object from a model database and from spatial models obtained from previous scans. It is then possible to use the matched information to successfully identify and track objects.

Maintenance chain integration using Petri-net enabled multiagent system modeling and implementation approach

Engineering asset management (EAM) is a broad discipline and the EAM functions and processes are characterized by its distributed nature. However, engineering asset nowadays mostly relies on self-maintained experiential rule bases and periodic maintenance, which is lacking a collaborative engineering approach. This research proposes a collaborative environment integrated by a service center with domain expertise such as diagnosis, prognosis, and asset operations. The collaborative maintenance chain combines asset operation sites, service center (i.e., maintenance operation coordinator), system provider, first tier collaborators, and maintenance part suppliers. Meanwhile, to realize the automation of communication and negotiation among organizations, multiagent system (MAS) technique is applied to enhance the entire service level. During the MAS design processes, this research combines Prometheus MAS modeling approach with Petri-net modeling methodology and unified modeling language to visualize and rationalize the design processes of MAS. The major contributions of this research include developing a Petri-net enabled Prometheus MAS modeling methodology and constructing a collaborative agent-based maintenance chain framework for integrated EAM.

Testing and simulation of extruded polystyrene foam at low to moderate strain rates

This paper presents a study into the behaviour of extruded polystyrene foam at low strain rates. The foam is being studied in order assess its potential for use as part of a new innovative design of portable road safety barrier the aim to consume less water and reduce rates of serious injury. The foam was tested at a range of low strain rates, with the stress and strain behaviour of the foam specimens being recorded. The energy absorption capabilities of the foam were assessed as well as the response of the foam to multiple loadings. The experimental data was then used to create a material model of the foam for use in the explicit finite element solver LS-DYNA. Simulations were carried out using the material model which showed excellent correlation between the numerical material model and the experimental data.

Oscillatory regulation of Hes1: Discrete stochastic delay modelling and simulation

Discrete stochastic simulations are a powerful tool for understanding the dynamics of chemical kinetics when there are small-to-moderate numbers of certain molecular species. In this paper we introduce delays into the stochastic simulation algorithm, thus mimicking delays associated with transcription and translation. We then show that this process may well explain more faithfully than continuous deterministic models the observed sustained oscillations in expression levels of hes1 mRNA and Hes1 protein.

Stochastic models and simulation of ion channel dynamics

The behaviour of ion channels within cardiac and neuronal cells is intrinsically stochastic in nature. When the number of channels is small this stochastic noise is large and can have an impact on the dynamics of the system which is potentially an issue when modelling small neurons and drug block in cardiac cells. While exact methods correctly capture the stochastic dynamics of a system they are computationally expensive, restricting their inclusion into tissue level models and so approximations to exact methods are often used instead. The other issue in modelling ion channel dynamics is that the transition rates are voltage dependent, adding a level of complexity as the channel dynamics are coupled to the membrane potential. By assuming that such transition rates are constant over each time step, it is possible to derive a stochastic differential equation (SDE), in the same manner as for biochemical reaction networks, that describes the stochastic dynamics of ion channels. While such a model is more computationally efficient than exact methods we show that there are analytical problems with the resulting SDE as well as issues in using current numerical schemes to solve such an equation. We therefore make two contributions: develop a different model to describe the stochastic ion channel dynamics that analytically behaves in the correct manner and also discuss numerical methods that preserve the analytical properties of the model.

Modeling and analyzing the carbon footprint of business processes

Many corporations and individuals realize that environmental sustainability is an urgent problem to address. In this chapter, we contribute to the emerging academic discussion by proposing two innovative approaches for engaging in the development of environmentally sustainable business processes. Specifically, we describe an extended process modeling approach for capturing and documenting the dioxide emissions produced during the execution of a business process. For illustration, we apply this approach to the case of a government Shared Service provider. Second, we then introduce an analysis method for measuring the carbon dioxide emissions produced during the execution of a business process. To illustrate this approach, we apply it in the real-life case of a European airport and show how this information can be leveraged in the re-design of "green" business processes.

Modeling and Analyzing the Carbon Footprint of Business Processes

Many corporations and individuals realize that environmental sustainability is an urgent problem to address. In this chapter, we contribute to the emerging academic discussion by proposing two innovative approaches for engaging in the development of environmentally sustainable business processes. Specifically, we describe an extended process modeling approach for capturing and documenting the dioxide emissions produced during the execution of a business process. For illustration, we apply this approach to the case of a governmental Shared Services provider. Second, we then introduce an analysis method for measuring the carbon dioxide emissions produced during the execution of a business process. To illustrative this approach, we apply it in the real-life case of an European airport and show how this information can be leveraged in the re-design of “green” busi-ness processes.

Role of kilometer-scale weak circular heterogeneities on upper crustal deformation patterns: Evidence from scaled analogue modeling and the Sudbury Basin, Canada

The Sudbury Basin is a non-cylindrical fold basin occupying the central portion of the Sudbury Impact Structure. The impact structure lends itself excellently to explore the structural evolution of continental crust containing a circular region of long-term weakness. In a series of scaled analogue experiments various model crustal configurations were shortened horizontally at a constant rate. In mechanically weakened crust, model basins formed that mimic several first-order structural characteristics of the Sudbury Basin: (1) asymmetric, non-cylindrical folding of the Basin, (2) structures indicating concentric shortening around lateral basin termini and (3) the presence of a zone of strain concentration near the hinge zones of model basins. Geometrically and kinematically this zone corresponds to the South Range Shear Zone of the Sudbury Basin. According to our experiments, this shear zone is a direct mechanical consequence of basin formation, rather than the result of thrusting following folding. Overall, the models highlight the structurally anomalous character of the Sudbury Basin within the Paleoproterozoic Eastern Penokean Orogen. In particular, our models suggest that the Basin formed by pure shear thickening of crust, whereas transpressive deformation prevailed elsewhere in the orogen. The model basin is deformed by thickening and non-cylindrical synformal buckling, while conjugate transpressive shear zones propagated away from its lateral tips. This is consistent with pure shear deformation of a weak circular inclusion in a strong matrix. The models suggest that the Sudbury Basin formed as a consequence of long-term weakening of the upper crust by meteorite impact.