Modeling object identification and tracking errors on image-based safety assessment of earthmoving operations

Object identification and tracking have become critical for automated on-site construction safety assessment. The primary objective of this paper is to present the development of a testbed to analyze the impact of object identification and tracking errors caused by data collection devices and algorithms used for safety assessment. The testbed models workspaces for earthmoving operations and simulates safety-related violations, including speed limit violations, access violations to dangerous areas, and close proximity violations between heavy machinery. Three different cases were analyzed based on actual earthmoving operations conducted at a limestone quarry. Using the testbed, the impacts of device and algorithm errors were investigated for safety planning purposes.

Petri net modeling of spatial and temporal constraints in track allocation problem at railway stations

The track allocation problem (TAP) at a multi-track, multi-platform mainline railway station is defined by the station track layout and service timetable, which implies combinations of spatial and temporal conflicts. Feasible solutions are available from either traditional planning or advanced intelligent searching methods and their evaluations with respect to operational requirements are essential for the operators. To facilitate thorough analysis, a timed Coloured Petri Nets (CPN) model is presented here to encapsulate the inter-relationships of the spatial and temporal constraints in the TAP.

Concurrent multi-scale modeling of civil infrastructures for analyses on structural deterioration—Part I : Modeling methodology and strategy

This paper aims to develop the methodology and strategy for concurrent finite element modeling of civil infrastructures at the different scale levels for the purposes of analyses of structural deteriorating. The modeling strategy and method were investigated to develop the concurrent multi-scale model of structural behavior (CMSM-of-SB) in which the global structural behavior and nonlinear damage features of local details in a large complicated structure could be concurrently analyzed in order to meet the needs of structural-state evaluation as well as structural deteriorating. In the proposed method, the “large-scale” modeling is adopted for the global structure with linear responses between stress and strain and the “small-scale” modeling is available for nonlinear damage analyses of the local welded details. A longitudinal truss in steel bridge decks was selected as a case to study how a CMSM-of-SB was developed. The reduced-scale specimen of the longitudinal truss was studied in the laboratory to measure its dynamic and static behavior in global truss and local welded details, while the multi-scale models using constraint equations and substructuring were developed for numerical simulation. The comparison of dynamic and static response between the calculated results by different models indicated that the proposed multi-scale model was found to be the most efficient and accurate. The verification of the model with results from the tested truss under the specific loading showed that, responses at the material scale in the vicinity of local details as well as structural global behaviors could be obtained and fit well with the measured results. The proposed concurrent multi-scale modeling strategy and implementation procedures were applied to Runyang cable-stayed bridge (RYCB) and the CMSM-of-SB of the bridge deck system was accordingly constructed as a practical application.

Concurrent multi-scale modeling of civil infrastructures for analyses on structural deteriorating—Part II : Model updating and verification

This paper is a continuation of the paper titled “Concurrent multi-scale modeling of civil infrastructure for analyses on structural deteriorating—Part I: Modeling methodology and strategy” with the emphasis on model updating and verification for the developed concurrent multi-scale model. The sensitivity-based parameter updating method was applied and some important issues such as selection of reference data and model parameters, and model updating procedures on the multi-scale model were investigated based on the sensitivity analysis of the selected model parameters. The experimental modal data as well as static response in terms of component nominal stresses and hot-spot stresses at the concerned locations were used for dynamic response- and static response-oriented model updating, respectively. The updated multi-scale model was further verified to act as the baseline model which is assumed to be finite-element model closest to the real situation of the structure available for the subsequent arbitrary numerical simulation. The comparison of dynamic and static responses between the calculated results by the final model and measured data indicated the updating and verification methods applied in this paper are reliable and accurate for the multi-scale model of frame-like structure. The general procedures of multi-scale model updating and verification were finally proposed for nonlinear physical-based modeling of large civil infrastructure, and it was applied to the model verification of a long-span bridge as an actual engineering practice of the proposed procedures.

Bayesian latent trait modeling of migraine symptom data

Definition of disease phenotype is a necessary preliminary to research into genetic causes of a complex disease. Clinical diagnosis of migraine is currently based on diagnostic criteria developed by the International Headache Society. Previously, we examined the natural clustering of these diagnostic symptoms using latent class analysis (LCA) and found that a four-class model was preferred. However, the classes can be ordered such that all symptoms progressively intensify, suggesting that a single continuous variable representing disease severity may provide a better model. Here, we compare two models: item response theory and LCA, each constructed within a Bayesian context. A deviance information criterion is used to assess model fit. We phenotyped our population sample using these models, estimated heritability and conducted genome-wide linkage analysis using Merlin-qtl. LCA with four classes was again preferred. After transformation, phenotypic trait values derived from both models are highly correlated (correlation = 0.99) and consequently results from subsequent genetic analyses were similar. Heritability was estimated at 0.37, while multipoint linkage analysis produced genome-wide significant linkage to chromosome 7q31-q33 and suggestive linkage to chromosomes 1 and 2. We argue that such continuous measures are a powerful tool for identifying genes contributing to migraine susceptibility.

Bitrate modeling of scalable videos using quantization parameter, frame rate and spatial resolution

The quality and bitrate modeling is essential to effectively adapt the bitrate and quality of videos when delivered to multiplatform devices over resource constraint heterogeneous networks. The recent model proposed by Wang et al. estimates the bitrate and quality of videos in terms of the frame rate and quantization parameter. However, to build an effective video adaptation framework, it is crucial to incorporate the spatial resolution in the analytical model for bitrate and perceptual quality adaptation. Hence, this paper proposes an analytical model to estimate the bitrate of videos in terms of quantization parameter, frame rate, and spatial resolution. The model can fit the measured data accurately which is evident from the high Pearson correlation. The proposed model is based on the observation that the relative reduction in bitrate due to decreasing spatial resolution is independent of the quantization parameter and frame rate. This modeling can be used for rate-constrained bit-stream adaptation scheme which selects the scalability parameters to optimize the perceptual quality for a given bandwidth constraint.

Hysteresis modeling of Magneto-Rheological (MR) fluid damper by self tuning fuzzy control

Magneto-rheological (MR) fluid damper is a semi-active control device that has recently received more attention by the vibration control community. But inherent nonlinear hysteresis character of magneto-rheological fluid dampers is one of the challenging aspects for utilizing this device to achieve high system performance. So the development of accurate model is necessary to take the advantage their unique characteristics. Research by others [3] has shown that a system of nonlinear differential equations can successfully be used to describe the hysteresis behavior of the MR damper. The focus of this paper is to develop an alternative method for modeling a damper in the form of centre average fuzzy interference system, where back propagation learning rules are used to adjust the weight of network. The inputs for the model are used from the experimental data. The resulting fuzzy interference system is satisfactorily represents the behavior of the MR fluid damper with reduced computational requirements. Use of the neuro-fuzzy model increases the feasibility of real time simulation.

Microscopic modelling of freeway operations

Freeways are divided roadways designed to facilitate the uninterrupted movement of motor vehicles. However, many freeways now experience demand flows in excess of capacity, leading to recurrent congestion. The Highway Capacity Manual (TRB, 1994) uses empirical macroscopic relationships between speed, flow and density to quantify freeway operations and performance. Capacity may be predicted as the maximum uncongested flow achievable. Although they are effective tools for design and analysis, macroscopic models lack an understanding of the nature of processes taking place in the system. Szwed and Smith (1972, 1974) and Makigami and Matsuo (1990) have shown that microscopic modelling is also applicable to freeway operations. Such models facilitate an understanding of the processes whilst providing for the assessment of performance, through measures of capacity and delay. However, these models are limited to only a few circumstances. The aim of this study was to produce more comprehensive and practical microscopic models. These models were required to accurately portray the mechanisms of freeway operations at the specific locations under consideration. The models needed to be able to be calibrated using data acquired at these locations. The output of the models needed to be able to be validated with data acquired at these sites. Therefore, the outputs should be truly descriptive of the performance of the facility. A theoretical basis needed to underlie the form of these models, rather than empiricism, which is the case for the macroscopic models currently used. And the models needed to be adaptable to variable operating conditions, so that they may be applied, where possible, to other similar systems and facilities. It was not possible to produce a stand-alone model which is applicable to all facilities and locations, in this single study, however the scene has been set for the application of the models to a much broader range of operating conditions. Opportunities for further development of the models were identified, and procedures provided for the calibration and validation of the models to a wide range of conditions. The models developed, do however, have limitations in their applicability. Only uncongested operations were studied and represented. Driver behaviour in Brisbane was applied to the models. Different mechanisms are likely in other locations due to variability in road rules and driving cultures. Not all manoeuvres evident were modelled. Some unusual manoeuvres were considered unwarranted to model. However the models developed contain the principal processes of freeway operations, merging and lane changing. Gap acceptance theory was applied to these critical operations to assess freeway performance. Gap acceptance theory was found to be applicable to merging, however the major stream, the kerb lane traffic, exercises only a limited priority over the minor stream, the on-ramp traffic. Theory was established to account for this activity. Kerb lane drivers were also found to change to the median lane where possible, to assist coincident mergers. The net limited priority model accounts for this by predicting a reduced major stream flow rate, which excludes lane changers. Cowan's M3 model as calibrated for both streams. On-ramp and total upstream flow are required as input. Relationships between proportion of headways greater than 1 s and flow differed for on-ramps where traffic leaves signalised intersections and unsignalised intersections. Constant departure onramp metering was also modelled. Minimum follow-on times of 1 to 1.2 s were calibrated. Critical gaps were shown to lie between the minimum follow-on time, and the sum of the minimum follow-on time and the 1 s minimum headway. Limited priority capacity and other boundary relationships were established by Troutbeck (1995). The minimum average minor stream delay and corresponding proportion of drivers delayed were quantified theoretically in this study. A simulation model was constructed to predict intermediate minor and major stream delays across all minor and major stream flows. Pseudo-empirical relationships were established to predict average delays. Major stream average delays are limited to 0.5 s, insignificant compared with minor stream delay, which reach infinity at capacity. Minor stream delays were shown to be less when unsignalised intersections are located upstream of on-ramps than signalised intersections, and less still when ramp metering is installed. Smaller delays correspond to improved merge area performance. A more tangible performance measure, the distribution of distances required to merge, was established by including design speeds. This distribution can be measured to validate the model. Merging probabilities can be predicted for given taper lengths, a most useful performance measure. This model was also shown to be applicable to lane changing. Tolerable limits to merging probabilities require calibration. From these, practical capacities can be estimated. Further calibration is required of traffic inputs, critical gap and minimum follow-on time, for both merging and lane changing. A general relationship to predict proportion of drivers delayed requires development. These models can then be used to complement existing macroscopic models to assess performance, and provide further insight into the nature of operations.

Design of a preliminary error impact analysis model for spatial safety assessment of earthmoving operations

Regardless of technology benefits, safety planners still face difficulties explaining errors related to the use of different technologies and evaluating how the errors impact the performance of safety decision making. This paper presents a preliminary error impact analysis testbed to model object identification and tracking errors caused by image-based devices and algorithms and to analyze the impact of the errors for spatial safety assessment of earthmoving and surface mining activities. More specifically, this research designed a testbed to model workspaces for earthmoving operations, to simulate safety-related violations, and to apply different object identification and tracking errors on the data collected and processed for spatial safety assessment. Three different cases were analyzed based on actual earthmoving operations conducted at a limestone quarry. Using the testbed, the impacts of the errors were investigated for the safety planning purpose.

In silico experimental modeling of cancer treatment

In silico experimental modeling of cancer involves combining findings from biological literature with computer-based models of biological systems in order to conduct investigations of hypotheses entirely in the computer laboratory. In this paper, we discuss the use of in silico modeling as a precursor to traditional clinical and laboratory research, allowing researchers to refine their experimental programs with an aim to reducing costs and increasing research efficiency. We explain the methodology of in silico experimental trials before providing an example of in silico modeling from the biomathematical literature with a view to promoting more widespread use and understanding of this research strategy.