Real-Time Three-Dimensional Occupancy Grid Modeling for the Detection and Tracking of Construction Resources

Awareness of the construction environment can be improved by automatic three-dimensional (3D) sensing and modeling of job sites in real time. Commercially available 3D modeling approaches based on range scanning techniques are capable of modeling static objects only, and thus cannot model dynamic objects in real time in an environment comprised of moving humans, equipment, and materials. Emerging prototype video range cameras offer an alternative by facilitating affordable, wide field of view, dynamic object tracking at frame rates better than 1?Hz (real time). This paper describes a methodology to model, detect, and track the position of static and moving objects in real time, based on data obtained from video range cameras. Experiments with this technology have produced results that indicate that video rate 3D data acquisition and analysis of construction environments can support effective modeling, detection, and tracking of project resources. This approach to job site awareness has inherent value and broad application. In combination with effective management practices and other sensing techniques, this technology has the potential to significantly improve safety on construction job sites.     

Challenges in the Application of Stochastic Modal Identification Methods to a Cable-Stayed Bridge

This paper presents an analysis of the data collected in the ambient vibration test of the International Guadiana cable-stayed Bridge, which links Portugal and Spain, based on different output-only identification techniques: peak-picking, frequency domain decomposition, covariance-driven stochastic subspace identification, and data-driven stochastic subspace identification. The purpose of the analysis is to compare the performance of the four techniques and evaluate their efficiency in dealing with specific challenges involved in the modal identification of the tested cable-stayed bridge, namely the existence of closely spaced modes, the perturbation produced by the local vibration of stay-cables, and the variation of modal damping coefficients with wind velocity. The identified natural frequencies and mode shapes are compared with the corresponding modal parameters provided by a previously developed numerical model. Additionally, the variability of some modal damping coefficients is related with the variation of the wind characteristics and associated with a component of aerodynamic damping.     

Role of Ponded Turbidity Currents in Reservoir Trap Efficiency

The capacity to store water in a reservoir declines as it traps sediment. A river entering a reservoir forms a prograding delta. Coarse sediment (e.g., sand) deposits in the fluvial topset and avalanching foreset of the delta, and is typically trapped with an efficiency near 100%. The trap efficiency of fine sediment (e.g., mud), on the other hand, may be below 100%, because some of this sediment may pass out of the reservoir without settling out. Here, a model of trap efficiency of mud is developed in terms of the mechanics of a turbidity current that plunges on the foreset. The dam causes a sustained turbidity current to reflect and form a muddy pond bounded upstream by a hydraulic jump. If the interface of this muddy pond rises above any vent or overflow point at the dam, the trap efficiency of mud drops below 100%. A model of the coevolution of topset, foreset, and bottomset in a reservoir that captures the dynamics of the internal muddy pond is presented. Numerical implementation, comparison against an experiment, and application to a field-scale case provide the basis for a physical understanding of the processes that determine reservoir trap efficiency.     

Examining a dimensional representation of depression and anxiety disorders' comorbidity in psychiatric outpatients with item response modeling.

The current study replicated, in a sample of 2,300 outpatients seeking psychiatric treatment, a previous study (R. F. Krueger & M. S. Finger, 2001) that implemented an item response theory approach for modeling the comorbidity of common mood and anxiety disorders as indicators along the continuum of a shared latent factor (internalizing). The 5 disorders examined were major depressive disorder, social phobia, panic disorder/agoraphobia, specific phobia, and generalized anxiety disorder. The findings were consistent with the prior research. First, a confirmatory factor analysis yielded sufficient evidence for a nonspecific factor underlying the 5 diagnostic indicators. Second, a 2-parameter logistic item response model showed that the diagnoses were represented in the upper half of the internalizing continuum, and each was a strongly discriminating indicator of the factor. Third, the internalizing factor was significantly associated with 3 indexes of social burden: poorer social functioning, time missed from work, and lifetime hospitalizations. Rather than the categorical system of presumably discrete disorders presented in DSM-IV, these 5 mood and anxiety disorders may be alternatively viewed as higher end indicators of a common factor associated with social cost. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Off-Site Exposure to Respirable Aerosols Produced during the Disk-Incorporation of Class B Biosolids

Field experiments were conducted at a Class B biosolids land application site in central Arizona to measure, model, and source-track the off-site transport of aerosols emitted when biosolids were disk-incorporated into soils. Real-time PM10 monitoring provided time-resolved aerosol information sufficient for verifying both off-site concentration and off-site exposure time model results. Under the conditions considered and at a distance of 165?m from the aerosol source, biosolids disk-incorporation resulted in an intermittent exposure to biosolids-derived aerosol concentration between 15 and 40?μg/m3 and an inhalable biosolids dose between 2 and 8?μg. Transport modeling predicted that these doses will decrease with increasing wind speed. In addition, three DNA sequence-based biosolids source tracking methods were applied to aerosol samples and confirmed the presence of biosolids in aerosols at 5, 65, and 165?m from the aerosol source. Field measurements and modeling indicate that the nature of biosolids-derived aerosol exposure is a series of intermittent high concentration puffs, rather than a continuous low concentration.     

Practical Equivalent Continuum Model for Simulation of Jointed Rock Mass Using FLAC3D

A simple practical equivalent continuum numerical model for simulating the behavior of jointed rock mass has been extended to three-dimensional using FLAC3D. This model estimates the properties of jointed rock mass from the properties of intact rock and a joint factor (Jf), which is the integration of the properties of joints to take care of the effects of frequency, orientation, and strength of joint. A new FISH function has been written in FLAC3D specifically for modeling jointed rocks using the Duncan and Chang hyperbolic model. This model has been validated first with simple element tests at different confining pressures for different rocks with different joint configurations. Explicit modeling of the joints has also been done in element tests and results obtained compare well with the results of equivalent continuum model and also with experimental results. Further, this has been applied for a case study of a large underground power house cavern in the Himalayas. The analysis has been done under various stages of excavation, assigning a null model available in FLAC3D for simulating the excavation.     

A fuzzy clustering algorithm enhancing local model interpretability

In this work, simple modifications on the cost index of particular local-model fuzzy clustering algorithms are proposed in order to improve the readability of the resulting models. The final goal is simultaneously providing local linear models (reasonably close to the plant’s Jacobian) and clustering in the input space so that desirable characteristics (regarding final model accuracy, and convexity and smoothness of the cluster membership functions) are improved with respect to other proposals in literature. Some examples illustrate the proposed approach.     

Modeling language acquisition in atypical phenotypes.

An increasing number of connectionist models have been proposed to explain behavioral deficits in developmental disorders. These simulations motivate serious consideration of the theoretical implications of the claim that a developmental disorder fits within the parameter space of a particular computational model of normal development. The authors examine these issues in depth with respect to a series of new simulations investigating past-tense formation in Williams syndrome. This syndrome and the past-tense domain are highly relevant because both have been used to make strong theoretical claims about the processes underlying normal language acquisition. The authors conclude that computational models have great potential to advance psychologists' understanding of developmental deficits because they focus on the developmental process itself as a pivotal causal factor in producing atypical phenotypic outcomes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Why is science difficult to learn? Things are seldom what they seem

Abstract The difficulties of learning science are related to the nature of science itself and to the methods by which science is customarily taught without regard to what is known about children's learning. An information processing model is proposed to guide thinking and research in this area.     

Seeking the truth about ad hoc join costs

In this paper, we re-examine the results of prior work on methods for computing ad hoc joins. We develop a detailed cost model for predicting join algorithm performance, and we use the model to develop cost formulas for the major ad hoc join methods found in the relational database literature. We show that various pieces of “common wisdom” about join algorithm performance fail to hold up when analyzed carefully, and we use our detailed cost model to derive op timal buffer allocation schemes for each of the join methods examined here. We show that optimizing their buffer allocations can lead to large performance improvements, e.g., as much as a 400% improvement in some cases. We also validate our cost model's predictions by measuring an actual implementation of each join algorithm considered. The results of this work should be directly useful to implementors of relational query optimizers and query processing systems. Edited by M. Adiba. Received May 1993 / Accepted April 1996