Effects of mental rotation, visual aids and training on inspection performance during airport baggage inspection

Since 9/11, airport security has become an area of critical national security. The current study investigates the effect of mental rotation training and the presence of visual decision aids on inspection performance. Forty-eight participants were divided into two groups (Group A and Group B) of twenty-four each. Each group was provided with training on visual inspection, baggage screening and on using the software simulation of airport baggage inspection. Participants had to identify from images any object that cannot be allowed on a passenger plane and register a response by clicking one of the buttons, “Threat” or “No Threat”. Participants in Group A were provided with visual decision making aids whereas participants in Group B were provided with none. Upon the completion of the first set of trials, all the participants underwent an advanced training session on mental rotation. The participants then repeated the same experiment as before. There was a significant interaction effect between training and rotation for response time, F(1, 184) = 8.59, p = .0038. Individuals that received no training and had rotated objects performed the worse compared to all other conditions. Response times for images with visual aids improves significantly (F(1, 184) = 20.74, p =0.0001) lower (M = 3.70 seconds, SD = 0.50) when compared to the response times for images after without visual aids (M = 4.03 seconds, SD = 0.53). Accuracy for images without training was significantly (F(1, 184) = 34.23, p \u3c 0.0001) lower (M = 74.73, SD = 10.92) than the accuracy for images after training (M = 83.42, SD = 10.51). Accuracy for images presented without visual aids was significantly (F(1, 184) = 19.58, p \u3c 0.0001) lower (M = 75.86, SD = 11.69) than the accuracy for images presented with visual aids (M = 82.29, SD = 10.51). The results from the experiment show that mental rotation has an effect on inspection performance of an airport baggage inspector and that the performance can be improved by training the inspector in mental rotation. It was also observed that providing visual decision making aids can improve the inspection performance

Doctor of Philosophy

dissertationThe present work focuses on developing a holistic understanding of flow and dispersion in urban environments. Toward this end, ideas are drawn from the fields of physical modeling, inverse modeling, and optimization in urban fluid dynamics. The physical modeling part of the dissertation investigates flow in the vicinity of tall buildings using wind tunnel two-dimensional particle image velocimetry (PIV) measurements. The data obtained have been used to evaluate and improve urban wind and dispersion models. In the inverse modeling part of the dissertation, an event reconstruction tool is developed to quickly and accurately characterize the source parameters of chemical / biological / radiological (CBR) agents released into the atmosphere in an urban domain. Event reconstruction is performed using concentration measurements obtained from a distributed sensor network in the city, where the spatial coordinates of the sensors are known a priori. Source characterization comprises retrieving several source parameters including the spatial coordinates of the source, the source strength, the wind speed, and wind direction at the source, etc. The Gaussian plume model is adopted as the forward model, and derivative-based optimization is chosen to take advantage of its simple analytical nature. The solution technique developed is independent of the forward model used and is comprised of stochastic search with regularized gradient optimization. The final part of the dissertation is comprised of urban form optimization. The problem of identification of urban forms that result in the best environmental conditions is referred to as the urban form optimization problem (UFOP). The decision variables optimized include the spatial locations and the physical dimensions of the buildings and the wind speed and wind direction over the domain of interest. For the UFOP, the quick urban and industrial complex (QUIC) dispersion model is used as the forward model. The UFOP is cast as a single optimization problem, and simulated annealing and genetic algorithms are used in the solution procedure

Mechanical performance of composite bonded joints in the presence of localised process-induced zero-thickness defects

Processing parameters and environmental conditions can introduce variation into the performance of adhesively bonded joints. The effect of such variation on the mechanical performance of the joints is not well understood. Moreover, there is no validated nondestructive inspection (NDI) available to ensure bond integrity post-process and in-service so as to guarantee initial and continued airworthiness in aerospace sector. This research studies polymer bond defects produced in the laboratory scale single-lap composite-to-composite joints that may represent the process-induced defects occurring in actual processing scenarios such as composite joining and repair in composite aircrafts. The effect of such defects on the degradation of a joint's mechanical performance is then investigated via quasi-static testing in conjunction with NDI ultrasonic C-scanning and pulsed thermography. This research is divided into three main sections: 1- manufacturing carbon fibre-reinforced composite joints containing representative nearly zero-thickness bond defects, 2- mechanical testing of the composite joints, and 3- assessment of the NDI capability for detection of the bond defects in such joints

Minimizing Error Rate in the Updation of Physicians’ Profile

The Provider Update Management is the project undertaken by iSpace Global Services Company. MultiPlan is the leading provider of independent national Payer and Provider Organizations (PPO) networks and related cost management services. It was founded in 1980 as a New York hospital network. With more than half a million healthcare providers under contract, an estimated 40 million consumers access the network products. About 65 million claims are processed through the network each year. The Company desired to understand the process of updating the Provider data without any errors committed by the users. The company believes that the SIX SIGMA methodology is the most useful methodology to understand the root cause and take the improvement steps to sustain the Benchmark in Quality. This study focuses on achieving internal and external quality targets by minimizing error incidence in the updating process of physicians’ data through systematic deployment of Six Sigma DMAIC methodology resulting in substantial improvement of the process quality

A case for adaptive sub-carrier level power allocation in OFDMA networks

In today's OFDMA networks, the transmission power is typically fixed and the same for all the sub-carriers that compose a channel. The sub-carriers though, experience different degrees of fading and thus, the received power is different for different sub-carriers; while some frequencies experience deep fades, others are relatively unaffected. In this paper, we make a case of redistributing the power across the sub-carriers (subject to a fixed power budget constraint) to better cope with this frequency selectivity. Specifically, we design a joint power and rate adaptation scheme (called JPRA for short) wherein power redistribution is combined with sub-carrier level rate adaptation to yield significant throughput benefits. We further consider two variants of JPRA: (a) JPRA-CR where, the power is redistributed across sub-carriers so as to support a maximum common rate (CR) across sub-carriers and (b) JPRA-MT where, the goal is to redistribute power such that the transmission time of a packet is minimized. While the first variant decreases transceiver complexity and is simpler, the second is geared towards achieving the maximum throughput possible. We implement both variants of JPRA on our WARP radio testbed. Our extensive experiments demonstrate that our scheme provides a 35% improvement in total network throughput in testbed experiments compared to FARA, a scheme where only sub-carrier level rate adaptation is used. We also perform simulations to demonstrate the efficacy of JPRA in larger scale networks. © 2012 ACM

Service Knowledge Capture and Reuse

The keynote will start with the need for service knowledge capture and reuse for industrial product-service systems. A novel approach to capture the service damage knowledge about individual component will be presented with experimental results. The technique uses active thermography and image processing approaches for the assessment. The paper will also give an overview of other non-destructive inspection techniques for service damage assessment. A robotic system will be described to automate the damage image capture. The keynote will then propose ways to reuse the knowledge to predict remaining life of the component and feedback to design and manufacturing

A concise review on lipidomics analysis in biological samples

Lipids are a complex and critical heterogeneous molecular entity, playing an intricate and key role in understanding biological activities and disease processes. Lipidomics aims to quantitatively define the lipid classes, including their molecular species. The analysis of the biological tissues and fluids are challenging due to the extreme sample complexity and occurrence of the molecular species as isomers or isobars. This review documents the overview of lipidomics workflow, beginning from the approaches of sample preparation, various analytical techniques and emphasizing the state-of-the-art mass spectrometry either by shotgun or coupled with liquid chromatography. We have considered the latest ion mobility spectroscopy technologies to deal with the vast number of structural isomers, different imaging techniques. All these techniques have their pitfalls and we have discussed how to circumvent them after reviewing the power of each technique with examples

Source characterization of atmospheric releases using quasi-random sampling and regularized gradient optimization

technical reportIn the present work, an inversion technique to solve the atmospheric source characterization problem is described. The inverse problem comprises characterizing the source (x, y and z coordinates and the source strength) and the meteorological conditions (wind speed and wind direction) at the source, given certain receptor locations and the concentration values at these receptor locations. A simple Gaussian plume dispersion model for continuous point releases has been adopted as the forward model. The solution methodology for this nonlinear inverse problem consists of Qausi-Monte Carlo (QMC) sampling of the model parameter space and the subsequent application of gradient optimization. The purpose of conducting QMC sampling is to provide the gradient scheme a good initial iterate to converge to the final solution. A new misfit functional that computes the L?-norm of the ratio of the observed and predicted data has been developed and was used in the QMC search stage. It has been demonstrated that the misfit functional developed, guides the inversion algorithm to the global minimum. Quasi-random sampling was performed using the Hammersley point-set in its original, scrambled and randomized form. Its performance was evaluated against the Mersenne-Twister uniform pseudo-random number generator in terms of the speed and quality of the initial iterate provided. Regularized Newton?s method with quadratic line-search was employed for gradient optimization. The standard Tikhonov stabilizing functional was used for regularization and the regularization parameter was updated adaptively during inversion. The proposed approach has been validated against both synthetic and field experiment data. Results obtained indicate that the proposed approach performs exceedingly well for inverse-source problems with the Gaussian dispersion equation as the forward operator. Also, the work presented highlights the advantages of using deterministic low-discrepancy sampling compared to the conventional pseudo-random sampling to solve the sourceinversion proble