Investigation of smart work zone technologies using mixed simulator and field studies

Safety is the top concern in transportation, especially in work zones, as work zones deviate from regular driving environment and driver behavior is very different. In order to protect workers and create a safer work zone environment, new technologies are proposed by agencies and deployed to work zones, however, some are without scientific study before deployment. Therefore, quantitative studies need to be conducted to show the effectiveness of technologies. Driving simulator is a safe and cost-effective way to test effectiveness of new designs and compare different configurations. Field study is another scientific way of testing, as it provides absolute validity, while simulator study provides relative validity. The synergy of field and simulator studies construct a precise experiment as field study calibrates simulator design and validates simulator results. Two main projects, Evaluation of Automated Flagger Assistance Devices (AFADs), and Evaluation of Green Lights on Truck-Mounted Attenuator (TMA), are discussed in this dissertation to illustrate the investigation of smart work zone technologies using mixed simulator and field studies, along with one simulator project investigating interaction between human driven car and autonomous truck platoon in work zones. Both field and simulator studies indicated that AFADs improved stationary work zone safety by enhancing visibility, isolating workers from immediate traffic, and conveying clear guidance message to traffic. The results of green light on TMAs implied an inverse relationship between visibility/awareness of work zone and arrow board recognition/easy on eyes, but did not show if any of the light configurations is superior. Results anticipated for autonomous truck platoon in work zones are drivers behave more uniformly after being educated about the meaning of signage displayed on the back of truck, and performance measured with signage would be more preferable than those without signage. Applications of statistics are extension of studies, including experimental design, survey design, and data analysis. Data obtained from AFAD and Green Light projects were utilized to illustrate the methodologies of data analysis and model building, which incorporated simulator data, biofeedback and survey response to interpret the relationship among driver perspective and mental status, and driving behavior. From the studies conducted, it could be concluded that mixed simulator and field study is a good fit for smart work zone technologies investigation. Simulators provide a safe environment, flexibility and cost-effectiveness, while field studies calibrate and validate simulator setup and its results. The collaboration of two forms of study generates legitimate and convincing results for investigations. Applying statistical methodologies into transportation simulator and field studies is a good way to make experiment and survey design more rational, and the statistical methods are applicable for further data analysis.Includes bibliographical reference

The effect of particle geometry and surface asperities on the result of Discrete Element Simulations

In recent years, analysis of the behavior of brittle materials, such as concrete, rocks or granular materials, is receiving more attention. These brittle materials share common characteristics, which are their high complexity and heterogeneity, especially when they fragment from their original shape into smaller particles. Traditionally, it was common to use continuum methods (like the finite element method) to reproduce the behavior of these materials, even though these methods require complex constitutive models, which contain a lot of parameters and variables. The Discrete Element Method (DEM), originally developed by Cundall and Strack (1979), in contrast to continuum methods, has been proven to be an irreplaceable and powerful tool for conducting analysis and modelling the behavior of granular (spherical) and polyhedral (non-spherical) particle systems, which also focus on micromechanics of soil particle interactions and displacements. Meanwhile, the DEM has been proven to be suitable for analysis of continuum materials and models as well. In addition, there is another method named The Combined Finite-Discrete Element Method (FEM/DEM) (Munjiza, 2004), which is a numerical solution that focuses on the analysis of problems for solids that are considered as both continua and discontinua. This research will present the basic numerical principles of DEM and FEM/DEM, then by using these methods, the analysis of the influence of the changes of the geometry or asperities of polyhedral granular particles will be investigated. Both the influence on solution time and solution accuracy will be critically reviewed and recommendations will be given for practical use in simulations

mm-Pose: Real-Time Human Skeletal Posture Estimation using mmWave Radars and CNNs

In this paper, mm-Pose, a novel approach to detect and track human skeletons in real-time using an mmWave radar, is proposed. To the best of the authors' knowledge, this is the first method to detect >15 distinct skeletal joints using mmWave radar reflection signals. The proposed method would find several applications in traffic monitoring systems, autonomous vehicles, patient monitoring systems and defense forces to detect and track human skeleton for effective and preventive decision making in real-time. The use of radar makes the system operationally robust to scene lighting and adverse weather conditions. The reflected radar point cloud in range, azimuth and elevation are first resolved and projected in Range-Azimuth and Range-Elevation planes. A novel low-size high-resolution radar-to-image representation is also presented, that overcomes the sparsity in traditional point cloud data and offers significant reduction in the subsequent machine learning architecture. The RGB channels were assigned with the normalized values of range, elevation/azimuth and the power level of the reflection signals for each of the points. A forked CNN architecture was used to predict the real-world position of the skeletal joints in 3-D space, using the radar-to-image representation. The proposed method was tested for a single human scenario for four primary motions, (i) Walking, (ii) Swinging left arm, (iii) Swinging right arm, and (iv) Swinging both arms to validate accurate predictions for motion in range, azimuth and elevation. The detailed methodology, implementation, challenges, and validation results are presented.Comment: Submitted to IEEE Sensors Journa

Design and Performance Comparisons of Brushless Doubly-Fed Generators with Different Rotor Structures

The Brushless Doubly-Fed Generator (BDFG) shows the great potential for use in large variable speed wind turbines due to its high reliability and cost benefits of a partially-rated power electronics converter. However, it suffers from the compromised efficiency and power factor in comparison with conventional doubly fed induction or synchronous generators. Therefore, optimizing the BDFG, especially the rotor, is necessary for enhancing its torque density and market competitiveness. In this paper, a novel cage-assisted magnetic barrier rotor, called the hybrid rotor, is proposed and analyzed. The detailed analytical design approaches based on the magnetic field modulation theory are investigated. In addition, the machine losses and mutual inductance values using the proposed rotor designs are calculated and their performance implications evaluated. Finally, the comparative experimental results for two BDFG prototypes are presented to verify the accuracy and effectiveness of the theoretical studies

Adrenomedullin expression in epithelial ovarian cancers and promotes HO8910 cell migration associated with upregulating integrin α5β1 and phosphorylating FAK and paxillin

<p>Abstract</p> <p>Background</p> <p>Epithelial ovarian cancer (EOC) is one of the leading causes of cancer deaths in women worldwide. Adrenomedullin (AM) is a multifunctional peptide which presents in various kinds of tumors.</p> <p>Methods</p> <p>In this study, we characterized the expression and function of AM in epithelial ovarian cancer using immunohistochemistry staining. Exogenous AM and small interfering RNA (siRNA) specific for AM receptor CRLR were treated to EOC cell line HO8910. Wound healing assay and flow cytometry were used to measure the migration ability and expression of integrin α5 of HO8910 cells after above treatments. Western blot was used to examine the phosphorylation of FAK and paxillin.</p> <p>Results</p> <p>We found that patients with high AM expression showed a higher incidence of metastasis, larger residual size of tumors after cytoreduction and shorter disease-free and overall survival time. Exogenous AM induced ovarian cancer cell migration in time- and dose- dependent manners. AM upregulated the expression of integrin α5 and phosphorylation of FAK, paxillin as well.</p> <p>Conclusions</p> <p>Our results suggested that AM contributed to the progression of EOC and had additional roles in EOC cell migration by activating the integrin α5β1 signaling pathway. Therefore, we presumed that AM could be a potential molecular therapeutic target for ovarian carcinoma.</p

Airfoil-gust interactions in transonic flow

Leading edge noise is a significant broadband noise source in aircraft engines, and is the primary broadband noise mechanism in outlet guide vane noise in turbofans, and broadband rotor wake interaction noise in contra-rotating open rotor engines. Previous authors have studied the effects of various aspects relating to this noise source, including airfoil geometry effects, cascade effects, and Mach number effects. However, previous literature has not addressed the effects on the noise due to locally supersonic regions that might be present inthe mean flow around the rotor blades. The current work uses computational aeroacoustic methods to investigate the effects of locally supersonic regions on the noise due to airfoil-gust interactions. An established computational aeroacoustics code has been extended to give stable predictions in supersonic regions with a localized artificial diffusivity method.Initial results of a NACA 0012 airfoil in M = 0.8 flow interacting with oncoming vortical waves are shown, alongside results for a NACA 0006 airfoil in M = 0.5 flow at a 6 ? angle of attack. The changes to the noise and the underlying mechanisms are discussed for both cases, including additional noise sources caused by the supersonic region

Noise invariant frame selection: a simple method to address the background noise problem for text-independent speaker verification

The performance of speaker-related systems usually degrades heavily in practical applications largely due to the background noise. To improve the robustness of such systems in unknown noisy environments, this paper proposes a simple pre-processing method called Noise Invariant Frame Selection (NIFS). Based on several noisy constraints, it selects noise invariant frames from utterances to represent speakers. Experiments conducted on the TIMIT database showed that the NIFS can significantly improve the performance of Vector Quantization (VQ), Gaussian Mixture Model-Universal Background Model (GMM-UBM) and i-vector-based speaker verification systems in different unknown noisy environments with different SNRs, in comparison to their baselines. Meanwhile, the proposed NIFS-based speaker systems has achieves similar performance when we change the constraints (hyper-parameters) or features, which indicates that it is easy to reproduce. Since NIFS is designed as a general algorithm, it could be further applied to other similar tasks