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In contemporary society, individuals with substance abuse histories face a multitude of challenges that extend far beyond the physical and psychological effects of addiction. As they embark on the path of recovery and strive for reintegration into society, they are confronted with an additional formidable barrier: the pervasive stigma and discrimination that persistently accompany their past struggles. This dissertation seeks to illuminate the profound impact of stigma and discrimination on individuals with substance abuse histories, exploring the underlying factors that perpetuate these harmful attitudes, and proposing potential strategies to alleviate their burden. Comprised of three interconnected papers, this research analyzes trust dynamics, stigma, and social support towards this population, offering valuable insights for combating stigma and fostering a more inclusive and compassionate society.
The first paper focuses on the power of positive information to counteract negative stereotypes and enhance trust in everyday interactions involving individuals with substance abuse histories. By examining the ways in which positive information can mitigate stigmatizing perceptions, this paper uncovers strategies to promote understanding and empathy in social encounters, paving the way for more meaningful connections and reduced discrimination.
Moving forward, the second paper explores participants' perceptions of trust and trustworthiness when engaging with partners who possess varying substance abuse histories in a trust game. By investigating how participants' knowledge of their partners' backgrounds influences expectations of reciprocity and trustworthiness, this paper unravels the complex dynamics that shape interpersonal relationships. The findings shed light on the potential for shifting perceptions and dismantling biases, ultimately fostering an environment where trust can flourish. Lastly, the third paper investigates the social and relational factors that influence cooperation and support for individuals with substance abuse histories within familial and friendship networks. By identifying the barriers that hinder cooperation and providing recommendations for creating supportive environments, this paper aims to strengthen social support networks and facilitate a more compassionate and inclusive community for individuals in recovery.
Collectively, these three papers contribute to the broader goal of combating stigma, building trust, and fostering cooperation towards individuals with substance abuse histories. The findings underscore the pivotal role of positive information, perceptions of warmth and trustworthiness, and the significance of individual attitudes and social support networks in reducing stigma and cultivating an environment that embraces recovery. By revealing the complexities of stigma and discrimination, this dissertation aspires to inform policies, interventions, and societal attitudes that empower individuals with substance abuse histories to thrive and reintegrate into society with dignity and respect.
Additive manufacturing, specifically the Fused Deposition Modeling (FDM) method, has emerged as a promising technique for manufacturing. Using FDM, complex geometries can be created using precise layer-by-layer deposition of material. Among the advantages of this method are its cost-effectiveness, rapid prototyping capabilities, and ability to customize. Due to the similar melting point of ferroelectric polymers PVDF and PVDF-TrFE, which can be used for FDM printers, this study examined the possibility of using FDM for additive manufacturing of PVDF and PVDF-TrFE sensors with enhanced piezoelectric and pyroelectric properties. The resulting sensors can find applications in diverse fields such as biomedical engineering, robotics, energy harvesting, and sensing technologies, enabling advancements in various sectors that require sensitive and reliable sensor systems. Although both PVDF and PVDF-TrFE can be printed by FDM, the XRD result indicated that only PVDF-TrFE crystallized in the polar phase upon cooling from the melt while PVDF always crystallized in the nonpolar phase. Therefore, only PVDF-TrFE could be used for piezoelectric and pyroelectric samples. Using the corona discharge method, consistent responses from both piezoand pyroelectric sensors were observed. Using a 30 mW laser, samples were measured for pyroelectricity. Upon poling at 25 kV for 10 minutes at room temperature, the maximum pyroelectric response was 50 mV. Samples were clamped in one end and measured in deflection mode for their piezoelectric response. Upon stimulating the free end of a PVDF-TrFE sample printed on a PVDF layer as a substrate, 130 V of open circuit piezoelectric response was observed.
Recent advancements in manufacturing and post-processing of optics with sub-aperture methods have enabled greater degrees of freedom to realize complex optical surfaces. Introduction of residual mid-spatial frequency (MSF) surface errors is a consequence of sub-aperture manufacturing. MSF errors have spatial frequencies between ‘low frequency’ form and ‘high frequency’ roughness with ambiguous bounds and with distributions that range from nearly random to highly deterministic and complex, depending on manufacturing method and conditions. MSF errors degrade optical performance and present significant challenges for both specification and optical performance predictions. The lack of specifications that directly connect to optical performance and the lack of widely available capabilities and procedures for modeling of generalized MSF errors are significant impediments to understanding their impacts in imaging systems.
The primary goals of this dissertation are (1) to explore and expand the connections between MSF specifications and optical performance for complex MSF error distributions, and (2) to demonstrate the implementation of these concepts within commercial software packages to enable the exploration of generalized MSF errors in optical systems. Results are addressed through three articles. The first article addresses the mathematical development and benefits of pupil-difference probability distribution (PDPD) moments to specify MSF errors and connect them to optical performance. The second article builds from this work to provide modeling procedures and explores their application to both random and deterministic MSF errors. The third article demonstrates the integration of these new concepts and methods into MATLAB™ and CODE V™, and their use on sample refractive and reflective imaging systems.
From the perspective of manufacturing, it is not always ideal to use conventional methods of surface and optical metrology. Most optical metrology systems require a stable and pressure-temperature controlled environment in a laboratory setting as they are sensitive to such disturbances. The main contributing factor to these levels of sensitivity is the presence of a reference mirror. In most interferometric systems, interference patterns are generated by overlapping the wavefield generated from the object being measured with that generated from a reference mirror. Different algorithms can be used further by modulating the interference patterns to generate three-dimensional surface maps. Similar setups and algorithms could be used to not only generate the surface maps but also the object complex wavefield which extends its applications in digital holography. The goal of this research is to develop interferometric holography systems that are robust to environmental effects and suitable for in-situ metrology in manufacturing processes. Part 1 of this dissertation focuses on developing a lateral shear interferometric holography system using a pair of geometric-phase (GP) gratings. Two designs are proposed which allowed for different shear selection strategies. The proposed designs are robust to environmental effects by virtue of their design as a self-referenced and common-path configuration. A polarized camera sensor is used to record the interferograms with different phase shifts. Using an alternating projection algorithm, the recorded intensity maps are used to estimate the object wavefield. The errors generated by the algorithm are studied as a function of the shears selected to record the interferograms using synthetic intensity maps for both designs. The correlation is investigated using spatial and frequency information density functions and the errors generated by both designs are compared. Part 2 investigates the limitations of selected shears from the perspective of the spatial information density function. The major outcome from Parts 1 and 2 is proof that the shear selection strategies, the shear amounts, and the shear orientations affect the wavefield reconstruction. This leads to Part 3 of the dissertation which focuses on the optimal selection of shears for this system. Due to the complexity of the equations that govern the effect of shears on the reconstruction of different surface frequencies, a statistical approach was used to optimize the shears based on simulations that reconstructed a defocused point source wavefield. A point source wavefield is used for these simulations because it is the ideal wavefield demonstrating the reconstruction of all possible frequencies within the field of view. The results were compared to frequency information density maps to correlate the results. Parts 1,2 and 3 show a complete work starting from exploring designs to identifying optimal shear settings for a coherent digital holography system to measure transmissive and reflective samples. Part 4 shows a secondary application for this system that uses the GP grating pairs to make a fringe projection system that is suitable for diffused surfaces. The proposed system provides flexibility to adjust the characteristics of the projected fringes easily by changing the space between the gratings and the grating pair orientation. Example measurements are presented, and the capabilities of the setup are demonstrated. The proposed design can produce adjustable fringe patterns with fringe spacing varying from large values to as small as sub-millimeter distances. The fringe orientation can also be changed, and the patterns can be projected on objects of a wide range of sizes without losing the fringe contrast.
Recent advancements in vehicular technology aim to enhance traffic safety by warning drivers or automating driving tasks. Driver warning systems (DWSs) alert drivers to unsafe situations. Advanced driver assistance systems (ADASs) can actively control acceleration, braking, and steering, reducing the reliance on human drivers. Although vehicles with DWS and ADAS are expected to enhance safety, the effectiveness of these systems in real-world driving conditions with varying traffic and vehicle interactions remains a knowledge gap. This dissertation provides an analysis framework to identify factors influencing fatal crashes involving vehicles with varying DWSs and ADASs. The objectives include evaluating data on vehicles with various DWSs and ADASs, comparing factors affecting fatal crashes involving vehicles with and without these systems, and examining the influence of traffic and vehicle characteristics on safety. Logistic regression models are employed to analyze the data and identify factors affecting fatal crashes, considering different DWSs, ADASs, and crash types. The findings from this research contribute to improving traffic safety by enhancing the understanding of factors that influence fatal crashes involving vehicles with DWSs and ADASs. The results will assist in developing effective strategies to mitigate risks, improve the design of these technologies, and facilitate infrastructure planning for future adoption.
Gas Metal Arc Welding (GMAW) was investigated as a method for the rapid Wire Arc Additive Manufacturing (WAAM) of magnesium alloys. Magnesium AZ61a deposition wire was used to build multilayer walls, large blocks, and hollow cylinders using both high and low input-energy-rate (IER) parameters. The printed structures were analyzed to determine mechanical properties, microstructure, and porosity. Multilayer-wall samples printed at the same torch travel speed (TTS) showed a material yield strength (YS) of 120 MPa, independent of print orientation in relation to the applied tensile test pull force. The samples that were printed at a faster TTS showed the same response to loading conditions, but had a lower YS of 106 MPa, thus demonstrating how an increase in TTS lowers the YS of the deposited material. The stress-at-fracture for all these samples was between 260 MPa and 270 MPa. For the large multi-layer/multi-row (MRML) samples a YS of 120 MPa was also obtained but with lower stress-at-fracture points between 150 MPa and 220 MPa depending on print orientation, due to the presence of larger internal defects caused by bead overlap issues. Scanning Electron Microscope (SEM) analysis was performed on the fracture surface, showing ductile behavior in the fused regions and also uncovering material defects in the MRML samples such as trapped spatter, trapped gas bubbles, and cracks. Optical micrographs were obtained to analyze the microstructure of the samples in the heat affected zone (HAZ) as well as in the bulk material. Grain refinement from 38 µm pre-weld down to 10 µm and 28 µm post-weld was determined for MRML blocks and multilayer walls, respectively. Multilayer hollow cylinders were printed to test the ability of the method to produce closed-shape parts. These cylinders were produced at both high and low IERs and yielded parts with post-deposition machined wall thicknesses ranging from 1.5 mm to 4.5 mm. X-ray Computed Tomography (XCT) was performed to determine the porosity of these parts. The three sections analyzed showed a total-part percent porosity of 0.04 %, 0.039 %, and 0.07%. Larger individual defects, particularly at the closure-of-bead zone were detected, with a maximum single layer percent porosity of 0.8 %. Lastly, a Finite Element Analysis (FEA) model was created to simulate the deposition of the beads and the heat transfer throughout the process. The element activation feature in COMSOL Multiphysics was combined with the simulated torch path to model the deposition of the material. Heat transfer modes of conduction, radiation, and convection were conditionally assigned to the boundaries of the substrate and of the beads as functions of time and material deposition. The Goldak double-ellipsoid heat source was used as the input heating method for the substrate. To simulate the true-to-life GMAW process, where already molten material drops onto the substrate, a bead pre-heating function was created and applied to the inactive elements of the bead before it gets deposited during the simulation so that when the elements are activated above the weld pool they are at the correct temperature.
Traditional cyber defense approaches lack the necessary agility to effectively counter stealthy and undetectable attacks, placing defenders at a disadvantage. In response, Active Cyber Deception (ACD) has emerged as a promising solution by dynamically orchestrating deceptive environments to mislead and corrupt attackers' decision-making processes. However, the development of efficient and effective deception systems requires the integration of human intelligence and comprehensive malware analysis to understand attack behaviors and automate deception strategies.
This dissertation presents three innovative approaches in the field of ACD. Firstly, DodgeTron combines dynamic analysis using symbolic execution tools and machine learning to automate the creation of deception schemes against malware by categorizing malware into known families and utilizing HoneyThings. Secondly, symbSODA performs dynamic analysis on real-world malware and data flow analysis to extract malicious sub-graphs (MSGs) and map them to the MITRE ATT&CK framework using Natural Language Processing. This enables the creation of a Deception Playbook for deceiving specific malicious behaviors with deceptive API hookings. Finally, ranDecepter integrates active cyber deception to identify ransomware in its early stages and employs binary orchestration methods to repurpose the malware as a channel for exhaustively transmitting encryption information (including keys) to the attacker, effectively depleting their available resources.
Comprehensive evaluations validate the accuracy and effectiveness of these approaches in deceiving adversaries, reducing analysis time, and mitigating malware threats. This research significantly contributes to the field of active cyber deception and offers efficient and scalable solutions for protecting digital systems against sophisticated adversaries.
Dense and porous Silicon Carbide (SiC) ceramics and composites are used in a wide range of applications that require high thermal, mechanical, and electrical stability, excellent corrosion, and wear resistance. However, manufacturing of SiC through conventional powder metallurgy technique techniques is often challenging due. Due to the covalent bonding between Si and C, they have a high melting point. Hence high temperatures, pressures, and controlled atmospheres are required during sintering to manufacture SiC ceramic with good mechanical and thermal strength. Other techniques to manufacture SiC at relatively low temperatures involve thermal oxidation, pressureless sintering, and the addition of sintering additives. Some applications like biological scaffolds, ballistic armor, space mirror substrates, and ceramic filters involve complex geometries. Manufacturing of complex geometries through the conventional route involves machining or molding. Machining SiC is a challenge due to its extreme hardness and abrasiveness. Molding a pre-form utilizes polymer resin which can cause shrinkage to the final product. upon debinding and sintering. Hence, the additive manufacturing route is considered feasible for the manufacturing of SiC ceramics or composites. Additive manufacturing (AM) enables 3D printing of complex geometries from a CAD model. Multiple direct AM methods were realized for the printing of SiC such as selective laser sintering (SLS), selective laser melting (SLM), stereolithography (SL), direct ink writing (DIW), and binder jetting (BJ). Among these techniques, the binder jetting technique was found to be easier to manufacture complex geometries of SiC as it does not require, i) polymer additives that cause shrinkage of the part upon sintering and it doesn’t require, ii) high laser power to melt SiC, and iii) ceramic slurry, where the amount of ceramic used is less. Binder jetting also allows the mixing of different ceramic particles and additives that can help in the densification and strengthening of the printed part. In this work, the following areas are addressed: i) a route for densifying and strengthening the powder bed binder jet-printed SiC through the mixing of particles of different sizes, formation of siloxane bonding, secondary surface modification, and sintering, ii) strengthening and densification of SiC composites using mineral binders using powder metallurgy technique, and iii) realizing the properties of SiC-mineral binder composites for space mirror and thermal applications. Part (ii) of the project was preliminary work done in order to realize the outcomes of SiC-mineral binder composites in strengthening so that it can be adopted into additive manufacturing mentioned in part (i). Future work will involve the inclusion of SiC-mineral binders into the feedstock in a powder bed binder jet in order to reduce the voids between the interspace of SiC particles and to have a strong interfacial region comprising of mineral binders that can fuse the SiC particles together and densify the printed part. This eliminates the need for the post-processing techniques such as melt infiltration, polymer impregnation, or chemical vapor infiltration.
SiC ceramics are 3D printed into cylindrical discs in a powder bed binder jet using a water binder. In this method, SiC of an average particle size of 40 µm was surface activated with NaOH to form a silica gel layer at room temperature, to which, 30% of 2 µm and 600 nm SiC particles were added and mixed homogeneously through milling. The presence of OH- ions in silica gel, creates a repulsion between SiC particles which eliminates agglomeration of particles upon spreading. The mixing of coarse and fine particle sizes reduced the percentage porosity by 50%. The as-printed green part was heat treated to 650 °C for 5h to create siloxane bonding which provided an improved handling strength. The heat-treated parts were then impregnated in various concentrations of NaOH to create silica gel through secondary surface activation. SEM images showed that the impregnated samples had more silica nucleation droplets that gave rise to silica nanowires upon sintering at temperatures between 800 °C – 1000 °C. The silica nanowires are responsible for fusing the SiC particles and bridging the pores. The optimum NaOH concentration for secondary surface activation, sintering temperature, and dwell time were determined. A 100% increase in the strength of the SiC was obtained in the samples heat treated at 650 °C, impregnated in 20% NaOH, and sintered at 1000 °C for 24h. Moreover, the formation of nanowires under an oxygen environment proved that silica nanowires can be formed at a temperature as low as 800 °C, and in air, the discs are oxygen deprived which hinders the growth of silica nanowires. Hence the mechanism of the growth of nanowires was found to be similar to the solid-vapor phase deposition. Cordierite and spodumene are silicate minerals that are known for their excellent thermal properties namely nearly zero thermal expansion coefficient. SiC is a ceramic with excellent mechanical and thermal properties. SiC, Cordierite, and Spodumene are materials that are considered for space mirrors, mirror substrates, and high-temperature applications. However, the glass ceramic form of Cordierite and Spodumene are less considered for space applications due to their poor stiffness and fracture toughness. On the other hand, SiC is highly considered for such applications however manufacturing them is a challenge considering their high melting point and hardness. Hence, in this work, a combination of SiC and the mineral format of cordierite and spodumene is introduced as SiC-mineral binder composites. SiC-mineral binder composites are 80% SiC and 20% Cordierite or Spodumene minerals prepared through the powder metallurgy technique. SiC-mineral binder composites were found to have good mechanical and thermal properties and can be a promising candidate for space mirror applications. SiC-mineral binders were combined with 1% of NaOH, pressed at 250 MPa, and heat treated to 1200 °C for 8 h. The SEM-EDX analysis showed a strong interfacial region of cordierite or spodumene fusing the SiC particles together. The fracture mechanism was found to be transgranular which is due to the strong interfacial bond that was created by the atomic diffusion of Si and Al at the grain boundary of SiC and the mineral interface. The characterization involves the comparison of SiC-mineral binders to the control SiC-cristobalite without mineral binders. The phase analysis from XRD showed the presence of cordierite, spodumene, and cristobalite phases. A transformation of β-SiC to α-SiC was also observed. A slight shift in the d-spacing, the lattice constants, and crystallite size was observed as a result of a solid solution of phases. The density and porosity of these composites were measured using Archimedes and mercury porosimetry. Further pore size analyses were done using SEM and ImageJ analysis. The results showed that the introduction of mineral binders reduced the pore size and the porosity percentage. The compressive strength of the SiC-Cordierite and SiC-Spodumene was 282.57 MPa and 184.58 MPa which was much higher than the control SiC-Cris, 97.45 MPa. The average compressive strength of SiC-Cord was three times higher than control SiC-Cris (p < 9.7 x 10-7) and two times higher than that of SiC-Spod (p <0.003). Moreover, the average compressive strength of the SiC-Spod was significantly higher than that of the control SiC-Cris (p <9.8 x10-7). Elastic modulus was found using the nanoindentation technique and was 380.54 GPa and 341.04 GPa for SiC-Cord and SiC-Spod composites. Thermal shock resistance is an important factor for materials to qualify for space applications. SiC-mineral composites showed excellent thermal shock resistance and dimensional stability when quenched from 1200 °C to room temperature. A thermal expansion coefficient of 3 x 10-6 /K was obtained for both SiC-Cord and SiC-Spod composites. The SiC-mineral composites were polished to a mirror finish and the surface roughness of areas comprised of SiC particles along with the mineral binder without pores measured using atomic force microscopy was 20.89 nm. The mean roughness of the SiC microconstituent in the SiC-Cord composite was found to be 2.37 ± 0.28 nm. Owing to these excellent thermos-mechanical properties, SiC-mineral binder composites are promising candidates for space mirror applications, mirror substrates, substrates for high-temperature devices, and catalytic converters. Also, porous SiC-mineral binder composites can be used as gas/fuel filters for automobile industries.
Recent advances in the field of Natural Language Processing, specifically in Natural Language Generation (NLG) towards Dialogue Systems have focused mainly on two-party conversations. However, group conversations or multi-party conversations (MPC) are just as prevalent in our everyday lives. While the area of multi-party conversation modeling has received some attention in recent times, MPC lacks resources for 1) corpora in differing settings (formal/informal, synchronous/asynchronous), 2) dialogue models which can participate in informal open-domain settings while maintaining speaker information, and 3) evaluation metrics which provide better insights into the performance of MPC models when it comes to operating in groups and interacting with multiple participants. We thus take a three-pronged approach towards contributing to research in the MPC modeling research area. For corpora collection, we contribute a mock social media tool that can be utilized for collecting asynchronous MPC conversations called Community Connect and utilize it for 3 experiments to collect everyday talk. For MPC modeling, we propose a response generation model, using large language models (LLMs) and graph structured networks, which is capable of taking participant relations into account towards maintaining multiple persona profiles and generating responses keeping the speaker characteristics in mind and responding accordingly. Lastly, for MPC evaluation, we present an expansion to the taxonomy of errors which specifically contributes MPC-specific metrics to the overall NLG errors. In addition to the taxonomy, we contribute to better evaluation standards across which progress in the tasks within MPC can be tracked more saliently. Through these contributions, we aim to fill the necessary gaps towards advancing MPC understanding and modeling, while also providing the tools to gauge progress until now.
