Microplastics in Our Oceans May Inhibit Aerosols From Cooling the Atmosphere

Sea spray aerosol (SSA) are liquid gaseous particles emitted directly from the ocean, making their way into the atmosphere. It is hypothesized that SSA enters the atmosphere from mechanical processes such as wind and ocean waves. Winds and waves promote bubble formation and these bubbles which make their way onto the ocean surface. After these wave-created bubbles rise to the ocean surface, the bubble ruptures and water evaporates which causes gaseous drops to be released into the air: this is the main source of SSA. SSA matter is known to affect Earth’s climate, by scattering light energy and solar radiation from the surrounding environment. They can also affect global temperature levels because they aid in cloud formation. With Earth’s waters covering about three-fourths of the planet’s surface area, SSA is crucial for managing Earth’s radiation budget. Their important environmental role may be blunted due to an ominous problem: ocean pollution. Microplastics in our oceans affect how and if aerosols form. This study goes into detail of how microplastics affect SSA formation and its implications. This experiment utilizes ocean movement laboratory simulations to measure SSA generation in the presence of various microplastics. The data suggests that larger microplastics have a greater, more significant effect on reducing aerosol production than finer, powdery plastics

Ground Robotic Hand Applications for the Space Program study (GRASP)

This document reports on a NASA-STDP effort to address research interests of the NASA Kennedy Space Center (KSC) through a study entitled, Ground Robotic-Hand Applications for the Space Program (GRASP). The primary objective of the GRASP study was to identify beneficial applications of specialized end-effectors and robotic hand devices for automating any ground operations which are performed at the Kennedy Space Center. Thus, operations for expendable vehicles, the Space Shuttle and its components, and all payloads were included in the study. Typical benefits of automating operations, or augmenting human operators performing physical tasks, include: reduced costs; enhanced safety and reliability; and reduced processing turnaround time

Evolvable Reconfigurable Hardware Framework for Edge Detection

Systems on Reconfigurable Chips contain rich resources of logic, memory, and processor cores on the same fabric. This platform is suitable for implementation of Evolvable Reconfigurable Hardware Architectures (ERHA). It is based on the idea of combining reconfigurable Field Programmable Gate Arrays (FPGA) along with genetic algorithms (GA) to perform the reconfiguration operation. This architecture is a suitable candidate for implementation of early-processing stage operators of image processing such as filtering and edge detection. However, there are still fundamental issues need to be solved regarding the on-chip reprogramming of the logic. This paper presents a framework for implementing an evolvable hardware architecture for edge detection on Xilinx Virtex–4 chip. Some preliminary results are discussed

Exploring clinical phenotypes of open-angle glaucoma and their significance in practice

There are several enduring questions regarding the differentiation of clinical phenotypes of glaucoma which clinicians may derive clinical meaning directed towards patient’s management and prognostication. This thesis seeks to address the following issues relating to distinguishing clinical phenotypes of glaucoma: “Evaluating the impact of changing visual field test density on macular structure-function relationships to identify central-involving glaucoma phenotypes”; and “Identifying quantitative structural and functional clinical parameters that may distinguish between intraocular pressure (IOP) defined glaucoma phenotypes”; Two studies were undertaken to examine clinical phenotypes of glaucoma. The first study utilised systematic approach to assessing the impact of test point density in macular visual field (VF) testing on structure-function concordance for identifying centrally-involving glaucoma phenotypes. The second study used multivariate regression analysis and principal component analysis (PCA) to examine quantitative structural (using optical coherence tomography) and functional (VF) clinical data of newly-diagnosed glucoma patients to determine if there are clinically meaningful distinctions between IOP-defined phenotypes (i.e. low-tension vs high-tension glaucoma). Study 1) Using a systematic approach of test point addition and subtraction, we identified a critical number of test locations (8-14) in macular VF testing where binarised structure-function concordance is maximised, and discordance minimised. This methodology provides a framework for optimising macular VF test patterns for detection of centrally-involving glaucoma phenotypes. Study 2) Despite statistical significance in differences between low- and high-tension glaucoma, PCA applied to quantitative clinical structural and functional parameters returned no groups of clinical parameters that reliably distinguished between patients in IOP-defined glaucoma phenotypes. The present work provides a framework to identify phenotypic groups of glaucoma, the clinical significance of which may vary. We identified the minimum number of test points required to detect central-involving glaucoma in visual field testing. We also demonstrate that IOP-defined phenotypes are not clinically distinguishable at the point of diagnosis, suggesting that these phenotypes form part of a continuum of open-angle glaucoma. These findings have implications for disease staging and preferred treatment modality

Real-Time 3D Image Visualization System for Digital Video on a Single Chip

Implementation of a real-time image visualization system on a reconfigurable chip (FPGA) is proposed. The system utilizes an innovative stereoscopic image capture, processing and visualization technique. Implementation is done as a two stage process. In the first stage, the stereo pair is captured using two image sensors. The captured images are then synchronized and sent to the second stage for fusion. A controller module is developed, designed, and placed on the FPGA for this purpose. The second stage is used for reconstruction and visualization of the 3D image. An innovative technique employing dual-processor architecture on the same single FPGA is developed for this purpose. The whole system is placed on a single PCB resulting in a fast processing time and the ability to view 3D video in real-time. The system is simulated, implemented, and tested on real images. Results show that this system is a low cost solution for efficient 3D video visualization using a single chip

Behaviour and strength of concrete beams reinforced and/or prestressed with FRP bars.

Concrete beams reinforced and/or prestressed with steel bars are used in a wide range of structures. However, the deterioration of such structures due to reinforcement corrosion is a major problem. The repair and maintenance of steel reinforced concrete structures, especially highway bridges, is quite costly in locations subject to severe weather conditions of rain and/or snow as in Canada and the USA. In order to overcome this problem, Advanced Composite Materials (ACM), which are produced in the form of Fibre Reinforced Polymers (FRP), are becoming a desirable replacement to the traditional steel reinforcement. While both materials have identical functions, basic differences exist in the mechanical properties between steel and FRP that should be taken into account in the structural design and analysis of concrete beams reinforced and/or prestressed with FRP bars. For example, a ductile failure takes place for steel bars subjected to tensile and/or shear stresses, while brittle failure takes place for FRP bars. Further more, FRP bars provide high tensile strength, while their modulus of elasticity and shear strength are lower than those of steel bars. These variations in properties lead to significant differences in the behaviour between concrete beams reinforced and/or prestressed with FRP bars and those reinforced and/or prestressed with steel bars. The properties of the reinforcing material, in both longitudinal and transverse directions, interact with the characteristics of the formed cracks, i.e. crack geometry and crack width, to determine the beam strength, as well as the mode of failure. Therefore, a reliable study of the behaviour and strength of concrete beams reinforced with FRP bars should include some parameters that used to be neglected in case of steel reinforcement such as crack geometry, crack width, and the mechanical properties of bars in their transverse direction. An experimental program has been conducted at the University of Windsor to study the above mentioned parameters and their effects on the behaviour and strength of both prestressed and non-prestressed concrete beams reinforced with Carbon Fibre Reinforced Polymer (CFRP) bars. The results of the study have been expressed through an analytical model that describes the interactive behaviour between crack progress, and the stresses induced in concrete as well as in both flexural and shear reinforcement. The degree of accuracy in modelling the crack path geometry has been also found to control the reliability of the calculated beam strength. A comparison has been made between the results of the proposed analytical modelling and those obtained from the experimental program mentioned above, as well as from other published test data. A good agreement has been observed between the analytical and experimental results. Another comparison has been made between the experimental beam strength, the strength obtained by the present analytical model, and the strength calculated by the formulas recommended by different design guidelines issued recently for FRP reinforced and/or prestressed concrete structures. The comparison emphasised the necessity of considering the above-mentioned parameters in order to achieve an accurate prediction of beam strength.Dept. of Civil and Environmental Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2001 .S25. Source: Dissertation Abstracts International, Volume: 62-10, Section: B, page: 4671. Adviser: George Abdel-Sayed. Thesis (Ph.D.)--University of Windsor (Canada), 2001

On-Chip Intrinsic Evolution Methodology for Sequential Logic Circuit Design

This paper focuses on the application of Virtual Reconfigurable Circuit (VRC) design methodology and intrinsic evolution for the design of small sequential circuits and their implementation on a single programmable chip with an embedded hardcore processor. The evolutionary algorithm is developed in software that runs on the embedded processor. Fitness function is calculated using hardware architecture and is used to guide the evolution process. This new method is applied to the development of a 3-bit sequence detector and the evolved architecture is implemented on a Xilinx™ Virtex-II pro device. Simulations were run on the evolved architecture and on the same circuit designed using conventional Hardware Descriptive Language (HDL). Both designs showed the same functional behavior. Synthesis results show that the new method can be used in successfully implementing small sequential circuits on a reconfigurable hardware environment

A Reconfigurable Pattern Matching Hardware Implementation Using On-Chip RAM-Based FSM

The use of synthesizable reconfigurable IP cores has increasingly become a trend in System on Chip (SoC) designs because of their flexibility and powerful functionality. The market introduction of multi-featured platform FPGAs equipped with embedded memory and processor blocks has further expanded the possibility of utilizing dynamic reconfiguration to improve overall system adaptability to meet varying product requirements. In this paper, a reconfigurable hardware implementation for pattern matching using Finite State machine (FSM) is proposed. The FSM design is RAMbased and is reconfigured on the fly through altering memory contents only. An embedded processor is used for orchestrating run time reconfiguration. Experimental results show that the system can reconfigure itself based on a new incoming pattern and perform the text search without the need of a host processor. Results also proved that each search iteration was executed in one clock cycle and the maximum achievable clock frequency is independent of search pattern length

A Study of Finite State Machine Coding Styles for Implementation in FPGAs

Finite State Machines (FSM), are one of the more complex structures found in almost all digital systems today. Hardware Description Languages are used for high-level digital system design. VHDL (VHSIC Hardware Description Language) provides the capability of different coding styles for FSMs. Therefore, a choice of a coding style is needed to achieve specific performance goals and to minimize resource utilization for implementation in a re-configurable computing environment such as an FPGA. This paper is a study of the tradeoffs that can be made by changing coding styles. A comparative study on three different FSM coding styles is shown to address their impact on performance and resource utilization for the most commonly used encoding methods for FPGA designs. The results show that a particular coding style leads to a savings in resource utilization with a significant performance improvement over the others while the others pose a consistent performance regardless of the resource utilization outcome

Hardware Trojan Detection in Chips by Removing Dependencies Between Features in Machine Learning

Globally, there has been an increase in demand for System on Chip (SoC) applications, active medical implants, and Internet of Things (IoT) devices. However, due to challenges in the global supply chain, the design, fabrication, and testing of Integrated Circuits are often outsourced to untrusted third-party entities around the world rather than a single trusted entity. This situation presents an opportunity for adversaries to compromise the device\u27s integrity, performance, and functionality by inserting malicious modifications known as Hardware Trojans (HTs) into the original design. HTs can also create a backdoor in the system for malicious alterations. In this research, a solution to the issue of hardware trojan is presented through the utilization of machine learning models that rely on supervised and unsupervised learning. The proposed method involves providing the netlist features of the digital hardware design post-synthesis to the machine learning model and removing any interdependence between features to prevent overfitting of the training dataset. The supervised model showed a 99.2\% true positive and true negative rate, as well as an F-measure of 99.3\%, while the unsupervised model achieved a 99.5\% true positive rate with the use of random projection, thereby offering a more resilient machine learning-based method for detecting hardware trojans