Saliency Driven Vasculature Segmentation with Infinite Perimeter Active Contour Model

Automated detection of retinal blood vessels plays an important role in advancing the understanding of the mechanism, diagnosis and treatment of cardiovascular disease and many systemic diseases, such as diabetic retinopathy and age-related macular degeneration. Here, we propose a new framework for precisely segmenting retinal vasculatures. The proposed framework consists of three steps. A non-local total variation model is adapted to the Retinex theory, which aims to address challenges presented by intensity inhomogeneities, and the relatively low contrast of thin vessels compared to the background. The image is then divided into superpixels, and a compactness-based saliency detection method is proposed to locate the object of interest. For better general segmentation performance, we then make use of a new infinite active contour model to segment the vessels in each superpixel. The proposed framework has wide applications, and the results show that our model outperforms its competitors

Quantification of Physiological Disparities and Task Performance in Stress and Control Conditions

In mental stress studies, cerebral activation and autonomic nervous system are important distinctly. This study aims to analyze disparities associated with scalp potential, which may have impact on autonomic activation of heart during mental stress. Ten healthy subjects participated in this study that performed arithmetic tasks in stress and control environment. Task difficulty was calculated from their correct responses. During the experiment, electroencephalogram (EEG) and electrocardiogram (ECG) signals were recorded concurrently. Sympathetic innervation of heart was estimated from heart rate (HR), which is extracted from the ECG. The value of theta Fz/alpha Pz was measured from EEG scalp potential. The results show a significant surge in the value of theta Fz/alpha Pz in stress as compared to baseline (p<;0.013) and control (p<;0.042). The results also present tachycardia while in stress as compared to baseline (p<;0.05). Task difficulty in stress is also considerably higher than control environment (p<;0.003)

Photoinduced Production of Chlorine Molecules from Titanium Dioxide Surfaces Containing Chloride

Titanium dioxide (TiO2) is extensively used with the process of urbanization and potentially influences atmospheric chemistry, which is yet unclear. In this work, we demonstrated strong production of Cl-2 from illuminated KCl-coated TiO2 membranes and suggested an important daytime source of chlorine radicals. We found that water and oxygen were required for the reactions to proceed, and Cl-2 production increased linearly with the amount of coated KCl, humidity of the carrier gas, and light intensity. These results suggested that water promotes the reactivity of coated KCl via interaction with the crystal lattice to release free chloride ions (Cl-). The free Cl- transfer charges to O-2 via photoactivated TiO2 to form Cl-2 and probably the O-2(-) radical. In addition to Cl-2, ClO and HOCl were also observed via the complex reactions between Cl/Cl-2 and HOx. An intensive campaign was conducted in Shanghai, during which evident daytime peaks of Cl-2 were observed. Estimated Cl-2 production from TiO2 photocatalysis can be up to 0.2 ppb/h when the TiO2-containing surface reaches 20% of the urban surface, and highly correlated to the observed Cl-2. Our results suggest a non-negligible role of TiO2 in atmospheric photochemistry via altering the radical budget.Peer reviewe

Heterogeneous N2O5 reactions on atmospheric aerosols at four Chinese sites : improving model representation of uptake parameters

Heterogeneous reactivity of N2O5 on aerosols is a critical parameter in assessing NOx fate, nitrate production, and particulate chloride activation. Accurate measurement of its uptake coefficient (gamma N2O5) and representation in air quality models are challenging, especially in the polluted environment. With an in situ aerosol flow-tube system, the gamma N2O5 was directly measured on ambient aerosols at two rural sites in northern and southern China. The results were analyzed together with the gamma N2O5 derived from previous field studies in China to obtain a holistic picture of gamma N2O5 uptake and the influencing factors under various climatic and chemical conditions. The field-derived or measured gamma N2O5 was generally promoted by the aerosol water content and suppressed by particle nitrate. Significant discrepancies were found between the measured gamma N2O5 and that estimated from laboratory-determined parameterizations. An observation-based empirical parameterization was derived in the present work, which better reproduced the mean value and variability of the observed gamma N2O5. Incorporating this new parameterization into a regional air quality model (WRF-CMAQ) has improved the simulation of N2O5, nitrogen oxides, and secondary nitrate in the polluted regions of China.Peer reviewe

Automatic generation of high level fault simulation models for analogue circuits

High level modelling (HLM) for operational amplifiers (op amps) has been previously carried out successfully using models generated by published automated model generation (AMG) approaches. Furthermore, high level fault modelling (HLFM) has been shown to work reasonably well using manually designed fault models. However, no evidence shows that published AMG approaches based on op amps have been used in HLFM.This thesis describes an investigation into the development of adaptive self-tuning algorithms for automated analogue circuit modelling suitable for HLM and HLFM applications. The algorithms and simulation packages were written in MATLAB and the hardware description language - VHDL-AMS.The properties of these self-tuning algorithms were investigated by modelling a two-stage CMOS op amp and a comparator, and comparing simulations of the macromodel against those of the original SPICE circuit utilizing transient analysis.The proposed algorithms generate multiple models to cover a wide range of input conditions by detecting nonlinearity through variations in output error, and can achieve bumpless transfer between models and handle nonlinearity.This thesis describes the design, implementation and validation of these algorithms, their performance being evaluated for HLFM for both analogue and mix mode systems.HLFM results show that the models can handle both linear and nonlinear situations with good accuracy in a low-pass filter, and model digital outputs in a flash ADC correctly. Comparing with a published fault model, better accuracy has been achieved in terms of output signals using fault coverage measurement

Automatic generation of high level fault simulation models for analogue circuits

High level modelling (HLM) for operational amplifiers (op amps) has been previously carried out successfully using models generated by published automated model generation (AMG) approaches. Furthermore, high level fault modelling (HLFM) has been shown to work reasonably well using manually designed fault models. However, no evidence shows that published AMG approaches based on op amps have been used in HLFM.This thesis describes an investigation into the development of adaptive self-tuning algorithms for automated analogue circuit modelling suitable for HLM and HLFM applications. The algorithms and simulation packages were written in MATLAB and the hardware description language - VHDL-AMS.The properties of these self-tuning algorithms were investigated by modelling a two-stage CMOS op amp and a comparator, and comparing simulations of the macromodel against those of the original SPICE circuit utilizing transient analysis.The proposed algorithms generate multiple models to cover a wide range of input conditions by detecting nonlinearity through variations in output error, and can achieve bumpless transfer between models and handle nonlinearity.This thesis describes the design, implementation and validation of these algorithms, their performance being evaluated for HLFM for both analogue and mix mode systems.HLFM results show that the models can handle both linear and nonlinear situations with good accuracy in a low-pass filter, and model digital outputs in a flash ADC correctly. Comparing with a published fault model, better accuracy has been achieved in terms of output signals using fault coverage measurement

Automatic generation of high level fault simulation models for analogue circuits

High level modelling (HLM) for operational amplifiers (op amps) has been previously carried out successfully using models generated by published automated model generation (AMG) approaches. Furthermore, high level fault modelling (HLFM) has been shown to work reasonably well using manually designed fault models. However, no evidence shows that published AMG approaches based on op amps have been used in HLFM.This thesis describes an investigation into the development of adaptive self-tuning algorithms for automated analogue circuit modelling suitable for HLM and HLFM applications. The algorithms and simulation packages were written in MATLAB and the hardware description language - VHDL-AMS.The properties of these self-tuning algorithms were investigated by modelling a two-stage CMOS op amp and a comparator, and comparing simulations of the macromodel against those of the original SPICE circuit utilizing transient analysis.The proposed algorithms generate multiple models to cover a wide range of input conditions by detecting nonlinearity through variations in output error, and can achieve bumpless transfer between models and handle nonlinearity.This thesis describes the design, implementation and validation of these algorithms, their performance being evaluated for HLFM for both analogue and mix mode systems.HLFM results show that the models can handle both linear and nonlinear situations with good accuracy in a low-pass filter, and model digital outputs in a flash ADC correctly. Comparing with a published fault model, better accuracy has been achieved in terms of output signals using fault coverage measurement.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Review of high level fault modeling approaches for mixed-signal systems

In the modern analogue design, Transistor Level Fault Simulation (TLFS) plays the importantpart since every fault in the whole circuit has to be simulated at that level. Unfortunately, it isa very CPU intensive task even though it maintains the high accuracy. Therefore, High Level FaultModeling (HLFM) and High Level Fault Simulation (HLFS) are required in order to alleviate the effortsof simulation. In this paper, different HLFM approaches are reviewed at the device level during last twodecades. We clarify their domains of application and evaluate their strengths and current limitations.We also analyze causes of faults and introduce various test approaches