Quantifying the complexity of chaos in multibasin multidimensional dynamics of molecular systems

The simulated classical dynamics of a small molecule exhibiting self-organizing behavior via a fast transition between two states is analyzed by calculation of the statistical complexity of the system. It is shown that the complexity of molecular descriptors such as atom coordinates and dihedral angles have different values before and after the transition. This provides a new tool to identify metastable states during molecular self-organization. The highly concerted collective motion of the molecule is revealed. Low-dimensional subspaces dynamics is found sensitive to the processes in the whole, high-dimensional phase space of the system. © 2004 Wiley Periodicals, Inc.

Experimental analysis of novel telecom source materials and devices

Incumbent telecommunication lasers emitting at 1.5 µm are fabricated on InP substrates and consist of multiple strained quantum well layers of the ternary alloy InGaAs, with barriers of InGaAsP or InGaAlAs. These lasers have been seen to exhibit very strong temperature dependence of the threshold current. This strong temperature dependence leads to a situation where external cooling equipment is required to stabilise the optical output power of these lasers. This results in a significant increase in the energy bill associated with telecommunications, as well as a large increase in equipment budgets. If the exponential growth trend of end user bandwidth demand associated with the internet continues, these inefficient lasers could see the telecommunications industry become the dominant consumer of world energy. For this reason there is strong interest in developing new, much more efficient telecommunication lasers. One avenue being investigated is the development of quantum dot lasers on InP. The confinement experienced in these low dimensional structures leads to a strong perturbation of the density of states at the band edge, and has been predicted to result in reduced temperature dependence of the threshold current in these devices. The growth of these structures is difficult due to the large lattice mismatch between InP and InAs; however, recently quantum dots elongated in one dimension, known as quantum dashes, have been demonstrated. Chapter 4 of this thesis provides an experimental analysis of one of these quantum dash lasers emitting at 1.5 µm along with a numerical investigation of threshold dynamics present in this device. Another avenue being explored to increase the efficiency of telecommunications lasers is bandstructure engineering of GaAs-based materials to emit at 1.5 µm. The cause of the strong temperature sensitivity in InP-based quantum well structures has been shown to be CHSH Auger recombination. Calculations have shown and experiments have verified that the addition of bismuth to GaAs strongly reduces the bandgap and increases the spin orbit splitting energy of the alloy GaAs1−xBix. This leads to a bandstructure condition at x = 10 % where not only is 1.5 µm emission achieved on GaAs-based material, but also the bandstructure of the material can naturally suppress the costly CHSH Auger recombination which plagues InP-based quantum-well-based material. It has been predicted that telecommunications lasers based on this material system should operate in the absence of external cooling equipment and offer electrical and optical benefits over the incumbent lasers. Chapters 5, 6, and 7 provide a first analysis of several aspects of this material system relevant to the development of high bismuth content telecommunication lasers.

Geometric properties of 2-dimensional minimal surfaces in a sub-Riemannian manifold which models the Visual Cortex

In this paper we study the notion of degree forsubmanifolds embedded in an equiregular sub-Riemannian manifold and we provide the definition of their associated area functional. In this setting we prove that the Hausdorff dimension of a submanifold coincides with its degree, as stated by Gromov. Using these general definitions we compute the first variation for surfaces embedded in low dimensional manifolds and we obtain the partial differential equation associated to minimal surfaces. These minimal surfaces have several applications in the neurogeometry of the visual cortex.

Convective Cold Pools over the Atlas Mountains and Their Influence on the Saharan Heat Low

The West African Monsoon (WAM) and its representation in numerical models are strongly influenced by the Saharan Heat Low (SHL), a low-pressure system driven by radiative heating over the central Sahara and ventilated by the cold and moist inflow from adjacent oceans. It has recently been shown that a significant part of the southerly moisture flux into the SHL originates from convective cold pools over the Sahel. These density currents driven by evaporation of rain are largely absent in models with parameterized convection. This crucial issue has been hypothesized to contribute to the inability of many climate models to reproduce the variability of the WAM. Here, the role of convective cold pools approaching the SHL from the Atlas Mountains, which are a strong orographic trigger for deep convection in Northwest Africa, is analyzed. Knowledge about the frequency of these events, as well as their impact on large-scale dynamics, is required to understand their contribution to the variability of the SHL and to known model uncertainties. The first aspect is addressed through the development of an objective and automated method for the generation of multi-year climatologies not available before. The algorithm combines freely available standard surface observations with satellite microwave data. Representativeness of stations and influence of their spatial density are addressed by comparison to a satellite-only climatology. Applying this algorithm to data from automated weather stations and manned synoptic stations in and south of the Atlas Mountains reveals the frequent occurrence. On the order of 6 events per month are detected from May to September when the SHL is in its northernmost position. The events tend to cluster into several-days long convectively active periods, often with strong events on consecutive days. This study is the first to diagnose dynamical impacts of such periods on the SHL, based on simulations of two example cases using the Weather Research and Forecast (WRF) model at convection-permitting resolution. Sensitivity experiments with artificially removed cold pools as well as different resolutions and parameterizations are conducted. Results indicate increases in surface pressure of more than 1 hPa and significant moisture transports into the desert over several days. This moisture affects radiative heating and thus the energy balance of the SHL. Even though cold pool events north of the SHL are less frequent when compared to their Sahelian counterparts, it is shown that they gain importance due to their temporal clustering on synoptic timescale. Together with studies focusing on the Sahel, this work emphasizes the need for improved parameterization schemes for deep convection in order to produce more reliable climate projections for the WAM.

Flexible Sensor for Wearable Vital Sign Monitoring System

In modern society, the body health is a very important issue to everyone. With the development of the science and technology, the new and developed body health monitoring device and technology will play the key role in the daily medical activities. This paper focus on making progress in the design of the wearable vital sign system. A vital sign monitoring system has been proposed and designed. The whole detection system is composed of signal collecting subsystem, signal processing subsystem, short-range wireless communication subsystem and user interface subsystem. The signal collecting subsystem is composed of light source and photo diode, after emiting light of two different wavelength, the photo diode collects the light signal reflected by human body tissue. The signal processing subsystem is based on the analog front end AFE4490 and peripheral circuits, the collected analog signal would be filtered and converted into digital signal in this stage. After a series of processing, the signal would be transmitted to the short-range wireless communication subsystem through SPI, this subsystem is mainly based on Bluetooth 4.0 protocol and ultra-low power System on Chip(SoC) nRF51822. Finally, the signal would be transmitted to the user end. After proposing and building the system, this paper focus on the research of the key component in the system, that is, the photo detector. Based on the study of the perovskite materials, a low temperature processed photo detector has been proposed, designed and researched. The device is made up of light absorbing layer, electron transporting and hole blocking layer, hole transporting and electron blocking layer, conductive substrate layer and metal electrode layer. The light absorbing layer is the important part of whole device, and it is fabricated by perovskite materials. After accepting the light, the electron-hole pair would be produced in this layer, and due to the energy level difference, the electron and hole produced would be transmitted to metal electrode and conductive substrate electrode through electron transporting layer and hole transporting layer respectively. In this way the response current would be produced. Based on this structure, the specific fabrication procedure including substrate cleaning; PEDOT:PSS layer preparation; pervoskite layer preparation; PCBM layer preparation; C60, BCP, and Ag electrode layer preparation. After the device fabrication, a series of morphological characterization and performance testing has been done. The testing procedure including film-forming quality inspection, response current and light wavelength analysis, linearity and response time and other optical and electrical properties testing. The testing result shows that the membrane has been fabricated uniformly; the device can produce obvious response current to the incident light with the wavelength from 350nm to 800nm, and the response current could be changed along with the light wavelength. When the light wavelength keeps constant, there exists a good linear relationship between the intensity of the response current and the power of the incident light, based on which the device could be used as the photo detector to collect the light information. During the changing period of the light signal, the response time of the device is several microseconds, which is acceptable working as a photo detector in our system. The testing results show that the device has good electronic and optical properties, and the fabrication procedure is also repeatable, the properties of the devices has good uniformity, which illustrates the fabrication method and procedure could be used to build the photo detector in our wearable system. Based on a series of testing results, the paper has drawn the conclusion that the photo detector fabricated could be integrated on the flexible substrate and is also suitable for the monitoring system proposed, thus made some progress on the research of the wearable monitoring system and device. Finally, some future prospect in system design aspect and device design and fabrication aspect are proposed.

Phobos: The design and implementation of embedded software for a low cost radar warning receiver

This portfolio thesis describes work undertaken by the author under the Engineering Doctorate program of the Institute for System Level Integration. It was carried out in conjunction with the sponsor company Teledyne Defence Limited. A radar warning receiver is a device used to detect and identify the emissions of radars. They were originally developed during the Second World War and are found today on a variety of military platforms as part of the platform’s defensive systems. Teledyne Defence has designed and built components and electronic subsystems for the defence industry since the 1970s. This thesis documents part of the work carried out to create Phobos, Teledyne Defence’s first complete radar warning receiver. Phobos was designed to be the first low cost radar warning receiver. This was made possible by the reuse of existing Teledyne Defence products, commercial off the shelf hardware and advanced UK government algorithms. The challenges of this integration are described and discussed, with detail given of the software architecture and the development of the embedded application. Performance of the embedded system as a whole is described and qualified within the context of a low cost system.

Strong shift equivalence, algebraic K-theory, and isolating zero-dimensional dynamics on manifolds

We study the relations of shift equivalence and strong shift equivalence for matrices over a ring $\mathcal{R}$, and establish a connection between these relations and algebraic K-theory. We utilize this connection to obtain results in two areas where the shift and strong shift equivalence relations play an important role: the study of finite group extensions of shifts of finite type, and the Generalized Spectral Conjectures of Boyle and Handelman for nonnegative matrices over subrings of the real numbers. We show the refinement of the shift equivalence class of a matrix $A$ over a ring $\mathcal{R}$ by strong shift equivalence classes over the ring is classified by a quotient $NK_{1}(\mathcal{R}) / E(A,\mathcal{R})$ of the algebraic K-group $NK_{1}(\calR)$. We use the K-theory of non-commutative localizations to show that in certain cases the subgroup $E(A,\mathcal{R})$ must vanish, including the case $A$ is invertible over $\mathcal{R}$. We use the K-theory connection to clarify the structure of algebraic invariants for finite group extensions of shifts of finite type. In particular, we give a strong negative answer to a question of Parry, who asked whether the dynamical zeta function determines up to finitely many topological conjugacy classes the extensions by $G$ of a fixed mixing shift of finite type. We apply the K-theory connection to prove the equivalence of a strong and weak form of the Generalized Spectral Conjecture of Boyle and Handelman for primitive matrices over subrings of $\mathbb{R}$. We construct explicit matrices whose class in the algebraic K-group $NK_{1}(\mathcal{R})$ is non-zero for certain rings $\mathcal{R}$ motivated by applications. We study the possible dynamics of the restriction of a homeomorphism of a compact manifold to an isolated zero-dimensional set. We prove that for $n \ge 3$ every compact zero-dimensional system can arise as an isolated invariant set for a homeomorphism of a compact $n$-manifold. In dimension two, we provide obstructions and examples.

Detecting Motifs in System Call Sequences

The search for patterns or motifs in data represents an area of key interest to many researchers. In this paper we present the Motif Tracking Algorithm, a novel immune inspired pattern identification tool that is able to identify unknown motifs which repeat within time series data. The power of the algorithm is derived from its use of a small number of parameters with minimal assumptions. The algorithm searches from a completely neutral perspective that is independent of the data being analysed and the underlying motifs. In this paper the motif tracking algorithm is applied to the search for patterns within sequences of low level system calls between the Linux kernel and the operating system’s user space. The MTA is able to compress data found in large system call data sets to a limited number of motifs which summarise that data. The motifs provide a resource from which a profile of executed processes can be built. The potential for these profiles and new implications for security research are highlighted. A higher level system call language for measuring similarity between patterns of such calls is also suggested.

Embedded representations of social interactions

Social interactions have been the focus of social science research for a century, but their study has recently been revolutionized by novel data sources and by methods from computer science, network science, and complex systems science. The study of social interactions is crucial for understanding complex societal behaviours. Social interactions are naturally represented as networks, which have emerged as a unifying mathematical language to understand structural and dynamical aspects of socio-technical systems. Networks are, however, highly dimensional objects, especially when considering the scales of real-world systems and the need to model the temporal dimension. Hence the study of empirical data from social systems is challenging both from a conceptual and a computational standpoint. A possible approach to tackling such a challenge is to use dimensionality reduction techniques that represent network entities in a low-dimensional feature space, preserving some desired properties of the original data. Low-dimensional vector space representations, also known as network embeddings, have been extensively studied, also as a way to feed network data to machine learning algorithms. Network embeddings were initially developed for static networks and then extended to incorporate temporal network data. We focus on dimensionality reduction techniques for time-resolved social interaction data modelled as temporal networks. We introduce a novel embedding technique that models the temporal and structural similarities of events rather than nodes. Using empirical data on social interactions, we show that this representation captures information relevant for the study of dynamical processes unfolding over the network, such as epidemic spreading. We then turn to another large-scale dataset on social interactions: a popular Web-based crowdfunding platform. We show that tensor-based representations of the data and dimensionality reduction techniques such as tensor factorization allow us to uncover the structural and temporal aspects of the system and to relate them to geographic and temporal activity patterns.

Thermal and air quality modeling of an electric vehicle cabin with low-cost sensors and reinforcement learning

The design process of any electric vehicle system has to be oriented towards the best energy efficiency, together with the constraint of maintaining comfort in the vehicle cabin. Main aim of this study is to research the best thermal management solution in terms of HVAC efficiency without compromising occupant’s comfort and internal air quality. An Arduino controlled Low Cost System of Sensors was developed and compared against reference instrumentation (average R-squared of 0.92) and then used to characterise the vehicle cabin in real parking and driving conditions trials. Data on the energy use of the HVAC was retrieved from the car On-Board Diagnostic port. Energy savings using recirculation can reach 30 %, but pollutants concentration in the cabin builds up in this operating mode. Moreover, the temperature profile appeared strongly nonuniform with air temperature differences up to 10° C. Optimisation methods often require a high number of runs to find the optimal configuration of the system. Fast models proved to be beneficial for these task, while CFD-1D model are usually slower despite the higher level of detail provided. In this work, the collected dataset was used to train a fast ML model of both cabin and HVAC using linear regression. Average scaled RMSE over all trials is 0.4 %, while computation time is 0.0077 ms for each second of simulated time on a laptop computer. Finally, a reinforcement learning environment was built in OpenAI and Stable-Baselines3 using the built-in Proximal Policy Optimisation algorithm to update the policy and seek for the best compromise between comfort, air quality and energy reward terms. The learning curves show an oscillating behaviour overall, with only 2 experiments behaving as expected even if too slow. This result leaves large room for improvement, ranging from the reward function engineering to the expansion of the ML model.

Design of a wearable platform for PPG analysis with multicore low-power processor

Photoplethysmography (PPG) sensors allow for noninvasive and comfortable heart-rate (HR) monitoring, suitable for compact wearable devices. However, PPG signals collected from such devices often suffer from corruption caused by motion artifacts. This is typically addressed by combining the PPG signal with acceleration measurements from an inertial sensor. Recently, different energy-efficient deep learning approaches for heart rate estimation have been proposed. To test these new solutions, in this work, we developed a highly wearable platform (42mm x 48 mm x 1.2mm) for PPG signal acquisition and processing, based on GAP9, a parallel ultra low power system-on-chip featuring nine cores RISC-V compute cluster with neural network accelerator and 1 core RISC-V controller. The hardware platform also integrates a commercial complete Optical Biosensing Module and an ARM-Cortex M4 microcontroller unit (MCU) with Bluetooth low-energy connectivity. To demonstrate the capabilities of the system, a deep learning-based approach for PPG-based HR estimation has been deployed. Thanks to the reduced power consumption of the digital computational platform, the total power budget is just 2.67 mW providing up to 5 days of operation (105 mAh battery).

Design and Implementation of Single phase 230V to Three Phase Inverter Based on the Embedded System STM-32 Applied to motor control

In the field of Power Electronics, several types of motor control systems have been developed using STM microcontroller and power boards. In both industrial power applications and domestic appliances, power electronic inverters are widely used. Inverters are used to control the torque, speed, and position of the rotor in AC motor drives. An inverter delivers constant-voltage and constant-frequency power in uninterruptible power sources. Because inverter power supplies have a high-power consumption and low transfer efficiency rate, a three-phase sine wave AC power supply was created using the embedded system STM32, which has low power consumption and efficient speed. It has the capacity of output frequency of 50 Hz and the RMS of line voltage. STM32 embedded based Inverter is a power supply that integrates, reduced, and optimized the power electronics application that require hardware system, software, and application solution, including power architecture, techniques, and tools, approaches capable of performance on devices and equipment. Power inverters are currently used and implemented in green energy power system with low energy system such as sensors or microcontroller to perform the operating function of motors and pumps. STM based power inverter is efficient, less cost and reliable. My thesis work was based on STM motor drives and control system which can be implemented in a gas analyser for operating the pumps and motors. It has been widely applied in various engineering sectors due to its ability to respond to adverse structural changes and improved structural reliability. The present research was designed to use STM Inverter board on low power MCU such as NUCLEO with some practical examples such as Blinking LED, and PWM. Then we have implemented a three phase Inverter model with Steval-IPM08B board, which converter single phase 230V AC input to three phase 380 V AC output, the output will be useful for operating the induction motor.

Structure and magnetism of homometallic ludwigites: Co(3)O(2)BO(3) versus Fe(3)O(2)BO(3)

We present an extensive study of the structural, magnetic, and thermodynamic properties of the oxyborate Co(3)O(2)BO(3). This is carried out through x-ray diffraction, static and dynamic magnetic susceptibilities, and specific heat experiments in single crystals in a large temperature range. The structure of Co(3)O(2)BO(3) is composed of subunits in the form of three-leg ladders where Co ions with mixed valency are located. The magnetic properties of this Co ludwigite are determined by a competition between superexchange and double-exchange interactions in the low-dimensional subunits. We discuss the observed physical properties in comparison with the only other known homometallic ludwigite, Fe(3)O(2)BO(3). The latter presents a structural distortion in the ladders and two magnetic transitions. Both features are not found in the present study of the Co ludwigite. The reason for these differences in the structural and magnetic behavior of two apparently similar compounds is discussed.

Lower Bounds on the Exchange-Correlation Energy in Reduced Dimensions

Bounds on the exchange-correlation energy of many-electron systems are derived and tested. By using universal scaling properties of the electron-electron interaction, we obtain the exponent of the bounds in three, two, one, and quasione dimensions. From the properties of the electron gas in the dilute regime, the tightest estimate to date is given for the numerical prefactor of the bound, which is crucial in practical applications. Numerical tests on various low-dimensional systems are in line with the bounds obtained and give evidence of an interesting dimensional crossover between two and one dimensions.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.