An Automata-Theoretic Approach to the Verification of Distributed Algorithms

We introduce an automata-theoretic method for the verification of distributed algorithms running on ring networks. In a distributed algorithm, an arbitrary number of processes cooperate to achieve a common goal (e.g., elect a leader). Processes have unique identifiers (pids) from an infinite, totally ordered domain. An algorithm proceeds in synchronous rounds, each round allowing a process to perform a bounded sequence of actions such as send or receive a pid, store it in some register, and compare register contents wrt. the associated total order. An algorithm is supposed to be correct independently of the number of processes. To specify correctness properties, we introduce a logic that can reason about processes and pids. Referring to leader election, it may say that, at the end of an execution, each process stores the maximum pid in some dedicated register. Since the verification of distributed algorithms is undecidable, we propose an underapproximation technique, which bounds the number of rounds. This is an appealing approach, as the number of rounds needed by a distributed algorithm to conclude is often exponentially smaller than the number of processes. We provide an automata-theoretic solution, reducing model checking to emptiness for alternating two-way automata on words. Overall, we show that round-bounded verification of distributed algorithms over rings is PSPACE-complete.Comment: 26 pages, 6 figure

A Study on Social Performance of Microfinance Institutes: A Consumer Perspective

The objective of the paper is to conduct a comparative study on the social performance of MFIs in rural and urban areas in various districts of Kerala and analyze the overall impact of micro financial services on the lives of respondents in these areas. The study is undertaken in rural and urban areas of four districts in Kerala using primary data. A total of 110 samples were collected from the districts of Alappuzha, Kollam, Pathanamthitta and Ernakulam. The analysis shows that the borrowers have seen an improvement in their standard of living because of the financial assistance provided by microfinance institutions. The comparison of the rural and urban areas shows that there are considerable differences as people in urban areas are more beneficial from the service provided by MFIs and the main reason behind this is their income status. The people in urban areas have high financial backup as compared to rural areas, so they are more benefitted from the loan facilities availed from MFIs to start their own ventures

CORRELATION BETWEEN MATERNAL COMPLICATIONS AND THE MENTAL HEALTH OF THE OFFSPRING

INTRODUCTION Children and young adults with mental disorders are twice as more likely to have experienced a complication of birth or pregnancy. Using an informatics approach, this study examines the impact of complications during birth and pregnancy on the mental health of the youth in the local pediatric population (Calgary Research Ethics Board ID: 21695). METHODS A data set containing physician visit for approximately 240,000 unique individuals from 1994-2009 was employed to examine the type of mental disorder associated with complications of birth and pregnancy (as a major class of ICD disorders). Additionally, a systematic literature review and meta-analysis of pediatric mental disorder associated with complications of birth and pregnancy was undertaken. RESULTS Mothers who experienced gestational infection, disease or exposure to drugs had a 3.7-fold increased risk of giving birth to children with mental disorders. Perinatal risk factors and obstetric complications caused a 1.5-fold increased risk. Emotional violence during pregnancy was seen to correlate with premature birth. Forest plot revealed that gestational diabetes and gestational influenza were the leading risk factors. In the local pediatric population from 1994 to 2009, the prevalence of offspring born with mental disorders whose mothers experienced complications during pregnancy and childbirth increased from 18 individuals/1000 to 28 individuals/1000 - an increase by 1.4. DISCUSSION One serious question that must be looked into is whether it is the influenza itself that impacts the child’s mental health, or the antibiotic medication that most mothers are prescribed as a remedy for influenza that has the negative impact on the child’s mental health. CONCLUSION On average, maternal gestational infection, disease and drug exposure, perinatal risk factors and obstetric complications, and maternal emotional violence leads to a 2 fold increased risk of offspring being born with mental disorders. In the local population, the prevalence of mental disorders consequent to pregnancy and childbirth complications has increased by a factor of 1.4 during the 1994-2009 period in the U19 category

Dual Signal Optical Bistability in a Semiconductor Optical Amplifier

Future all-optical signal processing applications may require the use of multiple optical signals passing through a single, optically bistable device. My thesis investigates an improved model for modeling two optical signals passing through an optically bistable Fabry-Perot semiconductor optical amplifier (FP-SOA). The optical power and phase of these signals are both modeled, as well as the optical gain of the FP-SOA. My improved model is based on an improved model used to study optical bistability of just a single optical signal, in which the internal power is related to the output power with an expression accounting for the Fabry-Perot structure. Work has been performed to put all models into a consistent notation. The resulting, improved model for dual-signal operation indicates lower critical powers to trigger bistable action

Cosmological horizon entropy and generalised second law for flat Friedmann Universe

We discuss the generalized second law (GSL) and the constraints imposed by it for two types of Friedmann universes. The first one is the Friedmann universe with radiation and a positive cosmological constant, and the second one consists of non-relativistic matter and a positive cosmological constant. The time evolution of the event horizon entropy and the entropy of the contents within the horizon are analyses in an analytical way by obtaining the Hubble parameter. It is shown that the GSL constraint the temperature of both the radiation and matter of the Friedmann universe. It is also shown that, even though the net entropy of the radiation (or matter) is decreasing at sufficiently large times as the universe expand, it exhibit an increase during the early times when universe is decelerating. That is the entropy of the radiation within the comoving volume is decreasing only when the universe has got an event horizon.Comment: 15 pages, 9 figure

Performance analysis of cutting graphite-epoxy composite using a 90,000 PSI abrasive waterjet

Graphite-epoxy composites are being widely used in many aerospace and structural applications because of their properties: which include lighter weight, higher strength to weight ratio and a greater flexibility in design. However, the inherent anisotropy of these composites makes it difficult to machine them using conventional methods. To overcome the major issues that develop with conventional machining such as fiber pull out, delamination, heat generation and high tooling costs, an effort is herein made to study abrasive waterjet machining of composites. An abrasive waterjet is used to cut 1 thick graphite epoxy composites based on baseline data obtained from the cutting of 1/4 thick material. The objective of this project is to study the surface roughness of the cut surface with a focus on demonstrating the benefits of using higher pressures for cutting composites. The effects of major cutting parameters: jet pressure, traverse speed, abrasive feed rate and cutting head size are studied at different levels. Statistical analysis of the experimental data provides an understanding of the effect of the process parameters on surface roughness. Additionally, the effect of these parameters on the taper angle of the cut is studied. The data is analyzed to obtain a set of process parameters that optimize the cutting of 1 thick graphite-epoxy composite. The statistical analysis is used to validate the experimental data. Costs involved in the cutting process are investigated in term of abrasive consumed to better understand and illustrate the practical benefits of using higher pressures. It is demonstrated that, as pressure increased, ultra-high pressure waterjets produced a better surface quality at a faster traverse rate with lower costs --Abstract, page iii

Carrier Transport and Electrical Conduction in Alloy-Mediated Graphene on Silicon

University of Technology Sydney. Faculty of Engineering and Information Technology.The possibility of graphene-based micro- and nanoelectronic devices that exploit the extraordinary electronic properties of graphene is the biggest inspiration behind the accelerated development of graphene science and technology. Although the remarkable efforts for establishing graphene as a new electronic material began over 15 years ago, the actual realisation of graphene devices on a large-scale remains elusive, mainly due to feasibility, cost-effectiveness and compatibility issues with the existing semiconductor technology and processes. Significant advancements have been achieved in the synthesis and establishment of transport properties of epitaxial graphene (EG) on 4H- and 6H-SiC, while equivalent progress using silicon (Si) as a platform (via a thin film of 3C-SiC) with reliable electrical transport measurements has not been elucidated to date, due to limitations such as non-uniform coverage of graphene on 3C-SiC/Si and high density of defects within the 3C-SiC. In this work, we first show that the heteroepitaxial 3C-SiC on Si as the substrate should be carefully approached, as the 3C-SiC/Si heterojunction is electrically unstable and prone to severe leakage or parallel conduction. Subsequently, we find that the interface instability is due to the diffusion of carbon into the silicon matrix during the 3C-SiC growth, creating electrically active interstitial carbon. We overcome these challenges using 3C-SiC on a highly-resistive silicon substrate. By addressing the parallel conduction issue of the 3C-SiC/Si heteroepitaxial system, in this work, we isolate the charge transport properties of epitaxial graphene (EG) grown directly on 3C-SiC over large areas via an alloy-mediated method and present corresponding physical ab-initio models. Here, we study the properties of EG synthesised on 3C-SiC(100) and 3C-SiC(111). The transport properties of EG on 3C-SiC follow a similar power-law dependence of sheet carrier concentration and mobility and comparable sheet resistance values with the EG on bulk-SiC – although the grain sizes for both are vastly different. Furthermore, we find that the transport properties of graphene within the observed regime are dominated by the substrate interaction, resulting in a large p-type doping, especially for the graphene on 3C-SiC(100). In the case of EG on 3C-SiC(111), the presence of buffer layer reduces the substrate interaction and the charge transfer up to an extent. This work demonstrates a more compelling need to focus on the engineering of the graphene-substrate interface as opposed to graphene grain sizes in order to tune the charge transport properties of the epitaxial graphene for the integration of 2D materials in functional nanosystems

NOVEL MODELING, TESTING AND CONTROL APPROACHES TOWARDS ENERGY EFFICIENCY IMPROVEMENT IN PERMANENT MAGNET SYNCHRONOUS MOTOR AND DRIVE SYSTEMS

This thesis investigates energy efficiency improvement in permanent magnet synchronous motor (PMSM) and drive system to achieve high–performance drive for practical industrial and primarily, traction applications. In achieving improved energy efficiency from a system level, this thesis proposes: (1) Accurate modeling and testing of loss components in PMSM considering inverter harmonics; (2) Easy–to–implement, accurate parameter determination techniques to understand variations in motor parameters due to saturation, cross–saturation and temperature; and (3) Control methodologies to improve system level efficiency considering improved loss models and parameter variations. An improved loss model to incorporate the influence of motor–drive interaction on the motor losses is developed by taking time and space harmonics into account. An improved winding function theory incorporating armature reaction fields due to fundamental and harmonic stator magnetic fields is proposed to calculate the additional harmonic losses in the PMSM. Once all contributing losses in the motor are modelled accurately, an investigation into control variables that affect the losses in the motor and inverter is performed. Three major control variables such as DC link voltage, switching frequency and current angle are chosen and the individual losses in the motor and inverter as well as the system losses are studied under varying control variables and wide operating conditions. Since the proposed loss as well as efficiency modeling involves machine operation dependent parameters, the effects of parameter variation on PMSM due to saturation and temperature variation are investigated. A recursive least square (RLS) based multi–parameter estimation is proposed to identify all the varying parameters of the PMSM to improve the accuracy and validity of the proposed model. The impact of losses on these parameters as well as the correct output torque considering the losses are studied. Based on the proposed loss models, parameter variations and the investigation into control variables, an off–line loss minimization procedure is developed to take into account the effects of parameter variations. The search–based procedure generates optimal current angles at varying operating conditions by considering maximization of system efficiency as the objective. In order to further simplify the consideration of parameter variations in real–time conditions, an on–line loss minimization procedure using DC power measurement and loss models solved on–line using terminal measurements in a PMSM drive is proposed. A gradient descent search–based algorithm is used to calculate the optimal current angle corresponding to maximum system efficiency from the input DC power measurement and output power based on the loss models. During the thesis investigations, the proposed models and control techniques are extensively evaluated on a laboratory PMSM drive system under different speeds, load conditions, and temperatures

Data management and Data Pipelines: An empirical investigation in the embedded systems domain

Context: Companies are increasingly collecting data from all possible sources to extract insights that help in data-driven decision-making. Increased data volume, variety, and velocity and the impact of poor quality data on the development of data products are leading companies to look for an improved data management approach that can accelerate the development of high-quality data products. Further, AI is being applied in a growing number of fields, and thus it is evolving as a horizontal technology. Consequently, AI components are increasingly been integrated into embedded systems along with electronics and software. We refer to these systems as AI-enhanced embedded systems. Given the strong dependence of AI on data, this expansion also creates a new space for applying data management techniques. Objective: The overall goal of this thesis is to empirically identify the data management challenges encountered during the development and maintenance of AI-enhanced embedded systems, propose an improved data management approach and empirically validate the proposed approach.Method: To achieve the goal, we conducted this research in close collaboration with Software Center companies using a combination of different empirical research methods: case studies, literature reviews, and action research.Results and conclusions: This research provides five main results. First, it identifies key data management challenges specific to Deep Learning models developed at embedded system companies. Second, it examines the practices such as DataOps and data pipelines that help to address data management challenges. We observed that DataOps is the best data management practice that improves the data quality and reduces the time tdevelop data products. The data pipeline is the critical component of DataOps that manages the data life cycle activities. The study also provides the potential faults at each step of the data pipeline and the corresponding mitigation strategies. Finally, the data pipeline model is realized in a small piece of data pipeline and calculated the percentage of saved data dumps through the implementation.Future work: As future work, we plan to realize the conceptual data pipeline model so that companies can build customized robust data pipelines. We also plan to analyze the impact and value of data pipelines in cross-domain AI systems and data applications. We also plan to develop AI-based fault detection and mitigation system suitable for data pipelines