Minimization of Reactive Probabilistic Automata

The problem of finite automata minimization is important for software and hardware designing. Different types of automata are used for modeling systems or machines with finite number of states. The limitation of number of states gives savings in resources and time. In this article we show specific type of probabilistic automata: the reactive probabilistic finite automata with accepting states (in brief the reactive probabilistic automata), and definitions of languages accepted by it. We present definition of bisimulation relation for automata's states and define relation of indistinguishableness of automata states, on base of which we could effectuate automata minimization. Next we present detailed algorithm reactive probabilistic automata���s minimization with determination of its complexity and analyse example solved with help of this algorithm.

Through wafer 3D Vertical Micro-Coaxial Probe for high frequency material characterization and millimeter wave packaging systems

This work presents the development of an in-plane vertical micro-coaxial probe using bulk micromachining technique for high frequency material characterization. The coaxial probe was fabricated in a silicon substrate by standard photolithography and a deep reactive ion etching (DRIE) technique. The through-hole structure in the form of a coaxial probe was etched and metalized with a diluted silver paste. A co-planar waveguide configuration was integrated with the design to characterize the probe. The electrical and RF characteristics of the coaxial probe were determined by simulating the probe design in Ansoft's High Frequency Structure Simulator (HFSS). The reflection coefficient and transducer gain performance of the probe was measured up to 65 GHz using a vector network analyzer (VNA). The probe demonstrated excellent results over a wide frequency band, indicating its ability to integrate with millimeter wave packaging systems as well as characterize unknown materials at high frequencies. The probe was then placed in contact with 3 materials where their unknown permittivities were determined. To accomplish this, the coaxial probe was placed in contact with the material under test and electromagnetic waves were directed to the surface using the VNA, where its reflection coefficient was then determined over a wide frequency band from dc-to -65GHz. Next, the permittivity of each material was deduced from its measured reflection coefficients using a cross ratio invariance coding technique. The permittivity results obtained when measuring the reflection coefficient data were compared to simulated permittivity results and agreed well. These results validate the use of the micro-coaxial probe to characterize the permittivity of unknown materials at high frequencies up to 65GHz.

System operational costs reduction with non-conventional reactive power sources

Wind energy installations are increasing in power systems worldwide and wind generation capacity tends to be located some distance from load centers. A conflict may arise at times of high wind generation when it becomes necessary to curtail wind energy in order to maintain conventional generators on-line for the provision of voltage control support at load centers. Using the island of Ireland as a case study and presenting commercially available reactive power support devices as possible solutions to the voltage control problems in urban areas, this paper explores the reduction in total generation costs resulting from the relaxation of the operational constraints requiring conventional generators to be kept on-line near load centers for reactive power support. The paper shows that by 2020 there will be possible savings of 87���m per annum and a reduction in wind curtailment of more than a percentage point if measures are taken to relax these constraints.

Preparation of Polymer Nanoparticles by Ring Opening Metathesis Polymerization in Aqueous Dispersed Systems with Water-Soluble Ruthenium-based Catalyst

Ring opening metathesis polymerization (ROMP) is a variant of olefin metathesis used to polymerize strained cyclic olefins. Ruthenium-based Grubbs��� catalysts are widely used in ROMP to produce industrially important products. While highly efficient in organic solvents such as dichloromethane and toluene, these hydrophobic catalysts are not typically applied in aqueous systems. With the advancements in emulsion and miniemulsion polymerization, it is promising to conduct ROMP in an aqueous dispersed phase to generate well-defined latex nanoparticles while improving heat transfer and reducing the use of volatile organic solvents (VOCs). Herein I report the efforts made using a PEGylated ruthenium alkylidene as the catalyst to initiate ROMP in an oil-in-water miniemulsion. 1H NMR revealed that the synthesized PEGylated catalyst was stable and reactive in water. Using 1,5-cyclooctadiene (COD) as monomer, we showed the highly efficient catalyst yielded colloidally stable polymer latexes with ~ 100% conversion at room temperature. Kinetic studies demonstrated first-order kinetics with good livingness as confirmed by the shift of gel permeation chromatography (GPC) traces. Depending on the surfactants used, the particle sizes ranged from 100 to 300 nm with monomodal distributions. The more strained cyclic olefin norbornene (NB) could also be efficiently polymerized with a PEGylated ruthenium alkylidene in miniemulsion to full conversion and with minimal coagulum formation.

Towards Proactive Context-aware Computing and Systems

A primary goal of context-aware systems is delivering the right information at the right place and right time to users in order to enable them to make effective decisions and improve their quality of life. There are three key requirements for achieving this goal: determining what information is relevant, personalizing it based on the users��� context (location, preferences, behavioral history etc.), and delivering it to them in a timely manner without an explicit request from them. These requirements create a paradigm that we term as ���Proactive Context-aware Computing���. Most of the existing context-aware systems fulfill only a subset of these requirements. Many of these systems focus only on personalization of the requested information based on users��� current context. Moreover, they are often designed for specific domains. In addition, most of the existing systems are reactive - the users request for some information and the system delivers it to them. These systems are not proactive i.e. they cannot anticipate users��� intent and behavior and act proactively without an explicit request from them. In order to overcome these limitations, we need to conduct a deeper analysis and enhance our understanding of context-aware systems that are generic, universal, proactive and applicable to a wide variety of domains. To support this dissertation, we explore several directions. Clearly the most significant sources of information about users today are smartphones. A large amount of users��� context can be acquired through them and they can be used as an effective means to deliver information to users. In addition, social media such as Facebook, Flickr and Foursquare provide a rich and powerful platform to mine users��� interests, preferences and behavioral history. We employ the ubiquity of smartphones and the wealth of information available from social media to address the challenge of building proactive context-aware systems. We have implemented and evaluated a few approaches, including some as part of the Rover framework, to achieve the paradigm of Proactive Context-aware Computing. Rover is a context-aware research platform which has been evolving for the last 6 years. Since location is one of the most important context for users, we have developed ���Locus���, an indoor localization, tracking and navigation system for multi-story buildings. Other important dimensions of users��� context include the activities that they are engaged in. To this end, we have developed ���SenseMe���, a system that leverages the smartphone and its multiple sensors in order to perform multidimensional context and activity recognition for users. As part of the ���SenseMe��� project, we also conducted an exploratory study of privacy, trust, risks and other concerns of users with smart phone based personal sensing systems and applications. To determine what information would be relevant to users��� situations, we have developed ���TellMe��� - a system that employs a new, flexible and scalable approach based on Natural Language Processing techniques to perform bootstrapped discovery and ranking of relevant information in context-aware systems. In order to personalize the relevant information, we have also developed an algorithm and system for mining a broad range of users��� preferences from their social network profiles and activities. For recommending new information to the users based on their past behavior and context history (such as visited locations, activities and time), we have developed a recommender system and approach for performing multi-dimensional collaborative recommendations using tensor factorization. For timely delivery of personalized and relevant information, it is essential to anticipate and predict users��� behavior. To this end, we have developed a unified infrastructure, within the Rover framework, and implemented several novel approaches and algorithms that employ various contextual features and state of the art machine learning techniques for building diverse behavioral models of users. Examples of generated models include classifying users��� semantic places and mobility states, predicting their availability for accepting calls on smartphones and inferring their device charging behavior. Finally, to enable proactivity in context-aware systems, we have also developed a planning framework based on HTN planning. Together, these works provide a major push in the direction of proactive context-aware computing.

Exposure to toxic Alexandrium minutum activates the detoxifying and antioxidant systems in gills of the oyster Crassostrea gigas

Harmful algal blooms of Alexandrium spp. dinoflagellates regularly occur in French coastal waters contaminating shellfish. Studies have demonstrated that toxic Alexandrium spp. disrupt behavioural and physiological processes in marine filter-feeders, but molecular modifications triggered by phycotoxins are less well understood. This study analyzed the mRNA levels of 7 genes encoding antioxidant/detoxifying enzymes in gills of Pacific oysters (Crassostrea gigas) exposed to a cultured, toxic strain of A. minutum, a producer of paralytic shellfish toxins (PST) or fed Tisochrysis lutea (T. lutea, formerly Isochrysis sp., clone Tahitian (T. iso)), a non-toxic control diet, in four repeated experiments. Transcript levels of sigma-class glutathione S-transferase (GST), glutathione reductase (GR) and ferritin (Fer) were significantly higher in oysters exposed to A. minutum compared to oysters fed T. lutea. The detoxification pathway based upon glutathione (GSH)-conjugation of toxic compounds (phase II) is likely activated, and catalyzed by GST. This system appeared to be activated in gills probably for the detoxification of PST and/or extra-cellular compounds, produced by A. minutum. GST, GR and Fer can also contribute to antioxidant functions to prevent cellular damage from increased reactive oxygen species (ROS) originating either from A. minutum cells directly, from oyster hemocytes during immune response, or from other gill cells as by-products of detoxification.

Modelling reactive and proactive behaviour in simulation

This research investigated the simulation model behaviour of a traditional and combined discrete event as well as agent based simulation models when modelling human reactive and proactive behaviour in human centric complex systems. A departmental store was chosen as human centric complex case study where the operation system of a fitting room in WomensWear department was investigated. We have looked at ways to determine the efficiency of new management policies for the fitting room operation through simulating the reactive and proactive behaviour of staff towards customers. Once development of the simulation models and their verification had been done, we carried out a validation experiment in the form of a sensitivity analysis. Subsequently, we executed a statistical analysis where the mixed reactive and proactive behaviour experimental results were compared with some reactive experimental results from previously published works. Generally, this case study discovered that simple proactive individual behaviour could be modelled in both simulation models. In addition, we found the traditional discrete event model performed similar in the simulation model output compared to the combined discrete event and agent based simulation when modelling similar human behaviour.

Real-time load-side control of electric power systems

<p>Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems.</p> <p>(1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control. </p> <p>(2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.</p>

PARAMETRIC STUDY OF REAXFF SIMULATION PARAMETERS FOR MOLECULAR DYNAMICS MODELING OF REACTIVE CARBON GASES

Abstract The development of innovative carbon-based materials can be greatly facilitated by molecular modeling techniques. Although the Reax Force Field (ReaxFF) can be used to simulate the chemical behavior of carbon-based systems, the simulation settings required for accurate predictions have not been fully explored. Using the ReaxFF, molecular dynamics (MD) simulations are used to simulate the chemical behavior of pure carbon and hydrocarbon reactive gases that are involved in the formation of carbon structures such as graphite, buckyballs, amorphous carbon, and carbon nanotubes. It is determined that the maximum simulation time step that can be used in MD simulations with the ReaxFF is dependent on the simulated temperature and selected parameter set, as are the predicted reaction rates. It is also determined that different carbon-based reactive gases react at different rates, and that the predicted equilibrium structures are generally the same for the different ReaxFF parameter sets, except in the case of the predicted formation of large graphitic structures with the Chenoweth parameter set under specific conditions.

Through Wafer 3D Vertical Micro-Coaxial Probe for High Frequency Material Characterization and Millimeter Wave Packaging Systems

This work presents the development of an in-plane vertical micro-coaxial probe using bulk micromachining technique for high frequency material characterization. The coaxial probe was fabricated in a silicon substrate by standard photolithography and a deep reactive ion etching (DRIE) technique. The through-hole structure in the form of a coaxial probe was etched and metalized with a diluted silver paste. A co-planar waveguide configuration was integrated with the design to characterize the probe. The electrical and RF characteristics of the coaxial probe were determined by simulating the probe design in Ansoft���s High Frequency Structure Simulator (HFSS). The reflection coefficient and transducer gain performance of the probe was measured up to 65 GHz using a vector network analyzer (VNA). The probe demonstrated excellent results over a wide frequency band, indicating its ability to integrate with millimeter wave packaging systems as well as characterize unknown materials at high frequencies. The probe was then placed in contact with 3 materials where their unknown permittivities were determined. To accomplish this, the coaxial probe was placed in contact with the material under test and electromagnetic waves were directed to the surface using the VNA, where its reflection coefficient was then determined over a wide frequency band from dc-to -65GHz. Next, the permittivity of each material was deduced from its measured reflection coefficients using a cross ratio invariance coding technique. The permittivity results obtained when measuring the reflection coefficient data were compared to simulated permittivity results and agreed well. These results validate the use of the micro-coaxial probe to characterize the permittivity of unknown materials at high frequencies up to 65GHz.

On the zeros of the Abelian integrals for a class of Li��nard systems

A planar polynomial differential system has a finite number of limit cycles. However, finding the upper bound of the number of limit cycles is an open problem for the general nonlinear dynamical systems. In this paper, we investigated a class of Li��nard systems of the form <i>x'=y, y'=f(x)+y g(x)</i> with deg f=5 and deg g=4. We proved that the related elliptic integrals of the Li��nard systems have at most three zeros including multiple zeros, which implies that the number of limit cycles bifurcated from the periodic orbits of the unperturbed system is less than or equal to 3.