A Bayesian approach to modeling the conditional density of the inverse controller

The inverse controller is traditionally assumed to be a deterministic function. This paper presents a pedagogical methodology for estimating the stochastic model of the inverse controller. The proposed method is based on Bayes' theorem. Using Bayes' rule to obtain the stochastic model of the inverse controller allows the use of knowledge of uncertainty from both the inverse and the forward model in estimating the optimal control signal. The paper presents the methodology for general nonlinear systems. For illustration purposes, the proposed methodology is applied to linear Gaussian systems. © 2004 IEEE.

Robust Estimation in Multitype Branching Processes Based on their Asymptotic Properties

2000 Mathematics Subject Classification: 60J80.

Offspring Mean Estimators in Branching Processes with Immigration

2000 Mathematics Subject Classification: 60J80.

Characterization of Schrödinger Processes with Unbounded Potentials

2000 Mathematics Subject Classification: 49L20, 60J60, 93E20

Using observation ageing to improve Markovian model learning in QoS engineering

Markovian models are widely used to analyse quality-of-service properties of both system designs and deployed systems. Thanks to the emergence of probabilistic model checkers, this analysis can be performed with high accuracy. However, its usefulness is heavily dependent on how well the model captures the actual behaviour of the analysed system. Our work addresses this problem for a class of Markovian models termed discrete-time Markov chains (DTMCs). We propose a new Bayesian technique for learning the state transition probabilities of DTMCs based on observations of the modelled system. Unlike existing approaches, our technique weighs observations based on their age, to account for the fact that older observations are less relevant than more recent ones. A case study from the area of bioinformatics workflows demonstrates the effectiveness of the technique in scenarios where the model parameters change over time.

Secure information flow via stripping and fast simulation

Type systems for secure information flow aim to prevent a program from leaking information from H (high) to L (low) variables. Traditionally, bisimulation has been the prevalent technique for proving the soundness of such systems. This work introduces a new proof technique based on stripping and fast simulation, and shows that it can be applied in a number of cases where bisimulation fails. We present a progressive development of this technique over a representative sample of languages including a simple imperative language (core theory), a multiprocessing nondeterministic language, a probabilistic language, and a language with cryptographic primitives. In the core theory we illustrate the key concepts of this technique in a basic setting. A fast low simulation in the context of transition systems is a binary relation where simulating states can match the moves of simulated states while maintaining the equivalence of low variables; stripping is a function that removes high commands from programs. We show that we can prove secure information flow by arguing that the stripping relation is a fast low simulation. We then extend the core theory to an abstract distributed language under a nondeterministic scheduler. Next, we extend to a probabilistic language with a random assignment command; we generalize fast simulation to the setting of discrete time Markov Chains, and prove approximate probabilistic noninterference. Finally, we introduce cryptographic primitives into the probabilistic language and prove computational noninterference, provided that the underling encryption scheme is secure.

Topologia de gerador de distúrbios elétricos baseada em conversores de potência

Electrical disturbances such as voltage sags, interruptions and voltage unbalances might cause serious problems for the end-user and for the companies of generation and transmission of energy. Few years ago, those companies have been using methods and equipments of protection to avoid the disturbances’ presence or to mitigate their effects on the power system. Disturbances generators are used to analyse the behavior of electrical and electronic equipments affected by disturbances. The analysis of those failures allows the development of appropriated protection equipments. In this paper, the development of a disturbances generator based on power converters is presented. The disturbance generator developed is able to generate some symmetrical disturbances, such as: voltage sags, voltage swells and harmonic distortion. The control strategy used in the disturbance generator is based on discrete and repetitive control. The steps of the design of the control and of the filter used for reducing harmonic in the output, are detailed in the text. Are presented the obtained results on computational simulations and the obtained results on laboratory tests.

Sinalização endógena do sistema Nociceptina/Orfanina FQ - receptor NOP: envolvimento na modulação da depressão experimental induzida por lipopolissacarídeo

During the last decades, it has been established that there is a relationship between major depression and activation of immune system. Nociceptin/orphanin FQ (N/OFQ) is the natural ligand of a Gi-protein coupled receptor named NOP, both compose the peptidergic system wich is involved in the regulation of mood states and inflammatory responses. Considering these actions, the present thesis aimed to investigate the consequences of blocking NOP signaling in lipopolysaccharide (LPS)-induced sickness and depressive-like behaviors in mice. Systemic administration of LPS doses, that do not cause sepsis in mice, induce changes in their behaviors related with activity of pro-inflammatory cytokines tumor necrosis factor-α (TNF-α) and interleukins 6 (IL-6) and 1β (IL-1 β). At the time points of 2 to 6 h and 24 h after intraperitoneal injection, mice treated with LPS displayed, respectively, sickness and depressive-like behaviors. In the present work the administration of LPS 0.8 mg/kg (ip) significantly induced sickness signs in Swiss and CD-1 mice, such as weight loss, transient reduction in rectal temperature and decrease of food and water intake. Moreover at 24 h after LPS injection these same mice strains displayed significantly increased immobility time on the tail suspension test (TST) when compared with control mice, this alteration was not related with possible locomotion impairments as verified on the open field test. Treatment with Nortriptyline 30 mg/kg (ip, 60 min prior the TST) reduced the immobility time of control and LPS-treated mice and was used as standard antidepressant. The NOP receptor antagonist SB-612111 (10 mg/kg, ip), 30 min prior LPS, did not modify LPS-induced sickness signs and depressive-like behavior. However, when injected 24 h after LPS treatment, SB-612111 (ip, 30 min prior the TST) as well as the peptidergic NOP receptor antagonist UFP-101 (10 nmol/2μL, icv, 5 min prior the TST) significantly reversed the toxin effects. The protocol of LPS-induced depressive-like states was also tested in NOP receptor knockout mice (NOP(-/-)) and their respective wild types (NOP(+/+)). LPS evoked transient rectal temperature reduction in NOP(-/-) mice and loss of body weight, food and water intake reduction in both NOP(+/+) and NOP(-/-) mice. The consumption of water was significantly different due to the genotype. LPS injection induced transient changes in pro-inflammatory cytokines. At 6 h after LPS injection, serum levels of TNF-α were significantly increased in NOP(+/+) and NOP(-/-) mice, as the IL-6 levels were significantly increased just in NOP(+/+) serum. At 24 h after LPS treatment the pro-inflammatory cytokines had returned to the baseline levels in both genotypes. LPS treatment elicited depressive-like effects in NOP(+/+) but not in NOP(-/-) mice. The data obtained during the execution of this doctoral thesis reveal that pharmacological and genetic blockade of NOP signaling does not affect LPS evoked sickness signs while reversing depressive-like behavior. In conclusion, these results highlight the involvement of the peptidergic system N/OFQ - NOP receptor in the modulation of behaviors related to mood and activation of the immune system.

Sediment and ice characteristics at a buried ice-wedge system at Barrow

Barrow, the northernmost point in Alaska, is one of the most intensively studied areas in the Arctic. However, paleoenvironmental evidence is limited for northern Alaska for the Lateglacial-Holocene transition. For a regional paleoenvironmental reconstruction, we investigated a permafrost ice-wedge tunnel near Barrow, Alaska. The studied site was first excavated in the early 1960s and intercepts a buried ice-wedge system at 3-6 m depth below the surface. A multi-methodological approach was applied to this buried ice-wedge system and the enclosing sediments, which in their combination, give new insight into the Late Quaternary environmental and climate history. Results of geochronological, sedimentological, cryolithological, paleoecological, isotope geochemical and microbiological studies reflect different stages of mid to late Wisconsin (MW to LW), Allerod (AD), Younger Dryas (YD), Preboreal (PB), and Late Holocene paleoenvironmental evolution. The LW age of the site is indicated by AMS dates in the surrounding sediments of 21.7 kyr BP at the lateral contact of the ice-wedge system as well as 39.5 kyr BP below the ice-wedge system. It is only recently that in this region, stable isotope techniques have been employed, i.e. to characterize different types of ground ice. The stable isotope record (oxygen: d18O; hydrogen: dD) of two intersecting ice wedges suggests different phases of the northern Alaskan climate history from AD to PB, with radiocarbon dates from 12.4 to 9.9 kyr BP (ranging from 14.8 to 10.6 kyr cal BP). Stable isotope geochemistry of ice wedges reveals winter temperature variations of the Lateglacial-Holocene transition including a prominent YD cold period, clearly separated from the warmer AD and PB phases. YD is only weakly developed in summer temperature indicators (such as pollen) for the northern Alaska area, and by consequence, the YD cold stadial was here especially related to the winter season. This highlights that the combination of winter and summer indicators comprehensively describes the seasonality of climate-relevant processes in discrete time intervals. The stable isotope record for the Barrow buried ice-wedge system documents for the first time winter climate change at the Lateglacial-Holocene transition continuously and at relatively high (likely centennial) resolution.

Process Monitoring and Defect Detection of Additive Manufacturing Using Inline Coherent Imaging

With applications ranging from aerospace to biomedicine, additive manufacturing (AM) has been revolutionizing the manufacturing industry. The ability of additive techniques, such as selective laser melting (SLM), to create fully functional, geometrically complex, and unique parts out of high strength materials is of great interest. Unfortunately, despite numerous advantages afforded by this technology, its widespread adoption is hindered by a lack of on-line, real time feedback control and quality assurance techniques. In this thesis, inline coherent imaging (ICI), a broadband, spatially coherent imaging technique, is used to observe the SLM process in 15 - 45 $\mu m$ 316L stainless steel. Imaging of both single and multilayer builds is performed at a rate of 200 $kHz$, with a resolution of tens of microns, and a high dynamic range rendering it impervious to blinding from the process beam. This allows imaging before, during, and after laser processing to observe changes in the morphology and stability of the melt. Galvanometer-based scanning of the imaging beam relative to the process beam during the creation of single tracks is used to gain a unique perspective of the SLM process that has been so far unobservable by other monitoring techniques. Single track processing is also used to investigate the possibility of a preliminary feedback control parameter based on the process beam power, through imaging with both coaxial and 100 $\mu m$ offset alignment with respect to the process beam. The 100 $\mu m$ offset improved imaging by increasing the number of bright A-lines (i.e. with signal greater than the 10 $dB$ noise floor) by 300\%. The overlap between adjacent tracks in a single layer is imaged to detect characteristic fault signatures. Full multilayer builds are carried out and the resultant ICI images are used to detect defects in the finished part and improve upon the initial design of the build system. Damage to the recoater blade is assessed using powder layer scans acquired during a 3D build. The ability of ICI to monitor SLM processes at such high rates with high resolution offers extraordinary potential for future advances in on-line feedback control of additive manufacturing.

Modeling, Analysis and Performance Comparison of Two Direct Sampling DCSK Receivers under Frequency Nonselective Fading Channels

Two direct sampling correlator-type receivers for differential chaos shift keying (DCSK) communication systems under frequency non-selective fading channels are proposed. These receivers operate based on the same hardware platform with different architectures. In the first scheme, namely sum-delay-sum (SDS) receiver, the sum of all samples in a chip period is correlated with its delayed version. The correlation value obtained in each bit period is then compared with a fixed threshold to decide the binary value of recovered bit at the output. On the other hand, the second scheme, namely delay-sum-sum (DSS) receiver, calculates the correlation value of all samples with its delayed version in a chip period. The sum of correlation values in each bit period is then compared with the threshold to recover the data. The conventional DCSK transmitter, frequency non-selective Rayleigh fading channel, and two proposed receivers are mathematically modelled in discrete-time domain. The authors evaluated the bit error rate performance of the receivers by means of both theoretical analysis and numerical simulation. The performance comparison shows that the two proposed receivers can perform well under the studied channel, where the performances get better when the number of paths increases and the DSS receiver outperforms the SDS one.

A Bias Compensated Cross-Relation approach to Thermocouple Characterisation

The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the in influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

Simulation of Distributed Contact in String Instruments: a Modal Expansion Approach

Impactive contact between a vibrating string and a barrier is a strongly nonlinear phenomenon that presents several challenges in the design of numerical models for simulation and sound synthesis of musical string instruments. These are addressed here by applying Hamiltonian methods to incorporate distributed contact forces into a modal framework for discrete-time simulation of the dynamics of a stiff, damped string. The resulting algorithms have spectral accuracy, are unconditionally stable, and require solving a multivariate nonlinear equation that is guaranteed to have a unique solution. Exemplifying results are presented and discussed in terms of accuracy, convergence, and spurious high-frequency oscillations.

An Efficient Precoder Design for Multiuser MIMO Cognitive Radio Networks with Interference Constraints

We consider a linear precoder design for an underlay cognitive radio multiple-input multiple-output broadcast channel, where the secondary system consisting of a secondary base-station (BS) and a group of secondary users (SUs) is allowed to share the same spectrum with the primary system. All the transceivers are equipped with multiple antennas, each of which has its own maximum power constraint. Assuming zero-forcing method to eliminate the multiuser interference, we study the sum rate maximization problem for the secondary system subject to both per-antenna power constraints at the secondary BS and the interference power constraints at the primary users. The problem of interest differs from the ones studied previously that often assumed a sum power constraint and/or single antenna employed at either both the primary and secondary receivers or the primary receivers. To develop an efficient numerical algorithm, we first invoke the rank relaxation method to transform the considered problem into a convex-concave problem based on a downlink-uplink result. We then propose a barrier interior-point method to solve the resulting saddle point problem. In particular, in each iteration of the proposed method we find the Newton step by solving a system of discrete-time Sylvester equations, which help reduce the complexity significantly, compared to the conventional method. Simulation results are provided to demonstrate fast convergence and effectiveness of the proposed algorithm. 

Evolutionary dynamics under various modes of reproduction

Thesis (Ph.D.)--University of Washington, 2016-08