Designing for User-facing Uncertainty in Everyday Sensing and Prediction

Thesis (Ph.D.)--University of Washington, 2016-07

The parallel solution of early-exercise Asian options with stochastic volatility

This paper describes an parallel semi-Lagrangian finite difference approach to the pricing of early exercise Asian Options on assets with a stochastic volatility. A multigrid procedure is described for the fast iterative solution of the discrete linear complementarity problems that result. The accuracy and performance of this approach is improved considerably by a strike-price related analytic transformation of asset prices. Asian options are contingent claims with payoffs that depend on the average price of an asset over some time interval. The payoff may depend on this average and a fixed strike price (Fixed Strike Asians) or it may depend on the average and the asset price (Floating Strike Asians). The option may also permit early exercise (American contract) or confine the holder to a fixed exercise date (European contract). The Fixed Strike Asian with early exercise is considered here where continuous arithmetic averaging has been used. Pricing such an option where the asset price has a stochastic volatility leads to the requirement to solve a tri-variate partial differential inequation in the three state variables of asset price, average price and volatility (or equivalently, variance). The similarity transformations [6] used with Floating Strike Asian options to reduce the dimensionality of the problem are not applicable to Fixed Strikes and so the numerical solution of a tri-variate problem is necessary. The computational challenge is to provide accurate solutions sufficiently quickly to support realtime trading activities at a reasonable cost in terms of hardware requirements.

Dynamic Workload Parallelization and System Calibration on Single-Chip Cloud Computer

Many-core systems are emerging from the need of more computational power and power efficiency. However there are many issues which still revolve around the many-core systems. These systems need specialized software before they can be fully utilized and the hardware itself may differ from the conventional computational systems. To gain efficiency from many-core system, programs need to be parallelized. In many-core systems the cores are small and less powerful than cores used in traditional computing, so running a conventional program is not an efficient option. Also in Network-on-Chip based processors the network might get congested and the cores might work at different speeds. In this thesis is, a dynamic load balancing method is proposed and tested on Intel 48-core Single-Chip Cloud Computer by parallelizing a fault simulator. The maximum speedup is difficult to obtain due to severe bottlenecks in the system. In order to exploit all the available parallelism of the Single-Chip Cloud Computer, a runtime approach capable of dynamically balancing the load during the fault simulation process is used. The proposed dynamic fault simulation approach on the Single-Chip Cloud Computer shows up to 45X speedup compared to a serial fault simulation approach. Many-core systems can draw enormous amounts of power, and if this power is not controlled properly, the system might get damaged. One way to manage power is to set power budget for the system. But if this power is drawn by just few cores of the many, these few cores get extremely hot and might get damaged. Due to increase in power density multiple thermal sensors are deployed on the chip area to provide realtime temperature feedback for thermal management techniques. Thermal sensor accuracy is extremely prone to intra-die process variation and aging phenomena. These factors lead to a situation where thermal sensor values drift from the nominal values. This necessitates efficient calibration techniques to be applied before the sensor values are used. In addition, in modern many-core systems cores have support for dynamic voltage and frequency scaling. Thermal sensors located on cores are sensitive to the core's current voltage level, meaning that dedicated calibration is needed for each voltage level. In this thesis a general-purpose software-based auto-calibration approach is also proposed for thermal sensors to calibrate thermal sensors on different range of voltages.

Development of a Real Time System in Algol 68.

For various reasons, many Algol 68 compilers do not directly implement the parallel processing operations defined in the Revised Algol 68 Report. It is still possible however, to perform parallel processing, multitasking and simulation provided that the implementation permits the creation of a master routine for the coordination and initiation of processes under its control. The package described here is intended for real time applications and runs in conjunction with the Algol 68R system; it extends and develops the original Algol 68RT package, which was designed for use with multiplexers at the Royal Radar Establishment, Malvern. The facilities provided, in addition to the synchronising operations, include an interface to an ICL Communications Processor enabling the abstract processes to be realised as the interaction of several teletypes or visual display units with a real time program providing a useful service.

Strategic Alert Throttling for Intrusion Detection Systems

Network intrusion detection systems are themselves becoming targets of attackers. Alert flood attacks may be used to conceal malicious activity by hiding it among a deluge of false alerts sent by the attacker. Although these types of attacks are very hard to stop completely, our aim is to present techniques that improve alert throughput and capacity to such an extent that the resources required to successfully mount the attack become prohibitive. The key idea presented is to combine a token bucket filter with a realtime correlation algorithm. The proposed algorithm throttles alert output from the IDS when an attack is detected. The attack graph used in the correlation algorithm is used to make sure that alerts crucial to forming strategies are not discarded by throttling.

Essays on the term structure of interest rates

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed timevarying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible realtime term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

Caracterização in vitro de um dosímetro de fibra ótica para braquiterapia de HDR

Recentemente foi desenvolvido um dosímetro baseado em fibras cintilantes (BCF-12 da companhia Saint Gobain Crystals com 1 e 0,5 mm de diâmetro e 5 mm de comprimento) para braquiterapia de baixa taxa de dose, em particular a braquiterapia direcionada para o tratamento do cancro da próstata. Este utiliza um novo fotomultiplicador de estado sólido dado pelo nome de MPPC - MultiPixel Photon Counter da companhia Hamamatsu Photonics (Japão). Nesta dissertação é estudado o mesmo dosímetro para a modalidade de braquiterapia de elevada taxa de dose (HDR). A informação sobre a dose neste tipo de dosímetros é obtida a partir de sinais óticos (em vez de sinais elétricos), que são imunes a interferências elétricas e eletromagnéticas. Adicionalmente as pequenas dimensões das fibras oferecem uma excelente resolução espacial e uma invasão mínima para uso em dosimetria in vivo, permitindo medir a dose diretamente ou próximo ao tumor e em tempo real. A sua utilização em braquiterapia para o cancro da próstata constitui-se assim como uma vantagem, uma vez que as fibras podem ser inseridas diretamente nos aplicadores utilizados neste tipo de tratamentos. Apesar de tudo, este tipo de dosímetros possui algumas desvantagens, como por exemplo a luz de Cherenkov e a fluorescência (forma de ruído dada pelo nome de stem effect) que, e a contrário da luz produzida pela fibra cintilante, não são diretamente proporcionais à energia depositada. Contudo, e para energias praticadas em braquiterapia de HDR, nesta dissertação, mostrou-se que este problema é pouco significativo dado que a percentagem de contribuição destes efeitos para o sinal medido é menor que 1% (ou 5% para distâncias menores que 25 mm). Ao longo desta dissertação é feita a caraterização do dosímetro (em modo corrente e impulso) e das suas várias partes em ambiente de laboratório e clínico. Nestes estudos o dosímetro, além de exibir uma boa reprodutibilidade (variação máxima de 3% entre medidas), mostrou uma alta linearidade para uma ampla gama de doses, assim como uma sensibilidade (µGy) semelhante à de uma câmara de ionização, tornando-o adequado para braquiterapia de HDR (tratamento que envolve altos gradientes de dose). Complementarmente, a sua grande versatilidade e simples utilização possibilita a sua aplicação prática em outras modalidades radioterapêuticas.

Experimenting with Innate Immunity

libtissue is a software system for implementing and testing AIS algorithms on real-world computer security problems. AIS algorithms are implemented as a collection of cells, antigen and signals interacting within a tissue compartment. Input data to the tissue comes in the form of realtime events generated by sensors monitoring a system under surveillance, and cells are actively able to affect the monitored system through response mechanisms. libtissue is being used by researchers on a project at the University of Nottingham to explore the application of a range of immune-inspired algorithms to problems in intrusion detection. This talk describes the architecture and design of libtissue, along with the implementation of a simple algorithm and its application to a computer security problem.

Strategic Alert Throttling for Intrusion Detection Systems

Network intrusion detection systems are themselves becoming targets of attackers. Alert flood attacks may be used to conceal malicious activity by hiding it among a deluge of false alerts sent by the attacker. Although these types of attacks are very hard to stop completely, our aim is to present techniques that improve alert throughput and capacity to such an extent that the resources required to successfully mount the attack become prohibitive. The key idea presented is to combine a token bucket filter with a realtime correlation algorithm. The proposed algorithm throttles alert output from the IDS when an attack is detected. The attack graph used in the correlation algorithm is used to make sure that alerts crucial to forming strategies are not discarded by throttling.

NIR-spectroscopy for bioprocess monitoring & control

The Ingold port adaption of a free beam NIR spectrometer is tailored for optimal bioprocess monitoring and control. The device shows an excellent signal to noise ratio dedicated to a large free aperture and therefore a large sample volume. This can be seen particularly in the batch trajectories which show a high reproducibility. The robust and compact design withstands rough process environments as well as SIP/CIP cycles. Robust free beam NIR process analyzers are indispensable tools within the PAT/QbD framework for realtime process monitoring and control. They enable multiparametric, non-invasive measurements of analyte concentrations and process trajectories. Free beam NIR spectrometers are an ideal tool to define golden batches and process borders in the sense of QbD. Moreover, sophisticated data analysis both quantitative and MSPC yields directly to a far better process understanding. Information can be provided online in easy to interpret graphs which allow the operator to make fast and knowledge-based decisions. This finally leads to higher stability in process operation, better performance and less failed batches.

Using ICT Energy consumption for monitoring ICT architecture

Energy efficient policies are being applied to network protocols, devices and classical network management systems. Researchers have already studied in depth each of those fields, including for instance a long monitoring processes of various number of individual ICT equipment from where power models are constructed. With the development of smart meters and emerging protocols such as SNMP and NETCONF, currently there is an open field to couple the power models, translated to the expected behavior, with the realtime energy measurements. The goal is to derive a comparison on the power data between both of the processes in the direction of detection for possible deviations on the expected results. The logical assumption is that a fault in the usage of a particular device will not only increase its own energy usage, but also may cause additional consumption on the other devices part of the network. A platform is developed to monitor and analyze the retrieved power data of a simulated enterprise ICT infrastructure. Moreover, smart algorithms are developed which are aware of the different states that are occurring on each device during their typical use phase, as well as to detect and isolate possible anomalies. The produced results are obtained and validated with the use of Cisco switches and routers, Dell Precision stations and Raritan PDU as part of the monitored infrastructure.

Information fusion in the immune system

Biologically-inspired methods such as evolutionary algorithms and neural networks are proving useful in the field of information fusion. Artificial immune systems (AISs) are a biologically-inspired approach which take inspiration from the biological immune system. Interestingly, recent research has shown how AISs which use multi-level information sources as input data can be used to build effective algorithms for realtime computer intrusion detection. This research is based on biological information fusion mechanisms used by the human immune system and as such might be of interest to the information fusion community. The aim of this paper is to present a summary of some of the biological information fusion mechanisms seen in the human immune system, and of how these mechanisms have been implemented as AISs.

Avaliação de desempenho : estudo de caso da aplicação do balanced scorecard numa organização especializada na área do exercício, saúde e bem-estar

Atividade física, saúde e bem-estar são temas presentes no dia-a-dia das pessoas. O mercado do Fitness está dinâmico e ativo, quer na comunicação, através das novas tecnologias de informação, quer na especialização da oferta de produtos ou serviços. O Personal training surge como um produto feito á medida do cliente, importante numa sociedade onde a individualidade sobressai, as preferências e necessidades divergem de cliente para cliente. É solicitada uma boa performance constantemente ao profissional, que se pretende traduzida em altas taxas de angariação e retenção. O Balanced Scorecard (BSC), apresenta soluções válidas neste contexto de mercado, já que é uma ferramenta de apoio á gestão estratégica e simultaneamente um sistema de monitorização em tempo real dos indicadores de performance dos profissionais (Personal Trainer) e dos restantes níveis hierárquicos da Organização. Num mercado concorrencial, a valorização do recurso humano tem-se revelado crucial nos resultados alcançados e principal fator de criação de valor e vantagem competitiva, quando bem monitorizada e orientada pela Gestão da Organização. Surge como desafio maior, elaborar, posicionar, implementar, avaliar e medir através deste instrumento (BSC), num contexto laboral diferente (prestadores de serviços) onde já foi aplicado e apurar o nível de desempenho alcançado pela organização orientado nas respetivas visões: financeira, clientes, aprendizagem – crescimento e processos internos.

Isolation and identification of two galangin metabolites from rat urine and determination of their in vitro hypolipidemic activity

Purpose: To investigate the lipid-lowering activity of two metabolites of galangin, namely, galangin-3-Oβ-D-glucuronic acid (GG-1) and galangin-7-O-β-D-glucuronic acid (GG-2). Methods: Female Sprague-Dawley rats were orally administered with galangin. The two metabolites of galangin were isolated from urine sample and purified using Sephadex LH-20 and semi-preparative high performance liquid chromatography (HPLC). The structures of the metabolites were identified by analyzing spectroscopic data. Hypolipidemic activity was evaluated in HepG2 cells. The down- or upregulation of lipogenic genes was detected using real-time quantitative polymerase chain reaction (qPCR). Results: Both metabolites of galangin showed hypolipidemic activity. These activities are closely associated with the down-regulation of lipogenic genes such as SREBP-1a, SREBP-1c, and SREBP-2 transcription factors, and the downstream genes such as FAS, ACC, and HMGR were revealed by realtime qPCR data. Conclusion: The results show that both metabolites possess better lipid-lowering activities than galangin. These hypolipidemic activities are closely associated with inhibiting key genes or proteins that regulated the biosynthesis of both cholesterol and triglycerides.

Cosmic Explosions: Observations Of Infant Hydrogen-Free Supernovae Towards An Understanding Of Their Parent Systems

Radiation in the first days of supernova explosions contains rich information about physical properties of the exploding stars. In the past three years, I used the intermediate Palomar Transient Factory to conduct one-day cadence surveys, in order to systematically search for infant supernovae. I show that the one-day cadences in these surveys were strictly controlled, that the realtime image subtraction pipeline managed to deliver transient candidates within ten minutes of images being taken, and that we were able to undertake follow-up observations with a variety of telescopes within hours of transients being discovered. So far iPTF has discovered over a hundred supernovae within a few days of explosions, forty-nine of which were spectroscopically classified within twenty-four hours of discovery.

Our observations of infant Type Ia supernovae provide evidence for both the single-degenerate and double-degenerate progenitor channels. On the one hand, a low-velocity Type Ia supernova iPTF14atg revealed a strong ultraviolet pulse within four days of its explosion. I show that the pulse is consistent with the expected emission produced by collision between the supernova ejecta and a companion star, providing direct evidence for the single degenerate channel. By comparing the distinct early-phase light curves of iPTF14atg to an otherwise similar event iPTF14dpk, I show that the viewing angle dependence of the supernova-companion collision signature is probably responsible to the difference of the early light curves. I also show evidence for a dark period between the supernova explosion and the first light of the radioactively-powered light curve. On the other hand, a peculiar Type Ia supernova iPTF13asv revealed strong near-UV emission and absence of iron in the spectra within the first two weeks of explosion, suggesting a stratified ejecta structure with iron group elements confined to the slow-moving part of the ejecta. With its total ejecta mass estimated to exceed the Chandrasekhar limit, I show that the stratification and large mass of the ejecta favor the double-degenerate channel.

In a separate approach, iPTF found the first progenitor system of a Type Ib supernova iPTF13bvn in the pre-explosion HST archival mages. Independently, I used the early-phase optical observations of this supernova to constrain its progenitor radius to be no larger than several solar radii. I also used its early radio detections to derive a mass loss rate of 3e-5 solar mass per year for the progenitor right before the supernova explosion. These constraints on the physical properties of the iPTF13bvn progenitor provide a comprehensive data set to test Type Ib supernova theories. A recent HST revisit to the iPTF13bvn site two years after the supernova explosion has confirmed the progenitor system.

Moving forward, the next frontier in this area is to extend these single-object analyses to a large sample of infant supernovae. The upcoming Zwicky Transient Facility with its fast survey speed, which is expected to find one infant supernova every night, is well positioned to carry out this task.