Model-Driven Methodology for Rapid Deployment of Smart Spaces based on Resource-Oriented Architectures

Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT) and Web of Things (WoT) are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i) to integrate sensing and actuating functionalities into everyday objects, and (ii) to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD) methodology based on the Model Driven Architecture (MDA). This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym.

3D simulation of complex shading affecting PV systems taking benefit from the power of graphics cards developed for the video game industry

Shading reduces the power output of a photovoltaic (PV) system. The design engineering of PV systems requires modeling and evaluating shading losses. Some PV systems are affected by complex shading scenes whose resulting PV energy losses are very difficult to evaluate with current modeling tools. Several specialized PV design and simulation software include the possibility to evaluate shading losses. They generally possess a Graphical User Interface (GUI) through which the user can draw a 3D shading scene, and then evaluate its corresponding PV energy losses. The complexity of the objects that these tools can handle is relatively limited. We have created a software solution, 3DPV, which allows evaluating the energy losses induced by complex 3D scenes on PV generators. The 3D objects can be imported from specialized 3D modeling software or from a 3D object library. The shadows cast by this 3D scene on the PV generator are then directly evaluated from the Graphics Processing Unit (GPU). Thanks to the recent development of GPUs for the video game industry, the shadows can be evaluated with a very high spatial resolution that reaches well beyond the PV cell level, in very short calculation times. A PV simulation model then translates the geometrical shading into PV energy output losses. 3DPV has been implemented using WebGL, which allows it to run directly from a Web browser, without requiring any local installation from the user. This also allows taken full benefits from the information already available from Internet, such as the 3D object libraries. This contribution describes, step by step, the method that allows 3DPV to evaluate the PV energy losses caused by complex shading. We then illustrate the results of this methodology to several application cases that are encountered in the world of PV systems design. Keywords: 3D, modeling, simulation, GPU, shading, losses, shadow mapping, solar, photovoltaic, PV, WebGL

Eliminación de nutrientes mediante tratamientos biopelícula : corrientes actuales y necesidades de investigación

Los tratamientos biopelícula fueron unos de los primeros tratamientos biológicos que se aplicaron en las aguas residuales. Los tratamientos biopelícula presentan importantes ventajas frente a los cultivos en suspensión, sin embargo, el control de los tratamientos biopelícula es complicado y su modelización también. Las bases teóricas del comportamiento de las biopelículas empezaron a desarrollarse fundamentalmente a partir de los años 80. Dado que el proceso es complejo con ecuaciones de difícil resolución, estas conceptualizaciones han sido consideradas durante años como ejercicios matemáticos más que como herramientas de diseño y simulación. Los diseños de los reactores estaban basados en experiencias de plantas piloto o en comportamientos empíricos de determinadas plantas. Las ecuaciones de diseño eran regresiones de los datos empíricos. La aplicabilidad de las ecuaciones se reducía a las condiciones particulares de la planta de la que provenían los datos empíricos. De tal forma que existía una gran variedad y diversidad de ecuaciones empíricas para cada tipo de reactor. La investigación médica durante los años 90 centró su atención en la formación y eliminación de las biopelículas. Gracias al desarrollo de nuevas prácticas de laboratorio que permitían estudiar el interior de las biopelículas y gracias también al aumento de la capacidad de los ordenadores, la simulación del comportamiento de las biopelículas tomó un nuevo impulso en esta década. El desarrollo de un tipo de biopelículas, fangos granulares, en condiciones aerobias realizando simultaneamente procesos de eliminación de nutrientes ha sido recientemente patentado. Esta patente ha recibido numerosos premios y reconocimientos internacionales tales como la Eurpean Invention Award (2012). En 1995 se descubrió que determinadas bacterias podían realizar un nuevo proceso de eliminación de nitrógeno denominado Anammox. Este nuevo tipo de proceso de eliminación de nitrógeno tiene el potencial de ofrecer importantes mejoras en el rendimiento de eliminación y en el consumo de energía. En los últimos 10 años, se han desarrollado una serie de tratamientos denominados “innovadores” de eliminación de nutrientes. Dado que no resulta posible el establecimiento de estas bacterias Anammox en fangos activos convencionales, normalmente se recurre al uso de cultivos biopelícula. La investigación se ha centrado en el desarrollo de estos procesos innovadores en cultivos biopelícula, en particular en los fangos granulares y MBBR e IFAs, con el objeto de establecer las condiciones bajo las cuales estos procesos se pueden desarrollar de forma estable. Muchas empresas y organizaciones buscan una segunda patente. Una cuestión principal en el desarrollo de estos procesos se encuentra la correcta selección de las condiciones ambientales y de operación para que unas bacterias desplacen a otras en el interior de las biopelículas. El diseño de plantas basado en cultivos biopelícula con procesos convencionales se ha realizado normalmente mediante el uso de métodos empíricos y semi-empíricos. Sin embargo, los criterios de selección avanzados aplicados en los Tratamientos Innovadores de Eliminación de Nitrógeno unido a la complejidad de los mecanismos de transporte de sustratos y crecimiento de la biomasa en las biopelículas, hace necesario el uso de herramientas de modelización para poder conclusiones no evidentes. Biofilms were one of the first biological treatments used in the wastewater treatment. Biofilms exhibit important advantages over suspended growth activated sludge. However, controlling biofilms growth is complicated and likewise its simulation. The theoretical underpinnings of biofilms performance began to be developed during 80s. As the equations that govern the growth of biofilms are complex and its resolution is challenging, these conceptualisations have been considered for years as mathematical exercises instead of practical design and simulation tools. The design of biofilm reactors has been based on performance information of pilot plants and specific plants. Most of the times, the designing equations were simple regressions of empirical data. The applicability of these equations were confined to the particular conditions of the plant from where the data came from. Consequently, there were a wide range of design equations for each type of reactor During 90s medical research focused its efforts on how biofilm´s growth with the ultimate goal of avoiding it. Thanks to the development of new laboratory techniques that allowed the study the interior of the biofilms and thanks as well to the development of the computers, simulation of biofilms’ performance had a considerable evolution during this decade. In 1995 it was discovered that certain bacteria can carry out a new sort of nutrient removal process named Anammox. This new type of nutrient removal process potentially can enhance considerably the removal performance and the energy consumption. In the last decade, it has been developed a range of treatments based on the Anammox generally named “Innovative Nutrient Removal Treatments”. As it is not possible to cultivate Anammox bacteria in activated sludge, normally scientists and designers resort to the use of biofilms. A critical issue in the development of these innovative processes is the correct selection of environment and operation conditions so as to certain bacterial population displace to others bacteria within the biofilm. The design of biofilm technology plants is normally based on the use of empirical and semi-empirical methods. However, the advanced control strategies used in the Innovative Nutrient Removal Processes together with the complexity of the mass transfer and biomass growth in biofilms, require the use of modeling tools to be able to set non evident conclusions.

Uso de modelagem de nicho fundamental na avaliação do padrão de distribuição geográfica de espécies vegetais

Atualmente vêm sendo desenvolvidas e utilizadas várias técnicas de modelagem de distribuição geográfica de espécies com os mais variados objetivos. Algumas dessas técnicas envolvem modelagem baseada em análise ambiental, nas quais os algoritmos procuram por condições ambientais semelhantes àquelas onde as espécies foram encontradas, resultando em áreas potenciais onde as condições ambientais seriam propícias ao desenvolvimento dessas espécies. O presente estudo trata do uso da modelagem preditiva de distribuição geográfica, através da utilização de algoritmo genético e algoritmo de distância, de espécies como ferramenta para a conservação de espécies vegetais, em três situações distintas: modelagem da distribuição do bioma cerrado no estado de São Paulo; previsão da ocorrência de espécies arbóreas visando à restauração da cobertura vegetal na bacia do Médio Paranapanema e modelagem da distribuição de espécies ameaçadas de extinção (Byrsonima subterranea). A metodologia empregada e os resultados obtidos foram considerados satisfatórios para a geração de modelos de distribuição geográfica de espécies vegetais, baseados em dados abióticos, para as regiões de estudo. A eficácia do modelo em predizer a ocorrência de espécies do cerrado é maior se forem utilizados apenas pontos de amostragem com fisionomias de cerrado, excluindo-se áreas de transição. Para minimizar problemas decorrentes da falta de convergência do algoritmo utilizado GARP (Genetic Algorithm for Rule Set Production), foram gerados 100 modelos para cada espécie modelada. O uso de modelagem pode auxiliar no entendimento dos padrões de distribuição de um bioma ou ecossistema em uma análise regional e local.

Produção de energia por mini e micro hidrelétricas na rede de distribuição de água.

A geração de energia hidrelétrica enfrenta uma crescente restrição a sua expansão, diretamente relacionada a fatores ambientais e da limitação de terrenos com potencial economicamente aproveitável. A partir deste fato, é relacionada uma possível fonte de energia hidrelétrica, resultante do aproveitamento dos potenciais presentes na rede de distribuição de água das cidades, ainda sem nenhum aproveitamento. O desenvolvimento desta fonte de energia se dá com a instalação de mini e micro centrais hidrelétricas nos condutos da rede distribuidora de água. Este trabalho tem por objetivo avaliar o potencial de aproveitamento hidrelétrico por mini e micro hidrelétricas por meio de técnicas de modelagem e de otimização, para agilizar e facilitar o procedimento de identificação dos potenciais e a instalação na rede de abastecimento. O trabalho leva em conta as diversas peculiaridades das redes de distribuição de água e dos equipamentos eletro-hidráulicos, discorrendo sobre a possível complementariedade da geração de energia durante os picos de consumo. Discorre também sobre a contribuição para a rede de distribuição elétrica, na logística e nos custos de implantação além de discutir a tipologia das turbinas capazes de aproveitar o potencial energético. É avaliado, com o auxilio de modelos hidráulicos e de otimização, o posicionamento das centrais geradoras na rede e os possíveis benefícios, restrições e impedimentos ao seu uso, desenvolvendo uma metodologia para facilitar a tomada de decisão quanto ao aproveitamento para geração, ou não, em redes diversas. A construção deste procedimento e ferramenta são desenvolvidos a partir do estudo de caso do sistema distribuidor de água do Município de Piquete no estado de São Paulo, Brasil.

An Empirical Comparison of Reuse in Embedded and Nonembedded Systems

High-quality software, delivered on time and budget, constitutes a critical part of most products and services in modern society. Our government has invested billions of dollars to develop software assets, often to redevelop the same capability many times. Recognizing the waste involved in redeveloping these assets, in 1992 the Department of Defense issued the Software Reuse Initiative. The vision of the Software Reuse Initiative was "To drive the DoD software community from its current "re-invent the software" cycle to a process-driven, domain-specific, architecture-centric, library-based way of constructing software.'' Twenty years after issuing this initiative, there is evidence of this vision beginning to be realized in nonembedded systems. However, virtually every large embedded system undertaken has incurred large cost and schedule overruns. Investigations into the root cause of these overruns implicates reuse. Why are we seeing improvements in the outcomes of these large scale nonembedded systems and worse outcomes in embedded systems? This question is the foundation for this research. The experiences of the Aerospace industry have led to a number of questions about reuse and how the industry is employing reuse in embedded systems. For example, does reuse in embedded systems yield the same outcomes as in nonembedded systems? Are the outcomes positive? If the outcomes are different, it may indicate that embedded systems should not use data from nonembedded systems for estimation. Are embedded systems using the same development approaches as nonembedded systems? Does the development approach make a difference? If embedded systems develop software differently from nonembedded systems, it may mean that the same processes do not apply to both types of systems. What about the reuse of different artifacts? Perhaps there are certain artifacts that, when reused, contribute more or are more difficult to use in embedded systems. Finally, what are the success factors and obstacles to reuse? Are they the same in embedded systems as in nonembedded systems? The research in this dissertation is comprised of a series of empirical studies using professionals in the aerospace and defense industry as its subjects. The main focus has been to investigate the reuse practices of embedded systems professionals and nonembedded systems professionals and compare the methods and artifacts used against the outcomes. The research has followed a combined qualitative and quantitative design approach. The qualitative data were collected by surveying software and systems engineers, interviewing senior developers, and reading numerous documents and other studies. Quantitative data were derived from converting survey and interview respondents' answers into coding that could be counted and measured. From the search of existing empirical literature, we learned that reuse in embedded systems are in fact significantly different from nonembedded systems, particularly in effort in model based development approach and quality where the development approach was not specified. The questionnaire showed differences in the development approach used in embedded projects from nonembedded projects, in particular, embedded systems were significantly more likely to use a heritage/legacy development approach. There was also a difference in the artifacts used, with embedded systems more likely to reuse hardware, test products, and test clusters. Nearly all the projects reported using code, but the questionnaire showed that the reuse of code brought mixed results. One of the differences expressed by the respondents to the questionnaire was the difficulty in reuse of code for embedded systems when the platform changed. The semistructured interviews were performed to tell us why the phenomena in the review of literature and the questionnaire were observed. We asked respected industry professionals, such as senior fellows, fellows and distinguished members of technical staff, about their experiences with reuse. We learned that many embedded systems used heritage/legacy development approaches because their systems had been around for many years, before models and modeling tools became available. We learned that reuse of code is beneficial primarily when the code does not require modification, but, especially in embedded systems, once it has to be changed, reuse of code yields few benefits. Finally, while platform independence is a goal for many in nonembedded systems, it is certainly not a goal for the embedded systems professionals and in many cases it is a detriment. However, both embedded and nonembedded systems professionals endorsed the idea of platform standardization. Finally, we conclude that while reuse in embedded systems and nonembedded systems is different today, they are converging. As heritage embedded systems are phased out, models become more robust and platforms are standardized, reuse in embedded systems will become more like nonembedded systems.

Análise da combustão e emissões em motores a bio-diesel.

A rápida evolução do mercado automotivo, em função de maiores restrições sobre as emissões, impulsionou a utilização de várias alternativas para melhorias dos motores diesel, entre elas as mudanças nos seus componentes com o auxílio de ferramentas de modelagem e a utilização de combustíveis alternativos. As características dos combustíveis afetarão a queima e, assim, alteram os resíduos do processo de combustão. Novos combustíveis podem também ser utilizados como uma alternativa para veículos de gerações anteriores com o intuito de reduzir as emissões. Este estudo mostra os efeitos da utilização do Biodiesel B20 e do Biodiesel Amyris em motores de combustão interna. Para isso, foram realizados testes de motores em salas dinamométricas, e seus resultados confrontados e discutidos. Além disso, são abordados os efeitos do combustível no processo da combustão. Esta Dissertação está concentrada, principalmente, na emissão de NOx e de material particulado, que são poluentes mais restritivos perante a Legislação brasileira de emissões CONAMA P7.

Human performance modelling as an aid to manufacturing system design

Once the factory worker was considered to be a necessary evil, soon to be replaced by robotics and automation. Today, many manufacturers appreciate that people in direct productive roles can provide important flexibility and responsiveness, and so significantly contribute to business success. The challenge is no longer to design people out of the factory, but to design factory environment that help to get the best performance from people. This paper describes research that has set out to help to achieve this by expanding the capabilities of simulation modeling tools currently used by practitioners.

Using ORG-Master for Knowledge Based Organizational Change

* Under Knowledge Infrastructure we imply all the means that enable effective knowledge management within organization ~ knowledge process support.

Improving resource management in virtualized data centers using application performance models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

Dynamic image precompensation for improving visual performance of computer users with ocular aberrations

With the progress of computer technology, computers are expected to be more intelligent in the interaction with humans, presenting information according to the user's psychological and physiological characteristics. However, computer users with visual problems may encounter difficulties on the perception of icons, menus, and other graphical information displayed on the screen, limiting the efficiency of their interaction with computers. In this dissertation, a personalized and dynamic image precompensation method was developed to improve the visual performance of the computer users with ocular aberrations. The precompensation was applied on the graphical targets before presenting them on the screen, aiming to counteract the visual blurring caused by the ocular aberration of the user's eye. A complete and systematic modeling approach to describe the retinal image formation of the computer user was presented, taking advantage of modeling tools, such as Zernike polynomials, wavefront aberration, Point Spread Function and Modulation Transfer Function. The ocular aberration of the computer user was originally measured by a wavefront aberrometer, as a reference for the precompensation model. The dynamic precompensation was generated based on the resized aberration, with the real-time pupil diameter monitored. The potential visual benefit of the dynamic precompensation method was explored through software simulation, with the aberration data from a real human subject. An "artificial eye'' experiment was conducted by simulating the human eye with a high-definition camera, providing objective evaluation to the image quality after precompensation. In addition, an empirical evaluation with 20 human participants was also designed and implemented, involving image recognition tests performed under a more realistic viewing environment of computer use. The statistical analysis results of the empirical experiment confirmed the effectiveness of the dynamic precompensation method, by showing significant improvement on the recognition accuracy. The merit and necessity of the dynamic precompensation were also substantiated by comparing it with the static precompensation. The visual benefit of the dynamic precompensation was further confirmed by the subjective assessments collected from the evaluation participants.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Petri Net Siphon Analysis and Network Centrality Measures for Identifying Combination Therapies in Signaling Pathways

Aberrant behavior of biological signaling pathways has been implicated in diseases such as cancers. Therapies have been developed to target proteins in these networks in the hope of curing the illness or bringing about remission. However, identifying targets for drug inhibition that exhibit good therapeutic index has proven to be challenging since signaling pathways have a large number of components and many interconnections such as feedback, crosstalk, and divergence. Unfortunately, some characteristics of these pathways such as redundancy, feedback, and drug resistance reduce the efficacy of single drug target therapy and necessitate the employment of more than one drug to target multiple nodes in the system. However, choosing multiple targets with high therapeutic index poses more challenges since the combinatorial search space could be huge. To cope with the complexity of these systems, computational tools such as ordinary differential equations have been used to successfully model some of these pathways. Regrettably, for building these models, experimentally-measured initial concentrations of the components and rates of reactions are needed which are difficult to obtain, and in very large networks, they may not be available at the moment. Fortunately, there exist other modeling tools, though not as powerful as ordinary differential equations, which do not need the rates and initial conditions to model signaling pathways. Petri net and graph theory are among these tools. In this thesis, we introduce a methodology based on Petri net siphon analysis and graph network centrality measures for identifying prospective targets for single and multiple drug therapies. In this methodology, first, potential targets are identified in the Petri net model of a signaling pathway using siphon analysis. Then, the graph-theoretic centrality measures are employed to prioritize the candidate targets. Also, an algorithm is developed to check whether the candidate targets are able to disable the intended outputs in the graph model of the system or not. We implement structural and dynamical models of ErbB1-Ras-MAPK pathways and use them to assess and evaluate this methodology. The identified drug-targets, single and multiple, correspond to clinically relevant drugs. Overall, the results suggest that this methodology, using siphons and centrality measures, shows promise in identifying and ranking drugs. Since this methodology only uses the structural information of the signaling pathways and does not need initial conditions and dynamical rates, it can be utilized in larger networks.

A method for assessing ecological values to reconcile multiple land use needs

We present a new method for ecologically sustainable land use planning within multiple land use schemes. Our aims were (1) to develop a method that can be used to locate important areas based on their ecological values; (2) to evaluate the quality, quantity, availability, and usability of existing ecological data sets; and (3) to demonstrate the use of the method in Eastern Finland, where there are requirements for the simultaneous development of nature conservation, tourism, and recreation. We compiled all available ecological data sets from the study area, complemented the missing data using habitat suitability modeling, calculated the total ecological score (TES) for each 1 ha grid cell in the study area, and finally, demonstrated the use of TES in assessing the success of nature conservation in covering ecologically valuable areas and locating ecologically sustainable areas for tourism and recreational infrastructure. The method operated quite well at the level required for regional and local scale planning. The quality, quantity, availability, and usability of existing data sets were generally high, and they could be further complemented by modeling. There are still constraints that limit the use of the method in practical land use planning. However, as increasing data become available and open access, and modeling tools improve, the usability and applicability of the method will increase.

Modelação da qualidade do ar interior em edifícios com ventilação natural

A qualidade do ar interior (QAI) em edifícios é uma preocupação que acompanha o Homem desde há séculos. A qualidade do ar interior nas escolas, em particular, tem vindo a provocar um crescente interesse, dado que o grupo populacional pertence a um grupo etário mais suscetível de ser afetado. A utilização de ferramentas numéricas de modelação na avaliação da QAI é uma mais valia, pois permite estimar as concentrações dos poluentes no interior dos edifícios. O principal objetivo deste estudo consiste na avaliação da qualidade do ar interior através da aplicação de uma ferramenta a um caso de estudo. Neste caso de estudo estimou-se a concentração de material particulado (PM10) numa sala de aula da Escola Básica nº 1 da Glória, em Aveiro. Neste âmbito, foi aplicado o modelo INDEX, Indoor Exposure model, que possibilita o cálculo de concentrações interiores de poluentes atmosféricos. Os resultados da aplicação indicam que as concentrações do ar interior são influenciadas pelas concentrações exteriores e pela velocidade do vento. Note-se, contudo, que os valores simulados cumprem os valores legislados na Portaria nº 353-A/2013, de 4 de Dezembro. Embora os resultados simulados não revelem uma má qualidade do ar interior na sala de aula da Escola Básica nº 1 da Glória, a avaliação de outros poluentes seria um ponto de extrema importância, de forma a verificar se os requisitos da qualidade do ar interior estarão a ser garantidos.