Networks of communicating agents require distributed algorithms for a variety of tasks in the field of network analysis and control. For applications such as swarms of autonomous vehicles, ad hoc and wireless sensor networks, and such military and civilian applications as exploring and patrolling a robust autonomous system that uses a distributed algorithm for self-partitioning can be significantly helpful. A single team of autonomous vehicles in a field may need to self-dissemble into multiple teams, conducive to completing multiple control tasks. Moreover, because communicating agents are subject to changes, namely, addition or failure of an agent or link, a distributed or decentralized algorithm is favorable over having a central agent. A framework to help with the study of self-partitioning of such multi agent systems that have most basic mobility model not only saves our time in conception but also gives us a cost effective prototype without negotiating the physical realization of the proposed idea. In this thesis I present my work on the implementation of a flexible and distributed stochastic partitioning algorithm on the Lego® Mindstorms’ NXT on a graphical programming platform using National Instruments’ LabVIEW™ forming a team of communicating agents via NXT-Bee radio module. We single out mobility, communication and self-partition as the core elements of the work. The goal is to randomly explore a precinct for reference sites. Agents who have discovered the reference sites announce their target acquisition to form a network formed based upon the distance of each agent with the other wherein the self-partitioning begins to find an optimal partition. Further, to illustrate the work, an experimental test-bench of five Lego NXT robots is presented.

This project first explored various methods of designing a communication and control system for an AGV. It then implemented a SOA based communication system in ROS on the selected AGV. The ROS package created in the project implemented functions of the Aria and ArNetworking libraries from Adept. The next step of the project implemented the functions of teleoperation, mapping and transfer of maps and navigation from Aria into ROS. The packages built implemented these functions in different ways to test the best method to transfer Aria functions into ROS. A generic set of rules were then formulated that aided the conversion of these functions for users unfamiliar with either of the two packages (ROS and Aria).

MSc (Med), Epidemiology and Biostatistics, Faculty of Health Sciences, University of the Witwatersrand / Introduction Given the increasing prevalence of non-typhoidal salmonella in humans, especially as an opportunistic illness associated with HIV, enhanced surveillance for non-typhoidal salmonella (NTS), including screening for antibiotic resistance, is conducted annually in South Africa. We aimed to determine whether there is an association between trimethoprim-sulfamethoxazole (TMP-SMX) prophylaxis and multi-drug resistant NTS infection, to establish whether various factors modify the relationship between TMP-SMX resistance and invasive NTS infection, to examine whether these associations vary by province, and to quantify the resistance rates of NTS to a range of antibiotics. Methods This study was a secondary analysis of enhanced surveillance data on NTS collected between 2003 and 2005. We used descriptive methods to assess the prevalence of NTS by year, province and serotype, and to determine the prevalence of four MDR patterns. Univariate and multivariate regression models were used to investigate the relationships between TMP-SMX prophylaxis and MDR NTS. Univariate logistic regression was used to assess the relationship between invasive NTS and TMP-SMX resistance. Results TMP-SMX prophylaxis is associated with the ACKSSuT pattern (OR 1.91, 95% CI 1.14 – 3.19, p=0.0080) and the AKSSuT MDR pattern (OR 2.00, 95% CI 1.26 – 3.15, p=0.0015). Being on TMP-SMX prophylaxis is associated with an increased odds of having at least one of the four MDR patterns investigated (OR 1.43, 95% CI 1.00 – 2.04, p=0.0388). We also found high rates of resistance to all antibiotics tested except for ciprofloxacin and imipenem. The highest resistance rate was observed for sulfamethoxazole (>75.85%). S. enterica Isangi isolates showed the highest levels of resistance, with 94.43% having at least one MDR pattern. Other factors significantly associated with MDR NTS were ESBL production, prior treatment with antibiotics, HIV status and resistance to TMP-SMX. Discussion and conclusions Isolates from patients on TMP-SMX prophylaxis were associated with an increased odds of having the ACKSSuT and AKSSuT MDR patterns, not taking into account other explanatory factors. These associations did not remain significant when possible confounders were taken into account. Despite the threat of increased multi-drug resistance, TMP-SMX prophylaxis remains important in certain clinical settings.

Machine condition monitoring is gaining importance in industry due to the need to increase machine reliability and decrease the possible loss of production due to machine breakdown. Often the data available to build a condition monitoring system does not fully represent the system. It is also often common that the data becomes available in small batches over a period of time. Hence, it is important to build a system that is able to accommodate new data as it becomes available without compromising the performance of the previously learned data. In real-world applications, more than one condition monitoring technology is used to monitor the condition of a machine. This leads to large amounts of data, which require a highly skilled diagnostic specialist to analyze. In this thesis, artificial intelligence (AI) techniques are used to build a condition monitoring system that has incremental learning capabilities. Two incremental learning algorithms are implemented, the first method uses Fuzzy ARTMAP (FAM) algorithm and the second uses Learn++ algorithm. In addition, intelligent agents and multi-agent systems are used to build a condition monitoring system that is able to accommodate various analysis techniques. Experimentation was performed on two sets of condition monitoring data; the dissolved gas analysis (DGA) data obtained from high voltage bushings and the vibration data obtained from motor bearing. Results show that both Learn++ and FAM are able to accommodate new data without compromising the performance of classifiers on previously learned information. Results also show that intelligent agent and multi-agent system are able to achieve modularity and flexibility.

Les systèmes de surveillance modernes doivent coordonner leurs stratégies d’observation pour améliorer l’information obtenue lors de leurs futures mesures afin d’estimer avec précision les états des objets d’intérêt (emplacement, vitesse, apparence, etc.). Par conséquent, la gestion adaptative des capteurs consiste à déterminer les stratégies de mesure des capteurs exploitant les informations a priori afin de déterminer les actions de détection actuelles. L’une des applications la plus connue de la gestion des capteurs est le suivi multi-objet, qui fait référence au problème de l’estimation conjointe du nombre d’objets et de leurs états ou trajectoires à partir de mesures bruyantes. Cette thèse porte sur les stratégies de gestion des capteurs en temps réel afin de résoudre le problème du suivi multi-objet dans le cadre de l’approche RFS labélisée. La première contribution est la formulation théorique rigoureuse du filtre mono-capteur LPHD avec son implémentation Gaussienne. La seconde contribution est l’extension du filtre LPHD pour le cas multi-capteurs. La troisième contribution est le développement de la méthode de gestion de capteurs basée sur la minimisation du risque Bayes et formulée dans les cadres POMDP et LRFS. En outre, des analyses et des simulations des approches de gestion de capteurs existantes pour le suivi multi-objets sont fournies / Modern surveillance systems must coordinate their observation strategies to enhance the information obtained by their future measurements in order to accurately estimate the states of objects of interest (location, velocity, appearance, etc). Therefore, adaptive sensor management consists of determining sensor measurement strategies that exploit a priori information in order to determine current sensing actions. One of the most challenging applications of sensor management is the multi-object tracking, which refers to the problem of jointly estimating the number of objects and their states or trajectories from noisy sensor measurements. This thesis focuses on real-time sensor management strategies formulated in the POMDP framework to address the multi-object tracking problem within the LRFS approach. The first key contribution is the rigorous theoretical formulation of the mono-sensor LPHD filter with its Gaussian-mixture implementation. The second contribution is the extension of the mono-sensor LPHD filter for superpositional sensors, resulting in the theoretical formulation of the multi-sensor LPHD filter. The third contribution is the development of the Expected Risk Reduction (ERR) sensor management method based on the minimization of the Bayes risk and formulated in the POMDP and LRFS framework. Additionally, analyses and simulations of the existing sensor management approaches for multi-object tracking, such as Task-based, Information-theoretic, and Risk-based sensor management, are provided.

Thesis advisor: Hans de Wit / Thesis advisor: Laura Rumbley / This study will identify to what extent the different campuses that compose the Universidad of Guadalajara (UdeG) have taken steps to internationalize uniquely and “independently,” beyond the frameworks for internationalization offered exclusively via central administration, and to identify some of the specific challenges and opportunities inherent in the internationalization processes for a multi-campus system. / Thesis (MA) — Boston College, 2018. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Leadership and Higher Education.

With so many developers writing code, so many choose to become a developer every day, using tools to aid in the work process is needed. With all the testing being done for multiple different devices and sources there is a need to make it better and more efficient. In this thesis connecting the variety of different tools such as version control, project management, issue tracking and test systems is explored as a possible solution. A possible solution was implemented and then analyzed through a questionnaire that were answered by developers. For an example results as high as 75\% answering 5 if they liked the connection between the issue tracking system and the test results. 75\% also gave a 5 when asked about if they liked the way the test results were presented. The answers they gave about the implementation made it possible to conclude that it is possible to achieve a solution that can solve some of the presented problems. A better way to connect various tools to present and analyze the test results coming from multiple different sources.

Orientador: Fernando Antonio de Ávila / Resumo: Escherichia coli patogênica aviária (APEC) é o principal agente da colibacilose, responsável por perdas econômicas em todo o mundo. Na literatura não há um consenso sobre o que define exatamente um patótipo APEC e não se sabe o papel das galinhas de angola na transmissão de APEC para humanos e outros animais. O presente estudo teve como objetivo investigar a presença de APEC em amostras de fezes e orofaringe de galinhas de angola saudáveis e de vida livre, bem como pesquisar fatores de virulência e caracterizá-las filogeneticamente e de acordo com o sorotipo e perfil de resistência a antimicrobianos. Os isolados obtidos apresentaram alta frequência de genes associados à virulência (VAGs) sendo a maioria pertencente ao grupo filogenético B1 e os pertencentes aos grupos B2 e F estiveram associados a um maior número de VAGs. Além disso, grande parte dos isolados foram considerados de alta patogenicidade e apresentaram um perfil de multi resistência a antimicrobianos, incluindo a presença de genes β-lactamases de espectro estendido. Os sorogrupos O2, O51e H4 foram os mais encontrados, sendo o sorotipo O51: H14 o de maior prevalência. As análises PFGE e MLST revelaram uma elevada heterogeneidade entre os isolados associados a 16 Sequence types (ST). Os resultados demonstraram que as galinhas de angola saudáveis e de vida livre podem se constituir como fontes de infecção de ExPEC para outros animais que têm contato próximo com essas aves, incluindo seres humanos. / Abstract: Avian Pathogenic Escherichia coli (APEC) is the main agent of colibacillosis, responsible for economic losses worldwide. In the literature there is no consensus on what exactly defines this pathotype and the role of guinea fowls in transmitting APEC to humans and other animals is unknown. The present study aimed to investigate the presence of APEC in feces and oropharynx samples from healthy and free-living guinea fowls, as well as to investigate virulence factors and characterize phylogenetically them and according to the serotype and antimicrobial resistance profile . The obtained isolates showed high frequency virulence associated genes (VAGs) being the majority belonging to the phylogenetic group B1 and those belonging to groups B2 and F were associated to a greater number of VAGs. In addition, most of the isolates were considered to be highly pathogenic and had a multi-resistant antimicrobial profile, including the presence of extended-spectrum βlactamases. Serogroups O2, O51 and H4 were the most frequently found, with serotype O51:H14 being the most prevalent. The PFGE and MLST analyzes revealed a high heterogeneity among isolates associated with 16 Sequence types (ST). The results showed that healthy and free-living guinea fowls may be sources of ExPEC infection for other animals that have close contact with these birds, including humans. / Doutor

We consider multi-objective simulation optimization (MOSO) problems, that is, nonlinear optimization problems in which multiple simultaneous objective functions can only be observed with stochastic error, e.g., as output from a Monte Carlo simulation model. In this context, the solution to a MOSO problem is the efficient set, which is the set of all feasible decision points for which no other feasible decision<br>point is at least as good on all objectives and strictly better on at least one objective. We are concerned primarily with MOSO problems on integer lattices, that is, MOSO<br><div>problems where the feasible set is a subset of an integer lattice. <br></div><div><br></div><div>In the first study, we propose the Retrospective Partitioned Epsilon-constraint with Relaxed Local Enumeration (R-PεRLE) algorithm to solve the bi-objective simulation optimization problem on integer lattices. R-PεRLE is designed for sampling efficiency. It uses a retrospective approximation (RA) framework to repeatedly call<br></div>the PεRLE sample-path solver at a sequence of increasing sample sizes, using the solution from the previous RA iteration as a warm start for the current RA iteration.<br>The PεRLE sample-path solver is designed to solve the sample-path problem only to within a tolerance commensurate with the sampling error. It comprises a call to<br>each of the Pε and RLE algorithms, in sequence. First, Pε searches for new points to add to the sample-path local efficient set by solving multiple constrained single-<br>objective optimization problems. Pε places constraints to locate new sample-path local efficient points that are a function of the standard error away, in the objective space, from those already obtained. Then, the set of sample-path local efficient points found by Pε is sent to RLE, which is a local crawling algorithm that ensures the set is a sample-path approximate local efficient set. As the number of RA iterations increases, R-PεRLE provably converges to a local efficient set with probability one under appropriate regularity conditions. We also propose a naive, provably-convergent<br>benchmark algorithm for problems with two or more objectives, called R-MinRLE. R-MinRLE is identical to R-PεRLE except that it replaces the Pε algorithm with an<br>algorithm that updates one local minimum on each objective before invoking RLE. R-PεRLE performs favorably relative to R-MinRLE and the current state of the art, MO-COMPASS, in our numerical experiments. Our work points to a family of<br><div>RA algorithms for MOSO on integer lattices that employ RLE for certification of a sample-path approximate local efficient set, and for which the convergence guarantees are provided in this study.</div><div><br></div><div>In the second study, we present the PyMOSO software package for solving multi-objective simulation optimization problems on integer lattices, and for implementing<br></div>and testing new simulation optimization (SO) algorithms. First, for solving MOSO problems on integer lattices, PyMOSO implements R-PεRLE and R-MinRLE, which<br>are developed in the first study. Both algorithms employ pseudo-gradients, are designed for sampling efficiency, and return solutions that, under appropriate regularity<br>conditions, provably converge to a local efficient set with probability one as the simulation budget increases. PyMOSO can interface with existing simulation software and<br>can obtain simulation replications in parallel. Second, for implementing and testing new SO algorithms, PyMOSO includes pseudo-random number stream management,<br>implements algorithm testing with independent pseudo-random number streams run in parallel, and computes the performance of algorithms with user-defined metrics.<br>For convenience, we also include an implementation of R-SPLINE for problems with one objective. The PyMOSO source code is available under a permissive open source<br>license.

No contexto da Engenharia de Software para a Computação em Nuvem as pesquisas relacionadas ao tema são cada vez mais crescentes e investiga-se como a Computação em Nuvem influenciará no desenvolvimento de sistemas de uma maneira geral. A atividade de construir sistemas para nuvem é uma tarefa complexa, criar aplicações de múltiplas nuvens, sobretudo, no contexto do modelo de serviço Plataforma-como-um-Serviço(PaaS), é ainda mais agravada devido especificidades de plataformas de nuvem que podem tornar a tarefa de desenvolvimento repetitiva, custosa e dependente de um provedor específico. As abordagens dirigidas por modelos(MDE) resolvem alguns desses problemas, elas propõem que a modelagem e mecanismos de transformação utilizados para gerar código a partir de modelos são uma melhor maneira de desenvolver sistemas de software, ao invés da codificação pura. Portanto, visando investigar como combinar os benefícios da Computação em Nuvem alinhados ao MDE, foi desenvolvida uma abordagem dirigida por modelos para desenvolvimento de aplicações multi-PaaS. Em direção a este objetivo foi realizado um Estudo de Caso em colaboração com uma empresa da indústria. Essa colaboração permitiu a criação de implementações de referencia que possibilitaram o desenvolvimento de uma Linguagem Específica de Domínio (DSL) e metaprogramas que compõem a abordagem. Para avaliar a abordagem desenvolvida foi realizado um Estudo de Caso. Os resultados mostram que MDE pode não só resolver o problema, mas trazer benefícios adicionais em relação a abordagens tradicionais de desenvolvimento de sistemas. Este trabalho explora esses benefícios, apresenta uma maneira de unir recursos heterogêneos de nuvem por meio de uma abordagem dirigida por modelos e aplicações orientadas a serviço. / Cloud computing is a computational paradigm that has increasingly been used in various sectors of industry and academia. Researchers have been studying how cloud technologies can influence several areas of science and research. In the context of Software Engineering, the researches related to cloud are increasingly increasing. Researchers are studying how to develop better cloud services offerings and how to find a strategy for combining existing resources to build improved services and solve problems. Building cloud systems is a complex task, in the context of the Platform-as-a-Service(PaaS) cloud service model; this activity is further aggravated by cloud platform specificities that can make the task of development repetitive, costly,and platform-specific. Model-driven approaches (MDE) solve some of these issues; they propose that the modeling and transformation mechanisms used to generate code from models are a better way to develop software systems, rather than pure coding. Development with MDE is a comprehensive and relevant research area and needs to be better explored in a wide range of contexts. Therefore, in order to investigate how to combine the benefits of multi-cloud appications aligned to the MDE, we developed a model-driven approach to build multi-PaaS applications.Toward this objective, we performed a case study in collaboration with an industry company.This collaboration allowed the creation of reference implementations that enabled the development of a Domain Specific Language (DSL) and metaprograms that constitute the approach. To evaluate the approach, we performed a case study. The results show that MDE cannot only solve the problem, but also bring additional benefits over traditional systems development approaches. This work explores these benefits, presents a way to combine heterogeneous cloud resources through a service-driven model and application-driven approach.