Models and algoritms for conflict Analysis and Prevention

The research on methods for conflict resolution and prevention has improved dras- tically in the last years. In particular computer-aided methods have acquired more importance because they allow for larger databases with more variables, complex statistical analysis, deeper insights etc... This thesis intends to give a description of those methods and pro jects that I consider most interesting and/or representative in the field, with the goal of pointing out some questions and problems which need still to be answered. Moreover two new methods, never used before for conflict situation, are also presented: Multicriteria-Clustering and Logic Functions

Using Formal Methods to Verify Transactional Abstract Concurrency Control

Concurrent application design and implementation is more important than ever in today\u27s multi-core processor world. Transactional Memory (TM) Concurrent application design and implementation is more important than ever in today\u27s multi-core processor world. Transactional Memory (TM). Each has its own particular advantages and disadvantages. However, these techniques each need some extra information to `glue\u27 the non-transactional operation into a transactional context. At the most general level, non-transactional code must be decorated in such a way that the TM run-time can determine how those non-transactional operations commute with one another, and how to `undo\u27 the non-transactional operations in case the run-time needs to abort a software transaction. The TM run-time trusts that these programmer-provided annotations are correct. Therefore, if an implementor needs to employ one of these transactional `escape hatches\u27, it is crucially important that their concurrency control annotations be correct. However, reasoning about the commutativity of data structure operations is often challenging, and increasing the burden on the programmer with a proof requirement does not simplify the task of concurrent programming. There is a way to leverage the structure that these TM extensions require to reduce greatly the burden on the programmer. If the programmer could describe the abstract state of the data structure and then reason about it with as much machine assistance as possible, then there would be much less opportunity for error. Abstract state is preferable to a more concrete state, because it permits the programmer to use different concrete implementations of the same abstract data type. Also, some TM extensions such as open nesting can handle concrete state conflicts without programmer intervention (making the abstract state the appropriate state for reasoning about commutativity). A solution to the problem of specifying and verifying the concurrency properties of abstract data structures is the subject of this thesis. We will describe a new language, ACCLAM, for describing the abstract state of a data structure and reasoning about its concurrency control properties. This thesis also describes a tool that can process ACCLAM descriptions into a machine verifiable form (they are converted to a SAT problem). We will also provides a more detailed overview of transactional memory and the more popular extensions, a detailed semantic description of ACCLAM and a set of example data structure models and the results of processing those examples with the language processing tool

ON EQUIVALENCY REASONING FOR CONFLICT DRIVEN CLAUSE LEARNING SATISFIABILITY SOLVERS

Satisfiability problem or SAT is the problem of deciding whether a Boolean function evaluates to true for at least one of the assignments in its domain. The satisfiability problem is the first problem to be proved NP-complete. Therefore, the problems in NP can be encoded into SAT instances. Many hard real world problems can be solved when encoded efficiently into SAT instances. These facts give SAT an important place in both theoretical and practical computer science. In this thesis we address the problem of integrating a special class of equivalency reasoning techniques, the strongly connected components or SCC based reasoning, into the class of conflict driven clause learning or CDCL SAT solvers. Because of the complications that arise from integrating the equivalency reasoning in CDCL SAT solvers, to our knowledge, there has been no CDCL solver which has applied SCC based equivalency reasoning dynamically during the search. We propose a method to overcome these complications. The method is integrated into a prominent satisfiability solver: MiniSat. The equivalency enhanced MiniSat, Eq-MiniSat, is used to explore the advantages and disadvantages of the equivalency reasoning in conflict clause learning satisfiability solvers. Different implementation approaches for Eq-MiniSat are discussed. The experimental results on 16 families of instances shows that equivalency reasoning does not have noticeable effects for the instances in one family. The equivalency reasoning enables Eq-MiniSat to outperform MiniSat on eight classes of instances. For the remaining seven families, MiniSat outperforms Eq- MiniSat. The experimental results for random instances demonstrate that almost in all cases the number of branchings for Eq-Minisat is smaller than Minisat

Pneumatic motion control systems for modular robots

This thesis describes a research study in the design, implementation, evaluation and commercialisation of pneumatic motion control systems for modular robots. The research programme was conducted as part of a collaborative study, sponsored by the Science and Engineering Research Council, between Loughborough University and Martonair (UK) Limited. Microprocessor based motion control strategies have been used to produce low cost pneumatic servo-drives which can be used for 'point-to-point' positioning of payloads. Software based realtime control strategies have evolved which accomplish servo-controlled positioning while compensating for drive system non-linearities and time delays. The application of novel compensation techniques has resulted in a significant improvement in both the static and dynamic performance of the drive. A theoretical foundation is presented based on a linearised model of a pneumatic actuator, servo-valve, and load system. The thesis describes the design and evolution of microprocessor based hardware and software for motion control of pneumatic drives. A British Standards based test-facility has allowed control strategies to be evaluated with reference to standard performance criteria. It is demonstrated in this research study that the dynamic and static performance characteristics of a pneumatic motion control system can be dramatically improved by applying appropriate software based realtime control strategies. This makes the application of computer controlled pneumatic servos in manufacturing very attractive with cost performance ratios which match or better alternative drive technologies. The research study has led to commercial products (marketed by Martonair Ltd), in which realtime control algorithms implementing these control strategy designs are executed within a microprocessor based motion controller

European sanctions reconsidered: regime type, strategic bargaining, and the imposition of EU sanctions

Since the end of the Cold War, the European Union (EU) has become a prominent sender of international sanctions. Most of its sanctions regimes have been imposed to address human rights violations and democratic shortcomings in autocratic regimes. While these developments have attracted an increased attention by academics and practitioners alike, not much is known about the underlying factors that trigger the EU’s decision to impose sanctions in the very first place. Using a new database of EU democratic sanctions between 1989 and 2010, this thesis develops a theoretical model that shows that the imposition of sanctions is the result of a strategic bargaining process between a sender and a target country. I argue that sanctions are only one possible outcome of this process, and claim that the likelihood that sanctions are imposed depends, to a large extent, on the target country’s decision to comply with the sender before sanctions are imposed or, alternatively, on its determination to ignore the sender’s threat of sanctions and resist its pressure. I show that the target’s decision to comply or resist is the result of an endogenous policy formation process, which is determined by the target regime’s domestic institutional setting. Different types of institutions (regime types) impose varying degrees of constraints on the ruler’s margin of manoeuvre and shape her policy choices vis-à-vis the threat and imposition of sanctions. I demonstrate that regimes that face no domestic constraints and rely on a small winning coalition of supporters are likely to be strong and willing to resist the sender’s pressure, thereby “self-selecting” themselves into sanctions. By the same token, regimes that face many domestic constraints are vulnerable to sanctions, and face incentives to comply with the sender before sanctions are imposed. My thesis makes several contributions to the literature. First, it provides a theoretical explanation of how domestic institutions matter in the imposition of sanctions, and identifies a set of conditions under which sanctions are more likely (not) to be imposed. Second, it empirically demonstrates the presence of selection effects in the study of sanctions imposition, and shows that these are channelled through the target regime’s domestic institutions. Finally, my findings have relevant policy implications, as they suggest that sanctions are more likely to be effective against certain types of targets. I show that sanctions are more likely to succeed against politically constrained regimes at the threat stage or early during a sanctions episode, whilst they are likely to fail against highly authoritarian regimes which rule free of domestic constraints

Exploring vulnerability to infectious disease in a small-holder farming community in rural western Kenya

More than 2 billion people live on less than 2 US dollars per day. People in these conditions often have inadequate access to basic sanitation, safe water, and medical services. These individuals, households and communities may be at high risk for a wide range of preventable and treatable infectious diseases. The aims of this study were to: 1) describe the prevalence of endemic helminth, protozoal, bacterial and viral infections of people in a small-holder farming community in western Kenya; 2) explore the spatial distribution of infection risk; 3) quantify associations between social and environmental conditions and individual- and household-level infection; 4) identify shared risk factors operating on multiple pathogens. All data were collected between July 2010 and July 2012 as part of a cross-sectional survey of 416 households and 2113 people. This sample was considered representative of a population of 1.4 million people living in an area of western Kenya characterised by high levels of poverty. Sampled individuals were tested for exposure to, or infection with, 21 infectious agents using a range of faecal, blood and serological tests. Extensive questionnaire-based data were also collected. Individual- and household-level risk factors for infection with prevalent pathogens were explored using multilevel logistic regression, with a particular focus on examining the impact of socioeconomic position (SEP). Hierarchical zero-inflated binomial (ZIB) regression was used to derive an estimate of household pathogen ‘species richness’ with correction for imperfect detection. This modelling framework allowed assessment of the relationship between household-level infection with each parasite and a range of social and environmental conditions and, uniquely for a single study setting, the average response of the ‘group’ of parasites to these conditions. This study found very high levels of parasitism in the community, particularly with hookworm (36.3% (95% CI 32.8 – 39.9)), Entamoeba histolytica/dispar (30.1% (27.5 – 32.8)), Plasmodium falciparum (29.4% (26.8 – 32.0)), and Taenia spp. (19.7% (16.7 – 22.7)). Some degree of within-household clustering was found for all pathogens, and this was particularly large for the helminth species and HIV. Most pathogens also showed spatial heterogeneity in infection risk, with evidence of spatial clustering in household-level infection, most notably for HIV, Schistosoma mansoni, P. falciparum and the soiltransmitted helminths. A socioeconomic gradient was identified, even in this predominantly poor community. Increasing socioeconomic position (SEP) resulted in significantly reduced risk of individual infection for E. histolytica/dispar, P. falciparum, and hookworm. By contrast, individuals living in the richest households were at significantly elevated risk of infection with Mycobacterium spp.. Individuals living in the poorest households were least likely to report the recent use of medical treatments. The average pathogen species richness (out of 21 species) per household was 4.7 (range: 0 to 13). Following correction for detection error, the predicted average helminth species count (out of 6 species) was 3 (range: 0.94 to 5.96). While socioeconomic position had little effect on the probability that a household was infected with any of the helminth species of interest, domestic (within-household) transmission appeared to be greatest in the poorest households for hookworm, S. mansoni, Ascaris lumbricoides and Strongyloides stercoralis. Household size had a consistent effect on probably of household infection with each helminth species, so that the largest households were also the most pathogen diverse. Household-level helminth species richness was identified as a significant positive predictor of individual risk of HIV infection, raising potentially important questions about helminth-HIV interactions in the study area. This study integrates approaches from epidemiology and ecology to explore infectious disease risk and its determinants at a range of social and geographic scales in a small-holder farming community in western Kenya. Considering risk at both the individual and household level within the same community can contribute to better understanding of the factors that influence disease transmission in both domestic and public domains

Rule-based system architecting of Earth observation satellite systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 399-412).System architecting is concerned with exploring the tradespace of early, high-level, system design decisions with a holistic, value-centric view. In the last few years, several tools and methods have been developed to support the system architecting process, focusing on the representation of an architecture as a set of interrelated decisions. These tools are best suited for applications that focus on breadth - i.e., enumerating a large and representative part of the architectural tradespace -as opposed to depth - modeling fidelity. However, some problems in system architecting require good modeling depth in order to provide useful results. In some cases, a very large body of expert knowledge is required. Current tools are not designed to handle such large bodies of knowledge because they lack scalability and traceability. As the size of the knowledge base increases, it becomes harder: a) to modify existing knowledge or add new knowledge; b) to trace the results of the tool to the model assumptions or knowledge base. This thesis proposes a holistic framework for architecture tradespace exploration of large complex systems that require a large body of expert knowledge. It physically separates the different bodies of knowledge required to solve a system architecting problem (i.e., knowledge about the domain, knowledge about the class of optimization or search problem, knowledge about the particular instance of problem) by using a rule-based expert system. It provides a generic population-based heuristic algorithm for search, which can be augmented with rules that encode knowledge about the domain, or about the optimization problem or class of problems. It identifies five major classes of system architecting problems from the perspective of optimization and search, and provides rules to enumerate architectures and search through the architectural tradespace of each class. A methodology is also defined to assess the value of an architecture using a rule-based approach. This methodology is based on a decomposition of stakeholder needs into requirements and a systematic comparison between system requirements and system capabilities using the rules engine. The framework is applied to the domain of Earth observing satellite systems (EOSS). Three EOSS are studied in depth: the NASA Earth Observing System, the NRC Earth Science Decadal Survey, and the Iridium GEOscan program. The ability of the framework to produce useful results is shown, and specific insights and recommendations are drawn.by Daniel Selva Valero.Ph.D

An Exact Inference Scheme for MinSAT

We describe an exact inference-based algorithm for the MinSAT problem. Given a multiset of clauses C, the algorithm derives as many empty clauses as the maximum number of clauses that can be falsified in C by applying finitely many times an inference rule, and returns an optimal assignment. We prove the correctness of the algorithm, describe how it can be extended to deal with weighted MinSAT and weighted partial MinSAT instances, analyze the differences between the MaxSAT and MinSAT inference schemes, and define and empirically evaluate the MinSAT Pure Literal Rule.Research partially supported by the Generalitat de Catalunya grant AGAUR 2014-SGR-118, CSIC Intramural Project 2014450E045, and the Ministerio de Economía y Competitividad project CO-PRIVACY TIN2011-27076-C03-03. The second author was supported by Mobility Grant PRX14/00195 of the Ministerio de Educación, Cultura y Deporte.Peer Reviewe