The thesis studies classes of Boolean formulae for which the well-known satisfiability problem is solvable in polynomially bounded time. It focusses on classes based on unit resolution; it describe classes of unit refutation complete formulae, unit propagation complete formulae and focuses on the class of SLUR formulae. It presents properties of SLUR formulae as well as the recently obtained results. The main result is the coNP-completness of membership testing. Finally, several hierarchies are built over the SLUR class and their properties and mutual relations are studied. Powered by TCPDF (www.tcpdf.org)

Title: Kind parser generator Author: Bc. Tomáš Dzurenko Department: Network and Labs Management Center Supervisor: RNDr. Michal Žemlička, Ph.D., Department of Software and Com- puter Science Education Abstract: This thesis introduces a generator which takes as its input a definition k-kind grammar and creates source code of analyzer or translator for the language generated by this kind grammar. Opposed to traditional LL(k) grammars, k-kind grammars allow usage of direct left recursion in its rules. This allows for more comfortable and clearer formulation of input grammar rules. Keywords: parser, translator, generator, C++, kind grammar

Large-scale distributed computing systems such as data centers are hosted on heterogeneous and networked servers that execute in a dynamic and uncertain operating environment, caused by factors such as time-varying user workload and various failures. Therefore, achieving stringent quality-of-service goals is a challenging task, requiring a comprehensive approach to performance control, fault diagnosis, and failure recovery. This work presents a model-based approach for fault management, which integrates limited lookahead control (LLC), diagnosis, and fault-tolerance concepts that: (1) enables systems to adapt to environment variations, (2) maintains the availability and reliability of the system, (3) facilitates system recovery from failures. We focused on memory leak errors in this thesis. A characterization function is designed to detect memory leaks. Then, a LLC is applied to enable the computing system to adapt efficiently to variations in the workload, and to enable the system recover from memory leaks and maintain functionality.

The construction area is one of the sectors that are most important in the development of a country, so we measure the growth rate being the same jobs and increases in other sectors. Despite being a great source of a country do not get to understand the reasons why, especially in Latin America is not generated as much expected development in Europe, Asia or North America. The construction industry has unique characteristics that fail to justify analyzed the degree of development in which there are: weather conditions, work under pressure, little training and above all existing schedule. In the thesis analyzes were taken in as a building project "Building Raygada" which was scheduled execution in 06 months however the lack of planning, organization and control culminated in 09 months, which not only affected the project but time economically in the profits of which were under S/686, 913.00 and finally got S/222, 527.00 equivalent to 67.60% less than the estimated This is why developing a Project Management to improve planning, scheduling and control work is the objective of this study demonstrate that the main problem of the construction is not knowing how to manage resources which should be available when required as otherwise generate unwanted delays for that reason is that we will apply the planning tools such as the theories of Lean Construction,Restrictions, Last Planner and thus develop a detailed analysis of the work and contribute to increased productivity sector construction dare the "Procedure for the planning, execution and control of organized work processes” , which is the contribution to young engineers and professionals who do not consider the benefits of working with Project Management in construction work.

Objective: This document is not an introduction to parser generators. Readers should rather have a good understanding of them, especially of LALR parser generators. This document merely describes the main aspects of the implementation of a LALR parser generator named wisent. It is divided into a concise description of the programming interface and an overview over the data structures and specifics of the implementation of the wisent parser generator.

<p dir="ltr">Employee staffing and scheduling are critical aspects of resource management in labor-intensive, customer-centric service organizations. This thesis investigates the optimal decision-making process for these critical tasks in the presence of non-stationary uncertainty, such as case-mix resident need, recommended staffing hours, and potential staffing turnover, a challenge prevalent in various domains, including healthcare and nursing home management.</p><p dir="ltr">The research begins predicting resident needs accurately. For this purpose, we present a novel Bayesian modeling approach to predict nursing home need-based resident census and staffing time. The resultant time series data of need-based resident census and staffing time are nonstationary with potential correlations between resource utilization groups. We thus propose Bayesian latent variable models with time-varying latent states to capture the dynamic patterns of resident service needs. We demonstrate the superiority of the proposed Bayesian prediction models by comparing their forecasting performance with several popular benchmark models, using historical assessment and aggregate staffing data from representative nursing homes.</p><p dir="ltr">The thesis further incorporates a rolling-horizon scheduling approach that integrates a periodically evolving Bayesian forecasting method into a series of stochastic look-ahead decision actions over multiple periods. To deal with the workforce scheduling with nonstationary demand uncertainty, we introduce a stochastic lookahead optimization framework that executes two-stage stochastic programming periodically along a rolling horizon to address the evolving non-stationary uncertainty. We obtain two-stage stochastic programming models to design effective work schedules, specifically assigning nurses to various shifts while balancing the staff workload and accommodating fluctuating resident needs.</p><p dir="ltr">We finally introduce the SNHSSO framework (stochastic nursing home staffing and scheduling optimizer), encompassing data modeling and addressing multi-period, multi-uncertainty, and multi-objective staffing and scheduling challenges. When the SNHSSO Optimizer is executed with the provided inputs, it generates recommended staffing decisions for longer planning horizons, as well as schedules and contingency plans for shorter planning horizons. These adapted decisions and adjusted parameters are archived for future reference, facilitating subsequent iterations of the process. SNHSSO optimizes caregiver assignments by taking into account probabilistic forecasts of service requirements, resident acuity, and staff turnover, all within two-stage stochastic mixed integer linear programs. Our approach leverages a scenario-based rolling horizon methodology to effectively solve the SNHSSO model.</p><p dir="ltr">The empirical foundation of this work is built on case studies conducted using Minimum Data Set (MDS) data spanning five years from 2014 to 2018 in Indiana nursing homes.</p>

Les travaux de cette thèse portent sur :<br />− la proposition d'algorithmes de simulation distribuée conservative de modèles DEVS / G-DEVS,<br />− la définition et la réalisation d'un environnement de modélisation & simulation (M&S) G-DEVS com-patible HLA implémentant les algorithmes proposés,<br />− l'application de l'environnement à la M&S de Workflow.<br />Dans un premier temps, nous avons introduit un composant coordinateur racine G-DEVS distribué, incluant un algorithme de communication avec le RTI HLA basé sur le mécanisme de synchronisation conservative et utilisant un Lookahead positif. Nous avons ensuite proposé deux algorithmes originaux pour le calcul d'un Loo-kahead relatif à l'état courant d'un modèle G-DEVS. Ces algorithmes, basés sur l'analyse du domaine de varia-tion de la fonction « durée de vie » du modèle, augmentent les performances de la simulation distribuée comme l'illustrent les expériences menées.<br />Basé sur ces approches, nous avons développé un environnement de M&S distribué G-DEVS / HLA. Cet environnement a été intégré à une application de Workflow. Les possibilités offertes par l'environnement ont été illustrées par l'étude de cas réels d'entreprises.

This thesis investigates decision-making in two-player imperfect information games against opponents whose actions can affect our rewards, and whose strategies may be based on memories of interaction, or may be changing, or both. The focus is on modelling these dynamic opponents, and using the models to learn high-reward strategies. The main contributions of this work are: 1. An approach to learn high-reward strategies in small simultaneous-move games against these opponents. This is done by using a model of the opponent learnt from sequence prediction, with (possibly discounted) rewards learnt from reinforcement learning, to lookahead using explicit tree search. Empirical results show that this gains higher average rewards per game than state-of-the-art reinforcement learning agents in three simultaneous-move games. They also show that several sequence prediction methods model these opponents effectively, supporting the idea of using them from areas such as data compression and string matching; 2. An online expectation-maximisation algorithm that infers an agent's hidden information based on its behaviour in imperfect information games; 3. An approach to learn high-reward strategies in medium-size sequential-move poker games against these opponents. This is done by using a model of the opponent learnt from sequence prediction, which needs its hidden information (inferred by the online expectation-maximisation algorithm), to train a state-of-the-art no-regret learning algorithm by simulating games between the algorithm and the model. Empirical results show that this improves the no-regret learning algorithm's rewards when playing against popular and state-of-the-art algorithms in two simplified poker games; 4. Demonstrating that several change detection methods can effectively model changing categorical distributions with experimental results comparing their accuracies to empirical distributions. These results also show that their models can be used to outperform state-of-the-art reinforcement learning agents in two simultaneous-move games. This supports the idea of modelling changing opponent strategies with change detection methods; 5. Experimental results for the self-play convergence to mixed strategy Nash equilibria of the empirical distributions of plays of sequence prediction and change detection methods. The results show that they converge faster, and in more cases for change detection, than fictitious play.

La filosofía Lean Construction (LC) o la construcción sin pérdida se da en la década de 1990, siendo este una adaptación del modelo automovilístico del Toyota Production System o Lean Production a la industria de la construcción, la introducción o el nuevo enfoque de la gestión de proyectos de construcción fue propuesta por el profesor Lauri Koskela, donde nos dice que veamos a la producción en la construcción como un proceso de transformación, de flujo y generador de valor, en consecuencia el objetivo de LC es crear buenos sistemas de producción que permitan optimizar, reducir o eliminar los flujos para mejorar los tiempos de entrega. El sector construcción uno de los más importantes gestores de la economía del país por su participación del PBI necesita la aplicación de metodologías en la gestión de proyectos como LC para generar valor sin pérdidas, sin embargo, su aplicación o su correcta aplicación es reducida, resultando con indicadores óptimos para un grupo selecto de empresas de construcción. En este trabajo de investigación se va a proponer la aplicación de la filosofía Lean Construction como herramienta para la planificación, ejecución y control para la construcción de una estación subterránea de pasajeros para la Línea 2 del Metro de Lima y Callao, vamos a detallar los conceptos y herramientas del LC que, nos sirvan como base para su aplicación y desarrollo para el cumplimiento de los objetivos del proyecto. Así también, se determinará la secuencia, división y sectorización de trabajo para la elaboración del plan de trabajo, se identificarán las actividades que no agregan valor o no productivas, atacando así las perdidas más visibles, reduciendo los ciclos y proponiendo actividades en paralelo. Aplicaremos las teorías Last Planner, Lookahead y Week Planning para el control del proyecto a fin de evaluar restricciones y determinar los que podemos hacer en la planificación diaria, con lo cual buscamos generar una guía para la ejecución del resto de estaciones que comprenden el proyecto. Finalmente se analizará los resultados del proyecto mediante herramientas de medición como el PAC (Porcentaje de Actividades Cumplidas), TC (trabajos contributorios) y otros para las conclusiones y recomendaciones para futuras estaciones aplicando la mejora continua. / The Lean Construction (LC) philosophy or construction without loss occurred in the 1990s, this being an adaptation of the automotive model of Lean Production to the construction industry, the introduction or the new approach to construction project management It was proposed by Professor Lauri Koskela, where he tells us to see production in construction as a process of transformation, flow and value generator, therefore the objective of LC is to create good production systems that allow optimizing, reducing or eliminate flows to improve delivery times. The construction sector, one of the most important managers of the country's economy due to its participation in GDP, needs the application of project management methodologies such as LC to generate value without losses, however its application or its correct application is reduced, resulting in Optimal indicators for a select group of construction companies. In this thesis, the application of the Lean Construction philosophy will be proposed as a tool for planning, executing and controlling the construction of an underground passenger station for Line 2 of the Lima and Callao Metro, we will detail the concepts and tools of the LC that serve as a basis for its application and development for the fulfillment of the project's objectives. Also, the sequence, division and sectorization of work for the preparation of the work plan will be determined, activities that do not add value or are not productive will be identified, thus attacking the most visible losses, reducing cycles and proposing activities in parallel. We will apply Last Planner, Lookahead and Week Planning theories for project control in order to evaluate restrictions and determine what we can do in daily planning, with which we seek to generate a guide for the execution of the rest of the stations that comprise the project. Finally, the results of the project will be analyzed using measurement tools such as the PAC (Percentage of Completed Activities), TC (contributory works) and others for the conclusions and recommendations for future stations applying continuous improvement. / Tesis