Atribuição de turmas para professores via Beam Search em Java

In the universities, before the start of each school year, is held the distribution of classes among available teachers. Therefore, it is necessary to consider the maximum workweek for each teacher and their preferences for each discipline, to prevent a teacher to give lessons in two separate locations at the same time and to avoid some teachers to become overloaded while others with large clearance. This process, manually performed, is time consuming and does not allow the visualization of other combinations of assignment of teachers to classes, besides being liable to error. This work aims to develop a decision support tool for the problem of assigning teachers to classes in college. The project encompasses the development of a computer program using the concepts of object orientation and a tree search algorithm of a combinatorial nature called Beam Search. The programming language used is Java and the program has a graphical interface for entering and manipulating data of the problem. Once obtained the schedule data of classes and teachers is possible, by means of the tool, perform various simulations and manual adjustments to achieve the final result. It is an efficient method of class scheduling, considering the speed of task execution and the fact that it generates only feasible results

Simulações de onda de cheia na sub-bacia do Ribeirão Claro - SP

Watersheds are considered important study units when it comes to environmental planning, with regard to the optimal use of water resources. Water scarcity is predicted and feared by many societies, and proves to be an increasingly tangible problem nowadays. Still from the perspective of extreme events, this dissertation considers the study of flood waves in the sub-basin of the stream Claro, which belongs to the Corumbataí watershed. - SP, since thay can also have devastating effects for the population, A Decision Support System for Flood Routing Analysis in Complex Basins, ABC 6 software was applied in order to obtain hydrographs and peak flows in the sub-basin of the stream Claro, for return periods of 10 and 100 years, aiming to comprise events of different magnitudes. The model Soil Conservation Service (SCS) and the triangular SCS hydrograph were adopted for the simulations. Simultaneously, the Kokei Uehara method was applied for the obtainment of peak flow values under the same conditions, seeking to compare results. Data collection was performed using geoprocessing tools. For data entry in ABC 6, the fragmentation of sub-basin of the stream Claro was necessary, which generated 7 small watersheds, in order to fulfill a software demand, as the maximum drainage area it accepts is 50km² for each watershed analyzed. For RT = 10 and 100 years, respectively, the results of peak flow with use of ABC 6 were 46.10 and 95.45 m³/s, while for Kokei Uehara method, the results were 47.17 and 65.26 m³/s. The adoption of a single value of discretization time for all watersheds was indicated as limitation of ABC 6, which interfered in the final results. Kokei method Uehara considered the sub-basin of the stream Claro as a whole, which reduced the error accumulation probability

Use of computer algebra in the calculation of Feynman diagrams

The increasing precision of current and future experiments in high-energy physics requires a likewise increase in the accuracy of the calculation of theoretical predictions, in order to find evidence for possible deviations of the generally accepted Standard Model of elementary particles and interactions. Calculating the experimentally measurable cross sections of scattering and decay processes to a higher accuracy directly translates into including higher order radiative corrections in the calculation. The large number of particles and interactions in the full Standard Model results in an exponentially growing number of Feynman diagrams contributing to any given process in higher orders. Additionally, the appearance of multiple independent mass scales makes even the calculation of single diagrams non-trivial. For over two decades now, the only way to cope with these issues has been to rely on the assistance of computers. The aim of the xloops project is to provide the necessary tools to automate the calculation procedures as far as possible, including the generation of the contributing diagrams and the evaluation of the resulting Feynman integrals. The latter is based on the techniques developed in Mainz for solving one- and two-loop diagrams in a general and systematic way using parallel/orthogonal space methods. These techniques involve a considerable amount of symbolic computations. During the development of xloops it was found that conventional computer algebra systems were not a suitable implementation environment. For this reason, a new system called GiNaC has been created, which allows the development of large-scale symbolic applications in an object-oriented fashion within the C++ programming language. This system, which is now also in use for other projects besides xloops, is the main focus of this thesis. The implementation of GiNaC as a C++ library sets it apart from other algebraic systems. Our results prove that a highly efficient symbolic manipulator can be designed in an object-oriented way, and that having a very fine granularity of objects is also feasible. The xloops-related parts of this work consist of a new implementation, based on GiNaC, of functions for calculating one-loop Feynman integrals that already existed in the original xloops program, as well as the addition of supplementary modules belonging to the interface between the library of integral functions and the diagram generator.

Landwirtschaftliche Schaderregerprognose mit Hilfe von geographischen Informationssystemen

In der hier vorliegenden Arbeit wurde am Beispiel der Kraut- und Knollenfäule an Kartoffeln Phytophthora infestans und des Kartoffelkäfers Leptinotarsa decemlineata untersucht, ob durch den Einsatz von Geographischen Informationssystemen (GIS) landwirtschaftliche Schader¬reger¬prognosen für jeden beliebigen Kartoffelschlag in Deutschland erstellt werden können. Um dieses Ziel zu erreichen, wurden die Eingangsparameter (Temperatur und relative Luftfeuchte) der Prognosemodelle für die beiden Schaderreger (SIMLEP1, SIMPHYT1, SIMPHYT3 and SIMBLIGHT1) so aufbereitet, dass Wetterdaten flächendeckend für Deutschland zur Verfügung standen. Bevor jedoch interpoliert werden konnte, wurde eine Regionalisierung von Deutschland in Interpolationszonen durchgeführt und somit Naturräume geschaffen, die einen Vergleich und eine Bewertung der in ihnen liegenden Wetterstationen zulassen. Hierzu wurden die Boden-Klima-Regionen von SCHULZKE und KAULE (2000) modifiziert, an das Wetterstationsnetz angepasst und mit 5 bis 10 km breiten Pufferzonen an der Grenze der Interpolationszonen versehen, um die Wetterstationen so häufig wie möglich verwenden zu können. Für die Interpolation der Wetterdaten wurde das Verfahren der multiplen Regression gewählt, weil dieses im Vergleich zu anderen Verfahren die geringsten Abweichungen zwischen interpolierten und gemessenen Daten aufwies und den technischen Anforderungen am besten entsprach. Für 99 % aller Werte konnten bei der Temperaturberechnung Abweichungen in einem Bereich zwischen -2,5 und 2,5 °C erzielt werden. Bei der Berechnung der relativen Luftfeuchte wurden Abweichungen zwischen -12 und 10 % relativer Luftfeuchte erreicht. Die Mittelwerte der Abweichungen lagen bei der Temperatur bei 0,1 °C und bei der relativen Luftfeuchte bei -1,8 %. Zur Überprüfung der Trefferquoten der Modelle beim Betrieb mit interpolierten Wetterdaten wurden Felderhebungsdaten aus den Jahren 2000 bis 2007 zum Erstauftreten der Kraut- und Knollenfäule sowie des Kartoffelkäfers verwendet. Dabei konnten mit interpolierten Wetterdaten die gleichen und auch höhere Trefferquoten erreicht werden, als mit der bisherigen Berechnungsmethode. Beispielsweise erzielte die Berechnung des Erstauftretens von P. infestans durch das Modell SIMBLIGHT1 mit interpolierten Wetterdaten im Schnitt drei Tage geringere Abweichungen im Vergleich zu den Berechnungen ohne GIS. Um die Auswirkungen interpretieren zu können, die durch Abweichungen der Temperatur und der relativen Luftfeuchte entstanden wurde zusätzlich eine Sensitivitätsanalyse zur Temperatur und relativen Luftfeuchte der verwendeten Prognosemodelle durchgeführt. Die Temperatur hatte bei allen Modellen nur einen geringen Einfluss auf das Prognoseergebnis. Veränderungen der relativen Luftfeuchte haben sich dagegen deutlich stärker ausgewirkt. So lag bei SIMBLIGHT1 die Abweichung durch eine stündliche Veränderung der relativen Luftfeuchte (± 6 %) bei maximal 27 Tagen, wogegen stündliche Veränderungen der Temperatur (± 2 °C) eine Abweichung von maximal 10 Tagen ausmachten. Die Ergebnisse dieser Arbeit zeigen, dass durch die Verwendung von GIS mindestens die gleichen und auch höhere Trefferquoten bei Schaderregerprognosen erzielt werden als mit der bisherigen Verwendung von Daten einer nahegelegenen Wetterstation. Die Ergebnisse stellen einen wesentlichen Fortschritt für die landwirtschaftlichen Schaderregerprognosen dar. Erstmals ist es möglich, bundesweite Prognosen für jeden beliebigen Kartoffelschlag zur Bekämpfung von Schädlingen in der Landwirtschaft bereit zu stellen.

Utilizzo delle bande dell’Infrarosso Termico in tecniche di remote sensing per applicazioni in ambito urbano

Il presente studio si concentra sulle diverse applicazioni del telerilevamento termico in ambito urbano. Vengono inizialmente descritti la radiazione infrarossa e le sue interazioni con l’atmosfera terrestre, le leggi principali che regolano lo scambio di calore per irraggiamento, le caratteristiche dei sensori e le diverse applicazioni di termografia. Successivamente sono trattati nel dettaglio gli aspetti caratteristici della termografia da piattaforma satellitare, finalizzata principalmente alla valutazione del fenomeno dell'Urban Heat Island; vengono descritti i sensori disponibili, le metodologie di correzione per gli effetti atmosferici, per la stima dell'emissività delle superfici e per il calcolo della temperatura superficiale dei pixels. Viene quindi illustrata la sperimentazione effettuata sull'area di Bologna mediante immagini multispettrali ASTER: i risultati mostrano come sull'area urbana sia riscontrabile la presenza dell'Isola di Calore Urbano, anche se la sua quantificazione risulta complessa. Si procede quindi alla descrizione di potenzialità e limiti della termografia aerea, dei suoi diversi utilizzi, delle modalità operative di rilievo e degli algoritmi utilizzati per il calcolo della temperatura superficiale delle coperture edilizie. Tramite l’analisi di alcune esperienze precedenti vengono trattati l’influenza dell’atmosfera, la modellazione dei suoi effetti sulla radianza rilevata, i diversi metodi per la stima dell’emissività. Viene quindi introdotto il progetto europeo Energycity, finalizzato alla creazione di un sistema GeoWeb di supporto spaziale alle decisioni per la riduzione di consumi energetici e produzione di gas serra su sette città dell'Europa Centrale. Vengono illustrate le modalità di rilievo e le attività di processing dei datasets digitali per la creazione di mappe di temperatura superficiale da implementare nel sistema SDSS. Viene infine descritta la sperimentazione effettuata sulle immagini termiche acquisite nel febbraio 2010 sulla città di Treviso, trasformate in un mosaico georiferito di temperatura radiometrica tramite correzioni geometriche e radiometriche; a seguito della correzione per l’emissività quest’ultimo verrà trasformato in un mosaico di temperatura superficiale.

Operational research applied to regional healthcare system

In this thesis we focus on optimization and simulation techniques applied to solve strategic, tactical and operational problems rising in the healthcare sector. At first we present three applications to Emilia-Romagna Public Health System (SSR) developed in collaboration with Agenzia Sanitaria e Sociale dell'Emilia-Romagna (ASSR), a regional center for innovation and improvement in health. Agenzia launched a strategic campaign aimed at introducing Operations Research techniques as decision making tools to support technological and organizational innovations. The three applications focus on forecast and fund allocation of medical specialty positions, breast screening program extension and operating theater planning. The case studies exploit the potential of combinatorial optimization, discrete event simulation and system dynamics techniques to solve resource constrained problem arising within Emilia-Romagna territory. We then present an application in collaboration with Dipartimento di Epidemiologia del Lazio that focuses on population demand of service allocation to regional emergency departments. Finally, a simulation-optimization approach, developed in collaboration with INESC TECH center of Porto, to evaluate matching policies for the kidney exchange problem is discussed.

Sviluppo di metodologie innovative di supporto decisionale alla progettazione basate su indicatori di prestazione

Il progetto di ricerca è finalizzato allo sviluppo di una metodologia innovativa di supporto decisionale nel processo di selezione tra alternative progettuali, basata su indicatori di prestazione. In particolare il lavoro si è focalizzato sulla definizione d’indicatori atti a supportare la decisione negli interventi di sbottigliamento di un impianto di processo. Sono stati sviluppati due indicatori, “bottleneck indicators”, che permettono di valutare la reale necessità dello sbottigliamento, individuando le cause che impediscono la produzione e lo sfruttamento delle apparecchiature. Questi sono stati validati attraverso l’applicazione all’analisi di un intervento su un impianto esistente e verificando che lo sfruttamento delle apparecchiature fosse correttamente individuato. Definita la necessità dell’intervento di sbottigliamento, è stato affrontato il problema della selezione tra alternative di processo possibili per realizzarlo. È stato applicato alla scelta un metodo basato su indicatori di sostenibilità che consente di confrontare le alternative considerando non solo il ritorno economico degli investimenti ma anche gli impatti su ambiente e sicurezza, e che è stato ulteriormente sviluppato in questa tesi. Sono stati definiti due indicatori, “area hazard indicators”, relativi alle emissioni fuggitive, per integrare questi aspetti nell’analisi della sostenibilità delle alternative. Per migliorare l’accuratezza nella quantificazione degli impatti è stato sviluppato un nuovo modello previsionale atto alla stima delle emissioni fuggitive di un impianto, basato unicamente sui dati disponibili in fase progettuale, che tiene conto delle tipologie di sorgenti emettitrici, dei loro meccanismi di perdita e della manutenzione. Validato mediante il confronto con dati sperimentali di un impianto produttivo, si è dimostrato che tale metodo è indispensabile per un corretto confronto delle alternative poiché i modelli esistenti sovrastimano eccessivamente le emissioni reali. Infine applicando gli indicatori ad un impianto esistente si è dimostrato che sono fondamentali per semplificare il processo decisionale, fornendo chiare e precise indicazioni impiegando un numero limitato di informazioni per ricavarle.

Internazionalizzazione e traduzione: Un'esperienza presso l'azienda TR Turoni S.R.L.

This dissertation was conducted within the project Language Toolkit, which has the aim of integrating the worlds of work and university. In particular, it consists of the translation into English of documents commissioned by the Italian company TR Turoni and its primary purpose is to demonstrate that, in the field of translation for companies, the existing translation support tools and software can optimise and facilitate the translation process. The work consists of five chapters. The first introduces the Language Toolkit project, the TR Turoni company and its relationship with the CERMAC export consortium. After outlining the current state of company internationalisation, the importance of professional translators in enhancing the competitiveness of companies that enter new international markets is highlighted. Chapter two provides an overview of the texts to be translated, focusing on the textual function and typology and on the addressees. After that, manual translation and the main software developed specifically for translators are described, with a focus on computer-assisted translation (CAT) and machine translation (MT). The third chapter presents the target texts and the corresponding translations. Chapter four is dedicated to the analysis of the translation process. The first two texts were translated manually, with the support of a purpose-built specialized corpus. The following two documents were translated with the software SDL Trados Studio 2011 and its applications. The last texts were submitted to the Google Translate service and to a process of pre and post-editing. Finally, in chapter five conclusions are drawn about the main limits and potentialities of the different translations techniques. In addition to this, the importance of an integrated use of all available instruments is underlined.

Transmission dynamics of Chlamydia trachomatis affect the impact of screening programmes

To assess the impact of screening programmes in reducing the prevalence of Chlamydia trachomatis, mathematical and computational models are used as a guideline for decision support. Unfortunately, large uncertainties exist about the parameters that determine the transmission dynamics of C. trachomatis. Here, we use a SEIRS (susceptible-exposed-infected-recovered-susceptible) model to critically analyze the turnover of C. trachomatis in a population and the impact of a screening programme. We perform a sensitivity analysis on the most important steps during an infection with C. trachomatis. Varying the fraction of the infections becoming symptomatic as well as the duration of the symptomatic period within the range of previously used parameter estimates has little effect on the transmission dynamics. However, uncertainties in the duration of temporary immunity and the asymptomatic period can result in large differences in the predicted impact of a screening programme. We therefore analyze previously published data on the persistence of asymptomatic C. trachomatis infection in women and estimate the mean duration of the asymptomatic period to be longer than anticipated so far, namely 433 days (95% CI: 420-447 days). Our study shows that a longer duration of the asymptomatic period results in a more pronounced impact of a screening programme. However, due to the slower turnover of the infection, a substantial reduction in prevalence can only be achieved after screening for several years or decades.

Randomized trial of a computerized coronary heart disease risk assessment tool in HIV-infected patients receiving combination antiretroviral therapy

Exposure to combination antiretroviral therapy (cART) can lead to important metabolic changes and increased risk of coronary heart disease (CHD). Computerized clinical decision support systems have been advocated to improve the management of patients at risk for CHD but it is unclear whether such systems reduce patients' risk for CHD.

SMARTDIAB: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients

SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.

Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.

Appraising and selecting conservation measures to mitigate desertification and land degradation based on stakeholder participation and global best practices

Most desertification research focuses on degradation assessments without putting sufficient emphasis on prevention and mitigation strategies, although the concept of Sustainable Land Management (SLM) is increasingly being acknowledged. A variety of already applied conservation measures exist at the local level, but they are not adequately recognised, evaluated and shared, either by land users, technicians, researchers, or policy makers. Likewise, collaboration between research and implementation is often insufficient. The aim of this paper is to present a new methodology for a participatory process of appraising and selecting desertification mitigation strategies, and to present first experiences from its application in the EU-funded DESIRE project. The methodology combines a collective learning and decision approach with the use of evaluated global best practices. In three parts, it moves through a concise process, starting with identifying land degradation and locally applied solutions in a stakeholder workshop, leading to assessing local solutions with a standardised evaluation tool, and ending with jointly selecting promising strategies for implementation with the help of a decision support tool. The methodology is currently being applied in 16 study sites. Preliminary analysis from the application of the first part of the methodology shows that the initial stakeholder workshop results in a good basis for stakeholder cooperation, and in promising land conservation practices for further assessment. Study site research teams appreciated the valuable results, as burning issues and promising options emerged from joint reflection. The methodology is suitable to initiate mutual learning among different stakeholder groups and to integrate local and scientific knowledge.

Adaptive Rückmeldungen im intelligenten Tutorensystem LARGO

Das intelligente Tutorensystem LARGO für die Rechtswissenschaften soll Jurastudenten helfen, Argumentationsstrategien zu lernen. Im verwendeten Ansatz werden Gerichtsprotokolle als Lernmaterialien verwendet: Studenten annotieren diese und erstellen graphische Repräsentationen des Argumentationsverlaufs. Das System kann dabei zur Reflexion über die von Anwälten vorgebrachten Argumente anregen und Lernende auf mögliche Schwächen in ihrer Analyse des Disputs hinweisen. Zur Erkennung von Schwächen verwendet das System Graphgrammatiken und kollaborative Filtermechanismen. Dieser Artikel stellt dar, wie in LARGO auf Basis der Bestimmung eines „Benutzungskontextes“ die Rückmeldungen im System benutzungsadaptiv gestaltet werden. Weiterhin diskutieren wir auf Basis der Ergebnisse einer kontrollierten Studie mit dem System, welche mit Jurastudierenden an der University of Pittsburgh stattfand, in wie weit der automatisch bestimmte Benutzungskontext zur Vorhersage von Lernerfolgen bei Studenten verwendbar ist.