An interactive learning approach to accounting classes

This working paper explores the use of interactive learning tools, such as business simulations, to facilitate the active learning process in accounting classes. Although business simulations were firstly introduced in the United States in the 1950s, the vast majority of accounting professors still use traditional teaching methods, based in end-of-chapter exercises and written cases. Moreover, the current students’ generation brings new challenges to the classroom related with their video, game, internet and mobile culture. Thus, a survey and an experimentation were conducted to understand, on one hand, if accounting professors are willing to adjust their teaching methods with the adoption of interactive learning tools and, on the other hand, if the adoption of interactive learning tools in accounting classes yield better academic results and levels of satisfaction among students. Students using more interactive learning approaches scored significantly higher means than others that did not. Accounting professors are clearly willing to try, at least once, the use of an accounting simulator in classes.

Autourheilusimulaattoreiden fysiikkamallinnuksen erot tuotekehityssimulaattoreihin

Kandidaatintyössä käsitellään ajoneuvosimulaattoreita pelien ja tuotekehityksen maailmasta. Tarkoituksena on selvittää lähinnä kirjallisuuskatsauksena, minkälaisia fysiikkamalleja simulaatiopeleissä käytetään ja miten ne eroavat tuotekehityksessä käytettävistä ajoneuvosimulaatiomalleista. Pelisimulaattorin tärkein tavoite on realistinen tuntuma. Lisäksi etuja ovat pelaajaa koukuttava haaste ja viihde. Tuotekehityssimulaattorissa tärkein tavoite taas on hyödyntämiskelpoinen tulos. Näkyvin ero on visualisoinnissa, mutta mallinnettavat ilmiöt sekä tapa mallintaa niitä eroavat myös monilta osin.

Höyryjärjestelmän pelisimulaattorikonsepti

Tässä diplomityössä on suunniteltu konsepti myöhemmin toteutettavaa pelisimulaat-toria varten. Pelisimulaattorista tulee osa öljynjalostamon tuotanto-operaattoreiden höyryjärjestelmän koulutusmoduulia. Työssä höyryjärjestelmän simulaattoriin on laadittu selkeä malli ja rakenne, joka arvioi käyttäjän suoritusta sekä antaa palautteen suorituksen onnistumisesta. Höyryjärjestelmän toiminnan ymmärtäminen on tärkeää, sillä sen avulla höyryntuotantoa voidaan optimoida. Kirjallisuusosassa on käsitelty koulutussimulaattoreita sekä niiden käyttökohteita. Lisäksi on esitetty höyryntuottajat sekä höyrynkuluttajat, jotka huomioitiin pelisimu-laattorikonseptissa. Jokaiselle yksikköprosessille on laadittu toimintakuvaus ja ope-rointiohjeet, joiden perusteella pelaaja saa käsityksen simulaattorin toimintaperiaat-teesta. Soveltavassa osassa on käsitelty kaikkien konseptissa mallinnettujen laitteiden aine- ja energiataseet sekä muut laskennassa tarvittavat teknilliset korrelaatiot. Soveltavas-sa osassa esitettiin myös pelisimulaattorin arviointiperusteet, arviointiin tarvittavien kustannusten korrelaatiot, häiriötilanne sekä esimerkkisimulointi ja suoritusesimerkki häiriön korjaamiseksi. Pelisuorituksen arvioinnin suunnitteluun kiinnitettiin huomiota, jolloin pelisimulaat-tori vastaa mahdollisimman hyvin todellista prosessia sekä säilyttää motivaation si-mulaattoriharjoitteluun.

Interações orais em língua inglesa no laboratório de multimídia com acesso à Internet

Pós-graduação em Estudos Linguísticos - IBILCE

Strategic bidding in electricity markets: an agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Investment focused strategies in electricity markets using the ITEM-game simulator

This paper presents a methodology to establish investment and trading strategies of a power generation company. These strategies are integrated in the ITEM-Game simulator in order to test their results when played against defined strategies used by other players. The developed strategies are focused on investment decisions, although trading strategies are also implemented to obtain base case results. Two cases are studied considering three players with the same trading strategy. In case 1, all players also have the same investment strategy driven by a market target share. In case 2, player 1 has an improved investment strategy with a target share twice of the target of players 2 and 3. Results put in evidence the influence of the CO2 and fuel prices in the company investment decision. It is also observed the influence of the budget constraint which might prevent the player to take the desired investment decision.

Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

MASCEM - an electricity market simulator providing coalition support for virtual power players

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimization techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper details some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study based on real data.

The development of the Virtual Construction Simulator 3: an interactive simulation environment for construction management education

This paper discusses the development of the Virtual Construction Simulator (VCS) 3 - a simulation game-based educational tool for teaching construction schedule planning and management. The VCS3 simulation game engages students in learning the concepts of planning and managing construction schedules through goal driven exploration, employed strategies, and immediate feedback. Through the planning and simulation mode, students learn the difference between the as-planned and as-built schedules resulting from varying factors such as resource availability, weather and labor productivity. This paper focuses on the development of the VCS3 and its construction physics model. Challenges inherent in the process of identifying variables and their relationships to reliably represent and simulate the dynamic nature of planning and managing of construction projects are also addressed.

Game Theoretic Bidding Strategies for Auctions in Green Electricity Markets

Electricity markets in the United States presently employ an auction mechanism to determine the dispatch of power generation units. In this market design, generators submit bid prices to a regulation agency for review, and the regulator conducts an auction selection in such a way that satisfies electricity demand. Most regulators currently use an auction selection method that minimizes total offer costs ["bid cost minimization" (BCM)] to determine electric dispatch. However, recent literature has shown that this method may not minimize consumer payments, and it has been shown that an alternative selection method that directly minimizes total consumer payments ["payment cost minimization" (PCM)] may benefit social welfare in the long term. The objective of this project is to further investigate the long term benefit of PCM implementation and determine whether it can provide lower costs to consumers. The two auction selection methods are expressed as linear constraint programs and are implemented in an optimization software package. Methodology for game theoretic bidding simulation is developed using EMCAS, a real-time market simulator. Results of a 30-day simulation showed that PCM reduced energy costs for consumers by 12%. However, this result will be cross-checked in the future with two other methods of bid simulation as proposed in this paper.

Game Theory Models for Multi-Robot Patrolling of Infraestructures

Abstract This work is focused on the problem of performing multi‐robot patrolling for infrastructure security applications in order to protect a known environment at critical facilities. Thus, given a set of robots and a set of points of interest, the patrolling task consists of constantly visiting these points at irregular time intervals for security purposes. Current existing solutions for these types of applications are predictable and inflexible. Moreover, most of the previous centralized and deterministic solutions and only few efforts have been made to integrate dynamic methods. Therefore, the development of new dynamic and decentralized collaborative approaches in order to solve the aforementioned problem by implementing learning models from Game Theory. The model selected in this work that includes belief‐based and reinforcement models as special cases is called Experience‐Weighted Attraction. The problem has been defined using concepts of Graph Theory to represent the environment in order to work with such Game Theory techniques. Finally, the proposed methods have been evaluated experimentally by using a patrolling simulator. The results obtained have been compared with previous available

Cooperative Multi-robot Patrolling: A study of distributed approaches based on mathematical models of game theory to protect infrastructures

El principio de Teoría de Juegos permite desarrollar modelos estocásticos de patrullaje multi-robot para proteger infraestructuras criticas. La protección de infraestructuras criticas representa un gran reto para los países al rededor del mundo, principalmente después de los ataques terroristas llevados a cabo la década pasada. En este documento el termino infraestructura hace referencia a aeropuertos, plantas nucleares u otros instalaciones. El problema de patrullaje se define como la actividad de patrullar un entorno determinado para monitorear cualquier actividad o sensar algunas variables ambientales. En esta actividad, un grupo de robots debe visitar un conjunto de puntos de interés definidos en un entorno en intervalos de tiempo irregulares con propósitos de seguridad. Los modelos de partullaje multi-robot son utilizados para resolver este problema. Hasta el momento existen trabajos que resuelven este problema utilizando diversos principios matemáticos. Los modelos de patrullaje multi-robot desarrollados en esos trabajos representan un gran avance en este campo de investigación. Sin embargo, los modelos con los mejores resultados no son viables para aplicaciones de seguridad debido a su naturaleza centralizada y determinista. Esta tesis presenta cinco modelos de patrullaje multi-robot distribuidos e impredecibles basados en modelos matemáticos de aprendizaje de Teoría de Juegos. El objetivo del desarrollo de estos modelos está en resolver los inconvenientes presentes en trabajos preliminares. Con esta finalidad, el problema de patrullaje multi-robot se formuló utilizando conceptos de Teoría de Grafos, en la cual se definieron varios juegos en cada vértice de un grafo. Los modelos de patrullaje multi-robot desarrollados en este trabajo de investigación se han validado y comparado con los mejores modelos disponibles en la literatura. Para llevar a cabo tanto la validación como la comparación se ha utilizado un simulador de patrullaje y un grupo de robots reales. Los resultados experimentales muestran que los modelos de patrullaje desarrollados en este trabajo de investigación trabajan mejor que modelos de trabajos previos en el 80% de 150 casos de estudio. Además de esto, estos modelos cuentan con varias características importantes tales como distribución, robustez, escalabilidad y dinamismo. Los avances logrados con este trabajo de investigación dan evidencia del potencial de Teoría de Juegos para desarrollar modelos de patrullaje útiles para proteger infraestructuras. ABSTRACT Game theory principle allows to developing stochastic multi-robot patrolling models to protect critical infrastructures. Critical infrastructures protection is a great concern for countries around the world, mainly due to terrorist attacks in the last decade. In this document, the term infrastructures includes airports, nuclear power plants, and many other facilities. The patrolling problem is defined as the activity of traversing a given environment to monitoring any activity or sensing some environmental variables If this activity were performed by a fleet of robots, they would have to visit some places of interest of an environment at irregular intervals of time for security purposes. This problem is solved using multi-robot patrolling models. To date, literature works have been solved this problem applying various mathematical principles.The multi-robot patrolling models developed in those works represent great advances in this field. However, the models that obtain the best results are unfeasible for security applications due to their centralized and predictable nature. This thesis presents five distributed and unpredictable multi-robot patrolling models based on mathematical learning models derived from Game Theory. These multi-robot patrolling models aim at overcoming the disadvantages of previous work. To this end, the multi-robot patrolling problem was formulated using concepts of Graph Theory to represent the environment. Several normal-form games were defined at each vertex of a graph in this formulation. The multi-robot patrolling models developed in this research work have been validated and compared with best ranked multi-robot patrolling models in the literature. Both validation and comparison were preformed by using both a patrolling simulator and real robots. Experimental results show that the multirobot patrolling models developed in this research work improve previous ones in as many as 80% of 150 cases of study. Moreover, these multi-robot patrolling models rely on several features to highlight in security applications such as distribution, robustness, scalability, and dynamism. The achievements obtained in this research work validate the potential of Game Theory to develop patrolling models to protect infrastructures.

Remediation Of 17-α-ethinylestradiol Aqueous Solution By Photocatalysis And Electrochemically-assisted Photocatalysis Using Tio2 And Tio2/wo3 Electrodes Irradiated By A Solar Simulator.

TiO2 and TiO2/WO3 electrodes, irradiated by a solar simulator in configurations for heterogeneous photocatalysis (HP) and electrochemically-assisted HP (EHP), were used to remediate aqueous solutions containing 10 mg L(-1) (34 μmol L(-1)) of 17-α-ethinylestradiol (EE2), active component of most oral contraceptives. The photocatalysts consisted of 4.5 μm thick porous films of TiO2 and TiO2/WO3 (molar ratio W/Ti of 12%) deposited on transparent electrodes from aqueous suspensions of TiO2 particles and WO3 precursors, followed by thermal treatment at 450 (°)C. First, an energy diagram was organized with photoelectrochemical and UV-Vis absorption spectroscopy data and revealed that EE2 could be directly oxidized by the photogenerated holes at the semiconductor surfaces, considering the relative HOMO level for EE2 and the semiconductor valence band edges. Also, for the irradiated hybrid photocatalyst, electrons in TiO2 should be transferred to WO3 conduction band, while holes move toward TiO2 valence band, improving charge separation. The remediated EE2 solutions were analyzed by fluorescence, HPLC and total organic carbon measurements. As expected from the energy diagram, both photocatalysts promoted the EE2 oxidation in HP configuration; after 4 h, the EE2 concentration decayed to 6.2 mg L(-1) (35% of EE2 removal) with irradiated TiO2 while TiO2/WO3 electrode resulted in 45% EE2 removal. A higher performance was achieved in EHP systems, when a Pt wire was introduced as a counter-electrode and the photoelectrodes were biased at +0.7 V; then, the EE2 removal corresponded to 48 and 54% for the TiO2 and TiO2/WO3, respectively. The hybrid TiO2/WO3, when compared to TiO2 electrode, exhibited enhanced sunlight harvesting and improved separation of photogenerated charge carriers, resulting in higher performance for removing this contaminant of emerging concern from aqueous solution.

As relações de gênero em uma escola de futebol : quando o jogo é possível? = Genders relations at a football school : when the game happen?

Universidade Estadual de Campinas . Faculdade de Educação Física