Does corruption inhibit foreign direct investment?

Globalization creates new opportunities for firms to invest abroad and many economies are making active efforts to attract Foreign Direct Investment (FDI) in order to promote economic growth. Decisions to invest abroad depend on a complex set of factors, but the least corrupt countries may attract more foreign direct investment because they provide a more favorable climate for investors. In this paper we investigate the impact of corruption on FDI inflows in 73 countries, over the period 1998-2008. Our results suggest that countries where corruption is lower, the FDI inflows are greater, and so controlling corruption may be an important strategy for increase FDI inflows.

System Level Simulation and Radio Resource Management for Distributed Antenna Systems with Cognitive Radio and Multi-Cell Cooperation

4th International Conference on Future Generation Communication Technologies (FGCT 2015), Luton, United Kingdom.

RoutesMobilityModel: easy realistic mobility simulation using external information services

Workshop on ns-3 (WNS '15). 13, May, 2015. Castelldefels, Spain.

A learning environment for robotic production line simulation

This paper presents a framework for a robotic production line simulation learning environment using Autonomous Ground Vehicles (AGV). An eLearning platform is used as interface with the simulator. The objective is to introduce students to the production robotics area using a familiar tool, an eLearning platform, and a framework that simulates a production line using AGVs. This framework allows students to learn about robotics but also about several areas of industrial management engineering without requiring an extensive prior knowledge on the robotics area. The robotic production line simulation learning environment simulates a production environment using AGVs to transport materials to and from the production line. The simulator allows students to validate the AGV dynamics and provides information about the whole materials supplying system which includes: supply times, route optimization and inventory management. The students are required to address several topics such as: sensors, actuators, controllers and an high level management and optimization software. This simulator was developed with a known open source tool from robotics community: Player/Stage. This tool was extended with several add-ons so that students can be able to interact with a complex simulation environment. These add-ons include an abstraction communication layer that performs events provided by the database server which is programmed by the students. An eLearning platform is used as interface between the students and the simulator. The students can visualize the effects of their instructions/programming in the simulator that they can access via the eLearning platform. The proposed framework aims to allow students from different backgrounds to fully experience robotics in practice by suppressing the huge gap between theory and practice that exists in robotics. Using an eLearning platform eliminates installation problems that can occur from different computers software distribution and makes the simulator accessible by all students at school and at home.

Improved Numerical Simulation for a Novel Adaptive Control Using Fractional Order Derivatives

A novel control technique is investigated in the adaptive control of a typical paradigm, an approximately and partially modeled cart plus double pendulum system. In contrast to the traditional approaches that try to build up ”complete” and ”permanent” system models it develops ”temporal” and ”partial” ones that are valid only in the actual dynamic environment of the system, that is only within some ”spatio-temporal vicinity” of the actual observations. This technique was investigated for various physical systems via ”preliminary” simulations integrating by the simplest 1st order finite element approach for the time domain. In 2004 INRIA issued its SCILAB 3.0 and its improved numerical simulation tool ”Scicos” making it possible to generate ”professional”, ”convenient”, and accurate simulations. The basic principles of the adaptive control, the typical tools available in Scicos, and others developed by the authors, as well as the improved simulation results and conclusions are presented in the contribution.

Teaching accounting and management through business simulation

Everyday accounting and management teachers face the challenge of creating learning environments that motivate students. This chapter describes the Business Simulation (BS) experience that has taken place at the Polytechnic Institute of Porto, Institute of Accounting and Administration (IPP/ISCAP). The chapter presents students’ perceptions about the course and the teaching/learning approach. The results show that pedagogical methods used (competency-oriented), generic competencies (cooperation and group work), and interpersonal skills (organisational and communication skills) are relevant for future accounting professionals. In addition, positive remarks and possible constraints based on observation, staff meetings, and past research are reported. The chapter concludes with some recommendations from the project implementation

Simulation Environment for Multi-Robot Cooperative 3D Target Perception

4th International Conference, SIMPAR 2014, Bergamo, Italy, October 20-23, 2014

Revalorization of spent coffee residues by a direct agronomic approach

Spent coffee grounds (SCG) represent a high-volume food waste worldwide, and several reuse approaches have been attempted. Herein, a greenhouse field experiment was carried out by cultivating Batavia lettuce with 5%, 10%, 15%, 20% and 30% (v/v) espresso SCG directly composted in the soil. Healthy vegetables were obtained for all treatments, without yield loss for up to 10% SCG. A progressive increment of green color intensity with increasing SCG content was observed, corroborated by the increase of their photosynthetic pigments (chlorophylls and carotenoids). Furthermore, total ascorbic acid and tocopherols showed statistical significant increases (p < 0.001) between control and all tested groups. Marked variations of nutritionally relevant minerals, particularly potassium, phosphorous and sodium were also revealed at higher percentage treatments (20% and 30%). This approach constitutes a clean, direct, simple and cost-effective measure to produce value-added vegetables, while reducing food waste disposal.

Separating sequential equilibrium in a Bayesian international duopoly

We consider two Cournot firms, one located in the home country and the other in the foreign country, producing substitute goods for consumption in a third country. We suppose that neither the home government nor the foreign firm know the costs of the home firm, while the foreign firm cost is common knowledge. We determine the separating sequential equilibrium outputs.

Comparison of direct immunofluorescence, conventional cell culture and polymerase chain reaction techniques for detecting respiratory syncytial virus in nasopharyngeal aspirates from infants

A total of 316 samples of nasopharyngeal aspirate from infants up to two years of age with acute respiratory-tract illnesses were processed for detection of respiratory syncytial virus (RSV) using three different techniques: viral isolation, direct immunofluorescence, and PCR. Of the samples, 36 (11.4%) were positive for RSV, considering the three techniques. PCR was the most sensitive technique, providing positive findings in 35/316 (11.1%) of the samples, followed by direct immunofluorescence (25/316, 7.9%) and viral isolation (20/315, 6.3%) (p < 0.001). A sample was positive by immunofluorescence and negative by PCR, and 11 (31.4%) were positive only by RT-PCR. We conclude that RT-PCR is more sensitive than IF and viral isolation to detect RSV in nasopharyngeal aspirate specimens in newborn and infants.

Negotiation context analysis in electricity markets

Contextualization is critical in every decision making process. Adequate responses to problems depend not only on the variables with direct influence on the outcomes, but also on a correct contextualization of the problem regarding the surrounding environment. Electricity markets are dynamic environments with increasing complexity, potentiated by the last decades' restructuring process. Dealing with the growing complexity and competitiveness in this sector brought the need for using decision support tools. A solid example is MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), whose players' decisions are supported by another multiagent system – ALBidS (Adaptive Learning strategic Bidding System). ALBidS uses artificial intelligence techniques to endow market players with adaptive learning capabilities that allow them to achieve the best possible results in market negotiations. This paper studies the influence of context awareness in the decision making process of agents acting in electricity markets. A context analysis mechanism is proposed, considering important characteristics of each negotiation period, so that negotiating agents can adapt their acting strategies to different contexts. The main conclusion is that context-dependant responses improve the decision making process. Suiting actions to different contexts allows adapting the behaviour of negotiating entities to different circumstances, resulting in profitable outcomes.

Multi-agent simulation of competitive electricity markets: Autonomous systems cooperation for European market modeling

The electricity market restructuring, and its worldwide evolution into regional and even continental scales, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in a rising complexity in power systems operation. Several power system simulators have been developed in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex and constantly changing environment. The main contribution of this paper is given by the integration of several electricity market and power system models, respecting to the reality of different countries. This integration is done through the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The continuous development of Multi-Agent System for Competitive Electricity Markets platform provides the means for the exemplification of the usefulness of this ontology. A case study using the proposed multi-agent platform is presented, considering a scenario based on real data that simulates the European Electricity Market environment, and comparing its performance using different market mechanisms. The main goal is to demonstrate the advantages that the integration of various market models and simulation platforms have for the study of the electricity markets’ evolution.