A influência dos patrocinadores nas estruturas organizacionais de comunidades de software livre

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Economia, Administração e Contabilidade, Programa de Pós-Graduação em Administração, 2016.

Development and Verification of Control and Protection Strategies in Hybrid AC/DC Power Systems for Smart Grid Applications

Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

Hybrid power system intelligent operation and protection involving plug-in electric vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. ^ The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. ^ The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.^

Factors influencig software migration decision: case studies of acerlormittal Tubarão and the city government of Serra, Espirito Santo

The objective of this research is to identify the factors that influence the migration of free software to proprietary software, or vice-versa. The theoretical framework was developed in light of the Diffusion of Innovations Theory (DIT) proposed by Rogers (1976, 1995), and the Unified Theory of Acceptance and Use of Technology (UTAUT) proposed by Venkatesh, Morris, Davis and Davis (2003). The research was structured in two phases: the first phase was exploratory, characterized by adjustments of the revised theory to fit Brazilian reality and the identification of companies that could be the subject of investigation; and the second phase was qualitative, in which case studies were conducted at ArcelorMittal Tubarão (AMT), a private company that migrated from proprietary software (Unix) to free software (Linux), and the city government of Serra, in Espírito Santo state, a public organization that migrated from free software (OpenOffice) to proprietary (MS Office). The results show that software migration decision takes into account factors that go beyond issues involving technical or cost aspects, such as cultural barriers, user rejection and resistance to change. These results underscore the importance of social aspects, which can play a decisive role in the decision regarding software migration and its successful implementation.

Entrepreneurship in project management systems: proposal of a model and preliminary empirical evidence

This study analyzes the manifestation of the dimensions of Entrepreneurial Orientation (EO) and Project Management Systems (PMS). We used a qualitative approach to conduct exploratory research through a study in literature and a pilot case in a software company. Data was collected from semi structured interviews, documents, and records on file, then triangulated and treated with content analysis. The model proposed for the relationship between the types of PMS (ad hoc, Classic PM, innovation, entrepreneurship/intrapreneurship) and the dimensions of EO (innovativeness, risk-taking, proactiveness, competitive aggressiveness, and autonomy), was partially corroborated by empirical studies. New studies are suggested to validate the applicability and setup of the model.

Favorability conditions in the adoption of agile method practices for software development in a public banking

The main purpose of this paper is to propose and test a model to assess the degree of conditions favorability in the adoption of agile methods to develop software where traditional methods predominate. In order to achieve this aim, a survey was applied on software developers of a Brazilian public retail bank. Two different statistical techniques were used in order to assess the quantitative data from the closed questions in the survey. The first, exploratory factorial analysis validated the structure of perspectives related to the agile model of the proposed assessment. The second, frequency distribution analysis to categorize the answers. Qualitative data from the survey opened question were analyzed with the technique of qualitative thematic content analysis. As a result, the paper proposes a model to assess the degree of favorability conditions in the adoption of Agile practices within the context of the proposed study.

OpenDataHub: an open dataset management system

This thesis presents a cloud-based software platform for sharing publicly available scientific datasets. The proposed platform leverages the potential of NoSQL databases and asynchronous IO technologies, such as Node.JS, in order to achieve high performances and flexible solutions. This solution will serve two main groups of users. The dataset providers, which are the researchers responsible for sharing and maintaining datasets, and the dataset users, that are those who desire to access the public data. To the former are given tools to easily publish and maintain large volumes of data, whereas the later are given tools to enable the preview and creation of subsets of the original data through the introduction of filter and aggregation operations. The choice of NoSQL over more traditional RDDMS emerged from and extended benchmark between relational databases (MySQL) and NoSQL (MongoDB) that is also presented in this thesis. The obtained results come to confirm the theoretical guarantees that NoSQL databases are more suitable for the kind of data that our system users will be handling, i. e., non-homogeneous data structures that can grow really fast. It is envisioned that a platform like this can lead the way to a new era of scientific data sharing where researchers are able to easily share and access all kinds of datasets, and even in more advanced scenarios be presented with recommended datasets and already existing research results on top of those recommendations.

Agent based risk patient management

This paper explores the role of information and communication technologies in managing risk and early discharge patients, and suggests innovative actions in the area of E-Health services. Treatments of chronic illnesses, or treatments of special needs such as cardiovascular diseases, are conducted in long-stay hospitals, and in some cases, in the homes of patients with a follow-up from primary care centre. The evolution of this model is following a clear trend: trying to reduce the time and the number of visits by patients to health centres and derive tasks, so far as possible, toward outpatient care. Also the number of Early Discharge Patients (EDP) is growing, thus permiting a saving in the resources of the care center. The adequacy of agent and mobile technologies is assessed in light of the particular requirements of health care applications. A software system architecture is outlined and discussed. The major contributions are: first, the conceptualization of multiple mobile and desktop devices as part of a single distributed computing system where software agents are being executed and interact from their remote locations. Second, the use of distributed decision making in multiagent systems, as a means to integrate remote evidence and knowledge obtained from data that is being collected and/or processed by distributed devices. The system will be applied to patients with cardiovascular or Chronic Obstructive Pulmonary Diseases (COPD) as well as to ambulatory surgery patients. The proposed system will allow to transmit the patient's location and some information about his/her illness to the hospital or care centre

A Microdata Analysis Approach to Transport Infrastructure Maintenance

Maintenance of transport infrastructure assets is widely advocated as the key in minimizing current and future costs of the transportation network. While effective maintenance decisions are often a result of engineering skills and practical knowledge, efficient decisions must also account for the net result over an asset's life-cycle. One essential aspect in the long term perspective of transport infrastructure maintenance is to proactively estimate maintenance needs. In dealing with immediate maintenance actions, support tools that can prioritize potential maintenance candidates are important to obtain an efficient maintenance strategy. This dissertation consists of five individual research papers presenting a microdata analysis approach to transport infrastructure maintenance. Microdata analysis is a multidisciplinary field in which large quantities of data is collected, analyzed, and interpreted to improve decision-making. Increased access to transport infrastructure data enables a deeper understanding of causal effects and a possibility to make predictions of future outcomes. The microdata analysis approach covers the complete process from data collection to actual decisions and is therefore well suited for the task of improving efficiency in transport infrastructure maintenance. Statistical modeling was the selected analysis method in this dissertation and provided solutions to the different problems presented in each of the five papers. In Paper I, a time-to-event model was used to estimate remaining road pavement lifetimes in Sweden. In Paper II, an extension of the model in Paper I assessed the impact of latent variables on road lifetimes; displaying the sections in a road network that are weaker due to e.g. subsoil conditions or undetected heavy traffic. The study in Paper III incorporated a probabilistic parametric distribution as a representation of road lifetimes into an equation for the marginal cost of road wear. Differentiated road wear marginal costs for heavy and light vehicles are an important information basis for decisions regarding vehicle miles traveled (VMT) taxation policies. In Paper IV, a distribution based clustering method was used to distinguish between road segments that are deteriorating and road segments that have a stationary road condition. Within railway networks, temporary speed restrictions are often imposed because of maintenance and must be addressed in order to keep punctuality. The study in Paper V evaluated the empirical effect on running time of speed restrictions on a Norwegian railway line using a generalized linear mixed model.

OpenDataHub: an open dataset management system

This thesis presents a cloud-based software platform for sharing publicly available scientific datasets. The proposed platform leverages the potential of NoSQL databases and asynchronous IO technologies, such as Node.JS, in order to achieve high performances and flexible solutions. This solution will serve two main groups of users. The dataset providers, which are the researchers responsible for sharing and maintaining datasets, and the dataset users, that are those who desire to access the public data. To the former are given tools to easily publish and maintain large volumes of data, whereas the later are given tools to enable the preview and creation of subsets of the original data through the introduction of filter and aggregation operations. The choice of NoSQL over more traditional RDDMS emerged from and extended benchmark between relational databases (MySQL) and NoSQL (MongoDB) that is also presented in this thesis. The obtained results come to confirm the theoretical guarantees that NoSQL databases are more suitable for the kind of data that our system users will be handling, i. e., non-homogeneous data structures that can grow really fast. It is envisioned that a platform like this can lead the way to a new era of scientific data sharing where researchers are able to easily share and access all kinds of datasets, and even in more advanced scenarios be presented with recommended datasets and already existing research results on top of those recommendations.

AgroDB - integration of database management systems with crop models.

2016

Development and Validation of a Model-Based Combustion Controller for Water Injection Management

This manuscript reports the overall development of a Ph.D. research project during the “Mechanics and advanced engineering sciences” course at the Department of Industrial Engineering of the University of Bologna. The project is focused on the development of a combustion control system for an innovative Spark Ignited engine layout. In details, the controller is oriented to manage a prototypal engine equipped with a Port Water Injection system. The water injection technology allows an increment of combustion efficiency due to the knock mitigation effect that permits to keep the combustion phasing closer to the optimal position with respect to the traditional layout. At the beginning of the project, the effects and the possible benefits achievable by water injection have been investigated by a focused experimental campaign. Then the data obtained by combustion analysis have been processed to design a control-oriented combustion model. The model identifies the correlation between Spark Advance, combustion phasing and injected water mass, and two different strategies are presented, both based on an analytic and semi-empirical approach and therefore compatible with a real-time application. The model has been implemented in a combustion controller that manages water injection to reach the best achievable combustion efficiency while keeping knock levels under a pre-established threshold. Three different versions of the algorithm are described in detail. This controller has been designed and pre-calibrated in a software-in-the-loop environment and later an experimental validation has been performed with a rapid control prototyping approach to highlight the performance of the system on real set-up. To further make the strategy implementable on an onboard application, an estimation algorithm of combustion phasing, necessary for the controller, has been developed during the last phase of the PhD Course, based on accelerometric signals.

Facebook per promozione turistica: Sviluppo di una piattaforma software per l'analisi delle recensioni

Sviluppo di una piattaforma software per l'estrazione e l'analisi dei dati dalle pagine Facebook ufficiali del turismo delle regioni italiane, per lo studio dell'andamento delle promozioni turistiche.