Proposta de modelagem de qualidade ambiental em áreas metropolitanas, por meio de dados de sensoriamento remoto

Tese (doutorado)—Universidade de Brasília, Instituto de Geociências, Pós-Graduação em Geociências Aplicadas, 2016.

Market-based sensor relocation by robot team inwireless sensor networks

Randomly scattered sensors may cause sensing holes and redundant sensors. In carrier-based sensor relocation, mobile robots (with limited capacity to carry sensors) pick up additional or redundant sensors and relocate them at sensing holes. In the only known localized algorithm, robots randomly traverse field and act based on identified pair of spare sensor and coverage hole. We propose a Market-based Sensor Relocation (MSR) algorithm, which optimizes sensor deployment location, and introduces bidding and coordinating among neighboring robots. Sensors along the boundary of each hole elect one of them as the representative, which bids to neighboring robots for hole filling service. Each robot randomly explores by applying Least Recently Visited policy. It chooses the best bid according to Cost over Progress ratio and fetches a spare sensor nearby to cover the corresponding sensing hole. Robots within communication range share their tasks to search for better possible solutions. Simulation shows that MSR outperforms the existing competing algorithm G-R3S2 significantly on total robot traversed path and energy, and time to cover holes, slightly on number of sensors needed to cover the hole and number of sensor messages for bidding and deployment location sharing.

Saliency detection using hierarchical manifold learning

Saliency detection is critical to many applications in computer vision by eliminating redundant backgrounds. The saliency detection approaches can be divided into two categories, i.e., top-down and bottom-up. Among them, bottom-up models have attracted more attention due to their simple mechanisms. However, many existing bottom-up models are not robust to crowded backgrounds because of missing salient regions within feedforward frameworks which is often not effective for complex scenes. We tackle these problems by modifying and extending a bottom-up saliency detection model through three phases, (1) constructing a hierarchical sequence of images from the perspective of entropy, (2) estimated mid-level cues are used as feedback information, (3) subsequently generating saliency maps by global context and local uniqueness in a graph-based framework. We also compare the proposed bottom-up model with state-of-the-art approaches on two benchmark datasets to evaluate its saliency detection performance. The experimental results demonstrate that the proposed bottom-up saliency detection approach is not only robust to both cluttered and clean scenes, but also able to obtain objects with different scales.

How the observed create ethical dilemmas for the observers: experiences from studies conducted in clinical settings in the UK and Australia

Observational research has a history of controversy, particularly when the research is conducted in a clinical setting. Existing ethical approval processes focus on protecting participants and the researcher's responsibilities, in particular where vulnerable populations are concerned. In this study, the authors explored the less overt and often understated ethical challenges that can arise when conducting observational research in a clinical setting. Reflecting on two recent studies conducted in different clinical settings, the authors described the challenges of blurring role boundaries, the risk of collecting redundant data, and the impact of reverse power relationships between researchers, clinicians, and managers. From their experiences, the authors suggested that the preparatory work undertaken with clinicians and managers onsite, which typically focuses on how the researchers will maintain the ethical robustness of the research and protect the rights of participants and the vulnerable, should also highlight the sometimes overlooked ethical issues associated with participatory research. This can help ensure that participants and managers understand the scope and limitations of the research, and consider the ways in which the observed can influence the researcher and the findings.

The distinctive common good

This paper defends the traditional distinctive notion of the common good against the claim that it is normatively redundant on the aggregative conception. The first two sections of the paper outline the different candidate conceptions of the common good and the normative role of the common good within natural law theories. The paper then considers some difficulties faced by the instrumental and aggregative conceptions, before developing an Aristotelian account of the distinctive conception of the common good and demonstrating its normative significance for a natural law account of political and legal authority.

Mathematical modelling of linear motion error for Hexarot parallel manipulators

Hexarot is a robotic manipulator that belongs to the family of axis symmetric parallel mechanisms. The robot is able to move the robot platform or tool center point in six degrees of freedom (DOF). This paper presents the kinematics model of the robot including the inverse and forward kinematics, and its time derivatives. Then using the kinematics formulations, investigation of the nonlinear motion of the Hexarot robot for a desired linear motion path is performed. For this purpose, the concept of curvature of the robot path is used for measuring the nonlinearity of the actual motion of the robot. The nonlinear motion error of the robot is analyzed for the scenario where the platform moves on a linear path between two arbitrary points of the robot workspace. The effects of different parameters on the nonlinear motion error of the mechanism are demonstrated and strategies for motions with low error values are proposed.

Big data storage security

The demand for data storage and processing is increasing at a rapid speed in the big data era. The management of such tremendous volume of data is a critical challenge to the data storage systems. Firstly, since 60% of the stored data is claimed to be redundant, data deduplication technology becomes an attractive solution to save storage space and traffic in a big data environment. Secondly, the security issues, such as confidentiality, integrity and privacy of the big data should also be considered for big data storage. To address these problems, convergent encryption is widely used to secure data deduplication for big data storage. Nonetheless, there still exist some other security issues, such as proof of ownership, key management and so on. In this chapter, we first introduce some major cyber attacks for big data storage. Then, we describe the existing fundamental security techniques, whose integration is essential for preventing data from existing and future security attacks. By discussing some interesting open problems, we finally expect to trigger more research efforts in this new research field.

Can Intersensory Redundancy and Social Contingency Enhance Memory in Bobwhite Quail Hatchlings?

Recent findings indicate that bimodal-redundant stimulation promotes perceptual learning and recruits attention to amodal properties in non-human as well as human infants. However it is not clear if bimodal-redundant stimulation can also facilitate memory during the postnatal period. Moreover, most animal and human studies have employed an operant paradigm to study memory, but have not compared the effectiveness of contingent versus passive presentation of information on memory. The current study investigated the role of unimodal versus bimodal presentation and, the role of a contingent versus passive exposure in memory retention in the bobwhite quail (Colinus virginianus). Results revealed that contingently trained chicks demonstrated a preference for the familiarized call under both unimodal and bimodal conditions. Between-group analyses revealed that the contingent-bimodal group preferred the familiarized call as compared to the passive-bimodal group. These results indicate that the contingency paradigm accompanied with the bimodal stimulus type facilitated memory during early development.

Essays on competition in the pharmaceutical industry

Chapter 1: Patents and Entry Competition in the Pharmaceutical Industry: The Role of Marketing Exclusivity. Effective patent length for innovation drugs is severely curtailed because of extensive efficacy and safety tests required for FDA approval, raising concern over adequacy of incentives for new drug development. The Hatch-Waxman Act extends patent length for new drugs by five years, but also promotes generic entry by simplifying approval procedures and granting 180-day marketing exclusivity to a first generic entrant before the patent expires. In this paper we present a dynamic model to examine the effect of marketing exclusivity. We find that marketing exclusivity may be redundant and its removal may increase generic firms' profits and social welfare. ^ Chapter 2: Why Authorized Generics?: Theoretical and Empirical Investigations Facing generic competition, the brand-name companies some-times launch generic versions themselves called authorized generics. This practice is puzzling. If it is cannibalization, it cannot be profitable. If it is divisionalization, it should be practiced always instead of sometimes. I explain this phenomenon in terms of switching costs in a model in which the incumbent first develops a customer base to ready itself against generic competition later. I show that only sufficiently low switching costs or large market size justifies launch of AGs. I then use prescription drug data to test those results and find support. ^ Chapter 3: The Merger Paradox and R&D Oligopoly theory says that merger is unprofitable, unless a majority of firms in industry merge. Here, we introduce R&D opportunities to resolve this so-called merger paradox. We have three results. First, when there is one R&D firm, that firm can profitably merge with any number of non-R&D firms. Second, with multiple R&D firms and multiple non-R&D firms, all R&D firms can profitably merge. Third, with two R&D firms and two non-R&D firms, each R&D firms prefer to merge with a non-R&D firm. With three or more than non-R&D firms, however, the R&D firms prefer to merge with each other.^

Improving the Performance of Database-Centric Applications Through Program Analysis

Thesis (Ph.D, Computing) -- Queen's University, 2016-09-30 09:55:51.506