Abstract

Abstract
The heated 5G network deployment race has already begun with the rapid progress in standardization efforts, backed by the current market availability of 5G-enabled network equipment, ongoing 5G spectrum auctions, early launching of non-standalone 5G network services in a few countries, among others. In this paper, we study current and future wireless networks from the viewpoint of energy efficiency (EE) and sustainability to meet the planned network and service evolution toward, along, and beyond 5G, as also inspired by the findings of the EU Celtic-Plus SooGREEN Project. We highlight the opportunities seized by the project efforts to enable and enrich this green nature of the network as compared to existing technologies. In specific, we present innovative means proposed in SooGREEN to monitor and evaluate EE in 5G networks and beyond. Further solutions are presented to reduce energy consumption and carbon footprint in the different network segments. The latter spans proposed virtualized/cloud architectures, efficient polar coding for fronthauling, mobile network powering via renewable energy and smart grid integration, passive cooling, smart sleeping modes in indoor systems, among others. Finally, we shed light on the open opportunities yet to be investigated and leveraged in future developments.

Abstract
The main task while developing a mobile robot is to achieve accurate and robust navigation in a given environment. To achieve such a goal, the ability of the robot to localize itself is crucial. In outdoor, namely agricultural environments, this task becomes a real challenge because odometry is not always usable and global navigation satellite systems (GNSS) signals are blocked or significantly degraded. To answer this challenge, this work presents a solution for outdoor localization based on an omnidirectional visual odometry technique fused with a gyroscope and a low cost planar light detection and ranging (LIDAR), that is optimized to run in a low cost graphical processing unit (GPU). This solution, named FAST-FUSION, proposes to the scientific community three core contributions. The first contribution is an extension to the state-of-the-art monocular visual odometry (Libviso2) to work with omnidirectional cameras and single axis gyro to increase the system accuracy. The second contribution, it is an algorithm that considers low cost LIDAR data to estimate the motion scale and solve the limitations of monocular visual odometer systems. Finally, we propose an heterogeneous computing optimization that considers a Raspberry Pi GPU to improve the visual odometry runtime performance in low cost platforms. To test and evaluate FAST-FUSION, we created three open-source datasets in an outdoor environment. Results shows that FAST-FUSION is acceptable to run in real-time in low cost hardware and that outperforms the original Libviso2 approach in terms of time performance and motion estimation accuracy.

Abstract

Abstract
Os artigos incluídos neste livro, após processo de revisão por pares, são desenvolvimentos de trabalhos apresentados nas JOCLAD 2014-17 e mostram, mais uma vez, a interdisciplinariedade e a diversidade das áreas que integram esta Jornadas.

Abstract
Information and Communication Technologies (ICT) emerge as a strategic tool, indispensable for the survival of any organization. However, excessive use of ICT can lead to drawbacks such as equipment dependency, rapid obsolescence, and rising maintenance costs. Inefficient use of ICT can result in higher costs for organizations, which may cause them to lose important competitive advantages. In this context, outsourcing printing may be an alternative for institutions to reduce their costs and become more competitive. The aim of this paper is to evaluate scenarios about the financial viability of printing outsourcing in a Federal Higher Education Institution (Instituicoo Federal de Ensino Superior - IFES). To this end, an exploratory research was conducted, with a quantitative approach, using computational modeling, and using the System Dynamics methodology, with simulation and evaluation of three different scenarios: current scenario, likely scenario, unlikely scenario. The results obtained indicate that the unlikely scenario (100% of leased printers) resulted in lower printing costs over the period of the experiment, totaling R$ 637,828.00; the probable scenario (50% of leased printers) totaled R$ 1,000,480.00; while the current scenario (20% of leased printers) resulted in costs of R$ 1,603,060. With the simulations, it was found that printer leasing (outsourcing printing) is the best financial alternative for IFES, which served as a reference for the study, resulting in lower printing costs compared to printer acquisition. The use of systems modeling to evaluate scenarios has been used to support managers in the decision making involving ICT; however, there were no studies in the literature focused on the financial viability simulation of printer outsourcing. Thus, this work sought to bridge this gap by developing and validating a simulation model that can be applied in different scenarios and types of organizations, and work as a reference for future studies.