Mass introduction of electric passenger vehicles in Brazil: impact assessment on energy use, climate mitigation and on charging infrastructure needs for several case studies

Mobility has proved to be a major challenge for human development, especially in urban centers worldwide, where more displacement is required, since fossil fuels consumption is increasing as well as greenhouse gas (GHG) emissions, causing air quality degradation and global warming. The predicted population increase in cities tends to increase the demand for mobility and to further exacerbate those impacts. Therefore, sustainable transport is key for the future of mobility, and electric vehicle (EV) has emerged as a recognized sustainable option. However, there are many electric vehicle barriers diffusion. This research aims to contribute to the diffusion of EV in Brazil, by assessing: 1) whether EV is a more sustainable technology when compared with ethanol vehicle; 2) the impacts of the expansion of electric mobility on CO2 emissions, in Sao Paulo; 3) how to overcome the barriers for the charging infrastructure deployment at the municipality level, in Sao Paulo, Rio de Janeiro and Belo Horizonte; and 4) key challenges and opportunities from the mass adoption of EV in Brazil. A plethora of different methods were used, including scenario analysis, multi-criteria decision methods, geographic information systems and SWOT analysis. Main results point to EV as the best technology to mitigate passenger transport related CO2 emissions in Brazil, due to its low carbon footprint. In Sao Paulo, this option could reduce around 11 MtCO2 by 2030 and save 6,200 billion USD in energy with the replacement of 20 percent of gasoline cars with EV. To meet 1 percent of EV's market share, Sao Paulo, Rio de Janeiro and Belo Horizonte together will need around 6,500 charging stations concentrated in around 1/3 of their territories (level 2). Brazil may likely have up to 10 percent of EV penetration by 2030, with the diffusion taking place mostly in southeastern municipality. Ethanol, lack of electric mobility public policy, non-urbanized like subnormal agglomerates, and risk areas, like flood hazard, are major obstacles for EV diffusion in Brazil

Spatial and temporal-based query disambiguation for improving web search

Queries submitted to search engines are ambiguous in nature due to users’ irrelevant input which poses real challenges to web search engines both towards understanding a query and giving results. A lot of irrelevant and ambiguous information creates disappointment among users. Thus, this research proposes an ambiguity evolvement process followed by an integrated use of spatial and temporal features to alleviate the search results imprecision. To enhance the effectiveness of web information retrieval the study develops an enhanced Adaptive Disambiguation Approach for web search queries to overcome the problems caused by ambiguous queries. A query classification method was used to filter search results to overcome the imprecision. An algorithm was utilized for finding the similarity of the search results based on spatial and temporal features. Users’ selection based on web results facilitated recording of implicit feedback which was then utilized for web search improvement. Performance evaluation was conducted on data sets GISQC_DS, AMBIENT and MORESQUE comprising of ambiguous queries to certify the effectiveness of the proposed approach in comparison to a well-known temporal evaluation and two-box search methods. The implemented prototype is focused on ambiguous queries to be classified by spatial or temporal features. Spatial queries focus on targeting the location information whereas temporal queries target time in years. In conclusion, the study used search results in the context of Spatial Information Retrieval (S-IR) along with temporal information. Experiments results show that the use of spatial and temporal features in combination can significantly improve the performance in terms of precision (92%), accuracy (93%), recall (95%), and f-measure (93%). Moreover, the use of implicit feedback has a significant impact on the search results which has been demonstrated through experimental evaluation.SHAHID KAMA

Evolutionary swarm algorithm for modelling and control of horizontal flexible plate structures

Numerous advantages offered by the horizontal flexible structure have attracted increasing industrial applications in many engineering fields particularly in the airport baggage conveyor system, micro hand surgery and semiconductor manufacturing industry. Nevertheless, the horizontal flexible structure is often subjected to disturbance forces as vibration is easily induced in the system. The vibration reduces the performance of the system, thus leading to the structure failure when excessive stress and noise prevail. Following this, it is crucial to minimize unwanted vibration so that the effectiveness and the lifetime of the structure can be preserved. In this thesis, an intelligent proportional-integral-derivative (PID) controller has been developed for vibration suppression of a horizontal flexible plate structure. Initially, a flexible plate experimental rig was designed and fabricated with all clamped edges boundary conditions at horizontal position. Then, the data acquisition and instrumentation systems were integrated into the experimental rig. Several experimental procedures were conducted to acquire the input-output vibration data of the system. Next, the dynamics of the system was modeled using linear auto regressive with exogenous, which is optimized with three types of evolutionary swarm algorithm, namely, the particle swarm optimization (PSO), artificial bee colony (ABC) and bat algorithm (BAT) model structure. Their effectiveness was then validated using mean squared error, correlation tests and pole zero diagram stability. Results showed that the PSO algorithm has superior performance compared to the other algorithms in modeling the system by achieving lowest mean squared error of 6103947.4 , correlation of up to 95 % confidence level and good stability. Next, five types of PID based controllers were chosen to suppress the unwanted vibration, namely, PID-Ziegler Nichols (ZN), PID-PSO, PID-ABC, Fuzzy-PID and PID-Iterative Learning Algorithm (ILA). The robustness of the controllers was validated by exerting different types of disturbances on the system. Amongst all controllers, the simulation results showed that PID tuned by ABC outperformed other controllers with 47.60 dB of attenuation level at the first mode (the dominant mode) of vibration, which is equivalent to 45.99 % of reduction in vibration amplitude. By implementing the controllers experimentally, the superiority of PID-ABC based controller was further verified by achieving an attenuation of 23.83 dB at the first mode of vibration and 21.62 % of reduction in vibration amplitude. This research proved that the PID controller tuned by ABC is superior compared to other tuning algorithms for vibration suppression of the horizontal flexible plate structure

Towards Mobility Data Science (Vision Paper)

Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracking technologies, mobility data is collected ubiquitously. In recent years, the use of mobility data has demonstrated significant impact in various domains including traffic management, urban planning, and health sciences. In this paper, we present the emerging domain of mobility data science. Towards a unified approach to mobility data science, we envision a pipeline having the following components: mobility data collection, cleaning, analysis, management, and privacy. For each of these components, we explain how mobility data science differs from general data science, we survey the current state of the art and describe open challenges for the research community in the coming years.Comment: Updated arXiv metadata to include two authors that were missing from the metadata. PDF has not been change

Better e-Learning for innovation in education

This book is an output from the ERASMUS+ project number 2015-1-TR01-KA204-021954 under the name 'Better e-Learning for All' (Project acronym: Better-E)This book - "Better e-Learning for Innovation in Education" - intends to provide an overview of the most important issues that relate Education through e-Learning and Pedagogical Innovation.Acknowledgements: The research leading to these results has received funding from the European Community's ERASMUS+ PROGRAMME under grant agreement no. 2015-1-TR01-KA204-021954 “Better e-Learning for All”.info:eu-repo/semantics/publishedVersio

SeLINA: a Self-Learning Insightful Network Analyzer

Understanding the behavior of a network from a large scale traffic dataset is a challenging problem. Big data frameworks offer scalable algorithms to extract information from raw data, but often require a sophisticated fine-tuning and a detailed knowledge of machine learning algorithms. To streamline this process, we propose SeLINA (Self-Learning Insightful Network Analyzer), a generic, self-tuning, simple tool to extract knowledge from network traffic measurements. SeLINA includes different data analytics techniques providing self-learning capabilities to state-of-the-art scalable approaches, jointly with parameter auto-selection to off-load the network expert from parameter tuning. We combine both unsupervised and supervised approaches to mine data with a scalable approach. SeLINA embeds mechanisms to check if the new data fits the model, to detect possible changes in the traffic, and to, possibly automatically, trigger model rebuilding. The result is a system that offers human-readable models of the data with minimal user intervention, supporting domain experts in extracting actionable knowledge and highlighting possibly meaningful interpretations. SeLINA's current implementation runs on Apache Spark. We tested it on large collections of realworld passive network measurements from a nationwide ISP, investigating YouTube and P2P traffic. The experimental results confirmed the ability of SeLINA to provide insights and detect changes in the data that suggest further analyse

Sustainability in design: now! Challenges and opportunities for design research, education and practice in the XXI century

Copyright @ 2010 Greenleaf PublicationsLeNS project funded by the Asia Link Programme, EuropeAid, European Commission

BRICS Cities: Facts & Analysis 2016

BRICS Cities: Facts & Analysis is a compendium of research produced through a partnership between the South African Cities Network (SACN) and the South African Research Chair in Spatial Analysis and City Planning (SA&CP) in the School of Architecture and Planning at the University of the Witwatersrand. It presents key general and thematic descriptive and comparative information about urban growth and development in the five BRICS states: Brazil, Russia, India, China and South Africa. The comparative analysis includes a section relating to cities in Africa, while the detailed Factsheets cover thirty-one of the largest BRICS cities. BRICS Cities provides a first-of-its-kind research base to inform ongoing sub-national BRICS research and policy consideration. Recent reports on urbanization point out that over the next 20-30 years, almost all of the expected growth in the world population will be concentrated in the urban areas of the less developed countries of which a significant 42% will occur in cities in BRICS countries. Despite the fact that the distribution of the urbanization figures will be highly unequal between the different countries, considering the currently high levels of urbanization in Russia and Brazil and the extremely low levels (just over 35%) in India, the realities of large scale urbanization can and no doubt will have substantial impacts on the material conditions of urban life, governance, service provision, social relations and the environment. There has also been, and will continue to be, the expansion of networks of all kinds far beyond designated urban boundaries. In some cases, these challenges and the expanding boundaries have been met with additional layers of government, innovations in policy-making, and the reconfiguring of relationships between urban actors. However little is known in a comparative sense around some of the most important sites and cities in the BRICS countries , and insufficient research has been undertaken to learn from the differences that have been identified. The SACN and SA&CP, in line with our mutual interest around the nature and shape of urbanization and urban processes in South Africa and in BRICS countries, have developed a compendium of comparable information around key cities in the BRICS countries. BRICS Cities will serve as a useful reference of important base line information but also offers comment on the state of key areas of shared concern: innovation-driven economies, transport and mobility, and green energy. Furthermore, the publication provides a careful analysis of these factors in a comparative and relational framing.AA2017https://www.wits.ac.za/archplan/research-entities/spatial-analysis-and-city-planning/featured-projects/brics-fact-sheet-book