Submitted by Luiz Felipe Barbosa (luiz.fbabreu2@ufpe.br) on 2015-03-10T19:41:00Z No. of bitstreams: 2 DISSERTAÇÃO Vinicius Cezar Monteiro de Lira.pdf: 4006584 bytes, checksum: 5d1301329fabe34879780b3b17bb1e8a (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Approved for entry into archive by Daniella Sodre (daniella.sodre@ufpe.br) on 2015-03-10T19:43:51Z (GMT) No. of bitstreams: 2 DISSERTAÇÃO Vinicius Cezar Monteiro de Lira.pdf: 4006584 bytes, checksum: 5d1301329fabe34879780b3b17bb1e8a (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-03-10T19:43:51Z (GMT). No. of bitstreams: 2 DISSERTAÇÃO Vinicius Cezar Monteiro de Lira.pdf: 4006584 bytes, checksum: 5d1301329fabe34879780b3b17bb1e8a (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2014-08-28 / The analysis of human movements has been the subject of several studies since the 70s. In recent years, the exponential growth of location aware devices must allow the study of the behavior of the individuals’ mobility from their trajectories collected. However, a significant part of the available literature is focused on the development of techniques for analyzing trajectories of people from a purely geometric point of view, while a smaller part, but increasingly group is looking at the semantic aspects of mobility. This work presents a contribution to the latest trend, and is concerned with the definition of semantic regularity profiles and the applicability of these concepts to the practice of carpooling. We propose a semantic regularity profile based on the entropy of the spatial and temporal frequency of visits to certain categories of places. We analyze the user’s behavior with respect to regularity and irregularity, identifying users who are more or less loyal to certain locations, in contrast to the irregularity of visiting different places. In a different point of view, an analysis over the place perspective was also performed. A web tool was developed to show on map, for each place of a given category, the computed information about the loyal behavior of their visitors. From the study about regularity, we have evidences that some human activities are not strictly associated to a unique POI (Point of Interest) and neither to a specific schedule of the day. Bringing to the carpooling context, in some situations it is worth for a person to change his destination or the time to perform an activity if there is a possibility of ride for him due all the benefits involved with the carpooling practice. This dissertation also presents a novel matching method for carpooling that is oriented to the passenger’s intended activity, aiming to boost the possibilities of rides. Three algorithms for carpool matching are proposed, which manipulates differently the spatial and temporal dimensions. Using a real data set of trajectories, we conducted experiments and our results showed that the proposed matching algorithms improved the traditional carpooling approach in +46.84% when the spatial dimension was considered, in +50.89% when the temporal dimension was prioritized and in +82.30% when both dimensions were tackled.

Urban energy systems are often studied in a very similar way in the sense that the characteristics of the underlying physical infrastructure are weighted as the main determinants of energy use predictions, while the behavior of the human population in relation to this systemthe so-called ``energy consumers''in time and urban spaces is effectively neglected. The spatial and temporal variations in infrastructure-population interactivity greatly complicate urban energy systems; the unremitting growth in population and advances in technology mean that the dynamic interrelationship between the population and urban environment will continue to grow exponentially, resulting in increasing uncertainties, unreliable predictions and poor management decisions given the inadequacy of existing approaches. In this dissertation, I explore the interdependencies of spatiotemporal fluctuations of human mobility as an indicator for human activities and energy use in urban areas in three main studies. First, I show that the fluctuations of intra-urban human mobility and energy use have an underlying structure across both time and space, and that human mobility can indeed be used as a predictor for energy use in both dimensions. Second, I examine how one of the dominant drivers of this structure, namely individuals' location-based activities, influence patterns in energy supply and demand across building types (i.e. residential and commercial buildings) and show how variations in the human mobility networks of two distinct urban populations (the so-called returners and explorers) can explain fluctuations in energy use. Third, I introduce an integrated approach for predicting urban energy use across time and space by incorporating these interdependencies. Generating predictive models that capture the spatiotemporal variations in these determinants in urban settings, as suggested in this research, will contribute to our understanding of how variations in urban population activities for particular times and locations influence can be applied to estimate energy use patterns in surrounding areas. / PHD / Today’s cities are the most complex built environments in human history, containing 54% of the world population and responsible for up to 80% of the world’s total energy consumption. As a result of population growth and advances in technology, the interdependencies between infrastructure, services, and individuals in urban spaces continue to increase, presaging an ambiguous future with challenges we are not yet aware of. In this research, I developed the concept of <i>urban spatiotemporal flux</i> to study the interdependencies between energy use and human activities using human mobility at various spatial and temporal scales to address the urgent need to incorporate the resulting fluctuations in energy use into future energy predictions. Intra-city human activities change more rapidly and exhibit higher levels of dynamic characteristics than the simple physical locations identified in current master plans. Previous research has tended to focus on predicting energy consumption at different spatial levels as a function of the physical characteristics of buildings or cities, often relying on sensor-based data-driven approaches. There has been some effort to explore the predictability of human mobility by building human mobility-based predictive models across applications such as traffic and travel demand predictions, human activity predictions, next place locations, epidemics and the spread of viruses, and air pollution. The two perspectives are rarely in conversation with each other, however, with only minimal integration of our understanding and predictions for different urban spatial and temporal scales. The technology that has become an integral part of everyday life in today’s smarter urban environments now allows us to use human beings as “sensors” that provide useful data for predictions of energy use. Using tens of millions of yearly individual positional records across thousands of spatial divisions, along with millions of corresponding measures of energy use from energy meters in Greater London and the City of Chicago, I discovered that fluctuations in urban energy consumption are likely governed by the structure of human mobility networks and are dominated by certain populations and buildings types, among other factors. Intra-urban human mobility and energy use are not spatially randomly distributed across urban settings; instead, there is an underlying structure that explains their dependency. Temporal manifestations of these fluctuations suggest a continuous spatiotemporal relationship between human mobility and energy use, which confirms that the values observed in one location depend to some extent on what is happening at adjacent locations at around the same time. This dependency represents a strong connection with the returner populations’ mobility and residential buildings’ energy use and there is an associated spatial spillover effect. Future energy efficiency strategies should thus reflect these spatiotemporal dependencies, enabling planners to create new and more effective ways for both different building types and the mobility networks of the urban population to play major roles in energy related strategies, as well as helping to identify the fluctuating determinants that represent additional evidence of a spatiotemporal structure.

The flexibility of future mobile networks exploiting modern technologies such as cloud-optimized radio access and software-defined networks opens a gateway to deploying dynamic strategies for live and on-demand content delivery. Traditional live broadcasting systems are spectral inefficient. It takes up a lot more radio spectrum than that of mobile networks, to cover the same size of an area. Furthermore, content caching at base stations reduces network traffic in core networks. However, numerous duplicated copies of contents are still transmitted in the unicast fashion in radio access networks. It consumes valuable radio spectrum and unnecessary energy. Finally, due to the present of numerous mobile receivers with a wide diversity of wireless channels in a base station coverage area, it is a challenge to select a proper modulation scheme for video broadcasting to optimize the quality of services for users. In this thesis, the challenges and the problems in the current strategies for content delivery are addressed. A holistic novel solution is proposed that considers user preferences, user mobility, device-to-device communication, physical-layer resource allocation, and video quality prediction. First, a system-level scheduling framework is introduced to increase the spectral efficiency on broadcasting live contents onto mobile networks. It considers the audience preferences for allocating radio resources spatially and temporally. Second, to reduce the redundant transmissions in radio access networks, a content distribution system that exploits user mobility is proposed that utilizes the urban-scale user mobility and broadcasting nature of wireless communication for delay-tolerant large size content. Third, to further reduce the energy consumption in network infrastructure, a content distribution system that relies on both user mobility, and device-to-device communication is proposed. It leverages the mobile users as content carriers to offload the heavy mobile traffic from network-level onto device-level. Fourth, to mitigate the multi-user channel diversity problem, a cross-layer approach is deployed to increase the video quality for users especially for those who have a low signal-to-noise ratio signal. Finally, data mining techniques are employed to predict video qualities of wireless transmissions over mobile networks. The holistic solution has been empirically developed and evaluated. It achieves high spectral and energy efficiency and mitigates the video quality degradation in mobile networks.

Natural disasters exert a profound impact on the world population. In 2012, natural disasters affected 106 million people, forcing over 31.7 million people to leave their homes. Climate change has intensified natural disasters, resulting in more catastrophic events and making extreme weather more difficult to predict. Understanding and predicting human movements plays a critical role in disaster evacuation, response and relief. Researchers have developed different methodologies and applied several models to study human mobility patterns, including random walks, Lévy flight, and Brownian walks. However, the extent to which these models may apply to perturbed human mobility patterns during disasters and the associated implications for improving disaster evacuation, response and relief efforts is lacking. My PhD research aims to address the limitation in human mobility research and gain a ground truth understanding of human mobility patterns under the influence of natural disasters. The research contains three interdependent projects. In the first project, I developed a novel data collecting system. The system can be used to collect large scale data of human mobility from large online social networking platforms. By analyzing both the general characteristics of the collected data and conducting a case study in NYC, I confirmed that the data collecting system is a viable venue to collect empirical data for human mobility research. My second project examined human mobility patterns in NYC under the influence of Hurricane Sandy. Using the data collecting system developed in the first project, I collected 12 days of human mobility data from NYC. The data set contains movements during and several days after the strike of Hurricane Sandy. The results showed that human mobility was strongly perturbed by Hurricane Sandy, but meanwhile inherent resilience was observed in human movements. In the third project, I extended my research to fifteen additional natural disasters from five categories. Using over 3.5 million data entries of human movement, I found that while human mobility still followed the Lévy flight model during these disaster events, extremely powerful natural disasters could break the correlation between human mobility in steady states and perturbation states and thus destroy the inherent resilience in human mobility. The overall findings have significant implications in improving understanding and predicting human mobility under the influence of natural disasters and extreme events. / Ph. D.

This thesis explores the dynamical and structural properties of human mobility within urban environments through the lens of complex systems and network science. Beginning with an introduction to the relevance of studying cities and human mobility, we outline our aim to investigate the interplay between transportation network properties and collective human flows. The theoretical background introduces essential concepts from network science and statistical physics, focusing on their application to spatial and transportation networks as well as urban systems. The thesis is devoted to three specific investigations. Firstly, we analyze the role of multiple pathways in defining effective network distances and their utility in predicting human mobility at diffusive scales, particularly in assessing pandemic potentials such as COVID-19 variants. Secondly, we delve into the optimization of flow-weighted transportation networks, demonstrating how network topologies can emerge from optimization processes under various constraints. We focus on a case study on the Greater London Area highlighting the integration of spatial attractiveness and traffic congestion in simulating human mobility patterns. The thesis finally explores the dynamics of out-of-routine mobility by integrating individual and collective behaviors. Leveraging large-scale datasets from US cities, we improve next-location prediction models by combining insights from individual trajectories and collective mobility dynamics. This approach is further examined in the context of novel mobility patterns influenced by COVID-19 restrictions, emphasizing the statistical properties of collective mobility near urban points of interests. Through these investigations, this thesis contributes to understanding complex urban systems and lays foundations for predictive models that integrate theoretical insights with empirical data to enhance our understanding of human mobility dynamics.

Given the significant burden that gun violence places on individuals and communities, it is important to understand the factors that produce differential rates of gun violence across communities. One robust predictor of city- and neighborhood-rates of gun violence has been drug market activity. Mounting evidence suggests that not only are drug markets criminogenic places themselves, they produce spillovers of violence into spatially proximate areas as well. Yet it is still unknown whether there is a more general spillover effect of drug markets that affects neighborhoods that are spatially distant. This dissertation fills this critical gap by examining the influence of drug market activity on gun violence across a “network of neighborhoods” in Baltimore, New York City, and Philadelphia. Using large-scale cellphone data on resident mobility patterns, this study creates a mobility-based network of urban neighborhoods representing census tracts that are linked by where their residents visited throughout the course of several months (year-quarters). Set within a social disorganization and environmental criminology framework, this study uses tract-level data on shootings, drug arrests, sociostructural characteristics, business and transit locations, and cell-phone based mobility to answer a series of research questions. The primary research questions addressed in this dissertation examine whether drug market activity in network neighbors contributes to elevated gun violence in local neighborhoods. To answer these questions, a series of network lag models are run predicting the net effect of mobility network-lagged drug market activity on local gun violence rates. A secondary research question is related to an exploration of the mobility-based network of neighborhoods in each city. Descriptive analyses are conducted on the resident routine mobility networks to answer this question. Results from this dissertation will add to the literature concerning the drug market-violence link, and the spatial patterning of violence in cities more generally. Using cellphone data capturing resident mobility to connect neighborhoods will also add to the literature on neighborhood networks, and provide insight into whether examining neighborhoods connected by the routine mobility of city residents is useful in explaining the spillover of drug market activity on gun violence in spatially close and distant neighborhoods. / Criminal Justice

京都大学 / 新制・課程博士 / 博士(社会健康医学) / 甲第25209号 / 社医博第136号 / 新制||社医||13(附属図書館) / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 長尾 美紀, 教授 今中 雄一, 教授 山崎 渉 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

This thesis examines the rising phenomenon of the internationalisation of Chinese firms, and aims to shed new light on our understanding of the emergence of firms from emerging economies in the global market. It consists of two parts: the country level study and the firm level. The former identifies the domestic and locational determinants of Chinese outward foreign direct investment (OFDI), while the latter examines the influence of dynamic capabilities and institutions on the post-internationalisation performance of Chinese firms, with a focus on state-owned enterprises (SOEs). To explore the domestic and locational determinants of Chinese OFDI, the thesis integrates network theory with the traditional explanations of OFDI, the investment development path and the eclectic paradigm. By doing so, a new factor, human mobility, is identified as one of the important domestic and locational determinants of Chinese OFDI. Drawing upon a time series data analysis for the period 1979-2007, this study confirms that Chinese OFDI is driven by its domestic economic development, human mobility and knowledge development and accumulation, and it has a substitute relationship with exports. By examining Chinese OFDI flows to 13 OECD countries over the period 1999-2007, it is shown that human mobility, the strategic assets of the host country, foreign direct investment to China and cultural distance have a positive impact on the locational choice of Chinese OFDI to OECD countries. To investigate the influence of dynamic capabilities and institutions on the post-internationalisation performance of Chinese firms, this study integrates the dynamic capability framework and the institution-based view, and embeds the analysis in a multi-perspective conceptual framework. It draws on four case studies of Chinese SOEs. The analysis shows the importance of internal dynamic capabilities in achieving overseas success when dealing with changing environments. The managerial mindset has a moderate effect on the impact of dynamic capabilities on post-internationalisation performance. The case analysis also shows how the external institutional environment of both host and home countries influence the performance of Chinese SOEs. ii Support from both host and home country governments, unsurprisingly, has a positive influence on performance. However, too much intervention from the home country government imposes constraints on the firms and reduces their willingness to commit to internationalisation. This thesis makes a number of contributions to the existing literature. First, it provides a better understanding of the overall picture of Chinese OFDI from the macro perspective. The findings also contribute to our understanding of the rise of OFDI from emerging economies in general and from China in particular. Second, a new factor, human mobility, is identified and proved to be significant in determining Chinese OFDI. In this era of globalisation, human mobility has become the driving force of OFDI from emerging economies. Third, a first step is taken towards exploring the influence of both internal and external factors on the post-internationalisation performance of Chinese firms. In order to achieve overseas success, not only do Chinese firms need to improve their internal dynamic capabilities, but also attention needs to be paid to the external institutional environment, which has a significant impact on the performance of Chinese firms pursuing overseas success.

Submitted by Kamila Costa (kamilavasconceloscosta@gmail.com) on 2015-06-24T20:06:17Z No. of bitstreams: 1 TESE-MÁRCIA MARIA DE OLIVEIRA.pdf: 2774285 bytes, checksum: 671b475060a4169eda3dc90120fd7c6f (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-03T13:23:07Z (GMT) No. of bitstreams: 1 TESE-MÁRCIA MARIA DE OLIVEIRA.pdf: 2774285 bytes, checksum: 671b475060a4169eda3dc90120fd7c6f (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-03T13:25:59Z (GMT) No. of bitstreams: 1 TESE-MÁRCIA MARIA DE OLIVEIRA.pdf: 2774285 bytes, checksum: 671b475060a4169eda3dc90120fd7c6f (MD5) / Made available in DSpace on 2015-07-03T13:25:59Z (GMT). No. of bitstreams: 1 TESE-MÁRCIA MARIA DE OLIVEIRA.pdf: 2774285 bytes, checksum: 671b475060a4169eda3dc90120fd7c6f (MD5) Previous issue date: 2014-06-24 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In this thesis, we discussed the main migration dynamics observed in the Amazon over the last decade and its importance for understanding the processes of social, political, economic and cultural changes in the region. Such changes are remarkable in all sectors of society to be almost impossible to think the Amazon without taking into account the internal and international migrations that give the region an intense human mobility. The study indicates that migration dynamics involve all dimensions of sociability and represent another possibility of reading and interpreting the Amazon inserted into the complexity of international migration in its various dimensions. The Migration Profile of the region identifies new and old phenomena of population movements that circulate new production basis, transfer of technology and knowledge. / Na presente tese, abordamos as principais dinâmicas migratórias observadas na Amazônia na última década e a sua importância para a compreensão dos processos de mudanças sociais, políticas, econômicas e culturais da região. Tais mudanças se fazem notar em todos os setores da sociedade a ponto de ser quase impossível pensar a Amazônia sem levar em consideração as migrações internas e internacionais que conferem à região uma mobilidade humana intensa. O estudo indica que as dinâmicas migratórias envolvem todas as dimensões da sociabilidadee representam mais uma possibilidade de leitura e interpretação da Amazônia inserida na complexidade da dinâmica da migração internacional em suas variadas dimensões. O Perfil Migratório da região identifica fatos novos e antigos de deslocamentos de populações que fazem circular novas bases de produção, transferências de tecnologias e conhecimentos.

A cidade de Caxias do Sul (RS), formada pela imigração italiana no final do século XIX, tornou-se desde 2011 um novo destino imigratório para fluxos compostos principalmente de haitianos e senegaleses. A presente dissertação busca compreender os processos de inclusão dos imigrantes na cidade, enfocando o seu acesso aos serviços públicos e às políticas locais. Sob a perspectiva local, estuda-se questões complexas como xenofobia, racismo e políticas migratórias, em especial sua articulação concreta dentro de um contexto histórico e cultural específico. Considerando o campo das migrações como um espaço político de disputa, são analisadas as dinâmicas de interação entre os principais atores locais, com destaque para o protagonismo da sociedade civil e da CDHCS e para a não-política do poder Executivo municipal. / The city of Caxias do Sul (RS), founded by Italian immigration in the end of the XIX century, has since 2011 become a new immigrant destination for flows mainly composed by Haitians and Senegalese. This dissertation aims to understand the immigrant inclusion processes in the city, focusing on their access to public services and to local policies. Complex issues such as xenophobia, racism and migration policies are studied from the local perspective, and especially how these issues are concretely articulated within a specific historic and cultural context. Considering the field of migrations as a political dispute arena, the interaction dynamics between the main local actors are analysed, particularly the protagonism of the civil society and of the CDHCS and the non-policy of the municipal Executive power.