Influence Analysis towards Big Social Data

Large scale social data from online social networks, instant messaging applications, and wearable devices have seen an exponential growth in a number of users and activities recently. The rapid proliferation of social data provides rich information and infinite possibilities for us to understand and analyze the complex inherent mechanism which governs the evolution of the new technology age. Influence, as a natural product of information diffusion (or propagation), which represents the change in an individual’s thoughts, attitudes, and behaviors resulting from interaction with others, is one of the fundamental processes in social worlds. Therefore, influence analysis occupies a very prominent place in social related data analysis, theory, model, and algorithms. In this dissertation, we study the influence analysis under the scenario of big social data. Firstly, we investigate the uncertainty of influence relationship among the social network. A novel sampling scheme is proposed which enables the development of an efficient algorithm to measure uncertainty. Considering the practicality of neighborhood relationship in real social data, a framework is introduced to transform the uncertain networks into deterministic weight networks where the weight on edges can be measured as Jaccard-like index. Secondly, focusing on the dynamic of social data, a practical framework is proposed by only probing partial communities to explore the real changes of a social network data. Our probing framework minimizes the possible difference between the observed topology and the actual network through several representative communities. We also propose an algorithm that takes full advantage of our divide-and-conquer strategy which reduces the computational overhead. Thirdly, if let the number of users who are influenced be the depth of propagation and the area covered by influenced users be the breadth, most of the research results are only focused on the influence depth instead of the influence breadth. Timeliness, acceptance ratio, and breadth are three important factors that significantly affect the result of influence maximization in reality, but they are neglected by researchers in most of time. To fill the gap, a novel algorithm that incorporates time delay for timeliness, opportunistic selection for acceptance ratio, and broad diffusion for influence breadth has been investigated. In our model, the breadth of influence is measured by the number of covered communities, and the tradeoff between depth and breadth of influence could be balanced by a specific parameter. Furthermore, the problem of privacy preserved influence maximization in both physical location network and online social network was addressed. We merge both the sensed location information collected from cyber-physical world and relationship information gathered from online social network into a unified framework with a comprehensive model. Then we propose the resolution for influence maximization problem with an efficient algorithm. At the same time, a privacy-preserving mechanism are proposed to protect the cyber physical location and link information from the application aspect. Last but not least, to address the challenge of large-scale data, we take the lead in designing an efficient influence maximization framework based on two new models which incorporate the dynamism of networks with consideration of time constraint during the influence spreading process in practice. All proposed problems and models of influence analysis have been empirically studied and verified by different, large-scale, real-world social data in this dissertation

Analyzing Granger causality in climate data with time series classification methods

Attribution studies in climate science aim for scientifically ascertaining the influence of climatic variations on natural or anthropogenic factors. Many of those studies adopt the concept of Granger causality to infer statistical cause-effect relationships, while utilizing traditional autoregressive models. In this article, we investigate the potential of state-of-the-art time series classification techniques to enhance causal inference in climate science. We conduct a comparative experimental study of different types of algorithms on a large test suite that comprises a unique collection of datasets from the area of climate-vegetation dynamics. The results indicate that specialized time series classification methods are able to improve existing inference procedures. Substantial differences are observed among the methods that were tested

Bloc party: investigating the strategies of AILAC in the UNFCCC

As climate change has become a pressing global political issue, academic interest in the negotiations within the United Nations Framework Convention on Climate Change (UNFCCC) has grown. However, whilst the outcomes, and levels of parties’ influence, have produced much scholarship, a lacuna remains on parties’ strategies. Specifically, strategies used by coalitions have been understudied. This thesis contributes with an investigation of strategies used by AILAC, a group of Latin American states co-operating to advance ambitious global climate action, between 2013 and 2018. As a relatively new coalition, AILAC has received little scholarly attention, with limited study assessing its positions and contributions towards the Paris Agreement. This thesis examines AILAC’s strategy choices and the reasoning behind them through a governmentality theoretical lens. Primarily a theory of power, it sees relations between actors as processes, questioning how actors interact with each other, making it a natural fit for the study of strategies and an attractive alternative to rational choice theories overlooking processes. To determine AILAC’s strategy use, the thesis employs Critical Discourse Analysis. CDA uncovers evidence of strategies within AILAC’s UNFCCC submission texts and interviews with AILAC delegates, providing insights into influences on AILAC’s strategic decision-making. It finds AILAC overwhelmingly preferred less aggressive strategies such as constructive proposals, persuasion, and coalition-building over more aggressive strategies like exerting moral pressure, demands, and threats. This primarily resulted from power relations between AILAC and its negotiating partners; while AILAC is resourcepoor vis-à-vis material power, it is rich in power/knowledge, allowing it to use less aggressive strategies with a reasonable expectation of success where more aggressive strategies reliant on material power would likely fail. The thesis also finds influence on AILAC strategies from various other factors; e.g. AILAC’s bridge-building identity reinforces the attractiveness of less aggressive strategies, while its delegation dynamics drive use of informal spaces

Fundamental Approaches to Software Engineering

This open access book constitutes the proceedings of the 24th International Conference on Fundamental Approaches to Software Engineering, FASE 2021, which took place during March 27–April 1, 2021, and was held as part of the Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg but changed to an online format due to the COVID-19 pandemic. The 16 full papers presented in this volume were carefully reviewed and selected from 52 submissions. The book also contains 4 Test-Comp contributions

The Political Economy and Coalitions in Botswana’s Water Sector Reform 2009-13: to what extent can the process of reform be understood?

This thesis examines the process of water sector reform in Botswana, focusing on barriers to effective delivery of clean water and improved sanitation services (WSS) to all, and water resource management (WRM), in a water insecure country, dependent for surface water on international river basin organisations. The study provides a crtitical analysis of policy change in progress. The impact of the water reforms on the poor and the process of centralising control of WSS, from both tribal and local authorities and the problems encountered are addressed. This study first reviews Botswana’s historical and recent performance on WRM and WSS and examines the underlying drivers and early outcomes of the recent major reform process. Advocacy Coalition Theory (Weible et al 2009, 2008; Sabatier and Jenkins-Smith 1999, 1993) provides the theoretical basis to give insights into the processes of policy reform. The research uses documents and observations of government policy planning and implementation processes from 2010 to 2013. Insights are also drawn from key informant interviews and focus groups from village to national level. The results show the relevance of Advocacy Coalition Theory to Botswana’s history of water sector reform; a struggle between a pre-2009 hydro-mission coalition comprised of an elite, grown successful on mining revenues and the culture of cattle; to a post-2009 coalition formed broadly around concern about water availability and an ecological culture that harks back to the past. Changes include new tariff reform policies, which could be seen as running counter to Water Demand Management (WDM), as they are mitigated within the Government’s policies of poverty eradication. The centralisation of WSS provision under a Parastatal, the Water Utilities Corporation, has been completed. A new Water Policy and Regulator, set to be established, appears to reflect the gradual success of the more environmentally focused coalition, seeking stronger water secure independent IWRM and WDM policies. This process is still in play and it will require strong political will to complete Botswana’s transition to a sustainable water-based political economy. Lessons about surmounting the barriers to effective IWRM and National WRM and delivery of WSS elsewhere in developing countries could be learned from the policy processes in this geographically large, water constrained African country

GEO-6 assessment for the pan-European region

Through this assessment, the authors and the United Nations Environment Programme (UNEP) secretariat are providing an objective evaluation and analysis of the pan-European environment designed to support environmental decision-making at multiple scales. In this assessment, the judgement of experts is applied to existing knowledge to provide scientifically credible answers to policy-relevant questions. These questions include, but are not limited to the following:• What is happening to the environment in the pan-European region and why?• What are the consequences for the environment and the human population in the pan-European region?• What is being done and how effective is it?• What are the prospects for the environment in the future?• What actions could be taken to achieve a more sustainable future?<br/

Adaptive User Authentication on Mobile Devices

Modern mobile devices allow users to access various applications and services anywhere. However, high mobility also exposes mobile devices to device loss, unauthorized access, and many other risks. Existing studies have proposed a variety of explicit authentication (EA) and implicit authentication (IA) mechanisms to secure sensitive personal and corporate data on mobile devices. Considering the limitations of these mechanisms under different circumstances, we expect that future authentication systems will be able to dynamically determine when and how to authenticate users based on the current context, which is called adaptive authentication. This thesis investigates adaptive authentication from the perspectives of context sensing techniques, authentication and access control adaptations, and adaptation modeling. First, we investigate the smartphone loss scenario. Context sensing is critical for triggering immediate device locking with re-authentication and an alert to the owner before they leave without the phone. We propose Chaperone, an active acoustic sensing based solution to detect a user's departure from the device. It is designed to robustly provide a user's proximity and motion contexts in real-world scenarios characterized by bursting high-frequency noise, bustling crowds, and diverse environmental layouts. Extensive evaluations at a variety of real-world locations have shown that Chaperone has high accuracy and low detection latency under various conditions. Second, we investigate temporary device sharing as a special scenario of adaptive authentication. We propose device sharing awareness (DSA), a new sharing-protection approach for temporarily shared mobile devices. DSA exploits natural handover gestures and behavioral biometrics as contextual factors to transparently enable and disable a device's sharing mode without requiring explicit input of the device owner. It also supports various access control strategies to fulfill sharing requirements imposed by an app. Our user study has shown the effectiveness of handover detection and demonstrated how DSA automatically processes sharing events to provide a secure sharing environment. Third, we investigate the adaptation of an IA system to shared mobile devices to reject imposters and distinguish between legitimate users in real-time. We propose a multi-user IA solution that incorporates multiple modalities and supports adding new users and automatically labeling new incoming data for model updating. Our solution adopts a score fusion strategy based on Dempster-Shafer (D-S) theory to improve accuracy with considering uncertainties among different IA mechanisms. We also provide an evaluation framework to support IA researchers in the evaluation of multi-user, multi-modal IA systems. We present two sample use cases to showcase how our framework helps address practical design questions of multi-user IA systems. Fourth, we investigate a high-level organization of different adaptation policies in an adaptive authentication system. We design and build a multi-stage risk-aware adaptive authentication and access control framework (MRAAC). MRAAC organizes adaptation policies in multiple stages to handle various scenarios and progressively adapts authentication mechanisms based on context, resource sensitivity, and user authenticity. We present three use cases to show how MRAAC enables various stakeholders (device manufacturers, enterprise and secure app developers) to provide adaptive authentication workflows on COTS Android with low processing and battery overhead. In conclusion, this thesis fills the gaps in adaptive authentication systems for shared mobile devices and adaptation models for authentication and access control. Our frameworks and implementations also benefit researchers and developers to develop and evaluate their adaptive authentication systems efficiently

Status of the Global Observing System for Climate

Status of the Global Observing System for Climat