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IntelliDrive systems, including inter-vehicle communication and vehicle infrastructure integration, aim to improve safety, mobility, and efficiency of transportation. They build on the wireless ad hoc network technologies, enabling vehicles to communicate with roadside infrastructure and with each other. The process of information propagation in a multi-hop network underlies the system design and efficiency. As of now, the research has been restricted to a single road of traffic. This work expands the study of information propagation to two parallel roads, a step further towards the discrete network case. This thesis presents two methodologies to model the process of information propagation. By identifying an approximate Bernoulli process, we are able to derive the expectation and variance of propagation distance. A road separation distance of square root of 3 over 2 times the transmission range distinguishes two cases for approximating the success probability in the Bernoulli process. In addition, our results take the single road as a special case. The numerical test shows that the developed approximation works well. This work further identities a Markov property for instantaneous information propagation along two parallel roads based on two types of transmission regions. Communication capable vehicles are assumed to follow two homogeneous Poisson processes on both roads. The Markov property enables us to derive exact expectation and variance of the propagation distance and further, obtain a recursive formula for the probability distribution of successful propagation distance. The developed formulas enable numerical calculation of the characteristics of propagation process. We hope this research will shed light on studies of vehicular ad hoc networks on more general discrete roadway networks.

Cette thèse présente une étude sur la mesure des réseaux sociaux en ligne avec un accent particulier sur Twitter qui est l'un des plus grands réseaux sociaux. Twitter utilise exclusivement des liens dirigés entre les comptes. Cela rend le graphe social de Twitter beaucoup plus proche que Facebok du graphe social représentant les communications dans la vie réelle. Par conséquent, la compréhension de la structure du graphe social de Twitter et de la manière dont les informations se propagent dans le graphe est intéressant non seulement pour les informaticiens, mais aussi pour les chercheurs dans d'autres domaines, tels que la sociologie. Cependant, on sait peu de choses sur la propagation de l'information sur Twitter. / This thesis presents the measurement study of Online Social Networks focusing on Twitter. Twitter is one of the largest social networks using exclusively directed links among accounts. This makes the Twitter social graph much closer to the social graph supporting real life communications than, for instance, Facebook. Therefore, understanding the structure of the Twitter social graph and the way information propagates through it is interesting not only for computer scientists, but also for researchers in other fields, such as sociologists. However, littles is known about the information propagation in Twitter. In the first part, we present an in-depth study of the macroscopic structure of the Twitter social graph. In the second part, we study the propagation of the news media articles shared on Twitter. In the third part we present an experimental study of graph sampling.

Online social networks have become a staging ground for many modern movements, with the Arab Spring being the most prominent example. In an effort to understand and predict those movements, social media can be regarded as a valuable social sensor for disclosing underlying behaviors and patterns. To fully understand mass movement information propagation patterns in social networks, several problems need to be considered and addressed. Specifically, modeling mass movements that incorporate multiple spaces, a dynamic network structure, and misinformation propagation, can be exceptionally useful in understanding information propagation in social media. This dissertation explores four research problems underlying efforts to identify and track the adoption of mass movements in social media. First, how do mass movements become mobilized on Twitter, especially in a specific geographic area? Second, can we detect protest activity in social networks by observing group anomalies in graph? Third, how can we distinguish real movements from rumors or misinformation campaigns? and fourth, how can we infer the indicators of a specific type of protest, say climate related protest? A fundamental objective of this research has been to conduct a comprehensive study of how mass movement adoption functions in social networks. For example, it may cross multiple spaces, evolve with dynamic network structures, or consist of swift outbreaks or long term slowly evolving transmissions. In many cases, it may also be mixed with misinformation campaigns, either deliberate or in the form of rumors. Each of those issues requires the development of new mathematical models and algorithmic approaches such as those explored here. This work aims to facilitate advances in information propagation, group anomaly detection and misinformation distinction and, ultimately, help improve our understanding of mass movements and their adoption in social networks. / Ph. D.

The aim of this thesis is to articulate and defend a general notion of 'perspectives' and some of the ways that they relate to one another, in order to help to clarify one of the preliminary conceptual problems in cybernetics, namely, the relation between energy propagation (signal) and information propagation (message). The literature on this topic is meagre, although the literature relevant to it is too great to cover comprehensively. The approach closely follows the ideas of Thomas Kuhn and Paul Feyerabend in the philosophy of science. It is found that the perspective notion has possible uses other than that of signal and message, since the same arguments apply to a wide variety of conceptual and human situations. The concepts considered include: point of view, field space, overall view, three broad categories of perspective difference, compatible and incompatible perspectives, the effect of values and goals, and mutual sensitivity and relevance of perspective spaces. There are five chapters: the first introduces the perspective approach to the 'problem of meanings' and provides a brief introduction to the other four chapters; the second examines two fragments of the philosophical background; the third offers a relatively informal discussion of perspectives and perspective relativity; the fourth suggests an example of a terminology of perspectives (true to perspective relativity, not the only possible one); and the final chapter summarises some immediate results as well as suggesting some possible specialised applications, including political models, information retrieval and machine intelligence.

Context. Connected vehicles use sensors such as cameras or radars to collect data about surrounding environments automatically and share these data with each other or with road side infrastructure using short-range wireless communication. Due to the large amount of information generated, strategies are required to minimize information redundancy when important information is propagated among connected vehicles. Objectives. This research aims to develop an information propagation strategy in connected vehicle systems using software agent-based coordination strategies to reduce unnecessary message broadcast and message propagation delay. Methods. A review of related work is used to acquire a deep insight as well as knowledge of the state-of-the-art and the state-of-practice from relevant studies in the subject area. Based on the review of related work, we propose an agent-based coordination strategy for information propagation in connected vehicle systems, in which connected vehicles coordinate their message broadcast activities using auctions. After that, a simulation experiment is conducted to evaluate the proposed strategy by comparing it with existing representative strategies. Results. Results of simulation experiments and statistical tests show that the proposed agent-based coordination strategy manifest some improvements in reducing unnecessary message broadcast and message propagation delay compared to other strategies involved in the simulation experiments. Conclusions. In this research, we suggest a new strategy to manage the propagation of information in connected vehicle systems. According to the small scale simulation analysis, the use of auctions to select message transmitters enables our proposed strategy to achieve some improvements in reducing unnecessary message broadcast and propagation delay than existing strategies. Thus, with the help of our proposed strategy, unnecessary message broadcast can be minimized and the communication resources of connected vehicle systems can be utilized effectively. Also, important safety messages can be propagated to drivers faster, negative traffic events could be averted. / 0707708513

Connected Vehicle research has emerged as one of the highest priorities in the transportation systems because connected vehicle technology has the potential to improve safety, mobility, and environment for the current transportation systems. Various connected vehicle based applications have been identified and evaluated through various measurements to assess the performance of connected vehicle applications. However, most of these previous studies have used hypothetical study areas with simple networks for connected vehicle environment. This study represents connected vehicle environment in TRANSIMS to assess the performance of V2V communication applications in the realistic urban network. The communication duration rate and spatial-temporal dispersion of equipped vehicles are investigated to evaluate the capability of V2V communication based on the market penetration rate of equipped vehicles and wireless communication coverage in the whole study area. The area coverage level is used to assess the spatial-temporal dispersion of equipped vehicles for two study areas. The distance of incident information propagation and speed estimation error are used to measure the performance of event-driven and periodic applications based on different market penetration rates of equipped vehicles and wireless communication coverage in both morning peak and non-peak times. The wireless communication coverage is the major factor for event-driven application and the market penetration rate of equipped vehicles has more impact on the performance of periodic application. The required minimum levels of deployment for each application are determined for each scenario. These study findings will be useful for making decisions about investments on deployment of connected vehicle applications to improve the current transportation systems. Notably, event-driven applications can be reliably deployed in the initial stage of deployment despite the low level of market penetration of equipped vehicles. / Ph. D.

Graphs (or networks) are now omnipresent, infusing into many aspects of society. This dissertation contributes unified graph-based algorithms and models to help solve large-scale societal problems affecting millions of individuals' daily lives, from cyber-attacks involving malware to tobacco and alcohol addiction. The main thrusts of our research are: (1) Propagation-based Graph Mining Algorithms: We develop graph mining algorithms to propagate information between the nodes to infer important details about the unknown nodes. We present three examples: AESOP (patented) unearths malware lurking in people's computers with 99.61% true positive rate at 0.01% false positive rate; our application of ADAGE on malware detection (patent-pending) enables to detect malware in a streaming setting; and EDOCS (patent-pending) flags comment spammers among 197 thousand users on a social media platform accurately and preemptively. (2) Graph-induced Behavior Characterization: We derive new insights and knowledge that characterize certain behavior from graphs using statistical and algorithmic techniques. We present two examples: a study on identifying attributes of smoking and drinking abstinence and relapse from an addiction cessation social media community; and an exploratory analysis of how company insiders trade. Our work has already made impact to society: deployed by Symantec, AESOP is protecting over 120 million people worldwide from malware; EDOCS has been deployed by Yahoo and it guards multiple online communities from comment spammers.

Online social networks (OSNs) have seen a remarkable rise in the presence of automated social agents, or social bots. Social bots are the new computing viral, that are surreptitious and clever. What facilitates the creation of social agents is the massive human user-base and business-supportive operating model of social networks. These automated agents are injected by agencies, brands, individuals, and corporations to serve their work and purpose; utilising them for news and emergency communication, marketing, social activism, political campaigning, and even spam and spreading malicious content. Their influence was recently substantiated by coordinated social hacking and computational political propaganda. The thesis of my dissertation argues that automated agents exercise a profound impact on OSNs that transforms into an array of influence on our society and systems. However, latent or veiled, these agents can be successfully detected through measurement, feature extraction and finely tuned supervised learning models. The various types of automated agents can be further unravelled through unsupervised machine learning and natural language processing, to formally inform the populace of their existence and impact.

本文提出一供應鏈規劃(Supply Chain Planning, SCP)整合的簡明模型，該模型能夠協助晶圓代工公司達到供應鏈規劃整合的目的。模型內含兩個主要部份。一是三維供應鏈規劃網路暨資訊傳遞模型((簡稱三維立體模型)，另一個是適用於晶圓代工業的核心供應鏈規劃模型(簡稱規劃引擎)。 三維立體模型，它整合供應鏈內垂直與水平方向的參與者，同時也將時間軸上不同時程規劃(長、中、短期)一起併入模式考量範圍。根據公司參與的製造步驟，三維立體模型亦可彈性地由基本型擴充為擴張型。不論是基本型或是擴張型，各節點根據座標軸(coordinate)定義功能並提供服務，這種設計可以提高模式穩健度，減低因外界的變化而引發系統變更需求。系統也可以由座標幫助輕易找到可以提供服務的節點與資訊傳遞的控制(資訊傳遞規則)，資訊可以有序的傳遞分享。 在核心規劃引擎部份，針對晶圓代工產業在長、中、短期規劃需求，以及產業長生產前置時間時間的特性，設計隨時間變化參數適用於長、中期的線性規劃 (Linear Programming, LP) 模型與適用於短期規劃的啟發式 (heursitic ) 演算模型，配合三維立體模型所定義結構與資料傳遞規則，各時程(長、中、短期)製造階段節點皆可獲取必要資料並進一步以適當規劃法則求取同步與整合的規劃結果。 最後利用物件導向分析 (object-oriented analysis) 中順序圖 (sequence diagram)、狀態圖(state diagram)、與類別圖 (class diagram) 展示三維立體模型的系統應用架構(application framework)。 關鍵字：供應鏈規劃，規劃整合，資訊傳遞，線性規劃，物件導向分析，應用架構