06472 Abstracts Collection - XQuery Implementation Paradigms

From 19.11.2006 to 22.11.2006, the Dagstuhl Seminar 06472 ``XQuery Implementation Paradigms'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

The material politics of smart building energy management: A view from Sydney\u27s commercial office space

The potential of cities in leveraging energy transformation is increasingly recognised, with a growing focus on urban built environments. In this paper we focus on smart building energy management as an increasingly pivotal material means through which energy transformation comes to matter in cities, and through which buildings are politicised in the negotiation of energy transformation. We advance a material political analysis of the case of Sydney\u27s premium commercial office building sector to explore how such buildings are conferred with political capacity. We explicitly extend this material politics framework to pluralise the \u27whereabouts\u27 of the politics of energy transformation, expanding recognition of the sites and moments of negotiation through which these politics are enacted, authority shaped, and where trajectories of energy transformation begin to be fashioned. Drawing on this extended conception of politics, the paper traces how the political capacity of buildings comes to matter through smart building energy management platforms as they are negotiated through the context of Sydney\u27s policy settings, the political-economy of the top tier commercial office sector, and building management cultures. We conclude with observations on how smart building energy management platforms might contribute to the shaping of particular trajectories, possibilities and limits for energy transformation advanced through the built environment

Toward a query language for organizational processes

Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (leaves 99-100).by Henry Tang.S.B.and M.Eng

A Peer-reviewed Newspaper About_ Datafied Research

An examination of the implications of datafication for research: to investigate and propose actions that push against the limits of today’s pervasive quantification of life, work, and play. Publication resulting from research workshop at School of Creative Media, City University of Hong Kong, organised in collaboration with School of Creative Media, City University of Hong Kong, and transmediale festival of art and digital culture, Berlin

Developing the Fringe Routing Protocol

An ISP style network often has a particular traffic pattern not typically seen in other networks and which is a direct result of the ISP’s purpose, to connect internal clients with a high speed external link. Such a network is likely to consist of a backbone with the clients on one ‘side’ and one or more external links on the other. Most traffic on the network moves between an internal client and the external world via the backbone. But what about traffic between two clients of the ISP? Typical routing protocols will find the ‘best’ path between the two gateway routers at the edge of the client stub networks. As these routers connect the stubs to the ISP core, this route should be entirely within the ISP network. Ideally, from the ISP point of view, this traffic will go up to the backbone and down again but it is possible that it may find another route along a redundant backup path. Don Stokes of Knossos Networks has developed a protocol to sit on the client fringes of this ISP style of network. It is based on the distance vector algorithm and is intended to be subordinate to the existing interior gateway protocol running on the ISPs backbone. It manipulates the route cost calculation so that paths towards the backbone become very cheap and paths away from the backbone become expensive. This forces traffic in the preferred direction unless the backup path ‘shortcut’ is very attractive or the backbone link has disappeared. It is the analysis and development of the fringe routing protocol that forms the content of this ME thesis

Run-time compilation techniques for wireless sensor networks

Wireless sensor networks research in the past decade has seen substantial initiative,support and potential. The true adoption and deployment of such technology is highly dependent on the workforce available to implement such solutions. However, embedded systems programming for severely resource constrained devices, such as those used in typical wireless sensor networks (with tens of kilobytes of program space and around ten kilobytes of memory), is a daunting task which is usually left for experienced embedded developers.Recent initiative to support higher level programming abstractions for wireless sensor networks by utilizing a Java programming paradigm for resource constrained devices demonstrates the development benefits achieved. However, results have shown that an interpreter approach greatly suffers from execution overheads. Run-time compilation techniques are often used in traditional computing to make up for such execution overheads. However, the general consensus in the field is that run-time compilation techniques are either impractical, impossible, complex, or resource hungry for such resource limited devices.In this thesis, I propose techniques to enable run-time compilation for such severely resource constrained devices. More so, I show not only that run-time compilation is in fact both practical and possible by using simple techniques which do not require any more resources than that of interpreters, but also that run-time compilation substantially increases execution efficiency when compared to an interpreter

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining

Data-Driven Framework for Understanding & Modeling Ride-Sourcing Transportation Systems

Ride-sourcing transportation services offered by transportation network companies (TNCs) like Uber and Lyft are disrupting the transportation landscape. The growing demand on these services, along with their potential short and long-term impacts on the environment, society, and infrastructure emphasize the need to further understand the ride-sourcing system. There were no sufficient data to fully understand the system and integrate it within regional multimodal transportation frameworks. This can be attributed to commercial and competition reasons, given the technology-enabled and innovative nature of the system. Recently, in 2019, the City of Chicago the released an extensive and complete ride-sourcing trip-level data for all trips made within the city since November 1, 2018. The data comprises the trip ends (pick-up and drop-off locations), trip timestamps, trip length and duration, fare including tipping amounts, and whether the trip was authorized to be shared (pooled) with another passenger or not. Therefore, the main goal of this dissertation is to develop a comprehensive data-driven framework to understand and model the system using this data from Chicago, in a reproducible and transferable fashion. Using data fusion approach, sociodemographic, economic, parking supply, transit availability and accessibility, built environment and crime data are collected from open sources to develop this framework. The framework is predicated on three pillars of analytics: (1) explorative and descriptive analytics, (2) diagnostic analytics, and (3) predictive analytics. The dissertation research framework also provides a guide on the key spatial and behavioral explanatory variables shaping the utility of the mode, driving the demand, and governing the interdependencies between the demand’s willingness to share and surge price. Thus, the key findings can be readily challenged, verified, and utilized in different geographies. In the explorative and descriptive analytics, the ride-sourcing system’s spatial and temporal dimensions of the system are analyzed to achieve two objectives: (1) explore, reveal, and assess the significance of spatial effects, i.e., spatial dependence and heterogeneity, in the system behavior, and (2) develop a behavioral market segmentation and trend mining of the willingness to share. This is linked to the diagnostic analytics layer, as the revealed spatial effects motivates the adoption of spatial econometric models to analytically identify the ride-sourcing system determinants. Multiple linear regression (MLR) is used as a benchmark model against spatial error model (SEM), spatially lagged X (SLX) model, and geographically weighted regression (GWR) model. Two innovative modeling constructs are introduced deal with the ride-sourcing system’s spatial effects and multicollinearity: (1) Calibrated Spatially Lagged X Ridge Model (CSLXR) and Calibrated Geographically Weighted Ridge Regression (CGWRR) in the diagnostic analytics layer. The identified determinants in the diagnostic analytics layer are then fed into the predictive analytics one to develop an interpretable machine learning (ML) modeling framework. The system’s annual average weekday origin-destination (AAWD OD) flow is modeled using the following state-of-the-art ML models: (1) Multilayer Perceptron (MLP) Regression, (2) Support Vector Machines Regression (SVR), and (3) Tree-based ensemble learning methods, i.e., Random Forest Regression (RFR) and Extreme Gradient Boosting (XGBoost). The innovative modeling construct of CGWRR developed in the diagnostic analytics is then validated in a predictive context and is found to outperform the state-of-the-art ML models in terms of testing score of 0.914, in comparison to 0.906 for XGBoost, 0.84 for RFR, 0.89 for SVR, and 0.86 for MLP. The CGWRR exhibits outperformance as well in terms of the root mean squared error (RMSE) and mean average error (MAE). The findings of this dissertation partially bridge the gap between the practice and the research on ride-sourcing transportation systems understanding and integration. The empirical findings made in the descriptive and explorative analytics can be further utilized by regional agencies to fill practice and policymaking gaps on regulating ride-sourcing services using corridor or cordon toll, optimally allocating standing areas to minimize deadheading, especially during off-peak periods, and promoting the ride-share willingness in disadvantage communities. The CGWRR provides a reliable modeling and simulation tool to researchers and practitioners to integrate the ride-sourcing system in multimodal transportation modeling frameworks, simulation testbed for testing long-range impacts of policies on ride-sourcing, like improved transit supply, congestions pricing, or increased parking rates, and to plan ahead for similar futuristic transportation modes, like the shared autonomous vehicles