92 research outputs found

    A Location-Aware Middleware Framework for Collaborative Visual Information Discovery and Retrieval

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    This work addresses the problem of scalable location-aware distributed indexing to enable the leveraging of collaborative effort for the construction and maintenance of world-scale visual maps and models which could support numerous activities including navigation, visual localization, persistent surveillance, structure from motion, and hazard or disaster detection. Current distributed approaches to mapping and modeling fail to incorporate global geospatial addressing and are limited in their functionality to customize search. Our solution is a peer-to-peer middleware framework based on XOR distance routing which employs a Hilbert Space curve addressing scheme in a novel distributed geographic index. This allows for a universal addressing scheme supporting publish and search in dynamic environments while ensuring global availability of the model and scalability with respect to geographic size and number of users. The framework is evaluated using large-scale network simulations and a search application that supports visual navigation in real-world experiments

    Modeling of Dynamic Hydrologic Connectivity: How Do Depressions Affect the Modeling of Hydrologic Processes?

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    Traditional delineation and modeling methods do not consider the spatial arrangement and dynamic threshold control of surface depressions. Instead, full structural hydrologic connectivity, uniform well-connected drainage networks, and an invariant contributing area are often assumed. In reality, depressions play an important role in quantifying hydrologic connectivity and outlet discharge. Current literature lacks a preferred foundation and tools to identify and quantify hydrologic connectivity on depression-dominated landscapes. Therefore, the objectives of this dissertation research are to (1) develop a new procedure to analyze functional hydrologic connectivity related to surface topography, specifically in depression-dominated areas; (2) evaluate the impacts of the puddle-to-puddle (P2P) filling-spilling-merging processes and dynamic hydrologic connectivity on watershed outlet discharge; and (3) address the combined effect of topographic depressions and wetland functions on hydrologic connectivity and watershed outlet discharge. To accomplish these objectives, three studies are conducted where (1) a new procedure was developed for identifying and analyzing hydrologic connectivity in depression-dominated areas; (2) an improved HEC-HMS modeling framework was developed by incorporating a depression threshold control proxy; and (3) a new hydrologic categorization of wetlands was adapted for watershed-scale hydrologic modeling. The major findings from these studies include: (1) traditional delineation methods may fail to represent the realistic contributing area (CA), especially for depression-dominated surfaces; (2) the consideration of the P2P processes and dynamic contributing area is essential for hydrologic modeling of depression-dominated areas; and (3) different wetland types have unique characteristics of contributing area and depression storage that are not simulated in detail in most traditional models. The conclusions from this research also provides useful information for future studies relating to sediment and pollutant transport in depression-dominated regions, ecological interactions in wetlands, and anthropogenic effects on hydrologic processes.North Dakota State University. Department of Civil and Environmental EngineeringNorth Dakota Water Resources Research InstituteNational Science Foundation Established Program to Stimulate Competitive Research (NSF EPSCoR, Grant No. IIA-1355466

    Peer-to-peer-based file-sharing beyond the dichotomy of 'downloading is theft' vs. 'information wants to be free': How Swedish file-sharers motivate their action

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    This thesis aims to offer a comprehensive analysis of peer-to-peer based file-sharing by focusing on the discourses about use, agency and motivation involved, and how they interrelate with the infrastructural properties of file-sharing. Peer-to-peer-based file-sharing is here defined as the unrestricted duplication of digitised media content between autonomous end nodes on the Internet. It has become an extremely popular pastime, largely involving music, film, games and other media which is copied without the permission of the copyright holders. Due to its illegality, the popular understanding of the phenomenon tends to overstate its conflictual elements, framing it within a legalistic 'copyfight'. This is most markedly manifested in the dichotomised image of file-sharers as 'pirates' allegedly opposed to the entertainment industry. The thesis is an attempt to counter this dichotomy by using a more heterodox synthesis of perspectives, aiming to assimilate the phenomenon's complex intermingling of technological, infrastructural, economic and political factors. The geographic context of this study is Sweden, a country characterised by early broadband penetration and subsequently widespread unrestricted file-sharing, paralleled by a lively and well-informed public debate. This gives geographic specificity and further context to the file sharers' own justificatory discourses, serving to highlight and problematise some principal assumptions about the phenomenon. The thesis thus serves as a geographically contained case study which will have analytical implications outside of its immediate local context, and as an inquiry into two aspects of file-sharer argumentation: the ontological understandings of digital technology and the notion of agency. These, in turn, relate to particular forms of sociality in late modernity. Although the agencies and normative forces involved are innumerable, controversies about agency tend to order themselves in a more comprehensive way, as they are appropriated discursively. The invocation to agency that is found in the justificatory discourses - both in the public debate and among individual respondents - thus allows for a more productive and critically attentive understanding of the phenomenon than previously

    Task Planner for Simultaneous Fulfillment of Operational, Geometric and Uncertainty-Reduction Goals

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    Our ultimate goal in robot planning is to develop a planner which can create complete assembly plans given as input a high level description of assembly goals, geometric models of the components of the assembly, and a description of the capabilities of the work cell (including the robot and the sensory system). In this paper, we introduce SPAR, a planning system which reasons about high level operational goals, geometric goals and uncertainty-reduction goals in order to create assembly plans which consist of manipulations as well as sensory operations when appropriate. Operational planning is done using a nonlinear, constraint posting planner. Geometric planning is accomplished by constraining the execution of operations in the plan so that geometric goals are satisfied, or, if the geometric configuration of the world prevents this, by introducing new operations into the plan with the appropriate constraints. When the uncertainty in the world description exceeds that specified by the uncertainty-reduction goals, SPAR introduces either sensing operations or manipulations to reduce that uncertainty to acceptable levels. If SPAR cannot find a way to sufficiently reduce uncertainties, it does not abandon the plan. Instead, it augments the plan with sensing operations to be used to verify the execution of the action, and, when possible, posts possible error recovery plans, although at this point, the verification operations and recovery plans are predefined

    Semantic Routed Network for Distributed Search Engines

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    Searching for textual information has become an important activity on the web. To satisfy the rising demand and user expectations, search systems should be fast, scalable and deliver relevant results. To decide which objects should be retrieved, search systems should compare holistic meanings of queries and text document objects, as perceived by humans. Existing techniques do not enable correct comparison of composite holistic meanings like: "evidences on role of DR2 gene in development of diabetes in Caucasian population", which is composed of multiple elementary meanings: "evidence", "DR2 gene", etc. Thus these techniques can not discern objects that have a common set of keywords but convey different meanings. Hence we need new methods to compare composite meanings for superior search quality. In distributed search engines, for scalability, speed and efficiency, index entries should be systematically distributed across multiple index-server nodes based on the meaning of the objects. Furthermore, queries should be selectively sent to those index nodes which have relevant entries. This requires an overlay Semantic Routed Network which will route messages, based on meaning. This network will consist of fast response networking appliances called semantic routers. These appliances need to: (a) carry out sophisticated meaning comparison computations at high speed; and (b) have the right kind of behavior to automatically organize an optimal index system. This dissertation presents the following artifacts that enable the above requirements: (1) An algebraic theory, a design of a data structure and related techniques to efficiently compare composite meanings. (2) Algorithms and accelerator architectures for high speed meaning comparisons inside semantic routers and index-server nodes. (3) An overlay network to deliver search queries to the index nodes based on meanings. (4) Algorithms to construct a self-organizing, distributed meaning based index system. The proposed techniques can compare composite meanings ~105 times faster than an equivalent software code and existing hardware designs. Whereas, the proposed index organization approach can lead to 33% savings in number of servers and power consumption in a model search engine having 700,000 servers. Therefore, using all these techniques, it is possible to design a Semantic Routed Network which has a potential to improve search results and response time, while saving resources

    Distributed Algorithms for Peer-to-Peer Energy Trading

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    A S the proliferation of the ’sharing economy’ increases, its phenomenon is actively extending to the power grid, where energy consumers are motivated to use, produce, trade or share energy with the main grid and themselves. To optimise the potential of this changing era in smart grid, considering the complexity requirements of the individual distributed connected components, a distributed coordination algorithm is required to manage the large influx of energy as well as the altruistic goal of diverse energy producers. Furthermore, a trading platform is actively needed to implement these distributed algorithms to match the prosumers, coordinate their resources and maximise their utilities for increased profits and cost savings. This research investigates distributed algorithms for peer-to-peer energy trading and sharing (P2P-ETS) to facilitate discovery, communication and utility maximisation of peers who are trading energy in a P2P fashion. To begin, a four-layer system architectural model is proposed to categorise the key elements and technologies associated with the P2P-ETS. Then, constrained by as few assumptions as possible, while showing promising performance and key metrics, three distributed algorithms are developed to facilitate discovery, peer’s matching, data routing, energy transfer, and utility maximisation of the trading entities. These algorithms utilise only local information to solve the problem with promising results, complementing their presentation with simulations that demonstrate their effectiveness over imperfect communication links. Finally, based on these distributed algorithms, a software platform is developed to support the pairing of prosumers on the P2P-ETS platform. A case study based on real microgrid data is used to verify the performance of the platform which demonstrate increase in local energy consumption. Simulation results show that the developed platform is able to balance local generation and consumption and increase cost savings of 45% for prosumers that trade energy among themselves compared to trading with the power grid. This savings however varies depending on the participants on the platform

    Transforming scientific research and development in precision agriculture : the case of hyperspectral sensing and imaging : a thesis presented in partial fulfilment of the requirements for the degree of Doctor in Philosophy in Agriculture at Massey University, Manawatū, New Zealand. EMBARGOED until 30 September 2023.

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    Embargoed until 30 September 2023There has been increasing social and academic debate in recent times surrounding the arrival of agricultural big data. Capturing and responding to real world variability is a defining objective of the rapidly evolving field of precision agriculture (PA). While data have been central to knowledge-making in the field since its inception in the 1980s, research has largely operated in a data-scarce environment, constrained by time-consuming and expensive data collection methods. While there is a rich tradition of studying scientific practice within laboratories in other fields, PA researchers have rarely been the explicit focal point of detailed empirical studies, especially in the laboratory setting. The purpose of this thesis is to contribute to new knowledge of the influence of big data technologies through an ethnographic exploration of a working PA laboratory. The researcher spent over 30 months embedded as a participant observer of a small PA laboratory, where researchers work with nascent data rich remote sensing technologies. To address the research question: “How do the characteristics of technological assemblages affect PA research and development?” the ethnographic case study systematically identifies and responds to the challenges and opportunities faced by the science team as they adapt their scientific processes and resources to refine value from a new data ecosystem. The study describes the ontological characteristics of airborne hyperspectral sensing and imaging data employed by PA researchers. Observations of the researchers at work lead to a previously undescribed shift in the science process, where effort moves from the planning and performance of the data collection stage to the data processing and analysis stage. The thesis develops an argument that changing data characteristics are central to this shift in the scientific method researchers are employing to refine knowledge and value from research projects. Importantly, the study reveals that while researchers are working in a rapidly changing environment, there is little reflection on the implications of these changes on the practice of science-making. The study also identifies a disjunction to how science is done in the field, and what is reported. We discover that the practices that provide disciplinary ways of doing science are not established in this field and moments to learn are siloed because of commercial constraints the commercial structures imposed in this case study of contemporary PA research
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