Global ETD Search

1	Navigating campus: a geospatial approach to 3-D routing Jenkins, Jacob Luke January 1900 (has links) Master of Landscape Architecture / Department of Landscape Architecture/Regional and Community Planning / Howard Hahn / Evolving needs for universities, municipalities, and corporations demand more sustainable and efficient techniques for data management. Geographic Information Systems (GIS) enables decision makers to spatially analyze the built environment to better understand facility usage by running test scenarios to evaluate current efficiencies and identify opportunities for investment. This can only be conducted when data is organized and leveraged across many departments in a collaborative environment. Data organization through GIS encourages interdepartmental collaboration uniting all efforts on a common front. An organized system facilitates a working relationship between the university and the community of Manhattan increasing efficiency, developing sustainable practices, and enhancing the health and safety of Kansas State University and larger community. Efficiency is increased through automation of many current practices such as work requests and routine maintenance. Sustainable practices will be developed by generating self-guided campus tours and identifying area appropriate for bioswales. Lastly, safety will be enhanced throughout campus by increasing emergency response access, determining areas within buildings difficult to reach in emergency situations, and identifying unsafe areas on campus. Evolving needs for universities, municipalities, and corporations demand more sustainable and efficient techniques for data management. Geographic Information Systems (GIS) enables decision makers to spatially analyze the built environment to better understand facility usage by running test scenarios to evaluate current efficiencies and identify opportunities for investment. This can only be conducted when data is organized and leveraged across many departments in a collaborative environment. Data organization through GIS encourages interdepartmental collaboration uniting all efforts on a common front. An organized system facilitates a working relationship between the university and the community of Manhattan increasing efficiency, developing sustainable practices, and enhancing the health and safety of Kansas State University and larger community. Efficiency is increased through automation of many current practices such as work requests and routine maintenance. Sustainable practices will be developed by generating self-guided campus tours and identifying area appropriate for bioswales. Lastly, safety will be enhanced throughout campus by increasing emergency response access, determining areas within buildings difficult to reach in emergency situations, and identifying unsafe areas on campus. Optimizing data management for Kansas State University was conducted in three phases. First, a baseline assessment for facility management at Kansas State University was conducted through discussions with campus departments. Second, case study interviews and research was conducted with leaders in GIS management. Third, practices for geospatial data management were adapted and implemented for Kansas State University: the building of a centralized database, constructing a 3-dimensional routing network, and modeling a virtual campus in 3D. Geodesign Campus planning 3D modeling Facilities management Emergency response Network dataset Landscape Architecture (0390)
2	Application-Based Network Traffic Generator for Networking AI Model Development Alsulami, Khalil Ibrahim D 18 May 2021 (has links) No description available. Artificial Intelligence Communication Computer Engineering Computer Science Educational Software Educational Technology Electrical Engineering Information Science Information Systems Information Technology Systems Science Technical Communication Technology NS-3 Artificial Intelligent network traffic traffic generator traffic simulator LSTM AI classification PCAP traffic flow packets payload database traffic database AI network dataset AI-based network networking AI models AI algorithm Finding highest peaks
3	GIS-based Episode Reconstruction Using GPS Data for Activity Analysis and Route Choice Modeling / GIS-based Episode Reconstruction Using GPS Data Dalumpines, Ron 26 September 2014 (has links) Most transportation problems arise from individual travel decisions. In response, transportation researchers had been studying individual travel behavior – a growing trend that requires activity data at individual level. Global positioning systems (GPS) and geographical information systems (GIS) have been used to capture and process individual activity data, from determining activity locations to mapping routes to these locations. Potential applications of GPS data seem limitless but our tools and methods to make these data usable lags behind. In response to this need, this dissertation presents a GIS-based toolkit to automatically extract activity episodes from GPS data and derive information related to these episodes from additional data (e.g., road network, land use). The major emphasis of this dissertation is the development of a toolkit for extracting information associated with movements of individuals from GPS data. To be effective, the toolkit has been developed around three design principles: transferability, modularity, and scalability. Two substantive chapters focus on selected components of the toolkit (map-matching, mode detection); another for the entire toolkit. Final substantive chapter demonstrates the toolkit’s potential by comparing route choice models of work and shop trips using inputs generated by the toolkit. There are several tools and methods that capitalize on GPS data, developed within different problem domains. This dissertation contributes to that repository of tools and methods by presenting a suite of tools that can extract all possible information that can be derived from GPS data. Unlike existing tools cited in the transportation literature, the toolkit has been designed to be complete (covers preprocessing up to extracting route attributes), and can work with GPS data alone or in combination with additional data. Moreover, this dissertation contributes to our understanding of route choice decisions for work and shop trips by looking into the combined effects of route attributes and individual characteristics. / Dissertation / Doctor of Philosophy (PhD) GPS time use diary episode extraction multinomial logit travel behavior mode detection episode reconstruction GIS map-matching route choice path size logit potential path area scale estimation Python ArcGIS activity analysis trip reconstruction smartphone global positioning system geographic information system toolkit work trip shop trip potential activity location land use activity episode travel episode stop episode transferability scalability modularity scripting big data travel survey respondent burden preprocessing multipath error tracking purpose detection segmentation data filter data smoothing fuzzy logic neural network decision tree rule-based algorithm trajectory point road network network dataset gateway shortest path horizontal dilution of precision HDOP commonality factor mode transfer point Halifax Nova Scotia Space-Time Activity Research variance inflation factor shapefile comma-separated values traveling salesman problem data mining branch-and-bound algorithm pedestrian network alternative route observed route route efficiency route attributes distance time heading bearing duration acceleration latitude longitude coordinate overlay analysis intersect shopping module data logger walk likelihood ratio test classification table path generation kappa statistic degrees data collection transportation research automate framework ArcToolbox spatio-temporal navigation positioning trace path spatial data topology horizontal accuracy SPSS Stata spatial resolution temporal resolution household survey trip reporting proximity analysis DMTI Desktop Mapping Technologies Inc. road intersection route overlap left turn right turn location analysis time geography spatial statistics buffer analysis cycling bus transit public transportation GEOIDE AGILE data need raw data urban canyon endpoint data cleaning elevation satellite outliers automatic processing nearest node classifier classification method short trip multi-point

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