Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 61 for “"acyclic graph"”.
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Explaining Regime Change: A Directed Acyclic Graph
… I build a Bayesian network (using a directed acyclic graph) based on theory from which I then derive testable hypotheses. I use discrete-time analysis to test two models using data for the dependent variable from the Democracy & Dictatorship Revisited Dataset (Cheibub, Gandhi, & Vreeland …
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Extracting the K best solutions from a valued and-or acyclic graph
… State Estimation algorithm, use a valued and-or acyclic graph to represent the possible estimates. These algorithms specifically use a valued smooth deterministic decomposable negation normal form (sd-DNNF) representation, a type of and-or acyclic graph. Prior work has focused on extracting …
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A Directed Acyclic Graph Demonstrating The Effects Of Population Aging On Saving And Interest Rates In Europe
… of the current literature into a directed acyclic graph (DAG) illustrating a theory of the impacts of population aging to European economies through the mechanisms of shrinking labor supplies and increasing dependency ratios. OLS regression models from the literature are then compared to …
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Doing time : inducing temporal graphs
… consider the problem of constructing a directed acyclic graph that encodes temporal relations found in a text. The unit of our analysis is a temporal segment, a fragment of text that maintains temporal coherence. The strength of our approach lies in its ability to simultaneously optimize pairwise …
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Self-stabilizing distributed algorithms for acyclic graphs
… processors in a distributed system of directed acyclic graph (DAG) topology and uses this information to build a shortest path routing table in each node in the system to all accessible nodes from that node. The second protocol determines the rank of the individual processors in a distributed …
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Structure learning in high-dimensional graphical models
… structure of undirected and directed (causal) graphical models in the high-dimensional setting. Structure learning in graphical models is a central problem in statistics with numerous applications including learning gene regulatory networks from RNA-seq data and learning the dependence …
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Influence of Social and Environmental Factors on FEMA Claims During Flood Disasters in St. Louis, MO.
… Missouri. It also explores the use of Directed Acyclic Graph (DAG) for variable selection, finding its limitations. Using publicly available ZIP Code Tabulation Area (ZCTA)-level data, the analysis examines this association and its variation by a set of environmental and social factors, which …
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A Model For Collaborative Creation And Ownership Of Digital Products
… history since creation in an immutable Directed Acyclic Graph (DAG) data structure. This history comprises digital content blocks used in its creation, including how they referenced each other in the development of the final digital product. Through referencing, credit attribution is achieved and …
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Minimal I-MAP MCMC for scalable structure discovery in causal DAG models
… in the maximum indegree of the true directed acyclic graph (DAG) of the BN. We here propose an alternative posterior approximation based on the observation that, if we incorporate empirical conditional independence tests, we can focus on a high-probability DAG associated with each order of the …
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Event-Driven Distributed Task Orchestration System with Applications to Automated PCB Design
… design structures the application as a directed acyclic graph (DAG) of microservices and achieves the following goals: decouples the stages of the design generation flow, supports flexible configuration and ordering of downstream stages, and brings the power of elastic compute from the cloud to …
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Optimal Inference for Distributed Detection
… architecture, and distributed detection by acyclic graph networks. In the conclusion we indicate several future research directions, which include possible generalizations of our optimization method and new research problems arising from each of the three applications considered.</p>
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Performance optimization and energy efficiency of big-data computing workflows
… a generalized problem with an arbitrary directed acyclic graph-structured workflow executed on virtual machines of multiple classes. The performance superiority of the proposed solution is illustrated by extensive simulation-based results in Hadoop/YARN in comparison with existing workflow mapping …
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Knowledge discovery and modeling in genomic databases
… S, it is always possible to construct a directed acyclic graph G such that the path for the actual coding region of S is in the set of all paths on G. Thus, the gene detection problem is reduced to the analysis of paths in the graph G. A dynamic programming algorithm is employed by GeneScout to …
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Geometric Deep Learning for Healthcare Applications
This thesis explores the application of Graph Neural Networks (GNNs), a subset of Geometric Deep Learning methods, for medical image analysis and causal structure learning. Tracking the progression of pathologies in chest radiography poses several challenges in anatomical motion estimation and …
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Towards Efficient Autonomous Vehicle Systems: A Multi-Layer Approach
… system layer, a novel Extended Conflict Directed Graph (ECDG) model is introduced to enable dynamic lane assignment in unsignalized intersection management, improving flexibility and traffic flow coordination. A scheduling algorithm based on breadth-first search achieves up to 16.3% reduction in …
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Maternal Fat Intake during Pregnancy and Breastfeeding Initiation
… with blockwise data entry based on a directed acyclic graph (DAG) created to conceptualize the hypothesized relationships and potential confounders. Results: Contrary to our hypothesis, higher maternal fat (>35% fat), compared to ≤35% fat, was associated with a higher odds of breastfeeding …
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Global EDF Scheduling for Parallel Real-Time Tasks
… Each task can be represented by a directed acyclic graph (DAG) where nodes represent computational work and edges represent dependences between nodes. In this model, we prove that GEDF provides a capacity augmentation bound of 4-2/m and a resource augmentation bound of 2-1/m. The capacity …
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Depicting variable elimination with Bayesian networks
This thesis presents a novel graphical representation of variable elimination in discrete Bayesian networks (BNs) utilizing the BN’s directed acyclic graph (DAG) component. This includes methods representing both multiplication and marginalization operations. This graphical representation is …
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An Empirical Study on Sum-Product Networks Structure Learning and Deep Convolutional Sum-Product Networks
… A DCSPN consists of a tree structure (a directed acyclic graph) coupled with parameters of the structure. Given that DCSPNs are in their infancy, many open questions remain regarding the properties and topology of their tree structure. As our second main contribution, we undertake three …
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A multimedia authoring tool for Web based learning
… and temporal constraints in a page. A Concept Graph Model, which is a directed acyclic graph is used to organise a web based presentation of the courseware. The authoring and presentation tool kits developed as part of this thesis work are evaluated by applying them to a real life problem. In …
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