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 30 for “"Solution Spaces"”.
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Quantifying and summarizing tumor phylogeny solution spaces
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-08-01
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Product grammar : construction and exploring solution spaces
… in generative design systems. A mapping of a solution space is achieved by parameterizing the constraints of the problem in order to develop a feasible envelope of possibilities at the component and system level. Once parametric modeling begins, then a flexible hierarchical and associative …
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K-means landscapes: exploring clustering solution spaces using energy landscape theory
… cost function supports many possible clustering solutions, and location of low-valued clustering solutions can be challenging. Hence, the topography of the cost function surface is crucial to understanding K-means performance. We present the application of energy landscape theory to the K-means …
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Towards measuring attention allocation in model-based engineering teamwork
… using team attention in the problem and solution spaces. The concept of situational awareness and attention allocation has been studied in literature in the context of user interaction design for individuals or teams in areas where team members could be overwhelmed with information. …
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Experts and novices: Differences in their use of mental representation and metacognition in engineering design
… engineering designers navigate their problem and solution spaces. This empirical study investigated the mental representation and metacognitive regulation of student and professional engineers while they solve an engineering design problem. The intent is to gain a deeper insight in the differences …
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Multi-objective particle swarm optimisation: methods and applications.
… points of view and reach a set of compromised solutions among the di erent objectives. The presented research brings together recent advances in the eld of multi-objective optimisation and particle swarm optimisation raising several challenges. This is tackled from di erent aspects including …
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Theory and application of neural and graphical models in early cancer diagnostics
… Classes (MECs), which defines the size of solution spaces when attempting to learn a graphical model from data. Through our analysis, we show that the size of these MECs can be exponential with respect to features of the graph (such as average degree). We then switch contexts to address the …
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Optimal Electrodynamic Tether Phasing and Orbit-Raising Maneuvers
We present optimal solutions for a point-mass electrodynamic tether (EDT) performing phasing and orbit-raising maneuvers. An EDT is a conductive tether on the order of 20 km in length and uses a Lorentz force to provide propellantless thrust. We develop the optimal equations of motion using …
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Energy Harvesting from Human Motion for the Powering of Implantable, Wearable, and Peripheral Electronic Devices
… are studied in the context of the three types of solution spaces in implantable (inside the body), wearable (on the body), and peripheral (outside the body) devices. Specifically, it is studied whether heartbeats can power the pacemakers regulating the heartbeat; whether walking can power the …
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Meta-data to enhance case-based prediction.
… to influence user confidence on the delivered solutions. The reliability information, referred to as meta-data, is then used to enhance prediction accuracy. CBP is a strain of Case-Based Reasoning (CBR) that differs from the latter only in the solution feature which is a continuous value. …
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Improving Results of Differential Evolution Algorithm
… as optimisation problems. Due to their enormous solution spaces, optimisation problems frequently lie in class NP. In such cases, engineers and researchers have to rely on algorithms and techniques that can find sub-optimal solutions to these problems. One of the most dependable algorithms for …
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System architecture analysis and selection under uncertainty
… consider more than just Pareto Optimal solutions to avoid the unintentional exclusion of viable and possibly even desirable designs. 2. The introduction of a proximity based filtering technique that explicitly links the design and solution spaces. The intent here is preserve diverse …
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Capabilities Engineering:Promoting Change-Reduction and Constructing Change-Tolerant Systems
… strives to develop systems based on a fixed solution. This is a mostly unsuccessful approach as evidenced by the history of system failures. In contrast, we utilize Capabilities — functional abstractions that are neither as amorphous as user needs nor as rigid as system requirements — to …
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Design and analysis of genetic algorithms for two classes of spatial optimization
… simplifications to the problem before a solution can be attempted. These simplifications often include mandatory pre-processing of viable alternatives and reducing complicated coupled systems to simple objective functions, which typically must be separable and differentiable. Genetic …
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Transnationalizing Indian education: Diasporic networks, politics and participation
… intervention and advocacy. The diasporan 'solution' spaces link, collaborate, and draw ideas from international funding agencies, multilateral institutions, the Indian state, corporations, NGOs and think tanks. The advocacy ideas, as a result, are products of such multi-level influences.
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Clinical Cost-Effectiveness as a Novel Metric for Steering Emerging Medical Technology
… treatment alternative, LDD, was proposed as a solution-neutral, generalized concept, and technological factors were posited that influence parameters in the CEA. A one-way sensitivity analysis was conducted to verify the model and observe its most sensitive parameters. A probabilistic …
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Trilemma in Optimization for Time-critical Cyber-Physical Systems: Balancing Optimality, Generality, and Scalability
… symbolic operations and efficient exploration of solution spaces. Similarly, a novel scheduling approach for DAG-based task models minimizes worst-case end-to-end latency and time disparity through 1-opt solutions with polynomial runtime complexity, achieving up to 40\% performance gains over …
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A Geometric Approach for Generating Feasible Configurations of Robotic Manipulators
… which are now expected to deal with infinite solution spaces and difficult, nonlinear constraints. On the other hand, the addition of degrees of freedom in recent robot designs has enabled algorithms to search for locally optimal configurations with respect to some performance criteria in an …
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Algorithms for phylogenetic tree correction in species and cancer evolution
… and low quality of input data, leading to large solution spaces of equally plausible phylogenies. In this dissertation, we explore current limitations in both species and tumor phylogeny estimation, connecting similarities and highlighting key differences. We then put forward four new methods …
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An Artificial Honeybee Colony Algorithm to Quantify Adaptability via Resilience for Space System Architectures
… search for and generate resilient (or optimal) solutions to highly interconnected or nonlinear problems. The AHC is an agent-based algorithm that integrates pollination models, particle swarm dynamics, and mutualistic relations to generate new solution spaces and locate optimal or resilient …
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