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.
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Showing 1 to 20 of 29 for “"artificial intelligence and machine learning"”.
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Artificial intelligence and machine learning : current applications in real estate
Real estate meets machine learning: real contribution or just hype? Creating and managing the built environment is a complicated task fraught with difficult decisions, challenging relationships, and a multitude of variables. Today's technology experts are building computers and software that can …
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Artificial Intelligence and Machine Learning Capabilities and Application Programming Interfaces at Amazon, Google, and Microsoft
With the continuous development of artificial intelligence (AI) and machine learning (ML), cloudbased AI and ML have been hot in recent years. The trend is that cloud-based services and products have become a strategic weapon for giant tech companies. However, each major manufacturer's competitive …
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Machine Learning in Consumer Credit: Legal, Economic, Ethical & Policy Implications
… plays a vital role in economic opportunity and social mobility, yet it has long been plagued by inefficiencies, inequalities, and inadequate regulatory protection. As consumer credit markets evolve in the 21st century, the integration of artificial intelligence and machine learning offers …
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Semi-supervised classification of social media posts : identifying sex-industry posts to enable better support for those experiencing sex-trafficking
Social media is both helpful and harmful to the work against sex trafficking. On one hand, social workers carefully use social media to support individuals experiencing sex trafficking. On the other hand, traffickers use social media to groom and recruit individuals into trafficking situations. …
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Computing the Social: How Capitalism and Taste Shape Computational Social Science
The contemporary prevalence of artificial intelligence and machine learning methods has resulted in a rich literature on the factors that shape computational research. Based on 24 months of digital ethnography of a university laboratory and in-depth interviews with its members, this dissertation …
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Evaluating Runtime Monitoring for Reinforcement Learning-Based Flight Control
… in aviation, especially as advancements in artificial intelligence and machine learning (AI/ML) trend upwards. Reinforcement learning is becoming more common in aerospace applications due to the ability to improve these models through training. While models such as reinforcement learning …
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AI-driven methods for resiliency and security assessment: the case for autonomous driving system and HPC storage system
… exploration, transportation, scientific study, and manufacturing. With the advances in computation technologies, computing systems have become ever more complex. Due to the system’s complexity, it is increasingly hard for humans operators to monitor, assess, and manage the system directly. …
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The Politics of Scale and Scaling in Chinese Governance and Venture Capitalism
… entrepreneurs, venture capital investors (VCs), and local government officials, this dissertation investigates the intersection between Chinese governance, venture capitalism, and "big data"-driven technologies. Through a parallel study of how scale and scaling feature in China's nation building …
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A strategic perspective on the commercialization of artificial intelligence : a socio-technical analysis
Many companies are increasing their focus on Artificial Intelligence as they incorporate Machine Learning and Cognitive technologies into their current offerings. Industries ranging from healthcare, pharmaceuticals, finance, automotive, retail, manufacturing and so many others are all trying to …
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Rethinking Serverless for Machine Learning Inference
In the era of artificial intelligence and machine learning, AI/ML inference tasks have become exceedingly popular. However, executing these workloads on dedicated hardware may not be feasible for many users due to high maintenance costs, varying load patterns, and time to production. Furthermore, …
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AI-Driven Suitability Modeling for Sustainable Olive Cultivation: An Environmental Assessment in a Changing Climate
… it." This idea captures the essence of using artificial intelligence (AI) to shape sustainable agricultural futures in a world facing accelerating climate change, resource depletion, and land degradation. Key crops can be made more resilient through effective frameworks that combine …
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Leave the Features: Take the Cannoli
<p>Programming languages like Python, JavaScript, and Ruby are becoming increasingly popular due to their dynamic capabilities. These languages are often much easier to learn than other, statically type checked, languages such as C++ or Rust. Unfortunately, these dynamic languages come at the cost …
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Improving project timelines using Al / ML to detect forecasting errors
… on the creation of a novel tool to detect and flag potential errors within Amgen's capacity management forecast data, in an automated manner using statistical analysis, artificial intelligence and machine learning. User interaction allows the tool to learn from experience, improving over …
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Mass production readiness of a hardware start-up : assessing and improving product designs for manufacturing and assembly
The US food and restaurant industry is witnessing a step change due to recent advancements in smart automation. Increasing labor costs, rising living costs and shortage of skilled labor is forcing restaurateurs to look for alternatives to remain in operation and maintain profit margins. Industrial …
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Application of Neural Networks to Inverter-Based Resources
… the deployment of sensors in hardware equipment and advanced metering infrastructure, system operators have access to unprecedented amounts of data. Simultaneously, grid-connected power electronics technology has had a large impact on the way electrical energy is generated, transmitted, and …
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Artificial neural networks and the cross-section of equity returns: identifying nonlinear opportunities on the Johannesburg Stock Exchange
This study investigates the potential of Artificial Neural Networks (ANNs) to forecast stock returns on the Johannesburg Stock Exchange (JSE) using fundamental and technical factors. The optimal neural network architecture is explored, considering varying model depths and node counts. The …
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Automatic Co-Synthesis of Hardware and Software Safety Monitors for Embedded Systems
Embedded systems have become pervasive and increasingly complex, especially in modern applications such as self-driving vehicles, where safety requires both accurate functionality and real-time guarantees. However, the complexity and the integration of artificial intelligence and machine learning …
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Probing the Mechanisms of Reinforcement Learning: Reinforcement Learning, Ventral Striatal Astrocytes, and the Dynamic Coordination of Information Seeking with Learning
While reinforcement learning has been a vital component in artificial intelligence and machine learning, there exist many open questions about its implementations and how to improve them, in both minds and machines. Among these are i) the contribution of non-neuronal cell types to reinforcement …
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Automatic Chest X-rays Analysis using Statistical Machine Learning Strategies
… every year. Even though it is preventable and curable, it remains a major threat to humanity that needs to be taken care of. It is often diagnosed in developed countries using approaches such as sputum smear microscopy and culture methods. However, since these approaches are rather …
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