Fine-tuning large language models (LLMs) for domain specific tasks is often an expensive resource intensive procedure requiring large computing and memory resources. In this paper, We introduce finetuned-leetcode-Code...
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Predicting customer purchase intent is crucial for modern businesses in order to improve engagement, refine marketing strategies, and increase revenue. Conventional rule-based systems encounter difficulties with dynam...
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Assessment of student responses during viva examinations presents challenges in terms of consistency, objectivity, and efficiency. Traditional methods rely on manual evaluation, which can be lengthy and prone to human...
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The swift progression of deepfake-generating technologies has elicited much apprehension about their potential misuse in digital media, necessitating the development of efficient detection methods. This research aims ...
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With the expansion of social media and advanced stages, the spread of fake news has ended up a noteworthy societal issue. This paper presents a comprehensive outline of machine learning strategies utilized for the det...
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We conduct an extensive study on deep learning-based spectrum sharing to resolve dynamic resource allocation in 6G cognitive radio networks in this paper. The approach uses modern machine learning models to optimize s...
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As biometric systems become increasingly relied on secure authentication, concerns about their susceptibility to Face Presentation Attacks (FPAs) have intensified. This paper introduces a framework for detection of im...
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作者:
Agarwal, EkanshZhang, XiongLuo, NingDept. of Engineering
College of Engineering and Computer Science Texas A&M Univ.–Corpus Christi Corpus ChristiTX United States Dept. of Civil
Architectural and Environmental Engineering Missouri Univ. of Science and Technology RollaMO United States
This study focuses on modeling a rigid pavement slab on expansive soil in extreme climates to understand the interaction between weather, pavement, and soil. Lightweight superstructures such as pavements are particula...
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ISBN:
(数字)9780784485996
This study focuses on modeling a rigid pavement slab on expansive soil in extreme climates to understand the interaction between weather, pavement, and soil. Lightweight superstructures such as pavements are particularly prone to damage due to the differential settlement of expansive soils. In the context of climate change, the occurrence of severe droughts followed by intense rainfall has risen, causing severe impacts on crack initiation and development, and thus infiltration patterns in the structures built on expansive soils. Pavements are typically designed for a limited lifespan, and early failure may occur if climate change is not considered during design. This is especially important in coastal areas when coastal flooding becomes more frequent. The interplay between climates, soils, and pavements leads to a spatial and temporal change in soil moisture and even soil structure, causing significant variations of volume change. Despite the dominant impact of expansive soils on pavement systems, a deep understanding of their role in pavement structural behavior remains challenging to both the researchers and the practitioners. This paper addresses this gap through a comprehensive numerical study using two-dimensional (2D) finite element modeling. We adopted the unsaturated soil constitutive relationship to understand the stress changes during the expansion and shrinkage of expansive soil. We employed four user-defined subroutines in ABAQUS to perform a coupled hydro-mechanical stress analysis. The study uses historical climate events as a reference to assess the impact of climate events on pavements. Mechanical, hydraulic, and soil-vegetation-atmosphere (SVA) boundary conditions are considered. The numerical findings highlight the vulnerability of pavements founded on expansive soils to climate change-induced events and indicate that a coupled hydro-climate-geotechnical analysis is necessary. Unprecedented climatic events lead to more uneven settling of pavements
Phishing attacks remain a critical threat to cybersecurity, leveraging deception to steal sensitive information from individuals and organizations. Traditional detection methods often fail to keep up with evolving phi...
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This paper explores the application of game theoretic approaches to load balancing across edge nodes within distributed computing systems. Focusing on a non-cooperative game model, we aim to enhance system efficiency ...
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