book

Artificial Intelligence

Name: Artificial Intelligence
ISBN: 9783111344171

by Leonidas Deligiannidis, George Dimitoglou, Hamid Arabnia

August 2024

Intermediate to advanced

444 pages

15h 37m

English

De Gruyter

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Machine learning (ML)
Omobayo Ayokunle Esan, Munienge Mbodila, Patrick Mukeninay Madimba Detection of lesions in breast image using median filtering and convolutional neural networks1 Introduction2 Background3 Method4 Experimental evaluations and results5 ConclusionMartin Roa-Villescas, Jin-Guo Liu, Patrick W. A. Wijnings, Sander Stuijk, Henk Corporaal Pushing the boundaries of probabilistic inference through message contraction optimization1 Introduction2 Inference in junction trees3 Message contraction optimization4 A metaprogramming-based inference framework5 Experimental evaluation6 Discussion7 ConclusionDarshan Nayak, Abhijot Bedi, David Degbor, Shelley Zhang, Eugene Chabot Facilitating cooperative missions through information sharing in heterogeneous agent teams1 Introduction2 RCRS agent rescue testbed and sample agents3 Role of communication in decision-making4 Communication among heterogeneous agents5 Communication among homogeneous agents6 Experimentation setup7 Results8 Conclusion and future workSait Alp, Taymaz Akan, Mohammad Alfrad Nobel Bhuiyan Transferring knowledge: CNNs in Martian surface image classification1 Introduction2 Proposed approach3 Experimental results and discussion4 ConclusionAcknowledgmentAlireza Bagheri Rajeoni, Breanna Pederson, Ali Firooz, Hamed Abdollahi, Andrew K. Smith, Daniel G. Clair, Susan M. Lessner, Homayoun Valafar Vascular system segmentation using deep learning1 Introduction2 Background and methods3 Results4 Discussion and future work5 ConclusionAfsaneh Shams, Kyle Becker, Drew Becker, Soheyla Amirian, Khaled Rasheed Evolutionary CNN-based architectures with attention mechanisms for enhanced image classification1 Introduction2 Related work3 Methodology4 Dataset5 Experiments6 Conclusion and future work
Convolutional neural network (CNN)
Md Mahmudur Rahman, Bikesh Regmi Multi-label concept detection in imaging entities of biomedical literature leveraging deep learning-based classification and object detection1 Introduction2 Related work3 Multi-label classification of concepts4 Concept detection as region-of-interests (ROIs)5 Experiments6 Result analysis7 ConclusionBeilei Zhu, Chandrasekar Vuppalapati Revolutionizing supply chain dynamics: deep meta-learning and multi-task learning for enhanced predictive insights1 Introduction2 Enhancing adaptability in supply chain management: Integrating mechanistic and probabilistic meta-learning approaches3 Meta-learning algorithms for addressing data dynamics in supply chain management4 Black box approach5 Optimization-based meta-learning6 Optimize based meta-learning implementation and results for supply chain regression use case7 A deep dive into supply chain product classification: meta-learning in master data management8 ConclusionCory Davis, Patrick Stockton, Eugene B. John, Zachary Susskind, Lizy K. John Characterization of Neuro-Symbolic AI and Graph Convolutional Network workloads1 Introduction2 Model overview3 Methodology4 Results5 Analysis6 ConclusionAppendixNikhila Vintha, Devinder Kaur Multivariant time series prediction using variants of LSTM deep neural networks1 Introduction2 Data preprocessing techniques3 Recurrent neural networks4 Methodology and implementation5 Optimizers and model accuracy6 Conclusion and future workAnthony C. Brunson, Ryan D. Clendening, Richard Dill, Brett J. Borghetti, Brett Smolenski, Darren Haddad, Douglas D. Hodson Cellphone-based sUAS range estimation: a deep-learning classification and regression approach1 Introduction2 Related works3 Methodology4 Results5 ConclusionB. Chandra, Kushal Pal Singh, Prem Kalra, Rajiv Narang Automatic diagnosis of 12-lead ECG using DINOv21 Introduction2 Related work3 Vision Transformer (ViT) and DINOv24 Methodology5 Results and analysis6 Conclusion & future scopeConclusion & future scope
Large language model (LLM)
Sean Choi, Jinyoung Jo Leveraging linguistic features to improve machine learning models for detecting ChatGPT usage on exams1 Introduction2 Background3 Overview4 Evaluations5 Related works6 Discussion and future works7 ConclusionMichael Sandborn, Carlos Olea, Anwar Said, Mudassir Shabir, Peter Volgyesi, Xenofon Koutsoukos, Jules White Towards AI-augmented design space exploration pipelines for UAVs1 Introduction2 Related work3 UAV design pipeline4 Experimental results5 Large language models in the design process6 ConclusionPaula Lauren Improving subword embeddings in large language models using morphological information1 Introduction2 Related work3 Analysis of GPT subword tokens4 Proposed work5 Result analysis6 Conclusion7 Future workMassoud Alibakhsh Swarm intelligence: a new software paradigm1 Introduction: it is all about communication2 A quick background: in the beginning, there were the paper forms, then came the computers3 Two major paradigm shifts: first the GUI and then the Cloud4 Email and the promise of panacea: the first wave5 Enterprise social networks for business: the second wave6 Workflow-based communication: the 3rd wave – OMIO [patents pending]7 A new software design approach for AI as a platform8 Self-aware intelligent objects9 Integration, deep integration, and AI fusion: meaningful integration with AI in one step10 A quick review of the mechanics11 Migrating to the new LLM AI platform12 What LLMs are not suited for13 A new kind of Operating System: introduction to OMIO OS14 Conclusion15 Project OMADEUSDisclosureXiaowei Xu, Bi T. Foua, Xingqiao Wang, Vivek Gunasekaran, John R. Talburt Leveraging large language models for efficient representation learning for entity resolution1 Introduction2 Related work3 Methodology4 Experimental results5 Conclusion and future work6 AppendixXiaowei Xu, Bi Foua, Xingqiao Wang, Vivek Gunasekaran, Jonathan White, John Talburt TOAA: Train once, apply anywhere1 Introduction2 Related work3 Methodology4 Experimental results5 Conclusion and future work6 Appendix
Index

Content preview from Artificial Intelligence

Large language model (LLM)

Leveraging linguistic features to improve machine learning models for detecting ChatGPT usage on exams

Sean Choi

Jinyoung Jo

Abstract

This work presents a case study, linguistic analyses, and the results of experiments on using linguistic features to improve the detection mechanism of the use of large language models (LLM) to generate solutions for exams that require domain-specific knowledge. The study involves analyzing the responses of three groups of students: a group who verbatim copied outputs of ChatGPT to plagiarize solutions, another group who referred to external non-LLM resources (e.g., web search) to plagiarize solutions, a control group who did not plagiarize. Linguistic analyses show that ...

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ISBN: 9783111344171

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Artificial Intelligence

by Leonidas Deligiannidis, George Dimitoglou, Hamid Arabnia

Large language model (LLM)