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[null,"1.","Record Nr.",null,"UNINA9911003689403321"]
[null,null,"Titolo",null,"Computational Science and Computational Intelligence : 11th International Conference, CSCI 2024, Las Vegas, NV, USA, December 11–13, 2024, Proceedings, Part I / / edited by Hamid R. Arabnia, Leonidas Deligiannidis, Farid Ghareh Mohammadi, Soheyla Amirian, Farzan Shenavarmasouleh"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"3-031-90341-2"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XVII, 366 p. 134 illus., 121 illus. in color.)"]
[null,null,"Collana",null,"Communications in Computer and Information Science, , 1865-0937 ; ; 2501"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computational linguistics"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Natural language processing (Computer science)"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computational Linguistics"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Natural Language Processing (NLP)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"SECTION: LARGE LANGUAGE MODELS & METHODOLOGIES -- Large Language Models for Text Classification: A New Era of Accuracy and Efficiency -- Exploring New Methods of Data Augmentation for Intent Classification through Large Language Models -- Towards Evaluating Large Language Models for Graph Query Generation -- Logical Fallacy Detection in Text: Leveraging Large Language Models for Improving Human Discourse -- Hallucinations and Training-data Bias: Results from two number transcription experiments using GPT models -- SECTION: DEEP LEARNING & APPLICATIONS -- On the Effectiveness of UAV Audio Detection and Identification Using Deep Learning Models and Mel Spectrograms.-DRNMS: An Enhanced Deep Learning-Based System for Data Recovery and Anomaly Detection in Network Monitoring -- Voice Disorder Prediction with Convolutional Neural "]
[{"$nulls":4},"Network (CNN) -- Unveiling the Unexpected: Transformer Outperforms Specialized Architectures in Volatile Supply Chain Forecasting -- SECTION: ARTIFICIAL INTELLIGENCE & PREDICTION METHODS -- Optimizing Predictive Performance: A Comparative Study of Machine Learning Algorithms for Classification Tasks.-Machine Learning-Based Prediction of Rabies Outbreaks Using Epidemiological and Environmental Data in Africa -- Assisting Personal Support Worker's e-Training with AI Prediction -- Predicting Late Delivery Risk in a Blockchain-based Supply Chain Management Architecture -- SECTION: ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, APPLICATIONS & ALGORITHMS -- Robots Playing Fair? - How Embodiment Shapes Trust and Perceptions of Cheating in AI.-Sentence-level Adversarial Examples in Arabic -- Analyzing Insurance Cost Estimation: A Supervised Regression Approach -- Collaborative Design between Intelligent Agents through Resource Sharing -- Early Detection of Mode Collapse in GANs Through Loss Monitoring -- DBRH-5: Legendre Polynomial-based Attention Mechanism in Dual-branch Hybrid-5 Towards Arrhythmia Diagnosis -- Sequential Disaggregation of Residential Energy Consumption Using Random Forest Regression -- A Declarative Approach to Tackle Sawmill Production Scheduling with Answer Set Programming -- Preferential Ensemble Method with Exponentially Weighted Scores and its Application to Facial Expression Classification -- Improving SOCIALDISTILBERT with Augmented Embeddings -- Next Generation Imminent Fracture Risk Assessment Using AI -- Multi-grain Parallel Processing of Intuctive Logic Programming."]
[null,null,null,"Sommario/riassunto","The CCIS book constitutes selected papers accepted in the Research Track on Artificial Intelligence of the 11th International Conference on Computational Science and Computational Intelligence, CSCI 2024, which took place in Las Vegas, NV, USA, during December 11–13, 2024. The 27 full papers included in this book were carefully reviewed and selected from a total of 383 submissions. They were organized in topical sections on large language models and methodologies; deep learning and applications; artificial intelligence and prediction methods; and artificial intelligence, machine learning, applications and alrogithms. ."]