This book is composed by a selection of articles from the 12th World Conference on Information Systems and Technologies (World CIST’24), held between 26 and 28 of March 2024, at Lodz University of Technology, Lodz, Poland.
World CIST is a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences and challenges of modern Information Systems and Technologies research, together with their technological development and applications.
The main and distinctive topics covered are: A) Information and Knowledge Management; B) Organizational Models and Information Systems; C) Software and Systems Modeling; D) Software Systems, Architectures, Applications and Tools; E) Multimedia Systems and Applications; F) Computer Networks, Mobility and Pervasive Systems; G) Intelligent and Decision Support Systems; H) Big Data Analytics and Applications; I) Human-Computer Interaction; J) Ethics, Computers and Security; K) Health Informatics; L) Information Technologies in Education; M) Information Technologies in Radiocommunications; and N) Technologies for Biomedical Applications.
The primary market of this book are postgraduates and researchers in Information Systems and Technologies field. The secondary market are undergraduates and professionals as well in Information Systems and Technologies field.
Table des matières
Maritime Management Ensemble Learning System.- Stock Market Prediction Integrating Explainable AI with Conv2D Models for Candlestick Image Analysis.- Resources optimization and value based prioritization for at risk cultural heritage assets management.- Expert Systems in Information Security A Comprehensive Exploration of Awareness Strategies Against Social Engineering Attacks.- Collaborative filtering recommendation systems based on deep learning An Experimental Study.- Assessment of LSTM and GRU models to predict the electricity production from biogas in a Wastewater Treatment Plant.- Fusing Temporal and Contextual Features for Enhanced Traffic Volume Prediction.- Target vs One and Target vs All classification of epilepsy using deep learning technique.
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