In the realm of automated document information extraction, Object Detection and Optical Character Recognition (OCR) approaches signify a pivotal leap forward. these advancements use machine learning and computer visio...
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the proceedings contain 38 papers. the topics discussed include: a public participatory approach toward the development of a comprehensive geospatial database in support of high-scale food security analysis;prediction...
ISBN:
(纸本)9789897584251
the proceedings contain 38 papers. the topics discussed include: a public participatory approach toward the development of a comprehensive geospatial database in support of high-scale food security analysis;prediction of spatiotemporal distributions of transient urban populations with statistics gathered by cell phones;location extraction from twitter messages using bidirectional long short-term memory model;design and development of an application for predicting bus travel times using a segmentation approach;spatial entity resolution between restaurant locations and transportation destinations in Southeast Asia;application of Rodrigues matrix in high accuracy geo-location for ZY-3 panchromatic imagery;alas landscape modeling by remote sensing image analysis and geographic ontology: study case of Central Yakutia (Russia);and selfie drones for 3D modeling, geological mapping and data collection: key examples from Santorini volcanic complex, Greece.
the proceedings contain 44 papers. the special focus in this conference is on EUropean Transnational Education. the topics include: the impact of international mobility in doctoral training in novel research groups: A...
ISBN:
(纸本)9783030577988
the proceedings contain 44 papers. the special focus in this conference is on EUropean Transnational Education. the topics include: the impact of international mobility in doctoral training in novel research groups: A case study;Enhancing interactive teaching of engineering topics using digital materials of the MERLOT database;technologies applied to the improvement of academic performance in the teaching-learning process in secondary students;data collection description for evaluation and analysis of engineering students academic performance;expansion of an evidence-based workshop for teaching of artificial intelligence in schools;Design of a PBL experience in the field of sustainability for industrial informatics;simple conception of photoresistor cell current-voltage characteristic measurement by arduino-based platform for educational purposes;Dual university training at the faculty of engineering Vitoria-Gasteiz (UPV-EHU);electromobility laboratory: A contribution for student participation in higher education;classroom improvement cycle in architecture by means of problem-based learning;Implementation of an integrated STEM activity in pre-primary schools;problem generalization for designing recursive algorithms;analysis of student achievement scores via cluster analysis;knowledge modelling for ill-defined domains using learning analytics: Lineworkers case;school success and school dropout in portuguese polytechnic higher education (case study);Use of IT in project-based learning applied to the subject surveying in civil engineering;Intentions towards following science and engineering studies among primary education pupils participating in integrated STEAM activities;engagement and learning from a team-based mini-project in mechatronic engineering;educational-oriented mobile robot: Hidden lessons;the acquisition of competences in transnational education through the ePortfolio;preface;estimating expected student academic performance.
the majority of driving errors resulting from poor driving habits, a lack of compliance withthe law, and inadequate driving knowledge continue to be a major global problem for public safety. Delivering accurate and t...
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the modern sedentary lifestyle has escalated health risks, underscoring the importance of tailored health solutions like yoga. this paper pioneers a method to determine yoga'srelevance for individuals by analyzing...
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Cloud computing is significantly assisting in addressing IT issues. To lessen the environmental impact, a thorough investigation of cloud computing and energy-efficient algorithms is required. A green cloud computing ...
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this study offers new insights into the management of liver cirrhosis, serving as a vital resource for public health practitioners. the findings emphasize the importance of evidence-based treatments and enhanced colla...
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Future 6G wireless networks will integrate communication and sensing functions, sharing resources across time, frequency, and space domains to achieve Integrated Sensing and Communication (ISAC). the millimeter-wave (...
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ISBN:
(纸本)9798350349184;9798350349191
Future 6G wireless networks will integrate communication and sensing functions, sharing resources across time, frequency, and space domains to achieve Integrated Sensing and Communication (ISAC). the millimeter-wave (mmWave) spectrum is poised to offer ISAC systems high communication rates and precise sensing capabilities, while the integration of RIS can enhance the stability of communication links. this advancement is significant for the Internet of things (IoT), where device interconnectivity and accurate environmental sensing are crucial for intelligent operations and decision-making. this paper introduces a passive relay RIS-assisted mmWave ISAC system for Multiple Input Single Output (MU-MISO) communication and multi-target sensing in IoT, aiming for efficient information exchange and high-precision sensing. Simulation results show that the proposed algorithms achieve high spectral efficiency (SE) and low bit error rates (BER), further propelling IoT technology towards more advanced levels of intelligence.
Modern online platforms for user modeling and recommendation require complex data infrastructures to collect and process data. Some of this data has to be kept to later be used in batches to train personalization mode...
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ISBN:
(纸本)9798400702419
Modern online platforms for user modeling and recommendation require complex data infrastructures to collect and process data. Some of this data has to be kept to later be used in batches to train personalization models. However, since user activity data can be generated at very fast rates it is also useful to have algorithms able to process data streams online, in real time. Given the continuous and potentially fast change of content, context and user preferences or intents, stream-based models, and their synchronization with batch models can be extremely challenging. therefore, it is important to investigate methods able to transparently and continuously adapt to the inherent dynamics of user interactions, preferably over long periods of time. Models able to continuously learn from such flows of data are gaining attention in the recommender systems community, and are being increasingly deployed in online platforms. However, many challenges associated with learning from streams need further investigation. the objective of this workshop is to foster contributions and bring together a growing community of researchers and practitioners interested in online, adaptive approaches to user modeling, recommendation and personalization, and their implications regarding multiple dimensions, such as reproducibility, privacy, fairness, diversity, transparency, auditability, and compliance with recently adopted or upcoming legal frameworks worldwide.
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