检索结果-内蒙古大学图书馆

2023 Italia Intelligenza Artificiale - Thematic Workshops, Ital-IA 2023

作者： Liguori, Angelica Mungari, Simone Zuppelli, Marco Comito, Carmela Cambiaso, Enrico Repetto, Matteo Guarascio, Massimo Caviglione, Luca Manco, Giuseppe Institute for High Performance Computing and Networking via P. Bucci 8-9/C Rende87036 Italy University of Calabria via P. Bucci Rende87036 Italy Institute of Electronics Computer and Telecommunication Engineering Via de Marini 6 Genova16149 Italy Institute for Applied Mathematics and Information Technologies Via de Marini 6 Genova16149 Italy

Recently, the number of attacks aiming at breaching networked and softwarized environments has been growing exponentially. In particular, information hiding methods and covert attacks have been proven to be able to elude traditional detection systems and exfiltrate sensitive data without producing visible network flows or data exchanges. In this context, Artificial Intelligence techniques can play a key role in detecting these new emerging attacks, owing to their capability of quickly processing huge amounts of data without the necessity of expert intervention. In this work, we discuss the main challenges to face covert attacks in IoT and softwarized environments and we describe some preliminary results obtained by adopting Deep Learning architectures. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Electronic data interchange

来源：评论

学校读者我要写书评

暂无评论

An AI-Driven Architecture for Precision Agriculture: IoT, Machine Learning, and Digital Twin Integration for Sustainable Crop Protection

An AI-Driven Architecture for Precision Agriculture: IoT, Ma...

引用

IEEE International Conference on Big Data

作者： Gianni Costa Agostino Forestiero Antonio Francesco Gentile Davide Macrì Riccardo Ortale Bruno Bernardi Emanuele Cerruto Institute for High Performance Computing and Networking National Research Council (CNR-ICAR) Rende Italy Department of Agriculture Mediterranean University of Reggio Calabria Reggio Calabria Italy Department of Agriculture Food and Environment (Di3A) University of Catania Catania Italy

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

General efficient crop protection in olive orchards is challenged by the need for precise agrochemical application minimizing environmental impact while ensuring effective spray coverage. Conventional approaches often lead to poor spray distribution, heavy off-target losses and a lack of real-time adaptability in variable field conditions. Such findings imply the need for an approach or system that can adjust application parameters dynamically to optimize both effectiveness and *** paper introduces an advanced AI-driven architecture designed to meet these challenges by integrating Internet of Things (IoT), machine learning, and digital twin technologies. The core of this approach is the development of a Digital Tree, a virtual model of olive trees that accurately simulates and predicts spray distribution and interactions with environmental variables. IoT sensors in the field collect real-time data on spray behavior and field conditions, which machine learning algorithms then process to refine application parameters dynamically. By enabling data-driven, adaptive decision-making, the digital twin supports optimal spray distribution, reduces off-target impact, and enhances environmental sustainability. This integrated solution offers a scalable and replicable methodology for smart agriculture, advancing precision and sustainability in complex agricultural environments.

关键词： Precision agriculture Adaptation models Agrochemicals Decision making Crops Machine learning Real-time systems Digital twins Internet of Things Protection

来源：评论

学校读者我要写书评

暂无评论

Editorial

引用

Journal of Reliable Intelligent Environments 2022年第2期8卷 77-77页

作者： Coronato, Antonio Augusto, Juan Carlos Department of Computer Science Research Group on Development of Intelligent Environments Middlesex University London United Kingdom Institute for High Performance Computing and Networking National Research Council Naples Italy

来源：评论

学校读者我要写书评

暂无评论

Human sentiments monitoring during COVID-19 using AI-based modeling

引用

Procedia computer science 2022年 203卷 753-758页

作者： Areeba Umair Elio Masciari Department of Electrical Engineering and Information Technologies University of Naples Federico II Naples 80125 Italy. Institute for High Performance Computing and Networking (ICAR) National Research Council Naples Italy.

The whole world is facing health challenges due to wide spread of COVID-19 pandemic. To control the spread of COVID-19, the development of its vaccine is the need of hour. Considering the importance of the vaccines, many industries have put their efforts in vaccine development. The higher immunity against the COVID can be achieved by high intake of the vaccines. Therefore, it is important to analysis the people's behaviour and sentiments towards vaccines. Today is the era of social media, where people mostly share their emotions, experience, or opinions about any trending topic in the form of tweets, comments or posts. In this study, we have used the freely available COVID-19 vaccines dataset and analysed the people reactions on the vaccine campaign using artificial intelligence methods. We used TextBlob() function of python and found out the polarity of the tweets. We applied the BERT model and classify the tweets into negative and positive classes based on their polarity values. The classification results show that BERT has achieved maximum values of precision, recall and F score for both positive and negative sentiment classification.

关键词： AI based modeling COVID-19 Sentiments monitoring Social media data analysis Vaccine hesitancy Vaccines campaign

来源：评论

学校读者我要写书评

暂无评论

Social Sensing for Personalized Orienteering Mediating the Need for Sociality and the Risk of COVID-19

IEEE Transactions on Technology and Society

引用

IEEE Transactions on Technology and Society 2022年第4期3卷 323-332页

作者： Pilato, Giovanni Persia, Fabio Ge, Mouzhi D'Auria, Daniela Institute for High Performance Computing and Networking National Research Council of Italy ICAR-CNR Palermo90146 Italy University of l'Aquila Computer Science and Mathematics Department of Information Engineering L'Aquila67100 Italy Deggendorf Institute of Technology Faculty of European Campus Rottal-Inn Deggendorf94469 Germany Free University of Bozen-Bolzano Faculty of Computer Science Bolzano39100 Italy

Orienteering or itinerary planning applications aim to optimize travel routes exploiting user preference and other constraints, such as time budget or traffic conditions. For these algorithms, it is essential to explore the user preference to predict potential Points-Of-Interest (POI) or touristic routes. However, user preference has been significantly affected by the COVID-19, since health concern plays a key trade-off role now. For example, people may try to avoid crowdedness, even if there is a strong social desire. However, most orienteering applications just focus on user preferences, thus paying less attention to the variety of the data inputs, which has become an essential factor for the utility of the application in the COVID-19 era. Therefore, this paper proposes a social sensing system that considers the trade-off between user preference and various factors, such as crowdedness, fear of being infected, knowledge of the COVID-19, POI features, and desire for socialization. The experiments are conducted on profiling user interests with Doc2Vec and FastText based on the Yelp dataset. Furthermore, the proposed system is modular and can be efficiently adapted to different applications for COVID-aware itinerary planning. © 2020 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Sensing the Web for Induction of Association Rules and their Composition through Ensemble Techniques 10

Sensing the Web for Induction of Association Rules and their...

引用

10th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2019

作者： Augello, Agnese Infantino, Ignazio Pilato, Giovanni Vella, Filippo ICAR-CNR Institute for High Performance Computing and Networking National Research Council of Italy Palermo Italy

Starting from geophysical data collected from heterogeneous sources, such as meteorological stations and information gathered from the web, we seek unknown connections between the sampled values through the extraction of association rules. These rules imply the co-occurrence of two or more symbols in the same representation, and the rule confidence may vary according to the collected data. We propose, starting from traditional algorithms such as FP-Growth and Apriori, the creation of complex association rules through boosting of simpler ones. The composition enables the creation of rules that are robust and let emerge a larger number of interesting rules. © 2020 The Authors. Published by Elsevier B.V.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Occupancy Prediction in Multi-Occupant IoT Environments Leveraging Federated Learning

Occupancy Prediction in Multi-Occupant IoT Environments Leve...

引用

IEEE International Symposium on Dependable, Autonomic and Secure computing (DASC)

作者： Irfanullah Khan Flavia C. Delicato Emilio Greco Massimo Guarascio Antonio Guerrieri Giandomenico Spezzano University of Calabria Rende (CS) Italy ICAR-CNR Institute for high performance computing and networking - National Research Council of Italy Rende (CS) Italy Instituto de Computacao Universidade Federal Fluminense Niteroi RJ Brazil

Energy efficiency and energy saving have become crucial issues in the face of increasing energy demand, the need for sustainable solutions, and concerns about climate change. Buildings, as significant contributors to energy consumption and greenhouse gas emissions, require effective measures for energy optimization that can also be reached by predicting the usage of the building spaces. This paper introduces a data-driven approach combining Internet of Things sensors, Machine Learning, Edge computing, and Federated Learning to predict multi-occupancy in buildings. The proposed approach is used on real data from the ICAR-CNR IoT Laboratory in order to extract insights into occupancy patterns within a multi-occupant environment. Finally, a comparative analysis conducted by varying Federated Learning configurations demonstrates the robustness of the solution.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Augmenting Collaborative Practices: The Hololiver Case Study

Augmenting Collaborative Practices: The Hololiver Case Study

引用

International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Agnese Augello Giuseppe Caggianese Luigi Casoria Luigi Gallo Roberto Montalti Pietro Neroni Gianluca Rompianesi Roberto Troisi Institute for high performance computing and networking (ICAR) National Research Council Palermo Italy Institute for high performance computing and networking (ICAR) National Research Council Naples Italy Department of Public Health Division of Hepato-Biliary-Pancreatic Minimally Invasive and Robotic Surgery and Kidney Transplantation Federico II University Hospital Naples Italy Department of Clinical Medicine and Surgery Division of Hepato-Biliary-Pancreatic Minimally Invasive and Robotic Surgery and Kidney Transplantation Federico II University Hospital Naples Italy

Advances in Mixed Reality (MR) technologies are reshaping collaborative practices. The seamless integration of physical and virtual elements enhances the perception of the working environment, providing a more enriched collaborative task experience. While revealing intriguing potential across various sectors, wearing head-mounted displays (HMDs) can pose challenges in communication and in understanding others’ behaviours. This paper analyses the main elements of collaborative augmented practices through the case study of Hololiver, a MR system developed to assist surgeons in planning laparoscopic liver surgeries. The work discusses guidelines for designing interfaces to preserve awareness in MR interactions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Lower and upper estimates of the quantity of algebraic numbers

arXiv

引用

arXiv 2022年

作者： Sergeyev, Yaroslav D. University of Calabria Rende Italy Lobachevsky University Nizhni Novgorod Russia Institute of High Performance Computing and Networking The National Research Council of Italy Rende Italy

It is well known that the set of algebraic numbers (let us call it A) is countable. In this paper, instead of the usage of the classical terminology of cardinals proposed by Cantor, a recently introduced methodology using ①-based infinite numbers is applied to measure the set A (where the number ① is called grossone). Our interest to this methodology is explained by the fact that in certain cases where cardinals allow one to say only whether a set is countable or it has the cardinality of the continuum, the ①-based methodology can provide a more accurate measurement of infinite sets. In this article, lower and upper estimates of the number of elements of A are obtained. Both estimates are expressed in ①-based *** Codes 11R04, 11B99, 00A30, 05A99, 03A05, 00A35 Copyright © 2022, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Some paradoxes of Infinity revisited

arXiv

引用

arXiv 2022年

In this article, some classical paradoxes of infinity such as Galileo's paradox, Hilbert's paradox of the Grand Hotel, Thomson's lamp paradox, and the rectangle paradox of Torricelli are considered. In addition, three paradoxes regarding divergent series and a new paradox dealing with multiplication of elements of an infinite set are also described. It is shown that the surprising counting system of an Amazonian tribe, Pirahã, working with only three numerals (one, two, many) can help us to change our perception of these paradoxes. A recently introduced methodology allowing one to work with finite, infinite, and infinitesimal numbers in a unique computational framework not only theoretically but also numerically is briefly described. This methodology is actively used nowadays in numerous applications in pure and applied mathematics and computer science as well as in teaching. It is shown in the article that this methodology also allows one to consider the paradoxes listed above in a new constructive *** Codes 00A30, 97F30, 40-08, 40A05, 03A05, 97E40, 97C30 Copyright © 2022, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：