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9th Scholar's Yearly Symposium of Technology, engineering and Mathematics, SYSTEM 2023

作者： Marinoni, Christian Ponzi, Valerio Comminiello, Danilo Dpt. of Information Engineering Electronics and Telecommunications Sapienza University of Rome Via Eudossiana 18 Roma00184 Italy Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Roma00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Via dei Taurini 19 Roma00185 Italy

During the COVID-19 pandemic, the use of a people tracking system could have been crucial, particularly in sensitive environments, such as hospitals. DPPL Hallway Tracker is a framework that uses security camera footage to determine which rooms in a corridor a person has entered. It generates a database containing all the people identified and allows quick identification of potential cases of infection based on the time spent in a room and its maximum capacity. DPPL Hallway Tracker is structured in two phases: detection and re-identification. In the first phase, it exploits Mask RCNN to identify people and room doors. In the second one, it uses the deep association metric model from DeepSORT to re-identify a person as he leaves a room. © 2023 Copyright for this paper by its authors.

关键词： COVID-19

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AUTOMATIC PIGMENT IDENTIFICATION ON ROMAN EGYPTIAN PAINTINGS BY USING SPARSE MODELING OF HYPERSPECTRAL IMAGES

AUTOMATIC PIGMENT IDENTIFICATION ON ROMAN EGYPTIAN PAINTINGS...

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European Signal Processing Conference

作者： Neda Rohani Johanna Salvant Sara Bahaadini Oliver Cossairt Marc Walton Aggelos Katsaggelos Dpt. of Electrical Engineering and Computer Science. Northwestern University Center for Scientific Studies in the Arts (NU-ACCESS) Northwestern University

ISBN: (纸本)9781509018918

In this paper, we study the problem of automatic identification of pigments applied to paintings using hyperspectral reflectance data. Here, we cast the problem of pigment identification in a novel way by decomposing the spectrum into pure pigments. The pure pigment exemplars, chosen and prepared in our laboratory based on historic sources and archaeological examples, closely resemble the materials used to make ancient paintings. To validate our algorithm, we created a set of mock-up paintings in our laboratory consisting of a broad palette of mixtures of pure pigments. Our results clearly demonstrate more accurate estimation of pigment composition than purely distance-based methods such as spectral angle mapping (SAM) and spectral correlation mapping (SCM). In addition, we studied hyperspectral imagery acquired of a Roman-Egyptian portrait, excavated from the site of Tebtunis in the Fayum region of Egypt, and dated to about the 2nd century CE. Using ground truth information obtained using Raman spectroscopy, we show qualitatively that our method accurately detects pigment composition for the specific pigments hematite and indigo.

关键词： Pigments Dictionaries Painting Libraries Hyperspectral imaging Image color analysis Signal processing algorithms painting Pigment image colour analysis Signal processing algorithms Dictionaries as Topic hyperspectral imagery Libraries

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Enriching social analytics with latent Twitter image information

Enriching social analytics with latent Twitter image informa...

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Gerasimos Razis Georgios Theofilou Ioannis Anagnostopoulos Computer Science and Biomedical Informatics Dpt. University of Thessaly Lamia Greece School of Electrical & Computer Engineering National Technical University of Athens Athens Greece

ISBN: (数字)9781728159195

ISBN: (纸本)9781728159201

In this paper, we propose a framework that uses latent information from Twitter images by employing the Google Cloud Vision API platform aiming at enriching social analytics with semantics and textual information. Our study reveals that user-generated content, linked data as well as hidden concepts and textual information from social images can be highly considered for enriching social analytics. Finally, we publish our annotated dataset for further use and evaluation from our research community.

关键词： Social networking (online) Linked data Conferences Semantics Blogs User-generated content

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Efficient big data analysis on a single machine using apache spark and self-organizing map libraries

Efficient big data analysis on a single machine using apache...

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： David Andrešić Petr Šaloun Ioannis Anagnostopoulos Faculty of Electrical Engineering and Computer Science VŠB - Technical University of Ostrava Ostrava Czech republic Computer Science and Biomedical Informatics Dpt. University of Thessaly Lamia Greece

Apache Spark is commonly used as a big data analytical platform on powerful computer clusters, as it primarily employ the main computer memory for the evaluation. Our attempt adds self-organizing map software libraries onto a single big data analytical stack and is efficient and fast enough even on a standard single computer. This innovative approach brings the big data analysis to researchers with limited resources. Our genuine idea was experimentally confirmed and is described here. As a case study for our method we we used the available #Brexit data and the sentiment analysis of corresponding tweets and the correlation with the stock exchange data.

关键词： Sparks Stock markets Correlation Twitter Finance Big Data Industries

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Semantic social analytics and linked open data cloud

Semantic social analytics and linked open data cloud

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Gerasimos Razis Ioannis Anagnostopoulos Michalis Vafopoulos Computer Science and Biomedical Informatics Dpt. University of Thessaly Lamia Greece NCSR “Demokritos” Software and Knowledge Engineering Laboratory Athens Greece

ISBN: (纸本)9781467383967

In this paper, we propose an ontology schema towards linking semantified Twitter social analytics with the Linked Open Data cloud. The ontology is deployed over a publicly available service that measures how influential a Twitter account is by combining its social activity in Twitter. According to our knowledge this is the first work that combines social analytics with the Linked Open Data (LOD) cloud.

关键词： Twitter Ontologies Resource description framework Measurement Semantics Tagging

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FraMark: A Blockchain Marketplace for a 5G Network Management using Fractional NFTs

FraMark: A Blockchain Marketplace for a 5G Network Managemen...

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IEEE World Symposium on Communication engineering (WSCE)

作者： George Michoulis Kyros Tsourdinis George Niotis Konstantinos Kyranou Eleutherios Fountoukidis Thomas Lagkas Vasileios Argyriou Panagiotis Sarigiannidis Konstantinos E. Psannis Sotirios K. Goudos R&D Dpt. Sidroco Holdings Ltd Thessaloniki Greece R&D Dpt. Sidroco Holdings Ltd Nicosia Cyprus Dpt. of Computer Science Democritus University of Thrace Kavala Greece Dpt. of Electrical & Computer Engineering University of Western Macedonia Kozani Greece Dpt. of Networks and Digital Media Kingston University London Kingston Upon Thames Surrey UK Department of Applied Informatics University of Macedonia Thessaloniki Greece ELEDIA@AUTH School of Physics Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (数字)9798331542825

ISBN: (纸本)9798331542832

This paper presents FraMark, a blockchain-based framework for 5G network management that utilizes Hyperledger Fabric and fractional Non-Fungible Tokens (NFTs) to optimize resource allocation. We introduce a comprehensive system that fractionalizes digital assets to represent 5G network resources, enhancing efficiency and allocation flexibility. Our framework addresses the challenges of 5G network management by ensuring low latency, high transaction throughput, and secure resource trading. We conduct experiments to evaluate the performance of our approach, including CPU and memory utilization, latency analysis, and block size assessment. The results demonstrate the effectiveness of FraMark in improving network resource utilization and transaction efficiency, validating our framework’s claims. By leveraging blockchain technology and innovative resource slicing techniques, FraMark paves the way for dynamic and efficient 5G network management.

关键词： 5G mobile communication Distributed ledger Throughput Dynamic scheduling Fabrics Resource management Nonfungible tokens Low latency communication

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A novel W-band radar for airport traffic monitoring: implementation, first operational results, perspectives

A novel W-band radar for airport traffic monitoring: impleme...

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International Kharkov Symposium on Physics and engineering of Microwaves, Millimeter, and Submillimeter Waves

作者： F. Mauro G. Galati M. Naldi Oerlikon Contraves Rome Italy Dpt. of Computer Science SYstems and Production Engineering (DISP) Roma Italy Department of Computer Science Systems and Production Engineering (DISP) Tor Vergate University Rome Italy

High resolution requirements for airport surface traffic monitoring with lightweight, small, all-weather sensors call for the use of a network of millimetre-wave radars to perform the surveillance function in the surface movement control and guidance system. In this paper a W-band radar employed as the basic sensor is described. Some results of recent and present field trials are reported.

关键词： Radar Airports Monitoring Communication system traffic control Air traffic control Sensor systems Surveillance Lighting control Control systems Sensor phenomena and characterization

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Secure image encryption based on a chua chaotic noise generator

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Journal of engineering science and Technology Review 2013年第4期6卷 90-103页

作者： Andreatos, A.S. Leros, A.P. Div. of Computer Engineering and Information Science Hellenic Air Force Academy Dekeleia Air Force Base Dekeleia Attica TGA-1010 Greece Dpt. of Automation School of Technological Applications Technological Educational Institute of Chalkis 34400 Psachna Evia Greece

This paper presents a secure image cryptography telecom system based on a Chua's circuit chaotic noise generator. A chaotic system based on synchronised Master-Slave Chua's circuits has been used as a chaotic true random number generator (CTRNG). Chaotic systems present unpredictable and complex behaviour. This characteristic, together with the dependence on the initial conditions as well as the tolerance of the circuit components, make CTRNGs ideal for cryptography. In the proposed system, the transmitter mixes an input image with chaotic noise produced by a CTRNG. Using thresholding techniques, the chaotic signal is converted to a true random bit sequence. The receiver must be able to reproduce exactly the same chaotic noise in order to subtract it from the received signal. This becomes possible with synchronisation between the two Chua's circuits: through the use of specific techniques, the trajectory of the Slave chaotic system can be bound to that of the Master circuit producing (almost) identical behaviour. Additional blocks have been used in order to make the system highly parameterisable and robust against common attacks. The whole system is simulated in Matlab. Simulation results demonstrate satisfactory performance, as well as, robustness against cryptanalysis. The system works with both greyscale and colour jpg images. © 2013 Kavala Institute of Technology.

关键词： Synchronization

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A Machine Learning-assisted Game Theoretical Service Selection Strategy in UAV Networks

A Machine Learning-assisted Game Theoretical Service Selecti...

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Emerging Technologies (GCET), Global Congress on

作者： Abdessalam Mohammed Hadjkouider Chaker Abdelaziz Kerrache Yesin Sahraoui Asma Adnane Carlos T. Calafate Dpt. of Computer Science and IT Kasdi Merbah University of Ouargla Ouargla Algeria Dpt. of Computer Science Université Amar Telidji de Laghouat Laghouat Algeria National Higher School of AI Algiers Algeria Computer Science Department Loughborough University Loughborough UK Computer Engineering Department (DISCA) Universitat Politècnica de València Valencia Spain

ISBN: (数字)9798331542603

ISBN: (纸本)9798331542610

The Unmanned Aerial Vehicle (UAV) has emerged as a transformative technology application in healthcare, environmental monitoring, and search and rescue operations, with the growing complexity of their services, Dynamic Environments, and limited resources. This paper introduces a novel approach that integrates machine learning (ML) with game theory to revolutionize the decision-making process in UAV service selection. Our method focuses on enhancing user experience by employing ML algorithms to analyze user requests and predict the most suitable UAV services. Concurrently, game theory is integrated to evaluate and ensure efficient selection regarding delay, throughput, packet loss ratio, and residual energy within UAV *** synergy aims to benefit both users and service providers by optimizing service delivery and user satisfaction. Experimental results demonstrate the efficacy of our model, highlighting its superior performance in terms of accuracy, precision, recall, and F-score.

关键词： Machine learning algorithms Packet loss Machine learning Medical services Autonomous aerial vehicles Throughput Prediction algorithms User experience Game theory Vehicle dynamics

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Internet of Musical Things for Children

Internet of Musical Things for Children

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Internet of Sounds, International Symposium on the

作者： Luc Nijs Luca Turchet Dept. of Education and Social Work University of Luxembourg Belval Luxembourg Dpt. of Information Engineering and Computer Science University of Trento Trento Italy

ISBN: (数字)9798350366525

ISBN: (纸本)9798350366532

One of the musical activities that can be positively impacted by the Internet of Musical Things (IoMusT) is music education. However, although the IoMusT's properties hold a promising potential to enrich music learning processes, the extent to which early childhood music educators and scholars have embraced this emerging type of technology and explored their potential is still very limited. To bridge this gap, we first survey the relevant literature at the confluence of the Internet of Things, music technology, and education. Then, we propose a pedagogical framework to support designing IoMusT applications for early childhood music education. The framework is based on five dimensions: embodied sense-making, nonlinearity, participatory sense-making, privacy and security, as well as accessibility and inclusiveness. Furthermore, we corroborate the framework with a set of pedagogical scenarios showing its usage. Our study aims to foster interdisciplinary research at the confluence of pedagogy and music technology in an application domain, that of early childhood music education, hitherto unexplored.

关键词： Surveys Privacy Ethics Education Music Market research Security Stakeholders Sustainable development Standards

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