Article
Computer Science, Information Systems
Joseph N. Mamvong, Gokop L. Goteng, Bo Zhou, Yue Gao
Summary: This research proposes an efficient security algorithm based on the Advanced Encryption Standard for constrained IoT devices. By providing a cryptanalytic overview on complexity reduction and mathematical support, along with a secure element as a tradeoff, it aims to address implementation attacks effectively. The software implementation of the algorithm shows a significant reduction in encryption time compared to current standards and literature results.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Xinyan Zhou, Jiaqi Pan, Zenan Zhang, Xiaoyu Ji, Haiming Chen
Summary: Verifying the user identity of wearable devices is important for system security, and a promising solution is PPG-based two-factor authentication using widely deployed PPG sensors. This article presents the design of G-PPG, a gesture-related PPG-based authentication mechanism that can validate the user's identity nonintrusively. G-PPG achieves high accuracy through a gesture detection module, specific feature extraction, user-defined security level, and adaptive update scheme, with over 90% accuracy in experimental scenarios.
IEEE SENSORS JOURNAL
(2023)
Article
Computer Science, Information Systems
Daojing He, Ziming Zhao, Sammy Chan, Mohsen Guizani
Summary: This article proposes an identity authentication protocol between embedded devices and servers using elliptic curve encryption and timestamp security attributes. The protocol ensures device anonymity and prevents replay attacks. The security and performance of the protocol are proven through formal verification and experimental comparison with existing protocols.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Vladimir Vakhter, Betul Soysal, Patrick Schaumont, Ulkuhan Guler
Summary: With the proliferation of proactive mobile healthcare, the landscape of miniaturized wireless biomedical devices (MWBDs) is rapidly expanding. However, the adoption of these technologies poses privacy and security risks to their users. Therefore, ensuring the security of MWBDs is crucial, and threat modeling is the first step in this process.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Gajraj Kuldeep, Qi Zhang
Summary: Compressive sensing (CS) can provide joint compression and encryption to address the challenges of massive sensor data and data security in the Internet of Things (IoT). This article proposes an energy concealment (EC) encryption scheme, a practical realization of the perfectly secure scheme by concealing energy. Experimental results show that the EC scheme outperforms advanced encryption standard in terms of code memory footprint and total energy consumption.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Medicine, General & Internal
Olfat M. Mirza, Hana Mujlid, Hariprasath Manoharan, Shitharth Selvarajan, Gautam Srivastava, Muhammad Attique Khan
Summary: The goal of this study is to develop a wearable device that uses IoT to identify infections in remote regions quickly and accurately. It operates with a multi-objective framework and utilizes different mathematical approaches to improve detection quality. The proposed method outperforms current state-of-the-art methods in all case studies.
Article
Computer Science, Information Systems
Jing Huey Khor, Michail Sidorov, Ming Tze Ong, Shen Yik Chua
Summary: This article proposes a data protection protocol that ensures data integrity, reduces transaction fees, and prolongs battery life for IoT devices used with public blockchain networks. It presents a proof of concept using an ESP32S2 device to evaluate the performance of the proposed data storage protocol. The evaluation results demonstrate that data integrity can be achieved for low-power sensor nodes connecting to public blockchains via Wi-Fi network.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Biophysics
Trinny Tat, Alberto Libanori, Christian Au, Andy Yau, Jun Chen
Summary: Biomedical sensors have played an essential role in healthcare outcomes over the past 30 years, but limited power source access and user wearability have hindered their active role in daily life. Triboelectric nanogenerators (TENGs) have shown exceptional capabilities in providing self-powered and wear-optimized biomedical sensors, paving the way for integration into the developing 5G/Internet-of-Things ecosystem. This new paradigm of TENG-based biomedical sensors aims to provide ubiquitous, real-time biomedical sensing for everyone.
BIOSENSORS & BIOELECTRONICS
(2021)
Review
Computer Science, Information Systems
Juan David Arias Correa, Alex Sandro Roschildt Pinto, Carlos Montez
Summary: This article presents a systematic review of literature on lossy data compression algorithms for reducing the data detected by IoT devices. Lossy algorithms have good compression ratio, preserve data quality, and minimize compression errors. A taxonomy was proposed based on the review results.
INTERNET OF THINGS
(2022)
Article
Computer Science, Information Systems
Foivos Michelinakis, Anas Saeed Al-Selwi, Martina Capuzzo, Andrea Zanella, Kashif Mahmood, Ahmed Elmokashfi
Summary: Proper configuration of parameters is crucial as it impacts the energy consumption of NB-IoT devices. Simple modifications to default settings can lead to significant energy savings based on empirical measurements and analysis.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Civil
Mauro A. A. da Cruz, Lucas R. Abbade, Pascal Lorenz, Samuel B. Mafra, Joel J. P. C. Rodrigues
Summary: The rapid development and widespread adoption of IoT have resulted in an increase in attacks targeting IoT environments. This paper proposes a solution to detect replication attacks in IoT by analyzing abnormal network traffic through machine learning.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Ashraf Mohamed Ali Hassan, Saeed Mohsen, Mohammed M. Abo-Zahhad
Summary: This paper proposes a novel compressive sensing technique for compressing electrocardiogram signals. The technique can be extended to multiple lead signals and uses a dynamic sensing matrix for processing. Experimental results demonstrate that the technique can achieve a high compression ratio without affecting the signal metrics.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Muhammad Nauman Khan, Asha Rao, Seyit Camtepe
Summary: The Internet of Things (IoT) is a growing technology that connects the cyber and physical worlds, with applications in various fields. However, the security challenges in IoT stem from the limited capabilities of smart devices. Lightweight cryptographic protocols address this issue but introduce vulnerabilities that require adaptive security protocols to cater to the asymmetric nature of IoT systems.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Jianqi Liu, Zhiwei Zhao, Pan Li, Geyong Min, Huiyong Li
Summary: This article proposes an Enhanced Embedded AutoEncoders framework for attribute-preserving face de-identification, which can protect personal identity while retaining desired face attributes. Experimental results show that the framework outperforms existing methods in terms of data utility, with an average improvement of 3.42% to 26.22%, indicating its effectiveness in retaining face attributes and protecting personal identity.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Ivan Sokol, Peter Hubinsky, Lubos Chovanec
Summary: The era of Internet of things brings smart homes, cities and infrastructure, with increasing demands for communication channels and data transmission volume. To maximize existing infrastructure, attention should be paid to reducing the volume of transmitted data.
Article
Anatomy & Morphology
Jean-Marie Graic, Antonella Peruffo, Livio Corain, Livio Finos, Enrico Grisan, Bruno Cozzi
Summary: By studying the primary visual cortex of Cetartiodactyls that live on land, in the sea, or in an amphibious environment, researchers have found significant differences in cortical structure compared to other mammals, with a close correlation between eye placement and cortical organization. Cetacean species, in particular, exhibit a distinct pattern of cortical organization compared to other mammals, possibly related to their deep-sea foraging habits, decreasing light availability, and reliance on echolocation.
BRAIN STRUCTURE & FUNCTION
(2022)
Article
Gastroenterology & Hepatology
Xianyong Gui, Alina Bazarova, Rocio Del Amor, Michael Vieth, Gert de Hertogh, Vincenzo Villanacci, Davide Zardo, Tommaso Lorenzo Parigi, Elin Synnove Royset, Uday N. Shivaji, Melissa Anna Teresa Monica, Giulio Mandelli, Pradeep Bhandari, Silvio Danese, Jose G. Ferraz, Bu'Hussain Hayee, Mark Lazarev, Adolfo Parra-Blanco, Luca Pastorelli, Remo Panaccione, Timo Rath, Gian Eugenio Tontini, Ralf Kiesslich, Raf Bisschops, Enrico Grisan, Valery Naranjo, Subrata Ghosh, Marietta Iacucci
Summary: Histological remission is emerging as a key treatment target in UC, and the development of a simple histological index PHRI showed high correlation with endoscopic activity and clinical outcomes. A deep learning AI system based on PHRI accurately predicted histological remission and differentiated active from quiescent UC, with promising sensitivity, specificity, and accuracy results.
Article
Gastroenterology & Hepatology
Marietta Iacucci, Tommaso Lorenzo Parigi, Rocio Del Amor, Pablo Meseguer, Giulio Mandelli, Anna Bozzola, Alina Bazarova, Pradeep Bhandari, Raf Bisschops, Silvio Danese, Gert De Hertogh, Jose G. Ferraz, Martin Goetz, Enrico Grisan, Xianyong Gui, Bu Hayee, Ralf Kiesslich, Mark Lazarey, Remo Panaccione, Adolfo Parra-Blanco, Luca Pastorelli, Timo Rath, Elin S. Royset, Gian Eugenio Tontini, Michael Vieth, Davide Zardo, Subrata Ghosh, Valery Naranjo, Vincenzo Villanacci
Summary: An artificial intelligence computer-aided diagnosis system was developed and validated to evaluate UC biopsies and predict prognosis. The system showed high accuracy and sensitivity in assessing biopsy results and predicting outcomes.
Article
Telecommunications
Giovanni Perin, Francesca Meneghello, Ruggero Carli, Luca Schenato, Michele Rossi
Summary: This study addresses the energy sustainability of multi-access edge computing platforms by developing a computing resource scheduler called EASE. It utilizes renewable energy resources and the power grid to power edge servers. EASE optimally allocates and migrates time-sensitive computing tasks in a resource-constrained Internet of Vehicles context, with the main objective of minimizing the carbon footprint of the edge network while ensuring adequate quality of service (QoS) for end users.
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING
(2023)
Article
Biology
Alireza Abdi, Masih Hajsaeedi, Mohsen Hooshmand
Summary: This paper proposes a novel hyper-heuristic for solving the longest common subsequence problem by introducing a new criterion to classify a set of strings. The study presents a general stochastic framework to identify the type of a given set of strings and introduces the set similarity dichotomizer (S2D) algorithm based on this framework. The proposed hyper-heuristic exploits S2D and the internal properties of the strings to choose the best matching heuristic. Experimental results show that the proposed method achieves competitive performance compared to the best methods and outperforms best hyper-heuristics for uncorrelated datasets in terms of solution quality and run time factors. All supplementary files are available on GitHub.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2023)
Article
Cell Biology
Rudy Celeghin, Giovanni Risato, Giorgia Beffagna, Marco Cason, Maria Bueno Marinas, Mila Della Barbera, Nicola Facchinello, Alice Giuliodori, Raquel Branas Casas, Micol Caichiolo, Andrea Vettori, Enrico Grisan, Stefania Rizzo, Luisa Dalla Valle, Francesco Argenton, Gaetano Thiene, Natascia Tiso, Kalliopi Pilichou, Cristina Basso
Summary: Arrhythmogenic cardiomyopathy (AC) is a hereditary disorder characterized by ventricular myocardium loss, and a zebrafish model can be used to study this disease and test environmental factors and candidate drugs. Our mutated zebrafish displayed cardiac alterations and signaling dysregulation, which can be worsened by intensive physical training. Treating the mutated larvae with a drug targeting the Wnt/β-catenin signaling pathway rescued the cardiac abnormalities and stabilized heart rhythm.
CELL DEATH DISCOVERY
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Valentina Vadori, Jean-Marie Graic, Livio Finos, Livio Corain, Antonella Peruffo, Enrico Grisan
Summary: The characterization of brain cell structure is essential in comparative neuroanatomy for understanding brain structure and function. Researchers have developed a new method (MR-NOM) for automatically segmenting brain cells, which has shown promising results in dealing with cells of different characteristics.
2023 IEEE 20TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING, ISBI
(2023)
Proceedings Paper
Computer Science, Information Systems
Neda Shalavi, Aria Khoshsirat, Marco Stellini, Andrea Zanella, Michele Rossi
Summary: This study focuses on calibrating the power measurements obtained from the built-in sensors of NVIDIA Jetson devices in order to collect reliable power consumption data. The results show that the internal sensors often underestimate the actual power, but calibration reduces the error to within +/- 3%. The calibrated sensor data can be used for precise assessment of power and energy figures, which is important for energy-efficient and autonomous edge services.
2023 IEEE INTERNATIONAL CONFERENCE ON EDGE COMPUTING AND COMMUNICATIONS, EDGE
(2023)
Proceedings Paper
Computer Science, Information Systems
Enver Bashirov, Marco Canil, Michele Rossi
Summary: This article introduces the application of mmWave radar network technology in human sensing. The RadNet experimental testbed allows for better deployment and testing of radar network algorithms, and enables multi-radar people tracking to be achieved.
PROCEEDINGS OF THE 1ST INTERNATIONAL WORKSHOP ON EMERGING TOPICS IN WIRELESS, EMERGING WIRELESS 2022
(2022)
Proceedings Paper
Computer Science, Theory & Methods
Jacopo Pegoraro, Michele Rossi
Summary: In this article, a convolutional-recurrent neural network is designed to accurately estimate the position and velocity of monitored subjects from radar data. The network is trained as a probabilistic model with explicit uncertainty estimation ability. Experimental assessment shows that the proposed architecture outperforms traditional methods.
2022 IEEE 23RD INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATION (SPAWC)
(2022)
Review
Materials Science, Multidisciplinary
Neal Munyebvu, Esme Lane, Enrico Grisan, Philip D. Howes
Summary: Quantum dots have attracted significant research attention in the past forty years, but their complex nature and challenges in product and device stability have hindered their proliferation in real-world applications. Utilizing emerging data-driven methodologies such as artificial intelligence and machine learning may help expedite the translation of quantum dots from the lab bench to impactful energy-related applications.
MATERIALS ADVANCES
(2022)
Meeting Abstract
Gastroenterology & Hepatology
Vincenzo Villanacci, Tommaso Lorenzo Parigi, Rocio Del Amor, Pablo Meseguer, Sean X. Gui, Alina Bazarova, Pradeep Bhandari, Raf Bisschops, Silvio Danese, Gert De Hertogh, Jose G. Ferraz, Martin Goetz, Enrico Grisan, Bu Hayee, Ralf Kiesslich, Mark Lazarev, Giulio Mandelli, Melissa Anna Teresa Monica, Remo Panaccione, Adolfo Parra-Blanco, Luca Pastorelli, Timo Rath, Elin Synnove Royset, Uday Shivaji, Gian Eugenio Tontini, Michael Vieth, Davide Zardo, Subrata Ghosh, Valery Naranjo, Marietta Iacucci
Meeting Abstract
Gastroenterology & Hepatology
Marietta Iacucci, Rosanna Cannatelli, Tommaso Lorenzo Parigi, Andrea Buda, Nunzia Labarile, Olga Maria Nardone, Gian Eugenio Tontini, Alessandro Rimondi, Alina Bazarova, Pradeep Bhandari, Raf Bisschops, Gert De Hertogh, Rocio Del Amor, Jose G. Ferraz, Martin Goetz, Sean X. Gui, Bu Hayee, Ralf Kiesslich, Mark Lazarev, Valery Naranjo, Remo Panaccione, Adolfo Parra-Blanco, Luca Pastorelli, Timo Rath, Elin Synnove Royset, Michael Vieth, Vincenzo Villanacci, Davide Zardo, Subrata Ghosh, Enrico Grisan
GASTROINTESTINAL ENDOSCOPY
(2022)
Meeting Abstract
Gastroenterology & Hepatology
V. Villanacci, T. L. Parigi, R. Del Amor, P. Mesguer Esbri, X. Gui, A. Bazarova, P. Bhandari, R. Bisschops, S. Danese, G. De Hertogh, J. G. Ferraz, M. Goetz, E. Grisan, B. Hayee, R. Kiesslich, M. Lazarev, G. Mandelli, M. A. T. Monica, R. Panaccione, A. Parra-Blanco, L. Pastorelli, T. Rath, E. S. Royset, U. Shivaji, G. E. Tontini, M. Vieth, D. Zardo, S. Ghosh, V. Naranjo, M. Iacucci
JOURNAL OF CROHNS & COLITIS
(2022)
Meeting Abstract
Gastroenterology & Hepatology
M. Iacucci, R. Cannatelli, T. L. Parigi, A. Buda, N. Labarile, O. M. Nardone, G. E. Tontini, A. Rimondi, A. Bazarova, P. Bhandari, R. Bisschops, G. De Hertogh, R. Del Amor, J. G. Ferraz, M. Goetz, X. Gui, B. Hayee, R. Kiesslich, M. Lazarev, V. Naranjo, R. Panaccione, A. Parra-Blanco, L. Pastorelli, T. Rath, E. S. Royset, M. Vieth, V. Villanacci, D. Zardo, S. Ghosh, E. Grisan
JOURNAL OF CROHNS & COLITIS
(2022)
