Editorial Material
Computer Science, Information Systems
Amrit Mukherjee, Mahmoud Daneshmand, Kathy Grise, Amir H. Gandomi
Summary: This article provides an overview of a collection of research studies focusing on the integration of IoT applications to advance healthcare services in smart cities. The studies cover a wide range of areas in healthcare, including privacy preservation, telemedicine, smart healthcare systems, and security, and propose innovative solutions.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Editorial Material
Computer Science, Hardware & Architecture
Luca Benini, Simone Benatti, Taekwang Jang, Abbas Rahimi
Summary: The papers in this special section focus on the evolution and impact of smart edge computing and the Internet of Things (IoT), highlighting the importance of novel sensor interfaces, processors, and communication protocols. Future IoT end-nodes will need to support a wide range of functionalities, leading to innovative applications in biomedical devices, drones, environmental monitoring, and more.
IEEE TRANSACTIONS ON COMPUTERS
(2021)
Editorial Material
Automation & Control Systems
Syed Hassan Ahmed Shah, Deepika Koundal, Vyasa Sai, Shalli Rani
Summary: The relationship between computing and healthcare has a long history, but the adoption of telemedicine has been slow due to political resistance, lack of infrastructure development frameworks, and lack of resources. The Internet of Medical Things (IoMT) is expected to bring about significant advancements, particularly when combined with edge computing and 5G speed. Artificial intelligence and edge computing have played a crucial role in improving the network for reliable communication in smart healthcare systems.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Editorial Material
Engineering, Electrical & Electronic
Huawei Huang, Salil Kanhere, Jiawen Kang, Zehui Xiong, Lei Zhang, Bhaskar Krishnamachari, Elisa Bertino, Sichao Yang
Summary: Blockchain technology plays a critical role in data sharing and incentives and serves as the cornerstone for the development of other technologies. However, scalability remains a challenge for blockchain, and various solutions have been proposed to address this issue.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2022)
Editorial Material
Computer Science, Artificial Intelligence
Jie Lu, Joao Gama, Xin Yao, Leandro Minku
Summary: In recent years, stream learning has significantly developed in both conceptual and application levels, becoming a hot research direction in machine learning and data science. Advancements include detecting concept drift, adapting to drifts, and utilizing online, active, incremental, and reinforcement learning in data streaming scenarios.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Editorial Material
Engineering, Civil
Wei Wei, Kwang-Cheng Chen, Ammar Rayes, Rafal Scherer
Summary: With the development of AI, IoT, and 5G technologies, diverse traffic data can be collected, which can contribute to the construction of intelligent transportation systems. Graph-based machine learning has the potential to model complex data relationships and mine useful information and temporal patterns for ITS analytics. However, there are still challenges to be addressed in this field.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Editorial Material
Engineering, Electrical & Electronic
Robert M. Cuzner, Josep M. Guerrero
Summary: The concept of DC power and energy delivery is increasingly applied in various fields, with protection becoming a paramount concern. From low voltage LVDC to high voltage HVDC, the demand for DC distribution is continuously increasing. The future trend is moving towards MVDC power and energy distribution.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2021)
Editorial Material
Computer Science, Artificial Intelligence
Gustavo Olague, Mario Koppen, Oscar Cordon
Summary: This article introduces the field of Evolutionary Computer Vision (ECV), which is at the intersection of computer vision (CV) and evolutionary computation (EC). ECV utilizes evolutionary algorithms and metaheuristic approaches combined with analytical methods to achieve human-competitive results. It aims to design software and hardware solutions for challenging CV problems and enhance our understanding of visual processing in nature.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2023)
Editorial Material
Computer Science, Information Systems
Liuqing Yang, Wentao Huang, Vassilios G. Agelidis, Dongliang Duan, Yang Cao
Summary: Recent years have seen significant advancements in the power grid, such as the replacement of traditional mechanical components with intelligent electronics devices, the introduction of renewable energy resources and large-scale energy storage, the production of smart appliances for customized and efficient energy usage, and the implementation of advanced sensors for real-time monitoring. In essence, the power grid is transforming into a big Internet of Things (IoT) network, where individual components operate intelligently in a distributed but interconnected manner.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Editorial Material
Automation & Control Systems
Patrick Siarry, Arun Kumar Sangaiah, Yi-Bing Lin, Shiwen Mao, Marek R. Ogiela
Summary: The convergence of cognitive data science methods and models with IoT and big data systems has brought challenges to industrial systems that need to be addressed. Cognitive science will enhance the fluidity of analytics and improve IoT systems through data science techniques, impacting the future IoT networking systems.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Editorial Material
Computer Science, Information Systems
Merouane Debbah, Hongliang Zhang, Walid Saad, Lingyang Song
Summary: The emerging UAVs have a larger service coverage for sensing purposes, but due to limited computation capability, real-time sensory data needs to be transmitted to the BS/server for processing. The use of cellular networks to support data transmission for UAVs is called the Internet of UAVs, for which 3GPP has approved a study item to seamlessly integrate UAVs into future cellular networks.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Hardware & Architecture
Zhiyan Chen, Claudio Fiandrino, Burak Kantarci
Summary: Mobile crowdsensing (MCS) is an important component of the Internet of Things (IoT), utilizing smart embedded devices to collect data and provide various services, but it faces challenges in terms of incentives, privacy, security and dependability. Blockchain technology, with its decentralization, immutability and consensus characteristics, has the potential to address these challenges and improve the effectiveness of MCS in smart environments.
JOURNAL OF SYSTEMS ARCHITECTURE
(2021)
Editorial Material
Engineering, Electrical & Electronic
Saeid Haghbin, Amir Sajjad Bahman, Hao Chen
Summary: Hybrid and all-electric vehicles have gained significant market share and are expected to see rapid development in the coming years. The powertrain unit in different configurations generates traction force in vehicles. More consistency and unification between the industry and academia are needed for better results.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Editorial Material
Engineering, Electrical & Electronic
Guifang Li, Ben Eggleton, Rene-Jean Essiambre, Daoxin Dai, Yikai Su
Summary: This article introduces the special issue of PTL, which includes excellent papers from ACP 2021 and provides additional technical results and in-depth discussions and insights.
IEEE PHOTONICS TECHNOLOGY LETTERS
(2022)
Editorial Material
Computer Science, Interdisciplinary Applications
Huazhu Fu, Yitian Zhao, Pew-Thian Yap, Carola-Bibiane Schonlieb, Alejandro F. Frangi
Summary: In recent years, there has been increasing attention on geometric deep learning (GDL) and its applications to various problems in medical imaging. Unlike convolutional neural networks (CNNs) limited to grid-structured data, GDL can handle non-Euclidean data and is well-suited for medical imaging data. However, there are still questions on how to learn representations of non-Euclidean medical imaging data effectively, perform convolution on graphs, handle heterogeneous data, and improve the interpretability of GDL. After discussing with domain experts, a special issue is identified as necessary to bring attention to these topics in the medical imaging community.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)
Editorial Material
Engineering, Industrial
Gwanggil Jeon, Valerio Bellandi, Abdellah Chehri, Ernesto Damiani
Review
Chemistry, Analytical
Oumaima Moutik, Hiba Sekkat, Smail Tigani, Abdellah Chehri, Rachid Saadane, Taha Ait Tchakoucht, Anand Paul
Summary: Understanding actions in videos is a significant challenge in computer vision, and research has been conducted on this topic for decades. Convolutional neural networks (CNNs) have played a crucial role and have been widely used in deep learning for visual data exploitation and various computer vision tasks, including action recognition. However, with the emergence of the Vision Transformer models (ViTs) and their success in natural language processing, there is a discussion on whether they will replace CNNs in action recognition in video clips. This study provides a detailed analysis of this trending topic, comparing CNNs and Transformers for action recognition and discussing the trade-off between accuracy and complexity.
Article
Chemistry, Physical
Reda Lakraimi, Hamid Abouchadi, Mourad Taha Janan, Abdellah Chehri, Rachid Saadane
Summary: This paper proposes a thermal simulation framework for the selective laser sintering (SLS) process based on the discrete element method (DEM) and numerically generated in Python. The framework accurately captures the temperature distribution in the laser-scanned domain. The reliability of DEM in simulating powder-based additive manufacturing processes is validated.
Article
Environmental Sciences
Qin Pu, Abdellah Chehri, Gwanggil Jeon, Lei Zhang, Xiaomin Yang
Summary: In remote sensing, the fusion of infrared and visible images is commonly used to synthesize a fused image with abundant common and differential information from the source images. Existing fusion networks based on deep learning fail to effectively integrate this information. To address this, we propose a dual-head fusion strategy and contextual information awareness fusion network (DCFusion) to preserve meaningful information. Firstly, we extract multi-scale features using multiple convolution and pooling layers. Then, we fuse the different modal features using a dual-headed fusion strategy (DHFS) from the encoder. Finally, we reconstruct the fused image using a contextual information awareness module (CIAM). Extensive experiments on MSRS and TNO datasets demonstrate good performance in target maintenance and texture preservation for fusion images.
Article
Environmental Sciences
Hu Ming, Minzhong Wang, Lianhui Gao, Yijia Qian, Mingliang Gao, Abdellah Chehri
Summary: This study conducted a comprehensive analysis of the high-resolution atmospheric and statistical characteristics of haze events at Xianyang Airport from 2016 to 2021. The results showed that the average boundary layer height during haze events was generally less than 1000 m, with lower values in December and January compared to June and July. The maximum average boundary layer height occurred between 13:00 and 15:00. Additionally, the study analyzed the relationships between boundary layer height, air quality index, and PM2.5 concentration.
Review
Computer Science, Information Systems
Sridhar Siripurapu, Naresh K. Darimireddy, Abdellah Chehri, B. Sridhar, A. V. Paramkusam
Summary: This article critically reviews the potential role of technological advancements in addressing the challenges faced by healthcare organizations and clinical pathologists globally, and highlights the implicit problems associated with providing high-quality lifesaving treatments to patients.
Article
Computer Science, Hardware & Architecture
Quy Vu Khanh, Van-Hau Nguyen, Quy Nguyen Minh, Anh Dang Van, Ngoc Le Anh, Abdellah Chehri
Summary: This study proposes an efficient edge computing management mechanism for IoT applications in smart cities. By establishing a small database (information map), edge computing servers can store edge service information and exchange it when mobile end-users move to a new edge server's managed coverage. The experimental results have shown that our proposed mechanism significantly improves service response time and energy consumption compared to the traditional mechanism. We hope that this mechanism will be widely applied to sustainable smart cities in the future.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS
(2023)
Editorial Material
Mathematics
Abdellah Chehri, Francois Rivest
Article
Computer Science, Hardware & Architecture
Medien Zeghid, Hassan Yousif Ahmed, Abdellah Chehri, Anissa Sghaier
Summary: With the rapid evolution of security technology, the small field-size elliptic curve-based point multiplication (PM) has become obsolete, leading to implementation of PM with large field sizes. In this article, an efficient PM implementation on the elliptic curve over GF(2(m)) is proposed through a novel algorithm-architecture co-design strategy. The proposed ECC processor shows the least area-delay product (ADP) among existing structures for large field sizes on the FPGA platform.
IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS
(2023)
Article
Biochemical Research Methods
Imran Ahmed, Abdellah Chehri, Gwanggil Jeon, Francesco Piccialli
Summary: Recent advancements in biomedical imaging technologies have created opportunities for the healthcare sector and the biomedical community. However, the analysis of large volumes of health-related data such as images is time-consuming for medical experts. This article introduces a deep learning-based system for classifying and detecting lung nodules, using state-of-the-art detection architectures, and evaluates their performance using a publicly available benchmark dataset.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Environmental Sciences
Hanae Belmajdoub, Khalid Minaoui, Anass El Aouni, Karim Hilmi, Rachid Saadane, Abdellah Chehri
Summary: This article introduces the seasonal variations in upwelling dynamics along Morocco's Atlantic coast and develops a new methodology to compute an upwelling index based on sea surface temperature analysis. The proposed index is simple, efficient, and improves the analysis and quantification of seasonal and interannual variations.
Article
Green & Sustainable Science & Technology
Vu Khanh Quy, Bui Trung Thanh, Abdellah Chehri, Dao Manh Linh, Do Anh Tuan
Summary: The Fourth Industrial Revolution presents new opportunities and challenges, with digital transformation being a critical issue. Artificial Intelligence (AI) and the Internet of Things (IoT) have the potential to revolutionize education. Digital transformation has been implemented in various sectors, including education, healthcare, agriculture, and transportation. IoT enables the creation of smart learning environments, while AI transforms the way we learn and teach.
Article
Energy & Fuels
Younes Ledmaoui, Adila El Maghraoui, Mohamed El Aroussi, Rachid Saadane, Ahmed Chebak, Abdellah Chehri
Summary: The use of solar energy has been growing rapidly as a clean and renewable energy source, with the installation of photovoltaic panels on various types of buildings. This helps to reduce reliance on non-renewable fossil fuels and mitigate the effects of climate change. Advances in technology have also made solar panels more efficient and cost-effective.
Proceedings Paper
Engineering, Electrical & Electronic
N. Seiffadini, B. Sekongo, F. Meghnefi, K. S. Lim, O. C. Weng, W. Udos, U. Mohan Rao, I. Fofana, A. Cherhi, M. Ouhrouche
Summary: The insulation system of a transformer consists of oil-paper insulation, which greatly affects its service life. The degradation of the transformer's oil-paper insulation is inevitable, even under normal conditions. To indirectly monitor the solid insulation system, an optical aging marker is investigated to correlate the reflectance spectrum with the degree of polymerization (DP) values, allowing for the monitoring of paper aging conditions in oil-filled transformers.
2023 IEEE ELECTRICAL INSULATION CONFERENCE, EIC
(2023)
Article
Computer Science, Theory & Methods
Imran Ahmed, Misbah Ahmad, Abdellah Chehri, Gwanggil Jeon
Summary: In the healthcare sector, patient data is crucial for medical diagnoses and treatment plans. Existing techniques for finding similar patients based on Electronic Health Record (EHR) data face challenges due to high-dimensional and sparse vectors. To overcome this, the paper proposes a novel heterogeneous network-embedded drug recommendation system. The system focuses on classifying the sentiment of drug users based on their reviews and relevant features, achieving a classification accuracy of 92%.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
