Article
Chemistry, Analytical
Fatemeh Sarhaddi, Iman Azimi, Sina Labbaf, Hannakaisa Niela-Vilen, Nikil Dutt, Anna Axelin, Pasi Liljeberg, Amir M. Rahmani
Summary: Pregnancy requires high-quality care to ensure the health of both the mother and the fetus. Research has proposed an IoT-based system for monitoring maternal health, including stress, sleep, and physical activity. Results show the system's feasibility for long-term monitoring.
Article
Computer Science, Information Systems
Hongru Li, Guiling Sun, Yue Li, Runzhuo Yang
Summary: The purpose of wearable technology is to integrate specific technology into user clothes or accessories using multimedia, sensors, and wireless communication. This technology has been widely used in patient monitoring and health management due to its low-load, mobile, and easy-to-use characteristics. In this paper, a Wi-Fi-based physiological monitoring system was established to accurately measure heart rate, body surface temperature, and motion data, as well as quickly detect and alert users of abnormal heart rates.
Article
Chemistry, Analytical
Shadab Faham, Abdollah Salimi, Raouf Ghavami
Summary: Internet of Wearable Things (IoWT) plays a significant role in remote medical monitoring, especially in developing countries where early disease diagnosis and continuous monitoring are challenging. This review summarizes the progress of wearable electrochemical biomarker sensors and microfluidics in tracking health status, and discusses the potential applicability of skin-conformal biomarker sensors in cloud-based telemedicine.
Review
Computer Science, Artificial Intelligence
Chioma Virginia Anikwe, Henry Friday Nweke, Anayo Chukwu Ikegwu, Chukwunonso Adolphus Egwuonwu, Fergus Uchenna Onu, Uzoma Rita Alo, Ying Wah Teh
Summary: Mobile and wearable devices embedded with multiple sensors offer an efficient means for remote health management. The heterogeneous sensor-based health monitoring system, which combines sensors from various domains, is the most effective in monitoring multiple health parameters. Researchers follow established procedures such as data collection, preprocessing, feature extraction, and evaluation of different algorithms for implementing the health monitoring system. Supervised machine learning algorithms are commonly used, and accuracy is the favored evaluation measure.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Hesham A. El Zouka, Mustafa M. Hosni
Summary: The study aims to integrate artificial intelligence technology, such as neural networks and fuzzy systems, into a secure healthcare monitoring system to create a smart healthcare model that provides reliable, accurate, secure, and real-time patient monitoring.
INTERNET OF THINGS
(2021)
Article
Chemistry, Analytical
Jose Miguel Paredes-Parra, Raquel Jimenez-Segura, David Campos-Penalver, Antonio Mateo-Aroca, Alfonso P. Ramallo-Gonzalez, Angel Molina-Garcia
Summary: With the rapid changes in power system configuration and performance, grids are now being influenced by microgeneration systems connected in low and medium voltage. However, these facilities often provide little to no information to distribution and transmission system operators, causing management problems. This paper proposes a monitoring solution using IoT technologies to address these issues, specifically for photovoltaic self-consumption installations. Field tests show that the proposed solution provides reliable and accurate results, making it a popular choice for those who cannot afford professional monitoring platforms.
Article
Computer Science, Artificial Intelligence
Ajan Ahmed, Mohammad Monirujjaman Khan, Parminder Singh, Ranbir Singh Batth, Mehedi Masud
Summary: Health care is underfunded in Bangladesh and other developing countries. This research aims to develop a cheap and accessible real-time health monitoring system using IoT sensors connected to an Arduino microprocessor. The data is transmitted to an Android application on a smartphone and updated on a website accessible by both doctors and patients. The proposed system has been tested successfully and includes vital signs monitoring and a treatment plan.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Chemistry, Analytical
Lizeth-Guadalupe Machado-Jaimes, Martin Rogelio Bustamante-Bello, Amadeo-Jose Arguelles-Cruz, Mariel Alfaro-Ponce
Summary: This paper presents the construction and application of the LM Research smart monitoring system, which aims to prevent wellness crises by continuously monitoring users' physical and mental indicators, and develops a model to predict user wellness using psychological questionnaires and machine learning algorithms.
Article
Chemistry, Analytical
Raquel Bouca-Machado, Filipa Pona-Ferreira, Mariana Leitao, Ana Clemente, Diogo Vila-Vicosa, Linda Azevedo Kauppila, Rui M. Costa, Ricardo Matias, Joaquim J. Ferreira
Summary: The study examined the feasibility and usability of an mHealth system for continuous and objective real-time monitoring of patients' health and functional mobility, with a majority of participants showing a medium-to-high level of compliance with the system. The results support the mKinetikos system as a promising tool to support clinical decisions.
Article
Engineering, Electrical & Electronic
Arif Reza Anwary, Deniz Cetinkaya, Michael Vassallo, Hamid Bouchachia
Summary: Prolonged asymmetrical sitting can worsen musculoskeletal back pain and spinal deformities. Current posture assessment methods are subjective and costly, but the Smart-Cover system offers a user-friendly and inexpensive solution for real-time posture evaluation using a Sitting Pressure Sensor and cloud connectivity.
SENSORS AND ACTUATORS A-PHYSICAL
(2021)
Review
Chemistry, Analytical
Analucia Morales, Maria Barbosa, Laura Moras, Silvio Cesar Cazella, Livia F. Sgobbi, Iwens Sene, Goncalo Marques
Summary: This article systematically reviews scientific publications on wrist wearables for identifying stress levels, highlighting the use of technologies like heart rate variability and cortisol analysis as main biomarkers. Stress assessments still rely on standardized questionnaires, but developing a wrist wearable for stress identification using physiological and chemical sensors is challenging yet possible.
Article
Computer Science, Information Systems
Md Ismail Hossain, Ahmad Fadhil Yusof, Ab Razak Che Hussin, Noorminshah A. Lahad, Ali Safaa Sadiq
Summary: The study explores factors influencing users' adoption of Continuous Glucose Monitoring Systems (CGMs) device, providing an adoption model. It found that interpersonal influence and trustworthiness are strong predictors of attitude and intention to use, while personal innovativeness and self-efficacy do not have a direct impact. Additionally, perceived value is not significant in measuring intention.
INTERNET OF THINGS
(2021)
Article
Computer Science, Hardware & Architecture
Shashi Shreya, Kakali Chatterjee, Ashish Singh
Summary: The rapid development of information technologies has propelled the growth of smart healthcare. By integrating edge technologies, Internet of Things (IoT), Internet of Medical Things (IoMT), and cloud computing, smart healthcare has replaced traditional medical systems, making healthcare more efficient, convenient, and personalized. However, healthcare systems face challenges in data security and privacy protection. This paper proposes a lightweight authentication technique with privacy-preserving schema using fully homomorphic encryption, which enables secure access to patient data and encrypted data sharing.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Review
Materials Science, Multidisciplinary
Md Nazibul Hasan, Marwan Nafea, Nafarizal Nayan, Mohamed Sultan Mohamed Ali
Summary: Thermoelectric generators have emerged as potential candidates for harvesting energy from temperature gradients to power wearable sensors and devices. Various promising inorganic and organic thermoelectric materials have been explored, showcasing their highest ZT values, along with the introduction of novel thermoelectric generator-powered wearable health monitoring sensors and Internet of Things devices. The current challenges and future perspectives for the development of thermoelectric generators, particularly focusing on efficient materials and self-powered devices, are also discussed.
ADVANCED MATERIALS TECHNOLOGIES
(2022)
Article
Computer Science, Information Systems
Yunpeng Liu, Fei Xiao
Summary: This article introduces a residential environment intelligent monitoring system based on cloud computing and the Internet of things, utilizing IoT and sensor technologies for system connection and communication, and employing distributed computing for integrated management. Through experiments, it was found that the system's monitoring performance was good, demonstrating effective use of IoT and cloud computing technologies.
Article
Computer Science, Hardware & Architecture
R. Bhaskaran, S. Saravanan, M. Kavitha, C. Jeyalakshmi, Seifedine Kadry, Hafiz Tayyab Rauf, Reem Alkhammash
Summary: Sentiment Analysis, a subfield of Natural Language Processing, focuses on identifying and extracting opinions from text. This research proposes a novel machine learning model that effectively handles unstructured text and achieves improved sentiment classification.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
R. Krishnaswamy, Kamalraj Subramaniam, V Nandini, K. Vijayalakshmi, Seifedine Kadry, Yunyoung Nam
Summary: This paper proposes an efficient Map Reduce based hybrid density based clustering and classification algorithm for big data analytics, which shows promising performance in terms of different measures through experimental validation.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
E. Dhiravidachelvi, M. Suresh Kumar, L. D. Vijay Anand, D. Pritima, Seifedine Kadry, Byeong-Gwon Kang, Yunyoung Nam
Summary: Human Activity Recognition (HAR) has become simpler in recent years due to advancements in Artificial Intelligence (AI) techniques. This research focuses on designing an Intelligent Hyperparameter Tuned Deep Learning-based HAR (IHPTDL-HAR) technique in healthcare for managing patients' healthcare service. Experimental results demonstrate that the proposed IHPTDL-HAR technique outperforms other recent techniques under different measures.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Information Systems
Javaria Amin, Muhammad Almas Anjum, Muhammad Sharif, Seifedine Kadry, Ruben Gonzalez Crespo
Summary: Liver cancer is a major cause of death worldwide, and manually detecting infected tissues is challenging and time-consuming. Computerized methods can assist in making accurate decisions and therapies. Semantic segmentation plays a vital role in segmenting infected liver regions.
IEEE LATIN AMERICA TRANSACTIONS
(2023)
Article
Physics, Applied
Muhammad Ramzan, Nazia Shahmir, Hassan Ali S. Ghazwani, Yasser Elmasry, Muhammad Bilal, Seifedine Kadry
Summary: In this study, the impact of nanoparticle size on the viscosity and thermal conductivity of nanofluid flow over an exponentially stretched surface is examined using the Corcione model. The results showed that the velocity of the copper-water nanofluid decreased with larger volume fractions of nanoparticles, while the temperature distribution showed the opposite trend. Additionally, at the surface, higher values of the slip parameter led to a reduction in velocity and higher values of the Biot number resulted in an increase in fluid temperature.
INTERNATIONAL JOURNAL OF MODERN PHYSICS B
(2023)
Article
Mathematics
Chandrakala Arya, Manoj Diwakar, Prabhishek Singh, Vijendra Singh, Seifedine Kadry, Jungeun Kim
Summary: Significant advances have been made in the field of text summarization, with a focus on news summarization. To create summaries of various news articles in the context of erroneous online data, it is essential to develop a synthesis approach that can extract, compare, and rank sentences. It is also necessary for the news summarization system to handle multi-document summaries due to content redundancy. This paper proposes a method for summarizing multi-document news web pages using similarity models and sentence ranking, which outperforms other recent methods in summarizing news articles according to experimental results.
Article
Biochemistry & Molecular Biology
Javeria Naz, Muhammad Imran Sharif, Muhammad Irfan Sharif, Seifedine Kadry, Hafiz Tayyab Rauf, Adham E. Ragab
Summary: Esophagitis, cancerous growths, bleeding, and ulcers are common symptoms of gastrointestinal disorders that contribute to high human mortality. This research proposes a hybrid method for accurate diagnosis and early treatment of gastrointestinal abnormalities. The method involves dataset augmentation, preprocessing, feature engineering, and classification, with image enhancement and deep learning techniques used. The proposed method achieved superior accuracy compared to recent methods on two datasets, with Q_SVM accuracies of 100% and 99.24% on the Hybrid dataset and Kvasir-V1 dataset, respectively.
Article
Computer Science, Artificial Intelligence
Ahmad Almadhor, Rizwana Irfan, Jiechao Gao, Nasir Saleem, Hafiz Tayyab Rauf, Seifedine Kadry
Summary: Dysarthria is a speech disability caused by weak muscles and organs involved in articulation, affecting speech intelligibility. This paper proposes a visual dysarthric ASR system using SCNN and MHAT to overcome speech challenges. The DASR system outperformed other systems, improving recognition accuracy for the UA-Speech database by 20.72%, with the largest improvements seen in very-low (25.75%) and low intelligibility (33.67%) cases.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Theory & Methods
Muhammad Attique Khan, Asif Mehmood, Seifedine Kadry, Nouf Abdullah Almujally, Majed Alhaisoni, Jamel Balili, Abdullah Al Hejaili, Abed Alanazi, Shtwai Alsubai, Abdullah Alqatani
Summary: Industrial advancements and financial stakes drive the aims of smart cities, which focus on increasing efficiency and citizens' quality of life. Human Gait Recognition (HGR) is an important application that utilizes walking styles for individual recognition. This paper proposes a deep learning method for HGR using a large gait database and transfer learning, achieving high accuracy by addressing constraints such as poor lighting and varying angles. The proposed technique combines improved BAT algorithm, entropy selection, and canonical correlation analysis to extract and fuse features for final gait recognition using a softmax classifier.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Thermodynamics
Nazia Shahmir, Muhammad Ramzan, C. Ahamed Saleel, Seifedine Kadry
Summary: This study aims to investigate the flow characteristics of ternary and hybrid nanofluids and the response of ferromagnetic nanoparticles. Experimental results show that the concentration distribution decreases more for hybrid nanofluids and they produce less entropy compared to ternary nanofluids. Additionally, it is found that the induced magnetic field is stronger for ternary nanofluids than hybrid nanofluids when the magnetic Prandtl number increases.
NUMERICAL HEAT TRANSFER PART A-APPLICATIONS
(2023)
Article
Medicine, General & Internal
Burak Yagin, Fatma Hilal Yagin, Cemil Colak, Feyza Inceoglu, Seifedine Kadry, Jungeun Kim
Summary: This research utilizes machine learning techniques and explainable artificial intelligence (XAI) to predict breast cancer metastasis and identify important genomic biomarkers associated with metastasis. The study finds that increased expression levels of certain genes and decreased expression levels of others are associated with an increased risk of breast cancer metastasis.
Article
Multidisciplinary Sciences
Muhammad Attique Khan, Yu-Dong Zhang, Majed Alhusseni, Seifedine Kadry, Shui-Hua Wang, Tanzila Saba, Tassawar Iqbal
Summary: In this paper, a method for action recognition based on the fusion of shape and deep learning features is proposed. The method consists of two steps: human extraction and action recognition. By combining entropy-controlled feature selection and parallel conditional entropy approach, the features are fused and classified, achieving a high accuracy rate.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Muhammad Attique Khan, Seifedine Kadry, Pritee Parwekar, Robertas Damasevicius, Asif Mehmood, Junaid Ali Khan, Syed Rameez Naqvi
Summary: Human gait analysis is an important topic in computer vision with various applications. However, the variability in patients' clothes, viewing angle, and carrying conditions can affect system performance. To enhance accuracy, this study proposes a deep learning feature aggregation method applied in gait recognition. The results demonstrate that the proposed method achieves accuracy beyond 96% and outperforms other classifiers.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Mathematics, Applied
M. Ijaz Khan, Sumaira Qayyum, Yu-Ming Chu, Seifedine Kadry
Summary: This article considers the Marangoni convective flow of nanofluid and entropy generation minimization. Equations are constructed for the Buongiorno model of nanofluid and the flow is generated by a rotating disk. The effects of activation energy, nonlinear mixed convection, and MHD are also taken into consideration. Ordinary differential equations are formed using appropriate variables and results are obtained using the Shooting method. The results of temperature, axial velocity, entropy, radial velocity, concentration, and Bejan number are discussed through graphs.
NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS
(2023)
Article
Mathematics, Applied
Muhammad Ijaz Khan, Sumaira Qayyum, Mehr Nigar, Yu-Ming Chu, Seifedine Kadry
Summary: This research addresses the impact of Brownian diffusion and thermophoresis on the flow of non-Newtonian fluid in nanofluids. By using similarity transformations, the nonlinear flow expressions are transformed into ordinary differential equations and numerically solved. The results show concentration, temperature, and velocity profiles, as well as mass transfer, surface drag force, and heat transfer rate. Additionally, graphs analyzing entropy and Bejan number reveal their changing behaviors.
NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS
(2023)
Review
Computer Science, Information Systems
Euclides Carlos Pinto Neto, Sajjad Dadkhah, Somayeh Sadeghi, Heather Molyneaux, Ali A. Ghorbani
Summary: The Internet of Things (IoT) has the potential to revolutionize medical treatment in healthcare, but it also faces security threats. Advanced analytics can enhance IoT security, but generating realistic datasets is complex. This research conducts a review of Machine Learning (ML) solutions for IoT security in healthcare, focusing on existing datasets, resources, applications, and challenges, to highlight the current landscape and future requirements.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Duncan Deveaux, Takamasa Higuchi, Seyhan Ucar, Jerome Harri, Onur Altintas
Summary: This paper investigates the ability to predict the risk patterns of vehicles in a roundabout and suggests that constraining knowledge transfer to roundabouts with a similar context can significantly improve accuracy.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Lingjun Zhao, Qinglin Yang, Huakun Huang, Longtao Guo, Shan Jiang
Summary: Metaverse seamlessly integrates the real and virtual worlds, and intelligent wireless sensing technology can serve as an intelligent, flexible, non-contact way to access the metaverse and accelerate the establishment of a bridge between the real physical world and the metaverse. However, there are still challenges and open issues in this field.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Jing Xiong, Hong Zhu
Summary: With the rapid growth of data in the era of IoT, the challenge of data privacy protection arises. This article proposes a federated learning approach that uses collaborative training to obtain a global model without direct exposure to local datasets. By utilizing dynamic masking and adaptive differential privacy methods, the approach reduces communication overhead and improves the converge performance of the model.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Carlos Rubio Garcia, Simon Rommel, Sofiane Takarabt, Juan Jose Vegas Olmos, Sylvain Guilley, Philippe Nguyen, Idelfonso Tafur Monroy
Summary: The reliance on asymmetric public key cryptography and symmetric encryption for cyber-security in current telecommunication networks is threatened by quantum computing technology. Quantum Key Distribution and post-quantum cryptography provide resistance to quantum attacks. This paper proposes two novel hybrid solutions integrating QKD and PQC into TLS for quantum-resistant key exchange.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Annisa Sarah, Gianfranco Nencioni
Summary: This article explores the concept of a Slice Broker, an intermediate entity that purchases resources from Infrastructure Providers to offer customized network slices to users. The article proposes a cost-minimization problem and compares it with alternative problems to demonstrate its effectiveness and cost-saving capabilities.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Sumana Maiti, Sudip Misra, Ayan Mondal
Summary: The broadcast proxy re-encryption methods extend traditional proxy re-encryption mechanisms and propose a scheme called MBP for IoT applications. MBP calculates a single re-encryption key for all user groups and uses multi-channel broadcast encryption to reduce security element size. However, it increases computation time for receiver IoT devices. The use of Rubinstein-Stahl bargaining game approach addresses this issue and MBP is secure against selective group chosen-ciphertext attack in the random oracle model.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Pankaj Kumar, Hari Om
Summary: This paper presents NextGenV2V, a protocol for the next-generation vehicular network that achieves authenticated communication between vehicles using symmetric keys and a (2, n)-threshold scheme. The protocol reduces communication overhead and improves authentication delay, ensuring better security. Comparative analysis demonstrates the suitability of NextGenV2V in next-generation vehicular networks.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Eric Ossongo, Moez Esseghir, Leila Merghem-Boulahia
Summary: The implementation of 5G networks allows for the efficient coexistence of heterogeneous services in a single physical virtualized infrastructure. Virtualization of network functions enables more flexible resource management and customizable services. However, the increasing number of connected objects poses challenges in managing physical and virtual resources, requiring intelligent systems to ensure communication quality.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Suvrima Datta, U. Venkanna
Summary: The Internet of Things (IoT) enables real-time sensing and data transmission to make homes smarter. Effective device-type identification methods are crucial as the number of IoT devices continues to grow. In this paper, a P4-based gateway called PiGateway is proposed to classify and prioritize the type of IoT devices. By utilizing a decision tree model and flow rules, PiGateway enables real-time granular analysis and in-network classification of IoT traffic.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Fahad Razaque Mughal, Jingsha He, Nafei Zhu, Saqib Hussain, Zulfiqar Ali Zardari, Ghulam Ali Mallah, Md. Jalil Piran, Fayaz Ali Dharejo
Summary: This paper explores the relationship between heterogeneous cluster networks and federated learning, as well as the challenges of implementing federated learning in heterogeneous networks and the Internet of Things. The authors propose an Intra-Clustered FL (ICFL) model that optimizes computation and communication to select heterogeneous FL nodes in each cluster, enabling efficient processing of asynchronous data and ensuring data security.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Rajesh Kumar, Deepak Sinwar, Vijander Singh
Summary: This paper investigates the coexistence mechanisms between eMBB and URLLC traffic for resource scheduling in 5G. Through examining different approaches and performance metrics, it provides detailed insights for researchers in the field, and highlights key issues, challenges, and future directions.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Giovanni Nardini, Giovanni Stea
Summary: Digital Twins of Networks (DTNs) are proposed as digital replicas of physical entities, enabling efficient data-driven network management and performance-driven network optimization. DTNs provide simulation services for dynamic reconfiguration and fault anticipation, using discrete-event network simulators as the ideal tools. Challenges include centralized vs. distributed implementation, input gathering from the physical network, security issues and hosting. The possibilities of network simulation for what-if analysis are explored, with the concepts of lockstep and branching analysis defined.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Zhaolin Ma, Jiali You, Haojiang Deng
Summary: This paper presents the Distributed In-Network Name Resolution System (DINNRS), which leverages software-defined networking and Information-Centric Networking (ICN) paradigm to provide high scalability and minimal request delay. Our methods, including an enhanced marked cuckoo filter for fast resolving, achieve significant performance gains in simulation experiments.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Yujie Wang, Ying Wang, Qingqing Liu, Yong Zhang
Summary: This paper proposes a dynamic indoor positioning method based on multi-scale metric learning of the channel state information (CSI). By constructing few-shot learning tasks, this method can achieve dynamic positioning using CSI signals without additional equipment. Experimental results show that compared to commonly used dynamic location and tracking algorithms, the proposed method has higher positioning accuracy and does not accumulate errors.
COMPUTER COMMUNICATIONS
(2024)
