All Outputs (164)

Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset (2021)
Journal Article
Umair, M., Khan, M. S., Ahmed, F., Baothman, F., Alqahtani, F., Alian, M., & Ahmad, J. (2021). Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset. Sensors, 21(17), Article 5813. https://doi.org/10.3390/s21175813

The COVID-19 outbreak began in December 2019 and has dreadfully affected our lives since then. More than three million lives have been engulfed by this newest member of the corona virus family. With the emergence of continuously mutating variants of... Read More about Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset.

Blockchain technology for the industrial Internet of Things: A comprehensive survey on security challenges, architectures, applications, and future research directions (2021)
Journal Article
Latif, S., Idrees, Z., e Huma, Z., & Ahmad, J. (2021). Blockchain technology for the industrial Internet of Things: A comprehensive survey on security challenges, architectures, applications, and future research directions. Transactions on Emerging Telecommunications Technologies, 32(11), Article e4337. https://doi.org/10.1002/ett.4337

The blockchain has emerged as an innovative and powerful technology that shows the tremendous potential to enhance the smart industrial frameworks by providing encryption, immutable storage, and decentralization. In the past few years, several applic... Read More about Blockchain technology for the industrial Internet of Things: A comprehensive survey on security challenges, architectures, applications, and future research directions.

Wireless Channel Modelling for Identifying Six Types of Respiratory Patterns With SDR Sensing and Deep Multilayer Perceptron (2021)
Journal Article
Saeed, U., Shah, S. Y., Zahid, A., Ahmad, J., Imran, M. A., Abbasi, Q. H., & Shah, S. A. (2021). Wireless Channel Modelling for Identifying Six Types of Respiratory Patterns With SDR Sensing and Deep Multilayer Perceptron. IEEE Sensors Journal, 21(18), 20833-20840. https://doi.org/10.1109/jsen.2021.3096641

Contactless or non-invasive technology has a significant impact on healthcare applications such as the prediction of COVID-19 symptoms. Non-invasive methods are essential especially during the COVID-19 pandemic as they minimise the burden on healthca... Read More about Wireless Channel Modelling for Identifying Six Types of Respiratory Patterns With SDR Sensing and Deep Multilayer Perceptron.

Infrared Sensing Based Non-Invasive Initial Diagnosis of Chronic Liver Disease Using Ensemble Learning (2021)
Journal Article
Rehman, M. U., Najam, S., Khalid, S., Shafique, A., Alqahtani, F., Baothman, F., Shah, S. Y., Abbasi, Q. H., Imran, M. A., & Ahmad, J. (2021). Infrared Sensing Based Non-Invasive Initial Diagnosis of Chronic Liver Disease Using Ensemble Learning. IEEE Sensors Journal, 21(17), 19395-19406. https://doi.org/10.1109/jsen.2021.3091471

The liver is a vital human body organ and its functionality can be degraded by several diseases such as hepatitis, fatty liver disease, and liver cancer and so forth. Hence, the early diagnosis of liver diseases is extremely crucial for saving human... Read More about Infrared Sensing Based Non-Invasive Initial Diagnosis of Chronic Liver Disease Using Ensemble Learning.

An Efficient Approach Based on Privacy-Preserving Deep Learning for Satellite Image Classification (2021)
Journal Article
Alkhelaiwi, M., Boulila, W., Ahmad, J., Koubaa, A., & Driss, M. (2021). An Efficient Approach Based on Privacy-Preserving Deep Learning for Satellite Image Classification. Remote Sensing, 13(11), Article 2221. https://doi.org/10.3390/rs13112221

Satellite images have drawn increasing interest from a wide variety of users, including business and government, ever since their increased usage in important fields ranging from weather, forestry and agriculture to surface changes and biodiversity m... Read More about An Efficient Approach Based on Privacy-Preserving Deep Learning for Satellite Image Classification.

Design of Portable Exoskeleton Forearm for Rehabilitation of Monoparesis Patients Using Tendon Flexion Sensing Mechanism for Health Care Applications (2021)
Journal Article
Imtiaz, M. S. B., Babar Ali, C., Kausar, Z., Shah, S. Y., Shah, S. A., Ahmad, J., Imran, M. A., & Abbasi, Q. H. (2021). Design of Portable Exoskeleton Forearm for Rehabilitation of Monoparesis Patients Using Tendon Flexion Sensing Mechanism for Health Care Applications. Electronics, 10(11), Article 1279. https://doi.org/10.3390/electronics10111279

Technology plays a vital role in patient rehabilitation, improving the quality of life of an individual. The increase in functional independence of disabled individuals requires adaptive and commercially available solutions. The use of sensor-based t... Read More about Design of Portable Exoskeleton Forearm for Rehabilitation of Monoparesis Patients Using Tendon Flexion Sensing Mechanism for Health Care Applications.

A novel CNN-LSTM-based approach to predict urban expansion (2021)
Journal Article
Boulila, W., Ghandorh, H., Khan, M. A., Ahmed, F., & Ahmad, J. (2021). A novel CNN-LSTM-based approach to predict urban expansion. Ecological Informatics, 64, Article 101325. https://doi.org/10.1016/j.ecoinf.2021.101325

Time-series remote sensing data offer a rich source of information that can be used in a wide range of applications, from monitoring changes in land cover to surveillance of crops, coastal changes, flood risk assessment, and urban sprawl. In this pap... Read More about A novel CNN-LSTM-based approach to predict urban expansion.

Granular Data Access Control with a Patient-Centric Policy Update for Healthcare (2021)
Journal Article
Khan, F., Khan, S., Tahir, S., Ahmad, J., Tahir, H., & Shah, S. A. (2021). Granular Data Access Control with a Patient-Centric Policy Update for Healthcare. Sensors, 21(10), Article 3556. https://doi.org/10.3390/s21103556

Healthcare is a multi-actor environment that requires independent actors to have a different view of the same data, hence leading to different access rights. Ciphertext Policy-Attribute-based Encryption (CP-ABE) provides a one-to-many access control... Read More about Granular Data Access Control with a Patient-Centric Policy Update for Healthcare.

A Lightweight Chaos-Based Medical Image Encryption Scheme Using Random Shuffling and XOR Operations (2021)
Journal Article
Masood, F., Driss, M., Boulila, W., Ahmad, J., ur Rehman, S., Jan, S. U., Qayyum, A., & Buchanan, W. J. (2022). A Lightweight Chaos-Based Medical Image Encryption Scheme Using Random Shuffling and XOR Operations. Wireless Personal Communications, 127, 1405-1432. https://doi.org/10.1007/s11277-021-08584-z

Medical images possess significant importance in diagnostics when it comes to healthcare systems. These images contain confidential and sensitive information such as patients’ X-rays, ultrasounds, computed tomography scans, brain images, and magnetic... Read More about A Lightweight Chaos-Based Medical Image Encryption Scheme Using Random Shuffling and XOR Operations.

Application of Artificial Neural Network in Predicting Flashover Behaviour of Outdoor Insulators under Polluted Conditions (2021)
Presentation / Conference Contribution
Sajjad, U., Arshad, Ahmad, J., & Shoaib, S. (2021, January). Application of Artificial Neural Network in Predicting Flashover Behaviour of Outdoor Insulators under Polluted Conditions. Presented at 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus), St. Petersburg, Moscow, Russia

Safe and reliable delivery of power through transmission lines mainly depends on the quality condition of the high voltage insulators. In the last few decades, demand in polymeric insulator has been dramatically increased due to their advanced perfor... Read More about Application of Artificial Neural Network in Predicting Flashover Behaviour of Outdoor Insulators under Polluted Conditions.

A Hybrid Deep Random Neural Network for Cyberattack Detection in the Industrial Internet of Things (2021)
Journal Article
Huma, Z. E., Latif, S., Ahmad, J., Idrees, Z., Ibrar, A., Zou, Z., Alqahtani, F., & Baothman, F. (2021). A Hybrid Deep Random Neural Network for Cyberattack Detection in the Industrial Internet of Things. IEEE Access, 9, 55595-55605. https://doi.org/10.1109/access.2021.3071766

The Industrial Internet of Things (IIoT) refers to the use of traditional Internet of Things (IoT) concepts in industrial sectors and applications. IIoT has several applications in smart homes, smart cities, smart grids, connected cars, and supply ch... Read More about A Hybrid Deep Random Neural Network for Cyberattack Detection in the Industrial Internet of Things.

An experimental analysis of attack classification using machine learning in IoT networks (2021)
Journal Article
Churcher, A., Ullah, R., Ahmad, J., Ur Rehman, S., Masood, F., Gogate, M., Alqahtani, F., Nour, B., & Buchanan, W. J. (2021). An experimental analysis of attack classification using machine learning in IoT networks. Sensors, 21(2), Article 446. https://doi.org/10.3390/s21020446

In recent years, there has been a massive increase in the amount of Internet of Things (IoT) devices as well as the data generated by such devices. The participating devices in IoT networks can be problematic due to their resource-constrained nature,... Read More about An experimental analysis of attack classification using machine learning in IoT networks.

Detecting the Security Level of Various Cryptosystems Using Machine Learning Models (2020)
Journal Article
Shafique, A., Ahmed, J., Boulila, W., Ghandorh, H., Ahmad, J., & Rehman, M. U. (2021). Detecting the Security Level of Various Cryptosystems Using Machine Learning Models. IEEE Access, 9, 9383-9393. https://doi.org/10.1109/access.2020.3046528

With recent advancements in multimedia technologies, the security of digital data has become a critical issue. To overcome the vulnerabilities of current security protocols, researchers tend to focus their efforts on modifying existing protocols. Ove... Read More about Detecting the Security Level of Various Cryptosystems Using Machine Learning Models.

A blockchain-based architecture for secure and trustworthy operations in the industrial Internet of Things (2020)
Journal Article
Latif, S., Idrees, Z., Ahmad, J., Zheng, L., & Zou, Z. (2021). A blockchain-based architecture for secure and trustworthy operations in the industrial Internet of Things. Journal of Industrial Information Integration, 21, Article 100190. https://doi.org/10.1016/j.jii.2020.100190

The industrial Internet of Things (IIoT) plays an important role in the industrial sector, where secure, scalable, and easily adopted technologies are being implemented for the smart industry. The traditional IIoT architectures are generally based on... Read More about A blockchain-based architecture for secure and trustworthy operations in the industrial Internet of Things.

Prediction of Critical Flashover Voltage of High Voltage Insulators Leveraging Bootstrap Neural Network (2020)
Journal Article
Niazi, M. T. K., Arshad, Ahmad, J., Alqahtani, F., Baotham, F. A., & Abu-Amara, F. (2020). Prediction of Critical Flashover Voltage of High Voltage Insulators Leveraging Bootstrap Neural Network. Electronics, 9(10), Article 1620. https://doi.org/10.3390/electronics9101620

Understanding the flashover performance of the outdoor high voltage insulator has been in the interest of many researchers recently. Various studies have been performed to investigate the critical flashover voltage of outdoor high voltage insulators... Read More about Prediction of Critical Flashover Voltage of High Voltage Insulators Leveraging Bootstrap Neural Network.

EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network (2020)
Journal Article
Abbasi, S. F., Ahmad, J., Tahir, A., Awais, M., Chen, C., Irfan, M., Siddiqa, H. A., Waqas, A. B., Long, X., Yin, B., Akbarzadeh, S., Lu, C., Wang, L., & Chen, W. (2020). EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network. IEEE Access, 8, 183025-183034. https://doi.org/10.1109/access.2020.3028182

Objective: Classification of sleep-wake states using multichannel electroencephalography (EEG) data that reliably work for neonates. Methods: A deep multilayer perceptron (MLP) neural network is developed to classify sleep-wake states using multichan... Read More about EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network.

Privacy-Preserving Wandering Behavior Sensing in Dementia Patients Using Modified Logistic and Dynamic Newton Leipnik Maps (2020)
Journal Article
Shah, S. A., Ahmad, J., Masood, F., Shah, S. Y., Pervaiz, H., Taylor, W., Imran, M. A., & Abbasi, Q. H. (2021). Privacy-Preserving Wandering Behavior Sensing in Dementia Patients Using Modified Logistic and Dynamic Newton Leipnik Maps. IEEE Sensors Journal, 21(3), 3669-3679. https://doi.org/10.1109/jsen.2020.3022564

The health status of an elderly person can be identified by examining the additive effects of aging along disease linked to it and can lead to the ’unstable incapacity’. This health status is essentially determined by the apparent decline of independ... Read More about Privacy-Preserving Wandering Behavior Sensing in Dementia Patients Using Modified Logistic and Dynamic Newton Leipnik Maps.

DNA and Plaintext Dependent Chaotic Visual Selective Image Encryption (2020)
Journal Article
Khan, J. S., Boulila, W., Ahmad, J., Rubaiee, S., Rehman, A. U., Alroobaea, R., & Buchanan, W. J. (2020). DNA and Plaintext Dependent Chaotic Visual Selective Image Encryption. IEEE Access, 8, 159732-159744. https://doi.org/10.1109/access.2020.3020917

Visual selective image encryption can both improve the efficiency of the image encryption algorithm and reduce the frequency and severity of attacks against data. In this article, a new form of encryption is proposed based on keys derived from Deoxyri... Read More about DNA and Plaintext Dependent Chaotic Visual Selective Image Encryption.

Forecasting Flashover Parameters of Polymeric Insulators under Contaminated Conditions Using the Machine Learning Technique (2020)
Journal Article
Arshad, Ahmad, J., Tahir, A., Stewart, B. G., & Nekahi, A. (2020). Forecasting Flashover Parameters of Polymeric Insulators under Contaminated Conditions Using the Machine Learning Technique. Energies, 13(15), Article 3889. https://doi.org/10.3390/en13153889

There is a vital need to understand the flashover process of polymeric insulators for safe and reliable power system operation. This paper provides a rigorous investigation of forecasting the flashover parameters of High Temperature Vulcanized (HTV)... Read More about Forecasting Flashover Parameters of Polymeric Insulators under Contaminated Conditions Using the Machine Learning Technique.

Chaos-Based Confusion and Diffusion of Image Pixels Using Dynamic Substitution (2020)
Journal Article
Qayyum, A., Ahmad, J., Boulila, W., Rubaiee, S., Arshad, Masood, F., Khan, F., & Buchanan, W. J. (2020). Chaos-Based Confusion and Diffusion of Image Pixels Using Dynamic Substitution. IEEE Access, 8, 140876-140895. https://doi.org/10.1109/access.2020.3012912

The evolution of wireless and mobile communication from 0G to the upcoming 5G gives riseto data sharing through the Internet. This data transfer via open public networks are susceptible to severaltypes of attacks. Encryption is a method that can prot... Read More about Chaos-Based Confusion and Diffusion of Image Pixels Using Dynamic Substitution.