• Bifurcation Analysis, Synchronization and FPGA Implementation of a New 3-D Jerk System with a Stable Equilibrium 

      Vaidyanathan, Sundarapandian; Azar, Ahmad Taher; Hameed, Ibrahim A.; Benkouider, Khaled; Tlelo-Cuautle, Esteban; Ovilla-Martinez, Brisbane; Lien, Chang-Hua; Sambas, Aceng (Peer reviewed; Journal article, 2023)
      This research paper addresses the modelling of a new 3-D chaotic jerk system with a stable equilibrium. Such chaotic systems are known to exhibit hidden attractors. After the modelling of the new jerk system, a detailed ...
    • COVID-19 Genome Sequence Analysis for New Variant Prediction and Generation 

      Ullah, Amin; Malik, Khalid Mahmood; Saudagar, Abdul Khader Jilani; Khan, Muhammad Badruddin; Hasanat, Mozaherul Hoque Abul; AlTameem, Abdullah; AlKhathami, Mohammed; Sajjad, Muhammad (Journal article; Peer reviewed, 2022)
    • EADN: An Efficient Deep Learning Model for Anomaly Detection in Videos 

      Ul Amin, Sareer; Ullah, Mohib; Sajjad, Muhammad; Alaya Cheikh, Faouzi; Hijji, Mohammad; Hijji, Abdulrahman; Khan, Muhammad (SKKU) (Peer reviewed; Journal article, 2022)
      Surveillance systems regularly create massive video data in the modern technological era, making their analysis challenging for security specialists. Finding anomalous activities manually in these enormous video recordings ...
    • An evolve-then-correct reduced order model for hidden fluid dynamics 

      Pawar, Suraj; Ahmed, Shady E; San, Omer; Rasheed, Adil (Journal article; Peer reviewed, 2020)
      n this paper, we put forth an evolve-then-correct reduced order modeling approach that combines intrusive and nonintrusive models to take hidden physical processes into account. Specifically, we split the underlying dynamics ...
    • FADS: An Intelligent Fatigue and Age Detection System 

      Hijji, Mohammad; Yar, Hikmat; Ullah, Fath U Min; Alwakeel, Mohammed M.; Harrabi, Rafika; Aradah, Fahad; Alaya Cheikh, Faouzi; Muhammad, Khan; Sajjad, Muhammad (Peer reviewed; Journal article, 2023)
      Nowadays, the use of public transportation is reducing and people prefer to use private transport because of its low cost, comfortable ride, and personal preferences. However, personal transport causes numerous real-world ...
    • Intelligent Image Super-Resolution for Vehicle License Plate in Surveillance Applications 

      Hijji, Mohammad; Khan, Abbas; M. Alwakeel, Mohammad; Harrabi, Rafika; Aradah, Fahad; Alaya Cheikh, Faouzi; Sajjad, Muhammad; Khan, Muhammad (SKKU) (Peer reviewed; Journal article, 2023)
      Vehicle license plate images are often low resolution and blurry because of the large distance and relative motion between the vision sensor and vehicle, making license plate identification arduous. The extensive use of ...
    • Mapping Tools for Open Source Intelligence with Cyber Kill Chain for Adversarial Aware Security 

      Yamin, Muhammad Mudassar; Ullah, Mohib; Ullah, Habib; Katt, Basel; Hijji, Mohammad; Muhammad, Khan (Peer reviewed; Journal article, 2022)
      Open-source intelligence (OSINT) tools are used for gathering information using different publicly available sources. With the rapid advancement in information technology and excessive use of social media in our daily ...
    • MoMo: Mouse-Based Motion Planning for Optimized Grasping to Declutter Objects Using a Mobile Robotic Manipulator 

      Jagatheesaperumal, Senthil Kumar; Rajamohan, Varun Prakash; Saudagar, Abdul Khader Jilani; AlTameem, Abdullah; Sajjad, Muhammad; Muhammad, Khan (Peer reviewed; Journal article, 2023)
      The aim of this study is to develop a cost-effective and efficient mobile robotic manipulator designed for decluttering objects in both domestic and industrial settings. To accomplish this objective, we implemented a deep ...
    • On a Low-Rank Matrix Single-Index Model 

      Mai, The Tien (Journal article; Peer reviewed, 2023)
    • Optimized Deep-Learning-Based Method for Cattle Udder Traits Classification 

      Afridi, Hina; Ullah, Mohib; Nordbø, Øyvind; Alaya Cheikh, Faouzi; Larsgard, Anne Guro (Peer reviewed; Journal article, 2022)
      We propose optimized deep learning (DL) models for automatic analysis of udder conformation traits of cattle. One of the traits is represented by supernumerary teats that is in excess of the normal number of teats. ...
    • Parameterization of a Novel Nonlinear Estimator for Uncertain SISO Systems with Noise Scenario 

      Azar, Ahmad Taher; Abdul-Majeed, Farah Ayad; Majdi, Hasan Sh.; Hameed, Ibrahim A.; Kamal, Nashwa Ahmad; Jawad, Anwar Jaafar Mohamad; Abbas, Ali Hashim; Abdul-Adheem, Wameedh Riyadh; Ibraheem, Ibraheem Kasim (Peer reviewed; Journal article, 2022)
      Dynamic observers are commonly used in feedback loops to estimate the system’s states from available control inputs and measured outputs. The presence of measurement noise degrades the performance of the observer and ...
    • Reliable Genetic Correlation Estimation via Multiple Sample Splitting and Smoothing 

      Mai, The Tien (Peer reviewed; Journal article, 2023)
      In this paper, we aim to investigate the problem of estimating the genetic correlation between two traits. Instead of making assumptions about the distribution of effect sizes of the genetic factors, we propose the use of ...
    • Second-Order Spatial-Temporal Correlation Filters for Visual Tracking 

      Yu, Yufeng; Chen, Long; He, Haoyang; Liu, Jianhui; Zhang, Weipeng; Xu, Guoxia (Peer reviewed; Journal article, 2022)
      Discriminative correlation filters (DCFs) have been widely used in visual object tracking, but often suffer from two problems: the boundary effect and temporal filtering degradation. To deal with these issues, many DCF-based ...
    • Towards Efficient and Trustworthy Pandemic Diagnosis in Smart Cities: A Blockchain-Based Federated Learning Approach 

      Abdel-Basset, Mohamed; Alrashdi, Ibrahim; Hawash, Hossam; Sallam, Karam; Hameed, Ibrahim A. (Peer reviewed; Journal article, 2023)
      In the aftermath of the COVID-19 pandemic, the need for efficient and reliable disease diagnosis in smart cities has become increasingly serious. In this study, we introduce a novel blockchain-based federated learning ...
    • Variational Inference over Nonstationary Data Streams for Exponential Family Models 

      Masegosa, Andres; Ramos-López, Dario; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D. (Peer reviewed; Journal article, 2020)
      In many modern data analysis problems, the available data is not static but, instead, comes in a streaming fashion. Performing Bayesian inference on a data stream is challenging for several reasons. First, it requires ...