Taher Al‐Shehari

A Novel Deep Reinforcement Learning Framework for Energy Management and Prediction in Smart Cities

Taher Al‐Shehari, Malaiyalathan Adimoolam, Kamalakannan Maithili, Nasser A Alsadhan et autres

ABSTRACT Machine learning and deep learning algorithms have recently been progressively integrated into business intelligence for smart city management. Predicting smart city energy utilisation is crucial for sustainable growth and resource efficiency and become essential due to the growing challenges and demands …

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Multi-stage Alzheimer’s Disease Classification Using Squeeze Excitation Light Channel Network with a Random Lyrebird: Achieving High Sensitivity and Precision in Early Detection

Rakan A. Alsowail, Taher Al‐Shehari

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LEFAM: Lightweight scalable efficient failover authentication mechanism for fog-based IoT environment

Mohammad Abdussami, Sanjeev Kumar Dwivedi, Ruhul Amin, Cheng‐Chi Lee et autres

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CyberSentry: Enhancing SCADA security through advanced deep learning and optimization strategies

Alaa O. Khadidos, Adil O. Khadidos, Shitharth Selvarajan, Taher Al‐Shehari et autres

SCADA systems form the core of infrastructural facilities, including power grids, water treatment facilities, and industrial processes. Changing cyber threats present increasingly sophisticated attacks against which traditional security models inadequately protect SCADA systems. These traditional models usually have drawbacks in the way …

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A secure medical image encryption technique based on DNA cryptography with elliptic curves

Vigna Kumaran, T. T. Manikandan, Rajesh Kumar Dhanaraj, Taher Al‐Shehari et autres

Health services and telemedicine have proven to be an important area for information protection in research, especially with medical services and smart health care applications. In these systems, medical imaging protection are important not only for clinical diagnosis, but also to protect …

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Intelligent traffic congestion forecasting using BiLSTM and adaptive secretary bird optimizer for sustainable urban transportation

Lalitha Krishnasamy, C. Siva, Rajesh Kumar Dhanaraj, Mahmoud Ahmad Al-Khasawneh et autres

Traffic congestion forecasting is one of the major elements of the Intelligent Transportation Systems (ITS). Traffic congestion in urban road networks significantly influences sustainability by increasing air pollution levels. Efficient congestion management enables drivers to bypass heavily trafficked areas and reducing pollutant …

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An algorithm for heterogeneous wireless network connections for user preferences and services

Sriram Krishnan, A. V. Daniel, Sudha Ayyasamy, Balamurugan Balusamy et autres

Heterogeneous wireless networks (HWNs) present a challenge in selecting the optimal network for user devices due to the overlapping availability of multiple networks. In order to help users choose the best HWN connection, this research is trying to build a decision-making framework …

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A modernized approach to sentiment analysis of product reviews using BiGRU and RNN based LSTM deep learning models

L. Godlin Atlas, Balamurugan Balusamy, Shitharth Selvarajan, Taher Al‐Shehari et autres

With the advent of Web 2.0 and popularization of online shopping applications, there has been a huge upsurge of user generated content in recent times. Leading companies and top brands are trying to exploit this data and analyze the market demands and …

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IoT driven healthcare monitoring with evolutionary optimization and game theory

Shitharth Selvarajan, Hariprasath Manoharan, Taher Al‐Shehari, Nasser A Alsadhan

In this paper the game theory procedures are applied for healthcare monitoring systems and it is analysed using two types of evolutionary algorithms that incorporate Artificial Intelligence (AI) based events. As most of the existing approaches face challenges in establishing real-time connectivity, …

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Advancing object detection performance: random replacement one–one optimized convolutional LeNet algorithm with novel strategies for improved efficiency

Rakan A. Alsowail, Taher Al‐Shehari

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A novel hybrid architecture for video frame prediction: combining convolutional LSTM and 3D CNN

C. V. Aravinda, Taher Al‐Shehari, Nasser A Alsadhan, Shashank Shetty et autres

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Correction: Predictive modeling of ALS progression: an XGBoost approach using clinical features

Richa Gupta, Taher Al‐Shehari, Mohammed Kadrie, Taha M. Alfakih et autres

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