Proposed Algorithm. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Comparisons between ADAM and NADAM optimizers. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses حسب Meichen Liu (8168148)

Secure MANET routing with blockchain-enhanced latent encoder coupled GANs and BEPO optimization حسب Sandeep Jagonda Patil (22048337)

"…The performance of the proposed LEGAN-BEPO-BCMANET technique attains 29.786%, 19.25%, 22.93%, 27.21%, 31.02%, 26.91%, and 25.61% greater throughput, compared to existing methods like Blockchain-based BATMAN protocol utilizing MANET with an ensemble algorithm (BATMAN-MANET), Block chain-based trusted distributed routing scheme with optimized dropout ensemble extreme learning neural network in MANET (DEELNN-MANET), A secured trusted routing utilizing structure of a new directed acyclic graph-blockchain in MANET internet of things environment (DAG-MANET), An Optimized Link State Routing Protocol with Blockchain Framework for Efficient Video-Packet Transmission and Security over MANET (OLSRP-MANET), Auto-metric Graph Neural Network based Blockchain Technology for Protected Dynamic Optimum Routing in MANET (AGNN-MANET) and Data security-based routing in MANETs under key management process (DSR-MANET) respectively.…"

<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

"…<b>(C)</b> The whole training data is then scanned, searching for these sequences and deriving a re-encoded dataset where interaction terms are binary features (i.e., 1 if sequence <i>i</i> is observed in <i>j</i>-th patient genotype, 0 otherwise). …"

The illustration depicts our CQ-CNN architecture for binary image classification. حسب Mominul Islam (3513758)

The steps of proposed method of RWMA detection using echocardiography images for RWMA detection, consisting with cardiac structure segmentation using a trained U-Net on both A4C an... حسب Sazzli Kasim (11218558)

LITNET-2020 data splitting approach. حسب Asmaa Ahmed Awad (16726315)

Analysis and design of algorithms for the manufacturing process of integrated circuits حسب Sonia Fleytas (16856403)

An Example of a WPT-MEC Network. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Related Work Summary. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Simulation parameters. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Training losses for N = 10. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Normalized computation rate for N = 10. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Summary of Notations Used in this paper. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Related studies on IDS using deep learning. حسب Arshad Hashmi (13835488)

"…<div><p>Due to the recent advances in the Internet and communication technologies, network systems and data have evolved rapidly. The emergence of new attacks jeopardizes network security and make it really challenging to detect intrusions. …"

The architecture of the BI-LSTM model. حسب Arshad Hashmi (13835488)

"…<div><p>Due to the recent advances in the Internet and communication technologies, network systems and data have evolved rapidly. The emergence of new attacks jeopardizes network security and make it really challenging to detect intrusions. …"

Comparison of accuracy and DR on UNSW-NB15. حسب Arshad Hashmi (13835488)

"…<div><p>Due to the recent advances in the Internet and communication technologies, network systems and data have evolved rapidly. The emergence of new attacks jeopardizes network security and make it really challenging to detect intrusions. …"

Comparison of DR and FPR of UNSW-NB15. حسب Arshad Hashmi (13835488)

"…<div><p>Due to the recent advances in the Internet and communication technologies, network systems and data have evolved rapidly. The emergence of new attacks jeopardizes network security and make it really challenging to detect intrusions. …"

Optimal Timings Codebook.xlsx حسب Emma Spillane (11249121)