Multi-marker-LD based genetic algorithm for tag SNP selection by Mansour, Nashat

“…The performance of the three algorithms are compared with those of a recognized tag SNP selection algorithm using three different real data sets from the HapMap project. …”
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Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy by Raad, M.W.

“…The classification technique has the unique feature of cutting down the computation largely by only allowing the event of interest to be executed by a particular algorithm. The set-up was also tested with random signals from a 137Cs test source. …”
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A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

“…We present experimental results that demonstrate the effectiveness of our method while outperforming reported techniques.…”
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Advancing Data Center Networks: A Focus on Energy and Cost Efficiency by Zina Chkirbene (16869987)

“…These topologies must incorporate fault-tolerant and efficient routing algorithms. Consequently, the data center network topology must dynamically adapt to ever-changing application requirements. …”

A New Hamiltonian Semi-Analytical Approach to Vibration Analysis of Piezoelectric Multi-Layered Plates by Andrianarison, O.

“…The whole piezoelectric multilayered plate’s dynamic stiffness is then built, from which its circular frequencies are computed with the help of the Wittrick-Williams algorithm. A detailed discussion is provided on the implementation aspects, followed by some numerical examples to assess the robustness, accuracy and effectiveness of the proposed method. …”
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Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic by AL MANSOORI, MOUZA

“…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. In this study, we used twitter as our data source. …”
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Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection by HAMDALLAH, KHALID WAJIH TURKI

“…The data was used as training and testing sets to analyze certain machine learning algorithms in terms of performance (cost / benefit analysis) and accuracy (mean error square and confusion matrix). …”
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Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks by Mohammed Almehdhar (22046597)

“…We highlight the transition from traditional signature-based to anomaly-based detection methods, emphasizing the significant advantages of AI-driven approaches in identifying novel and sophisticated intrusions. …”

Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”

The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions by Abdulmalik Alwarafy (17984104)

“…Then, we provide a comprehensive review of the most widely used DRL algorithms to address RRAM problems, including the value- and policy-based algorithms. …”

UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks by Ebrahimi, Dariush

“…Moreover, we propose a set of effective algorithms to generate solutions for relatively large-scale network scenarios. …”
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Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment by Omer, Dalia Fatahelrahman

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ThoraX-PriorNet: A Novel Attention-Based Architecture Using Anatomical Prior Probability Maps for Thoracic Disease Classification by Md. Iqbal Hossain (723299)

Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices by Neder Karmous (19743430)

Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu by Ayesha Atif (22155133)

Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle by Reza Jafari (3494018)

“…<p dir="ltr">This study presents an innovative solution for simultaneous energy optimization and dynamic yaw control of all-wheel-drive (AWD) electric vehicles (EVs) using deep reinforcement learning (DRL) techniques. To this end, three model-free DRL-based methods, based on deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and TD3 enhanced with curriculum learning (CL TD3), are developed for determining optimal yaw moment control and energy optimization online. …”

Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm by Saima Hassan (14918003)

“…Analysis of the performance, on the same data-sets, reveals that the proposed GOAIT2FELM could be a better approach for improving the accuracy of the IT2-FLS as compared to other variants of the optimized IT2-FLS.…”

Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet by Vineet Dhanawat (22361395)

“…This paper proposes an efficient deep BiLSTMNet model to solve and mitigate these problems. …”

KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…Several techniques have been proposed in the literature to add some semblance of balance to the data sets by adding artificial data points. Synthetic Minority Oversampling Technique(SMOTE) and Adaptive Synthetic Sampling(ADASYN) are some of the commonly used techniques to deal with class imbalance. …”