Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

“…We build our model using machine learning techniques in particular rule-based models. These have a white-box nature which gives the classification as well as the reason for it making them attractive to experts in the domain. …”
Get full text
Get full text

A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…We present a structured taxonomy covering value-based, policy-based, actor-critic, model-based, and advanced multi-agent and multi-objective approaches, and link algorithms to tasks such as dispatch, microgrid coordination, real-time pricing, load balancing, and demand–response. …”

Recent advances on artificial intelligence and learning techniques in cognitive radio networks by Abbas, Nadine

“…The literature survey is organized based on different artificial intelligence techniques such as fuzzy logic, genetic algorithms, neural networks, game theory, reinforcement learning, support vector machine, case-based reasoning, entropy, Bayesian, Markov model, multi-agent systems, and artificial bee colony algorithm. …”
Get full text
Get full text
Get full text
Get full text

Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images by Rehan Raza (17019105)

“…Moreover, it is faster and requires fewer parameters to train than other CNN based models, making it a good choice for large-scale deployment in clinical settings and a promising tool for automated lung cancer diagnosis from CT scan images.…”

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…This method offers precise endotoxin classification and holds significant potential for expedited medical diagnoses and therapeutic decision-making in cases of pathogenic infections. ConclusionWe present the effectiveness of DeepRaman, an innovative architecture inspired by the Progressive Fourier Transform and integrated with the scalogram transformation method, in classifying raw SERS Raman spectral data from biological specimens with unparalleled accuracy relative to conventional machine learning algorithms. …”
Get full text
Get full text
Get full text

From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

“…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”

Using machine learning to support students’ academic decisions by ALLAH, AISHA QASIM GHAZAL FATEH

“…This approach uses other students’ grades to make a prediction. This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
Get full text

Modeling and Control of Nonlinear Systems Using Wavelet Networks by Hassouneh, Wissam

Get full text

CEAP by Abdel Wahab, Omar

“…The infrastructureless and decentralized nature of Vehicular Ad Hoc Network (VANET) makes it quite vulnerable to different types of malicious attacks. …”
Get full text
Get full text
Get full text
Get full text

Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier by JAIN, SWETA

“…The hyper parameters are optimized with DM optimization algorithm which improves the accuracy of classifier. …”
Get full text
Get full text

Random vector functional link network: Recent developments, applications, and future directions by A.K. Malik (16003193)

“…To overcome these issues, randomization based neural networks such as random vector functional link (RVFL) network have been proposed. …”

Applications of fast fourier transform in the integrity evaluation of deep foundations by Abi Shdid, Caesar

“…The method is developed and validated using experimental data, and is based on applying the fast Fourier transform mapping algorithm on data obtained from cross-hole sonic logging. …”
Get full text
Get full text
Get full text
Get full text

PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits by Hind Almerekhi (7434776)

“…<p>Promoting healthy discourse on community-based online platforms like Reddit can be challenging, especially when conversations show ominous signs of toxicity. …”

Optimized 3D Deployment of UAV-Mounted Cloudlets to Support Latency-Sensitive Services in IoT Networks by Islambouli, Rania

“…We formulate the problem as a mixed integer program, and propose an efficient meta-heuristic solution based on the ions motion optimization algorithm. …”
Get full text
Get full text
Get full text
Get full text

Cooperative clustering models for Vehicular ad hoc networks. (c2013) by Abdel Wahab, Omar Mohammad

Get full text
Get full text

Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations by Md Mosarrof Hossen (21399056)

“…<p>Human behavior significantly impacts domestic energy consumption, making it essential to monitor and improve these consumption patterns. …”

Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects by Mohamed Massaoudi (16888710)

“…In this context, SG stands tied very closely to Deep Learning (DL) as an emerging technology for creating a more decentralized and intelligent energy paradigm while integrating high intelligence in supervisory and operational decision-making. Motivated by the outstanding success of DL-based prediction methods, this article attempts to provide a thorough review from a broad perspective on the state-of-the-art advances of DL in SG systems. …”

Developing an online hate classifier for multiple social media platforms by Joni Salminen (7434770)

“…While all the models significantly outperform the keyword-based baseline classifier, XGBoost using all features performs the best (F1 = 0.92). …”

Distinguishing Between Fake and Real Smiles Using EEG Signals and Deep Learning by Moussa, Mostafa Mohamed

Get full text

A Framework for Predictive Modeling in Sustainable Projects by Labban, Tarek

Get full text