Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... by Tarik Elhadd (5480393)

“…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…”

Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study by Abido, M.A.

“…A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

“…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

“…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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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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Practical single node failure recovery using fractional repetition codes in data centers by Itani, May

“…Hence, a practical solution for node failures is presented by using a self-designed genetic algorithm that searches within the feasible solution space. …”
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Scatter search for homology modeling by Mansour, Nashat

“…Results obtained by our SS algorithm are compared with other approaches. The 3D models predicted by our algorithm show improved root mean standard deviations with respect to the native structures.…”
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KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …”

TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …”

Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm by Mostafa Jabari (21841727)

“…The study evaluates the BDGOA by applying it to identify unknown parameters of five solar modules. The algorithm's effectiveness is demonstrated through the extraction of parameters for RTC France, PWP201, SM55, KC200GT, and SW255 models, validated against experimental data under diverse conditions. …”

Sentiment visualization of correlation of loneliness mapped through social intelligence analysis by Hurmat Ali Shah (18192889)

“…Social media platforms have become a valuable source of data to study this phenomenon.</p><h3>Objectives</h3><p dir="ltr">This paper aims to visualize the frequency of loneliness-related themes and topics in Twitter data. …”

Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar (16904526)

“…Several dataset analysis models are utilised to study the data diversity. Further, this study demonstrates the application of neural network-based models to effectively predict the permeability. …”

Development of a cerebral aneurysm segmentation method to prevent sentinel hemorrhage by Yousra Regaya (17788964)

The Detection of Dysarthria Severity Levels Using AI Models: A Review by Afnan Al-Ali (16888695)

Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models by EZZELDIN, KHALED MOHAMED KHALED

“…Additionally, the GRU-CNN hybrid model attained a notable accuracy of 90%. These findings establish the robustness and effectiveness of hybrid architectures in enhancing emotion recognition accuracy in Arabic speech data, presenting a novel approach for Arabic dialect sentiment analysis.…”
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Energy-Efficient VoI-Aware UAV-Assisted Data Collection in Wireless Sensor Networks by Kalash, Saeddin

“…To address these objectives, our proposed approach incorporates deep reinforcement learning (RL-DQN) techniques to optimize UAV deployment, minimizing the number of UAVs while maximizing the number of successfully collected SNs with non-redundant data. The model considers VoI and energy constraints of the SNs, enhancing both efficiency and sustainability. …”
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Developing a framework for using face recognition in transit payment transactions by HABEH, ORABI MOHAMMAD ABDULLAH

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DNA Base-Calling Techniques by Odeh, Fadi

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Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

“…Furthermore, this paper demonstrates the advantages of the developed ADL algorithm approach and DSM prediction of the DT using vector autoregressive model for anomaly detection in utility gas turbines with data from an operational power plant.…”

Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms by Abdelouahed Hamdi (14158899)

“…It was found that when solving the Mean-CVaR model with evolutionary algorithms, the risk decreased. …”