Image-CNN Based Process Control of Profile by Zeinab, Zeinab Jihad

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Application of Data Mining to Predict and Diagnose Diabetic Retinopathy by Haniyeh, Maryam

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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series by Lasfer, Assia

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Improving MRI Resolution: A Cycle Consistent Generative Adversarial Network-Based Approach for 3T to 7T Translation by Zakaria Shams Siam (22048001)

“…However, the exorbitant expenses associated with 7T MRI scanners hinder their broad use in research and clinical facilities. Efforts are underway to develop algorithms that can generate 7T MRI from 3T MRI to achieve better image quality without the need for 7T MRI machines. …”

Scrambled Prime Key Encryption by Haraty, Ramzi A.

“…To enhance data security different cryptographic algorithms are used. Nevertheless, but the fast increase in computers' speed may threaten these algorithms. …”
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Towards Multimedia Fragmentation by Saad, Samir

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Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review by Arfan Ahmed (17541309)

“…Wearable devices (WDs) make use of sensors historically reserved for hospital settings. …”

Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases by Muhammad Ali Muzammil (17910611)

“…To guarantee a safe and successful deployment in clinical practice, the use of AI in cardiology must be done with a thorough understanding of the algorithms and their limits. …”

Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort by Mohamed Adil Shah Khoodoruth (14589828)

“…Key measurements included complete blood count, lipid panel, HbA1c, and ferritin levels. Our findings indicated elevated body mass index (BMI) and triglyceride (TG) levels in both patient groups compared to controls. …”

Data Redundancy Management in Connected Environments by Mansour, Elio

“…To address these limitations, we propose a framework for data redundancy management at the device level, denoted DRMF. We describe its modules, and clustering-based algorithms. …”
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Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

“…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”

Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review by Yazeed Yasin Ghadi (16667109)

“…Furthermore, this study also focuses on different Machine learning algorithms that are used to secure wireless sensor networks. …”

Triage decisions for ICU admission by Blanch, Lluis

“…The team made recommendations and concluded that triage should be led by intensivists considering input from nurses, emergency medicine professionals, hospitalists, surgeons, and allied professionals. Triage algorithms and protocols can be useful but can never supplant the role of skilled intensivists basing their decisions on input from multidisciplinary teams. …”
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Data redundancy management for leaf-edges in connected environments by Mansour, Elio

“…To address these limitations, we propose here DRMF: Data Redundancy Management for leaF-edges allowing to identify and remove data redundancies in connected environments at the device level. DRMF considers both static and mobile edge devices, and provides two algorithms for temporal and spatio-temporal redundancy detection. …”
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Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper by Mutaz I. Othman (21186827)

“…</p><h3>Methods</h3><p dir="ltr">A discursive approach was used to optimise nurse–patient assignments and the impact of ML models. …”

Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures by JUMA, MAZEN GHAZI

“…The technology stack was also enhanced with three new algorithms and five protocols. The proposed solution was optimized using the iterative four-objective cycle based on previous primary phase results. …”
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Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying by Tekli, Joe

“…Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. …”
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Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling by Majed Hadid (17148364)

“…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. The experimental results indicate the positive effect of clustering similar appointments on the performance measures and the computational time. …”

Design and analysis of efficient and secure elliptic curve cryptoprocessors. by Al-Somani, Turki Faisal

“…Elliptic Curve Cryptosystems have attracted many researchers and have been included in many standards such as IEEE, ANSI, NIST, SEC and WTLS. The ability to use smaller keys and computationally more efficient algorithms compared with earlier public key cryptosystems such as RSA and ElGamal are two main reasons why elliptic curve cryptosystems are becoming more popular. …”
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Optimal Dispatch of Mobile Energy Storage Unit to Support EV Charging Stations by Elmeligy, Mohamed Mostafa Abdelazim

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