Efficient Test Compaction for Combinational Circuits Based on Fault Detection Count-Directed Clustering حسب El-Maleh, Aiman H.

"…Test compaction is an effective technique for reducing test data volume and test application time. In this paper, we present a new static test compaction algorithm based on test vector decomposition and clustering. …"
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai حسب ALGHANEM, HANI SUBHI MOHD

"…My research aims to develop a data-driven decision support framework for fleet management, focusing on leveraging advanced algorithms, including decision trees and random forests, to generate domain-specific AI models. …"
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Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks حسب Daou, Leonardo

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Optimized provisioning of edge computing resources with heterogeneous workload in IoT networks حسب Kherraf, Nouha

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Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression حسب Alaa Abd-Alrazaq (17430900)

"…<p dir="ltr">Given the limitations of traditional approaches, wearable artificial intelligence (AI) is one of the technologies that have been exploited to detect or predict depression. The current review aimed at examining the performance of wearable AI in detecting and predicting depression. …"

Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling حسب 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. …"

Energy-Efficient VoI-Aware UAV-Assisted Data Collection in Wireless Sensor Networks حسب 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. …"
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks حسب Najam Us Sahar Riyaz (22927843)

"…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …"

Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment حسب Farhat Mahmood (15468854)

"…However, it does not account for the inaccuracies and uncertainties existing in the system, leading to sub-optimal temperatures. Therefore, this study proposes a comprehensive data-driven robust model predictive control framework for greenhouse temperature control and its energy utilisation assessment in the presence of uncertainties. …"

Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain حسب Farshad Rahimi Ghashghaei (20880995)

Assigning proctors to exams using scatter search. (c2006) حسب Zeidan, Moujab Moustapha

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Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives حسب Yassine Himeur (14158821)

"…If leveraged properly, that data could assist end-users, energy producers and utility companies in detecting anomalous power consumption and understanding the causes of each anomaly. …"

A collaborative filtering recommendation framework utilizing social networks حسب Aamir Fareed (17019087)

Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control حسب Farhat Mahmood (15468854)

"…The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. The multilayer perceptron model is trained using historical data from the greenhouse with solar radiation, outside temperature, humidity difference, fan speed, HVAC control as the input parameters to predict the temperature. …"

Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights حسب Malekloo, Arman

"…In the age of the smart city, Internet of Things (IoT), and big data analytics, the complex nature of data-driven civil infrastructures monitoring frameworks has not been fully matured. …"
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Security in wire/wireless networks: sniffing attacks prevention/detection techniques in LAN networks & the effect on biometric technology حسب Al-Hemairy, Moh'd Hussain

"…Based on the surprising experimental results done by a previous study in the security lab which proposed an optimal algorithm to enhance their ability against the two famous network attacks; we implemented the proposed algorithm by this study and stimulate the experiment in order to test the algorithm performance. …"
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A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata حسب Siddiqui, Ansah Juned

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A Comprehensive Review of Digital Twin Technology in Building Energy Consumption Forecasting حسب Maissa Boukaf (22282279)

"…The digitalization of building energy forecasting systems, enhanced by Energy Digital Twin technology alongside IoT devices and advanced data-driven algorithms, offers substantial improvements in energy management and optimization, servicing, maintenance, and energy-efficient design. …"

Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks حسب Mohammed Almehdhar (22046597)

"…<p dir="ltr">The rapid evolution of modern automobiles into intelligent and interconnected entities presents new challenges in cybersecurity, particularly in Intrusion Detection Systems (IDS) for In-Vehicle Networks (IVNs). …"

Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) حسب Bitar, Mandy

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