Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering by Saadia Jamil (22045946)

“…This raises basic problems like the need for a dimensionality reduction technique for optimal selection of features, fusing the data of different views, and maintaining the inter- and intra-consensus of the multiview dataset. …”

Land Use/Land Cover Changes Impact on Groundwater Level and Quality in the Northern Part of the United Arab Emirates by Elmahdy, Samy

“…Each pair of enhanced LULC maps (1990–2000, 2000–2010, 2010–2018, and 1990–2018) were used as input data for an image difference algorithm to monitor LULC changes. …”
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Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method by Mohamed Massaoudi (16888710)

A Survey of Machine Learning Innovations in Ambulance Services: Allocation, Routing, and Demand Estimation by Reem Tluli (22282702)

A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study by Masurkar, Faeez

“…Further, As the quality of received signals differs at different sensing points as a result of the surface conditions of the specimen, the Self Adaptive Smart Algorithm (SASA) method was adopted to filter out the noise and accurately pinpoint the defect reflected wave packet which ultimately aids in better detection and localization. …”
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The use of multi-task learning in cybersecurity applications: a systematic literature review by Shimaa Ibrahim (22155739)

“…Five critical applications, such as network intrusion detection and malware detection, were identified, and several tasks used in these applications were observed. …”

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)

“…We conducted a comparative analysis of various models and algorithms used in the related works. The results indicated that our proposed approach outperforms others, showcasing its effectiveness in both detecting and mitigating DDoS attacks within SDNs. …”

Practical Multiple Node Failure Recovery in Distributed Storage Systems by Itani, M.

“…Fast convergence validates the efficacy of our algorithms for different system parameters. Simulation results are shown to be close to optimal for the case of newly arriving blocks.…”
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Building power consumption datasets: Survey, taxonomy and future directions by Yassine Himeur (14158821)

“…Based on the analytical study, a novel dataset has been presented, namely Qatar university dataset, which is an annotated power consumption anomaly detection dataset. The latter will be very useful for testing and training anomaly detection algorithms, and hence reducing wasted energy. …”

Enhancing building sustainability: A Digital Twin approach to energy efficiency and occupancy monitoring by Aya Nabil Sayed (17317006)

“…Our data-driven occupancy detection approach utilized Machine Learning (ML) algorithms to intelligently determine room occupancy, allowing for precise energy management based on real-time usage patterns. …”

Effective dispatch strategies assortment according to the effect of the operation for an islanded hybrid microgrid by Sk.A. Shezan (21323048)

“…The proposed off-grid microgrid's CO₂emissions, total net present cost (NPC), and the Levelized cost of energy (LCOE) have all been optimized. In HOMER software, all the possible dispatch algorithms were analyzed, and the power system responses and reliability study were carried out using DIgSILENT PowerFactory. …”

C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments by Raun, Kristo

“…The aim of streaming conformance checking is to find dis crepancies between process executions on streaming data and the refer ence process model. The state-of-the-art output from streaming confor mance checking is a prefix-alignment. …”
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Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

Learning-Based Space-Time Adaptive Processing by El Khatib, Alaa

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Information reconciliation through agent controlled graph model. (c2018) by Saba, Rita

“…Even though prevention techniques exist, they’re not enough to fully secure the data from malicious activities. Thus, the need for a detection and recovery algorithm to assess the damage and bring the database back to its consistent state in case of an attack. …”
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Boosting the visibility of services in microservice architecture by Ahmet Vedat Tokmak (17773479)

“…In this research, we evaluate the performance of several classification algorithms for estimating the quality of microservices using the QWS dataset containing traffic data of 2505 microservices. …”

Generative AI revolution in cybersecurity: a comprehensive review of threat intelligence and operations by Mueen Uddin (4903510)

“…<p dir="ltr">Cyber threats are increasingly frequent in today’s world, posing challenges for organizations and individuals to protect their data from cybercriminals. On the other hand, Generative Artificial Intelligence (GAI) technology offers an efficient way to automatically address these issues with the help of AI models and algorithms. …”

Bridge Structural Health Monitoring Using Mobile Sensor Networks by Amin, Fouad

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Empowering IoT Resilience: Hybrid Deep Learning Techniques for Enhanced Security by Muhammad Maaz (5600600)

“…The time efficiency of both proposed algorithms renders them well-suited for deployment in IoT ecosystems. …”

Blue collar laborers’ travel pattern recognition: Machine learning classifier approach by Aya Hasan Alkhereibi (17151070)

“…A pattern recognition model is applied to a revealed preference (RP) survey obtained from the Ministry of Transportation and Communication (MoTC) in Qatar for the travel diary for blue-collar workers. Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …”