Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

“…The proposed approach delivers an improvement of around 44% in training time while maintaining accuracy using single-core processing as compared to non-clustering models.…”

A Secure and Decentralized Blockchain Based EV Energy Trading Model Using Smart Contract in V2G Network by Atif Iqbal (5504636)

Developing a Cooperative Behavior for Multi Agents System Application to Robot Soccer by Idlan, Ayman Hashim

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Mapping realistic data sets on parallel computers by Mansour, N.

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GENETIC SCHEDULING OF TASK GRAPHS by Benten, M. S.

“…The problem of assigning tasks to processing elements as a combinatorital optimization is formulated, and a heuristic based on a genetic algorithm is presented. …”
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Localization of Damages in Plain And Riveted Aluminium Specimens using Lamb Waves by S. Andhale, Yogesh

“…The TOA data of the wave reflected from the damage is used in the two arrival time difference and astroid algorithms to locate the damage in an enclosed area. …”
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Mobile Robot Navigation in Dynamic Environments Using an Improved RRT* Approach by Mohammed, Hussein Ali

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

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Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

“…The learned system can apply sensor allocation online, works in real-time, and selects one radar and one camera at a time without having to reevaluate a cost function at every time step. …”
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Vehicular-OBUs-As-On-Demand-Fogs by Sami, Hani

“…Observing the headway in vehicular industry, new applications are developed demanding more resources. For instance, real-time vehicular applications require fast processing of the vast amount of generated data by vehicles in order to maintain service availability and reachability while driving. …”
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Spacecraft spin axis attitude determination by Emara-Shabaik, H.E.

“…The results show a tradeoff between estimation accuracy and computational requirements. One algorithm is about three times more accurate than the other and is therefore recommended even though it requires about 20% more in computer storage and operations, and about 50% more in central processing unit time…”
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Wavelet Analysis- Singular Value Decomposition Based Method for Precise Fault Localization in Power Distribution Networks Using k-NN Classifier by Abhishek Raj (7245425)

“…Additionally, the computational efficiency of the algorithm is evidenced by an average processing time of 0.0764 seconds per fault event, making it well-suited for real-time applications.…”

Indoor Localization Schemes for Mobile Robots by Al-Jarrah, Islam Mohammad-Amin

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Estimating Vehicle State by GPS/IMU Fusion with Vehicle Dynamics by Saadeddin, Kamal Mohamad

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Portable Electromagnetic Surface Profiling System by Al Homssi, Bassel Mohamad

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A novel few shot learning derived architecture for long-term HbA1c prediction by Marwa Qaraqe (10135172)

“…More importantly, the study specifically targeted the pediatric Type-1 diabetic population, as an early prediction of elevated HbA1c levels could help avert severe life-threatening complications in these young children. Short-term CGM time-series data are processed using both novel image transformation approaches, as well as using conventional signal processing methods. …”

Recovery of business intelligence systems by Haraty, Ramzi A.

“…Reducing the execution time of recovery is the key target of our algorithm. …”
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Supervised term-category feature weighting for improved text classification by Attieh, Joseph

“…Text classification is a central task in Natural Language Processing (NLP) that aims at categorizing text documents into predefined classes or categories. …”
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Digital Image Watermarking Using Balanced Multiwavelets by Ghouti, L.

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“Adaptive Control Technique Using Multilayer Feedforward Neural Networks” by Al-Duwaish, H.

“…This paper presents a new method for implementing adaptive controllers using multilayer feedforward neural networks (MFNN). The controlled process is approximated at each sampling time by a linear time-invariant (LTI) model. …”
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