Spatially-Distributed Missions With Heterogeneous Multi-Robot Teams حسب Eduardo Feo-Flushing (23276023)

"…Both combine a generic MILP solver and a genetic algorithm, resulting in efficient anytime algorithms. …"

CoLoSSI: Multi-Robot Task Allocation in Spatially-Distributed and Communication Restricted Environments حسب Ishaq Ansari (22047902)

"…<p dir="ltr">In our research, we address the problem of coordination and planning in heterogeneous multi-robot systems for missions that consist of spatially localized tasks. Conventionally, this problem has been framed as a task allocation problem that maps tasks to robots. …"

Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units حسب Shanableh, Tamer

"…The data embedding algorithm guarantees that a maximum of one partition is modified per message segment, therefore, in a given CU, either 0, 1 or 2 partitions are modified. …"
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Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk حسب Mohamed Chaouch (17983846)

"…<p dir="ltr">This paper introduces novel nonparametric supervised learning techniques for classifying massive datasets, addressing key limitations of existing methods in Big and Streaming Data framework. …"

Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm حسب Ayman Khallel Al-Ani (17541447)

"…Furthermore, a route management technique is combined with Artificial Intelligence (AI) algorithm to transmit the data to appropriate central servers. …"

STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization حسب Muhammad Salman Khan (7202543)

"…In this paper, a novel speech separation algorithm is proposed that integrates the twin-delayed deep deterministic (TD3) policy gradient reinforcement learning (RL) agent with the expectation maximization (EM) algorithm for clustering the spatial cues of individual sources separated on azimuth. …"

A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT حسب Dhananjay Bisen (19482454)

On-site workshop investment problem: A novel mathematical approach and solution procedure حسب Nima Moradi (19418821)

A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks حسب Umesh Kumar Lilhore (17727684)

"…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …"

A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems حسب Faria Nawshin (21841598)

"…<p dir="ltr">Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. However, the increasing adoption of FL in these devices exposes them to adversarial attacks that can compromise user data and device security. …"

Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification حسب Rajendra Babu Chikkala (22330876)

"…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …"

Sentiment Mining of Arabic Twitter Data حسب Ahmed, Soha Galalaldin Khider

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Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence حسب Atiq Ur Rehman (8843024)

"…Keeping in view the need of an optimization algorithm with fast convergence speed, suitable for high dimensional data space, this article proposes a novel concept of Multi-Cluster Jumping PSO. …"

Data Redundancy Management in Connected Environments حسب Mansour, Elio

"…In this work, we focus on managing sensor data redundancies in connected environments. Existing works often suffer from (i) disregarding either network core or edge device redundancies; (ii) disregarding the limited capabilities of edge devices; and (iii) disregarding sensors mobility and the dynamicity of the network. …"
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Unsupervised outlier detection in multidimensional data حسب Atiq ur Rehman (14153391)

"…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …"

Novel algorithms for accurate DNA base-calling حسب Mohammed, Omniyah Gul

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The Effects of Data Mining on Small Businesses in Dubai حسب AlMutawa, Rasha

"…While there are numerous studies on the best data mining models and their uses, even on certain industries, this study focuses on the applications more than the algorithms and models and their usefulness for small businesses specifically. …"
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting حسب Mohamed Massaoudi (16888710)

"…First, the NARXNN model acquires the data to generate a residual error vector. Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …"

Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks حسب Hassan, Yasmin Adel

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Data redundancy management for leaf-edges in connected environments حسب Mansour, Elio

"…In this work, we focus on managing data redundancies in connected environments. Existing approaches suffer from (i) disregarding edge data redundancies either at the edge or at the core of the network; (ii) disregarding sensor mobility and the dynamicity of the network; (iii) disregarding the limited resources of edge devices; (iv) disregarding network/infrastructure resources; and (v) disregarding data consumer needs/requirements when cleaning the data redundancies. …"
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