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Multi-Objective Co-optimization of Power and Gas under Uncertainties with P2H embedded
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Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice
Published 2020“…Our approach is a simple and efficient voice-based algorithm in which a multi-center and multi threshold based ternary pattern is used (MCMTTP). …”
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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization
Published 2024“…This paper presents a novel hybrid optimization method to solve the resource allocation problem for multi-target multi-sensor tracking of drones. This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. …”
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NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY
Published 2022“…Therefore, this thesis proposed a Novel Stacking Classification and Prediction (NSCP) algorithm based on AAL for the older people with Multi-strategy Combination based Feature Selection (MCFS) and Novel Clustering Aggregation (NCA) algorithms. …”
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A FeedForward–Convolutional Neural Network to Detect Low-Rate DoS in IoT
Published 2022“…An iterative wrapper-based feature selection using Support Vector Machine (SVM) is used to derive the significant features required for detection. The performance of FFCNN is compared to the machine learning algorithms-J48, Random Forest, Random Tree, REP Tree, SVM, and Multi-Layer Perceptron (MLP). …”
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YOLO-SAIL: Attention-Enhanced YOLOv5 With Optimized Bi-FPN for Ship Target Detection in SAR Images
Published 2025“…Nevertheless, the presence of intricate backgrounds and multi-scale vessels makes it difficult for deep networks to detect distinctive targets, in part due to the presence of intricate backgrounds and multi-scale vessels. …”
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VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems
Published 2019“…The Nonnested Generalized Exemplars (NNGE) algorithm is one of the most accurate classification techniques that can work with such data of CPPS. …”
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A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security
Published 2023“…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”
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Chlorophyll-a concentrations in the Arabian Gulf waters of arid region: A case study from the northern coast of Qatar
Published 2022“…This study characterizes the spectral absorption of Chl-a and detects and maps the Chl-a of Al Arish–Al Ghariyah coastal region of northern Qatar using the data of Hyperion of EO-1, MultiSpectral Instrument (MSI) of Sentinel-2, and Operational Land Imager (OLI) of Landsat-8 satellites. …”
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Chlorophyll-a concentrations in the Arabian Gulf waters of arid region: A case study from the northern coast of Qatar
Published 2022“…This study characterizes the spectral absorption of Chl-a and detects and maps the Chl-a of Al Arish–Al Ghariyah coastal region of northern Qatar using the data of Hyperion of EO-1, MultiSpectral Instrument (MSI) of Sentinel-2, and Operational Land Imager (OLI) of Landsat-8 satellites. …”
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CEAP
Published 2016“…To reduce the overhead of the proposed detection model and make it feasible for the resource-constrained nodes, we reduce the size of the training dataset by (1) restricting the data collection, storage, and analysis to concern only a set of specialized nodes (i.e., Multi-Point Relays) that are responsible for forwarding packets on behalf of their clusters; and (2) migrating only few tuples (i.e., support vectors) from one detection iteration to another. …”
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Benchmark on a large cohort for sleep-wake classification with machine learning techniques
Published 2019“…We propose the adoption of this publicly available large dataset, which is at least one order of magnitude larger than any other dataset, to systematically compare existing methods for the detection of sleep-wake stages, thus fostering the creation of new algorithms. …”
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Building power consumption datasets: Survey, taxonomy and future directions
Published 2020“…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. …”
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Developing an online hate classifier for multiple social media platforms
Published 2020“…Although researchers have found that hate is a problem across multiple platforms, there is a lack of models for online hate detection using multi-platform data. To address this research gap, we collect a total of 197,566 comments from four platforms: YouTube, Reddit, Wikipedia, and Twitter, with 80% of the comments labeled as non-hateful and the remaining 20% labeled as hateful. …”
