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81
Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation
Published 2023“…Additionally, a clustering algorithm with a fuzzy membership function is implemented, allowing the robots to advance in accordance with predefined clusters and arrive at their starting place within a predetermined amount of time. …”
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82
Correlation Clustering with Overlaps
Published 2020“…Moreover, we allow the new vertex splitting operation, which allows the resulting clusters to overlap. In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …”
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masterThesis -
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85
Multi-Robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees
Published 2017Get full text
doctoralThesis -
86
Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
Published 2019Get full text
doctoralThesis -
87
Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems
Published 2022“…Data-driven algorithms with capabilities to predict the system’s dynamic behavior still need to be developed. …”
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88
A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation
Published 2023“…Also, to evaluate the robustness of the algorithms, we test the neural network, without retraining it, on multiple scenarios with noisier data and bad data. …”
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masterThesis -
89
An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. …”
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An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System
Published 2019“…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. …”
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93
Recursive Parameter Identification Of A Class Of Nonlinear Systems From Noisy Measurements
Published 2020“…The model structure is made up of two linear dynamic elements separated by a nonlinear static one. The nonlinear element is assumed to be of the polynomial type with known order; The identification is based on input/output data where the output is contaminated with measurement noise. …”
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94
Plant disease detection using drones in precision agriculture
Published 2023“…Color-infrared (CIR) images are the most preferred data used and field images are the main focus. The machine learning algorithm applied most is convolutional neural network (CNN). …”
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95
A novel few shot learning derived architecture for long-term HbA1c prediction
Published 2024“…Short-term CGM time-series data are processed using both novel image transformation approaches, as well as using conventional signal processing methods. …”
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Lung nodule classification utilizing support vector machines
Published 2002“…The SVM classifier is trained with features extracted from 30 nodule images and 20 non-nodule images, and is tested with features out of 16 nodule/non-nodule images. …”
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98
An effective design system for dynamically reconfigurable architectures
Published 2017“…In this paper, we use the Joint Photographic Experts Group (JPEG) image compression algorithm as a design example to demonstrate the effectiveness of dynamic reconfiguration achieved using SPARCS. …”
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conferenceObject -
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A survey and comparison of wormhole routing techniques in a meshnetworks
Published 1997“…Although an extremely wide number of routing algorithms have been proposed and implemented in hardware and software, it is difficult for the designer of a multicomputer to choose the best routing algorithm given a particular architectural configuration. …”
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100
Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort
Published 2023“…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”