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81
Wearable Real-Time Heart Attack Detection and Warning System to Reduce Road Accidents
Published 2019“…It was observed that the linear classification algorithm was not able to detect heart attack in noisy data, whereas the support vector machine (SVM) algorithm with polynomial kernel with extended time–frequency features using extended modified B-distribution (EMBD) showed highest accuracy and was able to detect 97.4% and 96.3% of ST-elevation myocardial infarction (STEMI) and non-ST-elevation MI (NSTEMI), respectively. …”
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82
Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…The scammers are making money through fraudulent job postings. Online recruitment fraud has emerged as an important issue in cybercrime. …”
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Correlation Clustering with Overlaps
Published 2020“…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 -
85
What are artificial intelligence literacy and competency? A comprehensive framework to support them
Published 2024“…We also identify five effective learning experiences to foster abilities and confidences, and suggest five future research directions: prompt engineering, data literacy, algorithmic literacy, self-reflective mindset, and empirical research.…”
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86
Predicting Plasma Vitamin C Using Machine Learning
Published 2022“…The low R-squared scores obtained by the models are likely to be due to the low resolution of the NHANES data, particularly the dietary data. This emphasizes the need for high-quality data sets in Precision Nutrition research.…”
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87
Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting
Published 2019“…And while spatiotemporal data related to traffic is becoming common place due to the wide availability of cheap sensors and the rapid deployment of IoT platforms, the data still suffer some challenges related to sparsity, incompleteness, and noise which makes the traffic analytics difficult. …”
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88
An Alternating Projection Framework for Elementwise Masked Nonlinear Matrix Decomposition
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doctoralThesis -
89
Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
Published 2025“…<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. …”
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90
Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review
Published 2024“…It has been learned that image-processing techniques overwhelm the existing research and have the potential to integrate meteorological data. The most widely used algorithms incorporate Support Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network (CNN), and MobileNet with accuracy rates between 64.3 and 100%. …”
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91
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 -
92
A Cyber-Physical System and Graph-Based Approach for Transportation Management in Smart Cities
Published 2021“…Smart and on-ground real-time traffic analysis helps authorities further improve decision-making to ensure safe and convenient traveling. In this paper, we proposed a transport-control model that exploits cyber-physical systems (CPS) and sensor-technology to continuously monitor and mine the big city data for smart decision-making. …”
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93
Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective
Published 2024“…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …”
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Deep and transfer learning for building occupancy detection: A review and comparative analysis
Published 2022“…Besides, integrating artificial intelligence (AI) into the BIoT is essential for data analysis and intelligent decision-making. Thus, data-driven approaches to infer occupancy patterns usage are gaining growing interest in BIoT applications. …”
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An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model.…”
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98
Corona power loss computation in bundled bipolar conductors
Published 2000“…In this paper, a finite element (FE) based algorithm devoted for the computation of the corona current and hence the corona power loss associated with bundled bipolar high voltage direct current (HVDC) conductors is presented. …”
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99
Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT)
Published 2015“…Decision making and/or Decision Support Systems (DSS) using intelligent techniques like Genetic Algorithm and fuzzy logic is becoming popular in many new applications. …”
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conferenceObject -
100
Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants
Published 2006“…The U-model is utilized to design an adaptive inverse controller by using a simple root-solving algorithm of Newton-Raphson. The synergy of U-model with AIC structure has provided an effective and straight forward method for adaptive tracking of nonlinear plants. …”
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