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Action recognition through fusion of sEMG and skeletal data in feature level
Human action can be recognized through a unimodal way. However, the information obtained from a single mode is limited due to the fact that a single...
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Predicting and optimizing the concrete compressive strength using an explainable boosting machine learning model
Accurate and understandable prediction of concrete compressive strength (CCS) and determining the optimal mixture to maximize the CCS are crucial...
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A Comparison of Client Weighting Schemes in Federated Learning
Data is the new oil of the digital economy. Many business organizations are gathering and using their data to optimize their business performance....
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Prediction of Admissions and Jobs in Technical Courses with Respect to Demographic Location Using Multi-linear Regression Model
With more employment opportunities, we have seen tremendous growth in number of institutions which offer professional courses across globe. One side,...
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Tangent Space Approximation in Geometric Statistics
The Procrustes regression model provides a statistical framework to assess the errors in image registration (in arbitrary dimensions) from “landmark”...
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Robust Loss Function for Deep Learning Regression with Outliers
Sadouk, Lamyaa Gadi, Taoufiq Essoufi, El HassanIn regression analysis, the presence of outliers in the data set can strongly distort the classical...
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Application of Mathematical Modeling to Optimal Design of Biosensors
This chapter presents a method combining mathematical modeling, chemometrics, multi-objective optimization and multi-dimensional visualization...
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Explainable Artificial Intelligence for Deep Learning Models in Diagnosing Brain Tumor Disorder
Deep neural networks (DNNs) have shown great potential in diagnosing brain tumor disorder, but their decision-making processes can be difficult to...
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State of health estimation for lithium-ion batteries in real-world electric vehicles
The state of health (SOH) plays a significant role in the mileage and safety of an electric vehicle (EV). In recent years, many methods based on...
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Distributed Estimation of Scalar Fields with Implicit Coordination
Motivated by our ongoing work in robotics for precision agriculture, in this work we consider the problem of estimating a scalar field using a team...
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Demand Forecasting of Spare-Parts Using the Data Mining Techniques
Nowadays, many businesses use traditional inventory management techniques. Proper inventory management techniques save businesses from additional...
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Anomaly Detection in Medical IoT Devices Using Federated Learning
IoT as a technology has gained a lot of prominence, especially in the healthcare sector which is more commonly known as IoMT. The Internet of Things...
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Type 2 Diabetes Prediction Using Machine Learning and Validation Using Weka Tool
The purpose of this research is to figure out who is at risk for diabetes based on their lifestyle and family history. Accurate and timely...
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Dynamic Emotion Understanding Based on Two-Layer Fuzzy Support Vector Regression-Takagi-Sugeno Model
Two-layer Fuzzy SVR-TSSVR-TS Model is proposed for emotion understanding in human-robot interaction, where the real-time dynamic emotion is...
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On Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrix
This paper is concerned with the analysis of optimization procedures for optimal experiment design for locally affine Takagi-Sugeno (TS) fuzzy models...
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Model-Free Reaching of a 2-DOF Robotic Arm Using Neural Networks
In this paper, we present our results when using a Regression Deep Neural Network in an attempt to position the end-effector of a 2 Degrees of...
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Traffic Flow Labelling for Congestion Prediction with Improved Heuristic Algorithm and Atrous Convolution-based Hybrid Attention Networks
The quality of life and the development of urban areas are impacted by traffic-related issues. The delayed response of priority and emergency...
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Predictions of Root Tensile Strength for Different Vegetation Species Using Individual and Ensemble Machine Learning Models
Vegetation is needed to improve soil slope stability. The roots of different species stabilize the ground by their tensile strength. However, how the...
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Research on Data Reconstruction Methods Based on Multiple Models of Aero-Engine Sensor
Sensors are crucial to an aero-engine. If they fail, the control system will not be able to accurately assess the engine's state, cannot take timely...
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A Comparative Study of AdaBoost and K-Nearest Neighbor Regressors for the Prediction of Compressive Strength of Ultra-High Performance Concrete
One of the most promising materials for concrete buildings is ultra-high-performance concrete (UHPC). Traditional UHPC compositions include...