Search
212 articles for “accuracy parameter”
-
Neurodevelopmental Effects of Cell Tower Radiation in Children: A Longitudinal Study
Abstract: This study investigates the impact of radiation exposure from cell phone towers on the neurodevelopmental outcomes of children aged 0–5 years. A prospective cohort approach was employed to assess key developmental parameters, including Gross Motor Skills, Fine Motor Skills, and sleep disorders. Given the increasing presence of wireless communication infrastructure, understanding its potential effects on early childhood development is crucial for public health.To analyze the collected data, advanced machine learning …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 Read article
-
Measuring Microstructure, Wear Resistance, and Mechanical Reliability Enhancement in Polymer Nanocomposites via Data-Driven Analysis with Deep Learning
Abstract: Polymer nanocomposites have gained great attention owing to their superior mechanical performance, better wear resistance and customizable microstructural properties for aerospace, automotive, medicinal and industrial engineering applications. However, the correct evaluation of the link between the microstructure evolution and the material reliability is a huge issue due to the intricacy of nanoscale interactions and diverse material characteristics. In this study, we propose a data-driven approach that integrates deep learning and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 22–33 Read article
-
Investigation of Robotic Transverse Twin-Wire GMAW for Large-Scale Wire-Arc Additive Manufacturing Applications
Abstract: Bulk metal additive manufacturing using wire-arc processes has gained significant attention for fabricating large-scale engineering components due to their high deposition rate and material efficiency. In this study, the feasibility and performance of robotic transverse twin-wire gas metal arc welding (GMAW) for bulk wire-arc additive manufacturing (WAAM) is systematically assessed. The research focuses on understanding arc stability, weld bead characteristics, and process–product relationships under high-deposition conditions. Welding current signals from …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 4, Issue 1, 2026 · pp. 36–50 Read article
-
A Study of Cloud-Enabled Deep Learning for Monitoring and Predicting Soil Health in Agriculture
Abstract: Soil health is a critical factor in ensuring sustainable agricultural practices and food security. Traditional methods for soil health assessment are often time-consuming, localized, and lack scalability. This study explores the integration of cloud-enabled deep learning techniques to monitor and predict soil health efficiently. Leveraging data from IoT sensors, satellite imagery, and lab-based analyses, a cloud-based framework is proposed to process and analyze soil health parameters such as pH, moisture …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 8–16 Read article
-
Performance test to determine electric vehicle driving range
Abstract: A new method to estimate the driving range in electric vehicles has been developed. The new method is based on full electric energy supply from a unique lithium-ion battery that equips the electric vehicle. The simulation method includes engine consumption as well as auxiliary systems and accessories that are currently powered by a servicing lead-acid battery. The modeling uses an AC/DC double electric circuit to represent the AC electric engine …
Published in Journal of Mechatronics and Automation · Vol. 8, Issue 2, 2021 · pp. 10–20 Read article
-
Enhancement of Horizontal Jet Impingement Heat Transfer Analysis on Vertical Flat Plate
Abstract: This research investigates the heat transfer characteristics and heat flux distribution associated with parallel jet impingement on a vertical flat plate. A comprehensive computational fluid dynamics (CFD) analysis is carried out and systematically validated against available experimental data to ensure the accuracy and reliability of the numerical model. The jet length is maintained constant at 12 mm, while the jet-to-plate separation distance is varied at 6, 12, 18, and 24 …
Published in Journal of Experimental & Applied Mechanics · Vol. 17, Issue 1, 2026 · pp. 65–80 Read article
-
Effect of Various Process Parameters on MRR in Manual Air Plasma Arc Cutting of AISI 1017 Mild Steel using ANN
Abstract: As per recent industrial surveys it is investigated that manufacturing companies define the quality of thermal cutting process by the dimension of work material and cutting surface appearance. Therefore, the surface roughness and material removal rate (MRR) are primarily considered. In this work the effect of three input parameters air pressure (P), cutting current (I) and cutting velocity (v) on material removal rate (MRR) is obtained experimentally. An artificial neural …
Published in Journal of Mechatronics and Automation · Vol. 2, Issue 2, 2015 · pp. 8–14 Read article
-
Exploring the Influence of Machining Parameters on Geometric Form and Orientation Controls (23 Design)
Abstract: This work explores the influence of machining parameters using on geometric form controls flatness and straightness as well as orientation control parallelism using an aluminum 6061 workpiece. Due to its good strength, machinability and cost- effectiveness, aluminum 6061 is widely used. In this experimental work, full factorial design is used and each factor has two levels. The response parameters chosen include flatness, straightness, and parallelism, which govern the form and …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 1, 2025 · pp. 10–16 Read article
-
IoT Based SCADA for Electrical Measurements and Control
Abstract: The suggested system's primary goal is to shield electrical equipment against malfunctions. Thesystem consists of various sensors that deployed strategically on electrical equipment. The data of theequipment is collected and transmitted to cloud platform through Node MCU ESP8266. The data issimultaneously displayed using LCD display. The collected data is splitted into train and test data.Train the machine learning model by using different algorithms. The best algorithm is chosen bycalculating their …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 2, 2023 · pp. 38–47 Read article
-
Mechanical Testing Under Tensile-load
Abstract: Mechanical testing is a technique used to establish a material's mechanical qualities by examining its strength, toughness, hardness, and other characteristics. Specimens produced of various materials whose qualities need to be examined are used to verify this property. In which a static load is applied and a dynamic load is applied, and the test is completed. Understating loads in mechanical testing is the topic of this research article. Any manufacturing …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 1, 2025 · pp. 1–10 Read article
-
Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
-
Comparative Study of Aggregate and Disaggregate Traffic Forecasting Technique for Industrial Corridor: Case Study of Vadodara District
Abstract: AbstractTransportation occupies a prominent place in modern life and its impact is spread in all domains of life. Transport planning is a discipline to study problems rising while planning transport facilities at urban, regional or national level and to prepare efficient basis for providing such facilities. Aim of transport planning at regional level is provision of connectivity and circuity with other regions as well as for expansion of existing facility …
Published in Trends in Transport Engineering and Applications · Vol. 5, Issue 1, 2018 · pp. 14–21 Read article
-
Fuzzy Variable Frame Analysis for Speech Recognition
Abstract: AbstractRecent works in machine learning has focused on models such as support vector machine (SVM), artificial neural network (ANN) and long short-term memory (LSTM), for automatically controlling the generalization and parameterization of the optimization process. This paper presents a fuzzy interpretation frame analysis procedure using LSTM classifier for noisy speech at word level using thresholding and local maxima procedure at framing level for the recognition process. Front end MFCC procedure …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 9–18 Read article
-
Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
-
Hybrid Machine Learning and Finite Element Framework for Predicting Damage Behavior in Fiber-Reinforced Polymer Composites
Abstract: Fiber Reinforced Polymer (FRP) composites have broad spread use in aerospace, automotive, marine and structural applications due to its high specific strength, stiffness and corrosion resistance. The various damage mechanisms such as matrix cracking, fiber breakage, delamination and interfacial failure, however, make the forecasting of damage particularly complex. In this work, a hybrid machine learning (ML) and finite element (FE) system is proposed for predicting the damage behavior of FRP …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Dynamic Analysis of Isotropic Annular Plate using Finite Element Method
Abstract: The vibration and harmonic response of isotropic annular plates have been examined in order to determine the frequency parameters and resonance amplitude. The employment of finite element is made in this study. The effects of thickness ratios and diameter ratios are investigated on natural frequencies and resonance point for isotropic annular plates. Different combinations of three types of boundary conditions i.e. clamped-clamped, clamped-free and free-clamped end conditions are considered at …
Published in Journal of Experimental & Applied Mechanics · Vol. 9, Issue 3, 2018 · pp. 7–18 Read article
-
A Study on AI-Enhanced Environmental Toxicology: Sensor-Driven Predictive Framework
Abstract: Traditional environmental toxicology relies heavily on labor-intensive, often retrospective, sampling and analysis, limiting our understanding of dynamic pollutant behaviors and their real-time impact on ecosystems and human health. This study presents a novel, integrated framework leveraging advanced sensor networks and artificial intelligence (AI) to revolutionize the monitoring, assessment, and predictive modeling of environmental contaminants. We deployed a sophisticated array of multi-parameter sensors (e.g., electrochemical, optical, biosensors for heavy metals, organic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 Read article
-
Predictive Modeling and Optimization of Tensile and Flexural Strength in FDM 3D Printing Using Decision Trees and Bayesian Optimization.
Abstract: This research investigates predictive modelling and optimization technique for the tensile and flexural strength of PlA (Poly Lactic Acid) in Fused Deposition Modelling (FDM) 3D printing. Employing Decision Trees and Bayesian Optimization enhances comprehension and control of 3D printing process. Precise model predicts PLA material properties based on input parameters. Methodology involves rigorous data preprocessing, encompassing, cleaning, transformation, and normalization. Hyperparameter optimization via grid search systematically explores configurations, optimizing model …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 203–214 Read article
-
Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article