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225 articles for “linearity of data”
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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Blockchain Enabled IoT System for Tamper Proof Monitoring of Polymer Composite Manufacturing Quality
Abstract: Ensuring real-time process compliance in resin-based polymer composite manufacturing remains a persistent challenge due to non-linear material behaviors, unpredictable curing dynamics, and fragmented sensor data pipelines. Traditional centralized monitoring architectures struggle to guarantee data integrity, auditability, and adaptive response under high-frequency environmental fluctuations. Most existing frameworks fall short in unifying trust, traceability, and time-critical decision-making particularly during critical cure-phase deviations due to limited integration of blockchain with intelligent sensor systems. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 126–145 Read article
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Development of an Intelligent and Statistical Model for Prediction of Rock Mass Deformation Modulus
Abstract: The rock mass deformation modulus (Em) takes into account the plastic and the elastic deformation of the rock mass. It has been widely used for designing structures such as dams, tunnels, caverns, and mines, etc. Since the tests available for ascertaining Em are expensive and time consuming, several equations were suggested in the past. However, it has been found that the existing models are limited to specific type of rock …
Published in Journal of Geotechnical Engineering · Vol. 6, Issue 2, 2019 · pp. 39–50 Read article
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Non-Linear Dynamic Analysis of High-Rise Flat Slab Structure with Various Lateral Load Resisting System: Indian Scenario
Abstract: In this technological era, the construction of high-rise flat slab structure is increasing everywhere, due to its major advantages over a conventional beam slab structure. Due to the poor performance of high-rise flat slab structure in higher seismic zones, IS 1893 (Part 1): 2016 discourages the use of flat slab structure in higher seismic zones. The use of high-rise flat slab structure in high seismic region is a risk, because …
Published in Journal of Structural Engineering and Management · Vol. 9, Issue 2, 2022 · pp. 1–12 Read article
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Genetic Variability and Statistical Methods: Key Insights for Computational Genetics Research
Abstract: Genetic variability, defined as the differences in DNA sequences among individuals, serves as the foundation of evolutionary biology and plays a pivotal role in species’ adaptability, resilience, and overall survival. Advances in genomic technologies, particularly high-throughput sequencing, have enabled unprecedented exploration of genetic diversity, fostering the growth of computational genetics. This interdisciplinary field combines statistical methods and computational tools to analyze genetic data, identify patterns, and link phenotypes to genotypes. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 19–23 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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A Hierarchical Orchestration Framework for Parallelized Multi-Entity Web Ingestion and NoSQL Synchronization
Abstract: In the current EdTech sector, gathering structured data from various fragmented web portals is a major challenge for building reliable, real-time data systems. Standard sequential ETL (Extract, Transform, Load) pipelines often encounter significant bottlenecks, as a single failure in one module can halt the entire ingestion process. Furthermore, linear execution is often too slow to meet the demands for large, multi-category datasets. This paper presents a Modular Hierarchical Orchestration framework …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 2, 2026 · pp. 1–6 Read article
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Modeling Evapotranspiration using Artificial Neural Networks
Abstract: The prior knowledge of evapotranspiration (ET0) is crucial for estimating crop-water demand, preparation of water distribution schedules and water diversion. The present study investigates the utility of artificial neural networks (ANNs) and linear regression models (LRs) for forecasting ET0 based on hydro-meteorological data. Based on different inputs, eight ANN and LR models are developed. The results are compared with those of FAO-56 Penman-Monteith expression. The published daily climatic data from …
Published in Recent Trends in Civil Engineering & Technology · Vol. 3, Issue 3, 2013 · pp. 29–35 Read article
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Computer Aided Diagnosis of Breast Cancer using Machine Learning Techniques
Abstract: Breast cancer is one of the significant health problems that lead to early mortality in women, especially those between 40 and 55 years of age all over the world. In recent years, the number of breast cancer cases among women has risen significantly, making early and accurate diagnosis more important than ever. Computer-aided diagnostic (CAD) tools have become valuable in supporting radiologists by enhancing the precision of breast cancer detection. …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 2, 2025 · pp. 1–11 Read article
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Molecular Investigation of CO2 Solubility and Diffusion in Crude Oil
Abstract: It is important to know solubility and molecular diffusion coefficients of gas under reservoir CO2 Enhanced Oil Recovery. In this paper, a set complete device has been established to measure solubility and molecular diffusion coefficients of gas to improve the empirical formula and chart. Based on the experiment, molecular diffusion coefficients and solubility is evaluated, which provides the fundamental data to CO2 Enhanced Oil Recovery. The solubility vs. pressure linear …
Published in Journal of Petroleum Engineering & Technology · Vol. 3, Issue 2, 2013 · pp. 28–35 Read article
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OFDM Receiver Design Based on Adaptive Modulation and Channel Estimation for Underwater Acoustic Communication
Abstract: Submerged or under water acoustic communication (UWAC) is an intriguing area in communication research where we can expect to get a high information rate, a high throughput and a low latency which frequently is an exceptionally difficult assignment. In this work, we outline an OFDM receiver system that is reasonable for submerged acoustic communication in view of adaptive modulation and Kalman filter based channel estimation. We have concentrated on the …
Published in Recent Trends in Electronics Communication Systems · Vol. 4, Issue 1, 2017 · pp. 7–16 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Variation of Ground Acceleration with Increase in Lateral Distance
Abstract: Ground acceleration induced by dynamic loading decreases with increasing lateral distance from the source because of wave attenuation and energy dissipation through the ground. Accurate estimation of ground acceleration at different distances is essential for evaluating the safety and performance of nearby structures, particularly in blasting, seismic, and heavy construction activities. This study presents a simplified linear attenuation model for estimating ground acceleration at greater lateral distances using limited measured …
Published in Journal of Geotechnical Engineering · Vol. 13, Issue 2, 2026 · pp. 21–27 Read article
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Geomorphometric Characteristics and Associated Land Use/Land Cover in Sajnam Basin: A Remote Sensing and GIS Based Approach
Abstract: The present study makes an attempt to assess drainage basin characteristics of Sajnam watershed situated in Lalitpur district of Bundelkhand region, Uttar Pradesh. The basin covering an area of 995.87 km2 was delineated on Arc map software using Arc hydro tool and the ASTER data. Elevation and slope map were prepared using ASTER data and the maximum and minimum elevation encountered in the area are 283 meter and 563 meters …
Published in Journal of Remote Sensing & GIS · Vol. 8, Issue 3, 2017 · pp. 22–32 Read article
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Test methodology for validating drop arm of a tractor mechanical steering system under bi-axial loading
Abstract: The drop arm is a part of tractor mechanical steering system which connects the steering gearbox to drag link. The function of the drop arm is to convert the rotary motion of the steering gear shaft into linear motion of the drag link. During vehicle testing in the field drop arm failure was observed, which was not captured in the component level testing. Typically drop arm durability test is carried …
Published in Trends in Mechanical Engineering & Technology · Vol. 13, Issue 2, 2023 · pp. 74–81 Read article
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AI-Enabled Linear Regression Model for Spectroscopic Milk Adulteration Analysis
Abstract: Milk adulteration poses a serious threat to public health and quality assurance in the dairy industry. This requiring rapid, reliable, and non-destructive detection techniques. This study presents a linear regression-based analytical model for identifying and quantifying milk adulteration using spectroscopic data. Spectral measurements of milk samples, including both pure and adulterated variants were acquired using spectroscopic techniques at relevant wavelengths.Blending of other components in pure milk , is specifically called …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 28–42 Read article
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Optimal PMU Placement in Power Systems Using Graph Theory and PSAT
Abstract: Phasor measurement units (PMUs) play a vital role in modern power systems by delivering synchronized, real-time measurements. These devices enhance system reliability by supporting functions such as monitoring, protection, and control. By accurately capturing voltage and current phasors across different locations, PMUs enable better situational awareness and more effective decision-making in grid operations and management. Determining the optimal location of PMUs is essential to ensure system observability, reduce installation costs, …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 26–32 Read article
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Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article
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Convolutional Neural Network and its Architectures
Abstract: Convolutional neural network (CNN) is a type of artificial neural network (ANN) with multiple layers. From the past decades, it has been considered as a powerful classification technique as it can handle a huge amount of imagery data. It can be applied in the field of image recognition. The name CNN has been derived from the mathematical linear operation known as convolution which is performed between two matrices. CNN has …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 2, 2021 · pp. 6–14 Read article
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Fluid-Structure Interaction Simulation of Parachute by Eulerian-Lagrangian penalty method
Abstract: In general, modeling and simulation of a model consisting of fluid and solid combinations has been considered difficult, and it has become impossible in terms of computer dependencies and accuracy to be analyzed by Fluent or other programs. The parachute evaluation process, which is historically based on a large amount of experimental data, necessitates many falling experiments. These tests can be costly and time-consuming, and they don't always allow for …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article