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219 articles for “Error analysis”
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Artificial Neural Network Modelling to Optimize Micro-Drilling Parameters of ECDM of Developed Novel Zn/(Ag+Fe)-MMC
Abstract: Several engineering fields have increased their use of metal matrix composites (MMCs) in the past few years. Due to the increase in composites, the demand for accurate machining has also become important. Specifically, pertaining to biomaterial applications, accuracy factor with desired surface finish is critical. While the near-net shape manufacturing process has advanced, MMCs frequently require post-mould machining to achieve surface quality, and dimensional tolerances. In the present study, a …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 01–13 Read article
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Experimental Analysis Of Thermal Behaviour Of Phase Change Materials In Cooling Applications Of Roof Top Building Slabs
Abstract: In this research article, different phase change materials are incorporated inside the slabs to reduce the heat transfer from the roof. Experiments are conducted during summer season March 2021 to the time lag decrement factor and heat flux to that of results are compared with RCC slab to that of Green material I (CaCl26H2O) and Green Roof with Green material II (48%CaCl2+4.3%NaCl+0.4%KCl+47.3%H2O). On comparison Green Slab II is having better …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 102–114 Read article
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Intercomparison of Rainfall Estimates of Probability Distributions for Developing the Intensity-Duration-Frequency Curves
Abstract: Determination of short duration rainfall through the developed Intensity-Duration-Frequency (IDF) curve is of utmost importance for planning, design, operation and management of civil and hydraulic structures. For which, extreme value analysis (EVA) of rainfall that consists of fitting probability distributions such as Normal, Log Normal (LN2), Pearson Type-3, Log Pearson Type-3, Extreme Value Type-1 (EV1) and Generalized Extreme Value (GEV) to the annual 1-day maximum rainfall series is carried out. …
Published in Journal of Water Resource Engineering and Management · Vol. 9, Issue 3, 2022 · pp. 39–53 Read article
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Prediction and Comparative Analysis of Thermal Conductivity of Jatropha Oil-based Hybrid Nanofluid by Multivariable Regression and ANN
Abstract: In the present study, a multivariable regression (MR) and artificial neural network (ANN) method was used to predict the thermal conductivity of Jatropha oil-based ZnO-Ag hybrid nanofluid. Firstly, the ZnO-Ag hybrid nanoparticles were synthesized and mixed in the jatropha oil to prepare various nanofluids at different volume concentrations (F) ranging from 0.05 to 0.20%. The stability and thermal conductivity of the prepared nanofluids were investigated. Wide ranges of temperature and …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 32–39 Read article
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Comparative Analysis of Artificial Intelligence-based MPPT Algorithms for Wind Energy System
Abstract: By extracting maximum possible power from a wind generator system, the efficiency of the system can be increased. Radial basis function (RBF), feed forward back propagation (FFBP) and adaptive neuro-fuzzy inference system (ANFIS) are recognized as the universal estimators. This paper presents a single network based maximum power point tracking (MPPT) of a wind turbine system using these algorithms. The single network based maximum power extraction method is simple and …
Published in Journal of Power Electronics and Power Systems · Vol. 10, Issue 3, 2020 · pp. 7–18 Read article
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Glitches in the Implementation of Bioinformatics in Medical Settings: A Comprehensive Review
Abstract: Bioinformatics is a dynamic field at the intersection of biology, computer science, and information technology, offering new possibilities in medicine by enabling a deeper understanding of genomics, molecular biology, and personalized treatment approaches. Its integration into healthcare could greatly enhance diagnostics, enable tailored treatments for individuals, and facilitate the analysis of large biological datasets. However, despite its potential, several barriers impede its successful implementation in clinical settings. These include technical …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–6 Read article
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To Optimize the Efficiency of Bottle Sleeving Machine by Reducing Systematic Errors
Abstract: Bottle sleeving machines are the machines use to label and sleeving the caps to the bottle. To gain the mass production and to improve the efficiency of this machine our team decided to change the parameters and proper alignment of few parts in machine. Previously, there were several errors include like systematic errors. Firstly, we change the sensors positioning to get successive operation of sleeves to the bottle. There were …
Published in Journal of Production Research & Management · Vol. 12, Issue 2, 2022 · pp. 23–29 Read article
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Reliability-Aware Mathematical Model for Radiation-Hardened Satellite Communication Systems
Abstract: Satellite communication systems operate in radiation environments in which total ionizing dose (TID), displacement damage, and single-event effects (SEE) can progressively degrade electronic, optoelectronic, and communication components and can ultimately reduce link availability and mission reliability. This paper develops a Reliability-Aware Radiation-Hardened Satellite Communication Model (R-RHSCM) that mathematically couples the orbital radiation environment, accumulated radiation dose, component degradation, communication-link performance, single-event failure probability, redundancy, thermal effects, and adaptive mitigation. The …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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Review of Ayurvedic Drugs on Acid-peptic Diseases Regarding Its Personalized Management
Abstract: Acid-peptic Disease (~Amlapitta) is an illness wide-spread all around the world. In Ayurveda, Vidahi (which cause burning) and Pitta (dosha responsible for metabolic activities) aggravating diet and stressful –sedentary life-style has been stated as one of the leading cause for acceleration of Amlapitta. Detailed reviewing of drugs given in Ayurvedic texts are done according to specific stage of disease, Amlapitta Dosha predominance, chronicity, associated conditions, dosage, Anupana etc. Screening the …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 13, Issue 2, 2024 · pp. 24–38 Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing · Vol. 11, Issue 1, 2021 · pp. 9–25 Read article
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Emotions and Artificial Intelligence in Finance: Exploring the Relationship
Abstract: The integration of Artificial Intelligence (AI) into financial systems has profoundly transformed the industry, providing unprecedented efficiency, accuracy, and speed in decision-making processes. These technological advancements have streamlined operations, reduced human errors, and enabled more informed decision-making based on vast datasets analyzed in real-time. However, the role of emotions in finance remains a critical factor that cannot be ignored. Human emotions, such as fear, greed, and optimism, frequently drive market …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 1, 2025 · pp. 11–17 Read article
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Soft Sensor for Estimation and Identification of Reduced Dimensional Quality Control Inputs
Abstract: AbstractAdvances in instrumentation technology have equipped us with better process controlling set-ups for error detection and control that occurs in the industrial process plants. This in turn generates a large amount of data that is not always information rich. Additional sensor like a soft sensor can be used to modify the sensor to generate information rich data. Soft sensor are computational models that aid in the continuous or partial estimation …
Published in Journal of Instrumentation Technology & Innovations · Vol. 7, Issue 3, 2017 · pp. 24–29 Read article
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Data-Driven Material Design and Performance Improvement: Constructing Sustainable Polymer Nanocomposites Using Deep Learning
Abstract: In the formation of sustainable polymer nanocomposites, the effective material techniques are required to balance the mechanical qualities, environmental compatibility and processing efficiency. The optimization of polymer matrix, nanofiller loading, processing conditions and material properties is typically time consuming, resource intensive and highly dependent on trial-error methodology using standard experimental techniques. The present work provides a data-driven approach that combines deep learning with sustainable polymer nanocomposite design for predicting and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Advanced Deep Learning Techniques for Sickle Cell Anaemia Detection
Abstract: Sickle Cell Anemia (SCA) is a prevalent genetic blood disorder characterized by the presence of abnormal hemoglobin, resulting in the distinctive sickle shape of red blood cells. Timely and accurate identification of Sickle Cell Anemia (SCA) is essential for effective management and treatment. This study presents a new method that utilizes Convolutional Neural Networks (CNNs), a deep learning model particularly effective for image analysis. The process involves using microscopic images …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 9–15 Read article
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A Survey on Ensemble Technique for Enhanced Cyberattack Detection
Abstract: It is now more difficult than ever to safeguard enterprises against cyberattacks due to their fast growth and growing sophistication. Stronger cyberattack detection systems are becoming more and more necessary as hostile strategies continue to evolve in order to safeguard information, preserve corporate trust, and protect sensitive data. An overview of contemporary detection techniques is given in this study, with a focus on integrating machine learning (ML) to increase efficacy. …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 50–54 Read article
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Optimization of Process Parameters for ABS, Nylon, Polypropylene Material in Injection Molding Using Taguchi Method
Abstract: The process of plastic injection molding (IMP) itself is a multifarious of time, temperature and pressure variables with a profusion of manufacturing defects that can occur without upright fusion of processing parameters and design components. Ascertaining the reform foremost process parameter settings commentative dominates productivity, quality, and costs of production in the plastic injection molding industry. Most plastic injection molding industries are using trial-and-error method/approximation method, based on experience of …
Published in Trends in Mechanical Engineering & Technology · Vol. 11, Issue 3, 2021 · pp. 1–9 Read article
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Statistical Modeling for Weld Quality Assessment using AI SAW Welding of Mild Steel
Abstract: The main issue to the industries that apply Submerged Arc Welding (SAW) is quality assurance since the structural integrity dictates safety and the performance of the industry. The existing system of checking manuals is not only time consuming but also has human errors that make it mandatory to deploy automated intelligent systems. This study carries out an extensive comparison of the leading approaches based on the use of Artificial Intelligence …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 892–907 Read article
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Machine Learning-Based Structure–Property Quantification of Advanced Polymer Composites
Abstract: Advanced polymer composites are widely used in high-performance engineering due to their superior mechanical and multifunctional properties. Accurate structure–property quantification is essential for efficient material design and reducing experimental costs. Existing Machine Learning (ML) approaches often exhibit limited predictive generalization due to inadequate feature discrimination and suboptimal hyperparameter tuning. To address these limitations, the proposed method enhances the ability to capture the complex nonlinear interactions among composite structural descriptors. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article