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194 articles for “machining characteristics”
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Identifying and Implementing a Machine Learning Model Suitable for Processing Visually Evoked Potential
Abstract: A Brain-Computer Interface (BCI) is a system that translates brain activity patterns into computer commands, bypassing physical movement. Electroencephalography (EEG) is commonly used to acquire signals in BCI research. Visual evoked potentials (VEPs) are brain responses in the visual cortex to visual stimuli. Recent studies show that exposing individuals to flickering at a consistent frequency generates EEG signals synchronized with the stimulation. Efficient extraction of VEP signals begins with preprocessing …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1258–1284 Read article
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A Review on Parametric Optimization of WEDM Technique for OHNS Steel
Abstract: In this study, the Wire Electrical Discharge Machining (WEDM) process for OHNS (Oil Hardened Non-Shrinking) steel, a high-performance material frequently used in the production of dies, punches, and precision tooling components, is optimized parametrically and validated experimentally. A continuously moving wire electrode and a sequence of electrical discharges are used in WEDM, a non-traditional machining method, to erode material and produce intricate and precise profiles, particularly in materials that are …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 29–35 Read article
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Experimental Study of Roughness Analysis of AISI 316L Material using Fiber and CO2 LBM
Abstract: Laser beam machines have gained significant attention as a precise and versatile method for cutting and shaping materials in various industries. This study investigates the surface roughness characteristics of SS 316L, a commonly used stainless steel, when subjected to laser beam machining using both fiber and CO2 laser sources. The aim of this research is to compare the effects of these two laser types on the final surface finish of …
Published in International Journal of Solid State Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 12–21 Read article
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Interfacial and Tribo-Mechanical Performance of a TiO₂–Castor Oil Polymeric Nanofluid During Sustainable Machining of AISI 316L Stainless Steel Under MQL Conditions
Abstract: This research examines the tribo-mechanical performance and interfacial film characteristics of a TiO₂-reinforced castor-oil polymeric nanofluid during the turning of AISI 316L stainless steel under minimum-quantity lubrication (MQL). A Taguchi L9 orthogonal array was utilized to assess the synergistic effects of cutting speed, depth of cut, and coolant composition on surface integrity, while machining experiments were performed under dry, conventional, and TiO₂-nanofluid lubrication techniques. ANOVA and multiple-regression modeling were used …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 901–914 Read article
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Forecasting of Crushing Strength of Sustainable Concrete by Employing Deep and Random Forest Machine Learning
Abstract: Sustainable concrete is one of the milestone of the concrete industry. This concrete fulfills the requirements of concrete manufacturing industry such as strengthen, Durability, environment friendly and many of other. With this properties of concrete, sustainable concrete is an ideal substitute for ordinary concrete in the concrete industry. In the 21th century Machine learning is a tool which is use to employ the characteristics of sustainable concrete by using deep …
Published in Journal of Polymer & Composites · Vol. 12, Issue 7, 2024 · pp. 41–46 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
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Enhancing Delamination Resistance in CFRP Composites through surface Functionalization of Woven carbon Fiber by CuO Nanostructures
Abstract: In order to produce a nanostructured interphase that improves the interfacial interaction with an epoxy resin matrix, copper oxide (CuO) nanostructures were hydrothermally formed onto woven carbon fibers (WCF). Hexagonal CuO nanorods were created using a two-step, seed-assisted solvothermal technique on plain woven carbon fiber. This study investigates the effects of surface modification of carbon fibers by the formation of CuO nanostructures using a hydrothermal technique on the mechanical properties …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 589–602 Read article
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Establishment of A Set of Similarity Prerequisite Conditions for Low-Cost Similitude Design of Structural System
Abstract: Similitude theory and method is a branch of engineering to establish necessary and sufficient conditions for similarity among complex phenomena. It is of great significance to develop the theory and application method in a more comprehensive way so that the similitude theory can be widely applied to low-cost designs of modern complex structural systems When designing a similitude structural system with various loads and boundary conditions, including rotating machines, it …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 1–15 Read article
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Significance of Composite Materials for Making Better Future Society
Abstract: Since in the beginning of human history, Materials had been started in use. We can't imagine our world without materials. In fact, Materials has taken centre position in many developed and developing countries. The materials that humans have chosen to use for engineering projects throughout history, including the Stone, Iron, and Silicon ages. However, in order to meet today's difficulties, new materials must be discovered and developed with the necessary …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 2, 2023 · pp. 56–62 Read article
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Personality and Behavior Identification Based on Handwriting Analysis
Abstract: Graphing is the process of identifying, evaluating, and understanding a person's personality traits through handwritten patterns. The accuracy of handwriting analysis depends on the skill of the analyst, it is expensive and prone to errors. The proposed approach is therefore focused on building a system that can predict personality traits with the help of machine learning without human intervention. In this project, 657 authors' handwritten samples were taken as datasets. …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 1, 2022 · pp. 42–54 Read article
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Utilizing Machine Learning to Predict the Dimensional Variation of Shafts Printed using Fused Deposition Modeling
Abstract: With the onset of the fourth industrial paradigm, additive manufacturing techniques are coming to the forefront in mechanical engineering domain. The technological burgeoning of additive manufacturing, particularly 3-D printing, has observed substantial growth in rapid prototyping, functional part manufacturing, and tooling because it has significantly reduced the manufacturing costs and processing time. One of the most commonly used techniques of additive manufacturing is Fused Deposition Modelling (FDM), examining and controlling …
Published in Trends in Mechanical Engineering & Technology · Vol. 11, Issue 2, 2021 · pp. 41–46 Read article
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Study on Single-Slope Solar Still for Experimental and Data-Driven Analysis for Improving Productivity with Different Basin Materials.
Abstract: This study investigates the single-slope solar still under the diurnal variation of water temperature and distillate yield under identical operating conditions. Experimental analysis was conducted to evaluate the performance enhancement through the incorporation of natural basin materials, namely hemp and sand. The water distillation process is focused on improving potable water productivity and thermal behaviour. The inclusion of hemp and sand in the basin leads to noticeable differences in productivity …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 2, 2026 · pp. 31–46 Read article
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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
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An Experimental Investigation of Process Parameters for Aluminum Alloy Composites
Abstract: The objectives of this work are to develop an aluminum alloy composites and investigate machining process parameters effect on the tool wear rate for composites. The composite is enhanced using silicon carbide and graphite. The composite is made by a method called stir casting. Furthermore, it is investigated both mathematically and experimentally. This study takes trial on aluminum alloy composite to see output characteristics tool wear rate are affected by …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 185–193 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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A Review on Loan Approval Prediction Based on Machine Learning Techniques
Abstract: The banking industry has also benefited greatly from technological advancements. An increasing number of individuals are submitting loan applications on a daily basis. When deciding which loan applicants to approve, the bank must take certain rules into account. The bank needs to choose the best one for approval based on certain characteristics. The process of carefully verifying every person and recommending them for loan approval is laborious and fraught with …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 1–11 Read article
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Implement Artificial Intelligence and Machine Learning for Engineering Design, Predictive Modeling, and Optimizing Polymer Nanocomposites
Abstract: Polymer nanocomposites are high performance engineered materials obtained by inclusion of nano-sized fillers into the polymer matrix to enhance mechanical, thermal, electrical, barrier and functional properties. However, the complex and non-linear interactions among polymer chemistry, nanofiller characteristics, filler concentration, dispersion, interfacial bonding and processing conditions make it challenging to anticipate and maximize their properties. Artificial intelligence (AI) and machine learning (ML) offer powerful data-driven solutions to these difficulties by establishing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Finite Element, Experimental, and Machine Learning-Based Optimization of Machining Stability for Polymer Composite Material Processing
Abstract: The machining of polymer composite materials, particularly fibre-reinforced polymer-matrix composites, requires stable spindle-tool performance to avoid delamination, fibre pull-out, matrix cracking, thermal softening, poor surface integrity, and premature tool wear. In line with the scope of the Journal of Polymer & Composites, this study presents an integrated finite element, experimental, and machine learning framework for improving machining stability during end-milling of composite material systems. The spindle-tool assembly is modelled using …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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ML Associated DoS and DDoS Attack Observation in Protection
Abstract: DoS and DDoS assaults are significant risks to the availability and integrity of online services and networks. Attack traffic might come from a variety of geographical regions, making it difficult to filter and neutralize the attack. DDoS attacks are far more sophisticated and powerful than DoS attacks. They use a network of compromised devices, known as a botnet, to launch a coordinated attack on a target. Monitoring and evaluating the …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 1, 2024 · pp. 18–26 Read article