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206 articles for “perforation patterns”
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Music Reactive led using Arduino
Abstract: In recent years, the integration of technology into interactive systems has garnered significant attention. Among the many applications, music-reactive LED systems have become popular, offering dynamic visualizations that respond to audio inputs. This paper explores the development and implementation of a music-reactive LED system using Arduino, focusing on real-time audio signal processing and LED control based on the frequency spectrum of the sound. By utilizing Fast Fourier Transform (FFT) algorithms …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 27–33 Read article
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An Overview on Intelligent Operating Systems (iOS)
Abstract: The rapid convergence of artificial intelligence techniques with core operating system services is ushering in a new class of platforms—Intelligent Operating Systems (Intelligent OS)—that can anticipate, adapt, and optimize on behalf of both applications and users. This paper surveys the architectural shifts required to embed learning, reasoning, and self healing capabilities into the kernel, scheduler, memory manager, and I/O subsystems. We present a prototype framework, NeuroKernel, that augments traditional OS …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 Read article
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Investigation and Concerns on the Mechanics Behind Grain Refinement During ECAP Operation with Applications to Polymers
Abstract: Materials science and engineering have studied Equal Channel Angular Pressing (ECAP) grain refining. This abstract discusses important findings and concerns about grain refining mechanics during ECAP.A adaptable severe plastic deformation method; ECAP refines grain patterns in many metallic materials. Many researches have attempted to understand this phenomenon's complex mechanisms. Microhardness and microstructure (morphology) of AL alloy increase with the increase in pass numbers. It is observed that the mechanical property …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 1–11 Read article
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Nutrition Induced Remodeling Dynamics of Cell Membranes: Implications for Performance, Health, and Welfare Issues in Food Animals
Abstract: Cell membranes represent dynamic structural and functional platforms that integrate nutritional signals with cellular metabolism, immune competence, and physiological adaptation in food animals. Beyond their classical role as selective barriers, membranes actively regulate nutrient transport, signal transduction, and bioenergetics through highly responsive lipid and protein networks. Dietary components, particularly fatty acids, vitamins, minerals, amino acids, and bioactive compounds, critically influence membrane composition, fluidity, and stability, thereby shaping cellular function and …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 25–37 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Using AIML to Enhance Demand Forecasting in Business
Abstract: Artificial intelligence machine learning (AIML) can play a significant role in enhancing demand forecasting in business. AIML is a programming language designed for creating chatbots and conversational agents, but its application extends beyond simple interactions. In the context of demand forecasting, AIML can be utilized to analyze historical data, customer interactions, and market trends. By implementing AIML algorithms, businesses can create intelligent models that learn from past demand patterns, customer …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 35–40 Read article
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A Sol-Gel Approach for the Fabrication of Zinc Oxide Nanoparticles and Their Nanocomposite with Urea Formaldehyde (UF)
Abstract: In the performed work, zinc oxide nanoparticles were synthesized via the sol-gel method using zinc sulphate as the precursor material. Urea-formaldehyde (UF) resin was employed as a polymer matrix to encapsulate the produced ZnO through an acid-catalyzed polymerization process. This encapsulation aimed to improve the dispersion stability and surface reactivity of ZnO within the polymeric medium. The synthesized materials were subjected to comprehensive characterization using Fourier Transform Infrared Spectroscopy (FT-IR), …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 2, 2025 · pp. 21–27 Read article
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Hybrid Approach for Community Detection Using Deep Learning Techniques
Abstract: Community detection in complex networks is a fundamental problem with applications across diverse domains, ranging from social networks to biological systems and beyond. Traditional methods based on graph theory have been widely used for identifying communities within networks. However, the intricate and evolving nature of modern networks demands more sophisticated approaches. This research work proposes a hybrid approach that combines the strengths of deep learning techniques with traditional community detection …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 18–26 Read article
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Colostrum-Driven Epigenetic Programming in Dairy Cows: A Pathway to Optimal Reproductive Health
Abstract: Colostrum is a vital nutritional source for neonatal calves, providing immune support and essential growth factors. Recent research suggests that colostrum’s impact extends beyond immediate immunological protection, influencing long-term reproductive health through epigenetic modifications. In dairy heifers, early-life exposure to high-quality colostrum may program the developing reproductive system, affecting ovarian function, uterine health, and overall fertility. The components of colostrum, including hormones, growth factors, and bioactive peptides, can induce epigenetic …
Published in Emerging Trends in Metabolites · Vol. 2, Issue 1, 2025 · pp. 35–51 Read article
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Enhancing Smart Grid Resilience Through AI-Based Fault Classification
Abstract: Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation. This dynamic improves energy efficiency and the integration of renewables. Well, the dynamic and reversible power injection from Distributed Energy Resources (DERs) creates substantial operational problems. These …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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Thermal Stability and Impact Performance of Basalt–Carbon Hybrid Laminates in Polyimide–Phenolic Matrices
Abstract: The impact resistance and thermal stability of the advanced polymer composites are properties that are necessary for the components that are subjected to dynamic conditions, which show the overall reliability and service performance of the laminates applied in automotive structures, protective casings, etc. These properties prevent premature softening or breakdown during long-term exposure to heat. Impact resistance and thermal stability of composite laminates are studied based on fiber orientation and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 247–260 Read article
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Comparative Analysis of Processing-Property Relationships in Metal and Polymer Matrix Composites: A Unified Statistical Framework for Hardness Characterization
Abstract: Composite materials, encompassing both metal matrix composites (MMCs) and polymer matrix composites (PMCs), exhibit complex processing-property relationships that fundamentally govern their mechanical performance across diverse applications. This study presents a unified statistical framework for analyzing hardness characteristics in composite systems, using aluminum-tungsten carbide (Al-WC) metal matrix composites as a representative model system while establishing connections to polymer matrix composite behavior. The investigation employed comprehensive processing parameter optimization, microstructural characterization, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 419–430 Read article
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Student Academic Achievement Forecast Based on Emotional Intelligence, Personality, Demographic Characteristics and Attitude Towards Education and Future Career
Abstract: This study was aimed at predicting students' academic achievement based on emotional intelligence of personality traits, attitudes to education and future career. The present study was a correlational-analytical study. The statistical population of Zanjan University students in the academic year of 1395-1395 was the sample of 489 people selected by cluster random sampling method. Academic Resilience Scale (ARI) and Schotte Emotional Intelligence Questionnaire and Researcher Attitude Questionnaire were used to …
Published in International Journal of Education Sciences · Vol. 1, Issue 2, 2024 · pp. 25–36 Read article
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SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting
Abstract: This paper frames laptop pricing as a supervised predictive analytics problem, transforming product specifications into feature-rich signals to forecast price with calibrated regression models and operational guardrails against drift. A structured pipeline ingests tabular listings, performs data cleaning, and engineers domain-informed features (e.g., central processing unit (CPU) family and clocks, graphics processing unit (GPU) tiering, memory/storage density, display, and touch capabilities), followed by encoding and normalization to optimize model learnability. …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 61–71 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Artificial Intelligence and Machine Learning Applications in Optimizing Air Conditioning Systems
Abstract: The growing demand for air conditioning systems, especially in the wake of climate change and increasing global temperatures, has led to a significant increase in energy consumption. This, in turn, contributes to the growing concerns of environmental sustainability and operational costs. As a result, there is a pressing need for innovative solutions to optimize the performance and energy efficiency of air conditioning (AC) systems. Artificial Intelligence (AI) and Machine Learning …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
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Influence of Horizontal Crossflow on the Rayleigh-Taylor Instability: A Numerical Approach
Abstract: Rayleigh-Taylor Instability (RTI) is a typical occurrence in natural events, engineering, and industrial applications. When the lighter fluid (bottom medium) is forcing the heavier fluid (top medium) on top of the lighter fluid because of a gravitational field, then that phenomenon is called Rayleigh-Taylor instability (RTI). Despite extensive records of investigating this common phenomenon i.e., RTI with several unique boundary conditions, apparently, there are no prior investigations for the RTI …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 1, 2025 · pp. 1–11 Read article
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Performance Evaluation of Green Walnut Husk Waste Extract for Inhibiting Aluminium 8088 Corrosion in Acidic Solution
Abstract: The cumulative call for environmental and supportable corrosion inhibitors has obsessed curiosity in exploiting plant-based agronomic surplus resources. Presented research work discovers the corrosion inhibition probable of green walnut husk extract(GWH)—a normal and plentiful agro-waste—on Aluminium 8088 alloy in an acidic medium. Aluminium 8088, however identified for its corrosion resistance, is vulnerable to squalor in highly acidic settings, affectation trials in several industrial claims. GWH extract act as an ecologically …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 44–60 Read article
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An Optimize Formulation to Synthesis of size Controlled Hydrophobic Starch Acetate Nanoparticles using Box- Behnken Design
Abstract: The best way to improve the overall performance of native starch is by chemical modification. In recent years, hydrophobically modified starch has attracted considerable attention for the design and manufacture of novel nanoparticulate drug delivery carriers. The purpose of this research was to synthesize hydrophobic starch nanoparticles (NPs) and to optimize process factors through the use of response surface methodology (RSM). The corn starch acetate (CSA) NPs was synthesized using …
Published in Journal of Polymer & Composites Read article