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169 articles for “Classical”
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Using Machine Learning to Guess Photochemical Reaction Pathways
Abstract: Photochemical reactions are crucial to many activities in the fields of energy conversion, environmental cleanup, and synthetic chemistry. However, predicting their causes and results effectively is still very hard since they entail excited electronic states, nonadiabatic transitions, and complicated potential energy surfaces. Machine learning (ML) has been a powerful technique to go along with classic quantum chemistry methods in the last few years. It offers better prediction capability and lower …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 01–12 Read article
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Light-Matter Interactions in Molecular Photochemistry
Abstract: Molecular photochemistry explores the ways of molecules interaction with light, absorb photons, and excited‐state processes, and ultimately conversion of photon energy into chemical change. Core concepts of this innovative and relevant field are matter interaction like electronic, vibrational, and rotational transitions; non‐adiabatic couplings; energy & electron transfer; and light–matter coupling in weak and strong regimes. This article briefly surveys the multiplicity of these interactions, from the fundamentals of photon absorption …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 33–42 Read article
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Advanced Lithium-Ion Battery Prognostics: A Comprehensive Review of Machine Learning Approaches for Remaining Useful Life Prediction
Abstract: The lithium-ion battery (LIB), as one of the main sources for portable power systems, has been increasingly popular owing to its widespread applications in electric vehicles, consumer electronics, aerospace and renewable energy. Despite their advantages in high energy density and long cycle life, LIBs suffer from degradation over time of aging and cycling, resulting in loss of performance, safety issues, and economic bottlenecks. Predicting their Remaining Useful Life (RUL) is …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 12–27 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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A Detailed Review on Intelligent and Robust Control Strategies for Autonomous Underwater Vehicles with Emphasis on Navigation, Path Tracking, and Stability Enhancement
Abstract: Autonomous Underwater Vehicles (AUVs) have gained significant attention due to their applications in ocean exploration, underwater surveillance, environmental monitoring, and offshore industries. The control of AUVs presents various challenges due to the highly dynamic and uncertain underwater environment, nonlinear hydrodynamics, and external disturbances. This review paper explores various control strategies employed for AUVs, including classical control methods such as Proportional-Integral-Derivative (PID) controllers, modern techniques like Model Predictive Control (MPC), and …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 28–52 Read article
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Harmonically Varying Moving Load on Time-Dependent Uniform Beam Resting on Pasternak Foundation
Abstract: In this paper, we investigated elastic beam whose properties does not varies with spatial coordinate but constant along the span L of the beam. The moving load considered in this work is harmonically varying moving load with non-classical boundary conditions, time dependent boundary conditions in particular. Also, considered in this work is two parameters foundation which are Winkler and Pasternak foundations. Closed form solutions in plotted form are obtained using …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 2, 2025 · pp. 38–47 Read article
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DC Motor Control using Deep Reinforcement Learning for Enhanced Robustness and Precision
Abstract: DC motors remain the workhorse of industrial automation and mobile robotics, but achieving simultaneous high-speed transient response and negligible steady-state error under variable load conditions continues to challenge classical Proportional-Integral-Derivative (PID) controllers. These model-dependent systems often require extensive tuning and struggle to maintain optimal performance when confronted with parametric uncertainties, non-linear friction, or sudden voltage fluctuations. This study presents a novel, model-free control paradigm utilizing Deep Reinforcement Learning (DRL)—specifically, a …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 22–29 Read article
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Deploying Fuzzy Logic for Self-Tuning Regulator Design for Motion Control in Modern Electrical Machines
Abstract: Modern electrical machines require sophisticated motion control systems capable of adapting to varying operating conditions, load disturbances, and parameter uncertainties. Traditional self-tuning regulators (STR) based on classical control theory often struggle with nonlinearities, time-varying dynamics, and complex operational environments characteristic of contemporary electric drives. This article presents a comprehensive framework for deploying fuzzy logic in self-tuning regulator design to address these challenges in motion control applications. Fuzzy logic controllers leverage …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 11–21 Read article
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Comparative of Encryption-Decryption Performance of (Binary, Gray- Scale, Color) Images Using Discrete Fractional Fourier Transform (DFRFT)
Abstract: The Discrete Fractional Fourier transform (DFRFT) provides an effective model of image encryption by further developing the classic Fourier transform by adding fractional orders, which increase the degrees of freedom. Owing to the omnipresence of digital media in many industries like education, healthcare, and entertainment, the mobility of visual data has become a significant issue to keep confidential. Images form one of the main ways of exchanging information and, therefore, …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 1, 2026 · pp. 54–65 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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The Dual Crisis: Antibiotic Resistance and the Discovery Void – A Review of Novel Therapeutic Strategies and Non-Traditional Approaches
Abstract: The global rise of antimicrobial resistance (AMR) has emerged as one of the most critical public health challenges of the 21st century, threatening to undermine decades of therapeutic success and rendering conventional antibiotic regimens increasingly ineffective. Parallel to the escalating resistance rates is a profound “discovery void,” characterised by a steep decline in the development of new antibiotic classes since the late 20th century. Together, these two interconnected crises create …
Published in International Journal of Antibiotics · Vol. 3, Issue 1, 2026 · pp. 47–65 Read article
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CRISPR, Recombinant DNA, and LAMP-Based Platforms for Monkeypox: Emerging Tools for Diagnosis and Therapeutic Development
Abstract: Monkeypox, a zoonotic viral infection caused by the Monkeypox virus of the Orthopoxvirus genus, has recurred as a worldwide public health concern after recent outbreaks outside of its classical endemic areas in Central and West Africa. The resurgence has demanded a thorough reassessment of its epidemiology, mode of transmission, and clinical presentation. In light of these challenges, recombinant DNA technology (rDNA) has emerged as a candidate for developing vaccines, diagnostics, …
Published in International Journal of Virus Studies · Vol. 3, Issue 1, 2026 · pp. 7–28 Read article
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Ayurvedic Nutritional Interventions for Menstrual and Reproductive Health: A Narrative Review
Abstract: Menstrual health is a reflection of a woman’s reproductive health. A proper understanding of menstrual patterns helps in assessing women’s overall health. The menstrual period is a vital process involving endometrial regeneration and the initiation of follicular growth, which ultimately builds the foundation for a healthy offspring. Ayurveda describes various unique regimens for women. Adherence to these regimens helps prevent and manage growing menstrual disorders and infertility, along with the …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 13, Issue 1, 2026 · pp. 1–5 Read article
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Review on the Efficacy of Ayurvedic Formulations in Diabetes Management
Abstract: Diabetes mellitus is one of the most prevalent metabolic disorders globally, characterized by persistent hyperglycemia resulting from defects in insulin secretion, insulin action, or both. It leads to serious complications affecting the cardiovascular, renal, and nervous systems, imposing a significant health and economic burden. In Ayurveda, diabetes is described as Madhumeha, a subtype of Prameha, primarily caused by the vitiation of Kapha dosha, Meda dhatu (fat metabolism), and Agnimandya (impaired …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 13, Issue 1, 2026 · pp. 16–22 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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Integrative Perspectives on Lipoma: Traditional Therapeutics from Siddha, Ayurveda, and Unani with Biomedical Correlates
Abstract: Background: Lipoma is the most common benign soft tissue tumor, with an incidence of approximately 2 per 1,000 individuals annually. Modern biomedicine attributes its pathogenesis to genetic abnormalities like HMGA2 rearrangements and dysregulated adipogenesis via PPARγ pathways. Effective pharmacological therapies are lacking. Traditional Indian systems – Siddha, Ayurveda, and Unani – offer unique perspectives and non‑surgical approaches yet remain underexplored in integrative research. Objective: To critically evaluate the descriptions, pathophysiological …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 13, Issue 1, 2026 · pp. 19–33 Read article
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Pain Management Through Ayurvedic Tablets and Capsules
Abstract: Triphala Guggulu is a classical formulation widely used in Ayurveda for the management of metabolic and inflammatory disorders. It represents a synergistic combination of Triphala – composed of Emblica officinalis, Terminalia bellirica, and Terminalia chebula – along with the oleo-gum resin of Commiphora mukul. In traditional Ayurvedic practice, this formulation has been prescribed for conditions, such as arthritis, obesity, hyperlipidemia, and chronic constipation, primarily due to its reputed ability to …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 13, Issue 1, 2026 · pp. 23–28 Read article
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Epigenetic Modifications in Health, Disease, and Precision Therapeutics (From Genome to Epigenome)
Abstract: Introduction: Epigenetic alterations play a crucial role in regulating gene expression in both normal physiological and disease states. These reversible modifications—such as DNA methylation, histone acetylation, phosphorylation, ubiquitination, and chromatin remodelling—are increasingly implicated in complex diseases including cancer and neurodegenerative disorders. Despite advances in standard therapeutic approaches, patient responses remain variable, largely due to genetic heterogeneity and epigenetic dysregulation. This highlights the need for incorporating epigenetic understanding into personalized medicine. …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 Read article
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Mathematical Modelling of Semiconductor Device Physics: An Analytical Approach
Abstract: Semiconductor device physics forms the foundation of modern electronic and optoelectronic technologies. Mathematical modelling provides a rigorous framework for understanding, predicting, and optimizing the behavior of semiconductor devices by linking physical principles with device-level performance. This work presents an analytical approach to the mathematical modelling of semiconductor devices, emphasizing the derivation and interpretation of governing equations that describe charge transport and electrostatic behavior. The model is based on fundamental physical …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 36–42 Read article
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Effect of Span, Load Intensity, and Beam Geometry on Stress and Deflection Behavior of RCC Beams
Abstract: This study investigates the influence of variations in beam geometry, span, load intensity, and permissible stresses on the structural behavior of reinforced concrete beams. Using classical bending and shear stress formulations, the effects of a 20% increase in key parameters were analytically evaluated. Results indicate that a 20% increase in beam span leads to a proportional 20% increase in beam depth, whereas a 20% increase in beam width or permissible …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 9–22 Read article