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633 articles for “interpreter”
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IS-Aligned Strategic Evaluation of Fire Protection Systems for Improving Fire Safety in Mixed-Occupancy High-Rise Buildings
Abstract: This paper presents a substantially reworked Indian-context evaluation of fire protection systems in a 14-building high-rise sample from Indore. The study reuses the original field dataset but replaces the earlier code mix with an explicitly IS-aligned and NBC-oriented analytical framework. Physical observation, document review and interview inputs were screened against requirements related to means of egress, compartmentation, fire detection and alarm, hydrants and hose reels, extinguishers, emergency lighting, smoke control, …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 · pp. 15–26 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 26–33 Read article
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Ayurvedic Management of Vātadhika Vātarakta – A Case Series
Abstract: Vātarakta is a classical disorder described in Ayurveda that arises due to the simultaneous vitiation of Vāta and Rakta, resulting in a pathological condition characterized by mutual obstruction (Āvaraṇa) between these two factors. This complex interaction between Vāta and Rakta leads to a wide spectrum of clinical manifestations, making the condition challenging to diagnose and manage effectively. Among the four types of Vātarakta described in classical texts, Vātādhika Vātarakta predominantly …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 62–67 Read article
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Modelling -Based Evaluation of Hybrid Natural Synthetic Fiber Polymer Composites for Sustainable Energy Applications
Abstract: The growing need of lightweight, high-performance, and green energy system materials has increased the research on hybrid polymer composites. This paper gives a modelling-based evaluation of polymer matrix composites which are reinforced using natural fibers like jute, sisal, bamboo in a combination with synthetic glass fibers to be used in sustainable energy sources. An analytical model has been used to assess the effect of hybrid fiber composition on mechanical, thermal, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 682–688 Read article
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Physics-Informed Generative and Tensor-Based Framework for DNA Sequence Simulation and Genomic Structure Discovery
Abstract: In this paper, we explore the intersection of artificial intelligence (AI) and mathematical physics to propose advanced methods for DNA sequence generation and analysis. Specifically, we investigate how physics-informed Generative Adversarial Networks (GANs) and tensor network representations can be harnessed to restructure DNA for applications in genetic science. The proposed methodology offers a unique integration of concepts of thermodynamic modeling with innovative GAN architecture in order to allow the creation …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Prime Editing and Base Editing in Human Hematopoietic Stem Cells Toward Scarless Correction of Monogenic Blood Disorders
Abstract: Monogenic hematological disorders – such as sickle cell disease (SCD), β-thalassemia, and X-linked chronic granulomatous disease (X-CGD) – affect >400, 000 newborns worldwide each year, with a considerable burden in low-resource settings . Although donor-derived allogeneic hematopoietic stem-cell transplantation (HSCT) is widely regarded as curative, its application is limited due to issues of donor availability and graft-versus-host disease (GVHD) and conditioning-related toxicity. DSB-based conventional CRISPR-Cas9 strategies are limited by inefficient …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 · pp. 15–22 Read article
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Ethical AI and Data Protection in the Era of Industry 5.0
Abstract: This paper provides a comprehensive analysis of the critical intersection between Responsible AI (RAI), data privacy, and the Industry 5.0 paradigm. Industry 5.0, defined by its human-centric, sustainable, and resilient pillars, introduces a fundamental paradox: its core requirement for human-AI collaboration necessitates the collection and processing of granular human data, creating direct conflicts with emerging global data privacy and AI regulations. This research utilizes a systematic integrative review methodology, analyzing …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Sanskruti AI : Rediscovering Indian Culture Using Artificial Intelligence
Abstract: Away from old ways, many young people in India now find customs hard to reach, losing touch with sacred texts, local traditions, and deeper beliefs. Into this space steps Sanskruti AI - an intelligent tool using sound, text, and vision to bring culture closer, tailored to how today & users think and feel. Instead of flat translations, it unpacks verses from Sanskrit with layers: word-for-word sense, background context, inner meaning. …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 2, 2026 · pp. 30–36 Read article
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High-Energy Astrophysics: Exploring the Extreme Universe Through Radiation, Relativistic Phenomena, and Cosmic Cataclysms
Abstract: High-energy astrophysics is a fast-developing area of astrophysical research dedicated to exploring the universe’s most powerful and extreme events. It involves investigating dense and energetic cosmic objects and phenomena, including black holes, neutron stars, supernova remnants, gamma-ray bursts, and active galactic nuclei. These sources emit radiation predominantly in the X-ray and gamma-ray regions of the electromagnetic spectrum and are often associated with high-energy particles, including cosmic rays and neutrinos. Investigating …
Published in International Journal of Universe · Vol. 2, Issue 1, 2026 · pp. 10–15 Read article
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Real-Time Edge Detection Camera Module Using Discrete Taylor Transform and Heat Equation (PDE): An Applied Mathematical Approach
Abstract: In modern digital signal processing, the capability for denoising and smoothing in real time is very important in scientific, engineering, and industrial applications. This paper presents an efficient hybrid framework that merges two mathematically sound methods, namely, DTT and PDE defined as the Heat Equation, to robustly denoise a signal with minimal distortion. The model addresses one of the most challenging tasks in signal restoration, which maintains the fidelity of …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 9–14 Read article
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Digital Techniques for Preserving Cultural Heritage
Abstract: Digital heritage includes cultural materials that are available in digital form or have been transformed into digital formats so that they can be preserved and accessed over a long period of time. It represents valuable cultural content that technology helps to store, protect, and share with present and future generations. With the rapid expansion of digital technologies, cultural expressions and historical records are increasingly being created, shared, and stored through …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 2, 2026 · pp. 10–14 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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Quantum-Fuzzy Tensor Operators for Multi-Qubit Conjunction, Disjunction, and Symmetry-Preserving State Discrimination
Abstract: The integration of fuzzy logic and quantum information theory raises a fundamental mathematical question: how can degrees of truth be encoded in multi-qubit amplitudes while preserving the unitary dynamics and symmetry structure of quantum state spaces? This paper develops a tensor-operator framework for implementing quantum-fuzzy logical operations on finite qubit registers. Fuzzy truth values are represented by normalized quantum amplitude pairs, enabling logical information to be embedded directly into quantum …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 16–21 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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Generative Design of Bioactive Orthopedic Composites for Fracture Repair Using an Integrated Conditional GAN–Transformer Framework: A Multi-Objective Approach
Abstract: Orthopedic composite implants for fracture repair must simultaneously satisfy conflicting mechanical and biological demands: high fracture toughness, sufficient compressive stiffness, and bioactive surface chemistry enabling osteoblast adhesion and mineralization. Existing design approaches rely on trial-and-error experimentation, yielding sub-optimal trade-offs between these objectives. This paper presents an integrated conditional Generative Adversarial Network–Transformer (cGAN-T) framework for fully computational, multi-objective generative design of hydroxyapatite (HA)-reinforced polymer composite microstructures targeting Orthopedic fracture repair. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 21–35 Read article
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Ashaya as Abode: Reconciling Ayurvedic Vata Theory with Intestinal Neurophysiology
Abstract: Background-Ashaya refers to a site or structure within the body where a substance resides. Ashaya refers to the internal sites or structures within the body where various substances reside Commonly, seven Ashayas are described in males, while in females there are eight, while Sharangadhara has described 9 Ashayas. Vatashaya denotes the specific site of Vata Dosha, which is considered the chief among the three Doshas due to its vital role …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 2, 2026 · pp. 12–20 Read article
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AI-Based Discovery of High-Performance Energy Storage Polymer Composites: A Comprehensive Review
Abstract: The accelerating global demand for high-performance energy storage systems has stimulated significant research into advanced polymer composites as next-generation electrolytes, electrode binders, and functional membranes for batteries, supercapacitors, and photovoltaic devices. However, the vast compositional and structural design space of polymer materials presents formidable challenges for conventional trial-and-error discovery strategies, which remain slow, costly, and biased by prior expert knowledge. Machine learning (ML) and artificial intelligence (AI) have emerged as …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1083–1097 Read article