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1968 articles for “ztial arts” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Determination of Well Loss and Aquifer Loss of New Construction Deep Water Well at Artesian Aquifer in Khulna City, Bangladesh
Abstract: This work studied the performance of water well installed as artesian aquifer in South Western Region of Bangladesh. The main activities were known to the properties of aquifer condition on that area. Well performance was also measured after development of water well. The well performance and aquifer performance were justified by Rorabaugh’s graphical methods. The total depth of drilling was 305 m from the ground level. Drilling was completed by …
Published in Recent Trends in Civil Engineering & Technology · Vol. 3, Issue 1, 2013 · pp. 8–13 Read article
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A Hybrid voice identification System with Fuzzy Technique and ART2 Neural Network on BPF Technique
Abstract: Abstract:In this work, we evaluate the performance of voice identification through the hybrid method using fuzzy and Adaptive Resonance Theory2. The Voice identification is an important task, which shows the active interaction of natural human-machine, for over last important two decades. The objective of this work, it is consists in working out an identification rate of voice identification. The proposed methodology presented allows evaluating the identification process which considers a …
Published in Journal of Communication Engineering & Systems · Vol. 8, Issue 3, 2018 · pp. 1–6 Read article
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A Study of The Components of State-of-The-Art Agro-Based Management Information Systems in India
Abstract: This paper discusses the basic technologies that are required to develop state of the art agro-based management information systems (MIS) in India. It features a brief review of how agro-based MIS have developed from word of mouth information systems to complex computerized MISs having multiple sources and consumers of information. The value of timely, relevant and accurate dissemination of agro-based information to the farming community for enhancing productivity in agriculture …
Published in Journal of Computer Technology & Applications · Vol. 9, Issue 2, 2018 · pp. 7–14 Read article
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Evaluation of the Knowledge Regarding Risk Factors of Coronary Artery Disease (CAD) among Patients Attending Medical OPD in Doon Medical College Hospital, Dehradun
Abstract: Introduction: The acceleration of Coronary Artery Disease (CAD) has become an alarming health problem across the globe. The Global Burden of Disease study has reported that by the year 2025, CAD would be the major cause of death all over the world including the developing countries. CAD is the most common cause of death in country like India. CAD will be the single largest cause of disease burden globally by …
Published in Journal of Nursing Science & Practice · Vol. 9, Issue 2, 2019 · pp. 28–32 Read article
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Management Principles and Nursing- A Review Article
Abstract: Nursing profession stands as the vital interface between the medical practitioner and the patient. Its significance can be estimated from the fact that it stands tall and supports healthcare sector as the backbone. There are multipronged relationships which are thriving on this profession and needs to be managed to accomplish the ultimate goal of empathic patient care. In this article author has attempted to review the literature available in the …
Published in Journal of Nursing Science & Practice · Vol. 1, Issue 1-2, 2011 · pp. 55–63 Read article
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Analytical Study of Sara Pariksha and its Importance: A Review Article
Abstract: Ayurveda is not simply the science for treating illness but also the science of life which helps to maintain health. The main aim of Ayurveda is to sustain the health of a healthy individual and treat the illness. In Ayurveda, Sara Pariksha is one among the ten types of methods to examine a patient, stated as Dashvidha Aatura Pariksha. Sara Pariksha chiefly determines the strength of a person that is, …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 8, Issue 3, 2021 · pp. 48–54 Read article
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FIR Filter Design using Artificial Neural Network
Abstract: In this paper design a low pass FIR filter by artificial neural network. For this kind of application, a different type of model is used in ANN. In this work, MLP Back propagation algorithm is used to train the Neural Network. MLP network is very effective method for filter designing process. We also compare the result of this method and the normal mathematical method. Keywords: Neural network, MLP back propagation, …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 3, Issue 3, 2013 · pp. 29–35 Read article
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A Review on Al Hijamah (Cupping Therapy): The Unique Art of Healing
Abstract: Unani Medicine (Greco-Arab Medicine) is holistic medicine, art and science of healing which believes in treating the disease from the root, and thereby profiting the man and mankind from grief and sorrow of illness and disease. Four methods have been described for treatment of diseases in Unani Medicine, these are- Ilaj-bil-ghiza (dieto therapy), Ilaj-bil-tadbir (regimental therapy), Ilaj-bid-dawa (pharmacotherapy) and Ilaj-bil-Yad (surgery). Ilaj-bil-tadbir (regimental therapy) and particularly Hijamah (Cupping) is gaining …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 1, Issue 03, 2014 · pp. 1–7 Read article
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Sustainable Biomedical Polymer Composites Designed through Artificial Intelligence Approaches
Abstract: The development of sustainable biomedical polymer composites has become one solution that can be used to combat increasing environmental issues that have been presented by traditional medical materials without compromising functional performance. Implementation of the artificial intelligence (AI) in material design presents a paradigm shift of data-driven development, which improves the efficiency, accuracy, and scalability of composite development. The given work can serve as a universal guideline in developing biodegradable …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Artificial Intelligence-Based Optimization of Mechanical and Biocompatible Properties in Polymer Composite Implants
Abstract: Artificial Intelligence (AI) has already become a ground-breaking tool of streamlining polymer composite implants to enhance both mechanical strength and biocompatibility simultaneously. This paper recommend an AI-based multi-objective optimization model, which integrates the selection of materials, structural modelling, and biological evaluation. The in vitro biocompatibility indicators, including cytotoxicity and cell adhesion, can be used to model mechanical behavior, e.g. stress-strain behavior and fatigue behavior. To arrive at an optimal material …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Artificial Intelligence for Tracking Cognitive Deviation in Aging Populations: A Comprehensive Review of Techniques, Challenges, and Ethical Concerns
Abstract: Population aging is accelerating worldwide, and with it the burden of cognitive health conditions such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and dementia. Detecting and monitoring cognitive change early is central to timely intervention, yet conventional diagnostic tools often miss the subtle signals that appear before overt symptoms. Artificial intelligence (AI) has emerged as a promising complement to clinical assessment because it can work through high-dimensional data and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 27–37 Read article
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From Trace to Truth: Integrating Forensic Science, Analytical Chemistry, Medical Evidence and Artificial Intelligence in Modern Criminal Investigation
Abstract: Modern criminal investigations are inherently interdisciplinary, integrating medical research, forensic science, analytical chemistry, and artificial intelligence (AI) to transform hazy traces into reliable, legally recognised evidence. This study examines the ways in which different domains collaborate across the whole investigation process, ranging from judicial review, laboratory analysis, and computer processing to crime scene management and evidence retrieval. This research is based on a thorough review of scholarly literature and a …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 2, 2026 Read article
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Toxicology 4.0: Integrating Artificial Intelligence, Big Data, Health Informatics, and Precision Analytics for Predictive Toxicity Assessment, Real-Time Toxicovigilance, and Personalized Patient Safety
Abstract: Background: Toxicology is undergoing a major transformation, increasingly described as Toxicology 4.0, driven by the integration of artificial intelligence (AI), big data analytics, health informatics, and precision analytics. Conventional toxicity testing is limited by high costs, lengthy timelines, and challenges in translating animal and low-throughput in vitro findings to humans. Aim and Objectives: To comprehensively evaluate the emerging role of Toxicology 4.0 in predictive toxicity assessment, real-time toxicovigilance, and personalized …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 2, 2026 Read article
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Artificial Intelligence in Autonomous Military Weaponry Systems
Abstract: The rapid rise of artificial intelligence (AI) has transformed contemporary defence organizations, reshaping military structures, operational strategies, and the design and deployment of modern weapons. AI has significantly influenced the architecture, decision-making processes, and functionality of military systems, particularly in complex and rapidly evolving combat scenarios. This paper provides a comprehensive analysis of the growing use of autonomous military weapon systems, focusing on technological developments, regulatory challenges, governance gaps, and …
Published in International Journal on Drones · Vol. 2, Issue 2, 2026 · pp. 09–20 Read article
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Artificial Intelligence and Constitutive Modeling Equations for Predictive Design of High-Performance Polymer Composites
Abstract: Growing polymer composite applications demand accurate mechanical prediction, yet complex interactions and conventional constitutive models limit predictive capability and require extensive calibration. To report these challenges, this research recommends a combined Artificial Intelligence (AI) and constitutive modeling approach based on an Enhanced Tasmanian Devil Optimizer-tuned Residual Neural Network with Multilayer Perceptron (ETDO-ResNet-MLP) for the predictive design of high-performance polymer composites. The study uses a publicly available Polymer Composite Property Dataset …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Transforming Punjab's Education System: A Critical Analysis of Automation and Artificial Intelligence
Abstract: The rapid advancement of Artificial Intelligence (AI) and automation technologies is transforming education systems across the globe. In Punjab, one of India's leading educational regions, AI-driven tools and automated technologies are increasingly being adopted to improve teaching, learning, assessment, administration, and institutional management. This study critically examines the impact of AI and automation on Punjab's education system by exploring their opportunities, challenges, and future prospects. The research is based on …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 31–42 Read article
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Optimizing Performance Characteristics, Thermal Stability, and Manufacturing Performance of Polymer Nanocomposites Using Artificial Intelligence
Abstract: Artificial intelligence (AI) has proven an efficient method to optimize the design and manufacture of polymer nanocomposites, allowing the proper prediction of the behavior of the materials and the results of the processing. This work proposes an AI-based framework to enhance the performance characteristics, thermal stability and manufacturing performance of advanced polymer nanocomposites. The input variables of the proposed framework are the material composition, the nanoparticle concentration, the particle size, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Carbon quantum dots (CQDs) and bioinspired photonic nanomaterials have emerged as promising multifunctional platforms for a wide range of applications in optoelectronics, nanomedicine, biosensing, fluorescence imaging, and photodynamic therapy. CQDs are nanoscale carbon-based materials characterized by unique optical and electronic properties, including size-dependent photoluminescence, high photostability, excellent water solubility, low cytotoxicity, and remarkable biocompatibility. These characteristics make them attractive alternatives to conventional semiconductor quantum dots for both technological and biomedical applications. Inspired by natural photonic systems such as photosynthetic light-harvesting complexes, rhodopsin-based photoreceptors, butterfly wings, and bioluminescent organisms, researchers have developed advanced nanostructures capable of efficient photon capture, energy transfer, and photoinduced charge separation. Recent advances in synthesis techniques, including hydrothermal, solvothermal, microwave-assisted, and green synthesis approaches, have enabled precise control over the size, surface chemistry, and optical properties of CQDs. Functionalization and heteroatom doping further enhance their photophysical performance and application versatility. In optoelectronics, CQDs have been incorporated into photodetectors, solar cells, light-emitting diodes, and flexible electronic devices due to their tunable emission characteristics and efficient charge transport properties. In the biomedical field, CQDs are increasingly utilized for targeted drug delivery, bioimaging, biosensing, and photodynamic therapy because of their excellent fluorescence behavior and biological compatibility. Furthermore, bioinspired photonic nanomaterials are being explored for artificial photosynthesis and sustainable energy conversion systems, where efficient light harvesting and electron transfer are critical. This review highlights recent developments in the synthesis, photophysical properties, and multifunctional applications of CQDs and related bioinspired photonic nanomaterials, while discussing current challenges and future opportunities for the development of intelligent nanophotonic and bioelectronic technologies.
Abstract: Carbon quantum dots (CQDs) and bioinspired photonic nanomaterials have emerged as promising multifunctional platforms for a wide range of applications in optoelectronics, nanomedicine, biosensing, fluorescence imaging, and photodynamic therapy. CQDs are nanoscale carbon-based materials characterized by unique optical and electronic properties, including size-dependent photoluminescence, high photostability, excellent water solubility, low cytotoxicity, and remarkable biocompatibility. These characteristics make them attractive alternatives to conventional semiconductor quantum dots for both technological and biomedical …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 2, 2026 · pp. 16–24 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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The Influence of Artificial Intelligence on Literary Criticism
Abstract: Artificial Intelligence (AI) has emerged as a significant force in reshaping contemporary literary criticism. Traditionally, the interpretation of literature has relied primarily on human-centered methods such as close reading, contextual analysis, and theoretical framing. However, the integration of AI-based techniques including Natural Language Processing (NLP), Machine Learning (ML), stylometry, and sentiment analysis has introduced new possibilities for examining literary texts at both micro and macro levels. These computational approaches allow …
Published in International Journal of Trends in Humanities · Vol. 3, Issue 2, 2026 · pp. 22–29 Read article