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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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Open-Source Software Empowering Artificial Intelligence, Machine Learning, and Cyber Security: A Comprehensive Research Study
Abstract: Open-source software (OSS) has become a foundational pillar for rapid innovation across artificial intelligence (AI), machine learning (ML), and cybersecurity. This paper delivers a comprehensive, journal-length analysis of OSS-driven ecosystems, emphasizing collaborative development, transparency, and accelerated deployment. By providing freely available libraries, tools, and frameworks, OSS makes it easier for developers and researchers to experiment, build models, and deploy solutions quickly. This study examines how OSS can be combined with …
Published in Journal of Open Source Developments · Vol. 13, Issue 1, 2026 · pp. 08–15 Read article
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A Review Article on Oroxylum indicum: A Versatile Medicinal Tree
Abstract: Oroxylum indicum, commonly known as the Indian trumpet tree or Shyonaka, is a medicinal plant belonging to the Bignoniaceae family. It is widely used in traditional medicine systems such as Ayurveda for treating various ailments including neurodegenerative diseases, cardiovascular conditions, arthritis, hepatitis, malignancies, diarrhea, fever, and jaundice. The plant's therapeutic properties are primarily attributed to its rich content of bioactive flavonoids, which exhibit notable anti-cancer, anti-inflammatory, and analgesic effects. Found …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 13, Issue 2, 2026 · pp. 01–07 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Study of the Antibacterial Activity of Artemisia Absinthium against E. coli bacteria Isolated from Urinary Tract Infections
Abstract: Twenty clinically diagnosed samples were collected using transport medium swabs from the operating room at Al-Amal Specialized Laboratory in Iraq between November 2025 and February 10, 2026. Antibiotic susceptibility testing was performed on the 20 Escherichia coli samples. The results showed a clear difference in the bacterial isolates' response to the tested antibiotics. Imipenem demonstrated the highest inhibition rate, reaching 24.55% (100%), compared to the other antibiotics used in the …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 17–25 Read article
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Intelligent Power Quality Enhancement Strategies for PV-Integrated Smart Distribution Networks: A State-of-the-Art Review
Abstract: The rapid integration of photovoltaic (PV) systems into modern power distribution networks has introduced significant challenges related to power quality. Issues such as voltage fluctuations, harmonic distortion, flicker, and reactive power imbalance arise due to the intermittent and nonlinear nature of solar energy generation. This paper presents a concise literature review of various power quality enhancement techniques employed in PV-integrated networks. Key approaches include the use of active power filters …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 30–53 Read article
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Artificial Intelligence and Edge Computing in Oil and Gas: Applications, Architectures, and Operational Realities
Abstract: Artificial intelligence has arrived in oil and gas, and unlike some previous waves of digital enthusiasm in the sector, this one is sticking. Saudi Aramco analyses approximately 10 billion data point every day and reported USD 4 billion in technology-driven operational gains in 2024. ExxonMobil uses AI to increase shale well output by more than 5 percent. Shell has deployed machine learning across more than 10,000 assets using C3.ai to …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 01–06 Read article
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A Study on the Ethical Implications and Data Privacy Challenges in the Age of Artificial Intelligence
Abstract: The fast adoption of Artificial Intelligence (AI) in areas like education, business, and everyday life comes with both tectonic and important ethical and data privacy issues. This paper examines the principle-practice divide between the ideals of the ethics as they are set and applied in the realities of AI implementation. The study is based on a mixed-methodology design, comprising of a quantitative survey of 52 participants and a qualitative study …
Published in Current Trends in Information Technology · Vol. 16, Issue 2, 2025 Read article
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State of the art of Resource Description and Access and Library Information Science in UAE and Gulf in Global Context
Abstract: The purpose of this study is to investigates the state of the art of Resource Description and Access (RDA) and its implementation in Library and Information Science (LIS) within the United Arab Emirates (UAE) and the Gulf region in a global context. The study discusses the principles, structure, and conceptual foundations of RDA, including its relationship with FRBR, FRAD, and the IFLA Library Reference Model. It further explores the reasons …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 2, 2026 · pp. 70–80 Read article
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Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems.Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered nano‑biosensors, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Artificial Intelligence Techniques for Smart Polymer Nanocomposite Materials and Industrial Applications
Abstract: Protecting sensitive material data, manufacturing processes, and intelligent monitoring platforms is essential for the fast development of innovative polymer nanocomposite systems in fields such as aerospace, medicine, electronics, automobiles, and energy. In order to safeguard, consistently enhance, and optimize distributed industrial systems that consist of polymer nanocomposite materials, this study presents an AI-driven cybersecurity and cloud computing architecture. The suggested solution employs artificial intelligence (AI), machine learning (ML), cloud computing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1109–1134 Read article
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Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
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An Efficient Recursive Least Square (ERLS) Algorithm for Spectral Estimation with the Aid of Wavelet and Artificial Intelligence
Abstract: The spectral estimation technique is used for time frequency signal analysis, speech processing, and other signal processing applications. Some drawbacks of RLS algorithm are that it requires high computational power and the output obtained is numerically instability. So, the spectral efficiency of the signal is affected and a power error occurs in the estimator. In this paper, an efficient recursive least square (ERLS) algorithm is proposed for improving the power …
Published in Current Trends in Signal Processing · Vol. 2, Issue 1-3, 2012 · pp. 1–10 Read article
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Artificial Enzymes with Nanoparticle Architecture
Abstract: Nanozymes are a novel form of synthetic enzymes that consist of nanoparticles and exhibit similar properties to natural enzymes. They are more advanced and easier to produce. These nanozymes are grouped into four categories: metal-based, metal oxide-based, carbon-based, and single-atom-based nanozymes. They can be easily prepared using simple methods and are cost-effective. Nanozymes can be affected by various factors. They are commonly employed as biosensors, in bioimaging, and as anti-microbial …
Published in Journal of Catalyst & Catalysis · Vol. 9, Issue 3, 2022 · pp. 27–34 Read article
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Prediction of shear strength of reinforced concrete beams using Artificial Neural Network and evaluated by Finite Element Software
Abstract: ABSTRACTIn this paper, the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference Framework (ANFIS) are utilized to foresee the shear quality of Reinforced Concrete (RC) shafts, and the models are contrasted and American Concrete Institute (ACI) and Iranian Concrete Institute (ICI) observational codes. The ANN display, with Multi-Layer Perceptron (MLP), utilizing a Back-Propagation (BP) algorithm, is utilizedto foresee the shear quality of RC pillars. Six vital parameters are chosen …
Published in Journal of Construction Engineering, Technology & Management · Vol. 8, Issue 1, 2018 · pp. 34–42 Read article
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Time Cost Optimization Techniques in Construction Industries-A Review Article
Abstract: Construction project scheduling and optimizing the schedule has received a considerable amount of attention over the last few decades. Completion of a project in optimum time and minimum cost is a challenge in every project. There are many methods and algorithms available; using which time cost optimization (TCO) can be achieved. This article gives a review on critical path method (CPM), linear programming (LP), genetic algorithm (GA) and ant colony …
Published in Journal of Construction Engineering, Technology & Management · Vol. 5, Issue 2, 2015 · pp. 28–32 Read article
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An empirical investigation using artificial neural networks to evaluate the manageability of object-oriented systems
Abstract: Software can be called quality software if it produces consistent outputs over multiple time of testing. There can be very much difficulties to modify and maintain the software with poor maintainability. For assessing the characteristics of object-oriented software, such as scale, inheritance, integrity, and coupling, numerous object-oriented metrics have been recommended. In this study, we explore object-oriented variables that have the potential to be significant antecedents of software maintenance. In …
Published in Journal of Mechatronics and Automation · Vol. 9, Issue 2, 2022 · pp. 50–58 Read article
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Power Estimation of MAC Block for Artix 7 FPGA using Regression Technique
Abstract: This paper presents the power estimation approach using suitable machine learning technique. Artix-7 FPGA has been chosen as target FPGA (Field Programmable Gate Arrays) platform for understanding the methodology of power estimation. There are various approaches of power estimation for FPGAs have been given in the literature viz. probabilistic, statistical, and LUT based etc. However, this paper discussed a supervised machine learning approach namely curve fitting and regression analysis. The …
Published in Journal of Microcontroller Engineering and Applications · Vol. 8, Issue 3, 2021 · pp. 27–37 Read article
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Prediction of Process Parameters of Friction Stir Welding Using Artificial Neural Network
Abstract: In this paper an artificial neural network (ANN) approach is used to predict the process parameters of friction stir welding (FSW). Initially, the experiments are conducted using the design of experiment (DoE) approach on FSW using L27 orthogonal array. The experiments are conducted using speed, feed, and tool tilt angle as input parameters for DoE and tensile strength, hardness, and ductility as output. ANN is created having 25 neurons and …
Published in Journal of Polymer & Composites · Vol. 11, Issue 3, 2023 · pp. 13–25 Read article
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Artificial Neural Network Implementation in FPGA using Multiplexer-based Weight Updating for Efficient Resource Utilization
Abstract: This paper presents a novel scheme for field-programmable gate array (FPGA) implementation of an artificial neural network (ANN). The proposed implementation is aimed at reducing resource requirement, without compromising on the speed so that a complex ANN architecture could be realized on a single chip at a lower cost. The weight updating process in different layers of the ANN has been carried using a simple MUX-based architecture. Backpropagation algorithm which …
Published in Journal of Semiconductor Devices and Circuits · Vol. 2, Issue 1, 2015 · pp. 1–5 Read article
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Estimation of Discharge Over the Compound Sharp-Crested Weir using Artificial Neural Networks and Genetic Programming
Abstract: Truncated sharp crested weirs are used to measure flow rate and to control water surface upstream, in irrigation canals and laboratory flumes. The main advantages of such weirs are, ease of construction and capability of measuring a wide range of flows with sufficient accuracy. Artificial neural networks (ANNs) and genetic programming (GP) have recently been used for the estimation of hydraulic data. In this study, they were used as alternative …
Published in Journal of Water Resource Engineering and Management · Vol. 2, Issue 3, 2015 · pp. 28–37 Read article