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Journal articles on the topic 'AI fabric'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Derek Asir Muthurajan Caleb. "AI-Driven Smart Fabric Provisioning: Transforming Network Automation through Intelligent Orchestration and Dynamic Testing." Journal of Computer Science and Technology Studies 7, no. 3 (2025): 783–90. https://doi.org/10.32996/jcsts.2025.7.3.85.

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The evolution of modern data centers demands innovative approaches to fabric provisioning, particularly when integrating new switches, hosts, and storage into existing infrastructures. This article introduces a Smart Fabric Provisioning solution powered by Agentic AI that transforms traditional manual processes into automated, intelligent workflows. By creating dynamic full-mesh fabrics with simulated environments, the solution addresses critical challenges in solution qualification and resource utilization during proof-of-concept phases. The AI-driven approach enables logical link manipulatio

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D, Sujatha. "AI Based Fabric Inspection System." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 4866–69. https://doi.org/10.22214/ijraset.2025.71305.

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Textile industry continues to face challenges in ensuring consistent fabric quality due to its reliance on manual inspection processes. This study introduces an AI-driven automated fabric inspection system designed to detect surface defects in real time using deep learning and computer vision techniques. The system is built around a Raspberry Pi 5 platform integrated with TensorFlow and a Pi Camera module. A convolutional neural network (CNN) model processes captured images to identify defects, prompting the system to halt fabric movement and activate a pump-based liquid applicator for marking

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Siva Prasad Nandi. "Serverless databases: Architectural evolution, implementation strategies, and future directions in cloud-native data management." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 567–74. https://doi.org/10.30574/wjarr.2025.26.2.1591.

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The evolution of modern data centers demands innovative approaches to fabric provisioning, particularly when integrating new switches, hosts, and storage into existing infrastructures. This article introduces a Smart Fabric Provisioning solution powered by Agentic AI that transforms traditional manual processes into automated, intelligent workflows. By creating dynamic full-mesh fabrics with simulated environments, the solution addresses critical challenges in solution qualification and resource utilization during proof-of-concept phases. The AI-driven approach enables logical link manipulatio

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Petrak, Slavenka, Maja Mahnić Naglić, Martina Glogar, and Antoneta Tomljenović. "Assessment of Textile Material Properties and the Impact of Digital Ink-Jet Fabric Printing on 3D Simulation as a Sustainable Method for Garment Prototyping." Sustainability 17, no. 4 (2025): 1388. https://doi.org/10.3390/su17041388.

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In the context of sustainable fashion, this paper presents research on the impact of property assessment methods of textile materials and pigment digital printing on the mechanical properties of fabrics and their 3D simulation in the development of digital prototypes for clothing design. Six woven fabrics, with and without a textile ink-jet print, were tested using a KES-FB measuring system and digitized using SEDDI Textura AI technology. The determined mechanical parameters were used for 3D draping simulations based on Cusick Drape Meter method, as well as for the simulation of frilly women’s

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Tu, Yi-Fan, Mei-Ying Kwan, and Kit-Lun Yick. "A Systematic Review of AI-Driven Prediction of Fabric Properties and Handfeel." Materials 17, no. 20 (2024): 5009. http://dx.doi.org/10.3390/ma17205009.

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Artificial intelligence (AI) is revolutionizing the textile industry by improving the prediction of fabric properties and handfeel, which are essential for assessing textile quality and performance. However, the practical application and translation of AI-predicted results into real-world textile production remain unclear, posing challenges for widespread adoption. This paper systematically reviews AI-driven techniques for predicting these characteristics by focusing on model mechanisms, dataset diversity, and prediction accuracy. Among 899 papers initially identified, 39 were selected for in-

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Sandhya, NC, Nihal Mathew Sashikumar, M. Priyanka, Sebastian Maria Wenisch, and Kunaraj Kumarasamy. "Automated Fabric Defect Detection and Classification: A Deep Learning Approach." Textile & Leather Review 4 (December 14, 2021): 315–35. http://dx.doi.org/10.31881/tlr.2021.24.

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A computer-based intelligent visual inspection system plays a major role in evaluating the quality of textile fabrics and its demand is continuously increasing in the textile industry, especially when the quality of textile is to be considered. In this paper, we propose an AI-based automated fabric defect detection algorithm which utilizes pre-trained deep neural network models for classifying possible fabric defects. The fabric images are enhanced by pre-processing at various levels using conventional image processing techniques and they are used to train the networks. The Deep Convolutional

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Ms Shital K Dhamal, Dr Chandani Joshi, Dr D.S Chouhan. "Fabric Defect Analysis In Textile Manufacturing: Evaluating Methods For Generic And Jacquard Fabrics." Tuijin Jishu/Journal of Propulsion Technology 44, no. 3 (2023): 3534–41. http://dx.doi.org/10.52783/tjjpt.v44.i3.2064.

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Regarding maintaining product quality and satisfying customer expectations, fabric defect analysis is vital in textile manufacturing. This research provides a comprehensive assessment of many techniques used for analyzing and pinpointing flaws in standard and Jacquard textiles. This study considers machine vision systems and AI-based algorithms as two examples of cutting-edge automation alongside more conventional human inspection procedures. Manual inspection techniques are extensively reviewed in the first section, with particular emphasis on these techniques' inherent subjectivity and resou

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Li, Yun Feng, Li Qian Huang, and Jian Yong Yu. "Study on the Pore Structure of Cotton-Like Polyester Knitted Fabrics." Advanced Materials Research 821-822 (September 2013): 270–73. http://dx.doi.org/10.4028/www.scientific.net/amr.821-822.270.

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Porous structure of fabric has a significant impact on the fabric functions such as air permeability, water transport and heat retention. In this article, six knitted fabrics with different blend ratio of cotton-like modified polyester fiber and cotton fiber were prepared. Pore sizes and its distribution of the fabrics were measured by CFP-1100-AI pore diameter tester. Porosity of the fabrics was obtained by three ways respectively, namely loop model method, image method and density method. The results show that the pore diameter of blended knitted fabrics presents an asymmetric distribution,

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Mahnić Naglić, Maja, Slavenka Petrak, and Antoneta Tomljenović. "Analysis of Woven Fabric Mechanical Properties in the Context of Sustainable Clothing Development Process." Polymers 17, no. 15 (2025): 2013. https://doi.org/10.3390/polym17152013.

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This paper presents research in the field of computer-aided 3D clothing design, focusing on an investigation of three methods for determining the mechanical properties of woven fabrics and their impact on 3D clothing simulations in the context of sustainable apparel development. Five mechanical parameters were analyzed: tensile elongation in the warp and weft directions, shear stiffness, bending stiffness, specific weight, and fabric thickness. These parameters were integrated into the CLO3D CAD software v.2025.0.408, using data obtained via the KES-FB system, the Fabric Kit protocol, and the

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Oluwatosin Oladayo Aramide. "Architecting highly resilient AI Fabrics: A Blueprint for Next-Gen Data Centers." World Journal of Advanced Engineering Technology and Sciences 8, no. 1 (2023): 529–39. https://doi.org/10.30574/wjaets.2023.8.1.0049.

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The fast-growing advancement in AI technologies has resulted in huge loads on the data center architecture resulting in the need to create extremely resistant, and fault-tolerant AI fabrics. This paper looks at AI design principles and technologies necessitated in the construction of fault-tolerant AI infrastructures that can support complex, data-heavy workloads. The major technologies of VXLAN EVPN, RDMA and ultra-low latency interconnect like RoCEv2, NV Link and PCIe Gen5 are paramount to high availability, low latency and high throughput. This article reviews industrial best practice by ob

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Senarathne, Randitha, and Rusitha Thennakoon. "Fabric Inspection Using Computer Vision." International Journal of Media and Networks 3, no. 1 (2025): 01–07. https://doi.org/10.33140/ijmn.03.01.02.

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The textile industry is one of the basic parts of global manufacturing and is about to undergo a significant metamorphosis with the rise in technologies of artificial intelligence and computer vision. Traditionally, fabric inspection has been labor-intensive, requiring a lot of time and highly critical eyes for spotting defects, making it a process often blemished by human error. The advent of AI-enabled technology is allowing textile producers to implement automated inspection systems that enhance efficiency and raise quality benchmarks. This shift not only increases productivity but also gua

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Nalle, Derwi Rainord, Luh Gede Astuti, I. Gede Santi Astawa, Luh Arida Ayu Rahning Putri, AAIN Eka Karyawati, and I. Wayan Supriana. "Implementasi Metode Convolutional Neural Network Untuk Pengenalan Pola Motif Kain Tenun Rote Ndao Berbasis Android." JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) 11, no. 1 (2022): 157. http://dx.doi.org/10.24843/jlk.2022.v11.i01.p17.

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Rote ndao Ikat Weaving has interesting characteristics in each fabric motif because it has different motifs which indicate the ethnic differences contained in each of the resulting motifs. Rote Ndao weaving has a variety of motifs that are still unknown to many people, so in this study a classification of motifs of rote ndao woven fabrics was carried out using the Convolutional Neural Network method. Weaving motif classification uses 3 motifs with a total of 1050 data including 70 data for Ai Bunak, Dula Kakaik and Lafa Langgak motifs each. Data for 3 fabric motifs is divided into 80% training

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Yang, Yingxue, Xiuqin Zhang, Xiaogang Chen, and Shengnan Min. "Numerical Study on the Effect of Z-Warps on the Ballistic Responses of Para-Aramid 3D Angle-Interlock Fabrics." Materials 14, no. 3 (2021): 479. http://dx.doi.org/10.3390/ma14030479.

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In order to achieve an efficient ballistic protection at a low weight, it is necessary to deeply explore the energy absorption mechanisms of ballistic fabric structures. In this paper, finite element (FE) yarn-level models of the designed three-dimensional (3D) angle-interlock (AI) woven fabrics and the laminated two-dimensional (2D) plain fabrics are established. The ballistic impact responses of fabric panels with and without the interlocking Z-warp yarns during the projectile penetration are evaluated in terms of their energy absorption, deformation, and stress distribution. The Z-warps in

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Hassan, Syed Ali, Michail J. Beliatis, Agnieszka Radziwon, Arianna Menciassi, and Calogero Maria Oddo. "Textile Fabric Defect Detection Using Enhanced Deep Convolutional Neural Network with Safe Human–Robot Collaborative Interaction." Electronics 13, no. 21 (2024): 4314. http://dx.doi.org/10.3390/electronics13214314.

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The emergence of modern robotic technology and artificial intelligence (AI) enables a transformation in the textile sector. Manual fabric defect inspection is time-consuming, error-prone, and labor-intensive. This offers a great possibility for applying more AI-trained automated processes with safe human–robot interaction (HRI) to reduce risks of work accidents and occupational illnesses and enhance the environmental sustainability of the processes. In this experimental study, we developed, implemented, and tested a novel algorithm that detects fabric defects by utilizing enhanced deep convolu

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Singh, Jaidev. "AI-Empowered Security Data Fabrics: Review and Insights on Intelligent Data Pipeline Management." International Journal for Research in Applied Science and Engineering Technology 13, no. 6 (2025): 1889–93. https://doi.org/10.22214/ijraset.2025.72218.

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Security data fabrics have emerged as pivotal structures to integrate diverse security tools and data sources, providing streamlined, actionable insights. Leveraging artificial intelligence (AI) within intelligent data pipeline management significantly enhances threat detection, prediction, and response capabilities. AI methods such as machine learning, deep learning, and natural language processing automate complex analytical tasks, improve anomaly detection accuracy, and facilitate proactive threat mitigation. This review synthesizes recent developments and evaluates various AI-driven method

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Anugu, Swapna Reddy. "DATA FABRIC: THE FOUNDATION OF AI-DRIVEN ENTERPRISE INTELLIGENCE." INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY AND MANAGEMENT INFORMATION SYSTEMS 16, no. 2 (2025): 36–48. https://doi.org/10.34218/ijitmis_16_02_004.

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Gautam, Mamta, and Kathleen Ross. "Leadership in the era of AI: skills for 2025 and beyond." Canadian Journal of Physician Leadership 11, no. 2 (2025): 91–101. https://doi.org/10.37964/cr24792.

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As artificial intelligence (AI) transforms the fabric of health care, physician leaders face an urgent call to lead with vision, nimbleness, and a deep sense of ethical responsibility. AI is not a silver bullet; it is, however, here to stay. How we lead through disruption in this era of AI will shape the future of medicine.

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Marcus, Gary. "Hoping for the Best as AI Evolves." Communications of the ACM 66, no. 4 (2023): 6–7. http://dx.doi.org/10.1145/3583078.

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The Communications website, https://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of Communications , we'll publish selected posts or excerpts. twitter Follow us on Twitter at http://twitter.com/blogCACM https://cacm.acm.org/blogs/blog-cacm Gary Marcus on the systems that "pose a real and imminent threat to the fabric of society."

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Choi, Hee Sun (Sunny), Gerhard Bruyns, Tian Cheng, and Jiangtao Xie. "EVOLVING RESEARCH METHOD IN THREE-DIMENSIONAL AND VOLUMETRIC URBAN MORPHOLOGY OF A HIGHLY DENSE CITY: ASSESSING PUBLIC AND QUASI-PUBLIC SPACE TYPOLOGIES." JOURNAL OF ARCHITECTURE AND URBANISM 48, no. 1 (2024): 25–38. http://dx.doi.org/10.3846/jau.2024.18841.

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An appropriate urban density is a vital part of a sustainable urban fabric. However, when it comes to measuring the built urban fabric and how people walk through it and use, a difficulty has been observed in defining applicable measurement tools. With the intention of identifying the variables that will allow the best characterization of this fabric and movement, a multi-variable analysis methodology from the field of artificial intelligence (AI) is proposed. The main objective of this paper is to prove the capacity of AI as an evolving research method in urban morphology and specifically to

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Ghori, Ilham, Kayvan Karim, and Dima Alkawadri. "GenAI-Driven Image Generation Pipeline for Sustainable Garment Design and Waste Reduction in Fashion Production." Proceedings of the AAAI Symposium Series 6, no. 1 (2025): 218–26. https://doi.org/10.1609/aaaiss.v6i1.36056.

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The fashion industry’s linear production model generates significant pre-consumer textile waste, especially during pattern cutting. In response to the environmental impact of fashion consumption, strategies such as reuse, recycling, and refashioning aim to divert textiles from landfills and promote sustainable practices. However, challenges in the textile sector—such as raw material variability and complex manufacturing—require more targeted solutions. Recent studies have identified Artificial Intelligence (AI) as a promising tool to enhance sustainability, streamline production, and enable pe

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Narendra Kumar Reddy Choppa and Mark Knipp. "Advancing Generative AI with GraphQL API: Unified Data Access in Microsoft Fabric Ecosystem." Journal of Computer Science and Technology Studies 7, no. 5 (2025): 438–50. https://doi.org/10.32996/jcsts.2025.7.5.54.

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GraphQL API integration within the Microsoft Fabric ecosystem represents a transformative advancement in how organizations manage and access data across diverse data sources unified by OneLake, including Lakehouses, Data Warehouses, SQL Databases, Mirrored Databases, and Datamarts. This integration enables efficient data retrieval, optimized query processing, and seamless connectivity across the Microsoft Fabric ecosystem. This unified data access approach is particularly advantageous for generative AI applications, as it simplifies the process of gathering and integrating diverse datasets req

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Shih, Naai-Jung. "AI-Generated Graffiti Simulation for Building Façade and City Fabric." Societies 14, no. 8 (2024): 142. http://dx.doi.org/10.3390/soc14080142.

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Graffiti represents a multi-disciplinary social behavior. It is used to annotate urban landscapes under the assumption that building façades will constantly evolve and acquire modified skins. This study aimed to simulate the interaction between building façades and generative AI-based graffiti using Stable Diffusion® (SD v 1.7.0). The context used for graffiti generation considered the graffiti as the third skin, the remodeled façade as the second skin, and the original façade as the first skin. Graffiti was created based on plain-text descriptions, representative images, renderings of scaled

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MoDastoni, Dawood Ali. "Exploring methods to make AI decisions more transparent and understandable for humans." Advances in Engineering Innovation 3, no. 1 (2023): 32–36. http://dx.doi.org/10.54254/2977-3903/3/2023037.

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As Artificial Intelligence (AI) systems increasingly weave into the fabric of diverse sectors, their intricate and often opaque decision-making processes pose challenges to users and stakeholders alike. The 'black box' nature of AI, especially deep learning models, highlights a pressing need for transparency and interpretability. This paper delves into the significance of making AI decisions transparent and provides a comprehensive exploration of methods aimed at demystifying AI processes. Through the lens of Explainable AI (XAI) and advanced visualization tools, we underscore the importance o

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Shrivastava, Pranshul. "An Analytical Exploration of the AI-Based Startup Ecosystem in Madhya Pradesh." International Journal for Research in Applied Science and Engineering Technology 11, no. 10 (2023): 1663–68. http://dx.doi.org/10.22214/ijraset.2023.56023.

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Abstract: The rapid proliferation of advanced technologies, exemplified by AI systems like ChatGPT, has catalyzed profound transformations across industries, necessitating a nuanced comprehension of regional AI ecosystems. This research endeavors to delve into the AI landscape in Madhya Pradesh, driven by a burgeoning entrepreneurial ethos. Drawing on data sourced from the Madhya Pradesh Startup Centre, our study conducts a comprehensive examination of AI innovation from multiple perspectives. Our investigation encompasses an analysis of funding trends, the dynamics of diversity among leaders,

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Deng, Meizhen, Yimeng Liu, and Ling Chen. "AI-driven innovation in ethnic clothing design: an intersection of machine learning and cultural heritage." Electronic Research Archive 31, no. 9 (2023): 5793–814. http://dx.doi.org/10.3934/era.2023295.

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<abstract><p>This study delves into the innovative application of Artificial Intelligence (AI) and machine learning algorithms in the realm of ethnic fashion design, with a specific emphasis on the Miao women's apparel. We introduce an AI-powered approach that strategically bridges modern technology with traditional elements, denoting a significant stride in the field of fashion design. Our research underscores three major aspects: customization of body shape, fabric selection, and innovative design. An AI-driven statistical methodology was utilized to accurately adapt to the uniqu

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K. Sharath Kumar, Dr. M. Rama Bai. "ResNet50: Automated Fabric Defect Detection and Classification based on a Deep Learning Approach." Tuijin Jishu/Journal of Propulsion Technology 44, no. 4 (2023): 2156–65. http://dx.doi.org/10.52783/tjjpt.v44.i4.1194.

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"The demand for an intelligent computer-based system for visual inspection is on the rise in the textile business, especially among those who place a premium on textile quality. In this research, we present a fully automated AI-driven algorithm for defect detection in fabric, one that makes use of deep neural network models that have already been pre-trained. In order to train the networks, the fabric images go through a series of pre-processing steps where typical image processing techniques are applied. In order to train and categorize various fabric flaws, we use Deep Convolutional Neural N

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Siddiqa, Ayesha. "Revolutionary 3D Design with AI." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34308.

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The 3D design delves into the creation and deployment of an innovative web experience that seamlessly merges Artificial Intelligence (AI) technology and captivating 3D visuals within a React-based framework. It demonstrates the utilization of AI algorithms for enhancing user interactivity, personalization, and the creation of dynamic 3D elements, fostering a captivating user experience. Embark on a transformative journey into the heart of fashion's evolution, this unveils a paradigm-shifting collaboration between Artificial Intelligence (AI) and 3D cloth design, heralding a new era of creativi

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Kulkarni, Nilesh D., and Saurav Bansal. "Revolutionizing Manufacturing: The Integral Role of AI and Computer Vision in Shaping Future Industries." Journal of Global Economy, Business and Finance 6, no. 6 (2024): 5–10. http://dx.doi.org/10.53469/jgebf.2024.06(06).02.

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The emergence of artificial intelligence (AI), specifically generative AI and computer vision (CV), has marked a transformative period in the manufacturing industry. This article delves into the depths of these subfields, uncovering their significant impact on various aspects of manufacturing processes. It provides an insightful examination into how AI and CV are not mere technological advancements but rather essential tools for businesses striving for innovation and competitive edge in the technologically saturated market of today. The integration of AI, particularly computer vision, into the

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Oluwatosin Oladayo ARAMIDE. "Converged Ethernet and InfiniBand Strategies for Hybrid AI/HPC Environments." International Journal for Research Publication and Seminar 15, no. 1 (2024): 318–39. https://doi.org/10.36676/jrps.v15.i1.1665.

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Artificial intelligence (AI) and high-performance computing (HPC) have exponentially increased in the number of hybrid workloads, which has necessitated the demand of networking infrastructures with flexibility to support diverse performance, latency, and scaling needs. Conventionally, Ethernet and InfiniBand have been used to connect data centers in different ways- a general-purpose data center connectivity is Ethernet and improved low-latency HPC- intensive functions are housed on InfiniBand. Workloads, however, are converging between AI and HPC, moving data centers to either centralized or

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Iyer, S. S., S. Jangam, and B. Vaisband. "Silicon interconnect fabric: A versatile heterogeneous integration platform for AI systems." IBM Journal of Research and Development 63, no. 6 (2019): 5:1–5:16. http://dx.doi.org/10.1147/jrd.2019.2940427.

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Elmaoğlu, Erhan, Adnan Batuhan Coşkun, and Selda Yüzer Alsaç. "Redefining Nursing Practice: Integrating ChatGPT in the Fabric of Healthcare AI." Archives of Physiotherapy and Global Researches 26, no. 2 (2023): 7–10. http://dx.doi.org/10.5604/01.3001.0054.3313.

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This comprehensive study delves into the innovative application of ChatGPT, an Artificial Intelligence (AI) model, within the realm of nursing. Through an extensive literature review spanning from November 2022 to June 2023, this research has meticulously selected and analyzed 16 out of 32 identified articles that intersect the domains of ChatGPT and nursing. The core of the study lies in assessing the multifaceted roles of ChatGPT in healthcare, primarily focusing on its utility in nursing practices. The research underscores ChatGPT's efficacy in streamlining reporting, summarization, and doc

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Jin, Rui, and Qiang Niu. "Automatic Fabric Defect Detection Based on an Improved YOLOv5." Mathematical Problems in Engineering 2021 (September 30, 2021): 1–13. http://dx.doi.org/10.1155/2021/7321394.

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Fabric defect detection is particularly remarkable because of the large textile production demand in China. Traditional manual detection method is inefficient, time-consuming, laborious, and costly. A deep learning technique is proposed in this work to perform automatic fabric defect detection by improving a YOLOv5 object detection algorithm. A teacher-student architecture is used to handle the shortage of fabric defect images. Specifically, a deep teacher network could precisely recognize fabric defects. After information distillation, a shallow student network could do the same thing in real

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Ojha, Ayush Kumar. "Unveiling the Human Face of AI: Navigating the Social Terrain in Business Environments." April-May 2024, no. 43 (April 1, 2024): 1–7. http://dx.doi.org/10.55529/jaimlnn.43.1.7.

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This research paper delves into the intrcate interplay between artificial intelligence (AI) and the social fabric of business environments. As organizations increasingly integrate AI technologies, there is a profound impact on the dynamics of human interaction, communication, and collaboration. We explore the implications of AI adoption on employee relationships, team dynamics, and organizational culture, shedding light on both the positive transformations and challenges that emerge. Through a comprehensive examination of realworld case studies and relevant literature, this research aims to co

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García-Berrio Hernández, María Teresa. "Facing fundamental rights in the age of preventive ex ante AI: a contemporary form of discrimination." Deusto Journal of Human Rights, no. 14 (December 22, 2024): 101–25. https://doi.org/10.18543/djhr.3191.

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As Artificial Intelligence (AI) systems become increasingly integrated into the social fabric of contemporary communities, ethical considerations surrounding their impact on fundamental rights have come to the fore. Indeed, the growing significance of AI has recently prompted a pivotal discourse within academic and policy circles in Europe concerning the development of an ethical framework for human-centric AI. As part of a broader research project examining the implications of AI on fundamental rights, particularly the right to non-discrimination, our objective is to present a preliminary ove

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Kavitha, R., S. Sherin Fathma, and V. Vinitha. "AI: A Catalyst for Language Preservation in the Digital Era." Shanlax International Journal of English 12, S1-Dec (2023): 102–6. http://dx.doi.org/10.34293/rtdh.v12is1-dec.39.

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Languages, a cornerstone of human culture, embody the essence of a community’s history, values, and identity. However, amidst the vast tapestry of linguistic diversity, numerous languages face the precipice of extinction, threatening the very fabric of cultural heritage. In this digital age, the advent of Artificial Intelligence (AI) emerges as a beacon of hope in the race against language loss. AI technologies present unprecedented opportunities to document, revive, and preserve endangered languages, igniting a renewed vigour in safeguarding these invaluable linguistic treasures.

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Praveen, Borra. "Microsoft Fabric Review: Exploring Microsoft's New Data Analytics Platform." International Journal of Computer Science and Information Technology Research 12, no. 2 (2024): 34–39. https://doi.org/10.5281/zenodo.11502585.

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<strong>Abstract:</strong> Microsoft Fabric represents a significant leap forward in analytics services, combining data management, analytics, and machine learning into a unified platform. This paper offers a detailed examination of Microsoft Fabric, covering its architecture, prominent features, advantages, and potential applications. Engineered to streamline data processes and foster collaboration among data experts, Microsoft Fabric supports real-time analytics, scalable data storage, advanced machine learning capabilities, and robust security protocols. Future developments for the platform

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Zhu, Guangzhou, Yixuan Li, and Siyi Zhang. "Digital Restoration of Tang Dynasty Ladies’ Costumes in the “Ramming & Washing Silk Painting” Based on AI and 3D Technology." Electronics 14, no. 6 (2025): 1139. https://doi.org/10.3390/electronics14061139.

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Digital restoration has become an effective way to restore traditional costumes, but there are still problems such as low modeling efficiency and difficult pattern recognition. This study focuses on Tang Dynasty ladies in the “ramming & washing silk painting”, integrating AI + 3D technology with costume culture for comprehensive restoration. The methodology includes era-specific analysis for identity and body shape determination, image-based sizing, fabric identification, color matching, and pattern restoration using AI and edge-detection algorithms. Comparative analysis with original imag

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Kumar, Dr T. Sathish, S. Muthuvelammai, and N. Jayachandran. "AI in Textiles: A Review of Emerging Trends and Applications." International Journal for Research in Applied Science and Engineering Technology 12, no. 9 (2024): 1663–78. http://dx.doi.org/10.22214/ijraset.2024.64404.

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Abstract: The integration of Artificial Intelligence (AI) in the textile industry is driving significant advancements across various domains, including manufacturing, design, quality control, and sustainability. This review explores how AI technologies, such as machine learning, computer vision, and predictive analytics, are transforming traditional processes to enhance efficiency, reduce waste, and offer innovative solutions for smart textiles and wearable technology. AI-driven automation is optimizing production workflows, while AI-powered quality control ensures higher accuracy in defect de

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Jaganathan, Gowthami, and Shanthi Natesan. "Blockchain and explainable-AI integrated system for Polycystic Ovary Syndrome (PCOS) detection." PeerJ Computer Science 11 (February 28, 2025): e2702. https://doi.org/10.7717/peerj-cs.2702.

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In the modern era of digitalization, integration with blockchain and machine learning (ML) technologies is most important for improving applications in healthcare management and secure prediction analysis of health data. This research aims to develop a novel methodology for securely storing patient medical data and analyzing it for PCOS prediction. The main goals are to leverage Hyperledger Fabric for immutable, private data and to integrate Explainable Artificial Intelligence (XAI) techniques to enhance transparency in decision-making. The innovation of this study is the unique integration of

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Shih, Naai-Jung. "AI- and AR-Assisted 3D Reactivation of Characters in Paintings." Heritage 8, no. 6 (2025): 207. https://doi.org/10.3390/heritage8060207.

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Ancient paintings are an intangible window to the economy, politics, and customs of the past. Their characteristics have evolved or were made obsolete, with only limited contemporary connections remaining. This research aims to preserve and to interact with characters in 2D paintings to evolve their cultural identity through combining AI and AR. The scope of this research covers traditional Chinese paintings archived by the National Palace Museum in digital collections, mainly “New Year’s Market in a Time of Peace”. About 25 characters were used for training and 3D reconstruction in RODIN®. Th

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Germani, Federico, Giovanni Spitale, and Nikola Biller-Andorno. "The Dual Nature of AI in Information Dissemination: Ethical Considerations." JMIR AI 3 (October 15, 2024): e53505. http://dx.doi.org/10.2196/53505.

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Infodemics pose significant dangers to public health and to the societal fabric, as the spread of misinformation can have far-reaching consequences. While artificial intelligence (AI) systems have the potential to craft compelling and valuable information campaigns with positive repercussions for public health and democracy, concerns have arisen regarding the potential use of AI systems to generate convincing disinformation. The consequences of this dual nature of AI, capable of both illuminating and obscuring the information landscape, are complex and multifaceted. We contend that the rapid i

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del-Castillo-Borja, Isabel. "Empathy, Accessibility, and Transparency in the Future of Artificial Intelligence: A Critical Perspective on Technology's Role in Modern Life." Journal of Artificial Intelligence and Computing Applications 2, no. 1 (2025): 28–34. https://doi.org/10.5281/zenodo.14693083.

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Artificial intelligence (AI) has profoundly reshaped daily life, offering unprecedented efficiency and convenience across sectors such as healthcare, education, and agriculture. However, its rapid adoption raises critical concerns about its unintended societal consequences. This article argues that while AI enhances human capabilities, overreliance on its automation risks eroding creativity, critical thinking, and interpersonal connections, particularly among younger generations. Building on existing research, this paper adopts a critical perspective to highlight the dual nature of AI: its pot

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Hildebrand, Christian. "The Machine Age of Marketing: How Artificial Intelligence Changes the Way People Think, Act, and Decide." NIM Marketing Intelligence Review 11, no. 2 (2019): 10–17. http://dx.doi.org/10.2478/nimmir-2019-0010.

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AbstractWhatever your perception of AI is, the machine age of marketing has arrived. To fully grasp how AI is changing every fabric of both our professional and private lives, we need to abstract beyond the presence of autonomous cars, digital voice assistants, or using machines to translate some text for us. AI is creating new forms of competition, value chains, and novel ways of orchestrating economies around the world. AI is more than just technology, it’s creating a new economy. The fuel that runs this economy is the combination of computational processing power, data, and the algorithms t

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Tran, Tuyet Thi Minh. "Confucianism and Hồ Chí Minh’s Thought". Revista Amazonia Investiga 13, № 83 (2024): 24–35. https://doi.org/10.34069/ai/2024.83.11.2.

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This paper explores the profound influence of Confucianism on the ideological framework of Hồ Chí Minh, a pivotal figure in Vietnam’s history. Confucianism, rooted in political ethics and moral education, entered Vietnam early and played a dominant role in shaping its intellectual and social fabric. Hồ Chí Minh, born into a family deeply embedded in Confucian traditions, was extensively exposed to its principles from a young age. This study examines how Hồ Chí Minh adopted and adapted Confucian ideals, particularly its emphasis on moral integrity, education, and the value of people as the foun

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Abdullah, Ameera Ahmed, and Wrya Sabir Abdullah. "Impact of contemporary rebuilding process on changing architectural genotype." Revista Amazonia Investiga 11, no. 56 (2022): 250–63. http://dx.doi.org/10.34069/ai/2022.56.08.25.

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The rapid economical, socio-cultural changes in Sulaymaniyah city, Iraq in the last three decades promoted radical changes on both urban and architectural level. Several traditional houses in the historical center of the city have been demolished and replaced with rebuilt modern houses leaving negative impacts on the old fabric at both formal and spatial level. This paper aims to investigate the role of the contemporary rebuilding process achieved by landowners within the traditional neighborhoods of the city on changing the underlying genotype constants of housing spatial configuration throug

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Erçin, Çilen, and Luqmaan Fihri Abdallah. "Analyzing user satisfaction and perception for the sustainable development of Mama Ngina waterfront in Kenya." Revista Amazonia Investiga 12, no. 66 (2023): 116–33. http://dx.doi.org/10.34069/ai/2023.66.06.12.

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Public spaces play a crucial role in the well-being of communities, providing accessible, and open areas for various activities. This article focuses on the significance of analysing user satisfaction and perception in shaping the future of Mama Ngina Waterfront, a newly developed public space in Mombasa, Kenya. Mama Ngina Waterfront aims to enhance the social and economic welfare of the local society by offering a range of amenities and services. Understanding user perception and satisfaction is crucial for the waterfront's sustainable development. The article explores the research questions

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Shi, Jianzheng. "The Evolution and Future of DAOs: Embracing AI and New Technologies." Technium: Romanian Journal of Applied Sciences and Technology 13 (October 6, 2023): 117–23. http://dx.doi.org/10.47577/technium.v13i.9637.

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Decentralized Autonomous Organizations (DAOs) represent a paradigm shift in the realm of organizational structures, leveraging blockchain technology to operate autonomously through smart contracts and collective decision-making. This article delves into the evolution and potential future of DAOs, emphasizing the integration of Artificial Intelligence (AI) and emerging technologies. Drawing from seminal literature, the article underscores the transformative potential of DAOs in reshaping organizational governance, contract formulation, and decentralized operations. The integration of AI promise

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Mao, Makara, and Min Hong. "YOLO Object Detection for Real-Time Fabric Defect Inspection in the Textile Industry: A Review of YOLOv1 to YOLOv11." Sensors 25, no. 7 (2025): 2270. https://doi.org/10.3390/s25072270.

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Automated fabric defect detection is crucial for improving quality control, reducing manual labor, and optimizing efficiency in the textile industry. Traditional inspection methods rely heavily on human oversight, which makes them prone to subjectivity, inefficiency, and inconsistency in high-speed manufacturing environments. This review systematically examines the evolution of the You Only Look Once (YOLO) object detection framework from YOLO-v1 to YOLO-v11, emphasizing architectural advancements such as attention-based feature refinement and Transformer integration and their impact on fabric

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Bossard, Robert L., and Alberto B. Broce. "Evaluation of Glass, Nylon Fabric and Filter Paper as Substrates in Insecticide Bioassays of Cat Fleas (Siphonaptera: Pulicidae)1." Journal of Entomological Science 37, no. 2 (2002): 182–92. http://dx.doi.org/10.18474/0749-8004-37.2.182.

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Four bioassays for use in detecting and measuring insecticide resistance in newly-emerged, unfed adult cat fleas, Ctenocephalides felis (Bouché), were evaluated: horizontal glass, horizontal Nylon 6,6 fabric disk, horizontal cellulose filter paper disk, and vertical cellulose filter paper strip (WHO bioassay). Each bioassay was evaluated using five insecticides: carbaryl, chlorpyrifos, malathion, permethrin, and pyrethrum. LC50s, LC90s, probit line slopes, and slope standard errors were compared. The LC50s on glass were lower than those obtained with the other substrates. This difference was a

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Pasupuleti, Murali Krishna. "Supersymmetric Quantum Neural Networks: Bridging Superalgebras and AI Architectures." International Journal of Academic and Industrial Research Innovations(IJAIRI) 05, no. 04 (2025): 48–59. https://doi.org/10.62311/nesx/rp0425.

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Abstract: This paper proposes a novel paradigm for quantum artificial intelligence: the design and implementation of Supersymmetric Quantum Neural Networks (S-QNNs) that explicitly integrate superalgebraic structures into quantum circuit-based AI architectures. By embedding the symmetry principles of supersymmetry—captured by quantum superalgebras such as osp(1∣2) and sl(1∣1)—into the computational fabric of quantum neural networks, we aim to create models that exhibit both structural elegance and computational efficiency. The resulting framework allows for interpretable, energy-efficient, and

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