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55 articles for “machine learning (ML)”
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Cloud Security Using Machine Learning: A Study
Abstract: The rapid adoption of cloud computing has revolutionized IT infrastructure, offering unprecedented scalability, flexibility, and cost efficiency. However, this paradigm shift introduces a new spectrum of sophisticated security challenges that traditional, signature-based security mechanisms often struggle to address effectively given the dynamic, multi-tenant, and distributed nature of cloud environments. This paper explores the critical role of Machine Learning (ML) as a potent paradigm for strengthening cloud infrastructure. ML emerges as …
Published in International Journal of Distributed Computing and Technology · Vol. 11, Issue 2, 2025 · pp. 21–30 Read article
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Artificial Intelligence in Cyber Security
Abstract: Security isn't working. While security as a level of IT spend keeps on developing at a powerful rate, the expense of security breaks is becoming significantly quicker. Associations are spending near $100 billion on a bewildering cluster of security items. Truth be told, it isn't exceptional for CISO associations to have 30 to 40 security items in their condition. Be that as it may, in the event that you ask …
Published in International Journal of Software Computing and Testing · Vol. 5, Issue 1, 2019 · pp. 9–14 Read article
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A Study of 3D Printing Technology and M.L. Algorithms for Enhanced Production
Abstract: Abstract The realm of 3D printing technology, also referred to as additive manufacturing, has garnered increasing interest in recent times due to its capacity to construct intricate geometric structures. Fused deposition modeling (FDM) stands out among the various techniques and has gained widespread adoption. However, achieving optimal outcomes with FDM poses a challenge, necessitating meticulous selection of process parameters. Presently, many methodologies rely on Machine Learning (ML) algorithms akin to …
Published in International Journal of Computer Aided Manufacturing · Vol. 11, Issue 1, 2025 · pp. 6–15 Read article
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A Study on Machine-Learning-Driven Insight into theThermal Behavior of Polymers and Composite Materials
Abstract: The thermal performance of polymeric and composite systems underpins their suitability for aerospace, electronics, and energy‑storage applications, yet reliable prediction of temperature‑dependent properties remains a formidable challenge. In this work we present a data‑driven framework that harnesses modern machine‑learning (ML) techniques to forecast key thermal metrics – glass‑transition temperature (Tg), melting point (Tm), thermal conductivity (k), and decomposition onset (Td) – from a chemically informed descriptor space. A curated database …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 1–11 Read article
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A Comprehensive Review of Smart Parking Systems: Technologies, Challenges, and Future Directions
Abstract: Abstract Smart Parking Systems (SPS) are gaining significant attention as a critical solution to address the growing concerns of urban congestion, inefficient use of parking spaces, and environmental sustainability. This paper presents a comprehensive review of SPS, focusing on the key technologies, challenges, and future directions. We explore the integration of advanced technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and sensor networks in …
Published in International Journal of Manufacturing and Materials Processing · Vol. 11, Issue 1, 2025 · pp. 1–13 Read article
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An Overview on AI in Thermal Behaviour of Polymers
Abstract: The integration of Artificial Intelligence (AI) and Machine Learning (ML) into the thermalanalysis of polymers and composite materials has transitioned from experimental curiosity to acornerstone of material science. By replacing costly and time-consuming trial-and-errorlaboratory testing with predictive modeling, AI is accelerating the development of advancedthermal interface materials, fire-retardant polymers, and aerospace-grade composites. Theprediction and optimization of the thermal behavior of polymers and composite materialsrepresent a cornerstone of modern materials science, …
Published in International Journal of Composite and Constituent Materials · Vol. 12, Issue 1, 2026 · pp. 12–16 Read article
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Deep Learning Techniques for Optimizing Resource Allocation and Sustainability in the Next Generation of 6G Wireless Networks
Abstract: The upcoming sixth generation (6G) of wireless communication networks aims to meet challenging requirements such as ultra-reliable low-latency services, massive connectivity for billions of smart devices, and intelligent automation across highly diverse environments. Along with these goals, the issues of energy efficiency and environmental sustainability are becoming equally important, as the rising number of users and traffic volumes will directly increase power demand and carbon emissions. To lower total energy …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 Read article
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An Integrated Machine Learning and IoT-Based Framework for Predictive Urban Water Demand Management and Distribution Optimization
Abstract: Abstract Urban water resource management has become increasingly complex due to rapid urbanization, population growth, climate variability, and aging infrastructure. Conventional water management approaches are often reactive, inefficient, and incapable of handling real-time fluctuations in demand and supply. This study proposes an integrated framework that combines machine learning (ML) techniques with Internet of Things (IoT)-based real-time monitoring to enhance water demand prediction and optimize distribution systems in urban environments. The …
Published in International Journal of Water Resources Engineering · Vol. 12, Issue 1, 2026 Read article
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Predicting Traffic Congestion in Mumbai Using Artificial Intelligence
Abstract: Abstract — Mumbai's ongoing traffic problems are brought on by the city's fast urbanization, population expansion, and growing reliance on private automobiles. The majority of traffic management technologies in use today are reactive, frequently reacting only after congestion has already arisen. Using information from a variety of sources, such as commuter surveys, weather reports, and traffic incident logs, this study explores the application of artificial intelligence (AI) and machine learning …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 2, 2026 Read article
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Future-Ready Library Buildings: AI and IoT for Equity and Compliance
Abstract: Libraries are buildings presenting unique challenges when integrating different types of spaces under a single roof, like quiet reading spaces, central lobbies, book staging areas, archival rooms, discussion zones, seminar rooms, e-resources labs, etc. These spaces require specialized norms related to construction and involve varied daylighting requirements, anthropometric needs, indoor air environment requirements, and other specific functional needs. Moreover, libraries must follow various requirements mentioned in relevant IS codes, fire …
Published in International Journal of Sustainable Building Technology · Vol. 9, Issue 1, 2026 · pp. 19–24 Read article
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Data Science for Environmental Modelling
Abstract: Abstract: Soil moisture is a critical Earth system variable linking atmospheric, hydrological, and ecological processes. However, observations are sparse and fragmented: in situ gauges provide point data, satellite missions (SMAP, SMOS, Sentinel-1) offer broad coverage at coarse resolutionQ, and land‐surface models (GLDAS, ERA5, etc.) yield estimates with their own biase. Here we propose a conceptual framework for integrated environmental data modelling, combining rainfall, temperature, and soil moisture information with machine …
Published in International Journal of Water Resources Engineering · Vol. 12, Issue 1, 2026 · pp. 33–40 Read article
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Data Science for Environmental Modelling
Abstract: Abstract: Soil moisture is a critical Earth system variable linking atmospheric, hydrological, and ecological processes. However, observations are sparse and fragmented: in situ gauges provide point data, satellite missions (SMAP, SMOS, Sentinel-1) offer broad coverage at coarse resolutionQ, and land‐surface models (GLDAS, ERA5, etc.) yield estimates with their own biase. Here we propose a conceptual framework for integrated environmental data modelling, combining rainfall, temperature, and soil moisture information with machine …
Published in International Journal of Water Resources Engineering · Vol. 12, Issue 1, 2026 Read article
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A Review on Design and Analysis Model for Detectionand Classification of Lung Diseases Using Medical Images
Abstract: A key component of the human respiratory system, the lung regulates blood oxygen levels through gasexchange. Diseases linked to the lungs are becoming more common as pollution levels rise. In order topreserve human life, it is crucial to identify lung disorders early. In order to forecast lung disease, clinicalprofessionals analyze medical imaging, such as CT or X-rays. Clinicians identify lung disease by applyingtheir medical expertise and knowledge. Because expert knowledge …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 Read article
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Revolutionizing Design and Manufacturing: The Role ofComputer Languages in CAD and CAM
Abstract: The evolution of computer languages has played a crucial role in the advancement of modern computational technologies, with significant contributions to fields, such as Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM). Computer languages provide the essential tools to communicate between human users and machine systems, enabling the automation of design and manufacturing processes. This review explores the development and classification of computer languages, highlighting their impact on CAD and CAM …
Published in International Journal of Computer Aided Manufacturing · Vol. 11, Issue 1, 2025 · pp. 30–34 Read article
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Need of Modern Technologies in Agriculture
Abstract: The surge in population growth coupled with the diminishing availability of cultivable land has significantly heightened the strain on arable areas. While the provision of sustenance for the underprivileged remains a pressing issue, the focus has expanded beyond mere food provision to ensuring a nutritionally balanced diet. Consequently, there arises an urgent imperative to delve into contemporary methodologies aimed at not only feeding the burgeoning population but also preserving essential …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 1, 2024 · pp. 1–6 Read article
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Recognition and Detection of Content in Video Using OpenCV
Abstract: The emergence and continued reliance on the Internet and related technologies has resulted in massive amounts of data that can be analysed. Humans, on the other hand, do not have the cognitive abilities to comprehend such vast amounts of data. Machine learning (ML) is a mechanism that enables humans to process large amounts of data, gain insights into the data's behaviour, and make more informed decisions based on the analysis's …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 7, Issue 2, 2021 · pp. 42–47 Read article
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Crop Disease Classification and Detection Using Deep Learning Approach
Abstract: Early diagnosis of plant diseases is essential because they have an effect on the evolution of their unique species. For the identification and classification of plant diseases, a variety of Machine Learning (ML) models have been employed, but with the advent of Deep Learning (DL), a subset of ML, this area of research now seems to offer substantial potential for increased accuracy. The 4th most common staple food consumed worldwide …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 1, 2023 · pp. 22–27 Read article
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A Review Paper on The Smart Grocery Management System for Household Kitchen Using Raspberry PI
Abstract: The rise of the term Smart Homes in recent years is due to the possibility of applying Internet of Things (IOT) for the home automation. Brilliant basic food item framework is a sharp and better approach for shopping for food that help us and re-characterizes the demeanor towards shopping for food. For a larger than average scope of different heterogeneous end frameworks, the web of Things (IOT) and Machine Learning …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 6, Issue 2, 2020 · pp. 16–23 Read article
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Decision Trees in Intrusion Detection: A Comparative Analysis of Machine Learning Techniques
Abstract: Recent malware sophistication poses immense challenges in intrusion detection systems, making it imperative to develop highly sophisticated methodologies for detection of fast-evolving cyber threats. Traditional IDS typically employs a signature-based detection approach and has limitations in identifying unknown and obfuscated attacks, particularly zero-day vulnerabilities. This paper discusses the existing limitations of IDS based on ML techniques to further improve the detection capability of such systems. Machine learning algorithms, particularly decision …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
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Decision Trees in Intrusion Detection: A Comparative Analysis of Machine Learning Techniques
Abstract: Recent malware sophistication poses immense challenges in intrusion detection systems, making it imperative to develop highly sophisticated methodologies for detection of fast-evolving cyber threats. Traditional IDS typically employs a signature-based detection approach and has limitations in identifying unknown and obfuscated attacks, particularly zero-day vulnerabilities. This paper discusses the existing limitations of IDS based on ML techniques to further improve the detection capability of such systems. Machine learning algorithms, particularly decision …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article