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276 articles for “Accuracy”
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Design of Multispindle Drilling Head
Abstract: AbstractThis paper presents the design, analysis, and optimization of a multi-spindle drilling machine headaimed at enhancing productivity and efficiency in manufacturing processes. Engineered to drill multipleholes simultaneously, the multi-spindle head significantly reduces machining time and increasesoperational throughput, making it ideal for high-volume production environments where speed andaccuracy are essential. The design process begins with a thorough requirements analysis and materialselection to ensure the machine head can endure operational stresses while …
Published in International Journal of Manufacturing and Materials Processing · Vol. 10, Issue 2, 2024 · pp. 36–42 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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Construction Project Monitoring Using Computer Vision Technology – A Literature Review
Abstract: The construction industry is witnessing a transformative shift with the adoption of computer vision (CV) technologies for productivity monitoring and performance evaluation. This review consolidates the advancements in CV applications, focusing on areas, such as real-time progress tracking, resource management, and safety monitoring. The analysis highlights how automated systems, powered by deep learning models and object detection algorithms, are replacing traditional manual methods, offering enhanced accuracy, efficiency, and decision-making capabilities. …
Published in International Journal of Architecture and Infrastructure Planning · Vol. 11, Issue 1, 2025 · pp. 1–9 Read article
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Predictive Models for Drinking Water Quality: Leveraging Machine Learning for Improved Safety and Efficiency
Abstract: Quality of drinking water is one of the critical determinants of public health, leading to severe environmental and health-related issues when poor. The paper examines the integration of machine learning techniques that could improve accuracy and efficiency in assessing drinking water quality. The traditional techniques of monitoring drinking water are resource-intensive yet lack timely insight into contamination events. In this scenario, an evaluation of the performance of ML models such …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 11, Issue 1, 2025 Read article
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A Comprehensive Review of ARDS: From Pathogenesis to Innovative Treatment Modalities
Abstract: Acute Respiratory Distress Syndrome (ARDS) is a serious medical condition marked by significant low oxygen levels in the blood, bilateral lung infiltrates, and extensive lung inflammation. It is often caused by a range of direct or indirect injuries to the lungs. Despite considerable advances in understanding the pathophysiology of ARDS, its complex and multifactorial nature continues to challenge clinicians in both diagnosis and management. This review provides a comprehensive analysis …
Published in International Journal of Nursing Critical Care · Vol. 11, Issue 1, 2025 Read article
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Development of Nanocomposites for Sensor Applications
Abstract: The development of nanocomposites for sensor applications represents a significant breakthrough in materials science and engineering, driven by the unique properties of nanomaterials. Nanocomposites, which combine nanoparticles with polymers or other matrices, exhibit enhanced mechanical, electrical, and thermal properties, making them highly suitable for various sensing applications. The integration of nanoparticles, such as metal oxide, carbon nanotubes, and graphene, into a composite framework can dramatically increase sensitivity and selectivity, enabling …
Published in International Journal of Applied Nanotechnology · Vol. 11, Issue 1, 2025 · pp. 18–37 Read article
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A Review of AI and Machine Learning Techniques in Dew Point Pressure Prediction for Gas Condensate Systems
Abstract: Condensate gas reservoirs pose considerable management challenges due to their intricate phase behavior and the critical need for accurate predictions of dew point pressure (PDew). A precise determination of PDew is vital for optimizing production strategies, estimating reserves, and planning enhanced oil recovery operations. Traditional methods for PDew determination often involve experimental analyses that can be both costly and time-consuming, highlighting the necessity for alternative predictive models. This review consolidates …
Published in International Journal of Chemical Engineering and Processing · Vol. 11, Issue 1, 2025 Read article
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Software Contributions to Analytical Instruments
Abstract: Laboratory instruments used in the analysis of the sample or preparation of raw materials are crucial in research and business. Such features as accurately measured values and data coverage. The coordination between software and these instruments has changed their roles, gaining flexibility, accuracy and efficiency of work. This paper aims to outline the various roles of software in the analytical process. Instruments, describing the progress in data obtaining, analysis, and …
Published in International Journal of Analytical and Applied Chemistry · Vol. 11, Issue 1, 2025 · pp. 1–15 Read article
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Advanced Diabetic Retinopathy Detection Using Deep Learning Classifiers
Abstract: Diabetic Retinopathy (DR) is an eye condition that arises from diabetes-related complications, making early detection essential for effective treatment. As diabetes advances, an individual’s vision may deteriorate, potentially resulting in diabetic retinopathy. This condition is divided into two primary types: Non-Proliferative Diabetic Retinopathy (NPDR) and Proliferative Diabetic Retinopathy (PDR). Early treatment to maintain a strategic distance from a change less visual impedance is basic as it may save diabetic retinopathy …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 26–33 Read article
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Facial Emotion-Based Stress Detection Using CNN and Haar Cascade Algorithms
Abstract: Understanding human conduct requires the ability to recognize facial emotions, which has applications in everything from human–computer interaction to psychological wellness monitoring. This research provides a new approach to stress detection using convolutional neural networks and Haar Cascade classifiers. The suggested method uses convolutional neural network to recognize facial expressions and Haar Cascade algorithm for face detection. The methodology begins with preliminary processing of the input photos, followed by face …
Published in International Journal of Microwave Engineering and Technology · Vol. 10, Issue 2, 2024 · pp. 1–11 Read article
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Geotechnical and Geological Engineering: Interdisciplinary Approaches to Sustainable Infrastructure
Abstract: AbstractGeotechnical and geological engineering are foundational disciplines that play a critical role in thedesign, construction, and sustainability of civil infrastructure, as well as in hazard mitigation andeffective resource management. This paper delves into the intersection of geotechnical and geologicalengineering, underscoring the essential role of comprehensive site investigations, the study of soil androck mechanics, foundation design principles, and slope stability analysis. The paper highlights theimportance of these elements in ensuring the …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 10, Issue 2, 2024 · pp. 1–9 Read article
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Performance Evaluation of Geopolymer Masonry Units Using Fly Ash and GGBFS: Dimensionality, Density, Water Absorption, and Compressive Strength Analysis
Abstract: AbstractThis study investigates the production, properties, and performance of geopolymer masonry units,utilizing Class F fly ash and Ground Granulated Blast Furnace Slag (GGBFS) as primary binders.These binders were activated using an 8M alkaline solution, with the materials mixed alongsidemanufactured sand (M-sand) as the fine aggregate. The binder-to-aggregate ratio was maintained at1:1, while the alkaline solution-to-binder ratio was kept at 0.2. Various geopolymer masonry units,including geopolymer bricks (GPB), solid blocks (GPSB), …
Published in International Journal of Construction Engineering and Planning · Vol. 10, Issue 2, 2024 · pp. 26–32 Read article
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Quantification of Morphine, Codeine, and Dihydrocodeine in Carissa carandas Leaves and Fruit Using LC-MS/MS: The Impact of Drying on Alkaloid Concentration
Abstract: This study presents a method for quantifying morphine, codeine, and dihydrocodeine in Carissa carandas (Karonda) leaves and fruit, employing morphine-D3 as an internal standard (1 µg/mL) to ensure accuracy. Samples are prepared at 25 ng/mL and extracted using solvent techniques, with an optional solid-phase extraction step to mitigate matrix effects. Quantification is conducted via LC-MS/MS, providing robust sensitivity. Results show that drying concentrates these alkaloids, particularly morphine in fruit, due …
Published in International Journal of Environmental Chemistry · Vol. 11, Issue 1, 2025 · pp. 49–61 Read article
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Velocity and Concentration Distribution of Turbidity Currents
Abstract: AbstractThis study conducts a comprehensive analysis of the velocity and concentration characteristics withinturbidity currents, focusing on detailed evaluations of the hydrodynamic and sediment transportproperties. The investigation includes separate calculations for the velocity and concentrationdistributions within the near-boundary and jet regions, allowing for an in-depth comparison betweenthese distinct flow areas. By computing dimensionless profiles of both velocity and concentration, thestudy offers a visual representation of flow behaviors and sediment patterns, which …
Published in International Journal of Water Resources Engineering · Vol. 10, Issue 2, 2024 · pp. 15–22 Read article
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Effect of Segmentation of White matter, grey matter and CSF in the prediction of Neurological disorders
Abstract: The segmentation of white matter, grey matter, and cerebrospinal fluid (CSF) plays a crucial role in predicting and diagnosing neuro disorders. This study investigates the impact of precise segmentation techniques on identifying biomarkers and structural changes associated with various neurological conditions, including Alzheimer's disease, multiple sclerosis, and schizophrenia. By leveraging advanced imaging technologies and machine learning algorithms, we aim to enhance the accuracy of neuro disorder predictions through detailed analysis …
Published in International Journal of Neurological Nursing · Vol. 10, Issue 2, 2024 · pp. 9–14 Read article
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Facial Emotion Based Stress Detection Using CNN and Haar Cascade Algorithms
Abstract: Understanding human conduct requires the ability to recognize facial emotions, which has applications in everything from human-computer interaction to psychological wellness monitoring. This research provides a new approach to stress detection using Convolutional Neural Networks (or CNNs) and Haar Cascade classifiers. The suggested method uses CNN to recognize facial expressions and Haar Cascade algorithm for face detection. The methodology begins with preliminary processing the input photos, followed by face detection …
Published in International Journal of Microwave Engineering and Technology · Vol. 10, Issue 2, 2024 · pp. 41–50 Read article
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IoT Based Smart RFID Application in Healthcare
Abstract: The Internet of Things has become a promising technology in recent years that expands the idea of the internet and makes it more widespread, enabling smooth communication between all kinds of devices. To connect “Everything” and make it smarter, the Internet of Things plays several roles, including identification, information gathering, exchange and processing, decision-making, and security. Two important technologies that facilitate intelligent decision-making across a range of applications are cloud …
Published in International Journal of Microwave Engineering and Technology · Vol. 10, Issue 2, 2024 · pp. 24–29 Read article
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Machine Learning Approaches for Customer Churn Prediction in Telecommunications
Abstract: Customer churn prediction is a critical challenge for companies in the telecommunications industry. The competition is intense, and acquiring new customers can be costly. Predicting when existing customers might leave (churn) helps companies take proactive measures to retain them, reducing churn rates and costs. By analyzing historical customer data, including demographics, service usage, billing, and customer service interactions, this study aims to identify customers at risk of leaving their current …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–7 Read article
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Hybrid Cryptographic Framework for Cloud Data Security: Integration of AES-OTP, RSA, and Temporal Access Control Mechanisms
Abstract: This generation of cloud computing has characterized the Internet of Things with exponentially increasing data generation, processing, and storage. Regrettably, however, accompanying this trend of growth is the increased concern for cloud-based systems about security, privacy, and control of access to data. The proposed work introduces a hybrid cryptographic framework that combines AES, OTP, and RSA encryption methods with temporal mechanisms to enhance the security of data in the cloud. …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–6 Read article
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Optimized Fault Current Prediction for DFIG-Based Wind Turbines Using Type-I Fuzzy Logic Controller
Abstract: The increasing integration of Doubly-Fed Induction Generator (DFIG)-based wind turbines into modern power grids requires robust fault detection and prediction mechanisms to ensure stable and reliable operation. However, accurately predicting fault currents in such systems is challenging due to the nonlinear dynamics involved. This study presents an optimized fault current prediction framework using a Type-I Fuzzy Logic Controller (FLC) to address these challenges. The proposed approach effectively models the uncertainties …
Published in International Journal of Analog Integrated Circuits · Vol. 10, Issue 2, 2024 · pp. 41–50 Read article