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1983 articles for “failure-prediction AUROC of 0.967” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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A IoT-Enabled Predictive Intelligence for Real-Time Failure and Damage Evolution Monitoring of Polymer Composites
Abstract: Damage assessment of carbon-fibre-reinforced polymer composites is still challenging since the damage occurs as a combination of matrix cracking, interfacial debonding, delamination and fibre fracture. The present work proposes a framework for predictive-intelligence based on IoT for multiaxial fatigue and compression-after-impact (CAI) CFRP experiments, employing publicly available acoustic-emission (AE) datasets. A causal CNN–GRU attention model is developed by integrating time-domain, spectral, wavelet, loading-history and trend features to estimate the damage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Experimental Testing and Ply Wise Strength 0°-45°-0° Investigation of Multi-orientation Carbon Fiber Specimen by Using FEA and UTM
Abstract: Synthetic composites have higher strength to weight ratio and are extensively used in industrialapplications. Carbon fibers have extensively high tensile strength. Most of the composites haveorthotropic properties and their strength varies as per orientation. Laminar having differentply orientations have different properties and strengths. Hence, to enhance strength of carbonfiber specimen reducing layer wise damage becomes up most important. It is unimaginable toexpect to examine the layer insightful harm of each …
Published in Journal of Nuclear Engineering & Technology · Vol. 10, Issue 3, 2020 · pp. 29–37 Read article
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Comparison of Several Clinical Scoring Systems in Predicting the Outcome of Variceal Bleeding
Abstract: Background: Stratification of variceal bleeding patients into high-risk and low-risk group is very important to guide them through the suitable clinical pathway and to save the medical costs. We purposed to find out the best scoring system in the prediction of rebleeding and death after variceal bleeding by comparing four clinical scoring systems(clinical Rockall score, complete Rockall score, AIMS65 score, Child-Pugh score) which seemed to be applicable and simple. Method: …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 2, 2025 Read article
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Substitution of La3+ in Cu0.5Co0.5 LaxFe2-x O4 (x=0.02, 0.06) spinel ferrites improves the structural and dielectric Properties
Abstract: Nanosized Spinel ferrites with composition Cu0.5Co0.5 LaxFe2-x O4 (x=0.2, 0.6) synthesized by Sol-Gel auto Combustion method. The prepared sample was calcinated at 8000c for 4 hours. The substitution of La3+ effects the structural parameters, which is characterized by X-ray diffraction (XRD). The X-rd analysis shows that the crystallite size is 34.609 nm for 0.02 and 38.994 nm for 0.06 was calculated by using Debye-Scherrer’s formula. dislocation density shows at value …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 3, 2025 · pp. 45–48 Read article
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Survey of Predictive Models for Safe Route Predicting Using Machine Learning Techniques
Abstract: Safe route prediction is essential for the well-being and security of individuals in urban and rural environments. Machine learning techniques leverage historical data, real-time information, and algorithms to estimate the safety levels of different routes. The objective of safe route planning is to minimize risks, including crime-prone areas and accidents, reducing potential harm, property damage, and emotional distress. However, challenges arise from the complex and dynamic nature of urban environments, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 1, 2024 · pp. 13–22 Read article
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PREDICTIVE MAINTENANCE IN SEMICONDUCTOR SYSTEMS: INSIGHTS FROM MACHINE INTELLIGENCE AND DATA-DRIVEN METHODS
Abstract: With the fast-paced development of semiconductor technology comes the need to focus on device reliability, or how long devices will function and the likelihood of devices having operational issues. Predicting failures and avoiding downtime with the implementation of timely, actionable, and data-driven maintenance strategies are essential to insure devices function sustainably within predetermined performance levels. The implementation of predictive maintenance within artificial intelligence and machine learning technologies will provide the …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 1, 2026 · pp. 1–9 Read article
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Predicting and Prohibiting the Risk of Heart Failure Using Machine Learning
Abstract: It is challenging to estimate the likelihood of complex chronic disease while treating conditions like heart failure. The application of machine learning, an area of artificial intelligence, in cardiovascular care is growing quickly. In essence, it defines how computers classify and understand data, or choose a task with or without human intervention. The theoretical underpinnings of machine learning are models that accept input data (such as images or text) and …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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Decompensated Liver Failure and Acute Renal Failure in a Patient with Chronic HBV,HCV, and HIV Infections
Abstract: This case study focuses on a 30-year-old male patient suffering from decompensated liver failure and acute renal failure, complicated by chronic hepatitis B (HBV), hepatitis C (HCV), and HIV/AIDS. Presenting with severe abdominal pain, nausea, and general weakness, the patient had a history of alcohol and intravenous drug use, leading to chronic liver disease and acute renal failure. Despite aggressive interventions, including intravenous antibiotics and fluid therapy, his condition worsened …
Published in International Journal of Pathogens · Vol. 2, Issue 1, 2025 · pp. 17–23 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Predictive Model to Monitor the Exponential Transport of Spirochaeta Influenced by oxygen deficit And dispersion on natural pond
Abstract: Predictive model were considered to monitor the deposition of Spirochaeta in natural pond, the study considered the system to monitor the accumulation or exponential growth rate influenced by predominant parameters in the study environment, the effect from oxygen deficit observed characteristic of Dissolved Oxygen Levels. This includes Dissolved oxygen concentrations that are constantly influenced by diffusion and aeration, including photosynthesis, respiration and decomposition. This also includes water equilibrates toward hundred …
Published in Recent Trends in Fluid Mechanics · Vol. 8, Issue 1, 2021 · pp. 22–33 Read article
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Multi-way Protection Scheme to Handle Multiple Failures for Cost-Efficient Fiber-Wireless (FiWi) Access Networks
Abstract: AbstractFiber Wireless (FiWi) access networks prove themselves as promising broadband access networks. These networks enable users to access services in “Anywhere-Anytime” fashion. FiWi networks offer higher bandwidth and better flexibility at much lower price than passive optical network. As FiWi supports high data rate (typically about Gigabits per second), any failure may results in huge data loss. Therefore, to protect such loss of data, we need to design a more …
Published in Trends in Opto-electro & Optical Communication · Vol. 5, Issue 3, 2015 · pp. 1–15 Read article
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Integrating Sensor Technologies and Machine Learning for Detection and Mitigation of Structural Deformity and Slope Failure in Opencast Mines
Abstract: With furtherance in the mining industry, accidents due to slope failure are frequent in mining sites. Slope instability, a complex process, seriously threatens the miner’s life and properties. The damage inflicted by slope failures in the recent past has pulled the attention of authorities toward implementing disaster risk reduction measures. This research aims to develop an innovative approach that combines sensor technologies and machine learning techniques to detect and mitigate …
Published in Journal of Communication Engineering & Systems · Vol. 13, Issue 3, 2023 · pp. 38–45 Read article
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AI-Based House Price Prediction
Abstract: The housing market is one of the most dynamic and significant sectors of any economy, influencing both individual wealth and broader economic stability. Buyers, sellers, investors, and policymakers all rely on accurate housing price predictions. With the advent of artificial intelligence (AI) technologies, particularly machine learning algorithms, the task of house price prediction has seen remarkable advancements. This study provides a detailed overview of AI-based techniques for house price prediction. …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 1–7 Read article
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Prevention from Heat Exchanger Failure Analysis
Abstract: Abstract- Heat exchanger is the gear which is used to limit temperature of one technique fluid, which is preferred to cool, by using transferring heat to some other fluid which is favored to heat with or barring inter-mixing the fluid or altering the physical state of the fluid. There are a number of reasons by using which Heat exchanger can also fail. As they are used at huge vary of …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 6, Issue 3, 2019 · pp. 35–43 Read article
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A Factorial Investigation of Hyperparameter Tuning Strategies for Lasso- Based Genomic Prediction
Abstract: In an earlier comparative study of machine-learning methods for genomic prediction of wheat grain yield, we reported a counter-intuitive result: automated nested-cross-validation tuning of the Lasso regularization penalty reduced mean predictive ability relative to a fixed, arbitrarily chosen penalty (mean Pearson r falling from 0.408 to 0.349 across four environments), the opposite of the expected effect of hyperparameter tuning. We hypothesized two possible explanations at the time — high-variance penalty …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 42–51 Read article
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Implementation of Sense Amplifier-based D Flip-Flop using 0.25 µm and 0.18 µm Technology
Abstract: The traditional flip-flops and latches suffer from the large delays and the race conditions. This paper describes a new approach to the D flip-flop design using the sense amplifier. The previous efforts in the same direction made at the 0.25 µm technology exhibit improvements in clock-to-output delay and power dissipation with respect to recently proposed high-speed flip-flops. The paper discusses the flip-flop at 0.18 µm technology. The output latch of …
Published in Journal of Electronic Design Technology · Vol. 4, Issue 3, 2013 · pp. 10–13 Read article
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Predictive value of Systemic Inflammatory Response Syndrome score in assessing the clinical outcomes in patients with acute pancreatitis
Abstract: Background: The role of various clinical scoring systems to assess the severity and outcomes of acute pancreatitis is attracting a lot of attention to the experts. Purpose: We aimed to objectively reconfirm the predictive value of systemic inflammatory response syndrome (SIRS) score for predicting the various clinical outcomes of acute pancreatitis and also to evaluate the significance of monitoring SIRS score on day 1 and its duration. Methods: We retrospectively …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 11, Issue 1, 2022 · pp. 34–42 Read article
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Possible Risk Factors Associated with Tuberculosis Treatment Failure Among Patients Attending Tuberculosis Treatment Centers in Kano State, Nigeria
Abstract: The widespread failure of tuberculosis chemotherapy has led to an increase in mortality and morbidity associated with tuberculosis infection. This study was aimed at assessing the possible risk factors associated with tuberculosis treatment failure in patients attending Aminu Kano Teaching Hospital (AKTH) and Infectious Disease Hospital (IDH), Kano State. Treatment outcomes of the 436 tuberculosis patients attending selected hospitals in 2018 were obtained using a retrospective study (review of the …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 13, Issue 2, 2023 · pp. 1–9 Read article
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Pharmacophore mapping, 3D QSAR, docking, and ADME prediction studies of novel Benzothiazinone derivatives
Abstract: Background Tuberculosis is a major public health concern worldwide which is caused by Mycobacterium tuberculosis. DprE1 (Decaprenyl Phosphoryl Ribose 2’- Epimerase) is the most challenging target for development of novel anti- tubercular agents because it is a small protein and located into cytoplasmic membrane. So, novel anti-TB drugs did not bound effectively with it. DprE1 catalyzes the oxidation of the 2’ hydroxyl group of DPR (Decaprenyl Phosphoryl D- Ribose) …
Published in International Journal of Antibiotics · Vol. 1, Issue 1, 2024 · pp. 59–82 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article