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1732 articles for “Predicting”
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Improving Polymer Composite Properties Through Reinforcement Learning Guided Prototyping A Novel Approach for Material Engineering
Abstract: Innovative approaches integrating reinforcement learning (RL) and machine learning (ML) into the fields of polymer composite prototyping and soft actuator manufacturing for applications. This new an algorithm utilizing RL optimizes polymer composite fabrication parameters to enhance material properties efficiently. By iteratively adjusting parameters based on predefined objectives, the RL agent guides the prototyping process, promising to revolutionize polymer composite engineering. A finest control method for locked loop control of Shape …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 208–218 Read article
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A Study to Find the Relation Between School Bag Weight and Musculoskeletal Discomfort in School Going Children
Abstract: Background: School bags are one of the several forms of manual load carriage used by school children. Carrying school bags that exceed 10% of body weight can lead to heightened energy expenditure, causing increased forward lean of the neck and trunk, reduced lung capacity, and elevated cardio-respiratory measures. Musculoskeletal disorders (MSDs) are characterized by injuries or disorders affecting muscles, tendons, ligaments, cartilage, or spinal discs, as diagnosed by healthcare providers, …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 49–58 Read article
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Toxicological Optimization and Assessment of Buccal Films Containing Felodipine Co-crystals to Enhance Bioavailability
Abstract: The preformulation study of felodipine was carried out and it was found that the drug is poorly water soluble. The co-crystals were prepared using three different co-formers sorbitol, ascorbic acid and oxalic acid. The solublity enhancement was observed in combination with sorbitol compared to other co-formers used. The characterization of co crystals was performed like PXRD, FTIR, SEM Analysis. XRD results indicates the amorphous form of the drug. The co-crystals …
Published in Research and Reviews: A Journal of Toxicology · Vol. 14, Issue 2, 2024 · pp. 10–29 Read article
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Automated System for Attendance Tracking and Management Using Face Recognition
Abstract: A camera is used by an attendance tracking system that uses facial recognition to snap photos of people. After that, a computer program analyzes these images and uses facial feature analysis to identify specific individuals. Subsequently, the system can ascertain whether or not the identified individuals are present, by comparing the identified individuals to a database that already has information about known individuals. This technology can be used to expedite …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 1–12 Read article
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Developing an AI-Based Novel Forecasting Framework for Surface Irregularity in Metal Matrix Materials
Abstract: Surface irregularity in metal matrix materials (MMM) signifies the deviations from smoothness, influencing structural integrity and performance frequently arising from the manufacturing process along with intrinsic material characteristics that influence effectiveness. Limitations in data, model interpretability and complexity are the difficulties that impede artificial intelligence (AI) based surface irregularity in MMM. In this study, we suggested a novel framework of Gaussian regression fused multi-strategy adaptive boosting classifier (GR-MABC) for the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 48–56 Read article
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Review and Opportunities for Thermal examination approaches Used to Investigate the Thermal Properties of Composite Compounds
Abstract: The use of thermal examination approach to assess the thermal quality of energy materials in “China” is concisely described. They are often used to calculate thermal stability, compatibility, and thermophysical constants, as well as to study thermal breakdown kinetics, causes, and interactions. Furthermore, a few studies focused on creativity or advancement, such as analyzing the mechanisms of topochemical reactions, assessing condensed-phase reaction kinetics by tracking the change in functional groups …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 96–106 Read article
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Dynamic Cost Projection: Enhancing BIM-Integrated Estimation and Budgeting in Construction Projects
Abstract: In the realm of construction project management, the integration of Building Information Modeling (BIM) with dynamic cost projection tools represents a pivotal advancement. This paper explores the synergy between BIM and cost estimation, emphasizing their collective potential to revolutionize project budgeting. By harnessing real-time data and predictive analytics, BIM facilitates accurate and proactive cost projections throughout the project lifecycle. This integration not only enhances cost estimation precision but also fosters …
Published in Journal of Construction Engineering, Technology & Management · Vol. 14, Issue 2, 2024 · pp. 1–10 Read article
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Optimizing Routing and Placement of VLSI Circuits with Differential Algorithms and Neural Networks
Abstract: The performance of modern VLSI systems is heavily influenced by power constraints, necessitating precise power estimation and effective optimization techniques. Traditional methods, such as gate-level simulations, are often slow and computationally intensive. This paper introduces DRPENN (Differential Algorithm for Routing and Placement Optimization using Neural Networks), an innovative solution that combines a Switching Activity Estimator (SAE) with a neural network-assisted differential algorithm. By leveraging toggle rates from simulations to train …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 2, 2024 · pp. 14–20 Read article
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Implementation of Human Gesture Recognition Using CNN
Abstract: A gesture popularity system based entirely on convolutional neural networks (CNNs). Preprocessing techniques include segmentation, polygonal approximation, contour construction, morphological filters, and resource characteristic extraction. Various convolutional neural networks are employed for training and testing, with results compared to existing architectures and protocols. All generated measurements and convergence graphs produced at any point during education are examined and contested in order to verify the reliability of the approach offered. Our …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 2, 2024 · pp. 24–37 Read article
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Integrating Network Pharmacology and Molecular Docking to Investigate Boerhavia diffusa for Pancreatic Cancer Treatment
Abstract: Objective: In this study, network pharmacology was applied to determine the therapeutic effects of the bioactive compounds of Boerhavia diffusa. Network pharmacology can unearth the underlying mechanisms between drugs and the disease targets and aids in the discovery of novel medications for complex conditions such as cancer. Methods: To predict the molecular mechanisms of action of Boerhavia diffusa in the treatment of was screened using the GeneCards database. The Venn …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 1, 2024 · pp. 29–49 Read article
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Interaction of Bioactive Component of Aframomum melegueta on Molecular Docking
Abstract: Computational mimicry of the structure of large complexes created by di- and poly-interaction of molecules has been termed molecular docking. The purpose of molecular docking is the prediction of the three-dimensional structures of interest, this is due to that docking only produces plausible candidate structures. The docking was carried out between the bioactive compounds against 5α-reductase, 3β-hydroxy-steroid dehydrogenase, and 17β-hydroxy-steroid dehydrogenase of returned binding energy, BE (kcal/mol) between -5.9 and …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 2, Issue 1, 2024 · pp. 51–60 Read article
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Retinal Disease Detection Using Deep CNN
Abstract: Age-related macular degeneration, glaucoma, and diabetic retinopathy are the three main causes of blindness in the globe. To avoid visual loss, early identification and treatment of these disorders are essential. The goal of this research is to create an automated method for detecting retinal diseases by analyzing retinal fundus pictures with machine learning techniques. Python and the Tkinter package for the graphical user interface are used in the construction of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 46–50 Read article
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Avian Echoes: Convolutional Neural Network for Bird Vocalization Detection
Abstract: Bird species identification is a complex task within ornithology that demands advanced technological solutions. This research presents an approach leveraging Convolutional Neural Networks (CNNs) for bird species recognition based on identification of bird sound, each employing unique datasets and methodologies. The objective involves a two-stage identification process, beginning with the construction of an ideal dataset. The crucial step involves converting 1D audio waveforms to 2D spectrograms, enhancing CNNs' ability to …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 26–37 Read article
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The AI Revolution: Transforming Business Decision-Making
Abstract: Industries undergo a transformation thanks to artificial intelligence, which makes machines capable of activities that previously required human intelligence. This interdisciplinary field of computer science models human thought processes, impacting sectors from autonomous vehicles to creative AI tools. Integrating AI into business operations transforms decision-making and enhances corporate performance. AI-driven methodologies analyze vast datasets to provide valuable insights and facilitate decisions beyond human capability. Predictive modeling anticipates consumer behavior, market …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 25–32 Read article
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Metabolites in Modern Medicine: Decoding the Future of Health and Diseases
Abstract: The end products of many metabolic processes in cells are called metabolites. Each reaction contributes a specific metabolite. Metabolites act as fingerprints of on-going biological processes. Constant changes in cellular composition due to both environmental and internal factors. By analysing the types and presence of metabolites, scientists can effectively reconstruct the inner workings of a cell or organism. In the past, analysing metabolites was a slow and tedious process, often …
Published in Emerging Trends in Metabolites · Vol. 1, Issue 2, 2024 · pp. 1–13 Read article
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Assessment of Milk Quality Optimization of Yogurt Fermentation
Abstract: In the creation of new products, yogurt makers need to prioritize consumer preferences to enhance their market share. An advanced prediction method will help in grasping the fundamental connection between consumer preferences and sensory attributes. This study introduces a new deep learning approach that employs an autoencoder to derive product features from expert-scored sensory attributes. These sensory features are then analyzed through support vector machine regression to align them with …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 13, Issue 2, 2024 · pp. 6–12 Read article
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AI-Powered Approaches to Environmental Challenges: Trends, Benefits, and Limitations
Abstract: Dynamic and unpredictable characteristics of environmental processes create challenges in their management and regulation. Artificial intelligence (AI) offers a powerful solution for addressing these complexities.AI tools have become more and more popular across a range of fields and research domains due to their efficient development and rapid growth. We analyse key trends in AI applications, including predictive analytics for climate modelling, automated monitoring of biodiversity, and smart resource management. The …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Early Autism Diagnosis: Machine Learning Models and Their Effectiveness
Abstract: Diagnosis is of utmost importance for timely intervention and support. However, traditional diagnosis methods, which are based on subjective assessment, are delayed. This project explores the role that machine learning techniques might play in enhancing the accuracy and effectiveness of ASD detection. Several state-of-the-art classification algorithms were benchmarked using a dataset from Kaggle. Logistic Regression, XG Boost, Random Forest, Decision Tree, and Gradient Boosting were taken into consideration. Other performance …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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Optimization of Automatic Energy Management System Using Renewable Resources
Abstract: With the increasing demand for energy efficiency and sustainability, smart home energy management systems (SHEMS) have emerged as promising solutions to optimize residential energy consumption. This paper presents a comprehensive review of SHEMS technologies, focusing on their design, implementation, and impact. SHEMS integrates advanced sensors, real-time data analytics, and intelligent algorithms to monitor, control, and optimize energy usage within the home environment. By leveraging machine learning and predictive modelling techniques, …
Published in Journal of Thermal Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article