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1976 articles for “bending-mode piezoresistivity” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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An Adaptive Approach for Real-Time Embedded System Design, Analysis and Optimization
Abstract: Real-time embedded systems are critical components in various domains, such as automotive, aerospace, healthcare, and industrial automation. The design, analysis, and optimization of these systems are vital to ensure their reliable and efficient operation. In this paper, we propose an adaptive approach for real-time embedded systems that aims to address the challenges faced during the development process while maintaining high-quality results. Our approach leverages adaptive techniques to dynamically adjust the …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article
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Artificial Intelligence in Cerebellum Activation
Abstract: Neuroscience plays a significant function during the progression of artificial intelligence. It provided inspiration for the development of human-like AI. There are two ways that neuroscience encourages us to develop AI systems. Neural networks that replicate human cognition and those that match the structure of the brain are the two objectives. Neural networks, which draw inspiration from the architecture of the human brain, are the engine behind contemporary artificial intelligence …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 14–26 Read article
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Mindwell: A Psychological Guide for Well-being
Abstract: Mental health is a crucial aspect of overall well-being, yet access to professional therapy remains a significant challenge for many individuals due to various barriers, including cost, availability, and stigma. This research aims to develop an accessible and effective mental health therapy chatbot, named Mindwell Psychology, leveraging the power of large language models (LLMs) and state-of-the-art natural language processing techniques. The primary objective of this study is to create a …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 63–77 Read article
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A Study of The Performance of surface modified NACA 2416 Airfoils at various Angles of Attach at Re80000
Abstract: In the present investigation the effect of compressive strength of core and precast concrete on the behavior of columns retrofitted by attaching precast segments and followed by FRP wrapping through Finite Element Analysis. A rectangular column converted into an elliptical column by attaching precast segment is modeled using ANSYS workbench, A Finite Element Analysis software. A Finite Element Model is developed, considering various structural parameters such as grades of core …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 302–310 Read article
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Identification of Papaya Fruit Ripening Process Using AI
Abstract: Identifying the ripening process of papaya fruit using artificial intelligence involves employing machine learning algorithms to analyze various features such as color changes, texture alterations and chemical compositions. This model is capable of analyzing visual cues to determine the stage of ripeness. The dataset compares images of papaya at various ripening stages, and our AI model demonstrated high accuracy in classifying these stages. Employing machine learning algorithms and image processing …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 2, 2024 · pp. 23–30 Read article
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Presence of a Bulk Viscous Universe within f(R, T) Gravity
Abstract: This paper offers a comprehensive analysis of a bulk viscous universe in the context of f(R, T) gravity, where (R) signifies the Ricci scalar and (T) represents the trace of the energy-momentum tensor. The primary objective of our work is to get explicit solutions to the modified field equations by using a power-law scale factor representation. With this method, we have obtained functions of cosmic time and redshift for the …
Published in International Journal of Universe · Vol. 1, Issue 1, 2025 Read article
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Theoretical Study of Surface Waves in Hexagonal Boron Nitride (hBN)
Abstract: Hexagonal boron nitride (hBN) is a wide bandgap semiconductor material in which Boron (B) and Nitrogen (N) atoms form hexagonal structure and has number of robust properties of technological importance. Boron nitride nanotubes (BNNTs) are very nice area of research in recent years. Its structure is similar to carbon nanotubes (CNTs) where carbon atoms are arranged in hexagon. hBN is also known as White Graphene. Various methods are employed to …
Published in Research & Reviews : Journal of Physics · Vol. 13, Issue 1, 2024 Read article
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Visual Recognition with Convolutional Neural Networks for Object Detection
Abstract: Various research and development have taken place over the years on computer vision which is a branch of AI. AI disciplines like a vision system is applied in various fields like self-driving cars, face detection by social media apps and law enforcement software’s google lens and so on. The proposed system deals with design and implementation of an efficient way of training a GPU using python libraries to process and …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 07–13 Read article
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Study of Rehydration and Dehydration behavior of Scolecite by insitu Raman spectroscopy
Abstract: The study of structural changes of stretching and bending modes around 3000-4000cm-1 and 700-1800cm-1 in the temperature range of 299 to 503 K during the dehydration of naturally occurring scolecite was investigated using in-situ Raman spectroscopy. A Raman spectrum from 3000-4000cm-1 was measured for a fibrous zeolite called scolecite to regulate the behavior of water molecules in the passages. The extending vibrations of H2O molecules of scolecite are located between …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 152–159 Read article
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Container transportation in marine terminals and marine transportation infrastructure on the increase in export market share
Abstract: In order to achieve important policy goals like increasing global competitiveness, diversifying import sources, opening up new markets, and forging strategic partnerships, maritime transportation is essential. It also has a significant impact on reducing the economic vulnerability of nations that rely on the sale of gas and oil by carefully choosing its clients and growing the export of petroleum products, petrochemicals, and gas. This study develops a two-objective mathematical planning …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 36–42 Read article
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Sentiment Analysis of E-Commerce Reviews using Machine Learning
Abstract: In e-commerce, sentiment pertains to the emotional responses, opinions, or perceptions that customers have about their online shopping experiences, including factors like product quality, service, and various processes such as ordering, shipping, and customer support. Sentiment analysis, which involves machine learning techniques, plays a crucial role in deciphering these sentiments. By using sentiment analysis, companies can obtain valuable insights from customer feedback from diverse online sources, including social media, surveys, …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 25–37 Read article
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A Comparative Analysis of Machine Learning Techniques for Fruit Defect Detection Systems
Abstract: With evolving technologies in machine learning, significant advancements have been made in the livestock industry, helping to reduce waste, increase yield, achieve cost savings, and improve competitiveness in the marketplace. Fruit defect detection models support precision agriculture by providing valuable data for decision-making and enhancing overall efficiency through automated inspection processes. This study implements and comparatively evaluates machine learning models including MobileNetV2, a custom-designed convolutional neural network (CNN) model, ResNet50, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 37–47 Read article
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Performance Analysis of Machine Learning Algorithms For Disease Prediction
Abstract: In this 21st century, where Digitization makes humans measure, record, analyze and to manipulate the huge amount of data as per the requirement, prediction of the decease based on Machine Learning models will be representing one of the good applications of the efficient data handling. An Automatic Decease Prediction system based on the symptoms would be the great boon for the medical practitioners. The Supervised Machine Learning models, such as …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 9–18 Read article
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Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
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Enhancing Wildlife Tourism Management Using Deep Learning and Particle Swarm Optimization (PSO) for Animal Detection in Wildlife Sanctuaries
Abstract: Wildlife tourism is one of the most thriving sectors, faced with huge challenges in terms of safeguarding protected areas. As demand for wildlife experiences accelerates, it becomes necessary to find efficient measures that are friendly to conservation. The use of these advanced techniques in this field such as YOLO and PSO algorithm presents a new dimension on managing wildlife tourism. To harness the abilities of these techniques, this research centers …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 41–50 Read article
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Educating Compilers to Learn: Utilizing Machine Learning for More Brilliant Code Optimization
Abstract: This study explores the use of machine learning (ML) approaches to compiler optimization. The now-traditional static compilation techniques are transformed into adaptive, dynamic systems capable of making context-specific advancements. Traditional compilers rely mostly on heuristic or rule-based optimization techniques. While these techniques work well in general cases, they consistently fail to adapt well within the limits of code structures that modern machines display. This limitation is especially acute in today's …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 50–54 Read article
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Prevention of Water Overflows and Leakages at MPCOE Campus
Abstract: Water is one of the fundamental necessities of human life, essential for a wide range of daily activities. People rely on water for drinking, cleaning, cooking, irrigation, and industrial processes. To meet these needs, water is often pumped from ground storage to overhead tanks. However, the use of non-automated switches to operate pumping machines can lead to significant issues, such as water overflow and unnecessary electricity consumption. The proposed system …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 43–51 Read article
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Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks
Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article
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Investigation on Thermal and Modal Analysis of Brake Disc Made of SS410 And SS304 Using ANSYS
Abstract: The Primary purpose of the investigation is to investigate the vibration and noise that are present in the braking system. As a result of the application of braking force, the kinetic energy of the vehicle was transformed into heat, sound, and vibrational energy. The dynamic structural characteristics of the components that make up the braking system are closely linked to the modal behaviour, which refers to the vibration modes that …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 346–358 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 Read article