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123 articles for “RF”
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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Integration of Multispectral Satellite data with Ensemble Machine Learning Models for Wetland Classification: a new Ramsar Site in Central India
Abstract: For biodiversity conservation, several wetlands in India have been classified as Ramsar sites, and Sirpur Lake is a recent addition to the list. The objective of this paper is to use Sentinel optical data with 10-meter resolution to prepare a robust and accurate classified map which will be crucial for further analysis. The data on thirteen spectral bands along with four essential spectral indices, Normalized Difference Vegetation Index (NDVI), Normalized …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 Read article
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Resilient Shell-Based Networking Frameworks for DTN Environments: Enhancing Reliability and Security across Disrupted and High-Latency Satellite Channels
Abstract: The foundation of DTN, as suggested by the Internet Research Task Force (IRTF), is the definition of a suite of protocols that function in networks with periodic disconnections and long- duration route conditions. A permanent end-to-end channel from the source to the destination is the foundation of traditional IP-based networking. However, DTN employs a store-carry- forward approach that gives intermediary nodes the ability to temporarily hold messages (or bundles) until …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 3, 2025 Read article
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article
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Experimental Investigation and Optimization of Machining Parameters for Al6351 Alloy Using a Modified Taguchi Approach
Abstract: Machining processes encompass both conventional and non-conventional techniques and optimizing machining parameters is crucial for achieving high-quality outcomes. However, simplifying these processes remains a significant challenge. This study focuses on determining the optimal machining parameters—cutting speed, feed rate, and depth-of-cut to enhance performance characteristics in Al6351 alloy plates. The parameters evaluated include surface roughness (Ra), material removal rate (MRR), resultant forces (RF), and temperature at the tool- workpiece interface (Temp). …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1463–1481 Read article
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Design of a SmartMesh IP Network with Wireless Motes and GUI Control
Abstract: SmartMesh IP is an innovative way to connect smart devices with advanced network management and comprehensive security features. SmartMesh IP delivers reliable, scalable, and energy efficient wireless sensor connectivity. In recent years, SmartMesh IP has become the industry’s most energy- efficient wireless mesh sensing technology even in harsh and dynamically changing radio frequency (RF) environments. This paper proposes a SmartMesh IP network system that consists of a network manager and …
Published in Journal of Microcontroller Engineering and Applications Read article
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Development of Anti IgG Polyclonal Antibody Against Canine IgG and Their Roles in Diagnostic Purposes
Abstract: IgG plays an important part in immunological studies and also in living bodies for providing secondary immune response which triggers as passive immunization against harmful pathogens in dogs. Purpose: The aim of this investigation is to separate, identify, and refine immunoglobulin G from canine serum. Methods: Ammonium sulphate precipitation was used to separate the dog's serum, which was then concentrated over night in a dialysis bag inside of a refrigerator. …
Published in International Journal of Vaccines · Vol. 1, Issue 2, 2024 · pp. 01–06 Read article
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Panoramic review on Sida rhombifolia L.
Abstract: Sida Rhombifolia is also called Bala and is a well-known Ayurvedic herbal preparation used to treat inflammation, pain and neurological disorders. Literature calls Bala as Sida cordifolia, Sida, root powder acute, Sida cordata or Sida Rhombifolia subsp. retusa to achieve clinical efficacy of standardization of ksheerBala thailam Balamulacherna is essential.The objective of the study is to authenticate the pharmacognostic standards of Sida Rhombifolia root powder. Sida Rhombifolia was standardized with …
Published in International Journal of Pathogens · Vol. 1, Issue 1, 2024 · pp. 20–32 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Advancements in Intrusion Detection: Tackling Imbalanced Network Traffic with Machine Learning and Deep Learning Techniques
Abstract: Malicious cyberattacks can frequently hide enormous amounts of typical data in unbalanced network traffic. It is very stealthy and obfuscating in cyberspace, which makes it challenging for Network Intrusion Detection Systems (NIDS) to guarantee the precision and promptness of detection. This essay investigates. Machine learning and deep learning are utilized for intrusion detection in imbalanced network traffic. It offers a novel method for addressing the problem of class imbalance termed …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 18–24 Read article
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Li-Fi based Underwater Audio and Data Transmission System
Abstract: Visible Light Communication, or Li-Fi (Light Fidelity), is a wireless optical networking technique used for communication (VLC). Due to its lack of RF communication's drawbacks, such as water absorption and scattering, Li-Fi has the potential to completely transform underwater communication. This project suggests utilizing two Arduinos, a solar panel, a speaker, a display, an amplifier, a laser, a battery, and other components to create a Li-Fi based underwater audio and …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 2, 2024 · pp. 23–29 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Exploring the Evolution of Mobile Phone Detectors: From Basic Sensors to AI-Enhanced Solutions
Abstract: This work talks about the creation and plan of a portable phone locator that can discover approaching and active signals from versatile phones. This little, pocket-sized gadget can sense when a portable phone is dynamic from a separate of one and a half meters. Because of this, it can help anticipate the utilization of portable phones in places like exam corridors, private rooms, and petrol stations. It can moreover effectively …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 3, 2024 · pp. 17–23 Read article
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Comparative Analysis of Heart Disease Prediction System
Abstract: In the present world, where heart illnesses are on the rise, it is crucial to forecast these diseases. Performing the task on heart disease is a bit difficult and it must be finished precisely and successfully. Heart disease identification relies heavily on Machine Learning (ML) and data mining approaches. The primary focus of the review paper is that patients are easily prone to cardiac diseases depending on medical traits. Using …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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Textual Clues to Stress: A Machine Learning Approach
Abstract: Nowadays, numerous individuals utilize social media platforms to share tweets about their daily lives, which often reflect their mental well-being. Recognizing and managing stress is essential before it becomes a serious issue. Each day, a significant volume of informal messages is posted on discussion forums, blogs, and social networking sites. This study introduces a method for detecting stress using information gathered from social media, with a focus on Twitter. The …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 72–76 Read article
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HFSS-Based Helix Antenna Design Optimization and Simulation
Abstract: This project uses HFSS (High-Frequency Structure Simulator) to simulate, develop, and analyze the performance of a helix antenna for (a particular purpose, such as broadband wireless or satellite communication). Because of their distinctive structural characteristics, helix antennas are well-suited for a variety of high-frequency applications by balancing compactness, high gain, and wide bandwidth. In this work, we parametrically analyze important design parameters including pitch, radius, number of turns, and wire …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 29–35 Read article
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Reliable And Secure Audio Transmission in Underwater Communication Using Li-Fi
Abstract: Ensuring the security of audio transmission becomes crucial as underwater communication systems become more and more important in a variety of areas, including defense, marine research, and offshore organizations. For this reason, Li-Fi technology is an innovative solution that uses its immunity to electromagnetic interference to get around the restrictions of conventional radio frequencies. Li-Fi allows for high-speed data transfer while reducing interference and signal degradation by encoding audio onto …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 1, 2025 · pp. 23–29 Read article
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Optimized Design and Control of Oil Exploitation Strategies: An Assisted Approach
Abstract: Because there are so many factors and scenarios to consider, optimizing oil exploitation tactics requires complicated decision-making. Conventional approaches frequently concentrate on particular elements of the design infrastructure, which restricts their capacity to fully handle the process. In order to maximize a set of oil exploitation variables in a hierarchical fashion, this research proposes a novel assisted optimization technique that combines mathematical algorithms with engineering analysis. By grouping variables into …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 29–34 Read article
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Excoecaria agallocha Extract from Leaves Encounters Antifungal, Antibacterial, and Cytotoxic Activity – In Vitro Studies
Abstract: Mangroves contain a wide range of bioactive substances, certain of and these have been used as solutions for a variation of conditions for thousands of years. Excoecaria agallocha leaf application components have been extracted in the presence of organic solvents along with water-based with a Soxhlet apparatus and antibacterial research properties employing diffusion agar well assays towards nine different kinds of culture infectious agents, six clinical trials isolated compounds, as …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 15, Issue 2, 2025 · pp. 1–7 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article