Search
9 articles for “RF- MEMS”
-
Dielectric Polymer Based Tunable Bandpass Filter for RF MEMS Applications
Abstract: In this paper, we report on the design, modeling, and analysis of a tunable bandpass filter implemented in a coplanar waveguide (CPW) configuration, where a distributed MEMS transmission line (DMTL) is integrated with dielectric polymer layers to achieve dynamic frequency and bandwidth reconfigurability. The proposed filter architecture leverages the tunable dielectric response of polymer films, enabling precise control of the center frequency and passband width under applied electrostatic bias. Comprehensive …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1449–1470 Read article
-
Development of Compact RF Filters for Modern Wireless Communication Systems
Abstract: Modern wireless communication systems such as 5G, 6G, Internet of Things (IoT), satellite communication, radar systems, and smart wireless networks require compact and highly efficient RF filters for reliable signal transmission and interference suppression. RF filters are important components that allow desired frequency signals to pass while rejecting unwanted frequencies and noise. With the rapid growth of wireless devices and limited spectrum resources, the demand for miniaturized, low-loss, multi-band, and …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 2, 2026 Read article
-
Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
-
Influence of Polymeric Materials on Osseointegration and Stability of Dental Implants: An In-vivo Resonance Frequency Analysis
Abstract: Osseointegration, the successful integration of dental implants with surrounding bone tissue, is crucial for long-term implant stability. Resonance frequency analysis (RFA) provides a valuable tool for assessing implant stability. This in-vivo study investigates the potential role of polymeric materials used in dental implants, such as surface coatings or membranes, in influencing osseointegration and RFA-measured stability. By analysing the impact of these polymers on factors like cell adhesion, proliferation, and differentiation …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1051–1057 Read article
-
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
-
Design of Automated Student Permission System using RFID and NodeMCU
Abstract: Automated Student Permission System is a system that can be used to automate the process of monitoring students attendance and granting permission to students to leave college early. The system works by having a sign-out sheet placed at the college's entrance that students can access using their college ID. When a student wants to leave the college early, they log in to the electronic sign-out sheet using their college ID. …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 1, 2023 · pp. 23–31 Read article
-
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
-
Smart Card Based Lineman Safety
Abstract: As maintenance workers and electrical substations are being repaired, there are more electrical mishaps involving linemen today. Contact with overheated wires is the most frequent reason for electric shock and electrocution in the workplace, but there are other factors as well. When transporting equipment like poles and ladders, this happens when people underestimate the height of the ground and overhead wires. Not separating electrical supply is another common cause of …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 1, Issue 1, 2023 · pp. 1–7 Read article
-
AI-Driven Predictive Maintenance Framework for Intelligent Vehicle Health Monitoring
Abstract: The accelerated development of smart and connected car systems made the necessity to find the accurate and real-time predictive maintenance solutions which would minimize the number of unexpected failures as well as increase the cars on-road safety. The current paper proposes an artificial intelligence-based hybrid predictive maintenance system that combines Long Short-Memory (LSTM) networks and the XGBoost predictor to provide a potent vehicle fault diagnosis, Remaining Useful Life (RUL) prediction, …
Published in Trends in Machine design · Vol. 13, Issue 1, 2026 · pp. 1–17 Read article