Search
37 articles for “SOH”
-
Joint Estimation of CSI and IQ Imbalance, and Compensation of IQ Imbalance in Spatialy Multiplexed MIMO-OFDM Receivers
Abstract: This study presents a novel method for estimating Channel State Information (CSI) and IQ imbalance and compensating IQ imbalance in a spatially multiplexed MIMO OFDM receiver. Our approach integrates estimation of IQ imbalance with CSI estimation using an OFDM training frame, thus eliminating the need for additional pilot symbols for IQ imbalance estimation. This technique streamlines the process and avoids extra overhead. We conducted simulations on a 2×2 spatially multiplexed …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 11–17 Read article
-
Performance Comparison of Noise-Tolerant, High- Performance CMOS Domino Logic Configurations
Abstract: In high-performance VLSI chip design, domino logic configuration is often preferred over static logic due to its faster operation and smaller area footprint, especially in deep submicron (DSM) technology. However, DSM noise has become a significant challenge in domino-based circuits, leading to compromises in the reliability and signal integrity of integrated circuits (ICs). The switching threshold of domino logic, defined as the input voltage level at which the gate output …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 35–50 Read article
-
A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
-
Performance Evaluation of Lithium-Ion Batteries Considering State of Charge and State of Health for Electric Vehicle Applications
Abstract: This study aims to compare temperature-regulated and uncontrolled charging methodologies to determine the most effective approach for optimizing battery performance while minimizing charging duration. The study assesses both constant current (CC) and temperature-controlled pulse charging (TRPC) methods. The battery temperature increases in direct proportion to the applied current during CC charging and cannot be controlled in the absence of external cooling systems. Key performance measures, such as the effect on …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 15, Issue 3, 2025 · pp. 32–47 Read article
-
DR. REVIVE: An AI-Powered Medical Recommendation System for Optimised Resources and Improved Patient Care
Abstract: Dr. Revive is an AI-powered medical recommendation system designed to enhance virtual healthcare interactions by connecting patients, doctors, and healthcare stakeholders. Leveraging advanced machine learning algorithms, it analyses user-reported symptoms to provide initial medical recommendations, serving as a reliable first point of guidance. With access to a comprehensive medical database, the platform delivers accurate and timely advice, empowering patients while supporting healthcare professionals with data-driven decision-making. By offering a complete …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
-
Hydroponic Farming Monitoring System - Automated System to Monitor and Control Nutrient and pH Levels
Abstract: With growing urbanization and limited agricultural land, sustainable agriculture is becoming a necessity. This project introduces a smart, space-saving, and automated hydroponic farming system based on IoT (Internet of Things) technology. The proposed system employs an ESP8266 NodeMCU microcontroller with sensors like a pH sensor and an ultrasonic sensor to track critical plant growth parameters like nutrient solution pH and water level. A relay module controls a water pump for …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 11–16 Read article
-
Flavonoid Contents and Antioxidant Activity of an Endophytic Bacteria Associated with Medicinal Plant Humulus lupulus
Abstract: Endophytes are symbiotic microorganisms, most often bacteria or fungi, that reside and multiply within plant tissues without inducing visible signs of disease or negatively affecting the host plant. Endophytic bacteria contribute to plant development by stimulating growth, strengthening defence mechanisms, enhancing tolerance to both abiotic and biotic stresses, and facilitating improved nutrient uptake. Endophytic bacteria serve as an important reservoir of bioactive compounds, notably antioxidant molecules, that play a crucial …
Published in Research & Reviews : Journal of Herbal Science · Vol. 14, Issue 3, 2025 · pp. 1–6 Read article
-
Optimization of Sustainable Electrochemical Machining Parameters for Polymer based Materials Using AHP Integrated TOPSIS Method
Abstract: The current paper describes the use of the AHP-TOPSIS method to optimize process parameters in sustainable electrochemical machining of polymer composites. Combine lightweight polymer matrices with reinforcing particles or fibers such as TiB₂, SiC, or Al₂O₃, offering high strength-to-weight ratio, corrosion resistance, and design flexibility, making them ideal for aerospace and automotive applications. Non-conductive and heterogeneous nature poses challenges during electrochemical machining, as it affects current distribution and material removal …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1048–1059 Read article
-
A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
-
A Research on Goat milk and Papaya Face Wash
Abstract: The increasing demand for natural and sustainable skincare products has driven interest in bio-based cosmetic formulations. This study focuses on the development and evaluation of a goat milk and papaya–based face wash aimed at providing gentle cleansing, moisturizing, and exfoliating properties through natural ingredients. Goat milk, rich in lactic acid, proteins, and essential fatty acids, contributes to hydration and mild exfoliation, while papaya (Carica papaya) extract, containing papain enzyme and …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 30–38 Read article
-
Ferroelectric Materials for Next-Generation Non-Volatile Memory Applications
Abstract: The continuous scaling of conventional memory technologies is increasingly constrained by limitations in power consumption, speed, endurance, and integration density. As data-intensive applications such as artificial intelligence, Internet of Things, and edge computing demand fast and energy-efficient memory solutions, alternative non-volatile memory technologies have gained significant attention. Ferroelectric materials, characterized by their reversible spontaneous polarization, offer a promising pathway toward next-generation non-volatile memory due to their intrinsic non-volatility, low operating …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 1–9 Read article
-
FutureGen – Predicting Genetic Health
Abstract: FutureGen is an intelligent web-based system developed to help couples assess the risk of genetic disorders in their future child through data-driven analysis. The system brings together modern web technologies and machine learning to offer accurate and accessible predictions. The frontend, built with React, provides an intuitive interface for user interaction, while a Flask-based backend API handles model inference and manages communication with the Supabase database, which securely stores user …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
-
Cyber-Secure IoT Framework for Monitoring Fiber-Reinforced Polymer Composites Using Embedded Sensors
Abstract: The present research paper suggests a cyber-safe Internet of Things system in real-time monitoring of fiber-reinforced polymer composites with inbuilt sensors. It is aimed at enhancing structural health maintenance, using sensual, intelligent analysis, and data protection in the same platform. Multi-layer architecture An embedded sensor, signal processing, anomaly detection and lightweight layer of cyber-security are developed. Experimental validation is done under controlled conditions and the performance is measured by these …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 434–458 Read article
-
Machine Learning–Guided Cognitive RF System with Dynamic FFT Resolution and Multiplier Reconfiguration for Adaptive Anti-Jamming Communication
Abstract: This paper presents a hierarchical adaptive RF communication system that integrates signal quality-based pre- processing with machine learning-driven signal classification to achieve robust and resource-efficient operation in dynamic, interference-prone environments. Unlike prior art that addresses adaptive RF, ML classification, or anti-jamming individually, this work uniquely combines real-time SNR/RSSI-based signal strength estimation with dynamic FFT size selection (64-, 256- , or 512-point) and arithmetic-level multiplier reconfiguration (CORDIC, Distributed Arithmetic, and hybrid …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
-
Review of Battery Management System and SOC
Abstract: The perception of electric cars (EVs) as a strong alternative to for internal combustion engine automobiles is growing. For electric vehicle (EV) technologies to advance, they must develop quickly, especially in the area of battery technology. light weight, increased energy capacity, quick charging times, lithium-ion (Li-ion) batteries are generally used for electric vehicles (EVs). The efficiency of the battery management system (BMS) and battery performance are critical elements influencing electric …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 1, 2026 · pp. 08–16 Read article
-
Performance Analysis And Battery Management System Optimization In Electric Vehicles
Abstract: The rapid electrification of the automotive industry has led to an increased need for battery management systems that are not only efficient and safe but also intelligent. BMS is the device that guarantees the best use of the battery, prolongs its life, and allows its safe operation even under different environmental and load conditions. Through the synthesis of literature and industry practices, this paper acts as a tribute to the …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 Read article
-
IoT-Based Battery Health Monitoring for Electric Vehicles Using Machine Learning
Abstract: With increasing utilization of the Electric Vehicles (EV)s in global scale, battery health management becomes a critical factor which has great impact on vehicle performance, safety and longevity. Battery materials, such as NMC LFP lithium-ion batteries and lithium-ion batteries, degrade over time from charging behaviour, heat stress, discharging voltage profiles and environmental limits. Conventional BMS only offer threshold based health diagnostics and cannot perform accurate degradation prediction. This work presents …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article