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626 articles for “experimental results”
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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
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Thermally Adaptive Bio-Inspired VLSI Interconnect Model for Next-Generation Embedded Systems
Abstract: The increasing complexity of next-generation embedded systems has intensified the challenges associated with power dissipation, thermal instability, signal integrity, and interconnect reliability in Very Large- Scale Integration (VLSI) architectures. This research proposes a thermally adaptive bio-inspired VLSI interconnect model designed to enhance communication efficiency and thermal resilience in advanced embedded platforms. The proposed model integrates bio-inspired adaptive routing principles with dynamic thermal-aware interconnect management to optimize data transmission under varying …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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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
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Design and Implementation of an Automatic Rain Sensing Wiper System Using SEN0545 Sensor and Raspberry Pi Pico W
Abstract: This study presents the design and development of an intelligent, automatic rain-sensing wiper system designed to enhance vehicle safety. The system utilizes a SEN0545 capacitive rain sensor, integrated with internal signal processing, and a Raspberry Pi Pico W microcontroller as its central control unit. The proposed approach enables non-contact and corrosion-free rain detection, ensuring reliable performance under varying environmental conditions. Based on the detected rainfall intensity, the controller dynamically adjusts …
Published in Trends in Electrical Engineering · Vol. 16, Issue 2, 2025 Read article
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Machine Learning Based Sentiment Analysis of Student Feedback in Higher Education
Abstract: Educational institutions routinely collect feedback from students to understand their perceptions of academic programs, infrastructure, and campus facilities, to improve the overall quality of the college environment. In current practice, feedback is often gathered using numerical or grade-based rating systems, which tend to oversimplify student opinions and may overlook important details related to their level of satisfaction. In contrast, open-ended textual feedback allows students to clearly express their views, concerns, …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 01–10 Read article
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Polymer Composite-Enabled UAV Platform for Edge AI-Based Precision Agriculture: A System-Level Evaluation
Abstract: This study investigates the system-level role of commercially available polymer composite materials in enabling lightweight and energy-efficient unmanned aerial vehicle (UAV) platforms integrated with edge artificial intelligence for real-time agricultural monitoring. Rather than developing or experimentally characterizing new composite materials, the work evaluates fiber-reinforced polymer (FRP) composites and epoxy-based laminates as enabling structural components whose established properties support UAV performance in precision agriculture. Their high strength-to-weight ratio, corrosion resistance, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 218–240 Read article
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Smart Air Quality Monitoring System using IoT
Abstract: This paper presents the design and implementation of a Smart Air Quality Monitoring System using the ESP32 Wi-Fi microcontroller integrated with an MQ-2 gas sensor and a DHT-11 temperature and humidity sensor. The system continuously monitors environmental parameters including air quality (smoke, LPG, CO, and other combustible gases), temperature, and relative humidity in real time. The acquired sensor data is transmitted wirelessly to the Blynk IoT platform, enabling users to …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 17, Issue 2, 2026 Read article
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Photochemical Detoxification of Arsenic- and Mercury-Contaminated Soils: Geochemical Mechanisms and Pathways
Abstract: This study evaluates the geochemical aspects of soil detoxification in areas contaminated with arsenic (As) and mercury (Hg), emphasizing sustainable strategies for improving soil health and ensuring safe crop production. The research provides an ecological and toxicological assessment of regional soils and classifies them base on the concentration and mobility of toxic elements. Although the current levels of As and Hg do not yet present a critical risk to agricultural …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 1, 2026 · pp. 06–10 Read article
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Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Develop the Design of Sustainable Polymer Materials: Applying Reinforcement Learning, IoT-Enabled Monitoring, and Data-Driven Manufacturing Approaches
Abstract: Sustainable polymer materials development is a must due to resource constraints, environmental concerns, and the demand for designed materials with high performance. When it comes to material optimization, energy utilization, process unpredictability, and lifecycle sustainability, traditional polymer production methods have their challenges. Reinforcement Learning (RL), Internet of Things (IoT) monitoring, and data-driven production are utilized in the design and manufacturing of sustainable polymer materials. It is recommended to use Internet …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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Tailoring the Compressive Behavior of Tetra-Chiral Auxetic Structures through FDM Process Parameters
Abstract: This research evaluates how fused deposition modeling (FDM) fabrication process parameters affect the compressive behavior of tetra-chiral auxetic structures created from Polylactic Acid (PLA). Auxetic materials have a number of useful properties, including reversible deformation and high-energy absorbing capabilities, which are beneficial to creating ultra-lightweight structural, protective, and shock-resistance designs. Among the available auxetic topologies, the tetra-chiral configuration is particularly attractive for engineering use, because its rotation-dominated node–ligament deformation gives …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Record Linkage in Knowledge Discovery Process Using Angle Based Machine Learning
Abstract: Record linkage is a critical data cleansing step in the knowledge discovery process, aimed at identifying and resolving inconsistencies across datasets. This study proposes an enhanced record linkage framework tailored for uncertain and large-scale data using a combination of distance measurement, probabilistic modeling, and semantic reasoning. A novel angle-based distance measurement technique is introduced to optimize matching between candidate records. To further boost match accuracy, a Finite Mixture Model (FMM) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1157–1170 Read article
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IoT-Based Motor Protection and Control System Using PLC and ESP8266
Abstract: Because of their straightforward design and affordable price, single-phase induction motors are frequently utilized in residential and small-scale industrial settings. However, conventional direct-on-line (DOL) control provides fixed-speed operation and offers limited protection against thermal overload and fault conditions. This article describes the design and implementation of an ESP8266 Node MCU-based PLC- based closed-loop motor control system with Internet of Things features. To increase operating flexibility and maintenance efficiency, the suggested …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 54–62 Read article
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A Comprehensive Investigation of Bagging-Based Ensemble Methods for Improving Machine Learning Model Robustness
Abstract: Machine learning models such as Decision Trees, Logistic Regression, and K-Nearest Neighbors are widely used for classification tasks due to their simplicity and interpretability. However, these models often suffer from high variance, overfitting, and poor generalization when applied to real-world datasets, particularly those that are small, noisy, or imbalanced, as commonly encountered in healthcare, finance, and cybersecurity applications. To address these limitations, this research proposes a Bagging (Bootstrap Aggregating)-based ensemble …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 24–34 Read article
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The Strength of Dry, Fresh and Decomposed Raffia Palm Trunk in the Bioremediation of Oil-based Drill Cutting
Abstract: In this research, the impact of dry drill cuttings and compost tea on the environment's ability to degrade oil-based drill cutting contamination is investigated. The experiment was conducted in the research center located at the workshop of Agricultural and Environmental Engineering Department, Rivers State University, Port Harcourt. Oil-based drill cutting samples were placed in bulk in eleven reactors (T1, T2, T3-T11) with four replications. The original drill cuttings' physiochemical characteristics …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 15, Issue 3, 2024 · pp. 26–33 Read article
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Characterization of Fracture Toughness of As-Cast Si-Mo- Cr Ductile Cast Iron
Abstract: In the present study, a Si-Mo-Cr ductile cast iron is developed by taking three different combinations, viz. Heat-1, Heat-2 and Heat-3 of the selective amount of silicon, molybdenum, copper and chromium. For fracture toughness characterization, the specimens are prepared from the samples in "as-cast" conditions. The value of static fracture toughness obtained from the experiments for the specimen of Heat-2 with a fatigue pre-crack is 54.49 MPa√ , whereas, for …
Published in Journal of Polymer & Composites Read article
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Mechanical Properties Investigation of Green Waste Composite Material
Abstract: Widespread accessibility and abundance of natural fibres are driving forces behind renewed focus on eco-friendly solutions. Researchers have recently begun to focus on natural fibres as reinforcement due to their many advantages over more conventional materials. Natural fibre is an attractive ecological and biodegradable alternative to most common glass fibre, synthetic reinforcement, because of its high specific and low cost mechanical capabilities. India is home to a wealth of untapped …
Published in Journal of Polymer & Composites · Vol. 11, Issue 4, 2023 · pp. 28–36 Read article