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1267 articles for “extractant”
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Optimization of a new Bebq2/BCP-based OLED structure for optimum performance
Abstract: Opto-electronic devices exhibit highly nonlinear current–voltage (I–V) characteristics that significantly affect charge injection, transport, and recombination, evaluating their performance remains a difficult challenge. Device optimization is a key research goal in organic light-emitting diodes (OLEDs), as the thickness and arrangement of individual functional layers greatly influence electrical and optical responses. For a suggested Bebq2/BCP-based OLED structure, this work methodically examines the movement of charge carriers, their transport behavior, and the …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 2, 2026 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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Rheological Studies of a Cross-Linked Polymer Gel System
Abstract: The petroleum accumulations are found associated with water and it is rarely obtained without accompanying water production. Water production is a major technical, environmental, and economic challenge associated with oil and gas extraction. Rheological findings are of fundamental importance for the development, manufacture and processing of innumerable products. Polymeric gels exhibit a wide range of rheological properties and they are stable both mechanically and thermally in most cases thus are …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 13–26 Read article
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Farmer Producer Organizations as Catalysts of Rural Transformation: A Multidimensional Framework from Punjab, India
Abstract: Farmer Producer Organizations (FPOs) have evolved as an important institutional mechanism for resolving the socio-economic challenges of small and marginal farmers by fostering collective action, expanding market access, and boosting bargaining power. In the broader context of sustainable rural development, FPOs are increasingly acknowledged as catalysts of rural transformation by contributing to numerous dimensions of farmer well-being. However, current study has generally analyzed FPOs through economic and operational indicators, with …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 3, 2026 Read article
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Neuromorphic Self-Learning Polymer–MXene Photovoltaic Composites with Embedded Memristive Energy Routing for Adaptive Solar Energy Harvesting
Abstract: This dynamic and fast-growing intelligent renewable energy system requires photovoltaic materials that can autonomously adapt to fast-changing environmental conditions. In this study, a novel system is proposed for adaptive harvesting of solar energy based on Neuromorphic Self-Learning Polymer–MXene Photovoltaic Composites (NSPMPCs) with embedded memristive energy routing networks. To boost the charge generation and charge transport in the polymer–MXene heterostructure, the flexibility and processability of conductive polymers are integrated with the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 453–488 Read article
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Effect of Surface Modification on Properties of Kevlar/Epoxy Polymer Composites
Abstract: In this study, a high-performance Kevlar/epoxy polymer composite was prepared using a hand lay-up technique. The Kevlar fiber was treated with calcium chloride/ethanol solution (CaCl2/EtOH) to enhance the interfacial interaction between the fiber and the epoxy matrix. The optimization of fiber surface treatment and fiber content for the best tensile strength (TS) of Kevlar/epoxy polymer composite was achieved using Box-Behnken design (BBD) through response surface methodology (RSM). Three parameters: CaCl2 …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 35–46 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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Graphene-Based Electronic Skin for Wearable Health Monitoring and Human–Machine Interaction, Materials, Structures, and AI Integration
Abstract: Graphene-based electronic skin (e-skin) has emerged as a transformative technology for next-generation wearable health monitoring and advanced human–machine interaction (HMI). Owing to its outstanding electrical conductivity, mechanical flexibility, atomic-scale thickness, and biocompatibility, graphene enables the fabrication of ultrathin, conformal, and multifunctional sensors capable of mimicking the sensory functions of natural human skin. Over the past decade, research in this domain has progressed rapidly across four interconnected fronts: material synthesis and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 175–180 Read article
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
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Real-Time Deepfake Detection in Video Conferencing Systems
Abstract: Deepfake technology presents non-exemplary threats to video conferencing platforms, enabling advanced fraud, impression and misinformation campaigns worth billions annually. Current detection methods either exhibit latencies exceeding 100ms or rely on server-side cloud processing, raising privacy concerns. This paper presents DeepConfGuard, a lightweight hybrid architecture combining MobileNetV2 for spatial feature extraction, a bidirectional LSTM with attention for temporal modelling, and EfficientNetV2 for refinement. It reaches 94.8% accuracy with 85 ms end‑to‑end …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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A Review of Recent Advancements in Machine Learning and Deep Learning Approaches for Pet Diseases Prediction
Abstract: This systematic study assesses recent developments in Machine Learning (ML) and Deep Learning (DL) approaches to predict pet diseases. With the increasing role of Artificial Intelligence (AI) in pet healthcare, this study identifies recent research trends, limitations, and future directions. A comprehensive search was done using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines in selecting 20 relevant studies from over 300 articles published between 2020 and …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 14, Issue 3, 2025 · pp. 1–6 Read article
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Object Tracking Using Finite Element Method and Branching Filter
Abstract: AbstractWe present an approach to robustly track the object behavior that turns over time from a set of input points from a single viewpoint. The distortions considered are caused by applying forces to known Harris function on the object’s surface. Our method combines the use of prior information on the geometry of the object modeled by a smooth template and the use of a finite element method to predict the …
Published in Current Trends in Signal Processing · Vol. 7, Issue 3, 2017 · pp. 35–40 Read article
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P- and T-wave Characterization in the Presence of U-wave in Electrocardiogram
Abstract: AbstractEven after being noticed around a century ago the U-wave has not been studied much as compared to the other waveforms of the electrocardiogram (ECG). In this proposed work the effect of presence of U-wave on morphology of P-waves and T-waves has been studied. Characteristics of P-waves and T-waves from ECG beats with an U-wave has been compared with the P-waves and T-waves from ECG beat with an U-wave. Arithmetic …
Published in Current Trends in Signal Processing · Vol. 7, Issue 3, 2017 · pp. 30–34 Read article
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Speech Recognition and Analysis using Energy of the Signal
Abstract: AbstractSpeech plays an important role in day to day communication. It is a natural way to transfer thoughts from one to another. If any information needs to deliver in between human’s speech is the best way of delivery. With the help of the electronic system, we can extract the information from the original speech signal by doing signals processing. Here, in this research work, we formulate the system that recognizes …
Published in Current Trends in Signal Processing · Vol. 8, Issue 2, 2018 · pp. 25–33 Read article
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Constrained Online Non Negative Matrix Factorization (CONMF) for Visual Tracking
Abstract: Visual tracking is the process of locating a moving object (or multiple objects) over time using a camera. It is one of the most important components in numerous applications such as military, secure control, crime prevention systems, access control and biometric identification etc. of computer vision. In visual tracking, holistic and part-based representations are both popular choices to model target appearance. The former is known for great efficiency and convenience …
Published in Current Trends in Signal Processing · Vol. 7, Issue 1, 2017 · pp. 8–18 Read article
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Classification of PQ Disturbances in Induction Motor using Neuro-Fuzzy
Abstract: This paper presents a methodology of classification of PQ disturbances in the supply to induction motor using ANFIS. Wavelet transform is applied to the stator currents for the extraction of the signature indicating the variations in the supply. These wavelet coefficients are fed as input to ANFIS. This data has been divided into two sets: 37 training data set and 38 testing data set. The training data set has been …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 1–8 Read article
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Application of Compressive Sensing for Sampling and Reconstruction of MRI Images
Abstract: In recent years, a new theory of compressive sensing has evolved which asserts that super resolved signals and images can be recovered with far fewer samples than that demanded by the Nyquist sampling theorem. It is required that the signal being sensed has a low information-rate meaning that it is sparse in original or some transform domain. Former approaches capture the complete signal and process it to extract the information. …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 42–48 Read article
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Entropy Analysis Based Differential Evolution Approach for Emotion Classification for EEG
Abstract: Electroencephalography (EEG) signal processing is having its significance in various applications related to the emotion recognition and classification. The behavior monitoring, behavior class identification, emotion class identification are the major aspects for classification of EEG signal. In this paper, a feature adaptive differential evolution (DE) approach is defined to perform emotion classification. In this work, we used discrete wavelet transform (DWT), for extracting the statistical features from the EEG signal …
Published in Current Trends in Signal Processing · Vol. 5, Issue 3, 2015 · pp. 15–22 Read article
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Hand Grasp Recognition and Classification of Prehensile Surface EMG Signals
Abstract: Myoelectric control signals are commonly used as a convenient solution of prosthesis control for the disabled persons or amputees. Surface EMG signal being noninvasive is easy to acquire and is commonly used in prosthetic devices. Myoelectric control system is the fundamental component of modern prostheses, which uses the myoelectric signals from an individual’s muscles to control the prosthesis movements. In this paper data collected from several subjects using four surface …
Published in Current Trends in Signal Processing · Vol. 5, Issue 3, 2015 · pp. 29–38 Read article