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121 articles for “Temporal”
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Extracellular Vesicle-Based Liquid Biopsies: Decoding the Tumor Microenvironment for Precision Oncology
Abstract: The tumor microenvironment (TME) plays a pivotal role in cancer initiation, progression, and therapeutic response. Decoding the TME is, therefore, essential for advancing precision oncology. Extracellular vesicles (EVs), including exosomes and microvesicles, are nanoscale lipid bilayer particles secreted by tumor and stromal cells. They transport a wide range of bioactive molecules, such as DNA, RNA, proteins, lipids, and metabolites, which reflect the dynamic state of the TME. Recent advances in …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 43–62 Read article
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Optimizing Mango Harvest Timing in the Nasik Region (Maharashtra, India) by CNNs (Residual Network 101)
Abstract: The determination of optimal harvest timing is one of the most critical decisions in mango production, directly affecting postharvest quality, market value, transportation resilience, and export readiness. In regions such as Nashik, Maharashtra—one of India’s major fruit- producing belts—the climatic variability, cultivar differences, monsoon patterns, and market- driven pressures make accurate harvest timing essential. Traditional maturity assessment relies on subjective visual inspection, specific gravity, or destructive testing, each of which …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 Read article
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CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Smart E-Health Consultation Portal
Abstract: The Smart E-Health Consultation Portal is an e-healthcare application that allows access to high-quality, efficient, and accessible medical care services via remote consultation of doctors & patients. Patients can communicate with their healthcare provider through video, voice, or chat communication which eliminates geographic and temporal boundaries. Factors that influence a patient's perception of satisfaction consist of clear and timely responses from their healthcare provider, a guarantee of privacy when using …
Published in Research and Reviews: A Journal of Health Professions · Vol. 16, Issue 1, 2026 Read article
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Integrated Explainable Forecasting and Metaheuristic PI Optimization for LFC/AGC
Abstract: Since the last decade world has seen a paradigm shift towards alternate sources of energy, due to significant increase in population and ever-rising demand. However, the traditional systems were not designed to cope with these alternate sources and on the other hand these systems are posed with the challenges of efficiency and intermittency. So, it is inevitable that we need to design a system wherein forecasting data has to be …
Published in Trends in Electrical Engineering · Vol. 16, Issue 2, 2025 Read article
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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Spatiotemporal Analysis of Mean-Field Coupled Lorenz Oscillators for Applications in Electronic Network Design and Chaotic Synchronization
Abstract: This study investigates the spatiotemporal behavior of a network of 100 coupled Lorenz oscillators interacting through mean-field coupling with coupling strength κ = 0.1 and explores its relevance to electronic system design and nonlinear network architectures. While each oscillator follows classical Lorenz dynamics, the coupling mechanism enables collective behavior that resembles synchronization phenomena observed in distributed electronic and communication systems. Numerical simulations reveal rich dynamical characteristics including partial synchronization, emergent …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 Read article
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Integrated Polarimetric-Interferometric Fusion for Heterogeneous Urban Signature Extraction
Abstract: Mapping heterogeneous urban environments using conventional Synthetic Aperture Radar (SAR) backscatter intensity frequently produces classification errors due to spectral similarity between sparse built-up features, bare soil, and dry vegetation a challenge especially acute in semi-arid Deccan Plateau settings. This research presents a dual-path Pol- InSAR fusion framework that integrates polarimetric scattering decomposition and interferometric coherence stability to extract heterogeneous urban signatures over Beed Taluka, Maharashtra (area: 1,561.31 km²). A temporal …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Dissipative Particle Dynamics Simulation Study on the Evolution of Photoinitiated Free Radical Polymerization Crosslinked Networks
Abstract: Gradient polymer materials overcome the limitations of conventional homogeneous polymers by integrating multiple distinct functionalities within a single continuous structure. Although photoinitiated free-radical polymerization offers excellent spatial and temporal control, the underlying microscopic mechanisms governing network evolution under non-uniform light fields remain poorly understood. In this study, a mesoscale dissipative particle dynamics (DPD) model was successfully developed to couple free-radical polymerization kinetics—including initiation, propagation, crosslinking, and termination—with exponential light attenuation …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 142–158 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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The Tapper Approach: An Integrated Framework for Land Degradation, Restoration, and Climate-Conflict Dynamics
Abstract: Land systems across the globe are increasingly exposed to multiple and interacting pressures, including land degradation, climate change, biodiversity loss, unsustainable land-use practices, rapid population growth, and socio-economic conflicts. These challenges not only reduce ecosystem productivity and resilience but also threaten food security, water availability, rural livelihoods, and long-term environmental sustainability. Despite the growing recognition of these interconnected issues, most existing conceptual and analytical frameworks continue to address them in …
Published in Research & Reviews : Journal of Ecology · Vol. 15, Issue 2, 2026 Read article
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Molecular Surveillance of Spring Viraemia of Carp Virus (SVCV) and Koi Herpesvirus (KHV) Across Major Aquaculture Zones of Telangana, India
Abstract: Viral diseases represent a persistent threat to cyprinid aquaculture; however, region-specific surveillance data from tropical production systems remain limited. To address this gap, a comprehensive statewide active surveillance programme was undertaken across Telangana, India, from 2019 to 2022 to investigate the occurrence of two priority transboundary pathogens, Spring Viraemia of Carp Virus (SVCV) and Koi Herpesvirus (KHV). A total of 414 fish specimens were systematically collected from five surveillance sectors …
Published in International Journal of Virus Studies · Vol. 3, Issue 2, 2026 Read article
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Keyless: LQ Based On IOT
Abstract: In recent years, there has been a growing interest in smart home technologies, with smart door locks being one of the focal points due to their potential to enhance security and convenience. Smart door lock systems are transforming access control by offering a keyless alternative for both residential and commercial settings. These electronic locks replace traditional keys with secure methods such as emergency alarms, privacy modes, battery backup, cameras, voice …
Published in Journal Of Network security Read article
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Fluid Dynamics of a Stressed Freshwater Lens: Integrated Flow Modeling and Pathways for Material-Centric Interventions in Khadir Island, Gujarat
Abstract: This study applies principles of fluid dynamics and porous media mechanics to analyze the behavior and sustainability of the freshwater lens in Khadir Island, an arid sedimentary island in Gujarat, India. We develop an integrated fluid flow model that couples surface hydrology with aquifer dynamics to quantify recharge fluxes, extraction stresses, and hydraulic responses. Using 11-year hydro-meteorological data (2011–2021) and sectoral demand projections, we characterize the island’s water budget through …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 12–29 Read article
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Neuromorphic Spiking Neural Networks and Event-Driven Hardware: Architectures, Learning Paradigms, and Experimental Realizations
Abstract: With the current computational boom the research community is seeking for more sustainable energy efficient i.e. biologically inspired models of conventional Artificial Neural Networks (ANNs). Spiking Neural Networks (SNNs) known as the third generation of neural network models, provide a revolutionary approach by mimicking the asynchronized event-driven and temporally accurate signaling of the mammalian brain. Whereas conventional deep learning models operate with real-valued activations and dense matrix multiplications, SNNs use …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 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