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380 articles for “network processing”
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Evaluating the Efficiency of LLMs-SA (Sentiment Analysis) via Social Media Texts
Abstract: Sentiment analysis (SA) is becoming popular in business and scientific communities as the processing of natural language (NLP), computational linguistics, text analytics, image-based processing or video- based processing is used in extracting and mining subjective information in the web, social network, etc. It is able to detect positive, negative or neutral information and can be selected to absorb polarity, sentiments, urgency and goals of mount importance. The majority of the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article
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Reviewing Threat Detection Methods in SaaS Platforms Through the Use of Adaptive Cloud Security Models
Abstract: Software as a Service (SaaS) solution has revolutionized the contemporary business processes as scalable and service-on-demand solution on cloud networks. Yet, this expansion has brought in sophisticated cybersecurity risks because of a multi-tenant environment facing the internet in the SaaS environment. The key to assure the service availability and protection of the data stored off-site is effective threat detection in such dynamic ecosystems. This review article seeks to discuss the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 Read article
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Advanced Lithium-Ion Battery Prognostics: A Comprehensive Review of Machine Learning Approaches for Remaining Useful Life Prediction
Abstract: The lithium-ion battery (LIB), as one of the main sources for portable power systems, has been increasingly popular owing to its widespread applications in electric vehicles, consumer electronics, aerospace and renewable energy. Despite their advantages in high energy density and long cycle life, LIBs suffer from degradation over time of aging and cycling, resulting in loss of performance, safety issues, and economic bottlenecks. Predicting their Remaining Useful Life (RUL) is …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 12–27 Read article
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Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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A Study on Security Requirements of IOT
Abstract: In terms of speed, internet technologies have surpassed traditional technologies. Although the Internet's explosive growth has allowed it to reach its full potential, there are several security dangers associated with it. Many consumer-grade IoT devices are not designed with robust authentication protocols, making them easy targets for hackers. To address this, stronger multi-factor authentication (MFA) methods and certificate-based authentication should be implemented to ensure that only legitimate devices gain access …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 24–28 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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Exploring the Role of MAPK3 in Major Depressive Disorder: Molecular Docking, Dynamics, and Binding Free Energy Analysis of Natural Compounds as Alternatives to Conventional Drugs
Abstract: Major Depressive Disorder (MDD) is a prevalent neuropsychiatric disorder with limited treatment efficacy and significant side effects associated with conventional antidepressants. Recent studies have highlighted the role of mitogen-activated protein kinase 3 (MAPK3) in the mechanisms underlying MDD, positioning it as a potential target for the development of novel therapeutic drugs. In this study, we employed various computational approaches to explore natural compounds as viable alternatives to synthetic antidepressants. Researchers …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 53–68 Read article
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A Review Paper on The Mathematical Foundations of Artificial Intelligence
Abstract: Artificial Intelligence (AI) is deeply rooted in various branches of mathematics, which provide the theoretical foundation and practical tools for developing intelligent systems. This paper explores the crucial role of mathematics in AI, focusing on key areas such as Linear Algebra, Probability and Statistics, Optimization Techniques, Calculus, Graph Theory, and Fourier and Wavelet Transforms. Linear Algebra is fundamental for representing and manipulating data, with applications in dimensionality reduction and neural …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 7–14 Read article
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AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article
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Divorced Women Attitudes Towards Remarriage: A Qualitative Approach
Abstract: The current study aimed to investigate the attitudes of divorced women regarding remarriage and to comprehend the diverse factors that shape their viewpoints. The research population comprised divorced women, and a purposive sampling method was employed to select participants. Data were collected from ten divorced women through semi-structured interviews, allowing for in-depth exploration of personal experiences and viewpoints. A qualitative research design was adopted to capture the complexity of individual …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 1–14 Read article
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Handwritten Sanskrit Word Recognition: A Deep Learning Approach Using AlexNet
Abstract: Handwritten Sanskrit word recognition poses significant challenges due to the intricate structure of the script and the considerable variations in handwriting across individuals. To address these challenges, this research introduces a novel methodology employing transfer learning with the AlexNet convolutional neural network. The study utilized two distinct datasets: a specifically curated Sanskrit word image dataset containing 2616 samples, alongside a broader Devanagari character dataset used for validation purposes. The established …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 33–43 Read article
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AI Enhanced E-Voting System Securing Elections with Face Recognition and OTP Authentication in India
Abstract: The E-Voting domain seeks to leverage technology to address these issues, enabling citizens to vote securely and conveniently while maintaining the transparency of the electoral process. Machine learning algorithms like Haar cascade and CNN will enhance the system's security, accuracy, and efficiency by leveraging data- driven approaches. Conventional voting techniques frequently encounter obstacles including identity theft, convoluted processes, and hold-ups in the processing of results. This article suggests a complex …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 21–30 Read article
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Effect of Different Configurations of Reinforcement and Post-Cure Temperature Detailed Survey
Abstract: Composites with natural fillers have applied many applications, such as interior housekeeping, building and so on but their findings are seldom examined in the mechanical, tribological and dynamic situation. The addition of fillers in GFRP composites enhances the mechanical, thermal and tribological properties due to filler occupied in voids in thermoset resin. There has also been a lot of work done in quantifying the consistency of the operating parameters through …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1738–1753 Read article
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Enhancing Crop Health: A Review of Image Processing Methods for Leaf Disease Identification
Abstract: This research presents an overview of different image processing techniques for the identification of leaf disease. Many algorithms can be used to identify and categorize leaf diseases in plants, and digital image processing provides a quick, dependable, and accurate method of disease detection. This paper presents various techniques used on multiple crops and the achieved accuracy for each model. Leaf disease detection is a critical task in agriculture to ensure …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 10–14 Read article
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MXene-Infused Conductive Nano-Polymers for Edge-Computing Enabled Flexible Environmental Monitoring Devices
Abstract: MXene-infused conductive polymer composites have emerged as highly promising materials for next-generation flexible environmental monitoring devices because they combine electrical conductivity, mechanical flexibility, analyte sensitivity, and compatibility with low-power electronics. In this work, a Ti₃C₂Tₓ MXene–TPU/PVA conductive nano-polymer composite was developed as a multifunctional sensing platform for edge-computing enabled environmental monitoring. The composite was fabricated by dispersing MXene nanosheets into a thermoplastic polyurethane/poly(vinyl alcohol) (TPU/PVA) matrix, coating the conductive precursor …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Factors Influencing Online Purchase Behavior of Rural Consumers
Abstract: Online shopping has become a commonplace aspect of today's consumer landscape due to the rapid growth of e-commerce. This study explores the particular elements that impact rural consumers' online purchase behavior, whereas a large body of research has concentrated on the online shopping behavior of urban consumers. This study delves into the critical elements that influence rural consumers' online buying decision-making processes, based on comprehensive surveys and data analysis. The …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 5–16 Read article
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CLA0D1T—Auditing AWS Services S3 and IAM
Abstract: The swift embrace of cloud computing has revolutionized how organizations handle and provide their services, delivering unmatched scalability, flexibility, and cost-effectiveness. However, this shift has also introduced a range of new security challenges and vulnerabilities, particularly concerning data access and identity management. This project specifically aims to address these issues within the context of Amazon Web Services (AWS), focusing on auditing the Simple Storage Service (S3) and Identity and Access …
Published in Journal Of Network security · Vol. 12, Issue 3, 2024 · pp. 1–12 Read article
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Enhanced Task Automation through IoT and ChatGPT Integration in Personal AI Companions
Abstract: A new breed of clever, likable, and natural-sounding personal AI companions could be produced by integrating ChatGPT with IoT gadgets. The Internet of Things (IoT) and artificial intelligence (AI) are developing at a rapid pace, which has created exciting new opportunities for the creation of intelligent and personalized companions. The goal of this suggested system is to improve user experiences by offering a flexible AI-driven assistant. It does this by …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 2, 2024 · pp. 19–24 Read article