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634 articles for “architecture”
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Learning Data Structures: Key to Good Programming
Abstract: Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks. It explains how selecting and using the correct data structures may speed up computations, optimize memory, and scale code. How data structures and algorithms relate and how to think about …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 29–39 Read article
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Ethical AI and Data Protection in the Era of Industry 5.0
Abstract: This paper provides a comprehensive analysis of the critical intersection between Responsible AI (RAI), data privacy, and the Industry 5.0 paradigm. Industry 5.0, defined by its human-centric, sustainable, and resilient pillars, introduces a fundamental paradox: its core requirement for human-AI collaboration necessitates the collection and processing of granular human data, creating direct conflicts with emerging global data privacy and AI regulations. This research utilizes a systematic integrative review methodology, analyzing …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Deep Learning models for real time detection of crop diseases in the Maharashtra/Mumbai district
Abstract: This research project addresses the critical agricultural challenge of crop disease management in the Maharashtra region of India by leveraging modern deep learning techniques. The primary objective is to identify, implement, and compare the efficacy of various deep learning architectures—including Convolutional Neural Networks (CNNs), MobileNet, and EfficientNet—for the real-time classification of diseases in key crops such as cotton, soybean, and sugarcane. A custom dataset of agricultural images specific to Maharashtra's …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 36–48 Read article
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Smart Biopolymer–PCM Composite Modules with Embedded Wireless Thermal Sensing for Autonomous Energy Storage Applications
Abstract: The development of multifunctional polymer composite systems for intelligent thermal energy storage has gained significant attention due to the increasing demand for sustainable and autonomous thermal management technologies. In the present study, a wireless-integrated biopolymer–phase change material (PCM) composite module embedded with thermal feedback sensors was successfully fabricated and experimentally investigated for advanced thermal energy storage applications. Polylactic acid (PLA) was employed as the biodegradable polymer matrix, while paraffin wax …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 193–205 Read article
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Smart Education in the Context of Puducherry India
Abstract: This paper explores the concept of smart education and presents its conceptual framework in the context of Puducherry. It aims to enhance the understanding of smart education by analysing its fundamental components, including educational challenges, technological innovations, management strategies, policy frameworks, historical evolution, and emerging trends. The adoption of smart education has accelerated significantly in recent years, particularly during the COVID-19 pandemic, when educational institutions worldwide transitioned from traditional classroom-based …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 10–17 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Green AI-Enabled Opto-Electronic Communication Systems for Carbon-Neutral Digital Networks
Abstract: The rapid expansion of digital communication infrastructure, driven by cloud computing, Internet of Things (IoT), 6G networks, and artificial intelligence applications, has significantly increased the energy consumption and carbon footprint of modern communication systems. Conventional optical communication networks often rely on static resource allocation and energy-intensive signal processing mechanisms, resulting in inefficient utilization of network resources and elevated operational costs. This study proposes a Green Artificial Intelligence (Green AI)-Enabled Opto-Electronic …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 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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Quantum-Fuzzy Tensor Operators for Multi-Qubit Conjunction, Disjunction, and Symmetry-Preserving State Discrimination
Abstract: The integration of fuzzy logic and quantum information theory raises a fundamental mathematical question: how can degrees of truth be encoded in multi-qubit amplitudes while preserving the unitary dynamics and symmetry structure of quantum state spaces? This paper develops a tensor-operator framework for implementing quantum-fuzzy logical operations on finite qubit registers. Fuzzy truth values are represented by normalized quantum amplitude pairs, enabling logical information to be embedded directly into quantum …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 16–21 Read article
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Automatic Car Controller Based on Sign Board using Deep Learning and IOT
Abstract: The rapid growth of intelligent transportation systems has increased the demand for safer and more efficient driving solutions. Conventional vehicles often rely heavily on human intervention, which can lead to accidents due to negligence, fatigue, or poor visibility of traffic signs. This project proposes an automated car control system that utilizes deep learning and Internet of Things (IoT) technologies to recognize traffic signboards and respond accordingly. The primary objective is …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article
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Energy-Aware Task Offloading in 6G-Enabled Mobile Edge Computing Environments
Abstract: The emergence of sixth-generation (6G) wireless communication networks is expected to revolutionize future mobile systems by enabling ultra-low latency communication, extremely high data rates, massive connectivity, and intelligent network management. In parallel, mobile edge computing (MEC) has gained significant attention as a promising paradigm that brings computational resources closer to end users, thereby alleviating network congestion and reducing end-to-end service delays. Despite these advantages, the rapid growth of computation-intensive and …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 1, 2026 · pp. 14–19 Read article
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A Review on Smart Touchless Dustbin Systems for Hygienic Waste Management and Smart City Applications
Abstract: Municipal solid waste output has significantly increased as a result of rapid urbanization and population expansion, placing a strain on the infrastructure already in place for waste management. Traditional waste receptacles, requiring manual operation and lacking fill-level monitoring, present public hygiene risks and cause logistical inefficiencies. The emergence of the Internet of Things (IoT) and embedded automation technologies has introduced intelligent solutions to address these challenges. This paper provides a …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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Blockchain for Secure Health Records in India: Aligning with Ayushman Bharat
Abstract: India’s healthcare ecosystem continues to face significant hurdles, particularly in the efficient management, protection, and accessibility of patient health records. For decades, medical data in the country has remained scattered across institutions, recorded in incompatible formats, and stored in systems that rarely communicate with each other. These gaps not only slow down clinical decision-making but also increase exposure to data breaches and other cybersecurity risks. In this context, blockchain technology …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 01–05 Read article
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Early Lung Cancer Prediction using deep Learning
Abstract: Lung cancer is a global killer because it’s often found late. Finding it early is key to treatment and survival so computer assisted diagnostics are essential. This research uses deep learning to spot early stage lung cancer from CT scans. We trained and fine-tuned three convolutional neural networks—ResNet50, Dense Net 201 and EfficientNet-B0—using transfer learning. We preprocessed the lung CT images by resizing, normalizing and augmenting them to enhance the …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 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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AI-Enabled Voice-Interactive Smart Helmet For Two- Wheeler Road Safety
Abstract: The goal of this project is to improve rider safety through voice-controlled vehicle operations, automated emergency response, and real-time monitoring by designing and implementing a smart helmet system. The system continuously monitors motion and abrupt impact variations using an accelerometer (MPU6050) to identify accidents based on predetermined threshold values. When a fall or unusual impact is detected, a GSM module is triggered to send emergency alerts and location information to …
Published in Journal of Microcontroller Engineering and Applications · Vol. 13, Issue 2, 2026 Read article
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Framework-Based Optimization of Catalysis Efficiency through Reaction Pathway Engineering
Abstract: The rational design of heterogeneous catalysts through framework-based approaches has emerged as a transformative strategy for controlling reaction pathways and enhancing catalytic efficiency. This paper examines recent advances in the optimization of catalytic performance through engineered frameworks, including metal-organic frameworks (MOFs), zeolites, and related porous materials. By integrating computational methods with experimental validation, researchers have achieved unprecedented control overactive site architecture, reactant confinement, and elementary reaction steps. This work reviews …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 2, 2026 · pp. 88–99 Read article