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231 articles for “Generational identification”
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Passive Digital Phenotyping for Longitudinal Burnout and Occupational Mental Health Surveillance: A Transformer-Based Explainable Deep Learning Approach Using Smartphone Behavioral Streams
Abstract: Occupational burnout constitutes a pervasive yet chronically under-surveilled public health threat, its insidious temporal evolution rendering episodic self-report instruments structurally inadequate for early detection. This paper introduces BurnoutSense, a passive digital phenotyping framework that continuously harvests eight heterogeneous smartphone behavioral data streams encompassing application usage ecology, communication metadata, geospatial mobility, screen interaction dynamics, inferred sleep rhythmicity, keystroke kinematics, ambient noise exposure, and battery/charging cadence to construct individualized multivariate behavioral signatures …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 · pp. 44–53 Read article
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Surveillance Car using ESP32 Cam Module by using GAN Model
Abstract: This paper shows the Surveillance Car system which leverages the ESP32 Cam module and incorporates advanced image processing through a Generative Adversarial Network (GAN) model to redefine the landscape of mobile surveillance systems. The ESP32 Cam serves as the core hardware platform, offering compact design and wireless capabilities for real-time image capture and remote monitoring. The system’s innovation lies in the integration of a GAN model for image processing, enhancing …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 2, 2024 · pp. 28–37 Read article
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Strengthening Low Voltage Ride-Through in Wind Energy Systems: A Comparative Study of DVR and STATCOM
Abstract: This study looks at the various methods used to improve the low-voltage ride-through (LVRT) capabilities of wind turbine systems (WT) that are based on double-fed induction generators (DFIG). The Type-III WT machine, which is mostly based on DFIG, is instantly connected to the grid without the digital power interface, making the terminal voltage or reactive electricity output unmanageable. This is because the world utilizes between 20% and 25% of renewable …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 47–62 Read article
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Preliminary Survey & Documentation of Wetland Macrophyte Diversity from Chargaon Lake in Warora Taluka, Dist. Chandrapur Maharashtra, India
Abstract: Wetland macrophytes are most diverse group of aquatic macroscopic Angiosperms that has great ecological influence on wetland ecosystem, plays significant role in every food chain operated in aquatic ecosystem. Present study site has a total catchment area of 14.83 thousand hectors constructed in the year 1983 mainly for irrigation practices to nearby villages. The aim of present study is to conduct preliminary survey followed by proper documentation of floral diversity …
Published in Research & Reviews : Journal of Botany · Vol. 15, Issue 1, 2026 · pp. 1–7 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
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Sustainable Learning and Education
Abstract: Sustainable learning asnd education are approaches to learning that prioritize environmental stewardship, social equity, and economic prosperity. A comprehensive approach to education, sustainable learning and education acknowledges the interdependence of social, economic, and environmental systems. Rather than treating these aspects in isolation, sustainable education integrates them to foster a comprehensive understanding of sustainability issues. Sustainable education places a strong emphasis on systems thinking, which entails comprehending the feedback loops and …
Published in International Journal of Sustainability · Vol. 1, Issue 2, 2024 · pp. 15–19 Read article
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Comparative Study of Structural and Optical Properties of Bismuth Ferrite Nanoparticles for Photovoltaic Applications Synthesized via Different Sol-Gel Methods
Abstract: Pure multiferroic bismuth ferrite (BiFeO3) nanoparticles were successfully synthesized using an energy-efficient, low-temperature sol-gel method, comparing two distinct approaches: auto-combustion and non-auto-combustion. To ensure phase stability, the precursor solution's pH was strictly maintained between 1 and 2 using ammonia solution (NH4OH), while ethylene glycol (C2H6O2) was employed as a chelating agent for the Fe3+ and Bi3+ cations. All samples underwent a final annealing process at 500 °C to promote crystallization. …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 1, 2026 · pp. 83–94 Read article
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Molecular Docking Evaluation of Cedrus deodara Secondary Metabolites as a Potent Anti-ovarian Cancer Agent
Abstract: Objective: According to the statistics for the year 2022 it was seen that cancer total cases is 14,61,427. After breast cancer, ovarian cancer is the second most frequent cancer among women. The estrogen receptor (PDB ID: 1X7E), progesterone receptor (PDB ID: 1A28), and Phosphoinositide 3-kinases (PDB ID: 4FJY) can be considered as target protein for ovarian cancer. The plant Cedrus deodara and its phytochemicals were chosen in this study to …
Published in International Journal of Molecular Biotechnological Research · Vol. 1, Issue 1, 2023 · pp. 77–93 Read article
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Revolutionizing Motorcycle Safety: A Deep Learning Approach for Helmet and Triple Riding Detection using Computer Vision Technology and Machine Learning Model
Abstract: Introducing a revolutionary paradigm in road safety, our project unveils the Intelligent Traffic Surveillance System (ITSS), a groundbreaking initiative poised to transform urban traffic management. In an era where road safety is paramount, ITSS emerges as a beacon of innovation, harnessing the prowess of computer vision and machine learning to tackle two of the most pressing concerns plaguing our roads: helmet non-compliance and triple riding among motorcyclists. At its core, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 28–36 Read article
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To Propose an Effective Process for Refurbishment Projects: through BIM
Abstract: Building refurbishments include enhancing, upgrading, renovating, retrofitting, and repairing existing structures. The construction sector considers it to be an important component. Building refurbishment projects are known for their high degree of complexity and uncertainty, which frequently incorporates elements like design changes and inadequate or unavailable information that may lead to various issues. Issues related to different stages of refurbishment projects were identified through literature and case studies. According to the …
Published in International Journal of Architectural Design and Planning Read article
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Enhancing ABET Summative Direct Assessment with AI and Blockchain: A Framework for Personalized Learning and Secure Evaluation
Abstract: Accreditation Board for Engineering and Technology (ABET) emphasizes the achievement of specific measurable learning outcomes. However, conventional assessment methods often find it challenging to accurately capture the complexities of student learning and program effectiveness within the ABET framework. This study proposes a novel framework that enhances ABET summative direct assessment by integrating a carefully structured, weighted assessment system with the transformative potential of artificial intelligence (AI) and blockchain technologies. The …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 28–42 Read article
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The Economic Importance of Art and Craft: Men as Artisans at Ranchi Cluster in Jharkhand State
Abstract: There is an inseparable relationship between Art, culture and civilization in India. As man Gradually developed, art also kept on developing along with his civilization. Be it the civilization of any country. Its emergence has been the result of human imagination. Art has always had a significant historical significance, transcended cultural borders and acted as a monument to humanity's inventiveness and imagination. Artists have risen throughout history as guardians of …
Published in Recent Trends in Social Studies · Vol. 1, Issue 2, 2024 · pp. 47–56 Read article
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Secure Forge: Deepfake Image Detection Using Vision Transformers
Abstract: Deepfake technologies have become a major risk to the credibility and trustworthiness of digital visual information. Using powerful generative models like GANs and autoencoders, deepfakes can generate highly realistic fake videos and images, resulting in misinformation, identity theft, and public loss of trust in digital media. Classic Convolutional Neural Networks (CNNs) while being highly effective in initial-stage, deepfake detection tend to be limited by their local receptive fields and dependency …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 32–45 Read article
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Design of Disturbance Observer for Third- Order Interval Plants
Abstract: This paper outlines the development of a disturbance observer (DOB) specifically tailored for third-order interval plants, which are distinguished by uncertainties in their parameters. Utilizing an interval-based modeling approach, this design effectively captures variations in system dynamics, providing robust control solutions for plants with parameter uncertainties. The key focus is creating a disturbance observer capable of real-time estimation and compensation for external disturbances and model uncertainties. The proposed DOB is …
Published in Trends in Electrical Engineering · Vol. 14, Issue 3, 2024 Read article
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The Role of Artificial Intelligence in Mental Health: Applications in Neurodegenerative Disorders
Abstract: Artificial intelligence (AI) has significantly changed many aspects of medical care, particularly the early evaluation, therapy, and management of neurodegenerative illnesses like Alzheimer's, disease, Parkinson's diseases, and Huntington's diseases. The current research explores the application of AI in mental health with respect to neurological disorders, especially advancements in cognitive examination, neuroimaging analysis, predictive modeling, and customized therapy modalities. Artificial intelligence (AI) systems have shown enormous potential in detecting minute biomarkers …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 3, 2025 · pp. 34–40 Read article
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AI-Assisted Optimization of Supersonic Airfoil Shapes Using CFD Coupling
Abstract: This paper presents a novel framework for optimizing supersonic airfoil geometries through integrated artificial intelligence and computational fluid dynamics coupling. Traditional gradient-based optimization methods for high-speed aerodynamic shapes suffer from computational expense and convergence difficulties in non-convex design spaces. The proposed methodology employs a deep neural network surrogate model trained on high-fidelity Reynolds-Averaged Navier-Stokes solutions to approximate aerodynamic performance metrics across the design space. A hybrid particle swarm-genetic algorithm searches …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 Read article
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DDoS Detection Using Cascade Correlation for Improving Network Resources in Cloud Environment
Abstract: Intrusion detection is critical for protecting network security from emerging cyber threats. This study describes a unique intrusion detection system (IDS) based on the Random Forest algorithm. Random Forests are used as an effective classifier to identify patterns linked with malevolent behaviour. This technique uses Random Forests to improve the accuracy and efficiency of intrusion detection systems. The suggested methodology's value is shown by its performance on the benchmark KDD …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 17–22 Read article
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Blockchain-Enabled Secure Data Sharing in Mobile IoT Networks
Abstract: The rapid proliferation of mobile Internet of Things (IoT) devices has resulted in an exponential increase in data generation, storage, and sharing, which poses significant challenges related to security, privacy, integrity, and trustworthiness. Traditional centralized architectures for IoT data exchange are inherently vulnerable to single points of failure, unauthorized access, data tampering, and limitations in scalability. Blockchain technology, with its decentralized ledger structure, cryptographic integrity, and consensus mechanisms, provides a …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 1, 2026 · pp. 38–44 Read article
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article