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334 articles for “feature based model”
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Predictive Modeling of Polymer Composites for Medical Implants Using Artificial Intelligence Techniques
Abstract: The use of polymers in biomaterials was now key to designing the next generation of medical implants, which need to be strong and also compatible with living tissue. Tests for biocompatibility, such as those done in the laboratory and by doing experiments on animals, require much time and many resources, so the need for computer-based approaches becomes clear. An artificial intelligence approach was provided in this study to determine how …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 665–692 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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Virtual Reality Based Decentralized Educational Art Gallery
Abstract: One can experience the forefront of education by engaging with our virtual reality (VR) powered decentralized educational art gallery. This groundbreaking platform seamlessly integrates VR technology with decentralized networks, crafting an unmatched learning journey. Curated collections of art from diverse cultures and eras can be explored, accompanied by interactive educational modules that deepen one’s understanding of each piece. One can engage with fellow learners in real time, fostering collaboration and …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 31–37 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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Skin Cancer Detection System Based on Machine Learning for Recognition of Cancerous Images
Abstract: Skin cancer ranks among the most prevalent types of cancer globally and poses significant risks when left untreated. Skin cancer arises when abnormal cells proliferate uncontrollably in the skin. This uncontrolled growth can be triggered by genetic mutations, exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds, or various other factors. In this, the early detection of cancer plays a crucial role in treatment and …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Recognition of Thyroid Nodules Using Hierarchical Temporal Awareness Networking Scanning
Abstract: Contrast-enhanced ultrasonography (CEUS), a preferred imaging technique for thyroid nodule diagnosis, is able to reveal the vascular distribution within a thyroid nodule right away. With the aim of mining pathologically-related enhancing dynamics and creating predictions in one step without taking into account a native diagnostic dependency, a number of learning-based algorithms have recently been created. In clinics, separating benign from malignant nodules is always done before identifying pathological types. In …
Published in Trends in Opto-electro & Optical Communication · Vol. 12, Issue 2, 2022 · pp. 31–35 Read article
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Voting Based Classification Method for COVID-19 Prediction
Abstract: COVID-19 dataset comprises date, country, confirmed cases, recovered cases and total deaths. The data is integrated with climate data consisting of humidity, dew, ozone, perception, maximum temperature, minimum temperature, and UV. The artificial intelligence based COVID-19 diagnosis strategies can generate more accurate results, save radiologist time, and make the diagnosis process cheaper and faster than the usual laboratory techniques. The COVID-19 detection has various phases which include pre-processing, feature extraction, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 2, 2021 · pp. 34–41 Read article
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Energy harnessing solution using a vertical axis wind turbine installed on the automotive rooftop.
Abstract: The transportation sector plays a major role in greenhouse gas emissions, prompting worldwide initiatives to mitigate its environmental effects. While the shift from internal combustion engines to electric vehicles is growing, it often merely shifts emissions rather than eliminating them, as fossil fuels continue to dominate energy production. A comprehensive solution requires universal access to renewable energy sources like wind, solar, and hydro power, which is currently impractical due to …
Published in Journal of Automobile Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 1–21 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Arduino-Based Automatic Safety Vehicle Control
Abstract: Vehicle accidents due to various movements while driving is reduced using an arduino microcontroller, an automatic vehicle human-voice-based safety control is proposed in this paper. One of the most important safety control features is the automotive speed control (ASC) which prevents a vehicle sudden hit, the required action is taken based on the vehicle-to vehicle distance. In addition to this, several other automated safety control operations are provided (i.e., radio, …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 6, Issue 2, 2018 · pp. 11–17 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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Fortifying the Cloud: AI-Driven Security Paradigms and Evolving Threat Defenses in Modern Cloud Computing
Abstract: Organizations worldwide are raising their concerns about security maintenance while cloud computing expands rapidly to serve as a digital transformation foundation. The study explores modern cloud security patterns while also evaluating how artificial intelligence modifies the identification and evaluation of complex cyber threats along with their prevention methods. New security threats such as insider operations and DDoS attacks and data breaches alongside insecure APIs can be detected through machine learning …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
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An Evolution of the Pixel Embedding Techniques in Image Based Adaptive Steganography
Abstract: The word “Steganography” was basically derived from the Greek words with the meaning “covered writing.” This paper presents some of the main adaptive image steganography approaches. Many algorithms have been presented; in almost all the algorithms the approach is to embed the secret data in the images. Here we are discussing about adaptive steganography which is based upon spatial domain and frequency domain with an additional layer of mathematical model. …
Published in Journal of Web Engineering & Technology · Vol. 1, Issue 1, 2014 · pp. 1–18 Read article
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Study of Smart Device Based on Client–Server Communication on Linux using Socket Programming in ‘C’
Abstract: AbstractSmart device is an intelligent hardware that has more smart features. When a normal hardware is implementing on IOT, then a new hardware is developed in the form of smart hardware. When smart hardware is connected to a secure operating system as Linux, the hardware is more secure, then hardware is known as smart device. The mainly four components of Linux as utility, shell programming, kernel and hardware for develop …
Published in Journal of Advances in Shell Programming · Vol. 7, Issue 3, 2020 · pp. 11–15 Read article
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Electronics and Communication Design of an AI-Powered Smart Chair for Real-Time Multilingual Interaction
Abstract: Revolutionizing the passive listening experience, a smart chair designed for presentation attendees goes far beyond mere cushioning, dynamically adapting to individual posture and offering ergonomic support to combat fatigue during lengthy sessions. Equipped with integrated sensors, these intelligent seats can subtly prompt listeners to adjust their position for optimal comfort and focus, sometimes even providing gentle haptic feedback for key takeaways or to signal important transitions in the presentation. Furthermore, …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 16–29 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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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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Quantitative Image-Based Assessment of Degradation Patterns in Polymer-Based Medical Implants
Abstract: Polymer-based medical devices are widely used in clinical practice, where long-term material degradation can compromise performance and patient safety. Traditional polymer degradation studies predominantly rely on laboratory-based experiments, which often fail to capture real-world operational and usage conditions. In this study, a multimodal, data-driven framework is proposed for the quantitative assessment of degradation patterns in polymer-based medical devices using publicly available clinical failure data. Structured operational parameters, including cumulative usage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1510–1518 Read article
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Triangular Waveform Generation using Mixed Signal Modeling
Abstract: The development of modeling languages such as Verilog-HDL and Verilog-AMS allows the behavior of analogue and mixed signal circuits to be described with a more lucid way as compared to the conventional circuit-level simulators. Mixed-signal simulators are thus providing a new platform for more efficient modeling of mixed signal that contains both the analogue and discrete features which was not previously possible. The non-linear characteristics of many circuits are still …
Published in Journal of VLSI Design Tools and Technology · Vol. 4, Issue 2, 2014 · pp. 8–17 Read article
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Classification and Prediction of Weather Forecasting Dataset by using Artificial Neural Network
Abstract: Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 In the growing field of technology, wireless medium is playing a very important role. In this survey paper, different models which were used in the past for weather forecasting are discussed. In today’s Internet Technology, one of the most interesting model for accessing of various features. It shows how different models are important for different purposes. As it can be seen …
Published in Journal of Remote Sensing & GIS · Vol. 2, Issue 2, 2011 · pp. 1–4 Read article