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438 articles for “Detection Techniques”
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Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
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Bank Locker Security System Using Machine Learning
Abstract: The Bank Locker Security System integrates cutting-edge technology solutions to strengthen the security of bank locker facilities. This system uses biometric identification techniques, such as facial recognition and fingerprint scanning, to confirm users' identities before granting them access to the lockers. Furthermore, access control techniques based on RFID technology are employed to augment security protocols. The locker area is equipped with real-time monitoring and alerting tools that enable fast detection …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 16–20 Read article
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Awareness Regarding Cervical Cancer among Women Attending a Selected Hospital in Lucknow, Uttar Pradesh: A Cross-Sectional Study.
Abstract: Cervical cancer continues to be a significant health concern, particularly in low- and middle-income countries like India, where it remains a leading cause of cancer-related deaths among women. Despite the availability of preventive measures such as the Human Papillomavirus (HPV) vaccine and screening techniques like Pap smears, a considerable gap in awareness persists. Limited knowledge of cervical cancer, its risk factors, symptoms, and preventive strategies hampers the effectiveness of early …
Published in International Journal of Women's Health Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 19–24 Read article
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U-Net Based Approach for Automated Brain Tumor Classification
Abstract: Brain tumor detection and identification play vital roles in diagnostic procedures in the field of medicine, with the conventional analysis of MRI images requiring a lot of time and also subject to variability. The proposed study involves the use of a CNN-U-Net based approach for brain tumor detection and identification automatically. The study uses a database of 3,064 contrast-enhanced T1-weighted MRI images from 233 patients with the tumors of meningioma, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Molecular and Immunological Study for The Relationship of CMV in Miscarriage in Women with a History of Repeated Abortion in Najaf Governorate
Abstract: The study was conducted in Al-Zahra Hospital for Maternity and Children in Najaf Governorate for the period from 1/8/2024 to 1/1/2025., The stream study directed to establish the occurrence of CMV infectivity in women who experienced of continual miscarriage and perform a analyze of the amount of miscarriage situations arising in the Najaf governorate. The study was divided into two parts. The first part was aiming to determine the frequency …
Published in Research and Reviews : A Journal of Immunology · Vol. 16, Issue 2, 2026 · pp. 1–8 Read article
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Performance Analysis of Space Shift Keying and Quadrature Space Shift Keying for MIMO Channels
Abstract: In wireless communication the propagation channel is characterized by multipath propagation due to scattering on different obstacles. MIMO takes advantage of multi-path and uses multiple antennas to send multiple parallel signals from transmitter. “Multi-path” occurs when different signals arrive at the receiver at various times. MIMO exploits the space dimension to improve wireless systems capacity, range and reliability. There are two different modulation techniques that exploits the best features of …
Published in Research & Reviews : Journal of Space Science & Technology Read article
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Smart and adaptive cutting-edge IoT based implementation for remote environments
Abstract: In remote, mountainous, or snow-covered regions, mobile networks and GPS signals usually become unreliable, which creates major challenges for search and rescue (SAR) operations. To overcome the issue, this paper presents a compact, low-power, voice-activated wearable device that integrates LoRa communication with a TinyML-based keyword detection system. The proposed device enables individuals to send signals in areas where GPS coverage is unavailable. Using the Received Signal Strength Indicator (RSSI), the …
Published in Journal of Microcontroller Engineering and Applications · Vol. 13, Issue 2, 2026 Read article
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Applying Text Analysis Methods for Emotion Recognition
Abstract: This article presents a comprehensive study of sentiment analysis, a vital task in the realms of natural language processing (NLP) and artificial intelligence (AI). Sentiment analysis involves the extraction and classification of subjective information from textual data, determining whether the sentiment expressed is positive or negative. This paper investigates different approaches and methodologies used in sentiment analysis, encompassing machine learning models as well. Additionally, it discusses the challenges faced in …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 2, 2024 · pp. 12–22 Read article
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Cytogenotoxicity Assessment of Asphalt Plant Discharge Water using Plant Assay
Abstract: The Allium cepa assay test was used to evaluate cytogenotoxic effects of asphalt plant discharge water at the concentrations of 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100% (v/v) asphalt plant discharge water/distilled water. The distilled water served as the negative control. The analysis of the physicochemical properties and heavy metals concentrations showed that most parameters were higher than the established standards of WHO and FMENV. The …
Published in Journal of Water Pollution & Purification Research · Vol. 12, Issue 3, 2025 · pp. 100–110 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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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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Deep Learning for Real-Time Monitoring and Defect Detection in Additive Manufactured Polymer Composites
Abstract: Additives Fiber-reinforced polymer composite ADDs have high utility in making lightweight structural components, but due to process-related defects (interlayer delamination and reinforcement stacking) the integrity of consolidation during extrusion-based deposition is frequently compromised. This paper has presented a physics-informed deep learning framework that is applicable to real-time measurements of reinforced thermoplastic composite fabrication. Multimodal sensing was provided with thermal gradient, optical morphology, and acoustics emission signals being used to assess …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 974–999 Read article
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Design and Development of Screw Detection System : A case study
Abstract: This study explores the design of a vision-based screw detection and orientation system for industrial automation, inspection, and robot disassembly. By integrating machine learning algorithms like region-based convolutional neural networks (R-CNN) with traditional image processing and impedance sensing, the system performs real-time screw presence detection, head type identification, and alignment. Three key technologies—deep learning classification, edge-based geometric analysis, and impedance verification—are integrated into a single modular system. The findings indicate …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 30–36 Read article
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Innovative Approaches to Luminescence: Exciton-Polariton Lasers and Quantum Confinement in 2D Materials
Abstract: The phenomenon known as luminescence occurs when an external energy of any kind excites a substance's electronic state, and the excited energy is released as light. Luminescence is the absence of heat produced by light emission. Luminescence comes in a variety of forms, including thermoluminescence, bioluminescence, and chemiluminescence. Examples of luminescence include flat-screen TVs, LED lights, and bioluminescent phytoplankton. The measurement of the emission spectrum produced when previously excited atoms …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 2, Issue 1, 2024 · pp. 26–33 Read article
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Employment of Solid-State Technology in Sensor Design: A Study
Abstract: The rapid evolution of sensor technologies has been driven by the demand for more precise, durable, and compact systems to meet the needs of modern industries, healthcare, and consumer electronics. Solid state technologies have emerged as a transformative force in sensor design, offering unprecedented performance, reliability, and integration potential. Unlike traditional sensors, which often rely on mechanical, electrochemical, or piezoelectric principles, solid state sensors leverage the intrinsic properties of materials …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 31–41 Read article
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Enhancing Smart Grid Resilience Through AI-Based Fault Classification
Abstract: Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation. This dynamic improves energy efficiency and the integration of renewables. Well, the dynamic and reversible power injection from Distributed Energy Resources (DERs) creates substantial operational problems. These …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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Smart Vehicle Security System Using Fingerprint Authentication with Alcohol Detection
Abstract: An electronic device is installed in a car or fleet of vehicles as part of a vehicle tracking system, which allows the owner or a third party to follow the whereabouts of the vehicle while also gathering data. The technology known as a modern vehicle tracking system (VTS) uses a variety of techniques, including GPS and GSM modules as well as other radio navigation systems that employ satellites and ground-based …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 1, 2024 Read article
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Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks
Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article
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Depiction-inspired Recipe Generator Using Deep Learning
Abstract: Machine learning has become a crucial part of modern life, influencing various domains. Its applications range from enhancing data-driven business decisions to enabling autonomous vehicles. Advances in machine learning have brought about notable changes in how we interact with technology. In the culinary world, the idea of creating food recipes from images has gained increasing interest. This entails the development of innovative systems that seamlessly convert visual input, such as …
Published in Journal of Open Source Developments · Vol. 11, Issue 2, 2024 · pp. 47–55 Read article
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Enhancing Profanity Detection in Dravidian Languages: Leveraging Language Models for Optimization and Improvement
Abstract: Detecting and documenting instances of abusive behaviour can significantly improve the quality of virtual environments. Given the vast amount of content published daily on social media, it is impractical for human annotators to manually identify potentially harmful content. Recent algorithmic initiatives, especially on platforms like Twitter, have advanced in abuse detection. However, for Dravidian texts, there remains a need to understand the context better and build robust language models for …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 17–23 Read article