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1987 articles for “Lap Splice Detection” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Forest Fire Early Detection and Online Remote Monitoring Using Sensors
Abstract: Forest fire device networks represent a strong technology, particularly appropriate for environmental observation. With relation to wildfires, above all, they permit low-priced police work of venturesome locations like wild land urban interfaces. This report presents the work developed throughout the last 4 years targeting a fire device network node for the reliable, on-site detection of forest fires. The tasks dispensed ranged from detective work or sensing of conditions that rise …
Published in Journal of Industrial Safety Engineering · Vol. 9, Issue 1, 2022 · pp. 16–20 Read article
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Design of Digital Frequency Sensitive Phase Detector and study its Phase Response
Abstract: In this paper, a digital frequency sensitive phase detector (PD) with voltage controlled phase response is presented. This scheme is based on classical type flip-flop phase detectors and an improved PD operating on both edges of the input sequence. Phase-to-voltage response characteristic control is accomplished by the additional feedback of the low-pass filter output voltage to reset the control pin input. In this paper, we have presented a simulated frequency …
Published in Journal of Microwave Engineering and Technologies · Vol. 8, Issue 3, 2021 · pp. 43–51 Read article
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Convolution Neural Network Model for Intrusion Detection in Network
Abstract: The evolution of the internet has made protecting information a necessity. Network intrusion and prevention plays an integral role in network-based security. The Intrusion technologies primarily used in today’s world deploy various machine learning algorithms and train models based on them resulting in effectively low detection rates. A technical advancement from machine learning, Deep Learning employs complex mechanisms to extract features from samples. As observed that conventional intrusion detection systems …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 8, Issue 1, 2021 · pp. 7–13 Read article
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Traffic Sign Detection and Recognition Using Deep learning based- Convolutional Neural Network Algorithm
Abstract: The concept of Deep Convolutional Neural Organizations (CNNs) is a quickly arising new zone for Automatic traffic sign detection and recognition among the few master frameworks, such as independent driving and driver assistance. Here, in this paper, for traffic sign detection, we have utilized another methodology that uses a newly developed identification calculation and an RGB-based tone thresholding procedure. Results of the proposed identification and acknowledgement approaches are assessed on …
Published in Recent Trends in Electronics Communication Systems · Vol. 8, Issue 1, 2021 · pp. 24–29 Read article
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Heterogeneous Spectrum Sensing in Cognitive Radio Network using Enhanced Energy Detection and Matched Filter
Abstract: AbstractOne of the most predominant aspect in cognitive radio networks is spectrum sensing which allows a secondary user (unlicensed user) to detect the presence or absence of a primary user (licensed user). A number of sensing techniques have been proposed in the past. In order to achieve a high spectrum efficiency, the compatibility of the common spectrum detection techniques primarily used such as energy detection and matched filter are employed …
Published in Trends in Opto-electro & Optical Communication · Vol. 7, Issue 3, 2017 · pp. 35–42 Read article
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Crop Health Monitoring and Weed Detection Using Drone Technology
Abstract: In an agriculture-based economy like ours, farmers and their cultivation play a significant role. With the extension of agriculture to wider fields, manual interference to monitor and detect crop health is becoming more difficult. Unmanned aerial vehicles (UAVs) have become well-known and affordable technology for a variety of precision farm uses in recent years. Combining the capabilities of drone technology and machine learning/deep learning algorithms, we can monitor crop health …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 1–8 Read article
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Towards a Machine Learning Oriented Expert System for Intrusion Detection Model
Abstract: AbstractIn this paper, we describe the possibility of using machine learning and expert system for constructing a new intrusion detection model. The first main idea is to construct the classifier on the KDD intrusion data using a machine learning algorithm. For constructing the classifier J48 decision tree machine learning algorithm is used. The other key idea is to collect domain expert knowledge, and building an expert system to interpret and …
Published in Journal Of Network security · Vol. 8, Issue 3, 2020 · pp. 24–30 Read article
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Face Recognition or Detection using Image Processing and How Image will be Process Age Wise
Abstract: Biological feature popularity is a type of identification era that uses the person’s special mindset or behavior feature. It furnished of excessive accuracy, accurate balance technique to status prizing. Face reputation is very famous wing of the organic aspect popularity. And also, is very energetic situation in the range of laptop view and pattern popularity. Face detection is technique to hit upon face from a picture which have numerous aspects …
Published in Research and Reviews : Journal of Computational Biology · Vol. 10, Issue 2, 2021 · pp. 10–15 Read article
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Detection of Tannerella Forsythia by Pocket-out Method in Chronic Periodontitis Patients
Abstract: The outcome of microbiological diagnostics may depend upon the sampling techniques. The aim of the study was to detect using polymerase chain reaction (PCR), the presence of Tannerella forsythia (T. forsythia) in chronic periodontitis patients by pocket-out sampling technique, to compare the pocket-out and curette method as sampling techniques for detection of T. forsythia in chronic periodontitis patients using PCR. A total of 27 adult patients, 30–65 years of age …
Published in Research and Reviews: A Journal of Dentistry · Vol. 7, Issue 1, 2016 · pp. 1–6 Read article
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Role of Diagnostic Laparoscopy in Chronic Abdominal Pain and Its Therapeutic Value
Abstract: The aim of this study was to evaluate and establish the role of diagnostic laparoscopy in unexplained chronic abdominal pain and its therapeutic value. Diagnostic laparoscopy apart from visualizing the entire abdominal cavity, allows us to take precise biopsy. Laparoscopy also offers therapeutic solutions for multiple reasons of abdominal pain. The study covered 110 patients with history suggestive of chronic abdominal pain for 3 months or more duration, undiagnosed despite …
Published in Research and Reviews : Journal of Surgery · Vol. 7, Issue 3, 2018 · pp. 16–20 Read article
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Multi Face Detection and Gender Classification Based Attendance System
Abstract: Time management is critical in today's hectic classroom, and keeping track of attendance can take up valuable class time. Utilizing technologies like facial recognition and detection can greatly expedite this procedure. While face recognition algorithms compare the detected faces with known faces kept in a database, face detection algorithms can recognize human faces within a group photo or video stream. Without the need for human interaction, teachers can effectively record …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 1, 2024 · pp. 1–7 Read article
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Sentinels of Safety: A Robotic Revolution in Autonomous Landmine Detection for Humanitarian Resilience
Abstract: Landmine Detection Robotic Vehicle Project is to create an autonomous robotic system that can identify landmines in dangerous locations. The rover navigates through a variety of terrains by using modern sensor technology, such as metal detectors and infrared photography, to detect buried landmines. The rover can distinguish between potentially dangerous items and harmless ones. The principal aim of the project is to optimise the efficacy and security of landmine removal …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 28–34 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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Efficient Malware Detection in Cybersecurity: Leveraging Advanced Data Structures for Enhanced Threat Identification
Abstract: The cybersecurity landscape is constantly changing with more advanced malware creating major challenges for detection systems. To address these challenges effectively, advanced data structures have become essential in optimizing how data is managed, processed, and analyzed for malware detection. This review paper delves into the role of several cutting-edge data structures—bloom filters, tries, hash tables, graphs, decision trees, and suffix trees—in enhancing the efficiency and accuracy of malware detection mechanisms. …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 32–40 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 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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Intelligent Aquaculture System for Fish Disease Detection Using Machine Learning
Abstract: Aquaculture is one of the key factors for global food security, but fish diseases bring about heavy economic losses and jeopardize sustainability. One of the most important aspects of global food security is aquaculture, but fish infections endanger sustainability and cause significant financial losses. Early diagnosis is not possible since traditional disease detection techniques are laborious and necessitate expert intervention. To effectively detect fish infections, this study suggests an Intelligent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 30–37 Read article
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Smart Detection of Wild Animals in Residential Area
Abstract: In recent years, wild animals have been increasingly spotted in residential areas, posing risks to both humans and animals. The presence of these animals can cause accidents, damage to property, or even harm to the animals themselves. Therefore, it is important to have an effective method to detect wild animals in residential areas and ensure safety for everyone involved. This research focuses on creating a smart detection system that can …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 44–50 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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Automated Car License Plate Detection and Recognition Using Deep Learning
Abstract: The use of automated license plate detection and recognition (ALPR) systems to automate processes such as number plate detection is gaining popularity in traffic control, security, and law enforcement. This research focuses on achieving more accurate and efficient detection and recognition of number plates by leveraging deep learning techniques. The systems outlined in this study aim to improve the effectiveness of ALPR systems using advanced convolutional neural networks (CNNs) and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 23–29 Read article