Fatigue, Drowsiness, Sluggishness, Exhaustion, and Weariness are important problems in our day-to-day life because our life is becoming so hectic, and tiresome Due to the change in our sleep cycle and Work cycle chang...
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Fatigue, Drowsiness, Sluggishness, Exhaustion, and Weariness are important problems in our day-to-day life because our life is becoming so hectic, and tiresome Due to the change in our sleep cycle and Work cycle changes. So this paper introduces a new efficient and practical method,the use of machinelearning methods, especially the Haar algorithm, allows the development of complex systems that can accurately identify and evaluate the symptoms of fatigue and human fatigue, thus contributing to the improvement of safety and well-being in various environments. The Haar algorithm is designed for object detection and is suitable for analyzing faces and patterns to identify signs of fatigue and exhaustion in humans. This really helps in many areas such as transportation, health and occupational safety. The Approach will involve capturing live images or videos of people and processing them through a Haar-based algorithm to identify key facial features such as eye-aspect ratio, lowering of eyebrows, yawning, and slow facial movements. We use a machinelearning algorithm to identify faces and train the algorithm using a convolutional neural network (CNN), which is used to recognize facial patterns and measure the level of fatigue or exhaustion. This research contributes to solving safety and health issues in situations where fatigue can pose a serious risk, and helps develop interventions to prevent people from reporting their vulnerability.
This study explores the pivotal role of machinelearning models in predicting genetic diseases, revolutionizing the landscape of genomic medicine. Genetic diseases, often arising from mutations in DNA sequences, pose ...
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Alzheimer's disease is one of the neurodegenerative *** the symptoms are initially mild, they gradually worsen over *** there is no cure for the disease, Alzheimer's disease is one of the most challenging *** ...
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The usage of online entertainment has increased dramatically after some time with the enhancement of the Internet and has turned into the most compelling systems administration stage in this century. Notwithstanding, ...
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Planning and managing a power grid relies heavily on accurate predictions of future load. Operational choices involving resource utilization, infrastructural management, implementation schedule planning, investment pl...
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In the competition of modern marketing, it is highly important to foresee the correct personality profiles of customers because this may further improve the result of marketing campaigns. Therefore, in this research, ...
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Object recognition algorithms need to be very accurate and efficient in order for autonomous navigation systems to see and securely interact with their surroundings. Although conventional computer vision techniques ha...
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Artificial intelligence (AI) and its subset, machinelearning (ML), are growing in acceptance within the space *** days, autonomous navigation, spacecraft health monitoring, and operational management of satellite con...
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Diabetes is the serious and widespread disease worldwide. Common ingredients in modern diets, like sugar and fat, increase the risk of diabetes. Recognizing the symptoms is essential to predict and prevent the disease...
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Safety assurance is paramount across industries where mission-critical systems operate, mitigating risks of catastrophic failures. Safety cases play a pivotal role, particularly in safety critical systems (e.g., auton...
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ISBN:
(纸本)9798350395525;9798350395518
Safety assurance is paramount across industries where mission-critical systems operate, mitigating risks of catastrophic failures. Safety cases play a pivotal role, particularly in safety critical systems (e.g., autonomous vehicles), in ensuring system reliability and acceptability, providing a structured argument supported by evidence. However, in the safety case literature, it is challenging to get access to a complete safety case, which is crucial for the research community to contribute in this domain. Hence, in this research, we propose an approach to create a safety case for ML-enabled autonomous vehicle, specifically, the Quanser Qcar. We present a complete safety case for a reinforcement learning algorithm applied on the Quanser Qcar to avoid collisions in an unsignalized 4-way intersection. Finally, we report the lessons learned and provide the safety case for the research community to reuse.
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