Natural disasters like earthquakes have a profound and a wide-ranging effect on infrastructure, economic systems, and communities across the world. Accurately estimating an earthquake's 'level of impact' i...
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Accurately predicting long-term crop yield trends remains a crucial challenge in optimizing agricultural practices and ensuring food security. This paper proposes a novel framework that merges real-time data acquired ...
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one of the features of intelligent e-learning environments is the presence of a personalized mechanism to assist the effective learning for each learner. Exploiting personalized tutoring models, learners can experienc...
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ISBN:
(纸本)9798350387704
one of the features of intelligent e-learning environments is the presence of a personalized mechanism to assist the effective learning for each learner. Exploiting personalized tutoring models, learners can experience successful and satisfying learning outcomes due to their learning objectives. In this way, the learner (student) feels that there is always an aware and insightful tutor (teacher) alongside, providing private guidance on the learning path. While personalizing the learning environment is highly desirable, the continuous monitoring of the virtual teacher may lead to fatigue (and even disillusionment) for the learner, potentially reducing the efficiency of the e-learning environment. Considering the above points, in this article an intelligent system has been designed to identify fatigue in learners by examining changes in their facial expressions. To achieve this, a combination of eye and mouth features of the learner is utilized, and with the help of a deep neural network, the level of learner fatigue is detected. The proposed system employs the MediaPipe algorithm for face and eye-mouth feature identification, and for training the neural network model, the EfficientNet neural network has been utilized. In this system, databases NITYMED and DrowsinessDetection have been utilized for training the network. Additionally, 80% of dataset has been used for training and the remaining 20% for testing. It is worth mentioning that given the balanced distribution of samples for each class, accuracy is employed as the evaluation metric, considering the objective of minimizing false positives. The experimental results show the accuracy and precision of 99.73% and 99.72% for the eye model, respectively, and the same measures for the mouth model are 99.85% and 99.95%, respectively. The standard deviation value for the eye model is 0.4997, and for the mouth model, it is 0.4998, indicating that most of the data points are close to the mean. Additionally, the mean va
Technological advancements have resulted in a deluge of innovative activities, each requiring rigorous investigation and appraisal. The report recognizes the need for a centralized forum to address these limits by all...
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This study explores the utilization of Natural Language Processing (NLP) methods for analyzing documents in the legal field. More specifically, the study concentrates on summarizing legal documents and comparing their...
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Cloud computing is the most emerging technology. It has the capability to provide various services like infrastructure, security, data management, databases, and network over the internet. Several cloud service provid...
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The human-computer interaction (HCI) encompasses a variety of interactions, including gestural ones. In HCI, gesture recognition refers to nonverbal movements that can be utilized for communication. information can be...
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This study presents a Code Summarizer cum Explanation Tool which helps as the student specially those who are beginner in the world of coding to understand other's solution for a given problem statement. Our appro...
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In India, railways are a common and affordable mode of transportation, ranking as the fourth largest railway community worldwide. They serve as the primary means of passenger and long-distance travel, accounting for a...
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In Advanced Driver-Assistance Systems (ADAS) and automatic driving, it is important to accurately recognize objects around the vehicle. DETReg is one of the unsupervised pre-Training methods using Transformer, which i...
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