The proceedings contain 12 papers. The special focus in this conference is on Intelligent Edge Processing in the IoT Era, and Smart Governance for Sustainable Smart Cities. The topics include: Continuous Measurement o...
ISBN:
(纸本)9783031359811
The proceedings contain 12 papers. The special focus in this conference is on Intelligent Edge Processing in the IoT Era, and Smart Governance for Sustainable Smart Cities. The topics include: Continuous Measurement of Air Pollutant Concentrations in a Roadway Tunnel in Southern Italy;rating Urban Transport Services Quality Using a Sentiment Analysis Approach;edge Computing with Low-Cost Cameras for Object Detection in Smart Farming;Evaluating Maximum Operating Distance in COTS RFID TAGS for Smart Manufacturing;philippine Stock Direction Forecasting Utilizing Technical, Fundamental, and News Sentiment data;ioT Architectures for Indoor Radon Management: A Prospective Analysis;adversarial Training for Better Robustness;integrating Computer Vision and Crowd Sourcing to Infer Drug Use on Streets: A Case Study with 311 data in San Francisco;machinelearning Approach to Crisis Management Exercise Analysis: A Case Study in SURE Project;quantitative Evaluation of Saudi E-government Websites Using a Web Structure mining Methodology.
For aspect, a convolution Neural Network (CNN) for cardiac arrest would help establish a better output. Whilst a cardiac arrest occurs, the limited interventions available to shop-affected person's lives are relat...
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Aiming at the problem that it is difficult to accurately identify the mechanical fault of the transformer core, a method of transformer core mechanical fault diagnosis based on variational mode decomposition (VMD)-mul...
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Human activity recognition (HAR) and fall detection using smartphone sensors are currently popular because they can be extended to many useful applications especially when a person needs an urgent treatment such as a ...
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ISBN:
(数字)9781665457279
ISBN:
(纸本)9781665457279
Human activity recognition (HAR) and fall detection using smartphone sensors are currently popular because they can be extended to many useful applications especially when a person needs an urgent treatment such as a fall. Several methods based on machinelearning (ML) and deep learning (DL) have been proposed to improve classification performances. In this work, we propose hybrid models of convolutional neural network (CNN) models and ML algorithms to classify human activities and falls using smartphone-sensor data. The CNN model will be used as feature extraction to extract a set of features. Thereafter, the ML algorithm will apply this set of features to predict the corresponding activity and fall. Several combinations of CNN models and ML algorithms are investigated on two public datasets: UniMiB SHAR and UMAFall. Their accuracy scores are compared in order to determine the best hybrid model. On the UniMiB SHAR dataset, the hybrid model based on the AlexNet model and the extra trees algorithm achieves the highest accuracy score of 95.27%. On the UMAFall dataset, the hybrid model based on the Xception model and the support vector machine/k-nearest neighbors/extra trees algorithms offer the highest accuracy score of 82.24%.
We proposes a new kind of contrast learning method based on Temporal-Correlation characters of electroencephalogram (EEG) used in sleep staging. This method, called simple framework of temporal-correlation representat...
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Now, a day's Crime in every country is increasing day by day. Generally, Every day we listen to the news of different crimes of different categories like rape, assault, Kidnapping ,Robbery ,ATM Theft, Murders etc ...
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Wearable sensors and social networking sites help gather participant information for healthcare monitoring. Wearable sensors generate a lot of healthcare data for continuous patient monitoring. Social networking sites...
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Palm-vein recognition has garnered significant attention recently due to its superior privacy and safety features. However, the public dataset for palm-vein is much less. Moreover, manually collecting palm-vein data f...
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Traditionally, many people still wish to write on pen and paper. However, it has some drawbacks, like accessing and storing physical documents efficiently, searching through them, and sharing them efficiently. Handwri...
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Quantum computing shows immense potential for solving traditional, near to impossible, complex problems. It also shows how the performance and speed can be improved for the solution of existing classical problems by u...
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