The proceedings contain 245 papers. The topics discussed include: developing an advanced tool for transforming spreadsheet data into interactive dashboards with predictive insights;smart education ecosystems for enhan...
ISBN:
(纸本)9798331541217
The proceedings contain 245 papers. The topics discussed include: developing an advanced tool for transforming spreadsheet data into interactive dashboards with predictive insights;smart education ecosystems for enhancing learning experiences through deep attention learning and artificial intelligence;recent innovations in patch antenna technology for wearable biomedical devices;wine quality prediction using machinelearning techniques;data analytics and artificial intelligence for improving employee retention strategies;hybrid steganographic and encryption approach using color analysis for secure image communication;a robotic arm vehicle using voice recognition for physically challenged people;artificial intelligence based plant disease detection system;comprehensive review for video surveillance based suspicious human activity detection;edge computing in smart cities: enhancing real-time data processing;a comprehensive analysis of various federated learning techniques;cardiovascular disease prediction implementing artificial intelligence andmachinelearning approaches;andsignalprocessing techniques for enhanced wireless network performance.
For network traffic, how to distinguish malicious traffic from normal traffic is very important. To this end, we introduce deep learning as a powerful tool for malicious traffic detection, and its excellent learning a...
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Peak detection is a facile wing of signalprocessing. Conventional peak detection algorithms detect peaks when the entire signal is made available to them. In contrast, we propose a method that is based on recognizing...
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ISBN:
(纸本)9781509052561
Peak detection is a facile wing of signalprocessing. Conventional peak detection algorithms detect peaks when the entire signal is made available to them. In contrast, we propose a method that is based on recognizing the fundamental shapes of a signal, and the overall method intuitive in nature. Towards this, we use a feedforward neural network that is trained using the online sequential learning algorithm which provides better convergence performance relative to the back propagation algorithm. Moreover, the training avoids complex pre-processing tasks and feature extraction. Most importantly, the entire signal is not required for the algorithm to detect the peaks.
Autism Spectrum Disorder (ASD) diagnosis is difficult due to its complex and diverse symptomatology. This study focuses on using machinelearning, specifically the Random Forest algorithm, to identify ASD. We use a la...
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The proceedings contain 16 papers. The topics discussed include: self-supervised visual odometry with ego-motion sampling;pneumonia detection on chest X-rays with attention mask data augmentation;validation feedback b...
ISBN:
(纸本)9781450388931
The proceedings contain 16 papers. The topics discussed include: self-supervised visual odometry with ego-motion sampling;pneumonia detection on chest X-rays with attention mask data augmentation;validation feedback based image transfer network for data augmentation;human action recognition using pre-trained convolutional neural networks;traffic sign and vehicle classification based on machinelearning;a computer-aided diagnosis system of breast lesion classification based on multi angle fusion strategy in ultrasound images;high capacity steganography on float-point number with single precision;the utilization of social media in learning accounting information systems;serious game: confined space rescue based on virtual reality technology;and scrum based framework for teaching software engineering for game development.
Disposable and reusable face masks represent one of the key personal protective equipment (PPE) against COVID19 pandemic and their use in public environments is mandatory in many countries. According to the intended u...
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ISBN:
(纸本)9781665401708
Disposable and reusable face masks represent one of the key personal protective equipment (PPE) against COVID19 pandemic and their use in public environments is mandatory in many countries. According to the intended use, there exist different types of masks with varying level of filtration. World Health Organization (WHO) has developed a set of best practices and guidelines to the correct use of this fundamental PPE. Nevertheless, many people tend to neglect wearing the mask in presence of other people and to unintentionally overuse the mask before replacement, which results in increased exposure to airborne infections. This paper proposes the development of a smart wearable computing system, consisting of a reusable face mask augmented with sensing elements and wireless connected to a personal mobile device, to recognize correct positioning of the face and capable to monitor other parameters such as usage time. Specifically, we realized a 3D printed mask prototype with replaceable filter and equipped with a small electronic embedded device. The mask collects internal and external parameters including humidity, temperature, volatile organic compounds (VOC) inside the mask, inertial motion, and external temperature and light. Collected data are transmitted over Bluetooth Low Energy to a smartphone responsible of performing signal pre-processing and position classification. Two machinelearning algorithms are compared and obtained results from real experiments showed SVM performed slightly better than Naive Bayes, 98% and 97% accuracy, respectively.
This paper aims to develop a machinelearning-based system for automatically detecting honey adulteration with sugar syrup, based on honey hyperspectral imaging data. First, the floral source of a honey sample is clas...
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The title is 'Rainfall Prediction Using machinelearning'. The initiative's dataset is written in Python and stored in Microsoft Excel. A wide range of machinelearning algorithms are used to discover whic...
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作者：
Sahu, BanditaDas, P.K.Kabat, M.R.VSSUT
Department of Computer Science and Engineering Burla Odisha India VSSUT
Department of Information and Technoogy Burla Odisha India
This paper provides a new approach of executing the twin robot operation with the application of classical Q-learning and improved Q-learning algorithm. This approach has significantly less space and time requirement ...
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Aiming at the problem of low detection rate caused by class imbalance and limited detection ability of single model in abnormal traffic detection, an abnormal traffic detection model based on hybrid sampling and deep ...
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