In behaviour recognition, the development of the DL （Deep Learning） method introduced massive improvements in the field of artificial intelligence, where DL represents an upgrade of the present ANN （artificial neur...In behaviour recognition, the development of the DL （Deep Learning） method introduced massive improvements in the field of artificial intelligence, where DL represents an upgrade of the present ANN （artificial neural network） architecture. Deep Learning as a comprehensive new field of artificial intelligence completely covers the neural networks architecture that is devised to carry out certain forms of identification, such as behaviour, forms of things, trends, similarities in complex forms, etc. Regarding thermography in energy, the cases used to illustrate this are photographs of active energy components in the plant. Failures that are seen with thermography cannot be recognized by other methods. However, an expert needs to do segmentation of focusing and classification of failures. The need for daily sampling and expert work is growing. With the DL method, it can be done in real time any time. One of the popular network architectures for using DL in image analysis is the recognition algorithm--CNN （convolution neural network）. Traditional artificial intelligence methods require determining factors and computations, leading to training algorithm. Machine learning has important features as welt as the right weight to make decisions about new input data. This work presents DL as a flexible and adaptive method for the analysis of thermal images of energy facilities, as well as a tool used for the construction and implementation of an efficient fault analysis on the 10/0.4 kV service transformer.展开更多
This research investigates the application of multisource data fusion using a Multi-Layer Perceptron (MLP) for Human Activity Recognition (HAR). The study integrates four distinct open-source datasets—WISDM, DaLiAc, ...This research investigates the application of multisource data fusion using a Multi-Layer Perceptron (MLP) for Human Activity Recognition (HAR). The study integrates four distinct open-source datasets—WISDM, DaLiAc, MotionSense, and PAMAP2—to develop a generalized MLP model for classifying six human activities. Performance analysis of the fused model for each dataset reveals accuracy rates of 95.83 for WISDM, 97 for DaLiAc, 94.65 for MotionSense, and 98.54 for PAMAP2. A comparative evaluation was conducted between the fused MLP model and the individual dataset models, with the latter tested on separate validation sets. The results indicate that the MLP model, trained on the fused dataset, exhibits superior performance relative to the models trained on individual datasets. This finding suggests that multisource data fusion significantly enhances the generalization and accuracy of HAR systems. The improved performance underscores the potential of integrating diverse data sources to create more robust and comprehensive models for activity recognition.展开更多
The use of an electrical probe is forned by whispering gallery modes(WGMs)of light within the coated microring circuits,in which the electrical signal is generated by trapped electron tunneling along the circular path...The use of an electrical probe is forned by whispering gallery modes(WGMs)of light within the coated microring circuits,in which the electrical signal is generated by trapped electron tunneling along the circular path of the coa ted microring circuit.The ollection of electrons is formed within the WGMs,where in this study,a modifed nonlinear microring resonator known as a PANDA ring resonator is coated by gold material and forms the mirroring circuit.The induced current(magnetic field)within the circuit occurs by the coupling ffects between trapped electrons and coated ring,which can penetrate into the brain cells and transform to the required signals via the terahertz carier for peychiatric investigations.The use of WGMs for 3D image construction using a PANDA conjugate mirror is also discussed,which is useful for thermal and imaging sensons.展开更多
A PANDA ring resonator circuit has been applied to the measurement of muscle actions,measuring signals created by facial muscle contractions.A system,which is called the Optical Muscle Sensing System,was developed whi...A PANDA ring resonator circuit has been applied to the measurement of muscle actions,measuring signals created by facial muscle contractions.A system,which is called the Optical Muscle Sensing System,was developed which uses sensors to measure the mechanism of facial muscle contractions and the strength of contraction and degrees of perturbation of the facial muscles that are used directly for each facial gesture.The signal data was obtained from the simulation of the facial gestures and this data was applied in the classification of the facial gesture signals of each particular gesture.Facial gestures include blinking,smiling,grimacing and various other contortions of the face which may imply emotions and are part of normal human communication.Understanding of these mechanisms will be useful and applicable to facial rehabilitation services.展开更多
文摘In behaviour recognition, the development of the DL （Deep Learning） method introduced massive improvements in the field of artificial intelligence, where DL represents an upgrade of the present ANN （artificial neural network） architecture. Deep Learning as a comprehensive new field of artificial intelligence completely covers the neural networks architecture that is devised to carry out certain forms of identification, such as behaviour, forms of things, trends, similarities in complex forms, etc. Regarding thermography in energy, the cases used to illustrate this are photographs of active energy components in the plant. Failures that are seen with thermography cannot be recognized by other methods. However, an expert needs to do segmentation of focusing and classification of failures. The need for daily sampling and expert work is growing. With the DL method, it can be done in real time any time. One of the popular network architectures for using DL in image analysis is the recognition algorithm--CNN （convolution neural network）. Traditional artificial intelligence methods require determining factors and computations, leading to training algorithm. Machine learning has important features as welt as the right weight to make decisions about new input data. This work presents DL as a flexible and adaptive method for the analysis of thermal images of energy facilities, as well as a tool used for the construction and implementation of an efficient fault analysis on the 10/0.4 kV service transformer.
基金supported by the Royal Golden Jubilee(RGJ)Ph.D.Programme(Grant No.PHD/0079/2561)through the National Research Council of Thailand(NRCT)and Thailand Research Fund(TRF).
文摘This research investigates the application of multisource data fusion using a Multi-Layer Perceptron (MLP) for Human Activity Recognition (HAR). The study integrates four distinct open-source datasets—WISDM, DaLiAc, MotionSense, and PAMAP2—to develop a generalized MLP model for classifying six human activities. Performance analysis of the fused model for each dataset reveals accuracy rates of 95.83 for WISDM, 97 for DaLiAc, 94.65 for MotionSense, and 98.54 for PAMAP2. A comparative evaluation was conducted between the fused MLP model and the individual dataset models, with the latter tested on separate validation sets. The results indicate that the MLP model, trained on the fused dataset, exhibits superior performance relative to the models trained on individual datasets. This finding suggests that multisource data fusion significantly enhances the generalization and accuracy of HAR systems. The improved performance underscores the potential of integrating diverse data sources to create more robust and comprehensive models for activity recognition.
文摘The use of an electrical probe is forned by whispering gallery modes(WGMs)of light within the coated microring circuits,in which the electrical signal is generated by trapped electron tunneling along the circular path of the coa ted microring circuit.The ollection of electrons is formed within the WGMs,where in this study,a modifed nonlinear microring resonator known as a PANDA ring resonator is coated by gold material and forms the mirroring circuit.The induced current(magnetic field)within the circuit occurs by the coupling ffects between trapped electrons and coated ring,which can penetrate into the brain cells and transform to the required signals via the terahertz carier for peychiatric investigations.The use of WGMs for 3D image construction using a PANDA conjugate mirror is also discussed,which is useful for thermal and imaging sensons.
基金supported by the Faculty of Science,Naresuan University,Thailand.
文摘A PANDA ring resonator circuit has been applied to the measurement of muscle actions,measuring signals created by facial muscle contractions.A system,which is called the Optical Muscle Sensing System,was developed which uses sensors to measure the mechanism of facial muscle contractions and the strength of contraction and degrees of perturbation of the facial muscles that are used directly for each facial gesture.The signal data was obtained from the simulation of the facial gestures and this data was applied in the classification of the facial gesture signals of each particular gesture.Facial gestures include blinking,smiling,grimacing and various other contortions of the face which may imply emotions and are part of normal human communication.Understanding of these mechanisms will be useful and applicable to facial rehabilitation services.
