A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in th...A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in the need for applications and methodologies that are capable of automatically analyzing these contents. These technologies can be applied in automatic contentanalysis and emergency response systems. Breaks in manual communication usually occur in emergencies leading to accidents and equipment damage. The audio signal does a good job by sending a signal underground, which warrants action from an emergency management team at the surface. This paper, therefore, seeks to design and simulate an audio signal alerting and automatic control system using Unity Pro XL to substitute manual communication of emergencies and manual control of equipment. Sound data were trained using the neural network technique of machine learning. The metrics used are Fast Fourier transform magnitude, zero crossing rate, root mean square, and percentage error. Sounds were detected with an error of approximately 17%;thus, the system can detect sounds with an accuracy of 83%. With more data training, the system can detect sounds with minimal or no error. The paper, therefore, has critical policy implications about communication, safety, and health for underground mine.展开更多
This paper discusses the approaches for automatical searching of control points in the NOAA AVHRR image on the basis of data rearrangement in the form of latitude and longitude grid. The vegetation index transformatio...This paper discusses the approaches for automatical searching of control points in the NOAA AVHRR image on the basis of data rearrangement in the form of latitude and longitude grid. The vegetation index transformation and multi-level matching strategies have been proven effective and successful as the experiments show while the control point database is established.展开更多
Following the M_(S)6.4 earthquake that occurred on May 21,2021 in Yangbi,Yunnan,China,the earthquake emergency response system(EERS)responded immediately.The real-time software delivered many seismic parameters that p...Following the M_(S)6.4 earthquake that occurred on May 21,2021 in Yangbi,Yunnan,China,the earthquake emergency response system(EERS)responded immediately.The real-time software delivered many seismic parameters that provided a preliminary assessment of the earthquake.The 24-hour on-duty staff and scientific researchers revised these parameters and produced more detailed reports to understand the cause of the earthquake and the potential damage,which provided valuable information for emergency rescue operations and earthquake situation assessment.Emergency personnel were dispatched immedia-tely to the earthquake site to observe the aftershocks,investigate the damage,and guide and assist in the relief efforts.This paper describes the EERS response to the Yangbi earthquake to demonstrate the characteristics of the system and discuss the potential for further improvement.展开更多
文摘A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in the need for applications and methodologies that are capable of automatically analyzing these contents. These technologies can be applied in automatic contentanalysis and emergency response systems. Breaks in manual communication usually occur in emergencies leading to accidents and equipment damage. The audio signal does a good job by sending a signal underground, which warrants action from an emergency management team at the surface. This paper, therefore, seeks to design and simulate an audio signal alerting and automatic control system using Unity Pro XL to substitute manual communication of emergencies and manual control of equipment. Sound data were trained using the neural network technique of machine learning. The metrics used are Fast Fourier transform magnitude, zero crossing rate, root mean square, and percentage error. Sounds were detected with an error of approximately 17%;thus, the system can detect sounds with an accuracy of 83%. With more data training, the system can detect sounds with minimal or no error. The paper, therefore, has critical policy implications about communication, safety, and health for underground mine.
基金Project supported by the National Oommission of Defense Science and Technotocjy(No.Y96-10)
文摘This paper discusses the approaches for automatical searching of control points in the NOAA AVHRR image on the basis of data rearrangement in the form of latitude and longitude grid. The vegetation index transformation and multi-level matching strategies have been proven effective and successful as the experiments show while the control point database is established.
文摘Following the M_(S)6.4 earthquake that occurred on May 21,2021 in Yangbi,Yunnan,China,the earthquake emergency response system(EERS)responded immediately.The real-time software delivered many seismic parameters that provided a preliminary assessment of the earthquake.The 24-hour on-duty staff and scientific researchers revised these parameters and produced more detailed reports to understand the cause of the earthquake and the potential damage,which provided valuable information for emergency rescue operations and earthquake situation assessment.Emergency personnel were dispatched immedia-tely to the earthquake site to observe the aftershocks,investigate the damage,and guide and assist in the relief efforts.This paper describes the EERS response to the Yangbi earthquake to demonstrate the characteristics of the system and discuss the potential for further improvement.
