Steganography techniques are used in Multimedia data transfer to prevent adversaries from eaves dropping. Synchronized audio to audio steganography deals with recording the secret audio, hiding it in another audio fil...Steganography techniques are used in Multimedia data transfer to prevent adversaries from eaves dropping. Synchronized audio to audio steganography deals with recording the secret audio, hiding it in another audio file and subsequently sending to multiple receivers. This paper proposes a Multilevel Access control in Synchronized audio steganography, so that Audio files which are meant for the users of low level class can be listened by higher level users, whereas the vice-versa is not allowed. To provide multilevel access control, symmetric polynomial based scheme is used. The steganography scheme makes it possible to hide the audio in different bit locations of host media without inviting suspicion. The Secret file is embedded in a cover media with a key. At the receiving end the key can be derived by all the classes which are higher in the hierarchy using symmetric polynomial and the audio file is played. The system is implemented and found to be secure, fast and scalable. Simulation results show that the system is dynamic in nature and allows any type of hierarchy. The proposed approach is better even during frequent member joins and leaves. The computation cost is reduced as the same algorithm is used for key computation and descendant key derivation. Steganography technique used in this paper does not use the conventional LSB’s and uses two bit positions and the hidden data occurs only from a frame which is dictated by the key that is used. Hence the quality of stego data is improved.展开更多
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
In this paper, an active noise control(ANC) system is developed to provide an effective and non-intrusive solution for reducing loud snoring to provide a quiet environment for a snorer's bed partner. An adaptive l...In this paper, an active noise control(ANC) system is developed to provide an effective and non-intrusive solution for reducing loud snoring to provide a quiet environment for a snorer's bed partner. An adaptive least mean square(LMS)algorithm optimized for different kinds of snore signals is introduced and theoretically analyzed. Also, a residual noise masking approach is proposed to further reduce the effect of the snore noise without interfering with the LMS algorithm. Computer simulations followed by real-time experiments are conducted to demonstrate the feasibility of the snore ANC systems based on a pillow setup. For the optimum effect based on the characteristics of human hearing, the performance of the proposed approach is evaluated by using the multi-channel feedforward ANC systems based on the filtered-X least mean square(FXLMS) algorithm.Compared with a traditional headboard setup for snoring noise control, the proposed snore ANC systems optimized for ear field operation yield much higher noise reduction around the ears of the snorer's bed partner.展开更多
文摘Steganography techniques are used in Multimedia data transfer to prevent adversaries from eaves dropping. Synchronized audio to audio steganography deals with recording the secret audio, hiding it in another audio file and subsequently sending to multiple receivers. This paper proposes a Multilevel Access control in Synchronized audio steganography, so that Audio files which are meant for the users of low level class can be listened by higher level users, whereas the vice-versa is not allowed. To provide multilevel access control, symmetric polynomial based scheme is used. The steganography scheme makes it possible to hide the audio in different bit locations of host media without inviting suspicion. The Secret file is embedded in a cover media with a key. At the receiving end the key can be derived by all the classes which are higher in the hierarchy using symmetric polynomial and the audio file is played. The system is implemented and found to be secure, fast and scalable. Simulation results show that the system is dynamic in nature and allows any type of hierarchy. The proposed approach is better even during frequent member joins and leaves. The computation cost is reduced as the same algorithm is used for key computation and descendant key derivation. Steganography technique used in this paper does not use the conventional LSB’s and uses two bit positions and the hidden data occurs only from a frame which is dictated by the key that is used. Hence the quality of stego data is improved.
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.
文摘In this paper, an active noise control(ANC) system is developed to provide an effective and non-intrusive solution for reducing loud snoring to provide a quiet environment for a snorer's bed partner. An adaptive least mean square(LMS)algorithm optimized for different kinds of snore signals is introduced and theoretically analyzed. Also, a residual noise masking approach is proposed to further reduce the effect of the snore noise without interfering with the LMS algorithm. Computer simulations followed by real-time experiments are conducted to demonstrate the feasibility of the snore ANC systems based on a pillow setup. For the optimum effect based on the characteristics of human hearing, the performance of the proposed approach is evaluated by using the multi-channel feedforward ANC systems based on the filtered-X least mean square(FXLMS) algorithm.Compared with a traditional headboard setup for snoring noise control, the proposed snore ANC systems optimized for ear field operation yield much higher noise reduction around the ears of the snorer's bed partner.
