Abstract: To provide improved security in adjunct program modules such as plug-ins and dynamic link libraries, a requesting module provides an authorization interface to the invoked module such that the invoked module can require a certificate of the requesting module and can also challenge the authority of the requesting module. The certificate can include one or more permissions which are prerequisites for processing by the invoked module. The invoked module can challenge the authority of the requesting module by sending random test data to the requesting module and receiving in response a cryptographic signature of the test data. By verifying the signature of the requesting module using the received certificate, the invoked module confirms that the requesting module is, in fact, the owner of the receive certificate.

Abstract: To provide improved security in adjunct program modules such as plug-ins and dynamic link libraries, a requesting module provides an authorization interface to the invoked module such that the invoked module can require a certificate of the requesting module and can also challenge the authority of the requesting module. The certificate can include one or more permissions which are prerequisites for processing by the invoked module. The invoked module can challenge the authority of the requesting module by sending random test data to the requesting module and receiving in response a cryptographic signature of the test data. By verifying the signature of the requesting module using the received certificate, the invoked module confirms that the requesting module is, in fact, the owner of the receive certificate.

Abstract: To provide improved security in adjunct program modules such as plug-ins and dynamic link libraries, a requesting module provides an authorization interface to the invoked module such that the invoked module can require a certificate of the requesting module and can also challenge the authority of the requesting module. The certificate can include one or more permissions which are prerequisites for processing by the invoked module. The invoked module can challenge the authority of the requesting module by sending random test data to the requesting module and receiving in response a cryptographic signature of the test data. By verifying the signature of the requesting module using the received certificate, the invoked module confirms that the requesting module is, in fact, the owner of the receive certificate.

Abstract: A system and method for secure telerehabilitation is disclosed. The system and method can create results to evaluate patient performance. The results can then be uploaded to a server and stored in a database. The database can have secure fields for each doctor and secure fields for each patient within each doctor's field.

Abstract: A digitized signal is published with a blank watermark, i.e., a watermark which contains no specific watermark data, and a server computer system encodes specific watermark data into the watermark signal for each delivery of the digitized signal. A basis signal which is used to watermark a digitized signal is predetermined to enable embedding of transaction-specific watermark data to be embedded in the subject signal with minimal processing resources. Since the basis signal generally accounts for the majority of the processing resources required to watermark the subject signal, only a relatively small portion of the requisite processing resources are used to embed transaction-specific watermark into the subject signal.

Abstract: A system and method for aural rehabilitation is disclosed. A system and method for neurological rehabilitation or training is disclosed. The system can be controlled automatically by a remote device or manually by a physician's device. The system can store data in, and retrieve data from a database for analysis, reporting and execution. The system can adapt and adjust based on the subject's performance. The system can be used to treat hearing loss, tinnitus or other audiological health problems.

Abstract: A system 2 and method 64 for neurological rehabilitation or training is disclosed. The system 2 can be used to improve listening, comprehension, and communication. The system 2 can be controlled automatically by a remote device 6 or manually by a physician's device 4. The system 2 can store data in, and retrieve data from a database 10 for analysis, reporting and execution. The system 2 can adapt and adjust based on the subject's performance. The system 2 can be used to treat hearing loss, tinnitus or other audiological health problems.

Abstract: To provide improved security in adjunct program modules such as plug-ins and dynamic link libraries, a requesting module provides an authorization interface to the invoked module such that the invoked module can require a certificate of the requesting module and can also challenge the authority of the requesting module. The certificate can include one or more permissions which are prerequisites for processing by the invoked module. The invoked module can challenge the authority of the requesting module by sending random test data to the requesting module and receiving in response a cryptographic signature of the test data. By verifying the signature of the requesting module using the received certificate, the invoked module confirms that the requesting module is, in fact, the owner of the receive certificate.

Abstract: To provide improved security in adjunct program modules such as plug-ins and dynamic link libraries, a requesting module provides an authorization interface to the invoked module such that the invoked module can require a certificate of the requesting module and can also challenge the authority of the requesting module. The certificate can include one or more permissions which are prerequisites for processing by the invoked module. The invoked module can challenge the authority of the requesting module by sending random test data to the requesting module and receiving in response a cryptographic signature of the test data. By verifying the signature of the requesting module using the received certificate, the invoked module confirms that the requesting module is, in fact, the owner of the receive certificate.

Abstract: A system and method for treatment of neurological disorders with sound therapy is disclosed. The system can have a local PDA, a remote server, a physician's PC, and a database connected to the server. The PDA and PC can be networked with the server. The PC can initialize a treatment protocol stored at the server. The server can utilize the database and the protocol from the PC to come up with a recommended therapy. The recommended therapy can be selected by the PC and sent to the PDA. The PDA can then execute the selected therapy on the patient. The PDA can also record biometric and other feedback and send it to the server.

Abstract: A method and system for delivering data of a performance to audience members is disclosed. Delivery devices can be transferred to the audience members following the performance. The delivery devices can have redeemers, for example, unique codes. The audience members can use the unique codes to later download the performance and transfer it onto the delivery devices.

Abstract: Watermark data is encoded in a digitized signal by forming a noise threshold spectrum which represents a maximum amount of imperceptible noise, spread-spectrum chipping the noise threshold spectrum with a relatively endless stream of pseudo-random bits to form a basis signal, dividing the basis signal into segments, and filtering the segments to smooth segment boundaries. The data encoded in the watermark signal is precoded to make the watermark data inversion robust and is convolutional encoded to further increase the likelihood that the watermark data will subsequently be retrievable notwithstanding lossy processing of the watermarked signal.

Abstract: Watermark data is encoded in a digitized signal by forming a noise threshold spectrum which represents a maximum amount of imperceptible noise, spread-spectrum chipping the noise threshold spectrum with a relatively endless stream of pseudo-random bits to form a basis signal, dividing the basis signal into segments, and filtering the segments to smooth segment boundaries. The data encoded in the watermark signal is precoded to make the watermark data inversion robust and is convolutional encoded to further increase the likelihood that the watermark data will subsequently be retrievable notwithstanding lossy processing of the watermarked signal. A watermark alignment module determines which of a large number of offsets of the watermarked data is most likely to correspond to a recognizable watermark. The watermark alignment module uses a single basis signal to evaluate a number of offsets over a relatively narrow range of offsets.

Abstract: Watermark data is encoded in a digitized signal by forming a noise threshold spectrum which represents a maximum amount of imperceptible noise, spread-spectrum chipping the noise threshold spectrum with a relatively endless stream of pseudo-random bits to form a basis signal, dividing the basis signal into segments, and filtering the segments to smooth segment boundaries. The data encoded in the watermark signal is precoded to make the watermark data inversion robust and is convolutional encoded to further increase the likelihood that the watermark data will subsequently be retrievable notwithstanding lossy processing of the watermarked signal. To produce the endless pseudo-random bit stream, subsequent bits of the sequence are generated in a pseudo-random manner from previous bits of the sequence. The pseudo-random bits are appended to the stream of pseudo-random bits and, additionally, replace a number of bits of the state.

Abstract: Watermark data is encoded in a digitized signal by forming a noise threshold spectrum which represents a maximum amount of imperceptible noise, spread-spectrum chipping the noise threshold spectrum with a relatively endless stream of pseudo-random bits to form a basis signal, dividing the basis signal into segments, and filtering the segments to smooth segment boundaries. The data encoded in the watermark signal is precoded to make the watermark data inversion robust and is convolutional encoded to further increase the likelihood that the watermark data will subsequently be retrievable notwithstanding lossy processing of the watermarked signal. The basis signal fits noise thresholds determined by constant-quality quantization approximation. Noise introduced by quantization is estimated by determining a continuously differentiable function which approximates noise introduced by such quantization and using the function to solve for a relatively optimal gain to be applied during such quantization.

Abstract: Watermark data is encoded in a digitized signal by forming a noise threshold spectrum which represents a maximum amount of imperceptible noise, spread-spectrum chipping the noise threshold spectrum with a relatively endless stream of pseudo-random bits to form a basis signal, dividing the basis signal into segments, and filtering the segments to smooth segment boundaries. The data encoded in the watermark signal is precoded to make the watermark data inversion robust and is convolutional encoded to further increase the likelihood that the watermark data will subsequently be retrievable notwithstanding lossy processing of the watermarked signal. Watermark data is encoded in a basis signal by division of the basis signal into segments and inverting the basis signal in segments corresponding to watermark data bits with a first logical value and not inverting the basis signal in segment corresponding to watermark data bits with a different logical value.

Abstract: An adaptive linear predictor is used to predict samples, and residuals from such predictions are encoded using Golomb-Rice encoding. Linear prediction of samples of a signal which represents digitized sound tends to produce relatively low residuals and those residuals tend to be distributed exponentially. Accordingly, linear prediction combined with Golomb-Rice encoding produces particularly good compression rates with very efficient and simple implementation. The accuracy of the linear predictor is improved by including, in the prediction of a current sample of a first channel of the digitized signal, look-ahead sample data from a corresponding second channel of the digitized signal. For example, prediction of a right channel sample of a digitized, stereo, audio signal is improved by inclusion of look-ahead left channel sample data in the right channel sample predictor.

Abstract: An adaptive linear predictor is used to predict samples, and residuals from such predictions are encoded using Golomb-Rice encoding. Linear prediction of samples of a signal which represents digitized sound tends to produce relatively low residuals and those residuals tend to be distributed exponentially. Accordingly, linear prediction combined with Golomb-Rice encoding produces particularly good compression rates with very efficient and simple implementation. A code length used in Golomb-Rice, which is typically referred to as the parameter k, is adapted for each sample in a predictable and repeatable manner to further reduce the size of a Golomb-Rice encoding for each sample. An infinite incident response filter of processed residuals automatically reduces influences of previously processed residuals upon such adaptation as additional samples are processed.

Abstract: An adaptive linear predictor is used to predict samples, and residuals from such predictions are encoded using Golomb-Rice encoding. Linear prediction of samples of a signal which represents digitized sound tends to produce relatively low residuals and those residuals tend to be distributed exponentially. Accordingly, linear prediction combined with Golomb-Rice encoding produces particularly good compression rates with very efficient and simple implementation. A code length used in Golomb-Rice, which is typically referred to as the parameter k, is adapted for each sample in a predictable and repeatable manner to further reduce the size of a Golomb-Rice encoding for each sample. An infinite incident response filter of processed residuals automatically reduces influences of previously processed residuals upon such adaptation as additional samples are processed. The efficiency of Golomb-Rice encoding is improved by limiting the predicted samples to an efficient range.

Abstract: An adaptive predictor is used to predict samples, and residuals from such predictions are encoded using Golomb-Rice encoding to thereby compress a digital signal which includes the samples. The adaptive predictor adapts to residuals between actual and predicted samples at a particular rate. The rate of adaptation is itself adapted periodically to ensure optimum performance of the compression. A number of samples are repeatedly compressed using different adaptation rates, and the adaptation rate which produces the best compression results is used. The adaptation rate can be an exponential power of 2 such that incrementing the adaptation rate effectively doubles the rate at which the predictor is adapted and decrementing the adaptation rate effectively halves the rate at which the predictor is adapted. Accordingly, fewer trials are needed to find a relatively optimal adaptation rate for the predictor.