Abstract: A raster image processor (RIP) system is used in a printing system to process a variety of different jobs. A front end receives the jobs and determines the job type. The job types include a print job, a preview job, and an estimation job. Depending on the type of job, the front end configures the RIPs within RIP system accordingly to process the job. The RIPs may process the job in parallel, with a high performance RIP processing the first page of the job. If the job is not processed in parallel, then the front end assigns the job to a very high performance RIP. The front end also assigns the preview job to a preview RIP and the estimation job to an estimation RIP. The front end configures RIPs as needed.

Abstract: A printing system includes a digital front end (DFE) system connected to a plurality of printing devices. The DFE system manages printing operations to the plurality of printing devices. The DFE system also includes a printing device connectivity manager to manage connections with the printing devices. Printing connectivity modules are installed at the printing device connectivity manager using application programming interfaces (APIs) that are loaded at the creation of the printing connectivity modules. The DFE system also includes a display device connectivity manager to manage connections with display devices using display connectivity modules and display connectivity APIs. The DFE system also includes a storage connectivity manager to manage data storage and storage devices using storage connectivity modules and storage connectivity APIs.

Abstract: A printing system includes a digital front end (DFE) system connected to a plurality of printing devices. The DFE system manages printing operations to the plurality of printing devices. The DFE system also includes a printing device connectivity manager to manage connections with the printing devices. Printing connectivity modules are installed at the printing device connectivity manager using application programming interfaces (APIs) that are loaded at the creation of the printing connectivity modules. The DFE system also includes a display device connectivity manager to manage connections with display devices using display connectivity modules and display connectivity APIs. The DFE system also includes a storage connectivity manager to manage data storage and storage devices using storage connectivity modules and storage connectivity APIs.

Abstract: A printing system includes a digital front end (DFE) system connected to a plurality of printing devices. The DFE system manages printing operations to the plurality of printing devices. The DFE system also includes a printing device connectivity manager to manage connections with the printing devices. Printing connectivity modules are installed at the printing device connectivity manager using application programming interfaces (APIs) that are loaded at the creation of the printing connectivity modules. The APIs allow the printing connectivity modules to interact with the printing devices. The printing connectivity modules can communicate with application modules located at the printing devices.

Abstract: A printing system includes a digital front end (DFB) system connected to a plurality of printing devices. The DFE system manages printing operations to the plurality of printing devices. The DFE system also includes a printing device connectivity manager to manage connections with the printing devices. Printing connectivity modules are installed at the printing device connectivity manager using application programming interfaces (APIs) that are loaded at the creation of the printing connectivity modules. The DFE system also includes a display device connectivity manager to manage connections with display devices using display connectivity modules and display connectivity APIs. The DFE system also includes a storage connectivity manager to manage data storage and storage devices using storage connectivity modules and storage connectivity APIs.

Abstract: Example systems and related methods may relate to monitoring performance of an image forming operation. Namely, a system includes an image forming apparatus configured to execute an operation in response to receiving instructions to execute the operation. The system further includes an external sensor circuit that includes one or more sensors and a processor. The one or more sensors are configured to detect a status of an operational parameter of the image forming apparatus indicative of the image forming apparatus executing the operation and receive an instruction to exclude at least a portion of data used to detect the status of the operational parameter. The system further includes a host computing device. The host computing device is configured to generate a plurality of timestamps indicative of when the image forming apparatus executed the operation and a time frame when the external sensor circuit excluded data.

Abstract: Example systems and related methods may relate to monitoring performance of an image forming operation. Namely, a system includes an image forming apparatus configured to execute an operation in response to receiving instructions to execute the operation. The system further includes an external sensor circuit that includes one or more sensors and a processor. The one or more sensors are configured to detect a status of an operational parameter of the image forming apparatus indicative of the image forming apparatus executing the operation and receive an instruction to exclude at least a portion of data used to detect the status of the operational parameter. The system further includes a host computing device. The host computing device is configured to generate a plurality of timestamps indicative of when the image forming apparatus executed the operation and a time frame when the external sensor circuit excluded data.

Abstract: Example systems and related methods may relate to monitoring performance of an image forming operation. Namely, a system includes an image forming apparatus configured to execute an operation in response to receiving instructions to execute the operation. The system further includes an external sensor circuit that includes one or more sensors and a processor. The one or more sensors are configured to detect a status of a first operational parameter of the image forming apparatus indicative of the image forming apparatus executing the operation and detect a status of a second operational parameter of the image forming apparatus indicative of the image forming apparatus executing an intervening operation. The system further includes a host computing device. The host computing device is configured to generate a plurality of timestamps indicative of when the image forming apparatus executed the operation and when the image forming apparatus executed the intervening operation.

Abstract: Example systems and related methods may relate to monitoring performance of an image forming operation. Namely, a system may include an image forming apparatus configured to execute an operation. The system further includes an external sensor circuit comprising one or more sensors and a processor. The system yet further includes a host computing device configured to generate, in response to receiving notifications of a status of the operational parameter received from the one or more processors of the sensor circuit, a first timestamp indicative of when the image forming apparatus started to execute the printing operation, and a second timestamp indicative of when the image forming apparatus completed the printing operation. The host computing device is further configured to generate a log file. Data of the log file includes the first timestamp and the second timestamp, and is indicative of how quickly the image forming apparatus executed the operation.

Abstract: A printing system generating a personalized banner page has a client device that transmits print data. An image forming device receives the print data transmitted by the client device. A banner creation module is in communication with the client device and the image forming device. The banner creation module transmits a user selected personalized indicia to be inserted on a banner page to be printed with the print data to identify the user.

Abstract: Example systems and related methods may relate to compressing a plurality of data channels. An example embodiment may include a controller determining a plurality of interleave allocations within a memory allocation. The interleave allocations correspond to a plurality of planes, which may represent color information planes. The plurality of data channels may be compressed into a plurality of compressed data channels. Subsequently, each of the plurality of compressed data channels may be stored at respective interleave allocations. A full interleave allocation condition may be determined based on a capacity of a respective interleave allocation being less than a predetermined threshold. In response to determining the full interleave allocation condition, a new interleave allocation may be requested from the controller. In response, the controller may determine a new interleave allocation.

Abstract: An inflatable airbag system for a motor vehicle includes a restraining strap for delaying inflation of a central portion of an airbag and deflecting gas into adjacent elongate portions in the initial stages of deployment.

Abstract: An inflatable airbag system for a motor vehicle includes a restraining strap for delaying inflation of a central portion of an airbag and deflecting gas into adjacent elongate portions in the initial stages of deployment.

Abstract: The invention concerns a method for detecting voice activity in a digital speech signal, in at least a frequency band, for example by means of a detecting automaton whereof the status is controlled on the basis of an energy analysis of the signal. The control of said automaton, or more generally the determination of voice activity, comprises a comparison, in the frequency band, of two different versions of the speech signal one of which at least is a noise-corrected version.

Abstract: The invention concerns a method for conditioning a digital speech signal(s) processed by successive frames, which consists carrying out a harmonic analysis to estimate the pitch on each frame where it has a speech activity, and in oversampling at an oversampling frequency (fe) which is a multiple of the estimated pitch.

Abstract: A digital speech signal processed by successive frames is subjected to noise suppression taking account of estimates of the noise included in the signal, updated for each frame in a manner dependent on at least one degree of vocal activity. A priori noise suppression is applied to the speech signal of each frame on the basis of estimates of the noise obtained on processing at least one preceding frame, and the energy variations of the a priori noise-suppressed signal are analyzed to detect the degree of vocal activity of said frame.

Abstract: A spectral subtraction is effected including: a first subtraction step in which overestimates of the spectral component of the noise are taken into account, to obtain spectral components of a first noise-suppressed signal; the computation of a masking curve by applying an auditory perception model on the basis of the spectral components of the first noise-suppressed signal; and a second subtraction step in which a respective quantity depending on parameters including a difference between the overestimate of the corresponding spectral component of the noise and the computed masking curve is subtracted from each spectral component of the speech signal in the frame. The result of the spectral subtraction is transformed into the time domain to construct a noise-suppressed speech signal.

Abstract: A recognition test is applied to a segment of speech produced by a speaker. An examination is carried out to see whether a first optimum model, with which the recognition test has matched the spoken segment of speech, satisfies a criterion of likelihood. If the criterion of likelihood is satisfied, this first optimum model is selected. If not, a repetition of the speech segment is requested. The recognition test is applied to the segment of speech repeated by the speaker. This second optimum model is selected if it satisfies the likelihood criterion. If not, and if a combination of the results of the two recognition tests satisfies at least one criterion of combined selection, one of the models which the two recognition tests have matched with the spoken segment of speech and with the repeated segment is selected.

Abstract: A recognition test matches a speech segment supplied to the system with a set of parameters associated with a reference and memorized in a dictionary. A provisional version of each set of parameters to be memorized in the dictionary in association with a reference is estimated on the basis of one or more segments of speech, after which the provisional version is memorized in the dictionary in association with the reference. At least one repetition of the speech segment is submitted to a recognition test, after which depending on whether it has matched the speech segment with the provisional version, the provisional version is modified and the modified provisional version is memorized.

Abstract: In the recognition phase, the signal originating from a sensor is processed to obtain parameters which are compared with those stored in a dictionary in the learning phases so as to recognize the voice structures uttered by the user in a noisy environment. The obtaining of the said parameters during the learning and recognition phases includes the formation of digital frames of predetermined length from the signal originating from the sensor, the transformation of each frame from the time domain to the frequency domain to obtain a spectrum X(i), and the application of an inverse transformation, from the frequency domain to the time domain, to the magnitude .vertline.X(i).vertline..sup..gamma., where .vertline.X(i).vertline. represents the modulus of the spectrum and .gamma. represents an appropriate exponent.