Abstract: Systems and methods for decompressing compressed data that has been compressed by way of a lossless compression algorithm are described herein. In a general embodiment, a graphics processing unit (GPU) is programmed to receive compressed data packets and decompress such packets in parallel. The compressed data packets are compressed representations of an image, and the lossless compression algorithm is a Rice compression algorithm.

Abstract: Some embodiments include two-dimensional compressed data sets that can be re-aligned while preserving compression of the data. A set of one or more shifts and a corresponding set of one or more first dimension indices into a two-dimensional compressed data set for re-aligning the two-dimensional compressed data set are determined. Impact of re-aligning upon each vector in the second dimension of the two-dimensional compressed data set is determined while the two-dimensional compressed data set remains compressed. New compressed vectors are created in the second dimension resulting from re-aligning. Compression information is modified for each of the original vectors of the two-dimensional compressed data set that remain after re-aligning based, at least in part, on the new compressed vectors. A re-aligned version of the two-dimensional compressed data set is created with the new compressed vectors, and the remaining original vectors with their modified compression information.

Abstract: Some embodiments include an apparatus and a computer program product configured to re-align two-dimensional compressed data sets while preserving compression of the data. A set of one or more shifts and a corresponding set of one or more first dimension indices into a two-dimensional compressed data set for re-aligning the two-dimensional compressed data set are determined. Impact of re-aligning upon each vector in the second dimension of the two-dimensional compressed data set is determined while the two-dimensional compressed data set remains compressed. New compressed vectors are created in the second dimension resulting from re-aligning. Compression information is modified for each of the original vectors of the two-dimensional compressed data set that remain after re-aligning based, at least in part, on the new compressed vectors.

Abstract: A method for producing 3D multi-view visual contents including capturing a visual scene from at least one first point of view for generating a first bidimensional image of the scene and a corresponding first depth map indicative of a distance of different parts of the scene from the first point of view. The method further includes capturing the visual scene from at least one second point of view for generating a second bidimensional image; processing the first bidimensional image to derive at least one predicted second bidimensional image predicting the visual scene captured from the at least one second point of view; deriving at least one predicted second depth map predictive of a distance of different parts of the scene from the at least one second point of view by processing the first depth map, the at least one predicted second bidimensional image and the second bidimensional image.

Abstract: Methods and apparatuses for performing inter-color-plane prediction with adaptability to various existing video content representations are provided. A plurality of predetermined rescaling schemes based on a color plane format is selected. A first block of original samples of a first color plane is encoded into a compressed bitstream. A block of reconstructed samples of the first color plane is reconstructed. An inter-color-plane prediction process is performed to produce samples of a second color plane. Said block of prediction samples of the second color plane is subtracted from a second block of original samples of the second color plane to produce a block of residual samples of the second color plane where the positions of the first block and the second block of original samples are aligned. Finally, the block of residual samples of the second color plane is encoded.

Abstract: Techniques are described for tokenizing information to be stored in an untrusted environment. During tokenization, one or more strings in a file or data stream are replaced with a token. The token may be generated as a random number or a counter, such that the replaced string may not be derived based on the token. Token-to-string mapping data may be stored in a trusted environment, and the tokenized information may be stored in the untrusted environment. Users may search the tokenized information based on non-sensitive search terms present in a whitelist that is accessible from the untrusted environment, the whitelist providing a token-to-string mapping for the non-sensitive terms. The search results may be provided as redacted information, in which the non-sensitive strings have been detokenized based on the whitelist while the sensitive strings remain tokenized.

Abstract: Compression of floating-point numbers is realized by comparing the exponents of the floating-point numbers to one or more exponent thresholds to classify the floating-point numbers and to apply different compression types to the different classes. Each class and compression type is associated with an indicator. An indicator array contains M indicators for M floating-point numbers. The position of the indicator in the indicator array corresponds to one of the floating-point numbers and the indicator value specifies the class and compression type. The floating-point number is encoded in accordance with the compression type for its class. A compressed data packet contains the indicator array and up to M encoded floating-point numbers.

Abstract: Random sinogram variance is reduced in continuous bed motion acquisition. The randoms are modeled as a product of transverse singles efficiencies. The random sinogram is assumed to be a smooth function in the axial direction, collapsing the parameterization for estimating the transverse singles efficiencies into a single, conceptual ring. By solving the product, the mean random values are used to smooth the randoms in image reconstruction with less noise and artifacts.

Abstract: Memory system operations are extended for a data processor by DMA, cache, or memory controller to include a DMA descriptor, including a set of operations and parameters for the operations, which provides for data compression and decompression during or in conjunction with processes for moving data between memory elements of the memory system. The set of operations can be configured to use the parameters and perform the operations of the DMA, cache, or memory controller. The DMA, cache, or memory controller can support moves between memory having a first access latency, such as memory integrated on the same chip as a processor core, and memory having a second access latency that is longer than the first access latency, such as memory on a different integrated circuit than the processor core.

Abstract: A rendering apparatus and method are provided. The rendering method includes: reading a block, corresponding to a fragment, from among compressed blocks stored in a depth buffer, by considering frequency information corresponding to the fragment and prepared in advance; and performing a depth test for the fragment by considering the restored block.

Abstract: A method, executed by at least one processor, for compressing time-varying scientific data, includes receiving time-varying data corresponding to a physical phenomenon within a domain comprising one or more spatial dimensions, conducting a proper orthogonal decomposition of the time-varying data to provide basis vectors for the time-varying data, generating a set of expansion coefficients corresponding to the basis vectors that are most prominent in the time-varying data, conducting an image compression algorithm on the expansion coefficients to provide a compressed representation of the time-varying data, and storing the compressed representation of the time-varying data. The time-varying data may be numeric data generated from a physical simulation or from experimentation. In some embodiments, the time-varying data corresponds to one or more sub-domains within a larger dataset. The sub-domains may be coherent sub-domains that have similar modes.

Abstract: Method for fully adaptive calibration of a prediction error coder, comprising a first step of initialization; a second step of reception and accumulation of block-size data samples wherein for each received value, it is added one to the histogram bin associated to that value; a third step of analysis of the histogram and determination of the coding option; a fourth step of analysis of the histogram and determination of a coding table; a fifth step of output a header with the prediction error coder coding table determined; and wherein previous steps are repeated if more samples need to be compressed. It is useful as a data compression technique, with the advantage of being faster and more robust than the current CCSDS lossless compression standard.

Abstract: Methods and systems for adaptive compression include compressing input data according to a first compression ratio; pausing compression after a predetermined amount of input data is compressed; estimating which of a set of ranges a compressed output size will fall within using current settings; and performing compression on a remainder of the input data according to a second compression ratio based on the estimated range.

Abstract: An algorithm for efficiently compressing floating-point data in 3D meshes is disclosed. 3D meshes are represented by topology data, geometry data and property data. Geometry data specify vertex locations and are usually represented by floating-point coordinates. While geometry data are usually compressed by quantization, prediction and entropy coding, the present invention uses no prediction. A floating-point number consists of mantissa and exponent, and normally the exponent, sign and mantissa are compressed separately. A method for encoding floating-point formatted data comprises determining if a current floating-point value was previously stored in a memory, storing the current value in the memory if it was not previously stored in the memory, and encoding it. Otherwise, if the current floating-point value was previously stored in a memory, the storage position of the value within the memory is determined and a reference pointing to the storage position is encoded.

Abstract: An electronic device for sending a message is described. The electronic device includes a processor and instructions stored in memory that is in electronic communication with the processor. The electronic device determines whether a picture is allowed to be decoded on a sub-picture level. If the picture is allowed to be decoded on a sub-picture level, the electronic device generates at least one of a buffer size parameter and a buffer scale parameter. The electronic device sends at least one of the buffer size parameter and the buffer scale parameter.

Abstract: Various embodiments relating to encoding a sparse matrix into a data structure format that may be efficiently processed via parallel processing of a computing system are provided. In one embodiment, a sparse matrix may be received. A set of designated rows of the sparse matrix may be traversed until all non-zero elements in the sparse matrix have been placed in a first array. Each time a row in the set is traversed, a next non-zero element in that row may be placed in the first array. If all non-zero elements for a given row of the set of designated rows have been placed in the first array, the given row may be replaced in the set of designated rows with a next unprocessed row of the sparse matrix. The data structure in which the sparse matrix is encoded may be outputted. The data structure may include the first array.

Abstract: Exponents, mantissas and signs of floating-point numbers are compressed in encoding groups. Differences between maximum exponents of encoding groups are encoded by exponent tokens selected from a code table. Each mantissa of an encoding group is encoded to a mantissa token having a length based on the maximum exponent. Signs are encoded directly or are compressed to produce sign tokens. Exponent tokens, mantissa tokens and sign tokens are packed in a compressed data packet. For decompression, the exponent tokens are decoded using the code table. The decoded exponent difference is added to a previous reconstructed maximum exponent to produce the reconstructed maximum exponent for the encoding group. The reconstructed maximum exponent is used to determine the length of the mantissa tokens that are decoded to produce the reconstructed mantissas for the encoding group. The reconstructed sign, reconstructed exponent and reconstructed mantissa are combined to form a reconstructed floating-point number.

Abstract: An apparatus is provided for decoding last position information indicating a horizontal position and a vertical position of a last non-zero coefficient in a predetermined order within a current block to be decoded, the current block being included in a picture and including a plurality of coefficients. The apparatus includes one or more processors, a communication unit, and storage coupled to the one or more processors and the communication unit. The communication unit is configured to transmit a request for a bitstream to an external system, and receive the bitstream from the external system. The one or more processors are configured to obtain the bitstream, perform first arithmetic decoding, perform second arithmetic decoding, derive a horizontal component of the last position information, and derive a vertical component of the last position. A system for decoding and a displaying method are also provided.

Abstract: Compression of exponents, mantissas and signs of floating-point numbers is described. Differences between exponents are encoded by exponent tokens selected from a code table. The mantissa is encoded to a mantissa token having a length based on the exponent. The signs are encoded directly or are compressed to produce fewer sign tokens. The exponent tokens, mantissa tokens and sign tokens are packed in a compressed data packet. Decompression decodes the exponent tokens using the code table. The decoded exponent difference is added to a previous reconstructed exponent to produce the reconstructed exponent. The reconstructed exponent is used to determine the length of the mantissa token. The mantissa token is decoded to form the reconstructed mantissa. The sign tokens provide the reconstructed signs or are decompressed to provide the reconstructed signs. The reconstructed sign, reconstructed exponent and reconstructed mantissa are combined to form a reconstructed floating-point number.

Abstract: In a method for checking an output of a random number generator which includes at least one random source, the frequency of occurrence of at least one bit assignment is counted and established in a correlation with the total number of values which are taken into account.

Abstract: A method and as assemblage for post-processing an output of a random source of a random generator are presented. In the method, an output signal of the random source is compressed, thereby yielding a sequence of compressed signal values that are checked in terms of their distribution.

Abstract: A method for compressing a set of small strings may include calculating n-gram frequencies for a plurality of n-grams over the set of small strings, selecting a subset of n-grams from the plurality of n-grams based on the calculated n-gram frequencies, defining a mapping table that maps each n-gram of the subset of n-grams to a unique code, and compressing the set of small strings by replacing n-grams within each small string in the set of small strings with corresponding unique codes from the mapping table. The method may use linear optimization to select a subset of n-grams that achieves a maximum space saving amount over the set of small strings for inclusion in the mapping table. The unique codes may be variable-length one or two byte codes. The set of small strings may be domain names.

Abstract: A decoding method decodes last position information indicating horizontal and vertical positions of a last non-zero coefficient in a predetermined order within a current block to be decoded, the current block including plural coefficients. The decoding includes obtaining a bitstream including first, second, third and fourth partial signals, in this order, performing first arithmetic decoding on the first and the third partial signals respectively to obtain decoded first and decoded third partial signals, performing second arithmetic decoding on the second and the fourth partial signals respectively to obtain decoded second and decoded fourth partial signals, the second arithmetic decoding being different from the first arithmetic decoding, deriving a horizontal component of the last position information from the decoded first and decoded third partial signals, and deriving a vertical component of the last position information from the decoded second and decoded fourth partial signals.

Abstract: Methods and systems for decompressing data are described. The relative magnitudes of a first value and a second value are compared. The first value and the second value represent respective endpoints of a range of values. The first value and the second value each have N bits of precision. Either the first or second value is selected, based on the result of the comparison. The selected value is scaled to produce a third value having N+1 bits of precision. A specified bit value is appended as the least significant bit of the other (non-selected) value to produce a fourth value having N+1 bits of precision.

Abstract: Systems and methods are described for encoding quantized vector parameters in a bitstream are described. An exemplary method may include receiving a vector of integers used in a data compression codebook, the sum of the integers equaling a pulse sum. An initial expected magnitude may be determined for a first integer, the initial expected magnitude being based on the pulse sum, a distribution parameter, and a value corresponding to a number of integers in the vector. The actual magnitude of the first integer may be encoded based on the initial expected magnitude of the first integer. The pulse sum may be adjusted using the encoded actual magnitude. Also, the value corresponding to the number of integers in the vector may be reduced by one. Expected magnitudes for each of the remaining integers of the vector may then be calculated recursively.

Abstract: Sensor data is received from one or more sensors. The sensor data is organized within a hierarchy. The sensor data is organized within a hierarchy that is non-dyadic. A processor of a computing device generates a discrete wavelet transform, based on the sensor data and based on the hierarchy of the sensor data, to compress the sensor data. The sensor data, as has been compressed via generation of the discrete wavelet transform, is processed.

Abstract: A method and apparatus for compressing signal samples uses block floating point representations where the number of bits per mantissa is determined by the maximum magnitude sample in the group. The compressor defines groups of signal samples having a fixed number of samples per group. The maximum magnitude sample in the group determines an exponent value corresponding to the number of bits for representing the maximum sample value. The exponent values are encoded to form exponent tokens. Exponent differences between consecutive exponent values may be encoded individually or jointly. The samples in the group are mapped to corresponding mantissas, each mantissa having a number of bits based on the exponent value. Removing LSBs depending on the exponent value produces mantissas having fewer bits. Feedback control monitors the compressed bit rate and/or a quality metric. This abstract does not limit the scope of the invention as described in the claims.

Abstract: A method and apparatus for compressing signal samples uses block floating point representations where the number of bits per mantissa is determined by the maximum magnitude sample in the group. The compressor defines groups of signal samples having a fixed number of samples per group. The maximum magnitude sample in the group determines an exponent value corresponding to the number of bits for representing the maximum sample value. The exponent values are encoded to form exponent tokens. Exponent differences between consecutive exponent values may be encoded individually or jointly. The samples in the group are mapped to corresponding mantissas, each mantissa having a number of bits based on the exponent value. Removing LSBs depending on the exponent value produces mantissas having fewer bits. Feedback control monitors the compressed bit rate and/or a quality metric. This abstract does not limit the scope of the invention as described in the claims.

Abstract: Methods and arrangements for providing a compressed representation of a number sequence. An input number sequence is received, as is a stored number sequence. The input number sequence is compared to the stored number sequence. The comparing includes determining a set of coefficients corresponding to the input number sequence, via solving at least one algebraic equation, the at least one algebraic equation comprising at least one of: an arithmetic equation, and an exponential equation. The comparing further includes applying at least one test to determine whether the set of coefficients identifies at least a portion of the stored number sequence as matching the entire input number sequence.

Abstract: Method and system for partially cloning a data container with compression is provided. A storage operating system determines if a portion of a source data container that is to be cloned includes a plurality of compressed blocks that are compressed using a non-variable compression group size. The operating system clones the plurality compressed blocks with the non-variable compression group size and de-compresses a plurality of blocks of the data container that are not within the non-variable compression group size. The plurality of compressed blocks and the plurality of blocks that are not within the non-variable compression group size are then stored as a partially cloned copy of the source data container.

Abstract: A plurality of specialized processing blocks in a programmable logic device, including multipliers and circuitry for adding results of those multipliers, can be configured as a larger multiplier by adding to the specialized processing blocks selectable circuitry for shifting multiplier results before adding. In one embodiment, this allows all but the final addition to take place in specialized processing blocks, with the final addition occurring in programmable logic. In another embodiment, additional compression and adding circuitry allows even the final addition to occur in the specialized processing blocks.

Abstract: Embodiments disclosed herein include vector processing carry-save accumulators employing redundant carry-save format to reduce carry propagation. The multi-mode vector processing carry-save accumulators employing redundant carry-save format can be provided in a vector processing engine (VPE) to perform vector accumulation operations. Related vector processors, systems, and methods are also disclosed. The accumulator blocks are configured as carry-save accumulator structures. The accumulator blocks are configured to accumulate in redundant carry-save format so that carrys and saves are accumulated and saved without the need to provide a carry propagation path and a carry propagation add operation during each step of accumulation. A carry propagate adder is only required to propagate the accumulated carry once at the end of the accumulation.

Abstract: Systems and methods to reduce I/O (input/output) with regard to out-of-core liner solvers and/or to speed up out-of-core linear solvers.

Abstract: A method for compressing a cloud of points with imposed error constraints at each point is disclosed. Surfaces are constructed that approach each point to within the constraint specified at that point, and from the plurality of surfaces that satisfy the constraints at all points, a surface is chosen which minimizes the amount of memory required to store the surface on a digital computer.

Abstract: Compression of multidimensional sonic data is disclosed. Example methods disclosed herein to compress input multidimensional sonic data include decorrelating the input multidimensional sonic data to determine decorrelated multidimensional sonic data. In some such examples, the input multidimensional sonic data has a plurality of dimensions corresponding to a respective plurality of azimuthal directions from which the input multidimensional sonic data was obtained. In such examples, the decorrelated multidimensional sonic data is decorrelated among the plurality of dimensions of the input multidimensional sonic data. Such example methods also include processing the decorrelated multidimensional sonic data to determine compressed data representative of the input multidimensional sonic data.

Abstract: An image decoding method is an image decoding method of decoding coded image data, including selecting, based on a type of a decoding target signal, an arithmetic decoding method that is used to decode the decoding target signal, from among a plurality of arithmetic decoding methods that include: a first arithmetic decoding method which is performed based on a symbol occurrence probability obtained according to a context, and which involves update of the symbol occurrence probability according to a decoding symbol; and a second arithmetic decoding method which is performed based on a symbol occurrence probability obtained according to a context, and which maintains the symbol occurrence probability that is other than 50%.

Abstract: Various methods and devices are provided to address the need for reduced compression complexity in the area of compressive sensing. In one method, a vector x is compressed to obtain a vector y according to y=?RDx, where ?RD=U?RM·?RM is a compressive sensing matrix constructed using a second-order Reed-Muller code or a subcode of a second-order Reed-Muller code and U is a unitary matrix from the real or complex Clifford group G. In another method, vector y is decompressed to obtain vector x also according to y=?RDx. In some embodiments, decompression may involve computing y?=U?1y and then determining the vector x using the computed y?.

Abstract: A method for compressing measurement data which is transmitted from sensor control units via a data bus to a primary control unit of a battery management system for vehicles, includes transmitting a rate of change/slope of the measurement data to the primary control unit at a start of measurements. The method further includes transmitting deviations/differences in the measurement data from a current slope, and reconstructing, without loss of information, correct measured values from the rates of change/slope and the received deviations/differences with the primary control unit.

Abstract: Digital signal processing (“DSP”) circuit blocks are provided that can more easily work together to perform larger (e.g., more complex and/or more arithmetically precise) DSP operations if desired. These DSP blocks may also include redundancy circuitry that facilitates stitching together multiple such blocks despite an inability to use some block (e.g., because of a circuit defect). Systolic registers may be included at various points in the DSP blocks to facilitate use of the blocks to implement systolic form, finite-impulse-response (“FIR”), digital filters.

Abstract: A computer-implemented method includes dividing an image into one or more image channels for image compression. The method also includes dividing one or more of the image channels into one or more blocks. At least one of the blocks includes floating point representations of pixel values included in the block. The method also includes converting the floating point representations of pixel values into integer representations such that the sign of each floating point representation is preserved. The method also includes storing the difference of adjacent integer representations as a compressed version of the image.

Abstract: The disclosure relates to a method for estimating the number of leader vectors with norm lp equal to r?p,d, of dimension d, having co-ordinates which are lower than, or equal to k. The method is characterized in that r p delta, d is determined by the sum of the results of a function T(Xi) for i varying between 1 and d, the function T(Xi) providing, for at least some of the leader vectors, the result of the division of the co-ordinate Xi raised to the power p by a delta precision factor, the result of the division being rounded to the nearest whole number. The method does not comprise a step of determining leader vectors.

Abstract: Various embodiments of the present invention provide apparatuses and methods for encoding and decoding data for constrained systems with reduced or eliminated need for hardware and time intensive arithmetic operations such as multiplication and division.

Abstract: A method for decoding run-length encoded (RLE) data includes the steps of receiving the RLE data and storing a predetermined value (e.g., zero) in each of a plurality of consecutively-accessible storage locations of a buffer. The method further includes writing a first value different than the predetermined value to a first storage location based on the RLE data, jumping over (i.e., skipping) a number of the consecutively-accessible storage locations from the first storage location to a next storage location based on the RLE data, and writing a next value different than the predetermined value to the next storage location based on the RLE data. In the case of JPEG, the values stored in the storage locations of the buffer are quantized coefficients associated with a block of image data. A run-length decoder is also described.

Abstract: The LLMICT transform matrices are orthogonal, hence their inverses are their transpose. The LLMICT transform matrices are integer matrices, which can be implemented with high precision eliminating the drift error in video coding. The fast algorithms for the LLMICT transform are found, thus allowing a lower requirement on computation hardware. The LLMICT is also found to have high transform coding gain due to its similarity to the DCT.

Abstract: The present application addresses a fundamental problem in the design of computing systems, that of minimizing the cost of memory access. This is a fundamental limitation on the design of computer systems as regardless of the memory technology or manner of connection to the processor, there is a maximum limitation on how much data can be transferred between processor and memory in a given time, this is the available memory bandwidth and the limitation of compute power by available memory bandwidth is often referred to as the memory-wall. The solution provided creates a map of a data structure to be compressed, the map representing the locations of non-trivial data values in the structure (e.g. non-zero values) and deleting the trivial data values from the structure to provide a compressed structure.

Abstract: An integrated memory controller (IMC) may sit on the main CPU bus or a high speed system peripheral bus and couple to system memory. The IMC may use a lossless data compression and decompression scheme for improved performance. The IMC may also include microcode for specific decompression of particular data formats such as digital video and digital audio. Compressed data may be decompressed in the IMC and stored into system memory or saved in the system memory in compressed format. Internal memory mapping may allow for format definition spaces which may define the format of the data and the data type to be read or written. Software overrides may be placed in applications software in systems that desire to control data decompression at the software application level.

Abstract: Configurable compression and decompression of waveform data in a multi-core processing environment improves the efficiency of data transfer between cores and conserves data storage resources. In waveform data processing systems, input, intermediate, and output waveform data are often exchanged between cores and between cores and off-chip memory. At each core, a single configurable compressor and a single configurable decompressor can be configured to compress and to decompress integer or floating-point waveform data. At the memory controller, a configurable compressor compresses integer or floating-point waveform data for transfer to off-chip memory in compressed packets and a configurable decompressor decompresses compressed packets received from the off-chip memory. Compression reduces the memory or storage required to retain waveform data in a semiconductor or magnetic memory. Compression reduces both the latency and the bandwidth required to exchange waveform data.

Abstract: Digital signal processing (“DSP”) circuit blocks are provided that can more easily work together to perform larger (e.g., more complex and/or more arithmetically precise) DSP operations if desired. These DSP blocks may also include redundancy circuitry that facilitates stitching together multiple such blocks despite an inability to use some block (e.g., because of a circuit defect). Systolic registers may be included at various points in the DSP blocks to facilitate use of the blocks to implement systolic form, finite-impulse-response (“FIR”), digital filters.

Abstract: An image coding method including: binarizing a first component and a second component which are included in last position information, to generate a first binary signal and a second binary signal, respectively; coding, by first arithmetic coding, a first partial signal which is a part of the first binary signal and a second partial signal which a part of the second binary signal, and coding, by second arithmetic coding, a third partial signal which is another part of the first binary signal and a fourth partial signal which is another part of the second binary signal; and placing the coded first through fourth partial signals in a bit stream, wherein in the placing, (i) the coded second partial signal is placed next to the coded first partial signal, or (ii) the coded fourth partial signal is placed next to the coded third partial signal.

Abstract: A method of compressing data output from an acceleration measurement means configured to be transported, carried or worn by a user is provided. Acceleration values indicative of the movement of the user are measured at a first frequency and values representative of the measured acceleration values are generated at a second frequency, which is lower than the first frequency. The step of generating comprises: defining a plurality of time windows, each time window containing a plurality of measured acceleration values; and applying a transformation to the measured acceleration values within each time window to generate a plurality of transformed values. For each time window, storing at least one of said plurality of transformed values and/or one or more parameters associated therewith.