Abstract: A document processing apparatus includes a processor. The processor receives a document in which components suitable for a creation purpose are disposed. The processor extracts a piece of pattern information from pattern information stored in a memory. The extracted pattern information corresponds to the creation purpose of the received document. The memory stores the pattern information in which item values of items are set in association with a document creation purpose. The item values of the items define a document pattern. The processor refers to the extracted pattern information and sets a pattern for the components disposed in the received document.

Abstract: Disclosed systems and methods determine a reading order of an electronic document. In an example, a document processing application accesses a content stream that includes a first object with a first location within the electronic document, a second object with a second location within the electronic document, and a third object with a third location within the electronic document. The application computes a region that includes the first object and the second object by determining that the second object is adjacent to the first object in a first dimension, at least a portion of the first and second objects are aligned in a second dimension, and the boundaries of the region do not intersect or encompass the third object. Based on the objects in the region, the application determines that a reading order should include the first object and the second object and should exclude the third object.

Abstract: A webpage containing information to be extracted may undergo changes to a layout of elements that present the information. These changes could result in an inability to retrieve the information later. A first graph is determined that represents elements of a first version of a webpage at a first time. An element in the first graph for which information is being acquired is specified. A relevant portion of the first graph is designated that includes the element and immediate neighbors in the first graph. Later, a second version of the webpage is retrieved, and a second graph of that second version is determined. The relevant portion of the first graph is compared to the second graph. If a match is found, the information of interest is extracted from the specified element of the second graph. This allows extraction of information to proceed even if the layout of elements changes.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for dynamic document annotations. In some implementations, a keyword is identified in a first view of a document, the first view being provided on a user interface. An annotation for the keyword is provided for display at a first location with the first view provided on the user interface. An adjustment to the first view is detected that causes a second view of the document on the user interface, where a position of the keyword in the second view is different from a position of the keyword in the first view. In response to detecting the adjustment to the first view, the annotation is hidden from the user interface, and, after hiding the annotation, the annotation for the keyword is provided for display at a second location with the second view of the document.

Abstract: Ontology-based semantic rendering is performed by retrieving a rendering script from a location represented by an ontology reference of a concept of content included in a document, the document further including an ontology dataset identifier of the concept and the ontology reference, and rendering the concept of content according to the rendering script and a mode of rendering represented by a rendering device.

Abstract: A digital story includes textual, visual, and/or audio aspects. Generation of a new digital story and/or editing of an existing digital story can include, for instance, coordinating presentation of textual, visual, and/or audio aspects of the digital story. A digital story can be viewed and/or accessed by a user remote from one or more authors of the digital story.

Abstract: A system and method are provided for generating and publishing electronic content using predetermined templates. The method comprises providing a predetermined template specifying a predetermined layout for at least one slide to contain content; enabling the content to be added to the template by a plurality of contributors, each contributor having access to a project comprising the template over a network; receiving the content; and compiling a published output according to the received content and parameters of the predetermined template.

Abstract: A system for generating product label changes is described. The system includes a product labeling platform executable on a network enabled computing device and a database of at least one selectable master label and at least one selectable jurisdiction label associated with a labeled product. The platform associates at least one selected descriptor from a first pre-defined descriptor set to each change made to a selected master label, and further associates at least one selected descriptor from a second pre-defined descriptor set to each change made to a selected jurisdiction label. The platform further associates a report including the selected descriptors from the first and second pre-defined descriptor sets with the changed label. A system for generating and managing product labels for a product across multiple jurisdictions is also disclosed.

Abstract: A syntactic analysis apparatus according to an embodiment of the present disclosure may include an input device receiving a phrase uttered from a user, and a learning device performing at least one or more of extension of an intent output layer for classifying an utterance intent of the user from the uttered phrase and extension of a slot output layer for classifying a slot including information of the phrase and extending a pre-generated utterance syntactic analysis model, such that the uttered phrase is classified into the extended intent output layer and the extended slot output layer, thereby broadly classifying an intent and a slot for the phrase uttered from a user.

Abstract: Methods and apparatus for using one or more feature recognition system(s) to identify features in a scanned image and to associate tags with identified features are described. Probabilities of a feature being present are taken into consideration in some embodiments. In various embodiments once a tag has been determined as corresponding to a feature which has been confirmed as being in the scanned image synonyms for the tag word are identified and also associated with the scanned image. By using results of multiple automated feature recognition systems and generating overall probabilities that a feature is present in an image more reliable tagging can be implemented in an automated manner than in system which rely on a single AI system without the need for extensive operator input with respect to identification of all features in the image which are to be tagged.

Abstract: An automated presentation review system includes a controller in communication with a user device, the user device comprising an input mechanism and a display mechanism, and a memory coupled to the controller. The controller displays a graphical user interface through which a presentation review window is displayed. The presentation review window simultaneously provides a presentation display frame displaying a presentation comprising plurality of presentation slides and a results display frame. The controller then displays results of an analysis of the presentation that includes one or more icons signifying an inconsistency identified in the presentation across the plurality of presentation slides.

Abstract: According to one embodiment of the present invention, a system for modifying content associated with an item comprises at least one processor. Features of interest of the item to a plurality of different groups are determined based on user comments produced by members of the plurality of different groups. The members within each group have a common characteristic. The features of interest to each group within the content associated with the item are identified, and the content associated with the item is modified by balancing the features of interest to the plurality of different groups within the content associated with the item. Embodiments of the present invention further include a method and computer program product for modifying content associated with an item in substantially the same manner described above.

Abstract: An apparatus comprises processing circuitry configured to pre-process text data for inputting to a trained model, the pre-processing comprising: receiving a set of text data including numerical information, the set of text data comprising a plurality of tokens, wherein a first subset of the plurality of tokens comprises tokens that do not comprise numerical information, and a second subset of the plurality of tokens comprises tokens that each comprise respective numerical information; transforming each of the plurality of tokens into a respective encoding vector, each of the plurality of tokens in the second subset having a common encoding vector; assigning a respective numerical vector to each of the plurality of tokens, wherein each token in the second subset is assigned a respective numerical vector in dependence on the numerical information in said token; and combining the encoding vectors and numerical vectors to obtain a vector representation of the text data.

Abstract: A system and method are presented for model derivation for entity prediction. An LSTM with 100 memory cells is used in the system architecture. Sentences are truncated and provided with feature information to a named-entity recognition model. A forward and a backward pass of the LSTM are performed, and each pass is concatenated. The concatenated bi-directional LSTM encodings are obtained for the various features for each word. A fully connected set of neurons shared across all encoded words is obtained and the final encoded outputs with dimensions equal to the number of entities is determined.

Abstract: Providing cognitive responses with an electronic message system includes predicting an urgency level corresponding to an electronic message received by the system based on detecting pre-defined features within the message and assigning a classification to the message based on the detected features. The message and corresponding urgency level can be mapped to a response action based on the classification assigned to the message. A notification of the response action and corresponding urgency level can be generated.

Abstract: The present disclosure provides a method, which may comprise obtaining a plurality of essay prompts, processing each essay prompt of said plurality of essay prompts using a natural language processing (NLP) algorithm to extract at least one feature from said each essay prompt and, using said at least one feature from said each essay prompt, generating two or more subsets of said plurality of essay prompts, wherein an essay prompt in a subset satisfies a measure of similarity with respect to each other essay prompt in said subset such that a single essay can be responsive to each essay prompt in said subset.

Abstract: Systems and methods for identifying data of interest are disclosed. The system may retrieve unstructured data from an internet data source via an alert system or RSS feed. The system may input the unstructured data into various models and scoring systems to determine whether the data is of interest. The models and scoring systems may be executed in order or in parallel. For example, the system may input the unstructured data into a Naïve Bayes machine learning model, a long short-term memory (LSTM) machine learning model, a named entity recognition (NER) model, a semantic role labeling (SRL) model, a sentiment scoring algorithm, and/or a gradient boosted regression tree (GBRT) machine learning model. Based on determining that the unstructured data is of interest, a data alert may be generated and transmitted for manual review or as part of an automated decisioning process.

Abstract: The present disclosure provides computing systems and techniques for indicating an emotional and/or environmental state of a user in a digital messaging application. A computing device can determine an emotional and/or environmental state of a first user responsive to reading or responding to a message and can convey the determined emotional and/or environmental state to a second computing device, to be transiently presented by the second computing device.

Abstract: Provided are methods and systems for detecting deception in computer-mediated communications that can include (i) parsing digital text to identify processable language-action cues in the digital text, (ii) automatically analyzing, using a computing device and using a machine learning-based classifying algorithm, the processable language-action cues to produce respective probabilities of the digital text including the deceptive content, where the machine learning-based classifying algorithm is trained with training data including (A) training language-action cues from digital data indicating response information known to be deceptive and digital data indicating response information known to be truthful and (B) respective predictor weights associated with the training language-action cues, and (iii) displaying a histogram on a user display device, where the histogram indicates, over a period of time, frequencies of the respective probabilities of the digital text including the deceptive content.

Abstract: A processor is configured to execute instructions stored in a memory to identify distinct vehicle operational scenarios; instantiate decision components, where each of the decision components is an instance of a respective decision problem, and where the each of the decision components maintains a respective state describing the respective vehicle operational scenario; receive respective candidate vehicle control actions from the decision components; select an action from the respective candidate vehicle control actions, where the action is from a selected decision component of the decision components, and where the action is used to control the AV to traverse a portion of the vehicle transportation network; and generate an explanation as to why the action was selected, where the explanation includes respective descriptors of the action, the selected decision component, and a state factor of the respective state of the selected decision component.

Abstract: Embodiments of the present disclosure are directed to a system, methods, and computer-readable media for facilitating stylistic expression transfers in machine translation of source sequence data. Using integrated loss functions for style transfer along with content preservation and/or cross entropy, source sequence data is processed by an autoencoder trained to reduce loss values across the loss functions at each time step encoded for the source sequence data. The target sequence data generated by the autoencoder therefore exhibits reduced loss values for the integrated loss functions at each time step, thereby improving content preservation and providing for stylistic expression transfer.

Abstract: Systems and methods are described herein for replaying content dialogue in an alternate language in response to a user command. While the content is playing on a media device, a first language in which the content dialogue is spoken is identified. Upon receiving a voice command to repeat a portion of the dialogue, the language in which the command was spoken is identified. The portion of the content dialogue to repeat is identified and translated from the first language to the second language. The translated portion of the content dialogue is then output. In this way, the user can simply ask in their native language for the dialogue to be repeated and the repeated portion of the dialogue is presented in the user's native language.

Abstract: A reader device for attachment to a smart device comprising a display, the reader comprising an antenna, processing and reading circuitry, and a communications module, wherein the antenna, the processing and reading circuitry, the processor and the communications module are coupled to each other, and whereby the antenna encloses said display. When a card is tapped on the display, the antenna receives a signal and transmits the signal to the processing and reading circuitry. The processing and reading circuitry processes the signal to produce data, and the produced data is transmitted to a device external to the reader device by the communications module.

Abstract: High density read chambers are provided for scanning and/or encoding a plurality of RFID tagged items. Such chambers may include an enclosure with an interior defined by upper and lower surfaces, with a sidewall extending therebetween. An access (such as a door) may be associated with at least one of the surfaces or the sidewall, with the access being at least partially opened to access the interior of the enclosure from an outside location. The chamber further includes an antenna positioned within the interior of the enclosure and an RFID reader associated with the antenna. The RFID reader receives signals from and/or transmits signals to the antenna, while the antenna emits a scanning or encoding signal within the interior of the enclosure, with at least a portion of at least one of the surfaces or the sidewall including a signal-reflective material facing the interior of the enclosure.

Abstract: A switching device can provide a pass-through connection between a first set of reader inputs and antenna inputs. The switching device can disconnect the pass-through connection between the first set of reader inputs from a first reader and the plurality of antenna inputs. The switching device can generate a tuned signal based on the antenna inputs. The switching device can provide the tuned signal to a second set of reader inputs for a second reader.

Abstract: Systems, apparatuses and methods may provide for replacing floating point matrix multiplication operations with an approximation algorithm or computation in applications that involve sparse codes and neural networks. The system may replace floating point matrix multiplication operations in sparse code applications and neural network applications with an approximation computation that applies an equivalent number of addition and/or subtraction operations.

Abstract: The disclosed embodiments are generally directed to improving feature detection of rapidly acquired images using camera-enabled mobile devices involving a 2-D decal code, such as a QR code, for improving the reading accuracy of a rapid diagnostic antigen or antibody or enzymatic colorimetric directed test, such as for COVID-19 diagnosis. One primary issue with evaluating a Covid-19 rapid test is detecting and quantifying positive test lines from sampled test strips based on digital images of the test strip. Aspects of the present invention contemplate masking a QR code to improve the sample image resolution and contrast. Other aspects of the present invention contemplate methods and techniques to evaluate a test line on the sample image by enhancing an intensity curve along the test line and control line containing area by way of calculating the instantaneous change in pixel intensity and evaluating the position and intensity of those signals.

Abstract: The present disclosure relates to data readers including an improved imaging system that optimizes active and passive autofocus techniques for improving data reading functions. In an example, the data reader initially uses active autofocus techniques to focus a lens system based on a measurement reading by a rangefinder and acquire an image of an item in the field-of-view of the data reader. The data reader includes a decoding engine operable to decode an optical code of the item using the acquired image. If the decoding engine is unable to decode the optical code using the active autofocus technique, the data reader alternates to a passive autofocus technique to alter the focus settings of the lens system and reattempt the decoding process.

Abstract: Techniques are disclosed for using tag placement to determine 3D object orientation. An extended reality (XR) system detects, in a two-dimensional image, a data marker associated with an object viewable in an XR environment. The XR system applies a first function to the data marker to generate a rectilinear data marker by transforming a quadrilateral that circumscribes the data marker into a rectangle. The XR system determines a three-dimensional orientation of the object based on transformation of the data marker to the rectilinear data marker. The XR system determines an XR object associated with the data marker. The XR system applies a second function to the XR object, where the second function uses the three-dimensional orientation of the data marker to modify an orientation of the XR object to generate a transformed XR object. The XR system causes the transformed XR object to be displayed within the two-dimensional image.

Abstract: An information processing system including a circuitry configured to detect first identification information used to identify a job, generate second identification information associated with the first identification information, and create a slip on which the first identification information and the second identification information are displayed.

Abstract: A printing device includes a mounting part to which consumables to be used for printing is mounted, a print engine configured to print an image on a recording medium using the consumables, a display configured to display information regarding the consumables, and a controller. The printing device is operable based on a concluded contract with a contractor for the consumables used for printing. The controller is configured to perform obtaining arrival time information of a first consumable, determining a model of the consumables, and displaying consumable handling related information on the display based on the arrival time information and a determining result.

Abstract: An apparatus and method directed to a coin-type digital currency device that provides for a portable smart coin that has a universal and variable value with enhanced security features. The coin-type digital currency device is activated for a transaction and placed in a position proximate to a communications device and the communications device is altered that a transaction is awaiting execution. A secure communications link is established between the coin-type digital currency device and the communications device using a combination of RF and optical communications. Once the secure communications is established, the transaction is approved, executed, and registered together with updating the currency balance associated with the coin-type digital currency device.

Abstract: A system for determining positions of labels. Each label includes a processor and a transmitting and receiving device, and each label is configured for transmitting an electromagnetic first type beacon signal. The labels are also configured for receiving first type beacon signals from other labels, and for determining first type positioning data. The labels are also configured to transmit information about the positioning data. The system includes a receiver for receiving transmitted information about the positioning data, and a computer configured to calculate, on the basis of the received information, the relative positions of the labels relative to each other. The information about the relative positions of the labels can be exported by means of an electrical information signal.

Abstract: A system for controlling assignment and management of identities in ambient electromagnetic power harvesting (AEPH) chips. The system comprises a processor; a non-transitory memory; and an application stored in the non-transitory memory that, when executed by the processor, allocates a plurality of unique AEPH identities, wherein each unique identity comprises an identity of a product item and an instance identity; stores the plurality of unique AEPH identities in a first immutable record in a datastore, wherein the unique AEPH identities are associated with an initial state; provides the plurality of unique AEPH identities to an original equipment manufacturer of AEPH chips; provides an application programming interface (API); authorizes a request to update a state associated with a first unique AEPH identity in the datastore; and adds a second immutable record to the database that associates the first unique AEPH identity with an updated state of the first unique AEPH identity.

Abstract: A key fob, comprising an electronic communication circuit, a processor, and a battery configured to power the electronic communication circuit and the processor, further comprises: a communication module for exchanging data with an external electronic communication device, an access control module for exchanging access control data with an external electronic access control device, and a user activatable operating element which activates the communication module, or the access control module, depending on actuation of the operating element by a user.

Abstract: An identification device is provided having an optical detector (1), a controller (5) and an identification transmitter unit (6), wherein the optical detector (1) has a detection area with an identification pattern partially covering the detection area and the controller (5) is designed to interact with the detector (1) and the identification transmitter unit (6) in such a manner that the identification transmitter unit (6) can be activated to transmit an identification signal depending on an analysis of the temporal sequence of measurement signals from the detector (1). A method is also provided for identifying an object by an identification system.

Abstract: A wireless IC tag-attached metal medical instrument includes a metal medical instrument including a metal portion. The metal medical instrument is configured such that electric, magnetic, or electromagnetic field coupling is established between a resonant circuit and the metal portion when a wireless IC tag is fixed to the metal portion that includes the resonant circuit having an inductor with a spiral or helix shape that turns around a central axis more than one turn. In this configuration, the metal portion either emits a transmission signal with a frequency equal to a resonant frequency of an electromagnetic wave supplied from the resonant circuit or receives a reception signal having a frequency equal to the resonant frequency, and supplies the reception signal to the resonant circuit.

Abstract: An RFIC module includes an insulating substrate; a stacked coil formed into a plurality of layers in the insulating substrate and formed along four side surfaces of the insulating substrate; an RFIC mounted on a first planar surface of the insulating substrate; and a planar coil disposed on a second planar surface of the insulating substrate, that partially has an open portion, and that overlaps the stacked coil in a plan view of the insulating substrate. The stacked coil is connected to the RFIC. The RFIC is disposed at a position close to a first side surface and close to a third side surface of the insulating substrate. A part of the RFIC overlaps the stacked coil in a plan view of the insulating substrate. The open portion of the planar coil is formed at a position close to the first side surface.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network that is used to select actions to be performed by an agent interacting with an environment. In one aspect, the method comprises: receiving an observation characterizing a current state of the environment; processing the observation and an exploration importance factor using the action selection neural network to generate an action selection output; selecting an action to be performed by the agent using the action selection output; determining an exploration reward; determining an overall reward based on: (i) the exploration importance factor, and (ii) the exploration reward; and training the action selection neural network using a reinforcement learning technique based on the overall reward.

Abstract: A system and methods for generating and applying learning agents in simulated environments, in which an agent simulation is selected, one or more agent goals are received, and agents are created which are individual instances of the agent simulation with each agent having at least one of the agent goals, wherein the agents are used in the execution of an environment simulation which dynamically changes based on the collective behavior of the agents.

Abstract: Systems and methods for providing executable instructions to a neural network processor are provided. In one example, a system comprises a database that stores a plurality of executable instructions and a plurality of subgraph identifiers, each subgraph identifier of the plurality of subgraph identifiers being associated with a subset of instructions of the plurality of executable instructions.

Abstract: Methods, systems, and apparatus for classifying a new example using a comparison set of comparison examples. One method includes maintaining a comparison set, the comparison set including comparison examples and a respective label vector for each of the comparison examples, each label vector including a respective score for each label in a predetermined set of labels; receiving a new example; determining a respective attention weight for each comparison example by applying a neural network attention mechanism to the new example and to the comparison examples; and generating a respective label score for each label in the predetermined set of labels from, for each of the comparison examples, the respective attention weight for the comparison example and the respective label vector for the comparison example, in which the respective label score for each of the labels represents a likelihood that the label is a correct label for the new example.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for learning from delayed outcomes using neural networks. One of the methods includes receiving an input observation; generating, from the input observation, an output label distribution over possible labels for the input observation at a final time, comprising: processing the input observation using a first neural network configured to process the input observation to generate a distribution over possible values for an intermediate indicator at a first time earlier than the final time; generating, from the distribution, an input value for the intermediate indicator; and processing the input value for the intermediate indicator using a second neural network configured to process the input value for the intermediate indicator to determine the output label distribution over possible values for the input observation at the final time; and providing an output derived from the output label distribution.

Abstract: Disclosed is a method for distributed type training adaptation and apparatus in a deep learning framework and an AI accelerator card. The method includes the following steps: S1: the deep learning framework supports single-card configuration in a newly added AI accelerator card, and sub-steps thereof are as follows: S11: the deep learning framework supports new hardware; S12: the deep learning framework supports a device thread of the new hardware; S13: the deep learning framework supports a memory operation of the new hardware; and S14: the deep learning framework supports an operator kernel function of the new hardware; S2: the deep learning framework supports multi-card configuration in the newly added AI accelerator card; S3: the deep learning framework supports tensor segmentation and multi-card distribution; and S4: the deep learning framework supports multi-card collective communication in the newly added AI accelerator card.

Abstract: A computer-implemented method of training a student machine learning system comprises receiving data indicating execution of an expert, determining one or more actions performed by the expert during the execution and a corresponding state-action Jacobian, and training the student machine learning system using a linear-feedback-stabilized policy. The linear-feedback-stabilized policy may be based on the state-action Jacobian. Also a neural network system for representing a space of probabilistic motor primitives, implemented by one or more computers. The neural network system comprises an encoder configured to generate latent variables based on a plurality of inputs, each input comprising a plurality of frames, and a decoder configured to generate an action based on one or more of the latent variables and a state.

Abstract: Users interact with a computer system, which collects data about individual interactions the users have had with the computer system. The users are sorted into one of a first group or a second group. The computer system generates respective user sequence models for the users using information representing the individual interactions. The computer system analyzes the respective user sequence models using a recurrent neural network with an attention mechanism, which produces respective vectors corresponding to the user sequence models. Individual values in the vectors represent respective individual interactions by a given user and correspond to an amount of correlation between the respective individual interactions and the sorting of the given user into the first group or the second group. The computer system identifies a particular type of interaction that is correlated to users being sorted into the first group by analyzing the respective vectors.

Abstract: An apparatus to facilitate accelerating neural networks with low precision-based multiplication and exploiting sparsity in higher order bits is disclosed. The apparatus includes a processor comprising a re-encoder to re-encode a first input number of signed input numbers represented in a first precision format as part of a machine learning model, the first input number re-encoded into two signed input numbers of a second precision format, wherein the first precision format is a higher precision format than the second precision format. The processor further includes a multiply-add circuit to perform operations in the first precision format using the two signed input numbers of the second precision format; and a sparsity hardware circuit to reduce computing on zero values at the multiply-add circuit, wherein the processor to execute the machine learning model using the re-encoder, the multiply-add circuit, and the sparsity hardware circuit.

Abstract: Neuromorphic methods, systems and devices are provided. The embodiment may include a neuromorphic device which may comprise a crossbar array structure and an analog circuit. The crossbar array structure may include N input lines and M output lines interconnected at junctions via N×M electronic devices, which, in preferred embodiments, include, each, a memristive device. The input lines may comprise N1 first input lines and N2 second input lines. The first input lines may be connected to the M output lines via N1×M first devices of said electronic devices. Similarly, the second input lines may be connected to the M output lines via N2×M second devices of said electronic devices. The analog circuit may be configured to program the electronic devices so as for the first devices to store synaptic weights and the second devices to store neuronal states.

Abstract: Systems and methods are disclosed for inquiry-based deep learning. In one implementation, a first content segment is selected from a body of content. The content segment includes a first content element. The first content segment is compared to a second content segment to identify a content element present in the first content segment that is not present in the second content segment. Based on an identification of the content element present in the first content segment that is not present in the second content segment, the content element is stored in a session memory. A first question is generated based on the first content segment. The session memory is processed to compute an answer to the first question. An action is initiated based on the answer. Using deep learning, content segments can be encoded into memory. Incremental questioning can serve to focus various deep learning operations on certain content segments.

Abstract: This disclosure provides a computer-implemented method. The method may comprise estimating a value range of a water body parameter based on measured data for a water quality indicator of a first set of time-spatial points and measured data for the water quality indicator of a second set of time-spatial points; and determining an optimal value of the water body parameter from the estimated value range by comparing the measured data for the water quality indicator of the second set and simulated data for the water quality indicator of the second set, wherein the simulated data for the water quality indicator of the second set is obtained based on a fluid dynamic model using the measured data for the water quality indicator of the first set as an input of the fluid dynamic model and using a value in the estimated value range as a parameter of the fluid dynamic model.