Abstract: A system and method for table conversion including converting a table containing text in tabular form to an image, labeling each text area of the image with a bounding box, determining for each bounding box, a position information, a semantic information, and an image information, reconstructing the image into a graph form having a plurality of nodes, wherein each node represents the bounding box of the text areas of the image, inputting at least two nodes into a trained neural network to determine a relative relationship between the at least two nodes, building a knowledge graph using the relative relationship of the at least two nodes, and translating the knowledge graph into machine readable natural language.

Abstract: A system and method for field extraction including determining a key position of a key in an electronic file, isolating candidate key values based on a distance from the key position, selecting a key value from the candidate key values based on an output of a trained neural network, and extracting the key and the key value from the electronic file, regardless of a key-value structure.

Abstract: A method, computer program product, and computer system for generating and using a basic state layer. N task models are provided (N ? 2). Each task model was trained on a same pre-trained backbone model. Each task model includes M feature layers and a task layer (M ? 1). Each feature layer of each task model includes a parameter matrix that is different for the different models. An encoder-decoder model is trained. The encoder-decoder model includes sequentially: an input layer, an encoder, M hidden layers, a decoder, and an output layer. The encoder is a neural network that maps and compresses the parameter matrices in the input layer into the M hidden layers, which generates a basic state model. The decoder is a neural network that receives the basic state model as input and generates the output layer to be identical to the input layer.

Abstract: Embodiments of the present disclosure relate to question answering. A computer-implemented method includes determining a plurality of intention candidates of a user from the user's question; determining a set of entities and attributes associated with the set of entities from the plurality of intention candidates; constructing a decision tree from the set of entities and the attributes associated with the set of entities, wherein each node of the decision tree is associated with a respective one of the attributes and represents a respective subset of the plurality of intention candidates, and wherein the respective subset of the plurality of intention candidates are split based on the entities associated with the respective one of the attributes; and generating a question corresponding to a node of the decision tree to determine the user's intention.

Abstract: A computer-implemented method, according to one embodiment, includes: receiving an image having characters that correspond to a language, and using a text recognition algorithm to determine a first language believed to correspond to the characters. A first confidence level associated with the first language is also computed, and a determination is made as to whether the first confidence level associated with the first language is outside a predetermined range. In response to determining that the first confidence level associated with the first language is not outside the predetermined range, the first language is output as the given language. The text recognition algorithm is trained using a simple shallow neural network and a generated mixed language corpus. The generated mixed language corpus is formed by: randomly sampling libraries having vocabulary and/or characters therein, and combining the randomly sampled vocabulary and/or characters to form the generated mixed language corpus.

Abstract: A magnetic resonance (MR) imaging method of correcting nonuniformity in diffusion-weighted (DW) MR images of a subject is provided. The method includes applying a DW pulse sequence along a plurality of diffusion directions with one or more numbers of excitations (NEX), and acquiring a plurality of DW MR images of the subject along the plurality of diffusion directions with the one or more NEX. The method also includes deriving a reference image and a base image based on the plurality of DW MR images, generating a nonuniformity factor image based on the reference image and the base image, and combining the plurality of DW MR images into a combined image. The method also includes correcting nonuniformity of the combined image using the nonuniformity factor image, and outputting the corrected image.

Abstract: A method, system, and computer program product for segmenting and processing documents for optical character recognition is provided. The method includes receiving a document and detecting different types of text data. The document is divided into a plurality of text regions associated with the different types of said text data. Optical noise is removed from each text region and differing optical character recognition software code is selected for application to each text region. The differing optical character recognition software code is executed with respect to each text region resulting in extractable computer readable text located within each said text region.

Abstract: A data-driven model compression technique is introduced that only targets to provide same accuracy as the original (not compressed) model in certain areas by reducing compression parameters. A compression engine relies on backpropagation to determine an extent of parameter value changes and designate certain parameters as key parameters. The model matrix is reshaped according to importance of each neuron. Only randomly generated parameter values of the reshaped parameter matrix are fine tuned to create a reliable compressed neural network model.

Abstract: Label-based document classification using artificial intelligence includes collecting, by one or more processors, a plurality of pre-trained classification models into a model pool and a plurality of documents into a document pool. The collected plurality of pre-trained classification models are applied in parallel to the plurality of documents in the document pool to generate a list of labels. Based on the list of labels, a final label result is generated according to which a baseline algorithm for document classification is generated by the one or more processors.

Abstract: A method, system, and computer program product for segmenting and processing documents for optical character recognition is provided. The method includes receiving a document and detecting different types of text data. The document is divided into a plurality of text regions associated with the different types of said text data. Optical noise is removed from each text region and differing optical character recognition software code is selected for application to each text region. The differing optical character recognition software code is executed with respect to each text region resulting in extractable computer readable text located within each said text region.

Abstract: Systems and methods for suppressing Nyquist ghost for diffusion weighted magnetic resonance imaging are disclosed. An exemplary method includes acquiring multiple k-space data sets using multiple sets of diffusion weighted imaging pulse sequences, reconstructing a magnetic resonance image from each of the multiple k-space data sets respectively, and averaging magnitudes of the magnetic resonance images to generate an average magnitude magnetic resonance image.

Abstract: Systems and methods for suppressing Nyquist ghost for diffusion weighted magnetic resonance imaging are disclosed. An exemplary method includes acquiring multiple k-space data sets using multiple sets of diffusion weighted imaging pulse sequences, reconstructing a magnetic resonance image from each of the multiple k-space data sets respectively, and averaging magnitudes of the magnetic resonance images to generate an average magnitude magnetic resonance image.

Abstract: Provided are a proline hydroxylase and uses thereof. The proline hydroxylase comprises having the amino acid sequence of SEQ ID NO: 2 with the exception of a mutation of one or more amino acids; wherein the mutation of one or more amino acids must comprises E27K, and the mutation of one or more amino acids selected from the group consisting of: H14R, L16N, T25R, F26L, E27K, D30S, S33N, E34N, E34G, E34L, E34S, E34D, Y35W, Y35K, S37W, S37F, S37E, S37N, S37T, S37C, W40F, K41E, D54G, H55Q, S57L, I58T, I58Y, I58A, I58R, I58V, I58S, I58C, K86P, T91A, F95Y, C97Y, I98V, K106V, K106T, K106Q, F111S, K112E, K112R, S154A, K162E, L166M, I118F, I118V, I118R, H119R, H119F, I120V, K123D, K123N, K123Q, K123S, K123I, K123T, T130N, D134G, V135K, N165H, D173G, K209R, I223V and S225A, and having proline hydroxylase activity.

Abstract: Provided are a proline hydroxylase and uses thereof. The proline hydroxylase comprises (a) a protein having the amino acid sequence as shown in SEQ ID NO: 2; (b) a protein having an amino acid sequence of SEQ HD NO: 2 with a mutation of one or more amino acids and having a proline hydroxylase activity; or (c) a protein retaining the mutation of one or more amino acids as in (b), and having the proline hydroxylase activity and having at least 78% homology with the amino acid sequence of the protein in (b). Protein having the amino acid sequence as shown in SEQ HD NO: 2 and mutants obtained by genetically engineering have higher catalytic specificity or significantly increased catalytic activity when compared to proline hydroxylases in prior art.

Abstract: Provided are a proline hydroxylase and uses thereof. The proline hydroxylase comprises (a) a protein having the amino acid sequence as shown in SEQ ID NO: 2; (b) a protein having an amino acid sequence of SEQ HD NO: 2 with a mutation of one or more amino acids and having a proline hydroxylase activity; or (c) a protein retaining the mutation of one or more amino acids as in (b), and having the proline hydroxylase activity and having at least 78% homology with the amino acid sequence of the protein in (b). Protein having the amino acid sequence as shown in SEQ HD NO: 2 and mutants obtained by genetically engineering have higher catalytic specificity or significantly increased catalytic activity when compared to proline hydroxylases in prior art.

Abstract: An electronic device with a plurality of keys which correspond to a plurality of standard voltages respectively comprises a voltage generation module, a detection module, storage, an acquiring module, a comparison module, and an extraction module. The voltage generation module with an initial voltage decreases the initial voltage to the standard voltage corresponding to the pressed key. The detection module detects whether the current voltage of the voltage generation module is equal to the initial voltage. The storage stores the current voltage as a reference voltage when the current voltage is not equal to the initial voltage. The acquiring module acquires a current voltage of the voltage generation module after a predetermined time. The comparison module compares the acquired current voltage with the reference voltage. When the acquired current voltage is equal to the reference voltage, the extraction module executes an operation corresponding to the reference voltage.

Abstract: An electronic device with a battery displays a label for indicating different power levels of the battery. The label comprises a plurality of columns. Each of the columns is capable of being illuminated. A number of the columns lighted correspond to a corresponding the power levels in a one-to-one relationship. The electronic device comprises a detection module, storage, an acquiring module, a check module, and a display module. The detection module detects the current voltage of the battery at regular intervals and stores the information in the storage. The acquiring module acquires a previous detected voltage from the storage. The check module checks whether the current voltage is a fluctuated voltage. The display displays the label with the numbers of the lighted columns corresponding to the power level which contains the previous detected voltage when the current voltage is a fluctuated voltage.

Abstract: A control system for lighting up a screen of an electronic device is provided to decrease the length of user waiting time before activation of an electronic device. The device includes a state register. The state register is switched between a ready state and a non-ready state. The control system includes a detecting module, a first controlling module, and a second controlling module. The detecting module detects a ready or a non-ready state of the device. The first controlling module implements startup operations when the register is not in the ready state. The second controlling module lights up the screen when the state register is in the ready state. An electronic device and a method for lighting up the screen are also provided.

Abstract: An electronic device connected to an external device is capable of switching between a first state and a second state. The electronic device comprises a communication module, a detection module, a control module, and a processor. The communication module receives different control commands from the external device. The detection module detects whether the electronic device is in the first state or the second state, and generates corresponding signals.

Abstract: A testing signal generation device for testing performance of a disc drive includes a signal generating unit, a signal converting unit, and a signal transmitting unit. The signal generating unit generates at least one pulse signal for controlling the disc drive to work at predetermined working modes. The signal converting unit converts the at least one pulse signal into at least one test signal. The signal transmitting unit transmits the at least one test signal to the disc drive, to control the disc drive to read data from an optical disc in the disc drive. A testing signal generation method for testing performance of the disc drive is also provided.