Abstract: Provided is a movable electro-hydraulic composite drive spraying robot with a large working space, comprising movable bases, there being a plurality of movable bases cooperatively arranged for bearing a drive rope adjustment module, profile supporting columns in the driving rope adjusting module respectively being fixed on the movable bases, the plurality of movable bases encircling an operating space, a adjustable auxiliary motion platform that is movable being erected in the operating space, a rotary motion platform being arranged below the adjustable auxiliary motion platform, the adjustable auxiliary motion platform and the rotary motion platform being connected by means of a hydraulic push rod, the bottom end surface of the rotary motion platform being provided with a spray gun, and a balance mechanism and a fixed support mechanism for balancing the traction force of the rope and maintaining the balance of the mechanism also being mounted on the movable bases.

Abstract: A method and an apparatus for sequence labeling on an entity text, and a non-transitory computer-readable recording medium are provided. In the method, a start position of an entity text within a target text is determined. Then, a first matrix is generated based on the start position of the entity text. Elements in the first matrix indicates focusable weights of each word with respect to other words in the target text. Then, a named entity recognition model is generated using the first matrix. The named entity recognition model is obtained by training using first training data, the first training data includes word embeddings corresponding to respective texts in a training text set, and the texts are texts whose entity label has been labeled. Then, the target text is input to the named entity recognition model, and probability distribution of the entity label is output.

Abstract: The present invention relates to a coding gene of the SOSEKI protein SOK2 and an application thereof, wherein through molecular regulation of the SOSEKI protein SOK2, the flowering time of Panicum virgatum is delayed, biomass is increased, lignin content in the cell wall of Panicum virgatum is reduced and the fermentable sugar yield is boosted.

Abstract: Systems and methods for weakly supervised unit test quality scoring are disclosed. According to one embodiment, a method may include: parsing, by a generative model computer program, a plurality of code snippets in a repository using an abstract syntax tree; receiving, by the generative model computer program, a plurality of binary labelling functions from a labelling function repository; creating, by the generative model computer program, a labelling matrix by applying the binary labelling functions to the parsed code snippets; training, by the generative model computer program, a probabilistic generative model using the labelling matrix resulting in a vector of pseudo-labels; building, by a unit test scoring computer program, a discriminative model, wherein the discriminative model receives an array of real value inputs; and training, by the unit test scoring computer program, the discriminative model using the parsed code snippets, the vector of pseudo labels, and the abstract syntax tree.

Abstract: A method and an apparatus for named entity recognition, and a non-transitory computer-readable recording medium are provided. In the method, text elements are traversed according to a text span to obtain candidate entity words. Then, a class to which the candidate entity word belongs is recognized. The recognizing of the class includes generating a prompt template corresponding to the candidate entity word, and concatenating the text to be recognized and the prompt template to obtain a concatenated text; generating vector representations of the text elements in the concatenated text; generating the vector representation of the candidate entity word according to the vector representations of the text elements of each candidate entity word in the concatenated text, and the vector representation of the text element of the mask word; and classifying the vector representation of the candidate entity word to obtain the class of the candidate entity word.

Abstract: A method and an apparatus for training a machine reading comprehension model, and a non-transitory computer-readable recording medium are provided. A training process is repeatedly performed using a training sample set to obtain a machine reading comprehension model. The training process includes inputting a sample article and a sample question into the machine reading comprehension model, generating a first predicted answer, and calculating a first loss between the first predicted answer and a sample answer; replacing the sample question with a mask to obtain a mask question, inputting the sample article and the mask question into the machine reading comprehension model, generating a second predicted answer corresponding to the mask question, and calculating a second loss between the second predicted answer and the sample answer; and updating the machine reading comprehension model so as to minimize a total loss.

Abstract: Disclosed are a table recognition method and apparatus. The table recognition method includes steps of obtaining an image vision feature and a character content feature of a table image; fusing the image vision feature and the character content feature of the table image to acquire a first fusion feature, and carrying out recognition based on the first fusion feature to acquire a table structure; and performing, based on the table structure, character recognition on the table image to acquire table character contents.

Abstract: A method and system for remediating vulnerable code libraries, including open source libraries, in a software application. An application, that uses code libraries, and information regarding known library vulnerabilities are received, then it is determined if one or more libraries in the application are vulnerable based upon the information. For each of the one or more vulnerable libraries, a library version that minimizes risk is determined. The determined library version is incorporated into the application to form a test application, and an application test is performed on the test application. If an application test score on the test application is below a predetermined threshold, the determined library version is incorporated into a final application precursor. A final application can be determined from the final application precursor for each of the one or more vulnerable libraries.

Abstract: A method and an apparatus for machine reading comprehension, and a non-transitory computer-readable recording medium are provided. In the method, a paragraph-question pair is obtained, and subword vectors corresponding to subwords in the paragraph-question pair are generated. Then, for each subword, relative positions of the subword with respect to the other subwords are determined based on distances, and self-attention information of the subword in a first part and mutual attention information of the subword in a second part are calculated by using the relative positions and the subword vector. Then, a fusion vector of the subword is generated based on the self-attention information and the mutual attention information. Then, the fusion vectors of the subwords are input to a decoder of a machine reading comprehension model so as to obtain an answer predicted by the decoder.

Abstract: A method and an apparatus for fusing position information, and a non-transitory computer-readable recording medium are provided. In the method, words of an input sentence are segmented to obtain a first sequence of words in the input sentence, and absolute position information of the words in the first sequence is generated. Then, subwords of the words in the first sequence are segmented to obtain a second sequence including subwords, and position information of the subwords in the second sequence are generated, based on the absolute position information of the words in the first sequence, to which the respective subwords belong. Then, the position information of the subwords in the second sequence are fused into a self-attention model to perform model training or model prediction.

Abstract: A method and an apparatus for recognizing an intention, and a non-transitory computer-readable recording medium are provided.

Abstract: An intention identification method includes generating a heterogeneous text network based on a language material sample; using a graph embedding algorithm to perform learning with respect to the heterogeneous text network and obtain a vector representation of the language material sample and a word, and determining keywords of the language material sample based on a similarity in terms of a vector between the language material sample and the word in the language material sample; training an intention identification model until a predetermined training termination condition is satisfied, by using the keywords of the language material samples, and obtaining the trained intention identification model; and receiving a language material query, and using the trained intention identification model to identify an intention of the language material query.

Abstract: A method and system for remediating vulnerable code libraries, including open source libraries, in a software application are disclosed. An application that uses code libraries and information regarding known library vulnerabilities is received, then it can be determined if one or more libraries in the application is vulnerable based upon the information. For each of the one or more vulnerable libraries a library version that minimizes risk is determined. The determined library version is incorporated into the application to form a test application, and an application test is performed on the test application. If the application test is below a predetermined threshold, the determined library version is incorporated into a final application precursor. A final application can be determined from the final application precursor for each vulnerable library.

Abstract: A method and an apparatus for sequence labeling on an entity text, and a non-transitory computer-readable recording medium are provided. In the method, a start position of an entity text within a target text is determined. Then, a first matrix is generated based on the start position of the entity text. Elements in the first matrix indicates focusable weights of each word with respect to other words in the target text. Then, a named entity recognition model is generated using the first matrix. The named entity recognition model is obtained by training using first training data, the first training data includes word embeddings corresponding to respective texts in a training text set, and the texts are texts whose entity label has been labeled. Then, the target text is input to the named entity recognition model, and probability distribution of the entity label is output.

Abstract: The present invention relates to a coding gene of the SOSEKI protein SOK2 and an application thereof, wherein through molecular regulation of the SOSEKI protein SOK2, the flowering time of Panicum virgatum is delayed, biomass is increased, lignin content in the cell wall of Panicum virgatum is reduced and the fermentable sugar yield is boosted.

Abstract: A method and system for remediating vulnerable code libraries, including open source libraries, in a software application. An application that uses code libraries and information regarding known library vulnerabilities are received, then it identifies one or more libraries in the application that are vulnerable based upon the information. For each of the one or more vulnerable libraries, a library version that minimizes risk is determined. The determined library version is incorporated into the application to form a test application, and an application test is performed on the test application. If an application test score on the test application is below a predetermined threshold, the determined library version is incorporated into a final application precursor. A final application can be determined from the final application precursor for each of the one or more vulnerable libraries.

Abstract: Knowledge graph processing method and device are disclosed. The method includes steps of obtaining an entity set containing a first entity, a second entity, and relation information; acquiring text information and image information related to the first entity and the second entity; generating a first structural information vector of the first entity and a second structural information vector of the second entity, and creating a first text information vector of the first entity, a first image information vector of the first entity, a second text information vector of the second entity, and a second image information vector of the second entity; and building a joint loss function so as to attain a first target vector of the first entity, a second target vector of the second entity, and a target relation vector of the relation information between the first entity and the second entity.

Abstract: Disclosed is an apparatus for training a machine reading comprehension model. The apparatus is inclusive of a distance calculation part configured to calculate, based on a position of each word within a training text and a position of an answer label within the training text, a distance between the same word and the answer label; a label smoothing part configured to input the distance between the same word and the answer label into a smooth function to obtain a probability value corresponding to the same word, outputted from the smooth function; and a model training part configured to make the probability value corresponding to the same word serve as a smoothed label of the same word so as to train the machine reading comprehension model.

Abstract: A method and an apparatus for processing word vectors of a neural machine translation model, and a non-transitory computer-readable recording medium are provided. In the method, word vectors that are input to an encoder and a decoder of a neural machine translation model are updated using semantic information among head representations at the same time and semantic information among head representations at different times, and the model is trained or translation is performed using the updated word vectors, thereby improving the model performance of the neural machine translation model.

Abstract: A method and an apparatus for fusing position information, and a non-transitory computer-readable recording medium are provided. In the method, words of an input sentence are segmented to obtain a first sequence of words in the input sentence, and absolute position information of the words in the first sequence is generated. Then, subwords of the words in the first sequence are segmented to obtain a second sequence including subwords, and position information of the subwords in the second sequence are generated, based on the absolute position information of the words in the first sequence, to which the respective subwords belong. Then, the position information of the subwords in the second sequence are fused into a self-attention model to perform model training or model prediction.