Abstract: A method, system, and computer program product are disclosed. The method includes receiving a set of documents, selecting a topic, and determining that a first document from the set contains a topic label for the topic. The method also includes generating a topic sentiment score for the first document and adding the topic sentiment score to a set of training data. Additionally, the method includes determining that a second document from the set does not contain the topic label, generating an average sentiment score for the second document, and generating a bias factor for the average sentiment score.

Abstract: The present invention provides a C3N4 having a cubic crystal system and a method for producing same.

Abstract: An indoor unit includes a rear housing in which a heat exchanger and an electrical component box are disposed, a front housing disposed in front of the heat exchanger such that the front housing is removable, a front design panel disposed in front of the front housing such that the front design panel is removable, a securing and storage part into which a communication adapter is secured, and a temporary placement part for the communication adapter. The securing and storage part is disposed in the front housing such that the securing and storage part is exposed when the front design panel is removed. The temporary placement part is used to temporarily place the communication adapter on the temporary placement part.

Abstract: Described is a content mining system comprising a crawler configured to retrieve a plurality of files from a data storage system. The content mining system further comprises a plurality of converters configured to extract data from the plurality of files retrieved by the crawler from the data storage system, where each of the plurality of converters is configured to process a respective type of data. The content mining system further comprises a plurality of queues interposed between the crawler and the plurality of converters, where each queue is associated with a single converter.

Abstract: A method for producing a hydrocarbon, including: preparing a molten salt containing an oxide of a first metal; adding carbon dioxide to the molten salt; obtaining precipitates containing a first metal carbide by applying a voltage to the molten salt containing carbon dioxide; and obtaining a gas containing a hydrocarbon and a hydroxide of the first metal by hydrolyzing the first metal carbide.

Abstract: A method for producing a hydrocarbon including: preparing a molten salt containing a carbonate of a first metal; obtaining precipitates containing a first metal carbide by applying a voltage to the molten salt; and obtaining a gas containing the hydrocarbon and a hydroxide of the first metal by hydrolyzing the first metal carbide.

Abstract: An energy utilization system includes a circulation circuit. The circulation circuit includes a pump, a heating section, an electrolytic reduction apparatus, and a thermal energy recovery section. The pump receives a heating medium and outputs the heating medium. The heating section heats the heating medium by using renewable energy or energy obtained from waste heat. The electrolytic reduction apparatus heats an electrolytic solution with heat from the heating medium. The circulation circuit circulates the heating medium. A method for producing a carbon-containing material includes heating a heating medium circulating in a circulation circuit by using renewable energy or energy obtained from waste heat, and performing electrolytic reduction by heating an electrolytic solution with heat from the heating medium that has been heated.

Abstract: The present invention provides a method for manufacturing diamond, comprising electrolytically reducing carbon dioxide into diamond to obtain diamond in an electrolytic reduction apparatus having an anode, a cathode, and an electrolytic solution containing carbon dioxide, wherein the electrolytic solution comprises an ionic liquid.

Abstract: Methods and systems are provided for training a neural network with augmented data. A dataset comprising a plurality of classes is obtained for training a neural network. Prior to initiation of training, the dataset may be augmented by performing affine transformations of the data in the dataset, wherein the amount of augmentation is determined by a data augmentation variable. The neural network is trained with the augmented dataset. A training loss and a difference of class accuracy for each class is determined. The data augmentation variable is updated based on the total loss and class accuracy for each class. The dataset is augmented by performing affine transformations of the data in the dataset according to the updated data augmentation variable, and the neural network is trained with the augmented dataset.

Abstract: A pipe joint structure includes: a union; a flare nut that includes a female thread formed at one of axially opposite ends of the flare nut, and a first annular surface formed at the other of the axially opposite ends of the flare nut; a cylindrical sleeve that houses the flare nut such that the flare nut can be rotate and moved forward and backward; a rotary ring that has a second annular surface located to face the first annular surface, and is attached to the sleeve such that the rotary ring can be rotated for the union; and a pressing member that presses the flare nut toward the rotary ring. At the second annular surface, a claw is formed in such a manner as to protrude towards the flare nut.

Abstract: A method for manufacturing carbon monoxide or an organic compound, which includes electrolytically reducing carbon dioxide to obtain carbon monoxide or an organic compound in an electrolytic reduction apparatus having an anode, a cathode, and an electrolytic solution containing carbon dioxide. Carbon dioxide is selectively reduced into carbon monoxide or a specific organic compound by a potential to be applied to between the anode and the cathode.

Abstract: To provide a robot control system and a robot control method capable of placing a component grasped by a robot hand at an accurate location on another member. A robot control system is provided with: a robot hand configured to grasp a clip; a camera configured to capture an image of the clip grasped by the robot hand, a calculation unit configured to calculate a position of the clip or an inclination of a component based on an imaging result of the clip captured by the camera, and a robot control unit configured to control the robot hand to adjust, based on the position of the clip or the inclination of the component calculated by the calculation unit, a position or an inclination of the robot hand and move the clip to a stringer.

Abstract: A method, system, and computer program product are disclosed. The method includes receiving a set of documents, selecting a topic, and determining that a first document from the set contains a topic label for the topic. The method also includes generating a topic sentiment score for the first document and adding the topic sentiment score to a set of training data. Additionally, the method includes determining that a second document from the set does not contain the topic label, generating an average sentiment score for the second document, and generating a bias factor for the average sentiment score.

Abstract: A method, system, and computer program product for automated annotation scheduling for ground truth consistency are provided. The method receives data to be annotated by one or more annotators of a set of annotators. The data is passed to a student model to generate a student model output. The data is passed to a teacher model to generate a teacher model output. An annotation trend estimation model analyzes the student model output and the teacher model output to determine output characteristics of the student model. The method selects an annotator of the set of annotators as a designated annotator for at least a portion of the data based on the output characteristics of the student model.

Abstract: A feature of a subject file is identified. The feature is compared to a historical feature of a historical file. A similarity between the subject file and the historical file is calculated based on the comparing. A historical success metric for the historical file is identified. An intensive text extraction success value for the subject file is calculated based on the similarity and the historical success metric. Based on the intensive extraction success value, whether an intensive text extraction method should be performed on the subject file is determined.

Abstract: Described are techniques for topic modeling including a computer-implemented method of generating a plurality of topic labels corresponding to a plurality of documents clustered into a plurality of topics, where the plurality of topic labels include a sentiment-oriented topic label and a sentiment-neutral topic label. The method further comprises calculating term frequency-inverse document frequency (TF-IDF) values for respective topic labels and corresponding pluralities of documents. The method further comprises receiving a selected sentiment polarity from a user device. The method further comprises identifying a subset of the plurality of topic labels that satisfy the selected sentiment polarity. The method further comprises transmitting at least one topic label of the subset of the plurality of topic labels to the user device, where the at least one topic label has a higher TF-IDF value than other topic labels in the subset of the plurality of topic labels.

Abstract: A method for a multi-channel search includes receiving a specific post selection submitted in a first channel and query text associated with the specific post in the first channel, where the query text includes one or more words for performing a query evaluation. The method receives a query location which includes a plurality of channels for performing the query evaluation. Responsive to extracting one or more ranking factors from the specific post selection, the method performs the query evaluation at the query location to collect a plurality of potential matching posts based on the one or more ranking factors. The method reorders the plurality of potential matches according to a plurality of determined scores for the plurality of potential matches. The method displays two-dimensional search results based on a timeline and channel relevancy, where the plurality of channels is ordered according to channel relevancy compared to the first channel.

Abstract: Described is a content mining system comprising a crawler configured to retrieve a plurality of files from a data storage system. The content mining system further comprises a plurality of converters configured to extract data from the plurality of files retrieved by the crawler from the data storage system, where each of the plurality of converters is configured to process a respective type of data. The content mining system further comprises a plurality of queues interposed between the crawler and the plurality of converters, where each queue is associated with a single converter.

Abstract: Image classification using a generated mask image is performed by generating a mask image that extracts a target area from an input image, extracting an image feature map of the input image by inputting the input image in a first neural network including at least one image feature extracting layer, masking the image feature map by using the mask image, and classifying the input image by inputting the masked image feature map to a second neural network including at least one classification layer.

Abstract: An approach is provided in which a method, system, and program create a plurality of page clusters in feature space from a plurality of feature vectors corresponding to a plurality of unstructured pages. The method, system, and program product assign one of a plurality of machine learning models to each one of the plurality of page clusters based on a relationship in the feature space between the plurality of page clusters and a plurality of training clusters corresponding to the plurality of machine learning models. The method, system, and program product identify one of the plurality of page clusters that corresponds to a selected one of the plurality of unstructured pages, and transform the selected unstructured page into a structured page using a selected one of the plurality of machine learning models assigned to the identified page cluster.