Abstract: A machine learning hardening system and method for hardening machine learning models against adversarial attacks are disclosed, addressing the prevalent challenges of data imbalance and sophisticated adversarial attacks. The method involves preprocessing data for logistic regression, and augmenting the dataset with synthetic fraudulent transactions generated by a Negative-Calibrated Generative Adversarial Network (NCGAN) to ensure balance. Adversarial behavior is modeled to simulate fraudster responses to detection models, employing a Stackelberg game framework. A logistic regression model is trained using a sum of top-K loss function to focus on the transactions with the greatest loss, enhancing the detection of fraudulent activity.

Abstract: Evaluation data sets may be programmatically generated for code generation models. An evaluation data set is obtained that includes items that correspond to different evaluation tests for a code generation system. The individual items of the evaluation data set maybe converted, including the conversion of a function signature for the items, the test statements for the items and using a code generation system to generate the body of the function.

Abstract: Solutions for rapid ransomware detection and recovery include: receiving a first set of in-memory changed data blocks; identifying, within the first set of in-memory changed data blocks, a second set of in-memory changed data blocks addressed for storage within a file index for a virtual machine (VM) disk; determining, relative to a change history of the file index, an anomalous condition; based on at least determining the anomalous condition, identifying a third set of blocks within the file index that are changed between two versions of the VM disk; determining that changes in the third set of blocks indicate ransomware; and based on at least determining that changes in the third set of blocks indicate ransomware, generating an alert. Machine learning (ML) models may perform anomaly/ransomware detection. Remediation activities may include disk restoration storing the VM memory.

Abstract: A method and a system for identifying a glacial lake outburst debris flow (GLODF) are provided. The method is obtained based on considering induced influences of slopes of channels and particle sizes of source particles on the GLODF. The method not only compensates for deficiencies in identifying the GLODF, but also realizes determination of the GLODF, which provides data basis for disaster prevention and control layout such as monitoring and early warning on a glacial lake and assists preventing and managing disasters caused by the GLODF. Meanwhile, multiple parameters used in the method are easy and convenient to obtain, and the parameters can be directly used on site, which saves engineering cost, improves working efficiency, and has high practical and promotional value in environmental protection and disaster prevention and mitigation.

Abstract: A display panel, including a drive circuit, where the drive circuit is at least used to drive the display panel to display obtained display data. The drive circuit includes a shift register, a data buffer and a first control circuit; the shift register is used to output display data of each sub-pixel according to a preset timing sequence; the data buffer at least includes a first cache module composed of N repeat units; a repeat unit includes at least one cache unit, the cache unit is connected to the shift register, and two cache units at a same position in the k-th repeat unit and the (k+1)-th repeat unit are multiplexed with a same clock signal terminal; the cache unit is used to be turned on in response to an output signal from the clock signal terminal connected to the cache unit, to cache the received display data.

Abstract: The present disclosure provides a driving method for a liquid crystal display panel and a non-transitory computer storage medium. The driving method includes: for the plurality of sub-pixels, adopting a first gray-level table for displaying a picture in other frame pictures other than a first frame picture in each of the plurality of predetermined periods, the first gray-level table including a plurality of first gray-level values; and adopting a second gray-level table for displaying a picture in the first frame picture in each of the plurality of predetermined periods, the second gray-level table including a plurality of second gray-level values.

Abstract: Pre-fix matching may constrain the generation of next token predictions. Input text to perform a next token prediction may be received. Multiple tokens may be determined from the input text, including a partial token. From possible tokens, one or more matching possible tokens with the partial token may be identified. Next token predictions may then be filtered using the identified possible tokens in order to ensure that the partial token is matched.

Abstract: Interactive assistances for executing natural language queries to data sets may be performed. A natural language query may be received. Candidate entity linkages may be determined between an entity recognized in the natural language query and columns in data sets. The candidate linkages may be ranked according to confidence scores which may be evaluated to detect ambiguity for an entity linkage. Candidate entity linkages may be provided to a user via an interface to select an entity linkage to use as part of completing the natural language query.

Abstract: A method for determining a consistency coefficient of a power-law cement grout includes: determining a water-cement ratio of the power-law cement grout; according to engineering practice requirements, determining a time required to determine the consistency coefficient of the power-law cement grout; and obtaining the consistency coefficient of the power-law cement grout. The method is accurate and reliable, requires less calculation, etc.; and has very high practical value and popularization value in environmental protection and ecological restoration.

Abstract: A method for determining a three-dimensional tortuosity of a loose and broken rock-soil mass, includes the following steps: a particle grading curve of the loose and broken rock-soil mass is obtained by utilizing a particle size analysis, and followed by calculating an equivalent particle size and an average particle size; a porosity of the loose and broken rock-soil mass is obtained by utilizing a moisture content test, a density test, and a specific gravity test; the three-dimensional tortuosity of the loose and broken rock-soil mass is obtained by utilizing the equivalent particle size, the average particle size and the porosity of the loose and broken rock-soil mass. The method has the advantages of simple logic, accuracy and reliability, simple and fast parameter determination, and has high practical value and promotion value in the field of environmental protection and ecological restoration technology.

Abstract: Evaluation data sets may be programmatically generated for code generation models. An evaluation data set is obtained that includes items that correspond to different evaluation tests for a code generation system. The individual items of the evaluation data set maybe converted, including the conversion of a function signature for the items, the test statements for the items and using a code generation system to generate the body of the function.

Abstract: Code completion suggestions may be proactively obtained and validated. An event that triggers obtaining a code completion suggestion for inclusion in a code file being edited using an integrated development environment may be detected. The code completion suggestion may be obtained. The characters of the code completion suggestion may be compared with characters added to the code file after the detection of the event that triggered obtaining the code completion suggestion to determine whether the code completion suggestion is valid. A valid code completion suggestion may then be displayed.

Abstract: Random token segmentation may be implemented for next token prediction. Text data may be received for training a machine learning model to predict a next token given input text tokens. Multiple tokens may be determined from the text data. Different ones of the multiple token may be randomly segmented in to sub-tokens. The machine learning model may then be trained using the multiple tokens including the respective sub-tokens as a training data set.

Abstract: Pre-fix matching may constrain the generation of next token predictions. Input text to perform a next token prediction may be received. Multiple tokens may be determined from the input text, including a partial token. From possible tokens, one or more matching possible tokens with the partial token may be identified. Next token predictions may then be filtered using the identified possible tokens in order to ensure that the partial token is matched.

Abstract: Interactive assistances for executing natural language queries to data sets may be performed. A natural language query may be received. Candidate entity linkages may be determined between an entity recognized in the natural language query and columns in data sets. The candidate linkages may be ranked according to confidence scores which may be evaluated to detect ambiguity for an entity linkage. Candidate entity linkages may be provided to a user via an interface to select an entity linkage to use as part of completing the natural language query.

Abstract: Multiple stage filtering may be implemented for natural language query processing pipelines. Natural language queries may be received at a natural language query processing system and processed through a query language processing pipeline. The query language processing pipeline may filter candidate linkages for a natural language query before performing further filtering of the candidate linkages in the natural language query processing pipeline as part of generating an intermediate representation used to execute the natural language query.

Abstract: Query restatements may be provided for explaining natural language query results. A natural language query is received at a natural language query processing system. An intermediate representation of the natural language query is generated for executing the natural language query. The intermediate representation is translated into a natural language restatement of the natural language query. The natural language restatement is provided with a result of the natural language query via an interface of the natural language query processing system.

Abstract: Multiple stage filtering may be implemented for natural language query processing pipelines. Natural language queries may be received at a natural language query processing system and processed through a query language processing pipeline. The query language processing pipeline may filter candidate linkages for a natural language query before performing further filtering of the candidate linkages in the natural language query processing pipeline as part of generating an intermediate representation used to execute the natural language query.

Abstract: Interactive assistances for executing natural language queries to data sets may be performed. A natural language query may be received. Candidate entity linkages may be determined between an entity recognized in the natural language query and columns in data sets. The candidate linkages may be ranked according to confidence scores which may be evaluated to detect ambiguity for an entity linkage. Candidate entity linkages may be provided to a user via an interface to select an entity linkage to use as part of completing the natural language query.

Abstract: Techniques for displaying a search are described. An exemplary method includes receiving a search query, performing the search query on a plurality of documents, the documents including text passages, to generate a search query result, determining an aspect of the search query result that has a confidence value that exceeds a first confidence threshold with respect to its relevance to the search query; and, displaying the search result including an emphasis on the aspect of the result exceeds the first confidence threshold.