Abstract: A system for correcting an alignment of positions of points affiliated with an object, in images of a location, that has one or more of a linear feature or a planar feature can include a processor and a memory. The memory can store an alignment module and a communications module. The alignment module can include instructions to: (1) identify, within data affiliated with the images, the positions of the points affiliated with the object that has the one or more of the linear feature or the planar feature and (2) correct, in a manner that recognizes that the object has the one or more of the linear feature or the planar feature, the alignment of the positions to produce a digital map of the location. The communications module can include instructions to transmit the digital map to a vehicle to be used to control a movement of the vehicle.

Abstract: The present disclosure relates to a system and method for vulnerability localization based on deep learning, which comprises, at a minimum, a processor configured to: analyze a code file under detection to obtain a first abstract syntax tree devoid of semantic information; build upon the first abstract syntax tree by incorporating data-flow edges and/or control-flow edges, thereby forming a second abstract syntax tree with semantic-flow enhancement; split the second abstract syntax tree to obtain a plurality of second abstract syntax sub-trees; and input these second abstract syntax sub-trees into a pre-established vulnerability detection and localization model.

Abstract: The present invention relates to a highly flexible, scalable multi-blockchain, hierarchical data-sharing and data-storing system, at least comprising a third-party blockchain system, a data-sharing blockchain system, and an application-layer client, wherein the data-sharing blockchain system performs data aggregation and hierarchical storage on shared data uploaded by the third-party blockchain system through accessing the data-sharing blockchain system, so as to allow the application-layer client to require the shared data from the data-sharing blockchain system. The disclosure herein creates a single reliable data-sharing blockchain apparatus based on blockchain systems, so as to facilitate aggregation of data coming from different blockchain systems, reduce node complexity and block data redundancy when data are acquired from multiple parties, and define different sharing rules for different data contents, thereby being adaptive to scenarios where data are shared among parties.

Abstract: The present invention relates to a container-oriented Linux kernel virtualizing system, at least comprising: a virtual kernel constructing module, being configured to provide a virtual kernel customization template for a user to edit and customize a virtual kernel of a container, and generate the virtual kernel taking a form of a loadable kernel module based on the edited virtual kernel customization template; and a virtual kernel instance module, being configured to reconstruct and isolate a Linux kernel, and operate a virtual kernel instance in a separate address space in response to a kernel request from a corresponding container. The container-oriented Linux kernel virtualizing system of the present invention is based on the use of a loadable module.

Abstract: A method may include receiving input for a multiwell structure and subsurface target locations, where the multiwell structure includes slots; generating, based at least in part on the input, a position for the multiwell structure, slot-well assignments for the slots, and well trajectories, where each of the well trajectories extends from an assigned one of the slots to one or more of the subsurface target locations; and outputting a set of specifications for the position for the multiwell structure, the well trajectories, and an order for drilling the well trajectories.

Abstract: A system for producing, from data affiliated with images of a location, a digital map can include a processor and a memory. The memory can store a productions module and a communications module. The production module can include instructions that cause the processor to produce, from the data affiliated with the images of the location, the digital map. The data, for an image, can exclude pixel color data, but can include information about: (1) a pose of a camera that produced the image and (2) one or more of a position of a point on: (a) a lane boundary of a lane of a road in the image, (b) a road boundary of the road, or (c) a landmark in the image. The communications module can include instructions that cause the processor to transmit the digital map to a vehicle to be used to control a movement of the vehicle.

Abstract: A method can include receiving input for a multiwell pad; selecting, based at least in part on a portion of the input, a template for the multiwell pad; generating, based at least in part on the template, well trajectories for the multiwell pad, where each of the well trajectories extends from a surface location of the multiwell pad to one or more reservoir target locations and where each of the well trajectories includes at least one curve generated using one or more dogleg severity values and one or more geometric control points that are not required to lie on one or more of the well trajectories; and outputting specifications for the generated trajectories of the multiwell pad.

Abstract: An approach is provided for generating feature data. The approach, for example, involves determining a set of break points associated with at least one road feature based on mask image data. The mask image data is associated with overhead image data comprising the at least one road feature. The approach further involves generating a set of cropped feature maps based on processing of a global feature map obtained from a global feature segmentation model and the set of break points. The global feature map is associated with the overhead image data. The approach further involves generating the feature data associated with the at least one road feature based on application of a local feature detection model on the generated set of cropped feature maps and the set of break points. The approach further involves storing the generated feature data in a geographic database.

Abstract: A method, system and processor for enhancing robustness of a source-code classification model based on invariant features is provided, wherein the method includes: combining non-robustness features to generate different style templates, converting codes in an input code training set into new codes of different styles to obtain a converted-code training set, merging the input-code and the converted-code training set into an expanded training set, and converting code texts in the expanded training set into code images; and converting the code images into required vectors, pairing samples of identical class randomly picked from the expanded training set and inputting the matched sample pairs into a feature extractor, iteratively updating the feature extractor and the matched sample pairs and extracting target characteristics, and training the extracted invariant features in a classifier to produce a trained model. The disclosed system includes a training set-expanding module and a model-training module.

Abstract: The present invention relates to a dynamic memory management apparatus and method for HLS, the apparatus has several searching and caching modules and several modifying and writing-back modules, the searching and caching modules are in connection with a DRAM storing module and a BRAM buffer, respectively, and the modifying and writing-back modules are in connection with the DRAM storing module and the BRAM buffer, respectively, the BRAM buffer is for caching information about nodes on a search path and registering information about modification made to the nodes. To remedy the defect that the traditional operating system is directly transplanted to the FPGA and has low execution efficiency, the present invention utilizes the advantage of the large capacity of the DRAM on the FPGA to realize efficient dynamic memory allocation and deallocation, and improve the usability and code reusability of HLS.

Abstract: A method for synchronizing neighboring tiles in an electronic map is described. The method includes grouping neighboring tiles of the electronic map into a plurality of tile groups. The method also includes selecting a first tile group and a second tile group that border one another on at least a first tile in the first tile group and a second tile in the second tile group. The method further includes independently optimizing the first tile group and the second tile group if a feature crosses between the first tile group and the second tile group. The method also includes shifting a border of the first tile group and a border of the second tile group to join the first tile and the second tile in the second tile group or the first tile group.

Abstract: A method and system for encryption and assured deletion of information is provided, the method at least includes: sorting fields of the information into at least two sensitivity levels by sensitivity; generating encryption keys and key shards thereof based on predetermined thresholds, and creating mapping between targets and the key shards, based on the encryption keys for the sensitivity levels, encrypting the information fields of the corresponding sensitivity levels and deleting the original information and encryption keys; and in response to reception of a recover request, recovering the encryption keys based on the key shards and performing decryption, so as to recover the original information. The present disclosure aims at the problem that information is difficult to be safely stored and assuredly deleted, and realizes multi-party security key deletion of encrypted personal information.

Abstract: A method and system for automatic deletion of information based on time synchronization and trusted counting is provided, the method including: defining different data structures including configurations in a normalized manner; setting triggering conditions for automatic information deletion, including conditions for automatic deletion based on time synchronization and/or based on trusted counting; maintaining synchrony of the configurations across different domains; and after satisfying the triggering conditions, making an information source domain and/or an information propagation domain perform the automatic information deletion.

Abstract: A method and system for overwriting-based deletion of information and verification of deletion is provided, wherein the method at least includes: receiving a deletion request and/or a random seed; performing fine-grained overwriting on the information by means of random overwriting; in response to an extraction request for a post-deletion state, making a master node in a source domain of the information broadcast the extraction request to at least one slave node; and sending the post-deletion state fed back by the slave node and a related state-verification parameter to a verifying terminal, so that the verifying terminal verifies an overwriting result based on a verifiable pseudo-random function. Thus, the present application can effectively prevent information recovery after being logically deleted, and efficaciously ensure verifiability as well as non-recoverability of deleted information, thereby assuring non-recoverable deletion and providing verifiability of deletion to information subjects.

Abstract: The present invention relates to an implementation method for graphic-blockchain-orientated hybrid consensus, at least comprising: calling at least one module to generate a new data block and broadcast it; calling at least one module to check and validate the received new block based on predetermined rules; calling at least one module to generate a void block; and calling at least one module to update a committee member list. The existing graphic blockchain can only achieve probabilistic consensus, yet the present invention achieves deterministic consensus on graphic blockchain for the first time, thereby reaching consensus faster. The present invention decouples generation and consensus of blocks for the first time, so that the two parts can be designed separately in a modularized manner. The present invention provides the first totally decentralized hybrid consensus algorithm in the graphic blockchain. This is unachievable to many existing graphic blockchain such as IOTA and Obyte.

Abstract: A method and system for recognizing TLS fingerprints based on finite-state machines is provided, wherein the system at least includes: a model inference module, for learning state machine models of target TLS implementations according to mapping information sent by a message mapping module; a fingerprint extracting module, for analyzing the state machine models and extracting multi-level fingerprints of the target TLS implementations; and a version recognizing module, for verifying the multi-level fingerprints for validity and/or recognizing version information of unknown TLS implementations. As compared to other network protocol identification systems, the present disclosure can identify and judge fine-grained information such as the specific implementation type and version of the specific TLS implementation. At the same time, the inventive method is highly automated, thereby ensuring good usability and scalability.

Abstract: The present invention relates to a network transmission optimization device for a graph-type blockchain, at least comprising a transaction processing module, a node managing module, and a route managing module, wherein the transaction processing module performs compression on a transaction, and transaction data obtained through the compression are transmitted among different clusters through a routing node selected by the route managing module from at least one cluster, wherein the at least one cluster is obtained through dividing plural nodes by the node managing module. The network transmission optimization method provides a transaction coding scheme to the existing graph-type blockchain systems, and improve use efficiency of network bandwidth by means of parallelized broadcast. The structured network topology of the network transmission optimization method is made to address delay among nodes, and is adaptive to dynamic joining and exit of nodes, thereby improving network transmission efficiency.

Abstract: A method and system for deleting multi-copy personal data efficiently and securely is provided, wherein the personal data and its subject identifier are signed and uploaded to data domains and stored as personal data copies; the personal data copies along with its source and destination data are circulated among the data domains; the data domain receiving a deletion instruction transmits the deletion instruction to every relevant data domains based on the identifier of the personal data subject and the destination data and then performs deletion; and after completing the deletion, the data domain deposit its domain identifier and feedback data it receives into a log, and feed the log back to its superior data domain. And the system of the present disclosure includes a plurality of data domains that can perform the above operations, thereby realizing association-based storage, association-based deletion and verification of association-based deletion of multi-copy personal data.

Abstract: A system and method for acceleration of deep-learning computing with edge-terminal collaboration is provided, wherein the system includes at least one terminal device and at least one edge server. The terminal device is configured to, when being present in a service coverage of the at least one edge server, determine an inter-layer partitioning and/or intra-layer partitioning policy for a deep learning model based on first configuration information related to the terminal device itself and second configuration information related to the edge server. And the edge server is configured to execute the inter-layer partitioning and/or intra-layer partitioning policy for the deep learning model in response to an inference request message, so as to implement collaborative inference. In the present disclosure, by using the load-based random forest method to predict the execution time for the DNN model, more accurate prediction results can be obtained.

Abstract: A method and system for trusted third-party audit of personal-information deletion is provided, wherein the method includes: acquiring log data of an arbitrary source-domain personal-information deleting body in a network and of its associated-domain personal-information deleting bodies; normalizing the log data according to predetermined parsing rules and thereby generating normalized log data; and performing consistency-of-notification analysis and operation-compliance analysis on the normalized log data by means of association analysis. The present application is based on an audit analysis of log files to identify whether the information deletion process conforms to the multi-dimensional or multi-level audit judgment conditions and to perform forensics on abnormal deletion of personal information in a timely manner, so as to ensure that personal-information deletion can satisfy requirements of internal control, industrial standards, policies and regulations.