Abstract: Systems and methods providing access control and data privacy/security with decentralized ledger technology are disclosed. To ensure data privacy the decryption or access to data by a non-data owner requires joint orchestration of decentralized system nodes to provide partial decryption components with n-of-x required to fulfill request. Data can be encrypted, and access control policy can be decided including required number of key fragments to fulfill decryption. Access control policies can be stored in the decentralized ledger based system. Key information can be stored in the system in a decentralized manner with partial key fragments encrypted and split among system nodes. An access request can be sent to the system to fetch a data file, without disclosing the requester's identity in the system. The decentralized ledger based system can verify a legitimate request to access the data and denies access to malicious or faulty participants.

Abstract: The present disclosure provides an opening-closing type microwave catalytic reaction apparatus, including a microwave system, a microwave cavity, a protective cover, a cooling system, and a vertical furnace tube, where two ends of the furnace tube are respectively stretched out of the microwave cavity, the microwave system includes a plurality of microwave transmitting units, and the microwave transmitting unit includes a microwave transmitter; the furnace tube is provided with a gas inlet on a top and a gas outlet on a bottom; a compression hinge and a cavity cover capable of being opened or closed are arranged on the microwave cavity, a convex edge plate is disposed at an edge of the cavity cover, the compression hinge can compress the cavity cover such that the convex edge plate is tightly attached to a concave edge plate on the microwave cavity, and the protective cover can cover the entire cavity cover.

Abstract: An approach is provided in which the approach constructs a 3-dimensional (3D) matrix based on a plurality of historical transactions performed by a user. The 3D matrix includes a set of features, a set of rows, and a set of channels. The approach trains a convolutional neural network using the 3D matrix, and then uses the trained convolutional neural network to predict a risk level of a new transaction initiated by the user. The approach transmits an alert message based on the predicted risk level.

Abstract: A repairing method for micro-LED chip defective pixels is disclosed. By providing a main recess and a backup recess in each of sub-pixel areas of a substrate, wherein each of the main recesses is loaded with a main micro-LED chip, when all of the main micro-LED chips are detected for defective pixels, the backup recess in each of the sub-pixel areas where the defective pixel is detected is loaded with a backup micro-LED chip using a fluid mass transfer method, which improves the repair efficiency.

Abstract: Embodiments of the present invention relate to use of a GP73 inhibitor in preparation of a drug for treating diabetes. In the embodiments of the present invention, the inventor finds that GP73 plays a key role in blood glucose regulation, and in particular, finds that soluble GP73 can specifically bind to glucagon to form a complex, enhances the blood glucose-rising function and gluconeogenesis function of glucagon and prolongs the half-life of glucagon; and finds soluble GP73 can activate the glucose production in liver and/or kidney and a gluconeogenesis signaling pathway in a glucagon-independent manner. Based on the blood glucose regulation effect of the GP73 described above, the inventor also proves through animal experiments: the GP73 inhibitor can reduce the blood glucose level and glycated hemoglobin level of diabetic mice and have a protective effect on islet ? cells, and thereby having the effect of treating diabetes.

Abstract: An approach is provided in which the approach constructs a 3-dimensional (3D) matrix based on a plurality of historical transactions performed by a user. The 3D matrix includes a set of features, a set of rows, and a set of channels. The approach trains a convolutional neural network using the 3D matrix, and then uses the trained convolutional neural network to predict a risk level of a new transaction initiated by the user. The approach transmits an alert message based on the predicted risk level.

Abstract: Methods and apparatus for user transfer in a Cloud-radio access network (C-RAN) are disclosed. In an embodiment, a method includes in response to a request for migrating a user from a first user equipment (UE) virtualized network function component (VNFC) to a second UE VNFC, receiving at the second UE VNFC, dynamic context information of packet data convergence protocol (PDCP) layer and radio link control (RLC) layer for data transmission of the user from the first UE VNFC. The method further includes continuing process of the data transmission of the user at the second UE VNFC based on the dynamic context information.

Abstract: Provided are a bissulfonate compound, a preparation method therefor, an electrolytic solution and an energy storage device. The bissulfonate compound has a structure of (I) and is applied as an additive to an energy storage device, so that a stable SEI film can be formed on a surface of an anode of the energy storage device, and the decomposition of a solvent in the electrolytic solution can be suppressed. As the stable SEI film can be formed on the surface of the anode, lithium ions can be smoothly embedded and disembedded at a low temperature, thereby improving the low-temperature performance of the energy storage device.

Abstract: A computer transforms a machine learning model. The computer receives a first Machine Learning model trained to assign a first set of classes to data samples based, on data features. The computer receives a first set of data samples having features and being assigned to a class in accordance with the features. The computer calculates for each data sample, a vector representing features of the sample and determines, for each of the first set of classes, a class largest intra-sample distance. The computer generates data samples having feature combinations outside the first set of classes. The computer transforms the first Machine Learning model into a second Machine Learning model by training the first Machine Learning model with training data including second set data samples labeled with associated second data class assignments.

Abstract: A current signal segmentation algorithm is provided. The segmentation algorithm divides a current signal waveform into mutually different segments according to a physical feature thereof, extracts shape distribution, statistical and harmonic features of the segments, and calculates a similarity between a segment pair. The segmentation algorithm includes the following steps: segmenting a current signal to separate a standby current and an overshoot current, only leaving a working current; extracting a shape distribution feature of a working current segment; extracting a statistical feature of the working current segment; extracting a harmonic feature of the working current segment; calculating a similarity between a segment pair; and deriving a maximum clique set in a similarity graph through a maximum clique search algorithm as a class from automatic segmentation.

Abstract: Introduced here are computer programs and computer-implemented techniques for generating and then managing a federated database that can be used to ascertain the risk in interacting with vendors. At a high level, the federated database allows knowledge regarding the reputation of vendors to be shared amongst different enterprises with which those vendors may interact. A threat detection platform may utilize the federated database when determining how to handle incoming emails from vendors.

Abstract: The present disclosure relates to a data processing method, platform, a computer-readable storage medium and an electronic device. The method includes: extracting original data into a message engine based on a preset standardized data interface, the original data including terminal data generated by a terminal device and/or system data generated by an application system; reading the original data from the message engine, and storing the original data in a distributed file system to form a fact table; storing the fact table in a columnar database, and obtaining target column data required for generating a target chart from the columnar database; and generating the target chart according to the target column data.

Abstract: The present invention discloses a knowledge inference engine system and a method of implementation, relating to the field of wired communication networking technology. The system includes a data generation module, a stream partitioning model, an offline scheduling module, an online scheduling module, a scheduling solution base and a historical information base module, the data generation module used to generate a dataset and divide it into a plurality of partitions, the stream partitioning model used to partition the dataset, the offline scheduling module used to generate a scheduling solution for static network requirements, the online scheduling module used to rapidly generate a scheduling solution for a new TT stream, the scheduling solution base used to store a result of the partitioning, an iterative scheduling order for the partitions and the offline scheduling solution, the historical information base used to update and store relevant data information and performance indicators.

Abstract: A system comprises one or more processors. The system further comprises memory having computer readable instructions stored thereon that, when executed by the one or more processors, cause the system to: obtain a reference tree of nodes and linkages for a reference three dimensional volumetric representation of a branched anatomical formation in a reference state; based on the reference tree, generate a reference three dimensional geometric model; based on measurements from a sensor system, detect deformation of the branched anatomical formation; based on the detected deformation, obtain a deformed tree of nodes and linkages; and generate a three dimensional deformation field that represents the detected deformation of the branched anatomical formation.

Abstract: An approach is provided in which the approach builds a combination model that includes a normal status model and an abnormal status model. The normal status model is built from a set of time-sequenced normal status records and the abnormal status model is built from a set of time-sequenced abnormal status records. The approach computes a set of time-sequenced coefficient combination values of the normal status model and the abnormal status model based on applying a set of fitting coefficient characteristics to the normal status model and the abnormal status model. The approach performs goal seek analysis on a system using the combination model and the set of time-sequenced coefficient combination values.

Abstract: Systems and methods providing access control and data privacy/security with decentralized ledger technology are disclosed. To ensure data privacy the decryption or access to data by a non-data owner requires joint orchestration of decentralized system nodes to provide partial decryption components with n-of-x required to fulfill request. Data can be encrypted, and access control policy can be decided including required number of key fragments to fulfill decryption. Access control policies can be stored in the decentralized ledger based system. Key information can be stored in the system in a decentralized manner with partial key fragments encrypted and split among system nodes. An access request can be sent to the system to fetch a data file, without disclosing the requester's identity in the system. The decentralized ledger based system can verify a legitimate request to access the data and denies access to malicious or faulty participants.

Abstract: Method and apparatus for load balancing in a Cloud-radio access network (C-RAN) are disclosed. A method includes receiving control plane (CP) data associated with a user from a core network or a remote access point; and dispatching the CP data to a first user equipment (UE) virtualized network function component (VNFC) based on a first route.

Abstract: Techniques for detecting instances of external fraud by monitoring digital activities that are performed with accounts associated with an enterprise are disclosed. In one example, a threat detection platform determines the likelihood that an incoming email is indicative of external fraud based on the context and content of the incoming email. To understand the risk posed by an incoming email, the threat detection platform may seek to determine not only whether the sender normally communicates with the recipient, but also whether the topic is one normally discussed by the sender and recipient. In this way, the threat detection platform can establish whether the incoming email deviates from past emails exchanged between the sender and recipient.

Abstract: The subject invention pertains to methods to produce amorphous materials at nanometer scale, by solidifying or hardening the materials inside nanometer-sized pores of porous media (i.e., porous templates). The porous templates can be made by packing nanometer-sized particles or other means. The subject invention further pertains to methods to produce the porous templates used to produce amorphous material at nanometer scale.

Abstract: Techniques for detecting instances of external fraud by monitoring digital activities that are performed with accounts associated with an enterprise are disclosed. In one example, a threat detection platform determines the likelihood that an incoming email is indicative of external fraud based on the context and content of the incoming email. To understand the risk posed by an incoming email, the threat detection platform may seek to determine not only whether the sender normally communicates with the recipient, but also whether the topic is one normally discussed by the sender and recipient. In this way, the threat detection platform can establish whether the incoming email deviates from past emails exchanged between the sender and recipient.