Abstract: The invention concerns a method and a system of generating high-resolution digital try-on images of human models wearing arbitrary combinations of garments and shoes with faithfully represented spatial interrelationships and transformations using a system of neural networks. The method allows for a realistic representation and combination of neutral garment images from different sources on a human body model and has a potential for commercial use in online shopping experiences. The input of the system is 2D human body, garment, and shoe images. The method involves adjusting the human body to the position of the shoes, taking steps to create a controllable intermediate representation that predicts the garments' position and deformation on the body, and creating a semantic layout of the body wearing the garments. The method allows for adjusting the position and the dimension of every garment, including the creation of tucked-in tops and open or closed outerwear.

Abstract: A search engine server includes a communication interface through which to receive a multi-modal query from a browser of a client device, the multi-modal query including at least a first image of an item. A processing device, coupled to the communication interface, is to: execute a neural network (NN) regressor model on the first image to identify a plurality of second items that are similar to and compatible with the item depicted in the first image, wherein a set of images correspond to the plurality of second items; generate structured text that explains, within one of a phrase or a sentence, why the set of images are relevant to the item; and return, to the browser of the client device via the communication interface, a set of search results comprising the set of images and the structured text.

Abstract: An example for determining consensus by Parallel Proof of Voting (PPoV) in a consortium blockchain includes causing each bookkeeping node to generate and publish a block to a consortium blockchain network. After collecting all the block generated in the previous step, the consortium node votes send a total voting message (the hash value of each block, as well as the agreed opinion and signature) to the leader node. The leader node counts the voting results and random selects the next leader node, which publishes the block group header to the consortium blockchain network. When a blockchain node receives the block generated by the bookkeeping nodes and the block group header generated by the leader node, it will store them in the database as a block group.

Abstract: A method comprising: A. forming a consortium blockchain network using domain network nodes and selecting committee members from top-level domain nodes; B. the committee member who received most votes packs the genesis block and generates a random number; C. the housekeeper having the same number as the random number packs the current block and generates a random number for selecting a next housekeeper to pack the next block, each block is approved by more than half of the committee members; D. during the duty cycle, each housekeeper takes turns packing blocks and generating random numbers and the process is repeated. If a block is not approved, the housekeeper with the next number is requested to repack the block; and E. the last random number generated by a housekeeper before the duty cycle ends is used to select the housekeeper to pack the first block of the next duty cycle.

Abstract: An example topology construction method for satisfying partition tolerance, comprising: combining the consortium blockchain consensus mechanism with the network topology structure to make the consortium blockchain consensus satisfy the partition tolerance in probability; abstracting the partition tolerance of a system into a class of convergent Markov process and computing a steady-state probability of the system; estimating the probability and the average minimum repair time of failing to meet consistency or availability in the event of a partition failure with a given number of failure channels, and a partition tolerance probability and an average minimum repair time of the system are obtained; and analyzing the resource overhead and the partition tolerance under different network topologies according to the obtained partition tolerance probability and the average minimum repair time, and constructing the network topology structure with suitable scale and high partition tolerance for the consortium blockcha

Abstract: The invention relates to a blockchain-based domain name resolution system, characterized in that the domain name resolution system adopts a layered structure comprising a top-level domain name chain network, a second-level domain name chain network, a future network node and an existing DNS system network; the top-level domain name chain network links the second-level domain name chain network, the future network node and the existing DNS system network respectively, and the top-level domain name chain network is used for each professional organization to deploy the server nodes having a reliable performance respectively to form a union blockchain network, wherein each node server records the information of all the current top-level domain names, the second-level domain name chain nodes, the future network nodes and the root nodes of the existing DNS system; the second-level domain name chain network is used for the registration and management of domain names, and recording of all the second-level domain name

Abstract: The present disclosure relates generally to internet technology and more specifically to managing Top-level domain (TLD) name based on blockchain. An example method of managing Top-level domain name comprises the following steps: A. Using TLD nodes to form alliance network in the blockchain; B. Layering the system architecture in the alliance network to separate operations and data; and C. Reaching consensus among all nodes in the alliance network through consensus mechanism. A more effective and efficient consensus mechanism will increase the safety and reliability of the system and improve the efficiency of the system. Layering the system structure will ensure the efficiency and portability of the system.

Abstract: A method comprising: In some implementations, a method for indexing a multi-layer blockchain system, comprising: A. using, a top layer blockchain, to index a lower layer blockchain by recording a seed node in a transaction log of a block; B. requesting a distributed monitoring cluster to periodically check availabilities of IP addresses and ports that listed in the seed node stored in the top layer blockchain; C. maintaining, for each node in the lower layer blockchain, a separate instance of a global routing table. Each global routing table store entire topological structure of the multi-layer blockchain system, and final consistency of the global routing tables is maintained through a GOSSIP-based data communication protocol. Any node located on the lower layer blockchain described in Step C is configured to access data and services through any one of accessible nodes identified by IP addresses and ports recorded in the global routing table.

Abstract: The present disclosure relates generally to internet technology and more specifically to managing Top-level domain (TLD) name based on blockchain. An example method of managing Top-level domain name comprises the following steps: A. Using TLD nodes to form alliance network in the blockchain; B. Layering the system architecture in the alliance network to separate operations and data; and C. Reaching consensus among all nodes in the alliance network through consensus mechanism. A more effective and efficient consensus mechanism will increase the safety and reliability of the system and improve the efficiency of the system. Layering the system structure will ensure the efficiency and portability of the system.

Abstract: An example method includes: identifying message labels for electronic messages; identifying, based on a classification model specific to a first user, a first and a second message labels for a first and a second electronic messages; detecting a user action by the first user on the second electronic message to indicate the first message label is descriptive of the second electronic message; responsive to the user action, re-training the classification model based on tokens produced from the second electronic message to produce an updated classification model specific to the first user; after re-training is completed, detecting an incoming electronic message having a timestamp later in time than timestamps for the first and the second electronic messages; determining that the incoming electronic message shares a predefined number of tokens with the second electronic message; and assigning, based on the updated classification model, the first message label to the incoming electronic message.