Abstract: A method for privacy protection of smart contract includes: obtaining a variable identifier, a privacy-trigger sub-script, and ciphertexts of a plurality of privacy-trigger sub-scripts of other participating users input by the user intending to perform a transaction in response to a transaction instruction; determining a target state variable corresponding to the variable identifier from the smart contract, and obtaining a precomputed ciphertext corresponding to the target state variable; computing, using the preset digest algorithm, based on the plurality of privacy-trigger sub-scripts and the ciphertexts of the plurality of privacy-trigger sub-scripts to obtain the target ciphertext; executing a decision-making script bytecode in the privacy-trigger sub-script to obtain an execution result if the target ciphertext is identical to the precomputed ciphertext; and performing a predetermined operation on the target state variable when the execution result indicates execution success.

Abstract: This application provides an address detection method and a related apparatus. The method includes: receiving a first internet protocol (internet protocol, IP) address from a first device, where the first IP address is a to-be-detected IP address of the first device; determining a first information table, where the first information table includes an IP address of one or more devices, and the one or more devices and a first apparatus are at a media access control layer of a same network; determining a second information table based on the first information table; and detecting whether a second IP address that is the same as the first IP address exists in the second information table, where a first media access control address corresponding to the first IP address is different from a second media access control address corresponding to the second IP address.

Abstract: Techniques for implementing a performance-adaptive sampling strategy towards fast and accurate graph neural networks are provided. In one technique, a graph that comprises multiple nodes and edges connecting the nodes is stored. An embedding for each node is initialized, as well as a sampling policy for sampling neighbors of nodes. One or more machine learning techniques are used to train a graph neural network and learn embeddings for the nodes. Using the one or more machine learning techniques comprises, for each node: (1) selecting, based on the sampling policy, a set of neighbors of the node; (2) based on the graph neural network and embeddings for the node and the set of neighbors, computing a performance loss; and (3) based on a gradient of the performance loss, modifying the sampling policy.

Abstract: The present disclosure relates to the technical field of big data and artificial intelligence. Disclosed are a data processing and visualization method, medium and device. The method includes: selecting a data platform to acquire source data of a target enterprise, sorting the source data and loading the source data into a data system to serve as a source database table, executing a primary data operation to process the source data into target data, executing a secondary data operation to process the target data into value-added data, executing a tertiary data operation to process relevant data into graphic data, and executing data visualization, so as to draw and render a visual graph by using the graphic data.

Abstract: A children's toy with touch interactivity. The children's toy generally includes a user input panel and one or more touch sensors. The user input panel may be formed from a natural organic material such as wood. The toy can be shaped and ornamented to resemble a toy tablet with buttons or icons incorporating images of one or more animals and configured to play animal sounds or information about the animals in response to user input applied to the user input panel and sensed by the touch sensors.

Abstract: Apparatuses, systems, and methods for SoR list management and PLMN selection based on an SoR list. A UE may receive an SoR container which may include a list of OPLMNs. The UE may store a prior list of OPLMNs stored on a USIM of the UE on a memory of the UE. The UE replace the prior list of OPLMNs stored on the USIM with the list of OPLMNs included in the SoR container. The UE may consider the prior list of OPLMNs as a lower priority list as compared to the list of OPLMNs stored on the USIM. Additionally, in response to determining to move from a current PLMN, the UE may scan for a new PLMN based on the list of OPLMNs stored on the USIM.

Abstract: A method, an apparatus and a device for parallel execution of a smart contract, and a medium are provided. The method for parallel execution of the smart contract includes the following steps: determining, according to a chain table for a cross-contract calling of each transaction in target execution transactions and the contract type of a smart contract in the target execution transactions, a calling dependency relationship between the transactions, and obtaining, according to the calling dependency relationship, transaction calling chains that cannot affect each other during an execution process.

Abstract: This application provides an address detection method and a related apparatus. The method includes: receiving a first internet protocol (internet protocol, IP) address from a first device, where the first IP address is a to-be-detected IP address of the first device; determining a first information table, where the first information table includes an IP address of one or more devices, and the one or more devices and a first apparatus are at a media access control layer of a same network; determining a second information table based on the first information table; and detecting whether a second IP address that is the same as the first IP address exists in the second information table, where a first media access control address corresponding to the first IP address is different from a second media access control address corresponding to the second IP address.

Abstract: A children's toy with capacitive touch interactivity. The children's toy generally includes a user input overlay panel and one or more capacitive touch sensors. The overlay panel may be formed from a capacitive touch conductive natural organic material such as wood. The toy can be shaped and ornamented to resemble a musical instrument and configured to play music in response to user input applied to the user input overlay panel and sensed by the capacitive touch sensors.

Abstract: A user equipment (UE) is configured to prioritize a plurality of Public Land Mobile Networks (PLMNs) from an aggregate roaming priority public land mobile network (RPPLMN) list containing the plurality of PLMNs into a plurality of prioritized PLMNs and connect to a selected PLMN from the plurality of prioritized PLMNs based on a priority of the selected PLMN. The UE is further configured to determine if an application processor (AP) assisted location service is available, wherein the AP-assisted service is configured to identify a plurality of deployed PLMNs and a plurality of frequencies used by the plurality of deployed PLMNs at a current geographical location of the UE and when the AP) assisted location service is available, determining if a registered PLMN (RPLMN) is valid in a current mobile country code (MCC).

Abstract: Apparatuses, systems, and methods for SoR list management and PLMN selection based on an SoR list. A UE may receive an SoR container which may include a list of OPLMNs. The UE may store a prior list of OPLMNs stored on a USIM of the UE on a memory of the UE. The UE replace the prior list of OPLMNs stored on the USIM with the list of OPLMNs included in the SoR container. The UE may consider the prior list of OPLMNs as a lower priority list as compared to the list of OPLMNs stored on the USIM. Additionally, in response to determining to move from a current PLMN, the UE may scan for a new PLMN based on the list of OPLMNs stored on the USIM.

Abstract: A children's toy with capacitive touch interactivity. The children's toy generally includes a user input overlay panel and one or more capacitive touch sensors. The overlay panel may be formed from a capacitive touch conductive natural organic material such as wood. The toy can be shaped and ornamented to resemble a musical instrument and configured to play music in response to user input applied to the user input overlay panel and sensed by the capacitive touch sensors.

Abstract: In an example embodiment, a screening question-based online screening mechanism is provided to assess job applicants automatically. More specifically, job-specific questions are automatically generated and asked to applicants to assess the applicants using the answers they provide. Answers to these questions are more recent than facts contained in a user profile and thus are more reliable measures of an appropriateness of an applicant's skills for a particular job.

Abstract: Apparatuses, systems, and methods for SoR list management and PLMN selection based on an SoR list. A UE may receive an SoR container which may include a list of OPLMNs. The UE may store a prior list of OPLMNs stored on a USIM of the UE on a memory of the UE. The UE replace the prior list of OPLMNs stored on the USIM with the list of OPLMNs included in the SoR container. The UE may consider the prior list of OPLMNs as a lower priority list as compared to the list of OPLMNs stored on the USIM. Additionally, in response to determining to move from a current PLMN, the UE may scan for a new PLMN based on the list of OPLMNs stored on the USIM.

Abstract: Techniques for scoring data items using a machine-learned model are provided. In one technique, multiple skills are identifying based on a job posting. Multiple attribute values of the job posting are identified. For each identified skill, multiple probabilities are identified, each probability corresponding to a different attribute value of the identified attribute values. The probabilities are input into a machine-learned model to generate multiple scores. Multiple skills of a candidate user are identified. An affinity score between the job posting and the candidate user is generated based the scores and the skills of the candidate user.

Abstract: Apparatuses, computer readable medium, and methods are disclosed for verifying skills of members of an online connection network. The apparatus, computer readable medium, and methods may include a method including responding to a first member of the online connection network indicating a skill possessed by the first member by selecting a skill verification user interface (UI) to present to a second member of the online connection network where the first member and the second member are connected via the online connection network. The method may further include presenting the skill verification UI to the second member, where the skill verification UI presents an indication of the first member, an indication of the skill, and a query regarding a competence level of the skill possessed by the first member. The method may further include receiving a response to the query and determining a skill validation value of the skill for the first member based on the response and a machine learning model.

Abstract: In an example embodiment, a framework to infer a user's value for a particular attribute based upon a multi-task machine learning process with uncertainty weighting that incorporates signals from multiple contexts is provided. In an example embodiment, the framework aims to measure a level of a user attribute under a certain context. Rather than attempting to devise a universal, one-size-fits-all value for the attribute, the framework acknowledges that the user's value for that attribute can vary depending on context and factors in the context under which the user's attribute levels are measured. Multiple contexts are defined depending on different situations where users and entities such as companies and organizations need to evaluate user attribute levels. Signals for attribute levels are then collected for each context. Machine learning models are utilized to estimate attribute values for different contexts. Multi-task deep learning is used to level attributes from different contexts.

Abstract: An Internet Protocol version 6 (IPv6) based wireless network communication method and a communication device are provided. The method includes: determining a transmission path of a plaintext IPv6 packet based on a TEID field of the plaintext IPv6 packet, where the TEID field indicates a bearer to which the plaintext IPv6 packet belongs; and transmitting the plaintext IPv6 packet on the determined transmission path of the plaintext IPv6 packet.