Abstract: A method and system for diagnosis of error coding faults from multiple instruments are provided. The method includes acquiring sampling data series of a combination of instruments in a petrochemical process, determining a type of the sampling data series, and performing error diagnosis according to the type. The present disclosure can solve the error coding problem in a multi-instrument cooperation mode and provide safe and reliable data guarantee for safe and efficient petrochemical production.

Abstract: Provided is a light system, a light element, and a mounting pad of a light. The light system includes a light element and a mounting pad. The light element includes a light-emitting unit to emit light; an attachment unit to attach the light element to any position on a mounting surface on which the light element is mounted; a wireless electric-power receiving unit to receive electric power for driving the light element by wireless electric-power transmission; and a light-emitting unit power supply circuit, connected to the wireless electric-power receiving unit to transmit the electric power received by the wireless electric-power receiving unit to the light-emitting unit. The mounting pad includes a mounting area having the mounting surface on which the light element is mounted and a wireless electric-power transmitting unit to transmit the electric power to the wireless electric-power receiving unit on the mounting surface by wireless electric-power transmission.

Abstract: A method and system for diagnosis of error coding faults from multiple instruments are provided. The method includes acquiring sampling data series of a combination of instruments in a petrochemical process, determining a type of the sampling data series, and performing error diagnosis according to the type. The present disclosure can solve the error coding problem in a multi-instrument cooperation mode and provide safe and reliable data guarantee for safe and efficient petrochemical production.

Abstract: Methods, apparatus, and processor-readable storage media for authenticating usage data for processing by machine learning models are provided herein. An example method includes receiving, by a machine learning application installed in a user space of an operating system of a user device, a message from a software component, wherein the software component is: configured to collect usage data associated with the user device; signed with using private key corresponding to a digital certificate by an application installed on the user device; and deployed in a kernel space of the operating system, and wherein the message comprises usage data signed using the private key; authenticating, by the machine learning application, the usage data based on a public key corresponding to the digital certificate; and processing, by the machine learning application in response to a result of the authenticating, at least a portion of the authenticated usage data.

Abstract: Disclosed are a new AXL-targeting monoclonal antibody and antibody-drug conjugate. Also disclosed is a method for preparing said antibody and antibody-drug conjugate. The AXL antibody of the present invention can bind with purified human AXL protein and multiple AXL on tumor cell surface with high effectiveness and high specificity. Said humanized antibody also has high affinity and low immunogenicity. Said AXL antibody-drug conjugate has markable performance against tumors having high AXL expression.

Abstract: Embodiments of the present disclosure relate to a method, a device, and a computer program product for executing computer programs. The method includes implementing multiple executions of a deep neural network that includes a hooking portion outside a trusted execution environment (TEE), wherein an operator in the hooking portion, when executed outside the TEE, invokes a corresponding execution operator in the TEE. During the period, the method includes determining, on the basis of the invocation of the corresponding execution operator in the TEE by the operator in the hooking portion, a computation graph corresponding to the hooking portion. The method further includes executing, on the basis of the computation graph, the execution operator corresponding to the hooking portion in the TEE during the execution of the deep neural network after the multiple executions.

Abstract: Techniques for integrating a trusted execution platform with a function-based service framework are disclosed. For example, a method comprises reading configuration information identifying at least one data providing party and at least one function providing party, and generating, based at least in part on the configuration information, an enclave comprising a circuit configured to execute a function. The method further comprises receiving in the enclave and via at least a first secure communication channel, the function from the at least one function providing party, and receiving in the enclave and via at least a second secure communication channel, data from the at least one data providing party. The function and the data are sent to the circuit, wherein the circuit executes the function to compute at least one output based at least in part on the data.

Abstract: The present disclosure relates to a passive outlier-tolerant and active outlier-tolerant learning method with abnormal samples and a system thereof. The method includes the following steps: (1) judging the distribution of abnormal samples in a train set, and calling a corresponding outlier-tolerant algorithm based on the distribution to carry out feature learning on the sample feature quantity in the train set to obtain an outlier-tolerant learning result; (2) training an initial learning model by using the outlier-tolerant learning result to obtain an intermediate learning model; (3) processing the test set by a preset outlier-correction algorithm to obtain an outlier-corrected test set; (4) testing the intermediate learning model using the outlier-corrected test set to obtain a final learning model. The scheme of the present disclosure can improve the passive outlier tolerance and active outlier tolerance of a machine learning process to abnormal samples.

Abstract: The present application relates to a klotski game including a plurality of game pieces, a game board and a prompter. The plurality of game pieces includes a decisive game piece. The game board is configured to accommodate the plurality of game pieces and the game board is provided with an exit. The prompter is configured to indicate that a game of the klotski game is over when the decisive game piece is moved to a position corresponding to the exit on the game board.

Abstract: This disclosure provides a data processing method, including: receiving, by a first computing device, a first packet sent by a second computing device, where the first computing device is configured to assist the second computing device in performing service processing, the first computing device is a computing device in a heterogeneous resource pool, the first computing device communicates with the second computing device through a network, the heterogeneous resource pool includes at least one first computing device, and the first packet includes an instruction used to request the first computing device to process to-be-processed data; processing, by the first computing device, the to-be-processed data based on the instruction; and sending, by the first computing device, a second packet to the second computing device, where the second packet includes a processing result of the to-be-processed data.

Abstract: A rollover prevention system prevents a construction machine from rolling over. The rollover prevention system comprises a first angle detection unit (12) disposed adjacent to a turning joint (11) to detect a swing angle of the upper frame (5), a second angle detection unit (13) disposed on the upper frame to detect an angular movement of the upper frame, safety valves (40) disposed on flow passages (25, 32) communicating with hydraulic cylinders for a work attachment (10) and a swing motor (26) to control flows of working oil supplied to the hydraulic cylinders by opening and closing the flow passages in response to external signals, and an electronic controller (14) electrically connected to the first angle detection unit, the second angle detection unit, and the safety valves. The electronic controller comprises a barycenter calculating section (14a), a safety range determining section (14b), and a signal outputting section (14c). A rollover prevention method for a construction machine is also provided.

Abstract: A rollover prevention system prevents a construction machine from rolling over. The rollover prevention system comprises a first angle detection unit (12) disposed adjacent to a turning joint (11) to detect a swing angle of the upper frame (5), a second angle detection unit (13) disposed on the upper frame to detect an angular movement of the upper frame, safety valves (40) disposed on flow passages (25, 32) communicating with hydraulic cylinders for a work attachment (10) and a swing motor (26) to control flows of working oil supplied to the hydraulic cylinders by opening and closing the flow passages in response to external signals, and an electronic controller (14) electrically connected to the first angle detection unit, the second angle detection unit, and the safety valves. The electronic controller comprises a barycenter calculating section (14a), a safety range determining section (14b), and a signal outputting section (14c). A rollover prevention method for a construction machine is also provided.