17results about How to "Achieve fairness" patented technology

The invention provides a separate hospital guidance method and system for a large medical model, electronic equipment and a storage medium. The method comprises the following steps: receiving symptom description information of a natural language of a patient; performing natural language processing on the symptom description information by utilizing a large medical model, and determining symptom entity information and basic information of the patient; inputting the symptom entity information into a pre-constructed medical knowledge graph for matching, and determining candidate diseases and departments thereof corresponding to the patient; generating personalized triage suggestions by using the medical big model according to the candidate diseases and the departments thereof corresponding to the patient and in combination with the basic information of the patient; that is to say, according to the medical big model and the medical knowledge graph, symptom entity identification is performed on the symptom description of the patient, and then the corresponding candidate disease and the department thereof are determined, so that a manual separate hospital guide mode is avoided, the separate hospital guide efficiency and accuracy are improved, the waste of medical resources is reduced, and the fairness and sustainability of medical services are realized.

The invention provides a task scheduling method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of computers. The method comprises the following steps: adjusting the current priority of each task to be scheduled in a main queue according to the current resource load; under the condition that the priority adjustment frequency corresponding to the to-be-scheduled task reaches a preset frequency and the duration of the to-be-scheduled task entering the main queue exceeds a first preset duration, the to-be-scheduled task is stored in a retention queue as a retention task; for the detention tasks with overlong waiting time in the detention queue, the detention tasks are added into the main queue again after the priorities are adjusted, so that the tasks are scheduled to be dequeued and executed according to the dynamically adjusted priority sequence, the tasks with high priorities can be executed as soon as possible, and the situation that the tasks with low priorities cannot be processed for a long time can be avoided; the efficiency and the fairness of task processing are considered under the condition of high concurrency.

The invention relates to the technical field of smart communities, in particular to a future community construction method and system based on government big data, and the method comprises the following steps: collecting power use data, water resource consumption data and public transport utilization rate data in a community, synchronizing the data, and carrying out the standardization processing, and generating a community resource use data set. According to the method, through a time sequence analysis method, the resource demand of a community in a future week can be effectively predicted, a resource flow simulation model is established, prediction data is input in real time, model parameters are adjusted, influences of policies are continuously simulated and evaluated, optimal allocation of community resources is achieved, and the community resource allocation efficiency is improved by constructing a resource allocation diagram and determining an optimal path. The method achieves the high efficiency and fairness of resource distribution, continuously tracks the distribution effect and resident feedback, further guarantees the adaptability and continuity of resource distribution, not only optimizes the community resource management, but also improves the welfare of residents, and enhances the sustainable development of communities.

The invention discloses a method for isolating a server hook based on a sandbox, and according to the scheme, the security, the resource management efficiency and the isolation of Server hooks in a code management platform are remarkably improved, the defects in the aspects of resource consumption, authority control and the isolation in the prior art are effectively overcome, and the efficient and safe management requirements on the Server hooks in a multi-tenant environment are met. By the adoption of the scheme, resource consumption can be saved, and quick starting can be achieved, the Isole sandbox can execute codes immediately, the whole mirror image does not need to be loaded in advance, and resource use of each process can be specifically and finely controlled, so that resource management is more efficient. The Isole sandbox realizes quick response and efficient resource utilization through lightweight resource management and independent process space, and meanwhile, the process of each tenant is ensured not to interfere with each other.

The invention is suitable for the technical field of equipment management, and provides a laboratory equipment management method and system for chemical detection, and the method comprises the following steps: receiving an experimental equipment use demand inputted by a user, the experimental equipment use demand comprising an experimental item, user information, demand equipment and a demand time period; judging whether the demanded equipment needs to be queued for use, if so, calling the priority, the credit and the integrity of the corresponding user information, and calculating to obtain an equipment use cardinal number of the user information; determining the deadline of the demand time period, and determining user information allocated to the equipment at the deadline; and calling historical equipment use data of the distributed user information, analyzing the historical equipment use data, and sending equipment training information to the user account. According to the invention, based on a multi-dimensional equipment allocation strategy, the equipment use cardinal number is determined by calling the priority, the credit and the integrity of the user information, so that the fairness and the reasonability of equipment allocation are realized.

The invention relates to the technical field of micro-grids, and discloses a multi-virtual power plant carbon sharing optimization method. The method comprises the following steps: establishing a single virtual power plant optimization model, and considering carbon sharing between virtual power plants (VPP); establishing a multi-virtual power plant asymmetric Nash bargaining model based on the carbon sharing contribution degree: quantifying bargaining capability of each virtual power plant based on the carbon sharing contribution degree, and establishing a multi-virtual power plant (MVPP) asymmetric Nash bargaining model based on the carbon sharing contribution degree; and solving the MVPP asymmetric Nash bargaining model, and decomposing into two steps of solving: solving the cooperative alliance cost minimization model to obtain the carbon quota shared by the VPP, and solving the MVPP asymmetric Nash bargaining model to obtain the shared carbon price of the VPP. Compared with the prior art, the MVPP carbon sharing optimization method is established, and the carbon sharing strategy of the VPP is solved by adopting the asymmetric Nash bargaining game based on the carbon sharing contribution degree, so that the carbon cost of each VPP is reduced, the economic benefit of each VPP is improved, the benefit distributed by the VPP with the high carbon sharing contribution degree is larger, and the fairness of benefit distribution is ensured.

The embodiment of the present specification provides a kind of decision graph atlas graph data generation method and device.The method is executed by computer, comprising: reading first graph data from first storage area, wherein it includes the first node corresponding to the event attribute of first type business event.Several rules scripts are read from second storage area, rule script defines several decision rules, each decision rule includes identification field and expression field;Any variable included in the expression field of any decision rule is one of several event attributes or the identification value of the identification field of other decision rules.Through parsing rule script, determine second graph data, wherein it includes: parsing expression field obtains the dependent relationship between decision rule and event attribute and between each decision rule;Second graph data includes the second node corresponding to several rules, and the connection edge generated according to dependent relationship.Further, based on first graph data and second graph data, generate the graph data of decision graph atlas.

The application discloses a kind of settlement balance transparent data labeling crowd sourcing method, system and medium, method includes: establishing data labeling crowd sourcing system, determine interactive entity;Task requester mixes and is labeled data and unlabeled data to obtain to be labeled data, while setting the public condition of labeled data, public task information tuple after encryption through smart contract on blockchain, deposit task reward setting task deposit, public task download link;Worker confirms to accept task and deposits task deposit, generates proof after downloading and completing data labeling task, and public task result and proof;Task requester worker proof, evaluate task result, create and broadcast a piece of hash time lock transaction, pay task reward to worker.The application carries out fair trade under the supervision of no trusted third party by blockchain and hash time lock, realizes the objectivity and fairness of task reward distribution, guarantees the balance and transparency of task reward settlement.

The application relates to a loan quota credit method, device and equipment, which comprises the following steps: obtaining credit application information of a loan party, and obtaining financing credit evaluation information and prior business verification data of the loan party from a pre-constructed credit evaluation alliance chain; generating current business verification data according to the obtained current evaluation business data of the loan party, an investment party and a guarantee party, and verifying the prior business verification data according to the current business verification data; after verification, verifying the credit application information based on the financing credit evaluation information; if the credit application information meets preset credit conditions, obtaining credit quotas given by each financial institution in a pre-constructed credit alliance chain; determining a loan quota according to the credit quotas given by each financial institution, and if the loan quota meets preset consensus conditions, storing the loan quota in the credit alliance chain. The fairness, independence and verifiability of the credit quotas given by the financial institutions are ensured, and the individual evaluation risk of the financial institutions is effectively reduced.

The embodiment of the invention provides a method based on combination of block chain data acquisition and model training, and the method comprises the steps: receiving a training starting instruction, sending the starting instruction to a terminal node, and sending an expected result to a feedback unit; the terminal node forwards the instruction to a related peer node according to a preset global parameter; the peer-to-peer node generates training data by using pre-stored resources and weights and transmits the training data to a data processing unit; the data processing unit screens and integrates training data and then inputs the training data into the model training unit; the model training unit calculates an actual result and feeds back the actual result to the feedback unit, and the feedback unit calculates a difference value according to an expected result and the actual result, encapsulates the difference value, a weight and a peer node identifier into a resource packet and sends the resource packet to a terminal node; the terminal node forwards the resource packet to the smart contract of the block chain; the peer-to-peer node runs contract verification, and if the contract verification passes, the contract verification is sent to the sorting node; and the sorting node generates a block to each peer node, and after the peer nodes verify, the blocks are added to the local block chain if the blocks are valid, and the weights are updated if the blocks are invalid, so that subsequent training is optimized.

The application discloses a spoken language evaluation system and method based on multiple dimensions, and relates to the technical field of data processing.The system comprises the following steps: obtaining audio text, a phoneme list and a phoneme time boundary list corresponding to speech data according to a pre-trained text phoneme recognition model; calculating a fluency score according to the phoneme list and the phoneme time boundary list; obtaining a semantic score of the audio text through a pre-trained semantic model; obtaining a syntax score of the audio text through a pre-trained syntax model; matching the audio text and an answer text according to a text matching method based on an edit distance to obtain a text matching score; obtaining a pronunciation score of the audio data finally through phoneme confidence of the phoneme list; dynamically adjusting the weight of each dimension score according to the length of the audio text, and calculating a final spoken language evaluation score; and the application comprehensively evaluates the spoken language ability through multi-dimensional evaluation and dynamic weight adjustment according to the scene, and realizes the comprehensiveness, fairness, accuracy and high efficiency of the spoken language evaluation.

The invention discloses a data processing method, device and equipment based on a block chain and a readable storage medium, and the method comprises the steps: calling a grade calculation contract after a to-be-chained transaction data set is received, and calculating the to-be-chained transaction data set through calculation logic indicated by the grade calculation contract; performing grade calculation processing on each piece of to-be-linked transaction data in the to-be-linked transaction data set to obtain a transaction grade of each piece of to-be-linked transaction data; the grade calculation contract is created and deployed through a grade calculation factory contract; when a transaction packaging moment arrives, determining packaged transaction data at the transaction packaging moment in the to-be-linked transaction data set according to a grade sequence between transaction grades of the to-be-linked transaction data; and carrying out packaging and uplink processing on the packaged transaction data. By adopting the method and the device, in the transaction data processing business of the block chain, the emergency processing requirement of the transaction data can be met in time while the transaction processing fairness is realized.

The invention relates to the field of new energy power market transaction, in particular to a new energy station bundling sales transaction method, device and equipment and a storage medium, and designs a medium and long term bundling sales transaction framework of a new energy station and a conventional unit, introduces a centralized transaction platform, and establishes a power transaction alliance of the new energy station and the conventional unit; a new energy station transaction model based on a cooperative game is constructed, and the overall benefit of a power transaction alliance is maximized; according to the contract signing electric quantity and the actual power generation output condition of the new energy station, adjusting the output of the conventional unit to realize electric quantity compensation, and ensuring accurate performance of the contract electric quantity; and calculating and optimizing power transaction income distribution of the power transaction alliance, ensuring fairness and rationality of income distribution, and realizing maximization of the overall income of the power transaction alliance. Through the multi-source complementary bundling sales strategy, the contract performance capability and the power consumption level of the new energy station are remarkably improved.

The application belongs to the technical field of military research data management, and discloses a data right protection and contribution calculation system of a block chain, which comprises: an application layer, which is used for providing trusted military research data based on a block chain core layer to realize data evidence, whole-process operation tracing, multi-dimensional contribution calculation and auditing functions for a collaborative research and development scene; an enhanced component layer, which is used for providing management services, data scheduling, user access and security enhancement support for the application layer; a block chain core layer, which is used for providing block chain basic capabilities supporting multi-chain collaboration, high-throughput consensus, automatic execution of intelligent contracts, national secret level security protection and trusted node management; and an infrastructure layer, which provides computing, storage and network resources for the application layer, the enhanced component layer and the block chain core layer. The application realizes data right protection and contribution calculation by adopting block chain encryption algorithms, consensus mechanisms, distributed ledgers and intelligent contracts and other technologies.

The invention discloses a rapid matching method for an order and a multi-tenant driver, and particularly relates to the technical field of order matching, a main order is divided into a plurality of sub-orders, for each sub-order, a corresponding tenant is determined according to the sub-order, geographic position data of a driver and a passenger are acquired to determine a transport capacity pool of the tenant, and sub-order matching is performed according to the driver in the transport capacity pool, so that the order matching efficiency is improved. When the driver determines that the order is made, matching success information is sent to the passenger; if the driver does not make an order, the matching is ignored, and the next matching is carried out in the driver pool, so that the driver can be found as soon as possible, only one driver is ensured to make an order finally, only the company of the tenant selected by the passenger is matched, and the fairness of the drivers of the plurality of tenants is realized; one driver may register in a plurality of transport companies but is only registered for one time, and in addition, when the order is finally formed, the driver is judged according to the state of the order to judge secondary verification and determine the effectiveness of the order, so that the matching efficiency is ensured, and the riding experience of a customer is not influenced.

The application provides a data processing method and device of educational software, electronic equipment and a storage medium, and relates to the technical field of data processing. The method comprises the following steps: obtaining original data packets generated when a target educational software runs, wherein the original data packets at least comprise context parameters, and the context parameters comprise called algorithm identifiers, input parameters and output results; preprocessing the original data packets to generate algorithm data records; extracting structured algorithm archives of at least one algorithm to be verified from the algorithm data records, wherein the structured algorithm archives comprise static attribute information, dynamic running characteristics and model attribute information; performing risk assessment on the structured algorithm archives of each algorithm, determining risk scores of each algorithm, and performing differentiated hierarchical storage on the structured algorithm archives of the algorithms based on the risk scores of the algorithms, so that the whole-process traceability of algorithm behaviors in the educational software is realized, and the algorithm transparency is enhanced.

The invention discloses a non-ground network-oriented SCMA codebook design method and a communication method, and belongs to the field of Internet of Things communication, the codebook design method comprises the following steps: sorting users in an ascending order according to the distance between the users and a nadir point of an air base station, allocating df power factors to each orthogonal resource, and calculating # imgabs0 # 1 < = i < = df; generating a set P composed of K-dimensional column vectors including N 1 and K-N 0, dividing the set P into df orthogonal groups, and alternately arranging the remaining column vectors and the df orthogonal groups to form a set P '; after qi is sorted in an ascending order according to rho i, the ith element 1 in each row of P'is replaced by qi, and column vectors in the P 'are sorted in an ascending order according to the column vector power sum and then serve as a signature matrix FK * J; and constructing an SCMA codebook of each user based on the FK * J, calculating the worst bit error rate so as to enable the worst bit error rate to be minimum as an optimization target, solving corresponding parameters, and obtaining the SCMA codebook of each user. According to the invention, the problem of unfairness of users caused by channel difference in a non-ground network can be solved, and offline optimization of the SCMA codebook is realized.