105 results about "Chain model" patented technology

Nonlinear adaptive resource management systems and methods are provided. According to one embodiment, a controller identifies and prevents resource starvation in resource-limited systems. To function correctly, system processes require resources that can be exhausted when under high load conditions. If the load conditions continue a complete system failure may occur. Controllers functioning in accordance with embodiments of the present invention avoid these failures by distribution shaping that completely avoids undesirable states. According to one embodiment, a Markov Birth/Death Chain model of the resource usage is built based on the structure of the system, with the number of states determined by the amount of resources, and the transition probabilities by the instantaneous rates of observed consumption and release. A control stage is used to guide a controller that denies some resource requests in real systems in a principled manner, thereby reducing the demand rate and the resulting distribution of resource states.

Described herein are systems, methods, and apparatus for processing network packet data in a distributed computing platform, such as a content delivery network, to provide services to mobile network operators and/or their mobile subscribers. According to the teachings hereof, distributed computing resources can be organized into a service platform to provide certain value-add services—such as deep packet inspection, transcoding, lawful intercept, or otherwise—using a service function chaining model. The platform resources are preferably located external to the mobile network, on the public Internet. The platform preferably operates on and processes traffic entering or exiting the mobile network. In some embodiments, the service platform is able to establish an encrypted channel between itself and the mobile client through the mobile network, e.g., using content provider key and certificate information available to the platform (but which may not be available to the mobile network operator).

The invention discloses a block chain model with the privacy protection function. The block chain model is formed by a minimum trustrank administrator, a private part, and a public part. The minimum trustrank administrator is used for assisting in transaction; the private part is used for defining input information of all sides participating in transaction and sending and receiving of the information and defining relevant calculations during the transaction process and verification of relevant data during the transaction process; and the public part is used for ensuring fairness of the transaction. On the basis of currency encryption, a block chain is constructed by using a distributed anonymous mechanism, zero-knowledge verification, overtime penalties, and packaging methods. Realizationof currency generation and usage, and conversion into basic currency having the privacy protection function relays on zk-SNARK and related data in a ciphertext mode are verified, so that the user is able to realize data verification while the user information is not leaked.

The invention discloses a method and a system for detecting a malicious application of an Android system. The method comprises the following steps: acquiring a privilege characteristic by a reverse engineering de-compilation application program; matching by a behavior chain model for dynamic behavior collection and definition, thereby acquiring a behavior characteristic; combining plentiful privilege characteristics with behavior characteristics, thereby generating a characteristic data sample set; adopting a machine learning algorithm for utilizing the characteristic data sample set to generate a classifier; and inputting the characteristics of an unknown application program to the classifier, thereby acquiring a conclusion indicating if the unknown application program belongs to the malicious application. The invention provides the behavior chain model on the basis of the reverse engineering and the dynamic behavior collection, and then the unknown application program is detected through the machine learning algorithm, so that the efficient recognition for the malicious application is realized, the accuracy is high and the detection method and system provided by the invention are high in efficiency, need not change the system source code and are high in availability.

The invention discloses an information pushing method, system and equipment. The information pushing method mainly comprises the following steps: inquiring information chains with higher correlation degree for commodity information corresponding to information ordering request of a seller user in a first website through an information chain model prestored in a database, determining the category of all inquired information contained in the information chains in a second website, and pushing the commodity information belonging to the category in the second website to the seller user in the first website, thus, the information pushing accuracy is improved, and the aim for actively recommending information between the two websites is achieved.

A method, system, and computer program product for modeling a supply chain. The method includes modeling a storage element in the supply chain as a place node and modeling an activity in the supply chain as a transition node. The transition node includes at least one of an immediate transition node, a timed transition node, and a substitution transition node. An item moved through the supply chain is modeled as a token, where the token includes multiple attributes associated with the item. The place node is linked to the transition node with a directed arc, with the directed arc indicating the direction of token movement between the place node and the transition node. The linked place and transition nodes are organized as a supply chain model that represents the flow of items through the supply chain. In addition, performance metrics for the supply chain model are defined.

The invention requests to protect a block chain consensus method based on switching of network topology modes. The block chain consensus method is based on a master-slave multi-chain model of the block chains, different consensus mechanisms are adopted for the construction of a main chain and a slave chain, and a basic layer, a topological layer, a consensus layer and an application layer of the block chain are processed in a layered manner, so that the block chain consensus method is more suitable for a transaction-oriented block chain system, and a high-throughput, low-delay, high-efficiencyand energy-saving consensus algorithm is set. In addition, an asynchronous parallel algorithm is achieved in an environment based on the switching of the network topology structure, a single-chip computer which integrates multiple functional blocks, such as a CPU, a memory, a high-speed interconnection communication link, etc., is provided with four pairs of two-way communication links used for linking between processors so as to form a multi-processor system of various topology structures.

The invention provides a monitoring system. The monitoring system comprises a call chain model storage unit for storing one or more business call chain models and a log storage unit for storing interface call logs of interfaces in the business call chain models, and each business call chain model records all called interfaces according to an upstream and downstream relationship of the called interfaces in each business system related in a corresponding business process. The invention also provides a business system. The business system comprises a call chain model fragment storage unit for storing one or more business call chain model fragments related to the business system, a log generation unit for generating interface calling logs when the interfaces of the business system are called, and a log uploading unit for uploading the interface calling logs of the interfaces included in the business call chain model fragments to the monitoring system, and each business call chain model fragment records the portion of the called interface of the business system in the corresponding business call chain model.

The invention discloses a method for quick modeling of a Delta robot based on MAPLESIM. The method is characterized by comprising the following steps of 1, according to the multibody mechanical graph theory principle, abstracting a mechanism topology configuration of the actual Delta robot into a linear graph, and expressing in a character and graph type; 2, sequentially selecting the required elements from a built MAPLESIM element base, and setting attributes and parameters; 3, according to the linear graph, connecting the elements and components, and building a single-branch chain physical model of the Delta robot; 4, copying the built single-branch chain model in step 3 into two other branch chains, and connecting the three branch chains in parallel to build a complete basic model of the Delta robot; 5, solving the built single-branch chain model in step 4, and simulating the motion control on the complete model according to the solved explicit inverse solution. The method has the advantage that by operating the MAPLESIM to analyze, the built model is tested according to the three-dimensional cartoons and tracks, so as to obtain the satisfactory property.

The invention discloses a determination method of marine ecological environment damage causal-relationships, and belongs to the technical fields of marine ecological environment protection and pollution damage identification and evaluation. The method includes 6 marine ecological environment damage causal-relationship chain model, 4 types of causal-relationship determination criteria and indicators with logical progressive relationships, a multi-type auxiliary evaluation model system architecture scheme matching the determination criteria, a marine ecological environment damage environment baseline and damage degree determination criterion and indicator system construction scheme of distinguishing regions, classes, items and levels and a quantitative determination method of damage degreesof the vulnerable factors and contribution of damage source items. A set of clear, simple, fast, systematic and effective causal-relationship determination technology support is provided for scientific determination of damage and consequences caused on marine ecological environments and human body health by sea-related-engineering, production and life pollution emission and suddenly occurring pollution events, identification, evaluation, blaming and compensation of damage and active and effective taking of countermeasures of prevention, preparation and disposal of pollution damage and environment restoration.

The invention provides a method for constructing a three-dimensional digital block chain confirmation system. The method comprises the following steps of: uploading a work; Copyright Certification; Block Depository; The third edition confirms the right; Copyright trading; Net-wide investigation. The invention adopts a self-developed block chain copyright registration network, Match trusted timestamp, chain stamp double authentication, Generating copyright DNA for each original model can really realize the traceability of three-dimensional model, and the copyright guardian based on the block chain model certification system and the whole network copyright monitoring tool can monitor the network infringement of original works, reconstruct the industry order, make the sovereignty belong to three-dimensional designers, and ensure the legitimate rights and interests of three-dimensional designers.

The invention belongs to the technical field of network security, in particular to an APT attack behavior analysis and detection method and device based on a cascaded attack chain model, and the method comprises the steps: collecting multi-source heterogeneous network data, representing an attack process through the recursive structure of a plurality of sub-attack chains, forming an attack chain overall structure in a sub-attack chain cascading mode, and constructing the cascaded attack chain model; and based on the cascade attack chain model, analyzing and detecting APT attack behaviors in the network, and reconstructing an APT attack scene. According to the method, the limitation of the prior art is overcome, the APT attack behavior is effectively recognized and analyzed, the defect thatan existing analysis method excessively depends on manual analysis is overcome, the accuracy of attack behavior detection is improved, and the method can be conveniently applied to actual analysis.

The invention provides a Bayesian network-based dynamic risk analysis method for a high-speed rail contact network, which comprises the following steps of: establishing a risk propagation chain modelof high-speed rail contact network insulator flashover, carrying out characteristic quantity-dynamic probability dynamic mathematical modeling on the risk chain model, and putting the risk chain modelin a Bayesian network for calculation to obtain a risk occurrence probability; Using the passenger flow intensity index to determine the severity of risk dynamics in both time and space dimensions, taking basic time granularity and stations as basic units for obtaining real-time monitoring data, taking a risk propagation path and a propagation process as a passenger flow density index calculationprinciple, and calculating the severity degree of risk consequences caused by delay of different times of a train; And combining the dynamic probability with the severity, and obtaining the dynamic risk level of the risk chain according to the risk assessment matrix.

The invention discloses a hybrid block chain model construction method based on deep learning, a participation node in the method is used for constructing an operation model according to public chaindata and/or private chain data, a task node is used for constructing a hybrid block chain model according to the operation model, and the method comprises the following steps: the task node sends a task requirement to the participation node; the participation node constructs a neural network training model and records the neural network training model as an operation model by using a deep learningmethod according to task requirements, public chain data stored in a block chain and/or private chain data stored in the participation node; and the task node obtains the operation model, and utilizes a deep learning algorithm to fuse the operation model and record the operation model as a hybrid block chain model. Through the technical scheme provided by the invention, the utilization rate of private chain data in the block chain is favorably improved, and the accuracy in the block chain data processing process is improved.

The invention discloses a space-time chain model based bus route evaluation method. The method includes the steps: firstly, creating a passenger travel station point set; secondly, acquiring a movement track Sij(t) of a bus between two adjacent bus stations Zi and Zj; thirdly, forming a complete passenger travel space-time path L(t); fourthly, modeling the passenger travel time path L(t) by utilizing the time-space geography theory; fifthly, acquiring a mathematical model S' for evaluation of the complete passenger travel space-time path. The bus route and bus travel behaviors are evaluated and expressed visually, and the method has an important value to scientific evaluation and reasonable setting of the bus route.

A system and method are described for intelligently sourcing demand forecasts within a supply chain management (“SCM”) system based on a constrained supply chain model, in light of material and resource constraints. For example, a computer implemented method according to one embodiment of the invention comprises: calculating a demand forecast identifying anticipated demand for a product over a specified time period; identifying current sales orders for the product with delivery dates scheduled during the specified time period; generating an open forecast for the product based on the current sales orders and the anticipated demand; and sourcing different percentages of the open forecast from different plants, the percentages selected based on supply chain material and/or resource constraints. In addition, after the demand forecast is sourced, one embodiment of the invention employs additional techniques for intelligently sourcing new sales orders entering the SCM system.

Computer method, apparatus and system chains model-to-model transformations. In a series of model transformations, there are respective bridges before and after each model transformation. For each pair of consecutive model transformations in the series, the respective bridge (i) receives a model output from a first model transformation of the pair, the received model being in the respective output model format of the first model transformation of the pair, (ii) prepares the received model as input to a second model transformation of the pair, including preparing the received model to be in the respective input model format of the second model transformation of the pair, and (iii) inputs the prepared model to the second model transformation of the pair. The series of model transformations and respective bridges provide chaining of the model-to-model transformations. Each model transformation in the series is able to be separately configured.

The invention discloses a master-slave multi-chain cross-chain method and system based on a voting and credit mechanism. The ownership of an accounting right is determined by introducing a voting mechanism, so that the computing power competition between nodes is avoided, and all the nodes in the system can obtain the accounting right fairly; the credit value is given to the node, so that the influence of rights and interests on the system is reduced, and meanwhile, the behavior of the node can be better restrained by performing quantitative evaluation on the behavior of the node, so that the node can worry about malicious behaviors; on the basis, a master-slave multi-chain layered cross-chain model with a slave chain based on POVT consensus and a main chain based on PBFT consensus is constructed, experimental analysis is performed on the performance of the master-slave multi-chain layered cross-chain model, and results show that the efficiency of the system is improved; and meanwhile, the system has certain defense capability on attack means such as double-blossom attack, selfish mining and right and interest crushing.