292 results about "Interaction network" patented technology

A method and system for interactively shopping for groceries, especially on an Internet web site, where the user may create a shopping list, shop for items from the list at a selected Grocery Storey store, arrange for pick up or delivery of the selected items and payment, or to download the list to a PDA or for printing with the store's layout for use in the store. Users are required to register and provide specific demographic information (useful to Manufacturers and stores) to be eligible to receive the benefits of use of the web site, such as menu creation, coupon downloads, menu planning, and recipe input. Shopping lists may be created from a single input screen using standard language text; and products may be automatically suggested to the user based on best regular price or retailer's specials. Recipes may be altered to meet numbers of servings or dietary requirements and changes stored for future use.

A system and method for creating a social interaction network by generating a search request at a client device; transmitting the search request to a server; generating a user interface template specially configured for display on the client device; gathering static assets for the user interface template; gathering dynamic assets responsive to the request; merging the static assets and the dynamic assets into the user interface template; and transmitting the user interface to the client device. The gathering step is involves gathers the dynamic assets based upon user defined, system defined and partner defined matches.

Provided are methods, network devices, and computer-program products for detecting infiltration of an endpoint, and rerouting network traffic to and from the endpoint when infiltration is detected. In various implementations, a network device on a network can be configured to monitor access to the network device. The network device can further be configured to determine that a condition has occurred. The condition can indicate a suspect access to the network device has occurred. The network device can further be configured to determine a new access protocol for the network device. The network device can further be configured to use the new access protocol to cause communication between the network device and the network to be redirected to a high-interaction network. Redirecting the communication can disable communication between the network device and the network and enables communication between the network device and the high-interaction network.

The invention discloses a heterodimeric FC (fragment crystallizable) modification method based on a charge network and a preparation method of heterodimeric proteins. The modification method is characterized by establishing a charge interaction network and mutating one or more interfacial amino acids based on interaction of heavy-chain CH3 two-arm amino acids of the FC and modifying the amino acids in the CH3 domains through charge effect, thus weakening self interactions of the domains (which is beneficial to forming homodimers) and enhancing the interactions between the domains ( which is beneficial to forming heterodimers) and finally selecting sense mutation. The invention also relates to heterodimeric proteins prepared by the preparation method, independent polypeptides forming the heterodimeric FC and nucleotide sequences coding the polypeptides.

The invention provides a digital television user interface management system comprising at least one front-end server system, an interaction network and at least one user terminal. The front-end server is connected with and exchanged data with at least one user terminal through the interaction network. The front-end server carries out a management to the user interface and generates, alters, deletes, manages or transfers the user interface which is corresponding to the user according to the instruction sent by the terminal. The invention also provides a user interface management method based on the digital television user interface management system. The method supports the user-defined user interface and provides a personality service for the user without needing trough a way of uniformly exchanging a turning-on page layout, thus causing more characteristics to the user interface including the turning-on page layout, more conforming the personality requirement of the user as well as possessing a simple and convenient operation; The invention shields a difference of a set-top box. The realization of simplifying the set-top box reduces the operation cost; the invention provides a method of defining the user interface through a plurality of methods such as a network for the user.

The invention discloses a teacher-student interaction network system and method for classroom teaching. The teacher-student interaction network system for classroom teaching comprises teacher terminalequipment, a network server device and student terminal equipment, wherein the teacher terminal equipment is used for demonstrating electronic teaching plan documents during the class, acquiring voice information when a teacher gives a lesson, meanwhile copying interfaces during demonstration of the electronic teaching plan documents as image information, merging the interfaces with the voice information to generate teaching video information, compressing and encoding the teaching video information and then transmitting the teaching video information to the network server device, and sharingthe teaching video information to all the student terminal equipment. Students can decode and play the teaching video information through the student terminal equipment. The students can transmit character or expression information to the teacher terminal equipment, and the character or expression information is displayed in a rolling manner by a bullet screen mode to remind the teacher to adjustthe teaching speed in time or answer questions in a targeted manner. The teacher-student interaction network system and method for classroom teaching can be used for classroom teaching of colleges, middle schools and primary schools, disconnection of the teacher from students is avoided, and thus, the teaching efficiency and the teaching quality are improved.

The invention provides an abnormal account identification method and system. Through construction of a data interaction network, network attribute features of the data interaction network and non-network attribute features of the data interaction network are obtained, then according to the network attribute features of the data interaction network and the non-network attribute features of the data interaction network, a classification prediction model is obtained, and an account to be identified is identified by use of the classification prediction model, such that an abnormal account does not have to be identified through manual discrimination, numerous manpower resources are saved, and the identification efficiency is effectively improved. At the same time, by use of a scientific digital analysis means, the identification accuracy is improved.

The invention discloses a hybrid dynamic honeypot deployment system based on a cloud platform. The system is deployed on the cloud platform, and comprises a low-interaction honeypot, a firewall, an analysis module, a traffic redirector, a control module, a high-interaction network, and a safeguard module, wherein the low-interaction honeypot is arranged outside the firewall and used for attractingattack traffics of an attacker; the analysis module can analyze attack behaviors of the attacker, and find out the optimum deceiving mode for a specific suspicious network traffic; the traffic redirector is used for carrying out address redirection on the suspicious traffic obtained through analysis of the analysis module; and the control module is used for guiding the traffic, on which the address redirection is carried out, to a corresponding honeypot in the high-interaction network. The hybrid dynamic honeypot deployment system based on the cloud platform provided by the invention has theadvantages that characteristics of the low-interaction honeypot and a high-interaction honeypot are combined, and the two types of the honeypots are deployed at the same time to fully exert the corresponding characteristics and advantages, so that the fidelity and the performance of a honeypot system are improved.

The invention discloses a built-in drug target interaction prediction method based on a heterogeneous network. The built-in drug target interaction prediction method includes the steps: based on the assumption that a chemically similar drug can often interact with a similar target, combining a drug-drug similarity network, a target-target similarity network, and a drug-target interaction network into a drug-target heterogeneous network; using a starting-node-based migrating sequence, constructing a neural network classification model, taking the migrating sequence as input of the neural network classification model, training the classification model and learning to obtain vector representation of all nodes; and for prediction of drug-target interaction, giving a pair of drug-target pairs,extracting vector representation of the corresponding drug and target from the node vectors obtained from learning, performing Hadamard product operation on the two vectors, and taking the obtained result as the input of a random forest classifier to obtain the final prediction result. According to the experimental verification, the built-in drug target interaction prediction method based on a heterogeneous network has preferable prediction effect and applicability.

A method and apparatus for informing a plurality of terminals receiving the same Mobile Broadcast (BCAST) service of an upcoming event such as a BCAST service change in a BCAST system are provided. When receiving a notice of a notification event related to a BCAST service or an Service Guide (SG), a BCAST Subscription Management (SM), including a Notification Generation Function (NTG), creates a notification message about the notification event and sends it to a BCAST Service Distribution/Adaptation (SD/A). The BCAST SD/A sends the notification message to one terminal or a group of terminals through a Broadcast Distribution System (BDS) or an interaction network.

The invention discloses a method for identifying protein functions based on a protein-protein interaction network and network topological structure features. Firstly, a node and side-weighted protein-protection interaction network is established, wherein the node represents protein while the edge represents the interaction; then the nodes and the sides in the network are weighted by protein first-grade structural description and protein-protein interaction trust scoring; protection functional annotation data is collected to establish a data set, and a new protein with overall and local information network topological structure features is provided based on a graph theory; and finally, the protein functions are predicated by choosing features through adopting a minimum-redundancy maximum-correlation method and by modeling through a support vector machine. The protein function predication method is greatly better than the prior art, and has robustness on sequence similarity and sampling; and meanwhile, information of three-dimensional structure and the like of protein is not required, so that the method is simple, rapid, accurate and efficient, and the method is expected to be applied in the research fields of proteomics and the like.

The invention discloses a knowledge graph relational data extraction method based on a semantic syntax interaction network. The method mainly comprises the following steps: collecting a design document of a complex equipment design process, and establishing a design document corpus according to text data of the design document; performing text preprocessing on the design document text data; establishing a relation extraction model based on a semantic syntax multi-round interaction deep neural network; inputting the preprocessed text data and the relationship type label into a relationship extraction model for offline training; and preprocessing the text data of the entity relationship to be predicted, and inputting the preprocessed text data into the trained relationship extraction model to obtain a predicted relationship category. Through multiple rounds of interaction of the semantic information and the syntactic information, the utilization rate of the semantic information and the syntactic information is improved, the semantic information and the syntactic information beneficial to knowledge graph relation data extraction are dynamically and deeply mined, and the flexibility, generalization and accuracy of the model are improved.

The invention relates to a method and a system for predicting a protein interaction target point of a drug. The method comprises: 1) collecting a human protein interaction network and single protein target point data of the drug, and constructing an interactive protein target point data set of the drug; 2) obtaining description data of the drug and proteins; 3) constructing a bigraph for representing an interactive relationship between the drug and a protein pair, constructing a similar matrix for representing drug similarity and protein pair similarity, establishing a kernel function for correlating the similar matrix of the drug and the protein pair, and establishing a prediction model through a machine learning algorithm; and 4) performing independent set testing by utilizing unknown drug and interactive protein pair, and predicting a possibly existent unknown drug protein interaction target point, and verifying a prediction result through database and document retrieval. According to the method and the system, the search space of the drug target point can be expanded and the more specific drug protein interaction target point with the best classification performance can be obtained.

There is provided a system of estimating a building performance, the system comprising a memory configured to store instructions comprising a method of estimating the building performance and a processor interactively linked to the memory. The processor is configured to execute the method by designating a plurality of building performance variables for estimating the building performance, identifying an interaction network correlating a model building performance representative of the building performance with the designated plurality of building performance variables, selecting a known performance of at least one model structure as a proxy for the building performance, determining learned values for a plurality of initially unknown parameter values from the interaction network and the at least one model structure having the known performance, and utilizing the learned values in the interaction network to estimate the building performance.

This invention relates to an interaction network consultation system and a method for obtaining medical images by multiple addressing, in which, the system includes multiple image storage systems and multiple consultation working stations loaded on the Internet, the image storage system receives various DICOM images via collection gateways, carries out sorted management and storage, provides DICOM communication, WEB or other communication service and the stored DICOM image is marked and identified by UID, the consultation working station is a tool for doctors to diagnose and process digital medical images to display and process any medical images including DICOM images and non, support DICOM or other communication interfaces based on TCP/IP to connect with PACS or image storage system and inquire images for using UID by multiple storage systems to select the optimum storage point and download it timely to the working station.

The invention discloses a hierarchical routing algorithm based on a distributed type wireless aggregation network. The algorithm comprises the following steps of clustering of a wireless information interactive network, wherein the clustering is characterized by comprising the steps of utilizing nodes in the network to build a plurality of clusters by a cluster strategy, enabling each cluster to contain multiple common nodes and a cluster main node, and carrying out cluster management and cluster interior information interaction under the control of the cluster main nodes; building of the distributed type wireless aggregation network, wherein the building is characterized by comprising the steps of on the basis of the clusters of the wireless information interaction network, utilizing a series of aggregation nodes to build a distributed type hierarchical wireless aggregation network, reducing the data throughput pressure of the cluster main nodes, providing support for the inter-cluster information interaction of the distributed type information interaction network, and managing and optimizing the whole network; and designing of a hierarchical routing algorithm based on the distributed type wireless aggregation network, wherein the designing is characterized by comprising the steps of providing a lightweight routing protocol based on the cluster strategy and the distributed type wireless aggregation network, obtaining a node route list in the whole network range in the process of adding nodes into the network by the protocol under the conditions of smaller channel bandwidth and controlled cost, carrying out route management on the network, and addressing and routing all nodes in the network.

The invention belongs to the field of data excavation and discloses a protein functional module excavating method for multi-view data fusion. The method comprises the following steps: firstly performing quantifying description on strong and weak interaction of multiple data sources on protein and forming multi-view data; further performing uniform matrix decomposition on the multi-view data by utilizing a polymerization nonnegative matrix algorithm provided by the invention; determining the functional module of the protein by virtue of obtaining the optimal approximation of the multi-view information. The protein functional module excavating method for multi-view data fusion, provided by the invention, aims at simultaneously analyzing multiple biodata and comprises gene coexpression, GO annotation and PPIN and can be used for extracting the protein functional module with the most consistent polymerization characteristic from the multi-view. The method disclosed by the invention is especially suitable for interaction networks and biodata of the protein and meanwhile can be applied to community excavation problems of social complex networks and communication networks.

The invention discloses a method and a system for predicting the association relationship between a disease and LncRNA. The method comprises the steps: the LncRNA-miRNA association relationship and the miRNA-disease association relationship are obtained from a known database, and a LncRNA-miRNA-disease interaction network is constructed according to the two relationship; a disease hyper-expressionprofile and a LncRNA hyper-expression profile are constructed based on the LncRNA-miRNA-disease interaction network; the prediction model of the disease and LncRNA association relationship is trainedaccording to the disease hyper-expression profile and the LncRNA hyper-expression profile by using LncRNA similarity computing and disease similarity computing based on the RBF neural network; and the LncRNA-disease association pairs of the candidate samples are predicted by using the prediction model. The most promising LncRNA disease association for further experimental verification is provided, the potential disease-related LncRNA can be effectively mined from the mass biological data, the cost and the expense of the biological experiment can be reduced and the research progress in the bioinformatics field can be accelerated.

The invention discloses a protein complex identification method based on key protein and local adaptation. Based on the importance of the key protein to life activities of organisms and the topological property of a protein interaction network, the invention discloses the protein complex identification method (EPOF) based on key protein and locally adapted protein by using the key protein as a seed. The protein complex identification method not only can be applied to a non-weighted protein interaction network, but also can be applied to a weighted protein interaction network. The protein complex identification method can be used for recognizing the protein complex more accurately only according to the protein interaction information and the key protein information, and predicting a large quantity of protein complexes in one step, and solves the problems of high cost, high time consumption and the like of the chemical experiment method.

This invention discloses a digital TV living broadcast and playback system and a method including a front system, a broadcast and double-way interaction network and user receiving terminals, which sets a program collection subsystem, a storage and video subsystem, an order process server, a database server and a program navigation server in a front system and records living programs in the front stored server, which delivers said programs to users via the video server and sends instructions of pause, quick quit, speed and location to the video server to finish the operations.

Described herein is a system for inferring one or a population of biochemical interaction networks, including topology and chemical reaction rates and parameters, from dynamical or statical experimental data, with or without spatial localization information, and a database of possible interactions. Accordingly, the systems and methods described herein may be employed to infer the biochemical interaction networks that exist in a cell. To this end, the systems and methods described herein generate a plurality of possible candidate networks and then apply to these networks a forward simulation process to infer a network. Inferred networks may be analyzed via data fitting and other fitting criteria, to determine the likelihood that the network is correct. In this way, new and more complete models of cellular dynamics may be created.

The invention discloses a lightweight fine-grained image recognition method for cross-layer feature interaction in a weak supervision scene, and the method comprises the steps: constructing a novel residual module through employing multi-layer aggregation grouping convolution to replace conventional convolution, and enabling the novel residual module to be directly embedded into a deep residual network frame, thereby achieving the lightweight of a basic network; then, performing modeling on the interaction between the features by calculating efficient low-rank approximate polynomial kernel pooling, compressing the feature description vector dimension, reducing the storage occupation and calculation cost of a classification full-connection layer, meanwhile, the pooling scheme enables the linear classifier to have the discrimination capability equivalent to that of a high-order polynomial kernel classifier, and the recognition precision is remarkably improved; and finally, using a cross-layer feature interaction network framework to combine the feature diversity, the feature learning and expression ability is enhanced, and the overfitting risk is reduced. The comprehensive performance of the lightweight fine-grained image recognition method based on cross-layer feature interaction in the weak supervision scene in the three aspects of recognition accuracy, calculation complexity and technical feasibility is at the current leading level.

The invention provides a remote interaction network massage chair to overcome the technical defects that in the use process of an existing domestic intelligent massage chair, blind massage easily occurs and timely and accurate guidance is not available, and relates to the technical field of domestic intelligent massage chairs. The remote interaction network massage chair comprises a chair body, wherein a human body trunk massage unit is arranged in the chair body, leg massage units are connected to the front side of the chair body, arm massage units are arranged on armrests of the chair body, a micro-processing unit which is connected with and controls the human body truck massage unit, the leg massage units and the arm massage units is further arranged on the chair body, and the micro-processing unit is connected with a man-machine conversation unit. The remote interaction network massage chair is characterized in that the micro-processing unit is further connected with a sign detection unit and a network connection module, the sign detection unit is used for detecting sign information of a user, and the network connection module is used for being in communication connection with a network. When remote specialized guidance and analysis are conducted through the network connection module, a remote professional can timely and accurately obtain each item of sign information of the user according to the sign detection unit and make authority suggestions.