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292 results about "Interaction network" patented technology

Interaction network is a network of nodes that are connected by features. If the feature is a physical and molecular, the interaction network is molecular interactions usually found in cells. Interaction network has become a research topic in biology in recent years due to rapid progress in high throughput data production.

Digital TV user interface management system and method

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.
Owner:SHENZHEN COSHIP ELECTRONICS CO LTD

Teacher-student interaction network system and method for classroom teaching

InactiveCN109615961AEasy to ask questionsKeep abreast of difficultiesTransmissionElectrical appliancesTerminal equipmentDocumentation
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.
Owner:HUAZHONG NORMAL UNIV

Hybrid dynamic honeypot deployment system based on cloud platform

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.
Owner:BEIJING INST OF COMP TECH & APPL

Built-in drug target interaction prediction method based on heterogeneous network

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.
Owner:CENT SOUTH UNIV

Method for identifying protein functions based on protein-protein interaction network and network topological structure features

InactiveCN105138866ARobustSignificant predictive advantageSpecial data processing applicationsNODALData set
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.
Owner:SYSU CMU SHUNDE INT JOINT RES INST +2

Method and system for predicting protein interaction target point of drug

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.
Owner:ACAD OF MATHEMATICS & SYSTEMS SCIENCE - CHINESE ACAD OF SCI +1

Hierarchical routing algorithm based on distributed type wireless aggregation network

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.
Owner:CENT SOUTH UNIV

Method and system for predicting association relationship between disease and LncRNA

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.
Owner:CHANGSHA UNIVERSITY

Protein complex identification method based on key protein and local adaptation

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.
Owner:CENT SOUTH UNIV

Lightweight fine-grained image recognition method for cross-layer feature interaction in weak supervision scene

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.
Owner:SOUTHEAST UNIV

Remote interaction network massage chair

InactiveCN103610560APrevent blind damage to health phenomenaChiropractic devicesDiagnostic recording/measuringNetwork connectionSign detection
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.
Owner:深圳市诺嘉智能养生发展有限公司
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