50 results about "Core object" patented technology

Apps are secured or security-wrapped either before they are downloaded onto a device, such as a smartphone or tablet device, or after they are downloaded but before they are allowed to access the device operating system and cause any potential damage to the device. An app provider, such as an employer or a cellphone provider, can secure its apps before consumers download an app from their app store or marketplace. The app is secured before it is allowed to access the operating system of the device, thereby preventing the app from malicious behavior. Core object code of the app is obtained and the digital signature is removed. App object code is substituted with security program object code, thereby creating a security-wrapped app. The security-wrapped app is prepared for execution on the device and is re-signed with a new key.

In community mining based on core objects and affiliated objects, a set of core objects for a community of objects are identified from a plurality of objects. The community is expanded, based on the set of core objects, to include a set of affiliated objects. According to one aspect, a model of a community of objects is obtained by grouping a first collection of a plurality of objects into a center portion, and grouping a second collection of the plurality of objects into one or more concentric portions around the center portion. The groupings of the first and second collections of the objects are identified as the community of objects.

The invention discloses a method and device for determining a taxi pick-up and drop-off hot spot region center. The method includes the steps of obtaining taxi state information data, extracting geographical location data according to taxi serial numbers, ranking the geographical location data according to timestamps, and obtaining taxi track data; extracting pick-up and drop-off position data from the taxi track data, wherein the datum of each pick-up spot or drop-off spot of each taxi is a sample datum; carrying out DBSCAN clustering on the pick-up and drop-off position data primarily, and extracting out core object data, wherein the number of the sample data within the preset scanning radius of a core object is greater than or equal to a first preset threshold value; merging the core object data within the selected time period, carrying out secondary DBSCAN clustering on the merged core object data, extracting the cluster core object data, and determining the taxi pick-up and drop-off hot spot region center on the basis of the cluster core object data.

A type system employing structural subtyping is disclosed herein. A core type system supports several structural types, such as stream, choice, intersection and sequence. Also part of the core type system is a new invariant type, which denotes values whose dynamic type is the same as its static type, and type restrictions for limiting a range of a base type. Furthermore, a streamlined structural version of delegates, called structural delegates and a validation method thereof are introduce into the type system. To further facilitate type safety, strict statically checked interface casts are introduced.

The invention discloses a drilling type side-wall coring apparatus, which is consisted of ground electrical control system and down-hole coring system. The ground electrical control system is connected with the down-hole coring system by a high-voltage high-current collecting ring and a logging winder cable. The down-hole coring system is consisted of a halter, electron section, pressure balancing apparatus, hydraulic section and a mechanical section from above to below in series. The side-wall coring apparatus is put to down-hole by the logging winder cable, a natural gamma instrument is provided to trace and check depth of the same. When the coring object position is determined, signal is sent out by the ground electrical control system, and the down-hole coring instrument is driven to execute motions of pulling-against, drilling, core-folding, drilling back, stop pulling-against and core-storing. Meanwhile, real-time monitoring of instrument working condition and coring process are made by various sensing units, and recording data is transmitted to ground control system by the cable. Stratum core is acquired by side-wall vertically rotary drilling, which is accomplished by controlling down-hole instruments through the real-time digital display panel.

The invention discloses a big-data-based taxi service station site selection and feasibility evaluation method. The method comprises the steps of obtaining GPS data of a taxi, conducting preprocessing and removing wrong data; on the basis of the data, extracting information data of a parking position of the taxi; conducting divided period space clustering on the information data of the parking position of the taxi to obtain position information of a parking hot point of each period of time; visualizing a core object of a clustering result, determining the reasonable radius, determining the position range of the parking hot point of the taxi, and using the position range as a preliminary scheme of taxi service station site selection; on the basis of the preliminary scheme of taxi service station site selection, analyzing influence factors of site election feasibility; conducting feasibility evaluation on the preliminary scheme of taxi service station site selection and determining the final site selection scheme. According to the scientific intelligent site selection method, the existing problems that a user has difficulty taking a taxi and the taxi goes on a strike can be solved, the working environment of a taxi driver is improved, and the problem that a taxi is parked freely is solved.

The embodiment of the invention discloses a clustering method and device and a terminal device. The clustering method comprises the steps that firstly, when the number of neighbor objects of an object to be accessed in at least one neighborhood of multiple neighborhoods is not smaller than a corresponding preset threshold value, the object to be accessed is determined as a core object; secondly, the object to be accessed is classified into one type; thirdly, extension clustering is conducted on a directly density-reachable object of the object to be accessed in the assigned neighborhood; if the directly density-reachable object is not the core object, extension is stopped; fourthly, a next object to be accessed continues to be determined until clustering of all the objects to be accessed is completed. Due to the fact that multiple-neighborhood type judgment is used for judging whether the object to be accessed is the core object in the clustering method, it means that the limitation of the scanning radius and the minimum number of contained objects is loosened; in this way, the sensitivity of a clustering result to the two parameters including the scanning radius and the minimum number of contained objects is reduced, and the accuracy rate of the clustering result is increased.

The Core Network Management Object Model of the present invention generically models the physical and logical objects in a configuration management system. The present invention also models the generic action objects required to manipulate the network objects. Unique object level information is isolated at the leaf level of the object model and is not proliferated to other generic parts of the model. The action objects all model different actions that need to be performed in a configuration application architecture and insulates the network objects from having any knowledge of session and event information. Leaf objects and actions are specialized to perform any configuration related actions. In the Core Network Management Object Model an Object Factory creates the unique object and an Action Factory creates the unique action. The action shall then be performed on the unique object to get, set and modify device information through SNMP and also to store the information in the database. This makes the object model for both the network objects and actions re-usable, scalable, and extendable. Use of the present invention drastically reduces development time and effort so that the same objects can be re-used in different applications and solutions.

A computer-implemented method for performing data storage. The method comprises the steps of: receiving data to be stored from a data source; segmenting the data into immutable core objects each being written into a collection and being assigned a unique object ID; grouping the immutable objects into blobs each including at least one of the objects and being assigned a unique blob ID derived from the object ID of the at least one of the objects included therein, with the last blob of the collection being identifiable as such; defining a state of the collection by linking at least one subset of the core objects of the collection to one another with a last object of each subset being the object head of the corresponding subset and storing identification information of the head object; and storing each one of the blobs onto at least one backend.

The embodiment of the specification discloses a data labeling method, a data labeling device and data labeling equipment. A solution includes: obtaining feature vectors of all to-be-labeled data; using a density clustering algorithm to carry out clustering on all the feature vectors to obtain a plurality of class clusters; carrying out screening in points contained by the class clusters to obtaina core object set and a non-core object set according to density situations of the class clusters; selecting partial core objects in the core object set of the class clusters and partial non-core objects in the non-core object set of the class clusters, and carrying out labeling; and carrying out automatic diffusion labeling on at least partial other points in the class clusters according to a labeling result.

An embodiment of the invention relates to a method and a device for calculating a vehicle parking point. The method comprises the steps of performing weighting processing on all track points in a target track point set; according to a preset rule, randomly selecting a core object track point from the target track point set, and determining a neighborhood domain which corresponds with the core object track point, wherein the neighborhood domain comprises one or multiple track points; generating a cluster according to the target track point set; performing successive recursive traversal on the core object track point in the target track point set and the core track point included in the neighboring domain through an inspection queue; segmenting the cluster according to a plurality of core object track points obtained through traversal according to a time relation; determining the vehicle parking position according to the track point cluster, performing weighting processing on the vehicletrack points according to position information which is reported by the vehicle, determining the core object track point, calculating the vehicle parking point, and accurately determining a vehicle parking position.

The invention discloses a three-branch clustering method and system based on an improved DBSCAN, and belongs to the technical field of data processing. The three-branch clustering method comprises thefollowing steps: calculating Euclidean distances of any two objects in a clustering object set to obtain a similarity matrix of all the objects; recalculating the similarity matrix by utilizing a scaling function to obtain a scaling distance matrix; on the basis of the scaling distance matrix, obtaining a plurality of clusters and a noise point set through a DBSCAN algorithm; determining a positive domain and a boundary domain of each cluster; judging whether the object in the boundary domain of each cluster belongs to two or more than two clusters or not; and allocating each noise point to the boundary domain of the cluster where the corresponding core object is located. According to the three-branch clustering method provided by the invention, a good clustering result can be obtained onmost data sets, the obtained boundary domain is a delay decision result, and the error rate or decision risk of clustering can be reduced in practical application.

The invention relates to a method and system for determining high-frequency regions for roadside stall business in urban streets. The method comprises following steps: utilizing an optimized DBSCAN algorithm to process acquired data of roadside stall business in urban streets and classifying regions for roadside stall business in urban streets; and determining high-frequency regions for roadside stall business in urban streets based on classification results of regions for roadside stall business, wherein the optimized DBSCAN algorithm is used for selecting a point outside of the neighbor radius for pre-set threshold value of a current data object as a next data object to be processed. The method and system for determining high-frequency regions for roadside stall business in urban streets have following beneficial effects: the optimized DBSCAN algorithm is adopted to select the point outside of the neighborhood radius for pre-set threshold value of the current data object as the next data object to be processed; repeated search of objects in public neighborhood is avoided; calculations of neighborhood search for core objects are reduced; complexity of the algorithm is decreased; and determination efficiency of high-frequency regions for roadside stall business in urban streets can be increased for providing information and making decisions for urban management work.

The invention relates to the internet technology field and particularly relates to a user credit model establishment method and device in order to solve a problem that in the prior art a user credit score which is calculated by using a unified credit model is very low. The user credit model establishment method comprises steps of choosing at least one user as a core object in one cluster from a user database, for every core object in the cluster, determining similarities between each of other users and the core object according to the core object and characteristic values of each of other users under multiple characteristic parameters besides the core object in the cluster in the user database, determining other users classified into the cluster according to the similarities between each of the other users and the core object, and adopting a modeling mode corresponding to the cluster to establish the user credit model targeting various users in the cluster.

The invention provides an initial clustering center determination method and device based on a K-mean clustering algorithm, which can discover the public opinion hot topics quickly and accurately froma large amount of microblog data. The method comprises the steps of obtaining a data object set, wherein the data object set comprises a microblog document set; determining the average similarity between each data object in the data object set and other data objects, and obtaining the data object of which the average similarity is greater than or equal to a preset density threshold as a core object; and selecting a plurality of core objects which are most dissimilar from the core objects as an initial clustering center of a K-mean clustering algorithm, so that the K-mean clustering algorithmperforms clustering according to the obtained initial clustering center. The invention relates to the field of machine learning.

In one general aspect, a computer system can include instructions stored on a non-transitory computer-readable storage medium. The computer system can include an application link manager configured to receive an indicator that a first application is linked to a second application, and an object generator configured to store a copy of data from a database of the first application and represented within a user interface of the first application as a core object in a storage environment in response to the indicator that the first application is linked to the second application. The computer system can also include a database link manager configured to link a database of the second application with the core object stored in the storage environment in response to the copy of the data being stored as the core object in the storage environment.

The invention discloses a virtual game control method and device, equipment, a medium and a computer product, and relates to the field of virtual environments. The method comprises the steps: displaying at least one virtual object, wherein the at least one virtual object is used for automatically executing a battle behavior according to object attributes when participating in a virtual game, wherein the virtual game is a game composed of at least two rounds of battle processes; receiving a selection operation on a target object in the at least one virtual object, wherein the selection operation is used for marking the target object; and based on the target object, displaying a strategy execution result of a target game strategy in the standby stage, the target game strategy including a game behavior of automatically configuring the virtual object participating in the virtual game around the target object. That is, the target object is used as the core object according to the setting, and the game playing behavior in the virtual game playing is automatically controlled to be performed around the core object, so that the control efficiency of the virtual game playing is improved.

The embodiment of the invention discloses an object clustering method, and a model training method and device. The objective of the invention is to solve the problem that human intervention factors in the clustering division process influences the accuracy of the final clustering division in the prior art. The object clustering method comprises: determining a Euclidean distance of any two objects in an object set according to a preset feature value corresponding to each object in the object set to be clustered; performing distribution of objects in the object set in a three-dimensional space according to the Euclidean distance; determining a first core object of the number of objects in a neighborhood with a preset radius being not smaller than a preset value based on the distribution of the objects in the object set in the three-dimensional space; determining a second core object of the number of objects in the neighborhood with the preset radius being not smaller than the preset value and located in the neighborhood with the preset radius of the first core object; and belonging the first core object and the second core object to the same object cluster.

The invention discloses a herbal compound hydrophile-lipophile balance liquid foundation for increasing the skin texture and a preparation method thereof. The preparation method comprises the following steps: firstly and uniformly mixing gellan gum, aloe gel and sodium methyl cellulose, thus obtaining a capsule wall material; uniformly mixing water, shea butter, herba centellae extract, arbutin, sargassum extract and hyaluronic acid, thus obtaining a capsule core material; then uniformly mixing the capsule wall material with water, using the mixed solution as a capsule wall solution, uniformlystirring after heating the capsule core material to 60 to 70 DEG C, carrying out homogenization treatment, using the homogenized capsule core material as a capsule core object, and preparing microcapsules by adopting a dropping method; mixing white veseline, lanum, cetearyl ether, isopropyl palmitate, propanediol, enhanceparaben and titanium dioxide, heating and carrying out homogenization treatment, thus obtaining a base mixture; mixing the microcapsules with the base mixture, thus preparing the herbal compound hydrophile-lipophile balance liquid foundation. After the herbal compound hydrophile-lipophile balance disclosed by the invention is smeared, the skin can be moist and clear, a concealing effect is good, the whole makeup is not greasy, the makeup is lasting, and a water-oil separation phenomenon cannot be caused during a storage period.

The embodiment of the invention belongs to the field of information security, and relates to a data transmission method, which comprises the following steps: a server obtains an original file, encrypts the original file according to a preset key to obtain an encrypted file, packs the encrypted file to obtain a target file, and sends the target file to a client; the client obtains the class full name of the encrypted file, obtains the target file when the historical file does not exist in the cache, obtains the encrypted file from the target file according to the class full name, and decrypts the encrypted file according to the decryption key to obtain an original class file; the client generates a core object of the original class file according to a preset adapter, assembles a service request of the core object to obtain an assembly request, and sends the assembly request to the server; and the server processes request data of the assembly request. The invention further provides a data transmission system, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the original class file can be stored in a block chain. According to the invention, the security of data transmission is improved.

The invention relates to a positioning method for recording the abnormal exit of a common process by using a shared memory object. It uses shared memory objects in the form of ring buffers to directly record the latest information of each common process, and sets the monitoring process to perform regular handshakes with common processes to determine whether any common process exits, which facilitates the positioning of abnormal process exits. . In addition, because the shared memory object uses the ring buffer to store information, the amount of stored information is greatly reduced, the memory overhead is reduced, and the running speed is improved.