128 results about "Layered model" patented technology

An object of the present invention is to easily eliminate fumes inside a chamber, so as to improve a positional accuracy of irradiation with a light beam and a machining accuracy in a method for manufacturing a three-dimensional shaped object. A stacked-layers forming device 1 includes a powder layer forming unit 3, a light beam irradiating unit 4, a base 22 which is fixed and on which a powder layer 32 is formed, a lifting/lowering frame 34 which surrounds the circumference of the base 22 and is freely capable of being lifted and lowered, a cover frame 36 which has a window 36a allowing transmission of light beam in its top surface, and whose bottom surface is opened, and which is disposed on the lifting/lowering frame 34 to form a chamber C, and a gas tank 71 for supplying an ambient gas. The lifting/lowering frame 34 is lowered to reduce the volume of the chamber C, so as to discharge fumes generated inside the cover frame 36, which performs replacement with the ambient gas. Since the volume of the chamber C is reduced, it is possible to easily eliminate the fumes, which makes it possible to improve the positional accuracy of irradiation with the light beam L, and the machining accuracy.

Methods are described for assessing material condition. These methods include the use of multiple source fields for interrogating and loading of a multicomponent test material. Source fields include electric, magnetic, thermal, and acoustic fields. The loading field preferentially changes the material properties of a component of the test material, which allows the properties of the component materials to be separated. Methods are also described for monitoring changes in material state using separate drive and sense electrodes with some of the electrodes positioned on a hidden or even embedded material surface. Statistical characterization of the material condition is performed with sensor arrays that provide multiple responses for the material condition during loading. The responses can be combined into a statistical population that permits tracking with respect to loading history. Methods are also described for measuring the stress in the material by independently estimating effective electrical properties, such as magnetic permeability or electrical conductivity, using layered models or predetermined spatial distributions with depth that are then correlated with the stress.

It relates to a method of predicting the collapse and crack pressure underground with the drilling head. Recording the earthquake status of a well to be drilled and several other adjacent drills that have already been drilled, getting the earthquake record of the well to be drill and already drilled through weighting, through sound wave echoing difference and density measuring for the already drilled wells to get the log data of different strata, a hierarchical model can be established to predict the sound wave speed and wave resistance of each strata based on the earthquake record. Through the log curve predicted of the strata of the well to be drilled, the collapse and crack pressure of the strata can be predicted combined with the interpretative model of the well wall stability mechanics logging. It can effectively prevent the collapse of the well wall and accidents occurrence underground.

An advertising framework for transmitting advertisements from wireless access points to client devices that need not be connected to the wireless access point. The client device can display the advertisements on a user interface of the client device. Such advertisements may be transmitted, for example, as part of a control message transmitted by a wireless access point of a wireless network, or other message conventionally used to broadcast network characteristics necessary for a client device to establish a connection to the wireless access point. In terms of the Open Systems Interconnect (OSI) layered model of a network, layer 2 control messages, including announcement transmissions such as beacons, may be used for control messages.

The invention relates to a manufacturing method of a complex-structured intelligent material device based on a rapid forming technique. The manufacturing method comprises the following steps: determining the utilized rapid forming technique according to one or multiple requirements including the physicochemical properties and states of a forming raw material and the precision of the complex-structured intelligent material device; establishing a three-dimensional model of the complex-structured intelligent material device, carrying out discretization on the surface of the three-dimensional model of the complex-structured intelligent material device to generate a three-dimensional digital model file of the three-dimensional model of the complex-structured intelligent material device, carrying out support adding, layered model discretization and processing route generation on the three-dimensional digital model file to guide out a processing file capable of being identified by rapid forming equipment, and downloading the processing file to the rapid forming equipment; manufacturing the complex-structured intelligent material device by virtue of the rapid forming equipment according to the processing file. According to the manufacturing method, the problem that different types of the complex-structured intelligent material devices are difficult to manufacture is solved; a forming device has the advantages of high precision, adjustable performance, easiness in manufacturing and the like.

The invention belongs to the field of radar signal processing, and particularly relates to a sparse aperture ISAR self-focusing and lateral scaling method based on Bayesian learning. The method comprises the following steps: firstly performing sparse prior modeling on an ISAR image by using a Laplace layered model, and performing sparse reconstruction on the ISAR image by using a variational Bayesian method, wherein during the reconstruction of the ISAR image, a modified Newton iterative method is used to simultaneously estimate a phase error and a target rotational speed to achieve self-focusing and lateral scaling of the ISAR under the sparse aperture condition. The invention obtains the beneficial effects that: due to the sparse aperture ISAR self-focusing and lateral scaling method based on Bayesian learning, the self-focusing and lateral scaling of the ISAR under the sparse aperture condition can be realized, and the ISAR image with good focusing effect, high resolution and exactlateral scaling can still be obtained under the condition of sparse radar echo data aperture caused by the factors such as low SNR, strong interference and insufficient effective aperture, which has important engineering application value and can provide theoretical support for the design of a compressed sensing radar.

The invention provides an earth and rockfill dam construction unit partitioning method based on a BIM technology. The method comprises the steps that S1, an engineering design result model is read in; properties of the design model are expanded and managed according to material characteristics of engineering construction and the model as well as construction characteristics and properties, and construction-related property is added on the basis of property information of the design model; S2, hierarchical models are obtained according to hierarchical model construction characteristics; S3, property configuration and expansion are performed on hierarchical model construction according to the hierarchical model construction characteristics or parameters to obtain a BIM model for hierarchical model construction and properties of the BIM model; S4, framing models are obtained according to framing model construction characteristics; S5, property configuration and expansion are performed on framing model construction according to the framing model construction characteristics and parameters to obtain a BIM model for framing model construction and properties of the BIM model; and a total construction BIM model is obtained.

A streaming media concealed communication method based on hierarchical model belongs to a streaming media information concealing field. The invention is characterized in that before the entering of the source end for transmitting, and after the outputting of the target end from the internet, a secret information insertion module and a secret information extraction are respectively arranged for together forming a concealed communication module which is composed of a concealed application layer, a concealed transmission management layer and a concealed transmission adapting and executing layer in sequence. The input of the secret information, the reliable and concealed transmission of the secret information and the insertion and extraction operation of the secret information are respectively executed. The synchronous control and mistake control of the transmission management layer homogeneously adopt a sequence number mechanism. A finite state machine with a predetermined state flag bit is adopted for confirming the response under each state. A slide window is adopted for flow control. An application style token is adopted for realizing the transmission of different concealed applications in a same transmission channel according to priority. The invention has the advantages of wide adaptability and reliable transmission.

A system and method of using a multi-layered network model for analyzing the survivability of network services. The model is defined in terms of layers, connections, entities, physical processing elements, physical network elements, and physical infrastructure elements. Network services are modeled by sets of communicating entities at the application layer that are connected by connections at the underlying layers. The generality of the model constructs enable the construction of models of complex networks and services that can involve multiple layers of communication protocols, network elements, processing elements, and failover/backup mechanisms. The service survivability of a network is analyzed by projecting the failure of a set of physical elements onto the model and then determining the proportion of service affected at the application layer.

Interconnected networking systems is becoming a challenge in terms of dependability estimation as two main communication technologies co-exist in today's networks: switching and routing. These two technologies have two different and complementary levels of resilience. Switching is focused on sensitivity to delays and connectivity whereas routing is focused on traffic losses and traffic integrity. The main challenge in modeling these systems dependability is to aggregate the complexity and interactions from various layers of network functions and work with a viable model that reflects the resilience behavior from the service provider and the service user standpoints. The method uses a hierarchical approach based on the Markov Chains and RBD modeling techniques to build a multi-layered model of assuring a multi-services networking system meets its reliability targets dictated by a service level agreement. To cope with modeling complexity the multi-layered model is constructed so that each layer reflects the network resilience required level of details.

The invention discloses an unmanned plane target tracking method based on a hierarchical model, and belongs to the field of unmanned plane remote sensing image processing. The unmanned plane target tracking method based on a hierarchical model includes the following steps: 1) establishing characteristic expression of an initial frame target; 2) establishing a coarse tracking model taking mean value drifting as the basis; and 3) establishing a precise tracking model taking improved particle swarm optimization as the basis. The unmanned plane target tracking method based on a hierarchical model effectively overcomes the problem that the imaging particularity of an unmanned plane causes high difficulty and low accuracy in video tracking, and the video tracking is easy to lose by introducing hierarchical model combined with mean value drifting and improved particle swarm optimization, and effectively improves the accuracy of target tracking.

A method is disclosed herein that includes an act of causing a processor to access a deep-structured, layered or hierarchical model, called deep convex network, retained in a computer-readable medium, wherein the deep-structured model comprises a plurality of layers with weights assigned thereto. This layered model can produce the output serving as the scores to combine with transition probabilities between states in a hidden Markov model and language model scores to form a full speech recognizer. The method makes joint use of nonlinear random projections and RBM weights, and it stacks a lower module's output with the raw data to establish its immediately higher module. Batch-based, convex optimization is performed to learn a portion of the deep convex network's weights, rendering it appropriate for parallel computation to accomplish the training. The method can further include the act of jointly substantially optimizing the weights, the transition probabilities, and the language model scores of the deep-structured model using the optimization criterion based on a sequence rather than a set of unrelated frames.

A three-dimensional printer with a coloring function is provided. The three-dimensional printer includes a data unit, a three-dimensional object constructing unit, a coloring unit, and a controlling unit. The data unit has plural layered model data that are divided from a three-dimensional model data and has a color data corresponding to the three-dimensional model data. The three-dimensional object constructing unit includes a material nozzle. The coloring unit includes a lateral surface coloring nozzle. Under control of the controlling unit, plural construction materials are outputted downwardly through the material nozzle according to the plural layered model data sequentially, so that plural layered models are generated and stacked as a three-dimensional model. Moreover, under control of the controlling unit, plural inks are outputted through the lateral surface coloring nozzle according to the color data in order to color plural lateral surfaces of the three-dimensional model.

Various technologies for removing shoulder-bed effects from measurements of an earth formation made in a wellbore. In one implementation, a methodology for removing the shoulder-bed effects includes receiving the measurements and constructing a layered model of the earth formation. Each layer has a set of parameters corresponding to one or more types of the received measurements ascribed to each layer such that the set of parameters define a parameter space for the layered model. The methodology may further include dividing the parameter space into subspaces based on relationships among the parameters, selecting from the subspaces one or more starting points, minimizing a cost function using the one or more starting points to generate one or more candidate solutions having the shoulder-bed effects removed and selecting a final solution from the one or more candidate solutions.

The invention provides a target tracking method based on depth feature and average peak correlation energy. The method comprises the following steps: extracting color histogram feature of the target,depth feature and three-layer depth feature of upper, lower, left and right image blocks of the target, and calculating a color histogram discrimination model and a depth feature model; calculating the color histogram characteristic response and the depth characteristic response of the target of the current frame, and predicting the target position of the next frame; calculating an average peak correlation energy of the target response of the current frame; if the average peak correlation energy of the current frame target response is greater than the average peak correlation energy of all frames before the current frame, determining that the confidence level of the frame response is high, and updating the color histogram discriminant model and the depth feature model by using a layered model update scheme, otherwise, the color histogram discriminant model and the depth feature model being not updated; repeating the above steps until the video sequence ends. The invention effectively fuses the depth feature and the average peak correlation energy, and adopts a layered model updating scheme to further effectively improve the tracking performance.

Various embodiments of the present disclosure are directed to model feature classification, analysis, and updating for analyzing one or more risk determination model(s). Embodiments include an improved apparatus configured to generate an actionable feature data object subset of a risk model feature set for a risk determination model, for example using an actionable determination model. The apparatus may provide the actionable feature data object subset for rendering to an interface of a client device. The apparatus may additionally or alternatively be configured to utilize user feedback, provided either directly or identified by the apparatus based on user interactions, to update the actionable determination model. The apparatus may additionally or alternatively be configured to maintain and utilize linked claim data object(s) for use in rendering a linked claim scores analysis interface that provides additional insight regarding the risk level of a particular entity.

The invention discloses a method used for establishing underground medium models through physical geography calculation. On the basis of the hypothesis of underground medium layered models, with bottom boundaries of all stratums being bottoms and the surface layer being the top, a multi-layer combined model with coincidence regions is established, each layer of the model can be dissected freely through a vertical polygonal prism to establish a space model, and through performing attribute simulation on physical properties of the multi-layer model, real layered stratum properties are established. Through the method, underground layered media can be sufficiently and fine described, and the calculation efficiency of the physical geography effect is improved. The method can be used for the application field of forward-inversion calculation of physical geography gravity and magnetic prospecting and others.

The invention discloses a method for reducing grounding resistance in manner of digging a grounding deep well in a transformer station, comprising steps of calculating a station address soil layered model, calculating target parameters like a power frequency grounding resistance safety value of a horizontal grounding grid and safety values of a contact potential difference and a step potential difference, obtaining a power frequency grounding resistance calculation value of a horizontal grounding grid and calculation values of the contact potential difference and the step potential difference, determining the amount, the positions, the well depth, the perpendicular grounding electrode materials and equivalent radiuses of the grounding deep wells, regulating the parameters of the grounding deep well, providing a horizontal grounding grid material table, a perpendicular grounding body material table, rise of earth potential, the power frequency grounding resistance, the calculation values and the safety values of the contact potential difference and the step potential difference of the grounding grid of the station. The invention can dramatically reduce the grounding resistance of the transformer station, enables the contact potential difference and the step potential difference to be reduced to below the safety value, and enables the design of the high soil resistivity and transformer station grounding system having the ground water layer to be simple, accurate and effective.