1034 results about "Execution model" patented technology

A shared object memory system that includes a shared object memory for storing encapsulated software objects that are directly accessible by plural object application processes. The shared object memory is distinct from the process memories of the object application processes and does not include an execution model. A shared object memory manager provides management of objects within the shared object memory.

A model for determining the type of soil, the water content of a soil, and the soil properties, and a soil measurement data storage portion (60) to store therein measurement data necessary to carry out the model and correlated with specific measurement conditions are provided. The water content is measured by a water content measuring portion (57) on the basis of the measurement data fed from a soil sensor (S). The type of soil is determined by a feature extracting portion (56) and a type-of-soil determining portion (58), and the determined type of soil is sent to a determining portion (59). The determining portion (59) determines corresponding conditions and a model according to the type of soil and water content of the measured place received and sets them in a predetermined processing portion. The soil sensor feeds measurement data meeting the measurement conditions to a measurement information processing portion (55), and the processing portion (55) determines the soil properties according to the determined model.

Methods, mediums and systems are provided to enable a user to program the behaviors of a Unified Modeling Language (UML) model in a graphical programming or modeling environment, such as block diagram programming environment. The UML model is exported into a text-based format, which is subsequently imported into the graphical programming or modeling environment. The graphical programming or modeling environment represents the UML model using functional blocks so that the user can program the behaviors of the UML model. The graphical programming or modeling environment also enables the user to simulate or execute the UML model to determine the behaviors of the UML model

Systems and methods for providing convolutional neural network based image synthesis using localized loss functions is disclosed. A first image including desired content and a second image including a desired style are received. The images are analyzed to determine a local loss function. The first and second images are merged using the local loss function to generate an image that includes the desired content presented in the desired style. Similar processes can also be utilized to generate image hybrids and to perform on-model texture synthesis. In a number of embodiments, Condensed Feature Extraction Networks are also generated using a convolutional neural network previously trained to perform image classification, where the Condensed Feature Extraction Networks approximates intermediate neural activations of the convolutional neural network utilized during training.

An optimization method and apparatus for converting source code for a program written in a programming language into machine language and for optimizing the program includes employing a basic block as a unit to estimate an execution time for the program to be processed, generating a nested tree that represents the connections of the basic blocks using a nesting structure, when a conditional branch is accompanied by a node in the nested tree, employing the execution time estimated by using the basic blocks as units to obtain an execution time at the node of the program when a conditional branching portion of a program is directly executed and when the conditional branching portion is executed in parallel, and defining the node as a parallel execution area group when the execution time required for the parallel execution is shorter or dividing multiple child nodes of the nodes into multiple parallel execution areas when the execution time for the conditional branching portion is shorter.

Digital predistortion system, methods and circuitry for adapting a predistortion system linearizing a non-linear element. The system is a multiply partitioned architecture that addresses long or “memory” effects, and separately addresses shorter duration effects. In a preferred method, the non-linear element is first modeled in software as a nonlinearity and a linearity in cascade form, preferably a Wiener model. The model is validated and adapted to minimize an observed error between the model and the non-linear element. The software model of the non-linear element is then used first to model a predistortion block that addresses short duration effects, and second to separately model a predistortion block that addresses longer duration effects. The models are software executable by an external processor in real time. Periodically the models are executed and used to update the adaptive parameters of the predistortion system without interrupting the system operation.

A chipset is initialized in a secure environment for an isolated execution mode by an initialization storage. The secure environment has a plurality of executive entities and is associated with an isolated memory area accessible by at least one processor. The at least one processor has a plurality of threads and operates in one of a normal execution mode and the isolated execution mode. The executive entities include a processor executive (PE) handler. PE handler data corresponding to the PE handler are stored in a PE handler storage. The PE handler data include a PE handler image to be loaded into the isolated memory area after the chipset is initialized. The loaded PE handler image corresponds to the PE handler.

A translation method and system include a recognition engine having a plurality of models each being employed to decode a same utterance to provide an output. A model combiner is configured to assign probabilities to each model output and configured to assign weights to the outputs of the plurality of models based on the probabilities to provide a best performing model for the context of the utterance.

A GPGPU-compatible architecture combines a coarse-grain reconfigurable fabric (CGRF) with a dynamic dataflow execution model to accelerate execution throughput of massively thread-parallel code. The CGRF distributes computation across a fabric of functional units. The compute operations are statically mapped to functional units, and an interconnect is configured to transfer values between functional units.

Data flow graph representation is combined with message passing and delegation, a stackless execution model, and a real-time compiler technology, to provide an improved software development and distribution paradigm. Polymorphic objects represent nodes that can be reconfigured, replaced, and / or modified as needed. Complex functionality is achieved by passing messages among nodes. Authored content is published by replacing interactive nodes with fixed-value nodes as desired. Software representations can be translated among various isomorphic formats, including data flow graphs and scripts, without loss of information or modifiability.

Methods and apparatus for improving printability of a three-dimensional model are disclosed. For a computer-based three-dimensional model to be generated by a three-dimensional printing system, a three-dimensional printability analysis of the model is performed. The three-dimensional printability analysis applies one or more test cases representing forces that may be applied to the model. The three-dimensional printability analysis generates one or more points at which stresses associated with the test case exceed the structural tolerances of a material to be used by the three-dimensional printing system for a fabrication of the model. For each point of the one or more points, one or more corrections to the model designed to decrease the stresses associated with a respective test case are calculated. For each test case, the corrections are evaluated. The evaluating includes selecting a preferred correction based on one or more criteria.

A multithreaded computer system of the present invention includes a plurality of processor elements (PEs) 101 to 103, and a parallel processor control unit 200, which switches threads in each PE, and the parallel processor control unit 200 includes: a plurality of execution order registers, which hold, for each processor element, an execution order of threads to be executed; a plurality of counters 230, which count an execution time for a thread that is being executed by each processor element and generate a timeout signal when the counted time reaches a limit assigned to the thread; and a thread execution scheduler unit 210, which switches the thread that is being executed to the thread to be executed by each processor element based on the execution order held in said execution order register and the timeout signal.

A dataflow instruction set architecture and execution model, referred to as WaveScalar, which is designed for scalable, low-complexity / high-performance processors, while efficiently providing traditional memory semantics through a mechanism called wave-ordered memory. Wave-ordered memory enables “real-world” programs, written in any language, to be run on the WaveScalar architecture, as well as any out-of-order execution unit. Because it is software-controlled, wave-ordered memory can be disabled to obtain greater parallelism. Wavescalar also includes a software-controlled tag management system.

An adaptive multivariable process control system includes a multivariable process controller, such as a model predictive controller, having a multivariable process model characterized as a set of two or more single-input, single-output (SISO) models and an adaptation system which adapts the multivariable process model. The adaptation system detects changes in process inputs sufficient to start an adaptation cycle and, when such changes are detected, collects process input and output data needed to perform model adaptation. The adaptation system next determines a subset of the SISO models within the multivariable process model which are to be adapted, based on, for example, a determination of which process inputs are most correlated with the error between the actual (measured) process output and the process output developed by the multivariable process model. The adaptation system then performs standard or known model switching and parameter interpolation techniques to adapt each of the selected SISO models. After the adaptation of one or more of the SISO models, the resulting multivariable process model is validated by determining if the adapted multivariable process model has lower modeling error than the current multivariable process model. If so, the adapted multivariable process model is used in the multivariable controller.

Devices and methods for modeling and analysis of services provided over a common network include a processor configured to track services connected to the common network through nodes and links; run service models associated with the services under selected conditions, the selected conditions including failure and repair of one of the nodes or links; and propose corrective action and / or change of network resources of the common network to minimize impact of the failure. The processor may also run Network model(s). The models may be executed successively or simultaneously, and outputs of one model may be used as input to other models, including any necessary conversions for compatibility.

The invention discloses a restaurant service robot system, which comprises a control module, a travel module, an interaction module, a perception module, and an execution module, wherein the control module is in communication connection with the travel module, the interaction module, the perception module and the execution module respectively; the control module is used for analyzing and processing received information, perception information and information produced by the system, and controlling the execution module; the travel module is used for a robot body to move; the interaction module is used for providing an interaction platform; the perception module is used for perceiving external things; and the execution module is used for executing the operation according to a control instruction. The robot system adopts a mode that the execution module executes the operation according to the control instruction which is sent after the control module analyzes and processes the received information, the perception information and the information produced by the system, so the robot system can well finish the repeated, heavy and tedious work of catering industry, and achieve the aims of automation, intelligentization, employee reduction and convenient management of restaurant service.

A method for executing single-key multi-pattern includes setting a specific application pattern key on portable digital data processing device, ejecting out and item selection after said key is pressed for providing specific application pattern being able to be executing then enabling user to use only single application pattern key to execute multiple application pattern.

A static code analysis (SCA) tool, apparatus and method detects, prioritizes and fixes security defects and compliance violations in SAP® ABAP™ code. The code, meta information and computer system configuration settings are transformed into an interchangeable format, and parsed into an execution model. A rules engine is applied to the execution model to identify security and compliance violations. The rules engine may include information about critical database tables and critical SAP standard functions, and the step of applying the rules engine to the execution model may include the calculation of specific business risks or whether a technical defect has a business-relevant impact. In particular, an asset flow analysis may be used to determine whether critical business data is no longer protected by the computer system. Such critical business data may include credit or debit card numbers, financial data or personal data.

A system and method are provided which dynamically adapts to a changing economic environment by selecting or synthesizing an economic model from a set of economic models based on the selected model's ability to make accurate predictions about an actual economic market. The method and system each forms a space of different economic models, forms a behavioral landscape by extracting observables from executions of the economic models, and performs model selection and composite model synthesis through optimization over the behavioral landscape.

The invention discloses a scheduling system and a scheduling execution method of a multi-core heterogeneous system on chip. The scheduling system comprises a user service module which provides tasks needed to be executed and is suitable for a plurality of heterogeneous software and hardware, and a plurality of computing service modules for executing a plurality of tasks on a multi-core computing platform on chip; the scheduling system is characterized in that a core scheduling module is arranged between the user service module and the computing service modules, and the core scheduling module is used for accepting a task request of the user service module, recording and judging a data dependence relation among different tasks to schedule the task request to different computing service modules for execution in parallel; the computing service modules are packaged as IP (Internet Protocol) cores, and realize dynamic loading of the IP cores via a reconfigurable controller; and the computing service modules are in on chip interconnections with a plurality of computing processors of the multi-core heterogeneous system on chip, and accept instructions of the core scheduling module to execute different types of computing tasks. The scheduling system improves the platform throughput rate and the system performance by monitoring the relativity of the tasks and executing automatic parallelization in the running process.

A combine harvester (combine) includes any number of components to harvest plants as the combine travels through a plant field. The components take actions to harvest plants or facilitate harvesting plants. The combine includes any number of sensors to measure the state of the combine as the combine harvests plants. The combine includes a control system to generate actions for the components to harvest plants in the field. The control system includes an agent executing a model that functions to improve the performance of the combine harvesting plants. Performance improvement can be measured by the sensors of the combine. The model is an artificial neural network that receives measurements as inputs and generates actions that improve performance as outputs. The artificial neural network is trained using actor-critic reinforcement learning techniques.

A server, a system and a method for automatic virtual metrology (AVM) are disclosed. The AVM system comprises a model-creation server and a plurality of AVM servers. The model-creation server is used to construct the first set of virtual metrology (VM) models (of a certain equipment type) including a VM conjecture model, a RI (Reliance Index) model, a GSI (Global Similarity Index) model, a DQIx (Process Data Quality Index) model, and a DQIy (Metrology Data Quality Index) model. In the AVM method, the model-creation server also can fan out or port the first set of VM models generated to other AVM servers of the same process apparatus (equipment) type, and each individual fan-out-acceptor's AVM server can perform automatic model refreshing processes so as to gain and maintain its VM models' accuracy.

A method is disclosed for providing interoperation of a first execution image of a first version and a second execution image of a second version. A compatibility matrix specifies whether the versions are compatible, base-level compatible, or incompatible. In one embodiment, the compatibility matrix may comprise a sparse table that stores a compatibility indicator for all permutations of a plurality of versions of a network operating system. As part of initialization of a system that includes the first execution image and second execution image, version information for the execution images is determined. An entry in the compatibility matrix corresponding to the versions is identified. The execution images are operated in a fully synchronized state when the identified entry of the compatibility matrix specifies that the versions are either compatible or base-level compatible. Individual components of the execution images interoperate according to the results of individual session negotiations. If the versions are incompatible, an alternative redundancy operation mode may be used. Embodiments provide for negotiation of compatible message versions and capabilities among peer components or clients of the execution images as source information to generate the compatibility matrix.

In a processor, instructions of an instruction stream are supplied to an execution unit which executes the supplied instructions according to respective execution modes. A control unit recognizes a user-defined instruction sequence (UDIS) in the instruction stream. The UDIS is associated with a UDIS definition provided in-line and / or as contents of machine-state registers (MSRs), and specifying, at least in part, a start, optionally an end, and a particular execution mode for the UDIS. Subsequently, ones of the instructions of the UDIS are executed in accordance with the particular execution mode, such as by optionally altering recognition of asynchronous events. For example, disabling hardware interrupts during the executing results in apparent atomic execution. Fetching, decoding, issuing, and / or caching of the instructions of the UDIS are optionally dependent on the particular execution mode. MSRs optionally specify a maximum length and / or execution time.

In an active noise reduction apparatus with an adaptive notch filter used, a triangle wave as a reference signal input into a first coefficient updater and a second coefficient updater reduces the number of execution times of product-sum operations in a reference signal generator to reduce the operation load.

A biological modeling system and method for enhanced computer-aided analysis of biological response data provides information synthesized from multiple sources. An executable model of a biological system is developed from information and structures based on multiple sources. In a preferred embodiment, biological data sets are selected by a user from a first active viewer window on a user computer display. A model is created and then run using integrated pharmacokinetic software. The output is next analyzed using integrated analysis tools. Once analyzed, the model is balanced to ensure that it matches the information and structures. Once the model is created, run, and balanced, it can be used to draw attention to important relations through integrated reporting functions. This program could be run with such programs as NONMEM®.

A server, a system and a method for automatic virtual metrology (AVM) are disclosed. The AVM system comprises a model-creation server and a plurality of AVM servers. The model-creation server is used to construct the first set of virtual metrology (VM) models (of a certain equipment type) including a VM conjecture model, a RI (Reliance Index) model, a GSI (Global Similarity Index) model, a DQIx (Process Data Quality Index) model, and a DQIy (Metrology Data Quality Index) model. In the AVM method, the model-creation server also can fan out or port the first set of VM models generated to other AVM servers of the same process apparatus (equipment) type, and each individual fan-out-acceptor's AVM server can perform automatic model refreshing processes so as to gain and maintain its VM models' accuracy.