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Development of a standard simulation and related tool interface for component models written in VHDL, Verilog, C and other description languages.

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This guide provides guidance of using large-scale Artificial Intelligence (AI) models for financial risk management. For the application of such models, the guide provides capabilities of applicable scenarios, model design, development, deployment, and iterations. Specifically designed to assist financial institutions, the guide provides detailed directions on planning, constructing, deploying, and maintaining these AI models, with respect to algorithms, in financial lending scenarios.

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This standard applies to road vehicles. For a set of scenarios, a minimum set of assumptions regarding reasonably foreseeable behaviors of other road users are defined that shall be considered in the development of safety-related models for automated driving systems (ADS). This standard further defines a list of attributes common to contributed safety-related models and methods to help verify whether a safety-related model takes the minimum set of assumptions into consideration. An informative… read more annex instantiates several examples of how the proposed minimum set of assumptions could be employed in ADS development. Sources of uncertainty, such as prediction or perception errors, are out of scope to this standard. This standard does not guarantee the safety of the overall system in all scenarios. read less

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This document provides mathematical models for computer simulation studies of excitation systems and their associated controls for three-phase synchronous generators. The equipment modeled includes the automatic voltage regulator (AVR) as well as supplementary controls including reactive current compensation, power system stabilizers, overexcitation and underexcitation limiters, and stator current limiters. This revision is an update of the recommended practice and includes models of new… read more devices which have become available since the previous revision, as well as updates to some existing models. read less

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This standard describes the minimum set of reasonable assumptions used in foreseeable scenarios to be considered for road vehicles in the development of safety-related models that are part of automated driving systems (ADS). The standard includes consideration of rules of the road and their regional and/or temporal dependencies. This standard is not necessarily exhaustive to guarantee the safety of the ADS. In accordance with the IEEE SA Operations Manual Patent (6.3) and Structure (6.4)… read more Sections, the Informative portion of the standard identifies attributes of suitable models including best practices for balancing ADS assumptions with rules of the road used in the context of the Dynamic Driving Task. The Informative portion also identifies methods that may be used to verify whether an implementation conforms to the minimum set of required reasonable assumptions used in foreseeable scenarios, and defines an example model conformant with the standard. Out of scope are the algorithms or technologies in an ADS that the assumptions and attributes defined in this standard impact. read less

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This standard defines technical capability requirements for multimodal large language models in smart home applications.

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This standard specifies the general requirements and framework of data and model sharing across multiple computing centers, including the requirements on functional architecture, interfaces, security, and performance. The target applications and services include Artificial Intelligence Generated Content (AIGC), Large Language Model (LLM), and big data analytics.

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This standard provides: 1) a framework and functional requirements for energy market corpus construction; 2) a specification for the collection of data for the training of large language models for the energy market; 3) corpus structuring methodologies and safety requirements for energy market applications; 4) corpus quality validation and assessment methods for energy market large language models; and 5) corpora management tool construction methodologies.

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