The report focuses on the types of models used for TMDLs, the key assumptions underlying the models, how models are selected for specific surface waters and impairments, the data required to apply the models to a specific surface water and impairment, and how the predictive capability of the models is assessed.
This guide provides guidance of large scale Artificial Intelligence (AI) models in financial risk management. For the application of such models, the guide provides applicable scenarios, basic conditions, model creation, iterations, and suggested capabilities. The guide is specifically aimed at providing help to financial organizations by giving directions on planning, building, deploying, and maintaining these AI models, with respect to algorithms, in financial lending scenarios.
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.
IEEE Std 2846-2022 defines, for a set of initial scenarios, a minimum set of assumptions to be considered by safety-related models to represent the reasonably foreseeable behavior of other road users (ORUs). This recommended practice provides guidelines for using these assumptions in safety-related models during development, testing, and deployment of Automated Driving Systems (ADS). Specifically, it covers: (i) Approaches to identify values for the applicable IEEE Std 2846-2022 assumptions… read more given the scenario context, such as scenario type, roadway information, and safety-relevant objects. (ii) Approaches for identifying reasonably foreseeable values for the assumptions given the scenario context (from (i) above) and for updating the assumptions across the temporal evolution of a scenario; and (iii) Approaches to validate the selection of assumptions in (ii) through an analysis of the output of the safety-related model, considering different kinds of performance targets of interest. Compliance with this recommended practice does not guarantee the safety of the overall system. read less
This standard specifies the assessment methods to evaluate compliance of stationary and dynamic wireless power transfer systems with electromagnetic human exposure guidelines (external electric and magnetic fields, internal specific absorption rate (SAR), induced electric fields or current density including contact currents). The frequency range of this document is from 1 kHz to 30 MHz.
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