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This is the full ChatGPT transcript for the IEEE Power Engineering Letter "On the Potential of ChatGPT to Generate Distribution Systems for Load Flow Studies using OpenDSS". The abstract for the letter is as follows:

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812 Views

This document provides the data for the case studies of the work “Computational Performance Enhancement Strategies for Risk-Averse Two-Stage Stochastic Generation and Transmission Network Expansion Planning”.

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166 Views

In practical media distribution systems, visual content usually undergoes multiple stages of quality degradation along the delivery chain, but the pristine source content is rarely available at most quality monitoring points along the chain to serve as a reference for quality assessment. As a result, full-reference (FR) and reduced-reference (RR) image quality assessment (IQA) methods are generally infeasible. Although no-reference (NR) methods are readily applicable, their performance is often not reliable.

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239 Views

In practical media distribution systems, visual content usually undergoes multiple stages of quality degradation along the delivery chain, but the pristine source content is rarely available at most quality monitoring points along the chain to serve as a reference for quality assessment. As a result, full-reference (FR) and reduced-reference (RR) image quality assessment (IQA) methods are generally infeasible. Although no-reference (NR) methods are readily applicable, their performance is often not reliable.

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245 Views

Abstract— Objective: Recently, pupil oscillation synchronized with a steady visual stimulus was employed for an input of an interface. The system is inspired by steady-state visual evoked potential (SSVEP) BCIs, but it eliminates the need for contact with the participant because it does not need electrodes to measure electroencephalography. However, the stimulation frequency is restricted to being below 2.5 Hz because of the mechanics of pupillary vibration and information transfer rate (ITR) is lower than SSVEP BCIs.

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237 Views

This dataset consists of a bill of materials (.PDF) for the equipment and materials used in the fabrication of the M-BLUE hardware, and SolidWorks CAD models (.SLDPRT, .SLDASM) of the custom sheet metal components and 3D-printed spacer used in the M-BLUE assembly. Please download and unzip "MBLUEdataset.zip" to access the files referenced above.

Supplementary material for the article:

C. Nesler, G. Thomas, N. Divekar, E. Rouse, and R. Gregg, "Enhancing Voluntary Motion with Modular, Backdrivable, Powered Hip and Knee Orthoses," IEEE Robotics & Automation Letters, 2022.

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821 Views

This dataset consists of a bill of materials (.PDF) for the equipment and materials used in the fabrication of the M-BLUE hardware, and SolidWorks CAD models (.SLDPRT, .SLDASM) of the custom sheet metal components and 3D-printed spacer used in the M-BLUE assembly.

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229 Views

Abstract (for details, see https://osf.io/e4rvz/)

Last Updated On: 
Thu, 01/27/2022 - 18:19
Citation Author(s): 
Ji-Ping Lin

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