Sentence examples for aimed to handle from inspiring English sources

The phrase "aimed to handle" is correct and usable in written English.
It can be used when describing the intention or purpose of an action or project, particularly in a professional or technical context.
Example: "The new software was aimed to handle customer inquiries more efficiently."
Alternatives: "designed to manage" or "intended to address".

Exact(2)

This paper brings an overall view of the service-oriented architecture (SOA) used in VLab, a system aimed to handle concurrent calculations of geo-materials participating in extensive workflows.

VSQA [12] metric dedicated to view synthesis quality assessment is aimed to handle areas where disparity estimation may fail.

Similar(58)

We will always aim to handle your complaint fairly, courteously and with respect.

1) The Times aims to handle all complaints as efficiently and effectively as possible.

This paradigm aims to handle the uncertainties in the robot model.

Another such tool that is planned to emerge this month is IWantSandy, which aims to handle calendar functions via e-mail.

The proposed scheme, called TCP-BCL, aims to handle various OBS bursty conditions that negatively affect TCP throughput performance and fairness.

The MORSGO aims to handle multi-objective problems with satisfactory convergence and diversity via implementing adaptive root growth operators with a pool of multi-objective search rules and strategies.

Multi-instance learning (MIL) is one of promising paradigms in the supervised learning aiming to handle real world classification problems where a classification target contains several featured sections, e.g., an image typically contains several salient regions.

That wasn't quite right; the president had long hinted that he'd aim to handle deficit issues and immigration reform if re-elected, an agenda reaffirmed with the release of a transcript of an (initially off-the-record) interview with the Des Moines Register.

It aims to handle large data in the output of deep learning by using SR, moreover, to overcome local extrema and gradient diffusion problems in the training process, the overall network weights are fine-tuned to reach the global optimum, which makes the entire depth of the neural network more robust, thereby enhancing the performance of facial emotion recognition.

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