Macmesin Product Sheet

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Frequently Asked Questions

• What does mecmesin supply?

  Mecmesin supply an accompanying range of RS232, Digimatic and USB data cables for connection to peripheral devices. Closure Holders To avoid distortion of the closure on gripping, Mecmesin’s closure holders may be custom moulded to suit your specific closure design.

• Who is mecmesin?

  Mecmesin10 testing to perfection brochure ref: 431-038-08 Mecmesin - a world leader in affordable force and torque testing solutions Since 1977, Mecmesin has assisted thousands of companies achieve enhanced quality control in design and production. The Mecmesin brand represents excellence in accuracy, build, service, and value.

• Are mecmesin testing systems and instruments calibrated?

  Mecmesin testing systems and instruments are delivered fully calibrated. Each comes with its own calibration certificate traceable to national standards. Find out more about Mecmesin servicing and calibration.

• What size thread do I need for a mecmesin gauge?

  Your chosen grip can now be fitted to the extension rod which has a 10-32UNF male thread (10-500N), 5/16”UNC (1000-2500N). On the rear of the gauge there are two M5 threaded holes, which can be used for mounting the gauge to a Mecmesin test stand.

• What is a datasheet in the electronics industry?

  In the electronics industry, every component is accompanied by a datasheet describing standard operating characteristics, test results, and recommended usage.

• Where can I find technical data sheets for specific materials?

  Specific materials have technical data in individual sheets such as Ethanol (data page): this includes subjects such as structure and properties, thermodynamic properties, spectral data, vapor pressure, etc. Other chemical data sheets are available from individual producers of chemicals, often on their web pages.

• Is there a standardized process for documenting machine learning datasets?

  The machine learning community currently has no standardized process for documenting datasets, which can lead to severe consequences in high-stakes domains. To address this gap, we propose datasheets for datasets.

• What are the datasets in the appendix?

  The appendix includes a more complete proposal along with prototype datasheets for two well-known datasets: Labeled Faces in the Wild (Huang et al.,2007) and Pang and Lee’s polarity dataset (2004). 2. Context A foundational challenge in the use of machine learning is the risk of deploying systems in unsuitable environments.