1, The full form of MSE is Media Source Extensions

Media Source Extensions (MSE) is a JavaScript API that lets you build streams for playback from segments of audio or video. Although not covered in this article, understanding MSE is needed if you want to embed videos in your site that do things like:

• Adaptive streaming, which is another way of saying adapting to device capabilities and network conditions
• Adaptive splicing, such as ad insertion
• Time shifting
• Control of performance and download size

You can almost think of MSE as a chain. As illustrated in the figure, between the downloaded file and the media elements are several layers.

• An <audio> or <video> element to play the media.
• A MediaSource instance with a SourceBuffer to feed the media element.
• A fetch() or XHR call to retrieve media data in a Response object.
• A call to Response.arrayBuffer() to feed MediaSource.SourceBuffer.

2, The full form of MSE is MSE Group

MSE Group is an international environmental, engineering, and construction firm. Success for our clients, teaming partners, and employees is derived from an intense work ethic and the ability to enjoy the journey.

At MSE Group, LLC, we provide highly qualified and competitive environmental, engineering, health and safety services to public and private entities nationwide. Our newly formed company combines the assets and complementary capabilities of two highly successful firms—Texas-based MS Engineering and Florida-based 3E Consultants, Inc.

3, The full form of MSE is Mean squared error

In statistics, the mean squared error (MSE) or mean squared deviation (MSD) of an estimator (of a procedure for estimating an unobserved quantity) measures the average of the squares of the errors—that is, the average squared difference between the estimated values and the actual value. MSE is a risk function, corresponding to the expected value of the squared error loss. MSE is almost always strictly positive (and not zero) because of randomness or because the estimator does not account for information that could produce a more accurate estimate.

The MSE is a measure of the quality of an estimator. As it is derived from the square of Euclidean distance, it is always a positive value with the error decreasing as the error approaches zero