Don’t Throw Away RECIST 1.1 Quite Yet

Don't Throw Those Morphological Analyzers Away Just Yet: Neural Morphological Disambiguation for Arabic

This paper presents a model for Arabic morphological disambiguation based on Recurrent Neural Networks (RNN). We train Long Short-Term Memory (LSTM) cells in several configurations and embedding levels to model the various morphological features. Our experiments show that these models outperform state-of-theart systems without explicit use of feature engineering. However, adding learning featur...

Evaluating ‘Throw Away’ Prototyping for Requirements Capture

This paper demonstrates the advantages of extending the scope of prototyping to the requirements capture phase of a project. Prototyping has long been used to elicit users’ responses to ready-formed designs (Boehm, 1988), but only recently has the use of concept demonstrators (Sanderson, 1997) and early throw-away prototypes (Smith et al., 1990) been suggested as a means to capture response to ...

Throw the stethoscope away: a historical essay.

Am I going deaf, or are hearts not as noisy as they used to be? I’ve had my hearing tested, just some high-frequency loss (probably from that Edgar Winter concert). So I think it’s that hearts are more finely tuned than in the past. I can’t remember the last good S4, the one you could palpate. Or the rumble S3 complex or opening snap you called in the medical students to hear. Many of the wonde...

SPoID: Do Not Throw Meaningful Incomplete Sequences Away!

Industrial databases often contain a large amount of unfilled information. During the knowledge discovery process one processing step is often necessary in order to remove these incomplete data either by deleting or assessing them. When the data mining task consists in mining for frequent sequences, incomplete data are, most of the time, deleted, which leads to an important loss of information....

Keysight Technologies Testing 5G: Time to Throw Away the Cables