we usewe use ml shear wave velocity to derive a high resolution 2d ml shear wave velocity map for the iranian plateau. the ml amplitudes and arrival times are routinely measured for the calculation of local magnitude. ml shear wave velocity is very sensitive to the lateral change of crustal thickness and switches between the velocity of lg and sn waves. an lg wave will die out as soon as encoun...

The Maximum Likelihood Probabilistic Data Association (ML-PDA) tracker and the Maximum Likelihood Probabilistic Multi-Hypothesis (ML-PMHT) tracker were applied to five synthetic multistatic active sonar scenarios featuring multiple targets, multiple sources, and multiple receivers. For each of the scenarios, Monte Carlo testing was performed to quantify the performance differences between the t...

In this contribution will we conceptually derive two symbolchannel estimators, the joint-ML and the ML, both having exponential complexity. Pragmatically we derive three approximations with polynomial complexity, one to the joint-ML: the pseudo-joint-ML; two to the ML: the naive-ML and the linear-response-ML. We asses the resulting average bit error rates empirically. Performance gains of sever...

As the largest service industry in the world, tourism plays a special role in sustainable development. Geomorphic tourism is known to be a segment of this industry with lower environmental impact and underlying causes that explain lower demand; therefore, it is essential to study, identify, assess, plan, and manage natural tourist attractions. As such, the present study assesses the ability of ...

The ML type system was originally introduced as a means of identifying a class of terms in a simple untyped language, often referred to as core-ML, whose evaluation could be guaranteed not to “go wrong”. In subsequent work, the terms of core-ML have also been viewed as a ‘convenient shorthand’ for programs in typed languages. Notable examples include studies of ML polymorphism and investigation...

We describe the methodology and current features for ML2000, a new-generation design of ML. ML2000 adds a number of features to Standard ML and Caml, providing better support for extensibility and code reuse, while also fixing latent problems. Although none of the features is particularly novel on its own, the combination of features and design methodology are.

We describe the methodology and current features for ML2000, a new-generation design of ML. ML2000 adds a number of features to Standard ML and Caml, providing better support for extensibility and code reuse, while also fixing latent problems. Although none of the features is particularly novel on its own, the combination of features and design methodology are.