We describe a method for training accurate Transformer machine-translation models to run inference using 8-bit integer (INT8) hardware matrix multipliers, as opposed the more costly single-precision floating-point (FP32) hardware. Unlike previous work, which converted only 85 multiplications INT8, leaving 48 out of 133 them in FP32 because unacceptable accuracy loss, we convert all INT8 without...

In this research, we consider an application of the Bayesian Inferences in machine replacement problem. The application is concerned with the time to replace two machines producing a specific product; each machine doing a special operation on the product when there are manufacturing defects because of failures. A common practice for this kind of problem is to fit a single distribution to the co...

This study examines the capability of the Relevance Vector Machine (RVM) and Multivariate Adaptive Regression Spline (MARS) for prediction of ultimate capacity of driven piles and drilled shafts. RVM is a sparse method for training generalized linear models, while MARS technique is basically an adaptive piece-wise regression approach. In this paper, pile capacity prediction models are developed...

Working in monotonous environment often causes lack of concentration or fatigue in an operator and many times such non-vigilance leads to accidents. Therefore early detection of fatigued state has become essential in monotonous working environments like driving vehicle, operating machines etc. Such fatigued state often gets developed gradually and can be identified by certain symptoms. Differen...

Globalization and growth of Internet users truly demands for almost all internet based applications to support local languages. Support of local languages can be given in all internet based applications by means of Machine Transliteration and Machine Translation. This paper provides the thorough survey on machine transliteration models and machine learning approaches used for machine transliter...