نتایج جستجو برای: machine components

تعداد نتایج: 639599  

Journal: :CoRR 2014
Sreelekha S Pushpak Bhattacharyya

In this paper we describe some ways to utilize various lexical resources to improve the quality of statistical machine translation system. We have augmented the training corpus with various lexical resources such as IndoWordnet semantic relation set, function words, kridanta pairs and verb phrases etc. Our research on the usage of lexical resources mainly focused on two ways such as augmenting ...

Journal: :Vestnik of Don State Technical University 2019

2007
Adriana Badulescu Munirathnam Srikanth

This document provides a description of the Language Computer Corporation (LCC) SRN System that participated in the SemEval 2007 Semantic Relation between Nominals task. The system combines the outputs of different binary and multi-class classifiers build using machine learning algorithms like Decision Trees, Semantic Scattering, Iterative Semantic Specialization, and Support Vector Machines.

Journal: :علوم و فنون بسته بندی 0
امری مقدسه اکبری احمدرضا سرائیان رحیم یدالهی

continuous improvement in performance is essential for the success of the paperboard industry. strength improvement has always been an important consideration for papermakers. strength increasers are critical components for manufacturing of paperboard. these materials provide not only the required strength quality to paper products but also can improve the machine productivity and process effic...

2017
Guglielmo Fachini Catalin Hritcu Marco Stronati Ana Nora Evans Th'eo Laurent Arthur Azevedo de Amorim Benjamin C. Pierce Andrew Tolmach

We propose a new formal criterion for secure compilation, providing strong security guarantees for components written in unsafe, low-level languages with C-style undefined behavior. Our criterion goes beyond recent proposals, which protect the trace properties of a single component against an adversarial context, to model dynamic compromise in a system of mutually distrustful components. Each c...

2016
Jinsung Yoon Ahmed M. Alaa Scott Hu Mihaela van der Schaar

We develop ForecastICU: a prognostic decision support system that monitors hospitalized patients and prompts alarms for intensive care unit (ICU) admissions. ForecastICU is first trained in an offline stage by constructing a Bayesian belief system that corresponds to its belief about how trajectories of physiological data streams of the patient map to a clinical status. After that, ForecastICU ...

Journal: :Journal of the Japan Society for Precision Engineering 1986

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