718 research outputs found
Application of Schmidt Rebound Number for Estimating Coal Strength
In Rock Mechanics, determination of Unconfined Compressive Strength (UCS) of rock is of prime importance as its role in design and analysis of geotechnical problems is crucial. Though laboratory test is the most direct and easy way for estimating the rock compressive strength but UCS determination in the laboratory would be problematic. The laboratory test needs specimen of correct size and features. Obtaining such sample at a time is too difficult. Hence, there is no comprehensive solution to predict the UCS from Schmidt Rebound number. Researchers have developed several equations to make the process easier
Ganoderma applanatum extract mediated synthesis of silver nanoparticles
Nanotechnology has been used in the field of medicine and pharmacology for its greater efficacy of drug delivery than crude molecules of drugs. In the present study medicinal mushroom Ganoderma applanatum extract mediated silver nanoparticles (AgNPs) were synthesized, characterized by Ultraviolet-visible (UV-Vis.) spectroscopy, scanning electron microscopy (SEM), X-ray diffraction, Dynamic light scattering (DLS) and Furior transform-infrared (FTIR) spectroscopy. Maximum absorbance was recorded at 435nm by UV-Vis. The synthesized nanoparticles of 13.54nm-255nm in size with an average particle size of 58.77nm were analyzed by DLS. FTIR-Spectroscopy provided high transmission at 3606cm-1 corresponds for phenolic capping biochemical. Thus G. applanatum extract can be used for synthesis of silver nanoparticles and the synthesized nanoparticles may be used for development of future therapeutic agent for treatment of diseases
Statistically motivated example-based machine translation using translation memory
In this paper we present a novel way of integrating Translation Memory into an Example-based Machine translation System (EBMT) to deal with the issue of low
resources. We have used a dialogue of 380 sentences as the example-base for our system. The translation units in the
Translation Memories are automatically extracted based on the aligned phrases (words) of a statistical machine translation (SMT) system. We attempt to use the approach to improve translation from English to Bangla as many statistical machine translation systems have difficulty
with such small amounts of training data. We have found the approach shows improvement over a baseline SMT system
Mitigating problems in analogy-based EBMT with SMT and vice versa: a case study with named entity transliteration
Five years ago, a number of papers reported an experimental implementation of an Example Based Machine Translation (EBMT) system using proportional analogy. This approach, a type of analogical learning, was attractive because of its simplicity; and the paper reported considerable success with the method using various language pairs. In this paper, we describe our attempt to use this approach for tackling English–Hindi Named Entity (NE) Transliteration. We have implemented our own EBMT system using proportional analogy and have found that the analogy-based system on its own has low precision but a high recall due to the fact that a large number of names are untransliterated with the approach. However, mitigating problems in analogy-based EBMT with SMT and vice-versa have shown considerable improvement over the individual approach
Mitigating the problems of SMT using EBMT
Statistical Machine Translation (SMT) typically has difficulties with less-resourced languages even with homogeneous data. In this thesis we address the application of Example-Based Machine Translation (EBMT) methods to overcome some of these difficulties. We adopt three alternative approaches to tackle these problems focusing
on two poorly-resourced translation tasks (English–Bangla and English–Turkish). First, we adopt a runtime approach to EBMT using proportional analogy. In addition to the translation task, we have tested the EBMT system using proportional analogy for named entity transliteration. In the second attempt, we use a compiled approach to EBMT. Finally, we present a novel way of integrating Translation Memory (TM) into an EBMT system. We discuss the development of these three different EBMT systems and the experiments we have performed. In addition, we present an approach to augment the output quality by strategically combining EBMT systems and SMT systems. The hybrid system shows significant improvement for different language pairs.
Runtime EBMT systems in general have significant time complexity issues especially for large example-base. We explore two methods to address this issue in our system by making the system scalable at runtime for a large example-base (English–French). First, we use a heuristic-based approach. Secondly we use an IR-based indexing technique to speed up the time-consuming matching procedure of the EBMT system. The index-based matching procedure substantially improves run-time speed without affecting translation quality
Building a sign language corpus for use in machine translation
In recent years data-driven methods of machine translation (MT) have overtaken rule-based approaches as the predominant means of automatically translating between languages. A pre-requisite for such an approach is a parallel corpus of the source and target languages. Technological developments in sign language (SL) capturing, analysis and processing tools now mean that SL corpora are
becoming increasingly available. With transcription and language analysis tools being mainly designed and used for linguistic purposes, we describe the process of creating a multimedia parallel corpus specifically for the purposes of English to Irish Sign Language (ISL) MT. As part of our larger project on localisation, our research is focussed on developing assistive technology for patients with limited English in the domain of healthcare. Focussing on the first point of contact a patient has with a GP’s office, the
medical secretary, we sought to develop a corpus from the dialogue between the two parties when scheduling an appointment. Throughout the development process we have created one parallel corpus in six different modalities from this initial dialogue. In this paper we discuss the multi-stage process of the development of this parallel corpus as individual and interdependent entities, both for
our own MT purposes and their usefulness in the wider MT and SL research domains
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