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A long-standing area of material science has been the study of electrostatic and elastic fields in composite material. In high-contrast composites, when two adjacent inclusions are close to touching, ...
A long-standing area of material science has been the study of electrostatic and elastic fields in composite material. In high-contrast composites, when two adjacent inclusions are close to touching, ...
The last decade has witnessed an increasing interest in the study of acoustic/elastic metamaterials and their potential engineering applications. Acoustic/elastic metamaterials are a class of composit...
Columbia Engineering researchers, working with colleagues at Disney Research and MIT, have developed a new method to control sound waves, using a computational approach to inversely design acoustic fi...
Underwater acoustic positioning system solves the problem of how to position and navigate object underwater. Therefore, it can help people to locate the area of disaster to search and succor. But, bec...
Now, researchers at the Georgia Institute of Technology and Oak Ridge National Laboratory (ORNL) have developed a new nondestructive technique for investigating these material changes by examining the...
Recent developments in underwater acoustic communication enable real-time contact with underwater sensors, vehicles, and other instruments, offering novel ocean observational capabilities that may cha...
Remotely Operated underwater Vehicles (ROVs) play an important role in a number of operations conducted in shallow and deep water (e.g.: exploration, survey, intervention, etc.), in several applicatio...
Inordertoconformtopollutant-controlregulationsandminimizeNOxemissions, modernhouseholdboilersandcentralheatingsystemsaremovingtowardpremixed combustors.Thesecombustorshavebeensuccessfulwithregardsto...
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneously segments the speec...
In this paper, we propose a multi-level, contextdependent acoustic modeling framework for automatic speech recognition. For each context-dependent unit considered by the recognizer, we construct a set...
In this paper we propose a back-off discriminative acoustic model for Automatic Speech Recognition (ASR). We use a set of broad phonetic classes to divide the classification problem originating from c...
We address the task of unsupervised topic segmentation of speech data operating over raw acoustic information. In contrast to existing algorithms for topic segmentation of speech, our approach does no...

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