In this paper, we propose a novel reordering model based on sequence labeling techniques. Our model converts the reordering problem into a sequence labeling problem, i.e. a tagging task. Results on five Chinese-Englis...
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In this paper we address the problem of solving substitution ciphers using a beam search approach. We present a conceptually consistent and easy to implement method that improves the current state of the art for decip...
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We present a novel approach for translation model (TM) adaptation using phrase training. The proposed adaptation procedure is initialized with a standard general-domain TM, which is then used to perform phrase trainin...
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We present a novel approach for translation model (TM) adaptation using phrase training. The proposed adaptation procedure is initialized with a standard general-domain TM, which is then used to perform phrase trainin...
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In this paper we show that even for the case of 1:1 substitution ciphers-which encipher plaintext symbols by exchanging them with a unique substitute-finding the optimal decipherment with respect to a bigram language ...
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Automatic sign language recognition (ASLR) is a special case of automatic speech recognition (ASR) and computer vision (CV) and is currently evolving from using artificial labgenerated data to using 'real-life'...
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We present the first ever results showing that tuning a machine translation system against a semantic frame based objective function, MEANT, produces more robustly adequate translations than tuning against BLEU or TER...
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The linguistically transparent MEANT and UMEANT metrics are tunable, simple yet highly effective, fully automatic approximation to the human HMEANT MT evaluation metric which measures semantic frame similarity between...
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Internet of Things based health care systems play a significant role in Information and Communication Technologies and has contribution in development of medical information systems. The developing of IoT-based health...
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Internet of Things based health care systems play a significant role in Information and Communication Technologies and has contribution in development of medical information systems. The developing of IoT-based health care systems must ensure and increase the safety of patients, the quality of life and other health care activities. The tracking, tracing and monitoring of patients and health care actors activities are challenging research directions. In this paper we propose a general architecture of a health care system for monitoring of patients at risk in smart Intensive Care Units. The system advices and alerts in real time the doctors/medical assistants about the changing of vital parameters or the movement of the patients and also about important changes in environmental parameters, in order to take preventive measures.
In this study, brain, and gait dynamic information were combined and used for diagnosis and monitoring of Parkinson's disease (the most important Neurodegenerative Disorder). Analysis of the information correspond...
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In this study, brain, and gait dynamic information were combined and used for diagnosis and monitoring of Parkinson's disease (the most important Neurodegenerative Disorder). Analysis of the information corresponding to a prescribed movement involving tremor, and the related changes in brain connectivity is novel and original. Analytically, developing a space-time nonlinear adaptive system which fuses brain and gait information algorithmically is proposed here for the first time. The overall dynamic system will be constrained by the clinical impressions of the patient symptoms embedded in a knowledge-based system. The entire complex constrained problem were solved to enable a powerful model for recognition and monitoring of Parkinson's disease and establishing appropriate rules for its clinical following up.
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