In this paper we propose a first empirical mapping between the RST-DT and the PDTB 3.0. We provide an original algorithm which allows the mapping of 6,510 (80.0%) explicit and implicit discourse relations between the ...
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To analyze the physiological information within the acquired EEG signal is very cumbersome due to the possibility of several factors, viz. noise and artifacts, complexity of brain dynamics, and inter-subject variabili...
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Deep learning has become an important computational paradigm in our daily lives with a wide range of applications,from authentication using facial recognition to autonomous driving in smart vehicles. The quality of th...
Deep learning has become an important computational paradigm in our daily lives with a wide range of applications,from authentication using facial recognition to autonomous driving in smart vehicles. The quality of the deep learning models, i.e., neural architectures with parameters trained over a dataset, is crucial to our daily living and economy.
Tropical cyclones, characterized by strong winds and heavy rainfall, threaten human life in coastal regions crucial to the economy, including fisheries, agriculture, tourism, and infrastructure. Their frequent occurre...
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A neuron with binary inputs and a binary output represents a Boolean function. Our goal is to extract this Boolean function into a tractable representation that will facilitate the explanation and formal verification ...
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People with hearing loss or hard hearing struggle with daily life activities as sign language is not widely known by the public. There are many attempts to use technology to help assist hearing loss individuals. Howev...
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Aortic valve calcium scoring is extensively utilized for diagnosing, treating, monitoring, and assessing the risk of aortic stenosis and coronary artery disease. The gold standard method for determining aortic valve c...
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To determine the individual circumstances that account for a road traffic accident,it is crucial to consider the unplanned connections amongst various factors related to a crash that results in high casualty *** of th...
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To determine the individual circumstances that account for a road traffic accident,it is crucial to consider the unplanned connections amongst various factors related to a crash that results in high casualty *** of the road accident data concentrated mainly on categorizing accidents into different types using individually built classification methods which limit the prediction accuracy and fitness of the *** this article,we proposed a multi-model hybrid framework of the weighted majority voting(WMV)scheme with parallel structure,which is designed by integrating individually implemented multinomial logistic regression(MLR)and multilayer perceptron(MLP)classifiers using three different accident datasets i.e.,IRTAD,NCDB,and *** proposed WMV hybrid scheme overtook individual classifiers in terms of modern evaluation measures like ROC,RMSE,Kappa rate,classification accuracy,and performs better than state-of-theart approaches for the prediction of casualty severity ***,the proposed WMV hybrid scheme adds up to accident severity analysis through knowledge representation by revealing the role of different accident-related factors which expand the risk of casualty in a road *** aspects related to casualty severity recognized by the proposed WMV hybrid approach can surely support the traffic enforcement agencies to develop better road safety plans and ultimately save lives.
This study discusses the development of a web application aimed at facilitating Sinhala document creation, with a specific emphasis on Sinhala voice-to-text conversion and the handling of Sinhala commands through voca...
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ISBN:
(纸本)9798350319200
This study discusses the development of a web application aimed at facilitating Sinhala document creation, with a specific emphasis on Sinhala voice-to-text conversion and the handling of Sinhala commands through vocal input. Leveraging machine learning techniques, including convolutional neural networks and Natural Language Processing, the application's core features were established. Extensive research was conducted to tailor the application's content to the needs of its primary users, ensuring maximum effectiveness. The user-friendly interfaces of the web application are designed for clarity, simplicity, and consistency. The primary objective of this research is to comprehensively analyze the implementation of Sinhala voice-to-text conversion and Sinhala command handling systems. These systems are primarily designed to benefit diverse users, including journalists, content writers, and differently abled individuals with verbal abilities, by enhancing the efficiency of creating Sinhala documents. Through a detailed exploration of the research methodology, this study offers insight into the development process of the web-based system. The outcomes of the linguistic model training, presented within the study, reveal achievements and advancements that address the limitations inherent in existing solutions. Key findings from this research demonstrate the successful functionality of the Sinhala voice-to-text converter and the efficacy of the Sinhala command handler. The voice-to-text conversion system achieved an impressive accuracy rate of over 80%, while the Sinhala command handler exhibited an accuracy of approximately 80%. Moreover, this research envisions potential applications that extend beyond document creation. The technology showcased in the web application holds promise for broader language-based applications, impacting education, accessibility, and communication across the native Sinhala-speaking community in Sri Lanka. In summary, this research showcases th
This comprehensive review starts with diving into the progress and real-world applications of combining multi-omics data analysis with machine learning techniques in cancer research. Multi-omics involves examining var...
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