Blockchain (BC) in the Internet of Things (IoT) is a novel technology that acts with decentralized, distributed, public and real-time ledger to store transactions among IoT nodes. A blockchain is a series of blocks, e...
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A prototypical graph problem is centered around a graph-theoretic property for a set of vertices and a solution to it is a set of vertices for which the desired property holds. The task is to decide whether, in the gi...
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Air temperature (AT) prediction can play a significant role in studies related to climate change, radiation and heat flux estimation, and weather forecasting. This study applied and compared the outcomes of three adva...
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To train end-to-end automatic speech recognition models, it requires a large amount of labeled speech data. This goal is challenging for languages with fewer resources. In contrast to the commonly used feature level d...
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ISBN:
(数字)9781728193205
ISBN:
(纸本)9781728193236
To train end-to-end automatic speech recognition models, it requires a large amount of labeled speech data. This goal is challenging for languages with fewer resources. In contrast to the commonly used feature level data augmentation, we propose to expand the training set by using different audio codecs at the data level. The augmentation method consists of using different audio codecs with changed bit rate, sampling rate, and bit depth. The change reassures variation in the input data without drastically affecting the audio quality. Besides, we can ensure that humans still perceive the audio, and any feature extraction is possible later. To demonstrate the general applicability of the proposed augmentation technique, we evaluated it in an end-to-end automatic speech recognition architecture in four languages. After applying the method, on the Amharic, Dutch, Slovenian, and Turkish datasets, we achieved a 1.57 average improvement in the character error rates (CER) without integrating language models. The result is comparable to the baseline result, showing CER improvement of 2.78, 1.25, 1.21, and 1.05 for each language. On the Amharic dataset, we reached a syllable error rate reduction of 6.12 compared to the baseline result.
Billions of IoT devices and smart objects are already in operation today and even more are expected to be on the network over time. These IoT devices will generate enormous amounts of data that cannot be allowed to tr...
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Falls are a major health issue, particularly among the elderly. Increasing fall events require high service quality and dedicated medical treatment which is an economic burden. In the lack of appropriate care and supp...
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ISBN:
(数字)9781728169262
ISBN:
(纸本)9781728169279
Falls are a major health issue, particularly among the elderly. Increasing fall events require high service quality and dedicated medical treatment which is an economic burden. In the lack of appropriate care and support, serious injuries caused by fall will cost lives. Therefore, tracking systems with fall detection capabilities are required. Static-view sensors with machine learning techniques for human fall detection have been widely studied and achieved significant results. However, these systems unable to monitor a person if he or she is out of viewing angle which greatly impedes its performance. Mobile robots are an alternative for keeping the person in sight. However, existing mobile robots are unable to operate for a long time due to battery issues and movement constraints in complex environments. In this paper, we proposed a lightweight deep learning vision-based model for human fall detection with an assistive robot to provide assistance when a fall happens. The proposed detection system requires less computational power which can be implemented in a low-cost 2D camera and GPU board for real-time monitoring. The assistive robot equipped with various sensors that can perform SLAM, obstacle avoidance and navigation autonomously. Our proposed system integrates these two sub-systems to compensate for the weakness of each other to constitute a system that robust, adaptable, and high performance. The proposed method has been validated through a series of experiments.
In this work, we employ multiple energy harvesting relays to assist information transmission from a multi-antenna hybrid access point (HAP) to a receiver. All the relays are wirelessly powered by the HAP in the power-...
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