To adapt to various IoT services, Bluetooth Low Energy (BLE) specification has defined a variety of communication modes, such as advertising, extended advertising, and periodic advertising events. As services’ enviro...
To adapt to various IoT services, Bluetooth Low Energy (BLE) specification has defined a variety of communication modes, such as advertising, extended advertising, and periodic advertising events. As services’ environments, such as the number of users and QoS requirements, are changed, modes of protocols should be also adjusted to meet those services’ needs. This paper proposes an adaptive BLE scheme to reflect dynamically changing services’ environments. The effectiveness of the proposed scheme is verified through simulation experiments.
There is growing interest in the use of additive manufacturing for the fabrication of RF devices due to fast prototyping capabilities and the use of less material as opposed to traditional fabrication techniques. In a...
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With the growing data size and the increased amount of computational load in machine learning workloads, configuring the resources of IoT (Internet-of-Things) systems in an energy-saving way is becoming important. For...
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In this paper, multiple relay selection (MRS) schemes for untrusted unmanned aerial vehicle (UAV)-enabled networks are proposed. In this context, various machine learning (ML) models are employed to improve secrecy pe...
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Cross-hatching of PCB grounds refers to a process in which certain ground planes appear as copper lattices;regular openings are placed at regular intervals. Nowadays, the efficacy of ground hatching on rigid PCBs is m...
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With the rapid advancement of biological information, accurate analysis of treatment data aids in early disease detection. To uncover knowledge for medical research, advanced Machine Learning algorithms are applied. H...
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Predictive maintenance on medical equipment is to identify the equipment condition and to forecast when the maintenance is required. In this paper, the Computed Tomography scan machine is deployed with IoT sensors to ...
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CMOS technology evolution enhances integrated circuits (ICs) performance characteristics at the cost of their increased susceptibility to radiation and thus to the occurrence of single-event upsets (SEUs) that may lea...
CMOS technology evolution enhances integrated circuits (ICs) performance characteristics at the cost of their increased susceptibility to radiation and thus to the occurrence of single-event upsets (SEUs) that may lead to soft errors generation. SEUs may affect multiple nodes in a circuit (multiple node upsets - MNUs). Fortunately, these disturbances do not cause permanent damage to the circuits. Various techniques have been proposed to deal with SEUs that concurrently affect one, two or three nodes. In this paper, we propose the design of a latch that offers tolerance up to the level of triple-node upsets (TNUs). This is achieved by using redundancy in the hardware which provides the ability to store a logic value in multiple nodes within the latch as well as by using multiple feedback paths which allow it to recover its correct state in the event of an SEU. Compared to other techniques dealing with the same problem, our proposed method provides faster recovery time (higher than 16.87%) after an SEU, and at the same time reduced power consumption and higher speed performance.
Brain-computer interface (BCI) technology has promising applications as an intuitive communication tool and in fields such as language rehabilitation. This study aims to decode human speech intentions by analyzing EEG...
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ISBN:
(数字)9798331521929
ISBN:
(纸本)9798331521936
Brain-computer interface (BCI) technology has promising applications as an intuitive communication tool and in fields such as language rehabilitation. This study aims to decode human speech intentions by analyzing EEG signals recorded during actual and imagined speech. EEG data were collected using a 64 channels system, with preprocessing to remove artifacts. Automatic speech recognition (ASR) was used to extract precise speech onset times, generating time-specific speech annotations corresponding with EEG data. Pretrained Word2Vec embeddings were integrated to provide semantic context, combining neural signals with high-level linguistic features. Support vector machine (SVM), linear discriminant analysis (LDA) were employed for decoding. The results demonstrate that integrating speech annotations improves decoding accuracy, even for imagined speech, highlighting the potential of BCI technology for advanced applications in communication and rehabilitation.
The development of humidity sensors is essential for applications in the environmental, agriculture, medical and semiconductor industries. This research focused on using advanced printed board circuit (PCB) printing t...
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