We have developed HEARTS, a dementia care training system using augmented reality based on Humanitude. Humanitude is a multimodal comprehensive care technique for dementia, and has attracted attention as a method to r...
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The conventional paradigm of communication primarily concentrates on the transmission of raw data, often disregarding its contextual meaning. However, to tackle the exponential growth in data demands along with the li...
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The Supreme Court plays an extremely critical role in ensuring adherence to the rule of law and in strengthening the democracy. Due to this reason, modeling and analysis of small group interactions in t...
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Distributed machine learning at the network edge has emerged as a promising new paradigm. Various machine learning (ML) technologies will distill Artificial Intelligence (AI) from enormous mobile data to automate futu...
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Distributed machine learning at the network edge has emerged as a promising new paradigm. Various machine learning (ML) technologies will distill Artificial Intelligence (AI) from enormous mobile data to automate future wireless networking and a wide range of Internet-of-Things (IoT) applications. In distributed edge learning, multiple edge devices train a common learning model collaboratively without sending their raw data to a central server, which not only helps to preserve data privacy but also reduces network traffic. However, distributed edge training and edge inference typically still require extensive communications among devices and servers connected by wireless links. As a result, the salient features of wireless networks, including interference and channels’ heterogeneity, time-variability, and unreliability, have significant impacts on the learning performance.
For communications subject to correlated channel effects, noise recycling has recently been shown to enhance channel capacity with receiver-side-only changes. Using a taped-out chip, in a hard-detection scenario with ...
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With the rapid proliferation of mobile devices, the marriage of millimeter-wave (mmWave) and MIMO technologies is a natural trend to meet the communication demand of data-hungry applications. Following this trend, mmW...
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As artificial intelligence and big data become increasingly prevalent,resistive random-access memory(RRAM)has become one of the most promising alternatives for storing massive amounts of *** this study,we employed hig...
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As artificial intelligence and big data become increasingly prevalent,resistive random-access memory(RRAM)has become one of the most promising alternatives for storing massive amounts of *** this study,we employed high-quality crystalline TiN/Al2O3/BaTiO3/Pt RRAM with an optimized thin Al2O3 in-terlayer around 12 nm thick prepared using atomic layer deposition since the thickness of the inter-layer affects the memory window *** insertion of the Al2O3 interlayer,the novel RRAM exhibited outstanding uniform resistive switching voltage and the ON/OFF memory window drastically increased from 10 to 103 without any discernible decline in ***,the low-resistance state and high-resistance state operating current values decreased by almost one order and three orders of magni-tude,respectively,thereby decreasing the power consumption for the RESET and SET processes by more than three and almost one order of magnitude,*** device also exhibits multilevel resistive switching behavior when varying the applied ***,we also developed a 6 × 6 crossbar array which demonstrated consistent and reliable resistive switching behavior with minimal ***,our approach holds great promise for producing state-of-the-art non-volatile resistive switching devices.
Wireless charging is a promising solution for charging battery-driven devices pervasively. However, the wide deployment of wireless charging stations is vulnerable to the device masquerade attack, which causes financi...
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In this study, we propose a new deep convolutional generative adversarial kinematics network (DCGAKN) to establish inverse kinematics of self-assembly robotic arm. We design that the robot system uses a depth sensor d...
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Recently, generalized spatial modulation (GSM) multiple-input multiple-output (MIMO) systems have attracted intensive research interest due to their advantages in balancing spectral efficiency and interchannel interfe...
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