This study is related to a system that enables elderly people to communicate interactively with young people who use existing message exchange services by simply speaking to an avatar on a tablet PC, without having to...
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We report a high-energy Tm-doped chirped-pulse-amplification fiber laser system seeded by dissipative solitons at 1902 nm. The system provides output pulses with a pulse energy of 120 nJ and a pulse duration of 940 fs...
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This paper demonstrated the fabrication,characterization,datadriven modeling,and practical application of a 1D SnO_(2)nanofiber-based memristor,in which a 1D SnO_(2)active layer wassandwiched between silver(Ag)and alu...
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This paper demonstrated the fabrication,characterization,datadriven modeling,and practical application of a 1D SnO_(2)nanofiber-based memristor,in which a 1D SnO_(2)active layer wassandwiched between silver(Ag)and aluminum(Al)*** yielded a very high ROFF:RON of~104(ION:IOFF of~105)with an excellent activation slope of 10 mV/dec,low set voltage ofVSET~1.14 V and good *** paper physically explained the conduction mechanism in the layered SnO_(2)*** conductive network was composed of nanofibersthat play a vital role in the memristive action,since more conductive paths could facilitate the hopping of electron *** structures experimentally extracted with the adoption of ultraviolet photoelectron spectroscopy strongly support the claimsreported in this *** machine learning(ML)–assisted,datadriven model of the fabricated memristor was also developedemploying different popular algorithms such as polynomialregression,support vector regression,k nearest neighbors,andartificial neural network(ANN)to model the data of the *** have proposed two types of ANN models(type I andtype II)algorithms,illustrated with a detailed flowchart,to modelthe fabricated *** with standard ML techniques shows that the type II ANN algorithm provides the bestmean absolute percentage error of 0.0175 with a 98%R^(2)*** proposed data-driven model was further validated with the characterization results of similar new memristors fabricated adoptingthe same fabrication recipe,which gave satisfactory ***,the ANN type II model was applied to design and implementsimple AND&OR logic functionalities adopting the fabricatedmemristors with expected,near-ideal characteristics.
Ontology embeddings map classes, relations, and individuals in ontologies into Rn, and within Rn similarity between entities can be computed or new axioms inferred. For ontologies in the Description Logic EL++, severa...
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We introduce a constructive function approximation approach as a general tool, particularly useful in adaptive and data-driven methods for perception and control. The key idea is to estimate of a collection of simple ...
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ISBN:
(数字)9798350395440
ISBN:
(纸本)9798350395457
We introduce a constructive function approximation approach as a general tool, particularly useful in adaptive and data-driven methods for perception and control. The key idea is to estimate of a collection of simple local models as opposed to a single and complex regression model trained in the entire input space. We use principles from the Online Deterministic Annealing (ODA) optimization framework to construct an adaptive partition of the input space, which enables the introduction of local function approximation models within each subset of the partition. We show that both the partitioning and the local model training algorithms are stochastic approximation algorithms that operate online, and with the same observations, as part of a two-timescale stochastic approximation scheme. This process constitutes a heuristic method to gradually increase the complexity of the function approximation framework in a task-agnostic manner, giving emphasis to regions of the input space where the regression error is high. As a result this framework has inherent explainability properties, and is suitable for continuous learning applications where regression improvement without retraining from scratch is crucial. Simulation results illustrate the properties of the proposed approach.
Binocular vision serves as the foundation for stereo vision, providing humans with the ability to perceive the three-dimensional information of their surroundings. However, although some cortical neurons are reported ...
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ISBN:
(数字)9798350359312
ISBN:
(纸本)9798350359329
Binocular vision serves as the foundation for stereo vision, providing humans with the ability to perceive the three-dimensional information of their surroundings. However, although some cortical neurons are reported with 3D information selectivity, the interconnections between binocular input and cortical neuron firing have yet to be fully established, impeding progress in our understanding of stereo information perception. In this work, we aim to address this issue by examining the causality between retinal input and selective neuron firing. We propose a general mechanism of stereo orientation and motion direction detection based solely on binocular disparity input, which is the difference in visual information between the two eyes. Our results suggest that this disparity-based mechanism is robust and can effectively complete stereo orientation and motion direction detection. Our proposed general perceiving mechanism has the potential to contribute to the resolution of the complex problem of binocular information processing and computation. Further research into this area may help to deepen our understanding of stereo vision and provide insights into the underlying neural mechanisms.
Automated Theorem Proving (ATP) faces significant challenges due to the vast action space and the computational demands of proof generation. Recent advances have utilized Large Language Models (LLMs) for action select...
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We consider word-of-mouth social learning involving m Kalman filter agents that operate sequentially. The first Kalman filter receives the raw observations, while each subsequent Kalman filter receives a noisy measure...
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Two-dimensional van der Waals(2D vdW)material-based heterostructure devices have been widely studied for high-end electronic applications owing to their heterojunction *** this study,we demonstrate graphene(Gr)-bridge...
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Two-dimensional van der Waals(2D vdW)material-based heterostructure devices have been widely studied for high-end electronic applications owing to their heterojunction *** this study,we demonstrate graphene(Gr)-bridge heterostructure devices consisting of laterally series-connected ambipolar semiconductor/Gr-bridge/n-type molybdenum disulfide as a channel material for field-effect transistors(FET).Unlike conventional FET operation,our Gr-bridge devices exhibit nonclassical transfer characteristics(humped transfer curve),thus possessing a negative differential *** phenomena are interpreted as the operating behavior in two series-connected FETs,and they result from the gate-tunable contact capacity of the Gr-bridge ***-value logic inverters and frequency tripler circuits are successfully demonstrated using ambipolar semiconductors with narrow-and wide-bandgap materials as more advanced circuit applications based on non-classical transfer ***,we believe that our innovative and straightforward device structure engineering will be a promising technique for future multi-functional circuit applications of 2D nanoelectronics.
The Internet of Bodies is a body-centric network that connects smart devices to enable real-time monitoring of physiological data, including early detection of cardiovascular diseases through electrocardiograms (ECG) ...
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ISBN:
(数字)9798350371499
ISBN:
(纸本)9798350371505
The Internet of Bodies is a body-centric network that connects smart devices to enable real-time monitoring of physiological data, including early detection of cardiovascular diseases through electrocardiograms (ECG) monitoring. In contrast to power-intensive RF transceivers in many ECG wearables, Human Body Communication (HBC) offers an energy-efficient (EE) and secure alternative, utilizing the body as a communication channel. This paper explores the functionality of an IoB sensor node designed for ECG monitoring, leveraging HBC and incorporating energy harvesting techniques to ensure sustained power. It introduces a scheme that utilizes ECG signal characteristics to identify sensing and transmission time durations, and it formulates an optimization problem within a Markov Decision Process framework. Given the battery and computational power constraint of IoB nodes, we propose lightweight and EE policies. Simulations confirm their benefits over myopic policies in terms of maximizing node lifetime and optimizing energy utilization, making them a promising solution for IoB systems operating under dynamic energy arrival rates.
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