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In this paper, the nano-CMOS hybrid Autonomous Error-Tolerant (AET) cellular network architecture, which integrates today's mature CMOS technology with emerging nanotechnology, is proposed. Within the cellular network, each AET cell contains a nanocore, CMOS cell peripherals and their interface circuits. The overall network is homogenous. These imp...
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Quantum-dot cellular automata are the rising nanotechnology used to structure the nano scale circuits. QCA is the powerful elective technique to the CMOS innovation. In this paper,anovel effective design of encoder is proposed by the use of Majority gate and inverter.The proposed QCA encoder 4X2 and8X3 design outshines interms of cell count, area a...
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... By comparison, AET concepts exhibit better overall performance. In addition, the homogeneity of the cellular structure in AET arrays allows easier relocation of tasks when reconfiguration is needed for error-tolerance or system optimization reasons [17]. On the other hand, biological systems rely on local computation and communication as well as local state that demonstrate extreme robustness with respect to local errors as well as environmental disturbances at all levels of system abstractions. ...
The dental disease is a common disease for a human. Screening and visual diagnosis which are currently performed in clinics possibly cost a lot in various manners. Along with the progress of the Internet of Things (IoT) and Articial Intelligence (AI), the internet-based intelligent system have shown great potential in applying home-based healthcare. Therefore, a smart dental Health-IoT system based on intelligent hardware, deep learning and mobile terminal is proposed in this paper, aiming at exploring the feasibility of its application on In-home dental healthcare. Moreover, a smart dental device is designed and developed in this study to perform the image acquisition of teeth. Based on the data set of 12, 600 clinical images collected by the proposed device from 10 private dental clinics, an automatic diagnosis model trained by MASK R-CNN is developed for the detection and classication of 7 different dental diseases including decayed tooth, dental plaque, uorosis and periodontal disease, with the diagnosis accuracy of them reaching up to 90%, along with high sensitivity and high specicity. Following the one-month test in 10 clinics, compared with that last month when the platform is not used, the mean diagnosis time reduces by 37.5% for each patient, helping explain the increase of the number of treated patients by 18.4%. Furthermore, application software (App) on mobile terminal for client-side and for dentist-side are implemented to provide service of pre-examination, consultation, appointment, and evaluation.
... By comparison, AET concepts exhibit better overall performance. In addition, the homogeneity of the cellular structure in AET arrays allows easier relocation of tasks when reconfiguration is needed for error-tolerance or system optimization reasons [17]. On the other hand, biological systems rely on local computation and communication as well as local state that demonstrate extreme robustness with respect to local errors as well as environmental disturbances at all levels of system abstractions. ...
The massively parallel computing systems composed of many processors are connected on chips, which will become more and more complex and unreliable. This paper presents an error-tolerant design based on the autonomous error-tolerant (AET) architecture that aims to have a self-repairing capability. A nearby error sensing mechanism is designed to discover faults, and an active evolution scheme is studied to handle unrecoverable errors. A circuit backup switching mechanism is proposed to bypass the failed nodes. The board-level prototype is implemented based on dual-core embedded processors. The analysis shows that the error-tolerant capability of the proposed architecture is better than the conventional multimodular redundant system when the failure rate of a single core is less than 0.7. In the AET test system consisting of 16 processors, the error-tolerant capability is verified. The results show that the relative variation of the overall performance of the AET system will not be changed due to the high reliability requirements of the system. Through experimental comparison, under the premise that the architecture of AET and the triple modular redundancy method are basically consistent in reliability, whether on the logical-level error tolerant or on the physical-level error tolerant, the former has lower power consumption.
