Alzheimer's disease is a common and complex brain disorder that primarily affects the elderly. Because it is progressing and has few effective therapies, it requires a thorough understanding of the condition;our s...
详细信息
This article designs a 14-bit successive approximation register analog-to-digital converter（SAR ADC）.A novel digital bubble sorting calibration method is proposed and applied to eliminate the effect of capacitor mis...
详细信息
This article designs a 14-bit successive approximation register analog-to-digital converter（SAR ADC）.A novel digital bubble sorting calibration method is proposed and applied to eliminate the effect of capacitor mismatch on the linearity of the SAR ADC. To reduce the number of capacitors, a hybrid architecture of a high 8-bit binary-weighted capacitor array and a low 6-bit resistor array is adopted by the digital-to-analog（DAC）. The common-mode voltage VCM-based switching scheme is chosen to reduce the switching energy and area of the DAC. The time-domain comparator is employed to obtain lower power consumption. Sampling is performed through a gate voltage bootstrapped switch to reduce the nonlinear errors introduced when sampling the input signal. Moreover, the SAR logic and the whole calibration is totally implemented on-chip through digital integrated circuit（IC） tools such as design compiler, IC compiler, etc. Finally, a prototype is designed and implemented using 0.18 μm bipolar-complementary metal oxide semiconductor（CMOS）-double-diffused MOS 1.8 V CMOS technology. The measurement results show that the SAR ADC with on-chip bubble sorting calibration method achieves the signal-to-noise-and-distortion ratio of 69.75 dB and the spurious-free dynamic range of 83.77 dB.
The management of healthcare data has significantly benefited from the use of cloud-assisted MediVault for healthcare systems, which can offer patients efficient and convenient digital storage services for storin...
详细信息
The Internet of Things (IoT) occupies the entire world in its hands. IoT devices have a resource-constrained nature known as Low Power and Lossy Networks (LLN). The Routing Protocol for Low Power and Lossy Networks (R...
详细信息
Pancreatic cancer's devastating impact and low survival rates call for improved detection methods. While Artificial Intelligence has shown remarkable progress, its increasing complexity has led to "black box&...
详细信息
The key objective of intrusion detection systems(IDS)is to protect the particular host or network by investigating and predicting the network traffic as an attack or *** IDS uses many methods of machine learning(ML)to...
详细信息
The key objective of intrusion detection systems(IDS)is to protect the particular host or network by investigating and predicting the network traffic as an attack or *** IDS uses many methods of machine learning(ML)to learn from pastexperience attack *** based and identify the new *** though these methods are effective,but they have to suffer from large computational costs due to considering all the traffic features,***,emerging technologies like the Internet of Things(Io T),big data,*** getting advanced day by day;as a result,network traffics are also increasing ***,the issue of computational cost needs to be addressed ***,in this research,firstly,the ML methods have been used with the feature selection technique(FST)to reduce the number of features by picking out only the important ones from NSL-KDD,CICIDS2017,and CIC-DDo S2019datasets later that helped to build IDSs with lower cost but with the higher performance which would be appropriate for vast scale *** experimental result demonstrated that the proposed model *** tree(DT)with Recursive feature elimination(RFE)performs better than other classifiers with RFE in terms of accuracy,specificity,precision,sensitivity,F1-score,and G-means on the investigated datasets.
In recent years, artificial intelligence (AI)-driven computertechnology has become popular in many practical applications in the retail industry. In particular, the development of face recognition, mobile payment, cl...
详细信息
In 2018, there were 1 million occurrences of non-melanoma cancer and 288,000 occurrences of malignant skin cancer (MM) recorded worldwide. Given the aging of the population and limited resources for medical care, a co...
详细信息
Neural networks(NNs)often assign high confidence to their predictions,even for points far out of distribution,making uncertainty quantification(UQ)a *** they are employed to model interatomic potentials in materials s...
详细信息
Neural networks(NNs)often assign high confidence to their predictions,even for points far out of distribution,making uncertainty quantification(UQ)a *** they are employed to model interatomic potentials in materials systems,this problem leads to unphysical structures that disrupt simulations,or to biased statistics and dynamics that do not reflect the true *** UQ techniques can find new informative data and drive active learning loops for robust ***,a variety of UQ techniques,including newly developed ones,exist for atomistic simulations and there are no clear guidelines for which are most effective or suitable for a given *** this work,we examine multiple UQ schemes for improving the robustness of NN interatomic potentials(NNIPs)through active *** particular,we compare incumbent ensemble-based methods against strategies that use single,deterministic NNs:mean-variance estimation(MVE),deep evidential regression,and Gaussian mixture models(GMM).We explore three datasets ranging from in-domain interpolative learning to more extrapolative out-of-domain generalization challenges:rMD17,ammonia inversion,and bulk silica *** is measured across multiple metrics relating model error to *** experiments show that none of the methods consistently outperformed each other across the various *** remained better at generalization and for NNIP robustness;MVE only proved effective for in-domain interpolation,while GMM was better out-of-domain;and evidential regression,despite its promise,was not the preferable alternative in any of the *** broadly,cost-effective,single deterministic models cannot yet consistently match or outperform ensembling for uncertainty quantification in NNIPs.
With the rapid growth of science and technology,the Internet of Things(IoT)technology has matured and attracted the attention of many *** development of agricultural modernization leads to the gradual emergence of int...
详细信息
With the rapid growth of science and technology,the Internet of Things(IoT)technology has matured and attracted the attention of many *** development of agricultural modernization leads to the gradual emergence of intelligent management gradually taking root in agricultural *** many technologies in the IoT technologies,low-power Wide Area Network(WAN)technology has the characteristics of reliable and stable transmission with long distance and low power *** is very useful for data transmission in special environments,especially for orchards in mountainous *** paper proposed a new agricultural Internet of Things in orchard management based on multi-sensors,such as DHT11 for temperature/humidity and GY-30 for illumination,the Long Range(LoRa)technology for transmitting the collected data or control command between the terminal and data cloud center,*** a low-power IoT sensor network in the orchard can remotely measure the parameters in the *** WAN is used to transmit data to the central *** order to reduce power consumption and cost,a single monitoring node selects two power supplies,a solar power supply and a power supply,and the power supply can be turned on remotely by users in special *** in different environments in the peach orchard show that the monitoring system has enough reliability and accuracy,and is suitable for environmental monitoring in orchards in remote areas or areas with complex terrain.
暂无评论