Kidney disease (KD) is a gradually increasing global health concern. It is a chronic illness linked to higher rates of morbidity and mortality, a higher risk of cardiovascular disease and numerous other illnesses, and...
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Optical character recognition is a way of converting scanned images of printed or handwritten documents into machine-encoded text, making it easier to store, browse, retrieve, and process electronic data. In this rese...
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Several vital resources are increasingly being protected by cyber-physical systems (CPSs), makes the detection of incidents on these systems critical. CPSs along with other domains, such as the Internet of Things (IoT...
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Due to the poor accuracy, low efficiency and poor stability of fatigue driving detection of urban road at night, this paper proposes a fatigue driving detection of urban road at night based on multimodal information f...
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Learning network dynamics from the empirical structure and spatio-temporal observation data is crucial to revealing the interaction mechanisms of complex networks in a wide range of domains. However,most existing meth...
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Learning network dynamics from the empirical structure and spatio-temporal observation data is crucial to revealing the interaction mechanisms of complex networks in a wide range of domains. However,most existing methods only aim at learning network dynamic behaviors generated by a specific ordinary differential equation instance, resulting in ineffectiveness for new ones, and generally require dense *** observed data, especially from network emerging dynamics, are usually difficult to obtain, which brings trouble to model learning. Therefore, learning accurate network dynamics with sparse, irregularly-sampled,partial, and noisy observations remains a fundamental challenge. We introduce a new concept of the stochastic skeleton and its neural implementation, i.e., neural ODE processes for network dynamics(NDP4ND), a new class of stochastic processes governed by stochastic data-adaptive network dynamics, to overcome the challenge and learn continuous network dynamics from scarce observations. Intensive experiments conducted on various network dynamics in ecological population evolution, phototaxis movement, brain activity, epidemic spreading, and real-world empirical systems, demonstrate that the proposed method has excellent data adaptability and computational efficiency, and can adapt to unseen network emerging dynamics, producing accurate interpolation and extrapolation with reducing the ratio of required observation data to only about 6% and improving the learning speed for new dynamics by three orders of magnitude.
The Internet of Things (IoT) becomes the most demanding technology over the past few years. IoT is the basic need of daily life. The security of these devices is very important because they contain large files of sens...
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Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transp...
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Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time *** modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is *** paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.
The remarkable growth of machine learning has shown that it can perform at an expert level in a number of difficult tasks, such as medical decision-making and image processing. The goal of this research is to take adv...
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The tremendous development of cloud computing with related technol-ogies is an unexpected ***,centralized cloud storage faces few chal-lenges such as latency,storage,and packet drop in the *** storage gets more attent...
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The tremendous development of cloud computing with related technol-ogies is an unexpected ***,centralized cloud storage faces few chal-lenges such as latency,storage,and packet drop in the *** storage gets more attention due to its huge data storage and ensures the security of secret *** of the developments in cloud storage have been positive except better cost model and effectiveness,but still data leakage in security are billion-dollar questions to *** data security techniques are usually based on cryptographic methods,but these approaches may not be able to with-stand an attack from the cloud server's ***,we suggest a model called multi-layer storage(MLS)based on security using elliptical curve cryptography(ECC).The suggested model focuses on the significance of cloud storage along with data protection and removing duplicates at the initial *** on divide and combine methodologies,the data are divided into three ***,thefirst two portions of data are stored in the local system and fog nodes to secure the data using the encoding and decoding *** other part of the encrypted data is saved in the *** viability of our model has been tested by research in terms of safety measures and test evaluation,and it is truly a powerful comple-ment to existing methods in cloud storage.
作者：
Huang, Po-HsunHsiao, Tzu-Chien
Hsinchu300 Taiwan Nycu
Department of Computer Science College of Cs and Institute of Biomedical Engineering College of Electrical and Computer Engineering Hsinchu300 Taiwan
The determination of appropriate parameters and an appropriate window size in most entropy-based measurements of time-series complexity is a challenging problem. Inappropriate settings can lead to the loss of intrinsi...
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