With the increasing availability of real-time traffic information, dynamic spatial networks are pervasive nowa- days and path planning in dynamic spatial networks becomes an important issue. In this light, we propose ...
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With the increasing availability of real-time traffic information, dynamic spatial networks are pervasive nowa- days and path planning in dynamic spatial networks becomes an important issue. In this light, we propose and investigate a novel problem of dynamically monitoring shortest paths in spatial networks （DSPM query）. When a traveler aims to a des- tination, his/her shortest path to the destination may change due to two reasons： 1） the travel costs of some edges have been updated and 2） the traveler deviates from the pre-planned path. Our target is to accelerate the shortest path computing in dynamic spatial networks, and we believe that this study may be useful in many mobile applications, such as route planning and recommendation, car navigation and tracking, and location-based services in general. This problem is challenging due to two reasons： 1） how to maintain and reuse the existing computation results to accelerate the following computations, and 2） how to prune the search space effectively. To overcome these challenges, filter-and-refinement paradigm is adopted. We maintain an expansion tree and define a pair of upper and lower bounds to prune the search space. A series of optimization techniques are developed to accelerate the shortest path computing. The performance of the developed methods is studied in extensive experiments based on real spatial data.
Asthma is a far reaching non-communicable sickness that affects individuals of any age and is a significant danger to human wellbeing worldwide, especially in low and middle-income countries. Its prevalence is substan...
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Processing programming languages are very similar to processing natural languages, especially high-level languages such as Python, Java, C#, C, C++, and others. Therefore, the natural language processing concepts can ...
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This paper presents experimental study to distinguish between malignant and benign tumors in early breast cancer detection using Ultra Wide Band (UWB) imaging. The contrast between dielectric properties of these two t...
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Neural networks excel at capturing local spatial patterns through convolutional modules,but they may struggle to identify and effectively utilize the morphological and amplitude periodic nature of physiological *** th...
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Neural networks excel at capturing local spatial patterns through convolutional modules,but they may struggle to identify and effectively utilize the morphological and amplitude periodic nature of physiological *** this work,we propose a novel network named filtering module fully convolutional network(FM-FCN),which fuses traditional filtering techniques with neural networks to amplify physiological signals and suppress ***,instead of using a fully connected layer,we use an FCN to preserve the time-dimensional correlation information of physiological signals,enabling multiple cycles of signals in the network and providing a basis for signal ***,we introduce the FM as a network module that adapts to eliminate unwanted interference,leveraging the structure of the *** approach builds a bridge between deep learning and signal processing ***,we evaluate the performance of FM-FCN using remote *** results demonstrate that FM-FCN outperforms the second-ranked method in terms of both blood volume pulse(BVP)signal and heart rate(HR)*** substantially improves the quality of BVP waveform reconstruction,with a decrease of 20.23%in mean absolute error(MAE)and an increase of 79.95%in signal-to-noise ratio(SNR).Regarding HR estimation accuracy,FM-FCN achieves a decrease of 35.85%in MAE,29.65%in error standard deviation,and 32.88%decrease in 95%limits of agreement width,meeting clinical standards for HR accuracy *** results highlight its potential in improving the accuracy and reliability of vital sign measurement through high-quality BVP signal *** codes and datasets are available online at https://***/zhaoqi106/FM-FCN.
We consider the computation of r-th roots in finite fields. For the computation of square roots, there are two typical probabilistic methods: The Tonelli-Shanks method and the Cipolla-Lehmer method. The former method ...
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ISBN:
(纸本)9781849199094
We consider the computation of r-th roots in finite fields. For the computation of square roots, there are two typical probabilistic methods: The Tonelli-Shanks method and the Cipolla-Lehmer method. The former method can be extended to the case of r-th roots, which is called the Adleman-Manders- Miller(AMM) method. The latter method had been generalized to the case of r-th roots with r prime. In this paper, we extend the Cipolla-Lehmer to the case of r-th root with r prime power and give the expected running time of our algorithm.
Embedding context-aware self-adaptation mechanisms in pervasive systems is key to improve their acceptance by the users. These mechanisms involve a precise definition of the software structures that enable adding, rem...
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Motion tracking is a critical task in many computer vision applications. Existing motion tracking techniques require either a great amount of knowledge on the target object or specific hardware. These requirements dis...
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An integral-order hyperchaotic system with four-dimension is expanded to be a fractional-order system whose chaotic behaviors are analyzed, Firstly, based on the stability theory of fractional-order linear system and ...
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An integral-order hyperchaotic system with four-dimension is expanded to be a fractional-order system whose chaotic behaviors are analyzed, Firstly, based on the stability theory of fractional-order linear system and the thinking of tracking control, a synchronization method for two fractional-order systems with different structures is proposed, and an analytic expression for synchronization controller is given. Secondly, taking the extended fractional-order system and Rossler hyperchaotic system as example, the synchronization between them is numerical simulated. Finally, the proposed synchronization method is applied to encrypt and decrypt digital images. The simulation results show that the lowest order that extended fractional-order system appears chaos is 3.2, and this method has many advantages for encrypting and decrypting digital images, such as sensitive secret keys, random uniform distribution of pixels and low correlation between adjacent pixels.
The Visual Storytelling Task (VST) extends beyond describing a single image, such as image captioning, to sequential image descriptions in the form of a coherent story. However, such descriptions present challenges in...
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