In light of the rapid advancement of technologies related to the Internet of things (IoT), IoT service platforms have become one of the main solutions for providing intelligent and efficient services in the industrial...
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In light of the rapid advancement of technologies related to the Internet of things (IoT), IoT service platforms have become one of the main solutions for providing intelligent and efficient services in the industrial sector. Scheduling is an effective means to match resources and guarantee quality of service. However, existing service scheduling models and methods have not fully considered the special needs of new IoT platforms. Therefore, this article summarizes the special requirements of the new IoT platform, including the heterogeneity of IoT service platform resources, complexity and diversity of tasks, as well as considering the demand for low energy consumption and low latency. Constructed a multi-granularity task scheduling model for cloud-edge collaborative environments, which takes the special needs mentioned above into account. Combined with priority experience replay and importance sampling, a task scheduling algorithm priority replay with importance-based method in Actor Critic (PRIME-AC) based on deep reinforcement learning is proposed. The experimental results show that PRIME-AC has better performance in both task execution delay and load balancing than other baselines.
With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this *** symbolic computa...
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With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this *** symbolic computation,we find out,on one hand,a set of bilinear auto-Backlund transformations,which could connect certain solutions of that equation with other solutions of that equation itself,and on the other hand,a set of similarity reductions,which could go from that equation to a known ordinary differential *** results in this paper depend on all the oceanic variable coefficients in that equation.
Adversarial attack for time-series classification model is widely explored and many attack methods are *** there is not a method of attack based on the data *** this paper,we innovatively proposed a black-box sparse a...
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Adversarial attack for time-series classification model is widely explored and many attack methods are *** there is not a method of attack based on the data *** this paper,we innovatively proposed a black-box sparse attack method based on data *** method directly attack the sensitive points in the time-series data accord-ing to statistical features extract from the *** frst,we have validated the transferability of sensitive points among DNNs with different ***,we use the statistical features extract from the dataset and the sensi-tive rate of each point as the training set to train the predictive ***,predicting the sensitive rate of test set by predictive ***,perturbing according to the sensitive *** attack is limited by constraining the LO norm to achieve one-point *** conduct experiments on several datasets to validate the effectiveness of this method.
Traffic data is characterized by complexity in structure, high collection frequency, large volume, and uneven spatiotemporal distribution. Efficient range querying on traffic data poses a significant challenge in inte...
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Amid the rise of mobile technologies and Location-Based Social Networks (LBSNs), there’s an escalating demand for personalized Point-of-Interest (POI) recommendations. Especially pivotal in smart cities, these system...
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With the development of the science and technology service industry, there is an urgent need to effectively organize multi-source and heterogeneous science and technology resources to meet the personalized needs of sc...
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In the realm of chronic disease health dialog, natural language understanding plays a pivotal role. It encompasses two vital subtasks: recognizing user intentions and populating relevant data slots. To establish a sym...
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Decision making based on predictive traffic flow is one of effective solutions to relieve road congestion. Capturing and modeling the dynamic temporal relationships in global data is an important part of the traffic f...
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The scale and types of service resources on the internet are becoming increasingly complex, and providing services for users' personalized needs is a research hotspot. This article proposes a user-centered service...
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In order to enable the integration between Business Process Management (BPM) and the Internet of Things (IoT), it is imperative to create an IoT service capable of encapsulating IoT device resources, converting raw da...
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