Multi-scale visual representation have shown their advantages in effectiveness in a wide range of applications. However, existing methods fail to fully utilize the specific semantic information of the respective layer...
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Thoroughly monitoring the energy consumption of each appliance in a household is essential to assist users in better engaging in power-saving practices. To get per-Appliance electrical profile, non-intrusive load moni...
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It is well-known that counting formal concepts in a formal context is a challenging #P-complete problem. To determine the expected number of formal concepts in a formal context, we consider a random formal context, wh...
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The homomorphic encryption algorithm Paillier is a cryptographic method that can be applied in areas such as privacy-preserving computation and federated learning. However" due to the inherent complexity and comp...
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Image processing algorithms, which supply the image quality, are used by modern mobile devices to capture images. These methods need more RAM to process an image and fix these problems. Software pipelines are utilized...
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In order to solve the delay requirements of computing intensive tasks in industrial Internet of things,edge computing is moving from theoretical research to practical *** servers(ESs)have been deployed in factories,an...
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In order to solve the delay requirements of computing intensive tasks in industrial Internet of things,edge computing is moving from theoretical research to practical *** servers(ESs)have been deployed in factories,and on-site auto guided vehicles(AGVs),besides doing their regular transportation tasks,can partly act as mobile collectors and distributors of computing data and *** AGVs may offload tasks to the same ES if they have overlapping path segments,resource allocation conflicts are *** this paper,we study the problem of efficient task offloading from AGVs to ESs,along their fixed *** propose a multi-AGV task offloading optimization algorithm(MATO),which first uses the weighted polling algorithm to preliminarily allocate tasks for individual AGVs based on load balancing,and then uses the Deep Q-Network(DQN)model to obtain the updated offloading strategy for the AGV *** simulation results show that,compared with the existing methods,the proposed MATO algorithm can significantly reduce the maximum completion time of tasks and be stable under various parameter settings.
Named entity recognition (NER) is a fundamental task in natural language processing and a key technology for building knowledge graphs. However, the performance of NER is often limited by domain-specific characteristi...
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Stack Overflow is a widely-used community Q&A website for programming-related queries. In such a platform, providing related questions as suggestions to the users can significantly enhance their search experience....
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Many systems have been built to employ the delta-based iterative execution model to support iterative algorithms on distributed platforms by exploiting the sparse computational dependencies between data items of these...
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Many systems have been built to employ the delta-based iterative execution model to support iterative algorithms on distributed platforms by exploiting the sparse computational dependencies between data items of these iterative algorithms in a synchronous or asynchronous approach. However, for large-scale iterative algorithms, existing synchronous solutions suffer from slow convergence speed and load imbalance, because of the strict barrier between iterations;while existing asynchronous approaches induce excessive redundant communication and computation cost as a result of being barrier-free. In view of the performance trade-off between these two approaches, this paper designs an efficient execution manager, called Aiter-R, which can be integrated into existing delta-based iterative processing systems to efficiently support the execution of delta-based iterative algorithms, by using our proposed group-based iterative execution approach. It can efficiently and correctly explore the middle ground of the two extremes. A heuristic scheduling algorithm is further proposed to allow an iterative algorithm to adaptively choose its trade-off point so as to achieve the maximum efficiency. Experimental results show that Aiter-R strikes a good balance between the synchronous and asynchronous policies and outperforms state-of-the-art solutions. It reduces the execution time by up to 54.1% and 84.6% in comparison with existing asynchronous and the synchronous models, respectively.
The health of the mother is crucial to the well-being of the baby throughout pregnancy. Early treatments and individualized care may be more effective when maternal health hazards are properly classified. In this stud...
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