Preparing for the deployment of large scientific and engineering codes on upcoming exascale systems with GPU-dense nodes is made challenging by the unprecedented diversity of device architectures and heterogeneous pro...
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In this paper, we propose fast solvers for Maxwell’s equations in rectangular domains. We first discretize the simplified Maxwell’s eigenvalue problems by employing the lowest-order rectangular Nédélec ele...
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Regular expressions are widely used within and even outside of computer science due to their expressiveness and ***, regular expressions have a quite compact and rather tolerant syntax that makes them hard to understa...
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Regular expressions are widely used within and even outside of computer science due to their expressiveness and ***, regular expressions have a quite compact and rather tolerant syntax that makes them hard to understand, hard to compose,and error-prone. Faulty regular expressions may cause failures of the applications that use them. Therefore, ensuring the correctness of regular expressions is a vital prerequisite for their use in practical applications. The importance and necessity of ensuring correct definitions of regular expressions have attracted extensive attention from researchers and practitioners, especially in recent years. In this study, we provide a review of the recent works for ensuring the correct usage of regular expressions. We classify those works into different categories, including the empirical study, test string generation, automatic synthesis and learning, static checking and verification,visual representation and explanation, and repairing. For each category, we review the main results, compare different approaches, and discuss their advantages and disadvantages. We also discuss some potential future research directions.
At present, with the rapid development of economy and technology, the quality of the people's life has been generally improved, and the importance of the security system has become increasingly prominent. Among th...
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Deep Forest, a powerful alternative to deep neural networks, has gained much attention due to its advantages, such as low complexity, minimal hyperparameter requirements, and strong application performance. In the cur...
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Recent researches have shown that Large Language Models (LLMs) are susceptible to a security threat known as Backdoor Attack. The backdoored model will behave well in normal cases but exhibit malicious behaviours on i...
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Convolutional Neural Network (CNN) is one of the deep learning architectures that is very effective for handling images. CNN is able to automatically extract important features from images, making it very suitable for...
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Current vulnerability detection methods based on deep learning and program slicing techniques are widely used, but the program representations and slicing strategies they employ are not well-suited for this purpose. T...
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In this paper we consider the following 2-Central Path Problem (2CPP): Given a set of m polygonal curves = {P1,P2,...,Pm} in the plane, find two curves Pu and Pl, called 2-central paths, that best represent all curves...
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In this paper we consider the following 2-Central Path Problem (2CPP): Given a set of m polygonal curves = {P1,P2,...,Pm} in the plane, find two curves Pu and Pl, called 2-central paths, that best represent all curves in . Despite its theoretical interest and a wide range of practical applications, 2CPP has not been well studied. In this paper, we first establish criteria that Pu and Pl ought to meet in order for them to best represent . In particular, we require that there exists parametrizations fu(t) and fl(t) (t [a,b]) of Pu and Pl respectively such that the maximum distance from {fu(t),fl(t)} to curves in is minimized. Then an efficient algorithm is presented to solve 2CPP under certain realistic assumptions. Our algorithm constructs Pu and Pl in O(nmlog4n2α(n)α(n)) time, where n is the total complexity of (i.e., the total number of vertices and edges), m is the number of curves in , and α(n) is the inverse Ackermann function. Our algorithm uses parametric search technique and is considerably faster than arrangement-related algorithms (i.e. ω(n2)) when m ≪ n as in most real applications.
Local rough set models are efficient rough data analysis methods for weakly labeled data in the rough set field. However, the existing local models do not distinguish the importance of different attributes to decision...
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