The performance of a brick-based and hash-table-based framework, HashBrick, supporting distributed structured-grid calculations on heterogeneous architectures, is evaluated with a fourth-order accurate finite-volume a...
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The novel dynamic guider algorithm within the adaptive optimization spiking neural P system (AOSNPS) framework is employed to create an innovative English letter recognition algorithm. This algorithm utilizes adaptive...
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The novel dynamic guider algorithm within the adaptive optimization spiking neural P system (AOSNPS) framework is employed to create an innovative English letter recognition algorithm. This algorithm utilizes adaptive learning and diversity-based adaptation to regulate movement operators, achieving an average accuracy rate of 95.11% under low-noise conditions in classifying English letters. Leveraging the AOSNPS framework, the proposed algorithm surpasses back propagation neural networks with four gradient descent strategies across varying noise levels. The paper marks the initial application of the AOSNPS algorithm to pattern recognition, capitalizing on theoretical advancements in membrane computing and combinatorial optimization. The results underscore the potential of AOSNPS's methodological innovations in advancing pattern recognition capabilities.
Arrhythmia classification is crucial for identifying and preventing the potential risks associated with cardiovascular diseases. Currently., using deep learning for arrhythmia classification faces challenges of model ...
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With the development of deep learning and computer vision, face detection has achieved rapid progress owing. Face detection has several application domains, including identity authentication, security protection, medi...
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Diabetic foot ulcer (DFU) is a potentially fatal complication of diabetes. Traditional techniques of DFU analysis and therapy are more time-consuming and costly. Artificial intelligence (AI), particularly deep neural ...
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AdaptiveSGA is a method for achieving Adaptive Game Artificial Intelligence-Based Dynamic Difficulty Balancing through the Symbiotic Game Agent Model. Previous work has shown that AdaptiveSGA can achieve Dynamic Diffi...
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Traditionally, recommender systems use collaborative filtering or content-based approaches based on ratings and item descriptions. However, this information is unavailable in many domains and applications, and recomme...
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Traditionally, recommender systems use collaborative filtering or content-based approaches based on ratings and item descriptions. However, this information is unavailable in many domains and applications, and recommender systems can only tackle the problem using information about interactions or implicit knowledge. Within this scenario, this work proposes a novel approach based on link prediction techniques over graph structures that exclusively considers interactions between users and items to provide recommendations. We present and evaluate two alternative recommendation methods: one item-based and one user-based that apply the edge weight, common neighbours, Jaccard neighbours, Adar/Adamic, and Preferential Attachment link prediction techniques. This approach has two significant advantages, which are the novelty of our proposal. First, it is suitable for minimal knowledge scenarios where explicit data such as ratings or preferences are not available. However, as our evaluation demonstrates, this approach outperforms state-of-the-art techniques using a similar level of interaction knowledge. Second, our approach has another relevant feature regarding one of the most significant concerns in current artificial intelligence research: the recommendation methods presented in this paper are easily interpretable for the users, improving their trust in the recommendations.
Climate downscaling is crucial for detailed small-scale analysis and for acquiring climate data in regions without weather stations. Operator learning has proven potential for this task. However, several challenges re...
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In recent decades, the real-space finite-difference implementations of Kohn–Sham density functional theory have exhibited substantial improvements in computational efficiency for large-scale systems. However, the sub...
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In recent decades, the real-space finite-difference implementations of Kohn–Sham density functional theory have exhibited substantial improvements in computational efficiency for large-scale systems. However, the substantial memory consumption arising from the numerous grid points has begun to limit the widespread adoption of this method. In this study, a general method is presented—applicable to both periodic and Dirichlet boundary conditions—to reduce the number of real-space grids. This approach introduces a truncation of the real-space grids based on atomic positions, which reduces memory requirements and enables a more efficient real-space scheme tailored for simulating low-dimensional and porous materials with uneven spatial distributions. By testing the method on zero-dimensional clusters, one-dimensional tubes, two-dimensional clusters adsorbed on graphene, and three-dimensional metal-organic framework materials, a 30–73% reduction in grid points and a 36–71% reduction in computational time per step are observed for simulations with a 2 meV/atom energy difference.
Bell Labs was eager to apply evolving computing technologies and electronics to the Bell System, particularly for enabling the Bell System to be able to handle the rapidly increasing demands on the telephone network. ...
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Bell Labs was eager to apply evolving computing technologies and electronics to the Bell System, particularly for enabling the Bell System to be able to handle the rapidly increasing demands on the telephone network. By the mid-1940s and into the 1950s, Bell Labs had begun multiple efforts to develop electronic switching. In the late 1940s, the Switching Research group led by Deming Lewis was investigating the use of pulse code modulation (PCM) as a way of digitizing speech and building systems to leverage electronics not only for the control systems but for the switching fabric as well, particularly in the Experimental Solid State Exchange (ESSEX) [6], [23]. With the transistor's invention in 1947, there was an eagerness to apply this technology once it became reliable enough to replace vacuum tubes, which were considered less reliable and more power hungry than relays.
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