Network-on-Chip (NoC) offers a promising solution for on-chip communication in highly integrated System-on-Chips (SoCs). NoCs can be designed with either regular or application-specific network topologies. While regul...
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Chiplet-based systems have become prominent in large Systems-on-Chips (SoCs) as a means to mitigate increasing design costs. However, the integration of multiple chiplets introduces new challenges in the interconnecti...
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Marginal defects, such as high-resistance short or low-resistance open defects, are hard to detect by conventional pass-fail test methods because their manifestations are practically indistinguishable from the effects...
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Stochastic computing (SC) provides low-area, power-efficient hardware solutions suitable for edge systems, but its scalability poses challenges due to its precision limitations, especially in noisy environments. This ...
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Approximate computing allows designers to trade-off precision with hardware cost and power consumption. The possible degree of approximation relies on a realistic quality assessment with functional input sequences and...
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System-Level Test (SLT) is essential for testing integrated circuits, focusing on functional and non-functional properties of the Device under Test (DUT). Traditionally, test engineers manually create tests with comme...
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Memristive crossbars are attractive for in-memory computing due to their integration density combined with compute and storage capabilities of their basic devices. However, yield and fidelity of emerging memristive te...
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While memristive devices are highly attractive as memory cells, they are also capable of performing computations, paving the way to futuristic in-memory computing architecture. Several memristive logic families have b...
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Device-to-Device (D2D) communication maneuvers the proximity services for flexible communication between two nearby devices. It provides high data rates and enhances the spectral and energy efficiency of the D2D commu...
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Pedestrian wind flow is a critical factor in designing livable residential environments under growing complex urban *** pedestrian wind flow during the early design stages is essential but currently suffers from ineff...
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Pedestrian wind flow is a critical factor in designing livable residential environments under growing complex urban *** pedestrian wind flow during the early design stages is essential but currently suffers from inefficiencies in numerical *** learning,particularly generative adversarial networks(GAN),has been increasingly adopted as an alternative method to provide efficient prediction of pedestrian wind ***,existing GAN-based wind flow prediction schemes have limitations due to the lack of considering the spatial and frequency characteristics of wind flow *** study proposes a novel approach termed SFGAN,which embeds spatial and frequency characteristics to enhance pedestrian wind flow *** the spatial domain,Gaussian blur is employed to decompose wind flow into components containing wind speed and distinguished flow edges,which are used as the embedded spatial *** information of wind flow is obtained through discrete wavelet transformation and used as the embedded frequency *** spatial and frequency characteristics of wind flow are jointly utilized to enforce consistency between the predicted wind flow and ground truth during the training phase,thereby leading to enhanced *** results demonstrate that SFGAN clearly improves wind flow prediction,reducing Wind_MAE,Wind_RMSE and the Fréchet Inception Distance(FID)score by 5.35%,6.52%and 12.30%,compared to the previous best method,*** also analyze the effectiveness of incorporating the spatial and frequency characteristics of wind flow in predicting pedestrian wind *** reduces errors in predicting wind flow at large error intervals and performs well in wake regions and regions surrounding *** enhanced predictions provide a better understanding of performance variability,bringing insights at the early design stage to improve pedestrian wind *** proposed spatial-frequen
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