Currently, rapid and accurate prediction of targeting expression of a fluorescent protein tagged fusion protein remains a great challenge. Molecular docking simulation methods have been widely used to predict molecula...
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Emerging cross-point memory can in-situ perform vector-matrix multiplication (VMM) for energy-efficient scientific computation. However, parasitic-capacitance-induced row charging and discharging latency is a major pe...
ISBN:
(纸本)9798350323481
Emerging cross-point memory can in-situ perform vector-matrix multiplication (VMM) for energy-efficient scientific computation. However, parasitic-capacitance-induced row charging and discharging latency is a major performance bottleneck of subarray VMM. We propose a memory-timing-compliant bulk VMM processing-using-memory design with row access and column access co-optimization from rethinking of read access commands and μ-op timing. We propose row-level-parallelism-adaptive timing termination mechanism to reduce tail latency of tRCD and tRP by exploiting row nonlinear charging and bulk-interleaved row-column-cooperative VMM access mechanism to reduce tRAS and overlap CL without increasing column ADC precision. Evaluations show that our design can achieve 5.03× performance speedup compared with an aggressive baseline.
Emission forecasts can be an important way of creating awareness among the public and decision-makers on solving environmental problems. The main goal of this study is to forecast and compare the transport CO2 emissio...
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Emission forecasts can be an important way of creating awareness among the public and decision-makers on solving environmental problems. The main goal of this study is to forecast and compare the transport CO2 emissions of the Philippines using four different forecasting models. We use the models of Holt-Winters Exponential Smoothing, Autoregressive Integrated Moving Average (ARIMA), Vector Autoregressive (VAR), and the Artificial Neural Network (ANN). The performance of the different forecasting methods was compared using the coefficient of determination (R2) and the root mean squared error (RMSE) values. Several economic variables from 1990 to 2019 and the transport Carbon Dioxide (CO2) emissions in the Philippines were utilized in this study. The result show that all four methods exhibit goodness of fit and accuracy results according to the statistical measures. In comparison, the multivariate methods (ANN & VAR) performed better than univariate methods (ARIMA & Holt-Winters).
In order to bolster the next generation of wireless networks, there has been a great deal of interest in non-terrestrial networks (NTN), including satellites, high altitude platform stations (HAPS), and uncrewed aeria...
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Heterogeneity in federated learning (FL) is a critical and challenging aspect that significantly impacts model performance and convergence. In this paper, we propose a novel framework by formulating heterogeneous FL a...
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Recently, scene text detection has received significant attention due to its wide applications. Accurate detection in complex scenes of multiple scales, orientations, and curvature remains a challenge. Component-based...
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Mobile edge computing (MEC) mitigates the energy and computation burdens on mobile users (MUs) by offloading tasks to the network edge. To optimize MEC server utilization through effective resource allocation, a well-...
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Given the ubiquity of streaming data, online algorithms have been widely used for parameter estimation, with second-order methods particularly standing out for their efficiency and robustness. In this paper, we study ...
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Industrial Internet of Things (IIoT) plays a crucial role in advancing smart manufacturing by connecting numerous devices, enabling data exchanges, and supporting industrial applications. Yet, the timely and proper sc...
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