With the continuous improvement and rapid growth of meteorological service informatization, it is very necessary to apply real-time meteorological data (MD) processing to meteorological information business. In the er...
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Random drift is the main factor affecting the accuracy of MEMS accelerometers. Aiming at the problem that previous methods are brutal to suppress the random drift of MEMS accelerometers effectively, this paper propose...
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Workplace safety is crucial across all industries, particularly in dynamic environments like construction and road infrastructure. The application of computer vision holds promise in enhancing safety measures by autom...
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Are Renko charts suitable for algorithmic trading? What are their advantages and disadvantages? How can they be represented for convolutional neural networks (CNNs)? We contrast a classical trading approach (Renko cha...
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Academic and non-academic research institutes are the two key global sectors that are accomplishing the research agenda. This paper focuses on the implications of using AI tools in academic research. Academic institut...
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This paper investigates the effect of switch studying on clinical photo segmentation performance. Switch learning entails the usage of a pre-trained model as the basis for a new technique for a comparable project. By ...
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Edge computing requires low-power, real-time processing of complex information. Spiking neural networks are highly expected to be applied to edge computing due to their efficient computing properties. Here, we design ...
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ISBN:
(纸本)9798350359329;9798350359312
Edge computing requires low-power, real-time processing of complex information. Spiking neural networks are highly expected to be applied to edge computing due to their efficient computing properties. Here, we design a mixed-signal LSI consisting of an analog spiking neural network and digital inference circuits for edge device. The two-variable spiking neuron circuits operate in an analog manner using the physical properties of transistors and are connected through synaptic circuits to form a network. The neural network successfully operates and exhibits complex nonlinear behavior in response to external inputs. The power consumption of the spike generation is as low as tens of femtojoules per spike because the transistors in the circuits operate in the subthreshold region, which is enough to be used as edge computing devices. In addition, a digital circuit was designed to perform real-time inference using the spiking sequences from the analog spiking neural network. The result showed that the mixed-signal LSI consisting of the analog spiking neural network and the digital inference circuits can be applied to the spoken digit classification task in real time. The proposed system has the potential to be used as ultra-low-power neuromorphic hardware in practical applications.
This technical abstract provides a comprehensive observation of the system studying strategies for intrusion detection in network protection. Various tactics are discussed, along with supervised getting-to-know, unsup...
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Cloud SCM significantly benefits companies across industries by revealing its impact on business operations. Data collected facilitates management in devising solutions to enhance financial performance. Despite its in...
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ISBN:
(纸本)9798400717260
Cloud SCM significantly benefits companies across industries by revealing its impact on business operations. Data collected facilitates management in devising solutions to enhance financial performance. Despite its innovative functionalities, there has been a lack of study that examines the actual utilization of cloud SCM. The research evaluated enterprise-wide factors that could potentially affect the financial performance of manufacturing companies in Laguna, Philippines. Hence, the study employed quantitative causal research to evaluate cloud SCM usage and performance, considering technological, organizational, and environmental factors as adapted from TOE framework. The study also determined the mediating effect of information sharing between the significant correlation between cloud computing in SCM and financial performance. Results were analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) with WarpPLS 8.0 software. Non-probability purposive sampling was used to yield 80 respondents through online survey dissemination, surpassing the required 70 based on initial priori power analysis. The participants compromised Mal-lagers in finance and accounting roles working in manufacturing companies located on specific cities of Laguna, Philippines. Findings indicate significant relationships among hypotheses, except for H2 and H7, suggesting no significant relationship between financial performance and cloud SCM complexity, and no significant mediation effect of information sharing on the relationship between cloud computing in SCM and financial performance.
This study solves the problem of data fusion caused by multi-source and cross-domain power business data, proposes a cross-domain computing capability model for the entire network based on the data middle platform, re...
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