A reply network was extracted from the data set, and exponential random graph models were used to discover patterns of information exchange and social support from the network. Results: Results showed ...
Timothy Li is a consultant, accountant, and finance manager with an MBA from USC and over 15 years of corporate finance experience. Timothy has helped provide CEOs and CFOs with deep-dive analytics, ...
Abstract: Two-step linear-exponential architectures can be applied to incremental ADCs (IADC) to achieve high resolution. In the first step, the ADC works as a normal first-order IADC while, in the ...
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Abstract: Graph signal processing (GSP) is a prominent framework for analyzing signals on non-Euclidean domains. The graph Fourier transform (GFT) uses the combinatorial graph Laplacian matrix to ...
AI encompasses machine learning, natural language processing, and computer vision. It enables systems to learn from data, make predictions, and automate tasks. Examples include: Predictive analytics ...
Graphs of exponential functions and logarithmic functions provide a visual insight into their properties, such as growth, decay, and the inverse relationship between them. Graphs of exponential ...
Exponential and logarithmic functions are mathematical concepts with wide-ranging applications. Exponential functions are commonly used to model phenomena such as population growth, the spread of ...
The Slope Game is similar to the Slope Unblocked game. The goal of this game is also the same. You have to control the rolling ball on an infinite slope and protect it from colliding with the ...
It is 70 years since AT&T’s Bell Labs unveiled a new technology for turning sunlight into power. The phone company hoped it could replace the batteries that run equipment in out-of-the-way places. It ...
Graph Transformers (GTs) have successfully achieved state-of-the-art performance on various platforms. GTs can capture long-range information from nodes that are at large distances, unlike the local ...
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