Channel prediction permits to acquire channel state information(CSI) without signaling overhead. However,almost all existing channel prediction methods necessitate the deployment of a dedicated model to accommodate a ...
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Channel prediction permits to acquire channel state information(CSI) without signaling overhead. However,almost all existing channel prediction methods necessitate the deployment of a dedicated model to accommodate a specific configuration. Leveraging the powerful modeling and multi-task learning capabilities of foundation models, we propose the first space-time-frequency(STF) wireless foundation model(WiFo) to address time-frequency channel prediction tasks in a unified manner. Specifically, WiFo is initially pre-trained over massive and extensive diverse CSI datasets. Then, the model will be instantly used for channel prediction under various CSI configurations without any fine-tuning. We propose a masked autoencoder(MAE)-based network structure for WiFo to handle heterogeneous STF CSI data, and design several mask reconstruction tasks for self-supervised pre-training to capture the inherent 3D variations of CSI. To fully unleash its predictive power, we build a large-scale heterogeneous simulated CSI dataset consisting of 160k CSI samples for *** validate its superior unified learning performance across multiple datasets and demonstrate its state-of-the-art(SOTA) zero-shot generalization performance via comparisons with other full-shot baselines.
In this study, we explore the application of machine learning (ML) models for predicting human immunodeficiency virus (HIV) progression and patient outcomes, aiming to enhance patient-trial matching in clinical trials...
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Skin wounds are often covered with gauze to protect the injury and support the healing process. Accurate wound assessment is essential for monitoring healing progress and guiding treatment decisions. However, existing...
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Learning from unlabeled data or self-learning, can substantially reduce the complexity of machine learning (ML) utilization in real-time deployment. While the development of un/semisupervised algorithms shows promisin...
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This study presents a comprehensive optimization and comparative analysis of thermoelectric(TE)infrared(IR)detec-tors using Bi_(2)Te_(3) and Si *** theoretical modeling and numerical simulations,we explored the impact...
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This study presents a comprehensive optimization and comparative analysis of thermoelectric(TE)infrared(IR)detec-tors using Bi_(2)Te_(3) and Si *** theoretical modeling and numerical simulations,we explored the impact of TE mate-rial properties,device structure,and operating conditions on responsivity,detectivity,noise equivalent temperature difference(NETD),and noise equivalent power(NEP).Our study offers an optimally designed IR detector with responsivity and detectivity approaching 2×10^(5) V/W and 6×10^(9) cm∙Hz^(1/2)/W,*** enhancement is attributed to unique design features,includ-ing raised thermal collectors and long suspended thin thermoelectric wire sensing elements embedded in low thermal conductivity organic materials like ***,we demonstrate the compatibility of Bi_(2)Te_(3)-based detector fabrication pro-cesses with existing MEMS foundry processes,facilitating scalability and ***,for TE IR detectors,zT/κemerges as a critical parameter contrary to conventional TE material selection based solely on zT(where zT is the thermoelec-tric figure of merit andκis the thermal conductivity).
A significant fraction of the world’s population is living in cities. With the rapid development ofinformation and computing technologies (ICT), cities may be made smarter by embedding ICT intotheir infrastructure. B...
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A significant fraction of the world’s population is living in cities. With the rapid development ofinformation and computing technologies (ICT), cities may be made smarter by embedding ICT intotheir infrastructure. By smarter, we mean that the city operation will be more efficient, cost-effective,energy-saving, be more connected, more secure, and more environmentally friendly. As such, a smartcity is typically defined as a city that has a strong integration with ICT in all its components, includingits physical components, social components, and business components [1,2].
In the financial markets, artificial intelligence technology is widely used for stock forecasting. The precision of forecast results and the timing of transactions are crucial. In this paper, ten stocks from the U.S. ...
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The advent of Large Language Models (LLMs) has revolutionized numerous domains, notably education, by offering powerful tools for personalized learning and automated assistance. These models have the potential to sign...
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The success of Internet of Things (IoT) services will be determined by how the security of the IoT devices and the networks to which they are connected can be guaranteed. Integrating biometric recognition technology i...
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