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Found 26 papers, 4 papers with code
Collaborative Reinforcement Learning Based Unmanned Aerial Vehicle (UAV) Trajectory Design for 3D UAV Tracking
Meanwhile, since the accuracy of the distance estimation depends on the signal-to-noise ratio of the transmission signals, the active UAV must optimize its transmit power.
Importance-Aware Image Segmentation-based Semantic Communication for Autonomous Driving
Therefore, we propose a vehicular image segmentation-oriented semantic communication system, termed VIS-SemCom, where image segmentation features of important objects are transmitted to reduce transmission redundancy.
Attention-based UNet enabled Lightweight Image Semantic Communication System over Internet of Things
To make it affordable for IoT devices to deploy semantic communication systems, we propose an attention-based UNet enabled lightweight image semantic communication (LSSC) system, which achieves low computational complexity and small model size.
Base Station Beamforming Design for Near-field XL-IRS Beam Training
However, this approach may cause degraded beam training performance in practice due to the near-field channel model of the BS-IRS link.
Digital Over-the-Air Federated Learning in Multi-Antenna Systems
The PS, acting as a central controller, generates a global FL model using the received local FL models and broadcasts it back to all devices.
Performance Optimization for Variable Bitwidth Federated Learning in Wireless Networks
Compared to model-free RL, this model-based RL approach leverages the derived mathematical characterization of the FL training process to discover an effective device selection and quantization scheme without imposing additional device communication overhead.
Evolutionary trend of SARS-CoV-2 inferred by the homopolymeric nucleotide repeats
Peculiarly, the HP disparity measure infers that SARS-CoV-2 Omicron variants have a high disparity of HP poly-(A/T) and ploy-(C/G), suggesting a high adaption to the human hosts.
Emerging vaccine-breakthrough SARS-CoV-2 variants
The molecular mechanism underlying such surge is elusive due to 4, 653 non-degenerate mutations on the spike protein, which is the target of most COVID-19 vaccines.
Multi-Factors Aware Dual-Attentional Knowledge Tracing
In this paper, we propose Multi-Factors Aware Dual-Attentional model (MF-DAKT) which enriches question representations and utilizes multiple factors to model students' learning progress based on a dual-attentional mechanism.
Distributed Reinforcement Learning for Age of Information Minimization in Real-Time IoT Systems
In this paper, the problem of minimizing the weighted sum of age of information (AoI) and total energy consumption of Internet of Things (IoT) devices is studied.
Inverted repeats in coronavirus SARS-CoV-2 genome and implications in evolution
The study also reveals that the recent SARS-related coronavirus, SARSr-CoV/RmYN02, has a high amount of inverted repeats in the spike protein gene.
Host immune response driving SARS-CoV-2 evolution
Additionally, we show that children under age five and the elderly may be at high risk from COVID-19 because of their overreacting to the viral infection.
Characterizing SARS-CoV-2 mutations in the United States
Using genotyping, sequence-alignment, time-evolution, $k$-means clustering, protein-folding stability, algebraic topology, and network theory, we reveal that the US SARS-CoV-2 has four substrains and five top US SARS-CoV-2 mutations were first detected in China (2 cases), Singapore (2 cases), and the United Kingdom (1 case).
A Machine Learning Approach for Task and Resource Allocation in Mobile Edge Computing Based Networks
Since the data size of each computational task is different, as the requested computational task varies, the BSs must adjust their resource (subcarrier and transmit power) and task allocation schemes to effectively serve the users.
Decoding asymptomatic COVID-19 infection and transmission
By analyzing the distribution of 11083G>T in various countries, we unveil that 11083G>T may correlate with the hypotoxicity of SARS-CoV-2.
Dinucleotide repeats in coronavirus SARS-CoV-2 genome: evolutionary implications
The special dinucleotide regions in the SARS-CoV-2 genome identified in this study may become diagnostic and pharmaceutical targets in monitoring and curing the COVID-19 disease.
Mutations on COVID-19 diagnostic targets
Effective, sensitive, and reliable diagnostic reagents are of paramount importance for combating the ongoing coronavirus disease 2019 (COVID-19) pandemic at a time there is no preventive vaccine nor specific drug available for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
Decoding SARS-CoV-2 transmission, evolution and ramification on COVID-19 diagnosis, vaccine, and medicine
Tremendous effort has been given to the development of diagnostic tests, preventive vaccines, and therapeutic medicines for coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
Genotyping coronavirus SARS-CoV-2: methods and implications
The emerging global infectious COVID-19 coronavirus disease by novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) presents critical threats to global public health and the economy since it was identified in late December 2019 in China.
Federated Learning for Task and Resource Allocation in Wireless High Altitude Balloon Networks
This problem is posed as an optimization problem whose goal is to minimize the energy and time consumption for task computing and transmission by adjusting the user association, service sequence, and task allocation scheme.
A Joint Learning and Communications Framework for Federated Learning over Wireless Networks
This joint learning, wireless resource allocation, and user selection problem is formulated as an optimization problem whose goal is to minimize an FL loss function that captures the performance of the FL algorithm.
Analysis of Memory Capacity for Deep Echo State Networks
Then, a series architecture ESN is proposed in which ESN reservoirs are placed in cascade that the output of each ESN is the input of the next ESN in the series.
Federated Echo State Learning for Minimizing Breaks in Presence in Wireless Virtual Reality Networks
The proposed algorithm uses concept from federated learning to enable multiple BSs to locally train their deep ESNs using their collected data and cooperatively build a learning model to predict the entire users' locations and orientations.
Information Theory Information Theory
Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial
Next-generation wireless networks must support ultra-reliable, low-latency communication and intelligently manage a massive number of Internet of Things (IoT) devices in real-time, within a highly dynamic environment.
Identification of repeats in DNA sequences using nucleotide distribution uniformity
We present an $\textit{ab initio}$ method to quantitatively detect repetitive elements and infer the consensus repeat pattern in repetitive elements.
A Novel Method for Comparative Analysis of DNA Sequences by Ramanujan-Fourier Transform
To address the different lengths in Euclidean space of RFT coefficients, we pad zeros to short DNA binary sequences so that the binary sequences equal the longest length in the comparison sequence data.
