Automatic Modulation Classification for Adaptive OFDM Systems Using Convolutional Neural Networks With Residual Learning

Automatic modulation classification (AMC) is becoming a promising technique for future adaptive wireless transceiver systems.The existing blind modulation classification (BMC) methods for orthogonal frequency Cylinders, Tanks division multiplexing (OFDM) fail to achieve the required performance by using statistical-based methods.Thus, the modulatio

read more

Synthesis of real world drone signals based on lab recordings

There is a great interest in the generation of plausible drone signals in various applications, e.g.for auralization purposes or the compilation of training data for detection algorithms.Here, MULTITOOL a methodology is presented which synthesises realistic immission signals based on laboratory recordings and subsequent signal processing.The transf

read more

Methotrexate and mucositis: A merry-go-round for oncologists

High-dose methotrexate is the backbone of various regimens for treating lymphoid malignancies.Mucositis is a well-known, dose-related side effect of methotrexate.Prophylactic measures such Microwave Thermistor as folinic acid rescue are useful but do not prevent mucositis in all the cases.Once severe mucositis (WHO Grade IV) sets in, mortality is L

read more

TC10 is regulated by caveolin in 3T3-L1 adipocytes.

TC10 is a small GTPase found in lipid raft microdomains of adipocytes.The protein undergoes activation in response to insulin, and plays a key role in the regulation of glucose uptake by the hormone.TC10 requires high concentrations of magnesium in order to stabilize guanine nucleotide binding.Kinetic analysis of this process revealed that magnesiu

read more

Learning to Fly: A Distributed Deep Reinforcement Learning Framework for Software-Defined UAV Network Control

Control and performance optimization of wireless networks of Unmanned Aerial Vehicles (UAVs) require scalable approaches that go beyond architectures based on centralized network controllers.At the same time, the performance of model-based optimization approaches is often limited by the accuracy of the approximations and relaxations necessary to so

read more