Signal Processing

The performances of ENRZ (Ensemble NRZ) under
the interferences of crosstalk, in conjunction with NRZ (NonReturn-to-Zero), PAM4 (Pulse Amplitude Modulation of 4-level),
and PAM3 are investigated. One-side and two-side crosstalk scenarios with varying levels of crosstalk are studied. The simulated
eye-diagram obtained with the four signaling techniques under
a range of crosstalk levels are compared and the reasons that
lead to the prominent advantages of ENRZ are analyzed. As
an alternative approach of validating the performances of the

The measurement and diagnosis of the severity of failures in rotating machines allow the execution of predictive maintenance actions on equipment. These actions make it possible to monitor the operating parameters of the machine and to perform the prediction of failures, thus avoiding production losses, severe damage to the equipment, and safeguarding the integrity of the equipment operators. This paper describes the construction of a dataset composed of vibration signals of a rotating machine.

This dataset consists of the training and the evaluation datasets for the LiDAR-based maritime environment perception presented in our journal publication "Maritime Environment Perception based on Deep Learning." Within the datasets, LiDAR raw data are processed using Deep Neural Networks (DNN). In the training dataset, we introduce the method for generating training data in Gazebo simulation. In the evaluation datasets, we provide the real-world tests conducted by two research vessels, respectively.

Map of the system's operating area. Note: access roads in black.