The present paper proposes a crew workload analysis method of berthing operation. The method helps identifying the cause of crew workload variation based on the analysis of multiple data obtained from berthing operation. It consists of mental workload analysis, crew behavior analysis and ship movement analysis. Mental workload is estimated from heart rate variability measured by physiological sensor. Crew behavior is recorded by handy and fixed video cameras to analyze frequency of behavior and response time. Ship movement is measured with two GPS receivers to calculate turning and distance to pier. Based on these data, mental workload is compared with other measures. The method is applied to three berthing operations and the causes of workload change during berthing operation are partly cleared.

Models based on Artificial Neural Networks (ANN) have been developed for predicting ship motions using the information about the wave field around the ship and historical time-series of motions. The ANN models developed in this study were able to predict all six degrees of freedom ship motions in irregular wave conditions with different significant waveheight, peak period and wave directions along with directional spreading. Preparation of training, validation and test datasets has been described along with the development and training of ANNs. The models were tested using the observed wave conditions recorded by a wave radar installed onboard the ship. A physics-based approach has been applied when selecting the length of input and output data. The effect of input and output window length on the accuracy of results was further studied by developing two sets of ANNs with different length of input and output window. Performance of both sets of ANNs on training, validation and test datasets has been presented along with detailed investigation on test dataset. Reducing the length of input window and increasing the length of output window was seen to reduce the accuracy of prediction.

No abstract

The spin angular momentum of light can induce the orbital rotation of matter via spin-orbit angular momentum conversion. In this work, we demonstrate the orbital rotation of nanoparticles using two different physical mechanisms. First, a nanoscale Poynting vector vortex is created above the nanogap of a plasmonic trimer nanoantenna upon circularly polarized laser irradiation. Using these trimer nanotweezers, single fluorescent nanodiamond trapping and rotation is experimentally achieved. Second, the orbital rotation of VO2 nanoparticles is achieved using a focused, circularly polarized Gaussian laser beam. We demonstrate that the non-linear optical response caused by the insulator-to-metal phase transition of VO2 leads to the formation of an annular trapping potential well around the center of the laser beam.

No abstract