A powertrain is adapted to drive ground-engaging elements disposed along longitudinally-opposing sides of a vehicle. The powertrain includes at least one engine, a first electric machine, a second electric machine, a third electric machine, a first differential mechanism and a second differential ...
FD uses online courses to train 350 employees and external suppliers entering its facility on health and safety best practices. Using iSpring Suite, FD creates safety training courses in-house, reducing warehouse accidents by 50%. A screenshot from one of the compliance courses created with iSp...
Pretrained neural network models for biological segmentation can provide good out-of-the-box results for many image types. However, such models do not allow users to adapt the segmentation style to their specific needs and can perform suboptimally for te
This study uses the NLS Mature Women's Cohort to examine labor market effects of education and training on women at pre-retirement ages, comparing training methods: formal education, on-the-job training, and other training. Results show that younger, more educated women tend to train more than...
Reducing inrush current when transformer in electric vehicle is connected to power A method of controlling connection of a transformer of an electric vehicle, such as a train locomotive, to an alternating voltage supply carried by a trolley wire, the object being to reduce the transformer inrush...
While the power of deep learning has been illustrated in various imaging modalities including MSI38,39,40, our method exploits unique signal characteristics in FTMS data and a special network design. Instead of training a deep neural network to generate high-resolution mass spectra from a low-...
Using the scriptexample_train_script.shto train various KD methods. You can simply specify the hyper-parameters listed intrain_xxx.pyor manually change them. The hyper-parameters I used can be found in thetraining logs(code: ezed).
Traditional classifiers use only labeled data (feature / label pairs) to train. Labeled instances however are often difficult, expensive, or time consuming to obtain, as they require the efforts of experienced human annotators. Meanwhile unlabeled data may be relatively easy to collect, but there ...
Subsequently, machine learning algorithms were employed to train and analyze this data, with the aim of uncovering the influence of these different factors on the fatigue status of medical security personnel. The analysis reveals that GBM with the gradient descent method, used to adjust sample ...
While these phenomena can happen under different conditions, they both mean that an exponential number of circuit evaluations can be needed to train and make use of these models. Therefore, aside from the considerations made in this work, emphasis should also be placed on avoiding these obstacles...