Toyota

About: Toyota is a company organization based out in Safenwil, Switzerland. It is known for research contribution in the topics: Internal combustion engine & Battery (electricity). The organization has 40032 authors who have published 55003 publications receiving 735317 citations. The organization is also known as: Toyota Motor Corporation & Toyota Jidosha KK.

Capture Lithium in αMnO2: Insights from First Principles

Abstract: Here we report the study of Li and Li oxides insertion in αMnO2 with first-principles density functional theory calculations. For Li insertion, the redox reaction is characterized with a particular order of the reduction of Mn ions. It induces asymmetric changes of lattice parameters through Jahn–Teller distortion of MnO6 units. At composition of LiMn2O4, the ratio between lattice parameter a and b extends to the highest value, 1.19. The severe structural deformation is concluded to be the major cause of the irreversible capacity when αMnO2 is used as Li-ion battery cathodes. On the other hand, the structure of αMnO2 is stable to reversibly insert and remove Li oxides. Li oxides inserted αMnO2 is half metallic instead of insulating. On the basis of our results, a mechanism is proposed to explain the role of αMnO2 in the catalyzed decomposition of Li2O2. The key step in this mechanism is the insertion of Li oxides in αMnO2. The insertion transfers electrons from Li oxides to MnO2 and partially oxidized Li ...

Parts supply instruction apparatus

Abstract: The parts supply instruction apparatus includes a production schedule system, a parts information system, a car information system, and an order issue managing system which are preferably located at an assembly factory. The order issue managing system scans a parts master file and extracts required data therefrom relating to parts to be ordered to produce order issue data. The order issue data is sent to a received order managing system which is located at a parts supply factory. The type of parts supply order system operated by the apparatus can be changed between the production schedule system, the part information system and the car information system merely by changing a designation parameter corresponding to a respective system, inserted in an order type column of the parts master file.

Learning to Zoom: a Saliency-Based Sampling Layer for Neural Networks

Abstract: We introduce a saliency-based distortion layer for convolutional neural networks that helps to improve the spatial sampling of input data for a given task Our differentiable layer can be added as a preprocessing block to existing task networks and trained altogether in an end-to-end fashion The effect of the layer is to efficiently estimate how to sample from the original data in order to boost task performance For example, for an image classification task in which the original data might range in size up to several megapixels, but where the desired input images to the task network are much smaller, our layer learns how best to sample from the underlying high resolution data in a manner which preserves task-relevant information better than uniform downsampling This has the effect of creating distorted, caricature-like intermediate images, in which idiosyncratic elements of the image that improve task performance are zoomed and exaggerated Unlike alternative approaches such as spatial transformer networks, our proposed layer is inspired by image saliency, computed efficiently from uniformly downsampled data, and degrades gracefully to a uniform sampling strategy under uncertainty We apply our layer to improve existing networks for the tasks of human gaze estimation and fine-grained object classification Code for our method is available in: http://githubcom/recasens/Saliency-Sampler