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Institution

Toyota

CompanySafenwil, Switzerland
About: Toyota is a company organization based out in Safenwil, Switzerland. It is known for research contribution in the topics: Internal combustion engine & Exhaust gas. 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.


Papers
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Patent
17 Oct 1973
TL;DR: In this article, a sodium-sulfur storage battery having as part of its sulfur electrode a porous current collector formed of knitted or woven carbon or graphite yarn of high elastic modulus and tensile strength is described.
Abstract: A sodium-sulfur storage battery having as part of its sulfur electrode a porous current collector formed of knitted or woven carbon or graphite yarn of high elastic modulus and tensile strength so as to yield greater mobility of sodium polysulfide (Na2Sx) within the current collector Also, highly improved current collecting function is attained by virtue of use of knitted or woven yarn, and excellent corrosion resistance and high mechanical strength is attained by virtue of the use of carbon yarn of high elastic modulus and tensile strength, resulting in a storage battery having excellent discharge performance and durability

97 citations

Journal ArticleDOI
TL;DR: Particulate TiC-reinforced aluminum composite specimens were processed by compacting a mixture of titanium, carbon, and aluminum powders into preforms that were infiltrated with molten aluminum and subsequently heated in a differential thermal analyzer to about 1573 K under argon atmosphere as mentioned in this paper.
Abstract: Particulate TiC-reinforced aluminum composite specimens were processed by compacting a mixture of titanium, carbon, and aluminum powders into preforms that were infiltrated with molten aluminum and subsequently heated in a differential thermal analyzer to about 1573 K under argon atmosphere. The onset of formation of TiC particles began at about 1150 K by reaction of TiAl3 with Al4C3. Subsequent formation of TiC particles at higher temperatures to approx-imately 1265 K occurred by direct reaction of carbon with TiAl3. Above this temperature, the TiC particles coarsened with increasing temperature from an initial size of about 0.15μm. TiC particles were also produced in preforms that were not infiltrated; however, the presence of liquid aluminum in infiltrated specimens inhibited particle agglomeration and sintering. Infil-trated preforms could, therefore, serve as excellent "master alloys" for subsequent dilution in an aluminum melt and processing of metal-matrix composites (MMCs) reinforced with sub-micron TiC particulates.

97 citations

Proceedings ArticleDOI
27 Oct 2019
TL;DR: This paper introduces a large real-world video dataset for activities of daily living: Toyota Smarthome, and proposes a pose driven spatio-temporal attention mechanism through 3D ConvNets that outperforms state-of-the-art methods on benchmark datasets, as well as on the ToyotaSmarthome dataset.
Abstract: The performance of deep neural networks is strongly influenced by the quantity and quality of annotated data. Most of the large activity recognition datasets consist of data sourced from the web, which does not reflect challenges that exist in activities of daily living. In this paper, we introduce a large real-world video dataset for activities of daily living: Toyota Smarthome. The dataset consists of 16K RGB+D clips of 31 activity classes, performed by seniors in a smarthome. Unlike previous datasets, videos were fully unscripted. As a result, the dataset poses several challenges: high intra-class variation, high class imbalance, simple and composite activities, and activities with similar motion and variable duration. Activities were annotated with both coarse and fine-grained labels. These characteristics differentiate Toyota Smarthome from other datasets for activity recognition. As recent activity recognition approaches fail to address the challenges posed by Toyota Smarthome, we present a novel activity recognition method with attention mechanism. We propose a pose driven spatio-temporal attention mechanism through 3D ConvNets. We show that our novel method outperforms state-of-the-art methods on benchmark datasets, as well as on the Toyota Smarthome dataset. We release the dataset for research use.

97 citations

Journal ArticleDOI
TL;DR: In this paper, a high-pressure MH tank with a hydrogen-absorbing alloy with high dissociation pressure and compressed hydrogen was constructed, and the van't Hoff plots showed that the hydrogen capacity changed gradually over many cycles and that after 1000 cycles was 94% of the initial capacity.

97 citations

Patent
Susumu Ukita1
21 Aug 1997
TL;DR: In this paper, a bidirectional boosting converter is placed in a battery circuit, where the main contactor is turned off to disconnect one battery block from another, and contactors are turned on to connect a first battery block to one terminal pair of the BCH.
Abstract: In an electric motor vehicle, a bidirectional boosting converter is placed in a battery circuit. A main contactor is turned off to disconnect one battery block from another and contactors are turned on to connect a first battery block to one terminal pair of the bidirectional boosting converter and to connect a second battery block to another terminal pair of the bidirectional boosting converter. A refreshing discharge of the first battery block or an equalizing charge of the second battery block is performed by boosting output of the first battery block and using this output to charge the second battery block. The boosting direction of the bidirectional boosting converter is changed to perform an equalizing charge of the first battery block or a refreshing discharge of the second battery block. The boosting direction is changed again to balance battery block SOCs, these by eliminating need for a charging device for equalizing charge or a discharging device for refreshing discharge.

97 citations


Authors

Showing all 40045 results

NameH-indexPapersCitations
Derek R. Lovley16858295315
Edward H. Sargent14084480586
Shanhui Fan139129282487
Susumu Kitagawa12580969594
John B. Buse117521101807
Meilin Liu11782752603
Zhongfan Liu11574349364
Wolfram Burgard11172864856
Douglas R. MacFarlane11086454236
John J. Leonard10967646651
Ryoji Noyori10562747578
Stephen J. Pearton104191358669
Lajos Hanzo101204054380
Masashi Kawasaki9885647863
Andrzej Cichocki9795241471
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
202232
2021942
20201,846
20192,981
20182,541