Results 261 to 270 of about 38,248 (315)

Bayesian‐Optimized Dual‐Mode Luminescence‐Based Optical Thermometry Enabled by Negative Thermal Expansion in Lu2(MoO4)3:Yb–Er–Tm Phosphor

Advanced Optical Materials, EarlyView.
A Bayesian optimization framework identifies the ideal composition for Lu2(MoO4)3:Yb–Er–Tm phosphors with minimal experimental trials. By leveraging the host's negative thermal expansion, the material achieves remarkable thermal quenching compensation.
Reiko Furukawa, Takuya Hasegawa, Tong Fang, Saneyuki Ohno, Tomoyo Goto, Yasushi Sato, Ayahisa Okawa, Shu Yin   +7 more
wiley   +1 more source

VEHICLE SPEED DETECTION USING OPENCV FOR INTELLIGENT TRANSPORTATION SYSTEMS

Mrs. S.Subhashini Mrs. S.Subhashini
openalex   +1 more source

Collaborative and Context-Aware Applications for Intelligent and Green Transportation

, 2018
Yingqi Gu
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Intelligent Transportation Systems

IEEE Vehicular Technology Magazine, 2010
The increasing need for mobility has brought about significant changes in transportation infrastructures. Inefficiencies cause enormous losses of time, decrease in the level of safety for both vehicles and pedestrians, high pollution, degradation of quality of life, and huge waste of nonrenewable fossil energy.The scope of this article is to introduce ...
George Dimitrakopoulos 0001, Panagiotis Demestichas   +1 more
openaire   +2 more sources

Intelligent Transportation Systems

IEEE Pervasive Computing, 2006
This issues Works in Progress department features 10 interesting ongoing intelligent transportation systems projects. The first five projects (TIME, Sentient Transport, EVT, DynaCHINA, TrafficView) focus on traffic and vehicular data collection, transmission, and analysis.
Anthony D. Joseph, Alastair R. Beresford, Jean Bacon, David Naveen Cottingham, Jonathan J. Davies, Brian D. Jones, Haitao Guo, Wei Guan, Yong Lin, Houbing Song, Liviu Iftode, Simone Fuchs, Bernhard Lamprecht, Kyandoghere Kyamakya, Jorge González Fernández, Juan Carlos Yelmo García, Yod Samuel Martín García, Jorge de Gracia Santos, Milind Nimesh, Gang Pan 0001, Zhaohui Wu 0001, Qing Wu, Zhenyu Shan, Jie Sun 0003, Jian Lu, Guoqing Yang, Muhammad Khurram Khan, Jiashu Zhang   +27 more
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Future Transportation: Intelligent Vehicles in Intelligent Environment

2007 4th International Symposium on Applied Computational Intelligence and Informatics, 2007
In the paper there the structure and build-up of transportation systems, their development, and especially, the needs established by the society that motivate the continuous expansion of such systems will be outlined. The development is determined by the four participants ("components") of these systems, namely by the human beings, vehicles ...
László Nádai, Roland Kovács
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Vectus—Intelligent Transport

Proceedings of the IEEE, 2009
Personal Rapid Transit (PRT) is a transportation concept with small vehicles on a low weight structure, that combines many of the best aspects of today's urban public transport, and packages them together with unparalleled service and lower total cost of ownership.
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RHODES to intelligent transportation systems

IEEE Intelligent Systems, 2005
To help fulfill the promises of ITS (intelligent transportation system), the ATLAS (Advanced Traffic and Logistics Algorithms and Systems) research center is developing and testing the RHODES (real-time hierarchical optimized distributed effective system) traffic control system.
Pitu B. Mirchandani, Fei-Yue Wang 0001
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RoadEye — The Intelligent Transportation System

2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA), 2017
RoadEye is an intelligent transportation system project that will solve many traffic problems and make traffic safer. RoadEye is a system that will be able to detect weather conditions, maintain a safe distance and fixed speeds between vehicles. The proposed project implements a vehicle-to-vehicle-to-infrastructure system.
Mennatallah Ibrahim, Mark Riad, Mohammed El-Abd   +2 more
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“ARTIFICIAL INTELLIGENCE IN INTELLIGENT TRANSPORTATION SYSTEMS”

I V H S Journal, 1995
This article gives a brief overview of Artificial Intelligence (AI) and its applications to Intelligent Transportation Systems (ITS). The author defines AI as being a combination of technologies, including knowledge- based expert systems, natural language processing artificial neural networks, fuzzy systems, genetic algorithms learning systems, virtual
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