Results 71 to 80 of about 359,562 (287)

Short-term Demand Forecasting for Online Car-hailing Services using Recurrent Neural Networks

, 2019
Short-term traffic flow prediction is one of the crucial issues in intelligent transportation system, which is an important part of smart cities. Accurate predictions can enable both the drivers and the passengers to make better decisions about their ...
Bahrak, Behnam, Mahini, Hamid, Nejadettehad, Alireza   +2 more
core   +1 more source

Expanding Chemical Space of Nucleic Acid Nanoparticles for Tunable Antiviral‐Like Immunomodulatory Responses and Potent Adjuvant Activity

Advanced Functional Materials, EarlyView.
We introduce a nucleic acid nanoparticle (NANP) platform designed to be rrecognized by the human innate immune system in a regulated manner. By changing chemical composition while maintaining constant architectural parameters, we identify key determinants of immunorecognition enabling the rational design of NANPs with tunable immune activation profiles
Martin Panigaj, Hannah S. Newton, Jian Wang, Laxmi Pandey, Yelixza I. Avilla, Phong Nguyen, Morgan Chandler, Justin Halman, Yasmine Radwan, Stephanie Smith, Elijah Edmondson, Simone Difilippantonio, Chelsea Sanders, Bao Tran, Yongmei Zhao, Shaojun Xie, Edward Cedrone, Barry W. Neun, Meni Wanunu, Nikolay V. Dokholyan, Marina A. Dobrovolskaia, Kirill A. Afonin   +21 more
wiley   +1 more source

Golden‐Ratio–Guided Aperiodic Architected Metamaterials with Simultaneously Enhanced Strength and Toughness

Advanced Functional Materials, EarlyView.
Guided by the golden ratio, a class of aperiodic architected metamaterials is introduced to address the intrinsic trade‐off between strength and toughness. By unifying local geometric heterogeneity with global order, the golden‐ratio‐guided aperiodic architecture promotes spatial delocalization of damage tolerence regions, leading to more tortuous ...
Junjie Deng, Xinxin Wang, Ruochao Zhao, Zhendong Li, Kai Liu, Ke Yuan, Jia An, Xinwei Li, Chee Kai Chua, Zhonggang Wang   +9 more
wiley   +1 more source

DDP-GCN: Multi-Graph Convolutional Network for Spatiotemporal Traffic Forecasting

, 2020
Traffic speed forecasting is one of the core problems in Intelligent Transportation Systems. For a more accurate prediction, recent studies started using not only the temporal speed patterns but also the spatial information on the road network through ...
Lee, Kyungeun, Rhee, Wonjong
core  

Global Modeling and Prediction of Computer Network Traffic [PDF]

, 2009
We develop a probabilistic framework for global modeling of the traffic over a computer network. This model integrates existing single-link (-flow) traffic models with the routing over the network to capture the global traffic behavior.
Michailidis, George, Stoev, Stilian A., Vaughan, Joel   +2 more
core  

A MapReduce-based nearest neighbor approach for big-data-driven traffic flow prediction

, 2016
In big-data-driven traffic flow prediction systems, the robustness of prediction performance depends on accuracy and timeliness. This paper presents a new MapReduce-based nearest neighbor (NN) approach for traffic flow prediction using correlation ...
Li, Huaqing, Li, Yantao, Wang, Binfeng, Xia, Dawen, Zhang, Zili   +4 more
core   +1 more source

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Hybrid traffic prediction scheme for intelligent transportation systems based on historical and real-time data

International Journal of Distributed Sensor Networks, 2017
Traffic prediction in smart cities is an essential way for intelligent transportation system. The objective of this article is designing and implementing a traffic prediction scheme which can forecast the traffic flow with high efficiency and accuracy in
Jiaming Xie, Yi-King Choi
doaj   +1 more source

A Combined Deep Learning Method with Attention-Based LSTM Model for Short-Term Traffic Speed Forecasting

Journal of Advanced Transportation, 2020
Short-term traffic speed prediction is a promising research topic in intelligent transportation systems (ITSs), which also plays an important role in the real-time decision-making of traffic control and guidance systems.
Pan Wu, Zilin Huang, Yuzhuang Pian, Lunhui Xu, Jinlong Li, Kaixun Chen   +5 more
doaj   +1 more source

Liquid Crystalline Inverted Lipid Phases and Reverse Micelles in Drug Delivery: From Molecular Design to Therapeutic Potential

Advanced Functional Materials, EarlyView.
Liquid crystalline inverted lipid phases and reverse micelles are self‐assembled lipid nanostructures that enhance the solubility, stability, and delivery of diverse therapeutics. This review integrates their physicochemical principles, formulation strategies, drug loading mechanisms, and biomedical applications, highlighting their growing ...
Numan Eczacioglu, Mulazim Hussain Asim, Soheil Haddadzadegan, Andreas Bernkop‐Schnürch   +3 more
wiley   +1 more source