Results 151 to 160 of about 5,336 (287)

Automated Multi-Type Pavement Distress Segmentation and Quantification Using Transformer Networks for Pavement Condition Index Prediction

Pavement distress detection is a crucial task when assessing pavement performance conditions. Here, a novel deep-learning method based on a transformer network, referred to as ISTD-DisNet, is proposed for multi-type pavement distress semantic ...
Yangyang Zhuang, Zaiyan Zhang, Weidong Song, Jiachen Wu, Bing Zhang   +4 more
core   +1 more source

Dual-Layer Fusion Model Using Bayesian Optimization for Asphalt Pavement Condition Index Prediction. [PDF]

Sensors (Basel)
Hao J, Sun Z, Xing Z, Pei L, Feng X.
europepmc   +1 more source

Using Pavement Condition Index to Evaluate the Condition of Flexible and Rigid Pavements

Eurasian Journal of Science and Engineering, 2019
openaire   +1 more source

New‐Era Polymer Thermoelectrics: Material Innovations, Doping Frontiers, Decoupling Strategies, and Unconventional Applications

Advanced Materials, EarlyView.
The field of polymer thermoelectrics is entering a new era, featuring breakthroughs in addressing the conventional performance disparity between p‐type and n‐type polymers, pioneering doping frontiers, and sophisticated decoupling strategies. This review explores innovations in molecular design and superior stabilities, bridging the gap from ...
Suhao Wang
wiley   +1 more source

Automated Pavement Condition Index Assessment with Deep Learning and Image Analysis: An End-to-End Approach. [PDF]

Sensors (Basel)
Ibragimov E, Kim Y, Lee JH, Cho J, Lee JJ.   +4 more
europepmc   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Machine learning approaches for predicting preventive maintenance costs of expressways in Xinjiang. [PDF]

PLoS One
Jia C, An J, Ma S, Dai X.
europepmc   +1 more source

Clustomesogen Showing Sub‐Zero Liquid Crystal Properties: Supramolecular Assembly Between Cs2[Mo6Ii8(OCOC2F5)6] and Hexaethylenoxide Containing Mesogenic Dimers

Advanced Materials, EarlyView.
Associating a red‐NIR phosphorescent octahedral hexanuclear molybdenum cluster compound with hexaethyleneoxide chains bearing mesogenic units on both ends leads to an emissive hybrid liquid crystal showing mesomorphism on a very unusual temperature range down to −25°C.
Killiann Heinz, Jeanne Rebours, Zoulikha Zerrouqi, Noée Dumait, Maria Amela‐Cortes, Nikolai Scheuring, Sara Simonovska, Sebastian Marino, Max Ebert, Stéphane Cordier, Sabine Laschat, Yann Molard   +11 more
wiley   +1 more source

Intelligent pavement management: a machine learning framework for condition classification and maintenance prioritization. [PDF]

Sci Rep
Gupta B, Agrawal M, Narooka P, Panwar D, Anand S.   +4 more
europepmc   +1 more source

Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics

Advanced Materials, EarlyView.
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair, Hrisheekesh Thachoth Chandran, Karl Leo, Hans Kleemann   +3 more
wiley   +1 more source