Results 221 to 230 of about 99,612 (292)

Robotics‐assisted acoustic surveys could deliver reliable, landscape‐level biodiversity insights

Remote Sensing in Ecology and Conservation, EarlyView.
Deploying and maintaining sensors is often a major bottleneck in collecting rapid biodiversity data. We tested whether autonomous hopping drones equipped with acoustic recorders could collect reliable biodiversity data in Costa Rica. Using 26,000+ hours of existing audio from 341 sites, with machine learning detections of 19 bird species and spider ...
Peggy A. Bevan, Cristina Banks‐Leite, Mirko Kovac, Jenna Lawson, Lorenzo Picinali, Sarab S. Sethi   +5 more
wiley   +1 more source

Short term demand forecasting of electric vehicle charging stations using context aware temporal transformer model. [PDF]

Sci Rep
Hussain A, Lu QC, Rizvi SS, Wang S, Kwon SJ.   +4 more
europepmc   +1 more source

Large‐scale characterization of horizontal forest structure from remote sensing optical images

Remote Sensing in Ecology and Conservation, EarlyView.
Sub‐meter resolution remote sensing data and tree crown segmentation techniques hold promise in offering detailed information that can support the characterization of forest structure from a horizontal perspective, offering new insights in the tree crown structure at scale.
Xin Xu, Martin Brandt, Xiaowei Tong, Maurice Mugabowindekwe, Yuemin Yue, Sizhuo Li, Qiue Xu, Siyu Liu, Florian Reiner, Kelin Wang, Zhengchao Chen, Yongqing Bai, Rasmus Fensholt   +12 more
wiley   +1 more source

Deep learning predicts real-world electric vehicle direct current charging profiles and durations. [PDF]

Nat Commun
Li S, Zhang M, Doel R, Ross B, Piggott MD.   +4 more
europepmc   +1 more source

Beyond 5G and Non‐terrestrial Network (NTN) Integrated Architecture: Access Challenges for Expanding Artificial Intelligence of Things (AIoT)

International Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT This study analyzes the architecture of the beyond 5G‐NTN (Non‐terrestrial Network) integrated network and presents the technical, legal, and regulatory challenges and considerations for expanding the Artificial Intelligence of Things (AIoT) ecosystem.
Byung Woon Kim, Ga Eun Choi
wiley   +1 more source

Lightweight machine learning framework using temporal features for electric vehicle demand response forecasting on edge devices. [PDF]

Sci Rep
Durrani AM, Asar AU, Aziz A, Khan W, Yousaf MZ, Anjam F, Farooq U, Abdullah M, Shabaz M.   +8 more
europepmc   +1 more source

Determinants of Circular Economy Participation Among Gen Z in a Sun‐and‐Beach Destination: A Theory of Planned Behavior Approach

Sustainable Development, EarlyView.
ABSTRACT Using the Theory of Planned Behavior, this study examines the determinants influencing Generation Z in adopting circular practices when traveling as tourists, focusing on 300 respondents from Majorca. Employing a PLS‐SEM framework, the research evaluates the influence of TPB factors on circular economy participation and investigates the impact
Marta Jacob, Ana Domínguez‐Quintero, Carmen Florido, Margarita Payeras   +3 more
wiley   +1 more source

Optimizing EV charging stations and power trading with deep learning and path optimization. [PDF]

PLoS One
Zhu Q.
europepmc   +1 more source

Wafer‐Scale Self‐Limiting Epitaxy of Bernal‐Stacked Single‐Crystal Boron Nitride

Small, EarlyView.
Wafer‐scale, single‐crystal Bernal‐stacked boron nitride (bBN) bilayers are grown by flow‐modulated MOCVD, where monoatomic Ni step edges on Ni(111) deterministically direct AB stacking. As an ultrathin interlayer, bBN suppresses interfacial scattering and enables robust, nonvolatile polarization switching in MoS2 channels, offering a scalable platform
Jaewon Wang, Hyeonwoo Lee, Jaemin Kim, Haeng Un Yeo, Cheol Hwan Yoon, Min Seok Yoo, Junseop Noh, Sora Jang, Ju‐Hyoung Han, Juwon Han, Jaeeun Park, Young Ho Jin, Huijun Han, Kitae Park, Joonki Suh, Tae‐Sik Yoon, Seunguk Song, Minsu Seol, Chanyong Hwang, Hyung‐Joon Shin, Zonghoon Lee, Changwook Jeong, Soon‐Yong Kwon   +22 more
wiley   +1 more source

Analyzing Mega-mobility Systems in Smart Cities: A Macro-Micro Integration with Feedback Paradigm Empowered by Artificial Intelligence. [PDF]

Research (Wash D C)
Wang Z, Cheng Q, Gu Z, Liu C, Cun D, Shi X, Wu X, Zhou Z, He X, Vlacic L, Liu Z.   +10 more
europepmc   +1 more source