Results 141 to 150 of about 3,234,615 (293)

Real‐time lithology identification while drilling based on drill cuttings image analysis with ensemble learning

Deep Underground Science and Engineering, EarlyView.
A lithology identification while drilling method was developed, integrating an automated cuttings sampling system, a smart drilling rig, and an ensemble learning model. Underground trials achieved 97.42% accuracy in real‐time identification of cuttings lithology and composition, enhancing hazard management and supporting unmanned drilling technology in
Kun Li, Ting Ren, Ningping Yao, Jon Roberts, Haitao Song, Zhongbei Li, Xueqiu He, Liang Zhao   +7 more
wiley   +1 more source

Marine soundscape forecasting: A deep learning-based approach

Ecological Informatics
Advancements in autonomous monitoring technology over the past decade have led to the widespread use of marine soundscape monitoring to assess marine environments.
Shashidhar Siddagangaiah
doaj   +1 more source

Strengthening urban resilience in China through underground infrastructures management: Addressing global climate challenges with technological solutions

Deep Underground Science and Engineering, EarlyView.
This paper explores how climate‐resilient technologies, such as smart grids, digital twins, and self‐healing materials, can enhance urban resilience. It highlights the urgent need for proactive planning, public‐private collaboration, and data‐driven innovation to future‐proof underground infrastructure amid accelerating climate and urban pressures ...
Kai Chen Goh, Tonni Agustiono Kurniawan, Christia Meidiana, Abdelkader Anouzla, Faissal Aziz, Imran Ali, Joan Cecilia C. Casila, M. Imran Khan, Dongdong Zhang, Meihui Jiang, Mohd Hafiz Dzarfan Othman, Md Munir Hayet Khan, Kasun Kumara Dissanayake   +12 more
wiley   +1 more source

CoopASD: Cooperative Machine Anomalous Sound Detection with Privacy Concerns

GLOBECOM 2024 - 2024 IEEE Global Communications Conference
Machine anomalous sound detection (ASD) has emerged as one of the most promising applications in the Industrial Internet of Things (IIoT) due to its unprecedented efficacy in mitigating risks of malfunctions and promoting production efficiency. Previous works mainly investigated the machine ASD task under centralized settings.
Anbai Jiang, Yuchen Shi, Pingyi Fan, Wei-Qiang Zhang 0001, Jia Liu 0001   +4 more
openaire   +4 more sources

Research progress and current status of dynamic wave propagation characteristics in rock mass: A review

Deep Underground Science and Engineering, EarlyView.
This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu, Tao Li, Ruiqi Yuan, Yue Li, Bingni Wu, Bo Liu, Zhengding Deng, Galindo Rubén, Fausto Molina‐Gómez   +8 more
wiley   +1 more source

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source

Exponentially‐constrained Gaussian mixture model for quantifying vertical development of water‐conducting fracture zones in lithologically stratified mining roofs

Deep Underground Science and Engineering, EarlyView.
This study proposes an exponentially‐constrained Gaussian mixture model (EcGMM) to quantify vertical fracture heterogeneity in stratified roof strata. The model integrates a piecewise exponential decay term capturing global stress dissipation with Gaussian components representing localized fracture intensification at lithological interfaces.
Huiqing Yuan, Zhimin Xu, Weixiao Chen, Chenghang Zhang, Shijie Xiong, Yajun Sun   +5 more
wiley   +1 more source

Elementary Steps of Energy Conversion in Strongly Correlated Systems: Beyond Single Quasiparticles and Rigid Bands

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This article reviews the fundamental consequences of strong correlations on excitations and elementary steps of energy conversion leading to new opportunities to control energy conversion. Examples include friction at surfaces, thermal transport, and photovoltaic energy conversion.
Vasily Moshnyaga, Peter E. Blöchl, Vitaly Bruchmann‐Bamberg, Annika Dehning, Lukas Allen‐Rump, Christopher Hausmann, Matthias Krüger, Amrith Rathnakaran, Sangeeta Rajpurohit, Daniel Steil, Christoph Flathmann, Jörg Hoffmann, Michael Seibt, Cynthia Volkert, Christian Jooss   +14 more
wiley   +1 more source

Sensory auditory processing and intuitive sound detection : an investigation of musical experts and nonexperts [PDF]

, 2006
The auditory system can detect occasional changes (deviants) in acoustic regularities without the need for subjects to focus their attention on the sound material.
van Zuijen, Titia
core  

Mindfulness meditation increases interictal epileptiform discharges in meditation‐naïve surgical epilepsy patients

Epilepsia, EarlyView.
Abstract Objective Meditation has widely recognized psychological and neuromodulatory benefits, yet its effects on epileptiform activity remain unclear. This study examined whether novice meditation modulates interictal epileptiform discharges (IEDs) in patients with drug‐resistant epilepsy using intracranial electroencephalography (iEEG).
Shweta Soni, Karine Brochu, Paolo Federico, Walter Hader, Julia W. Y. Kam, Fady Girgis   +5 more
wiley   +1 more source