標題: Titlebook: Data Science in Engineering Vol. 10; Proceedings of the 4 Thomas Matarazzo,Fran?ois Hemez,Austin Downey Conference proceedings 2025 The Soc [打印本頁] 作者: Lampoon 時間: 2025-3-21 19:57
書目名稱Data Science in Engineering Vol. 10影響因子(影響力)
書目名稱Data Science in Engineering Vol. 10影響因子(影響力)學科排名
書目名稱Data Science in Engineering Vol. 10網(wǎng)絡公開度
書目名稱Data Science in Engineering Vol. 10網(wǎng)絡公開度學科排名
書目名稱Data Science in Engineering Vol. 10被引頻次
書目名稱Data Science in Engineering Vol. 10被引頻次學科排名
書目名稱Data Science in Engineering Vol. 10年度引用
書目名稱Data Science in Engineering Vol. 10年度引用學科排名
書目名稱Data Science in Engineering Vol. 10讀者反饋
書目名稱Data Science in Engineering Vol. 10讀者反饋學科排名
作者: 強制令 時間: 2025-3-21 22:06
Statistical Evaluation of Machine Learning for Vibration Data,om large quantities of data collected under varying conditions to make predictions, such as detection, identification, and characterization. Current ML implementation consists of training a model for narrow, task-specific needs, such as training a neural network to detect the presence of structural 作者: 肉體 時間: 2025-3-22 02:16 作者: mortuary 時間: 2025-3-22 06:19 作者: 模范 時間: 2025-3-22 11:37
Optimal Modeling of Deep Groove Ball Bearings for Application in Multibody Dynamics Simulations,e normal contact force between the rolling elements and the two bearing races are established, including the effects of raceway surface roughness. Various contact force models with different hysteresis damping formulations are examined in order to select the best suited for the application. The bear作者: Matrimony 時間: 2025-3-22 16:38
Utilization of Bridge Acceleration Response for Indirect Strain Sensing,onse under daily traffic loading. However, deploying and maintaining strain sensors is costly and labor-intensive compared to acceleration sensors. To address this issue, we propose a neural network architecture that can perform indirect sensing by estimating strain from measured acceleration respon作者: Matrimony 時間: 2025-3-22 19:25 作者: 過份艷麗 時間: 2025-3-23 00:04
Physics-Informed Machine Learning Part II: Applications in Structural Response Forecasting,interpretability of predictive models. By incorporating physical laws and constraints into the learning process, physics-informed machine learning enables more robust predictions and reduces the need for large amounts of training data. In part II of this two-part series, the authors present structur作者: 使迷惑 時間: 2025-3-23 05:03 作者: diathermy 時間: 2025-3-23 07:28
Understanding High-Frequency Modes in Electromechanical Impedance Measurement Using Noncontact Vibr measurements are recorded via a bonded piezoelectric transducer, at a high-frequency range, typically 30 kHz and above. Because EMI measurements are single input single output, the peaks in these measurements can be related to either mechanical, electrical, or coupled electromechanical modes, espec作者: inventory 時間: 2025-3-23 13:06 作者: Ingenuity 時間: 2025-3-23 14:57
Markov Chain Monte Carlo on Matrix Manifolds for Probabilistic Model Order Reduction,probabilistic case, within the Bayesian framework. We present a method to draw samples from a given target distribution defined on various matrix manifolds. The collected samples can be used to propagate uncertainty on the reduction matrix and other quantities of interest.作者: allergen 時間: 2025-3-23 20:12 作者: dry-eye 時間: 2025-3-24 01:11
,A Machine Learning–Based Damage Estimation Model for Monitoring Reinforced Concrete Structures,frastructure. As a phenomenon, when structures are loaded, AE sensors mounted on the surface of the structure receive the waves released from the damage and convert them into electrical signals. By analyzing and evaluating these recorded signals, critical information such as type, location, time of 作者: artless 時間: 2025-3-24 04:58
Adaptive Radio Frequency Target Localization,c devices and search and rescue. This recently has been done using a greedy approach, where a sensor is moved closer to the target after each measurement. However, this does not allow for other constraints, such as maintaining a fixed distance from the target or optimization of energy consumption. S作者: 全部 時間: 2025-3-24 09:43
Estimation of Acoustic Emission Arrival Time in Concrete Structures Using Convolutional Neural Netwing buildings, bridges, pipelines, and storage tanks. It relies on analyzing the acoustic activity, primarily associated with cracking phenomena, to assess structural integrity. However, one crucial parameter derived from AE signals is the time of arrival (ToA) of acoustic events, which is challengi作者: Predigest 時間: 2025-3-24 13:41 作者: Devastate 時間: 2025-3-24 18:17
2191-5644 nth volume of ten from the Conference brings together contributions to this important area of research and engineering.? The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on:.. .Novel Data-driven Analysis Metho作者: instructive 時間: 2025-3-24 19:13 作者: Banquet 時間: 2025-3-24 23:47 作者: 比目魚 時間: 2025-3-25 05:18 作者: landfill 時間: 2025-3-25 10:52 作者: MAIZE 時間: 2025-3-25 12:48 作者: 不開心 時間: 2025-3-25 18:17
Conference Proceedings of the Society for Experimental Mechanics Serieshttp://image.papertrans.cn/e/image/284452.jpg作者: indifferent 時間: 2025-3-25 21:26 作者: 小說 時間: 2025-3-26 03:20
om large quantities of data collected under varying conditions to make predictions, such as detection, identification, and characterization. Current ML implementation consists of training a model for narrow, task-specific needs, such as training a neural network to detect the presence of structural 作者: Reclaim 時間: 2025-3-26 07:03 作者: beta-cells 時間: 2025-3-26 10:11 作者: diathermy 時間: 2025-3-26 14:18 作者: Expiration 時間: 2025-3-26 17:22 作者: 怎樣才咆哮 時間: 2025-3-26 21:51
Olivia Bennett,Christopher McDowelluctural health monitoring (SHM) tasks, such as structural damage detection (SDD). The structures must meet specific similitude criteria for the proposed TL technique’s effectiveness in current one-to-one domain approaches. To overcome this challenge, the authors have developed a novel TL method that作者: LANCE 時間: 2025-3-27 03:43 作者: 原告 時間: 2025-3-27 07:33
H.-D. Bolte,TH. v. Arnim,U. Tebbe,E. Erdmannble sensor packages has gained significant attention. While compact sensors with wireless data transfer capabilities have demonstrated potential for monitoring structural dynamics of critical infrastructure, such systems typically require data to be processed off-device and often off-site. These add作者: 侵略者 時間: 2025-3-27 11:55
Tony Burnett,Simon Kettleborough measurements are recorded via a bonded piezoelectric transducer, at a high-frequency range, typically 30 kHz and above. Because EMI measurements are single input single output, the peaks in these measurements can be related to either mechanical, electrical, or coupled electromechanical modes, espec作者: LEVER 時間: 2025-3-27 14:57
Chronische Erkrankungen und Neoplasmen,omena that affect the structure, one can follow a data-driven approach to model its behaviour, relying exclusively on data acquired from it. However, a common problem of this approach is the scarcity of data or biased data. To deal with these two problems, approaches have been considered to transfer作者: lymphoma 時間: 2025-3-27 18:40
https://doi.org/10.1007/978-3-642-67123-4probabilistic case, within the Bayesian framework. We present a method to draw samples from a given target distribution defined on various matrix manifolds. The collected samples can be used to propagate uncertainty on the reduction matrix and other quantities of interest.作者: 狂怒 時間: 2025-3-27 23:46
tem can be inferred by monitoring key species which are indicative of the overall health of the ecosystem. Microphones have emerged as a powerful tool for detecting bird calls of these key indicator species. However, using an array of microphones to monitor a large area requires a power source at ea作者: 細微的差異 時間: 2025-3-28 05:21
frastructure. As a phenomenon, when structures are loaded, AE sensors mounted on the surface of the structure receive the waves released from the damage and convert them into electrical signals. By analyzing and evaluating these recorded signals, critical information such as type, location, time of 作者: 猛烈責罵 時間: 2025-3-28 10:16
c devices and search and rescue. This recently has been done using a greedy approach, where a sensor is moved closer to the target after each measurement. However, this does not allow for other constraints, such as maintaining a fixed distance from the target or optimization of energy consumption. S作者: 腐爛 時間: 2025-3-28 10:55
https://doi.org/10.1007/978-3-642-56116-0ing buildings, bridges, pipelines, and storage tanks. It relies on analyzing the acoustic activity, primarily associated with cracking phenomena, to assess structural integrity. However, one crucial parameter derived from AE signals is the time of arrival (ToA) of acoustic events, which is challengi作者: 同步信息 時間: 2025-3-28 18:16
tures’ health since traditional nondestructive testing (NDT) methods such as visual inspection take longer time to carry out and it is sensitive to the user’s skill in operating the apparatuses. Various methods incorporating reverse algorithms have been explored with the help of machine learning; ho作者: 粗鄙的人 時間: 2025-3-28 22:04 作者: 平息 時間: 2025-3-29 02:41
Data Science in Engineering Vol. 10978-3-031-68142-4Series ISSN 2191-5644 Series E-ISSN 2191-5652 作者: 凝視 時間: 2025-3-29 03:34
https://doi.org/10.1007/978-3-642-67123-4probabilistic case, within the Bayesian framework. We present a method to draw samples from a given target distribution defined on various matrix manifolds. The collected samples can be used to propagate uncertainty on the reduction matrix and other quantities of interest.作者: Cupping 時間: 2025-3-29 10:26
https://doi.org/10.1007/978-3-031-68142-4Conference Proceedings; Novel Data-driven Analysis Methods; Deep Learning Gaussian Process Analysis; Re作者: Physiatrist 時間: 2025-3-29 13:55 作者: affinity 時間: 2025-3-29 16:12 作者: Infuriate 時間: 2025-3-29 20:29 作者: agglomerate 時間: 2025-3-30 00:48 作者: minimal 時間: 2025-3-30 08:01 作者: orient 時間: 2025-3-30 09:27
Optimal Modeling of Deep Groove Ball Bearings for Application in Multibody Dynamics Simulations, bearing model. The system’s response is examined by means of signal analysis as well as by using deep learning methods in order to characterize the health state of the system, thus proving the applicability of the present bearing modeling method for condition monitoring applications.作者: NATTY 時間: 2025-3-30 15:38
Utilization of Bridge Acceleration Response for Indirect Strain Sensing,h our novel approach, we can estimate strain with high accuracy from acceleration data and reconstruct rainflow cycle counting diagrams that can subsequently be used for bridge condition and life cycle assessment.作者: 法律 時間: 2025-3-30 16:46 作者: 極大的痛苦 時間: 2025-3-30 22:40 作者: arbovirus 時間: 2025-3-31 02:47 作者: Maximizer 時間: 2025-3-31 08:40
On the Use of Symbolic Regression for Population-Based Modelling of Structures,that of symbolic regression and the transfer is attempted between an extensively monitored structure and a data-poor structure for a regression application. The methodology is applied in a prognosis problem of crack growth in metal plates, and the results reveal the potential of symbolic regression 作者: Prosaic 時間: 2025-3-31 13:00
Identification of Bird Species in Large Multi-channel Data Streams Using Distributed Acoustic Sensi benefit that DAS does not suffer from time synchronization errors and remote power issues like traditional microphone arrays. This work investigates the performance of DAS when used to detect bird calls, with particular focus on the Great Horned Owl (GHO), an indicator species for prey vulnerabilit作者: Cardiac-Output 時間: 2025-3-31 13:55 作者: NEX 時間: 2025-3-31 19:06
Adaptive Radio Frequency Target Localization,blem as a Partially Observable Markov Decision Process (POMDP) and was solved through the use of particle filtering and reinforcement learning. The purpose of this work is to build upon this prior study by training a deep neural network in a simulated environment and applying inference in the real w作者: 慢慢啃 時間: 2025-3-31 23:22 作者: 說明 時間: 2025-4-1 05:39
