huang, jing zhang, xuenan yang, hang zhenbiao, li xue, zhengfang wang, qingqing zhang, xinyuan ding, shenghua luo, zisheng yanqun, xu
...
Volatile organic compounds (VOCs) are closely associated with the maturity and variety of strawberries. However, the complexity of VOCs hinders their potential application in strawberry classification. This study developed a novel classification workflow using strawberry VOC profiles and machine learning (ML) models for precise fruit classification...
charilogis, vasileios
Artificial neural networks are parametric machine learning models that have been applied successfully to an extended series of classification and regression problems found in the recent literature. For the effective identification of the parameters of the artificial neural networks, a series of optimization techniques have been proposed in the rele...
Allouche, Michaël Girard, Stéphane Gobet, Emmanuel
We propose new parameterizations for neural networks in order to estimate out-of-sample Expected Shortfall, and even more generally, out-of-sample conditional tail moments, in heavy-tailed settings as functions of confidence levels. The proposed neural network estimator is able to extrapolate in the distribution tails thanks to an extension of the ...
Charles, Ssemuyiga Mahapatra, Rajani Kanta
Published in
Journal of biomolecular structure & dynamics
Plasmodium falciparum is the leading cause of malaria with 627,000 deaths annually. Invasion and egress are critical stages for successful infection of the host yet depend on proteins that are extensively pre-processed by various maturases. Plasmepsins (Plasmodium pepsins, abbreviated PM, I-X) are pepsin-like aspartic proteases that are involved in...
niu, xiping sang, ling duan, xiaoling shijie, gu zhao, peng zhu, tao kaixuan, xu yawei, he zheyang, li zhang, jincheng
...
The SiC MOSFET with an integrated SBD (SBD-MOSFET) exhibits excellent performance in power electronics. However, the static and dynamic characteristics of this device are influenced by a multitude of parameters, and traditional TCAD simulation methods are often characterized by their complexity. Due to the increasing research on neural networks in ...
Zhou, Shuai Yang, Changcheng Cheng, Yi Jiao, Jian Bi, Fengyi
Published in
Measurement Science and Technology
Airborne gravity gradient dynamic measurement error compensation is a crucial aspect of data processing in gravity gradient dynamic measurements. This study introduces a deep learning approach based on a residual backpropagation (Res-BP) neural network for post-error compensation in airborne gravity gradient dynamic measurement. The network employs...
walczyna, tomasz jankowski, damian piotrowski, zbigniew
This article explores the practical implementation of autoencoders for anomaly detection, emphasizing their latent space manipulation and applicability across various domains. This study highlights the impact of optimizing parameter configurations, lightweight architectures, and training methodologies to enhance anomaly detection performance. A com...
Liu, Bang Fu, Zhuang Hua, Zuohao Zhang, Jiazheng
Published in
Measurement Science and Technology
Fault diagnosis and condition monitoring are critical to the real-time and accurate flow regulation of the flow regulating valve. For the blockage fault, one of the main types of flow control valve faults, this paper proposes a collision detection and fault diagnosis method based on gated recurrent unit (GRU) and dynamic model-based adaptive extern...
arce, armando arce, fernando stevens-navarro, enrique pineda-rico, ulises cardenas-juarez, marco garcia-barrientos, abel
This work proposes and describes a deep learning-based approach utilizing recurrent neural networks (RNNs) for beam pattern synthesis considering uniform linear arrays. In this particular case, the deep neural network (DNN) learns from previously optimized radiation patterns as inputs and generates complex excitations as output. Beam patterns are o...
grcić, ivan pandžić, hrvoje
Detection of high-impedance faults in direct current microgrid lines presents a challenge for most conventional protection schemes because the magnitude of the fault current is similar to other transients that occur during normal operation. However, the waveform of high-impedance faults differs from that of other transients as it is characterized b...
