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Hanieh Panahi
Numerous heavy-tailed distributions are used for modeling financial data and in problems related to the modeling of economics processes. These distributions have higher peaks and heavier tails than normal distributions. Moreover, in some situations, we c...
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Kuniyuki Miyazaki, Norio Tenma, Kazuo Aoki and Tsutomu Yamaguchi
A constitutive model for marine sediments containing natural gas hydrate is essential for the simulation of the geomechanical response to gas extraction from a gas-hydrate reservoir. In this study, the triaxial compressive properties of artificial methan...
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O. O. Lunin,V. S. Kossov,O. S. Yevstratov
Pág. 127 - 131
The directions of special rolling stock development and problems of the choice of elastic and dissipative characteristics for vehicle components have been considered.
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Songpu Li, Xinran Yu and Peng Chen
Model robustness is an important index in medical cybersecurity, and hard-negative samples in electronic medical records can provide more gradient information, which can effectively improve the robustness of a model. However, hard negatives pose difficul...
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Ling Wang, H. J. (Ilja) Van Meerveld and Jan Seibert
Many studies have shown that isotope data are valuable for hydrological model calibration. Recent developments have made isotope analyses more accessible but event sampling still involves significant time and financial costs. Therefore, it is worth to st...
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Xiaojuan Wang and Weilan Wang
As there is a lack of public mark samples of Tibetan historical document image characters at present, this paper proposes an unsupervised Tibetan historical document character recognition method based on deep learning (UD-CNN). Firstly, using the Tibetan...
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Yizhun Zhang and Qisheng Yan
Landslide susceptibility prediction has the disadvantages of being challenging to apply to expanding landslide samples and the low accuracy of a subjective random selection of non-landslide samples. Taking Fu?an City, Fujian Province, as an example, a mo...
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Weiwei Yuan, Wanxia Yang, Liang He, Tingwei Zhang, Yan Hao, Jing Lu and Wenbo Yan
The extraction of entities and relationships is a crucial task in the field of natural language processing (NLP). However, existing models for this task often rely heavily on a substantial amount of labeled data, which not only consumes time and labor bu...
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Giuseppe Sappa, Maurizio Barbieri and Francesca Andrei
Groundwater contamination due to municipal solid waste landfills? leachate is a serious environmental threat. Deuterium (2H) and oxygen (18O) isotopes have been successfully applied to identify groundwater contamination processes, due to interactions wit...
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Shenghua Xu, Meng Zhang, Yu Ma, Jiping Liu, Yong Wang, Xinrui Ma and Jie Chen
Geological disaster risk assessment can quantitatively assess the risk of disasters to hazard-bearing bodies. Visualizing the risk of geological disasters can provide scientific references for regional engineering construction, urban planning, and disast...
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William Hodgetts, Qi Song, Xinyue Xiang and Jacqueline Cummine
(1) Background: The application of machine learning techniques in the speech recognition literature has become a large field of study. Here, we aim to (1) expand the available evidence for the use of machine learning techniques for voice classification a...
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Edilson Marcelino Silva, Thais Destefani Ribeiro Furtado, Ariana Campos Frühauf, Joel Augusto Muniz, Tales Jesus Fernandes (Author)
Pág. e46893
Zinc uptake is essential for crop development; thus, knowledge about soil zinc availability is fundamental for fertilization in periods of higher crop demand. A nonlinear first-order kinetic model has been employed to evaluate zinc availability. Studies ...
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Edilson Marcelino Silva, Thais Destefani Ribeiro Furtado, Ariana Campos Frühauf, Joel Augusto Muniz, Tales Jesus Fernandes
Pág. e46893
Zinc uptake is essential for crop development; thus, knowledge about soil zinc availability is fundamental for fertilization in periods of higher crop demand. A nonlinear first-order kinetic model has been employed to evaluate zinc availability. Studies ...
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Yong Fang, Cheng Huang, Yijia Xu and Yang Li
With the development of artificial intelligence, machine learning algorithms and deep learning algorithms are widely applied to attack detection models. Adversarial attacks against artificial intelligence models become inevitable problems when there is a...
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Zhuohao Zhou, Chunyue Lu, Wenchao Wang, Wenhao Dang and Ke Gong
The training of deep neural networks usually requires a lot of high-quality data with good annotations to obtain good performance. However, in clinical medicine, obtaining high-quality marker data is laborious and expensive because it requires the profes...
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Vera Bernardoni, Rosaria Erika Pileci, Lorenzo Caponi and Dario Massabò
The multi-wavelength absorption analyzer model (MWAA model) was recently proposed to provide a source (fossil fuel combustion vs. wood burning) and a component (black carbon BC vs. brown carbon BrC) apportionment of babs measured at different wavelengths...
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Ye Tian, Jiahang Zhang, Junyue Tang, Wei Xu, Weiwei Zhang, Lijun Tao, Shengyuan Jiang and Yanbin Sun
To provide reliable input information for the load design and extraction of lunar soil water ice samples, it is necessary to study the water content distribution and water migration of simulated lunar soil water ice samples. On this basis, the temperatur...
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Jinting Zhu, Julian Jang-Jaccard, Amardeep Singh, Paul A. Watters and Seyit Camtepe
Malware authors apply different techniques of control flow obfuscation, in order to create new malware variants to avoid detection. Existing Siamese neural network (SNN)-based malware detection methods fail to correctly classify different malware familie...
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Qingbin Tong, Feiyu Lu, Ziwei Feng, Qingzhu Wan, Guoping An, Junci Cao and Tao Guo
The data-driven intelligent fault diagnosis method of rolling bearings has strict requirements regarding the number and balance of fault samples. However, in practical engineering application scenarios, mechanical equipment is usually in a normal state, ...
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