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Jinhong Wu, Konstantinos Plataniotis, Lucy Liu, Ehsan Amjadian and Yuri Lawryshyn
Synthetic data, artificially generated by computer programs, has become more widely used in the financial domain to mitigate privacy concerns. Variational Autoencoder (VAE) is one of the most popular deep-learning models for generating synthetic data. Ho...
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Fahim Sufi
GPT (Generative Pre-trained Transformer) represents advanced language models that have significantly reshaped the academic writing landscape. These sophisticated language models offer invaluable support throughout all phases of research work, facilitatin...
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Khishigsuren Davagdorj, Jong Seol Lee, Van Huy Pham and Keun Ho Ryu
Smoking is one of the major public health issues, which has a significant impact on premature death. In recent years, numerous decision support systems have been developed to deal with smoking cessation based on machine learning methods. However, the ine...
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Peeyush Gupta, Swati Uniyal, Swati Goyal
Pág. 74 - 90
A plant community acquires many characteristics which are not found in its constituents, (organisms or population). A community is described through species diversity, life forms, structure, dominance and developmental status. To delineate these aspects ...
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Jiachen Zhang, Guoqing Tu, Shubo Liu and Zhaohui Cai
The rapid development of speech synthesis technology has significantly improved the naturalness and human-likeness of synthetic speech. As the technical barriers for speech synthesis are rapidly lowering, the number of illegal activities such as fraud an...
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Franck Schoefs, Michael O?Byrne, Vikram Pakrashi, Bidisha Ghosh, Mestapha Oumouni, Thomas Soulard and Marine Reynaud
Hard marine growth is an important process that affects the design and maintenance of floating offshore wind turbines. A key parameter of hard biofouling is roughness since it considerably changes the level of drag forces. Assessment of roughness from on...
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Roberta Fusco, Adele Piccirillo, Mario Sansone, Vincenza Granata, Paolo Vallone, Maria Luisa Barretta, Teresa Petrosino, Claudio Siani, Raimondo Di Giacomo, Maurizio Di Bonito, Gerardo Botti and Antonella Petrillo
Purpose: The aim of the study was to estimate the diagnostic accuracy of textural, morphological and dynamic features, extracted by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images, by carrying out univariate and multivariate statist...
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Shaona Wang, Yang Liu and Linlin Li
In this study, a novel feature learning method for synthetic aperture radar (SAR) image automatic target recognition is presented. It is based on spatial pyramid matching (SPM), which represents an image by concatenating the pooling feature vectors that ...
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Zeynel Cebeci and Cagatay Cebeci
The goal of partitioning clustering analysis is to divide a dataset into a predetermined number of homogeneous clusters. The quality of final clusters from a prototype-based partitioning algorithm is highly affected by the initially chosen centroids. In ...
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Nadia Brancati and Maria Frucci
To support pathologists in breast tumor diagnosis, deep learning plays a crucial role in the development of histological whole slide image (WSI) classification methods. However, automatic classification is challenging due to the high-resolution data and ...
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Lei Li, Xiaobao Zeng, Xinpeng Pan, Ling Peng, Yuyang Tan and Jianxin Liu
Microseismic monitoring plays an essential role for reservoir characterization and earthquake disaster monitoring and early warning. The accuracy of the subsurface velocity model directly affects the precision of event localization and subsequent process...
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Mohammad Alauthman, Ahmad Al-qerem, Bilal Sowan, Ayoub Alsarhan, Mohammed Eshtay, Amjad Aldweesh and Nauman Aslam
Developing an effective classification model in the medical field is challenging due to limited datasets. To address this issue, this study proposes using a generative adversarial network (GAN) as a data-augmentation technique. The research aims to enhan...
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Oleg O. Kartashov, Sergey V. Chapek, Dmitry S. Polyanichenko, Grigory I. Belyavsky, Alexander A. Alexandrov, Maria A. Butakova and Alexander V. Soldatov
Microfluidic devices have opened new opportunities for functional material chemical synthesis in a few applications. The screening of microfluidic synthesis processes is an urgent task of the experimental process in terms of automation and intellectualiz...
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Ziquan Zhu, Zeyu Ren, Siyuan Lu, Shuihua Wang and Yudong Zhang
Background: Blood is responsible for delivering nutrients to various organs, which store important health information about the human body. Therefore, the diagnosis of blood can indirectly help doctors judge a person?s physical state. Recently, researche...
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Omar E. Elejla, Mohammed Anbar, Shady Hamouda, Serri Faisal, Abdullah Ahmed Bahashwan and Iznan H. Hasbullah
Internet Protocol version six (IPv6) is more secure than its forerunner, Internet Protocol version four (IPv4). IPv6 introduces several new protocols, such as the Internet Control Message Protocol version six (ICMPv6), an essential protocol to the IPv6 n...
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Weiying Feng, Daniel Bonamy, Fabrice Célarié, Paul C. M. Fossati, Stéphane Gossé, Patrick Houizot and Cindy L. Rountree
Stress corrosion cracking is a well-known phenomenon in oxide glasses. However, how amorphous phase separation (APS) alters stress corrosion cracking, and the overall mechanical response of an oxide glass is less known in literature. APS is a dominant fe...
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Girma Neshir, Andreas Rauber and Solomon Atnafu
Topic Modeling is a statistical process, which derives the latent themes from extensive collections of text. Three approaches to topic modeling exist, namely, unsupervised, semi-supervised and supervised. In this work, we develop a supervised topic model...
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Sahan Yoruç Selçuk, Perin Ünal, Özlem Albayrak and Moez Jomâa
Digital twins, virtual representations of real-life physical objects or processes, are becoming widely used in many different industrial sectors. One of the main uses of digital twins is predictive maintenance, and these technologies are being adapted to...
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Yaohang Lu and Zhongming Teng
Principal component analysis (PCA) is one of the most popular tools in multivariate exploratory data analysis. Its probabilistic version (PPCA) based on the maximum likelihood procedure provides a probabilistic manner to implement dimension reduction. Re...
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Vladimir Tcheverda and Kirill Gadylshin
The depth velocity model is a critical element for providing seismic data processing success, as it is responsible for the times of waves? propagation and, therefore, prescribes the location of geological objects in the resulting seismic images. Construc...
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