Scope and trends of the digital transformation in the world industry by E. N. Smirnov, M. Yu. Antropova

“…The state of industrial production is constantly changing due to the instability of global, economic and political decisions, so the adoption and expansion of digital solutions based on Industry 4.0, the Internet of things, machine learning and other technologies of the future is accelerating. …”
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A twofold perspective on the quality of research publications: The use of ICTs and research activity models. by Jolanta Wartini-Twardowska, Natalia Paulina Twardowska

“…We conducted web-based surveys among academic scientists and applied machine learning techniques to model behaviors during and after the COVID-19 pandemic. …”
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SDN TCP-SYN Dataset: A dataset for TCP-SYN flood DDoS attack detection in software-defined networksMendeley Data by Sudesh Kumar, Sunanda Gupta

“…Generated in a controlled testbed using advanced simulation tools Mininet(v2.3.0) and real internet traffic captured from real-world internet browsing sessions via Google Chrome and recorded using Wireshark(v3.0.2), this dataset is essential for researchers and practitioners working on TCP-SYN flood DDoS attack detection and machine learning-based traffic classification. The dataset is publicly available at Mendeley Data.…”
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An Audit Risk Model Based on Improved BP Neural Network Data Mining Algorithm by Wenjia Niu, Lihua Zhao, Peiyao Jia, Jiankun Chu

“…For auditors, it is a great challenge to use data mining algorithms, machine learning, artificial intelligence, and other emerging technologies to identify high-quality audit data from the vast amount of data of audited enterprises. …”
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Efficient optimisation of physical reservoir computers using only a delayed input by Enrico Picco, Lina Jaurigue, Kathy Lüdge, Serge Massar

“…Abstract Reservoir computing is a machine learning algorithm for processing time dependent data which is well suited for experimental implementation. …”
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Causal processes of shallow and deep seismicity at Campi Flegrei caldera by Genny Giacomuzzi, Rossella Fonzetti, Aladino Govoni, Pasquale De Gori, Claudio Chiarabba

“…Here, we show that detailed imaging of seismicity, improved by phase detection with machine-learning algorithms, and velocity models shed light on the active processes at the unresting caldera. …”
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Evaluation and Testing in Operational Environments: Accelerating Development Cycles for Maritime Unmanned Systems by João Borges de Sousa

“…This is exacerbated by the fact that we are also witnessing a paradigm change in MUS, from the operation of vehicles to the operation of systems of systems (SoS), delivering unprecedented capabilities and powered by recent developments in artificial intelligence and machine learning. Here, we discuss the impact of these trends on technological and organizational development from the perspective of the increasing role of evaluation and testing in operational environments. …”
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An Expert Diagnosis System for Parkinson Disease Based on Genetic Algorithm-Wavelet Kernel-Extreme Learning Machine by Derya Avci, Akif Dogantekin

“…The Parkinson disease datasets are obtained from the UCI machine learning database. In wavelet kernel-Extreme Learning Machine (WK-ELM) structure, there are three adjustable parameters of wavelet kernel. …”
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The Use of Natural Language Processing Model in Literary Style Analysis of Chinese Text by Ye Jinze

“…As a promising branch of Machine Learning, NLP focuses on the understanding, generating and analysing of human languages. …”
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Adaptive multi‐agent smart academic advising framework by Abdelaziz A. Abdelhamid, Sultan R. Alotaibi

“…These agents are interacting together with the help of smart advisor agent, which manages the communication between them and provides smart advice based on machine learning techniques. In addition, the analysis of the proposed framework along with the deployment map is discussed by the authors. …”
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Forecasting Volatility of Stock Index: Deep Learning Model with Likelihood-Based Loss Function by Fang Jia, Boli Yang

“…Most related research studies use distance loss function to train the machine learning models, and they gain two disadvantages. …”
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Refining potential energy surface through dynamical properties via differentiable molecular simulation by Bin Han, Kuang Yu

“…Abstract Recently, machine learning potential (MLP) largely enhances the reliability of molecular dynamics, but its accuracy is limited by the underlying ab initio methods. …”
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Digital Determinants of Health: Health data poverty amplifies existing health disparities-A scoping review. by Kenneth Eugene Paik, Rachel Hicklen, Fred Kaggwa, Corinna Victoria Puyat, Luis Filipe Nakayama, Bradley Ashley Ong, Jeremey N I Shropshire, Cleva Villanueva

“…Artificial intelligence (AI) and machine learning (ML) have an immense potential to transform healthcare as already demonstrated in various medical specialties. …”
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Neural quantum propagators for driven-dissipative quantum dynamics by Jiaji Zhang, Carlos L. Benavides-Riveros, Lipeng Chen

“…Describing the dynamics of strong-laser driven open quantum systems is a very challenging task that requires the solution of highly involved equations of motion. While machine learning techniques are being applied with some success to simulate the time evolution of individual quantum states, their use to approximate time-dependent operators (that can evolve various states) remains largely unexplored. …”
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A Theoretical Framework for Interrogating the Integration of Artificial Intelligence in Education by Tarisayi Kudzayi Savious

“…Artificial intelligence (AI) and machine learning have become increasingly important in modern society and are poised to play an increasingly prominent role in education. …”
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Research on the Influence of New Media Technology on Internet Short Video Content Production under Artificial Intelligence Background by Zhiqin Lu, Inyong Nam

“…Therefore, video content analysis is a very important and popular work in machine learning and artificial intelligence currently. …”
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A Study of Supplier Selection Method Based on SVM for Weighting Expert Evaluation by Li Zhao, Wenjing Qi, Meihong Zhu

“…To tackle this problem, this paper proposes a novel method that employs machine learning to learn the credibility of expert from historical data, which is converted to weights in evaluation process. …”
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Exploring the performance of ChatGPT for numerical solution of ordinary differential equations by Saso Koceski, Natasa Koceska, Limonka Koceva Lazarova, Marija Miteva, Biljana Zlatanovska

“…It also requires further improvement of the machine learning model and the ability to provide an explanation of how the output was obtained.…”
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Studying Same-Sign Top Pair Production through Top-Higgs FCNC Interactions at the HL-LHC by O. M. Ozsimsek, V. Ari, O. Cakir

“…We use angular observables of the same-sign lepton pairs and the top quark kinematics in the process which provide the possibility of separation of new physics signal from the SM backgrounds using machine-learning techniques. We find that the same-sign top quark pair production is quite capable of testing the top-Higgs FCNCs at the HL-LHC.…”
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Audiogmenter: a MATLAB toolbox for audio data augmentation by Gianluca Maguolo, Michelangelo Paci, Loris Nanni, Ludovico Bonan

“…This study aims to help machine learning researchers to improve their models using the algorithms proposed by the authors. …”
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