Automated Stellar Spectra Classification with Ensemble Convolutional Neural Network by Zhuang Zhao, Jiyu Wei, Bin Jiang

“…Large sky survey telescopes have produced a tremendous amount of astronomical data, including spectra. Machine learning methods must be employed to automatically process the spectral data obtained by these telescopes. …”
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Cognitive Mimetics for Designing Intelligent Technologies by Tuomo Kujala, Pertti Saariluoma

“…We conclude by a practical example showing how cognitive mimetics can be a highly valuable complimentary approach for pattern matching and machine learning based design of artificial intelligence (AI) for solving specific human-AI interaction design problems.…”
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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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Area under the ROC Curve has the most consistent evaluation for binary classification. by Jing Li

“…Analyzing 156 data scenarios, 18 model evaluation metrics and five commonly used machine learning models as well as a naive random guess model, I find that evaluation metrics that are less influenced by prevalence offer more consistent evaluation of individual models and more consistent ranking of a set of models. …”
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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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Green approaches to heavy metal removal from wastewater: Microalgae solutions in a circular economy framework by Nikolaos A. Kazakis

“…Efforts are also made to explore potential applications of the contaminated or regenerated cells. Machine learning techniques are also employed to analyze the acquired data and develop a model for the prediction of cell growth based on cultivation parameters, which will be validated in real case studies.…”
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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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Recurrences Reveal Shared Causal Drivers of Complex Time Series by William Gilpin

“…Through extensive benchmarks against classical signal processing and machine learning techniques, we demonstrate our method’s ability to extract causal drivers from diverse experimental datasets spanning ecology, genomics, fluid dynamics, and physiology.…”
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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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Survey of FPGA based recurrent neural network accelerator by Chen GAO, Fan ZHANG

“…Recurrent neural network(RNN) has been used wildly used in machine learning field in recent years,especially in dealing with sequential learning tasks compared with other neural network like CNN.However,RNN and its variants,such as LSTM,GRU and other fully connected networks,have high computational and storage complexity,which makes its inference calculation slow and difficult to be applied in products.On the one hand,traditional computing platforms such as CPU are not suitable for large-scale matrix operation of RNN.On the other hand,the shared memory and global memory of hardware acceleration platform GPU make the power consumption of GPU-based RNN accelerator higher.More and more research has been done on the RNN accelerator of the FPGA in recent years because of its parallel computing and low power consumption performance.An overview of the researches on RNN accelerator based on FPGA in recent years is given.The optimization algorithm of software level and the architecture design of hardware level used in these accelerator are summarized and some future research directions are proposed.…”
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Particle-flow reconstruction with Transformer by Wahlen Paul, Suehara Taikan

“…Transformers are one of the recent big achievements of machine learning, which enables realistic communication on natural language processing such as ChatGPT, as well as being applied to many other fields such as image processing. …”
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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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Timing data visualization: tactical intent recognition and portable framework by SONG Yafei, LI Lemin, QUAN Wen, NI Peng, WANG Ke

“…Experimental results demonstrate that the proposed framework achieves over 0.99% higher accuracy compared to machine learning and deep learning methods, exhibiting superior performance, scalability, robustness, and transferability.…”
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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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