Natural language processing-based approach for automatically coding ship sensor data by Yunhui Kim, Kwangphil Park, Byeongwoo Yoo

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The Leakage Identification and Location of Ship Pipeline System Based on Vibration Signal Processing by Pan Su, JieChang Wu, Guanghui Chang, Shuyong Liu, Xuejiao Feng

“…Second, the vibration signal is processed based on the variational mode decomposition (VMD) and radial basis function (RBF) neural networks. …”
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Machine Learning Innovations for Improving Mineral Recovery and Processing: A Comprehensive Review* by Korie, Josephmartin Izuchukwu*, Chudi-Ajabor, Ogochukwu Gabriela, Ezeonyema, Chukwudalu Chukwuekezie, Oshim, Francisca Ogechukwu

“…The emergence of ML algorithms, such as Artificial Neural Networks (ANN), Support Vector Machines, and others, trigger this paradigm. …”
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Approach to design of distributed multi-agent system for processing sound information of the environment by U. A. Vishniakou, B. H. Shaya

“…Three different classification methods are investigated: KNearest neighbors, Gaussian mixture model and Support vector machine.Multi-agent system (M)AS characteristics are given, the classification, trends in the use of multi-agent intelligent technologies for information processing are presented. …”
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Adaptive Prediction of a Random Process Using a Sequential Regression Algorithm by Vladimir A. Golovkov

“…Models of random interferences in the form of infinitely and finitely differentiable random processes were considered. The sequential regression algorithm required to estimate the correlation selection matrix, the selection vector of correlation of the forecast and sample units. …”
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Recent Trends and Advances in Utilizing Digital Image Processing for Crop Nitrogen Management by Bhashitha Konara, Manokararajah Krishnapillai, Lakshman Galagedara

“…A total of 95 articles remained after the screening and selection process. Interest in integrating machine learning and deep learning algorithms with DIP has increased, with the frequently used algorithms—Random Forest, Support Vector Machine, Extreme Gradient Boost, and Convolutional Neural Networks—achieving higher prediction accuracy levels. …”
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Comparison of theoretical and experimental investigation of protonation process of some thiones in acid media by Mirjana S. Jankulovska, Vesna Dimova, Ilinka Spirevska, Milena Jankulovska

“…The protonation process in perchloric and hydrochloric acid took place in one step, while in phosphoric acid was not finished even when its concentration was to the highest degree. …”
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Research Progress on Process Optimization of Metal Materials in Wire Electrical Discharge Machining by Xinfeng Zhao, Binghui Dong, Shengwen Dong, Wuyi Ming

“…Subsequently, this paper reviews AI-based approaches, traditional machine-learning methods (e.g., neural networks, support vector machines, and random forests), and deep-learning models (e.g., convolutional neural networks and deep neural networks) in aspects such as state recognition, process prediction, multi-objective optimization, and intelligent control. …”
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Machine learning-driven design of support structures and process parameters in additive manufacturing by Yang Mo, Jinlong Su, Qinzhi Li, Fulin Jiang, Swee Leong Sing

“…However, the combined effects of support geometry and process parameters on key qualities such as residual stress (RS) and geometric accuracy remain insufficiently explored. …”
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Crow Search Algorithm for MEMS Gyroscope Temperature Drift Signal and Processing for Denoising by Xichen Wang, Huiliang Cao, Xiaomin Duan

“…Finally, the processed signal is reconstructed to achieve the goal of denoising. …”
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Investigation of aerodynamic processes in porous materials based on triply periodic minimal surfaces by D. M. Bragin, R. M. Mustafin, A. I. Popov, S. A. Zinina, A. V. Eremin

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Research on digital twin modeling method for combustion process based on model reduction by Yue Zhang, Jiale Li

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Nonlinear characteristics and prediction of gas and temperature in coal spontaneous combustion oxidation process by Ping ZHAN, Changkui LEI, Renhui CHENG

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Machine Learning-Assisted Optimization of Femtosecond Laser-Induced Superhydrophobic Microstructure Processing by Lifei Wang, Yucheng Gu, Xiaoqing Tian, Jun Wang, Yan Jia, Junjie Xu, Zhen Zhang, Shiying Liu, Shuo Liu

“…Three additional dimensional variables, i.e., the number of effective pulses, energy deposition rate, and roughness, were also added to the original dataset vectors as extra dimensions to participate in and guide the model training process. …”
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Decoding dynamic landslide hazard processes for a massive refugee camp in Bangladesh by Dewan Mohammad Enamul Haque, Ritu Roy, Sumya Tasnim, Shamima Ferdousi Sifa, Suniti Karunatillake, A.S.M. Maksud Kamal, Juan M. Lorenzo

“…Our research findings advance landslide hazard assessments by integrating time-varying dynamic processes with a slope units-based approach and facilitating risk mitigation at KTP.…”
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Detecting ADHD through natural language processing and stylometric analysis of adolescent narratives by Juan Barrios, Elena Poznyak, Jessica Lee Samson, Halima Rafi, Simon Gabay, Florian Cafiero, Martin Debbané, Martin Debbané

“…Stylometric features were extracted and used to train a Support Vector Machine (SVM) classifier to distinguish between narratives from the ADHD and control groups. …”
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Vector Autoregressive Spatio-Temporal (VAST) models for biomass distribution of pacific cod Gadus macrocephalus (Gadidae) considering water temperature at the sea bottom in the Wes... by V. V. Kulik, A. B. Savin

“…After stacking with statistical weights and previously published estimates of biomass, the obtained time series allow to estimate dynamics of biological processes deviations from stationary assumptions and to estimate approximately the volume of “extra” cod not considered by these processes in the Bayesian State-Space Surplus Production Model. …”
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Estimation the Variogram Function Indicator which represent the Transmissivity Coefficient in the groundwater by Seerwan Sulieman Noon

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A comprehensive literature review on ransomware detection using deep learning by Er. Kritika

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DO FIRM CHARACTERISTICS AFFECT PRICE DISCOVERY? EVIDENCE FROM CHINESE CROSS-LISTED STOCKS by Yen-Sheng Lee, Yi-Heng Tseng

“…Our study adds to the existing literature on the price discovery process within Chinese stock markets. …”
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