Performance Enhancement of EEG Signatures for Person Authentication Using CNN BiLSTM Method by Ashish Ranjan Mishra, Rakesh Kumar, Rajkumar Saini

“…We propose a multiscale convolutional neural network (CNN) and a Bidirectional LSTM (BiLSTM) model called CNN-BiLSTM to extract features and classify raw EEG data. This methodology involves acquiring raw EEG data, preprocessing for noise reduction, standardization, normalization, and employing deep learning techniques for feature extraction and classification. …”
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Shaping the appearance of a long-range aircraft at the stage of developing a technical proposal by A. A. Gorbunov, A. D. Pripadchev

“…At the same time, the problem of choosing the composition of rational design parameters is solved, which is an actual problem of the preliminary design stage of a long-range aircraft. …”
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Research on Storage Grain Temperature Prediction Method Based on FTA-CNN-SE-LSTM with Dual-Domain Data Augmentation and Deep Learning by Hailong Peng, Yuhua Zhu, Zhihui Li

“…The prediction model uses a long short-term memory (LSTM) network, enhanced with convolution layers for feature extraction and a Squeeze-and-Excitation Networks (SENet) module to suppress unimportant features and highlight important ones. …”
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Something’s different: elaboration’s transferrable role for false alarm reduction by Lauren A. Mason, Abigail Miller, Gregory Hughes, Holly A. Taylor

“…Taken together, our findings provide insight on the transferrable role of feature elaboration to reduce false alarm rates during complex visual display assessments.…”
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Resonant Energy Transfer and Storage in Coupled Flow-Driven Heat Oscillators by Qian Ye, Stephen Sanders, Alessandro Alabastri

“…While it is shown that a two-channel heat oscillator displays a resonance when the flow rates are equal and opposite, a complete understanding of these systems, especially when such heat oscillators are coupled and feature multiple channels, is still an open problem. …”
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Characterization of Aquifer Multiscale Properties by Generating Random Fractal Field with Truncated Power Variogram Model Using Karhunen–Loève Expansion by Liang Xue, Diao Li, Cheng Dai, Tongchao Nan

“…The latter provides a foundation to perform dimensionality reduction and saves computational effort when analyzing the stochastic flow and transport problems.…”
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Electric Submersible Pump Fault Diagnosis Based on Laplacian Eigenmaps and Weighted Extreme Learning Machine by XU Zekun, FU Jun, GAO Xiaoyong, ZHANG Yu, LI Qiang, TAN Chaodong

“…In response to the serious imbalance in the data collected by ESP, firstly, a fault diagnosis model is established using a weighted extreme learning machine; Then, to solve the problems of insufficient algorithm learning, high computational costs caused by weighted strategies, and poor performance in applying to high-dimensional feature spaces, the Laplacian eigenmaps method is introduced to further optimize the model; finally, the effectiveness of the proposed method was validated on the TE chemical process dataset, and the practicality of the algorithm was experimentally validated on the real-time fault dataset of electric submersible pump. …”
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Deep learning-based multi-criteria recommender system for technology-enhanced learning by Latifat Salau, Hamada Mohamed, Yunusa Simpa Abdulsalam, Hassan Mohammed

“…The model captures both low-order feature interactions using factorization machines and high-order dependencies through deep neural networks, enabling more adaptive recommendations. …”
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Creation of a Regional Edition of Ruwiki (a Case of the Komi-Language Edition) by Marina Fedina

“…Using the example of the Komi language, emerging problems, intralinguistic and extralinguistic features are analyzed. …”
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Fault diagnosis model of rolling bearings based on the M-YOLO network by NING Shaohui, ZHANG Shaopeng, WU Yukun, DU Yue, FAN Xiaoning

“…The rolling bearing is taken as the research object, and the fault diagnosis algorithm with two-dimensional signal as the input is studied, and the fault diagnosis model of rolling bearing based on M-YOLO network is constructed for the problems of multi-condition fault diagnosis, small data sample, and long model training time.MethodsFirstly, the mosaic data augmentation method was used to enrich the samples to improve the interference of unbalanced data on the diagnostic results. …”
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Research on Quality Anomaly Recognition Method Based on Optimized Probabilistic Neural Network by Li-li Li, Kun Chen, Jian-min Gao, Hui Li

“…Principal component analysis (PCA) reduced the dimension and extracted the feature of the original data of a control chart, which reduced the training time of PNN. …”
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Exploring development pathways for mining rural areas in the context of urban-rural integration: A case study in Shanxi Province, China. by Hao Xu, Shengyu Zhang, Zhenyu Wu

“…Then, non-parametric test was applied for feature difference test. Finally, mining rural areas transformation pathways were given by using land use transfer matrix and chord diagram. …”
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KukArt Magazine as a Cultural Project by Tatyana V. Zvereva

“…The author gives a detailed description of all issues of the magazine in the synchronous and diachronic aspects. The main feature of KukArt is absence of a unifi ed framework (making features which were based on objectives set and problems solved: the puppet and the avant-garde, the puppet and literature, the puppet and folklore, the puppet and the masquerade mask, the puppet and home theatre, the puppet and the mannequin, etc.) …”
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A Garbage Detection and Classification Method Based on Visual Scene Understanding in the Home Environment by Yuezhong Wu, Xuehao Shen, Qiang Liu, Falong Xiao, Changyun Li

“…The ESA attention mechanism is added to the backbone network part of the YOLOv5 network, aiming to improve the feature extraction ability of the network, combining with the built multimodal knowledge graph to form the YOLOv5-Attention-KG model, and deploying it to the service robot to perform real-time perception on the items in the scene. …”
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Philosophy of Science: How to Identify the Potential Research for the Day after Tomorrow? by Søren Ventegodt, Joav Merrick

“…We would suggest that the most promising projects have the following characteristics: (1) they are led by a brilliant researcher who considers his/her research to be “sweet science”, who wants to explain the anomalies of his/her field of science, and who lives in a nonmainstream scientific paradigm; (2) they are deeply engaged in the philosophical problems of their research field, they are searching eagerly for a new understanding and a new theory, giving new tools for measurement and creating change, and results are taken as feedback on all levels from tool to theory and philosophy; (3) they are focused on the key point(s), which is an essential feature of the universe that creates global change if intervened upon. …”
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A Novel Shearer Cutting State Recognition Method Based on Improved Variational Mode Decomposition and LSSVM with Acoustic Signals by Zhongbin Wang, Bin Liang, Lei Si, Kuangwei Tong, Chao Tan

“…Then, the feature extraction is achieved by calculating the envelope entropy and kurtosis of the decomposed intrinsic mode functions (IMFs). …”
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Addressing Hybrid Confounder Issue for Causal Session-Based Recommendation by Quan Li, Xinhua Xu, Jinjun Liu, Guangmin Li

“…Then, implicit environmental features are learned with observation sequence data. …”
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Convolutional neural networks and vision transformers for Plankton Classification by Loris Nanni, Alessandra Lumini, Leonardo Barcellona, Stefano Ghidoni

“…Such ensembles were tested together with transformer-based models in a detailed comparative analysis considering feature extraction efficiency, computational cost, and robustness to species imbalances. …”
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Buryat Language in Multi-Ethnic Buryatia: Functional Distribution, Language Competence, Motivations by G. A. Dyrkheeva, D. D. Badaraev, E. V. Khilkhanova

“…The analysis of some of the results of a sociolinguistic survey conducted in 2020 in the Republic of Buryatia is presented in the article. A feature of this survey is a large sample (1289 respondents of Buryat and Russian nationality) and a wide coverage of the problems of the functioning of the Buryat language. …”
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The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports. by Guomei Cui, Chuanjun Wang

“…This study aims to solve the problems of insufficient accuracy and low efficiency of the existing methods in sprint pattern recognition to optimize the training and competition strategies of athletes. …”
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