European sovereign debt control through reinforcement learning by Tato Khundadze, Willi Semmler, Willi Semmler, Willi Semmler

“…We demonstrate that the Soft Actor-Critic algorithm provides comparable or, in some cases, better solutions to multi-objective macroeconomic optimization problems, in comparison to Nonlinear Model Predictive Control (NMPC) algorithm.…”
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Mining patterns of comorbidity evolution in patients with multiple chronic conditions using unsupervised multi-level temporal Bayesian network. by Syed Hasib Akhter Faruqui, Adel Alaeddini, Carlos A Jaramillo, Jennifer S Potter, Mary Jo Pugh

“…We also use a longest path algorithm to identify the most likely sequence of comorbidities emerging from and/or leading to specific chronic conditions. …”
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Research on GNNs with stable learning by Wenbin Li, Wenxuan Wei, Peiyang Wang, Li Pan, Bo Yang, Yanling Xu

“…While guaranteeing predictive performance on the training distribution data, it also reduces prediction bias on data from unseen test distributions. …”
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An Ensemble Learning Method for the Kernel-Based Nonlinear Multivariate Grey Model and its Application in Forecasting Greenhouse Gas Emissions by Lan Wang, Nan Li, Ming Xie

“…In order to give policy makers more power to set the specific target of GHG emission reduction, we propose an ensemble learning method with the least squares boosting (LSBoost) algorithm for the kernel-based nonlinear multivariate grey model (KGM) (1, N), and it is abbreviated as BKGM (1, N). …”
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Potaxies and Fifes: The Formation of New Subcultures on TikTok by Pablo Santaolalla-Rueda, Cristóbal Fernández-Muñoz

“…Additionally, the study examines how digital platforms mediate intersectional experiences, favouring certain types of content through algorithms, and how participants navigate these opportunities and constraints to express their intersecting identities. …”
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Digitalization of human resource management: current trends and challenges for Russian enterprises by Mikhail K. Chernyakov, Irina A. Chernyakova

“…The findings of the article can be applied in shaping corporate strategies, government programs to support business digitalization, as well as in educational courses on HR management and IT. EDN: YPKICO…”
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Application of a Dual-Stream Network Collaboratively Based on Wavelet and Spatial-Channel Convolution in the Inpainting of Blank Strips in Marine Electrical Imaging Logging Images:... by Guilan Lin, Sinan Fang, Manxin Li, Hongtao Wu, Chenxi Xue, Zeyu Zhang

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Generalized perception of tree-row with distribution-peak feature in 3D point cloud for various orchards navigation by Yingxing Jiang, Wuhao Li, Jizhan Liu, Muhammad Mahmood ur Rehman, Binbin Xie, Jie Wang

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DS-AdaptNet: An Efficient Retinal Vessel Segmentation Framework With Adaptive Enhancement and Depthwise Separable Convolutions by Shuting Chen, Chengxi Hong, Hong Jia

“…Most importantly, DS-AdaptNet achieves these results with only 1.57M parameters and 44.08 GFLOPs—a 94.9% reduction in parameters and 77.2% reduction in computational operations compared to standard U-Net. …”
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Quantitative analysis of deep learning-based denoising model efficacy on optical coherence tomography images with different noise levels by Furkan Kirik, Farid Iskandarov, Kamile Melis Erturk, Hakan Ozdemir

“…Background: To quantitatively evaluate the effectiveness of the Noise2Noise (N2N) model, a deep learning (DL)-based noise reduction algorithm, on enhanced depth imaging-optical coherence tomography (EDI-OCT) images with different noise levels. …”
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Abnormal sound detection method for coal mine belt conveyors based on convolutional autoencoder by SHEN Long, SHAN Haoran, PEI Wenliang, YANG Guixiang, WANG Yongli

“…Background noise in the signals was filtered using the WebRTC noise reduction algorithm, and Mel-Frequency Cepstral Coefficients (MFCC) were calculated from the denoised signals to obtain audio features of normal operation. …”
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Spot Position Extraction Based on High-resolution Parametric Subspace Method without Eigen decomposition by Azad Raheem Kareem

“…A simulated example is provided to evaluate the proposed method and the simulation results shows that the proposed algorithm has the advantages of reduction the computational load and superior estimation performance. …”
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Real-time classification of EEG signals using Machine Learning deployment by Swati CHOWDHURI, Satadip SAHA, Samadrita KARMAKAR, Ankur CHANDA

“…The prevailing educational methods predominantly rely on traditional classroom instruction or online delivery, often limiting the teachers’ ability to engage effectively with all the students simultaneously. …”
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Classical special functions of matrix arguments by Dmytro Shutiak, Gleb Podkolzin, Victor Bondarenko, Yury Chapovsky

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Design and optimization of an open personalized human-computer interaction system for New Year Painting based on the learner's model by Zaozao Guo, Muhamad Firdaus Ramli, Wenpeng Zhang

“…Firstly, the attention mechanism based long and short term memory network is used to mine the emotion from the course review text of learners, and the association rule algorithm and ID3 algorithm are used to initialize and dynamically update the text. …”
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Cereal and Rapeseed Yield Forecast in Poland at Regional Level Using Machine Learning and Classical Statistical Models by Edyta Okupska, Dariusz Gozdowski, Rafał Pudełko, Elżbieta Wójcik-Gront

“…This study performed in-season yield prediction, about 2–3 months before the harvest, for cereals and rapeseed at the province level in Poland for 2009–2024. …”
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Comparison of artificial intelligence approaches for estimating wind energy production: A real-world case study by Mohamed Bousla, Mohamed Belfkir, Ali Haddi, Youness El Mourabit, Badre Bossoufi

“…These results emphasise the need of accurate prediction for the efficient operation and maintenance of contemporary wind turbines and provide direction on choosing the most appropriate prediction techniques considering variables such as time frames, input properties, and processing needs.…”
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Neural Network Models for the Half-Cell Potential of Reinforced Slabs with Magnesium Sacrificial Anodes Subjected to Chloride Ingress by Yogesh Murthy

“…The network architecture [5-10-1] and 10 neurons in the hidden layer were used for all the prediction models. Out of all the training algorithms used, the overall performance was best with LM in all stages of modelling (>96%). …”
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Artificial Intelligence in Virtual Screening: Transforming Drug Research and Discovery—A Review by Sayantani Roy, Karuppiah Nagaraj, Amit Mittal, Flora C. Shah, Kaliyaperumal Raja

“…Virtual screening (VS) has become an essential computational tool in drug discovery that helps to identify bioactive compounds by predicting their interactions with biological targets. …”
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Failure Management Overview in Optical Networks by Sergio Cruzes

“…This study surveys ML techniques for early-warning and failure prediction, failure detection, identification, localization, magnitude estimation, and soft failure detection and prediction. …”
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