Optimized Two-Stage Anomaly Detection and Recovery in Smart Grid Data Using Enhanced DeBERTa-v3 Verification System by Xiao Liao, Wei Cui, Min Zhang, Aiwu Zhang, Pan Hu

“…The increasing sophistication of cyberattacks on smart grid infrastructure demands advanced anomaly detection and recovery systems that balance high recall rates with acceptable precision while providing reliable data restoration capabilities. This study presents an optimized two-stage anomaly detection and recovery system combining an enhanced TimerXL detector with a DeBERTa-v3-based verification and recovery mechanism. …”
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On applicability of mathematical scaling and normalization in applied problem solving by A. I. Dolgov, D. V. Marshakov

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Use of artificial intelligence to increase the efficiency of the management accounting system by G.I., O.V.

“…Data analysis technology allows you to discover new patterns of relationships between data and provide useful conclusions to decision-makers in companies. …”
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Calibration and Validation of NOAA-21 Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper Sensor Data Record Data by Banghua Yan, Trevor Beck, Junye Chen, Steven Buckner, Xin Jin, Ding Liang, Sirish Uprety, Jingfeng Huang, Lawrence E. Flynn, Likun Wang, Quanhua Liu, Warren D. Porter

“…This study presents calibration and validation analysis results for the NOAA-21 OMPS NM SDR data to meet the JPSS scientific requirements. …”
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Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies. by Johan L Vinther, Tim Cadman, Demetris Avraam, Claus T Ekstrøm, Thorkild I A Sørensen, Ahmed Elhakeem, Ana C Santos, Angela Pinot de Moira, Barbara Heude, Carmen Iñiguez, Costanza Pizzi, Elinor Simons, Ellis Voerman, Eva Corpeleijn, Faryal Zariouh, Gilian Santorelli, Hazel M Inskip, Henrique Barros, Jennie Carson, Jennifer R Harris, Johanna L Nader, Justiina Ronkainen, Katrine Strandberg-Larsen, Loreto Santa-Marina, Lucinda Calas, Luise Cederkvist, Maja Popovic, Marie-Aline Charles, Marieke Welten, Martine Vrijheid, Meghan Azad, Padmaja Subbarao, Paul Burton, Puishkumar J Mandhane, Rae-Chi Huang, Rebecca C Wilson, Sido Haakma, Sílvia Fernández-Barrés, Stuart Turvey, Susana Santos, Suzanne C Tough, Suzanne C Tough, Sylvain Sebert, Theo J Moraes, Theodosia Salika, Vincent W V Jaddoe, Deborah A Lawlor, Anne-Marie Nybo Andersen

“…Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). …”
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Enhancing Temperature Data Quality for Agricultural Decision-Making with Emphasis to Evapotranspiration Calculation: A Robust Framework Integrating Dynamic Time Warping, Fuzzy Logi... by Christos Koliopanos, Alexandra Gemitzi, Petros Kofakis, Nikolaos Malamos, Ioannis Tsirogiannis

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Selection of keratometric data for the IOL toricity calculation by S.V. Shukhaev

“…Centroid analysis showed similar values of centroid error in 1st group and 2nd group (0.09 and 0.08), while the dispersion was higher in 2nd group (0.42 and 0.51, respectively). …”
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Normative values of spinal and peripheral proprioception in position sense among healthy adolescents and young adults by Kenney Ki Lee Lau, Kenny Yat Hong Kwan, Jason Pui Yin Cheung, Karlen Ka Pui Law, Arnold Yu Lok Wong, Daniel Hung Kay Chow, Kenneth Man Chee Cheung

“…Six position sense tests were implemented on the trunk, neck, elbow, and knee. Data were captured using a three-dimensional motion capture system. …”
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Diagnosis of depression based on facial multimodal data by Nani Jin, Renjia Ye, Peng Li

“…Through the multi-modal feature fusion, the model can effectively capture different feature patterns related to depression.ResultsWe conduct extensive experiments on the publicly available clinical dataset, the Extended Distress Analysis Interview Corpus (E-DAIC). The experimental results show that we achieve robust accuracy on the E-DAIC dataset, with a Mean Absolute Error (MAE) of 3.51 in estimating PHQ-8 scores from recorded interviews.DiscussionCompared with existing methods, our model shows excellent performance in multi-modal information fusion, which is suitable for early evaluation of depression.…”
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Variational AutoEncoder for synthetic insurance data by Charlotte Jamotton, Donatien Hainaut

“…Our experimental results and analysis highlight the potential of VAEs in addressing challenges related to data availability in the insurance industry.…”
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A missing data processing method for dam deformation monitoring data using spatiotemporal clustering and support vector machine model by Yan-tao Zhu, Chong-shi Gu, Mihai A. Diaconeasa

“…However, the deformation monitoring data are often incomplete due to environmental changes, monitoring instrument faults, and human operational errors, thereby often hindering the accurate assessment of actual deformation patterns. …”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…This improves the smoothness of the data. Principal component analysis (PCA) is applied to reduce the dimensionality of the decomposed components. …”
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scE2EGAE: enhancing single-cell RNA-Seq data analysis through an end-to-end cell-graph-learnable graph autoencoder with differentiable edge sampling by Shuo Wang, Yuanning Liu, Hao Zhang, Zhen Liu

“…Numerous computational methods, including methods based on graph neural networks (GNNs), have been developed to enhance scRNA-Seq data analysis. However, existing GNNs-based methods usually construct fixed graphs by applying the k-nearest neighbors algorithm, which may result in information loss. …”
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Feasibility Analysis for Predicting Indian Ocean Bigeye Tuna (<i>Thunnus obesus</i>) Fishing Grounds Based on Temporal Characteristics of FY-3 Microwave Radiation Imager Data by Yun Zhang, Jinglan Ye, Shuhu Yang, Yanling Han, Zhonghua Hong, Wanting Meng

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An anomaly identifying method for metering of standard electricity meters in an automatic verification assembly line based on correlated time-invariant by XING Yu, QU Zemin, SUN Yanling, DONG Xianguang, ZOU Lu, CHEN Mianzhou

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ANCHOR: Global Parametrized Ionospheric Data Assimilation by Victoriya V. Forsythe, Sarah E. McDonald, Kenneth F. Dymond, Bruce A. Fritz, Angeline G. Burrell, Katherine A. Zawdie, Douglas P. Drob, Meghan R. Burleigh, Dustin A. Hickey, Christopher A. Metzler, David D. Kuhl, Daniel Hodyss, Joe H. Hughes

“…ANCHOR reduces the root mean square errors in the analysis by more than a half for all of the ionospheric parameters in comparison to the background. …”
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Research on Thickness Error Optimization Method of Rolling System Based on Improved Sparrow Search Algorithm–Bidirectional Long Short-Term Memory Network–Attention by Qingyun Wu, Xinchen Li, Jiafei Ji, Bowen Xing

“…In addition, this paper establishes a web-based host computer, which provides an effective data source for the experimental analysis. The experimental results show that the optimized model has a mean square error of 1.22%, which is more accurate than other models, and has good generalization ability. …”
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Benchmarking the Non-Paraxial Beam Propagation Method for Deep-Tissue Microscopy by Praveen Kalarickel Ramakrishnan, Qi Hu, Peter R. T. Munro

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A novel 5.1–7.1 GHz front-end power amplifier for wireless applications with −35 dB Error Vector Magnitude by Pawankumar B., Prashantha Kumar H.

“…The increased bandwidth facilitates high data rate applications, such as streaming and gaming.…”
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Machine learning analysis of breast cancer treatment protocols and cycle counts: A case study at Mohammed vi hospital, Morocco by Houda AIT BRAHIM, Salah EL-HADAJ, Abdelmoutalib METRANE

“…The second model, based on Random Forest Regressor algorithm, which integrates the results of the first model during the training, predicted the treatment cycle of patients with a Root Mean Square Error (RMSE) score of 0.050 and a Mean Absolute Percentage Error (MAPE) score of 0.020. …”
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