Subnational variations in the quality of household survey data in sub-Saharan Africa by Valentin Seidler, Edson C. Utazi, Amelia B. Finaret, Sebastian Luckeneder, Gregor Zens, Maksym Bodarenko, Abigail W. Smith, Sarah E. K. Bradley, Andrew J. Tatem, Patrick Webb

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TAME Pain data release: using audio signals to characterize pain by Tu-Quyen Dao, Eike Schneiders, Jennifer Williams, John Robert Bautista, Tina Seabrooke, Ganesh Vigneswaran, Rishik Kolpekwar, Ritwik Vashistha, Arya Farahi

“…This dataset stands as the largest of its kind to date and includes comprehensive annotations detailing background noise, speech errors, and non-speech vocal features, maximizing its utility for in-depth audio analysis. …”
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An Assessment of Data from the Advanced Technology Microwave Sounder at the Met Office by Amy Doherty, Nigel Atkinson, William Bell, Andrew Smith

“…This suggests benefits beyond redundancy, associated with reducing already small analysis errors.…”
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Optimising ensemble streamflow predictions with bias correction and data assimilation techniques by M. Tanguy, M. Tanguy, M. Eastman, M. Eastman, A. Chevuturi, E. Magee, E. Cooper, R. H. B. Johnson, K. Facer-Childs, J. Hannaford, J. Hannaford

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Detection of Banana Diseases Based on Landsat-8 Data and Machine Learning by Renata Retkute, Kathleen S. Crew, John E. Thomas, Christopher A. Gilligan

“…Recent outbreaks of banana diseases are threatening the global banana industry and smallholder livelihoods. Remote sensing data offer the potential to detect the presence of disease, but formal analysis is needed to compare inferred disease data with observed disease data. …”
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Operational Energy Consumption Map for Urban Electric Buses: Case Study for Warsaw by Maciej Kozłowski, Andrzej Czerepicki

“…We aim to present a comprehensive data-driven methodology for analysing energy consumption within a large urban agglomeration. …”
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Quantitative Analysis of 3-Monochloropropane-1,2-diol in Fried Oil Using Convolutional Neural Networks Optimizing with a Stepwise Hybrid Preprocessing Strategy Based on Fourier Tra... by Xi Wang, Siyi Wang, Shibing Zhang, Jiping Yin, Qi Zhao

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Methods of calculating electric power generation by wind turbines and their influence on wind speed by E. A. Bekirov, S. N. Voskresenskaya, Z. U. Ramazanova, O. S. Bekirov

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Forecast of demand for the rmal energy for buildings of secondary educational institutions based on the properties of heteromorphism of their energy systems by S. V. Guzhov

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Modern techniques in variance estimation with auxiliary information: a logarithmic perspective by Poonam Singh, Prayas Sharma, Anjali Singh, Anamika Kumari

“…The usefulness of the suggested estimators is illustrated by real-world examples, including biological measures, income distribution studies, and environmental data assessments. To evaluate the performance in general, theoretical characteristics are derived, such as mean square error and bias. …”
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ICBoost: An XGBoost-Based Unbiased Transformed Algorithm for Survival Regression by Jingyi Zhang, Shishun Zhao, Yang Xu, Tao Hu

“…Prediction models for disease onset are critical in biomedical research and survival analysis. With machine learning methods increasingly being used to handle survival data with censoring, unbiased transformation theory offers an alternative method for estimating survival tasks in the presence of such censoring, thereby enhancing model accuracy. …”
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Virtual Signal Processing-Based Integrated Multi-User Detection by Dabao Wang, Zhao Li

“…Our theoretical analysis and simulation results demonstrate that VSP-IMUD effectively reduces the frequency of SIC applications and mitigates its error propagation effects, thereby improving the system’s bit-error rate (BER) performance.…”
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Trend equation prediction in medical and pharmaceutical studies (the example of respiratory diseases development in children in the region) by O. V. Zhukova, S. V. Kononova, T. M. Konyshkina

“…The function selection was determined by the temporal data changes. The trend calculation involves three stages: data entry into an Excel spreadsheet, plotting a graph, the selection of a trend line parameters. …”
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Dataset of speech produced with delayed auditory feedbackOpen Science FrameworkOpen Science Framework by Matthias Heyne, Monique C. Tardif, Alexander Ocampo, Ashley P. Petitjean, Emily J. Hacker, Caroline N. Fox, Megan A. Liu, Madeline Fontana, Vincent Pennetti, Jason W. Bohland

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Reliability and Quality of Complex Systems by D.N. Novomeisky, M.N. Piganov, E.T. Eskibaev

“…Computer modeling, programming, full-scale experiment, expert assessments were used. A systematic analysis of errors in the electrophysical processing of film resistors by high-frequency flare discharge is carried out. …”

Research results of the screw dispenser of dry bulk feed components by S. Yu. Bulatov, A. N. Pronin

“…To do this, the Box-Benkin plan was implemented for five factors. As a result of the analysis of the data obtained, a regression model was built, on the basis of which three combinations of factor values were determined, in which the grain dosing error by an additional dispenser screw was 0. …”
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Evaluating text representations for unsupervised legal semantic textual similarity in Brazilian Portuguese by Daniel da Silva Junior, Daniel de Oliveira, Aline Paes

“…Another investigation shows that text characteristics directly impact the performance of Transformer-based models with different attention mechanisms. Furthermore, the analysis comparing the impact of fine-tuning BERT on legal domain data and changing the attention mechanism shows that the latter preserves the BERT original vector space more than the former. …”
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Optimizing Renewable Energy Systems Placement Through Advanced Deep Learning and Evolutionary Algorithms by Konstantinos Stergiou, Theodoros Karakasidis

“…Validation against real-world data demonstrates improved prediction accuracy using metrics like root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). …”
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Data transmission optimization algorithm for network utility maximization in wireless sensor networks by Chengtie Li, Jinkuan Wang, Mingwei Li

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Compressive sensing based data gathering algorithm over unreliable links in WSN by Ce ZHANG, Xia ZHANG, Ou LI, Guan-lin MEI, Zhe HAN, Da-long ZHANG, Guang-yi LIU

“…To solve the problem that the ubiquitous unreliable links in the WSN influence the performance of the compressive sensing (CS) based data gathering,first the relationship between the reconstruction SNR of CS-based data gathering algorithm and the bit-error-ratio (BER) were simulated quantitatively.Then classify two cases were classified,namely light-payload and heavy-payload,relying on the analysis of wireless link packet loss characteristics.The random packet loss model was conceived to describe the packet loss under light-payload scenario.Further the neighbor topology spatial correlation prediction-based CS data gathering (CS-NTSC) algorithm was proposed,which utilized the nodes spatial correlation to reduce the impact of error.Additionally,the node pseudo-failure model was conceived to describe the packet loss occurred in network congestion,and then the sparse schedule-aided CS data gathering (CS-SSDG) algorithm were conceived,for the purpose of changing the sparsity of measurement matrix and avoiding measurements amongst the nodes affected by unreliable links,thus weakening the impact of error/loss on data reconstruction.Simulation analysis indicates that the proposed algorithms are not only capable of improving the accuracy of the data reconstruction without extra energy,but also effectively reducing the impact affected by the unreliable links imposed on CS-based data gathering.…”
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