Impacts of Missing Data Imputation on Resilience Evaluation for Water Distribution System by Amrit Babu Ghimire, Binod Ale Magar, Utsav Parajuli, Sangmin Shin

“…Incomplete datasets for the nodal pressure of the C-town WDS were developed with 10%, 30%, and 50% missing data percentages by manipulating a true dataset for normal operation conditions produced using EPANET. …”
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Personalized Privacy-Preserving Data Utilization Approach Powered by Distributed-GAN by Shuo Wang, Chao Wang, Tianshuo Dong, Yunhua He, Ke Xiao

“…Recently, Machine Learning (ML) has made great achievements in a wide range of fields with the increasing data exploring. However, the development of ML faces the challenges of data silos due to privacy considerations. …”
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Automatic Detection and Tracking of Objects of Interest in Video Data with Global Motion by N. A. Obukhova, A. A. Motyko, A. A. Chirkunova, A. A. Pozdeev, E. A. Litvinov

“…In order to ensure stable tracking, several detectors are used simultaneously with the subsequent analysis of the data obtained. The tracking stage involves a detector based on histograms of oriented gradients (HOG), supplemented by a detector based on correlation filtering and motion trajectory prediction based on the Kalman filter.Results. …”
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Data-driven Oxidation Kinetic Model Construction of Silicon Carbide Composites by Xiao Manyu, Zheng Wenqing, Luan Xingang, Xu Xinming

“…This research integrates experimental methods with intelligent data analysis techniques to accurately characterize and predict the oxidation behavior and mechanical property evolution of SiCf/SiC composites under complex service conditions. …”
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Data-Driven Approaches for Predicting and Forecasting Air Quality in Urban Areas by Cosmina-Mihaela Rosca, Madalina Carbureanu, Adrian Stancu

“…The study integrates pollutant factors (CO, NO₂, SO₂, PM_2.5), meteorological parameters (temperature, humidity, wind speed), and traffic data to determine air quality. For this purpose, 19 predictive models were developed and compared: 12 machine learning algorithms, 7 deep learning, and 1 forecasting model based on structural component analysis. …”
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Optimization algorithms for multivariate sampling reduction using spatial-temporal data by Tamara Cantú Maltauro, Luciana Pagliosa Carvalho Guedes, Miguel Angel Uribe-Opazo

“…Clusters were obtained by considering the analysis of spatio-temporal dependence through the empirical orthogonal function. …”
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Filtering and Overlapping Data for Accuracy Enhancement of Doppler-Based Location Method by Rafał Szczepanik, Jan M. Kelner

“…The use of overlapping at the signal sample level with a factor of 10% allows for more than a twofold decrease in localization errors, while overlapping at the DFS vector provides an increase in the refresh rate of the position of localized objects. Comparative analysis with direct position determination techniques additionally showed high effectiveness of the SDF method, especially using data filtration and overlapping. …”
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Simplex-structured matrix factorisation: application of soft clustering to metabolomic data by Wenxuan Liu, Thomas Brendan Murphy, Lorraine Brennan

“…In the simulation study, the cluster prototypes and cluster memberships were well estimated. In the real data application to metabolomic data, the presence of four soft clusters was suggested by the gap statistic. …”
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Discussing Relations Between Dynamic Business Environments and Big Data Analytics by Daniel Staegemann, Matthias Volk, Christian Daase, Klaus Turowski

“…Relevant data sources as well as the questions that are supposed to be answered by their analysis may change rapidly and so do subsequently the requirements regarding the functionalities of the system. …”
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Perception and Reuse of Open Data in the Spanish University Teaching and Research Community by Christian Vidal-Cabo, Enrique Alfonso Sánchez-Pérez, Antonia Ferrer-Sapena

“…Analysis. The data obtained through this quantitative methodology were processed, normalised, and analysed. …”
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Data-Driven Approach to Safety Control in Jacket-Launching Installation Operations by Sheng Chen, Mingxin Li, Yankun Liu, Xu Bai

“…The real-world data, including the barge attitude before launching, jacket weight distribution, and actual environmental conditions, are used to refine the model and guide the development of a fully parameterized adaptive controller. …”
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Prediction of dialysis adequacy using data-driven machine learning algorithms by Yi-Chen Liu, Ji-Ping Qing, Rong Li, Juan Chang, Li-Xia Xu

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Dashboards for visual display of patient safety data: a systematic review by Hardeep Singh, Daniel R Murphy, Dean F Sittig, April Savoy, Tyler Satterly

“…Two reviewers independently reviewed search results for inclusion in analysis and resolved disagreements by consensus. We collected data on development, use and impact via standardised data collection forms and analysed data using descriptive statistics.Results Literature search identified 4624 results which were narrowed to 33 publications after applying inclusion and exclusion criteria and consensus across reviewers. …”
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Evaluating the effectiveness of vaccination campaigns: Insights from unvaccinated mortality data by Lixin Lin, Haydar Demirhan, Lewi Stone

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Swahili questions and answers dataset for aflatoxin knowledge domainMendeley Data by Pamela Chogo, Elizabeth Mkoba, Neema Kassim

“…Respondents for the study were farmers, traders, and consumers of maize and groundnuts. The collected data were processed and analyzed using R qualitative data analysis tool. …”
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Building and explaining data-driven energy demand models for Indian states by Kieran M R Hunt, Hannah C Bloomfield

“…Accurate forecasts of energy demand are crucial for managing India’s rapidly growing energy needs as it continues to decarbonise its grid. In this study, we develop state-level data driven models to predict weather-driven energy demand across India using the eXtreme Gradient Boosting framework. …”
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Construction of application platform for operational data of natural gas pipeline network by Hongtao DIAO, Weichao YU, Kaihong WANG, Huai SU, Yi ZHANG, Zhaoming YANG

“…Objective The PipeChina Oil & Gas Control Center has independently developed an application platform for the operational data of its natural gas pipeline network, in an attempt to fully explore the value of network operational data and to address issues such as low data value density, significant heterogeneity of data sources, incomplete data acquisition and aggregation, insufficient data circulation and sharing, a lack of in-depth development and application, and notable weaknesses in data governance and security. …”
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Harnessing dynamic capabilities for data-driven business model innovation in incumbents by Shailesh Tripathi, Nadine Bachmann, Manuel Brunner, Herbert Jodlbauer

“…Data-driven business model innovation (DDBMI) leverages digital technologies to seize opportunities and address challenges, yet incumbents often struggle due to their reliance on existing capabilities. …”
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scFocus: Detecting branching probabilities in single-cell data with SAC by Chunlin Chen, Zeyu Fu, Jiajia Yang, Huaqing Chen, Jiabao Huang, Shitian Qin, Chuhuai Wang, Xiaoqian Hu

“…This demonstrates its applicability on different types of datasets and showcases its potential in discovering biological changes due to experimental treatments through multi-batch dataset processing. Finally, an online analysis tool based on scFocus was developed, helping researchers and clinicians in the process and visualization of single-cell RNA sequencing data as well as the interpretation of these data through branch probabilities in a streamlined and intuitive way.…”
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GATEKEEPER Platform: Secure Processing Environment for European Health Data Space by Eugenio Gaeta, Muhammad Salman Haleem, Laura Lopez-Perez, Mirko Manea, Maria Fernanda Cabrera Umpierrez, Maria Teresa Arredondo Waldmeyer, Leandro Pecchia, Giuseppe Fico

“…However, there are certain challenges associated with compliance to EHDS, such as secure continuous integration (CI) and continuous delivery (CD), scalability and adaptability towards new technologies and applications, tolerance against IoT cyber-attacks, requirement of advanced data storage methods, processing power, interoperability solutions for data analysis and connectivity. …”
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