A Distributed and Scalable Framework for Low-Latency Continuous Trajectory Stream Processing by Salman Ahmed Shaikh, Hiroyuki Kitagawa, Akiyoshi Matono, Kyoung-Sook Kim

“…Conversely, while scalable SPEs do exist, they lack the necessary data structures, operators, and indices essential for processing trajectory streams. …”
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A Data and Machine Learning-Based Approach for the Conversion of the Encounter Wave Frequency Spectrum to the Original Wave Spectrum by JeongYong Park, MooHyun Kim

“…The results demonstrate that the ANN model can effectively predict the original wave spectrum with high accuracy, as evidenced by a favorable R2 value and error distribution analysis. This approach not only enhances the reliability of wave spectrum estimation during maritime navigation but also broadens the capability of real-time operational controls and adjustments.…”
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A comparative study of machine learning classifiers for intelligent fault diagnosis of electric vehicles based on FMECA data by Leila Boucerredj, Nadir Benalia

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PERFORMANCE STUDY OF THE DTU MODEL FOR RELATIONAL DATABASES ON THE AZURE PLATFORM by Serhii Minukhin

“…The following methods were used in the research: methods of relational database design; methods of creating queries in SQL-oriented databases with any number of tables; methods of creating and migrating data to cloud platforms; methods of monitoring the results of queries based on time and resource indicators; methods of generating test data for relational databases; system approach for complex assessment and analysis of productivity of work with relational databases. …”
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Assessing Public Transit Network Efficiency and Accessibility in Johor Bahru and Penang, Malaysia: A Data-Driven Approach by Mahbub Hassan, Hridoy Deb Mahin, Ferdoushi Ahmed, Md. Maruf Hassan, Atikur Rahaman, Masuk Abdullah

“…This study conducts a comprehensive analysis of public bus transit networks in Johor Bahru and Penang, Malaysia, using General Transit Feed Specification (GTFS) data. …”
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StationNet: An Algorithm for the Extraction and Visualization of Top-n Correlated Bike Stations in Bike Sharing Systems Big Datasets by Ahmet Şakir Dokuz

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Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework by Kaushik Sathupadi, Sandesh Achar, Shinoy Vengaramkode Bhaskaran, Nuruzzaman Faruqui, M. Abdullah-Al-Wadud, Jia Uddin

“…A K-Nearest Neighbors (KNNs) model is deployed on edge devices to detect anomalies in real-time, reducing the need for continuous data transfer to the cloud. Meanwhile, a Long Short-Term Memory (LSTM) model in the cloud analyzes time-series data for predictive failure analysis, enhancing maintenance scheduling and operational efficiency. …”
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The Impact of Mesoscale Environmental Uncertainty on the Prediction of a Tornadic Supercell Storm Using Ensemble Data Assimilation Approach by Nusrat Yussouf, Jidong Gao, David J. Stensrud, Guoqing Ge

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Rapid Probabilistic Inundation Mapping Using Local Thresholds and Sentinel-1 SAR Data on Google Earth Engine by Jiayong Liang, Desheng Liu, Lihan Feng, Kangning Huang

“…Traditional inundation mapping often relies on deterministic methods that offer only binary outcomes (inundated or not) based on satellite imagery analysis. While widely used, these methods do not convey the level of confidence in inundation classifications to account for ambiguity or uncertainty, limiting their utility in operational decision-making and rapid response contexts. …”
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Experimentation in Exploring Photovoltaic Inverter Dynamics Under Different Irradiance Levels Through a Data-Driven Approach by Bidur Poudel, Nischal Guruwacharya, Sunil Subedi, Ujjwol Tamrakar, Felipe Wilches-Bernal, Hossein Moradi Rekabdarkolaee, Timothy M. Hansen, Reinaldo Tonkoski

“…This study introduces an active probing signal-based data-driven modeling technique to accurately derive the dynamics model of a smart photovoltaic inverter operating in Volt-Watt and Freq-Watt modes, in compliance with the IEEE 1547–2018 standard. …”
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Accident Analysis Modeling and Case Study of Hydrogen Refueling Station Using Root Cause Analysis (RCA) by Il Jae Lee, A Ran Lee, Kyung-Sun Lee

“…The RCA modeling map developed in this study uses accident cause investigation data from accident investigation reports over the past five years, which include information on the organizational structure and operational status of hydrogen refueling stations, as well as the RCA handbook. …”
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Designing a Model for Implementing Digital Banking Policy Based on Using Big Data in Iranian Banking Industry by Rahmatollah Gholipour Souteh, Hamed Esmaeili Rad

“…Results The resulting model identifies 15 main themes, including Big Data Management, Data Governance (encompassing Data Collection, Data Refinement, Data Design and Modeling, Data Security), Data Regulation, Various Sources of Data Acquisition, Trust in Big Data Analysis, the Banking System Ecosystem, Organizational Agility, Big Data Analysis Tools, Scenario Development (practical application of data), Executive Structure, Improvement of Banks' Business, Customer Orientation, Transparency, Technological Infrastructure, and Dominant Culture. …”
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Sex Differences in Profile and In‐Hospital Death for Acute Stroke in Chile: Data From a Nationwide Hospital Registry by Marilaura Nuñez, Ma.Ignacia Allende, Francisca González, Gabriel Cavada, Craig S. Anderson, Paula Muñoz Venturelli

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Intense Hard X-Ray Emissions in C-class Flares: A Statistical Study with ASO-S/HXI Data by Changxue Chen, Yang Su, Wei Chen, Jingwei Li, Fu Yu, Weiqun Gan

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A Real Network Environment Dataset for Traffic Analysis by Wei Jiang, Bin Zhang, Qixun Zhu, Conghui Liao, Wenyong Wang

“…Abstract The objective of internet traffic analysis is to identify latent patterns and ascertain the true state of internet operations by examining traffic data. …”
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An overview of pink eye infection to evaluate its medications: group decision-making approach with 2-tuple linguistic T-spherical fuzzy WASPAS method by M. Waheed Rasheed, Hind Y. Saleh, Areen A. Salih, Jahangeer Karamat, Muhammad Bilal

“…The constructed multi-attribute group decision-making framework includes the following scenario: (1) In contrast to other types of fuzzy sets, the 2-tuple linguistic T-spherical fuzzy set (2TLT-SFS) looks to be a potent tool for dealing with informational inconsistencies in decision-making scenarios; (2) in order to render the 2TLT-SF accumulation details processing more flexible, the addition, multiplication, scalar multiplication, and exponential laws that are predicated on the Schweizer-Sklar collection of t-conorms and t-norms are described; (3) the Schweizer-Sklar weighted average and Schweizer-Sklar weighted geometric operators are then put forward employing the aforementioned operations to combine the data; (4) subsequently, using newly developed operators (referred to as 2TLT-SF Schweizer-Sklar weighted average and 2TLT-SF Schweizer-Sklar weighted geometric), this work enhances the conventional weighted aggregated sum product assessment (WASPAS) approach. …”
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Relative fat mass as a predictor of gallstones: insights from national health and nutrition examination survey data by Xiaochun Lin, Hao Lin, Jing Xu, Shouxing Yang, Lei Miao

“…Methods A cross-sectional analysis was conducted on the data from the NHANES 2017–2020. …”
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Construction and validation of nomogram prediction model for ketoacidosis in elderly diabetic patients based on baseline data and glycolipid metabolism by Aijin Niu, Jing Zhuang, Yangdi Li, Wei Wei

“…The effectiveness of the model was evaluated by Receiver Operating Characteristiv (ROC) curve, calibration curve analysis, and decision curve analysis (DCA). …”
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Air Traffic Trends and UAV Safety: Leveraging Automatic Dependent Surveillance–Broadcast Data for Predictive Risk Mitigation by Prasad Pothana, Paul Snyder, Sreejith Vidhyadharan, Michael Ullrich, Jack Thornby

“…The framework was developed using historical Automatic Dependent Surveillance–Broadcast (ADS-B) data obtained from the OpenSky Network. Historical flight data from Class B, C, and D airports in California are processed, and statistical analysis is carried out to identify temporal variations in flight traffic, including daily, weekly, and seasonal trends. …”
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Financial Data as a Mirror of an Economic Story. An Empirical Approach to the Impact of the COVID19 Pandemic on the Financial Equilibrium by Simona NICOLAE, George-Eduard GRIGORE, Radu-Cristian MUȘETESCU

“… The present article aims to analyze how the imbalances generated by the economic and medical crisis caused by the COVID 19 pandemic in 2020 were reflected in the balance and economic performance at the microeconomic level. Two companies operating in two of the most affected economic areas in 2020, Tourism and Pharmaceutical Industry, represented the foundation of our analysis. …”
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