Enhancing Data Recovery in RAID6: A Comparative Analysis of Row-Diagonal Parity Codes by Zhang Wenxu

“…This approach markedly improves RAID6's functionality by optimizing recovery processes, thus supporting high-volume storage systems with stringent data integrity requirements. The potential for future enhancements in RAID6 data recovery through further research into hardware acceleration and artificial intelligence is also acknowledged, aiming to refine recovery times and efficiency in large-scale storage applications.…”
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APPROXIMATING MATHEMATICAL MODEL DEVELOPMENT ACCORDING TO POINT EXPERIMENTAL DATA THROUGH “CUT-GLUE” METHOD by Rudolf Anatolyevich Neydorf

“…The obtained results are illustrated w ith the specific technical sample applications of the method to practical pr oblems, tabular and graphical data.…”
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Enhancing Brain Tumor Detection: A Comparative Study of CNN Architectures Using MRI Data by Zhu Zhimeng

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Predicting ecotopes from hydrodynamic model data: Towards an ecological assessment of nature-based solutions by Soesja Brunink, Gijs G. Hendrickx

“…The method successfully reproduced an existing ecotope-map, which is dependent on real-time data such as aerial photographs. The developed method not only proves applicable in assessing the current ecological state and future ecological shifts for hypothetical scenarios but also demonstrates utility in predicting future situations, providing valuable insights for decision-makers in estuarine ecosystem management and contributing to climate and environmental preservation goals.…”
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EEFDA: enabling efficient and fault-tolerant data aggregation scheme without TA in smart grid by Yuanyuan Wang, Liqiang Wu, Yiliang Han, Xuguang Wu, Ruifeng Li

“…Most existing solutions depend on auxiliary computation in trusted authority for data aggregation. However, for practical smart grid applications, it is often unrealistic to expect these centers to remain online at all times. …”
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Status Quo and Prospect of Multi-source Heterogeneous Data Fusion Technology for New Power System by Zhen WANG, Dong LIU, Chongyou XU, Jiaming WENG, Fei CHEN

“…Then the data model of the new power system and the hierarchical division of multi-source heterogeneous data fusion technologies are introduced, and the advantages and limitations of the key fusion technologies and their applicable scenarios are analyzed. …”
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Balancing Privacy and Accuracy: Exploring the Impact of Data Anonymization on Deep Learning Models in Computer Vision by Jun Ha Lee, Su Jeong You

“…In recent years, the quality of training data has emerged as a critical factor for ensuring effectiveness in real-world scenarios. …”
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Simultaneous Wavelength- and Mode-Division (De)multiplexing for High-Capacity On-Chip Data Transmission Link by Liangshun Han, Song Liang, Junjie Xu, Lijun Qiao, Hongliang Zhu, Wei Wang

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Analysis of Multivariate Indoor Building Data: A Comparative Study of Time-Series Clustering Methods by Quoc-Dung Ngo, Ly-Huynh Phan

“…Clustering multivariate time-series data is crucial for uncovering complex temporal patterns in dynamic environments, such as building indoor conditions and behavior where variables like temperature, humidity, and CO2 concentration evolve simultaneously. …”
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Benchmarking universal machine learning interatomic potentials for rapid analysis of inelastic neutron scattering data by Bowen Han, Yongqiang Cheng

“…We further assess these models in real-world applications by using them to analyze experimental inelastic neutron scattering data collected on a variety of materials. …”
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Exploring Purpose-Driven Methods and a Multifaceted Approach in Dam Health Monitoring Data Utilization by Zhanchao Li, Ebrahim Yahya Khailah, Xingyang Liu, Jiaming Liang

“…This review examines monitoring data applications, covering structural health assessment methods, historical motivations, and key challenges. …”
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Measured spectrum environment map dataset with multi-radiation sources in urban scenariosMendeley Data by Haotian Zou, Qiuming Zhu, Qianhao Gao, Jie Wang, Zhipeng Lin, Yang Huang, Qihui Wu, Weizhi Zhong

“…It includes spectrum strength or received signal strength (RSS) data in dBm for 80×105 grids. Each grid includes the information such as longitude, latitude, altitude, and time. …”
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Bridging Interoperability Gaps Between LCA and BIM: Analysis of Limitations for the Integration of EPD Data in IFC by Aitor Aragón, Paulius Spudys, Darius Pupeikis, Óscar Nieto, Marcos Garcia Alberti

“…While prior studies have analyzed the environmental data in IFC, this research is significant in two key areas. …”
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Time-Shifted Maps for Industrial Data Analysis: Monitoring Production Processes and Predicting Undesirable Situations by Tomasz Blachowicz, Sara Bysko, Szymon Bysko, Alina Domanowska, Jacek Wylezek, Zbigniew Sokol

“…The rapid advancement of computing power, combined with the ability to collect vast amounts of data, has unlocked new possibilities for industrial applications. …”
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Artificial Intelligence-Based Transmission Frequency Prediction in Cable Systems Using Electromagnetic Field Data by Abbas Seif, Hamid Radmanesh, Amir Ahmarinejad, Ahmad Ali Ashrafian

“…Findings validate AI’s potential to streamline frequency estimation in cable systems, bridging theoretical and data-driven paradigms. This work advances applications in electrical and telecommunications engineering, emphasizing scalable, intelligent solutions for electromagnetic analysis.…”
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Automated Classification Model for Elementary Mathematics Diagnostic Assessment Data Based on TF-IDF and XGBoost by Seonghyun Park, Seungmin Oh, Woncheol Park

“…This study highlights the automation and scalability of educational data analysis, suggesting potential applications across various subjects and grade levels.…”
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Reflections on dynamic prediction of Alzheimer’s disease: advancements in modeling longitudinal outcomes and time-to-event data by Durong Chen, Meiling Zhang, Hongjuan Han, Yalu Wen, Hongmei Yu

“…Future work should consider various data types, complex longitudinal data, missing data, assumption violations, survival outcomes, and interpretability of models.…”
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Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms by Abdul Aabid, Md Abdul Raheman, Meftah Hrairi, Muneer Baig

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Enhancing landslide susceptibility predictions with XGBoost and SHAP: a data-driven explainable AI method by Danish Khan, Wasim Akram, Sajid Ullah

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Learning based lower limb joint kinematic estimation using open source IMU data by Benjamin Hur, Sunin Baek, Inseung Kang, Daekyum Kim

“…This framework not only reduces the need for extensive data collection but also enhances personalized gait analysis, enabling more efficient and accessible applications in both clinical assessments and real-world environments for broader use.…”
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