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An Exploratory Data Analysis on Air Quality Data of Trivandrum
Data analysis is the most integral part of any research. It is the process of examining the data using statistical methods to identify the hidden...
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Power Quality Disturbances Data Dimensionality Reduction Using Autoencoder
Dimensionality reduction is an important techniques to reduce the size of the data in terms of number of input features so that light weight models...
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Multi-dimensional Data Optimal Classification Algorithm for Quality Evaluation of Distance Teaching in Universities
In order to effectively extract the multi-dimensional data of teaching quality evaluation and accurately evaluate the quality of network distance...
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Prediction of blast furnace gas generation based on data quality improvement strategy
The real-time energy flow data obtained in industrial production processes are usually of low quality. It is difficult to accurately predict the...
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Data Integration Method of Multi-source Feedback Evaluation for Remote Teaching Quality
Distance teaching is a teaching method widely concerned and used in the current education field, and accurate evaluation of the quality of distance...
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Beyond Data Quality: The Assessment of Data Utilization in Indonesian Telecommunication Industry
Data quality issues are exacerbated when information is distributed across heterogeneous siloes data stores throughout the organization. The nature...
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A Blockchain-Based Method for Power-Related Data Quality Auditing
Power big data technology is playing an increasingly important role in the regulation and data analysis of smart grids, which face “data silos” and...
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Sustainable Development in Water Quality Assessment: Data for Khadakwasla Dam, Pune
The study represents data collection and analysis of the water quality index (WQI) and different parameters considered for calculating water quality...
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Comprehensive Evaluation Method for Traffic Flow Data Quality Based on Grey Correlation Analysis and Particle Swarm Optimization
Nowadays, data are more and more used for intelligent modeling and prediction, and the comprehensive evaluation of data quality is getting more and...
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Data Quality Management for Interoperability
The challenge of enhancing and generalizing interoperability as an important pre-requisite for Digital Twin is often hindered by the fact that data...
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Taxonomy of Data Quality Metrics in Digital Citizen Science
Data quality is key in the success of a citizen science project. Valid datasets serve as evidence for scientific research. Numerous projects have...
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Edge Learning-Based Efficient Data Imputation of Water Quality
Water quality monitoring is critical for develo** effective surface water management strategies, whereas data preprocessing is the foundation for...
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A Multidimensional Model of Wireless Sensor Data Quality
This article presents a multidimensional model of WSN data quality that links the types of errors with the methods for their detection and...
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Exploring Software Quality Through Data-Driven Approaches and Knowledge Graphs
Context: The quality of software systems has always been a crucial task and has led to the establishment of various reputable software quality...
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Data quality augmentation and parallel network modeling for residual life prediction of lithium-ion batteries
Research on the data-driven health state estimation of lithium-ion batteries has gained significant attention in recent years. However, the practical...
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Data Quality Evaluation Method Based on Density Clustering Algorithm and Its Application
Data quality assessment is mainly to analyze, evaluate and calculate the collected original information, and then to obtain the decision results. At...
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Factors contributing to poor healthcare data quality: qualitative study from Southern Ethiopia
BackgroundAlthough quality information is key to reliable healthcare, health management information system (HMIS) data in low-income countries are...
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Data Quality Driven Design Patterns for Internet of Things
Many IoT applications are now using microservices design concepts and have developed as an emergent technology by leveraging containerization,...
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Creating Synthetic Training Data for Machine Vision Quality Gates
Manufacturing companies face the challenge of combining increasing productivity and quality standards with customer″=oriented mass production. To...
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Machine Learning-Aided Prediction of Pile Behaviour: The Role of Data Quality
Machine learning (ML), a data-based approach, has recently emerged as an effective method to predict the behaviour of pile foundation. However, the...