Related papers: On-the-fly Data Assessment for High Throughput X-r…

Investment in brighter sources and larger detectors has resulted in an explosive rise in the data collected at synchrotron facilities. Currently, human experts extract scientific information from these data, but they cannot keep pace with…

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli…

The increasing importance of artificial intelligence and machine learning in materials research has created demand for automated, high-throughput characterization techniques capable of rapidly generating large data sets. We describe here a…

Machine learning is attracting surging interest across nearly all scientific areas by enabling the analysis of large datasets and the extraction of scientific information from incomplete data. Data-driven science is rapidly growing,…

Multiple advantages had been identified with the integration of data acquisition into any existing system configuration and implementation. Using data acquisition as a support into a monitoring system has not only improved its overall…

Data-intensive applications often require exploratory analysis of large datasets. If analysis is performed on distributed resources, data locality can be crucial to high throughput and performance. We propose a "data diffusion" approach…

Data is evolving with the rapid progress of population and communication for various types of devices such as networks, cloud computing, Internet of Things (IoT), actuators, and sensors. The increment of data and communication content goes…

Data intensive applications often involve the analysis of large datasets that require large amounts of compute and storage resources. While dedicated compute and/or storage farms offer good task/data throughput, they suffer low resource…

In the era of big data, ensuring the quality of datasets has become increasingly crucial across various domains. We propose a comprehensive framework designed to automatically assess and rectify data quality issues in any given dataset,…

In this thesis we investigate high throughput computational methods for processing large quantities of data collected from synchrotrons and their application to spectral analysis of powder diffraction data. We also present the main product…

In conventional x-ray ptychography, diffraction data is collected by scanning a sample through a monochromatic, and spatially coherent, x-ray beam. A high-resolution image is then retrieved using an iterative algorithm. Combined with a scan…

In order to take full advantage of the U.S. Department of Energy's billion-dollar investments into the next-generation research infrastructure (e.g., exascale, light sources, colliders), advances are required not only in detector technology…

The advent of modern technology, permitting the measurement of thousands of characteristics simultaneously, has given rise to floods of data characterized by many large or even huge datasets. This new paradigm presents extraordinary…

Data-oriented applications, their users, and even the law require data of high quality. Research has divided the rather vague notion of data quality into various dimensions, such as accuracy, consistency, and reputation. To achieve the goal…

In industrial environments, data acquisition accuracy is crucial for process control and optimization. Wireless telemetry has proven to be a valuable tool for improving efficiency in well-testing operations, enabling bidirectional…

Coherent microscopy techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells. Driven by the…

With the increasing penetration of high-frequency sensors across a number of biological and physical systems, the abundance of the resulting observations offers opportunities for higher statistical accuracy of down-stream estimates, but…

Connected vehicles disseminate detailed data, including their position and speed, at a very high frequency. Such data can be used for accurate real-time analysis, prediction and control of transportation systems. The outstanding challenge…

The increasing capabilities of machine learning models, such as vision-language and multimodal language models, are placing growing demands on data in automotive systems engineering, making the quality and relevance of collected data…

Advances in technology and computing hardware are enabling scientists from all areas of science to produce massive amounts of data using large-scale simulations or observational facilities. In this era of data deluge, effective coordination…