Related papers: Large Data Acquisition and Analytics at Synchrotro…
Deep learning systems have become increasingly energy- and computation-intensive, raising concerns about their environmental impact. As organizers of the Detection and Classification of Acoustic Scenes and Events (DCASE) challenge, we…
Centralized RAG pipelines struggle with heterogeneous and privacy-sensitive data, especially in distributed healthcare settings where patient data spans SQL, knowledge graphs, and clinical notes. Clinicians face difficulties retrieving rare…
With the rapid rise of intelligent data services, modern enterprises increasingly require efficient, multimodal, and cost-effective data analytics infrastructures. However, in ByteDance's production environments, existing systems fall short…
In this proceeding, we describe the scientific motivation and technical development of the Colorado High-resolution Echelle Stellar Spectrograph (CHESS), focusing on the hardware advancements and testing supporting the second flight of the…
The ATLAS Event Streaming Service (ESS) at the LHC is an approach to preprocess and deliver data for Event Service (ES) that has implemented a fine-grained approach for ATLAS event processing. The ESS allows one to asynchronously deliver…
Accurate single-cell analysis is critical for diagnostics, immunomonitoring, and cell therapy, but coincident events - where multiple cells overlap in a sensing zone - can severely compromise signal fidelity. We present a hybrid framework…
Astronomical photometry is the science of measuring the flux of a celestial object. Since its introduction, the CCD has been the principle method of measuring flux to calculate the apparent magnitude of an object. Each CCD image taken must…
The promise of increasing channel counts in high density ($> 10^4$) neural Microelectrode Arrays (MEAs) for high resolution recording comes with the curse of developing faster characterization strategies for concurrent acquisition of…
Battery Energy Storage Systems (BESSs) are increasingly critical to power-system stability, yet their operation and maintenance remain dominated by reactive, expert-dependent diagnostics. While cell-level inconsistencies provide early…
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…
Authentication and encryption are traditionally treated as two separate processes in wireless networks, this paper integrates user authentication into the process of solving eavesdropping attacks. A compressed sensing (CS)-based framework…
Collaborative Intrusion Detection Systems (CIDS) are increasingly adopted to counter cyberattacks, as their collaborative nature enables them to adapt to diverse scenarios across heterogeneous environments. As distributed critical…
The last decades have seen a surge of interests in distributed computing thanks to advances in clustered computing and big data technology. Existing distributed algorithms typically assume {\it all the data are already in one place}, and…
X-ray absorption spectroscopy (XAS) is a powerful characterization technique for probing the local chemical environment of absorbing atoms. However, analyzing XAS data presents significant challenges, often requiring extensive,…
As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented comprehensiveness, unobtrusiveness, and ecological validity.…
The space ultraviolet (UV) is a critical astronomical observing window, where a multitude of atomic, ionic, and molecular signatures provide crucial insight into planetary, interstellar, stellar, intergalactic, and extragalactic objects.…
Cloud data centers are evolving fast. At the same time, today's large-scale data analytics applications require non-trivial performance tuning that is often specific to the applications, workloads, and data center infrastructure. We propose…
The analysis of large-scale complex networks is a major challenge in the Big Data domain. Given the large-scale of the complex networks researchers commonly deal with nowadays, the use of localized information (i.e. restricted to a limited…
As scientific data repositories and filesystems grow in size and complexity, they become increasingly disorganized. The coupling of massive quantities of data with poor organization makes it challenging for scientists to locate and utilize…
The ATLAS collaboration defines methods, establishes procedures, and organises advisory groups to manage the publication processes of scientific papers, conference papers, and public notes. All stages are managed through web systems,…