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Scientists today collect, analyze, and generate TeraBytes and PetaBytes of data. These data are often shared and further processed and analyzed among collaborators. In order to facilitate sharing and data interpretations, data need to carry…
Large, open datasets can accelerate ecological research, particularly by enabling researchers to develop new insights by reusing datasets from multiple sources. However, to find the most suitable datasets to combine and integrate,…
High-level I/O libraries, such as HDF5 and PnetCDF, are commonly used by large-scale scientific applications to perform I/O tasks in parallel. These I/O libraries store the metadata such as data types and dimensionality along with the raw…
Data Warehouses are structures with large amount of data collected from heterogeneous sources to be used in a decision support system. Data Warehouses analysis identifies hidden patterns initially unexpected which analysis requires great…
Longitudinal studies are frequently used in medical research and involve collecting repeated measures on individuals over time. Observations from the same individual are invariably correlated and thus an analytic approach that accounts for…
A large number of cloud middleware platforms and tools are deployed to support a variety of Internet of Things (IoT) data analytics tasks. It is a common practice that such cloud platforms are only used by its owners to achieve their…
Scientific research frequently involves the use of computational tools and methods. Providing thorough documentation, open-source code, and data -- the creation of reproducible computational research -- helps others understand a…
In recent IoT (Internet of Things) and Web 2.0 technologies, a critical problem arises with respect to storing and processing the large amount of collected data. In this paper we develop and evaluate distributed infrastructures for storing…
Using parallel embedded systems these days is increasing. They are getting more complex due to integrating multiple functionalities in one application or running numerous ones concurrently. This concerns a wide range of applications,…
A status updating system is considered in which multiple data sources generate packets to be delivered to a destination through a shared energy harvesting sensor. Only one source's data, when available, can be transmitted by the sensor at a…
With advances in multimedia technologies and the proliferation of smart phone, digital cameras, storage devices, there are a rapidly growing massive amount of multimedia data collected in many applications such as multimedia retrieval and…
Open-weight large language models (LLMs) are usually named as model artifacts, but production users often consume them as hosted API services. This paper argues that the operational unit is a service object: a provider-specific,…
Hash coding has been widely used in the approximate nearest neighbor search for large-scale image retrieval. Recently, many deep hashing methods have been proposed and shown largely improved performance over traditional…
As the amount of scientific data continues to grow at ever faster rates, the research community is increasingly in need of flexible computational infrastructure that can support the entirety of the data science lifecycle, including…
A package's source code repository records the development history of the package, providing indispensable information for the use and risk monitoring of the package. However, a package release often misses its source code repository due to…
Real-world data typically contain repeated and periodic patterns. This suggests that they can be effectively represented and compressed using only a few coefficients of an appropriate basis (e.g., Fourier, Wavelets, etc.). However, distance…
A similarity join aims to find all similar pairs between two collections of records. Established approaches usually deal with synthetic differences like typos and abbreviations, but neglect the semantic relations between words. Such…
Given the proliferation of the massive machine type communication devices (MTCDs) in beyond 5G (B5G) wireless networks, energy harvesting (EH) aided next generation multiple access (NGMA) systems have drawn substantial attention in the…
We consider the problem of sampling from a posterior distribution arising in Bayesian inverse problems in science, engineering, and imaging. Our method belongs to the family of independence Metropolis-Hastings (IMH) sampling algorithms,…
In this paper we propose a bayesian approach for near-duplicate image detection, and investigate how different probabilistic models affect the performance obtained. The task of identifying an image whose metadata are missing is often…