A fully coupled ship motion and sloshing analysis in various container geometries

Damage to Grass Covered Slopes Due to Overtopping

Many dike failures have been ignited by damage due to erosion on the landward slopes. This paper investigates how grass covered slopes perform when being attacked by overtopping flow during storm surges. Based on observations during a number of simulator tests, damage is classified into three types 'head-cut', 'roll-up' and 'collapse' depending...

Roadmap on digital holography-based quantitative phase imaging

Quantitative Phase Imaging (QPI) provides unique means for the imaging of biological or technical microstructures, merging beneficial features identified with microscopy, interferometry, holography, and numerical computations. This roadmap article reviews several digital holography-based QPI approaches developed by prominent research groups....

Metadata Representations for Queryable ML Model Zoos

Machine learning (ML) practitioners and organizations are building model zoos of pre-trained models, containing metadata describing properties of the ML models and datasets that are useful for reporting, auditing, reproducibility, and interpretability purposes. The metatada is currently not standardised; its expressivity is limited; and there is...

Amalur: Next-generation Data Integration in Data Lakes

Data science workflows often require extracting, preparing and integrating data from multiple data sources. This is a cumbersome and slow process: most of the times, data scientists prepare data in a data processing system or a data lake, and export it as a table, in order for it to be consumed by a Machine Learning (ML) algorithm. Recent...

Join Path-Based Data Augmentation for Decision Trees

Machine Learning (ML) applications require high-quality datasets. Automated data augmentation techniques can help increase the richness of training data, thus increasing the ML model accuracy. Existing solutions focus on efficiency and ML model accuracy but do not exploit the richness of dataset relationships. With relational data, the challenge...

Dynamic Digital Twin: Diagnosis, Treatment, Prediction, and Prevention of Disease During the Life Course

A digital twin (DT), originally defined as a virtual representation of a physical asset, system, or process, is a new concept in health care. A DT in health care is not a single technology but a domain-adapted multimodal modeling approach incorporating the acquisition, management, analysis, prediction, and interpretation of data, aiming to...

Optimizing ML Inference Queries Under Constraints

The proliferation of pre-trained ML models in public Web-based model zoos facilitates the engineering of ML pipelines to address complex inference queries over datasets and streams of unstructured content. Constructing optimal plan for a query is hard, especially when constraints (e.g. accuracy or execution time) must be taken into consideration...

Macaroni: Crawling and Enriching Metadata from Public Model Zoos

Machine learning (ML) researchers and practitioners are building repositories of pre-trained models, called model zoos. These model zoos contain metadata that detail various properties of the ML models and datasets, which are useful for reporting, auditing, reproducibility, and interpretability. Unfortunately, the existing metadata...

Metadata Representations for Queryable Repositories of Machine Learning Models

Machine learning (ML) practitioners and organizations are building model repositories of pre-trained models, referred to as model zoos. These model zoos contain metadata describing the properties of the ML models and datasets. The metadata serves crucial roles for reporting, auditing, ensuring reproducibility, and enhancing interpretability....

Topio Marketplace: Search and Discovery of Geospatial Data

The increasing need for data trading has created a high demand for data marketplaces. These marketplaces require a set of valueadded services, such as advanced search and discovery, that have been proposed in the database research community for years, but are yet to be put to practice. In this paper we propose to demonstrate the Topio...

Accelerating Machine Learning Queries with Linear Algebra Query Processing

The rapid growth of large-scale machine learning (ML) models has led numerous commercial companies to utilize ML models for generating predictive results to help business decision-making. As two primary components in traditional predictive pipelines, data processing, and model predictions often operate in separate execution environments,...

An Empirical Performance Comparison between Matrix Multiplication Join and Hash Join on GPUs

Recent advances in Graphic Processing Units (GPUs) have facilitated a significant performance boost for database operators, in particular, joins. It has been intensively studied how conventional join implementations, such as hash joins, benefit from the massive parallelism of GPUs. With the proliferation of machine learning, more databases...

Optimizing Machine Learning Inference Queries for Multiple Objectives

Given a set of pre-trained Machine Learning (ML) models, can we solve complex analytic tasks that make use of those models by formulating ML inference queries? Can we mitigate different tradeoffs, e.g., high accuracy, low execution costs and memory footprint, when optimizing the queries? In this work we present different multi-objective ML...

Amalur: Data Integration Meets Machine Learning

Machine learning (ML) training data is often scattered across disparate collections of datasets, called data silos. This fragmentation poses a major challenge for data-intensive ML applications: integrating and transforming data residing in different sources demand a lot of manual work and computational resources. With data privacy and...

Data Lakes: A Survey of Functions and Systems

Data lakes are becoming increasingly prevalent for Big Data management and data analytics. In contrast to traditional 'schema-on-write' approaches such as data warehouses, data lakes are repositories storing raw data in its original formats and providing a common access interface. Despite the strong interest raised from both academia and...