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This paper presents an applied AI pipeline for realtime geolocation from noisy microblog streams, unifying statistical hashtag segmentation, part-of-speech-driven proper-noun detection, dependency parsing around disaster lexicons,…
Mobile network performance measurement is important for understanding mobile user experience, problem diagnosis, and service comparison. A number of crowdsourcing measurement apps (e.g., MobiPerf [4, 6] and Netalyzr [5, 7]) have been…
Adaptive networks (ANs) are effective real time techniques to process and track events observed by sensor networks and, more recently, to equip Internet of Things (IoT) applications. ANs operate over nodes equipped with collaborative…
Traditional network monitoring solutions usually lack of scalability due to their centralized nature collecting heartbeats from all network components via a single controller. As a solution, In-Band Network Telemetry (INT) framework has…
We make a case for "planetary computing" -- infrastructure to handle the ingestion, transformation, analysis and publication of global data products for furthering environmental science and enabling better informed policy-making. We draw on…
The study of dynamical systems on networks, describing complex interactive processes, provides insight into how network structure affects global behaviour. Yet many methods for network dynamics fail to cope with large or partially-known…
The increasing ubiquity of low-cost wireless sensors has enabled users to easily deploy systems to remotely monitor and control their environments. However, this raises privacy concerns for third-party occupants, such as a hotel room guest…
Modern network performance monitoring toolkits, such as perfSONAR, take a remarkable number of measurements about the local network environment. To gain a complete picture of network performance, however, one needs to aggregate data across…
The notion of grid computing has gained an increasing popularity recently as a realistic solution to many of our large-scale data storage and processing needs. It enables the sharing, selection and aggregation of resources geographically…
The rise of big data systems has created a need for benchmarks to measure and compare the capabilities of these systems. Big data benchmarks present unique scalability challenges. The supercomputing community has wrestled with these…
In an age where the distribution of information is crucial, current file sharing solutions suffer significant deficiencies. Popular systems such as Google Drive, torrenting and IPFS suffer issues with compatibility, accessibility and…
Understanding network health is essential to improve Internet reliability. For instance, detecting disruptions in peer and provider networks facilitates the identification of connectivity problems. Currently this task is time consuming for…
The parallel and distributed processing are becoming de facto industry standard, and a large part of the current research is targeted on how to make computing scalable and distributed, dynamically, without allocating the resources on…
Smart cities are growing significantly due to the growth of smart connected vehicles and Internet of Things (IoT) where a wide range of devices are connected to share data. Online mapping is one of the fundamental services offered in smart…
Smart homes have attracted much attention due to the expanding of Internet-of-Things (IoT) and smart devices. In this paper, we propose a smart gateway platform for data collection and awareness in smart home networks. A smart gateway will…
JINet is a web browser-based platform intended to democratise access to advanced clinical and genomic data analysis software. It hosts numerous data analysis applications that are run in the safety of each User's web browser, without the…
A rich amount of geographic information exists in unstructured texts, such as Web pages, social media posts, housing advertisements, and historical archives. Geoparsers are useful tools that extract structured geographic information from…
Developing generalizable AI for medical imaging requires both access to large, multi-center datasets and standardized, reproducible tooling within research environments. However, leveraging real-world imaging data in clinical research…
In the era of big data, graph sampling is indispensable in many settings. Existing sampling methods are mostly designed for static graphs, and aim to preserve basic structural properties of the original graph (such as degree distribution,…
Local news has become increasingly important in the news industry due to its various benefits. It offers local audiences information that helps them participate in their communities and interests. It also serves as a reliable source of…