Web services such as Twitter and Facebook provide direct access to their streaming APIs. The data generated by all of their users is forwarded in quasi-real-time to any external client requesting it: this continuous feed opens up new ways to create mashups that differ from existing data aggregation approaches, which focus on presenting with multiple widgets an integrated view of the data that i...

Debugging control software for Micro Aerial Vehicles (MAV) can be risky out of the simulator, especially with professional drones that might harm people around or result in a high bill after a crash. We have designed a framework that enables a software application to communicate with multiple MAVs from a single unified interface. In this way, visual controllers can be first tested on a low-cost...

We propose a method for the fair and efficient allocation of wireless resources over a cognitive radio system network to transmit multiple scalable video streams to multiple users. The method exploits the dynamic architecture of the Scalable Video Coding extension of the H.264 standard, along with the diversity that OFDMA networks provide. We use a game-theoretic Nash Bargaining Solution (NBS) ...

This paper presents a framework to support analysis and trend detection in historical data from Neonatal Intensive Care Unit (NICU) patients. The clinical research extensions contribute to fundamental data mining framework research through the integration of temporal abstraction and support of null hypothesis testing within the data mining processes. The application of this new data mining appr...

Temporal and spatio-temporal aggregations are important but costly operations for applications that maintain time-evolving data (data warehouses, temporal databases, etc.). In this paper we examine the problem of computing such aggregates over data streams. The aggregates are maintained using multiple levels of temporal granularities: older data is aggregated using coarser granularities while m...

This paper presents a novel framework for view-dependent streaming of multiresolution meshes. In contrast to conventional progressive streaming in which the resolution of a model changes globally, our server dynamically adjusts the transmission order of the detail data with respect to the client’s current viewpoint. By extending the truly selective refinement scheme for progressive meshes to a ...

Secure knowledge management for eBusiness processes that span multiple organizations requires intraorganizational and interorganizational perspectives on security and access control issues. There is paucity in research on information assurance of distributed interorganizational eBusiness processes from a business process perspective. This paper presents a framework for secure semantic eBusiness...

This paper proposes a meta-learning framework in the context of information extraction from the Web. The proposed framework relies on learning a meta-level classifier, based on the output of base-level information extraction systems. Such systems are typically trained to recognize relevant information within documents, i.e., streams of lexical units, which differs significantly from the task of...

The change point model (CPM) framework introduced in Hawkins, Qiu, and Kang (2003) and Hawkins and Zamba (2005) provides an effective and computationally efficient method for sequentially detecting multiple changes points in streams of Gaussian random variables, when no information is available regarding the parameters of the distribution in the various segments. It has since been extended in v...

Java 8 has introduced new capabilities such as lambda expressions and streams which simplify data-parallel computing. However, as a base language for Big Data systems, it still lacks a number of important capabilities such as processing very large datasets and distributing the computation over multiple machines. This paper gives an overview of the Java 8 Streams API and proposes extensions to a...