State-of-the-art review and critical success factors for mobile business intelligence

Due to ubiquitous information requirements, market interest in mobile business intelligence (BI) has grown markedly. However, mobile BI market is a relatively new area that has been driven primarily by the IT industry. Yet, there is a lack of systematic study on the critical success factors for mobile BI. This research reviews the state-of-the-art of mobile BI, and explores the critical success factors based on a rigorous examination of the academic and practitioner literature. The study reveals that critical success factors of mobile BI generally fall into four key dimensions, namely security, mobile technology, system content and quality, and organisational support perspectives. The various research findings will be useful to organisations which are considering or undertaking mobile business intelligence initiatives

Visual programming tools for parallel processing

With the increased complexity of applications, parallel computing has proved to be an alternative to supercomputing in solving large problems. Although the performance and cost-performance benefits of parallel systems are attractive, the difficulties in pro-gramming have been a major hindrance in greater acceptance.Master of Applied Scienc

VHDL Modeling Of Fetal QRS Complex Detection Algorithm

Fetal Heart Rate (FHR) monitoring using electrocardiogram (ECG) is important to detect the condition of the fetus during pregnancy. An algorithm has been adopted and improved to extract the maternal and fetal QRS interval from the raw AECG data. The algorithm is based on cross-correlation, adaptive thresholding and maternal template subtraction

Localized matching using Earth Mover's Distance towards discovery of common patterns from small image samples

This paper proposes a new approach for the discovery of common patterns in a small set of images by region matching. The issues in feature robustness, match-ing robustness and noise artifact are addressed to delve into the potential of using regions as the basic matching unit. We novelly employ the many-to-many (M2M) matching strategy, specifically with the Earth Mover’s Distance (EMD), to increase resilience towards the structural inconsistency from improper region segmentation. However, the matching pattern of M2M is dispersed and unregulated in nature, lead-ing to the challenges of mining a common pattern while identifying the underlying transformation. To avoid analysis on unregulated matching, we propose localized matching for the collaborative mining of common patterns from multiple images. The patterns are refined iteratively using the expectation-maximization algorithm by taking advantage of the ‘crowding ’ phenomenon in the EMD flows. Experimen-tal results show that our approach can handle images with significant image noise and background clutter. To pinpoint the potential of Common Pattern Discovery (CPD), we further use image retrieval as an example to show the application of CPD for pattern learning in relevance feedback

VPEcons: A Visual Constructor for Parallel Programming

The performance and cost-performance benefits of parallel systems make them attractive platforms for many applications. But, these are unfortunately offset by the difficulties of programming parallel computers. Therefore, programming tools are the key to achieve greater success in developing applications for parallel architectures. This paper describes a new tool, VPEcons, for parallel programming development. It uses graphics to assist in the design of parallel programs. To facilitate the portability of the constructor, a VPEcons Builder has also been developed. It is a tool for creating basic component blocks and binding an existing language to the blocks created. The usefulness of the constructor is demonstrated with a parallel discrete-event simulation example and by comparing it with other visual parallel programming tools. Keywords: visual programming, BLOX methodology, parallel programming, message passing model, process-processor mapping, MPI, CODE, HeNCE, parallel discrete-ev..