Future Prospects of Selected Intelligent Decision Technologies and their Deployment in Information Systems

This paper presents an overview of technological prospective studies on selected classes of decision support and intelligent information systems. Technological trends and scenarios were generated from simulation experiments with hybrid models consisting of discrete-time control and discrete-event components. These trends were then merged with the outcomes of an innovative Delphi survey. Both techniques yielded a complex information technology model, capable of describing various factors relevant to the evolution and adsorption of intelligent technologies. Specifically, we investigated the development of intelligent decision support systems, recommenders, and specialized information systems supporting e-commerce, e-science, e-learning, and crisis management. The technological evolution model features software development paradigms such as DevOps, Next Release choice, and competition among system suppliers. Additionally, the survey highlighted customers’ preferences and market prospects. The foresight results are presented in the context of overall progress in information systems, software market needs, and user behavior

A hierarchical clustering based non-maximum suppression method in pedestrian detection

Conference Name:2nd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2011. Conference Address: Xi'an, China. Time:October 23, 2011 - October 25, 2011.We learned that one true positive would have a cluster with dense detected windows near the geometric center of pedestrian, so we adopted clustering methods based on ellipse Euclidean distance to get the location of pedestrian. Moreover, considering the big-size pedestrians and small ones respond differently to the same classifier and a 'weak' true positive (few fire times) may be filtered, we partitioned the non-maximum suppression process into two parts to analyze them distinctively. We call this method hierarchical non-maximum suppression. The experiment showed that our non-hierarchical clustering based method did well as proposed by Dalal and consumed much less time (nearly 100 fold less time at 150 magnitude windows), while the proposed hierarchical algorithm recalled more true positives than the non-hierarchical method (5% percent higher detection rate at FPPI = 1). 漏 2012 Springer-Verlag