Crop Classification by Forward Neural Network with Adaptive Chaotic Particle Swarm Optimization

Sensors, 2011, 11(5), 4721-4743

Yudong Zhang and Lenan Wu

“This paper proposes a hybrid crop classifier for polarimetric synthetic aperture radar (SAR) images. The feature sets consisted of span image, the H/A/α decomposition, and the gray-level co-occurrence matrix (GLCM) based texture features. Then, the features were reduced by principle component analysis (PCA). Finally, a two-hidden-layer forward neural network (NN) was constructed and trained by adaptive chaotic particle swarm optimization (ACPSO). K-fold cross validation was employed to enhance generation. The experimental results on Flevoland sites demonstrate the superiority of ACPSO to back-propagation (BP), adaptive BP (ABP), momentum BP (MBP), Particle Swarm Optimization (PSO), and Resilient back-propagation (RPROP) methods. Moreover, the computation time for each pixel is only 1.08 × 10−7 s.”

Protecting Private Data on Mobile Systems based on Spatio-temporal Analysis

1st International Conference on Pervasive and Embedded Computing and Communication Systems, 2011

Sausan Yazji, Robert P. Dick, Peter Scheuermann, and Goce Trajcevski

“Mobile devices such as smart phones and laptops are in common use and carry a vast amount of personal data. This paper presents an efficient behavior-based system for rapidly detecting the theft of mobile devices in order to protect the private data of their users. Our technique uses spatio-temporal information to construct models of user motion patters. These models are used to detect theft, which may produce anomalous spatio-temporal patterns. We consider two types of user models, each of which builds on the relationship between location and time of day. Our evaluation, based on the Reality Mining dataset, shows that our system is capable of detecting an attack within 15 minutes with 81% accuracy.”

Comparison of Spatial Knowledge Acquisition with Different Presentation Forms in the Context of GPS-based Pedestrian Navigation

GeoViz: Linking Geovisualization with Spatial Analysis and Modeling, 10-11 March 2011, Hamburg, Germany

Haosheng Huang, Manuela Schmidt, Georg Gartner

“This paper deals with current ongoing efforts to investigate the influence of different presentation forms on spatial knowledge acquisition. The acquisition of spatial knowledge based on map, augmented reality (AR), and language is analyzed and compared in an empirical test for GPS-based pedestrian navigation. This paper describes the hypothesis and the methodology. Also work in progress on interpreting the results is presented. It is proposed that the results will be very useful for future mobile navigation system developments, as navigation systems typically use different presentation forms for conveying information, which may affect users’ spatial knowledge acquistion, and thus influence wayfinding success.”