Vision-Based Fuzzy 2D Motion Control of a Model Helicopter

©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.Presented at NAFIPS 2006 : 2006 Annual Meeting of the North American Fuzzy Information Processing Society : Montréal, Canada, 3-6 June 2006.DOI: 10.1109/NAFIPS.2006.365497In this paper the 2D motion of a model helicopter is studied. The position control of a 2D model helicopter falls into complex nonlinear problems domain which makes it rather hard. In this paper a fuzzy controller is proposed to stabilize the helicopter on a designated target. The 3D model of the helicopter is simplified to derive a 2D model and all the states are assumed to be measurable. Based on the model, it was possible to decouple the position and orientation control of the helicopter. However the two parts are related through a fuzzy rule base. To verify the proposed method a simulation program is written in C++ which takes advantages of OpenGL to enable having 3D features. The response graphs are then presented       

Juxtaposition of Women, Culture, and Nature in Alice Walker's Possessing the Secret of Joy

The present paper focuses on the tradition of women's circumsicion in the African tribe of Olinkan in Alice Walker's Possesing the Secret of Joy. The Olinkans are asked by the white settlers to stop women's mutilation, but Olinkan men continue this custom stealthily to ensure their patriarchial dominance. This novel is a complicated juxtaposition of two different types of oppression: one by White male colonizers over an African native land, and the other one by the native Olinkan men over native women. In this juxtaposition women and land are both victims exploited and manipulated by men, no matter Black or White. This novel is also seen as a fertile ground to analyze the dual domination of both nature and women by the Olinkan men and White colonizers who are both trying to impose their androcentric rules that are created to dominate women and land, respectively

BN Nanotube Serving as a Gas Chemical Sensor for N₂O by Parallel Electric Field

Density functional theory calculations were performed to understand the electronic properties of C₂₄, B₁₂N₁₂, B₁₂P₁₂, and (6, 0) BNNT interacted with N₂O molecule in the presence and absence of an external electric field using the B3LYP method and 6-31G** basis set. The adsorption of N₂O from O-side on the surface of (6, 0) BNNT has high sensitivity in comparison with B₁₂N₁₂ nano-cage. The adsorption energy of N₂O (O-side) on the sidewalls of B₁₂N₁₂ and BNNT in the presence of an electric field are −21.01 and −15.48 kJ mol⁻¹, respectively. Our results suggest that in the presence of an electric field, the B₁₂N₁₂ nano-cage is the more energetically notable upon the N₂O adsorption than (6, 0) BNNT, C₂₄, and B₁₂P₁₂. Whereas, our results indicate that the electronic property of BNNT is more sensitive to N₂O molecule at the presence of an electric field than B₁₂N₁₂ nano-cage. It is anticipated that BNNT could be a favorable gas sensor for the detection of N₂O molecule. © 2016, Springer Science+Business Media New York

Modelling peri-perceptual brain processes in a deep learning spiking neural network architecture

Familiarity of marketing stimuli may affect consumer behaviour at a peri-perceptual processing level. The current study introduces a method for deep learning of electroencephalogram (EEG) data using a spiking neural network (SNN) approach that reveals the complexity of peri-perceptual processes of familiarity. The method is applied to data from 20 participants viewing familiar and unfamiliar logos. The results support the potential of SNN models as novel tools in the exploration of peri-perceptual mechanisms that respond differentially to familiar and unfamiliar stimuli. Specifically, the activation pattern of the time-locked response identified by the proposed SNN model at approximately 200 milliseconds post-stimulus suggests greater connectivity and more widespread dynamic spatio-temporal patterns for familiar than unfamiliar logos. The proposed SNN approach can be applied to study other peri-perceptual or perceptual brain processes in cognitive and computational neuroscience