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       

The Devil is not in the Detail: Representational absence and Stereotyping in the Trojan Horse News Story

Using Content Analysis, this study investigated the coverage of the Trojan Horse news story aiming to ascertain whether its representation by the British press emphasised ‘Islamist extremism’ over ‘poor school governance’. The sample coverage was extracted from five national newspapers and ranged from 9 June (the date of release of the Ofsted Advice Note) to 26 June 2014. Our analysis shows that the coverage reported evidence of Islamist ideology much more frequently (61.5%) than evidence of poor governance (38.5%). This suggests that the Trojan Horse news story was predominantly represented as a case of Islamist extremism and therefore covered in an unbalanced manner. Such a partial coverage relied on ideological dualisms and negative stereotypes to represent Islam and Muslims, and on the textual strategy of selecting some features (extremism) whilst omitting others (governors’ professional misconduct). This bias has arguably diverted attention away from systemic problems within the national school system whilst reinforcing Islamophobic discourses

Catalytic Ozonation of Phenolic Wastewater: Identification and Toxicity of Intermediates

A new strategy in catalytic ozonation removal method for degradation and detoxification of phenol from industrial wastewater was investigated. Magnetic carbon nanocomposite, as a novel catalyst, was synthesized and then used in the catalytic ozonation process (COP) and the effects of operational conditions such as initial pH, reaction time, and initial concentration of phenol on the degradation efficiency and the toxicity assay have been investigated. The results showed that the highest catalytic potential was achieved at optimal neutral pH and the removal efficiency of phenol and COD is 98.5% and 69.8%, respectively. First-order modeling demonstrated that the reactions were dependent on the initial concentration of phenol, with kinetic constants varying from 0.038 min−1 ([phenol]o = 1500mg/L) to 1.273 min−1 ([phenol]o = 50mg/L). Bioassay analysis showed that phenol was highly toxic to Daphnia magna (LC50 96 h = 5.6mg/L). Comparison of toxicity units (TU) of row wastewater (36.01) and the treated effluent showed that TU value, after slightly increasing in the first steps of ozonation for construction of more toxic intermediates, severely reduced at the end of reaction (2.23).Thus, COP was able to effectively remove the toxicity of intermediates which were formed during the chemical oxidation of phenolic wastewaters

Cryptosporidium infection in patients with gastroenteritis in Sari, Iran

Background: Cryptosporidiosis is a common coccidian parasite infection in patients with diarrhea that has worldwide distribution especially in developed countries. Therefore, the aim of this study was to determine the occurrence of Cryptosporidium infection in patients with gastroenteritis admitted to hospitals of Mazandaran University of Medical Sciences by parasitological and molecular methods in Sari, Iran. Methods: Stool samples were collected from 348 patients with gastroenteritis admitted to the hospitals of Medical University in the Sari and Ghaemshahr cities in Mazandaran Province, Northern Iran in 2010-2011. Oocysts of Cryptosporidium identified using Formalin-Ether concentration method and stained by Aacidfast staining (AFS) and Auramine phenol fluorescence (APF). Genomic DAN extracted from microscopically positive samples and nested PCR -RFLP by using SSU rRNA that identifies of the species of cryptosporidium. Results: In 348 patients with gastroenteritis, the most clinical symptoms were diarrhea, nausea, vomiting, dehydration, fever and weight loss. 2.3% (8 cases) of diarrheal samples tested by both microscopy and molecular methods were positive for the presence of cryptosporidium. Nested PCR products yielded unique bands of 846 bp, correspond to cryptosporidium. Species diagnosis carried out by digesting the secondary PCR product with SspI restriction enzyme, which noted 3 clearly bands of 449, 254, and 108 bp correspond to Cryptosporidium spp. Conclusion: The results of present study on Cryptosporidium spp. in this area can make a background data for control programs and further molecular analyses. Thus, further work needs to determine the origin of Cryptosporidium species in this area

Improved Stack-Slide Searches for Gravitational-Wave Pulsars

We formulate and optimize a computational search strategy for detecting gravitational waves from isolated, previously-unknown neutron stars (that is, neutron stars with unknown sky positions, spin frequencies, and spin-down parameters). It is well known that fully coherent searches over the relevant parameter-space volumes are not computationally feasible, and so more computationally efficient methods are called for. The first step in this direction was taken by Brady & Creighton (2000), who proposed and optimized a two-stage, stack-slide search algorithm. We generalize and otherwise improve upon the Brady-Creighton scheme in several ways. Like Brady & Creighton, we consider a stack-slide scheme, but here with an arbitrary number of semi-coherent stages and with a coherent follow-up stage at the end. We find that searches with three semi-coherent stages are significantly more efficient than two-stage searches (requiring about 2-5 times less computational power for the same sensitivity) and are only slightly less efficient than searches with four or more stages. We calculate the signal-to-noise ratio required for detection, as a function of computing power and neutron star spin-down-age, using our optimized searches.Comment: 19 pages, 7 figures, RevTeX

Upper bounds on position error of a single location estimate in wireless sensor networks

This paper studies upper bounds on the position error for a single estimate of an unknown target node position based on distance estimates in wireless sensor networks. In this study, we investigate a number of approaches to confine the target node position to bounded sets for different scenarios. Firstly, if at least one distance estimate error is positive, we derive a simple, but potentially loose upper bound, which is always valid. In addition assuming that the probability density of measurement noise is nonzero for positive values and a sufficiently large number of distance estimates are available, we propose an upper bound, which is valid with high probability. Secondly, if a reasonable lower bound on negative measurement errors is known a priori, we manipulate the distance estimates to obtain a new set with positive measurement errors. In general, we formulate bounds as nonconvex optimization problems. To solve the problems, we employ a relaxation technique and obtain semidefinite programs. We also propose a simple approach to find the bounds in closed forms. Simulation results show reasonable tightness for different bounds in various situations. © 2014 Gholami et al.; licensee Springer

TuNet: End-to-end Hierarchical Brain Tumor Segmentation using Cascaded Networks

Glioma is one of the most common types of brain tumors; it arises in the glial cells in the human brain and in the spinal cord. In addition to having a high mortality rate, glioma treatment is also very expensive. Hence, automatic and accurate segmentation and measurement from the early stages are critical in order to prolong the survival rates of the patients and to reduce the costs of the treatment. In the present work, we propose a novel end-to-end cascaded network for semantic segmentation that utilizes the hierarchical structure of the tumor sub-regions with ResNet-like blocks and Squeeze-and-Excitation modules after each convolution and concatenation block. By utilizing cross-validation, an average ensemble technique, and a simple post-processing technique, we obtained dice scores of 88.06, 80.84, and 80.29, and Hausdorff Distances (95th percentile) of 6.10, 5.17, and 2.21 for the whole tumor, tumor core, and enhancing tumor, respectively, on the online test set.Comment: Accepted at MICCAI BrainLes 201

TDOA based positioning in the presence of unknown clock skew

Cataloged from PDF version of article.This paper studies the positioning problem of a single target node based on time-difference-of-arrival (TDOA) measurements in the presence of clock imperfections. Employing an affine model for the behaviour of a local clock, it is observed that TDOA based approaches suffer from a parameter of the model, called the clock skew. Modeling the clock skew as a nuisance parameter, this paper investigates joint clock skew and position estimation. The maximum likelihood estimator (MLE) is derived for this problem, which is highly nonconvex and difficult to solve. To avoid the difficulty in solving the MLE, we employ suitable approximations and relaxations and propose two suboptimal estimators based on semidefinite programming and linear estimation. To further improve the estimation accuracy, we also propose a refining step. In addition, the Cramer-Rao ´ lower bound (CRLB) is derived for this problem as a benchmark. Simulation results show that the proposed suboptimal estimators can attain the CRLB for sufficiently high signal-to-noise ratios