Close-quarters Quadrotor flying for a pole inspection with position based visual servoing and high-speed vision

This paper presents a 100 Hz monocular position based visual servoing system to control a quadrotor flying in close proximity to vertical structures approximating a narrow, locally linear shape. Assuming the object boundaries are represented by parallel vertical lines in the image, detection and tracking is achieved using Plücker line representation and a line tracker. The visual information is fused with IMU data in an EKF framework to provide fast and accurate state estimation. A nested control design provides position and velocity control with respect to the object. Our approach is aimed at high performance on-board control for applications allowing only small error margins and without a motion capture system, as required for real world infrastructure inspection. Simulated and ground-truthed experimental results are presented.

Detection of sinkhole attack in wireless sensor networks

Generally wireless sensor networks rely of many-to-one communication approach for data gathering. This approach is extremely susceptible to sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and subsequently presents selective forwarding or change the data that carry through it. A sinkhole attack causes an important threat to sensor networks and it should be considered that the sensor nodes are mostly spread out in open areas and of weak computation and battery power. In order to detect the intruder in a sinkhole attack this paper suggests an algorithm which firstly finds a group of suspected nodes by analyzing the consistency of data. Then, the intruder is recognized efficiently in the group by checking the network flow information. The proposed algorithm's performance has been evaluated by using numerical analysis and simulations. Therefore, accuracy and efficiency of algorithm would be verified.

Telomerase activity : detection and clinical implications in human cancer

Telomerase is an extremely important enzyme required for the immortalisation of tumour cells. Because the gene is activated in the vast majority of tumour tissues and remains unused in most somatic cells, it represents a marker with huge diagnostic, prognostic and treatment implications in cancer. This article summarises the basic structure and functions of telomerase and considers its clinical implications in colorectal and other cancers.

Detection of dynamic primary user with cooperative spectrum sensing

In this paper we demonstrate that existing cooperative spectrum sensing formulated for static primary users cannot accurately detect dynamic primary users regardless of the information fusion method. Performance error occurs as the sensing parameters calculated by the conventional detector result in sensing performance that violates the sensing requirements. Furthermore, the error is accumulated and compounded by the number of cooperating nodes. To address this limitation, we design and implement the duty cycle detection model for the context of cooperative spectrum sensing to accurately calculate the sensing parameters that satisfy the sensing requirements. We show that longer sensing duration is required to compensate for dynamic primary user traffic.

Electron tomography reveals the steps in filovirus budding

The filoviruses, Marburg and Ebola, are non-segmented negative-strand RNA viruses causing severe hemorrhagic fever with high mortality rates in humans and nonhuman primates. The sequence of events that leads to release of filovirus particles from cells is poorly understood. Two contrasting mechanisms have been proposed, one proceeding via a "submarine-like" budding with the helical nucleocapsid emerging parallel to the plasma membrane, and the other via perpendicular "rocketlike" protrusion. Here we have infected cells with Marburg virus under BSL-4 containment conditions, and reconstructed the sequence of steps in the budding process in three dimensions using electron tomography of plastic-embedded cells. We find that highly infectious filamentous particles are released at early stages in infection. Budding proceeds via lateral association of intracellular nucleocapsid along its whole length with the plasma membrane, followed by rapid envelopment initiated at one end of the nucleocapsid, leading to a protruding intermediate. Scission results in local membrane instability at the rear of the virus. After prolonged infection, increased vesiculation of the plasma membrane correlates with changes in shape and infectivity of released viruses. Our observations demonstrate a cellular determinant of virus shape. They reconcile the contrasting models of filovirus budding and allow us to describe the sequence of events taking place during budding and release of Marburg virus. We propose that this represents a general sequence of events also followed by other filamentous and rod-shaped viruses.

Outbreak detection algorithms for seasonal disease data : a case study using Ross River virus disease

Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.

Electron-accepting conjugated materials based on 2-Vinyl-4,5- dicyanoimidazoles for application in organic electronics

We report the Heck coupling of 2-vinyl-4,5-dicyanoimidazole (vinazene) with selected di- and trihalo aromatics in an effort to prepare linear and branched electron-accepting conjugated materials for application in organic electronics. By selecting the suitable halo-aromatic moiety, it is possible to tune the HOMO - LUMO energy levels, absorption, and emission properties for a specific application. In this regard, materials with strong photoluminescence from blue → green → red are reported that may have potential application in organic light-emitting diodes (OLEDs). Furthermore, derivatives with strong absorption in the visible spectrum, coupled with favorable HOMO-LUMO levels, have been used to prepare promising organic photovoltaic devices (OPVs) when combined with commercially available semiconducting donor polymers.

4-hexylbithieno[3,2-b:2′3′-e]pyridine: An efficient electron-accepting unit in fluorene and indenofluorene copolymers for light-emitting devices

4-Hexylbithienopyridine has been prepared as a novel electron-accepting monomer for conjugated polymers. To test its electronic properties, alternating copolymers with fluorene and indenofluorene polymers have been prepared. The copolymers displayed reduction potentials about 0.5 V lower than for the corresponding fluorene and indenofluorene homopolymers, indicating much improved electron-accepting properties. Analysis of the microscopic morphology of thin films of the copolymers by AFM shows that they lack the extensive supramolecular order seen with the homopolymers, which is attributed to the bithienopyridine units disrupting the π-stacking. LEDs using these polymers as the emitting layer produce blue-green emission with low turn-on voltages with aluminum electrodes confirming their improved electron affinity. The indenofluorene copolymer displayed an irreversible red shift in emission at high voltages, which is attributed to oxidation of the indenofluorene units. This red shift occurred at higher potentials than for indenofluorene homopolymers in LEDs, suggesting that the heterocyclic moieties offer some protection against electrically promoted oxidation.

Topic dependent language modelling for spoken term detection

This paper investigates the effect of topic dependent language models (TDLM) on phonetic spoken term detection (STD) using dynamic match lattice spotting (DMLS). Phonetic STD consists of two steps: indexing and search. The accuracy of indexing audio segments into phone sequences using phone recognition methods directly affects the accuracy of the final STD system. If the topic of a document in known, recognizing the spoken words and indexing them to an intermediate representation is an easier task and consequently, detecting a search word in it will be more accurate and robust. In this paper, we propose the use of TDLMs in the indexing stage to improve the accuracy of STD in situations where the topic of the audio document is known in advance. It is shown that using TDLMs instead of the traditional general language model (GLM) improves STD performance according to figure of merit (FOM) criteria.

Engineering thin film semiconductor gas sensors to increase sensitivity and decrease operation temperature

Thin film nanostructured gas sensors typically operate at temperatures above 400°C, but lower temperature operation is highly desirable, especially for remote area field sensing as this reduces significantly power consumption. We have investigated a range of sensor materials based on both pure and doped tungsten oxide (mainly focusing on Fe-doping), deposited using both thermal evaporation and electron-beam evaporation, and using a variety of post-deposition annealing. The films show excellent sensitivity at operating temperatures as low as 150°C for detection of NO2. There is a definite relationship between the sensitivity and the crystallinity and nanostructure obtained through the deposition and heat treatment processes, as well as variations in the conductivity caused both by doping and heat treatmetn. The ultimate goal of this work is to control the sensing properties, including selectivity to specific gases through the engineering of the electronic properties and the nanostructure of the films.

Unusual event detection in crowded scenes

Novel computer vision techniques have been developed to automatically detect unusual events in crowded scenes from video feeds of surveillance cameras. The research is useful in the design of the next generation intelligent video surveillance systems. Two major contributions are the construction of a novel machine learning model for multiple instance learning through compressive sensing, and the design of novel feature descriptors in the compressed video domain.

Detection of rain in acoustic recordings of the environment

Environmental monitoring has become increasingly important due to the significant impact of human activities and climate change on biodiversity. Environmental sound sources such as rain and insect vocalizations are a rich and underexploited source of information in environmental audio recordings. This paper is concerned with the classification of rain within acoustic sensor re-cordings. We present the novel application of a set of features for classifying environmental acoustics: acoustic entropy, the acoustic complexity index, spectral cover, and background noise. In order to improve the performance of the rain classification system we automatically classify segments of environmental recordings into the classes of heavy rain or non-rain. A decision tree classifier is experientially compared with other classifiers. The experimental results show that our system is effective in classifying segments of environmental audio recordings with an accuracy of 93% for the binary classification of heavy rain/non-rain.