Autonomous UAVs wildlife detection using thermal imaging, predictive navigation and computer vision

There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.

Design and flight testing of a bio-inspired plume tracking algorithm for unmanned serial vehicles

There is an increased interest on the use of UAVs for environmental research such as tracking bush fires, volcanic eruptions, chemical accidents or pollution sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A method for generating sparse plumes in a virtual environment was also developed. Results indicated the ability of the algorithms to track plumes in 2D and 3D. The system has been tested with hardware in the loop (HIL) simulations and in flight using a CO2 gas sensor mounted to a multi-rotor UAV. The UAV is controlled by the plume tracking algorithm running on the ground control station (GCS).

Differential recognition by tick-resistant cattle of the recombinantly expressed Rhipicephalus microplus serine protease inhibitor-3 (RMS-3)

Rhipicephalus micro plus is an important bovine ectoparasite, widely distributed in tropical and subtropical regions of the world causing large economic losses to the cattle industry. Its success as an ectoparasite is associated with its capacity to disarm the antihemostatic and anti-inflammatory reactions of the host. Serpins are protease inhibitors with an important role in the modulation of host-parasite interactions. The cDNA that encodes for a R. microplus serpin was isolated by RACE and subsequently cloned into the pPICZ alpha A vector. Sequence analysis of the cDNA and predicted amino acid showed that this cDNA has a conserved serpin domain. B- and T-cell epitopes were predicted using bioinformatics tools. The recombinant R. microplus serpin (rRMS-3) was secreted into the culture media of Pichia pastoris after methanol induction at 0.2 mg l(-1) qRT-PCR expression analysis of tissues and life cycle stages demonstrated that RMS-3 was mainly expressed in the salivary glands of female adult ticks. Immunological recognition of the rRMS-3 and predicted B-cell epitopes was tested using tick-resistant and susceptible cattle sera. Only sera from tick-resistant bovines recognized the B-cell epitope AHYNPPPPIEFT (Seq7). The recombinant RMS-3 was expressed in P. pastoris, and ELISA screening also showed higher recognition by tick-resistant bovine sera. The results obtained suggest that RMS-3 is highly and specifically secreted into the bite site of R. microplus feeding on tick-resistant bovines. Capillary feeding of semi-engorged ticks with anti-AHYNPPPPIEFT sheep sera led to an 81.16% reduction in the reproduction capacity of R. microplus. Therefore, it is possible to conclude that R. microplus serpin (RMS-3) has an important role in the host-parasite interaction to overcome the immune responses in resistant cattle. (C) 2012 Elsevier GmbH. All rights reserved.

Improved optical character recognition by matched filtering

The effectiveness of linear matched filters for improved character discrimination in presence of random noise and poorly defined characters has been investigated. We have found that although the performance of the filter in presence of random noise is reasonably good (16 dB gain in signal-to-noise-ratio) its performance is poor when the unknown character is distorted (linear shift and rotation).

Jer. (Jerusalem) - Temple Pl. (place) - Golden Gate

Digital image

Divide-and-Correct Algorithm for Division in a Negative Base

A divide-and-correct algorithm is described for multiple-precision division in the negative base number system. In this algorithm an initial quotient estimate is obtained from suitable segmented operands; this is then corrected by simple rules to arrive at the true quotient.

Improved optical character recognition by matched filtering

The effectiveness of linear matched filters for improved character discrimination in presence of random noise and poorly defined characters has been investigated. We have found that although the performance of the filter in presence of random noise is reasonably good (16 dB gain in signal-to-noise-ratio) its performance is poor when the unknown character is distorted (linear shift and rotation).

Divide-and-Correct Algorithm for Division in a Negative Base

A divide-and-correct algorithm is described for multiple-precision division in the negative base number system. In this algorithm an initial quotient estimate is obtained from suitable segmented operands; this is then corrected by simple rules to arrive at the true quotient.

Adaptive frequency scaled wavelet packet decomposition for frog call classification

Environmental changes have put great pressure on biological systems leading to the rapid decline of biodiversity. To monitor this change and protect biodiversity, animal vocalizations have been widely explored by the aid of deploying acoustic sensors in the field. Consequently, large volumes of acoustic data are collected. However, traditional manual methods that require ecologists to physically visit sites to collect biodiversity data are both costly and time consuming. Therefore it is essential to develop new semi-automated and automated methods to identify species in automated audio recordings. In this study, a novel feature extraction method based on wavelet packet decomposition is proposed for frog call classification. After syllable segmentation, the advertisement call of each frog syllable is represented by a spectral peak track, from which track duration, dominant frequency and oscillation rate are calculated. Then, a k-means clustering algorithm is applied to the dominant frequency, and the centroids of clustering results are used to generate the frequency scale for wavelet packet decomposition (WPD). Next, a new feature set named adaptive frequency scaled wavelet packet decomposition sub-band cepstral coefficients is extracted by performing WPD on the windowed frog calls. Furthermore, the statistics of all feature vectors over each windowed signal are calculated for producing the final feature set. Finally, two well-known classifiers, a k-nearest neighbour classifier and a support vector machine classifier, are used for classification. In our experiments, we use two different datasets from Queensland, Australia (18 frog species from commercial recordings and field recordings of 8 frog species from James Cook University recordings). The weighted classification accuracy with our proposed method is 99.5% and 97.4% for 18 frog species and 8 frog species respectively, which outperforms all other comparable methods.

Schoolman family papers, undated, 1889-1994

The Schoolman Papers reflect Dr. Albert P. and Mrs. Bertha Schoolmans' staunch dedication to Jewish education, Jewish causes, and Israel. Bertha Schoolman, a lifelong member of Hadassah, assisted thousands of Israeli youth as chairman of the Youth Aliyah Committee. Her diaries, photos, scrapbooks, and correspondence record her numerous visits to Israel on which she helped set up schools, met with Israeli dignitaries, and participated in Zionist Conferences and events. The collection includes a 1936 letter from Hadassah founder, Henrietta Szold, praising Mrs. Schoolman's work as well as a letter from the father of Anne Frank, thanking Mrs. Schoolman for naming a Youth Aliyah center the "Anne Frank Haven" after his later daughter.

An algebraic algorithm for the design and analysis of linear dynamical systems

In an earlier paper [1], it has been shown that velocity ratio, defined with reference to the analogous circuit, is a basic parameter in the complete analysis of a linear one-dimensional dynamical system. In this paper it is shown that the terms constituting velocity ratio can be readily determined by means of an algebraic algorithm developed from a heuristic study of the process of transfer matrix multiplication. The algorithm permits the set of most significant terms at a particular frequency of interest to be identified from a knowledge of the relative magnitudes of the impedances of the constituent elements of a proposed configuration. This feature makes the algorithm a potential tool in a first approach to a rational design of a complex dynamical filter. This algorithm is particularly suited for the desk analysis of a medium size system with lumped as well as distributed elements.

Deterministic Division Algorithm in a Negative Base

Described here is a deterministic division algorithm in a negative-base number system; here, the divisor is mapped into a suitable range by premultiplication, so that the choice of the quotient digit is deterministic.

The impact of retention of heritage places

The movement to protect heritage places has grown enormously in Australia over the past decade. The renewed recognition of the significant roles that heritage places play in the urban environment today is encouraging but has a way to go if the demolition of memorable places and irreversible loss of intangible values seen in previous times is to be discontinued. This study investigated the perceptions of the general public and the professional stakeholders in heritage projects and found that they were very similar, particularly in relation to the reasons for heritage retention. The results indicate that, while there is growing interest in sustaining the reflection of the historic urban landscape by retaining cherished icons for the future, there needs to be better ways to overcome the modern development pressures on heritage sites. The paper concludes that, despite the challenges in heritage retention, they are outweighed by the value that accrues from preserving heritage places and the widespread appreciation of that value.

Activity recognition using binary tree SVM

This paper presents an effective classification method based on Support Vector Machines (SVM) in the context of activity recognition. Local features that capture both spatial and temporal information in activity videos have made significant progress recently. Efficient and effective features, feature representation and classification plays a crucial role in activity recognition. For classification, SVMs are popularly used because of their simplicity and efficiency; however the common multi-class SVM approaches applied suffer from limitations including having easily confused classes and been computationally inefficient. We propose using a binary tree SVM to address the shortcomings of multi-class SVMs in activity recognition. We proposed constructing a binary tree using Gaussian Mixture Models (GMM), where activities are repeatedly allocated to subnodes until every new created node contains only one activity. Then, for each internal node a separate SVM is learned to classify activities, which significantly reduces the training time and increases the speed of testing compared to popular the `one-against-the-rest' multi-class SVM classifier. Experiments carried out on the challenging and complex Hollywood dataset demonstrates comparable performance over the baseline bag-of-features method.