Evaluation of features for leaf classification in challenging conditions

Fine-grained leaf classification has concentrated on the use of traditional shape and statistical features to classify ideal images. In this paper we evaluate the effectiveness of traditional hand-crafted features and propose the use of deep convolutional neural network (ConvNet) features. We introduce a range of condition variations to explore the robustness of these features, including: translation, scaling, rotation, shading and occlusion. Evaluations on the Flavia dataset demonstrate that in ideal imaging conditions, combining traditional and ConvNet features yields state-of-theart performance with an average accuracy of 97:3%�0:6% compared to traditional features which obtain an average accuracy of 91:2%�1:6%. Further experiments show that this combined classification approach consistently outperforms the best set of traditional features by an average of 5:7% for all of the evaluated condition variations.

Causal factors of hot air ballooning incidents : identification, frequency, and potential impact

Background: Hot air ballooning incidents are relatively rare, however, when they do occur they are likely to result in a fatality or serious injury. Human error is commonly attributed as the cause of hot air ballooning incidents; however, error in itself is not an explanation for safety failures. This research aims to identify, and establish the relative importance of factors contributing towards hot air ballooning incidents. Methods: Twenty-two Australian Ballooning Federation (ABF) incident reports were thematically coded using a bottom up approach to identify causal factors. Subsequently, 69 balloonists (mean 19.51 years’ experience) participated in a survey to identify additional causal factors and rate (out of seven) the perceived frequency and potential impact to ballooning operations of each of the previously identified causal factors. Perceived associated risk was calculated by multiplying mean perceived frequency and impact ratings. Results: Incident report coding identified 54 causal factors within nine higher level areas: Attributes, Crew resource management, Equipment, Errors, Instructors, Organisational, Physical Environment, Regulatory body and Violations. Overall, ‘weather’, ‘inexperience’ and ‘poor/inappropriate decisions’ were rated as having greatest perceived associated risk. Discussion: Although errors were nominated as a prominent cause of hot air ballooning incidents, physical environment and personal attributes are also particularly important for safe hot air ballooning operations. In identifying a range of causal factors the areas of weakness surrounding ballooning operations have been defined; it is hoped that targeted safety and training strategies can now be put into place removing these contributing factors and reducing the chance of pilot error.

Vocalizations of the North Island Brown Kiwi (Apteryx mantelli)

Few studies have investigated the vocal communication of ratites, and none has investigated the spectral and temporal structure of vocalizations of Apteryx, the only extant ratite genus in New Zealand. We describe the long-range vocalization (whistle call) and vocal behavior of male and female North Island Brown Kiwi (Apteryx mantelli). Spontaneous calling by seven pairs was recorded in the field over a one-year period. Call notes produced by males were tonal in nature; the fundamental frequency was ~1.5 kHz, with overtones reaching up to ~13.0 kHz. Call notes produced by females contained a series of tightly packed, poorly defined harmonics and consisted of a fundamental frequency of ~0.1 kHz, with overtones reaching ~7.0 kHz. The amplitude within notes of females was concentrated into two prominent formants. Some individuals of pairs exhibited duetting behavior that resulted in alteration of the inter-note interval after the onset of the call of their mate. Our findings draw attention to the uniqueness of the North Island Brown Kiwi's vocalizations, and we uncovered some unexpected structural features that call for further investigation.

Genetic divergence and echolocation call frequency in cryptic species of Hipposideros larvatus s.l. (Chiroptera : Hipposideridae) from the Indo-Malayan region

The intermediate leaf-nosed bat (Hipposideros larvatus) is a medium-sized bat distributed throughout the Indo-Malay region. In north-east India, bats identified as H. larvatus captured at a single cave emitted echolocation calls with a bimodal distribution of peak frequencies, around either 85 kHz or 98 kHz. Individuals echolocating at 85 kHz had larger ears and longer forearms than those echolocating at 98 kHz, although no differences were detected in either wing morphology or diet, suggesting limited resource partitioning. A comparison of mitochondrial control region haplotypes of the two phonic types with individuals sampled from across the Indo-Malay range supports the hypothesis that, in India, two cryptic species are present. The Indian 98-kHz phonic bats formed a monophyletic clade with bats from all other regional populations sampled, to the exclusion of the Indian 85-kHz bats. In India, the two forms showed 12–13% sequence divergence and we propose that the name Hipposideros khasiana for bats of the 85-kHz phonic type. Bats of the 98-kHz phonic type formed a monophyletic group with bats from Myanmar, and corresponded to Hipposideros grandis, which is suggested to be a species distinct from Hipposideros larvatus. Differences in echolocation call frequency among populations did not reflect phylogenetic relationships, indicating that call frequency is a poor indicator of evolutionary history. Instead, divergence in call frequency probably occurs in allopatry, possibly augmented by character displacement on secondary contact to facilitate intraspecific communication.

The effects of flight speed on ranging performance of bats using frequency modulated echolocation pulses

Many species of bat use ultrasonic frequency modulated (FM) pulses to measure the distance to objects by timing the emission and reception of each pulse. Echolocation is mainly used in flight. Since the flight speed of bats often exceeds 1% of the speed of sound, Doppler effects will lead to compression of the time between emission and reception as well as an elevation of the echo frequencies, resulting in a distortion of the perceived range. This paper describes the consequences of these Doppler effects on the ranging performance of bats using different pulse designs. The consequences of Doppler effects on ranging performance described in this paper assume bats to have a very accurate ranging resolution, which is feasible with a filterbank receiver. By modeling two receiver types, it was first established that the effects of Doppler compression are virtually independent of the receiver type. Then, used a cross-correlation model was used to investigate the effect of flight speed on Doppler tolerance and range–Doppler coupling separately. This paper further shows how pulse duration, bandwidth, function type, and harmonics influence Doppler tolerance and range–Doppler coupling. The influence of each signal parameter is illustrated using calls of several bat species. It is argued that range–Doppler coupling is a significant source of error in bat echolocation, and various strategies bats could employ to deal with this problem, including the use of range rate information are discussed.

Acoustic identification of 12 species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Echolocation calls of the long tailed bat: a quantitative analysis of types of calls

The echolocation calls of long-tailed bats (Chalinolobus tuberculatus) were recorded in the Eglinton Valley, Fjordland, New Zealand, and digitized for analysis with the signal-processing software. Univariate and multivariate analyses of measure features facilitated a quantitative classification of the calls. Cluster analysis was used to categorize calls into two groups equating to search and terminal buzz calls described qualitatively for other species. When moving from search to terminal phases, the calls decrease in bandwidth, maximum and minimum frequency of call, and duration. Search calls begin with a steep-downward FM sweep followed by a short, less-modulated component. Buzz calls are FM sweeps. Although not found quantitatively, a broad pre-buzz group of calls also was identified. Ambiguity analysis of calls from the three groups shows that search-phrase calls are well suited to resolving the velocity of targets, and hence, identifying moving targets in a stationary clutter. Pre-buzz and buzz calls are better suited to resolving range, a feature that may aid the bats in capture of evasive prey after it has been identified.

The use of a Riesz fractional differential-based approach for texture enhancement in image processing

Texture enhancement is an important component of image processing that finds extensive application in science and engineering. The quality of medical images, quantified using the imaging texture, plays a significant role in the routine diagnosis performed by medical practitioners. Most image texture enhancement is performed using classical integral order differential mask operators. Recently, first order fractional differential operators were used to enhance images. Experimentation with these methods led to the conclusion that fractional differential operators not only maintain the low frequency contour features in the smooth areas of the image, but they also nonlinearly enhance edges and textures corresponding to high frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we apply the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other first order fractional differential operators, we find that our new algorithms provide higher signal to noise values and superior image quality.

Achieving competence: The interactional features of children's storytelling

Early years researchers interested in storytelling have largely focused on the development of children’s language and social skills within constructed story sessions. Less focus has been given to the interactional aspects of storytelling in children’s everyday conversation and how the members themselves, the storytellers and story recipients, manage storytelling. An interactional view, using ethnomethodological and conversation analytic approaches, offers the opportunity to study children’s narratives in terms of ‘members work’. Detailed examination of a video-recorded interaction among a group of children in a preparatory year playground shows how the children managed interactions within conversational storytelling. Analyses highlight the ways in which children worked at gaining a turn and made a story tellable within a round of second stories. Investigating children’s competence-in-action ‘from within’, the findings from this research show how children invoke and accomplish competence through their interactions.

Identifying weak linear features with the "coalescing shortest path image transform"

The detection of line-like features in images finds many applications in microanalysis. Actin fibers, microtubules, neurites, pilis, DNA, and other biological structures all come up as tenuous curved lines in microscopy images. A reliable tracing method that preserves the integrity and details of these structures is particularly important for quantitative analyses. We have developed a new image transform called the "Coalescing Shortest Path Image Transform" with very encouraging properties. Our scheme efficiently combines information from an extensive collection of shortest paths in the image to delineate even very weak linear features. © Copyright Microscopy Society of America 2011.

Using upper bounds on attainable discrimination to select discrete valued features

Selection of features that will permit accurate pattern classification is a difficult task. However, if a particular data set is represented by discrete valued features, it becomes possible to determine empirically the contribution that each feature makes to the discrimination between classes. This paper extends the discrimination bound method so that both the maximum and average discrimination expected on unseen test data can be estimated. These estimation techniques are the basis of a backwards elimination algorithm that can be use to rank features in order of their discriminative power. Two problems are used to demonstrate this feature selection process: classification of the Mushroom Database, and a real-world, pregnancy related medical risk prediction task - assessment of risk of perinatal death.

Estimating the impact of reduced inertia on frequency stability due to large-scale wind penetration in Australian electricity network

Large-scale integration of non-inertial generators such as wind farms will create frequency stability issues due to reduced system inertia. Inertia based frequency stability study is important to predict the performance of power system with increased level of renewables. This paper focuses on the impact large-scale wind penetration on frequency stability of the Australian Power Network. MATLAB simulink is used to develop a frequency based dynamic model utilizing the network data from a simplified 14-generator Australian power system. The loss of generation is modeled as the active power disturbance and minimum inertia required to maintain the frequency stability is determined for five-area power system.

Battery energy storage systems to improve power system frequency response

Battery energy storage systems (BESS) are becoming feasible to provide system frequency support due to recent developments in technologies and plummeting cost. Adequate response of these devices becomes critical as the penetration of the renewable energy sources increases in the power system. This paper proposes effective use of BESS to improve system frequency performance. The optimal capacity and the operation scheme of BESS for frequency regulation are obtained using two staged optimization process. Furthermore, the effectiveness of BESS for improving the system frequency response is verified using dynamic simulations.

Effects of magnetite on high-frequency ground-penetrating radar

Large concentrations of magnetite in sedimentary deposits and soils with igneous parent material have been reported to affect geophysical sensor performance. We have undertaken the first systematic experimental effort to understand the effects of magnetite for ground-penetrating radar (GPR) characterization of the shallow subsurface. Laboratory experiments were conducted to study how homogeneous magnetite-sand mixtures and magnetite concentrated in layers affect the propagation behavior (velocity, attenuation) of high-frequency GPR waves and the reflection characteristics of a buried target. Important observations were that magnetite had a strong effect on signal velocity and reflection, at magnitudes comparable to what has been observed in small-scale laboratory experiments that measured electromagnetic properties of magnetite-silica mixtures. Magnetite also altered signal attenuation and affected the reflection characteristics of buried targets. Our results indicated important implications for several fields, including land mine detection, Martian exploration, engineering, and moisture mapping using satellite remote sensing and radiometers.

Characterization of frequency‐dependent magnetic susceptibility in UXO electromagnetic geophysics

Soils at many locations that have their origin in volcanic parent material and have undergone extensive weathering often exhibit strong frequency-dependent magnetic susceptibilities. The presence of such susceptibility has a profound effect on electromagnetic induction data acquired in such environments. Their transient electromagnetic response is characterized by a t-1 decay that is strong enough to mask UXO responses. In a field study and associated laboratory work on characterizing the frequency-dependent magnetic susceptibility and its influence on transient electromagnetic data, we collected soil samples on the surface and in soil pits from the Island of Kaho'olawe, Hawaii, and measured their frequency dependent magnetic susceptibilities. We present the details of the field investigation, confirm previous theoretical work with field and laboratory measurements, characterize the susceptibility with a Cole-Cole model, and investigate the response specific to the measured susceptibility.