A Bias in ML Estimates of Branch Lengths in the Presence of Multiple Signals

Sequence data often have competing signals that are detected by network programs or Lento plots. Such data can be formed by generating sequences on more than one tree, and combining the results, a mixture model. We report that with such mixture models, the estimates of edge (branch) lengths from maximum likelihood (ML) methods that assume a single tree are biased. Based on the observed number of competing signals in real data, such a bias of ML is expected to occur frequently. Because network methods can recover competing signals more accurately, there is a need for ML methods allowing a network. A fundamental problem is that mixture models can have more parameters than can be recovered from the data, so that some mixtures are not, in principle, identifiable. We recommend that network programs be incorporated into best practice analysis, along with ML and Bayesian trees.

Activity analysis in complicated scenes using DFT coefficients of particle trajectories

Modelling activities in crowded scenes is very challenging as object tracking is not robust in complicated scenes and optical flow does not capture long range motion. We propose a novel approach to analyse activities in crowded scenes using a “bag of particle trajectories”. Particle trajectories are extracted from foreground regions within short video clips using particle video, which estimates long range motion in contrast to optical flow which is only concerned with inter-frame motion. Our applications include temporal video segmentation and anomaly detection, and we perform our evaluation on several real-world datasets containing complicated scenes. We show that our approaches achieve state-of-the-art performance for both tasks.

Robust facial feature extraction and matching

Automated feature extraction and correspondence determination is an extremely important problem in the face recognition community as it often forms the foundation of the normalisation and database construction phases of many recognition and verification systems. This paper presents a completely automatic feature extraction system based upon a modified volume descriptor. These features form a stable descriptor for faces and are utilised in a reversible jump Markov chain Monte Carlo correspondence algorithm to automatically determine correspondences which exist between faces. The developed system is invariant to changes in pose and occlusion and results indicate that it is also robust to minor face deformations which may be present with variations in expression.

Towards robust night and day place recognition using visible and thermal imaging

The chief challenge facing persistent robotic navigation using vision sensors is the recognition of previously visited locations under different lighting and illumination conditions. The majority of successful approaches to outdoor robot navigation use active sensors such as LIDAR, but the associated weight and power draw of these systems makes them unsuitable for widespread deployment on mobile robots. In this paper we investigate methods to combine representations for visible and long-wave infrared (LWIR) thermal images with time information to combat the time-of-day-based limitations of each sensing modality. We calculate appearance-based match likelihoods using the state-of-the-art FAB-MAP [1] algorithm to analyse loop closure detection reliability across different times of day. We present preliminary results on a dataset of 10 successive traverses of a combined urban-parkland environment, recorded in 2-hour intervals from before dawn to after dusk. Improved location recognition throughout an entire day is demonstrated using the combined system compared with methods which use visible or thermal sensing alone.

Communications materials on methods of development of revenue and cost estimates to non-technical audiences

This CDROM includes PDFs of presentations on the following topics: "TXDOT Revenue and Expenditure Trends;" "Examine Highway Fund Diversions, & Benchmark Texas Vehicle Registration Fees;" "Evaluation of the JACK Model;" "Future highway construction cost trends;" "Fuel Efficiency Trends and Revenue Impact"

Novel methods and the maximum likelihood estimation technique for estimating traffic critical gap

Most unsignalised intersection capacity calculation procedures are based on gap acceptance models. Accuracy of critical gap estimation affects accuracy of capacity and delay estimation. Several methods have been published to estimate drivers’ sample mean critical gap, the Maximum Likelihood Estimation (MLE) technique regarded as the most accurate. This study assesses three novel methods; Average Central Gap (ACG) method, Strength Weighted Central Gap method (SWCG), and Mode Central Gap method (MCG), against MLE for their fidelity in rendering true sample mean critical gaps. A Monte Carlo event based simulation model was used to draw the maximum rejected gap and accepted gap for each of a sample of 300 drivers across 32 simulation runs. Simulation mean critical gap is varied between 3s and 8s, while offered gap rate is varied between 0.05veh/s and 0.55veh/s. This study affirms that MLE provides a close to perfect fit to simulation mean critical gaps across a broad range of conditions. The MCG method also provides an almost perfect fit and has superior computational simplicity and efficiency to the MLE. The SWCG method performs robustly under high flows; however, poorly under low to moderate flows. Further research is recommended using field traffic data, under a variety of minor stream and major stream flow conditions for a variety of minor stream movement types, to compare critical gap estimates using MLE against MCG. Should the MCG method prove as robust as MLE, serious consideration should be given to its adoption to estimate critical gap parameters in guidelines.

A mitochondrial genome phylogeny of termites (Blattodea: Termitoidae) : robust support for interfamilial relationships and molecular synapomorphies define major clades

Despite their ecological significance as decomposers and their evolutionary significance as the most speciose eusocial insect group outside the Hymenoptera, termite (Blattodea: Termitoidae or Isoptera) evolutionary relationships have yet to be well resolved. Previous morphological and molecular analyses strongly conflict at the family level and are marked by poor support for backbone nodes. A mitochondrial (mt) genome phylogeny of termites was produced to test relationships between the recognised termite families, improve nodal support and test the phylogenetic utility of rare genomic changes found in the termite mt genome. Complete mt genomes were sequenced for 7 of the 9 extant termite families with additional representatives of each of the two most speciose families Rhinotermitidae (3 of 7 subfamilies) and Termitidae (3 of 8 subfamilies). The mt genome of the well supported sister group of termites, the subsocial cockroach Cryptocercus, was also sequenced. A highly supported tree of termite relationships was produced by all analytical methods and data treatment approaches, however the relationship of the termites + Cryptocercus clade to other cockroach lineages was highly affected by the strong nucleotide compositional bias found in termites relative to other dictyopterans. The phylogeny supports previously proposed suprafamilial termite lineages, the Euisoptera and Neoisoptera, a later derived Kalotermitidae as sister group of the Neoisoptera and a monophyletic clade of dampwood (Stolotermitidae, Archotermopsidae) and harvester termites (Hodotermitidae). In contrast to previous termite phylogenetic studies, nodal supports were very high for family-level relationships within termites. Two rare genomic changes in the mt genome control region were found to be molecular synapomorphies for major clades. An elongated stem-loop structure defined the clade Polyphagidae + (Cryptocercus + termites), and a further series of compensatory base changes in this stem loop is synapomorphic for the Neoisoptera. The complicated repeat structures first identified in Reticulitermes, composed of short (A-type) and long (B-type repeats) defines the clade Heterotermitinae + Termitidae, while the secondary loss of A-type repeats is synapomorphic for the non-macrotermitine Termitidae.

The iatrogenic reflex and belief that repression can coercively suppress asymmetric coercive violence : does very robust action by the government decrease functional support for insurgents?

Non-state insurgent actors are too weak to compel powerful adversaries to their will, so they use violence to coerce. A principal objective is to grow and sustain violent resistance to the point that it either militarily challenges the state, or more commonly, generates unacceptable political costs. To survive, insurgents must shift popular support away from the state and to grow they must secure it. State actor policies and actions perceived as illegitimate and oppressive by the insurgent constituency can generate these shifts. A promising insurgent strategy is to attack states in ways that lead angry publics and leaders to discount the historically established risks and take flawed but popular decisions to use repressive measures. Such decisions may be enabled by a visceral belief in the power of coercion and selective use of examples of where robust measures have indeed suppressed resistance. To avoid such counterproductive behaviours the cases of apparent 'successful repression' must be understood. This thesis tests whether robust state action is correlated with reduced support for insurgents, analyses the causal mechanisms of such shifts and examines whether such reduction is because of compulsion or coercion? The approach is founded on prior research by the RAND Corporation which analysed the 30 insurgencies most recently resolved worldwide to determine factors of counterinsurgent success. This new study first re-analyses their data at a finer resolution with new queries that investigate the relationship between repression and insurgent active support. Having determined that, in general, repression does not correlate with decreased insurgent support, this study then analyses two cases in which the data suggests repression seems likely to be reducing insurgent support: the PKK in Turkey and the insurgency against the Vietnamese-sponsored regime after their ousting of the Khmer Rouge. It applies 'structured-focused' case analysis with questions partly built from the insurgency model of Leites and Wolf, who are associated with the advocacy of US robust means in Vietnam. This is thus a test of 'most difficult' cases using a 'least likely' test model. Nevertheless, the findings refute the deterrence argument of 'iron fist' advocates. Robust approaches may physically prevent effective support of insurgents but they do not coercively deter people from being willing to actively support the insurgency.

Sufficiently informative measurements for stability of approximate conditional mean estimates

This paper establishes sufficient conditions to bound the error in perturbed conditional mean estimates derived from a perturbed model (only the scalar case is shown in this paper but a similar result is expected to hold for the vector case). The results established here extend recent stability results on approximating information state filter recursions to stability results on the approximate conditional mean estimates. The presented filter stability results provide bounds for a wide variety of model error situations.

International differences in management of physical activity data: Can they explain some of the difference in prevalence estimates?

Background: National physical activity data suggest that there is a considerable difference in physical activity levels of US and Australian adults. Although different surveys (Active Australia and BRFSS) are used, the questions are similar. Different protocols, however, are used to estimate “activity” from the data collected. The primary aim of this study was to assess whether the 2 approaches to the management of PA data could explain some of the difference in prevalence estimates derived from the two national surveys. Methods: Secondary data analysis of the most recent AA survey (N = 2987). Results: 15% of the sample was defined as “active” using Australian criteria but as “inactive” using the BRFSS protocol, even though weekly energy expenditure was commensurate with meeting current guidelines. Younger respondents (age < 45 y) were more likely to be “misclassified” using the BRFSS criteria. Conclusions: The prevalence of activity in Australia and the US appears to be more similar than we had previously thought.

Suspended sediment properties and suspended sediment flux estimates in an inundated urban environment during a major flood event

During a major flood event, the inundation of urban environments leads to some complicated flow motion most often associated with significant sediment fluxes. In the present study, a series of field measurements were conducted in an inundated section of the City of Brisbane (Australia) about the peak of a major flood in January 2011. Some experiments were performed to use ADV backscatter amplitude as a surrogate estimate of the suspended sediment concentration (SSC) during the flood event. The flood water deposit samples were predominantly silty material with a median particle size about 25 μm and they exhibited a non-Newtonian behavior under rheological testing. In the inundated urban environment during the flood, estimates of suspended sediment concentration presented a general trend with increasing SSC for decreasing water depth. The suspended sediment flux data showed some substantial sediment flux amplitudes consistent with the murky appearance of floodwaters. Altogether the results highlighted the large suspended sediment loads and fluctuations in the inundated urban setting associated possibly with a non-Newtonian behavior. During the receding flood, some unusual long-period oscillations were observed (periods about 18 min), although the cause of these oscillations remains unknown. The field deployment was conducted in challenging conditions highlighting a number of practical issues during a natural disaster.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular, and time-varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper evaluates a number of matching techniques for possible use in a stereo vision sensor for mining automation applications. Area-based techniques have been investigated because they have the potential to yield dense maps, are amenable to fast hardware implementation, and are suited to textured scenes. In addition, two nonparametric transforms, namely, rank and census, have been investigated. Matching algorithms using these transforms were found to have a number of clear advantages, including reliability in the presence of radiometric distortion, low computational complexity, and amenability to hardware implementation.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. The objective is to produce a stereo vision sensor suited to close-range scenes consisting primarily of rocks. This sensor should be able to produce a dense depth map within real-time constraints. Speed and robustness are of foremost importance for this investigation. A number of area based matching metrics have been implemented, including the SAD, SSD, NCC, and their zero-meaned versions. The NCC and the zero meaned SAD and SSD were found to produce the disparity maps with the highest proportion of valid matches. The plain SAD and SSD were the least computationally expensive, due to all their operations taking place in integer arithmetic, however, they were extremely sensitive to radiometric distortion. Non-parametric techniques for matching, in particular, the rank and the census transform, have also been investigated. The rank and census transforms were found to be robust with respect to radiometric distortion, as well as being able to produce disparity maps with a high proportion of valid matches. An additional advantage of both the rank and the census transform is their amenability to fast hardware implementation.