Empirical evaluation of public transport travel time variability

Although transit travel time variability is essential for understanding the deterioration of reliability, optimising transit schedule and route choice; it has not attracted enough attention from the literature. This paper proposes public transport-oriented definitions of travel time variability and explores the distributions of public transport travel time using the Transit Signal Priority data. First, definitions of public transport travel time variability are established by extending the common definitions of variability in the literature and by using route and services data of public transport vehicles. Second, the paper explores the distribution of public transport travel time. A new approach for analysing the distributions involving all transit vehicles as well as vehicles from a specific route is proposed. The Lognormal distribution is revealed as the descriptors for public transport travel time from the same route and service. The methods described in this study could be of interest for both traffic managers and transit operators for planning and managing the transit systems.

Establishing definitions and modeling public transport travel time variability

Public transport travel time variability (PTTV) is essential for understanding deteriorations in the reliability of travel time, optimizing transit schedules and route choices. This paper establishes key definitions of PTTV in which firstly include all buses, and secondly include only a single service from a bus route. The paper then analyses the day-to-day distribution of public transport travel time by using Transit Signal Priority data. A comprehensive approach using both parametric bootstrapping Kolmogorov-Smirnov test and Bayesian Information Creation technique is developed, recommends Lognormal distribution as the best descriptor of bus travel time on urban corridors. The probability density function of Lognormal distribution is finally used for calculating probability indicators of PTTV. The findings of this study are useful for both traffic managers and statisticians for planning and researching the transit systems.

Local inter-session variability modelling for object classification

Object classification is plagued by the issue of session variation. Session variation describes any variation that makes one instance of an object look different to another, for instance due to pose or illumination variation. Recent work in the challenging task of face verification has shown that session variability modelling provides a mechanism to overcome some of these limitations. However, for computer vision purposes, it has only been applied in the limited setting of face verification. In this paper we propose a local region based intersession variability (ISV) modelling approach, and apply it to challenging real-world data. We propose a region based session variability modelling approach so that local session variations can be modelled, termed Local ISV. We then demonstrate the efficacy of this technique on a challenging real-world fish image database which includes images taken underwater, providing significant real-world session variations. This Local ISV approach provides a relative performance improvement of, on average, 23% on the challenging MOBIO, Multi-PIE and SCface face databases. It also provides a relative performance improvement of 35% on our challenging fish image dataset.

Characterising an ECG signal using statistical modelling : a feasibility study

For clinical use, in electrocardiogram (ECG) signal analysis it is important to detect not only the centre of the P wave, the QRS complex and the T wave, but also the time intervals, such as the ST segment. Much research focused entirely on qrs complex detection, via methods such as wavelet transforms, spline fitting and neural networks. However, drawbacks include the false classification of a severe noise spike as a QRS complex, possibly requiring manual editing, or the omission of information contained in other regions of the ECG signal. While some attempts were made to develop algorithms to detect additional signal characteristics, such as P and T waves, the reported success rates are subject to change from person-to-person and beat-to-beat. To address this variability we propose the use of Markov-chain Monte Carlo statistical modelling to extract the key features of an ECG signal and we report on a feasibility study to investigate the utility of the approach. The modelling approach is examined with reference to a realistic computer generated ECG signal, where details such as wave morphology and noise levels are variable.

Public transport travel time variability definitions and monitoring

Public Transport Travel Time Variability (PTTV) is essential for understanding the deteriorations in the reliability of travel time, optimizing transit schedules and route choices. This paper establishes the key definitions of PTTV in which firstly include all buses, and secondly include only a single service from a bus route. The paper then analyzes the day-to-day distribution of public transport travel time by using Transit Signal Priority data. A comprehensive approach, using both parametric bootstrapping Kolmogorov-Smirnov test and Bayesian Information Creation technique is developed, recommends Lognormal distribution as the best descriptor of bus travel time on urban corridors. The probability density function of Lognormal distribution is finally used for calculating probability indicators of PTTV. The findings of this study are useful for both traffic managers and statisticians for planning and analyzing the transit systems.

Inter-cycle variability of ignition delay in an ethanol fumigated common rail diesel engine

An experimental study has been performed to investigate the ignition delay of a modern heavy-duty common-rail diesel engine run with fumigated ethanol substitutions up to 40% on an energy basis. The ignition delay was determined through the use of statistical modelling in a Bayesian framework this framework allows for the accurate determination of the start of combustion from single consecutive cycles and does not require any differentiation of the in-cylinder pressure signal. At full load the ignition delay has been shown to decrease with increasing ethanol substitutions and evidence of combustion with high ethanol substitutions prior to diesel injection have also been shown experimentally and by modelling. Whereas, at half load increasing ethanol substitutions have increased the ignition delay. A threshold absolute air to fuel ratio (mole basis) of above ~110 for consistent operation has been determined from the inter-cycle variability of the ignition delay, a result that agrees well with previous research of other in-cylinder parameters and further highlights the correlation between the air to fuel ratio and inter-cycle variability. Numerical modelling to investigate the sensitivity of ethanol combustion has also been performed. It has been shown that ethanol combustion is sensitive to the initial air temperature around the feasible operating conditions of the engine. Moreover, a negative temperature coefficient region of approximately 900{1050 K (the approximate temperature at fuel injection) has been shown with for n-heptane and n-heptane/ethanol blends in the numerical modelling. A consequence of this is that the dominate effect influencing the ignition delay under increasing ethanol substitutions may rather be from an increase in chemical reactions and not from in-cylinder temperature. Further investigation revealed that the chemical reactions at low ethanol substitutions are different compared to the high (> 20%) ethanol substitutions.

Improving out-domain PLDA speaker verification using unsupervised inter-dataset variability compensation approach

Experimental studies have found that when the state-of-the-art probabilistic linear discriminant analysis (PLDA) speaker verification systems are trained using out-domain data, it significantly affects speaker verification performance due to the mismatch between development data and evaluation data. To overcome this problem we propose a novel unsupervised inter dataset variability (IDV) compensation approach to compensate the dataset mismatch. IDV-compensated PLDA system achieves over 10% relative improvement in EER values over out-domain PLDA system by effectively compensating the mismatch between in-domain and out-domain data.

Food intake, growth and social interactions of signal crayfish, Pacifastacus leniusculus (Dana)

The knowledge about the optimal rearing conditions, such as water temperature and quality, photoperiod and density, with the understanding of animal nutritional requirements forms the basis of economically stable aquaculture for freshwater crayfish. However, the shift from a natural environment to effective culture conditions induces several changes, not only at the population level, but also at the individual level. The social contacts between conspecifics increase with increasing animal density. The competition for limited resources (e.g. food, shelter, mates) is more severe with the presence of agonistic behaviour and may lead to unequal distribution of these. The objectives of this study were to: 1) study the distribution of a common food resource between communally reared signal crayfish (Pacifastacus leniusculus) and to assign potential feeding hierarchy on the basis of individual food intake measurements, 2) explore the possibilities of size distribution manipulations to affect population dynamics and food intake to improve growth and survival in culture and 3) study the effect of food ration and spatial distribution on food intake and to explore the effect of temperature and food ration on growth and body composition of freshwater crayfish. The feeding ranks between animals were assigned with a new method for individual food intake measurement of communally reared crayfish. This technique has a high feasibility and a great potential to be applied in crayfish aquaculture studies. In this study, signal crayfish showed high size-related variability in food consumption both among individuals within a group (inter-individual) and within individual day-to-day variation (intra-individual). Increased competition for food led to an unequal distribution of this resource and this may be a reason for large growth differences between animals. The consumption was significantly higher when reared individually in comparison with communal housing. These results suggest that communally housed crayfish form a feeding hierarchy and that the animal size is the major factor controlling the position in this hierarchy. The optimisation of the social environment ( social conditions ) was evaluated in this study as a new approach to crayfish aquaculture. The results showed that the absence of conspecifics (individual rearing vs. communal housing) affects growth rate, food intake and the proportion of injured animals, whereas size variation between animals influences the number and duration of agonistic encounters. In addition, animal size had a strong influence on the fighting success of signal crayfish reared in a social milieu with a wide size variation of conspecifics. Larger individuals initiated and won most of the competitions, which suggests size-based social hierarchy of P. leniusculus. This is further supported by the fact that the length and weight gain of smaller animals increased after size grading, maybe because of a better access to the food resource due to diminished social pressure. However, the high dominance index was not based on size under conditions of limited size variation, e.g. those characteristic of restocked natural populations and aquaculture, indicating the important role of behaviour on social hierarchy.

Atrial Electric Signal During Sinus Rhythm in Lone Paroxysmal Atrial Fibrillation

Atrial fibrillation (AF) is the most common tachyarrhythmia and is associated with substantial morbidity, increased mortality and cost. The treatment modalities of AF have increased, but results are still far from optimal. More individualized therapy may be beneficial. Aiming for this calls improved diagnostics. Aim of this study was to find non-invasive parameters obtained during sinus rhythm reflecting electrophysiological patterns related to propensity to AF and particularly to AF occurring without any associated heart disease, lone AF. Overall 240 subjects were enrolled, 136 patients with paroxysmal lone AF and 104 controls (mean age 45 years, 75% males). Signal measurements were performed by non-invasive magnetocardiography (MCG) and by invasive electroanatomic mapping (EAM). High-pass filtering techniques and a new method based on a surface gradient technique were adapted to analyze atrial MCG signal. The EAM was used to elucidate atrial activation in patients and as a reference for MCG. The results showed that MCG mapping is an accurate method to detect atrial electrophysiologic properties. In lone paroxysmal AF, duration of the atrial depolarization complex was marginally prolonged. The difference was more obvious in women and was also related to interatrial conduction patterns. In the focal type of AF (75%), the root mean square (RMS) amplitudes of the atrial signal were normal, but in AF without demonstrable triggers the late atrial RMS amplitudes were reduced. In addition, the atrial characteristics tended to remain similar even when examined several years after the first AF episodes. The intra-atrial recordings confirmed the occurrence of three distinct sites of electrical connection from right to left atrium (LA): the Bachmann bundle (BB), the margin of the fossa ovalis (FO), and the coronary sinus ostial area (CS). The propagation of atrial signal could also be evaluated non-invasively. Three MCG atrial wave types were identified, each of which represented a distinct interatrial activation pattern. In conclusion, in paroxysmal lone AF, active focal triggers are common, atrial depolarization is slightly prolonged, but with a normal amplitude, and the arrhythmia does not necessarily lead to electrical or mechanical dysfunction of the atria. In women the prolongation of atrial depolarization is more obvious. This may be related to gender differences in presentation of AF. A significant minority of patients with lone AF lack frequent focal triggers, and in them, the late atrial signal amplitude is reduced, possibly signifying a wider degenerative process in the LA. In lone AF, natural impulse propagation to LA during sinus rhythm goes through one or more of the principal pathways described. The BB is the most common route, but in one-third, the earliest LA activation occurs outside the BB. Susceptibility to paroxysmal lone AF is associated with propagation of the atrial signal via the margin of the FO or via multiple pathways. When conduction occurs via the BB, it is related with prolonged atrial activation. Thus, altered and alternative conduction pathways may contribute to pathogenesis of lone AF. There is growing evidence of variability in genesis of AF also within lone paroxysmal AF. Present study suggests that this variation may be reflected in cardiac signal pattern. Recognizing the distinct signal profiles may assist in understanding the pathogenesis of AF and identifying subgroups for patient-tailored therapy.

Climatic variability in Central Indian Himalaya during the last similar to 1800 years: Evidence from a high resolution speleothem record

Stable isotopes from a U/Th dated aragonite stalagmite from the Central Kumaun Himalaya provide evidence of variation in climatic conditions in the last similar to 1800 years. The delta O-18 and delta C-13 values vary from -4.3 parts per thousand to -7.6 parts per thousand and -3.4 parts per thousand to -9.1 parts per thousand respectively, although the stalagmite was not grown in isotopic equilibrium with cave drip water, a clear palaeoclimatic signal in stalagmite delta O-18 values is evident based on the regional climate data. The stalagmite showed a rapid growth rate during 830-910 AD, most likely the lower part of Medieval Warm Period (MWP), and 1600-1640 AD, the middle part of Little Ice Age (LIA). Two distinct phases of reduced precipitation are marked by a 2 parts per thousand shift in 8180 values towards the end of MWP (similar to 1080-1160 AD) and after its termination from similar to 1210 to 1440 AD. The LIA (similar to 1440-1880 AD) is represented by sub-tropical climate similar to modern conditions, whereas the post-LIA was comparatively drier. The Inter Tropical Convergence Zone (ITCZ) was located over the cave location during wetter/warmer conditions. When it shifted southward, precipitation over the study area decreased. A prominent drop in delta O-18 and delta C-13 values during the post-LIA period may also have been additionally influenced by anthropogenic activity in the area. (C) 2013 Elsevier Ltd and INQUA. All rights reserved.

Daily scale wintertime sea surface temperature and IPC-Navidad variability in the southern Bay of Biscay from 1981 to 2010

The combination of remotely sensed gappy Sea surface temperature (SST) images with the missing data filling DINEOF (data interpolating empirical orthogonal functions) technique, followed by a principal component analysis of the reconstructed data, has been used to identify the time evolution and the daily scale variability of the wintertime surface signal of the Iberian Poleward Current (IPC), or Navidad, during the 1981-2010 period. An exhaustive comparison with the existing bibliography, and the vertical temperature and salinity profiles related to its extremes over the Bay of Biscay area, show that the obtained time series accurately reflect the IPC-Navidad variability. Once a time series for the evolution of the SST signal of the current over the last decades is well established, this time series is used to propose a physical mechanism in relation to the variability of the IPC-Navidad, involving both atmospheric and oceanic variables. According to the proposed mechanism, an atmospheric circulation anomaly observed in both the 500 hPa and the surface levels generates atmospheric surface level pressure, wind-stress and heat-flux anomalies. In turn, those surface level atmospheric anomalies induce mutually coherent SST and sea level anomalies over the North Atlantic area, and locally, in the Bay of Biscay area. These anomalies, both locally over the Bay of Biscay area and over the North Atlantic, are in agreement with several mechanisms that have separately been related to the variability of the IPC-Navidad, i.e. the south-westerly winds, the joint effect of baroclinicity and relief (JEBAR) effect, the topographic beta effect and a weakened North Atlantic gyre.

High-resolution natural recording systems: intercomparisons of the response to interannual climatic variability [abstract]

The goal of this work is to examine the properties of recording mechanisms which are common to continuously recording high-resolution natural systems in which climatic signals are imprinted and preserved as proxy records. These systems produce seasonal structures as an indirect response to climatic variability over the annual cycle. We compare the proxy records from four different high-resolution systems: the Quelccaya ice cap of the Peruvian Andes; composite tree ring growth from southern California and the southwestern United States; and the marine varve sedimentation systems in the Santa Barbara basin (off California, United States) and in the Gulf of California, Mexico. An important focus of this work is to indicate how the interannual climatic signal is recorded in a variety of different natural systems with vastly different recording mechanisms and widely separated in space. These high-resolution records are the products of natural processes which should be comparable, to some degree, to human-engineered systems developed to transmit and record physical quantities. We therefore present a simple analogy of a data recording system as a heuristic model to provide some unifying concepts with which we may better understand the formation of the records. This analogy assumes special significance when we consider that natural proxy records are the principal means to extend our knowledge of climatic variability into the past, beyond the limits of instrumentally recorded data.

Inter-decadal climate variability in the Southern Hemisphere: evidence from Tasmanian tree rings over the past three millennia

EXTRACT (SEE PDF FOR FULL ABSTRACT): The characterization of inter-decadal climate variability in the Southern Hemisphere is severely constrained by the shortness of the instrumental climate records. To help relieve this constraint, we have developed and analyzed a reconstruction of warm-season (November-April) temperatures from Tasmanian tree rings that now extends back to 800 BC. A detailed analysis of this reconstruction in the time and frequency domains indicates that much of the inter-decadal variability is principally confined to four frequency bands with mean periods of 31, 57, 77, and 200 years. ... In so doing, we show how a future greenhouse warming signal over Tasmania could be masked by these natural oscillations unless they are taken into account.

Radiolarian flux in the Santa Barbara Basin as an index of climate variability

Annual radiolarian flux (1954-1986) extrapolated from varved Santa Barbara Basin sediments was compared to instrumental data to examine the effect of interannual climate variability. Paleo-reconstructions over large geographic areas or 10^3 years and longer typically rely on changes in species composition to signal environment or climate shifts. In the relatively short period studied, climate fluctuations were insufficient to significantly alter the assemblage, but there was considerable variability in the total flux of radiolarians. This variability, greatest on 5- to 25-year time scales, appears to be linked to regional climate variability. Total flux correlates to regional California sea surface temperature and the composite of sea level pressure over the Northern Hemisphere for years of high radiolarian flux resembles positive PNA circulation.

Bayesian classification of acoustical waveforms under environmental variability

We present in this paper a new multivariate probabilistic approach to Acoustic Pulse Recognition (APR) for tangible interface applications. This model uses Principle Component Analysis (PCA) in a probabilistic framework to classify tapping pulses with a high degree of variability. It was found that this model, achieves a higher robustness to pulse variability than simpler template matching methods, specifically when allowed to train on data containing high variability. © 2011 IEEE.