Estimation of basis frequencies for time-varying SIMO channels : a second-order method

The complex exponential basis expansion model (CE-BEM) provides an accurate description for the time-varying (TV) channels encountered in mobile communications. Many blind channel identification and equalization approaches based on the CE-BEM require precise knowledge of the basis frequencies of TV channels. Existing methods for basis frequency estimation usually resort to the higher-order statistics of channel outputs and impose strict constraints on the source signal. In this paper, we propose a novel method to estimate the basis frequencies for blind identification and equalization of time-varying single-input multiple-output (SIMO) finite-impulse-response (FIR) channels. The proposed method exploits only the second-order statistics of channel outputs and does not require strong conditions on the source signal. As a result, it exhibits superior performance to the existing basis frequency estimation methods. The validity of our method is demonstrated by numerical simulations.

CM-based blind equalization of time-varying SIMO-FIR channel with single pulsation estimation

It is known that the constant modulus (CM) property of the source signal can be exploited to blindly equalize time-invariant single-inputmultiple-output (SIMO) and finite-impulse-response (FIR) channels. However, the time-invariance assumption about the channel cannot be satisfied in several practical applications, e.g., mobile communication. In this paper, we show that, under some mild conditions, the CM criterion can be extended to the blind equalization of a time-varying channel that is described by the complex exponential basis expansion model (CE-BEM). Although several existing blind equalization methods that are based on the CE-BEM have to employ higher order statistics to estimate all nonzero channel pulsations, the CM-based method only needs to estimate one pulsation using second-order statistics, which yields better estimation results. It also relaxes the restriction on the source signal and is applicable to some classes of signals with which the existing methods cannot deal.

Key predistribution scheme using finite fields and reed muller codes

Resource constraint sensors of a Wireless Sensor Network (WSN) cannot afford the use of costly encryption techniques like public key while dealing with sensitive data. So symmetric key encryption techniques are preferred where it is essential to have the same cryptographic key between communicating parties. To this end, keys are preloaded into the nodes before deployment and are to be established once they get deployed in the target area. This entire process is called key predistribution. In this paper we propose one such scheme using unique factorization of polynomials over Finite Fields. To the best of our knowledge such an elegant use of Algebra is being done for the first time in WSN literature. The best part of the scheme is large number of node support with very small and uniform key ring per node. However the resiliency is not good. For this reason we use a special technique based on Reed Muller codes proposed recently by Sarkar, Saha and Chowdhury in 2010. The combined scheme has good resiliency with huge node support using very less keys per node.

How is active transport associated with children's and adolescents' physical activity over time?

Background : As few longitudinal studies have examined how active transport is associated with physical activity among children and adolescents over time, and how active transport tracks through childhood and adolescence, it is important to understand whether physically active children retain their activity patterns through adolescence. This study aimed to examine (a) tracking of active transport and of moderate-to-vigorous physical activity (MVPA) across childhood and adolescence in two age cohorts; and (b) associations between active transport and MVPA at three distinct time-points, over five years.

Methods : This longitudinal study of two cohorts aged 5-6 years (n = 134) and 10-12 years (n = 201) at baseline (T1), in Melbourne, Australia, gathered follow-up data at three (T2) and five years (T3). Walking/cycling to local destinations was survey-reported; while MVPA was recorded using accelerometers and mean time spent daily in MVPA on week days and on weekends was computed. Tracking of these behaviours was examined over five years using General Estimating Equations. Linear regression analyses were performed to examine associations between active transport and MVPA at each time-point.

Results : Active transport tracked moderately among children (boys, bs = 0.36; girls, bs = 0.51) but not among adolescents. Physical activity tracked moderately (bs value range: 0.33-0.55) for both cohorts. Active transport was not associated with children’s MVPA at any time-point, but was associated with adolescent boys’ MVPA on week days at T1 (B = 1.37 (95% CI: 0.15, 2.59)), at T2 (B = 1.27 (95% CI: 0.03, 2.51)) and at T3 (B = 0.74 (95% CI: 0.01, 1.47)), and with adolescent girls’ MVPA on week days (B = 0.40 (95% CI: 0.04, 0.76)) and on weekends (B = 0.54 (95% CI:0.16, 0.93)) at T3 only.

Conclusion : Active transport was associated only with boys’ MVPA during early adolescence and with boys’ and girls’ MVPA during late adolescence. While active transport should be encouraged among all school-aged children, it may provide an important source of habitual physical activity for adolescent girls, in particular, among whom low and declining physical activity levels have been reported world-wide.

Threshold dynamic time warping for spatial activity recognition

Non-invasive spatial activity recognition is a difficult task, complicated by variation in how the same activities are conducted and furthermore by noise introduced by video tracking procedures. In this paper we propose an algorithm based on dynamic time warping (DTW) as a viable method with which to quantify segmented spatial activity sequences from a video tracking system. DTW is a widely used technique for optimally aligning or warping temporal sequences through minimisation of the distance between their components. The proposed algorithm threshold DTW (TDTW) is capable of accurate spatial sequence distance quantification and is shown using a three class spatial data set to be more robust and accurate than DTW and the discrete hidden markov model (HMM). We also evaluate the application of a band dynamic programming (DP) constraint to TDTW in order to reduce extraneous warping between sequences and to reduce the computation complexity of the approach. Results show that application of a band DP constraint to TDTW improves runtime performance significantly, whilst still maintaining a high precision and recall.

Tracking in a space variant active vision system

Without the ability to foveate on and maintain foveation, active vision for applications such as surveillance, object recognition and object tracking are difficult to build. Although foveation in cartesian coordinates is being actively pursued by many, multi-resolution high accuracy foveation in log polar space has not been given much attention. This paper addresses the use of foveation to track a single object as well as multiple objects for a simulated space variant active vision system. Complex logarithmic mapping is chosen firstly because it provides high resolution and wide angle viewing. Secondly, the spatially variant structure of log polar space leads to an object increasing in size as it moves towards the fovea. This is important as we know which object is closer to the fovea at any instant in time.

Damage identification of civil infrastructure in the time domain using FEM calibrated ARMAX model

Due to environmental loads, mechanical damages, structural aging and human factors, civil infrastructure inevitably deteriorate during their service lives. Since their damage may claim human lives and cause significant economic losses, how to identify damages and assess structural conditions timely and accurately has drawn increasingly more attentions from structural engineering community worldwide. In this study, a fast and sensitive time domain damage identification method will be developed. First, a high quality finite element model is built and the structural responses are simulated under different damage scenarios. Based on the simulated data, an Auto Regressive Moving Average Exogenous (ARMAX) model is then developed and calibrated. The calibrated ARMAX model can be used to identify damage in different scenarios through model updating process using clonal selection algorithm (CSA). The identification results demonstrate the performance of the proposed methodology, which has the potential to be used for damage identification in practices.

FEM calibrated ARMAX model updating method for time domain damage identification

Due to environmental loads, mechanical damages, structural aging and human factors, civil infrastructure inevitably deteriorate during their service lives. Since their damage may claim human lives and cause significant economic losses, how to identify damages and assess structural conditions timely and accurately has drawn increasingly more attentions from structural engineering community worldwide. In this study, a fast and sensitive time domain damage identification method will be developed. To do this, a finite element model of a steel pipe laid on the soil is built and the structural responses are simulated under different damage scenarios. Based on the simulated data, an Auto Regressive Moving Average Exogenous (ARMAX) model is then built and calibrated. The calibrated ARMAX model is used to identify different damage scenarios through model updating process using clonal selection algorithm (CSA). The results demonstrate the application potential of the proposed method in identifying the pipeline conditions. To further verify its performance, laboratory tests of a steel pipe laid on the soil with and without soil support (free span damage) are carried out. The identification results of pipe-soil system show that the proposed method is capable of identifying damagein a complex structural system. Therefore, it can be applied to identifying pipeline conditions.

Tracking of dietary intakes in early childhood : the Melbourne InFANT program

Background/Objectives: The objectives of the present study were to describe food and nutrient intakes in children aged 9 and 18 months, and to assess tracking of intakes between these two ages.

Subjects/Methods: Participants were 177 children of first-time mothers from the control arm of the Melbourne Infant Feeding Activity and Nutrition Trial (InFANT) Program. Dietary intake was collected at 9 and 18 months using three 24 h diet recalls. Tracking was assessed for food and nutrient intakes using logistic regression analysis and estimating partial correlation coefficients, respectively.

Results: Although overall nutrient intakes estimated in this study did not indicate a particular risk of nutrient deficiency, our findings suggest that consumption of energy-dense, nutrient-poor foods occurred as early as 9 months of age, with some of these foods tracking highly over the weaning period. Intakes of healthier foods such as fruits, vegetables, dairy products, eggs, fish and water were also relatively stable over this transition from infancy to toddlerhood, along with moderate tracking for riboflavin, iodine, fibre, calcium and iron. Tracking was low but close to ρ=0.3 for zinc, magnesium and potassium intakes.

Conclusions: The tracking of energy-dense, nutrient-poor foods has important implications for public health, given the development of early eating behaviours is likely to be modifiable. At this stage of life, dietary intakes are largely influenced by the foods parents provide, parental feeding practices and modelling. This study supports the importance of promoting healthy dietary trajectories from infancy.

Quantification of tackling demands in professional Australian football using integrated wearable athlete tracking technology

Objectives
To describe and quantify the frequency, velocity and acceleration at impact during tackling in Australian football using a combination of video and athlete tracking technology.

Design
Quasi-experimental.

Methods
Data was collected from twenty professional Australian Football League players during four in-season matches. All tackles made by the player and those against the player were video-coded and time stamped at the point of contact and then subjectively categorised into low, medium and high intensity impact groups. Peak GPS and acceleration data were identified at the point of contact. Two-way analysis of variance was used to assess differences (p < 0.05) between tackle type (made and against) and tackle intensity.

Results
A total of 173 tackles made and 179 tackles against were recorded. Significant differences were found between all tackle intensity groups. Peak velocity was significantly greater in high (19.5 ± 6.1 km h−1) compared to medium (13.4 ± 5.8 km h−1) and low intensity (11.3 ± 5.0 km h−1) tackles. Peak Player Load™, a modified vector magnitude of tri-axial acceleration, was significantly greater in high (7.5 ± 1.7 a.u.) compared to medium (4.9 ± 1.5 a.u.) and low intensity (4.0 ± 1.3 a.u.) tackles.

Conclusions
High intensity tackles, although less frequent, are significantly greater in speed of movement immediately prior to contact and in the resultant impact acceleration compared to tackles of lower intensity. Differences in accelerometer data between tackles observed to be progressively greater in intensity suggest a level of ecological validity and provide preliminary support for the use of accelerometers to assess impact forces in contact invasion sports.

Satellite tracking reveals unusual diving characteristics for a marine reptile, the olive ridley turtle : Lepidochelys olivacea

The movements, diving behaviour and thermal environment occupied by 4 adult female olive ridley turtles Lepidochelys olivacea in northern Australia were determined through satellite telemetry. Patterns of behaviour recorded were rather unusual compared to other sea turtles in that dives were mainly deep, largely benthic and exceptionally long (>2 h) in some cases, characteristics typical of over-wintering turtles in colder environments. One individual occupied shallow coastal foraging zones, while the others foraged far from land (probably on the seabed) in relatively deep water (>100 m). Individuals performed long dives (frequently >100 min), but from the short post-dive intervals we suggest that these dives were mainly aerobic. Maximum dive depth recorded was 200 ± 20 m (mean maximum depths ranged from 20.1 to 46.7 m across individuals; n = 17328 dives in total; depths ≥3 m were considered ‘dives’) and the maximum duration was 200 ± 20 min (mean durations ranged from 24.5 to 48.0 min across individuals). Temperature profiles indicate that turtles experienced temperatures ranging from 23 to 29°C at the surface, with the lowest temperature recorded (18.7°C) at a depth of 98 m. Only 6.9% of the dives were in water <20°C. From time-allocation at depth (TAD) scores, we demonstrated that many dives reaching the known or inferred sea bottom were U-shaped, but there was no apparent diel signal in dive depth. This suggests that many benthic dives were not associated exclusively with resting behaviour and likely had a foraging component as well. The ability to perform long benthic dives allows this species to exploit deeper benthic environments in addition to the shallow coastal areas more generally occupied by adult hard-shelled sea turtles (e.g. green and hawksbill turtles). Deep benthic dives also occur in certain marine mammals (e.g. narwhals) and sea birds (e.g. rockhopper penguins) and therefore seem to be a general foraging strategy exploited by animals that can perform long dives.

Multiple-object tracking in cluttered and crowded public spaces

This paper addresses the problem of tracking moving objects of variable appearance in challenging scenes rich with features and texture. Reliable tracking is of pivotal importance in surveillance applications. It is made particularly difficult by the nature of objects encountered in such scenes: these too change in appearance and scale, and are often articulated (e.g. humans). We propose a method which uses fast motion detection and segmentation as a constraint for both building appearance models and their robust propagation (matching) in time. The appearance model is based on sets of local appearances automatically clustered using spatio-kinetic similarity, and is updated with each new appearance seen. This integration of all seen appearances of a tracked object makes it extremely resilient to errors caused by occlusion and the lack of permanence of due to low data quality, appearance change or background clutter. These theoretical strengths of our algorithm are empirically demonstrated on two hour long video footage of a busy city marketplace.

The good news about television: attitudes aren't getting worse: tracking public attitudes toward TV advertising

Periodically tracking public sentiment toward television advertising (TVA) is an important barometer for the advertising industry and its myriad stakeholders. To date, however, most studies of consumers’ attitudes to TVA have been cross-sectional. This study, alternatively, provides a quasi-longitudinal examination of Australian attitudes toward TVA across four time points (2002, 2005, 2008, and 2010). Findings suggest that although attitudes toward TVA are generally negative, in fact they have not deteriorated over time. Considerable scope consequently exists for improving consumer attitudes toward TVA.

Finite element model updating using estimation of distribution algorithm

Finite Element (FE) model updating has been attracting research attentions in structural engineering fields for over 20 years. Its immense importance to the design, construction and maintenance of civil and mechanical structures has been highly recognised. However, many sources of uncertainties may affect the updating results. These uncertainties may be caused by FE modelling errors, measurement noises, signal processing techniques, and so on. Therefore, research efforts on model updating have been focusing on tackling with uncertainties for a long time. Recently, a new type of evolutionary algorithms has been developed to address uncertainty problems, known as Estimation of Distribution Algorithms (EDAs). EDAs are evolutionary algorithms based on estimation and sampling from probabilistic models and able to overcome some of the drawbacks exhibited by traditional genetic algorithms (GAs). In this paper, a numerical steel simple beam is constructed in commercial software ANSYS. The various damage scenarios are simulated and EDAs are employed to identify damages via FE model updating process. The results show that the performances of EDAs for model updating are efficient and reliable.

Wireless sensor networks for heritage object deformation detection and tracking algorithm

Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.