Modelling collision potentials in Port Anchorages: Application of the Navigational Traffic Conflict Technique (NTCT)

Despite the extent of works done on modelling port water collisions, not much research effort has been devoted to modelling collisions at port anchorages. This paper aims to fill this important gap in literature by applying the Navigation Traffic Conflict Technique (NTCT) for measuring the collision potentials in anchorages and for examining the factors contributing to collisions. Grounding on the principles of the NTCT, a collision potential measurement model and a collision potential prediction model were developed. These models were illustrated by using vessel movement data of the anchorages in Singapore port waters. Results showed that the measured collision potentials are in close agreement with those perceived by harbour pilots. Higher collision potentials were found in anchorages attached to shoreline and international fairways, but not at those attached to confined water. Higher operating speeds, larger numbers of isolated danger marks and day conditions were associated with reduction in the collision potentials.

Creative adaptations: Integrating Feldenkrais principles in contemporary dance technique to facilitate the transition into tertiary dance education

As conservatoire-style dance teaching has traditionally utilised a hierarchical approach through which the student must conform to the ideal requirements of the conventional technique, current discourse is beginning to question how dance training can develop technical acuity without stifling students' ability to engage creatively. In recent years, there has been growing interest in the field of somatics and its relationship to tertiary dance training due to the understanding that this approach supports creative autonomy by radically repositioning the student's relationship to embodied learning, skill acquisition, enquiry and performance. This research addresses an observable disjuncture between the skills of dancers graduating from tertiary training and Australian dance industry needs, which increasingly demand the co-creative input of the dancer in choreographic practice. Drawing from Action Research, this paper will discuss a project which introduces somatic learning approaches, primarily from Feldenkrais Method and Hanna Somatics, to first-year dance students in their transition into tertiary education. This paper acknowledges previous research undertaken, most specifically the Somdance Manual by the University of Western Sydney, while directing focus to the first-year student transition from private dance studio training into the pre-professional arena.

Does the technique employed for skin temperature assessment alter outcomes? A systematic review

Skin temperature is an important physiological measure that can reflect the presence of illness and injury as well as provide insight into the localised interactions between the body and the environment. The aim of this systematic review was to analyse the agreement between conductive and infrared means of assessing skin temperature which are commonly employed in in clinical, occupational, sports medicine, public health and research settings. Full-text eligibility was determined independently by two reviewers. Studies meeting the following criteria were included in the review: 1) the literature was written in English, 2) participants were human (in vivo), 3) skin surface temperature was assessed at the same site, 4) with at least two commercially available devices employed—one conductive and one infrared—and 5) had skin temperature data reported in the study. A computerised search of four electronic databases, using a combination of 21 keywords, and citation tracking was performed in January 2015. A total of 8,602 were returned. Methodology quality was assessed by 2 authors independently, using the Cochrane risk of bias tool. A total of 16 articles (n = 245) met the inclusion criteria. Devices are classified to be in agreement if they met the clinically meaningful recommendations of mean differences within ±0.5 °C and limits of agreement of ±1.0 °C. Twelve of the included studies found mean differences greater than ±0.5 °C between conductive and infrared devices. In the presence of external stimulus (e.g. exercise and/or heat) five studies foundexacerbated measurement differences between conductive and infrared devices. This is the first review that has attempted to investigate presence of any systemic bias between infrared and conductive measures by collectively evaluating the current evidence base. There was also a consistently high risk of bias across the studies, in terms of sample size, random sequence generation, allocation concealment, blinding and incomplete outcome data. This systematic review questions the suitability of using infrared cameras in stable, resting, laboratory conditions. Furthermore, both infrared cameras and thermometers in the presence of sweat and environmental heat demonstrate poor agreement when compared to conductive devices. These findings have implications for clinical, occupational, public health, sports science and research fields.

Let’s talk about lex: Narrative analysis as both research method and teaching technique in law

Law is narration: it is narrative, narrator and the narrated. As a narrative, the law is constituted by a constellation of texts – from official sources such as statutes, treaties and cases, to private arrangements such as commercial contracts, deeds and parenting plans. All are a collection of stories: cases are narrative contests of facts and rights; statutes are recitations of the substantive and procedural bases for social, economic and political interactions; private agreements are plots for future relationships, whether personal or professional. As a narrator, law speaks in the language of modern liberalism. It describes its world in abstractions rather than in concrete experience, universal principles rather than individual subjectivity. It casts people into ‘parties’ to legal relationships; structures human interactions into ‘issues’ or ‘problems’; and tells individual stories within larger narrative arcs such as ‘the rule of law’ and ‘the interests of justice’. As the narrated, the law is a character in its own story. The scholarship of law, for example, is a type of story-telling with law as its central character. For positivists, still the dominant group in the legal genre, law is a closed system of formal rules with an “immanent rationality” and its own “structure, substantive content, procedure and tradition,” dedicated to finality of judgment. For scholars inspired by the interpretative tradition in the humanities, law is a more ambivalent character, susceptible to influences from outside its realm and masking a hidden ideological agenda under its cloak of universality and neutrality. For social scientists, law is a protagonist on a wider social stage, impacting on society, the economy and the polity is often surprising ways.

Transition to an unsteady flow induced by a fin on the sidewall of a differentially heated air-filled square cavity and heat transfer

The transition from a steady to an unsteady flow induced by an adiabatic fin on the sidewall of a differentially heated air-filled cavity is numerically investigated. Numerical simulations have been performed over the range of Rayleigh numbers from Ra = 105–109. The temporal development and spatial structures of natural convection flows in the cavity with a fin are described. It has been demonstrated that the fin may induce the transition to an unsteady flow and the critical Rayleigh number for the occurrence of the transition is between 3.72 × 106 and 3.73 × 106. Furthermore, the peak frequencies of the oscillations triggered by different mechanisms are obtained through spectral analysis. It has been found that the flow rate through the cavity with a fin is larger than that without a fin under the unsteady flow, indicating that the fin may improve the unsteady flow in the cavity.

Graphene quantum dots and the resonance light scattering technique for trace analysis of phenol in different water samples

A novel, highly selective resonance light scattering (RLS) method was researched and developed for the analysis of phenol in different types of industrial water. An important aspect of the method involved the use of graphene quantum dots (GQDs), which were initially obtained from the pyrolysis of citric acid dissolved in aqueous solutions. The GQDs in the presence of horseradish peroxidase (HRP) and H2O2 were found to react quantitatively with phenol such that the RLS spectral band (310 nm) was quantitatively enhanced as a consequence of the interaction between the GQDs and the quinone formed in the above reaction. It was demonstrated that the novel analytical method had better selectivity and sensitivity for the determination of phenol in water as compared to other analytical methods found in the literature. Thus, trace amounts of phenol were detected over the linear ranges of 6.00×10−8–2.16×10−6 M and 2.40×10−6–2.88×10−5 M with a detection limit of 2.20×10−8 M. In addition, three different spiked waste water samples and two untreated lake water samples were analysed for phenol. Satisfactory results were obtained with the use of the novel, sensitive and rapid RLS method.

Comparison of oropharyngeal and oral cavity squamous cell cancer incidence and trends in New Zealand and Queensland, Australia

Background Increases in the incidence of squamous cell oropharyngeal cancer (OPC) have been reported from some countries, but have not been assessed in Australia or New Zealand. This study examines trends for squamous cell OPC and squamous cell oral cavity cancer (OCC) in two similarly sized populations, New Zealand and Queensland, Australia. Methods Incidence data for 1982–2010 were obtained from the respective population-based cancer registries for squamous cell OPC and OCC, by subsite, sex, and age. Time trends and annual percentage changes (APCs) were assessed by joinpoint regression. Results The incidence rates of squamous cell OPC in males in New Zealand since 2005 and Queensland since 2006 have increased rapidly, with APCs of 11.9% and 10.6% respectively. The trends were greatest at ages 50–69 and followed more gradual increases previously. In females, rates increased by 2.1% per year in New Zealand from 1982, but by only 0.9% (not significant) in Queensland. In contrast, incidence rates for OCC decreased by 1.2% per year in males in Queensland since 1982, but remained stable for females in Queensland and for both sexes in New Zealand. Overall, incidence rates for both OCC and OPC were substantially higher in Queensland than in New Zealand. In males in both areas, OPC incidence is now higher than that of OCC. Conclusions Incidence rates of squamous cell OPC have increased rapidly in men, while rates of OCC have been stable or reducing, showing distinct etiologies. This has both clinical and public health importance, including implications for the extension of human papilloma virus (HPV) vaccination to males.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Studies of water and electrolyte movement from oral rehydration solutions (rice- and glucose-based) across a normal and secreting gut using a dual isotope tracer technique in a rat perfusion model

Aims: To establish a model to measure bidirectional flow of water from a glucose oral rehydration solution (G-ORS) and a newly developed rice-based oral rehydration solution (R-ORS) using a dual isotope tracer technique in a rat perfusion model. To measure net water, sodium and potassium absorption from the ORS. Methods: In viva steady-state perfusion studies were carried out in normal and secreting (induced by cholera toxin) rat small intestine (n = 11 in each group). To determine bidirectional flow of water from the ORS the animals were initially labelled with tritium, and deuterium was added to the perfusion solution. Sequential perfusate and blood samples were collected after attainment of steady-state conditions and analysed for water and electrolyte content. Results: There was a significant increase in net water absorption from the R-ORS compared to the G-ORS in both the normal (P < 0.02) and secreting intestine (P < 0.05). Water efflux was significantly reduced in the R-ORS group compared to the G-ORS group in both the normal (P < 0.01) and the secreting intestine (P < 0.01). There was an increase in sodium absorption in the R-ORS group compared to the G-ORS. The G-ORS produced a significantly greater blood glucose level at 75 min compared to the R-ORS (P < 0.03) in the secreting intestine. Conclusions: This study demonstrates the improved water absorption from a rice-based ORS in both the normal and secreting intestine. Evidence that the absorption of water may be influenced by the osmolality of the ORS was also demonstrated.

Constrained Linear Spectral Unmixing Technique for Regional Land Cover Mapping Using MODIS Data

Over the last few decades, there has been a significant land cover (LC) change across the globe due to the increasing demand of the burgeoning population and urban sprawl. In order to take account of the change, there is a need for accurate and up-to-date LC maps. Mapping and monitoring of LC in India is being carried out at national level using multi-temporal IRS AWiFS data. Multispectral data such as IKONOS, Landsat-TM/ETM+, IRS-ICID LISS-III/IV, AWiFS and SPOT-5, etc. have adequate spatial resolution (similar to 1m to 56m) for LC mapping to generate 1:50,000 maps. However, for developing countries and those with large geographical extent, seasonal LC mapping is prohibitive with data from commercial sensors of limited spatial coverage. Superspectral data from the MODIS sensor are freely available, have better temporal (8 day composites) and spectral information. MODIS pixels typically contain a mixture of various LC types (due to coarse spatial resolution of 250, 500 and 1000 in), especially in more fragmented landscapes. In this context, linear spectral unmixing would be useful for mapping patchy land covers, such as those that characterise much of the Indian subcontinent. This work evaluates the existing unmixing technique for LC mapping using MODIS data, using end-members that are extracted through Pixel Purity Index (PPI), Scatter plot and N-dimensional visualisation. The abundance maps were generated for agriculture, built up, forest, plantations, waste land/others and water bodies. The assessment of the results using ground truth and a LISS-III classified map shows 86% overall accuracy, suggesting the potential for broad-scale applicability of the technique with superspectral data for natural resource planning and inventory applications. Index Terms-Remote sensing, digital

Influence of friction during forming processes-a study using a numerical simulation technique

Friction has an important influence in metal forming operations, as it contributes to the success or otherwise of the process. In the present investigation, the effect of friction on metal forming was studied by simulating compression tests on cylindrical Al-Mg alloy using the finite element method (FEM) technique. Three kinds of compression tests were considered wherein a constant coefficient of friction was employed at the upper die-work-piece interface. However, the coefficient of friction between the lower die-work-piece interfaces was varied in the tests. The simulation results showed that a difference in metal flow occurs near the interfaces owing to the differences in the coefficient of friction. It was concluded that the variations in the coefficient of friction between the dies and the work-piece directly affect the stress distribution and shape of the work-piece, having implications on the microstructure of the material being processed.

SPSA Based Feature Relevance Estimation For Video Retrieval

With the availability of a huge amount of video data on various sources, efficient video retrieval tools are increasingly in demand. Video being a multi-modal data, the perceptions of ``relevance'' between the user provided query video (in case of Query-By-Example type of video search) and retrieved video clips are subjective in nature. We present an efficient video retrieval method that takes user's feedback on the relevance of retrieved videos and iteratively reformulates the input query feature vectors (QFV) for improved video retrieval. The QFV reformulation is done by a simple, but powerful feature weight optimization method based on Simultaneous Perturbation Stochastic Approximation (SPSA) technique. A video retrieval system with video indexing, searching and relevance feedback (RF) phases is built for demonstrating the performance of the proposed method. The query and database videos are indexed using the conventional video features like color, texture, etc. However, we use the comprehensive and novel methods of feature representations, and a spatio-temporal distance measure to retrieve the top M videos that are similar to the query. In feedback phase, the user activated iterative on the previously retrieved videos is used to reformulate the QFV weights (measure of importance) that reflect the user's preference, automatically. It is our observation that a few iterations of such feedback are generally sufficient for retrieving the desired video clips. The novel application of SPSA based RF for user-oriented feature weights optimization makes the proposed method to be distinct from the existing ones. The experimental results show that the proposed RF based video retrieval exhibit good performance.

Model Predictive Static Programming: A Computationally Efficient Technique For Suboptimal Control Design

Combining the philosophies of nonlinear model predictive control and approximate dynamic programming, a new suboptimal control design technique is presented in this paper, named as model predictive static programming (MPSP), which is applicable for finite-horizon nonlinear problems with terminal constraints. This technique is computationally efficient, and hence, can possibly be implemented online. The effectiveness of the proposed method is demonstrated by designing an ascent phase guidance scheme for a ballistic missile propelled by solid motors. A comparison study with a conventional gradient method shows that the MPSP solution is quite close to the optimal solution.

Constraining the low-energy pion electromagnetic form factor with space-like and phase of time-like data

The Taylor coefficients c and d of the EM form factor of the pion are constrained using analyticity, knowledge of the phase of the form factor in the time-like region, 4m(pi)(2) <= t <= t(in) and its value at one space-like point, using as input the (g - 2) of the muon. This is achieved using the technique of Lagrange multipliers, which gives a transparent expression for the corresponding bounds. We present a detailed study of the sensitivity of the bounds to the choice of time-like phase and errors present in the space-like data, taken from recent experiments. We find that our results constrain c stringently. We compare our results with those in the literature and find agreement with the chiral perturbation-theory results for c. We obtain d similar to O(10) GeV-6 when c is set to the chiral perturbation-theory values.

A probabilistic constrained nonlinear optimization framework to optimize RED parameters

The random early detection (RED) technique has seen a lot of research over the years. However, the functional relationship between RED performance and its parameters viz,, queue weight (omega(q)), marking probability (max(p)), minimum threshold (min(th)) and maximum threshold (max(th)) is not analytically availa ble. In this paper, we formulate a probabilistic constrained optimization problem by assuming a nonlinear relationship between the RED average queue length and its parameters. This problem involves all the RED parameters as the variables of the optimization problem. We use the barrier and the penalty function approaches for its Solution. However (as above), the exact functional relationship between the barrier and penalty objective functions and the optimization variable is not known, but noisy samples of these are available for different parameter values. Thus, for obtaining the gradient and Hessian of the objective, we use certain recently developed simultaneous perturbation stochastic approximation (SPSA) based estimates of these. We propose two four-timescale stochastic approximation algorithms based oil certain modified second-order SPSA updates for finding the optimum RED parameters. We present the results of detailed simulation experiments conducted over different network topologies and network/traffic conditions/settings, comparing the performance of Our algorithms with variants of RED and a few other well known adaptive queue management (AQM) techniques discussed in the literature.