End-to-end Lip-reading: A Preliminary Study

Deep lip-reading is the combination of the domains of computer vision and natural language processing. It uses deep neural networks to extract speech from silent videos. Most works in lip-reading use a multi staged training approach due to the complex nature of the task. A single stage, end-to-end, unified training approach, which is an ideal of machine learning, is also the goal in lip-reading. However, pure end-to-end systems have not yet been able to perform as good as non-end-to-end systems. Some exceptions to this are the very recent Temporal Convolutional Network (TCN) based architectures. This work lays out preliminary study of deep lip-reading, with a special focus on various end-to-end approaches. The research aims to test whether a purely end-to-end approach is justifiable for a task as complex as deep lip-reading. To achieve this, the meaning of pure end-to-end is first defined and several lip-reading systems that follow the definition are analysed. The system that most closely matches the definition is then adapted for pure end-to-end experiments. Four main contributions have been made: i) An analysis of 9 different end-to-end deep lip-reading systems, ii) Creation and public release of a pipeline1 to adapt sentence level Lipreading Sentences in the Wild 3 (LRS3) dataset into word level, iii) Pure end-to-end training of a TCN based network and evaluation on LRS3 word-level dataset as a proof of concept, iv) a public online portal2 to analyse visemes and experiment live end-to-end lip-reading inference. The study is able to verify that pure end-to-end is a sensible approach and an achievable goal for deep machine lip-reading

Stock message board recommendations and share trading activity

University of Technology, Sydney. Faculty of Business.The efficiency of capital markets is largely attributable to an effective information network that exists among market participants that include fund managers, analysts, and investors. The role of many market participants is to improve the flow of information to assist the market in becoming aware of, and understanding, information. In this work, we look at the role of message boards in improving market efficiency. We examine the impact of message boards on stock returns, volatility, trading volume and liquidity. The overall findings of our study are that message boards serve no useful purpose for stock returns and liquidity. However, message boards do seem to add risk to share trading by increasing the turnover and share price volatility. We also observe that message board participants are likely to follow the stock market activity. Our results make one think that participation in message boards serves more for social purposes such as interaction with like-minded investors, general amusement etc than anything else

Prevalence of Postpartum Family Planning Service Coverage in Selected Referral Facilities of Nepal

Introduction: Nepal Society of Obstetricians and Gynecologists jointly with the Nepalese government and with the support from the International Federation of Obstetrics and Gynecology has implemented an initiative to institutionalize postpartum family planning services in selected major referral facilities of Nepal to address the gap of low uptake of postpartum family planning in Nepal. The aim of the study is to find the prevalence of the service coverage of postpartum contraception in the selected facilities. Methods: A descriptive cross-sectional study was conducted in seven major referral facilities across Nepal. Data were collected from the hospital records of all women who delivered in these facilities between October 2018 and March 2019. Ethical approval for this study was obtained from Nepal Health Research Council. Data analysis was done with SPSS version 23. Results: Among the 29,072 deliveries from all the facilities, postpartum family planning counseling coverage was 27,301 (93.9%). The prevalence of uptake of Postpartum Intrauterine Device is 1581 (5.4%) and female sterilization is 1830 (6.3%). In total 11387 mothers (52.2%) had the intention to choose a postpartum family planning method. However, 36% of mothers neither used nor had the intention to choose a postpartum family planning method. Conclusions: The coverage of Postpartum Intrauterine Device counseling service coverage in Nepal is higher in 2018 as compared to 2016-2017 and in other countries implementing Postpartum Intrauterine Device initiatives. However, the prevalence of service coverage of immediate Postpartum Family Planning methods, mainly Postpartum Intrauterine Device in 2018 is lower in Nepal as compared to 2016-2017, and other countries implementing Postpartum Intrauterine Device initiative. More efforts are needed to encourage mothers delivering in the facilities to use the postpartum family planning method

WKB Approximation to the Power Wall

We present a semiclassical analysis of the quantum propagator of a particle confined on one side by a steeply, monotonically rising potential. The models studied in detail have potentials proportional to $x^{\alpha}$ for $x>0$; the limit $\alpha\to\infty$ would reproduce a perfectly reflecting boundary, but at present we concentrate on the cases $\alpha =1$ and 2, for which exact solutions in terms of well known functions are available for comparison. We classify the classical paths in this system by their qualitative nature and calculate the contributions of the various classes to the leading-order semiclassical approximation: For each classical path we find the action $S$, the amplitude function $A$ and the Laplacian of $A$. (The Laplacian is of interest because it gives an estimate of the error in the approximation and is needed for computing higher-order approximations.) The resulting semiclassical propagator can be used to rewrite the exact problem as a Volterra integral equation, whose formal solution by iteration (Neumann series) is a semiclassical, not perturbative, expansion. We thereby test, in the context of a concrete problem, the validity of the two technical hypotheses in a previous proof of the convergence of such a Neumann series in the more abstract setting of an arbitrary smooth potential. Not surprisingly, we find that the hypotheses are violated when caustics develop in the classical dynamics; this opens up the interesting future project of extending the methods to momentum space.Comment: 30 pages, 8 figures. Minor corrections in v.

Counting crocodiles from the sky: Monitoring the critically endangered gharial (Gavialis gangeticus) population with an Unmanned Aerial Vehicle (UAV).

Technology is rapidly changing the methods in the field of wildlife monitoring. Unmanned aerial vehicle (UAV) is an example of a new technology that allows biologists to take to the air to monitor wildlife. Fixed Wing UAV was used to monitor critically endangered gharial population along 46 km of the Babai River in Bardia National Park. The UAV was flown at an altitude of 80 m along 12 pre-designed missions with a search effort of 2.72 hours of flight time acquired a total of 11,799 images covering an effective surface area of 8.2 km2 of river bank habitat. The images taken from the UAV could differentiate between gharial and muggers. A total count of 33 gharials and 31 muggers with observed density (per km2) of 4.64 and 4.0 for gharial and mugger respectively. Comparison of count data between one-time UAV and multiple conventional visual encounter rate surveys data showed no significant difference in the mean. Basking season and turbidity were important factors for monitoring crocodiles along the river bank habitat. Efficacy of monitoring crocodiles by UAV at the given altitude can be replicated in high priority areas with less operating cost and acquisition of high resolution data

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems