Coverage algorithms for an under-actuated car-like vehicle in an uncertain environment

A coverage algorithm is an algorithm that deploys a strategy as to how to cover all points in terms of a given area using some set of sensors. In the past decades a lot of research has gone into development of coverage algorithms. Initially, the focus was coverage of structured and semi-structured indoor areas, but with time and development of better sensors and introduction of GPS, the focus has turned to outdoor coverage. Due to the unstructured nature of an outdoor environment, covering an outdoor area with all its obstacles and simultaneously performing reliable localization is a difficult task. In this paper, two path planning algorithms suitable for solving outdoor coverage tasks are introduced. The algorithms take into account the kinematic constraints of an under-actuated car-like vehicle, minimize trajectory curvatures, and dynamically avoid detected obstacles in the vicinity, all in real-time. We demonstrate the performance of the coverage algorithm in the field by achieving 95% coverage using an autonomous tractor mower without the aid of any absolute localization system or constraints on the physical boundaries of the area.

Coverage of international and Pacific news in the Fiji Times and The Australian

The debate over the nature and flow of international news has dominated intellectual debate about journalism practice for some time. Developing countries argued there was an imbalance in the nature and amount of international news concerning them. They argued that the Western media rarely reported on developing countries and when they did, reported predominantly negative news about developing countries. The debate led to calls for a New World Information and Communication Order (NWICO). A number of studies examined its arguments, many finding developing countries were indeed disadvantaged by the Western media. This study compared foreign news coverage in The Australian and The Fiji Times, with special attention on news from the Pacific Islands region. It found the coverage of the Pacific Islands was still grossly inadequate in both newspapers. The coverage consisted of only a small number of stories, which were predominantly negative, surprising especially in the case of The Fiji Times.

Foreign news coverage in five African newspapers

One of the principal arguments that dominated intellectual debate in the 19805 concerned the imbalance in the quantity and quality of world news, in particular news from developing countries. African delegates at the United Nations Educational, Scientific and Cultural Organisation (UNESCO), supported by other developing countries, argued that most of the news disseminated by the major Western news agencies was unfavourable to developing countries in qualitative and quantitative terms. Not only did Western news media pay little attention to news of developing countries, it was also argued that the few items that made the news tended to focus on negative events such as crises, wars, coups, riots, street demonstrations, diseases, poverty, pestilence, etc. More than 20 years after the intellectual debate received attention in academic journals, this study set out to examine systematically how African newspapers report the world. The researchers investigate the relative degree of balance and imbalance in the coverage of world news by Nigerian and Ghanaian newspapers. The study also examines Nigerian and Ghanaian journalists’ perceptions of world news coverage by local and foreign newspapers.

Populations of models, experimental designs and coverage of parameter space by Latin Hypercube and Orthogonal Sampling

In this paper we have used simulations to make a conjecture about the coverage of a t-dimensional subspace of a d-dimensional parameter space of size n when performing k trials of Latin Hypercube sampling. This takes the form P(k,n,d,t) = 1 - e^(-k/n^(t-1)). We suggest that this coverage formula is independent of d and this allows us to make connections between building Populations of Models and Experimental Designs. We also show that Orthogonal sampling is superior to Latin Hypercube sampling in terms of allowing a more uniform coverage of the t-dimensional subspace at the sub-block size level. These ideas have particular relevance when attempting to perform uncertainty quantification and sensitivity analyses.

The root locus method: application to linear stability analysis and design of cooperative car-following models

A global framework for linear stability analyses of traffic models, based on the dispersion relation root locus method, is presented and is applied taking the example of a broad class of car-following (CF) models. This approach is able to analyse all aspects of the dynamics: long waves and short wave behaviours, phase velocities and stability features. The methodology is applied to investigate the potential benefits of connected vehicles, i.e. V2V communication enabling a vehicle to send and receive information to and from surrounding vehicles. We choose to focus on the design of the coefficients of cooperation which weights the information from downstream vehicles. The coefficients tuning is performed and different ways of implementing an efficient cooperative strategy are discussed. Hence, this paper brings design methods in order to obtain robust stability of traffic models, with application on cooperative CF models

Combining HPLC-DAD and ICP-MS data for improved analysis of complex samples: Classification of the root samples from Cortex moutan

A combined data matrix consisting of high performance liquid chromatography–diode array detector (HPLC–DAD) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements of samples from the plant roots of the Cortex moutan (CM), produced much better classification and prediction results in comparison with those obtained from either of the individual data sets. The HPLC peaks (organic components) of the CM samples, and the ICP-MS measurements (trace metal elements) were investigated with the use of principal component analysis (PCA) and the linear discriminant analysis (LDA) methods of data analysis; essentially, qualitative results suggested that discrimination of the CM samples from three different provinces was possible with the combined matrix producing best results. Another three methods, K-nearest neighbor (KNN), back-propagation artificial neural network (BP-ANN) and least squares support vector machines (LS-SVM) were applied for the classification and prediction of the samples. Again, the combined data matrix analyzed by the KNN method produced best results (100% correct; prediction set data). Additionally, multiple linear regression (MLR) was utilized to explore any relationship between the organic constituents and the metal elements of the CM samples; the extracted linear regression equations showed that the essential metals as well as some metallic pollutants were related to the organic compounds on the basis of their concentrations

Estimates on the coverage of parameter space using populations of models

In this paper we provide estimates for the coverage of parameter space when using Latin Hypercube Sampling, which forms the basis of building so-called populations of models. The estimates are obtained using combinatorial counting arguments to determine how many trials, k, are needed in order to obtain specified parameter space coverage for a given value of the discretisation size n. In the case of two dimensions, we show that if the ratio (Ø) of trials to discretisation size is greater than 1, then as n becomes moderately large the fractional coverage behaves as 1-exp-ø. We compare these estimates with simulation results obtained from an implementation of Latin Hypercube Sampling using MATLAB.

Shift in disease burden from communicable to non-communicable diseases: Aiming to achieve Universal Health Coverage in Nepal

A major barrier to accessing healthcare services is spending, and the extended time that non-communicable diseases require treatment for means that many people around the world do not have proper access to care. Saval Khanal from Sankalpa Foundation, Nepal, Lennert Veerman and Samantha Hollingworth from the University of Queensland and Lisa Nissen from Queensland University of Technology lay out the results of their study and establish a method to forecast medicine use in Nepal.

Does the addition of Clonidine to lumbar nerve root blocks improve outcome? A randomised, prospective, single-blinded controlled pilot study

Purpose To evaluate if adding clonidine to a standard nerve root block containing local anaesthetic and steroid improved the outcome of patients with severe lumbar nerve root pain secondary to MRI proven lumbar disc prolapse. Methods We undertook a single blind, prospective, randomised controlled trial evaluating 100 consecutive patients with nerve root pain secondary to lumbar disc prolapse undergoing trans-foraminal epidural steroid injection either with or without the addition of clonidine. 50 patients were allocated to each arm of the study. The primary outcome measure was the avoidance of a second procedure- repeat injection or micro-discectomy surgery. Secondary outcome measures were also studied: pain scores for leg and back pain using a visual analogue scale (VAS), the Roland Morris Disability Questionnaire (RMDQ) and the Measure Your Own Medical Outcome Profile (MYMOP). Follow up was carried out at 6 weeks, 6 months and 1 year. Results No serious complications occurred. Of the 50 patients who received the addition of clonidine, 56% were classified as successful injections, with no further intervention required, as opposed to 40% who received the standard injection. This difference did not reach statistical significance (p=0.109, chi-squared test). All secondary measures showed no statistically significant differences between the groups except curiously, the standard group who had been classified as successful had better leg pain relief than the clonidine group (p=0.026) at 1 year. Conclusions This pilot study has shown a 16% treatment effect with adding clonidine to lumbar nerve root blocks and that it is a safe injectate for this purpose.

Lung cancer stem cells: The root of resistance

In the absence of specific treatable mutations, platinum-based chemotherapy remains the gold standard of treatment for lung cancer patients. However, 5-year survival rates remain poor due to the development of resistance and eventual relapse. Resistance to conventional cytotoxic therapies presents a significant clinical challenge in the treatment of this disease. The cancer stem cell (CSC) hypothesis suggests that tumors are arranged in a hierarchical structure, with the presence of a small subset of stem-like cells that are responsible for tumor initiation and growth. This CSC population has a number of key properties such as the ability to asymmetrically divide, differentiate and self-renew, in addition to having increased intrinsic resistance to therapy. While cytotoxic chemotherapy kills the bulk of tumor cells, CSCs are spared and have the ability to recapitulate the heterogenic tumor mass. The identification of lung CSCs and their role in tumor biology and treatment resistance may lead to innovative targeted therapies that may ultimately improve clinical outcomes in lung cancer patients. This review will focus on lung CSC markers, their role in resistance and their relevance as targets for future therapies.