Obstacle avoidance routing scheme through optimal sink movement for home monitoring and mobile robotic consumer devices

In recent years, ZigBee has been proven to be an excellent solution to create scalable and flexible home automation networks. In a home automation network, consumer devices typically collect data from a home monitoring environment and then transmit the data to an end user through multi-hop communication without the need for any human intervention. However, due to the presence of typical obstacles in a home environment, error-free reception may not be possible, particularly for power constrained devices. A mobile sink based data transmission scheme can be one solution but obstacles create significant complexities for the sink movement path determination process. Therefore, an obstacle avoidance data routing scheme is of vital importance to the design of an efficient home automation system. This paper presents a mobile sink based obstacle avoidance routing scheme for a home monitoring system. The mobile sink collects data by traversing through the obstacle avoidance path. Through ZigBee based hardware implementation and verification, the proposed scheme successfully transmits data through the obstacle avoidance path to improve network performance in terms of life span, energy consumption and reliability. The application of this work can be applied to a wide range of intelligent pervasive consumer products and services including robotic vacuum cleaners and personal security robots1.

Nonlinear identification using orthogonal forward regression with nested optimal regularization

An efficient data based-modeling algorithm for nonlinear system identification is introduced for radial basis function (RBF) neural networks with the aim of maximizing generalization capability based on the concept of leave-one-out (LOO) cross validation. Each of the RBF kernels has its own kernel width parameter and the basic idea is to optimize the multiple pairs of regularization parameters and kernel widths, each of which is associated with a kernel, one at a time within the orthogonal forward regression (OFR) procedure. Thus, each OFR step consists of one model term selection based on the LOO mean square error (LOOMSE), followed by the optimization of the associated kernel width and regularization parameter, also based on the LOOMSE. Since like our previous state-of-the-art local regularization assisted orthogonal least squares (LROLS) algorithm, the same LOOMSE is adopted for model selection, our proposed new OFR algorithm is also capable of producing a very sparse RBF model with excellent generalization performance. Unlike our previous LROLS algorithm which requires an additional iterative loop to optimize the regularization parameters as well as an additional procedure to optimize the kernel width, the proposed new OFR algorithm optimizes both the kernel widths and regularization parameters within the single OFR procedure, and consequently the required computational complexity is dramatically reduced. Nonlinear system identification examples are included to demonstrate the effectiveness of this new approach in comparison to the well-known approaches of support vector machine and least absolute shrinkage and selection operator as well as the LROLS algorithm.

Deforestation, leakage and avoided deforestation policies: a spatial analysis

This paper analyses the impact of several avoided deforestation policies within a patchy forested landscape. Central is the idea that deforestation choices in one area influence deforestation decisions in nearby patches. We explore the interplay between forest landscapes comprising heterogeneous patches, localised spatial displacement, and avoided deforestation policies. Avoided deforestation policies at a landscape level are respectively: two Payments for Environmental Services (PES) policies, one focused on deforestation hotspots, the second being equally available to all agents; a conservation area; and, an agglomeration bonus. We demonstrate how the "best" policy, in terms of reduced leakage, depends on landscape heterogeneity. Agglomeration bonuses are shown to be more effective where there is less landscape heterogeneity, whilst conservation areas are most effective where there is more spatial heterogeneity.

Improving climate change detection through optimal seasonal averaging: the case of the North Atlantic jet and European precipitation

The detection of anthropogenic climate change can be improved by recognising the seasonality in the climate change response. This is demonstrated for the North Atlantic jet (zonal wind at 850 hPa, U850) and European precipitation responses projected by the CMIP5 climate models. The U850 future response is characterised by a marked seasonality: an eastward extension of the North Atlantic jet into Europe in November-April, and a poleward shift in May-October. Under the RCP8.5 scenario, the multi-model mean response in U850 in these two extended seasonal means emerges by 2035-2040 for the lower--latitude features and by 2050-2070 for the higher--latitude features, relative to the 1960-1990 climate. This is 5-15 years earlier than when evaluated in the traditional meteorological seasons (December--February, June--August), and it results from an increase in the signal to noise ratio associated with the spatial coherence of the response within the extended seasons. The annual mean response lacks important information on the seasonality of the response without improving the signal to noise ratio. The same two extended seasons are demonstrated to capture the seasonality of the European precipitation response to climate change and to anticipate its emergence by 10-20 years. Furthermore, some of the regional responses, such as the Mediterranean precipitation decline and the U850 response in North Africa in the extended winter, are projected to emerge by 2020-2025, according to the models with a strong response. Therefore, observations might soon be useful to test aspects of the atmospheric circulation response predicted by some of the CMIP5 models.

Housing Policies in Latin America: overview of the four largest economies

The aim of this paper is to examine the differences and similarities in housing policies in the four Latin American countries of Argentina, Brazil, Chile and Colombia. The article uses the welfare regime approach, modified by a recognition of path dependence, to identify a number of phases that each country has passed through. However, attention is drawn to the substantial differences in the circumstances in each country and the extent and duration of the different phases. It is concluded that it can be beneficial to use the concept of a Latin American housing regime, but that this general picture has to be used with an understanding of the path dependence caused by the different context in the individual countries.

Asset liability modelling and pension schemes: the application of robust optimization to USS

This paper uses a novel numerical optimization technique - robust optimization - that is well suited to solving the asset-liability management (ALM) problem for pension schemes. It requires the estimation of fewer stochastic parameters, reduces estimation risk and adopts a prudent approach to asset allocation. This study is the first to apply it to a real-world pension scheme, and the first ALM model of a pension scheme to maximise the Sharpe ratio. We disaggregate pension liabilities into three components - active members, deferred members and pensioners, and transform the optimal asset allocation into the scheme’s projected contribution rate. The robust optimization model is extended to include liabilities and used to derive optimal investment policies for the Universities Superannuation Scheme (USS), benchmarked against the Sharpe and Tint, Bayes-Stein, and Black-Litterman models as well as the actual USS investment decisions. Over a 144 month out-of-sample period robust optimization is superior to the four benchmarks across 20 performance criteria, and has a remarkably stable asset allocation – essentially fix-mix. These conclusions are supported by six robustness checks.

Research data management and openness: the role of data sharing in developing institutional policies and practices

Purpose: To investigate the relationship between research data management (RDM) and data sharing in the formulation of RDM policies and development of practices in higher education institutions (HEIs). Design/methodology/approach: Two strands of work were undertaken sequentially: firstly, content analysis of 37 RDM policies from UK HEIs; secondly, two detailed case studies of institutions with different approaches to RDM based on semi-structured interviews with staff involved in the development of RDM policy and services. The data are interpreted using insights from Actor Network Theory. Findings: RDM policy formation and service development has created a complex set of networks within and beyond institutions involving different professional groups with widely varying priorities shaping activities. Data sharing is considered an important activity in the policies and services of HEIs studied, but its prominence can in most cases be attributed to the positions adopted by large research funders. Research limitations/implications: The case studies, as research based on qualitative data, cannot be assumed to be universally applicable but do illustrate a variety of issues and challenges experienced more generally, particularly in the UK. Practical implications: The research may help to inform development of policy and practice in RDM in HEIs and funder organisations. Originality/value: This paper makes an early contribution to the RDM literature on the specific topic of the relationship between RDM policy and services, and openness – a topic which to date has received limited attention.

Transformation through translation: translation policies at Amnesty International

International non-governmental organisations (NGOs) are powerful political players who aim to influence global society. In order to be effective on a global scale, they must communicate their goals and achievements in different languages. Translation and translation policy play an essential role here. Despite NGOs’ important position in politics and society, not much is known about how these organisations, who often have limited funds available, organise their translation work. This study aims to contribute to Translation Studies, and more specifically to investigating institutional translation, by exploring translation policies at Amnesty International, one of the most successful and powerful human rights NGOs around the world. Translation policy is understood as comprising three components: translation management, translation practices, and translation beliefs, based on Spolsky’s study of language policy (2004). The thesis investigates how translation is organised and what kind of policies different Amnesty offices have in place, and how this is reflected in their translation products. The thesis thus also pursues how translation and translation policy impact on the organisation’s message and voice as it is spread around the world. An ethnographic approach is used for the analysis of various data sets that were collected during fieldwork. These include policy documents, guidelines on writing and translation, recorded interviews, e-mail correspondence, and fieldnotes. The thesis at first explores Amnesty’s global translation policy, and then presents the results of a comparative analysis of local translation policies at two concrete institutions: Amnesty International Language Resource Centre in Paris (AILRC-FR) and Amnesty International Vlaanderen (AIVL). A corpus of English source texts and Dutch (AIVL) and French (AILRC-FR) target texts are analysed. The findings of the analysis of translation policies and of the translation products are then combined to illustrate how translation impacts on Amnesty’s message and voice. The research results show that there are large differences in how translation is organised depending on the local office and the language(s), and that this also influences the way in which Amnesty’s message and voice are represented. For Dutch and French specifically, translation policies and translation products differ considerably. The thesis describes how these differences are often the result of different beliefs and assumptions relating to translation, and that staff members within Amnesty are not aware of the different conceptions of translation that exist within Amnesty International as a formal institution. Organising opportunities where translation can be discussed (meetings, workshops, online platforms) can help in reducing such differences. The thesis concludes by suggesting that an increased awareness of these issues will enable Amnesty to make more effective use of translation in its fight against human rights violations.

Optimal infinity-quasiconformal immersions

For a Hamiltonian K ∈ C2(RN × n) and a map u:Ω ⊆ Rn − → RN, we consider the supremal functional (1) The “Euler−Lagrange” PDE associated to (1)is the quasilinear system (2) Here KP is the derivative and [ KP ] ⊥ is the projection on its nullspace. (1)and (2)are the fundamental objects of vector-valued Calculus of Variations in L∞ and first arose in recent work of the author [N. Katzourakis, J. Differ. Eqs. 253 (2012) 2123–2139; Commun. Partial Differ. Eqs. 39 (2014) 2091–2124]. Herein we apply our results to Geometric Analysis by choosing as K the dilation function which measures the deviation of u from being conformal. Our main result is that appropriately defined minimisers of (1)solve (2). Hence, PDE methods can be used to study optimised quasiconformal maps. Nonconvexity of K and appearance of interfaces where [ KP ] ⊥ is discontinuous cause extra difficulties. When n = N, this approach has previously been followed by Capogna−Raich ? and relates to Teichmüller’s theory. In particular, we disprove a conjecture appearing therein.

Mesh adaptation on the sphere using optimal transport and the numerical solution of a Monge-Ampère type equation

An equation of Monge-Ampère type has, for the first time, been solved numerically on the surface of the sphere in order to generate optimally transported (OT) meshes, equidistributed with respect to a monitor function. Optimal transport generates meshes that keep the same connectivity as the original mesh, making them suitable for r-adaptive simulations, in which the equations of motion can be solved in a moving frame of reference in order to avoid mapping the solution between old and new meshes and to avoid load balancing problems on parallel computers. The semi-implicit solution of the Monge-Ampère type equation involves a new linearisation of the Hessian term, and exponential maps are used to map from old to new meshes on the sphere. The determinant of the Hessian is evaluated as the change in volume between old and new mesh cells, rather than using numerical approximations to the gradients. OT meshes are generated to compare with centroidal Voronoi tesselations on the sphere and are found to have advantages and disadvantages; OT equidistribution is more accurate, the number of iterations to convergence is independent of the mesh size, face skewness is reduced and the connectivity does not change. However anisotropy is higher and the OT meshes are non-orthogonal. It is shown that optimal transport on the sphere leads to meshes that do not tangle. However, tangling can be introduced by numerical errors in calculating the gradient of the mesh potential. Methods for alleviating this problem are explored. Finally, OT meshes are generated using observed precipitation as a monitor function, in order to demonstrate the potential power of the technique.

Conditioning and preconditioning of the optimal state estimation problem

Optimal state estimation is a method that requires minimising a weighted, nonlinear, least-squares objective function in order to obtain the best estimate of the current state of a dynamical system. Often the minimisation is non-trivial due to the large scale of the problem, the relative sparsity of the observations and the nonlinearity of the objective function. To simplify the problem the solution is often found via a sequence of linearised objective functions. The condition number of the Hessian of the linearised problem is an important indicator of the convergence rate of the minimisation and the expected accuracy of the solution. In the standard formulation the convergence is slow, indicating an ill-conditioned objective function. A transformation to different variables is often used to ameliorate the conditioning of the Hessian by changing, or preconditioning, the Hessian. There is only sparse information in the literature for describing the causes of ill-conditioning of the optimal state estimation problem and explaining the effect of preconditioning on the condition number. This paper derives descriptive theoretical bounds on the condition number of both the unpreconditioned and preconditioned system in order to better understand the conditioning of the problem. We use these bounds to explain why the standard objective function is often ill-conditioned and why a standard preconditioning reduces the condition number. We also use the bounds on the preconditioned Hessian to understand the main factors that affect the conditioning of the system. We illustrate the results with simple numerical experiments.

A multi level analysis on pollination-related policies

The paper explores pollination from a multi level policy perspective and analyses the institutional fit and inter play of multi-faceted pollination-related policies. First, it asks what the major policies are that frame pollination at the EU level. Second, it explores the relationship between the EU policies and localised ways of understanding pollination. Addressed third is how the concept of ecosystem services can aid in under- standing the various ways of framing and governing the situation. The results show that the policy systems affecting pollination are abundant and that these systems create different kinds of pressure on stakeholders, at several levels of society. The local-level concerns are more about the loss of pollination services than about loss of pollinators. This points to the problem of fit between local activity driven by economic reasoning and biodiversity-driven EU policies. Here we see the concept of ecosystem services having some potential, since its operationalisation can combine economic and environmental considerations. Further- more, the analysis shows how, instead of formal institutions, it seems that social norms, habits, and motivation are the key to understanding and developing effective and attractive governance measures.