An Africa strategy for IIMI

Irrigation management / Policy / Africa

A Stochastic View of Optimal Regret through Minimax Duality

We study the regret of optimal strategies for online convex optimization games. Using von Neumann's minimax theorem, we show that the optimal regret in this adversarial setting is closely related to the behavior of the empirical minimization algorithm in a stochastic process setting: it is equal to the maximum, over joint distributions of the adversary's action sequence, of the difference between a sum of minimal expected losses and the minimal empirical loss. We show that the optimal regret has a natural geometric interpretation, since it can be viewed as the gap in Jensen's inequality for a concave functional--the minimizer over the player's actions of expected loss--defined on a set of probability distributions. We use this expression to obtain upper and lower bounds on the regret of an optimal strategy for a variety of online learning problems. Our method provides upper bounds without the need to construct a learning algorithm; the lower bounds provide explicit optimal strategies for the adversary

Farmer-based financing of operations in the Niger Valley irrigation schemes.

Irrigation management / Irrigation systems / River basin development / Sustainability / Water resources development / Low-lift irrigation / Low-lift pumps / Farmer managed irrigation systems / Farmers' associations / Institution building / Privatization / Performance evaluation / Constraints / Case studies / Financing / Costs / Climate / Food production / Niger

Private irrigation in Sub-Saharan Africa: regional Seminar on Private Sector Participation and Irrigation Expansion in Sub-Saharan Africa, Accra, Ghana, 22-26 October 2001

Irrigation management / Privatization / Irrigated farming / Financing / Irrigation systems / Gender / Women / Government managed irrigation systems / Farmer managed irrigation systems / Rice / Horticulture / Technology transfer / Pumps / Drip irrigation / Filtration / Capacity building / Urban agriculture / Poverty / Water users associations / Agricultural credit

Optimal Strategies and Minimax Lower Bounds for Online Convex Games

A number of learning problems can be cast as an Online Convex Game: on each round, a learner makes a prediction x from a convex set, the environment plays a loss function f, and the learner’s long-term goal is to minimize regret. Algorithms have been proposed by Zinkevich, when f is assumed to be convex, and Hazan et al., when f is assumed to be strongly convex, that have provably low regret. We consider these two settings and analyze such games from a minimax perspective, proving minimax strategies and lower bounds in each case. These results prove that the existing algorithms are essentially optimal

Quantitative measurement of blood flow in paediatric brain tumours. A comparative study of dynamic susceptibility contrast and multi-timepoint arterial spin-labelled MRI

OBJECTIVE: Arterial spin-labelling (ASL) MRI uses intrinsic blood water to quantify the cerebral blood flow (CBF), removing the need for the injection of a gadolinium-based contrast agent used for conventional perfusion imaging such as dynamic susceptibility contrast (DSC). Owing to the non-invasive nature of the technique, ASL is an attractive option for use in paediatric patients. This work compared DSC and multi-timepoint ASL measures of CBF in paediatric brain tumours. METHODS: Patients (n = 23; 20 low-grade tumours and 3 high-grade tumours) had DSC and multi-timepoint ASL with and without vascular crushers (VC). VC removes the contribution from larger vessel blood flow. Mean perfusion metrics were extracted from control and T(1)-enhanced tumour regions of interest (ROIs): arterial arrival time (AAT) and CBF from the ASL images with and without VC, relative cerebral blood flow (rCBF), relative cerebral blood volume, delay time (DT) and mean transit time (MTT) from the DSC images. RESULTS: Significant correlations existed for: AAT and DT (r = 0.77, p = 0.0002) and CBF and rCBF (r = 0.56, p = 0.02) in control ROIs for ASL-noVC. No significant correlations existed between DSC and ASL measures in the tumour region. Significant differences between control and tumour ROI were found for MTT (p < 0.001) and rCBF (p < 0.005) measures. CONCLUSION: Significant correlations between ASL-noVC and DSC measures in the normal brain suggest that DSC is most sensitive to macrovascular blood flow. The absence of significant correlations within the tumour ROI suggests that ASL is sensitive to different physiological mechanisms compared with DSC measures. ADVANCES IN KNOWLEDGE: ASL provides information which is comparable with that of DSC in healthy tissues, but appears to reflect a different physiology in tumour tissues

Implications for telehealth for accessing education in rural areas: children with a severe chronic disease.

Children and their families who live in rural and remote areas are often disadvantaged by distance. In healthcare, this can be especially problematic. Children can suffer from a range of chronic conditions, e.g. diabetes, asthma, cardiac conditions, cystic fibrosis and others. In Australia, health services for children and families with such conditions are centred in specialist children’s hospitals in the capital cities in each state, but the burden of health care often falls to the parents and the children themselves. While rural health services do a wonderful job providing health care for these children, it is very rare to find specialist services in any rural situation. For example, children with cystic fibrosis who live in remote parts of Queensland attend specialist clinics in their local hospital twice or three times a year for routine check-ups, when the cystic fibrosis team of nurses, doctors and allied health staff from the children’s hospital in Brisbane travels to rural areas. If children become acutely ill, they might be able to be treated in the local hospital if they are not too sick, or they could be taken to the children’s hospital in Brisbane by their parents. If they are having a serious exacerbation of the illness, they will be transported there by aircraft and ambulance. Any child being sick is stressful for the family, regardless of where they live. However, if families live thousands of kilometres from the main treatment centres, scenarios described above can be common, with subsequent family disruption and emotional, social and economic costs. Telehealth is being installed in many rural and remote health services, thereby allowing country families the benefit of specialist consultation and care. However, governments and health departments are only slowly engaging with such technology. This paper presents findings of a study in Far North Queensland which examined how care was delivered to rural and remote families with children with cystic fibrosis, and how they cope. It will discuss how telehealth could improve care to such families and pose questions about why this is so slow in being implemented in Australia

Changing Bases: Multistage Optimization for Matroids and Matchings

This paper is motivated by the fact that many systems need to be maintained continually while the underlying costs change over time. The challenge is to continually maintain near-optimal solutions to the underlying optimization problems, without creating too much churn in the solution itself. We model this as a multistage combinatorial optimization problem where the input is a sequence of cost functions (one for each time step); while we can change the solution from step to step, we incur an additional cost for every such change. We study the multistage matroid maintenance problem, where we need to maintain a base of a matroid in each time step under the changing cost functions and acquisition costs for adding new elements. The online version of this problem generalizes online paging. E.g., given a graph, we need to maintain a spanning tree $T_t$ at each step: we pay $c_t(T_t)$ for the cost of the tree at time $t$, and also $| T_t\setminus T_{t-1} |$ for the number of edges changed at this step. Our main result is an $O(\log m \log r)$-approximation, where $m$ is the number of elements/edges and $r$ is the rank of the matroid. We also give an $O(\log m)$ approximation for the offline version of the problem. These bounds hold when the acquisition costs are non-uniform, in which caseboth these results are the best possible unless P=NP. We also study the perfect matching version of the problem, where we must maintain a perfect matching at each step under changing cost functions and costs for adding new elements. Surprisingly, the hardness drastically increases: for any constant $\epsilon>0$, there is no $O(n^{1-\epsilon})$-approximation to the multistage matching maintenance problem, even in the offline case