Resources and Tools:A Step-by-Step Methodological Guide for Costing HIV/AIDS Activities

Many developing countries have recognized the need for comprehensive national reforms and comprehensive prevention, treatment, and care and support initiatives to reduce future transmission of and to meet the growing demand for HIV/AIDS services. As a part of these national health reform initiatives, governments are exploring ways to allocate resources in the most efficient and effective way to mitigate the HIV/AIDS epidemic. However, many countries lack information on the level and nature of the costs of HIV/AIDS programs. This document provides an introduction to the procedure for calculating and analyzing the costs of HIV/AIDS programs and describes how to measure directly the actual costs of a program that is up and running. The step-by-step guide is intended to provide project managers in the field with a framework for how to do measure costs for a single, recent year in the life of an HIV/AIDS program. An illustrative activities list in the report annex will assist the user to develop an activities-based framework. The information gleaned from the costing framework will enable policymakers and program managers to make informed resource allocation decisions

Learning to Look Around: Intelligently Exploring Unseen Environments for Unknown Tasks

It is common to implicitly assume access to intelligently captured inputs (e.g., photos from a human photographer), yet autonomously capturing good observations is itself a major challenge. We address the problem of learning to look around: if a visual agent has the ability to voluntarily acquire new views to observe its environment, how can it learn efficient exploratory behaviors to acquire informative observations? We propose a reinforcement learning solution, where the agent is rewarded for actions that reduce its uncertainty about the unobserved portions of its environment. Based on this principle, we develop a recurrent neural network-based approach to perform active completion of panoramic natural scenes and 3D object shapes. Crucially, the learned policies are not tied to any recognition task nor to the particular semantic content seen during training. As a result, 1) the learned "look around" behavior is relevant even for new tasks in unseen environments, and 2) training data acquisition involves no manual labeling. Through tests in diverse settings, we demonstrate that our approach learns useful generic policies that transfer to new unseen tasks and environments. Completion episodes are shown at https://goo.gl/BgWX3W

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Machine Learning for Microcontroller-Class Hardware -- A Review

The advancements in machine learning opened a new opportunity to bring intelligence to the low-end Internet-of-Things nodes such as microcontrollers. Conventional machine learning deployment has high memory and compute footprint hindering their direct deployment on ultra resource-constrained microcontrollers. This paper highlights the unique requirements of enabling onboard machine learning for microcontroller class devices. Researchers use a specialized model development workflow for resource-limited applications to ensure the compute and latency budget is within the device limits while still maintaining the desired performance. We characterize a closed-loop widely applicable workflow of machine learning model development for microcontroller class devices and show that several classes of applications adopt a specific instance of it. We present both qualitative and numerical insights into different stages of model development by showcasing several use cases. Finally, we identify the open research challenges and unsolved questions demanding careful considerations moving forward.Comment: Accepted for publication at IEEE Sensors Journa

Report of the 6th Tanzania Joint Annual Health Sector Review

\ud The 6th Annual Joint Health Sector Review was concluded successfully at Kunduchi Beach hotel, between 4th and 6th April 2005. It was preceded by a Technical preparatory meeting, held at Belinda Hotel. This year’s was the largest Review yet, with over 200 participants. As well as government and donor representatives, the meeting was attended by a variety of civil society and NGO representatives. The Honourable Minister of Health opened the meeting. Judged by the milestones, performance over the last year has been mixed. The advent of the Joint\ud Rehabilitation Fund, the successful integration of Health into MKUKUTA, the scaling up of AIDS Care and Treatment and a steep budget increase (FY2004/5) were all registered as achievements. However, little if any progress was achieved in tackling the Human Resources crisis. The meeting resolved to address the issue with renewed commitment and urgency. A good deal of quantitative data was presented at the meeting, including the State of Health report, the updated health sector performance profile, and the ten-district study. In most respects these reports point to improvement in health service delivery between 2000 and 2003. The major areas of concern were maternal health services and child malnutrition – neither of which seem to have made any improvement over the last 2 decades. Weaknesses in the routine information system mean that data for 2004 is still patchy. Public Private Partnership was the theme of the technical review this year. The clearest message emerging in plenary was the need to replace the current government subsidy to faith-based providers by a service agreement, linked to outputs. Another resonating theme was the need to expand the opportunity for NGOs (including FBOs) to participate in health planning and management at district level. More generally, there was a commitment by both public and private stakeholders to deepen their collaboration. The recommendations of the Technical Review extended well beyond these themes. A good start has been made with the rehabilitation of district health infrastructure. This is expected to accelerate in the year ahead. Participants called for a holistic approach towards prioritisation and effective monitoring of implementation. The Honourable Minister called for a new approach and renewed urgency in tackling the human resources crisis. The challenges and the priorities are clear enough. But the shared commitment of MOF, PO-PSM, PORALG and MOH will be needed in order to move forward. A cabinet paper was seen as one way to secure this joint commitment. The financing situation for Health has improved markedly. The PER demonstrates a 33% nominal rise in health budget between 2003/4 and this budget year. FY2005/6 will witness a further steep increase. This good news is tempered by the fact that payroll expenditure is not keeping up with “other charges”, and central government expenditure is expanding much faster than local government. Even these increases are not sufficient to cover the requirements of the health sector. A T. Shilling 167 billion resource gap was documented by the MOH. New financial commitments continue to come on stream, often initiated by short-term donor funding. Moreover, a substantial portion of new money coming into the sector is tightly earmarked. Flexible, discretionary resources remain highly constrained and tough choices on resource allocation will have to be made. Detailed discussion of health financing in general, and user charges / CHF in particular, was deferred to the Health Financing Workshop due in early May. A new set of Milestones, some of them carried over from last year, was debated and concluded after the meeting. These are reproduced in Table 7.\u