Deep Learning for Mobile Mental Health: Challenges and recent advances

Mental health plays a key role in everyone’s day-to-day lives, impacting our thoughts, behaviours, and emotions. Also, over the past years, given its ubiquitous and affordable characteristics, the use of smartphones and wearable devices has grown rapidly and provided support within all aspects of mental health research and care, spanning from screening and diagnosis to treatment and monitoring, and attained significant progress to improve remote mental health interventions. While there are still many challenges to be tackled in this emerging cross-discipline research field, such as data scarcity, lack of personalisation, and privacy concerns, it is of primary importance that innovative signal processing and deep learning techniques are exploited. Particularly, recent advances in deep learning can help provide the key enabling technology for the development of the next-generation user-centric mobile mental health applications. In this article, we first brief basic principles associated with mobile device-based mental health analysis, review the main system components, and highlight conventional technologies involved. Next, we describe several major challenges and various deep learning technologies that have potentials for a strong contribution in dealing with these challenges, respectively. Finally, we discuss other remaining problems which need to be addressed via research collaboration across multiple disciplines.This paper has been partially funded by the Bavarian Ministry of Science and Arts as part of the Bavarian Research Association ForDigitHealth, the National Natural Science Foundation of China (Grant No. 62071330, 61702370), and the Key Program of the National Natural Science Foundation of China (Grant No: 61831022)

Networks, complexity and internet regulation: scale-free law

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Adaptive Management in SDC: Challenges and Opportunities

Adaptive management (AM) is a programme management approach that helps international development organisations to become more learning-oriented and more effective in addressing complex development challenges. AM practices have been applied for decades within other sectors as varied as logistics, manufacturing, product design, military strategy, software development and lean enterprise. At its core, AM is not much more than common sense, as it essentially recognises that the solutions to complex and dynamic problems cannot be identified at the outset of a programme but need to emerge throughout the process of implementation as a result of systematic and intentional monitoring and learning. The generic AM process typically involves an iterative cycle of design, implementation, reflection and adaptation activities, supported both by system monitoring and stakeholder involvement to obtain a better understanding of the evolving system and improve how the intervention is managed. A favourable context for AM in development. During recent decades, the international development sector has aimed to increase its results and impact orientation. As a result, a growing number of development organisations and governments have become increasingly aware of the limitations of traditional ‘linear and prescriptive’ programming approaches. They are now recognising the need to handle complexity better, and have begun to adapt their policies and practices to facilitate adaptive approaches. The World Bank, for example, now acknowledges that aid agencies need to increase flexibility of implementation, tolerate greater risk and ambiguity, devolve power from aid providers to aid partners, and avoid simplistic linear schemes for measuring results. Multilateral and bilateral organisations such as the World Bank, the United Kingdom’s (UK) Department for International Development (DFID) and the United States Agency for International Development (USAID) are currently experimenting with adaptive approaches. A multitude of adaptive approaches and communities of practice have emerged that aim to improve the effectiveness of aid, including Collaborating, Learning, and Adapting, Thinking and Working Politically, Doing Development Differently, Market Systems Development, Conflict-Sensitive Programme Management, and Science of Delivery. Since generic AM approaches have existed for decades in other sectors, AM has the potential to act as a neutral ‘bridge language’ that facilitates exchange and learning among the different communities and donors. This report is the result of a learning partnership between the Swiss Agency for Development and Cooperation (SDC) and the Institute of Development Studies (IDS). It assesses the relevance of AM to SDC, how it relates to working practices across SDC, and the key challenges and opportunities for SDC. Its process of elaboration involved a literature review on AM, an exploration of AM approaches from several bilateral donors, a series of 6 interviews with SDC staff and partners working in different countries and thematic domains, and a learning workshop at SDC headquarters (HQ), where staff from several SDC divisions reflected on AM and on how to advance the organisation’s capacity for adaptive programming and learning

A Strategic Digital Transformation for the Water Industry

This book is a compilation of the knowledge shared and generated so far in the IWA Digital Water Programme. It is an insightful collection of white papers covering best practices, linking academic and industrial studies/insights with applications to give real-world examples of digital transformation. These White Papers are designed to help utilities, water professionals and all those interested in water management and stewardship issues to better understand the opportunities of digital technologies. This book covers a plethora of topics including: Instrumentation and data generation Artificial intelligence and digital twins The digital transformation and public health Mapping the digital transformation journey into the future With these topics, the aim is to present an all-encompassing reference for practitioners to use in their day-to-day activities. Through the Digital Water Programme, the IWA leverages its worldwide member expertise to guide a new generation of water and wastewater utilities on their digital journey towards the uptake of digital technologies and their integration into water services

Incentive-driven QoS in peer-to-peer overlays

A well known problem in peer-to-peer overlays is that no single entity has control over the software, hardware and configuration of peers. Thus, each peer can selfishly adapt its behaviour to maximise its benefit from the overlay. This thesis is concerned with the modelling and design of incentive mechanisms for QoS-overlays: resource allocation protocols that provide strategic peers with participation incentives, while at the same time optimising the performance of the peer-to-peer distribution overlay. The contributions of this thesis are as follows. First, we present PledgeRoute, a novel contribution accounting system that can be used, along with a set of reciprocity policies, as an incentive mechanism to encourage peers to contribute resources even when users are not actively consuming overlay services. This mechanism uses a decentralised credit network, is resilient to sybil attacks, and allows peers to achieve time and space deferred contribution reciprocity. Then, we present a novel, QoS-aware resource allocation model based on Vickrey auctions that uses PledgeRoute as a substrate. It acts as an incentive mechanism by providing efficient overlay construction, while at the same time allocating increasing service quality to those peers that contribute more to the network. The model is then applied to lagsensitive chunk swarming, and some of its properties are explored for different peer delay distributions. When considering QoS overlays deployed over the best-effort Internet, the quality received by a client cannot be adjudicated completely to either its serving peer or the intervening network between them. By drawing parallels between this situation and well-known hidden action situations in microeconomics, we propose a novel scheme to ensure adherence to advertised QoS levels. We then apply it to delay-sensitive chunk distribution overlays and present the optimal contract payments required, along with a method for QoS contract enforcement through reciprocative strategies. We also present a probabilistic model for application-layer delay as a function of the prevailing network conditions. Finally, we address the incentives of managed overlays, and the prediction of their behaviour. We propose two novel models of multihoming managed overlay incentives in which overlays can freely allocate their traffic flows between different ISPs. One is obtained by optimising an overlay utility function with desired properties, while the other is designed for data-driven least-squares fitting of the cross elasticity of demand. This last model is then used to solve for ISP profit maximisation

A Strategic Digital Transformation for the Water Industry

This book is a compilation of the knowledge shared and generated so far in the IWA Digital Water Programme. It is an insightful collection of white papers covering best practices, linking academic and industrial studies/insights with applications to give real-world examples of digital transformation. These White Papers are designed to help utilities, water professionals and all those interested in water management and stewardship issues to better understand the opportunities of digital technologies. This book covers a plethora of topics including: Instrumentation and data generation Artificial intelligence and digital twins The digital transformation and public health Mapping the digital transformation journey into the future With these topics, the aim is to present an all-encompassing reference for practitioners to use in their day-to-day activities. Through the Digital Water Programme, the IWA leverages its worldwide member expertise to guide a new generation of water and wastewater utilities on their digital journey towards the uptake of digital technologies and their integration into water services

Networks, complexity and internet regulation scale-free law

This book, then, starts with a general statement: that regulators should try, wherever possible, to use the physical methodological tools presently available in order to draft better legislation. While such an assertion may be applied to the law in general, this work will concentrate on the much narrower area of Internet regulation and the science of complex networks The Internet is the subject of this book not only because it is my main area of research, but also because –without over-emphasising the importance of the Internet to everyday life– one cannot deny that the growth and popularisation of the global communications network has had a tremendous impact on the way in which we interact with one another. The Internet is, however, just one of many interactive networks. One way of looking at the complex and chaotic nature of society is to see it as a collection of different nodes of interaction. Humans are constantly surrounded by networks: the social network, the financial network, the transport network, the telecommunications network and even the network of our own bodies. Understanding how these systems operate and interact with one another has been the realm of physicists, economists, biologists and mathematicians. Until recently, the study of networks has been mainly theoretical and academic, because it is difficult to gather data about large and complex systems that is sufficiently reliable to support proper empirical application. In recent years, though, the Internet has given researchers the opportunity to study and test the mathematical descriptions of these vast complex systems. The growth rate and structure of cyberspace has allowed researchers to map and test several previously unproven theories about how links and hubs within networks interact with one another. The Web now provides the means with which to test the organisational structures, architecture and growth of networks, and even permits some limited prediction about their behaviour, strengths and vulnerabilities. The main objective of this book is first and foremost to serve as an introduction to the wider legal audience to some of the theories of complexity and networks. The second objective is more ambitious. By looking at the application of complexity theory and network science in various areas of Internet regulation, it is hoped that there will be enough evidence to postulate a theory of Internet regulation based on network science. To achieve these two goals, Chapter 2 will look in detail at the science of complex networks to set the stage for the legal and regulatory arguments to follow. With the increase in reliability of the descriptive (and sometimes predictive) nature of network science, a logical next step for legal scholars is to look at the legal implications of the characteristics of networks. Chapter 3 highlights the efforts of academics and practitioners who have started to find potential uses for network science tools. Chapter 4 takes this idea further, and explores how network theory can shape Internet regulation. The following chapters will analyse the potential for application of the tools described in the previous chapters, applying complexity theory to specific areas of study related to Internet Law. Chapter 5 deals with the subject of copyright in the digital world. Chapter 6 explores the issue of peer-production and user-generated content using network science as an analytical framework. Chapter 7 finishes the evidence section of the work by studying the impact of network architecture in the field of cybercrime, and asks whether the existing architecture hinders or assists efforts to tackle those problems. It is clear that these are very disparate areas of study. It is not the intention of this book to be overreaching in its scope, although I am mindful that it covers a lot of ground and attempts to study and describe some disciplines that fall outside of my intellectual comfort zone. While the focus of the work is the Internet, its applications may extend beyond mere electronic bits. Without trying to be over-ambitious, it is my strong belief that legal scholarship has been neglectful in that it has been slow to respond to the wealth of research into complexity. That is not to say that there has been no legal research on the topic, but it would seem that lawyers, legislators and policy-makers are reluctant to consider technical solutions to legal problems. It is hoped then that this work will serve as a stepping stone that will lead to new interest in some of the theories that I describe

A biography of open source software: community participation and individuation of open source code in the context of microfinance NGOs in North Africa and the Middle East

For many, microfinance is about building inclusive financial systems to help the poor gain direct access to financial services. Hundreds of grassroots have specialised in the provision of microfinance services worldwide. Most of them are adhoc organisations, which suffer severe organisational and informational deficiencies. Over the past decades, policy makers and consortia of microfinance experts have attempted to improve their capacity building through ICTs. In particular, there is strong emphasis on open source software (OSS) initiatives, as it is commonly believed that MFIs are uniquely positioned to benefit from the advantages of openness and free access. Furthermore, OSS approaches have recently become extremely popular. The OSS gurus are convinced there is a business case for a purely open source approach, especially across international development spheres. Nonetheless, getting people to agree on what is meant by OSS remains hard to achieve. On the one hand scholarly software research shows a lack of consensus and documents stories in which the OSS meaning is negotiated locally. On the other, the growing literature on ICT-for-international development does not provide answers as research, especially in the microfinance context, presents little empirical scrutiny. This thesis therefore critically explores the OSS in the microfinance context in order to understand itslong-term development and what might be some of the implications for MFIs. Theoretically I draw on the 3rd wave of research within the field of Science and Technology Studies –studies of Expertise and Experience (SEE). I couple the software ‘biography’ approach (Pollock and Williams 2009) with concepts from Simondon’s thesis on the individuation of technical beings (1958) as an integrated framework. I also design a single case study, which is supported by an extensive and longitudinal collection of data and a three-stage approach, including the analysis of sociograms, and email content. This case provides a rich empirical setting that challenges the current understanding of the ontology of software and goes beyond the instrumental views of design, building a comprehensive framework for community participation and software sustainability in the context of the microfinance global industry

Distributed D3: A web-based distributed data visualisation framework for Big Data

The influx of Big Data has created an ever-growing need for analytic tools targeting towards the acquisition of insights and knowledge from large datasets. Visual perception as a fundamental tool used by humans to retrieve information from the outside world around us has its unique ability to distinguish patterns pre-attentively. Visual analytics via data visualisations is therefore a very powerful tool and has become ever more important in this era. Data-Driven Documents (D3.js) is a versatile and popular web-based data visualisation library that has tended to be the standard toolkit for visualising data in recent years. However, the library is technically inherent and limited in capability by the single thread model of a single browser window in a single machine, and therefore not able to deal with large datasets. The main objective of this thesis is to overcome this limitation and address possible challenges by developing the Distributed D3 framework that employs distributed mechanism to enable the possibility of delivering web-based visualisations for large-scale data, which also allows to effectively utilise the graphical computational resources of the modern visualisation environments. As a result, the first contribution is that the integrated version of Distributed D3 framework has been developed for the Data Observatory. The work proves the concept of Distributed D3 is feasible in reality and also enables developers to collaborate on large-scale data visualisations by using it on the Data Observatory. The second contribution is that the Distributed D3 has been optimised by investigating the potential bottlenecks for large-scale data visualisation applications. The work finds the key performance bottlenecks of the framework and shows an improvement of the overall performance by 35.7% after optimisations, which improves the scalability and usability of Distributed D3 for large-scale data visualisation applications. The third contribution is that the generic version of Distributed D3 framework has been developed for the customised environments. The work improves the usability and flexibility of the framework and makes it ready to be published in the open-source community for further improvements and usages.Open Acces