Real-time image classification for adaptive mission planning using an Autonomous Underwater Vehicle

Real-time image analysis and classification onboard robotic marine vehicles, such as AUVs, is a key step in the realisation of adaptive mission planning for large-scale habitat mapping in previously unexplored environments. This paper describes a novel technique to train, process, and classify images collected onboard an AUV used in relatively shallow waters with poor visibility and non-uniform lighting. The approach utilises Förstner feature detectors and Laws texture energy masks for image characterisation, and a bag of words approach for feature recognition. To improve classification performance we propose a usefulness gain to learn the importance of each histogram component for each class. Experimental results illustrate the performance of the system in characterisation of a variety of marine habitats and its ability to operate onboard an AUV's main processor suitable for real-time mission planning.

Mission path planning of aerial survey tasks using hybrid game evolutionary algorithm

The work presented in this report is aimed to implement a cost-effective offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. Understandably, the objectives of a practical optimisation problem are conflicting each other and the minimisation of one of them necessarily implies the impossibility to minimise the other ones. This leads to the need to find a set of optimal solutions for the problem; once such a set of available options is produced, the mission planning problem is reduced to a decision making problem for the mission specialists, who will choose the solution which best fit the requirements of the mission. The goal of this work is then to develop a Multi-Objective optimisation tool able to provide the mission specialists a set of optimal solutions for the inspection task amongst which the final trajectory will be chosen, given the environment data, the mission requirements and the definition of the objectives to minimise. All the possible optimal solutions of a Multi-Objective optimisation problem are said to form the Pareto-optimal front of the problem. For any of the Pareto-optimal solutions, it is impossible to improve one objective without worsening at least another one. Amongst a set of Pareto-optimal solutions, no solution is absolutely better than another and the final choice must be a trade-off of the objectives of the problem. Multi-Objective Evolutionary Algorithms (MOEAs) are recognised to be a convenient method for exploring the Pareto-optimal front of Multi-Objective optimization problems. Their efficiency is due to their parallelism architecture which allows to find several optimal solutions at each time

What Costs Accountability? Financial Accountability, Mission and Fundraising in Nonprofits

Although greater calls for accountability have been articulated by academics, policy makers and donors in the recent years, a stream of thought has been questioning where the giving of an account should stop. In conveying the limits to the giving of an account (Messner, 2009) and associated transparency (Roberts, 2009), critical accounting scholars have also pointed to as yet unresolved contradictions intrinsic to accountability (McKernan, 2012), especially when it comes to be operationalised (Joannides, 2012). The impact of accountability's discharging on nonprofits' strategy or operations has to date been underexplored (Dhanni & Connelly, 2012; Tucker & Parker, 2013). Accordingly, this chapter seeks to contribute to this body of literature on the consequences of accountability on fundraising strategies in nonprofits, questioning whether accountability practice may hamper the effectiveness of the nonprofit sector by restraining the fundraising profession. Our chapter seeks to fill a dual theoretical gap. Firstly, only a number of publications have investigated the interplay between accountability and the making of organisational strategy (Parker, 2002, 2003b, 2011, 2012, 2013; Tucker & Parker, 2013). Therefore, we seek to fill a theoretical gap as to the impact of accountability on the conduct of straegic operations. By questioning whether accountability hampers fundraising strategy in non-profits we are also contributing to the literature balancing accountability and the mission. In this literature, it appears that money and the mission are often conflictual, financial managers being often seen by mission advocates as guardians shielding organisational resources (Chiapello, 1993, 1998; Lightbody, 2000, 2003). Another approach shows that making nonprofits accountable to capital and multiple stakeholders (donors, public authorities) leaders to changes in organisational culture (O'Dwyer & Unerman, 2007; Unerman & Bennett, 2004; Underman & O'Dwyer, 2006a, 2006b, 2008). By examining a small number of cases we show how accountability practices result in fundraising adapting and adjusting under such external pressures and constraints. We also show accountability systems may have a direct impact on the conduct of strategic operations, which might hamper mission conduct.

Deep geothermal: The ‘Moon Landing’ mission in the unconventional energy and minerals space

Deep geothermal from the hot crystalline basement has remained an unsolved frontier for the geothermal industry for the past 30 years. This poses the challenge for developing a new unconventional geomechanics approach to stimulate such reservoirs. While a number of new unconventional brittle techniques are still available to improve stimulation on short time scales, the astonishing richness of failure modes of longer time scales in hot rocks has so far been overlooked. These failure modes represent a series of microscopic processes: brittle microfracturing prevails at low temperatures and fairly high deviatoric stresses, while upon increasing temperature and decreasing applied stress or longer time scales, the failure modes switch to transgranular and intergranular creep fractures. Accordingly, fluids play an active role and create their own pathways through facilitating shear localization by a process of time-dependent dissolution and precipitation creep, rather than being a passive constituent by simply following brittle fractures that are generated inside a shear zone caused by other localization mechanisms. We lay out a new theoretical approach for the design of new strategies to utilize, enhance and maintain the natural permeability in the deeper and hotter domain of geothermal reservoirs. The advantage of the approach is that, rather than engineering an entirely new EGS reservoir, we acknowledge a suite of creep-assisted geological processes that are driven by the current tectonic stress field. Such processes are particularly supported by higher temperatures potentially allowing in the future to target commercially viable combinations of temperatures and flow rates.

Phased-Mission Analysis for Evaluating the Effectiveness of Aerospace Computing-Systems

Effectiveness evaluation of aerospace fault-tolerant computing systems used in a phased-mission environment is rather tricky and difficult because of the interaction of its several degraded performance levels with the multiple objectives of the mission and the use environment. Part I uses an approach based on multiobjective phased-mission analysis to evaluate the effectiveness of a distributed avionics architecture used in a transport aircraft. Part II views the computing system as a multistate s-coherent structure. Lower bounds on the probabilities of accomplishing various levels of performance are evaluated.

Displaying and celebrating the "other": A study of the mission, scope, and roles of ethnic museums in Los Angeles

In the last thirty years, ethnic museums have mushroomed in American cities. Although this is certainly a national phenomenon, it has been particularly evident in Los Angeles. In this paper we examine the genesis and evolution of these emerging institutions. We survey the mission, scope, and role of ethnic museums in Los Angeles, and we contrast them with the stated mission and scope of “mainstream” museums in the city. We further present case studies of three Los Angeles ethnic museums. The museums vary considerably in the ways they perceive their role in the community, the city, and the nation and in the preservation and display of ethnic culture. At their best, ethnic museums serve to make new art and histories more accessible and visible and provide a forum in which to debate contemporary issues of politics and identity. The paper highlights some of the tensions faced by ethnic museums as they seek to define their audience and role(s) in multi-ethnic, twenty-first century Los Angeles.

Sustainability and Mission Drift in Microfinance

Microfinance institutions (MFIs) are constrained by double bottom-lines: meeting social obligations (the first bottom-line) and obtaining financial self-sufficiency (the second bottom-line). The proponents of the first bottom-line, however, are increasingly concerned that there is a trade-off between these two bottom-lines—i.e., getting hold of financial self-sufficiency may lead MFIs to drift away from their original social mission of serving the very poor, commonly known as mission drift in microfinance which is still a controversial issue. This study aims at addressing the concerns for mission drift in microfinance in a performance analysis framework. Chapter 1 deals with theoretical background, motivation and objectives of the topic. Then the study explores the validity of three major and related present-day concerns. Chapter 2 explores the impact of profitability on outreach-quality in MFIs, commonly known as mission drift, using a unique panel database that contains 4-9 years’ observations from 253 MFIs in 69 countries. Chapter 3 introduces factor analysis, a multivariate tool, in the process of analysing mission drift in microfinance and the exercise in this chapter demonstrates how the statistical tool of factor analysis can be utilised to examine this conjecture. In order to explore why some microfinance institutions (MFIs) perform better than others, Chapter 4 looks at factors which have an impact on several performance indicators of MFIs—profitability or sustainability, repayment status and cost indicators—based on quality-data on 353 institutions in 77 countries. The study also demonstrates whether such mission drift can be avoided while having self-sustainability. In Chapter 5 we examine the impact of capital and financing structure on the performance of microfinance institutions where estimations with instruments have been performed using a panel dataset of 782 MFIs in 92 countries for the period 2000-2007. Finally, Chapter 6 concludes the study by summarising the results from the previous chapters and suggesting some directions for future studies.

Greening India Mission

The Government of India has announced the Greening India Mission (GIM) under the National Climate Change Action Plan. The Mission aims to restore and afforest about 10 mha over the period 2010-2020 under different sub-missions covering moderately dense and open forests, scrub/grasslands, mangroves, wetlands, croplands and urban areas. Even though the main focus of the Mission is to address mitigation and adaptation aspects in the context of climate change, the adaptation component is inadequately addressed. There is a need for increased scientific input in the preparation of the Mission. The mitigation potential is estimated by simply multiplying global default biomass growth rate values and area. It is incomplete as it does not include all the carbon pools, phasing, differing growth rates, etc. The mitigation potential estimated using the Comprehensive Mitigation Analysis Process model for the GIM for the year 2020 has the potential to offset 6.4% of the projected national greenhouse gas emissions, compared to the GIM estimate of only 1.5%, excluding any emissions due to harvesting or disturbances. The selection of potential locations for different interventions and species choice under the GIM must be based on the use of modelling, remote sensing and field studies. The forest sector provides an opportunity to promote mitigation and adaptation synergy, which is not adequately addressed in the GIM. Since many of the interventions proposed are innovative and limited scientific knowledge exists, there is need for an unprecedented level of collaboration between the research institutions and the implementing agencies such as the Forest Departments, which is currently non-existent. The GIM could propel systematic research into forestry and climate change issues and thereby provide global leadership in this new and emerging science.

Multiple UAV Coalitions for a Search and Prosecute Mission

Unmanned aerial vehicles (UAVs) have the potential to carry resources in support of search and prosecute operations. Often to completely prosecute a target, UAVs may have to simultaneously attack the target with various resources with different capacities. However, the UAVs are capable of carrying only limited resources in small quantities, hence, a group of UAVs (coalition) needs to be assigned that satisfies the target resource requirement. The assigned coalition must be such that it minimizes the target prosecution delay and the size of the coalition. The problem of forming coalitions is computationally intensive due to the combinatorial nature of the problem, but for real-time applications computationally cheap solutions are required. In this paper, we propose decentralized sub-optimal (polynomial time) and decentralized optimal coalition formation algorithms that generate coalitions for a single target with low computational complexity. We compare the performance of the proposed algorithms to that of a global optimal solution for which we need to solve a centralized combinatorial optimization problem. This problem is computationally intensive because the solution has to (a) provide a coalition for each target, (b) design a sequence in which targets need to be prosecuted, and (c) take into account reduction of UAV resources with usage. To solve this problem we use the Particle Swarm Optimization (PSO) technique. Through simulations, we study the performance of the proposed algorithms in terms of mission performance, complexity of the algorithms and the time taken to form the coalition. The simulation results show that the solution provided by the proposed algorithms is close to the global optimal solution and requires far less computational resources.