Application of remote sensing to marine fisheries: alternative approaches

A discussion is presented on the applications of remote sensing to fisheries. The measurement of temperature, wind stress, and ocean colour using remote sensing techniques is considered.

Bayesian and L1 Approaches to Sparse Unsupervised Learning

The use of L1 regularisation for sparse learning has generated immense research interest, with successful application in such diverse areas as signal acquisition, image coding, genomics and collaborative filtering. While existing work highlights the many advantages of L1 methods, in this paper we find that L1 regularisation often dramatically underperforms in terms of predictive performance when compared with other methods for inferring sparsity. We focus on unsupervised latent variable models, and develop L1 minimising factor models, Bayesian variants of "L1", and Bayesian models with a stronger L0-like sparsity induced through spike-and-slab distributions. These spike-and-slab Bayesian factor models encourage sparsity while accounting for uncertainty in a principled manner and avoiding unnecessary shrinkage of non-zero values. We demonstrate on a number of data sets that in practice spike-and-slab Bayesian methods outperform L1 minimisation, even on a computational budget. We thus highlight the need to re-assess the wide use of L1 methods in sparsity-reliant applications, particularly when we care about generalising to previously unseen data, and provide an alternative that, over many varying conditions, provides improved generalisation performance.

Model-based approaches to handling additive noise in reverberant environments

Model-based approaches to handle additive and convolutional noise have been extensively investigated and used. However, the application of these schemes to handling reverberant noise has received less attention. This paper examines the extension of two standard additive/convolutional noise approaches to handling reverberant noise. The first is an extension of vector Taylor series (VTS) compensation, reverberant VTS, where a mismatch function including reverberant noise is used. The second scheme modifies constrained MLLR to allow a wide-span of frames to be taken into account and projected into the required dimensionality. To allow additive noise to be handled, both these schemes are combined with standard VTS. The approaches are evaluated and compared on two tasks, MC-WSJ-AV, and a reverberant simulated version of AURORA-4. © 2011 IEEE.

New approaches to materials education for students of engineering

A novel approach to the teaching of materials to engineering students is outlined. It starts from the overview of the "world" of materials made possible by material property charts, and develops both an understanding of material properties and skills in selecting materials and processes to meet design specifications. It is supported by extensive computer-based methods and tools, and is well adapted both for elementary and for advanced courses.

Feasibility study: the methods and approaches to implementing a SEREAD teacher training programme in BOBLME countries

Objectives included a desk-top feasibility study to explore opportunities to adapt the Scientific Educational Resources and Experience Associated with the Deployment of Argo profiling floats in the South Pacific Ocean (SEREAD) to BOBLME country schools.The programme included teacher resources on climate change and facilitating interactions between scientists, students and teachers.

Approaches to the evaluation and management of the fish stock in Kainji Lake, Nigeria

Estimates of potential yield for Kainji Lake, and the methods of analysis by earlier workers are discussed. Also summarized is the state of the fishery after impoundment, between 1969 and 1971, based on experimental gillnet catches. Recent sampling of the young of the year along the littoral margin indicates that most of the commercially important species have spawned successful1y in the lake. An intense fishing mortality of juvenile fish, owing to the use of small mesh nets by local fishermen, presents a possible threat to the future establishment of the fish in the lake. The results of gill-net selection studies based on HOLT'S (1957) method are given. The data have been extracted from experimental gill-net catches with graded fleets of nets between 1969 and 1971. Recommendations based on the above studies have been made to ensure a successful establishment of the fish species in the lake and an increase in catch-per~unit effort in subsequent years.

Data fusion approaches and applications for construction engineering

Data fusion can be defined as the process of combining data or information for estimating the state of an entity. Data fusion is a multidisciplinary field that has several benefits, such as enhancing the confidence, improving reliability, and reducing ambiguity of measurements for estimating the state of entities in engineering systems. It can also enhance completeness of fused data that may be required for estimating the state of engineering systems. Data fusion has been applied to different fields, such as robotics, automation, and intelligent systems. This paper reviews some examples of recent applications of data fusion in civil engineering and presents some of the potential benefits of using data fusion in civil engineering.

Alternative approaches to slum upgrading in Kibera, Nairobi

This paper discusses the sustainability of two different approaches to upgrade water and sanitation infrastructure in Kenya’s largest informal settlement, Kibera. A background to the urbanization of poverty is outlined along with approaches to urban slums. Two case-studies of completed interventions of infrastructure upgrading have been investigated. In one case-study, the upgrading method driven by an NGO uses an integrated livelihoods and partnership technique at community level to create an individual project. in the other case-study, the method is a collaboration between the government and a multi-lateral agency to deliver upgraded services as a part of a country-wide programme. The ‘bottom-up’ (project) and ‘top-down’ (programme) approaches each seek sustainability and aim to achieve this in the same context using different techniques. This paper investigates the sustainability of each approach. The merits and challenges of the approaches are discussed with the projected future of Kibera. The paper highlights the valuable opportunity for the role of appropriate engineering infrastructure for sustainable urban development, as well as the alleviation of poverty in a developing context.

Convex approaches to model wavelet sparsity patterns

Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees (HMTs). However, in linear inverse problems such as deconvolution, tomography, and compressed sensing, the presence of a sensing or observation matrix produces a linear mixing of the simple Markovian dependency structure. This leads to reconstruction problems that are non-convex optimizations. Past work has dealt with this issue by resorting to greedy or suboptimal iterative reconstruction methods. In this paper, we propose new modeling approaches based on group-sparsity penalties that leads to convex optimizations that can be solved exactly and efficiently. We show that the methods we develop perform significantly better in de-convolution and compressed sensing applications, while being as computationally efficient as standard coefficient-wise approaches such as lasso. © 2011 IEEE.