Meeting on BOBLME engagement in the International Indian Ocean Expedition 50th anniversary initiative (IIOE-2), Bangkok, Thailand, 17-18 March, 2015

Objectives included; a contribution to understanding large-scale processes affecting the Bay of Bengal Large Marine Ecosystem Project (BOBLME) and it's living resources; and to align with International Indian Ocean Expedition (IIOE-2) (2015-2020) which will extensively explore and study the Indian Ocean to improve understanding of the ocean and coupled climate processes.

Report on science communication training and Wayamba International Conference (WINC) on Sustainable Development through Equitable Sharing

This report presents presentations from representatives of 12 countries, key outcomes and recommendations for the future.

International Workshop on Fluid-Structure Interaction. Theory, Numerics and Applications

... Fluid-Structure Interaction Simulation of Viscoplastic and Fracturing Thin- Shells Subjected to Underwater Shock Loading Ralf Deiterding, Fehmi Cirak, ...

Perspectives of impacts of international fish trade in Kenya

There has been tremendous growth in international trade on fish and fisheries products in the last four decades. In 1970 the value of internationally traded fish was estimated at 3 billion; this increased to US$ 15 billion in 1980, US$ 36 billion in 1990 and US$ 55 billion in 2000 (Ahmed, 2003). Recent statistics show that fish trade has surpassed other agricultural commodities that have traditionally been traded internationally such as coffee, tea, cocoa, sugar, cereals, meat, oils and milk. In 2000, fish contributed 22% of the value of all agricultural exports, making it the highest internationally traded food product (Ahmed, 2003). In another perspective, nearly 40% of the world's fish is now sold in the international market. The flow of fish in the international market is highly lopsided. About 50% of fish exportscomefromthedevelopingworld ,ofwhich 20%arefrom low-incomefood deficient countries. Most of this fish, however, is consumed by the developed countries, which account for nearly 80% of all imported fish. The EU, USA and Japan are the major importers, accounting for over 77% of global fish imports. Thus, while developing countries playa big role in fish production , they consume very little of it, instead preferring to sell for the hard currency. In some fish exporting countries, especially those in Asia, there is some link between fish exports and imports of substitute and complementary foods. Much of the increased earning from fish exports in those countries is explained by a corresponding rise in expenditure on imported foods. This is not the case in many of the fish exporter nations in Africa. In their case, fish exports generate foreign exchange that they use to meet other socio-political objectives; hardly is it aimed at solving the wider food needs. Therefore, one of the most immediate concerns of international fish trade is its impact on food security in the poor exporter nations.

Shape Recognition of Linear Construction Entities from Construction Site Images

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. This capability is a product of the technological breakthroughs in the area of Image Processing that has allowed for the development of a large number of digital imaging applications in all industries. In this paper, an automated and content based shape recognition model is presented. This model was devised to enhance the recognition capabilities of our existing material based image retrieval model. The shape recognition model is based on clustering techniques, and specifically those related with material and object segmentation. The model detects the borders of each previously detected material depicted in the image, examines its linearity (length/width ratio) and detects its orientation (horizontal/vertical). The results emonstrate the suitability of this model for construction site image retrieval purposes and reveal the capability of existing clustering technologies to accurately identify the shape of a wealth of materials from construction site images.