Population dynamics and the management of the Indian mackerel Rastrelliger kanagurta from the Bay of Bengal

FiSAT program was used to estimate population parameters of Rastrelliger kanagurta from length frequency data. Loc and K were found to be 27.4 em and 0.90 year1 respectively. The Wetherall plot provided an estimate of Loc and Z/K were 26.7 cm and 4.683 respectively. The annual rate of natural and fishing mortality were estimated as 1.71 and 3.21 respectively. The exploitation rate was 0.652. The selection pattern L50 was 18.09 cm. Recruitment pattern suggests two seasonal pulses one in March-May and another in September-October. Peak recruitment appeared in March-May. Maximum yield could be achieved by decreasing length at first capture to 13.0 em. The relationship between total length and body weight was found to be W = 0.01583 L8952. Yield and stock prediction analysis suggested that highest yield and price could be achieved by decreasing the fishing mortality to 2.0 coefficient rate.

Content Based Integration of Construction Site Images in Architecture, Engineering, Construction, and Facilities Management (AEC/FM) Model based Systems

This book explores the processes for retrieval, classification, and integration of construction images in AEC/FM model based systems. The author describes a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval that have been integrated into a novel method for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks. objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.

Briefing: Re-Engineering the City 2020-2050 - Urban Foresight and Transition Management

Cities may be responsible for up to 70% of global carbon emissions and 75% of global energy consumption and by 2050 it is estimated that 70% of the world's population could live in cities. The critical challenge for contemporary urbanism, therefore, is to understand how to develop the knowledge, capacity and capability for public agencies, the private sector and multiple users in city regions systemically to re-engineer their built environment and urban infrastructure in response to climate change and resource constraints. Re-Engineering the City 2020-2050: Urban Foresight and Transition Management (Retrofit 2050) is a major new interdisciplinary project funded under the Engineering and Physical Science Research Council's (EPSRC) Sustainable Urban Environments Programme which seeks to address this challenge. This briefing describes the background and conceptual framing of Retrofit 2050 project, its aims and objectives and research approach.

requirement analysis of information and knowledge management in postmodern perspective on curriculum

National Basic Research Program of China; Chinese Academy of Sciences; Information Society Technologies; Institute of Computing Technology, Chinese Academy of Sciences; Zhuhai National Hi-tech Industrial Development Zone

Levantamento pedológico de uma área-piloto relacionada ao Projeto BiosBrasil (Conservation and Sustainable Management of Below-Ground Biodiversity: Phase I), município de Benjamin Constant (AM): janela 6.

2005

Solos das áreas-piloto do Projeto BiosBrasil (Conservation and Sustainable Management of Below-Ground Biodiversity: Phase I), Município de Benjamin Constant, Estado do Amazonas.

2005