Chemical, microbiological and sensory examinations of dried Lake Tanganyika sardine presently marketed in Zambia

Proximate composition, PH, total aerabic counts, coliform counts, appearance and taste of dried Lake Tanganyika sardine (Limnothrissa miodon and Stolothrissa tanganicae) sampled at Lusaka markets were analysed for the period July 1969 to February 1970. Water content for the dried sardine varied between 7 and l4% and oil content between 8 and 14% according to season. Flavour of the cooked sardine was scored as good to fair, which discredits the common belief that is poor in quality. Cooked fish scores correlated poorly to the oil content and bacterial counts of the dried fish.

Chemical, bacteriological and sensory examination of split, dried, smoked bream on the market in Zambia

A critical examination of the market quality of split, dried and smoked bream (Tilapia spp.) was chemically, bacteriologically and organoleptically conducted for the period of August 1968 to January 1969. The aim of this survey was to obtain basic information for the development of national quality standards for the commodity. Relationships of cooked meat score to pH, fish size, appearance and smell score, and water content wcre significantly correlated and responsive. Therefore, these parameters were proposed to be used as indices for the quality standards of the products.

Active glass-polymer superlattice structure for photonic integration.

We propose an all-laser processing approach allowing controlled growth of organic-inorganic superlattice structures of rare-earth ion doped tellurium-oxide-based glass and optically transparent polydimethyl siloxane (PDMS) polymer; the purpose of which is to illustrate the structural and thermal compatibility of chemically dissimilar materials at the nanometer scale. Superlattice films with interlayer thicknesses as low as 2 nm were grown using pulsed laser deposition (PLD) at low temperatures (100 °C). Planar waveguides were successfully patterned by femtosecond-laser micro-machining for light propagation and efficient Er(3+)-ion amplified spontaneous emission (ASE). The proposed approach to achieve polymer-glass integration will allow the fabrication of efficient and durable polymer optical amplifiers and lossless photonic devices. The all-laser processing approach, discussed further in this paper, permits the growth of films of a multitude of chemically complex and dissimilar materials for a range of optical, thermal, mechanical and biological functions, which otherwise are impossible to integrate via conventional materials processing techniques.

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.

Content Based Integration of Construction Site Images in AEC/FM Model Based Systems

The Architecture, Engineering, Construction and Facilities Management (AEC/FM) industry is rapidly becoming a multidisciplinary, multinational and multi-billion dollar economy, involving large numbers of actors working concurrently at different locations and using heterogeneous software and hardware technologies. Since the beginning of the last decade, a great deal of effort has been spent within the field of construction IT in order to integrate data and information from most computer tools used to carry out engineering projects. For this purpose, a number of integration models have been developed, like web-centric systems and construction project modeling, a useful approach in representing construction projects and integrating data from various civil engineering applications. In the modern, distributed and dynamic construction environment it is important to retrieve and exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research demonstrated that a major hurdle in AEC/FM data integration in such systems is caused by its variety of data types and that a significant part of the data is stored in semi-structured or unstructured formats. Therefore, new integrative approaches are needed to handle non-structured data types like images and text files. This research is focused on the integration of construction site images. These images are a significant part of the construction documentation with thousands stored in site photographs logs of large scale projects. However, locating and identifying such data needed for the important decision making processes is a very hard and time-consuming task, while so far, there are no automated methods for associating them with other related 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.