Information Outlook, May 1997

Volume 1, Issue 5https://scholarworks.sjsu.edu/sla_io_1997/1004/thumbnail.jp

Principles of Multimedia News Systems for Business Applications

In the past few years considerable demand for business oriented multimedia information systems has developed. A multimedia information system is one that can create, import, integrate, store, retrieve, edit, and delete two or more types of media materials in digital form, such as audio, image, full-motion video, and text information. Multimedia information systems play a central role in many business activities. They represent a very special class complex computing systems. This paper surveys a special type of multimedia information systems: multimedia news systems. Multimedia news systems deal with architectures to manage complex multimedia news databases, online presentation and distribution services or the integration of several existing services to meta-services using intelligent news retrieval engines. The leading presentation platform in multimedia news presentation is news networks providing television services and Internet content distribution. The primary focus is on advanced multimedia news systems infrastructure, document standards, application architecture and principles for multimedia news on the Web that suggest long-term trends in this increasingly important area.multimedia, information systems, business applications

Reviews

Judith Jeffcoate, Multimedia in Practice ‐Technology and Applications, BCS Practitioner Series, Prentice‐Hall International, 1995. ISBN: 0–13–123324–6. £24.95

Applied Research Through Partnership: the Experience of the Yorkshire and Humberside Regional Research Observatory

Paper presented at a seminar on ‘Los Observatorios Regionales de Políticas Públicas como Herramientas de Gestión de Información: Una Aproximación al Estudio del Rendimiento Autonómico, at the Centro de Estudios de Gestión, Análisis y Información, Campus de Somosaguas, La Universidad Complutense, Madrid, 23-24 November, 2000 Ten years ago, a Regional Research Observatory (ReRO) was established to provide ‘clients’ in Yorkshire and Humberside with a single point access to a region-wide data and analysis service. The Observatory’s portfolio covered activities relating to applied research and consultancy, intelligence, education and training, publications and networking. The first part of the paper explains the concept of the Observatory as it was initially conceived as a form of partnership across all the universities in the region, outlines the structure of the organization that was created, explains the arrangements for operating the Observatory as a partnership initiative, and exemplifies the outputs and achievements during the first half of the decade. In order to facilitate its regional monitoring activities, ReRO constructed a Regional Intelligence Centre (RIC), a customised geographical information system in which to store key data sets and generate a range of statistical indicators for the region as a whole or its constituent parts. The second part of the paper explains the structure of the RIC and its contents. It argues that the main advantage that derives from the construction of such a centre is the value that is added to raw information through data handling and integration, through skilled interpretation and through the provision of new information, maybe in the form of forecasts of what is likely to happen in the future, as well as analyses of what has happened in the past. The third and final part of the paper explores some of the key issues and difficulties relating to the operation of the Observatory and considers some of the reasons that have accounted for its loss of momentum in the last few years. This has occurred over a period of increased political attention to regional administration and planning in the UK, exemplified by the creation of Scottish and Welsh Assemblies and the emergence of Regional Development Agencies and Regional Assemblies across England. A retrospective evaluation demonstrates a number of lessons that have been learnt and provides a number of useful guidelines to those attempting to establish similar structures elsewhere in the developed world

Energy Efficiency Prediction using Artificial Neural Network

Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a dataset for building energy performance. The main factors for input variables are: relative compactness, roof area, overall height, surface area, glazing are a, wall area, glazing area distribution of a building, orientation, and the output variables: heating and cooling loads of the building. The dataset used for training are the data published in the literature for various 768 residential buildings. The model was trained and validated, most important factors affecting heating load and cooling load are identified, and the accuracy for the validation was 99.60%