Toward a framework for data quality in cloud-based health information system

This Cloud computing is a promising platform for health information systems in order to reduce costs and improve accessibility. Cloud computing represents a shift away from computing being purchased as a product to be a service delivered over the Internet to customers. Cloud computing paradigm is becoming one of the popular IT infrastructures for facilitating Electronic Health Record (EHR) integration and sharing. EHR is defined as a repository of patient data in digital form. This record is stored and exchanged securely and accessible by different levels of authorized users. Its key purpose is to support the continuity of care, and allow the exchange and integration of medical information for a patient. However, this would not be achieved without ensuring the quality of data populated in the healthcare clouds as the data quality can have a great impact on the overall effectiveness of any system. The assurance of the quality of data used in healthcare systems is a pressing need to help the continuity and quality of care. Identification of data quality dimensions in healthcare clouds is a challenging issue as data quality of cloud-based health information systems arise some issues such as the appropriateness of use, and provenance. Some research proposed frameworks of the data quality dimensions without taking into consideration the nature of cloud-based healthcare systems. In this paper, we proposed an initial framework that fits the data quality attributes. This framework reflects the main elements of the cloud-based healthcare systems and the functionality of EHR

Information technology and urban green analysis

It is well recognized that green area plays a pivotal role in improving urban environment, such as preserving water and soil, controlling temperature and humidity of air, preventing pollution, flood prevention, functioning as buffers between incompatible land uses, preserving natural habitat, and providing space for recreation and relaxation. However, due to pressures from new development both in urban fringes and urban centres, urban green and open spaces are seen to be rapidly declining in term of allocated spaces and quality. Without careful urban land use planning, many open spaces will be filled with residential and commercial buildings. Therefore, there is a need for proper planning control to ensure that the provisions of green spaces are adequately being conserved for current and future generations. The need for an urban green information system is particularly important for strategic planning at macro level and local planning at the micro level. The advent of information technology has created an opportunity for the development of new approaches in preserving and monitoring the development of urban green and open spaces. This paper will discuss the use of Geographical Information Systems (GIS) incorporated with other data sources such as remote sensing images and aerial photographs in providing innovative and alternative solutions in the management and monitoring of urban green. GIS is widely accepted in urban landscape planning as it can provide better understanding on the spatial pattern and changes of land use in an area. This paper will primarily focus on digital database that are developed to assist in monitoring urban green and open spaces at regional and local context. The application of GIS in the Klang Valley region or better known as AGISwlk developed since mid-1990's is currently being used by various organisations in the region. The focus of AGISwlk is not merely in providing relevant database to its stakeholders but more importantly, assist in making specific and relevant decisions with regard to spatial planning. It is also used to monitor the loss of green areas by using several temporal data sets. The method of classifying green and open spaces in the region is also being discussed. This paper demonstrates that GIS can be an effective tool in preserving and monitoring green and open spaces in an urban area. The contribution of urban green digital database in someway may leads toward landscape sustainability as to satisfy the ever changing society

Optimal land cover mapping and change analysis in northeastern oregon using landsat imagery.

Abstract The necessity for the development of repeatable, efficient, and accurate monitoring of land cover change is paramount to successful management of our planet’s natural resources. This study evaluated a number of remote sensing methods for classifying land cover and land cover change throughout a two-county area in northeastern Oregon (1986 to 2011). In the past three decades, this region has seen significant changes in forest management that have affected land use and land cover. This study employed an accuracy assessment-based empirical approach to test the optimality of a number of advanced digital image processing techniques that have recently emerged in the field of remote sensing. The accuracies are assessed using traditional error matrices, calculated using reference data obtained in the field. We found that, for single-time land cover classification, Bayes pixel-based classification using samples created with scale and shape segmentation parameters of 8 and 0.3, respectively, resulted in the highest overall accuracy. For land cover change detection, using Landsat-5 TM band 7 with a change threshold of 1.75 standard deviations resulted in the highest accuracy for forest harvesting and regeneration mapping