Towards using ICT to enhance flow of information to aid farmer sustainability in Sri Lanka

Farmers need information at all stages of the farming life cycle to make optimal decisions. The required information includes not only prior knowledge but also real time (dynamic) information such as market prices and current production levels. Some valuable information needed by the farmers is produced by government organizations and is available in different locations in different formats. Although farmer is the most important stakeholder in agriculture, there has not been much effort to provide the essential information to farmers on a real time basis. This lack of information is creating many difficulties for farmers as they are not being able to make the correct decisions relating to their farming activities. Through field studies we have identified information required by farmers at various stages of the farming cycle and official sources where this information is available. Next we developed an information flow model that connects various information sources to farmers’ information needs. Based on these findings we are now developing a mobile phone based information system to deliver the required information to farmers in real time.

Estimating non-response bias in a web-based survey of technology acceptance : a case study of unit guide information systems

Surveys are mostly challenged by response rates. Among the various types of survey research, web-based (internet-based/electronic/online) surveys are commonly used for data collection for a geographically diverse population. In surveys with high/low response rates, non-response bias can be a major concern. While it is not always possible to measure the actual bias due to non-response there are different approaches and techniques that help to identify reasons of non-response bias. The aims of this paper are twofold. (1) To provide an appropriate, interesting and important non-response bias case study for future web-based surveys that will provide guidance to other Information Systems researchers. The case-study concerns an online-survey to evaluate a technology acceptance model for Unit Guide Information systems (UGIS). (2) To discuss how nonresponse bias in a web-based technology acceptance study of an information system (UGIS in this case) can be contained and managed.

Developing a spatial decision support system for sustainable built environments in Abu Dhabi

 The research aims at developing a set of sustainability indicators for the challenging Abu Dhabi built environment and examine the possible use of GIS. The research has illustrated the real potential of the sustainability indicators for managing built environment sustainability performance and provides a clear perspective on how the proposed indicators can be used to develop a DSS to assess and improve Abu Dhabi’s sustainability.

A real-time abnormality detection system for intensive care management

Detecting abnormalities from multiple correlated time series is valuable to those applications where a credible realtime event prediction system will minimize economic losses (e.g. stock market crash) and save lives (e.g. medical surveillance in the operating theatre). For example, in an intensive care scenario, anesthetists perform a vital role in monitoring the patient and adjusting the flow and type of anesthetics to the patient during an operation. An early awareness of possible complications is vital for an anesthetist to correctly react to a given situation. In this demonstration, we provide a comprehensive medical surveillance system to effectively detect abnormalities from multiple physiological data streams for assisting online intensive care management. Particularly, a novel online support vector regression (OSVR) algorithm is developed to approach the problem of discovering the abnormalities from multiple correlated time series for accuracy and real-time efficiency. We also utilize historical data streams to optimize the precision of the OSVR algorithm. Moreover, this system comprises a friendly user interface by integrating multiple physiological data streams and visualizing alarms of abnormalities. © 2013 IEEE.