Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Building National Forest and Land-Use Information Systems: Lessons from Cameroon, Indonesia, and Peru

This working paper examines the institutional, human resources, and financial capacities of three countries that have developed a forest and land-use information system, and highlights common enabling factors and challenges

Sustainable management: a strategic challenge for a global minerals and metals industry

This paper refers to the concept of sustainable management as the management approach which efficiently integrates economic, environmental and social issues into the operations of the minerals and metals industries, with the aim of creating long-term benefits for all stakeholders, and securing the support, cooperation, and trust of the local community. Among many other issues, sustainable management deals with strategy, responsible project feasibility decisions, managing for operational efficiency, improved risk management, enhanced stakeholder relationships, and corporate reputation. Overall, it deals with seeking long-term competitive advantages through responsible management of environmental and social issues. An essential requirement for sustainable management is the corporate commitment to the values of sustainability, but this is not sufficient. Also essential is the development of a business culture where sustainability is a high professional and business value. Furthermore, an organizational structure with specific roles and integration mechanisms and adequate management systems are also required. Regarding business culture, a well-established business code is a necessary but an insufficient condition. Sustainable management relies on individual ethical conduct and trust to foster full participation of stakeholders and to encourage commitment among them. It allows decision making at appropriate levels in the organization and encourages individual risk-taking for continuous improvement. Without trust, social licence is not achievable. In this paper, the concept of sustainable management is introduced as the management approach that integrates a business culture, strong leadership and an organizational structure that strives for long term economics benefits through sustainability. To achieve this goal, sustainability must be vertically integrated at three organizational levels (corporate, divisional and operational) and three functional levels (strategy, planning and implementation)

A survey on utilization of data mining approaches for dermatological (skin) diseases prediction

Due to recent technology advances, large volumes of medical data is obtained. These data contain valuable information. Therefore data mining techniques can be used to extract useful patterns. This paper is intended to introduce data mining and its various techniques and a survey of the available literature on medical data mining. We emphasize mainly on the application of data mining on skin diseases. A categorization has been provided based on the different data mining techniques. The utility of the various data mining methodologies is highlighted. Generally association mining is suitable for extracting rules. It has been used especially in cancer diagnosis. Classification is a robust method in medical mining. In this paper, we have summarized the different uses of classification in dermatology. It is one of the most important methods for diagnosis of erythemato-squamous diseases. There are different methods like Neural Networks, Genetic Algorithms and fuzzy classifiaction in this topic. Clustering is a useful method in medical images mining. The purpose of clustering techniques is to find a structure for the given data by finding similarities between data according to data characteristics. Clustering has some applications in dermatology. Besides introducing different mining methods, we have investigated some challenges which exist in mining skin data

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care