Real Decision Support System Research Articles

NOISE REDUCTION OF LUNGS COMPUTED TOMOGRAPHY IMAGES

This article deals with the problem of improving the quality of the decision support system by improving the preprocessing of human lungs computed tomography images. These images are low-contrast and contain various noise, so pre-processing such images is an actual current issue. This problem is very important because quality of the preprocessing determines the efficiency of the decision support system. decision support system is used in the processing of computerized tomograms to reduce the level of noise in images in order to increase the probability of correct diagnosis. The aim of the work was to create a better method for apply in this applied area. This article has been analyzed existing methods of reducing the level of noise in the images of humans lungs computed tomography. This work revealed the main disadvantages of the existing methods. Combined method with contrasting was proposed for reducing the level of noise on images of computed tomography, on the basis of the received information. The efficiency of the proposed method was evaluated by three indicators and compared with the efficiency of the considered methods. Based on the data of these assessments, the method with contrasting turned out to be the best among those considered, which shows the expediency of applying the proposed method in real decision support systems in medicine. The application of the combined method with contrasting which proposed in the article for the preprocessing of images of humans lungs computed tomography will improve the quality of the system as a whole, which in turn will increase the probability of correct diagnosis..

Decision support systems in manufacturing: a survey and future trends

PurposeThis paper aims to propose a theoretical decision support framework, which integrates artificial intelligence (AI), discrete-event simulation (DES) and database management technologies so as to determine the steady state flow of items (e.g. fixtures, jigs, tools, etc.) in manufacturing.Design/methodology/approachThe existing literature was carefully reviewed to address the state of the arts in decision support systems (DSS), the shortcomings of pure simulation-based and pure AI-based DSS. A conceptual example is illustrated to show the integrated application of AI, simulation and database components of the proposed DSS framework.FindingsRecent DSS studies have revealed the limitations of pure simulation-based and pure AI-based DSS. A new DSS framework is required in manufacturing to address these limitations, taking into account the problems of flowing items.Research limitations/implicationsThe theoretical DSS framework is proposed using simple rules and equations. This implies that it is not complex for software development and implementation. Practical data are not presented in this paper. A real DSS will be developed using the proposed theoretical framework and realistic results will be presented in the near future.Originality/valueThe proposed theoretical framework reveals how the integrated components of DSS can work together in manufacturing in order to determine the stable flow of items in a specific production period. Especially, the integrated performance of case-based reasoning (CBR) and DES is conceptually illustrated.

Analysis of the process of representing clinical statements for decision-support applications: a comparison of openEHR archetypes and HL7 virtual medical record.

Delivering patient-specific decision-support based on computer-interpretable guidelines (CIGs) requires mapping CIG clinical statements (data items, clinical recommendations) into patients' data. This is most effectively done via intermediate data schemas, which enable querying the data according to the semantics of a shared standard intermediate schema. This study aims to evaluate the use of HL7 virtual medical record (vMR) and openEHR archetypes as intermediate schemas for capturing clinical statements from CIGs that are mappable to electronic health records (EHRs) containing patient data and patient-specific recommendations. Using qualitative research methods, we analyzed the encoding of ten representative clinical statements taken from two CIGs used in real decision-support systems into two health information models (openEHR archetypes and HL7 vMR instances) by four experienced informaticians. Discussion among the modelers about each case study example greatly increased our understanding of the capabilities of these standards, which we share in this educational paper. Differing in content and structure, the openEHR archetypes were found to contain a greater level of representational detail and structure while the vMR representations took fewer steps to complete. The use of openEHR in the encoding of CIG clinical statements could potentially facilitate applications other than decision-support, including intelligent data analysis and integration of additional properties of data items from existing EHRs. On the other hand, due to their smaller size and fewer details, the use of vMR potentially supports quicker mapping of EHR data into clinical statements.

Using global search heuristics for the capacity vehicle routing problem

In this work, a frame is posed which allows to define global search heuristics in an efficient and declarative way, which interacts with a specific computational implementation of a problem. An overview of different ways to solve problems by the use of global search is presented, followed by the specification of the language proposed. A real decision support system was developed through the use of the language. The problem faced was an extension of the capacity vehicle routing problem. The followed approach minimizes the development cost of a decision support system for logistic and productive environments, since the performance of different heuristics can be tested using the language in a straightforward way. Besides, when new requirements or additional knowledge about the problem appear, the solving engine can be easily modified through the heuristic language.

Risk‐taking behaviour of decision‐makers in Finnish timber procurement organizations

The results of several studies have revealed that various personal, organizational, and situational factors are correlated with individual decision‐makers’ willingness to take risks. It has also been proposed that people are averse to risky choices involving unspecified probabilities. Hence people avoid choosing ambiguous alternatives. The main objectives of this study were (1) to describe peoples’ attitudes towards risk by decision‐makers engaged in timber procurement, (2) to discover the variables that are the most significantly related to risk‐taking by managers, and (3) to express managers’ needs and desire for taking advantage of real decision support systems (DSSs). The study was executed in the form of a mail‐survey questionnaire. The results indicated that there were risk‐averters, risk‐neutrals, and risk‐seekers in timber procurement organizations. Furthermore, several variables were found to differ in statistical significance among risk‐averse, risk‐neutral, and risk‐seeking managers. They recognized many potential areas of activity where their decision‐making could be supported by DSSs. Consequently, the next phase would be to design and construct DSSs that would help managers to specify the probabilities of the possible outcomes of the different alternatives more effectively.

Pour un système interactif d'aide à la décision pour la résorption de l'habitat spontané en milieu urbain

ABSTRACT The developping countries are facing many urban problems caracterized by the proliferation of spontaneous habitat in quarters. This paper describes an approach of intervention in urban sector in order to improve the knowledge and the management of characteristics parameters (site, land, building, road, network, equipement) of a quarter. According to the complexity of decision in town management and the diversity of datas to manage, we propose a computer—based solution. It frees the different actors of urban management from the fastidious work of data collection, data organization and manipulation before any decision making. In this paper, a first step is realised concerning the data storage and the judicious presentation of statistical datas to the decsion makers. The system to implement allows through its flexibility and its interactivity to help them in the decision making process. This approach is closed to a real DSS (decision support system): the datas are formated in a way that can improve the decision making, the choice of the final action depends on the way the decision maker percieves the quarter and his personal capability to solve problems and conflits.

Decision support systems for aquaculture licensing

Models used to assess the environmental impacts of aquaculture are becoming increasingly numerous and complicated. It is therefore becoming more and more difficult to present these models to non-scientists; even though the ultimate clients of research on a aquaculture impacts are administrators and producers who have to deal with practical considerations and have little time or inclination to deal with the complexities of scientific models. The Aquaculture Research Group within the Habitat Ecology Division has therefore been exploring the development of a decision support system (DSS) as a tool for communicating scientific advice to managers, specifically addressing the use of models to evaluate environmental impacts in order to assess whether the licensing of finfish aquaculture sites is likely to lead to degradation of natural marine habitat. The proposed DSS will incorporate simplified versions of several models along with a geographical data base of relevant hydrographic and other environmental information. The user will be able to enter various scenarios in a simple Fashion (for example, a mouse can be used to specify site locations) and see an evaluation of the proposal based on several scientific models. Although a computer program cannot be expected to represent more than a fraction of the expertise of real scientists, the DSS approach appears to have several advantages; these include the ability to deliver a degree of expertise in remote and isolated regions, and, perhaps most important, a chance for managers to access scientific resources in a private environment which lets them ex lore various options without having to justify their eventual actions to scientists who may not fully appreciate all the pressures which bear on their decisions. The material developed so far includes a prototype of the proposed DSS in form of a computer program which demonstrates what the user interface for a working DSS would look like. The program has only a crude graphical user interface and does not actually interact with a real database, but the models are realistic and the output offers a simplified representation of what a real Decision Support System might provide