Decision Support Level in Monitoring Systems for Railway Automation Based on Questionnaire Theory

Abstract Background: One of the most important types of information systems that play important role today in providing quality health care services are clinical decision support systems (CDSSs). These systems are effective in overcoming human resource constraint and intelligent analysis of information generated by Tele-monitoring systems. In spite of the many advantages of this architectures, these are single-purpose, meaning that only the CDSS of a disease is located on them. If we want to use the same model of architecture in the decision-making process of another disease, all the components of this architecture should be redevelopment with a new CDSS, which is time-consuming and costly. Due to the increasing demand for health information technology at low cost and mobile access in the health care industry, in this article, a scalable software platform(Patient Tele monitoring: PATEL) based on SOA for implementing and use different CDSSs on a common platform, for use in Tele-monitoring Systems, was created.Implementation: To develop PATEL platform, the component-based software development approach and hybrid programming approach to implementing various components used. In the evaluation phase of the proposed platform, the case study, accuracy and performance evaluation (transmission delays, patient data fetch, parsing overhead and inference time) used.Results: The results of the case study evaluation confirmed the scalability and interoperability between CDSSs on the platform. Based on performance evaluation, the proposed platform has responded to 89% of the requests in less than one second. Also, based on accuracy evaluation, the platform presented in this article was successful in diagnosing 91.6% of the cases.Conclusion: The proposed platform can support CDSSs of various diseases simultaneously and provides the necessary scalability to add a new CDSS. Tele-monitoring systems will be capable of service by connecting to this platform. Using this infrastructure is expected to be a lot of duplication in the implementation of tele-monitoring systems based CDSSs will be reduced.

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Interfaces Usability for Monitoring Systems

Encyclopedia of Decision Making and Decision Support Technologies ◽

10.4018/978-1-59904-843-7.ch060 ◽

2011 ◽

pp. 528-538

Author(s):

R.A. Ribeiro ◽

I.L. Nunes

Keyword(s):

Decision Support ◽

Detection System ◽

European Space Agency ◽

Decision Support Tool ◽

Monitoring Systems ◽

Support Tool ◽

Knowledge Based ◽

Space Agency ◽

Mission Success ◽

Graphical Visualization

The objective of this article is to discuss the usability and suitability of having graphical visualization tools for decision support in Space monitoring systems. Operators dealing with specific Space missions are burdened with continuous real-time telemetry data about components’ behavior and they have to take quick actions when some malfunction occurs. To have a decision support tool for monitoring what is happening is essential for ensuring the mission success. In this work, for discussing interface usability concerns for decision support, we use a real case study, called MODI-Monitoring and Diagnosis for Mars Driller project (MODI, 2006), which was financed by the European Space Agency (ESA). The MODI objectives were the development of a fuzzy alarm fault detection system as well as a fuzzy terrain-hardness detection system, for the drill device included in the ExoMars rover (ExoMars, 2007). Although a number of positive results have been achieved using different knowledge-based technologies for monitoring, diagnosis and control, for instance inference systems, expert systems, data mining, fuzzy logic, and so forth (Isermann, 1998; Ross, 2004), only recently attention on the usability and suitability of graphical visualization interfaces, acting as a decision support tool, is starting to be considered a relevant issue in software applications (Nunes, in press).

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Patient-Specific Statistics-Based Decision Support in Health Monitoring Using Fuzzy Logic

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1117.273 ◽

2015 ◽

Vol 1117 ◽

pp. 273-276

Author(s):

Edit Tóth-Laufer ◽

Annamária R. Várkonyi-Kóczy

Keyword(s):

Fuzzy Logic ◽

Decision Support ◽

Membership Function ◽

Health Monitoring ◽

Processing Method ◽

Reduced Model ◽

Patient Specific ◽

Monitoring Systems ◽

Health Monitoring Systems ◽

Specific Evaluation

In this paper, the usage possibilities of personal statistics are introduced, which can be applied to improve the patient-specific evaluation in health monitoring systems. The aim of these techniques is to obtain reliable results based on previous measurements. This goal can be achieved by membership function tuning or modification, as well as by a pre-processing method, which is used to judge whether a situation is normal or not. In the latter case, a further requirement, that the appropriate result should be available in time, can also be fulfilled. If the situation is judged to be critical then a reduced model is evaluated instead of the full one.

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The Research of WebGIS-Based Data Mining

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.267.774 ◽

2011 ◽

Vol 267 ◽

pp. 774-777

Author(s):

Chun Chang Fu

Keyword(s):

Data Mining ◽

Decision Making ◽

Decision Support ◽

Network Analysis ◽

Gis Analysis ◽

Mining Technology ◽

Mass Data ◽

Support Level ◽

Decision Making Support

Data mining provide us a technical found potential knowledge technical from mass data , the data mining technology is applied to GIS can promote GIS analysis of the data, so as to improve the ability of decision support level. WebGIS is traditional GIS space outspread, current network analysis and decision making support capability are low, the network-based integration of data mining and WebGIS can strengthen the analytical capacity.

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A decision support system (DSS) for critical landslides and rockfalls and its application to some cases in the Western Italian Alps

10.5194/nhess-2017-396 ◽

2017 ◽

Author(s):

Davide Bertolo

Keyword(s):

Decision Support ◽

Decision Support System ◽

Support System ◽

Early Warning ◽

Early Warning Systems ◽

Decision Makers ◽

Monitoring Systems ◽

Landslide Monitoring ◽

Civil Protection ◽

Degree Of Confidence

Abstract. Operative geologists who are involved in emergency management have often to deal with the consequences of assuming critical and strongly impacting decisions in uncertain conditions. Geohazards induced by active landslides are one of the civil protection situations requiring such decisions. Nowadays, the monitoring of active landslides is almost always supported by numerical early warning systems, based on instrumental geotechnical and topographic networks. These networks provide numerical early warning thresholds, which are set up in order to activate alert conditions at various levels of criticality in an objective way. Despite these progresses the issue related to the possibility to dispatch false alerts has not yet effectively solved and that’s the reason why the critical stages of the decisional processes are frequently relying not only on quantitative thresholds but also on the subjective experience of the emergency managers. Therefore it is not so uncommon to read landslide-monitoring procedures that combine the quantitative information provided by the monitoring systems with the qualitative decisional elements coming from their professional experience in order to assume the most correct decision. It's therefore evident that such an approach weakens the objectiveness provided by instrumental monitoring systems but, at the same time, collecting geological empirical and qualitative data can strengthen an hypothesis like the one that an active landslide could finally collapse. Bayesian methods are frequently used in clinical decision making, another field of the human activity where critical decisions have to be made in a short time, combining objective values such as those provided by medical tests with diagnostic qualitative markers. Based on the methods of clinical diagnosis, the has author has elaborated a reliable and objective Bayesian Decision Support System (or DSS), developed to support the decision makers in assuming the most correct decisions based on all the elements, both quantitative and qualitative, that are available at a certain step of the decision process. Thanks to the Bayesian approach, the DSS allows also to assess the predictivity of any single decisional step, which is the probability that a monitored landslide actually collapses when particular diagnostic evidences are detected, either instrumental or observational. Hence the decision makers who are able to issue a civil protection alert when a given degree of confidence about the chance that a monitored landslide will collapse is reached. The degree of confidence associated to the civil protection alert can be declared in the alert bulletin (e.g.: 80 % or 93 %). The decisional process can be tracked and replied by everyone in complete transparency. It's therefore evident that such a DSS allows the civil protection authorities to increase the reliability of the alerts, reducing at the same time the so-called “cry wolf” effect and the discomfort related to evacuations and to other civil protection measures. As a matter of fact, the decisional process becomes clearer and the people’s trust in the civil protection systems is being strengthened by a more transparent emergency communication. The DSS here described is an evolution and a statistical improvement of the method adopted in 2013 and 2014 during the emergency of the Mont the la Saxe landslide, and is now being successfully applied to two other hazardous situations in the Aosta Valley Alps: the Brenva Site (Mont Blanc Massif) and the Berlachu site in the municipality of Lillianes (Lower Lys Valley).

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Inter-Transactional Association Analysis for Prediction

Encyclopedia of Data Warehousing and Mining ◽

10.4018/978-1-59140-557-3.ch124 ◽

2011 ◽

pp. 653-658

Author(s):

Ling Feng ◽

Tharam Dillon

Keyword(s):

Data Mining ◽

Decision Support ◽

Marketing Strategy ◽

Association Analysis ◽

Association Rules ◽

Confidence Level ◽

Structured Data ◽

Market Basket Analysis ◽

Market Basket ◽

Support Level

The discovery of association rules from large amounts of structured or semi-structured data is an important data-mining problem (Agrawal et al., 1993; Agrawal & Srikant, 1994; Braga et al., 2002, 2003; Cong et al., 2002; Miyahara et al., 2001; Termier et al., 2002; Xiao et al., 2003). It has crucial applications in decision support and marketing strategy. The most prototypical application of association rules is market-basket analysis using transaction databases from supermarkets. These databases contain sales transaction records, each of which details items bought by a customer in the transaction. Mining association rules is the process of discovering knowledge such as, 80% of customers who bought diapers also bought beer, and 35% of customers bought both diapers and beer, which can be expressed as “diaper Þ beer” (35%, 80%), where 80% is the confidence level of the rule, and 35% is the support level of the rule indicating how frequently the customers bought both diapers and beer. In general, an association rule takes the form X Þ Y (s, c), where X and Y are sets of items, and s and c are support and confidence, respectively.

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Significance of risk assessment metric in audit of financial statements and reports

Acta Agraria Debreceniensis ◽

10.34101/actaagrar/34/2844 ◽

2009 ◽

pp. 215-225

Author(s):

Vilmos Wágner

Keyword(s):

Risk Assessment ◽

Decision Making ◽

Decision Support ◽

Risk Analysis ◽

Accounting Information ◽

Financial Statements ◽

Financial Accounting ◽

Monitoring Systems ◽

Financial Reports ◽

Source Of Information

Management and decision-support of today’s businesses require design and application of management reports based and high-end controlling systems. One of the main source of information for controlling systems is financial accounting that should be designed to support planning, controlling and monitoring systems. Financial and accounting information is essential for decision making support of organizations. Thereforeeligible assurance is needed that these information are true and fair. Internal and external financial audits as assurance qualifiers are linking to the controlling systems through assurance. Weaknesses of and threats to controlling systems shall be recovered and communicated to the management during qualifying process. Recovering of threats should be based on risk analysis, assessment. In this study I would like to present some methods and tools of risk assessment of financial reports, statements and a way on they can be further developed.

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