In the present paper we discuss how to assist critical decisions taken under complex, contingent circumstances, with a high degree of uncertainty and short time frames. In such sharp-end decision regimes, standard rule-based decision support systems do not capture the complexity of the situation. At the same time, traditional risk analysis is of little use due to variability in the specific circumstances. How then, can an organisation provide assistance to, e.g. pilots in dealing with such emergencies? A method called 'contingent risk and decision analysis' is presented, to provide decision support for decisions under variable circumstances and short available time scales. The method consists of nine steps of definition, modelling, analysis and criteria definition to be performed 'off-line' by analysts, and procedure generation to transform the analysis result into an operational decision aid. Examples of pilots' decisions in response to sudden vibration in offshore helicopter transport method are used to illustrate the approach
A knowledge-based diagnostic model which helps decisionmakers learn about hidden liabilities in their plan scenarios is developed in this paper. It offers critical opinions on plan deficiencies that may otherwise remain undetected. Decisionmakers preserve the freedom to explore solutions and retain the authority of making adjustments. This approach to human - computer interface design contributes to a more advanced domain-specific decision support system.
National Aeronautics and Space Administration — Phoenix Integration's vision is the creation of an intuitive human-in-the-loop engineering environment called Decision Navigator that leverages recent advances in...
with an overview of the web-based Decision Support System (DSS) developed to facilitate its wide adop- tion. The DSS and ... Assessment; management, participation; indicators; decision support systems, protected area management. J. Earth Syst. Sci. ..... tors, which are increasingly technical, require use of software that is ...
The Fire Control Division at ARDEC is developing prototype decision aid tools to enable fire support echelons to rapidly respond to requests for fire support. Decision aids on fire support platforms can assist in route planning, site selection, and develop mobility overlays to enable the shooter to rapidly move into position and prepare for the fire mission. The Decision Aid system utilizes an integrated design approach which has each module interacting with the others by sharing data bases and common algorithms to provide recommended courses of action for route planning and generation, position selection, self defense, logistics estimates, situational awareness and fire mission planning aids such as tactical assessment, tactical planning, sustainment, etc. The Decision Aid system will use expert system artificial intelligence which will be developed from knowledge bases utilizing object oriented design. The modules currently reason on Defense Mapping Agency Interim Terrain Data and Digital Terrain Elevation Data and collect mission, intelligence, and sensor data from the digitized battlefield information distribution system to provide the crew or mission planners with intelligent recommendations. The system can provide a trade off analysis of time vs. safety, enable commanders to rapidly respond to fire support request, automatically generate OpOrders, and create overlays which depict mobility corridors, NBC areas, friendly units, overhead concealment, communications, and threat areas. The Decision Aids system can provide a vastly improved mobility, situational awareness, and decision cycle capabilities which can be utilized to increase the tempo of battle.
Vasilecas, Olegas; Smaizys, Aidas; Brazinskas, Ramunas
Intelligent information systems are acting by structured rules and do not deal with possible impact on the business environment or future consequences. That is the main reason why automated decisions based on such rules cannot take responsibility and requires involvement or approval of dedicated business people. This limits decision automation possibilities in information systems. However, business rules describe business policy and represent business logics. This can be used in intelligent information systems, together with risk assessment model to simulate real business environment and evaluate possible impact of automated decisions, to support intelligent decision automation. The chapter proposes risk and business rule model integration to provide full intelligent decision automation model used for business rule enforcement and implementation into intelligent software systems of information systems.
Tyagi, Rajesh; Tseng, Fan T.
This paper presents the development of a prototype Knowledge-based Decision Support System, currently under development, for scheduling payloads/experiments on space station missions. The DSS is being built on Symbolics, a Lisp machine, using KEE, a commercial knowledge engineering tool.
van Harten, Aart; Worm, J.M.; Worm, J.M.
In this article we describe a Decision Support Model, based on Operational Research methods, for the multi-period planning of maintenance of bituminous pavements. This model is a tool for the road manager to assist in generating an optimal maintenance plan for a road. Optimal means: minimising the
Safety is an important element in business decision making processes in nuclear power plants. Information about component reliability, structures and systems, data recorded during the nuclear power plant's operation and outage periods, as well as experiences from other power plants are located in different database systems throughout the power plant. It would be possible to create a decision support system which would collect data, transform it into a standardized form and store it in a single location in a format more suitable for analyses and knowledge discovery. This single location where the data would be stored would be a data warehouse. Such data warehouse based decision support system could help make decision making processes more efficient by providing more information about business processes and predicting possible consequences of different decisions. Two main functionalities in this decision support system would be an OLAP (On Line Analytical Processing) and a data mining system. An OLAP system would enable the users to perform fast, simple and efficient multidimensional analysis of existing data and identify trends. Data mining techniques and algorithms would help discover new, previously unknown information from the data as well as hidden dependencies between various parameters. Data mining would also enable analysts to create relevant prediction models that could predict behaviour of different systems during operation and inspection results during outages. The basic characteristics and theoretical foundations of such decision support system are described and the reasons for choosing a data warehouse as the underlying structure are explained. The article analyzes obvious business benefits of such system as well as potential uses of OLAP and data mining technologies. Possible implementation methodologies and problems that may arise, especially in the field of data integration, are discussed and analyzed.(author)
The overall goal for the design of Intelligent Decision Support Systems (IDSS) is to enhance understanding of the process under all operating conditions. For an IDSS to be effective, it must: select or generate the right information; produce reliable and consistent information; allow flexible and effective operator interaction; relate information presentation to current plant status and problems; and make the presentation at the right time. Several ongoing R and D programs try to design and build IDSSs. A particular example is the ESPRIT project Graphics and Knowledge Based Diaglogue for Dynamic Systems (GRADIENT). This project, the problems it addresses, and its uses, are discussed here
Sojda, Richard S.
The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988
Full Text Available We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender, are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system.
Gräßer, Felix; Beckert, Stefanie; Küster, Denise; Schmitt, Jochen; Abraham, Susanne; Malberg, Hagen; Zaunseder, Sebastian
We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender , are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system.
Ritchie, Stephen G.
Fundamental to the operation of most currently envisioned Intelligent Vehicle-Roadway System (IVRS) projects are advanced systems for surveillance, control and management of integrated freeway and arterial networks. A major concern in the development of such Smart Roads, and the focus of this paper, is the provision of decision support for traffic management center personnel, particularly for addressing nonrecurring congestion in large or complex networks. Decision support for control room st...
Ostadzadeh, S. Shervin; Habibi, Jafar; Ostadzadeh, S. Arash
Recent challenges have brought about an inevitable tendency for enterprises to lunge towards organizing their information activities in a comprehensive way. In this respect, Enterprise Architecture (EA) has proven to be the leading option for development and maintenance of information systems. EA clearly provides a thorough outline of the whole information system comprising an enterprise. To establish such an outline, a logical framework needs to be laid upon the entire information system. Zachman framework (ZF) has been widely accepted as a standard scheme for identifying and organizing descriptive representations that have critical roles in enterprise management and system development. In this paper, we propose a framework based on ZF for Decision Support Systems (DSS). Furthermore, a modeling approach based on Model-Driven Architecture (MDA) is utilized to obtain compatible models for all cells in the framework. The efficiency of the proposed framework is examined through a case study.
Full Text Available Decision Support Systems (DSS form a specific class of computerized information systems that support business and managerial decision-making activities. Making the right decision in business primarily depends on the quality of data. It also depends on the ability to analyze the data with a view to identifying trends that can suggest solutions and strategies. A “cooperative” decision support system means the data are collected, analyzed and then provided to a human agent who can help the system to revise or refine the data. It means that both a human component and computer component work together to come up with the best solution. This paper describes the usage of a software product (Vanguard System to a specific economic application (evaluating the financial risk assuming that the rate of the economic profitability can be under the value of the interest rate.
Олег Николаевич ГУЦА
Full Text Available State-of-the-art decision support systems (DSS used in project management are mainly based on quantitative methods. However, formal methods of modern mathematics alone are not capable of being a universal means of solving all practical problems in this area. Due to their limited capabilities and lack of statistical and other relevant information, economic-mathematical methods find limited application in management and marketing. In addition, there are few reliable validation and verification methods available. On the other hand, expert assessment methods are free of these disadvantages and are almost the only way to solve this type of problem. Advantages of this approach include simplicity of prediction in nearly every case and excellent performance in incomplete information scenarios. This work presents a new information technology which generates a DSS, based on qualitative methods of verbal decision analysis. The authors propose certain modifications to the method of ordinary classification. The proposed technology is implemented as a web application, which is used to design a system that evaluates the probability of a successful project.
Decision Support Systems (DSS) are a specific class of computerized information system that supports business and organizational decision-making activities. A properly-designed DSS is an interactive software-based system intended to help decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make decisions. DSS belong to an environment with multidisciplinary foundations, including database reasearch, a...
Doctor, P.G.; O'Neil, T.K.; Sackschewsky, M.R.; Becker, J.M.; Rykiel, E.J.; Walters, T.B.; Brandt, C.A.; Hall, J.A.
Environmental restoration and management decisions facing the US Department of Energy require balancing trade-offs between diverse land uses and impacts over multiple spatial and temporal scales. Many types of environmental data have been collected for the Hanford Site and the Columbia River in Washington State over the past fifty years. Pacific Northwest National Laboratory (PNNL) is integrating these data into a Geographic Information System (GIS) based computer decision support tool. This tool provides a comprehensive and concise description of the current environmental landscape that can be used to evaluate the ecological and monetary trade-offs between future land use, restoration and remediation options before action is taken. Ecological impacts evaluated include effects to individual species of concern and habitat loss and fragmentation. Monetary impacts include those associated with habitat mitigation. The tool is organized as both a browsing tool for educational purposes, and as a framework that leads a project manager through the steps needed to be in compliance with environmental requirements
Gøtze, John; Hijikata, Masao
Introducing the notion of Group Decision Process Support Systems (GDPSS) to traditional decision-support theorists.......Introducing the notion of Group Decision Process Support Systems (GDPSS) to traditional decision-support theorists....
Alvarado, Lori; Gates, Ann Q.; Gray, Bob; Reyes, Raul
Tilting the Balance: Climate Variability and Water Resource Management in the Southwest, a regional conference hosted by the Pan American Center for Environmental Studies, will be held at The University of Texas at El Paso on March 2-4, 1998. The conference is supported through the US Global Change Research Program (USGCRP) established by the President in 1989, and codified by Congress in the Global Change Research Act of 1990. The NASA Mission to Planet Earth program is one of the workshops sponsors. The purpose of the regional workshops is to improve understanding of the consequences of global change. This workshop will be focused on issues along the border and the Rio Grande River and thus will bring together stakeholders from Mexico, California, Texas, New Mexico, Arizona and Colorado representing federal, state, and local governments; universities and laboratories; industry, agricultural and natural resource managers; and non-governmental organizations. This paper discusses the efforts of the NASA PACES center create a GIS-based decision-support system that can be used to facilitate discussion of the complex issues of resource management within the targeted international region.
...) of the Marine Air Ground Task Force (MAGTF). Through the use of Intranet-based decision support, internet technology can be leveraged to improve the decision support and information processes of the ACE...
Full Text Available The difficulty in knowledge representation of a water distribution network (WDN problem has contributed to the limited use of artificial intelligence (AI based expert systems (ES in the management of these networks. This paper presents a design of a Decision Support System (DSS that facilitates "on-demand'' knowledge generation by utilizing results of simulation runs of a suitably calibrated and validated hydraulic model of an existing aged WDN corresponding to emergent or even hypothetical but likely scenarios. The DSS augments the capability of a conventional expert system by integrating together the hydraulic modelling features with heuristics based knowledge of experts under a common, rules based, expert shell named CLIPS (C Language Integrated Production System. In contrast to previous ES, the knowledge base of the DSS has been designed to be dynamic by superimposing CLIPS on Structured Query Language (SQL. The proposed ES has an inbuilt calibration module that enables calibration of an existing (aged WDN for the unknown, and unobservable, Hazen-Williams C-values. In addition, the daily run and simulation modules of the proposed ES further enable the CLIPS inference engine to evaluate the network performance for any emergent or suggested test scenarios. An additional feature of the proposed design is that the DSS integrates computational platforms such as MATLAB, open source Geographical Information System (GIS, and a relational database management system (RDBMS working under the umbrella of the Microsoft Visual Studio based common user interface. The paper also discusses implementation of the proposed framework on a case study and clearly demonstrates the utility of the application as an able aide for effective management of the study network.
Schubert, Johan; Hörling, Pontus
In this paper, we develop methods for analyzing large amounts of data from a military ground combat simulation system. Through a series of processes, we focus the big data set on situations that correspond to important questions and show advantageous outcomes. The result is a decision support methodology that provides commanders with results that answer specific questions of interest, such as what the consequences for the Blue side are in various Red scenarios or what a particular Blue force can withstand. This approach is a step toward taking the traditional data farming methodology from its analytical view into a prescriptive operation planning context and a decision making mode.
Full Text Available Information hasbecome an essentialresource for managing modern organizations. This is so because today’sbusiness environment is volatile, dynamic, turbulent and necessitates the burgeoning demand for accurate, relevant, complete,timely and economical information needed to drive the decision-making process in order to accentuate organizational abilities to manage opportunities and threat. MIS work on online mode with an average processing speed. Generally, it is used by low level management. Decision support system are powerful tool that assist corporate executives, administrators and other senior officials in making decision regarding the problem. Management Information Systems is a useful tool that provided organized and summarized information in a proper time to decision makers and enable making accurate decision for managers in organizations. This paper will discuss the concept, characteristics, types of MIS, the MIS model, and in particular it will highlight the impact and role of MIS on decision making.
Jørgensen, L.N.; Noe, E.; Langvad, A.M.
The highly complex knowledge of scientific disciplines makes nuanced analysis and modelling possible. However, the information produced often does not reach farmers because it is presented in a way that does not correspond to the way their work is carried out in practice. The decision support...... 1000 farmers). A sociological investigation of farmers' decision-making styles in the area of crop protection has shown that arable farmers can be divided into three major groups: (a) system-orientated farmers, (b) experience-based farmers and (c) advisory-orientated farmers. The information required...... by these three groups to make their decisions varies and therefore different ways of using decision support systems need to be provided. Decision support systems need to be developed in close dialogue and collaboration with user groups....
Hoffman, Aubri S; Llewellyn-Thomas, Hilary A; Tosteson, Anna N A; O'Connor, Annette M; Volk, Robert J; Tomek, Ivan M; Andrews, Steven B; Bartels, Stephen J
Over 100 trials show that patient decision aids effectively improve patients' information comprehension and values-based decision making. However, gaps remain in our understanding of several fundamental and applied questions, particularly related to the design of interactive, personalized decision aids. This paper describes an interdisciplinary development process for, and early field testing of, a web-based patient decision support research platform, or virtual decision lab, to address these questions. An interdisciplinary stakeholder panel designed the web-based research platform with three components: a) an introduction to shared decision making, b) a web-based patient decision aid, and c) interactive data collection items. Iterative focus groups provided feedback on paper drafts and online prototypes. A field test assessed a) feasibility for using the research platform, in terms of recruitment, usage, and acceptability; and b) feasibility of using the web-based decision aid component, compared to performance of a videobooklet decision aid in clinical care. This interdisciplinary, theory-based, patient-centered design approach produced a prototype for field-testing in six months. Participants (n = 126) reported that: the decision aid component was easy to use (98%), information was clear (90%), the length was appropriate (100%), it was appropriately detailed (90%), and it held their interest (97%). They spent a mean of 36 minutes using the decision aid and 100% preferred using their home/library computer. Participants scored a mean of 75% correct on the Decision Quality, Knowledge Subscale, and 74 out of 100 on the Preparation for Decision Making Scale. Completing the web-based decision aid reduced mean Decisional Conflict scores from 31.1 to 19.5 (p decision science and health informatics approaches facilitated rapid development of a web-based patient decision support research platform that was feasible for use in research studies in terms of recruitment
West, Paul D; Trainor, Timothy E
.... A model is presented that combines a new risk assessment methodology with traditional decision-making tools to enable systems engineers to capture the full spectrum of operational risks during the design process...
Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The
Optimization-based decision support systems for planning problems in processing industries
Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in
Keith Reynolds; Micahel Saunders; Richard Olson; Daniel Schmoldt; Michael Foster; Donald Latham; Bruce Miller; John Steffenson; Lawrence Bednar; Patrick Cunningham
The Pacific Northwest Research Station (USDA Forest Service) is developing a knowledge-based information management system to provide decision support for watershed analysis in the Pacific Northwest region of the U.S. The decision support system includes: (1) a GIS interface that allows users to graphically navigate to specific provinces and watersheds and display a...
Keith M. Reynolds
The USDA Forest Service Pacific Northwest Research Station in Corvallis, Oregon, has developed the ecosystem management decision support (EMDS) system. The system integrates the logical formalism of knowledge-based reasoning into a geographic information system (GIS) environment to provide decision support for ecological landscape assessment and evaluation. The...
National Aeronautics and Space Administration — SMH Consulting proposes to develop a web-based decision support system to assist in Rapid Assessment, Monitoring, and Management (RAMM-DSS) on a regional scale. SMH...
We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environ...
Ritsema van Eck, Gerard; Ceross, Aaron
The decision support tool is part of the toolkit for policy makers which came out of the FP7 RESPECT project, which dealt with privacy and surveillance. It's aim is to support decision makers at all levels of government who face difficult decisions regarding the implementation of surveillance
Ajay Kumar Saxena
Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.
Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.
Nowadays, web based decision support systems (DSS) play an essential role in disaster risk management because of their supporting abilities which help the decision makers to improve their performances and make better decisions without needing to solve complex problems while reducing human resources and time. Since the decision making process is one of the main factors which highly influence the damages and losses of society, it is extremely important to make right decisions at right time by combining available risk information with advanced web technology of Geographic Information System (GIS) and Decision Support System (DSS). This paper presents an integrated web-based decision support system (DSS) of how to use risk information in risk management efficiently and effectively while highlighting the importance of a decision support system in the field of risk reduction. Beyond the conventional systems, it provides the users to define their own strategies starting from risk identification to the risk reduction, which leads to an integrated approach in risk management. In addition, it also considers the complexity of changing environment from different perspectives and sectors with diverse stakeholders' involvement in the development process. The aim of this platform is to contribute a part towards the natural hazards and geosciences society by developing an open-source web platform where the users can analyze risk profiles and make decisions by performing cost benefit analysis, Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) with the support of others tools and resources provided. There are different access rights to the system depending on the user profiles and their responsibilities. The system is still under development and the current version provides maps viewing, basic GIS functionality, assessment of important infrastructures (e.g. bridge, hospital, etc.) affected by landslides and visualization of the impact
Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.
To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high' level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the ''glue'' or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission
Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.
To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high' level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the glue'' or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.
Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.
To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high` level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the ``glue`` or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.
Fortney, John C; Pyne, Jeffrey M; Steven, Christopher A; Williams, J Silas; Hedrick, Richard G; Lunsford, Amanda K; Raney, William N; Ackerman, Betty A; Ducker, Loretta O; Bonner, Laura M; Smith, Jeffrey L
To inform the design of future informatics systems that support the chronic care model. We describe the development and functionality of a decision support system for the chronic care model of depression treatment, known as collaborative care. Dissemination of evidence-based collaborative care models has been slow, and fidelity to the evidence base has been poor during implementation initiatives. Implementation could be facilitated by a decision support system for depression care managers, the cornerstone of the collaborative care model. The Net Decision Support System (https://www.netdss.net/) is a free Web-based system that was developed to support depression care manager activities and to facilitate the dissemination of collaborative care models that maintain high fidelity to the evidence base. The NetDSS was based on intervention materials used for a randomized trial of depression care management that improved clinical outcomes compared with usual care. The NetDSS was developed jointly by a cross-functional design team of psychiatrists, depression care managers, information technology specialists, technical writers, and researchers. The NetDSS has the following functional capabilities: patient registry, patient encounter scheduler, trial management, clinical decision support, progress note generator, and workload and outcomes report generator. The NetDSS guides the care manager through a self-documenting patient encounter using evidence-based scripts and self-scoring instruments. The NetDSS has been used to provide evidence-based depression care management to more than 1700 primary care patients. Intervention protocols can be successfully converted to Web-based decision support systems that facilitate the implementation of evidence-based chronic care models into routine care with high fidelity.
Viana Da Rocha, T. C.; Stipanovic, I.; Hartmann, A.; Bakker, J.
As a cornerstone of transportation asset management, risk-based approaches have been used to support maintenance decisions of civil structures. However, ambiguous and subjective risk criteria and inconsistency on the use of risk-based approaches can lead to a fuzzy understanding of the risks
Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom
We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.
Mukhlash, Imam; Maulidiyah, Ratna; Sutikno; Setiyono, Budi
Appropriate decision making in risk management of rice production is very important in agricultural planning, especially for Indonesia which is an agricultural country. Good decision would be obtained if the supporting data required are satisfied and using appropriate methods. This study aims to develop a Decision Support System that can be used to predict the risk level of rice production in some districts which are central of rice production in East Java. Web-based decision support system is constructed so that the information can be easily accessed and understood. Components of the system are data management, model management, and user interface. This research uses regression models of OLS and Copula. OLS model used to predict rainfall while Copula model used to predict harvested area. Experimental results show that the models used are successfully predict the harvested area of rice production in some districts which are central of rice production in East Java at any given time based on the conditions and climate of a region. Furthermore, it can predict the amount of rice production with the level of risk. System generates prediction of production risk level in the long term for some districts that can be used as a decision support for the authorities.
Sousa, Tiago; Pinto, Tiago; Praca, Isabel
proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM......-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach...... provides the means for simulating a real electricity market environment, based on real data from real electricity market operators...
U. Kayande (Ujwal); A. de Bruyn (Arnoud); G.L. Lilien (Gary); A. Rangaswamy (Arvind); G.H. van Bruggen (Gerrit)
textabstractMarketing managers often provide much poorer evaluations of model-based marketing decision support systems (MDSSs) than are warranted by the objective performance of those systems. We show that a reason for this discrepant evaluation may be that MDSSs are often not designed to help users
Krauth, Elfriede I.; van Hillegersberg, Jos; van de Velde, Steef L.
Adoption rates of traditional Operations Research (OR) based decision support systems (DSS) suffer from perceived complexity of the underlying model and its detrimental effect on user-friendliness. The mental effort required to understand abstract models can hinder adoption. This barrier may seem
Computer graphics and scientific visualization are fields of computational science that have evolved rapidly over the past decades. Scientific visualization has become an important technology in serious gaming and science-based decision support. Water management is a complex process dealing with a
Franco de los Ríos, Camilo; Pedersen, Søren Marcus; Papaharalampos, Haris
for the implementation of automatic weed recognition procedures. The objective of this paper is to develop a decision support methodology for detecting the undesired weed from aerial images, building an image-based viewpoint consisting in relevant operational knowledge for applying precision spraying. In this way...
Full Text Available Material selection is a delicate process, typically hinged on a number of factors which can be either cost or environmental related. This process becomes more complicated when designers are faced with several material options of building elements and each option can be supplied by different suppliers whose selection criteria may affect the budgetary and environmental requirements of the project. This paper presents the development of a decision support system based on the integration of building information models, a modified harmony search algorithm and supplier performance rating. The system is capable of producing the cost and environmental implications of different material combinations or building designs. A case study is presented to illustrate the functionality of the developed system.
Yu, Peter Paul
One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care. Copyright © 2015 by American Society of Clinical Oncology.
Westrom, G.; Vance, J.N.; Gelhaus, F.E.
The purpose of the Radwaste Decision Support System (RDSS) is to provide expert advice, analysis results and instructional material relative to the treatment, handling, transport and disposal of low-level radioactive waste produced in nuclear power plants. This functional specification addresses the following topics: Functions of the RDSS, Relationships and interfaces between the function, Development of the decisions and logic tree structures embodied in waste management, Elements of the database and the characteristics required to support the decision-making process, Specific User requirements for the RDSS, Development of the user interface, Basic software architecture, and Concepts for the RDSS usage including updating and maintenance
Ben Rabah, N.; Saddem, R.; Ben Hmida, F.; Carre-Menetrier, V.; Tagina, M.
Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach.
Ben Rabah, N; Saddem, R; Carre-Menetrier, V; Ben Hmida, F; Tagina, M
Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach. (paper)
Khorshid, M.; Hassan, H.; Abdel Latife, M.A.
Decision Support System (DSS) is an interactive, flexible and adaptable computer-based support system specially developed for supporting the solution of unstructured management problems  DSS has become widespread for oil industry domain in recent years. The computer-based DSS, which were developed and implemented in oil industry, are used to address the complex short-term planning and operational issues associated with downstream industry. Most of these applications concentrate on the data-centered tools, while the model-centered applications of DSS are still very limited up till now . This study develops an Intelligent Model-Based DSS for an integrated oil company, to help policy makers and petroleum planner in improving the effectiveness of the strategic planning in oil sector. This domain basically imposes semi-structured or unstructured decisions and involves a very complex modeling process
Full Text Available Using distributed hydrological models to evaluate the effectiveness of reducing non-point source pollution by applying best management practices (BMPs is an important support to decision making for watershed management. However, complex interfaces and time-consuming simulations of the models have largely hindered the applications of these models. We designed and developed a prototype web-based decision support system for watershed management (DSS-WMRJ, which is user friendly and supports quasi-real-time decision making. DSS-WMRJ is based on integrating an open-source Web-based Geographical Information Systems (Web GIS tool (Geoserver, a modeling component (SWAT, Soil and Water Assessment Tool, a cloud computing platform (Hadoop and other open source components and libraries. In addition, a private cloud is used in an innovative manner to parallelize model simulations, which are time consuming and computationally costly. Then, the prototype DSS-WMRJ was tested with a case study. Successful implementation and testing of the prototype DSS-WMRJ lay a good foundation to develop DSS-WMRJ into a fully-fledged tool for watershed management. DSS-WMRJ can be easily customized for use in other watersheds and is valuable for constructing other environmental decision support systems, because of its performance, flexibility, scalability and economy.
van Hillegersberg, Jos; Koenen, Sebastiaan
While organizations have massively adopted enterprise information systems to support business processes, business meetings in which key decisions are made about products, services and processes, are usually held without much support of information systems. This is remarkable as group decision
Zheng Qiyan; Zhang Lijun; Huang Weiqi; Chen Lin
For nuclear emergency decision-making support system based on the results of radiation monitoring, its main assignment is receiving radiation monitoring data and analyzing them, to accomplish some works such as environment influence evaluation, dose assessment for emergency responder, decision-making analyzing and effectiveness evaluation for emergency actions, etc.. This system is made up of server, communication terminal, data-analyzing terminal, GPRS modules, printer, and so on. The whole system make of a LAN. The system's software is made up of six subsystems: data-analyzing subsystem, reporting subsystem, GIS subsystem, communication subsystem, user-managing subsystem and data-base. (authors)
Aven, T.; Flage, R.
We consider decision problems related to production assurance and safety. The issue is to what extent we should use decision criteria based on expected values, such as the expected net present value (E[NPV]) and the expected cost per expected number of saved lives (ICAF), to guide the decision. Such criteria are recognised as practical tools for supporting decision-making under uncertainty, but is uncertainty adequately taken into account by these criteria? Based on the prevailing practice and the existing literature, we conclude that there is a need for a clarification of the rationale of these criteria. Adjustments of the standard approaches have been suggested to reflect risks and uncertainties, but can cautionary and precautionary concerns be replaced by formulae and mechanical procedures? These issues are discussed in the present paper, particularly addressing the company level. We argue that the search for such formulae and procedures should be replaced by a more balanced perspective acknowledging that there will always be a need for management review and judgment beyond the realm of the analyses. Most of the suggested adjustments of the E[NPV] and ICAF approaches should be avoided. They add more confusion than value.
Full Text Available In this paper, a Web-based Decision Support System (Web DSS, that supports humanitarian demining operations and restoration of mine-contaminated areas, is presented. The financial shortage usually triggers a need for priority setting in Project Management in Mine actions. As part of the FP7 Project TIRAMISU, a specialized Web DSS has been developed to achieve a fully transparent priority setting process. It allows stakeholders and donors to actively join the decision making process using a user-friendly and intuitive Web application. The main advantage of this Web DSS is its unique way of managing a mine action project using Multi-Criteria Analysis (MCA, namely the PROMETHEE method, in order to select priorities for demining actions. The developed Web DSS allows decision makers to use several predefined scenarios (different criteria weights or to develop their own, so it allows project managers to compare different demining possibilities with ease.
Sabeur, Z. A.; Wächter, J.; Middleton, S. E.; Zlatev, Z.; Häner, R.; Hammitzsch, M.; Loewe, P.
The intelligent management of large volumes of environmental monitoring data for early tsunami warning requires the deployment of robust and scalable service oriented infrastructure that is supported by an agile knowledge-base for critical decision-support In the TRIDEC project (TRIDEC 2010-2013), a sensor observation service bus of the TRIDEC system is being developed for the advancement of complex tsunami event processing and management. Further, a dedicated TRIDEC system knowledge-base is being implemented to enable on-demand access to semantically rich OGC SWE compliant hydrodynamic observations and operationally oriented meta-information to multiple subscribers. TRIDEC decision support requires a scalable and agile real-time processing architecture which enables fast response to evolving subscribers requirements as the tsunami crisis develops. This is also achieved with the support of intelligent processing services which specialise in multi-level fusion methods with relevance feedback and deep learning. The TRIDEC knowledge base development work coupled with that of the generic sensor bus platform shall be presented to demonstrate advanced decision-support with situation awareness in context of tsunami early warning and crisis management.
Zini, Elisa M; Lanzola, Giordano; Bossi, Paolo; Quaglini, Silvana
We propose an architecture for monitoring outpatients that relies on mobile technologies for acquiring data. The goal is to better control the onset of possible side effects between the scheduled visits at the clinic. We analyze the architectural components required to ensure a high level of abstraction from data. Clinical practice guidelines were formalized with Alium, an authoring tool based on the PROforma language, using SNOMED-CT as a terminology standard. The Alium engine is accessible through a set of APIs that may be leveraged for implementing an application based on standard web technologies to be used by doctors at the clinic. Data sent by patients using mobile devices need to be complemented with those already available in the Electronic Health Record to generate personalized recommendations. Thus a middleware pursuing data abstraction is required. To comply with current standards, we adopted the HL7 Virtual Medical Record for Clinical Decision Support Logical Model, Release 2. The developed architecture for monitoring outpatients includes: (1) a guideline-based Decision Support System accessible through a web application that helps the doctors with prevention, diagnosis and treatment of therapy side effects; (2) an application for mobile devices, which allows patients to regularly send data to the clinic. In order to tailor the monitoring procedures to the specific patient, the Decision Support System also helps physicians with the configuration of the mobile application, suggesting the data to be collected and the associated collection frequency that may change over time, according to the individual patient's conditions. A proof of concept has been developed with a system for monitoring the side effects of chemo-radiotherapy in head and neck cancer patients. Our environment introduces two main innovation elements with respect to similar works available in the literature. First, in order to meet the specific patients' needs, in our work the Decision
Bayesian statistical decision theory offers a natural framework for decision-policy making in the presence of uncertainty. Key advantages of the approach include efficient incorporation of information and observations. However, in complicated settings it is very difficult, perhaps essentially impossible, to formalize the mathematical inputs needed in the approach. Nevertheless, using the approach as a template is useful for decision support; that is, organizing and communicating our analyses. Bayesian hierarchical modeling is valuable in quantifying and managing uncertainty such cases. I review some aspects of the idea emphasizing statistical model development and use in the context of sea-level rise.
A short introduction will be given to the Nordic project ''NKA/INF: Information Technology for Accident and Emergency Management'', which is now in its final phase. To perform evaluation of the project, special scenarious have been developed, and experiments based on these will be fulfilled and compared with experiments without use of the decision support system. Furthermore, the succeeding European project, ''IT Support for Emergency Management - ISEM'', with the purpose of developing a decision support system for complex and distributed decision making in emergency management in full scale, will be described and the preliminary conceptual model for the system will be presented. (author)
Full Text Available Communication and marketing professionals make strategic decisions in highly complex and dynamic contexts. These decisions are highly uncertain on the outcome and process level when, for example, consumer behaviour is at stake. Decision support systems can provide insights in these levels of uncertainty and the professional process of decision making. However, literature describing decision support tools for strategic communication and marketing management that provide clear insights in uncertainty levels is lacking. This study therefore aims at developing a consumer behaviour simulation module as an important element of such a future decision support tool. The consumer behaviour simulation we propose in this paper is based on data collected from a survey among 386 households with which a behavioural change model was calibrated. We show how various decision scenarios for strategic communication and marketing challenges can be explored and how such a simulation based decision support system can facilitate strategic communication and marketing management concerning the introduction of a smart energy meter.
Wimmer, G Elliott; Büchel, Christian
Rewarding experiences exert a strong influence on later decision making. While decades of neuroscience research have shown how reinforcement gradually shapes preferences, decisions are often influenced by single past experiences. Surprisingly, relatively little is known about the influence of single learning episodes. Although recent work has proposed a role for episodes in decision making, it is largely unknown whether and how episodic experiences contribute to value-based decision making and how the values of single episodes are represented in the brain. In multiple behavioral experiments and an fMRI experiment, we tested whether and how rewarding episodes could support later decision making. Participants experienced episodes of high reward or low reward in conjunction with incidental, trial-unique neutral pictures. In a surprise test phase, we found that participants could indeed remember the associated level of reward, as evidenced by accurate source memory for value and preferences to re-engage with rewarded objects. Further, in a separate experiment, we found that high-reward objects shown as primes before a gambling task increased financial risk taking. Neurally, re-exposure to objects in the test phase led to significant reactivation of reward-related patterns. Importantly, individual variability in the strength of reactivation predicted value memory performance. Our results provide a novel demonstration that affect-related neural patterns are reactivated during later experience. Reactivation of value information represents a mechanism by which memory can guide decision making. Copyright © 2016 the authors 0270-6474/16/362868-13$15.00/0.
Cortet, J.; Bohanec, M.; ?nidar?ic, M.
a computer-based decision support system for the assessment of economic and ecological impacts of using GM crops, with special emphasis on soil biology and ecology. For model development, we have taken the approach of qualitative multi-attribute modeling (Bohanec 2003). The idea is to develop a hierarchical...... model, consisting of qualitative attributes and utility (aggregation) functions, represented by decision rules. The development is supported by the software tool DEXi, which facilitates the development of a tree of attributes, definition of aggregation rules, evaluation of options (cropping systems...... fields in France and Denmark. The model is hierarchical, consisting of 37 attributes in total, grouped into 7 hierarchical levels. There are 24 input attributes, most of which measure the richness and biomass of representative soil organisms. The assessment of soil quality is based on two main indicators...
The architecture of an automated decision support system for nuclear plant operators is presented and discussed. The system is based on the use of 'logic flowgraph' process models and is designed in a hierarchical fashion. Its functionality spans from 'function oriented' plant status and alternative success path information displayed to the plant operators at its higher access levels to 'process oriented' diagnostic and recovery information deduced and displayed at its lowest. The design basis for this architecture is the 'defense in depth' plant safety concept. The decision support system goal is to provide plant operators, in the presence of an unforeseen transient, with the best and safest alternative between plant stabilization after shutdown and recovery of normal operation based on early diagnosis. Examples of the system capability to interpret and diagnose abnormal plant conditions and of the information that it can supply to the operators at its three access levels are presented and discussed. (author)
Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet
This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care.
di, L.; Yang, Z.
Timely and accurate information on weekly crop progress and development is essential to a dynamic agricultural industry in the U. S. and the world. By law, the National Agricultural Statistics Service (NASS) of the U. S. Department of Agriculture’s (USDA) is responsible for monitoring and assessing U.S. agricultural production. Currently NASS compiles and issues weekly state and national crop progress and development reports based on reports from knowledgeable state and county agricultural officials and farmers. Such survey-based reports are subjectively estimated for an entire county, lack spatial coverage, and are labor intensive. There has been limited use of remote sensing data to assess crop conditions. NASS produces weekly 1-km resolution un-calibrated AVHRR-based NDVI static images to represent national vegetation conditions but there is no quantitative crop progress information. This presentation discusses the early result for developing a National Crop Progress Monitoring and Decision Support System. The system will overcome the shortcomings of the existing systems by integrating NASA satellite and model-based land surface and weather products, NASS’ wealth of internal crop progress and condition data and Cropland Data Layers (CDL), and the Farm Service Agency’s (FSA) Common Land Units (CLU). The system, using service-oriented architecture and web service technologies, will automatically produce and disseminate quantitative national crop progress maps and associated decision support data at 250-m resolution, as well as summary reports to support NASS and worldwide users in their decision-making. It will provide overall and specific crop progress for individual crops from the state level down to CLU field level to meet different users’ needs on all known croplands. This will greatly enhance the effectiveness and accuracy of the NASS aggregated crop condition data and charts of and provides objective and scientific evidence and guidance for the
Borlawsky, Tara; Li, Jianrong; Jalan, Srikant; Stern, Edie; Williams, Rose; Lussier, Yves A
Due to the varying rates of change of ephemeral administrative and enduring clinical knowledge in decision support systems (DSSs), the functional partition of knowledge base (KB) components can lead to more efficient and cost-effective system implementation and maintenance. Our prototype loosely couples a clinical event monitor developed by Columbia University Medical Center (CUMC) with a secure notification service proxy developed by IBM Research to form a novel and complex clinical event communication service.
Brodin, N. Patrik [Department of Radiation Oncology, Albert Einstein College of Medicine of Yeshiva University, New York, New York (United States); Maraldo, Maja V., E-mail: firstname.lastname@example.org [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Aznar, Marianne C. [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Niels Bohr Institute, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Vogelius, Ivan R. [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Petersen, Peter M. [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Department of Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Department of Hematology, Rigshospitalet, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Bentzen, Søren M. [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Department of Human Oncology, University of Wisconsin Medical School, Madison, Wisconsin (United States); Specht, Lena [Department of Radiation Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Department of Oncology, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark); Department of Hematology, Rigshospitalet, Faculty of Sciences, University of Copenhagen, Copenhagen (Denmark)
Purpose: To present a novel tool that allows quantitative estimation and visualization of the risk of various relevant normal tissue endpoints to aid in treatment plan comparison and clinical decision making in radiation therapy (RT) planning for Hodgkin lymphoma (HL). Methods and Materials: A decision-support tool for risk-based, individualized treatment plan comparison is presented. The tool displays dose–response relationships, derived from published clinical data, for a number of relevant side effects and thereby provides direct visualization of the trade-off between these endpoints. The Quantitative Analyses of Normal Tissue Effects in the Clinic reports were applied, complemented with newer data where available. A “relevance score” was assigned to each data source, reflecting how relevant the input data are to current RT for HL. Results: The tool is applied to visualize the local steepness of dose–response curves to drive the reoptimization of a volumetric modulated arc therapy treatment plan for an HL patient with head-and-neck involvement. We also use this decision-support tool to visualize and quantitatively evaluate the trade-off between a 3-dimensional conformal RT plan and a volumetric modulated arc therapy plan for a patient with mediastinal HL. Conclusion: This multiple-endpoint decision-support tool provides quantitative risk estimates to supplement the clinical judgment of the radiation oncologist when comparing different RT options.
Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C
The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratiodecisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.
van Hillegersberg, Jos; Koenen, Sebastiaan
While organizations have massively adopted enterprise information systems to support business processes, business meetings in which key decisions are made about products, services and processes are usually held without much support of information systems. This is remarkable as group decision support
Delgado-Ortegon, Alberto; Jensen, Rune Møller; Guilbert, Nicolas
save port fees, optimize use of vessel capacity, and reduce bunker consumption. Stowage Coordinators (SCs) produce these plans manually with the help of graphical tools, but high-quality SPs are hard to generate with the limited support they provide. In this abstract, we introduce AngelStow which...... is a commercial optimization-based decision support tool for stowing container vessels developed in collaboration between Ange Optimization and The IT University of Copenhagen. The tool assists SCs in the process of generating SPs interactively, focusing on satisfying and optimizing constraints and objectives...
Mera, David; Cotos, José M.; Varela-Pet, José; Rodríguez, Pablo G.; Caro, Andrés
Global trade is mainly supported by maritime transport, which generates important pollution problems. Thus, effective surveillance and intervention means are necessary to ensure proper response to environmental emergencies. Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillages on the oceans surface. Several decision support systems have been based on this technology. This paper presents an automatic oil spill detection system based on SAR data which was developed on the basis of confirmed spillages and it was adapted to an important international shipping route off the Galician coast (northwest Iberian Peninsula). The system was supported by an adaptive segmentation process based on wind data as well as a shape oriented characterization algorithm. Moreover, two classifiers were developed and compared. Thus, image testing revealed up to 95.1% candidate labeling accuracy. Shared-memory parallel programming techniques were used to develop algorithms in order to improve above 25% of the system processing time.
Full Text Available The authors are investigating whether Web-based Group Support System (GSS) tools can support and enhance procedural fairness in administrative decision making in South Africa. They report here on work that emanates from a masters dissertation...
Greenberg, Michael R; Lowrie, Karen; Mayer, Henry; Altiok, Tayfur
We consider the value of decision support tools for passenger rail system managers. First, we call for models that follow events along main rail lines and then into the surrounding environment where they can cascade onto connected light rail, bus, auto, truck, and other transport modes. Second, we suggest that both probabilistic risk assessment (PRA-based) and agent-based models have a role to play at different scales of analysis and for different kinds of risks. Third, we argue that economic impact tools need more systematic evaluation. Fourth, we note that developers of decision support tools face a challenge of balancing their desire for theoretical elegance and the tendency to focus only on high consequence events against decisionmakers' mistrust of complex tools that they and their staff cannot manage and incorporate into their routine operations, as well as the high costs of developing, updating, and applying decision support tools to transport systems undergoing budget cuts and worker and service reductions. © 2011 Society for Risk Analysis.
Wu, Xianguo; Liu, Huitao; Zhang, Limao; Skibniewski, Miroslaw J.; Deng, Qianli; Teng, Jiaying
This paper presents a systemic decision approach with step-by-step procedures based on dynamic Bayesian network (DBN), aiming to provide guidelines for dynamic safety analysis of the tunnel-induced road surface damage over time. The proposed DBN-based approach can accurately illustrate the dynamic and updated feature of geological, design and mechanical variables as the construction progress evolves, in order to overcome deficiencies of traditional fault analysis methods. Adopting the predictive, sensitivity and diagnostic analysis techniques in the DBN inference, this approach is able to perform feed-forward, concurrent and back-forward control respectively on a quantitative basis, and provide real-time support before and after an accident. A case study in relating to dynamic safety analysis in the construction of Wuhan Yangtze Metro Tunnel in China is used to verify the feasibility of the proposed approach, as well as its application potential. The relationships between the DBN-based and BN-based approaches are further discussed according to analysis results. The proposed approach can be used as a decision tool to provide support for safety analysis in tunnel construction, and thus increase the likelihood of a successful project in a dynamic project environment. - Highlights: • A dynamic Bayesian network (DBN) based approach for safety decision support is developed. • This approach is able to perform feed-forward, concurrent and back-forward analysis and control. • A case concerning dynamic safety analysis in Wuhan Yangtze Metro Tunnel in China is presented. • DBN-based approach can perform a higher accuracy than traditional static BN-based approach
Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta
The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river
Miller, Matthew James; McGuire, Kerry M; Feigh, Karen M
The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity . The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design.
Zar Chi Aye
Full Text Available This paper presents the current state and development of a prototype web-GIS (Geographic Information System decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo framework and its client side software development kit (SDK. The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform.
Full Text Available Abstract Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA, which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1 Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA, and 2 Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR. In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1 Data collection and data preparation; 2 acquisition of "Prior Expert Knowledge" (PEK and design of the "Prior Knowledge Base" (PKB; 3 PKB-guided analysis; 4 support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited; 5 incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6 post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering, applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This
Silviu Ioan Bejinariu
Full Text Available The satellite image processing is an important tool for decision making in domains like agriculture, forestry, hydrology, for normal activity tracking but also in special situations caused by natural disasters. In this paper it is proposed a method for forestry surface evaluation in terms of occupied surface and also as number of trees. The segmentation method is based on watershed transform which offers good performances in case the objects to detect have connected borders. The method is applied for automatic multi-temporal analysis of forestry areas and represents a useful instrument for decision makers.
Jabez Christopher, J; Khanna Nehemiah, H; Kannan, A
Allergic Rhinitis is a universal common disease, especially in populated cities and urban areas. Diagnosis and treatment of Allergic Rhinitis will improve the quality of life of allergic patients. Though skin tests remain the gold standard test for diagnosis of allergic disorders, clinical experts are required for accurate interpretation of test outcomes. This work presents a clinical decision support system (CDSS) to assist junior clinicians in the diagnosis of Allergic Rhinitis. Intradermal Skin tests were performed on patients who had plausible allergic symptoms. Based on patient׳s history, 40 clinically relevant allergens were tested. 872 patients who had allergic symptoms were considered for this study. The rule based classification approach and the clinical test results were used to develop and validate the CDSS. Clinical relevance of the CDSS was compared with the Score for Allergic Rhinitis (SFAR). Tests were conducted for junior clinicians to assess their diagnostic capability in the absence of an expert. The class based Association rule generation approach provides a concise set of rules that is further validated by clinical experts. The interpretations of the experts are considered as the gold standard. The CDSS diagnoses the presence or absence of rhinitis with an accuracy of 88.31%. The allergy specialist and the junior clinicians prefer the rule based approach for its comprehendible knowledge model. The Clinical Decision Support Systems with rule based classification approach assists junior doctors and clinicians in the diagnosis of Allergic Rhinitis to make reliable decisions based on the reports of intradermal skin tests. Copyright © 2015 Elsevier Ltd. All rights reserved.
Full Text Available This article presents the architecture, features, and operating mode of a DSS (Decision Support System aiming to assist entrepreneurs and managers in the process of location decision making. The research assembled concepts derived from theory, findings of empirical studies, together with open GIS (Geographical Information System software and data, and modelled them into a DSS software tool, according to an original methodology and design. The users are guided step-by-step to input information on their businesses into the DSS (industry, preferences for land-use areas and facility types, weights of key location factors, and are returned two sets of results: one based on own options, and another one aggregate for the industry they operate in. The results consist in the top five locations for the user's firm, as well as for the industry, depicted both in a graphical report (map and a text report (explanation of results.
Meirina, Candra; Ruan, Sui; Yu, Feili; Zhu, Liang; Pattipati, Krishna R; Kleinman, David L
...) based on the third-generation distributed dynamic decision-making (DDD-III) simulator and contingency theory to increase the organizational cognitive capacity and to facilitate the processes of adaptation...
Adlassnig, Klaus-Peter; Fehre, Karsten; Rappelsberger, Andrea
This study's objective is to develop and use a scalable genuine technology platform for clinical decision support based on Arden Syntax, which was extended by fuzzy set theory and fuzzy logic. Arden Syntax is a widely recognized formal language for representing clinical and scientific knowledge in an executable format, and is maintained by Health Level Seven (HL7) International and approved by the American National Standards Institute (ANSI). Fuzzy set theory and logic permit the representation of knowledge and automated reasoning under linguistic and propositional uncertainty. These forms of uncertainty are a common feature of patients' medical data, the body of medical knowledge, and deductive clinical reasoning.
permettant de suivre la logique du système au moyen de l’argumentation. vi DRDC Valcartier TR 2008 - 088 Table of contents Abstract...Scientist c© Her Majesty the Queen in Right of Canada as represented by the Minister of National Defence, 2008 c© Sa Majesté la Reine (en droit du...Canada), telle que représentée par le ministre de la Défense nationale, 2008 Abstract This report describes an argumentation-based Decision Support
In the past 50 years, the military, communication, and transportation systems that permeate our world, have grown exponentially in size and complexity. The development and production of these systems has seen ballooning costs and increased risk. This is particularly critical for the aerospace industry. The inability to deal with growing system complexity is a crippling force in the advancement of engineered systems. Value-Driven Design represents a paradigm shift in the field of design engineering that has potential to help counteract this trend. The philosophy of Value-Driven Design places the desires of the stakeholder at the forefront of the design process to capture true preferences and reveal system alternatives that were never previously thought possible. Modern aerospace engineering design problems are large, complex, and involve multiple levels of decision-making. To find the best design, the decision-maker is often required to analyze hundreds or thousands of combinations of design variables and attributes. Visualization can be used to support these decisions, by communicating large amounts of data in a meaningful way. Understanding the design space, the subsystem relationships, and the design uncertainties is vital to the advancement of Value-Driven Design as an accepted process for the development of more effective, efficient, robust, and elegant aerospace systems. This research investigates the use of multi-dimensional data visualization tools to support decision-making under uncertainty during the Value-Driven Design process. A satellite design system comprising a satellite, ground station, and launch vehicle is used to demonstrate effectiveness of new visualization methods to aid in decision support during complex aerospace system design. These methods are used to facilitate the exploration of the feasible design space by representing the value impact of system attribute changes and comparing the results of multi-objective optimization formulations
Jackson, Cath; Cheater, Francine M.; Peacock, Rose; Leask, Julie; Trevena, Lyndal
Objective: The objective of this feasibility study was to evaluate the acceptability and potential effectiveness of a web-based MMR decision aid in supporting informed decision-making for the MMR vaccine. Design: This was a prospective before-and-after evaluation. Setting: Thirty parents of children eligible for MMR vaccination were recruited from…
In the US the evolution of automated decision support tools for plant operators has spanned from ''event-oriented'' diagnostic systems to ''symptom-oriented'' computer-based emergency operating procedures. A problem common to both kind of systems is in the initial level of effort required for development of the associated models and software. In the following we will discuss some of the general issues that arise in the development and application of these decision-support systems. We will also propose and discuss an approach founded on the application of an event diagnosis and plant stabilization philosophy. This approach is based on the use of logic flowgraph process-oriented models - arranged in a modular architecture and developed with the aid of an expert-system model builder - as a possible means of achieving the development of an automated and integrated plant management system. This approach should allow the developer to achieve a high process recovery and management capability with a focused and controlled expenditure of development time and resources
Gorsevski, Pece V.; Cathcart, Steven C.; Mirzaei, Golrokh; Jamali, Mohsin M.; Ye, Xinyue; Gomezdelcampo, Enrique
The purpose of this paper is to demonstrate the benefits of applying a spatial decision support system (SDSS) framework for evaluating the suitability for wind farm siting in Northwest Ohio. The multiple criteria evaluation (MCE) prototype system is intended for regional planning but also for promoting group decision making that could involve participants with different interests in the development of decision alternatives. The framework integrates environmental and economic criteria and builds a hierarchy for wind farm siting using weighted linear combination (WLC) techniques and GIS functionality. The SDSS allows the multiple participants to interact and develop an understanding of the spatial data for assigning importance values to each factor. The WLC technique is used to combine the assigned values with map layers, which are standardized using fuzzy set theory, to produce individual suitability maps. The maps created by personal preferences from the participants are aggregated for producing a group solution using the Borda method. Sensitivity analysis is performed on the group solution to examine how small changes in the factor weights affect the calculated suitability scores. The results from the sensitivity analysis are intended to aid understanding of compromised solutions through changes in the input data from the participant's perspective. - Highlights: ► We present a prototype tool that we developed for wind farm site selection. ► Multiple participants rank the factors for promoting group-based decision making. ► The factors are aggregated by WLC technique to generate maps from participants. ► Group-based solution uses Borda method to aggregate the maps from participants. ► Sensitivity analysis is performed on the group solution to examine solution affects
Jones, Vincent P; Brunner, Jay F; Grove, Gary G; Petit, Brad; Tangren, Gerald V; Jones, Wendy E
Integrated pest management (IPM) decision-making has become more information intensive in Washington State tree crops in response to changes in pesticide availability, the development of new control tactics (such as mating disruption) and the development of new information on pest and natural enemy biology. The time-sensitive nature of the information means that growers must have constant access to a single source of verified information to guide management decisions. The authors developed a decision support system for Washington tree fruit growers that integrates environmental data [140 Washington State University (WSU) stations plus weather forecasts from NOAA], model predictions (ten insects, four diseases and a horticultural model), management recommendations triggered by model status and a pesticide database that provides information on non-target impacts on other pests and natural enemies. A user survey in 2008 found that the user base was providing recommendations for most of the orchards and acreage in the state, and that users estimated the value at $ 16 million per year. The design of the system facilitates education on a range of time-sensitive topics and will make it possible easily to incorporate other models, new management recommendations or information from new sensors as they are developed.
Full Text Available In areas of medical diagnosis and decision-making, several uncertainty and ambiguity shrouded situations are most often imposed. In this regard, one may well assume that intuitionistic fuzzy sets (IFS should stand as a potent technique useful for demystifying associated with the real healthcare decision-making situations. To this end, we are developing a prototype model helpful for detecting the patients risk degree in Intensive Care Unit (ICU. Based on the intuitionistic fuzzy sets, dubbed Medical Intuitionistic Fuzzy Expert Decision Support System (MIFEDSS, the shown work has its origins in the Modified Early Warning Score (MEWS standard. It is worth noting that the proposed prototype effectiveness validation is associated through a real case study test at the Polyclinic ESSALEMA cited in Sfax, Tunisia. This paper does actually provide some practical initial results concerning the system as carried out in real life situations. Indeed, the proposed system turns out to prove that the MIFEDSS does actually display an imposing capability for an established handily ICU related uncertainty issues. The performance of the prototypes is compared with the MEWS standard which exposed that the IFS application appears to perform highly better in deferring accuracy than the expert MEWS score with higher degrees of sensitivity and specificity being recorded.
.... We solve the problem in two ways. First, we create a UAV Decision Support Tool (UAV DST) that uses a set of Java software objects to display maps and convert between latitude-longitude coordinates and x-y coordinates...
The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the human capabilities to perceive, evaluate and ultimately select a suitable solution. While performance prediction can be highly automated through the use of computers, performance evaluation cannot, unless it is with respect to a single criterion. The need to address multi-criteria requirements makes it more valuable for a designer to know the "latitude" or "degrees of freedom" he has in changing certain design variables while achieving preset criteria such as energy performance, life cycle cost, environmental impacts etc. This requirement can be met by a decision support framework based on near-optimal "satisficing" as opposed to purely optimal decision making techniques. Currently, such a comprehensive design framework is lacking, which is the basis for undertaking this research. The primary objective of this research is to facilitate a complementary relationship between designers and computers for Multi-Criterion Decision Making (MCDM) during high performance building design. It is based on the application of Monte Carlo approaches to create a database of solutions using deterministic whole building energy simulations, along with data mining methods to rank variable importance and reduce the multi-dimensionality of the problem. A novel interactive visualization approach is then proposed which uses regression based models to create dynamic interplays of how varying these important variables affect the multiple criteria, while providing a visual range or band of variation of the different design parameters. The MCDM process has been incorporated into an alternative methodology for high performance building design referred to as
Full Text Available In the last decade the development of the economical and social life increased the complexity of transportation systems. In this context, the role of Decision Support Systems (DSS became more and more important. The paper presents the characteristics, necessity, and usage of DSS in transportation and describes a practical application in the railroad field. To compute the optimal transportation capacity and flow on a certain railroad, specialized decision-support software which is available on the market was used.
Chen Dengke; Zhang Dafa; Jiang Wei; Chen Yonghong
Emergency decision-making to Marine Pressurized-Water Reactor (MPWR) was severely restricted by the complex environment. To enhance the emergency decision-making ability of MPWR, reducing the effect of emergencies, an emergency Decision-making Support System (DSS) which based on Multi-agent System (MAS) was presented. In the system, the HLA/RTI was used as the support environment, and the structure and the Control Agent (SCA), Analyse Agent (AA), Countermeasure Agent (CA), Evaluation Agent (EVA) and Environment Agent (ENA) were designed. The MAS were with the characteristics of autonomy, reactivity and initiative, which were fully used in the system to make effective decision for emergencies. (authors)
Chou, Wan-Yi; Tien, Peng-Tai; Lin, Fang-Yu; Chiu, Pin-Chi
Medical education has shifted from memory-based practice to evidence-based decisions. The question arises: how can we ensure that all students get correct and systematic information? Visually based, computerised diagnostic decision support system (VCDDSS, VisualDx) may just fit our needs. A pilot study was conducted to investigate its role in medical education and clinical practice. This was a prospective study, including one consultant dermatologist, 51 medical students and 13 dermatology residents, conducted in the dermatology teaching clinic at China Medical University Hospital from 30 December 2014 to 21 April 2015. Clinical diagnoses of 13 patients were made before and after using VCDDSS. Questionnaires were filled out at the end. The consultant dermatologist's diagnosis was defined as the standard answer; the Sign test was used to analyse diagnostic accuracy and the Fisher exact test to analyse questionnaires. There was an 18.75% increase in diagnostic accuracy after use of VCDDSS (62.5-81.25%; p value system in clinical practice, medical education, residency training, and patient education in the future. Further large-scale studies should be planned to confirm its application. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Full Text Available The vocational orientation of the youngsters who are about to enter, study, or have recently graduated at higher education (HE institutions, and linking HE with labor market are two research areas which have not been investigated extensively in Balkan countries. Job (or occupational profiles, among other tools used in vocational orientation, provide standardized and digitized descriptions of different professions. This article focuses on the analysis and the design of a web-based decision support system (DSS to assist its users in getting thoroughly informed about HE studies in Greece, and eventually in choosing their vocational prospects. Apart from reviewing the related previous research work and relevant web-based systems, we present the main elements of the system’s analysis and its design, the extensions that could lead to even more powerful systems, and conclusions about the advantages, limitations and practical application of the DSS.
Davidson, Rachel A; Nozick, Linda K; Wachtendorf, Tricia; Blanton, Brian; Colle, Brian; Kolar, Randall L; DeYoung, Sarah; Dresback, Kendra M; Yi, Wenqi; Yang, Kun; Leonardo, Nicholas
This article introduces a new integrated scenario-based evacuation (ISE) framework to support hurricane evacuation decision making. It explicitly captures the dynamics, uncertainty, and human-natural system interactions that are fundamental to the challenge of hurricane evacuation, but have not been fully captured in previous formal evacuation models. The hazard is represented with an ensemble of probabilistic scenarios, population behavior with a dynamic decision model, and traffic with a dynamic user equilibrium model. The components are integrated in a multistage stochastic programming model that minimizes risk and travel times to provide a tree of evacuation order recommendations and an evaluation of the risk and travel time performance for that solution. The ISE framework recommendations offer an advance in the state of the art because they: (1) are based on an integrated hazard assessment (designed to ultimately include inland flooding), (2) explicitly balance the sometimes competing objectives of minimizing risk and minimizing travel time, (3) offer a well-hedged solution that is robust under the range of ways the hurricane might evolve, and (4) leverage the substantial value of increasing information (or decreasing degree of uncertainty) over the course of a hurricane event. A case study for Hurricane Isabel (2003) in eastern North Carolina is presented to demonstrate how the framework is applied, the type of results it can provide, and how it compares to available methods of a single scenario deterministic analysis and a two-stage stochastic program. © 2018 Society for Risk Analysis.
Dhiman, R.; Kalbar, P.; Inamdar, A. B.
Coastal area classification in India is a challenge for federal and state government agencies due to fragile institutional framework, unclear directions in implementation of costal regulations and violations happening at private and government level. This work is an attempt to improvise the objectivity of existing classification methods to synergies the ecological systems and socioeconomic development in coastal cities. We developed a Geographic information system coupled Multi-criteria Decision Making (GIS-MCDM) approach to classify urban coastal areas where utility functions are used to transform the costal features into quantitative membership values after assessing the sensitivity of urban coastal ecosystem. Furthermore, these membership values for costal features are applied in different weighting schemes to derive Coastal Area Index (CAI) which classifies the coastal areas in four distinct categories viz. 1) No Development Zone, 2) Highly Sensitive Zone, 3) Moderately Sensitive Zone and 4) Low Sensitive Zone based on the sensitivity of urban coastal ecosystem. Mumbai, a coastal megacity in India is used as case study for demonstration of proposed method. Finally, uncertainty analysis using Monte Carlo approach to validate the sensitivity of CAI under specific multiple scenarios is carried out. Results of CAI method shows the clear demarcation of coastal areas in GIS environment based on the ecological sensitivity. CAI provides better decision support for federal and state level agencies to classify urban coastal areas according to the regional requirement of coastal resources considering resilience and sustainable development. CAI method will strengthen the existing institutional framework for decision making in classification of urban coastal areas where most effective coastal management options can be proposed.
Kalina, Jan; Zvárová, Jana
Roč. 4, č. 2 (2014), s. 53-65 ISSN 1947-3133 Grant - others:GA MŠk(CZ) ED2.1.00/03.0078 Institutional support: RVO:67985807 Keywords : big data * classification rule * decision support systems * e-health * mental health care Subject RIV: IN - Informatics, Computer Science
Greg Thoma; John Veil; Fred Limp; Jackson Cothren; Bruce Gorham; Malcolm Williamson; Peter Smith; Bob Sullivan
This report describes work performed during the initial period of the project 'Probabilistic Risk Based Decision Support for Oil and Gas Exploration and Production Facilities in Sensitive Ecosystems.' The specific region that is within the scope of this study is the Fayetteville Shale Play. This is an unconventional, tight formation, natural gas play that currently has approximately 1.5 million acres under lease, primarily to Southwestern Energy Incorporated and Chesapeake Energy Incorporated. The currently active play encompasses a region from approximately Fort Smith, AR east to Little Rock, AR approximately 50 miles wide (from North to South). The initial estimates for this field put it almost on par with the Barnett Shale play in Texas. It is anticipated that thousands of wells will be drilled during the next several years; this will entail installation of massive support infrastructure of roads and pipelines, as well as drilling fluid disposal pits and infrastructure to handle millions of gallons of fracturing fluids. This project focuses on gas production in Arkansas as the test bed for application of proactive risk management decision support system for natural gas exploration and production. The activities covered in this report include meetings with representative stakeholders, development of initial content and design for an educational web site, and development and preliminary testing of an interactive mapping utility designed to provide users with information that will allow avoidance of sensitive areas during the development of the Fayetteville Shale Play. These tools have been presented to both regulatory and industrial stakeholder groups, and their feedback has been incorporated into the project.
Full Text Available In today`s rapidly changing and globally volatile world, manufacturers pay strong efforts on conducting lean production, outsourcing their components, and management on the complex supply chain. Warehouse management plays a vital role to be a successful player in the any kinds of industry which put-away process is a key activity that brings significant influence and challenges to warehouse performance. In this dynamic operating environment, minimizing the operation mistakes and providing accurate real time inventory information to stakeholder become the basic requirements to be an order qualifier. An OLAP based intelligent system called Fuzzy Storage Assignment System (FSAS is proposed to increase availability of decision support data and convert the human knowledge into system for tackling the storage location assignment problem (SLAP. To validate the feasibility of this proposed system, a prototype will be worked out for a third party logistics company.
Full Text Available This paper develops a unified method to support contractor for bidding selection in construction projects. A cross-functional contractor with 28 candidate units distributed in the three departments (construction units, design units, and suppliers is used as an example. This problem is first formulated as a 0-1 quadratic programming problem through optimizing individual performance and collaborative performance of the candidate units based on individual information and collaborative information. Then, a multiobjective evolutionary algorithm is designed to solve this problem and a bidding selection problem for a major bridge project is used to demonstrate our proposed method. The results show that the decision-maker (DM obtains a better contractor if he pays more attention to collaborative performance.
Full Text Available Traditional techniques of data analysis do not enable the solution of all kind of problems and for that reason they have become insufficient. This caused a newinterdisciplinary field of data mining to arise, encompassing both classical statistical, and modern machine learning techniques to support the data analysis and knowledge discovery from data. Data mining methods are powerful in dealing with large quantities of data, but on the other hand they are difficult to master by business users to facilitate decision support. In this paper we introduce our approach to integration of decision support system with data mining. We discuss the role of data mining to facilitate decision support, the use of data mining methods in decision support systems, discuss applied approaches and introduce a data mining decision support system called DMDSS - Data Mining Decision Support System. We also present some obtained results and plans for future development.
Terribile, F.; Agrillo, A.; Bonfante, A.; Buscemi, G.; Colandrea, M.; D'Antonio, A.; De Mascellis, R.; De Michele, C.; Langella, G.; Manna, P.; Marotta, L.; Mileti, F. A.; Minieri, L.; Orefice, N.; Valentini, S.; Vingiani, S.; Basile, A.
Today it is evident that there are many contrasting demands on our landscape (e.g. food security, more sustainable agriculture, higher income in rural areas, etc.) as well as many land degradation problems. It has been proved that providing operational answers to these demands and problems is extremely difficult. Here we aim to demonstrate that a spatial decision support system based on geospatial cyberinfrastructure (GCI) can address all of the above, so producing a smart system for supporting decision making for agriculture, forestry, and urban planning with respect to the landscape. In this paper, we discuss methods and results of a special kind of GCI architecture, one that is highly focused on land management and soil conservation. The system allows us to obtain dynamic, multidisciplinary, multiscale, and multifunctional answers to agriculture, forestry, and urban planning issues through the Web. The system has been applied to and tested in an area of about 20 000 ha in the south of Italy, within the framework of a European LIFE+ project (SOILCONSWEB). The paper reports - as a case study - results from two different applications dealing with agriculture (olive growth tool) and environmental protection (soil capability to protect groundwater). Developed with the help of end users, the system is starting to be adopted by local communities. The system indirectly explores a change of paradigm for soil and landscape scientists. Indeed, the potential benefit is shown of overcoming current disciplinary fragmentation over landscape issues by offering - through a smart Web-based system - truly integrated geospatial knowledge that may be directly and freely used by any end user (www.landconsultingweb.eu). This may help bridge the last very important divide between scientists working on the landscape and end users.
Terribile, F.; Agrillo, A.; Bonfante, A.; Buscemi, G.; Colandrea, M.; D'Antonio, A.; De Mascellis, R.; De Michele, C.; Langella, G.; Manna, P.; Marotta, L.; Mileti, F. A.; Minieri, L.; Orefice, N.; Valentini, S.; Vingiani, S.; Basile, A.
Today it is evident that there are many contrasting demands on our landscape (e.g. food security, more sustainable agriculture, higher income in rural areas, etc.) but also many land degradation problems. It has been proved that providing operational answers to these demands and problems is extremely difficult. Here we aim to demonstrate that a Spatial Decision Support System based on geospatial cyber-infrastructure (GCI) can embody all of the above, so producing a smart system for supporting decision making for agriculture, forestry and urban planning with respect to the landscape. In this paper, we discuss methods and results of a special kind of GCI architecture, one that is highly focused on soil and land conservation (SOILCONSWEB-LIFE+ project). The system allows us to obtain dynamic, multidisciplinary, multiscale, and multifunctional answers to agriculture, forestry and urban planning issues through the web. The system has been applied to and tested in an area of about 20 000 ha in the South of Italy, within the framework of a European LIFE+ project. The paper reports - as a case study - results from two different applications dealing with agriculture (olive growth tool) and environmental protection (soil capability to protect groundwater). Developed with the help of end users, the system is starting to be adopted by local communities. The system indirectly explores a change of paradigm for soil and landscape scientists. Indeed, the potential benefit is shown of overcoming current disciplinary fragmentation over landscape issues by offering - through a smart web based system - truly integrated geospatial knowledge that may be directly and freely used by any end user (http://www.landconsultingweb.eu). This may help bridge the last much important divide between scientists working on the landscape and end users.
Tweddle, J. F.; Byg, A.; Davies, I.; Gubbins, M.; Irvine, K.; Kafas, A.; Kenter, J.; MacDonald, A.; Murray, R. B. O.; Potts, T.; Slater, A. M.; Wright, K.; Scott, B. E.
The marine environment is under increasing use, putting pressure on marine ecosystems and increasing competition for space. New activities (e.g. renewable energy developments), evolving marine policies (e.g. implementation of marine protected areas), and climate change may drive changes in biodiversity and resulting ecosystem services (ES) that society and business utilise from coastal and marine systems. A process is needed that integrates ecological assessment of changes with stakeholder perceptions and valuation of ES, whilst balancing ease of application with the ability to deal with complex social-economic-ecological issues. The project "Cooperative participatory assessment of the impact of renewable technology on ecosystem services: CORPORATES" involved natural and social scientists, law and policy experts, and marine managers, with the aim of promoting more integrated decision making using ES concepts in marine management. CORPORATES developed a process to bring ES concepts into stakeholders' awareness. The interactive process, involving 2 workshops, employs interludes of knowledge exchange by experts on ecological processes underpinning ES and on law and policy. These enable mapping of benefits linked to activities, participatory system modelling, and deliberation of policy impacts on different sectors. The workshops were attended by industry representatives, regulatory/advisory partners, and other stakeholders (NGOs, SMEs, recreationalists, local government). Mixed sector groups produced new insights into links between activities and ES, and highlighted cross-sector concerns. Here we present the aspects of the process that successfully built shared understanding between industry and stakeholders of inter-linkages and interactions between ES, benefits, activities, and economic and cultural values. These methods provide an ES-based decision-support model for exchanging societal-ecological knowledge and providing stakeholder interaction in marine planning
Samwald, Matthias; Miñarro Giménez, Jose Antonio; Boyce, Richard D; Freimuth, Robert R; Adlassnig, Klaus-Peter; Dumontier, Michel
Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured formalizations. This is a source of potential ambiguity and complexity, making it difficult to create reliable information technology systems for enabling clinical pharmacogenomics. We developed Web Ontology Language (OWL) ontologies and automated reasoning methodologies to meet the following goals: 1) provide a simple and concise formalism for representing pharmacogenomic knowledge, 2) finde errors and insufficient definitions in pharmacogenomic knowledge bases, 3) automatically assign alleles and phenotypes to patients, 4) match patients to clinically appropriate pharmacogenomic guidelines and clinical decision support messages and 5) facilitate the detection of inconsistencies and overlaps between pharmacogenomic treatment guidelines from different sources. We evaluated different reasoning systems and test our approach with a large collection of publicly available genetic profiles. Our methodology proved to be a novel and useful choice for representing, analyzing and using pharmacogenomic data. The Genomic Clinical Decision Support (Genomic CDS) ontology represents 336 SNPs with 707 variants; 665 haplotypes related to 43 genes; 22 rules related to drug-response phenotypes; and 308 clinical decision support rules. OWL reasoning identified CDS rules with overlapping target populations but differing treatment recommendations. Only a modest number of clinical decision support rules were triggered for a collection of 943 public genetic profiles. We found significant performance differences across available OWL reasoners. The ontology-based framework we developed can be used to represent, organize and reason over the growing wealth of
Brodin, N. Patrik; Maraldo, Maja V.; Aznar, Marianne C.
PURPOSE: To present a novel tool that allows quantitative estimation and visualization of the risk of various relevant normal tissue endpoints to aid in treatment plan comparison and clinical decision making in radiation therapy (RT) planning for Hodgkin lymphoma (HL). METHODS AND MATERIALS...... and a volumetric modulated arc therapy plan for a patient with mediastinal HL. CONCLUSION: This multiple-endpoint decision-support tool provides quantitative risk estimates to supplement the clinical judgment of the radiation oncologist when comparing different RT options....
Full Text Available Talking about Big Data in healthcare we usually refer to how to use data collected from current electronic medical records, either structured or unstructured, to answer clinically relevant questions. This operation is typically carried out by means of analytics tools (e.g. machine learning or by extracting relevant data from patient summaries through natural language processing techniques. From other perspective of research in medical informatics, powerful initiatives have emerged to help physicians taking decisions, in both diagnostics and therapeutics, built from the existing medical evidence (i.e. knowledge-based decision support systems. Much of the problems these tools have shown, when used in real clinical settings, are related to their implementation and deployment, more than failing in its support, but, technology is slowly overcoming interoperability and integration issues. Beyond the point-of-care decision support these tools can provide, the data generated when using them, even in controlled trials, could be used to further analyze facts that are traditionally ignored in the current clinical practice. In this paper, we reflect on the technologies available to make the leap and how they could help driving healthcare organizations shifting to a value-based healthcare philosophy.
One way to frame the job of planetary defense is to “find the optimal approach for finding the optimal approach” to NEO mitigation. This requires a framework for defining in advance what should be done under various circumstances. The two-dimensional action matrix from the recent NRC report “Defending Planet Earth” can be generalized to a notional “Impact Decision Support Diagram” by extending it into a third dimension. The NRC action matrix incorporated two important axes: size and time-to-impact, but probability of impact is also critical (it is part of the definitions of both the Torino and Palermo scales). Uncertainty has been neglected, but is also crucial. It can be incorporated by subsuming it into the NEO size axis by redefining size to be three standard deviations greater than the best estimate, thereby providing a built-in conservative margin. The independent variable is time-to-impact, which is known with high precision. The other two axes are both quantitative assessments of uncertainty and are both time dependent. Thus, the diagram is entirely an expression of uncertainty. The true impact probability is either one or zero, and the true size does not change. The domain contains information about the current uncertainty, which changes with time (as opposed to reality, which does not change).
Aye, Zar Chi; Olyazadeh, Roya; Jaboyedoff, Michel; Derron, Marc-Henri
This paper discusses the proposed background architecture and prototype development of an internet-based decision support system (DSS) in the field of natural hazards and risk management using open-source geospatial software and web technologies. It is based on a three-tier, client-server architecture with the support of boundless (opengeo) framework and its client side SDK application environment using customized gxp components and data utility classes. The main purpose of the system is to integrate the workflow of risk management systematically with the diverse involvement of stakeholders from different organizations dealing with natural hazards and risk for evaluation of management measures through the active online participation approach. It aims to develop an adaptive user friendly, web-based environment that allows the users to set up risk management strategies based on actual context and data by integrating web-GIS and DSS functionality associated with process flow and other visualization tools. Web-GIS interface has been integrated within the DSS to deliver maps and provide certain geo-processing capabilities on the web, which can be easily accessible and shared by different organizations located in case study sites of the project. This platform could be envisaged not only as a common web-based platform for the centralized sharing of data such as hazard maps, elements at risk maps and additional information but also to ensure an integrated platform of risk management where the users could upload data, analyze risk and identify possible alternative scenarios for risk reduction especially for floods and landslides, either quantitatively or qualitatively depending on the risk information provided by the stakeholders in case study regions. The level of involvement, access to and interaction with the provided functionality of the system varies depending on the roles and responsibilities of the stakeholders, for example, only the experts (planners, geological
The International Journal of Multicriteria Decision Making describing the Triage Method • Chapter 4 contains a paper published in 2014 in The...International Journal of Multicriteria Decision Making describing extensions to the Triage Method to consider resource constraints • Chapter 5 contains a...was under review by The International Journal of Multicriteria Decision Making 7 • Chapter 6 contains a paper describing methods for eliciting
Full Text Available Abstract Background We introduce a Knowledge-based Decision Support System (KDSS in order to face the Protein Complex Extraction issue. Using a Knowledge Base (KB coding the expertise about the proposed scenario, our KDSS is able to suggest both strategies and tools, according to the features of input dataset. Our system provides a navigable workflow for the current experiment and furthermore it offers support in the configuration and running of every processing component of that workflow. This last feature makes our system a crossover between classical DSS and Workflow Management Systems. Results We briefly present the KDSS' architecture and basic concepts used in the design of the knowledge base and the reasoning component. The system is then tested using a subset of Saccharomyces cerevisiae Protein-Protein interaction dataset. We used this subset because it has been well studied in literature by several research groups in the field of complex extraction: in this way we could easily compare the results obtained through our KDSS with theirs. Our system suggests both a preprocessing and a clustering strategy, and for each of them it proposes and eventually runs suited algorithms. Our system's final results are then composed of a workflow of tasks, that can be reused for other experiments, and the specific numerical results for that particular trial. Conclusions The proposed approach, using the KDSS' knowledge base, provides a novel workflow that gives the best results with regard to the other workflows produced by the system. This workflow and its numeric results have been compared with other approaches about PPI network analysis found in literature, offering similar results.
Banias, G; Achillas, Ch; Vlachokostas, Ch; Moussiopoulos, N; Papaioannou, I
Wastes from construction activities constitute nowadays the largest by quantity fraction of solid wastes in urban areas. In addition, it is widely accepted that the particular waste stream contains hazardous materials, such as insulating materials, plastic frames of doors, windows, etc. Their uncontrolled disposal result to long-term pollution costs, resource overuse and wasted energy. Within the framework of the DEWAM project, a web-based Decision Support System (DSS) application - namely DeconRCM - has been developed, aiming towards the identification of the optimal construction and demolition waste (CDW) management strategy that minimises end-of-life costs and maximises the recovery of salvaged building materials. This paper addresses both technical and functional structure of the developed web-based application. The web-based DSS provides an accurate estimation of the generated CDW quantities of twenty-one different waste streams (e.g. concrete, bricks, glass, etc.) for four different types of buildings (residential, office, commercial and industrial). With the use of mathematical programming, the DeconRCM provides also the user with the optimal end-of-life management alternative, taking into consideration both economic and environmental criteria. The DSS's capabilities are illustrated through a real world case study of a typical five floor apartment building in Thessaloniki, Greece. Copyright © 2011 Elsevier Ltd. All rights reserved.
Gilliams, S.; Orshoven, van J.; Muys, B.; Kros, J.; Heil, G.W.; Deursen, van W.
The concept and structure of the Spatial Decision Support System AFFOREST sDSS dealing with environmental performance (EP) of afforestation on agricultural land in northwestern Europe, is presented. EP is defined in terms of three environmental impact categories: (1) carbon sequestration (2)
Haas, T.C.; Maigan, M.; Arutyunyan, R.V.; Bolshov, L.A.; Demianov, V.V.
The report deals with description of the concept and prototype of environmental decision support system (EDSS) for the analysis of late off-site consequences of severe nuclear accidents and analysis, processing and presentation of spatially distributed radioecological data. General description of the available software, use of modem achievements of geostatistics and stochastic simulations for the analysis of spatial data are presented and discussed
Adler, Richard M.; Koehn, David J.
Guiding organizations through transformational changes such as restructuring or adopting new technologies is a daunting task. Such changes generate workforce uncertainty, fear, and resistance, reducing morale, focus and performance. Conventional project management techniques fail to mitigate these disruptive effects, because social and individual changes are non-mechanistic, organic phenomena. CALM (for Change, Adaptation, Learning Model) is an innovative decision support system for enabling change based on CAS principles. CALM provides a low risk method for validating and refining change strategies that combines scenario planning techniques with "what-if" behavioral simulation. In essence, CALM "test drives" change strategies before rolling them out, allowing organizations to practice and learn from virtual rather than actual mistakes. This paper describes the CALM modeling methodology, including our metrics for measuring organizational readiness to respond to change and other major CALM scenario elements: prospective change strategies; alternate futures; and key situational dynamics. We then describe CALM's simulation engine for projecting scenario outcomes and its associated analytics. CALM's simulator unifies diverse behavioral simulation paradigms including: adaptive agents; system dynamics; Monte Carlo; event- and process-based techniques. CALM's embodiment of CAS dynamics helps organizations reduce risk and improve confidence and consistency in critical strategies for enabling transformations.
Saito, Yoshihito; Matsuo, Tokuro
Education institutions such as universities have a lot of information including book information, equipment administrative information, student information, and several others. The institutions also have multiple information in time series. As collective intelligence in campus, integrating and reusing these preserved information regarding career and taking a class, university can effectively support students' decision making of their getting jobs and subjects choice. Our purpose of support is to increase student's motivation. In this paper, we focus on course record and job information included in students' information, and propose the method to analyze correlation between a pattern of taking class and job lined up. Afterwards, we propose a support system regarding getting a job and taking class by using our proposed method. For a student who has his/her favorite job to get, the system supports his/her decision making of lecture choice by recommending a set of appropriate lecture groups. On another hand, for a student who does not have favorite job to get, the system supports his/her decision making of getting job by presenting appropriate job families related with lecture group in which he/she has ever taken. The contribution of this paper is showing a concrete method to reuse the campus collective information, implementing a system, and user perspectives.
Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza
Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15
Schnase, John; Carroll, Mark; Gill, Roger; Wooten, Margaret; Weber, Keith; Blair, Kindra; May, Jeffrey; Toombs, William
NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.
Jeffery, Alvin D; Novak, Laurie L; Kennedy, Betsy; Dietrich, Mary S; Mion, Lorraine C
To describe nurses' preferences for the design of a probability-based clinical decision support (PB-CDS) tool for in-hospital clinical deterioration. A convenience sample of bedside nurses, charge nurses, and rapid response nurses (n = 20) from adult and pediatric hospitals completed participatory design sessions with researchers in a simulation laboratory to elicit preferred design considerations for a PB-CDS tool. Following theme-based content analysis, we shared findings with user interface designers and created a low-fidelity prototype. Three major themes and several considerations for design elements of a PB-CDS tool surfaced from end users. Themes focused on "painting a picture" of the patient condition over time, promoting empowerment, and aligning probability information with what a nurse already believes about the patient. The most notable design element consideration included visualizing a temporal trend of the predicted probability of the outcome along with user-selected overlapping depictions of vital signs, laboratory values, and outcome-related treatments and interventions. Participants expressed that the prototype adequately operationalized requests from the design sessions. Participatory design served as a valuable method in taking the first step toward developing PB-CDS tools for nurses. This information about preferred design elements of tools that support, rather than interrupt, nurses' cognitive workflows can benefit future studies in this field as well as nurses' practice. Published by Oxford University Press on behalf of the American Medical Informatics Association 2017. This work is written by US Government employees and is in the public domain in the United States.
Lobach, David F; Johns, Ellis B; Halpenny, Barbara; Saunders, Toni-Ann; Brzozowski, Jane; Del Fiol, Guilherme; Berry, Donna L; Braun, Ilana M; Finn, Kathleen; Wolfe, Joanne; Abrahm, Janet L; Cooley, Mary E
Management of uncontrolled symptoms is an important component of quality cancer care. Clinical guidelines are available for optimal symptom management, but are not often integrated into the front lines of care. The use of clinical decision support (CDS) at the point-of-care is an innovative way to incorporate guideline-based symptom management into routine cancer care. The objective of this study was to develop and evaluate a rule-based CDS system to enable management of multiple symptoms in lung cancer patients at the point-of-care. This study was conducted in three phases involving a formative evaluation, a system evaluation, and a contextual evaluation of clinical use. In Phase 1, we conducted iterative usability testing of user interface prototypes with patients and health care providers (HCPs) in two thoracic oncology clinics. In Phase 2, we programmed complex algorithms derived from clinical practice guidelines into a rules engine that used Web services to communicate with the end-user application. Unit testing of algorithms was conducted using a stack-traversal tree-spanning methodology to identify all possible permutations of pathways through each algorithm, to validate accuracy. In Phase 3, we evaluated clinical use of the system among patients and HCPs in the two clinics via observations, structured interviews, and questionnaires. In Phase 1, 13 patients and 5 HCPs engaged in two rounds of formative testing, and suggested improvements leading to revisions until overall usability scores met a priori benchmarks. In Phase 2, symptom management algorithms contained between 29 and 1425 decision nodes, resulting in 19 to 3194 unique pathways per algorithm. Unit testing required 240 person-hours, and integration testing required 40 person-hours. In Phase 3, both patients and HCPs found the system usable and acceptable, and offered suggestions for improvements. A rule-based CDS system for complex symptom management was systematically developed and tested. The
V. A. Rybak
Full Text Available A new technology of intelligent decision support on Forex, including forming algorithms of trading signals, rules for the training sample based on technical indicators, which have the highest correlation with the price, the method of reducing the number of losing trades, is proposed. The last is based on an analysis of the wave structure of the market, while the beginning of the cycle (the wave number one is offered to be identified using Bill Williams Oscillator (Awesome oscillator. The process chain of constructing neuro-fuzzy model using software package MatLab is described.
Kahn, Charles E
Many computer applications have been developed in radiology and other medical disciplines to help physicians make decisions. Artificial intelligence (AI)--an approach to computer-based manipulation of symbols to simulate human reasoning--forms the basis of many of these systems. This article's goals are to: acquaint the reader with the motivations and opportunities for computer-based medical decision support systems; identify AI techniques and applications in radiology decision making; assess the impact of these technologies; and consider new directions and opportunities for AI in radiology. Among the exciting new directions is the use of AI to integrate radiology reporting, online decision support, and just-in-time learning to provide useful information and continuing education that is embedded within a radiologist's daily workflow.
Cannata, Massimiliano; Antonovic, Milan; Pozzoni, Maurizio; Graf, Andrea
The Locarno area (Switzerland, Canton Ticino) is exposed to lacual floods with a return period of about 7-8 years. The risk is of particular concern because the area is located in a floodplain that registered in the last decades a great increase in settlement and values of the real estates. Moreover small differences in lake altitude may produce a significant increase in flooded area due to the very low average slope of the terrain. While fatalities are not generally registered, several important economic costs are associated, e.g.: damages to real estates, interruption of activities, evacuation and relocation and environmental damages. While important events were registered in 1978, 1993, 2000, 2002 and 2014 the local stakeholder invested time and money in the set-up of an up-to-date decision support system that allows for the reduction of risks. Thanks to impressive technological advances the visionary concept of the Digital Earth (Gore 1992, 1998) is being realizing: geospatial coverages and monitoring systems data are increasingly available on the Web, and more importantly, in a standard format. As a result, today is possible to develop innovative decision support systems (Molinari et al. 2013) which mesh-up several information sources and offers special features for risk scenarios evaluation. In agreement with the exposed view, the authors have recently developed a new Web system whose design is based on the Service Oriented Architecture pattern. Open source software (e.g.: Geoserver, PostGIS, OpenLayers) has been used throughout the whole system and geospatial Open Standards (e.g.: SOS, WMS, WFS) are the pillars it rely on. SITGAP 2.0, implemented in collaboration with the Civil protection of Locarno e Vallemaggia, combines a number of data sources such as the Federal Register of Buildings and Dwellings, the Cantonal Register of residents, the Cadastral Surveying, the Cantonal Hydro-meteorological monitoring observations, the Meteoswiss weather forecasts, and
Fritz Bradley Keith
Full Text Available Droplet size, which is affected by nozzle type, nozzle setups and operation, and spray solution, is one of the most critical factors influencing spray performance, environment pollution, food safety, and must be considered as part of any application scenario. Characterizing spray nozzles can be a timely and expensive proposition if the entire operational space (all combinations of spray pressure and orifice size, what influence flow rate is to be evaluated. This research proposes a structured, experimental design that allows for the development of computational models for droplet size based on any combination of a nozzle’s potential operational settings. The developed droplet size determination model can be used as Decision Support System (DSS for precise selection of sprayer working parameters to adapt to local field scenarios. Five nozzle types (designs were evaluated across their complete range of orifice size (flow rate* and spray pressures using a response surface experimental design. Several of the models showed high level fits of the modeled to the measured data while several did not as a result of the lack of significant effect from either orifice size (flow rate* or spray pressure. The computational models were integrated into a spreadsheet based user interface for ease of use. The proposed experimental design provides for efficient nozzle evaluations and development of computational models that allow for the determination of droplet size spectrum and spraying classification for any combination of a given nozzle’s operating settings. The proposed DSS will allow for the ready assessment and modification of a sprayers performance based on the operational settings, to ensure the application is made following recommendations in plant protection products (PPP labels.
Nannings, B.; Abu-Hanna, A.
OBJECTIVES: Decision Support Telemedicine Systems (DSTS) are at the intersection of two disciplines: tele-medicine and clinical decision support systems (CDSS). The objective of this paper is to provide a set of characterizing properties for DSTSs. This characterizing property set (CPS) can be used
Gomez, Jorge; Garrido, Leonardo; Perez, Francisco
Intelligent Decision-Making Support Systems (i-DMSS) are specialized IT-based systems that support some or several phases of the individual, team, organizational or inter-organizational decision making process by deploying some or several intelligent mechanisms. This book pursues the following academic aims: (i) generate a compendium of quality theoretical and applied contributions in Intelligent Decision-Making Support Systems (i-DMSS) for engineering and management IT-based service systems (ITSS); (ii) diffuse scarce knowledge about foundations, architectures and effective and efficient methods and strategies for successfully planning, designing, building, operating, and evaluating i-DMSS for ITSS, and (iii) create an awareness of, and a bridge between ITSS and i-DMSS academicians and practitioners in the current complex and dynamic engineering and management ITSS organizational. The book presents a collection of 11 chapters referring to relevant topics for both IT service systems and i-DMSS including: pr...
Zhang, Xinxin; Lind, Morten; Ravn, Ole
For complex engineering systems, there is an increasing demand forsafety and reliability. Decision support system (DSS) is designed to offersupervision and analysis about operational situations. A proper modelrepresentation is required for DSS to understand the process knowledge.Multilevel flow m...... available techniques of MFM reasoning and less matureyet relevant MFM concepts are considered. It also offers an architecture designof task organisation for MFM software tools by using the concept of agent andtechnology of multiagent software system...
Zhang, Xinxin; Lind, Morten; Ravn, Ole
For complex engineering systems, there is an increasing demand for safety and reliability. Decision support system (DSS) is designed to offer su-pervision and analysis about operational situations. A proper model representa-tion is required for DSS to understand the process knowledge. Multilevel ...... techniques of MFM reasoning and less mature yet relevant MFM concepts are considered. It also offers an architecture design of task organization for MFM software tools by using the concept of agent and technology of multiagent software system....
van Gasselt, Stephan; Nass, Andrea
The increase of surface coverage and the availability and accessibility of planetary data allow researchers and engineers to remotely perform detailed studies on surface processes and properties, in particular on objects such as Mars and the Moon for which Terabytes of multi-temporal data at multiple spatial resolution levels have become available during the last 15 years. Orbiters, rovers and landers have been returning information and insights into the surface evolution of the terrestrial planets in unprecedented detail. While rover- and lander-based analyses are one major research aim to obtain ground truth, resource exploration or even potential establishment of bases using autonomous platforms are others and they require detailed investigation of settings in order to identify spots on the surface that are suitable for spacecraft to land and operate safely and over a long period of time. What has been done using hardcopy material in the past is today being carried by using either in-house developments or off-the-shelf spatial information system technology which allows to manage, integrate and analyse data as well as visualize and create user-defined reports for performing assessments. Usually, such analyses can be broken down (manually) by considering scientific wishes, engineering boundary conditions, potential hazards and various tertiary constraints. We here (1) review standard tasks of landing site analyses, (2) discuss issues inherently related to the analysis using integrated spatial analysis systems and (3) demonstrate a modular analysis framework for integration of data and for the evaluation of results from individual tasks in order to support decisions for landing-site selection.
The purposes of this review are to examine the types of clinical decision support systems in use and to identify patterns of how critical care advanced practice nurses (APNs) have integrated these systems into their nursing care patient management practices. The decision-making process itself is analyzed with a focus on how automated systems attempt to capture and reflect human decisional processes in critical care nursing, including how systems actually organize and process information to create outcome estimations based on patient clinical indicators and prognosis logarithms. Characteristics of APN clinicians and implications of these characteristics on decision system use, based on the body of decision system user research, are introduced. A review of the Medline, Ovid, CINAHL, and PubMed literature databases was conducted using "clinical decision support systems,"computerized clinical decision making," and "APNs"; an examination of components of several major clinical decision systems was also undertaken. Use patterns among APNs and other clinicians appear to vary; there is a need for original research to examine how APNs actually use these systems in their practices in critical care settings. Because APNs are increasingly responsible for admission to, and transfer from, critical care settings, more understanding is needed on how they interact with this technology and how they see automated decision systems impacting their practices. APNs who practice in critical care settings vary significantly in how they use the clinical decision systems that are in operation in their practice settings. These APNs must have an understanding of their use patterns with these systems and should critically assess whether their patient care decision making is affected by the technology.
Full Text Available Recently increasing attention has been paid to complementing environmental Life Cycle Assessment (LCA with social aspects. The paper discusses the selection of social impacts and indicators from existing frameworks like Social Life Cycle Assessment (SLCA and Social Impact Assessment (SIA. Two ongoing case studies, addressing sustainability assessment within decision support, were considered: (1 Integrated Water Resources Management (IWRM in Indonesia; and (2 Integrated Packaging Waste Management in Spain and Portugal (FENIX. The focus was put on social impacts occurring due to decisions within these systems, such as choice of technologies, practices or suppliers. Thus, decision makers—here understood as intended users of the studies’ results—are not consumers that buy (or do not buy a product, such as in recent SLCA case-studies, but mainly institutions that decide about the design of the water or packaging waste management system. Therefore, in the FENIX project, a list of social impacts identified from literature was sent to the intended users to be ranked according to their priorities. Finally, the paper discusses to what extent the entire life cycle is reflected in SLCA impact categories and indicators, and explains how both life-cycle and on-site-related social impacts were chosen to be assessed. However, not all indicators in the two projects will assess all stages of the life cycle, because of their varying relevance in the different stages, data availability and practical interest of decision makers.
Dövényi-Nagy, Tamás; Bakó, Károly; Molnár, Krisztina; Rácz, Csaba; Vasvári, Gyula; Nagy, János; Dobos, Attila
The significant changes in the structure of ownership and control of irrigation infrastructure in the past decades resultted in the decrease of total irrigable and irrigated area (Szilárd, 1999). In this paper, the development of a model-based online service is described whose aim is to aid reasonable irrigation practice and increase water use efficiency. In order to establish a scientific background for irrigation, an agrometeorological station network has been built up by the Agrometeorological and Agroecological Monitoring Centre. A website has been launched in order to provide direct access for local agricultural producers to both the measured weather parameters and results of model based calculations. The public site provides information for general use, registered partners get a handy model based toolkit for decision support at the plot level concerning irrigation, plant protection or frost forecast. The agrometeorological reference station network was established in the recent years by the Agrometeorological and Agroecological Monitoring Centre and is distributed to cover most of the irrigated cropland areas of Hungary. From the spatial aspect, the stations have been deployed mainly in Eastern Hungary with concentrated irrigation infrastructure. The meteorological stations' locations have been carefully chosen to represent their environment in terms of soil, climatic and topographic factors, thereby assuring relevant and up-to-date input data for the models. The measured parameters range from classic meteorological data (air temperature, relative humidity, solar irradiation, wind speed etc.) to specific data which are not available from other services in the region, such as soil temperature, soil water content in multiple depths and leaf wetness. In addition to the basic grid of reference stations, specific stations under irrigated conditions have been deployed to calibrate and validate the models. A specific modeling framework (MetAgro) has been developed
Chen, Qingxiao; Wu, Ji; Li, Shusen; Lyu, Peijun; Wang, Yong; Li, Miao
We present the initial work toward developing a clinical decision support model for specific design of removable partial dentures (RPDs) in dentistry. We developed an ontological paradigm to represent knowledge of a patient’s oral conditions and denture component parts. During the case-based reasoning process, a cosine similarity algorithm was applied to calculate similarity values between input patients and standard ontology cases. A group of designs from the most similar cases were output as the final results. To evaluate this model, the output designs of RPDs for 104 randomly selected patients were compared with those selected by professionals. An area under the curve of the receiver operating characteristic (AUC-ROC) was created by plotting true-positive rates against the false-positive rate at various threshold settings. The precision at position 5 of the retrieved cases was 0.67 and at the top of the curve it was 0.96, both of which are very high. The mean average of precision (MAP) was 0.61 and the normalized discounted cumulative gain (NDCG) was 0.74 both of which confirmed the efficient performance of our model. All the metrics demonstrated the efficiency of our model. This methodology merits further research development to match clinical applications for designing RPDs. This paper is organized as follows. After the introduction and description of the basis for the paper, the evaluation and results are presented in Section 2. Section 3 provides a discussion of the methodology and results. Section 4 describes the details of the ontology, similarity algorithm, and application.
Fabri Simon G
Full Text Available Abstract Background In this work we consider hidden signs (biomarkers in ongoing EEG activity expressing epileptic tendency, for otherwise normal brain operation. More specifically, this study considers children with controlled epilepsy where only a few seizures without complications were noted before starting medication and who showed no clinical or electrophysiological signs of brain dysfunction. We compare EEG recordings from controlled epileptic children with age-matched control children under two different operations, an eyes closed rest condition and a mathematical task. The aim of this study is to develop reliable techniques for the extraction of biomarkers from EEG that indicate the presence of minor neurophysiological signs in cases where no clinical or significant EEG abnormalities are observed. Methods We compare two different approaches for localizing activity differences and retrieving relevant information for classifying the two groups. The first approach focuses on power spectrum analysis whereas the second approach analyzes the functional coupling of cortical assemblies using linear synchronization techniques. Results Differences could be detected during the control (rest task, but not on the more demanding mathematical task. The spectral markers provide better diagnostic ability than their synchronization counterparts, even though a combination (or fusion of both is needed for efficient classification of subjects. Conclusions Based on these differences, the study proposes concrete biomarkers that can be used in a decision support system for clinical validation. Fusion of selected biomarkers in the Theta and Alpha bands resulted in an increase of the classification score up to 80% during the rest condition. No significant discrimination was achieved during the performance of a mathematical subtraction task.
Fung, L.S.N.; Jones, Valerie M.; Bults, Richard G.A.; Hermens, Hermanus J.
We present a mobile decision support system (mDSS) which helps patients adhere to best clinical practice by providing pervasive and evidence-based health guidance via their smartphones. Similar to some existing clinical DSSs, the mDSS is designed to execute clinical guidelines, but it operates on
Keith M. Reynolds; Edward H. Holsten
SBexpert version 2.0 is a knowledge-based decision-support system for spruce beetle (Dendroctonus rufipennis (Kby.)) management developed for use in Microsoft (MS) Windows with the KnowledgePro Windows development language. Version 2.0 is a significant enhancement of version 1.0. The SBexpert users guide provides detailed instructions on the use of...
Keith M. Reynolds; Edward H. Holsten; Richard A. Werner
SBexpert version 1.0 is a knowledge-based decision-support system for spruce beetle (Dendroctonus rutipennis (Kby.)) management developed for use in Microsoft Windows with the KnowledgePro Windows development language. The SBexpert users guide provides detailed instructions on the use of all SBexpert features. SBexpert has four main topics (...
Adewale Opeoluwa Ogunde
Full Text Available Precision agriculture in recent times had assumed a different dimension in order to improve on the poor standard of agriculture. Similarly, the upsurge in technological advancement, most especially in the aspect of machine learning and artificial intelligence, is a promising trend towards a positive solution to this problem. Therefore, this research work presents a decision support system for analyzing and mining knowledge from soil data with respect to its suitability for cassava cultivation. Past data consisting of some major soil attributes were obtained from relevant literature sources. This data was preprocessed using the ARFF Converter, available in WEKA. 70% of the data were used as training data set while remaining 30% were used for testing. Classification rule mining was carried out using J48 decision tree algorithm for the data training. ‘If-then’ construct models were then generated from the decision tree, which was used to develop a system for predicting the suitability status of soil for cassava cultivation. The percentage accuracy of the data classification was 76.5% and 23.5% for correctly classified and incorrectly classified instances respectively. Practically, the developed system was esteemed a prospective tool for farmers, soil laboratories and other users in predicting soil suitability for cassava cultivation.
Enzenhöfer, R.; Geiges, A.; Nowak, W.
Advection-based well-head protection zones are commonly used to manage the contamination risk of drinking water wells. Considering the insufficient knowledge about hazards and transport properties within the catchment, current Water Safety Plans recommend that catchment managers and stakeholders know, control and monitor all possible hazards within the catchments and perform rational risk-based decisions. Our goal is to supply catchment managers with the required probabilistic risk information, and to generate tools that allow for optimal and rational allocation of resources between improved monitoring versus extended safety margins and risk mitigation measures. To support risk managers with the indispensable information, we address the epistemic uncertainty of advective-dispersive solute transport and well vulnerability (Enzenhoefer et al., 2011) within a stochastic simulation framework. Our framework can separate between uncertainty of contaminant location and actual dilution of peak concentrations by resolving heterogeneity with high-resolution Monte-Carlo simulation. To keep computational costs low, we solve the reverse temporal moment transport equation. Only in post-processing, we recover the time-dependent solute breakthrough curves and the deduced well vulnerability criteria from temporal moments by non-linear optimization. Our first step towards optimal risk management is optimal positioning of sampling locations and optimal choice of data types to reduce best the epistemic prediction uncertainty for well-head delineation, using the cross-bred Likelihood Uncertainty Estimator (CLUE, Leube et al., 2011) for optimal sampling design. Better monitoring leads to more reliable and realistic protection zones and thus helps catchment managers to better justify smaller, yet conservative safety margins. In order to allow an optimal choice in sampling strategies, we compare the trade-off in monitoring versus the delineation costs by accounting for ill
U.S. Department of Health & Human Services — The Clinical Decision Support (CDS) Inventory contains descriptions of past and present CDS projects across the Federal Government. It includes Federal projects,...
RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.
Full Text Available Due to the rapid spread of computer technologies into day-to-day lives many purchases or purchase-related decisions are made in the electronic environment of the Web. In order to handle information overload that is the result of the availability of many web-based stores, products and services, consumers use decision support aids that help with need recognition, information retrieval, filtering, comparisons and choice making. Decision support systems (DSS discipline spreads about 40 years back and was mostly focused on assisting managers. However, online environments and decision support in such environments bring new opportunities also to the customers. The focus on decision support for consumers is also not investigated to the large extent and not documented in the literature. Providing customers with well designed decision aids can lead to lower cognitive decision effort associated with the purchase decision which results in significant increase of consumer’s confidence, satisfaction, and cost savings. During decision making process the subjects can chose from several methods (optimizing, reasoning, analogizing, and creating, DSS types (data-, model-, communication-, document-driven, and knowledge-based and benefit from different modern technologies. The paper investigates popular customer decision making aids, such as search, filtering, comparison, e-negotiations and auctions, recommendation systems, social network systems, product design applications, communication support etc. which are frequently related to e-commerce applications. Results include the overview of such decision supporting tools, specific examples, classification according the way how the decisions are supported, and possibilities of applications of progressive technologies. The paper thus contributes to the process of development of the interface between companies and the customers where customer decisions take place.
Jones, N.; Nelson, J.; Pulla, S. T.; Ames, D. P.; Souffront, M.; David, C. H.; Zaitchik, B. F.; Gatlin, P. N.; Matin, M. A.
The objective of the NASA SERVIR project is to assist developing countries in using information provided by Earth observing satellites to assess and manage climate risks, land use, and water resources. We present a collection of web apps that integrate earth observations and in situ data to facilitate deployment of data and water resources models as decision-making tools in support of this effort. The interactive nature of web apps makes this an excellent medium for creating decision support tools that harness cutting edge modeling techniques. Thin client apps hosted in a cloud portal eliminates the need for the decision makers to procure and maintain the high performance hardware required by the models, deal with issues related to software installation and platform incompatibilities, or monitor and install software updates, a problem that is exacerbated for many of the regional SERVIR hubs where both financial and technical capacity may be limited. All that is needed to use the system is an Internet connection and a web browser. We take advantage of these technologies to develop tools which can be centrally maintained but openly accessible. Advanced mapping and visualization make results intuitive and information derived actionable. We also take advantage of the emerging standards for sharing water information across the web using the OGC and WMO approved WaterML standards. This makes our tools interoperable and extensible via application programming interfaces (APIs) so that tools and data from other projects can both consume and share the tools developed in our project. Our approach enables the integration of multiple types of data and models, thus facilitating collaboration between science teams in SERVIR. The apps developed thus far by our team process time-varying netCDF files from Earth observations and large-scale computer simulations and allow visualization and exploration via raster animation and extraction of time series at selected points and/or regions.
Full Text Available The development of a decision support system (DSS to inform policy making has been progressing rapidly. This paper presents a generic framework and the development steps of a decision tool prototype of geographic information systems (GIS-based decision support system of river health diagnosis (RHD-DSS. This system integrates data, calculation models, and human knowledge of river health status assessment, causal factors diagnosis, and restoration decision making to assist decision makers during river restoration and management in Zhejiang Province, China. Our RHD-DSS is composed of four main elements: the graphical user interface (GUI, the database, the model base, and the knowledge base. It has five functional components: the input module, the database management, the diagnostic indicators management, the assessment and diagnosis, and the visual result module. The system design is illustrated with particular emphasis on the development of the database, model schemas, diagnosis and analytical processing techniques, and map management design. Finally, the application of the prototype RHD-DSS is presented and implemented for Xinjiangtang River of Haining County in Zhejiang Province, China. This case study is used to demonstrate the advantages gained by the application of this system. We conclude that there is great potential for using the RHD-DSS to systematically manage river basins in order to effectively mitigate environmental issues. The proposed approach will provide river managers and designers with improved insight into river degradation conditions, thereby strengthening the assessment process and the administration of human activities in river management.
This document is a preliminary effort to draw together some of the important simulation models that are available to Reclamation or that have been developed by Reclamation since 1987. This document has also attempted to lay out a framework by which these models might be used both for the purposes for which they were originally intended and to support the analysis of other issues that relate to the hydrology and to salt and water quality management within the San Joaquin Valley. To be successful as components of a larger Decision Support System the models should to be linked together using custom designed interfaces that permit data sharing between models and that are easy to use. Several initiatives are currently underway within Reclamation to develop GIS - based and graphics - based decision support systems to improve the general level of understanding of the models currently in use, to standardize the methodology used in making planning and operations studies and to permit improved data analysis, interpretation and display. The decision support systems should allow greater participation in the planning process, allow the analysis of innovative actions that are currently difficult to study with present models and should lead to better integrated and more comprehensive plans and policy decisions in future years.
Samantra, Chitrasen; Datta, Saurav; Mahapatra, Siba Sankar
In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.
Full Text Available An original interactive procedure is proposed, which aims at overcoming some of the major weaknesses of existing pseudocriterion based methods for group decision analysis. It refers to absolute judgements of feasible alternatives and is focused on complementary activities of opinion elicitation and robustness analysis. As a foundation, four interdependent principles are introduced – problem localization, interactivity on the basis of progressiveness approach, semiautomatic derivation of criteria weights according to selective effects of veto thresholds, and group consensus seeking. The principles are grounded and realized by appropriate methodological solutions.
Kato, Mitsue; Yamamoto, Toru; Matsui, Itsuo; Hamamura, Norihisa; Iwamura, Noriki
This paper describes a mattress decision system based on users' characteristics. Generally, the comfortable bed means what sleeping habits and body pressure keep a good condition. The term “good condition” is that sleeping habits are close to the standing position and the wide body pressure. Therefore, the proposed system makes use of these as the evaluation indexes. In the past, they have been actually measuring that sleeping habits and body pressure. However, this way takes a lot of time and physical load. Consequently, we propose a way to predict users' sleeping habits and body pressures using neural networks.
The research finality of this paper is how to support Authors to develop rule driven—subject oriented, adaptable course content, meta-rules—representing the disciplinary epistemology, model of teaching, Learning Path structure, and assessment parameters—for intelligent Tutoring actions in a personalized, adaptive e-Learning environment. The focus is to instruct the student to be a decision manager for himself, able to recognize the elements of a problem, select the necessary information with the perspective of factual choices. In particular, our research intends to provide some fundamental guidelines for the definition of didactical rules and logical relations, that Authors should provide to a cognitive Tutoring system through the use of an Instructional Design method (PENTHA Model) which proposes an educational environment, able to: increase productivity and operability, create conditions for a cooperative dialogue, developing participatory research activities of knowledge, observations and discoveries, customizing the learning design in a complex and holistic vision of the learning / teaching processes.
Davies, Andrew J; Hope, Max J
Contingency plans are essential in guiding the response to marine oil spills. However, they are written before the pollution event occurs so must contain some degree of assumption and prediction and hence may be unsuitable for a real incident when it occurs. The use of Bayesian networks in ecology, environmental management, oil spill contingency planning and post-incident analysis is reviewed and analysed to establish their suitability for use as real-time environmental decision support systems during an oil spill response. It is demonstrated that Bayesian networks are appropriate for facilitating the re-assessment and re-validation of contingency plans following pollutant release, thus helping ensure that the optimum response strategy is adopted. This can minimise the possibility of sub-optimal response strategies causing additional environmental and socioeconomic damage beyond the original pollution event. Copyright © 2015 Elsevier Ltd. All rights reserved.
Kahn, C E
Computer-based systems that incorporate artificial intelligence techniques can help physicians make decisions about their patients' care. In radiology, systems have been developed to help physicians choose appropriate radiologic procedures and to formulate accurate diagnoses. These decision support systems use techniques such as rule-based reasoning, artificial neural networks, hypertext, Bayesian networks, and case-based reasoning. This article reviews these artificial intelligence techniques, describes their application in radiology, and discusses the role that decision support systems may play in radiology's future.
Terribile, F.; Basile, A.; D'Antonio, A.; De Michele, C.; Bonfante, A.; Colandrea, M.; De Mascellis, R.; D'Urso, G.; Iamarino, M.; Langella, G.; Manna, P.; Marotta, L.; Minieri, L.
This work aims to present the first results of the LIFE+ SOILCONSWEB project (LIFE08 ENV/IT/000408 ) aiming to produce, to test and to apply a decision supporting system (DSS) tool. The practical focus of this tool is to support (stakeholders) decision on landscape issues aiming to both the best soil conservation and land management and also to an easy landscape implementation of some important but complex environmental related EU directives. The project acknowledge that some of these EU directives/regulation have an intrinsic complexity because they apply to soils and landscapes which have the well recognized "multiple functions" as a fundamental feature. Then it is not surprising that this decision supporting tool requires, as fundamental feature, to include and mix many different high quality digital information, engine and processing in order to be successfully applied. Our DSS tool has been developed in the framework of a "Web-based Spatial Decision Supporting System" (WS-DSS) and it will consider soil and landscape. Decision makers (individuals, groups of interests and public bodies) can have real-time (or near real-time) access to critical, accurate, complete and up-to-date spatial data held in multiple data stores. The system produce detailed spatial documents, report and maps on a series of questions including agriculture, environment and climate change. The tool is available to and it will also allow to integrate classical top-down decision with bottom-up contributions to landscape planning and managing. The tool, as prototype, has been developed, tested and applied in an area of about 20,000 hectares in South Italy (Valle Telesina, province of Benevento in the Campania region) but its development will enable future applications in other areas. Among the several topics having a different level of complexity and already implemented in the DSS, we will show those concerning soil sealing and viticulture zoning (terroir). Emphasis will be on how combining
The objective of SCK-CEN's R and D programme on decision strategy research are (1) to support and advise the Belgian authorities on specific problems concerning existing and potential hazards from exposure to ionising radiation, both in normal and emergency situations; (2) to perform research on relevant topics that might have an important impact on decision making related to nuclear applications, including social and economic sciences. Main achievements in this area in 1999 are described
Abstract:Managing urban water infrastructures faces the challenge of jointly dealing with assets of diverse types, useful life, cost, ages and condition. Service quality and sustainability require sound long-term planning, well aligned with tactical and operational planning and management. In summary, the objective of an integrated approach to infrastructure asset management is to assist utilities answer the following questions:•Who are we at present?•What service do we deliver?•What do we own?•Where do we want to be in the long-term?•How do we get there?The AWARE-P approach (www.aware-p.org) offers a coherent methodological framework and a valuable portfolio of software tools. It is designed to assist water supply and wastewater utility decision-makers in their analyses and planning processes. It is based on a Plan-Do-Check-Act process and is in accordance with the key principles of the International Standards Organization (ISO) 55000 standards on asset management. It is compatible with, and complementary to WERF’s SIMPLE framework. The software assists in strategic, tactical, and operational planning, through a non-intrusive, web-based, collaborative environment where objectives and metrics drive IAM planning. It is aimed at industry professionals and managers, as well as at the consultants and technical experts that support them. It is easy to use and maximizes the value of information from multiple existing data sources, both in da
Torralba-Rodríguez, Francisco Jesús; Bixquert-Montagud, Vicente; Fernández-Breis, Jesualdo Tomás; Martínez-Béjar, Rodrigo
In Intensive Care Units doctors have to manage several alarm situations in patients. When a doctor analyzes the state of the patient, (s)he has to decide if there is an alarm situation and make decisions about what actions to perform. It is desirable to detect these situations before they occur, because the solution could be easier and the doctor has more time to react. An intelligent system could analyze the information, extract conclusions, format and order the causes leading to the severe condition. This would be helpful for a doctor, and would make the decision-making process easier. A system capable of performing such operations is presented here. This is not a diagnosis application but a tool to detect alarm situations for patient safety. A prototype capable of making retrospective evaluation of the condition of the patients has been developed. This system is based on the MCRDR technology, which has been extended to deal with the requirements of this domain. The evaluation of the system is also reported in this paper. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.
Nong, Bao Anh; Ertsen, Maurits; Schoups, Gerrit
Complexity and uncertainty in natural resources management have been focus themes in recent years. Within these debates, with the aim to define an approach feasible for water management practice, we are developing an integrated conceptual modeling framework for simulating decision-making processes of citizens, in our case in the Day river area, Vietnam. The model combines Bayesian Networks (BNs) and Agent-Based Modeling (ABM). BNs are able to combine both qualitative data from consultants / experts / stakeholders, and quantitative data from observations on different phenomena or outcomes from other models. Further strengths of BNs are that the relationship between variables in the system is presented in a graphical interface, and that components of uncertainty are explicitly related to their probabilistic dependencies. A disadvantage is that BNs cannot easily identify the feedback of agents in the system once changes appear. Hence, ABM was adopted to represent the reaction among stakeholders under changes. The modeling framework is developed as an attempt to gain better understanding about citizen's behavior and factors influencing their decisions in order to reduce uncertainty in the implementation of water management policy.
Jones, M.; Pitts, R.
For emergency managers, government officials, and others who must respond to rapidly changing natural disasters, timely access to detailed information related to affected terrain, population and infrastructure is critical for planning, response and recovery operations. Accessing, analyzing and disseminating such disparate information in near real-time are critical decision support components. However, finding a way to handle a variety of informative yet complex datasets poses a challenge when preparing for and responding to disasters. Here, we discuss the implementation of a web-based data integration and decision support tool for earthquakes developed by the Federal Emergency Management Agency (FEMA) as a solution to some of these challenges. While earthquakes are among the most well- monitored and measured of natural hazards, the spatially broad impacts of shaking, ground deformation, landslides, liquefaction, and even tsunamis, are extremely difficult to quantify without accelerated access to data, modeling, and analytics. This web-based application, deemed the "Earthquake Incident Journal", provides real-time access to authoritative and event-specific data from external (e.g. US Geological Survey, NASA, state and local governments, etc.) and internal (FEMA) data sources. The journal includes a GIS-based model for exposure analytics, allowing FEMA to assess the severity of an event, estimate impacts to structures and population in near real-time, and then apply planning factors to exposure estimates to answer questions such as: What geographic areas are impacted? Will federal support be needed? What resources are needed to support survivors? And which infrastructure elements or essential facilities are threatened? This presentation reviews the development of the Earthquake Incident Journal, detailing the data integration solutions, the methodology behind the GIS-based automated exposure model, and the planning factors as well as other analytical advances that
Sullivan, T.M.; Moskowitz, P.D.; Gitten, M.
Decision Support Software (DSS) continues to be developed to support analysis of decisions pertaining to environmental management. Decision support systems are computer-based systems that facilitate the use of data, models, and structured decision processes in decision making. The optimal DSS should attempt to integrate, analyze, and present environmental information to remediation project managers in order to select cost-effective cleanup strategies. The optimal system should have a balance between the sophistication needed to address the wide range of complicated sites and site conditions present at DOE facilities, and ease of use (e.g., the system should not require data that is typically unknown and should have robust error checking of problem definition through input, etc.). In the first phase of this study, an extensive review of the literature, the Internet, and discussions with sponsors and developers of DSS led to identification of approximately fifty software packages that met the preceding definition
This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective. While many degree programs require a course in parametric statistics, these methods are often inadequate for real-world decision making in business environments. Much of the data collected today by business executives (for example, customer satisfaction opinions) requires nonparametric statistics for valid analysis, and this book provides the reader with a set of tools that can be used to validly analyze all data, regardless of type. Through numerous examples and exercises, this book explains why nonparametric statistics will lead to better decisions and how they are used to reach a decision, with a wide array of business applications. Online resources include exercise data, spreadsheets, and solutions.
Keum, Jongho; Coulibaly, Paulin
Adequate and accurate hydrologic information from optimal hydrometric networks is an essential part of effective water resources management. Although the key hydrologic processes in the water cycle are interconnected, hydrometric networks (e.g., streamflow, precipitation, groundwater level) have been routinely designed individually. A decision support framework is proposed for integrated design of multivariable hydrometric networks. The proposed method is applied to design optimal precipitation and streamflow networks simultaneously. The epsilon-dominance hierarchical Bayesian optimization algorithm was combined with Shannon entropy of information theory to design and evaluate hydrometric networks. Specifically, the joint entropy from the combined networks was maximized to provide the most information, and the total correlation was minimized to reduce redundant information. To further optimize the efficiency between the networks, they were designed by maximizing the conditional entropy of the streamflow network given the information of the precipitation network. Compared to the traditional individual variable design approach, the integrated multivariable design method was able to determine more efficient optimal networks by avoiding the redundant stations. Additionally, four quantization cases were compared to evaluate their effects on the entropy calculations and the determination of the optimal networks. The evaluation results indicate that the quantization methods should be selected after careful consideration for each design problem since the station rankings and the optimal networks can change accordingly.
Jarre, Astrid; Paterson, B.; Moloney, C.L.
rule-based Boolean and fuzzy-logic models have been used successfully as knowledge-based decision support tools. This study compares two such systems relevant to fisheries management in an EAF developed for the southern Benguela. The first is a rule-based system for the prediction of anchovy...
Goldstein, M. K.; Hoffman, B. B.; Coleman, R. W.; Tu, S. W.; Shankar, R. D.; O’Connor, M.; Martins, S.; Advani, A.; Musen, M. A.
The Institute of Medicine recently issued a landmark report on medical error.1 In the penumbra of this report, every aspect of health care is subject to new scrutiny regarding patient safety. Informatics technology can support patient safety by correcting problems inherent in older technology; however, new information technology can also contribute to new sources of error. We report here a categorization of possible errors that may arise in deploying a system designed to give guideline-based ...
Goldstein, M. K.; Hoffman, B. B.; Coleman, R. W.; Tu, S. W.; Shankar, R. D.; O'Connor, M.; Martins, S.; Martins, S.; Advani, A.; Musen, M. A.
The Institute of Medicine recently issued a landmark report on medical error.1 In the penumbra of this report, every aspect of health care is subject to new scrutiny regarding patient safety. Informatics technology can support patient safety by correcting problems inherent in older technology; however, new information technology can also contribute to new sources of error. We report here a categorization of possible errors that may arise in deploying a system designed to give guideline-based ...
Briceno, Simon Ignacio
This dissertation describes the development of a game-based methodology that facilitates the exploration and selection of research and development (R&D) projects under uncertain competitive scenarios. The proposed method provides an approach that analyzes competitor positioning and formulates response strategies to forecast the impact of technical design choices on a project's market performance. A critical decision in the conceptual design phase of propulsion systems is the selection of the best architecture, centerline, core size, and technology portfolio. This selection can be challenging when considering evolving requirements from both the airframe manufacturing company and the airlines in the market. Furthermore, the exceedingly high cost of core architecture development and its associated risk makes this strategic architecture decision the most important one for an engine company. Traditional conceptual design processes emphasize performance and affordability as their main objectives. These areas alone however, do not provide decision-makers with enough information as to how successful their engine will be in a competitive market. A key objective of this research is to examine how firm characteristics such as their relative differences in completing R&D projects, differences in the degree of substitutability between different project types, and first/second-mover advantages affect their product development strategies. Several quantitative methods are investigated that analyze business and engineering strategies concurrently. In particular, formulations based on the well-established mathematical field of game theory are introduced to obtain insights into the project selection problem. The use of game theory is explored in this research as a method to assist the selection process of R&D projects in the presence of imperfect market information. The proposed methodology focuses on two influential factors: the schedule uncertainty of project completion times and
Nair, Bala G; Horibe, Mayumi; Newman, Shu-Fang; Wu, Wei-Ying; Peterson, Gene N; Schwid, Howard A
Intraoperative hypotension and hypertension are associated with adverse clinical outcomes and morbidity. Clinical decision support mediated through an anesthesia information management system (AIMS) has been shown to improve quality of care. We hypothesized that an AIMS-based clinical decision support system could be used to improve management of intraoperative hypotension and hypertension. A near real-time AIMS-based decision support module, Smart Anesthesia Manager (SAM), was used to detect selected scenarios contributing to hypotension and hypertension. Specifically, hypotension (systolic blood pressure 1.25 minimum alveolar concentration [MAC]) of inhaled drug and hypertension (systolic blood pressure >160 mm Hg) with concurrent phenylephrine infusion were detected, and anesthesia providers were notified via "pop-up" computer screen messages. AIMS data were retrospectively analyzed to evaluate the effect of SAM notification messages on hypotensive and hypertensive episodes. For anesthetic cases 12 months before (N = 16913) and after (N = 17132) institution of SAM messages, the median duration of hypotensive episodes with concurrent high MAC decreased with notifications (Mann Whitney rank sum test, P = 0.031). However, the reduction in the median duration of hypertensive episodes with concurrent phenylephrine infusion was not significant (P = 0.47). The frequency of prolonged episodes that lasted >6 minutes (sampling period of SAM), represented in terms of the number of cases with episodes per 100 surgical cases (or percentage occurrence), declined with notifications for both hypotension with >1.25 MAC inhaled drug episodes (δ = -0.26% [confidence interval, -0.38% to -0.11%], P 1.25 MAC inhaled drug episodes. However, since phenylephrine infusion is manually documented in an AIMS, the impact of notification messages was less pronounced in reducing episodes of hypertension with concurrent phenylephrine infusion. Automated data capture and a higher frequency of
Kaniuka, Theodore S.; Vitale, Michael R.; Romance, Nancy R.
Successful school reform is dependent on the quality of decisions made by educational leaders. In such decision making, educational leaders are charged with using sound research findings as the basis for choosing school reform initiatives. As part of the debate regarding the usability of various evaluative research designs in providing information…
Tian, Yangge; Bian, Fuling
The technology of artificial intelligence should be imported on the basis of the geographic information system to bring up the spatial decision-supporting system (SDSS). The paper discusses the structure of SDSS, after comparing the characteristics of RBR and CBR, the paper brings up the frame of a spatial decisional system that combines RBR and CBR, which has combined the advantages of them both. And the paper discusses the CBR in agriculture spatial decisions, the application of ANN (Artificial Neural Network) in CBR, and enriching the inference rule base based on association rules, etc. And the paper tests and verifies the design of this system with the examples of the evaluation of the crops' adaptability.
Peck Chui Betty Khong
Full Text Available The selection of appropriate wound products for the treatment of pressure injuries is paramount in promoting wound healing. However, nurses find it difficult to decide on the most optimal wound product(s due to limited live experiences in managing pressure injuries resulting from successfully implemented pressure injury prevention programs. The challenges of effective decision-making in wound treatments by nurses at the point of care are compounded by the yearly release of wide arrays of newly researched wound products into the consumer market. A clinical decision support system for pressure injury (PI-CDSS was built to facilitate effective decision-making and selection of optimal wound treatments. This paper describes the development of PI-CDSS with an expert knowledge base using an interactive development environment, Blaze Advisor. A conceptual framework using decision-making and decision theory, knowledge representation, and process modelling guided the construct of the PI-CDSS. This expert system has incorporated the practical and relevant decision knowledge of wound experts in assessment and wound treatments in its algorithm. The construct of the PI-CDSS is adaptive, with scalable capabilities for expansion to include other CDSSs and interoperability to interface with other existing clinical and administrative systems. The algorithm was formatively evaluated and tested for usability. The treatment modalities generated after using patient-specific assessment data were found to be consistent with the treatment plan(s proposed by the wound experts. The overall agreement exceeded 90% between the wound experts and the generated treatment modalities for the choice of wound products, instructions, and alerts. The PI-CDSS serves as a just-in-time wound treatment protocol with suggested clinical actions for nurses, based on the best evidence available.
Full Text Available The paper proposes an overview of decision support systems in order to define the role of a system to assist decision in university management. The authors present new technologies and the basic concepts of multidimensional data analysis using models of business processes within the universities. Based on information provided by scientific literature and on the authors’ experience, the study aims to define selection criteria in choosing a development environment for designing a support system dedicated to university management. The contributions consist in designing a data warehouse model and models of OLAP analysis to assist decision in university management.
Shi Chunsheng; Meng Dapeng
The prediction index for supply risk is developed based on the factor identifying of nuclear equipment manufacturing industry. The supply risk prediction model is established with the method of support vector machine and decision tree, based on the investigation on 3 important nuclear power equipment manufacturing enterprises and 60 suppliers. Final case study demonstrates that the combination model is better than the single prediction model, and demonstrates the feasibility and reliability of this model, which provides a method to evaluate the suppliers and measure the supply risk. (authors)
Schnipper, Jeffrey L; Linder, Jeffrey A; Palchuk, Matvey B; Einbinder, Jonathan S; Li, Qi; Postilnik, Anatoly; Middleton, Blackford
Clinical decision support systems (CDSS) integrated within Electronic Medical Records (EMR) hold the promise of improving healthcare quality. To date the effectiveness of CDSS has been less than expected, especially concerning the ambulatory management of chronic diseases. This is due, in part, to the fact that clinicians do not use CDSS fully. Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance of the content to the patient at hand. At Partners HealthCare, we are developing "Smart Forms" to facilitate documentation-based clinical decision support. Rather than being interruptive in nature, the Smart Form enables writing a multi-problem visit note while capturing coded information and providing sophisticated decision support in the form of tailored recommendations for care. The current version of the Smart Form is designed around two chronic diseases: coronary artery disease and diabetes mellitus. The Smart Form has potential to improve the care of patients with both acute and chronic conditions.
Christine E. Kerschus
The Paducah Gaseous Diffusion Plant (PGDP) operated by the Department of Energy is challenged with selecting the appropriate remediation technology to cleanup contaminants at Waste Area Group (WAG) 6. This research utilizes value-focused thinking and multiattribute preference theory concepts to produce a decision analysis model designed to aid the decision makers in their selection process. The model is based on CERCLA's five primary balancing criteria, tailored specifically to WAG 6 and the contaminants of concern, utilizes expert opinion and the best available engineering, cost, and performance data, and accounts for uncertainty in contaminant volume. The model ranks 23 remediation technologies (trains) in their ability to achieve the CERCLA criteria at various contaminant volumes. A sensitivity analysis is performed to examine the effects of changes in expert opinion and uncertainty in volume. Further analysis reveals how volume uncertainty is expected to affect technology cost, time and ability to meet the CERCLA criteria. The model provides the decision makers with a CERCLA-based decision analysis methodology that is objective, traceable, and robust to support the WAG 6 Feasibility Study. In addition, the model can be adjusted to address other DOE contaminated sites.
Christine E. Kerschus
The Paducah Gaseous Diffusion Plant (PGDP) operated by the Department of Energy is challenged with selecting the appropriate remediation technology to cleanup contaminants at Waste Area Group (WAG) 6. This research utilizes value-focused thinking and multiattribute preference theory concepts to produce a decision analysis model designed to aid the decision makers in their selection process. The model is based on CERCLA's five primary balancing criteria, tailored specifically to WAG 6 and the contaminants of concern, utilizes expert opinion and the best available engineering, cost, and performance data, and accounts for uncertainty in contaminant volume. The model ranks 23 remediation technologies (trains) in their ability to achieve the CERCLA criteria at various contaminant volumes. A sensitivity analysis is performed to examine the effects of changes in expert opinion and uncertainty in volume. Further analysis reveals how volume uncertainty is expected to affect technology cost, time and ability to meet the CERCLA criteria. The model provides the decision makers with a CERCLA-based decision analysis methodology that is objective, traceable, and robust to support the WAG 6 Feasibility Study. In addition, the model can be adjusted to address other DOE contaminated sites
Renardel de Lavalette, G R; Groenboom, R.; Rotterdam, E; van Harmelen, F; ten Teije, A; de Geus, F.
This paper reports on research for decision support for anaesthesiologists at the University Hospital in Groningen, the Netherlands. Based on CAROLA, an existing automated operation documentation system, we designed a support environment that will assist in real-time diagnosis. The core of the work
Janssen, R.; van Herwijnen, M.; Stewart, T.J.; Aerts, J.C.J.H.
The overall objective of this paper is to show how a formal decision support method can be used effectively to support a land-use planning problem. Central to our approach is a heuristic algorithm based on a goal-programming/reference-point approach. The algorithm is tested on a small region in the
Kalina, Jan; Zvárová, Jana
Roč. 4, č. 1 (2016), s. 30-34 ISSN 1805-8698 Grant - others:Nadační fond na opdporu vědy(CZ) Neuron Institutional support: RVO:67985807 Keywords : decision support * data mining * multivariate statistics * psychiatry * information based medicine Subject RIV: BB - Applied Statistics, Operational Research
Zhang, Yi-Fan; Gou, Ling; Tian, Yu; Li, Tian-Chang; Zhang, Mao; Li, Jing-Song
Clinical decision support (CDS) systems provide clinicians and other health care stakeholders with patient-specific assessments or recommendations to aid in the clinical decision-making process. Despite their demonstrated potential for improving health care quality, the widespread availability of CDS systems has been limited mainly by the difficulty and cost of sharing CDS knowledge among heterogeneous healthcare information systems. The purpose of this study was to design and develop a sharable clinical decision support (S-CDS) system that meets this challenge. The fundamental knowledge base consists of independent and reusable knowledge modules (KMs) to meet core CDS needs, wherein each KM is semantically well defined based on the standard information model, terminologies, and representation formalisms. A semantic web service framework was developed to identify, access, and leverage these KMs across diverse CDS applications and care settings. The S-CDS system has been validated in two distinct client CDS applications. Model-level evaluation results confirmed coherent knowledge representation. Application-level evaluation results reached an overall accuracy of 98.66 % and a completeness of 96.98 %. The evaluation results demonstrated the technical feasibility and application prospect of our approach. Compared with other CDS engineering efforts, our approach facilitates system development and implementation and improves system maintainability, scalability and efficiency, which contribute to the widespread adoption of effective CDS within the healthcare domain.
Wehrly, Kevin E. [Michigan Dept. Natural Resources and Environment, Lansing, MI (United States); Rutherford, Edward S. [Great Lakes Environmental Research Lab., Ann Harbor, MI (United States); Wang, Lizhu [Michigan Dept. Natural Resources and Environment, Lansing, MI (United States); Breck, Jason [Univ. of Michigan, Ann Arbor, MI (United States). School of Natural Resources and Environment (UM-SNRE); Mason, Lacey [Univ. of Michigan, Ann Arbor, MI (United States). School of Natural Resources and Environment (UM-SNRE); Nelson, Scott [USGS Great Lakes Science Center, Ann Arbor, MI (United States)
As an outcome of our research project, we developed software and data for the Lakebed Alteration Decision Support Tool (LADST), a web-based decision support program to assist resource managers in making siting decisions for offshore wind farms (as well as other lakebed-altering projects) in the United States' waters of the Great Lakes. Users of the LADST can create their own offshore wind farm suitability maps, based upon suitability criteria of their own choosing by visiting a public web site. The LADST can be used to represent the different priorities or values of different Great Lakes stakeholders for wind farm siting, as well as the different suitability requirements of wind farms (or different types of development projects) in a single suitability analysis system. The LADST makes this type of customized suitability analysis easily accessible to users who have no specialized software or experience with geographic information systems (GIS). It also may increase the transparency of the siting and permitting process for offshore wind farms, as it makes the suitability analysis equally accessible to resource managers, wind farm developers, and concerned citizens.
Booth, N. L.; Everman, E.; Kuo, I.; Sprague, L.; Murphy, L.
A new web-based decision support system has been developed as part of the U.S. Geological Survey (USGS) National Water Quality Assessment Program's (NAWQA) effort to provide ready access to Spatially Referenced Regressions On Watershed attributes (SPARROW) results of stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via an intuitive graphical user interface with a map-based display. The SPARROW Decision Support System (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions, distribution of nutrient sources, nutrient delivery to downstream waterbodies, and simulations of altered nutrient inputs including atmospheric and agricultural sources. The DSS offers other features for analysis including various background map layers, model output exports, and the ability to save and share prediction scenarios. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. The underlying modeling framework and server infrastructure illustrate innovations in the information technology and geosciences fields for delivering SPARROW model predictions over the web by performing intensive model computations and map visualizations of the predicted conditions within the stream network.
Yatsalo, B.I.; Demin, V.F.
Overall questions of decision making support of the contaminated territories management on a basis of risk assessment were considered. Characteristics and possibilities of the applied geoinformation system of decision making support PRANA developed for the risk control and rehabilitation of contaminated territories are demonstrated. The PRANA system involves estimations of all fundamental characteristics of risk during analysis of results and contaminated territories management [ru
Grim, Katarina; Rosenberg, David; Svedberg, Petra; Schön, Ulla-Karin
Shared decision making (SMD) related to treatment and rehabilitation is considered a central component in recovery-oriented practice. Although decision aids are regarded as an essential component for successfully implementing SDM, these aids are often lacking within psychiatric services. The aim of this study was to use a participatory design to facilitate the development of a user-generated, web-based decision aid for individuals receiving psychiatric services. The results of this effort as well as the lessons learned during the development and usability processes are reported. The participatory design included 4 iterative cycles of development. Various qualitative methods for data collection were used with potential end users participating as informants in focus group and individual interviews and as usability and pilot testers. Interviewing and testing identified usability problems that then led to refinements and making the subsequent prototypes increasingly user-friendly and relevant. In each phase of the process, feedback from potential end-users provided guidance in developing the formation of the web-based decision aid that strengthens the position of users by integrating access to information regarding alternative supports, interactivity between staff and users, and user preferences as a continual focus in the tool. This web-based decision aid has the potential to strengthen service users' experience of self-efficacy and control as well as provide staff access to user knowledge and preferences. Studies employing participatory models focusing on usability have potential to significantly contribute to the development and implementation of tools that reflect user perspectives. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Park, Jeong Eun; Kim, Hwa Sun; Chang, Min Jung; Hong, Hae Sook
The influence of dietary composition on blood pressure is an important subject in healthcare. Interactions between antihypertensive drugs and diet (IBADD) is the most important factor in the management of hypertension. It is therefore essential to support healthcare providers' decision making role in active and continuous interaction control in hypertension management. The aim of this study was to implement an ontology-based clinical decision support system (CDSS) for IBADD management (IBADDM). We considered the concepts of antihypertensive drugs and foods, and focused on the interchangeability between the database and the CDSS when providing tailored information. An ontology-based CDSS for IBADDM was implemented in eight phases: (1) determining the domain and scope of ontology, (2) reviewing existing ontology, (3) extracting and defining the concepts, (4) assigning relationships between concepts, (5) creating a conceptual map with CmapTools, (6) selecting upper ontology, (7) formally representing the ontology with Protégé (ver.4.3), (8) implementing an ontology-based CDSS as a JAVA prototype application. We extracted 5,926 concepts, 15 properties, and formally represented them using Protégé. An ontology-based CDSS for IBADDM was implemented and the evaluation score was 4.60 out of 5. We endeavored to map functions of a CDSS and implement an ontology-based CDSS for IBADDM.
Full Text Available IntroductionEpilepsy is a neurological disorder involving recurrent seizures. It affects approximately 5 million people in the U.S. To optimize their quality of life people with epilepsy are encouraged to engage in self-management (S-M behaviors. These include managing their treatment (e.g., adhering to anti-seizure medication and clinical visit schedules, managing their seizures (e.g., responding to seizure episodes, managing their safety (e.g., monitoring and avoiding environmental seizure triggers, and managing their co-morbid conditions (e.g., anxiety, depression. The clinic-based Management Information Decision Support Epilepsy Tool (MINDSET is a decision-support system founded on theory and empirical evidence. It is designed to increase awareness by adult patients (≥18 years and their health-care provider regarding the patient’s epilepsy S-M behaviors, facilitate communication during the clinic visit to prioritize S-M goals and strategies commensurate with the patient’s needs, and increase the patient’s self-efficacy to achieve those goals.MethodsThe purpose of this paper is to describe the application of intervention mapping (IM to develop, implement, and formatively evaluate the clinic-based MINDSET prototype and in developing implementation and evaluation plans. Deliverables comprised a logic model of the problem (IM Step 1; matrices of program objectives (IM Step 2; a program planning document comprising scope, sequence, theory-based methods, and practical strategies (IM Step 3; a functional MINDSET program prototype (IM Step 4; plans for implementation (IM Step 5; and evaluation (IM Step 6. IM provided a logical and systematic approach to developing and evaluating clinic-based decision support toward epilepsy S-M.
Effective contaminated land management requires a number of decisions addressing a suite of technical, economic, and social concerns. These concerns include human health risks, ecological risks, economic costs, technical feasibility of proposed remedial actions, and the value society places on clean-up and re-use of formerly contaminated lands. Decision making, in the face of uncertainty and multiple and often conflicting objectives, is a vital and challenging role in environmental management that affects a significant economic activity. Although each environmental remediation problem is unique and requires a site-specific analysis, many of the key decisions are similar in structure. This has led many to attempt to develop standard approaches. As part of the standardization process, attempts have been made to codify specialist expertise into decision support tools. This activity is intended to facilitate reproducible and transparent decision making. The process of codifying procedures has also been found to be a useful activity for establishing and rationalizing management processes. This study will have two primary objectives. The first is to develop taxonomy for Decision Support Tools (DST) to provide a framework for understanding the different tools and what they are designed to address in the context of environmental remediation problems. The taxonomy will have a series of subject areas for the DST. From these subjects, a few key areas will be selected for further study and software in these areas will be identified. The second objective, will be to review the existing DST in the selected areas and develop a screening matrix for each software product.
Skevofilakas, M.T.; Nikita, K.S.; Templaleksis, P.H.; Birbas, K.N.; Kaklamanos, I.G.; Bonatsos, G.N.
Evidence based medicine is the clinical practice that uses medical data and proof in order to make efficient clinical decisions. Information technology (IT) can play a crucial role in exploiting the huge size of raw medical data involved. In an attempt to improve clinical efficacy, health care society nowadays also utilizes a new assistant, clinical guidelines. Our research concerns the medical domain of the breast cancer disease. Our research's focus is twofold; our primary goal is to ensure consistency in clinical practice by importing clinical guidelines in an IT driven decision support system (DSS). Furthermore, we seek to improve visualization of disease specific, clinical data, providing for it's faster and more efficient use. (orig.)
Fu, R.; Fernando, D. N.; Pu, B.
Drought prone states such as Texas requires creditable and actionable drought early warning ranging from seasonal to multi-decadal scales. Such information cannot be simply extracted from the available climate prediction and projections because of their large uncertainties at regional scales and unclear connections to the needs of the decision makers. In particular, current dynamic seasonal predictions and climate projections, such as those produced by the NOAA national multi-models ensemble experiment (NMME) and the IPCC AR5 (CMIP5) models, are much more reliable for winter and spring than for the summer season for the US Southern Plains. They also show little connection between the droughts in winter/spring and those in summer, in contrast to the observed dry memory from spring to summer over that region. To mitigate the weakness of dynamic prediction/projections, we have identified three key processes behind the spring-to-summer dry memory through observational studies. Based on these key processes and related fields, we have developed a multivariate principle component statistical model to provide a probabilistic summer drought early warning indicator, using the observed or predicted climate conditions in winter and spring on seasonal scale and climate projection for the mid-21stcentury. The summer drought early warning indicator is constructed in a similar way to the NOAA probabilistic predictions that are familiar to water resource managers. The indicator skill is assessed using the standard NOAA climate prediction assessment tools, i.e., the two alternative forced choice (2AFC) and the Receiver Operating Characteristic (ROC). Comparison with long-term observations suggest that this summer drought early warning indicator is able to capture nearly all the strong summer droughts and outperform the dynamic prediction in this regard over the US Southern Plains. This early warning indicator has been used by the state water agency in May 2014 in briefing the state
Jauregui, Barbara; Janusz, Cara Bess; Clark, Andrew D; Sinha, Anushua; Garcia, Ana Gabriela Felix; Resch, Stephen; Toscano, Cristiana M; Sanderson, Colin; Andrus, Jon Kim
The Pan American Health Organization (PAHO) created the ProVac Initiative in 2004 with the goal of strengthening national technical capacity to make evidence-based decisions on new vaccine introduction, focusing on economic evaluations. In view of the 10th anniversary of the ProVac Initiative, this article describes its progress and reflects on lessons learned to guide the next phase. We quantified the output of the Initiative's capacity-building efforts and critically assess its progress toward achieving the milestones originally proposed in 2004. Additionally, we reviewed how country studies supported by ProVac have directly informed and strengthened the deliberations around new vaccine introduction. Since 2004, ProVac has conducted four regional workshops and supported 24 health economic analyses in 15 Latin American and Caribbean countries. Five Regional Centers of Excellence were funded, resulting in six operational research projects and nine publications. Twenty four decisions on new vaccine introductions were supported with ProVac studies. Enduring products include the TRIVAC and CERVIVAC cost-effectiveness models, the COSTVAC program costing model, methodological guides, workshop training materials and the OLIVES on-line data repository. Ten NITAGs were strengthened through ProVac activities. The evidence accumulated suggests that initiatives with emphasis on sustainable training and direct support for countries to generate evidence themselves, can help accelerate the introduction of the most valuable new vaccines. International and Regional Networks of Collaborators are necessary to provide technical support and tools to national teams conducting analyses. Timeliness, integration, quality and country ownership of the process are four necessary guiding principles for national economic evaluations to have an impact on policymaking. It would be an asset to have a model that offers different levels of complexity to choose from depending on the vaccine being
While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the
Wang, Jun; Chen, J. M.; Li, Manchun; Ju, Weimin
As the major eligible land use activities in the Clean Development Mechanism (CDM), afforestation and reforestation offer opportunities and potential economic benefits for developing countries to participate in carbon-trade in the potential international carbon (C) sink markets. However, the design and selection of appropriate afforestation and reforestation locations in CDM are complex processes which need integrated assessment (IA) of C sequestration (CS) potential, environmental effects, and socio-economic impacts. This paper promotes the consideration of CS benefits in local land use planning and presents a GIS-based integrated assessment and spatial decision support system (IA-SDSS) to support decision-making on 'where' and 'how' to afforest. It integrates an Integrated Terrestrial Ecosystem Carbon Model (InTEC) and a GIS platform for modeling regional long-term CS potential and assessment of geo-referenced land use criteria including CS consequence, and produces ranking of plantation schemes with different tree species using the Analytic hierarchy process (AHP) method. Three land use scenarios are investigated: (i) traditional land use planning criteria without C benefits, (ii) land use for CS with low C price, and (iii) land use for CS with high price. Different scenarios and consequences will influence the weights of tree-species selection in the AHP decision process.
Benmimoune, Lamine; Hajjam, Amir; Ghodous, Parisa; Andres, Emmanuel; Talha, Samy; Hajjam, Mohamed
The aim of this paper is to describe an original approach which consists of designing ontology based Medical Decision Support System (MDSS) to enhance the patients' lifestyle. This system is composed of two main parts: data collector which collects relevant lifestyle-related patent data by prompting the only significant questions in connection with the patient's medical background, and advices provider which provides personalized lifestyle advices to the patients regarding their lifestyle changes. The proposed MDSS is integrated within E-care home health monitoring platform in order to: (i) improve the patient's healthy lifestyle; (ii) educate the patients towards their disease; (iii) increase the early detection of risky situation.
Shimon Y. Nof
Full Text Available Collaborative Decision Support Systems, CDSS, depend on cost-effective collaboration among the decision participants. Those may include, in addition to human decision makers, non-human entities such as robots, software and hardware agents, sensors, and autonomous instruments. The purpose of this article is to explore the impact that CCT, the Collaborative Control Theory, has on cyber supported augmentation of collaboration in general, and its proven and potential impacts on CDSS in particular. Three recent case studies are discussed. The correlation between CDSS decision process and quality; and the level of CCT-based collaboration augmentation and the resulting level of Collaborative Intelligence, CI, is presented. It is concluded that while there are clear positive impacts of CCT based augmentation and level of CI, they need to be measured and optimized, not maximized. Further research in this area is also described.
Aragon, Cecilia R.
In order to safely operate their aircraft, pilots must make rapid decisions based on integrating and processing large amounts of heterogeneous information. Visual displays are often the most efficient method of presenting safety-critical data to pilots in real time. However, care must be taken to ensure the pilot is provided with the appropriate amount of information to make effective decisions and not become cognitively overloaded. The results of two usability studies of a prototype airflow hazard visualization cockpit decision support system are summarized. The studies demonstrate that such a system significantly improves the performance of helicopter pilots landing under turbulent conditions. Based on these results, design principles and implications for cockpit decision support systems using visualization are presented.
This study developed a web-based prototype decision support platform to demonstrate the benefits of transportation asset management in monitoring asset performance, supporting asset funding decisions, planning budget tradeoffs, and optimizing resourc...
Chaubey, I.; Vema, V. K.; Sudheer, K.
Site suitability evaluation of water conservation structures in water scarce rainfed agricultural areas consist of assessment of various landscape characteristics and various criterion. Many of these landscape characteristic attributes are conveyed through linguistic terms rather than precise numeric values. Fuzzy rule based system are capable of incorporating uncertainty and vagueness, when various decision making criteria expressed in linguistic terms are expressed as fuzzy rules. In this study a fuzzy rule based decision support system is developed, for optimal site selection of water harvesting technologies. Water conservation technologies like farm ponds, Check dams, Rock filled dams and percolation ponds aid in conserving water for irrigation and recharging aquifers and development of such a system will aid in improving the efficiency of the structures. Attributes and criteria involved in decision making are classified into different groups to estimate the suitability of the particular technology. The developed model is applied and tested on an Indian watershed. The input attributes are prepared in raster format in ArcGIS software and suitability of each raster cell is calculated and output is generated in the form of a thematic map showing the suitability of the cells pertaining to different technologies. The output of the developed model is compared against the already existing structures and results are satisfactory. This developed model will aid in improving the sustainability and efficiency of the watershed management programs aimed at enhancing in situ moisture content.
Documet, Jorge R.; Liu, Brent; Le, Anh; Law, Maria
During the last 2 years we have been working on developing a DICOM-RT (Radiation Therapy) ePR (Electronic Patient Record) with decision support that will allow physicists and radiation oncologists during their decision-making process. This ePR allows offline treatment dose calculations and plan evaluation, while at the same time it compares and quantifies treatment planning algorithms using DICOM-RT objects. The ePR framework permits the addition of visualization, processing, and analysis tools, which combined with the core functionality of reporting, importing and exporting of medical studies, creates a very powerful application that can improve the efficiency while planning cancer treatments. Usually a Radiation Oncology department will have disparate and complex data generated by the RT modalities as well as data scattered in RT Information/Management systems, Record & Verify systems, and Treatment Planning Systems (TPS) which can compromise the efficiency of the clinical workflow since the data crucial for a clinical decision may be time-consuming to retrieve, temporarily missing, or even lost. To address these shortcomings, the ACR-NEMA Standards Committee extended its DICOM (Digital Imaging & Communications in Medicine) standard from Radiology to RT by ratifying seven DICOM RT objects starting in 1997 [1,2]. However, they are not broadly used yet by the RT community in daily clinical operations. In the past, the research focus of an RT department has primarily been developing new protocols and devices to improve treatment process and outcomes of cancer patients with minimal effort dedicated to integration of imaging and information systems. Our attempt is to show a proof-of-concept that a DICOM-RT ePR system can be developed as a foundation to perform medical imaging informatics research in developing decision-support tools and knowledge base for future data mining applications.
Full Text Available Abstract Heart disease is the main leading killer as well as a major cause of disability. Its timely detection and correct diagnosis plays a vital role in human life. In a limited period of time recalling the data from Doctors unaided memory may lead to wrong judgments. While taking decisions Doctor analyses the physical condition and test results of the patient. In the same way our system compares the data provided to Doctor and getting a result through CBR technique. Results from the system will help the Doctor to conclude the decision and reduce human errors may occur. Our system is able to analyze scanned results of heart and being a helping hand to the doctor in all manners.
Kohn, M S; Sun, J; Knoop, S; Shabo, A; Carmeli, B; Sow, D; Syed-Mahmood, T; Rapp, W
This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation.
Treweek, Shaun; Oxman, Andrew D; Alderson, Philip; Bossuyt, Patrick M; Brandt, Linn; Brożek, Jan; Davoli, Marina; Flottorp, Signe; Harbour, Robin; Hill, Suzanne; Liberati, Alessandro; Liira, Helena; Schünemann, Holger J; Rosenbaum, Sarah; Thornton, Judith; Vandvik, Per Olav; Alonso-Coello, Pablo
Healthcare decision makers face challenges when using guidelines, including understanding the quality of the evidence or the values and preferences upon which recommendations are made, which are often not clear. GRADE is a systematic approach towards assessing the quality of evidence and the strength of recommendations in healthcare. GRADE also gives advice on how to go from evidence to decisions. It has been developed to address the weaknesses of other grading systems and is now widely used internationally. The Developing and Evaluating Communication Strategies to Support Informed Decisions and Practice Based on Evidence (DECIDE) consortium (http://www.decide-collaboration.eu/), which includes members of the GRADE Working Group and other partners, will explore methods to ensure effective communication of evidence-based recommendations targeted at key stakeholders: healthcare professionals, policymakers, and managers, as well as patients and the general public. Surveys and interviews with guideline producers and other stakeholders will explore how presentation of the evidence could be improved to better meet their information needs. We will collect further stakeholder input from advisory groups, via consultations and user testing; this will be done across a wide range of healthcare systems in Europe, North America, and other countries. Targeted communication strategies will be developed, evaluated in randomized trials, refined, and assessed during the development of real guidelines. Results of the DECIDE project will improve the communication of evidence-based healthcare recommendations. Building on the work of the GRADE Working Group, DECIDE will develop and evaluate methods that address communication needs of guideline users. The project will produce strategies for communicating recommendations that have been rigorously evaluated in diverse settings, and it will support the transfer of research into practice in healthcare systems globally.
Wang, Ximing; Verma, Sneha; Qin, Yi; Sterling, Josh; Zhou, Alyssa; Zhang, Jeffrey; Martinez, Clarisa; Casebeer, Narissa; Koh, Hyunwook; Winstein, Carolee; Liu, Brent
With the rapid development of science and technology, large-scale rehabilitation centers and clinical rehabilitation trials usually involve significant volumes of multimedia data. Due to the global aging crisis, millions of new patients with age-related chronic diseases will produce huge amounts of data and contribute to soaring costs of medical care. Hence, a solution for effective data management and decision support will significantly reduce the expenditure and finally improve the patient life quality. Inspired from the concept of the electronic patient record (ePR), we developed a prototype system for the field of rehabilitation engineering. The system is subject or patient-oriented and customized for specific projects. The system components include data entry modules, multimedia data presentation and data retrieval. To process the multimedia data, the system includes a DICOM viewer with annotation tools and video/audio player. The system also serves as a platform for integrating decision-support tools and data mining tools. Based on the prototype system design, we developed two specific applications: 1) DOSE (a phase 1 randomized clinical trial to determine the optimal dose of therapy for rehabilitation of the arm and hand after stroke.); and 2) NEXUS project from the Rehabilitation Engineering Research Center(RERC, a NIDRR funded Rehabilitation Engineering Research Center). Currently, the system is being evaluated in the context of the DOSE trial with a projected enrollment of 60 participants over 5 years, and will be evaluated by the NEXUS project with 30 subjects. By applying the ePR concept, we developed a system in order to improve the current research workflow, reduce the cost of managing data, and provide a platform for the rapid development of future decision-support tools.
Vithayasrichareon, Peerapat; MacGill, Iain F.
This paper presents a novel decision-support tool for assessing future generation portfolios in an increasingly uncertain electricity industry. The tool combines optimal generation mix concepts with Monte Carlo simulation and portfolio analysis techniques to determine expected overall industry costs, associated cost uncertainty, and expected CO 2 emissions for different generation portfolio mixes. The tool can incorporate complex and correlated probability distributions for estimated future fossil-fuel costs, carbon prices, plant investment costs, and demand, including price elasticity impacts. The intent of this tool is to facilitate risk-weighted generation investment and associated policy decision-making given uncertainties facing the electricity industry. Applications of this tool are demonstrated through a case study of an electricity industry with coal, CCGT, and OCGT facing future uncertainties. Results highlight some significant generation investment challenges, including the impacts of uncertain and correlated carbon and fossil-fuel prices, the role of future demand changes in response to electricity prices, and the impact of construction cost uncertainties on capital intensive generation. The tool can incorporate virtually any type of input probability distribution, and support sophisticated risk assessments of different portfolios, including downside economic risks. It can also assess portfolios against multi-criterion objectives such as greenhouse emissions as well as overall industry costs. - Highlights: ► Present a decision support tool to assist generation investment and policy making under uncertainty. ► Generation portfolios are assessed based on their expected costs, risks, and CO 2 emissions. ► There is tradeoff among expected cost, risks, and CO 2 emissions of generation portfolios. ► Investment challenges include economic impact of uncertainties and the effect of price elasticity. ► CO 2 emissions reduction depends on the mix of
Kim, Hyungyung; Kim, Insook; Chae, Yougmoon
This study a methodological study; to acquire knowledge on the nursing process by steps of knowledge definition, collection, and representation; then, to design a data warehouse and nursing process clinical decision support system.
Henshall, Catherine; Marzano, Lisa; Smith, Katharine; Attenburrow, Mary-Jane; Puntis, Stephen; Zlodre, Jakov; Kelly, Kathleen; Broome, Matthew R; Shaw, Susan; Barrera, Alvaro; Molodynski, Andrew; Reid, Alastair; Geddes, John R; Cipriani, Andrea
Treatment decision tools have been developed in many fields of medicine, including psychiatry, however benefits for patients have not been sustained once the support is withdrawn. We have developed a web-based computerised clinical decision support tool (CDST), which can provide patients and clinicians with continuous, up-to-date, personalised information about the efficacy and tolerability of competing interventions. To test the feasibility and acceptability of the CDST we conducted a focus group study, aimed to explore the views of clinicians, patients and carers. The CDST was developed in Oxford. To tailor treatments at an individual level, the CDST combines the best available evidence from the scientific literature with patient preferences and values, and with patient medical profile to generate personalised clinical recommendations. We conducted three focus groups comprising of three different participant types: consultant psychiatrists, participants with a mental health diagnosis and/or experience of caring for someone with a mental health diagnosis, and primary care practitioners and nurses. Each 1-h focus group started with a short visual demonstration of the CDST. To standardise the discussion during the focus groups, we used the same topic guide that covered themes relating to the acceptability and usability of the CDST. Focus groups were recorded and any identifying participant details were anonymised. Data were analysed thematically and managed using the Framework method and the constant comparative method. The focus groups took place in Oxford between October 2016 and January 2017. Overall 31 participants attended (12 consultants, 11 primary care practitioners and 8 patients or carers). The main themes that emerged related to CDST applications in clinical practice, communication, conflicting priorities, record keeping and data management. CDST was considered a useful clinical decision support, with recognised value in promoting clinician
Wilson Carlene J
Full Text Available Abstract Background Australia has a comparatively high incidence of colorectal (bowel cancer; however, population screening uptake using faecal occult blood test (FOBT remains low. This study will determine the impact on screening participation of a novel, Internet-based Personalised Decision Support (PDS package. The PDS is designed to measure attitudes and cognitive concerns and provide people with individually tailored information, in real time, that will assist them with making a decision to screen. The hypothesis is that exposure to (tailored PDS will result in greater participation in screening than participation following exposure to non-tailored PDS or resulting from the current non-tailored, paper-based approach. Methods/design A randomised parallel trial comprising three arms will be conducted. Men and women aged 50-74 years (N = 3240 will be recruited. They must have access to the Internet; have not had an FOBT within the previous 12 months, or sigmoidoscopy or colonoscopy within the previous 5 years; have had no clinical diagnosis of bowel cancer. Groups 1 and 2 (PDS arms will access a website and complete a baseline survey measuring decision-to-screen stage, attitudes and cognitive concerns and will receive immediate feedback; Group 1 will receive information 'tailored' to their responses in the baseline survey and group 2 will received 'non-tailored' bowel cancer information. Respondents in both groups will subsequently receive an FOBT kit. Group 3 (usual practice arm will complete a paper-based version of the baseline survey and respondents will subsequently receive 'non-tailored' paper-based bowel cancer information with accompanying FOBT kit. Following despatch of FOBTs, all respondents will be requested to complete an endpoint survey. Main outcome measures are (1 completion of FOBT and (2 change in decision-to-screen stage. Secondary outcomes include satisfaction with decision and change in attitudinal scores from baseline to
Hong, Taehoon; Koo, Choongwan; Kim, Hyunjoong
The number of deteriorated multi-family housing complexes in South Korea continues to rise, and consequently their electricity consumption is also increasing. This needs to be addressed as part of the nation's efforts to reduce energy consumption. The objective of this research was to develop a decision support model for determining the need to improve multi-family housing complexes. In this research, 1664 cases located in Seoul were selected for model development. The research team collected the characteristics and electricity energy consumption data of these projects in 2009-2010. The following were carried out in this research: (i) using the Decision Tree, multi-family housing complexes were clustered based on their electricity energy consumption; (ii) using Case-Based Reasoning, similar cases were retrieved from the same cluster; and (iii) using a combination of Multiple Regression Analysis, Artificial Neural Network, and Genetic Algorithm, the prediction performance of the developed model was improved. The results of this research can be used as follows: (i) as basic research data for continuously managing several energy consumption data of multi-family housing complexes; (ii) as advanced research data for predicting energy consumption based on the project characteristics; (iii) as practical research data for selecting the most optimal multi-family housing complex with the most potential in terms of energy savings; and (iv) as consistent and objective criteria for incentives and penalties. Copyright © 2012 Elsevier Ltd. All rights reserved.
van Beusekom, Frits; Brazier, Frances; Schipper, Piet; Treur, Jan; del Pobil, A.P.
In this paper a knowledge-based decision support system is described that determines the abiotic (chemical and physical) characteristics of a site on the basis of in-homogeneous samples of plant species. Techniques from the area of non-monotonic reasoning are applied to model multi-interpretable
The present study is focused on the identification of suitable sites for locating water harvesting structures using morphometric analysis and multi-criteria based decision support system. The Hathmati watershed of river Hathmati at Idar taluka, Sabarkantha district, Gujarat is experiencing excessive runoff and soil erosion due ...
Full Text Available The operation of modern buildings can support a vast amount of static and real-time data. Static information such as building schematics is vital for security and rescue purposes. There is a need for building managers and for first responders to be notified of designated building alerts in real-time so that actions can be performed promptly. The capability to monitor building devices and to keep the first responder community updated with the latest building information during emergency situations, as well as the ability to remotely control certain building devices and processes, can be realized today. This paper describes the various challenges encountered in the research area of building interoperability and proposes methods and insights for developing a standards framework to enable communication between building information systems and first responder information systems. Having a standards framework in place will assist in the development and deployment of commercial products in support of building interoperability.
Hossain, Mohammad Shahadat; Hossain, Emran; Khalid, Md. Saifuddin
conditions of uncertainty. The Belief Rule-Based Inference Methodology Using the Evidential Reasoning (RIMER) approach was adopted to develop this expert system; which is named the Belief Rule-Based Expert System (BRBES). The system can handle various types of uncertainty in knowledge representation...
Based on a practical project and urban police professional work requirements, this paper has offered a solution for constructing the police spatial information decision support systems based on COM GIS technologies. According to the principles of software engineering, the systems development work contains the general system structure design, data requirements design, system function design, software interface design as well as the systems function realization methods. The main software technologies used in the systems development contain the spatial database, COM GIS, Web GIS, Oracle Objects for OLE (OO4O), and Police Decision Analysis Modeling technologies. In order to illustrate the basic principles and methods for the systems development, the realization process and relevant sample codes for crime case precaution function component has been described in the paper as an example for integrating GIS functions with police professional work models by using VC and VB developing tools. The realized systems function interfaces have also been offered in the paper for displaying the real effects of the systems. The development practice has proved that the COM GIS technology is very suitable for integrating police professional work models with GIS functions.
Kozulia, T.V.; Kozulia, M.M.
The mathematical model of natural-technogenic objects is substantiated in the article. Natural-technogenic object of research is defined in form of a system model, which includes the economic, ecological and social components and processes system occurring in the selected systems and in their interaction. Basis for introduction systematic analysis methods for consistent problematic environmental safety tasks solution under conditions of uncertainty has been formed. The complex methods system includes entropy theory provisions on the objects state evaluation, the comparator identification method, substantively substantiated for solving complex environment quality assessment problems. An example of ecological state technogenically loaded landscape-geochemical complexes on the proposed methodological support studied in the work.
and its surround, pictured below in Figure 1 and site of the large Kinyon Road fire in July 2012, was chosen as the initial application area for this...lands above. A GIS is designed for this type of fusion activity, providing a more complete sight picture to decision makers. In Figure 28, 1 August is...divisions are based on the changes in moisture content from “weather cycles of 1-day (diurnal), 4-day ( synoptic ), 30-day (planetary), and 1- year (annual
Kraus, Stefan; Castellanos, Ixchel; Toddenroth, Dennis; Prokosch, Hans-Ulrich; Bürkle, Thomas
The purpose of this study was to introduce clinical decision support (CDS) that exceeds conventional alerting at tertiary care intensive care units. We investigated physicians' functional CDS requirements in periodic interviews, and analyzed technical interfaces of the existing commercial patient data management system (PDMS). Building on these assessments, we adapted a platform that processes Arden Syntax medical logic modules (MLMs). Clinicians demanded data-driven, user-driven and time-driven execution of MLMs, as well as multiple presentation formats such as tables and graphics. The used PDMS represented a black box insofar as it did not provide standardized interfaces for event notification and external access to patient data; enabling CDS thus required periodically exporting datasets for making them accessible to the invoked Arden engine. A client-server-architecture with a simple browser-based viewer allows users to activate MLM execution and to access CDS results, while an MLM library generates hypertext for diverse presentation targets. The workaround that involves a periodic data replication entails a trade-off between the necessary computational resources and a delay of generated alert messages. Web technologies proved serviceable for reconciling Arden-based CDS functions with alternative presentation formats, including tables, text formatting, graphical outputs, as well as list-based overviews of data from several patients that the native PDMS did not support.
Anselin, L.; Henderson, J.S.
In a previous NRRI report (Anselin, Pike, Smith (1981), ''The Measurement of Electric Utility Performance: Preliminary Analysis''), an overview of several traditional methodologies to achieve this was presented (management audits, financial and engineering indexes, econometric studies), and a new technique based on multicriteria decision analysis was suggested. In this report, the decision analytic method for performance evaluation is considered in more detail, and compared to the more traditional approaches of a total factor productivity index (TFP) and econometric cost function estimates. Utility performance evaluation is considered as part of a decision support system, i.e., the combination of an information system (data base) and a set of operational decision rules (performance indexes). As part of this decision support system, an extensive data on 210 variables for 123 privately owned electric utilities over the period 1964-1981. Multicriteria evaluation techniques, such as the analytic hierarchy process and concordance analysis, and economic techniques, such as a total factor productivity (TFP) index and the residual analysis of econometric short- and long-run cost functions are discussed in detail with respect to their methodological and theoretical foundations. They are also implemented empirically on a common data base, and compared with respect to the resulting performance rating of the companies. 78 references.
Al-Jibouri, Saad H.S.; Mawdesley, Michael J.
This work describes the development of a project model centred on the information and knowledge generated and used by managers. It describes a knowledge-based system designed for this purpose. A knowledge acquisition exercise was undertaken to determine the tasks of project managers and the
Galina O. Artemova
Full Text Available This article is about an algorithm of educational ontology’s development based on intermediate models – mind maps and concept maps. It is offered to use different metrics such as subjective metrics and graph topology’s metrics for automated optimization of mind maps.
Larsen, Henrik Fred; Hansen, Peter Augusto; Boyer-Souchet, Florence
The environmental sustainability assessments described in this report is based on life cycle assessments (LCA) of selected waste water treatment technology (WWTT) cases included in NEPTUNE. The basic approach in these assessments (avoided against induced impacts) is described in Deliverable 4...... inventoried. Figure 2.1 Do we induce more environmental impact than we avoid by introducing a new waste water treatment technology (sub-optimisation)? The study is based as much as possible on data obtained directly from NEPTUNE partners for the physical and functional inventory. In particular, the functional.......1 (Larsen et al. 2007) and other methodological issues (e.g. normalization and weighting) in Deliverable 4.2 (Larsen et al. 2009). The basic approach is illustrated in a simplified way for the case ozonation in Figure 2.1. The technologies investigated include conventional WWT (reference), ozonation, sand...
Full Text Available In this paper a comprehensive framework that maximizes advertising revenues of a company in a personalized advertisement setting is presented. The research was motivated from a real life problem faced by a company that develops a web based 3-D virtual reality social platform. The objective of the research was both development of a business model and the framework. Four heuristics are proposed as part of the framework. The performance of these heuristics was tested with an experimental analysis.
Bajo Pérez, Javier; Paz Santana, Juan Francisco de; Rodríguez, Sara; Corchado Rodríguez, Juan Manuel
[EN]Microarray technology can measure the expression levels of thousands of genes in an experiment. This fact makes the use of computational methods in cancer research absolutely essential. One of the possible applications is in the use of Artificial Intelligence techniques. Several of these techniques have been used to analyze expression arrays, but there is a growing need for new and effective solutions. This paper presents a Case-based reasoning (CBR) system for automatic classification of...
Africa, E.; Nehzati, T.; Strandhagen, J.O.
This study aims to identify the actual needs of decision makers for decision support in the production control activity, considering the role and cognitive skills of human decision-makers in the decision-making process. Multiple case studies have been conducted in order to gain practical insights...... from the manufacturing industry. This paper contributes to raise the issues that should be considered for successful implementation of the decision support systems in practice....
Crabtree, Elizabeth A; Brennan, Emily; Davis, Amanda; Squires, Jerry E
Evidence-based practice (EBP) skills are crucial for delivering high-quality patient care. It is essential that medical students learn EBP concepts through a practical, in-depth research project. To date, literature on preparing students in this manner is limited. In academic year 2014-2015, the Medical University of South Carolina's (MUSC's) Center for Evidence-Based Practice (now known as the Value Institute) partnered with College of Medicine faculty to revitalize the undergraduate medical student EBP curriculum. Without adding to the number of the lecture hours, the curriculum was restructured to be more process driven, project based, and clinically relevant. The resulting yearlong EBP course partnered small teams of medical students with interprofessional clinical teams to engage the students in developing evidence-based clinical decision support tools. The content developed during the EBP projects is currently being used to develop evidence-based clinical practice guidelines and accompanying order sets. It is likely that this model will serve as a new framework for guideline development and will greatly expand the breadth of evidence-based content currently produced and available for clinicians at the MUSC. It would be feasible to offer a similar course within the MUSC to other disciplines and colleges, or at other institutions, if there were support from administration, interest on the part of clinicians and medical faculty, and individuals with the required expertise available to develop the curriculum and facilitate the course. It is worth considering how to improve the course and evaluating opportunities to implement it within other settings.
Full Text Available This paper describes the use of machine learning methods to build a decision support system for predicting the distribution of coastal ocean algal blooms based on remote sensing data in Monterey Bay. This system can help scientists obtain prior information in a large ocean region and formulate strategies for deploying robots in the coastal ocean for more detailed in situ exploration. The difficulty is that there are insufficient in situ data to create a direct statistical machine learning model with satellite data inputs. To solve this problem, we built a Random Forest model using MODIS and MERIS satellite data and applied a threshold filter to balance the training inputs and labels. To build this model, several features of remote sensing satellites were tested to obtain the most suitable features for the system. After building the model, we compared our random forest model with previous trials based on a Support Vector Machine (SVM using satellite data from 221 days, and our approach performed significantly better. Finally, we used the latest in situ data from a September 2014 field experiment to validate our model.
Background We have developed a framework for translating existing sources of synthesized and quality-assessed evidence, primarily systematic reviews, into actionable messages in the form of short accessible briefings. The service aims to address real-life problems in response to requests from decision-makers. Development of the framework was based on a scoping review of existing resources and our initial experience with two briefing topics, including models of service provision for young people with eating disorders. We also drew on previous experience in dissemination research and practice. Where appropriate, we made use of the SUPporting POlicy relevant Reviews and Trials (SUPPORT) tools for evidence-informed policymaking. Findings To produce a product that it is fit for this purpose it has been necessary to go beyond a traditional summary of the available evidence relating to effectiveness. Briefings have, therefore, included consideration of cost effectiveness, local applicability, implications relating to local service delivery, budgets, implementation and equity. Our first evidence briefings produced under this framework cover diagnostic endoscopy by specialist nurses and integrated care pathways in mental healthcare settings. Conclusions The framework will enable researchers to present and contextualize evidence from systematic reviews and other sources of synthesized and quality-assessed evidence. The approach is designed to address the wide range of questions of interest to decision-makers, especially those commissioning services or managing service delivery and organization in primary or secondary care. Evaluation of the use and usefulness of the evidence briefings we produce is an integral part of the framework and will help to fill a gap in the literature. PMID:22775986
Full Text Available Abstract Background We have developed a framework for translating existing sources of synthesized and quality-assessed evidence, primarily systematic reviews, into actionable messages in the form of short accessible briefings. The service aims to address real-life problems in response to requests from decision-makers. Development of the framework was based on a scoping review of existing resources and our initial experience with two briefing topics, including models of service provision for young people with eating disorders. We also drew on previous experience in dissemination research and practice. Where appropriate, we made use of the SUPporting POlicy relevant Reviews and Trials (SUPPORT tools for evidence-informed policymaking. Findings To produce a product that it is fit for this purpose it has been necessary to go beyond a traditional summary of the available evidence relating to effectiveness. Briefings have, therefore, included consideration of cost effectiveness, local applicability, implications relating to local service delivery, budgets, implementation and equity. Our first evidence briefings produced under this framework cover diagnostic endoscopy by specialist nurses and integrated care pathways in mental healthcare settings. Conclusions The framework will enable researchers to present and contextualize evidence from systematic reviews and other sources of synthesized and quality-assessed evidence. The approach is designed to address the wide range of questions of interest to decision-makers, especially those commissioning services or managing service delivery and organization in primary or secondary care. Evaluation of the use and usefulness of the evidence briefings we produce is an integral part of the framework and will help to fill a gap in the literature.
Full Text Available Aim of the study: Decision support systems for forest management (FMDSS have been developed world wide to account for a broad range of forest ecosystems, management goals and organizational frameworks (e.g. the wiki page of the FORSYS project reports 62 existing FMDSSs from 23 countries. The need to enhance the collaboration among this diverse community of developers and users fostered the rise of new group communication processes that could capture useful knowledge from past experiences in order to efficiently provide it to new FMDSS development efforts.Material and methods: This paper presents and tests an exploratory process aiming to identify the empirical guidelines assisting developers and users of FMDSS. This process encompasses aDelphi survey built upon the consolidation of the lessons-learned statements that summarize the past experiences of the experts involved in the FORSYS project. The experts come from 34 countries and have diverse interests, ranging from forest planners, IT developers, social scientists studying participatory planning, and researchers with interests in knowledge management and in quantitative models for forest planning.Main results: The proposed 37 empirical guidelines that group 102 lessons-learned cover a broad range of issues including the DSS development cycle, involvement of the stakeholders, methods, models and knowledge-based techniques in use.Research highlights: These results may be used for improving new FMDSS development processes, teaching and training and further suggest new features of FMDSS and future research topics. Furthermore, the guidelines may constitute a knowledge repository that may be continuously improved by a community of practice.Keywords: Forest management; guidelines; guidelines definition process; lessons learned; decision support systems; system architecture; knowledge management; participatory planning; Delphi.
Martín Ruiz, María Luisa; Valero Duboy, Miguel Ángel; Torcal Loriente, Carmen; Pau de la Cruz, Iván
Early and effective identification of developmental disorders during childhood remains a critical task for the international community. The second highest prevalence of common developmental disorders in children are language delays, which are frequently the first symptoms of a possible disorder. This paper evaluates a Web-based Clinical Decision Support System (CDSS) whose aim is to enhance the screening of language disorders at a nursery school. The common lack of early diagnosis of language disorders led us to deploy an easy-to-use CDSS in order to evaluate its accuracy in early detection of language pathologies. This CDSS can be used by pediatricians to support the screening of language disorders in primary care. This paper details the evaluation results of the "Gades" CDSS at a nursery school with 146 children, 12 educators, and 1 language therapist. The methodology embraces two consecutive phases. The first stage involves the observation of each child's language abilities, carried out by the educators, to facilitate the evaluation of language acquisition level performed by a language therapist. Next, the same language therapist evaluates the reliability of the observed results. The Gades CDSS was integrated to provide the language therapist with the required clinical information. The validation process showed a global 83.6% (122/146) success rate in language evaluation and a 7% (7/94) rate of non-accepted system decisions within the range of children from 0 to 3 years old. The system helped language therapists to identify new children with potential disorders who required further evaluation. This process will revalidate the CDSS output and allow the enhancement of early detection of language disorders in children. The system does need minor refinement, since the therapists disagreed with some questions from the CDSS knowledge base (KB) and suggested adding a few questions about speech production and pragmatic abilities. The refinement of the KB will address
Power, Daniel J
Competition is becoming more intense and decision makers are encountering increasing complexity, rapid change, and higher levels of risk. In many situations, the solution is more and better computerized decision support, especially analytics and business intelligence. Today managers need to learn about and understand computerized decision support. If a business is to succeed, managers must know much more about information technology solutions. This second edition of a powerful introductory book is targeted at busy managers and MBA students who need to grasp the basics of computerized decision support, including the following: What are analytics? What is a decision support system? How can managers identify opportunities to create innovative computerized support? Inside, the author addresses these questions and some 60 more fundamental questions that are key to understanding the rapidly changing realm of computerized decision support. In a short period of time, you'll "get up to speed" on decision support, anal...
Full Text Available An innovative newly developed modular and standards based Decision Support System (DSS is presented which forms part of the German Indonesian Tsunami Early Warning System (GITEWS. The GITEWS project stems from the effort to implement an effective and efficient Tsunami Early Warning and Mitigation System for the coast of Indonesia facing the Sunda Arc along the islands of Sumatra, Java and Bali. The geological setting along an active continental margin which is very close to densely populated areas is a particularly difficult one to cope with, because potential tsunamis' travel times are thus inherently short. National policies require an initial warning to be issued within the first five minutes after an earthquake has occurred. There is an urgent requirement for an end-to-end solution where the decision support takes the entire warning chain into account. The system of choice is based on pre-computed scenario simulations and rule-based decision support which is delivered to the decision maker through a sophisticated graphical user interface (GUI using information fusion and fast information aggregation to create situational awareness in the shortest time possible. The system also contains risk and vulnerability information which was designed with the far end of the warning chain in mind – it enables the decision maker to base his acceptance (or refusal of the supported decision also on regionally differentiated risk and vulnerability information (see Strunz et al., 2010. While the system strives to provide a warning as quickly as possible, it is not in its proper responsibility to send and disseminate the warning to the recipients. The DSS only broadcasts its messages to a dissemination system (and possibly any other dissemination system which is operated under the responsibility of BMKG – the meteorological, climatological and geophysical service of Indonesia – which also hosts the tsunami early warning center. The system is to be seen
Shaker H. El-Sappagh
Full Text Available This paper proposes an open and distributed clinical decision support system architecture. This technical architecture takes advantage of Electronic Health Record (EHR, data mining techniques, clinical databases, domain expert knowledge bases, available technologies and standards to provide decision-making support for healthcare professionals. The architecture will work extremely well in distributed EHR environments in which each hospital has its own local EHR, and it satisfies the compatibility, interoperability and scalability objectives of an EHR. The system will also have a set of distributed knowledge bases. Each knowledge base will be specialized in a specific domain (i.e., heart disease, and the model achieves cooperation, integration and interoperability between these knowledge bases. Moreover, the model ensures that all knowledge bases are up-to-date by connecting data mining engines to each local knowledge base. These data mining engines continuously mine EHR databases to extract the most recent knowledge, to standardize it and to add it to the knowledge bases. This framework is expected to improve the quality of healthcare, reducing medical errors and guaranteeing the safety of patients by helping clinicians to make correct, accurate, knowledgeable and timely decisions.
Kukhareva, Polina V; Kawamoto, Kensaku; Shields, David E; Barfuss, Darryl T; Halley, Anne M; Tippetts, Tyler J; Warner, Phillip B; Bray, Bruce E; Staes, Catherine J
Electronic quality measurement (QM) and clinical decision support (CDS) are closely related but are typically implemented independently, resulting in significant duplication of effort. While it seems intuitive that technical approaches could be re-used across these two related use cases, such reuse is seldom reported in the literature, especially for standards-based approaches. Therefore, we evaluated the feasibility of using a standards-based CDS framework aligned with anticipated EHR certification criteria to implement electronic QM. The CDS-QM framework was used to automate a complex national quality measure (SCIP-VTE-2) at an academic healthcare system which had previously relied on time-consuming manual chart abstractions. Compared with 305 manually-reviewed reference cases, the recall of automated measurement was 100%. The precision was 96.3% (CI:92.6%-98.5%) for ascertaining the denominator and 96.2% (CI:92.3%-98.4%) for the numerator. We therefore validated that a standards-based CDS-QM framework can successfully enable automated QM, and we identified benefits and challenges with this approach. PMID:25954389
Nielsen, Ulrik Dam; Friis-Hansen, Peter; Jensen, Jørgen Juncher
Onboard decision support systems (DSS) are used to increase the operational safety of ships. Ideally, DSS can estimate future ship responses within a time scale of the order of 1–3 h taking into account speed and course changes, assuming stationary sea states. In principle, the calculations depend...
Pecen, Ladislav; Eben, Kryštof; Vondráček, Jiří; Holubec, L.; Topolčan, O.; Pikner, R.; Kausitz, J.; Nekulová, M.; Šimíčková, M.
Roč. 23, Suppl.1 (2002), s. 38 ISSN 1010-4283. [Meeting of the International Society for Oncodevelopmental Biology and Medicine /30./. 08.09.2002-12.09.2002, Boston] Institutional research plan: AV0Z1030915 Keywords : tumor markers * decision support systems Subject RIV: BA - General Mathematics
Heussen, Kai; Weckesser, Johannes Tilman Gabriel; Kullmann, Daniel
Improved information and insight for decision support in operations and design are central promises of a smart grid. Well-structured information about the composition of power systems is increasingly becoming available in the domain, e.g. due to standard information models (e.g. CIM or IEC61850...
Alexandra Polášková; Jitka Feberová; Taťjána Dostálová; Pavel Kříž; Michaela Seydlová
Implantology is rapidly developing interdisciplinary field providing enormous amounts of data to be classified, evaluated and interpreted. The analysis of clinical data remains a big challenge, because each new system has specific requirements. The aim of study was prepare specific tool for treatment planning. Decision support system is built on Expert system. It is interactive software which provides clinical recommendations and treatment planning. Expert systems are knowledge-based computer...
Yager, Ronald R.
We first formulate the problem of decision making under uncertainty. The importance of the representation of our knowledge about the uncertainty in formulating a decision process is pointed out. We begin with a brief discussion of the case of probabilistic uncertainty. Next, in considerable detail, we discuss the case of decision making under ignorance. For this case the fundamental role of the attitude of the decision maker is noted and its subjective nature is emphasized. Next the case in which a Dempster-Shafer belief structure is used to model our knowledge of the uncertainty is considered. Here we also emphasize the subjective choices the decision maker must make in formulating a decision function. The case in which the uncertainty is represented by a fuzzy measure (monotonic set function) is then investigated. We then return to the Dempster-Shafer belief structure and show its relationship to the fuzzy measure. This relationship allows us to get a deeper understanding of the formulation the decision function used Dempster- Shafer framework. We discuss how this deeper understanding allows a decision analyst to better make the subjective choices needed in the formulation of the decision function
Shirkhodaie, Amir; Elangovan, Vinayak; Alkilani, Amjad; Habibi, Mohammad
This paper presents an ongoing effort towards development of an intelligent Decision-Support System (iDSS) for fusion of information from multiple sources consisting of data from hard (physical sensors) and soft (textural sources. Primarily, this paper defines taxonomy of decision support systems for latent semantic data mining from heterogeneous data sources. A Probabilistic Latent Semantic Analysis (PLSA) approach is proposed for latent semantic concepts search from heterogeneous data sources. An architectural model for generating semantic annotation of multi-modality sensors in a modified Transducer Markup Language (TML) is described. A method for TML messages fusion is discussed for alignment and integration of spatiotemporally correlated and associated physical sensory observations. Lastly, the experimental results which exploit fusion of soft/hard sensor sources with support of iDSS are discussed.
Caballero-Ruiz, Estefanía; García-Sáez, Gema; Rigla, Mercedes; Villaplana, María; Pons, Belen; Hernando, M Elena
The growth of diabetes prevalence is causing an increasing demand in health care services which affects the clinicians' workload as medical resources do not grow at the same rate as the diabetic population. Decision support tools can help clinicians with the inspection of monitoring data, providing a preliminary analysis to ease their interpretation and reduce the evaluation time per patient. This paper presents Sinedie, a clinical decision support system designed to manage the treatment of patients with gestational diabetes. Sinedie aims to improve access to specialized healthcare assistance, to prevent patients from unnecessary displacements, to reduce the evaluation time per patient and to avoid gestational diabetes adverse outcomes. A web-based telemedicine platform was designed to remotely evaluate patients allowing them to upload their glycaemia data at home directly from their glucose meter, as well as report other monitoring variables like ketonuria and compliance to dietary treatment. Glycaemia values, not tagged by patients, are automatically labelled with their associated meal by a classifier based on the Expectation Maximization clustering algorithm and a C4.5 decision tree learning algorithm. Two finite automata are combined to determine the patient's metabolic condition, which is analysed by a rule-based knowledge base to generate therapy adjustment recommendations. Diet recommendations are automatically prescribed and notified to the patients, whereas recommendations about insulin requirements are notified also to the physicians, who will decide if insulin needs to be prescribed. The system provides clinicians with a view where patients are prioritized according to their metabolic condition. A randomized controlled clinical trial was designed to evaluate the effectiveness and safety of Sinedie interventions versus standard care and its impact in the professionals' workload in terms of the clinician's time required per patient; number of face
Hansen, Poul H. Kyvsgård; Mikkola, Juliana Hsuan
is the application of on-line games in order to provide training for decision makers and in order to generate overview over the implications of platform decisions. However, games have to be placed in a context with other methods and we argue that a mixture of games, workshops, and simulations can provide improved...
Lobanova, E. N.; Zmitrovich, A. I.; Voshevoz, A. A.; Krivko-Krasko, A. V.
In this article we consider concepts and components of the Financial Decision Making System that is being developed in the Institute of Business and Management Technology, BSU. Such system can be successfully used either for training experts in financial analytics and financial management or for financial managers and financial directors in an enterprise for the effective financial decision making.
Workman, T Elizabeth; Fiszman, Marcelo; Hurdle, John F
Abstract Background PubMed data potentially can provide decision support information, but PubMed was not exclusively designed to be a point-of-care tool. Natural language processing applications that summarize PubMed citations hold promise for extracting decision support information. The objective of this study was to evaluate the efficiency of a text summarization application called Semantic MEDLINE, enhanced with a novel dynamic summarization method, in identifying decision support data. Me...
Rajeevan, Nallakkandi; Niehoff, Kristina M; Charpentier, Peter; Levin, Forrest L; Justice, Amy; Brandt, Cynthia A; Fried, Terri R; Miller, Perry L
The US Veterans Administration (VA) has developed a robust and mature computational infrastructure in support of its electronic health record (EHR). Web technology offers a powerful set of tools for structuring clinical decision support (CDS) around clinical care. This paper describes informatics challenges and design issues that were confronted in the process of building three Web-based CDS systems in the context of the VA EHR. Over the course of several years, we implemented three Web-based CDS systems that extract patient data from the VA EHR environment to provide patient-specific CDS. These were 1) the VACS (Veterans Aging Cohort Study) Index Calculator which estimates prognosis for HIV+ patients, 2) Neuropath/CDS which assists in the medical management of patients with neuropathic pain, and 3) TRIM (Tool to Reduce Inappropriate Medications) which identifies potentially inappropriate medications in older adults and provides recommendations for improving the medication regimen. The paper provides an overview of the VA EHR environment and discusses specific informatics issues/challenges that arose in the context of each of the three Web-based CDS systems. We discuss specific informatics methods and provide details of approaches that may be useful within this setting. Informatics issues and challenges relating to data access and data availability arose because of the particular architecture of the national VA infrastructure and the need to link to that infrastructure from local Web-based CDS systems. Idiosyncrasies of VA patient data, especially the medication data, also posed challenges. Other issues related to specific functional needs of individual CDS systems. The goal of this paper is to describe these issues so that our experience may serve as a useful foundation to assist others who wish to build such systems in the future.
Benjamin W. Heumann
Full Text Available Mangroves provide valuable ecosystem goods and services such as carbon sequestration, habitat for terrestrial and marine fauna, and coastal hazard mitigation. The use of satellite remote sensing to map mangroves has become widespread as it can provide accurate, efficient, and repeatable assessments. Traditional remote sensing approaches have failed to accurately map fringe mangroves and true mangrove species due to relatively coarse spatial resolution and/or spectral confusion with landward vegetation. This study demonstrates the use of the new Worldview-2 sensor, Object-based image analysis (OBIA, and support vector machine (SVM classification to overcome both of these limitations. An exploratory spectral separability showed that individual mangrove species could not be spectrally separated, but a distinction between true and associate mangrove species could be made. An OBIA classification was used that combined a decision-tree classification with the machine-learning SVM classification. Results showed an overall accuracy greater than 94% (kappa = 0.863 for classifying true mangroves species and other dense coastal vegetation at the object level. There remain serious challenges to accurately mapping fringe mangroves using remote sensing data due to spectral similarity of mangrove and associate species, lack of clear zonation between species, and mixed pixel effects, especially when vegetation is sparse or degraded.
Chen, Wei; Zhang, Junfeng; Gao, Mingyi; Shen, Gangxiang
High-order modulation signals are suited for high-capacity communication systems because of their high spectral efficiency, but they are more vulnerable to various impairments. For the signals that experience degradation, when symbol points overlap on the constellation diagram, the original linear decision boundary cannot be used to distinguish the classification of symbol. Therefore, it is advantageous to create an optimum symbol decision boundary for the degraded signals. In this work, we experimentally demonstrated the 64-quadrature-amplitude modulation (64-QAM) coherent optical communication system using support-vector machine (SVM) decision boundary algorithm to create the optimum symbol decision boundary for improving the system performance. We investigated the influence of various impairments on the 64-QAM coherent optical communication systems, such as the impairments caused by modulator nonlinearity, phase skew between in-phase (I) arm and quadrature-phase (Q) arm of the modulator, fiber Kerr nonlinearity and amplified spontaneous emission (ASE) noise. We measured the bit-error-ratio (BER) performance of 75-Gb/s 64-QAM signals in the back-to-back and 50-km transmission. By using SVM to optimize symbol decision boundary, the impairments caused by I/Q phase skew of the modulator, fiber Kerr nonlinearity and ASE noise are greatly mitigated.
Khanian, Seyed Mohammad Shafi
Vehicle Routing and Scheduling (VRS) constitute an important part of logistics management. Given the fact that the worldwide cost on physical distribution is evermore increasing, the global competition and the complex nature of logistics problems, one area, which determines the efficiency of all others, is the VRS activities. The application of Decision Support Systems (DSS) to assist logistics management with an efficient VRS could be of great benefit. Although the benefits of DSS in VRS are...
Full Text Available In 1997–1998, the Netherlands experienced a large epidemic of classical swine fever (CSF. The magnitude of this epidemic stressed the role information systems could play in supporting the management during an eradication campaign. The enforcement of an eradication strategy can become very complicated, especially with large epidemics, due to time pressure and many different procedures that have to be executed at the same time. The application of comprehensive information systems may result in more control over the process and in a relief of the operational management. After a brief description of the Dutch epidemic the authors provide an overview and the general application of four different types of information systems, classified as decision support systems. The application of these information systems in animal disease control is illustrated by providing concepts for a system architecture for transaction processing, management and executive information support and decision support. The application of a data warehouse as part of this systems architecture is explained. The eradication of CSF from the Netherlands was complicated by several factors. It is important to notice that information systems cannot prevent these factors. However, information systems can support disease control authorities in controlling these factors.
Full Text Available Generalised uncertainty, a phenomenon that today’s managers are facing as part of their professional experience, makes it impossible to anticipate the way the business environment will evolve or what will be the consequences of the decisions they plan to implement. Any decision making process within the company entails the simultaneous presence of a number of economic, technical, juridical, human and managerial variables. The development and the approval of a decision is the result of decision making activities developed by the decision maker and sometimes by a decision support team or/and a decision support system (DSS. These aspects related to specific applications of decision support systems in risk management will be approached in this research paper. Decisions in general and management decisions in particular are associated with numerous risks, due to their complexity and increasing contextual orientation. In each business entity, there are concerns with the implementation of risk management in order to improve the likelihood of meeting objectives, the trust of the parties involved, increase the operational safety and security as well as the protection of the environment, minimise losses, improve organisational resilience in order to diminish the negative impact on the organisation and provide a solid foundation for decision making. Since any business entity is considered to be a wealth generator, the analysis of their performance should not be restricted to financial efficiency alone, but will also encompass their economic efficiency as well. The type of research developed in this paper entails different dimensions: conceptual, methodological, as well as empirical testing. Subsequently, the conducted research entails a methodological side, since the conducted activities have resulted in the presentation of a simulation model that is useful in decision making processes on the capital market. The research conducted in the present paper
Lewis, Timothy J.; Mitchell, Barbara S.
Students with emotional and behavioral disorders are at great risk for long-term negative outcomes. Researchers and practitioners alike acknowledge the need for evidence-based, preventive, and early intervention strategies. Accordingly, in this chapter an expanded view of prevention is presented as a series of data driven decisions to guide…
Arwin Datumaya Wahyudi Sumari
Full Text Available Quick, accurate, and complete information is highly required for supporting strategically impact decision making in a Military Operation (MO in order to reduce the decision cycle and to minimize the loss. For that purpose, we propose, design and implement a hierarchical Multi Agent-based Information Fusion System for Decision Making Support (MAIFS-DMS. The information fusion is implemented by applying Maximum Score of the Total Sum of Joint Probabilities (MSJP fusion method and is done by a collection of Information Fusion Agents (IFA that forms a multiagent system. MAIFS uses a combination of generalization of Dasarathy and Joint Director’s Laboratory (JDL process models for information fusion mechanism. Information fusion products that are displayed in graphical forms provide comprehensive information regarding the MO area dynamics. By observing the graphics resulted from the information fusion, the commandant will have situational awareness and knowledge in order to make the most accurate strategic decision as fast as possible
Nii Antiaye Addy
Full Text Available Multi-stakeholder partnerships (MSPs have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a “portrait”, which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed
Jansen, Anton; Ven, Jan van der; Avgeriou, Paris; Hammer, Dieter K.
In contrast to software architecture models, architectural decisions are often not explicitly documented, and therefore eventually lost. This contributes to major problems such as high-cost system evolution, stakeholders miscommunication, and limited reusability of core system assets. An approach is
Describes research at Leicester Polytechnic Institute (UK) which examined possible applications of decision support system tools in libraries; in particular, this research explored the role of decision support systems in relation to the development of resources allocation modelling. (five references) (MAB)
Laffineur, Quentin; Haeffelin, Martial; Bravo-Aranda, Juan-Antonio; Drouin, Marc-Antoine; Casquero-Vera, Juan-Andrés; Dupont, Jean-Charles; De Backer, Hugo
Radiation fog is the most frequent cause of surface visibility below 1 km, and is one of the most common and persistent weather hazards encountered in aviation and to nearly all forms of surface transport. Forecasting radiation fog can be difficult, a number of approaches have been used to integrate the satellite data, numerical modeling and standard surface observations. These approaches lack generally the vertical and temporal resolution, representation of boundary layer and microphysical processes. They typically do not represent accurately the activation processes of fog droplets that depend on the chemical and physical properties of the aerosols. The automatic LIDAR-ceilometer (ALC) primarily designed for cloud base height detection has greatly improved over the last years and now offers the opportunity to analyse in near real-time the backscatter signal in the boundary layer that potentially contains major information to predict radiation fog formation or not. During the preliminary stage of fog formation, the backscatter profile may be influenced by atmospheric humidity due to the presence in the atmosphere of hygroscopic aerosols that see their size increase with their moisture content inducing an increase of the backscatter magnitude. In the framework of TOPROF (COST-ACTION, http://www.toprof.imaa.cnr.it/) activities, collaboration was initiated between the Royal Meteorological Institute of Belgium (RMI) and the Site Instrumental de Recherche par Télédéction Atmosphérique (SIRTA, IPSL) to develop a forward stepwise screening algorithm (PARAFOG) to help prediction of radiation fog formation. PARAFOG is a new decision support system for radiation fog forecasting based on analysis of the attenuated backscatter measured by ALCs, found at most airports, which provides information about the aerosol-particle hygroscopic growth process (Haeffelin et al., 2016). The monitoring of this hygroscopic growth process could provide useful warning to forecasters, in
Marques, A. F.; Ficko, A.; Kangas, A.; Rosset, C.; Ferreti, F.; Rasinmaki, J.; Packalen, T.; Gordom, S.
Aim of the study: Decision support systems for forest management (FMDSS) have been developed world wide to account for a broad range of forest ecosystems, management goals and organizational frameworks (e.g. the wiki page of the FORSYS project reports 62 existing FMDSSs from 23 countries). The need to enhance the collaboration among this diverse community of developers and users fostered the rise of new group communication processes that could capture useful knowledge from past experiences in order to efficiently provide it to new FMDSS development efforts. Material and methods: This paper presents and tests an exploratory process aiming to identify the empirical guidelines assisting developers and users of FMDSS. This process encompasses a Delphi survey built upon the consolidation of the lessons-learned statements that summarize the past experiences of the experts involved in the FORSYS project. The experts come from 34 countries and have diverse interests, ranging from forest planners, IT developers, social scientists studying participatory planning, and researchers with interests in knowledge management and in quantitative models for forest planning. Main results: The proposed 37 empirical guidelines that group 102 lessons-learned cover a broad range of issues including the DSS development cycle, involvement of the stakeholders, methods, models and knowledge based techniques in use. Research highlights: These results may be used for improving new FMDSS development processes, teaching and training and further suggest new features of FMDSS and future research topics. Furthermore, the guidelines may constitute a knowledge repository that may be continuously improved by a community of practice. (Author)
Fung, Kin Wah; Kapusnik-Uner, Joan; Cunningham, Jean; Higby-Baker, Stefanie; Bodenreider, Olivier
To compare 3 commercial knowledge bases (KBs) used for detection and avoidance of potential drug-drug interactions (DDIs) in clinical practice. Drugs in the DDI tables from First DataBank (FDB), Micromedex, and Multum were mapped to RxNorm. The KBs were compared at the clinical drug, ingredient, and DDI rule levels. The KBs were evaluated against a reference list of highly significant DDIs from the Office of the National Coordinator for Health Information Technology (ONC). The KBs and the ONC list were applied to a prescription data set to simulate their use in clinical decision support. The KBs contained 1.6 million (FDB), 4.5 million (Micromedex), and 4.8 million (Multum) clinical drug pairs. Altogether, there were 8.6 million unique pairs, of which 79% were found only in 1 KB and 5% in all 3 KBs. However, there was generally more agreement than disagreement in the severity rankings, especially in the contraindicated category. The KBs covered 99.8-99.9% of the alerts of the ONC list and would have generated 25 (FDB), 145 (Micromedex), and 84 (Multum) alerts per 1000 prescriptions. The commercial KBs differ considerably in size and quantity of alerts generated. There is less variability in severity ranking of DDIs than suggested by previous studies. All KBs provide very good coverage of the ONC list. More work is needed to standardize the editorial policies and evidence for inclusion of DDIs to reduce variation among knowledge sources and improve relevance. Some DDIs considered contraindicated in all 3 KBs might be possible candidates to add to the ONC list. Published by Oxford University Press on behalf of the American Medical Informatics Association 2017. This work is written by US Government employees and is in the public domain in the United States.
Full Text Available Implantology is rapidly developing interdisciplinary field providing enormous amounts of data to be classified, evaluated and interpreted. The analysis of clinical data remains a big challenge, because each new system has specific requirements. The aim of study was prepare specific tool for treatment planning. Decision support system is built on Expert system. It is interactive software which provides clinical recommendations and treatment planning. Expert systems are knowledge-based computer programs designed to provide assistance in diagnosis and treatment planning. These systems are used for health care (dentistry, medicine, pharmacy etc.. The application contained the medical history analysis to obtaining information useful in formulating a diagnosis and providing implant insertion and prosthetic reconstruction to the patient; the diagnostic examination of dental implant procedure; implant positioning diagnosis – 3-D measurement; diagnostic information for treatment planning; treatment plan in the form of objective measurement of implant placement that helps surgeon and prosthodontics. The decision algorithm implemented by programming language is used. Core of program is an expert knowledge programming like a decision tree. The analysis of the decision-making process for implant treatment in general practice is prepared and analyzed.
Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.
The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).
Cirstoiu, C; Betev, L; Saiz, P; Peters, A J; Muraru, A; Voicu, R; Legrand, I
We are developing a general purpose monitoring system for the ALICE experiment, based on the MonALISA framework. MonALISA (Monitoring Agents using a Large Integrated Services Architecture) is a fully distributed system with no single point of failure that is able to collect, store monitoring information and present it as significant perspectives and synthetic views on the status and the trends of the entire system. Furthermore, agents can use it for taking automated operational decisions. Monitoring information is gathered locally from all the components running in each site. The entire flow of information is aggregated on site level by a MonALISA service and then collected and presented in various forms by a central MonALISA Repository. Based on this information, other services take operational decisions such as alerts, triggers, service restarts and automatic production job or transfer submissions. The system monitors all the components: computer clusters (all major parameters of each computing node), jobs ...
Harris, Claire; Allen, Kelly; Waller, Cara; Dyer, Tim; Brooke, Vanessa; Garrubba, Marie; Melder, Angela; Voutier, Catherine; Gust, Anthony; Farjou, Dina
This is the seventh in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. The SHARE Program was a systematic, integrated, evidence-based program for resource allocation within a large Australian health service. It aimed to facilitate proactive use of evidence from research and local data; evidence-based decision-making for resource allocation including disinvestment; and development, implementation and evaluation of disinvestment projects. From the literature and responses of local stakeholders it was clear that provision of expertise and education, training and support of health service staff would be required to achieve these aims. Four support services were proposed. This paper is a detailed case report of the development, implementation and evaluation of a Data Service, Capacity Building Service and Project Support Service. An Evidence Service is reported separately. Literature reviews, surveys, interviews, consultation and workshops were used to capture and process the relevant information. Existing theoretical frameworks were adapted for evaluation and explication of processes and outcomes. Surveys and interviews identified current practice in use of evidence in decision-making, implementation and evaluation; staff needs for evidence-based practice; nature, type and availability of local health service data; and preferred formats for education and training. The Capacity Building and Project Support Services were successful in achieving short term objectives; but long term outcomes were not evaluated due to reduced funding. The Data Service was not implemented at all. Factors influencing the processes and outcomes are discussed. Health service staff need access to education, training, expertise and support to enable evidence-based decision-making and to implement and evaluate the changes arising from those decisions. Three support services were proposed based on research
Jarre, Astrid; Paterson, Barbara; Moloney, Coleen L.; Miller, David C. M.; Field, John G.; Starfield, Anthony M.
In an ecosystem approach to fisheries (EAF), management must draw on information of widely different types, and information addressing various scales. Knowledge-based systems assist in the decision-making process by summarising this information in a logical, transparent and reproducible way. Both rule-based Boolean and fuzzy-logic models have been used successfully as knowledge-based decision support tools. This study compares two such systems relevant to fisheries management in an EAF developed for the southern Benguela. The first is a rule-based system for the prediction of anchovy recruitment and the second is a fuzzy-logic tool to monitor implementation of an EAF in the sardine fishery. We construct a fuzzy-logic counterpart to the rule-based model, and a rule-based counterpart to the fuzzy-logic model, compare their results, and include feedback from potential users of these two decision support tools in our evaluation of the two approaches. With respect to the model objectives, no method clearly outperformed the other. The advantages of numerically processing continuous variables, and interpreting the final output, as in fuzzy-logic models, can be weighed up against the advantages of using a few, qualitative, easy-to-understand categories as in rule-based models. The natural language used in rule-based implementations is easily understood by, and communicated among, users of these systems. Users unfamiliar with fuzzy-set theory must “trust” the logic of the model. Graphical visualization of intermediate and end results is an important advantage of any system. Applying the two approaches in parallel improved our understanding of the model as well as of the underlying problems. Even for complex problems, small knowledge-based systems such as the ones explored here are worth developing and using. Their strengths lie in (i) synthesis of the problem in a logical and transparent framework, (ii) helping scientists to deliberate how to apply their science to
Rupnik, Rok; Kukar, Matjaž
Traditional techniques of data analysis do not enable the solution of all kind of problems and for that reason they have become insufficient. This caused a newinterdisciplinary field of data mining to arise, encompassing both classical statistical, and modern machine learning techniques to support the data analysis and knowledge discovery from data. Data mining methods are powerful in dealing with large quantities of data, but on the other hand they are difficult to master by business users t...
Full Text Available Supported decision-making is at the forefront of modern disability research. This is due to Article 12 of the Convention on the Rights of Persons with Disabilities (CRPD, which creates a state obligation to provide support for the exercise of legal capacity. This turned the practice of supported decision-making into a human rights imperative. Government and funding agencies are increasingly focusing their attention on the area. Researchers are similarly increasing their interest in the field. The impending danger is that the rush of interest in the area will overshadow the original intention of supported decision-making: to ensure that people with cognitive disability are provided with the freedom and the tools to participate as equal citizens and for every individual to be free to direct their own life. This article explores the theoretical foundations of supported decision-making and the evolution of supported decision-making research. It explains the research that is emerging in leading jurisdictions, the United States and Australia, and its potential to transform disability services and laws related to decision-making. Finally, it identifies areas of concern in the direction of such research and provides recommendations for ensuring that supported decision-making remains protective of the rights, will and preferences of people with cognitive disability.
Luo, Y; McShan, D; Schipper, M; Matuszak, M; Ten Haken, R; Kong, F
Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity to different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for
Luo, Y; McShan, D; Schipper, M; Matuszak, M; Ten Haken, R [University of Michigan, Ann Arbor, MI (United States); Kong, F [Georgia Regents University, Augusta, GA (Georgia)
Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity to different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more
Jose Antonio Miñarro-Giménez
Full Text Available The development of genotyping and genetic sequencing techniques and their evolution towards low costs and quick turnaround have encouraged a wide range of applications. One of the most promising applications is pharmacogenomics, where genetic profiles are used to predict the most suitable drugs and drug dosages for the individual patient. This approach aims to ensure appropriate medical treatment and avoid, or properly manage, undesired side effects.We developed the Medicine Safety Code (MSC service, a novel pharmacogenomics decision support system, to provide physicians and patients with the ability to represent pharmacogenomic data in computable form and to provide pharmacogenomic guidance at the point-of-care. Pharmacogenomic data of individual patients are encoded as Quick Response (QR codes and can be decoded and interpreted with common mobile devices without requiring a centralized repository for storing genetic patient data. In this paper, we present the first fully functional release of this system and describe its architecture, which utilizes Web Ontology Language 2 (OWL 2 ontologies to formalize pharmacogenomic knowledge and to provide clinical decision support functionalities.The MSC system provides a novel approach for enabling the implementation of personalized medicine in clinical routine.
Adumitroaie, Virgil; Hua, Hook; Lincoln, William; Block, Gary; Mrozinski, Joseph; Shelton, Kacie; Weisbin, Charles; Elfes, Alberto; Smith, Jeffrey
Strategic Assessment of Risk and Technology (START) is a user-friendly computer program that assists human managers in making decisions regarding research-and-development investment portfolios in the presence of uncertainties and of non-technological constraints that include budgetary and time limits, restrictions related to infrastructure, and programmatic and institutional priorities. START facilitates quantitative analysis of technologies, capabilities, missions, scenarios and programs, and thereby enables the selection and scheduling of value-optimal development efforts. START incorporates features that, variously, perform or support a unique combination of functions, most of which are not systematically performed or supported by prior decision- support software. These functions include the following: Optimal portfolio selection using an expected-utility-based assessment of capabilities and technologies; Temporal investment recommendations; Distinctions between enhancing and enabling capabilities; Analysis of partial funding for enhancing capabilities; and Sensitivity and uncertainty analysis. START can run on almost any computing hardware, within Linux and related operating systems that include Mac OS X versions 10.3 and later, and can run in Windows under the Cygwin environment. START can be distributed in binary code form. START calls, as external libraries, several open-source software packages. Output is in Excel (.xls) file format.
Balson, W.E.; Wilson, D.S.
This paper reviews a number of decision support methods developed and applied by Decision Focus Incorporated to help utility personnel manage current environmental problems. This work has been performed for the Environmental Risk Analysis Program of EPRI's Environment Division, and also for a number of electric utilities across the country. These are two distinct types of decision support software tools that have been created: economic risk management and environmental risk analysis. These types differ primarily in the identification of who will make a decision. Economic risk management tools are directed primarily at decisions made by electric utilities. Environmental risk analysis tools are directed primarily at decisions made by legislative or regulatory agencies, about which a utility may wish to comment
Lajic, Zoran; Blanke, Mogens; Nielsen, Ulrik Dam
Fault detection and fault isolation for in-service decision support systems for marine surface vehicles will be presented in this paper. The stochastic wave elevation and the associated ship responses are modeled in the frequency domain. The paper takes as an example fault isolation...... of a containership on which a decision support system has been installed and it will be demonstrated that all the faults can be isolated. The paper shows how a shipboard decision support system could become highly reliable and comprise built-in supervision of the quality of the sensor signals that are crucial...
Venter, Jacobus P
Full Text Available . The objective of this study is to apply decision support techniques (especially Bayesian networks) to the area of new product development management in order to address some of the shortcomings. The research approach is one of decision structuring and modeling...
Hulsey Thomas C
Full Text Available Abstract Background Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU census. Methods A five-step procedure was developed to identify predictive variables. Clinical expert (CE thought processes comprised one model. Variables from that model were used to develop two mathematical models for the decision-support tool: an artificial neural network (ANN and a multivariate logistic regression model (MLR. The ranking of the variables in the three models was compared using the Wilcoxon Signed Rank Test. The best performing model was used in a web-based decision-support tool with a user interface implemented in Hypertext Markup Language (HTML and the mathematical model employing the ANN. Results CEs identified 51 potentially predictive variables for extubation decisions for an infant on mechanical ventilation. Comparisons of the three models showed a significant difference between the ANN and the CE (p = 0.0006. Of the original 51 potentially predictive variables, the 13 most predictive variables were used to develop an ANN as a web-based decision-tool. The ANN processes user-provided data and returns the prediction 0–1 score and a novelty index. The user then selects the most appropriate threshold for categorizing the prediction as a success or failure. Furthermore, the novelty index, indicating the similarity of the test case to the training case, allows the user to assess the confidence level of the prediction with
Armenian, H. K
.... The increase in and complexity of medical data at various levels of resolution has increased the need for system level advancements in clinical decision support systems that provide computer-aided...
This is a guide for transportation professionals on why and how to deploy winter Maintenance Decision Support Systems (MDSS). Adverse winter weather can cause traffic delays and crashes. Treating the effects of winter weather can also have impacts on...
Lajic, Zoran; Blanke, Mogens; Nielsen, Ulrik Dam
Fault detection and fault isolation for in-service decision support systems for marine surface vehicles will be presented in this paper. The stochastic wave elevation and the associated ship responses are modeled in the frequency domain. The paper takes as an example fault isolation of a containe......Fault detection and fault isolation for in-service decision support systems for marine surface vehicles will be presented in this paper. The stochastic wave elevation and the associated ship responses are modeled in the frequency domain. The paper takes as an example fault isolation...... of a containership on which a decision support system has been installed and it will be demonstrated that all the faults can be isolated. The paper shows how a shipboard decision support system could become highly reliable and comprise built-in supervision of the quality of the sensor signals that are crucial...
Bouaud, Jacques; Spano, Jean-Philippe; Lefranc, Jean-Pierre; Cojean-Zelek, Isabelle; Blaszka-Jaulerry, Brigitte; Zelek, Laurent; Durieux, Axel; Tournigand, Christophe; Rousseau, Alexandra; Vandenbussche, Pierre-Yves; Séroussi, Brigitte
When wrongly used, guideline-based clinical decision support systems (CDSSs) may generate inappropriate propositions that do not match the recommendations provided by clinical practice guidelines (CPGs). The user may decide to comply with or react to the CDSS, and her decision may finally comply or not with CPGs. OncoDoc2 is a guideline-based CDSS for breast cancer management. We collected 394 decisions made by multidisciplinary meeting physicians in three hospitals where the CDSS was evaluated. We observed a global CPG compliance of 86.8% and a global CDSS compliance of 75.4%. Non-CPG compliance was observed in case of a negative reactance to the CDSS, when users did not follow a correct CDSS proposition (8.6% of decisions). Because of errors in patient data entry, OncoDoc2 delivered non-recommended propositions in 21.3% of decisions, leading to compliances with CDSS and CPGs of respectively 21.4% and 65.5%, whereas both compliances exceeded 90% when CDSS advices included CPG recommendations. Automation bias, when users followed an incorrect CDSS proposition explained the remaining non-compliance with CPGs (4.6% of decisions). Securing the use of CDSSs is of major importance to warranty patient safety and benefit of their potential to improve care.
Flight, Ingrid H; Wilson, Carlene J; Zajac, Ian T; Hart, Elizabeth; McGillivray, Jane A
Colorectal cancer (CRC) is the third most commonly diagnosed cancer in males and the second in females throughout the developed world. Population screening using fecal occult blood tests (FOBTs) facilitates early detection and greater chance of survival, but participation rates are low. We developed a Web-based decision tool to provide information tailored to an individual's decision stage for CRC screening and attitude toward screening utilizing the Preventive Health Model (PHM) and Precaution Adoption Process Model (PAPM) as theoretical frameworks for screening behavior. We describe the practical steps employed in the tool's design and the subsequent conduct of an exploratory study. To design a decision tool for CRC screening and conduct an exploratory study among average-risk men and women to (1) test the impact of message type (tailored vs non-tailored) and message delivery modality (Web-based vs paper-based) on attitudes toward screening and screening uptake, and (2) investigate the acceptability of the decision tool and relevance of materials. Participants (n = 100), recruited from a population sample of men and women aged 50-76 residing in urban Adelaide, Australia, were randomly assigned to a control group or one of 4 interventions: (1) Web-based and tailored information, (2) paper-based and tailored information, (3) Web-based and non-tailored (generic) information, or (4) paper-based and non-tailored information. Participation was augmented by snowball recruitment (n = 19). Questionnaires based on PHM variables were administered pre- and post-intervention. Participants were given the opportunity to request an FOBT. Following the intervention, participants discussed the acceptability of the tool. Full data were available for 87.4% (104/119) of participants. Post-intervention, perceived susceptibility scores for individuals receiving tailored information increased from mean 10.6 (SD 2.1) to mean 11.8 (SD 2.2). Scores on self-efficacy increased in the
At Darlington Nuclear aggregate assessment of plant conditions is carried out in support of Operational Decision Making. This paper discusses how aggregate assessments have been applied to Operator Workarounds leading to improved prioritisation and alignment of work programs in different departments. As well, aggregate assessment of plant and human performance factors has been carried out to identify criteria which support conservative decision making in the main control room during unit transients. (author)
Samal, Lipika; D'Amore, John D; Bates, David W; Wright, Adam
Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electronic health records (EHRs), other options are available. As a clinical case study, we sought to build a scalable, web-based system that would automate calculation of kidney failure risk and display clinical decision support to users in primary care practices. We developed a single-page application, web server, database, and application programming interface to calculate and display kidney failure risk. Data were extracted from the EHR using the Consolidated Clinical Document Architecture interoperability standard for Continuity of Care Documents (CCDs). EHR users were presented with a noninterruptive alert on the patient's summary screen and a hyperlink to details and recommendations provided through a web application. Clinic schedules and CCDs were retrieved using existing application programming interfaces to the EHR, and we provided a clinical decision support hyperlink to the EHR as a service. We debugged a series of terminology and technical issues. The application was validated with data from 255 patients and subsequently deployed to 10 primary care clinics where, over the course of 1 year, 569 533 CCD documents were processed. We validated the use of interoperable documents and open-source components to develop a low-cost tool for automated clinical decision support. Since Consolidated Clinical Document Architecture-based data extraction extends to any certified EHR, this demonstrates a successful modular approach to clinical decision support. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.
Kim, Hyun-Young; Park, Hyeoun-Ae
The purpose of this study was to develop and evaluate the functionality of structured data entry templates using the entity-attribute-value (EAV) model for clinical decision support of pressure ulcer wound management. A data set for wound assessment of pressure ulcers that has commonly been recommended by clinical practice guidelines was identified, and then the EAV models on each data were developed. Structured data entry templates and a database were developed based on these EAV models. These were integrated with a knowledge engine into the clinical decision support system (CDSS) to provide patient-specific recommendations on pressure ulcer wound management. The functionality of the EAV model and structured data entry templates for the CDSS was evaluated heuristically by five nurse experts using clinical scenarios. The data set containing 13 entities was identified and EAV models of these entities were created. Cardinalities and data types of attributes were defined to represent the models in more detail. Terms used in the EAV models were mapped to SNOMED CT concepts. Six data entry templates and the relational database with ten tables were developed. Five nurses successfully entered all data in the scenarios except one data element and retrieved expected recommendations successfully from the clinical decision support system when all data were entered correctly. The clinical data models and structured data entry templates developed in this study were useful in supporting clinical decision making on pressure ulcer wound management. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Ahmad M. Kabil
Full Text Available Decision makers have considerable autonomy on how they make decisions and what type of support they receive. This situation places the DSS analyst in a different relationship with the client than his colleagues who support regular MIS applications. This paper addresses an ethical dilemma in “Inverse Decision Support,” when the analyst supports a decision maker who requires justification for a preconceived selection that does not correspond to the best option that resulted from the professional resolution of the problem. An extended application of the AHP model is proposed for evaluating the ethical responsibility in selecting a suboptimal alternative. The extended application is consistent with the Inverse Decision Theory that is used extensively in medical decision making. A survey of decision analysts is used to assess their perspective of using the proposed extended application. The results show that 80% of the respondents felt that the proposed extended application is useful in business practices. 14% of them expanded the usability of the extended application to academic teaching of the ethics theory. The extended application is considered more usable in a country with a higher Transparency International Corruption Perceptions Index (TICPI than in a country with a lower one.
Project accomplishments as of the date of the report: The first part of the project involves development of software in preparation for field testing of the trauma web-based decision support system. Dr...
Conclusion Using a guideline-based CDSS for the GPs' own patient cases had an impact on the GPs' confidence in the diagnosis of chronic heart failure and their considerations about investigations and medications: they also perceived substantial support in every third case. Applying a CDSS developed using evidence-based guidelines for chronic heart failure in primary care could have a significant influence on GPs' disease management.
Beemer, Brandon Alan
The research presented in this dissertation focuses on the organizational and consumer need for knowledge based support in unstructured domains, by developing a measurement scale for dynamic interaction. Addressing this need is approached and evaluated from two different perspectives. The first approach is the development of Knowledge Based…
Oh, Sungyoung; Cha, Jieun; Ji, Myungkyu; Kang, Hyekyung; Kim, Seok; Heo, Eunyoung; Han, Jong Soo; Kang, Hyunggoo; Chae, Hoseok; Hwang, Hee; Yoo, Sooyoung
To design a cloud computing-based Healthcare Software-as-a-Service (SaaS) Platform (HSP) for delivering healthcare information services with low cost, high clinical value, and high usability. We analyzed the architecture requirements of an HSP, including the interface, business services, cloud SaaS, quality attributes, privacy and security, and multi-lingual capacity. For cloud-based SaaS services, we focused on Clinical Decision Service (CDS) content services, basic functional services, and mobile services. Microsoft's Azure cloud computing for Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) was used. The functional and software views of an HSP were designed in a layered architecture. External systems can be interfaced with the HSP using SOAP and REST/JSON. The multi-tenancy model of the HSP was designed as a shared database, with a separate schema for each tenant through a single application, although healthcare data can be physically located on a cloud or in a hospital, depending on regulations. The CDS services were categorized into rule-based services for medications, alert registration services, and knowledge services. We expect that cloud-based HSPs will allow small and mid-sized hospitals, in addition to large-sized hospitals, to adopt information infrastructures and health information technology with low system operation and maintenance costs.
JACOBUS PETRUS VENTER; CORNELIS CRISTO VAN WAVEREN
The development of new and improved management methods for new product development is important. Existing methods suffer from a number of shortcomings, especially their inability to deal with a mixture of quantitative and qualitative data. The objective of this study is to apply decision support techniques (especially Bayesian networks) to the area of new product development management in order to address some of the shortcomings.The research approach is one of decision structuring and modeli...
Grant H. Kruger
Full Text Available Information overload of the anesthesiologist through technological advances have threatened the safety of patients under anesthesia in the operating room (OR. Traditional monitoring and alarm systems provide independent, spatially distributed indices of patient physiological state. This creates the potential to distract caregivers from direct patient care tasks. To address this situation, a novel reactive agent decision support system with graphical human machine interface was developed. The system integrates the disparate data sources available in the operating room, passes the data though a decision matrix comprising a deterministic physiologic rule base established through medical research. Patient care is improved by effecting change to the care environment by displaying risk factors and alerts as an intuitive color coded animation. The system presents a unified, contextually appropriate snapshot of the patient state including current and potential risk factors, and alerts of critical patient events to the operating room team without requiring any user intervention. To validate the efficacy of the system, a retrospective analysis focusing on the hypotension rules were performed. Results show that even with vigilant and highly trained clinicians, deviations from ideal patient care exist and it is here that the proposed system may allow more standardized and improved patient care and potentially outcomes.
Shalom, Erez; Shahar, Yuval; Parmet, Yisrael; Lunenfeld, Eitan
To quantify the effect of a new continuous-care guideline (GL)-application engine, the Picard decision support system (DSS) engine, on the correctness and completeness of clinicians' decisions relative to an established clinical GL, and to assess the clinicians' attitudes towards a specific DSS. Thirty-six clinicians, including residents at different training levels and board-certified specialists at an academic OB/GYN department that handles around 15,000 deliveries annually, agreed to evaluate our continuous-care guideline-based DSS and to perform a cross-over assessment of the effects of using our guideline-based DSS. We generated electronic patient records that realistically simulated the longitudinal course of six different clinical scenarios of the preeclampsia/eclampsia/toxemia (PET) GL, encompassing 60 different decision points in total. Each clinician managed three scenarios manually without the Picard DSS engine (Non-DSS mode) and three scenarios when assisted by the Picard DSS engine (DSS mode). The main measures in both modes were correctness and completeness of actions relative to the PET GL. Correctness was further decomposed into necessary and redundant actions, relative to the guideline and the actual patient data. At the end of the assessment, a questionnaire was administered to the clinicians to assess their perceptions regarding use of the DSS. With respect to completeness, the clinicians applied approximately 41% of the GL's recommended actions in the non-DSS mode. Completeness increased to the performance of approximately 93% of the guideline's recommended actions, when using the DSS mode. With respect to correctness, approximately 94.5% of the clinicians' decisions in the non-DSS mode were correct. However, these included 68% of the actions that were correct but redundant, given the patient's data (e.g., repeating tests that had been performed), and 27% of the actions, which were necessary in the context of the GL and of the given scenario
Kealey, Edith; Leckman-Westin, Emily; Finnerty, Molly T
Training has been identified as an important barrier to implementation of clinical decision support systems (CDSSs), but little is known about the effectiveness of different training approaches. Using an observational retrospective cohort design, we examined the impact of four training conditions on physician use of a CDSS: (1) computer lab training with individualized follow-up (CL-FU) (n=40), (2) computer lab training without follow-up (CL) (n=177), (3) lecture demonstration (LD) (n=16), or (4) no training (NT) (n=134). Odds ratios of any use and ongoing use under training conditions were compared to no training over a 2-year follow-up period. CL-FU was associated with the highest percent of active users and odds for any use (90.0%, odds ratio (OR)=10.2, 95% confidence interval (CI): 3.2-32.9) and ongoing use (60.0%, OR=6.1 95% CI: 2.6-13.7), followed by CL (any use=81.4%, OR=5.3, CI: 2.9-9.6; ongoing use=28.8%, OR=1.7, 95% CI: 1.0-3.0). LD was not superior to no training (any use=47%, ongoing use=22.4%). Training format may have differential effects on initial and long-term follow-up of CDSSs use by physicians. Copyright © 2013 Elsevier B.V. All rights reserved.
This book presents different methods for analyzing the body language (movement, position, use of personal space, silences, pauses and tone, the eyes, pupil dilation or constriction, smiles, body temperature and the like) for better understanding people’s needs and actions, including biometric data gathering and reading. Different studies described in this book indicate that sufficiently much data, information and knowledge can be gained by utilizing biometric technologies. This is the first, wide-ranging book that is devoted completely to the area of intelligent decision support systems, biometrics technologies and their integrations. This book is designated for scholars, practitioners and doctoral and master’s degree students in various areas and those who are interested in the latest biometric and intelligent decision making support problems and means for their resolutions, biometric and intelligent decision making support systems and the theory and practice of their integration and the opportunities fo...
Full Text Available Abstract Background A real-time clinical decision support system (RTCDSS with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC architecture, by which the system can easily be adapted to different diseases and applications. Methods We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. Results The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Conclusions Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital
Blasch, Erik P.; Breton, Richard; Valin, Pierre
For decades, there have been discussions on measures of merits (MOM) that include measures of effectiveness (MOE) and measures of performance (MOP) for system-level performance. As the amount of sensed and collected data becomes increasingly large, there is a need to look at the architectures, metrics, and processes that provide the best methods for decision support systems. In this paper, we overview some information fusion methods in decision support and address the capability to measure the effects of the fusion products on user functions. The current standard Information Fusion model is the Data Fusion Information Group (DFIG) model that specifically addresses the needs of the user in an information fusion system. Decision support implies that information methods augment user decision making as opposed to the machine making the decision and displaying it to user. We develop a list of suggested measures of merits that facilitate decision support decision support Measures of Effectiveness (MOE) metrics of quality, information gain, and robustness, from the analysis based on the measures of performance (MOPs) of timeliness, accuracy, confidence, throughput, and cost. We demonstrate in an example with motion imagery to support the MOEs of quality (time/decision confidence plots), information gain (completeness of annotated imagery for situation awareness), and robustness through analysis of imagery over time and repeated looks for enhanced target identification confidence.
Hair, D. Charles; Pickslay, Kent
NCCOSC RDT&E Division (NRaD) is conducting research into ways of improving decision support systems (DSS) that are used in tactical Navy decision making situations. The research has focused on the incorporation of findings about naturalistic decision-making processes into the design of the DSS. As part of that research, two computer tools were developed that model the two primary naturalistic decision-making strategies used by Navy experts in tactical settings. Current work is exploring how best to incorporate the information produced by those tools into an existing simulation of current Navy decision support systems. This work has implications for any applications involving the need to make decisions under time constraints, based on incomplete or ambiguous data.
Full Text Available Identifying and making the correct decision on the best health treatment or screening test option can become a difficult task. Therefore is important that the patients get all types of information appropriate to manage their health. Decision aids can be very useful when there is more than one reasonable option about a treatment or uncertain associated with screening tests. The decision aids tools help people to understand their clinical condition, through the description of the different options available. The purpose of this paper is to present the project “Supporting Informed Decision Making In Prevention of Prostate Cancer” (SIDEMP. This project is focused on the creation of a Web-based decision platform specifically directed to screening prostate cancer, that will support the patient in the process of making an informed decision
Yatsalo, B.I.; Mirzeabassov, O.A.; Okhrimenko, I.V.; Pichugina, I.A.
Geographic Information System (GIS) PRANA is a Decision Support System (DSS) for countermeasure analysis in agriculture in the long-term period of liquidating the consequences of a nuclear accident. However, though PRANA(-98) is used at the Chernobyl Department (Ministry of Agriculture) and at the Bryansk Centre of Agrochemical Radiology for practical needs, but its possibilities are limited by the questions of agriculture. Conceptual requirements to GIS-DSSs, which are some considerable extension of the PRANA(-98) and meet all the main demands to DSSs for practical use, research and training on rehabilitation of contaminated territories, were elaborated in contacts with interested parties in Russia: Ministry of Agriculture, Minatom, Emercom, Ministry of Health, Ministry of Science and Administration of Bryansk region. Realisation of the planned requirements and tasks have been achieved not through developing the only universal system, but through creating several GIS-DSSs (family of PRANA systems, each of them is intended for analysis of specific range of problems): - GIS-DSS for practical use (with introduction at appropriate Ministries and Centres); - GIS-DSS for research and for scientific and practical estimations; - GIS-DSS for training of the specialists; - GIS-DSS as well as computer realisation of thematic blocks for use as lectures, seminars and tests/questionnaires for aims of education (students, specialists); - elements of distributed systems and remote access to components of GIS-DSS (for practical use, training and education). The following sections, which have been realised in accordance with the chosen level of the system, represent in the aggregate a basis of each GIS-DSS indicated above: - databases (radioecological, economic, demographic and other monitoring data); - libraries of electronic maps (including different layers of vector maps of land use for territories under consideration); - spatial analysis of various data from databases
Schwartz, Mark W.; Cook, Carly N.; Pressey, Robert L.; Pullin, Andrew S.; Runge, Michael C.; Salafsky, Nick; Sutherland, William J.; Williamson, Matthew A.
The practice of conservation occurs within complex socioecological systems fraught with challenges that require transparent, defensible, and often socially engaged project planning and management. Planning and decision support frameworks are designed to help conservation practitioners increase planning rigor, project accountability, stakeholder participation, transparency in decisions, and learning. We describe and contrast five common frameworks within the context of six fundamental questions (why, who, what, where, when, how) at each of three planning stages of adaptive management (project scoping, operational planning, learning). We demonstrate that decision support frameworks provide varied and extensive tools for conservation planning and management. However, using any framework in isolation risks diminishing potential benefits since no one framework covers the full spectrum of potential conservation planning and decision challenges. We describe two case studies that have effectively deployed tools from across conservation frameworks to improve conservation actions and outcomes. Attention to the critical questions for conservation project planning should allow practitioners to operate within any framework and adapt tools to suit their specific management context. We call on conservation researchers and practitioners to regularly use decision support tools as standard practice for framing both practice and research.
Dolan, James G; Veazie, Peter J
Multicriteria decision-making (MCDM) methods are well-suited to serve as the foundation for clinical decision support systems. To do so, however, they need to be appropriate for use in busy clinical settings. We compared decision-making processes and outcomes of patient-level analyses done with a range of multicriteria methods that vary in ease of use and intensity of decision support, 2 factors that could affect their ease of implementation into practice. We conducted a series of Internet surveys to compare the effects of 5 multicriteria methods that differ in user interface and required user input format on decisions regarding selection of a preferred method for lowering the risk of cardiovascular disease. The study sample consisted of members of an online Internet panel maintained by Fluidsurveys, an Internet survey company. Study outcomes were changes in preferred option, decision confidence, preparation for decision making, the Values Clarification and Decisional Uncertainty subscales of the Decisional Conflict Scale, and method ease of use. The frequency of changes in the preferred option ranged from 9% to 38%, P decision support provided by the MCDM method increased. The proportion of respondents who rated the method as easy ranged from 57% to 79% and differed significantly among MCDM methods, P = 0.003, but was not consistently related to intensity of decision support or ease of use. Decision support based on MCDM methods is not necessarily limited by decreases in ease of use. This result suggests that it is possible to develop decision support tools using sophisticated multicriteria techniques suitable for use in routine clinical care settings.
Home; Journals; Journal of Earth System Science; Volume 124; Issue 1. Decision Support System integrated with Geographic Information System to target restoration actions in watersheds of arid environment: A case study of Hathmati watershed, Sabarkantha district, Gujarat. Dhruvesh P Patel Prashant K Srivastava ...
Qualitative evaluation of smallholder farmer decisions, support systems, knowledge and disease management tools. ... A group of 15 extension officers and 12 researchers were purposively selected for the study because they play a major role in organising and disseminating information to the farmers. Participatory ...
Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.
One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.
Home; Journals; Journal of Earth System Science; Volume 124; Issue 1. Decision Support System integrated with Geographic Information System to target restoration actions in watersheds of arid environment: A case study of Hathmati watershed, Sabarkantha district, Gujarat. Dhruvesh P Patel Prashant K Srivastava ...
Van Der Merwe, A
Full Text Available models. The three features of the decision support system are first to assist in the scheduling process of assigning grapes from the different suppliers to the different tipping bins by suggesting rapidly and in an automated fashion a possible schedule...
Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Chang, Kyung Hwan; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie
The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.
Full Text Available Abstract Background PubMed data potentially can provide decision support information, but PubMed was not exclusively designed to be a point-of-care tool. Natural language processing applications that summarize PubMed citations hold promise for extracting decision support information. The objective of this study was to evaluate the efficiency of a text summarization application called Semantic MEDLINE, enhanced with a novel dynamic summarization method, in identifying decision support data. Methods We downloaded PubMed citations addressing the prevention and drug treatment of four disease topics. We then processed the citations with Semantic MEDLINE, enhanced with the dynamic summarization method. We also processed the citations with a conventional summarization method, as well as with a baseline procedure. We evaluated the results using clinician-vetted reference standards built from recommendations in a commercial decision support product, DynaMed. Results For the drug treatment data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.848 and 0.377, while conventional summarization produced 0.583 average recall and 0.712 average precision, and the baseline method yielded average recall and precision values of 0.252 and 0.277. For the prevention data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.655 and 0.329. The baseline technique resulted in recall and precision scores of 0.269 and 0.247. No conventional Semantic MEDLINE method accommodating summarization for prevention exists. Conclusion Semantic MEDLINE with dynamic summarization outperformed conventional summarization in terms of recall, and outperformed the baseline method in both recall and precision. This new approach to text summarization demonstrates potential in identifying decision support data for multiple needs.
Workman, T Elizabeth; Fiszman, Marcelo; Hurdle, John F
PubMed data potentially can provide decision support information, but PubMed was not exclusively designed to be a point-of-care tool. Natural language processing applications that summarize PubMed citations hold promise for extracting decision support information. The objective of this study was to evaluate the efficiency of a text summarization application called Semantic MEDLINE, enhanced with a novel dynamic summarization method, in identifying decision support data. We downloaded PubMed citations addressing the prevention and drug treatment of four disease topics. We then processed the citations with Semantic MEDLINE, enhanced with the dynamic summarization method. We also processed the citations with a conventional summarization method, as well as with a baseline procedure. We evaluated the results using clinician-vetted reference standards built from recommendations in a commercial decision support product, DynaMed. For the drug treatment data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.848 and 0.377, while conventional summarization produced 0.583 average recall and 0.712 average precision, and the baseline method yielded average recall and precision values of 0.252 and 0.277. For the prevention data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.655 and 0.329. The baseline technique resulted in recall and precision scores of 0.269 and 0.247. No conventional Semantic MEDLINE method accommodating summarization for prevention exists. Semantic MEDLINE with dynamic summarization outperformed conventional summarization in terms of recall, and outperformed the baseline method in both recall and precision. This new approach to text summarization demonstrates potential in identifying decision support data for multiple needs.
The purpose of this research project is to improve current onboard decision support systems. Special focus is on the onboard prediction of the instantaneous sea state. In this project a new approach to increasing the overall reliability of a monitoring and decision support system has been...... advice regarding speed and course changes to decrease the wave-induced loads. The SeaSense system is based on the combined use of a mathematical model and measurements from a set of sensors. The overall dependability of a shipboard monitoring and decision support system such as the SeaSense system can...... of a fault. A supervisory function determines the severity of the fault once its origin has been isolated and its magnitude estimated. Fault-tolerant Sensor Fusion means that the monitoring and decision support system can accommodate faults so that the overall system continues to satisfy its goal...
May Florence J. Franco
Full Text Available The study aimed to develop an online system that would expedite the response of agencies after disaster strikes; generate a list of the kinds and volume of relief aids needed per family affected for a fair, precise and timely distribution; implement community-based ICT by remotely gathering all the necessary data needed for disaster assessment; and adhere to ISO 9126 standards. The system was designed to calculate the effects of disaster in human lives and economy. Integrated into the system were Goggle Maps, Mines and GeoSciences Bureau Hazard Maps, SMS sending features, best passable routes calculations, and decision support on the needs that has to be addressed. The system was made live at pdrrmcguimaras.herokuapp.com to allow remote data entry. The functionality and usability of the system were evaluated by 19 potential users by computing for the arithmetic Mean and Standard Deviation of the survey. The result showed that most of them strongly agreed that the system is acceptable based on these criteria. A group of IT experts also evaluated the system’s conformance to ISO 9126 standards using the same method. The result showed that majority of them strongly agreed that the system conforms to this international standard. The system is seen as a valuable tool for the Provincial Disaster Risk Reduction Management Council (PDRRMC and the National Disaster Risk Reduction Management Council (NDRRMC for it could help expedite the assessment of the effects of disasters and the formulation of response plans and strategies.
Decision Support System For Approval New Student And Majoring Selection Based On Student’s Interest And Talent By Fuzzy Multiple Decision Making, Simple Additive Weighting And Buble Sort Method In SMK Telekomunikasi Tunas Harapan
Full Text Available Decision Support System for New Student Acceptance aims to simplify the Decision Maker who is the Committee of New Student Acceptance to select prospective new students based on eight criteria. That is registration number, the average value of National Examinations, medical tests, interview, their achievements, salary of parents per month, number of siblings who are still in school and administration department and give recommendations for the major of accepted students based on their interests and talents. There are four major in SMK Telekomunikasi Tunas Harapan, these are Rekayasa Perangkat Lunak (RPL, Teknik Komputer dan Jaringan (TKJ, Multimedia and Teknik Kendaraan Ringan (TKR. And the talents be measured by math test, electro test, daw test and physics test.
Mullinix, C.; Hearn, P.; Zhang, H.; Aguinaldo, J.
Federal, State, and local water quality managers charged with restoring the Chesapeake Bay ecosystem require tools to maximize the impact of their limited resources. To address this need, the U.S. Geological Survey (USGS) and the Environmental Protection Agency's Chesapeake Bay Program (CBP) are developing a suite of Web-based tools called the Chesapeake Online Assessment Support Toolkit (COAST). The goal of COAST is to help CBP partners identify geographic areas where restoration activities would have the greatest effect, select the appropriate management strategies, and improve coordination and prioritization among partners. As part of the COAST suite of tools focused on environmental restoration, a water quality management visualization component called the Nutrient Yields Mapper (NYM) tool is being developed by USGS. The NYM tool is a web application that uses watershed yield estimates from USGS SPAtially Referenced Regressions On Watershed (SPARROW) attributes model (Schwarz et al., 2006)  to allow water quality managers to identify important sources of nitrogen and phosphorous within the Chesapeake Bay watershed. The NYM tool utilizes new open source technologies that have become popular in geospatial web development, including components such as OpenLayers and GeoServer. This paper presents examples of water quality data analysis based on nutrient type, source, yield, and area of interest using the NYM tool for the Chesapeake Bay watershed. In addition, we describe examples of map-based techniques for identifying high and low nutrient yield areas; web map engines; and data visualization and data management techniques.
Full Text Available There are many tasks that revolve around combinatorial analysis problems, same tasks found in Decision Support Systems (DSS as most of these are responsible for assessing a number of possibilities to deliver the best options. Within the analysis of possible solutions is performed by the DSS there are alternative procedures inside the engine for making decisions that involve them. As part of these alternative procedures today has highlighted the use of metaheuristics, thus in this paper we propose a comparison of some of them trying to broaden the spectrum we have for the applications nowadays.
Ben Salem, Samira; Bacha, Khmais; Chaari, Abdelkader
In this work we suggest an original fault signature based on an improved combination of Hilbert and Park transforms. Starting from this combination we can create two fault signatures: Hilbert modulus current space vector (HMCSV) and Hilbert phase current space vector (HPCSV). These two fault signatures are subsequently analysed using the classical fast Fourier transform (FFT). The effects of mechanical faults on the HMCSV and HPCSV spectrums are described, and the related frequencies are determined. The magnitudes of spectral components, relative to the studied faults (air-gap eccentricity and outer raceway ball bearing defect), are extracted in order to develop the input vector necessary for learning and testing the support vector machine with an aim of classifying automatically the various states of the induction motor. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.
Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen
This paper concerns composite decision support based on combining cost-benefit analysis (CBA) with multi-criteria decision analysis (MCDA) for the assessment of economic as well as strategic impacts within transport projects. Specifically a composite model for assessment (COSIMA) is presented......, and it is concluded that appraisals of large transport projects can be effectively supported using a combination of CBA and MCDA. Finally, perspectives of the future modelling work are given....
The objective of SCK-CEN's R and D programme on decision strategies and policy support is: (1) to investigate the decision making process, with all its relevant dimensions, in the context of radiation protection or other nuclear issues (with particular emphasis on emergency preparedness); (2) to disseminate knowledge on decision making and nuclear emergencies, including the organisation of training courses, the contribution to manuals or guidelines, the participation in working groups or discussion forums; (3) to assist the authorities and the industry on any topic related to radiation protection and to make expertise and infrastructure available; (4) to participate in and contribute to initiatives related to social sciences and their implementation into SCK-CEN; (5) to co-ordinate efforts of SCK-CEN related to medical applications of ionising radiation. Principal achievements in 2001 are described
Zhu, H.; Ou, Carol; Davison, R.M.; Pavlou, P.A.; Liu, H.W.
With the increasing prosperity of online marketplaces, millions of items are available on a single plat-form. Due to the limited cognitive capacity of human beings, consumers make purchase decisions in a way that balances both effort and accuracy, as contended by the effort-accuracy trade-off (EATO)
Treweek, Shaun; Oxman, Andrew D.; Alderson, Philip; Bossuyt, Patrick M.; Brandt, Linn; Brożek, Jan; Davoli, Marina; Flottorp, Signe; Harbour, Robin; Hill, Suzanne; Liberati, Alessandro; Liira, Helena; Schünemann, Holger J.; Rosenbaum, Sarah; Thornton, Judith; Vandvik, Per Olav; Alonso-Coello, Pablo; Hartley, Claire; Loudon, Kirsty; Slater, William; Stewart, Neil; Glenton, Claire; Kristiansen, Annette; Lewin, Simon; Moberg, Jenny; Morelli, Angela; Oxman, Andy; Ødgaard-Jensen, Jan; Martinez-García, Laura; Rigau, David; Solà, Ivan; Sanabria, Andrea Juliana; Amato, Laura; Brunetti, Massimo; Magrini, Nicola; Parmelli, Elena; Nonino, Francesco; de Palma, Rossana; Papini, Donato; Pregno, Silvia; Saitto, Carlo; Gopalakrishna, Gowri; Langendam, Miranda; Leeflang, Mariska; Scholten, Rob; Gülmezoglu, Metin; Permanand, Govin; Weerasuriyak, Krisantha; Antes, Gerd; Meerpohl, Jörg; Schünemann, Holger; Alderson, Phil; McFarlane, Emma; Callaghan, Margaret; Graham, Karen; Ritchie, Karen; Service, Duncan; Kunnamo, Ilkka; Guyatt, Gordon; Mustafa, Reem; Neumann, Ignacio; Santesso, Nancy; Spencer, Fred; Falck-Ytter, Yngve; Brignardello-Petersen, Romina; Carrasco- Labra, Alonso; Kunz, Regina; Akl, Elie
Healthcare decision makers face challenges when using guidelines, including understanding the quality of the evidence or the values and preferences upon which recommendations are made, which are often not clear. GRADE is a systematic approach towards assessing the quality of evidence and the
Jiménez, David; Resano, Santiago; Otero, Remedios; Jurkojc, Carolina; Portillo, Ana Karina; Ruiz-Artacho, Pedro; Corres, Jesús; Vicente, Agustina; den Exter, Paul L; Huisman, Menno V; Moores, Lisa; Yusen, Roger D
This study aimed to determine the effect of an evidence-based clinical decision support (CDS) algorithm on the use and yield of CT pulmonary angiography (CTPA) and on outcomes of patients evaluated in the emergency department (ED) for suspected PE. The study included 1363 consecutive patients evaluated for suspected PE in an ED during 12 months before and 12 months after initiation of CDS use. Introduction of CDS was associated with decreased CTPA use (55% vs 49%; absolute difference (AD), 6.3%; 95% CI 1.0% to 11.6%; p=0.02). The use of CDS was associated with fewer symptomatic venous thromboembolic events during follow-up in patients with an initial negative diagnostic evaluation for PE (0.7% vs 3.2%; AD 2.5%; 95% CI 0.9% to 4.6%; p<0.01). Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Filip, Florin Gheorghe; Ciurea, Cristian
This is a book about how management and control decisions are made by persons who collaborate and possibly use the support of an information system. The decision is the result of human conscious activities aiming at choosing a course of action for attaining a certain objective (or a set of objectives). The act of collaboration implies that several entities who work together and share responsibilities to jointly plan, implement and evaluate a program of activities to achieve the common goals. The book is intended to present a balanced view of the domain to include both well-established concepts and a selection of new results in the domains of methods and key technologies. It is meant to answer several questions, such as: a) “How are evolving the business models towards the ever more collaborative schemes?”; b) “What is the role of the decision-maker in the new context?” c) “What are the basic attributes and trends in the domain of decision-supporting information systems?”; d) “Which are the basic...
This book is organized into three sections in accordance with the structure of the conference program. First section contains four major papers which were commissioned by the Programme Committee to set the tone for the conference and to provide a structured source of relevant material from contributing disciplines. The second section contains specific papers submitted to the conference, and concerned with the following topics of specific interest: epistemological issues for decision support systems (DSS), capturing organizational knowledge for DSS, complementarity between human and formal DSS, and representations for adaption. The third section contains the short papers on any topic of relevance to the theme of the conference. It is hoped that the two working conferences organized by WG 8.3 will contribute to the development of a coherent knowledge and understanding of the class of computerized information systems called Decision Support Systems. (Auth.)
Schreiner, W.; Buchberger, M.; Kaltofen, T.
JKU/RISC currently develops in cooperation with Upper Austrian Research (UAR) the SEE-GRID software system. SEE-GRID is based on the SEE++ software for the biomechanical 3D simulation of the human eye and its muscles. SEE++ simulates the common eye muscle surgery techniques in a graphic interactive way that is familiar to an experienced surgeon. SEE++ is world-wide the most advanced software for this purpose; it is used by various hospitals and medical doctors for surgery training and planning, SEE++ deals with the support of diagnosis and treatment of strabismus, which is the common name given to usually persistent or regularly occuring misalignment of the eyes. Strabismus is a visual defect in which eyes point in different directions. A person suffering from it may see double images due to misaligned eyes. SEE++ is able to simulate the result of the Hess-Lancaster test, from which the pathological reason of strabismus can be estimated. The outcome of such an examination is two gaze patterns of blue points a...
Fahim Akhter; Zakaria Maamar; Dave Hobbs
The purpose of this article is to present an application of fuzzy logic to human reasoning about electronic commerce (e-commerce) transactions. This article uncovers some of the hidden relationships between critical factors such as security, familiarity, design, and competitiveness. We analyze the effect of these factors on human decision process and how they affect the Business-to-Consumer (B2C) outcome when they are used collectively. This research provides a toolset for B2C vendors to acce...
The growth of Data Science, and, more in general, Artificial Intelligence tools largely influences the way people interact with the huge amount of information available on the Internet. In the context of a free knowledge community, we want to use those techniques not to replace, but to support human judgment. While communities take informed decisions, machines can help processing, linking and summarizing large amount of data, including different formats (text, images) and languages. In this...
General objective (d), to avoid the “ Orson Welles Effect” by controlling the public mess- age, was achieved. Numer- ous steps were taken in the...unshakable economy, a more diverse and deployable Inter Agency, and perhaps most importantly a well -informed and supportive citizenry” (Porter and Mykleby...planned response decisions depicted in CRDS. The experiment evaluated ease of use, how well CERPS facilitates and encourages citizen participation, and
centered on the TeraData relational database machine. TeraData provided training and a six month trial period. Still within August, an initial...EIS (no nickname), learning and use is very easy. The workstation interface is entirely menu driven. Data is automatically refreshed by the TeraData ...used by the six top executives, is used for strategy and planning decision support. Most folks use TeraData for direct access to corporate data and
The objective of this technology is to provide risk managers with a defensible, objective way to select capping alternatives for remediating radioactive and mixed waste landfills. The process of selecting containment cover technologies for mixed waste landfills requires consideration of many complex and interrelated technical, regulatory, and economic issues. A Decision Support System (DSS) is needed to integrate the knowledge of experts from scientific, engineering, and management disciplines to help in selecting the best capping practice for the site
Full Text Available This paper presents the development of a decision support system (DSS for a low-voltage grid with renewable energy sources (photovoltaic panels and wind turbine which aims at achieving energy balance in a pilot microgrid with less energy consumed from the network. The DSS is based on a procedural decision algorithm that is applied on a pilot microgrid, with energy produced from renewable energy sources, but it can be easily generalized for any microgrid. To underline the benefits of the developed DSS two case scenarios (a household and an office building with different energy consumptions were analyzed. The results and throw added value of the paper is the description of an implemented microgrid, the development and testing of the decision support system on real measured data. Experimental results have demonstrated the validity of the approach in rule-based decision switching.
Full Text Available Competitive advantage in logistics operations is possible by analyzing data to create information and turning that information into decision. Supply chain optimization depends on effective management of chain knowledge. Analyzing data from supply chain and making a decision creates complex operations. Therefore, these operations require benefitting from information technology. In today’s global world, businesses use outsourcing for logistics services to focus on their own field, so are seeking to achieve competitive advantage against competitors. Outsourcing requires sharing of various information and data with companies that provide logistical support. Effective strategies are based on well-analyzed the data and information. Best options for right decisions can be created only from good analysis. That’s why companies that supply logistics services achieve competitive advantage using decision support systems (DSS in industrial competition. In short, DSS has become driving force for every business in today’s knowledge-based economy.
Scholz, Miklas; Uzomah, Vincent C
The retrofitting of sustainable drainage systems (SuDS) such as permeable pavements is currently undertaken ad hoc using expert experience supported by minimal guidance based predominantly on hard engineering variables. There is a lack of practical decision support tools useful for a rapid assessment of the potential of ecosystem services when retrofitting permeable pavements in urban areas that either feature existing trees or should be planted with trees in the near future. Thus the aim of this paper is to develop an innovative rapid decision support tool based on novel ecosystem service variables for retrofitting of permeable pavement systems close to trees. This unique tool proposes the retrofitting of permeable pavements that obtained the highest ecosystem service score for a specific urban site enhanced by the presence of trees. This approach is based on a novel ecosystem service philosophy adapted to permeable pavements rather than on traditional engineering judgement associated with variables based on quick community and environment assessments. For an example case study area such as Greater Manchester, which was dominated by Sycamore and Common Lime, a comparison with the traditional approach of determining community and environment variables indicates that permeable pavements are generally a preferred SuDS option. Permeable pavements combined with urban trees received relatively high scores, because of their great potential impact in terms of water and air quality improvement, and flood control, respectively. The outcomes of this paper are likely to lead to more combined permeable pavement and tree systems in the urban landscape, which are beneficial for humans and the environment. Copyright © 2013 Elsevier B.V. All rights reserved.
Backus, Ge B.C.; Timmer, G. Th.; Dijkhuizen, A.A.; Eidman, V.R.; Vos, F.
This paper reported on a decision support system (DSS) for strategic planning on pig farms. The DSS was based . on a stochastic simulation model of investment decisions (ISM). ISM described a farm with one loan and one building using 23 variables. The simulation model calculated the results of a strategic plan for an individual pig farm over a time horizon of a maximum of 20 years for a given scenario. For six distinct replacement strategies, regression metamodels were specified to describe t...
Podinovski, V. V.
A set of interrelated methods is presented for analyzing multicriteria decision-making problems on the basis of an information on the criteria importance and change of the preferences along their scales. Computer systems of decision-making support, implementing these methods within the methodology
Transit Operations Decision Support Systems (TODSS) are decision support systems designed to support dispatchers in real-time bus operations : management in response to incidents, special events, and other changing conditions in order to restore serv...
Mioc, Darka; Anton, François; Liang, Gengsheng
In this paper the development of Web GIS based decision support system for flood events is presented. To improve flood prediction we developed the decision support system for flood prediction and monitoring that integrates hydrological modelling and CARIS GIS. We present the methodology for data...... integration, floodplain delineation, and online map interfaces. Our Web-based GIS model can dynamically display observed and predicted flood extents for decision makers and the general public. The users can access Web-based GIS that models current flood events and displays satellite imagery and digital...... elevation model integrated with flood plain area. The system can show how the flooding prediction based on the output from hydrological modeling for the next 48 hours along the lower Saint John River Valley....
Chin, L. (Bentley College, Waltham, MA (United States)); Vollmann, T.E. (International Inst. for Management Development, Lausanne (Switzerland))
A decision support model is presented which will give utilities the support tools to manage the purchasing of natural gas supplies in the most cost effective manner without reducing winter safety stocks to below minimum levels. In Business As Usual (BAU) purchasing quantities vary with the daily forecasts. With Material Requirements Planning (MRP) and Linear Programming (LP), two types of factors are used: seasonal weather and decision rule. Under current practices, BAU simulation uses the least expensive gas source first, then adding successively more expensive sources. Material Requirements Planning is a production planning technique which uses a parent item master production schedule to determine time phased requirements for component points. Where the MPS is the aggregate gas demand forecasts for the contract year. This satisfies daily demand with least expensive gas and uses more expensive when necessary with automatic computation of available-to-promise (ATP) gas a dispacher knows daily when extra gas supplies may be ATP. Linear Programming is a mathematical algorithm used to determine optimal allocations of scarce resources to achieve a desired result. The LP model determines optimal daily gas purchase decisions with respect to supply cost minimization. Using these models, it appears possible to raise gross income margins 6 to 10% with minimal additions of customers and no new gas supply.
Chin, L.; Vollmann, T.E.
A decision support model is presented which will give utilities the support tools to manage the purchasing of natural gas supplies in the most cost effective manner without reducing winter safety stocks to below minimum levels. In Business As Usual (BAU) purchasing quantities vary with the daily forecasts. With Material Requirements Planning (MRP) and Linear Programming (LP), two types of factors are used: seasonal weather and decision rule. Under current practices, BAU simulation uses the least expensive gas source first, then adding successively more expensive sources. Material Requirements Planning is a production planning technique which uses a parent item master production schedule to determine time phased requirements for component points. Where the MPS is the aggregate gas demand forecasts for the contract year. This satisfies daily demand with least expensive gas and uses more expensive when necessary with automatic computation of available-to-promise (ATP) gas a dispacher knows daily when extra gas supplies may be ATP. Linear Programming is a mathematical algorithm used to determine optimal allocations of scarce resources to achieve a desired result. The LP model determines optimal daily gas purchase decisions with respect to supply cost minimization. Using these models, it appears possible to raise gross income margins 6 to 10% with minimal additions of customers and no new gas supply
Di Stefano, M.; Fox, P. A.; Beaulieu, S. E.; Maffei, A. R.; West, P.; Hare, J. A.
Integrated assessments of large marine ecosystems require the understanding of interactions between environmental, ecological, and socio-economic factors that affect production and utilization of marine natural resources. Assessing the functioning of complex coupled natural-human systems calls for collaboration between natural and social scientists across disciplinary and national boundaries. We are developing a platform to implement and sustain informatics solutions for these applications, providing interoperability among very diverse and heterogeneous data and information sources, as well as multi-disciplinary organizations and people. We have partnered with NOAA NMFS scientists to facilitate the deployment of an integrated ecosystem approach to management in the Northeast U.S. (NES) and California Current Large Marine Ecosystems (LMEs). Our platform will facilitate the collaboration and knowledge sharing among NMFS natural and social scientists, promoting community participation in integrating data, models, and knowledge. Here, we present collaborative software tools developed to aid the production of the Ecosystem Status Report (ESR) for the NES LME. The ESR addresses the D-P-S portion of the DPSIR (Driver-Pressure-State-Impact-Response) management framework: reporting data, indicators, and information products for climate drivers, physical and human (fisheries) pressures, and ecosystem state (primary and secondary production and higher trophic levels). We are developing our tools in open-source software, with the main tool based on a web application capable of providing the ability to work on multiple data types from a variety of sources, providing an effective way to share the source code used to generate data products and associated metadata as well as track workflow provenance to allow in the reproducibility of a data product. Our platform retrieves data, conducts standard analyses, reports data quality and other standardized metadata, provides iterative
Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.
Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736
Singer, Alexander; Salman, Mo; Thulke, Hans-Hermann
Animal health is of societal importance as it affects human welfare, and anthropogenic interests shape decision making to assure animal health. Scientific advice to support decision making is manifold. Modelling, as one piece of the scientific toolbox, is appreciated for its ability to describe and structure data, to give insight in complex processes and to predict future outcome. In this paper we study the application of scientific modelling to support practical animal health decisions. We reviewed the 35 animal health related scientific opinions adopted by the Animal Health and Animal Welfare Panel of the European Food Safety Authority (EFSA). Thirteen of these documents were based on the application of models. The review took two viewpoints, the decision maker's need and the modeller's approach. In the reviewed material three types of modelling questions were addressed by four specific model types. The correspondence between tasks and models underpinned the importance of the modelling question in triggering the modelling approach. End point quantifications were the dominating request from decision makers, implying that prediction of risk is a major need. However, due to knowledge gaps corresponding modelling studies often shed away from providing exact numbers. Instead, comparative scenario analyses were performed, furthering the understanding of the decision problem and effects of alternative management options. In conclusion, the most adequate scientific support for decision making - including available modelling capacity - might be expected if the required advice is clearly stated. Copyright © 2011 Elsevier B.V. All rights reserved.
Shirley Jie Xuan Wang
Full Text Available This article addresses the possibility of incorporating intelligent decision support systems into reinsurance decision-making. This involves the insurance company and the reinsurance company, and is negotiated through reinsurance intermediaries. The article proposes a decision flow to model the reinsurance design and selection process. This article focuses on adopting more than one optimality criteria under a more generic combinational design of commonly used reinsurance products, i.e., proportional reinsurance and stop-loss reinsurance. In terms of methodology, the significant contribution of the study the incorporation of the well-established decision analysis tool multiple-attribute decision-making (MADM into the modelling of reinsurance selection. To illustrate the feasibility of incorporating intelligent decision supporting systems in the reinsurance market, the study includes a numerical case study using the simulation software @Risk in modeling insurance claims, as well as programming in MATLAB to realize MADM. A list of managerial implications could be drawn from the case study results. Most importantly, when choosing the most appropriate type of reinsurance, insurance companies should base their decisions on multiple measurements instead of single-criteria decision-making models so that their decisions may be more robust.
Meli, Mattia; Grimm, V; Augusiak, J.
The potential of ecological models for supporting environmental decision making is increasingly acknowledged. However, it often remains unclear whether a model is realistic and reliable enough. Good practice for developing and testing ecological models has not yet been established. Therefore, TRACE......, thereby also linking modellers and model users, for example stakeholders, decision makers, and developers of policies. We report on first experiences in producing TRACE documents. We found that the original idea underlying TRACE was valid, but to make its use more coherent and efficient, an update of its......, a general framework for documenting a model's rationale, design, and testing was recently suggested. Originally TRACE was aimed at documenting good modelling practice. However, the word 'documentation' does not convey TRACE's urgency. Therefore, we re-define TRACE as a tool for planning, performing...
Yu, Sen; He, Li; Lu, Hongwei
This paper presented a new environmental fairness based optimisation model (EFOM) for the decision-support of water resources management and water pollution control at the watershed scale. The model integrated three prediction modules for water consumption and pollutant discharge (WCPD), environmental Gini coefficient (EGC) and water quality (WASP). The model is capable of optimizing the total discharge quantity in the whole basin and controlling units both spatially and temporally, and addressing the conflicts between environmental fairness and efficiency. The model was applied to the Songhua River basin, attempting to support decision-making of joint control over the water quantity and quality. Validation of the WASP module showed that the simulation agreed well with water quality monitoring values (2013) in the Harbin section. Results from the EFOM model also indicated that the water environment in the Harbin section would be improved significantly by effectively controlling the total pollution discharge. The identified optimal strategy obtained from the EFOM showed that the percentage of water in good quality reaches 72% in 2020, suggesting that the strategy would guarantee the planning goals of The China Action Plan for Water Pollution Control to be satisfied. Hence, the modelling under the consideration of environmental fairness can be a new attempt, which is beneficial to optimal joint control of water quantity and water quality at the watershed scale.
Benndorf, Matthias; Kotter, Elmar; Langer, Mathias; Herda, Christoph; Wu, Yirong; Burnside, Elizabeth S
To develop and validate a decision support tool for mammographic mass lesions based on a standardized descriptor terminology (BI-RADS lexicon) to reduce variability of practice. We used separate training data (1,276 lesions, 138 malignant) and validation data (1,177 lesions, 175 malignant). We created naïve Bayes (NB) classifiers from the training data with tenfold cross-validation. Our "inclusive model" comprised BI-RADS categories, BI-RADS descriptors, and age as predictive variables; our "descriptor model" comprised BI-RADS descriptors and age. The resulting NB classifiers were applied to the validation data. We evaluated and compared classifier performance with ROC-analysis. In the training data, the inclusive model yields an AUC of 0.959; the descriptor model yields an AUC of 0.910 (P BI-RADS categories alone, P BI-RADS descriptors. We provide our classifier at www.ebm-radiology.com/nbmm/index.html . • We provide a decision support tool for mammographic masses at www.ebm-radiology.com/nbmm/index.html . • Our tool may reduce variability of practice in BI-RADS category assignment. • A formal analysis of BI-RADS descriptors may enhance radiologists' diagnostic performance.
Berry, Donna L; Halpenny, Barbara; Wolpin, Seth; Davison, B Joyce; Ellis, William J; Lober, William B; McReynolds, Justin; Wulff, Jennifer
Given that no other disease with the high incidence of localized prostate cancer (LPC) has so many treatments with so few certainties related to outcomes, many men are faced with assuming some responsibility for the treatment decision along with guidance from clinicians. Men strongly consider their own personal characteristics and other personal factors as important and influential to the decision. Clinical researchers have not developed or comprehensively investigated interventions to facilitate the insight and prioritizing of personal factors along with medical factors that are required of a man in preparation for the treatment decision. The purpose of this pilot study was to develop and evaluate the feasibility and usability of a Web-based decision support technology, the Personal Patient Profile-Prostate (P3P), in men newly diagnosed with LPC. Use cases were developed followed by infrastructure and content application. The program was provided on a personal desktop computer with a touch screen monitor. Participant responses to the query component of P3P determined the content of the multimedia educational and coaching intervention. The intervention was tailored to race, age, and personal factors reported as influencing the decision. Prepilot usability testing was conducted using a "think aloud" interview to identify navigation and content challenges. These issues were addressed prior to deployment in the clinic. A clinical pilot was conducted in an academic medical center where men sought consultation and treatment for LPC. Completion time, missing data, and acceptability were measured. Prepilot testing included 4 men with a past diagnosis of LPC who had completed therapy. Technical navigation issues were documented along with confusing content language. A total of 30 additional men with a recent diagnosis of LPC completed the P3P program in clinic prior to consulting with a urologist regarding treatment options. In a mean time of 46 minutes (SD 13 minutes
interventions to advance the EBP competencies of nurses . Researchers continue to report that the use of EBP in clinical settings by RNs remains low (Duffy... nurses to know and use best practices to achieve optimal patient outcomes. Objective: This study was designed to evaluate the impact of the Knowledge...EHR to support nurses to use best practices for six phenomena (pain, medication adherence, depression/suicide, fall risk, pressure ulcer risk/actual
Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt
Intelligent decision support should allow integrating human knowledge with efficient algorithms for making interpretable and useful recommendations on real world decision problems. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled...
Alfonso, J. C. L.; Herrero, M. A.; Núñez, L.
The choice of any radiotherapy treatment plan is usually made after the evaluation of a few preliminary isodose distributions obtained from different beam configurations. Despite considerable advances in planning techniques, such final decision remains a challenging task that would greatly benefit from efficient and reliable assessment tools. For any dosimetric plan considered, data on dose-volume histograms supplied by treatment planning systems are used to provide estimates on planning target coverage as well as on sparing of organs at risk and the remaining healthy tissue. These partial metrics are then combined into a dose distribution index (DDI), which provides a unified, easy-to-read score for each competing radiotherapy plan. To assess the performance of the proposed scoring system, DDI figures for fifty brain cancer patients were retrospectively evaluated. Patients were divided in three groups depending on tumor location and malignancy. For each patient, three tentative plans were designed and recorded during planning, one of which was eventually selected for treatment. We thus were able to compare the plans with better DDI scores and those actually delivered. When planning target coverage and organs at risk sparing are considered as equally important, the tentative plan with the highest DDI score is shown to coincide with that actually delivered in 32 of the 50 patients considered. In 15 (respectively 3) of the remaining 18 cases, the plan with highest DDI value still coincides with that actually selected, provided that organs at risk sparing is given higher priority (respectively, lower priority) than target coverage. DDI provides a straightforward and non-subjective tool for dosimetric comparison of tentative radiotherapy plans. In particular, DDI readily quantifies differences among competing plans with similar-looking dose-volume histograms and can be easily implemented for any tumor type and localization, irrespective of the planning system and
Effective decision support for site characterization is key to determining the nature and extent of contamination and the associated human and environmental risks. Site characterization data, however, present particular problems to technical analysts and decision-makers. Such data are four dimensional, incorporating temporal and spatial components. Their sheer volume can be daunting -- sites with hundreds of monitoring wells and thousands of samples sent for laboratory analyses are not uncommon. Data are derived from a variety of sources including laboratory analyses, non-intrusive geophysical surveys, historical information, bore logs, in-field estimates of key physical parameters such as aquifer transmissivity, soil moisture content, depth-to-water table, etc. Ultimately, decisions have to be made based on data that are always incomplete, often confusing, inaccurate, or inappropriate, and occasionally wrong. In response to this challenge, two approaches to environmental decision support have arisen, Data Quality Objectives (DQOS) and the Observational Approach (OA). DQOs establish criteria for data collection by clearly defining the decisions that need to be made, the uncertainty that can be tolerated, and the type and amount of data that needs to be collected to satisfy the uncertainty requirements. In practice, DQOs are typically based on statistical measures. The OA accepts the fact that the process of characterizing and remediating contaminated sites is always uncertain. Decision-making with the OA is based on what is known about a site, with contingencies developed for potential future deviations from the original assumptions about contamination nature, extent, and risks posed
Villarreal, Miguel; Norman, Laura M.; Labiosa, William B.
In this paper we describe an application of a GIS-based multi-criteria decision support web tool that models and evaluates relative changes in ecosystem services to policy and land management decisions. The Santa Cruz Watershed Ecosystem Portfolio (SCWEPM) was designed to provide credible forecasts of responses to ecosystem drivers and stressors and to illustrate the role of land use decisions on spatial and temporal distributions of ecosystem services within a binational (U.S. and Mexico) watershed. We present two SCWEPM sub-models that when analyzed together address bidirectional relationships between social and ecological vulnerability and ecosystem services. The first model employs the Modified Socio-Environmental Vulnerability Index (M-SEVI), which assesses community vulnerability using information from U.S. and Mexico censuses on education, access to resources, migratory status, housing situation, and number of dependents. The second, relating land cover change to biodiversity (provisioning services), models changes in the distribution of terrestrial vertebrate habitat based on multitemporal vegetation and land cover maps, wildlife habitat relationships, and changes in land use/land cover patterns. When assessed concurrently, the models exposed some unexpected relationships between vulnerable communities and ecosystem services provisioning. For instance, the most species-rich habitat type in the watershed, Desert Riparian Forest, increased over time in areas occupied by the most vulnerable populations and declined in areas with less vulnerable populations. This type of information can be used to identify ecological conservation and restoration targets that enhance the livelihoods of people in vulnerable communities and promote biodiversity and ecosystem health.
... stands within the context of a ground based air defence system (GBADS) at the turn of the twenty first century. However, much of the contents of the paper maye generalized to military environments other than a GBADS one. Keywords: Threat evaluation, weapon assignment, decision support. ORiON Vol. 23 (2) 2007: pp.
A genetic algorithm based method has been proposed to solve the problem in a large scale realistic environment. The efficacy of the developed strategic decision support model in achieving better utilization of network and resources to fulfill the customer demand is demonstrated using illustrative scenarios inspired from the ...
Wismans, Luc Johannes Josephus; de Romph, E.; Friso, K.; Zantema, K.
Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various
Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.
Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various
Full Text Available The support of decision-making activities in small and medium-sized enterprises (SME has its specific features. When suggesting steps for the implementation of decision-support tools in the enterprise, we identified two main ways of decision-making support based on the data analysis: ERP (Enterprise Resource Planning without BI (Business Intelligence and ERP with BI. In our contribution, we present costs models of both mentioned decision support systems and their practical interpretation.
The performance evaluation of innovative and alternative environmental technologies is an integral part of the US Environmental Protection Agency's (EPA) mission. Early efforts focused on evaluating technologies that supported the implementation of the Clean Air and Clean Water Acts. In 1986 the Agency began to demonstrate and evaluate the cost and performance of remediation and monitoring technologies under the Superfund Innovative Technology Evaluation (SITE) program (in response to the mandate in the Superfund Amendments and Reauthorization Act of 1986 (SARA)). In 1990, the US Technology Policy was announced. This policy placed a renewed emphasis on making the best use of technology in achieving the national goals of improved quality of life for all Americans, continued economic growth, and national security. In the spirit of the technology policy, the Agency began to direct a portion of its resources toward the promotion, recognition, acceptance, and use of US-developed innovative environmental technologies both domestically and abroad. Decision Support Software (DSS) packages integrate environmental data and simulation models into a framework for making site characterization, monitoring, and cleanup decisions. To limit the scope which will be addressed in this demonstration, three endpoints have been selected for evaluation: Visualization; Sample Optimization; and Cost/Benefit Analysis. Five topics are covered in this report: the objectives of the demonstration; the elements of the demonstration plan; an overview of the Site Characterization and Monitoring Technology Pilot; an overview of the technology verification process; and the purpose of this demonstration plan.
Marotta, Stephen; Metzger, Max; Gorman, Joe; Sliva, Amy
The Dual Node Decision Wheels (DNDW) architecture is a new approach to information fusion and decision support systems. By combining cognitive systems engineering organizational analysis tools, such as decision trees, with the Dual Node Network (DNN) technical architecture for information fusion, the DNDW can align relevant data and information products with an organization's decision-making processes. In this paper, we present the Compositional Inference and Machine Learning Environment (CIMLE), a prototype framework based on the principles of the DNDW architecture. CIMLE provides a flexible environment so heterogeneous data sources, messaging frameworks, and analytic processes can interoperate to provide the specific information required for situation understanding and decision making. It was designed to support the creation of modular, distributed solutions over large monolithic systems. With CIMLE, users can repurpose individual analytics to address evolving decision-making requirements or to adapt to new mission contexts; CIMLE's modular design simplifies integration with new host operating environments. CIMLE's configurable system design enables model developers to build analytical systems that closely align with organizational structures and processes and support the organization's information needs.
Zhang, Shanghong; Li, Yueqiang; Zhang, Tianxiang; Peng, Yang
This paper details the development and application of an integrated environmental decision support system (EDSS) for water pollution control based on total maximum daily load (TMDL). The system includes an infrastructure, simulation, and application platforms. Using the water pollution control of Beiyun River in China as a case study, the key development processes and technologies of the EDSS are discussed including relations and links between various environmental simulation models, and model integration, visualization and real-time simulation methods. A loose coupling method is used to connect the environmental models, and an XML file is used to complete data exchange between different models. Project configuration and scheme configuration are used for simulation data organization. The integration approach is easy to implement and enables different development languages and reuse of existing models. The EDSS has been applied to water environment management of Beiyun River, and can be applied to other geographic regions. Copyright © 2015 Elsevier Ltd. All rights reserved.
Schwaegerl, Christine; Seifert, Olaf; Buschmann, Robert; Dellwing, Hermann; Geretshuber, Stefan; Leick, Claus
The increased interconnection and automation of critical infrastructures enlarges the complexity of the dependency structures and - as consequence - the danger of cascading effects, e.g. causing area-wide blackouts in power supply networks that are currently after deregulation operated closer to their limits. New tools or an intelligent combination of existing approaches are required to increase the survivability of critical infrastructures. Within the IRRIIS project the expert system CRIPS was developed based on network simulations realised with PSS®SINCAL, an established tool to support the analysis and planning of electrical power, gas, water or heat networks. CRIPS assesses the current situation in power supply networks analysing the simulation results of the physical network behaviour and recommends corresponding decisions.
Karakülah, G; Karakuş, M; Suner, A; Demir, S; Arserim, S K; Töz, S; Özbel, Y
Species identification of sandflies is mainly performed according to morphological characters using classical written identification keys. This study introduces a new web-based decision support tool (sandflyDST) for guiding the morphological identification of sandfly species present in Anatolia and mainland Europe and classified in the Phlebotomus and Sergentomyia genera (both: Diptera: Psychodidae). The current version of the tool consists of 111 questions and 36 drawings obtained from classical written keys, and 107 photographs for the quick and easy identification of 26 species of the genus Phlebotomus and four species of the genus Sergentomyia. The tool guides users through a decision tree using yes/no questions about the morphological characters of the specimen. The tool was applied by 30 individuals, who then completed study questionnaires. The results of subsequent analyses indicated that the usability (x‾SUSScore=75.4) and users' level of appreciation (86.6%) of the tool were quite high; almost all of the participants considered recommending the tool to others. The tool may also be useful in training new entomologists and maintaining their level of expertise. This is a dynamic tool and can be improved or upgraded according to feedback. The tool is now available online at http://parasitology.ege.edu.tr/sandflyDST/index.php. © 2016 The Royal Entomological Society.
Miller, Perry; Phipps, Michael; Chatterjee, Sharmila; Rajeevan, Nallakkandi; Levin, Forrest; Frawley, Sandra; Tokuno, Hajime
Computer-based clinical decision support (CDS) is an important component of the electronic health record (EHR). As an increasing amount of CDS is implemented, it will be important that this be accomplished in a fashion that assists in clinical decision making without imposing unacceptable demands and burdens upon the provider's practice. The objective of our study was to explore an approach that allows CDS to be clinician-friendly from a variety of perspectives, to build a prototype implementation that illustrates features of the approach, and to gain experience with a pilot framework for assessment. The paper first discusses the project's design philosophy and goals. It then describes a prototype implementation (Neuropath/CDS) that explores the approach in the domain of neuropathic pain and in the context of the US Veterans Administration EHR. Finally, the paper discusses a framework for assessing the approach, illustrated by a pilot assessment of Neuropath/CDS. The paper describes the operation and technical design of Neuropath/CDS, as well as the results of the pilot assessment, which emphasize the four areas of focus, scope, content, and presentation. The work to date has allowed us to explore various design and implementation issues relating to the approach illustrated in Neuropath/CDS, as well as the development and pilot application of a framework for assessment.
Robson, Barry; Boray, Srinidhi
Extracting medical knowledge by structured data mining of many medical records and from unstructured data mining of natural language source text on the Internet will become increasingly important for clinical decision support. Output from these sources can be transformed into large numbers of elements of knowledge in a Knowledge Representation Store (KRS), here using the notation and to some extent the algebraic principles of the Q-UEL Web-based universal exchange and inference language described previously, rooted in Dirac notation from quantum mechanics and linguistic theory. In a KRS, semantic structures or statements about the world of interest to medicine are analogous to natural language sentences seen as formed from noun phrases separated by verbs, prepositions and other descriptions of relationships. A convenient method of testing and better curating these elements of knowledge is by having the computer use them to take the test of a multiple choice medical licensing examination. It is a venture which perhaps tells us almost as much about the reasoning of students and examiners as it does about the requirements for Artificial Intelligence as employed in clinical decision making. It emphasizes the role of context and of contextual probabilities as opposed to the more familiar intrinsic probabilities, and of a preliminary form of logic that we call presyllogistic reasoning. Copyright © 2016 Elsevier Ltd. All rights reserved.
Full Text Available Management of higher education must continue to evaluate on an ongoing basis in order to improve the quality of institutions. This will be able to do the necessary evaluation of various data, information, and knowledge of both internal and external institutions. They plan to use more efficiently the collected data, develop tools so that to collect and direct management information, in order to support managerial decision making. The collected data could be utilized to evaluate quality, perform analyses and diagnoses, evaluate dependability to the standards and practices of curricula and syllabi, and suggest alternatives in decision processes. Data minings to support decision making are well suited methods to provide decision support in the education environments, by generating and presenting relevant information and knowledge towards quality improvement of education processes. In educational domain, this information is very useful since it can be used as a base for investigating and enhancing the current educational standards and managements. In this paper, a review on data mining for academic decision support in education field is presented. The details of this paper will review on recent data mining in educational field and outlines future researches in educational data mining.
Mould, D. R.; D'Haens, G.; Upton, R. N.
Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug
The Baltic Sea is especially susceptible to multiple human impacts due to its estuarine mixing patterns and long water residence times. Temporally and spatially, it is one of the best investigated marginal seas worldwide allowing for a deep knowledge of natural and human processes forming this unique brackish ecosystem. In this presentation, we shortly summarize the physical, biogeochemical and ecological settings of the Baltic Sea and address major human drivers and pressures threatening its ecosystem. Further, we summarize the scientific and political efforts that led to the formulation of Baltic Sea Action Plan, a milestone for eutrophication management and European environmental governance. Further, we summarize the efforts and societal pitfalls towards an Ecosystem Based Fisheries Management, strategies to decrease loads of environmental pollutants and management of marine biodiversity/habitat issues in the unique Baltic Sea context.
Kathrin Rodríguez Llanes
Full Text Available Making decisions is complicated in a generalized way, the materials and humans resources of the entity we belong to depends on it, such as the fulfillment of its goals. But when the situations are complex, making decisions turns into a very difficult work, due to the great amount of aspects to consider when making the right choice. To make this efficiently the administration must to consult an important volume of information, which generally, is scattered and in any different formats. That’s why appears the need of developing software that crowd together all that information and be capable of, by using powerful search engines and process algorithms improve the good decisions making process. Considering previous explanation, a complete freeware developed product is proposed, this constitutes a generic and multi-platform solution, that using artificial intelligence techniques, specifically the cases based reasoning, gives the possibility to leaders of any institution or organism of making the right choice in any situation.With client-server architecture, this system is consumed from web as a service and it can be perfectly integrated with a management system or the geographic information system to facilitate the business process.
Khan, Shiraj [ORNL; Ganguly, Auroop R [ORNL; Gupta, Amar [University of Arizona
The process of Data Mining converts information to knowledge by utilizing tools from the disciplines of computational statistics, database technologies, machine learning, signal processing, nonlinear dynamics, process modeling, simulation, and allied disciplines. Data Mining allows business problems to be analyzed from diverse perspectives, including dimensionality reduction, correlation and co-occurrence, clustering and classification, regression and forecasting, anomaly detection, and change analysis. The predictive insights generated from Data Mining can be further utilized through real-time analysis and decision sciences, as well as through human-driven analysis based on management by exceptions or by objectives, to generate actionable knowledge. The tools that enable the transformation of raw data to actionable predictive insights are collectively referred as Decision Support tools. This chapter presents a new formalization of the decision process, leading to a new Decision Superiority model, partially motivated by the Joint Directors of Laboratories (JDL) Data Fusion Model. In addition, it examines the growing importance of Data Fusion concepts.
Erin Noonan-Wright; Tonja S. Opperman; Mark A. Finney; Tom Zimmerman; Robert C. Seli; Lisa M. Elenz; David E. Calkin; John R. Fiedler
A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply...
Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive
In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…
G.H. van Bruggen (Gerrit); B. Wierenga (Berend)
textabstractMarketing management support systems (MMSS) are computer-enabled devices that help marketers to make better decisions. Marketing processes can be quite complex, involving large numbers of variables and mostly outcomes are the results of the actions of many different stakeholders (e.g.,
Novac Ududec, Cornelia / C
The paper purpose an intelligent software system agents–based to support decision in aquculture and the approach of fish diagnosis with informatics methods, techniques and solutions. A major purpose is to develop new methods and techniques for quick fish diagnosis, treatment and prophyilaxis at infectious and parasite-based known disorders, that may occur at fishes raised in high density in intensive raising systems. But, the goal of this paper is to presents a model of an intelligent agents-...
Glasscoe, M. T.; Stough, T. M.; Parker, J. W.; Burl, M. C.; Donnellan, A.; Blom, R. G.; Pierce, M. E.; Wang, J.; Ma, Y.; Rundle, J. B.; Yoder, M. R.
Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing capabilities for decision-making utilizing remote sensing data and modeling software in order to provide decision support for earthquake disaster management and response. E-DECIDER incorporates earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project in order to produce standards-compliant map data products to aid in decision-making following an earthquake. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools, help provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). E-DECIDER utilizes a service-based GIS model for its cyber-infrastructure in order to produce standards-compliant products for different user types with multiple service protocols (such as KML, WMS, WFS, and WCS). The goal is to make complex GIS processing and domain-specific analysis tools more accessible to general users through software services as well as provide system sustainability through infrastructure services. The system comprises several components, which include: a GeoServer for thematic mapping and data distribution, a geospatial database for storage and spatial analysis, web service APIs, including simple-to-use REST APIs for complex GIS functionalities, and geoprocessing tools including python scripts to produce standards-compliant data products. These are then served to the E-DECIDER decision support gateway (http://e-decider.org), the E-DECIDER mobile interface, and to the Department of Homeland Security decision support middleware UICDS (Unified Incident Command and Decision Support). The E-DECIDER decision support gateway features a web interface that
Arkad, K; Ahlfeldt, H; Gao, X; Shahsavar, N; Wigertz, O; Jean, F C; Degoulet, P
The development of large-scale, clinically accepted decision support systems (DSS) calls for powerful and commonly available methods and tools for knowledge acquisition, system realisation, and knowledge base maintenance. The paper addresses problems associated with the integration of knowledge-based systems within the clinical setting with special reference to (i) data driven decision support, (ii) the Arden Syntax as a knowledge representation format and, (iii) the HELIOS software engineering environment. Architecture of a DSS based on Arden Syntax and its integration in the HELIOS environment are presented. Realisation of the DSS is discussed in relation to client-server architecture and object-oriented databases, which are essential concepts of the HELIOS environment. Sharability and reusability of the knowledge, together with commonality of used software tools are also discussed.
Hudson, Donna L; Cohen, Maurice E
Attempts to automate the medical decision making process have been underway for the at least fifty years, beginning with data-based approaches that relied chiefly on statistically-based methods. Approaches expanded to include knowledge-based systems, both linear and non-linear neural networks, agent-based systems, and hybrid methods. While some of these models produced excellent results none have been used extensively in medical practice. In order to move these methods forward into practical use, a number of obstacles must be overcome, including validation of existing systems on large data sets, development of methods for including new knowledge as it becomes available, construction of a broad range of decision models, and development of non-intrusive methods that allow the physician to use these decision aids in conjunction with, not instead of, his or her own medical knowledge. None of these four requirements will come easily. A cooperative effort among researchers, including practicing MDs, is vital, particularly as more information on diseases and their contributing factors continues to expand resulting in more parameters than the human decision maker can process effectively. In this article some of the basic structures that are necessary to facilitate the use of an automated decision support system are discussed, along with potential methods for overcoming existing barriers.
The Containment and Release Management project was carried out within the Reinforced Concerted Action Programme for Accident Management Support and partly financed by the European Union. In this report a prototype of an accident management support system is presented. The support system integrates several concepts from accident management research, like safety objective trees, severe accident phenomena, calculation models and an emergency response data system. These concepts are provided by the prototype in such a way that the decision making process of accident management is supported. The prototype application is demonstrated by process data taken from a severe accident scenario for a pressurized water reactor (PWR) that was simulated with the thermohydraulic computer program MAAP. The prototype was derived from a decision support framework based on a decision theory. For established and innovative concepts from accident management research it is pointed out in which way these concepts can support accident management and how these concepts can be integrated. This approach is generic in two ways; it applies to both pressurized and boiling water reactors and it applies to both in vessel management and containment and release management. The prototype application was developed in Multimedia Toolbox 3.0 and requires at least a 386 PC with 4 MB memory, 6 MB free disk space and MS Windows 3.1. (orig.)
Full Text Available that are not always explicitly linked to development outcomes. Throughout this process, scope exists to aid decision makers, through a simplistic set of decision models, to make better decisions. The emphasis is on decisions that support long-term value creation...
Gill, Roger; Schnase, John L.
The Invasive Species Forecasting System (ISFS) is an online decision support system that allows users to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of interest, such as a national park, monument, forest, or refuge. Target customers for ISFS are natural resource managers and decision makers who have a need for scientifically valid, model- based predictions of the habitat suitability of plant species of management concern. In a joint project involving NASA and the Maryland Department of Natural Resources, ISFS has been used to model the potential distribution of Wavyleaf Basketgrass in Maryland's Chesapeake Bay Watershed. Maximum entropy techniques are used to generate predictive maps using predictor datasets derived from remotely sensed data and climate simulation outputs. The workflow to run a model is implemented in an iRODS microservice using a custom ISFS file driver that clips and re-projects data to geographic regions of interest, then shells out to perform MaxEnt processing on the input data. When the model completes, all output files and maps from the model run are registered in iRODS and made accessible to the user. The ISFS user interface is a web browser that uses the iRODS PHP client to interact with the ISFS/iRODS- server. ISFS is designed to reside in a VMware virtual machine running SLES 11 and iRODS 3.0. The ISFS virtual machine is hosted in a VMware vSphere private cloud infrastructure to deliver the online service.
Neves-Silva, Rui; Jain, Lakhmi; Phillips-Wren, Gloria; Watada, Junzo; Howlett, Robert
This book contains a collection of innovative chapters emanating from topics raised during the 5th KES International Conference on Intelligent Decision Technologies (IDT), held during 2013 at Sesimbra, Portugal. The authors were invited to expand their original papers into a plethora of innovative chapters espousing IDT methodologies and applications. This book documents leading-edge contributions, representing advances in Knowledge-Based and Intelligent Information and Engineering System. It acknowledges that researchers recognize that society is familiar with modern Advanced Information Processing and increasingly expect richer IDT systems. Each chapter concentrates on the theory, design, development, implementation, testing or evaluation of IDT techniques or applications. Anyone that wants to work with IDT or simply process knowledge should consider reading one or more chapters and focus on their technique of choice. Most readers will benefit from reading additional chapters to access alternative techniq...
Booister, Nikéh; Verkade, Jan; Werner, Micha; Cranston, Michael; Cumiskey, Lydia; Zevenbergen, Chris
Flood forecasting systems reduce, but cannot eliminate uncertainty about the future. Probabilistic forecasts explicitly show that uncertainty remains. However, as - compared to deterministic forecasts - a dimension is added ('probability' or 'likelihood'), with this added dimension decision making is made slightly more complicated. A technique of decision support is the cost-loss approach, which defines whether or not to issue a warning or implement mitigation measures (risk-based method). With the cost-loss method a warning will be issued when the ratio of the response costs to the damage reduction is less than or equal to the probability of the possible flood event. This cost-loss method is not widely used, because it motivates based on only economic values and is a technique that is relatively static (no reasoning, yes/no decision). Nevertheless it has high potential to improve risk-based decision making based on probabilistic flood forecasting because there are no other methods known that deal with probabilities in decision making. The main aim of this research was to explore the ways of making decision making based on probabilities with the cost-loss method better applicable in practice. The exploration began by identifying other situations in which decisions were taken based on uncertain forecasts or predictions. These cases spanned a range of degrees of uncertainty: from known uncertainty to deep uncertainty. Based on the types of uncertainties, concepts of dealing with situations and responses were analysed and possible applicable concepts where chosen. Out of this analysis the concepts of flexibility and robustness appeared to be fitting to the existing method. Instead of taking big decisions with bigger consequences at once, the idea is that actions and decisions are cut-up into smaller pieces and finally the decision to implement is made based on economic costs of decisions and measures and the reduced effect of flooding. The more lead-time there is in
Full Text Available This paper deals with formalization of business rules by formal grammars. In our work we focus on methods for high frequency data processing. We process data by using complex event platforms (CEP which allow to process high volume of data in nearly real time. Decision making process is contained by one level of processing of CEP. Business rules are used for decision making process description. For the business rules formalization we chose matrix grammar. The use of formal grammars is quite natural as the structure of rules and its rewriting is very similar both for the business rules and for formal grammar. In addition the matrix grammar allows to simulate dependencies and correlations between the rules. The result of this work is a model for data processing of knowledge-based decision support system described by the rules of formal grammar. This system will support the decision making in CEP. This solution may contribute to the speedup of decision making process in complex event processing and also to the formal verification of these systems.
Bhave, Ajay; Dessai, Suraje; Conway, Declan; Stainforth, David
Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing
Full Text Available To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids.Scale development study, involving construct, item and scale development, validation and reliability testing.There has been increasing use of decision support technologies--adjuncts to the discussions clinicians have with patients about difficult decisions. A global interest in developing these interventions exists among both for-profit and not-for-profit organisations. It is therefore essential to have internationally accepted standards to assess the quality of their development, process, content, potential bias and method of field testing and evaluation.Scale development study, involving construct, item and scale development, validation and reliability testing.Twenty-five researcher-members of the International Patient Decision Aid Standards Collaboration worked together to develop the instrument (IPDASi. In the fourth Stage (reliability study, eight raters assessed thirty randomly selected decision support technologies.IPDASi measures quality in 10 dimensions, using 47 items, and provides an overall quality score (scaled from 0 to 100 for each intervention. Overall IPDASi scores ranged from 33 to 82 across the decision support technologies sampled (n = 30, enabling discrimination. The inter-rater intraclass correlation for the overall quality score was 0.80. Correlations of dimension scores with the overall score were all positive (0.31 to 0.68. Cronbach's alpha values for the 8 raters ranged from 0.72 to 0.93. Cronbach's alphas based on the dimension means ranged from 0.50 to 0.81, indicating that the dimensions, although well correlated, measure different aspects of decision support technology quality. A short version (19 items was also developed that had very similar mean scores to IPDASi and high correlation between short score and overall score 0.87 (CI 0.79 to 0.92.This work
Yang, Cheng-Yi; Lo, Yu-Sheng; Chen, Ray-Jade; Liu, Chien-Tsai
A computerized physician order entry (CPOE) system combined with a clinical decision support system can reduce duplication of medications and thus adverse drug reactions. However, without infrastructure that supports patients' integrated medication history across health care facilities nationwide, duplication of medication can still occur. In Taiwan, the National Health Insurance Administration has implemented a national medication repository and Web-based query system known as the PharmaCloud, which allows physicians to access their patients' medication records prescribed by different health care facilities across Taiwan. This study aimed to develop a scalable, flexible, and thematic design-based clinical decision support (CDS) engine, which integrates a national medication repository to support CPOE systems in the detection of potential duplication of medication across health care facilities, as well as to analyze its impact on clinical encounters. A CDS engine was developed that can download patients' up-to-date medication history from the PharmaCloud and support a CPOE system in the detection of potential duplicate medications. When prescribing a medication order using the CPOE system, a physician receives an alert if there is a potential duplicate medication. To investigate the impact of the CDS engine on clinical encounters in outpatient services, a clinical encounter log was created to collect information about time, prescribed drugs, and physicians' responses to handling the alerts for each encounter. The CDS engine was installed in a teaching affiliate hospital, and the clinical encounter log collected information for 3 months, during which a total of 178,300 prescriptions were prescribed in the outpatient departments. In all, 43,844/178,300 (24.59%) patients signed the PharmaCloud consent form allowing their physicians to access their medication history in the PharmaCloud. The rate of duplicate medication was 5.83% (1843/31,614) of prescriptions. When
Allen, Will; Cruz, Jennyffer; Warburton, Bruce
Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.
Allen, Will; Cruz, Jennyffer; Warburton, Bruce
Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.
Non-hazardous solid materials from industrial processes, once regarded as waste and disposed in landfills, offer numerous environmental and economic advantages when put to beneficial uses (BUs). Proper management of these industrial non-hazardous secondary materials (INSM) requires estimates of their probable environmental impacts among disposal as well as BU options. The U.S. Environmental Protection Agency (EPA) has recently approved new analytical methods (EPA Methods 1313–1316) to assess leachability of constituents of potential concern in these materials. These new methods are more realistic for many disposal and BU options than historical methods, such as the toxicity characteristic leaching protocol. Experimental data from these new methods are used to parameterize a chemical fate and transport (F&T) model to simulate long-term environmental releases from flue gas desulfurization gypsum (FGDG) when disposed of in an industrial landfill or beneficially used as an agricultural soil amendment. The F&T model is also coupled with optimization algorithms, the Beneficial Use Decision Support System (BUDSS), under development by EPA to enhance INSM management. The objective of this paper is to demonstrate the methodologies and encourage similar applications to improve environmental management and BUs of INSM through F&T simulation coupled with optimization, using realistic model parameterization.
Ciolofan, Sorin N; Draghia, Aurelian; Drobot, Radu; Mocanu, Mariana; Cristea, Valentin
Accidental river pollution can cause damage to the environment, put at risk the health of people that use the water for domestic purposes, and, not lastly, compromise dependent economic activities (e.g., agriculture). The reduction of the concentration of pollutant on any river following an accidental pollution can be achieved using dilution, by opening for certain duration the bottom gates of the reservoirs placed on the river's tributaries and releasing a significant volume of clean water in the main river. The hydraulic simulation and the pollutant transport are executed, firstly considering there is no dilution and secondly for the dilution scenario (bottom gates of the reservoirs open). A database was created, containing the results of simulations of pollutant transport for various values of the pollution characteristics in both diluted/undiluted scenarios. The database served for the implementation of a web decision support tool that presents an intuitive and easy to use GUI that allows the user to input details of the accidental pollution. Straightforward actions to be taken are presented to the end-user (e.g., "Open the bottom gates of the reservoir X at time T1 and close it at time T2") and synchronized charts show the effect of the dilution in respect to the concentration of pollutant at certain locations on the river. Using the described approach, a reduction of pollutant concentration in the river with up to 90% can be obtained.
Bruggen, Gerrit; Wierenga, Berend
textabstractMarketing management support systems (MMSS) are computer-enabled devices that help marketers to make better decisions. Marketing processes can be quite complex, involving large numbers of variables and mostly outcomes are the results of the actions of many different stakeholders (e.g., the company itself, its customers, its competitors). Moreover, a large number of interdependencies exist between the relevant variables and the outcomes of marketing actions are subject to major unc...
Dudchenko, Aleksey; Kopanitsa, Georgy
The aim of this work was to identify the most common approaches used in the intelligent decision support systems employed in the diagnosis of cardiovascular diseases and identify accuracy of these systems. Forty-one relevant publications were included in the review using Scopus and Web of Science. Knowledge base and fuzzy logic and ANN is the most commonly used approach to diagnosis and prediction. The accuracy of the considered systems reaches 98%.
Behnood, Hamid Reza; Ayati, Esmaeel; Brijs, Tom; Neghab, Mohammadali Pirayesh; Shen, Yongjun
The objective of this research was to develop a decision-support system to help road safety policy makers make the right choices in road safety planning based on the efficiency of previously implemented safety measures. The measures considered for each region in the study include performance indicators about police operations, treated black spots, freeway and highway facility supplies, speed control cameras, emergency medical services and road lighting projects. To this end, an inefficiency m...
Van der Merwe, A
Full Text Available Recent technological advances have had a major impact on the management of traditional wineries, giving rise to the prospect of computerised decision support with respect to a range of complex harvesting and wine making decisions which have...
Full Text Available A decision support concept (DSC for sustainable management of the bottom trawl fleet was created in line with ecosystem-based management. It is based on principles that integrate ecological, social and techno-economic aspects of trawl fisheries in a multicriteria analysis approach. For the sake of greater transparency and improved stakeholder participation, elements of the proposed multicriteria models were discussed, generated and evaluated in collaboration with designated experts from four stakeholder groups: fishers, environmentally focused non-governmental organizations, fisheries scientists and government representatives. The proposed DSC management could facilitate management and assist decision makers in adequately using data and scientific advice to shape management strategies and related policies for the bottom trawl fleet. It may also assist in finding compromise solutions based on deliverables from the multicriteria analysis, while taking stakeholder requirements into account by using the multicriteria Analytic Hierarchy Process (AHP and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE methods. The final decision is then based on a vast amount of knowledge and relevant information collected from different sources. The proposed DSC represents a novel approach to fishery fleet management and assists in systematizing management processes and instruments to make it operational at the strategic level. The method was applied to the Adriatic bottom trawl fishery, and the obtained results confirmed its managerial potential in the strategic decision-making process, aimed at improving conventional management, while considering the specific requirements of an ecosystem-based approach and ensuring stakeholder participation.
Raskob, W.; Heling, R.; Zheleznyak, M.
This paper discusses the role of hydrological modelling in decision support systems for nuclear emergencies. In particular, most recent developments such as, the radionuclide transport models integrated in to the decision support system RODOS will be explored. Recent progress in the implementation of physically-based distributed hydrological models for operational forecasting in national and supranational centres, may support a closer cooperation between national hydrological services and therefore, strengthen the use of hydrological and radiological models implemented in decision support systems. (authors)
Full Text Available Nesting habitat for the federally endangered loggerhead sea turtle (Caretta caretta were designated as critical in 2014 for beaches along the Atlantic Coast and Gulf of Mexico. Nesting suitability is routinely determined based on site specific information. Given the expansive geographic location of the designated critical C. caretta nesting habitat and the highly dynamic coastal environment, understanding nesting suitability on a regional scale is essential for monitoring the changing status of the coast as a result of hydrodynamic forces and maintenance efforts. The increasing spatial resolution and temporal frequency of remote sensing data offers the opportunity to study this dynamic environment on a regional scale. Remote sensing data were used as input into the spatially-explicit, multi-criteria decision support model to determine nesting habitat suitability. Results from the study indicate that the morphological parameters used as input into the model are well suited to provide a regional level approach with the results from the optimized model having sensitivity and detection prevalence values greater than 80% and the detection rate being greater than 70%. The approach can be implemented in various geographic locations to better communicate priorities and evaluate management strategies as a result of changes to the dynamic coastal environment.
Benndorf, Matthias; Kotter, Elmar; Langer, Mathias; Herda, Christoph; Wu, Yirong; Burnside, Elizabeth S.
Purpose To develop and validate a decision support tool for mammographic mass lesions based on a standardized descriptor terminology (BI-RADS lexicon) to reduce variability of practice. Materials and Methods We used separate training data (1276 lesions, 138 malignant) and validation data (1177 lesions, 175 malignant). We created naïve Bayes (NB) classifiers from the training data with 10-fold cross validation. Our “inclusive model” comprised BI-RADS categories, BI-RADS descriptors and age as predictive variables, our “descriptor model” comprised BI-RADS descriptors and age. The resulting NB classifiers were applied to the validation data. We evaluated and compared classifier performance with ROC-analysis. Results In the training data, the inclusive model yields an AUC of 0.959, the descriptor model yields an AUC of 0.910 (PBI-RADS categories alone, PBI-RADS descriptors. We provide our classifier at www.ebm-radiology.com/nbmm/index.html. PMID:25576230
Benndorf, Matthias; Kotter, Elmar; Langer, Mathias; Herda, Christoph; Wu, Yirong; Burnside, Elizabeth S.
To develop and validate a decision support tool for mammographic mass lesions based on a standardized descriptor terminology (BI-RADS lexicon) to reduce variability of practice. We used separate training data (1,276 lesions, 138 malignant) and validation data (1,177 lesions, 175 malignant). We created naive Bayes (NB) classifiers from the training data with tenfold cross-validation. Our ''inclusive model'' comprised BI-RADS categories, BI-RADS descriptors, and age as predictive variables; our ''descriptor model'' comprised BI-RADS descriptors and age. The resulting NB classifiers were applied to the validation data. We evaluated and compared classifier performance with ROC-analysis. In the training data, the inclusive model yields an AUC of 0.959; the descriptor model yields an AUC of 0.910 (P < 0.001). The inclusive model is superior to the clinical performance (BI-RADS categories alone, P < 0.001); the descriptor model performs similarly. When applied to the validation data, the inclusive model yields an AUC of 0.935; the descriptor model yields an AUC of 0.876 (P < 0.001). Again, the inclusive model is superior to the clinical performance (P < 0.001); the descriptor model performs similarly. We consider our classifier a step towards a more uniform interpretation of combinations of BI-RADS descriptors. We provide our classifier at www.ebm-radiology.com/nbmm/index.html. (orig.)
Benndorf, Matthias; Kotter, Elmar; Langer, Mathias [University Hospital Freiburg, Department of Radiology, Freiburg (Germany); Herda, Christoph [Kantonsspital Graubuenden, Chur (Switzerland); Wu, Yirong; Burnside, Elizabeth S. [University of Wisconsin-Madison School of Medicine and Public Health, Department of Radiology, Madison, WI (United States)
To develop and validate a decision support tool for mammographic mass lesions based on a standardized descriptor terminology (BI-RADS lexicon) to reduce variability of practice. We used separate training data (1,276 lesions, 138 malignant) and validation data (1,177 lesions, 175 malignant). We created naive Bayes (NB) classifiers from the training data with tenfold cross-validation. Our ''inclusive model'' comprised BI-RADS categories, BI-RADS descriptors, and age as predictive variables; our ''descriptor model'' comprised BI-RADS descriptors and age. The resulting NB classifiers were applied to the validation data. We evaluated and compared classifier performance with ROC-analysis. In the training data, the inclusive model yields an AUC of 0.959; the descriptor model yields an AUC of 0.910 (P < 0.001). The inclusive model is superior to the clinical performance (BI-RADS categories alone, P < 0.001); the descriptor model performs similarly. When applied to the validation data, the inclusive model yields an AUC of 0.935; the descriptor model yields an AUC of 0.876 (P < 0.001). Again, the inclusive model is superior to the clinical performance (P < 0.001); the descriptor model performs similarly. We consider our classifier a step towards a more uniform interpretation of combinations of BI-RADS descriptors. We provide our classifier at www.ebm-radiology.com/nbmm/index.html. (orig.)
Sørup, Christian Michel; Jacobsen, Peter
The purpose of this study is to first create an overview of relevant factors directly influencing employee absence in the healthcare sector. The overview is used to further investigate the factors identified using employee satisfaction survey scores exclusively. The result of the overall objective is a management framework that allows managers to gain insight into the current status of risk factors with high influence on employee absence levels. The research consists of a quantitative literature study supported by formal and semi-formal interviews conducted at the case organisations. Employee satisfaction surveys were applied to analyse the development over time of selected factors correlated with concurrent employee absence rates. Checking for causal results, comparisons with the included published literature findings were also carried out. Four major clustered factors, three of which constitute the term "social capital", showed a high degree of connection with employee absence rates. The factors are general satisfaction, fairness, reliance and co-operation. Integrating the four elements in a management framework will provide valuable and holistic information about the determinants with regard to current levels of employee absence. The framework will be a valuable support for leaders with the authority to alter the determinants of employee absence. Since a great part of the empirical material is supplied from the healthcare sector, the results obtained could be restricted to this sector. Inclusion of data from Arbejdsmarkedets Tillaegspension (ATP) showed no deviation from the results in the healthcare sector. The product of the study is a decision support tool for leaders to cope with levels of employee absence. The framework is holistic and can prove to be a valuable tool to take a bearing of where to focus future initiatives. Gathering former observational studies in a complete overview embracing many relevant factors that influence sickness absence has not yet
Franklin, Amy; Gantela, Swaroop; Shifarraw, Salsawit; Johnson, Todd R; Robinson, David J; King, Brent R; Mehta, Amit M; Maddow, Charles L; Hoot, Nathan R; Nguyen, Vickie; Rubio, Adriana; Zhang, Jiajie; Okafor, Nnaemeka G
Providing timely and effective care in the emergency department (ED) requires the management of individual patients as well as the flow and demands of the entire department. Strategic changes to work processes, such as adding a flow coordination nurse or a physician in triage, have demonstrated improvements in throughput times. However, such global strategic changes do not address the real-time, often opportunistic workflow decisions of individual clinicians in the ED. We believe that real-time representation of the status of the entire emergency department and each patient within it through information visualizations will better support clinical decision-making in-the-moment and provide for rapid intervention to improve ED flow. This notion is based on previous work where we found that clinicians' workflow decisions were often based on an in-the-moment local perspective, rather than a global perspective. Here, we discuss the challenges of designing and implementing visualizations for ED through a discussion of the development of our prototype Throughput Dashboard and the potential it holds for supporting real-time decision-making. Copyright © 2017. Published by Elsevier Inc.
Liu, Brent J.; Winstein, Carolee; Wang, Ximing; Konersman, Matt; Martinez, Clarisa; Schweighofer, Nicolas
Stroke is one of the major causes of death and disability in America. After stroke, about 65% of survivors still suffer from severe paresis, while rehabilitation treatment strategy after stroke plays an essential role in recovery. Currently, there is a clinical trial (NIH award #HD065438) to determine the optimal dose of rehabilitation for persistent recovery of arm and hand paresis. For DOSE (Dose Optimization Stroke Evaluation), laboratory-based measurements, such as the Wolf Motor Function test, behavioral questionnaires (e.g. Motor Activity Log-MAL), and MR, DTI, and Transcranial Magnetic Stimulation (TMS) imaging studies are planned. Current data collection processes are tedious and reside in various standalone systems including hardcopy forms. In order to improve the efficiency of this clinical trial and facilitate decision support, a web-based imaging informatics system has been implemented together with utilizing mobile devices (eg, iPAD, tablet PC's, laptops) for collecting input data and integrating all multi-media data into a single system. The system aims to provide clinical imaging informatics management and a platform to develop tools to predict the treatment effect based on the imaging studies and the treatment dosage with mathematical models. Since there is a large amount of information to be recorded within the DOSE project, the system provides clinical data entry through mobile device applications thus allowing users to collect data at the point of patient interaction without typing into a desktop computer, which is inconvenient. Imaging analysis tools will also be developed for structural MRI, DTI, and TMS imaging studies that will be integrated within the system and correlated with the clinical and behavioral data. This system provides a research platform for future development of mathematical models to evaluate the differences between prediction and reality and thus improve and refine the models rapidly and efficiently.
Hudspeth, W. B.; Budge, A.
There is widespread recognition within the public health community that ongoing changes in climate are expected to increasingly pose threats to human health. Environmentally induced health risks to populations with respiratory illnesses are a growing concern globally. Of particular concern are dust and smoke events carrying PM2.5 and PM10 particle sizes, ozone, and pollen. There is considerable interest in documenting the precise linkages between changing patterns in the climate and how these shifts impact the prevalence of respiratory illnesses. The establishment of these linkages can drive the development of early warning and forecasting systems to alert health care professionals of impending air-quality events. As a component of a larger NASA-funded project on Integration of Airborne Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems, the Earth Data Analysis Center (EDAC) at the University of New Mexico, is developing web-based visualization and analysis services for forecasting pollen concentration data. This decision-support system, New Mexico's Environmental Public Health Tracking System (NMEPHTS), funded by the Centers for Disease Control (CDC) Environmental Public Health Tracking Network (EPHTN), aims to improve health awareness and services by linking health effects data with levels and frequency of environmental exposure. The forecast of atmospheric events with high pollen concentrations has employed a modified version of the DREAM (Dust Regional Atmospheric Model, a verified model for atmospheric dust transport modeling. In this application, PREAM (Pollen Regional Atmospheric Model) models pollen emission using a MODIS-derived phenology of Juniperus spp. communities. Model outputs are verified and validated with ground-based records of pollen release timing and quantities. Outputs of the PREAM model are post-processed and archived in EDAC's Geographic Storage, Transformation, and
Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F
Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.
H. Michael Rauscher
The basic concept of sustainable development, formulated in the Brundtland report and applied to forest management by the Montreal Process, has focused attention on the need for formal decision processes (Brundtland. 1987). The application of decision theory is essential because meeting the needs of the present without compromising the ability of future generations to...
Groot, E.H. de; Mallory, S.M.; Zutphen, R.H.M. van; Vries, B. de
The design of buildings is a complex task for a variety of reasons. In the conceptual stage, particularly in the inception phase, a small number of people make decisions that have far reaching impact on the final result in terms of efficiency and effectiveness. Decision-making in the inception phase
Papaioannou, Alexandra; Kennedy, Courtney C; Campbell, Glenda; Stroud, Jacqueline B; Wang, Luqi; Dolovich, Lisa; Crowther, Mark A
Previous studies in long-term care (LTC) have demonstrated that warfarin management is suboptimal with preventable adverse events often occurring as a result of poor International Normalized Ratio (INR) control. To assist LTC teams with the challenge of maintaining residents on warfarin in the therapeutic range (INR of 2.0 to 3.0), we developed an electronic decision support system that was based on a validated algorithm for warfarin dosing. We evaluated the MEDeINR system in a pre-post implementation design by examining the impact on INR control, testing frequency, and experiences of staff in using the system. For this feasibility study, we piloted the MEDeINR system in six LTC homes in Ontario, Canada. All128 residents (without a prosthetic valve) who were taking warfarin were included. Three-months of INR data prior to MEDeINR was collected via a retrospective chart audit, and three-months of INR data after implementation of MEDeINR was captured in the central computer database. The primary outcomes compared in a pre-post design were time in therapeutic range (TTR) and time in sub/supratherapeutic ranges based on all INR measures for every resident on warfarin. Secondary measures included the number of monthly INR tests/resident and survey/focus-group feedback from the LTC teams. LTC homes in our study had TTR's that were higher than past reports prior to the intervention. Overall, the TTR increased during the MEDeINR phase (65 to 69%), but was only significantly increased for one home (62% to 71%, p management and decisions, and was generally easy to use. Although LTC homes in our sample had TTR's that were relatively high prior to the intervention, the MEDeINR program represented a useful tool to promote optimal TTR, decrease INR venipunctures, streamline processes, and increase nurse and physician confidence around warfarin management. We have demonstrated that MEDeINR was a practical, usable clinical information system that can be incorporated into the LTC
Kart, Özge; Mevsim, Vildan; Kut, Alp; Yürek, İsmail; Altın, Ayşe Özge; Yılmaz, Oğuz
Background Physicians’ guideline use rates for diagnosis, treatment and monitoring of diabetes mellitus (DM) is very low. Time constraints, patient overpopulation, and complex guidelines require alternative solutions for real time patient monitoring. Rapidly evolving e-health technology combined with clinical decision support and monitoring systems (CDSMS) provides an effective solution to these problems. The purpose of the study is to develop a user-friendly, comprehensive, fully integrated ...
Fabio Diniz de Souza
Full Text Available Objective: To explore some possibilities of computer applications in medicine, and to discuss an online infertility clinical decision support system. Methods: Retrospective data were obtained from 52 couples, and then entered into the online tool. Both its results and the initial diagnoses obtained by the treating physicians were compared with the final diagnoses established by laparoscopy and other diagnostic tests (semen analysis, hormone analysis, endometrial biopsy, ultrasound and hysteroscopy. The initial hypothesis of the research was that the online tool’s output was statistically associated with the final diagnoses. In order to verify that hypothesis, a chi-square (氈2 test with Yates’ correction for continuity (P<0.05 was performed to verify if the online tool’s and the doctor’s diagnoses were statistically associated with the final diagnoses. Results: Four etiological factors were present in more than 50% of the couples (ovarian, tubal-peritoneal, uterine, and endometriosis. The statistical results confirmed the research hypothesis for eight out of the nine etiological factors (ovarian, tubal-peritoneal, uterine, cervical, male, vaginal, psychosomatic, and endometriosis; P<0.05. Since there were no cases related to the immune factor in the sample, further clinical data are necessary in order to assess the online tool’s performance for that factor. Conclusions: The online tool tends to present more false-positives than false negatives, whereas the expert physician tends to present more false-negatives than false-positives. Therefore, the online tool and the doctor seem to complement each other. Finally, the obtained results suggest that the infertility online tool discussed herein might be a useful research and instructional tool.
Mørland, Berit; Ringard, Anen; Røttingen, John-Arne
We describe, in general, the principles used in priority setting and, in particular, policy processes and decision making in Norway. A newly established council for setting priorities in health care is presented to illustrate how health technology assessments (HTAs) can support national advisors in complex priority-setting processes. Setting priorities in health care is a complex task. Careful thinking is, therefore, required in determining the components of a system for priority-setting. Based on recent Norwegian experiences, we believe that the following generic parts may provide some of the solution: a common set of values; an organizational structure made up of key stakeholders; supporting mechanisms in the form of HTA organizations and documented best evidence; and loyalty to decisions by stakeholders responsible for implementing national policies.
Lajic, Zoran; Nielsen, Ulrik Dam
In this paper a basic idea of a fault-tolerant monitoring and decision support system will be explained. Fault detection is an important part of the fault-tolerant design for in-service monitoring and decision support systems for ships. In the paper, a virtual example of fault detection...... will be presented for a containership with a real decision support system onboard. All possible faults can be simulated and detected using residuals and the generalized likelihood ratio (GLR) algorithm....
Elwyn, G.; O'Connor, A.M.; Bennett, C.; Newcombe, R.G.; Politi, M.; Durand, M.A.; Drake, E.; Joseph-Williams, N.; Khangura, S.; Saarimaki, A.; Sivell, S.; Stiel, M.; Bernstein, S.J.; Col, N.; Coulter, A.; Eden, K.; Harter, M.; Rovner, M.H.; Moumjid, N.; Stacey, D.; Thomson, R.; Whelan, T.; Weijden, G.D.E.M. van der; Edwards, A.
OBJECTIVES: To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids). DESIGN: Scale development study, involving construct, item and scale development, validation and reliability testing.
Bivainis, Juozas; Jansevičiūtė, Daina; Dieninis, Jonas
This paper examines the problem of supplier selection. The supplier selection process has been expressed as decision cycle, which involves such phases: searching for suppliers, preliminary selection, complex evaluation, negotiations, preparing a contract, monitoring. The present situation in this field has been described in such a way: large interest to increase validity of decisions for supplier selection from side of business practice, diversity of methods and models for supplier selection ...
SelectCare is a computerized decision support system for psychotherapists who decide how to treat their depressed patients. This paper descibes the decision making model that is implemented in SelectCare and the decision elements it uses to give advice to its users. The system itself is then
Donald Nute; Geneho Kim; Walter D. Potter; Mark J. Twery; H. Michael Rauscher; Scott Thomasma; Deborah Bennett; Peter Kollasch
We describe a research project that has as its goal development of a full-featured decision support system for managing forested land to satisfy multiple criteria represented as timber, wildlife, water, ecological, and wildlife objectives. The decision process proposed for what was originally conceived of as a Northeast Decision Model (NED) includes data acquisition,...
Rojas-Palma, C.; Madsen, H.; Gering, F.
. The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based on Kalman...... filters, are under development for several modules of the RODOS system, including the atmospheric dispersion, deposition, food chain and hydrological models. The use of such a generic data assimilation methodology enables the propagation of uncertainties throughout the various modules of the system....... This would in turn provide decision makers with uncertainty estimates taking into account both model and observation errors. This paper describes the methodology employed as well as results of some preliminary studies based on simulated data....
Natasha A Loghmanpour
Full Text Available This study investigated the use of Bayesian Networks (BNs for left ventricular assist device (LVAD therapy; a treatment for end-stage heart failure that has been steadily growing in popularity over the past decade. Despite this growth, the number of LVAD implants performed annually remains a small fraction of the estimated population of patients who might benefit from this treatment. We believe that this demonstrates a need for an accurate stratification tool that can help identify LVAD candidates at the most appropriate point in the course of their disease. We derived BNs to predict mortality at five endpoints utilizing the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS database: containing over 12,000 total enrolled patients from 153 hospital sites, collected since 2006 to the present day, and consisting of approximately 230 pre-implant clinical variables. Synthetic minority oversampling technique (SMOTE was employed to address the uneven proportion of patients with negative outcomes and to improve the performance of the models. The resulting accuracy and area under the ROC curve (% for predicted mortality were 30 day: 94.9 and 92.5; 90 day: 84.2 and 73.9; 6 month: 78.2 and 70.6; 1 year: 73.1 and 70.6; and 2 years: 71.4 and 70.8. To foster the translation of these models to clinical practice, they have been incorporated into a web-based application, the Cardiac Health Risk Stratification System (CHRiSS. As clinical experience with LVAD therapy continues to grow, and additional data is collected, we aim to continually update these BN models to improve their accuracy and maintain their relevance. Ongoing work also aims to extend the BN models to predict the risk of adverse events post-LVAD implant as additional factors for consideration in decision making.
Breznik, B.; Kusar, A.; Boznar, M.Z.; Mlakar, P.
Local decision support system has been developed based on the needs of Krsko Nuclear Power Plant for quick dose projection and it is one of important features required for proposal of intervention before actual release may occur. Radiological emergency assessment in the case of nuclear accident is based on plant status analysis, radiation monitoring data and on prediction of release of radioactive sources to the environment. There are possibilities to use automatic features to predict release source term and manual options for selection of release parameters. Advanced environmental modelling is used for assessment of atmospheric dispersion of radioactive contamination in the environment. (author)
National Aeronautics and Space Administration — GRID has had a successfully completed Phase I 'Mobile Online Intelligent Decision Support System' (MOIDSS). The system developed into a total solution that supports...
Schnabel, William; Brumbelow, Kelly
The objective of this project was to enhance the water resource decision-making process with respect to oil and gas exploration/production activities on Alaska’s North Slope. To this end, a web-based software tool was developed to allow stakeholders to assemble, evaluate, and communicate relevant information between and amongst themselves. The software, termed North Slope Decision Support System (NSDSS), is a visually-referenced database that provides a platform for running complex natural system, planning, and optimization models. The NSDSS design was based upon community input garnered during a series of stakeholder workshops, and the end product software is freely available to all stakeholders via the project website. The tool now resides on servers hosted by the UAF Water and Environmental Research Center, and will remain accessible and free-of-charge for all interested stakeholders. The development of the tool fostered new advances in the area of data evaluation and decision support technologies, and the finished product is envisioned to enhance water resource planning activities on Alaska’s North Slope.
Wei Yanhui; Su Desong; Chen Weihua; Zhang Jianbo
The article first reviewed three operation support systems currently used in NPP: real-time information surveillance system, important equipment surveillance system and plant process control and monitoring system, then presents the structure and function of three expert support sub-systems (intelligent alarm monitoring system, computer-based operating procedure support system, safety information expert decision support system). Finally the article discussed the meaning of a kind of operation decision making support system. (authors)
Melnick, Edward R; Hess, Erik P; Guo, George; Breslin, Maggie; Lopez, Kevin; Pavlo, Anthony J; Abujarad, Fuad; Powsner, Seth M; Post, Lori A
The Canadian Computed Tomography (CT) Head Rule, a clinical decision rule designed to safely reduce imaging in minor head injury, has been rigorously validated and implemented, and yet expected decreases in CT were unsuccessful. Recent work has identified empathic care as a key component in decreasing CT overuse. Health information technology can hinder the clinician-patient relationship. Patient-centered decision tools to support the clinician-patient relationship are needed to promote evidence-based decisions. Our objective is to formatively evaluate an electronic tool that not only helps clinicians at the bedside to determine the need for CT use based on the Canadian CT Head Rule but also promotes evidence-based conversations between patients and clinicians regarding patient-specific risk and patients' specific concerns. User-centered design with practice-based and participatory decision aid development was used to design, develop, and evaluate patient-centered decision support regarding CT use in minor head injury in the emergency department. User experience and user interface (UX/UI) development involved successive iterations with incremental refinement in 4 phases: (1) initial prototype development, (2) usability assessment, (3) field testing, and (4) beta testing. This qualitative approach involved input from patients, emergency care clinicians, health services researchers, designers, and clinical informaticists at every stage. The Concussion or Brain Bleed app is the product of 16 successive iterative revisions in accordance with UX/UI industry design standards. This useful and usable final product integrates clinical decision support with a patient decision aid. It promotes shared use by emergency clinicians and patients at the point of care within the emergency department context. This tablet computer app facilitates evidence-based conversations regarding CT in minor head injury. It is adaptable to individual clinician practice styles. The resultant tool
Dolecheck, K A; Heersche, G; Bewley, J M
Assessing the economic implications of investing in automated estrus detection (AED) technologies can be overwhelming for dairy producers. The objectives of this study were to develop new regression equations for estimating the cost per day open (DO) and to apply the results to create a user-friendly, partial budget, decision support tool for investment analysis of AED technologies. In the resulting decision support tool, the end user can adjust herd-specific inputs regarding general management, current reproductive management strategies, and the proposed AED system. Outputs include expected DO, reproductive cull rate, net present value, and payback period for the proposed AED system. Utility of the decision support tool was demonstrated with an example dairy herd created using data from DairyMetrics (Dairy Records Management Systems, Raleigh, NC), Food and Agricultural Policy Research Institute (Columbia, MO), and published literature. Resulting herd size, rolling herd average milk production, milk price, and feed cost were 323 cows, 10,758kg, $0.41/kg, and $0.20/kg of dry matter, respectively. Automated estrus detection technologies with 2 levels of initial system cost (low: $5,000 vs. high: $10,000), tag price (low: $50 vs. high: $100), and estrus detection rate (low: 60% vs. high: 80%) were compared over a 7-yr investment period. Four scenarios were considered in a demonstration of the investment analysis tool: (1) a herd using 100% visual observation for estrus detection before adopting 100% AED, (2) a herd using 100% visual observation before adopting 75% AED and 25% visual observation, (3) a herd using 100% timed artificial insemination (TAI) before adopting 100% AED, and (4) a herd using 100% TAI before adopting 75% AED and 25% TAI. Net present value in scenarios 1 and 2 was always positive, indicating a positive investment situation. Net present value in scenarios 3 and 4 was always positive in combinations using a $50 tag price, and in scenario 4, the $5
The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating
The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating
Cummings, Mary L.
When the human element is introduced into decision support system design, entirely new layers of social and ethical issues emerge but are not always recognized as such. This paper discusses those ethical and social impact issues specific to decision support systems and highlights areas that interface designers should consider during design with an…
Kalina, Jan; Zvárová, Jana
Roč. 5, č. 1 (2017), s. 21-27 ISSN 1805-8698 R&D Projects: GA ČR GA17-01251S Institutional support: RVO:67985807 Keywords : decision support systems * decision rules * statistical analysis * nonparametric regression Subject RIV: IN - Informatics, Computer Science OBOR OECD: Statistics and probability
Aerts, J.C.J.H.; Clarke, L.A.; Keuper, A.D.
Many land allocation issues, such as land-use planning, require input from extensive spatial databases and involve complex decision-making. Spatial decision support systems (SDSS) are designed to make these issues more transparent and to support the design and evaluation of land allocation
This paper aims to develop a strategic decision support system for logistics and supply chain network design of a multi-stage, ... strategic decision support model in achieving better utilization of network and resources to fulfil the customer demand is demonstrated ..... planning and multi-period pricing. Transp. Res. E: Logist.
Nannings, Barry; Abu-Hanna, A.
Decision support telemedicine systems (DSTSs) are systems combining elements from telemedicine and clinical decision support systems. Although emerging more, these types of systems have not been given much attention in the literature. Our objective is to define the term DSTS, to propose a general
Puig, Daniel; Aparcana Robles, Sandra Roxana
options) against a particular evaluation criterion or set of criteria. Most often decision-support tools are applied with the help of purpose-designed software packages and drawing on specialised databases.The evaluation criteria alluded to above define and characterise each decision-support tool...
Auberger, Elise; Gély, Jean-Pierre; De Wever, Patrick; Merle, Didier
thus serving as a decision support-tool for government members, territorial administrations and non-profit organisations in the creation of projects of protection and promotion of the geoheritage. This methodology will represent a reference for the management of the geological heritage in urban and peri-urban contexts.
Full Text Available Background. Pharmacogenomic testing has the potential to improve the safety and efficacy of pharmacotherapy, but clinical application of pharmacogenetic knowledge has remained uncommon. Clinical Decision Support (CDS systems could help overcome some of the barriers to clinical implementation. The aim of this study was to evaluate the perception and usability of a web- and mobile-enabled CDS system for pharmacogenetics-guided drug therapy–the Medication Safety Code (MSC system–among potential users (i.e., physicians and pharmacists. Furthermore, this study sought to collect data on the practicability and comprehensibility of potential layouts of a proposed personalized pocket card that is intended to not only contain the machine-readable data for use with the MSC system but also human-readable data on the patient’s pharmacogenomic profile. Methods. We deployed an emergent mixed methods design encompassing (1 qualitative interviews with pharmacists and pharmacy students, (2 a survey among pharmacogenomics experts that included both qualitative and quantitative elements and (3 a quantitative survey among physicians and pharmacists. The interviews followed a semi-structured guide including a hypothetical patient scenario that had to be solved by using the MSC system. The survey among pharmacogenomics experts focused on what information should be printed on the card and how this information should be arranged. Furthermore, the MSC system was evaluated based on two hypothetical patient scenarios and four follow-up questions on the perceived usability. The second survey assessed physicians’ and pharmacists’ attitude towards the MSC system. Results. In total, 101 physicians, pharmacists and PGx experts coming from various relevant fields evaluated the MSC system. Overall, the reaction to the MSC system was positive across all investigated parameters and among all user groups. The majority of participants were able to solve the patient
Shropshire, David Earl; Jacobson, Jacob Jordan; Berrett, Sharon; Cobb, D. A.; Worhach, P.
The Demonstration of Decision Support Tools for Sustainable Development project integrated the Bechtel/Nexant Industrial Materials Exchange Planner and the Idaho National Engineering and Environmental Laboratory System Dynamic models, demonstrating their capabilities on alternative fuel applications in the Greater Yellowstone-Teton Park system. The combined model, called the Dynamic Industrial Material Exchange, was used on selected test cases in the Greater Yellow Teton Parks region to evaluate economic, environmental, and social implications of alternative fuel applications, and identifying primary and secondary industries. The test cases included looking at compressed natural gas applications in Teton National Park and Jackson, Wyoming, and studying ethanol use in Yellowstone National Park and gateway cities in Montana. With further development, the system could be used to assist decision-makers (local government, planners, vehicle purchasers, and fuel suppliers) in selecting alternative fuels, vehicles, and developing AF infrastructures. The system could become a regional AF market assessment tool that could help decision-makers understand the behavior of the AF market and conditions in which the market would grow. Based on this high level market assessment, investors and decision-makers would become more knowledgeable of the AF market opportunity before developing detailed plans and preparing financial analysis.
Full Text Available Long-term forest management planning often involves several stakeholders with conflicting objectives, creating a complex decision process. Multiple-criteria decision analysis (MCDA presents a promising framework for finding solutions in terms of suitable trade-offs among the objectives. However, many of the MCDA methods that have been implemented in forest management planning can only be used to compare and evaluate a limited number of management plans, which increases the risk that the most suitable plan is not included in the decision process. The aim of this study is to test whether the combination of two MCDA methods can facilitate the evaluation of a large number of strategic forest management plans in a situation with multiple objectives and several stakeholders. The Analytic Hierarchy Process (AHP was used to set weights for objectives based on stakeholder preferences and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS was used to produce an overall ranking of alternatives. This approach was applied to a case study of the Vilhelmina municipality, northern Sweden. The results show that the combination of AHP and TOPSIS is easy to implement in participatory forest planning and takes advantage of the capacity of forest decision support systems to create a wide array of management plans. This increases the possibility that the most suitable plan for all stakeholders will be identified.
Erskine, Michael A.
As many consumer and business decision makers are utilizing Spatial Decision Support Systems (SDSS), a thorough understanding of how such decisions are made is crucial for the information systems domain. This dissertation presents six chapters encompassing a comprehensive analysis of the impact of geospatial reasoning ability on…
A software system called the Waste Flow Analysis has been developed and applied to complex environmental management processes for the United States Department of Energy (US DOE). The system can evaluate proposed methods of waste retrieval, treatment, storage, transportation, and disposal. Analysts can evaluate various scenarios to see the impacts to waste slows and schedules, costs, and health and safety risks. Decision analysis capabilities have been integrated into the system to help identify preferred alternatives based on a specific objectives may be to maximize the waste moved to final disposition during a given time period, minimize health risks, minimize costs, or combinations of objectives. The decision analysis capabilities can support evaluation of large and complex problems rapidly, and under conditions of variable uncertainty. The system is being used to evaluate environmental management strategies to safely disposition wastes in the next ten years and reduce the environmental legacy resulting from nuclear material production over the past forty years
Full Text Available Control over the company, an objective that any manager wants, can only be exercised on the basis of real and complex business data. For this, a higher level of application is required, with Business Intelligence applications that provide information that no one else can offer faster. Winning time can be used to identify other issues related to available information or activities that add value to the company. After all, management time is a decision, and the decision is valuable only if it occurs at the right time. In this article I presented the benefits of implementing a business intelligence solution in a company, as well as how to design analytical reports using the QlikView application.
Sakellarios, Antonis I; Rigas, George; Kigka, Vassiliki; Siogkas, Panagiotis; Tsompou, Panagiota; Karanasiou, Georgia; Exarchos, Themis; Andrikos, Ioannis; Tachos, Nikolaos; Pelosi, Gualtriero; Parodi, Oberdan; Fotiaids, Dimitrios I
SMARTool aims to the development of a clinical decision support system (CDSS) for the management and stratification of patients with coronary artery disease (CAD). This will be achieved by performing computational modeling of the main processes of atherosclerotic plaque growth. More specifically, computed tomography coronary angiography (CTCA) is acquired and 3-dimensional (3D) reconstruction is performed for the arterial trees. Then, blood flow and plaque growth modeling is employed simulating the major processes of atherosclerosis, such as the estimation of endothelial shear stress (ESS), the lipids transportation, low density lipoprotein (LDL) oxidation, macrophages migration and plaque development. The plaque growth model integrates information from genetic and biological data of the patients. The SMARTool system enables also the calculation of the virtual functional assessment index (vFAI), an index equivalent to the invasively measured fractional flow reserve (FFR), to provide decision support for patients with stenosed arteries. Finally, it integrates modeling of stent deployment. In this work preliminary results are presented. More specifically, the reconstruction methodology has mean value of Dice Coefficient and Hausdorff Distance is 0.749 and 1.746, respectively, while low ESS and high LDL concentration can predict plaque progression.
Chirk Jenn Ng
Full Text Available Patient decision aids (PDAs help to support patients in making an informed and value-based decision. Despite advancement in decision support technologies over the past 30 years, most PDAs are still inaccessible and few address individual needs. Health innovation may provide a solution to bridge these gaps. Information and computer technology provide a platform to incorporate individual profiles and needs into PDAs, making the decision support more personalised. Health innovation may enhance accessibility by using mobile, tablet and Internet technologies; make risk communication more interactive; and identify patient values more effectively. In addition, using databases to capture patient data and the usage of PDAs can help: developers to improve PDAs’ design; clinicians to facilitate the decisionmaking process more effectively; and policy makers to make shared decision making more feasible and cost-effective. Health innovation may hold the key to advancing PDAs by creating a more personalised and effective decision support tool for patients making healthcare decisions.
This document proposes a streamlined approach and methodology for performing risk assessment in support of interim remedial measure (IRM) decisions involving the remediation of contaminated groundwater on the Hanford Site. This methodology, referred to as ''risk-based decision analysis,'' also supports the specification of target cleanup volumes and provides a basis for design and operation of the groundwater remedies. The risk-based decision analysis can be completed within a short time frame and concisely documented. The risk-based decision analysis is more versatile than the qualitative risk assessment (QRA), because it not only supports the need for IRMs, but also provides criteria for defining the success of the IRMs and provides the risk-basis for decisions on final remedies. For these reasons, it is proposed that, for groundwater operable units, the risk-based decision analysis should replace the more elaborate, costly, and time-consuming QRA
An, Sang Ha; Lee, Sung Jin; Chang, Soon Heung; Kim, Sung Ho; Kim, Tae Woon
Korea is meeting the growing electric power needs by using nuclear, fissile, hydro energy and so on. But we can not use fissile energy forever, and the people's consideration about nature has been changed. So we have to prepare appropriate energy by the conditions before people need more energy. And we should prepare dynamic response because people's need would be changed as the time goes on. So we designed graphic analysis model (GAM) for the dynamic analysis of decision on the energy sources. It can support Analytic Hierarchy Process (AHP) analysis based on Graphic User Interface
Kortteisto, Tiina; Komulainen, Jorma; Mäkelä, Marjukka
the use of computer-based clinical decision support (eCDS) in primary care and how different professional groups experience it. Our aim was to describe specific reasons for using or not using eCDS among primary care professionals. METHODS: The setting was a Finnish primary health care organization with 48...... professionals receiving patient-specific guidance at the point of care. Multiple data (focus groups, questionnaire and spontaneous feedback) were analyzed using deductive content analysis and descriptive statistics. RESULTS: The content of the guidance is a significant feature of the primary care professional...
A rule-based decision making model is designed in G2 environment. A theoretical and methodological frame for the model is composed and motivated. The rule-based decision making model is based on object-oriented modelling, knowledge engineering and decision theory. The idea of safety objective tree is utilized. Advanced rule-based methodologies are applied. A general decision making model 'decision element' is constructed. The strategy planning of the decision element is based on e.g. value theory and utility theory. A hypothetical process model is built to give input data for the decision element. The basic principle of the object model in decision making is division in tasks. Probability models are used in characterizing component availabilities. Bayes' theorem is used to recalculate the probability figures when new information is got. The model includes simple learning features to save the solution path. A decision analytic interpretation is given to the decision making process. (author)
Pinto, Tiago; Sousa, Tiago M.; Praça, Isabel
. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated...... by being included in ALBidS and then compared with the application of an Artificial Neural Network (ANN), originating promising results: an effective electricity market price forecast in a fast execution time. The proposed approach is tested and validated using real electricity markets data from MIBEL......׳ research group has developed a multi-agent system: Multi-Agent System for Competitive Electricity Markets (MASCEM), which simulates the electricity markets environment. MASCEM is integrated with Adaptive Learning Strategic Bidding System (ALBidS) that works as a decision support system for market players...
Carsjens, G.J.; Chen, W.
The main challenge of developing of a spatial DST (Decision Support Tool) to support the decision making on future livestock production will not be a technical one, but instead a challenge of meeting the con-text requirements of the tool, such as the characteristics of the country-specific spatial
Nergård, Henrik; Sandberg, Marcus; Larsson, Tobias
In this paper a decision support tool with the focus on how to generate and visualize decision base coupled to the business agreement is outlined and discussed. Decision support tools for the early design phases are few and especially tools that visualize the readiness level of activities throughout the product life-cycle. Aiming for the sustainable society there is an indication that business-to-business manufacturers move toward providing a function rather than selling off the hardware and ...
The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.
Wang, Wenchao; Cui, Yuanlai
Irrigation has played an important role in agricultural production. Irrigation decision support system is developed for irrigation water management, which can raise irrigation efficiency with few added engineering services. An online irrigation decision support system (OIDSS), in consist of in-field sensors and central computer system, is designed for surface irrigation management in large irrigation district. Many functions have acquired in OIDSS, such as data acquisition and detection, real-time irrigation forecast, water allocation decision and irrigation information management. The OIDSS contains four parts: Data acquisition terminals, Web server, Client browser and Communication system. Data acquisition terminals are designed to measure paddy water level, soil water content in dry land, ponds water level, underground water level, and canals water level. A web server is responsible for collecting meteorological data, weather forecast data, the real-time field data, and manager's feedback data. Water allocation decisions are made in the web server. Client browser is responsible for friendly displaying, interacting with managers, and collecting managers' irrigation intention. Communication system includes internet and the GPRS network used by monitoring stations. The OIDSS's model is based on water balance approach for both lowland paddy and upland crops. Considering basic database of different crops water demands in the whole growth stages and irrigation system engineering information, the OIDSS can make efficient decision of water allocation with the help of real-time field water detection and weather forecast. This system uses technical methods to reduce requirements of user's specialized knowledge and can also take user's managerial experience into account. As the system is developed by the Browser/Server model, it is possible to make full use of the internet resources, to facilitate users at any place where internet exists. The OIDSS has been applied in
Nair, U. S.; Keiser, K.; Wu, Y.; Kaulfus, A.; Srinivasan, K.; Anderson, E. R.; McEniry, M.
An Event-Driven Data delivery (ED3) framework has been created that provides reusable services and configurations to support better data preparedness for decision support of disasters and other events by rapidly providing pre-planned access to data, special processing, modeling and other capabilities, all executed in response to criteria-based events. ED3 facilitates decision makers to plan in advance of disasters and other types of events for the data necessary for decisions and response activities. A layer of services provided in the ED3 framework allows systems to support user definition of subscriptions for data plans that will be triggered when events matching specified criteria occur. Pre-planning for data in response to events lessens the burden on decision makers in the aftermath of an event and allows planners to think through the desired processing for specialized data products. Additionally the ED3 framework provides support for listening for event alerts and support for multiple workflow managers that provide data and processing functionality in response to events. Landslides are often costly and, at times, deadly disaster events. Whereas intense and/or sustained rainfall is often the primary trigger for landslides, soil type and slope are also important factors in determining the location and timing of slope failure. Accounting for the substantial spatial variability of these factors is one of the major difficulties when predicting the timing and location of slope failures. A wireless sensor network (WSN), developed by NASA SERVIR and USRA, with peer-to-peer communication capability and low power consumption, is ideal for high spatial in situ monitoring in remote locations. In collaboration with the University of Huntsville at Alabama, WSN equipped with accelerometer, rainfall and soil moisture sensors is being integrated into an end-to-end landslide warning system. The WSN is being tested to ascertain communication capabilities and the density of
). The thesis balances between the use of IT tools to aid Humanities research and the understanding that Humanities research must involve human beings. It does not attempt to develop a system that can automate the reading of ancient documents. Instead it seeks to demonstrate and develop tools that can support......The research presented in this thesis is based in the Humanities discipline of Ancient History and begins by attempting to understand the interpretation process involved in reading ancient documents and how this process can be aided by computer systems such as Decision Support Systems (DSS...... this process in the five areas: remembering complex reasoning, searching huge datasets, international collaboration, publishing editions, and image enhancement. This research contains a large practical element involving the development of a DSS prototype. The prototype is used to illustrate how a DSS...
Havelaar, A.H.; Bräunig, J.; Christiansen, K.; Cornu, M.; Hald, T.; Mangen, M.J.J.; Molbak, K.; Pielaat, A.; Snary, E.; Pelt, van W.; Velthuis, A.G.J.; Wahlström, H.
Decisions on food safety involve consideration of a wide range of concerns including the public health impact of foodborne illness, the economic importance of the agricultural sector and the food industry, and the effectiveness and efficiency of interventions. To support such decisions, we propose
Tseng, Chiu-Che; Gmytrasiewicz, Piotr J.
The challenge of the investment domain is that a large amount of diverse information can be potentially relevant to an investment decision, and that, frequently, the decisions have to be made in a timely manner. This presents the potential for better decision support, but poses the challenge of building a decision support agent that gathers information from different sources and incorporates it for timely decision support. These problems motivate us to investigate ways in which the investors can be equipped with a flexible real-time decision support system to be practical in time-critical situations. The flexible real-time decision support system considers a tradeoff between decision quality and computation cost. For this purpose, we propose a system that uses the object oriented Bayesian knowledge base (OOBKB) design to create a decision model at the most suitable level of detail to guide the information gathering activities, and to produce an investment recommendation within a reasonable length of time. The decision models our system uses are implemented as influence diagrams. We validate our system with experiments in a simplified investment domain. The experiments show that our system produces a quality recommendation under different urgency situations. The contribution of our system is that it provides the flexible decision recommendation for an investor under time constraints in a complex environment.
van Essen, J Theresia; Hurink, Johann L; Hartholt, Woutske; van den Akker, Bernd J
Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.
Chrimes, Dillon; Kitos, Nicole R; Kushniruk, Andre; Mann, Devin M
Usability testing can be used to evaluate human-computer interaction (HCI) and communication in shared decision making (SDM) for patient-provider behavioral change and behavioral contracting. Traditional evaluations of usability using scripted or mock patient scenarios with think-aloud protocol analysis provide a way to identify HCI issues. In this paper we describe the application of these methods in the evaluation of the Avoiding Diabetes Thru Action Plan Targeting (ADAPT) tool, and test the usability of the tool to support the ADAPT framework for integrated care counseling of pre-diabetes. The think-aloud protocol analysis typically does not provide an assessment of how patient-provider interactions are effected in "live" clinical workflow or whether a tool is successful. Therefore, "Near-live" clinical simulations involving applied simulation methods were used to compliment the think-aloud results. This complementary usability technique was used to test the end-user HCI and tool performance by more closely mimicking the clinical workflow and capturing interaction sequences along with assessing the functionality of computer module prototypes on clinician workflow. We expected this method to further complement and provide different usability findings as compared to think-aloud analysis. Together, this mixed method evaluation provided comprehensive and realistic feedback for iterative refinement of the ADAPT system prior to implementation. The study employed two phases of testing of a new interactive ADAPT tool that embedded an evidence-based shared goal setting component into primary care workflow for dealing with pre-diabetes counseling within a commercial physician office electronic health record (EHR). Phase I applied usability testing that involved "think-aloud" protocol analysis of eight primary care providers interacting with several scripted clinical scenarios. Phase II used "near-live" clinical simulations of five providers interacting with standardized
Wierenga, B.; Oude Ophuis, P.A.M.
This paper deals with marketing decision support systems (MDSS) in companies. In a conceptual framework five categories of factors are distinguished that potentially affect adoption, use, and satisfaction: external environment factors, organizational factors, task environment factors, user factors
National Aeronautics and Space Administration — We propose to design a working prototype Geospatial Decision Support Toolkit (GeoKit) that will enable scientists, agencies, and stakeholders to configure and deploy...
lying properties. Existing decision support systems available in the field of water distribution system maintenance mainly focus on leak detection and pipe rehabilitation/replacement strategies. These existing systems, however, do not address the ...
B. Wierenga (Berend); P.A.M. Oude Ophuis (Peter)
textabstractThis paper deals with marketing decision support systems (MDSS) in companies. In a conceptual framework five categories of factors are distinguished that potentially affect adoption, use, and satisfaction: external environment factors, organizational factors, task environment factors,
National Aeronautics and Space Administration — We propose to build and commercialize a working prototype Geospatial Decision Support Toolkit (GeoKit). GeoKit will enable scientists, agencies, and stakeholders to...
Klemke, Roland; Börner, Dirk; Suarez, Angel; Schneider, Jan; Antonaci, Alessandra
This interactive workshop session introduces mobile serious games as situated, contextualized learning games. Example cases for mobile serious games for decision support training are introduced and discussed. Participants will get to know contextualization techniques used in modern mobile
This interactive workshop session introduces mobile serious games as situated, contextualized learning games. Example cases for mobile serious games for decision support training are introduced and discussed. Participants will get to know contextualization techniques used in modern mobile devices
Boukhanovsky, A.V.; Krzhizhanovskaya, V.V.; Bubak, M.
Urgent computing for decision support in critical situations requires a cutting-edge interdisciplinary research combining data-driven modelling, high-performance computing, advanced numerical simulation and visualization. Examples of critical situations arising in complex technical, environmental
This thesis focuses on developing a spreadsheet decision support model that can be used by combat engineer platoon and company commanders in determining the material requirements and estimated costs...
Elizabeth S. Burnside MD, MPH, MS
Full Text Available Background: There are no publicly available tools designed specifically to assist policy makers to make informed decisions about the optimal ages of breast cancer screening initiation for different populations of US women. Objective: To use three established simulation models to develop a web-based tool called Mammo OUTPuT. Methods: The simulation models use the 1970 US birth cohort and common parameters for incidence, digital screening performance, and treatment effects. Outcomes include breast cancers diagnosed, breast cancer deaths averted, breast cancer mortality reduction, false-positive mammograms, benign biopsies, and overdiagnosis. The Mammo OUTPuT tool displays these outcomes for combinations of age at screening initiation (every year from 40 to 49, annual versus biennial interval, lifetime versus 10-year horizon, and breast density, compared to waiting to start biennial screening at age 50 and continuing to 74. The tool was piloted by decision makers (n = 16 who completed surveys. Results: The tool demonstrates that benefits in the 40s increase linearly with earlier initiation age, without a specific threshold age. Likewise, the harms of screening increase monotonically with earlier ages of initiation in the 40s. The tool also shows users how the balance of benefits and harms varies with breast density. Surveys revealed that 100% of users (16/16 liked the appearance of the site; 94% (15/16 found the tool helpful; and 94% (15/16 would recommend the tool to a colleague. Conclusions: This tool synthesizes a representative subset of the most current CISNET (Cancer Intervention and Surveillance Modeling Network simulation model outcomes to provide policy makers with quantitative data on the benefits and harms of screening women in the 40s. Ultimate decisions will depend on program goals, the population served, and informed judgments about the weight of benefits and harms.
Knies, Saskia; Lombardi, Gloria; Commers, Matt; Dauben, Hans-Peter; Evers, Silvia; Michelsen, Kai; Oortwijn, Wija; Opara, Chibuzo; Brand, Helmut
The aim of this study was to develop an health technology assessment (HTA) decision tool to support the decision-making process on health technologies for hospital decision makers in cross-border regions. Several methods were used to collect information necessary to develop the cross-border mini-HTA decision tool. The literature was inventoried on HTA in border regions and local settings and the use of HTA by local decision makers. Semi-structured interviews with hospital decision makers in cross-border regions were also performed. Based on group discussion of the resulting information, it was decided to use the Danish mini-HTA guideline as a starting point for development of the decision tool. After finishing the first version of the decision tool it was tested in two pilot studies. Some questions in the Danish mini-HTA guideline were not relevant. Other questions needed rephrasing and questions about cross-border situations were added. The pilots showed several missing topics, including legal questions and reimbursement issues. The final decision tool consists of three sections: a general section, a section for hospitals not cooperating cross-border and a section for hospitals that are cooperating with hospitals across a national or regional border. Based on our literature search, this may be the first cross-border mini-HTA decision tool. The decision tool will be of help for healthcare professionals and decision makers in border settings who would like to use HTA evidence to support their decision-making process.
Horváth, Klaudia; van Esch, Bart; Baayen, Jorn; Pothof, Ivo; Talsma, Jan; van Heeringen, Klaas-Jan
Deltares and Eindhoven University of Technology are developing a new decision support system (DSS) for regional water authorities. In order to maintain water levels in the Dutch polder system, water should be drained and pumped out from the polders to the sea. The time and amount of pumping depends on the current sea level, the water level in the polder, the weather forecast and the electricity price forecast and possibly local renewable power production. This is a multivariable optimisation problem, where the goal is to keep the water level in the polder within certain bounds. By optimizing the operation of the pumps the energy usage and costs can be reduced, hence the operation of the regional water authorities can be more sustainable, while also anticipating on increasing share of renewables in the energy mix in a cost-effective way. The decision support system, based on Delft-FEWS as operational data-integration platform, is running an optimization model built in RTC-Tools 2, which is performing real-time optimization in order to calculate the pumping strategy. It is taking into account the present and future circumstances. As being the core of the real time decision support system, RTC-Tools 2 fulfils the key requirements to a DSS: it is fast, robust and always finds the optimal solution. These properties are associated with convex optimization. In such problems the global optimum can always be found. The challenge in the development is to maintain the convex formulation of all the non-linear components in the system, i.e. open channels, hydraulic structures, and pumps. The system is introduced through 4 pilot projects, one of which is a pilot of the Dutch Water Authority Rivierenland. This is a typical Dutch polder system: several polders are drained to the main water system, the Linge. The water from the Linge can be released to the main rivers that are subject to tidal fluctuations. In case of low tide, water can be released via the gates. In case of high
.... Architecture for a decision support system was then developed to provide the necessary automation support and a prototype for the user interface of the proposed system was constructed to evaluate the architectural design. The proposal software will improve the decision making ability of the leader of this organization and the heads of each department. It will make the routine tasks easier, and provide the necessary and accurate data in a timely manner.
Semioshkina, N.; Voigt, G.; Fiedler, I.
According to Wikipedia Radioecology is a branch of ecology, which studies how radioactive substances interact with nature; how different mechanisms affect the substances’ migration and uptake in food chains and ecosystems. Investigations in radioecology might include aspects of field sampling, designed field and laboratory experiments and the development of predictive simulation models. This science combines techniques from some of the more basic, traditional fields, such as physics, chemistry, mathematics, biology, and ecology, with applied concepts in radiation protection. Radioecological studies form the basis for estimating doses and assessing the consequences of radioactive pollution for human health and the environment. Significant economic and social disruptions arise after radioactive contamination of land as a result of releases of radioactivity into the environment be it from accidents, routine and war operations or during decommissioning and waste management of nuclear facilities. Measures carried out to reduce and minimise radiation doses to the public can give rise to even more concerns as often they are not understood and the stakeholders are often not involved into the decision making process. Countermeasures are needed to reduce population exposure, at the same time minimising economic and social costs. The effectiveness of countermeasures is not only highly dependent on factors which are connected to environmental transfer, but also to special behaviour and consumption behaviours in varying food production systems. A central aspect of radioecology is the identification of vulnerable areas which, by virtue of the processes governing the transfer of radiocaesium through food chains, deliver high individual, or collective doses to man. Social factors (e.g. dietary preferences) and agricultural production techniques also contribute to vulnerability. (author)
Verberne, C.J.; Nijboer, Cornelis H.; de Bock, G.H.; Grossmann, I.; Wiggers, T.; Havenga, K.
Background: The present paper is a first evaluation of the use of "CEAwatch", a clinical support software system for surgeons for the follow-up of colorectal cancer (CRC) patients. This system gathers Carcino-Embryonic Antigen (CEA) values and automatically returns a recommendation based on the
Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of
Full Text Available Abstract Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language process definition language (XPDL. The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent. We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We
Chalal, Rachid; National Institute of Computer Science; Nader, Fahima; National Institute of Computer Science
The paper proposes a generic approach to design and develop an Organizational Decision Support System (ODSS). This approach is based at the follows definition: the ODSS is considered as the experts' memory and their decision-taking. Therefore, the ODSS is constituted by two elements, a strategic DSS and a specific referential of the decision situation. Our generic approach for ODSS design is based on the MUSIC (Management and Use of Co-operative Information Systems) model. An illustration of ...
The listing of a species as endangered under the Endangered Species Act invokes a suite of responses to help improve conditions for the recovery of that species, to include identification of stressors contributing to population loss, decision analysis of the impacts of proposed recovery options, and implementation of optimal recovery measures. The ability of a decision support system to quantify inherent stressor uncertainties and to identify the key stressors that can be controlled or eliminated becomes key to ensuring the recovery of an endangered species. The listing of the Snake River sockeye, spring/summer chinook, and fall chinook salmon species in the Snake River as endangered provides a vivid example of the importance of sophisticated decision support systems. Operational and physical changes under consideration at eight of the hydroelectric dams along the Columbia and Lower Snake River pose significant financial impacts to a variety of stakeholders involved in the salmon population recovery process and carry significant uncertainties of outcome. A decision support system is presented to assist in the identification of optimal recovery actions for this example that includes the following: creation of datamarts of information on environmental, engineering, and ecological values that influence species survival; incorporation of decision analysis tools to determine optimal decision policies; and the use of geographic information systems (GIS) to provide a context for decision analysis and to communicate the impacts of decision policies
Full Text Available The Special Issue “Providing Ecosystem Services under Climate Change: Community of Practice of Forest Decision Support Systems” is based on the presentations given at the 24th World Congress of the International Union of Forest Research Organizations and provides an overview on Forest Management Decision Support Systems currently designed and applied for the sustained provision of ecosystem services within the context of climate change. The contributions provide an overview on models, methods, techniques used in decision support and the proposed frameworks to support decision making. With populations and economies growing worldwide, the demands on forest resources increase, and sustaining the supply of ecosystem services becomes crucial. Through growing public participation in decisions regarding the management of natural resources, new demands have emerged for tools that support our understanding of environmental issues, and for the development and evaluation of alternative management options; there is a desire to project the consequences of different courses of action. Decision Support Systems (DSS have been proven to solve such ill-structured decision problems by integrating database management systems with analytical and operational research models, thus providing various reporting capabilities. Several case studies focus on decision problems, the development and evaluation of alternative management options, and on projecting the consequences of different courses of action in the provision of ecosystem services. Conclusions on the state-of-the-art in decision support and the needed advances in research are drawn.
Full Text Available In this article we present the foundations of a decision support system for blockage management in Fire Service. Blockage refers to the situation when all fire units are out and a new incident occurs. The approach is based on two phases: off-line data preparation and online blockage estimation. The off-line phase consists of methods from data mining and natural language processing and results in semantically coherent information granules. The online phase is about building the probabilistic models that estimate the block-age probability based on these granules. Finally, the selected classifier judges whether a blockage can occur and whether the resources from neighbour fire stations should be asked for assistance.
Lin, Zhihang; Chen, Hang; Chen, Kuen; Che, Ada
This paper describes the work on the development of a group decision support system for customer driven product design. The customer driven is to develop products, which meet all customer requirements in whole life cycle of products. A process model of decision during product primary design is proposed to formulate the structured, semi-structured and unstructured decision problems. The framework for the decision support system is presented that integrated both advances in the group decision making and distributed artificial intelligent. The system consists of the product primary design tool kit and the collaborative platform with multi-agent structure. The collaborative platform of the system and the product primary design tool kit, including the VOC (Voice of Customer) tool, QFD (Quality Function Deployment) tool, the Conceptual design tool, Reliability analysis tool and the cost and profit forecasting tool, are indicated.
whilst safeguarding a transparent and informative decision making process. Through the PhD thesis spatial temporal issues regarding slurry biomass resource availability is analysed together with the aspects of spatial competition in order to achieve national biogas policy ambitions. We find that slurry......, understand the industrial economic aspects of such a role. Through the use of spatial multi-criteria evaluation models stakeholder preferences to decision criteria are included in a sustainable biogas facility location analysis. By the use of these models it is demonstrated how overall biogas production...... costs can be reduced by 3% while also environmental and social concerns are appreciated. Spatial decision support models offer great potential for enhancing transparency and qualifying the basis for decision making with regard to location of future biogas plant. The spatial decision support tools, which...
Full Text Available The first part of this text deals with a convention site selection as one of the most lucrative areas in the tourism industry. The second part gives a further description of a method for decision making - the analytic hierarchy process. The basic characteristics: hierarchy constructions and pair wise comparison on the given level of the hierarchy are allured. The third part offers an example of application. This example is solved using the Super - Decision software, which is developed as a computer support for the analytic hierarchy process. This indicates that the AHP approach is a useful tool to help support a decision of convention site selection. .
Full Text Available Data Driven Decision Support Systems are mature technologies whose effectiveness in business and management seem to be well established and uncontroversial. Under the circumstances of increased competition between universities in their attempt to better position themselves on the market of educational services, a Data Driven Decision Support System could become a powerful instrument meant to enhance all the decisions that target various aspects of the educational process. This paper is a case study conducted in a Romanian university, presenting the development of such a system, emphasizing the analytical capabilities related to student results at exams, as this topic is of interest for the users of the system.
Yang, Qian; Zimmerman, John; Steinfeld, Aaron; Carey, Lisa; Antaki, James F.
Clinical decision support tools (DSTs) are computational systems that aid healthcare decision-making. While effective in labs, almost all these systems failed when they moved into clinical practice. Healthcare researchers speculated it is most likely due to a lack of user-centered HCI considerations in the design of these systems. This paper describes a field study investigating how clinicians make a heart pump implant decision with a focus on how to best integrate an intelligent DST into their work process. Our findings reveal a lack of perceived need for and trust of machine intelligence, as well as many barriers to computer use at the point of clinical decision-making. These findings suggest an alternative perspective to the traditional use models, in which clinicians engage with DSTs at the point of making a decision. We identify situations across patients’ healthcare trajectories when decision supports would help, and we discuss new forms it might take in these situations. PMID:27833397
SULLIVAN, T.; BARDOS, P.
The emphasis of the session was on the use of decision support tools for actual remediation decisions. It considered two perspectives: site-specific decision making for example choosing a particular remediation system; and remediation in terms of a risk management/risk reduction process as part of a wider process of site management. These were addressed both as general topics and as case studies. Case studies were included to provide information on decision support techniques for specific contamination problems such as remedy selection. In the case studies, the authors present the general process to provide decision support and then discuss the application to a specific problem. The intent of this approach is to provide the interested reader with enough knowledge to determine if the process could be used on their specific set of problems. The general topics included broader issues that are not directly tied to a specific problem. The general topics included papers on the role of stakeholders in the decision process and decision support approaches for sustainable development
Grasso, Raffaele; Giannecchini, Simone
.... This paper describes a tactical decision aid system based on fuzzy logic reasoning for data fusion and on current Open Geospatial Consortium specifications for interoperability, data dissemination...
Groth, Julie Jespersen
Real-time recovery is receiving a fast growing interest in an increasingly competitive railway operation market. This thesis considers the area of rolling stock dispatching which is one of the typical real-time railway dispatching problems. All work of the thesis is based on the network...... and planning processes of the railway operator DSB S-tog a/s. In the thesis the problems existing in the railway planning process from the strategic to real-time level are briefly sketched. Network planning, line planning, timetabling, crew and rolling stock planning is outlined and relevant references...... are given. Specifically the thesis references the operation research studies based on the railway operation of DSB S-tog a/s. Subsequently the process of dispatching is outlined with a specific emphasis on rolling stock. The rolling stock recovery problem is the problem of assigning train units to train...
Tran, Cong; Jain, Lakhmi; Abraham, Ajith
Normally a decision support system is build to solve problem where multi-criteria decisions are involved. The knowledge base is the vital part of the decision support containing the information or data that is used in decision-making process. This is the field where engineers and scientists have applied several intelligent techniques and heuristics to obtain optimal decisions from imprecise information. In this paper, we present a hybrid neuro-genetic learning approach for the adaptation a Ma...
Gerven, M.A.J. van
This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesian networks are used as a framework for (dynamic) decision-making under uncertainty and applied to a variety of diagnostic, prognostic, and treatment problems in medicine. It is shown that the proposed
Gerven, M.A.J. van
This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesian networks are used as a framework for (dynamic) decision-making under uncertainty and applied to a variety of diagnostic, prognostic, and treatment problems in medicine. It is shown that the proposed models perform well in realistic settings
Biscarini, C.; di Francesco, S.; Manciola, P.
. In the present paper we propose a novel methodology for supporting the priority setting in the assessment of such issues, beyond the typical "expected value" approach. Scientific contribution and management aspects are merged to create a simplified method for plan basin implementation, based on risk and economic analyses. However, the economic evaluation is not the sole criterion for flood-damage reduction plan selection. Among the different criteria that are relevant to the decision process, safety and quality of human life, economic damage, expenses related with the chosen measures and environmental issues should play a fundamental role on the decisions made by the authorities. Some numerical indices, taking in account administrative, technical, economical and risk aspects, are defined and are combined together in a mathematical formula that defines a Priority Index (PI). In particular, the priority index defines a ranking of priority interventions, thus allowing the formulation of the investment plan. The research is mainly focused on the technical factors of risk assessment, providing quantitative and qualitative estimates of possible alternatives, containing measures of the risk associated with those alternatives. Moreover, the issues of risk management are analyzed, in particular with respect to the role of decision making in the presence of risk information. However, a great effort is devoted to make this index easy to be formulated and effective to allow a clear and transparent comparison between the alternatives. Summarizing this document describes a major- steps for incorporation of risk analysis into the decision making process: framing of the problem in terms of risk analysis, application of appropriate tools and techniques to obtain quantified results, use of the quantified results in the choice of structural and non-structural measures. In order to prove the reliability of the proposed methodology and to show how risk-based information can be
Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains information and analysis tools for all a...
The Waste Reduction Decision Support System (WAR DSS) is a Java-based software product providing comprehensive modeling of potential adverse environmental impacts (PEI) predicted to result from newly designed or redesigned chemical manufacturing processes. The purpose of this so...
Advanced management technique and Decision Support System (DSS) are needed to solve the problems of the nuclear reactor decommissioning decision-making. In this study, a kind of new DSS technique for nuclear reactor decommissioning is introduced. It is based on the Virtual Reality (VR) and Geography Information System (GIS), which combine with the scientific management method, operational research, cybernetics and behavior science. The proposed DDSS (Decommissioning Decision Support System) can provide decision-maker the real time 3-D virtual Environment, GIS information and background material of the decommissioning reactor, help to ascertain the decision-making target, modify the decision module and optimize the dismantling plan. The data from three modules (VR Environment Module, VR-DOSE Management Module and Route Layout GIS Module) are used to continuously update and show the statistic at the same time, and the final advice will be given to decision-maker. (authors)
Full Text Available Commercially available clinical decision support systems (CDSSs for skin cancer have been designed for the detection of melanoma only. Correct use of the systems requires expert knowledge, hampering their utility for nonexperts. Furthermore, there are no systems to detect other common skin cancer types, that is, nonmelanoma skin cancer (NMSC. As early diagnosis of skin cancer is essential, there is a need for a CDSS that is applicable to all types of skin lesions and is suitable for nonexperts. Nevus Doctor (ND is a CDSS being developed by the authors. We here investigate ND’s ability to detect both melanoma and NMSC and the opportunities for improvement. An independent test set of dermoscopic images of 870 skin lesions, including 44 melanomas and 101 NMSCs, were analysed by ND. Its sensitivity to melanoma and NMSC was compared to that of Mole Expert (ME, a commercially available CDSS, using the same set of lesions. ND and ME had similar sensitivity to melanoma. For ND at 95% melanoma sensitivity, the NMSC sensitivity was 100%, and the specificity was 12%. The melanomas misclassified by ND at 95% sensitivity were correctly classified by ME, and vice versa. ND is able to detect NMSC without sacrificing melanoma sensitivity.
Cresswell, Kathrin; Majeed, Azeem; Bates, David W; Sheikh, Aziz
Computerised decision support systems are designed to support clinicians in making decisions and thereby enhance the quality and safety of care. We aimed to undertake an interpretative review of the empirical evidence on computerised decision support systems, their contexts of use, and summarise evidence on the effectiveness of these tools and insights into how these can be successfully implemented and adopted. We systematically searched the empirical literature to identify systematic literature reviews on computerised decision support applications and their impact on the quality and safety of healthcare delivery over a 13-year period (1997-2010). The databases searched included: MEDLINE, EMBASE, The Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, The Cochrane Central Register of Controlled Trials, The Cochrane Methodology Register, The Health Technology Assessment Database, and The National Health Service (NHS) Economic Evaluation Database. To be eligible for inclusion, systematic reviews needed to address computerised decision support systems, and at least one of the following: impact on safety; quality; or organisational, implementation or adoption considerations. Our searches yielded 121 systematic reviews relating to eHealth, of which we identified 41 as investigating computerised decision support systems. These indicated that, whilst there was a lack of investigating potential risks, such tools can result in improvements in practitioner performance in the promotion of preventive care and guideline adherence, particularly if specific information is available in real time and systems are effectively integrated into clinical workflows. However, the evidence regarding impact on patient outcomes was less clear-cut with reviews finding either no, inconsistent or modest benefits. Whilst the potential of clinical decision support systems in improving, in particular, practitioner performance is considerable, such technology may
Kalina, Jan; Seidl, L.; Zvára, K.; Grünfeldová, H.; Slovák, Dalibor; Zvárová, Jana
Roč. 1, č. 1 (2013), s. 46-46 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : decision support system * web-service * information extraction * high-dimension * gene expressions Subject RIV: IN - Informatics, Computer Science
Martinková, Patrícia; Zvára Jr., Karel; Dostálová, T.; Zvárová, Jana
Roč. 1, č. 1 (2013), s. 40-40 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : education * decision support * knowledge evaluation * e- learning Subject RIV: IN - Informatics, Computer Science
checklist for the provision of nutritional care which would be supported by decision support technology akin to what we had done previously with...order to encourage Annual Report, Grant W81XWH-12-2-0074 17 eating a regular diet . At this point, only days when the patient received ≥ 90% of
Lindsey, Tony; Shetye, Sandeep; Shaw, Tianna (Editor)
The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear
.... Decision Support Systems (DSS) can help manage these networks by attempting to create optimized scheduling solutions for routing aircraft, crews and logistical support needed to successfully operate in this new environment...
Gaitanaru, Dragos; Leonard, Anghel; Radu Gogu, Constantin; Le Guen, Yvi; Scradeanu, Daniel; Pagnejer, Mihaela
Environmental decision support systems (DSS) paradigm evolves and changes as more knowledge and technology become available to the environmental community. Geographic Information Systems (GIS) can be used to extract, assess and disseminate some types of information, which are otherwise difficult to access by traditional methods. In the same time, with the help of the Internet and accompanying tools, creating and publishing online interactive maps has become easier and rich with options. The Decision Support System (MDSS) developed for the MUSTANG (A MUltiple Space and Time scale Approach for the quaNtification of deep saline formations for CO2 storaGe) project is a user friendly web based application that uses the GIS capabilities. MDSS can be exploited by the experts for CO2 injection and storage in deep saline aquifers. The main objective of the MDSS is to help the experts to take decisions based large structured types of data and information. In order to achieve this objective the MDSS has a geospatial objected-orientated database structure for a wide variety of data and information. The entire application is based on several principles leading to a series of capabilities and specific characteristics: (i) Open-Source - the entire platform (MDSS) is based on open-source technologies - (1) database engine, (2) application server, (3) geospatial server, (4) user interfaces, (5) add-ons, etc. (ii) Multiple database connections - MDSS is capable to connect to different databases that are located on different server machines. (iii)Desktop user experience - MDSS architecture and design follows the structure of a desktop software. (iv)Communication - the server side and the desktop are bound together by series functions that allows the user to upload, use, modify and download data within the application. The architecture of the system involves one database and a modular application composed by: (1) a visualization module, (2) an analysis module, (3) a guidelines module
Medlock, Stephanie; Wyatt, Jeremy C; Patel, Vimla L; Shortliffe, Edward H; Abu-Hanna, Ameen
A fundamental challenge in the field of clinical decision support is to determine what characteristics of systems make them effective in supporting particular types of clinical decisions. However, we lack such a theory of decision support itself and a model to describe clinical decisions and the systems to support them. This article outlines such a framework. We present a two-stream model of information flow within clinical decision-support systems (CDSSs): reasoning about the patient (the clinical stream), and reasoning about the user (the cognitive-behavioral stream). We propose that CDSS "effectiveness" be measured not only in terms of a system's impact on clinical care, but also in terms of how (and by whom) the system is used, its effect on work processes, and whether it facilitates appropriate decisions by clinicians and patients. Future research into which factors improve the effectiveness of decision support should not regard CDSSs as a single entity, but should instead differentiate systems based on their attributes, users, and the decision being supported. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: email@example.com.
Moutsouri, Irene; Nikou, Amalia; Pampalou, Machi; Lentza, Maria; Spyridakis, Paulos; Mathiopoulou, Natassa; Konsoulas, Dimitris; Lampou, Marianna; Alexiou, Athanasios
It is common that children confront psychological problems when they reach puberty. These problems could easily be overcome, but in many cases they could be severe, leading to social estrangement or worse in madness or death. According to information collected we designed a questionnaire about the psychology of adolescents in order to help people in that age or their elders find out if they have health issues. We used already published researches and material concerning all the psychological problems a child can confront in order to make a reliable questionnaire and to develop the clinical decision support system. Our main objective is to publish and administrate a web-based free tool for sharing medical knowledge about any psychological disease a child can already have or develop during puberty.
Today’s software business development projects often lay claim to low-risk value to the customers in order to be financed. Emerging agile processes offer shorter investment periods, faster time-to-market and better customer satisfaction. To date, however, in agile environments there is no sound methodological schedule support contrary to the traditional plan-based approaches. To address this situation, we present an agile iteration scheduling method whose usefulness is evaluated with post-mortem simulation. It demonstrates that the method can significantly improve load balancing of resources (cca. 5×), produce higher quality and lower-risk feasible schedule, and provide more informed and established decisions by optimized schedule production. Finally, the paper analyzes benefits and issues from the use of this method.
Abidin, Mohammad Zukuwwan Zainol; Nawawi, Mohd Kamal Mohd; Kasim, Maznah Mat
This paper proposes a suitable research procedure that can be referred to while conducting a Decision Support System (DSS) study, especially when the development activity of system artifacts becomes one of the research objectives. The design of the research procedure was based on the completion of a football DSS development that can help in determining the position of a player and the best team formation to be used during a game. After studying the relevant literature, we found that it is necessary to combine the conventional rainfall System Development Life Cycle (SDLC) approach with Case Study approach to help in structuring the research task and phases, which can contribute to the fulfillment of the research aim and objectives.