Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen
This paper presents a decision support system for assessment of transport infrastructure projects. The composite modelling approach, COSIMA, combines a cost-benefit analysis by use of the CBA-DK model with multi-criteria analysis applying the AHP and SMARTER techniques. The modelling uncertainties...
Salling, Kim Bang; Banister, David
This paper presents the final version of the CBA-DK decision support model for assessment of transport projects. The model makes use of conventional cost-benefit analysis resulting in aggregated single point estimates and quantitative risk analysis using Monte Carlo simulation resulting in interval...... results. Two special concerns in this paper is firstly the treatment of feasibility risk assessment adopted for evaluation of transport infrastructure projects, and secondly whether this can provide a more robust decision support model. This means moving away from a single point estimate to an interval...... result, and the determination of suitable probability distributions. Use is made of the reference class forecasting information, such as that developed in Optimism Bias for adjustments to investment decisions that relate to all modes of transport. The CBA-DK decision support model results in more...
Salling, Kim Bang; Banister, David
The scope of this paper is to present a newly developed decision support model to assess transport infrastructure projects: CBA-DK. The model makes use of conventional cost-benefit analysis resulting in aggregated single point estimates and quantitative risk analysis using Monte Carlo simulation...... resulting in interval results. The embedded uncertainties within traditional CBA such as ex-ante based investment costs and travel time savings are of particular concern. The methodological approach has been to apply suitable probability distribution functions on the uncertain parameters, thus resulting...
Salling, Kim Bang; Leleur, Steen
(epistemic uncertainty). After a short introduction to deterministic calculation resulting in some evaluation criteria a more comprehensive evaluation of the stochastic calculation is made. Especially, the risk analysis part of CBA-DK, with considerations about which probability distributions should be used...
Salling, Kim Bang; Banister, David
use of both deterministic and stochastic based information. Decision support as illustrated in this paper aims to provide assistance in the development and ultimately the choice of action, while accounting for the uncertainties surrounding transport appraisal schemes. The modelling framework...... interval results. The embedded uncertainties within traditional CBA such as ex-ante based investment costs and travel time savings are of particular concern. The paper investigates these two impacts in terms of the Optimism Bias principle which is used to take account of the underestimation of construction...
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....
Power, Daniel J
This book is targeted to busy managers and MBA students who need to grasp the basics of computerized decision support. Some of the topics covered include: What is a DSS? What do managers need to know about computerized decision support? And how can managers identify opportunities to create innovative DSS? Overall the book addresses 35 fundamental questions that are relevant to understanding computerized decision support.
Full Text Available Introduction & Background: Radiology practice like any other discipline in medicine consists of professional problem solving. A practicing radiologist may face different kinds of problems from pathology finding in im-age, suggestion of appropriate workup in a specific situation, formulating relevant differential diagnosis list for comparison with normal variants and artifacts. When a radiologist has the opportunity to use a computer he/she will also be able to use digital material/technology to solve these problems and make sound decisions. The available methods/materials for digital decision support in radiology may be categorized as follow: A. Image Processing When a radiological image is captured or converted to digital format, techniques like edge enhancement and contrast change may improve the diagnostic value of an image and help in decision making. B. Computer-aided Detection Thoracic imaging and mammography are two fields with promising advances in computer-aided diagnosis (CAD. The ultimate role of CAD is as a second opinion besides radiologists own perception. It is obvious how-ever that when available, CAD may decrease detection errors in radiology practice. C. Decision Support Databases Image Banks: An electronic atlas may be used to compare patients’ image to a predefined classified set of im-ages in order to help radiologist in pattern recognition. This may also be used for anatomic details and variants. Knowledge Bases: A digital differential diagnosis table or algorithmic approach to a specific problem may be helpful in reading room. Digital Textbooks: Classical radiological textbooks may be used in routine practice to remember some definitions, lists or hints, When available, digital version of textbooks are invaluable decision aids. D. Internet resources Online resources can be easily updated, widely used by different users, uniformly applied by different radiolo-gists. Although digital decision support materials and
Goosen, H.; Janssen, R.H.H.; Vermaat, J.E.
Decision support systems can be helpful tools in wetland planning and management. Decision support systems can contribute to efficient exchange of information between experts, stakeholders, decision makers and laypeople. However, the achievements of decision support systems are repeatedly being repo
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.
Jørgensen, L N; Noe, E; Langvad, A M;
system Crop Protection Online is widely used by advisors and as a learning tool for students. Although the system has been validated in many field trials over the years and has shown reliable results, the number of end-users among farmers has been relatively low during the last 10 years (approximately...... 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...
Encheva, Sylvia; Kondratenko, Yuriy; Solesvik, Maryna Z.; Tumin, Sharil
Experience shows that intuitive judgment and decision making is not allwas of sufficient quality and is getting worse in the presence of increasing complexity. One of the solutions to such problems is to use decision support systems. This paper focuses on assessment criteria of delivery quality in the transport logistics.
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,...
A decision support system (DSS) shell is being constructed that can support applications in a variety of fields, e.g., engineering, manufacturing, finance. The shell provides a hypertext-style interface for 'navigating' among DSS application models, data, and reports. The traditional notion of hypertext had to be enhanced. Hypertext normally requires manually, pre-defined links. A DSS shell, however, requires that hypertext connections to be built 'on the fly'. The role of hypertext is discussed in augmenting DSS applications and the decision making process. Also discussed is how hypertext nodes, links, and link markers tailored to an arbitrary DSS application were automatically generated.
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.
Vriens, D.J.; Achterbergh, J.M.I.M.
In this paper, we assess the characteristics decision support tools should have in order to support “responsible decision-making”. To this end, we first describe responsible decision-making. We argue that responsibility relates to both the outcome and the process of decision-making. On the basis of
van Merode, G G; Hasman, A; Derks, J; Goldschmidt, H M; Schoenmaker, B; Oosten, M
The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.
Lanzagorta, Marco O.; Kuo, Eddy; Uhlmann, Jeffrey K.
In this paper we describe the GROTTO visualization projects being carried out at the Naval Research Laboratory. GROTTO is a CAVE-like system, that is, a surround-screen, surround- sound, immersive virtual reality device. We have explored the GROTTO visualization in a variety of scientific areas including oceanography, meteorology, chemistry, biochemistry, computational fluid dynamics and space sciences. Research has emphasized the applications of GROTTO visualization for military, land and sea-based command and control. Examples include the visualization of ocean current models for the simulation and stud of mine drifting and, inside our computational steering project, the effects of electro-magnetic radiation on missile defense satellites. We discuss plans to apply this technology to decision support applications involving the deployment of autonomous vehicles into contaminated battlefield environments, fire fighter control and hostage rescue operations.
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...
Hansen, Poul H. Kyvsgård; Mikkola, Juliana Hsuan
of these decisions can cause a high strategic risk. This paper describes and discusses the complexity of the platform decisions. We argue that new methods have to be introduced in order to create a comprehensive picture of the consequences of the platform decisions. One of the promising new methods...
will enable proactive analysis within the decision support layer to anticipate, request, compute , and pre-position information supporting the decision... Proactive and Adaptive Decision Support Study (PDS) Final Report CDRL: C001 CLIN: 0006 Contract Number: N00014-14-P-1187 Submitted...PAGES 19a. NAME OF RESPONSIBLE PERSON 19b. TELEPHONE NUMBER (Include area code) 12/09/2014 Final Report 28 Jul 2014 - 31 Dec 2014 Proactive and
Full Text Available We elaborate on the shifting of decision support systems towards social networking, which is based on the concepts of Web 2.0 and Semantic Web technology. As the characteristics of the relevant components are different from traditional decision support systems, we present necessary adaptations when adopting social networks for decision support within an organization. We also present organizational obstacles when adopting/using such systems and clues to overcome them.
064, CC in GIScience; Malczewski, Jacek; Keller, C Peter
This unit focuses on the concept of Spatial Decision Support Systems (SDSS). It covers the major characteristics of spatial decision problems; the decision-making process; a definition of SDSS; principles of SDSS; the dialog, data, model (DDM) paradigm; and technologies for developing SDSS.
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
result in extreme fire behavior, making them dangerous to emergency personnel. Features also influence the mechanics of the hydrologic cycle in an...assessing wildfire risk in the wilderness urban interface (WUI) to facilitate better informed land management decisions and reduce mission impacts of...Information Systems, Landsat 8, Remote Sensing, Wildfire, Wildland Urban Interface v Acknowledgments I would like to thank Dr. Jonathan
Aragon, Cecilia R.
In order to safely operate their aircraft, pilots must makerapid decisions based on integrating and processing large amounts ofheterogeneous information. Visual displays are often the most efficientmethod of presenting safety-critical data to pilots in real time.However, care must be taken to ensure the pilot is provided with theappropriate amount of information to make effective decisions and notbecome cognitively overloaded. The results of two usability studies of aprototype airflow hazard visualization cockpit decision support systemare summarized. The studies demonstrate that such a system significantlyimproves the performance of helicopter pilots landing under turbulentconditions. Based on these results, design principles and implicationsfor cockpit decision support systems using visualization arepresented.
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
Vesselinov, V. V.; O'Malley, D.
Uncertainty quantifications and decision analyses under severe lack of information are ubiquitous in every applied field of engineering, policy, and science. A severe lack of information precludes our ability to determine unbiased probabilistic distributions for model parameters and model predictions; therefore, model and decision uncertainties due to a severe lack of information cannot be characterized probabilistically. To circumvent this problem, information gap (info-gap) theory has been developed to explicitly recognize and quantify the implications of information gaps in decision making. Here we present a decision analysis based on info-gap theory developed for a source identification problem where the locations and mass fluxes of contaminants impacting groundwater resources are unknown. The problem is characterized with a lack of information related to (1) model parameters representing contaminant migration in the aquifer, and (2) observed contamination concentration in the existing monitoring wells. These two sources of uncertainty are coupled through an inverse model where the observed concentrations are applied to estimate model parameters. The decision goal is based on contaminant predictions at points of compliance. The decision analysis is demonstrated for synthetic and real-world test cases. The applied uncertainty-quantification, decision-support techniques and computational algorithms are implemented in code MADS (Model Analyses for Decision Support; http://mads.lanl.gov). MADS is C/C++ code that provides a framework for model-based decision support. MADS performs various types of model analyses including sensitivity analysis, parameter estimation, uncertainty quantification, model calibration, selection and averaging. To perform the analyses, MADS can be coupled with any external simulators. Our efforts target development of an interactive computer-based Decision Support System (DSS) that will help domain scientist, managers, regulators, and
Sullivan, T.M.; Moskowitz, P.D. [Brookhaven National Lab., Upton, NY (United States); Gitten, M. [Environmental Project Control, Maynard, MA (United States)
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.
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
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...
Earthquake DSS is an information technology environment which can be used by government to sharpen, make faster and better the earthquake mitigation decision. Earthquake DSS can be delivered as E-government which is not only for government itself but in order to guarantee each citizen's rights for education, training and information about earthquake and how to overcome the earthquake. Knowledge can be managed for future use and would become mining by saving and maintain all the data and information about earthquake and earthquake mitigation in Indonesia. Using Web technology will enhance global access and easy to use. Datawarehouse as unNormalized database for multidimensional analysis will speed the query process and increase reports variation. Link with other Disaster DSS in one national disaster DSS, link with other government information system and international will enhance the knowledge and sharpen the reports.
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.
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.
Janssen, T. [Argonne National Lab., IL (United States)]|[George Mason Univ., Fairfax, VA (United States). School of Information Technology and Engineering; Sage, A.P. [George Mason Univ., Fairfax, VA (United States). School of Information Technology and Engineering
This paper addresses the need for sound science, technology, and management assessment relative to environmental policy decision making through an approach that involves a logical structure for evidence, a framed decision-making process, and an environment that encourages group participation. Toulmin-based logic possesses these characteristics and is used as the basis for development of a group decision support system. This system can support several user groups, such as pesticide policy-making experts, who can use the support system to state arguments for or against an important policy issue, and pest management experts, who can use the system to assist in identifying and evaluating alternatives for controlling pests on agricultural commodities. The resulting decision support system assists in improving the clarity of the lines of reasoning used in specific situations; the warrants, grounds, and backings that are used to support claims and specific lines of reasoning; and the contradictions, rebuttals, and arguments surrounding each step in the reasoning process associated with evaluating a claim or counterclaim. Experts and decisions makers with differing views can better understand each other`s thought processes. The net effect is enhanced communications and understanding of the whole picture and, in many cases, consensus on decisions to be taken.
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...
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...
Booker, Corenthian Corey J; Andrews, Paige N
The software known as Clinical Decision Support Services (CDSS) has emerged as a buzzword from the explosion of information systems within health care. CDSS is installed within a practice to provide resources and tools to support the utilization of patient data in the provider decision-making process. Additional applications of CDSS include streamlining administrative duties and assisting in cost control. This paper examines the details of CDSS design and implementation to analyze strengths, weaknesses, and feasibility of CDSS for practices of varying sizes and objectives.
Wong, Simon C. H.
A decision support system integrates individuals' intellectual resources with computer capabilities to improve decision-making quality. This paper presents the theoretical aspects of decision making and decision support and shows how the theories can be applied in developing an operational management decision-making support system for room booking…
Full Text Available A decision support system (DSS is described to form schedules of traffic from a central warehouse to a set of consumers by cyclic routes. The system may be used by dispatchers at transportation enterprises. The system structure, short description of modules, and algorithms solving the originating problems are presented.
Verweij, P.J.F.M.; Winograd, M.; Perez-Soba, M.; Knapen, M.J.R.; Randen, van Y.
Decision Support Tools (DST) are a key instrument for preparing legislative proposals and policy initiatives. They provide insight about options, conflicts, synergies and trade-offs between issues, sectors and regions at multiple scales. DST range from integrated systems modelling to value-based kno
Konsynski, Benn R.; And Others
A series of articles addresses issues concerning decision support and knowledge based systems. Topics covered include knowledge-based systems for information centers; object oriented systems; strategic information systems case studies; user perception; manipulation of certainty factors by individuals and expert systems; spreadsheet program use;…
Erisman, J.W.; Hensen, A.; Vries, de W.; Kros, H.; Wal, van der T.; Winter, de W.; Wien, J.E.; Elswijk, van M.; Maat, M.; Sanders, K.
A nitrogen decision support system in the form of a game (NitroGenius) was developed for the Second International Nitrogen Conference. The aims were to: i) improve understanding among scientists and policy makers about the complexity of nitrogen pollution problems in an area of intensive agricultura
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.
J. Roukema (Jolt)
textabstractThe overall aim of the studies described in this thesis was to investigate and optimize the diagnostic process of (febrile) children presenting to the hospital emergency department (ed), and to study aspects of this process as a base for clinical decision support systems. We discussed
A knowledge representation approach for expert systems supporting decision processes in business is proposed. A description of a knowledge representation schema using a logic programming metalanguage is described, then the role of such a schema in a management expert system is demonstrated through the problem of nursing management control in hospitals. 18 references.
Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele
Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization.
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.
Ozbolt, Judy; Ozdas, Asli; Waitman, Lemuel R; Smith, Janis B; Brennan, Grace V; Miller, Randolph A
The application of principles and methods of cybernetics permits clinicians and managers to use feedback about care effectiveness and resource expenditure to improve quality and to control costs. Keys to the process are the specification of therapeutic goals and the creation of an organizational culture that supports the use of feedback to improve care. Daily feedback on the achievement of each patient's therapeutic goals provides tactical decision support, enabling clinicians to adjust care as needed. Monthly or quarterly feedback on aggregated goal achievement for all patients on a clinical pathway provides strategic decision support, enabling clinicians and managers to identify problems with supposed "best practices" and to test hypotheses about solutions. Work is underway at Vanderbilt University Medical Center to implement feedback loops in care and management processes and to evaluate the effects.
Kozma, Robert; Tanigawa, Timothy; Furxhi, Orges; Consul, Sergi
There is a need to model complementary aspects of various data channels in distributed sensor networks in order to provide efficient tools of decision support in rapidly changing, dynamic real life scenarios. Our aim is to develop an autonomous cyber-sensing system that supports decision support based on the integration of information from diverse sensory channels. Target scenarios include dismounts performing various peaceful and/or potentially malicious activities. The studied test bed includes Ku band high bandwidth radar for high resolution range data and K band low bandwidth radar for high Doppler resolution data. We embed the physical sensor network in cyber network domain to achieve robust and resilient operation in adversary conditions. We demonstrate the operation of the integrated sensor system using artificial neural networks for the classification of human activities.
Jacyk, P.; Schultz, D.; Spangenberg, L.
A decision support system (DSS) is being developed at the Radioactive Liquid Waste Treatment Facility, Los Alamos National Laboratory (LANL). The DSS will be used to evaluate alternatives for improving LANL`s existing central radioactive waste water treatment plant and to evaluate new site-wide liquid waste treatment schemes that are required in order to handle the diverse waste streams produced at LANL. The decision support system consists of interacting modules that perform the following tasks: rigorous process simulation, configuration management, performance analysis, cost analysis, risk analysis, environmental impact assessment, transportation modeling, and local, state, and federal regulation compliance checking. Uncertainty handling techniques are used with these modules and also with a decision synthesis module which combines results from the modules listed above. We believe the DSS being developed can be applied to almost any other industrial water treatment facility with little modification because in most situations the waste streams are less complex, fewer regulations apply, and the political environment is simpler. The techniques being developed are also generally applicable to policy and planning decision support systems in the chemical process industry.
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
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.
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...
Bennett, Casey C
Purpose: This goal of this study was to evaluate the effects of a data-driven clinical productivity system that leverages Electronic Health Record (EHR) data to provide productivity decision support functionality in a real-world clinical setting. The system was implemented for a large behavioral health care provider seeing over 75,000 distinct clients a year. Design/methodology/approach: The key metric in this system is a "VPU", which simultaneously optimizes multiple aspects of clinical care. The resulting mathematical value of clinical productivity was hypothesized to tightly link the organization's performance to its expectations and, through transparency and decision support tools at the clinician level, affect significant changes in productivity, quality, and consistency relative to traditional models of clinical productivity. Findings: In only 3 months, every single variable integrated into the VPU system showed significant improvement, including a 30% rise in revenue, 10% rise in clinical percentage, a...
Full Text Available The environment where managers make decisions has been significantly changed ttiese years. Today, organizations design their products in one country, purchase of materials and raw materials in the other one, production is done in the third country, and finished products are brought out in many countries in the world. Logistics, as a transaction intensive function mutually connect these substantially different business processes and enables more effective and efficient management of the long logistics chains. In realizing such a task, the intensive use of infomiation technologies that provide timely transaction processing and give support in decisionmaking processes is especially important for logistics. The work reviews information systems development in the field of logistics, and a special attention is paid to the conceptual level of the global structure in decision support systems (DSS. Possible contents of identified subsystems are cited and potential development trends of its application are discussed.
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...
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.
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...
Full Text Available This paper describes the possibility of the Geographic Information Systems (GIS as a means to support decision making in solving spatial problems. Spatial problems accompany every human activity, of which agriculture is no exception. The solutions to these problems requires the application of available knowledge in the relevant decision-making processes. GISs integrate hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information. Coupled with GISs, geography helps to better understand and apply geographic knowledge to a host of global problems (unemployment, environmental pollution, the loss of arable land, epidemics etc.. The result may be a geographical approach represents a new way of thinking and solutions to existing spatial problems. This approach allows to apply existing knowledge to model and analyze these problems and thus help to solve them.
HONG Xiao-kang; LIU Jian-lin; XIE Jian-cang; LIU Fu-chao; MA Bin
On the bases of the properties of abstract hierarchical structure model and the concrete structure of the model system, which is convenient to solve practical problems, a visual interactive hierarchical coordination method has been proposed. In this paper, a compensation adjustment sub-model for hydropower stations, an optimal operation sub-model for hydro-thermal power systems, and an aggregation model based on the aspiration level theory are built, and these models can be solved with decision support algorithm. The set of objectives and its structure could be made by the decision-maker in visual software,which could be decided by AHP. Finally, the application results show that this methodology is feasible,however, the software (DSS) needs further improvement.
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...
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 tool for planning, documenting, and assessing model evaludation, which includes understanding the rationale behind a model and its envisaged use. We introduce the new structure and revised terminology of TRACE and provide examples...
Chai, Junyi; Liu, James N. K.
The study proposes a framework of ONTOlogy-based Group Decision Support System (ONTOGDSS) for decision process which exhibits the complex structure of decision-problem and decision-group. It is capable of reducing the complexity of problem structure and group relations. The system allows decision makers to participate in group decision-making through the web environment, via the ontology relation. It facilitates the management of decision process as a whole, from criteria generation, alternat...
Hardin, D. M.; Keiser, K.; Graves, S. J.; Conover, H.; Ebersole, S.
Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The recently awarded Sediment Analysis Network for Decision Support will generate decision support products using NASA satellite observations from MODIS, Landsat and SeaWiFS instruments to support resource management, planning, and decision making activities in the Gulf of Mexico. Specifically, SANDS will generate decision support products that address the impacts of tropical storms
VonPlinsky, Michael J.; Johnson, Pete; Crowder, Ed
The "Decision Integration and Support Environment" (DISE) is a Bayesian network (BN) based modeling and simulation of the target nomination and aircraft tasking decision process. FTI has developed two BNs to model these processes, incorporating aircraft, target, and overall mission priorities from the Air Operations Center (OAC) and the mission planners/command staff. DISE operates in event driven interactions with FTI's AOC model, being triggered from within the Time Critical Target (TCT) Operations cell. As new target detections are received by the AOC from off-board ISR Sources and processed by the Automatic Target Recognition (ATR) module in the AOC, DISE is called to determine if the target should be prosectued, and if so, which of the available aircraft should be tasked to attack it. A range of decision criteria, with priorities established off-line and input into the tool, are associated with this process, including factors such as: * Fuel Level - amount of fuel in aircraft * Type of Weapon - available weapons on board aircraft * Probability of Survival - depends on the type of TST, time criticality and other factors * Potential Collateral Damage - amount of damage incurred on TST surroundings * Time Criticality of TST - how "critical" it is to attack the target depending on its launch status * Time to Target - aircraft's distance (in minutes) from the TST * Current Mission Priority - priority of the mission to which the aircraft is currently assigned * TST Mission Priority - determined when the target is originally nominated * Possible Reassignment - represents whether it is even possible to reassign the aircraft * Aircraft Re-tasking Availability - represents any factor not taken into account by the model, including commander override.
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., t
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.
Randleff, Lars Rosenberg
During a mission over enemy territory a fighter aircraft may be engaged by ground based threats. The pilot can use different measures to avoid the aircraft from being detected by e.g. enemy radar systems. If the enemy detects the aircraft a missile may be fired to seek and destroy the aircraft...... and countermeasures that can be applied to mitigate threats. This work is concerned with finding proper evasive actions when a fighter aircraft is engaged by ground based threats. To help the pilot in deciding on these actions a decision support system may be implemented. The environment in which such a system must...... platforms (aircraft, ships, etc.) is described. Different approaches to finding the combination of countermeasures and manoeuvres improving the pilots survivability is investigated. During training a fighter pilot will learn a set of rules to follow when threat occurs. For the pilot these rules...
Gerrit H. van Bruggen; Ale Smidts; Berend Wierenga
Marketing decision makers are confronted with an increasing amount of information. This leads to a complex decision environment that may cause decision makers to lapse into using mental-effort-reducing heuristics such as anchoring and adjustment. In an experimental study, we find that the use of a marketing decision support system (MDSS) increases the effectiveness of marketing decision makers. An MDSS is effective because it assists its users in identifying the important decision variables a...
Smith, L. A.
Is it conceivable that models run on 2007 computer hardware could provide robust and credible probabilistic information for decision support and user guidance at the ZIP code level for sub-daily meteorological events in 2060? In 2090? Retrospectively, how informative would output from today’s models have proven in 2003? or the 1930’s? Consultancies in the United Kingdom, including the Met Office, are offering services to “future-proof” their customers from climate change. How is a US or European based user or policy maker to determine the extent to which exciting new Bayesian methods are relevant here? or when a commercial supplier is vastly overselling the insights of today’s climate science? How are policy makers and academic economists to make the closely related decisions facing them? How can we communicate deep uncertainty in the future at small length-scales without undermining the firm foundation established by climate science regarding global trends? Three distinct aspects of the communication of the uses of climate model output targeting users and policy makers, as well as other specialist adaptation scientists, are discussed. First, a brief scientific evaluation of the length and time scales at which climate model output is likely to become uninformative is provided, including a note on the applicability the latest Bayesian methodology to current state-of-the-art general circulation models output. Second, a critical evaluation of the language often employed in communication of climate model output, a language which accurately states that models are “better”, have “improved” and now “include” and “simulate” relevant meteorological processed, without clearly identifying where the current information is thought to be uninformative and misleads, both for the current climate and as a function of the state of the (each) climate simulation. And thirdly, a general approach for evaluating the relevance of quantitative climate model output
陈晓红; 周艳菊; 胡东滨
A new problem solving framework for group decision support system using layer model approach is proposed. This kind of framework includes four basic layers, namely, application layer, task layer, logical layer and physical layer. Based on indicating the respective meanings of those layers a task skeleton of group decision support system and a logical structure of group decision support system generator are put forward and discussed in detail. The framework provides theoretical guidance for developing group decision support system to lower systematic development complexity and support reuse of software.
Søndergaard, Erik Stefan; Ahmed-Kristensen, Saeema
This paper investigates how global product development decisions are made through a multiple-case study in three Danish engineering. The paper identifies which information and methods are applied for making decisions and how decision-making can be supported based on previous experience. The paper...... presents results from 51 decisions made in the three companies, and based on the results of the studies a framework for a decision-support tool is outlined and discussed. The paper rounds off with an identification of future research opportunities in the area of global product development and decision-making....
30/2014 Final Report 07/11/2014 - 11/30/2014 Final Report - Proactive Decision Support Via Narrative -Integrated Multi-Level Support System (NIMSS...think, demonstrated via a realistic Naval/Marine Corps warfighting domain. Context-driven decision making; proactive decision support; narrative ...0005, CDRL B001 Proactive Decision Support via Narrative -Integrated Multi-level Support System (NIMSS) CHI Project # 14002 Purchase Order: N00014
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.
Dr. Richard Adler
Full Text Available This article presents a dynamic decision support methodology forcounter-terrorism decision support. The initial sections introduce basic objectives and challenges of terrorism risk analysis and risk management. The remainder of the paper describes TRANSEC, a decision support framework for defining, validating, and monitoring strategies focused on managing terrorism risks to international transportation networks. The methodology and software tools underlying TRANSEC are applicable to other homeland security problems, such as critical infrastructure and border protection.
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. SETT
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
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 present
Fan Jiancong; Liang Yongquan; Zeng Qingtian
The concept of organization decision support system (ODSS) is defined according to practical applications and novel understanding. And a framework for ODSS is designed. The framework has three components: infrastructure, decision-making process and decision execution process. Infrastructure is responsible to transfer data and information. Decision-making process is the ODSS's soul to support decision-making. Decision execution process is to evaluate and execute decision results derived from decision-making process. The framework presents a kind of logic architecture. An example is given to verify and analyze the framework. The analysis shows that the framework has practical values, and has also reference values for understanding ODSS and for theoretical studies.
Mohemad, Rosmayati; Othman, Zulaiha Ali; Noor, Noor Maizura Mohamad
The successful execution of a construction project is heavily impacted by making the right decision during tendering processes. Managing tender procedures is very complex and uncertain involving coordination of many tasks and individuals with different priorities and objectives. Bias and inconsistent decision are inevitable if the decision-making process is totally depends on intuition, subjective judgement or emotion. In making transparent decision and healthy competition tendering, there exists a need for flexible guidance tool for decision support. Aim of this paper is to give a review on current practices of Decision Support Systems (DSS) technology in construction tendering processes. Current practices of general tendering processes as applied to the most countries in different regions such as United States, Europe, Middle East and Asia are comprehensively discussed. Applications of Web-based tendering processes is also summarised in terms of its properties. Besides that, a summary of Decision Support Sy...
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...
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...
ZHANG Rong-mei; SUN Jie-li
This paper studies how to apply GIS, ES, and Data mining and WEB technologies in agriculture Decision Support System, with the researching background of Hebei expert system for farming soil variable rate fertilization. A model of agriculture intelligent spatial decision support system is built and the key technologies to implement this system are described in details.
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 p...
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...
Durand, M.A.; Boivin, J.; Elwyn, G.
BACKGROUND: There is an increasing interest in designing decision tools [decision support technologies (DSTs)] that support patients when they have to decide about health matters. The purpose of this review was to describe and evaluate existing DSTs for amniocentesis testing. METHODS: Ten medical an
Puig, Daniel; Aparcana Robles, Sandra Roxana
This document describes three decision-support tools that can aid the process of planning climate change mitigation actions. The phrase ‘decision-support tools’ refers to science-based analytical procedures that facilitate the evaluation of planning options (individually or compared to alternative...... 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....... For example, in the case of life-cycle analysis, the evaluation criterion entails that the impacts of interest are examined across the entire life-cycle of the product under study, from extraction of raw materials, to product disposal. Effectively, then, the choice of decision-support tool directs...
Erin K. Noonan-Wright
Full Text Available 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 information to the decision making process. Risk-informed decision-making is becoming increasingly important as a means of improving fire management and offers substantial opportunities to benefit natural and community resource protection, management response effectiveness, firefighter resource use and exposure, and, possibly, suppression costs. This paper reviews the development, structure, and function of WFDSS, and how it contributes to increased flexibility and agility in decision making, leading to improved fire management program effectiveness.
Poole, Marshall Scott; And Others
Explores the effects of Group Decision Support Systems (GDSS) on small group communication and decision-making processes. Finds that comparing GDSS, manual, and baseline conditions enables separation of effects resulting from procedural structures from those resulting from computerization. Results support some aspects of the research model and…
Liebers, A.; Kals, H.J.J.
The constraints addressed in decision making during product design, process planning and production planning determine the admissible solution space for the manufacture of products. The solution space determines largely the costs that are incurred in the production process. In order to be able to ma
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 Frie
Full Text Available Social networking sites prove to be indispensible tools for decision making owing to the large repository of user views accumulated over a period of time. Such a real data can be exploited for various purposes such as making buying decisions, analysing the user views about new product launched by a company, product promotion campaign , impact of policy decisions made by a political party on society etc. In the current work the authors have proposed a generic model for feature based polarity determination by sentiment analysis of tweets. This model has been implemented by the seamless integration of R tool, XML, JAVA, Link Parser A practical multistep system, in place, efficiently extracts data from tweet text, pre-process the raw data to remove noise, and tags their polarity. Data used in the current study is derived from online product feature based reviews collected from tweeter tweets. Link parser version 4.1 b is employed for parsing a natural sentence which is broken into multiple tokens corresponding to noun and adjective before being stored in a persistent storage medium. The objectivity score is determined using SentiWordNet 3.0 lexical resource which is parsed using a tool implemented in Java. The linguistic hedges are taken care of using Zadeh’s proposition which modifies the final objectivity score. The objectivity score so computed, provides the necessary guidelines in influencing decisions. The authors have tested the model for product purchase decisions of two different sets of products, smart phone and laptop based on predefined set of features. The model is generic and can be applied to any set of products evaluated on a predefined set of features.
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.
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 p
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 FrieslandCampina (FC), which was the fourth largest dairy company in the world at that time. In 2009, a new Milk Valorization & Allocation (MVA) department was created at the corporate level to opt...
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.
Huizingh, Eelko K.R.E.; Vrolijk, Hans C.J.
Decision-making in the field of information systems has become more complex due to a larger number of alternatives, multiple and sometimes conflicting goals, and an increasingly turbulent environment. In this paper we explore the appropriateness of Analytic Hierarchy Process to support I/S decision making. AHP can be applied if the decision problem includes multiple objectives, conflicting criteria, incommensurable units, and aims at selecting an alternative from a known set of alternatives. ...
Doctors must frequently make decisions during medical treatment, whether in an acute care facility, such as an Intensive Care Unit (ICU), or in an operating room. These decisions rely on a various information sources, such as the patient's medical history, preoperative images, and general medical knowledge. Decision support systems can assist by facilitating access to this information when and where it is needed. This paper presents some research eorts that address the integration of information with clinical practice. The example systems include a clinical decision support system (CDSS) for pediatric traumatic brain injury, an augmented reality head- mounted display for neurosurgery, and an augmented reality telerobotic system for minimally-invasive surgery. While these are dierent systems and applications, they share the common theme of providing information to support clinical decisions and actions, whether the actions are performed with the surgeon's own hands or with robotic assistance.
Decision making in design is of great importance, resulting in success or failure of a system. This paper describes a robust decision support tool for engineering design process, which can be used throughout the design process. The tool is graphical and designed to communicate efficiently with diffe
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 a
H.C. De Kock; Sinclair, M. (Michael)
Decision support systems were developed for use on stock farms. The systems were designed to run on Commodore 8032 microcomputers. They give the user quantitative results on which decisions such as feed mixes, sale of livestock, work programmes, etc can be based. In this paper these systems are described and illustrated with printouts from sample runs.
Sønderskov, Mette; Kudsk, Per; Mathiassen, Solvejg K;
Crop Protection Online (CPO) is a decision support system, which integrates decision algorithms quantifying the requirement for weed control and a herbicide dose model. CPO was designed to be used by advisors and farmers to optimize the choice of herbicide and dose. The recommendations from CPO...
Rajabalinejad, Mohammad; Spitas, Christos
Decision-making in design is of great importance, resulting in success or failure of a system (Liu et al., 2010; Roozenburg and Eekels, 1995; Spitas, 2011a). This paper describes a robust decision-support tool for engineering design process, which can be used throughout the design process in either
Huizingh, Eelko K.R.E.; Vrolijk, Hans C.J.
Decision-making in the field of information systems has become more complex due to a larger number of alternatives, multiple and sometimes conflicting goals, and an increasingly turbulent environment. In this paper we explore the appropriateness of Analytic Hierarchy Process to support I/S decision
National Aeronautics and Space Administration — This proposal is submitted under the Innovative Tools and Techniques Supporting the Practical Uses of Earth Science Observations topic. We seek to create a prototype...
B. Wierenga (Berend); P.A.M. Oude Ophuis
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, us
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 a
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...
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 devices
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 a
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...
Woosley, R L; Whyte, J; Mohamadi, A; Romero, K
For decades, medical practice has increasingly relied on prescription medicines to treat, cure, or prevent illness but their net benefit is reduced by prescribing errors that result in adverse drug reactions (ADRs) and tens of thousands of deaths each year. Optimal prescribing requires effective management of massive amounts of data. Clinical decision support systems (CDSS) can help manage information and support optimal therapeutic decisions before errors are made by operating as the prescribers' "autopilot."
Seamon Matthew J; Polen Hyla H; Marsh Wallace A; Clauson Kevin A; Ortiz Blanca I
Abstract Background Online drug information databases are used to assist in enhancing clinical decision support. However, the choice of which online database to consult, purchase or subscribe to is likely made based on subjective elements such as history of use, familiarity, or availability during professional training. The purpose of this study was to evaluate clinical decision support tools for drug information by systematically comparing the most commonly used online drug information datab...
Full Text Available Improving decisions efficiency is one of the major concerns of the decision support systems. Specially in the uncertain environment, decision support systems could be implemented efficiently to simplify decision making process. In this paper stochastic economic order quantity (EOQ problem is investigated in which decision variables and objective function are uncertain in nature and optimum probability distribution functions of them are calculated through a geometric programming model. Obtained probability distribution functions of the decision variables and the objective function are used as optimum knowledge to design a new probabilistic rule base (PRB as a decision support system for EOQ model. The developed PRB is a new type of the stochastic rule bases that can be used to infer optimum or near optimum values of the decision variables and the objective function of the EOQ model without solving the geometric programming problem directly. Comparison between the results of the developed PRB and the optimum solutions which is provided in the numerical example illustrates the efficiency of the developed PRB.
Roxana POPA STRAINU
Full Text Available A system built to support management decisions and not only needs to be accurate and well adapted to the requirements of the decision and the variables involved in it, and this happens because a decision is still a human act in any type of business and institution. We can say that a decision support system has a part in it that cannot be determined by any software: the human decision which is not a determinist act. It depends on a lot of variables but also still involves the decision maker intuition and experience. This is why an important problem emerged to be discussed in this paper: the need to implement and develop an in house solution to help management decisions and not only, using existing tools and this with no additional fees. This can be a good opportunity to discover models and solutions. An identified solution using Microsoft Excel and Access is discussed in this paper and a model applied on a case study will be presented. The results of the case study showed a real support in making decisions and a better transparency in manipulating the data, improving also the time needed to collect, transform and present data. The model can be applied in any type of problem that needs a visual presentation of data as well as in situations that need working with a large amount of data, but especially in small and medium size companies.
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. .
Agile Supply Chain Management (ASCM) is an important topic and has received much attention recently.ASCM is a new management technology.Agile Supply Chain Management Decision Support System (ASCM-DSS) is presented.Firstly, agile supply chain management technology is introduced.Secondly a decision support system for agile supply chain management is proposed.Then, the implementation of ASCM-DSS in enterprise is discussed.Finally, a fuzzy intelligence decision-making process in Shanghai Turbine Generator Company (STGC) is described in detail.
阎威武; 陈治纲; 邵惠鹤
Support Vector Machines (SVM) is a powerful machine learning method developed from statistical learning theory and is currently an active field in artificial intelligent technology. SVM is sensitive to noise vectors near hyperplane since it is determined only by few support vectors. In this paper, Multi SVM decision model(MSDM)was proposed. MSDM consists of multiple SVMs and makes decision by synthetic information based on multi SVMs. MSDM is applied to heart disease diagnoses based on UCI benchmark data set. MSDM somewhat inproves the robust of decision system.
谢勇; 王红卫; 费奇
With the prevalence of the Web, most decision-makers are likely to use the Web to support their decision-making. Web-based technologies are leading a major stream of researching decision support systems (DSS). We propose a formal definition and a conceptual framework for Web-based open DSS (WODSS). The formal definition gives an overall view of WODSS, and the conceptual framework based on browser/broker/server computing mode employs the electronic market to mediate decision-makers and providers, and facilitate sharing and reusing of decision resources. We also develop an admitting model, a trading model and a competing model of electronic market in WODSS based on market theory in economics. These models reveal the key mechanisms that drive WODSS operate efficiently.
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.
Sørup, Christian Michel; Jacobsen, Peter
Purpose – 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. Design/methodology/approach – The research consists of a quantitative literature study supported by formal and semi-formal interviews conducted...... 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. Research limitations/implications – Since a great part of the empirical material is supplied...
the GMU campus: a large concert at the Patriot Center, and a speech by a fictional controversial author named Simon Pierce taking place at the...Separately, the websites of the County and GMU were hacked by a fictional terrorist group called the Anti-Pierce Group. They defaced the websites and...Internet. Interaction was limited to laptops. Support for mobile devices would increase realism and improve student access, but required too much
Decision Support Systems in the sense of online alternative course of action (ACAO) development and analysis as well as tools for online Development of Doctrine and Tactics Techniques, and Procedures (DTTP) for support to operations make it possible to evaluate and forecast the command and control processes and the performance capabilities of the friendly and enemy forces and other decision relevant factors, support the military commander (brigade and higher) and his staff in their headquarter by increasing their ability to identify own opportunities, support all phases of the command and control process, use computer based, automatic and closed models, that can be adapted to the current situation. Objective of the paper is to present the results of studies conducted in Germany on behalf of the German Ministry of Defense with the objective to work out the conceptual basis for decision support systems and to evaluate, how this technique will influence the command and control system of the army of the federal a...
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.
Militello, Laura G.; Saleem, Jason J.; Borders, Morgan R.; Sushereba, Christen E.; Haverkamp, Donald; Wolf, Steven P.; Doebbeling, Bradley N.
Adoption of clinical decision support has been limited. Important barriers include an emphasis on algorithmic approaches to decision support that do not align well with clinical work flow and human decision strategies, and the expense and challenge of developing, implementing, and refining decision support features in existing electronic health records (EHRs). We applied decision-centered design to create a modular software application to support physicians in managing and tracking colorectal cancer screening. Using decision-centered design facilitates a thorough understanding of cognitive support requirements from an end user perspective as a foundation for design. In this project, we used an iterative design process, including ethnographic observation and cognitive task analysis, to move from an initial design concept to a working modular software application called the Screening & Surveillance App. The beta version is tailored to work with the Veterans Health Administration’s EHR Computerized Patient Record System (CPRS). Primary care providers using the beta version Screening & Surveillance App more accurately answered questions about patients and found relevant information more quickly compared to those using CPRS alone. Primary care providers also reported reduced mental effort and rated the Screening & Surveillance App positively for usability. PMID:26973441
Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F
System-agnostic clinical decision support (CDS) services provide patient evaluation capabilities that are independent of specific CDS systems and system implementation contexts. While such system-agnostic CDS services hold great potential for facilitating the widespread implementation of CDS systems, little has been described regarding the benefits and challenges of their use. In this manuscript, the authors address this need by describing potential benefits and challenges of using a system-agnostic CDS service. This analysis is based on the authors' formal assessments of, and practical experiences with, various approaches to developing, implementing, and maintaining CDS capabilities. In particular, the analysis draws on the authors' experience developing and leveraging a system-agnostic CDS Web service known as SEBASTIAN. A primary potential benefit of using a system-agnostic CDS service is the relative ease and flexibility with which the service can be leveraged to implement CDS capabilities across applications and care settings. Other important potential benefits include facilitation of centralized knowledge management and knowledge sharing; the potential to support multiple underlying knowledge representations and knowledge resources through a common service interface; improved simplicity and componentization; easier testing and validation; and the enabling of distributed CDS system development. Conversely, important potential challenges include the increased effort required to develop knowledge resources capable of being used in many contexts and the critical need to standardize the service interface. Despite these challenges, our experiences to date indicate that the benefits of using a system-agnostic CDS service generally outweigh the challenges of using this approach to implementing and maintaining CDS systems.
Subject of study is the possible organisation of the Olympic Games of 2028 in the Netherlands, as seen from an urban development viewpoint. The project focuses on the decision-making process in the initiative phase. Aim of the project is the development of a decision support tool for the complex, in
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
Decision support intended to improve ecosystem sustainability requires that we link stakeholder priorities directly to quantitative tools and measures of desired outcomes. Actions taken at the community level can have large impacts on production and delivery of ecosystem service...
Full Text Available Traditional Decision Support Systems (DSS give not enough possibilities of intervention to the user. These systems are reduced to an insular and very technical state in which the objective is not support decision but to dump data on the screen in the hope that the user will know what to do with. In complex situations, decision is not structured and it becomes primordial to design intelligent and cooperative systems allowing a joint resolution of problem based on dynamic sharing of the tasks between the user and the system and according to problems to be solved. In this perspective, we propose a cooperative architecture for intelligent decision support system. The framework embeds expert knowledge within the DSS to provide intelligent DSS using collaboration technologies by putting the decision maker effectively in the loop of the decision process. To this end, we used a structure based on domain and task conceptual modelling. Applicability and relevance of this model are illustrated through a case study where the system and the operator cooperate in decision problem which consists of identifying boiler defects, diagnosing and suggesting actions of cure.
Full Text Available The successful execution of a construction project is heavily impacted by making the right decision during tendering processes. Managing tender procedures is very complex and uncertain involving coordination of many tasks and individuals with different priorities and objectives. Bias and inconsistent decision are inevitable if the decision-making process is totally depends on intuition, subjective judgement or emotion. In making transparent decision and healthy competition tendering, there exists a need for flexible guidance tool for decision support. Aim of this paper is to give a review on current practices of Decision Support Systems (DSS technology in construction tendering processes. Current practices of general tendering processes as applied to the most countries in different regions such as United States, Europe, Middle East and Asia are comprehensively discussed. Applications of Web-based tendering processes is also summarised in terms of its properties. Besides that, a summary of Decision Support System (DSS components is included in the next section. Furthermore, prior researches on implementation of DSS approaches in tendering processes are discussed in details. Current issues arise from both of paper-based and Web-based tendering processes are outlined. Finally, conclusion is included at the end of this paper.
Herrmann, Ivan Tengbjerg; Hauschild, Michael Zwicky; Sohn, Michael D.
The aim of this article is to help confront uncertainty in life cycle assessments (LCAs) used for decision support. LCAs offer a quantitative approach to assess environmental effects of products, technologies, and services and are conducted by an LCA practitioner or analyst (AN) to support...
Bomber, T.M.; Baxter, J.
This paper discusses criteria for selecting analytical support tools for manufacturing engineering in the early phases of product development, and the lessons learned at Sandia National Laboratories in selecting and applying these tools. The IPPD (Integrated Product and Process Design) process requires manufacturing process developers to be involved earlier than ever before in product development. Operating in an IPPD environment, Sandia`s manufacturing engineers were required to develop early estimates of the cost and performance of manufacturing plans. In early pre-production, there are very little actual data on manufacturing processes and almost no detailed data on the performance of various manufacturing process steps. The manufacturing engineer needs the capability to analyze various manufacturing process flows over a large set of assumptions involving capacity, resource requirements (equipment, labor, material, utilities,...), yields, product designs, etc. If the manufacturing process involves many process steps, or if there are multiple products in a single manufacturing area that share resources, or there are multiple part starts resulting in merged flow for final assembly, then this analysis capability must somehow be mechanized. This situation led them to look to modeling and simulation tools for a solution. Example analyses of manufacturing issues for two product sets in the early phases of product development are presented.
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.
Full Text Available Data Mining refers to using a variety of techniques to identify suggest of information or decision making knowledge in thedatabase and extracting these in a way that they can put to use in areas such as decision support, predictions, forecasting and estimation. The healthcare industry collects huge amounts of healthcare data which, unfortunately, are not “mined” to discover hidden information for effective decision making. Discovering relations that connect variables in a database is the subject of data mining. This research has developed a Decision Support in Heart Disease Prediction System (DSHDPS using data mining modeling technique, namely, Naïve Bayes. Using medical profiles such as age, sex, blood pressure and blood sugar it can predict the likelihood of patients getting a heart disease. It is implemented as web based questionnaire application. It can serve a training tool to train nurses and medical students to diagnose patients with heart disease.
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.
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...... as a decision support system (DSS). This COSIMA DSS ensures that the assessment is conducted in a systematic, transparent and explicit way. The modelling principles presented are illuminated with a case study concerning a complex decision problem. The outcome demonstrates the approach as a valuable DSS......, 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....
Zhou, Jianlan; Sun, Koumei
It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.
Watkins, David W.; McKinney, Daene C.
In order to limit the scope of this review, a working definition of a decision support system is needed. L. Adelman has defined decision support systems (DSSs) as "interactive computer programs that utilize analytical methods, such as decision analysis, optimization algorithms, program scheduling routines, and so on, for developing models to help decision makers formulate alternatives, analyze their impacts, and interpret and select appropriate options for implementation" (Adelman , p. 2). Another definition has been offered by S. J. Andriole, who defined decision support as consisting of "any and all data, information, expertise or activities that contribute to option selection" (Andriole , p. 3). A common idea explicit in each of these definitions is that DSSs integrate various technologies and aid in option selection. Implicit in each definition is that these are options for solving relatively large, unstructured problems. Thus, the following working definition of a DSS will be used in this review: A DSS is an integrated, interactive computer system, consisting of analytical tools and information management capabilities, designed to aid decision makers in solving relatively large, unstructured problems.
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.
Full Text Available The scientific production in a certain field shows, in great extent, the research interests in that field. Decision Support Systems are a particular class of information systems which are gaining more popularity in various domains. In order to identify the evolution in time of the publications number, authors, subjects, publications in the Decision Support Systems (DSS field, and therefore the scientific world interest for this field, in November 2010 there have been organized a series of queries on three major international scientific databases: ScienceDirect, IEEE Xplore Digital Library and ACM Digital Library. The results presented in this paper shows that, even the decision support systems research field started in 1960s, the interests for this type of systems grew exponentially with each year in the last decades.
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.
Rodriquez, Luis F.
Decision support systems have been implemented in many applications including strategic planning for battlefield scenarios, corporate decision making for business planning, production planning and control systems, and recommendation generators like those on Amazon.com(Registered TradeMark). Such tools are reviewed for developing a similar tool for NASA's ALS Program. DSS are considered concurrently with the development of the OPIS system, a database designed for chronicling of research and development in ALS. By utilizing the OPIS database, it is anticipated that decision support can be provided to increase the quality of decisions by ALS managers and researchers.
Andersson, Kasper Grann; Roos, Per; Hou, Xiaolin;
in connection with management of the consequences of other types of contaminating incidents, including ‘dirty bomb’ explosions. This would require a number of new modelling features and parametric changes. Also for nuclear power plant preparedness a number of revisions of the decision support systems are called......The paper presents examples of current needs for improvement and extended applicability of the European decision support systems. The systems were originally created for prediction of the radiological consequences of accidents at nuclear installations. They could however also be of great value...
ZhouXingyu; ZhangJiang; LiuYang; XieYanqing; ZhangRan; ZhaoYang; HeZhongxiong
Based on the intelligent decision support system, a new method was presented to defense the catastrophic infectious disease such as SARS, Bird Flu, etc.. By using All Set theory, the decision support system (DSS) model can be built to analyze the noise information and forecast the trend of the catastrophe then to give the method or policy to defend the disease. The model system is composed of four subsystems: the noise analysis subsystem, forecast and simulation subsystem, diagnosis subsystem and second recovery subsystem. They are discussed briefly in this paper. This model can be used not only for SARS but also for other paroxysmal accidences.
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
Full Text Available Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.
Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.
Full Text Available In this article, we describe simulation-based decision support techniques for evaluation of operational plans within effects-based planning. Using a decision support tool, developers of operational plans are able to evaluate thousands of alternative plans against possible courses of events and decide which of these plans are capable of achieving a desired end state. The objective of this study is to examine the potential of a decision support system that helps operational analysts understand the consequences of numerous alternative plans through simulation and evaluation. Operational plans are described in the effects-based approach to operations concept as a set of actions and effects. For each action, we examine several different alternative ways to perform the action. We use a representation where a plan consists of several actions that should be performed. Each action may be performed in one of several different alternative ways. Together these action alternatives make up all possible plan instances, which are represented as a tree of action alternatives that may be searched for the most effective sequence of alternative actions. As a test case, we use an expeditionary operation with a plan of 43 actions and several alternatives for these actions, as well as a scenario of 40 group actors. Decision support for planners is provided by several methods that analyze the impact of a plan on the 40 actors, e.g., by visualizing time series of plan performance. Detailed decision support for finding the most influential actions of a plan is presented by using sensitivity analysis and regression tree analysis. Finally, a decision maker may use the tool to determine the boundaries of an operation that it must not move beyond without risk of drastic failure. The significant contribution of this study is the presentation of an integrated approach for evaluation of operational plans.
De Kleermaeker, Simone; Verkade, Jan
Often, water management decisions are based on hydrological forecasts. These forecasts, however, are affected by inherent uncertainties. It is increasingly common for forecasting agencies to make explicit estimates of these uncertainties and thus produce probabilistic forecasts. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a stricter separation of responsibilities between forecasters and decision maker can be made. However, simply having probabilistic forecasts available is not sufficient to realise the associated benefits. Additional effort is required in areas such as forecast visualisation and communication, decision making in uncertainty and forecast verification. Also, revised separation of responsibilities requires a shift in institutional arrangements and responsibilities. A recent study identified a number of additional issues related to the effective use of probability forecasts. When moving from deterministic to probability forecasting, a dimension is added to an already multi-dimensional problem; this makes it increasingly difficult for forecast users to extract relevant information from a forecast. A second issue is that while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be present. For example, in many cases no estimates of flood damage, of costs of management measures and of damage reduction are available. This paper presents the results of the study, including some suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development of the DSS is outlined.
Sirola, Miki; Lampi, Golan; Parviainen, Jukka
Knowledge-based decision support systems of today are due to development of many decades. More and more methodologies and application areas have been involved during this time. In this paper neural methods are combined with knowledge-based methodologies. Self-Organizing Map (SOM) is used together with rule-based reasoning, and realized in a prototype of a decision support system. This system, which can be used e.g. in fault diagnosis, is based on an earlier study including compatibility analysis. A Matlab-based tool is capable of doing tasks in fault detection and identification. We show with an example how SOM analysis can help decision making in a computerized decision support system. Quantisation error between normal data and error data is one important methodological tool in this analysis. This kind of decision making is needed for instance in control room in state monitoring of a safety critical process in industry. A scenario about a leak in the primary circuit of a BWR nuclear power plant is also shortly demonstrated. (Author)
Full Text Available This paper reports the results of an empirical examination of the effectiveness of one type of knowledge management technology, namely 'contextual knowledge repository', for supporting individual decision makers in a predictive judgement task context. 31 volunteer subjects participated in the study. The results indicate that a given technology was fairly useful, but insufficient to maximally enhance individual decision making. On one hand, subjects were found to extract more knowledge and make significantly smaller decision errors than their notional naive counterparts. On the other hand, subjects tended to extract less knowledge and make significantly larger decision errors compared to notional optimal counterparts. These findings suggest that individuals could potentially benefit from those knowledge management technologies that would provide additional explicit analytical and procedural knowledge, or those that would facilitate sharing of tacit knowledge through interaction with others. Future research is necessary to address these issues.
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.
In order to meet the requirement of separating power plants from power network and that of the competition based power transaction in power market, the pricing decision support system for generation companies (GCPDSS) is built in electricity market. This paper introduces the conception of intelligent decision support system (IDSS) and puts emphasis on the systematical structural framework,work process, design principal, and fundamental function of GCPDSS. The system has the module to analyze the cost, to forecast the demand of power, to construct the pricing strategies, to manage the pricing risk, and to dispatch giving the pricing strategies.The case study illustrates that the friendly window-based user interface of the system enables the user to take full advantage of the capabilities of the system in order to make effective real-time decisions.
Mioc, Darka; Anton, François; Liang, Gengsheng
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.......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...
Salling, Kim Bang
The subject of this thesis is risk analysis and decision support in the context of transport infrastructure assessment. During my research I have observed a tendency in studies of assessing transport projects of overlooking the substantial amount of uncertainties within the decision making process....... Even though vast amounts of money are spent upon preliminary models, environmental investigations, public hearings, etc., the resulting outcome is given by point estimates, i.e. in terms of net present values or benefit-cost rates. This thesis highlights the perspective of risks when assessing...... transport projects, namely by moving from point estimates to interval results. The main focus of this Ph.D. study has been to develop a valid, flexible and functional decision support tool in which risk oriented aspects of project evaluation is implemented. Throughout the study six papers have been produced...
A subjective expected utility policy making centre, managing complex, dynamic systems, needs to draw on the expertise of a variety of disparate panels of experts and integrate this information coherently. To achieve this, diverse supporting probabilistic models need to be networked together, the output of one model providing the input to the next. In this paper we provide a technology for designing an integrating decision support system and to enable the centre to explore and compare the effi...
Hirsch, Gary B.; Homer, Jack (Homer Consulting); Chenoweth, Brooke N.; Backus, George A.; Strip, David R.
As Sandia National Laboratories serves its mission to provide support for the security-related interests of the United States, it is faced with considering the behavioral responses that drive problems, mitigate interventions, or lead to unintended consequences. The effort described here expands earlier works in using healthcare simulation to develop behavior-aware decision support systems. This report focuses on using qualitative choice techniques and enhancing two analysis models developed in a sister project.
Worm, J.M.; Harten, van A.
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 N
Kessel, G.J.T.; Hansen, J.G.
Developments Decision Support Models. In France, the DSS’s Mildi-LIS and MilPV merged to form a new DSS for advisors and potato growers: Mileos. Furthermore, DSS’s for organic production in France (Fredon) and Germany (Oko-SIMPHYT) were developed to help scheduling copper applications within the nat
Wismans, L.J.J.; Romph, de 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 con
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 con
Filatovas, Ernestas; Kurasova, Olga
In this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting different weight coefficient values for the criteria…
Andersson, Kasper Grann; Astrup, Poul; Mikkelsen, Torben;
It is described how ongoing work will extend European standard decision support systems currently integrated in the nuclear power plant preparedness in many countries, to enable estimation of the radiological consequences of atmospheric dispersion of contaminants following a terror attack in a ci...
G. van Valkenhoef (Gert); T. Tervonen (Tommi); T. Zwinkels (Tijs); B. de Brock (Bert); H.L. Hillege (Hans)
textabstractClinical trials are the main source of information for the efficacy and safety evaluation of medical treatments. Although they are of pivotal importance in evidence-based medicine, there is a lack of usable information systems providing data-analysis and decision support capabilities for
Full Text Available The possibility of supporting in decision – making shows an increase in recent years. Based on mathematic simulation tools, knowledge databases, processing methods, medical data and methods, artificial intelligence for coding of the available knowledge and for resolving complex problems arising into clinical practice. Aim: the aim of this review is to present the development of new methods and modern services, in clinical practice and the emergence in their implementation. Data and methods: the methodology that was followed included research of articles that referred to health sector and modern technologies, at the electronic data bases “pubmed” and “medline”. Results: Is a useful tool for medical experts using characteristics and medical data used by the doctors. Constitute innovation for the medical community, and ensure the support of clinical decisions with an overall way by providing a comprehensive solution in the light of the integration of computational decision support systems into clinical practice. Conclusions: Decision Support Systems contribute to improving the quality of health services with simultaneous impoundment of costs (i.e. avoid medical errors
Bergey, Paul; King, Mark
This paper reports on the cross-disciplinary research that resulted in a decision-support tool, Team Machine (TM), which was designed to create maximally diverse student teams. TM was used at a large United States university between 2004 and 2012, and resulted in significant improvement in the performance of student teams, superior overall balance…
Joziasse, J.; Bakker, T.; Eggels, P.G.
A decision support system for treatment of dredged sediments (DSTS) has been constructed, in which the environmental effects of various treatment options applied can be compared. The effects are evaluated by scores on environmental themes like global warming and acidification, using life cycle asses
Oosterhuis, B. [Twente Univ., Enschede (Netherlands). Computer Science Dept.
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 Purpose 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.Methods 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.Results 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.Conclusions Whilst the potential of clinical decision support systems in improving, in particular
Rashidi, Maria; Lemass, Brett; Gibson, Peter
The maintenance of bridges as a key element in transportation infrastructure has become a major concern for asset managers and society due to increasing traffic volumes, deterioration of existing bridges and well-publicised bridge failures. A pivotal responsibility for asset managers in charge of bridge remediation is to identify the risks and assess the consequences of remediation programs to ensure that the decisions are transparent and lead to the lowest predicted losses in recognized constraint areas. The ranking of bridge remediation treatments can be quantitatively assessed using a weighted constraint approach to structure the otherwise ill-structured phases of problem definition, conceptualization and embodiment . This Decision Support System helps asset managers in making the best decision with regards to financial limitations and other dominant constraints imposed upon the problem at hand. The risk management framework in this paper deals with the development of a quantitative intelligent decision support system for bridge maintenance which has the ability to provide a source for consistent decisions through selecting appropriate remediation treatments based upon cost, service life, product durability/sustainability, client preferences, legal and environmental constraints. Model verification and validation through industry case studies is ongoing.
Full Text Available 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. SETTING: 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. METHODS: Scale development study, involving construct, item and scale development, validation and reliability testing. PARTICIPANTS: 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. RESULTS: 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
Panchard, J; Sheshshayee, M S; Papadimitratos, P; Kumar, S; Hubaux, J-P
Wireless sensor networks (WSNs) can be a valuable decision-support tool for farmers. This motivated our deployment of a WSN system to support rain-fed agriculture in India. We defined promising use cases and resolved technical challenges throughout a two-year deployment of our COMMON-Sense Net system, which provided farmers with environment data. However, the direct use of this technology in the field did not foster the expected participation of the population. This made it difficult to develop the intended decision-support system. Based on this experience, we take the following position in this paper: currently, the deployment of WSN technology in developing regions is more likely to be effective if it targets scientists and technical personnel as users, rather than the farmers themselves. We base this claim on the lessons learned from the COMMON-Sense system deployment and the results of an extensive user experiment with agriculture scientists, which we describe in this paper.
Gomoi, Valentin-Sergiu; Dragu, Daniel; Stoicu-Tivadar, Vasile
Development of clinical decision support systems (CDS) is a process which highly depends on the local databases, this resulting in low interoperability. To increase the interoperability of CDS a standard representation of clinical information is needed. The paper suggests a CDS architecture which integrates several HL7 standards and the new vMR (virtual Medical Record). The clinical information for the CDS systems (the vMR) is represented with Topic Maps technology. Beside the implementation of the vMR, the architecture integrates: a Data Manager, an interface, a decision making system (based on Egadss), a retrieving data module. Conclusions are issued.
Marco-Ruiz, Luis; Bellika, Johan Gustav
The interoperability of Clinical Decision Support (CDS) systems with other health information systems has become one of the main limitations to their broad adoption. Semantic interoperability must be granted in order to share CDS modules across different health information systems. Currently, numerous standards for different purposes are available to enable the interoperability of CDS systems. We performed a literature review to identify and provide an overview of the available standards that enable CDS interoperability in the areas of clinical information, decision logic, terminology, and web service interfaces.
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.
Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul
Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.
Full Text Available Decisions about the development of the energy system should take all relevant criteria into account, including costs and health, environmental and climate impacts. As usually no decision alternative fulfils all criteria better than all other alternatives, a weighting between the indicators that show the degree of fulfilment of the criteria, is necessary. In the following the “impact pathway approach” is described that supports decisions by using weighting factors that are derived from measuring or observing the preferences of the population. The methodology is applied to rank technologies for generating electricity according to their social costs, which is a summary indicator comprising simultaneously costs, impacts of air pollution on health and biodiversity and climate impacts.
Chernovita, H. P.; Manongga, D.; Iriani, A.
One of company activities to retain their business is marketing the products which include in acquisition management to get new customers. Insurance contract analysis using ID3 to produce decision tree and rules to be decision support for the insurance company. The decision tree shows 13 rules that lead to contract termination claim. This could be a guide for the insurance company in acquisition management to prevent contract binding with these contract condition because it has a big chance for the customer to terminate their insurance contract before its expired date. As the result, there are several strong points that could be the determinant of contract termination such as: 1) customer age whether too young or too old, 2) long insurance period (above 10 years), 3) big insurance amount, 4) big amount of premium charges, and 5) payment method.
The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.
Volandes, A.E.; Barry, M.J.; Wood, F.; Elwyn, G.
Objective Decision support tools are increasingly using audio-visual materials. However, disagreement exists about the use of audio-visual materials as they may be subjective and biased. Methods This is a literature review of the major texts for documentary film studies to extrapolate issues of obje
Full Text Available Osteoporosis Choice, an encounter decision aid, can engage patients and clinicians in shared decision making about osteoporosis treatment. Its effectiveness compared to the routine provision to clinicians of the patient's estimated risk of fracture using the FRAX calculator is unknown.Patient-level, randomized, three-arm trial enrolling women over 50 with osteopenia or osteoporosis eligible for treatment with bisphosphonates, where the use of Osteoporosis Choice was compared to FRAX only and to usual care to determine impact on patient knowledge, decisional conflict, involvement in the decision-making process, decision to start and adherence to bisphosphonates.We enrolled 79 women in the three arms. Because FRAX estimation alone and usual care produced similar results, we grouped them for analysis. Compared to these, use of Osteoporosis Choice increased patient knowledge (median score 6 vs. 4, p = .01, improved understanding of fracture risk and risk reduction with bisphosphonates (p = .01 and p<.0001, respectively, had no effect on decision conflict, and increased patient engagement in the decision making process (OPTION scores 57% vs. 43%, p = .001. Encounters with the decision aid were 0.8 minutes longer (range: 33 minutes shorter to 3.0 minutes longer. There were twice as many patients receiving and filling prescriptions in the decision aid arm (83% vs. 40%, p = .07; medication adherence at 6 months was no different across arms.Supporting both patients and clinicians during the clinical encounter with the Osteoporosis Choice decision aid efficiently improves treatment decision making when compared to usual care with or without clinical decision support with FRAX results.clinical trials.gov NCT00949611.
paper), one opinion shared is that the rational, economic, deliberate listing/evaluation of all options is NOT representative of how many decision are made. A framework gaining interest lately describes two systems predominantly at work: intuition and reasoning (Kahneman, 2003). Intuition is fast, automatic, and parallel contrasted with the more effortful, deliberative, and sequential reasoning. One of the issues of contention is that considerable research is stacked supporting both sides claiming that intuition is: • A hallmark of expertise responsible for rapid, optimal decisions in the face of adversity • A vulnerability where biases serve as decision traps leading to wrong choices Using seminal studies from a range of domains and tasking, potential solutions for SSA decision support will be offered. Important issues such as managing uncertainty, framing inquiries, and information architecture, and contextual cues will be discussed. The purpose is to provide awareness of the human limitations and capabilities in complex decision making so engineers and designers can consider such factors in their development of SSA tools.
Hao, Angelica Te-Hui; Hsu, Chien-Yeh; Li-Fang, Huang; Jian, Wen-Shan; Wu, Li-Bin; Kao, Ching-Chiu; Lu, Mei-Show; Chang, Her-Kung
The nursing process consists of five interrelated steps: assessment, diagnosis, planning, intervention, and evaluation. In the nursing process, the nurse collects a great deal of data and information. The amount of data and information may exceed the amount the nurse can process efficiently and correctly. Thus, the nurse needs assistance to become proficient in the planning of nursing care, due to the difficulty of simultaneously processing a large set of information. Computer systems are viewed as tools to expand the capabilities of the nurse's mind. Using computer technology to support clinicians' decision making may provide high-quality, patient-centered, and efficient healthcare. Although some existing nursing information systems aid in the nursing process, they only provide the most fundamental decision support--i.e., standard care plans associated with common nursing diagnoses. Such a computerized decision support system helps the nurse develop a care plan step-by-step. But it does not assist the nurse in the decision-making process. The decision process about how to generate nursing diagnoses from data and how to individualize the care plans still reminds of the nurse. The purpose of this study is to develop a pilot structure in electronic nursing record system integrated with international nursing standard for improving the proficiency and accuracy of plan of care in clinical pathway process. The proposed pilot systems not only assist both student nurses and nurses who are novice in nursing practice, but also experts who need to work in a practice area which they are not familiar with.
Wagholikar, Kavishwar; Mangrulkar, Sanjeev; Deshpande, Ashok; Sundararajan, Vijayraghavan
The potential of computer based tools to assist physicians in medical decision making, was envisaged five decades ago. Apart from factors like usability, integration with work-flow and natural language processing, lack of decision accuracy of the tools has hindered their utility. Hence, research to develop accurate algorithms for medical decision support tools, is required. Pioneering research in last two decades, has demonstrated the utility of fuzzy set theory for medical domain. Recently, Wagholikar and Deshpande proposed a fuzzy relation based method (FR) for medical diagnosis. In their case studies for heart and infectious diseases, the FR method was found to be better than naive bayes (NB). However, the datasets in their studies were small and included only categorical symptoms. Hence, more evaluative studies are required for drawing general conclusions. In the present paper, we compare the classification performance of FR with NB, for a variety of medical datasets. Our results indicate that the FR method is useful for classification problems in the medical domain, and that FR is marginally better than NB. However, the performance of FR is significantly better for datasets having high proportion of unknown attribute values. Such datasets occur in problems involving linguistic information, where FR can be particularly useful. Our empirical study will benefit medical researchers in the choice of algorithms for decision support tools.
Huang, Jung; Tien, Yu-Chuan; Lin, Hsuan-Te; Liu, Tzu-Ming; Tung, Ching-Pin
Climate change creates more challenges for water resources management. Due to the lack of sufficient precipitation in Taiwan in fall of 2014, many cities and counties suffered from water shortage during early 2015. Many companies in Hsinchu Science Park were significantly influenced and realized that they need a decision support tool to help them managing water resources. Therefore, a customized computer program was developed, which is capable of predicting the future status of public water supply system and water storage of factories when the water rationing is announced by the government. This program presented in this study for drought decision support (DDSS) is a customized model for a semiconductor company in the Hsinchu Science Park. The DDSS is programmed in Java which is a platform-independent language. System requirements are any PC with the operating system above Windows XP and an installed Java SE Runtime Environment 7. The DDSS serves two main functions. First function is to predict the future storage of Baoshan Reservoir and Second Baoshan Reservoir, so to determine the time point of water use restriction in Hsinchu Science Park. Second function is to use the results to help the company to make decisions to trigger their response plans. The DDSS can conduct real-time scenario simulations calculating the possible storage of water tank for each factory with pre-implementation and post-implementation of those response plans. In addition, DDSS can create reports in Excel to help decision makers to compare results between different scenarios.
Xu, L D
In recent years, the importance of information systems has been identified as a vital issue to continuing success in AIDS intervention and prevention (AIP). The advances in information technology have resulted in integrative information systems including decision support systems (DSS). The concept of DSS for AIP was created at the intersection of two trends. The first trend was a growing belief that AIP information systems are successful in automating operations in AIP programs. The second was a continuing improvement in modeling and software development in the AIP area. This paper presents an integrated DSS for AIP. The system is integrated with a database and achieves its efficiency by incorporating various algorithms and models to support AIP decision processes. The application examples include screening AIDS-risky behaviors, evaluating educational interventions, and scheduling AIP sessions. The implementation results present evidence of the usefulness of the system in AIP.
This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.
Ali, A; Riaz, Zahid
This book is dedicated to applied computational intelligence and soft computing techniques with special reference to decision support in Cyber Physical Systems (CPS), where the physical as well as the communication segment of the networked entities interact with each other. The joint dynamics of such systems result in a complex combination of computers, software, networks and physical processes all combined to establish a process flow at system level. This volume provides the audience with an in-depth vision about how to ensure dependability, safety, security and efficiency in real time by making use of computational intelligence in various CPS applications ranging from the nano-world to large scale wide area systems of systems. Key application areas include healthcare, transportation, energy, process control and robotics where intelligent decision support has key significance in establishing dynamic, ever-changing and high confidence future technologies. A recommended text for graduate students and researche...
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...... – Iberian market operator....
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 control strategies and enhance the performance of the overall network. By taking proactive action deploying traffic management measures, congestion may be prevented or its effects limited. An approach...
Varshney, Rajeev K.; Singh, Vikas K; Hickey, John M.; Xun, Xu; Marshall, David F; Wang, Jun; Edwards, David; Ribaut, Jean-Marcel
To successfully implement genomics-assisted breeding (GAB) in crop improvement programs, efficient and effective analytical and decision support tools (ADSTs) are 'must haves' to evaluate and select plants for developing next-generation crops. Here we review the applications and deployment of appropriate ADSTs for GAB, in the context of next-generation sequencing (NGS), an emerging source of massive genomic information. We discuss suitable software tools and pipelines for marker-based approac...
杨保安; 马云飞; 俞莲
Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.
Keshavjee, K; Holbrook, AM; Lau, E; Esporlas-Jewer, I; Troyan, S
The COMPETE III Vascular Disease Tracker (C3VT) is a personalized, Web-based, clinical decision support tool that provides patients and physicians access to a patient’s 16 individual vascular risk markers, specific advice for each marker and links to best practices in vascular disease management. It utilizes the chronic care model1 so that physicians can better manage patients with chronic diseases. Over 1100 patients have been enrolled into the COMPETE III study to date.
Hilletofth, Per; Lättilä, Lauri
Purpose – The purpose of this paper is to investigate the benefits and the barriers of agent based decision support (ABDS) systems in the supply chain context. Design/methodology/approach – Two ABDS systems have been developed and evaluated. The first system concerns a manufacturing supply chain while the second concerns a service supply chain. The systems are based on actual case companies. Findings – This research shows that the benefits of ABDS systems in the supply chain context include t...
Fienen, M. N.; Masterson, J.; Plant, N. G.; Gutierrez, B. T.; Thieler, E. R.
Bayesian decision networks (BDN) have long been used to provide decision support in systems that require explicit consideration of uncertainty; applications range from ecology to medical diagnostics and terrorism threat assessments. Until recently, however, few studies have applied BDNs to the study of groundwater systems. BDNs are particularly useful for representing real-world system variability by synthesizing a range of hydrogeologic situations within a single simulation. Because BDN output is cast in terms of probability—an output desired by decision makers—they explicitly incorporate the uncertainty of a system. BDNs can thus serve as a more efficient alternative to other uncertainty characterization methods such as computationally demanding Monte Carlo analyses and others methods restricted to linear model analyses. We present a unique application of a BDN to a groundwater modeling analysis of the hydrologic response of Assateague Island, Maryland to sea-level rise. Using both input and output variables of the modeled groundwater response to different sea-level (SLR) rise scenarios, the BDN predicts the probability of changes in the depth to fresh water, which exerts an important influence on physical and biological island evolution. Input variables included barrier-island width, maximum island elevation, and aquifer recharge. The variability of these inputs and their corresponding outputs are sampled along cross sections in a single model run to form an ensemble of input/output pairs. The BDN outputs, which are the posterior distributions of water table conditions for the sea-level rise scenarios, are evaluated through error analysis and cross-validation to assess both fit to training data and predictive power. The key benefit for using BDNs in groundwater modeling analyses is that they provide a method for distilling complex model results into predictions with associated uncertainty, which is useful to decision makers. Future efforts incorporate
Hankach, Pierre; CHACHOUA, Mohamed; MARTIN, Jean Marc; GOYAT, YANN
In this paper, a decision support system for managing urban building sites nuisances is described. First, the decision process for nuisance management is studied in order to understand the use context of the decision support system. Two levels are identified where decision support is appropriate : at the territorial level for the administrator of the public space and at the building site level for the project owner. The decision support system at the former level is described. The interactio...
In this study the effectiveness of multi-attribute utility (MAU) decision support in groups is evaluated for personnel selection problems differing in complexity. Subjects were asked to make an initial individual decision with or without MAU decision support. Next individuals formed small groups and were asked to reach a decision about the same problem. Groups received either MAU support or no support. Results show that for relatively simple problems the most effective method is to provide subjects with both individual and group decision support. Here, decision support had a clear impact on subjects' preferences and the level of agreement between group members. In addition, satisfaction with the decision and the decision procedure was relatively high. Overall, decision support improved communication; subjects reported to find the problem easier, to have more influence on the group decision, and to find it easier to express their opinions. For more complex problems, however, decision making without group support (whether preceded by individual support or not) was evaluated most favorably. Individual decision support in this condition was sometimes better than no support; i.e., there was a lower reported problem difficulty, a higher satisfaction with the group decision, and a higher reported influence on the group decision. The effectiveness of group MAU decision support for complex problems was evaluated less favorably.
Fienen, Michael N.; Masterson, John P.; Plant, Nathaniel G.; Gutierrez, Benjamin T.; Thieler, E. Robert
Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.
White, Douglas C
How can investments that would potentially improve a manufacturing plant's decision process be economically justified? What is the value of "better information," "more flexibility," or "improved integration" and the technologies that provide these effects? Technology investments such as improved process modelling, new real time historians and other databases, "smart" instrumentation, better data analysis and visualization software, and/or improved user interfaces often include these benefits as part of their valuation. How are these "soft" benefits to be converted to a quantitative economic return? Quantification is important if rational management decisions are to be made about the correct amount of money to invest in the technologies, and which technologies to choose among the many available ones. Modelling the plant operational decision cycle-detect, analyse, forecast, choose and implement--provides a basis for this economic quantification. In this paper a new economic model is proposed for estimation of the value of decision support investments based on their effect upon the uncertainty in forecasting plant financial performance. This model leads to quantitative benefit estimates that have a realistic financial basis. An example is presented demonstrating the application of the method.
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.
VonPlinsky, Michael J.; Crowder, Ed
The Decision Integration and Support Environment (DISE) is a Bayesian network (BN) based modeling and simulation of the target nomination and aircraft tasking decision processes. DISE operates in event driven interactions with FTI's AOC model, being triggered from within the Time Critical Target (TCT) Operations cell. As new target detections are received by the AOC from off-board ISR sources and processed by the Automatic Target Recognition (ATR) module in the AOC, DISE is called to determine if the target should be prosecuted, and if so, which of the available aircraft should be tasked to attack it. A range of decision criteria, with priorities established off-line and input into the tool, are associated with this process. DISE, when running in its constructive mode, automatically selects the best-suited aircraft and assigns the new target. In virtual mode, with a human operator, DISE presents the user with a suitability ranked list of the available aircraft for assignment. Recent DISE enhancements are applying this concept to the prioritization and scheduling of ISR support requests from Users to support both latent and dynamic tasking and scheduling of both space-based and airborne ISR assets.
Song, M.; Li, W.; Zhou, X.
In the era of big data, polar sciences have already faced an urgent demand of utilizing intelligent approaches to support precise and effective spatiotemporal decision-making. Service-oriented cyberinfrastructure has advantages of seamlessly integrating distributed computing resources, and aggregating a variety of geospatial data derived from Earth observation network. This paper focuses on building a smart service-oriented cyberinfrastructure to support intelligent question answering related to polar datasets. The innovation of this polar cyberinfrastructure includes: (1) a problem-solving environment that parses geospatial question in natural language, builds geoprocessing rules, composites atomic processing services and executes the entire workflow; (2) a self-adaptive spatiotemporal filter that is capable of refining query constraints through semantic analysis; (3) a dynamic visualization strategy to support results animation and statistics in multiple spatial reference systems; and (4) a user-friendly online portal to support collaborative decision-making. By means of this polar cyberinfrastructure, we intend to facilitate integration of distributed and heterogeneous Arctic datasets and comprehensive analysis of multiple environmental elements (e.g. snow, ice, permafrost) to provide a better understanding of the environmental variation in circumpolar regions.
Tidwell, Vincent Carroll; Malczynski, Leonard A.; Kobos, Peter Holmes; Castillo, Cesar; Hart, William Eugene; Klise, Geoffrey T.
Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 39% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. Coupled to this water use is the required pumping, conveyance, treatment, storage and distribution of the water which requires on average 3% of all electric power generated. While water and energy use are tightly coupled, planning and management of these fundamental resources are rarely treated in an integrated fashion. Toward this need, a decision support framework has been developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to identify trade-offs, and 'best' alternatives among a broad list of energy/water options and objectives. The decision support framework is formulated in a modular architecture, facilitating tailored analyses over different geographical regions and scales (e.g., national, state, county, watershed, NERC region). An interactive interface allows direct control of the model and access to real-time results displayed as charts, graphs and maps. Ultimately, this open and interactive modeling framework provides a tool for evaluating competing policy and technical options relevant to the energy-water nexus.
Sanfilippo, Antonio P.; Cowell, Andrew J.; Malone, Elizabeth L.; Riensche, Roderick M.; Thomas, James J.; Unwin, Stephen D.; Whitney, Paul D.; Wong, Pak C.
A main challenge we face in fostering sustainable growth is to anticipate outcomes through predictive and proactive across domains as diverse as energy, security, the environment, health and finance in order to maximize opportunities, influence outcomes and counter adversities. The goal of this paper is to present new methods for anticipatory analytical thinking which address this challenge through the development of a multi-perspective approach to predictive modeling as a core to a creative decision making process. This approach is uniquely multidisciplinary in that it strives to create decision advantage through the integration of human and physical models, and leverages knowledge management and visual analytics to support creative thinking by facilitating the achievement of interoperable knowledge inputs and enhancing the user’s cognitive access. We describe a prototype system which implements this approach and exemplify its functionality with reference to a use case in which predictive modeling is paired with analytic gaming to support collaborative decision-making in the domain of agricultural land management.
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.
Elwyn, G.; Kreuwel, I.; Durand, M.A.; Sivell, S.; Joseph-Williams, N.; Evans, R.; Edwards, A.
OBJECTIVE: Significant advances have been made in the development of decision support interventions, also called decision aids, for patients facing difficult or uncertain decisions. However, challenges related to the definition, the theoretical underpinnings, the relative contribution of different c
Jensen, Rune Møller; Leknes, Eilif; Bebbington, Thomas
Low cost containerized shipping requires high quality stowage plans. Scalable stowage planning optimization algorithms have been developed recently. All of these algorithms, however, produce monolithic solutions that are hard for stowage coordinators to modify, which is necessary in practice due ...... fast, complete, and backtrack-free decision support. Our computational results show that the approach can solve real-sized instances when breaking symmetries among similar containers...
DSS decision-support system EBO effects-based operations EBP effects-based planning HBP heuristics and biases paradigm IIASA International Institute for...policy among citizens); 15 The work done by the International Institute for Applied Systems Analysis ( IIASA ) in Austria is basically the same as what...www.cbo.gov. Although some CBO documents are exclusively focused on economic issues, many are substantial policy analyses. IIASA also has a great many
Kamarudin, Anis Aklima; Othman, Zulaiha Ali; Sarim, Hafiz Mohd
This paper discuss about the role of Decision Support Tool in Travelling Salesman Problem (TSP) for helping the researchers who doing research in same area will get the better result from the proposed algorithm. A study has been conducted and Rapid Application Development (RAD) model has been use as a methodology which includes requirement planning, user design, construction and cutover. Water Flow Algorithm (WFA) with initialization technique improvement is used as the proposed algorithm in this study for evaluating effectiveness against TSP cases. For DST evaluation will go through usability testing conducted on system use, quality of information, quality of interface and overall satisfaction. Evaluation is needed for determine whether this tool can assists user in making a decision to solve TSP problems with the proposed algorithm or not. Some statistical result shown the ability of this tool in term of helping researchers to conduct the experiments on the WFA with improvements TSP initialization.
Utama, D. N.; Zaki, F. A.; Munjeri, I. J.; Putri, N. U.
Several ways and efforts have been already conducted to formally solve the road traffic congestion. However, the objective strategy type of road traffic engineering could not be proven truly. Try and error is one inefficient way in road traffic engineering to degrade the level of congestion. The combination between fuzzy-logic and water flow algorithm methods (called FWFA) was used as a main method to construct the decision support system (DSS) for selecting the objective strategy in road traffic engineering. The proposed DSS can suggest the most optimal strategy decision in road traffic engineering. Here, a main traffic road of Juanda in area Ciputat, Tangerang Selatan, province Banten, Indonesia; was selected as a research object in this study. The constructed DSS for road traffic engineering was structurally delivered in this paper.
biomass resource availability is expected to decline by 10% until 2020 but with regional variation. We find that large scale biogas producers enjoy 16% lower transportation costs than small biogas producers. It is argued that biogas producers need to see themselves as agro-based retailers and accordingly...... 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...... are developed through this PhD project, may be combined into integrated spatial planning and decision support systems with a human expert based user interface....
Full Text Available Many European metallurgical companies are forced to import iron ore from remote destinations. For these companies it is necessary to determine the amount of iron ore that will have to be ordered and to create such a delivery schedule so that the continuous operation of blast-furnace plant is not disrupted and there is no exceedingly large stock of this raw material. The objective of this article is to design the decision support system for iron ore supply which would effi ciently reduce uncertainty and risk of that decision-making. The article proposes a hybrid intelligent system which represents a combination of diff erent artifi cial intelligence methods with dynamic simulation technique for that purpose.
Khajeh-Hosseini, Ali; Bogaerts, Jurgen; Teregowda, Pradeep
This paper describes two tools that aim to support decision making during the migration of IT systems to the cloud. The first is a modeling tool that produces cost estimates of using public IaaS clouds. The tool enables IT architects to model their applications, data and infrastructure requirements in addition to their computational resource usage patterns. The tool can be used to compare the cost of different cloud providers, deployment options and usage scenarios. The second tool is a spreadsheet that outlines the benefits and risks of using IaaS clouds from an enterprise perspective; this tool provides a starting point for risk assessment. Two case studies were used to evaluate the tools. The tools were useful as they informed decision makers about the costs, benefits and risks of using the cloud.
CERN (European Organization for Nuclear Research) is the world's leading particle physics research laboratory. It is a truly global organization, collaborating with more than 500 research institutes around the world. The laboratory is currently working on the construction of its largest and most complex scientific instrument ever, the Large Hadron Collider (LHC), due for completion in 2007. Under the current economic climate, however, the laboratory, along with many other businesses and organizations, is having to face shrinking resources and reduced staff levels. Since CERN is expected to continue to grow, it will be forced to achieve higher productivity with fewer resources. In the area of administrative information systems, the situation described above led us to the decision to use Oracle's Data Warehousing concepts and J2EE for the implementation of a scalable and flexible financial decision support system with a low maintenance cost. This paper outlines the experiences drawn from this implementation, fr...
The maintenance process has undergone several major developments that have led to proactive considerations and the transformation from the traditional "fail and fix" practice into the "predict and prevent" proactive maintenance methodology. The anticipation action, which characterizes this proactive maintenance strategy is mainly based on monitoring, diagnosis, prognosis and decision-making modules. Oil monitoring is a key component of a successful condition monitoring program. It can be used as a proactive tool to identify the wear modes of rubbing parts and diagnoses the faults in machinery. But diagnosis relying on oil analysis technology must deal with uncertain knowledge and fuzzy input data. Besides other methods, Bayesian Networks have been extensively applied to fault diagnosis with the advantages of uncertainty inference; however, in the area of oil monitoring, it is a new field. This paper presents an integrated Bayesian network based decision support for maintenance of diesel engines.
This chapter examines data quality management (DQM) and information governance (IG) of electronic decision support (EDS) systems so that they are safe and fit for use by clinicians and patients and their carers. This is consistent with the ISO definition of data quality as being fit for purpose. The scope of DQM & IG should range from data creation and collection in clinical settings, through cleaning and, where obtained from multiple sources, linkage, storage, use by the EDS logic engine and algorithms, knowledge base and guidance provided, to curation and presentation. It must also include protocols and mechanisms to monitor the safety of EDS, which will feedback into DQM & IG activities. Ultimately, DQM & IG must be integrated across the data cycle to ensure that the EDS systems provide guidance that leads to safe and effective clinical decisions and care.
Rüping, Stefan; Anguita, Alberto; Bucur, Anca; Cirstea, Traian Cristian; Jacobs, Björn; Torge, Antje
Clinical decision support (CDS) systems promise to improve the quality of clinical care by helping physicians to make better, more informed decisions efficiently. However, the design and testing of CDS systems for practical medical use is cumbersome. It has been recognized that this may easily lead to a problematic mismatch between the developers' idea of the system and requirements from clinical practice. In this paper, we will present an approach to reduce the complexity of constructing a CDS system. The approach is based on an ontological annotation of data resources, which improves standardization and the semantic processing of data. This, in turn, allows to use data mining tools to automatically create hypotheses for CDS models, which reduces the manual workload in the creation of a new model. The approach is implemented in the context of EU research project p-medicine. A proof of concept implementation on data from an existing Leukemia study is presented.
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
Adler, Richard M.
Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.
Seamon Matthew J
Full Text Available Abstract Background Online drug information databases are used to assist in enhancing clinical decision support. However, the choice of which online database to consult, purchase or subscribe to is likely made based on subjective elements such as history of use, familiarity, or availability during professional training. The purpose of this study was to evaluate clinical decision support tools for drug information by systematically comparing the most commonly used online drug information databases. Methods Five commercially available and two freely available online drug information databases were evaluated according to scope (presence or absence of answer, completeness (the comprehensiveness of the answers, and ease of use. Additionally, a composite score integrating all three criteria was utilized. Fifteen weighted categories comprised of 158 questions were used to conduct the analysis. Descriptive statistics and Chi-square were used to summarize the evaluation components and make comparisons between databases. Scheffe's multiple comparison procedure was used to determine statistically different scope and completeness scores. The composite score was subjected to sensitivity analysis to investigate the effect of the choice of percentages for scope and completeness. Results The rankings for the databases from highest to lowest, based on composite scores were Clinical Pharmacology, Micromedex, Lexi-Comp Online, Facts & Comparisons 4.0, Epocrates Online Premium, RxList.com, and Epocrates Online Free. Differences in scope produced three statistical groupings with Group 1 (best performers being: Clinical Pharmacology, Micromedex, Facts & Comparisons 4.0, Lexi-Comp Online, Group 2: Epocrates Premium and RxList.com and Group 3: Epocrates Free (p Conclusion Online drug information databases, which belong to clinical decision support, vary in their ability to answer questions across a range of categories.
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
Nielsen, Ulrik Dam
Onboard decision support systems (DSS) are used to increase the operational safety of ships. Ideally, DSS can estimate - in the statistical sense - future ship responses on a time scale of the order of 1-3 hours taking into account speed and course changes. The calculations depend on both...... operational and environmental parameters that are known only in the statistical sense. The present paper suggests a procedure to incorporate random variables and associated uncertainties in calculations of outcrossing rates, which are the basis for risk-based DSS. The procedure is based on parallel system...
Pertl, Michael; Weckesser, Tilman; Rezkalla, Michel M.N.
The paper presents a decision support tool for transient stability preventive control contributing to increased situation awareness of control room operators by providing additional information about the state of the power system in terms of transient stability. A time-domain approach is used...... to assess the transient stability for potentially critical faults. Potential critical fault locations are identified by a critical bus screening through analysis of pre-disturbance steady-state conditions. The identified buses are subject to a fast critical contingency screening determining the actual....... The effectiveness of the proposed method is demonstrated on a standard nine-bus and the New England test system...
Full Text Available In this paper, a collaborative DSS Model for health care systems and results obtained are described. The proposed framework  embeds expert knowledge within DSS to provide intelligent decision support, and implements the intelligent DSS using collaboration technologies. The problem space contains several Hub and Spoke networks. Information about such networks is dynamically captured and represented in a Meta-data table. This master table enables collaboration between any two networks in the problem space, through load transfer, between them. In order to show the collaboration the sample database of 15 health care centers is taken assuming that there are 5 health care centers in one network.
Ito, M; Ramos, M P; Chern, M S; Espósito, S R; Carmagnani, M I; Cunha, I C; Piveta, V M; Nespoulos, E; Iwasa, A T; Anção, M S
The present work proposes a Decision Support System for nursing procedures: SAPIEN-Tx. The discussion includes the acquisition, modeling , and implementation of nursing expertise professionals in Renal Transplant. It was developed to obtain better quality healthcare services, as well as an effective contribution to the nursing professional in the global assistance of their clientele. We used the KADS methodology to develop the system knowledge base. This methodology permitted us to perform the knowledge modeling with quality and organization. In opposition to the old method, errors were detected before the implementation, avoiding possible modification on the whole project structure.
Lewis Brooks, Anthony
at the core of an open-ended custom system where unencumbered residual function manipulates selected audiovisual and robotic feedback that results in afferent-efferent neural feedback loop closure. Such loop closure is hypothesized as the reason why such interactive system environments are so effective......-support of adjustment of difficulty encountered. To date facilitator role has included manual parameter manipulation of interface to affect an invisible active zone quality (typically, sensitivity or location) and/or content quality. Inaction human adjustment-decisions are according to interpretation of user state...
0542 IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBEN ETIca , VOL SMC-10, NO. 12, DBCDMER 1980 891 REFERENCES The options assumed available to the...nore gen - and decision support is strong; consequently there erally determining the set P2 9H x n, where (7’, is much motivation to seek an approach...1. 8 -h* a. o" 6*81t & aS t hSO.418 bal-.. 0) * 11. $500 $750 3 1.0 .5 3/S 5-1000.0 A - $0 IS) C.-. SiLaiata 6 Decisin treefor ~ Fig. 3. Gen . probi
Rojas-Palma, C.; Madsen, H.; Gering, F.;
Model predictions for a rapid assessment and prognosis of possible radiological consequences after an accidental release of radionuclides play an important role in nuclear emergency management. Radiological observations, e.g. dose rate measurements. can be used to improve such model predictions....... 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...
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.
Full Text Available Despite the well-established benefits of home energy retrofits (HER, its adoption has faced huge challenges. Though homeowners typically depend on energy practitioners for HER advice, previous work by the researchers has identified the inadequateness of such information as a barrier. Using an earlier developed information model, an energy retrofit intelligent decision support system (ERIDSS, that integrates expert knowledge with quantitative information to provide homeowners with accurate information for decision-making, was developed. This paper identifies the key components of the proposed ERIDSS, develops rules for relevant energy retrofit expert knowledge to be employed in the knowledge-based system of the proposed ERIDSS, develops the ERIDSS for decision-making for home energy retrofits, and demonstrates the application of the ERIDSS using a pilot system on two test homes. The quantitative information was obtained from published sources and the U.S. Department of Energy’s cost database, and the expert knowledge was obtained through the application of the modified Delphi technique and job shadowing of energy auditors and retrofit contractors. The research contributes to improving the adoption of energy retrofits by homeowners, assisting industry practitioners with the corroboration of knowledge/information they provide to homeowners in order to reduce homeowner bias, providing a good understanding of available implicit domain knowledge through the development of six knowledge-based modules, and the development of a system and approach that may be replicated in other domains.
周章玉; 成思危; 华贲; 曾敏刚; 尹清华
Most studies on investment evaluation mainly focus on enterprise economic benefits only, without process operability and sustainability considered. In this paper, we suggest that investment evaluation in process industries should be executed under three strategic objectives--enterprise benefits, social benefits and customer benefits. A systematic investment evaluation and decision-making method with a four-step procedure based on the analytic hierarchy process (AHP) is proposed to evaluate various qualitative and quantitative elements with various criteria. At the first step, the decision hierarchy is constructed under the three strategic objectives. Second, pair-wise comparison is utilized to evaluate the weights of elements and criteria. Third, qualitative elements are quantified by pair-wise comparison and quantitative elements are re-scaled by a uniform criterion. At the last, the best choice is made through synthesizing values upward in the hierarchy. An investment decision support system (DSS) is developed based on Microsoft Excel, and applied to a retrofit investment of united fluid catalytic cracking(FCC) and liquefied gas separation process in a refinery plant.
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......). 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...
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.
Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.
Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this
Decision Support Systems (DSS) have a vital role to play in today's scenario for Patient Care. They can embody a vast knowledge not normally found in one individual where diagnosis and treatment are involved. This paper highlights the training in minute details and precise mathematics needed in a successful DSS and indicates how such attention-to-detail was instilled into the writer as a result of working with Alan Turing and Emil Wolf who have both since achieved world-wide recognition in their own fields as a result of international publicity by the current writer. The article discusses four Decision Support Systems written by the present writer all of which have been shown to improve patient treatment and care, and which are of such complexity that, without their use, patient care would fall short of optimum. The Systems considered are those for Intensive Care Units, Cardiovascular Surgery, a Programmed Investigation Unit, and Diagnosis of Congenital Abnormalities. All these Systems have performed better than the human alternatives and have shown their value in the improvement of patient care.
Alexandra Ruiz G.
Full Text Available Decision support systems (DSS and e-business (EB have emerged as separate areas. However, currently, and for some years now, DSS and EB have become merged to provide customers with greater benefits and added value. There are different types of DSS and different categories and business models for EB; one area’s applicability to the other thus expands the possible combi- nations which can arise from such different categories. Some representative examples would include auction sites which, through applying intelligent agents, can learn about which products to offer or when and where to sell them; DSS allow a company’s in- formation avilable in web portals for customers and employees to be accessed in a controlled way and decisions thus made; vir- tual stores may be positively affected by data mining and data warehousing being applied; complex algorithms could be used in customer relationship management for predicting and analysing “what would happen if” to identify revenue opportunities in com- petitive markets; and a wide range of other applications where imagination is the limit. Research into DSS / BE must be ongoing due to the constant emergence of new business models and DSS subsystems. Applications can be varied and provide bi-directio- nal support for each one. New interaction mechanisms and efforts to satisfy customers are also the focus of inspiration for new applications for DSS systems in EB.
Alpert, J. C.
model output offering access to probability and calibrating information for real time decision making. The aggregation content server reports over ensemble component and forecast time in addition to the other data dimensions of vertical layer and position for each variable. The unpacking, organization and reading of many binary packed files is accomplished most efficiently on the server while weather element event probability calculations, the thresholds for more accurate decision support, or display remain for the client. Our goal is to reduce uncertainty for variables of interest, e.g, agricultural importance. The weather service operational GFS model ensemble and short range ensemble forecasts can make skillful probability forecasts to alert users if and when their selected weather events will occur. A description of how this framework operates and how it can be implemented using existing NOMADS content services and applications is described.
Herrmann, Ivan Tengbjerg
for the application of decision support and evaluation of uncertainty in LCA. From a decision maker’s (DM’s) point of view there are at least three main “illness” factors influencing the quality of the information that the DM uses for making decisions. The factors are not independent of each other, but it seems...... the different steps. A deterioration of the quality in each step is likely to accumulate through the statistical value chain in terms of increased uncertainty and bias. Ultimately this can make final decision support problematic. The "Law of large numbers" (LLN) is the methodological tool/probability theory......) refrain from making a decision based on an LCA and thus support a decision on other parameters than the LCA environmental parameters. Conversely, it may in some decision support contexts be acceptable to base a decision on highly uncertain information. This all depends on the specific decision support...
Biscarini, C.; di Francesco, S.; Manciola, P.
The focus of the present document is on specific decision-making aspects of flood risk analysis. A flood is the result of runoff from rainfall in quantities too great to be confined in the low-water channels of streams. Little can be done to prevent a major flood, but we may be able to minimize damage within the flood plain of the river. This broad definition encompasses many possible mitigation measures. Floodplain management considers the integrated view of all engineering, nonstructural, and administrative measures for managing (minimizing) losses due to flooding on a comprehensive scale. The structural measures are the flood-control facilities designed according to flood characteristics and they include reservoirs, diversions, levees or dikes, and channel modifications. Flood-control measures that modify the damage susceptibility of floodplains are usually referred to as nonstructural measures and may require minor engineering works. On the other hand, those measures designed to modify the damage potential of permanent facilities are called non-structural and allow reducing potential damage during a flood event. Technical information is required to support the tasks of problem definition, plan formulation, and plan evaluation. The specific information needed and the related level of detail are dependent on the nature of the problem, the potential solutions, and the sensitivity of the findings to the basic information. Actions performed to set up and lay out the study are preliminary to the detailed analysis. They include: defining the study scope and detail, the field data collection, a review of previous studies and reports, and the assembly of needed maps and surveys. Risk analysis can be viewed as having many components: risk assessment, risk communication and risk management. Risk assessment comprises an analysis of the technical aspects of the problem, risk communication deals with conveying the information and risk management involves the decision process
Frost, C. R.; Enomoto, F. Y.; D'Ortenzio, M. V.; Nguyen, Q. B.
NASA developed the Collaborative Decision Environment (CDE), the ground-based component of its Intelligent Mission Management (IMM) technology for science missions employing long endurance unmanned aerial vehicles (UAVs). The CDE was used to support science mission planning and decision-making for a NASA- and U.S. Forest Service-sponsored mission to monitor wildfires in the western United States using a multi- spectral imager flown onboard the General Atomics Altair UAV in summer of 2006. The CDE is a ground-based system that provides the mission/science team with situational awareness, collaboration, and decision tools. The CDE is used for pre-flight planning, mission monitoring, and visualization of acquired data. It integrates external data products used for planning and executing a mission, such as weather, large wildfire locations, satellite-derived fire detection data, temporarily restricted airspace, and satellite imagery. While a prototype CDE was developed as a Java-based client/server application in 2004-2005, the team investigated the use of Google Earth to take advantage of its 3-D visualization capabilities, friendly user interface, and enhanced graphics performance. External data is acquired via the Internet by leveraging established and emerging Open Geospatial Consortium (OGC) standards and is re-formatted into the Keyhole Markup Language (KML) specification used by Google Earth. Aircraft flight position and sensor data products are relayed from the instrument ground station to CDE servers where they are made available to users. An instant messaging chat server is used to facilitate real-time communication between remote users. This paper will present an overview of the CDE system architecture, and discuss how science user input was crucial to shaping and developing the system. Examples from the UAV mission will be used to illustrate the presentation. Plans for future development work to improve mission operations, such as integration with
Full Text Available The Water Distribution Networks (WDN are managed by experts, who, over the years of their association and responsibility, acquire an empirical knowledge of the system and, characteristically, this knowledge remains largely confined to their respective personal domains. In the event of any new information and/or emergence of a new problem, these experts apply simple heuristics to design corrective measures and cognitively seek to predict network performance. The human interference leads to inefficient utilization of resources and unfair distribution. Researchers over the past, have tried to address to the problem and they have applied Artificial Intelligence (AI tool to automate the decision process and encode the heuristic rules. The application of AI tool in the field of WDN management is meager. This paper describes a component of an ongoing research initiative to investigate the potential application of artificial intelligence package CLIPS (short for C Language Integrated Production System, developed at NASA/Johnson Space Center in the development of an expert decision support system for management of a water distribution network. The system aims to meet several concerns of modern water utility managers as it attempts to formalize operational and management experiences, and provides a frame work for assisting water utility managers even in the absence of expert personnel.
Ahmed Abou Elfetouh Saleh
Full Text Available In the molecular era the management of cancer is no more a plan based on simple guidelines. Clinical findings, tumor characteristics, and molecular markers are integrated to identify different risk categories, based on which treatment is planned for each individual case. This paper aims at developing a fuzzy decision support system (DSS to guide the doctors for the risk stratification of breast cancer, which is expected to have a great impact on treatment decision and to minimize individual variations in selecting the optimal treatment for a particular case. The developed system was based on clinical practice of Oncology Center Mansoura University (OCMU. This system has six input variables (Her2, hormone receptors, age, tumor grade, tumor size, and lymph node and one output variable (risk status. The output variable is a value from 1 to 4; representing low risk status, intermediate risk status and high risk status. This system uses Mamdani inference method and simulation applied in MATLAB R2009b fuzzy logic toolbox.
GUO Yinqiao; ZHAO Chuande; WANG Wenxin; LI Cundong
Based on the relationship between crops and circumstances,a dynamic knowledge model for maize management with wide applicability was developed using the system method and mathematical modeling technique.With soft component characteristics incorporated,a component and digital knowledge model-based decision support system for maize management was established on the Visual C++platform.This system realized six major functions:target yield calculation,design of pre-sowing plan,prediction of regular indices,real-time management control,expert knowledge reference and system administration.Cases were studied on the target yield knowledge model with data sets that include different eco-sites,yield levels of the last three years,and fertilizer and water management levels.The results indicated that this system overcomes the shortcomings of traditional expert systems and planting patterns,such as sitespecific conditions and narrow applicability,and can be used more under different conditions and environments.This system provides a scientific knowledge system and a broad decision-making tool for maize management.
Luiz Dourado Dias Junior
Full Text Available Mining software repositories (MSR research had significantly contributed to software engineering.However, MSR results integration across repositories is a recent concern that is getting more attentionfrom researchers each day. Some noticeable research in this sense is related to the approximation betweenMSR and semantic web, specially linked data approaches which makes it possible to integrate repositoriesand mined results. Manifested that way, we believe that current research is not fully addressing thepractical integration of MSR results, specially, in software engineering due to not considering that theseresults needs to be integrated to the tools as assistance to activity performers, as a kind of decision makingsupport. Based on this statement this research describes an approach, named Sambasore, which isconcerned with MSR results inter-repository integration and also to decision making support processes,based on tool assistance modelling. To show its feasibility we describe the main concepts, some relatedworks and also a proof of concept experiment applied to a software process modelling tool named SpiderPM.
V. A. Rybak
Full Text Available The article presents the results of an analytical review and comparison of the most common managerial decision support technologies: the analytic hierarchy method, neural networks, fuzzy set theory, genetic algorithms and neural-fuzzy modeling. The advantages and disadvantages of these approaches are shown. Determine the scope of their application. It is shown that the hierarchy analysis method works well with the full initial information, but due to the need for expert comparison of alternatives and the selection of evaluation criteria has a high proportion of subjectivity. For problems in the conditions of risk and uncertainty prediction seems reasonable use of the theory of fuzzy sets and neural networks. It is also considered technology collective decision applied both in the general election, and the group of experts. It reduces the time for conciliation meetings to reach a consensus by the preliminary analysis of all views submitted for the plane in the form of points. At the same time the consistency of opinion is determined by the distance between them.
Wanderer, Jonathan P; Ehrenfeld, Jesse M
Clinical decision support (CDS) systems are being used to optimize the increasingly complex care that our health care system delivers. These systems have become increasingly important in the delivery of perioperative care for patients undergoing cardiac, thoracic, and vascular procedures. The adoption of perioperative information management systems (PIMS) has allowed these technologies to enter the operating room and support the clinical work flow of anesthesiologists and operational processes. Constructing effective CDS systems necessitates an understanding of operative work flow and technical considerations as well as achieving integration with existing information systems. In this review, we describe published examples of CDS for PIMS, including support for cardiopulmonary bypass separation physiological alarms, β-blocker guideline adherence, enhanced revenue capture for arterial line placement, and detection of hemodynamic monitoring gaps. Although these and other areas are amenable to CDS systems, the challenges of latency and data reliability represent fundamental limitations on the potential application of these tools to specific types of clinical issues. Ultimately, we expect that CDS will remain an important tool in our efforts to optimize the quality of care delivered.
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.
Pamela J. Fletcher
Full Text Available The decline in coral reef health presents a complex management issue. While several causes of decline have been identified and are under continued study, it is often difficult to discern management actions necessary to address multiple near- and far-field stressors to these ecosystems. As a result, resource managers seek tools to improve the understanding of ecosystem condition and to develop management responses to reduce local and regional pressures in the wake of larger, global impacts. A research study conducted from 2010 to 2014 in southeast Florida, USA consisted of two objectives: (1 conduct a needs assessment survey with coral reef and marine resource managers to identify data needs and the preferred design and delivery of climate information; and (2 develop and evaluate prototype decision support tools. The needs assessment process was helpful for identifying the types of climate information managers would like to obtain to inform decision making and to specify the preferred format for the delivery of that information. Three prototype tools were evaluated by managers using pre/post surveys that included hands-on tutorials to explore the functionality of each. Manager responses were recorded using a five-point scale with 1 being No or Not Useful to 5 being Absolutely or Very Useful. The median responses rated the usefulness of the tools (4, if they would consider using the tool (4, and if they would recommend using the tool to other managers (4 or 5. The median response for increasing manager’s knowledge about climate impacts after completing a tutorial of each of the climate tools was a 3 (moderately useful. Of the managers surveyed in the pre/post-survey, all but one stated they believed they would use the decision support tools in the future with the single response due to wealth of data availability in their institution.
SULLIVAN,T.; BARDOS,R.P.; MAROT,C.; MARIOTTI,R.
Effective contaminated land management requires a number of decisions addressing a suite of technical, economic and social concerns. This paper offers a common framework and terminology for describing decision support approaches, along with an overview of recent applications of decision support tools in Europe and the USA. A common problem with work on decision support approaches is a lack of a common framework and terminology to describe the process. These have been proposed in this paper.
Nidhra, Srinivas; Ethiraj, Vinay Sudha
Travelling salesman problem is a problem which is of high interest for researchers, industry professionals, and academicians. Visitor or salesman used to face lot of problems with respect to scheduling based on meeting top ranked clients. Even excel sheet made the work tedious. So these flaws propelled us to design an intelligent decision support system. This paper reports the problem definition we tried to address and possible solution to this problem. We even explained the project design and implementation of our visitor schedule management system.. Our system made a major contribution in terms of valuable resources such as time and satisfying high ranked clients efficiently. We used optimization via mathematical programming to solve these issues.
Khalifa, Mohamed; Alswailem, Osama
Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital.
Abraham, Ajith; Siarry, Patrick; Sheng, Michael
This unique book dicusses the latest research, innovative ideas, challenges and computational intelligence (CI) solutions in sustainable computing. It presents novel, in-depth fundamental research on achieving a sustainable lifestyle for society, either from a methodological or from an application perspective. Sustainable computing has expanded to become a significant research area covering the fields of computer science and engineering, electrical engineering and other engineering disciplines, and there has been an increase in the amount of literature on aspects sustainable computing such as energy efficiency and natural resources conservation that emphasizes the role of ICT (information and communications technology) in achieving system design and operation objectives. The energy impact/design of more efficient IT infrastructures is a key challenge in realizing new computing paradigms. The book explores the uses of computational intelligence (CI) techniques for intelligent decision support that can be explo...
Broverman, C A; Clyman, J I; Schlesinger, J M; Want, E
We report on a joint development effort between ALLTEL Information Services Health Care Division and IBM Worldwide Healthcare Industry to demonstrate concurrent clinical decision support using Arden Syntax at order-entry time. The goal of the partnership is to build a high performance CDS toolkit that may be easily customized for multiple health care enterprises. Our work uses and promotes open technologies and health care standards while building a generalizable interface to a legacy patient-care system and clinical database. This paper identifies four areas of design challenges and solutions unique to a concurrent order-entry environment: the clinical information model, the currency of the patient virtual chart, the granularity of event triggers and rule evaluation context, and performance.
Gavanelli, Marco; Milano, Michela; Cagnoli, Paolo; 10.1017/S1471068410000335
Strategic Environmental Assessment is a procedure aimed at introducing systematic assessment of the environmental effects of plans and programs. This procedure is based on the so-called coaxial matrices that define dependencies between plan activities (infrastructures, plants, resource extractions, buildings, etc.) and positive and negative environmental impacts, and dependencies between these impacts and environmental receptors. Up to now, this procedure is manually implemented by environmental experts for checking the environmental effects of a given plan or program, but it is never applied during the plan/program construction. A decision support system, based on a clear logic semantics, would be an invaluable tool not only in assessing a single, already defined plan, but also during the planning process in order to produce an optimized, environmentally assessed plan and to study possible alternative scenarios. We propose two logic-based approaches to the problem, one based on Constraint Logic Programming a...
Hayward, Robert S; El-Hajj, Mohamad; Voth, Tanya K; Deis, Kelly
This paper analyses information behavior data automatically gathered by an integrated clinical information environment used by internal medicine physicians and trainees at the University of Alberta. The study reviews how clinical information systems, decision-support tools and evidence resources were used over a 13 month period. Aggregate and application-specific frequency and duration of use was compared for location, time of day, physician status, and application-type (clinical information system or 5 categories of knowledge resources). Significant differences are observed for when and where resources were used, diurnal patterns of use, minutes spent per encounter, and patterns of use for physicians and trainees. We find that evidence use is not restricted to either the place or time of clinical work, resources are used for very short periods at the point-of-care, and that use of filtered evidence-based resources is concentrated among trainees.
Mohan, L; Muse, L; McInerney, C
Financing of mental health care has changed radically, especially with managed care. Shrinking revenues have forced providers to look for creative ways in which to provide quality services at less expense. Delivery of quality services depends largely on the productive use of the provider's prime resource--the clinicians. Productivity was the focus of the PC-based decision support system developed for mental health providers in New York State. It enables administrators to track key indicators of productivity such as face-to-face time and non-face-to-face time against goals. Unmet goals can be pinpointed quickly, and clinicians' caseloads can be reviewed to determine the underlying causes. A key feature of the system is the conversion of raw data into actionable information to help in problem finding and problem solving. The system has been implemented in Ulster County, the pilot site for the project. The software can be customized easily to suit the data of other providers.
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.
Timofeyeva, M. M.; Higgins, W.; Strager, C.; Horsfall, F. M.
NOAA is an active participant of the Global Framework for Climate Services (GFCS) contributing data, information, analytical capabilities, forecasts, and decision support services to the Climate Services Partnership (CSP). These contributions emerge from NOAA's own climate services, which have evolved to respond to the urgent and growing need for reliable, trusted, transparent, and timely climate information across all sectors of the U.S. economy. Climate services not only enhance development opportunities in many regions, but also reduce vulnerability to climate change around the world. The NOAA contribution lies within the NOAA Climate Goal mission, which is focusing its efforts on four key climate priority areas: water, extremes, coastal inundation, and marine ecosystems. In order to make progress in these areas, NOAA is exploiting its fundamental capabilities, including foundational research to advance understanding of the Earth system, observations to preserve and build the climate data record and monitor changes in climate conditions, climate models to predict and project future climate across space and time scales, and the development and delivery of decision support services focused on risk management. NOAA's National Weather Services (NWS) is moving toward provision of Decision Support Services (DSS) as a part of the Roadmap on the way to achieving a Weather Ready National (WRN) strategy. Both short-term and long-term weather, water, and climate information are critical for DSS and emergency services and have been integrated into NWS in the form of pilot projects run by National and Regional Operations Centers (NOC and ROCs respectively) as well as several local offices. Local offices with pilot projects have been focusing their efforts on provision of timely and actionable guidance for specific tasks such as DSS in support of Coastal Environments and Integrated Environmental Studies. Climate information in DSS extends the concept of climate services to
Scott, C. A.
The National Weather Service Alaska Region's (AR) Regional Operation Center (ROC) provided weather and ice decision support services for the Bureau of Ocean and Energy Management (BOEM) oversight of Royal Dutch Shell's exploratory drilling operations in the Chukchi Sea during the summer and early fall of 2015. The AR ROC, coordinated input from WFO's Anchorage and Fairbanks, the NCEP/Ocean Prediction Center and Climate Prediction Center, and NOAA's National Ice Center. Briefings began in early Spring 2015, focused on melt-out and freeze up dates in the vicinity of the "Burger" drill site. Initially packages were prepared and briefed twice weekly. The frequency increased as the drilling season progressed, and included marine and aviation weather forecasts, current and forecast sea ice conditions as it impacts vessels and aircraft transiting to and from the drilling sites in the Chukchi Sea. Spot forecasts are also available for specific missions as needed.
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.
Sekhri A. Arezki
Full Text Available During the last years, the Sebkha Lake of Oran (Algeria has been the subject of many studies for its protection and recovery. Many environmental and wetlands experts are a hope on the integration of this rich and fragile space, ecologically, as a pilot project in "management of water tides". Support the large of Sebkha (Lake of Oran is a major concern for governments looking to make this a protected natural area and viable place. It was a question of putting in place a management policy to respond to the requirements of economic, agricultural and urban development and the preservation of this natural site through management of its water and the preservation of its quality. The objective of this study is to design and develop a Spatial Decision Support System, namely AQUAZONE, able to assist decision makers in various natural resource management projects. The proposed system integrates remote sensing image processing methods, from display operations, to analysis results, in order to extract useful knowledge to best natural resource management, and in particular define the extension of Sebkha Lake of Oran (Algeria. Two methods were applied to classify LANDSAT 5 TM images of Oran (Algeria: Fuzzy C-Means (FCM applied on multi spectral images, and the other that comes with the manual which is the Ordered Queue-based Watershed (OQW. The FCM will serve as initialization phase, to automatically discover the different classes (urban, forest, water, etc.. from a LANDSAT 5 TM images, and also minimize ambiguity in grayscale and establish Land cover map of this region.
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.
Kohn, Nina A; Blumenthal, Jeremy A
Supported decision-making is increasingly being promoted as an alternative to guardianship for persons aging with intellectual disabilities. Proponents argue that supported decision-making, unlike guardianship, empowers persons with disabilities by providing them with help in making their own decisions, rather than simply providing someone else to make decisions for them. To evaluate the empirical support for these claims, we reviewed the evidence base on supported decision-making. Our review found little such empirical research, suggesting that significant further research is warranted to determine whether--and under what conditions--supported decision-making can benefit persons with intellectual disabilities. Indeed, without more empirical evidence as to how supported decision-making functions in practice, it is too early to rule out the possibility it may actually disempower individuals with disabilities by facilitating undue influence by their alleged supporters. We therefore suggest several key areas for future research.
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
Pulwarty, R. S.
As has been long noted, a comprehensive, coordinated observing system is the backbone of any Earth information system. Demands are increasingly placed on earth observation and prediction systems and attendant services to address the needs of economically and environmentally vulnerable sectors and investments, including energy, water, human health, transportation, agriculture, fisheries, tourism, biodiversity, and national security. Climate services include building capacity to interpret information and recognize standards and limitations of data in the promotion of social and economic development in a changing climate. This includes improving the understanding of climate in the context of a variety of temporal and spatial scales (including the influence of decadal scale forcings and land surface feedbacks on seasonal forecast reliability). Climate data and information are central for developing decision options that are sensitive to climate-related uncertainties and the design of flexible adaptation pathways. Ideally monitoring should be action oriented to support climate risk assessment and adaptation including informing robust decision making to multiple risks over the long term. Based on the experience of global observations programs and empirical research we outline- Challenges in developing effective monitoring and climate information systems to support adaptation. The types of observations of critical importance needed for sector planning to enhance food, water and energy security, and to improve early warning for disaster risk reduction Observations needed for ecosystem-based adaptation including the identification of thresholds, maintenance of biological diversity and land degradation The benefits and limits of linking regional model output to local observations including analogs and verification for adaptation planning To support these goals a robust systems of integrated observations are needed to characterize the uncertainty surrounding emergent risks
Marshall, M. T.
Population driven water scarcity, aggravated by climate-driven evaporative demand in dry regions of the world, has the potential of transforming ecological and social systems to the point of armed conflict. Water shortages will be most severe in agricultural areas, as the priority shifts to urban and industrial use. In order to design, evaluate, and monitor appropriate mitigation strategies, predictive models must be developed that quantify exposure to water shortage. Remote sensing data has been used for more than three decades now to parametrize these models, because field measurements are costly and difficult in remote regions of the world. In the past decade, decision-makers for the first time can make accurate and near real-time evaluations of field conditions with the advent of hyper- spatial and spectral and coarse resolution continuous remote sensing data. Here, we summarize two projects representing diverse applications of remote sensing to improve agricultural water decision support. The first project employs MODIS (coarse resolution continuous data) to drive an evapotranspiration index, which is combined with the Standardized Precipitation Index driven by meteorological satellite data to improve famine early warning in Africa. The combined index is evaluated using district-level crop yield data from Kenya and Malawi and national-level crop yield data from the United Nations Food and Agriculture Organization. The second project utilizes hyper- spatial (GeoEye 1, Quickbird, IKONOS, and RapidEye) and spectral (Hyperion/ALI), as well as multi-spectral (Landsat ETM+, SPOT, and MODIS) data to develop biomass estimates for key crops (alfalfa, corn, cotton, and rice) in the Central Valley of California. Crop biomass is an important indicator of crop water productivity. The remote sensing data is combined using various data fusion techniques and evaluated with field data collected in the summer of 2012. We conclude with a brief discussion on implementation of
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
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.
Vlek, C.A.J.; Timmermans, D.
In this study the effectiveness of multi-attribute utility (MAU) decision support in groups is evaluated for personnel selection problems differing in complexity. Subjects were asked to make an initial individual decision with or without MAU decision support. Next individuals formed small groups and
Baba, A. Fevzi; Kuscu, Dincer; Han, Kerem
The complex nature and uncertain information in social problems required the emergence of fuzzy decision support systems in social areas. In this paper, we developed user-friendly Fuzzy Group Decision Support Systems (FGDSS) software. The software can be used for multi-purpose decision making processes. It helps the users determine the main and…
Full Text Available As part of the integrated ECOOP (European Coastal Sea Operational observing and Forecasting System project, HCMR upgraded the already existing standalone Oil Spill Forecasting System for the Aegean Sea, initially developed for the Greek Operational Oceanography System (POSEIDON, into an active element of the European Decision Support System (EuroDeSS. The system is accessible through a user friendly web interface where the case scenarios can be fed into the oil spill drift model component, while the synthetic output contains detailed information about the distribution of oil spill particles and the oil spill budget and it is provided both in text based ECOOP common output format and as a series of sequential graphics. The main development steps that were necessary for this transition were the modification of the forcing input data module in order to allow the import of other system products which are usually provided in standard formats such as NetCDF and the transformation of the model's calculation routines to allow use of current, density and diffusivities data in z instead of sigma coordinates. During the implementation of the Aegean DeSS, the system was used in operational mode in order support the Greek marine authorities in handling a real accident that took place in North Aegean area. Furthermore, the introduction of common input and output files by all the partners of EuroDeSS extended the system's interoperability thus facilitating data exchanges and comparison experiments.
Full Text Available As part of the integrated ECOOP (European Coastal Sea Operational observing and Forecasting System project, HCMR upgraded the already existing standalone Oil Spill Forecasting System for the Aegean Sea, initially developed for the Greek Operational Oceanography System (POSEIDON, into an active element of the European Decision Support System (EuroDeSS. The system is accessible through a user friendly web interface where the case scenarios can be fed into the oil spill drift model component, while the synthetic output contains detailed information about the distribution of oil spill particles and the oil spill budget and it is provided both in text based ECOOP common output format and as a series of sequential graphics. The main development steps that were necessary for this transition were the modification of the forcing input data module in order to allow the import of other system products which are usually provided in standard formats such as NetCDF and the transformation of the model's calculation routines to allow use of current, density and diffusivities data in z instead of sigma coordinates. During the implementation of the Aegean DeSS, the system was used in operational mode in order to support the Greek marine authorities in handling a real accident that took place in North Aegean area. Furthermore, the introduction of common input and output files by all the partners of EuroDeSS extended the system's interoperability thus facilitating data exchanges and comparison experiments.
Full Text Available This paper presents a Decision Support System (DSS for planning of farm regions in Greece. The DSS is based on the development possibilities of the agricultural sector in relation with the agricultural processing industries of the region and aims at the development of farm regions through a better utilization of available agricultural recourses and agricultural industries. The DSS uses Linear and Goal Programming models and provides for different goals alternative production plans that optimize the use of available recourses. On the other hand, the alternative plans achieve a better utilization of the existent agricultural processing industries or propose their expansion by taking into account the supply and demand of agricultural products in the region. The DSS is computerized and supported by a set of relational data bases. The corresponding software has been developed in Microsoft Windows platform, using Microsoft Visual Basic, Microsoft Access and LINDO. For demonstration reasons, the paper includes an application of the proposed DSS in the region of Servia Kozanis in Northern Greece.
De Kleermaeker, S.; Verkade, J.S.
Often, water management decisions are based on hydrological forecasts, which are affected by inherent uncertainties. It is increasingly common for forecasters to make explicit estimates of these uncertainties. Associated benefits include the decision makers’ increased awareness of forecasting uncert
This document describes a proposed decision model that, if developed to its fullest, can provide a wide range of analysis options and insights to pretreatment/sludge washing alternatives. A recent decision has been made to terminate this work
Wu, Shu-Chieh; Luna, Rocio; Johnson, Walter W.
Weather related disruptions account for seventy percent of the delays in the National Airspace System (NAS). A key component in the weather plan of the Next Generation of Air Transportation System (NextGen) is to assimilate observed weather information and probabilistic forecasts into the decision process of flight crews and air traffic controllers. In this research we explore supporting flight crew weather decision making through the development of a flight deck predicted weather display system that utilizes weather predictions generated by ground-based radar. This system integrates and presents this weather information, together with in-flight trajectory modification tools, within a cockpit display of traffic information (CDTI) prototype. that the CDTI features 2D and perspective 3D visualization models of weather. The weather forecast products that we implemented were the Corridor Integrated Weather System (CIWS) and the Convective Weather Avoidance Model (CWAM), both developed by MIT Lincoln Lab. We evaluated the use of CIWS and CWAM for flight deck weather avoidance in two part-task experiments. Experiment 1 compared pilots' en route weather avoidance performance in four weather information conditions that differed in the type and amount of predicted forecast (CIWS current weather only, CIWS current and historical weather, CIWS current and forecast weather, CIWS current and forecast weather and CWAM predictions). Experiment 2 compared the use of perspective 3D and 21/2D presentations of weather for flight deck weather avoidance. Results showed that pilots could take advantage of longer range predicted weather forecasts in performing en route weather avoidance but more research will be needed to determine what combinations of information are optimal and how best to present them.
Schreck, M. B.; Nelson, J. A., Jr.; Heim, R.
The National Weather Service's Alaska Sea Ice Program is designed to service customers and partners operating and planning operations within Alaska waters. The Alaska Sea Ice Program offers daily sea ice and sea surface temperature analysis products. The program also delivers a five day sea ice forecast 3 times each week, provides a 3 month sea ice outlook at the end of each month, and has staff available to respond to sea ice related information inquiries. These analysis and forecast products are utilized by many entities around the state of Alaska and nationally for safety of navigation and community strategic planning. The list of current customers stem from academia and research institutions, to local state and federal agencies, to resupply barges, to coastal subsistence hunters, to gold dredgers, to fisheries, to the general public. Due to a longer sea ice free season over recent years, activity in the waters around Alaska has increased. This has led to a rise in decision support services from the Alaska Sea Ice Program. The ASIP is in constant contact with the National Ice Center as well as the United States Coast Guard (USCG) for safety of navigation. In the past, the ASIP provided briefings to the USCG when in support of search and rescue efforts. Currently, not only does that support remain, but our team is also briefing on sea ice outlooks into the next few months. As traffic in the Arctic increases, the ASIP will be called upon to provide more and more services on varying time scales to meet customer needs. This talk will address the many facets of the current Alaska Sea Ice Program as well as delve into what we see as the future of the ASIP.
Pahl, Julia; Voss, Stefan; Sebastian, Hans-Jürgen
Intelligent Decision Support and Big Data for Logistics and Supply Chain Management” features theoretical developments, real-world applications and information systems related to solving decision problems in logistics and supply chain management. Methods include optimization, heuristics...
Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.
Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it
Jacob, Joseph; Turmon, Michael; Stough, Timothy; Siegel, Herbert; Walter, patrick; Kurt, Cindy
The visualization front-end of a Decision Support System (DSS) also includes an analysis engine linked to vehicle telemetry, and a database of learned models for known behaviors. Because the display is graphical rather than text-based, the summarization it provides has a greater information density on one screen for evaluation by a flight controller.This tool provides a system-level visualization of the state of a vehicle, and drill-down capability for more details and interfaces to separate analysis algorithms and sensor data streams. The system-level view is a 3D rendering of the vehicle, with sensors represented as icons, tied to appropriate positions within the vehicle body and colored to indicate sensor state (e.g., normal, warning, anomalous state, etc.). The sensor data is received via an Information Sharing Protocol (ISP) client that connects to an external server for real-time telemetry. Users can interactively pan, zoom, and rotate this 3D view, as well as select sensors for a detail plot of the associated time series data. Subsets of the plotted data can be selected and sent to an external analysis engine to either search for a similar time series in an historical database, or to detect anomalous events. The system overview and plotting capabilities are completely general in that they can be applied to any vehicle instrumented with a collection of sensors. This visualization component can interface with the ISP for data streams used by NASA s Mission Control Center at Johnson Space Center. In addition, it can connect to, and display results from, separate analysis engine components that identify anomalies or that search for past instances of similar behavior. This software supports NASA's Software, Intelligent Systems, and Modeling element in the Exploration Systems Research and Technology Program by augmenting the capability of human flight controllers to make correct decisions, thus increasing safety and reliability. It was designed specifically as a
Meshkat, Leila; Hogle, Charles; Ruszkowski, James
The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of
Zuniga, Areli A.
Modern radiation therapy techniques allow for improved target conformity and normal tissue sparing. These highly conformal treatment plans have allowed dose escalation techniques increasing the probability of tumor control. At the same time this conformation has introduced inhomogeneous dose distributions, making delivered dose characterizations more difficult. The concept of equivalent uniform dose (EUD) characterizes a heterogeneous dose distribution within irradiated structures as a single value and has been used in biologically based treatment planning (BBTP); however, there are no substantial validation studies on clinical outcome data supporting EUD's use and therefore has not been widely adopted as decision-making support. These highly conformal treatment plans have also introduced the need for safety margins around the target volume. These margins are designed to minimize geometrical misses, and to compensate for dosimetric and treatment delivery uncertainties. The margin's purpose is to reduce the chance of tumor recurrence. This dissertation introduces a new EUD formulation designed especially for tumor volumes, called generalized Tumor Dose (gTD). It also investigates, as a second objective, margins extensions for potential improvements in local control while maintaining or minimizing toxicity. The suitability of gTD to rank LC was assessed by means of retrospective studies in a head and neck (HN) squamous cell carcinoma (SCC) and non-small cell lung cancer (NSCLC) cohorts. The formulation was optimized based on two datasets (one of each type) and then, model validation was assessed on independent cohorts. The second objective of this dissertation was investigated by ranking the probability of LC of the primary disease adding different margin sizes. In order to do so, an already published EUD formula was used retrospectively in a HN and a NSCLC datasets. Finally, recommendations for the viability to implement this new formulation into a routine treatment
Olumuyiwa S. Asaolu
Full Text Available Inadequate rainfall, water resources scarcity and attendant food security-related problems have made irrigation technology a necessity. This work presents the development of a decision support system for solving surface irrigation design problems in northern Nigeria. The arid northern states affected by desert encroachment constitute a good candidate and their climatological data was obtained from the Nigerian Metrological Agency. The interactive system was defined in terms of inputs and outputs. The inputs were properties of soil, surface irrigation method and climate. The outputs were mainly the quantity of water application, scheduling pattern, possible design configuration, advance time, cut-off time, application rate, and water use efficiency. The FAO Penman-Monteith equation was used to estimate evapotranspiration values of major crops grown in Nigeria. Mathematical models outlined by Walker and Skogerboe were adapted, and heuristics applied in determining the best configuration that achieves optimum water application efficiency. We encoded the knowledge base using Matlab® software. The application was successfully used for the modification of a farm irrigation scheme in Kaduna state. This indicates that the adoption of new technologies for irrigation design issues could enhance agricultural productivity in northern Nigeria.
Soman, Sandeep; Zasuwa, Gerard; Yee, Jerry
Increasing data suggest that errors in medicine occur frequently and result in substantial harm to the patient. The Institute of Medicine report described the magnitude of the problem, and public interest in this issue, which was already large, has grown. The traditional approach in medicine has been to identify the persons making the errors and recommend corrective strategies. However, it has become increasingly clear that it is more productive to focus on the systems and processes through which care is provided. If these systems are set up in ways that would both make errors less likely and identify those that do occur and, at the same time, improve efficiency, then safety and productivity would be substantially improved. Clinical decision support systems (CDSSs) are active knowledge systems that use 2 or more items of patient data to generate case specific recommendations. CDSSs are typically designed to integrate a medical knowledge base, patient data, and an inference engine to generate case specific advice. This article describes how automation, templating, and CDSS improve efficiency, patient care, and safety by reducing the frequency and consequences of medical errors in nephrology. We discuss practical applications of these in 3 settings: a computerized anemia-management program (CAMP, Henry Ford Health System, Detroit, MI), vascular access surveillance systems, and monthly capitation notes in the hemodialysis unit.
Konstantinidis, Stathis Th; Bamidis, Panagiotis D
During the last decades, the inclusion of digital tools in health education has rapidly lead to a continuously enlarging digital era. All the online interactions between learners and tutors, the description, creation, reuse and sharing of educational digital resources and the interlinkage between them in conjunction with cheap storage technology has led to an enormous amount of educational data. Medical education is a unique type of education due to accuracy of information needed, continuous changing competences required and alternative methods of education used. Nowadays medical education standards provide the ground for organising the educational data and the paradata. Analysis of such education data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research. To the best of our knowledge, there is a gap and a clear need for identifying the challenges for DSSs in medical education in the era of medical education standards. Thus, in this Letter the role and the attributes of such a DSS for medical education are delineated and the challenges and vision for future actions are identified.
Tarik A. Rashid
Full Text Available recently, the diseases of diabetes mellitus have grown into extremely feared problems that can have damaging effects on the health condition of their sufferers globally. In this regard, several machine learning models have been used to predict and classify diabetes types. Nevertheless, most of these models attempted to solve two problems; categorizing patients in terms of diabetic types and forecasting blood surge rate of patients. This paper presents an automatic decision support system for diabetes mellitus through machine learning techniques by taking into account the above problems, plus, reflecting the skills of medical specialists who believe that there is a great relationship between patient’s symptoms with some chronic diseases and the blood sugar rate. Data sets are collected from Layla Qasim Clinical Center in Kurdistan Region, then, the data is cleaned and proposed using feature selection techniques such as Sequential Forward Selection and the Correlation Coefficient, finally, the refined data is fed into machine learning models for prediction, classification, and description purposes. This system enables physicians and doctors to provide diabetes mellitus (DM patients good health treatments and recommendations.
van der Bolt, Frank; Seid, Abdulkarim
To analyze options for increasing food supply in the Nile basin the Nile Agricultural Model (AM) was developed. The AM includes state-of-the-art descriptions of biophysical, hydrological and economic processes and realizes a coherent and consistent integration of hydrology, agronomy and economics. The AM covers both the agro-ecological domain (water, crop productivity) and the economic domain (food supply, demand, and trade) and allows to evaluate the macro-economic and hydrological impacts of scenarios for agricultural development. Starting with the hydrological information from the NileBasin-DSS the AM calculates the available water for agriculture, the crop production and irrigation requirements with the FAO-model AquaCrop. With the global commodity trade model MAGNET scenarios for land development and conversion are evaluated. The AM predicts consequences for trade, food security and development based on soil and water availability, crop allocation, food demand and food policy. The model will be used as a decision support tool to contribute to more productive and sustainable agriculture in individual Nile countries and the whole region.
Liedgren, Pernilla; Elvhage, Gudrun; Ehrenberg, Anna; Kullberg, Christian
Decision support systems are known to be helpful for professionals in many medical professions. In social work, decision support systems have had modest use, accompanied by strong criticism from the profession but often by praise from political management. In this study the aim of the authors was to collect and report on the published evidence on decision support systems in social work. The conclusion of the authors is that a decision support system gives support to social workers in conducting a thorough investigation, but at the same time gives them the freedom to make autonomous decisions that might be the most helpful for and used by social workers. Their results also indicate that decision support systems focusing on atypical rather than typical cases are perceived as the most useful among experienced staff.
Hillegersberg, van 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
This research aimed to recognize the cause and effect of decision support system on reengineering the Jordanian tourism companies. In order to achieve the research aims, researcher developed a questionnaire and distributed it to a 43-individual sample randomly. The research results in that the extent of interest in decision support systems and reengineering work systems doesn’t get that high, and clearly there was a cause and effect relationship between decision support systems and reengineer...
Rahmadwati, Rahmadwati; Naghdy, Golshah; Ros, Montserrat; Todd, Catherine
Conventional analysis of a cervical histology image, such a pap smear or a biopsy sample, is performed by an expert pathologist manually. This involves inspecting the sample for cellular level abnormalities and determining the spread of the abnormalities. Cancer is graded based on the spread of the abnormal cells. This is a tedious, subjective and time-consuming process with considerable variations in diagnosis between the experts. This paper presents a computer aided decision support system (CADSS) tool to help the pathologists in their examination of the cervical cancer biopsies. The main aim of the proposed CADSS system is to identify abnormalities and quantify cancer grading in a systematic and repeatable manner. The paper proposes three different methods which presents and compares the results using 475 images of cervical biopsies which include normal, three stages of pre cancer, and malignant cases. This paper will explore various components of an effective CADSS; image acquisition, pre-processing, segmentation, feature extraction, classification, grading and disease identification. Cervical histological images are captured using a digital microscope. The images are captured in sufficient resolution to retain enough information for effective classification. Histology images of cervical biopsies consist of three major sections; background, stroma and squamous epithelium. Most diagnostic information are contained within the epithelium region. This paper will present two levels of segmentations; global (macro) and local (micro). At the global level the squamous epithelium is separated from the background and stroma. At the local or cellular level, the nuclei and cytoplasm are segmented for further analysis. Image features that influence the pathologists' decision during the analysis and classification of a cervical biopsy are the nuclei's shape and spread; the ratio of the areas of nuclei and cytoplasm as well as the texture and spread of the abnormalities
A Decision Management System (DMS) provides means to model and automate enterprise decisions and they are applied in a wide range of industries, among which health care, commerce, insurance, finance and transportation. These systems make millions of decisions each day without direct human supervisio
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.
Ng, Chirk Jenn; Lee, Yew Kong; Lee, Ping Yein; Abdullah, Khatijah Lim
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.
Wright, Adam; Sittig, Dean F
In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:
Maughan, T.; Das, J.; McCann, M. P.; Rajan, K.
Thom Maughan, Jnaneshwar Das, Mike McCann, Danelle Cline, Mike Godin, Fred Bahr, Kevin Gomes, Tom O'Reilly, Frederic Py, Monique Messie, John Ryan, Francisco Chavez, Jim Bellingham, Maria Fox, Kanna Rajan Monterey Bay Aquarium Research Institute Moss Lading, California, United States Many of the coastal ocean processes we wish to observe in order to characterize marine ecosystems have large spatial extant (tens of square km) and are dynamic moving kilometers in a day with biological processes spanning anywhere from minutes to days. Some like harmful algal blooms generate toxins which can significantly impact human health and coastal economies. In order to obtain a viable understanding of the biogeochemical processes which define their dynamics and ecology, it is necessary to persistently observe, track and sample within and near the dynamic fields using augmented methods of observation such as autonomous platforms like AUVs, gliders and surface craft. Field experiments to plan, execute and manage such multitude of assets are challenging. To alleviate this problem the autonomous systems group with its collaborators at MBARI and USC designed, built and fielded a prototype Oceanographic Decision Support System (ODSS) that provides situational awareness and a single portal to visualize and plan deployments for the large scale October 2010 CANON field program as well as a series of 2 week field programs in 2011. The field programs were conducted in Monterey Bay, a known 'red tide' incubator, and varied from as many as twenty autonomous platforms, four ships and 2 manned airplanes to coordinated AUV operations, drifters and a single ship. The ODSS web-based portal was used to assimilate information from a collection of sources at sea, including AUVs, moorings, radar data as well as remote sensing products generated by partner organizations to provide a synthesis of views useful to predict the movement of a chlorophyll patch in the confines of the northern Monterey Bay
Delavari-Edalat, Farideh; Abdi, M Reza
The specific aim of this study is to investigate popular attitudes toward trees. The paper is involved the understanding of biophilia tendencies with respect to people's views in an urban area. Biophilia is considered as the idea insisting on the dependency of human identity on his relationship with nature. The biophilia fundamental tendencies were explored to establish a biological framework for valuing and affiliating the natural world. Accordingly, the nine tendencies i.e. utilitarian, naturalistic, ecologistic-scientific, aesthetic, symbolic, humanistic, moralistic, dominionistic, and negativistic were investigate to find out how people relate to the nature especially trees. The investigation was based on a quantitative interview which was applied to the public population in the Liverpool urban parks. Data collected from the designed questionnaire was followed by analysis of the data to identify people's attitudes towards trees. The results indicated how important the physical appeal and beauty of trees was for the people and also showed the people's emotional attachments to trees. Furthermore, a decision support model was proposed to evaluate human instincts and preferences in relation to their surrounding areas using the Analytical Hierarchical Process (AHP). The proposed model composed the environmental factors and the biophilia tendencies as the criteria of evaluating environmental-human interactions. A case study was then conducted in Liverpool parks to examine theses interactions. The data gathered was used as the input to the AHP model for the attribute analysis. The AHP model would enable environment managers to compose the relevant information via a link between human feelings about urban trees, and environmental factors for monitoring purposes and performance analysis.
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.
Bonazountas, Marc; Kallidromitou, Despina; Kassomenos, Pavlos; Passas, Nikos
Southern Europe is exposed to anthropogenic and natural forest fires. These result in loss of lives, goods and infrastructure, but also deteriorate the natural environment and degrade ecosystems. The early detection and combating of such catastrophes requires the use of a decision support system (DSS) for emergency management. The current literature reports on a series of efforts aimed to deliver DSSs for the management of the forest fires by utilising technologies like remote sensing and geographical information systems (GIS), yet no integrated system exists. This manuscript presents the results of scientific research aiming to the development of a DSS for managing forest fires. The system provides a series of software tools for the assessment of the propagation and combating of forest fires based on Arc/Info, ArcView, Arc Spatial Analyst, Arc Avenue, and Visual C++ technologies. The system integrates GIS technologies under the same data environment and utilises a common user interface to produce an integrated computer system based on semi-automatic satellite image processing (fuel maps), socio-economic risk modelling and probabilistic models that would serve as a useful tool for forest fire prevention, planning and management. Its performance has been demonstrated via real time up-to-date accurate information on the position and evolution of the fire. The system can assist emergency assessment, management and combating of the incident. A site demonstration and validation has been accomplished for the island of Evoia, Greece, an area particularly vulnerable to forest fires due to its ecological characteristics and prevailing wind patterns.
Cole, Rod; Green, Steve; Jardin, Matt; Schwartz, Barry; Benjamin, Stan
The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an
Kaltoft, Mette Kjer; Nielsen, Jesper Bo; Salkeld, Glenn;
An interactive decision support tool based on Multi-Criteria Decision Analysis (MCDA) can help health professionals integrate the principlist (principle-based) and casuist (case-based) approaches to ethical decision making in both their training and practice. MCDA can incorporate generic ethical...
Windhouwer, C.J.; Klunder, G.A.; Sanders, F.M.
The Decision Support System (DSS) Emergency Planning is designed for use in the event of sea or river flooding. It makes accessible all the information related to the decision whether to evacuate an area. An important factor in this decision is the time required for the evacuation. The model used by
Elwyn, Glyn; Frosch, Dominick; Volandes, Angelo E; Edwards, Adrian; Montori, Victor M
This article provides an analysis of 'decision aids', interventions to support patients facing tough decisions. Interest has increased since the concept of shared decision making has become widely considered to be a means of achieving desirable clinical outcomes. We consider the aims of these interventions and examine assumptions about their use. We propose three categories, interventions that are used in face-to-face encounters, those designed for use outside clinical encounters and those which are mediated, using telephone or other communication media. We propose the following definition: decision support interventions help people think about choices they face; they describe where and why choice exists; they provide information about options, including, where reasonable, the option of taking no action. These interventions help people to deliberate, independently or in collaboration with others, about options, by considering relevantattributes; they support people to forecast how they might feel about short, intermediate and long-term outcomes which have relevant consequences, in ways which help the process of constructing preferences and eventual decision making, appropriate to their individual situation. Although quality standards have been published for these interventions, we are also cautious about premature closure and consider that the need for short versions for use inside clinical encounters and long versions for external use requires further research. More work is also needed on the use of narrative formats and the translation of theory into practical designs. The interest in decision support interventions for patients heralds a transformation in clinical practice although many important areas remain unresolved.
Full Text Available Disease development and progression are very complex processes which make clinical decision making non-trivial. On the one hand, examination results that are stored in multiple formats and data types in clinical information systems need to be considered. Beyond, biological or molecular-biological processes can influence clinical decision making. So far, biological knowledge and patient data is separated from each other. This complicates inclusion of all relevant knowledge and information into the decision making. In this paper, we describe a concept of model-based decision support that links knowledge about biological processes, treatment decisions and clinical data. It consists of three models: 1 a biological model, 2 a decision model encompassing medical knowledge about the treatment workflow and decision parameters, and 3 a patient data model generated from clinical data. Requirements and future steps for realizing the concept will be presented and it will be shown how the concept can support the clinical decision making.
van Os, Herman W. A.; Herber, Rien; Scholtens, Bert
In this paper, we present a novel perspective on evaluating subsurface activities by increasing the role of social acceptance in the decision-making process. We use the triangle of social acceptance to structure and analyze the decision-making problem in three classes: social-political, market and c
Dong, Yan; Miraglia, Simona; Manzo, Stefano
The study aims at developing a methodology using decision analysis theory and tools to find the optimal policy (or design) of the studied system, to ensure both sustainability and meanwhile manage risks....
The seabed characterization from sonar images is a very hard task because of the produced data and the unknown environment, even for an human expert. In this work we propose an original approach in order to combine binary classifiers arising from different kinds of strategies such as one-versus-one or one-versus-rest, usually used in the SVM-classification. The decision functions coming from these binary classifiers are interpreted in terms of belief functions in order to combine these functions with one of the numerous operators of the belief functions theory. Moreover, this interpretation of the decision function allows us to propose a process of decisions by taking into account the rejected observations too far removed from the learning data, and the imprecise decisions given in unions of classes. This new approach is illustrated and evaluated with a SVM in order to classify the different kinds of sediment on image sonar.
Østergård, Torben; Jensen, Rasmus Lund; Maagaard, Steffen
framework that facilitates proactive, intelligent, and experience based building simulation which aid decision making in early design. To find software candidates accommodating this framework, we compare existing software with regard to intended usage, interoperability, complexity, objectives, and ability...
Gomoi, Valentin; Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Stoicu-Tivadar, Vasile
The paper presents a method connecting medical databases to a medical decision system, and describes a service created to extract the necessary information that is transferred based on standards. The medical decision can be improved based on many inputs from different medical locations. The developed solution is described for a concrete case concerning the management for chronic pelvic pain, based on the information retrieved from diverse healthcare databases.
Feather, Martin S.; Kiper, James D.; Menzies, Tim
Key decisions are made in the early stages of planning and management of software developments. The information basis for these decisions is often a mix of analogy with past developments, and the best judgments of domain experts. Visualization of this information can support to such decision making by clarifying the status of the information and yielding insights into the ramifications of that information vis-a-vis decision alternatives.
Barfod, Michael Bruhn; Salling, Kim Bang
. The proposed framework is based on the use of cost-benefit analysis featuring feasibility risk assessment in combination with multi-criteria decision analysis and is supported by the concept of decision conferencing. The framework is applied for a transport related case study dealing with the complex decision......This paper concerns the development of a new decision support framework for the appraisal of transport infrastructure projects. In such appraisals there will often be a need for including both conventional transport impacts as well as criteria of a more strategic and/or sustainable character....... The outcome of the case study demonstrates the decision making framework as a valuable decision support system (DSS), and it is concluded that appraisals of transport projects can be effectively supported by the use of the DSS. Finally, perspectives of the future modelling work are given....
With the agricultural development and the modernization of decision-making, it is necessary to establish the agricultural sustainable development decision support system supported by GIS. We set Jianli county as an example; our aim is to realize decision spatialiazation with the support of information system, remote sensing and artificial intelligence. The system components are described in the aspects of database, knowledge base, model-base, and method-base. This system will provide a workable system for local decision-makers and agricultural management sections.
Full Text Available Organizational decisions involve with unusually vague and conflicting criteria. This controversy increases empirical uncertainties, disputes, and the resulting consequences of these decisions. One possible method in subduing this problem is to apply quantitative approaches to provide a transparent process for resolute conclusions which enables decision makers to formulate accurate and decisive on time decisions. Although numerous methods are presented in the literature, the majority of them aim to develop theoretical models. However, this article aims to develop and implement an integrated fuzzy virtual MCDM model based on fuzzy AHP and fuzzy TOPSIS as a decision support system (DDS. Preventing disadvantageous face-to-face decision-making by achieving positive benefit from virtual decision making causes the proposed DDS to be suitable for making crucial decisions such as supplier selection, employee selection, employee appraisal, R&D project selection, etc. The proposed DDS has been implemented in an optical company in Iran.
Hankach, Pierre; SADOUN, Isma; AMANZOUGARENE, Fatiha; CHACHOUA, Mohamed; Zeitouni, Karine; MARTIN, Jean Marc
Effective planning of urban building sites is essential because they are often a source of various kinds of nuisances. In this paper, we present a decision support system for the public space administrator in order to manage building sites nuisances efficiently. The decision support offered through the system is a hybrid approach of two categories. In the first, the decision maker is assisted by supplying relevant information so he can choose the appropriate actions. The second involves activ...
International audience; AbstractSustainable pest management implies less pesticide use and replacement by safe control alternatives. This requires decision support for rational pest management. However, in practice, successful decision making is dependent upon the availability of integrated, high-quality information. Computer-aided forecasting and related decision support systems make pest control more sustainable by avoiding unwanted consequences of pesticide applications. Here, I review int...
S-Y Han; Kim, T. J.; I Adiguzel
A case study is reported of the design, implementation, and evaluation of a knowledge-based decision support system, XPLanner. XPLanner integrates an expert system with optimization modeling technique, database management system, and interactive user interface to create a comprehensive decision aid for facility management and planning by the US Army. It is believed that integrating the expert system with the modeling and data management capabilities of decision support systems can create a co...
Gudmundsson, Henrik; Ericsson, Eva; Tight, Miles
” to examine to what extent various kinds of decision support are used and have become influential in three different planning situations—a local cycle plan in Copenhagen, the Stockholm congestion charging trial and the UK national transport strategy. The results reveal the extensive use of decision support...
Full Text Available This article describes PostGeoOlap, a free software open source tool for decision support that integrates OLAP (On-Line Analytical Processing and GIS (Geographical Information Systems. Besides describing the tool, we show how it can be used to achieve effective and low cost decision support that is adequate for small and medium companies and for small public offices.
GAO Chang-yuan; LIANG Jing-guo; CAO Xiu-ying
According to high-tech product features and decision support system theory, a decision support system (DSS) for identification and evaluation of high-tech products has been designed which consists of the user interface subsystem, the data management subsystem, the model management subsystem and the knowledge management subsystem. This paper describes the function and the framework of the system.
Sousa, Tiago; Pinto, Tiago; Praca, Isabel
-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...
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 tremendo
Burns, Gary N.; Jasinski, Dale; Dunn, Steve; Fletcher, Duncan
This study examined the relationship between evaluations of academic support services and student athletes' career decision-making self-efficacy. One hundred and fifty-eight NCAA athletes (68% male) from 11 Division I teams completed measures of satisfaction with their academic support services, career decision-making self-efficacy, general…
Full Text Available Public sector procurement should be a transparent and fair process. Strict legal requirements are enforced on public sector procurement to make it a standardised process. To make fair decisions on selecting suppliers, a practical method which adheres to legal requirements is important. The research that is the base for this paper aimed at identifying a suitable Multi-Criteria Decision Analysis (MCDA method for the specific legal and functional needs of the Maldivian Public Sector. To identify such operational requirements, a set of focus group interviews were conducted in the Maldives with public officials responsible for procurement decision making. Based on the operational requirements identified through focus groups, criteria-based evaluation is done on published MCDA methods to identify the suitable methods for e-procurement decision making. This paper describes the identification of the operational requirements and the results of the evaluation to select suitable decision models for the Maldivian context.
Full Text Available In raw milk production decision support systems for control of food safety hazards has not been developed but main points of this system are available. The decision support systems’ elements include data identification at critical points in the milk supply chain, an information management system and data exchange. Decision supports systems has been developed on the basis of these elements. In dairy sector decision support systems are significant for controlling of food safety hazards and preferred by producers. When these systems are implemented in the milk supply chain, it can be prevented unnecessary sampling and analysis. In this article it will be underlined effects of decision support system elements on food safety of raw milk.
van Breukelen, C. M.; Osiensky, J. M.
The NWS Alaska Region's Regional Operations Center (AR ROC) provides a variety of decision support services to partners and customers across the state. The AR ROC is virtual most times but can flex to stand up support for partners as needed. Support can vary from briefings over the phone or in person to dedicated virtual support to providing on-site meteorologist at an Emergency Operations Center or Incident Command Post to provide tailored support services. During 2015 there have been a number of situations where the AR ROC provided unique support services. This presentation will outline a few examples of how these unique support services benefitted partner agency decisions.
Ismael Cristofer Baierle
Full Text Available Many authors claim that to cope with rapid changes in social and productive environments, and especially for responding quickly to customer demands and / or users in an organization, information is needed and its management. Decision-making processes also take into account only the past experiences, and this model no longer meets the precepts of today's corporate world, considering the speed with which the market and competition are in search of improvement. Centered on the concepts of Competitive Intelligence and Artificial Intelligence, this article aims to show the importance of information processing, focusing on the processes of decision making and provide a model for their organization and storage. The findings point to the use of intelligent systems, contributing to improved decision-making process and seeking to obtain answers with high quality standards relating to market demand.
13th ICCRTS: C2 for Complex Endeavors “ Multi - agent System for Rapid TST Decision Support” Topic #5, #8 and #9 Joseph Barker, Dr. Robert...OMB control number. 1. REPORT DATE JUN 2008 2. REPORT TYPE 3. DATES COVERED 00-00-2008 to 00-00-2008 4. TITLE AND SUBTITLE Multi - agent System for...unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 13th ICCRTS: C2 for Complex Endeavors Multi - agent System for Rapid TST Decision
The textured images' classification assumes to consider the images in terms of area with the same texture. In uncertain environment, it could be better to take an imprecise decision or to reject the area corresponding to an unlearning class. Moreover, on the areas that are the classification units, we can have more than one texture. These considerations allows us to develop a belief decision model permitting to reject an area as unlearning and to decide on unions and intersections of learning classes. The proposed approach finds all its justification in an application of seabed characterization from sonar images, which contributes to an illustration.
Full Text Available Abstract Background In patients with Stage 5 Chronic Kidney Disease who require renal replacement therapy a major decision concerns modality choice. However, many patients defer the decision about modality choice or they have an urgent or emergent need of RRT, which results in them starting hemodialysis with a Central Venous Catheter. Thereafter, efforts to help patients make more timely decisions about access choices utilizing education and resource allocation strategies met with limited success resulting in a high prevalent CVC use in Canada. Providing decision support tailored to meet patients' decision making needs may improve this situation. The Registered Nurses Association of Ontario has developed a clinical practice guideline to guide decision support for adults living with Chronic Kidney Disease (Decision Support for Adults with Chronic Kidney Disease. The purpose of this study is to determine the impact of implementing selected recommendations this guideline on priority provincial targets for hemodialysis access in patients with Stage 5 CKD who currently use Central Venous Catheters for vascular access. Methods/Design A non-experimental intervention study with repeated measures will be conducted at St. Michaels Hospital in Toronto, Canada. Decisional conflict about dialysis access choice will be measured using the validated SURE tool, an instrument used to identify decisional conflict. Thereafter a tailored decision support intervention will be implemented. Decisional conflict will be re-measured and compared with baseline scores. Patients and staff will be interviewed to gain an understanding of how useful this intervention was for them and whether it would be feasible to implement more widely. Quantitative data will be analyzed using descriptive and inferential statistics. Statistical significance of difference between means over time for aggregated SURE scores (pre/post will be assessed using a paired t-test. Qualitative analysis
Crickard, Elizabeth L; O'Brien, Megan S; Rapp, Charles A; Holmes, Cheryl L
Medical shared decision making has demonstrated success in increasing collaboration between clients and practitioners for various health decisions. As the importance of a shared decision making approach becomes increasingly valued in the adult mental health arena, transfer of these ideals to youth and families of youth in the mental health system is a logical next step. A review of the literature and preliminary, formative feedback from families and staff at a Midwestern urban community mental health center guided the development of a framework for youth shared decision making. The framework includes three functional areas (1) setting the stage for youth shared decision making, (2) facilitating youth shared decision making, and (3) supporting youth shared decision making. While still in the formative stages, the value of a specific framework for a youth model in support of moving from a client-practitioner value system to a systematic, intentional process is evident.
Andersson, Kasper Grann
to parameterisation in the decision support systems of indoor/outdoor air exchange and time budgets, considering recommendations on data sources and regional implementation, as well as the novel reference person concept. Other needs for technological developments for the decision support systems are discussed....... An ongoing RTD activity supported by the European Commission deals with the practical implementation of the recently revised ICRP recommendations, e.g., through adaptation of the existing decision support systems ARGOS and RODOS. Examples are given of the outcome of this activity with respect...
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
National Association of College and University Business Officers (NJ3), 2004
Developed and edited by the National Association of College and University Business Officers' (NACUBO's) Accounting Principles Council, this guidebook, written by highly experienced, seasoned college and university leaders, is designed to help readers make sense of today's world and provide the right tools to make the right decisions. The book,…
Dongen, C.J.G. van; Schraagen, J.M.C.; Eikelboom, A.; Brake, G.M. te
Building up situation understanding is one of the most difficult tasks in the beginning stages of largescale accidents. As ambiguous information about the events becomes available, decision-makers are often tempted to quickly develop a particular story to explain the observed events. As the accident
Schraagen, Jan Maarten; Ven, van de Josine G.M.
In this study, we describe how to use innovative techniques to improve the decision-making process in crisis response organizations. The focus was on building situation awareness of a crisis and overcoming pitfalls such as tunnel vision and information bias through using critical thinking. We starte
Granato, Gregory E.
The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought. This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime. Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions
Faber, Michael Havbro
This book provides the reader with the basic skills and tools of statistics and probability in the context of engineering modeling and analysis. The emphasis is on the application and the reasoning behind the application of these skills and tools for the purpose of enhancing decision making in engineering. The purpose of the book is to ensure that the reader will acquire the required theoretical basis and technical skills such as to feel comfortable with the theory of basic statistics and probability. Moreover, in this book, as opposed to many standard books on the same subject, the perspective is to focus on the use of the theory for the purpose of engineering model building and decision making. This work is suitable for readers with little or no prior knowledge on the subject of statistics and probability.
Full Text Available Data envelopment analysis (DEA and multiple criteria decision making (MCDM models are one of the most often used modelling techniques in managerial practice. Both techniques evaluate the given set of alternatives by several decision making criteria. Availability of appropriate simple software tools for mentioned models is a necessary condition for their wider real application. The paper presents two freeware software systems that are available for downloading on the author's web pages. The first system is the DEA Excel solver and the second one is Sanna - application of multi-criteria evaluation of alternatives. DEA Excel solver covers all basic DEA models and uses internal MS Excel optimization solver. The application includes standard envelopment models with constant and variable returns to scale including superefficiency models. As the second software system the paper presents a simple MS Excel based application Sanna for multiple criteria evaluation of alternatives using several main MCDM methods (WSA, ELECTRE I and III, PROMETHHEE, ORESTE, TOPSIS and MAPPAC.
Ahmed A. Saleh
Full Text Available Decision Support Systems (DSS is a particular type of computerized information system that support business and organizational decision making activities. on the other hand, Data Mining (DM expand the potentials for decision support by finding styles and connections hidden in the data and in this way enabling an inductive way to deal with data analysis. Data is analyzed through a mechanized process, known as Knowledge Discovery in data mining techniques. Data mining can be characterized as a process of browsing and analysis for large amounts of data with a particular focus on discovering significantly important patterns and rules. Data mining helps discovering knowledge from raw, not equipped data. Utilizing data mining techniques permits extracting knowledge from data mart, data warehouse and, specifically cases, even from operational databases. In this paper a methodology is introduced to integrate the DSS with DM for loans to the Real Estate developments fund (REDF Customers. It causes to cooperative interaction of DSS, through getting more options to analysis, utilizing expert's data, and improving assessment process. So I will talk about the function of data mining to simplify decision support, the utilization of data mining methods in decision support systems, talking about applied approaches and present a data mining decision support system called DMDSS – (Data Mining Decision Support System. We also present some obtained results and plans for future development.
Full Text Available Environmental burden of disease represents one quarter of overall disease burden, hence necessitating greater attention from decision makers both inside and outside the health sector. Economic evaluation techniques such as cost- effectiveness analysis and cost-benefit analysis provide key information to health decision makers on the efficiency of environmental health interventions, assisting them in choosing interventions which give the greatest social return on limited public budgets and private resources. The aim of this article is to review economic evaluation studies in three environmental health areas—water, sanitation, hygiene (WSH, vector control, and air pollution—and to critically examine the policy relevance and scientific quality of the studies for selecting and funding public programmers. A keyword search of Medline from 1990–2008 revealed 32 studies, and gathering of articles from other sources revealed a further 18 studies, giving a total of 50 economic evaluation studies (13 WSH interventions, 16 vector control and 21 air pollution. Overall, the economic evidence base on environmental health interventions remains relatively weak—too few studies per intervention, of variable scientific quality and from diverse locations which limits generalisability of findings. Importantly, there still exists a disconnect between economic research, decision making and programmer implementation. This can be explained by the lack of translation of research findings into accessible documentation for policy makers and limited relevance of research findings, and the often low importance of economic evidence in budgeting decisions. These findings underline the importance of involving policy makers in the defining of research agendas and commissioning of research, and improving the awareness of researchers of the policy environment into which their research feeds.
Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael
Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application.
Liu, Brent J; Law, Maria Y Y; Documet, Jorge; Gertych, Arkadiusz
The need for quantified knowledge and decision-support tools to handle complex radiation therapy (RT) imaging and informatics data is becoming steadily apparent. Lessons can be learned from current CAD applications in radiology. This paper proposes a methodology to develop this quantified knowledge and decision-support tools to facilitate RT treatment planning. The methodology is applied to cancer patient cases treated by intensity modulated radiation therapy (IMRT). The use of the "inverse treatment planning" and imaging intensive nature of IMRT allows for the development of such image-assisted tools for supporting decision-making thus providing better workflow efficiency and more precise dose predictions.
Sayyad Shirabad, Jelber; Wilk, Szymon; Michalowski, Wojtek; Farion, Ken
Clinical decision making is a complex multi-stage process. Decision support can play an important role at each stage of this process. At present, the majority of clinical decision support systems have been focused on supporting only certain stages. In this paper we present the design and implementation of MET3-a prototype multi-agent system providing an integrative decision support that spans over the entire decision making process. The system helps physicians with data collection, diagnosis formulation, treatment planning and finding supporting evidence. MET3 integrates with external hospital information systems via HL7 messages and runs on various computing platforms available at the point of care (e.g., tablet computers, mobile phones). Building MET3 required sophisticated and reliable software technologies. In the past decade the open source software movement has produced mature, stable, industrial strength software systems with a large user base. Therefore, one of the decisions that should be considered before developing or acquiring a decision support system is whether or not one could use open source technologies instead of proprietary ones. We believe MET3 shows that the answer to this question is positive.
Anbalagan Thirunavukarasu; Uma Maheswari
This study proposes a Fuzzy Metagraph based Decision Support System (DSS) for short term and long term investment in share market. This rule base decision system will help traders to make correct decision at very low risk. Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD) and WILLIAM- %R are some of the Technical Indicators which are used as input to train the system which is integrated with Fuzzy Metagraph. This approach of incorporating Fuzzy Metagraph with RSI, MA...
Mortensen, Michael Lind
-world decisions if provided with the right tools. The class of multi-criteria decision support queries is said to be one such set of tools, with skyline and top-$k$ queries being the main representatives. Over the past decades, skylines and top-$k$ queries have been extensively studied, yet due to a number...... the theory and intent of multi-criteria decision support queries and how users actually analyze their options and make decisions in real life. The thesis is separated into two parts. In the first part, we investigate the use of skyline queries for exploratory search, in which users pose a string of related......-based methods for their efficient computation in those settings. We also present a method for the targeted sampling of $k$-representative skyline points, enabling a fixed size diverse and relevant overview of all options. In the second part, we investigate the expansion of multi-criteria decision support...
Gemelli, Alberto; Diamantini, Claudia; Longhi, Sauro
Through the results of a developed case study of information system for low temperature geothermal energy, GIS to Support Cost-effective Decisions on Renewable Sources addresses the issue of the use of Geographic Information Systems (GIS) in evaluating cost-effectiveness of renewable resource exploitation regional scale. Focusing on the design of a Decision Support System, a process is presented aimed to transform geographic data into knowledge useful for analysis and decision-making on the economic exploitation of geothermal energy. This detailed description includes a literature review and technical issues related to data collection, data mining, decision analysis for the informative system developed for the case study. A multi-disciplinary approach to GIS design is presented which is also an innovative example of fusion of georeferenced data acquired from multiple sources including remote sensing, networks of sensors and socio-economic censuses. GIS to Support Cost-effective Decisions on Renewable Sources ...
Draelos, Timothy John; Zhang, Peng-Chu.; Wunsch, Donald C. (University of Missouri, Rolla, MO); Seiffertt, John (University of Missouri, Rolla, MO); Conrad, Gregory N.; Brannon, Nathan Gregory
For applications such as force protection, an effective decision maker needs to maintain an unambiguous grasp of the environment. Opportunities exist to leverage computational mechanisms for the adaptive fusion of diverse information sources. The current research employs neural networks and Markov chains to process information from sources including sensors, weather data, and law enforcement. Furthermore, the system operator's input is used as a point of reference for the machine learning algorithms. More detailed features of the approach are provided, along with an example force protection scenario.
Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.; Strasburg, Jana D.
We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.
?The introduction of Enterprise Identity Management Systems (EIdMS) in organizations even beyond the purely technological level is a costly and challenging endeavor. However, for decision makers it seems difficult to fully understand the impacts and opportunities arising from the introduction of EIdMS. This book explores the relevant aspects for an ex-ante evaluation of EIdMS. Therefore it examines this domain by employing a qualitative expert interview study to better understand the nature of EIdMS, as they are situated between security and productive IT systems. To this regard, the focus is
Spratt, Trevor; Devaney, John; Hayes, David
The aims of this study were to identify the themes Social Workers regard as important in supporting decisions to remove children from, or return them to, the care of their parents. To further elicit underlying hypotheses that are discernible in interpretation of evidence. A case study, comprising a two-part vignette with a questionnaire, recorded demographic information, child welfare attitudes and risk assessments, using scales derived from standardised instruments, was completed by 202 Social Workers in Northern Ireland. There were two manipulated variables, mother's attitude to removal and child's attitude to reunification 2 years later. In this paper we use data derived from respondents' qualitative comments explaining their reasoning for in and out of home care decisions. Some 60.9% of respondent's chose the parental care option at part one, with 94% choosing to have the child remain in foster care at part two. The manipulated variables were found to have no significant statistical effect. However, three underlying hypotheses were found to underpin decisions; (a) child rescue, (b) kinship defence and (c) a hedged position on calculation of risk subject to further assessment. Reasoning strategies utilised by social workers to support their decision making suggest that they tend to selectively interpret information either positively or negatively to support pre-existing underlying hypotheses. This finding is in keeping with the literature on 'confirmation bias.' The research further draws attention to the need to incorporate open questions in quantitative studies, to help guard against surface reading of data, which often does not 'speak for itself.'
Full Text Available Normal 0 21 false false false SL X-NONE X-NONE Business decisions must rely not only on organisation’s internal data but also on external data from competitors or relevant events. This information can be obtained from the Web but must be integrated with the data in an organisation’s Data Warehouse (DW. In this paper we discuss the agent-based integration approach using ontologies. To enable common understanding of a domain between people and application systems we introduce business rules approach towards ontology management. Because knowledge in organisation’s ontologies is acquired from business users without technical knowledge simple user interface based on ontology restrictions and predefined templates are used. After data from internal DW, Web and business rules are acquired; agent can deduce new knowledge and therefore facilitate decision making process. Tasks like information retrieval from competitors, creating and reviewing OLAP reports are autonomously performed by agents, while business users have control over their execution through knowledge base in ontology. The approach presented in the paper was verified on the case study from the domain of mobile communications with the emphasis on supply and demand of mobile phones and its accessories.
A Decision Support Tool (DST) has been developed that will aid Distribution Service Operators (DSOs) in their decision making process on which investments to make in the gas distribution grid in order to facilitate the use of biogas. The DST considers both the conversion of biogas to electricity as
Elwyn, G.; Stiel, M.; Durand, M.A.; Boivin, J.
BACKGROUND: Although an increasing number of decision support interventions for patients (including decision aids) are produced, few make explicit use of theory. We argue the importance of using theory to guide design. The aim of this work was to address this theory-practice gap and to examine how a
Scott, Craig R.
The nature of group decision support systems (GDSS), its key advantages, and the experience of using it with several classes help illustrate that this type of computer technology can serve an important function in supplementing instruction of the small group course. The primary purpose of a GDSS is to improve group decision-making and…
Larburu, Nekane; Schooten, van Boris; Shalom, Erez; Fung, Nick; Sinderen, van Marten; Hermens, Hermie; Jones, Val; Riano, David; Lenz, Richard; Miksch, Silvia; Peleg, Mor; Reichert, Manfred; Teije, ten Annette
We present a mobile decision support system (mDSS) which runs on a patient Body Area Network consisting of a smartphone and a set of biosensors. Quality-of-Data (QoD) awareness in decision making is achieved by means of a component known as the Quality-of-Data Broker, which also runs on the smartpho
Bentley, Kia J; Price, Sarah Kye; Cummings, Cory R
In their work in human services organizations and community agencies across service sectors, social workers encounter pregnant and postpartum women experiencing mental health challenges. This article offers an evidence-informed Decision Support Guide designed for use by social workers working with pregnant and postpartum women who are struggling with complicated decisions about psychiatric medication use. The guide is built on contemporary notions of health literacy and shared decision making and is informed by three areas: (1) research into the lived experiences of pregnant and postpartum women and health care providers around psychiatric medication decision making, (2) a critical review of existing decision aids, and (3) feedback on the strategy from social work practitioners who work with pregnant and postpartum women. Emphasizing the relational nature of social work in supporting effective health-related decision making, the guide relies on maintaining a collaborative practice milieu and using a decision aid that engages clients in discussions about mental health during and around the time of pregnancy. The guide offers social workers a practice tool to support responsive and compassionate care by embracing their roles in problem solving and decision making, providing emotional and psychosocial support, and making appropriate referrals to prescribers.
The purpose of this quantitative correlation study was to examine the predictors of user behavioral intention on the decision of oncology care providers to adopt or reject the clinical decision support system. The Unified Theory of Acceptance and Use of Technology (UTAUT) formed the foundation of the research model and survey instrument. The…
Forecasting and communicating the potential outcomes of decision options requires support tools that aid in evaluating alternative scenarios in a user-friendly context and that highlight variables relevant to the decision options and valuable stakeholders. Envision is a GIS-base...
Kert, Serhat Bahadir; Uz, Cigdem; Gecu, Zeynep
This study examined the effectiveness of an electronic performance support system (EPSS) on computer ethics education and the ethical decision-making processes. There were five different phases to this ten month study: (1) Writing computer ethics scenarios, (2) Designing a decision-making framework (3) Developing EPSS software (4) Using EPSS in a…
Haasnoot, Marjolijn; van Deursen, W.P.A.; Kwakkel, J. H.; Middelkoop, H.
There is a long tradition of model-based decision support in water management. The consideration of deep uncertainty, however, changes the requirements imposed on models.. In the face of deep uncertainty, models are used to explore many uncertainties and the decision space across multiple outcomes o
Ghana’s slow progress towards attaining millennium development goal 5 has been associated with gaps in quality of care, particularly quality of clinical decision making for clients. This thesis reviews the relevance and effect of clinical decision making support tools on pregnancy outcomes. Relevanc
US Fish and Wildlife Service, Department of the Interior — Progress report on the GIS support the Upper Midwest Environmental Sciences Center (UMESC) is providing to the U.S. Fish and Wildlife Service (FWS) in the...
Tjosvold, Dean; Santamaria, Philip
Seventy-seven fourth- and fifth-grade students were placed in either a cooperative or a competititve learning structure and the teacher either supported or did not support their decision-making competence. As hypothesized, students whose teacher supported them indicated that they were more confident and committed to making a classroom decision…
National Aeronautics and Space Administration — The key innovation in this effort is the development of a decision support tool and simulation testbed for Airborne Spacing and Merging (ASM). We focus on concepts...
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...
Niès, Julie; Steichen, Olivier; Jaulent, Marie-Christine
We propose an experiment to validate the hypothesis that archetypes enable better access and reliable use of patient data by a decision support system, mainly because they are designed to consistently link patient data with terminological systems and metadata.
If appropriate security mechanisms aren't in place, individuals and groups can get unauthorized access to personal health data residing in clinical decision support systems (CDSS). These concerns are well founded; there has been a dramatic increase in reports of security incidents. The paper provides a framework for securing personal health data in CDSS. The framework breaks down CDSS into data gathering, data management and data delivery functions. It then provides the vulnerabilities that can occur in clinical decision support activities and the measures that need to be taken to protect the data. The framework is applied to protect the confidentiality, integrity and availability of personal health data in a decision support system. Using the framework, project managers and architects can assess the potential risk of unauthorized data access in their decision support system. Moreover they can design systems and procedures to effectively secure personal health data.
Tägil, K; Jakobsson, D; Lomsky, M
The aim of this study was to investigate the influence of a computer-based decision support system (DSS) on performance and inter-observer variability of interpretations regarding ischaemia and infarction in myocardial perfusion scintigraphy (MPS)....
National Aeronautics and Space Administration — The key innovation in this effort is the development of a decision support tool for distributed air-ground scheduling sequencing, spacing and merging of aircraft in...
Drachsler, H. (2009). Decision Support for Learners in Mash-Up Personal Learning Environments. Presentation given at PLE course. December, 15, 2009‚ Hamburg, Germany: Fakultät für Erziehungswissenschaft, Psychologie und Bewegungswissenschaft.
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...
Salling, Kim Bang; Jensen, Anders Vestergaard; Holvad, Torben;
This paper presents a new proto-type decision support system named COSIMA-DSS for composite method for assessment - decision support system. This userfriendly system makes it possible for decision makers to assess large infrastructure projects and take special account of various uncertainties...... in a systematic and explicit way. The model applied is based on cost-benefit analysis (CBA) embedded in a wider multi-criteria analysis (MCA) and makes use of scenario analysis (SA) and Monte Carlo simulation (MCS). A particular concern of the model is the handling of varying information across the assessment...... the features of the COSIMA-DSS model as a useful decision support tool. It is finally concluded that appraisal of large infrastructure projects can be effectively supported by dealing with uncertainty issues in accordance with the described principles....
This viewgraph presentation reviews the development of an Integrated Medical Model (IMM) decision support tool for in-flight crew health care safety. Clinical methods, resources, and case scenarios are also addressed.
National Aeronautics and Space Administration — The feasibility of developing a statistical decision support system for traffic flow management in the terminal area and runway load balancing was demonstrated in...
Full Text Available In today’s business scenario, we percept major changes in how managers use computerized support inmaking decisions. As more number of decision-makers use computerized support in decision making,decision support systems (DSS is developing from its starting as a personal support tool and is becomingthe common resource in an organization. DSS serve the management, operations, and planning levels of anorganization and help to make decisions, which may be rapidly changing and not easily specified inadvance. Data mining has a vital role to extract important information to help in decision making of adecision support system. It has been the active field of research in the last two-three decades. Integration ofdata mining and decision support systems (DSS can lead to the improved performance and can enable thetackling of new types of problems. Artificial Intelligence methods are improving the quality of decisionsupport, and have become embedded in many applications ranges from ant locking automobile brakes tothese days interactive search engines. It provides various machine learning techniques to support datamining. The classification is one of the main and valuable tasks of data mining. Several types ofclassification algorithms have been suggested, tested and compared to determine the future trends based onunseen data. There has been no single algorithm found to be superior over all others for all data sets.Various issues such as predictive accuracy, training time to build the model, robustness and scalabilitymust be considered and can have tradeoffs, further complex the quest for an overall superior method. Theobjective of this paper is to compare various classification algorithms that have been frequently used indata mining for decision support systems. Three decision trees based algorithms, one artificial neuralnetwork, one statistical, one support vector machines with and without adaboost and one clusteringalgorithm are tested and compared on
Lehner, P.; Elsaesser, C.; Seligman, L. [Mitre Corp., McLean, VA (United States)
This paper has described an approach to controlling the process of pulling data/information from distributed data bases in a way that is specific to a persons specific decision making context. Our prototype implementation of this approach uses a knowledge-based planner to generate a plan, an automatically constructed Bayesian network to evaluate the plan, specialized processing of the network to derive key information items that would substantially impact the evaluation of the plan (e.g., determine that replanning is needed), automated construction of Standing Requests for Information (SRIs) which are automated functions that monitor changes and trends in distributed data base that are relevant to the key information items. This emphasis of this paper is on how Bayesian networks are used.
Ren, Jingzheng; Wei, Shunan; Goodsite, Michael Evan
A multicriteria decision-making methodology for the sustainability prioritization of industrial systems is proposed. The methodology incorporates a fuzzy Analytic Hierarchy Process method that allows the users to assess the soft criteria using linguistic terms. A fuzzy Analytic Network Process...... method is used to calculate the weights of each criterion, which can tackle the interdependencies and interactions among the criteria. The Preference Ranking Organization Method for Enrichment Evaluation approach is used to prioritize the sustainability sequence of the alternative systems. Moreover......, a sensitivity analysis method was developed to investigate the most critical and sensitive criteria. The developed methodology was illustrated by a case study to rank the sustainability of five alternative hydrogen production technologies. The advantages of the developed methodology over the previous approaches...
Kang, Sunghyun; Seo, Jiwan; Choi, Seungjin; Kim, Junho; Han, Sangyong
As the Internet technology and social media advance, various information and opinions are shared and distributed through the online communities. However, the existence of implicit and explicit bias of opinions may have a potential influence on the outcomes. Compared to the importance of mitigating biased information, the study in this field is relatively young and does not address many important issues. In this paper we propose the noble approach to mitigate the biased opinions using conventional machine learning methods. The proposed method extracts the useful features such as inclination and sentiment of the community members. They are classified based on their previous behavior, and the propensity of the members is understood. This information on each community and its members is very useful and improve the ability to make an unbiased decision. The proposed method presented in this paper is shown to have the ability to assist optimal, fair and good decision making while also reducing the influence of implicit bias.
Tejedo, Pablo; Benayas, Javier; Cajiao, Daniela; Albertos, Belén; Lara, Francisco; Pertierra, Luis R; Andrés-Abellán, Manuela; Wic, Consuelo; Luciáñez, Maria José; Enríquez, Natalia; Justel, Ana; Reck, Günther K
Thousands of tourists visit certain Antarctic sites each year, generating a wide variety of environmental impacts. Scientific knowledge of human activities and their impacts can help in the effective design of management measures and impact mitigation. We present a case study from Barrientos Island in which a management measure was originally put in place with the goal of minimizing environmental impacts but resulted in new undesired impacts. Two alternative footpaths used by tourist groups were compared. Both affected extensive moss carpets that cover the middle part of the island and that are very vulnerable to trampling. The first path has been used by tourists and scientists since over a decade and is a marked route that is clearly visible. The second one was created more recently. Several physical and biological indicators were measured in order to assess the environmental conditions for both paths. Some physical variables related to human impact were lower for the first path (e.g. soil penetration resistance and secondary treads), while other biochemical and microbiological variables were higher for the second path (e.g. β-glucosidase and phosphatase activities, soil respiration). Moss communities located along the new path were also more diverse and sensitive to trampling. Soil biota (Collembola) was also more abundant and richer. These data indicate that the decision to adopt the second path did not lead to the reduction of environmental impacts as this path runs over a more vulnerable area with more outstanding biological features (e.g. microbiota activity, flora and soil fauna diversity). In addition, the adoption of a new route effectively doubles the human footprint on the island. We propose using only the original path that is less vulnerable to the impacts of trampling. Finally from this process, we identify several key issues that may be taken into account when carrying out impact assessment and environmental management decision-making in the
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.
Platz, M.; Rapp, J.; Groessler, M.; Niehaus, E.; Babu, A.; Soman, B.
A Spatial Decision Support System (SDSS) provides support for decision makers and should not be viewed as replacing human intelligence with machines. Therefore it is reasonable that decision makers are able to use a feature to analyze the provided spatial decision support in detail to crosscheck the digital support of the SDSS with their own expertise. Spatial decision support is based on risk and resource maps in a Geographic Information System (GIS) with relevant layers e.g. environmental, health and socio-economic data. Spatial fuzzy logic allows the representation of spatial properties with a value of truth in the range between 0 and 1. Decision makers can refer to the visualization of the spatial truth of single risk variables of a disease. Spatial fuzzy logic rules that support the allocation of limited resources according to risk can be evaluated with measure theory on topological spaces, which allows to visualize the applicability of this rules as well in a map. Our paper is based on the concept of a spatial fuzzy logic on topological spaces that contributes to the development of an adaptive Early Warning And Response System (EWARS) providing decision support for the current or future spatial distribution of a disease. It supports the decision maker in testing interventions based on available resources and apply risk mitigation strategies and provide guidance tailored to the geo-location of the user via mobile devices. The software component of the system would be based on open source software and the software developed during this project will also be in the open source domain, so that an open community can build on the results and tailor further work to regional or international requirements and constraints. A freely available EWARS Spatial Fuzzy Logic Demo was developed wich enables a user to visualize risk and resource maps based on individual data in several data formats.
Dinitz, Laura; Forney, William; Byrd, Kristin
Scientists at the USGS Western Geographic Science Center are developing decision-support systems (DSSs) for natural-hazards and land-management issues. DSSs are interactive computer-based tools that use data and models to help identify and solve problems. These systems can provide crucial support to policymakers, planners, and communities for making better decisions about long-term natural hazards mitigation and land-use planning.
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.
acquisition decision through the Internet . It also allows organizations to search for buyers or sellers of systems. It has been identified that the...following things : ♦ Be equipped with an adjustable head-mounted eye tracker. The eye tracker will be explained and calibrated. ♦ Complete a baseline...p. 47-62. 7. Mukhopadhyay, T. and S. Kekre, Strategic and Operational Benefits of Electronic Integration in B2B Procurement Processes. Management
Full Text Available The paper deals with the decision of small and medium-sized software companies in transition to SaaS model. The goal of the research is to design a comprehensive methodic to support decision making based on actual data of the company itself. Based on a careful analysis, taxonomy of costs, revenue streams and decision-making criteria are proposed in the paper. On the basis of multi-criteria decision-making methods, each alternative is evaluated and the alternative with the highest score is identified as the most appropriate. The proposed methodic is implemented as a web application and verified through case studies.
Barfod, Michael Bruhn; Salling, Kim Bang
. The proposed framework is based on the use of cost-benefit analysis featuring feasibility risk assessment in combination with multi-criteria decision analysis and is supported by the concept of decision conferencing. The framework is applied for a transport related case study dealing with the complex decision...... problem of determining the most attractive alternative for a new fixed link between Denmark and Sweden – the so-called HH-connection. Applying the framework to the case study made it possible to address the decision problem from an economic, a strategic, and a sustainable point of view simultaneously...
to deal most efficiently with the situation. For situations not foreseen, however, no rules exist, and no support may be given to the user by suggested actions to be fulfilled. The idea of ecological user interface is to present to the user the complete situation at various interrelated levels...... of abstraction supporting the situation assessment and remedial actions based on the domain knowledge of the user. The concept of ecological user interface has been tested and appreciated in a variety of other domains using prototypes designed to be representative of industrial processes. The purpose...
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
Full Text Available Purpose. In conditions of active development of e-learning the high quality of e-learning resources is very important. Providing the high quality of e-learning resources in situation with mass higher education and rapid obsolescence of information requires the automation of information decision support for improving the quality of e-learning resources by development of decision support system. Methodology. The problem is solved by methods of artificial intelligence. The knowledge base of information structure of decision support system that is based on frame model of knowledge representation and inference production rules are developed. Findings. According to the results of the analysis of life cycle processes and requirements to the e-learning resources quality the information model of the structure of the knowledge base of the decision support system, the inference rules for the automatically generating of recommendations and the software implementation are developed. Practical value. It is established that the basic requirements for quality are performance, validity, reliability and manufacturability. It is shown that the using of a software implementation of decision support system for researched courses gives a growth of the quality according to the complex quality criteria. The information structure of a knowledge base system to support decision-making and rules of inference can be used by methodologists and content developers of learning systems.
Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko
This paper discusses a knowledge management system for clinical laboratories. In the clinical laboratory of Toranomon Hospital, we receive about 20 questions relevant to laboratory tests per day from medical doctors or co-medical staff. These questions mostly involve the essence to appropriately accomplish laboratory tests. We have to answer them carefully and suitably because an incorrect answer may cause a medical accident. Up to now, no method has been in place to achieve a rapid response and standardized answers. For this reason, the laboratory staff have responded to various questions based on their individual knowledge. We began to develop a knowledge management system to promote the knowledge of staff working for the laboratory. This system is a type of knowledge base for assisting the work, such as inquiry management, laboratory consultation, process management, and clinical support. It consists of several functions: guiding laboratory test information, managing inquiries from medical staff, reporting results of patient consultation, distributing laboratory staffs notes, and recording guidelines for laboratory medicine. The laboratory test information guide has 2,000 records of medical test information registered in the database with flexible retrieval. The inquiry management tool provides a methos to record all questions, answer easily, and retrieve cases. It helps staff to respond appropriately in a short period of time. The consulting report system treats patients' claims regarding medical tests. The laboratory staffs notes enter a file management system so they can be accessed to aid in clinical support. Knowledge sharing using this function can achieve the transition from individual to organizational learning. Storing guidelines for laboratory medicine will support EBM. Finally, it is expected that this system will support intellectual activity concerning laboratory work and contribute to the practice of knowledge management for clinical work support.
Silich, V. A.; Savelev, A. O.; Isaev, A. N.
The paper contains aspects of developing a decision support systems aimed for well interventions planning within the process of oil production engineering. The specific approach described by authors is based on system analysis methods and object model for system design. Declared number of problem-decision principles as follows: the principle of consolidated information area, the principle of integrated control, the principle of development process transparency. Also observed a set of models (class model, object model, attribute interdependence model, component model, coordination model) specified for designing decision support system for well intervention planning.
Egi Badar Sambani
Full Text Available Decision-making in a company is important because decisions taken by managers is the result of a final thought to be carried out by employees. Asia is the largest mall Plaza sepriangan east, where the assessment process includes the promotion employee attendance, productivity (work, integrity (nature, skill (ability and loyalty (faithfulness. Method Using Weighted Product (WP can help in decision-making to determine the promotion of employees in the company, as well as the appraisal process more efficient so the store manager can determine employee promotions quickly. By using decision support system that has a database, employee data can be stored in the database. So that in case of errors in inputting can be corrected without having to re-enter the data. With the Decision Support System will address the issues raised in the Plaza Asia, so the promotion process will be faster.
Day, W; Audsley, E; Frost, A R
Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability-all essential to sustainable systems.
Franco de los Ríos, Camilo; Pedersen, Søren Marcus; Papaharalampos, Haris
the information for assessing decision makers and farmers in the efficient and sustainable management of the field. Focusing on weed management, the integration of operational aspects for weed spraying is an open challenge for modeling the farmers’ decision problem, identifying satisfactory solutions......Decision support methodologies in precision agriculture should integrate the different dimensions composing the added complexity of operational decision problems. Special attention has to be given to the adequate knowledge extraction techniques for making sense of the collected data, processing...... 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...
Dowie, Jack; Kaltoft, Mette Kjer; Salkeld, Glenn
OBJECTIVE: To introduce a new online generic decision support system based on multicriteria decision analysis (MCDA), implemented in practical and user-friendly software (Annalisa©). BACKGROUND: All parties in health care lack a simple and generic way to picture and process the decisions to be made...... in pursuit of improved decision making and more informed choice within an overall philosophy of person- and patient-centred care. METHODS: The MCDA-based system generates patient-specific clinical guidance in the form of an opinion as to the merits of the alternative options in a decision, which are all...... software within which the Annalisa file is embedded (Elicia©) customizes and personalizes the presentation and inputs. Principles relevant to the development of such decision-specific MCDA-based aids are noted and comparisons with alternative implementations presented. The necessity to trade...
Full Text Available Decision Support System (DSS aims to help decision maker in the process of making decision, a Spatial Decision Support System (SDSS is a DSS deals with spatial problem or use spatial data in solving a problem. Animal Diseases Spatial Decision Support System (ADSDSS utilizes the capabilities of Data warehouse, Online Analytical Processing (OLAP, Geographic Information System (GIS, data mining techniques and knowledge base systems to provide decision makers with their needed information about the infected animals, infected places and diseases outbreaks. This information is displayed as reports or charts or allocated on a map which illustrates the most and the least affected places in an easy and fast way. So decision makers can take the right decision to control the spread of diseases outbreaks. For building ADSDSS the following steps are done (a Animal diagnosis data from different data bases with climate database collected into a repository data warehouse for generating diagnosis data mart, (b OLAP capabilities integrated with the diagnosis data mart for analysis and aggregation of data, (c One of data mining techniques was applied and integrated into the system (association rules to discover the relationships between different data items, (d GIS spatial analysis and visualization capabilities integrated with the system to analyze diagnosis data and generate maps of diseases and outbreaks, (e decisions suggestion capability integrated into the system to provide decision makers with suggestions and solutions to deal with diseases outbreaks. The experimental results show that the proposed system can provide the decision makers with their needed information in a fast and easy way.
Full Text Available Building owners are encouraged to reduce energy use in order to both contribute to national energy-saving goals and reduce the costs of heating and operation. It is important to choose the most optimal renovation measures available so as to achieve cost-effective energy use while maintaining excellent indoor environments, without sacrificing architectural quality or negatively affecting the environment. Building owners and managers often have neither the time nor the expertise required to properly evaluate the available renovation options before making a final decision. Renovation measures are often calculated to repay investments in a short time, rather than taking into account life-cycle costs (LCC, despite the fact that a thoughtful, comprehensive renovation is often more cost-effective in the long run. This paper presents a systematic approach for evaluating different renovation alternatives based on a number of sustainability criteria. The methodology has been verified using three multi-family apartment buildings in Sweden. The benefit of using the proposed methodology is made clear through a comparison between the different renovation alternatives from a sustainability perspective, and will hopefully serve as encouragement to choose renovation measures which involve marginally increased investments but lead to significant environmental and social benefits in the long-term.
Full Text Available The objective of this work is to establish an information system which would facilitate decision making for the exploitation of a model consisting of the main stakeholders of the university (teachers, students and administrators. This system is based on the relationship between actors (players on the one hand and their activities and their aggregations in a graduate level on the other. It aims to make available to managers of the university a set of dashboards that can improve the quality of education. We will start by modeling the actors upstream and we will study the processes on their own organizations, their activities and their aggregations. This approach is based on the analysis made by the actors to switch to an information technology approach in the process of searching for knowledge. The first applications of this work focus on data related to the department of English Studies at the Faculty of Arts and Humanities at Ibn Zohr University in Agadir, Morocco. The results are encouraging and can be generalized to all courses offered by academic institutions.
Andersson, K.G. (Technical Univ. of Denmark, Risoe National Lab. for Sustainable Energy, Roskilde (Denmark)); Ammann, M. (STUK, Helsinki (Finland)); Backe, S. (IFE, Kjeller (Norway)); Rosen, K. (Swedish Univ. of Agricultural Sciences, Uppsala (Sweden))
The handbook is aimed at providing Nordic decision-makers and their expert advisors with required background material for the development of an optimised, operational preparedness for situations where airborne radioactive matter has contaminated a Nordic inhabited area. The focus is on the mitigation of long-term problems. It should be stressed that the information given in the handbook is comprehensive, and many details require careful consideration well in time before implementation of countermeasures in a specific area. Training sessions are therefore recommended. The handbook describes the current relevant Nordic preparedness (dissemination routes) in detail, and suggests methods for measurement of contamination and prognoses of resultant doses, and data for evaluation of countermeasures and associated waste management options. A number of non-technical aspects of contamination in inhabited areas, and of countermeasures for its mitigation, are discussed, and a series of recommendations on the application of all the handbook data in a holistic countermeasure strategy are given. A part of the handbook development has been a dialogue with end-user representatives in each of the Nordic countries, to focus the work of the specific needs of the users. (au)
Saarela, Olli; Lehtonen, Mikko; Halme, Jari; Aikala, Antti; Raivio, Kimmo
This paper describes a software toolbox (a software library) designed for condition monitoring and diagnosis of machines. This toolbox implements both new methods and prior art and is aimed for practical down-to-earth data analysis work. The target is to improve knowledge of the operation and behaviour of machines and processes throughout their entire life-cycles. The toolbox supports different phases of condition based maintenance with tools that extract essential information and automate data processing. The paper discusses principles that have guided toolbox design and the implemented toolbox structure. Case examples are used to illustrate how condition monitoring applications can be built using the toolbox. In the first case study the toolbox is applied to fault detection of industrial centrifuges based on measured electrical current. The second case study outlines an application for centralized monitoring of a fleet of machines that supports organizational learning.
Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri
Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in
configurable suite of natural language processing ( NLP ) compo- nents, to compute a relevance score for each article and topic. We describe our ensemble...approach, the strategies and tools we use to create labeled data to support this approach, the components in our IR / NLP pipeline, and our results on...Indri/Lemur5 – and includes several text processing and natural lan- guage processing ( NLP ) modules, such as negation tagging, age grouping, and
software domain, enterprise scripting software domain, and outsourcing ( maintenance and training) processes found to be included in the new model but not in...accounting and order entry) software domains, and outsourcing ( maintenance , configuration management and software engineer support) processes were...found in the original model but not in the new model included: enterprise (scripting and order entry) software domains and outsourcing maintenance process
demographics of those gang-hosting areas. Such demographics vary widely. We identified gang culture differences that corresponded with defined...be applied to code-switched African language social media data in Zulu and Swahili to support the Army’s needs and to understand how identity in...20 implicit tracking of language use and demographic associations between physical and virtual cultures . Tuning techniques for Army-relevant
Fossum, Mariann; Ehnfors, Margareta; Fruhling, Ann; Ehrenberg, Anna
The aim was to describe the facilitators and barriers influencing the ability of nursing personnel to effectively use a CDSS for planning and treating pressure ulcers and malnutrition in nursing homes. Usability evaluations and group interviews were conducted. Facilitators were ease of use, usefulness and a supportive work environment. Lack of training, resistance to using computers and limited integration of the CDSS with the electronic health record system were reported. PMID:24199144
Adriaenssens, Veronique; De Baets, Bernard; Goethals, Peter L M; De Pauw, Niels
To facilitate decision support in the ecosystem management, ecological expertise and site-specific data need to be integrated. Fuzzy logic can deal with highly variable, linguistic, vague and uncertain data or knowledge and, therefore, has the ability to allow for a logical, reliable and transparent information stream from data collection down to data usage in decision-making. Several environmental applications already implicate the use of fuzzy logic. Most of these applications have been set up by trial and error and are mainly limited to the domain of environmental assessment. In this article, applications of fuzzy logic for decision support in ecosystem management are reviewed and assessed, with an emphasis on rule-based models. In particular, the identification, optimisation, validation, the interpretability and uncertainty aspects of fuzzy rule-based models for decision support in ecosystem management are discussed.
Ddamba, Joshua; Dittrich, Yvonne
Current literature on urban planning explores how to use ICT to support citizen participation. Advances in open data and its possibility to easily represent data on maps, opens up new opportunities to support participation and decision making in urban projects. This article investigates how spatial...... process and the decisions that are part of it. The paper concludes with design implications for decision support for urban planning. In future research, the intention is to explore these implications in a Participatory Design process....... of an urban renewal project, the article investigates the use of structured and unstructured data for participation. The fieldwork is conducted using ethnographically inspired methods, based on participatory observations, interviews and document analysis. As a result, the incremental decisions, the resulting...
Booth, Steven Richard [Los Alamos National Laboratory
AET-2 has expertise in process modeling, economics, business case analysis, risk assessment, Lean/Six Sigma tools, and decision analysis to provide timely decision support to LANS leading to continuous improvement. This capability is critical during the current tight budgetary environment as LANS pushes to identify potential areas of cost savings and efficiencies. An important arena is business systems and operations, where processes can impact most or all laboratory employees. Lab-wide efforts are needed to identify and eliminate inefficiencies to accomplish Director McMillan’s charge of “doing more with less.” LANS faces many critical and potentially expensive choices that require sound decision support to ensure success. AET-2 is available to provide this analysis support to expedite the decisions at hand.
Ahmed Bahgat El Seddawy
Full Text Available Decision Support System (DSS is equivalent synonym as management information systems (MIS. Most of imported data are being used in solutions like data mining (DM. Decision supporting systems include also decisions made upon individual data from external sources, management feeling, and various other data sources not included in business intelligence. Successfully supporting managerial decision-making is critically dependent upon the availability of integrated, high quality information organized and presented in a timely and easily understood manner. Data mining have emerged to meet this need. They serve as anintegrated repository for internal and external data-intelligence critical to understanding and evaluating the business within its environmental context. With the addition of models, analytic tools, and user interfaces, they have the potential to provide actionable information that supports effective problem and opportunity identification, critical decision-making, and strategy formulation, implementation, and evaluation. The proposed system will support top level management to make a good decision in any time under any uncertain environment.
hmed Bahgat El Seddawy
Full Text Available Decision Support System (DSS is equivalent synonym as management information systems (MIS. Most of imported data are being used in solutions like data mining (DM. Decision supporting systems include also decisions made upon individual data from external sources, management feeling, and various other data sources not included in business intelligence. Successfully supporting managerial decision-making is critically dependent upon the availability of integrated, high quality information organized and presented in a timely and easily understood manner. Data mining have emerged to meet this need. They serve as anintegrated repository for internal and external data-intelligence critical to understanding and evaluating the business within its environmental context. With the addition of models, analytic tools, and user interfaces, they have the potential to provide actionable information that supports effective problem and opportunity identification, critical decision-making, and strategy formulation, implementation, and evaluation. The proposed system will support top level management to make a good decision in any time under any uncertain environment.
Land resource sustainability for urban development characterizes the problem of decision-making with multiplicity and uncertainty. A decision support system prototype aids in the assessment of incremental land development plan proposals put forth within the long-term community priority of a sustainable growth. Facilitating this assessment is the analytic hierarchy process (AHP), a multi-criteria evaluation and decision support system. The decision support system incorporates multiple sustainability criteria, weighted strategically responsive to local public policy priorities and community-specific situations and values, while gauging and directing desirable future courses of development. Furthermore, the decision support system uses a GIS, which facilitates an assessment of urban form with multiple indicators of sustainability as spatial criteria thematically. The resultant land-use sustainability scores indicate, on the ratio-scale of AHP, whether or not a desirable urban form is likely in the long run, and if so, to what degree. The two alternative modes of synthesis in AHP-ideal and distributive-provide assessments of a land development plan incrementally (short-term) and city-wide pattern comprehensively (long-term), respectively. Thus, the spatial decision support system facilitates proactive and collective public policy determination of land resource for future sustainable urban development.
Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.
A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a
Multidimensional databases support efficiently on-line analytical processing (OLAP). In this paper, we depict a model dedicated to multidimensional databases. The approach we present designs decisional information through a constellation of facts and dimensions. Each dimension is possibly shared between several facts and it is organised according to multiple hierarchies. In addition, we define a comprehensive query algebra regrouping the more popular multidimensional operations in current commercial systems and research approaches. We introduce new operators dedicated to a constellation. Finally, we describe a prototype that allows managers to query constellations of facts, dimensions and multiple hierarchies.
The majority of today's software systems and organizational/business structures have been built on the foundation of solving problems via long-term data collection, analysis, and solution design. This traditional approach of solving problems and building corresponding software systems and business processes, falls short in providing the necessary solutions needed to deal with many problems that require agility as the main ingredient of their solution. For example, such agility is needed in responding to an emergency, in military command control, physical security, price-based competition in business, investing in the stock market, video gaming, network monitoring and self-healing, diagnosis in emergency health care, and many other areas that are too numerous to list here. The concept of Observe, Orient, Decide, and Act (OODA) loops is a guiding principal that captures the fundamental issues and approach for engineering information systems that deal with many of these problem areas. However, there are currently few software systems that are capable of supporting OODA. In this talk, we provide a tour of the research issues and state of the art solutions for supporting OODA. In addition, we provide specific examples of OODA solutions we have developed for the video surveillance and emergency response domains.
Brinner Kristin M
Full Text Available Abstract Background Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Discussion Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures, and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. Summary This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In
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.
Rees, Stephen Edward; Karbing, Dan Stieper; Allerød, Charlotte
Management of mechanical ventilation in intensive care patients is complicated by conflicting clinical goals. Decision support systems (DSS) may support clinicians in finding the correct balance. The objective of this study was to evaluate a computerized model-based DSS for its advice on inspired...
De Vent, I.A.E.
This prototype of a diagnostic decision support tool for structural damage in traditional masonry is the result of a PhD research project. The research project has aimed to improve and facilitate the diagnostic process by offering support in the initial phase in which hypotheses are generated. The m
Carlson, Mary L.; And Others
Examined influences on decisions regarding pregnancy outcome in 43 adolescents who completed the Adolescent Life Change Event Questionnaire and the Social Support Questionnaire. Those continuing the pregnancy (N=30) had higher life event change scores, lower social support scores, and more personal and family problems. (JAC)
has included software support for naval tactical systems, intelligence analysis, and research into systems of systems and architecture practice ...UNCLASSIFIED Fit-for-Purpose Visualisation of Architecture to support Defence Capability Decision-Making Kevin O’Shea, Peter Pong and...architecture development approach to capture capability development information with an emphasis on developing a fit-for-purpose visualisation to
Frosch, D.; Legare, F.; Fishbein, M.; Elwyn, G.
ABSTRACT: BACKGROUND: A growing body of literature documents the efficacy of decision support interventions (DESI) in helping patients make informed clinical decisions. DESIs are frequently described as an adjunct to shared decision-making between a patient and healthcare provider, however little is
Full Text Available The Ecosystem Management Decision Support (EMDS system is an application framework for designing and implementing spatially enabled knowledge-based decision support systems for environmental analysis and planning at any geographic scale(s. The system integrates state-of-the-art geographic information system, as well as knowledge-based reasoning and decision modeling, technologies to provide decision support for the adaptive management process of ecosystem management. It integrates a logic engine to perform landscape evaluations, and a decision engine for developing management priorities. The logic component: (1 reasons about large, abstract, multi-faceted ecosystem management problems; (2 performs useful evaluations with incomplete information; (3 evaluates the influence of missing information, and (4 determines priorities for missing information. The planning component determines priorities for management activities, taking into account not only ecosystem condition, but also criteria that account for logistical concerns of potential management actions. Both components include intuitive diagnostic features that facilitate communicating modeling results to a broad audience. Features of the system design that have figured in its success over the past 20 years are highlighted, together with design features planned for the next several versions needed to provide spatial decision support for adaptive management under climate change.
Yan Weiwu(阎威武); Shao Huihe
Many industrial process systems are becoming more and more complex and are characterized by distributed features. To ensure such a system to operate under working order, distributed parameter values are often inspected from subsystems or different points in order to judge working conditions of the system and make global decisions. In this paper, a parallel decision model based on Support Vector Machine (PDMSVM) is introduced and applied to the distributed fault diagnosis in industrial process. PDMSVM is convenient for information fusion of distributed system and it performs well in fault diagnosis with distributed features. PDMSVM makes decision based on synthetic information of subsystems and takes the advantage of Support Vector Machine. Therefore decisions made by PDMSVM are highly reliable and accurate.
MA Zhiliang; LU Ning; GU Weihua
Large amounts of documents are exchanged during the construction phase of projects, which covers the important management information. To utilize the exchanged documents to support decision-making of the management staffs, the requirement analysis was carried out based on the interviews to the practitioners. A decision support system called Explyzer+ was developed based on the previous prototype system Explyzer. The latter was enhanced by adding the functions to automate the whole process and the techniques of data mining including decision tree analysis and clustering analysis. A case study for in-depth information analysis was conducted based on the data obtained from a large construction project to demon-strate its feasibility and effectiveness. The system could effectively assist the management staffs to carry out in-depth information analysis for decision-making in construction projects.
Cornalba, Chiara; Bellazzi, Roberto G; Bellazzi, Riccardo
This paper describes the design and implementation of a decision support system for risk management in hemodialysis (HD) departments. The proposed system exploits a domain ontology to formalize the problem as a Bayesian network. It also relies on a software tool, able to automatically collect HD data, to learn the network conditional probabilities. By merging prior knowledge and the available data, the system allows to estimate risk profiles both for patients and HD departments. The risk management process is completed by an influence diagram that enables scenario analysis to choose the optimal decisions that mitigate a patient's risk. The methods and design of the decision support tool are described in detail, and the derived decision model is presented. Examples and case studies are also shown. The tool is one of the few examples of normative system explicitly conceived to manage operational and clinical risks in health care environments.
Full Text Available In a military environment an operator is typically required to evaluate the tactical situation in real-time and protect defended assets against enemy threats by assigning available weapon systems to engage enemy craft. This environment requires rapid operational planning and decision making under severe stress conditions, and the associated responsibilities are usually divided between a number of operators and computerized decision support systems that aid these operators during the decision making processes. The aim in this paper is to review the state of the art of this kind of threat evaluation and weapon assignment decision support process as it 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 may be generalized to military environments other than a GBADS one.
Wu, Jie Ying; Beland, Michael; Konrad, Joseph; Tuomi, Adam; Glidden, David; Grand, David; Merck, Derek
We propose a general ultrasound (US) texture-analysis and machine-learning framework for detecting the presence of disease that is suitable for clinical application across clinicians, disease types, devices, and operators. Its stages are image selection, image filtering, ROI selection, feature parameterization, and classification. Each stage is modular and can be replaced with alternate methods. Thus, this framework is adaptable to a wide range of tasks. Our two preliminary clinical targets are hepatic steatosis and adenomyosis diagnosis. For steatosis, we collected US images from 288 patients and their pathology-determined values of steatosis (%) from biopsies. Two radiologists independently reviewed all images and identified the region of interest (ROI) most representative of the hepatic echotexture for each patient. To parameterize the images into comparable quantities, we filter the US images at multiple scales for various texture responses. For each response, we collect a histogram of pixel features within the ROI, and parameterize it as a Gaussian function using its mean, standard deviation, kurtosis, and skew to create a 36-feature vector. Our algorithm uses a support vector machine (SVM) for classification. Using a threshold of 10%, we achieved 72.81% overall accuracy, 76.18% sensitivity, and 65.96% specificity in identifying steatosis with leave-ten-out cross-validation (p<0.0001). Extending this framework to adenomyosis, we identified 38 patients with MR-confirmed findings of adenomyosis and previous US studies and 50 controls. A single rater picked the best US-image and ROI for each case. Using the same processing pipeline, we obtained 76.14% accuracy, 86.00% sensitivity, and 63.16% specificity with leave-one-out cross-validation (p<0.0001).
Zandstra, D; Busser, J A S; Aarts, J W M; Nieboer, T E
This review studies women's preferences for shared decision-making about heavy menstrual bleeding treatment and evaluates interventions that support shared decision-making and their effectiveness. PubMed, Cochrane, Embase, Medline and ClinicalTrials.gov were searched. Three research questions were predefined: 1) What is the range of perspectives gathered in studies that examine women facing a decision related to heavy menstrual bleeding management?; 2) What types of interventions have been developed to support shared decision-making for women experiencing heavy menstrual bleeding?; and 3) In what way might women benefit from interventions that support shared decision-making? All original studies were included if the study population consisted of women experiencing heavy menstrual bleeding. We used the TIDieR (Template for Intervention: Description and Replication) checklist to assess the quality of description and the reproducibility of interventions. Interventions were categorized using Grande et al. guidelines and collated and summarized outcomes measures into three categories: 1) patient-reported outcomes; 2) observer-reported outcomes; and 3) doctor-reported outcomes. Fifteen studies were included. Overall, patients preferred to decide together with their doctor (74%). Women's previsit preference was the strongest predictor for treatment choice in two studies. Information packages did not have a statistically significant effect on treatment choice or satisfaction. However, adding a structured interview or decision aid to increase patient involvement did show a positive effect on treatment choice and results, patient satisfaction and shared decision-making related outcomes. In conclusion shared decision-making is becoming more important in the care of women with heavy menstrual bleeding. Structured interviews or well-designed (computerized) tools such as decision aids seem to facilitate this process, but there is room for improvement. A shared treatment choice
Portela, Filipe; Pinto, Filipe; Santos, Manuel Filipe
The introduction of an Intelligent Decision Support System (IDSS) in a critical area like the Intensive Medicine is a complex and difficult process. In this area, their professionals don’t have much time to document the cases, because the patient direct care is always first. With the objective to reduce significantly the manual records and, enabling, at the same time, the possibility of developing an IDSS which can help in the decision making process, all data acquisition process ...
Samwald, Matthias; Dumontier, Michel; Marshall, M Scott; Luciano, Joanne; Adlassnig, Klaus-Peter; 10.3233/978-1-60750-806-9-165
Genetic dispositions play a major role in individual disease risk and treatment response. Genomic medicine, in which medical decisions are refined by genetic information of particular patients, is becoming increasingly important. Here we describe our work and future visions around the creation of a distributed infrastructure for pharmacogenetic data and medical decision support, based on industry standards such as the Web Ontology Language (OWL) and the Arden Syntax.
J. L. Schnase; Carroll, M. L.; Weber, K. T.; Brown, M. E.; R. L. Gill; Wooten, M.; J. May; K. Serr; Smith, E.; Goldsby, R.; K. Newtoff; K. Bradford; Doyle, C; E. Volker; Weber, S
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 wildfi...
Wilk, Szymon; Michalowski, Wojtek; O’Sullivan, Dympna; Farion, Ken; Matwin, Stan
Computerized decision support for use at the point of care has to be comprehensive. It means that clinical information stored in electronic health records needs to be integrated with various forms of clinical knowledge (elicited from experts, discovered from data or summarized in systematic reviews of clinical trials). In order to provide such comprehensive support we created the MET-A3Support framework for constructing clinical applications aimed at various medical conditions. We employed th...
Frize, Monique; Yang, Lan; Walker, Robin C; O'Connor, Annette M
This research is built on the belief that artificial intelligence estimations need to be integrated into clinical social context to create value for health-care decisions. In sophisticated neonatal intensive care units (NICUs), decisions to continue or discontinue aggressive treatment are an integral part of clinical practice. High-quality evidence supports clinical decision-making, and a decision-aid tool based on specific outcome information for individual NICU patients will provide significant support for parents and caregivers in making difficult "ethical" treatment decisions. In our approach, information on a newborn patient's likely outcomes is integrated with the physician's interpretation and parents' perspectives into codified knowledge. Context-sensitive content adaptation delivers personalized and customized information to a variety of users, from physicians to parents. The system provides structuralized knowledge translation and exchange between all participants in the decision, facilitating collaborative decision-making that involves parents at every stage on whether to initiate, continue, limit, or terminate intensive care for their infant.
detail to these models. Operations Research (OR) Community built successively more complicated models, traded verisimilitude for opacity, and in...devices, etc) and make decision to do what next considering its mission and observed situation, and perform its action (dash, open fire, communicate ...education and analysis system for SSC based on modelling and simulation technologies Cost Efectiveness , Concept and Force Strucuture Analysis for
Gimon de Graaf
Full Text Available Translational research is conducted to achieve a predefined set of economic or societal goals. As a result, investment decisions on where available resources have the highest potential in achieving these goals have to be made. In this paper, we first describe how multicriteria decision analysis can assist in defining the decision context and in ensuring that all relevant aspects of the decision problem are incorporated in the decision making process. We then present the results of a case study to support priority setting in a translational research consortium aimed at reducing the burden of disease of type 2 diabetes. During problem structuring, we identified four research alternatives (primary, secondary, tertiary microvascular, and tertiary macrovascular prevention and a set of six decision criteria. Scoring of these alternatives against the criteria was done using a combination of expert judgement and previously published data. Lastly, decision analysis was performed using stochastic multicriteria acceptability analysis, which allows for the combined use of numerical and ordinal data. We found that the development of novel techniques applied in secondary prevention would be a poor investment of research funds. The ranking of the remaining alternatives was however strongly dependent on the decision maker’s preferences for certain criteria.
Doan Ha D.
Full Text Available At the present stage the solution to the problem of decision-making support in the conditions of uncertainty is seen in the application of decision-making support systems (DMSS, which are based on the theory of fuzzy sets and fuzzy logic. One of the most important stages of decision-making support in the conditions of uncertainty is the analysis of the accumulated statistical data. At present, the fuzzy algorithms, including the algorithms of fuzzy clustering of data, are successfully applied to effective research of such data. In recent years, for the effective solution to problems of fuzzy clustering, the device of fuzzy relations that is based on building fuzzy relations of data objects and their properties is widely and successfully used.
Salling, Kim Bang; Pryn, Marie Ridley
risk analysis as well as sustainable planning criteria in the assessment of the project uncovering new solutions. Thereof the decision support model reveals large potential for the inclusion of planning criteria if the overall objective of development toward a sustainable transportation system...... definitions of the criteria planned for, in order to achieve a sustainable transport system. This alternative approach proves that with relatively small changes in objectives, sustainable development within transport planning can be reached.......This article will expose the necessity for a sustainable planning and decision support framework for transport infrastructure assessment. This will be operationalized through a set of planning criteria and scenario alternatives, which is assessed in the SUSTAIN decision support system (SUSTAIN...
Sutcliffe, Alistair; Al-Qaed, Faisal
The paper describes a set of tools designed to support a variety of user decision-making strategies. The tools are complemented by an online advisor so they can be adapted to different domains and users can be guided to adopt appropriate tools for different choices in e-commerce, e.g. purchasing high-value products, exploring product fit to users’ needs, or selecting products which satisfy requirements. The tools range from simple recommenders to decision support by interactive querying and comparison matrices. They were evaluated in a scenario-based experiment which varied the users’ task and motivation, with and without an advisor agent. The results show the tools and advisor were effective in supporting users and agreed with the predictions of ADM (adaptive decision making) theory, on which the design of the tools was based.
Bal, Mert; Amasyali, M Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse
The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.
Full Text Available The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.
Bal, Mert; Amasyali, M. Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse
The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets. PMID:25295291
Haemaelaeinen, R.P.; Lindstedt, M. [Helsinki Univ. of Technology, Otaniemi (Finland). System Analysis Lab.; Sinkko, K.; Ammann, M. [Radiation and Nuclear Safety Authority, Helsinki (Finland); Salo, A. [Lepolantie 54, Helsinki (Finland)
This work was undertaken in order to study the utilisation of decision analysis interviews and of the RODOS system when planning protective actions in the case of a nuclear accident. Six decision analysis interview meetings were organised. Interviewees were competent national safety authorities and technical level decision-makers, i.e., those who are responsible for drawing up advice or making presentations of matters to decision-makers responsible for the practical implementation of the actions. The theme of the meetings was to study how uncertainties could be included in the decision-making process and whether pre-structured generic attributes and value trees would help this process and save time. The approach was to present a generic value tree, a decision table and a selected information package at the beginning of the interviews. The interviewees then examined the suggested value tree in order to ensure that no important factors have been omitted and they made changes when necessary. Also, the decision table was examined and altered by some participants and some of them asked for further information on some issues. But all in all the selected approach allowed for more time and effort to be allocated to value trade-offs and elicitation of risk attitudes. All information was calculated with the support of the RODOS system. Predefined value trees were found to ensure that all relevant factors are considered. The participants also felt that RODOS could provide the required information but, as in previous RODOS exercises, they found it more problematic to use decision analysis methods when planning countermeasures in the early phase of a nuclear accident. Furthermore, it was again noted that understanding the actual meaning 'soft' attributes, such as socio-psychological impacts, was not a straightforward issue. Consequently, the definition of attributes and training in advance would be beneficial. The incorporation of uncertainties also proved to be
Oddo, Paolo; Acierno, Arianna; Cuna, Daniela; Federico, Ivan; Galati, Maria Barbara; Awad, Esam; Korres, Gerasimos; Lecci, Rita; Manzella, Giuseppe M. R.; Merico, Walter; Perivoliotis, Leonidas; Pinardi, Nadia; Shchekinova, Elena; Mannarini, Gianandrea; Vamvakaki, Chrysa; Pecci, Leda; Reseghetti, Franco
A decision Support System is composed by four main steps. The first one is the definition of the problem, the issue to be covered, decisions to be taken. Different causes can provoke different problems, for each of the causes or its effects it is necessary to define a list of information and/or data that are required in order to take the better decision. The second step is the determination of sources from where information/data needed for decision-making can be obtained and who has that information. Furthermore it must be possible to evaluate the quality of the sources to see which of them can provide the best information, and identify the mode and format in which the information is presented. The third step is relying on the processing of knowledge, i.e. if the information/data are fitting for purposes. It has to be decided which parts of the information/data need to be used, what additional data or information is necessary to access, how can information be best presented to be able to understand the situation and take decisions. Finally, the decision making process is an interactive and inclusive process involving all concerned parties, whose different views must be taken into consideration. A knowledge based discussion forum is necessary to reach a consensus. A decision making process need to be examined closely and refined, and modified to meet differing needs over time. The report is presenting legal framework and knowledge base for a scientific based decision support system and a brief exploration of some of the skills that enhances the quality of decisions taken.
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.
Brodin, N. Patrik; Maraldo, Maja V.; Aznar, Marianne C.
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......: 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...
This paper studies urban waterlog-draining decision support system based on the 4D data fusion technique.4D data includes DEM,DOQ,DLG and DRG.It supplies entire databases for waterlog forecast and analysis together with non-spatial fundamental database.Data composition and reasoning are two key steps of 4D data fusion.Finally,this paper gives a real case: Ezhou Waterlog-Draining Decision Support System (EWDSS) with two application models,i.e.,DEM application model,water generating and draining model.
Delavarian, Mona; Towhidkhah, Farzad; Dibajnia, Parvin; Gharibzadeh, Shahriar
In this study, a decision support system was designed to distinguish children with ADHD from other similar children behavioral disorders such as depression, anxiety, comorbid depression and anxiety and conduct disorder based on the signs and symptoms. Accuracy of classifying with Radial basis function and multilayer neural networks were compared. Finally, the average accuracy of the networks in classification reached to 95.50% and 96.62% by multilayer and radial basis function networks respectively. Our results indicate that a decision support system, especially RBF, may be a good preliminary assistant for psychiatrists in diagnosing high risk behavioral disorders of children.
This paper describes the design and proof of concept of a web-based e-business decision-making support system (EBDMSS), to deliver a balanced scorecard (BSC)-based modeling and analysis in support of e-business strategic management. EBDMSS is designed, built and validated through a conceptual design research method. Its design is theoretically underpinned in three DMSS design schemes: an e-business BSC (EBBSC) framework for decision-making process (DMP), a DMSS architecture, and a DMSS design...
Full Text Available A decision support system for production planning in a brewing company was developed to assist with the planning of brewing, packaging and distribution of beer and to minimise production costs. Having been in operation for some time, the system has changed and adapted in a very dynamic environment. The system's present form and current use are discussed. Initial management approval for system development was based on faith rather than proper cost-benefit and value analyses. This paper aims at retrospectively highlighting these values and benefits with regard to supporting decision-making in the company.
Fritzsche, Mathias; Picht, Michael; Gilani, Wasif; Spence, Ivor; Brown, John; Kilpatrick, Peter
What-if Simulations have been identified as one solution for business performance related decision support. Such support is especially useful in cases where it can be automatically generated out of Business Process Management (BPM) Environments from the existing business process models and performance parameters monitored from the executed business process instances. Currently, some of the available BPM Environments offer basic-level performance prediction capabilities. However, these functionalities are normally too limited to be generally useful for performance related decision support at business process level. In this paper, an approach is presented which allows the non-intrusive integration of sophisticated tooling for what-if simulations, analytic performance prediction tools, process optimizations or a combination of such solutions into already existing BPM environments. The approach abstracts from process modelling techniques which enable automatic decision support spanning processes across numerous BPM Environments. For instance, this enables end-to-end decision support for composite processes modelled with the Business Process Modelling Notation (BPMN) on top of existing Enterprise Resource Planning (ERP) processes modelled with proprietary languages.
Moss, R. H.; Patwardhan, A.
This presentation examines decision-making contexts to clarify how globally-oriented scenarios of future demographic, economic, and social conditions (the Shared Socioeconomic Pathways -- SSPs) can be extended or nested with scenarios that are targeted on uncertainties of more immediate concern to decision makers. A number of use cases are explored to identify key uncertainties and the attributes of scenarios that would help decision-makers think through the implications of these uncertainties. These uncertainties concern future conditions at national to regional spatial and governance scales regarding factors outside the locus of control of the decision makers. The exogenous factors that need to be represented in scenarios affect supply and demand of relevant commodities/products, institutional conditions, and vulnerability. They include: demographics & societal conditions; economic growth; policy and institutional context (including public & private responses); technology/resource price and performance; and climate/environmental outcomes. The presentation will explore development of decision-support oriented scenarios that are built from the 'bottom-up' and highlight points of divergence in national/regional social and economic conditions. The authors draw preliminary conclusions regarding methods for nesting decision support scenarios in high-level global narratives.
Andersson-Sköld, Y; Bardos, P; Chalot, M; Bert, V; Crutu, G; Phanthavongsa, P; Delplanque, M; Track, T; Cundy, A B
Marginal, often contaminated, sites exist in large areas across the world as a result of historic activities such as industry, transportation and mineral extraction. Remediation, or other improvements, of these sites is typically only considered for sites with high exploitation pressure and those posing the highest risks to human health or the environment. At the same time there is increasing competition for land resources for different needs such as biofuel production. Potentially some of this land requirement could be met by production of biomass on brownfield or other marginal land, thereby improving the land while applying the crop cultivation as part of an integrated management strategy. The design and decision making for such a strategy will be site specific. A decision support framework, the Rejuvenate DST (decision support tool) has been developed with the aim of supporting such site specific decision making. This tool is presented here, and has been tested by applying it to a number of case study sites. The consequent SWOT (strength, weakness, opportunities and threats) analysis is discussed and evaluated. The DST was found to be systematic, transparent, and applicable for diverse sites in France, Romania and Sweden, in addition to the sites to which it was applied through its development. The DST is regarded as especially useful if applied as a checklist in an iterative way throughout the decision process, from identifying potential crops to identifying knowledge gaps, working/non-working management strategies and potential risks. The DST also provides a structure promoting effective stakeholder engagement.
Mittu, Ranjeev; Lin, Jessica; Li, Qingzhe; Gao, Yifeng; Rangwala, Huzefa; Shargo, Peter; Robinson, Joshua; Rose, Carolyn; Tunison, Paul; Turek, Matt; Thomas, Stephen; Hanselman, Phil
Intelligence analysts and military decision makers are faced with an onslaught of information. From the now ubiquitous presence of intelligence, surveillance, and reconnaissance (ISR) platforms providing large volumes of sensor data, to vast amounts of open source data in the form of news reports, blog postings, or social media postings, the amount of information available to a modern decision maker is staggering. Whether tasked with leading a military campaign or providing support for a humanitarian mission, being able to make sense of all the information available is a challenge. Due to the volume and velocity of this data, automated tools are required to help support reasoned, human decisions. In this paper we describe several automated techniques that are targeted at supporting decision making. Our approaches include modeling the kinematics of moving targets as motifs; developing normalcy models and detecting anomalies in kinematic data; automatically classifying the roles of users in social media; and modeling geo-spatial regions based on the behavior that takes place in them. These techniques cover a wide-range of potential decision maker needs.
Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli
Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.
Full Text Available Research on smart homes (SHs has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.
The United Nations Convention on the Rights of Persons with Disabilities urges and requires changes to how signatories discharge their duties to people with intellectual disabilities, in the direction of their greater recognition as legal persons with expanded decision-making rights. Australian jurisdictions are currently undertaking inquiries and pilot projects that explore how these imperatives should be implemented. One of the important changes advocated is to move from guardianship models to supported or assisted models of decision-making. A driving force behind these developments is a strong allegiance to the social model of disability, in the formulation of the Convention, in inquiries and pilot projects, in implementation and in the related academic literature. Many of these instances suffer from confusing and misleading statements and conceptual misinterpretations of certain elements such as legal capacity, decision-making capacity, and support for decision-making. This paper analyses some of these confusions and their possible negative implications for supported decision-making instruments and those whose interests these instruments would serve, and advises a more incremental development of existing guardianship regimes. This provides a more realistic balance between neglecting the real limits of those with mental disabilities and thereby ignoring their identity and particularity, and continuing to bring them equally and fully into society.
Scherrer, Alexander; Schwidde, Ilka; Dinges, Andreas; Rüdiger, Patrick; Kümmel, Sherko; Küfer, Karl-Heinz
Breast cancer is the most common carcinosis with the largest number of mortalities in women. Its therapy comprises a wide spectrum of different treatment modalities a breast oncologist decides about for the individual patient case. These decisions happen according to medical guide lines, current scientific publications and experiences acquired in former cases. Clinical decision making therefore involves the time-consuming search for possible therapy options and their thorough testing for applicability to the current patient case.This research work addresses breast cancer therapy planning as a multi-criteria sequential decision making problem. The approach is based on a data model for patient cases with therapy descriptions and a mathematical notion for therapeutic relevance of medical information. This formulation allows for a novel decision support concept, which targets at eliminating observed weaknesses in clinical routine of breast cancer therapy planning.
Wild, Christopher; Rosca, Daniela
The business rules that underlie an enterprise emerge as a new category of system requirements that represent decisions about how to run the business, and which are characterized by their business-orientation and their propensity for change. In this report, we introduce a decision making methodology which addresses several aspects of the business rules lifecycle: acquisition, deployment and evolution. We describe a meta-model for representing business rules in terms of an enterprise model, and also a decision support submodel for reasoning about and deriving the rules. The possibility for lifecycle automated assistance is demonstrated in terms of the automatic extraction of business rules from the decision structure. A system based on the metamodel has been implemented, including the extraction algorithm. This is the final report for Daniela Rosca's PhD fellowship. It describes the work we have done over the past year, current research and the list of publications associated with her thesis topic.
Full Text Available Abstract Background The use of computerized clinical decision support systems (CCDSSs may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease and associated patient outcomes (such as effects on biomarkers and clinical exacerbations. Methods We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes. Results Of 55 included trials, 87% (n = 48 measured system impact on the process of care and 52% (n = 25 of those demonstrated statistically significant improvements. Sixty-five percent (36/55 of trials measured impact on, typically, non-major (surrogate patient outcomes, and 31% (n = 11 of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported. Conclusions A small majority (just over half of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies
Alongi, M.; Howard, C.; Kasprzyk, J. R.; Ryan, J. N.
Unconventional oil and gas development (UOGD) using hydraulic fracturing and horizontal drilling has recently fostered an unprecedented acceleration in energy development. Regulations seek to protect environmental quality of areas surrounding UOGD, while maintaining economic benefits. One such regulation is a setback distance, which dictates the minimum proximity between an oil and gas well and an object such as a residential or commercial building, property line, or water source. In general, most setback regulations have been strongly politically motivated without a clear scientific basis for understanding the relationship between the setback distance and various performance outcomes. This presentation discusses a new decision support framework for setback regulations, as part of a large NSF-funded sustainability research network (SRN) on UOGD. The goal of the decision support framework is to integrate a wide array of scientific information from the SRN into a coherent framework that can help inform policy regarding UOGD. The decision support framework employs multiobjective evolutionary algorithm (MOEA) optimization coupled with simulation models of air quality and other performance-based outcomes on UOGD. The result of the MOEA optimization runs are quantitative tradeoff curves among different objectives. For example, one such curve could demonstrate air pollution concentrations versus estimates of energy development profits, for different levels of setback distance. Our results will also inform policy-relevant discussions surrounding UOGD such as comparing single- and multi-well pads, as well as regulations on the density of well development over a spatial area.
Hameed Syed M
Full Text Available Abstract Background During a mass casualty incident, evacuation of patients to the appropriate health care facility is critical to survival. Despite this, no existing system provides the evidence required to make informed evacuation decisions from the scene of the incident. To mitigate this absence and enable more informed decision making, a web based spatial decision support system (SDSS was developed. This system supports decision making by providing data regarding hospital proximity, capacity, and treatment specializations to decision makers at the scene of the incident. Methods This web-based SDSS utilizes pre-calculated driving times to estimate the actual driving time to each hospital within the inclusive trauma system of the large metropolitan region within which it is situated. In calculating and displaying its results, the model incorporates both road network and hospital data (e.g. capacity, treatment specialties, etc., and produces results in a matter of seconds, as is required in a MCI situation. In addition, its application interface allows the user to map the incident location and assists in the execution of triage decisions. Results Upon running the model, driving time from the MCI location to the surrounding hospitals is quickly displayed alongside information regarding hospital capacity and capability, thereby assisting the user in the decision-making process. Conclusions The use of SDSS in the prioritization of MCI evacuation decision making is potentially valuable in cases of mass casualty. The key to this model is the utilization of pre-calculated driving times from each hospital in the region to each point on the road network. The incorporation of real-time traffic and hospital capacity data would further improve this model.
Hongsermeier, Tonya; Maviglia, Saverio; Tsurikova, Lana; Bogaty, Dan; Rocha, Roberto A; Goldberg, Howard; Meltzer, Seth; Middleton, Blackford
The goal of the CDS Consortium (CDSC) is to assess, define, demonstrate, and evaluate best practices for knowledge management and clinical decision support in healthcare information technology at scale - across multiple ambulatory care settings and Electronic Health Record technology platforms. In the course of the CDSC research effort, it became evident that a sound legal foundation was required for knowledge sharing and clinical decision support services in order to address data sharing, intellectual property, accountability, and liability concerns. This paper outlines the framework utilized for developing agreements in support of sharing, accessing, and publishing content via the CDSC Knowledge Management Portal as well as an agreement in support of deployment and consumption of CDSC developed web services in the context of a research project under IRB oversight.
GALANTE, A. C.
Full Text Available The Macaé County is one of the greatest economy of the state of Rio de Janeiro. With the use of the information technology is possible to create a powerful tool for supporting the decision making processing for this County, aiding the process of improvement of life quality. For that one, intends to use a Decision Support System able to give different kind of information of County areas, like health and education. For the union of all information the datawarehouse technology will be used. For query implementation the technologies of OLAP and GIS are used together. Therefore, those technologies together make a powerful tool for aiding the decision making process of the Macaé County.
AbuKhousa, Eman; Al-Jaroodi, Jameela; Lazarova-Molnar, Sanja; Mohamed, Nader
Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM) by improving the decision making pertaining processes' efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM) has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges.
Yu, Fan-Chieh; Chen, Chien-Yuan; Lin, Sheng-Chi; Lin, Yu-Ching; Wu, Shang-Yu; Cheung, Kei-Wai
A WebGIS decision support system for slopeland hazard warning based on real-time monitored rainfall is introduced herein. This paper presents its framework, database, processes of setting up the threshold line for debris flow triggering and the calculation algorithm implemented in the system. The web-based GIS via the Microsoft Internet Explorer is designed for analysis of areas prone to debris flows outburst and landslides during torrential rain. Its function is to provide suggestions to commander for immediate response to the possibility of slopeland hazards, and determine if pre-evacuation is necessary. The defining characteristics of the internet-based decision support system is not to automatically show the dangerous areas but acts as part of the decision process via information collection to help experts judge the prone debris flow creeks and the tendency of landslides initiation. The combination with real-time rainfall estimation by the QPESUMS radar system is suggested for further enhancement.
Full Text Available Equipping farm machines is the key link of agricultural production process. The decision support system of equipping farm machines is able to aid managers to make scientific and effective decision. In this paper, the decision support system of equipping farm machines is designed and developed based on the related theories and the thought of prototype. The system chooses Delphi 7.0 as development language, and uses three classic equipping methods to establish system models. For the complex linear programming model, firstly it is established by M-file of Matlab, then COM components are generated; finally Delphi calls the COM components to solve. The database of the system is established and managed by SQL Server 2005. It can be seen from the result of the system application study that the system could assist users to equip farm machines more scientifically and dynamically
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.
Full Text Available Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM by improving the decision making pertaining processes’ efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges.
Kallestrup, Kasper Bislev; Lynge, Lasse Hadberg; Akkerman, Renzo;
In this paper, we discuss the development of decision support systems for hierarchically structured planning approaches, such as commercially available advanced planning systems. We develop a framework to show how such a decision support system can be designed with the existing organization in mind......, and how a decision process and corresponding software can be developed from this basis. Building on well-known hierarchical planning concepts, we include the typical anticipation mechanisms used in such systems to be able to decompose planning problems, both from the perspective of the planning problem...... and from the perspective of the organizational aspects involved. To exemplify and develop our framework, we use a case study of crude oil procurement planning in the refining industry. The results of the case study indicate an improved organizational embedding of the DSS, leading to significant savings...
Chang, Yao-Jen; Lin, Min-Der
Municipal solid waste management (MSWM) is an important, practical and challenging environmental subject. The processes of a MSWM system include household collection, transportation, treatment, material recycling, compost and disposal. A regional program of MSWM is more complicated owing to the involvement of multi-municipality and multi-facility issues. Therefore, an effective decision support system capable of solving regional MSWM problems is necessary for decision-makers. This article employs linear programming techniques to establish a MSWM decision support system (MSWM-DSS) that is able to determine the least costs of regional MSWM strategies. The results of investigating a real-world case in central Taiwan indicate that a regional program is more economical and efficient. For the redeployment of MSW streams, the relatively least cost of operation for the MSWM system can still be achieved through the re-estimation of the MSWM-DSS. This tool and results are useful for MSWM policy-making in central Taiwan.
Deshpande, Ruchi; DeMarco, John; Kessel, Kerstin; Liu, Brent J.
We have developed an imaging informatics based decision support system that learns from retrospective treatment plans to provide recommendations for healthy tissue sparing to prospective incoming patients. This system incorporates a model of best practices from previous cases, specific to tumor anatomy. Ultimately, our hope is to improve clinical workflow efficiency, patient outcomes and to increase clinician confidence in decision-making. The success of such a system depends greatly on the training dataset, which in this case, is the knowledge base that the data-mining algorithm employs. The size and heterogeneity of the database is essential for good performance. Since most institutions employ standard protocols and practices for treatment planning, the diversity of this database can be greatly increased by including data from different institutions. This work presents the results of incorporating cross-country, multi-institutional data into our decision support system for evaluation and testing.
Many of our everyday concepts are vague. It is next to impossible, for example, to state necessary and sufficient conditions for something to be a chair, or a building. This would appear to pose a potential problem for the construction of knowledge-based decision-support systems; notably systems ...
Ozaltin, Nur Ozge; Besterfield-Sacre, Mary; Clark, Renee M.
Learning how to design innovatively is a critical process skill for undergraduate engineers in the 21st century. To this end, our paper discusses the development and validation of a Bayesian network decision support tool that can be used by engineering educators to make recommendations that positively impact the innovativeness of product designs.…
The second generation of the Waste Reduction (WAR) Algorithm is constructed as a decision support system (DSS) in the design of chemical manufacturing facilities. The WAR DSS is a software tool that can help reduce the potential environmental impacts (PEIs) of industrial chemical...
Cegarra, J.; van Wezel, Wouter
In this article, the authors focus on scheduling situations. Because of their unstructured nature and hard combinatorial complexity, scheduling situations have always been a predominant application area for decision support systems (DSSes). After setting out the generic characteristics of a DSS, the
Streefkerk, J.W.; Smets, N.; Varkevisser, M.; Hiemstra-Van Mastrigt, S.
On future battlefields, increasingly more sensor information will become available for military commanders to support mission execution. To improve (shared) situational awareness, decision-making and communication in face of this increased amount of information, the design of command and control (C2
Bauer, Nerissa S.; Sturm, Lynne A.; Carroll, Aaron E.; Downs, Stephen M.
An autism module was added to an existing computer decision support system (CDSS) to facilitate adherence to recommended guidelines for screening for autism spectrum disorders in primary care pediatric clinics. User satisfaction was assessed by survey and informal feedback at monthly meetings between clinical staff and the software team. To assess…
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.
Ierland, van E.C.
The KfC program Decision Support Tools aims at improving tools for design and evaluation of adaptation strategies with a special focus on spatial planning and cross cutting issues. The program focuses on three core elements 1. tools for formulation of the adaptation task, based on climate scenarios
In this paper, we give an overview of methadone treatment in Ireland and outline the rationale for designing an electronic health record (EHR) with extensibility, interoperability and decision support functionality. Incorporating several international standards, a conceptual model applying a problem orientated approach in a hierarchical structure has been proposed for building the EHR.
Linden AMA van der; Douven WJAM; Herrchen M; Ferioli A; Hoogenboom FGG; LBG; VUA; FHG; ISPS
Dit rapport beschrijft de definitie van het project 'Development of decision support systems for the admission of pesticides', zoals dat wordt uitgevoerd met de "Environment Research Programm (1990 - 1994) van de Europese Unie, als sponsor, onder contract nummer EV5V-CT92-0217. De
In this dissertation we develop a framework that combines data mining, statistics and operations research methods for improving real-time decision support systems in healthcare. Our approach consists of three main concepts: data gathering and preprocessing, modeling, and deployment. We introduce the notion of offline and semi-offline modeling to…
Harms, W.B.; Knaapen, J.P.; Roos-Klein-Lankhorst sic, J.
To evaluate scenarios for nature restoration, a landscape ecological decision-support system has been developed, a knowledge-based system integrated in a geographical information system. The grid-based application in the Central Open Space of the Netherlands (the COSMO model) is presented here. Four
thoracic or abdominal hematomas, (3) explicit vascular injury that required operative repair, or (4) limb amputation . • Alternative definitions...which an automated computer algorithm processes available data and, through artificial intelligence, offers caregivers accurate information about...processing, artificial intelligence, and knowledge engineering technologies to develop an automated decision-support system. Our system for major hemorrhage
Nielsen, Ulrik Dam; Lajic, Zoran; Jensen, Jørgen Juncher
Fault detection and isolation are very important elements in the design of fault-tolerant decision support systems for ship operator guidance. This study outlines remedies that can be applied for fault diagnosis, when the ship responses are assumed to be linear in the wave excitation. A novel...
Heringa, Mette; Floor-Schreudering, Annemieke; Tromp, P. Chris; de Smet, Peter A G M; Bouvy, Marcel L.
Purpose: The purpose of this study is to investigate the nature, frequency, and determinants of drug therapy alerts generated by a clinical decision support system (CDSS) in community pharmacy in order to propose CDSS improvement strategies. Methods: This is a retrospective analysis of dispensed dru
ZHAI Li-li; GAO Chang-yuan; HAO Hong-jun
According to the relation of the developing speed and scale of higher education and those of national economy, the establishing method and structure of higher education appropriate scale DSS (HEASDSS) are researched applying to educational economic principle and decision support system theory.
A land allocation model for sustainable industrial forest plantation (IFP) project establishment is developed in this research. The model provides the foundation for a spatial decision support system (DSS) that deals with analytical and practical problem solving in IFP land allocation in Indonesia.
Helmons, Pieter J.; Suijkerbuijk, Bas O.; Nannan Panday, Prashant V.; Kosterink, Jos G. W.
Increased budget constraints and a continuous focus on improved quality require an efficient inpatient drug surveillance process. We describe a hospital-wide drug surveillance strategy consisting of a multidisciplinary evaluation of drug surveillance activities and using clinical decision support to
Full Text Available A lack of mature domain knowledge and well established guidelines makes the medical diagnosis of skeletal dysplasias (a group of rare genetic disorders a very complex process. Machine learning techniques can facilitate objective interpretation of medical observations for the purposes of decision support. However, building decision support models using such techniques is highly problematic in the context of rare genetic disorders, because it depends on access to mature domain knowledge. This paper describes an approach for developing a decision support model in medical domains that are underpinned by relatively sparse knowledge bases. We propose a solution that combines association rule mining with the Dempster-Shafer theory (DST to compute probabilistic associations between sets of clinical features and disorders, which can then serve as support for medical decision making (e.g., diagnosis. We show, via experimental results, that our approach is able to provide meaningful outcomes even on small datasets with sparse distributions, in addition to outperforming other Machine Learning techniques and behaving slightly better than an initial diagnosis by a clinician.
Lang, Robin Lynn Neal
A growing national emphasis has been placed on health information technology (HIT) with robust computerized clinical decision support (CCDS) integration into health care delivery. Catheter-associated urinary tract infection is the most frequent health care-associated infection in the United States and is associated with high cost, high volumes and…
Delgado-Ortegon, Alberto; Jensen, Rune Møller; Guilbert, Nicolas
Decision support systems have become a viable approach to tackle complex optimization problems. The combination of experts' know-how and efficient optimization algorithms can dramatically improve solution quality and reduce work time. Some of these systems rely on continuous interaction with thei...
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
Gintautas, Tomas; Sørensen, John Dalsgaard
This paper briefly describes a novel approach of estimating weather windows for decision support in offshore wind turbine installation projects. The proposed methodology is based on statistical analysis of extreme physical responses of the installation equipment (such as lifting cable loads, moti...
Spiegel, van der M.; Sterrenburg, P.; Haasnoot, W.; Fels-Klerx, van der H.J.
Decision support systems (DSS) for controlling multiple food safety hazards in raw milk production have not yet been developed, but the underlying components are fragmentarily available. This article presents the state-of-the-art of essential DSS elements for judging food safety compliance of raw mi
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) groundw