Propulsion Airframe Aeroacoustics Technology Evaluation and Selection Using a Multi-Attribute Decision Making Process and Non-Deterministic Design

NASA Technical Reports Server (NTRS)

Burg, Cecile M.; Hill, Geoffrey A.; Brown, Sherilyn A.; Geiselhart, Karl A.

2004-01-01

The Systems Analysis Branch at NASA Langley Research Center has investigated revolutionary Propulsion Airframe Aeroacoustics (PAA) technologies and configurations for a Blended-Wing-Body (BWB) type aircraft as part of its research for NASA s Quiet Aircraft Technology (QAT) Project. Within the context of the long-term NASA goal of reducing the perceived aircraft noise level by a factor of 4 relative to 1997 state of the art, major configuration changes in the propulsion airframe integration system were explored with noise as a primary design consideration. An initial down-select and assessment of candidate PAA technologies for the BWB was performed using a Multi-Attribute Decision Making (MADM) process consisting of organized brainstorming and decision-making tools. The assessments focused on what effect the PAA technologies had on both the overall noise level of the BWB and what effect they had on other major design considerations such as weight, performance and cost. A probabilistic systems analysis of the PAA configurations that presented the best noise reductions with the least negative impact on the system was then performed. Detailed results from the MADM study and the probabilistic systems analysis will be published in the near future.

Trusted Advisors, Decision Models and Other Keys to Communicating Science to Decision Makers

NASA Astrophysics Data System (ADS)

Webb, E.

2006-12-01

Water resource management decisions often involve multiple parties engaged in contentious negotiations that try to navigate through complex combinations of legal, social, hydrologic, financial, and engineering considerations. The standard approach for resolving these issues is some form of multi-party negotiation, a formal court decision, or a combination of the two. In all these cases, the role of the decision maker(s) is to choose and implement the best option that fits the needs and wants of the community. However, each path to a decision carries the risk of technical and/or financial infeasibility as well as the possibility of unintended consequences. To help reduce this risk, decision makers often rely on some type of predictive analysis from which they can evaluate the projected consequences of their decisions. Typically, decision makers are supported in the analysis process by trusted advisors who engage in the analysis as well as the day to day tasks associated with multi-party negotiations. In the case of water resource management, the analysis is frequently a numerical model or set of models that can simulate various management decisions across multiple systems and output results that illustrate the impact on areas of concern. Thus, in order to communicate scientific knowledge to the decision makers, the quality of the communication between the analysts, the trusted advisor, and the decision maker must be clear and direct. To illustrate this concept, a multi-attribute decision analysis matrix will be used to outline the value of computer model-based collaborative negotiation approaches to guide water resources decision making and communication with decision makers. In addition, the critical role of the trusted advisor and other secondary participants in the decision process will be discussed using examples from recent water negotiations.

Comparison of two multi-criteria decision techniques for eliciting treatment preferences in people with neurological disorders.

PubMed

Ijzerman, Maarten J; van Til, Janine A; Snoek, Govert J

2008-12-01

To present and compare two multi-criteria decision techniques (analytic hierarchy process [AHP] and conjoint analysis [CA]) for eliciting preferences in patients with cervical spinal cord injury (SCI) who are eligible for surgical augmentation of hand function, either with or without implantation of a neuroprosthesis. The methods were compared in respect to attribute weights, overall preference, and practical experiences. Two previously designed and administered multi-criteria decision surveys in patients with SCI were compared and further analysed. Attributes and their weights in the AHP experiment were determined by an expert panel, followed by determination of the weights in the patient group. Attributes for the CA were selected and validated using an expert panel, piloted in six patients with SCI and subsequently administered to the same group of patients as participated in the AHP experiment. Both experiments showed the importance of non-outcome-related factors such as inpatient stay and number of surgical procedures. In particular, patients were less concerned with clinical outcomes in actual decision making. Overall preference in both the AHP and CA was in favor of tendon reconstruction (0.6 vs 0.4 for neuroprosthetic implantation). Both methods were easy to apply, but AHP was less easily explained and understood. Both the AHP and CA methods produced similar outcomes, which may have been caused by the obvious preferences of patients. CA may be preferred because of the holistic approach of considering all treatment attributes simultaneously and, hence, its power in simulating real market decisions. On the other hand, the AHP method is preferred as a hands-on, easy-to-implement task with immediate feedback to the respondent. This flexibility allows AHP to be used in shared decision making. However, the way the technique is composed results in many inconsistencies. Patients preferred CA but complained about the number of choice tasks.

Screening and Evaluation Tool (SET) Users Guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pincock, Layne

This document is the users guide to using the Screening and Evaluation Tool (SET). SET is a tool for comparing multiple fuel cycle options against a common set of criteria and metrics. It does this using standard multi-attribute utility decision analysis methods.

Multi-criteria decision analysis in environmental sciences: ten years of applications and trends.

PubMed

Huang, Ivy B; Keisler, Jeffrey; Linkov, Igor

2011-09-01

Decision-making in environmental projects requires consideration of trade-offs between socio-political, environmental, and economic impacts and is often complicated by various stakeholder views. Multi-criteria decision analysis (MCDA) emerged as a formal methodology to face available technical information and stakeholder values to support decisions in many fields and can be especially valuable in environmental decision making. This study reviews environmental applications of MCDA. Over 300 papers published between 2000 and 2009 reporting MCDA applications in the environmental field were identified through a series of queries in the Web of Science database. The papers were classified by their environmental application area, decision or intervention type. In addition, the papers were also classified by the MCDA methods used in the analysis (analytic hierarchy process, multi-attribute utility theory, and outranking). The results suggest that there is a significant growth in environmental applications of MCDA over the last decade across all environmental application areas. Multiple MCDA tools have been successfully used for environmental applications. Even though the use of the specific methods and tools varies in different application areas and geographic regions, our review of a few papers where several methods were used in parallel with the same problem indicates that recommended course of action does not vary significantly with the method applied. Published by Elsevier B.V.

Evaluate the use of tanning agent in leather industry using material flow analysis, life cycle assessment and fuzzy multi-attribute decision making (FMADM)

NASA Astrophysics Data System (ADS)

Alfarisi, Salman; Sutono, Sugoro Bhakti; Sutopo, Wahyudi

2017-11-01

Tanning industry is one of the companies that produce many pollutants and cause the negative impact on the environment. In the production process of tanning leather, the use of input material need to be evaluated. The problem of waste, not only have a negative impact on the environment, but also human health. In this study, the impact of mimosa as vegetable tanning agent evaluated. This study will provide alternative solutions for improvements to the use of vegetable tanning agent. The alternative solution is change mimosa with indusol, gambier, and dulcotan. This study evaluate the vegetable tanning of some aspects using material flow analysis and life cycle assessment approach. Life cycle assessment (LCA) is used to evaluate the environmental impact of vegetable tanning agent. Alternative solution selection using fuzzy multi-attribute decision making (FMADM) approach. Results obtained by considering the environment, human toxicity, climate change, and marine aquatic ecotoxicity, is to use dulcotan.

Robust Sensitivity Analysis for Multi-Attribute Deterministic Hierarchical Value Models

DTIC Science & Technology

2002-03-01

such as weighted sum method, weighted 5 product method, and the Analytic Hierarchy Process ( AHP ). This research focuses on only weighted sum...different groups. They can be termed as deterministic, stochastic, or fuzzy multi-objective decision methods if they are classified according to the...weighted product model (WPM), and analytic hierarchy process ( AHP ). His method attempts to identify the most important criteria weight and the most

Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average.

PubMed

Gorsevski, Pece V; Donevska, Katerina R; Mitrovski, Cvetko D; Frizado, Joseph P

2012-02-01

This paper presents a GIS-based multi-criteria decision analysis approach for evaluating the suitability for landfill site selection in the Polog Region, Macedonia. The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process. Copyright © 2011 Elsevier Ltd. All rights reserved.

The eyes have it: Using eye tracking to inform information processing strategies in multi-attributes choices.

PubMed

Ryan, Mandy; Krucien, Nicolas; Hermens, Frouke

2018-04-01

Although choice experiments (CEs) are widely applied in economics to study choice behaviour, understanding of how individuals process attribute information remains limited. We show how eye-tracking methods can provide insight into how decisions are made. Participants completed a CE, while their eye movements were recorded. Results show that although the information presented guided participants' decisions, there were also several processing biases at work. Evidence was found of (a) top-to-bottom, (b) left-to-right, and (c) first-to-last order biases. Experimental factors-whether attributes are defined as "best" or "worst," choice task complexity, and attribute ordering-also influence information processing. How individuals visually process attribute information was shown to be related to their choices. Implications for the design and analysis of CEs and future research are discussed. Copyright © 2017 John Wiley & Sons, Ltd.

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

PubMed

Dolan, James G

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare

PubMed Central

Dolan, James G.

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218

A consensus reaching model for 2-tuple linguistic multiple attribute group decision making with incomplete weight information

NASA Astrophysics Data System (ADS)

Zhang, Wancheng; Xu, Yejun; Wang, Huimin

2016-01-01

The aim of this paper is to put forward a consensus reaching method for multi-attribute group decision-making (MAGDM) problems with linguistic information, in which the weight information of experts and attributes is unknown. First, some basic concepts and operational laws of 2-tuple linguistic label are introduced. Then, a grey relational analysis method and a maximising deviation method are proposed to calculate the incomplete weight information of experts and attributes respectively. To eliminate the conflict in the group, a weight-updating model is employed to derive the weights of experts based on their contribution to the consensus reaching process. After conflict elimination, the final group preference can be obtained which will give the ranking of the alternatives. The model can effectively avoid information distortion which is occurred regularly in the linguistic information processing. Finally, an illustrative example is given to illustrate the application of the proposed method and comparative analysis with the existing methods are offered to show the advantages of the proposed method.

Some induced intuitionistic fuzzy aggregation operators applied to multi-attribute group decision making

NASA Astrophysics Data System (ADS)

Su, Zhi-xin; Xia, Guo-ping; Chen, Ming-yuan

2011-11-01

In this paper, we define various induced intuitionistic fuzzy aggregation operators, including induced intuitionistic fuzzy ordered weighted averaging (OWA) operator, induced intuitionistic fuzzy hybrid averaging (I-IFHA) operator, induced interval-valued intuitionistic fuzzy OWA operator, and induced interval-valued intuitionistic fuzzy hybrid averaging (I-IIFHA) operator. We also establish various properties of these operators. And then, an approach based on I-IFHA operator and intuitionistic fuzzy weighted averaging (WA) operator is developed to solve multi-attribute group decision-making (MAGDM) problems. In such problems, attribute weights and the decision makers' (DMs') weights are real numbers and attribute values provided by the DMs are intuitionistic fuzzy numbers (IFNs), and an approach based on I-IIFHA operator and interval-valued intuitionistic fuzzy WA operator is developed to solve MAGDM problems where the attribute values provided by the DMs are interval-valued IFNs. Furthermore, induced intuitionistic fuzzy hybrid geometric operator and induced interval-valued intuitionistic fuzzy hybrid geometric operator are proposed. Finally, a numerical example is presented to illustrate the developed approaches.

Schizophrenia: multi-attribute utility theory approach to selection of atypical antipsychotics.

PubMed

Bettinger, Tawny L; Shuler, Garyn; Jones, Donnamaria R; Wilson, James P

2007-02-01

Current guidelines/algorithms recommend atypical antipsychotics as first-line agents for the treatment of schizophrenia. Because there are extensive healthcare costs associated with the treatment of schizophrenia, many institutions and health systems are faced with making restrictive formulary decisions regarding the use of atypical antipsychotics. Often, medication acquisition costs are the driving force behind formulary decisions, while other treatment factors are not considered. To apply a multi-attribute utility theory (MAUT) analysis to aid in the selection of a preferred agent among the atypical antipsychotics for the treatment of schizophrenia. Five atypical antipsychotics (risperidone, olanzapine, quetiapine, ziprasidone, aripiprazole) were selected as the alternative agents to be included in the MAUT analysis. The attributes identified for inclusion in the analysis were efficacy, adverse effects, cost, and adherence, with relative weights of 35%, 35%, 20%, and 10%, respectively. For each agent, attribute scores were calculated, weighted, and then summed to generate a total utility score. The agent with the highest total utility score was considered the preferred agent. Aripiprazole, with a total utility score of 75.8, was the alternative agent with the highest total utility score in this model. This was followed by ziprasidone, risperidone, and quetiapine, with total utility scores of 71.8, 69.0, and 65.9, respectively. Olanzapine received the lowest total utility score. A sensitivity analysis was performed and failed to displace aripiprazole as the agent with the highest total utility score. This model suggests that aripiprazole should be considered a preferred agent for the treatment of schizophrenia unless found to be otherwise inappropriate.

Multi-Attribute Consensus Building Tool

ERIC Educational Resources Information Center

Shyyan, Vitaliy; Christensen, Laurene; Thurlow, Martha; Lazarus, Sheryl

2013-01-01

The Multi-Attribute Consensus Building (MACB) method is a quantitative approach for determining a group's opinion about the importance of each item (strategy, decision, recommendation, policy, priority, etc.) on a list (Vanderwood, & Erickson, 1994). This process enables a small or large group of participants to generate and discuss a set…

An optimized solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman filter

NASA Astrophysics Data System (ADS)

Gorsevski, Pece V.; Jankowski, Piotr

2010-08-01

The Kalman recursive algorithm has been very widely used for integrating navigation sensor data to achieve optimal system performances. This paper explores the use of the Kalman filter to extend the aggregation of spatial multi-criteria evaluation (MCE) and to find optimal solutions with respect to a decision strategy space where a possible decision rule falls. The approach was tested in a case study in the Clearwater National Forest in central Idaho, using existing landslide datasets from roaded and roadless areas and terrain attributes. In this approach, fuzzy membership functions were used to standardize terrain attributes and develop criteria, while the aggregation of the criteria was achieved by the use of a Kalman filter. The approach presented here offers advantages over the classical MCE theory because the final solution includes both the aggregated solution and the areas of uncertainty expressed in terms of standard deviation. A comparison of this methodology with similar approaches suggested that this approach is promising for predicting landslide susceptibility and further application as a spatial decision support system.

Evaluation of infectious diseases and clinical microbiology specialists' preferences for hand hygiene: analysis using the multi-attribute utility theory and the analytic hierarchy process methods.

PubMed

Suner, Aslı; Oruc, Ozlem Ege; Buke, Cagri; Ozkaya, Hacer Deniz; Kitapcioglu, Gul

2017-08-31

Hand hygiene is one of the most effective attempts to control nosocomial infections, and it is an important measure to avoid the transmission of pathogens. However, the compliance of healthcare workers (HCWs) with hand washing is still poor worldwide. Herein, we aimed to determine the best hand hygiene preference of the infectious diseases and clinical microbiology (IDCM) specialists to prevent transmission of microorganisms from one patient to another. Expert opinions regarding the criteria that influence the best hand hygiene preference were collected through a questionnaire via face-to-face interviews. Afterwards, these opinions were examined with two widely used multi-criteria decision analysis (MCDA) methods, the Multi-Attribute Utility Theory (MAUT) and the Analytic Hierarchy Process (AHP). A total of 15 IDCM specialist opinions were collected from diverse private and public hospitals located in İzmir, Turkey. The mean age of the participants was 49.73 ± 8.46, and the mean experience year of the participants in their fields was 17.67 ± 11.98. The findings that we obtained through two distinct decision making methods, the MAUT and the AHP, suggest that alcohol-based antiseptic solution (ABAS) has the highest utility (0.86) and priority (0.69) among the experts' choices. In conclusion, the MAUT and the AHP, decision models developed here indicate that rubbing the hands with ABAS is the most favorable choice for IDCM specialists to prevent nosocomial infection.

Technology selection for ballast water treatment by multi-stakeholders: A multi-attribute decision analysis approach based on the combined weights and extension theory.

PubMed

Ren, Jingzheng

2018-01-01

This objective of this study is to develop a generic multi-attribute decision analysis framework for ranking the technologies for ballast water treatment and determine their grades. An evaluation criteria system consisting of eight criteria in four categories was used to evaluate the technologies for ballast water treatment. The Best-Worst method, which is a subjective weighting method and Criteria importance through inter-criteria correlation method, which is an objective weighting method, were combined to determine the weights of the evaluation criteria. The extension theory was employed to prioritize the technologies for ballast water treatment and determine their grades. An illustrative case including four technologies for ballast water treatment, i.e. Alfa Laval (T 1 ), Hyde (T 2 ), Unitor (T 3 ), and NaOH (T 4 ), were studied by the proposed method, and the Hyde (T 2 ) was recognized as the best technology. Sensitivity analysis was also carried to investigate the effects of the combined coefficients and the weights of the evaluation criteria on the final priority order of the four technologies for ballast water treatment. The sum weighted method and the TOPSIS was also employed to rank the four technologies, and the results determined by these two methods are consistent to that determined by the proposed method in this study. Copyright © 2017 Elsevier Ltd. All rights reserved.

Experimental analysis of multi-attribute decision-making based on Atanassov intuitionistic fuzzy sets: a discussion of anchor dependency and accuracy functions

NASA Astrophysics Data System (ADS)

Chen, Ting-Yu

2012-06-01

This article presents a useful method for relating anchor dependency and accuracy functions to multiple attribute decision-making (MADM) problems in the context of Atanassov intuitionistic fuzzy sets (A-IFSs). Considering anchored judgement with displaced ideals and solution precision with minimal hesitation, several auxiliary optimisation models have proposed to obtain the optimal weights of the attributes and to acquire the corresponding TOPSIS (the technique for order preference by similarity to the ideal solution) index for alternative rankings. Aside from the TOPSIS index, as a decision-maker's personal characteristics and own perception of self may also influence the direction in the axiom of choice, the evaluation of alternatives is conducted based on distances of each alternative from the positive and negative ideal alternatives, respectively. This article originates from Li's [Li, D.-F. (2005), 'Multiattribute Decision Making Models and Methods Using Intuitionistic Fuzzy Sets', Journal of Computer and System Sciences, 70, 73-85] work, which is a seminal study of intuitionistic fuzzy decision analysis using deduced auxiliary programming models, and deems it a benchmark method for comparative studies on anchor dependency and accuracy functions. The feasibility and effectiveness of the proposed methods are illustrated by a numerical example. Finally, a comparative analysis is illustrated with computational experiments on averaging accuracy functions, TOPSIS indices, separation measures from positive and negative ideal alternatives, consistency rates of ranking orders, contradiction rates of the top alternative and average Spearman correlation coefficients.

Information networks in the stock market based on the distance of the multi-attribute dimensions between listed companies

NASA Astrophysics Data System (ADS)

Liu, Qian; Li, Huajiao; Liu, Xueyong; Jiang, Meihui

2018-04-01

In the stock market, there are widespread information connections between economic agents. Listed companies can obtain mutual information about investment decisions from common shareholders, and the extent of sharing information often determines the relationships between listed companies. Because different shareholder compositions and investment shares lead to different formations of the company's governance mechanisms, we map the investment relationships between shareholders to the multi-attribute dimensional spaces of the listed companies (each shareholder investment in a company is a company dimension). Then, we construct the listed company's information network based on co-shareholder relationships. The weights for the edges in the information network are measured with the Euclidean distance between the listed companies in the multi-attribute dimension space. We define two indices to analyze the information network's features. We conduct an empirical study that analyzes Chinese listed companies' information networks. The results from the analysis show that with the diversification and decentralization of shareholder investments, almost all Chinese listed companies exchanged information through common shareholder relationships, and there is a gradual reduction in information sharing capacity between listed companies that have common shareholders. This network analysis has benefits for risk management and portfolio investments.

Model for multi-stand management based on structural attributes of individual stands

Treesearch

G.W. Miller; J. Sullivan

1997-01-01

A growing interest in managing forest ecosystems calls for decision models that take into account attribute goals for large forest areas while continuing to recognize the individual stand as a basic unit of forest management. A dynamic, nonlinear forest management model is described that schedules silvicultural treatments for individual stands that are linked by multi-...

An interval-valued 2-tuple linguistic group decision-making model based on the Choquet integral operator

NASA Astrophysics Data System (ADS)

Liu, Bingsheng; Fu, Meiqing; Zhang, Shuibo; Xue, Bin; Zhou, Qi; Zhang, Shiruo

2018-01-01

The Choquet integral (IL) operator is an effective approach for handling interdependence among decision attributes in complex decision-making problems. However, the fuzzy measures of attributes and attribute sets required by IL are difficult to achieve directly, which limits the application of IL. This paper proposes a new method for determining fuzzy measures of attributes by extending Marichal's concept of entropy for fuzzy measure. To well represent the assessment information, interval-valued 2-tuple linguistic context is utilised to represent information. Then, we propose a Choquet integral operator in an interval-valued 2-tuple linguistic environment, which can effectively handle the correlation between attributes. In addition, we apply these methods to solve multi-attribute group decision-making problems. The feasibility and validity of the proposed operator is demonstrated by comparisons with other models in illustrative example part.

Sustainability assessment of tertiary wastewater treatment technologies: a multi-criteria analysis.

PubMed

Plakas, K V; Georgiadis, A A; Karabelas, A J

2016-01-01

The multi-criteria analysis gives the opportunity to researchers, designers and decision-makers to examine decision options in a multi-dimensional fashion. On this basis, four tertiary wastewater treatment (WWT) technologies were assessed regarding their sustainability performance in producing recycled wastewater, considering a 'triple bottom line' approach (i.e. economic, environmental, and social). These are powdered activated carbon adsorption coupled with ultrafiltration membrane separation (PAC-UF), reverse osmosis, ozone/ultraviolet-light oxidation and heterogeneous photo-catalysis coupled with low-pressure membrane separation (photocatalytic membrane reactor, PMR). The participatory method called simple multi-attribute rating technique exploiting ranks was employed for assigning weights to selected sustainability indicators. This sustainability assessment approach resulted in the development of a composite index as a final metric, for each WWT technology evaluated. The PAC-UF technology appears to be the most appropriate technology, attaining the highest composite value regarding the sustainability performance. A scenario analysis confirmed the results of the original scenario in five out of seven cases. In parallel, the PMR was highlighted as the technology with the least variability in its performance. Nevertheless, additional actions and approaches are proposed to strengthen the objectivity of the final results.

Research of Simple Multi-Attribute Rating Technique for Decision Support

NASA Astrophysics Data System (ADS)

Siregar, Dodi; Arisandi, Diki; Usman, Ari; Irwan, Dedy; Rahim, Robbi

2017-12-01

One of the roles of decision support system is that it can assist the decision maker in obtaining the appropriate alternative with the desired criteria, one of the methods that could apply for the decision maker is SMART method with multicriteria decision making. This multi-criteria decision-making theory has meaning where every alternative has criteria and has value and weight, and the author uses this approach to facilitate decision making with a compelling case. The problems discussed in this paper are classified into problems of a variety Multiobjective (multiple goals to be accomplished) and multicriteria (many of the decisive criteria in reaching such decisions).

Value-Based Assessment of New Medical Technologies: Towards a Robust Methodological Framework for the Application of Multiple Criteria Decision Analysis in the Context of Health Technology Assessment.

PubMed

Angelis, Aris; Kanavos, Panos

2016-05-01

In recent years, multiple criteria decision analysis (MCDA) has emerged as a likely alternative to address shortcomings in health technology assessment (HTA) by offering a more holistic perspective to value assessment and acting as an alternative priority setting tool. In this paper, we argue that MCDA needs to subscribe to robust methodological processes related to the selection of objectives, criteria and attributes in order to be meaningful in the context of healthcare decision making and fulfil its role in value-based assessment (VBA). We propose a methodological process, based on multi-attribute value theory (MAVT) methods comprising five distinct phases, outline the stages involved in each phase and discuss their relevance in the HTA process. Importantly, criteria and attributes need to satisfy a set of desired properties, otherwise the outcome of the analysis can produce spurious results and misleading recommendations. Assuming the methodological process we propose is adhered to, the application of MCDA presents three very distinct advantages to decision makers in the context of HTA and VBA: first, it acts as an instrument for eliciting preferences on the performance of alternative options across a wider set of explicit criteria, leading to a more complete assessment of value; second, it allows the elicitation of preferences across the criteria themselves to reflect differences in their relative importance; and, third, the entire process of preference elicitation can be informed by direct stakeholder engagement, and can therefore reflect their own preferences. All features are fully transparent and facilitate decision making.

Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

PubMed

Wall, Emily; Das, Subhajit; Chawla, Ravish; Kalidindi, Bharath; Brown, Eli T; Endert, Alex

2018-01-01

People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.

District Heating Systems Performance Analyses. Heat Energy Tariff

NASA Astrophysics Data System (ADS)

Ziemele, Jelena; Vigants, Girts; Vitolins, Valdis; Blumberga, Dagnija; Veidenbergs, Ivars

2014-12-01

The paper addresses an important element of the European energy sector: the evaluation of district heating (DH) system operations from the standpoint of increasing energy efficiency and increasing the use of renewable energy resources. This has been done by developing a new methodology for the evaluation of the heat tariff. The paper presents an algorithm of this methodology, which includes not only a data base and calculation equation systems, but also an integrated multi-criteria analysis module using MADM/MCDM (Multi-Attribute Decision Making / Multi-Criteria Decision Making) based on TOPSIS (Technique for Order Performance by Similarity to Ideal Solution). The results of the multi-criteria analysis are used to set the tariff benchmarks. The evaluation methodology has been tested for Latvian heat tariffs, and the obtained results show that only half of heating companies reach a benchmark value equal to 0.5 for the efficiency closeness to the ideal solution indicator. This means that the proposed evaluation methodology would not only allow companies to determine how they perform with regard to the proposed benchmark, but also to identify their need to restructure so that they may reach the level of a low-carbon business.

Prospect Theory and Interval-Valued Hesitant Set for Safety Evacuation Model

NASA Astrophysics Data System (ADS)

Kou, Meng; Lu, Na

2018-01-01

The study applies the research results of prospect theory and multi attribute decision making theory, combined with the complexity, uncertainty and multifactor influence of the underground mine fire system and takes the decision makers’ psychological behavior of emotion and intuition into full account to establish the intuitionistic fuzzy multiple attribute decision making method that is based on the prospect theory. The model established by this method can explain the decision maker’s safety evacuation decision behavior in the complex system of underground mine fire due to the uncertainty of the environment, imperfection of the information and human psychological behavior and other factors.

Multi-Attribute Tradespace Exploration in Space System Design

NASA Astrophysics Data System (ADS)

Ross, A. M.; Hastings, D. E.

2002-01-01

The complexity inherent in space systems necessarily requires intense expenditures of resources both human and monetary. The high level of ambiguity present in the early design phases of these systems causes long, highly iterative, and costly design cycles. This paper looks at incorporating decision theory methods into the early design processes to streamline communication of wants and needs among stakeholders and between levels of design. Communication channeled through formal utility interviews and analysis enables engineers to better understand the key drivers for the system and allows a more thorough exploration of the design tradespace. Multi-Attribute Tradespace Exploration (MATE), an evolving process incorporating decision theory into model and simulation- based design, has been applied to several space system case studies at MIT. Preliminary results indicate that this process can improve the quality of communication to more quickly resolve project ambiguity, and enable the engineer to discover better value designs for multiple stakeholders. MATE is also being integrated into a concurrent design environment to facilitate the transfer knowledge of important drivers into higher fidelity design phases. Formal utility theory provides a mechanism to bridge the language barrier between experts of different backgrounds and differing needs (e.g. scientists, engineers, managers, etc). MATE with concurrent design couples decision makers more closely to the design, and most importantly, maintains their presence between formal reviews.

Thermal power systems small power systems applications project. Decision analysis for evaluating and ranking small solar thermal power system technologies. Volume 1: A brief introduction to multiattribute decision analysis. [explanation of multiattribute decision analysis methods used in evaluating alternatives for small powered systems

NASA Technical Reports Server (NTRS)

Feinberg, A.; Miles, R. F., Jr.

1978-01-01

The principal concepts of the Keeney and Raiffa approach to multiattribute decision analysis are described. Topics discussed include the concepts of decision alternatives, outcomes, objectives, attributes and their states, attribute utility functions, and the necessary independence properties for the attribute states to be aggregated into a numerical representation of the preferences of the decision maker for the outcomes and decision alternatives.

A Stochastic Multi-Attribute Assessment of Energy Options for Fairbanks, Alaska

NASA Astrophysics Data System (ADS)

Read, L.; Madani, K.; Mokhtari, S.; Hanks, C. L.; Sheets, B.

2012-12-01

Many competing projects have been proposed to address Interior Alaska's high cost of energy—both for electricity production and for heating. Public and private stakeholders are considering the costs associated with these competing projects which vary in fuel source, subsidy requirements, proximity, and other factors. As a result, the current projects under consideration involve a complex cost structure of potential subsidies and reliance on present and future market prices, introducing a significant amount of uncertainty associated with each selection. Multi-criteria multi-decision making (MCMDM) problems of this nature can benefit from game theory and systems engineering methods, which account for behavior and preferences of stakeholders in the analysis to produce feasible and relevant solutions. This work uses a stochastic MCMDM framework to evaluate the trade-offs of each proposed project based on a complete cost analysis, environmental impact, and long-term sustainability. Uncertainty in the model is quantified via a Monte Carlo analysis, which helps characterize the sensitivity and risk associated with each project. Based on performance measures and criteria outlined by the stakeholders, a decision matrix will inform policy on selecting a project that is both efficient and preferred by the constituents.

Strategic Technology Investment Analysis: An Integrated System Approach

NASA Technical Reports Server (NTRS)

Adumitroaie, V.; Weisbin, C. R.

2010-01-01

Complex technology investment decisions within NASA are increasingly difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Due to a restricted science budget environment and numerous required technology developments, the investment decisions need to take into account not only the functional impact on the program goals, but also development uncertainties and cost variations along with maintaining a healthy workforce. This paper describes an approach for optimizing and qualifying technology investment portfolios from the perspective of an integrated system model. The methodology encompasses multi-attribute decision theory elements and sensitivity analysis. The evaluation of the degree of robustness of the recommended portfolio provides the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy nontechnical constraints. The methodology is presented in the context of assessing capability development portfolios for NASA technology programs.

Coding Theory Information Theory and Radar

DTIC Science & Technology

2005-01-01

the design and synthesis of artificial multiagent systems and for the understanding of human decision-making processes. This... altruism that may exist in a complex society. SGT derives its ability to account simultaneously for both group and individual interests from the structure of ...satisficing decision theory as a model of human decision mak- ing. 2 Multi-Attribute Decision Making Many decision problems involve the consideration of

Decision Making In Assignment Problem With Multiple Attributes Under Intuitionistic Fuzzy Environment

NASA Astrophysics Data System (ADS)

Mukherjee, Sathi; Basu, Kajla

2010-10-01

In this paper we develop a methodology to solve the multiple attribute assignment problems where the attributes are considered to be Intuitionistic Fuzzy Sets (IFS). We apply the concept of similarity measures of IFS to solve the Intuitionistic Fuzzy Multi-Attribute Assignment Problem (IFMAAP). The weights of the attributes are determined from expert opinion. An illustrative example is solved to verify the developed approach and to demonstrate its practicality.

Hierarchical competitions subserving multi-attribute choice

PubMed Central

Hunt, Laurence T; Dolan, Raymond J; Behrens, Timothy EJ

2015-01-01

Valuation is a key tenet of decision neuroscience, where it is generally assumed that different attributes of competing options are assimilated into unitary values. Such values are central to current neural models of choice. By contrast, psychological studies emphasize complex interactions between choice and valuation. Principles of neuronal selection also suggest competitive inhibition may occur in early valuation stages, before option selection. Here, we show behavior in multi-attribute choice is best explained by a model involving competition at multiple levels of representation. This hierarchical model also explains neural signals in human brain regions previously linked to valuation, including striatum, parietal and prefrontal cortex, where activity represents competition within-attribute, competition between attributes, and option selection. This multi-layered inhibition framework challenges the assumption that option values are computed before choice. Instead our results indicate a canonical competition mechanism throughout all stages of a processing hierarchy, not simply at a final choice stage. PMID:25306549

Can Carbon Nanomaterials Improve CZTS Photovoltaic Devices? Evaluation of Performance and Impacts Using Integrated Life-Cycle Assessment and Decision Analysis.

PubMed

Scott, Ryan P; Cullen, Alison C; Fox-Lent, Cate; Linkov, Igor

2016-10-01

In emergent photovoltaics, nanoscale materials hold promise for optimizing device characteristics; however, the related impacts remain uncertain, resulting in challenges to decisions on strategic investment in technology innovation. We integrate multi-criteria decision analysis (MCDA) and life-cycle assessment (LCA) results (LCA-MCDA) as a method of incorporating values of a hypothetical federal acquisition manager into the assessment of risks and benefits of emerging photovoltaic materials. Specifically, we compare adoption of copper zinc tin sulfide (CZTS) devices with molybdenum back contacts to alternative devices employing graphite or graphene instead of molybdenum. LCA impact results are interpreted alongside benefits of substitution including cost reductions and performance improvements through application of multi-attribute utility theory. To assess the role of uncertainty we apply Monte Carlo simulation and sensitivity analysis. We find that graphene or graphite back contacts outperform molybdenum under most scenarios and assumptions. The use of decision analysis clarifies potential advantages of adopting graphite as a back contact while emphasizing the importance of mitigating conventional impacts of graphene production processes if graphene is used in emerging CZTS devices. Our research further demonstrates that a combination of LCA and MCDA increases the usability of LCA in assessing product sustainability. In particular, this approach identifies the most influential assumptions and data gaps in the analysis and the areas in which either engineering controls or further data collection may be necessary. © 2016 Society for Risk Analysis.

Adaptive management in the U.S. National Wildlife Refuge System: Science-management partnerships for conservation delivery

USGS Publications Warehouse

Moore, C.T.; Lonsdorf, E.V.; Knutson, M.G.; Laskowski, H.P.; Lor, S.K.

2011-01-01

Adaptive management is an approach to recurrent decision making in which uncertainty about the decision is reduced over time through comparison of outcomes predicted by competing models against observed values of those outcomes. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service is a large land management program charged with making natural resource management decisions, which often are made under considerable uncertainty, severe operational constraints, and conditions that limit ability to precisely carry out actions as intended. The NWRS presents outstanding opportunities for the application of adaptive management, but also difficult challenges. We describe two cooperative programs between the Fish and Wildlife Service and the U.S. Geological Survey to implement adaptive management at scales ranging from small, single refuge applications to large, multi-refuge, multi-region projects. Our experience to date suggests three important attributes common to successful implementation: a vigorous multi-partner collaboration, practical and informative decision framework components, and a sustained commitment to the process. Administrators in both agencies should consider these attributes when developing programs to promote the use and acceptance of adaptive management in the NWRS. ?? 2010 .

Texas Urban Triangle : pilot study to implement a spatial decision support system (SDSS) for sustainable mobility.

DOT National Transportation Integrated Search

2011-03-01

This project addressed sustainable transportation in the Texas Urban Triangle (TUT) by conducting a pilot : project at the county scale. The project tested and developed the multi-attribute Spatial Decision Support : System (SDSS) developed in 2009 u...

Application of the fuzzy topsis multi-attribute decision making method to determine scholarship recipients

NASA Astrophysics Data System (ADS)

Irvanizam, I.

2018-03-01

Some scholarships have been routinely offered by Ministry of Research, Technology and Higher Education of the Republic of Indonesia for students at Syiah Kuala University. In reality, the scholarship selection process is becoming subjective and highly complex problem. Multi-Attribute Decision Making (MADM) techniques can be a solution in order to solve scholarship selection problem. In this study, we demonstrated the application of a fuzzy TOPSIS as an MADM technique by using a numerical example in order to calculate a triangular fuzzy number for the fuzzy data onto a normalized weight. We then use this normalized value to construct the normalized fuzzy decision matrix. We finally use the fuzzy TOPSIS to rank alternatives in descending order based on the relative closeness to the ideal solution. The result in terms of final ranking shows slightly different from the previous work.

A decision aid for intensity-modulated radiation-therapy plan selection in prostate cancer based on a prognostic Bayesian network and a Markov model.

PubMed

Smith, Wade P; Doctor, Jason; Meyer, Jürgen; Kalet, Ira J; Phillips, Mark H

2009-06-01

The prognosis of cancer patients treated with intensity-modulated radiation-therapy (IMRT) is inherently uncertain, depends on many decision variables, and requires that a physician balance competing objectives: maximum tumor control with minimal treatment complications. In order to better deal with the complex and multiple objective nature of the problem we have combined a prognostic probabilistic model with multi-attribute decision theory which incorporates patient preferences for outcomes. The response to IMRT for prostate cancer was modeled. A Bayesian network was used for prognosis for each treatment plan. Prognoses included predicting local tumor control, regional spread, distant metastases, and normal tissue complications resulting from treatment. A Markov model was constructed and used to calculate a quality-adjusted life-expectancy which aids in the multi-attribute decision process. Our method makes explicit the tradeoffs patients face between quality and quantity of life. This approach has advantages over current approaches because with our approach risks of health outcomes and patient preferences determine treatment decisions.

Impact of Decision Criteria on Federal Aviation Administration Certification of Military Commercial Derivative Aircraft

DTIC Science & Technology

2012-03-01

Capt Low was a member of the Sigma Iota Epsilon professional management fraternity. He has performed as an on-equipment and off-equipment...FAA Certification, Military Commercial Derivative Aircraft, Multi-Attribute Decision Making 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

Comparative SWOT analysis of strategic environmental assessment systems in the Middle East and North Africa region.

PubMed

Rachid, G; El Fadel, M

2013-08-15

This paper presents a SWOT analysis of SEA systems in the Middle East North Africa region through a comparative examination of the status, application and structure of existing systems based on country-specific legal, institutional and procedural frameworks. The analysis is coupled with the multi-attribute decision making method (MADM) within an analytical framework that involves both performance analysis based on predefined evaluation criteria and countries' self-assessment of their SEA system through open-ended surveys. The results show heterogenous status with a general delayed progress characterized by varied levels of weaknesses embedded in the legal and administrative frameworks and poor integration with the decision making process. Capitalizing on available opportunities, the paper highlights measures to enhance the development and enactment of SEA in the region. Copyright © 2013 Elsevier Ltd. All rights reserved.

Deciding how to decide: ventromedial frontal lobe damage affects information acquisition in multi-attribute decision making.

PubMed

Fellows, Lesley K

2006-04-01

Ventromedial frontal lobe (VMF) damage is associated with impaired decision making. Recent efforts to understand the functions of this brain region have focused on its role in tracking reward, punishment and risk. However, decision making is complex, and frontal lobe damage might be expected to affect it at other levels. This study used process-tracing techniques to explore the effect of VMF damage on multi-attribute decision making under certainty. Thirteen subjects with focal VMF damage were compared with 11 subjects with frontal damage that spared the VMF and 21 demographically matched healthy control subjects. Participants chose rental apartments in a standard information board task drawn from the literature on normal decision making. VMF subjects performed the decision making task in a way that differed markedly from all other groups, favouring an 'alternative-based' information acquisition strategy (i.e. they organized their information search around individual apartments). In contrast, both healthy control subjects and subjects with damage predominantly involving dorsal and/or lateral prefrontal cortex pursued primarily 'attribute-based' search strategies (in which information was acquired about categories such as rent and noise level across several apartments). This difference in the pattern of information acquisition argues for systematic differences in the underlying decision heuristics and strategies employed by subjects with VMF damage, which in turn may affect the quality of their choices. These findings suggest that the processes supported by ventral and medial prefrontal cortex need to be conceptualized more broadly, to account for changes in decision making under conditions of certainty, as well as uncertainty, following damage to these areas.

Multi Attribute Decision Analysis in Public Health - Analyzing Effectiveness of Alternate Modes of Dispensing

DTIC Science & Technology

2007-09-01

curve (Smith, 2007). This curve shows the relative performance of an option based on the selected factors (Chan & Mauborgne, 2007). Value cures ...that they and their families are safe; anything less will result in staffing shortages and absenteeism . d. POD Staff Training POD volunteers would...can expect high rates of absenteeism . Local law enforcement in LAC has therefore not guaranteed one- on-one protection for the 3,750 postal carriers

Judgement heuristics and bias in evidence interpretation: The effects of computer generated exhibits.

PubMed

Norris, Gareth

2015-01-01

The increasing use of multi-media applications, trial presentation software and computer generated exhibits (CGE) has raised questions as to the potential impact of the use of presentation technology on juror decision making. A significant amount of the commentary on the manner in which CGE exerts legal influence is largely anecdotal; empirical examinations too are often devoid of established theoretical rationalisations. This paper will examine a range of established judgement heuristics (for example, the attribution error, representativeness, simulation), in order to establish their appropriate application for comprehending legal decisions. Analysis of both past cases and empirical studies will highlight the potential for heuristics and biases to be restricted or confounded by the use of CGE. The paper will conclude with some wider discussion on admissibility, access to justice, and emerging issues in the use of multi-media in court. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis respons to the implementation of nuclear installations safety culture using AHP-TOPSIS

NASA Astrophysics Data System (ADS)

Situmorang, J.; Kuntoro, I.; Santoso, S.; Subekti, M.; Sunaryo, G. R.

2018-02-01

An analysis of responses to the implementation of nuclear installations safety culture has been done using AHP (Analitic Hierarchy Process) - TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). Safety culture is considered as collective commitments of the decision-making level, management level, and individual level. Thus each level will provide a subjective perspective as an alternative approach to implementation. Furthermore safety culture is considered by the statement of five characteristics which in more detail form consist of 37 attributes, and therefore can be expressed as multi-attribute state. Those characteristics and or attributes will be a criterion and its value is difficult to determine. Those criteria of course, will determine and strongly influence the implementation of the corresponding safety culture. To determine the pattern and magnitude of the influence is done by using a TOPSIS that is based on decision matrix approach and is composed of alternatives and criteria. The weight of each criterion is determined by AHP technique. The data used are data collected through questionnaires at the workshop on safety and health in 2015. .Reliability test of data gives Cronbah Alpha value of 95.5% which according to the criteria is stated reliable. Validity test using bivariate correlation analysis technique between each attribute give Pearson correlation for all attribute is significant at level 0,01. Using confirmatory factor analysis gives Kaise-Meyer-Olkin of sampling Adequacy (KMO) is 0.719 and it is greater than the acceptance criterion 0.5 as well as the 0.000 significance level much smaller than 0.05 and stated that further analysis could be performed. As a result of the analysis it is found that responses from the level of decision maker (second echelon) dominate the best order preference rank to be the best solution in strengthening the nuclear installation safety culture, except for the first characteristics, safety is a clearly recognized value. The rank of preference order is obtained sequentially according to the level of policy maker, management and individual or staff.

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

PubMed

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

Multiple Criteria Decision Analysis (MCDA) for evaluating new medicines in Health Technology Assessment and beyond: The Advance Value Framework.

PubMed

Angelis, Aris; Kanavos, Panos

2017-09-01

Escalating drug prices have catalysed the generation of numerous "value frameworks" with the aim of informing payers, clinicians and patients on the assessment and appraisal process of new medicines for the purpose of coverage and treatment selection decisions. Although this is an important step towards a more inclusive Value Based Assessment (VBA) approach, aspects of these frameworks are based on weak methodologies and could potentially result in misleading recommendations or decisions. In this paper, a Multiple Criteria Decision Analysis (MCDA) methodological process, based on Multi Attribute Value Theory (MAVT), is adopted for building a multi-criteria evaluation model. A five-stage model-building process is followed, using a top-down "value-focused thinking" approach, involving literature reviews and expert consultations. A generic value tree is structured capturing decision-makers' concerns for assessing the value of new medicines in the context of Health Technology Assessment (HTA) and in alignment with decision theory. The resulting value tree (Advance Value Tree) consists of three levels of criteria (top level criteria clusters, mid-level criteria, bottom level sub-criteria or attributes) relating to five key domains that can be explicitly measured and assessed: (a) burden of disease, (b) therapeutic impact, (c) safety profile (d) innovation level and (e) socioeconomic impact. A number of MAVT modelling techniques are introduced for operationalising (i.e. estimating) the model, for scoring the alternative treatment options, assigning relative weights of importance to the criteria, and combining scores and weights. Overall, the combination of these MCDA modelling techniques for the elicitation and construction of value preferences across the generic value tree provides a new value framework (Advance Value Framework) enabling the comprehensive measurement of value in a structured and transparent way. Given its flexibility to meet diverse requirements and become readily adaptable across different settings, the Advance Value Framework could be offered as a decision-support tool for evaluators and payers to aid coverage and reimbursement of new medicines. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Decision Making for Pap Testing among Pacific Islander Women

ERIC Educational Resources Information Center

Weiss, Jie W.; Mouttapa, Michele; Sablan-Santos, Lola; DeGuzman Lacsamana, Jasmine; Quitugua, Lourdes; Park Tanjasiri, Sora

2016-01-01

This study employed a Multi-Attribute Utility (MAU) model to examine the Pap test decision-making process among Pacific Islanders (PI) residing in Southern California. A total of 585 PI women were recruited through social networks from Samoan and Tongan churches, and Chamorro family clans. A questionnaire assessed Pap test knowledge, beliefs and…

Perceptual grouping does not affect multi-attribute decision making if no processing costs are involved.

PubMed

Ettlin, Florence; Bröder, Arndt

2015-05-01

Adaptive strategy selection implies that a decision strategy is chosen based on its fit to the task and situation. However, other aspects, such as the way information is presented, can determine information search behavior; especially when the application of certain strategies over others is facilitated. But are such display effects on multi-attribute decisions also at work when the manipulation does not entail differential costs for different decision strategies? Three Mouselab experiments with hidden information and one eye tracking experiment with an open information board revealed that decision behavior is unaffected by purely perceptual manipulations of the display based on Gestalt principles; that is, based on manipulations that induce no noteworthy processing costs for different information search patterns. We discuss our results in the context of previous findings on display effects; specifically, how the combination of these findings and our results reveal the crucial role of differential processing costs for different strategies for the emergence of display effects. This finding describes a boundary condition of the commonly acknowledged influence of information displays and is in line with the ideas of adaptive strategy selection and cost-benefit tradeoffs. Copyright © 2015. Published by Elsevier B.V.

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop.

PubMed

Li, Lian-Hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility.

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop

PubMed Central

Li, Lian-hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility. PMID:26414758

Four Common Simplifications of Multi-Criteria Decision Analysis do not hold for River Rehabilitation

PubMed Central

2016-01-01

River rehabilitation aims at alleviating negative effects of human impacts such as loss of biodiversity and reduction of ecosystem services. Such interventions entail difficult trade-offs between different ecological and often socio-economic objectives. Multi-Criteria Decision Analysis (MCDA) is a very suitable approach that helps assessing the current ecological state and prioritizing river rehabilitation measures in a standardized way, based on stakeholder or expert preferences. Applications of MCDA in river rehabilitation projects are often simplified, i.e. using a limited number of objectives and indicators, assuming linear value functions, aggregating individual indicator assessments additively, and/or assuming risk neutrality of experts. Here, we demonstrate an implementation of MCDA expert preference assessments to river rehabilitation and provide ample material for other applications. To test whether the above simplifications reflect common expert opinion, we carried out very detailed interviews with five river ecologists and a hydraulic engineer. We defined essential objectives and measurable quality indicators (attributes), elicited the experts´ preferences for objectives on a standardized scale (value functions) and their risk attitude, and identified suitable aggregation methods. The experts recommended an extensive objectives hierarchy including between 54 and 93 essential objectives and between 37 to 61 essential attributes. For 81% of these, they defined non-linear value functions and in 76% recommended multiplicative aggregation. The experts were risk averse or risk prone (but never risk neutral), depending on the current ecological state of the river, and the experts´ personal importance of objectives. We conclude that the four commonly applied simplifications clearly do not reflect the opinion of river rehabilitation experts. The optimal level of model complexity, however, remains highly case-study specific depending on data and resource availability, the context, and the complexity of the decision problem. PMID:26954353

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation

PubMed Central

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment. PMID:26368541

Qualitatively Coherent Representation Makes Decision-Making Easier with Binary-Colored Multi-Attribute Tables: An Eye-Tracking Study

PubMed Central

Morii, Masahiro; Ideno, Takashi; Takemura, Kazuhisa; Okada, Mitsuhiro

2017-01-01

We aimed to identify the ways in which coloring cells affected decision-making in the context of binary-colored multi-attribute tables, using eye movement data. In our black-white attribute tables, the value of attributes was limited to two (with a certain threshold for each attribute) and each cell of the table was colored either black or white on the white background. We compared the two natural ways of systematic color assignment: “quantitatively coherent” ways and “qualitatively coherent” ways (namely, the ways in which the black-white distinction represented the quantitative amount distinction, and the ways in which the black-white distinction represented the quality distinction). The former consists of the following two types: (Type 1) “larger is black,” where the larger value-level was represented by black, and “smaller is white,” and (Type 2) “smaller is black.” The latter consisted of the following two types: (Type 3) “better is black,” and (Type 4) “worse is black.” We obtained the following two findings. [Result 1] The qualitatively coherent black-white tables (Types 3 and 4) made decision-making easier than the quantitatively coherent ones (Types 1 and 2). [Result 2] Among the two qualitatively coherent types, the “black is better” tables (Type 3) made decision making easier; in fact, the participants focused on the more important (black) cells in the case of “black is better” tables (Type 3) while they did not focus enough on the more important (white) ones in the case of the “white is better” tables (Type 4). We also examined some measures of eye movement patterns and showed that these measures supported our hypotheses. The data showed differences in the eye movement patterns between the first and second halves of each trial, which indicated the phased or combined decision strategies taken by the participants. PMID:28861020

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes

NASA Astrophysics Data System (ADS)

Lu, Hongwei; Ren, Lixia; Chen, Yizhong; Tian, Peipei; Liu, Jia

2017-12-01

Due to the uncertainty (i.e., fuzziness, stochasticity and imprecision) existed simultaneously during the process for groundwater remediation, the accuracy of ranking results obtained by the traditional methods has been limited. This paper proposes a cloud model based multi-attribute decision making framework (CM-MADM) with Monte Carlo for the contaminated-groundwater remediation strategies selection. The cloud model is used to handle imprecise numerical quantities, which can describe the fuzziness and stochasticity of the information fully and precisely. In the proposed approach, the contaminated concentrations are aggregated via the backward cloud generator and the weights of attributes are calculated by employing the weight cloud module. A case study on the remedial alternative selection for a contaminated site suffering from a 1,1,1-trichloroethylene leakage problem in Shanghai, China is conducted to illustrate the efficiency and applicability of the developed approach. Totally, an attribute system which consists of ten attributes were used for evaluating each alternative through the developed method under uncertainty, including daily total pumping rate, total cost and cloud model based health risk. Results indicated that A14 was evaluated to be the most preferred alternative for the 5-year, A5 for the 10-year, A4 for the 15-year and A6 for the 20-year remediation.

Comparing multi-criteria decision analysis and integrated assessment to support long-term water supply planning

PubMed Central

Maurer, Max; Lienert, Judit

2017-01-01

We compare the use of multi-criteria decision analysis (MCDA)–or more precisely, models used in multi-attribute value theory (MAVT)–to integrated assessment (IA) models for supporting long-term water supply planning in a small town case study in Switzerland. They are used to evaluate thirteen system scale water supply alternatives in four future scenarios regarding forty-four objectives, covering technical, social, environmental, and economic aspects. The alternatives encompass both conventional and unconventional solutions and differ regarding technical, spatial and organizational characteristics. This paper focuses on the impact assessment and final evaluation step of the structured MCDA decision support process. We analyze the performance of the alternatives for ten stakeholders. We demonstrate the implications of model assumptions by comparing two IA and three MAVT evaluation model layouts of different complexity. For this comparison, we focus on the validity (ranking stability), desirability (value), and distinguishability (value range) of the alternatives given the five model layouts. These layouts exclude or include stakeholder preferences and uncertainties. Even though all five led us to identify the same best alternatives, they did not produce identical rankings. We found that the MAVT-type models provide higher distinguishability and a more robust basis for discussion than the IA-type models. The needed complexity of the model, however, should be determined based on the intended use of the model within the decision support process. The best-performing alternatives had consistently strong performance for all stakeholders and future scenarios, whereas the current water supply system was outperformed in all evaluation layouts. The best-performing alternatives comprise proactive pipe rehabilitation, adapted firefighting provisions, and decentralized water storage and/or treatment. We present recommendations for possible ways of improving water supply planning in the case study and beyond. PMID:28481881

Deriving preference order of post-mining land-uses through MLSA framework: application of an outranking technique

NASA Astrophysics Data System (ADS)

Soltanmohammadi, Hossein; Osanloo, Morteza; Aghajani Bazzazi, Abbas

2009-08-01

This study intends to take advantage of a previously developed framework for mined land suitability analysis (MLSA) consisted of economical, social, technical and mine site factors to achieve a partial and also a complete pre-order of feasible post-mining land-uses. Analysis by an outranking multi-attribute decision-making (MADM) technique, called PROMETHEE (preference ranking organization method for enrichment evaluation), was taken into consideration because of its clear advantages on the field of MLSA as compared with MADM ranking techniques. Application of the proposed approach on a mined land can be completed through some successive steps. First, performance of the MLSA attributes is scored locally by each individual decision maker (DM). Then the assigned performance scores are normalized and the deviation amplitudes of non-dominated alternatives are calculated. Weights of the attributes are calculated by another MADM technique namely, analytical hierarchy process (AHP) in a separate procedure. Using the Gaussian preference function beside the weights, the preference indexes of the land-use alternatives are obtained. Calculation of the outgoing and entering flows of the alternatives and one by one comparison of these values will lead to partial pre-order of them and calculation of the net flows, will lead to a ranked preference for each land-use. At the final step, utilizing the PROMETHEE group decision support system which incorporates judgments of all the DMs, a consensual ranking can be derived. In this paper, preference order of post-mining land-uses for a hypothetical mined land has been derived according to judgments of one DM to reveal applicability of the proposed approach.

Using multi-criteria decision making for selection of the optimal strategy for municipal solid waste management.

PubMed

Jovanovic, Sasa; Savic, Slobodan; Jovicic, Nebojsa; Boskovic, Goran; Djordjevic, Zorica

2016-09-01

Multi-criteria decision making (MCDM) is a relatively new tool for decision makers who deal with numerous and often contradictory factors during their decision making process. This paper presents a procedure to choose the optimal municipal solid waste (MSW) management system for the area of the city of Kragujevac (Republic of Serbia) based on the MCDM method. Two methods of multiple attribute decision making, i.e. SAW (simple additive weighting method) and TOPSIS (technique for order preference by similarity to ideal solution), respectively, were used to compare the proposed waste management strategies (WMS). Each of the created strategies was simulated using the software package IWM2. Total values for eight chosen parameters were calculated for all the strategies. Contribution of each of the six waste treatment options was valorized. The SAW analysis was used to obtain the sum characteristics for all the waste management treatment strategies and they were ranked accordingly. The TOPSIS method was used to calculate the relative closeness factors to the ideal solution for all the alternatives. Then, the proposed strategies were ranked in form of tables and diagrams obtained based on both MCDM methods. As shown in this paper, the results were in good agreement, which additionally confirmed and facilitated the choice of the optimal MSW management strategy. © The Author(s) 2016.

Qualitative analysis of patient-centered decision attributes associated with initiating hepatitis C treatment.

PubMed

Zuchowski, Jessica L; Hamilton, Alison B; Pyne, Jeffrey M; Clark, Jack A; Naik, Aanand D; Smith, Donna L; Kanwal, Fasiha

2015-10-01

In this era of a constantly changing landscape of antiviral treatment options for chronic viral hepatitis C (CHC), shared clinical decision-making addresses the need to engage patients in complex treatment decisions. However, little is known about the decision attributes that CHC patients consider when making treatment decisions. We identify key patient-centered decision attributes, and explore relationships among these attributes, to help inform the development of a future CHC shared decision-making aid. Semi-structured qualitative interviews with CHC patients at four Veterans Health Administration (VHA) hospitals, in three comparison groups: contemplating CHC treatment at the time of data collection (Group 1), recently declined CHC treatment (Group 2), or recently started CHC treatment (Group 3). Participant descriptions of decision attributes were analyzed for the entire sample as well as by patient group and by gender. Twenty-nine Veteran patients participated (21 males, eight females): 12 were contemplating treatment, nine had recently declined treatment, and eight had recently started treatment. Patients on average described eight (range 5-13) decision attributes. The attributes most frequently reported overall were: physical side effects (83%); treatment efficacy (79%), new treatment drugs in development (55%); psychological side effects (55%); and condition of the liver (52%), with some variation based on group and gender. Personal life circumstance attributes (such as availability of family support and the burden of financial responsibilities) influencing treatment decisions were also noted by all participants. Multiple decision attributes were interrelated in highly complex ways. Participants considered numerous attributes in their CHC treatment decisions. A better understanding of these attributes that influence patient decision-making is crucial in order to inform patient-centered clinical approaches to care (such as shared decision-making augmented with relevant decision-making aids) that respond to patients' needs, preferences, and circumstances.

Single-step affinity purification of enzyme biotherapeutics: a platform methodology for accelerated process development.

PubMed

Brower, Kevin P; Ryakala, Venkat K; Bird, Ryan; Godawat, Rahul; Riske, Frank J; Konstantinov, Konstantin; Warikoo, Veena; Gamble, Jean

2014-01-01

Downstream sample purification for quality attribute analysis is a significant bottleneck in process development for non-antibody biologics. Multi-step chromatography process train purifications are typically required prior to many critical analytical tests. This prerequisite leads to limited throughput, long lead times to obtain purified product, and significant resource requirements. In this work, immunoaffinity purification technology has been leveraged to achieve single-step affinity purification of two different enzyme biotherapeutics (Fabrazyme® [agalsidase beta] and Enzyme 2) with polyclonal and monoclonal antibodies, respectively, as ligands. Target molecules were rapidly isolated from cell culture harvest in sufficient purity to enable analysis of critical quality attributes (CQAs). Most importantly, this is the first study that demonstrates the application of predictive analytics techniques to predict critical quality attributes of a commercial biologic. The data obtained using the affinity columns were used to generate appropriate models to predict quality attributes that would be obtained after traditional multi-step purification trains. These models empower process development decision-making with drug substance-equivalent product quality information without generation of actual drug substance. Optimization was performed to ensure maximum target recovery and minimal target protein degradation. The methodologies developed for Fabrazyme were successfully reapplied for Enzyme 2, indicating platform opportunities. The impact of the technology is significant, including reductions in time and personnel requirements, rapid product purification, and substantially increased throughput. Applications are discussed, including upstream and downstream process development support to achieve the principles of Quality by Design (QbD) as well as integration with bioprocesses as a process analytical technology (PAT). © 2014 American Institute of Chemical Engineers.

Multi-criteria decision analysis tools for prioritising emerging or re-emerging infectious diseases associated with climate change in Canada.

PubMed

Cox, Ruth; Sanchez, Javier; Revie, Crawford W

2013-01-01

Global climate change is known to result in the emergence or re-emergence of some infectious diseases. Reliable methods to identify the infectious diseases of humans and animals and that are most likely to be influenced by climate are therefore required. Since different priorities will affect the decision to address a particular pathogen threat, decision makers need a standardised method of prioritisation. Ranking methods and Multi-Criteria Decision approaches provide such a standardised method and were employed here to design two different pathogen prioritisation tools. The opinion of 64 experts was elicited to assess the importance of 40 criteria that could be used to prioritise emerging infectious diseases of humans and animals in Canada. A weight was calculated for each criterion according to the expert opinion. Attributes were defined for each criterion as a transparent and repeatable method of measurement. Two different Multi-Criteria Decision Analysis tools were tested, both of which used an additive aggregation approach. These were an Excel spreadsheet tool and a tool developed in software 'M-MACBETH'. The tools were trialed on nine 'test' pathogens. Two different methods of criteria weighting were compared, one using fixed weighting values, the other using probability distributions to account for uncertainty and variation in expert opinion. The ranking of the nine pathogens varied according to the weighting method that was used. In both tools, using both weighting methods, the diseases that tended to rank the highest were West Nile virus, Giardiasis and Chagas, while Coccidioidomycosis tended to rank the lowest. Both tools are a simple and user friendly approach to prioritising pathogens according to climate change by including explicit scoring of 40 criteria and incorporating weighting methods based on expert opinion. They provide a dynamic interactive method that can help to identify pathogens for which a full risk assessment should be pursued.

Multi-Criteria Decision Analysis Tools for Prioritising Emerging or Re-Emerging Infectious Diseases Associated with Climate Change in Canada

PubMed Central

Cox, Ruth; Sanchez, Javier; Revie, Crawford W.

2013-01-01

Global climate change is known to result in the emergence or re-emergence of some infectious diseases. Reliable methods to identify the infectious diseases of humans and animals and that are most likely to be influenced by climate are therefore required. Since different priorities will affect the decision to address a particular pathogen threat, decision makers need a standardised method of prioritisation. Ranking methods and Multi-Criteria Decision approaches provide such a standardised method and were employed here to design two different pathogen prioritisation tools. The opinion of 64 experts was elicited to assess the importance of 40 criteria that could be used to prioritise emerging infectious diseases of humans and animals in Canada. A weight was calculated for each criterion according to the expert opinion. Attributes were defined for each criterion as a transparent and repeatable method of measurement. Two different Multi-Criteria Decision Analysis tools were tested, both of which used an additive aggregation approach. These were an Excel spreadsheet tool and a tool developed in software ‘M-MACBETH’. The tools were trialed on nine ‘test’ pathogens. Two different methods of criteria weighting were compared, one using fixed weighting values, the other using probability distributions to account for uncertainty and variation in expert opinion. The ranking of the nine pathogens varied according to the weighting method that was used. In both tools, using both weighting methods, the diseases that tended to rank the highest were West Nile virus, Giardiasis and Chagas, while Coccidioidomycosis tended to rank the lowest. Both tools are a simple and user friendly approach to prioritising pathogens according to climate change by including explicit scoring of 40 criteria and incorporating weighting methods based on expert opinion. They provide a dynamic interactive method that can help to identify pathogens for which a full risk assessment should be pursued. PMID:23950868

Multi-criteria decision making to support waste management: A critical review of current practices and methods.

PubMed

Goulart Coelho, Lineker M; Lange, Liséte C; Coelho, Hosmanny Mg

2017-01-01

Solid waste management is a complex domain involving the interaction of several dimensions; thus, its analysis and control impose continuous challenges for decision makers. In this context, multi-criteria decision-making models have become important and convenient supporting tools for solid waste management because they can handle problems involving multiple dimensions and conflicting criteria. However, the selection of the multi-criteria decision-making method is a hard task since there are several multi-criteria decision-making approaches, each one with a large number of variants whose applicability depends on information availability and the aim of the study. Therefore, to support researchers and decision makers, the objectives of this article are to present a literature review of multi-criteria decision-making applications used in solid waste management, offer a critical assessment of the current practices, and provide suggestions for future works. A brief review of fundamental concepts on this topic is first provided, followed by the analysis of 260 articles related to the application of multi-criteria decision making in solid waste management. These studies were investigated in terms of the methodology, including specific steps such as normalisation, weighting, and sensitivity analysis. In addition, information related to waste type, the study objective, and aspects considered was recorded. From the articles analysed it is noted that studies using multi-criteria decision making in solid waste management are predominantly addressed to problems related to municipal solid waste involving facility location or management strategy.

Decision-making Strategies and Performance among Seniors1

PubMed Central

Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael

2011-01-01

Using paper and pencil experiments administered in senior centers, we examine decision-making performance in multi-attribute decision problems. We differentiate the effects of declining cognitive performance and changing cognitive process on decision-making performance of seniors as they age. We find a significant decline in performance with age due to reduced reliance on common heuristics and increased decision-making randomness among our oldest subjects. However, we find that increasing the number of options in a decision problem increases the number of heuristics brought to the task. This challenges the choice overload view that people give up when confronted with too much choice. PMID:22408282

A Literature Review and Compilation of Nuclear Waste Management System Attributes for Use in Multi-Objective System Evaluations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalinina, Elena Arkadievna; Samsa, Michael

The purpose of this work was to compile a comprehensive initial set of potential nuclear waste management system attributes. This initial set of attributes is intended to serve as a starting point for additional consideration by system analysts and planners to facilitate the development of a waste management system multi-objective evaluation framework based on the principles and methodology of multi-attribute utility analysis. The compilation is primarily based on a review of reports issued by the Canadian Nuclear Waste Management Organization (NWMO) and the Blue Ribbon Commission on America's Nuclear Future (BRC), but also an extensive review of the available literaturemore » for similar and past efforts as well. Numerous system attributes found in different sources were combined into a single objectives-oriented hierarchical structure. This study provides a discussion of the data sources and the descriptions of the hierarchical structure. A particular focus of this study was on collecting and compiling inputs from past studies that involved the participation of various external stakeholders. However, while the important role of stakeholder input in a country's waste management decision process is recognized in the referenced sources, there are only a limited number of in-depth studies of the stakeholders' differing perspectives. Compiling a comprehensive hierarchical listing of attributes is a complex task since stakeholders have multiple and often conflicting interests. The BRC worked for two years (January 2010 to January 2012) to "ensure it has heard from as many points of view as possible." The Canadian NWMO study took four years and ample resources, involving national and regional stakeholders' dialogs, internet-based dialogs, information and discussion sessions, open houses, workshops, round tables, public attitude research, website, and topic reports. The current compilation effort benefited from the distillation of these many varied inputs conducted by the previous studies.« less

Preferences of processing companies for attributes of Swiss milk: a conjoint analysis in a business-to-business market.

PubMed

Boesch, I

2013-04-01

This study aimed to determine key attributes of milk that drive a processor's supply decisions and possibilities for differentiation based on these product attributes. Feedback-driven exploration was applied to derive product attributes relevant to the buying decision. Conjoint analysis with hierarchical Bayes estimation methods was used to determine the relative importance of attributes. Results show that the technical aspects of milk, as well as the price and country of origin, dominate the buying decision. Potential for differentiation was found for environmental and societal attributes as well as freedom from genetically modified products. Product and supplier criteria also provide the potential to segment the market if the price premium is held within limits. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Economics of human performance and systems total ownership cost.

PubMed

Onkham, Wilawan; Karwowski, Waldemar; Ahram, Tareq Z

2012-01-01

Financial costs of investing in people is associated with training, acquisition, recruiting, and resolving human errors have a significant impact on increased total ownership costs. These costs can also affect the exaggerate budgets and delayed schedules. The study of human performance economical assessment in the system acquisition process enhances the visibility of hidden cost drivers which support program management informed decisions. This paper presents the literature review of human total ownership cost (HTOC) and cost impacts on overall system performance. Economic value assessment models such as cost benefit analysis, risk-cost tradeoff analysis, expected value of utility function analysis (EV), growth readiness matrix, multi-attribute utility technique, and multi-regressions model were introduced to reflect the HTOC and human performance-technology tradeoffs in terms of the dollar value. The human total ownership regression model introduces to address the influencing human performance cost component measurement. Results from this study will increase understanding of relevant cost drivers in the system acquisition process over the long term.

Enriching the national map database for multi-scale use: Introducing the visibilityfilter attribution

USGS Publications Warehouse

Stauffer, Andrew J.; Webinger, Seth; Roche, Brittany

2016-01-01

The US Geological Survey’s (USGS) National Geospatial Technical Operations Center is prototyping and evaluating the ability to filter data through a range of scales using 1:24,000-scale The National Map (TNM) datasets as the source. A “VisibilityFilter” attribute is under evaluation that can be added to all TNM vector data themes and will permit filtering of data to eight target scales between 1:24,000 and 1:5,000,000, thus defining each feature’s smallest applicable scale-of-use. For a prototype implementation, map specifications for 1:100,000- and 1:250,000-scale USGS Topographic Map Series are being utilized to define feature content appropriate at fixed mapping scales to guide generalization decisions that are documented in a ScaleMaster diagram. This paper defines the VisibilityFilter attribute, the generalization decisions made for each TNM data theme, and how these decisions are embedded into the data to support efficient data filtering.

Non-monetary valuation using Multi-Criteria Decision Analysis: Sensitivity of additive aggregation methods to scaling and compensation assumptions

EPA Science Inventory

Analytical methods for Multi-Criteria Decision Analysis (MCDA) support the non-monetary valuation of ecosystem services for environmental decision making. Many published case studies transform ecosystem service outcomes into a common metric and aggregate the outcomes to set land ...

Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

NASA Astrophysics Data System (ADS)

Subagadis, Y. H.; Schütze, N.; Grundmann, J.

2014-09-01

The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

Comparison of potential method in analytic hierarchy process for multi-attribute of catering service companies

NASA Astrophysics Data System (ADS)

Mamat, Siti Salwana; Ahmad, Tahir; Awang, Siti Rahmah

2017-08-01

Analytic Hierarchy Process (AHP) is a method used in structuring, measuring and synthesizing criteria, in particular ranking of multiple criteria in decision making problems. On the other hand, Potential Method is a ranking procedure in which utilizes preference graph ς (V, A). Two nodes are adjacent if they are compared in a pairwise comparison whereby the assigned arc is oriented towards the more preferred node. In this paper Potential Method is used to solve problem on a catering service selection. The comparison of result by using Potential method is made with Extent Analysis. The Potential Method is found to produce the same rank as Extent Analysis in AHP.

Prioritization of highway maintenance functions using multi-attribute decision making with fuzzy pairwise comparison.

DOT National Transportation Integrated Search

2011-09-01

"As is the case for most of the Departments of Transportation in the U.S., the Texas Department of : Transportation has been experiencing fluctuations of budget for maintaining and preserving its highway : infrastructure over the recent years. If the...

Advanced GPR imaging of sedimentary features: integrated attribute analysis applied to sand dunes

NASA Astrophysics Data System (ADS)

Zhao, Wenke; Forte, Emanuele; Fontolan, Giorgio; Pipan, Michele

2018-04-01

We evaluate the applicability and the effectiveness of integrated GPR attribute analysis to image the internal sedimentary features of the Piscinas Dunes, SW Sardinia, Italy. The main objective is to explore the limits of GPR techniques to study sediment-bodies geometry and to provide a non-invasive high-resolution characterization of the different subsurface domains of dune architecture. On such purpose, we exploit the high-quality Piscinas data-set to extract and test different attributes of the GPR trace. Composite displays of multi-attributes related to amplitude, frequency, similarity and textural features are displayed with overlays and RGB mixed models. A multi-attribute comparative analysis is used to characterize different radar facies to better understand the characteristics of internal reflection patterns. The results demonstrate that the proposed integrated GPR attribute analysis can provide enhanced information about the spatial distribution of sediment bodies, allowing an enhanced and more constrained data interpretation.

Improving IT Portfolio Management Decision Confidence Using Multi-Criteria Decision Making and Hypervariate Display Techniques

ERIC Educational Resources Information Center

Landmesser, John Andrew

2014-01-01

Information technology (IT) investment decision makers are required to process large volumes of complex data. An existing body of knowledge relevant to IT portfolio management (PfM), decision analysis, visual comprehension of large volumes of information, and IT investment decision making suggest Multi-Criteria Decision Making (MCDM) and…

Integrated seismic stochastic inversion and multi-attributes to delineate reservoir distribution: Case study MZ fields, Central Sumatra Basin

NASA Astrophysics Data System (ADS)

Haris, A.; Novriyani, M.; Suparno, S.; Hidayat, R.; Riyanto, A.

2017-07-01

This study presents the integration of seismic stochastic inversion and multi-attributes for delineating the reservoir distribution in term of lithology and porosity in the formation within depth interval between the Top Sihapas and Top Pematang. The method that has been used is a stochastic inversion, which is integrated with multi-attribute seismic by applying neural network Probabilistic Neural Network (PNN). Stochastic methods are used to predict the probability mapping sandstone as the result of impedance varied with 50 realizations that will produce a good probability. Analysis of Stochastic Seismic Tnversion provides more interpretive because it directly gives the value of the property. Our experiment shows that AT of stochastic inversion provides more diverse uncertainty so that the probability value will be close to the actual values. The produced AT is then used for an input of a multi-attribute analysis, which is used to predict the gamma ray, density and porosity logs. To obtain the number of attributes that are used, stepwise regression algorithm is applied. The results are attributes which are used in the process of PNN. This PNN method is chosen because it has the best correlation of others neural network method. Finally, we interpret the product of the multi-attribute analysis are in the form of pseudo-gamma ray volume, density volume and volume of pseudo-porosity to delineate the reservoir distribution. Our interpretation shows that the structural trap is identified in the southeastern part of study area, which is along the anticline.

Watermark: An Application and Methodology and Application for Interactive and intelligent Decision Support for Groundwater Systems

NASA Astrophysics Data System (ADS)

Pierce, S. A.; Wagner, K.; Schwartz, S.; Gentle, J. N., Jr.

2016-12-01

Critical water resources face the effects of historic drought, increased demand, and potential contamination, the need has never been greater to develop resources to effectively communicate conservation and protection across a broad audience and geographical area. The Watermark application and macro-analysis methodology merges topical analysis of context rich corpus from policy texts with multi-attributed solution sets from integrated models of water resource and other subsystems, such as mineral, food, energy, or environmental systems to construct a scalable, robust, and reproducible approach for identifying links between policy and science knowledge bases. The Watermark application is an open-source, interactive workspace to support science-based visualization and decision making. Designed with generalization in mind, Watermark is a flexible platform that allows for data analysis and inclusion of large datasets with an interactive front-end capable of connecting with other applications as well as advanced computing resources. In addition, the Watermark analysis methodology offers functionality that streamlines communication with non-technical users for policy, education, or engagement with groups around scientific topics of societal relevance. The technology stack for Watermark was selected with the goal of creating a robust and dynamic modular codebase that can be adjusted to fit many use cases and scale to support usage loads that range between simple data display to complex scientific simulation-based modelling and analytics. The methodology uses to topical analysis and simulation-optimization to systematically analyze the policy and management realities of resource systems and explicitly connect the social and problem contexts with science-based and engineering knowledge from models. A case example demonstrates use in a complex groundwater resources management study highlighting multi-criteria spatial decision making and uncertainty comparisons.

The Valuation of Scientific and Technical Experiments

NASA Technical Reports Server (NTRS)

Williams, F. E.

1972-01-01

Rational selection of scientific and technical experiments for space missions is studied. Particular emphasis is placed on the assessment of value or worth of an experiment. A specification procedure is outlined and discussed for the case of one decision maker. Experiments are viewed as multi-attributed entities, and a relevant set of attributes is proposed. Alternative methods of describing levels of the attributes are proposed and discussed. The reasonableness of certain simplifying assumptions such as preferential and utility independence is explored, and it is tentatively concluded that preferential independence applies and utility independence appears to be appropriate.

Multi-Metric Sustainability Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cowlin, Shannon; Heimiller, Donna; Macknick, Jordan

2014-12-01

A readily accessible framework that allows for evaluating impacts and comparing tradeoffs among factors in energy policy, expansion planning, and investment decision making is lacking. Recognizing this, the Joint Institute for Strategic Energy Analysis (JISEA) funded an exploration of multi-metric sustainability analysis (MMSA) to provide energy decision makers with a means to make more comprehensive comparisons of energy technologies. The resulting MMSA tool lets decision makers simultaneously compare technologies and potential deployment locations.

Selecting the Best Thermal Building Insulation Using a Multi-Attribute Decision Model

DTIC Science & Technology

2008-03-01

materials which come in various forms. Rock wool, also called mineral wool , is made from natural minerals and was developed in the mid-1800s (NAIMA...2008). Fiberglass is a form of mineral wool and accounts for approximately 85% of the market for residential insulation. Synthetic insulating

Modeling recreation participants' willingness to substitute using multi-attribute indicators

Treesearch

Yung-Ping (Emilio) Tseng; Robert B. Ditton

2008-01-01

A logistic regression was used to predict anglers' resource-substitution decisions based on three dimensions of recreation specialization (behavior, skill and knowledge, and commitment), two dimensions of place attachment (place identity and place dependence), and three demographic indicators. Results indicated that place dependence was the most effective...

Decision Support for Personalized Cloud Service Selection through Multi-Attribute Trustworthiness Evaluation

PubMed Central

Ding, Shuai; Xia, Chen-Yi; Zhou, Kai-Le; Yang, Shan-Lin; Shang, Jennifer S.

2014-01-01

Facing a customer market with rising demands for cloud service dependability and security, trustworthiness evaluation techniques are becoming essential to cloud service selection. But these methods are out of the reach to most customers as they require considerable expertise. Additionally, since the cloud service evaluation is often a costly and time-consuming process, it is not practical to measure trustworthy attributes of all candidates for each customer. Many existing models cannot easily deal with cloud services which have very few historical records. In this paper, we propose a novel service selection approach in which the missing value prediction and the multi-attribute trustworthiness evaluation are commonly taken into account. By simply collecting limited historical records, the current approach is able to support the personalized trustworthy service selection. The experimental results also show that our approach performs much better than other competing ones with respect to the customer preference and expectation in trustworthiness assessment. PMID:24972237

Decision support for personalized cloud service selection through multi-attribute trustworthiness evaluation.

PubMed

Ding, Shuai; Xia, Cheng-Yi; Xia, Chen-Yi; Zhou, Kai-Le; Yang, Shan-Lin; Shang, Jennifer S

2014-01-01

Facing a customer market with rising demands for cloud service dependability and security, trustworthiness evaluation techniques are becoming essential to cloud service selection. But these methods are out of the reach to most customers as they require considerable expertise. Additionally, since the cloud service evaluation is often a costly and time-consuming process, it is not practical to measure trustworthy attributes of all candidates for each customer. Many existing models cannot easily deal with cloud services which have very few historical records. In this paper, we propose a novel service selection approach in which the missing value prediction and the multi-attribute trustworthiness evaluation are commonly taken into account. By simply collecting limited historical records, the current approach is able to support the personalized trustworthy service selection. The experimental results also show that our approach performs much better than other competing ones with respect to the customer preference and expectation in trustworthiness assessment.

The effect of uncertainties in distance-based ranking methods for multi-criteria decision making

NASA Astrophysics Data System (ADS)

Jaini, Nor I.; Utyuzhnikov, Sergei V.

2017-08-01

Data in the multi-criteria decision making are often imprecise and changeable. Therefore, it is important to carry out sensitivity analysis test for the multi-criteria decision making problem. The paper aims to present a sensitivity analysis for some ranking techniques based on the distance measures in multi-criteria decision making. Two types of uncertainties are considered for the sensitivity analysis test. The first uncertainty is related to the input data, while the second uncertainty is towards the Decision Maker preferences (weights). The ranking techniques considered in this study are TOPSIS, the relative distance and trade-off ranking methods. TOPSIS and the relative distance method measure a distance from an alternative to the ideal and antiideal solutions. In turn, the trade-off ranking calculates a distance of an alternative to the extreme solutions and other alternatives. Several test cases are considered to study the performance of each ranking technique in both types of uncertainties.

Temporary site selection and decision-making methods: a case study of Tehran, Iran.

PubMed

Omidvar, Babak; Baradaran-Shoraka, Mohammad; Nojavan, Mehdi

2013-07-01

Decisions on selecting an appropriate site for temporary shelter used to be taken in a limited amount of time after a disaster. The need for a systematic method in this area inspired the MADM (multi-attribute decision making) for complex disaster management decisions. This research proposes a model for appropriate and systematic site selection for temporary shelters, before an earthquake, using a geographical information system and MADM based on an earthquake damage assessment. After the effective criteria for site selection of temporary shelters are determined, the geographical layers of these criteria are prepared for Municipal District No.1 of Greater Tehran, the capital of Iran. Given these attributes and the required shelter area (415-610 hectares), 14 zones are proposed initially. Various MADM methods are used for the final selection. The mean of the aggregated ranking results are determined, and 10 of the 14 initial zones are ranked. © 2013 The Author(s). Journal compilation © Overseas Development Institute, 2013.

Measurements of Rationality: Individual Differences in Information Processing, the Transitivity of Preferences and Decision Strategies

PubMed Central

Sleboda, Patrycja; Sokolowska, Joanna

2017-01-01

The first goal of this study was to validate the Rational-Experiential Inventory (REI) and the Cognitive Reflection Test (CRT) through checking their relation to the transitivity axiom. The second goal was to test the relation between decision strategies and cognitive style as well as the relation between decision strategies and the transitivity of preferences. The following characteristics of strategies were investigated: requirements for trade-offs, maximization vs. satisficing and option-wise vs. attribute-wise information processing. Respondents were given choices between two multi-attribute options. The options were designed so that the choice indicated which strategy was applied. Both the REI-R and the CRT were found to be good predictors of the transitivity of preferences. Respondents who applied compensatory strategies and the maximization criterion scored highly on the REI-R and in the CRT, whereas those who applied the satisficing rule scored highly on the REI-R but not in the CRT. Attribute-wise information processing was related to low scores in both measurements. Option-wise information processing led to a high transitivity of preferences. PMID:29093695

Measurements of Rationality: Individual Differences in Information Processing, the Transitivity of Preferences and Decision Strategies.

PubMed

Sleboda, Patrycja; Sokolowska, Joanna

2017-01-01

The first goal of this study was to validate the Rational-Experiential Inventory ( REI ) and the Cognitive Reflection Test ( CRT ) through checking their relation to the transitivity axiom. The second goal was to test the relation between decision strategies and cognitive style as well as the relation between decision strategies and the transitivity of preferences. The following characteristics of strategies were investigated: requirements for trade-offs, maximization vs. satisficing and option-wise vs. attribute-wise information processing. Respondents were given choices between two multi-attribute options. The options were designed so that the choice indicated which strategy was applied. Both the REI-R and the CRT were found to be good predictors of the transitivity of preferences. Respondents who applied compensatory strategies and the maximization criterion scored highly on the REI-R and in the CRT , whereas those who applied the satisficing rule scored highly on the REI-R but not in the CRT . Attribute-wise information processing was related to low scores in both measurements. Option-wise information processing led to a high transitivity of preferences.

The conceptual foundation of environmental decision support.

PubMed

Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele

2015-05-01

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. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Informing vaccine decision-making: A strategic multi-attribute ranking tool for vaccines-SMART Vaccines 2.0.

PubMed

Knobler, Stacey; Bok, Karin; Gellin, Bruce

2017-01-20

SMART Vaccines 2.0 software is being developed to support decision-making among multiple stakeholders in the process of prioritizing investments to optimize the outcomes of vaccine development and deployment. Vaccines and associated vaccination programs are one of the most successful and effective public health interventions to prevent communicable diseases and vaccine researchers are continually working towards expanding targets for communicable and non-communicable diseases through preventive and therapeutic modes. A growing body of evidence on emerging vaccine technologies, trends in disease burden, costs associated with vaccine development and deployment, and benefits derived from disease prevention through vaccination and a range of other factors can inform decision-making and investment in new and improved vaccines and targeted utilization of already existing vaccines. Recognizing that an array of inputs influences these decisions, the strategic multi-attribute ranking method for vaccines (SMART Vaccines 2.0) is in development as a web-based tool-modified from a U.S. Institute of Medicine Committee effort (IOM, 2015)-to highlight data needs and create transparency to facilitate dialogue and information-sharing among decision-makers and to optimize the investment of resources leading to improved health outcomes. Current development efforts of the SMART Vaccines 2.0 framework seek to generate a weighted recommendation on vaccine development or vaccination priorities based on population, disease, economic, and vaccine-specific data in combination with individual preference and weights of user-selected attributes incorporating valuations of health, economics, demographics, public concern, scientific and business, programmatic, and political considerations. Further development of the design and utility of the tool is being carried out by the National Vaccine Program Office of the Department of Health and Human Services and the Fogarty International Center of the National Institutes of Health. We aim to demonstrate the utility of SMART Vaccines 2.0 through the engagement of a community of relevant stakeholders and to identify a limited number of pilot projects to determine explicitly defined attribute preferences and the related data and model requirements that are responsive to user needs and able to improve the use of evidence for vaccine-related decision-making and consequential priorities of vaccination options. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exploring the impact of different multi-level measures of physician communities in patient-centric care networks on healthcare outcomes: A multi-level regression approach.

PubMed

Uddin, Shahadat

2016-02-04

A patient-centric care network can be defined as a network among a group of healthcare professionals who provide treatments to common patients. Various multi-level attributes of the members of this network have substantial influence to its perceived level of performance. In order to assess the impact different multi-level attributes of patient-centric care networks on healthcare outcomes, this study first captured patient-centric care networks for 85 hospitals using health insurance claim dataset. From these networks, this study then constructed physician collaboration networks based on the concept of patient-sharing network among physicians. A multi-level regression model was then developed to explore the impact of different attributes that are organised at two levels on hospitalisation cost and hospital length of stay. For Level-1 model, the average visit per physician significantly predicted both hospitalisation cost and hospital length of stay. The number of different physicians significantly predicted only the hospitalisation cost, which has significantly been moderated by age, gender and Comorbidity score of patients. All Level-1 findings showed significance variance across physician collaboration networks having different community structure and density. These findings could be utilised as a reflective measure by healthcare decision makers. Moreover, healthcare managers could consider them in developing effective healthcare environments.

A matter of tradeoffs: reintroduction as a multiple objective decision

USGS Publications Warehouse

Converse, Sarah J.; Moore, Clinton T.; Folk, Martin J.; Runge, Michael C.

2013-01-01

Decision making in guidance of reintroduction efforts is made challenging by the substantial scientific uncertainty typically involved. However, a less recognized challenge is that the management objectives are often numerous and complex. Decision makers managing reintroduction efforts are often concerned with more than just how to maximize the probability of reintroduction success from a population perspective. Decision makers are also weighing other concerns such as budget limitations, public support and/or opposition, impacts on the ecosystem, and the need to consider not just a single reintroduction effort, but conservation of the entire species. Multiple objective decision analysis is a powerful tool for formal analysis of such complex decisions. We demonstrate the use of multiple objective decision analysis in the case of the Florida non-migratory whooping crane reintroduction effort. In this case, the State of Florida was considering whether to resume releases of captive-reared crane chicks into the non-migratory whooping crane population in that state. Management objectives under consideration included maximizing the probability of successful population establishment, minimizing costs, maximizing public relations benefits, maximizing the number of birds available for alternative reintroduction efforts, and maximizing learning about the demographic patterns of reintroduced whooping cranes. The State of Florida engaged in a collaborative process with their management partners, first, to evaluate and characterize important uncertainties about system behavior, and next, to formally evaluate the tradeoffs between objectives using the Simple Multi-Attribute Rating Technique (SMART). The recommendation resulting from this process, to continue releases of cranes at a moderate intensity, was adopted by the State of Florida in late 2008. Although continued releases did not receive support from the International Whooping Crane Recovery Team, this approach does provide a template for the formal, transparent consideration of multiple, potentially competing, objectives in reintroduction decision making.

A decision support for an integrated multi-scale analysis of irrigation: DSIRR.

PubMed

Bazzani, Guido M

2005-12-01

The paper presents a decision support designed to conduct an economic-environmental assessment of the agricultural activity focusing on irrigation called 'Decision Support for IRRigated Agriculture' (DSIRR). The program describes the effect at catchment scale of choices taken at micro scale by independent actors, the farmers, by simulating their decision process. The decision support (DS) has been thought of as a support tool for participatory water policies as requested by the Water Framework Directive and it aims at analyzing alternatives in production and technology, according to different market, policy and climate conditions. The tool uses data and models, provides a graphical user interface and can incorporate the decision makers' own insights. Heterogeneity in preferences is admitted since it is assumed that irrigators try to optimize personal multi-attribute utility functions, subject to a set of constraints. Consideration of agronomic and engineering aspects allows an accurate description of irrigation. Mathematical programming techniques are applied to find solutions. The program has been applied in the river Po basin (northern Italy) to analyze the impact of a pricing policy in a context of irrigation technology innovation. Water demand functions and elasticity to water price have been estimated. Results demonstrate how different areas and systems react to the same policy in quite a different way. While in the annual cropping system pricing seems effective to save the resource at the cost of impeding Water Agencies cost recovery, the same policy has an opposite effect in the perennial fruit system which shows an inelastic response to water price. The multidimensional assessment conducted clarified the trades-off among conflicting economic-social-environmental objectives, thus generating valuable information to design a more tailored mix of measures.

The use of multi-criteria decision analysis to tackle waste management problems: a literature review.

PubMed

Achillas, Charisios; Moussiopoulos, Nicolas; Karagiannidis, Avraam; Banias, Georgias; Perkoulidis, George

2013-02-01

Problems in waste management have become more and more complex during recent decades. The increasing volumes of waste produced and social environmental consciousness present prominent drivers for environmental managers towards the achievement of a sustainable waste management scheme. However, in practice, there are many factors and influences - often mutually conflicting - criteria for finding solutions in real-life applications. This paper presents a review of the literature on multi-criteria decision aiding in waste management problems for all reported waste streams. Despite limitations, which are clearly stated, most of the work published in this field is reviewed. The present review aims to provide environmental managers and decision-makers with a thorough list of practical applications of the multi-criteria decision analysis techniques that are used to solve real-life waste management problems, as well as the criteria that are mostly employed in such applications according to the nature of the problem under study. Moreover, the paper explores the advantages and disadvantages of using multi-criteria decision analysis techniques in waste management problems in comparison to other available alternatives.

Is it the time to rethink clinical decision-making strategies? From a single clinical outcome evaluation to a Clinical Multi-criteria Decision Assessment (CMDA).

PubMed

Migliore, Alberto; Integlia, Davide; Bizzi, Emanuele; Piaggio, Tomaso

2015-10-01

There are plenty of different clinical, organizational and economic parameters to consider in order having a complete assessment of the total impact of a pharmaceutical treatment. In the attempt to follow, a holistic approach aimed to provide an evaluation embracing all clinical parameters in order to choose the best treatments, it is necessary to compare and weight multiple criteria. Therefore, a change is required: we need to move from a decision-making context based on the assessment of one single criteria towards a transparent and systematic framework enabling decision makers to assess all relevant parameters simultaneously in order to choose the best treatment to use. In order to apply the MCDA methodology to clinical decision making the best pharmaceutical treatment (or medical devices) to use to treat a specific pathology, we suggest a specific application of the Multiple Criteria Decision Analysis for the purpose, like a Clinical Multi-criteria Decision Assessment CMDA. In CMDA, results from both meta-analysis and observational studies are used by a clinical consensus after attributing weights to specific domains and related parameters. The decision will result from a related comparison of all consequences (i.e., efficacy, safety, adherence, administration route) existing behind the choice to use a specific pharmacological treatment. The match will yield a score (in absolute value) that link each parameter with a specific intervention, and then a final score for each treatment. The higher is the final score; the most appropriate is the intervention to treat disease considering all criteria (domain an parameters). The results will allow the physician to evaluate the best clinical treatment for his patients considering at the same time all relevant criteria such as clinical effectiveness for all parameters and administration route. The use of CMDA model will yield a clear and complete indication of the best pharmaceutical treatment to use for patients, helping physicians to choose drugs with a complete set of information, imputed in the model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Contextual Attributes of Indirect Bullying Situations that Influence Teachers' Decisions to Intervene

ERIC Educational Resources Information Center

Blain-Arcaro, Christine; Smith, J. David; Cunningham, Charles E.; Vaillancourt, Tracy; Rimas, Heather

2012-01-01

Indirect bullying occurs frequently yet receives little attention by teachers. Using conjoint analysis, we examined the influence of situational attributes on teachers' decisions to intervene in indirect bullying. Results revealed that teachers (N = 235) were most influenced by victimized children's distress. Additional analyses identified two…

Patients' Non-Medical Characteristics Contribute to Collective Medical Decision-Making at Multidisciplinary Oncological Team Meetings.

PubMed

Restivo, Léa; Apostolidis, Thémis; Bouhnik, Anne-Déborah; Garciaz, Sylvain; Aurran, Thérèse; Julian-Reynier, Claire

2016-01-01

The contribution of patients' non-medical characteristics to individual physicians' decision-making has attracted considerable attention, but little information is available on this topic in the context of collective decision-making. Medical decision-making at cancer centres is currently carried out using a collective approach, at MultiDisciplinary Team (MDT) meetings. The aim of this study was to determine how patients' non-medical characteristics are presented at MDT meetings and how this information may affect the team's final medical decisions. Observations were conducted at a French Cancer Centre during MDT meetings at which non-standard cases involving some uncertainty were discussed from March to May 2014. Physicians' verbal statements and predefined contextual parameters were collected with a non-participant observational approach. Non numerical data collected in the form of open notes were then coded for quantitative analysis. Univariate and multivariate statistical analyses were performed. In the final sample of patients' records included and discussed (N = 290), non-medical characteristics were mentioned in 32.8% (n = 95) of the cases. These characteristics corresponded to demographics in 22.8% (n = 66) of the cases, psychological data in 11.7% (n = 34), and relational data in 6.2% (n = 18). The patient's age and his/her "likeability" were the most frequently mentioned characteristics. In 17.9% of the cases discussed, the final decision was deferred: this outcome was positively associated with the patients' non-medical characteristics and with uncertainty about the outcome of the therapeutic options available. The design of the study made it difficult to draw definite cause-and-effect conclusions. The Social Representations approach suggests that patients' non-medical characteristics constitute a kind of tacit professional knowledge that may be frequently mobilised in physicians' everyday professional practice. The links observed between patients' attributes and the medical decisions made at these meetings show that these attributes should be taken into account in order to understand how medical decisions are reached in difficult situations of this kind.

Building a picture: Prioritisation of exotic diseases for the pig industry in Australia using multi-criteria decision analysis.

PubMed

Brookes, V J; Hernández-Jover, M; Cowled, B; Holyoake, P K; Ward, M P

2014-01-01

Diseases that are exotic to the pig industry in Australia were prioritised using a multi-criteria decision analysis framework that incorporated weights of importance for a range of criteria important to industry stakeholders. Measurements were collected for each disease for nine criteria that described potential disease impacts. A total score was calculated for each disease using a weighted sum value function that aggregated the nine disease criterion measurements and weights of importance for the criteria that were previously elicited from two groups of industry stakeholders. One stakeholder group placed most value on the impacts of disease on livestock, and one group placed more value on the zoonotic impacts of diseases. Prioritisation lists ordered by disease score were produced for both of these groups. Vesicular diseases were found to have the highest priority for the group valuing disease impacts on livestock, followed by acute forms of African and classical swine fever, then highly pathogenic porcine reproductive and respiratory syndrome. The group who valued zoonotic disease impacts prioritised rabies, followed by Japanese encephalitis, Eastern equine encephalitis and Nipah virus, interspersed with vesicular diseases. The multi-criteria framework used in this study systematically prioritised diseases using a multi-attribute theory based technique that provided transparency and repeatability in the process. Flexibility of the framework was demonstrated by aggregating the criterion weights from more than one stakeholder group with the disease measurements for the criteria. This technique allowed industry stakeholders to be active in resource allocation for their industry without the need to be disease experts. We believe it is the first prioritisation of livestock diseases using values provided by industry stakeholders. The prioritisation lists will be used by industry stakeholders to identify diseases for further risk analysis and disease spread modelling to understand biosecurity risks to this industry. Copyright © 2013 Elsevier B.V. All rights reserved.

Decision Making and Priority Setting: The Evolving Path Towards Universal Health Coverage.

PubMed

Paolucci, Francesco; Redekop, Ken; Fouda, Ayman; Fiorentini, Gianluca

2017-12-01

Health technology assessment (HTA) is widely viewed as an essential component in good universal health coverage (UHC) decision-making in any country. Various HTA tools and metrics have been developed and refined over the years, including systematic literature reviews (Cochrane), economic modelling, and cost-effectiveness ratios and acceptability curves. However, while the cost-effectiveness ratio is faithfully reported in most full economic evaluations, it is viewed by many as an insufficient basis for reimbursement decisions. Emotional debates about the reimbursement of cancer drugs, orphan drugs, and end-of-life treatments have revealed fundamental disagreements about what should and should not be considered in reimbursement decisions. Part of this disagreement seems related to the equity-efficiency tradeoff, which reflects fundamental differences in priorities. All in all, it is clear that countries aiming to improve UHC policies will have to go beyond the capacity building needed to utilize the available HTA toolbox. Multi-criteria decision analysis (MCDA) offers a more comprehensive tool for reimbursement decisions where different weights of different factors/attributes can give policymakers important insights to consider. Sooner or later, every country will have to develop their own way to carefully combine the results of those tools with their own priorities. In the end, all policymaking is based on a mix of facts and values.

Zoning of an agricultural field using a fuzzy indicator model in combination with tool for multi-attributed decision-making

USDA-ARS?s Scientific Manuscript database

Zoning of agricultural fields is an important task for utilization of precision farming technology. This paper extends previously published work entitled “Zoning of an agricultural field using a fuzzy indicator model” to a general case where there is disagreement between groups of managers or expert...

Visual Attention Allocation Between Robotic Arm and Environmental Process Control: Validating the STOM Task Switching Model

NASA Technical Reports Server (NTRS)

Wickens, Christopher; Vieanne, Alex; Clegg, Benjamin; Sebok, Angelia; Janes, Jessica

2015-01-01

Fifty six participants time shared a spacecraft environmental control system task with a realistic space robotic arm control task in either a manual or highly automated version. The former could suffer minor failures, whose diagnosis and repair were supported by a decision aid. At the end of the experiment this decision aid unexpectedly failed. We measured visual attention allocation and switching between the two tasks, in each of the eight conditions formed by manual-automated arm X expected-unexpected failure X monitoring- failure management. We also used our multi-attribute task switching model, based on task attributes of priority interest, difficulty and salience that were self-rated by participants, to predict allocation. An un-weighted model based on attributes of difficulty, interest and salience accounted for 96 percent of the task allocation variance across the 8 different conditions. Task difficulty served as an attractor, with more difficult tasks increasing the tendency to stay on task.

Multi-Case Review of the Application of the Precautionary Principle in European Union Law and Case Law.

PubMed

Garnett, Kenisha; Parsons, David J

2017-03-01

The precautionary principle was formulated to provide a basis for political action to protect the environment from potentially severe or irreversible harm in circumstances of scientific uncertainty that prevent a full risk or cost-benefit analysis. It underpins environmental law in the European Union and has been extended to include public health and consumer safety. The aim of this study was to examine how the precautionary principle has been interpreted and subsequently applied in practice, whether these applications were consistent, and whether they followed the guidance from the Commission. A review of the literature was used to develop a framework for analysis, based on three attributes: severity of potential harm, standard of evidence (or degree of uncertainty), and nature of the regulatory action. This was used to examine 15 pieces of legislation or judicial decisions. The decision whether or not to apply the precautionary principle appears to be poorly defined, with ambiguities inherent in determining what level of uncertainty and significance of hazard justifies invoking it. The cases reviewed suggest that the Commission's guidance was not followed consistently in forming legislation, although judicial decisions tended to be more consistent and to follow the guidance by requiring plausible evidence of potential hazard in order to invoke precaution. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework

NASA Astrophysics Data System (ADS)

Afsordegan, A.; Sánchez, M.; Agell, N.; Aguado, J. C.; Gamboa, G.

2016-03-01

A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks.

Maclaurin symmetric mean operators of linguistic intuitionistic fuzzy numbers and their application to multiple-attribute decision-making

NASA Astrophysics Data System (ADS)

Liu, Peide; Qin, Xiyou

2017-11-01

Linguistic intuitionistic fuzzy number (LIFN) is a special intuitionistic fuzzy number which can more easily describe the vagueness existing in the real decision-making. Maclaurin symmetric mean (MSM) operator has the characteristic of considering the interrelationships among any number of input parameters. In this paper, we extended the MSM operator to the LIFNs and some extended MSM operators for LIFNs were proposed, some new decision-making methods were developed. Firstly, we introduced the definition, score function, properties and operational rules of the LIFNs. Then, we proposed some linguistic intuitionistic fuzzy MSM operators, such as linguistic intuitionistic fuzzy Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy Maclaurin symmetric mean (WLIFMSM) operator, linguistic intuitionistic fuzzy dual Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy dual Maclaurin symmetric mean (WLIFDMSM) operator. In the meantime, we studied some important properties of these operators, and developed some methods based on WLIFMSM operator and WLIFDMSM operator for multi-attribute decision-making. Finally, we use an example to demonstrate the effectiveness of the proposed methods.

A decision support tool to prioritize risk management options for contaminated sites.

PubMed

Sorvari, Jaana; Seppälä, Jyri

2010-03-15

The decisions on risk management (RM) of contaminated sites in Finland have typically been driven by practical factors such as time and money. However, RM is a multifaceted task that generally involves several additional determinants, e.g. performance and environmental effects of remediation methods, psychological and social factors. Therefore, we adopted a multi-criteria decision analysis approach and developed a decision support tool (DST) that is viable in decision-making in such a complex situation. The basic components of the DST are based on the Dutch REC system. However, our DST is more case-specific and allows the consideration of the type, magnitude and scale of contamination, land use, environmental conditions and socio-cultural aspects (e.g. loss of cultural heritage, image aspects). The construction of the DST was started by structuring the decision problem using a value tree. Based on this work we adopted the Multi-Attribute Value Theory (MAVT) for data aggregation. The final DST was demonstrated by two model sites for which the RM alternatives and site-specific data were created on the basis of factual remediation projects and by interviewing experts. The demonstration of the DST was carried out in a workshop where representatives of different stakeholders were requested to rank and weight the decision criteria involved. To get information on the consistency of the ranking of the RM alternatives, we used different weighting techniques (ratio estimation and pair-wise weighting) and alternative ways to treat individual respondents' weights in calculating the preference scores for each RM alternative. These dissimilar approaches resulted in some differences in the preference order of the RM alternatives. The demonstration showed that attention has to be paid to the proper description of the site, the principles of the procedure and the decision criteria. Nevertheless, the procedure proved to enable efficient communication between different stakeholders and the identification of the preferred RM option.

A case for multi-model and multi-approach based event attribution: The 2015 European drought

NASA Astrophysics Data System (ADS)

Hauser, Mathias; Gudmundsson, Lukas; Orth, René; Jézéquel, Aglaé; Haustein, Karsten; Seneviratne, Sonia Isabelle

2017-04-01

Science on the role of anthropogenic influence on extreme weather events such as heat waves or droughts has evolved rapidly over the past years. The approach of "event attribution" compares the occurrence probability of an event in the present, factual world with the probability of the same event in a hypothetical, counterfactual world without human-induced climate change. Every such analysis necessarily faces multiple methodological choices including, but not limited to: the event definition, climate model configuration, and the design of the counterfactual world. Here, we explore the role of such choices for an attribution analysis of the 2015 European summer drought (Hauser et al., in preparation). While some GCMs suggest that anthropogenic forcing made the 2015 drought more likely, others suggest no impact, or even a decrease in the event probability. These results additionally differ for single GCMs, depending on the reference used for the counterfactual world. Observational results do not suggest a historical tendency towards more drying, but the record may be too short to provide robust assessments because of the large interannual variability of drought occurrence. These results highlight the need for a multi-model and multi-approach framework in event attribution research. This is especially important for events with low signal to noise ratio and high model dependency such as regional droughts. Hauser, M., L. Gudmundsson, R. Orth, A. Jézéquel, K. Haustein, S.I. Seneviratne, in preparation. A case for multi-model and multi-approach based event attribution: The 2015 European drought.

Rooftop greenhouses in educational centers: A sustainability assessment of urban agriculture in compact cities.

PubMed

Nadal, Ana; Pons, Oriol; Cuerva, Eva; Rieradevall, Joan; Josa, Alejandro

2018-06-01

Today, urban agriculture is one of the most widely used sustainability strategies to improve the metabolism of a city. Schools can play an important role in the implementation of sustainability master plans, due their socio-educational activities and their cohesive links with families; all key elements in the development of urban agriculture. Thus, the main objective of this research is to develop a procedure, in compact cities, to assess the potential installation of rooftop greenhouses (RTGs) in schools. The generation of a dynamic assessment tool capable of identifying and prioritizing schools with a high potential for RTGs and their eventual implementation would also represent a significant factor in the environmental, social, and nutritional education of younger generations. The methodology has four-stages (Pre-selection criteria; Selection of necessities; Sustainability analysis; and Sensitivity analysis and selection of the best alternative) in which economic, environmental, social and governance aspects all are considered. It makes use of Multi-Attribute Utility Theory and Multi-Criteria Decision Making, through the Integrated Value Model for Sustainability Assessments and the participation of two panels of multidisciplinary specialists, for the preparation of a unified sustainability index that guarantees the objectivity of the selection process. This methodology has been applied and validated in a case study of 11 schools in Barcelona (Spain). The social perspective of the proposed methodology favored the school in the case-study with the most staff and the largest parent-teacher association (social and governance indicators) that obtained the highest sustainability index (S11); at a considerable distance (45%) from the worst case (S3) with fewer school staff and parental support. Finally, objective decisions may be taken with the assistance of this appropriate, adaptable, and reliable Multi-Criteria Decision-Making tool on the vertical integration and implementation of urban agriculture in schools, in support of the goals of sustainable development and the circular economy. Copyright © 2018 Elsevier B.V. All rights reserved.

Assessing the Reliability and Validity of Multi-Attribute Utility Procedures: An Application of the Theory of Generalizability

DTIC Science & Technology

1975-07-01

I WIWIHIHlipi pqpv<Hi^«^Rii.i ii mmw AD-A016 282 ASSESSING THE REALIBILITY AND VALIDITY OF MULTI-ATTRIBUTE UTILITY PROCEDURES: AN...more complicated and use data from actual experiments. Example 1: Analysis of raters making Importance judgments about attributes. In MAU studies...generaluablllty of JUDGE as contrasted to ÜASC. To do this, we win reanaIyze the data for each syste™ separately. This 1. valid since the initial

CPTAC Develops LinkedOmics – Public Web Portal to Analyze Multi-Omics Data Within and Across Cancer Types | Office of Cancer Clinical Proteomics Research

Cancer.gov

Multi-omics analysis has grown in popularity among biomedical researchers given the comprehensive characterization of thousands of molecular attributes in addition to clinical attributes. Several data portals have been devised to make these datasets directly available to the cancer research community. However, none of the existing data portals allow systematic exploration and interpretation of the complex relationships between the vast amount of clinical and molecular attributes. CPTAC investigator Dr.

Don't Discount Societal Value in Cost-Effectiveness Comment on "Priority Setting for Universal Health Coverage: We Need Evidence-Informed Deliberative Processes, Not Just More Evidence on Cost-Effectiveness".

PubMed

Hall, William

2017-01-14

As healthcare resources become increasingly scarce due to growing demand and stagnating budgets, the need for effective priority setting and resource allocation will become ever more critical to providing sustainable care to patients. While societal values should certainly play a part in guiding these processes, the methodology used to capture these values need not necessarily be limited to multi-criterion decision analysis (MCDA)-based processes including 'evidence-informed deliberative processes.' However, if decision-makers intend to not only incorporates the values of the public they serve into decisions but have the decisions enacted as well, consideration should be given to more direct involvement of stakeholders. Based on the examples provided by Baltussen et al, MCDA-based processes like 'evidence-informed deliberative processes' could be one way of achieving this laudable goal. © 2017 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Multi-Response Optimization of WEDM Process Parameters Using Taguchi Based Desirability Function Analysis

NASA Astrophysics Data System (ADS)

Majumder, Himadri; Maity, Kalipada

2018-03-01

Shape memory alloy has a unique capability to return to its original shape after physical deformation by applying heat or thermo-mechanical or magnetic load. In this experimental investigation, desirability function analysis (DFA), a multi-attribute decision making was utilized to find out the optimum input parameter setting during wire electrical discharge machining (WEDM) of Ni-Ti shape memory alloy. Four critical machining parameters, namely pulse on time (TON), pulse off time (TOFF), wire feed (WF) and wire tension (WT) were taken as machining inputs for the experiments to optimize three interconnected responses like cutting speed, kerf width, and surface roughness. Input parameter combination TON = 120 μs., TOFF = 55 μs., WF = 3 m/min. and WT = 8 kg-F were found to produce the optimum results. The optimum process parameters for each desired response were also attained using Taguchi’s signal-to-noise ratio. Confirmation test has been done to validate the optimum machining parameter combination which affirmed DFA was a competent approach to select optimum input parameters for the ideal response quality for WEDM of Ni-Ti shape memory alloy.

The Influence of Game Design on the Collaborative Problem Solving Process: A Cross-Case Study of Multi-Player Collaborative Gameplay Analysis

ERIC Educational Resources Information Center

Yildirim, Nilay

2013-01-01

This cross-case study examines the relationships between game design attributes and collaborative problem solving process in the context of multi-player video games. The following game design attributes: sensory stimuli elements, level of challenge, and presentation of game goals and rules were examined to determine their influence on game…

Decision fatigue: A conceptual analysis.

PubMed

Pignatiello, Grant A; Martin, Richard J; Hickman, Ronald L

2018-03-01

Decision fatigue is an applicable concept to healthcare psychology. Due to a lack of conceptual clarity, we present a concept analysis of decision fatigue. A search of the term "decision fatigue" was conducted across seven research databases, which yielded 17 relevant articles. The authors identified three antecedent themes (decisional, self-regulatory, and situational) and three attributional themes (behavioral, cognitive, and physiological) of decision fatigue. However, the extant literature failed to adequately describe consequences of decision fatigue. This concept analysis provides needed conceptual clarity for decision fatigue, a concept possessing relevance to nursing and allied health sciences.

Using multi-attribute decision-making approaches in the selection of a hospital management system.

PubMed

Arasteh, Mohammad Ali; Shamshirband, Shahaboddin; Yee, Por Lip

2018-01-01

The most appropriate organizational software is always a real challenge for managers, especially, the IT directors. The illustration of the term "enterprise software selection", is to purchase, create, or order a software that; first, is best adapted to require of the organization; and second, has suitable price and technical support. Specifying selection criteria and ranking them, is the primary prerequisite for this action. This article provides a method to evaluate, rank, and compare the available enterprise software for choosing the apt one. The prior mentioned method is constituted of three-stage processes. First, the method identifies the organizational requires and assesses them. Second, it selects the best method throughout three possibilities; indoor-production, buying software, and ordering special software for the native use. Third, the method evaluates, compares and ranks the alternative software. The third process uses different methods of multi attribute decision making (MADM), and compares the consequent results. Based on different characteristics of the problem; several methods had been tested, namely, Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Elimination and Choice Expressing Reality (ELECTURE), and easy weight method. After all, we propose the most practical method for same problems.

Mapping clinical outcomes expectations to treatment decisions: an application to vestibular schwannoma management.

PubMed

Cheung, Steven W; Aranda, Derick; Driscoll, Colin L W; Parsa, Andrew T

2010-02-01

Complex medical decision making obligates tradeoff assessments among treatment outcomes expectations, but an accessible tool to perform the necessary analysis is conspicuously absent. We aimed to demonstrate methodology and feasibility of adapting conjoint analysis for mapping clinical outcomes expectations to treatment decisions in vestibular schwannoma (VS) management. Prospective. Tertiary medical center and US-based otologists/neurotologists. Treatment preference profiles among VS stakeholders-61 younger and 74 older prospective patients, 61 observation patients, and 60 surgeons-were assessed for the synthetic VS case scenario of a 10-mm tumor in association with useful hearing and normal facial function. Treatment attribute utility. Conjoint analysis attribute levels were set in accordance to the results of a meta-analysis. Forty-five case series were disaggregated to formulate microsurgery facial nerve and hearing preservation outcomes expectations models. Attribute utilities were computed and mapped to the realistic treatment choices of translabyrinthine craniotomy, middle fossa craniotomy, and gamma knife radiosurgery. Among the treatment attributes of likelihoods of causing deafness, temporary facial weakness for 2 months, and incurable cancer within 20 years, and recovery time, permanent deafness was less important to tumor surgeons, and temporary facial weakness was more important to tumor surgeons and observation patients (Wilcoxon rank-sum, p < 0.001). Inverse mapping of preference profiles to realistic treatment choices showed all study cohorts were inclined to choose gamma knife radiosurgery. Mapping clinical outcomes expectations to treatment decisions for a synthetic clinical scenario revealed inhomogeneous drivers of choice selection among study cohorts. Medical decision engines that analyze personal preferences of outcomes expectations for VS and many other diseases may be developed to promote shared decision making among health care stakeholders and transparency in the informed consent process.

Visualization-based decision support for value-driven system design

NASA Astrophysics Data System (ADS)

Tibor, Elliott

In the past 50 years, the military, communication, and transportation systems that permeate our world, have grown exponentially in size and complexity. The development and production of these systems has seen ballooning costs and increased risk. This is particularly critical for the aerospace industry. The inability to deal with growing system complexity is a crippling force in the advancement of engineered systems. Value-Driven Design represents a paradigm shift in the field of design engineering that has potential to help counteract this trend. The philosophy of Value-Driven Design places the desires of the stakeholder at the forefront of the design process to capture true preferences and reveal system alternatives that were never previously thought possible. Modern aerospace engineering design problems are large, complex, and involve multiple levels of decision-making. To find the best design, the decision-maker is often required to analyze hundreds or thousands of combinations of design variables and attributes. Visualization can be used to support these decisions, by communicating large amounts of data in a meaningful way. Understanding the design space, the subsystem relationships, and the design uncertainties is vital to the advancement of Value-Driven Design as an accepted process for the development of more effective, efficient, robust, and elegant aerospace systems. This research investigates the use of multi-dimensional data visualization tools to support decision-making under uncertainty during the Value-Driven Design process. A satellite design system comprising a satellite, ground station, and launch vehicle is used to demonstrate effectiveness of new visualization methods to aid in decision support during complex aerospace system design. These methods are used to facilitate the exploration of the feasible design space by representing the value impact of system attribute changes and comparing the results of multi-objective optimization formulations with a Value-Driven Design formulation. The visualization methods are also used to assist in the decomposition of a value function, by representing attribute sensitivities to aid with trade-off studies. Lastly, visualization is used to enable greater understanding of the subsystem relationships, by displaying derivative-based couplings, and the design uncertainties, through implementation of utility theory. The use of these visualization methods is shown to enhance the decision-making capabilities of the designer by granting them a more holistic view of the complex design space.

Comparative analysis of decision maker preferences for equity/efficiency attributes in reimbursement decisions in three European countries.

PubMed

Baji, Petra; García-Goñi, Manuel; Gulácsi, László; Mentzakis, Emmanouil; Paolucci, Francesco

2016-09-01

In addition to cost-effectiveness, national guidelines often include other factors in reimbursement decisions. However, weights attached to these are rarely quantified, thus decisions can depend strongly on decision-maker preferences. To explore the preferences of policymakers and healthcare professionals involved in the decision-making process for different efficiency and equity attributes of interventions and to analyse cross-country differences. Discrete choice experiments (DCEs) were carried out in Austria, Hungary, and Norway with policymakers and other professionals working in the health industry (N = 153 respondents). Interventions were described in terms of different efficiency and equity attributes (severity of disease, target age of the population and willingness to subsidise others, potential number of beneficiaries, individual health benefit, and cost-effectiveness). Parameter estimates from the DCE were used to calculate the probability of choosing a healthcare intervention with different characteristics, and to rank different equity and efficiency attributes according to their importance. In all three countries, cost-effectiveness, individual health benefit and severity of the disease were significant and equally important determinants of decisions. All countries show preferences for interventions targeting young and middle aged populations compared to those targeting populations over 60. However, decision-makers in Austria and Hungary show preferences more oriented to efficiency than equity, while those in Norway show equal preferences for equity and efficiency attributes. We find that factors other than cost-effectiveness seem to play an equally important role in decision-making. We also find evidence of cross-country differences in the weight of efficiency and equity attributes.

Selection for inpatient rehabilitation after severe stroke: what factors influence rehabilitation assessor decision-making?

PubMed

Hakkennes, Sharon; Hill, Keith D; Brock, Kim; Bernhardt, Julie; Churilov, Leonid

2013-01-01

This study aimed to identify factors that assessors considered important in decision-making regarding suitability for inpatient rehabilitation after acute severe stroke. Multi-site prospective observational cohort study. Consecutive acute, severe stroke patients and their assessors for inpatient rehabilitation. Rehabilitation assessors completed a questionnaire, rating the importance (10 point visual analogue scale) and direction (positive, negative or neutral) of 15 patient related and 2 organisational items potentially affecting their decision regarding patients' acceptance to rehabilitation. Of the 75 patients referred to rehabilitation and included in this study 61 (81.3%) were accepted for inpatient rehabilitation. The items considered to be most important in the decision to accept the patient for rehabilitation were pre-morbid cognition, pre-morbid mobility and pre-morbid communication. For those not accepted the most important items were current mobility, social support and current cognition. Factor analysis revealed 3 underlying factors, interpreted as post-stroke status, pre-morbid status, and social attributes, accounting for 61.8% of the total variance. All were independently associated with acceptance for rehabilitation (p < 0.05). This study highlights the importance of pre-morbid function and social factors in addition to post-stroke function in the decision making process for acceptance to rehabilitation following severe stroke. Future models for selection for rehabilitation should consider inclusion of these factors.

Distributed Cooperation Solution Method of Complex System Based on MAS

NASA Astrophysics Data System (ADS)

Weijin, Jiang; Yuhui, Xu

To adapt the model in reconfiguring fault diagnosing to dynamic environment and the needs of solving the tasks of complex system fully, the paper introduced multi-Agent and related technology to the complicated fault diagnosis, an integrated intelligent control system is studied in this paper. Based on the thought of the structure of diagnostic decision and hierarchy in modeling, based on multi-layer decomposition strategy of diagnosis task, a multi-agent synchronous diagnosis federation integrated different knowledge expression modes and inference mechanisms are presented, the functions of management agent, diagnosis agent and decision agent are analyzed, the organization and evolution of agents in the system are proposed, and the corresponding conflict resolution algorithm in given, Layered structure of abstract agent with public attributes is build. System architecture is realized based on MAS distributed layered blackboard. The real world application shows that the proposed control structure successfully solves the fault diagnose problem of the complex plant, and the special advantage in the distributed domain.

LinkedOmics: analyzing multi-omics data within and across 32 cancer types.

PubMed

Vasaikar, Suhas V; Straub, Peter; Wang, Jing; Zhang, Bing

2018-01-04

The LinkedOmics database contains multi-omics data and clinical data for 32 cancer types and a total of 11 158 patients from The Cancer Genome Atlas (TCGA) project. It is also the first multi-omics database that integrates mass spectrometry (MS)-based global proteomics data generated by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) on selected TCGA tumor samples. In total, LinkedOmics has more than a billion data points. To allow comprehensive analysis of these data, we developed three analysis modules in the LinkedOmics web application. The LinkFinder module allows flexible exploration of associations between a molecular or clinical attribute of interest and all other attributes, providing the opportunity to analyze and visualize associations between billions of attribute pairs for each cancer cohort. The LinkCompare module enables easy comparison of the associations identified by LinkFinder, which is particularly useful in multi-omics and pan-cancer analyses. The LinkInterpreter module transforms identified associations into biological understanding through pathway and network analysis. Using five case studies, we demonstrate that LinkedOmics provides a unique platform for biologists and clinicians to access, analyze and compare cancer multi-omics data within and across tumor types. LinkedOmics is freely available at http://www.linkedomics.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Decision Support Framework For Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

EPA Science Inventory

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...

The Relationship of Decision-Making Styles and Attributional Styles in Addicted and Non-addicted Men.

PubMed

Shaghaghy, Farhad; Saffarinia, Majid; Iranpoor, Mohadeseh; Soltanynejad, Ali

2011-01-01

One of social problems which has affected our society and resulted in problems for different groups of people is drug abuse. This issue indicates a serious psychological, physical and social problem in community. Social skills have positive and successful influences in prevention of substance abuse. This includes the ability to explain events correctly and then appropriate decision making. This study compares decision making styles and attributional styles between addicted and non addicted men to recognize their role in addiction. In this study, 200 addicted and non addicted men were randomly selected. Decision-making style and attributional style questionnaires were used. Data analysis was performed by independent Student's t and Pearson correlation tests. The study population included 81 addicted and 90 non-addicted men. Addicted and non addicted men were significantly different in rational decision-making style (P < 0.05). Negative relationship was found between rational decision making and optimistic attribution style (r = -0.305, P < 0.01) and direct relationship was found between rational decision making and learned helplessness (r = 0.309, P < 0.01). Our study showed that addicts are less rational in decision making and addicts that developed learned helplessness were less rational and did not have optimistic attribution style. These issues show that addiction institutions and therapists have to pay attention to cognitive factors for addiction prevention.

Responding to Vaccine Safety Signals during Pandemic Influenza: A Modeling Study

PubMed Central

Maro, Judith C.; Fryback, Dennis G.; Lieu, Tracy A.; Lee, Grace M.; Martin, David B.

2014-01-01

Background Managing emerging vaccine safety signals during an influenza pandemic is challenging. Federal regulators must balance vaccine risks against benefits while maintaining public confidence in the public health system. Methods We developed a multi-criteria decision analysis model to explore regulatory decision-making in the context of emerging vaccine safety signals during a pandemic. We simulated vaccine safety surveillance system capabilities and used an age-structured compartmental model to develop potential pandemic scenarios. We used an expert-derived multi-attribute utility function to evaluate potential regulatory responses by combining four outcome measures into a single measure of interest: 1) expected vaccination benefit from averted influenza; 2) expected vaccination risk from vaccine-associated febrile seizures; 3) expected vaccination risk from vaccine-associated Guillain-Barre Syndrome; and 4) expected change in vaccine-seeking behavior in future influenza seasons. Results Over multiple scenarios, risk communication, with or without suspension of vaccination of high-risk persons, were the consistently preferred regulatory responses over no action or general suspension when safety signals were detected during a pandemic influenza. On average, the expert panel valued near-term vaccine-related outcomes relative to long-term projected outcomes by 3∶1. However, when decision-makers had minimal ability to influence near-term outcomes, the response was selected primarily by projected impacts on future vaccine-seeking behavior. Conclusions The selected regulatory response depends on how quickly a vaccine safety signal is identified relative to the peak of the pandemic and the initiation of vaccination. Our analysis suggested two areas for future investment: efforts to improve the size and timeliness of the surveillance system and behavioral research to understand changes in vaccine-seeking behavior. PMID:25536228

Choices, choices: the application of multi-criteria decision analysis to a food safety decision-making problem.

PubMed

Fazil, A; Rajic, A; Sanchez, J; McEwen, S

2008-11-01

In the food safety arena, the decision-making process can be especially difficult. Decision makers are often faced with social and fiscal pressures when attempting to identify an appropriate balance among several choices. Concurrently, policy and decision makers in microbial food safety are under increasing pressure to demonstrate that their policies and decisions are made using transparent and accountable processes. In this article, we present a multi-criteria decision analysis approach that can be used to address the problem of trying to select a food safety intervention while balancing various criteria. Criteria that are important when selecting an intervention were determined, as a result of an expert consultation, to include effectiveness, cost, weight of evidence, and practicality associated with the interventions. The multi-criteria decision analysis approach we present is able to consider these criteria and arrive at a ranking of interventions. It can also provide a clear justification for the ranking as well as demonstrate to stakeholders, through a scenario analysis approach, how to potentially converge toward common ground. While this article focuses on the problem of selecting food safety interventions, the range of applications in the food safety arena is truly diverse and can be a significant tool in assisting decisions that need to be coherent, transparent, and justifiable. Most importantly, it is a significant contributor when there is a need to strike a fine balance between various potentially competing alternatives and/or stakeholder groups.

Describing three-class task performance: three-class linear discriminant analysis and three-class ROC analysis

NASA Astrophysics Data System (ADS)

He, Xin; Frey, Eric C.

2007-03-01

Binary ROC analysis has solid decision-theoretic foundations and a close relationship to linear discriminant analysis (LDA). In particular, for the case of Gaussian equal covariance input data, the area under the ROC curve (AUC) value has a direct relationship to the Hotelling trace. Many attempts have been made to extend binary classification methods to multi-class. For example, Fukunaga extended binary LDA to obtain multi-class LDA, which uses the multi-class Hotelling trace as a figure-of-merit, and we have previously developed a three-class ROC analysis method. This work explores the relationship between conventional multi-class LDA and three-class ROC analysis. First, we developed a linear observer, the three-class Hotelling observer (3-HO). For Gaussian equal covariance data, the 3- HO provides equivalent performance to the three-class ideal observer and, under less strict conditions, maximizes the signal to noise ratio for classification of all pairs of the three classes simultaneously. The 3-HO templates are not the eigenvectors obtained from multi-class LDA. Second, we show that the three-class Hotelling trace, which is the figureof- merit in the conventional three-class extension of LDA, has significant limitations. Third, we demonstrate that, under certain conditions, there is a linear relationship between the eigenvectors obtained from multi-class LDA and 3-HO templates. We conclude that the 3-HO based on decision theory has advantages both in its decision theoretic background and in the usefulness of its figure-of-merit. Additionally, there exists the possibility of interpreting the two linear features extracted by the conventional extension of LDA from a decision theoretic point of view.

Building a maintenance policy through a multi-criterion decision-making model

NASA Astrophysics Data System (ADS)

Faghihinia, Elahe; Mollaverdi, Naser

2012-08-01

A major competitive advantage of production and service systems is establishing a proper maintenance policy. Therefore, maintenance managers should make maintenance decisions that best fit their systems. Multi-criterion decision-making methods can take into account a number of aspects associated with the competitiveness factors of a system. This paper presents a multi-criterion decision-aided maintenance model with three criteria that have more influence on decision making: reliability, maintenance cost, and maintenance downtime. The Bayesian approach has been applied to confront maintenance failure data shortage. Therefore, the model seeks to make the best compromise between these three criteria and establish replacement intervals using Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II), integrating the Bayesian approach with regard to the preference of the decision maker to the problem. Finally, using a numerical application, the model has been illustrated, and for a visual realization and an illustrative sensitivity analysis, PROMETHEE GAIA (the visual interactive module) has been used. Use of PROMETHEE II and PROMETHEE GAIA has been made with Decision Lab software. A sensitivity analysis has been made to verify the robustness of certain parameters of the model.

Take-the-best and the influence of decision-inconsistent attributes on decision confidence and choices in memory-based decisions.

PubMed

Dummel, Sebastian; Rummel, Jan

2016-11-01

Take-the-best (TTB) is a decision strategy according to which attributes about choice options are sequentially processed in descending order of validity, and attribute processing is stopped once an attribute discriminates between options. Consequently, TTB-decisions rely on only one, the best discriminating, attribute, and lower-valid attributes need not be processed because they are TTB-irrelevant. Recent research suggests, however, that when attribute information is visually present during decision-making, TTB-irrelevant attributes are processed and integrated into decisions nonetheless. To examine whether TTB-irrelevant attributes are retrieved and integrated when decisions are made memory-based, we tested whether the consistency of a TTB-irrelevant attribute affects TTB-users' decision behaviour in a memory-based decision task. Participants first learned attribute configurations of several options. Afterwards, they made several decisions between two of the options, and we manipulated conflict between the second-best attribute and the TTB-decision. We assessed participants' decision confidence and the proportion of TTB-inconsistent choices. According to TTB, TTB-irrelevant attributes should not affect confidence and choices, because these attributes should not be retrieved. Results showed, however, that TTB-users were less confident and made more TTB-inconsistent choices when TTB-irrelevant information was in conflict with the TTB-decision than when it was not, suggesting that TTB-users retrieved and integrated TTB-irrelevant information.

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale

PubMed Central

Diao, Yuzhu; Hu, Aqin

2018-01-01

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation. PMID:29498699

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale.

PubMed

Li, Qingsheng; Diao, Yuzhu; Gong, Zaiwu; Hu, Aqin

2018-03-02

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation.

Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

NASA Astrophysics Data System (ADS)

Chu, J.; Zhang, C.; Fu, G.; Li, Y.; Zhou, H.

2015-08-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.

Improving multi-objective reservoir operation optimization with sensitivity-informed problem decomposition

NASA Astrophysics Data System (ADS)

Chu, J. G.; Zhang, C.; Fu, G. T.; Li, Y.; Zhou, H. C.

2015-04-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce the computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed problem decomposition dramatically reduces the computational demands required for attaining high quality approximations of optimal tradeoff relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed problem decomposition and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform problem decomposition when solving the complex multi-objective reservoir operation problems.

How to use multi-criteria decision analysis methods for reimbursement decision-making in healthcare: a step-by-step guide.

PubMed

Diaby, Vakaramoko; Goeree, Ron

2014-02-01

In recent years, the quest for more comprehensiveness, structure and transparency in reimbursement decision-making in healthcare has prompted the research into alternative decision-making frameworks. In this environment, multi-criteria decision analysis (MCDA) is arising as a valuable tool to support healthcare decision-making. In this paper, we present the main MCDA decision support methods (elementary methods, value-based measurement models, goal programming models and outranking models) using a case study approach. For each family of methods, an example of how an MCDA model would operate in a real decision-making context is presented from a critical perspective, highlighting the parameters setting, the selection of the appropriate evaluation model as well as the role of sensitivity and robustness analyses. This study aims to provide a step-by-step guide on how to use MCDA methods for reimbursement decision-making in healthcare.

'spup' - an R package for uncertainty propagation analysis in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2017-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability and being able to deal with case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

Decision aids for multiple-decision disease management as affected by weather input errors.

PubMed

Pfender, W F; Gent, D H; Mahaffee, W F; Coop, L B; Fox, A D

2011-06-01

Many disease management decision support systems (DSSs) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation, or estimation from off-site sources, may affect model calculations and management decision recommendations. The extent to which errors in weather inputs affect the quality of the final management outcome depends on a number of aspects of the disease management context, including whether management consists of a single dichotomous decision, or of a multi-decision process extending over the cropping season(s). Decision aids for multi-decision disease management typically are based on simple or complex algorithms of weather data which may be accumulated over several days or weeks. It is difficult to quantify accuracy of multi-decision DSSs due to temporally overlapping disease events, existence of more than one solution to optimizing the outcome, opportunities to take later recourse to modify earlier decisions, and the ongoing, complex decision process in which the DSS is only one component. One approach to assessing importance of weather input errors is to conduct an error analysis in which the DSS outcome from high-quality weather data is compared with that from weather data with various levels of bias and/or variance from the original data. We illustrate this analytical approach for two types of DSS, an infection risk index for hop powdery mildew and a simulation model for grass stem rust. Further exploration of analysis methods is needed to address problems associated with assessing uncertainty in multi-decision DSSs.

Visual analytics techniques for large multi-attribute time series data

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel A.

2008-01-01

Time series data commonly occur when variables are monitored over time. Many real-world applications involve the comparison of long time series across multiple variables (multi-attributes). Often business people want to compare this year's monthly sales with last year's sales to make decisions. Data warehouse administrators (DBAs) want to know their daily data loading job performance. DBAs need to detect the outliers early enough to act upon them. In this paper, two new visual analytic techniques are introduced: The color cell-based Visual Time Series Line Charts and Maps highlight significant changes over time in a long time series data and the new Visual Content Query facilitates finding the contents and histories of interesting patterns and anomalies, which leads to root cause identification. We have applied both methods to two real-world applications to mine enterprise data warehouse and customer credit card fraud data to illustrate the wide applicability and usefulness of these techniques.

Integrated optimisation technique based on computer-aided capacity and safety evaluation for managing downstream lane-drop merging area of signalised junctions

NASA Astrophysics Data System (ADS)

Chen, CHAI; Yiik Diew, WONG

2017-02-01

This study provides an integrated strategy, encompassing microscopic simulation, safety assessment, and multi-attribute decision-making, to optimize traffic performance at downstream merging area of signalized intersections. A Fuzzy Cellular Automata (FCA) model is developed to replicate microscopic movement and merging behavior. Based on simulation experiment, the proposed FCA approach is able to provide capacity and safety evaluation of different traffic scenarios. The results are then evaluated through data envelopment analysis (DEA) and analytic hierarchy process (AHP). Optimized geometric layout and control strategies are then suggested for various traffic conditions. An optimal lane-drop distance that is dependent on traffic volume and speed limit can thus be established at the downstream merging area.

Delineating chalk sand distribution of Ekofisk formation using probabilistic neural network (PNN) and stepwise regression (SWR): Case study Danish North Sea field

NASA Astrophysics Data System (ADS)

Haris, A.; Nafian, M.; Riyanto, A.

2017-07-01

Danish North Sea Fields consist of several formations (Ekofisk, Tor, and Cromer Knoll) that was started from the age of Paleocene to Miocene. In this study, the integration of seismic and well log data set is carried out to determine the chalk sand distribution in the Danish North Sea field. The integration of seismic and well log data set is performed by using the seismic inversion analysis and seismic multi-attribute. The seismic inversion algorithm, which is used to derive acoustic impedance (AI), is model-based technique. The derived AI is then used as external attributes for the input of multi-attribute analysis. Moreover, the multi-attribute analysis is used to generate the linear and non-linear transformation of among well log properties. In the case of the linear model, selected transformation is conducted by weighting step-wise linear regression (SWR), while for the non-linear model is performed by using probabilistic neural networks (PNN). The estimated porosity, which is resulted by PNN shows better suited to the well log data compared with the results of SWR. This result can be understood since PNN perform non-linear regression so that the relationship between the attribute data and predicted log data can be optimized. The distribution of chalk sand has been successfully identified and characterized by porosity value ranging from 23% up to 30%.

The Voice of the Patient Methodology: A Novel Mixed-Methods Approach to Identifying Treatment Goals for Men with Prostate Cancer.

PubMed

Saigal, Christopher S; Lambrechts, Sylvia I; Seenu Srinivasan, V; Dahan, Ely

2017-06-01

Many guidelines advocate the use of shared decision making for men with newly diagnosed prostate cancer. Decision aids can facilitate the process of shared decision making. Implicit in this approach is the idea that physicians understand which elements of treatment matter to patients. Little formal work exists to guide physicians or developers of decision aids in identifying these attributes. We use a mixed-methods technique adapted from marketing science, the 'Voice of the Patient', to describe and identify treatment elements of value for men with localized prostate cancer. We conducted semi-structured interviews with 30 men treated for prostate cancer in the urology clinic of the West Los Angeles Veteran Affairs Medical Center. We used a qualitative analysis to generate themes in patient narratives, and a quantitative approach, agglomerative hierarchical clustering, to identify attributes of treatment that were most relevant to patients making decisions about prostate cancer. We identified five 'traditional' prostate cancer treatment attributes: sexual dysfunction, bowel problems, urinary problems, lifespan, and others' opinions. We further identified two novel treatment attributes: a treatment's ability to validate a sense of proactivity and the need for an incision (separate from risks of surgery). Application of a successful marketing technique, the 'Voice of the Customer', in a clinical setting elicits non-obvious attributes that highlight unique patient decision-making concerns. Use of this method in the development of decision aids may result in more effective decision support.

A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty

NASA Astrophysics Data System (ADS)

Madani, Kaveh; Lund, Jay R.

2011-05-01

Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.

Critical care nurses' decision making: sedation assessment and management in intensive care.

PubMed

Aitken, Leanne M; Marshall, Andrea P; Elliott, Rosalind; McKinley, Sharon

2009-01-01

This study was designed to examine the decision making processes that nurses use when assessing and managing sedation for a critically ill patient, specifically the attributes and concepts used to determine sedation needs and the influence of a sedation guideline on the decision making processes. Sedation management forms an integral component of the care of critical care patients. Despite this, there is little understanding of how nurses make decisions regarding assessment and management of intensive care patients' sedation requirements. Appropriate nursing assessment and management of sedation therapy is essential to quality patient care. Observational study. Nurses providing sedation management for a critically ill patient were observed and asked to think aloud during two separate occasions for two hours of care. Follow-up interviews were conducted to collect data from five expert critical care nurses pre- and postimplementation of a sedation guideline. Data from all sources were integrated, with data analysis identifying the type and number of attributes and concepts used to form decisions. Attributes and concepts most frequently used related to sedation and sedatives, anxiety and agitation, pain and comfort and neurological status. On average each participant raised 48 attributes related to sedation assessment and management in the preintervention phase and 57 attributes postintervention. These attributes related to assessment (pre, 58%; post, 65%), physiology (pre, 10%; post, 9%) and treatment (pre, 31%; post, 26%) aspects of care. Decision making in this setting is highly complex, incorporating a wide range of attributes that concentrate primarily on assessment aspects of care. Clinical guidelines should provide support for strategies known to positively influence practice. Further, the education of nurses to use such guidelines optimally must take into account the highly complex iterative process and wide range of data sources used to make decisions.

Patients’ Non-Medical Characteristics Contribute to Collective Medical Decision-Making at Multidisciplinary Oncological Team Meetings

PubMed Central

Restivo, Léa; Apostolidis, Thémis; Bouhnik, Anne-Déborah; Garciaz, Sylvain; Aurran, Thérèse; Julian-Reynier, Claire

2016-01-01

Background The contribution of patients’ non-medical characteristics to individual physicians’ decision-making has attracted considerable attention, but little information is available on this topic in the context of collective decision-making. Medical decision-making at cancer centres is currently carried out using a collective approach, at MultiDisciplinary Team (MDT) meetings. The aim of this study was to determine how patients’ non-medical characteristics are presented at MDT meetings and how this information may affect the team’s final medical decisions. Design Observations were conducted at a French Cancer Centre during MDT meetings at which non-standard cases involving some uncertainty were discussed from March to May 2014. Physicians’ verbal statements and predefined contextual parameters were collected with a non-participant observational approach. Non numerical data collected in the form of open notes were then coded for quantitative analysis. Univariate and multivariate statistical analyses were performed. Results In the final sample of patients’ records included and discussed (N = 290), non-medical characteristics were mentioned in 32.8% (n = 95) of the cases. These characteristics corresponded to demographics in 22.8% (n = 66) of the cases, psychological data in 11.7% (n = 34), and relational data in 6.2% (n = 18). The patient’s age and his/her “likeability” were the most frequently mentioned characteristics. In 17.9% of the cases discussed, the final decision was deferred: this outcome was positively associated with the patients’ non-medical characteristics and with uncertainty about the outcome of the therapeutic options available. Limitations The design of the study made it difficult to draw definite cause-and-effect conclusions. Conclusion The Social Representations approach suggests that patients’ non-medical characteristics constitute a kind of tacit professional knowledge that may be frequently mobilised in physicians’ everyday professional practice. The links observed between patients’ attributes and the medical decisions made at these meetings show that these attributes should be taken into account in order to understand how medical decisions are reached in difficult situations of this kind. PMID:27167521

An Evidence Framework for Off-Patent Pharmaceutical Review (EFOR) for Health Technology Assessment in Emerging Markets.

PubMed

Brixner, Diana; Kaló, Zoltán; Maniadakis, Nikos; Kim, Kyoo; Wijaya, Kalman

2018-03-29

This article introduces an Evidence Framework for Off-Patent Pharmaceutical Review (EFOR), which establishes value-based criteria in a template that manufacturers use to provide evidence showing how their products meet those criteria. Health authorities in emerging markets can then use the evidence presented in the EFOR to evaluate off-patent pharmaceuticals (OPPs) in a consistent, transparent, and evidence-based manner to support policy decisions, including pricing, reimbursement, formulary listing, and drug procurement. A literature search found no multi-criteria evidence framework for evaluating OPPs in emerging markets. An International Outcomes Research Board (IORB) of academia and industry experts conducted extensive research, meetings, and workshops to define high-priority criteria to incorporate into an evidence-based health technology assessment (HTA) tool using the multi-criteria decision analysis (MCDA) technique. The resulting framework was further tailored for country-specific needs in workshops in three emerging countries (Kazakhstan, Vietnam, and Indonesia). The IORB defined nine criteria four categories (Product, Manufacturing, Service, and Value Assessment), which OPP manufacturers can use to provide evidence for reimbursement and health policy decision making. Then the IORB developed the EFOR as a base case document, which can be adapted and used as a template by health authorities in emerging countries. Emerging countries have a significant need for an HTA tool that balances affordability with accurate evidence showing the value differentiation of OPPs. The value attributes in this setting often are different from those in developed markets, which emphasize new products and have high regulation and manufacturing standards. The EFOR is an easy-to-use, adaptable framework that emerging countries can use to increase the consistency, transparency, and effectiveness of drug decision making. The open source EFOR is available as Supplemental Materials. Copyright © 2018. Published by Elsevier Inc.

Research on the influence of parking charging strategy based on multi-level extension theory of group decision making

NASA Astrophysics Data System (ADS)

Cheng, Fen; Hu, Wanxin

2017-05-01

Based on analysis of the impact of the experience of parking policy at home and abroad, design the impact analysis process of parking strategy. First, using group decision theory to create a parking strategy index system and calculate its weight. Index system includes government, parking operators and travelers. Then, use a multi-level extension theory to analyze the CBD parking strategy. Assess the parking strategy by calculating the correlation of each indicator. Finally, assess the strategy of parking charges through a case. Provide a scientific and reasonable basis for assessing parking strategy. The results showed that the model can effectively analyze multi-target, multi-property parking policy evaluation.

Preferences for Training Options: A Conjoint Analysis

ERIC Educational Resources Information Center

Gan, Chui Goh; Lee, Julie Anne; Soutar, Geoffrey N.

2009-01-01

Singapore is a growing educational hub for the Asia Pacific region. However, no prior research has examined how Singaporean managers trade off attributes of training programs when making executive training decisions. The current study used conjoint analysis to identify the most important attributes of training programs as word of mouth, trainers'…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rowe, M.D.; Pierce, B.L.

This report presents results of tests of different final site selection methods used for siting large-scale facilities such as nuclear power plants. Test data are adapted from a nuclear power plant siting study conducted on Long Island, New York. The purpose of the tests is to determine whether or not different final site selection methods produce different results, and to obtain some understanding of the nature of any differences found. Decision rules and weighting methods are included. Decision rules tested are Weighting Summation, Power Law, Decision Analysis, Goal Programming, and Goal Attainment; weighting methods tested are Categorization, Ranking, Rating Ratiomore » Estimation, Metfessel Allocation, Indifferent Tradeoff, Decision Analysis lottery, and Global Evaluation. Results show that different methods can, indeed, produce different results, but that the probability that they will do so is controlled by the structure of differences among the sites being evaluated. Differences in weights and suitability scores attributable to methods have reduced significance if the alternatives include one or two sites that are superior to all others in many attributes. The more tradeoffs there are among good and bad levels of different attributes at different sites, the more important are the specifics of methods to the final decision. 5 refs., 14 figs., 19 tabs.« less

m2-ABKS: Attribute-Based Multi-Keyword Search over Encrypted Personal Health Records in Multi-Owner Setting.

PubMed

Miao, Yinbin; Ma, Jianfeng; Liu, Ximeng; Wei, Fushan; Liu, Zhiquan; Wang, Xu An

2016-11-01

Online personal health record (PHR) is more inclined to shift data storage and search operations to cloud server so as to enjoy the elastic resources and lessen computational burden in cloud storage. As multiple patients' data is always stored in the cloud server simultaneously, it is a challenge to guarantee the confidentiality of PHR data and allow data users to search encrypted data in an efficient and privacy-preserving way. To this end, we design a secure cryptographic primitive called as attribute-based multi-keyword search over encrypted personal health records in multi-owner setting to support both fine-grained access control and multi-keyword search via Ciphertext-Policy Attribute-Based Encryption. Formal security analysis proves our scheme is selectively secure against chosen-keyword attack. As a further contribution, we conduct empirical experiments over real-world dataset to show its feasibility and practicality in a broad range of actual scenarios without incurring additional computational burden.

Dual conception of risk in the Iowa Gambling Task: effects of sleep deprivation and test-retest gap.

PubMed

Singh, Varsha

2013-01-01

Risk in the Iowa Gambling Task (IGT) is often understood in terms of intertemporal choices, i.e., preference for immediate outcomes in favor of delayed outcomes is considered risky decision making. According to behavioral economics, healthy decision makers are expected to refrain from choosing the short-sighted immediate gain because, over time (10 trials of the IGT), the immediate gains result in a long term loss (net loss). Instead decision makers are expected to maximize their gains by choosing options that, over time (10 trials), result in delayed or long term gains (net gain). However, task choices are sometimes made on the basis of the frequency of reward and punishment such that frequent rewards/infrequent punishments are favored over infrequent rewards/frequent punishments. The presence of these two attributes (intertemporality and frequency of reward) in IGT decision making may correspond to the emotion-cognition dichotomy and reflect a dual conception of risk. Decision making on the basis of the two attributes was tested under two conditions: delay in retest and sleep deprivation. An interaction between sleep deprivation and time delay was expected to attenuate the difference between the two attributes. Participants were 40 male university students. Analysis of the effects of IGT attribute type (intertemporal vs. frequency of reinforcement), sleep deprivation (sleep deprivation vs. no sleep deprivation), and test-retest gap (short vs. long delay) showed a significant within-subjects effect of IGT attribute type thus confirming the difference between the two attributes. Sleep deprivation had no effect on the attributes, but test-retest gap and the three-way interaction between attribute type, test-retest gap, and sleep deprivation were significantly different. Post-hoc tests revealed that sleep deprivation and short test-retest gap attenuated the difference between the two attributes. Furthermore, the results showed an expected trend of increase in intertemporal decision making at retest suggesting that intertemporal decision making benefited from repeated task exposure. The present findings add to understanding of the emotion-cognition dichotomy. Further, they show an important time-dependent effect of a universally experienced constraint (sleep deprivation) on decision making. It is concluded that risky decision making in the IGT is contingent on the attribute under consideration and is affected by factors such as time elapsed and constraint experienced before the retest.

Based on a multi-agent system for multi-scale simulation and application of household's LUCC: a case study for Mengcha village, Mizhi county, Shaanxi province.

PubMed

Chen, Hai; Liang, Xiaoying; Li, Rui

2013-01-01

Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the quantitative method and model, especially the scenario analysis model which may reflect the interaction among different household types.

A Three Stage Multi-attribute Procurement Auction: A Proposal for Department of Defense (DoD) Vendor Selection Decisions.

DTIC Science & Technology

2010-04-30

regarding production capabilities and costs, but must somehow form beliefs about the likelihood of a bid being accepted. We facilitate formulation...which both vendors believe the buyer places equal weight on the two attributes, but the vendors differ in their capabilities of producing those...exchange—the future of B2B . Harvard Business Review, 78(6), 86-96. = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= 444= k^s^i

Bayesian outcome-based strategy classification.

PubMed

Lee, Michael D

2016-03-01

Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014) recently developed a method for making inferences about the decision processes people use in multi-attribute forced choice tasks. Their paper makes a number of worthwhile theoretical and methodological contributions. Theoretically, they provide an insightful psychological motivation for a probabilistic extension of the widely-used "weighted additive" (WADD) model, and show how this model, as well as other important models like "take-the-best" (TTB), can and should be expressed in terms of meaningful priors. Methodologically, they develop an inference approach based on the Minimum Description Length (MDL) principles that balances both the goodness-of-fit and complexity of the decision models they consider. This paper aims to preserve these useful contributions, but provide a complementary Bayesian approach with some theoretical and methodological advantages. We develop a simple graphical model, implemented in JAGS, that allows for fully Bayesian inferences about which models people use to make decisions. To demonstrate the Bayesian approach, we apply it to the models and data considered by Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014), showing how a prior predictive analysis of the models, and posterior inferences about which models people use and the parameter settings at which they use them, can contribute to our understanding of human decision making.

Preferences of colorectal cancer patients for treatment and decision-making: a systematic literature review.

PubMed

Damm, K; Vogel, A; Prenzler, A

2014-11-01

Treatment decisions in life-threatening diseases, like colorectal cancer (CRC), are crucial, since they have a great impact on patient's survival and health-related quality of life. Thereby, the inclusion of patient's preferences becomes more and more important; however, these first need to be identified. Therefore, we conducted a systematic literature review in 12 electronic databases, published between 2000 and 2012, in order to identify patient's preferences concerning treatment preferences and involvement in the decision-making process. Nineteen studies were included and thoroughly analysed. This review shows that CRC patients do have preferences regarding different treatment options and outcomes; however, these preferences are not homogenous and seem to depend on personal factors like age and gender. Despite the existence of these preferences, the majority of patients prefer a passive role in the decision-making process, which in part may be explained by the severity of the disease. Again, subgroup analyses reveal the impact of personal factors like gender and education on the preference. Due to the importance of personal factors in the analysis of patient preferences, we identified an urgent need for larger studies that are suitable for subgroup analyses and incorporate multi-attributive measurement techniques, like discrete choice methods. © 2014 John Wiley & Sons Ltd.

Global Educators' Personal Attribution of a Global Perspective

ERIC Educational Resources Information Center

Carano, Kenneth Thomas

2013-01-01

This case study of self-identifying global educators investigated factors that they attributed to the development of their global perspective and how it influenced curricular decision-making. Analysis resulted in seven themes identified by the participants as having attributed to the development of a global perspective: (a) family, (b) exposure to…

A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.

PubMed

Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe

2011-05-30

Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

Geographic Profiling: Knowledge Through Prediction

DTIC Science & Technology

2014-06-01

FTO Foreign Terrorist Organization GIS geographic information systems LE lawless elements MADM multi-attribute decision making MILF Moro Islamic...or her life. Anchor points can include the offender’s home , his or her workplace, a home of a friend of the offender, or even a bar or restaurant...more generally for the improvement of police patrols. In Memphis, TN, city officials have seen a decrease in crime with the help of operation Blue

Using multicriteria decision analysis during drug development to predict reimbursement decisions.

PubMed

Williams, Paul; Mauskopf, Josephine; Lebiecki, Jake; Kilburg, Anne

2014-01-01

Pharmaceutical companies design clinical development programs to generate the data that they believe will support reimbursement for the experimental compound. The objective of the study was to present a process for using multicriteria decision analysis (MCDA) by a pharmaceutical company to estimate the probability of a positive recommendation for reimbursement for a new drug given drug and environmental attributes. The MCDA process included 1) selection of decisions makers who were representative of those making reimbursement decisions in a specific country; 2) two pre-workshop questionnaires to identify the most important attributes and their relative importance for a positive recommendation for a new drug; 3) a 1-day workshop during which participants undertook three tasks: i) they agreed on a final list of decision attributes and their importance weights, ii) they developed level descriptions for these attributes and mapped each attribute level to a value function, and iii) they developed profiles for hypothetical products 'just likely to be reimbursed'; and 4) use of the data from the workshop to develop a prediction algorithm based on a logistic regression analysis. The MCDA process is illustrated using case studies for three countries, the United Kingdom, Germany, and Spain. The extent to which the prediction algorithms for each country captured the decision processes for the workshop participants in our case studies was tested using a post-meeting questionnaire that asked the participants to make recommendations for a set of hypothetical products. The data collected in the case study workshops resulted in a prediction algorithm: 1) for the United Kingdom, the probability of a positive recommendation for different ranges of cost-effectiveness ratios; 2) for Spain, the probability of a positive recommendation at the national and regional levels; and 3) for Germany, the probability of a determination of clinical benefit. The results from the post-meeting questionnaire revealed a high predictive value for the algorithm developed using MCDA. Prediction algorithms developed using MCDA could be used by pharmaceutical companies when designing their clinical development programs to estimate the likelihood of a favourable reimbursement recommendation for different product profiles and for different positions in the treatment pathway.

Using multicriteria decision analysis during drug development to predict reimbursement decisions

PubMed Central

Williams, Paul; Mauskopf, Josephine; Lebiecki, Jake; Kilburg, Anne

2014-01-01

Background Pharmaceutical companies design clinical development programs to generate the data that they believe will support reimbursement for the experimental compound. Objective The objective of the study was to present a process for using multicriteria decision analysis (MCDA) by a pharmaceutical company to estimate the probability of a positive recommendation for reimbursement for a new drug given drug and environmental attributes. Methods The MCDA process included 1) selection of decisions makers who were representative of those making reimbursement decisions in a specific country; 2) two pre-workshop questionnaires to identify the most important attributes and their relative importance for a positive recommendation for a new drug; 3) a 1-day workshop during which participants undertook three tasks: i) they agreed on a final list of decision attributes and their importance weights, ii) they developed level descriptions for these attributes and mapped each attribute level to a value function, and iii) they developed profiles for hypothetical products ‘just likely to be reimbursed’; and 4) use of the data from the workshop to develop a prediction algorithm based on a logistic regression analysis. The MCDA process is illustrated using case studies for three countries, the United Kingdom, Germany, and Spain. The extent to which the prediction algorithms for each country captured the decision processes for the workshop participants in our case studies was tested using a post-meeting questionnaire that asked the participants to make recommendations for a set of hypothetical products. Results The data collected in the case study workshops resulted in a prediction algorithm: 1) for the United Kingdom, the probability of a positive recommendation for different ranges of cost-effectiveness ratios; 2) for Spain, the probability of a positive recommendation at the national and regional levels; and 3) for Germany, the probability of a determination of clinical benefit. The results from the post-meeting questionnaire revealed a high predictive value for the algorithm developed using MCDA. Conclusions Prediction algorithms developed using MCDA could be used by pharmaceutical companies when designing their clinical development programs to estimate the likelihood of a favourable reimbursement recommendation for different product profiles and for different positions in the treatment pathway.

Supporting multi-stakeholder environmental decisions.

PubMed

Hajkowicz, Stefan A

2008-09-01

This paper examines how multiple criteria analysis (MCA) can be used to support multi-stakeholder environmental management decisions. It presents a study through which 48 stakeholders from environmental, primary production and community interest groups used MCA to prioritise 30 environmental management problems in the Mackay-Whitsunday region of Queensland, Australia. The MCA model, with procedures for aggregating multi-stakeholder output, was used to inform a final decision on the priority of the region's environmental management problems. The result was used in the region's environmental management plan as required under Australia's Natural Heritage Trust programme. The study shows how relatively simple MCA methods can help stakeholders make group decisions, even when they hold strongly conflicting preferences.

Multi-criteria decision analysis for health technology assessment in Canada: insights from an expert panel discussion.

PubMed

Diaby, Vakaramoko; Goeree, Ron; Hoch, Jeffrey; Siebert, Uwe

2015-02-01

Multi-criteria decision analysis (MCDA), a decision-making tool, has received increasing attention in recent years, notably in the healthcare field. For Canada, it is unclear whether and how MCDA should be incorporated into the existing health technology assessment (HTA) decision-making process. To facilitate debate on improving HTA decision-making in Canada, a workshop was held in conjunction with the 8th World Congress on Health Economics of the International Health Economics Association in Toronto, Canada in July 2011. The objective of the workshop was to discuss the potential benefits and challenges related to the use of MCDA for HTA decision-making in Canada. This paper summarizes and discusses the recommendations of an expert panel convened at the workshop to discuss opportunities and concerns with reference to the implementation of MCDA in Canada.

ANFIS multi criteria decision making for overseas construction projects: a methodology

NASA Astrophysics Data System (ADS)

Utama, W. P.; Chan, A. P. C.; Zulherman; Zahoor, H.; Gao, R.; Jumas, D. Y.

2018-02-01

A critical part when a company targeting a foreign market is how to make a better decision in connection with potential project selection. Since different attributes of information are often incomplete, imprecise and ill-defined in overseas projects selection, the process of decision making by relying on the experiences and intuition is a risky attitude. This paper aims to demonstrate a decision support method in deciding overseas construction projects (OCPs). An Adaptive Neuro-Fuzzy Inference System (ANFIS), the amalgamation of Neural Network and Fuzzy Theory, was used as decision support tool to decide to go or not go on OCPs. Root mean square error (RMSE) and coefficient of correlation (R) were employed to identify the ANFIS system indicating an optimum and efficient result. The optimum result was obtained from ANFIS network with two input membership functions, Gaussian membership function (gaussmf) and hybrid optimization method. The result shows that ANFIS may help the decision-making process for go/not go decision in OCPs.

[Treatment Decision-Making Process of Cancer Patients].

PubMed

Lee, Shiu-Yu C Katie

2016-10-01

The decision-making process that is used by cancer patients to determine their treatment has become more multi-foci, difficult and complicated in recent years. This has in part been attributed to the increasing incidence rate of cancer in Taiwan and the rapid development of medical technologies and treatment modalities. Oncology nurses must assist patients and family to make informed and value-based treatment decisions. Decision-making is an information process that involves appraising one's own expectation and values based on his/her knowledge on cancer and treatment options. Because cancer treatment involves risks and uncertainties, and impacts quality of life, the treatment decision-making for cancer is often stressful, or even conflicting. This paper discusses the decision-making behaviors of cancer patients and the decisional conflict, participation, and informational needs that are involved in cancer treatment. The trend toward shared decision-making and decisional support will be also explored in order to facilitate the future development of appropriate clinical interventions and research.

METHODS FOR MULTI-SPATIAL SCALE CHARACTERIZATION OF RIPARIAN CORRIDORS

EPA Science Inventory

This paper describes the application of aerial photography and GIS technology to develop flexible and transferable methods for multi-spatial scale characterization and analysis of riparian corridors. Relationships between structural attributes of riparian corridors and indicator...

Non-ad-hoc decision rule for the Dempster-Shafer method of evidential reasoning

NASA Astrophysics Data System (ADS)

Cheaito, Ali; Lecours, Michael; Bosse, Eloi

1998-03-01

This paper is concerned with the fusion of identity information through the use of statistical analysis rooted in Dempster-Shafer theory of evidence to provide automatic identification aboard a platform. An identity information process for a baseline Multi-Source Data Fusion (MSDF) system is defined. The MSDF system is applied to information sources which include a number of radars, IFF systems, an ESM system, and a remote track source. We use a comprehensive Platform Data Base (PDB) containing all the possible identity values that the potential target may take, and we use the fuzzy logic strategies which enable the fusion of subjective attribute information from sensor and the PDB to make the derivation of target identity more quickly, more precisely, and with statistically quantifiable measures of confidence. The conventional Dempster-Shafer lacks a formal basis upon which decision can be made in the face of ambiguity. We define a non-ad hoc decision rule based on the expected utility interval for pruning the `unessential' propositions which would otherwise overload the real-time data fusion systems. An example has been selected to demonstrate the implementation of our modified Dempster-Shafer method of evidential reasoning.

Collaborative human-machine analysis to disambiguate entities in unstructured text and structured datasets

NASA Astrophysics Data System (ADS)

Davenport, Jack H.

2016-05-01

Intelligence analysts demand rapid information fusion capabilities to develop and maintain accurate situational awareness and understanding of dynamic enemy threats in asymmetric military operations. The ability to extract relationships between people, groups, and locations from a variety of text datasets is critical to proactive decision making. The derived network of entities must be automatically created and presented to analysts to assist in decision making. DECISIVE ANALYTICS Corporation (DAC) provides capabilities to automatically extract entities, relationships between entities, semantic concepts about entities, and network models of entities from text and multi-source datasets. DAC's Natural Language Processing (NLP) Entity Analytics model entities as complex systems of attributes and interrelationships which are extracted from unstructured text via NLP algorithms. The extracted entities are automatically disambiguated via machine learning algorithms, and resolution recommendations are presented to the analyst for validation; the analyst's expertise is leveraged in this hybrid human/computer collaborative model. Military capability is enhanced by these NLP Entity Analytics because analysts can now create/update an entity profile with intelligence automatically extracted from unstructured text, thereby fusing entity knowledge from structured and unstructured data sources. Operational and sustainment costs are reduced since analysts do not have to manually tag and resolve entities.

Decision analysis for a data collection system of patient-controlled analgesia with a multi-attribute utility model.

PubMed

Lee, I-Jung; Huang, Shih-Yu; Tsou, Mei-Yung; Chan, Kwok-Hon; Chang, Kuang-Yi

2010-10-01

Data collection systems are very important for the practice of patient-controlled analgesia (PCA). This study aimed to evaluate 3 PCA data collection systems and selected the most favorable system with the aid of multiattribute utility (MAU) theory. We developed a questionnaire with 10 items to evaluate the PCA data collection system and 1 item for overall satisfaction based on MAU theory. Three systems were compared in the questionnaire, including a paper record, optic card reader and personal digital assistant (PDA). A pilot study demonstrated a good internal and test-retest reliability of the questionnaire. A weighted utility score combining the relative importance of individual items assigned by each participant and their responses to each question was calculated for each system. Sensitivity analyses with distinct weighting protocols were conducted to evaluate the stability of the final results. Thirty potential users of a PCA data collection system were recruited in the study. The item "easy to use" had the highest median rank and received the heaviest mean weight among all items. MAU analysis showed that the PDA system had a higher utility score than that in the other 2 systems. Sensitivity analyses revealed that both inverse and reciprocal weighting processes favored the PDA system. High correlations between overall satisfaction and MAU scores from miscellaneous weighting protocols suggested a good predictive validity of our MAU-based questionnaire. The PDA system was selected as the most favorable PCA data collection system by the MAU analysis. The item "easy to use" was the most important attribute of the PCA data collection system. MAU theory can evaluate alternatives by taking into account individual preferences of stakeholders and aid in better decision-making. Copyright © 2010 Elsevier. Published by Elsevier B.V. All rights reserved.

Integrating evidence and individual preferences using a web-based multi-criteria decision analytic tool: an application to prostate cancer screening.

PubMed

Cunich, Michelle; Salkeld, Glenn; Dowie, Jack; Henderson, Joan; Bayram, Clare; Britt, Helena; Howard, Kirsten

2011-01-01

Annalisa© (AL) is a web-based decision-support template grounded in multi-criteria decision analysis (MCDA). It uses a simple expected value algorithm to calculate a score for each option by taking into account the individual's preferences for different criteria (as importance weights) and the evidence of the performance of each option on each criterion. Given the uncertainty surrounding the trade offs between benefits and harms for prostate cancer screening, this topic was chosen as the vehicle to introduce this new decision-support template. The aim of the study was to introduce a new decision-support template, AL, and to develop and pilot a decision-support tool for prostate cancer screening using it. A decision-support tool for prostate cancer screening (ALProst) was implemented in the AL template. ALProst incorporated evidence on both the benefits and the potential harms of prostate cancer screening (the 'attributes') from published randomized controlled trials (RCTs). Individual weights for each attribute were elicited during interviews. By combining the individual's preferences and the evidence, the best option for the user was identified on the basis of quantified scores. A convenience sample of computer-proficient primary-care physicians (general practitioners [GPs] in Australia) from the Sydney Metropolitan area (Australia) were invited to complete a face-to-face interview involving the decision-support tool. Preference for undergoing prostate-specific antigen testing for prostate cancer, both personally and for their patients, was sought prior to seeing the tool. After gaining hands-on experience with using the tool, GPs were asked to comment on the merits of the template and the tool. Preference for presenting the benefits of prostate cancer screening as the relative or absolute risk reduction in prostate cancer-specific mortality was also sought. Of 60 GPs approached, ten (six men and four women) completed an interview (16.7% response rate). Most GPs agreed/strongly agreed with positive statements about the ease with which they could use AL (seven GPs), and understand the information in, and format of, AL (nine and eight, respectively). Eight agreed/strongly agreed that ALProst would be a useful tool for discussing prostate cancer screening with their patients. GPs were also asked to nominate difficult clinical decisions that they, and their patients, have had to make; responses included cancer screening (including prostate cancer); treating patients with multiple illnesses/diseases; managing multiple cardiovascular disease risk factors; and managing patients who are receiving multiple medications. The common element was the need to consider multiple factors in making these complex decisions. AL is distinguishable from most other decision-support templates available today by its underlying conceptual framework, MCDA, and its power to combine individual preferences with evidence to derive the best option for the user quantitatively. It therefore becomes potentially useful for all decisions at all levels in the healthcare system. Moreover, it will provide a universal graphic 'language' that can overcome the burden to patients of encountering a plethora of widely varying decision aids for different conditions during their lifetime.

An improved hybrid multi-criteria/multidimensional model for strategic industrial location selection: Casablanca industrial zones as a case study.

PubMed

Boutkhoum, Omar; Hanine, Mohamed; Agouti, Tarik; Tikniouine, Abdessadek

2015-01-01

In this paper, we examine the issue of strategic industrial location selection in uncertain decision making environments for implanting new industrial corporation. In fact, the industrial location issue is typically considered as a crucial factor in business research field which is related to many calculations about natural resources, distributors, suppliers, customers, and most other things. Based on the integration of environmental, economic and social decisive elements of sustainable development, this paper presents a hybrid decision making model combining fuzzy multi-criteria analysis with analytical capabilities that OLAP systems can provide for successful and optimal industrial location selection. The proposed model mainly consists in three stages. In the first stage, a decision-making committee has been established to identify the evaluation criteria impacting the location selection process. In the second stage, we develop fuzzy AHP software based on the extent analysis method to assign the importance weights to the selected criteria, which allows us to model the linguistic vagueness, ambiguity, and incomplete knowledge. In the last stage, OLAP analysis integrated with multi-criteria analysis employs these weighted criteria as inputs to evaluate, rank and select the strategic industrial location for implanting new business corporation in the region of Casablanca, Morocco. Finally, a sensitivity analysis is performed to evaluate the impact of criteria weights and the preferences given by decision makers on the final rankings of strategic industrial locations.

Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2014-05-01

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 this case study namely: construction of defense structures, relocation, implementation of an early warning system and spatial planning regulations. Some of the criteria are determined partly in other modules of the CHANGES SDSS, such as the costs for implementation, the risk reduction in monetary values, and societal risk. Other criteria, which could be environmental, economic, cultural, perception in nature, are defined by different stakeholders such as local authorities, expert organizations, private sector, and local public. In the next step, the stakeholders weight the importance of the criteria by pairwise comparison and visualize the decision matrix, which is a matrix based on criteria versus alternatives values. Finally alternatives are ranked by Analytic Hierarchy Process (AHP) method. We expect that this approach will help the decision makers to ease their works and reduce their costs, because the process is more transparent, more accurate and involves a group decision. In that way there will be more confidence in the overall decision making process. Keywords: MCDM, Analytic Hierarchy Process (AHP), SDSS, Natural Hazard Risk Management

The development of a multi-criteria decision analysis aid to help with contraceptive choices: My Contraception Tool.

PubMed

French, Rebecca S; Cowan, Frances M; Wellings, Kaye; Dowie, Jack

2014-04-01

My Contraception Tool (MCT) applies the principles of multi-criteria decision analysis to the choice of contraceptive method. Its purpose is to make the decision-making process transparent to the user and to suggest a method to them based on their own preferences. The contraceptive option that emerges as optimal from the analysis takes account of the probability of a range of outcomes and the relative weight ascribed to them by the user. The development of MCT was a collaborative project between London School of Hygiene & Tropical Medicine, Brook, FPA and Maldaba Ltd. MCT is available online via the Brook and FPA websites. In this article we describe MCT's development and how it works. Further work is needed to assess the impact it has on decision quality and contraceptive behaviour.

Assortativity Patterns in Multi-dimensional Inter-organizational Networks: A Case Study of the Humanitarian Relief Sector

NASA Astrophysics Data System (ADS)

Zhao, Kang; Ngamassi, Louis-Marie; Yen, John; Maitland, Carleen; Tapia, Andrea

We use computational tools to study assortativity patterns in multi-dimensional inter-organizational networks on the basis of different node attributes. In the case study of an inter-organizational network in the humanitarian relief sector, we consider not only macro-level topological patterns, but also assortativity on the basis of micro-level organizational attributes. Unlike assortative social networks, this inter-organizational network exhibits disassortative or random patterns on three node attributes. We believe organizations' seek of complementarity is one of the main reasons for the special patterns. Our analysis also provides insights on how to promote collaborations among the humanitarian relief organizations.

Decision support for risk prioritisation of environmental health hazards in a UK city.

PubMed

Woods, Mae; Crabbe, Helen; Close, Rebecca; Studden, Mike; Milojevic, Ai; Leonardi, Giovanni; Fletcher, Tony; Chalabi, Zaid

2016-03-08

There is increasing appreciation of the proportion of the health burden that is attributed to modifiable population exposure to environmental health hazards. To manage this avoidable burden in the United Kingdom (UK), government policies and interventions are implemented. In practice, this procedure is interdisciplinary in action and multi-dimensional in context. Here, we demonstrate how Multi Criteria Decision Analysis (MCDA) can be used as a decision support tool to facilitate priority setting for environmental public health interventions within local authorities. We combine modelling and expert elicitation to gather evidence on the impacts and ranking of interventions. To present the methodology, we consider a hypothetical scenario in a UK city. We use MCDA to evaluate and compare the impact of interventions to reduce the health burden associated with four environmental health hazards and rank them in terms of their overall performance across several criteria. For illustrative purposes, we focus on heavy goods vehicle controls to reduce outdoor air pollution, remediation to control levels of indoor radon, carbon monoxide and fitting alarms, and encouraging cycling to target the obesogenic environment. Regional data was included as model evidence to construct a ratings matrix for the city. When MCDA is performed with uniform weights, the intervention of heavy goods vehicle controls to reduce outdoor air pollution is ranked the highest. Cycling and the obesogenic environment is ranked second. We argue that a MCDA based approach provides a framework to guide environmental public health decision makers. This is demonstrated through an online interactive MCDA tool. We conclude that MCDA is a transparent tool that can be used to compare the impact of alternative interventions on a set of pre-defined criteria. In our illustrative example, we ranked the best intervention across the equally weighted selected criteria out of the four alternatives. Further work is needed to test the tool with decision makers and stakeholders.

'spup' - an R package for uncertainty propagation in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2016-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability, including case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected static and interactive visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

Applying Recursive Sensitivity Analysis to Multi-Criteria Decision Models to Reduce Bias in Defense Cyber Engineering Analysis

DTIC Science & Technology

2015-10-28

techniques such as regression analysis, correlation, and multicollinearity assessment to identify the change and error on the input to the model...between many of the independent or predictor variables, the issue of multicollinearity may arise [18]. VII. SUMMARY Accurate decisions concerning

Multi-level multi-criteria analysis of alternative fuels for waste collection vehicles in the United States.

PubMed

Maimoun, Mousa; Madani, Kaveh; Reinhart, Debra

2016-04-15

Historically, the U.S. waste collection fleet was dominated by diesel-fueled waste collection vehicles (WCVs); the growing need for sustainable waste collection has urged decision makers to incorporate economically efficient alternative fuels, while mitigating environmental impacts. The pros and cons of alternative fuels complicate the decisions making process, calling for a comprehensive study that assesses the multiple factors involved. Multi-criteria decision analysis (MCDA) methods allow decision makers to select the best alternatives with respect to selection criteria. In this study, two MCDA methods, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW), were used to rank fuel alternatives for the U.S. waste collection industry with respect to a multi-level environmental and financial decision matrix. The environmental criteria consisted of life-cycle emissions, tail-pipe emissions, water footprint (WFP), and power density, while the financial criteria comprised of vehicle cost, fuel price, fuel price stability, and fueling station availability. The overall analysis showed that conventional diesel is still the best option, followed by hydraulic-hybrid WCVs, landfill gas (LFG) sourced natural gas, fossil natural gas, and biodiesel. The elimination of the WFP and power density criteria from the environmental criteria ranked biodiesel 100 (BD100) as an environmentally better alternative compared to other fossil fuels (diesel and natural gas). This result showed that considering the WFP and power density as environmental criteria can make a difference in the decision process. The elimination of the fueling station and fuel price stability criteria from the decision matrix ranked fossil natural gas second after LFG-sourced natural gas. This scenario was found to represent the status quo of the waste collection industry. A sensitivity analysis for the status quo scenario showed the overall ranking of diesel and fossil natural gas to be more sensitive to changing fuel prices as compared to other alternatives. Copyright © 2016 Elsevier B.V. All rights reserved.

The application of natural science data to land management decision-making

NASA Technical Reports Server (NTRS)

Williams, D. L.; Sharpe, C. P.; Rowe, P. G.

1974-01-01

A natural environmental analysis process which allows the decision maker to know the probable consequences of a decision prior to the act is developed. Emphasis is placed on the fit between the natural environment and the social, economic, and functional attributes of man's communities and the transition from nature in its present state to various forms and intensities of development. Applications of the analysis are examined. It is concluded that the analysis is a workable system for land use management.

Interpersonal reactivity and the attribution of emotional reactions.

PubMed

Haas, Brian W; Anderson, Ian W; Filkowski, Megan M

2015-06-01

The ability to identify the cause of another person's emotional reaction is an important component associated with improved success of social relationships and survival. Although many studies have investigated the mechanisms involved in emotion recognition, very little is currently known regarding the processes involved during emotion attribution decisions. Research on complementary "emotion understanding" mechanisms, including empathy and theory of mind, has demonstrated that emotion understanding decisions are often made through relatively emotion- or cognitive-based processing streams. The current study was designed to investigate the behavioral and brain mechanisms involved in emotion attribution decisions. We predicted that dual processes, emotional and cognitive, are engaged during emotion attribution decisions. Sixteen healthy adults completed the Interpersonal Reactivity Index to characterize individual differences in tendency to make emotion- versus cognitive-based interpersonal decisions. Participants then underwent functional MRI while making emotion attribution decisions. We found neuroimaging evidence that emotion attribution decisions engage a similar brain network as other forms of emotion understanding. Further, we found evidence in support of a dual processes model involved during emotion attribution decisions. Higher scores of personal distress were associated with quicker emotion attribution decisions and increased anterior insula activity. Conversely, higher scores in perspective taking were associated with delayed emotion attribution decisions and increased prefrontal cortex and premotor activity. These findings indicate that the making of emotion attribution decisions relies on dissociable emotional and cognitive processing streams within the brain. (c) 2015 APA, all rights reserved).

Measuring sustainable development using a multi-criteria model: a case study.

PubMed

Boggia, Antonio; Cortina, Carla

2010-11-01

This paper shows how Multi-criteria Decision Analysis (MCDA) can help in a complex process such as the assessment of the level of sustainability of a certain area. The paper presents the results of a study in which a model for measuring sustainability was implemented to better aid public policy decisions regarding sustainability. In order to assess sustainability in specific areas, a methodological approach based on multi-criteria analysis has been developed. The aim is to rank areas in order to understand the specific technical and/or financial support that they need to develop sustainable growth. The case study presented is an assessment of the level of sustainability in different areas of an Italian Region using the MCDA approach. Our results show that MCDA is a proper approach for sustainability assessment. The results are easy to understand and the evaluation path is clear and transparent. This is what decision makers need for having support to their decisions. The multi-criteria model for evaluation has been developed respecting the sustainable development economic theory, so that final results can have a clear meaning in terms of sustainability. Copyright 2010 Elsevier Ltd. All rights reserved.

Multiattribute evaluation in formulary decision making as applied to calcium-channel blockers.

PubMed

Schumacher, G E

1991-02-01

The use of multiattribute utility theory (MAUT) to make a formulary decision involving calcium-channel blockers (CCBs) is described. The MAUT method is a procedure for identifying, characterizing, and comparing the many variables that may affect a decision. Although applications in pharmacy have been infrequent, MAUT should be particularly appealing to formulary committees. The steps of the MAUT method are (1) determine the viewpoint of the decision makers, (2) identify the decision alternatives, (3) identify the attributes to be evaluated, (4) identify the factors to be used in evaluating the attributes, (5) establish a utility scale for scoring each factor, (6) transform the values for each factor to its utility scale, (7) determine weights for each attribute and factor, (8) calculate the total utility score for each decision alternative, (9) determine which decision alternative has the greatest total score, and (10) perform a sensitivity analysis. The viewpoint of a formulary committee in a health maintenance organization was simulated to develop a model for using the MAUT method to compare CCBs for single-agent therapy of chronic stable angina in ambulatory patients for one year. The attributes chosen were effectiveness, safety, patient acceptance, and cost and weighted 36%, 29%, 21%, and 14%, respectively, as contributions to the evaluation. The rank order of the decision alternatives was (1) generic verapamil, (2) brand-name verapamil, (3) diltiazem, (4) nicardipine, and (5) nifedipine. The MAUT method provides a standardized yet flexible format for comparing and selecting among formulary alternatives.

Intelligent data management for real-time spacecraft monitoring

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.; Gasser, Les; Abramson, Bruce

1992-01-01

Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

Nicotine replacement therapy decision based on fuzzy multi-criteria analysis

NASA Astrophysics Data System (ADS)

Tarmudi, Zamali; Matmali, Norfazillah; Abdullah, Mohd Lazim

2017-08-01

It has been observed that Nicotine Replacement Therapy (NRT) is one of the alternatives to control and reduce smoking addiction among smokers. Since the decision to choose the best NRT alternative involves uncertainty, ambiguity factors and diverse input datasets, thus, this paper proposes a fuzzy multi-criteria analysis (FMA) to overcome these issues. It focuses on how the fuzzy approach can unify the diversity of datasets based on NRT's decision-making problem. The analysis done employed the advantage of the cost-benefit criterion to unify the mixture of dataset input. The performance matrix was utilised to derive the performance scores. An empirical example regarding the NRT's decision-making problem was employed to illustrate the proposed approach. Based on the calculations, this analytical approach was found to be highly beneficial in terms of usability. It was also very applicable and efficient in dealing with the mixture of input datasets. Hence, the decision-making process can easily be used by experts and patients who are interested to join the therapy/cessation program.

Underground Mining Method Selection Using WPM and PROMETHEE

NASA Astrophysics Data System (ADS)

Balusa, Bhanu Chander; Singam, Jayanthu

2018-04-01

The aim of this paper is to represent the solution to the problem of selecting suitable underground mining method for the mining industry. It is achieved by using two multi-attribute decision making techniques. These two techniques are weighted product method (WPM) and preference ranking organization method for enrichment evaluation (PROMETHEE). In this paper, analytic hierarchy process is used for weight's calculation of the attributes (i.e. parameters which are used in this paper). Mining method selection depends on physical parameters, mechanical parameters, economical parameters and technical parameters. WPM and PROMETHEE techniques have the ability to consider the relationship between the parameters and mining methods. The proposed techniques give higher accuracy and faster computation capability when compared with other decision making techniques. The proposed techniques are presented to determine the effective mining method for bauxite mine. The results of these techniques are compared with methods used in the earlier research works. The results show, conventional cut and fill method is the most suitable mining method.

A Decision Support Framework for Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

NASA Astrophysics Data System (ADS)

Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom

2012-12-01

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.

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis

PubMed Central

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization. PMID:29377956

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis.

PubMed

Zu, Xianghuan; Yang, Chuanlei; Wang, Hechun; Wang, Yinyan

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.

Fuzzy decision-making framework for treatment selection based on the combined QUALIFLEX-TODIM method

NASA Astrophysics Data System (ADS)

Ji, Pu; Zhang, Hong-yu; Wang, Jian-qiang

2017-10-01

Treatment selection is a multi-criteria decision-making problem of significant concern in the medical field. In this study, a fuzzy decision-making framework is established for treatment selection. The framework mitigates information loss by introducing single-valued trapezoidal neutrosophic numbers to denote evaluation information. Treatment selection has multiple criteria that remarkably exceed the alternatives. In consideration of this characteristic, the framework utilises the idea of the qualitative flexible multiple criteria method. Furthermore, it considers the risk-averse behaviour of a decision maker by employing a concordance index based on TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) method. A sensitivity analysis is performed to illustrate the robustness of the framework. Finally, a comparative analysis is conducted to compare the framework with several extant methods. Results indicate the advantages of the framework and its better performance compared with the extant methods.

Neural signatures of trust in reciprocity: a coordinate-based meta-analysis

PubMed Central

Bellucci, Gabriele; Chernyak, Sergey V.; Goodyear, Kimberly; Eickhoff, Simon B.; Krueger, Frank

2017-01-01

Trust in reciprocity (TR) is defined as the risky decision to invest valued resources in another party with the hope of mutual benefit. Several fMRI studies have investigated the neural correlates of TR in one-shot and multi-round versions of the investment game (IG). However, an overall characterization of the underlying neural networks remains elusive. Here, we employed a coordinate-based meta-analysis (activation likelihood estimation method, 30 papers) to investigate consistent brain activations in each of the IG stages (i.e., the trust, reciprocity and feedback stage). Our results showed consistent activations in the anterior insula (AI) during trust decisions in the one-shot IG and decisions to reciprocate in the multi-round IG, likely related to representations of aversive feelings. Moreover, decisions to reciprocate also consistently engaged the intraparietal sulcus, probably involved in evaluations of the reciprocity options. On the contrary, trust decisions in the multi-round IG consistently activated the ventral striatum, likely associated with reward prediction error signals. Finally, the dorsal striatum was found consistently recruited during the feedback stage of the multi-round IG, likely related to reinforcement learning. In conclusion, our results indicate different neural networks underlying trust, reciprocity and feedback learning. These findings suggest that although decisions to trust and reciprocate may elicit aversive feelings likely evoked by the uncertainty about the decision outcomes and the pressing requirements of social standards, multiple interactions allow people to build interpersonal trust for cooperation via a learning mechanism by which they arguably learn to distinguish trustworthy from untrustworthy partners. PMID:27859899

A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis.

PubMed

Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

2014-03-01

GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

2014-03-01

GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

Priority Determination of Underwater Tourism Site Development in Gorontalo Province using Analytical Hierarchy Process (AHP)

NASA Astrophysics Data System (ADS)

Rohandi, M.; Tuloli, M. Y.; Jassin, R. T.

2018-02-01

This research aims to determine the development of priority of underwater tourism in Gorontalo province using the Analytical Hierarchy Process (AHP) method which is one of DSS methods applying Multi-Attribute Decision Making (MADM). This method used 5 criteria and 28 alternatives to determine the best priority of underwater tourism site development in Gorontalo province. Based on the AHP calculation it appeared that the best priority development of underwater tourism site is Pulau Cinta whose total AHP score is 0.489 or 48.9%. This DSS produced a reliable result, faster solution, time-saving, and low cost for the decision makers to obtain the best underwater tourism site to be developed.

Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis.

PubMed

Wichary, Szymon; Magnuski, Mikołaj; Oleksy, Tomasz; Brzezicka, Aneta

2017-01-01

In multi-attribute choice, people use heuristics to simplify decision problems. We studied the use of heuristic and rational strategies and their electrophysiological correlates. Since previous work linked the P3 ERP component to attention and decision making, we were interested whether the amplitude of this component is associated with decision strategy use. To this end, we recorded EEG when participants performed a two-alternative choice task, where they could acquire decision cues in a sequential manner and use them to make choices. We classified participants' choices as consistent with a rational Weighted Additive rule (WADD) or a simple heuristic Take The Best (TTB). Participants differed in their preference for WADD and TTB. Using a permutation-based single trial approach, we analyzed EEG responses to consecutive decision cues and their relation to the individual strategy preference. The preference for WADD over TTB was associated with overall higher signal amplitudes to decision cues in the P3 time window. Moreover, the preference for WADD was associated with similar P3 amplitudes to consecutive cues, whereas the preference for TTB was associated with substantial decreases in P3 amplitudes to consecutive cues. We also found that the preference for TTB was associated with enhanced N1 component to cues that discriminated decision alternatives, suggesting very early attention allocation to such cues by TTB users. Our results suggest that preference for either WADD or TTB has an early neural signature reflecting differences in attentional weighting of decision cues. In light of recent findings and hypotheses regarding P3, we interpret these results as indicating the involvement of catecholamine arousal systems in shaping predecisional information processing and strategy selection.

Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis

PubMed Central

Wichary, Szymon; Magnuski, Mikołaj; Oleksy, Tomasz; Brzezicka, Aneta

2017-01-01

In multi-attribute choice, people use heuristics to simplify decision problems. We studied the use of heuristic and rational strategies and their electrophysiological correlates. Since previous work linked the P3 ERP component to attention and decision making, we were interested whether the amplitude of this component is associated with decision strategy use. To this end, we recorded EEG when participants performed a two-alternative choice task, where they could acquire decision cues in a sequential manner and use them to make choices. We classified participants’ choices as consistent with a rational Weighted Additive rule (WADD) or a simple heuristic Take The Best (TTB). Participants differed in their preference for WADD and TTB. Using a permutation-based single trial approach, we analyzed EEG responses to consecutive decision cues and their relation to the individual strategy preference. The preference for WADD over TTB was associated with overall higher signal amplitudes to decision cues in the P3 time window. Moreover, the preference for WADD was associated with similar P3 amplitudes to consecutive cues, whereas the preference for TTB was associated with substantial decreases in P3 amplitudes to consecutive cues. We also found that the preference for TTB was associated with enhanced N1 component to cues that discriminated decision alternatives, suggesting very early attention allocation to such cues by TTB users. Our results suggest that preference for either WADD or TTB has an early neural signature reflecting differences in attentional weighting of decision cues. In light of recent findings and hypotheses regarding P3, we interpret these results as indicating the involvement of catecholamine arousal systems in shaping predecisional information processing and strategy selection. PMID:28867996

History matching through dynamic decision-making

PubMed Central

Maschio, Célio; Santos, Antonio Alberto; Schiozer, Denis; Rocha, Anderson

2017-01-01

History matching is the process of modifying the uncertain attributes of a reservoir model to reproduce the real reservoir performance. It is a classical reservoir engineering problem and plays an important role in reservoir management since the resulting models are used to support decisions in other tasks such as economic analysis and production strategy. This work introduces a dynamic decision-making optimization framework for history matching problems in which new models are generated based on, and guided by, the dynamic analysis of the data of available solutions. The optimization framework follows a ‘learning-from-data’ approach, and includes two optimizer components that use machine learning techniques, such as unsupervised learning and statistical analysis, to uncover patterns of input attributes that lead to good output responses. These patterns are used to support the decision-making process while generating new, and better, history matched solutions. The proposed framework is applied to a benchmark model (UNISIM-I-H) based on the Namorado field in Brazil. Results show the potential the dynamic decision-making optimization framework has for improving the quality of history matching solutions using a substantial smaller number of simulations when compared with a previous work on the same benchmark. PMID:28582413

Multi-criteria decision assessments using Subjective Logic: Methodology and the case of urban water strategies

NASA Astrophysics Data System (ADS)

Moglia, Magnus; Sharma, Ashok K.; Maheepala, Shiroma

2012-07-01

SummaryPlanning of regional and urban water resources, and in particular with Integrated Urban Water Management approaches, often considers inter-relationships between human uses of water, the health of the natural environment as well as the cost of various management strategies. Decision makers hence typically need to consider a combination of social, environmental and economic goals. The types of strategies employed can include water efficiency measures, water sensitive urban design, stormwater management, or catchment management. Therefore, decision makers need to choose between different scenarios and to evaluate them against a number of criteria. This type of problem has a discipline devoted to it, i.e. Multi-Criteria Decision Analysis, which has often been applied in water management contexts. This paper describes the application of Subjective Logic in a basic Bayesian Network to a Multi-Criteria Decision Analysis problem. By doing this, it outlines a novel methodology that explicitly incorporates uncertainty and information reliability. The application of the methodology to a known case study context allows for exploration. By making uncertainty and reliability of assessments explicit, it allows for assessing risks of various options, and this may help in alleviating cognitive biases and move towards a well formulated risk management policy.

Integrating multi-criteria decision analysis for a GIS-based hazardous waste landfill sitting in Kurdistan Province, western Iran

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharifi, Mozafar; Hadidi, Mosslem; Vessali, Elahe

2009-10-15

The evaluation of a hazardous waste disposal site is a complicated process because it requires data from diverse social and environmental fields. These data often involve processing of a significant amount of spatial information which can be used by GIS as an important tool for land use suitability analysis. This paper presents a multi-criteria decision analysis alongside with a geospatial analysis for the selection of hazardous waste landfill sites in Kurdistan Province, western Iran. The study employs a two-stage analysis to provide a spatial decision support system for hazardous waste management in a typically under developed region. The purpose ofmore » GIS was to perform an initial screening process to eliminate unsuitable land followed by utilization of a multi-criteria decision analysis (MCDA) to identify the most suitable sites using the information provided by the regional experts with reference to new chosen criteria. Using 21 exclusionary criteria, as input layers, masked maps were prepared. Creating various intermediate or analysis map layers a final overlay map was obtained representing areas for hazardous waste landfill sites. In order to evaluate different landfill sites produced by the overlaying a landfill suitability index system was developed representing cumulative effects of relative importance (weights) and suitability values of 14 non-exclusionary criteria including several criteria resulting from field observation. Using this suitability index 15 different sites were visited and based on the numerical evaluation provided by MCDA most suitable sites were determined.« less

Integrating multi-criteria decision analysis for a GIS-based hazardous waste landfill sitting in Kurdistan Province, western Iran.

PubMed

Sharifi, Mozafar; Hadidi, Mosslem; Vessali, Elahe; Mosstafakhani, Parasto; Taheri, Kamal; Shahoie, Saber; Khodamoradpour, Mehran

2009-10-01

The evaluation of a hazardous waste disposal site is a complicated process because it requires data from diverse social and environmental fields. These data often involve processing of a significant amount of spatial information which can be used by GIS as an important tool for land use suitability analysis. This paper presents a multi-criteria decision analysis alongside with a geospatial analysis for the selection of hazardous waste landfill sites in Kurdistan Province, western Iran. The study employs a two-stage analysis to provide a spatial decision support system for hazardous waste management in a typically under developed region. The purpose of GIS was to perform an initial screening process to eliminate unsuitable land followed by utilization of a multi-criteria decision analysis (MCDA) to identify the most suitable sites using the information provided by the regional experts with reference to new chosen criteria. Using 21 exclusionary criteria, as input layers, masked maps were prepared. Creating various intermediate or analysis map layers a final overlay map was obtained representing areas for hazardous waste landfill sites. In order to evaluate different landfill sites produced by the overlaying a landfill suitability index system was developed representing cumulative effects of relative importance (weights) and suitability values of 14 non-exclusionary criteria including several criteria resulting from field observation. Using this suitability index 15 different sites were visited and based on the numerical evaluation provided by MCDA most suitable sites were determined.

k-RP*{sub s}: A scalable distributed data structure for high-performance multi-attribute access

DOE Office of Scientific and Technical Information (OSTI.GOV)

Litwin, W.; Neimat, M.A.

k-RP*{sub s} is a new data structure for scalable multicomputer files with multi-attribute (k-d) keys. We discuss the k-RP*{sub s} file evolution and search algorithms. Performance analysis shows that a k-RP*{sub s} file can be much larger and orders of magnitude faster than a traditional k-d file. The speed-up is especially important for range and partial match searches that are often impractical with traditional k-d files. This opens up a new perspective for many applications.

PATIENT-CENTERED DECISION MAKING: LESSONS FROM MULTI-CRITERIA DECISION ANALYSIS FOR QUANTIFYING PATIENT PREFERENCES.

PubMed

Marsh, Kevin; Caro, J Jaime; Zaiser, Erica; Heywood, James; Hamed, Alaa

2018-01-01

Patient preferences should be a central consideration in healthcare decision making. However, stories of patients challenging regulatory and reimbursement decisions has led to questions on whether patient voices are being considered sufficiently during those decision making processes. This has led some to argue that it is necessary to quantify patient preferences before they can be adequately considered. This study considers the lessons from the use of multi-criteria decision analysis (MCDA) for efforts to quantify patient preferences. It defines MCDA and summarizes the benefits it can provide to decision makers, identifies examples of MCDAs that have involved patients, and summarizes good practice guidelines as they relate to quantifying patient preferences. The guidance developed to support the use of MCDA in healthcare provide some useful considerations for the quantification of patient preferences, namely that researchers should give appropriate consideration to: the heterogeneity of patient preferences, and its relevance to decision makers; the cognitive challenges posed by different elicitation methods; and validity of the results they produce. Furthermore, it is important to consider how the relevance of these considerations varies with the decision being supported. The MCDA literature holds important lessons for how patient preferences should be quantified to support healthcare decision making.

Selection of adequate site location during early stages of construction project management: A multi-criteria decision analysis approach

NASA Astrophysics Data System (ADS)

Marović, Ivan; Hanak, Tomaš

2017-10-01

In the management of construction projects special attention should be given to the planning as the most important phase of decision-making process. Quality decision-making based on adequate and comprehensive collaboration of all involved stakeholders is crucial in project’s early stages. Fundamental reasons for existence of this problem arise from: specific conditions of construction industry (final products are inseparable from the location i.e. location has a strong influence of building design and its structural characteristics as well as technology which will be used during construction), investors’ desires and attitudes, and influence of socioeconomic and environment aspects. Considering all mentioned reasons one can conclude that selection of adequate construction site location for future investment is complex, low structured and multi-criteria problem. To take into account all the dimensions, the proposed model for selection of adequate site location is devised. The model is based on AHP (for designing the decision-making hierarchy) and PROMETHEE (for pairwise comparison of investment locations) methods. As a result of mixing basis feature of both methods, operational synergies can be achieved in multi-criteria decision analysis. Such gives the decision-maker a sense of assurance, knowing that if the procedure proposed by the presented model has been followed, it will lead to a rational decision, carefully and systematically thought out.

The best marketing strategy in aesthetic plastic surgery: evaluating patients' preferences by conjoint analysis.

PubMed

Marsidi, Nick; van den Bergh, Maurice W H M; Luijendijk, Roland W

2014-01-01

To provide the best marketing strategy for a private clinic, knowledge of patients' preferences is essential. In marketing, conjoint analysis has been frequently used to calculate which attributes of a product are most valuable to consumers. This study investigates the relative importance of attributes that influence the selection and decision-making process when choosing an aesthetic private clinic, using conjoint analysis. The following attributes were chosen by the senior author (R.W.L.) and a marketing and communications director after a preselection of 25 randomly selected people: relative cost of the procedure, travel time, experience of the plastic surgeon, size of the clinic, method of referral, and online presentation. The attributes were then divided into levels. Using a random factor conducted by SPSS, 18 different scenarios were created and rated online by 150 potential patients before their potential visit or consultation. The patients could rate these scenarios on a scale from 1 to 7 with respect to the likeliness of visiting the clinic. The most important attribute was experience of the surgeon (35.6 percent), followed by method of referral (21.5 percent), travel time (14.2 percent), cost of procedure (12.9 percent), online presentation (9.7 percent), and size of the clinic (6.1 percent). Six of 16 levels gave a negative influence on the decision making. The authors' study shows that the two most important attributes are the experience of the surgeon and the method of referral and that conjoint analysis is effective in determining patients' preferences. It also shows which levels positively or negatively contribute per attribute.

BagMOOV: A novel ensemble for heart disease prediction bootstrap aggregation with multi-objective optimized voting.

PubMed

Bashir, Saba; Qamar, Usman; Khan, Farhan Hassan

2015-06-01

Conventional clinical decision support systems are based on individual classifiers or simple combination of these classifiers which tend to show moderate performance. This research paper presents a novel classifier ensemble framework based on enhanced bagging approach with multi-objective weighted voting scheme for prediction and analysis of heart disease. The proposed model overcomes the limitations of conventional performance by utilizing an ensemble of five heterogeneous classifiers: Naïve Bayes, linear regression, quadratic discriminant analysis, instance based learner and support vector machines. Five different datasets are used for experimentation, evaluation and validation. The datasets are obtained from publicly available data repositories. Effectiveness of the proposed ensemble is investigated by comparison of results with several classifiers. Prediction results of the proposed ensemble model are assessed by ten fold cross validation and ANOVA statistics. The experimental evaluation shows that the proposed framework deals with all type of attributes and achieved high diagnosis accuracy of 84.16 %, 93.29 % sensitivity, 96.70 % specificity, and 82.15 % f-measure. The f-ratio higher than f-critical and p value less than 0.05 for 95 % confidence interval indicate that the results are extremely statistically significant for most of the datasets.

Application of GIS in foreign direct investment decision support system

NASA Astrophysics Data System (ADS)

Zhou, Jianlan; Sun, Koumei

2007-06-01

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.

A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis☆

PubMed Central

Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

2014-01-01

GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987

Natural Hazard Susceptibility Assessment for Road Planning Using Spatial Multi-Criteria Analysis

NASA Astrophysics Data System (ADS)

Karlsson, Caroline S. J.; Kalantari, Zahra; Mörtberg, Ulla; Olofsson, Bo; Lyon, Steve W.

2017-11-01

Inadequate infrastructural networks can be detrimental to society if transport between locations becomes hindered or delayed, especially due to natural hazards which are difficult to control. Thus determining natural hazard susceptible areas and incorporating them in the initial planning process, may reduce infrastructural damages in the long run. The objective of this study was to evaluate the usefulness of expert judgments for assessing natural hazard susceptibility through a spatial multi-criteria analysis approach using hydrological, geological, and land use factors. To utilize spatial multi-criteria analysis for decision support, an analytic hierarchy process was adopted where expert judgments were evaluated individually and in an aggregated manner. The estimates of susceptible areas were then compared with the methods weighted linear combination using equal weights and factor interaction method. Results showed that inundation received the highest susceptibility. Using expert judgment showed to perform almost the same as equal weighting where the difference in susceptibility between the two for inundation was around 4%. The results also showed that downscaling could negatively affect the susceptibility assessment and be highly misleading. Susceptibility assessment through spatial multi-criteria analysis is useful for decision support in early road planning despite its limitation to the selection and use of decision rules and criteria. A natural hazard spatial multi-criteria analysis could be used to indicate areas where more investigations need to be undertaken from a natural hazard point of view, and to identify areas thought to have higher susceptibility along existing roads where mitigation measures could be targeted after in-situ investigations.

Natural Hazard Susceptibility Assessment for Road Planning Using Spatial Multi-Criteria Analysis.

PubMed

Karlsson, Caroline S J; Kalantari, Zahra; Mörtberg, Ulla; Olofsson, Bo; Lyon, Steve W

2017-11-01

Inadequate infrastructural networks can be detrimental to society if transport between locations becomes hindered or delayed, especially due to natural hazards which are difficult to control. Thus determining natural hazard susceptible areas and incorporating them in the initial planning process, may reduce infrastructural damages in the long run. The objective of this study was to evaluate the usefulness of expert judgments for assessing natural hazard susceptibility through a spatial multi-criteria analysis approach using hydrological, geological, and land use factors. To utilize spatial multi-criteria analysis for decision support, an analytic hierarchy process was adopted where expert judgments were evaluated individually and in an aggregated manner. The estimates of susceptible areas were then compared with the methods weighted linear combination using equal weights and factor interaction method. Results showed that inundation received the highest susceptibility. Using expert judgment showed to perform almost the same as equal weighting where the difference in susceptibility between the two for inundation was around 4%. The results also showed that downscaling could negatively affect the susceptibility assessment and be highly misleading. Susceptibility assessment through spatial multi-criteria analysis is useful for decision support in early road planning despite its limitation to the selection and use of decision rules and criteria. A natural hazard spatial multi-criteria analysis could be used to indicate areas where more investigations need to be undertaken from a natural hazard point of view, and to identify areas thought to have higher susceptibility along existing roads where mitigation measures could be targeted after in-situ investigations.

Relative importance of attributes of drug benefit plans: Thai civil servants' perspective.

PubMed

Ngorsuraches, Surachat; Wanishayakorn, Tanatape; Tanvejsilp, Pimwara; Udomaksorn, Siripa

2013-01-01

The drug benefit plan of Thailand's Civil Servant Medical Benefit Scheme (CSMBS) must be amended to control increasing costs; to that end, it is important to gather the views of beneficiaries before making changes to the benefit plan. To examine the relative importance of attributes of drug benefit plans from the perspective of CSMBS beneficiaries. Attributes and levels adopted from focus group discussions and a preliminary survey were used to develop a questionnaire concerning hypothetical drug benefit plans. A convenience sample of 650 CSMBS beneficiaries in Songkhla province was asked to rate the drug benefit plans. To determine the beneficiaries' decision models, judgment analysis was used. Policy-capturing analysis was used to examine the beneficiaries' preferences, and cluster analysis was conducted to explore the variability among judgment plans. Judgment policy insight was also examined. The results of the study showed that the beneficiaries weighed on cost-sharing as their most important attribute. The results remained unchanged, although only data from the beneficiaries who used the compensatory model were analyzed. The results of the cluster analysis showed that the largest cluster of beneficiaries weighed mostly on the cost-sharing attribute. The judgment policy insight results not only supported the finding that most beneficiaries focused on the cost-sharing attribute but also revealed that they might have the least understanding of how the formulary attribute affected beneficiaries' decision making. Cost-sharing was the most important attribute for the CSMBS beneficiaries. This study indicated that a possible preferred drug benefit plan should have no cost-sharing, permit access only to drugs listed in a closed formulary, allow beneficiaries to obtain 3 months of drugs, and allow them to obtain drugs from either a community pharmacy or a government hospital. Copyright © 2013 Elsevier Inc. All rights reserved.

A multi-valued neutrosophic qualitative flexible approach based on likelihood for multi-criteria decision-making problems

NASA Astrophysics Data System (ADS)

Peng, Juan-juan; Wang, Jian-qiang; Yang, Wu-E.

2017-01-01

In this paper, multi-criteria decision-making (MCDM) problems based on the qualitative flexible multiple criteria method (QUALIFLEX), in which the criteria values are expressed by multi-valued neutrosophic information, are investigated. First, multi-valued neutrosophic sets (MVNSs), which allow the truth-membership function, indeterminacy-membership function and falsity-membership function to have a set of crisp values between zero and one, are introduced. Then the likelihood of multi-valued neutrosophic number (MVNN) preference relations is defined and the corresponding properties are also discussed. Finally, an extended QUALIFLEX approach based on likelihood is explored to solve MCDM problems where the assessments of alternatives are in the form of MVNNs; furthermore an example is provided to illustrate the application of the proposed method, together with a comparison analysis.

Energy Decision Science and Informatics | Integrated Energy Solutions |

Science.gov Websites

Science Advanced decision science methods include multi-objective and multi-criteria decision support. Our decision science methods, including multi-objective and multi-criteria decision support. For example, we

A multi-criteria decision analysis assessment of waste paper management options.

PubMed

Hanan, Deirdre; Burnley, Stephen; Cooke, David

2013-03-01

The use of Multi-criteria Decision Analysis (MCDA) was investigated in an exercise using a panel of local residents and stakeholders to assess the options for managing waste paper on the Isle of Wight. Seven recycling, recovery and disposal options were considered by the panel who evaluated each option against seven environmental, financial and social criteria. The panel preferred options where the waste was managed on the island with gasification and recycling achieving the highest scores. Exporting the waste to the English mainland for incineration or landfill proved to be the least preferred options. This research has demonstrated that MCDA is an effective way of involving community groups in waste management decision making. Copyright © 2012 Elsevier Ltd. All rights reserved.

Estimated Costs of Sporadic Gastrointestinal Illness Associated with Surface Water Recreation: A Combined Analysis of Data from NEEAR and CHEERS Studies

EPA Science Inventory

BACKGROUND: The ·burden of illness can be described by addressing both incidence and illness severity attributable to water recreation. Monetized as cost. attributable disease burden estimates can be useful for environmental management decisions. OBJECTIVES: We characterize the ...

Priority setting for the prevention and control of cardiovascular diseases: multi-criteria decision analysis in four eastern Mediterranean countries.

PubMed

Ghandour, Rula; Shoaibi, Azza; Khatib, Rana; Abu Rmeileh, Niveen; Unal, Belgin; Sözmen, Kaan; Kılıç, Bülent; Fouad, Fouad; Al Ali, Radwan; Ben Romdhane, Habiba; Aissi, Wafa; Ahmad, Balsam; Capewell, Simon; Critchley, Julia; Husseini, Abdullatif

2015-01-01

To explore the feasibility of using a simple multi-criteria decision analysis method with policy makers/key stakeholders to prioritize cardiovascular disease (CVD) policies in four Mediterranean countries: Palestine, Syria, Tunisia and Turkey. A simple multi-criteria decision analysis (MCDA) method was piloted. A mixed methods study was used to identify a preliminary list of policy options in each country. These policies were rated by different policymakers/stakeholders against pre-identified criteria to generate a priority score for each policy and then rank the policies. Twenty-five different policies were rated in the four countries to create a country-specific list of CVD prevention and control policies. The response rate was 100% in each country. The top policies were mostly population level interventions and health systems' level policies. Successful collaboration between policy makers/stakeholders and researchers was established in this small pilot study. MCDA appeared to be feasible and effective. Future applications should aim to engage a larger, representative sample of policy makers, especially from outside the health sector. Weighting the selected criteria might also be assessed.

Multiple-attribute group decision making with different formats of preference information on attributes.

PubMed

Xu, Zeshui

2007-12-01

Interval utility values, interval fuzzy preference relations, and interval multiplicative preference relations are three common uncertain-preference formats used by decision-makers to provide their preference information in the process of decision making under fuzziness. This paper is devoted in investigating multiple-attribute group-decision-making problems where the attribute values are not precisely known but the value ranges can be obtained, and the decision-makers provide their preference information over attributes by three different uncertain-preference formats i.e., 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first utilize some functions to normalize the uncertain decision matrix and then transform it into an expected decision matrix. We establish a goal-programming model to integrate the expected decision matrix and all three different uncertain-preference formats from which the attribute weights and the overall attribute values of alternatives can be obtained. Then, we use the derived overall attribute values to get the ranking of the given alternatives and to select the best one(s). The model not only can reflect both the subjective considerations of all decision-makers and the objective information but also can avoid losing and distorting the given objective and subjective decision information in the process of information integration. Furthermore, we establish some models to solve the multiple-attribute group-decision-making problems with three different preference formats: 1) utility values; 2) fuzzy preference relations; and 3) multiplicative preference relations. Finally, we illustrate the applicability and effectiveness of the developed models with two practical examples.

Multi-criteria decision making--an approach to setting priorities in health care.

PubMed

Nobre, F F; Trotta, L T; Gomes, L F

1999-12-15

The objective of this paper is to present a multi-criteria decision making (MCDM) approach to support public health decision making that takes into consideration the fuzziness of the decision goals and the behavioural aspect of the decision maker. The approach is used to analyse the process of health technology procurement in a University Hospital in Rio de Janeiro, Brazil. The method, known as TODIM, relies on evaluating alternatives with a set of decision criteria assessed using an ordinal scale. Fuzziness in generating criteria scores and weights or conflicts caused by dealing with different viewpoints of a group of decision makers (DMs) are solved using fuzzy set aggregation rules. The results suggested that MCDM models, incorporating fuzzy set approaches, should form a set of tools for public health decision making analysis, particularly when there are polarized opinions and conflicting objectives from the DM group. Copyright 1999 John Wiley & Sons, Ltd.

Multi-criteria analysis for PM10 planning

NASA Astrophysics Data System (ADS)

Pisoni, Enrico; Carnevale, Claudio; Volta, Marialuisa

To implement sound air quality policies, Regulatory Agencies require tools to evaluate outcomes and costs associated to different emission reduction strategies. These tools are even more useful when considering atmospheric PM10 concentrations due to the complex nonlinear processes that affect production and accumulation of the secondary fraction of this pollutant. The approaches presented in the literature (Integrated Assessment Modeling) are mainly cost-benefit and cost-effective analysis. In this work, the formulation of a multi-objective problem to control particulate matter is proposed. The methodology defines: (a) the control objectives (the air quality indicator and the emission reduction cost functions); (b) the decision variables (precursor emission reductions); (c) the problem constraints (maximum feasible technology reductions). The cause-effect relations between air quality indicators and decision variables are identified tuning nonlinear source-receptor models. The multi-objective problem solution provides to the decision maker a set of not-dominated scenarios representing the efficient trade-off between the air quality benefit and the internal costs (emission reduction technology costs). The methodology has been implemented for Northern Italy, often affected by high long-term exposure to PM10. The source-receptor models used in the multi-objective analysis are identified processing long-term simulations of GAMES multiphase modeling system, performed in the framework of CAFE-Citydelta project.

Multi Criteria Evaluation Module for RiskChanges Spatial Decision Support System

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; Jaboyedoff, Michel; van Westen, Cees; Bakker, Wim

2015-04-01

Multi-Criteria Evaluation (MCE) module is one of the five modules of RiskChanges spatial decision support system. RiskChanges web-based platform aims to analyze changes in hydro-meteorological risk and provides tools for selecting the best risk reduction alternative. It is developed under CHANGES framework (changes-itn.eu) and INCREO project (increo-fp7.eu). MCE tool helps decision makers and spatial planners to evaluate, sort and rank the decision alternatives. The users can choose among different indicators that are defined within the system using Risk and Cost Benefit analysis results besides they can add their own indicators. Subsequently the system standardizes and prioritizes them. Finally, the best decision alternative is selected by using the weighted sum model (WSM). The Application of this work is to facilitate the effect of MCE for analyzing changing risk over the time under different scenarios and future years by adopting a group decision making into practice and comparing the results by numeric and graphical view within the system. We believe that this study helps decision-makers to achieve the best solution by expressing their preferences for strategies under future scenarios. Keywords: Multi-Criteria Evaluation, Spatial Decision Support System, Weighted Sum Model, Natural Hazard Risk Management

General Matthew B. Ridgway: Attributes of Battle Command and Decision-Making

DTIC Science & Technology

1998-02-13

information dominance require the attributes of future battle commanders be different than those of the past? This paper focuses on the intellectual and personality traits of General Matthew B. Ridgway as they apply to operational command and decision-making. These traits are considered essential for analysis and serve as a framework in which to examine their applicability to future command. The essential qualities of an operational commander are divided into two categories: intellect and personality. Each category is further divided into elemental traits. The application

Multi-objective game-theory models for conflict analysis in reservoir watershed management.

PubMed

Lee, Chih-Sheng

2012-05-01

This study focuses on the development of a multi-objective game-theory model (MOGM) for balancing economic and environmental concerns in reservoir watershed management and for assistance in decision. Game theory is used as an alternative tool for analyzing strategic interaction between economic development (land use and development) and environmental protection (water-quality protection and eutrophication control). Geographic information system is used to concisely illustrate and calculate the areas of various land use types. The MOGM methodology is illustrated in a case study of multi-objective watershed management in the Tseng-Wen reservoir, Taiwan. The innovation and advantages of MOGM can be seen in the results, which balance economic and environmental concerns in watershed management and which can be interpreted easily by decision makers. For comparison, the decision-making process using conventional multi-objective method to produce many alternatives was found to be more difficult. Copyright © 2012 Elsevier Ltd. All rights reserved.

Use of structured decision making to identify monitoring variables and management priorities for salt marsh ecosystems

USGS Publications Warehouse

Neckles, Hilary A.; Lyons, James E.; Guntenspergen, Glenn R.; Shriver, W. Gregory; Adamowicz, Susan C.

2015-01-01

Most salt marshes in the USA have been degraded by human activities, and coastal managers are faced with complex choices among possible actions to restore or enhance ecosystem integrity. We applied structured decision making (SDM) to guide selection of monitoring variables and management priorities for salt marshes within the National Wildlife Refuge System in the northeastern USA. In general, SDM is a systematic process for decomposing a decision into its essential elements. We first engaged stakeholders in clarifying regional salt marsh decision problems, defining objectives and attributes to evaluate whether objectives are achieved, and developing a pool of alternative management actions for achieving objectives. Through this process, we identified salt marsh attributes that were applicable to monitoring National Wildlife Refuges on a regional scale and that targeted management needs. We then analyzed management decisions within three salt marsh units at Prime Hook National Wildlife Refuge, coastal Delaware, as a case example of prioritizing management alternatives. Values for salt marsh attributes were estimated from 2 years of baseline monitoring data and expert opinion. We used linear value modeling to aggregate multiple attributes into a single performance score for each alternative, constrained optimization to identify alternatives that maximized total management benefits subject to refuge-wide cost constraints, and used graphical analysis to identify the optimal set of alternatives for the refuge. SDM offers an efficient, transparent approach for integrating monitoring into management practice and improving the quality of management decisions.

Multi-Agent simulation of generation capacity expansion decisions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Botterud, A.; Mahalik, M.; Conzelmann, G.

2008-01-01

In this paper, we use a multi-agent simulation model, EMCAS, to analyze generation expansion in the Iberian electricity market. The expansion model simulates generation investment decisions of decentralized generating companies (GenCos) interacting in a complex, multidimensional environment. A probabilistic dispatch algorithm calculates prices and profits for new candidate units in different future states of the system. Uncertainties in future load, hydropower conditions, and competitorspsila actions are represented in a scenario tree, and decision analysis is used to identify the optimal expansion decision for each individual GenCo. We run the model using detailed data for the Iberian market. In a scenariomore » analysis, we look at the impact of market design variables, such as the energy price cap and carbon emission prices. We also analyze how market concentration and GenCospsila risk preferences influence the timing and choice of new generating capacity.« less

Modelling innovation performance of European regions using multi-output neural networks

PubMed Central

Henriques, Roberto

2017-01-01

Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes. PMID:28968449

Modelling innovation performance of European regions using multi-output neural networks.

PubMed

Hajek, Petr; Henriques, Roberto

2017-01-01

Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.

Assessing the multi-scale predictive ability of ecosystem functional attributes for species distribution modelling.

PubMed

Arenas-Castro, Salvador; Gonçalves, João; Alves, Paulo; Alcaraz-Segura, Domingo; Honrado, João P

2018-01-01

Global environmental changes are rapidly affecting species' distributions and habitat suitability worldwide, requiring a continuous update of biodiversity status to support effective decisions on conservation policy and management. In this regard, satellite-derived Ecosystem Functional Attributes (EFAs) offer a more integrative and quicker evaluation of ecosystem responses to environmental drivers and changes than climate and structural or compositional landscape attributes. Thus, EFAs may hold advantages as predictors in Species Distribution Models (SDMs) and for implementing multi-scale species monitoring programs. Here we describe a modelling framework to assess the predictive ability of EFAs as Essential Biodiversity Variables (EBVs) against traditional datasets (climate, land-cover) at several scales. We test the framework with a multi-scale assessment of habitat suitability for two plant species of conservation concern, both protected under the EU Habitats Directive, differing in terms of life history, range and distribution pattern (Iris boissieri and Taxus baccata). We fitted four sets of SDMs for the two test species, calibrated with: interpolated climate variables; landscape variables; EFAs; and a combination of climate and landscape variables. EFA-based models performed very well at the several scales (AUCmedian from 0.881±0.072 to 0.983±0.125), and similarly to traditional climate-based models, individually or in combination with land-cover predictors (AUCmedian from 0.882±0.059 to 0.995±0.083). Moreover, EFA-based models identified additional suitable areas and provided valuable information on functional features of habitat suitability for both test species (narrowly vs. widely distributed), for both coarse and fine scales. Our results suggest a relatively small scale-dependence of the predictive ability of satellite-derived EFAs, supporting their use as meaningful EBVs in SDMs from regional and broader scales to more local and finer scales. Since the evaluation of species' conservation status and habitat quality should as far as possible be performed based on scalable indicators linking to meaningful processes, our framework may guide conservation managers in decision-making related to biodiversity monitoring and reporting schemes.

The Impact of Quantitative Data Provided by a Multi-spectral Digital Skin Lesion Analysis Device on Dermatologists'Decisions to Biopsy Pigmented Lesions.

PubMed

Farberg, Aaron S; Winkelmann, Richard R; Tucker, Natalie; White, Richard; Rigel, Darrell S

2017-09-01

BACKGROUND: Early diagnosis of melanoma is critical to survival. New technologies, such as a multi-spectral digital skin lesion analysis (MSDSLA) device [MelaFind, STRATA Skin Sciences, Horsham, Pennsylvania] may be useful to enhance clinician evaluation of concerning pigmented skin lesions. Previous studies evaluated the effect of only the binary output. OBJECTIVE: The objective of this study was to determine how decisions dermatologists make regarding pigmented lesion biopsies are impacted by providing both the underlying classifier score (CS) and associated probability risk provided by multi-spectral digital skin lesion analysis. This outcome was also compared against the improvement reported with the provision of only the binary output. METHODS: Dermatologists attending an educational conference evaluated 50 pigmented lesions (25 melanomas and 25 benign lesions). Participants were asked if they would biopsy the lesion based on clinical images, and were asked this question again after being shown multi-spectral digital skin lesion analysis data that included the probability graphs and classifier score. RESULTS: Data were analyzed from a total of 160 United States board-certified dermatologists. Biopsy sensitivity for melanoma improved from 76 percent following clinical evaluation to 92 percent after quantitative multi-spectral digital skin lesion analysis information was provided ( p <0.0001). Specificity improved from 52 percent to 79 percent ( p <0.0001). The positive predictive value increased from 61 percent to 81 percent ( p <0.01) when the quantitative data were provided. Negative predictive value also increased (68% vs. 91%, p<0.01), and overall biopsy accuracy was greater with multi-spectral digital skin lesion analysis (64% vs. 86%, p <0.001). Interrater reliability improved (intraclass correlation 0.466 before, 0.559 after). CONCLUSION: Incorporating the classifier score and probability data into physician evaluation of pigmented lesions led to both increased sensitivity and specificity, thereby resulting in more accurate biopsy decisions.

Placement Decisions and Disparities among Aboriginal Groups: An Application of the Decision Making Ecology through Multi-Level Analysis

ERIC Educational Resources Information Center

Fluke, John D.; Chabot, Martin; Fallon, Barbara; MacLaurin, Bruce; Blackstock, Cindy

2010-01-01

Objective: This paper examined the relative influence of clinical and organizational characteristics on the decision to place a child in out-of-home care at the conclusion of a child maltreatment investigation. It tested the hypothesis that extraneous factors, specifically, organizational characteristics, impact the decision to place a child in…

GIS Based Multi-Criteria Decision Analysis For Cement Plant Site Selection For Cuddalore District

NASA Astrophysics Data System (ADS)

Chhabra, A.

2015-12-01

India's cement industry is a vital part of its economy, providing employment to more than a million people. On the back of growing demands, due to increased construction and infrastructural activities cement market in India is expected to grow at a compound annual growth rate (CAGR) of 8.96 percent during the period 2014-2019. In this study, GIS-based spatial Multi Criteria Decision Analysis (MCDA) is used to determine the optimum and alternative sites to setup a cement plant. This technique contains a set of evaluation criteria which are quantifiable indicators of the extent to which decision objectives are realized. In intersection with available GIS (Geographical Information System) and local ancillary data, the outputs of image analysis serves as input for the multi-criteria decision making system. Moreover, the following steps were performed so as to represent the criteria in GIS layers, which underwent the GIS analysis in order to get several potential sites. Satellite imagery from LANDSAT 8 and ASTER DEM were used for the analysis. Cuddalore District in Tamil Nadu was selected as the study site as limestone mining is already being carried out in that region which meets the criteria of raw material for cement production. Several other criteria considered were land use land cover (LULC) classification (built-up area, river, forest cover, wet land, barren land, harvest land and agriculture land), slope, proximity to road, railway and drainage networks.

Smart Grid as Multi-layer Interacting System for Complex Decision Makings

NASA Astrophysics Data System (ADS)

Bompard, Ettore; Han, Bei; Masera, Marcelo; Pons, Enrico

This chapter presents an approach to the analysis of Smart Grids based on a multi-layer representation of their technical, cyber, social and decision-making aspects, as well as the related environmental constraints. In the Smart Grid paradigm, self-interested active customers (prosumers), system operators and market players interact among themselves making use of an extensive cyber infrastructure. In addition, policy decision makers define regulations, incentives and constraints to drive the behavior of the competing operators and prosumers, with the objective of ensuring the global desired performance (e.g. system stability, fair prices). For these reasons, the policy decision making is more complicated than in traditional power systems, and needs proper modeling and simulation tools for assessing "in vitro" and ex-ante the possible impacts of the decisions assumed. In this chapter, we consider the smart grids as multi-layered interacting complex systems. The intricacy of the framework, characterized by several interacting layers, cannot be captured by closed-form mathematical models. Therefore, a new approach using Multi Agent Simulation is described. With case studies we provide some indications about how to develop agent-based simulation tools presenting some preliminary examples.

Analysis of Multi-State Systems with Multi-State Components Using EVMDDs

DTIC Science & Technology

2012-05-01

Fault-Tolerant Computing (FTCS), pp. 249– 258, June 1995. [5] T. Kam, T. Villa, R. K. Brayton , and A. L. Sangiovanni- Vincentelli, “Multi-valued...Shmerko, and R. S. Stankovic, Decision Diagram Techniques for Micro- and Nanoelectronic Design, CRC Press, Taylor & Francis Group, 2006. [16] X. Zang, D

Multi-agent simulation of generation expansion in electricity markets.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Botterud, A; Mahalik, M. R.; Veselka, T. D.

2007-06-01

We present a new multi-agent model of generation expansion in electricity markets. The model simulates generation investment decisions of decentralized generating companies (GenCos) interacting in a complex, multidimensional environment. A probabilistic dispatch algorithm calculates prices and profits for new candidate units in different future states of the system. Uncertainties in future load, hydropower conditions, and competitors actions are represented in a scenario tree, and decision analysis is used to identify the optimal expansion decision for each individual GenCo. We test the model using real data for the Korea power system under different assumptions about market design, market concentration, and GenCo'smore » assumed expectations about their competitors investment decisions.« less

Counseling Students' Decision Making Regarding Teaching Effectiveness: A Conjoint Analysis

ERIC Educational Resources Information Center

Pietrzak, Dale; Duncan, Kelly; Korcuska, James S.

2008-01-01

The authors examined the relative importance of 4 attributes of decision making for student evaluation of teaching effectiveness: perceived knowledge base of the professor, professor's delivery style, course organization, and course workload. Participants were 234 counseling graduate students from 6 midwestern universities in the United States.…

PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

NASA Astrophysics Data System (ADS)

Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.

2018-03-01

Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.

Using Technical Performance Measures

NASA Technical Reports Server (NTRS)

Garrett, Christopher J.; Levack, Daniel J. H.; Rhodes, Russel E.

2011-01-01

All programs have requirements. For these requirements to be met, there must be a means of measurement. A Technical Performance Measure (TPM) is defined to produce a measured quantity that can be compared to the requirement. In practice, the TPM is often expressed as a maximum or minimum and a goal. Example TPMs for a rocket program are: vacuum or sea level specific impulse (lsp), weight, reliability (often expressed as a failure rate), schedule, operability (turn-around time), design and development cost, production cost, and operating cost. Program status is evaluated by comparing the TPMs against specified values of the requirements. During the program many design decisions are made and most of them affect some or all of the TPMs. Often, the same design decision changes some TPMs favorably while affecting other TPMs unfavorably. The problem then becomes how to compare the effects of a design decision on different TPMs. How much failure rate is one second of specific impulse worth? How many days of schedule is one pound of weight worth? In other words, how to compare dissimilar quantities in order to trade and manage the TPMs to meet all requirements. One method that has been used successfully and has a mathematical basis is Utility Analysis. Utility Analysis enables quantitative comparison among dissimilar attributes. It uses a mathematical model that maps decision maker preferences over the tradeable range of each attribute. It is capable of modeling both independent and dependent attributes. Utility Analysis is well supported in the literature on Decision Theory. It has been used at Pratt & Whitney Rocketdyne for internal programs and for contracted work such as the J-2X rocket engine program. This paper describes the construction of TPMs and describes Utility Analysis. It then discusses the use of TPMs in design trades and to manage margin during a program using Utility Analysis.

Use of the AHP methodology in system dynamics: Modelling and simulation for health technology assessments to determine the correct prosthesis choice for hernia diseases.

PubMed

Improta, Giovanni; Russo, Mario Alessandro; Triassi, Maria; Converso, Giuseppe; Murino, Teresa; Santillo, Liberatina Carmela

2018-05-01

Health technology assessments (HTAs) are often difficult to conduct because of the decisive procedures of the HTA algorithm, which are often complex and not easy to apply. Thus, their use is not always convenient or possible for the assessment of technical requests requiring a multidisciplinary approach. This paper aims to address this issue through a multi-criteria analysis focusing on the analytic hierarchy process (AHP). This methodology allows the decision maker to analyse and evaluate different alternatives and monitor their impact on different actors during the decision-making process. However, the multi-criteria analysis is implemented through a simulation model to overcome the limitations of the AHP methodology. Simulations help decision-makers to make an appropriate decision and avoid unnecessary and costly attempts. Finally, a decision problem regarding the evaluation of two health technologies, namely, the evaluation of two biological prostheses for incisional infected hernias, will be analysed to assess the effectiveness of the model. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Green supplier selection: a new genetic/immune strategy with industrial application

NASA Astrophysics Data System (ADS)

Kumar, Amit; Jain, Vipul; Kumar, Sameer; Chandra, Charu

2016-10-01

With the onset of the 'climate change movement', organisations are striving to include environmental criteria into the supplier selection process. This article hybridises a Green Data Envelopment Analysis (GDEA)-based approach with a new Genetic/Immune Strategy for Data Envelopment Analysis (GIS-DEA). A GIS-DEA approach provides a different view to solving multi-criteria decision making problems using data envelopment analysis (DEA) by considering DEA as a multi-objective optimisation problem with efficiency as one objective and proximity of solution to decision makers' preferences as the other objective. The hybrid approach called GIS-GDEA is applied here to a well-known automobile spare parts manufacturer in India and the results presented. User validation developed based on specific set of criteria suggests that the supplier selection process with GIS-GDEA is more practical than other approaches in a current industrial scenario with multiple decision makers.

Making Good Decisions in Healthcare with Multi-Criteria Decision Analysis: The Use, Current Research and Future Development of MCDA.

PubMed

Mühlbacher, Axel C; Kaczynski, Anika

2016-02-01

Healthcare decision making is usually characterized by a low degree of transparency. The demand for transparent decision processes can be fulfilled only when assessment, appraisal and decisions about health technologies are performed under a systematic construct of benefit assessment. The benefit of an intervention is often multidimensional and, thus, must be represented by several decision criteria. Complex decision problems require an assessment and appraisal of various criteria; therefore, a decision process that systematically identifies the best available alternative and enables an optimal and transparent decision is needed. For that reason, decision criteria must be weighted and goal achievement must be scored for all alternatives. Methods of multi-criteria decision analysis (MCDA) are available to analyse and appraise multiple clinical endpoints and structure complex decision problems in healthcare decision making. By means of MCDA, value judgments, priorities and preferences of patients, insurees and experts can be integrated systematically and transparently into the decision-making process. This article describes the MCDA framework and identifies potential areas where MCDA can be of use (e.g. approval, guidelines and reimbursement/pricing of health technologies). A literature search was performed to identify current research in healthcare. The results showed that healthcare decision making is addressing the problem of multiple decision criteria and is focusing on the future development and use of techniques to weight and score different decision criteria. This article emphasizes the use and future benefit of MCDA.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options.

PubMed

Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

A Multi-Objective Decision-Making Model for Resources Allocation in Humanitarian Relief

DTIC Science & Technology

2007-03-01

Applied Mathematics and Computation 163, 2005, pp756 19. Malczewski, J., GIS and Multicriteria Decision Analysis , John Wiley and Sons, New York... used when interpreting the results of the analysis . (Raimo et al. 2002) (7) Sensitivity analysis Sensitivity analysis in a DA process answers...Budget Scenario Analysis The MILP is solved ( using LINDO 6.1) for high, medium and low budget scenarios in both damage degree levels. Tables 17 and

Using multi-criteria decision analysis to appraise orphan drugs: a systematic review.

PubMed

Friedmann, Carlotta; Levy, Pierre; Hensel, Paul; Hiligsmann, Mickaël

2018-04-01

Multi-criteria decision analysis (MCDA) could potentially solve current methodological difficulties in the appraisal of orphan drugs. Areas covered: We provide an overview of the existing evidence regarding the use of MCDA in the appraisal of orphan drugs worldwide. Three databases (Pubmed, Embase, Web of Science) were searched for English, French and German literature published between January 2000 and April 2017. Full-text articles were supplemented with conference abstracts. A total of seven articles and six abstracts were identified. Expert commentary: The literature suggests that MCDA is increasingly being used in the context of appraising orphan drugs. It has shown itself to be a flexible approach with the potential to assist in decision-making regarding reimbursement for orphan drugs. However, further research regarding its application must be conducted.

A fuzzy MCDM framework based on fuzzy measure and fuzzy integral for agile supplier evaluation

NASA Astrophysics Data System (ADS)

Dursun, Mehtap

2017-06-01

Supply chains need to be agile in order to response quickly to the changes in today's competitive environment. The success of an agile supply chain depends on the firm's ability to select the most appropriate suppliers. This study proposes a multi-criteria decision making technique for conducting an analysis based on multi-level hierarchical structure and fuzzy logic for the evaluation of agile suppliers. The ideal and anti-ideal solutions are taken into consideration simultaneously in the developed approach. The proposed decision approach enables the decision-makers to use linguistic terms, and thus, reduce their cognitive burden in the evaluation process. Furthermore, a hierarchy of evaluation criteria and their related sub-criteria is employed in the presented approach in order to conduct a more effective analysis.

Decision technology.

PubMed

Edwards, W; Fasolo, B

2001-01-01

This review is about decision technology-the rules and tools that help us make wiser decisions. First, we review the three rules that are at the heart of most traditional decision technology-multi-attribute utility, Bayes' theorem, and subjective expected utility maximization. Since the inception of decision research, these rules have prescribed how we should infer values and probabilities and how we should combine them to make better decisions. We suggest how to make best use of all three rules in a comprehensive 19-step model. The remainder of the review explores recently developed tools of decision technology. It examines the characteristics and problems of decision-facilitating sites on the World Wide Web. Such sites now provide anyone who can use a personal computer with access to very sophisticated decision-aiding tools structured mainly to facilitate consumer decision making. It seems likely that the Web will be the mode by means of which decision tools will be distributed to lay users. But methods for doing such apparently simple things as winnowing 3000 options down to a more reasonable number, like 10, contain traps for unwary decision technologists. The review briefly examines Bayes nets and influence diagrams-judgment and decision-making tools that are available as computer programs. It very briefly summarizes the state of the art of eliciting probabilities from experts. It concludes that decision tools will be as important in the 21st century as spreadsheets were in the 20th.

Single-process versus multiple-strategy models of decision making: evidence from an information intrusion paradigm.

PubMed

Söllner, Anke; Bröder, Arndt; Glöckner, Andreas; Betsch, Tilmann

2014-02-01

When decision makers are confronted with different problems and situations, do they use a uniform mechanism as assumed by single-process models (SPMs) or do they choose adaptively from a set of available decision strategies as multiple-strategy models (MSMs) imply? Both frameworks of decision making have gathered a lot of support, but only rarely have they been contrasted with each other. Employing an information intrusion paradigm for multi-attribute decisions from givens, SPM and MSM predictions on information search, decision outcomes, attention, and confidence judgments were derived and tested against each other in two experiments. The results consistently support the SPM view: Participants seemingly using a "take-the-best" (TTB) strategy do not ignore TTB-irrelevant information as MSMs would predict, but adapt the amount of information searched, choose alternative choice options, and show varying confidence judgments contingent on the quality of the "irrelevant" information. The uniformity of these findings underlines the adequacy of the novel information intrusion paradigm and comprehensively promotes the notion of a uniform decision making mechanism as assumed by single-process models. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Real-Time Analysis of a Sensor's Data for Automated Decision Making in an IoT-Based Smart Home.

PubMed

Khan, Nida Saddaf; Ghani, Sayeed; Haider, Sajjad

2018-05-25

IoT devices frequently generate large volumes of streaming data and in order to take advantage of this data, their temporal patterns must be learned and identified. Streaming data analysis has become popular after being successfully used in many applications including forecasting electricity load, stock market prices, weather conditions, etc. Artificial Neural Networks (ANNs) have been successfully utilized in understanding the embedded interesting patterns/behaviors in the data and forecasting the future values based on it. One such pattern is modelled and learned in the present study to identify the occurrence of a specific pattern in a Water Management System (WMS). This prediction aids in making an automatic decision support system, to switch OFF a hydraulic suction pump at the appropriate time. Three types of ANN, namely Multi-Input Multi-Output (MIMO), Multi-Input Single-Output (MISO), and Recurrent Neural Network (RNN) have been compared, for multi-step-ahead forecasting, on a sensor's streaming data. Experiments have shown that RNN has the best performance among three models and based on its prediction, a system can be implemented to make the best decision with 86% accuracy.

A Multi-criteria Decision Analysis System for Prioritizing Sites and Types of Low Impact Development Practices

NASA Astrophysics Data System (ADS)

Song, Jae Yeol; Chung, Eun-Sung

2017-04-01

This study developed a multi-criteria decision analysis framework to prioritize sites and types of low impact development (LID) practices. This framework was systemized as a web-based system coupled with the Storm Water Management Model (SWMM) from the Environmental Protection Agency (EPA). Using the technique for order of preference by similarity to ideal solution (TOPSIS), which is a type of multi-criteria decision-making (MCDM) method, multiple types and sites of designated LID practices are prioritized. This system is named the Water Management Prioritization Module (WMPM) and is an improved version of the Water Management Analysis Module (WMAM) that automatically generates and simulates multiple scenarios of LID design and planning parameters for a single LID type. WMPM can simultaneously determine the priority of multiple LID types and sites. In this study, an infiltration trench and permeable pavement were considered for multiple sub-catchments in South Korea to demonstrate the WMPM procedures. The TOPSIS method was manually incorporated to select the vulnerable target sub-catchments and to prioritize the LID planning scenarios for multiple types and sites considering socio-economic, hydrologic and physical-geometric factors. In this application, the Delphi method and entropy theory were used to determine the subjective and objective weights, respectively. Comparing the ranks derived by this system, two sub-catchments, S16 and S4, out of 18 were considered to be the most suitable places for installing an infiltration trench and porous pavement to reduce the peak and total flow, respectively, considering both socio-economic factors and hydrological effectiveness. WMPM can help policy-makers to objectively develop urban water plans for sustainable development. Keywords: Low Impact Development, Multi-Criteria Decision Analysis, SWMM, TOPSIS, Water Management Prioritization Module (WMPM)

Pharmacists’ Opinions of the Value of CAPE Outcomes in Hiring Decisions

PubMed Central

Marsh, Wallace A.; Castleberry, Ashley N.; Kelley, Katherine A.; Boyce, Eric G.

2017-01-01

Objective. The Hiring Intent Reasoning Examination (HIRE) was designed to explore the utility of the CAPE 2013 outcomes attributes from the perspective of practicing pharmacists, examine how each attribute influences hiring decisions, and identify which of the attributes are perceived as most and least valuable by practicing pharmacists. Methods. An electronic questionnaire was developed and distributed to licensed pharmacists in four states to collect their opinions about 15 CAPE subdomains plus five additional business related attributes. The attributes that respondents identified were: necessary to be a good pharmacist, would impact hiring decisions, most important to them, and in short supply in the applicant pool. Data were analyzed using statistical analysis software to determine the relative importance of each to practicing pharmacists and various subsets of pharmacists. Results. The CAPE subdomains were considered necessary for most jobs by 51% or more of the 3723 respondents (range, 51% to 99%). The necessity for business-related attributes ranged from 21% to 92%. The percentage who would not hire an applicant who did not possess the attribute ranged from 2% to 71.5%; the percentage who considered the attribute most valuable ranged from 0.3% to 35%; and the percentage who felt the attribute was in short supply ranged from 5% to 36%. Opinions varied depending upon gender, practice setting and whether the pharmacist was an employee or employer. Conclusion. The results of this study can be used by faculty and administrators to inform curricular design and emphasis on CAPE domains and business-related education in pharmacy programs. PMID:29367774

Evaluation of stormwater harvesting sites using multi criteria decision methodology

NASA Astrophysics Data System (ADS)

Inamdar, P. M.; Sharma, A. K.; Cook, Stephen; Perera, B. J. C.

2018-07-01

Selection of suitable urban stormwater harvesting sites and associated project planning are often complex due to spatial, temporal, economic, environmental and social factors, and related various other variables. This paper is aimed at developing a comprehensive methodology framework for evaluating of stormwater harvesting sites in urban areas using Multi Criteria Decision Analysis (MCDA). At the first phase, framework selects potential stormwater harvesting (SWH) sites using spatial characteristics in a GIS environment. In second phase, MCDA methodology is used for evaluating and ranking of SWH sites in multi-objective and multi-stakeholder environment. The paper briefly describes first phase of framework and focuses chiefly on the second phase of framework. The application of the methodology is also demonstrated over a case study comprising of the local government area, City of Melbourne (CoM), Australia for the benefit of wider water professionals engaged in this area. Nine performance measures (PMs) were identified to characterise the objectives and system performance related to the eight alternative SWH sites for the demonstration of the application of developed methodology. To reflect the stakeholder interests in the current study, four stakeholder participant groups were identified, namely, water authorities (WA), academics (AC), consultants (CS), and councils (CL). The decision analysis methodology broadly consisted of deriving PROMETHEE II rankings of eight alternative SWH sites in the CoM case study, under two distinct group decision making scenarios. The major innovation of this work is the development and application of comprehensive methodology framework that assists in the selection of potential sites for SWH, and facilitates the ranking in multi-objective and multi-stakeholder environment. It is expected that the proposed methodology will assist the water professionals and managers with better knowledge that will reduce the subjectivity in the selection and evaluation of SWH sites.

Multi Objective Decision Analysis for Assignment Problems

DTIC Science & Technology

2011-03-01

needed data or try to get data from related databases. 2.3.8 Deterministic Analysis In order to determine an overall score for each...The views expressed in this thesis are those of the author and do not reflect the official policy or position of the Turkish Air...DECISION ANALYSIS FOR ASSIGNMENT PROBLEMS THESIS Presented to the Faculty Department of Operational Sciences Graduate School of

Qualitative and quantitative comparison of geostatistical techniques of porosity prediction from the seismic and logging data: a case study from the Blackfoot Field, Alberta, Canada

NASA Astrophysics Data System (ADS)

Maurya, S. P.; Singh, K. H.; Singh, N. P.

2018-05-01

In present study, three recently developed geostatistical methods, single attribute analysis, multi-attribute analysis and probabilistic neural network algorithm have been used to predict porosity in inter well region for Blackfoot field, Alberta, Canada, an offshore oil field. These techniques make use of seismic attributes, generated by model based inversion and colored inversion techniques. The principle objective of the study is to find the suitable combination of seismic inversion and geostatistical techniques to predict porosity and identification of prospective zones in 3D seismic volume. The porosity estimated from these geostatistical approaches is corroborated with the well log porosity. The results suggest that all the three implemented geostatistical methods are efficient and reliable to predict the porosity but the multi-attribute and probabilistic neural network analysis provide more accurate and high resolution porosity sections. A low impedance (6000-8000 m/s g/cc) and high porosity (> 15%) zone is interpreted from inverted impedance and porosity sections respectively between 1060 and 1075 ms time interval and is characterized as reservoir. The qualitative and quantitative results demonstrate that of all the employed geostatistical methods, the probabilistic neural network along with model based inversion is the most efficient method for predicting porosity in inter well region.

Patient perspectives of telemedicine quality

PubMed Central

LeRouge, Cynthia M; Garfield, Monica J; Hevner, Alan R

2015-01-01

Background The purpose of this study was to explore the quality attributes required for effective telemedicine encounters from the perspective of the patient. Methods We used a multi-method (direct observation, focus groups, survey) field study to collect data from patients who had experienced telemedicine encounters. Multi-perspectives (researcher and provider) were used to interpret a rich set of data from both a research and practice perspective. Results The result of this field study is a taxonomy of quality attributes for telemedicine service encounters that prioritizes the attributes from the patient perspective. We identify opportunities to control the level of quality for each attribute (ie, who is responsible for control of each attribute and when control can be exerted in relation to the encounter process). This analysis reveals that many quality attributes are in the hands of various stakeholders, and all attributes can be addressed proactively to some degree before the encounter begins. Conclusion Identification of the quality attributes important to a telemedicine encounter from a patient perspective enables one to better design telemedicine encounters. This preliminary work not only identifies such attributes, but also ascertains who is best able to address quality issues prior to an encounter. For practitioners, explicit representation of the quality attributes of technology-based systems and processes and insight on controlling key attributes are essential to implementation, utilization, management, and common understanding. PMID:25565781

Characterising volcanic cycles at Soufriere Hills Volcano, Montserrat: Time series analysis of multi-parameter satellite data

NASA Astrophysics Data System (ADS)

Flower, Verity J. B.; Carn, Simon A.

2015-10-01

The identification of cyclic volcanic activity can elucidate underlying eruption dynamics and aid volcanic hazard mitigation. Whilst satellite datasets are often analysed individually, here we exploit the multi-platform NASA A-Train satellite constellation to cross-correlate cyclical signals identified using complementary measurement techniques at Soufriere Hills Volcano (SHV), Montserrat. In this paper we present a Multi-taper (MTM) Fast Fourier Transform (FFT) analysis of coincident SO2 and thermal infrared (TIR) satellite measurements at SHV facilitating the identification of cyclical volcanic behaviour. These measurements were collected by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) (respectively) in the A-Train. We identify a correlating cycle in both the OMI and MODIS data (54-58 days), with this multi-week feature attributable to episodes of dome growth. The 50 day cycles were also identified in ground-based SO2 data at SHV, confirming the validity of our analysis and further corroborating the presence of this cycle at the volcano. In addition a 12 day cycle was identified in the OMI data, previously attributed to variable lava effusion rates on shorter timescales. OMI data also display a one week (7-8 days) cycle attributable to cyclical variations in viewing angle resulting from the orbital characteristics of the Aura satellite. Longer period cycles possibly relating to magma intrusion were identified in the OMI record (102-, 121-, and 159 days); in addition to a 238-day cycle identified in the MODIS data corresponding to periodic destabilisation of the lava dome. Through the analysis of reconstructions generated from cycles identified in the OMI and MODIS data, periods of unrest were identified, including the major dome collapse of 20th May 2006 and significant explosive event of 3rd January 2009. Our analysis confirms the potential for identification of cyclical volcanic activity through combined analysis of satellite data, which would be of particular value at poorly monitored volcanic systems.

EVMDD-Based Analysis and Diagnosis Methods of Multi-State Systems with Multi-State Components

DTIC Science & Technology

2014-01-01

Springer-Verlag New York Inc., 2001. [7] T. Kam, T. Villa, R. K. Brayton , and A. L. Sangiovanni-Vincentelli, “Multi-valued deci- sion diagrams: Theory and...Decision Diagram Techniques for Micro- and Nanoelectronic Design, CRC Press, Taylor & Francis Group, 2006. [22] X. Zang, D. Wang, H. Sun, and K. S. Trivedi

Multi-Attribute Sequential Search

ERIC Educational Resources Information Center

Bearden, J. Neil; Connolly, Terry

2007-01-01

This article describes empirical and theoretical results from two multi-attribute sequential search tasks. In both tasks, the DM sequentially encounters options described by two attributes and must pay to learn the values of the attributes. In the "continuous" version of the task the DM learns the precise numerical value of an attribute when she…

Multi-Task Learning with Low Rank Attribute Embedding for Multi-Camera Person Re-Identification.

PubMed

Su, Chi; Yang, Fan; Zhang, Shiliang; Tian, Qi; Davis, Larry Steven; Gao, Wen

2018-05-01

We propose Multi-Task Learning with Low Rank Attribute Embedding (MTL-LORAE) to address the problem of person re-identification on multi-cameras. Re-identifications on different cameras are considered as related tasks, which allows the shared information among different tasks to be explored to improve the re-identification accuracy. The MTL-LORAE framework integrates low-level features with mid-level attributes as the descriptions for persons. To improve the accuracy of such description, we introduce the low-rank attribute embedding, which maps original binary attributes into a continuous space utilizing the correlative relationship between each pair of attributes. In this way, inaccurate attributes are rectified and missing attributes are recovered. The resulting objective function is constructed with an attribute embedding error and a quadratic loss concerning class labels. It is solved by an alternating optimization strategy. The proposed MTL-LORAE is tested on four datasets and is validated to outperform the existing methods with significant margins.

Strategic Planning in Population Health and Public Health Practice: A Call to Action for Higher Education.

PubMed

Phelps, Charles; Madhavan, Guruprasad; Rappuoli, Rino; Levin, Scott; Shortliffe, Edward; Colwell, Rita

2016-03-01

Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning. Public health agencies' current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost-effectiveness. As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost-effectiveness analyses widely recommended and used for public health planning. Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost-effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Our work employed a multicriteria systems analysis approach--specifically, multiattribute utility theory--to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost-effectiveness analysis approach. (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost-effectiveness analysis. (2) More sophisticated systems-level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost-effectiveness analysis. The Strategic Multi-Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support. © 2016 Milbank Memorial Fund.

Parental Influences, Career Decision-Making Attributions, and Self-Efficacy: Differences for Men and Women?

ERIC Educational Resources Information Center

Lease, Suzanne H.; Dahlbeck, David T.

2009-01-01

This study investigated the relations of maternal and paternal attachment, parenting styles, and career locus of control to college students' career decision self-efficacy and explored whether these relations differed by student gender. Data analysis using hierarchical multiple regression revealed that attachment was relevant for females' career…

Multi-disciplinary decision making in general practice.

PubMed

Kirby, Ann; Murphy, Aileen; Bradley, Colin

2018-04-09

Purpose Internationally, healthcare systems are moving towards delivering care in an integrated manner which advocates a multi-disciplinary approach to decision making. Such an approach is formally encouraged in the management of Atrial Fibrillation patients through the European Society of Cardiology guidelines. Since the emergence of new oral anticoagulants switching between oral anticoagulants (OACs) has become prevalent. This case study considers the role of multi-disciplinary decision making, given the complex nature of the agents. The purpose of this paper is to explore Irish General Practitioners' (GPs) experience of switching between all OACs for Arial Fibrillation (AF) patients; prevalence of multi-disciplinary decision making in OAC switching decisions and seeks to determine the GP characteristics that appear to influence the likelihood of multi-disciplinary decision making. Design/methodology/approach A probit model is used to determine the factors influencing multi-disciplinary decision making and a multinomial logit is used to examine the factors influencing who is involved in the multi-disciplinary decisions. Findings Results reveal that while some multi-disciplinary decision-making is occurring (64 per cent), it is not standard practice despite international guidelines on integrated care. Moreover, there is a lack of patient participation in the decision-making process. Female GPs and GPs who have initiated prescriptions for OACs are more likely to engage in multi-disciplinary decision-making surrounding switching OACs amongst AF patients. GPs with training practices were less likely to engage with cardiac consultants and those in urban areas were more likely to engage with other (non-cardiac) consultants. Originality/value For optimal decision making under uncertainty multi-disciplinary decision-making is needed to make a more informed judgement and to improve treatment decisions and reduce the opportunity cost of making the wrong decision.

How consumers choose health insurance.

PubMed

Chakraborty, G; Ettenson, R; Gaeth, G

1994-01-01

The authors used choice-based conjoint analysis to model consumers' decision processes when evaluating and selecting health insurance in a multiplan environment. Results indicate that consumer choice is affected by as many as 19 attributes, some of which have received little attention in previous studies. Moreover, the importance of the attributes varies across different demographic segments, giving marketers several targeting opportunities.

Arctic Collaborative Environment: A New Multi-National Partnership for Arctic Science and Decision Support

NASA Technical Reports Server (NTRS)

Laymon, Charles A,; Kress, Martin P.; McCracken, Jeff E.; Spehn, Stephen L.; Tanner, Steve

2011-01-01

The Arctic Collaborative Environment (ACE) project is a new international partnership for information sharing to meet the challenges of addressing Arctic. The goal of ACE is to create an open source, web-based, multi-national monitoring, analysis, and visualization decision-support system for Arctic environmental assessment, management, and sustainability. This paper will describe the concept, system architecture, and data products that are being developed and disseminated among partners and independent users through remote access.

Blame attribution as a moderator of perceptions of sexual orientation-based hate crimes.

PubMed

Cramer, Robert J; Chandler, Joseph F; Wakeman, Emily E

2010-05-01

Blame attribution is a valuable mechanism explaining decision making. However, present literature mainly employs blame attribution as a dependent variable. The shortcoming of this fact is that blame attribution offers a potentially valuable explanatory mechanism for decision making. The authors designed two studies to investigate blame attribution as a moderator of sentencing decisions in sexual orientation-based hate crimes. Study 1 showed that mock jurors punished perpetrators of hate crimes more severely than a control condition. Also, degree of victim blame influenced punitive decision making. In Study 2, mock jurors extended findings that perpetrators of hate crimes are more harshly punished than those of other types of crimes. Victim and perpetrator blame failed to moderate decision making in this more complex scenario. Results are discussed in relation to hate crimes definitions and attribution theory.

Multiple attribute decision making model and application to food safety risk evaluation.

PubMed

Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

2017-01-01

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Robotic intelligence kernel

DOEpatents

Bruemmer, David J [Idaho Falls, ID

2009-11-17

A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

Multiple stakeholders in multi-criteria decision-making in the context of Municipal Solid Waste Management: A review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh

2015-01-15

Highlights: • We review Municipal Solid Waste Management studies with focus on multiple stakeholders. • We focus on studies with multi-criteria decision analysis methods and discover their trends. • Most studies do not offer solutions for situations where stakeholders compete for more benefits or have unequal voting powers. • Governments and experts are the most participated stakeholders and AHP is the most dominant method. - Abstract: Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, andmore » finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deshmukh, Ranjit; Wu, Grace

The MapRE (Multi-criteria Analysis for Planning Renewable Energy) GIS (Geographic Information Systems) Tools are a set of ArcGIS tools to a) conduct site suitability analysis for wind and solar resources using inclusion and exclusion criteria, and create resource maps, b) create project opportunity areas and compute various attributes such as cost, distances to existing and planned infrastructure. and environmental impact factors; and c) calculate and update various attributes for already processed renewable energy zones. In addition, MapRE data sets are geospatial data of renewable energy project opportunity areas and zones with pre-calculated attributes for several countries. These tools and datamore » are available at mapre.lbl.gov.« less

Multi - party Game Analysis of Coal Industry and Industry Regulation Policy Optimization

NASA Astrophysics Data System (ADS)

Jiang, Tianqi

2018-01-01

In the face of the frequent occurrence of coal mine safety accidents, this paper analyses the relationship between central and local governments, coal mining enterprises and miners from the perspective of multi - group game. In the actual production, the decision of one of the three groups can affect the game strategy of the other of the three, so we should assume the corresponding game order. In this order, the game analysis of the income and decision of the three is carried out, and the game decision of the government, the enterprise and the workers is obtained through the establishment of the benefit matrix and so on. And then on the existing system to optimize the coal industry regulation proposed practical recommendations to reduce the frequency of industry safety accidents, optimize the industry production environment.

Qualitative analysis of MTEM response using instantaneous attributes

NASA Astrophysics Data System (ADS)

Fayemi, Olalekan; Di, Qingyun

2017-11-01

This paper introduces new technique for qualitative analysis of multi-transient electromagnetic (MTEM) earth impulse response over complex geological structures. Instantaneous phase and frequency attributes were used in place of the conventional common offset section for improved qualitative interpretation of MTEM data by obtaining more detailed information from the earth impulse response. The instantaneous attributes were used to describe the lateral variation in subsurface resistivity and the visible geological structure with respect to given offsets. Instantaneous phase attribute was obtained by converting the impulse response into a complex form using the Hilbert transform. Conversely, the polynomial phase difference (PPD) estimator was favored over the center finite difference (CFD) approximation method in calculating the instantaneous frequency attribute because it is computationally efficient and has the ability to give a smooth variation of the instantaneous frequency over a common offset section. The observed results from the instantaneous attributes were in good agreement with both the subsurface model used and the apparent resistivity section obtained from the MTEM earth impulse response. Hence, this study confirms the capability of both instantaneous phase and frequency attributes as highly effective tools for MTEM qualitative analysis.

Use of multiattribute utility theory for formulary management in a health system.

PubMed

Chung, Seonyoung; Kim, Sooyon; Kim, Jeongmee; Sohn, Kieho

2010-01-15

The application, utility, and flexibility of the multiattribute utility theory (MAUT) when used as a formulary decision methodology in a Korean medical center were evaluated. A drug analysis model using MAUT consisting of 10 steps was designed for two drug classes of dihydropyridine calcium channel blockers (CCBs) and angiotensin II receptor blockers (ARBs). These two drug classes contain the most diverse agents among cardiovascular drugs on Samsung Medical Center's drug formulary. The attributes identified for inclusion in the drug analysis model were effectiveness, safety, patient convenience, and cost, with relative weights of 50%, 30%, 10%, and 10%, respectively. The factors were incorporated into the model to quantify the contribution of each attribute. For each factor, a utility scale of 0-100 was established, and the total utility score for each alternative was calculated. An attempt was made to make the model adaptable to changing health care and regulatory circumstances. The analysis revealed amlodipine besylate to be an alternative agent, with the highest total utility score among the dihydropyridine CCBs, while barnidipine hydrochloride had the lowest score. For ARBs, losartan potassium had the greatest total utility score, while olmesartan medoxomil had the lowest. A drug analysis model based on the MAUT was successfully developed and used in making formulary decisions for dihydropyridine CCBs and ARBs for a Korean health system. The model incorporates sufficient utility and flexibility of a drug's attributes and can be used as an alternative decision-making tool for formulary management in health systems.

Team performance in networked supervisory control of unmanned air vehicles: effects of automation, working memory, and communication content.

PubMed

McKendrick, Ryan; Shaw, Tyler; de Visser, Ewart; Saqer, Haneen; Kidwell, Brian; Parasuraman, Raja

2014-05-01

Assess team performance within a net-worked supervisory control setting while manipulating automated decision aids and monitoring team communication and working memory ability. Networked systems such as multi-unmanned air vehicle (UAV) supervision have complex properties that make prediction of human-system performance difficult. Automated decision aid can provide valuable information to operators, individual abilities can limit or facilitate team performance, and team communication patterns can alter how effectively individuals work together. We hypothesized that reliable automation, higher working memory capacity, and increased communication rates of task-relevant information would offset performance decrements attributed to high task load. Two-person teams performed a simulated air defense task with two levels of task load and three levels of automated aid reliability. Teams communicated and received decision aid messages via chat window text messages. Task Load x Automation effects were significant across all performance measures. Reliable automation limited the decline in team performance with increasing task load. Average team spatial working memory was a stronger predictor than other measures of team working memory. Frequency of team rapport and enemy location communications positively related to team performance, and word count was negatively related to team performance. Reliable decision aiding mitigated team performance decline during increased task load during multi-UAV supervisory control. Team spatial working memory, communication of spatial information, and team rapport predicted team success. An automated decision aid can improve team performance under high task load. Assessment of spatial working memory and the communication of task-relevant information can help in operator and team selection in supervisory control systems.

A Moral (Normative) Framework for the Judgment of Actions and Decisions in the Construction Industry and Engineering: Part II.

PubMed

Alkhatib, Omar J

2017-12-01

The construction industry is typically characterized as a fragmented, multi-organizational setting in which members from different technical backgrounds and moral values join together to develop a particular business or project. The most challenging obstacle in the construction process is to achieve a successful practice and to identify and apply an ethical framework to manage the behavior of involved specialists and contractors and to ensure the quality of all completed construction activities. The framework should reflect a common moral ground for myriad people involved in this process to survive and compete ethically in today's turbulent construction market. This study establishes a framework for moral judgment of behavior and actions conducted in the construction process. The moral framework provides the basis of judging actions as "moral" or "immoral" based on three levels of moral accountability: personal, professional, and social. The social aspect of the proposed framework is developed primarily from the essential attributes of normative business decision-making models identified in the literature review and subsequently incorporates additional attributes related to professional and personal moral values. The normative decision-making models reviewed are based primarily on social attributes as related to moral theories (e.g., utilitarianism, duty, rights, virtue, etc.). The professional and moral attributes are established by identifying a set of common moral values recognized by professionals in the construction industry and required to prevent common construction breaches. The moral framework presented here is the complementary part of the ethical framework developed in Part I of this article and is based primarily on the personal behavior or the moral aspect of professional responsibility. The framework can be implemented as a form of preventive personal ethics, which would help avoid ethical dilemmas and moral implications in the first place. Furthermore, the moral framework can be considered as a decision-making model to guide actions and improve the moral reasoning process, which would help individuals think through possible implications and the consequences of ethical and moral issues in the construction industry.

Harnessing ecosystem models and multi-criteria decision analysis for the support of forest management.

PubMed

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Harnessing Ecosystem Models and Multi-Criteria Decision Analysis for the Support of Forest Management

NASA Astrophysics Data System (ADS)

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Knowledge based system and decision making methodologies in materials selection for aircraft cabin metallic structures

NASA Astrophysics Data System (ADS)

Adhikari, Pashupati Raj

Materials selection processes have been the most important aspects in product design and development. Knowledge-based system (KBS) and some of the methodologies used in the materials selection for the design of aircraft cabin metallic structures are discussed. Overall aircraft weight reduction means substantially less fuel consumption. Part of the solution to this problem is to find a way to reduce overall weight of metallic structures inside the cabin. Among various methodologies of materials selection using Multi Criterion Decision Making (MCDM) techniques, a few of them are demonstrated with examples and the results are compared with those obtained using Ashby's approach in materials selection. Pre-defined constraint values, mainly mechanical properties, are employed as relevant attributes in the process. Aluminum alloys with high strength-to-weight ratio have been second-to-none in most of the aircraft parts manufacturing. Magnesium alloys that are much lighter in weight as alternatives to the Al-alloys currently in use in the structures are tested using the methodologies and ranked results are compared. Each material attribute considered in the design are categorized as benefit and non-benefit attribute. Using Ashby's approach, material indices that are required to be maximized for an optimum performance are determined, and materials are ranked based on the average of consolidated indices ranking. Ranking results are compared for any disparity among the methodologies.

Choices Behind Numbers: a Review of the Major Air Pollution Health Impact Assessments in Europe.

PubMed

Malmqvist, E; Oudin, A; Pascal, M; Medina, S

2018-03-01

The aim of this review is to identify the key contextual and methodological differences in health impact assessments (HIA) of ambient air pollution performed for Europe. We limited our review to multi-country reviews. An additional aim is to quantify some of these differences by applying them in a HIA template in three European cities. Several HIAs of ambient air pollution have been performed for Europe, and their key results have been largely disseminated. Different studies have, however, come up with substantial differences in attributed health effects. It is of importance to review the background contributing to these differences and to quantify their importance for decision makers who will use them. We identified several methodological differences that could explain the discrepancy behind the number of attributable deaths or years of life lost. The main differences are due to the exposure-response functions chosen, the ways of assessing air pollution levels, the air pollution scenarios and the study population. In the quantification part, we found that using risk estimates from the European Study of Cohorts for Air Pollution Effects (ESCAPE) instead of the American Cancer Society (ACS) study could nearly double the attributable burden of ambient air pollution. This study provides some insights into the differential results in previously published HIAs on air pollution in Europe. These results are important for stakeholders in order to make informed decisions.

Good-parent beliefs of parents of seriously ill children.

PubMed

Feudtner, Chris; Walter, Jennifer K; Faerber, Jennifer A; Hill, Douglas L; Carroll, Karen W; Mollen, Cynthia J; Miller, Victoria A; Morrison, Wynne E; Munson, David; Kang, Tammy I; Hinds, Pamela S

2015-01-01

Parents' beliefs about what they need to do to be a good parent when their children are seriously ill influence their medical decisions, and better understanding of these beliefs may improve decision support. To assess parents' perceptions regarding the relative importance of 12 good-parent attributes. A cross-sectional, discrete-choice experiment was conducted at a children's hospital. Participants included 200 parents of children with serious illness. Ratings of 12 good-parent attributes, with subsequent use of latent class analysis to identify groups of parents with similar ratings of attributes, and ascertainment of whether membership in a particular group was associated with demographic or clinical characteristics. The highest-ranked good-parent attribute was making sure that my child feels loved, followed by focusing on my child's health, making informed medical care decisions, and advocating for my child with medical staff. We identified 4 groups of parents with similar patterns of good-parent-attribute ratings, which we labeled as: child feels loved (n=68), child's health (n=56), advocacy and informed (n=55), and spiritual well-being (n=21). Compared with the other groups, the child's health group reported more financial difficulties, was less educated, and had a higher proportion of children with new complex, chronic conditions. Parents endorse a broad range of beliefs that represent what they perceive they should do to be a good parent for their seriously ill child. Common patterns of how parents prioritize these attributes exist, suggesting future research to better understand the origins and development of good-parent beliefs among these parents. More important, engaging parents individually regarding what they perceive to be the core duties they must fulfill to be a good parent may enable more customized and effective decision support.

A new spatial multi-criteria decision support tool for site selection for implementation of managed aquifer recharge.

PubMed

Rahman, M Azizur; Rusteberg, Bernd; Gogu, R C; Lobo Ferreira, J P; Sauter, Martin

2012-05-30

This study reports the development of a new spatial multi-criteria decision analysis (SMCDA) software tool for selecting suitable sites for Managed Aquifer Recharge (MAR) systems. The new SMCDA software tool functions based on the combination of existing multi-criteria evaluation methods with modern decision analysis techniques. More specifically, non-compensatory screening, criteria standardization and weighting, and Analytical Hierarchy Process (AHP) have been combined with Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA). This SMCDA tool may be implemented with a wide range of decision maker's preferences. The tool's user-friendly interface helps guide the decision maker through the sequential steps for site selection, those steps namely being constraint mapping, criteria hierarchy, criteria standardization and weighting, and criteria overlay. The tool offers some predetermined default criteria and standard methods to increase the trade-off between ease-of-use and efficiency. Integrated into ArcGIS, the tool has the advantage of using GIS tools for spatial analysis, and herein data may be processed and displayed. The tool is non-site specific, adaptive, and comprehensive, and may be applied to any type of site-selection problem. For demonstrating the robustness of the new tool, a case study was planned and executed at Algarve Region, Portugal. The efficiency of the SMCDA tool in the decision making process for selecting suitable sites for MAR was also demonstrated. Specific aspects of the tool such as built-in default criteria, explicit decision steps, and flexibility in choosing different options were key features, which benefited the study. The new SMCDA tool can be augmented by groundwater flow and transport modeling so as to achieve a more comprehensive approach to the selection process for the best locations of the MAR infiltration basins, as well as the locations of recovery wells and areas of groundwater protection. The new spatial multicriteria analysis tool has already been implemented within the GIS based Gabardine decision support system as an innovative MAR planning tool. Copyright © 2012 Elsevier Ltd. All rights reserved.

Ranking of pharmaceuticals detected in the environment: aggregation and weighting procedures.

PubMed

Voigt, Kristina; Brüggemann, Rainer

2008-12-01

Pharmaceuticals are omnipresent in waste-water world-wide. Research has shown that many pharmaceuticals are not completely removed during wastewater treatment, and as a result, this has led to their occurrence being reported in waste water treatment plant effluents, rivers and lakes, and more rarely in groundwater and in drinking water. Hence, it is only logical that pharmaceutical residues in the environment and their potential toxic effects have been recognized as one of the emerging research areas in environmental chemistry. A lack of data, especially ecotoxicological and fate data on pharmaceuticals, is evident. The extent to which data are missing should therefore be looked upon in more detail in order to trigger further political steps in performing studies concerning the risk assessment of pharmaceuticals in the environment. In this investigation, we evaluate the data-availability of 16 pharmaceuticals in 17 Internet databases which means we examine a 16 (objects) x 17 (attributes) data-matrix. The consideration of the chosen pharmaceutical in databases is coded 0 = not available, or 1 = available. For the evaluation of the data-matrix, we apply the multi-criteria decision method named METEOR (Method of Evaluation by Order Theory). In contrast to conventional multi-criteria decision aids, like the well-known PROMETHEE, AHP, SMART, ORESTE as well as different versions of ELECTRE, we support the basic consideration of environmetrics: let first the data speak and let us then include subjective preferences in order to get a unique decision. The basis of METEOR is a data-matrix in which the objects are characterized by a set of attributes (indicators). By means of the attributes, a partial order is derived. In the subsequent steps, attributes are aggregated by a weighting procedure, allowing a high degree of involvement of experts, stakeholders and other participants. All conducted approaches show that the data-situation on the chosen test-set of 16 well-known and highly produced pharmaceuticals is far from being satisfactory. For the two well-known pharmaceuticals roxithomycin (antibiotic) and diatrizoate (contrast media), the data-situation is extremely bad, independent of how the weighting is performed. The data-availability for diatrizoate is a little better. The best data coverage is detected for the chemicals carbamazepine, diazepam, ethinyl estradiol, 5-fluorouracil, and phenazone. The issue of pharmaceuticals in the environment and the unavailability of data necessitate much closer communication between science and medical healthcare and politicians in the future.

Contribution of the Multi Attribute Value Theory to conflict resolution in groundwater management. Application to the Mancha Oriental groundwater system, Spain

NASA Astrophysics Data System (ADS)

Apperl, B.; Andreu, J.; Karjalainen, T. P.; Pulido-Velazquez, M.

2014-09-01

The implementation of the EU Water Framework Directive demands participatory water resource management approaches. Decision making in groundwater quantity and quality management is complex because of the existence of many independent actors, heterogeneous stakeholder interests, multiple objectives, different potential policies, and uncertain outcomes. Conflicting stakeholder interests have been often identified as an impediment to the realization and success of water regulations and policies. The management of complex groundwater systems requires clarifying stakeholders' positions (identifying stakeholders preferences and values), improving transparency with respect to outcomes of alternatives, and moving the discussion from the selection of alternatives towards definition of fundamental objectives (value-thinking approach), what facilitates negotiation. The aims of the study are to analyse the potential of the multi attribute value theory for conflict resolution in groundwater management and to evaluate the benefit of stakeholder incorporation in the different stages of the planning process to find an overall satisfying solution for groundwater management. The research was conducted in the Mancha Oriental groundwater system (Spain), subject to an intensive use of groundwater for irrigation. A complex set of objectives and attributes were defined, and the management alternatives were created by a combination of different fundamental actions, considering different implementation stages and future changes in water resources availability. Interviews were conducted with representative stakeholder groups using an interactive platform, showing simultaneously the consequences of changes of preferences to the alternative ranking. Results show that the acceptation of alternatives depends strongly on the combination of measures and the implementation stages. Uncertainties of the results were notable but did not influence heavily on the alternative ranking. The expected reduction of future groundwater resources by climate change increases the conflict potential. The implementation of the method to a very complex case study, with many conflicting objectives and alternatives and uncertain outcomes, including future scenarios under water limiting conditions, illustrate the potential of the method for supporting management decisions.

Contribution of the multi-attribute value theory to conflict resolution in groundwater management - application to the Mancha Oriental groundwater system, Spain

NASA Astrophysics Data System (ADS)

Apperl, B.; Pulido-Velazquez, M.; Andreu, J.; Karjalainen, T. P.

2015-03-01

The implementation of the EU Water Framework Directive demands participatory water resource management approaches. Decision making in groundwater quantity and quality management is complex because of the existence of many independent actors, heterogeneous stakeholder interests, multiple objectives, different potential policies, and uncertain outcomes. Conflicting stakeholder interests have often been identified as an impediment to the realisation and success of water regulations and policies. The management of complex groundwater systems requires the clarification of stakeholders' positions (identifying stakeholder preferences and values), improving transparency with respect to outcomes of alternatives, and moving the discussion from the selection of alternatives towards the definition of fundamental objectives (value-thinking approach), which facilitates negotiation. The aims of the study are to analyse the potential of the multi-attribute value theory for conflict resolution in groundwater management and to evaluate the benefit of stakeholder incorporation into the different stages of the planning process, to find an overall satisfying solution for groundwater management. The research was conducted in the Mancha Oriental groundwater system (Spain), subject to intensive use of groundwater for irrigation. A complex set of objectives and attributes was defined, and the management alternatives were created by a combination of different fundamental actions, considering different implementation stages and future changes in water resource availability. Interviews were conducted with representative stakeholder groups using an interactive platform, showing simultaneously the consequences of changes in preferences to the alternative ranking. Results show that the approval of alternatives depends strongly on the combination of measures and the implementation stages. Uncertainties in the results were notable, but did not influence the alternative ranking heavily. The expected reduction in future groundwater resources by climate change increases the conflict potential. The implementation of the method in a very complex case study, with many conflicting objectives and alternatives and uncertain outcomes, including future scenarios under water limiting conditions, illustrates the potential of the method for supporting management decisions.

Stakeholder engagement in dredged material management decisions.

PubMed

Collier, Zachary A; Bates, Matthew E; Wood, Matthew D; Linkov, Igor

2014-10-15

Dredging and disposal issues often become controversial with local stakeholders because of their competing interests. These interests tend to manifest themselves in stakeholders holding onto entrenched positions, and deadlock can result without a methodology to move the stakeholder group past the status quo. However, these situations can be represented as multi-stakeholder, multi-criteria decision problems. In this paper, we describe a case study in which multi-criteria decision analysis was implemented in a multi-stakeholder setting in order to generate recommendations on dredged material placement for Long Island Sound's Dredged Material Management Plan. A working-group of representatives from various stakeholder organizations was formed and consulted to help prioritize sediment placement sites for each dredging center in the region by collaboratively building a multi-criteria decision model. The resulting model framed the problem as several alternatives, criteria, sub-criteria, and metrics relevant to stakeholder interests in the Long Island Sound region. An elicitation of values, represented as criteria weights, was then conducted. Results show that in general, stakeholders tended to agree that all criteria were at least somewhat important, and on average there was strong agreement on the order of preferences among the diverse groups of stakeholders. By developing the decision model iteratively with stakeholders as a group and soliciting their preferences, the process sought to increase stakeholder involvement at the front-end of the prioritization process and lead to increased knowledge and consensus regarding the importance of site-specific criteria. Published by Elsevier B.V.

Incorporating ecosystem function concept in environmental planning and decision making by means of multi-criteria evaluation: the case-study of Kalloni, Lesbos, Greece.

PubMed

Oikonomou, Vera; Dimitrakopoulos, Panayiotis G; Troumbis, Andreas Y

2011-01-01

Nature provides life-support services which do not merely constitute the basis for ecosystem integrity but also benefit human societies. The importance of such multiple outputs is often ignored or underestimated in environmental planning and decision making. The economic valuation of ecosystem functions or services has been widely used to make these benefits economically visible and thus address this deficiency. Alternatively, the relative importance of the components of ecosystem value can be identified and compared by means of multi-criteria evaluation. Hereupon, this article proposes a conceptual framework that couples ecosystem function analysis, multi criteria evaluation and social research methodologies for introducing an ecosystem function-based planning and management approach. The framework consists of five steps providing the structure of a participative decision making process which is then tested and ratified, by applying the discrete multi-criteria method NAIADE, in the Kalloni Natura 2000 site, on Lesbos, Greece. Three scenarios were developed and evaluated with regard to their impacts on the different types of ecosystem functions and the social actors' value judgements. A conflict analysis permitted the better elaboration of the different views, outlining the coalitions formed in the local community and shaping the way towards reaching a consensus.

Incorporating Ecosystem Function Concept in Environmental Planning and Decision Making by Means of Multi-Criteria Evaluation: The Case-Study of Kalloni, Lesbos, Greece

NASA Astrophysics Data System (ADS)

Oikonomou, Vera; Dimitrakopoulos, Panayiotis G.; Troumbis, Andreas Y.

2011-01-01

Nature provides life-support services which do not merely constitute the basis for ecosystem integrity but also benefit human societies. The importance of such multiple outputs is often ignored or underestimated in environmental planning and decision making. The economic valuation of ecosystem functions or services has been widely used to make these benefits economically visible and thus address this deficiency. Alternatively, the relative importance of the components of ecosystem value can be identified and compared by means of multi-criteria evaluation. Hereupon, this article proposes a conceptual framework that couples ecosystem function analysis, multi criteria evaluation and social research methodologies for introducing an ecosystem function-based planning and management approach. The framework consists of five steps providing the structure of a participative decision making process which is then tested and ratified, by applying the discrete multi-criteria method NAIADE, in the Kalloni Natura 2000 site, on Lesbos, Greece. Three scenarios were developed and evaluated with regard to their impacts on the different types of ecosystem functions and the social actors' value judgements. A conflict analysis permitted the better elaboration of the different views, outlining the coalitions formed in the local community and shaping the way towards reaching a consensus.

Theory of the decision/problem state

NASA Technical Reports Server (NTRS)

Dieterly, D. L.

1980-01-01

A theory of the decision-problem state was introduced and elaborated. Starting with the basic model of a decision-problem condition, an attempt was made to explain how a major decision-problem may consist of subsets of decision-problem conditions composing different condition sequences. In addition, the basic classical decision-tree model was modified to allow for the introduction of a series of characteristics that may be encountered in an analysis of a decision-problem state. The resulting hierarchical model reflects the unique attributes of the decision-problem state. The basic model of a decision-problem condition was used as a base to evolve a more complex model that is more representative of the decision-problem state and may be used to initiate research on decision-problem states.

Attributions of responsibility and affective reactions to decision outcomes.

PubMed

Zeelenberg, M; van der Pligt, J; de Vries, N K

2000-06-01

Immediate affective reactions to outcomes are more intense following decisions to act than following decisions not to act. This finding holds for both positive and negative outcomes. We relate this "actor-effect" to attribution theory and argue that decision makers are seen as more responsible for outcomes when these are the result of a decision to act as compared to a decision not to act. Experiment 1 (N = 80) tests the main assumption underlying our reasoning and shows that affective reactions to decision outcomes are indeed more intense when the decision maker is seen as more responsible. Experiment 2 (N = 40) tests whether the actor effect can be predicted on the basis of differential attributions following action and inaction. Participants read vignettes in which active and passive actors obtained a positive or negative outcome. Action resulted in more intense affect than inaction, and positive outcomes resulted in more intense affect than negative outcomes. Experiment 2 further shows that responsibility attributions and affective reactions to outcomes are highly correlated; that is, more extreme affective reactions are associated with more internal attributions. We discuss the implications for research on post-decisional reactions.

Consumer preferences for general practitioner services.

PubMed

Morrison, Mark; Murphy, Tom; Nalder, Craig

2003-01-01

This study focuses on segmenting the market for General Practitioner services in a regional setting. Using factor analysis, five main service attributes are identified. These are clear communication, ongoing doctor-patient relationship, same gender as the patient, provides advice to the patient, and empowers the patient to make his/her own decisions. These service attributes are used as a basis for market segmentation, using both socio-demographic variables and cluster analysis. Four distinct market segments are identified, with varying degrees of viability in terms of target marketing.

Decision precision or holistic heuristic?: Insights on on-site selection of student nurses and midwives.

PubMed

Macduff, Colin; Stephen, Audrey; Taylor, Ruth

2016-01-01

Concerns about quality of care delivery in the UK have led to more scrutiny of criteria and methods for the selection of student nurses. However few substantive research studies of on-site selection processes exist. This study elicited and interpreted perspectives on interviewing processes and related decision making involved in on-site selection of student nurses and midwives. Individual and focus group interviews were undertaken with 36 lecturers, 5 clinical staff and 72 students from seven Scottish universities. Enquiry focused primarily on interviewing of candidates on-site. Qualitative content analysis was used as a primary strategy, followed by in-depth thematic analysis. Students had very mixed experiences of interview processes. Staff typically took into account a range of candidate attributes that they valued in order to achieve holistic assessments. These included: interpersonal skills, team working, confidence, problem-solving, aptitude for caring, motivations, and commitment. Staff had mixed views of the validity and reliability of interview processes. A holistic heuristic for overall decision making predominated over belief in the precision of, and evidence base for, particular attribute measurement processes. While the development of measurement tools for particular attributes continues apace, tension between holism and precision is likely to persist within on-site selection procedures. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Real-time detection of quality of Chinese materia medica: strategy of NIR model evaluation].

PubMed

Wu, Zhi-sheng; Shi, Xin-yuan; Xu, Bing; Dai, Xing-xing; Qiao, Yan-jiang

2015-07-01

The definition of critical quality attributes of Chinese materia medica ( CMM) was put forward based on the top-level design concept. Nowadays, coupled with the development of rapid analytical science, rapid assessment of critical quality attributes of CMM was firstly carried out, which was the secondary discipline branch of CMM. Taking near infrared (NIR) spectroscopy as an example, which is a rapid analytical technology in pharmaceutical process over the past decade, systematic review is the chemometric parameters in NIR model evaluation. According to the characteristics of complexity of CMM and trace components analysis, a multi-source information fusion strategy of NIR model was developed for assessment of critical quality attributes of CMM. The strategy has provided guideline for NIR reliable analysis in critical quality attributes of CMM.

Implementing interactive decision support: A case for combining cyberinfrastructure, data fusion, and social process to mobilize scientific knowledge in sustainability problems

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2014-12-01

Geosciences are becoming increasingly data intensive, particularly in relation to sustainability problems, which are multi-dimensional, weakly structured and characterized by high levels of uncertainty. In the case of complex resource management problems, the challenge is to extract meaningful information from data and make sense of it. Simultaneously, scientific knowledge alone is insufficient to change practice. Creating tools, and group decision support processes for end users to interact with data are key challenges to transforming science-based information into actionable knowledge. The ENCOMPASS project began as a multi-year case study in the Atacama Desert of Chile to design and implement a knowledge transfer model for energy-water-mining conflicts in the region. ENCOMPASS combines the use of cyberinfrastructure (CI), automated data collection, interactive interfaces for dynamic decision support, and participatory modelling to support social learning. A pilot version of the ENCOMPASS CI uses open source systems and serves as a structure to integrate and store multiple forms of data and knowledge, such as DEM, meteorological, water quality, geomicrobiological, energy demand, and groundwater models. In the case study, informatics and data fusion needs related to scientific uncertainty around deep groundwater flowpaths and energy-water connections. Users may upload data from field sites with handheld devices or desktops. Once uploaded, data assets are accessible for a variety of uses. To address multi-attributed decision problems in the Atacama region a standalone application with touch-enabled interfaces was created to improve real-time interactions with datasets by groups. The tool was used to merge datasets from the ENCOMPASS CI to support exploration among alternatives and build shared understanding among stakeholders. To date, the project has increased technical capacity among stakeholders, resulted in the creation of both for-profit and non-profit entities, enabled cross-sector collaboration with mining-indigenous stakeholders, and produced an interactive application for group decision support. ENCOMPASS leverages advances in computational tools to deliver data and models for group decision support applied to sustainability science problems.

Integrating Multiple Criteria Evaluation and GIS in Ecotourism: a Review

NASA Astrophysics Data System (ADS)

Mohd, Z. H.; Ujang, U.

2016-09-01

The concept of 'Eco-tourism' is increasingly heard in recent decades. Ecotourism is one adventure that environmentally responsible intended to appreciate the nature experiences and cultures. Ecotourism should have low impact on environment and must contribute to the prosperity of local residents. This article reviews the use of Multiple Criteria Evaluation (MCE) and Geographic Information System (GIS) in ecotourism. Multiple criteria evaluation mostly used to land suitability analysis or fulfill specific objectives based on various attributes that exist in the selected area. To support the process of environmental decision making, the application of GIS is used to display and analysis the data through Analytic Hierarchy Process (AHP). Integration between MCE and GIS tool is important to determine the relative weight for the criteria used objectively. With the MCE method, it can resolve the conflict between recreation and conservation which is to minimize the environmental and human impact. Most studies evidences that the GIS-based AHP as a multi criteria evaluation is a strong and effective in tourism planning which can aid in the development of ecotourism industry effectively.

Development of a decision support system for monitoring, reporting and forecasting ecological conditions of the Appalachian Trail

USGS Publications Warehouse

Wang, Yeqiao; Nemani, Ramakrishna; Dieffenbach, Fred; Stolte, Kenneth; Holcomb, Glenn B.; Robinson, Matt; Reese, Casey C.; McNiff, Marcia; Duhaime, Roland; Tierney, Geri; Mitchell, Brian; August, Peter; Paton, Peter; LaBash, Charles

2010-01-01

This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decisionmaking on management of the A.T. by providing a coherent framework for data integration, status reporting and trend analysis. The A.T. MEGA-Transect DSS is to integrate NASA multi-platform sensor data and modeling through the Terrestrial Observation and Prediction System (TOPS) and in situ measurements from A.T. MEGA-Transect partners to address identified natural resource priorities and improve resource management decisions.

Revealed preferences towards the appraisal of orphan drugs in Poland - multi criteria decision analysis.

PubMed

Kolasa, Katarzyna; Zwolinski, Krzysztof Miroslaw; Zah, Vladimir; Kaló, Zoltán; Lewandowski, Tadeusz

2018-04-27

A Multi Criteria Decision Analysis (MCDA) technique was adopted to reveal the preferences of the Appraisal Body of the Polish HTA agency towards orphan drugs (OMPs). There were 34 positive and 23 negative HTA recommendations out of 54 distinctive drug-indication pairs. The MCDA matrix consisted of 13 criteria, seven of which made the most impact on the HTA process. Appraisal of clinical evidence, cost of therapy, and safety considerations were the main contributors to the HTA guidance, whilst advancement of technology and manufacturing costs made the least impact. MCDA can be regarded as a valuable tool for revealing decision makers' preferences in the healthcare sector. Given that only roughly half of all criteria included in the MCDA matrix were deemed to make an impact on the HTA process, there is certainly some room for improvement with respect to the adaptation of a new approach towards the value assessment of OMPs in Poland.

Decision-Aiding and Optimization for Vertical Navigation of Long-Haul Aircraft

NASA Technical Reports Server (NTRS)

Patrick, Nicholas J. M.; Sheridan, Thomas B.

1996-01-01

Most decisions made in the cockpit are related to safety, and have therefore been proceduralized in order to reduce risk. There are very few which are made on the basis of a value metric such as economic cost. One which can be shown to be value based, however, is the selection of a flight profile. Fuel consumption and flight time both have a substantial effect on aircraft operating cost, but they cannot be minimized simultaneously. In addition, winds, turbulence, and performance vary widely with altitude and time. These factors make it important and difficult for pilots to (a) evaluate the outcomes associated with a particular trajectory before it is flown and (b) decide among possible trajectories. The two elements of this problem considered here are: (1) determining what constitutes optimality, and (2) finding optimal trajectories. Pilots and dispatchers from major u.s. airlines were surveyed to determine which attributes of the outcome of a flight they considered the most important. Avoiding turbulence-for passenger comfort-topped the list of items which were not safety related. Pilots' decision making about the selection of flight profile on the basis of flight time, fuel burn, and exposure to turbulence was then observed. Of the several behavioral and prescriptive decision models invoked to explain the pilots' choices, utility maximization is shown to best reproduce the pilots' decisions. After considering more traditional methods for optimizing trajectories, a novel method is developed using a genetic algorithm (GA) operating on a discrete representation of the trajectory search space. The representation is a sequence of command altitudes, and was chosen to be compatible with the constraints imposed by Air Traffic Control, and with the training given to pilots. Since trajectory evaluation for the GA is performed holistically, a wide class of objective functions can be optimized easily. Also, using the GA it is possible to compare the costs associated with different airspace design and air traffic management policies. A decision aid is proposed which would combine the pilot's notion of optimality with the GA-based optimization, provide the pilot with a number of alternative pareto-optimal trajectories, and allow him to consider unmodelled attributes and constraints in choosing among them. A solution to the problem of displaying alternatives in a multi-attribute decision space is also presented.

Decision-Aiding and Optimization for Vertical Navigation of Long-Haul Aircraft

NASA Technical Reports Server (NTRS)

Patrick, Nicholas J. M.; Sheridan, Thomas B.

1996-01-01

Most decisions made in the cockpit are related to safety, and have therefore been proceduralized in order to reduce risk. There are very few which are made on the basis of a value metric such as economic cost. One which can be shown to be value based, however, is the selection of a flight profile. Fuel consumption and flight time both have a substantial effect on aircraft operating cost, but they cannot be minimized simultaneously. In addition, winds, turbulence, and performance x,ary widely with altitude and time. These factors make it important and difficult for pilots to (a) evaluate the outcomes associated with a particular trajectory before it is flown and (b) decide among possible trajectories. The two elements of this problem considered here are (1) determining, what constitutes optimality, and (2) finding optimal trajectories. Pilots and dispatchers from major U.S. airlines were surveyed to determine which attributes of the outcome of a flight they considered the most important. Avoiding turbulence-for passenger comfort topped the list of items which were not safety related. Pilots' decision making about the selection of flight profile on the basis of flight time, fuel burn, and exposure to turbulence was then observed. Of the several behavioral and prescriptive decision models invoked to explain the pilots' choices, utility maximization is shown to best reproduce the pilots' decisions. After considering more traditional methods for optimizing trajectories, a novel method is developed using a genetic algorithm (GA) operating on a discrete representation of the trajectory search space. The representation is a sequence of command altitudes, and was chosen to be compatible with the constraints imposed by Air Traffic Control, and with the training given to pilots. Since trajectory evaluation for the GA is performed holistically, a wide class of objective functions can be optimized easily. Also, using the GA it is possible to compare the costs associated with different airspace design and air traffic management policies. A decision aid is proposed which would combine the pilot's notion of optimility with the GA-based optimization, provide the pilot with a number of alternative pareto-optimal trajectories, and allow him to consider un-modelled attributes and constraints in choosing among them. A solution to the problem of displaying alternatives in a multi-attribute decision space is also presented.

Multi-agent framework for negotiation in a closed environment

NASA Astrophysics Data System (ADS)

Cretan, Adina; Coutinho, Carlos; Bratu, Ben; Jardim-Goncalves, Ricardo

2013-10-01

The goal of this paper is to offer support for small and medium enterprises which cannot or do not want to fulfill a big contract alone. Each organization has limited resources and in order to better accomplish a higher external demand, the managers are forced to outsource parts of their contracts even to concurrent organizations. In this concurrent environment each enterprise wants to preserve its decision autonomy and to disclose as little as possible from its business information. To describe this interaction, our approach is to define a framework for managing parallel and concurrent negotiations among independent organizations acting in the same industrial market. The complexity of our negotiation framework is done by the dynamic environment in which multi-attribute and multi-participant negotiations are racing over the same set of resources. Moreover, the proposed framework helps the organizations within the collaborative networked environment to augment their efficiency and ability to react to unforeseen situations, thus improving their market competitiveness.

Development of the Attributed Dignity Scale.

PubMed

Jacelon, Cynthia S; Dixon, Jane; Knafl, Kathleen A

2009-07-01

A sequential, multi-method approach to instrument development beginning with concept analysis, followed by (a) item generation from qualitative data, (b) review of items by expert and lay person panels, (c) cognitive appraisal interviews, (d) pilot testing, and (e) evaluating construct validity was used to develop a measure of attributed dignity in older adults. The resulting positively scored, 23-item scale has three dimensions: Self-Value, Behavioral Respect-Self, and Behavioral Respect-Others. Item-total correlations in the pilot study ranged from 0.39 to 0.85. Correlations between the Attributed Dignity Scale (ADS) and both Rosenberg's Self-Esteem Scale (0.17) and Crowne and Marlowe's Social Desirability Scale (0.36) were modest and in the expected direction, indicating attributed dignity is a related but independent concept. Next steps include testing the ADS with a larger sample to complete factor analysis, test-retest stability, and further study of the relationships between attributed dignity and other concepts.

Classification and Progression Based on CFS-GA and C5.0 Boost Decision Tree of TCM Zheng in Chronic Hepatitis B.

PubMed

Chen, Xiao Yu; Ma, Li Zhuang; Chu, Na; Zhou, Min; Hu, Yiyang

2013-01-01

Chronic hepatitis B (CHB) is a serious public health problem, and Traditional Chinese Medicine (TCM) plays an important role in the control and treatment for CHB. In the treatment of TCM, zheng discrimination is the most important step. In this paper, an approach based on CFS-GA (Correlation based Feature Selection and Genetic Algorithm) and C5.0 boost decision tree is used for zheng classification and progression in the TCM treatment of CHB. The CFS-GA performs better than the typical method of CFS. By CFS-GA, the acquired attribute subset is classified by C5.0 boost decision tree for TCM zheng classification of CHB, and C5.0 decision tree outperforms two typical decision trees of NBTree and REPTree on CFS-GA, CFS, and nonselection in comparison. Based on the critical indicators from C5.0 decision tree, important lab indicators in zheng progression are obtained by the method of stepwise discriminant analysis for expressing TCM zhengs in CHB, and alterations of the important indicators are also analyzed in zheng progression. In conclusion, all the three decision trees perform better on CFS-GA than on CFS and nonselection, and C5.0 decision tree outperforms the two typical decision trees both on attribute selection and nonselection.

Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes.

PubMed

Naujokaitis-Lewis, Ilona; Curtis, Janelle M R

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options.

Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes

PubMed Central

Curtis, Janelle M.R.

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options. PMID:27547529

Assessing the burden of paediatric influenza in Europe: the European Paediatric Influenza Analysis (EPIA) project.

PubMed

Paget, W John; Balderston, Catherine; Casas, Inmaculada; Donker, Gé; Edelman, Laurel; Fleming, Douglas; Larrauri, Amparo; Meijer, Adam; Puzelli, Simona; Rizzo, Caterina; Simonsen, Lone

2010-08-01

The European Paediatric Influenza Analysis (EPIA) project is a multi-country project that was created to collect, analyse and present data regarding the paediatric influenza burden in European countries, with the purpose of providing the necessary information to make evidence-based decisions regarding influenza immunisation recommendations for children. The initial approach taken is based on existing weekly virological and age-specific influenza-like illness (ILI) data from surveillance networks across Europe. We use a multiple regression model guided by longitudinal weekly patterns of influenza virus to attribute the weekly ILI consultation incidence pattern to each influenza (sub)type, while controlling for the effect of respiratory syncytial virus (RSV) epidemics. Modelling the ILI consultation incidence during 2002/2003-2008 revealed that influenza infections that presented for medical attention as ILI affected between 0.3% and 9.8% of children aged 0-4 and 5-14 years in England, Italy, the Netherlands and Spain in an average season. With the exception of Spain, these rates were always higher in children aged 0-4 years. Across the six seasons analysed (five seasons were analysed from the Italian data), the model attributed 47-83% of the ILI burden in primary care to influenza virus infection in the various countries, with the A(H3N2) virus playing the most important role, followed by influenza viruses B and A(H1N1). National season averages from the four countries studied indicated that between 0.4% and 18% of children consulted a physician for ILI, with the percentage depending on the country and health care system. Influenza virus infections explained the majority of paediatric ILI consultations in all countries. The next step will be to apply the EPIA modelling approach to severe outcomes indicators (i.e. hospitalisations and mortality data) to generate a complete range of mild and severe influenza burden estimates needed for decision making concerning paediatric influenza vaccination.

A statistic-thermodynamic model for the DOM degradation in the estuary

NASA Astrophysics Data System (ADS)

Zheng, Quanan; Chen, Qin; Zhao, Haihong; Shi, Jiuxin; Cao, Yong; Wang, Dan

2008-03-01

This study aims to clarify the role of dissolved salts playing in the degradation process of terrestrial dissolved organic matter (DOM) at a scale of molecular movement. The molecular thermal movement is perpetual motion. In a multi-molecular system, this random motion also causes collision between the molecules. Seawater is a multi-molecular system consisting from water, salt, and terrestrial DOM molecules. This study attributes the DOM degradation in the estuary to the inelastic collision of DOM molecule with charged salt ions. From statistic-thermodynamic theories of molecular collision, the DOM degradation model and the DOM distribution model are derived. The models are validated by the field observations and satellite data. Thus, we conclude that the inelastic collision between the terrestrial DOM molecules and dissolved salt ions in seawater is a decisive dynamic mechanism for rapid loss of terrestrial DOM.

Rough Evaluation Structure: Application of Rough Set Theory to Generate Simple Rules for Inconsistent Preference Relation

NASA Astrophysics Data System (ADS)

Gehrmann, Andreas; Nagai, Yoshimitsu; Yoshida, Osamu; Ishizu, Syohei

Since management decision-making becomes complex and preferences of the decision-maker frequently becomes inconsistent, multi-attribute decision-making problems were studied. To represent inconsistent preference relation, the concept of evaluation structure was introduced. We can generate simple rules to represent inconsistent preference relation by the evaluation structures. Further rough set theory for the preference relation was studied and the concept of approximation was introduced. One of our main aims of this paper is to introduce a concept of rough evaluation structure for representing inconsistent preference relation. We apply rough set theory to the evaluation structure, and develop a method for generating simple rules for inconsistent preference relations. In this paper, we introduce concepts of totally ordered information system, similarity class of preference relation, upper and lower approximation of preference relations. We also show the properties of rough evaluation structure and provide a simple example. As an application of rough evaluation structure, we analyze questionnaire survey of customer preferences about audio players.

Enhanced Decision Analysis Support System.

DTIC Science & Technology

1981-03-01

autorrares "i., the method for determining preferences when multiple and competing attributes are involved. Worth assessment is used as the model which...1967 as a method for determining preferenoe when multiple and competing attributes are involved (Rf 10). The tern worth can be - equated to other... competing objectives. After some discussion, the group decided that the problem could best be decided using the worth assessment procedure. They

Rejecting a bad option feels like choosing a good one.

PubMed

Perfecto, Hannah; Galak, Jeff; Simmons, Joseph P; Nelson, Leif D

2017-11-01

Across 4,151 participants, the authors demonstrate a novel framing effect, attribute matching, whereby matching a salient attribute of a decision frame with that of a decision's options facilitates decision-making. This attribute matching is shown to increase decision confidence and, ultimately, consensus estimates by increasing feelings of metacognitive ease. In Study 1, participants choosing the more attractive of two faces or rejecting the less attractive face reported greater confidence in and perceived consensus around their decision. Using positive and negative words, Study 2 showed that the attribute's extremity moderates the size of the effect. Study 3 found decision ease mediates these changes in confidence and consensus estimates. Consistent with a misattribution account, when participants were warned about this external source of ease in Study 4, the effect disappeared. Study 5 extended attribute matching beyond valence to objective judgments. The authors conclude by discussing related psychological constructs as well as downstream consequences. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Empirical study of seven data mining algorithms on different characteristics of datasets for biomedical classification applications.

PubMed

Zhang, Yiyan; Xin, Yi; Li, Qin; Ma, Jianshe; Li, Shuai; Lv, Xiaodan; Lv, Weiqi

2017-11-02

Various kinds of data mining algorithms are continuously raised with the development of related disciplines. The applicable scopes and their performances of these algorithms are different. Hence, finding a suitable algorithm for a dataset is becoming an important emphasis for biomedical researchers to solve practical problems promptly. In this paper, seven kinds of sophisticated active algorithms, namely, C4.5, support vector machine, AdaBoost, k-nearest neighbor, naïve Bayes, random forest, and logistic regression, were selected as the research objects. The seven algorithms were applied to the 12 top-click UCI public datasets with the task of classification, and their performances were compared through induction and analysis. The sample size, number of attributes, number of missing values, and the sample size of each class, correlation coefficients between variables, class entropy of task variable, and the ratio of the sample size of the largest class to the least class were calculated to character the 12 research datasets. The two ensemble algorithms reach high accuracy of classification on most datasets. Moreover, random forest performs better than AdaBoost on the unbalanced dataset of the multi-class task. Simple algorithms, such as the naïve Bayes and logistic regression model are suitable for a small dataset with high correlation between the task and other non-task attribute variables. K-nearest neighbor and C4.5 decision tree algorithms perform well on binary- and multi-class task datasets. Support vector machine is more adept on the balanced small dataset of the binary-class task. No algorithm can maintain the best performance in all datasets. The applicability of the seven data mining algorithms on the datasets with different characteristics was summarized to provide a reference for biomedical researchers or beginners in different fields.

Periodic benefit-risk assessment using Bayesian stochastic multi-criteria acceptability analysis

PubMed Central

Li, Kan; Yuan, Shuai Sammy; Wang, William; Wan, Shuyan Sabrina; Ceesay, Paulette; Heyse, Joseph F.; Mt-Isa, Shahrul; Luo, Sheng

2018-01-01

Benefit-risk (BR) assessment is essential to ensure the best decisions are made for a medical product in the clinical development process, regulatory marketing authorization, post-market surveillance, and coverage and reimbursement decisions. One challenge of BR assessment in practice is that the benefit and risk profile may keep evolving while new evidence is accumulating. Regulators and the International Conference on Harmonization (ICH) recommend performing periodic benefit-risk evaluation report (PBRER) through the product's lifecycle. In this paper, we propose a general statistical framework for periodic benefit-risk assessment, in which Bayesian meta-analysis and stochastic multi-criteria acceptability analysis (SMAA) will be combined to synthesize the accumulating evidence. The proposed approach allows us to compare the acceptability of different drugs dynamically and effectively and accounts for the uncertainty of clinical measurements and imprecise or incomplete preference information of decision makers. We apply our approaches to two real examples in a post-hoc way for illustration purpose. The proposed method may easily be modified for other pre and post market settings, and thus be an important complement to the current structured benefit-risk assessment (sBRA) framework to improve the transparent and consistency of the decision-making process. PMID:29505866

Management of complex knowledge in planning for sustainable development: The use of multi-criteria decision aids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kain, Jaan-Henrik; Soederberg, Henriette

2008-01-15

The vision of sustainable development entails new and complex planning situations, confronting local policy makers with changing political conditions, different content in decision making and planning and new working methods. Moreover, the call for sustainable development has been a major driving force towards an increasingly multi-stakeholder planning system. This situation requires competence in working in, and managing, groups of actors, including not only experts and project owners but also other categories of stakeholders. Among other qualities, such competence requires a working strategy aimed at integrating various, and sometimes incommensurable, forms of knowledge to construct a relevant and valid knowledge basemore » prior to decision making. Consequently, there lies great potential in methods that facilitate the evaluation of strategies for infrastructural development across multiple knowledge areas, so-called multi-criteria decision aids (MCDAs). In the present article, observations from six case studies are discussed, where the common denominators are infrastructural planning, multi-stakeholder participation and the use of MCDAs as interactive decision support. Three MCDAs are discussed - NAIADE, SCA and STRAD - with an emphasis on how they function in their procedural context. Accordingly, this is not an analysis of MCDA algorithms, of software programming aspects or of MCDAs as context-independent 'decision machines'-the focus is on MCDAs as actor systems, not as expert systems. The analysis is carried out across four main themes: (a) symmetrical management of different forms of knowledge; (b) management of heterogeneity, pluralism and conflict; (c) functionality and ease of use; and (d) transparency and trust. It shows that STRAD, by far, seems to be the most useful MCDA in interactive settings. NAIADE and SCA are roughly equivalent but have their strengths and weaknesses in different areas. Moreover, it was found that some MCDA issues require further attention, i.e., regarding transparency and understandability; qualitative/quantitative knowledge input; switching between different modes of weighting; software flexibility; as well as graphic and user interfaces.« less

Group decision making with the analytic hierarchy process in benefit-risk assessment: a tutorial.

PubMed

Hummel, J Marjan; Bridges, John F P; IJzerman, Maarten J

2014-01-01

The analytic hierarchy process (AHP) has been increasingly applied as a technique for multi-criteria decision analysis in healthcare. The AHP can aid decision makers in selecting the most valuable technology for patients, while taking into account multiple, and even conflicting, decision criteria. This tutorial illustrates the procedural steps of the AHP in supporting group decision making about new healthcare technology, including (1) identifying the decision goal, decision criteria, and alternative healthcare technologies to compare, (2) structuring the decision criteria, (3) judging the value of the alternative technologies on each decision criterion, (4) judging the importance of the decision criteria, (5) calculating group judgments, (6) analyzing the inconsistency in judgments, (7) calculating the overall value of the technologies, and (8) conducting sensitivity analyses. The AHP is illustrated via a hypothetical example, adapted from an empirical AHP analysis on the benefits and risks of tissue regeneration to repair small cartilage lesions in the knee.

A Multi-Attribute-Utility-Theory Model that Minimizes Interview-Data Requirements: A Consolidation of Space Launch Decisions.

DTIC Science & Technology

1994-12-01

satel~ lites on th" .gruunu" U, .U,- orbit affects the priority given to a new launch. Table 3.9 Launch Priorities Level Level Title Description 0.00 No...value of a satellite’s mission(s) relative to the misston(s) of other sate• lites As such the rating given may reflect an endre class of satellites for...Expected Remaining Lifetime 0 Years Assign a number between 0 and I that best describes the utility of a sate; lite ’,th Vh,,V- ,ta .=.... ,. A at these

Assessment of Trading Partners for China's Rare Earth Exports Using a Decision Analytic Approach

PubMed Central

He, Chunyan; Lei, Yalin; Ge, Jianping

2014-01-01

Chinese rare earth export policies currently result in accelerating its depletion. Thus adopting an optimal export trade selection strategy is crucial to determining and ultimately identifying the ideal trading partners. This paper introduces a multi-attribute decision-making methodology which is then used to select the optimal trading partner. In the method, an evaluation criteria system is established to assess the seven top trading partners based on three dimensions: political relationships, economic benefits and industrial security. Specifically, a simple additive weighing model derived from an additive utility function is utilized to calculate, rank and select alternatives. Results show that Japan would be the optimal trading partner for Chinese rare earths. The criteria evaluation method of trading partners for China's rare earth exports provides the Chinese government with a tool to enhance rare earth industrial policies. PMID:25051534

Assessment of trading partners for China's rare earth exports using a decision analytic approach.

PubMed

He, Chunyan; Lei, Yalin; Ge, Jianping

2014-01-01

Chinese rare earth export policies currently result in accelerating its depletion. Thus adopting an optimal export trade selection strategy is crucial to determining and ultimately identifying the ideal trading partners. This paper introduces a multi-attribute decision-making methodology which is then used to select the optimal trading partner. In the method, an evaluation criteria system is established to assess the seven top trading partners based on three dimensions: political relationships, economic benefits and industrial security. Specifically, a simple additive weighing model derived from an additive utility function is utilized to calculate, rank and select alternatives. Results show that Japan would be the optimal trading partner for Chinese rare earths. The criteria evaluation method of trading partners for China's rare earth exports provides the Chinese government with a tool to enhance rare earth industrial policies.

Decerns: A framework for multi-criteria decision analysis

DOE PAGES

Yatsalo, Boris; Didenko, Vladimir; Gritsyuk, Sergey; ...

2015-02-27

A new framework, Decerns, for multicriteria decision analysis (MCDA) of a wide range of practical problems on risk management is introduced. Decerns framework contains a library of modules that are the basis for two scalable systems: DecernsMCDA for analysis of multicriteria problems, and DecernsSDSS for multicriteria analysis of spatial options. DecernsMCDA includes well known MCDA methods and original methods for uncertainty treatment based on probabilistic approaches and fuzzy numbers. As a result, these MCDA methods are described along with a case study on analysis of multicriteria location problem.

Drug benefit decisions among older adults: a policy-capturing analysis.

PubMed

Cline, Richard R; Gupta, Kiran

2006-01-01

Under the Medicare Prescription Drug Improvement and Modernization Act, beneficiaries remaining in the traditional fee-for-service plan will face a variety of drug benefit options provided by private stand-alone prescription drug plans. Although these plans likely will differ with regard to a number of important attributes, little is known about older adults' judgment processes in this context. The objectives of this study were to 1) better understand the manner in which drug insurance attributes are weighted in older adults' judgments of drug benefit suitability, 2) explore variability in judgment strategies among seniors, and 3) assess seniors' insight into their judgment policies. Three focus groups were conducted with 19 older adults to elicit important drug plan attributes. A policy-capturing study with 32 seniors, none of whom had participated in the focus groups, then was employed to quantify the impacts of these attributes on judgments of plan suitability. Focus group participants reported that copayment, monthly premium, deductible, formulary use, and mail-order pharmacy use were important drug insurance attributes. The policy-capturing study showed that deductibles and premiums were weighted most heavily in judgment formation. However, significant variability in judgment policies was apparent, with 3 distinct groups emerging from cluster analysis. The first emphasized deductibles and copayments, the second premiums and deductibles, and the third use of a mail-order pharmacy and deductibles. Study volunteers exhibited insight into the role of some plan attributes in their judgments, but not others. Cost-sharing provisions appear to be most important in older adults' evaluations of drug benefit plans. However, significant heterogeneity in attribute preferences also was apparent in this study. Older adults may not be cognizant of the manner in which some plan attributes affect their evaluations, suggesting a role for decision aids in this process.

Graduate Attributes for Master's Programs in Health Services and Policy Research: Results of a National Consultation

PubMed Central

Morgan, Steve; Orr, Karen; Mah, Catherine

2010-01-01

Objective: Our objective was to identify desirable attributes to be developed through graduate training in health services and policy research (HSPR) by identifying the knowledge, skills and abilities thought to be keys to success in HSPR-related careers. We aimed for a framework clear enough to serve as a touchstone for HSPR training programs across Canada yet flexible enough to permit diversity of specialization across and within those programs. Methods: Our approach involved several stages of data collection and analysis: a review of literature; telephone interviews with opinion leaders; online surveys of HSPR students, recent graduates and employers; an invitational workshop; and an interactive panel at a national conference. Our final framework was arrived at through an iterative process of thematic analysis, reflection on invited feedback from consultation participants and triangulation with existing competency frameworks. Results: Our final result was a framework that identifies traits, knowledge and abilities of master's-level graduates who are capable of fostering health system improvement through planning, management, analysis or monitoring that is informed by credible evidence and relevant theory. These attributes are organized into three levels: generic graduate attributes, knowledge related to health and health systems and, finally, attributes related to the application of knowledge for health system improvement. The HSPR-specific attributes include not only an understanding of HSPR theories and methods but also the skills related to the practical application of knowledge in the complex environments of health system decision-making and healthcare policy. Conclusion: Master's-level HSPR training programs should prepare students to pose and seek answers to important questions and provide them with the skills necessary to apply their knowledge within complex decision-making environments. PMID:21804839

Self-determination and older people--a concept analysis.

PubMed

Ekelund, Christina; Dahlin-Ivanoff, Synneve; Eklund, Kajsa

2014-03-01

Self-determination has emerged as an important concept within health care, used to emphasize clients' control and independence as they participate in rehabilitation. To strengthen clients' self-determination is a central aim in occupational therapy. However, there is a lack of a clear definition of self-determination concerning community-dwelling older people. The definition should be flexible in different contexts, such as cultural. To define and clarify the concept of self-determination in relation to community-dwelling frail older people. Walker & Avant's analysis procedure was carried out to identify textual attributes to the concept of self-determination, supplemented by a content analysis of 21 articles that were used to define and further justify the textual attributes. Self-determination was used in diverse contexts for community-dwelling older people, concerning: decision-making in everyday life, professionals' views, health, and legal/ethical rights. Different textual attributes were identified, to propose a conceptual definition of self-determination in relation to community-dwelling frail older people: A process in which a person has control and legal/ethical rights, and has the knowledge and ability to make a decision of his/her own free choice. This concept analysis has contributed to clarifying the concept for the convenience of research with community-dwelling frail older people.

An evaluation of treatment decisions at a colorectal cancer multi-disciplinary team.

PubMed

Wood, J J; Metcalfe, C; Paes, A; Sylvester, P; Durdey, P; Thomas, M G; Blazeby, J M

2008-10-01

It is mandatory for treatment decisions for patients with colorectal cancer to be made within the context of a multi-disciplinary team (MDT) meeting. It is currently uncertain, however, how to best evaluate the quality of MDT decision-making. This study examined MDT decision-making by studying whether MDT treatment decisions were implemented and investigated the reasons why some decisions changed after the meeting. Consecutive MDT treatment decisions were prospectively recorded. Implementation of decisions was studied by examining hospital records. Reasons for changes in MDT decisions were identified. In all, 201 consecutive treatment decisions were analysed, concerning 157 patients. Twenty decisions (10.0%, 95% confidence interval 6.3-15.2%) were not implemented. Looking at the reasons for nonimplementation, nine (40%) related to co-morbidity, seven (35%) to patient choice, two changed in light of new clinical information, one doctor changed a decision and for one changed decision, no reason was apparent. When decisions changed, the final treatment was always more conservative than was originally planned and decisions were more likely to change for colon rather than rectal cancer (P = 0.024). The vast majority of colorectal MDT decisions were implemented and when decisions changed, it mostly related to patient factors that had not been taken into account. Analysis of the implementation of team decisions is an informative process to monitor the quality of MDT decision-making.

Better Informing Decision Making with Multiple Outcomes Cost-Effectiveness Analysis under Uncertainty in Cost-Disutility Space

PubMed Central

McCaffrey, Nikki; Agar, Meera; Harlum, Janeane; Karnon, Jonathon; Currow, David; Eckermann, Simon

2015-01-01

Introduction Comparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses—where outcomes are considered separately, with their joint relationship under uncertainty ignored—lead to incorrect inference regarding preferred strategies. Objective The objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison. Methods Multiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL. Results Conventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home ( 1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when 1=$2,000 and 2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective. Conclusion Comparison in CDU space and associated summary measures have distinct advantages to multiple domain comparisons, aiding transparent and robust joint comparison of costs and multiple effects under uncertainty across potential threshold values for effect, better informing net benefit assessment and related reimbursement and research decisions. PMID:25751629

Nutritional Attributes, Substitutability, Scalability, and Environmental Intensity of an Illustrative Subset of Current and Future Protein Sources for Aquaculture Feeds: Joint Consideration of Potential Synergies and Trade-offs.

PubMed

Pelletier, Nathan; Klinger, Dane H; Sims, Neil A; Yoshioka, Janice-Renee; Kittinger, John N

2018-05-15

Aquaculture is anticipated to play an increasingly important role in global food security because it may represent one of the best opportunities to increase the availability of healthy animal protein in the context of resource and environmental constraints. However, the growth and sustainability of the aquaculture industry faces important bottlenecks with respect to feed resources, which may be derived from diverse sources. Here, using a small but representative subset of potential aquafeed inputs (which we selected to highlight a range of relevant attributes), we review a core suite of considerations that need to be accommodated in concert in order to overcome key bottlenecks to the continued development and expansion of the aquaculture industry. Specifically, we evaluate the nutritional attributes, substitutability, scalability, and resource and environmental intensity of each input. On this basis, we illustrate a range of potential synergies and trade-offs within and across attributes that are characteristic of ingredient types. We posit that the recognition and management of such synergies and trade-offs is imperative to satisfying the multi-objective decision-making associated with sustainable increases in future aquaculture production.

Attention and attribute overlap in preferential choice.

PubMed

Bhatia, Sudeep

2017-07-01

Attributes that are common, or overlapping, across alternatives in two-alternative forced preferential choice tasks are often non-diagnostic. In many settings, attending to and evaluating these attributes does not help the decision maker determine which of the available alternatives is the most desirable. For this reason, many existing behavioural theories propose that decision makers ignore common attributes while deliberating. Across six experiments, we find that decision makers do direct their attention selectively and ignore attributes that are not present in or associated with either of the available alternatives. However, they are as likely to attend to common attributes as they are to attend to attributes that are unique to a single alternative. These results suggest the need for novel theories of attention in preferential choice.

Development of policies for Natura 2000 sites: a multi-criteria approach to support decision makers.

PubMed

Cortina, Carla; Boggia, Antonio

2014-08-01

The aim of this study is to present a methodology to support decision makers in the choice of Natura 2000 sites needing an appropriate management plan to ensure a sustainable socio-economic development. In order to promote sustainable development in the Natura 2000 sites compatible with nature preservation, conservation measures or management plans are necessary. The main issue is to decide when only conservation measures can be applied and when the sites need an appropriate management plan. We present a case study for the Italian Region of Umbria. The methodology is based on a multi-criteria approach to identify the biodiversity index (BI), and on the development of a human activities index (HAI). By crossing the two indexes for each site on a Cartesian plane, four groups of sites were identified. Each group corresponds to a specific need for an appropriate management plan. Sites in the first group with a high level both of biodiversity and human activities have the most urgent need of an appropriate management plan to ensure sustainable development. The proposed methodology and analysis is replicable in other regions or countries by using the data available for each site in the Natura 2000 standard data form. A multi-criteria analysis is especially suitable for supporting decision makers when they deal with a multidimensional decision process. We found the multi-criteria approach particularly sound in this case, due to the concept of biodiversity itself, which is complex and multidimensional, and to the high number of alternatives (Natura 2000 sites) to be assessed. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Quadrupole Dalton-based multi-attribute method for product characterization, process development, and quality control of therapeutic proteins.

PubMed

Xu, Weichen; Jimenez, Rod Brian; Mowery, Rachel; Luo, Haibin; Cao, Mingyan; Agarwal, Nitin; Ramos, Irina; Wang, Xiangyang; Wang, Jihong

2017-10-01

During manufacturing and storage process, therapeutic proteins are subject to various post-translational modifications (PTMs), such as isomerization, deamidation, oxidation, disulfide bond modifications and glycosylation. Certain PTMs may affect bioactivity, stability or pharmacokinetics and pharmacodynamics profile and are therefore classified as potential critical quality attributes (pCQAs). Identifying, monitoring and controlling these PTMs are usually key elements of the Quality by Design (QbD) approach. Traditionally, multiple analytical methods are utilized for these purposes, which is time consuming and costly. In recent years, multi-attribute monitoring methods have been developed in the biopharmaceutical industry. However, these methods combine high-end mass spectrometry with complicated data analysis software, which could pose difficulty when implementing in a quality control (QC) environment. Here we report a multi-attribute method (MAM) using a Quadrupole Dalton (QDa) mass detector to selectively monitor and quantitate PTMs in a therapeutic monoclonal antibody. The result output from the QDa-based MAM is straightforward and automatic. Evaluation results indicate this method provides comparable results to the traditional assays. To ensure future application in the QC environment, this method was qualified according to the International Conference on Harmonization (ICH) guideline and applied in the characterization of drug substance and stability samples. The QDa-based MAM is shown to be an extremely useful tool for product and process characterization studies that facilitates facile understanding of process impact on multiple quality attributes, while being QC friendly and cost-effective.

Learning from examples - Generation and evaluation of decision trees for software resource analysis

NASA Technical Reports Server (NTRS)

Selby, Richard W.; Porter, Adam A.

1988-01-01

A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

How can multi criteria decision analysis support value assessment of pharmaceuticals? - Findings from a systematic literature review.

PubMed

Kolasa, Katarzyna; Zah, Vladimir; Kowalczyk, Marta

2018-04-29

As budget constraints become more and more visible, there is growing recognition for greater transparency and greater stakeholders' engagement in the pharmaceuticals' pric-ing&reimbursement (P&R) decision making. New frameworks of drugs' value assessments are searched for. Among them, the multi-criteria decision analysis (MCDA) receives more and more attention. In 2014, ISPOR established Task Force to provide methodological recommendations for MCDA utilization in the health care decision making. Still, there is not so much knowledge about the real life experience with MCDA's adaptation to the P&R processes. Areas covered: A systematic literature review was performed to understand the rationale for MCDA adaptation, methodology used as well as its impact on P&R outcomes. Expert commentary: In total 102 hits were found through the search of databases, out of which 18 publications were selected. Although limited in scope, the review highlighted how MCDA can im-prove the decision making processes not only regarding pricing & reimbursement but also contribute to the the risk benefit assessment as well as optimization of treatment outcomes. Still none of re-viewed studies did report how MCDA results actually impacted the real life settings.

Systems Analysis - a new paradigm and decision support tools for the water framework directive

NASA Astrophysics Data System (ADS)

Bruen, M.

2008-05-01

In the early days of Systems Analysis the focus was on providing tools for optimisation, modelling and simulation for use by experts. Now there is a recognition of the need to develop and disseminate tools to assist in making decisions, negotiating compromises and communicating preferences that can easily be used by stakeholders without the need for specialist training. The Water Framework Directive (WFD) requires public participation and thus provides a strong incentive for progress in this direction. This paper places the new paradigm in the context of the classical one and discusses some of the new approaches which can be used in the implementation of the WFD. These include multi-criteria decision support methods suitable for environmental problems, adaptive management, cognitive mapping, social learning and cooperative design and group decision-making. Concordance methods (such as ELECTRE) and the Analytical Hierarchy Process (AHP) are identified as multi-criteria methods that can be readily integrated into Decision Support Systems (DSS) that deal with complex environmental issues with very many criteria, some of which are qualitative. The expanding use of the new paradigm provides an opportunity to observe and learn from the interaction of stakeholders with the new technology and to assess its effectiveness.

A prospective analysis of implementation of multi-disciplinary team decisions in breast cancer.

PubMed

English, Rachel; Metcalfe, Chris; Day, James; Rayter, Zenon; Blazeby, Jane M

2012-09-01

Multi-disciplinary teams (MDTs) management of patients with cancer is mandatory in the United Kingdom, and auditing team decision-making by examining rates of decision implementation and reasons for nonimplementation may inform this practice. Consecutive breast cancer MDT decisions, subsequent decision implementation, and reasons for nonimplementation were prospectively recorded. Factors associated with nonimplementation of the MDT decision were analyzed with logistic regression. Of 289 consecutive MDT decisions involving 210 women, 20 (6.9%, 95% CIs 4.3%-10.5%) were not implemented. Most changed MDT decisions did so because of patient preferences (n = 13, 65%), with the discovery of new clinical information (n = 3) and individual doctor's views (n = 4) also leading to decision nonimplementation. MDT decisions were significantly less likely to be adhered to in patients with confirmed malignant disease compared to those with benign or 'unknown' disease categories (p < 0.001) and MDT decisions in older patients were significantly more likely not to be implemented than in younger patients (p = 0.002). Auditing nonimplementation of MDT recommendations and examining reasons for changed decisions is a useful process to monitor team performance and to identify factors that need more attention during the MDT meeting to ensure that the process makes optimal patient centered decisions. © 2012 Wiley Periodicals, Inc.

Comparing AMSR-E soil moisture estimates to the extended record of the U.S. Climate Reference Network (USCRN)

USDA-ARS?s Scientific Manuscript database

Soil moisture plays an integral role in various aspects ranging from multi-scale hydrologic modeling to agricultural decision analysis to multi-scale hydrologic modeling, from climate change assessments to drought prediction and prevention. The broad availability of soil moisture estimates has only...

Attributes Affecting Computer-Aided Decision Making--A Literature Survey.

ERIC Educational Resources Information Center

Moldafsky, Neil I; Kwon, Ik-Whan

1994-01-01

Reviews current literature about personal, demographic, situational, and cognitive attributes that affect computer-aided decision making. The effectiveness of computer-aided decision making is explored in relation to decision quality, effectiveness, and confidence. Studies of the effects of age, anxiety, cognitive type, attitude, gender, and prior…

WeightLifter: Visual Weight Space Exploration for Multi-Criteria Decision Making.

PubMed

Pajer, Stephan; Streit, Marc; Torsney-Weir, Thomas; Spechtenhauser, Florian; Muller, Torsten; Piringer, Harald

2017-01-01

A common strategy in Multi-Criteria Decision Making (MCDM) is to rank alternative solutions by weighted summary scores. Weights, however, are often abstract to the decision maker and can only be set by vague intuition. While previous work supports a point-wise exploration of weight spaces, we argue that MCDM can benefit from a regional and global visual analysis of weight spaces. Our main contribution is WeightLifter, a novel interactive visualization technique for weight-based MCDM that facilitates the exploration of weight spaces with up to ten criteria. Our technique enables users to better understand the sensitivity of a decision to changes of weights, to efficiently localize weight regions where a given solution ranks high, and to filter out solutions which do not rank high enough for any plausible combination of weights. We provide a comprehensive requirement analysis for weight-based MCDM and describe an interactive workflow that meets these requirements. For evaluation, we describe a usage scenario of WeightLifter in automotive engineering and report qualitative feedback from users of a deployed version as well as preliminary feedback from decision makers in multiple domains. This feedback confirms that WeightLifter increases both the efficiency of weight-based MCDM and the awareness of uncertainty in the ultimate decisions.

Can streamlined multi-criteria decision analysis be used to implement shared decision making for colorectal cancer screening?

PubMed Central

Dolan, James G.; Boohaker, Emily; Allison, Jeroan; Imperiale, Thomas F.

2013-01-01

Background Current US colorectal cancer screening guidelines that call for shared decision making regarding the choice among several recommended screening options are difficult to implement. Multi-criteria decision analysis (MCDA) is an established methodology well suited for supporting shared decision making. Our study goal was to determine if a streamlined form of MCDA using rank order based judgments can accurately assess patients’ colorectal cancer screening priorities. Methods We converted priorities for four decision criteria and three sub-criteria regarding colorectal cancer screening obtained from 484 average risk patients using the Analytic Hierarchy Process (AHP) in a prior study into rank order-based priorities using rank order centroids. We compared the two sets of priorities using Spearman rank correlation and non-parametric Bland-Altman limits of agreement analysis. We assessed the differential impact of using the rank order-based versus the AHP-based priorities on the results of a full MCDA comparing three currently recommended colorectal cancer screening strategies. Generalizability of the results was assessed using Monte Carlo simulation. Results Correlations between the two sets of priorities for the seven criteria ranged from 0.55 to 0.92. The proportions of absolute differences between rank order-based and AHP-based priorities that were more than ± 0.15 ranged from 1% to 16%. Differences in the full MCDA results were minimal and the relative rankings of the three screening options were identical more than 88% of the time. The Monte Carlo simulation results were similar. Conclusion Rank order-based MCDA could be a simple, practical way to guide individual decisions and assess population decision priorities regarding colorectal cancer screening strategies. Additional research is warranted to further explore the use of these methods for promoting shared decision making. PMID:24300851

Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies

NASA Astrophysics Data System (ADS)

Chalabi, Zaid; Milojevic, Ai; Doherty, Ruth M.; Stevenson, David S.; MacKenzie, Ian A.; Milner, James; Vieno, Massimo; Williams, Martin; Wilkinson, Paul

2017-10-01

A decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed.

Blame Attribution as a Moderator of Perceptions of Sexual Orientation-Based Hate Crimes

ERIC Educational Resources Information Center

Cramer, Robert J.; Chandler, Joseph F.; Wakeman, Emily E.

2010-01-01

Blame attribution is a valuable mechanism explaining decision making. However, present literature mainly employs blame attribution as a dependent variable. The shortcoming of this fact is that blame attribution offers a potentially valuable explanatory mechanism for decision making. The authors designed two studies to investigate blame attribution…

Memory-based decision-making with heuristics: evidence for a controlled activation of memory representations.

PubMed

Khader, Patrick H; Pachur, Thorsten; Meier, Stefanie; Bien, Siegfried; Jost, Kerstin; Rösler, Frank

2011-11-01

Many of our daily decisions are memory based, that is, the attribute information about the decision alternatives has to be recalled. Behavioral studies suggest that for such decisions we often use simple strategies (heuristics) that rely on controlled and limited information search. It is assumed that these heuristics simplify decision-making by activating long-term memory representations of only those attributes that are necessary for the decision. However, from behavioral studies alone, it is unclear whether using heuristics is indeed associated with limited memory search. The present study tested this assumption by monitoring the activation of specific long-term-memory representations with fMRI while participants made memory-based decisions using the "take-the-best" heuristic. For different decision trials, different numbers and types of information had to be retrieved and processed. The attributes consisted of visual information known to be represented in different parts of the posterior cortex. We found that the amount of information required for a decision was mirrored by a parametric activation of the dorsolateral PFC. Such a parametric pattern was also observed in all posterior areas, suggesting that activation was not limited to those attributes required for a decision. However, the posterior increases were systematically modulated by the relative importance of the information for making a decision. These findings suggest that memory-based decision-making is mediated by the dorsolateral PFC, which selectively controls posterior storage areas. In addition, the systematic modulations of the posterior activations indicate a selective boosting of activation of decision-relevant attributes.

The Distribution of Climate Change Public Opinion in Canada.

PubMed

Mildenberger, Matto; Howe, Peter; Lachapelle, Erick; Stokes, Leah; Marlon, Jennifer; Gravelle, Timothy

2016-01-01

While climate scientists have developed high resolution data sets on the distribution of climate risks, we still lack comparable data on the local distribution of public climate change opinions. This paper provides the first effort to estimate local climate and energy opinion variability outside the United States. Using a multi-level regression and post-stratification (MRP) approach, we estimate opinion in federal electoral districts and provinces. We demonstrate that a majority of the Canadian public consistently believes that climate change is happening. Belief in climate change's causes varies geographically, with more people attributing it to human activity in urban as opposed to rural areas. Most prominently, we find majority support for carbon cap and trade policy in every province and district. By contrast, support for carbon taxation is more heterogeneous. Compared to the distribution of US climate opinions, Canadians believe climate change is happening at higher levels. This new opinion data set will support climate policy analysis and climate policy decision making at national, provincial and local levels.

The Distribution of Climate Change Public Opinion in Canada

PubMed Central

Gravelle, Timothy

2016-01-01

While climate scientists have developed high resolution data sets on the distribution of climate risks, we still lack comparable data on the local distribution of public climate change opinions. This paper provides the first effort to estimate local climate and energy opinion variability outside the United States. Using a multi-level regression and post-stratification (MRP) approach, we estimate opinion in federal electoral districts and provinces. We demonstrate that a majority of the Canadian public consistently believes that climate change is happening. Belief in climate change’s causes varies geographically, with more people attributing it to human activity in urban as opposed to rural areas. Most prominently, we find majority support for carbon cap and trade policy in every province and district. By contrast, support for carbon taxation is more heterogeneous. Compared to the distribution of US climate opinions, Canadians believe climate change is happening at higher levels. This new opinion data set will support climate policy analysis and climate policy decision making at national, provincial and local levels. PMID:27486659

Policy impacts of ecosystem services knowledge

PubMed Central

Posner, Stephen M.; McKenzie, Emily; Ricketts, Taylor H.

2016-01-01

Research about ecosystem services (ES) often aims to generate knowledge that influences policies and institutions for conservation and human development. However, we have limited understanding of how decision-makers use ES knowledge or what factors facilitate use. Here we address this gap and report on, to our knowledge, the first quantitative analysis of the factors and conditions that explain the policy impact of ES knowledge. We analyze a global sample of cases where similar ES knowledge was generated and applied to decision-making. We first test whether attributes of ES knowledge themselves predict different measures of impact on decisions. We find that legitimacy of knowledge is more often associated with impact than either the credibility or salience of the knowledge. We also examine whether predictor variables related to the science-to-policy process and the contextual conditions of a case are significant in predicting impact. Our findings indicate that, although many factors are important, attributes of the knowledge and aspects of the science-to-policy process that enhance legitimacy best explain the impact of ES science on decision-making. Our results are consistent with both theory and previous qualitative assessments in suggesting that the attributes and perceptions of scientific knowledge and process within which knowledge is coproduced are important determinants of whether that knowledge leads to action. PMID:26831101

Multi-criteria decision analysis and environmental risk assessment for nanomaterials

NASA Astrophysics Data System (ADS)

Linkov, Igor; Satterstrom, F. Kyle; Steevens, Jeffery; Ferguson, Elizabeth; Pleus, Richard C.

2007-08-01

Nanotechnology is a broad and complex discipline that holds great promise for innovations that can benefit mankind. Yet, one must not overlook the wide array of factors involved in managing nanomaterial development, ranging from the technical specifications of the material to possible adverse effects in humans. Other opportunities to evaluate benefits and risks are inherent in environmental health and safety (EHS) issues related to nanotechnology. However, there is currently no structured approach for making justifiable and transparent decisions with explicit trade-offs between the many factors that need to be taken into account. While many possible decision-making approaches exist, we believe that multi-criteria decision analysis (MCDA) is a powerful and scientifically sound decision analytical framework for nanomaterial risk assessment and management. This paper combines state-of-the-art research in MCDA methods applicable to nanotechnology with a hypothetical case study for nanomaterial management. The example shows how MCDA application can balance societal benefits against unintended side effects and risks, and how it can also bring together multiple lines of evidence to estimate the likely toxicity and risk of nanomaterials given limited information on physical and chemical properties. The essential contribution of MCDA is to link this performance information with decision criteria and weightings elicited from scientists and managers, allowing visualization and quantification of the trade-offs involved in the decision-making process.

Medical decision-making and the patient: understanding preference patterns for growth hormone therapy using conjoint analysis.

PubMed

Singh, J; Cuttler, L; Shin, M; Silvers, J B; Neuhauser, D

1998-08-01

This study examines two questions that relate to patients' role in medical decision making: (1) Do patients utilize multiple attributes in evaluating different treatment options?, and (2) Do patient treatment preferences evidence heterogeneity and disparate patterns? Although research has examined these questions by using either individual- or aggregate-level approaches, the authors demonstrate an intermediate level approach (ie, relating to patient subgroups). The authors utilize growth augmentation therapy (GAT) as a context for analyzing these questions because GAT reflects a class of nonemergency treatments that (1) are based on genetic technology, (2) aim to improve the quality (rather than quantity) of life, and (3) offer useful insights for the patient's role in medical decision making. Using conjoint analysis, a methodology especially suited for the study of patient-consumer preferences but largely unexplored in the medical field, data were obtained from 154 parents for their decision to pursue GAT for their child. In all, six attributes were utilized to study GAT, including risk of long-term side effects (1:10,000 or 1:100,000), certainty of effect (50% or 100% of cases), amount of effect (1-2 inches or 4-5 inches in adult height), out-of-pocket cost ($100, $2,000, or $10,000/year) and child's attitude (likes or not likes therapy). An experimental design using conjoint analysis procedures revealed five preference patterns that reflect clear disparities in the importance that parents attach to the different attributes of growth therapy. These preference patterns are (1) child-focused (23%), (2) risk-conscious (36%), (3) balanced (23%), (4) cost-conscious (14%), and (5) ease-of-use (4%) oriented. Additional tests provided evidence for the validity of these preference patterns. Finally, this preference heterogeneity related systematically to parental characteristics (eg, demographic, psychologic). The study results offer additional insights into medical decision making with the consumer as the focal point and extend previous work that has tended to emphasize either an individual- or aggregate-based analysis. Implications for researchers and health care delivery in general and growth hormone management in particular are provided.

Qualitative Analysis of Surveyed Emergency Responders and the Identified Factors That Affect First Stage of Primary Triage Decision-Making of Mass Casualty Incidents

PubMed Central

Klein, Kelly R.; Burkle Jr., Frederick M.; Swienton, Raymond; King, Richard V.; Lehman, Thomas; North, Carol S.

2016-01-01

Introduction: After all large-scale disasters multiple papers are published describing the shortcomings of the triage methods utilized. This paper uses medical provider input to help describe attributes and patient characteristics that impact triage decisions. Methods: A survey distributed electronically to medical providers with and without disaster experience. Questions asked included what disaster experiences they had, and to rank six attributes in order of importance regarding triage. Results: 403 unique completed surveys were analyzed. 92% practiced a structural triage approach with the rest reporting they used “gestalt”.(gut feeling) Twelve per cent were identified as having placed patients in an expectant category during triage. Respiratory status, ability to speak, perfusion/pulse were all ranked in the top three. Gut feeling regardless of statistical analysis was fourth. Supplies were ranked in the top four when analyzed for those who had placed patients in the expectant category. Conclusion: Primary triage decisions in a mass casualty scenario are multifactorial and encompass patient mobility, life saving interventions, situational instincts, and logistics. PMID:27651979

The association between job strain and emotional exhaustion in a cohort of 1,028 Finnish teachers.

PubMed

Santavirta, Nina; Solovieva, Svetlana; Theorell, Töres

2007-03-01

Teachers' work overload has been the subject of intense research, and the results of these studies show that a substantial proportion of teachers perceive their job as very stressful. To investigate how different formulations of high demands and low decision latitude was related to teachers' burnout, and to estimate the possible interaction between these factors. The sample consisted of 1,028 school teachers. Multivariate covariant analyses (MANCOVA) was used to evaluate the relationship between a high-strain job defined by 3 different cut-off points and burnout. Logistical regression analysis was used to estimate the separate and joint effects of demand and decision authority on emotional exhaustion. Interaction between high demands and low decision authority was analysed using relative excess risk due to interaction (RERI). An attributable proportion (AP) was calculated in order to estimate the proportion of emotionally exhausted teachers among those exposed to both risk factors that was attributable to their synergistic interaction. The group of teachers who perceived their job as a low-strain job was used as the reference group in the analysis. The effect of job strain on burnout was proved to be consistent and robust across alternative formulations. The main effect of high demands exceeded that of low decision authority in relation to emotional exhaustion. Furthermore, the 2 factors acted synergistically to increase the risk of burnout. In the case of burnout, teachers who perceived their job as highly demanding and low in control, 69% of the effect could be attributed to the synergism of these 2 factors.

The Role of Social Constructions and Biophysical Attributes of the Environment in Decision-Making in the Context of Biofuels and Rubber Production Partnership Regimes in Upland Philippines

NASA Astrophysics Data System (ADS)

Montefrio, M. F.

2012-12-01

Burgeoning attention in biofuels and natural rubber has spurred interest among governments and private companies in integrating marginalized communities into global commodity markets. Upland farmers from diverse cultural backgrounds and biophysical settings today are deciding whether to agree with partnership proposals from governments and private firms to grow biofuels and natural rubber. In this paper, I examine whether upland farmers' socio-environmental constructions (evaluative beliefs, place satisfaction, and ecological worldviews) and the actual biophysical attributes (land cover and soil types) of upland environments, respectively, function as significant predictors of the intent and decisions of indigenous and non-indigenous farmers to cooperate with government and private actors to establish certain biofuel crops and natural rubber production systems in Palawan, Philippines. Drawing from ethnography and statistical analysis of household surveys, I propose that social constructions and the biophysical attributes of the environment are closely related with each other and in turn both influence individual decision-making behavior in resource-based production partnership regimes. This has significant implications on the resilience of socio-ecological systems, particularly agro-ecosystems, as certain upland farmers prefer to engage in intensive, monocrop production of biofuels and natural rubber on relatively more biodiverse areas, such as secondary forests and traditional shifting cultivation lands. The study aims to advance new institutional theories of resource management, particularly Ostrom's Institutional Analysis and Development and Socio-Ecological Systems frameworks, and scholarship on environmental decision-making in the context of collective action.

[Comparative study on promoting blood effects of Danshen-Honghua herb pair with different preparations based on chemometrics and multi-attribute comprehensive index methods].

PubMed

Qu, Cheng; Tang, Yu-Ping; Shi, Xu-Qin; Zhou, Gui-Sheng; Shang, Er-Xin; Shang, Li-Li; Guo, Jian-Ming; Liu, Pei; Zhao, Jing; Zhao, Bu-Chang; Duan, Jin-Ao

2017-08-01

To evaluate the promoting blood circulation and removing blood stasis effects of Danshen-Honghua(DH) herb pair with different preparations (alcohol, 50% alcohol and water) on blood rheology and coagulation functions in acute blood stasis rats, and optimize the best preparation method of DH based on principal component analysis(PCA), hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods. Ice water bath and subcutaneous injection of adrenaline were both used to establish the acute blood stasis rat model. Then the blood stasis rats were administrated intragastrically with DH (alcohol, 50% alcohol and water) extracts. The whole blood viscosity(WBV), plasma viscosity(PV), erythrocyte sedimentation rate(ESR) and haematocrit(HCT) were tested to observe the effects of DH herb pair with different preparations and doses on hemorheology of blood stasis rats; the activated partial thromboplastin time(APTT), thrombin time(TT), prothrombin time(PT), and plasma fibrinogen(FIB) were tested to observe the effects of DH herb pair with different preparations on blood coagulation function and platelet aggregation of blood stasis rats. Then PCA, hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods were all used to comprehensively evaluate the total promoting blood circulation and removing blood stasis effects of DH herb pair with different preparations. The hemorheological indexes and coagulation parameters of model group had significant differences with normal blank group. As compared with the model group, the DH herb pair with different preparations at low, middle and high doses could improve the blood hemorheology indexes and coagulation parameters in acute blood stasis rats with dose-effect relation. Based on the PCA, hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods, the high dose group of 50% alcohol extract had the best effect of promoting blood circulation and removing blood stasis. Under the same dose but different preparations, 50% alcohol DH could obviously improve the hemorheology and blood coagulation function in acute blood stasis rats. These results suggested that DH herb pair with different preparations could obviously ameliorate the abnormality of hemorheology and blood coagulation function in acute blood stasis rats, and the optimized preparation of DH herb pair on promoting blood effects was 50% alcohol extract, providing scientific basis for more effective application of the DH herb pair in modern clinic medicine. Copyright© by the Chinese Pharmaceutical Association.

Multi-view Decision Making (MVDM) Workshop

DTIC Science & Technology

2009-02-01

reflect the realities of system-of-systems development, acquisition, fielding and support: multi-view decision making (MVDM). MVDM addresses the...including mission risk, interoperable acquisition, and operational security and survivability. Hence, a multi-view approach to decision making is

The role of contraceptive attributes in women's contraceptive decision making.

PubMed

Madden, Tessa; Secura, Gina M; Nease, Robert F; Politi, Mary C; Peipert, Jeffrey F

2015-07-01

Contraceptive methods have differing attributes. Women's preferences for these attributes may influence contraceptive decision making. Our objective was to identify women's contraceptive preferences among women initiating a new contraceptive method. We conducted a cross-sectional, self-administered survey of women's contraceptive preferences at the time of enrollment into the Contraceptive CHOICE Project. Participants were asked to rank the importance of 15 contraceptive attributes on a 3-point scale (1 = not at all important, 2 = somewhat important, and 3 = very important) and then to rank the 3 attributes that were the most important when choosing a contraceptive method. The survey also contained questions about prior contraceptive experience and barriers to contraceptive use. Information about demographic and reproductive characteristics was collected through the CHOICE Project baseline survey. There were 2590 women who completed the survey. Our sample was racially and socioeconomically diverse. Method attributes with the highest importance score (mean score [SD]) were effectiveness (2.97 [0.18]), safety (2.96 [0.22]), affordability (2.61 [0.61]), whether the method is long lasting (2.58 [0.61]), and whether the method is "forgettable" (2.54 [0.66]). The attributes most likely to be ranked by respondents among the top 3 attributes included effectiveness (84.2%), safety (67.8%), and side effects of the method (44.6%). Multiple contraceptive attributes influence decision making and no single attribute drives most women's decisions. Tailoring communication and helping women make complex tradeoffs between attributes can better support their contraceptive decisions and may assist them in making value-consistent choices. This process could improve continuation and satisfaction. Copyright © 2015 Elsevier Inc. All rights reserved.

A Bottom-up Vulnerability Analysis of Water Systems with Decentralized Decision Making and Demographic Shifts- the Case of Jordan.

NASA Astrophysics Data System (ADS)

Lachaut, T.; Yoon, J.; Klassert, C. J. A.; Talozi, S.; Mustafa, D.; Knox, S.; Selby, P. D.; Haddad, Y.; Gorelick, S.; Tilmant, A.

2016-12-01

Probabilistic approaches to uncertainty in water systems management can face challenges of several types: non stationary climate, sudden shocks such as conflict-driven migrations, or the internal complexity and dynamics of large systems. There has been a rising trend in the development of bottom-up methods that place focus on the decision side instead of probability distributions and climate scenarios. These approaches are based on defining acceptability thresholds for the decision makers and considering the entire range of possibilities over which such thresholds are crossed. We aim at improving the knowledge on the applicability and relevance of this approach by enlarging its scope beyond climate uncertainty and single decision makers; thus including demographic shifts, internal system dynamics, and multiple stakeholders at different scales. This vulnerability analysis is part of the Jordan Water Project and makes use of an ambitious multi-agent model developed by its teams with the extensive cooperation of the Ministry of Water and Irrigation of Jordan. The case of Jordan is a relevant example for migration spikes, rapid social changes, resource depletion and climate change impacts. The multi-agent modeling framework used provides a consistent structure to assess the vulnerability of complex water resources systems with distributed acceptability thresholds and stakeholder interaction. A proof of concept and preliminary results are presented for a non-probabilistic vulnerability analysis that involves different types of stakeholders, uncertainties other than climatic and the integration of threshold-based indicators. For each stakeholder (agent) a vulnerability matrix is constructed over a multi-dimensional domain, which includes various hydrologic and/or demographic variables.

Multi-enzyme logic network architectures for assessing injuries: digital processing of biomarkers.

PubMed

Halámek, Jan; Bocharova, Vera; Chinnapareddy, Soujanya; Windmiller, Joshua Ray; Strack, Guinevere; Chuang, Min-Chieh; Zhou, Jian; Santhosh, Padmanabhan; Ramirez, Gabriela V; Arugula, Mary A; Wang, Joseph; Katz, Evgeny

2010-12-01

A multi-enzyme biocatalytic cascade processing simultaneously five biomarkers characteristic of traumatic brain injury (TBI) and soft tissue injury (STI) was developed. The system operates as a digital biosensor based on concerted function of 8 Boolean AND logic gates, resulting in the decision about the physiological conditions based on the logic analysis of complex patterns of the biomarkers. The system represents the first example of a multi-step/multi-enzyme biosensor with the built-in logic for the analysis of complex combinations of biochemical inputs. The approach is based on recent advances in enzyme-based biocomputing systems and the present paper demonstrates the potential applicability of biocomputing for developing novel digital biosensor networks.

Four Vantage Points to the Language Performance and Capacity of Human Beings: Response to Saloviita and Sariola.

ERIC Educational Resources Information Center

Niemi, Jussi; Karna-Lin, Eija

2003-01-01

This response to EC 633 617, an analysis of a purported case of facilitated communication, stresses the role of linguistic and grammatical analysis of texts attributed to a Finnish man diagnosed with mental retardation and cerebral palsy. It identifies weaknesses in the analysis, urges use of multi-theoretical approaches, and notes the benefits…

An application of multiattribute decision analysis to the Space Station Freedom program. Case study: Automation and robotics technology evaluation

NASA Technical Reports Server (NTRS)

Smith, Jeffrey H.; Levin, Richard R.; Carpenter, Elisabeth J.

1990-01-01

The results are described of an application of multiattribute analysis to the evaluation of high leverage prototyping technologies in the automation and robotics (A and R) areas that might contribute to the Space Station (SS) Freedom baseline design. An implication is that high leverage prototyping is beneficial to the SS Freedom Program as a means for transferring technology from the advanced development program to the baseline program. The process also highlights the tradeoffs to be made between subsidizing high value, low risk technology development versus high value, high risk technology developments. Twenty one A and R Technology tasks spanning a diverse array of technical concepts were evaluated using multiattribute decision analysis. Because of large uncertainties associated with characterizing the technologies, the methodology was modified to incorporate uncertainty. Eight attributes affected the rankings: initial cost, operation cost, crew productivity, safety, resource requirements, growth potential, and spinoff potential. The four attributes of initial cost, operations cost, crew productivity, and safety affected the rankings the most.

Comparing capacity coefficient and dual task assessment of visual multitasking workload

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blaha, Leslie M.

Capacity coefficient analysis could offer a theoretically grounded alternative approach to subjective measures and dual task assessment of cognitive workload. Workload capacity or workload efficiency is a human information processing modeling construct defined as the amount of information that can be processed by the visual cognitive system given a specified of amount of time. In this paper, I explore the relationship between capacity coefficient analysis of workload efficiency and dual task response time measures. To capture multitasking performance, I examine how the relatively simple assumptions underlying the capacity construct generalize beyond the single visual decision making tasks. The fundamental toolsmore » for measuring workload efficiency are the integrated hazard and reverse hazard functions of response times, which are defined by log transforms of the response time distribution. These functions are used in the capacity coefficient analysis to provide a functional assessment of the amount of work completed by the cognitive system over the entire range of response times. For the study of visual multitasking, capacity coefficient analysis enables a comparison of visual information throughput as the number of tasks increases from one to two to any number of simultaneous tasks. I illustrate the use of capacity coefficients for visual multitasking on sample data from dynamic multitasking in the modified Multi-attribute Task Battery.« less

Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials.

PubMed

Hristozov, Danail; Zabeo, Alex; Alstrup Jensen, Keld; Gottardo, Stefania; Isigonis, Panagiotis; Maccalman, Laura; Critto, Andrea; Marcomini, Antonio

2016-11-01

Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.

Multi-objective, multiple participant decision support for water management in the Andarax catchment, Almeria

NASA Astrophysics Data System (ADS)

van Cauwenbergh, N.; Pinte, D.; Tilmant, A.; Frances, I.; Pulido-Bosch, A.; Vanclooster, M.

2008-04-01

Water management in the Andarax river basin (Almeria, Spain) is a multi-objective, multi-participant, long-term decision-making problem that faces several challenges. Adequate water allocation needs informed decisions to meet increasing socio-economic demands while respecting the environmental integrity of this basin. Key players in the Andarax water sector include the municipality of Almeria, the irrigators involved in the intensive greenhouse agricultural sector, and booming second residences. A decision support system (DSS) is developed to rank different sustainable planning and management alternatives according to their socio-economic and environmental performance. The DSS is intimately linked to sustainability indicators and is designed through a public participation process. Indicators are linked to criteria reflecting stakeholders concerns in the 2005 field survey, such as fulfilling water demand, water price, technical and economical efficiency, social and environmental impacts. Indicators can be partly quantified after simulating the operation of the groundwater reservoir over a 20-year planning period and partly through a parallel expert evaluation process. To predict the impact of future water demand in the catchment, several development scenarios are designed to be evaluated in the DSS. The successive multi-criteria analysis of the performance indicators permits the ranking of the different management alternatives according to the multiple objectives formulated by the different sectors/participants. This allows more informed and transparent decision-making processes for the Andarax river basin, recognizing both the socio-economic and environmental dimensions of water resources management.

Development of a First-of-a-Kind Deterministic Decision-Making Tool for Supervisory Control System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cetiner, Sacit M; Kisner, Roger A; Muhlheim, Michael David

2015-07-01

Decision-making is the process of identifying and choosing alternatives where each alternative offers a different approach or path to move from a given state or condition to a desired state or condition. The generation of consistent decisions requires that a structured, coherent process be defined, immediately leading to a decision-making framework. The overall objective of the generalized framework is for it to be adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or nomore » human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision- making modules that can perform a given set of tasks reliably. Risk-informed decision making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The implementation of the probabilistic portion of the decision-making engine of the proposed supervisory control system was detailed in previous milestone reports. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic multi-attribute decision-making framework uses variable sensor data (e.g., outlet temperature) and calculates where it is within the challenge state, its trajectory, and margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. Metrics to be evaluated include stability, cost, time to complete (action), power level, etc. The integration of deterministic calculations using multi-physics analyses (i.e., neutronics, thermal, and thermal-hydraulics) and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermal-hydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies.« less

Fuzzy Logic Approaches to Multi-Objective Decision-Making in Aerospace Applications

NASA Technical Reports Server (NTRS)

Hardy, Terry L.

1994-01-01

Fuzzy logic allows for the quantitative representation of multi-objective decision-making problems which have vague or fuzzy objectives and parameters. As such, fuzzy logic approaches are well-suited to situations where alternatives must be assessed by using criteria that are subjective and of unequal importance. This paper presents an overview of fuzzy logic and provides sample applications from the aerospace industry. Applications include an evaluation of vendor proposals, an analysis of future space vehicle options, and the selection of a future space propulsion system. On the basis of the results provided in this study, fuzzy logic provides a unique perspective on the decision-making process, allowing the evaluator to assess the degree to which each option meets the evaluation criteria. Future decision-making should take full advantage of fuzzy logic methods to complement existing approaches in the selection of alternatives.

Coastal flooding as a parameter in multi-criteria analysis for industrial site selection

NASA Astrophysics Data System (ADS)

Christina, C.; Memos, C.; Diakoulaki, D.

2014-12-01

Natural hazards can trigger major industrial accidents, which apart from affecting industrial installations may cause a series of accidents with serious impacts on human health and the environment far beyond the site boundary. Such accidents, also called Na-Tech (natural - technical) accidents, deserve particular attention since they can cause release of hazardous substances possibly resulting in severe environmental pollution, explosions and/or fires. There are different kinds of natural events or, in general terms, of natural causes of industrial accidents, such as landslides, hurricanes, high winds, tsunamis, lightning, cold/hot temperature, floods, heavy rains etc that have caused accidents. The scope of this paper is to examine the coastal flooding as a parameter in causing an industrial accident, such as the nuclear disaster in Fukushima, Japan, and the critical role of this parameter in industrial site selection. Land use planning is a complex procedure that requires multi-criteria decision analysis involving economic, environmental and social parameters. In this context the parameter of a natural hazard occurrence, such as coastal flooding, for industrial site selection should be set by the decision makers. In this paper it is evaluated the influence that has in the outcome of a multi-criteria decision analysis for industrial spatial planning the parameter of an accident risk triggered by coastal flooding. The latter is analyzed in the context of both sea-and-inland induced flooding.

TELEMAM: a cluster randomised trial to assess the use of telemedicine in multi-disciplinary breast cancer decision making.

PubMed

Kunkler, I H; Prescott, R J; Lee, R J; Brebner, J A; Cairns, J A; Fielding, R G; Bowman, A; Neades, G; Walls, A D F; Chetty, U; Dixon, J M; Smith, M E; Gardner, T W; Macnab, M; Swann, S; Maclean, J R

2007-11-01

The TELEMAM trial aimed to assess the clinical effectiveness and costs of telemedicine in conducting breast cancer multi-disciplinary meetings (MDTs). Over 12 months 473 MDT patient discussions in two district general hospitals (DGHs) were cluster randomised (2:1) to the intervention of telemedicine linkage to breast specialists in a cancer centre or to the control group of 'in-person' meetings. Primary endpoints were clinical effectiveness and costs. Economic analysis was based on a cost-minimisation approach. Levels of agreement of MDT members on a scale from 1 to 5 were high and similar in both the telemedicine and standard meetings for decision sharing (4.04 versus 4.17), consensus (4.06 versus 4.20) and confidence in the decision (4.16 versus 4.07). The threshold at which the telemedicine meetings became cheaper than standard MDTs was approximately 40 meetings per year. Telemedicine delivered breast cancer multi-disciplinary meetings have similar clinical effectiveness to standard 'in-person' meetings.

Multi-criteria decision analysis for waste management in Saharawi refugee camps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garfi, M.; Tondelli, S.; Bonoli, A.

2009-10-15

The aim of this paper is to compare different waste management solutions in Saharawi refugee camps (Algeria) and to test the feasibility of a decision-making method developed to be applied in particular conditions in which environmental and social aspects must be considered. It is based on multi criteria analysis, and in particular on the analytic hierarchy process (AHP), a mathematical technique for multi-criteria decision making (Saaty, T.L., 1980. The Analytic Hierarchy Process. McGraw-Hill, New York, USA; Saaty, T.L., 1990. How to Make a Decision: The Analytic Hierarchy Process. European Journal of Operational Research; Saaty, T.L., 1994. Decision Making for Leaders:more » The Analytic Hierarchy Process in a Complex World. RWS Publications, Pittsburgh, PA), and on participatory approach, focusing on local community's concerns. The research compares four different waste collection and management alternatives: waste collection by using three tipper trucks, disposal and burning in an open area; waste collection by using seven dumpers and disposal in a landfill; waste collection by using seven dumpers and three tipper trucks and disposal in a landfill; waste collection by using three tipper trucks and disposal in a landfill. The results show that the second and the third solutions provide better scenarios for waste management. Furthermore, the discussion of the results points out the multidisciplinarity of the approach, and the equilibrium between social, environmental and technical impacts. This is a very important aspect in a humanitarian and environmental project, confirming the appropriateness of the chosen method.« less

DRUG EVALUATION AND DECISION MAKING IN CATALONIA: DEVELOPMENT AND VALIDATION OF A METHODOLOGICAL FRAMEWORK BASED ON MULTI-CRITERIA DECISION ANALYSIS (MCDA) FOR ORPHAN DRUGS.

PubMed

Gilabert-Perramon, Antoni; Torrent-Farnell, Josep; Catalan, Arancha; Prat, Alba; Fontanet, Manel; Puig-Peiró, Ruth; Merino-Montero, Sandra; Khoury, Hanane; Goetghebeur, Mireille M; Badia, Xavier

2017-01-01

The aim of this study was to adapt and assess the value of a Multi-Criteria Decision Analysis (MCDA) framework (EVIDEM) for the evaluation of Orphan drugs in Catalonia (Catalan Health Service). The standard evaluation and decision-making procedures of CatSalut were compared with the EVIDEM methodology and contents. The EVIDEM framework was adapted to the Catalan context, focusing on the evaluation of Orphan drugs (PASFTAC program), during a Workshop with sixteen PASFTAC members. The criteria weighting was done using two different techniques (nonhierarchical and hierarchical). Reliability was assessed by re-test. The EVIDEM framework and methodology was found useful and feasible for Orphan drugs evaluation and decision making in Catalonia. All the criteria considered for the development of the CatSalut Technical Reports and decision making were considered in the framework. Nevertheless, the framework could improve the reporting of some of these criteria (i.e., "unmet needs" or "nonmedical costs"). Some Contextual criteria were removed (i.e., "Mandate and scope of healthcare system", "Environmental impact") or adapted ("population priorities and access") for CatSalut purposes. Independently of the weighting technique considered, the most important evaluation criteria identified for orphan drugs were: "disease severity", "unmet needs" and "comparative effectiveness", while the "size of the population" had the lowest relevance for decision making. Test-retest analysis showed weight consistency among techniques, supporting reliability overtime. MCDA (EVIDEM framework) could be a useful tool to complement the current evaluation methods of CatSalut, contributing to standardization and pragmatism, providing a method to tackle ethical dilemmas and facilitating discussions related to decision making.

Urban photogrammetric data base for multi-purpose cadastral-based information systems: the Riyadh city case

NASA Astrophysics Data System (ADS)

Al-garni, Abdullah M.

Urban information systems are economic resources that can benefit decision makers in the planning, development, and management of urban projects and resources. In this research, a conceptual model-based prototype Urban Geographic Information System (UGIS) is developed. The base maps used in developing the system and acquiring visual attributes are obtained from aerial photographs. The system is a multi-purpose parcel-based one that can serve many urban applications such as public utilities, health centres, schools, population estimation, road engineering and maintenance, and many others. A modern region in the capital city of Saudi Arabia is used for the study. The developed model is operational for one urban application (population estimation) and is tested for that particular application. The results showed that the system has a satisfactory accuracy and that it may well be promising for other similar urban applications in countries with similar demographic and social characteristics.

Evaluating the Role of Attention in the Context of Unconscious Thought Theory: Differential Impact of Attentional Scope and Load on Preference and Memory

PubMed Central

Srinivasan, Narayanan; Mukherjee, Sumitava; Mishra, Maruti V.; Kesarwani, Smriti

2013-01-01

Attention is a key process used to conceptualize and define modes of thought, but we lack information about the role of specific attentional processes on preferential choice and memory in multi-attribute decision making. In this study, we examine the role of attention based on two dimensions, attentional scope and load on choice preference strength and memory using a paradigm that arguably elicits unconscious thought. Scope of attention was manipulated by using global or local processing during distraction (Experiment 1) and before the information-encoding stage (Experiment 2). Load was manipulated by using the n-back task in Experiment 1. Results from Experiment 1 show that global processing or distributed attention during distraction results in stronger preference irrespective of load but better memory only at low cognitive load. Task difficulty or load did not have any effect on preference or memory. In Experiment 2, distributed attention before attribute encoding facilitated only memory but did not influence preference. Results show that attentional processes at different stages of processing like distraction and information-encoding influence decision making processes. Scope of attention not only influences preference and memory but the manner in which attentional scope influences them depends on both load and stage of information processing. The results indicate the important role of attention in processes critical for decision making and calls for a re-evaluation of the unconscious thought theory (UTT) and the need for reconceptualizing the role of attention. PMID:23382726

Evaluating the role of attention in the context of unconscious thought theory: differential impact of attentional scope and load on preference and memory.

PubMed

Srinivasan, Narayanan; Mukherjee, Sumitava; Mishra, Maruti V; Kesarwani, Smriti

2013-01-01

Attention is a key process used to conceptualize and define modes of thought, but we lack information about the role of specific attentional processes on preferential choice and memory in multi-attribute decision making. In this study, we examine the role of attention based on two dimensions, attentional scope and load on choice preference strength and memory using a paradigm that arguably elicits unconscious thought. Scope of attention was manipulated by using global or local processing during distraction (Experiment 1) and before the information-encoding stage (Experiment 2). Load was manipulated by using the n-back task in Experiment 1. Results from Experiment 1 show that global processing or distributed attention during distraction results in stronger preference irrespective of load but better memory only at low cognitive load. Task difficulty or load did not have any effect on preference or memory. In Experiment 2, distributed attention before attribute encoding facilitated only memory but did not influence preference. Results show that attentional processes at different stages of processing like distraction and information-encoding influence decision making processes. Scope of attention not only influences preference and memory but the manner in which attentional scope influences them depends on both load and stage of information processing. The results indicate the important role of attention in processes critical for decision making and calls for a re-evaluation of the unconscious thought theory (UTT) and the need for reconceptualizing the role of attention.

Outcome based state budget allocation for diabetes prevention programs using multi-criteria optimization with robust weights.

PubMed

Mehrotra, Sanjay; Kim, Kibaek

2011-12-01

We consider the problem of outcomes based budget allocations to chronic disease prevention programs across the United States (US) to achieve greater geographical healthcare equity. We use Diabetes Prevention and Control Programs (DPCP) by the Center for Disease Control and Prevention (CDC) as an example. We present a multi-criteria robust weighted sum model for such multi-criteria decision making in a group decision setting. The principal component analysis and an inverse linear programming techniques are presented and used to study the actual 2009 budget allocation by CDC. Our results show that the CDC budget allocation process for the DPCPs is not likely model based. In our empirical study, the relative weights for different prevalence and comorbidity factors and the corresponding budgets obtained under different weight regions are discussed. Parametric analysis suggests that money should be allocated to states to promote diabetes education and to increase patient-healthcare provider interactions to reduce disparity across the US.

Parental Health Attributions of Childhood Health and Illness: Development of the Pediatric Cultural Health Attributions Questionnaire (Pedi-CHAQ).

PubMed

Vaughn, Lisa M; McLinden, Daniel J; Shellmer, Diana; Baker, Raymond C

2011-01-01

The causes attributed to childhood health and illness across cultures (cultural health attributions) are key factors that are now more frequently identified as affecting the health outcomes of children. Research suggests that the causes attributed to an event such as illness are thought to affect subsequent motivation, emotional response, decision making, and behavior. To date, there is no measure of health attributions appropriate for use with parents of pediatric patients. Using the Many-Facets approach to Rasch analysis, this study assesses the psychometrics of a newly developed instrument, the Pediatric Health Attributions Questionnaire (Pedi-CHAQ), a measure designed to assess the cultural health attributions of parents in diverse communities. Results suggest acceptable Rasch model statistics of fit and reliability for the Pedi-CHAQ. A shortened version of the questionnaire was developed as a result of this study and next steps are discussed.

Optimization of the decision-making process for the selection of therapeutics to undergo clinical testing for spinal cord injury in the North American Clinical Trials Network.

PubMed

Guest, James; Harrop, James S; Aarabi, Bizhan; Grossman, Robert G; Fawcett, James W; Fehlings, Michael G; Tator, Charles H

2012-09-01

The North American Clinical Trials Network (NACTN) includes 9 clinical centers funded by the US Department of Defense and the Christopher Reeve Paralysis Foundation. Its purpose is to accelerate clinical testing of promising therapeutics in spinal cord injury (SCI) through the development of a robust interactive infrastructure. This structure includes key committees that serve to provide longitudinal guidance to the Network. These committees include the Executive, Data Management, and Neurological Outcome Assessments Committees, and the Therapeutic Selection Committee (TSC), which is the subject of this manuscript. The NACTN brings unique elements to the SCI field. The Network's stability is not restricted to a single clinical trial. Network members have diverse expertise and include experts in clinical care, clinical trial design and methodology, pharmacology, preclinical and clinical research, and advanced rehabilitation techniques. Frequent systematic communication is assigned a high value, as is democratic process, fairness and efficiency of decision making, and resource allocation. This article focuses on how decision making occurs within the TSC to rank alternative therapeutics according to 2 main variables: quality of the preclinical data set, and fit with the Network's aims and capabilities. This selection process is important because if the Network's resources are committed to a therapeutic, alternatives cannot be pursued. A proposed methodology includes a multicriteria decision analysis that uses a Multi-Attribute Global Inference of Quality matrix to quantify the process. To rank therapeutics, the TSC uses a series of consensus steps designed to reduce individual and group bias and limit subjectivity. Given the difficulties encountered by industry in completing clinical trials in SCI, stable collaborative not-for-profit consortia, such as the NACTN, may be essential to clinical progress in SCI. The evolution of the NACTN also offers substantial opportunity to refine decision making and group dynamics. Making the best possible decisions concerning therapeutics selection for trial testing is a cornerstone of the Network's function.

Monte Carlo-based interval transformation analysis for multi-criteria decision analysis of groundwater management strategies under uncertain naphthalene concentrations and health risks

NASA Astrophysics Data System (ADS)

Ren, Lixia; He, Li; Lu, Hongwei; Chen, Yizhong

2016-08-01

A new Monte Carlo-based interval transformation analysis (MCITA) is used in this study for multi-criteria decision analysis (MCDA) of naphthalene-contaminated groundwater management strategies. The analysis can be conducted when input data such as total cost, contaminant concentration and health risk are represented as intervals. Compared to traditional MCDA methods, MCITA-MCDA has the advantages of (1) dealing with inexactness of input data represented as intervals, (2) mitigating computational time due to the introduction of Monte Carlo sampling method, (3) identifying the most desirable management strategies under data uncertainty. A real-world case study is employed to demonstrate the performance of this method. A set of inexact management alternatives are considered in each duration on the basis of four criteria. Results indicated that the most desirable management strategy lied in action 15 for the 5-year, action 8 for the 10-year, action 12 for the 15-year, and action 2 for the 20-year management.

Urban Vulnerability Assessment to Seismic Hazard through Spatial Multi-Criteria Analysis. Case Study: the Bucharest Municipality/Romania

NASA Astrophysics Data System (ADS)

Armas, Iuliana; Dumitrascu, Silvia; Bostenaru, Maria

2010-05-01

In the context of an explosive increase in value of the damage caused by natural disasters, an alarming challenge in the third millennium is the rapid growth of urban population in vulnerable areas. Cities are, by definition, very fragile socio-ecological systems with a high level of vulnerability when it comes to environmental changes and that are responsible for important transformations of the space, determining dysfunctions shown in the state of the natural variables (Parker and Mitchell, 1995, The OFDA/CRED International Disaster Database). A contributing factor is the demographic dynamic that affects urban areas. The aim of this study is to estimate the overall vulnerability of the urban area of Bucharest in the context of the seismic hazard, by using environmental, socio-economic, and physical measurable variables in the framework of a spatial multi-criteria analysis. For this approach the capital city of Romania was chosen based on its high vulnerability due to the explosive urban development and the advanced state of degradation of the buildings (most of the building stock being built between 1940 and 1977). Combining these attributes with the seismic hazard induced by the Vrancea source, Bucharest was ranked as the 10th capital city worldwide in the terms of seismic risk. Over 40 years of experience in the natural risk field shows that the only directly accessible way to reduce the natural risk is by reducing the vulnerability of the space (Adger et al., 2001, Turner et al., 2003; UN/ISDR, 2004, Dayton-Johnson, 2004, Kasperson et al., 2005; Birkmann, 2006 etc.). In effect, reducing the vulnerability of urban spaces would imply lower costs produced by natural disasters. By applying the SMCA method, the result reveals a circular pattern, signaling as hot spots the Bucharest historic centre (located on a river terrace and with aged building stock) and peripheral areas (isolated from the emergency centers and defined by precarious social and economic conditions). In effect, the example of Bucharest demonstrates how the results shape the ‘vulnerability to seismic hazard profile of the city, based on which decision makers could develop proper mitigation strategies. To sum up, the use of an analytical framework as the standard Spatial Multi-Criteria Analysis (SMCA) - despite all difficulties in creating justifiable weights (Yeh et al., 1999) - results in accurate estimations of the state of the urban system. Although this method was often mistrusted by decision makers (Janssen, 2001), we consider that the results can represent, based on precisely the level of generalization, a decision support framework for policy makers to critically reflect on possible risk mitigation plans. Further study will lead to the improvement of the analysis by integrating a series of daytime and nighttime scenarios and a better definition of the constructed space variables.

Application of multi-criteria decision-making on strategic municipal solid waste management in Dalmatia, Croatia.

PubMed

Vego, Goran; Kucar-Dragicević, Savka; Koprivanac, Natalija

2008-11-01

The efficiency of providing a waste management system in the coastal part of Croatia consisting of four Dalmatian counties has been modelled. Two multi-criteria decision-making (MCDM) methods, PROMETHEE and GAIA, were applied to assist with the systematic analysis and evaluation of the alternatives. The analysis covered two levels; first, the potential number of waste management centres resulting from possible inter-county cooperation; and second, the relative merits of siting of waste management centres in the coastal or hinterland zone was evaluated. The problem was analysed according to several criteria; and ecological, economic, social and functional criteria sets were identified as relevant to the decision-making process. The PROMETHEE and GAIA methods were shown to be efficient tools for analysing the problem considered. Such an approach provided new insights to waste management planning at the strategic level, and gave a reason for rethinking some of the existing strategic waste management documents in Croatia.

Multi-parameter approach to evaluate the timing of memory status after 17DD-YF primary vaccination.

PubMed

Costa-Pereira, Christiane; Campi-Azevedo, Ana Carolina; Coelho-Dos-Reis, Jordana Grazziela; Peruhype-Magalhães, Vanessa; Araújo, Márcio Sobreira Silva; do Vale Antonelli, Lis Ribeiro; Fonseca, Cristina Toscano; Lemos, Jandira Aparecida; Malaquias, Luiz Cosme Cote; de Souza Gomes, Matheus; Rodrigues Amaral, Laurence; Rios, Maria; Chancey, Caren; Persi, Harold Richard; Pereira, Jorge Marcelo; de Sousa Maia, Maria de Lourdes; Freire, Marcos da Silva; Martins, Reinaldo de Menezes; Homma, Akira; Simões, Marisol; Yamamura, Anna Yoshida; Farias, Roberto Henrique Guedes; Romano, Alessandro Pecego Martins; Domingues, Carla Magda; Tauil, Pedro Luiz; Vasconcelos, Pedro Fernando Costa; Caldas, Iramaya Rodrigues; Camacho, Luiz Antônio; Teixeira-Carvalho, Andrea; Martins-Filho, Olindo Assis

2018-06-01

In this investigation, machine-enhanced techniques were applied to bring about scientific insights to identify a minimum set of phenotypic/functional memory-related biomarkers for post-vaccination follow-up upon yellow fever (YF) vaccination. For this purpose, memory status of circulating T-cells (Naïve/early-effector/Central-Memory/Effector-Memory) and B-cells (Naïve/non-Classical-Memory/Classical-Memory) along with the cytokine profile (IFN/TNF/IL-5/IL-10) were monitored before-NV(day0) and at distinct time-points after 17DD-YF primary vaccination-PV(day30-45); PV(year1-9) and PV(year10-11). A set of biomarkers (eEfCD4; EMCD4; CMCD19; EMCD8; IFNCD4; IL-5CD8; TNFCD4; IFNCD8; TNFCD8; IL-5CD19; IL-5CD4) were observed in PV(day30-45), but not in NV(day0), with most of them still observed in PV(year1-9). Deficiencies of phenotypic/functional biomarkers were observed in NV(day0), while total lack of memory-related attributes was observed in PV(year10-11), regardless of the age at primary vaccination. Venn-diagram analysis pre-selected 10 attributes (eEfCD4, EMCD4, CMCD19, EMCD8, IFNCD4, IL-5CD8, TNFCD4, IFNCD8, TNFCD8 and IL-5CD4), of which the overall mean presented moderate accuracy to discriminate PV(day30-45)&PV(year1-9) from NV(day0)&PV(year10-11). Multi-parameter approaches and decision-tree algorithms defined the EMCD8 and IL-5CD4 attributes as the top-two predictors with moderated performance. Together with the PRNT titers, the top-two biomarkers led to a resultant memory status observed in 80% and 51% of volunteers in PV(day30-45) and PV(year1-9), contrasting with 0% and 29% found in NV(day0) and PV(year10-11), respectively. The deficiency of memory-related attributes observed at PV(year10-11) underscores the conspicuous time-dependent decrease of resultant memory following17DD-YF primary vaccination that could be useful to monitor potential correlates of protection in areas under risk of YF transmission.

Multi-parameter approach to evaluate the timing of memory status after 17DD-YF primary vaccination

PubMed Central

Costa-Pereira, Christiane; Campi-Azevedo, Ana Carolina; Coelho-dos-Reis, Jordana Grazziela; Peruhype-Magalhães, Vanessa; Araújo, Márcio Sobreira Silva; do Vale Antonelli, Lis Ribeiro; Fonseca, Cristina Toscano; Lemos, Jandira Aparecida; Malaquias, Luiz Cosme Cote; de Souza Gomes, Matheus; Rodrigues Amaral, Laurence; Rios, Maria; Chancey, Caren; Persi, Harold Richard; Pereira, Jorge Marcelo; de Sousa Maia, Maria de Lourdes; Freire, Marcos da Silva; Martins, Reinaldo de Menezes; Homma, Akira; Simões, Marisol; Yamamura, Anna Yoshida; Farias, Roberto Henrique Guedes; Romano, Alessandro Pecego Martins; Domingues, Carla Magda; Tauil, Pedro Luiz; Vasconcelos, Pedro Fernando Costa; Caldas, Iramaya Rodrigues; Camacho, Luiz Antônio; Teixeira-Carvalho, Andrea; Martins-Filho, Olindo Assis

2018-01-01

In this investigation, machine-enhanced techniques were applied to bring about scientific insights to identify a minimum set of phenotypic/functional memory-related biomarkers for post-vaccination follow-up upon yellow fever (YF) vaccination. For this purpose, memory status of circulating T-cells (Naïve/early-effector/Central-Memory/Effector-Memory) and B-cells (Naïve/non-Classical-Memory/Classical-Memory) along with the cytokine profile (IFN/TNF/IL-5/IL-10) were monitored before-NV(day0) and at distinct time-points after 17DD-YF primary vaccination—PV(day30-45); PV(year1-9) and PV(year10-11). A set of biomarkers (eEfCD4; EMCD4; CMCD19; EMCD8; IFNCD4; IL-5CD8; TNFCD4; IFNCD8; TNFCD8; IL-5CD19; IL-5CD4) were observed in PV(day30-45), but not in NV(day0), with most of them still observed in PV(year1-9). Deficiencies of phenotypic/functional biomarkers were observed in NV(day0), while total lack of memory-related attributes was observed in PV(year10-11), regardless of the age at primary vaccination. Venn-diagram analysis pre-selected 10 attributes (eEfCD4, EMCD4, CMCD19, EMCD8, IFNCD4, IL-5CD8, TNFCD4, IFNCD8, TNFCD8 and IL-5CD4), of which the overall mean presented moderate accuracy to discriminate PV(day30-45)&PV(year1-9) from NV(day0)&PV(year10-11). Multi-parameter approaches and decision-tree algorithms defined the EMCD8 and IL-5CD4 attributes as the top-two predictors with moderated performance. Together with the PRNT titers, the top-two biomarkers led to a resultant memory status observed in 80% and 51% of volunteers in PV(day30-45) and PV(year1-9), contrasting with 0% and 29% found in NV(day0) and PV(year10-11), respectively. The deficiency of memory-related attributes observed at PV(year10-11) underscores the conspicuous time-dependent decrease of resultant memory following17DD-YF primary vaccination that could be useful to monitor potential correlates of protection in areas under risk of YF transmission. PMID:29879134

Estimation of Survival Probabilities for Use in Cost-effectiveness Analyses: A Comparison of a Multi-state Modeling Survival Analysis Approach with Partitioned Survival and Markov Decision-Analytic Modeling

PubMed Central

Williams, Claire; Lewsey, James D.; Mackay, Daniel F.; Briggs, Andrew H.

2016-01-01

Modeling of clinical-effectiveness in a cost-effectiveness analysis typically involves some form of partitioned survival or Markov decision-analytic modeling. The health states progression-free, progression and death and the transitions between them are frequently of interest. With partitioned survival, progression is not modeled directly as a state; instead, time in that state is derived from the difference in area between the overall survival and the progression-free survival curves. With Markov decision-analytic modeling, a priori assumptions are often made with regard to the transitions rather than using the individual patient data directly to model them. This article compares a multi-state modeling survival regression approach to these two common methods. As a case study, we use a trial comparing rituximab in combination with fludarabine and cyclophosphamide v. fludarabine and cyclophosphamide alone for the first-line treatment of chronic lymphocytic leukemia. We calculated mean Life Years and QALYs that involved extrapolation of survival outcomes in the trial. We adapted an existing multi-state modeling approach to incorporate parametric distributions for transition hazards, to allow extrapolation. The comparison showed that, due to the different assumptions used in the different approaches, a discrepancy in results was evident. The partitioned survival and Markov decision-analytic modeling deemed the treatment cost-effective with ICERs of just over £16,000 and £13,000, respectively. However, the results with the multi-state modeling were less conclusive, with an ICER of just over £29,000. This work has illustrated that it is imperative to check whether assumptions are realistic, as different model choices can influence clinical and cost-effectiveness results. PMID:27698003

Estimation of Survival Probabilities for Use in Cost-effectiveness Analyses: A Comparison of a Multi-state Modeling Survival Analysis Approach with Partitioned Survival and Markov Decision-Analytic Modeling.

PubMed

Williams, Claire; Lewsey, James D; Mackay, Daniel F; Briggs, Andrew H

2017-05-01

Modeling of clinical-effectiveness in a cost-effectiveness analysis typically involves some form of partitioned survival or Markov decision-analytic modeling. The health states progression-free, progression and death and the transitions between them are frequently of interest. With partitioned survival, progression is not modeled directly as a state; instead, time in that state is derived from the difference in area between the overall survival and the progression-free survival curves. With Markov decision-analytic modeling, a priori assumptions are often made with regard to the transitions rather than using the individual patient data directly to model them. This article compares a multi-state modeling survival regression approach to these two common methods. As a case study, we use a trial comparing rituximab in combination with fludarabine and cyclophosphamide v. fludarabine and cyclophosphamide alone for the first-line treatment of chronic lymphocytic leukemia. We calculated mean Life Years and QALYs that involved extrapolation of survival outcomes in the trial. We adapted an existing multi-state modeling approach to incorporate parametric distributions for transition hazards, to allow extrapolation. The comparison showed that, due to the different assumptions used in the different approaches, a discrepancy in results was evident. The partitioned survival and Markov decision-analytic modeling deemed the treatment cost-effective with ICERs of just over £16,000 and £13,000, respectively. However, the results with the multi-state modeling were less conclusive, with an ICER of just over £29,000. This work has illustrated that it is imperative to check whether assumptions are realistic, as different model choices can influence clinical and cost-effectiveness results.

I know why you voted for Trump: (Over)inferring motives based on choice.

PubMed

Barasz, Kate; Kim, Tami; Evangelidis, Ioannis

2018-05-10

People often speculate about why others make the choices they do. This paper investigates how such inferences are formed as a function of what is chosen. Specifically, when observers encounter someone else's choice (e.g., of political candidate), they use the chosen option's attribute values (e.g., a candidate's specific stance on a policy issue) to infer the importance of that attribute (e.g., the policy issue) to the decision-maker. Consequently, when a chosen option has an attribute whose value is extreme (e.g., an extreme policy stance), observers infer-sometimes incorrectly-that this attribute disproportionately motivated the decision-maker's choice. Seven studies demonstrate how observers use an attribute's value to infer its weight-the value-weight heuristic-and identify the role of perceived diagnosticity: more extreme attribute values give observers the subjective sense that they know more about a decision-maker's preferences, and in turn, increase the attribute's perceived importance. The paper explores how this heuristic can produce erroneous inferences and influence broader beliefs about decision-makers. Copyright © 2018 Elsevier B.V. All rights reserved.

Periodic benefit-risk assessment using Bayesian stochastic multi-criteria acceptability analysis.

PubMed

Li, Kan; Yuan, Shuai Sammy; Wang, William; Wan, Shuyan Sabrina; Ceesay, Paulette; Heyse, Joseph F; Mt-Isa, Shahrul; Luo, Sheng

2018-04-01

Benefit-risk (BR) assessment is essential to ensure the best decisions are made for a medical product in the clinical development process, regulatory marketing authorization, post-market surveillance, and coverage and reimbursement decisions. One challenge of BR assessment in practice is that the benefit and risk profile may keep evolving while new evidence is accumulating. Regulators and the International Conference on Harmonization (ICH) recommend performing periodic benefit-risk evaluation report (PBRER) through the product's lifecycle. In this paper, we propose a general statistical framework for periodic benefit-risk assessment, in which Bayesian meta-analysis and stochastic multi-criteria acceptability analysis (SMAA) will be combined to synthesize the accumulating evidence. The proposed approach allows us to compare the acceptability of different drugs dynamically and effectively and accounts for the uncertainty of clinical measurements and imprecise or incomplete preference information of decision makers. We apply our approaches to two real examples in a post-hoc way for illustration purpose. The proposed method may easily be modified for other pre and post market settings, and thus be an important complement to the current structured benefit-risk assessment (sBRA) framework to improve the transparent and consistency of the decision-making process. Copyright © 2018 Elsevier Inc. All rights reserved.

Graduate Attribute Attainment in a Multi-Level Undergraduate Geography Course

ERIC Educational Resources Information Center

Mager, Sarah; Spronken-Smith, Rachel

2014-01-01

We investigated students' perceptions of graduate attributes in a multi-level (second and third year) geography course. A case study with mixed methodology was employed, with data collected through focus groups and a survey. We found that undergraduate geography students can identify the skills, knowledge and attributes that are developed through…

Attitudes towards poverty, organizations, ethics and morals: Israeli social workers' shared decision making.

PubMed

Levin, Lia; Schwartz-Tayri, Talia

2017-06-01

Partnerships between service users and social workers are complex in nature and can be driven by both personal and contextual circumstances. This study sought to explore the relationship between social workers' involvement in shared decision making with service users, their attitudes towards service users in poverty, moral standards and health and social care organizations' policies towards shared decision making. Based on the responses of 225 licensed social workers from health and social care agencies in the public, private and third sectors in Israel, path analysis was used to test a hypothesized model. Structural attributions for poverty contributed to attitudes towards people who live in poverty, which led to shared decision making. Also, organizational support in shared decision making, and professional moral identity, contributed to ethical behaviour which led to shared decision making. The results of this analysis revealed that shared decision making may be a scion of branched roots planted in the relationship between ethics, organizations and Stigma. © 2016 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

Research on AHP decision algorithms based on BP algorithm

NASA Astrophysics Data System (ADS)

Ma, Ning; Guan, Jianhe

2017-10-01

Decision making is the thinking activity that people choose or judge, and scientific decision-making has always been a hot issue in the field of research. Analytic Hierarchy Process (AHP) is a simple and practical multi-criteria and multi-objective decision-making method that combines quantitative and qualitative and can show and calculate the subjective judgment in digital form. In the process of decision analysis using AHP method, the rationality of the two-dimensional judgment matrix has a great influence on the decision result. However, in dealing with the real problem, the judgment matrix produced by the two-dimensional comparison is often inconsistent, that is, it does not meet the consistency requirements. BP neural network algorithm is an adaptive nonlinear dynamic system. It has powerful collective computing ability and learning ability. It can perfect the data by constantly modifying the weights and thresholds of the network to achieve the goal of minimizing the mean square error. In this paper, the BP algorithm is used to deal with the consistency of the two-dimensional judgment matrix of the AHP.

Field of Study Choice: Using Conjoint Analysis and Clustering

ERIC Educational Resources Information Center

Shtudiner, Ze'ev; Zwilling, Moti; Kantor, Jeffrey

2017-01-01

Purpose: The purpose of this paper is to measure student's preferences regarding various attributes that affect their decision process while choosing a higher education area of study. Design/ Methodology/Approach: The paper exhibits two different models which shed light on the perceived value of each examined area of study: conjoint analysis and…

A Market-oriented Approach To Maximizing Product Benefits: Cases in U.S. Forest Products Industries

Treesearch

Vijay S. Reddy; Robert J. Bush; Ronen Roudik

1996-01-01

Conjoint analysis, a decompositional customer preference modelling technique, has seen little application to forest products. However, the technique provides useful information for marketing decisions by quantifying consumer preference functions for multiattribute product alternatives. The results of a conjoint analysis include the contribution of each attribute and...

Patient‐focussed decision‐making in early‐stage prostate cancer: insights from a cognitively based decision aid

PubMed Central

Feldman‐Stewart, Deb; Brundage, Michael D; Manen, Lori Van; Svenson, Ola

2004-01-01

Abstract Purpose  To study the cognitive processes of early‐stage prostate cancer patients as they determined which treatment they preferred, using our cognitively based decision aid. Method  The aid was a one‐to‐one interview that included the structured presentation of information, listing exercises in which the patient identified attributes important to his decision, and trade‐off exercises to help him weigh and integrate those attributes together. At various points of the interview, patients identified the attributes they felt were important to their decision, rated their treatment options and completed standardized assessments relating to their decision. In addition, patients participated in a follow‐up interview at the time they made their actual treatment decision and again 3 months later. Results  Sixty of 70 (86%) of the invited patients participated in the study. Participating patients identified a median of four important attributes (range 1–10); 36 different attributes were identified at some point in the interview by the group. During the interview, 78% of patients changed which attributes they considered important, and 72% changed their treatment ratings. Stability of treatment choice after the interview and lack of regret after the decision were each positively associated with increasing differentiation between treatment options over time. Conclusions  The decision process appears to be dynamic for the patients with great variability across patients in what is important to the decision. Increasing stability of choice and lack of regret appear to be related positively to increasing difference over time in how attractive the preferred option is over its closest competitor, rather than to the size of the difference at any one point in time. PMID:15117387

TESTING MULTI-CRITERIA DECISION ANALYSIS FOR MORE TRANSPARENT RESOURCE-ALLOCATION DECISION MAKING IN COLOMBIA.

PubMed

Castro Jaramillo, Hector Eduardo; Goetghebeur, Mireille; Moreno-Mattar, Ornella

2016-01-01

In 2012, Colombia experienced an important institutional transformation after the establishment of the Health Technology Assessment Institute (IETS), the disbandment of the Regulatory Commission for Health and the reassignment of reimbursement decision-making powers to the Ministry of Health and Social Protection (MoHSP). These dynamic changes provided the opportunity to test Multi-Criteria Decision Analysis (MCDA) for systematic and more transparent resource-allocation decision-making. During 2012 and 2013, the MCDA framework Evidence and Value: Impact on Decision Making (EVIDEM) was tested in Colombia. This consisted of a preparatory stage in which the investigators conducted literature searches and produced HTA reports for four interventions of interest, followed by a panel session with decision makers. This method was contrasted with a current approach used in Colombia for updating the publicly financed benefits package (POS), where narrative health technology assessment (HTA) reports are presented alongside comprehensive budget impact analyses (BIAs). Disease severity, size of population, and efficacy ranked at the top among fifteen preselected relevant criteria. MCDA estimates of technologies of interest ranged between 71 to 90 percent of maximum value. The ranking of technologies was sensitive to the methods used. Participants considered that a two-step approach including an MCDA template, complemented by a detailed BIA would be the best approach to assist decision-making in this context. Participants agreed that systematic priority setting should take place in Colombia. This work may serve as the basis to the MoHSP on its interest of setting up a systematic and more transparent process for resource-allocation decision-making.

An environmental decision framework applied to marine engine control technologies.

PubMed

Corbett, James J; Chapman, David

2006-06-01

This paper develops a decision framework for considering emission control technologies on marine engines, informed by standard decision theory, with an open structure that may be adapted by operators with specific vessel and technology attributes different from those provided here. Attributes relate objectives important to choosing control technologies with specific alternatives that may meet several of the objectives differently. The transparent framework enables multiple stakeholders to understand how different subjective judgments and varying attribute properties may result in different technology choices. Standard scoring techniques ensure that attributes are not biased by subjective scoring and that weights are the primary quantitative input where subjective preferences are exercised. An expected value decision structure is adopted that considers probabilities (likelihood) that a given alternative can meet its claims; alternative decision criteria are discussed. Capital and annual costs are combined using a net present value approach. An iterative approach is advocated that allows for screening and disqualifying alternatives that do not meet minimum conditions for acceptance, such as engine warranty or U.S. Coast Guard requirements. This decision framework assists vessel operators in considering explicitly important attributes and in representing choices clearly to other stakeholders concerned about reducing air pollution from vessels. This general decision structure may also be applied similarly to other environmental controls in marine applications.

Integrated Risk-Informed Decision-Making for an ALMR PRISM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muhlheim, Michael David; Belles, Randy; Denning, Richard S.

Decision-making is the process of identifying decision alternatives, assessing those alternatives based on predefined metrics, selecting an alternative (i.e., making a decision), and then implementing that alternative. The generation of decisions requires a structured, coherent process, or a decision-making process. The overall objective for this work is that the generalized framework is adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace ormore » supplement human decision makers with reconfigurable decision-making modules that can perform a given set of tasks rationally, consistently, and reliably. Risk-informed decision-making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The probabilistic portion of the decision-making engine of the supervisory control system is based on the control actions associated with an ALMR PRISM. Newly incorporated into the probabilistic models are the prognostic/diagnostic models developed by Pacific Northwest National Laboratory. These allow decisions to incorporate the health of components into the decision–making process. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic portion of the decision-making engine uses thermal-hydraulic modeling and components for an advanced liquid-metal reactor Power Reactor Inherently Safe Module. The deterministic multi-attribute decision-making framework uses various sensor data (e.g., reactor outlet temperature, steam generator drum level) and calculates its position within the challenge state, its trajectory, and its margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. The metrics that are evaluated are based on reactor trip set points. The integration of the deterministic calculations using multi-physics analyses and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermalhydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies, and developing a user interface to mimic display panels at a modern nuclear power plant.« less

Meta-modelling, visualization and emulation of multi-dimensional data for virtual production intelligence

NASA Astrophysics Data System (ADS)

Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik

2017-07-01

Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.

EXPERIMENTING WITH MULTI-ATTRIBUTE UTILITY SURVEY METHODS IN A MULTI-DIMENSIONAL VALUATION PROBLEM. (R824699)

EPA Science Inventory

Abstract

The use of willingness-to-pay (WTP) survey techniques based on multi-attribute utility (MAU) approaches has been recommended by some authors as a way to deal simultaneously with two difficulties that increasingly plague environmental valuation. The first of th...

The effect of subjective awareness measures on performance in artificial grammar learning task.

PubMed

Ivanchei, Ivan I; Moroshkina, Nadezhda V

2018-01-01

Systematic research into implicit learning requires well-developed awareness-measurement techniques. Recently, trial-by-trial measures have been widely used. However, they can increase complexity of a study because they are an additional experimental variable. We tested the effects of these measures on performance in artificial grammar learning study. Four groups of participants were assigned to different awareness measures conditions: confidence ratings, post-decision wagering, decision strategy attribution or none. Decision-strategy-attribution participants demonstrated better grammar learning and longer response times compared to controls. They also exhibited a conservative bias. Grammaticality by itself was a stronger predictor of strings endorsement in decision-strategy-attribution group compared to other groups. Confidence ratings and post-decision wagering only affected the response times. These results were supported by an additional experiment that used a balanced chunk strength design. We conclude that a decision-strategy-attribution procedure may force participants to adopt an analytical decision-making strategy and rely mostly on conscious knowledge of artificial grammar. Copyright © 2017 Elsevier Inc. All rights reserved.

Clarifying values: an updated review

PubMed Central

2013-01-01

Background Consensus guidelines have recommended that decision aids include a process for helping patients clarify their values. We sought to examine the theoretical and empirical evidence related to the use of values clarification methods in patient decision aids. Methods Building on the International Patient Decision Aid Standards (IPDAS) Collaboration’s 2005 review of values clarification methods in decision aids, we convened a multi-disciplinary expert group to examine key definitions, decision-making process theories, and empirical evidence about the effects of values clarification methods in decision aids. To summarize the current state of theory and evidence about the role of values clarification methods in decision aids, we undertook a process of evidence review and summary. Results Values clarification methods (VCMs) are best defined as methods to help patients think about the desirability of options or attributes of options within a specific decision context, in order to identify which option he/she prefers. Several decision making process theories were identified that can inform the design of values clarification methods, but no single “best” practice for how such methods should be constructed was determined. Our evidence review found that existing VCMs were used for a variety of different decisions, rarely referenced underlying theory for their design, but generally were well described in regard to their development process. Listing the pros and cons of a decision was the most common method used. The 13 trials that compared decision support with or without VCMs reached mixed results: some found that VCMs improved some decision-making processes, while others found no effect. Conclusions Values clarification methods may improve decision-making processes and potentially more distal outcomes. However, the small number of evaluations of VCMs and, where evaluations exist, the heterogeneity in outcome measures makes it difficult to determine their overall effectiveness or the specific characteristics that increase effectiveness. PMID:24625261

Identifying Important Attributes for Prognostic Prediction in Traumatic Brain Injury Patients. A Hybrid Method of Decision Tree and Neural Network.

PubMed

Pourahmad, Saeedeh; Hafizi-Rastani, Iman; Khalili, Hosseinali; Paydar, Shahram

2016-10-17

Generally, traumatic brain injury (TBI) patients do not have a stable condition, particularly after the first week of TBI. Hence, indicating the attributes in prognosis through a prediction model is of utmost importance since it helps caregivers with treatment-decision options, or prepares the relatives for the most-likely outcome. This study attempted to determine and order the attributes in prognostic prediction in TBI patients, based on early clinical findings. A hybrid method was employed, which combines a decision tree (DT) and an artificial neural network (ANN) in order to improve the modeling process. The DT approach was applied as the initial analysis of the network architecture to increase accuracy in prediction. Afterwards, the ANN structure was mapped from the initial DT based on a part of the data. Subsequently, the designed network was trained and validated by the remaining data. 5-fold cross-validation method was applied to train the network. The area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, and accuracy rate were utilized as performance measures. The important attributes were then determined from the trained network using two methods: change of mean squared error (MSE), and sensitivity analysis (SA). The hybrid method offered better results compared to the DT method. The accuracy rate of 86.3 % vs. 82.2 %, sensitivity value of 55.1 % vs. 47.6 %, specificity value of 93.6 % vs. 91.1 %, and the area under the ROC curve of 0.705 vs. 0.695 were achieved for the hybrid method and DT, respectively. However, the attributes' order by DT method was more consistent with the clinical literature. The combination of different modeling methods can enhance their performance. However, it may create some complexities in computations and interpretations. The outcome of the present study could deliver some useful hints in prognostic prediction on the basis of early clinical findings for TBI patients.

Multisensor satellite data for water quality analysis and water pollution risk assessment: decision making under deep uncertainty with fuzzy algorithm in framework of multimodel approach

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim

2017-10-01

Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.

Minimization of the Number of Edges in an EVMDD by Variable Grouping for Fast Analysis of Multi-State Systems

DTIC Science & Technology

2013-05-01

Nov. 1991. [8] T. Kam, T. Villa, R. K. Brayton , and A. L. Sangiovanni- Vincentelli, “Multi-valued decision diagrams: Theory and ap- plications...Micro- and Nanoelectronic Design, CRC Press, Taylor & Francis Group, 2006. [22] X. Zang, D. Wang, H. Sun, and K. S. Trivedi, “A BDD-based algorithm

Gender and food, a study of attitudes in the USA towards organic, local, U.S. grown, and GM-free foods.

PubMed

Bellows, Anne C; Alcaraz V, Gabriela; Hallman, William K

2010-12-01

Food choice is influenced by consumer attitudes towards food attributes. This U.S.-based study (n = 601) simultaneously compares attitudes towards selected food attributes of organic, locally grown, U.S. grown, and GM-free food in relation to other food attributes. Exploratory factor analysis identifies underlying constructs that determine, together and separately, female and male food choice decisions. Gendered analysis of the value of food in life and food behaviours (cooking and shopping) support the investigation of the highlighted food attributes. Respondents generally assigned greater importance to the U.S. grown, followed by GM-free, locally grown, and organically produced food attributes in deciding what to eat. Analysis of the female and male subsamples yielded similar factor results. All four main attributes were captured in a single factor, associated with respondents in both the female and male subsamples who are older, have lower incomes, and who are religiously observant. Additionally, among females, this factor was associated with higher education; and among males, living in households with children and/or with partners. Additional studies should further explore the interaction of food attributes now becoming increasingly important and prevalent in current food products. Copyright © 2010 Elsevier Ltd. All rights reserved.

Assessing the value of healthcare interventions using multi-criteria decision analysis: a review of the literature.

PubMed

Marsh, Kevin; Lanitis, Tereza; Neasham, David; Orfanos, Panagiotis; Caro, Jaime

2014-04-01

The objective of this study is to support those undertaking a multi-criteria decision analysis (MCDA) by reviewing the approaches adopted in healthcare MCDAs to date, how these varied with the objective of the study, and the lessons learned from this experience. Searches of EMBASE and MEDLINE identified 40 studies that provided 41 examples of MCDA in healthcare. Data were extracted on the objective of the study, methods employed, and decision makers' and study authors' reflections on the advantages and disadvantages of the methods. The recent interest in MCDA in healthcare is mirrored in an increase in the application of MCDA to evaluate healthcare interventions. Of the studies identified, the first was published in 1990, but more than half were published since 2011. They were undertaken in 18 different countries, and were designed to support investment (coverage and reimbursement), authorization, prescription, and research funding allocation decisions. Many intervention types were assessed: pharmaceuticals, public health interventions, screening, surgical interventions, and devices. Most used the value measurement approach and scored performance using predefined scales. Beyond these similarities, a diversity of different approaches were adopted, with only limited correspondence between the approach and the type of decision or product. Decision makers consulted as part of these studies, as well as the authors of the studies are positive about the potential of MCDA to improve decision making. Further work is required, however, to develop guidance for those undertaking MCDA.

Combining multi-criteria decision analysis and mini-health technology assessment: A funding decision-support tool for medical devices in a university hospital setting.

PubMed

Martelli, Nicolas; Hansen, Paul; van den Brink, Hélène; Boudard, Aurélie; Cordonnier, Anne-Laure; Devaux, Capucine; Pineau, Judith; Prognon, Patrice; Borget, Isabelle

2016-02-01

At the hospital level, decisions about purchasing new and oftentimes expensive medical devices must take into account multiple criteria simultaneously. Multi-criteria decision analysis (MCDA) is increasingly used for health technology assessment (HTA). One of the most successful hospital-based HTA approaches is mini-HTA, of which a notable example is the Matrix4value model. To develop a funding decision-support tool combining MCDA and mini-HTA, based on Matrix4value, suitable for medical devices for individual patient use in French university hospitals - known as the IDA tool, short for 'innovative device assessment'. Criteria for assessing medical devices were identified from a literature review and a survey of 18 French university hospitals. Weights for the criteria, representing their relative importance, were derived from a survey of 25 members of a medical devices committee using an elicitation technique involving pairwise comparisons. As a test of its usefulness, the IDA tool was applied to two new drug-eluting beads (DEBs) for transcatheter arterial chemoembolization. The IDA tool comprises five criteria and weights for each of two over-arching categories: risk and value. The tool revealed that the two new DEBs conferred no additional value relative to DEBs currently available. Feedback from participating decision-makers about the IDA tool was very positive. The tool could help to promote a more structured and transparent approach to HTA decision-making in French university hospitals. Copyright © 2015 Elsevier Inc. All rights reserved.

Construction of social value or utility-based health indices: the usefulness of factorial experimental design plans.

PubMed

Cadman, D; Goldsmith, C

1986-01-01

Global indices, which aggregate multiple health or function attributes into a single summary indicator, are useful measures in health research. Two key issues must be addressed in the initial stages of index construction from the universe of possible health and function attributes, which ones should be included in a new index? and how simple can the statistical model be to combine attributes into a single numeric index value? Factorial experimental designs were used in the initial stages of developing a function index for evaluating a program for the care of young handicapped children. Beginning with eight attributes judged important to the goals of the program by clinicians, social preference values for different function states were obtained from 32 parents of handicapped children and 32 members of the community. Using category rating methods each rater scored 16 written multi-attribute case descriptions which contained information about a child's status for all eight attributes. Either a good or poor level of each function attribute and age 3 or 5 years were described in each case. Thus, 2(8) = 256 different cases were rated. Two factorial design plans were selected and used to allocate case descriptions to raters. Analysis of variance determined that seven of the eight clinician selected attributes were required in a social value based index for handicapped children. Most importantly, the subsequent steps of index construction could be greatly simplified by the finding that a simple additive statistical model without complex attribute interaction terms was adequate for the index. We conclude that factorial experimental designs are an efficient, feasible and powerful tool for the initial stages of constructing a multi-attribute health index.

ELICIT: An alternative imprecise weight elicitation technique for use in multi-criteria decision analysis for healthcare.

PubMed

Diaby, Vakaramoko; Sanogo, Vassiki; Moussa, Kouame Richard

2016-01-01

In this paper, the readers are introduced to ELICIT, an imprecise weight elicitation technique for multicriteria decision analysis for healthcare. The application of ELICIT consists of two steps: the rank ordering of evaluation criteria based on decision-makers' (DMs) preferences using the principal component analysis; and the estimation of criteria weights and their descriptive statistics using the variable interdependent analysis and the Monte Carlo method. The application of ELICIT is illustrated with a hypothetical case study involving the elicitation of weights for five criteria used to select the best device for eye surgery. The criteria were ranked from 1-5, based on a strict preference relationship established by the DMs. For each criterion, the deterministic weight was estimated as well as the standard deviation and 95% credibility interval. ELICIT is appropriate in situations where only ordinal DMs' preferences are available to elicit decision criteria weights.

The Influence of Organizational Image on College Selection: What Students Seek in Institutions of Higher Education

ERIC Educational Resources Information Center

Pampaloni, Andrea M.

2010-01-01

Colleges and universities rely on their image to attract new members. This study focuses on the decision-making process of students preparing to apply to college. High school students were surveyed at college open houses to identify the factors most influential to their college application decision-making. A multi-methods analysis found that…

The analysis of the pilot's cognitive and decision processes

NASA Technical Reports Server (NTRS)

Curry, R. E.

1975-01-01

Articles are presented on pilot performance in zero-visibility precision approach, failure detection by pilots during automatic landing, experiments in pilot decision-making during simulated low visibility approaches, a multinomial maximum likelihood program, and a random search algorithm for laboratory computers. Other topics discussed include detection of system failures in multi-axis tasks and changes in pilot workload during an instrument landing.

Enablement in health care context: a concept analysis.

PubMed

Hudon, Catherine; St-Cyr Tribble, Denise; Bravo, Gina; Poitras, Marie-Eve

2011-02-01

The enablement process is defined as a professional intervention aiming to recognize, support and emphasize the patient's capacity to have control over her or his health and life. The purpose of this article was to study the enablement concept through a concept analysis in the health care context to identify: (1) its attributes and (2) its antecedents and consequents. A concept analysis was performed according to the method of Rodgers. The literature was reviewed from 1980 to June 2008, using search strategies adapted to the databases Cinahl, Medline, Embase, PsycInfo and Social Works Abstract, and hand searching. All articles contributing to a deeper understanding of the concept were included. The analysis was carried out according to a thematic analysis procedure, as described by Miles & Huberman. The search identified 1305 citations. After in-depth assessment of 148 potentially eligible citations, 61 articles were included in the review. Five articles were added with hand searching. Sixty-seven per cent of these articles were related to nursing. The attributes of the enablement concept included: contribution to the therapeutic relationship; consideration of the person as a whole; facilitation of learning; valorization of the person's strengths; implication and support to decision making; and broadening of the possibilities. These attributes could be used as a basis for other studies on enablement. Conceptual and empirical work is still needed to better position this concept among others such as patient-centred care, shared decision making and patient's participation. © 2010 Blackwell Publishing Ltd.

Utilization of a Multi-Disciplinary Approach to Building Effective Command Centers: Process and Products

DTIC Science & Technology

2005-06-01

cognitive task analysis , organizational information dissemination and interaction, systems engineering, collaboration and communications processes, decision-making processes, and data collection and organization. By blending these diverse disciplines command centers can be designed to support decision-making, cognitive analysis, information technology, and the human factors engineering aspects of Command and Control (C2). This model can then be used as a baseline when dealing with work in areas of business processes, workflow engineering, information management,

Application of Visual Attention in Seismic Attribute Analysis

NASA Astrophysics Data System (ADS)

He, M.; Gu, H.; Wang, F.

2016-12-01

It has been proved that seismic attributes can be used to predict reservoir. The joint of multi-attribute and geological statistics, data mining, artificial intelligence, further promote the development of the seismic attribute analysis. However, the existing methods tend to have multiple solutions and insufficient generalization ability, which is mainly due to the complex relationship between seismic data and geological information, and undoubtedly own partly to the methods applied. Visual attention is a mechanism model of the human visual system which can concentrate on a few significant visual objects rapidly, even in a mixed scene. Actually, the model qualify good ability of target detection and recognition. In our study, the targets to be predicted are treated as visual objects, and an object representation based on well data is made in the attribute dimensions. Then in the same attribute space, the representation is served as a criterion to search the potential targets outside the wells. This method need not predict properties by building up a complicated relation between attributes and reservoir properties, but with reference to the standard determined before. So it has pretty good generalization ability, and the problem of multiple solutions can be weakened by defining the threshold of similarity.

Family involvement in medical decision-making: Perceptions of nursing and psychology students.

PubMed

Itzhaki, Michal; Hildesheimer, Galya; Barnoy, Sivia; Katz, Michael

2016-05-01

Family members often rely on health care professionals to guide and support them through the decision-making process. Although family involvement in medical decisions should be included in the preservice curriculum for the health care professions, perceptions of students in caring professions on family involvement in medical decision-making have not yet been examined. To examine the perceptions of nursing and psychology students on family involvement in medical decision-making for seriously ill patients. A descriptive cross-sectional design was used. First year undergraduate nursing and psychology students studying for their Bachelor of Arts degree were recruited. Perceptions were assessed with a questionnaire constructed based on the Multi-Attribute Utility Theory (MAUT), which examines decision-maker preferences. The questionnaire consisted of two parts referring to the respondent once as the patient and then as the family caregiver. Questionnaires were completed by 116 nursing students and 156 psychology students. Most were of the opinion that family involvement in decision-making is appropriate, especially when the patient is incapable of making decisions. Nursing students were more inclined than psychology students to think that financial, emotional, and value-based considerations should be part of the family's involvement in decision-making. Both groups of students perceived the emotional consideration as most acceptable, whereas the financial consideration was considered the least acceptable. Nursing and psychology students perceive family involvement in medical decision-making as appropriate. In order to train students to support families in the process of decision-making, further research should examine Shared Decision-Making (SDM) programs, which involve patient and clinician collaboration in health care decisions. Copyright © 2016 Elsevier Ltd. All rights reserved.

DLA Systems Modernization Methodology: Logical Analysis and Design Procedures

DTIC Science & Technology

1990-07-01

Information Requirement would have little meaning and thus would lose its value . 3 I3 I 1.1.3 INPUT PRODUCTS 3 1.1.3.1 Enterprise Model Objective List 1.1.3.2...at the same time, the attribute is said to be multi- valued . i For example, an E-R model may contain information on the languages an employee speaks...Relationship model is examined in detail to ensure that each data group contains attributes whose values are absolutely determined by their respective

Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model.

PubMed

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals.

Coupling Meteorology, Metal Concentrations, and Pb Isotopes for Source Attribution in Archived Precipitation Samples

EPA Science Inventory

A technique that couples lead (Pb) isotopes and multi-element concentrations with meteorological analysis was used to assess source contributions to precipitation samples at the Bondville, Illinois USA National Trends Network (NTN) site. Precipitation samples collected over a 16 ...

Inhalation Exposure and Lung Dose Analysis of Multi-mode Complex Ambient Aerosols

EPA Science Inventory

Rationale: Ambient aerosols are complex mixture of particles with different size, shape and chemical composition. Although they are known to cause health hazard, it is not fully understood about causal mechanisms and specific attributes of particles causing the effects. Internal ...

Post-Marketing Regulation of Medicines Withdrawn from the Market Because of Drug-Attributed Deaths: An Analysis of Justification.

PubMed

Onakpoya, Igho J; Heneghan, Carl J; Aronson, Jeffrey K

2017-05-01

Several medicinal products have been withdrawn from the market because of drug-attributed deaths. However, there has been no investigation of whether such withdrawals were justified, and the extent to which confirmatory studies are used to investigate drug-adverse event relationships when deaths are reported is uncertain. We documented medicinal products withdrawn from the market because of drug-attributed deaths, identified confirmatory studies investigating the drug-adverse event relationships, examined whether withdrawals of medicinal products because of drug-attributed deaths after marketing were justified based on a mechanistic analysis, and examined the trends over time. We searched electronic and non-electronic sources to identify medicinal products that were withdrawn because of drug-attributed deaths. We used a previously published algorithm to examine whether the withdrawals of products were justified. We then searched PubMed and Google Scholar to identify studies investigating the drug-adverse event relationships, used the Oxford Centre for Evidence-Based Medicine criteria to document the levels of evidence, and assessed whether the evidence of an association was confirmed. We included 83 medicinal products. The reasons for withdrawal appeared to have been justified in 80 cases (96%). The median interval between the first reported adverse reaction that was related to the cause of death and the first reported death was 1 year (interquartile range = 1-3); products were withdrawn sooner when the interval between the first reported relevant adverse reaction and the first death was shorter. Confirmatory studies were conducted in 57 instances (69%), and there was evidence of an association in 52 cases (63%). Four products (5%) were re-introduced after initial withdrawal. Regulatory authorities have been justified in making withdrawal decisions when deaths have been attributed to medicinal products, using the precautionary principle when alternative decisions could have been made. Medicinal products are likely to be quickly withdrawn from the market when there is a short interval to the first reported deaths. The use of an algorithm such as we have used in this study could help to expedite the process of decision making.

Secure Data Access Control for Fog Computing Based on Multi-Authority Attribute-Based Signcryption with Computation Outsourcing and Attribute Revocation.

PubMed

Xu, Qian; Tan, Chengxiang; Fan, Zhijie; Zhu, Wenye; Xiao, Ya; Cheng, Fujia

2018-05-17

Nowadays, fog computing provides computation, storage, and application services to end users in the Internet of Things. One of the major concerns in fog computing systems is how fine-grained access control can be imposed. As a logical combination of attribute-based encryption and attribute-based signature, Attribute-based Signcryption (ABSC) can provide confidentiality and anonymous authentication for sensitive data and is more efficient than traditional "encrypt-then-sign" or "sign-then-encrypt" strategy. Thus, ABSC is suitable for fine-grained access control in a semi-trusted cloud environment and is gaining more and more attention recently. However, in many existing ABSC systems, the computation cost required for the end users in signcryption and designcryption is linear with the complexity of signing and encryption access policy. Moreover, only a single authority that is responsible for attribute management and key generation exists in the previous proposed ABSC schemes, whereas in reality, mostly, different authorities monitor different attributes of the user. In this paper, we propose OMDAC-ABSC, a novel data access control scheme based on Ciphertext-Policy ABSC, to provide data confidentiality, fine-grained control, and anonymous authentication in a multi-authority fog computing system. The signcryption and designcryption overhead for the user is significantly reduced by outsourcing the undesirable computation operations to fog nodes. The proposed scheme is proven to be secure in the standard model and can provide attribute revocation and public verifiability. The security analysis, asymptotic complexity comparison, and implementation results indicate that our construction can balance the security goals with practical efficiency in computation.

Cost-Effectiveness and Cost-Benefit Analysis: Confronting the Problem of Choice.

ERIC Educational Resources Information Center

Clardy, Alan

Cost-effectiveness analysis and cost-benefit analysis are two related yet distinct methods to help decision makers choose the best course of action from among competing alternatives. For both types of analysis, costs are computed similarly. Costs may be reduced to present value amounts for multi-year programs, and parameters may be altered to show…

Modeling organizational justice improvements in a pediatric health service : a discrete-choice conjoint experiment.

PubMed

Cunningham, Charles E; Kostrzewa, Linda; Rimas, Heather; Chen, Yvonne; Deal, Ken; Blatz, Susan; Bowman, Alida; Buchanan, Don H; Calvert, Randy; Jennings, Barbara

2013-01-01

Patients value health service teams that function effectively. Organizational justice is linked to the performance, health, and emotional adjustment of the members of these teams. We used a discrete-choice conjoint experiment to study the organizational justice improvement preferences of pediatric health service providers. Using themes from a focus group with 22 staff, we composed 14 four-level organizational justice improvement attributes. A sample of 652 staff (76 % return) completed 30 choice tasks, each presenting three hospitals defined by experimentally varying the attribute levels. Latent class analysis yielded three segments. Procedural justice attributes were more important to the Decision Sensitive segment, 50.6 % of the sample. They preferred to contribute to and understand how all decisions were made and expected management to act promptly on more staff suggestions. Interactional justice attributes were more important to the Conduct Sensitive segment (38.5 %). A universal code of respectful conduct, consequences encouraging respectful interaction, and management's response when staff disagreed with them were more important to this segment. Distributive justice attributes were more important to the Benefit Sensitive segment, 10.9 % of the sample. Simulations predicted that, while Decision Sensitive (74.9 %) participants preferred procedural justice improvements, Conduct (74.6 %) and Benefit Sensitive (50.3 %) participants preferred interactional justice improvements. Overall, 97.4 % of participants would prefer an approach combining procedural and interactional justice improvements. Efforts to create the health service environments that patients value need to be comprehensive enough to address the preferences of segments of staff who are sensitive to different dimensions of organizational justice.

Optimized production planning model for a multi-plant cultivation system under uncertainty

NASA Astrophysics Data System (ADS)

Ke, Shunkui; Guo, Doudou; Niu, Qingliang; Huang, Danfeng

2015-02-01

An inexact multi-constraint programming model under uncertainty was developed by incorporating a production plan algorithm into the crop production optimization framework under the multi-plant collaborative cultivation system. In the production plan, orders from the customers are assigned to a suitable plant under the constraints of plant capabilities and uncertainty parameters to maximize profit and achieve customer satisfaction. The developed model and solution method were applied to a case study of a multi-plant collaborative cultivation system to verify its applicability. As determined in the case analysis involving different orders from customers, the period of plant production planning and the interval between orders can significantly affect system benefits. Through the analysis of uncertain parameters, reliable and practical decisions can be generated using the suggested model of a multi-plant collaborative cultivation system.

A decision support model for improving a multi-family housing complex based on CO2 emission from electricity consumption.

PubMed

Hong, Taehoon; Koo, Choongwan; Kim, Hyunjoong

2012-12-15

The number of deteriorated multi-family housing complexes in South Korea continues to rise, and consequently their electricity consumption is also increasing. This needs to be addressed as part of the nation's efforts to reduce energy consumption. The objective of this research was to develop a decision support model for determining the need to improve multi-family housing complexes. In this research, 1664 cases located in Seoul were selected for model development. The research team collected the characteristics and electricity energy consumption data of these projects in 2009-2010. The following were carried out in this research: (i) using the Decision Tree, multi-family housing complexes were clustered based on their electricity energy consumption; (ii) using Case-Based Reasoning, similar cases were retrieved from the same cluster; and (iii) using a combination of Multiple Regression Analysis, Artificial Neural Network, and Genetic Algorithm, the prediction performance of the developed model was improved. The results of this research can be used as follows: (i) as basic research data for continuously managing several energy consumption data of multi-family housing complexes; (ii) as advanced research data for predicting energy consumption based on the project characteristics; (iii) as practical research data for selecting the most optimal multi-family housing complex with the most potential in terms of energy savings; and (iv) as consistent and objective criteria for incentives and penalties. Copyright © 2012 Elsevier Ltd. All rights reserved.

Architecture Design of Healthcare Software-as-a-Service Platform for Cloud-Based Clinical Decision Support Service.

PubMed

Oh, Sungyoung; Cha, Jieun; Ji, Myungkyu; Kang, Hyekyung; Kim, Seok; Heo, Eunyoung; Han, Jong Soo; Kang, Hyunggoo; Chae, Hoseok; Hwang, Hee; Yoo, Sooyoung

2015-04-01

To design a cloud computing-based Healthcare Software-as-a-Service (SaaS) Platform (HSP) for delivering healthcare information services with low cost, high clinical value, and high usability. We analyzed the architecture requirements of an HSP, including the interface, business services, cloud SaaS, quality attributes, privacy and security, and multi-lingual capacity. For cloud-based SaaS services, we focused on Clinical Decision Service (CDS) content services, basic functional services, and mobile services. Microsoft's Azure cloud computing for Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) was used. The functional and software views of an HSP were designed in a layered architecture. External systems can be interfaced with the HSP using SOAP and REST/JSON. The multi-tenancy model of the HSP was designed as a shared database, with a separate schema for each tenant through a single application, although healthcare data can be physically located on a cloud or in a hospital, depending on regulations. The CDS services were categorized into rule-based services for medications, alert registration services, and knowledge services. We expect that cloud-based HSPs will allow small and mid-sized hospitals, in addition to large-sized hospitals, to adopt information infrastructures and health information technology with low system operation and maintenance costs.

Decision Making in Nursing Practice: A Concept Analysis.

PubMed

Johansen, Mary L; O'Brien, Janice L

2016-01-01

The study aims to gain an understanding of the concept of decision making as it relates to the nurse practice environment. Rodgers' evolutionary method on concept analysis was used as a framework for the study of the concept. Articles from 1952 to 2014 were reviewed from PsycINFO, Medline, Cumulative Index to Nursing and Allied Health Literature (CINAHL), JSTOR, PubMed, and Science Direct. Findings suggest that decision making in the nurse practice environment is a complex process, integral to the nursing profession. The definition of decision making, and the attributes, antecedents, and consequences, are discussed. Contextual factors that influence the process are also discussed. An exemplar is presented to illustrate the concept. Decision making in the nurse practice environment is a dynamic conceptual process that may affect patient outcomes. Nurses need to call upon ways of knowing to make sound decisions and should be self-reflective in order to develop the process further in the professional arena. The need for further research is discussed. © 2015 Wiley Periodicals, Inc.

Selecting sustainable alternatives for cruise ships in Venice using multi-criteria decision analysis.

PubMed

Pesce, Marco; Terzi, Stefano; Al-Jawasreh, Raid Issa Mahmoud; Bommarito, Claudia; Calgaro, Loris; Fogarin, Stefano; Russo, Elisabetta; Marcomini, Antonio; Linkov, Igor

2018-06-14

The rapid growth of cruise ship tourism increases the use of historic port cities as strategic hubs for cruise ship operators. Benefits derived from increased tourism for the municipality and cruise ships are often at odds with the environmental and social impacts associated with continued historical port use. This study illustrates the use of Multi-Criteria Decision Analysis (MCDA) for weighing of various criteria and metrics related to the environment, economy, and social sustainability for the selection of a sustainable cruise line route. Specifically, MCDA methodology was employed in Venice, Italy to illustrate its application. First, the four most representative navigational route projects among those presented to local authorities were assessed based on social, economic, and environmental considerations. Second, a pool of experts representing the local authority, private port businesses, and cruise line industry were consulted to evaluate the validity and weight assignments for the selected criteria. Finally, a sensitivity analysis was employed to assess the robustness of the recommendations using an evaluation of weight changes and their effects on the ranking of alternative navigational routes. The results were presented and discussed in a multi-stakeholder meeting to further the route selection process. Published by Elsevier B.V.

Time Sharing Between Robotics and Process Control: Validating a Model of Attention Switching.

PubMed

Wickens, Christopher Dow; Gutzwiller, Robert S; Vieane, Alex; Clegg, Benjamin A; Sebok, Angelia; Janes, Jess

2016-03-01

The aim of this study was to validate the strategic task overload management (STOM) model that predicts task switching when concurrence is impossible. The STOM model predicts that in overload, tasks will be switched to, to the extent that they are attractive on task attributes of high priority, interest, and salience and low difficulty. But more-difficult tasks are less likely to be switched away from once they are being performed. In Experiment 1, participants performed four tasks of the Multi-Attribute Task Battery and provided task-switching data to inform the role of difficulty and priority. In Experiment 2, participants concurrently performed an environmental control task and a robotic arm simulation. Workload was varied by automation of arm movement and both the phases of environmental control and existence of decision support for fault management. Attention to the two tasks was measured using a head tracker. Experiment 1 revealed the lack of influence of task priority and confirmed the differing roles of task difficulty. In Experiment 2, the percentage attention allocation across the eight conditions was predicted by the STOM model when participants rated the four attributes. Model predictions were compared against empirical data and accounted for over 95% of variance in task allocation. More-difficult tasks were performed longer than easier tasks. Task priority does not influence allocation. The multiattribute decision model provided a good fit to the data. The STOM model is useful for predicting cognitive tunneling given that human-in-the-loop simulation is time-consuming and expensive. © 2016, Human Factors and Ergonomics Society.

Neural Signatures of Controlled and Automatic Retrieval Processes in Memory-based Decision-making.

PubMed

Khader, Patrick H; Pachur, Thorsten; Weber, Lilian A E; Jost, Kerstin

2016-01-01

Decision-making often requires retrieval from memory. Drawing on the neural ACT-R theory [Anderson, J. R., Fincham, J. M., Qin, Y., & Stocco, A. A central circuit of the mind. Trends in Cognitive Sciences, 12, 136-143, 2008] and other neural models of memory, we delineated the neural signatures of two fundamental retrieval aspects during decision-making: automatic and controlled activation of memory representations. To disentangle these processes, we combined a paradigm developed to examine neural correlates of selective and sequential memory retrieval in decision-making with a manipulation of associative fan (i.e., the decision options were associated with one, two, or three attributes). The results show that both the automatic activation of all attributes associated with a decision option and the controlled sequential retrieval of specific attributes can be traced in material-specific brain areas. Moreover, the two facets of memory retrieval were associated with distinct activation patterns within the frontoparietal network: The dorsolateral prefrontal cortex was found to reflect increasing retrieval effort during both automatic and controlled activation of attributes. In contrast, the superior parietal cortex only responded to controlled retrieval, arguably reflecting the sequential updating of attribute information in working memory. This dissociation in activation pattern is consistent with ACT-R and constitutes an important step toward a neural model of the retrieval dynamics involved in memory-based decision-making.

Large-scale optimization-based classification models in medicine and biology.

PubMed

Lee, Eva K

2007-06-01

We present novel optimization-based classification models that are general purpose and suitable for developing predictive rules for large heterogeneous biological and medical data sets. Our predictive model simultaneously incorporates (1) the ability to classify any number of distinct groups; (2) the ability to incorporate heterogeneous types of attributes as input; (3) a high-dimensional data transformation that eliminates noise and errors in biological data; (4) the ability to incorporate constraints to limit the rate of misclassification, and a reserved-judgment region that provides a safeguard against over-training (which tends to lead to high misclassification rates from the resulting predictive rule); and (5) successive multi-stage classification capability to handle data points placed in the reserved-judgment region. To illustrate the power and flexibility of the classification model and solution engine, and its multi-group prediction capability, application of the predictive model to a broad class of biological and medical problems is described. Applications include: the differential diagnosis of the type of erythemato-squamous diseases; predicting presence/absence of heart disease; genomic analysis and prediction of aberrant CpG island meythlation in human cancer; discriminant analysis of motility and morphology data in human lung carcinoma; prediction of ultrasonic cell disruption for drug delivery; identification of tumor shape and volume in treatment of sarcoma; discriminant analysis of biomarkers for prediction of early atherosclerois; fingerprinting of native and angiogenic microvascular networks for early diagnosis of diabetes, aging, macular degeneracy and tumor metastasis; prediction of protein localization sites; and pattern recognition of satellite images in classification of soil types. In all these applications, the predictive model yields correct classification rates ranging from 80 to 100%. This provides motivation for pursuing its use as a medical diagnostic, monitoring and decision-making tool.

New integrated and multiscale decision-aiding framework in a context of imperfect information: application to the assessment of torrent checkdams' effectiveness.

NASA Astrophysics Data System (ADS)

Tacnet, Jean-Marc; Carladous, Simon; Dezert, Jean; Batton-Hubert, Mireille

2017-04-01

Mountain natural phenomena (e.g. torrential floods) put people and buildings at risk. Civil engineering protection works such as torrent check-dams are designed to mitigate those natural risks. Protection works act on both causes and effects of phenomena to reduce consequences and therefore risks. For instance, check-dams control sediment production and liquid/solid flow of torrential floods: several series of dams are located in the headwaters of a watershed, each having specific functions. All those works are damaged by time passing and flood impacts. Effectiveness assessment is needed to define, compare or choose strategies for investment and maintenance which are essential issues in risk management process. Decision support tools are expected to analyze at different scales both their technical effectiveness (related to their structural state and functional effects on phenomena such as stopping, braking, guiding, etc.) and their economic efficiency through comparison between benefits and costs. Several methods, often based on expert knowledge, have already been developed to care about decision under risk. But uncertainty has also to be considered, since decisions are indeed often taken in a context of lack of information and knowledge on natural phenomena, heterogeneity of available information and, finally, reliability of sources. First methods derived from classical industrial contexts, such as dependability analysis, are used to formalize expert knowledge used for decision-making. After having defined the concept of effectiveness, dependability analysis are used to identify decision contexts and problems: criteria and indicators are identified in relation with structural or functional features. Then, innovative and multi-scales multi-criteria decision-making methods (MCDMs) and frameworks are proposed to help assessing protection works effectiveness. They combine classical MCDM approaches, belief function, fuzzy sets and possibility theories. Those methods allow to make decisions based on heterogeneous, imprecise and uncertain evaluation of criteria provided by more or less reliable sources in an uncertain context: COWA-ER (Cautious Ordered Weighted Averaging with Evidential Reasoning), Fuzzy-Cautious OWA or ER-MCDA (Evidential Reasoning for Multi Criteria Decision Analysis) are thus applied to several scales of torrent check-dams' effectiveness assessment. Those methods are then improved for a better knowledge representation and final decision. Enhanced methods are then associated together. Finally, individual problems and associated methods are integrated in a generic methodology to move from torrential protective single measure effectiveness assessment to complete protection systems at watershed scale.

Processing companies' preferences for attributes of beef in Switzerland.

PubMed

Boesch, Irene

2014-01-01

The aim of this work was to assess processing companies' preferences for attributes of Swiss beef. To this end, qualitative interviews were used to derive product attributes that determine the buying decision. Through an adaptive-choice based conjoint analysis survey and latent class analysis of choice data, we compute class preferences. Results show that there are two distinct classes. A smaller class emphasizes traceability back to the birth farm and low producer price, a larger class focuses on environmental effects and origin. Additionally we see that larger companies are more price-sensitive and smaller companies are more sensitive to origin of the animals. The results outlined in this paper may be used to target market segments and to derive differentiation strategies based on product characteristics. Copyright © 2013 Elsevier Ltd. All rights reserved.

Understanding Residential Location Decision in the New York Region - A Data Collection Effort

DOT National Transportation Integrated Search

2010-06-17

Literature in residential location analysis is voluminous and profound and much has been learned. We now understand that there are three main categories of factors affecting our residential location choices: housing attributes (e.g., housing size), n...

Physician as partner or salesman? Shared decision-making in real-time encounters.

PubMed

Karnieli-Miller, Orit; Eisikovits, Zvi

2009-07-01

The results of recent research have led to the increased advocacy of shared decision-making regarding medical treatment. Nonetheless, only a limited number of studies have focused on the process of decision-making in real-time encounters. The present paper aims to document and analyze this process. Specifically, we assess whether these decisions are the result of partnership or of persuasive tactics based on power and hierarchical relationships. We will describe and analyze different strategies used by pediatric gastroenterologists in breaking bad news encounters, as well as their consequences. The analysis is based on a multi-method, multi-participant phenomenological study on breaking bad news to adolescents and their families regarding a chronic illness. It included 17 units of analysis (actual encounters and 52 interviews with physicians, parents and adolescents). Data were collected from three hospitals in Northern Israel using observations and audiotapes of diagnosis disclosure encounters and audio-taped interviews with all participants. The analysis identified eight different presentation tactics used in actual encounters during which physicians made various use of language, syntax and different sources of power to persuade patients to agree with their preferred treatment choice. The tactics included various ways of presenting the illness, treatment and side effects; providing examples from other success or failure stories; sharing the decision only concerning technicalities; and using plurals and authority. The findings suggest that shared decision-making may be advocated as a philosophical tenet or a value, but it is not necessarily implemented in actual communication with patients. Rather, treatment decisions tend to be unilaterally made, and a variety of persuasive approaches are used to ensure agreement with the physician's recommendation. The discussion is focused on the complexity of sharing a decision, especially in the initial bad news encounter; and the potentially harmful implications on building a trusting relationship between the physician and the family when a decision is not shared.

Multi-attribute criteria applied to electric generation energy system analysis LDRD.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuswa, Glenn W.; Tsao, Jeffrey Yeenien; Drennen, Thomas E.

2005-10-01

This report began with a Laboratory-Directed Research and Development (LDRD) project to improve Sandia National Laboratories multidisciplinary capabilities in energy systems analysis. The aim is to understand how various electricity generating options can best serve needs in the United States. The initial product is documented in a series of white papers that span a broad range of topics, including the successes and failures of past modeling studies, sustainability, oil dependence, energy security, and nuclear power. Summaries of these projects are included here. These projects have provided a background and discussion framework for the Energy Systems Analysis LDRD team to carrymore » out an inter-comparison of many of the commonly available electric power sources in present use, comparisons of those options, and efforts needed to realize progress towards those options. A computer aid has been developed to compare various options based on cost and other attributes such as technological, social, and policy constraints. The Energy Systems Analysis team has developed a multi-criteria framework that will allow comparison of energy options with a set of metrics that can be used across all technologies. This report discusses several evaluation techniques and introduces the set of criteria developed for this LDRD.« less

Decision support framework for evaluating the operational environment of forest bioenergy production and use: Case of four European countries.

PubMed

Pezdevšek Malovrh, Špela; Kurttila, Mikko; Hujala, Teppo; Kärkkäinen, Leena; Leban, Vasja; Lindstad, Berit H; Peters, Dörte Marie; Rhodius, Regina; Solberg, Birger; Wirth, Kristina; Zadnik Stirn, Lidija; Krč, Janez

2016-09-15

Complex policy-making situations around bioenergy production and use require examination of the operational environment of the society and a participatory approach. This paper presents and demonstrates a three-phase decision-making framework for analysing the operational environment of strategies related to increased forest bioenergy targets. The framework is based on SWOT (strengths, weaknesses, opportunities and threats) analysis and the Simple Multi-Attribute Rating Technique (SMART). Stakeholders of four case countries (Finland, Germany, Norway and Slovenia) defined the factors that affect the operational environments, classified in four pre-set categories (Forest Characteristics and Management, Policy Framework, Technology and Science, and Consumers and Society). The stakeholders participated in weighting of SWOT items for two future scenarios with SMART technique. The first scenario reflected the current 2020 targets (the Business-as-Usual scenario), and the second scenario contained a further increase in the targets (the Increase scenario). This framework can be applied to various problems of environmental management and also to other fields where public decision-making is combined with stakeholders' engagement. The case results show that the greatest differences between the scenarios appear in Germany, indicating a notably negative outlook for the Increase scenario, while the smallest differences were found in Finland. Policy Framework was a highly rated category across the countries, mainly with respect to weaknesses and threats. Intensified forest bioenergy harvesting and utilization has potentially wide country-specific impacts which need to be anticipated and considered in national policies and public dialogue. Copyright © 2016 Elsevier Ltd. All rights reserved.

Shapley value-based multi-objective data envelopment analysis application for assessing academic efficiency of university departments

NASA Astrophysics Data System (ADS)

Abing, Stephen Lloyd N.; Barton, Mercie Grace L.; Dumdum, Michael Gerard M.; Bongo, Miriam F.; Ocampo, Lanndon A.

2018-02-01

This paper adopts a modified approach of data envelopment analysis (DEA) to measure the academic efficiency of university departments. In real-world case studies, conventional DEA models often identify too many decision-making units (DMUs) as efficient. This occurs when the number of DMUs under evaluation is not large enough compared to the total number of decision variables. To overcome this limitation and reduce the number of decision variables, multi-objective data envelopment analysis (MODEA) approach previously presented in the literature is applied. The MODEA approach applies Shapley value as a cooperative game to determine the appropriate weights and efficiency score of each category of inputs. To illustrate the performance of the adopted approach, a case study is conducted in a university in the Philippines. The input variables are academic staff, non-academic staff, classrooms, laboratories, research grants, and department expenditures, while the output variables are the number of graduates and publications. The results of the case study revealed that all DMUs are inefficient. DMUs with efficiency scores close to the ideal efficiency score may be emulated by other DMUs with least efficiency scores.

Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis.

PubMed

Scholten, Lisa; Scheidegger, Andreas; Reichert, Peter; Maurer, Max; Mauer, Max; Lienert, Judit

2014-02-01

To overcome the difficulties of strategic asset management of water distribution networks, a pipe failure and a rehabilitation model are combined to predict the long-term performance of rehabilitation strategies. Bayesian parameter estimation is performed to calibrate the failure and replacement model based on a prior distribution inferred from three large water utilities in Switzerland. Multi-criteria decision analysis (MCDA) and scenario planning build the framework for evaluating 18 strategic rehabilitation alternatives under future uncertainty. Outcomes for three fundamental objectives (low costs, high reliability, and high intergenerational equity) are assessed. Exploitation of stochastic dominance concepts helps to identify twelve non-dominated alternatives and local sensitivity analysis of stakeholder preferences is used to rank them under four scenarios. Strategies with annual replacement of 1.5-2% of the network perform reasonably well under all scenarios. In contrast, the commonly used reactive replacement is not recommendable unless cost is the only relevant objective. Exemplified for a small Swiss water utility, this approach can readily be adapted to support strategic asset management for any utility size and based on objectives and preferences that matter to the respective decision makers. Copyright © 2013 Elsevier Ltd. All rights reserved.

Selecting wool-type fabrics for sensorial comfort in women office clothing for the cold season, using the multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Harpa, Rodica

2017-10-01

This article presents the strategy and the procedure used to achieve the declared goal: fabrics selection, pursuing sensorial comfort of a specific women-clothing item, by using the multi-criteria decision analysis. First, the objective evaluation of seven wool-type woven fabrics, suitable to the quality profile expected for the defined destination, was accomplished. Then, a survey was conducted on a sample of 187 consumers, women aged between 18 to 60 years old, with a background in the textile field, regarding both the preferences manifested in purchasing products, and the importance of various sensory perceptions through handling materials used in clothing products. Finally, the MCDM applied through the implementation of previous accomplished software STAT-ADM, allowed choosing the preferred wool-type fabric in order to get the expected sensorial comfort of women office trousers for the cold season, according to the previously established criteria. This overall approach showed good results in fabrics selection for assuring the sensorial comfort in women’s clothing, by using the multicriteria decision analysis based on a rating scale delivered by customers with knowledge in the textile field, but non-experts in the fabrics hand evaluation topic.

Multi-modal management of acromegaly: a value perspective.

PubMed

Kimmell, Kristopher T; Weil, Robert J; Marko, Nicholas F

2015-10-01

The Acromegaly Consensus Group recently released updated guidelines for medical management of acromegaly patients. We subjected these guidelines to a cost analysis. We conducted a cost analysis of the recommendations based on published efficacy rates as well as publicly available cost data. The results were compared to findings from a previously reported comparative effectiveness analysis of acromegaly treatments. Using decision tree software, two models were created based on the Acromegaly Consensus Group's recommendations and the comparative effectiveness analysis. The decision tree for the Consensus Group's recommendations was subjected to multi-way tornado analysis to identify variables that most impacted the value analysis of the decision tree. The value analysis confirmed the Consensus Group's recommendations of somatostatin analogs as first line therapy for medical management. Our model also demonstrated significant value in using dopamine agonist agents as upfront therapy as well. Sensitivity analysis identified the cost of somatostatin analogs and growth hormone receptor antagonists as having the most significant impact on the cost effectiveness of medical therapies. Our analysis confirmed the value of surgery as first-line therapy for patients with surgically accessible lesions. Surgery provides the greatest value for management of patients with acromegaly. However, in accordance with the Acromegaly Consensus Group's recent recommendations, somatostatin analogs provide the greatest value and should be used as first-line therapy for patients who cannot be managed surgically. At present, the substantial cost is the most significant negative factor in the value of medical therapies for acromegaly.

Multicriteria decision analysis applied to Glen Canyon Dam

USGS Publications Warehouse

Flug, M.; Seitz, H.L.H.; Scott, J.F.

2000-01-01

Conflicts in water resources exist because river-reservoir systems are managed to optimize traditional benefits (e.g., hydropower and flood control), which are historically quantified in economic terms, whereas natural and environmental resources, including in-stream and riparian resources, are more difficult or impossible to quantify in economic terms. Multicriteria decision analysis provides a quantitative approach to evaluate resources subject to river basin management alternatives. This objective quantification method includes inputs from special interest groups, the general public, and concerned individuals, as well as professionals for each resource considered in a trade-off analysis. Multicriteria decision analysis is applied to resources and flow alternatives presented in the environmental impact statement for Glen Canyon Dam on the Colorado River. A numeric rating and priority-weighting scheme is used to evaluate 29 specific natural resource attributes, grouped into seven main resource objectives, for nine flow alternatives enumerated in the environmental impact statement.

Multi-criteria development and incorporation into decision tools for health technology adoption.

PubMed

Poulin, Paule; Austen, Lea; Scott, Catherine M; Waddell, Cameron D; Dixon, Elijah; Poulin, Michelle; Lafrenière, René

2013-01-01

When introducing new health technologies, decision makers must integrate research evidence with local operational management information to guide decisions about whether and under what conditions the technology will be used. Multi-criteria decision analysis can support the adoption or prioritization of health interventions by using criteria to explicitly articulate the health organization's needs, limitations, and values in addition to evaluating evidence for safety and effectiveness. This paper seeks to describe the development of a framework to create agreed-upon criteria and decision tools to enhance a pre-existing local health technology assessment (HTA) decision support program. The authors compiled a list of published criteria from the literature, consulted with experts to refine the criteria list, and used a modified Delphi process with a group of key stakeholders to review, modify, and validate each criterion. In a workshop setting, the criteria were used to create decision tools. A set of user-validated criteria for new health technology evaluation and adoption was developed and integrated into the local HTA decision support program. Technology evaluation and decision guideline tools were created using these criteria to ensure that the decision process is systematic, consistent, and transparent. This framework can be used by others to develop decision-making criteria and tools to enhance similar technology adoption programs. The development of clear, user-validated criteria for evaluating new technologies adds a critical element to improve decision-making on technology adoption, and the decision tools ensure consistency, transparency, and real-world relevance.

Multi-model attribution of upper-ocean temperature changes using an isothermal approach.

PubMed

Weller, Evan; Min, Seung-Ki; Palmer, Matthew D; Lee, Donghyun; Yim, Bo Young; Yeh, Sang-Wook

2016-06-01

Both air-sea heat exchanges and changes in ocean advection have contributed to observed upper-ocean warming most evident in the late-twentieth century. However, it is predominantly via changes in air-sea heat fluxes that human-induced climate forcings, such as increasing greenhouse gases, and other natural factors such as volcanic aerosols, have influenced global ocean heat content. The present study builds on previous work using two different indicators of upper-ocean temperature changes for the detection of both anthropogenic and natural external climate forcings. Using simulations from phase 5 of the Coupled Model Intercomparison Project, we compare mean temperatures above a fixed isotherm with the more widely adopted approach of using a fixed depth. We present the first multi-model ensemble detection and attribution analysis using the fixed isotherm approach to robustly detect both anthropogenic and natural external influences on upper-ocean temperatures. Although contributions from multidecadal natural variability cannot be fully removed, both the large multi-model ensemble size and properties of the isotherm analysis reduce internal variability of the ocean, resulting in better observation-model comparison of temperature changes since the 1950s. We further show that the high temporal resolution afforded by the isotherm analysis is required to detect natural external influences such as volcanic cooling events in the upper-ocean because the radiative effect of volcanic forcings is short-lived.

Multi-model attribution of upper-ocean temperature changes using an isothermal approach

NASA Astrophysics Data System (ADS)

Weller, Evan; Min, Seung-Ki; Palmer, Matthew D.; Lee, Donghyun; Yim, Bo Young; Yeh, Sang-Wook

2016-06-01

Both air-sea heat exchanges and changes in ocean advection have contributed to observed upper-ocean warming most evident in the late-twentieth century. However, it is predominantly via changes in air-sea heat fluxes that human-induced climate forcings, such as increasing greenhouse gases, and other natural factors such as volcanic aerosols, have influenced global ocean heat content. The present study builds on previous work using two different indicators of upper-ocean temperature changes for the detection of both anthropogenic and natural external climate forcings. Using simulations from phase 5 of the Coupled Model Intercomparison Project, we compare mean temperatures above a fixed isotherm with the more widely adopted approach of using a fixed depth. We present the first multi-model ensemble detection and attribution analysis using the fixed isotherm approach to robustly detect both anthropogenic and natural external influences on upper-ocean temperatures. Although contributions from multidecadal natural variability cannot be fully removed, both the large multi-model ensemble size and properties of the isotherm analysis reduce internal variability of the ocean, resulting in better observation-model comparison of temperature changes since the 1950s. We further show that the high temporal resolution afforded by the isotherm analysis is required to detect natural external influences such as volcanic cooling events in the upper-ocean because the radiative effect of volcanic forcings is short-lived.

Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

2018-03-01

GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

Visualising Pareto-optimal trade-offs helps move beyond monetary-only criteria for water management decisions

NASA Astrophysics Data System (ADS)

Hurford, Anthony; Harou, Julien

2014-05-01

Water related eco-system services are important to the livelihoods of the poorest sectors of society in developing countries. Degradation or loss of these services can increase the vulnerability of people decreasing their capacity to support themselves. New approaches to help guide water resources management decisions are needed which account for the non-market value of ecosystem goods and services. In case studies from Brazil and Kenya we demonstrate the capability of many objective Pareto-optimal trade-off analysis to help decision makers balance economic and non-market benefits from the management of existing multi-reservoir systems. A multi-criteria search algorithm is coupled to a water resources management simulator of each basin to generate a set of Pareto-approximate trade-offs representing the best case management decisions. In both cases, volume dependent reservoir release rules are the management decisions being optimised. In the Kenyan case we further assess the impacts of proposed irrigation investments, and how the possibility of new investments impacts the system's trade-offs. During the multi-criteria search (optimisation), performance of different sets of management decisions (policies) is assessed against case-specific objective functions representing provision of water supply and irrigation, hydropower generation and maintenance of ecosystem services. Results are visualised as trade-off surfaces to help decision makers understand the impacts of different policies on a broad range of stakeholders and to assist in decision-making. These case studies show how the approach can reveal unexpected opportunities for win-win solutions, and quantify the trade-offs between investing to increase agricultural revenue and negative impacts on protected ecosystems which support rural livelihoods.

Uncertainty analysis for effluent trading planning using a Bayesian estimation-based simulation-optimization modeling approach.

PubMed

Zhang, J L; Li, Y P; Huang, G H; Baetz, B W; Liu, J

2017-06-01

In this study, a Bayesian estimation-based simulation-optimization modeling approach (BESMA) is developed for identifying effluent trading strategies. BESMA incorporates nutrient fate modeling with soil and water assessment tool (SWAT), Bayesian estimation, and probabilistic-possibilistic interval programming with fuzzy random coefficients (PPI-FRC) within a general framework. Based on the water quality protocols provided by SWAT, posterior distributions of parameters can be analyzed through Bayesian estimation; stochastic characteristic of nutrient loading can be investigated which provides the inputs for the decision making. PPI-FRC can address multiple uncertainties in the form of intervals with fuzzy random boundaries and the associated system risk through incorporating the concept of possibility and necessity measures. The possibility and necessity measures are suitable for optimistic and pessimistic decision making, respectively. BESMA is applied to a real case of effluent trading planning in the Xiangxihe watershed, China. A number of decision alternatives can be obtained under different trading ratios and treatment rates. The results can not only facilitate identification of optimal effluent-trading schemes, but also gain insight into the effects of trading ratio and treatment rate on decision making. The results also reveal that decision maker's preference towards risk would affect decision alternatives on trading scheme as well as system benefit. Compared with the conventional optimization methods, it is proved that BESMA is advantageous in (i) dealing with multiple uncertainties associated with randomness and fuzziness in effluent-trading planning within a multi-source, multi-reach and multi-period context; (ii) reflecting uncertainties existing in nutrient transport behaviors to improve the accuracy in water quality prediction; and (iii) supporting pessimistic and optimistic decision making for effluent trading as well as promoting diversity of decision alternatives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Applying Subject Matter Expertise (SME) Elicitation Techniques to TRAC Studies

DTIC Science & Technology

2014-09-30

prioritisation, budgeting and resource allocation with multi-criteria decision analysis and decision conferencing ”. English. In: Annals of Operations... electronically . Typically, in responding to survey items, experts are not expected to elaborate beyond providing responses in the format requested in the...between them, however irrelevant to probability Kynn and Ayyub.84 For example, an electronic jamming device might disrupt a cell phone signal at certain

Amplifying Each Patient's Voice: A Systematic Review of Multi-criteria Decision Analyses Involving Patients.

PubMed

Marsh, Kevin; Caro, J Jaime; Hamed, Alaa; Zaiser, Erica

2017-04-01

Qualitative methods tend to be used to incorporate patient preferences into healthcare decision making. However, for patient preferences to be given adequate consideration by decision makers they need to be quantified. Multi-criteria decision analysis (MCDA) is one way to quantify and capture the patient voice. The objective of this review was to report on existing MCDAs involving patients to support the future use of MCDA to capture the patient voice. MEDLINE and EMBASE were searched in June 2014 for English-language papers with no date restriction. The following search terms were used: 'multi-criteria decision*', 'multiple criteria decision*', 'MCDA', 'benefit risk assessment*', 'risk benefit assessment*', 'multicriteri* decision*', 'MCDM', 'multi-criteri* decision*'. Abstracts were included if they reported the application of MCDA to assess healthcare interventions where patients were the source of weights. Abstracts were excluded if they did not apply MCDA, such as discussions of how MCDA could be used; or did not evaluate healthcare interventions, such as MCDAs to assess the level of health need in a locality. Data were extracted on weighting method, variation in patient and expert preferences, and discussion on different weighting techniques. The review identified ten English-language studies that reported an MCDA to assess healthcare interventions and involved patients as a source of weights. These studies reported 12 applications of MCDA. Different methods of preference elicitation were employed: direct weighting in workshops; discrete choice experiment surveys; and the analytical hierarchy process using both workshops and surveys. There was significant heterogeneity in patient responses and differences between patients, who put greater weight on disease characteristics and treatment convenience, and experts, who put more weight on efficacy. The studies highlighted cognitive challenges associated with some weighting methods, though patients' views on their ability to undertake weighting tasks was positive. This review identified several recent examples of MCDA used to elicit patient preferences, which support the feasibility of using MCDA to capture the patient voice. Challenges identified included, how best to reflect the heterogeneity of patient preferences in decision making and how to manage the cognitive burden associated with some MCDA tasks.

Analysis of Multi-Criteria Evaluation Method of Landfill Site Selection for Municipal Solid Waste Management

NASA Astrophysics Data System (ADS)

Mohammed, Habiba Ibrahim; Majid, Zulkepli; Yusof, Norhakim Bin; Bello Yamusa, Yamusa

2018-03-01

Landfilling remains the most common systematic technique of solid waste disposal in most of the developed and developing countries. Finding a suitable site for landfill is a very challenging task. Landfill site selection process aims to provide suitable areas that will protect the environment and public health from pollution and hazards. Therefore, various factors such as environmental, physical, socio-economic, and geological criteria must be considered before siting any landfill. This makes the site selection process vigorous and tedious because it involves the processing of large amount of spatial data, rules and regulations from different agencies and also policy from decision makers. This allows the incorporation of conflicting objectives and decision maker preferences into spatial decision models. This paper particularly analyzes the multi-criteria evaluation (MCE) method of landfill site selection for solid waste management by means of literature reviews and surveys. The study will help the decision makers and waste management authorities to choose the most effective method when considering landfill site selection.

Percutaneous Trigger Finger Release: A Cost-effectiveness Analysis.

PubMed

Gancarczyk, Stephanie M; Jang, Eugene S; Swart, Eric P; Makhni, Eric C; Kadiyala, Rajendra Kumar

2016-07-01

Percutaneous trigger finger releases (TFRs) performed in the office setting are becoming more prevalent. This study compares the costs of in-hospital open TFRs, open TFRs performed in ambulatory surgical centers (ASCs), and in-office percutaneous releases. An expected-value decision-analysis model was constructed from the payer perspective to estimate total costs of the three competing treatment strategies for TFR. Model parameters were estimated based on the best available literature and were tested using multiway sensitivity analysis. Percutaneous TFR performed in the office and then, if needed, revised open TFR performed in the ASC, was the most cost-effective strategy, with an attributed cost of $603. The cost associated with an initial open TFR performed in the ASC was approximately 7% higher. Initial open TFR performed in the hospital was the least cost-effective, with an attributed cost nearly twice that of primary percutaneous TFR. An initial attempt at percutaneous TFR is more cost-effective than an open TFR. Currently, only about 5% of TFRs are performed in the office; therefore, a substantial opportunity exists for cost savings in the future. Decision model level II.

Survival or Mortality: Does Risk Attribute Framing Influence Decision-Making Behavior in a Discrete Choice Experiment?

PubMed

Veldwijk, Jorien; Essers, Brigitte A B; Lambooij, Mattijs S; Dirksen, Carmen D; Smit, Henriette A; de Wit, G Ardine

2016-01-01

To test how attribute framing in a discrete choice experiment (DCE) affects respondents' decision-making behavior and their preferences. Two versions of a DCE questionnaire containing nine choice tasks were distributed among a representative sample of the Dutch population aged 55 to 65 years. The DCE consisted of four attributes related to the decision regarding participation in genetic screening for colorectal cancer (CRC). The risk attribute included was framed positively as the probability of surviving CRC and negatively as the probability of dying from CRC. Panel mixed-logit models were used to estimate the relative importance of the attributes. The data of the positively and negatively framed DCE were compared on the basis of direct attribute ranking, dominant decision-making behavior, preferences, and importance scores. The majority (56%) of the respondents ranked survival as the most important attribute in the positively framed DCE, whereas only a minority (8%) of the respondents ranked mortality as the most important attribute in the negatively framed DCE. Respondents made dominant choices based on survival significantly more often than based on mortality. The framing of the risk attribute significantly influenced all attribute-level estimates and resulted in different preference structures among respondents in the positively and negatively framed data set. Risk framing affects how respondents value the presented risk. Positive risk framing led to increased dominant decision-making behavior, whereas negative risk framing led to risk-seeking behavior. Attribute framing should have a prominent part in the expert and focus group interviews, and different types of framing should be used in the pilot version of DCEs as well as in actual DCEs to estimate the magnitude of the effect of choosing different types of framing. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Identification and Prioritization of Important Attributes of Disease-Modifying Drugs in Decision Making among Patients with Multiple Sclerosis: A Nominal Group Technique and Best-Worst Scaling.

PubMed

Kremer, Ingrid E H; Evers, Silvia M A A; Jongen, Peter J; van der Weijden, Trudy; van de Kolk, Ilona; Hiligsmann, Mickaël

2016-01-01

Understanding the preferences of patients with multiple sclerosis (MS) for disease-modifying drugs and involving these patients in clinical decision making can improve the concordance between medical decisions and patient values and may, subsequently, improve adherence to disease-modifying drugs. This study aims first to identify which characteristics-or attributes-of disease-modifying drugs influence patients´ decisions about these treatments and second to quantify the attributes' relative importance among patients. First, three focus groups of relapsing-remitting MS patients were formed to compile a preliminary list of attributes using a nominal group technique. Based on this qualitative research, a survey with several choice tasks (best-worst scaling) was developed to prioritize attributes, asking a larger patient group to choose the most and least important attributes. The attributes' mean relative importance scores (RIS) were calculated. Nineteen patients reported 34 attributes during the focus groups and 185 patients evaluated the importance of the attributes in the survey. The effect on disease progression received the highest RIS (RIS = 9.64, 95% confidence interval: [9.48-9.81]), followed by quality of life (RIS = 9.21 [9.00-9.42]), relapse rate (RIS = 7.76 [7.39-8.13]), severity of side effects (RIS = 7.63 [7.33-7.94]) and relapse severity (RIS = 7.39 [7.06-7.73]). Subgroup analyses showed heterogeneity in preference of patients. For example, side effect-related attributes were statistically more important for patients who had no experience in using disease-modifying drugs compared to experienced patients (p < .001). This study shows that, on average, patients valued effectiveness and unwanted effects as most important. Clinicians should be aware of the average preferences but also that attributes of disease-modifying drugs are valued differently by different patients. Person-centred clinical decision making would be needed and requires eliciting individual preferences.

Attribute Development Using Continuous Stakeholder Engagement to Prioritize Treatment Decisions: A Framework for Patient-Centered Research.

PubMed

dosReis, Susan; Castillo, Wendy Camelo; Ross, Melissa; Fitz-Randolph, Marcy; Vaughn-Lee, Angela; Butler, Beverly

To develop a methodological approach for selecting, validating, and prioritizing attributes for health care decision making. Participants (n = 48) were recruited from community support groups if they had a child aged 26 years or younger diagnosed with a coexisting mental health condition and cognitive impairment. Six in-depth interviews eliciting care management experiences were transcribed and coded into themes following the principles of grounded theory and the constant comparative method. Six focus groups involving 42 participants assessed the relevance, priority, and meaning and inter-relationship among the themes. The positive predictive value and sensitivity assessed agreement on thematic meaning. A final list was selected from the top priorities with good agreement as candidate attributes. Attribute levels reflecting the range of experiences in care management decisions emerged from the verbatim passages within each coded theme. Participants were the child's mother (73%), white (77%), married (69%), and on average 48 years old. The children were on average 14 years old; 44% had an intellectual disability, 25% had autism, and more than half had anxiety or attention-deficit/hyperactivity disorder. All 14 attributes identified from the in-depth interviews were deemed relevant. The positive predictive value exceeded 90%, and the sensitivity ranged from 64% to 89%. The final set of attributes formed the framework for care management decisions consisting of six attributes (medication, behavior, services, social, treatment effects, and school) each with three levels. A systematic approach grounded in qualitative methods produced a framework of relevant, important, and actionable attributes representing competing alternatives in clinical decisions. Copyright © 2016. Published by Elsevier Inc.

Using Arden Syntax for the creation of a multi-patient surveillance dashboard.

PubMed

Kraus, Stefan; Drescher, Caroline; Sedlmayr, Martin; Castellanos, Ixchel; Prokosch, Hans-Ulrich; Toddenroth, Dennis

2015-10-09

Most practically deployed Arden-Syntax-based clinical decision support (CDS) modules process data from individual patients. The specification of Arden Syntax, however, would in principle also support multi-patient CDS. The patient data management system (PDMS) at our local intensive care units does not natively support patient overviews from customizable CDS routines, but local physicians indicated a demand for multi-patient tabular overviews of important clinical parameters such as key laboratory measurements. As our PDMS installation provides Arden Syntax support, we set out to explore the capability of Arden Syntax for multi-patient CDS by implementing a prototypical dashboard for visualizing laboratory findings from patient sets. Our implementation leveraged the object data type, supported by later versions of Arden, which turned out to be serviceable for representing complex input data from several patients. For our prototype, we designed a modularized architecture that separates the definition of technical operations, in particular the control of the patient context, from the actual clinical knowledge. Individual Medical Logic Modules (MLMs) for processing single patient attributes could then be developed according to well-tried Arden Syntax conventions. We successfully implemented a working dashboard prototype entirely in Arden Syntax. The architecture consists of a controller MLM to handle the patient context, a presenter MLM to generate a dashboard view, and a set of traditional MLMs containing the clinical decision logic. Our prototype could be integrated into the graphical user interface of the local PDMS. We observed that with realistic input data the average execution time of about 200ms for generating dashboard views attained applicable performance. Our study demonstrated the general feasibility of creating multi-patient CDS routines in Arden Syntax. We believe that our prototypical dashboard also suggests that such implementations can be relatively easy, and may simultaneously hold promise for sharing dashboards between institutions and reusing elementary components for additional dashboards. Copyright © 2015 Elsevier B.V. All rights reserved.

GPA and Attribute Framing Effects: Are Better Students More Sensitive or More Susceptible?

ERIC Educational Resources Information Center

Dunegan, Ken

2010-01-01

Data from 2 studies show students differ in terms of how attribute framing alters perceptions and reactions in a decision-making episode. Using student GPA as a moderator, results from a role-play-decision-making exercise (Experiment 1) show perceptions and intended actions of higher GPA students were more strongly affected by attribute framing…

The importance of accurate muscle modelling for biomechanical analyses: a case study with a lizard skull

PubMed Central

Gröning, Flora; Jones, Marc E. H.; Curtis, Neil; Herrel, Anthony; O'Higgins, Paul; Evans, Susan E.; Fagan, Michael J.

2013-01-01

Computer-based simulation techniques such as multi-body dynamics analysis are becoming increasingly popular in the field of skull mechanics. Multi-body models can be used for studying the relationships between skull architecture, muscle morphology and feeding performance. However, to be confident in the modelling results, models need to be validated against experimental data, and the effects of uncertainties or inaccuracies in the chosen model attributes need to be assessed with sensitivity analyses. Here, we compare the bite forces predicted by a multi-body model of a lizard (Tupinambis merianae) with in vivo measurements, using anatomical data collected from the same specimen. This subject-specific model predicts bite forces that are very close to the in vivo measurements and also shows a consistent increase in bite force as the bite position is moved posteriorly on the jaw. However, the model is very sensitive to changes in muscle attributes such as fibre length, intrinsic muscle strength and force orientation, with bite force predictions varying considerably when these three variables are altered. We conclude that accurate muscle measurements are crucial to building realistic multi-body models and that subject-specific data should be used whenever possible. PMID:23614944

A Compact Review of Multi-criteria Decision Analysis Uncertainty Techniques

DTIC Science & Technology

2013-02-01

9 3.4 PROMETHEE -GAIA Method...obtained (74). 3.4 PROMETHEE -GAIA Method Preference Ranking Organization Method for Enrichment Evaluation ( PROMETHEE ) and Geometrical Analysis for...greater understanding of the importance of their selections. The PROMETHEE method was designed to perform MCDA while accounting for each of these

Attribute-based Decision Graphs: A framework for multiclass data classification.

PubMed

Bertini, João Roberto; Nicoletti, Maria do Carmo; Zhao, Liang

2017-01-01

Graph-based algorithms have been successfully applied in machine learning and data mining tasks. A simple but, widely used, approach to build graphs from vector-based data is to consider each data instance as a vertex and connecting pairs of it using a similarity measure. Although this abstraction presents some advantages, such as arbitrary shape representation of the original data, it is still tied to some drawbacks, for example, it is dependent on the choice of a pre-defined distance metric and is biased by the local information among data instances. Aiming at exploring alternative ways to build graphs from data, this paper proposes an algorithm for constructing a new type of graph, called Attribute-based Decision Graph-AbDG. Given a vector-based data set, an AbDG is built by partitioning each data attribute range into disjoint intervals and representing each interval as a vertex. The edges are then established between vertices from different attributes according to a pre-defined pattern. Classification is performed through a matching process among the attribute values of the new instance and AbDG. Moreover, AbDG provides an inner mechanism to handle missing attribute values, which contributes for expanding its applicability. Results of classification tasks have shown that AbDG is a competitive approach when compared to well-known multiclass algorithms. The main contribution of the proposed framework is the combination of the advantages of attribute-based and graph-based techniques to perform robust pattern matching data classification, while permitting the analysis the input data considering only a subset of its attributes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multiple stakeholders in multi-criteria decision-making in the context of Municipal Solid Waste Management: A review.

PubMed

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh; Sadiq, Rehan

2015-01-01

Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, and finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Insurees' preferences in hospital choice-A population-based study.

PubMed

Schuldt, Johannes; Doktor, Anna; Lichters, Marcel; Vogt, Bodo; Robra, Bernt-Peter

2017-10-01

In Germany, the patient himself makes the choice for or against a health service provider. Hospital comparison websites offer him possibilities to inform himself before choosing. However, it remains unclear, how health care consumers use those websites, and there is little information about how preferences in hospital choice differ interpersonally. We conducted a Discrete-Choice-Experiment (DCE) on hospital choice with 1500 randomly selected participants (age 40-70) in three different German cities selecting four attributes for hospital vignettes. The analysis of the study draws on multilevel mixed effects logit regression analyses with the dependent variables: "chance to select a hospital" and "choice confidence". Subsequently, we performed a Latent-Class-Analysis to uncover consumer segments with distinct preferences. 590 of the questionnaires were evaluable. All four attributes of the hospital vignettes have a significant impact on hospital choice. The attribute "complication rate" exerts the highest impact on consumers' decisions and reported choice confidence. Latent-Class-Analysis results in one dominant consumer segment that considered the complication rate the most important decision criterion. Using DCE, we were able to show that the complication rate is an important trusted criterion in hospital choice to a large group of consumers. Our study supports current governmental efforts in Germany to concentrate the provision of specialized health care services. We suggest further national and cross-national research on the topic. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Multi-criteria group decision making for evaluating the performance of e-waste recycling programs under uncertainty.

PubMed

Wibowo, Santoso; Deng, Hepu

2015-06-01

This paper presents a multi-criteria group decision making approach for effectively evaluating the performance of e-waste recycling programs under uncertainty in an organization. Intuitionistic fuzzy numbers are used for adequately representing the subjective and imprecise assessments of the decision makers in evaluating the relative importance of evaluation criteria and the performance of individual e-waste recycling programs with respect to individual criteria in a given situation. An interactive fuzzy multi-criteria decision making algorithm is developed for facilitating consensus building in a group decision making environment to ensure that all the interest of individual decision makers have been appropriately considered in evaluating alternative e-waste recycling programs with respect to their corporate sustainability performance. The developed algorithm is then incorporated into a multi-criteria decision support system for making the overall performance evaluation process effectively and simple to use. Such a multi-criteria decision making system adequately provides organizations with a proactive mechanism for incorporating the concept of corporate sustainability into their regular planning decisions and business practices. An example is presented for demonstrating the applicability of the proposed approach in evaluating the performance of e-waste recycling programs in organizations. Copyright © 2015 Elsevier Ltd. All rights reserved.

A fuzzy model for achieving lean attributes for competitive advantages development using AHP-QFD-PROMETHEE

NASA Astrophysics Data System (ADS)

Roghanian, E.; Alipour, Mohammad

2014-06-01

Lean production has become an integral part of the manufacturing landscape as its link with superior performance and its ability to provide competitive advantage is well accepted among academics and practitioners. Lean production helps producers in overcoming the challenges organizations face through using powerful tools and enablers. However, most companies are faced with restricted resources such as financial and human resources, time, etc., in using these enablers, and are not capable of implementing all these techniques. Therefore, identifying and selecting the most appropriate and efficient tool can be a significant challenge for many companies. Hence, this literature seeks to combine competitive advantages, lean attributes, and lean enablers to determine the most appropriate enablers for improvement of lean attributes. Quality function deployment in fuzzy environment and house of quality matrix are implemented. Throughout the methodology, fuzzy logic is the basis for translating linguistic judgments required for the relationships and correlation matrix to numerical values. Moreover, for final ranking of lean enablers, a multi-criteria decision-making method (PROMETHEE) is adopted. Finally, a case study in automotive industry is presented to illustrate the implementation of the proposed methodology.

Network-centric decision architecture for financial or 1/f data models

NASA Astrophysics Data System (ADS)

Jaenisch, Holger M.; Handley, James W.; Massey, Stoney; Case, Carl T.; Songy, Claude G.

2002-12-01

This paper presents a decision architecture algorithm for training neural equation based networks to make autonomous multi-goal oriented, multi-class decisions. These architectures make decisions based on their individual goals and draw from the same network centric feature set. Traditionally, these architectures are comprised of neural networks that offer marginal performance due to lack of convergence of the training set. We present an approach for autonomously extracting sample points as I/O exemplars for generation of multi-branch, multi-node decision architectures populated by adaptively derived neural equations. To test the robustness of this architecture, open source data sets in the form of financial time series were used, requiring a three-class decision space analogous to the lethal, non-lethal, and clutter discrimination problem. This algorithm and the results of its application are presented here.

Efficiently Multi-User Searchable Encryption Scheme with Attribute Revocation and Grant for Cloud Storage

PubMed Central

Wang, Shangping; Zhang, Xiaoxue; Zhang, Yaling

2016-01-01

Cipher-policy attribute-based encryption (CP-ABE) focus on the problem of access control, and keyword-based searchable encryption scheme focus on the problem of finding the files that the user interested in the cloud storage quickly. To design a searchable and attribute-based encryption scheme is a new challenge. In this paper, we propose an efficiently multi-user searchable attribute-based encryption scheme with attribute revocation and grant for cloud storage. In the new scheme the attribute revocation and grant processes of users are delegated to proxy server. Our scheme supports multi attribute are revoked and granted simultaneously. Moreover, the keyword searchable function is achieved in our proposed scheme. The security of our proposed scheme is reduced to the bilinear Diffie-Hellman (BDH) assumption. Furthermore, the scheme is proven to be secure under the security model of indistinguishability against selective ciphertext-policy and chosen plaintext attack (IND-sCP-CPA). And our scheme is also of semantic security under indistinguishability against chosen keyword attack (IND-CKA) in the random oracle model. PMID:27898703

Efficiently Multi-User Searchable Encryption Scheme with Attribute Revocation and Grant for Cloud Storage.

PubMed

Wang, Shangping; Zhang, Xiaoxue; Zhang, Yaling

2016-01-01

Cipher-policy attribute-based encryption (CP-ABE) focus on the problem of access control, and keyword-based searchable encryption scheme focus on the problem of finding the files that the user interested in the cloud storage quickly. To design a searchable and attribute-based encryption scheme is a new challenge. In this paper, we propose an efficiently multi-user searchable attribute-based encryption scheme with attribute revocation and grant for cloud storage. In the new scheme the attribute revocation and grant processes of users are delegated to proxy server. Our scheme supports multi attribute are revoked and granted simultaneously. Moreover, the keyword searchable function is achieved in our proposed scheme. The security of our proposed scheme is reduced to the bilinear Diffie-Hellman (BDH) assumption. Furthermore, the scheme is proven to be secure under the security model of indistinguishability against selective ciphertext-policy and chosen plaintext attack (IND-sCP-CPA). And our scheme is also of semantic security under indistinguishability against chosen keyword attack (IND-CKA) in the random oracle model.

Clinical decision regret among critical care nurses: a qualitative analysis.

PubMed

Arslanian-Engoren, Cynthia; Scott, Linda D

2014-01-01

Decision regret is a negative cognitive emotion associated with experiences of guilt and situations of interpersonal harm. These negative affective responses may contribute to emotional exhaustion in critical care nurses (CCNs), increased staff turnover rates and high medication error rates. Yet, little is known about clinical decision regret among CCNs or the conditions or situations (e.g., feeling sleepy) that may precipitate its occurrence. To examine decision regret among CCNs, with an emphasis on clinical decisions made when nurses were most sleepy. A content analytic approach was used to examine the narrative descriptions of clinical decisions by CCNs when sleepy. Six decision regret themes emerged that represented deviations in practice or performance behaviors that were attributed to fatigued CCNs. While 157 CCNs disclosed a clinical decision they made at work while sleepy, the prevalence may be underestimated and warrants further investigation. Copyright © 2014 Elsevier Inc. All rights reserved.

A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE

NASA Astrophysics Data System (ADS)

Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

2009-11-01

A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

A comparative approach for ranking contaminated sites based on the risk assessment paradigm using fuzzy PROMETHEE.

PubMed

Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

2009-11-01

A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

Lawyers' attitudes toward involuntary treatment.

PubMed

Luchins, Daniel J; Cooper, Amy E; Hanrahan, Patricia; Heyrman, Mark J

2006-01-01

This study examined whether lawyers' attributions of responsibility for mental illnesses affect their decisions about involuntary treatment. A survey that was mailed in 2003 to Illinois lawyers involved in involuntary commitment elicited recommendations for involuntary treatment for characters presented in vignettes. The survey also sought respondents' attributions of personal responsibility for the onset and recurrence of mental illnesses. A total of 89 lawyers responded to the survey, a response rate of 48 percent. Decisions to hospitalize persons with mental illness involuntarily increased significantly with the level of risk of harm and were significantly related to attributions of responsibility for the recurrence of mental illness. Decisions to recommend involuntary medication were not related to attributions of responsibility.

Systems analysis - a new paradigm and decision support tools for the water framework directive

NASA Astrophysics Data System (ADS)

Bruen, M.

2007-06-01

In the early days of Systems Analysis the focus was on providing tools for optimisation, modelling and simulation for use by experts. Now there is a recognition of the need to develop and disseminate tools to assist in making decisions, negotiating compromises and communicating preferences that can easily be used by stakeholders without the need for specialist training. The Water Framework Directive (WFD) requires public participation and thus provides a strong incentive for progress in this direction. This paper places the new paradigm in the context of the classical one and discusses some of the new approaches which can be used in the implementation of the WFD. These include multi-criteria decision support methods suitable for environmental problems, adaptive management, cognitive mapping, social learning and cooperative design and group decision-making. Concordance methods (such as ELECTRE) and the Analytical Hierarchy Process (AHP) are identified as multi-criteria methods that can be readily integrated into Decision Support Systems (DSS) that deal with complex environmental issues with very many criteria, some of which are qualitative. The expanding use of the new paradigm provides an opportunity to observe and learn from the interaction of stakeholders with the new technology and to assess its effectiveness. This is best done by trained sociologists fully integrated into the processes. The WINCOMS research project is an example applied to the implementation of the WFD in Ireland.

[Analyzing consumer preference by using the latest semantic model for verbal protocol].

PubMed

Tamari, Yuki; Takemura, Kazuhisa

2012-02-01

This paper examines consumers' preferences for competing brands by using a preference model of verbal protocols. Participants were 150 university students, who reported their opinions and feelings about McDonalds and Mos Burger (competing hamburger restaurants in Japan). Their verbal protocols were analyzed by using the singular value decomposition method, and the latent decision frames were estimated. The verbal protocols having a large value in the decision frames could be interpreted as showing attributes that consumers emphasize. Based on the estimated decision frames, we predicted consumers' preferences using the logistic regression analysis method. The results indicate that the decision frames projected from the verbal protocol data explained consumers' preferences effectively.

Distinction between Externally vs. Internally Guided Decision-Making: Operational Differences, Meta-Analytical Comparisons and Their Theoretical Implications

PubMed Central

Nakao, Takashi; Ohira, Hideki; Northoff, Georg

2012-01-01

Most experimental studies of decision-making have specifically examined situations in which a single less-predictable correct answer exists (externally guided decision-making under uncertainty). Along with such externally guided decision-making, there are instances of decision-making in which no correct answer based on external circumstances is available for the subject (internally guided decision-making). Such decisions are usually made in the context of moral decision-making as well as in preference judgment, where the answer depends on the subject’s own, i.e., internal, preferences rather than on external, i.e., circumstantial, criteria. The neuronal and psychological mechanisms that allow guidance of decisions based on more internally oriented criteria in the absence of external ones remain unclear. This study was undertaken to compare decision-making of these two kinds empirically and theoretically. First, we reviewed studies of decision-making to clarify experimental–operational differences between externally guided and internally guided decision-making. Second, using multi-level kernel density analysis, a whole-brain-based quantitative meta-analysis of neuroimaging studies was performed. Our meta-analysis revealed that the neural network used predominantly for internally guided decision-making differs from that for externally guided decision-making under uncertainty. This result suggests that studying only externally guided decision-making under uncertainty is insufficient to account for decision-making processes in the brain. Finally, based on the review and results of the meta-analysis, we discuss the differences and relations between decision-making of these two types in terms of their operational, neuronal, and theoretical characteristics. PMID:22403525

Multi-disciplinary team meetings in stroke rehabilitation: an observation study and conceptual framework.

PubMed

Tyson, S F; Burton, L; McGovern, A

2014-12-01

To explore how multi-disciplinary team meetings operate in stroke rehabilitation. Non-participant observation of multi-disciplinary team meetings and semi-structured interviews with attending staff. Twelve meetings were observed (at least one at each site) and 18 staff (one psychologist, one social worker; four nurses; four physiotherapists four occupational therapists, two speech and language therapists, one stroke co-ordinator and one stroke ward manager) were interviewed in eight in-patient stroke rehabilitation units. Multi-disciplinary team meetings in stroke rehabilitation were complex, demanding and highly varied. A model emerged which identified the main inputs to influence conduct of the meetings were personal contributions of the members and structure and format of the meetings. These were mediated by the team climate and leadership skills of the chair. The desired outputs; clinical decisions and the attributes of apparently effective meetings were identified by the staff. A notable difference between the meetings that staff considered effective and those that were not, was their structure and format. Successful meetings tended to feature a set agenda, structured documentation; formal use of measurement tools; pre-meeting preparation and skilled chairing. These features were often absent in meetings perceived to be ineffective. The main features of operation of multi-disciplinary team meetings have been identified which will enable assessment tools and interventions to improve effectiveness to be developed. © The Author(s) 2014.

Multi-Stakeholder Decision Aid for Improved Prioritization of the Public Health Impact of Climate Sensitive Infectious Diseases

PubMed Central

Hongoh, Valerie; Michel, Pascal; Gosselin, Pierre; Samoura, Karim; Ravel, André; Campagna, Céline; Cissé, Hassane Djibrilla; Waaub, Jean-Philippe

2016-01-01

The effects of climate change on infectious diseases are an important global health concern and necessitate decisions for allocation of resources. Economic tools have been used previously; however, how prioritization results might differ when done using broader considerations identified by local stakeholders has yet to be assessed. A multicriteria decision analysis (MCDA) approach was used to assess multi-stakeholder expressed concerns around disease prioritization via focus groups held in Quebec and Burkina Faso. Stakeholders weighted criteria and comparisons were made across study sites. A pilot disease prioritization was done to examine effects on disease rankings. A majority of identified criteria were common to both sites. The effect of context specific criteria and weights resulted in similar yet distinct prioritizations of diseases. The presence of consistent criteria between sites suggests that common concerns exist for prioritization; however, context-specific adjustments reveal much regarding resource availability, capacity and concerns that should be considered as this impacts disease ranking. Participatory decision aid approaches facilitate rich knowledge exchange and problem structuring. Furthermore, given multiple actors in low- and middle-income countries settings, multi-actor collaborations across non-governmental organizations, local government and community are important. Formal mechanisms such as MCDA provide means to foster consensus, shared awareness and collaboration. PMID:27077875

Diverse Expected Gradient Active Learning for Relative Attributes.

PubMed

You, Xinge; Wang, Ruxin; Tao, Dacheng

2014-06-02

The use of relative attributes for semantic understanding of images and videos is a promising way to improve communication between humans and machines. However, it is extremely labor- and time-consuming to define multiple attributes for each instance in large amount of data. One option is to incorporate active learning, so that the informative samples can be actively discovered and then labeled. However, most existing active-learning methods select samples one at a time (serial mode), and may therefore lose efficiency when learning multiple attributes. In this paper, we propose a batch-mode active-learning method, called Diverse Expected Gradient Active Learning (DEGAL). This method integrates an informativeness analysis and a diversity analysis to form a diverse batch of queries. Specifically, the informativeness analysis employs the expected pairwise gradient length as a measure of informativeness, while the diversity analysis forces a constraint on the proposed diverse gradient angle. Since simultaneous optimization of these two parts is intractable, we utilize a two-step procedure to obtain the diverse batch of queries. A heuristic method is also introduced to suppress imbalanced multi-class distributions. Empirical evaluations of three different databases demonstrate the effectiveness and efficiency of the proposed approach.

Averaging Models: Parameters Estimation with the R-Average Procedure

ERIC Educational Resources Information Center

Vidotto, G.; Massidda, D.; Noventa, S.

2010-01-01

The Functional Measurement approach, proposed within the theoretical framework of Information Integration Theory (Anderson, 1981, 1982), can be a useful multi-attribute analysis tool. Compared to the majority of statistical models, the averaging model can account for interaction effects without adding complexity. The R-Average method (Vidotto &…

Strategic planning decision making using fuzzy SWOT-TOPSIS with reliability factor

NASA Astrophysics Data System (ADS)

Mohamad, Daud; Afandi, Nur Syamimi; Kamis, Nor Hanimah

2015-10-01

Strategic planning is a process of decision making and action for long-term activities in an organization. The Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis has been commonly used to help organizations in strategizing their future direction by analyzing internal and external environment. However, SWOT analysis has some limitations as it is unable to prioritize appropriately the multiple alternative strategic decisions. Some efforts have been made to solve this problem by incorporating Multi Criteria Decision Making (MCDM) methods. Nevertheless, another important aspect has raised concerns on obtaining the decision that is the reliability of the information. Decision makers evaluate differently depending on their level of confidence or sureness in the evaluation. This study proposes a decision making procedure for strategic planning using SWOT-TOPSIS method by incorporating the reliability factor of the evaluation based on Z-number. An example using a local authority in the east coast of Malaysia is illustrated to determine the strategic options ranking and to prioritize factors in each SWOT category.

Neural correlates of depressive realism – An fMRI study on causal attribution in depression

PubMed Central

Seidel, Eva-Maria; Satterthwaite, Theodore D.; Eickhoff, Simon B.; Schneider, Frank; Gur, Ruben C.; Wolf, Daniel H.; Habel, Ute; Derntl, Birgit

2013-01-01

Background Biased causal attribution is a critical factor in the cognitive model of depression. Whereas depressed patients interpret events negatively, healthy people show a self-serving bias (internal attribution of positive events and external attribution of negative events). Methods Using fMRI, depressed patients (n=15) and healthy controls (n=15) were confronted with positive and negative social events and made causal attributions (internal vs. external). Functional data were analyzed using a mixed effects model. Results Behaviourally, controls showed a self-serving bias, whereas patients demonstrated a balanced attributional pattern. Analysis of functional data revealed a significant group difference in a fronto-temporal network. Higher activation of this network was associated with non self-serving attributions in controls but self-serving attributions in patients. Applying a psycho-physiological interaction analysis, we observed reduced coupling between a dorsomedial PFC seed region and limbic areas during self-serving attributions in patients compared to controls. Limitations Results of the PPI analysis are preliminary given the liberal statistical threshold. Conclusions The association of the behaviourally less frequent attributional pattern with activation in a fronto-temporal network suggests that non self-serving responses may produce a self-related response conflict in controls, while self-serving responses produce this conflict in patients. Moreover, attribution-modulated coupling between the dorsomedial PFC and limbic regions was weaker in patients than controls. This preliminary finding suggests that depression may be associated with disturbances in fronto-limbic coupling during attributional decisions. Our results implicate that treatment of major depression may benefit from approaches that facilitate reinterpretation of emotional events in a more positive, more self-serving way. PMID:22377511

Research on Attribute Reduction in Hoisting Motor State Recognition of Quayside Container Crane

NASA Astrophysics Data System (ADS)

Li, F.; Tang, G.; Hu, X.

2017-07-01

In view of too many attributes in hoisting motor state recognition of quayside container crane. Attribute reduction method based on discernibility matrix is introduced to attribute reduction of lifting motor state information table. A method of attribute reduction based on the combination of rough set and genetic algorithm is proposed to deal with the hoisting motor state decision table. Under the condition that the information system's decision-making ability is unchanged, the redundant attribute is deleted. Which reduces the complexity and computation of the recognition process of the hoisting motor. It is possible to realize the fast state recognition.

Selecting an Architecture for a Safety-Critical Distributed Computer System with Power, Weight and Cost Considerations

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2014-01-01

This report presents an example of the application of multi-criteria decision analysis to the selection of an architecture for a safety-critical distributed computer system. The design problem includes constraints on minimum system availability and integrity, and the decision is based on the optimal balance of power, weight and cost. The analysis process includes the generation of alternative architectures, evaluation of individual decision criteria, and the selection of an alternative based on overall value. In this example presented here, iterative application of the quantitative evaluation process made it possible to deliberately generate an alternative architecture that is superior to all others regardless of the relative importance of cost.

Allometric constraints to inversion of canopy structure from remote sensing

NASA Astrophysics Data System (ADS)

Wolf, A.; Berry, J. A.; Asner, G. P.

2008-12-01

Canopy radiative transfer models employ a large number of vegetation architectural and leaf biochemical attributes. Studies of leaf biochemistry show a wide array of chemical and spectral diversity that suggests that several leaf biochemical constituents can be independently retrieved from multi-spectral remotely sensed imagery. In contrast, attempts to exploit multi-angle imagery to retrieve canopy structure only succeed in finding two or three of the many unknown canopy arhitectural attributes. We examine a database of over 5000 destructive tree harvests from Eurasia to show that allometry - the covariation of plant form across a broad range of plant size and canopy density - restricts the architectural diversity of plant canopies into a single composite variable ranging from young canopies with many short trees with small crowns to older canopies with fewer trees and larger crowns. Moreover, these architectural attributes are closely linked to biomass via allometric constraints such as the "self-thinning law". We use the measured variance and covariance of plant canopy architecture in these stands to drive the radiative transfer model DISORD, which employs the Li-Strahler geometric optics model. This correlations introduced in the Monte Carlo study are used to determine which attributes of canopy architecture lead to important variation that can be observed by multi-angle or multi-spectral satellite observations, using the sun-view geometry characteristic of MODIS observations in different biomes located at different latitude bands. We conclude that although multi-angle/multi-spectral remote sensing is only sensitive to some of the many unknown canopy attributes that ecologists would wish to know, the strong allometric covariation between these attributes and others permits a large number of inferrences, such as forest biomass, that will be meaningful next-generation vegetation products useful for data assimilation.

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

PubMed Central

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355

A multi-criteria decision analysis perspective on the health economic evaluation of medical interventions.

PubMed

Postmus, Douwe; Tervonen, Tommi; van Valkenhoef, Gert; Hillege, Hans L; Buskens, Erik

2014-09-01

A standard practice in health economic evaluation is to monetize health effects by assuming a certain societal willingness-to-pay per unit of health gain. Although the resulting net monetary benefit (NMB) is easy to compute, the use of a single willingness-to-pay threshold assumes expressibility of the health effects on a single non-monetary scale. To relax this assumption, this article proves that the NMB framework is a special case of the more general stochastic multi-criteria acceptability analysis (SMAA) method. Specifically, as SMAA does not restrict the number of criteria to two and also does not require the marginal rates of substitution to be constant, there are problem instances for which the use of this more general method may result in a better understanding of the trade-offs underlying the reimbursement decision-making problem. This is illustrated by applying both methods in a case study related to infertility treatment.

Secure Data Access Control for Fog Computing Based on Multi-Authority Attribute-Based Signcryption with Computation Outsourcing and Attribute Revocation

PubMed Central

Xu, Qian; Tan, Chengxiang; Fan, Zhijie; Zhu, Wenye; Xiao, Ya; Cheng, Fujia

2018-01-01

Nowadays, fog computing provides computation, storage, and application services to end users in the Internet of Things. One of the major concerns in fog computing systems is how fine-grained access control can be imposed. As a logical combination of attribute-based encryption and attribute-based signature, Attribute-based Signcryption (ABSC) can provide confidentiality and anonymous authentication for sensitive data and is more efficient than traditional “encrypt-then-sign” or “sign-then-encrypt” strategy. Thus, ABSC is suitable for fine-grained access control in a semi-trusted cloud environment and is gaining more and more attention recently. However, in many existing ABSC systems, the computation cost required for the end users in signcryption and designcryption is linear with the complexity of signing and encryption access policy. Moreover, only a single authority that is responsible for attribute management and key generation exists in the previous proposed ABSC schemes, whereas in reality, mostly, different authorities monitor different attributes of the user. In this paper, we propose OMDAC-ABSC, a novel data access control scheme based on Ciphertext-Policy ABSC, to provide data confidentiality, fine-grained control, and anonymous authentication in a multi-authority fog computing system. The signcryption and designcryption overhead for the user is significantly reduced by outsourcing the undesirable computation operations to fog nodes. The proposed scheme is proven to be secure in the standard model and can provide attribute revocation and public verifiability. The security analysis, asymptotic complexity comparison, and implementation results indicate that our construction can balance the security goals with practical efficiency in computation. PMID:29772840

DARHT Multi-intelligence Seismic and Acoustic Data Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, Garrison Nicole; Van Buren, Kendra Lu; Hemez, Francois M.

The purpose of this report is to document the analysis of seismic and acoustic data collected at the Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility at Los Alamos National Laboratory for robust, multi-intelligence decision making. The data utilized herein is obtained from two tri-axial seismic sensors and three acoustic sensors, resulting in a total of nine data channels. The goal of this analysis is to develop a generalized, automated framework to determine internal operations at DARHT using informative features extracted from measurements collected external of the facility. Our framework involves four components: (1) feature extraction, (2) data fusion, (3) classification, andmore » finally (4) robustness analysis. Two approaches are taken for extracting features from the data. The first of these, generic feature extraction, involves extraction of statistical features from the nine data channels. The second approach, event detection, identifies specific events relevant to traffic entering and leaving the facility as well as explosive activities at DARHT and nearby explosive testing sites. Event detection is completed using a two stage method, first utilizing signatures in the frequency domain to identify outliers and second extracting short duration events of interest among these outliers by evaluating residuals of an autoregressive exogenous time series model. Features extracted from each data set are then fused to perform analysis with a multi-intelligence paradigm, where information from multiple data sets are combined to generate more information than available through analysis of each independently. The fused feature set is used to train a statistical classifier and predict the state of operations to inform a decision maker. We demonstrate this classification using both generic statistical features and event detection and provide a comparison of the two methods. Finally, the concept of decision robustness is presented through a preliminary analysis where uncertainty is added to the system through noise in the measurements.« less

Clinical factors and the decision to transfuse chronic dialysis patients.

PubMed

Whitman, Cynthia B; Shreay, Sanatan; Gitlin, Matthew; van Oijen, Martijn G H; Spiegel, Brennan M R

2013-11-01

Red blood cell transfusion was previously the principle therapy for anemia in CKD but became less prevalent after the introduction of erythropoiesis-stimulating agents. This study used adaptive choice-based conjoint analysis to identify preferences and predictors of transfusion decision-making in CKD. A computerized adaptive choice-based conjoint survey was administered between June and August of 2012 to nephrologists, internists, and hospitalists listed in the American Medical Association Masterfile. The survey quantified the relative importance of 10 patient attributes, including hemoglobin levels, age, occult blood in stool, severity of illness, eligibility for transplant, iron indices, erythropoiesis-stimulating agents, cardiovascular disease, and functional status. Triggers of transfusions in common dialysis scenarios were studied, and based on adaptive choice-based conjoint-derived preferences, relative importance by performing multivariable regression to identify predictors of transfusion preferences was assessed. A total of 350 providers completed the survey (n=305 nephrologists; mean age=46 years; 21% women). Of 10 attributes assessed, absolute hemoglobin level was the most important driver of transfusions, accounting for 29% of decision-making, followed by functional status (16%) and cardiovascular comorbidities (12%); 92% of providers transfused when hemoglobin was 7.5 g/dl, independent of other factors. In multivariable regression, Veterans Administration providers were more likely to transfuse at 8.0 g/dl (odds ratio, 5.9; 95% confidence interval, 1.9 to 18.4). Although transplant eligibility explained only 5% of decision-making, nephrologists were five times more likely to value it as important compared with non-nephrologists (odds ratio, 5.2; 95% confidence interval, 2.4 to 11.1). Adaptive choice-based conjoint analysis was useful in predicting influences on transfusion decisions. Hemoglobin level, functional status, and cardiovascular comorbidities most strongly influenced transfusion decision-making, but preference variations were observed among subgroups.

A novel design process for selection of attributes for inclusion in discrete choice experiments: case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke.

PubMed

De Brún, Aoife; Flynn, Darren; Ternent, Laura; Price, Christopher I; Rodgers, Helen; Ford, Gary A; Rudd, Matthew; Lancsar, Emily; Simpson, Stephen; Teah, John; Thomson, Richard G

2018-06-22

A discrete choice experiment (DCE) is a method used to elicit participants' preferences and the relative importance of different attributes and levels within a decision-making process. DCEs have become popular in healthcare; however, approaches to identify the attributes/levels influencing a decision of interest and to selection methods for their inclusion in a DCE are under-reported. Our objectives were: to explore the development process used to select/present attributes/levels from the identified range that may be influential; to describe a systematic and rigorous development process for design of a DCE in the context of thrombolytic therapy for acute stroke; and, to discuss the advantages of our five-stage approach to enhance current guidance for developing DCEs. A five-stage DCE development process was undertaken. Methods employed included literature review, qualitative analysis of interview and ethnographic data, expert panel discussions, a quantitative structured prioritisation (ranking) exercise and pilot testing of the DCE using a 'think aloud' approach. The five-stage process reported helped to reduce the list of 22 initial patient-related factors to a final set of nine variable factors and six fixed factors for inclusion in a testable DCE using a vignette model of presentation. In order for the data and conclusions generated by DCEs to be deemed valid, it is crucial that the methods of design and development are documented and reported. This paper has detailed a rigorous and systematic approach to DCE development which may be useful to researchers seeking to establish methods for reducing and prioritising attributes for inclusion in future DCEs.

Analysis of student attitudes towards e-learning using Fishbein Multiattribute approach

NASA Astrophysics Data System (ADS)

Jasuli

2018-01-01

This research aimed to know students’ attitudes toward e-learning and to determine what attributes were considered to be dominant by students toward the use of e-learning. The research population was all postgraduate students in the 2016 academic year at Universitas Negeri Surabaya. The sampling technique is using nonprobability sampling and purposive sampling with the sample totaled 100 respondents. The research instrument is using questionnaire with semantic differential scale. The models used to analyze is multi-attribute Fishbein model. The findings indicated that student attitudes toward e-learning are positive and easy accessibility which is considered as the most important attribute by students toward the use of e-learning.

Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty.

PubMed

Chen, Xudong; Xu, Zhongwen; Yao, Liming; Ma, Ning

2018-03-05

This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

Systematic assessment of benefits and risks: study protocol for a multi-criteria decision analysis using the Analytic Hierarchy Process for comparative effectiveness research

PubMed Central

Singh, Sonal

2013-01-01

Background: Regulatory decision-making involves assessment of risks and benefits of medications at the time of approval or when relevant safety concerns arise with a medication. The Analytic Hierarchy Process (AHP) facilitates decision-making in complex situations involving tradeoffs by considering risks and benefits of alternatives. The AHP allows a more structured method of synthesizing and understanding evidence in the context of importance assigned to outcomes. Our objective is to evaluate the use of an AHP in a simulated committee setting selecting oral medications for type 2 diabetes.  Methods: This study protocol describes the AHP in five sequential steps using a small group of diabetes experts representing various clinical disciplines. The first step will involve defining the goal of the decision and developing the AHP model. In the next step, we will collect information about how well alternatives are expected to fulfill the decision criteria. In the third step, we will compare the ability of the alternatives to fulfill the criteria and judge the importance of eight criteria relative to the decision goal of the optimal medication choice for type 2 diabetes. We will use pairwise comparisons to sequentially compare the pairs of alternative options regarding their ability to fulfill the criteria. In the fourth step, the scales created in the third step will be combined to create a summary score indicating how well the alternatives met the decision goal. The resulting scores will be expressed as percentages and will indicate the alternative medications' relative abilities to fulfill the decision goal. The fifth step will consist of sensitivity analyses to explore the effects of changing the estimates. We will also conduct a cognitive interview and process evaluation.  Discussion: Multi-criteria decision analysis using the AHP will aid, support and enhance the ability of decision makers to make evidence-based informed decisions consistent with their values and preferences. PMID:24555077

Systematic assessment of benefits and risks: study protocol for a multi-criteria decision analysis using the Analytic Hierarchy Process for comparative effectiveness research.

PubMed

Maruthur, Nisa M; Joy, Susan; Dolan, James; Segal, Jodi B; Shihab, Hasan M; Singh, Sonal

2013-01-01

Regulatory decision-making involves assessment of risks and benefits of medications at the time of approval or when relevant safety concerns arise with a medication. The Analytic Hierarchy Process (AHP) facilitates decision-making in complex situations involving tradeoffs by considering risks and benefits of alternatives. The AHP allows a more structured method of synthesizing and understanding evidence in the context of importance assigned to outcomes. Our objective is to evaluate the use of an AHP in a simulated committee setting selecting oral medications for type 2 diabetes.  This study protocol describes the AHP in five sequential steps using a small group of diabetes experts representing various clinical disciplines. The first step will involve defining the goal of the decision and developing the AHP model. In the next step, we will collect information about how well alternatives are expected to fulfill the decision criteria. In the third step, we will compare the ability of the alternatives to fulfill the criteria and judge the importance of eight criteria relative to the decision goal of the optimal medication choice for type 2 diabetes. We will use pairwise comparisons to sequentially compare the pairs of alternative options regarding their ability to fulfill the criteria. In the fourth step, the scales created in the third step will be combined to create a summary score indicating how well the alternatives met the decision goal. The resulting scores will be expressed as percentages and will indicate the alternative medications' relative abilities to fulfill the decision goal. The fifth step will consist of sensitivity analyses to explore the effects of changing the estimates. We will also conduct a cognitive interview and process evaluation.  Multi-criteria decision analysis using the AHP will aid, support and enhance the ability of decision makers to make evidence-based informed decisions consistent with their values and preferences.

Multi-criteria decision analysis as an innovative approach to managing zoonoses: results from a study on Lyme disease in Canada

PubMed Central

2013-01-01

Background Zoonoses are a growing international threat interacting at the human-animal-environment interface and call for transdisciplinary and multi-sectoral approaches in order to achieve effective disease management. The recent emergence of Lyme disease in Quebec, Canada is a good example of a complex health issue for which the public health sector must find protective interventions. Traditional preventive and control interventions can have important environmental, social and economic impacts and as a result, decision-making requires a systems approach capable of integrating these multiple aspects of interventions. This paper presents the results from a study of a multi-criteria decision analysis (MCDA) approach for the management of Lyme disease in Quebec, Canada. MCDA methods allow a comparison of interventions or alternatives based on multiple criteria. Methods MCDA models were developed to assess various prevention and control decision criteria pertinent to a comprehensive management of Lyme disease: a first model was developed for surveillance interventions and a second was developed for control interventions. Multi-criteria analyses were conducted under two epidemiological scenarios: a disease emergence scenario and an epidemic scenario. Results In general, we observed a good level of agreement between stakeholders. For the surveillance model, the three preferred interventions were: active surveillance of vectors by flagging or dragging, active surveillance of vectors by trapping of small rodents and passive surveillance of vectors of human origin. For the control interventions model, basic preventive communications, human vaccination and small scale landscaping were the three preferred interventions. Scenarios were found to only have a small effect on the group ranking of interventions in the control model. Conclusions MCDA was used to structure key decision criteria and capture the complexity of Lyme disease management. This facilitated the identification of gaps in the scientific literature and enabled a clear identification of complementary interventions that could be used to improve the relevance and acceptability of proposed prevention and control strategy. Overall, MCDA presents itself as an interesting systematic approach for public health planning and zoonoses management with a “One Health” perspective. PMID:24079303

Multi-criteria decision analysis as an innovative approach to managing zoonoses: results from a study on Lyme disease in Canada.

PubMed

Aenishaenslin, Cécile; Hongoh, Valérie; Cissé, Hassane Djibrilla; Hoen, Anne Gatewood; Samoura, Karim; Michel, Pascal; Waaub, Jean-Philippe; Bélanger, Denise

2013-09-30

Zoonoses are a growing international threat interacting at the human-animal-environment interface and call for transdisciplinary and multi-sectoral approaches in order to achieve effective disease management. The recent emergence of Lyme disease in Quebec, Canada is a good example of a complex health issue for which the public health sector must find protective interventions. Traditional preventive and control interventions can have important environmental, social and economic impacts and as a result, decision-making requires a systems approach capable of integrating these multiple aspects of interventions. This paper presents the results from a study of a multi-criteria decision analysis (MCDA) approach for the management of Lyme disease in Quebec, Canada. MCDA methods allow a comparison of interventions or alternatives based on multiple criteria. MCDA models were developed to assess various prevention and control decision criteria pertinent to a comprehensive management of Lyme disease: a first model was developed for surveillance interventions and a second was developed for control interventions. Multi-criteria analyses were conducted under two epidemiological scenarios: a disease emergence scenario and an epidemic scenario. In general, we observed a good level of agreement between stakeholders. For the surveillance model, the three preferred interventions were: active surveillance of vectors by flagging or dragging, active surveillance of vectors by trapping of small rodents and passive surveillance of vectors of human origin. For the control interventions model, basic preventive communications, human vaccination and small scale landscaping were the three preferred interventions. Scenarios were found to only have a small effect on the group ranking of interventions in the control model. MCDA was used to structure key decision criteria and capture the complexity of Lyme disease management. This facilitated the identification of gaps in the scientific literature and enabled a clear identification of complementary interventions that could be used to improve the relevance and acceptability of proposed prevention and control strategy. Overall, MCDA presents itself as an interesting systematic approach for public health planning and zoonoses management with a "One Health" perspective.

Regulating Emotions during Difficult Multiattribute Decision Making: The Role of Pre-Decisional Coherence Shifting.

PubMed

Carpenter, Stephanie M; Yates, J Frank; Preston, Stephanie D; Chen, Lydia

2016-01-01

Almost all real-life decisions entail attribute conflict; every serious choice alternative is better than its competitors on some attribute dimensions but worse on others. In pre-decisional "coherence shifting," the decision maker gradually softens that conflict psychologically to the point where one alternative is seen as dominant over its competitors, or nearly so. Specifically, weaknesses of the eventually chosen alternative come to be perceived as less severe and less important while its strengths seem more desirable and significant. The research described here demonstrates that difficult multiattribute decision problems are aversive and that pre-decisional coherence shifting aids individuals in regulating that emotional discomfort. Across three studies, attribute conflict was confirmed to be aversive (Study 1), and skin conductance responses and ratings of decision difficulty both decreased in participants who coherence shifted (Study 2). Coherence shifting was also diminished among decision makers who were depleted of regulatory resources, known to be required for common emotion regulation mechanisms. Further, coherence shifting was shown to be relatively common among people who reported strong suppression tendencies in everyday emotion regulation (Study 3). Overall, the data suggest that, at least in part, coherence shifting serves as a tool that helps decision makers manage the pre-decisional discomfort generated by attribute conflict. Theoretical and practical implications are discussed.

Regulating Emotions during Difficult Multiattribute Decision Making: The Role of Pre-Decisional Coherence Shifting

PubMed Central

Carpenter, Stephanie M.; Yates, J. Frank; Preston, Stephanie D.; Chen, Lydia

2016-01-01

Almost all real-life decisions entail attribute conflict; every serious choice alternative is better than its competitors on some attribute dimensions but worse on others. In pre-decisional “coherence shifting,” the decision maker gradually softens that conflict psychologically to the point where one alternative is seen as dominant over its competitors, or nearly so. Specifically, weaknesses of the eventually chosen alternative come to be perceived as less severe and less important while its strengths seem more desirable and significant. The research described here demonstrates that difficult multiattribute decision problems are aversive and that pre-decisional coherence shifting aids individuals in regulating that emotional discomfort. Across three studies, attribute conflict was confirmed to be aversive (Study 1), and skin conductance responses and ratings of decision difficulty both decreased in participants who coherence shifted (Study 2). Coherence shifting was also diminished among decision makers who were depleted of regulatory resources, known to be required for common emotion regulation mechanisms. Further, coherence shifting was shown to be relatively common among people who reported strong suppression tendencies in everyday emotion regulation (Study 3). Overall, the data suggest that, at least in part, coherence shifting serves as a tool that helps decision makers manage the pre-decisional discomfort generated by attribute conflict. Theoretical and practical implications are discussed. PMID:26986752

Information theoretic partitioning and confidence based weight assignment for multi-classifier decision level fusion in hyperspectral target recognition applications

NASA Astrophysics Data System (ADS)

Prasad, S.; Bruce, L. M.

2007-04-01

There is a growing interest in using multiple sources for automatic target recognition (ATR) applications. One approach is to take multiple, independent observations of a phenomenon and perform a feature level or a decision level fusion for ATR. This paper proposes a method to utilize these types of multi-source fusion techniques to exploit hyperspectral data when only a small number of training pixels are available. Conventional hyperspectral image based ATR techniques project the high dimensional reflectance signature onto a lower dimensional subspace using techniques such as Principal Components Analysis (PCA), Fisher's linear discriminant analysis (LDA), subspace LDA and stepwise LDA. While some of these techniques attempt to solve the curse of dimensionality, or small sample size problem, these are not necessarily optimal projections. In this paper, we present a divide and conquer approach to address the small sample size problem. The hyperspectral space is partitioned into contiguous subspaces such that the discriminative information within each subspace is maximized, and the statistical dependence between subspaces is minimized. We then treat each subspace as a separate source in a multi-source multi-classifier setup and test various decision fusion schemes to determine their efficacy. Unlike previous approaches which use correlation between variables for band grouping, we study the efficacy of higher order statistical information (using average mutual information) for a bottom up band grouping. We also propose a confidence measure based decision fusion technique, where the weights associated with various classifiers are based on their confidence in recognizing the training data. To this end, training accuracies of all classifiers are used for weight assignment in the fusion process of test pixels. The proposed methods are tested using hyperspectral data with known ground truth, such that the efficacy can be quantitatively measured in terms of target recognition accuracies.

ELICIT: An alternative imprecise weight elicitation technique for use in multi-criteria decision analysis for healthcare

PubMed Central

Diaby, Vakaramoko; Sanogo, Vassiki; Moussa, Kouame Richard

2015-01-01

Objective In this paper, the readers are introduced to ELICIT, an imprecise weight elicitation technique for multicriteria decision analysis for healthcare. Methods The application of ELICIT consists of two steps: the rank ordering of evaluation criteria based on decision-makers’ (DMs) preferences using the principal component analysis; and the estimation of criteria weights and their descriptive statistics using the variable interdependent analysis and the Monte Carlo method. The application of ELICIT is illustrated with a hypothetical case study involving the elicitation of weights for five criteria used to select the best device for eye surgery. Results The criteria were ranked from 1–5, based on a strict preference relationship established by the DMs. For each criterion, the deterministic weight was estimated as well as the standard deviation and 95% credibility interval. Conclusions ELICIT is appropriate in situations where only ordinal DMs’ preferences are available to elicit decision criteria weights. PMID:26361235

A visual analysis of multi-attribute data using pixel matrix displays

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel; Schreck, Tobias

2007-01-01

Charts and tables are commonly used to visually analyze data. These graphics are simple and easy to understand, but charts show only highly aggregated data and present only a limited number of data values while tables often show too many data values. As a consequence, these graphics may either lose or obscure important information, so different techniques are required to monitor complex datasets. Users need more powerful visualization techniques to digest and compare detailed multi-attribute data to analyze the health of their business. This paper proposes an innovative solution based on the use of pixel-matrix displays to represent transaction-level information. With pixelmatrices, users can visualize areas of importance at a glance, a capability not provided by common charting techniques. We present our solutions to use colored pixel-matrices in (1) charts for visualizing data patterns and discovering exceptions, (2) tables for visualizing correlations and finding root-causes, and (3) time series for visualizing the evolution of long-running transactions. The solutions have been applied with success to product sales, Internet network performance analysis, and service contract applications demonstrating the benefits of our method over conventional graphics. The method is especially useful when detailed information is a key part of the analysis.

Shared decision-making at the end of life: A focus group study exploring the perceptions and experiences of multi-disciplinary healthcare professionals working in the home setting.

PubMed

Brogan, Paula; Hasson, Felicity; McIlfatrick, Sonja

2018-01-01

Globally recommended in healthcare policy, Shared Decision-Making is also central to international policy promoting community palliative care. Yet realities of implementation by multi-disciplinary healthcare professionals who provide end-of-life care in the home are unclear. To explore multi-disciplinary healthcare professionals' perceptions and experiences of Shared Decision-Making at end of life in the home. Qualitative design using focus groups, transcribed verbatim and analysed thematically. A total of 43 participants, from multi-disciplinary community-based services in one region of the United Kingdom, were recruited. While the rhetoric of Shared Decision-Making was recognised, its implementation was impacted by several interconnecting factors, including (1) conceptual confusion regarding Shared Decision-Making, (2) uncertainty in the process and (3) organisational factors which impeded Shared Decision-Making. Multiple interacting factors influence implementation of Shared Decision-Making by professionals working in complex community settings at the end of life. Moving from rhetoric to reality requires future work exploring the realities of Shared Decision-Making practice at individual, process and systems levels.

Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model

PubMed Central

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals. PMID:27877103

Multi-resolution information mining and a computer vision approach to pavement condition distress analysis.

DOT National Transportation Integrated Search

2014-07-01

Pavement Condition surveys are carried out periodically to gather information on pavement distresses that will guide decision-making for maintenance and preservation. Traditional methods involve manual pavement inspections which are time-consuming : ...

Some Muirhead Mean Operators for Intuitionistic Fuzzy Numbers and Their Applications to Group Decision Making.

PubMed

Liu, Peide; Li, Dengfeng

2017-01-01

Muirhead mean (MM) is a well-known aggregation operator which can consider interrelationships among any number of arguments assigned by a variable vector. Besides, it is a universal operator since it can contain other general operators by assigning some special parameter values. However, the MM can only process the crisp numbers. Inspired by the MM' advantages, the aim of this paper is to extend MM to process the intuitionistic fuzzy numbers (IFNs) and then to solve the multi-attribute group decision making (MAGDM) problems. Firstly, we develop some intuitionistic fuzzy Muirhead mean (IFMM) operators by extending MM to intuitionistic fuzzy information. Then, we prove some properties and discuss some special cases with respect to the parameter vector. Moreover, we present two new methods to deal with MAGDM problems with the intuitionistic fuzzy information based on the proposed MM operators. Finally, we verify the validity and reliability of our methods by using an application example, and analyze the advantages of our methods by comparing with other existing methods.