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Antsiferova, A. A., V. A. Demin, Vladimir F. Demin, and V. Yu Soloviev. "CONCEPT OF TECHNOGENIC RISK MANAGEMENT." Hygiene and sanitation 96, no. 8 (March 27, 2019): 780–85. http://dx.doi.org/10.18821/0016-9900-2017-96-8-780-785.
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There are proposed conceptual positions and levels of decision-making on provision of the safety, social and medical protection of the human on the base of the assessment, analysis and risk management in different areas of human activity in normal and emergency conditions under the exposure to man-made and some natural hazard sources. At the base of developed applications there is a unified approach to the development and use of modern risk assessment methodology: the elaboration of a common method of the risk assessment and, basing on it, specific and simplified methods for concrete sources of hazard impact. This structure of methodological bases of risk assessment, in its full development makes it more transparent and comparable as well specific methods, as the support of decision-making on protective and other measures from different sources of danger. There were formulated proposals for universal safety standards (SSs) and other levels of decision-making on safety, social and medical protection of the population and staff of hazardous industries, including acceptable levels of risk. For the establishment of SSs and other decision-making levels, a special risk index is used: the relative damage (ratio of years of life lost to a year of stay-at-risk). This index is most appropriate for evaluation, comparison and management of risk, especially in conditions of two or more acting danger sources. On the base of universal SSs there are developed branch main SSs for certain isolated sources of danger. They are expressed in those indices (specific risk indices or impact indices in their different definitions), which by now are widely used in the practice or will be chosen for practical use in the future. In the ensuring human safety in normal conditions, the main use of the risk assessment is the development and support of SSs and other levels of decision-making. In emergencies the specific risk assessment besides to the establishment the decision-making levels is essentially needed to make justified optimal decisions on the measures of social and medical protection of the population and professionals.
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Sim, Hock Kheng, and Zhi Xin Wong. "Fuzzy Decision Tree Approach for Optimal Supplier Base." Applied Mechanics and Materials 315 (April 2013): 283–87. http://dx.doi.org/10.4028/www.scientific.net/amm.315.283.
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Minimizing supplier base allows better supplier relationship management, but any supplier failure will interrupt the supplies chain. Earth quake in Fukushima, Japan and flood in Bangkok, Thailand, caused supply chain breakdown and affect the global production. Decision tree method is recommended to determine optimal number of supplier in supplier base with the risk of supplier failure. This paper presented an approach to integrate fuzzy logic in decision tree approach by rating the supplier risk in linguistic terms for imperfect environment. Numerical example and sensitivity are carried out and presented, and optimal supplier base was identified.
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Harris, Grant T., and Marnie E. Rice. "Characterizing the Value of Actuarial Violence Risk Assessments." Criminal Justice and Behavior 34, no. 12 (December 2007): 1638–58. http://dx.doi.org/10.1177/0093854807307029.
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Using the Violence Risk Appraisal Guide, relative operating characteristic (ROC) statistics are exemplified. Criticisms of actuarials and ROCs as measures of accuracy are discussed—ROC statistics are independent of base rates, but optimal decisions are not. Using sex offenders, the importance of accurate base rate information in the relevant population is examined. Although Bayes affords estimates of posterior probabilities for any base rate, Bayesian corrections can be too extreme in practice. This article illustrates that undesirable posterior probabilities are improved by superior selection ratios and refutes the criticism that “confidence intervals around individual scores” are so large as to make actuarial assessment meaningless. Personal values play a role in forensic decision making, and actuarial methods sharpen the focus on such values.
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Thompson, Matthew P., Yu Wei, David E. Calkin, Christopher D. O’Connor, Christopher J. Dunn, Nathaniel M. Anderson, and John S. Hogland. "Risk Management and Analytics in Wildfire Response." Current Forestry Reports 5, no. 4 (November 20, 2019): 226–39. http://dx.doi.org/10.1007/s40725-019-00101-7.
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Abstract Purpose of Review The objectives of this paper are to briefly review basic risk management and analytics concepts, describe their nexus in relation to wildfire response, demonstrate real-world application of analytics to support response decisions and organizational learning, and outline an analytics strategy for the future. Recent Findings Analytics can improve decision-making and organizational performance across a variety of areas from sports to business to real-time emergency response. A lack of robust descriptive analytics on wildfire incident response effectiveness is a bottleneck for developing operationally relevant and empirically credible predictive and prescriptive analytics to inform and guide strategic response decisions. Capitalizing on technology such as automated resource tracking and machine learning algorithms can help bridge gaps between monitoring, learning, and data-driven decision-making. Summary By investing in better collection, documentation, archiving, and analysis of operational data on response effectiveness, fire management organizations can promote systematic learning and provide a better evidence base to support response decisions. We describe an analytics management framework that can provide structure to help deploy analytics within organizations, and provide real-world examples of advanced fire analytics applied in the USA. To fully capitalize on the potential of analytics, organizations may need to catalyze cultural shifts that cultivate stronger appreciation for data-driven decision processes, and develop informed skeptics that effectively balance both judgment and analysis in decision-making.
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Nelson, Robert C. "Drug Safety, Pharmacoepidemiology, and Regulatory Decision Making." Drug Intelligence & Clinical Pharmacy 22, no. 4 (April 1988): 336–44. http://dx.doi.org/10.1177/106002808802200419.
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The safety or risk assessment of a pharmacotherapeutic agent begins early in its development and continues throughout its use cycle. The practice of pharmacoepidemiology is the art of using the sciences and the tools of science to generate information about pharmaceutical outcomes, including associated risks, in the postmarketing environment. A pharmacoepidemiologist must be capable of functioning with a matrix constructed of three components: a knowledge base, a conceptual framework, and an interpretive framework. From this perspective one can establish surveillance schemes, or understand a posed research question, select strategies, apply methodologies, and interpret the results of purposeful investigations. When conveyed to the risk manager, appropriately interpreted results of a properly conducted risk assessment can be used in regulatory decision making. Seven case studies are presented as examples of this approach.
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Brady, Michael E., and Howard B. Lee. "Is There an Allais Paradox? A Note on its Resolution." Psychological Reports 64, no. 3_suppl (June 1989): 1223–30. http://dx.doi.org/10.2466/pr0.1989.64.3c.1223.
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If a decision maker uses J. M. Keynes' “conventional coefficient of risk and weight” in making decisions under conditions of risk and/or uncertainty, then a consistent pattern of ranked outcome results is not paradoxical as proposed by Allais. Similarly, the paradoxical aspects of the “reflection effect” in Kahneman and Tversky's Prospect Theory analysis of the Allais' paradox, also vanishes. The Allais Paradox can only exist when probabilities are used in a decision-making process without a measure of confidence. By incorporating an information base for calculated probabilities the Allais Paradox results are rendered nonparadoxical.
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Rajagopal, Sandhya, and Aengus Kelly. "Shared Decision Making in Endodontics." Primary Dental Journal 9, no. 4 (November 23, 2020): 31–36. http://dx.doi.org/10.1177/2050168420963303.
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Engaging patients in shared decision making (SDM) is a professional requirement since the Montgomery ruling in 2015. Endodontic treatments present a specific challenge to achieving SDM, both for the clinician and the patient. The treatments are often perceived as more challenging to complete by the clinician, and the assessment of risk and likely outcome requires a deep understanding of the (limited) evidence base. For the patient, decisions can be required at a time of acute symptoms and prolonged treatments. There are health literacy demands in comparison to some less complex dental treatments. Treatment decisions may be based more on inherent biases and prior experiences than objective probabilities. This article discusses options and supports effective shared decision making in endodontic treatment.
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Johansson, Cristina, Johan Ölvander, and Micael Derelöv. "Multi-objective optimization for safety and reliability trade-off: Optimization and results processing." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 232, no. 6 (February 26, 2018): 661–76. http://dx.doi.org/10.1177/1748006x18757075.
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In early design phases, it is vital to be able to screen the design space for a set of promising design alternatives for further study. This article presents a method able to balance several objectives of different mathematical natures, with high impact on the design choices. The method (MOSART) handles multi-objective optimization for safety and reliability trade-offs. The article focuses on optimization problem approach and processing of results as a base for decision-making. The output of the optimization step is the selection of specific system elements obtaining the best balance between the targets. However, what is a good base for decision can easily transform into too much information and overloading of the decision-maker. To solve this potential issue, from a set of Pareto optimal solutions, a smaller sub-set of selected solutions are visualized and filtered out using preference levels of the objectives, yielding a solid base for decision-making and valuable information on potential solutions. Trends were observed regarding each system element and discussed while processing the results of the analysis, supporting the decision of one final best solution.
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Travers, R., and A. Kumar. "Structured clinical decision making: Is it different ?" European Psychiatry 26, S2 (March 2011): 788. http://dx.doi.org/10.1016/s0924-9338(11)72493-2.
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IntroductionThe Psychiatrists are called to assess the level of risk in violent and sex offenders’ population. There are differing perceptions about formalising the severity and management of risk. The proponents of actuarial decision making propose that it is scientific and evidence based approach. The advocates of professional judgment however think that actuarial tools usually miss out on the interplay of compounding factors and can under or over estimate the level of risk.ObjectivesTo review consecutive patient assessments and qualitatively compare it with HCR-20 and RSVP tools for violent and sex offending patients.AimsTo report the difference in outcome in the domains of overall severity of risk, risk formulation and clinical decision making for management of the risk in these patient groups.MethodsWe aim to compare twenty consecutive patients where professional judgment of the clinician determined the severity of the risk, risk formulation and management. We then aim to use the information available to check for any differences in these areas when HCR-20 and RSVP are employed.ResultsThe comparison and benefits of professional judgment and actuarial decision making are reported.ConclusionsThe professionals (providers) are being increasingly compelled by commissioners(purchasers) to evidence base their clinical decision making. The professional judgments are more likely to be challenged in the courts. People are easily impressed by decisions which are evidence based though they may have limited understanding of research environment and population studied.
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Acula, Donata D. "Classification of Disaster Risks in the Philippines using Adaptive Boosting Algorithm with Decision Trees and Support Vector Machine as Based Estimators." Journal of Modeling and Simulation of Materials 4, no. 1 (June 3, 2021): 7–18. http://dx.doi.org/10.21467/jmsm.4.1.7-18.
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This paper employed the intelligent approach based on machine learning categorized as base and ensemble methods in classifying the disaster risk in the Philippines. It focused on the Decision Trees, Support Vector Machine, Adaptive Boosting Algorithm with Decision Trees, and Support Vector Machine as base estimators. The research used the Exponential Regression for missing value imputation and converted the number of casualties, damaged houses, and properties into five (5) risk levels using Quantile Method. The 10-fold cross-validation was used to validate the proposed algorithms. The experiment shows that Decision Trees and Adaptive Decision Trees are the most suitable models for the disaster data with the score of more than 90%, more than 75%, more than 75% in all the classification metrics (accuracy, precision, recall f1-score) when applied to classification risk levels of casualties, damaged houses and damaged properties respectively.
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Wang, Neng. "The Study on Partners Relationship for Virtual Enterprises Risk Management Based on Distributed Decision." Key Engineering Materials 439-440 (June 2010): 1024–29. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.1024.
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To reduce risks of Virtual Enterprise （VE）, a novel Distributed Decision Making （DDM） model for VE risk management was presented. This model had two levels, namely, the top-model and the base-model, which described the decision processes of the owner and the partners, respectively. The owner allocated funds to each member of the VE, the partners then selected their own optimal risk control actions to reduce their risks with the constraint given by the allocated budget. When number of members in VE, the number of risk factors and the number of actions increased, the size of the search space would be very huge, the brief solutions of the models are also discussed.
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Jones, Felipe J. S., Paula R. Sanches, Jason R. Smith, Sahar F. Zafar, Sonia Hernandez-Diaz, Deborah Blacker, John Hsu, Lee H. Schwamm, Michael B. Westover, and Lidia M. V. R. Moura. "Anticonvulsant Primary and Secondary Prophylaxis for Acute Ischemic Stroke Patients: A Decision Analysis." Stroke 52, no. 9 (September 2021): 2782–91. http://dx.doi.org/10.1161/strokeaha.120.033299.
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Background and Purpose: We examined the impact of 3 anticonvulsant prophylaxis strategies on quality-adjusted life-years (QALYs) among patients with an incident acute ischemic stroke. Methods: We created a decision tree to evaluate 3 strategies: (1) long-term primary prophylaxis; (2) short-term secondary prophylaxis after an early seizure with lifetime prophylaxis if persistent or late seizures (LSs) developed; and (3) long-term secondary prophylaxis if either early, late, or persistent seizures developed. The outcome was quality-adjusted life expectancy (QALY). We created 4 base cases to simulate common clinical scenarios: (1) female patient aged 40 years with a 2% or 11% lifetime risk of an LS and a 33% lifetime risk of an adverse drug reaction (ADR); (2) male patient aged 65 years with a 6% or 29% LS risk and 60% ADR risk; (3) male patient aged 50 years with an 18% or 65% LS risk and 33% ADR risk; and (4) female patient aged 80 years with a 29% or 83% LS risk and 80% ADR risk. In sensitivity analyses, we altered the parameters and assumptions. Results: Across all 4 base cases, primary prophylaxis yielded the fewest QALYs when compared with secondary prophylaxis. For example, under scenario 1, strategies 2 and 3 resulted in 7.17 QALYs each, but strategy 1 yielded only 6.91 QALYs. Under scenario 4, strategies 2 and 3 yielded 2.85 QALYs compared with 1.40 QALYs for strategy 1. Under scenarios in which patients had higher ADR risks, strategy 2 led to the most QALYs. Conclusions: Short-term therapy with continued anticonvulsant prophylaxis only after postischemic stroke seizures arise dominates lifetime primary prophylaxis in all scenarios examined. Our findings reinforce the necessity of close follow-up and discontinuation of anticonvulsant seizure prophylaxis started during acute ischemic stroke hospitalization.
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Howarth, Candice, Sian Morse-Jones, Andrew Kythreotis, Katya Brooks, and Matt Lane. "Informing UK governance of resilience to climate risks: improving the local evidence-base." Climatic Change 163, no. 1 (August 10, 2020): 499–520. http://dx.doi.org/10.1007/s10584-020-02821-3.
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AbstractInternational assessments of evidence on climate change (e.g. Intergovernmental Panel on Climate Change, IPCC) or national climate change risk assessments (e.g. UK Climate Change Risk Assessment, CCRA) do not offer a sufficiently granular perspective on climate impacts to adequately inform governance of resilience to climate risks at the local level. Using an analysis of UK decision-makers managing and responding to heatwaves and flood risks, this paper argues how more robust local evidence is needed to inform decision-making regarding adaptation options for enhancing local resilience. We identify evidence gaps and issues relating to local climate change impacts, including sources and quality of evidence used, adequacy and accessibility of evidence available, ill-communicated evidence and conflicting or misused evidence. A lack of appreciation regarding how scientific evidence and personal judgement can mutually enhance the quality of decision-making underpins all of these gaps. Additionally, we find that the majority of evidence currently used is reductively based upon socio-economic and physical characteristics of climate risks. We argue that a step change is needed in local climate resilience that moves beyond current physical and socio-economic risk characterisation to a more inclusive co-constitution of social and politically defined climate risks at the local scale that are better aligned with the local impacts felt and needs of stakeholders.
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Gallego Arrubla, Julián A., Lewis Ntaimo, and Curt Stripling. "Wildfire initial response planning using probabilistically constrained stochastic integer programming." International Journal of Wildland Fire 23, no. 6 (2014): 825. http://dx.doi.org/10.1071/wf13204.
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This paper presents a new methodology for making strategic dozer deployment plans for wildfire initial response planning for a given fire season. This approach combines a fire behaviour simulation, a wildfire risk model and a probabilistically constrained stochastic integer programming model, and takes into account the level of risk the decision-maker is willing to take when making deployment and dispatching plans. The new methodology was applied to Texas District 12, a Texas A&M Forest Service fire planning unit located in East Texas. This study demonstrates the effect of the decision-maker’s risk attitude level on deployment decisions in terms of the dozers positioned at each operations base, fires contained and their associated wildfire risk, and total containment cost. The results show that the total number of fires contained and their associated total expected cost increase when the tolerance towards risk decreases. Thus, more dozers are deployed to operations bases in areas with high wildfire risk and a high need for initial response.
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McNeill, Ilona M., Patrick D. Dunlop, Timothy C. Skinner, and David L. Morrison. "Predicting delay in residents’ decisions on defending v. evacuating through antecedents of decision avoidance." International Journal of Wildland Fire 24, no. 2 (2015): 153. http://dx.doi.org/10.1071/wf12213.
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In the event of a wildfire, Australian residents of wildfire-prone areas have a choice to defend their home or evacuate early. However, rather than deciding on and preparing for one of these fire-responses ahead of time, most residents delay deciding on defending v. evacuating (e.g. they wait and see instead). Recent research has shown that delaying this decision is associated with reduced levels of preparedness for both responses and on the day of a fire, an increased risk to life and property. The current study empirically examined what predicts this decision delay regarding one’s fire-response by measuring two personality traits and several decision-related factors. A longitudinal survey study of residents of multiple wildfire-prone areas in Western Australia showed that the strongest predictor of delaying their decision to defend v. evacuate was a lack of difference in perceived values of defending v. evacuating. These findings have important implications for the design of interventions to reduce the risks associated with such delay. For one, agencies could utilise residents’ value base to reduce decision delay. Alternatively, they could focus on the formation of proper contingency plans and stress the necessity to prepare well for both defending and evacuating.
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Malasowe, B. O., and A. Emuobonuvie. "Modelling Entrepreneurial Decision Making Process Using Fuzzy Inference Systems." Advances in Multidisciplinary and scientific Research Journal Publication 29 (December 15, 2021): 99–110. http://dx.doi.org/10.22624/aims/abmic2021-v2-p8.
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The essence of Entrepreneurship is making decisions that are constantly required to evaluate alternatives and make decisions regarding a wide range of matters. Decision making involves a lot of uncertainty and risk which poses serious challenges for Entrepreneurs to joggle among them in other to take the best decision. Study have shown that focus has been mainly on the analysis of the characteristics of potential entrepreneurs and the firm-creation process leaving the critical incredient that will help in decision making. The increasing challenges and complexity of business environments are making business decisions and operations more difficult for entrepreneurs to predict the outcomes of these processes. Hence, this paper proposes a decision support model -Fuzzy Inference System- that could be adapted for various business decision processes. This system has the capability to handle decision making, by critically considering the degree of membership of all the risk involved in a given problem space. The model uses the concept of fuzzy set theory to judiciously select the variables in a given problem space in an uncertain situations. From a real life practical point of view, this theory offers a natural approach to the resolution of multidimensional and complex problems when the available information is sparse and/or of poor quality. The fuzzy rule base sytem soften the adverse effects that a business may suffer from these uncertain factors. Keywords: Fuzzy logic, Membership functions, Decision, Fuzzy Set, Entrepreneur
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Septiani, W., Marimin, Y. Herdiyeni, L. Haditjaroko, and T. S. Dewayana. "Intelligent decision support system for risk assessment and dairy price of dairy agroindustry supply chain." Journal of Modern Manufacturing Systems and Technology 5, no. 2 (August 25, 2021): 41–51. http://dx.doi.org/10.15282/jmmst.v5i2.6851.
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Dairy and dairy processing industries are included in the group of food products and high-risk industries. Decision making in relation to risk management in dairy industry supply chain is significant. This study aimed at designing a Intelligent decision support system (DSS) for risk assessment of dairy agroindustry supply chain and the estimation of dairy price in the risk-based farmer level. The risk assessment is analyzed by fuzzy logic approach which is Fuzzy Inference System (FIS) and Fuzzy Assosiative Memories (FAMs). The basic knowledge of this system is obtained through the preparation of rule base of risk assessment and the relation of production cost and risks at the farm based on the expert arguments variables. There are six outputs yielded from RSDA, that is risk assessment in accordance with priority issue, risk assessment for delivery activity, risk source exploration, risk performance, risk management partially and the estimation of production cost and price with risks. The system provides several alternatives which will help decision making in preparing risk management in dairy agroindustry supply chain. Moreover, this system also provides several scenarios of dairy price estimation at the level of farmer who includes risk factor in the farmer. By this system, it is expected that the opportunity of risk and risk impact of dairy agroindustry supply chain can be minimized.
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Blair, Andrew Nyakaana, Bilal M. Ayyub, and William J. Bender. "Fuzzy stochastic risk-based decision analysis with the mobile offshore base as a case study." Marine Structures 14, no. 1-2 (January 2001): 69–88. http://dx.doi.org/10.1016/s0951-8339(00)00027-7.
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Ray, Pritee. "Agricultural Supply Chain Risk Management Under Price and Demand Uncertainty." International Journal of System Dynamics Applications 10, no. 2 (April 2021): 17–32. http://dx.doi.org/10.4018/ijsda.2021040102.
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Agricultural supply chain (ASC) plays a vital role for sustainability as it is the main source of food supply. ASC encounters more sources of risk due to seasonality, perishability, and weather conditions, which makes the global food security system complex. This paper develops an optimization model for a perishable product supply chain to decide the optimal risk management strategy that maximizes the decision maker's expected profit under demand and price uncertainty. A base-case scenario is considered to show the impact of risk management strategy on performance improvement. The expected profit of the decision maker is obtained for different combination of strategies, and sensitivity analysis is performed to show the impact of perishability on the percentage of improvement from the base case scenario. The results show that backup supplier strategy is very effective during the yield disruption, but it is not as effective during harvest disruption. Hence, a single approach is inadequate to provide solution in all types of risk scenarios; thus, the combination of approaches is most effective.
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Fatima, Afreen, and Jitendra Kumar Sharma. "Segmenting Investors on their Biases Manifested in Investment Decision-Making by Individual Investors." SEISENSE Journal of Management 4, no. 4 (July 11, 2021): 16–32. http://dx.doi.org/10.33215/sjom.v4i4.663.
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Purpose- This study proposes to identify the certain biases affecting investor decision-making and to segment investors accordingly. Design/Methodology- A quantitative research method was applied to measure the existence and impact of the biases on investment decision-making. A survey was administered among the stock market investors in Uttar Pradesh. Factor analysis was used to extract those biases that significantly impact investment decision-making and their mean score to assess the level of agreement that affects their investment decisions. Findings - The finding reveals that eight extracted factors affect the investment decisions and accordingly segment them on the biases they exhibit. The investors tend to fall into Imitator, Stereotypical, Independent Individualist, Risk Intolerant, Efficient Planner, Confident, Passive, and Competent Confirmer. The Imitators, Independent Individualists, and Confident investors show their higher level of agreement that highly affects their equity investment decision-making. Practical Implication- This study provides a base to segment the investors on their biases. In addition, it will help in customizing the investment recommendation based on their biases to improve the investment decisions.
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Gupta, A. K., S. F. Mekan, and M. H. Eckman. "Trastuzumab for all? A decision analysis examining tradeoffs between efficacy and cardiac toxicity of adjuvant therapy in HER2 positive breast cancer." Journal of Clinical Oncology 24, no. 18_suppl (June 20, 2006): 6022. http://dx.doi.org/10.1200/jco.2006.24.18_suppl.6022.
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6022 Background: Early results from three randomized trials showed that adjuvant trastuzumab (T) results in significant reduction in recurrence rates in high risk HER2 positive breast cancer patients (pts). However, the long term survival benefits and the balance of risk and benefit of adjuvant T in pts with lower risk of cancer recurrence and a higher risk of cardiac toxicity (elderly and pre-existing heart disease) remain undetermined. Methods: We evaluated these tradeoffs through a Markov state transition decision analytic model to simulate the survival benefits in a variety of subpopulations of HER2 positive cancer pts. Efficacy and cardiac toxicity of T were based on B-31 and N9831 trials. Outcomes were expressed in quality adjusted life years (QALYs) and 10 year survival rates. We explored a number of prototypic scenarios that varied in age, risk of cancer recurrence, and cardiac toxicity rates. Our base case focused on a 50 year-old, 2 cm, node positive, ER/PR negative pt with a 6% cumulative risk of cardiac toxicity. Results: Survival rates and the cardiac death rates for the base case and a hypothetical elderly pt with low risk of cancer recurrence are illustrated in the table . One-way sensitivity analyses on the base case, across a wide range of values for age (50–80); hazard ratio for T efficacy (0.48 to 0.95); annual cancer recurrence risk (0.5–5%) and cardiac toxicity (4–60%) demonstrated that adjuvant T was the more effective strategy. Conclusions: The addition of T in HER2 positive cancer is more effective than standard chemotherapy alone in most cases, including elderly pts with node negative disease and those with increased risk of cardiac toxicity. However, the incremental benefit decreases with advancing age, higher risk of cardiac toxicity and in pts with lower risk of recurrence. This model is a useful clinical tool to quantify risks and benefits of adjuvant T and in predicting long term survival in different subpopulations of HER2 positive breast cancer pts. [Table: see text] No significant financial relationships to disclose.
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Srinivasaiah, N., B. Joseph, J. Gunn, J. Hartley, and J. Monson. "A qualitative analysis of a focus group discussion on patient decision making in cancer care." Journal of Clinical Oncology 27, no. 15_suppl (May 20, 2009): e15145-e15145. http://dx.doi.org/10.1200/jco.2009.27.15_suppl.e15145.
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e15145 Background: Patient preferences should play an important role when decision making in cancer care. Literature is increasingly demonstrating that surgeons and physicians have divergent preferences for treatment options compared with their patients and with each other. Cancer psychology is an important aspect of cancer care. Qualitative research is a gateway to explore this. We aim to explore opinions and thoughts among surgical colleagues about “patient decision making in cancer care”. Methods: A pilot focus group discussion among members of the academic surgical unit involving 4 consultants, 3 registrars and 3 research fellows. The discussion was audio-taped and transcribed. Qualitative methodology was adopted for analysis. Thematic analysis using framework approach was done thereby identifying Themes & Outcomes. Results: Themes that emerged are Evidence based clinical practice, Knowledge, Decision making, Patient Information, Risk, Communication, Consent, Socioeconomic factors and Patient empowerment, Outcomes derived are to increase the evidence base, Increase the clinician and patient knowledge, provide adequate information, Decisions to be based on patients best interest, Communicate risk in a understandable manner, Take patients views, knowledge and demands into consideration, Conclusions: Patient decision making in cancer care is slowly evolving, where decisions are not only made taking into account patients views, knowledge and demand but are also driven by them in a minority. Time is a factor and in years to come the patients will play an increased role in their treatments taking into account tradeoffs and risks between survival and quality of life. No significant financial relationships to disclose.
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Wei, Lei, Yun Bin Li, Jun Hui Xu, and Xiao Xia Luo. "Unmanned Aerial Vehicle Maritime Cruise Base Site Selection Strategy Research in the Bohai Sea." Applied Mechanics and Materials 724 (January 2015): 378–82. http://dx.doi.org/10.4028/www.scientific.net/amm.724.378.
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Since the maritime traffic accidents and oil spill risk problem is getting increasingly serious, on the base of the maritime and oil spill accidents historical data analysis, the risk source in the Bohai Sea is discretized into finite cell. The risk analysis in matter element analysis method has been used to determine every cell’s level of risk and the demand for cruising power of each risk point has been evaluated. The specific location to build maritime unmanned aerial vehicle (UAV) cruise base needs to go through a cost-effectiveness analysis. Taking the relationship between risk point and cruise base’s location into consideration, the multi-target site selection model of UAV cruise base has been established. In this model, genetic algorithm has been used to optimize the site selection and finally, it is able to provide decision-making suggestions for the planning and construction of the Bohai maritime UAV cruise base.
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Bentley, Tanya G. K., Milton C. Weinstein, and Karen M. Kuntz. "Effects of Categorizing Continuous Variables in Decision-Analytic Models." Medical Decision Making 29, no. 5 (July 13, 2009): 549–56. http://dx.doi.org/10.1177/0272989x09340238.
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Purpose. When using continuous predictor variables in discrete-state Markov modeling, it is necessary to create categories of risk and assume homogeneous disease risk within categories, which may bias model outcomes. This analysis assessed the tradeoffs between model bias and complexity and/or data limitations when categorizing continuous risk factors in Markov models. Methods. The authors developed a generic Markov cohort model of disease, defining bias as the percentage change in life expectancy gain from a hypothetical intervention when using 2 to 15 risk factor categories as compared with modeling the risk factor as a continuous variable. They evaluated the magnitude and sign of bias as a function of disease incidence, disease-specific mortality, and relative difference in risk among categories. Results. Bias was positive in the base case, indicating that categorization overestimated life expectancy gains. The bias approached zero as the number of risk factor categories increased and did not exceed 4% for any parameter combinations or numbers of categories considered. For any given disease-specific mortality and disease incidence, bias increased with relative risk of disease. For any given relative risk, the relationship between bias and parameters such as disease-specific mortality or disease incidence was not always monotonic. Conclusions. Under the assumption of a normally distributed risk factor and reasonable assumption regarding disease risk and moderate values for the relative risk of disease given risk factor category, categorizing continuously valued risk factors in Markov models is associated with less than 4% absolute bias when at least 2 categories are used.
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Knapp, Stephen T., Anna Revette, Meghan Underhill-Blazey, Jill E. Stopfer, Chinedu I. Ukaegbu, Cole Poulin, Madison Parenteau, et al. "MyLynch: A Patient-Facing Clinical Decision Support Tool for Genetically-Guided Personalized Medicine in Lynch Syndrome." Cancers 15, no. 2 (January 6, 2023): 391. http://dx.doi.org/10.3390/cancers15020391.
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Lynch syndrome (LS) is a hereditary cancer susceptibility condition associated with varying cancer risks depending on which of the five causative genes harbors a pathogenic variant; however, lifestyle and medical interventions provide options to lower those risks. We developed MyLynch, a patient-facing clinical decision support (CDS) web application that applies genetically-guided personalized medicine (GPM) for individuals with LS. The tool was developed in R Shiny through a patient-focused iterative design process. The knowledge base used to estimate patient-specific risk leveraged a rigorously curated literature review. MyLynch informs LS patients of their personal cancer risks, educates patients on relevant interventions, and provides patients with adjusted risk estimates, depending on the interventions they choose to pursue. MyLynch can improve risk communication between patients and providers while also encouraging communication among relatives with the goal of increasing cascade testing. As genetic panel testing becomes more widely available, GPM will play an increasingly important role in patient care, and CDS tools offer patients and providers tailored information to inform decision-making. MyLynch provides personalized cancer risk estimates and interventions to lower these risks for patients with LS.
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Jin, Chang Hong. "Research on Risk Evaluation of Investment Decision Stage Base on Sensitivity Analysis for Building Engineering Projects." Advanced Materials Research 1046 (October 2014): 131–34. http://dx.doi.org/10.4028/www.scientific.net/amr.1046.131.
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The Sensitivity Analysis is a risk valuation method to calculate the variety range of project economic effect evaluation index, and to judge the influence degree of project expectation target caused by indetermination factors. The paper discusses the risk evaluation of investment decision stage for building engineering projects based on Sensitivity Analysis, which would be beneficial to perfect the practice of the risk evaluation of investment decision stage for building engineering projects.
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Glaser, Daniel. "Who Gets Probation and Parole: Case Study Versus Actuarial Decision Making." Crime & Delinquency 31, no. 3 (July 1985): 367–78. http://dx.doi.org/10.1177/0011128785031003003.
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Probation and parole decisions have traditionally been based upon case studies, governed by informal norms prescribing base rates, and made with overconfidence in their wisdom. Actuarial tables that statistically identify the best predictors of past violations, then convert information from them into a prediction score, have repeatedly been shown to classify offenders into future risk categories more accurately than do case study prognoses. Although such tables have been available since the 1920s, they were only widely adopted by parole boards during the 1970s with the development of decision guidelines that also take offense severity into account and that prescribe for any current case not a specific penalty but a choice within the range of punishments previously imposed for cases similar in actuarial risk and in offense severity. Application of actuarial prediction to sentencing decisions by use of guidelines analogous to those for parole has been attempted, but in practice thus far has had little impact due to the custom of determining sentences by pretrial plea bargaining.
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Wei, Xianfu. "A Method of Enterprise Financial Risk Analysis and Early Warning Based on Decision Tree Model." Security and Communication Networks 2021 (September 25, 2021): 1–9. http://dx.doi.org/10.1155/2021/6950711.
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At present, the domestic and foreign financial crisis early-warning model research will provide only prediction accuracy as the only standard of success for early-warning model, ignoring an important problem, namely, will the financial crisis early-warning model for normal business, compared with the normal enterprise, forecast the financial crisis? This paper reviews the research situation at home and abroad from the perspective of the definition of the enterprise financial crisis, the form of expression, and so on. From the theoretical level, the relationship between the cause of the financial crisis and the change of financial indicators is established by explaining the early-warning theory, early-warning theory of financial crisis, and cost-sensitive learning theory, and the framework of early warning modeling of financial crisis based on decision tree is put forward. The decision tree model is constructed on several training subsets as the base learner so that the decision tree base learner can learn the characteristics of the healthy sample and crisis sample roughly equally. Taking the bond issuing enterprises of manufacturing industry as samples, the empirical comparison shows that the financial warning model based on decision tree integration is more accurate, which indicates that the model can improve the correct identification rate of financial crisis enterprises under the premise of higher overall warning accuracy.
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Wu, Xian Guo, Hui Tao Liu, Li Mao Zhang, Bao Jun Ding, Hai Zhou Zhai, and Xi Li. "The Reliability Theory Based Expert System Research for Subway Construction Safety Risk Identification." Applied Mechanics and Materials 353-356 (August 2013): 1739–48. http://dx.doi.org/10.4028/www.scientific.net/amm.353-356.1739.
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According to the existence of uncertainty in the subway risk identification, introduced rule-based expert system technology, integrated expertise into the knowledge base, automatically identified construction parameters based on CAD drawings, discussed and designed automatic subway security risk identification expert system based on confidence factor theory. And taken underflow sand pit in subway station construction as an example, elaborated the key issues in the knowledge base construction in details, such as risk mechanism analysis, fact base structuring and rule base structuring. And proposed to combine the contribution (C(eij)) with fact credibility ( F(eij)) to confirm the evidence credibility CF(eij) =C(eij) × F(eij), solving the credibility assignment conflict when the fact of certainty and uncertainty existed simultaneously; Selected the threshold of risk conclusions credibility in representative conditions as the sub-boundary for risk potential classification, avoiding the risk omission problem. In this way, the application of expert intelligent decision technology was broadened in subway construction.
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Zalewski, Paweł. "Analysis of Ship's Safety Improvement in Confined Waters with use of the Decision Support System Based on Expert Manoeuvres." Journal of Konbin 7, no. 4 (January 1, 2008): 249–67. http://dx.doi.org/10.2478/v10040-008-0091-x.
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Analysis of Ship's Safety Improvement in Confined Waters with use of the Decision Support System Based on Expert ManoeuvresThe paper presents analysis of possible ship's safety improvement in confined waters with the use of an expert system for navigator's decision support, constructed on the grounds of the knowledge base of gathered manoeuvres for a given type of ship, loading and hydrometeorological condition. The system generates results of encountered decision problems in the form of information about proposed adjustments of main engine, helm and tugs controls and future trajectory presented by means of panoramic graphic interface equivalent to vector large scale ENC and text interface of commands.
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Shapiro, Alexander, and Linwei Xin. "Technical Note—Time Inconsistency of Optimal Policies of Distributionally Robust Inventory Models." Operations Research 68, no. 5 (September 2020): 1576–84. http://dx.doi.org/10.1287/opre.2019.1932.
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The authors extend previous studies of time inconsistency to risk averse (distributionally robust) inventory models and show that time inconsistency is not unique to robust multistage decision making, but may happen for a large class of risk averse/distributionally robust settings. In particular, they demonstrate that if the respective risk measures are not strictly monotone, then there may exist infinitely many optimal policies which are not base-stock and not time consistent. This is in a sharp contrast with the risk neutral formulation of the inventory model where all optimal policies are base-stock and time consistent.
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Quigley, Mark C., Wendy Saunders, Chris Massey, Russ Van Dissen, Pilar Villamor, Helen Jack, and Nicola Litchfield. "The utility of earth science information in post-earthquake land-use decision-making: the 2010–2011 Canterbury earthquake sequence in Aotearoa New Zealand." Natural Hazards and Earth System Sciences 20, no. 12 (December 11, 2020): 3361–85. http://dx.doi.org/10.5194/nhess-20-3361-2020.
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Abstract. Earth science information (data, knowledge, advice) can enhance the evidence base for land-use decision-making. The utility of this information depends on factors including the context and objectives of land-use decisions, the timeliness and efficiency with which earth science information is delivered, and the strength, relevance, uncertainties, and risks assigned to earth science information relative to other inputs. We investigate land-use decision-making practices in Christchurch, New Zealand, and the surrounding region in response to mass movement (e.g., rockfall, cliff collapses) and ground-surface fault rupture hazards incurred during the 2010–2011 Canterbury earthquake sequence (CES). Rockfall fatality risk models combining hazard, exposure, and vulnerability data were co-produced by earth scientists and decision makers and formed primary evidence for risk-based land-use decision-making with adaptive capacity. A public consultation and submission process enabled consideration of additional earth science information primarily via stakeholder requests. For fault rupture hazards, pre-disaster geotechnical guidelines and collaboration networks enhanced the ability of earth scientists to rapidly acquire relevant observational data to meet the demands of decision makers. Expeditious decision-making granted permissive consent for rebuilding in the fault rupture zone based on preliminary scientific advice that was subsequently supported by more comprehensive geological investigations. Rapidly fluctuating and diverse demands for post-disaster earth science information may be best met through the prior establishment of (i) land-use policies and technical guidelines tailored for a variety of diverse disaster scenarios, (ii) hazard and risk analyses in land-use plans, including acquisition of geospatial and other earth science data, and (iii) coordinated scientific networks that may comprise subgroups with diverse goals, operational perspectives, and protocols which allow the many facets of scientific information acquisition and delivery to be successfully addressed. Despite the collective knowledge shared here, some recent land-use practices in New Zealand continue to prioritize other (e.g., socioeconomic) factors above earth science information, even in areas of extreme disaster risk.
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Stoklosa, R. T. "THE RELEVANCE OF RISK ASSESSMENT IN ENVIRONMENTAL APPROVALS AND DECISION MAKING." APPEA Journal 38, no. 1 (1998): 715. http://dx.doi.org/10.1071/aj97047.
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The relevance of ecological risk assessment is the principal subject of this paper. The petroleum industry has demonstrated expertise in characterising process safety risk, and can confidently analyse the circumstances of accidental or routine emissions to the environment. However, the task of characterising the effects of environmental hazards on ecological systems has until recently been the domain of a select group of research scientists and theoreticians.As environmental risk assessment practices evolve, they, of course, gain the attention of decision-makers that must consider the possible consequences of industrial development in potentially sensitive settings. There would appear to be an opportunity for advancing risk assessment techniques and methodologies to fill this demand. It might seem appropriate for the petroleum industry to exercise leadership in this endeavour, applying new technology in ecological risk assessment and setting new standards of performance.But what would be the purpose of refining the petroleum industry's approach to environmental risk assessment if decision makers and the public do not wish to embrace the ideology of more perfect scientific expressions of the risk of development to the environment? Decision makers seek to obtain the best possible scientific advice on which to base decisions. However, the criteria for decision-making is understandably weighted in favour of consultation with stakeholders on issues of high social significance.In order for risk assessment to constructively influence debate and decision-making on environmental issues, it is essential to recognise the features of the environment at risk that have both biological and societal relevance. Even so, the scientific practice of ecological risk assessment can only serve to highlight the issues at hand and communicate the strategy for managing risk. It does not stand to be regarded by decision-makers as the panacea for justifying industrial development in the foreseeable future.A methodology for applying the practice of risk assessment in environmental approvals and decision making is proposed. A strategy of early government participation ensures that the major scientific and social issues can be incorporated explicitly in the risk assessment process. The criteria for interpreting the acceptability of risk must be stated unambiguously at the outset to foster credibility in the results. To be a successful and relevant practice, risk must be communicated to stakeholders with both an explanation of the uncertainty in the results, and a comparison of the risk of industrial development to naturally occurring and anthropogenic environmental hazards.
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Brooks, Jay P. "Using Basic Ethical Principles to Evaluate Safety Efforts in Transfusion Medicine." Journal of Blood Transfusion 2012 (January 19, 2012): 1–6. http://dx.doi.org/10.1155/2012/407326.
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Pursuit of pharmaceutical purity of the blood in the bag has led to a shrinking donor base and a significantly more expensive product. Decisions regarding new infectious marker testing and donor deferrals have typically been made emphasizing decreasing one specific risk without considering the effect the intervention will have on the overall safety and availability of blood transfusion. Regulations have been formulated by governmental agencies with limited input from the medical community. The decision making process has lacked risk benefit analyses and has not had the robustness associated with spirited discussions. Policies made in this manner may result in certain risks being decreased but can also have adverse unintended consequences. Being guided by the ethical principles of nonmaleficence, beneficence, autonomy, and justice, we need to evaluate our actions in the context of overall blood safety rather than narrowly focusing on any one area.
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Stamm, Fabian Antonio, Miguel de la Varga, and Florian Wellmann. "Actors, actions, and uncertainties: optimizing decision-making based on 3-D structural geological models." Solid Earth 10, no. 6 (November 18, 2019): 2015–43. http://dx.doi.org/10.5194/se-10-2015-2019.
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Abstract. Uncertainties are common in geological models and have a considerable impact on model interpretations and subsequent decision-making. This is of particular significance for high-risk, high-reward sectors. Recent advances allows us to view geological modeling as a statistical problem that we can address with probabilistic methods. Using stochastic simulations and Bayesian inference, uncertainties can be quantified and reduced by incorporating additional geological information. In this work, we propose custom loss functions as a decision-making tool that builds upon such probabilistic approaches. As an example, we devise a case in which the decision problem is one of estimating the uncertain economic value of a potential fluid reservoir. For subsequent true value estimation, we design a case-specific loss function to reflect not only the decision-making environment, but also the preferences of differently risk-inclined decision makers. Based on this function, optimizing for expected loss returns an actor's best estimate to base decision-making on, given a probability distribution for the uncertain parameter of interest. We apply the customized loss function in the context of a case study featuring a synthetic 3-D structural geological model. A set of probability distributions for the maximum trap volume as the parameter of interest is generated via stochastic simulations. These represent different information scenarios to test the loss function approach for decision-making. Our results show that the optimizing estimators shift according to the characteristics of the underlying distribution. While overall variation leads to separation, risk-averse and risk-friendly decisions converge in the decision space and decrease in expected loss given narrower distributions. We thus consider the degree of decision convergence to be a measure for the state of knowledge and its inherent uncertainty at the moment of decision-making. This decisive uncertainty does not change in alignment with model uncertainty but depends on alterations of critical parameters and respective interdependencies, in particular relating to seal reliability. Additionally, actors are affected differently by adding new information to the model, depending on their risk affinity. It is therefore important to identify the model parameters that are most influential for the final decision in order to optimize the decision-making process.
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Liu, Dengzhuo, Zhongkai Li, Chao He, and Shuai Wang. "Risk-Averse Co-Decision for Lower-Carbon Product Family Configuration and Resilient Supplier Selection." Sustainability 14, no. 1 (December 30, 2021): 384. http://dx.doi.org/10.3390/su14010384.
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Due to global pandemics, political unrest and natural disasters, the stability of the supply chain is facing the challenge of more uncertain events. Although many scholars have conducted research on improving the resilience of the supply chain, the research on integrating product family configuration and supplier selection (PCSS) under disruption risks is limited. In this paper, the centralized supply chain network, which contains only one major manufacturer and several suppliers, is considered, and one resilience strategy (i.e., the fortified supplier) is used to enhance the resilience level of the selected supply base. Then, an improved stochastic bi-objective mixed integer programming model is proposed to support co-decision for PCSS under disruption risks. Furthermore, considering the above risk-neutral model as a benchmark, a risk-averse mixed integer program with Conditional Value-at-Risk (CVaR) is formulated to achieve maximum potential worst-case profit and minimum expected total greenhouse gases (GHG) emissions. Then, NSGA-II is applied to solve the proposed stochastic bi-objective mixed integer programming model. Taking the electronic dictionary as a case study, the risk-neutral solutions and risk-averse solutions that optimize, respectively, average and worst-case objectives of co-decision are also compared under two different ranges of disruption probability. The sensitivity analysis on the confidence level indicates that fortifying suppliers and controlling market share in co-decision for PCSS can effectively reduce the risk of low-profit/high-cost while minimizing the expected GHG emissions. Meanwhile, the effects of low-probability risk are more likely to be ignored in the risk-neutral solution, and it is necessary to adopt a risk-averse solution to reduce potential worst-case losses.
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Choi, Sungyong, and Kyungbae Park. "A Risk-Averse Inventory Model with Markovian Purchasing Costs." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/925765.
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We study a few dynamic risk-averse inventory models using additive utility functions. We add Markovian behavior of purchasing costs in our models. Such Markovian purchasing costs can reflect a market situation in a global supply chain such as fluctuations at exchange rates or the existence of product spot markets. We provide our problem formulations with finite and infinite MDP (Markovian Decision Process) problems. For finite time models, we first prove (joint) concavity of the model for each state and obtain a (modified) base-stock optimal policy. Then, we conduct comparative static analysis for model parameters and derive monotone properties to the optimal solutions. For infinite time models, we show the existence of stationary base-stock optimal policies and the inheritance of the monotone properties proven at our finite time models.
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Kim, Esther L., and Sarah Tanford. "Seeking reward or avoiding risk from restaurant reviews: does distance matter?" International Journal of Contemporary Hospitality Management 31, no. 12 (December 9, 2019): 4482–99. http://dx.doi.org/10.1108/ijchm-03-2018-0235.
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Purpose The purpose of this paper is to evaluate the extent to which consumers will exert more effort to avoid risk (negative reviews) versus seek reward (positive reviews) when making a restaurant decision. Design/methodology/approach This study investigates the influence of distance and review valence on restaurant decisions. A 2 (base restaurant review valence: negative, neutral) × 2 (target restaurant review valence: neutral, positive) × 2 (distance: 30 min, 60 min) between-subjects factorial design was used. Findings People exert more effort to seek a reward versus avoid a risk. People will drive any distance to dine at a restaurant with positive reviews. However, the tendency to avoid a restaurant with negative reviews declines as distance increases. Practical implications This study emphasizes the critical role of positive reviews in the restaurant industry. This research provides guidance to operators to manage online reviews effectively. The marketing strategy taking into account review valence and distance allows the business to attract new customers and grow its customer base. Originality/value This research synthesizes asymmetry effects and prospect theory with the level of risk associated with the outcome. This research is theoretically noteworthy since the finding of a reverse asymmetry principle is in contrast with the traditional belief of risk-avoidance when comparing gains and losses.
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Shrimpton, Roger. "Evidence ν. rights-based decision making for nutrition." Proceedings of the Nutrition Society 62, no. 2 (May 2003): 553–62. http://dx.doi.org/10.1079/pns2003264.
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The need for an evidence base for human nutrition action is analysed in the context of human rights. Over the last 50 years the twin tracks of development, economical needs based and normative rights based, have come progressively closer in terms of goals and objectives, even if they do maintain different orientations and origins. The international human rights machinery is described, together with those parts that are of relevance to the right to food and nutrition. The role of the State in respecting, protecting and facilitating these rights is further described. The evidence base for the benefit of nutrition interventions during the fetal and infant period to the health and well-being of populations throughout life's course is briefly reviewed, and reasons why such a large body of evidence has not been acted upon are discussed. The power of nutrition is in prevention more than cure, and the prevention of nutritional deficiency is best suited to radical population-wide strategies rather than high-risk strategies targeted at individuals. The population-wide distribution of benefits of nutrition is in congruence with universality of human rights. In the UK much remains to be done to ensure that food and nutrition rights are realised, especially during the critical period of fetal and infant growth. What role the Nutrition Society might play in the realisation of these rights, including the creation of a robust evidence base for nutrition action, is further discussed.
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Sujith, A. V. L. N., Naila Iqbal Qureshi, Venkata Harshavardhan Reddy Dornadula, Abinash Rath, Kolla Bhanu Prakash, and Sitesh Kumar Singh. "A Comparative Analysis of Business Machine Learning in Making Effective Financial Decisions Using Structural Equation Model (SEM)." Journal of Food Quality 2022 (February 23, 2022): 1–7. http://dx.doi.org/10.1155/2022/6382839.
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Globally, organisations are focused on deriving more value from the data which has been collected from various sources. The purpose of this research is to examine the key components of machine learning in making efficient financial decisions. The business leaders are now faced with huge volume of data, which needs to be stored, analysed, and retrieved so as to make effective decisions for achieving competitive advantage. Machine learning is considered to be the subset of artificial intelligence which is mainly focused on optimizing the business process with lesser or no human interventions. The ML techniques enable analysing the pattern and recognizing from large data set and provide the necessary information to the management for effective decision making in different areas covering finance, marketing, supply chain, human resources, etc. Machine learning enables extracting the quality patterns and forecasting the data from the data base and fosters growth; the machine learning enables transition from the physical data to electronically stored data, enables enhancing the memory, and supports with financial decision making and other aspects. This study is focused on addressing the application of machine learning in making the effective financial decision making among the companies; the application of ML has emerged as a critical technology which is being applied in the current competitive market, and it has offered more opportunities to the business leaders in leveraging the large volume of data. The study is intended to collect the data from employees, managers, and business leaders in various industries to understand the influence of machine learning in financial decision making .
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Wei, Yu, Matthew Thompson, Joe Scott, Christopher O’Connor, and Christopher Dunn. "Designing Operationally Relevant Daily Large Fire Containment Strategies Using Risk Assessment Results." Forests 10, no. 4 (April 5, 2019): 311. http://dx.doi.org/10.3390/f10040311.
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In this study, we aim to advance the optimization of daily large fire containment strategies for ground-based suppression resources by leveraging fire risk assessment results commonly used by fire managers in the western USA. We begin from an existing decision framework that spatially overlays fire risk assessment results with pre-identified potential wildland fire operational delineations (PODs), and then clusters PODs into a response POD (rPOD) using a mixed integer program (MIP) model to minimize expected loss. We improve and expand upon this decision framework through enhanced fire modeling integration and refined analysis of probabilistic and time-sensitive information. Specifically, we expand the set of data inputs to include raster layers of simulated burn probability, flame length probability, fire arrival time, and expected net value change, all calculated using a common set of stochastic weather forecasts and landscape data. Furthermore, we develop a secondary optimization model that, for a given optimal rPOD, dictates the timing of fire line construction activities to ensure completion of containment line prior to fire arrival along specific rPOD edges. The set of management decisions considered includes assignment of PODs to be included in the rPOD, assignment of suppression resources to protect susceptible structures within the rPOD, and assignment of suppression resources to construct fire lines, on specific days, along the perimeter of the rPOD. We explore how fire manager risk preferences regarding firefighter safety affect optimal rPOD characteristics, and use a simple decision tree to display multiple solutions and support rapid assessment of alternatives. We base our test cases on the FSPro simulation of the 2017 Sliderock Fire that burned on the Lolo National Forest in Montana, USA. The overarching goal of this research is to generate operationally relevant decision support that can best balance the benefits and losses from wildfire and the cost from responding to wildfire.
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Vitkus, Donatas, Žilvinas Steckevičius, Nikolaj Goranin, Diana Kalibatienė, and Antanas Čenys. "Automated Expert System Knowledge Base Development Method for Information Security Risk Analysis." International Journal of Computers Communications & Control 14, no. 6 (November 27, 2019): 743–58. http://dx.doi.org/10.15837/ijccc.2019.6.3668.
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Information security risk analysis is a compulsory requirement both from the side of regulating documents and information security management decision making process. Some researchers propose using expert systems (ES) for process automation, but this approach requires the creation of a high-quality knowledge base. A knowledge base can be formed both from expert knowledge or information collected from other sources of information. The problem of such approach is that experts or good quality knowledge sources are expensive. In this paper we propose the problem solution by providing an automated ES knowledge base development method. The method proposed is novel since unlike other methods it does not integrate ontology directly but utilizes automated transformation of existing information security ontology elements into ES rules: The Web Ontology Rule Language (OWL RL) subset of ontology is segregated into Resource Description Framework (RDF) triplets, that are transformed into Rule Interchange Format (RIF); RIF rules are converted into Java Expert System Shell (JESS) knowledge base rules. The experiments performed have shown the principal method applicability. The created knowledge base was later verified by performing comparative risk analysis in a sample company.
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Chew Hernandez, M. L., E. K. Velazquez Hernandez, and S. Leon Dominguez. "A Decision-Analytic Feasibility Study of Upgrading Machinery at a Tools Workshop." Engineering, Technology & Applied Science Research 2, no. 2 (April 11, 2012): 182–89. http://dx.doi.org/10.48084/etasr.139.
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This paper presents the evaluation, from a Decision Analysis point of view, of the feasibility of upgrading machinery at an existing metal-forming workshop. The Integral Decision Analysis (IDA) methodology is applied to clarify the decision and develop a decision model. One of the key advantages of the IDA is its careful selection of the problem frame, allowing a correct problem definition. While following most of the original IDA methodology, an addition to this methodology is proposed in this work, that of using the strategic Means-Ends Objective Network as a backbone for the development of the decision model. The constructed decision model uses influence diagrams to include factual operator and vendor expertise, simulation to evaluate the alternatives and a utility function to take into account the risk attitude of the decision maker. Three alternatives are considered: Base (no modification), CNC (installing an automatic lathe) and CF (installation of an automatic milling machine). The results are presented as a graph showing zones in which a particular alternative should be selected. The results show the potential of IDA to tackle technical decisions that are otherwise approached without the due care.
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Stutchfield, Benjamin M., Manu Nayar, and Ian D. Penman. "Pancreatic cystic lesions: risk stratification and management based on recent guidelines." Frontline Gastroenterology 10, no. 2 (February 18, 2019): 182–87. http://dx.doi.org/10.1136/flgastro-2018-101076.
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Pancreatic cystic lesions (PCLs) can present complex diagnostic and management challenges with uncertainty as to the most appropriate investigations, interventions and surveillance. Guidelines have been developed to aid decision making, including the European Study Group, American College of Gastroenterology and International Study Group guidelines. This paper presents issues relating to risk stratification and the appropriate management of patients with PCLs, reviewing these recently published guidelines. While there are similarities across these expert guidelines, there are notable differences in terms of features associated with increased risk of malignant transformation, the most appropriate imaging modality and timing of interval imaging. Where variations exist, this reflects differing interpretations of a limited evidence base, and decision making will likely evolve further as experience with these guidelines develops.
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Dragoi, George, Anca Draghici, Sebastian Marius Rosu, Alexandru Radovici, and Costel Emil Cotet. "Knowledge Base Development in Virtual Enterprise Network as Support for Workplace Risk Assessment." International Journal of Human Capital and Information Technology Professionals 2, no. 3 (July 2011): 44–60. http://dx.doi.org/10.4018/jhcitp.2011070104.
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The article presents research results based on the concept of collaborative infrastructure (as the virtual enterprise network PREMINV e-platform from “Politehnica” University of Bucharest, Romania), in order to unify existing standards for supply chain management and to provide support in various decision making processes in manufacturing supply networks. The intent is to facilitate and enhance the required knowledge management processes linked with the business process management. The virtual enterprise network expects to reduce small and medium-sized enterprises involvement in networking efforts, enable better and faster decision processes and promote the development of the business services. In addition, the new product development paradigm requires software tools for risk estimation and assessment. For this purpose, the authors describe a knowledge bases method build and use for the professional risk assessment as part of risk management process. The risk level is established based on the probability and severity of its consequences.
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De Vito, Katherine. "Seeking a secure base: Gangs as attachment figures." Qualitative Social Work 19, no. 4 (May 24, 2019): 754–69. http://dx.doi.org/10.1177/1473325019852659.
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Street gangs are problematic throughout the world. Youth involved with street gangs are at a higher risk for winding up seriously physically injured, dead, or incarcerated. The purpose of this qualitative research study was to examine (a) how the childhood experiences of former gang members shape their decision to join a gang and (b) the factors that contribute to former gang members’ decision to disengage from gang membership. This study will promote the use of attachment theory to analyze motivating/disengagement factors for gang involvement. The voices of 14 former gang members are heard through qualitative interviews. Thematic analysis was used to identify the following themes: Lack of Family Consistency, Brotherhood, Sisterhood, Unity: Gang as Replacement Family, “No other Option,” and “Jail, Death, or a Turnaround:” Making the Decision to Disengage. Findings could be used to aid in youth gang prevention and intervention.
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Head, Michael G. "A real-time policy dashboard can aid global transparency in the response to coronavirus disease 2019." International Health 12, no. 5 (July 10, 2020): 373–74. http://dx.doi.org/10.1093/inthealth/ihaa039.
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Abstract There has been great provision of open data across the coronavirus disease 2019 (COVID-19) pandemic response, with, for example, dashboards presenting real-time descriptions of new daily cases and risk factors. Transparency has been an important discussion point and there have been concerns and criticisms of governments for not publishing the evidence base that is informing their decision-making. A ‘policy dashboard’ could act as a hub to show the localised reasoning behind COVID-19 policy decisions and allow the global health community to provide further support to governments and international stakeholders.
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Tiutyk, O. V., and M. E. Butakova. "Simulation as Implementation of Digital Approach to Decision-Making under Uncertainty and Risk." SHS Web of Conferences 62 (2019): 11004. http://dx.doi.org/10.1051/shsconf/20196211004.
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The paper articulates the problem of modeling management decision-making process in new digital reality: decision-making under uncertainty, volatile environment, huge amount of data to be accounted, objective analytical risk attitude. The proposed solution includes critical selection of risk and uncertainty management tools aimed at improvement quality of management decision-making information support in the sustainable development context (on the example of construction projects). The aim of research is the development of the new “digital” approach to the process of reducing uncertainty when decision making in highly risk projects, including the process model and toolkit. Methodology is based on logical analysis and synthesis, decomposition, qualitative analysis of the relevant literature and primary data (top management informal interviews, targeted sample), comparative and regression analysis, time series analysis, mathematical statistics and simulation modelling based on nine sets of design estimation paperwork and turnover-balance sheets. The contribution into the existing knowledge includes substantiating the correlation of the terms of the digital decision-making and simulation modeling tools in high-risk projects management under insufficient statistical data and their mutual interaction. Also, advisability of formalization of the decision-making method based on unprocessed design estimates is justified, and appropriate methods for sustainable decision-making information support are selected. The approbation demonstrated practical significance and economic effectiveness of developed approach; experiment was carried out on the base of «RSU – 6» LLC’s projects (Tchaikovsky, Perm region).
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Campbell, Rebecca J., and Peter Lichtenberg. "THE LFDSS DETECTS HIGH-RISK FINANCIAL DECISION-MAKING IN COGNITIVELY VULNERABLE OLDER ADULTS." Innovation in Aging 3, Supplement_1 (November 2019): S125. http://dx.doi.org/10.1093/geroni/igz038.457.
Full textAbstract:
Abstract The Lichtenberg Financial Decision-Making Screening Scale (LFDSS) is a brief screening tool that quantifies an individual’s informed decision making and risk for exploitation in a real-world financial transaction. Previous literature found that the ideal cut-off score for those at higher risk of financial exploitation was five and above. The purpose of the present study was to examine the utility of the LFDSS as a screening tool for financial decision-making ability in a high-risk sample of people with cognitive impairment. The sample was obtained from the Michigan Alzheimer’s Disease Center and was comprised of both cognitively healthy individuals (n=73) and those with cognitive impairment (n=45). All participants completed the LFDSS as part of a larger test battery. A Pearson chi-square analysis was used to examine group differences in financial decision-making risk between cognitively healthy individuals and those with cognitive impairment. A Pearson chi-square analysis found that those who had cognitive impairment were significantly more likely to score above the cut-off for high-risk financial decision-making compared to those who were cognitively healthy (χ2(1)=4.61, p=.032). The base rate of high-risk financial decision-making was 3.2x greater for those with cognitive impairment compared (17.7%) to those who were cognitively healthy (5.5%). These results demonstrate the utility of the LFDSS to detect high-risk decision-making in individuals with cognitive impairment. This tool serves a need in many professional settings (e.g. doctor’s offices and Adult Protective Services) for a brief, standardized assessment measure of financial decision-making and exploitation risk for a real-world, significant financial transaction.
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Habib, Shaista, Wardat us Salam, M. Arif Butt, M. Akram, and F. Smarandache. "A neutrosophic clinical decision-making system for cardiovascular diseases risk analysis." Journal of Intelligent & Fuzzy Systems 39, no. 5 (November 19, 2020): 7807–29. http://dx.doi.org/10.3233/jifs-201163.
Full textAbstract:
Cardiovascular diseases are the leading cause of death worldwide. Early diagnosis of heart disease can reduce this large number of deaths so that treatment can be carried out. Many decision-making systems have been developed, but they are too complex for medical professionals. To target these objectives, we develop an explainable neutrosophic clinical decision-making system for the timely diagnose of cardiovascular disease risk. We make our system transparent and easy to understand with the help of explainable artificial intelligence techniques so that medical professionals can easily adopt this system. Our system is taking thirty-five symptoms as input parameters, which are, gender, age, genetic disposition, smoking, blood pressure, cholesterol, diabetes, body mass index, depression, unhealthy diet, metabolic disorder, physical inactivity, pre-eclampsia, rheumatoid arthritis, coffee consumption, pregnancy, rubella, drugs, tobacco, alcohol, heart defect, previous surgery/injury, thyroid, sleep apnea, atrial fibrillation, heart history, infection, homocysteine level, pericardial cysts, marfan syndrome, syphilis, inflammation, clots, cancer, and electrolyte imbalance and finds out the risk of coronary artery disease, cardiomyopathy, congenital heart disease, heart attack, heart arrhythmia, peripheral artery disease, aortic disease, pericardial disease, deep vein thrombosis, heart valve disease, and heart failure. There are five main modules of the system, which are neutrosophication, knowledge base, inference engine, de-neutrosophication, and explainability. To demonstrate the complete working of our system, we design an algorithm and calculates its time complexity. We also present a new de-neutrosophication formula, and give comparison of our the results with existing methods.