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We have described a new DMRCS process for structured decision making, which mirrors the approach of the DMAIC process which has become so popular within Lean Six Sigma. By dividing a complex often unstructured process into distinct steps, we hope to have made the task of balancing multiple competing objectives less daunting.
Purpose: The purpose of this study was to assess the accuracy of a virtual consultation (VC) process in determining treatment strategy for patients with malignant epidural spinal cord compression (MESCC). Methods and Materials: A prospective clinical database was maintained for patients with MESCC. A virtual consultation process (involving exchange of key predetermined clinical information and diagnostic imaging) facilitated rapid decision-making between oncologists and spinal surgeons. Diagnostic imaging was reviewed retrospectively (by R.R.) for surgical opinions in all patients. The primary outcome was the accuracy of virtual consultation opinion in predicting the final treatment recommendation. Results: After excluding 20 patients who were referred directly to the spinal surgeon, 125 patients were eligible for virtual consultation. Of the 46 patients who had a VC, surgery was recommended in 28 patients and actually given to 23. A retrospective review revealed that 5/79 patients who did not have a VC would have been considered surgical candidates. The overall accuracy of the virtual consultation process was estimated at 92%. Conclusion: The VC process for MESCC patients provides a reliable means of arriving at a multidisciplinary opinion while minimizing patient transfer. This can potentially shorten treatment decision time and enhance clinical outcomes.
Progress has been made on "Personality as it relates to decision making, information processing and error management in commercial aviation" in several areas during the first phase of the project.
In this paper, we introduce a quantity measure which is called (R, S)-norm entropy and discuss some of its major properties with Shannon’s and other entropies in the literature. Based on this (R, S)-norm entropy, we have proposed a new (R, S)-norm fuzzy information measure and discussed its validity and properties. Further, we have given its comparison with other fuzzy information measures to prove its effectiveness. Attribute weights play an important role in multiple-attribute decision-making problems. In the present communication, two methods of determining the attribute weights are introduced. First is the case when the information regarding attribute weights is incompletely known or completely unknown and second is when we have partial information about attribute weights. For the first case, the extension of ordinary entropy weight method is used to calculate attribute weights and minimum entropy principle method based on solving a linear programming model is used in the second case. Finally, two methods are explained through numerical examples.
This is a three-paper dissertation that responds to a call for empirical research on stakeholder influence in the implementation of evaluation recommendations. The literature is consistent but mostly theoretical: stakeholder participation should positively influence and increase the probability of implementation (see e.g., Christie, 2011; Cousins & Earl, 1992; Fetterman, 2004). In response, I use two Goddard Space Flight Center engineering technical training and development programs to build a causal argument supporting my proposition that stakeholder influence in the logic modeling process impacts organizational decision-making and change. I first introduce the logic modeling process as a tool to involve stakeholders in program and evaluation design (paper 1); then use the data collection process to implement the collaboratively constructed logic model outcomes (paper 2); and, finally, I triangulate the data using the Toal (2009) Evaluation Involvement Scale (paper 3). I do this to “increase the validity of the findings” (Noble & Heale, 2019, p. 67) and to garner potential mechanisms. I found that stakeholder participation in the logic modeling process positively influenced the use of data to inform recommendations which in turn positively influenced implementation of evaluation recommendations. I identified the process itself as the mechanism and the key decision points as links or influencers. Potential factors included power and interest (measured by role) and time-on-job.
The National Renewable Energy Laboratory (NREL) offers a variety of models and analysis tools to help decision makers evaluate and make informed decisions about solar projects, policies, and programs. This fact sheet aims to help decision makers determine which NREL tool to use for a given solar project or policy question, depending on its scope.
Disposal of radioactive waste aims to protect people and the environment from the potential hazards of the materials by removing the wastes from the human environment. This approach is considered desirable to dispersal of the waste in the environment. However, the waste becomes concentrated in one location, which poses potential hazards should the waste become disturbed at a future date. For radioactive waste, it is generally expected that in preparing safety cases for such disposal facilities, the possibility of the wastes being inadvertently disturbed at some point in the future and the potential consequences of such an intrusion need to be considered. Potential inadvertent human intrusion (IHI) has a role in the decision-making and the safety case throughout the lifecycle of a disposal facility. In 2013, the International Atomic Energy Agency (IAEA) formally initiated a project entitled 'Human Intrusion in the Context of Disposal of Radioactive Waste' (HIDRA) to provide insights regarding the role of IHI for these decisions and to provide a common framework for consideration of IHI as part of development of a safety case for a disposal facility. HIDRA was implemented with a series of annual plenary meetings involving participants from more than 20 countries organised into three working groups. The working groups addressed: societal factors, stylised scenarios, and protective measures. The project resulted in a general approach with specific suggestions for consideration of IHI during the lifecycle of a disposal facility. From a general perspective, it was emphasized that IHI is a contributing factor to the safety case, but does not outweigh considerations related to safety of operations and long-term performance for the normal evolution of the facility. (authors)
Rectal cancer predominantly affects patients older than 70 years, with peak incidence at age 80 to 85 years. However, the standard treatment paradigm for rectal cancer oftentimes cannot be feasibly applied to these patients owing to frailty or comorbid conditions. There are currently little information and no treatment guidelines to help direct therapy for patients who are elderly and/or have significant comorbidities, because most are not included or specifically studied in clinical trials. More recently various alternative treatment options have been brought to light that may potentially be utilized in this group of patients. This critical review examines the available literature on alternative therapies for rectal cancer and proposes a treatment algorithm to help guide clinicians in treatment decision making for elderly and comorbid patients.
The NASA Risk Informed Decision Making process is used to assess a trade space of three dimensionally woven thermal protection systems for application to the Mars Sample Return Earth Entry Vehicle. Candidate architectures are assessed based on mission assurance, technical development, cost, and schedule risk. Assessment methodology differed between the architectures, utilizing a four-point quantitative scale for mission assurance and technical development and highly tailored PERT techniques for cost and schedule. Risk results are presented, in addition to a review of RIDM effectiveness for this application.
Highlights: • Environmental criteria for the MSW incineration location procurements are needed. • Focus should be placed on annual energy efficiency and on substitute fuels. • In SRF combustion it is crucial to know the share and the treatment of rejects. • The GWP of transportation is a small part of the total emissions. - Abstract: The ongoing trend in the public sector is to make more sustainable procurements by taking into account the impacts throughout the entire life cycle of the procurement. Despite the trend, the only deciding factor can still be the total costs. This article answers the question of how greenhouse gas (GHG) emissions should be taken into account in municipal solid waste (MSW) management when selecting an incineration plant for source separated mixed MSW. The aim is to guide the decision making of MSW management towards more environmentally friendly procurements. The study was carried out by calculating the global warming potentials (GWPs) and costs of mixed MSW management by using the waste composition from a case area in Finland. Scenarios of landfilling and combustion in three actual waste incineration plants were used to recognise the main processes that affect the results. GWP results show that the combustion of mixed MSW is a better alternative than landfilling the waste. The GHG results from combustion are greatly affected by emissions from the combustion and substituted energy production. The significance of collection and transportation is higher from the costs’ perspective than from the point of view of GHG emissions. The main costs, in addition to collection and transportation costs, result from the energy utilization or landfilling of mixed MSW. When tenders are invited for the incineration location of mixed MSW, the main focus should be: What are the annual electricity and heat recovery efficiencies and which are the substituted fuels in the area? In addition, in the case of a fluidized bed combustor it is crucial to know the combusted share of mixed MSW after preparing solid recovered fuel (SRF) and the treatment of rejects. The environmental criteria for the waste incineration plant procurements should be made in order to obtain clear instructions for the procurement units. The results can also be utilized more widely. The substituted fuels in the area and the effect of the plant location on the utilization of the produced energy can already be identified when planning an appropriate site for the waste incineration plant.
Multidimensional data efficient decomposition for communication interface between man machine system, considering decision making and pattern recognition on digital computers with orthogonal transformations
For every $1 billion invested in projects, $97 million is wasted due to poor project performance. That means 9.7% of money spent on projects is wasted due to poor risk and uncertainty management. High-risk projects, similar to those in waste remediation, have the most to lose. A solid quantitative risk management program is one of the keys to increasing the likelihood that a project will succeed. A quantitative risk program solves two major problems that challenge the effective management of risk and uncertainty: 1. Risks arise at all levels of an organization; however, not all organizational levels have an effective way to identify and resolve them. This can lead to risks that, even if identified, are not reported. 2. Decision-makers are often forced to operate solely on intuition when implementing mitigation strategies, not fully understanding the effects that certain decisions have on the program's cost and schedule. A quantitative risk program uses a risk register and builds it into the project/program integrated schedule to assess the impact of these risks, typically at the 80% confidence contingency level for specific milestones and/or project completion. Implementing a quantitative risk program drives a forward-thinking, proactive mentality to problem solving into all levels of the organization. A healthy risk program for regular reporting and communication ensures that all members of an organization are thinking about risks and using their communication channels to resolve them. It gives a method of communication and incentive for all levels in the organization and helps to ensure that risks will be reported and resolved. Pacific Northwest National Laboratory (PNNL) has developed tools and methods that provide a level of realism for analyzing different scenarios and estimating contingency that does not exist in the standard industry risk tool kit. These tools and methods provide decision-makers with actionable, quantitatively based information to guide their decision making. The first tool is a probabilistic branching risk model for mitigation strategies. Current quantitative risk analysis tools in the industry simulate two cases: fully mitigated and un-mitigated. In the fully mitigated case, the user assumes that every planned mitigation activity is successful. In the un-mitigated case, the user assumes that none are successful. The truth lies between these two extremes. The PNNL team has developed a probabilistic risk model for mitigation scenarios that includes a probability that a mitigation activity will succeed and a probability that a mitigation action will be funded. These probabilities are elicited from subject matter experts and ensure that the contingency calculations at the specified confidence are approaching reality. The second tool developed at PNNL is the Risk Box, which is a tool that integrates with different scenarios in the risk register. For example, say the user is faced with two different and mutually exclusive mitigation actions to reduce a risk. The Risk Box methodology performs the contingency calculations and then displays them on a time-phased graph that shows how each scenario reduces the risk contingency needed on the project/program. This graph then provides quantitative information to show decision-makers which mitigation action provides the greatest reduction (cost and schedule) in risk contingency for the program. Implementing these and other tools within a structured risk program increases the likelihood that a project will come in on schedule and budget, ensures that all personnel are proactively thinking about problems and resolutions, creates communication channels for all members to submit and resolve potential problems, produces a prioritized list of risk rankings to focus leadership on issues that may cause the biggest problems, and implements processes that drive updates to the risk program as the risk profile changes. PNNL has been developing these methods and using them on projects for over 20 years. They have been successfully applied on waste management projects, high-tech research and development projects, and construction projects, and they continue to be used on a number of U.S. Department of Energy projects today. (authors)
Under DOE Order 435.1, 'Radioactive Waste Management', Washington River Protection Solutions, LLC and INTERA, Inc are currently preparing a performance assessment for the Hanford Integrated Disposal Facility, a near-surface low-activity waste disposal facility located on the Hanford Site in southeast Washington State. The disposal facility is expected to receive vitrified low-activity waste produced at the Hanford Waste Treatment and Immobilization Plant, as well as other secondary solid wastes generated during the treatment process. The performance assessment performs the analyses that will be relied upon to receive the Disposal Authorization Statement, establish waste acceptance criteria, modify the RCRA permit for the facility and make a waste-incidental-to-reprocessing determination for the vitrified tank waste. In January 2006 in the case State of Washington v. Bodman (Civil No. 2:03-cv-05018-AAM), DOE, the Washington State Department of Ecology (Ecology) and the State of Washington Attorney General's office reached a settlement agreement in Ecology's claim regarding off-site waste shipments to Hanford and the adequacy of modeling in the environmental impact statement. In response to the agreement, the DOE Office of Environmental Management set a policy to establish a consistent use of commercially available and public domain software for a vadose zone and groundwater model platform to support regulatory decisions at Hanford. In October 2012, the Associate Principal Deputy Assistant Secretary for Environmental Management released a memorandum to the manager of the Richland Operation Office directing how future environmental modeling activities to support regulatory decision making on the Hanford Site would be undertaken to be consistent with the 2006 settlement agreement. The preparation of the performance assessment must meet DOE Order 435.1 requirements and the additional direction provided by DOE. This paper will identify the approach taken to comply with the requirements in the 2012 memorandum. The paper will describe how environmental modeling performed for the 2017 Integrated Disposal Facility Performance Assessment was planned in a phased approach and how the current modeling is tied to the analyses that supported the decisions made in the environmental impact statement published in 2012. Additionally, the selection and qualification of the software selected to perform modeling activities for the performance assessment will be described. (authors)
Sealed radioactive sources are used for an extremely wide range of purposes, including as radiation sources in various nuclear facilities, universities, hospitals, biomedical and industrial applications, as well as for geological prospecting and exploration. The proper management of these sealed radioactive sources once they have reached their end-of-life is still a global challenge. Very few field-tested Mobile Hot Cells (MHC) exist in the world to support the end-of-life management of disused high-activity radioactive sources. One of the critical challenges that a source recovery team encounters on each site is to find adequate space, and access to that space to complete the staging and recapture process with a MHC; this process is tedious, uncertain, and time-consuming. Therefore, it is essential to understand the planning and management of the MHC setup and takedown. Currently, there isn't an single capable planning tool that will provide an effective medium to plan, inform, educate, and communicate knowledge about the environment where the MHC will be deployed. We present a novel approach for the planning and management of the deployment of the MHC to several different sites that relies on technology. Furthermore, this planning tool will support collaboration, promote information sharing, and foster better decision making processes, resulting in a more efficient, and reliable setup and source recovery with the MHC.
Purpose: This study presents an adaptive error detection algorithm (AEDA) for real-timein vivo point dosimetry during high dose rate (HDR) or pulsed dose rate (PDR) brachytherapy (BT) where the error identification, in contrast to existing approaches, does not depend on an a priori reconstruction of the dosimeter position. Instead, the treatment is judged based on dose rate comparisons between measurements and calculations of the most viable dosimeter position provided by the AEDA in a data driven approach. As a result, the AEDA compensates for false error cases related to systematic effects of the dosimeter position reconstruction. Given its nearly exclusive dependence on stable dosimeter positioning, the AEDA allows for a substantially simplified and time efficient real-time in vivo BT dosimetry implementation. Methods: In the event of a measured potential treatment error, the AEDA proposes the most viable dosimeter position out of alternatives to the original reconstruction by means of a data driven matching procedure between dose rate distributions. If measured dose rates do not differ significantly from the most viable alternative, the initial error indication may be attributed to a mispositioned or misreconstructed dosimeter (false error). However, if the error declaration persists, no viable dosimeter position can be found to explain the error, hence the discrepancy is more likely to originate from a misplaced or misreconstructed source applicator or from erroneously connected source guide tubes (true error). Results: The AEDA applied on twoin vivo dosimetry implementations for pulsed dose rate BT demonstrated that the AEDA correctly described effects responsible for initial error indications. The AEDA was able to correctly identify the major part of all permutations of simulated guide tube swap errors and simulated shifts of individual needles from the original reconstruction. Unidentified errors corresponded to scenarios where the dosimeter position was sufficiently symmetric with respect to error and no-error source position constellations. The AEDA was able to correctly identify all false errors represented by mispositioned dosimeters contrary to an error detection algorithm relying on the original reconstruction. Conclusions: The study demonstrates that the AEDA error identification during HDR/PDR BT relies on a stable dosimeter position rather than on an accurate dosimeter reconstruction, and the AEDA’s capacity to distinguish between true and false error scenarios. The study further shows that the AEDA can offer guidance in decision making in the event of potential errors detected with real-timein vivo point dosimetry.
The business rules that underlie an enterprise emerge as a new category of system requirements that represent decisions about how to run the business, and which are characterized by their business-orientation and their propensity for change. In this report, we introduce a decision making methodology which addresses several aspects of the business rules lifecycle: acquisition, deployment and evolution. We describe a meta-model for representing business rules in terms of an enterprise model, and also a decision support submodel for reasoning about and deriving the rules. The possibility for lifecycle automated assistance is demonstrated in terms of the automatic extraction of business rules from the decision structure. A system based on the metamodel has been implemented, including the extraction algorithm. This is the final report for Daniela Rosca's PhD fellowship. It describes the work we have done over the past year, current research and the list of publications associated with her thesis topic.
The ways in which human characteristics and especially human limitations provide input for the design of automated problem solving and decisions making systems are explored.
Geomagnetic disturbances can greatly disrupt the power grid operation. This is caused by low-frequency changes in the earth’s magnetic field, which upon interaction with the deep earth conductivity induces a changing electric field at the earth’s surface. This in turn induces quasi-direct currents which have the potential to cause protective devices to operate, widespread damage to high-voltage transformers, or voltage collapse due to induced reactive power losses. While these impacts have been known since the 1940s, only recently have standards for GMD response been implemented. Because these standards are heavily based on models, it is important to understand when it is appropriate to make certain modeling assumptions. In this work, implicit modeling uncertainty is quantified for the purpose of enhanced decision making for disturbance impact mitigation. Considering electromagnetic models, modeling assumptions of non-uniform grounding, imbalanced operation, transformer saturation, and geomagnetically induced currents, voltage estimation values are analyzed. Statistical characteristics of modeling uncertainty are obtained by analysis of synthetically generated data. Results statistically characterize geomagnetic disturbances modeling uncertainty, providing an important tool for impact mitigation.