Mermaid

2018 ◽  
Vol 9 (3) ◽  
pp. 38-53
Author(s):  
F. S. Conte ◽  
A. Ahmadi
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
Visual Basic ◽  
National Standards ◽  
Decision Support Tools ◽  
Microsoft Excel ◽  
Support Tool ◽  
Support Tools ◽  
Visual Basic For Application ◽  
The U.S

Mermaid is a new decision support tool for managing shellfish growing areas. It is written in Visual Basic for Application (VBA) language and uses Microsoft Excel for input, calculation, and output modules. The program automatically imports the regulatory agency's data and generates scattergrams that can be used as decision support tools to help decide which shellfish growing areas should be closed and which ones should be open for harvest. The Mermaid program uses the equations developed by the Pearl model that provide more sensitive and accurate measures of sanitation safety for consumption of shellfish, and are more accurate than the U.S. National Standards.

Spreadsheets as Knowledge Documents

2011 ◽  
pp. 521-537 ◽  
Author(s):  
Stephen Burgess ◽  
Don Schauder
Keyword(s):  
Knowledge Management ◽  
Decision Support ◽  
Small Business ◽  
Information Management ◽  
Explicit Knowledge ◽  
Decision Support Tool ◽  
Decision Support Tools ◽  
Support Tool ◽  
Applied Model ◽  
Support Tools

How should a small business decide whether and in what ways to use Web technology for interactions with customers? This case describes the creation of a practical decision support tool (using a spreadsheet) for the initiation and development of small business Web sites. Decisions arise from both explicit and tacit knowledge. Using selected literature from a structuration theory, information management and knowledge management, decision support tools are characterized as knowledge documents (communication agents for explicit knowledge). Understanding decision support tools as knowledge documents sheds light on their potentialities and limitations for knowledge transfer, and assists in maximizing their potentialities. The case study deploys three levels of modeling: a high-level structuration model of the interplay between information management and knowledge management, a conceptual model of small-business decision-making, and an applied model the practical decision support tool, itself. An action-research methodology involving experts and stakeholders validated the development of conceptual categories and their instantiation in the practical tool.

Decision Support Tools in the Evaluation of Risk for Violence

2015 ◽  
Author(s):  
Adam J. E. Blanchard ◽  
Catherine S. Shaffer ◽  
Kevin S. Douglas
Keyword(s):  
Risk Assessment ◽  
Decision Support ◽  
Empirical Evaluation ◽  
Decision Support Tool ◽  
Assessment Instrument ◽  
Professional Judgment ◽  
Decision Support Tools ◽  
Support Tool ◽  
Risk Assessment Instrument ◽  
Support Tools

Professionals often utilize some form of structured approach (i.e., decision support tool or risk assessment instrument) when evaluating the risk of future violence and associated management needs. This chapter presents an overview of decision support tools that are used to assist professionals when conducting a violence risk assessment and that have received considerable empirical evaluation and professional uptake. The relative strengths and weaknesses of the two main approaches to evaluations of risk (actuarial and structured professional judgment) are discussed, including a review of empirical findings regarding their predictive validity. Following a summary of commonalities among the tools, this chapter provides a brief description of 10 decision support tools focusing on their applicability and purpose, content and characteristics, and available empirical research. Finally, the chapter concludes with a discussion of several critical considerations regarding the appropriate use and selection of tools.

scholarly journals Toward a User-Centered Design of a Weather Forecasting Decision-Support Tool

2017 ◽  
Vol 98 (2) ◽  
pp. 373-382 ◽  
Author(s):  
Elizabeth M. Argyle ◽  
Jonathan J. Gourley ◽  
Zachary L. Flamig ◽  
Tracy Hansen ◽  
Kevin Manross
Keyword(s):  
Decision Support ◽  
Weather Forecasting ◽  
Decision Support Tool ◽  
The United States ◽  
Usability Evaluation ◽  
Error Rates ◽  
Decision Support Tools ◽  
User Centered Design ◽  
Support Tool ◽  
Support Tools

ABSTRACT Hazard Services is a software toolkit that integrates information management, hazard alerting, and communication functions into a single user interface. When complete, National Weather Service forecasters across the United States will use Hazard Services for operational issuance of weather and hydrologic alerts, making the system an instrumental part of the threat management process. As a new decision-support tool, incorporating an understanding of user requirements and behavior is an important part of building a system that is usable, allowing users to perform work-related tasks efficiently and effectively. This paper discusses the Hazard Services system and findings from a usability evaluation with a sample of end users. Usability evaluations are frequently used to support software and website development and can provide feedback on a system’s efficiency of use, effectiveness, and learnability. In the present study, a user-testing evaluation assessed task performance in terms of error rates, error types, response time, and subjective feedback from a questionnaire. A series of design recommendations was developed based on the evaluation’s findings. The recommendations not only further the design of Hazard Services, but they may also inform the designs of other decision-support tools used in weather and hydrologic forecasting. Incorporating usability evaluation into the iterative design of decision-support tools, such as Hazard Services, can improve system efficiency, effectiveness, and user experience.

scholarly journals Worker-Recovered Companies in Brazil: self-management process assessment by applying multi-criteria decision support tools

2017 ◽  
Vol 14 (2) ◽  
pp. 249
Author(s):  
Fernanda Santos Araujo ◽  
Vicente Nepomuceno Oliveira ◽  
Denise Alvarez ◽  
Helder Costa
Keyword(s):  
Decision Support ◽  
Management Practices ◽  
Decision Support Tool ◽  
Self Management ◽  
Management Process ◽  
Decision Support Tools ◽  
Process Assessment ◽  
Support Tool ◽  
Support Tools ◽  
Means Of Production

Company recovery is a practice developed by workers who, in the imminence of becoming unemployed, negotiate or fight for access to the means of production of bankrupting companies, and start to manage them collectively, guided by the principles of self-management.  Nevertheless, how to assess self-management in worker-recovered companies (WRCs)? The criteria selected by a bibliographic review on the concept of self-management were used in dealing with the data collected by the Brazilian WRCs national mapping. A multi-criteria decision support tool was used to build a model for analyzing and classifying the companies in three categories related to their form of management. The multi-criteria approach allowed to create an assessment of self-management practices in the WRCs studied.

A Model-Based Mission Planning and Decision Support Tool

2009 ◽  
Author(s):  
Simon M. Jessop ◽  
Thomas C. Cook
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
Relational Model ◽  
Maintenance Optimization ◽  
Decision Support Tools ◽  
Modeling Tool ◽  
Support Tool ◽  
Model Based ◽  
Support Tools ◽  
Mission Profile

Impact Technologies developed a model-based decision support Framework that facilitates the use and development of decision support tools in a CBM environment. The Framework leverages existing CBM and PHM data to provide enhanced automated strategic analysis. Its modular structure promotes reusability of components to expedite development of new decision capabilities, making it extensible to many different operational environments. The Framework also embraces open architecture and standardized data interfaces for increased supportability and upgradeability. An advanced probability-based mission readiness forecasting and assessment tool developed by Impact Technologies for the U.S. Navy was used to illustrate how the proposed Framework facilitates the assembly of independent decision support tools to provide a high fidelity knowledge product. In this application the Framework combined three separate functional areas — a mission profile modeling tool, a system relational model, and a maintenance optimization module. The mission profile modeling tool provided the ability to create functional representations of multi-layered complex systems for any mode of operation, accounting for different machinery line-ups, redundancy, system-to-system interactions, and component and sub-system criticalities. The system relational model provided the overall system probability of failure calculated based on the current and projected system configuration and usage. The maintenance optimization module determined the safest and most cost-effective time to perform required and opportunistic maintenance. The resulting software product enables the comparison of multiple what-if scenarios where the scheduling of maintenance and logistics support activities can be optimized based on resource availability and the propagation effects of those actions can be measured in terms of readiness at any level within the system hierarchy. A visual assessment of the ship’s probability of completing the prescribed mission of any combination of ship operations (e.g., anti-surface warfare, non-combat operations, or mine warfare) can be generated so corrective actions in the form of maintenance or changes to mission operations can be evaluated. The tool incorporates several novel approaches including fusion of multiple independent low-level indicators to predict overall system readiness, methodologies to account for the interactive effects of interconnected subsystems, and a risk-based optimization to select and schedule the optimal maintenance schedule. This paper summarizes the features of the model-based decision support tool Framework and the mission readiness software application developed using this architecture.

scholarly journals Ten Simple Rules for Researchers Who Want to Develop Web Apps

2021 ◽  
Author(s):  
Sheila Saia ◽  
Natalie Nelson ◽  
Sierra Young ◽  
Stanton Parham ◽  
Micah Vandegrift
Keyword(s):  
Decision Support ◽  
Web Applications ◽  
Decision Support Tool ◽  
Lessons Learned ◽  
Decision Support Tools ◽  
Support Tool ◽  
Support Tools ◽  
Simple Rules ◽  
Web App ◽  
Scenario Testing

Growing interest in data-driven, decision-support tools across the life sciences and physical sciences has motivated development of web applications, also known as web apps. Web apps can help disseminate research findings and present research outputs in ways that are more accessible and meaningful to the general public--from individuals, to governments, to companies. Specifically, web apps enable exploration of scenario testing and policy analysis (i.e., to answer “what if?”) as well as co-evolution of scientific and public knowledge. However, the majority of researchers developing web apps receive little formal training or technical guidance on how to develop and evaluate the effectiveness of their web-based decision support tools. Take some of us for example. We (Saia and Nelson) are agricultural and environmental engineers with little experience in web app development, but we are interested in creating web apps to support sustainable aquaculture production in the Southeast. We had user (i.e., shellfish growers) interest, a goal in mind (i.e., develop a new forecast product and decision-support tool for shellfish aquaculturalists), and received funding to support this work. Yet, we experienced several unexpected hurdles from the start of our project that ended up being fairly common hiccups to the seasoned web app developers among us (Young, Parham). As a result, we share the following Ten Simple Rules, which highlight take home messages, including lessons learned and practical tips, of our experience as burgeoning web app developers. We hope researchers interested in developing web apps draw insights from our (in)experience as they set out on their decision support tool development journey.

Abstract P305: Assessing the Feasibility of Implementing a Clinical Decision Support Tool in the Office-Based Setting: Experiences From the American College of Cardiology's Improving Continuous Cardiac Care (IC3) Pilot Program

2011 ◽  
Vol 4 (suppl_1) ◽  
Author(s):  
Katie Kehoe ◽  
Kristi Mitchell ◽  
Fran Fiocchi ◽  
Mary Anne Elma ◽  
Tracie Breeding ◽  
...  
Keyword(s):  
Decision Support ◽  
Data Collection ◽  
Clinical Decision Support ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Valuable Insight ◽  
Decision Support Tools ◽  
Patient Encounter ◽  
Support Tool ◽  
Support Tools

BACKGROUND: Clinical decision support tools have been used to improve guideline adherence amidst challenges during implementation in the office-based setting. As such, these tools require pilot testing to assess feasibility and ease of use. METHODS: The IC 3 Program, now known as the PINNACLE Registry, is a prospective, practice-based QI program designed to capture and report outpatient performance measures (PM) and provide decision support tools to optimize the quality of care delivered to outpatient cardiac patients. ACC/AHA guidelines and PMs for CAD, atrial fibrillation, heart failure and hypertension were translated into key data elements collected systematically via a paper-based data collection form (DCF). In September 2008, four offices participated in a 2-week pilot to assess the feasibility of implementing the DCF. A self-reported survey was administered, followed by a phone interview with participants. RESULTS: Results of the implementation pilot found that all respondents agreed with the overall layout of the DCF and that the data collected were typical of that routinely collected during a patient encounter. Physicians completed the DCFs more often( 57.1%) than other staff in the office. However, nurses or other staff(80%) were more likely to fax the data into the ACC. DCFs were faxed generally at the end of the week (66.7%). Most practices entered data both during and after the patient encounter (60%). Time for data entry ranged from 10-20 minutes. Roughly, half of the participants found data collection easy and others found it time consuming. One physician suggested making changes in the office work flow for future data collection. CONCLUSION: The pilot of the DCF provided valuable insight regarding the feasibility of collecting and reporting data, as well as the usability of a paper-based DCF in the outpatient setting. Although challenging, implementation of a paper-based decision support tool in practices can be successful. These findings demonstrate that it takes a team effort with clear delineation of roles and responsibilities to insure practice-wide adoption of a systematic QI process for accurately collecting and reporting clinical data.

scholarly journals A survey on the perceived need and value of decision-support tools for joint mitigation of air pollution and climate change in cities

Elem Sci Anth ◽  
2017 ◽  
Vol 5 ◽  
Author(s):  
Erika von Schneidemesser ◽  
Rebecca D. Kutzner ◽  
Julia Schmale†
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Decision Support ◽  
Air Quality ◽  
Regional Scale ◽  
Decision Support Tool ◽  
Mitigation Measures ◽  
Decision Support Tools ◽  
Support Tool ◽  
Support Tools

Decision-support tools are increasingly popular for informing policy decisions linked to environmental issues. For example, a number of decision-support tools on transport planning provide information on expected effects of different measures (actions, policies, or interventions) on air quality, often combined with information on noise pollution or mitigation costs. These tools range in complexity and scale of applicability, from city to international, and include one or several polluting sectors. However, evaluation of the need and utility of tools to support decisions on such linked issues is often lacking, especially for tools intended to support local authorities at the city scale. Here we assessed the need for and value of combining air pollution and climate change mitigation measures into one decision-support tool and the existing policy context in which such a tool might be used. We developed a prototype decision-support tool for evaluating measures for coordinated management of air quality and climate change; and administered a survey in which respondents used the prototype to answer questions about demand for such tools and requirements to make them useful. Additionally, the survey asked questions about participants’ awareness of linkages between air pollution and climate change that are crucial for considering synergies and trade-offs among mitigation measures. Participants showed a high understanding of the linkages between air pollution and climate change, especially recognizing that emissions of greenhouse gases and air pollutants come from the same source. Survey participants were: European, predominantly German; employed across a range of governmental, non-governmental and research organizations; and responsible for a diversity of issues, primarily involving climate change, air pollution or environment. Survey results showed a lack of awareness of decision-support tools and little implementation or regular use. However, respondents expressed a general need for such tools while also recognizing barriers to their implementation, such as limited legal support or lack of time, finances, or manpower. The main barrier identified through this study is the mismatch between detailed information needed from such tools to make them useful at the local implementation scale and the coarser scale information readily available for developing such tools. Significant research efforts at the local scale would be needed to populate decision-support tools with salient mitigation alternatives at the location of implementation. Although global- or regional-scale information can motivate local action towards sustainability, effective on-the-ground implementation of coordinated measures requires knowledge of local circumstances and impacts, calling for active engagement of the local research communities.

scholarly journals Model-Based Decision Support Tools at Jugos S.A. Concentrated Fruit Juice Plant

2020 ◽  
Vol 50 (4) ◽  
pp. 255-268
Author(s):  
Aníbal M. Blanco ◽  
M. Susana Moreno ◽  
Carolina Taraborelli ◽  
Flavio D’Angelo ◽  
Facundo Iturmendi ◽  
...  
Keyword(s):  
Decision Support ◽  
User Interfaces ◽  
Decision Support Tool ◽  
Raw Material ◽  
Mixed Integer ◽  
Support Tool ◽  
Support Tools ◽  
Optimal Target ◽  
And Storage

We describe the development of a decision-support tool to assist in the operations of a large concentrated apple and pear juice plant. The tool’s objective is to generate detailed schedules of clarified juice batches to be produced in the following weeks considering incoming fruit forecasts, commercial commitments, and infrastructural constraints. The tool is based on two interactive modules, PLANNER and SIMOPT, with different and complementary purposes. Each module is based on mixed-integer models with specific inputs, outputs, and user interfaces. PLANNER consists of three submodules: (i) planning assigns a batch of concentrated juice to be produced on a specific day, taking into account cleaning activities, rest days, raw material availability, and production and storage constraints; (ii) preprocessing organizes juice orders in batches; and (iii) pooling provides a detailed monitoring of semielaborated juice in storage pools in terms of inventories and sugar and acid content. Finally, SIMOPT provides a detailed optimal operative condition of the plant together with a thorough calculation of specific costs. This information is used by PLANNER to evaluate the corresponding economic objective functions. Besides providing optimal target conditions to the plant and feasible production schedules, the developed tools generate production guidelines in the long term and allow performing scenario studies.

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