diff --git a/models/Application_examples/FindAdvisor.mp b/models/Application_examples/FindAdvisor.mp index de0fa912b07b2027f562604678f31b1da8f3863e..7c4fa4089cd7a1440fc8664530b906cd7a9a985b 100644 --- a/models/Application_examples/FindAdvisor.mp +++ b/models/Application_examples/FindAdvisor.mp @@ -1,23 +1,22 @@ /* Model of Find Advisor -Created by Kristin Giammarco. +Created by Kristin Giammarco in 2015. Edited by Keane Reynolds in July, 2021. Edited by Pamela Dyer in July and August, 2021. Purpose: To show that human interaction and organizational -processes can be modeled as well as technological system -and subsystem interactions. +processes can be modeled using MP. Description: Alternate behaviors for humans are described -in terms of possible decisions they could make. In this -example, the process of a student finding an advisor for a -potentially MP-related research topic is modeled. To do so, -it only uses roots, composites, "or" blocks, and COORDINATE -statements. Users should inspect this model when considering -the process of finding a mentor, or looking to learn how to -use COORDINATE statements to make a model. Because the same -modeling approach can be used for human systems and -technological systems, it becomes possible to have +in terms of possible decisions they could make. This example +models the process of a student finding an advisor for a +potentially MP-related research topic. To do so, it uses root +events, composite events, atomic events, "or" logic +( ... | ... ), and COORDINATE statements. Users should inspect +this model when considering the process of finding a mentor, +or looking to learn how to use COORDINATE statements to make a +model. Because the same modeling approach can be used for human +systems and technological systems, it becomes possible to have integrated behavior models containing both humans and technology to study the possible interactions among them. @@ -28,8 +27,7 @@ human interactions modeling; behavior, human systems Instructions: Run for Scope 1 (there is no iteration in this example, so increasing the scope will not produce more -scenarios). "Sequence" mode yields views very similar to -the UML or SysML Sequence Diagrams. +scenarios). Scope 1: 3 traces in less than 1 sec. ==========================================================*/ diff --git a/models/Application_examples/First_Responder.mp b/models/Application_examples/First_Responder.mp index 0586f2d6dfc76153951ad488b6cdd847c774cf81..e6ff0e9876893069c861a32e21a99c605de08672 100644 --- a/models/Application_examples/First_Responder.mp +++ b/models/Application_examples/First_Responder.mp @@ -4,31 +4,52 @@ Created by Jordan Bryant in May, 2016. Edited by Keane Reynolds in July, 2021. Edited by Pamela Dyer in July and August, 2021. -Purpose: To demonstrate a first responder scenario -involving the administation of a rescue medication (Narcan) -to an overdose victim by a First Responder or a Bystander. +Purpose: To demonstrate unexpected emergent behavior in a +first responder scenario involving the administation of a +rescue medication (Narcan) to an overdose victim. Description: This model demonstrates the administration of Narcan by bystanders in order to determine the possible consequences of allowing or even encouraging bystanders to -administer medication in an overdose scenario. The model -accomplishes this using "or" blocks and COORDINATE -statements. Users may find this model useful when looking -into COORDINATE statements, or scenarios with bystanders -who could possibly become involved in whatever process -is being modeled. - -References: +administer medication in an overdose scenario. + +This model is a draft snapshot of a high school student's +senior capstone project studying safety issues pertaining to +a proposed process for layperson administration of a rescue +medication called Narcan (Bryant 2016). It produces various +possible scenarios that could emerge based on the possible +actions of bystanders and first responders and their +interactions with the victim. The original analysis goal was +to determine the time savings in having bystanders prepared to +administer the rescue medication, but an unexpected behavior +was found among the generated a trace that neither student nor +mentor considered. For example, trace 6 prompted the idea to +modify the process to include the bystander marking the victim +to indicate the dose and time they administered while waiting +for the first responders. Being a work in progress, this model +is incomplete, but this version of it was archived in order to +capture the state of the model in which the unexpected emergent +behavior was first observed. + +References: +Bryant, Jordan (2016). "Using Monterey Phoenix to analyze an +alternative process for administering Naloxone," mentored by +Kristin Giammarco (NPS) and Rick Schlegel (EMT). +Available online: +http://scienceandmathacademy.com/academics/srt4/student_work/2016/bryant_jordan.pdf + +Giammarco, Kristin, and Kathleen Giles. "Verification and validation +of behavior models using lightweight formal methods." In Disciplinary +convergence in systems engineering research, pp. 431-447. Springer, +Cham, 2018. +Available online: +https://calhoun.nps.edu/handle/10945/58237 Search terms: behavior, first responder; behavior, bystander; behavior, unexpected; behavior, emergent -Instructions: Run for Scope 1. The model was developed to -compare response times, but unexpected scenarios emerged -that were previously not considered. Trace 6 and others -show a double administration of Narcan by both the -bystander and the first responder. +Instructions: Run for Scope 1. Scope 1: 8 traces in less than 1 sec. ==========================================================*/