Simulating The Evacuation Of Students Attending Classes At The York University's Keele Campus
Notice bibliographique
Résumé
Since 1901, Canada has recorded over a thousand disasters (CDD, 2015). Ontario, a province possessing the highest number of incidents and evacuations, has adapted and learned from these experiences. The Emergency Movement and Civil Protection Act (1990) for example, legally obliged government organizations to maintain an emergency management program. Despite the measures set out by the government there were still a dominant paradigm of disaster, leading many to believe nothing could be done, when one occurs, or that they would not be affected one. Morris (2009) proved otherwise when it came to school shootings (a technological disaster). Morris illustrated awareness and preparedness in school led to resilient students who were less affected by the disasters. An important observation, as school disasters in particular have the ability to cause jarring impacts to a community. This Major Paper presents a simulation model that evacuates students attending classes at the York University Keele Campus. The agent-based model was constructed with data acquired from York University's Office of Institutional Planning & Analysis, York University?s Planning & Architectural Design branch of the Campus Services and Business Operation, and scientific journals. The model reproduces the number of registered students during the winter semester of 2014, from Monday to Sunday. This cycle stops, when a signal is given, informing of an evacuation. From this instance, students, proceeded through a series of steps before arriving to one of four predetermined evacuation zones. These steps included: 1) pre-movement 2) descend the corresponding multi-floored building and 3) travel at an assigned speed to the evacuation zone. Forty evacuation scenarios, ten for each evacuation zones, were generated at varying times of day, throughout the week. The gathered times were further analyzed with three variables: the student population, the number of buildings holding classes, and the percentage of buildings within the vicinity of an evacuation zone. The student population demonstrated a logarithmic relationship with time, where evacuation time became more consistent as the population sized increased. When it came to the analysis of the number of buildings holding classes, the greater number of buildings, meant the buildings were more spread out and resulted in similar evacuation time for all four evacuation zones. The last case examined the percentage of buildings within the vicinity of an evacuation zone, half of the evacuation zones possessed a linear relationship, where the greater percentages meant a shorter arrival time.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».