当社グループは 3,000 以上の世界的なカンファレンスシリーズ 米国、ヨーロッパ、世界中で毎年イベントが開催されます。 1,000 のより科学的な学会からの支援を受けたアジア および 700 以上の オープン アクセスを発行ジャーナルには 50,000 人以上の著名人が掲載されており、科学者が編集委員として名高い
。オープンアクセスジャーナルはより多くの読者と引用を獲得
700 ジャーナル と 15,000,000 人の読者 各ジャーナルは 25,000 人以上の読者を獲得
Edward Melnick
A natural epidemic is a disease that suddenly affects many individuals in a short time period, spreading from person to person in a locality where thedisease is not usually prevalent. The sudden outbreak of an epidemic is usually modeled as a random variable because it cannot be anticipated. Epidemics introduced by bioterrorists are planned events by intelligent adversaries, who might also introduce other terrorists’ activities that dependon the responses of the defenders. Since these events are not random, models maybe helpful for anticipating terrorist attacks. Since defendingagainst such attacks does not fit into the classical modeling paradigmbecause there is a scarcity of data, the defender must respond quickly, the attacker can also adapt new strategies in response to the actions of thedefender, new modeling strategies are required to improve the strategies of the defender. In this article, a Stackelberg model combined with fault trees is proposed for determining sequential optimal defense strategies for thedefender by identifying minimal cut sets of events that would most likely lead to a successful terrorist attack. Further, if the model can be formulated as a sequence of Markovian state changes based on default trees, a dynamic programming problem with the Bellman equation reduces the solution from evaluating a complex model to evaluating a sequence of simple problems