Abstract-Decisionmaking and emergency communication system play an important role in rescue process when emergency situations happen. The rescue process will be more effective if we have appropriate decision making method and accessible emergency communication system. In this paper, we propose a centralized rescue model for people with disabilities. The decision making method to decide which volunteers should help which disabled persons is proposed by utilizing the auction mechanism. The GIS data are used to present the objects in a large-scale disaster simulation environment such as roads, buildings, and humans. The Gama simulation platform is used to test our proposed rescue simulation model.

Abstract-In this paper, we present a task allocation model for search and rescue persons with disabilities in case of disaster. The multi agent-based simulation model is used to simulate the rescue process. Volunteers and disabled persons are modeled as agents, which each have their own attributes and behaviors. The task of volunteers is to help disabled persons in emergency situations. This task allocation problem is solved by using combinatorial auction mechanism to decide which volunteers should help which disabled persons. The disaster space, road network, and rescue process are also described in detail. The RoboCup Rescue simulation platform is used to present proposed model with different scenarios.

Abstract-Vietnamese word segmentation is an important step in Vietnamese natural language processing such as text categorization, text summary, and automated machine translation. The problem with Vietnamese word segmentation is complicated because Vietnamese words are not always separated by a space. One word can include one or more syllables depending on the context. This paper proposes a method for Vietnamese word segmentation based on the mutual information among the syllables combined with dynamic programming. With this method, we can achieve an accuracy rate of about 90% with a raw text corpus.