We present a multiagent-based framework for crowd simulation in large space urban area on a standalone PC. We use Belief-Desire-Intention (BDI) for modeling individual agent behavior. We use RVO for handling a large number of agents. The simulation engine is Unity3d which also take care of the visualization. We experimented our framework with up to 20;000 agents; navigating them from origins to destinations. We found that we can navigate agents successfully. The execution time increases when the number of agent increase. The visualization becomes slow when the number of agent is higher than 1000 agents. We found that the the simulation steps also increases when the number of agent is not higher than 5005.

One well known and long-lasting problem in the video tracking is that one particular algorithm would perform well on a certain environmental characteristic. Whenever the characteristic in the scene changes; the performance of the algorithm affected. This research proposes a multiagent-based for video tracking system. The agents follow the odd-man out strategy; which odd agents will be credited less than the favorite ones. We tested our algorithm against two tough videos. The results show that our approach yield satisfactory outcomes. The final tracking results are always within the boundary of the groundtruth; given that there are two out of five correct results.

This paper proposes a solution for network monitoring and forecasting of user behavior activities in social network applications. This method can describe the log of various types of data; behaviors and traces in the power monitoring system. The monitoring system analyzes by using Pentaho BI open source software to extract the data. In this study; the monitoring system analyzes and identifies types of TCP packets. The monitoring and packet capturing system was implemented on the campus's wire and wireless LAN network at the Faculty of Information Technology; King Mongkut's University of Technology North Bangkok during active hours. The system implementation uncovered the percentage of several social media types mostly used in the network during each time period. The result showed that several kinds of data packet such as packet loss; TCP or SYN flooding provided useful information for the network administrator to improve and manage the system.

This study aims to synthesize cultural knowledge on Thai-Khmer textiles by using content analysis. Research population is articles, books, and related research from various databases such as ThaiLIS, Digital Research Information Center (DRIC), Science Direct, Emeral, H.W.Wilson, and 125 data from Department of Cultural of Thailand database. Analysis form and information science and library science framework were used in categorizing knowledge and knowledge structure, additionally, Faceted Analysis approach was used in analyzing attributes of knowledge. There were 2 major aspects of the synthesis as 1) 2 classes of tangible Thai-Khmer textile culture which are 1.1) 7 subclasses of tangible and moveable textile culture as weaving tools, materials used to build weaving tools, raw materials for weaving, types of weaving textiles, clothes and common equipment textiles, textile patterns, and 21 subclasses of textile color. 1.2) textile culture is tangible but immovable consisting of 2 classes as places where textile were produced, 5 subclasses of places where textiles were used and 2) 2 classes of intangible textile culture which are 2.1) 3 subclasses of textile culture concepts as teachings, beliefs, and 15 subclasses of values and 2.2) textile culture norms consisting of 4 subclasses as ways of life, traditions, rituals, and 14 subclasses of principles which relates to Thai-Khmer textiles. Attributes of knowledge which are from Faceted Analysis approach are categorized into 2 classes and each class consists of 4 subclasses and 16 divisions. Each category contains explanation, scope, and significant attributes of knowledge which is divided into 16 auxiliary tables as table 1 a list of weaving tools, table 2 a list of materials used to build weaving tools, table 3 a list of weaving raw materials, table 4 a list of dying materials, table 5 categories and names of textiles, table 6 a list of textile types, table 7 a list of textile patterns, table 8 a list of textile colors, table 9 a list of places related to textiles, table 10 teachings, table 11 beliefs, table 12 values, table 13 ways of life, table 14, traditions, table 15 rituals, and table 16 principles. The significant attributes of knowledge are gathered from faceted analysis approach which sorts concepts and categorizes content. The findings are able to apply as principles in scoping cultural knowledge of Thai-Khmer textiles and as guidelines in developing cultural knowledge of Thai-Khmer textiles database.

Shapley value is regarded as a fair payoff distribution concept for cooperative agents. While traditional cooperative game assume superadditivity and non-externalty; real world environments do not hold this assumption. We show that in linear production game; the environment is non-superadditive is with externalties. In such environment; grand coalition does not provide optimal solution to the system. Consequently; applying traditional shapley value does not provide an attractive payoff to agents. In addition; fairness may also be lost because individual payoffs are less than singleton coalition values. We show how this environments may occur and how we can propose a more attractive and; still; fair payoffs to agents.

Today; the MEDLINE is an important repository containing more than 26 million citations and abstracts in the fields of medicine; while PubMed provides free access to MEDLINE and links to full-text articles. MEDLINE abstracts becomes a potential source of new knowledge in medical field. However; it is time-consuming and labour-intensive to find knowledge from MEDLINE abstracts; when a search returns much abstracts and each may contain a large volume of information. Therefore; this work aims to present a method of summarizing clinical knowledge from a MEDLINE abstract. The main mechanisms of the proposed method are driven on natural language processing (NLP) and text filtering techniques. The case study of this work is to summarize the clinical knowledge from a MEDLINE abstracts relating to cervical cancer in clinical trials. In the evaluation stage; the actual results obtained from a domain expert are used to compare the predicted results. After testing by recall; precision; and F-score; they return the satisfactory results; where the average of recall; precision; and F-measure are 0.84; 1.00; and 0.91 respectively.