Effect of aging on synthesis of graft copolymer of EPDM and styrene (EPDM‐g‐PS)

The effect of aging on synthesis by the graft copolymerization of styrene onto random ethylene–propylene–diene monomer with benzoyl peroxide (BPO) as the initiator is described. Results showed that yields of graft copolymer are increased in the first 10 min. After 10 min, the total polymer produced has a maximum at about 25 min. However, the portion of the graft copolymer is decreased and the portion of the pure polystyrene is increased. In addition, the influence factors, such as reaction time, temperature, BPO concentrations and styrene concentrations, effect of solvents on the extent of graft copolymerization were discussed. The extent of grafted copolymerization was verified by hexane and acetone Soxhlet (solvent extraction). © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 4809–4813, 2006     

Economic land evaluation for agricultural resource management in Northern Thailand

This paper describes a GIS-based system, EconSuit, that supports dynamic assessment of economic land suitability for major economic crops in Northern Thailand. Prior to economic land evaluation, a physical land suitability index is computed using a fuzzy set approach in GIS. The procedure bypasses crop modeling and permits suitability to be defined in a continuous scale with a graphic interface enabling a user to dynamically assign diagnostic factors and weights for physical land evaluation. Economic land evaluation is accomplished by assigning field survey data to land mapping units using spatial interpolation. Unit costs of inputs and outputs can be entered through the graphic user interface, allowing constant updates of economic values in the system. Scenarios of agricultural land use planning may be formulated by users depending on policy or economic circumstances.     

Providing fault tolerance in wireless access networks

Research and development on network survivability has largely focused on public switched telecommunications networks and high-speed data networks with little attention on the survivability of wireless access networks supporting cellular and PCS communications. This article discusses the effects of failures and survivability issues in PCS networks with emphasis on the unique difficulties presented by user mobility and the wireless channel environment. A simulation model to study a variety of failure scenarios on a PCS network is described, and the results show that user mobility significantly worsens network performance after failures, as disconnected users move among adjacent cells and attempt to reconnect to the network. Thus, survivability strategies must be designed to contend with spatial as well as temporal network behavior. A multilayer framework for the study of PCS network survivability is presented. Metrics for quantifying network survivability are identified at each layer. Possible survivability strategies and restoration techniques for each layer in the framework are also discussed     

Practical real-time intrusion detection using machine learning approaches

The growing prevalence of network attacks is a well-known problem which can impact the availability, confidentiality, and integrity of critical information for both individuals and enterprises. In this paper, we propose a real-time intrusion detection approach using a supervised machine learning technique. Our approach is simple and efficient, and can be used with many machine learning techniques. We applied different well-known machine learning techniques to evaluate the performance of our IDS approach. Our experimental results show that the Decision Tree technique can outperform the other techniques. Therefore, we further developed a real-time intrusion detection system (RT-IDS) using the Decision Tree technique to classify on-line network data as normal or attack data. We also identified 12 essential features of network data which are relevant to detecting network attacks using the information gain as our feature selection criterions. Our RT-IDS can distinguish normal network activities from main attack types (Probe and Denial of Service (DoS)) with a detection rate higher than 98% within 2 s. We also developed a new post-processing procedure to reduce the false-alarm rate as well as increase the reliability and detection accuracy of the intrusion detection system.