Denial of service attacks and challenges in broadband wireless networks

Broadband wireless networks are providing internet and related services to end users. The three most important broadband wireless technologies are IEEE 802.11, IEEE 802.16, and Wireless Mesh Network (WMN). Security attacks and vulnerabilities vary amongst these broadband wireless networks because of differences in topologies, network operations and physical setups. Amongst the various security risks, Denial of Service (DoS) attack is the most severe security threat, as DoS can compromise the availability and integrity of broadband wireless network. In this paper, we present DoS attack issues in broadband wireless networks, along with possible defenses and future directions

An intelligent system for risk classification of stock investment projects

The proposed paper demonstrates that a hybrid fuzzy neural network can serve as a risk classifier of stock investment projects. The training algorithm for the regular part of the network is based on bidirectional incremental evolution proving more efficient than direct evolution. The approach is compared with other crisp and soft investment appraisal and trading techniques, while building a multimodel domain representation for an intelligent decision support system. Thus the advantages of each model are utilised while looking at the investment problem from different perspectives. The empirical results are based on UK companies traded on the London Stock Exchange

Theory of deferred action: Agent-based simulation model for designing complex adaptive systems

Deferred action is the axiom that agents act in emergent organisation to achieve predetermined goals. Enabling deferred action in designed artificial complex adaptive systems like business organisations and IS is problematical. Emergence is an intractable problem for designers because it cannot be predicted. We develop proof-of-concept, conceptual proto-agent model, of emergent organisation and emergent IS to understand better design principles to enable deferred action as a mechanism for coping with emergence in artefacts. We focus on understanding the effect of emergence when designing artificial complex adaptive systems by developing an exploratory proto-agent model and evaluate its suitability for implementation as agent-based simulation

Performance of voice over frame relay

Frame Relay (FR) represents one of the most important paradigm shifts in modern telecommunication. This technology is beginning to evolve from data only application to broad spectrum of multimedia users and potential to provide end users with cost effective transport of voice traffic for intra office communication. In this project the recent development in voice communication over Frame relay is investigated. Computer ssimulations were carried out using the powerful simulation software OPNET. Performance measures such as delays, jitter, and throughput are reported. It is evident from the results that real-time voice or video across a frame relay network providing acceptable performance is possible

Signal Detection for QPSK Based Cognitive Radio Systems using Support Vector Machines

Cognitive radio based network enables opportunistic dynamic spectrum access by sensing, adopting and utilizing the unused portion of licensed spectrum bands. Cognitive radio is intelligent enough to adapt the communication parameters of the unused licensed spectrum. Spectrum sensing is one of the most important tasks of the cognitive radio cycle. In this paper, the auto-correlation function kernel based Support Vector Machine (SVM) classifier along with Welch's Periodogram detector is successfully implemented for the detection of four QPSK (Quadrature Phase Shift Keying) based signals propagating through an AWGN (Additive White Gaussian Noise) channel. It is shown that the combination of statistical signal processing and machine learning concepts improve the spectrum sensing process and spectrum sensing is possible even at low Signal to Noise Ratio (SNR) values up to -50 dB

BB and BcB_c mesons with NRQCD and Clover actions

We present preliminary results from our study of the heavy-light spectrum and decay constants. For the heavy quark, we use NRQCD at various masses around and above the $b$ quark mass. For the first time, the heavy quark action and the heavy-light current consistently include corrections at second order in the non-relativistic expansion, as well as the leading finite $a$ corrections. The light quarks are simulated using a tadpole-improved Clover action at various masses in the strange and $c$ quark region.Comment: 6 Pages LaTex. Axis files of figures included. Joint writeup of two talks presented at LATTICE96(heavy quarks

The chiral phase transition and the role of vacuum fluctuations

We investigate the chiral phase transition in the quark-meson effective model using optimised perturbation theory to one loop. Certain terms in the free energy are frequently omitted in calculations, on the assumption that their contribution is negligible. We show that this is not necessarily the case, and that the order of the phase transition, as well as the critical temperature, depends heavily on which contributions are included.Comment: Talk given at the IX International Conference on Quark Confinement and the Hadron Spectrum (QCHS9), Madrid, 2010. 3 pages, 4 figure