Minimal Proof Search for Modal Logic K Model Checking

Most modal logics such as S5, LTL, or ATL are extensions of Modal Logic K. While the model checking problems for LTL and to a lesser extent ATL have been very active research areas for the past decades, the model checking problem for the more basic Multi-agent Modal Logic K (MMLK) has important applications as a formal framework for perfect information multi-player games on its own. We present Minimal Proof Search (MPS), an effort number based algorithm solving the model checking problem for MMLK. We prove two important properties for MPS beyond its correctness. The (dis)proof exhibited by MPS is of minimal cost for a general definition of cost, and MPS is an optimal algorithm for finding (dis)proofs of minimal cost. Optimality means that any comparable algorithm either needs to explore a bigger or equal state space than MPS, or is not guaranteed to find a (dis)proof of minimal cost on every input. As such, our work relates to A* and AO* in heuristic search, to Proof Number Search and DFPN+ in two-player games, and to counterexample minimization in software model checking.Comment: Extended version of the JELIA 2012 paper with the same titl

Tree-based Intelligent Intrusion Detection System in Internet of Vehicles

The use of autonomous vehicles (AVs) is a promising technology in Intelligent Transportation Systems (ITSs) to improve safety and driving efficiency. Vehicle-to-everything (V2X) technology enables communication among vehicles and other infrastructures. However, AVs and Internet of Vehicles (IoV) are vulnerable to different types of cyber-attacks such as denial of service, spoofing, and sniffing attacks. In this paper, an intelligent intrusion detection system (IDS) is proposed based on tree-structure machine learning models. The results from the implementation of the proposed intrusion detection system on standard data sets indicate that the system has the ability to identify various cyber-attacks in the AV networks. Furthermore, the proposed ensemble learning and feature selection approaches enable the proposed system to achieve high detection rate and low computational cost simultaneously.Comment: Accepted in IEEE Global Communications Conference (GLOBECOM) 201

Resonances and Spectral Shift Function for the semi-classical Dirac operator

We consider the self-adjoint operator $H=H_0+V$, where $H_0$ is the free semi-classical Dirac operator on $R^3$. We suppose that the smooth matrix-valued potential $V=O(^{-\delta}), \delta>0,$ has an analytic continuation in a complex sector outside a compact. We define the resonances as the eigenvalues of the non-selfadjoint operator obtained from the Dirac operator $H$ by a complex distortions of $R^{3}$.We establish an upper bound $O(h^{-3})$ for the number of resonances in any compact domain. For $\delta>3$, a representation of the derivative of the spectral shift function $\xi(\lambda,h)$ related to the semi-classical resonances of $H$ and a local trace formula are obtained. In particular, if $V$ is an electro-magnetic potential, we deduce a Weyl-type asymptotic of the spectral shift function. As a by-product, we obtain an upper bound $O(h^{-2})$ for the number of resonances close to non-critical energy levels in domains of width $h$ and a Breit-Wigner approximation formula for the derivative of the spectral shift function.Comment: 39 pages, 1 figur

On Plane Curves with Double and Triple Points

We describe in simple geometric terms the Hodge filtration on the cohomology groups of the complement U in the projective plane of a curve C with ordinary double and triple points. Relations to Milnor algebra, syzygies of the Jacobian ideal and pole order filtration on the second cohomology of U are given.Comment: 10 page

Developing a knowledge management approach to support managing credit risk in Jordanian banks

It is becoming increasing clear that; in banks; the sharing of knowledge amongst the senior executives has not been as effective as it should have been. The lack of knowledge amongst senior executives about the level of risks taken in sub-prime lending, the resulting "toxic assets‟ and the global nature of the instruments used to spread risks is said to be the main contributing reason for the current worldwide crisis in banks. Banks in Jordan, the focus of this study, are not immune from the exposure to the risks. The banking sector in Jordan is the most important in the Jordanian national economy and has effectively contributed to improving economic development through its important role in mobilising savings and channelling them into different fields of investment. Therefore, the overall aim of this research is to propose that developing a knowledge management (KM) approach to support managing credit risk will help banks in general, and Jordanian banks in particular, in improving the process of managing credit risk. To reach the aim, several objectives have been constructed: 1. Reviewing current status of KM and its relationship with CRM 2. Developing a scale to measure KM behaviour and practices 3. Determining current KM status in Jordanian banks 4. Building a CR decision support system using internal implicit knowledge to reduce the rate of defaults. As a result of this research, a KM approach has been developed to support managing credit risk. The approach contains the following steps: identify, measure, analyse, improve, and evaluate. Using the new KM approach, the main conclusion of this research suggest that considering credit risk management and KM together gives a much stronger basis for banks to manage credit risk