Session Program

Abstract - The financial fraud risk assessment requires expertise concerning the audit methodology and the risk assessment of business processes. The assessment of financial fraud risks is a significant challenge for independent, external auditors chiefly when dealing with the audit in an information technology (IT) environment. A meta-analysis financial fraud risk governance model taking into account an IT environment and based on fuzzy inference system is proposed in this paper. The fuzzy set theory and fuzzy logic are employed to deal with actual business audits, which do not always concern dichotomic fraud risk conditions. The inputs of the proposed fuzzy financial fraud risk governance system concern meta-analysis factors related to the fundamental domains of risk in IT audit. The input premise space comprises the effective identity and access protocol, system development, control of business operations, and change in systems or applications. Results demonstrate that the proposed approach enables supporting the operational risk management to promote the operational efficiency by identifying, measuring, and disclosing events (risk conditions) both in terms of qualitative (stratification) and quantitative (score) analysis. The fuzzy IT financial fraud risk system is able to work as a first barrier to reflect the adequacy of the information technologies and systems used to avoid risk in the financial fraud governance.

Abstract - Identification methods based on biometrics are going through great expansion lately. Therefore in this article we propose a realization of experimental multibiometric system for laboratory verification of theoretical knowledge. The system identifies hand veins using biometric characteristics of hand contour and bloodstream on the dorsum of the hand. Moreover we alternatively put forward a fuzzy approach for segmentation of veins and estimation of the vein system by maximum curvature method.

Abstract - Wireless Sensor Networks (WSNs) facilitate efficient data gathering requirements occurring in indoor and outdoor environments. A great deal of WSNs operates by sensing the area-of-interest (AOI) and transmitting the obtained data to a sink/(s). The transmitted data is then utilized in decision making processes. In this regard, security of raw and relayed data is both crucial and susceptible to malicious attempts targeting the task of the network which occurs on the wireless transmission medium. A node, when compromised, may deliberately forward data packets selectively. When this happens, nodes adjacent to the malicious nodes cannot identify the malevolent node and mitigate the effects of the attacks. In this study, we introduce a fuzzy path selection approach that efficiently mitigates single selective forwarding attacks in WSNs. Performance of our proposed approach and its evaluations are simulated and obtained. Our experimental results show that our approach is an effective solution to serve as a defense mechanism in terms of the efficiency metrics, such as Half of the Nodes Alive (HNA), Total Remaining Energy (TRE), and Packet Drop Ratio (PDR).

Abstract - Movement sequence of a real air combat flight contains valuable information that can be used to infer artificial air combat learning. There are different ways to control unmanned aerial vehicles for a given flight path. But identifying the best move at the time being relative to an enemy air craft requires learning flight experience from real air combat fighters. This paper shows how to set up learning and control environment with adaptive neuro fuzzy inference system for maneuver decisions using real F-16 flight information. Real flight information is also utilized to justify the test results.

Abstract - This paper proposes structures of Takagi-Sugeno fuzzy (TSF) controllers along with approaches to design these structures dedicated to the azimuth and pitch position control of twin rotor aerodynamic systems (TRASs). The azimuth and the pitch positions are separately controlled using Single Input-Single Output (SISO) control system structures. Two Proportional-Integral-Derivative (PID) TSF controllers are suggested for azimuth position control, and they are build around linear PID controller structures. A PI and a PID TSF controller are suggested for pitch position control by fuzzifying the linear PI and PID controller structures. The validation of the new TFS controllers is carried out on nonlinear TRAS laboratory equipment. The performance of the SISO control systems with the new TFS controllers is compared with two linear controllers tuned by a metaheuristic Gravitational Search Algorithm optimizer.