intrusion detection in wireless networks has been a challenging researchproblem in network security for more than half a century. this paper presents anovel intrusion detection method based on received signal strength acceptancetest (rssat) to improve the ids capabilities in anomaly-based host-basedintrusion detection systems (hids). the new system can identify suspiciousbehaviors detecting ano...

Acoustic emission technology relies on detecting and converting elastic (acoustic) waves from solids undergoing internal structural irreversible changes into electrical signals. This technique represents a non-destructive testing method used in industrial fields such as weld monitoring, proof testing, flaw detection of pressure vessels. In this study, the applicability acoustic for monitoring d...

 Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...

in this paper, we examine target detection in the surveillance channels of fm-based passive bistatic radars (fbpbrs) in the presence of interference signals in the reference channels of these systems. to do so, we propose a new signal conditioning algorithm to remove interference signals form reference channel. simulation results show that the proposed signal conditioning algorithm outperform t...

A partial discharge (PD) is the dissipation of energy caused by the buildup of localized electric field intensity. In high voltage devices such as transformers, this buildup of charge and its release can be symptomatic of problems associated with aging, such as floating components and insulation breakdown. This is why PD detection is used in power systems to monitor the state of health of high ...

For complex perceptual tasks that are characterized by object occlusion and non stationarity recognition systems with adaptive signal processing front ends have been developed These systems rely on hand crafted symbolic object models which constitutes a knowledge acquisition bottleneck We propose an approach to automate object model acquisition that relies on the detection of signal processing ...

 Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...

For complex perceptual tasks that are characterized by object occlusion and non-stationarity, recognition systems with adaptive signal processing front-ends have been developed. These systems rely on hand-crafted symbolic object models, which constitutes a knowledge acquisition bottleneck. We propose an approach to automate object model acquisition that relies on the detection and resolution of...