This paper gives an overview of identification of linear systems. It covers the classical approach of parametric methods using Maximum Likelihood and Predicion Error Methods, as well all classical non-parametric methods through spectral analysis. It also covers very recent techniques dealing with convex formulations by regularization of FIR and ARX models, as well as new alternatives to spectra...

Biometric identification systems are principally related to the information security as well as data protection and encryption. The paper proposes a method to integrate biometrics data encryption and authentication into error correction techniques. The normal methods of biometric templates matching are replaced by a more powerful and high quality identification approach based on Grӧbner bases c...

A great challenge in the biomedical engineering is the non-invasive assessment of the physiological changes occurring inside the human body. Specifically, detecting the abnormalities in the human eye is extremely difficult due to the various complexities associated with the process. Retina is the significant part of the human eye which can reflect the abnormal changes in the human eye. Hence, r...

The Internet of Things (IoT) has started to empower the future many industrial and mass-market applications. Localization techniques are becoming key add location context IoT data without human perception intervention. Meanwhile, newly-emerged Low-Power Wide-Area Network (LPWAN) technologies have advantages such as long-range, low power consumption, cost, massive connections, capability for com...

Fast and accurate network traffic identification is becoming essential for network management, high quality of service control and early detection of network traffic abnormalities. Techniques based on statistical features of packet flows have recently become popular for network classification due to the limitations of traditional port and payload based methods. In this paper, we propose a metho...

We participated in the i2b2 smoking status classification challenge task. The purpose of this task was to evaluate the ability of systems to automatically identify patient smoking status from discharge summaries. Our submission included several techniques that we compared and studied, including hot-spot identification, zero-vector filtering, inverse class frequency weighting, errorcorrecting ou...

We present an approach to design of fault tolerant computing systems. In this paper, a technique is employed that enable the combination of several codes, in order to obtain flexibility in the design of error correcting codes. Code combining techniques are very effective, which one of these codes are turbo codes. The Algorithm-based fault tolerance techniques that to detect errors rely on the c...