In the past decade, biomedical instrumentations have witnessed major developments and now it is very easy to measure human biomedical electrical signals. One of these signals is the brain waves, known as electroencephalogram (EEG) signals, which became very easy to be measured using portable devices and dry electrodes. This opens the way for the use of brain waves in different applications rather than the biomedical diagnosis. One of the most recent nonmedical applications for brain waves is the biometric authentication. Brain waves have some advantages which are not present in the commonly used identifiers, such as face and fingerprints, making them robust to spoof attacks. However, brain waves still face many challenges with reference to permanence and uniqueness. In this study, the authors discuss the employment of brain signals for human recognition tasks and focus on the challenges facing these signals towards the deployment of a practical biometric system. This study, also, provides a comprehensive review of the proposed approaches developed in EEG-based biometric authentication systems.
In this paper, a novel technique is adopted for human recognition based on eye blinking waveform extracted from electro-oculogram signals. For this purpose, a database of 25 subjects is collected using Neurosky Mindwave headset. Then, the eye blinking signal is extracted and applied for identification and verification tasks. The pre-processing stage includes empirical mode decomposition to isolate electro-oculogram signal from brainwaves. Then, time delineation of the eye blinking waveform is utilized for feature extraction. Finally, linear discriminant analysis is adopted for classification. Based on the achieved results, the proposed system can identify subjects with best accuracy of 97.3% and verify them with an equal error rate of 3.7%. The obtained results in this paper confirm that eye blinking waveform carries discriminant information and is therefore appropriate as a basis for human recognition task.
Abstract-Using digital signal processing in genomic field is a key of solving most problems in this area such as prediction of gene locations in a genomic sequence and identifying the defect regions in DNA sequence. It is found that, using DSP is possible only if the symbol sequences are mapped into numbers. In literature many techniques have been developed for numerical representation of DNA sequences. They can be classified into two types, Fixed Mapping (FM) and Physico Chemical Property Based Mapping (PCPBM ( . The open question is that, which one of these numerical representation techniques is to be used? The answer to this question needs understanding these numerical representations considering the fact that each mapping depends on a particular application. This paper explains this answer and introduces comparison between these techniques in terms of their precision in exon and intron classification. Simulations are carried out using short sequences of the human genome (GRch37/hg19). The final results indicate that the classification performance is a function of the numerical representation method.
In this study, the effects of different precursor concentrations on the growth and characteristics properties of the zinc oxide (ZnO) nanorods (NRs) synthesized by using modified and conventional chemical bath deposition (CBD) methods were investigated. The morphologic, structural and optical properties of synthesized ZnO NRs with different precursor concentrations were studied using various characterization techniques. The experimental results show that the varying precursor concentration of the reactants has a remarkable and significant effect on the growth and characteristics properties of ZnO NRs. In addition, the characteristic properties of ZnO NRs grown using the modified method showed significantly improved and enhanced properties. The average length of grown ZnO NRs increased with increased precursor concentration; it can be seen that longer ZnO NRs have been investigated using the modified CBD methods. The ZnO NRs synthesized at 0.05 M using the modified method were grown with high aspect ratios than the ZnO NRs grown using conventional means which were 25 and 11, respectively. The growth rate increased with increased precursor concentration; it can be observed that a higher growth rate was seen using the modification CBD method. Furthermore, XRD results for the two cases reveal that the grown ZnO samples were a nanorod-like in shape and possessed a hexagonal wurtzite structure with high crystal quality. No other phases from the impurity were observed. The diffraction peaks along (002) plane became higher, sharper and narrower as precursor concentration increased, suggesting that the crystalline quality of ZnO NRs grown using the modified method was more enhanced and better than conventional methods. However, optical studies show that the transmittance at each concentration was more than two times higher than the transmittance using the modified CBD method. In addition, optical studies demonstrated that the ZnO NRs grown by using modified and conventional methods had a direct Eg in the range of (3.2–3.26) eV and (3.15–3.19) eV, respectively. It was demonstrated in two methods that ZnO NRs grown at a precursor concentration 0.05 M gave the most favorable result, since the NRs had best characteristic properties.
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