Fingerprint recognition is one among oldest procedures of identification. An important step in automatic fingerprint matching is to mechanically and dependably extract features. The quality of the input fingerprint image has a major impact on the performance of a feature extraction algorithm. The target of this paper is to present a fingerprint recognition technique that utilizes local features for fingerprint representation and matching. The adopted local features have determined: (i) the energy of Haar wavelet subbands, (ii) the normalized of Haar wavelet subbands. Experiments have been made on three completely different sets of features which are used when partitioning the fingerprint into overlapped blocks. Experiments are conducted on FVC2004 databases that have a four database; every database is eighty fingers and eight impressions per finger. The implemented recognition results of the proposed system show high recognition performance which is 100%.
There are two ways that the contract might be formed with (contracting between persons who are attended and contracting between absence persons).the need for determining the precise moment of the contract , is so clear because there is a specify period separate between the declaration of acceptance and the knowledge with it .and it is clear from the four theories known for jurisprudence (theory of the declaration of the acceptance, theory of exporting the acceptance , theory of the arrival of the acceptance , theory of the knowledge with the acceptance ) . It is difficult to promote one theory on another one if we look at each one and the justification of its supporters and what the opponents of each theory expose. Legal background and diff
... Show MoreIn this study, an efficient photocatalyst for dissociation of water was prepared and studied. The chromium oxide (Cr2O3) with Titanium dioxide (TiO2) nanofibers (Cr2O3-TNFs) nanocomposite with (chitosan extract) were synthesized using ecologically friendly methods such as ultrasonic and hydrothermal techniques; such TiO2 exhibits nanofibers (TNFs) shape struct
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Wireless sensor networks (WSNs) are emerging in various application like military, area monitoring, health monitoring, industry monitoring and many more. The challenges of the successful WSN application are the energy consumption problem. since the small, portable batteries integrated into the sensor chips cannot be re-charged easily from an economical point of view. This work focusses on prolonging the network lifetime of WSNs by reducing and balancing energy consumption during routing process from hop number point of view. In this paper, performance simulation was done between two types of protocols LEACH that uses single hop path and MODLEACH that uses multi hop path by using Intel Care i3 CPU (2.13GHz) laptop with MATLAB (R2014a). Th
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Low back pain a major causes of morbidity throughout the world and it is a most debilitating condition ,and can lead to decreased physical function ,compromised quality of life, and psychological distress.
Obesity is nowadays a pandemic condition. Obese subjects are commonly characterized by musculoskeletal disorders and particularly by non-specific LBP. However, the relationship between obesity and LBP remain to date unsupported by objective measurements of mechanical behavior of spine and it is morphology in obese subjects. &nb
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Low back pain a major causes of morbidity throughout the world and it is a most debilitating condition ,and can lead to decreased physical function ,compromised quality of life, and psychological distress. Obesity is nowadays a pandemic condition. Obese subjects are commonly characterized by musculoskeletal disorders and particularly by non-specific LBP. However, the relationship between obesity and LBP remain to date unsupported by objective measurements of mechanical behavior of spine and it is morphology in obese subjects. Key words: obesity, low back pain,
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In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.
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In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.
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A reduced-order extended state observer (RESO) based a continuous sliding mode control (SMC) is proposed in this paper for the tracking problem of high order Brunovsky systems with the existence of external perturbations and system uncertainties. For this purpose, a composite control is constituted by two consecutive steps. First, the reduced-order ESO (RESO) technique is designed to estimate unknown system states and total disturbance without estimating an available state. Second, the continuous SMC law is designed based on the estimations supplied by the RESO estimator in order to govern the nominal system part. More importantly, the robustness performance is well achieved by compensating not only the lumped disturbance, but also its esti
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