Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time. In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as DCT, DWT, DFT, PCA, LBP, SURF, SIFT, etc., or deep learning techniques such as CNN, DNN, Alex Net CNN, VGG-16, SVM, Squeeze Net, Google Net, MobileNetV2, etc. The effort will make it easier for researchers, especially those who are new to the field, to have a brief understanding of the trend of employing deep learning in a trustworthy biometric for the identification and recognition of human identification.
To obtain the approximate solution to Riccati matrix differential equations, a new variational iteration approach was proposed, which is suggested to improve the accuracy and increase the convergence rate of the approximate solutons to the exact solution. This technique was found to give very accurate results in a few number of iterations. In this paper, the modified approaches were derived to give modified solutions of proposed and used and the convergence analysis to the exact solution of the derived sequence of approximate solutions is also stated and proved. Two examples were also solved, which shows the reliability and applicability of the proposed approach.
Smear zone is usually formed around the prefabricated vertical drains (PVD’s) due to mandrel driving. The geotechnical properties of the soil in this zone exhibit significant changes that affect the performance of the PVD’s. The most relevant property in this respect is the coefficient of permeability. So far, no serious attention is paid to investigate the effects of shearing under large shear strains on the geotechnical properties of the soft soil in Fao region. In this study, an extensive laboratory testing program was conducted to assess the characteristics of the smear zone with an emphasis on the permeability coefficient of Fao soft soil. The results show that the permeability of the smear zone is about 70% of
... Show MoreThe quality of groundwater in the Al-Hawija area was assessed using a water quality index. Data of nine physico-chemical parameters of 28 groundwater wells were used to calculate the water quality index (WQI). A heterogeneous water quality was reported, where in close proximity to the Lesser Zab River (LZR), it has low WQI values and permissible for human consumptions due to the dilution processes by fresh water; whereas, it becomes deteriorated in areas located far away the river. The values of WQI ranges from 22 to 336, indicating a good to very poor groundwater quality.
The current study aims to identify soil pollutants from heavy metals The study utilized 40 topsoil (5 cm) samples, which adapted and divided into seven regions lies in Baghdad governorate, included (Al-Husainya,(Hs) Al-Doura (Do), Sharie Al-Matar (SM), Al-Waziria (Wz), Nharawan (Nh), Abu Ghraib (Abu) and Al-Mahmoodyia (Mh)). Spatial distribution maps of Nickel (Ni), Manganese (Mn), Lead (Pb) and Zinc (Zn) were created for Baghdad city using Geographic Information Systems (GIS). The concentrations of four heavy metals in the soil of different area of Baghdad were measured and observed using XRF instrument. The result found highest values of Pb and Zn at the middle of the Baghdad in (Wz
ZnS nanoparticles were prepared by a simple microwave irradiation method under mild condition. The starting materials for the synthesis of ZnS quantum dots were zinc acetate (R & M Chemical) as zinc source, thioacetamide as a sulfur source and ethylene glycol as a solvent. All chemicals were analytical grade products and used without further purification. The quantum dots of ZnS with cubic structure were characterized by X-ray powder diffraction (XRD), the morphology of the film is seen by scanning electron microscopy (SEM). The particle size is determined by field effect scanning electron microscopy (FESEM), UV-Visible absorption spectroscopy and XRD. UV-Visible absorption spectroscopy analysis shows that the absorption peak of the as-prep
... Show MoreSensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar
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