One of the most popular and legally recognized behavioral biometrics is the individual's signature, which is used for verification and identification in many different industries, including business, law, and finance. The purpose of the signature verification method is to distinguish genuine from forged signatures, a task complicated by cultural and personal variances. Analysis, comparison, and evaluation of handwriting features are performed in forensic handwriting analysis to establish whether or not the writing was produced by a known writer. In contrast to other languages, Arabic makes use of diacritics, ligatures, and overlaps that are unique to it. Due to the absence of dynamic information in the writing of Arabic signatures, it will be more difficult to attain greater verification accuracy. On the other hand, the characteristics of Arabic signatures are not very clear and are subject to a great deal of variation (features’ uncertainty). To address this issue, the suggested work offers a novel method of verifying offline Arabic signatures that employs two layers of verification, as opposed to the one level employed by prior attempts or the many classifiers based on statistical learning theory. A static set of signature features is used for layer one verification. The output of a neutrosophic logic module is used for layer two verification, with the accuracy depending on the signature characteristics used in the training dataset and on three membership functions that are unique to each signer based on the degree of truthiness, indeterminacy, and falsity of the signature features. The three memberships of the neutrosophic set are more expressive for decision-making than those of the fuzzy sets. The purpose of the developed model is to account for several kinds of uncertainty in describing Arabic signatures, including ambiguity, inconsistency, redundancy, and incompleteness. The experimental results show that the verification system works as intended and can successfully reduce the FAR and FRR.
In this work Nano crystalline (Cu2S) thin films pure and doped 3% Al with a thickness of 400±20 nm was precipitated by thermic steaming technicality on glass substrate beneath a vacuum of ~ 2 × 10− 6 mbar at R.T to survey the influence of doping and annealing after doping at 573 K for one hour on its structural, electrical and visual properties. Structural properties of these movies are attainment using X-ray variation (XRD) which showed Cu2S phase with polycrystalline in nature and forming hexagonal temple ,with the distinguish trend along the (220) grade, varying crystallites size from (42.1-62.06) nm after doping and annealing. AFM investigations of these films show that increase average grain size from 105.05 nm to 146.54 nm
... Show MoreAn efficient combination of Adomian Decomposition iterative technique coupled Elzaki transformation (ETADM) for solving Telegraph equation and Riccati non-linear differential equation (RNDE) is introduced in a novel way to get an accurate analytical solution. An elegant combination of the Elzaki transform, the series expansion method, and the Adomian polynomial. The suggested method will convert differential equations into iterative algebraic equations, thus reducing processing and analytical work. The technique solves the problem of calculating the Adomian polynomials. The method’s efficiency was investigated using some numerical instances, and the findings demonstrate that it is easier to use than many other numerical procedures. It has
... Show MoreAerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.
... Show MoreThis research shows the experimental results of the bending moment in a flexible and rigid raft foundation rested on dense sandy soil with different embedded depth throughout 24 tests. A physical model of dimensions (200mm*200mm) and (320) mm in height was constructed with raft foundation of (10) mm thickness for flexible raft and (23) mm for rigid raft made of reinforced concrete. To imitate the seismic excitation shaking table skill was applied, the shaker was adjusted to three frequencies equal to (1Hz,2Hz, and 3Hz) and displacement magnitude of (13) mm, the foundation was located at four different embedment depths (0,0.25B = 50mm,0.5B = 100mm, and B = 200mm), where B is the raft width. Generally, the maximum bending
... Show MoreWireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi
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