􀀤􀁅􀁖􀁗􀁕􀁄􀁆􀁗􀀑􀀃􀀬􀁑􀀃􀁗􀁋􀁌􀁖􀀃􀁕􀁈􀁖􀁈􀁄􀁕􀁆􀁋􀀏􀀃􀀤􀁊􀀤􀁏􀀔􀀐􀁛􀀬􀁑􀁛􀀶􀁈􀀕􀀃􀀋􀀤􀀤􀀬􀀶􀀌􀀃􀁆􀁒􀁐􀁓􀁒􀁘􀁑􀁇􀀃􀁄􀁏􀁏􀁒􀁜􀁖􀀃􀁓􀁕􀁈􀁓􀁄􀁕􀁈􀁇􀀃􀁉􀁒􀁕􀀃􀁇􀁌􀁉􀁉􀁈􀁕􀁈􀁑􀁗􀀃􀁛􀀃􀀋􀀓􀀑􀀖􀀏􀀃􀀓􀀑􀀙􀀃􀁄􀁑􀁇􀀃􀀓􀀑􀀜􀀌􀀃􀁅􀁜􀀃􀁐􀁈􀁏􀁗􀁌􀁑􀁊􀀃 􀁗􀁋􀁈􀁐􀀃 􀁌􀁑􀀃 􀁄􀁑􀀃 􀁈􀁙􀁄􀁆􀁘􀁄􀁗􀁈􀁇􀀃 􀁔􀁘􀁄􀁕􀁗􀁝􀀃 􀁗􀁘􀁅􀁈􀀃 􀀋􀀕􀀑􀀘􀀍􀀔􀀓􀀐􀀖􀀃 􀁗􀁒􀁕􀁕􀀌􀀑􀀃 􀀤􀀤􀀬􀀶􀀃 􀁚􀁌􀁗􀁋􀀃 􀁇􀁌􀁉􀁉

High-resolution imaging of celestial bodies, especially the sun, is essential for understanding dynamic phenomena and surface details. However, the Earth's atmospheric turbulence distorts the incoming light wavefront, which poses a challenge for accurate solar imaging. Solar granulation, the formation of granules and intergranular lanes on the sun's surface, is important for studying solar activity. This paper investigates the impact of atmospheric turbulence-induced wavefront distortions on solar granule imaging and evaluates, both visually and statistically, the effectiveness of Zonal Adaptive Optics (AO) systems in correcting these distortions. Utilizing cellular automata for granulation modelling and Zonal AO correction methods,

The rotor dynamics generally deals with vibration of rotating structures. For designing rotors of a high speeds, basically its important to take into account the rotor dynamics characteristics. The modeling features for rotor and bearings support flexibility are described in this paper, by taking these characteristics of rotor dynamics features into standard Finite Element Approach (FEA) model. Transient and harmonic analysis procedures have been found by ANSYS, the idea has been presented to deal with critical speed calculation. This papers shows how elements BEAM188 and COMBI214 are used to represent the shaft and bearings, the dynamic stiffness and damping coefficients of journal bearings as a matrices have been found

Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

In this paper, a least squares group finite element method for solving coupled Burgers' problem in   2-D is presented. A fully discrete formulation of least squares finite element method is analyzed, the backward-Euler scheme for the time variable is considered, the discretization with respect to space variable is applied as biquadratic quadrangular elements with nine nodes for each element. The continuity, ellipticity, stability condition and error estimate of least squares group finite element method are proved.  The theoretical results  show that the error estimate of this method is . The numerical results are compared with the exact solution and other available literature when the convection-dominated case to illustrate the effic

    Identification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed