This paper presents a study of a syndrome coding scheme for different binary linear error correcting codes that refer to the code families such as BCH, BKLC, Golay, and Hamming. The study is implemented on Wyner’s wiretap channel model when the main channel is error-free and the eavesdropper channel is a binary symmetric channel with crossover error probability (0 < Pe ≤ 0.5) to show the security performance of error correcting codes while used in the single-staged syndrome coding scheme in terms of equivocation rate. Generally, these codes are not designed for secure information transmission, and they have low equivocation rates when they are used in the syndrome coding scheme. Therefore, to improve the transmiss

Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

Expansion the engineering consultancy offices in the universities of Iraq, about (14) offices, leading to increas the competition between them, especially after the great trends of Iraqi government agencies to use the academic experiences and their efficiencies in general, due to non-existence of the engineering qualification in the government institutions to do the engineering designs ,supervision of projects and other engineering works which are practicing by the engineering consultancy offices in order to get the best performance of the work.Within this serious competition, needing a specific approach to enable government agencies to choose the optimal and alternative consultancy office to meet specific project and not rely on cronyis

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

Ficus (FIC) leaf extract used as corrosion inhibitor for carbon steel alloy (C.S) in two corrosive environments (saline and acidic) with four concentrations (1, 2, 3 and 4 ppm) at varied temperature range between (298-328 K) using electrochemical polarization measurements. The importance of this work focused on the use the green chemistry that is far from the chemical materials effect. The results of polarization presented the FIC inhibitor consider a mixed type (anodic and cathodic) inhibitor. Tafel curve used to evaluate the corrosion inhibition activity. In a saline medium, the best inhibitor efficiency reaches to (87%) in 2 ppm and IE% reach to (99%) for HCl medium inhibited by 1ppm. Langmuir isotherm obeys the study by thermodynamic pa