Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w

Cryptography algorithms play a critical role in information technology against various attacks witnessed in the digital era. Many studies and algorithms are done to achieve security issues for information systems. The high complexity of computational operations characterizes the traditional cryptography algorithms. On the other hand, lightweight algorithms are the way to solve most of the security issues that encounter applying traditional cryptography in constrained devices. However, a symmetric cipher is widely applied for ensuring the security of data communication in constraint devices. In this study, we proposed a hybrid algorithm based on two cryptography algorithms PRESENT and Salsa20. Also, a 2D logistic map of a chaotic system is a

In the present survey 18 species of endo and ecto-parasites were recorded during the examination of 50 Mus musculus (Linnaeus, 1758) among 10 localities in Erbil city, of which 7 species were protozoan and as follows : Chilomastix bettencourti (da Fonseca 1915)82%; Giardia muris (Filice, 1952) 68%; Tritrichomonas muris (Grassi,1879)36%; Entamoeba histolytica (Schaudinn,1903) 24%; Entamoeba coli (Grassi,1879)32%; Eimeria sp. 28% and Trypanosoma musculi (Kendall,1906)2%; and 8 species were helminthes as follows: 4 Cestodes: Rodentolepis nana (von Siebold, 1852) 8%; Hymenolepis diminuta (Rudolphi, 1819)2%; larval stage of Echinococcus granulosus (Batsch, 1786)8%, Cysticercus fasciolaris (Rudolphi, 1808)6%, 4 Nematodes: Aspiculuris tetrapter