In this paper, a miniaturized 2 × 2 electro-optic plasmonic Mach– Zehnder switch (MZS) based on metal–polymer–silicon hybrid waveguide is presented. Adiabatic tapers are designed to couple the light between the plasmonic phase shifter, implemented in each of the MZS arms, and the 3-dB input/output directional couplers. For 6 µm-long hybrid plasmonic waveguide supported by JRD1 polymer (r33= 390 pm/V), a π-phase shift voltage of 2 V is obtained. The switch is designed for 1550 nm operation wavelength using COMSOL software and characterizes by 2.3 dB insertion loss, 9.9 fJ/bit power consumption, and 640 GHz operation bandwidth

Cipher security is becoming an important step when transmitting important information through networks. The algorithms of cryptography play major roles in providing security and avoiding hacker attacks. In this work two hybrid cryptosystems have been proposed, that combine a modification of the symmetric cryptosystem Playfair cipher called the modified Playfair cipher and two modifications of the asymmetric cryptosystem RSA called the square of RSA technique and the square RSA with Chinese remainder theorem technique. The proposed hybrid cryptosystems have two layers of encryption and decryption. In the first layer the plaintext is encrypted using modified Playfair to get the cipher text, this cipher text will be encrypted using squared

The study aimed at identifying the strategic gaps in the actual reality of the management of public organizations investigated to determine the strategy used based on the study model. The study relied on the variable of the general organization strategy in its dimensions (the general organization strategy, the organization's political strategy and the defense strategy of the organization) The sample of the study was (General Directorate of Traffic, Civil Status Directorate and Civil Defense Directorate), formations affiliated to the Ministry of the Interior, for the importance of the activity carried out by these public organizations by providing them In order to translate the answers into a quantitative expression in the analysi

A Strength Pareto Evolutionary Algorithm 2 (SPEA 2) approach for solving the multi-objective Environmental / Economic Power Dispatch (EEPD) problem is presented in this paper. In the past fuel cost consumption minimization was the aim (a single objective function) of economic power dispatch problem. Since the clean air act amendments have been applied to reduce SO2 and NOX emissions from power plants, the utilities change their strategies in order to reduce pollution and atmospheric emission as well, adding emission minimization as other objective function made economic power dispatch (EPD) a multi-objective problem having conflicting objectives. SPEA2 is the improved version of SPEA with better fitness assignment, density estimation, an

Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an