An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co

The aim of the current study is to identify the level of goal conflict with twelfth-grade students in South Sharqiah/ Sultanate of Oman according to gender and specialization. The study used the descriptive method. A scale of (28) items was developed and divided into six dimensions: time pressure, goal achievement, limit of power, limit of budget, incompatible strategies, and unclear task. To validate the scale, it was piloted (40) students. The scale was administered to a sample of (402) students (209) males in the Governorate of South Sharqiah. The results showed that the conflict level was high in “unclear task”, and an average conflict level in “limit of power”. Other dimensions (goal achievement, time pressure, limit of powe

In this paper, a description of a design for new DES block cipher, namely DES64X and DES128X. The goals of this design, a part of its security level, are large implementation flexibility on various operating systems as well as high performances. The high level structure is based on the principle of DES and Feistel schema, and proposes the design of an efficient key-schedule algorithm which will output pseudorandomsequences of subkeys. The main goal is to reach the highest possible flexibility, in terms of round numbers, key size, and block size. A comparison of the proposed systems on 32-bit, 64-bit operating system, using 32-bit and 64-bit Java Virtual Machine (JVM), showed that the latter has much better performance than the former.

The effected of the long transmission line (TL) between the actuator and the hydraulic control valve sometimes essentials. The study is concerned with modeling the TL which carries the oil from the electro-hydraulic servovalve to the actuator. The pressure value inside the TL has been controlled by the electro-hydraulic servovalve as a voltage supplied to the servovalve amplifier. The flow rate through the TL has been simulated by using the lumped π element electrical analogy method for laminar flow. The control voltage supplied to servovalve can be achieved by the direct using of the voltage function generator or indirect C⁺⁺ program connected to the DAP-view program built in the DAP-card data acqu

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

Grabisch and Labreuche have recently proposed a generalization of capacities, called the bi-capacities. Recently, a new approach for studying bi-capacities through introducing a notion of ternary-element sets proposed by the author. In this paper, we propose many results such as bipolar Mobius transform, importance index, and interaction index of bi-capacities based on our approach.

The synthesis of new substituted cobalt Phthalocyanine (CoPc) was carried out using starting materials Naphthalene-1,4,5, tetracarbonic acid dianhydride (NDI) employing dry process method. Metal oxides (MO) alloy of (60%Ni₃O₄ 40%-Co₃O₄ ) have been functionalized with multiwall carbon nanotubes (F-MWCNTs) to produce (F-MWCNTs/MO) nanocomposite (E2) and mixed with  CoPc to yield (F-MWCNT/CoPc/MO) (E3). These composites were investigated using different analytical and spectrophotometric methods such as ¹H-NMR (0-18 ppm), FTIR spectroscopy in the range of (400-4000cm-1), powder X-rays diffraction (PXRD, 2θ ^o = 10-80), Raman spectroscopy (0-4000 cm^-1), and UV-Visib