The design and implementation of an active router architecture that enables flexible network programmability based on so-called "user components" will be presents. This active router is designed to provide maximum flexibility for the development of future network functionality and services. The designed router concentrated mainly on the use of Windows Operating System, enhancing the Active Network Encapsulating Protocol (ANEP). Enhancing ANEP gains a service composition scheme which enables flexible programmability through integration of user components into the router's data path. Also an extended program that creates and then injects data packets into the network stack of the testing machine will be proposed, we will call this program

CdSe quantum dots possess a tuning energy gap which can control gap values according to the size of the quantum dots, this is made the material able to absorb the wavelengths within visible light. A simple model is provided for the absorption coefficient, optical properties, and optical constants for CdSe quantum dots from the size 10nm to 1nm with the range of visible region between (300-730) nm at room temperature. It turns out that there is an absorption threshold for each wavelength, CdSe quantum dots begin to absorb the visible spectrum of 1.4 nm at room temperature for a wavelength of 300 nm. It has been noted that; when the wavelength is increased, the absorption threshold also increases. This applies to the optical propertie

Use of electrodes that provide a high surface area for reaction, such as Nickel foam and Carbon Fiber Felt, has proven highly efficient in treating wastewater. In this study, a mixture of dyes (Eosin Y, Methylene Blue, and Methylene Violet) was treated using Ni foam as a cathode and carbon fiber felt as an anode in the Electro-Fenton process, relying on iron waste, such as iron filings, as the catalyst source. The analysis characterization of electrodes and iron filings was determined by Energy dispersive X-Ray (EDX) and Scanning electron microscopy (SEM) tests. The results showed high efficiency in decomposing the dye mixture. The highest Re % 96.4591 which attained after accomplishing the experiments based on Response Surface Method (RSM)

In this work, the design and implementation of a smart energy metering system has been developed. This system consists of two parts: billing center and a set of distributed smart energy meters. The function of smart energy meter is measuring and calculating the cost of consumed energy according to a multi-tariff scheme. This can be effectively solving the problem of stressing the electrical grid and rising consumer awareness. Moreover, smart energy meter decreases technical losses by improving power factor. The function of the billing center is to issue a consumer bill and contributes in locating the irregularities on the electrical grid (non-technical losses). Moreover, it sends the switch off command in case of the consumer bill is not

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

In this paper, an approach for object tracking that is inspired from human oculomotor system is proposed and verified experimentally. The developed approach divided into two phases, fast tracking or saccadic phase and smooth pursuit phase. In the first phase, the field of the view is segmented into four regions that are analogue to retinal periphery in the oculomotor system. When the object of interest is entering these regions, the developed vision system responds by changing the values of the pan and tilt angles to allow the object lies in the fovea area and then the second phase will activate. A fuzzy logic method is implemented in the saccadic phase as an intelligent decision maker to select the values of the pan and tilt angle based

The deployment of UAVs is one of the key challenges in UAV-based communications while using UAVs for IoT applications. In this article, a new scheme for energy efficient data collection with a deadline time for the Internet of things (IoT) using the Unmanned Aerial Vehicles (UAV) is presented. We provided a new data collection method, which was set to collect IoT node data by providing an efficient deployment and mobility of multiple UAV, used to collect data from ground internet of things devices in a given deadline time. In the proposed method, data collection was done with minimum energy consumption of IoTs as well as UAVs. In order to find an optimal solution to this problem, we will first provide a mixed integer linear programming m