The traditional centralized network management approach presents severe efficiency and scalability limitations in large scale networks. The process of data collection and analysis typically involves huge transfers of management data to the manager which cause considerable network throughput and bottlenecks at the manager side. All these problems processed using the Agent technology as a solution to distribute the management functionality over the network elements. The proposed system consists of the server agent that is working together with clients agents to monitor the logging (off, on) of the clients computers and which user is working on it. file system watcher mechanism is used to indicate any change in files. The results were presente

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

This paper presents a comparison between the electroencephalogram (EEG) channels during scoliosis correction surgeries. Surgeons use many hand tools and electronic devices that directly affect the EEG channels. These noises do not affect the EEG channels uniformly. This research provides a complete system to find the least affected channel by the noise. The presented system consists of five stages: filtering, wavelet decomposing (Level 4), processing the signal bands using four different criteria (mean, energy, entropy and standard deviation), finding the useful channel according to the criteria’s value and, finally, generating a combinational signal from Channels 1 and 2. Experimentally, two channels of EEG data were recorded fro

Abstract: Background: Optical biosensors offer excellent properties and methods for detecting bacteria when compared to traditional analytical techniques.  It allows direct detection of many biological and chemical materials.  Bacteria are found in the human body naturally non-pathogenic and pathologically, as they are found in other living organisms.  One of these bacteria is Escherichia coli (E. coli) which are found in the human body in its natural and pathogenic form. E.coli bacteria cause many diseases, including Stomach, intestines, urinary system infections, and others. The aim of this study: is sensing and differentiation between normal flora and pathogenic E.coli. Material and method:

Staphylococci are common commensals in human beings, yet certain species are pathogenic. Staphylococcus aureus, particularly, is a very virulent human pathogen. The capacity of staphylococci to sense the density of bacterial cell, i.e., quorum, and thereafter respond via genetic modifications is attributable to one primary mechanism known as accessory gene regulator (Agr). Agr's extracellular signal is a peptide that is posttranslationally modified with a thiolactone molecule. Agr is in charge of the upregulation of numerous exotoxins and hydrolyzing enzymes, as well as the downregulation of many colonization determinants, under circumstances of high cell density. This modulation is critical for the scheduling synthesis of virul

The aim of this paper is to present method for solving ordinary differential equations of eighth order with two point boundary conditions. We propose two-point osculatory interpolation to construct polynomial solution.

In this study, the behavior of square helical piles models (5×5) mm² embedded in expansive soil bed overlaying a layer of sandy soil was investigated. The sand layer 200mm thickness was compacted into four sub layers in a steel container with diameter 400mm in size. Sandy soil layer was compacted into two relative densities 40% and 80%. The bed of ثءحties 40% and 80%.The bed of o00mm in size.Sandy soil layer was compacted into two relative densities 40% and 80%.The bed of oexpansive soil 300mm thickness was compacted into six sub layers on sandy soil layer. Model tests are performed with helical pile length 350mm, 400mm and 450mm and with helix diameter 15mm and 20mm. Also, one helix and double helix were

The Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process

Fractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal ima