The detection of diseases affecting wheat is very important as it relates to the issue of food security, which poses a serious threat to human life. Recently, farmers have heavily relied on modern systems and techniques for the control of the vast agricultural areas. Computer vision and data processing play a key role in detecting diseases that affect plants, depending on the images of their leaves. In this article, Fuzzy- logic based Histogram Equalization (FHE) is proposed to enhance the contrast of images. The fuzzy histogram is applied to divide the histograms into two subparts of histograms, based on the average value of the original image, then equalize them freely and independently to conserve the brightness of the image. The prop

Cadmium oxide thin films were prepared by D.C magnetron plasma sputtering using different voltages (700, 800, 900, 1000, 1100 and 1200) Volt. The Cadmium oxide structural properties using XRD analysis for just a voltage of 1200 volt at room temperature after annealing in different temperatures (523 and 623) K were studied .The results show that the films prepared at room temperature have some peaks belong to cadmium element along the directions (002), (100), (102) and (103) while the other peaks along the directions of (111), (200) and (222) belong to cadmium oxide. Annealed samples display only cadmium oxide peaks. Also, the spectroscopic properties of plasma diagnostic for CdO thin films were determined and the results show that the el

The organization uses many techniques and methods to ensure that they will succeed and adapted with velocity change in the internal and external environment by decision taking, especially strategic decisions.

Strategic decisions are very important for organization success because it can predict the future and deal with uncertainty, in this circumstances they need accurate and comprehensive information to make effective strategic decision.

To achieve that purpose it must owned successful Strategic Information System ( SIS ) and determined the critical success factors for this system ,which can assisted the worker to focus on the important activities to develop it.

The provision of openings in serviceable reinforced concrete beams may result in a substantial decline in the beam's capacity and integrity, indicating the necessity of opening strengthening. The present study investigates the experimental response of reinforced concrete T-beams with multiple web-strengthened openings disposed in shear span to static and impact loads. Fourteen RC T-beams were tested in two groups, each of seven beams. The first group was tested under static loading up to failure, while the second group was tested under repeated impact loading until the width of shear cracks reached 0.3 mm. The residual static strengths of the beams subjected to impact loading were then determined. The test variables considered were

In this research, experimental and numerical studies were carried out to investigate the performance of encased glass-fiber-reinforced polymer (GFRP) beams under fire. The test specimens were divided into two peer groups to be tested under the effect of ambient and elevated temperatures. The first group was statically tested to investigate the monotonic behavior of the specimens. The second group was exposed to fire loading first and then statically tested to explore the residual behavior of the burned specimens. Adding shear connectors and web stiffeners to the GFRP beam was the main parameter in this investigation. Moreover, service loads were applied to the tested beams during the fire. Utilizing shear connectors, web stiffeners,

The Internet of Things (IoT) has become a hot area of research in recent years due to the significant advancements in the semiconductor industry, wireless communication technologies, and the realization of its ability in numerous applications such as smart homes, health care, control systems, and military. Furthermore, IoT devices inefficient security has led to an increase cybersecurity risks such as IoT botnets, which have become a serious threat. To counter this threat there is a need to develop a model for detecting IoT botnets.

This paper's contribution is to formulate the IoT botnet detection problem and introduce multiple linear regression (MLR) for modelling IoT botnet features with discriminating capability and alleviatin