Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

􀀨􀀅􀀆􀀔􀀜􀀄􀀂􀀆􀀈􀀓􀀌􀀩􀀏􀀆􀀉􀀅􀀆􀀉􀀅􀀉􀀚􀀝􀀔􀀄􀀗􀀉􀀚􀀆􀀂􀀓􀀚􀀁􀀔􀀄􀀓􀀅􀀆􀀄􀀂􀀆􀀔􀀓􀀆􀀃􀀂􀀔􀀄􀀟􀀉􀀔􀀃􀀆􀀔􀀜􀀃􀀆􀀛􀀃􀀜􀀄􀀗􀀚􀀃􀀆􀀗􀀌􀀄􀀔􀀄􀀗􀀉􀀚􀀆􀀂􀀘􀀃􀀃􀀊􀀂􀀆􀀓􀀖􀀆􀀓􀀛􀀃􀀌􀀔􀀁􀀌􀀅􀀄􀀅􀀕􀀢􀀆􀀪􀀜􀀃􀀆􀀄􀀅􀀛􀀃􀀂􀀔􀀄􀀕􀀉􀀔􀀄􀀓􀀅􀀂􀀆 􀀉􀀌􀀃􀀆􀀙􀀉􀀂􀀃􀀊􀀆􀀓􀀅􀀆􀀉􀀁􀀔􀀓􀀟􀀓􀀙􀀄􀀚􀀃􀀆􀀚􀀉􀀔􀀃􀀌􀀉􀀚􀀆􀀂􀀘􀀉􀀗􀀃􀀆􀀟􀀄􀀊􀀂􀀔􀀆􀀔􀀜􀀃􀀆􀀗􀀃􀀅􀀔􀀃􀀌􀀚􀀄􀀅􀀃􀀂􀀆􀀓􀀖􀀆􀀔􀀜􀀃􀀆􀀙􀀉􀀂􀀃􀀆

With the increasing reliance on microgrids as flexible and sustainable solutions for energy distribution, securing decentralized electricity grids requires robust cybersecurity strategies tailored to microgrid-specific vulnerabilities. The research paper focuses on enhancing detection capabilities and response times in the face of coordinated cyber threats in microgrid systems by implementing advanced technologies, thereby supporting decentralized operations while maintaining robust system performance in the presence of attacks. It utilizes advanced power engineering techniques to strengthen cybersecurity in modern power grids. A real-world CPS testbed was utilized to simulate the smart grid environment and analyze the impact of cyberattack

* Khalifa E. Sharquie1, Hayder Al-Hamamy2, Adil A. Noaimi1, Mohammed A. Al-Marsomy3, Husam Ali Salman4, American Journal of Dermatology and Venereology, 2014 - Cited by 2

This study was designed to look for certain biochemical markers(serum uric acid and serum peroxynitrite) in women presented with obesity and to compare the level of these markers with non-obese women. A total number of 63 women were recruited from outpatients and private clinics to admit in this study. The patients were grouped into non obese women (Group I) and obese women (Group II). The anthropometric and blood pressure were determined and venous blood was obtained from each patient for determination of C-reactive protein, uric acid and peroxynitrite. The results showed that there were no significant differences in age or in concomitant or associated diseases in both groups except rheumatoid arthritis which account 80% of group I and 25%

        fashion designers who have benefited greatly from the mobilization of ancient aesthetic ideas in the heritage of the people and guaranteed in their productions so that there is no change In the aesthetic value created by the designers of the research in the ancient heritage to find new signs that reflect the connection of man to the present as the aesthetic value of all the man created by the designs of fabrics and fashion through the ages      The problem of research was determined in the absence of a precise understanding of the nature of classical thought in fashion and the absence of a clear perception of the sustainability of this thought in contemporary fashion. He