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

Sultan Said bin Sultan bin Ahmed bin Said Al-Busaidi (1223-1273 AH / 1806-1856 AD) was able to rule Oman and Zanzibar in a unified Arab-African state during his reign. However, it was separated for several reasons. Thus, the study aims to clarify the efforts made by Sultan Said for annexing Zanzibar to Oman, establishing the Arab-African Sultanate, and shedding light on the role played by Britain in dividing the Arab-African Sultanate and separating Zanzibar from the Omani rule in (1275 AH-1861 AD). The study has adopted the historical descriptive analytical approach. The study has reached several conclusions, such as: The economic motivators  were the most important factors that pushed Sultan Said to move his capital from Muscat to

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method

In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and

Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

Effects of Ozonated Water on Micro Leakage between Enamel and Fissure Sealants Prepared by Different Etching Technique (An in vitro Study), Baraa M Jabar*, Muna S Khalaf

BACKGROUND: Acute appendicitis (AA) remains a complex case even for experienced surgeons. Rate of negative appendectomy is 5–40% and delayed intervention result in perforated appendicitis in 5–30% of cases. AIM: The aim of the study was to evaluate NPT as a marker for the diagnosis of AA concerning its severity. And compare the diagnostic value of it with the ALV scoring system. METHODS: One hundred twenty patients presented with signs and symptoms of AA and underwent appendectomy, only 84 patients proved to be AA by histopathological examination, were included in the study. Blood samples for neopterin (NPT) estimation and Alvarado (ALV) score was calculated. Control group consists of 45 healthy individual. RESULTS: NPT levels were s

Through this research, We have tried to evaluate the health programs and their effectiveness in improving the health situation through a study of the health institutions reality in Baghdad to identify the main reasons that affect the increase in maternal mortality by using two regression models, "Poisson's Regression Model" and "Hierarchical Poisson's Regression Model". And the study of that indicator (deaths) was through a comparison between the estimation methods of the used models. The "Maximum Likelihood" method was used to estimate the "Poisson's Regression Model"; whereas the "Full Maximum Likelihood" method were used for the "Hierarchical Poisson's Regression Model