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Detecting plant diseases using the traditional method such as the naked eye can sometimes lead to incorrect identification and classification of the diseases. Consequently, this traditional method can strongly contribute to the losses of the crop. Image processing techniques have been used as an approach to detect and classify plant diseases. This study aims to focus on the diseases affecting the leaves of al-berseem and how to use image processing techniques to detect al-berseem diseases. Early detection of diseases important for finding appropriate treatment quickly and avoid economic losses. Detect the plant disease is based on the symptoms and signs that appear on the leaves. The detection steps include image preprocessing, segmentation, and identification. The image noise is removed in the preprocessing stage by using the MATLAB features energy, mean, homogeneity, and others. The k-mean-clustering is used to detect the affected area in leaves. Finally, KNN will be used to recognize unhealthy leaves and determines disease types (fungal diseases, pest diseases (shall), leaf minor (red spider), and deficiency of nutrient (yellow leaf)); these four types of diseases will detect in this thesis. Identification is the last step in which the disease will identify and classified.

In these days, Smartphone application plays an important role that has an impact effect on the users. Cell phones are an essential tool in our daily lives because they provide many communication and fun services. Therefore, it can be a powerful tool for helping the patient who has diabetes. This research paper aims to develop a smartphone application for the self-management of diabetes patient activities. It also seeks to monitor the diabetes patient status and through the smartphone application. The paper reviews the available applications on the smartphone and articles published in the online resources database. The review papers covered various applications to support the self-management tasks such as diet, blood testing, education, exercises, alter, etc. The critical analysis indicates that mobile applications have been improving patients' positive behavior to have the self-management of diabetes. Using the application is a handy tool to change the attitude in self-care activities related to diabetes management and increased user stratification.

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The use of digital images has become very common because of the rapid increase of the internet over time. Moving digital images over the internet is easy, but keeping ownership is complex, and serious issues have emerged. Forgery, fraud, and pirating of this content are rising. Different techniques used to protect images, like watermarking and steganography, but these methods are not enough toprotect. So, providing new techniques is essential for protecting image ownership. We have proposed a fusion method of steganography and watermarking in this work. First, the secret message is encoded within the original image using the LSB technique to obtain the stego image. Secondly, the watermarking process is applied on the stego image using text watermarking or image watermarking to provide stego-watermarked-image. The proposed fusion watermarking and steganography method is very useful for protecting image ownership over insecure communication channels. An attacker cannot get the desired watermarked image from the stego-watermarked-image without knowing the secret message hiding inside it using the LSB technique. The proposed method is efficient, simple and secure; it provides significant protection for image ownership.