Univesity of Thi-Qar Journal

Fuel cell power systems employing renewable energy to reduce power outages and problems is affecting the network and their are generation systems. Many researches has been to integrate photovoltaic energy with other sources contributes a lot in the field of electrical energy. High efficiency, high quality, and decrease fuel consumption . We its noted that the development of renewable energy means finding a new source of energy, a safe environment, and economic factors. On the other hand, the development of battery technology with solar cells and other sources is sufficient for our need for energy. The integration of the solar cell with fuel cells and batteries will obtain an uninterrupted source of energy. This study aims to find and design efficient and hybrid energy systems according to the hybrid energy system strategy. The results were obtained through simulation using the Matlab program.

The paper aims to protect the databases using multiple encryption. and presented a new method in the use of multiple encodings for a single selected experimental database. A number of methods were used to protect the selected database, the selected method is to hide database objects, The method develop be using in the Visual Basic programming language application in the databases, while the other method dealt with the design of the software code to convert the explicit text to the encrypted text. All of these methods were used for a single, trial-selected database, and all the methods used were designed to protect the elected database from unauthorized access to and manipulation of the database.

By this paper, we intend structure of some class of permutation polynomials which ‎having the form D_(n,k) (x,a)+〖(〖Tr〗_m^n (D_(n,k) (x,a)^k+α_1)〗^(s_1 )+‎‎〖(〖Tr〗_m^n (D_(n,k) (x,a)^k+α_2)〗^(s_2 ) over F_2^2m depend on (AGW ‎criterion ).‎

Skin cancer is one of the leading causes of death in humans, ‎however, it is treatable if caught early. Therefore, early detection of skin ‎cancer contributes to saving many patients. Skin cancer is divided into two ‎types, benign tumor, and malignant tumor that leads to the death of a person ‎if not treated early, and both are similar in appearance only a dermatologist ‎can classify cancer as malignant or benign. ‎
The proposed system consists of several basic stages. The first stage ‎is the creation and provision of a large database, the second stage is the use ‎of data compression techniques (images), and the third stage is the use of ‎artificial intelligence by applying an artificial neural network to image ‎processing technology, specifically in the field of deep learning approach. ‎The database used in the proposed system consists of a set of skin cancer ‎images from the International Skin Imaging Cooperation (ISIC) and a set of ‎images also brought from the Medical City in Iraq (Dermatology ‎Consultation Department). Be clear and free of distortion at a good rate.‎
Huffman technology is used to compression images while preserving ‎image information from loss, reducing image size, saving storage space, ‎saving time, and thus increasing system speed, as a neural network (deep ‎learning) was used with the SVM classifier for the support machine. Also, a ‎set of deep learning models VGG16, AlexNet, ResNet-50 and Inception v3 ‎were used only without any modifications to the models except the last layer ‎of each model. Finally, a special model that detects skin cancer (SkinNet) ‎was proposed.‎
The method used in detecting skin cancer is deep learning that works ‎by inserting compressed images and then splitting the images 70% for the ‎training process, 30% for the testing process, and the proposed model ‎‎(SkinNet) performed better with accuracy, and the performance was with ‎‎98.2% accuracy.‎