The purpose of this research is to test the ability of the true strength index To time and manage trading in the financial market to select the best stocks and achieve a higher return than the Simple buy and hold strategy. And To achieve the objectives of the research, it relied on the main hypothesis, which is By using the True Strength Index to manage trading decisions buying and selling, can be achieved higher returns than the buy and hold strategy . The research community has been identified with all stocks listed on the Iraq Stock Exchange. Implementing the financial research tests requires selecting a sample from the research community that fulfills the test requirements according to a number of conditions So (38) companies we

Image quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel

Fingerprints are commonly utilized as a key technique and for personal recognition and in identification systems for personal security affairs. The most widely used fingerprint systems utilizing the distribution of minutiae points for fingerprint matching and representation. These techniques become unsuccessful when partial fingerprint images are capture, or the finger ridges suffer from lot of cuts or injuries or skin sickness. This paper suggests a fingerprint recognition technique which utilizes the local features for fingerprint representation and matching. The adopted local features have determined using Haar wavelet subbands. The system was tested experimentally using FVC2004 databases, which consists of four datasets, each set holds

In modern technology, the ownership of electronic data is the key to securing their privacy and identity from any trace or interference. Therefore, a new identity management system called Digital Identity Management, implemented throughout recent years, acts as a holder of the identity data to maintain the holder’s privacy and prevent identity theft. Therefore, an overwhelming number of users have two major problems, users who own data and third-party applications will handle it, and users who have no ownership of their data. Maintaining these identities will be a challenge these days. This paper proposes a system that solves the problem using blockchain technology for Digital Identity Management systems. Blockchain is a powerful techniqu

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th

Efficient and cost-effective drilling of directional wells necessitates the implementation of best drilling practices and advanced techniques to optimize drilling operations. Failure to adequately consider drilling risks can result in inefficient drilling operations and non-productive time (NPT). Although advanced drilling techniques may be expensive, they offer promising technical solutions for mitigating drilling risks. This paper aims to demonstrate the effectiveness of advanced drilling techniques in mitigating risks and improving drilling operations when compared to conventional drilling techniques. Specifically, the advanced drilling techniques employed in Buzurgan Oil Field, including vertical drilling with mud motor, managed pres

Microalgae have been increasingly used for wastewater treatment due to their capacity to assimilate nutrients. Samples of wastewater were taken from the Erbil wastewater channel near Dhahibha village in northern Iraq. The microalga Coelastrella sp. was used in three doses (0.2, 1, and 2g. l^-1) in this experiment for 21 days, samples were periodically (every 3 days) analyzed for physicochemical parameters such as pH, EC, Phosphate, Nitrate, and BOD₅, in addition to, Chlorophyll a concentration. Results showed that the highest dose 2g.l^-1 was the most effective dose for removing nutrients, confirmed by significant differences (p≤0.05) between all doses. The highest removal percentage was

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.