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

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,

Sara and other kid's Agony: - Back to Innocence to Save Iraq

This work presents an investigation on the fabrication and characterization of Fe doped zeolitic imidazolate framework (ZIF-8) of 1:1 M ratio of Zn:Fe (Fe/Zn-ZIF-8) and adsorption performances of acquired materials. The synthesized Zn-ZIF-8, Fe-ZIF-8, and Fe/Zn-ZIF-8 materials were characterized for the phase structure, morphology, elemental analysis and surface area by using X-ray diffraction (XRD), Field emission scanning electron microscope (FESEM), Energy Dispersive X-Ray (EDX), and BET surface area, respectively. The results revealed the adsorption capacity was enhanced by incorporation of Fe into ZIF-8 structure. The CR dye adsorption capacities were 287, 219, and 412 mg/g for Zn-ZIF-8, Fe-ZIF-8, and Fe/Zn-ZIF-8 adsorbers, respectivel

Home New Trends in Information and Communications Technology Applications Conference paper Audio Compression Using Transform Coding with LZW and Double Shift Coding Zainab J. Ahmed & Loay E. George Conference paper First Online: 11 January 2022 126 Accesses Part of the Communications in Computer and Information Science book series (CCIS,volume 1511) Abstract The need for audio compression is still a vital issue, because of its significance in reducing the data size of one of the most common digital media that is exchanged between distant parties. In this paper, the efficiencies of two audio compression modules were investigated; the first module is based on discrete cosine transform and the second module is based on discrete wavelet tr

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.

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

New designs of solar using ray tracing program, have been presented for improved the performance and the out put power of the silicon solar cell, as well as reducing the cost of system working by solar energy. Two dimensional solar concentrator (Fresnel lenses) and three dimensional concentrators (parabola dish and cassegrain) were used as concentrator for photovoltaic applications (CPV). The results show that the performance efficiency and out power for crystalline silicon solar cells are improved.