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

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.

Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

The green production of iron oxide nanoparticles (FeONPs) due to its numerous biotechnological uses has attracted a lot of attention and clean and eco-friendly approaches in the medical field.

With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev

This article aims to provide a bibliometric analysis of intellectual capital research published in the Scopus database from 1956 to 2020 to trace the development of scientific activities that can pave the way for future studies by shedding light on the gaps in the field. The analysis focuses on 638 intellectual capital-related papers published in the Scopus database over 60 years, drawing upon a bibliometric analysis using VOSviewer. This paper highlights the mainstream of the current research in the intellectual capital field, based on the Scopus database, by presenting a detailed bibliometric analysis of the trend and development of intellectual capital research in the past six decades, including journals, authors, countries, inst

Abstract

In this manuscript, a simple new method for the green synthesis of platinum nanoparticles (Pt NPs) utilizing F. carica Fig extract as reducing agent for antimicrobial activities was reported. Simultaneously, the microstructural and morphological features of the synthesized Pt NPs were thoroughly investigated. In particular, the attained Pt NPs exhibited spherical shape with diameter range of 5-30 nm and root mean square of 9.48 nm using Transmission Electron Microscopy (TEM) and Atomic Force Microscopy (AFM), respectively. Additionally, the final product (Pt NPs) was screened as antifungal and antibacterial agent against Candida and Aspergillus species as well as Gram-positive Staphyllococcus aureus and G

Phosphorus is usually the limiting nutrient for eutrophication in inland receiving waters; therefore, phosphorus concentrations must be controlled. In the present study, a series of jar test was conducted to evaluate the optimum pH, dosage and performance parameters for coagulants alum and calcium chloride. Phosphorus removal by alum was found to be highly pH dependent with an optimum pH of 5.7-6. At this pH an alum dosage of 80 mg/l removed 83 % of the total phosphorus. Better removal was achieved when the solution was buffered at pH = 6. Phosphorus removal was not affected by varying the slow mixing period; this is due to the fact that the reaction is relatively fast.
The dosage of calcium chloride and pH of solution play an importa

Peer-Reviewed Journal