Leukemia or cancer of the blood is the most common childhood cancer, Acute lymphoblastic leukemia (ALL), is the most common form of leukemia that occurs in children. It is characterized by the presence of too many immature white blood cells in the child’s blood and bone marrow, Acute lymphoblastic leukemia can occur in adults too, treatment is different for children. Children with ALL develop symptoms related to infiltration of blasts in the bone marrow, lymphoid system, and extramedullary sites, such as the central nervous system (CNS). Common constitutional indications consist of fatigue (50%), pallor (25%), fever (60%), and weight loss (26%). Infiltration of blast cells in the marrow cavity and periosteum often lead to bone

     Data mining is a data analysis process using software to find certain patterns or rules in a large amount of data, which is expected to provide knowledge to support decisions. However, missing value in data mining often leads to a loss of information. The purpose of this study is to improve the performance of data classification with missing values, ​​precisely and accurately. The test method is carried out using the Car Evaluation dataset from the UCI Machine Learning Repository. RStudio and RapidMiner tools were used for testing the algorithm. This study will result in a data analysis of the tested parameters to measure the performance of the algorithm. Using test variations: performance at C5.0, C4.5, and k-NN at 0% missi

Permanent deformation in asphalt concrete pavements is pervasive distress [1], influenced by various factors such as environmental conditions, traffic loading, and mixture properties. A meticulous investigation into these factors has been conducted, yielding a robust dataset from uniaxial repeated load tests on 108 asphalt concrete samples. Each sample underwent systematic evaluation under varied test temperatures, loading conditions, and mixture properties, ensuring the data’s comprehensiveness and reliability. The materials used, sourced locally, were selected to enhance the study ʼs relevance to pavement constructions in hot climate areas, considering different asphalt cement grades and con- tents to understand material variability ef

Learning the vocabulary of a language has great impact on acquiring that language. Many scholars in the field of language learning emphasize the importance of vocabulary as part of the learner's communicative competence, considering it the heart of language. One of the best methods of learning vocabulary is to focus on those words of high frequency. The present article is a corpus based approach to the study of vocabulary whereby the research data are analyzed quantitatively using the software program "AntWordprofiler". This program analyses new input research data in terms of already stored reliable corpora. The aim of this article is to find out whether the vocabularies used in the English textbook for Intermediate Schools in Iraq are con

In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

Psychological research centers help indirectly contact professionals from the fields of human life, job environment, family life, and psychological infrastructure for psychiatric patients. This research aims to detect job apathy patterns from the behavior of employee groups in the University of Baghdad and the Iraqi Ministry of Higher Education and Scientific Research. This investigation presents an approach using data mining techniques to acquire new knowledge and differs from statistical studies in terms of supporting the researchers’ evolving needs. These techniques manipulate redundant or irrelevant attributes to discover interesting patterns. The principal issue identifies several important and affective questions taken from

The objective of this study was to evaluate the alteration in levels of gonado trophins hormones i.e.,Leutizing (LH),Follicular(FSH) in sera of patients with thyroid disorders and molecular binding study of (LH ,FSH) with their antibodies The study was conducted at the specialized center for endocrinology and diabetes from January / 2009 to March / 2010.Two hundreds and twenty three Iraqi subjects, 109 patients with thyroid disorders at age range between (40-50) years and 114 healthy individuals as control group were included in this study.The majority of patients were female with hyperthyroidism and (49.54 % ) were at age range between(40 - 50) years. The levels of hormones(LH,FSH.tri iodothyronine(T3).thyroxine(T4), thy

Chronic renal failure (CRF) is progressive irreversible destruction of kidney tissue by disease which, if not treated by dialysis or transplant, will result in patient's death. This study was carried out on 30 patients (17 male and 13 female) with chronic renal failure. The aim of this research was studied the changes in the level of total protein ,albumin, calcium ,ionized calcium, phosphorous , iron ,ALP, LDH ,CK and FFA in patients with CRF before and after hemodialysis .The obtained results have been compared with 30 healthy subjects as control group (18male and 12 female). The results showed that there was significant increase in the level of calcium ,ionized calcium, phosphorous ,iron ,ALP,LDH,CK and FFA ,while there was a signifi

This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward