In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

Geotechnical engineering like any other engineering field has to develop and cope with new technologies. This article intends to investigate the spatial relationships between soil’s liquid limit (LL), plasticity index (PI) and Liquidity index (LI) for particular zones of Sulaymaniyah City. The main objective is to study the ability to produce digital soil maps for the study area and determine regions of high expansive soil. Inverse Distance Weighting (IDW) interpolation tool within the GIS (Geographic Information System) program was used to produce the maps. Data from 592 boreholes for LL and PI and 245 boreholes for LI were used for this study. Layers were allocated into three depth ranges (1 to 2, 2 to 4 and 4 to 6)

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th

The current research aims to :
•know the level of social intelligence of the sample as a whole .
. •taraf statistically significant differences in social intelligence between disadvantaged and
non-disadvantaged peers .
To achieve these objectives, the selected sample of Talbhalmrahlh medium and specifically
students of the second grade average, were chosen randomly stratified's (360) students
included sex (male, female) and (deprived of the Father and the non-deprived) for the
academic year (2013-2014) for the province of Baghdad on both sides (Rusafa-Karkh (
As applied to them measurements of social intelligence, which is prepared by the researcher,
having achieved _khasaúsma of psychometric (valid and re

Background: Blood vessels injury is one of the most
common causes of medical emergencies that admitted to
hospitals and at the same time it regarded as one of the
most important causes of death. They may represent less
than 15% of all injuries; they deserve special attention
because of their severe complications.
Objective: The aim of the present study is to assess
anatomically the injures of major arteries and veins in the
lower limb with their management.
Methods: The present study extended from April 2006 to
February 2007, in which 65 patients with lower limb
vascular injury were examined in Emergency Department
and Forensic Medicine Department of Tikrit Teaching
Hospital in Salah-Aldin governora

    The present study was conducted in order to focus on the effect of the addition of Carnitine and Niacin on some blood serum parameters of Common Carp Cyprinus Carpio. 48 fish carp mean weight 44.13 gm were distributed randomly on four feeding treatments (12 fish each) with replicates (6 fish each) in 8 glass aquaria. Treatments were as follows: fish were fed on basic diet without any addition and conducted as control (T1); addition of 200 mg Carnitine/ Kg diet, (T2) addition of 28 mg Niacin/Kg diet (T3), addition of a mixture of 200 mg Carnitine and 28 mg Niacin/ Kg diet as (T4). The experiment was conducted for 70 days and the results showed an increase in the Cholesterol concentration of T1 (187.6 mg/ 100 ml) and differed s