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

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

Air pollution is one of the important problems facing Iraq. Air pollution is the result of uncontrolled emissions from factories, car exhaust electric generators, and oil refineries and often reaches unacceptable limits by international standards. These pollutants can greatly affect human health and regular population activities. For this reason, there is an urgent need for effective devices to monitor the molecular concentration of air pollutants in cities and urban areas. In this research, an optical system has been built consisting of aHelium-Neonlaser,5mWand at 632.8 nm, a glass cell with a defined size, and a power meter(Gentec-E-model: uno) where a scattering of the laser beam occurs due to air pollution. Two pollutants were examin

The increasing number of orphans and their organizations and institutes in our community makes it increasingly important to design and develop an expert system that supports decisions concerning orphans and their families. This system can be used by any orphans organization to facilitate its work.
The proposed work is designed to manage the Orphans and Families of Martyrs of Terrorism Expert System (OFMTES) by registry all information about all orphans to display mostly orphan deserves bill, data is entered for each orphan, and with each entry a counter is increased according to this input information; the output result represents the score for that orphan. Different orphans have different scores. Coloring is used to know the degree o

Objectives: The study aims to assess  the nurses knowledge toward prevention of complications related to valvular  replacement surgery and to find out the relationship between nurses knowledge and their demographic and occupational characteristic's Which as (Age, gender, level of education ,years of experience in Surgical Department , and training sessions)

Methodology: A descriptive design  (a cross-sectional study ) was carried out from December 2017 to May 2018 in order to assess nurses' knowledge of preventing complications Valvular Replacement Surgery at Surgical Department in  Nasiriyah Heart Center on a purposive (non-probability) sample

Objective(s): To assess parents' attitude toward immunization and its relation with their compliance and to find out the relationship between parents' attitude and their socio-demographic characteristics.
Methodology: A descriptive design is conducted from the period of 19th September 2020 to the 6th of March 2021. A non-probability (convenient) sample of (292) parents was selected from (5) primary health care centers in Karbala city. These centers are distributed throughout (2) primary health care sectors selected randomly as (20%) from each sectors. The questionnaire is developed and composed of three parts: First part: parent's socio-demographic characteristics, Second part: parents' attitude domain, which involves (13 items), and

Objective(s): To evaluate nurses' practices who work in respiratory intensive care units to control the
complications of patients admitted at this unit and determine the relationship between nurses' sociodemographic
characteristics and their practices.
Methodology: A descriptive study was carried out at Respiratory Care Unit at Baghdad teaching hospitals that
started from February 22th, 2013 to August 30th, 2013. A purposive "non-probability" sample of (70) nurses who
work in Respiratory Care Unit was selected from Baghdad teaching hospitals. The data were collected through the
use of constructed questionnaire that consists of two parts; (l) Demographic data form that consists of 7items and
(2) nurses' practice form

The research aims to study the elements of attraction in television advertising and determine their relationship to consumer preferences, the extent to which the sample (250) watches television advertisements, and the motives for viewing. Males and females, and the statistical program spss was used to analyze the results using percentages, arithmetic mean, correlation coefficients ch2, Pearson’s coefficient and Alpha Cronbach for the stability of the test, and the research came to the conclusion that the percentage of watching television advertisements is good motivated by the identification of new goods and services in the market, as advertisements sometimes achieve consumer preferences, and the most prominent The forms that a

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings