Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

Background: Few updated retrospective histopathological-based studies in Iraq evaluate a comprehensive spectrum of oro-maxillofacial lesions. Also, there was a need for a systematic way of categorizing the diseases and reporting results in codes according to the WHO classification that helps occupational health professionals in the clinical-epidemiological approach.

Objectives: to establish an electronic archiving database according to the ICD-10 that encompasses oro-maxillofacial lesions in Sulaimani city for the last 12 years, then to study the prevalence trend and correlation with clinicopathological parameters.

Subjects and Methods:  A descri

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

The study of the language through the prophetic curriculum in general and the semantics in particular through the books of Professor Abdul Salam Yassin, may God have mercy on him and the most distinctive linguistic phenomena, and then study semantics and the most prominent methods that reveal the emotions dominated by this study to indicate the semantics of religious terms In this research we try to dive into the sea of ​​significance to know the relationship between the words and their connotations, and to monitor aspects of semantic development, although we have left non-essential words in order to avoid lengthening. N or three and sometimes Aguetsarna on one example we thought it was enough to clarify the meaning.

The traditional method adopted in the preparation of the general budget in Iraq is not consistent with developments in the size specification response and spending and the associated weakness in the size of the amounts earmarked for investment projects which could adversely affect future generations and not to enable them to continue the development, which requires talking to estimate the adoption of style public expenditure in the state budget and reduce waste and extravagant where and invest public revenues of the state in investment projects and preservation of the environment and natural resources in order to ensure the benefit of future generations system, according to the system serves to achieve the overwhelming majority of member

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

The research current ( features tendency cosmic in contemporary Iraqi configuration) attempt to study the dimensions of the conceptual and philosophical foundations upon which the tendency of cosmic within the period that extended its influence beyond the place where I grew up to be circulated concepts in all parts of the world, it is no doubt that the world is now heading to rapprochement after the tremendous developments in the field of communication technology and reflected heavily on identity concepts, privacy, the concept of nation-states ... etc. to become an individual and a large area of access to other cultures, and all that aroused the interest of contemporary Iraqi artist this interest arising from the desire to keep up with d

This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),