This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

chronic obstructive pulmonary disease (COPD) is a common respiratory disease with episodes of exacerbation. Variable factors including infectious pathogen can predispose for this exacerbation. The aim of this study is to evaluate the role of intestinal protozoa in COPD exacerbation. A total of 56 patients with COPD were included in this study. Patients were categorized into two groups based on the frequency of exacerbation during the last 6 months: those with ≤1 exacerbation (32 patients) and those with ≥2 exacerbations (24 patients). Stool specimens from each patient were collected two times (one week interval) examined for intestinal parasite. In univariate analysis, rural residence and parasitic infection were more common among patie

  The research aims to reveal the role of financial analysis in rationalizing the investor decision on the Iraqi stock Exchange market, by studying the relationship and impact techniques and methods of financial analysis on the decisions of investors in the market. The most important techniques and methods discussed in this study were: analysis (financial ratios analysis, comparison of financial statements analysis, cash flow statement analysis) for companies listed in the Iraqi stock Exchange market. The researcher adopted the analytical descriptive method which depends on the collection of data on the phenomenon and its interpretation. The questionnaire wa

The current research aims to measure the impact of the skills of human resources management professionals in information technology in Iraqi private banks, as the skills of human resources management professionals constitute the modern trend of banks' interest in employees with outstanding performance, and the presence of information technology in banks is a prerequisite for dealing with the huge amount of data. And converting it into information to support the decision-maker in light of a complex environment, and the field research problem was the presence of a clear lack of interest in the skills of human resource management professionals and the weak adoption of information technology, which was reflected negatively on the compet

According to so many previous studies, lack of sufficient information during prescribing steps may lead to medication errors. Thus, the presence of the clinical pharmacist during routine rounding process in the ward with intervention of patient care plan may reduce the probability of adverse drug events (ADEs).This study evaluate role of the clinical pharmacists, as a member of medical team with the physician, on ADEs and report their interventions in the internal medicine unit. This study was designed to compare between two groups of patients, those receiving care from a rounding team (physician, nurse, and clinical pharmacist) (study or intervention group with 51 patient); and those receiving c