Article information: COVID-19 has roused the scientic community, prompting calls for immediate solutions to avoid the infection or at least reduce the virus's spread. Despite the availability of several licensed vaccinations to boost human immunity against the disease, various mutated strains of the virus continue to emerge, posing a danger to the vaccine's ecacy against new mutations. As a result, the importance of the early detection of COVID-19 infection becomes evident. Cough is a prevalent symptom in all COVID-19 mutations. Unfortunately, coughing can be a symptom of various of diseases, including pneumonia and inuenza. Thus, identifying the coughing behavior might help clinicians diagnose the COVID-19 infection earlier and distinguish coronavirus-induced from non-coronavirus-induced coughs. From this perspective, this research proposes a novel approach for diagnosing COVID-19 infection based on cough sound. The main contributions of this study are the encoding of cough behavior, the investigation of its unique characteristics, and the representation of these traits as association rules. These rules are generated and distinguished with the help of data mining and machine learning techniques. Experiments on the Virufy COVID-19 open cough dataset reveal that cough encoding can provide the desired accuracy (100%).
Background: The gene responsible for encoding the protein of cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) has been found to be associated with rheumatoid arthritis (RA) in different ethnic populations. But the association of +49A/G CTLA-4 polymorphism with susceptibility of RA among Iraqi Arab populations has not yet been determined. Methods: One hundred and seventy-eight patients were examined, 67 of them were males (mean age 54.71 ± 10.4 years), while 167 were examined for the control group, of whom 64 were males and the rest were females. CTLA-4 DNA genotyping was carried on to determine the +49 A/G (rs231775) polymorphism using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Enzyme-linked immuno
... Show MoreBreast cancer is the most commonly diagnosed cancer and remains one of the main reasons of cancer-related mortality in women worldwide. KRAS variant rs61764370 (T>G) is associated with an increased risk of occurrence of many cancers, Here The case-control study was accomplished on 135 women including 45 women with breast cancer patients, 45 women with benign breast lesions and 45 healthy women to analyze the association of KRAS variant rs (61764370 T>G) with breast cancer. LCS 6 variant in KRAS gene was amplified by using specific primers, then genotype was detected after sequencing the PCR products. The results showed that the genotype and allele frequency of TT and GT allele of KRAS
... Show Moreervical cancer is one of the most frequently diag nosed malignancies representing the fourth leading cause of cancer-related death in females’ worldwide, with approximately 500,000 new cases diagnosed and 280,000 deaths occurring each year. Mxi1, an antagonist of c-Myc, maps to human chromosome 10q24-q25, a region altered in a substantial fraction of prostate tumors, in prostate cancer, where a high frequency of loss and mutation of the MXI1 gene has been reported. The aim of present study was to find out the possible association of exon deletion of MXI1 gene with incidence of cervical abnormalities and cancers in some Iraqi married women. The present study include collection of 120 scraping cervical cells samples from women clinically di
... Show MoreObjective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using
... Show MoreBased on Lyapunov exponent criterion, the aircraft lateral-directional stability during critical flight cases is presented. A periodic motion or limit cycle oscillation isdisplayed. A candidate mechanism for the wing rock limit cycle is the inertia coupling between an unstable lateral-directional (Dutch roll) mode with stable longitudinal (short period) mode. The coupling mechanism is provided by the nonlinear interaction of motion related terms in the complete set equations of motion. To analyze the state variables of the system, the complete set of nonlinear equations of motion at different high angles of attack are solved. A novel analysis including the variation of roll angle as a function of angle of attack is proposed. Furthermore
... Show MorePolyaniline films were successfully synthesized in this study using an oxidative polymerization method at temperatures ranging from 0 to 4 ° C. Polyaniline films were deposited using a single step of chemical oxidative polymerization rather than electrochemical polymerization. The polyaniline was examined using FTIR, XRD, SEM, AFM, and Four Point Probe. This result demonstrates that polyaniline synthesized using this method has a uniform morphology, small size (17 to 40) nm, high crystallinity, and high conductivity (9.42 s/cm).
In this paper two axis sun tracking method is used to absorb maximum power from the sun's rays on the solar panel via calculating the sun’s altitude and azimuth angles, which describe the solar position on the Iraqi capital Baghdad for the hours 6:00, 7:00, 8:00, 9:00, 12:00, 15:00 and 17:00 per day. The angles were calculated in an average approach within one month, so certain values were determined for each month. The daily energy achieved was calculated for the solar tracking method compared with the fixed tracking method. Designed, modeled and simulated a control circuit consisting of reference position truth table, PI Controller and two servomotors that tracked the sun position to adjust the PV panel perpendicular
... Show MoreAn efficient combination of Adomian Decomposition iterative technique coupled Elzaki transformation (ETADM) for solving Telegraph equation and Riccati non-linear differential equation (RNDE) is introduced in a novel way to get an accurate analytical solution. An elegant combination of the Elzaki transform, the series expansion method, and the Adomian polynomial. The suggested method will convert differential equations into iterative algebraic equations, thus reducing processing and analytical work. The technique solves the problem of calculating the Adomian polynomials. The method’s efficiency was investigated using some numerical instances, and the findings demonstrate that it is easier to use than many other numerical procedures. It has
... Show MoreIn this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in