The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, which is used to cluster genes. FCM allows an object to belong to two or more clusters with a membership grade between zero and one and the sum of belonging to all clusters of each gene is equal to one. This paradigm is useful when dealing with microarray data. The total time required to implement the first model is 22.2589 s. The second model combines FCM and particle swarm optimization (PSO) to obtain better results. The hybrid algorithm, i.e., FCM–PSO, uses the DB index as objective function. The experimental results show that the proposed hybrid FCM–PSO method is effective. The total time of implementation of this model is 89.6087 s. The third model combines FCM with a genetic algorithm (GA) to obtain better results. This hybrid algorithm also uses the DB index as objective function. The experimental results show that the proposed hybrid FCM–GA method is effective. Its total time of implementation is 50.8021 s. In addition, this study uses cluster validity indexes to determine the best partitioning for the underlying data. Internal validity indexes include the Jaccard, Davies Bouldin, Dunn, Xie–Beni, and silhouette. Meanwhile, external validity indexes include Minkowski, adjusted Rand, and percentage of correctly categorized pairings. Experiments conducted on brain tumor gene expression data demonstrate that the techniques used in this study outperform traditional models in terms of stability and biological significance.
The Isolated Combustion and Diluted Expansion (ICADE) internal combustion engine cycle combines the advantages of constant volume combustion of the Otto cycle with the high compression ratio of the Diesel cycle. This work studies the effect of isolated air mass (charge stratification) on the efficiency of the cycle; the analysis shows that the decrease of isolated air mass will increase the efficiency of the cycle and the large dilution air mass will quench all NOx forming reactions and reduce unburned hydrocarbons. Furthermore, the effect of Fuel / Air ratio on the efficiency shows that the increase of Fuel / Air ratio will increase efficiency of the cycle.
During infection, T. gondii disseminates by the circulatory system and establishes chronic infection in several organs. Almost third of humans, immunosuppressed individuals such as HIV/AIDS patients, cancer patients, and organ transplant recipients are exposed to toxoplasmosis. Therefore, the study aimed to investigate the possibility that Toxoplasma infection could be a risk factor for COVID-19 patients and its possible correlation with C-reactive protein and ferritin. Overall 220 patients referred to the Al Furat General Hospital, Baghdad, Iraq were enrolled from 2020–2021. All serum samples were tested for T. gondii immunoglobulins (IgG and IgM) antibodies, C-reactive protein and ferritin levels. In patients with COVID-19, the results
... Show MoreThis study was carried out in Plant Tissue Culture Labs, College of Agricultural Engineering Sciences, University of Baghdad from November 2018 to June 2019. Fresh stem cuttings, 5 cm long were selected from 6-month old C-35 Citrange rootstock. Five concentrations of BA (0, 1, 1.5, 2 and 2.5 mg.L-1) were studied and addition of meta-Topolin (mT) at four concentrations (0, 1, 5 and 10 mg.L-1) was also studied to find out its effect individually on shoot number and shoot length in multiplication stage. Rooting media supplemented with four concentrations of IBA (0, 1, 2 and 3 mg.L-1) was also studied to find out its effect on rooting percentage, root number and root length. Results showed that BA as concentration of 2.5mg.L-1 significantly gav
... Show MoreIn the resent years, there is a robust scientific interest in discovery of new anti-septic and anti-oxidant naturally products with no/or limited side effects. The current study aimed to investigate the protective role of the quercetin on inflammations induced by lipopolysaccharide (LPS) in male mice A number of criteria included i.e. liver and spleen index and IL-6 and IL1-β cytokines level in spleen homogenate were considered. Sixty male mice (8-9 week age) was divided into six groups and treated for 5 days as the following: the first group represented control, the second and third group were injected with 5, 10 mg/kg b.w doses of quercetin respectively. While the fourth and fifth groups were co-treatment with (5, 10 mg/kg b.w.) intraper
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In this paper synthesis and extensive investigation of the microstructural and optoelectronic properties of polyaniline (PANI), Multiwalled carbon nanotube (MWCNTs) and MWCNTs reinforced PANI composites is presented. MWCNTs- PANI composites have been deposited by spin coating on silicon wafer substrate. Fourier Transform Infrared Spectroscopy shows no difference between PANI and its composites. However a change in peaks shape and absorption intensity has been observed. A strong effect of the MWCNTs weight percentage on the PANI/MWCNTs composites has been demonstrated. It was find that the thermal stability improved with increasing MWCNTs content. The optical band gap of the PANI thin
Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
... Show MoreThe objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.
Was conducted to compare the two methods above and it became clear by comparing the logistic regression model best of a Linear Discriminant function written
... Show MoreThis work represents study the rock facies and flow unit classification for the Mishrif carbonate reservoir in Buzurgan oil Field, which located n the south eastern Iraq, using wire line logs, core samples and petrophysical data (log porosity and core permeability). Hydraulic flow units were identified using flow zone indicator approach and assessed within each rock type to reach better understanding of the controlling role of pore types and geometry in reservoir quality variations. Additionally, distribution of sedimentary facies and Rock Fabric Number along with porosity and permeability was analyzed in three wells (BU-1, BU-2, and BU-3). The interactive Petrophysics - IP software is used to assess the rock fabric number, flow zon
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