The density-based spatial clustering for applications with noise (DBSCAN) is one of the most popular applications of clustering in data mining, and it is used to identify useful patterns and interesting distributions in the underlying data. Aggregation methods for classifying nonlinear aggregated data. In particular, DNA methylations, gene expression. That show the differentially skewed by distance sites and grouped nonlinearly by cancer daisies and the change Situations for gene excretion on it. Under these conditions, DBSCAN is expected to have a desirable clustering feature i that can be used to show the results of the changes. This research reviews the DBSCAN and compares its performance with other algorithms, such as the traditional number of clustering, K-mean particle swarm optimization (PSO), and Grey–Wolf optimization (GWO). This method offers high performance for improvement. The DBSCAN algorithm also offers better results of clusters and gives better performance assessment according to the results shown in this study.
Despite extensive investigations, an effective treatment for sepsis remains elusive and a better understanding of the inflammatory response to infection is required to identify potential new targets for therapy. In this study we have used RNAi technology to show, for the first time, that the inducible lysophosphatidylcholine acyltransferase 2 (LPCAT2) plays a key role in macrophage inflammatory gene expression in response to stimulation with bacterial ligands. Using siRNA- or shRNA-mediated knockdown, we demonstrate that, in contrast to the constitutive LPCAT1, LPCAT2 is required for macrophage cytokine gene expression and release in response to TLR4 and TLR2 ligand stimulation but not for TLR-independent stimuli. In addition, cells transfe
... Show MoreThis research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg
... Show MoreText Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t
... Show MoreA biostimulant is any microorganism or substance used to enhance the efficiency of nutrition, tolerance to abiotic stress and/or quality traits of crops, depending on its contents from nutrients. Plant biostimulants like honey bee (HB) and silymarin (Sm) are a strategic trend for managing stressed crops by promoting nutritional and hormonal balance, regulating osmotic protectors, antioxidants, and genetic potential, reflecting plant growth and productivity. We applied diluted honey bee (HB) and silymarin-enriched honey bee (HB- Sm) as foliar nourishment to investigate their improving influences on growth, yield, nutritional and hormonal balance, various osmoprotectant levels, different components of antioxidant system, and genetic p
... Show MoreThis study has been carried out to evaluate the expression level of beta 2 microglobulin gene on patients infected by hepatitis C virus before and after treatment with interferon. The study included 117 hepatitis C patients comprising as 63 pre-treated patients, the range of age was between 20-65 year with a mean age of 48.12 ± 16.1 and 54 post-treated patients with age range was between 23-63 year with the mean of 46.1 ± 18.1. Also it was found that more than half of patients were located within third and fourth decade i.e. 30-49 year, with a percentage of 52.4% and 55.6 % for pre-treatment and post-treatment patients respectively. Moreover , regarding both groups, males are more than females with the ratio of ( 3.2:1) among p
... Show MoreThe research work represent a fast and simple method for the determination of methionine using chemiluminescence for the methionine-sodium hydroxide-luminol for the generation of a chemiluminesecent derivative of luminal. The emission was measured by continuous flow analysis made sample size of 83µL was used.Response versus concentration extended from 0.2-20 mM.L-1 with a percentage linearity of 96.17% or with 99.17% percentage of linearity for the range 0.6-20 mM.L-1. Reaching to a L.O.D. at (S/N=3) for 5 µM.L-1 from the gradual dilution for the minimum concentration in the calibration graph with a repeatability of less than 0.5% (n=10). A comparison was made between the new developed method with the classical method for the spectrophoto
... Show MoreIn recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor
... Show MoreThe current study aims to identify soil pollutants from heavy metals The study utilized 40 topsoil (5 cm) samples, which adapted and divided into seven regions lies in Baghdad governorate, included (Al-Husainya,(Hs) Al-Doura (Do), Sharie Al-Matar (SM), Al-Waziria (Wz), Nharawan (Nh), Abu Ghraib (Abu) and Al-Mahmoodyia (Mh)). Spatial distribution maps of Nickel (Ni), Manganese (Mn), Lead (Pb) and Zinc (Zn) were created for Baghdad city using Geographic Information Systems (GIS). The concentrations of four heavy metals in the soil of different area of Baghdad were measured and observed using XRF instrument. The result found highest values of Pb and Zn at the middle of the Baghdad in (Wz