In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used where six parameters are calculated from the Co-occurrence matrix. These parameter were inserted in the K-mean. The best classifier feature is the angular second moment. When we use the angular second moment is used with any textural feature a good result were obtained for cloud classification, since the angular second moment gives indications on cloud homogeneity.
There are many events which causes nonproductive time (NPT) in the drilling industry. The mostly effective in this NPT is pipe sticking event. A considerable amount of time and resources can be spent in efforts to free a stuck pipe. In addition, Unsuccessful fishing operations results in costly alternatives including side-tracking. The drilling in Khabaz oil field poses many operational challenges among of them stuck pipe , lost circulation, flow of salt water during drilling, and hole caving. Stuck pipe can be considered the quite difficult problem in Khabaz oil field due to associated incidents which lead to NPT activities.Well Khabaz -34 was selected to study the problem of stuck pipe in this field. An analysis of stuck pipe even
... Show MoreWhen embankment is constructed on very soft soil, special construction methods are adopted. One of the techniques is a piled embankment. Piled (stone columns) embankments provide an economic and effective solution to the problem of constructing embankments over soft soils. This method can reduce settlements, construction time and cost. Stone columns provide an effective improvement method for soft soils under light structures such as rail or road embankments. The present work investigates the behavior of the embankment models resting on soft soil reinforced with stone columns. Model tests were performed with different spacing distances between stone columns and two lengths to diameter ratios of the stone columns, in addition to different
... Show MoreThe use of composite materials has vastly increased in recent years. Great interest is therefore developed in the damage detection of composites using non- destructive test methods. Several approaches have been applied to obtain information about the existence and location of the faults. This paper used the vibration response of a composite plate to detect and localize delamination defect based on the modal analysis. Experiments are conducted to validate the developed model. A two-dimensional finite element model for multi-layered composites with internal delamination is established. FEM program are built for plates under different boundary conditions. Natural frequencies and modal displacements of the intact and damaged
... Show MoreIn this paper, the static analysis for finding the best location of boxes inside the composite wing-box structure has been performed. A software ANSYS (ver.11) was used to analyses the Aluminum wing to find the maximum stresses reached in. These results are used as a base for the composite wingbox to find the numbers of layers and location of the box beam and its dimensions so that the composite wingbox may carry the same loading conditions in the Aluminum wing. Analysis showed that a composite wingbox having two boxes is better than the single or triple boxes wing based on stress to weight ratio. Mass saving of (40%) had been achieved when composite wing-box is used instead of Aluminum wing.
Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus. The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patien
... Show MoreThis study discusses the Critical Discourse Analysis of 2012 American Presidential Election Debate’. The researcher adopts a model proposed by Van Dijk’s (2006 d). Six ideological categories have been selected within the overall strategies of the ideological square are used. The categories are of three levels of discourse structure : (the meaning, the argumentation, and the rhetoric) .They have shown effective criteria for detecting the most disguised systems of racism and manipulation.
Based on the analysis, it can be concluded that the elite discourses of candidates contribute to the reproduction of domination, Orientalism, and Islamophobia. This can be appl
... Show MoreFactor analysis is distinguished by its ability to shorten and arrange many variables in a small number of linear components. In this research, we will study the essential variables that affect the Coronavirus disease 2019 (COVID-19), which is supposed to contribute to the diagnosis of each patient group based on linear measurements of the disease and determine the method of treatment with application data for (600) patients registered in General AL-KARAMA Hospital in Baghdad from 1/4/2020 to 15/7/2020. The explanation of the variances from the total variance of each factor separately was obtained with six elements, which together explained 69.266% of the measure's variability. The most important variable are cough, idleness, fever, headach
... Show MoreThis paper proposed a new method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA)) for measureing the closeness between curves. Root Mean Square Errors is used for the implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when the cov
... Show More