Sewage water is a mixture of water and solids added to water for various uses, so it needs to be treated to meet local or global standards for environmentally friendly waste production. The present study aimed to analyze the new Maaymyrh sewage treatment plant's quality parameters statistically at Hilla city. The plant is designed to serve 500,000 populations, and it is operating on a biological treatment method (Activated Sludge Process) with an average wastewater inflow of 107,000m³/day. Wastewater data were collected daily by the Mayoralty of Hilla from November 2019 to June 2020 from the influent and effluent in the (STP) new in Maaymyrh for five water quality standards, such as (BOD5), (COD), (TSS), (TP)

The idea of ​​carrying out research on incomplete data came from the circumstances of our dear country and the horrors of war, which resulted in the missing of many important data and in all aspects of economic, natural, health, scientific life, etc.,. The reasons for the missing are different, including what is outside the will of the concerned or be the will of the concerned, which is planned for that because of the cost or risk or because of the lack of possibilities for inspection. The missing data in this study were processed using Principal Component  Analysis and self-organizing map methods using simulation. The variables of child health and variables affecting children's health were taken into account: breastfeed

Characteristic evolving is most serious move that deal with image discrimination. It makes the content of images as ideal as possible. Gaussian blur filter used to eliminate noise and add purity to images. Principal component analysis algorithm is a straightforward and active method to evolve feature vector and to minimize the dimensionality of data set, this paper proposed using the Gaussian blur filter to eliminate noise of images and improve the PCA for feature extraction. The traditional PCA result as total average of recall and precision are (93% ,97%) and for the improved PCA average recall and precision are (98% ,100%), this show that the improved PCA is more effective in recall and precision.

In this paper, a new hybridization of supervised principal component analysis (SPCA) and stochastic gradient descent techniques is proposed, and called as SGD-SPCA, for real large datasets that have a small number of samples in high dimensional space. SGD-SPCA is proposed to become an important tool that can be used to diagnose and treat cancer accurately. When we have large datasets that require many parameters, SGD-SPCA is an excellent method, and it can easily update the parameters when a new observation shows up. Two cancer datasets are used, the first is for Leukemia and the second is for small round blue cell tumors. Also, simulation datasets are used to compare principal component analysis (PCA), SPCA, and SGD-SPCA. The results sh

This paper tackles with principal component analysis method (PCA ) to dimensionality reduction in the case of linear combinations to digital image processing and analysis. The PCA is statistical technique that shrinkages a multivariate data set consisting of inter-correlated variables into a data set consisting of variables that are uncorrelated linear combination, while ensuring the least possible loss of useful information. This method was applied to a group of satellite images of a certain area in the province of Basra, which represents the mouth of the Tigris and Euphrates rivers in the Shatt al-Arab in the province of Basra.

This study was conducted to determining the variable effects on water quality of Greater Zab River in Erbil province, Iraq, using multivariate statistical analysis. Seventeen variables were monitored in four sampling sites during one year (from May 2012 to April 2013). The dataset were treated using principal component analysis (PCA)/ factor analysis (FA), cluster analysis (CA) to the most important factors affecting water quality, sources of pollution and suitability of water for drinking consumption and irrigation. Six factors were identified as responsible for the data structure explaining 73.5% of the total variance in the dataset and are conditionally named, hydrochemical from weathering, mineral salts and domestic wastes. CA showed

This 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

Treated effluent wastewater is considered an alternative water resource which can provide an important contribution for using it in different purposes, so, the wastewater quality is very important for knowing its suitability for different uses before discharging it into fresh water ecosystems. The wastewater quality index (WWQI) may be considered as a useful and effective tool to assess wastewater quality by indicating one value representing the overall characteristic of the wastewater. It could be used to indicate the suitability of wastewater for different uses in water quality management and decision making. The present study was conducted to evaluate the Al-Diwaniyah sewage treatment plant (STP) effluent quality based on wastewa

Baghdad city has been faced numerous issues related to freshwater environment deteriorations due to many reasons, mainly was the discharge of wastewater without adequate treatment. Al- Rustamiya Wastewater Treatment Plant (WWTP) have been constructed among many plants in Baghdad city to reduce the amount of wastewater discharged into natural environment and its subsequent adverse effects. This study was conducted to evaluate the performance of the plant which consist of a conventional activated sludge (CAS) and sequencing batch reactors (SBR) systems as secondary treatment units and its ability to meet Iraqi specifications. A reliability level determination and analysis also were conducted to find the plant's stability and its capabi