In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

Various activities taking place within the city of Baghdad have significantly contributed to organic pollution in Rivers Tigris and Diyala. The present study aimed to assess some physical, chemical and biological aspects of six sites on Rivers Tigris and Diyala as they flow through the city of Baghdad. Monthly samples were collected for the period January to December, 2005. Marked differences in the physical and chemical characteristics of water were noted between the two rivers’ sites. Average values during the study period of dissolved oxygen, biochemical oxygen demand, particulate organic matter, nitrate, phosphate and total dissolved solids for Tigris and Diyala were 7.8,4.7; 2.4,10.4; 350.1,921.4;7.8,13.9;1.2,4.8;814,2176 mg / l re

Dora petroleum refinery waste water is the one of the important source of pollution by priority pollutant aromatic compound discharged to Tigris river in Iraq. the station has waste water treatment unit contains many treatment subunits The most important sub units is :skimmer units ,physiochemical unit ,daf unit, biological unit. The aim of research project is to study the ability of unit to remove the priority pollutant aromatic compound and follow up these compounds in river to study ability of river to self removal. A solid phase extraction (SPE) followed by high performance liquid chromatography-ultra violet (HPLC-UV) technique is depicted for the quantitative estimation of benzidines and phenols. Experimental studies were performed to

Due to the availability of technology stemming from in-depth research in this sector and the drawbacks of other identifying methods, biometrics has drawn maximum attention and established itself as the most reliable alternative for recognition in recent years. Efforts are still being made to develop a user-friendly system that is up to par with security-system requirements and yields more reliable outcomes while safeguarding assets and ensuring privacy. Human age estimation and Gender identification are both challenging endeavours. Biomarkers and methods for determining biological age and gender have been extensively researched, and each has advantages and disadvantages. Facial-image-based positioning is crucial for many application

The aim of this research is to use robust technique by trimming, as the analysis of maximum likelihood (ML) often fails in the case of outliers in the studied phenomenon. Where the (MLE) will lose its advantages because of the bad influence caused by the Outliers. In order to address this problem, new statistical methods have been developed so as not to be affected by the outliers. These methods have robustness or resistance. Therefore, maximum trimmed likelihood: (MTL) is a good alternative to achieve more results. Acceptability and analogies, but weights can be used to increase the efficiency of the resulting capacities and to increase the strength of the estimate using the maximum weighted trimmed likelihood (MWTL). In order to perform t

Investigating the heavy metals in soil is important to the life of humans and living organisms. Diyala River Lower Reaches was chosen due to the changes in environmental characteristics that took place in recent years. Twelve sediment samples were collected from four different sites. The physical, and chemical properties and the concentrations of nine heavy metals were indicated. The results showed that the average concentrations of arsenic, copper, chromium, cobalt, iron, manganese, nickel, lead, and zinc are 8.5, 45.7, 538.5, 12.2, 5.07, 991.7, 183.5, 16.07, 136.5 ppm, respectively. They reflect contamination with arsenic, chromium, and nickel, while they are free of lead, and zinc contamination, according to the Environmental Pro

This study was carried out to measure the percentage of heavy metals pollution in the water of the Diyala river and to measure the percentage of contamination of these elements in the leafy vegetables grown on both sides of the Diyala river, which are irrigated by the contaminated river water (celery, radish, lepidium, green onions, beta vulgaris subsp, and malva). Laboratory analysis was achieved to measure the ratio of heavy element contamination (Pb, Fe, Ni, Cd, Zn and Cr) using flame atomic absorption spectrophotometer during the summer months of July and August for the year 2017. The study showed that the elements of zinc, chromium, nickel and cadmium were high concentrations and exceeded. The maximum concentration of these

The present work initiated to eaIuate the efficiency of Al-Rustamivah sewage treatment plant
as reflected by the quality of final effluent that is thrown to Di ala river. Weekly samples of
wastewater and final effluent were collected between November 1994 and end of January
1995 and analyzed for different chemical and biological features. Results ha e inidicated that
Al-Rustamiyah sewage treatment plant could not be able efficiently to purify the raw sewage.
The mean values of suspended solids. BOD. COD Dichromate and Oil & grease effluents
were felt to pass standard limits (98.4. 92.8. 125.2 and 39.1 ppm. respectiel). The atherse
possible effects of pollution on Diuala equatic life hae been also discussed in res

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci