This research aims to predict the value of the maximum daily loss that the fixed-return securities portfolio may suffer in Qatar National Bank - Syria, and for this purpose data were collected for risk factors that affect the value of the portfolio represented by the time structure of interest rates in the United States of America over the extended period Between 2017 and 2018, in addition to data related to the composition of the bonds portfolio of Qatar National Bank of Syria in 2017, And then employing Monte Carlo simulation models to predict the maximum loss that may be exposed to this portfolio in the future. The results of the Monte Carlo simulation showed the possibility of decreasing the value at risk in the future due to the dec

The purpose of this study was to find out the connection between the water parameters that were examined in the laboratory and the water index acquired from the examination of the satellite image of the study area. This was accomplished by analysing the Landsat-8 satellite picture results as well as the geographic information system (GIS). The primary goal of this study is to develop a model for the chemical and physical characteristics of the Al-Abbasia River in Al-Najaf Al-Ashraf Governorate. The water parameters employed in this investigation are as follows: (PH, EC, TDS, TSS, Na, Mg, K, SO₄, Cl, and NO₃). To collect the samples, ten sampling locations were identified, and the satellite image was obtained on the

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

Background: Plasma-activated water (PAW) is considered one of the emerging strategies that has been highlighted recently in the food industry for microbial decontamination and mycotoxin detoxification, due to its unique provisional characteristics. Aim: The effectiveness of PAW for aflatoxin B1 (AFB1), ochratoxin A (OTA), and fumonisin B1 (FB1) detoxification in naturally contaminated poultry feeds with its impacts on the feed quality were inspected. Methods: PAW-30 and PAW-60 were utilized for feed treatment for six time durations (5, 10, 15, 20, 40 and 60 min) each. The alterations in the physicochemical properties of PAW after different time durations of plasma inducement and treatment with and without feed samples were monit

This  study  is concerned   measuri ng the concentration of some

ions l ike  calci um,  sodium, potassium, chlor,  lithium, carbonate and bicarbonate in drinking  and  river water  in AI-Muthana  and AI-Basrah

cities_

These  ions usually are found in normal water.  When we take di!Ierent samples  from different  regions  on the  E uph rates river  in Al­ Muthana  and A1-Basrah cities  we fou nd that the d rinking water  in Al­ Basrah contains a high prccent from  those ions. The  low preccnt from those  ions found  in Arab  river as compared with Euphrates  river. This study

The right to property is one of the most fundamental rights enjoyed by individuals, and most national constitutions and laws, as well as international conventions, have to be respected and protected only in accordance with the economic and social development of the country (the so-called public benefit) and in return for just compensation. What is fair compensation?

Tigris River is one of the main important surface water resources in Iraq. This necessitates continuous study of its quality . The present study is concerned with the characteristics and quality of Tigris water passing through in Baghdad city. (eight) samples were collected from the river in the area Grea't City. The study periods were carried over four season, which has been sampled once represent the every season. First sampling 12-11-2012 represent the autumn season The second sampling 20-1-2013 to represent the winter season. The third in 25-3- 2013 to represent the Springer season. The fourth during 29-5-2013 to represent the summer spring season. In order to specify the water quality, a group of physical and chemical analyses have bee

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.