The electronic properties and Hall effect of thin amorphous Si1-xGex:H films of thickness (350 nm) have been studied such as dc conductivity, activation energy, Hall coefficient under magnetic field (0.257 Tesla) for measuring carrier density of electrons and holes and Hall mobility as a function of germanium content (x = 0–1), deposition temperature (303-503) K and dopant concentration for Al and As in the range (0-3.5)%. The composition of the alloys and films were determined by using energy dispersive spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS).
This study showed that dc conductivity of a-Si1-xGex:H thin films is found to increase with increasing Ge content and dopant concentration, whereas conductivity activation energy decreases with increasing Ge content and dopant concentration. The carrier density (electrons and holes) of prepared films increases with increasing Ge content, dopant concentration and deposition temperature. The mobility and the mobility activation energy increase with increasing Ge content. The width of localized state is 0.215 eV for a- Si0.5Ge0.5:H thin film deposited at 503 K.
Banks face different types of banking risks that limit the performance of its functions and achieve its objectives, including the financial risk that is based on current research into two types including a credit and liquidity risks. And established credit risk due to the possibility of delaying the borrowers to fulfill their obligations to the bank when due or non-payments on according to the terms agreed upon, while liquidity risk arises as a result of the inability of the bank to fund the financial needs, any inability to provide cash to pay its obligations short on credit without achieving tangible loss or the inability to employ the funds properly and show the liquidity risk in the event of inadequate cash inflows to the bank for an
... Show MoreThe experiment was carried out in the Department of Biology, College of Education for Pure Science –Ibn AL Haitham, University of Baghdad, Iraq, during the growing season 2017 – 2018. The objective was to find out the effect of foliar spraying of tryptophan and IQ COMBI nano fertilizer on cumin plants. The obtained results show that both tryptophan and IQ COMBI nano fertilizer increased plant height, root length, shoot dry weight, the content of nitrogen, phosphorus, potassium, protein percentage, no. compound umbel.plant-1, wt. seeds. plant-1. The optimum treatment combination was calculated as 30 mg.L-1 tryptophan, 1000mg.L-1 IQ COMBI nano fertilizer, which gave the highest values for most of the parameters studied
n this study new derivatives of Schiff bases (5-10) were synthesized from the new starting material 1 . Which has been synthesized by the reaction of (1 mol.) of dichloroacetic acid with two moles of morpholine, in the presence of potassium hydroxide, Ester derivatives 2 and 3 were synthesized by the reaction of 1 with methanol or ethanol respectively in the presence of sulphuric acid as catalyst . Compound 2 was also prepared from dimethylsulphate with high yield , 2 and 3 was used to synthesized 2,2-dimorpholinylacetohydrazide 4 via reaction with NH2NH2.H2O 80% .Imines (5-10) were synthesized via the reaction of 4 with appropriate aromatic aldehydes in the presence of G.A.A as a catalyst . Derivatives compounds (1-10) were identifie
... Show MoreThe logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .
The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result. &nbs
... Show MoreThis research represents a practical attempt applied to calibrate and verify a hydraulic model for the Blue Nile River. The calibration procedures are performed using the observed data for a previous period and comparing them with the calibration results while verification requirements are achieved with the application of the observed data for another future period and comparing them with the verification results. The study objective covered a relationship of the river terrain with the distance between the assumed points of the dam failures along the river length. The computed model values and the observed data should conform to the theoretical analysis and the overall verification performance of the model by comparing i
... Show MoreReducing global warming potential (GWP) of refrigerants is needed to the decrease of ozone-depleting of refrigeration systems leakages. Refrigerant R1234yf is now used to substitute R134a inside mobile air conditioning systems. Thermodynamic properties of R1234yf are similar to R134a. Also, it has a very low GWP of 4, compared to 1430 for R134a, making it a proper choice for future automobile refrigerants. The purpose of this research is to represent the main operating and performance differences between R1234yf and R134a. Experimental analysis was carried out on the automotive air conditioning system (AACS) with 3 kW nominal capacity, to test and compare the performance of R134a with R1234yf. Experiments were accomplish
... Show MoreThe prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices
... Show MoreThyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
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