Baker's Yeast is an important additive among the substances, which improves bred quality, thus, a consideration has been made to study the conditions and parameters that affecting the production of the yeast in a batch fermenter experimentally and theoretically. Experimental runs were implemented in a 12-liter pilot-scale fermenter to predict the rate of growth and other parameters such as amount of additive consumed and the amount of heat generated. The process is modeled and performed using a computer programming prepped for this purpose, the model gave a good agreement comparing to the experimental work specially in the log phase.

THE Schiff base reaction played an important role of the condensation reaction between 2-aminophenol and Glyoxylic acid in the presence of calculated amounts of KOH as a catalyst. The reaction has been carried out in ethanol under reflux and stirring condition for 3.5 hrs. All syntheses were carried out under hydrogen gas forming a new potassium (E)-1-hydroxy-2-(2-hydroxyphenylimino)ethanolate ligand type [NO2]. The ligand of the general formula K2[Mn(L2)] type and its Mnп complex K2[Mn(N2O4)] type, has been characterized by spectroscopic methods (F.T-I.R. and U.V-Vis.), elemental analysis (C.H.N) metal content, magnetic susceptibility measurement, Thin-layer chromatography (T.L.C), X-RD powder diffraction, 1H-NMR, 13C-NMR molar conductanc

The present study has three objectives: 1) to investigate the prevalence of complex nominals in economic discourse represented via the selected business news texts, 2) to shed some light on the most common translation errors made by second year students in the Department of Translation in rendering complex nominals into Arabic, and 3) to detect the possible causes behind such translation errors and suggest some translation tips which might sound helpful to the students of translation to find the most suitable translation equivalent. The present study is based on an empirical survey in which a selective analysis of someeconomic texts represented in business news texts is made. A corpus of 159 complex nominals was selected from seven busin

In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%

In this research tri metal oxides were fabricated by simple chemical spray pyrolysis technique from (Sn(NO₃)₂.20 H₂O, Zn(NO₃)₂.6 H₂O, Cd(NO₃)₂.4 H₂O) salts at concentration 0.1M with mixing weight ratio 50:50 were fabricated on silicon substrate n-type (111). (with & without the presence of grooves by the following diemensions (20μm width, 7.5μm depth) with thickness was about ( 0.1 ±0.05 µm) using water soluble as precursors at a substrate temperature 550 ºC±5, with spray distance (15 cm) and their gas sensing properties toward H₂S gas at different concentrations (10,50,100,500 ppmv) in air were investigated at room te

The oil and gas industry relies heavily on IT innovations to manage business processes, but the exponential generation of data has led to concerns about processing big data, generating valuable insights, and making timely decisions. Many companies have adopted Big Data Analytics (BDA) solutions to address these challenges. However, determining the adoption of BDA solutions requires a thorough understanding of the contextual factors influencing these decisions. This research explores these factors using a new Technology-Organisation-Environment (TOE) framework, presenting technological, organisational, and environmental factors. The study used a Delphi research method and seven heterogeneous panelists from an Oman oil and gas company

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol