Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning models for a variety of tasks under the control of a unified architecture for each proposed model.
The current study performed in order to detect and quantify epicatechin in two tea samples of Camellia sinensis (black and green tea) by thin layer chromatography (TLC) and high performance liquid chromatography (HPLC). Extraction of epicatechin from black and green tea was done by using two different methods: maceration (cold extraction method) and decoction (hot extraction method). Qualitative and quantitative determinations of epicatechin in two tea samples were investigated. Epicatechin identification was made by utilizing preliminary chemical tests and TLC. This identification was also boosted by HPLC and then quantified epicatechin in all ethyl acetate fractions of two tea samples. This research revealed the existence of epica
... Show MoreSome azo compounds were prepared by coupling the diazonium salts of amines with 2,4-dimethylphenol The structure of azo compounds were determined on the basis of elemental analyses, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Complexes of nickel(II) and copper(II) have been synthesized and characterized. The composition of complexes has been established by using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as conductivity magnetic susceptibility measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range (1×10-4 - 3×10-4 M). High molar absorbtivity of the complex solutions were observ
... Show MoreA rapid high performance liquid chromatography method for the determination of sphinganine (Sa) and sphingosine (So) in urine samples by employing a silica-based monolithic column is described. The samples were first extracted using ethyl acetate and derivatized using ortho-phthaldialdehyde in the presence of 2-mercaptoethanol. C20 sphinganine was used as internal standard. Under the optimized conditions, separation was achieved using a mixture of methanol:water (93:7, v/v), column temperature at 30°C, flow rate of 1 mL min−1, and an injection volume of 10 μL. Good linearity was obtained for Sa and So over the concentration range 20–500 ng mL−1(correlation coefficients ≥0.9978). The detection limits were 0.45 ng mL−1 for Sa and
... Show MoreABSTRACT
Two compounds were isolated from the fruit part of Rhus coriaria that grow wildly or cultivated in the north of Iraq. The compounds were separated by preparative high-Performance Liquid Chromatography and their structures were established based on detailed spectroscopic techniques like FTIR and LC-MS/MS.
Keywords: Rhus coriaria, Preparative HPLC, LC-MSMS, FTIR
The tourism industry has undergone exponential transformation, reshaped by online travel agencies (OTAs), shifting consumer preferences, and technological advancements. Established OTAs like TripAdvisor and Travelocity face pressures to adapt their strategies to capitalize on these disruptive landscape changes. This research involves a comparative analysis examining the key challenges confronting TripAdvisor and Travelocity, with a focus on opportunities to leverage artificial intelligence (AI) in enhancing personalization and the traveler experience. The study utilizes publicly available data on the companies and academic literature on AI innovation diffusion. Findings reveal that while TripAdvisor has actively developed AI-based trip plan
... Show MoreThe aim of this study is to construct a Mathematical model connecting the variation between the ambient temperatures and the level of consumption of kerosene in Iraq during the period (1985-1995), and use it to predict the level of this consumption during the years (2005-2015) based on the estimation of the ambient temperatures.
This research aims to apply the Performance Focused Activity Based Costing System in the offices of scientific and advisory services at the University of Technology for the purpose of measuring the cost of services provided by these offices in order to reduce costs. To test the hypothesis of the research, the research was applied in the consulting offices of the University of Technology through the financial statements for the year ending 12/31/2017 of the Scientific and Consulting Services Office of the University of Technology, because the data of these years were issued and audited by the Federal Office of Financial Supervision.
A number of
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