The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Vol. 6, Issue 1 (2025)

Abstract

  In this study, modified organic solvent (organosolv) method was applied to remove high lignin content in the date palm fronds (type Al-Zahdi) which was taken from the Iraqi gardens. In modified organosolv, lignocellulosic material is fractionated into its constituents (lignin, cellulose and hemicellulose). In this process, solvent (organic)-water is brought into contact with the lignocellulosic biomass at high temperature, using stainless steel reactor (digester). Therefor; most of hemicellulose will remove from the biomass, while the solid residue (mainly cellulose) can be used in various industrial fields. Three variables were studied in this process: temperature, ratio of ethano

This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The

(4R)-2, 3-(2`-chloro-2`- carboxyl)-1, 3-dioxolano-4- (2- dimethyl –dioxolane -yl) ascorbic acid (HL), a derivative of L-ascorbic acid was prepared by the reaction of 5,6-O-isopropylidene–L-ascorbic acid with trichloroacetic acid in alkaline medium. Seven new metal ion complexes of this ligand (HL) were prepared through its direct reaction with the chlorides of Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II) ions respectively. The new ligand and its ion metal complexes were characterized applying elemental analyses,1H and 13C NMR, IR as well as UV-Visible spectra. Spectroscopic data showed that the ligand (C11H11O8Cl) was coordinated to the metal ions through the two oxygen atoms of the carboxyl group as abidentate ligan

This work includes a detailed description of the Leucostoma nigricorpuris sp. nov. from
Iraq. Locality, host plants and data of collection were given.