JOURNAL OF EDUCATION AND SCIENCE

This research deals with the preparation number of composite materials by casting the base alloy (Al-Co-Ni) by adding chromium oxide (Cr2O3) as reinforcement material, by weight ratios of (5, 10, 15 wt%) for the base alloy, with heat treatment of the prepared alloys. The basic alloys and composite materials were prepared by using solution casting method and manual mixing method to disperse reinforcement grains in the base alloy floor and with pressure of 5 ton in purpose of forming. The materials were melted and poured into molds and suddenly cooled in cold water, after the molten samples were frozen. The attenuation factor of gamma rays was founded the prepared alloys and their homogeneity was examined by shining a narrow beam of single energy gamma rays emitted from the radiating source (137Cs) with different energies (511, 662, 1173, 1284, 1333) keV respectively, gamma ray system (UCS-20) was being used which bounded to NaI(Tl) scintillation detector. The homogeneity of base alloy and composite material was determined by studying the contrast of gamma ray intensity, the linear attenuation coefficient at seven different locations at any samples and the percentage standard deviation. The results showed that the highest value of the linear attenuation coefficient was 0.252 mm-1 for sample [5%Cr2O3+Al+Co+Ni] with the energy (511 keV) and that the lowest value for the ratio of linear attenuation coefficient was 0.062 mm-1 at the energy of sample [15%Cr2O3+Al+Co+Ni] with the energy (1333 keV) indicating that the homogeneity of the sample [15%Cr2O3+Al+Co+Ni] at energy (1333 KeV).

Abstract:
Human activity recognition has an important role in the interaction between human and human relationships because it provides information about a person's identity, personality, activities, psychological state, and health, all this information is difficult to extract due to the difficulty of a person's ability to identify the activities of another person and is considered one of the basic research topics in the scientific fields in the field of computer vision and machine learning. the purpose of human activity recognition (HAR) is to identify the different human activities throw monitoring and register the human activates and the various surrounded environment, by using computers, the human activity recognition researches which depending on visions is the basics of lots of applications even video monitoring or health care and security monitoring and the interaction between the human and the computers.
In this research, a review of the newest development in the human activity recognition branch have been studied, and the different ways to recognize the human actions, an important detail have been shown to preview the HAR researches and the methodologies used to represent the human activates and its classifications, to provide an overview of the HAR methods and comparing them

Data mining (DM) is an amazing innovation with incredible potential to help organizations centre on the main data in the information they have gathered about the conduct of their clients and expected clients. It finds data inside the information that questions and reports can't viably uncover. For the most part, DM is the way toward examining information from alternate points of view and summing up it into helpful data - data that can be utilized to expand income, reduces expenses, or both. There are four types of DM: 1) Classification and regression, 2) Clustering, 3) Association Rule Mining, and 4) Outlier/Anomaly Detection. Tending to the velocity part of Big Data (BD) has as of late pulled in a lot of revenue in the investigation local area because of its critical effect on information from pretty much every area of life like medical services, financial exchange, and interpersonal organizations, and so on. Many research works have investigated this velocity issue through mining data streams. Most existing data stream mining research centres on adjusting the primary classifications of approaches, methods and methods for static information to the dynamic information circumstance. This research explores widely the current writing in the field of data stream mining and recognizes the fundamental preparing units supporting different existing methods. This study not simply benefits examiner to make strong assessment subjects and separate gaps in the field yet moreover helps specialists for DM and BD application structure headway.

The uranium concentration and radioactivity of radon gas were measured in Al-Kasik refinery and Ain Zala field using the CR-39 detector. Soil and water samples associated with the production stages of oil, Sludge and crude oil were collected. The levels of uranium concentration in soil ranged from 0.703 to 1.480 ppm, in water samples from 0.681 to 0.716 ppm, in Sludge samples from 0.849 to 1.014 ppm, and in crude oil from 0.785 to 0.933 ppm. As for the radioactivity of radon gas, when comparing the radon rate in the samples we obtained with the global values, it was found that it falls within the internationally permissible limit, where the radon rate in the soil was 12.81 Bq/kg and when compared with the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) which has a value of 32 Bq/kg, and in the produced water it was 8.66 Bq/kg compared to (UNSCEAR)which has a value of 50 Bq/kg. In Sludge samples 11.81 Bq/kg and when compared with the International Atomic Energy Agency (IAEA) whose value is(8-5×〖10〗^5) Bq/kg, and in crude oil samples 10.56 Bq/kg and when compared with the International Federation of Oil and Gas Producer (IOGP) whose value is (800-4×〖10〗^5) Bq/kg. As for the alpha ray hazard index, the results showed that it is within the permissible limits internationally, where the results were less than 1 and therefore does not pose a threat to the health of workers and environment.

ABSTRACT :
In the current research, 23 wells were chosen from some residential neighborhoods located in the city of Mosul. To study some of the physical properties of well water represented by temperature, electrical conductivity, and total dissolved salts, as well as, the study of chemical analyzes are: (sulfates, chlorides, phosphates, nitrates, sodium, potassium, calcium, magnesium, dissolved oxygen and pH).
The results of the study refer to the height of the electrical conductivity, which ranged between (791-2456) µmhos/cm. The results showed that a lot of water is free of dissolved oxygen, as it recorded the highest value of 4.6 mg/l. Whereas, the temperature of the studied water ranged between (20-28.4)Cº, and it is considered warm water. In the current study, the calcium ion concentration was greater than the magnesium ion concentration in all well water, and the highest concentration reached (264 and 134) mg/L at well 22 and 23, respectively. There was an increase in the concentration of chloride ion, which reached (204) mg/L and the lowest concentration (32) mg/l at wells 11 and 7, respectively.
When comparing the values of the electrical conductivity of the well water with the global determinants of drinking, it was determined that they are not suitable for drinking.
When applying the relationship between the value of the electrical conductivity and the ratio of sodium adsorption to well water, it was found that all water from wells Class (C3 - S1) except for wells (11 and 19) are classified as Class (C4 - S1)

The main purpose of this paper is to create a palmprint recognition system (PPRS) that uses the curvelet transform and co-occurrence matrix to recognize a hand's palmprint.
The suggested system is composed of several stages: in the first stage, the region of interest (ROI) was taken from a palmprint image, then in the second stage, the curvelet transform was applied to the (ROI) to get a blurred version of the image, and finally, unsharp masking process and sobel filtering were done for edge detection. The third stage involves feature extraction using a co-occurrence matrix to obtain 16 features, while the fourth stage inclusion is the training and testing of the suggested approach. The algorithm ACO (ant colony optimization) has been adopted to evaluate the shortest path to the goal.
CASIA PalmprintV dataset of 100 people (60 male and 40 female) was used in proposed work to rate the performance of the proposed system. ARR and EER metrics have been adopted to assess the performance of the proposed system.
The experimental results showed a very high recognition rate (ARR) that reaches 100% for the right hand of a male and the left hand of a female. The overall accuracy rate (ARR) reaches 98.5% and EER equals 0.015.

Vertical cavity surface emitting laser VCSEL is currently the main solution for many technological aspects, ultrafast optical interconnecting, Gigabit Ethernet, etc. In this paper we present the simulation results by using Optiwave™ software version 7, of the effects of optical mode confinement factor on the modulation properties)which inspected by eye diagram of the received signals)of the vertical cavity surface emitting laser VCSEL, with the range (8-20)Gbps of pseudo random bit sequence PRBS. The quality of the VCSEL modulation have been inspected by time domain signals, spectrums and eye diagram. Simulation results appeared an improvement in the characteristics of received bit sequences of (8, 10, 12.5, 16 and 20)Gbps bit rates, represented by the rising the value of quality factor QF (1.77 to 4.81) versus increasing the value of optical mode confinement factor Γ(0.2 to 0.5) respectively, and a decreasing in jitter time of superimposed traces of eye pattern and well opining eye pattern. And in the corresponding, the bit error rates BERs of the received signals have been decreased, with rising the value of mode confinement factor Γ of the laser at constant modulation index and constant temperature of the laser. Also, the VCSEL’s modulation response differences with different bitrates, causes different values of QF and BER for individual value of mode confinement factor Γ.

In every day, there is a great growth of the Internet and smart devices connected to the network. On the other hand, there is an increasing in number of malwares that attacks networks, devices, systems and apps. One of the biggest threats and newest attacks in cybersecurity is Ransom Software (Ransomware). Although there is a lot of research on detecting malware using machine learning (ML), only a few focuses on ML-based ransomware detection. Especially attacks targeting smartphone operating systems (e.g., Android) and applications. In this research, a new system was proposed to protect smartphones from malicious apps through monitoring network traffic. Six ML methods (Random Forest (RF), k-Nearest Neighbors (k-NN), Multi-Layer Perceptron (MLP), Decision tree (DT), Logistic Regression (LR), and eXtreme Gradient Boosting (XGB)) are applied on CICAndMal2017 dataset which consists of benign and various kinds of android malware samples. A 603288 benign and ransomware samples were extracted from this collection. Ransomware samples are collected from 10 different families. Several types of feature selection techniques have been used on the dataset. Finally, seven performance metrics were used to determine the best one of feature selection and ML classifiers for ransomware detection. The experiments results imply that DT and XGB outperforms other classifiers with best detection accuracy are more than (99.30%) and (99.20%) for (DT) and (XGB) respectively.

This research work include studying one of the natural mineral ores available in Al-Hawy area (Mosul city – Northern Iraq) by chemical analysis and X-ray fluorescence (XRF) to identify its components of the elements as oxides, X-ray diffraction was carried out  to determine the percentages of clay minerals (natural zeolites) and non-clay minerals in the natural ore. The natural zeolites were concentrated by removing carbonate, iron and separating the convertible silica into sodium silicate, the prepared zeolite was converted  into (H-form) by treated with  ammonium nitrite solution (1M) ,then grafted with ruthenium chloride (RuCl₃.6H₂O) .The properties and specifications of the prepared zeolite (grafted and non-grafted) were studied using techniques of (XRF) ,(XRD),(BET) , (SEM) and (differential& thermo gravimetric analysis(DTA)&(TGA) ) ,it was found that have a chemical and crystalline composition within the specifications of zeolites, as well as a good surface area , thermal stability and selective porous channels.

The detection and tracking of head movements have been such an active area of research during the past years. This area contributes highly to computer vision and has many applications of computer vision. Thus, several methods and algorithms of face detection have been proposed because they are required in most modern applications, in which they act as the cornerstone in many interactive projects. Implementation of the detected angles of the head or head direction is very useful in many fields, such as disabled people assistance, criminal behavior tracking, and other medical applications. In this paper, a new method is proposed to estimate the angles of head direction based on Dlib face detection algorithm that predicts 68 landmarks in the human face. The calculations are mainly based on the predicated landmarks to estimate three types of angles Yaw, Pitch and Roll. A python program has been designed to perform face detection and its direction. To ensure accurate estimation, the particular landmarks were selected, such that, they are not affected by the movement of the head, so, the calculated angles are approximately accurate. The experimental results showed high accuracy measures for the entire three angles according to real and predicted measures. The sample standard deviation results for each real and calculated angle were Yaw (0.0046), Pitch (0.0077), and Roll (0.0021), which confirm the accuracy of the proposed method compared with other studies. Moreover, the method performs faster which promotes accurate online tracking.

The objective is to use AI techniques to build a citrus image recognition system and to produce an integrated program that will assist plant protection professionals in determining whether the disease is infected and early detection for the purpose of taking the necessary preventive measures and reducing its spread to other plants. In this research, the RBF and FRBF networks were used and applied to 830 images, to detect whether citrus fruits were healthy or ill. At first, the preprocessing of these images was done, and they were reduced to 250 x 250 pixels, and the features were extracted from them using the co-occurrence matrix method (GLCM) after setting the gray level at 8 gradients and 1 pixel distance, 21 statistical features were derived, and then these features were introduced to RBF after determine the number of input layer nodes by 21 , 20 for the hidden layer and 1 node for output layer, the centers were randomly selected from the training data and the weights were also randomly selected and trained using the Pseudo Inverse method. The RBF network was hybridized with the fuzzy logic using the FCM method, the fuzziness parameter = 2.3 was selected, and a new network called FRBF was acquired. These networks were trained and tested in training data (660 images) and testing (170 images) for citrus fruits. The detection rate was then calculated, and the results showed that the (FRBF) had a higher accuracy of 98.24% compared to RBF of 94.71%.

A simple sensitive spectrophotometric method has been suggested for the estimation of pure p-aminophenol(p-AMPL), and p-AMPL results from the hydrolysis of paracetamol(PARL). The suggested method is based on oxidative coupling reaction of p-AMPL with 4-chlororesorcinol (4-CLRL) and potassium periodate to produce a stable, and water-soluble coloured product with maximum absorption at wavelength 556 nm. Beer's law is followed over the range of concentration from 2 to 20 µg p-AMPL. ml-1. The molar absorptivity value is equal to 1.0277×104 l.mol-1cm-1. All factors responsible for the completed reaction and highest intensity of the product have been studied, and the optimal of each factor has been selected. The suggested method was applied in an indirect method for the
determination of paracetamol in tablets and injection after acidic hydrolysis to p-AMPL. The common excipients added did not interfere in the estimation of paracetamol.
The suggested method was applied in an indirect method for the
determination of paracetamol in tablets and injection after acidic hydrolysis to p-AMPL. The common excipients added did not interfere in the estimation of paracetamol.

Cinnamaldehyde was used to condense with substituted acetophenone then with acetone to form substituted 2,4- diene -1- pentanone (1- 4), after two moles of cinnamaldehyde condense with one mole of acetone to form 1, 5- diphenyl nona- 8- tetraene -5 – one (5), for these reactions, sodium hydroxide was used as a catalyst, the resulted compounds reduced by Luche (specific reduction agent use cerium chloride as a catalyst with sodium borohydride to protect double bond) reaction to form 2,4- diene-1- methoxy pentane (6-9) and -5- methoxy nona- 1,3,6,8 – tetraene – 1,9 - diyl dibenzene (10), the resulted dienes compound converted to endoperoxides (11- 15) via singlet oxygen reaction in the present of Rose Bengal as a catalyst with light in chlorinated solvent and finally by appling of Appel reaction condition these compounds converted to furans (16- 20). All mechanisms of the reaction were listed. These compounds were identified by thin layer chromatography TLC, and by their physical properties in addition, the IR spectroscopy and 1HNMR.

The importance of atmospheric nitrogen-fixing bacteria The study aimed to isolate bacteria from the roots of plants From four areas of the city of Mosul the winter agriculture, season 2020-2021 and using biochemical tests and phenotypic and agricultural characteristics to diagnose bacterial isolates and study sensitivity and resistance of bacterial isolates to ten antibiotics. if the results showed that the highest percentage of resistance was to the two antibiotics, Trimethoprim, and streptomycin, at 100%, while The least resistance was to the two antivirals Gentamycin and Rifampicin by 20%. In addition to Studying The sensitivity and resistance of bacterial isolates to four heavy Metals, namely Mercury chloride (HgCl), Cobalt chloride (CoCl), Cadmium Chloride (CdCl), and nickel chloride (NiCl). The resistance was high with Cadmium chloride salt (CdCl) and the lowest salt Mercury Chloride (HgCl). PCR techniques were used to diagnose samples based on 16S rRNA sequence analysis and comparison of sequences resulting from DNA amplification with standard isolates within NCBI to detect new bacterial isolates

Abstract.
The prediction of rate constant of Ethers reaction with Chloramine-T has been studied theoretically in this work using ab-initio and statistical calculations. The first order reaction between Ethers and Chloramine-T shows that the rate constant depends on the Ethers concentration. Therefore, ab initio calculations were used using DFT/ b3lyp with 6-311++G** as a basis set to extract the most stable geometry of the chosen ethers. Also, several physical parameters have been gained form these calculations such as mulliken charge at the active atoms, dipole moment, Homo and Lomo energy levels, Hardness, Electronic Chemical Potential and Global Electrophilicity Index. The relationship between these physical variables plays an effective role in the reaction rate. Therefore, statistical calculations were used to investigate the possible relationship between these physical parameters. These relationships can be predicted from the value of the correlation coefficient (R2) and the Standard error (SE). Simple regression analysis and multiple regression analysis were performed between these physical variables as independent variables and rate constant as a dependent variable using SPSS software. The results show high value of R2 (0.993) of the regression analysis which reflects the high relationship between these variables that affects the reaction rate concentration. The out data illustrates negligible differences (about 0.008) between the experimental and calculated rate constant value.