The objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have been selected (spindle speed, feed rate and cut depth) with three levels for each parameter. Three tools with different materials and geometry have been also used to design the experimental tests and runs based on matrix L9. The end milling process with several output characteristics is solved using a grey relational analysis. The results of analysis of variance (ANOVA) showed that the major influencing parameters on multi-objective response were spindle speed and cutting tool with contribution percentage (52.75%, 24%), respectively. In addition, the optimum combination of end milling process parameters was then validated by performing confirmation tests to determine the improvement in multi-response outputs. The confirmation tests obtained a minimum (surface roughness and micro-hardness) and maximum metal removal rate with grey relational grade of 0.784 and improvement percentage of 2.3%.
The quality of groundwater in the Al-Hawija area was assessed using a water quality index. Data of nine physico-chemical parameters of 28 groundwater wells were used to calculate the water quality index (WQI). A heterogeneous water quality was reported, where in close proximity to the Lesser Zab River (LZR), it has low WQI values and permissible for human consumptions due to the dilution processes by fresh water; whereas, it becomes deteriorated in areas located far away the river. The values of WQI ranges from 22 to 336, indicating a good to very poor groundwater quality.
In this work, the emission spectra and atomic structure of the aluminum target had been studied theoretically using Cowan code. Cowan code was used to calculate the transitions of electrons between atomic configuration interactions using the mathematical method called (Hartree-Fock). The aluminum target can give a good emission spectrum in the XUV region at 10 nm with oscillator strength of 1.82.
The hydrodynamic properties of laser produced plasma (LPP) were investigated for the purpose of creating a light source working in the EUV region. Such a light source is very important for lithography (semiconductor manufacturing). The improved MEDUSA (Med103) code can calculate the plasma hydrodynamic properties (velocity, electron density,
Analysis system of sports players is very important for individuals in weightlifting. Assessment of player and strength is important for the performance of weightlifting. This paper proposes an analytical method for weightlifters with check-by-frame video. This analysis system can compute the major steps of seven positions in both snatch and clean and jerk methods in frame-video weightlifting monitoring of movements. Each user can compute the major steps of the seven positions of Hu moments among two frames in the video during training, and the Euclidian distance can be computed for the Hu moment values and lifting moment values in the snatch and clean and jerk methods during training. The outcome of the proposed system shows on efficien
... Show MoreIn this paper, the theoretical cross section in pre-equilibrium nuclear reaction has been studied for the reaction at energy 22.4 MeV. Ericson’s formula of partial level density PLD and their corrections (William’s correction and spin correction) have been substituted in the theoretical cross section and compared with the experimental data for nucleus. It has been found that the theoretical cross section with one-component PLD from Ericson’s formula when doesn’t agree with the experimental value and when . There is little agreement only at the high value of energy range with the experimental cross section. The theoretical cross section that depends on the one-component William's formula and on-component corrected to spi
... Show MoreObjective: The aim of this study is to detect the effect of continuous exposure to Sodium Nitrite on 8-oxoguanine
DNA glycosylase (OGG1) gene which responsible on DNA repairs. DNA repair play a major role in maintaining
genomic stability when DNA exposure to damage. Genomic stability is very important for keeping body cells
healthy and to prevent many types of tumor development. Many genes are responsible for this job; one of them is
OGG1 gene.
Methodology: In current study two groups of mice were chronically exposed to sodium nitrite for six months and
eighteen months while third group was used as a control. Then sizes of OGG1 were estimated.
Results: The results exhibited in the unexposed (control) mice had two dif
An experiment was carried out in the fields of Agriculture College-Baghdad University during spring and autumn of 2015 by using a randomized complete blocks design with three replications. The first season hybridization was established among three pure cultivars of cowpea (Vigna uniguiculata L.) which: Ramshorn, California black eye and Rahawya in full diallel crosses according to Griffing with first method and fixed model (3 parents+ 3 diallel hybrids +3 reciprocal hybrids) and a comparison experiment was in autumn season. The result of statistical analysis showed that there was a significant difference among the parents and their hybrids for all the studied characters. The parent 1 was the higher for root nodules number , leaf number, pod
... Show MoreRenewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of
... Show MoreThe aim of this research is controlling the amount of the robotic hand catching force using the artificial muscle wire as an actuator to achieve the desired response of the robotic hand in order to catch different things without destroying or dropping them; where the process is to be similar to that of human hand catching way. The proper selection of the amount of the catching force is achieved through out simulation using the fuzzy control technique. The mechanism of the arrangement of the muscle wires is proposed to achieve good force selections. The results indicate the feasibility of using this proposed technique which mimics human reasoning where as the weight of the caught peace increases, the force increases also with approximatel
... Show MoreImage is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the tran
... Show MoreAutism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
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