This study aims to reveal the role of one of the artificial intelligence (AI) techniques, “ChatGPT,” in improving the educational process by following it as a teaching method for the subject of automatic analysis for students of the Chemistry Department and the subject of computer security for students of the Computer Science Department, from the fourth stage at the College of Education for Pure Science (Ibn Al-Haitham), and its impact on their computational thinking to have a good educational environment. The experimental approach was used, and the research samples were chosen intentionally by the research community. Research tools were prepared, which included a scale for CT that included 12 items and the achievement test in b

The study explored applications of artificial intelligence and its dialectical relationship with international human rights law of individuals, which requires assessing the effects of this technology on human rights and freedoms. The problem of privacy of humanity, as AI technologies can control human rights and freedoms, while monitoring potential violations in this context. The study use of documentary research and qualitative lens to analyze the data. In conclusion, unawareness of the use of AI may impose significant hurdles on future generations and may infringe on human rights across all sectors of society. The government should mandate obligations for artificial intelligence businesses concerning education, health, human right

The study intends to explore the obstacles that encounter a program of rehabilitating released prisoners as perceived by prisoners themselves in tubas' province. To this end, the researcher used a questionnaire as an instrument which was applied on (150) prisoner had chosen randomly to collect the study data. The findings revealed no significant differences among obstacles the encounter program regarding to the following variables: age, detention period, and number of detention, additionally, the findings found that there is a variance of obstacles mean according to the prisoners themselves, rehabilitation program, and the facility of that program.

This study focused on the improvement of the quality of gasoline and enhancing its octane number by the reduction of n-paraffins using zeolite 5A. This study was made using batch and continuous mode. The parameters which affected the n-paraffin removal efficiency for each mode were studied. Temperature (30 and 40 ˚C) and mixing time up to 120 min for different amounts of zeolite ranging (10-60 g) were investigated in a batch mode. A maximum removal efficiency of 64% was obtained using 60 g of zeolite at 30 ˚C after a mixing time 120 min. The effect of feed flow rate (0.3-0.8 l/hr) and bed height (10-20 cm) were also studied in a continuous mode. The equilibrium isotherm study was made using different amounts of zeolite (2-20 g) and the

This work is aiming to study and compare the removal of lead (II) from simulated wastewater by activated carbon and bentonite as adsorbents with particle size of 0.32-0.5 mm. A mathematical model was applied to describe the mass transfer kinetic.

The batch experiments were carried out to determine the adsorption isotherm constants for each adsorbent, and five isotherm models were tested to choose the best fit model for the experimental data. The pore, surface diffusion coefficients and mass transfer coefficient were found by fitting the experimental data to a theoretical model. Partial differential equations were used to describe the adsorption in the bulk and solid phases. These equations were simplified and the

 Prepared zeolite type A was used for theremoval of cesium ions from aqueous solution. The experimental data were analyzed by Langmuir, Freundlich isotherms. Various parameters, such as contact time, zeolite weight, pH, and initial concentration, were studied. The results indicated that the highest removal efficiency was95.53% at (2h time, 0.04 g weight, and pH=6.8). The results also showed that the Freundlic model fits well with the experimental results and is better than the Langmuir model.

This article aims to investigate how war contributes to the pollution of water bodies with harmful substances including heavy metals and toxic substances. The paper explains how these pollutants, carelessly dumped by military operations, have severely damaged the water quality of rivers and lakes all across Iraq. Based on the Jassim River as case study, the paper shows a close relationship between military operations and pollution. Shown is the effects of this pollution on local ecosystems like fish and wildlife, and human population, dependent on the river for drinking, irrigation, and other basic needs. The article reveals the problem of military waste in Iraq, focusing on the absence of satisfactory waste disposal techniques and

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le