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Artificial Intelligence and Cybersecurity in Face Sale Contracts: Legal Issues and Frameworks
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The sale of facial features is a new modern contractual development that resulted from the fast transformations in technology, leading to legal, and ethical obligations. As the need rises for human faces to be used in robots, especially in relation to industries that necessitate direct human interaction, like hospitality and retail, the potential of Artificial Intelligence (AI) generated hyper realistic facial images poses legal and cybersecurity challenges. This paper examines the legal terrain that has developed in the sale of real and AI generated human facial features, and specifically the risks of identity fraud, data misuse and privacy violations. Deep learning (DL) algorithms are analyzed for their ability to detect AI generated faces in order to potentially function as an AI safety in face sale agreement to allow the authenticity and protecting data. In addition, it examines the legal mechanisms surrounding consent, liability and data protection and suggests changes to help accommodate the complexity of AI. This paper proposes a framework by which AI tools can be integrated into the evolution of cybersecurity strategies, to mitigate risks and ensure compliance with such new legal standards and contribute to discussing the ethical and secure use of AI in Face sale contracts.

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Publication Date
Sun Dec 31 2023
Journal Name
College Of Islamic Sciences
The Approach of Discretion in Contemporary Jurisprudential Issues, with Imam Al-Qaradawi The Jurisprudence of Minorities as a Model
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Research Objectives: The research aims to highlight the approach of Imam Al-Qaradawi in contemporary jurisprudence in the recent issues of the jurisprudence of minorities, and mentioning the foundations of jurisprudence of minorities, along with some of the practical applications of Imam Al-Qaradawi.

Study Methodology: The researcher applied the inductive, analytical and comparative approach by tracking the scientific material related to the subject of the study from the books of Al-Qaradawi in the first place, then by comparing the legal provisions with what had been stated in the four schools of jurisprudence.

Findings: The interest and need of Muslim minorities in non-

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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of The College Of Languages (jcl)
DIFICULTADES DE TRADUCCIÓN DE LOS TEXTOS JURÍDICOS DEL ESPAÑOL AL ÁRABE DIFFICULTIES OF TRANSLATION OF LEGAL TEXTS IN SPANISH ARABIC
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Resumen:

 El presente trabajo intenta analizar las características del lenguaje jurídico español a cuya estructura se debe su complejidad. A la vez, damos una descripción detallada de sus rasgos morfosintácticos, léxico-semánticos y estilísticos. En ningún momento, pretendemos fijar unas pautas o normas para la traducción de este lenguaje que requiere unos previos conocimientos jurídicos y cierta preparación para proceder a realizar esta tarea. Nuestra intención es, simplemente, ofrecer al lector árabe una pequeña visión de lo difícil que es comprender los textos legales españoles hasta para los nativos para imaginarse las posibles dificultades a la hora de iniciar a traducirlos.

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Publication Date
Mon May 19 2025
Journal Name
Retos
The effect of the cube model on visual-spatial intelligence and learning the skill of spiking in volleyball for female students
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Objective: To identify the effect of the cube model on visual-spatial intelligence and learning the skill of spikinging in volleyball for female students, The researchers used the experimental method by designing two equivalent groups with pre- and post-measurements. Research methodology: The main research sample of (30) female students was selected from the research community represented by second-stage students in the College of Physical Education and Sports Sciences - University of Baghdad for the academic year (2024-2025). The sample was divided equally into two control and experimental groups. The researchers conducted the sample homogenization process and the equivalence process between the two groups in the variables of visua

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Publication Date
Sun Mar 10 2024
Journal Name
Journal Of Sport And Health Research
Personal social and self-intelligence and its relationship to the performance of the individual and collective kinetic formation rhythmic gymnastics of school students.
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The study aims to follow modern methods in teaching rhythmic gymnastics skills by directing learners to develop their perceptions and absorb what the world deals with today and develop intelligence among learners, the researchers searched for the strengths of the learner by providing them with an opportunity to form their kinetic formation, hence the problem came by introducing a method of self-intelligence and social to guide the learner in the search for ways and solutions to overcome boredom and economy Time and effort in the educational process in learning and give them the freedom to express their ideas And their skills and here came the role of social and self-intelligence to teach the individual and collective kinetic formati

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Water Quality Assessment and Sodium Adsorption Ratio Prediction of Tigris River Using Artificial Neural Network
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Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-201

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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Publication Date
Tue Jul 17 2018
Journal Name
International Journal Of Adaptive Control And Signal Processing
Single channel informed signal separation using artificial-stereophonic mixtures and exemplar-guided matrix factor deconvolution
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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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