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.
This work concerns the thermal and sound insulation as well as the mechanical properties of polymer matrix composite reinforced with glass fibers. These fibers may have dangerous effect during handling, for example the glass fibers might cause some damage to the eyes, lungs and even skin. For this reason the present work, investigates the behavior of polymer composite reinforced with natural fibers (Plant fibers) as replacement to glass fibers. Unsaturated Polyester resin was used as matrix material reinforced with two types of fibers, one of them is artificial (Glass fibers) and the other type is natural (Jute, Fronds Palm and Reed Fibers) by hand lay-up technique. All fibers are untreated with any chemical solvent. The Percentage of mi
... Show MoreThis study proposed a biometric-based digital signature scheme proposed for facial recognition. The scheme is designed and built to verify the person’s identity during a registration process and retrieve their public and private keys stored in the database. The RSA algorithm has been used as asymmetric encryption method to encrypt hashes generated for digital documents. It uses the hash function (SHA-256) to generate digital signatures. In this study, local binary patterns histograms (LBPH) were used for facial recognition. The facial recognition method was evaluated on ORL faces retrieved from the database of Cambridge University. From the analysis, the LBPH algorithm achieved 97.5% accuracy; the real-time testing was done on thirty subj
... Show MoreIn this work, the antibacterial effectiveness of face masks made from polypropylene, against Candida albicans and Pseudomonas aeruginosa pathogenic was improved by soaking in gold nanoparticles suspension prepared by a one-step precipitation method. The fabricated nanoparticles at different concentrations were characterized by UV-visible absorption and showed a broad surface Plasmon band at around 520 nm. The FE-SEM images showed the polypropylene fibres highly attached with the spherical AuNPs of diameters around 25 nm over the surfaces of the soaked fibres. The Fourier Transform Infrared Spectroscopy (FTIR) of pure and treated face masks in AuNPs conform to the characteristics bands for the polypropylene bands. There are some differences
... Show MoreFace recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima
... Show MoreFor the duration of the last few many years many improvement in computer technology, software program programming and application production had been followed with the aid of diverse engineering disciplines. Those trends are on the whole focusing on synthetic intelligence strategies. Therefore, a number of definitions are supplied, which recognition at the concept of artificial intelligence from exclusive viewpoints. This paper shows current applications of artificial intelligence (AI) that facilitate cost management in civil engineering tasks. An evaluation of the artificial intelligence in its precise partial branches is supplied. These branches or strategies contributed to the creation of a sizable group of fashions s
... Show MoreAdverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
... Show MoreOver the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.
The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame
Stylistics is the analysis of the language of literary texts integrated within various approaches to create a framework of different devices that describe and distinct a particular work. Therefore, feminist stylistics relied on theories of feminist criticism tries to present a counter- image of a woman both in language use and society, to draw attention , raise awareness and change ways that gender represents. Feminist stylistic analysis is related not only to describe sexism in a text, but also to analyze the way that point of view, agency, metaphor, and transitivity choices are unanticipatedly and carefully connected to issues of gender(Mills,1995:1) &nb
... Show MoreHR Al-Hamamy, AA Noaimi, HA Salman, NAA Jabbar, American Journal of Dermatology and Venereology, 2013