On the propagation of disturbances in certain fluid flows

Imperial Users onl

Discrete Wavelet Transform Based Cancelable Biometric System for Speaker Recognition

The biometric template characteristics and privacy conquest are challenging issues. To resolve such limitations, the cancelable biometric systems have been briefed. In this paper, the efficient cancelable biometric system based on the cryptosystem is introduced. It depends on permutation using a chaotic Baker map and substitution using masks in various transform domains. The proposed cancelable system features extraction phase is based on the Cepstral analysis from the encrypted speech signal in the time domain combined with the encrypted speech signal in the discrete wavelet transform (DWT). Then, the resultant features are applied to the artificial neural network for classification. Furthermore, wavelet denoising is used at the receiver side to enhance the proposed system. The cryptosystem provides a robust protection level of the speech template. This speech template can be replaced and recertified if it is breached. Our proposed system enables the generation of various templates from the same speech signal under the constraint of linkability between them. The simulation results confirmed that the proposed cancelable biometric system achieved higher a level of performance than traditional biometric systems, which achieved 97.5% recognition rate at low signal to noise ratio (SNR) of -25dB and 100% with -15dB and above

The January 25th Uprisings: Through or in Spite of Civil Society?

Did the January 25th revolution emanate from civil society? Not if the conventional Western understanding of the term is used, and certainly not if its programmatic association with established organisations is assumed. This article explores the highly complex relationship between the arena we call civil society and the forms of activism we witnessed prior to, during and after the uprisings of January 25th. The article first argues that traditional civic associations did not catalyse the kind of agency that manifested itself in the January 25th uprisings. It suggests that pre?revolutionary associational life in Egypt reflects the presence of a civic rather than a civil society, which manifests itself in the values that the organisations and their leaders uphold. The second argument is that when state restrictions on political space were temporarily relaxed in 2005, those that assumed a civil role were groups and movements that did not organise through the conventional mainstream civic associations that we have come to identify as ‘civil society’. Finally, the article argues that the core group to have instigated the uprisings – the youth – had turned to a virtual participatory arena, precisely because their opportunities for exercising their agency fully were blocked in mainstream civil or civic associations

A Novel Convolutional Neural Network Based on Combined Features from Different Transformations for Brain Tumor Diagnosis

Brain tumors are a leading cause of death worldwide. With the advancements in medicine and deep learning technologies, the dependency on manual classification-based diagnosis drives down owing to their inaccurate diagnosis and prognosis. Accordingly, the proposed model provides an accurate multi-class classification model for brain tumor using the convolution neural network (CNN) as a backbone. Our novel model is based on concatenating the extracted features from the proposed three branches of CNN, where each branch is fed by the output of different transform domains of the original magnetic resonance image (MRI). These transformations include Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and the time-domain of the original image. Then, the CNN is employed followed by a concatenation layer, flatten laver, and dense layer, before using the SoftMax layer. The proposed model was applied to the Figshare dataset of brain tumor which consists of three classes pituitary, glioma, and meningioma. The results proved the advantage of the proposed system which achieved a high mean performance over 5-fold cross-validation with 98.89% accuracy, 98.78% F1-score, 98.74% precision, 98.82% recall, and 99.44% specificity. The comparative study with well-known models, as well as the pre-trained CNN models, established the potential of the proposed model. This novel approach has the potential to significantly improve brain tumor classification accuracy. It enables a more comprehensive and objective analysis of brain tumors, leading to improved treatment decisions and better patient care

A Novel Convolutional Neural Network Based on Combined Features from Different Transformations for Brain Tumor Diagnosis

Brain tumors are a leading cause of death worldwide. With the advancements in medicine and deep learning technologies, the dependency on manual classification-based diagnosis drives down owing to their inaccurate diagnosis and prognosis. Accordingly, the proposed model provides an accurate multi-class classification model for brain tumor using the convolution neural network (CNN) as a backbone. Our novel model is based on concatenating the extracted features from the proposed three branches of CNN, where each branch is fed by the output of different transform domains of the original magnetic resonance image (MRI). These transformations include Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and the time-domain of the original image. Then, the CNN is employed followed by a concatenation layer, flatten laver, and dense layer, before using the SoftMax layer. The proposed model was applied to the Figshare dataset of brain tumor which consists of three classes pituitary, glioma, and meningioma. The results proved the advantage of the proposed system which achieved a high mean performance over 5-fold cross-validation with 98.89% accuracy, 98.78% F1-score, 98.74% precision, 98.82% recall, and 99.44% specificity. The comparative study with well-known models, as well as the pre-trained CNN models, established the potential of the proposed model. This novel approach has the potential to significantly improve brain tumor classification accuracy. It enables a more comprehensive and objective analysis of brain tumors, leading to improved treatment decisions and better patient care

A Comparative Study Between the Taxation of Companies in the United Kingdom and Egypt With Particular Reference to United Kingdom Based Multinational Companies Operating in Egypt

Taxation plays a major role in economic activity, as a prime source of revenue and as a tool of economic mangement for all governments in either developed or less developed countries

Introduction of Purple and Deep Purple F1 Carrot Hybrids to Egypt Showed High Antioxidant Activity and High Content of Total Flavonoids and Phenols

For the improvement of carrot cultivation in Egypt and because of the deterioration of the local Egyptian purple carrots, two novel colored (Purple and Deep Purple) F1 carrot hybrids were introduced for the first time from Netherland to be evaluated and compared to the broadly cultivated yellow Japanese F1 hybrid (Kuruda) under the Middle Egypt sandy soil growing conditions. The horticultural evaluation showed that the two purple hybrids have elongated thick roots and good vegetative growth and gave a very high yield of roots in two successive winter seasons of 2013/2014 and 2014/2015. The Deep Purple hybrid exceeded the other two hybrids in almost all studied chemical and horticultural characteristics. It showed about three folds of leaves fresh weight/plant, two folds of both root fresh weight/plant and yield/m2 when compared with Purple and Kuruda hybrids. The chemical analyses declared that the Purple and Deep Purple hybrids have higher contents of all estimated components and the Deep Purple hybrid had the highest values of total flavonoids (about two folds), total phenols (about 5-6 folds), antioxidant activity percentage (7-8 times), and total soluble solids percentage (1.5-2 times) than that of the yellow F1 hybrid “Kuruda”. These newly introduced two Purple and Deep Purple F1 hybrids may be very promising in production and processing purposes of purple carrots and good materials in carrot breeding programs in Egypt

An Improve the Onboarding Process in Trade Finance Applications Using Blockchain Technology

Today, challenges in Know Your Customer (KYC) and Anti-Money Laundering (AML) processes include inefficiencies, data silos, and the risk of fraudulent activities. Integrating blockchain technology offers a transformative solution to these issues. Blockchain's decentralized and tamper-resistant nature ensures a single, verifiable source of truth for customer information, reducing data discrepancies across institutions. Smart contracts can automate AML compliance checks, ensuring real-time monitoring and rapid response to suspicious activities. The immutability of blockchain records enhances auditability, facilitating regulatory compliance. Furthermore, the secure and transparent nature of blockchain instills trust among stakeholders, fostering collaboration in combating financial crimes. By leveraging blockchain in KYC and AML processes, the financial industry can achieve enhanced efficiency, reduced fraud, and strengthened regulatory adherence

New Flame Retardant and Antimicrobial Paints Based on Epoxy Paint Incorporated by Hexachlorocylodiphosphazane Derivatives for Protective Coating

Flame retardants can be incorporated into polymeric material either as additives or as reactive materials. Additive type flame retardants are widely used by means of blending them with a specific polymeric material. In this particular research, hexachlorocylodiphosphazane derivatives type (I-II) were synthesized for use as flame retardant and antimicrobial additives with epoxy varnish. These additives are physically incorporated into the epoxy varnish formula. Experimental coatings were manufactured on a laboratory scale and applied by brush on wood and steel panels. The fire retardant ability of each coating type was characterized using the limiting oxygen index (LOI) test. The mechanical properties of these flame retardants were also examined to evaluate the drawbacks of the additives. Results of the LOI indicated that coating with these compounds containing chlorine, nitrogen and phosphorus exhibit a very good retardant effect, when blended with epoxy varnish comparing with the blanket sample which not contain on the hexachlorocylodiphosphazane derivative as a additives. The hexachlorocylodiphosphazane derivative also exhibit mild results as preservative against microbiological attack. The mechanical properties of the painted dry films were investigated acordinting to ASTM