Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni

This paper proposes a new encryption method. It combines two cipher algorithms, i.e., DES and AES, to generate hybrid keys. This combination strengthens the proposed W-method by generating high randomized keys. Two points can represent the reliability of any encryption technique. Firstly, is the key generation; therefore, our approach merges 64 bits of DES with 64 bits of AES to produce 128 bits as a root key for all remaining keys that are 15. This complexity increases the level of the ciphering process. Moreover, it shifts the operation one bit only to the right. Secondly is the nature of the encryption process. It includes two keys and mixes one round of DES with one round of AES to reduce the performance time. The W-method deals with

High-power density supercapacitors and high-energy–density batteries have gotten a lot of interest since they are critical for the power supply of future electric cars, portable electronic gadgets, unmanned aircraft, and so on. The electrode materials used in supercapacitors and batteries have a significant impact on the practical energy and power density. Metal–organic frameworks (MOFs) have the outstanding electrochemical ability because of their ultrahigh porous structure, ease of functionalization, and great specific surface area. These features make it an intriguing electrode material with good electrochemical efficiency for high-storage batteries. Thus, this review summarizes current developments in MOFs-based materials as an elec

In the field of implantology, peri-implantitis is still a common complication of implant failure. Similar to periodontal disease, this kind of pathological condition is characterized by inflammation of the tissues surrounding dental implants or fillings. The sources of infection have been shown to be chronic periodontitis and poor maintenance of the communion. A thorough examination of the intricate components of peri-implantitis was sought in this review in order to identify common characteristics of the disease with regard to bacteria, biofilm formation, host immunological responses, diagnostic tools, and therapeutic treatments. The aim of this study was to provide a detailed overview of the different bacterial species associated

Texture synthesis using genetic algorithms is one way; proposed in the previous research, to synthesis texture in a fast and easy way. In genetic texture synthesis algorithms ,the chromosome consist of random blocks selected manually by the user .However ,this method of selection is highly dependent on the experience of user .Hence, wrong selection of blocks will greatly affect the synthesized texture result. In this paper a new method is suggested for selecting the blocks automatically without the participation of user .The results show that this method of selection eliminates some blending caused from the previous manual method of selection.

Signature verification involves vague situations in which a signature could resemble many reference samples or might differ because of handwriting variances. By presenting the features and similarity score of signatures from the matching algorithm as fuzzy sets and capturing the degrees of membership, non-membership, and indeterminacy, a neutrosophic engine can significantly contribute to signature verification by addressing the inherent uncertainties and ambiguities present in signatures. But type-1 neutrosophic logic gives these membership functions fixed values, which could not adequately capture the various degrees of uncertainty in the characteristics of signatures. Type-1 neutrosophic representation is also unable to adjust to various