M. A. El-Dosuky

A. M. El-Edkawy, M. A. El-Dosuky, Taher Hamza

Biological cells can transmit, process and receive chemically encoded data in the same way as network devices transmit, process, and receive digitally encoded data. Communication protocols have led to the rapid development of computer networks. Therefore, we need to develop communication protocols for biological cell networks, which will lead to significant development, especially in medical applications where surgery or delivery of drugs can be performed using nanoscale devices. Blockchain is a peer-to-peer network that contains a series of clusters to make a valid and secure transaction. Blockhain technology is used in many areas such as e-commerce, public services, security, finance, Internet stuff, etc. Although blockchain has a major impact on Internet technology, it suffers from time problems and scalability. DNA computing is the execution of computations using natural molecules, especially DNA. DNA gaps above silicon because of massive parallelism, size and storage density. In this paper, biological cells and DNA are used to create the necessary protocols for the networks to be used in the performance of the cell-based communication system. The proposed hybrid solution involves DNA as well as calculated on an enzymatic basis, where each contributes to the function of a given protocol. Also a correspondence between blockchain and DNA is proposed that can be utilized to create DNA based blockchain.

A. M. El-Edkawy, M. A. El-Dosuky

Unmanned Aerial Vehicle (UAV) quadrotor is a UAV with four rotors. The quadrotor control is a difficult task because the four-wheel system is inefficient. The purpose of this paper is to provide specifications and implement a separate quad system that integrates data from the camera and IMU (Inertial Measurement Unit) to allow high -resolution optical transmission. In this paper, a separate quad system was proposed. The system specification is specified. The system application introduced the SolidWorks design of the system, the mathematical modeling of the pickup and delivery (PDP) problem. The simulation results using MATLB for model implementation and the simultaneous localization and mapp ing (SLAM) were presented using the Extended Kalman (EKF-SLAM) filter algorithm used to make the system independent. Experimental results were introduced to use the candy edge detection algorithm.

A. M. Raid, W. M. Khedr, M. A. El-dosuky et al.

Due to the increasing requirements for transmission of images in computer, mobile environments, the research in the field of image compression has increased significantly. Image compression plays a crucial role in digital image processing, it is also very important for efficient transmission and storage of images. When we compute the number of bits per image resulting from typical sampling rates and quantization methods, we find that Image compression is needed. Therefore development of efficient techniques for image compression has become necessary .This paper is a survey for lossy image compression using Discrete Cosine Transform, it covers JPEG compression algorithm which is used for full-colour still image applications and describes all the components of it.

M. A. El-Dosuky

Large-scale problems are nonlinear problems that need metaheuristics, or global optimization algorithms. This paper reviews nature-inspired metaheuristics, then it introduces a framework named Competitive Ant Colony Optimization inspired by the chemical communications among insects. Then a case study is presented to investigate the proposed framework for large-scale global optimization.

M. A. El-Dosuky, M. Z. Rashad, T. T. Hamza et al.

Recommender systems are needed to find food items of ones interest. We review recommender systems and recommendation methods. We propose a food personalization framework based on adaptive hypermedia. We extend Hermes framework with food recommendation functionality. We combine TF-IDF term extraction method with cosine similarity measure. Healthy heuristics and standard food database are incorporated into the knowledgebase. Based on the performed evaluation, we conclude that semantic recommender systems in general outperform traditional recommenders systems with respect to accuracy, precision, and recall, and that the proposed recommender has a better F-measure than existing semantic recommenders.

M. A. El-Dosuky

Automatic analysis of the enormous sets of images is a critical task in life sciences. This faces many challenges such as: algorithms are highly parameterized, significant human input is intertwined, and lacking a standard meta-visualization approach. This paper proposes an alternative iterative approach for optimizing input parameters, saving time by minimizing the user involvement, and allowing for understanding the workflow of algorithms and discovering new ones. The main focus is on developing an interactive visualization technique that enables users to analyze the relationships between sampled input parameters and corresponding output. This technique is implemented as a prototype called Veni Vidi Vici, or "I came, I saw, I conquered." This strategy is inspired by the mathematical formulas of numbering computable functions and is developed atop ImageJ, a scientific image processing program. A case study is presented to investigate the proposed framework. Finally, the paper explores some potential future issues in the application of the proposed approach in parameter space analysis in visualization.

M. A. El-Dosuky, M. Z. Rashad, T. T. Hamza et al.

For a mobile robot to be truly autonomous, it must solve the simultaneous localization and mapping (SLAM) problem. We develop a new metaheuristic algorithm called Simulated Tom Thumb (STT), based on the detailed adventure of the clever Tom Thumb and advances in researches relating to path planning based on potential functions. Investigations show that it is very promising and could be seen as an optimization of the powerful solution of SLAM with data association and learning capabilities. STT outperform JCBB. The performance is 100 % match.

M. A. El-Dosuky, M. Z. Rashad, T. T. Hamza et al.

Data association methods are used by autonomous robots to find matches between the current landmarks and the new set of observed features. We seek a framework for opinion mining to benefit from advancements in autonomous robot navigation in both research and development