Cryptography is the technology of protecting information and communication by means of encoding the sending information. Existing methods often operate within predetermined mathematical structures which can be subject to pattern recognition and which are lack biological randomness. To address these challenges, this paper introduced a new bio-inspired cryptography approach to protect text messages using the coding mechanisms of DNA and RNA materials. The encryption system consists of six steps: encoding the plaintext message into DNA sequences, transcribing DNA into RNA, applying the complementary base pairing, scrambling RNA segments, optional reverse transcription, and encoding the resulting DNA-RNA characters into ciphertext. Rand

In the current digitalized world, cloud computing becomes a feasible solution for the virtualization of cloud computing resources.  Though cloud computing has many advantages to outsourcing an organization’s information, but the strong security is the main aspect of cloud computing. Identity authentication theft becomes a vital part of the protection of cloud computing data. In this process, the intruders violate the security protocols and perform attacks on the organizations or user’s data. The situation of cloud data disclosure leads to the cloud user feeling insecure while using the cloud platform. The different traditional cryptographic techniques are not able to stop such kinds of attacks. BB84 protocol is the first quantum cry

The study included a statement toxicity of some heavy metals individually and collectively and the existence of plant nutrients in the center Agirenk bluish green moss growth and Askhaddm biomass as an indicator of the study, in addition to portability moss on the accumulation of the metal

The main focus of research is on how to achieve the internal and external dimensions of corporate social responsibility through human resources management strategies, which is a major of research aimed. The main problem of this research was confirmed, which confirms that there is an unclear role for social responsibility, lack of human resources management strategies, and ambiguity of roles in the municipality under study. The diagnose of the problem and determining the gap between the internal and external dimensions of social responsibility and human resources management was identified, which attacked the researcher's attention to navigate in this subject, look for the reasons for the gaps and try to reduce them. The case study

Amis: NAFLD is considered to be the most common cause of liver conditions worldwide. Also, it is a primary reason that leads to coronary artery diseases, limiting blood flow to the heart. Therefore, This study aimed to evaluate the serum level of Nesfatin-1 and its ability to indicate the prognosis of CAD in patients with NAFLD. Material & Methods: one-hundred eighty Individuals were enrolled in the study, including In both genders, blood was collected from each Individual and sent to the laboratory for biochemical tests. Findings: Data from the current study showed a significant increase in Nesfatin-1 in the CAD group and a significant decrease in Nesfatin-1 in the NAFLD group compared to the control group. In addition, there w

The aim of human lower limb rehabilitation robot is to regain the ability of motion and to strengthen the weak muscles. This paper proposes the design of a force-position control for a four Degree Of Freedom (4-DOF) lower limb wearable rehabilitation robot. This robot consists of a hip, knee and ankle joints to enable the patient for motion and turn in both directions. The joints are actuated by Pneumatic Muscles Actuators (PMAs). The PMAs have very great potential in medical applications because the similarity to biological muscles. Force-Position control incorporating a Takagi-Sugeno-Kang- three- Proportional-Derivative like Fuzzy Logic (TSK-3-PD) Controllers for position control and three-Proportional (3-P) controllers for force contr

This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm