Wireless Sensor Networks (WSNs) are promoting the spread of the Internet for devices in all areas of
life, which makes it is a promising technology in the future. In the coming days, as attack technologies become
more improved, security will have an important role in WSN. Currently, quantum computers pose a significant
risk to current encryption technologies that work in tandem with intrusion detection systems because it is
difficult to implement quantum properties on sensors due to the resource limitations. In this paper, quantum
computing is used to develop a future-proof, robust, lightweight and resource-conscious approach to sensor
networks. Great emphasis is placed on the concepts of using the BB8

    Today the Genetic Algorithm (GA) tops all the standard algorithms in solving complex nonlinear equations based on the laws of nature. However, permute convergence is considered one of the most significant drawbacks of GA, which is known as increasing the number of iterations needed to achieve a global optimum. To address this shortcoming, this paper proposes a new GA based on chaotic systems. In GA processes, we use the logistic map and the Linear Feedback Shift Register (LFSR) to generate chaotic values to use instead of each step requiring random values. The Chaos Genetic Algorithm (CGA) avoids local convergence more frequently than the traditional GA due to its diversity. The concept is using chaotic sequences with LFSR to gene

 This study seeks to highlights on the behavioral approach in organization theory as modern and effective entrance in constructing this theory and reflection extent on the behavior of both the product and the information user (accountant and financial information).

 The study also focus on behavioral approach role in consolidating accounting concepts through making harmony between them so that the accountant can influence the user behavior with the concepts and principles of accounting in an effort to provide quality characteristic of accounting information produced by him in consistent with his behavior and information user and its impact on the decision making process by the latter.

The fall angle of sun rays on the surface of a photovoltaic PV panel and its temperature is negatively affecting the panel electrical energy produced and efficiency. The fall angle problem was commonly solved by using a dual-axis solar tracker that continually maintains the panel orthogonally positioning to the sun rays all day long. This leads to maximum absorption for solar radiation necessary to produce maximum amount of energy and maintain high level of electrical efficiency. To solve the PV panel temperature problem, a Water-Flow Double Glazing WFDG technique has been introduced as a new cooling tool to reduce the panel temperature. In this paper, an integration design of the water glazing system with a dual-axis tracker has been ac

      The modern systems that have been based upon the hash function are more suitable compared to the conventional systems; however, the complicated algorithms for the generation of the invertible functions have a high level of time consumption. With the use of the GAs, the key strength is enhanced, which results in ultimately making the entire algorithm sufficient. Initially, the process of the key generation is performed by using the results of n-queen problem that is solved by the genetic algorithm, with the use of a random number generator and through the application of the GA operations. Ultimately, the encryption of the data is performed with the use of the Modified Reverse Encryption Algorithm (MREA). It was noticed that the

In the last few years, the Internet of Things (IoT) is gaining remarkable attention in both academic and industrial worlds. The main goal of the IoT is laying on describing everyday objects with different capabilities in an interconnected fashion to the Internet to share resources and to carry out the assigned tasks. Most of the IoT objects are heterogeneous in terms of the amount of energy, processing ability, memory storage, etc. However, one of the most important challenges facing the IoT networks is the energy-efficient task allocation. An efficient task allocation protocol in the IoT network should ensure the fair and efficient distribution of resources for all objects to collaborate dynamically with limited energy. The canonical de

Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

planning is among the most significant in the field of robotics research.  As it is linked to finding a safe and efficient route in a cluttered environment for wheeled mobile robots and is considered a significant prerequisite for any such mobile robot project to be a success. This paper proposes the optimal path planning of the wheeled mobile robot with collision avoidance by using an algorithm called grey wolf optimization (GWO) as a method for finding the shortest and safe. The research goals in this study for identify the best path while taking into account the effect of the number of obstacles and design parameters on performance for the algorithm to find the best path. The simulations are run in the MATLAB environment to test the