Mobile robots use is rising every day. Path planning algorithms are needed to make a traveler of robots with the least cost and without collisions. Many techniques have been developed in path planning for mobile robot worldwide, however, the most commonly used techniques are presented here for further study. This essay aims to review various path planning strategies for mobile robots using different optimization methods taken recent publisher’s paper in last five year.
Low-Density Parity Check (LDPC) codes are viewed as one of the best error correction coding (ECC) methods in terms of correction efficiency. They have been used in several modern data transmission standards, where the codecs are often built inside specialized integrated circuits (ICs). On the other hand, Complementary Metal-Oxide-Semiconductor (CMOS) circuits have evolved as a critical design characteristic that the designer must consider such as power, which has been overlooked by many researchers. For that reason, in this paper, a research work that reduces LDPC encoder power consumption is presented using a well-known power reduction method named Dynamic Voltage and Frequency Scaling (DVFS), which is one of the most powerful power reduction strategies in CMOS circuits. The proposed system includes a fuzzy logic controller with the DVFS technique to control and select the optimum level of voltage that enters the encoder to reduce its total power consumption. This combination of these two techniques showed significant power reduction and control while causing no impact on the LDPC efficiency, flexibility, and performance. Comparisons with other studies covering power reduction in LDPC codes have shown that the purposed system has the best performance over similar systems in the literature.
Recently, online-medicine got increased global interest, particularly during COVID19 pandemic. Data protection is important in the medical field since when promoting telemedicine applications, it is necessary to protect the patient data and personal information. A secured process is needed to transmit medical images over the Internet. In this paper hash algorithm is employed to protect the data by using powerful features from the coupled frequency domains of the Slantlet Transformation (SLT) and the Discrete Cosine Transform (DCT). The Region of Interest (ROI) is localized from an MRI image then extraction of a feature set is performed for calculating the hash code. Then, hash code is enciphered to maintain security by employing a secure Chaotic Shift Keying (CSK). The suggested method of security is ensured by the strength of the CSK and the encryption key secrecy. A detailed analysis was conducted using 1000 uncompressed images that were chosen randomly from a publicly available AANLIB database. The proposed methodology can be useful for JPEG compression. Also, this method could resist many attacks of image processing likes filtering, noise addition, and some geometric transforms.
Autonomous mobile robots developed using metaheuristic algorithms are increasingly becoming a hot topic in control and computer sciences. Specifically, finding the shortest root to the goal and avoiding hurdles are current subjects of autonomous mobile robots. The main drawbacks of classic methods are the incapacity to move the robot in a dynamic and unknown environment, deadlock in a local minimum and complicated environments, and incapacity to foretell the speed vector of obstacles and non-optimality of the route. This article exhibits a recent path planning approach that utilizes the African Vultures Optimization (AVOA) for navigation of the mobile robot in static and dynamic unknown environments with a dynamic target. The proposed online optimization approach is used in three different environments including an environment with unknown static obstacles, an environment with unknown dynamic obstacles, and an environment with a dynamic target. The proposed approach can solve a local minima problem in the environment with static obstacles. The online optimization method is performed using two phases which are the sensors’ reading phase and the path calculation phase and the results are given based on computer simulation in different unknown environments. A comparative study was conducted between the suggested algorithm and two other algorithms and the results showed that the AVOA algorithm was better in avoiding obstacles successfully including the local minima situation. Finally, the average enhancement rates in the path length compared with the Adaptive Particle Swarm Optimization (APSO) and the Hybrid Fuzzy-Wind Driven Optimization (WDO) are 2.21% and 1.02207%, respectively.
This paper discusses power consumption in the full adder circuit using some fabrication technologies. Though many studies related to power consumption in the full adder circuit were performed, however, few investigations about the effect of the number of bits on the power consumption are addressed. In this paper, the effect of changing the number of bits on the power consumption and time delay of the full adder circuit will be observed and the effect of changing the technology size is going to be calculated. The results will show that there is a direct relationship between the number of bits and power.
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