Fawad Salam Khan^1,4, Mohd Norzali Haji Mohd^1,*, Saiful Azrin B. M. Zulkifli², Ghulam E Mustafa Abro², Suhail Kazi³, Dur Muhammad Soomro¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5741-5759, 2022, DOI:10.32604/cmc.2022.024927 - 21 April 2022

Abstract The evident change in the design of the autopilot system produced massive help for the aviation industry and it required frequent upgrades. Reinforcement learning delivers appropriate outcomes when considering a continuous environment where the controlling Unmanned Aerial Vehicle (UAV) required maximum accuracy. In this paper, we designed a hybrid framework, which is based on Reinforcement Learning and Deep Learning where the traditional electronic flight controller is replaced by using 3D hand gestures. The algorithm is designed to take the input from 3D hand gestures and integrate with the Deep Deterministic Policy Gradient (DDPG) to receive… More >

Yujiang Li^1,2, Chun Ding^1,2, Zhili Zhou^1,2,*

Journal of New Media, Vol.4, No.1, pp. 51-58, 2022, DOI:10.32604/jnm.2022.028775 - 21 April 2022

Abstract With the development of new media technology, vehicle matching plays a further significant role in video surveillance systems. Recent methods explored the vehicle matching based on the feature extraction. Meanwhile, similarity metric learning also has achieved enormous progress in vehicle matching. But most of these methods are less effective in some realistic scenarios where vehicles usually be captured in different times. To address this cross-domain problem, we propose a cross-domain similarity metric learning method that utilizes the GAN to generate vehicle images with another domain and propose the two-channel Siamese network to learn a similarity More >

Wenhao Lu¹, Shuai Guo^1,2, Tao Song^1,*, Yuwen Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1197-1227, 2022, DOI:10.32604/cmes.2022.019770 - 19 April 2022

Abstract Multiple Automatic Guided Vehicle (multi-AGVs) management systems provide an effective solution to ensuring stable operations of multi-AGVs in the same scenario, such as flexible manufacturing systems, warehouses, container terminals, etc. This type of systems need to balance the relationship among the resources of the system and solve the problems existing in the operation to make the system in line with the requirement of the administrator. The multi-AGVs management problem is a multi-objective, multi-constraint combinatorial optimization problem, which depends on the types of application scenarios. This article classifies and compares the research papers on multi-AGVs management… More >

M. L. Ramamoorthy¹, S. Selvaperumal^2,*, G. Prabhakar³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 485-497, 2022, DOI:10.32604/iasc.2022.025824 - 15 April 2022

Abstract The scope of this research is to design and fuse the sensors used in the self-balancing vehicle through Adaptive Neuro-Fuzzy Inference systems (ANFIS) algorithm to optimize the output. The self-balancing vehicle is a wheeled inverted pendulum, which is extremely complex, nonlinear and unstable. Homogeneous and Heterogeneous sensors are involved in this sensor fusion research to identify the best feasible value among them. The data fusion algorithm present inside the controller of the self-balancing vehicle makes the inputs of the homogeneous sensors and heterogeneous sensors separately for ameliorate surrounding perception. Simulation is performed by modeling the… More >

Sandeep Kumar¹, Arpit Jain^2,*, Shilpa Rani³, Hammam Alshazly⁴, Sahar Ahmed Idris⁵, Sami Bourouis⁶

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 119-131, 2022, DOI:10.32604/iasc.2022.024812 - 15 April 2022

Abstract The detection of the objects in the ariel image has a significant impact on the field of parking space management, traffic management activities and surveillance systems. Traditional vehicle detection algorithms have some limitations as these algorithms are not working with the complex background and with the small size of object in bigger scenes. It is observed that researchers are facing numerous problems in vehicle detection and classification, i.e., complicated background, the vehicle’s modest size, other objects with similar visual appearances are not correctly addressed. A robust algorithm for vehicle detection and classification has been proposed… More >

Vishnu Kumar Kaliappan¹, Tuan Anh Nguyen¹, Dugki Min^2,*, Jae-Woo Lee¹, U. Sakthi³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 575-591, 2022, DOI:10.32604/iasc.2022.024577 - 15 April 2022

Abstract In recent years, the applications of rotorcraft-based unmanned aerial vehicles (RUAV) have increased rapidly. In particular, the integration of bio-inspired techniques to enhance intelligence in coordinating multiple Rotorcraft-based Unmanned Aerial Vehicles (RUAVs) has been a focus of recent research and development. Due to the limitation in intelligence, these RUAVs are restricted in flying low altitude with high maneuverability. To make it possible, the RUAVs must have the ability to avoid both static and dynamic obstacles while operating at low altitudes. Therefore, developing a state-of-the-art intelligent control algorithm is necessary to avoid low altitude obstacles and… More >

Jenson Jose^1,*, Jose P. Therattil²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 339-355, 2022, DOI:10.32604/iasc.2022.023863 - 15 April 2022

Abstract The Wireless Power Transmission (WPT) technology is a significant source of operation in the field of power transmission with tremendous potential in a wide range of applications. This paper proposes a novel strategy for L2CL-LCL topology, which comprises two capacitors and one inductor in the essential and one capacitor and one inductor in the auxiliary. Using MATLAB simulation, this paper compares the traditional DSLCL system and the proposed L2CL-LCL. The various parameters of this system are simulated. In the current system, input and output power are set to 200.1 and 182.4 W. The common framework’s… More >

A. Backia Abinaya^1,*, G. Karthikeyan²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 325-338, 2022, DOI:10.32604/iasc.2022.020896 - 15 April 2022

Abstract The Internet of Vehicles (IoV) is utilized for collecting enormous real time information driven traffics and alert drivers depending on situations. In recent times, all smart vehicles are developed with IoT devices. These devices communicate with a radio access unit (RAU) at road side. Moreover, a 5G system is equipped with a base station and connection interfaces that use optic fiber for their effective communication. For a fast mode of communication, the IoV must offload its data to the nearest edge nodes. The main problem with the IoV is that it generates enormous data which… More >

Wen Sun, Hao Liu, Ming Han, Ke Sun, Shuzhan Bai^*, Guoxiang Li^*

FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.4, pp. 867-882, 2022, DOI:10.32604/fdmp.2022.018923 - 06 April 2022

Abstract Fuel cell hybrid electric vehicles are currently being considered as ideal means to solve the energy crisis and global warming in today’s society. In this context, this paper proposes a method to solve the problem related to the dependence of the so-called optimal equivalent factor (determined in the framework of the equivalent consumption minimum strategy-ECMS) on the working conditions. The simulation results show that under typical conditions (some representative cities being considered), the proposed strategy can maintain the power balance; for different initial battery’s states of charge (SOC), after the SOC stabilizes, the fuel consumption More >

Wei Chen¹, Mi Liu^1,*, Xuhong Zhou², Jiandong Pan³, Haozhi Tan⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3159-3174, 2022, DOI:10.32604/cmc.2022.026664 - 29 March 2022

Abstract In construction, it is important to check whether workers wear safety helmets in real time. We proposed using an unmanned aerial vehicle (UAV) to monitor construction workers in real time. As the small target of aerial photography poses challenges to safety-helmet-wearing detection, we proposed an improved YOLOv4 model to detect the helmet-wearing condition in aerial photography: (1) By increasing the dimension of the effective feature layer of the backbone network, the model's receptive field is reduced, and the utilization rate of fine-grained features is improved. (2) By introducing the cross stage partial (CSP) structure into… More >