A.C. Budiman^a,*, S. M. Hasheminejad^b, Sudirja^a, A. Mitayani^c, S. H. Winoto^d

Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-6, 2022, DOI:10.5098/hmt.19.9

Abstract Streamwise development of counter-rotating vortices induced by three different types of chevron Vortex Generators (VGs) placed upstream an Electric Vehicles (EV) dummy battery module is experimentally visualized using a smoke-wire method. From the single chevron reference case, the mushroom-like vortices do not collapse until passing the module. When more chevrons are used in line, the vortices become more prominent. It can also be observed that the vortex sizes and shapes are significantly influenced by the spanwise base length of the chevron. The induced vortices from all three VGs suggest a potential heat transfer augmentation for the EV battery module application. More >

Weiguang Zheng^1,2,3, Junzhu Zhang^1,2, Shanchao Wang^2,*, Gaoshan Feng², Xiaohong Xu², Qiuxiang Ma²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 489-508, 2023, DOI:10.32604/cmes.2023.025169

Abstract The extended Kalman filter (EKF) algorithm and acceleration sensor measurements were used to identify vehicle mass and road gradient in the work. Four different states of fixed mass, variable mass, fixed slope and variable slope were set to simulate real-time working conditions, respectively. A comprehensive electric commercial vehicle shifting strategy was formulated according to the identification results. The co-simulation results showed that, compared with the recursive least square (RLS) algorithm, the proposed algorithm could identify the real-time vehicle mass and road gradient quickly and accurately. The comprehensive shifting strategy formulated had the following advantages, e.g., avoiding frequent shifting of vehicles… More > Graphic Abstract

Khalil Chebil^1,2, Skander Htiouech³, Mahdi Khemakhem^1,2,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 233-263, 2023, DOI:10.32604/cmes.2023.026476

Abstract Crowd management and analysis (CMA) systems have gained a lot of interest in the vulgarization of unmanned aerial vehicles (UAVs) use. Crowd tracking using UAVs is among the most important services provided by a CMA. In this paper, we studied the periodic crowd-tracking (PCT) problem. It consists in using UAVs to follow-up crowds, during the life-cycle of an open crowded area (OCA). Two criteria were considered for this purpose. The first is related to the CMA initial investment, while the second is to guarantee the quality of service (QoS). The existing works focus on very specified assumptions that are highly… More >

D. Ribeiro^1,*, B. Costa², P. Montenegro², R. Calçada²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.24, No.1, pp. 1-1, 2022, DOI:10.32604/icces.2022.08682

Abstract The present article focuses on the evaluation of the dynamic behaviour of a centenary steel arch bridge, located in Portugal, under light railway traffic loads. The work aims to assess the dynamic behaviour of the bridge subjected to an alternative type of railway vehicle, more specifically, a typical underground vehicle that is currently in service in the Lisbon Metro. The dynamic response of the system has been evaluated using two distinct methodologies, namely a moving loads model and a vehicle-bridge interaction model. To achieve this goal, finite element (FE) models from both the bridge and the vehicle have been developed… More >

Fawad Nasim^1,2,*, Sohail Masood^1,2, Arfan Jaffar^1,2, Usman Ahmad¹, Muhammad Rashid³

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3175-3190, 2023, DOI:10.32604/csse.2023.034550

Abstract An intelligent sound-based early fault detection system has been proposed for vehicles using machine learning. The system is designed to detect faults in vehicles at an early stage by analyzing the sound emitted by the car. Early detection and correction of defects can improve the efficiency and life of the engine and other mechanical parts. The system uses a microphone to capture the sound emitted by the vehicle and a machine-learning algorithm to analyze the sound and detect faults. A possible fault is determined in the vehicle based on this processed sound. Binary classification is done at the first stage… More >

Siling Feng¹, Yinjie Chen¹, Mengxing Huang^1,2,*, Feng Shu¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4341-4355, 2023, DOI:10.32604/cmc.2023.037154

Abstract Due to their adaptability, Unmanned Aerial Vehicles (UAVs) play an essential role in the Internet of Things (IoT). Using wireless power transfer (WPT) techniques, an UAV can be supplied with energy while in flight, thereby extending the lifetime of this energy-constrained device. This paper investigates the optimization of resource allocation in light of the fact that power transfer and data transmission cannot be performed simultaneously. In this paper, we propose an optimization strategy for the resource allocation of UAVs in sensor communication networks. It is a practical solution to the problem of marine sensor networks that are located far from… More >

Abida Sharif¹, Muhammad Imran Sharif¹, Muhammad Attique Khan², Nisar Ali², Abdullah Alqahtani³, Majed Alhaisoni⁴, Ye Jin Kim⁵, Byoungchol Chang^6,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2383-2396, 2023, DOI:10.32604/cmc.2023.033894

Abstract The content-centric networking (CCN) architecture allows access to the content through name, instead of the physical location where the content is stored, which makes it a more robust and flexible content-based architecture. Nevertheless, in CCN, the broadcast nature of vehicles on the Internet of Vehicles (IoV) results in latency and network congestion. The IoV-based content distribution is an emerging concept in which all the vehicles are connected via the internet. Due to the high mobility of vehicles, however, IoV applications have different network requirements that differ from those of many other networks, posing new challenges. Considering this, a novel strategy… More >

Zihao Sun^1,*, Xiao Hu², Yining Qi², Yongfeng Huang², Songbin Li³

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1657-1669, 2023, DOI:10.32604/cmc.2023.036558

Abstract The marine environment is becoming increasingly complex due to the various marine vehicles, and the diversity of maritime objects poses a challenge to marine environmental governance. Maritime object detection technology plays an important role in this segment. In the field of computer vision, there is no sufficiently comprehensive public dataset for maritime objects in the contrast to the automotive application domain. The existing maritime datasets either have no bounding boxes (which are made for object classification) or cover limited varieties of maritime objects. To fulfil the vacancy, this paper proposed the Multi-Category Large-Scale Dataset for Maritime Object Detection (MCMOD) which… More >

Waleed Aldosari^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1253-1269, 2023, DOI:10.32604/cmc.2023.036111

Abstract This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks on Wireless Sensor Networks (WSNs). Jamming is a type of Denial of Service (DoS) attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly. To defend and prevent such attacks, the first step is to detect them. The current detection approaches use centralized techniques to detect jamming, where each node collects information and forwards it to the base station. As a result, overhead and communication costs… More >

Jin Shang^1,*, Hailong Su^2,*, Kai Hu³, Xin Guo³, Defa Sun³

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 799-814, 2023, DOI:10.32604/cmc.2023.035729

Abstract Urban traffic volume detection is an essential part of traffic planning in terms of urban planning in China. To improve the statistics efficiency of road traffic volume, this thesis proposes a method for predicting motor vehicle traffic volume on urban roads in small and medium-sized cities during the traffic peak hour by using mobile signal technology. The method is verified through simulation experiments, and the limitations and the improvement methods are discussed. This research can be divided into three parts: Firstly, the traffic patterns of small and medium-sized cities are obtained through a questionnaire survey. A total of 19745 residents… More >