Zhiheng He¹, Hui Guo², Houguang Liu^1,*, Yu Zhao^1,3, Zipeng Zhang¹, Shanguo Yang¹

Sound & Vibration, Vol.58, pp. 47-58, 2024, DOI:10.32604/sv.2024.045470

Abstract When designing and optimizing the hull of vehicles, their sound quality needs to be considered, which greatly depends on the psychoacoustic parameters. However, the traditional psychoacoustic calculation method does not consider the influence of the real human ear anatomic structure, even the loudness which is most related to the auditory periphery. In order to introduce the real physiological structure of the human ear into the evaluation of vehicle sound quality, this paper first carried out the vehicle internal noise test to obtain the experimental samples. Then, the physiological loudness was predicted based on an established More >

Cheng Peng¹, Siwei Cheng², Min Sun¹, Chao Ren¹, Jun Song¹, Haibo Huang^2,*

Sound & Vibration, Vol.58, pp. 25-46, 2024, DOI:10.32604/sv.2024.046940

Abstract The Noise, Vibration, and Harshness (NVH) experience during driving is significantly influenced by the sound insulation performance of the car floor acoustic package. As such, accurate and efficient predictions of its sound insulation performance are crucial for optimizing related noise reduction designs. However, the complex acoustic transmission mechanisms and difficulties in characterizing the sound absorption and insulation properties of the floor acoustic package pose significant challenges to traditional Computer-Aided Engineering (CAE) methods, leading to low modeling efficiency and prediction accuracy. To address these limitations, a hierarchical multi-objective decomposition system for predicting the sound insulation performance More >

Jiarui Deng^1,2, Wuqiang Shen^1,3, Yihua Feng⁴, Guosheng Lu⁵, Guiquan Shen^1,3, Lei Cui^1,3, Shanxiang Lyu^1,2,*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1345-1361, 2024, DOI:10.32604/cmc.2023.047079

Abstract The blockchain-empowered Internet of Vehicles (IoV) enables various services and achieves data security and privacy, significantly advancing modern vehicle systems. However, the increased frequency of data transmission and complex network connections among nodes also make them more susceptible to adversarial attacks. As a result, an efficient intrusion detection system (IDS) becomes crucial for securing the IoV environment. Existing IDSs based on convolutional neural networks (CNN) often suffer from high training time and storage requirements. In this paper, we propose a lightweight IDS solution to protect IoV against both intra-vehicle and external threats. Our approach achieves More >

Yaoyao Du, Xiangkui Jiang^*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 303-327, 2024, DOI:10.32604/cmc.2023.046068

Abstract To address the challenges of high complexity, poor real-time performance, and low detection rates for small target vehicles in existing vehicle object detection algorithms, this paper proposes a real-time lightweight architecture based on You Only Look Once (YOLO) v5m. Firstly, a lightweight upsampling operator called Content-Aware Reassembly of Features (CARAFE) is introduced in the feature fusion layer of the network to maximize the extraction of deep-level features for small target vehicles, reducing the missed detection rate and false detection rate. Secondly, a new prediction layer for tiny targets is added, and the feature fusion network… More >

Tianmin Deng^*, Xiyue Zhang, Xinxin Cheng

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 533-549, 2024, DOI:10.32604/cmc.2023.044639

Abstract Vehicle detection plays a crucial role in the field of autonomous driving technology. However, directly applying deep learning-based object detection algorithms to complex road scene images often leads to subpar performance and slow inference speeds in vehicle detection. Achieving a balance between accuracy and detection speed is crucial for real-time object detection in real-world road scenes. This paper proposes a high-precision and fast vehicle detector called the feature-guided bidirectional pyramid network (FBPN). Firstly, to tackle challenges like vehicle occlusion and significant background interference, the efficient feature filtering module (EFFM) is introduced into the deep network,… More >

Deyong Shang^1,2, Xi Zhang¹, Fengqi Liang¹, Chunde Zhai¹, Hang Yang¹, Yanqi Niu^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2027-2041, 2024, DOI:10.32604/cmes.2023.045750

Abstract When the amphibious vehicle navigates in water, the angle of the anti-wave plate and the position of the center of gravity greatly influence the navigation characteristics. In the relevant research on reducing the navigation resistance of amphibious vehicles by adjusting the angle of the anti-wave plate, there is a lack of scientific selection of parameters and reasonable research of simulation results by using mathematical methods, and the influence of the center of gravity position on navigation characteristics is not considered at the same time. To study the influence of the combinations of the angle of… More >

Xingwang Li^1,2, Hua Pang¹, Geng Li^1,*, Junjie Jiang¹, Hui Zhang³, Changfei Gu⁴, Dong Yuan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1135-1166, 2024, DOI:10.32604/cmes.2023.031534

Abstract The development of the fifth-generation (5G) mobile communication systems has entered the commercialization stage. 5G has a high data rate, low latency, and high reliability that can meet the basic demands of most industries and daily life, such as the Internet of Things (IoT), intelligent transportation systems, positioning, and navigation. The continuous progress and development of society have aroused wide concern. Positioning accuracy is the core demand for the applications, especially in complex environments such as airports, warehouses, supermarkets, and basements. However, many factors also affect the accuracy of positioning in those environments, for example, More >

Liang Liu, Guangda Xu^*, Yuan Zhao, Yi Lu, Yu Li, Jing Gao

Energy Engineering, Vol.121, No.2, pp. 377-404, 2024, DOI:10.32604/ee.2023.041311

Abstract The couple between the power network and the transportation network (TN) is deepening gradually with the increasing penetration rate of electric vehicles (EV), which also poses a great challenge to the traditional voltage control scheme. In this paper, we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV. In the first stage, the action of on-load tap changer and capacitor banks, etc., are determined by optimal power flow calculation, and the node electricity price is also determined based on dynamic time-of-use tariff mechanism. In the second stage, multiple… More >

Zain Anwar Ali^1,2,*, Dingnan Deng¹, Muhammad Kashif Shaikh³, Raza Hasan⁴, Muhammad Aamir Khan²

Computer Systems Science and Engineering, Vol.48, No.1, pp. 1-34, 2024, DOI:10.32604/csse.2023.041866

Abstract Technological advances in unmanned aerial vehicles (UAVs) pursued by artificial intelligence (AI) are improving remote sensing applications in smart agriculture. These are valuable tools for monitoring and disease identification of plants as they can collect data with no damage and effects on plants. However, their limited carrying and battery capacities restrict their performance in larger areas. Therefore, using multiple UAVs, especially in the form of a swarm is more significant for monitoring larger areas such as crop fields and forests. The diversity of research studies necessitates a literature review for more progress and contribution in… More >

A. Vikram¹, J. Akshya², Sultan Ahmad^3,4, L. Jerlin Rubini⁵, Seifedine Kadry^6,7,8, Jungeun Kim^9,*

Computer Systems Science and Engineering, Vol.48, No.1, pp. 115-130, 2024, DOI:10.32604/csse.2023.037928

Abstract Traffic monitoring through remote sensing images (RSI) is considered an important research area in Intelligent Transportation Systems (ITSs). Vehicle counting systems must be simple enough to be implemented in real-time. With the fast expansion of road traffic, real-time vehicle counting becomes essential in constructing ITS. Compared with conventional technologies, the remote sensing-related technique for vehicle counting exhibits greater significance and considerable advantages in its flexibility, low cost, and high efficiency. But several techniques need help in balancing complexity and accuracy technique. Therefore, this article presents a deep learning-based vehicle detection and counting system for ITS More >