Tiezhou Wu, Yukan Zhang^*

Energy Engineering, Vol.121, No.8, pp. 2231-2255, 2024, DOI:10.32604/ee.2024.049883

Abstract In order to solve the problem of inconsistent energy in the charging and discharging cycles of lithium-ion battery packs, a new multilayer equilibrium topology is designed in this paper. The structure adopts a hierarchical structure design, which includes intra-group equilibrium, primary inter-group equilibrium and secondary inter-group equilibrium. This structure greatly increases the number of equilibrium paths for lithium-ion batteries, thus shortening the time required for equilibrium, and improving the overall efficiency. In terms of control strategy, fuzzy logic control (FLC) is chosen to control the size of the equilibrium current during the equilibrium process. We… More >

Randeep Singh^1,*, Tomoki Oridate², Tien Nguyen²

Frontiers in Heat and Mass Transfer, Vol.22, No.3, pp. 703-717, 2024, DOI:10.32604/fhmt.2024.050744

Abstract Electrification of vehicles intensifies their cooling demands due to the requirements of maintaining electronics/electrical systems below their maximum temperature threshold. In this paper, passive cooling approaches based on heat pipes have been considered for the thermal management of electric vehicle (EV) traction systems including battery, inverter, and motor. For the battery, a heat pipe base plate is used to provide high heat removal (180 W per module) and better thermal uniformity (<5°C) for the battery modules in a pack while downsizing the liquid cold plate system. In the case of Inverter, two phase cooling system… More > Graphic Abstract

Yuanyao Lu^1,*, Wei Chen², Zhanhe Yu¹, Jingxuan Wang¹, Chaochao Yang²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5051-5066, 2024, DOI:10.32604/cmc.2024.050865

Abstract With the rapid advancement of social economies, intelligent transportation systems are gaining increasing attention. Central to these systems is the detection of abnormal vehicle behavior, which remains a critical challenge due to the complexity of urban roadways and the variability of external conditions. Current research on detecting abnormal traffic behaviors is still nascent, with significant room for improvement in recognition accuracy. To address this, this research has developed a new model for recognizing abnormal traffic behaviors. This model employs the R3D network as its core architecture, incorporating a dense block to facilitate feature reuse. This… More >

Aneel Kumar¹, Mahesh Kumar¹, Amir Mahmood Soomro¹, Laveet Kumar^2,*

Energy Engineering, Vol.121, No.6, pp. 1439-1457, 2024, DOI:10.32604/ee.2024.049977

Abstract Electric vehicles (EVs) are the most interesting and innovative technology in the 21st century because of their enormous advantages, both technically and economically. Their emissions rate compared to fuel-based vehicles is negligible as they do not consume fuel and hence do not emit any harmful gases. However, their bulk production, adoption and lack of charging stations increase the stress of power stations due to modern-day lifestyles. If Electric vehicles demand increases drastically then conventional power stations will not bear their demand and if they generate electricity by conventional means it will be very costly and… More >

Zhijian Liu^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3787-3803, 2024, DOI:10.32604/cmc.2024.048998

Abstract Considering the variations in imaging sizes of the unmanned aerial vehicles (UAV) at different aerial photography heights, as well as the influence of factors such as light and weather, which can result in missed detection and false detection of the model, this paper presents a comprehensive detection model based on the improved lightweight You Only Look Once version 8s (YOLOv8s) algorithm used in natural light and infrared scenes (L_YOLO). The algorithm proposes a special feature pyramid network (SFPN) structure and substitutes most of the neck feature extraction module with the Special deformable convolution feature extraction… More >

Guojun Chen^*, Danguo Cheng, Wei Chen, Xue Yang, Tiezheng Guo

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3721-3741, 2024, DOI:10.32604/cmc.2024.047325

Abstract With the increase in ocean exploration activities and underwater development, the autonomous underwater vehicle (AUV) has been widely used as a type of underwater automation equipment in the detection of underwater environments. However, nowadays AUVs generally have drawbacks such as weak endurance, low intelligence, and poor detection ability. The research and implementation of path-planning methods are the premise of AUVs to achieve actual tasks. To improve the underwater operation ability of the AUV, this paper studies the typical problems of path-planning for the ant colony algorithm and the artificial potential field algorithm. In response to… More >

Usman Khan¹, Muhammad Khalid Khan¹, Muhammad Ayub Latif¹, Muhammad Naveed^1,2,*, Muhammad Mansoor Alam^2,3,4, Salman A. Khan¹, Mazliham Mohd Su’ud^2,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 2967-3000, 2024, DOI:10.32604/cmc.2024.045101

Abstract Recently, there has been a notable surge of interest in scientific research regarding spectral images. The potential of these images to revolutionize the digital photography industry, like aerial photography through Unmanned Aerial Vehicles (UAVs), has captured considerable attention. One encouraging aspect is their combination with machine learning and deep learning algorithms, which have demonstrated remarkable outcomes in image classification. As a result of this powerful amalgamation, the adoption of spectral images has experienced exponential growth across various domains, with agriculture being one of the prominent beneficiaries. This paper presents an extensive survey encompassing multispectral and… More >

Asifa Mehmood Qureshi¹, Naif Al Mudawi², Mohammed Alonazi³, Samia Allaoua Chelloug⁴, Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3683-3701, 2024, DOI:10.32604/cmc.2024.043611

Abstract Road traffic monitoring is an imperative topic widely discussed among researchers. Systems used to monitor traffic frequently rely on cameras mounted on bridges or roadsides. However, aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger area. To this end, different models have shown the ability to recognize and track vehicles. However, these methods are not mature enough to produce accurate results in complex road scenes. Therefore, this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with… More >

Peng Geng^1,*, Annan Yang², Yan Liu³

Journal on Artificial Intelligence, Vol.6, pp. 43-52, 2024, DOI:10.32604/jai.2024.047642

Abstract This article presents a real-time localization method for Unmanned Aerial Vehicles (UAVs) based on continuous image processing. The proposed method employs the Scale Invariant Feature Transform (SIFT) algorithm to identify key points in multi-scale space and generate descriptor vectors to match identical objects across multiple images. These corresponding points in the image provide pixel positions, which can be combined with transformation equations, allow for the calculation of the UAV’s actual ground position. Additionally, the physical coordinates of matching points in the image can be obtained, corresponding to the UAV’s physical coordinates. The method achieves real-time More >

Abdullah Alsaleh^1,2,*

Computer Systems Science and Engineering, Vol.48, No.2, pp. 431-449, 2024, DOI:10.32604/csse.2023.043107

Abstract With the increasing number of connected devices in the Internet of Things (IoT) era, the number of intrusions is also increasing. An intrusion detection system (IDS) is a secondary intelligent system for monitoring, detecting and alerting against malicious activity. IDS is important in developing advanced security models. This study reviews the importance of various techniques, tools, and methods used in IoT detection and/or prevention systems. Specifically, it focuses on machine learning (ML) and deep learning (DL) techniques for IDS. This paper proposes an accurate intrusion detection model to detect traditional and new attacks on the… More >