Hao Chen¹, Jie Xu¹, Yibo Hu¹, Fuzhou Niu^1,*, Zhiyan Li², Dan Wang², Guizhong Fu¹, Chuanxin Li^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1251-1262, 2023, DOI:10.32604/cmes.2022.022279 - 31 August 2022

Abstract Aiming at the in situ and mobile observation of urban environmental air pollution, a portable instrument using ultraviolet spectrum retrieval algorithm was developed based on the basis of Differential Optical Absorption Spectroscopy (DOAS) and multiple-pass cell technique. Typical trace gas pollutants, NH₃, SO₂, and NO₂, were explored using their optical spectral characteristics in deep ultraviolet wavelength range from 210 to 215 nm. The gas concentration was retrieved by Lambert-Beer's law and nonlinear least square method. With an optimized optical alignment, the detection limits of NH₃, SO₂, NO₂ were estimated to be 2.2, 2.3, and 36.2 ppb, respectively. The More >

Yingpeng Dai¹, Junzheng Wang¹, Jing Li^1,*, Lingfeng Meng², Songfeng Wang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 135-156, 2023, DOI:10.32604/cmes.2022.021525 - 24 August 2022

Abstract It is important for the autonomous system to understand environmental information. For the autonomous system, it is desirable to have a strong generalization ability to deal with different complex environmental information, as well as have high accuracy and quick inference speed. Network ensemble architecture is a good choice to improve network performance. However, it is unsuitable for real-time applications on the autonomous system. To tackle this problem, a new neural network ensemble named partial-shared ensemble network (PSENet) is presented. PSENet changes network ensemble architecture from parallel architecture to scatter architecture and merges multiple component networks More >

Meng Zhang¹, Zhichao Zhou¹, Guifeng Zhao^1,*, Fangfang Wang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 673-698, 2023, DOI:10.32604/cmes.2022.021463 - 24 August 2022

Abstract Computational fluid dynamics (CFD) and the finite element method (FEM) are used to investigate the wind-driven dynamic response of cantilever traffic signal support structures as a whole. By building a finite element model with the same scale as the actual structure and performing modal analysis, a preliminary understanding of the dynamic properties of the structure is obtained. Based on the two-way fluid-structure coupling calculation method, the wind vibration response of the structure under different incoming flow conditions is calculated, and the vibration characteristics of the structure are analyzed through the displacement time course data of… More >

Tsu-Yang Wu¹, Qian Meng¹, Lei Yang¹, Saru Kumari², Matin Pirouz^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 317-341, 2023, DOI:10.32604/cmes.2022.019595 - 24 August 2022

Abstract The development of the Internet of Things has facilitated the rapid development of various industries. With the improvement in people’s living standards, people’s health requirements are steadily improving. However, owing to the scarcity of medical and health care resources in some areas, the demand for remote surgery has gradually increased. In this paper, we investigate remote surgery in the healthcare environment. Surgeons can operate robotic arms to perform remote surgery for patients, which substantially facilitates successful surgeries and saves lives. Recently, Kamil et al. proposed a secure protocol for surgery in the healthcare environment. However, More >

Raqinah Alrabiah, Muhammad Hussain^*, Hatim A. AboAlSamh

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2941-2962, 2023, DOI:10.32604/iasc.2023.030036 - 17 August 2022

Abstract The gender recognition problem has attracted the attention of the computer vision community due to its importance in many applications (e.g., surveillance and human–computer interaction [HCI]). Images of varying levels of illumination, occlusion, and other factors are captured in uncontrolled environments. Iris and facial recognition technology cannot be used on these images because iris texture is unclear in these instances, and faces may be covered by a scarf, hijab, or mask due to the COVID-19 pandemic. The periocular region is a reliable source of information because it features rich discriminative biometric features. However, most existing… More >

Nitish Pathak¹, Shams Tabrez Siddiqui², Anjani Kumar Singha³, Heba G Mohamed⁴, Shabana Urooj^4,*, Abhinandan R Patil⁵

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3021-3036, 2023, DOI:10.32604/iasc.2023.029053 - 17 August 2022

Abstract The coronavirus, formerly known as COVID-19, has caused massive global disasters. As a precaution, most governments imposed quarantine periods ranging from months to years and postponed significant financial obligations. Furthermore, governments around the world have used cutting-edge technologies to track citizens’ activity. Thousands of sensors were connected to IoT (Internet of Things) devices to monitor the catastrophic eruption with billions of connected devices that use these novel tools and apps, privacy and security issues regarding data transmission and memory space abound. In this study, we suggest a blockchain-based methodology for safeguarding data in the billions More >

Anwar R Shaheen^*, Sundar Santhosh Kumar

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2963-2978, 2023, DOI:10.32604/iasc.2023.025780 - 17 August 2022

Abstract Cloud computing plays a significant role in Information Technology (IT) industry to deliver scalable resources as a service. One of the most important factor to increase the performance of the cloud server is maximizing the resource utilization in task scheduling. The main advantage of this scheduling is to maximize the performance and minimize the time loss. Various researchers examined numerous scheduling methods to achieve Quality of Service (QoS) and to reduce execution time. However, it had disadvantages in terms of low throughput and high response time. Hence, this study aimed to schedule the task efficiently… More >

Fatih Aydemir¹, Aydin Cetin^2,*

Computer Systems Science and Engineering, Vol.45, No.1, pp. 215-230, 2023, DOI:10.32604/csse.2023.031116 - 16 August 2022

Abstract Dynamic area coverage with small unmanned aerial vehicle (UAV) systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process. Collaborative behavior of a group of UAVs in an unknown environment is another hard problem to be solved. In this paper, we propose a method for decentralized execution of multi-UAVs for dynamic area coverage problems. The proposed decentralized decision-making dynamic area coverage (DDMDAC) method utilizes reinforcement learning (RL) where each UAV is represented by an intelligent agent that learns policies to create collaborative behaviors in partially observable… More >

Fadwa Alrowais¹, Sami Althahabi², Saud S. Alotaibi³, Abdullah Mohamed⁴, Manar Ahmed Hamza^5,*, Radwa Marzouk⁶

Computer Systems Science and Engineering, Vol.45, No.1, pp. 687-700, 2023, DOI:10.32604/csse.2023.030188 - 16 August 2022

Abstract Recently, Internet of Things (IoT) devices produces massive quantity of data from distinct sources that get transmitted over public networks. Cybersecurity becomes a challenging issue in the IoT environment where the existence of cyber threats needs to be resolved. The development of automated tools for cyber threat detection and classification using machine learning (ML) and artificial intelligence (AI) tools become essential to accomplish security in the IoT environment. It is needed to minimize security issues related to IoT gadgets effectively. Therefore, this article introduces a new Mayfly optimization (MFO) with regularized extreme learning machine (RELM)… More >

B. Chellapraba^1,*, D. Manohari², K. Periyakaruppan³, M. S. Kavitha⁴

Computer Systems Science and Engineering, Vol.45, No.1, pp. 483-495, 2023, DOI:10.32604/csse.2023.029854 - 16 August 2022

Abstract Owing to massive technological developments in Internet of Things (IoT) and cloud environment, cloud computing (CC) offers a highly flexible heterogeneous resource pool over the network, and clients could exploit various resources on demand. Since IoT-enabled models are restricted to resources and require crisp response, minimum latency, and maximum bandwidth, which are outside the capabilities. CC was handled as a resource-rich solution to aforementioned challenge. As high delay reduces the performance of the IoT enabled cloud platform, efficient utilization of task scheduling (TS) reduces the energy usage of the cloud infrastructure and increases the income… More >