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 - 26 January 2024

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 >

Chunlin Xiong^1,2, Zhengqiu Weng^3,4,*, Jia Liu¹, Liang Gu², Fayez Alqahtani⁵, Amr Gafar⁶, Pradip Kumar Sharma⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 3013-3032, 2024, DOI:10.32604/cmes.2023.031088 - 15 December 2023

Abstract With the development of hardware devices and the upgrading of smartphones, a large number of users save privacy-related information in mobile devices, mainly smartphones, which puts forward higher demands on the protection of mobile users’ privacy information. At present, mobile user authentication methods based on human-computer interaction have been extensively studied due to their advantages of high precision and non-perception, but there are still shortcomings such as low data collection efficiency, untrustworthy participating nodes, and lack of practicability. To this end, this paper proposes a privacy-enhanced mobile user authentication method with motion sensors, which mainly… More >

Narit Hnoohom¹, Sakorn Mekruksavanich², Anuchit Jitpattanakul^3,4,*

Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 139-151, 2023, DOI:10.32604/iasc.2023.033940 - 05 February 2024

Abstract Accidents are still an issue in an intelligent transportation system, despite developments in self-driving technology (ITS). Drivers who engage in risky behavior account for more than half of all road accidents. As a result, reckless driving behaviour can cause congestion and delays. Computer vision and multimodal sensors have been used to study driving behaviour categorization to lessen this problem. Previous research has also collected and analyzed a wide range of data, including electroencephalography (EEG), electrooculography (EOG), and photographs of the driver’s face. On the other hand, driving a car is a complicated action that requires… More >

Tariq Qayyum¹, Zouheir Trabelsi^1,*, Asadullah Tariq¹, Muhammad Ali², Kadhim Hayawi³, Irfan Ud Din⁴

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1739-1757, 2023, DOI:10.32604/cmc.2023.043684 - 29 November 2023

Abstract Federated Learning (FL) enables collaborative and privacy-preserving training of machine learning models within the Internet of Vehicles (IoV) realm. While FL effectively tackles privacy concerns, it also imposes significant resource requirements. In traditional FL, trained models are transmitted to a central server for global aggregation, typically in the cloud. This approach often leads to network congestion and bandwidth limitations when numerous devices communicate with the same server. The need for Flexible Global Aggregation and Dynamic Client Selection in FL for the IoV arises from the inherent characteristics of IoV environments. These include diverse and distributed… More >

Jianguo Wang¹, Kuan Zhang^1,*, Yuesheng Zhao^2,*, Xiaoling Wang², Muhammad Shamrooz Aslam²

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 79-96, 2023, DOI:10.32604/cmc.2023.040506 - 31 October 2023

Abstract The purpose of Human Activities Recognition (HAR) is to recognize human activities with sensors like accelerometers and gyroscopes. The normal research strategy is to obtain better HAR results by finding more efficient eigenvalues and classification algorithms. In this paper, we experimentally validate the HAR process and its various algorithms independently. On the base of which, it is further proposed that, in addition to the necessary eigenvalues and intelligent algorithms, correct prior knowledge is even more critical. The prior knowledge mentioned here mainly refers to the physical understanding of the analyzed object, the sampling process, the More >

Fadhil Mukhlif^1,*, Norafida Ithnin¹, Roobaea Alroobaea², Sultan Algarni³, Wael Y. Alghamdi², Ibrahim Hashem⁴

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 583-599, 2023, DOI:10.32604/cmc.2023.038757 - 31 October 2023

Abstract The World Health Organization (WHO) refers to the 2019 new coronavirus epidemic as COVID-19, and it has caused an unprecedented global crisis for several nations. Nearly every country around the globe is now very concerned about the effects of the COVID-19 outbreaks, which were previously only experienced by Chinese residents. Most of these nations are now under a partial or complete state of lockdown due to the lack of resources needed to combat the COVID-19 epidemic and the concern about overstretched healthcare systems. Every time the pandemic surprises them by providing new values for various… More >

Sakorn Mekruksavanich¹, Narit Hnoohom², Anuchit Jitpattanakul^3,4,*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2669-2686, 2023, DOI:10.32604/iasc.2023.038549 - 11 September 2023

Abstract Recognition of human activity is one of the most exciting aspects of time-series classification, with substantial practical and theoretical implications. Recent evidence indicates that activity recognition from wearable sensors is an effective technique for tracking elderly adults and children in indoor and outdoor environments. Consequently, researchers have demonstrated considerable passion for developing cutting-edge deep learning systems capable of exploiting unprocessed sensor data from wearable devices and generating practical decision assistance in many contexts. This study provides a deep learning-based approach for recognizing indoor and outdoor movement utilizing an enhanced deep pyramidal residual model called SenPyramidNet… More >

Pan Chen^1,2,3, Baojin Chu^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09199

Abstract Generally, film dielectric materials often exhibit size-dependent structure and electric properties. In this work, we demonstrate a similar behavior in bulk Na_0.5Bi_0.5TiO₃ (NBT)-based polycrystalline ceramics. According to the results from X-ray diffraction, the (Na_0.5Bi_0.5)_0.92Ba_0.08Ti_0.99Mg_0.01O_2.99 (NBT8M1.0) ceramic showed a complex structure that consists of rhombohedral, tetragonal and cubic symmetries. We found, when decreasing the thickness of a ϕ 10 mm NBT8M1.0 ceramic from 1230 μm to 230 μm, the ceramic showed increased content of cubic symmetry (CC) from 28% to 56%. Meanwhile, the piezoelectric response (d₃₃₎ increased from 107 pC/N to 134 pC/N and the depolarization temperature (T_d) decreased… More >

Madallah Alruwaili^1,*, Muhammad Hameed Siddiqi¹, Kamran Farid², Mohammad Azad¹, Saad Alanazi¹, Asfandyar Khan², Abdullah Khan²

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2293-2311, 2023, DOI:10.32604/csse.2023.040312 - 28 July 2023

Abstract Numerous types of research on healthcare monitoring systems have been conducted for calculating heart rate, ECG, nasal/oral airflow, temperature, light sensor, and fall detection sensor. Different researchers have done different work in the field of health monitoring with sensor networks. Different researchers used built-in apps, such as some used a small number of parameters, while some other studies used more than one microcontroller and used senders and receivers among the microcontrollers to communicate, and outdated tools for study development. While no efficient, cheap, and updated work is proposed in the field of sensor-based health monitoring… More >

Apurva Sonavane¹, Aditya Khamparia^2,*, Deepak Gupta³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1525-1550, 2023, DOI:10.32604/cmes.2023.028203 - 26 June 2023

Abstract IoT usage in healthcare is one of the fastest growing domains all over the world which applies to every age group. Internet of Medical Things (IoMT) bridges the gap between the medical and IoT field where medical devices communicate with each other through a wireless communication network. Advancement in IoMT makes human lives easy and better. This paper provides a comprehensive detailed literature survey to investigate different IoMT-driven applications, methodologies, and techniques to ensure the sustainability of IoMT-driven systems. The limitations of existing IoMT frameworks are also analyzed concerning their applicability in real-time driven systems More >