Shabana Ramzan¹, Yazeed Yasin Ghadi², Hanan Aljuaid³, Aqsa Mahmood^1,*, Basharat Ali⁴

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 183-199, 2024, DOI:10.32604/cmc.2024.047603

Abstract Traditional farming procedures are time-consuming and expensive as based on manual labor. Farmers have no proper knowledge to select which crop is suitable to grow according to the environmental factors and soil characteristics. This is the main reason for the low yield of crops and the economic crisis in the agricultural sector of the different countries. The use of modern technologies such as the Internet of Things (IoT), machine learning, and ensemble learning can facilitate farmers to observe different factors such as soil electrical conductivity (EC), and environmental factors like temperature to improve crop yield. These parameters play a vital… More >

Yan Xiang^1,2, Daofeng Li^1,2,*, Xinyi Meng^1,2, Chengfeng Dong^1,2, Guanglin Qin^1,2

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1005-1023, 2024, DOI:10.32604/cmc.2024.047143

Abstract The rapid expansion of Internet of Things (IoT) devices across various sectors is driven by steadily increasing demands for interconnected and smart technologies. Nevertheless, the surge in the number of IoT device has caught the attention of cyber hackers, as it provides them with expanded avenues to access valuable data. This has resulted in a myriad of security challenges, including information leakage, malware propagation, and financial loss, among others. Consequently, developing an intrusion detection system to identify both active and potential intrusion traffic in IoT networks is of paramount importance. In this paper, we propose ResNeSt-biGRU, a practical intrusion detection… More >

SOBHA KOTA^*, RATNAKUMARI ANANTHA, VAYUNANDANA RAO GOVADA, PRADEEP DUMPALA

Journal of Polymer Materials, Vol.40, No.3-4, pp. 285-303, 2023, DOI:10.32381/JPM.2023.40.3-4.10

Abstract The exoskeleton of marine shrimp contains a natural, biocompatible polymer chitin, which is dumped as a waste. The study proposes the sustainable single-pot-extraction of chitosan from the waste and its use in the fabrication of wound-dressings, and thus leverage its piezoelectric, antioxidant, hypoglycaemic and medicinal properties in wound-healing. The Fourier transform infrared spectrum revealed that marine chitosan contains functional groups with N-O, O-H, and CO stretching. Scanning electron micrographs demonstrated the spherical and mesoporous structures of the extracted chitosan. X-ray diffraction analysis showed a semi-crystalline phase of chitosan particles with a mean size of 28.9 nm. The film prepared with… More >

LIJUN CHEN^*, ZHEQING GONG, ZHENGRONG FU

Journal of Polymer Materials, Vol.40, No.3-4, pp. 157-164, 2023, DOI:10.32381/JPM.2023.40.3-4.3

Abstract The organic fluorine modified/containing cationic acrylic resin is prepared via solution polymerization technique using hexafluorobutyl methacrylate (HFMA) along with butyl acrylate (BA), methyl methacrylate (MMA), styrene (St), dimethylaminoethyl methacrylate (DMAEMA) and hydroxy propyl methacrylate (HPMA) as the comonomers, proprylene glycol monomethyl ether (PGME) as the solvent, and 2, 2-Azo-bis-iso-butyronitrile (AIBN) as the initiator. The synthesized resin in which fluorine atom is introduced into the polymer chains. The cathodic electrodeposition (CED) coatings were prepared by mixing the synthesized resin and blocked isocyanate. The influence of the amount of organic fluorine on the resin and the resultant CED coatings is investigated in… More >

Mir Abdullatif Yahya¹, Fatma Tunali¹, Dilek Killi^2,*, Atalay Sökmen²

Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 427-444, 2024, DOI:10.32604/phyton.2024.046271

Abstract An effective in vitro propagation protocol was designed for Lavandula angustifolia Miller, a medicinal aromatic plant that is a prominent source of volatile organic compounds (VOCs). Murashige and Skoog media were supplemented with various concentrations of Plant Growth Regulators (PGRs), and the growth parameters of the nodal segments were examined. Nodal explants formed callus when they were supplemented with 2 mg/L of 6-Benzylaminopurine (BAP). The superior hormonal concentration of Murashige and Skoog (MS) media for the proliferation of shoots from callus cultures (39.33%) was 5 mg/L of 2-Isopentenyl adenine (2iP), and the favorable media for the growth of L. angustifolia… More >

Shaha Al-Otaibi¹, Rahim Khan^2,*, Hashim Ali², Aftab Ahmed Khan², Amir Saeed³, Jehad Ali^4,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3805-3823, 2024, DOI:10.32604/cmc.2024.049017

Abstract The Internet of Things (IoT) is a smart networking infrastructure of physical devices, i.e., things, that are embedded with sensors, actuators, software, and other technologies, to connect and share data with the respective server module. Although IoTs are cornerstones in different application domains, the device’s authenticity, i.e., of server(s) and ordinary devices, is the most crucial issue and must be resolved on a priority basis. Therefore, various field-proven methodologies were presented to streamline the verification process of the communicating devices; however, location-aware authentication has not been reported as per our knowledge, which is a crucial metric, especially in scenarios where… More >

Bing Liu¹, Zhe Zhang¹, Shengrong Hu², Song Sun^3,*, Dapeng Liu⁴, Zhenyu Qiu⁵

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4049-4069, 2024, DOI:10.32604/cmc.2024.048099

Abstract Internet of Things (IoT) is vulnerable to data-tampering (DT) attacks. Due to resource limitations, many anomaly detection systems (ADSs) for IoT have high false positive rates when detecting DT attacks. This leads to the misreporting of normal data, which will impact the normal operation of IoT. To mitigate the impact caused by the high false positive rate of ADS, this paper proposes an ADS management scheme for clustered IoT. First, we model the data transmission and anomaly detection in clustered IoT. Then, the operation strategy of the clustered IoT is formulated as the running probabilities of all ADSs deployed on… More >

Jiangang Lu, Ruifeng Zhao^*, Zhiwen Yu, Yue Dai, Kaiwen Zeng

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4453-4469, 2024, DOI:10.32604/cmc.2024.048020

Abstract Time synchronization (TS) is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things (IoT). Multi-clock source time synchronization (MTS) has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales, and the coupling of synchronization latency jitter and pulse phase difference. In this paper, the multi-timescale MTS model is conducted, and the reinforcement learning (RL) and analytic hierarchy process (AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation… More >

Bin Li^*, Linghui Kong, Xiangyi Zhang, Bochuo Kou, Hui Yu, Bowen Liu

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3267-3282, 2024, DOI:10.32604/cmc.2024.047193

Abstract The automatic collection of power grid situation information, along with real-time multimedia interaction between the front and back ends during the accident handling process, has generated a massive amount of power grid data. While wireless communication offers a convenient channel for grid terminal access and data transmission, it is important to note that the bandwidth of wireless communication is limited. Additionally, the broadcast nature of wireless transmission raises concerns about the potential for unauthorized eavesdropping during data transmission. To address these challenges and achieve reliable, secure, and real-time transmission of power grid data, an intelligent security transmission strategy with sensor-transmission-computing… More >

Haomiao Wang¹, Jinxi Wang², Qingmei Sui^2,*, Faye Zhang², Yibin Li¹, Mingshun Jiang², Phanasindh Paitekul³

Structural Durability & Health Monitoring, Vol.18, No.2, pp. 91-110, 2024, DOI:10.32604/sdhm.2023.041522

Abstract Due to their robust learning and expression ability for complex features, the deep learning (DL) model plays a vital role in bearing fault diagnosis. However, since there are fewer labeled samples in fault diagnosis, the depth of DL models in fault diagnosis is generally shallower than that of DL models in other fields, which limits the diagnostic performance. To solve this problem, a novel transfer residual Swin Transformer (RST) is proposed for rolling bearings in this paper. RST has 24 residual self-attention layers, which use the hierarchical design and the shifted window-based residual self-attention. Combined with transfer learning techniques, the… More >