Mengxu Su¹, Zhanjiang Han^1,*, Zhen Zhao², Xiaofeng Wu¹, Jiaju Wu¹

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1689-1703, 2024, DOI:10.32604/phyton.2024.052814

Abstract Leaves are important ‘source’ organs that synthesize organic matter, providing carbon sources for plant growth. Here, we used Populus talassica × Populus euphratica, the dominant species in ecological and timber forests, to simulate carbon limitation through artificial 25%, 50%, and 75% defoliation treatments and explore the effects on root, stem, and leaf morphology, biomass accumulation, and carbon allocation strategies. At the 60th d after treatment, under 25% defoliation treatment, the plant height, specific leaf weight, root surface area and volume, and concentrations of non-structural carbohydrates in stem and root were significantly increased by 9.13%, 20.00%, 16.60%,… More >

Song Gao¹, Ruocheng Xu², Lin Li³, Jiao Wang², Nian Liu², Johannes M. H. Knops⁴, Junfeng Wang^2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1667-1675, 2024, DOI:10.32604/phyton.2024.051548

Abstract Understanding how summer warming influences the parent and daughter shoot production in a perennial clonal grass is vital for comprehending the response of grassland productivity to global warming. Here, we conducted a simulated experiment using potted Leymus chinensis, to study the relationship between the photosynthetic activity of parent shoots and the production of daughter shoots under a whole (90 days) summer warming scenario (+3°C). The results showed that the biomass of parents and buds decreased by 25.52% and 33.45%, respectively, under warming conditions. The reduction in parent shoot biomass due to warming directly resulted from decreased… More >

Xu Zhang¹, Yi He¹, Haiwen Yi¹, Yulu Zhang², Yuan Li², Shuai Ma², Gui Li³, Zhiyuan Zhao⁴, Yue Liu¹, Junyang Liu¹, Guangjun Wen¹, Jian Li^1,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 897-912, 2024, DOI:10.32604/cmc.2024.050000

Abstract When the radio frequency identification (RFID) system inventories multiple tags, the recognition rate will be seriously affected due to collisions. Based on the existing dynamic frame slotted Aloha (DFSA) algorithm, a sub-frame observation and cyclic redundancy check (CRC) grouping combined dynamic framed slotted Aloha (SUBF-CGDFSA) algorithm is proposed. The algorithm combines the precise estimation method of the quantity of large-scale tags, the large-scale tags grouping mechanism based on CRC pseudo-random characteristics, and the Aloha anti-collision optimization mechanism based on sub-frame observation. By grouping tags and sequentially identifying them within subframes, it accurately estimates the number More >

Ahmed Khalid¹, Rana Asif Rehman¹, Byung-Seo Kim^2,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 61-103, 2024, DOI:10.32604/cmc.2024.049981

Abstract Wireless Ad Hoc Networks consist of devices that are wirelessly connected. Mobile Ad Hoc Networks (MANETs), Internet of Things (IoT), and Vehicular Ad Hoc Networks (VANETs) are the main domains of wireless ad hoc network. Internet is used in wireless ad hoc network. Internet is based on Transmission Control Protocol (TCP)/Internet Protocol (IP) network where clients and servers interact with each other with the help of IP in a pre-defined environment. Internet fetches data from a fixed location. Data redundancy, mobility, and location dependency are the main issues of the IP network paradigm. All these… More >

Amal Al-Rasheed¹, Rahim Khan^2,3,*, Tahani Alsaed⁴, Mahwish Kundi^2,5, Mohamad Hanif Md. Saad⁶, Mahidur R. Sarker^7,8

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1305-1323, 2024, DOI:10.32604/cmc.2024.049215

Abstract Due to the overwhelming characteristics of the Internet of Things (IoT) and its adoption in approximately every aspect of our lives, the concept of individual devices’ privacy has gained prominent attention from both customers, i.e., people, and industries as wearable devices collect sensitive information about patients (both admitted and outdoor) in smart healthcare infrastructures. In addition to privacy, outliers or noise are among the crucial issues, which are directly correlated with IoT infrastructures, as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing, i.e.,… More >

Soumia Mounir^1,2,*, Miloudia Slaoui², Youssef Maaloufa^1,2, Fatima Zohra El Wardi^2,3, Yakubu Aminu Dodo^4,5, Sara Ibn-Elhaj², Abdelhamid Khabbazi²

Journal of Renewable Materials, Vol.12, No.5, pp. 1007-1027, 2024, DOI:10.32604/jrm.2024.049392

Abstract Creating sustainable cities is the only way to live in a clean environment, and this problem can be solved by using bio-sourced and recycled materials. For this purpose, the authors contribute to the valuation of sheep wool waste as an eco-friendly material to be used in insulation. The paper investigates the thermal, hygrothermal, and biological aspects of sheep wool by testing a traditional treatment. The biological method of aerobic mesophilic flora has been applied. Fluorescence X was used to determine the chemical composition of the materials used. Also, thermal characterization has been conducted. The thermal… More >

Tahir Abbas^1,*, Ali Haider Khan², Khadija Kanwal³, Ali Daud^4,*, Muhammad Irfan⁵, Amal Bukhari⁶, Riad Alharbey⁶

Computer Systems Science and Engineering, Vol.48, No.4, pp. 871-895, 2024, DOI:10.32604/csse.2024.049026

Abstract The integration of the Internet of Medical Things (IoMT) and the Internet of Things (IoT), which has revolutionized patient care through features like remote critical care and real-time therapy, is examined in this study in response to the changing healthcare landscape. Even with these improvements, security threats are associated with the increased connectivity of medical equipment, which calls for a thorough assessment. With a primary focus on addressing security and performance enhancement challenges, the research classifies current IoT communication devices, examines their applications in IoMT, and investigates important aspects of IoMT devices in healthcare. The More >

Asad Raza^1,*, Shahzad Memon¹, Muhammad Ali Nizamani¹, Mahmood Hussain Shah²

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 545-566, 2024, DOI:10.32604/iasc.2024.051779

Abstract Smart Industrial environments use the Industrial Internet of Things (IIoT) for their routine operations and transform their industrial operations with intelligent and driven approaches. However, IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the internet. Traditional signature-based IDS are effective in detecting known attacks, but they are unable to detect unknown emerging attacks. Therefore, there is the need for an IDS which can learn from data and detect new threats. Ensemble Machine Learning (ML) and individual Deep Learning (DL) based IDS have been developed, and these individual models achieved… More >

Yue Wan, Nan Jiang^*, Ziyu Liu

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 3017-3034, 2024, DOI:10.32604/cmes.2024.051101

Abstract The Social Internet of Things (SIoT) integrates the Internet of Things (IoT) and social networks, taking into account the social attributes of objects and diversifying the relationship between humans and objects, which overcomes the limitations of the IoT’s focus on associations between objects. Artificial Intelligence (AI) technology is rapidly evolving. It is critical to build trustworthy and transparent systems, especially with system security issues coming to the surface. This paper emphasizes the social attributes of objects and uses hypergraphs to model the diverse entities and relationships in SIoT, aiming to build an SIoT hypergraph generation… More >

Huang Zeng, Mingtian Zhang, Tengfei Liu, Anjia Yang^*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5125-5142, 2024, DOI:10.32604/cmc.2024.052846

Abstract Federated learning is an important distributed model training technique in Internet of Things (IoT), in which participant selection is a key component that plays a role in improving training efficiency and model accuracy. This module enables a central server to select a subset of participants to perform model training based on data and device information. By doing so, selected participants are rewarded and actively perform model training, while participants that are detrimental to training efficiency and model accuracy are excluded. However, in practice, participants may suspect that the central server may have miscalculated and thus… More >