Kranthi Alluri, S. Gopikrishnan^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 943-961, 2024, DOI:10.32604/cmc.2024.048621

Abstract Secure authentication and accurate localization among Internet of Things (IoT) sensors are pivotal for the functionality and integrity of IoT networks. IoT authentication and localization are intricate and symbiotic, impacting both the security and operational functionality of IoT systems. Hence, accurate localization and lightweight authentication on resource-constrained IoT devices pose several challenges. To overcome these challenges, recent approaches have used encryption techniques with well-known key infrastructures. However, these methods are inefficient due to the increasing number of data breaches in their localization approaches. This proposed research efficiently integrates authentication and localization processes in such a way that they complement each… More >

Sapiah Sakri¹, Shakila Basheer¹, Zuhaira Muhammad Zain¹, Nurul Halimatul Asmak Ismail^2,*, Dua’ Abdellatef Nassar¹, Manal Abdullah Alohali¹, Mais Ayman Alharaki¹

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1157-1185, 2024, DOI:10.32604/cmc.2024.048051

Abstract Background: Sepsis, a potentially fatal inflammatory disease triggered by infection, carries significant health implications worldwide. Timely detection is crucial as sepsis can rapidly escalate if left undetected. Recent advancements in deep learning (DL) offer powerful tools to address this challenge. Aim: Thus, this study proposed a hybrid CNNBDLSTM, a combination of a convolutional neural network (CNN) with a bi-directional long short-term memory (BDLSTM) model to predict sepsis onset. Implementing the proposed model provides a robust framework that capitalizes on the complementary strengths of both architectures, resulting in more accurate and timelier predictions. Method: The sepsis prediction method proposed here utilizes… More >

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 >

BIN LI^1,2,3,#, YUCHENG SHENG^4,#, XIAOYING XU⁴, SHENGCUN WANG³, HONGYAN SONG³, JINGYUAN LI³, HAONAN JI¹, QINGHUA WANG³, XIAODI ZHOU^1,*, LONGJU QI^2,*

BIOCELL, Vol.48, No.4, pp. 601-611, 2024, DOI:10.32604/biocell.2024.047404

Abstract Objective: Chronic kidney disease (CKD) is a progressive disorder characterized by intricate structural and functional alterations in the kidneys, attributable to diverse causative factors. Notably, the therapeutic promise of miR-145-5p in addressing renal pathologies has been discerned. This investigation seeks to elucidate the functional role of miR-145-5p in injured kidneys by subjecting human glomerular mesangial cells (HGMCs) to stimulation with Angiotensin II (AngII). Materials and Methods: Cellular viability and the levels of inflammatory mediators were evaluated utilizing Cell Counting Kit-8 (CCK-8), quantitative real-time polymerase chain reaction (qRT-PCR), and western blot methodologies, both in the presence of AngII incubation and in… More >

Kaiyue Hong, Yasmina Radani, Teja Manda, Jinhui Chen, Liming Yang^*

Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 413-425, 2024, DOI:10.32604/phyton.2024.047739

Abstract This study explores CAMTA genes in the rare and endangered Chinese plant species, Liriodendron chinense. Despite the completion of whole-genome sequencing, the roles of CAMTA genes in calcium regulation and stress responses in this species remain largely unexplored. Within the L. chinense genome, we identified two CAMTA genes, Lchi09764 and Lchi222536, characterized by four functional domains: CG-1, TIG, ANK repeats, and IQ motifs. Our analyses, including phylogenetic investigations, cis-regulatory element analyses, and chromosomal location studies, aim to elucidate the defining features of CAMTA genes in L. chinense. Applying Weighted Gene Co-Expression Network Analysis (WGCNA), we explored the impact of CAMTA… More >

Muhammad Farhan^1,#, Manda Sathish², Rafia Kiran¹, Aroosa Mushtaq³, Alaa Baazeem⁴, Ammarah Hasnain⁵, Fahad Hakim¹, Syed Atif Hasan Naqvi^1,#,*, Mustansar Mubeen⁶, Yasir Iftikhar^6,*, Aqleem Abbas⁷, Muhammad Zeeshan Hassan¹, Mahmoud Moustafa⁸

Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 581-609, 2024, DOI:10.32604/phyton.2024.046857

Abstract

Plant growth and resilience to abiotic stresses, such as soil salinity and drought, depend intricately on nitrogen metabolism. This review explores nitrogen’s regulatory role in plant responses to these challenges, unveiling a dynamic interplay between nitrogen availability and abiotic stress. In the context of soil salinity, a nuanced relationship emerges, featuring both antagonistic and synergistic interactions between salinity and nitrogen levels. Salinity-induced chlorophyll depletion in plants can be alleviated by optimal nitrogen supplementation; however, excessive nitrogen can exacerbate salinity stress. We delve into the complexities of this interaction and its agricultural implications. Nitrogen, a vital element within essential plant structures… 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 >

Muhammad Umar Nasir¹, Omar Kassem Khalil², Karamath Ateeq³, Bassam SaleemAllah Almogadwy⁴, Muhammad Adnan Khan⁵, Muhammad Hasnain Azam⁶, Khan Muhammad Adnan^7,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3303-3321, 2024, DOI:10.32604/cmc.2024.048035

Abstract Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or pathologic. Various cardiotocography measures infer wrongly and give wrong predictions because of human error. The traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as well. Fetal condition is very important to measure at numerous stages and give proper medications to the fetus for its well-being. In the current period Machine learning… More >

Hong Huang¹, Xingxing Zhang^1,*, Ye Lu¹, Ze Li¹, Shaohua Zhou²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3929-3951, 2024, DOI:10.32604/cmc.2024.047918

Abstract While encryption technology safeguards the security of network communications, malicious traffic also uses encryption protocols to obscure its malicious behavior. To address the issues of traditional machine learning methods relying on expert experience and the insufficient representation capabilities of existing deep learning methods for encrypted malicious traffic, we propose an encrypted malicious traffic classification method that integrates global semantic features with local spatiotemporal features, called BERT-based Spatio-Temporal Features Network (BSTFNet). At the packet-level granularity, the model captures the global semantic features of packets through the attention mechanism of the Bidirectional Encoder Representations from Transformers (BERT) model. At the byte-level granularity,… More >

Yilei Wang¹, Xin Sun¹, Guiping Zheng^2,3, Ahmar Rashid⁴, Sami Ullah⁵, Hisham Alasmary⁶, Muhammad Waqas^7,8,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3909-3927, 2024, DOI:10.32604/cmc.2024.047767

Abstract The application of Intelligent Internet of Things (IIoT) in constructing distribution station areas strongly supports platform transformation, upgrade, and intelligent integration. The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer, with the former using intelligent fusion terminals for real-time data collection and processing. However, the influx of multiple low-voltage in the smart grid raises higher demands for the performance, energy efficiency, and response speed of the substation fusion terminals. Simultaneously, it brings significant security risks to the entire distribution substation, posing a major challenge to the smart grid. In response to these challenges, a… More >