Sumit Sow^1,#, Shivani Ranjan^1,#,*, Mahmoud F. Seleiman^2,3, Hiba M. Alkharabsheh^4,*, Mukesh Kumar¹, Navnit Kumar¹, Smruti Ranjan Padhan⁵, Dhirendra Kumar Roy¹, Dibyajyoti Nath⁶, Harun Gitari⁷, Daniel O. Wasonga⁸

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1569-1598, 2024, DOI:10.32604/phyton.2024.052241

Abstract Agriculture plays a crucial role in the economy, and there is an increasing global emphasis on automating agricultural processes. With the tremendous increase in population, the demand for food and employment has also increased significantly. Agricultural methods traditionally used to meet these requirements are no longer adequate, requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers. Integration of technologies such as the Internet of Things, wireless communication, machine learning, artificial intelligence (AI), and deep learning shows promise in addressing these challenges. However, there is a lack of comprehensive documentation… More >

Dongbo Wu^1,#, Shuang Qu^2,#, Lianwen Shen², Shengqun Chen², Xia Jiang^2,3, Ai Rao¹, Yuxue Zhao^2,*, Yueyun Wang^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1455-1466, 2024, DOI:10.32604/phyton.2024.051652

Abstract Cymbidium goeringii is an economically important ornamental plant, and flower color is one of the main features of C. goeringii that contributes to its high economic value. To clarify the molecular mechanisms underlying the role of anthocyanins in mediating differences in color among varieties, liquid chromatography–tandem mass spectrometry was used to perform anthocyanin-targeted metabolomics of seven C. goeringii varieties, including ‘Jin Qian Yuan’ (JQY), ‘Jin Xiu Qian Yuan’ (JXQY), ‘Miao Jiang Su Die’ (MJSD), ‘Qian Ming Su’ (QMS), ‘Shi Chan’ (SC), and ‘Yang Ming Su’ (YMS), as well as the C. goeringii. We detected 64 anthocyanins, including cyanidins, delphinidins,… More >

Ramiro Reyes-Castro¹, Héctor G. Núñez-Palenius^1,*, Juan I. Valiente-Banuet², María E. Sosa-Morales¹, Blanca E. Orosco-Alcalá¹, Rafael Guzmán-Mendoza¹, Graciela M. L. Ruiz-Aguilar¹, Rogelio Costilla-Salazar¹

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1467-1484, 2024, DOI:10.32604/phyton.2024.051644

Abstract Bell pepper (Capsicum annuum L.), along with potato and tomato, is one of the three most cultivated vegetables in the world. Bell pepper is worldwide accepted due to its characteristics of color, smell, flavor, and texture. Bell pepper is also considered a nutritious food due to its vitamin and antioxidant contents. In Mexico, bell pepper production has a high value because it is grown for the international markets, particularly the United States of America. Nevertheless, the abscission of flowers and fruits is a factor that limits the yield, hinders the planning of activities, and causes a More >

Wenjie Dong^1,2,#, Zhibin Hong^1,#, Aqian Wang², Kaiyu Jiang², Hai Zhu², Fu zhang², Zhaoxia Guo², Hongling Su^2,*, Yunshan Cao^3,*

Congenital Heart Disease, Vol.19, No.3, pp. 325-339, 2024, DOI:10.32604/chd.2024.052267

Abstract Background: Current guidelines for managing pulmonary arterial hypertension (PAH) recommend a risk stratification approach. However, the applicability and accuracy of these strategies for PAH associated with congenital heart disease (PAH-CHD) require further validation. This study aims to validate the reliability and predictive accuracy of a simplified stratification strategy for PAH-CHD patients over a three-year follow-up. Additionally, new prognostic variables are identified and novel risk stratification methods are developed for assessing and managing PAH-CHD patients. Methods: This retrospective study included 126 PAH-CHD patients. Clinical and biochemical variables across risk groups were assessed using Kruskal-Wallis and Fisher’s… More > Graphic Abstract

S. F. Ismael^1,2,*, A. H. Alias¹, N. A. Haron¹, B. B. Zaidan³, Abdulrahman M. Abdulghani⁴

Structural Durability & Health Monitoring, Vol.18, No.5, pp. 525-551, 2024, DOI:10.32604/sdhm.2024.050088

Abstract In this review paper, we present a thorough investigation into the role of pavement technologies in advancing urban sustainability. Our analysis traverses the historical evolution of these technologies, meticulously evaluating their socio-economic and environmental impacts, with a particular emphasis on their role in mitigating the urban heat island effect. The evaluation of pavement types and variables influencing pavement performance to be used in the multi-criteria decision-making (MCDM) framework to choose the optimal pavement application are at the heart of our research. Which serves to assess a spectrum of pavement options, revealing insights into the most More >

Nisreen Innab¹, Ahmed Abdelgader Fadol Osman², Mohammed Awad Mohammed Ataelfadiel², Marwan Abu-Zanona^3,*, Bassam Mohammad Elzaghmouri⁴, Farah H. Zawaideh⁵, Mouiad Fadeil Alawneh⁶

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1325-1345, 2024, DOI:10.32604/cmc.2024.051778

Abstract Phishing, an Internet fraud where individuals are deceived into revealing critical personal and account information, poses a significant risk to both consumers and web-based institutions. Data indicates a persistent rise in phishing attacks. Moreover, these fraudulent schemes are progressively becoming more intricate, thereby rendering them more challenging to identify. Hence, it is imperative to utilize sophisticated algorithms to address this issue. Machine learning is a highly effective approach for identifying and uncovering these harmful behaviors. Machine learning (ML) approaches can identify common characteristics in most phishing assaults. In this paper, we propose an ensemble approach… More >

Jinqiao Dai, Pengsen Cheng, Jiayong Liu^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 547-565, 2024, DOI:10.32604/cmc.2024.051745

Abstract Generating diverse and factual text is challenging and is receiving increasing attention. By sampling from the latent space, variational autoencoder-based models have recently enhanced the diversity of generated text. However, existing research predominantly depends on summarization models to offer paragraph-level semantic information for enhancing factual correctness. The challenge lies in effectively generating factual text using sentence-level variational autoencoder-based models. In this paper, a novel model called fact-aware conditional variational autoencoder is proposed to balance the factual correctness and diversity of generated text. Specifically, our model encodes the input sentences and uses them as facts to… More >

Hong Huang, Yunfei Wang^*, Guotao Yuan, Xin Li

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 361-387, 2024, DOI:10.32604/cmc.2024.051633

Abstract Deep Neural Networks (DNNs) are integral to various aspects of modern life, enhancing work efficiency. Nonetheless, their susceptibility to diverse attack methods, including backdoor attacks, raises security concerns. We aim to investigate backdoor attack methods for image categorization tasks, to promote the development of DNN towards higher security. Research on backdoor attacks currently faces significant challenges due to the distinct and abnormal data patterns of malicious samples, and the meticulous data screening by developers, hindering practical attack implementation. To overcome these challenges, this study proposes a Gaussian Noise-Targeted Universal Adversarial Perturbation (GN-TUAP) algorithm. This approach… More >

Mohamed Karray^1,*, Nesrine Triki^2,*, Mohamed Ksantini²

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 119-138, 2024, DOI:10.32604/cmc.2024.051562

Abstract Advanced Driver Assistance Systems (ADAS) technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the road. Traffic Sign Recognition System (TSRS) is one of the most important components of ADAS. Among the challenges with TSRS is being able to recognize road signs with the highest accuracy and the shortest processing time. Accordingly, this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed modules. Firstly, the Speed Limit Detection (SLD) module uses… More >

Saad Abdalla Agaili Mohamed^*, Sefer Kurnaz

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 819-841, 2024, DOI:10.32604/cmc.2024.050474

Abstract VPNs are vital for safeguarding communication routes in the continually changing cybersecurity world. However, increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorize VPN network data. We present a novel VPN network traffic flow classification method utilizing Artificial Neural Networks (ANN). This paper aims to provide a reliable system that can identify a virtual private network (VPN) traffic from intrusion attempts, data exfiltration, and denial-of-service assaults. We compile a broad dataset of labeled VPN traffic flows from various apps and usage patterns. Next, we create an ANN architecture that can… More >