Nazik Alturki¹, Abdulaziz Altamimi², Muhammad Umer^3,*, Oumaima Saidani¹, Amal Alshardan¹, Shtwai Alsubai⁴, Marwan Omar⁵, Imran Ashraf^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3513-3534, 2024, DOI:10.32604/cmes.2023.045868 - 11 March 2024

Abstract Chronic kidney disease (CKD) is a major health concern today, requiring early and accurate diagnosis. Machine learning has emerged as a powerful tool for disease detection, and medical professionals are increasingly using ML classifier algorithms to identify CKD early. This study explores the application of advanced machine learning techniques on a CKD dataset obtained from the University of California, UC Irvine Machine Learning repository. The research introduces TrioNet, an ensemble model combining extreme gradient boosting, random forest, and extra tree classifier, which excels in providing highly accurate predictions for CKD. Furthermore, K nearest neighbor (KNN) More >

Xin Fan^1,2, Shuqing Zhang^1,2,*, Kaisheng Wu^1,2, Wei Zheng^1,2, Yu Ge^1,2

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1687-1711, 2024, DOI:10.32604/cmc.2023.046187 - 27 February 2024

Abstract Cross-Project Defect Prediction (CPDP) is a method that utilizes historical data from other source projects to train predictive models for defect prediction in the target project. However, existing CPDP methods only consider linear correlations between features (indicators) of the source and target projects. These models are not capable of evaluating non-linear correlations between features when they exist, for example, when there are differences in data distributions between the source and target projects. As a result, the performance of such CPDP models is compromised. In this paper, this paper proposes a novel CPDP method based on… More >

Mingzhao Han¹, Susilawati Kasim^1,*, Zhongming Yang², Xi Deng², Md Kamal Uddin¹, Noor Baity Saidi³, Effyanti Mohd Shuib¹

Phyton-International Journal of Experimental Botany, Vol.93, No.2, pp. 213-226, 2024, DOI:10.32604/phyton.2024.047150 - 27 February 2024

Abstract Drought stress is a major factor affecting plant growth and crop yield production. Plant extracts as natural biostimulants hold great potential to strengthen plants to overcome drought impacts. To explore the effect of Polygonum minus extract (PME) in enhancing drought tolerance in plants, a study was set up in a glasshouse environment using 10 different treatment combinations. PME foliar application were designed in CRD and effects were closely observed related to the growth, physiology, and antioxidant system changes in maize (Zea mays L.) under well-watered and drought conditions. The seaweed extract (SWE) was used as a comparison.… More >

Congjun Rao¹, Mengxi Li¹, Tingting Huang^2,*, Feiyu Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 699-724, 2024, DOI:10.32604/cmes.2023.044898 - 30 December 2023

Abstract Stroke is a chronic cerebrovascular disease that carries a high risk. Stroke risk assessment is of great significance in preventing, reversing and reducing the spread and the health hazards caused by stroke. Aiming to objectively predict and identify strokes, this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost (Logistic-AB) based on machine learning. First, the categorical boosting (CatBoost) method is used to perform feature selection for all features of stroke, and 8 main features are selected to form a new index evaluation system to predict the risk of stroke. Second, the borderline… More >

Dongmei Huang¹, Dang Hong², Wei Li^1,*, Guidong Yang¹, Vesna Rajic³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 509-524, 2024, DOI:10.32604/cmes.2023.029215 - 22 September 2023

Abstract In this paper, the bifurcation properties of the vibro-impact systems with an uncertain parameter under the impulse and harmonic excitations are investigated. Firstly, by means of the orthogonal polynomial approximation (OPA) method, the nonlinear damping and stiffness are expanded into the linear combination of the state variable. The condition for the appearance of the vibro-impact phenomenon is to be transformed based on the calculation of the mean value. Afterwards, the stochastic vibro-impact system can be turned into an equivalent high-dimensional deterministic non-smooth system. Two different Poincaré sections are chosen to analyze the bifurcation properties and… More >

Linlin Fang, Jiamei Xu, Chunxue Yang^*

Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3195-3209, 2023, DOI:10.32604/phyton.2023.043049 - 28 December 2023

Abstract Syneilesis aconitifolia is a potential ground cover and decorative material in gardens, which exhibits a strong salt-alkali tolerance, and also has medicinal value. In this study, the arbuscular mycorrhizal (AM) fungi community in the soil surrounding S. aconitifolia roots in the Songnen saline-alkali grassland was used as the inoculation medium for a pot cultivation experiment. After normal culture for 90 days, NaCl and NaHCO₃ solutions were applied to subject plants to salt or alkali stress. Solution concentrations of 50, 100, and 200 mmol/L were applied for 10 days, and mycorrhizal colonization, biomass, relative water content (RWC), chlorophyll concentration,… More >

CHENYANG CHEN^1,*, JUAN WEN¹, WEI HUANG¹, JIANG LI^2,*

BIOCELL, Vol.47, No.11, pp. 2423-2433, 2023, DOI:10.32604/biocell.2023.044459 - 27 November 2023

Abstract Background: Pulmonary arterial hypertension (PAH) is a chronic and progressive disease that is strongly associated with dysregulation of glucose metabolism. Alterations in nuclear receptor subfamily 4 group A member 1 (NR4A1) activity alter the outcome of PAH. This study aimed to investigate the effects of NR4A1 on glycolysis in PAH and its underlying mechanisms. Methods: This study included twenty healthy volunteers and twenty-three PAH patients, and plasma samples were collected from the participants. To mimic the conditions of PAH in vitro, a hypoxia-induced model of pulmonary artery smooth muscle cell (PASMC) model was established. The proliferation… More > Graphic Abstract

Dana F. Doghramachi^1,*, Siddeeq Y. Ameen²

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 717-732, 2023, DOI:10.32604/cmc.2023.041186 - 31 October 2023

Abstract The rapid adoption of the Internet of Things (IoT) across industries has revolutionized daily life by providing essential services and leisure activities. However, the inadequate software protection in IoT devices exposes them to cyberattacks with severe consequences. Intrusion Detection Systems (IDS) are vital in mitigating these risks by detecting abnormal network behavior and monitoring safe network traffic. The security research community has shown particular interest in leveraging Machine Learning (ML) approaches to develop practical IDS applications for general cyber networks and IoT environments. However, most available datasets related to Industrial IoT suffer from imbalanced class… More >

Ali Khan^1,4, Somaiya Khan², Bilal Hassan³, Rizwan Khan^1,4, Zhonglong Zheng^1,4,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 403-424, 2023, DOI:10.32604/cmc.2023.040251 - 31 October 2023

Abstract Smoking has an economic and environmental impact on society due to the toxic substances it emits. Convolutional Neural Networks (CNNs) need help describing low-level features and can miss important information. Moreover, accurate smoker detection is vital with minimum false alarms. To answer the issue, the researchers of this paper have turned to a self-attention mechanism inspired by the ViT, which has displayed state-of-the-art performance in the classification task. To effectively enforce the smoking prohibition in non-smoking locations, this work presents a Vision Transformer-inspired model called SmokerViT for detecting smokers. Moreover, this research utilizes a locally… More >

Rufus Gikera^1,*, Jonathan Mwaura², Elizaphan Muuro³, Shadrack Mambo³

Journal on Artificial Intelligence, Vol.5, pp. 75-112, 2023, DOI:10.32604/jai.2023.043229 - 26 October 2023

Abstract k-means is a popular clustering algorithm because of its simplicity and scalability to handle large datasets. However, one of its setbacks is the challenge of identifying the correct k-hyperparameter value. Tuning this value correctly is critical for building effective k-means models. The use of the traditional elbow method to help identify this value has a long-standing literature. However, when using this method with certain datasets, smooth curves may appear, making it challenging to identify the k-value due to its unclear nature. On the other hand, various internal validation indexes, which are proposed as a solution to this… More >