G. Geetha^1,2,*, K. Mohana Prasad¹

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 703-718, 2023, DOI:10.32604/iasc.2023.032530 - 29 September 2022

Abstract Diabetes mellitus is a metabolic disease in which blood glucose levels rise as a result of pancreatic insulin production failure. It causes hyperglycemia and chronic multiorgan dysfunction, including blindness, renal failure, and cardiovascular disease, if left untreated. One of the essential checks that are needed to be performed frequently in Type 1 Diabetes Mellitus is a blood test, this procedure involves extracting blood quite frequently, which leads to subject discomfort increasing the possibility of infection when the procedure is often recurring. Existing methods used for diabetes classification have less classification accuracy and suffer from vanishing… More >

Amel Ksibi¹, Amina Salhi¹, Ala Saleh Alluhaidan^1,*, Sahar A. El-Rahman²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2073-2096, 2023, DOI:10.32604/cmc.2023.032566 - 22 September 2022

Abstract The quality of the air we breathe during the courses of our daily lives has a significant impact on our health and well-being as individuals. Unfortunately, personal air quality measurement remains challenging. In this study, we investigate the use of first-person photos for the prediction of air quality. The main idea is to harness the power of a generalized stacking approach and the importance of haze features extracted from first-person images to create an efficient new stacking model called AirStackNet for air pollution prediction. AirStackNet consists of two layers and four regression models, where the… More >

D. Karthikeyan^1,*, V. Mohan Raj², J. Senthilkumar², Y. Suresh²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 645-659, 2023, DOI:10.32604/iasc.2023.027039 - 06 June 2022

Abstract The number of attacks is growing tremendously in tandem with the growth of internet technologies. As a result, protecting the private data from prying eyes has become a critical and tough undertaking. Many intrusion detection solutions have been offered by researchers in order to decrease the effect of these attacks. For attack detection, the prior system has created an SMSRPF (Stacking Model Significant Rule Power Factor) classifier. To provide creative instance detection, the SMSRPF combines the detection of trained classifiers such as DT (Decision Tree) and RF (Random Forest). Nevertheless, it does not generate any… More >

Zeyong Sun¹, Guo Ran², Zilong Jin^1,3,*

Journal on Internet of Things, Vol.4, No.2, pp. 99-111, 2022, DOI:10.32604/jiot.2022.037416 - 28 March 2023

Abstract Intrusion detection is a hot field in the direction of network security. Classical intrusion detection systems are usually based on supervised machine learning models. These offline-trained models usually have better performance in the initial stages of system construction. However, due to the diversity and rapid development of intrusion techniques, the trained models are often difficult to detect new attacks. In addition, very little noisy data in the training process often has a considerable impact on the performance of the intrusion detection system. This paper proposes an intrusion detection system based on active incremental learning with… More >

Zeyad Ghaleb Al-Mekhlafi¹, Badiea Abdulkarem Mohammed^1,2,*, Mohammed Al-Sarem³, Faisal Saeed³, Tawfik Al-Hadhrami⁴, Mohammad T. Alshammari¹, Abdulrahman Alreshidi¹, Talal Sarheed Alshammari¹

Computer Systems Science and Engineering, Vol.41, No.1, pp. 109-125, 2022, DOI:10.32604/csse.2022.020414 - 08 October 2021

Abstract Phishing attacks are security attacks that do not affect only individuals’ or organizations’ websites but may affect Internet of Things (IoT) devices and networks. IoT environment is an exposed environment for such attacks. Attackers may use thingbots software for the dispersal of hidden junk emails that are not noticed by users. Machine and deep learning and other methods were used to design detection methods for these attacks. However, there is still a need to enhance detection accuracy. Optimization of an ensemble classification method for phishing website (PW) detection is proposed in this study. A Genetic More >

Kunkun Wang^1,2, Xianda Liu^2,3,4,*

Journal on Artificial Intelligence, Vol.3, No.1, pp. 9-19, 2021, DOI:10.32604/jai.2021.016706 - 02 April 2021

Abstract With the development of Internet technology, the computing power of data has increased, and the development of machine learning has become faster and faster. In the industrial production of industrial control systems, quality inspection and safety production of process products have always been our concern. Aiming at the low accuracy of anomaly detection in process data in industrial control system, this paper proposes an anomaly detection method based on stacking integration using the machine learning algorithm. Data are collected from the industrial site and processed by feature engineering. Principal component analysis (PCA) and integrated rule… More >

Ali M. Aseere^1,*, Ayodele Lasisi²

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 683-699, 2021, DOI:10.32604/iasc.2021.014811 - 01 March 2021

Abstract In the absence of fast and adequate measures to combat them, life-threatening diseases are catastrophic to human health. Computational intelligent algorithms characterized by their adaptability, robustness, diversity, and recognition abilities allow for the diagnosis of medical diseases. This enhances the decision-making process of physicians. The objective is to predict and classify diseases accurately. In this paper, we proposed a multi-agent stacked ensemble classifier based on a vaguely quantified rough set, simple logistic algorithm, sequential minimal optimization (SMO), and JRip. The vaguely quantified rough set (VQRS) is used for feature selection and eradicating noise in the More >

Tabrej Khan¹, Mohamed Thariq Hameed Sultan^1,2,3,*, Mohammad Jawaid², Syafiqah Nur Azrie Safri², Ain Umaira Md Shah², Mohd Shukry Abdul Majid^4,5,*, Nik Noriman Zulkepli⁶, Haliza Jaya⁶

Journal of Renewable Materials, Vol.9, No.1, pp. 73-84, 2021, DOI:10.32604/jrm.2021.011385 - 30 November 2020

Abstract This research focused on the dynamic mechanical and thermal properties of woven mat jute/kenaf/jute (J/K/J) and kenaf/jute/kenaf (K/J/K) hybrid composites. Dynamic mechanical analysis (DMA) and Thermo-gravimetric Analysis (TGA) were used to study the effect of layering sequence on the thermal properties of kenaf/jute hybrid composites. The DMA results; it was found that the differences in the stacking sequence between the kenaf/jute composites do not affect their storage modulus, loss modulus and damping factor. From the TGA and DMA results, it has been shown that stacking sequence has given positive effect to the kenaf/jute hybrid composite… More >

Lewis Nkenyereye¹, Bayu Adhi Tama², Sunghoon Lim^3,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2217-2227, 2021, DOI:10.32604/cmc.2020.012432 - 26 November 2020

Abstract An anomaly-based intrusion detection system (A-IDS) provides a critical aspect in a modern computing infrastructure since new types of attacks can be discovered. It prevalently utilizes several machine learning algorithms (ML) for detecting and classifying network traffic. To date, lots of algorithms have been proposed to improve the detection performance of A-IDS, either using individual or ensemble learners. In particular, ensemble learners have shown remarkable performance over individual learners in many applications, including in cybersecurity domain. However, most existing works still suffer from unsatisfactory results due to improper ensemble design. The aim of this study More >

Lianping Wu, Wenshan Yu*, Shuling Hu, Shengping Shen*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.1, pp. 101-101, 2019, DOI:10.32604/icces.2019.05016

Abstract Multiple collision cascades (MCC) of nanotwinned (nt) Cu with three different twin spacings are performed to model the response of nt Cu upon a radiation dose of 1 displacement per atom (dpa). The microstructural evolutions during the radiation process shows that the main radiation defect in Cu is stacking fault tetrahedron (SFT). Smaller size of defect clusters and lower defect density are seen in the nt Cu with smaller twin spacing. Besides, the potential formation and elimination mechanisms of SF are found to be due to the climb of Frank partial dislocation and glide of… More >