Milos Dobrojevic^1,4, Luka Jovanovic¹, Lepa Babic³, Miroslav Cajic⁵, Tamara Zivkovic⁶, Miodrag Zivkovic², Suresh Muthusamy⁷, Milos Antonijevic², Nebojsa Bacanin^2,4,8,9,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4997-5027, 2024, DOI:10.32604/cmc.2024.054459 - 12 September 2024

Abstract Cyberbullying is a form of harassment or bullying that takes place online or through digital devices like smartphones, computers, or tablets. It can occur through various channels, such as social media, text messages, online forums, or gaming platforms. Cyberbullying involves using technology to intentionally harm, harass, or intimidate others and may take different forms, including exclusion, doxing, impersonation, harassment, and cyberstalking. Unfortunately, due to the rapid growth of malicious internet users, this social phenomenon is becoming more frequent, and there is a huge need to address this issue. Therefore, the main goal of the research… More >

ABHIJEET SURYAWANSHI¹, NIRANJANA BEHERA^2,*

Journal of Polymer Materials, Vol.40, No.3-4, pp. 305-316, 2023, DOI:10.32381/JPM.2023.40.3-4.11

Abstract Resin composites are commonly applied as the material for dental restoration. Wear of these materials is a major issue. In this study specimens made of dental composite materials were subjected to an in-vitro test in a pin-on-disc tribometer. Four different dental composite materials applied in the experiment were soaked in a solution of chewing tobacco for certain days before being removed and put through a wear test. Subsequently, four different machine learning (ML) algorithms (AdaBoost, CatBoost, Gradient Boosting, Random Forest) were implemented for developing models for the prediction of wear of dental materials. AdaBoost, CatBoost, More >

Asma A. Alhashmi¹, Abdulbasit A. Darem^1,*, Sultan M. Alanazi¹, Abdullah M. Alashjaee², Bader Aldughayfiq³, Fuad A. Ghaleb^4,5, Shouki A. Ebad¹, Majed A. Alanazi¹

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3483-3498, 2023, DOI:10.32604/cmc.2023.041038 - 08 October 2023

Abstract In an era marked by escalating cybersecurity threats, our study addresses the challenge of malware variant detection, a significant concern for a multitude of sectors including petroleum and mining organizations. This paper presents an innovative Application Programmable Interface (API)-based hybrid model designed to enhance the detection performance of malware variants. This model integrates eXtreme Gradient Boosting (XGBoost) and an Artificial Neural Network (ANN) classifier, offering a potent response to the sophisticated evasion and obfuscation techniques frequently deployed by malware authors. The model’s design capitalizes on the benefits of both static and dynamic analysis to extract… More >

Shahid Mohammad Ganie¹, Pijush Kanti Dutta Pramanik², Majid Bashir Malik³, Anand Nayyar⁴, Kyung Sup Kwak^5,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3993-4006, 2023, DOI:10.32604/csse.2023.035244 - 03 April 2023

Abstract Cardiovascular disease is among the top five fatal diseases that affect lives worldwide. Therefore, its early prediction and detection are crucial, allowing one to take proper and necessary measures at earlier stages. Machine learning (ML) techniques are used to assist healthcare providers in better diagnosing heart disease. This study employed three boosting algorithms, namely, gradient boost, XGBoost, and AdaBoost, to predict heart disease. The dataset contained heart disease-related clinical features and was sourced from the publicly available UCI ML repository. Exploratory data analysis is performed to find the characteristics of data samples about descriptive and… More >

Saeed Ali Alsareii¹, Muhammad Awais^2,*, Abdulrahman Manaa Alamri¹, Mansour Yousef AlAsmari¹, Muhammad Irfan³, Mohsin Raza², Umer Manzoor⁴

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3715-3728, 2023, DOI:10.32604/csse.2023.035687 - 03 April 2023

Abstract Obesity is a critical health condition that severely affects an individual’s quality of life and well-being. The occurrence of obesity is strongly associated with extreme health conditions, such as cardiac diseases, diabetes, hypertension, and some types of cancer. Therefore, it is vital to avoid obesity and or reverse its occurrence. Incorporating healthy food habits and an active lifestyle can help to prevent obesity. In this regard, artificial intelligence (AI) can play an important role in estimating health conditions and detecting obesity and its types. This study aims to see obesity levels in adults by implementing… More >

P. Shanmuga Prabha^*, S. Magesh Kumar

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3101-3119, 2023, DOI:10.32604/iasc.2023.034885 - 15 March 2023

Abstract Today, securing devices connected to the internet is challenging as security threats are generated through various sources. The protection of cyber-physical systems from external attacks is a primary task. The presented method is planned on the prime motive of detecting cybersecurity attacks and their impacted parameters. The proposed architecture employs the LYSIS dataset and formulates Multi Variant Exploratory Data Analysis (MEDA) through Principle Component Analysis (PCA) and Singular Value Decomposition (SVD) for the extraction of unique parameters. The feature mappings are analyzed with Recurrent 2 Convolutional Neural Network (R2CNN) and Gradient Boost Regression (GBR) to More >

Sumayh S. Aljameel¹, Malak Aljabri^1,2, Nida Aslam¹, Dorieh M. Alomari^3,*, Arwa Alyahya¹, Shaykhah Alfaris¹, Maha Balharith¹, Hiessa Abahussain¹, Dana Boujlea¹, Eman S. Alsulmi⁴

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1291-1304, 2023, DOI:10.32604/cmc.2023.035710 - 06 February 2023

Abstract Currently, the risk factors of pregnancy loss are increasing and are considered a major challenge because they vary between cases. The early prediction of miscarriage can help pregnant ladies to take the needed care and avoid any danger. Therefore, an intelligent automated solution must be developed to predict the risk factors for pregnancy loss at an early stage to assist with accurate and effective diagnosis. Machine learning (ML)-based decision support systems are increasingly used in the healthcare sector and have achieved notable performance and objectiveness in disease prediction and prognosis. Thus, we developed a model… More >

Neenavath Veeraiah^1,*, Youseef Alotaibi², Saleh Alghamdi³, Satish Thatavarti⁴

Computer Systems Science and Engineering, Vol.46, No.1, pp. 637-657, 2023, DOI:10.32604/csse.2023.034224 - 20 January 2023

Abstract Mobile Ad Hoc Network (MANET) is an infrastructure-less network that is comprised of a set of nodes that move randomly. In MANET, the overall performance is improved through multipath multicast routing to achieve the quality of service (quality of service). In this, different nodes are involved in the information data collection and transmission to the destination nodes in the network. The different nodes are combined and presented to achieve energy-efficient data transmission and classification of the nodes. The route identification and routing are established based on the data broadcast by the network nodes. In transmitting… More >

Behnaz Alafchi¹, Leili Tapak^1,*, Hassan Doosti², Christophe Chesneau³, Ghodratollah Roshanaei¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2047-2064, 2023, DOI:10.32604/cmes.2022.022647 - 23 November 2022

Abstract Survival data with a multi-state structure are frequently observed in follow-up studies. An analytic approach based on a multi-state model (MSM) should be used in longitudinal health studies in which a patient experiences a sequence of clinical progression events. One main objective in the MSM framework is variable selection, where attempts are made to identify the risk factors associated with the transition hazard rates or probabilities of disease progression. The usual variable selection methods, including stepwise and penalized methods, do not provide information about the importance of variables. In this context, we present a two-step More >

R. Dhanya^1,*, R. Kalaiselvi²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1577-1593, 2023, DOI:10.32604/csse.2023.031319 - 03 November 2022

Abstract A severe problem in modern information systems is Digital media tampering along with fake information. Even though there is an enhancement in image development, image forgery, either by the photographer or via image manipulations, is also done in parallel. Numerous researches have been concentrated on how to identify such manipulated media or information manually along with automatically; thus conquering the complicated forgery methodologies with effortlessly obtainable technologically enhanced instruments. However, high complexity affects the developed methods. Presently, it is complicated to resolve the issue of the speed-accuracy trade-off. For tackling these challenges, this article put… More >