Abdallah Ghourabi^*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2743-2760, 2024, DOI:10.32604/cmc.2024.053163 - 15 August 2024

Abstract The dominance of Android in the global mobile market and the open development characteristics of this platform have resulted in a significant increase in malware. These malicious applications have become a serious concern to the security of Android systems. To address this problem, researchers have proposed several machine-learning models to detect and classify Android malware based on analyzing features extracted from Android samples. However, most existing studies have focused on the classification task and overlooked the feature selection process, which is crucial to reduce the training time and maintain or improve the classification results. The… More >

DIMITRA P. VAGELI^1,2,*, PANAGIOTIS G. DOUKAS³, KERASIA GOUPOU², ANTONIOS D. BENOS², KYRIAKI ASTARA^2,4, KONSTANTINA ZACHAROULI², SOTIRIS SOTIRIOU⁵, MARIA IOANNOU²

Oncology Research, Vol.32, No.8, pp. 1239-1256, 2024, DOI:10.32604/or.2024.052130 - 17 July 2024

Abstract Glioblastoma multiforme (GBM) is an aggressive primary brain tumor characterized by extensive heterogeneity and vascular proliferation. Hypoxic conditions in the tissue microenvironment are considered a pivotal player leading tumor progression. Specifically, hypoxia is known to activate inducible factors, such as hypoxia-inducible factor 1alpha (HIF-1α), which in turn can stimulate tumor neo-angiogenesis through activation of various downward mediators, such as the vascular endothelial growth factor (VEGF). Here, we aimed to explore the role of HIF-1α/VEGF immunophenotypes alone and in combination with other prognostic markers or clinical and image analysis data, as potential biomarkers of GBM prognosis… More >

ZHAOYING ZHU^1,#, YANJIA HU^2,#, FENG YE², HAIBO TENG², GUOLIANG YOU¹, YUNHUI ZENG², MENG TIAN², JIANGUO XU², JIN LI², ZHIYONG LIU², HAO LIU^2,*, NIANDONG ZHENG^1,*

Oncology Research, Vol.32, No.7, pp. 1173-1184, 2024, DOI:10.32604/or.2024.042456 - 20 June 2024

Abstract Background: Inhibitor of NF-κB kinase-interacting protein (IKIP) is known to promote proliferation of glioblastoma (GBM) cells, but how it affects migration and invasion by those cells is unclear. Methods: We compared levels of IKIP between glioma tissues and normal brain tissue in clinical samples and public databases. We examined the effects of IKIP overexpression and knockdown on the migration and invasion of GBM using transwell and wound healing assays, and we compared the transcriptomes under these different conditions to identify the molecular mechanisms involved. Results: Based on data from our clinical samples and from public databases, More >

Naif Al Mudawi^*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4945-4962, 2024, DOI:10.32604/cmc.2024.048967 - 20 June 2024

Abstract Parkinson’s disease (PD) is a chronic neurological condition that progresses over time. People start to have trouble speaking, writing, walking, or performing other basic skills as dopamine-generating neurons in some brain regions are injured or die. The patient’s symptoms become more severe due to the worsening of their signs over time. In this study, we applied state-of-the-art machine learning algorithms to diagnose Parkinson’s disease and identify related risk factors. The research worked on the publicly available dataset on PD, and the dataset consists of a set of significant characteristics of PD. We aim to apply… More >

Kai Wang¹, Biao He^2,*, Pijush Samui³, Jian Zhou⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 229-253, 2024, DOI:10.32604/cmes.2024.047569 - 16 April 2024

Abstract Rock bursts represent a formidable challenge in underground engineering, posing substantial risks to both infrastructure and human safety. These sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock, leading to severe seismic events and structural damage. Therefore, the development of reliable prediction models for rock bursts is paramount to mitigating these hazards. This study aims to propose a tree-based model—a Light Gradient Boosting Machine (LightGBM)—to predict the intensity of rock bursts in underground engineering. 322 actual rock burst cases are collected to constitute an exhaustive… More >

LEI ZHANG^*, YUAN ZHANG, HUIJUAN GAO, XIN LI, PEIFENG LI^*

Oncology Research, Vol.31, No.4, pp. 449-462, 2023, DOI:10.32604/or.2023.029062 - 25 June 2023

Abstract Glioblastoma (GBM) is the most malignant form of glioma and is difficult to diagnose, leading to high mortality rates. Circular RNAs (circRNAs) are noncoding RNAs with a covalently closed loop structure. CircRNAs are involved in various pathological processes and have been revealed to be important regulators of GBM pathogenesis. CircRNAs exert their biological effects by 4 different mechanisms: serving as sponges of microRNAs (miRNAs), serving as sponges of RNA binding proteins (RBPs), modulating parental gene transcription, and encoding functional proteins. Among the 4 mechanisms, sponging miRNAs is predominant. Their good stability, broad distribution and high More > Graphic Abstract

Turke Althobaiti^1,2, Yousef Sanjalawe^3,*, Naeem Ramzan⁴

Computer Systems Science and Engineering, Vol.47, No.1, pp. 453-469, 2023, DOI:10.32604/csse.2023.039207 - 26 May 2023

Abstract Flash Crowd attacks are a form of Distributed Denial of Service (DDoS) attack that is becoming increasingly difficult to detect due to its ability to imitate normal user behavior in Cloud Computing (CC). Botnets are often used by attackers to perform a wide range of DDoS attacks. With advancements in technology, bots are now able to simulate DDoS attacks as flash crowd events, making them difficult to detect. When it comes to application layer DDoS attacks, the Flash Crowd attack that occurs during a Flash Event is viewed as the most intricate issue. This is… More >

Sesikala Bapatla¹, J. Harikiran^2,*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 597-617, 2023, DOI:10.32604/csse.2023.034998 - 20 January 2023

Abstract Diabetes problems can lead to an eye disease called Diabetic Retinopathy (DR), which permanently damages the blood vessels in the retina. If not treated early, DR becomes a significant reason for blindness. To identify the DR and determine the stages, medical tests are very labor-intensive, expensive, and time-consuming. To address the issue, a hybrid deep and machine learning technique-based autonomous diagnostic system is provided in this paper. Our proposal is based on lesion segmentation of the fundus images based on the LuNet network. Then a Refined Attention Pyramid Network (RAPNet) is used for extracting global… More >

Abdulaziz Almazyad, Laila Halman, Alaa Alsaeed^*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4769-4784, 2023, DOI:10.32604/cmc.2023.033382 - 28 December 2022

Abstract The novel Software Defined Networking (SDN) architecture potentially resolves specific challenges arising from rapid internet growth of and the static nature of conventional networks to manage organizational business requirements with distinctive features. Nevertheless, such benefits lead to a more adverse environment entailing network breakdown, systems paralysis, and online banking fraudulence and robbery. As one of the most common and dangerous threats in SDN, probe attack occurs when the attacker scans SDN devices to collect the necessary knowledge on system susceptibilities, which is then manipulated to undermine the entire system. Precision, high performance, and real-time systems… More >

S. Priya^1,*, N. K. Karthikeyan¹, D. Palanikkumar²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2673-2685, 2023, DOI:10.32604/iasc.2023.028599 - 17 August 2022

Abstract In recent years, cervical cancer is one of the most common diseases which occur in any woman regardless of any age. This is the deadliest disease since there were no symptoms shown till it is diagnosed to be the last stage. For women at a certain age, it is better to have a proper screening for cervical cancer. In most underdeveloped nations, it is very difficult to have frequent scanning for cervical cancer. Data Mining and machine learning methodologies help widely in finding the important causes for cervical cancer. The proposed work describes a multi-class More >