Arshad Mehmmod^1,#, Komal Batool^1,#, Ahthsham Sajid^2,3, Muhammad Mansoor Alam^2,3, Mazliham MohD Su’ud^3,*, Inam Ullah Khan³

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5155-5179, 2025, DOI:10.32604/cmc.2025.062971 - 19 May 2025

Abstract Traditional rule-based Intrusion Detection Systems (IDS) are commonly employed owing to their simple design and ability to detect known threats. Nevertheless, as dynamic network traffic and a new degree of threats exist in IoT environments, these systems do not perform well and have elevated false positive rates—consequently decreasing detection accuracy. In this study, we try to overcome these restrictions by employing fuzzy logic and machine learning to develop an Enhanced Rule-Based Model (ERBM) to classify the packets better and identify intrusions. The ERBM developed for this approach improves data preprocessing and feature selections by utilizing… More >

Debiao Meng^1,2,3, Shiyuan Yang¹, Tao Lin^4,5,*, Jiapeng Wang¹, Hengfei Yang¹, Zhiyuan Lv¹

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 553-568, 2022, DOI:10.32604/cmes.2022.020756 - 15 June 2022

Abstract Actual engineering systems will be inevitably affected by uncertain factors. Thus, the Reliability-Based Multidisciplinary Design Optimization (RBMDO) has become a hotspot for recent research and application in complex engineering system design. The Second-Order/First-Order Mean-Value Saddlepoint Approximate (SOMVSA/FOMVSA) are two popular reliability analysis strategies that are widely used in RBMDO. However, the SOMVSA method can only be used efficiently when the distribution of input variables is Gaussian distribution, which significantly limits its application. In this study, the Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation (GMM-SOMVSA) is introduced to tackle above problem. It is integrated with the More >

S. Rajasekaran^1,*, G. Kousalya²

Computer Systems Science and Engineering, Vol.42, No.3, pp. 985-1000, 2022, DOI:10.32604/csse.2022.022234 - 08 February 2022

Abstract The demand for better health services has resulted in the advancement of remote monitoring health, i.e., virtual nursing systems, to watch and support the elderly with innovative concepts such as being patient-centric, easier to use, and having smarter interactions and more accurate conclusions. While virtual nursing services attempt to provide consumers and medical practitioners with continuous medical and health monitoring services, access to allied healthcare experts such as nurses remains a challenge. In this research, we present Virtual Nursing Using Deep Belief Networks for Elderly People (DBN-EP), a new framework that provides a virtual nurse… More >

LI JIANG^1,*, KE ZHANG¹, CHONG HU¹, HONGWEI ZHANG¹, DANPU WANG¹, WEIWEI ZHAI²

BIOCELL, Vol.46, No.4, pp. 969-978, 2022, DOI:10.32604/biocell.2022.017765 - 15 December 2021

Abstract In recent decades, RNA binding motif (RBM) proteins have been widespread concerned by researchers. Among them, RBM5 is considered as a potential tumor suppressor gene in HCC. RBM10, also belonging to the RBM family, have similar structure and high homology with RBM5, indicating its potential as potential tumor suppressor genes. However, the role of RBM10 in tumors is controversial. The purpose of this study was to analyze the expression correlation and functional relationship of miR-21 and RBM10 in human hepatocellular carcinoma (HCC) tissues and corresponding tumor cells. Bioinformatics analysis showed that miR-21 and RBM10 were… More >

Xuan Chen^1,*, Zhiping Wan¹, Jiatong Wang²

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1531-1548, 2020, DOI:10.32604/iasc.2020.011723 - 24 December 2020

Abstract Addressing the shortcomings of unmanned path planning, such as significant error and low precision, a path-planning algorithm based on the whale optimization algorithm (WOA)-optimized double-blinking restricted Boltzmann machine-back propagation (RBM-BP) deep neural network model is proposed. The model consists mainly of two twin RBMs and one BP neural network. One twin RBM is used for feature extraction of the unmanned path location, and the other RBM is used for the path similarity calculation. The model uses the WOA algorithm to optimize parameters, which reduces the number of training sessions, shortens the training time, and reduces… More >

Yuan Yang^*, Lingli Quan^†, Ye Ling^*

Oncology Research, Vol.26, No.1, pp. 9-15, 2018, DOI:10.3727/096504017X14871200709504

Abstract RBMS3, a gene encoding a glycine-rich RNA-binding protein, belongs to the family of c-Myc gene singlestrand binding proteins (MSSP). Recently, several reports have provided evidence that RBMS3 was deregulated in a diverse range of solid tumors and played a critical role in tumor progression. However, it remains unclear whether RBMS3 inhibits the progression of human breast cancer. Thus, the aim of this study was to investigate the role of RBMS3 in breast cancer and explore the underlying mechanism in breast cancer progression. Our results showed, for the first time, that the expression of RBMS3 at… More >