Pierre-Frédéric Villard^1,*, Maureen Boudart², Ioana Ilea³, Fabien Pierre¹

FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.6, pp. 1639-1648, 2022, DOI:10.32604/fdmp.2022.021726 - 27 June 2022

Abstract Industrial woven meshes are composed of metal materials and are often used in construction, industrial and residential activities or applications. The objective of this work is defect detection in industrial fabrics in the quality control stage. In order to overcome the limitations of manual methods, which are often tedious and time-consuming, we propose a strategy that can automatically detect defects in micrometric steel meshes by means of a Convolutional Neural Network. The database used for such a purpose comes from real problem data for anomaly detection in micrometric woven meshes. This detection is performed through More >

Ming Wan¹, Quanliang Li¹, Jiangyuan Yao^2,*, Yan Song³, Yang Liu⁴, Yuxin Wan⁵

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4033-4049, 2022, DOI:10.32604/cmc.2022.030895 - 16 June 2022

Abstract Anomaly detection is becoming increasingly significant in industrial cyber security, and different machine-learning algorithms have been generally acknowledged as various effective intrusion detection engines to successfully identify cyber attacks. However, different machine-learning algorithms may exhibit their own detection effects even if they analyze the same feature samples. As a sequence, after developing one feature generation approach, the most effective and applicable detection engines should be desperately selected by comparing distinct properties of each machine-learning algorithm. Based on process control features generated by directed function transition diagrams, this paper introduces five different machine-learning algorithms as alternative… More >

Murtaza Ahmed Siddiqi, Wooguil Pak^*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3921-3949, 2022, DOI:10.32604/cmc.2022.029541 - 16 June 2022

Abstract The network infrastructure has evolved rapidly due to the ever-increasing volume of users and data. The massive number of online devices and users has forced the network to transform and facilitate the operational necessities of consumers. Among these necessities, network security is of prime significance. Network intrusion detection systems (NIDS) are among the most suitable approaches to detect anomalies and assaults on a network. However, keeping up with the network security requirements is quite challenging due to the constant mutation in attack patterns by the intruders. This paper presents an effective and prevalent framework for More >

GIUSEPPE STEFANO NETTI^1,*, FEDERICA SPADACCINO¹, VALERIA CATALANO¹, GIUSEPPE CASTELLANO², GIOVANNI STALLONE³, ELENA RANIERI¹

BIOCELL, Vol.46, No.10, pp. 2235-2239, 2022, DOI:10.32604/biocell.2022.020209 - 13 June 2022

Abstract Pentraxin-3 (PTX3), the prototype of long pentraxins, seems to influence complement system (CS) modulation. PTX3 and CS sustain carcinogenesis, enriching tumor microenvironment (TME) with pro-inflammatory molecules promoting angiogenesis in prostate cancer (PC) and renal cell carcinoma (RCC). Furthermore, cancer cells overexpress complement regulatory proteins, such as CD46, CD55 and CD59, which negatively affect complement pathways for support cancer cells survival. This viewpoint aims to elucidate the ambivalent role of PTX3 and the CS in the context of tumor microenvironment (TME). More >

FEIFEI TIAN¹, HUAN HU¹, DI WANG¹, HUAN DING¹, QINGJIA CHI², HUAPING LIANG³, WENLI ZENG^4,*

BIOCELL, Vol.46, No.10, pp. 2291-2301, 2022, DOI:10.32604/biocell.2022.020198 - 13 June 2022

Abstract This study used transcriptome and epigenetic data to predict the prognosis of immune-related genes (IRGs) Apelin (APLN) in patients with hepatocellular carcinoma (HCC). The TCGA database has gene expression and clinical data for HCC. And DNA methylation 450 k data for HCC was download from the University of California Santa Cruz (UCSC) Xena browser. Performing clinical and prognostic analysis of APLN expression, results show that APLN is highly expressed in tumor samples. And it has an increasing trend with the development of clinical stage and T stage. To explore the prognostic role of APLN, the… More >

HUILI ZHU¹, LINA XIAO¹, XIA YIN¹, SHIBING XIANG¹, CHUNHUI WANG^2,*

BIOCELL, Vol.46, No.10, pp. 2241-2256, 2022, DOI:10.32604/biocell.2022.020389 - 13 June 2022

Abstract Pancreatic ductal adenocarcinoma (PDAC) is highly heterogeneous, making its prognosis prediction difficult. The arachidonic acid (AA) cascade is involved in carcinogenesis. Therefore, the metabolic enzymes of the AA cascade consist of lipoxygenases (LOXs), phospholipase A2s (PLA2s), and cyclooxygenases (COXs) along with their metabolic products, including leukotrienes. Nevertheless, the prognostic potential of AA metabolism-associated PDAC has not been explored. Herein, the mRNA expression patterns and the matching clinical information of individuals with PDAC were abstracted from online data resources. We employed the LASSO Cox regression model to develop a multigene clinical signature in the TCGA queue.… More >

Jiaqi Wang¹, Jie Zhang², Genlin Ji^2,*, Bo Sheng³

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1629-1642, 2022, DOI:10.32604/iasc.2022.029535 - 25 May 2022

Abstract The surveillance applications generate enormous video data and present challenges to video analysis for huge human labor cost. Reconstruction-based convolutional autoencoders have achieved great success in video anomaly detection for their ability of automatically detecting abnormal event. The approaches learn normal patterns only with the normal data in an unsupervised way due to the difficulty of collecting anomaly samples and obtaining anomaly annotations. But convolutional autoencoders have limitations in global feature extraction for the local receptive field of convolutional kernels. What is more, 2-dimensional convolution lacks the capability of capturing temporal information while videos change… More >

K. Muthulakshmi^1,*, N. Krishnaraj², R. S. Ravi Sankar³, A. Balakumar⁴, S. Kanimozhi⁵, B. Kiruthika⁶

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 2083-2096, 2022, DOI:10.32604/iasc.2022.026628 - 25 May 2022

Abstract In recent times, Cyber-physical system (CPS) integrates the cyber systems and physical world for performing critical processes that are started from the development in digital electronics. The sensors deployed in CPS are commonly employed for monitoring and controlling processes that are susceptible to anomalies. For identifying and detecting anomalies, an effective anomaly detection system (ADS) is developed. But ADS faces high false alarms and miss detection rate, which led to the degraded performance in CPS applications. This study develops a novel deep learning (DL) approach for anomaly detection in sensor-based CPS using Bidirectional Long Short… More >

Rajneesh Pareek¹, Karthikeyan Rajagopal², Himanshu Sharma¹, Nidhi Gour¹, Arun Kumar³, Sami Althahabi⁴, Haya Mesfer Alshahrani⁵, Mohamed Mousa⁶, Manar Ahmed Hamza^7,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1637-1648, 2022, DOI:10.32604/cmc.2022.029563 - 18 May 2022

Abstract Multi and single carrier waveforms are utilized in cellular systems for high-speed data transmission. In The Fifth Generation (5G) system, several waveform techniques based on multi carrier waveforms are proposed. However, the Peak to Average Power Ratio (PAPR) is seen as one of the significant concerns in advanced waveforms as it degrades the efficiency of the framework. The proposed article documents the study, progress, and implementation of PAPR reduction algorithms for the 5G radio framework. We compare the PAPR algorithm performance for advanced and conventional waveforms. The simulation results reveal that the advanced Partial Transmission More >

Tahani Alatawi^*, Ahamed Aljuhani

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1067-1086, 2022, DOI:10.32604/cmc.2022.029283 - 18 May 2022

Abstract The rapid development of the Internet of Things (IoT) in the industrial domain has led to the new term the Industrial Internet of Things (IIoT). The IIoT includes several devices, applications, and services that connect the physical and virtual space in order to provide smart, cost-effective, and scalable systems. Although the IIoT has been deployed and integrated into a wide range of industrial control systems, preserving security and privacy of such a technology remains a big challenge. An anomaly-based Intrusion Detection System (IDS) can be an effective security solution for maintaining the confidentiality, integrity, and… More >