HENG LI^1,#, YOUMING LEI^3,#, GAOFENG LI¹, YUNCHAO HUANG^2,*

Oncology Research, Vol.32, No.1, pp. 187-197, 2024, DOI:10.32604/or.2023.030656 - 15 November 2023

Abstract Lung cancer is a prevalent malignancy, and fatalities of the disease exceed 400,000 cases worldwide. Lung squamous cell carcinoma (LUSC) has been recognized as the most common pathological form of lung cancer. The comprehensive understanding of molecular features related to LUSC progression has great significance in LUSC prognosis assessment and clinical management. In this study, we aim to identify a panel of signature genes closely associated with LUSC, which can provide novel insights into the progression of LUSC. Gene expression profiles were retrieved from public resources including gene expression omnibus (GEO) and the cancer genome… More >

Baixuan Tang^1,2,#, Xiaolong Xu^1,2,#, Fei Dai³, Song Wang^4,*

Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 35-55, 2023, DOI:10.32604/iasc.2023.036715 - 26 January 2024

Abstract Person re-identification (ReID) aims to recognize the same person in multiple images from different camera views. Training person ReID models are time-consuming and resource-intensive; thus, cloud computing is an appropriate model training solution. However, the required massive personal data for training contain private information with a significant risk of data leakage in cloud environments, leading to significant communication overheads. This paper proposes a federated person ReID method with model-contrastive learning (MOON) in an edge-cloud environment, named FRM. Specifically, based on federated partial averaging, MOON warmup is added to correct the local training of individual edge… More >

Xiaoyang Shen¹, Xiaojing Zhang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.28, No.1, pp. 1-3, 2023, DOI:10.32604/icces.2023.010519

Abstract 1 General Introduction
Reliable structural health monitoring with high detection probability is very important [1]. Therefore, the method of finite element simulation was adopted. Based on the basic equation of material mechanics and stiffness degradation theory, to detect the damage of composite laminates, and further improves the intelligence of the detection process through the method of visual detection neural network.

2 Theoretical derivation and simulation
2.1 Equations for buckling
In the stratified damage area, each layer bears the load independently, and the bearing capacity is determined by the stiffness there: the larger the axial stiffness, the stronger the bearing… More >

Zheng Shi, Wanru Song^*, Junhao Shan, Feng Liu

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3467-3488, 2023, DOI:10.32604/cmc.2023.045849 - 26 December 2023

Abstract Visible-infrared Cross-modality Person Re-identification (VI-ReID) is a critical technology in smart public facilities such as cities, campuses and libraries. It aims to match pedestrians in visible light and infrared images for video surveillance, which poses a challenge in exploring cross-modal shared information accurately and efficiently. Therefore, multi-granularity feature learning methods have been applied in VI-ReID to extract potential multi-granularity semantic information related to pedestrian body structure attributes. However, existing research mainly uses traditional dual-stream fusion networks and overlooks the core of cross-modal learning networks, the fusion module. This paper introduces a novel network called the… More >

Manjur Kolhar^*, Sultan Mesfer Aldossary

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2857-2879, 2023, DOI:10.32604/cmc.2023.042726 - 26 December 2023

Abstract In many commercial and public sectors, the Internet of Things (IoT) is deeply embedded. Cyber security threats aimed at compromising the security, reliability, or accessibility of data are a serious concern for the IoT. Due to the collection of data from several IoT devices, the IoT presents unique challenges for detecting anomalous behavior. It is the responsibility of an Intrusion Detection System (IDS) to ensure the security of a network by reporting any suspicious activity. By identifying failed and successful attacks, IDS provides a more comprehensive security capability. A reliable and efficient anomaly detection system… More >

KUAILU LIN^1,2, QIANYU GU², XIXI LAI^2,3,*

BIOCELL, Vol.47, No.12, pp. 2681-2696, 2023, DOI:10.32604/biocell.2023.043298 - 27 December 2023

Abstract Objectives: Triple-negative breast cancer (TNBC) poses a significant challenge due to the lack of reliable prognostic gene signatures and an understanding of its immune behavior. Methods: We analyzed clinical information and mRNA expression data from 162 TNBC patients in TCGA-BRCA and 320 patients in METABRIC-BRCA. Utilizing weighted gene coexpression network analysis, we pinpointed 34 TNBC immune genes linked to survival. The least absolute shrinkage and selection operator Cox regression method identified key TNBC immune candidates for prognosis prediction. We calculated chemotherapy sensitivity scores using the “pRRophetic” package in R software and assessed immunotherapy response using the… More >

Xiaoqi Xin^*, Dezhi Han, Mingming Cui

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2407-2425, 2023, DOI:10.32604/cmc.2023.042308 - 29 November 2023

Abstract Person Search is a task involving pedestrian detection and person re-identification, aiming to retrieve person images matching a given objective attribute from a large-scale image library. The Person Search models need to understand and capture the detailed features and context information of smaller objects in the image more accurately and comprehensively. The current popular Person Search models, whether end-to-end or two-step, are based on anchor boxes. However, due to the limitations of the anchor itself, the model inevitably has some disadvantages, such as unbalance of positive and negative samples and redundant calculation, which will affect… More >

Wei Li^1,2, Benjian Zou¹, Yuxiang Luo², Ning Yang², Faye Zhang^1,*, Mingshun Jiang¹, Lei Jia¹

Structural Durability & Health Monitoring, Vol.17, No.6, pp. 485-500, 2023, DOI:10.32604/sdhm.2023.025989 - 17 November 2023

Abstract As a critical structure of aerospace equipment, aluminum alloy stiffened plate will influence the stability of spacecraft in orbit and the normal operation of the system. In this study, a GWO-ELM algorithm-based impact damage identification method is proposed for aluminum alloy stiffened panels to monitor and evaluate the damage condition of such stiffened panels of spacecraft. Firstly, together with numerical simulation, the experimental simulation to obtain the damage acoustic emission signals of aluminum alloy reinforced panels is performed, to establish the damage data. Subsequently, the amplitude-frequency characteristics of impact damage signals are extracted and put… More >

XUELIAN CHEN^1,*, YUNZHENG ZHANG², JUNJIAN HE³, YIBING LI⁴

BIOCELL, Vol.47, No.10, pp. 2283-2300, 2023, DOI:10.32604/biocell.2023.030086 - 08 November 2023

Abstract Background: The late detection of endometrial carcinoma (EC) at an advanced stage often results in a poor patient prognosis. It is hence important to identify reliable biomarkers to facilitate early detection of EC. Signal transducer and activator of transcription (STAT) family members play an important role in several tumors, however, their impact on EC development and progression remains unclear. Methods: Machine learning methods were used to investigate the importance of STAT5B in EC. Results: Hence, we explored the UALCAN data mining platform and found that while STAT1 and STAT2 were upregulated, STAT5A, STAT5B, and STAT6 were… More >

Wenqiu Zhu^1,2, Yongsheng Li^1,2, Qiang Liu^1,2,*, Zhigao Zeng^1,2

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1373-1392, 2023, DOI:10.32604/cmc.2023.037216 - 31 October 2023

Abstract Aiming at the problems of short duration, low intensity, and difficult detection of micro-expressions (MEs), the global and local features of ME video frames are extracted by combining spatial feature extraction and temporal feature extraction. Based on traditional convolution neural network (CNN) and long short-term memory (LSTM), a recognition method combining global identification attention network (GIA), block identification attention network (BIA) and bi-directional long short-term memory (Bi-LSTM) is proposed. In the BIA, the ME video frame will be cropped, and the training will be carried out by cropping into 24 identification blocks (IBs), 10 IBs… More >