Ang Liu¹, Qing Zhang², Shengwei Xu^3,*, Huamin Feng⁴, Xiu-bo Chen⁵, Wen Liu¹

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1727-1751, 2024, DOI:10.32604/cmc.2024.051233

Abstract The Internet of Things (IoT) is a network system that connects physical devices through the Internet, allowing them to interact. Nowadays, IoT has become an integral part of our lives, offering convenience and smart functionality. However, the growing number of IoT devices has brought about a corresponding increase in cybersecurity threats, such as device vulnerabilities, data privacy concerns, and network susceptibilities. Integrating blockchain technology with IoT has proven to be a promising approach to enhance IoT security. Nevertheless, the emergence of quantum computing poses a significant challenge to the security of traditional classical cryptography used… More >

Jane Kim¹, Soojin Lee¹, Chan Yeob Yeun², Seung-Hyun Seo^1,3,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3495-3518, 2024, DOI:10.32604/cmc.2024.050461

Abstract As big data, Artificial Intelligence, and Vehicle-to-Everything (V2X) communication have advanced, Intelligent Transportation Systems (ITS) are being developed to enable efficient and safe transportation systems. Electronic Toll Collection (ETC), which is one of the services included in ITS systems, is an automated system that allows vehicles to pass through toll plazas without stopping for manual payment. The ETC system is widely deployed on highways due to its contribution to stabilizing the overall traffic system flow. To ensure secure and efficient toll payments, designing a distributed model for sharing toll payment information among untrusted toll service… More >

Fangjun Luan^1,2,3, Xuewen Mu^1,2,3, Shuai Yuan^1,2,3,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 695-712, 2024, DOI:10.32604/cmc.2024.048502

Abstract Online Signature Verification (OSV), as a personal identification technology, is widely used in various industries. However, it faces challenges, such as incomplete feature extraction, low accuracy, and computational heaviness. To address these issues, we propose a novel approach for online signature verification, using a one-dimensional Ghost-ACmix Residual Network (1D-ACGRNet), which is a Ghost-ACmix Residual Network that combines convolution with a self-attention mechanism and performs improvement by using Ghost method. The Ghost-ACmix Residual structure is introduced to leverage both self-attention and convolution mechanisms for capturing global feature information and extracting local information, effectively complementing whole and… More >

Hongliang Tian, Jiaming Wang^*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1611-1629, 2024, DOI:10.32604/cmc.2023.046698

Abstract Blockchain, known for its secure encrypted ledger, has garnered attention in financial and data transfer realms, including the field of energy trading. However, the decentralized nature and identity anonymity of user nodes raise uncertainties in energy transactions. The broadcast consensus authentication slows transaction speeds, and frequent single-point transactions in multi-node settings pose key exposure risks without protective measures during user signing. To address these, an alliance blockchain scheme is proposed, reducing the resource-intensive identity verification among nodes. It integrates multi-signature functionality to fortify user resources and transaction security. A novel multi-signature process within this framework… More >

Cai Ming Liu^1,2,3, Yan Zhang^1,2,*, Zhihui Hu^1,2, Chunming Xie¹

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2361-2389, 2024, DOI:10.32604/cmc.2023.045282

Abstract Artificial immune detection can be used to detect network intrusions in an adaptive approach and proper matching methods can improve the accuracy of immune detection methods. This paper proposes an artificial immune detection model for network intrusion data based on a quantitative matching method. The proposed model defines the detection process by using network data and decimal values to express features and artificial immune mechanisms are simulated to define immune elements. Then, to improve the accuracy of similarity calculation, a quantitative matching method is proposed. The model uses mathematical methods to train and evolve immune More >

DAIXIN ZHAO¹, QINGYU WANG², JIANBO WANG^1,*

BIOCELL, Vol.48, No.2, pp. 271-281, 2024, DOI:10.32604/biocell.2023.029094

Abstract Background: Esophageal cancer (ESCA) is a common digestive tract tumor. As a result, optimization of the early diagnosis of ESCA and identifying the contributing prognostic genes is urgently required. Herein, the prognosis of mitochondrial autophagy-related genes was analyzed in different subtypes of ESCA, and prognostic models were constructed to identify the immune cell infiltration with significant differences between subtypes. Methods: The Cancer Genome Atlas database was searched to download 185 ESCA samples, covering gene expression level data and clinical follow-up data, and 179 samples from the Gene Expression Omnibus database for subsequent validation analysis. The… More >

QIOU GU¹, CHUILIN LAI¹, XIAO GUAN¹, JING ZHU², TIAN ZHAN¹, JIANPING ZHANG^1,*

BIOCELL, Vol.48, No.2, pp. 253-269, 2024, DOI:10.32604/biocell.2023.028336

Abstract Objectives: Colorectal cancer (CRC) is a serious threat to human health worldwide. Oxaliplatin is a platinum analog and is widely used to treat CRC. However, resistance to oxaliplatin restricts its effectiveness and application while its target recognition and mechanism of action also remain unclear. Therefore, we aimed to develop an oxaliplatin-resistant prognostic model to clarify these aspects. Methods: We first obtained oxaliplatin-resistant and parental cell lines, and identified oxaliplatin-resistant genes using RNA sequencing (RNA-seq) and differential gene analysis. We then acquired relevant data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.… More > Graphic Abstract

QI XIA¹, XING CHEN², QINGHUA MA³, XIANXIU WEN^2,*

BIOCELL, Vol.48, No.2, pp. 217-228, 2024, DOI:10.32604/biocell.2023.027414

Abstract Background: Breast cancer (BC) is the most common cancer and the leading cause of cancer death in women. Immune features play an important role in improving the prognosis prediction of BC. However, while previous immune signatures consisted mainly of immune genes, immune cell-based signatures have been rarely reported. Methods: In this study, we report that a novel immune cell signature is effective in improving prognostic prediction by combining M2 macrophages. We identified 17 differentially infiltrating immune cells between cancer and normal groups. Prognostic features of the four immune cells identified by LASSO COX analysis showed… More >

HENG ZHANG^1,#, WENJING CHENG^2,#, HAIBO ZHAO², WEIDONG CHEN², QIUJIE ZHANG^2,*, QING-QING YU^2,*

Oncology Research, Vol.32, No.2, pp. 297-308, 2024, DOI:10.32604/or.2023.043138

Abstract Background: Colorectal cancer (CRC) belongs to the class of significantly malignant tumors found in humans. Recently, dysregulated fatty acid metabolism (FAM) has been a topic of attention due to its modulation in cancer, specifically CRC. However, the regulatory FAM pathways in CRC require comprehensive elucidation. Methods: The clinical and gene expression data of 175 fatty acid metabolic genes (FAMGs) linked with colon adenocarcinoma (COAD) and normal cornerstone genes were gathered through The Cancer Genome Atlas (TCGA)-COAD corroborating with the Molecular Signature Database v7.2 (MSigDB). Initially, crucial prognostic genes were selected by uni- and multi-variate Cox… More >

WEI HU^1,#, THOMAS WARTMANN^2,#, MARCO STRECKER², ARISTOTELIS PERRAKIS², ROLAND CRONER², ARPAD SZALLASI³, WENJIE SHI^2,*, ULF D. KAHLERT^2,*

Oncology Research, Vol.32, No.1, pp. 227-239, 2024, DOI:10.32604/or.2023.043053

Abstract Transient receptor potential (TRP) channels are strongly associated with colon cancer development and progression. This study leveraged a multivariate Cox regression model on publicly available datasets to construct a TRP channels-associated gene signature, with further validation of signature in real world samples from our hospital treated patient samples. Kaplan-Meier (K-M) survival analysis and receiver operating characteristic (ROC) curves were employed to evaluate this gene signature’s predictive accuracy and robustness in both training and testing cohorts, respectively. Additionally, the study utilized the CIBERSORT algorithm and single-sample gene set enrichment analysis to explore the signature’s immune infiltration… More > Graphic Abstract