Jiqiang Chen, Ranran Han, Dongqing Zhang, Litao Ma^*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5067-5082, 2024, DOI:10.32604/cmc.2024.051494

Abstract Imbalanced datasets are common in practical applications, and oversampling methods using fuzzy rules have been shown to enhance the classification performance of imbalanced data by taking into account the relationship between data attributes. However, the creation of fuzzy rules typically depends on expert knowledge, which may not fully leverage the label information in training data and may be subjective. To address this issue, a novel fuzzy rule oversampling approach is developed based on the learning vector quantization (LVQ) algorithm. In this method, the label information of the training data is utilized to determine the antecedent… More >

Suyi Liu^1,*, Jianning Chi¹, Chengdong Wu¹, Fang Xu^2,3,4, Xiaosheng Yu¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4471-4489, 2024, DOI:10.32604/cmc.2024.049450

Abstract In recent years, semantic segmentation on 3D point cloud data has attracted much attention. Unlike 2D images where pixels distribute regularly in the image domain, 3D point clouds in non-Euclidean space are irregular and inherently sparse. Therefore, it is very difficult to extract long-range contexts and effectively aggregate local features for semantic segmentation in 3D point cloud space. Most current methods either focus on local feature aggregation or long-range context dependency, but fail to directly establish a global-local feature extractor to complete the point cloud semantic segmentation tasks. In this paper, we propose a Transformer-based… More >

Amerah Alabrah^*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3897-3912, 2024, DOI:10.32604/cmc.2024.048528

Abstract The emergence of digital networks and the wide adoption of information on internet platforms have given rise to threats against users’ private information. Many intruders actively seek such private data either for sale or other inappropriate purposes. Similarly, national and international organizations have country-level and company-level private information that could be accessed by different network attacks. Therefore, the need for a Network Intruder Detection System (NIDS) becomes essential for protecting these networks and organizations. In the evolution of NIDS, Artificial Intelligence (AI) assisted tools and methods have been widely adopted to provide effective solutions. However,… More >

Bo Zhu^*, Xiaona Jing, Lan Qiu, Runbo Li

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3977-3999, 2024, DOI:10.32604/cmc.2024.048062

Abstract When building a classification model, the scenario where the samples of one class are significantly more than those of the other class is called data imbalance. Data imbalance causes the trained classification model to be in favor of the majority class (usually defined as the negative class), which may do harm to the accuracy of the minority class (usually defined as the positive class), and then lead to poor overall performance of the model. A method called MSHR-FCSSVM for solving imbalanced data classification is proposed in this article, which is based on a new hybrid… More >

Haoan Gu¹, Kai Zhu¹, Alfred Strauss², Yehui Shi^3,4, Dragoslav Sumarac⁵, Maosen Cao^1,*

Structural Durability & Health Monitoring, Vol.18, No.4, pp. 363-380, 2024, DOI:10.32604/sdhm.2024.042388

Abstract Concrete materials and structures are extensively used in transformation infrastructure and they usually bear cracks during their long-term operation. Detecting cracks using deep-learning algorithms like YOLOv3 (You Only Look Once version 3) is a new trend to pursue intelligent detection of concrete surface cracks. YOLOv3 is a typical deep-learning algorithm used for object detection. Owing to its generality, YOLOv3 lacks specific efficiency and accuracy in identifying concrete surface cracks. An improved algorithm based on YOLOv3, specialized in the rapid and accurate identification of concrete surface cracks is worthy of investigation. This study proposes a tailored… More >

Xin-sheng Cheng^*†, Shi-bo Sun^*, Feng Zhong^*, Kun He^*, Jie Zhou^*

Oncology Research, Vol.24, No.4, pp. 239-245, 2016, DOI:10.3727/096504016X14648701448011

Abstract Our aim was to study the expression of human SET domain containing protein 1A (hSETD1A) in hepatocellular carcinoma patients and its relationship with human hepatocellular carcinoma cell function. A total of 30 patients with hepatocellular carcinoma were enrolled in this study. The expression of hSETD1A was detected by real-time polymerase chain reaction (PCR) and Western blotting. The immortalized normal human liver cell line including SMMC-7721 was subjected to real-time PCR for hSETD1A mRNA. Furthermore, hSETD1A-small hairpin RNA (shRNA) was used to knock down hSETD1A expression in SMMC-7721 cells. Cell proliferation, cell apoptosis, and cell migration More >

I Wayan Sumardika^*†, Chen Youyi^*, Eisaku Kondo^‡, Yusuke Inoue^§, I Made Winarsa Ruma^*†, Hitoshi Murata^*, Rie Kinoshita^*, Ken-Ichi Yamamoto^*, Shuta Tomida^¶, Kazuhiko Shien^#, Hiroki Sato^#, Akira Yamauchi^**, Junichiro Futami^††, Endy Widya Putranto^‡‡, Toshihiko Hibino^§§, Shinichi Toyooka^¶#¶¶, Masahiro Nishibori^##, Masakiyo Sakaguchi^*

Oncology Research, Vol.26, No.3, pp. 431-444, 2018, DOI:10.3727/096504017X15031557924123

Abstract We previously identified novel S100A8/A9 receptors, extracellular matrix metalloproteinase inducer (EMMPRIN), melanoma cell adhesion molecule (MCAM), activated leukocyte cell adhesion molecule (ALCAM), and neuroplastin (NPTN) β, that are critically involved in S100A8/A9-mediated cancer metastasis and inflammation when expressed at high levels. However, little is known about the presence of any cancerspecific mechanism(s) that modifies these receptors, further inducing upregulation at protein levels without any transcriptional regulation. Expression levels of glycosyltransferase-encoding genes were examined by a PCRbased profiling array followed by confirmation with quantitative real-time PCR. Cell migration and invasion were assessed using a Boyden chamber.… More >

Ping He^*, Hong-xia Zhang^†, Chang-yu Sun^*, Chun-yong Chen^‡, He-qing Jiang^*

Oncology Research, Vol.24, No.1, pp. 25-32, 2016, DOI:10.3727/096504016X14575597858609

Abstract The SASH1 (SAM- and SH3-domain containing 1) gene, a member of the SLY (SH3 domain containing expressed in lymphocytes) family of signal adapter proteins, has been implicated in tumorigenesis of many types of cancers. However, the role and mechanism of SASH1 in the invasion and metastasis of hepatocarcinoma are largely unknown. In this study, we investigated the role and mechanism of SASH1 in the invasion and metastasis of hepatocarcinoma. Our results showed that SASH1 was lowly expressed in hepatocarcinoma cell lines. The in vitro experiments showed that overexpression of SASH1 inhibited the proliferation and migration/invasion More >

Wei Zong^*, Chen Yu^†, Ping Wang^*, Lei Dong^‡

Oncology Research, Vol.24, No.1, pp. 17-23, 2016, DOI:10.3727/096504016X14570992647203

Abstract The epithelial–mesenchymal transition (EMT) is considered to be one of the critical steps in gastric cancer cell invasion and metastasis. SAM- and SH3-domain containing 1 (SASH1), a member of the SLY family of signal adapter proteins, is a candidate for tumor suppression in several cancers. However, the biological role of SASH1 in gastric cancer remains largely unknown. Therefore, the purpose of this study was to investigate the impact of SASH1 on the biological behavior of gastric cancer cells treated with transforming growth factor (TGF)-β1. In the current study, we provide evidence that SASH1 was lowly More >

Di Wang, Yuefei Zhu, Jinlong Fei^*, Maohua Guo

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2253-2276, 2024, DOI:10.32604/cmc.2024.049504

Abstract Website fingerprinting, also known as WF, is a traffic analysis attack that enables local eavesdroppers to infer a user’s browsing destination, even when using the Tor anonymity network. While advanced attacks based on deep neural network (DNN) can perform feature engineering and attain accuracy rates of over 98%, research has demonstrated that DNN is vulnerable to adversarial samples. As a result, many researchers have explored using adversarial samples as a defense mechanism against DNN-based WF attacks and have achieved considerable success. However, these methods suffer from high bandwidth overhead or require access to the target… More >