Mengqi Zhang¹, Jiazhao Chai², Jianxiang Cao³, Jialing Ji³, Tong Yi^4,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048486

Abstract In recent years, deep learning methods have developed rapidly and found application in many fields, including natural language processing. In the field of aspect-level sentiment analysis, deep learning methods can also greatly improve the performance of models. However, previous studies did not take into account the relationship between user feature extraction and contextual terms. To address this issue, we use data feature extraction and deep learning combined to develop an aspect-level sentiment analysis method. To be specific, we design user comment feature extraction (UCFE) to distill salient features from users’ historical comments and transform them into representative user feature vectors.… More >

Hongjun Zhang^1,2, Hao Zhang², Yu Lei³, Hao Ye¹, Peng Li^1,*, Desheng Shi¹

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048355

Abstract The study delves into the expanding role of network platforms in our daily lives, encompassing various mediums like blogs, forums, online chats, and prominent social media platforms such as Facebook, Twitter, and Instagram. While these platforms offer avenues for self-expression and community support, they concurrently harbor negative impacts, fostering antisocial behaviors like phishing, impersonation, hate speech, cyberbullying, cyberstalking, cyberterrorism, fake news propagation, spamming, and fraud. Notably, individuals also leverage these platforms to connect with authorities and seek aid during disasters. The overarching objective of this research is to address the dual nature of network platforms by proposing innovative methodologies aimed… More >

Guojun Chen^*, Danguo Cheng, Wei Chen, Xue Yang, Tiezheng Guo

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.047325

Abstract With the increase in ocean exploration activities and underwater development, the autonomous underwater vehicle (AUV) has been widely used as a type of underwater automation equipment in the detection of underwater environments. However, nowadays AUVs generally have drawbacks such as weak endurance, low intelligence, and poor detection ability. The research and implementation of path-planning methods are the premise of AUVs to achieve actual tasks. To improve the underwater operation ability of the AUV, this paper studies the typical problems of path-planning for the ant colony algorithm and the artificial potential field algorithm. In response to the limitations of a single… More >

Yunchang Liu^1,*, Fei Wan¹, Chengwu Liang²

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.047211

Abstract Traffic flow prediction plays a key role in the construction of intelligent transportation system. However, due to its complex spatio-temporal dependence and its uncertainty, the research becomes very challenging. Most of the existing studies are based on graph neural networks that model traffic flow graphs and try to use fixed graph structure to deal with the relationship between nodes. However, due to the time-varying spatial correlation of the traffic network, there is no fixed node relationship, and these methods cannot effectively integrate the temporal and spatial features. This paper proposes a novel temporal-spatial dynamic graph convolutional network (TSADGCN). The dynamic… More >

Chun-Ming Wu¹, Jin Lei^1,*, Wu-Kai Liu¹, Mei-Ling Ren¹, Ling-Li Ran²

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.047062

Abstract Aiming at defects such as low contrast in infrared ship images, uneven distribution of ship size, and lack of texture details, which will lead to unmanned ship leakage misdetection and slow detection, this paper proposes an infrared ship detection model based on the improved YOLOv8 algorithm (R_YOLO). The algorithm incorporates the Efficient Multi-Scale Attention mechanism (EMA), the efficient Reparameterized Generalized-feature extraction module (CSPStage), the small target detection header, the Repulsion Loss function, and the context aggregation block (CABlock), which are designed to improve the model’s ability to detect targets at multiple scales and the speed of model inference. The algorithm… More >

Sherly Alphonse^1,*, S. Abinaya¹, Sourabh Paul²

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.046403

Abstract The use of metamaterial enhances the performance of a specific class of antennas known as metamaterial antennas. The radiation cost and quality factor of the antenna are influenced by the size of the antenna. Metamaterial antennas allow for the circumvention of the bandwidth restriction for small antennas. Antenna parameters have recently been predicted using machine learning algorithms in existing literature. Machine learning can take the place of the manual process of experimenting to find the ideal simulated antenna parameters. The accuracy of the prediction will be primarily dependent on the model that is used. In this paper, a novel method… More >

Shoukun Xu¹, Lujun Zhang¹, Guangqi Jiang¹, Yining Hua², Yi Liu^1,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.045853

Abstract This paper focuses on the task of few-shot 3D point cloud semantic segmentation. Despite some progress, this task still encounters many issues due to the insufficient samples given, e.g., incomplete object segmentation and inaccurate semantic discrimination. To tackle these issues, we first leverage part-whole relationships into the task of 3D point cloud semantic segmentation to capture semantic integrity, which is empowered by the dynamic capsule routing with the module of 3D Capsule Networks (CapsNets) in the embedding network. Concretely, the dynamic routing amalgamates geometric information of the 3D point cloud data to construct higher-level feature representations, which capture the relationships… More >

XINRU FENG¹, LI XIAO^2,*

BIOCELL, Vol., , DOI:10.32604/biocell.2024.048395

Abstract Background: Galectin 2 (LGALS2) is a protein previously reported to serve as a mediator of disease progression in a range of cancers. The function of LGALS2 in oral squamous cell carcinoma (OSCC), however, has yet to be explored, prompting the present study to address this literature gap. Methods: Overall, 144 paired malignant tumor tissues and paracancerous OSCC patient samples were harvested and the LGALS2 expression levels were examined through qPCR and western immunoblotting. The LGALS2 coding sequence was introduced into the pcDNA3.0 vector, to enable the overexpression of this gene, while an LGALS2-specific shRNA and corresponding controls were also obtained.… More >

BINGJIE LI^1,#, WENBO CAO^1,2,3,#, JINJING XIAO¹, YIXIAO CHEN¹, QIYING WEI¹, MINGJIN YUE⁴, SAIJUN MO^1,2,3,*

BIOCELL, Vol., , DOI:10.32604/biocell.2024.049160

Abstract Perineural invasion (PNI), a particularly insidious form of tumor metastasis distinct from hematogenous or lymphatic spread, has the capacity to extend well beyond the primary tumor site, infiltrating distant regions devoid of lymphatic or vascular structures. PNI often heralds a decrease in patient survival rates and is recognized as an indicator of an unfavorable prognosis across a variety of cancers. Despite its clinical significance, the underlying molecular mechanisms of PNI remain elusive, complicating the development of specific and efficacious diagnostic and therapeutic strategies. In the realm of cancer research, non-coding RNAs (ncRNAs) have attracted considerable attention due to their multifaceted… More >

VIRAAJ VISHNU PRASAD, JENNIFER SALLY SAMSON, VENKATACHALAM DEEPA PARVATHI^*

BIOCELL, Vol., , DOI:10.32604/biocell.2024.048776

Abstract Physical activity and exercise have several beneficial roles in enhancing both physiological and psychological well-being of an individual. In addition to aiding the regulation of aerobic and anaerobic metabolism, exercise can stimulate the synthesis of exerkine hormones in the circulatory system. Among several exerkines that have been investigated for their therapeutic potential, Brain-derived neurotrophic factor (BDNF) is considered the most promising candidate, especially in the management of neurodegenerative diseases. Owing to the ability of physical activity to enhance BDNF synthesis, several experimental studies conducted so far have validated this hypothesis and produced satisfactory results at the pre-clinical level. This review… More > Graphic Abstract