Sanxia Shi, Yinglei Song^*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2911-2934, 2024, DOI:10.32604/cmc.2024.055363 - 18 November 2024

Abstract Infrared small target detection technology plays a pivotal role in critical military applications, including early warning systems and precision guidance for missiles and other defense mechanisms. Nevertheless, existing traditional methods face several significant challenges, including low background suppression ability, low detection rates, and high false alarm rates when identifying infrared small targets in complex environments. This paper proposes a novel infrared small target detection method based on a transformed Gaussian filter kernel and clustering approach. The method provides improved background suppression and detection accuracy compared to traditional techniques while maintaining simplicity and lower computational costs.… More >

Suya Li¹, Ying Cao^1,*, Hengyi Ren², Dongsheng Zhu³, Xin Xie¹

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1449-1470, 2024, DOI:10.32604/cmc.2024.056824 - 15 October 2024

Abstract Multi-object tracking (MOT) has seen rapid improvements in recent years. However, frequent occlusion remains a significant challenge in MOT, as it can cause targets to become smaller or disappear entirely, resulting in low-quality targets, leading to trajectory interruptions and reduced tracking performance. Different from some existing methods, which discarded the low-quality targets or ignored low-quality target attributes. LQTTrack, with a low-quality association strategy (LQA), is proposed to pay more attention to low-quality targets. In the association scheme of LQTTrack, firstly, multi-scale feature fusion of FPN (MSFF-FPN) is utilized to enrich the feature information and assist… More >

Tongan Yu¹, Yali Xue^1,*, Yiming He¹, Shan Cui², Jun Hong²

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1235-1250, 2024, DOI:10.32604/cmc.2024.056075 - 15 October 2024

Abstract With the rapid development of deep learning-based detection algorithms, deep learning is widely used in the field of infrared small target detection. However, well-designed adversarial samples can fool human visual perception, directly causing a serious decline in the detection quality of the recognition model. In this paper, an adversarial defense technology for small infrared targets is proposed to improve model robustness. The adversarial samples with strong migration can not only improve the generalization of defense technology, but also save the training cost. Therefore, this study adopts the concept of maximizing multidimensional feature distortion, applying noise… More >

Oncology Research Editorial Office

Oncology Research, Vol.32, No.10, pp. 1693-1694, 2024, DOI:10.32604/or.2024.056909 - 18 September 2024

Abstract This article has no abstract. More >

FEI CHU¹, KAI TONG¹, XIANG GU¹, MEI BAO¹, YANFEN CHEN¹, BIN WANG², YANHUA SHAO¹, LING WEI^1,*

Oncology Research, Vol.32, No.10, pp. 1661-1671, 2024, DOI:10.32604/or.2024.048287 - 18 September 2024

Abstract Glutamine is one of the most abundant non-essential amino acids in human plasma and plays a crucial role in many biological processes of the human body. Tumor cells take up a large amount of glutamine to meet their rapid proliferation requirements, which is supported by the upregulation of glutamine transporters. Targeted inhibition of glutamine transporters effectively inhibits cell growth and proliferation in tumors. Among all cancers, digestive system malignant tumors (DSMTs) have the highest incidence and mortality rates, and the current therapeutic strategies for DSMTs are mainly surgical resection and chemotherapy. Due to the relatively More > Graphic Abstract

Oncology Research Editorial Office

Oncology Research, Vol.32, No.9, pp. 1537-1537, 2024, DOI:10.32604/or.2024.056125 - 23 August 2024

Abstract This article has no abstract. More >

Bo Cao^1,*, Qinghua Xing², Longyue Li², Huaixi Xing¹, Zhanfu Song¹

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1251-1275, 2024, DOI:10.32604/cmc.2024.052842 - 18 July 2024

Abstract As a core part of battlefield situational awareness, air target intention recognition plays an important role in modern air operations. Aiming at the problems of insufficient feature extraction and misclassification in intention recognition, this paper designs an air target intention recognition method (KGTLIR) based on Knowledge Graph and Deep Learning. Firstly, the intention recognition model based on Deep Learning is constructed to mine the temporal relationship of intention features using dilated causal convolution and the spatial relationship of intention features using a graph attention mechanism. Meanwhile, the accuracy, recall, and F1-score after iteration are introduced More >

LINGLI ZHANG^1,2,#, YAN LI^1,#, JINGXIN MAO^1,*

BIOCELL, Vol.48, No.6, pp. 905-922, 2024, DOI:10.32604/biocell.2024.050396 - 10 June 2024

Abstract Hepatocellular carcinoma (HCC) remains a prevalent and challenging malignancy globally, characterized by its numerous causal factors and generally unfavorable prognosis. In the relentless pursuit of effective treatment modalities, natural products have emerged as a promising and relatively non-toxic alternative, garnering significant interest. The integration of natural products with contemporary medical research has yielded encouraging therapeutic outcomes in the management of HCC. This review offers a comprehensive overview of the causal factors underlying HCC, and the diverse treatment options available, and highlights the advancements made by natural products in anti-HCC research. Particularly, we provide an outline More >

ELHAM SHAKIBA¹, SETI BOROOMAND², SIMA KHERADMAND KIA³, MEHDI HEDAYATI^4,*

Oncology Research, Vol.32, No.6, pp. 1011-1019, 2024, DOI:10.32604/or.2024.049235 - 23 May 2024

Abstract This review aimed to describe the inculpation of microRNAs (miRNAs) in thyroid cancer (TC) and its subtypes, mainly medullary thyroid carcinoma (MTC), and to outline web-based tools and databases for bioinformatics analysis of miRNAs in TC. Additionally, the capacity of miRNAs to serve as therapeutic targets and biomarkers in TC management will be discussed. This review is based on a literature search of relevant articles on the role of miRNAs in TC and its subtypes, mainly MTC. Additionally, web-based tools and databases for bioinformatics analysis of miRNAs in TC were identified and described. MiRNAs can… More > Graphic Abstract

Yujing Ma^1,4, Zhongwang Wang², Jieyuan Zhang³, Ruijin Huo^1,4, Xiaohui Yuan^1,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 2079-2102, 2024, DOI:10.32604/cmes.2024.048488 - 20 May 2024

Abstract In this paper, an adaptive polynomial chaos expansion method (PCE) based on the method of moments (MoM) is proposed to construct surrogate models for electromagnetic scattering and further sensitivity analysis. The MoM is applied to accurately solve the electric field integral equation (EFIE) of electromagnetic scattering from homogeneous dielectric targets. Within the bistatic radar cross section (RCS) as the research object, the adaptive PCE algorithm is devoted to selecting the appropriate order to construct the multivariate surrogate model. The corresponding sensitivity results are given by the further derivative operation, which is compared with those of More >