Zhuo Huang, Ye Tian, Yifan Zhang, Tielin Shi, Qi Xia^*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 711-733, 2024, DOI:10.32604/cmes.2024.045411

Abstract Stiffened structures have great potential for improving mechanical performance, and the study of their stability is of great interest. In this paper, the optimization of the critical buckling load factor for curved grid stiffeners is solved by using the level set based density method, where the shape and cross section (including thickness and width) of the stiffeners can be optimized simultaneously. The grid stiffeners are a combination of many single stiffeners which are projected by the corresponding level set functions. The thickness and width of each stiffener are designed to be independent variables in the projection applied to each level… More >

Zhuoqun Xia¹, Hangyu Hu¹, Wenjing Li^2,3, Qisheng Jiang¹, Lan Pu¹, Yicong Shu¹, Arun Kumar Sangaiah^4,5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 409-430, 2024, DOI:10.32604/cmes.2024.030052

Abstract Early screening of diabetes retinopathy (DR) plays an important role in preventing irreversible blindness. Existing research has failed to fully explore effective DR lesion information in fundus maps. Besides, traditional attention schemes have not considered the impact of lesion type differences on grading, resulting in unreasonable extraction of important lesion features. Therefore, this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator (MPAG) and a lesion localization module (LLM). Firstly, MPAG is used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained… More >

Xueyan Xia^1,#, Xiaohong Fu^2,#, Yu Zhao¹, Jihan Cui¹, Nuoya Xiao¹, Jingxin Wang¹, Yiwei Lu¹, Meihong Huang¹, Cheng Chu¹, Jia Zhang², Mengxin Yang², Shunguo Li^1,*, Jianfeng Liu^2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 445-465, 2024, DOI:10.32604/phyton.2024.048273

Abstract Foxtail millet (Setaria italica) growth was inhibited because of waterlogging stress, which has caused yield reduction. ERF family plays an important role to plant adversity tolerance. In our study, we obtained 19,819 differential expressed genes (DEGs) between the two treatments based on the RNA-seq sequencing of foxtail millet of waterlogging stress. Furthermore, a total of 28 ERF family members were obtained, which have a complete open reading frame. We studied the evolution and function of SiERF family and how they affected the waterlogging tolerance. It was found that SiERF1A/B/C (GenBank ID: OR775217, OR775219, OR775218) and SiRAP2-12 (GenBank ID: OR775216) have… More >

Asifa Mehmood Qureshi¹, Naif Al Mudawi², Mohammed Alonazi³, Samia Allaoua Chelloug⁴, Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3683-3701, 2024, DOI:10.32604/cmc.2024.043611

Abstract Road traffic monitoring is an imperative topic widely discussed among researchers. Systems used to monitor traffic frequently rely on cameras mounted on bridges or roadsides. However, aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger area. To this end, different models have shown the ability to recognize and track vehicles. However, these methods are not mature enough to produce accurate results in complex road scenes. Therefore, this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image bursts. The extracted frames… More >

Navaneetha Krishnan Muthunambu¹, Senthil Prabakaran², Balasubramanian Prabhu Kavin³, Kishore Senthil Siruvangur⁴, Kavitha Chinnadurai¹, Jehad Ali^5,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3089-3127, 2024, DOI:10.32604/cmc.2023.043172

Abstract The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the Internet. Regrettably, this development has expanded the potential targets that hackers might exploit. Without adequate safeguards, data transmitted on the internet is significantly more susceptible to unauthorized access, theft, or alteration. The identification of unauthorised access attempts is a critical component of cybersecurity as it aids in the detection and prevention of malicious attacks. This research paper introduces a novel intrusion detection framework that utilizes Recurrent Neural Networks (RNN) integrated with… More >

Jing Yang, Bin Ji, Shasha Li^*, Jun Ma, Jie Yu

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4303-4315, 2024, DOI:10.32604/cmc.2023.035594

Abstract Named entity recognition (NER) is a fundamental task of information extraction (IE), and it has attracted considerable research attention in recent years. The abundant annotated English NER datasets have significantly promoted the NER research in the English field. By contrast, much fewer efforts are made to the Chinese NER research, especially in the scientific domain, due to the scarcity of Chinese NER datasets. To alleviate this problem, we present a Chinese scientific NER dataset–SciCN, which contains entity annotations of titles and abstracts derived from 3,500 scientific papers. We manually annotate a total of 62,059 entities, and these entities are classified… More >

SHAN OU^#, YUN XU^#, QINGLAN LIU, TIANWEN YANG, WEI CHEN, XIU YUAN, XIN ZUO, PENG SHI^*, JIE YAO^*

BIOCELL, Vol.48, No.3, pp. 415-429, 2024, DOI:10.32604/biocell.2024.046178

Abstract Background: The interrelation between intestinal polyps, metabolic syndrome (MetS), and colorectal cancer (CRC) is a critical area of study. This research focuses on pinpointing potential molecular targets to understand the link between intestinal polyp formation, metabolic irregularities, and CRC progression. Methods: We examined clinical samples from patients with intestinal polyps coexisting with MetS and compared them with samples from patients with standard intestinal polyps. Transcriptome sequencing and public database analysis were employed to identify significant pathways and genes. These targets were then validated through immunohistochemistry (IHC). Following the RNA interference of key target expression, a series of experiments, including the… More > Graphic Abstract

Tomio Okawa^*,†

Frontiers in Heat and Mass Transfer, Vol.3, No.1, pp. 1-8, 2012, DOI:10.5098/hmt.v3.1.3001

Abstract The present article summarizes the studies on the thermalhydraulic condition under which the onset of nucleate boiling (ONB) is triggered in subcooled flow boiling. Available correlations and experimental data show that the ONB is tended to be delayed in mini and microchannels. It is known that the ONB condition is significantly dependent on the surface condition even in conventional-sized channels. Accumulation of ONB data accompanied by the information on the surface condition is therefore considered of importance to elucidate the mechanisms of boiling incipience in microchannels. Discussion is also made for the bubble dynamics observed in mini and microchannels. It… More >

Murugan Palanikumar¹, Nasreen Kausar^2,*, Dragan Pamucar^3,4, Seifedine Kadry^5,6,7,*, Chomyong Kim⁸, Yunyoung Nam⁹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3353-3385, 2024, DOI:10.32604/cmes.2024.031439

Abstract In this article, multiple attribute decision-making problems are solved using the vague normal set (VNS). It is possible to generalize the vague set (VS) and q-rung fuzzy set (FS) into the q-rung vague set (VS). A log q-rung normal vague weighted averaging (log q-rung NVWA), a log q-rung normal vague weighted geometric (log q-rung NVWG), a log generalized q-rung normal vague weighted averaging (log Gq-rung NVWA), and a log generalized q-rung normal vague weighted geometric (log Gq-rung NVWG) operator are discussed in this article. A description is provided of the scoring function, accuracy function and operational laws of the log… More >

Chirag Chandrashekar¹, K. P. Vijayakumar^1,*, K. Pradeep¹, A. Balasundaram^1,2

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2511-2533, 2024, DOI:10.32604/cmc.2024.047697

Abstract The most widely farmed fruit in the world is mango. Both the production and quality of the mangoes are hampered by many diseases. These diseases need to be effectively controlled and mitigated. Therefore, a quick and accurate diagnosis of the disorders is essential. Deep convolutional neural networks, renowned for their independence in feature extraction, have established their value in numerous detection and classification tasks. However, it requires large training datasets and several parameters that need careful adjustment. The proposed Modified Dense Convolutional Network (MDCN) provides a successful classification scheme for plant diseases affecting mango leaves. This model employs the strength… More >