Haizhen Wang^1,2,*, Jinying Yan^1,*, Na Jia¹

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 569-588, 2024, DOI:10.32604/cmc.2023.046055

Abstract Encrypted traffic identification pertains to the precise acquisition and categorization of data from traffic datasets containing imbalanced and obscured content. The extraction of encrypted traffic attributes and their subsequent identification presents a formidable challenge. The existing models have predominantly relied on direct extraction of encrypted traffic data from imbalanced datasets, with the dataset’s imbalance significantly affecting the model’s performance. In the present study, a new model, referred to as UD-VLD (Unbalanced Dataset-VAE-LSTM-DRN), was proposed to address above problem. The proposed model is an encrypted traffic identification model for handling unbalanced datasets. The encoder of the variational autoencoder (VAE) is combined… More >

Chih-Fang Huang^1,*, Cheng-Yuan Huang²

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1939-1953, 2022, DOI:10.32604/iasc.2022.017559

Abstract Musical emotion is important for the listener’s cognition. A smooth emotional expression generated through listening to music makes driving a car safer. Music has become more diverse and prolific with rapid technological developments. However, the cost of music production remains very high. At present, because the cost of music creation and the playing copyright are still very expensive, the music that needs to be listened to while driving can be executed by the way of automated composition of AI to achieve the purpose of driving safety and convenience. To address this problem, automated AI music composition has gradually gained attention… More >

R. Sujatha¹, B. Venkata Siva Krishna¹, Jyotir Moy Chatterjee², P. Rahul Naidu¹, NZ Jhanjhi^3,*, Challa Charita¹, Eza Nerin Mariya¹, Mohammed Baz⁴

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 525-541, 2022, DOI:10.32604/iasc.2022.021216

Abstract In the current times, COVID-19 has taken a handful of people’s lives. So, vaccination is crucial for everyone to avoid the spread of the disease. However, not every vaccine will be perfect or will get success for everyone. In the present work, we have analyzed the data from the Vaccine Adverse Event Reporting System and understood that the vaccines given to the people might or might not work considering certain demographic factors like age, gender, and multiple other variables like the state of living, etc. This variable is considered because it explains the unmentioned variables like their food habits and… More >

Yang Wu¹, Lihong Xu^1,*, Erik D. Goodman²

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 561-576, 2021, DOI:10.32604/iasc.2021.016415

Abstract Deep convolutional neural network (DCNN) requires a lot of data for training, but there has always been data vacuum in agriculture, making it difficult to label all existing data accurately. Therefore, a lightweight tomato leaf disease identification network supported by Variational auto-Encoder (VAE) is proposed to improve the accuracy of crop leaf disease identification. In the lightweight network, multi-scale convolution can expand the network width, enrich the extracted features, and reduce model parameters such as deep separable convolution. VAE makes full use of a large amount of unlabeled data to achieve unsupervised learning, and then uses labeled data for supervised… More >

Francesco Bertelli¹, Claudia Cattapan¹, Alvise Guariento², Vladimiro L. Vida^1,*

Congenital Heart Disease, Vol.16, No.1, pp. 39-43, 2021, DOI:10.32604/CHD.2021.013256

Abstract We report the case of three female patients who were scheduled for surgical correction of residual left-to-right shunt after initial repair of sinus venosus atrial septal defect (SV-ASD) during childhood. After excluding the possibility of an hemodynamic intervention, all three patients underwent a successful surgical closure through a right mini sub-axillary approach by using total peripheral cannulation for cardiopulmonary bypass and leaving the inferior vena cava completely un-snared allowing for an optimal visualization of the residual atrial septal communication and avoiding extensive dissection of mediastinal structures. More >

Xintao Duan^{1, *}, Daidou Guo¹, Chuan Qin²

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 721-745, 2020, DOI:10.32604/cmes.2020.09463

Abstract Image steganography is a technique that hides secret information into the cover image to protect information security. The current image steganography is mainly to embed a smaller secret image in an area such as a texture of a larger-sized cover image, which will cause the size of the secret image to be much smaller than the cover image. Therefore, the problem of small steganographic capacity needs to be solved urgently. This paper proposes a steganography framework that combines image compression. In this framework, the Vector Quantized Variational AutoEncoder (VQ-VAE) is used to achieve the compression of the secret image. The… More >

ELIANE VICTORIANO, ELISA A. GREGÓRIO

BIOCELL, Vol.28, No.2, pp. 165-169, 2004, DOI:10.32604/biocell.2004.28.165

Abstract The Lyonet’s gland is found in Lepidoptera larvae, close to the excretory duct of the silk gland. The role played by this gland is still uncertain. This work aims to describe the ultrastructure of the Lyonet’s gland in Diatraea saccharalis larvae, offering suggestions regarding its possible function. The insects were reared under laboratory-controlled conditions. The glands were conventionally prepared for transmission (TEM) and scanning (SEM) electron microscopy. SEM showed that Lyonet’s glands are paired small structures located in the ventral side of the head. They are composed by clustered long cells resembling leaves. Under TEM observations, each cell is surrounded… More >

Shigeaki Shiotani¹, Atsushi Hagiwara², Yoshitaka Sakakura³

The International Conference on Computational & Experimental Engineering and Sciences, Vol.4, No.1, pp. 19-24, 2007, DOI:10.3970/icces.2007.004.019

Abstract Marine fish larvae are fragile against physical stress. However, few studies have been conducted to evaluate the flow field in a rearing tank, which is assumed to provide a high degree of physical stress to marine fish larvae. This paper is a report on the numerical estimation of stationary flow in the rearing tank of marine fish larvae. The calculated flow in the rearing tank was compared with the experimental one. The calculation of the stationary flow in the rearing tank showed good qualitative and quantitative agreement with the experimental results. More >