Arslan Akram^1,2, Imran Khan¹, Javed Rashid^2,3, Mubbashar Saddique^4,*, Muhammad Idrees⁴, Yazeed Yasin Ghadi⁵, Abdulmohsen Algarni⁶

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1311-1328, 2024, DOI:10.32604/cmc.2023.040512

Abstract Algorithms for steganography are methods of hiding data transfers in media files. Several machine learning architectures have been presented recently to improve stego image identification performance by using spatial information, and these methods have made it feasible to handle a wide range of problems associated with image analysis. Images with little information or low payload are used by information embedding methods, but the goal of all contemporary research is to employ high-payload images for classification. To address the need for both low- and high-payload images, this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to… More >

Derwin Suhartono^1,*, Alif Tri Handoyo¹, Franz Adeta Junior²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3637-3657, 2023, DOI:10.32604/cmc.2023.045301

Abstract Sarcasm detection in text data is an increasingly vital area of research due to the prevalence of sarcastic content in online communication. This study addresses challenges associated with small datasets and class imbalances in sarcasm detection by employing comprehensive data pre-processing and Generative Adversial Network (GAN) based augmentation on diverse datasets, including iSarcasm, SemEval-18, and Ghosh. This research offers a novel pipeline for augmenting sarcasm data with Reverse Generative Adversarial Network (RGAN). The proposed RGAN method works by inverting labels between original and synthetic data during the training process. This inversion of labels provides feedback to the generator for generating… More >

Jongwook Si¹, Sungyoung Kim^2,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3119-3138, 2023, DOI:10.32604/cmc.2023.043797

Abstract The objective of style transfer is to maintain the content of an image while transferring the style of another image. However, conventional methods face challenges in preserving facial features, especially in Korean portraits where elements like the “Gat” (a traditional Korean hat) are prevalent. This paper proposes a deep learning network designed to perform style transfer that includes the “Gat” while preserving the identity of the face. Unlike traditional style transfer techniques, the proposed method aims to preserve the texture, attire, and the “Gat” in the style image by employing image sharpening and face landmark, with the GAN. The color,… More >

Lipei Chen, Rilie Deng, Xuewen Li, Min Yu, Hongdong Xiao^*

Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3359-3370, 2023, DOI:10.32604/phyton.2023.046877

Abstract

In the rice-wheat rotation system, biochar (BC) can be applied at the initiation of the rice or wheat season. Here, we compared the effects of BC that were applied at two different crop seasons on wheat production, quality, and soil profile properties in a rice-wheat rotation system with nitrogen (N) fertilizer applied at 280 kg/ha rate. Results showed that both wheat grain production and N recovery use efficiency were influenced by BC applied at two crop seasons. Biochar application did not affect the total non-essential amino-acid, but when applied during wheat season, BC significantly (p < 0.05) increased total essential… More >

Anwar Ullah¹, Xinguo Yu^1,*, Muhammad Numan²

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2359-2383, 2023, DOI:10.32604/cmc.2023.041219

Abstract Generating realistic and synthetic video from text is a highly challenging task due to the multitude of issues involved, including digit deformation, noise interference between frames, blurred output, and the need for temporal coherence across frames. In this paper, we propose a novel approach for generating coherent videos of moving digits from textual input using a Deep Deconvolutional Generative Adversarial Network (DD-GAN). The DD-GAN comprises a Deep Deconvolutional Neural Network (DDNN) as a Generator (G) and a modified Deep Convolutional Neural Network (DCNN) as a Discriminator (D) to ensure temporal coherence between adjacent frames. The proposed research involves several steps.… More >

Shahina Anwarul¹, Sunil Kumar², Ashok Bhansali³, Hammam Alshazly^4,*, Hany S. Hussein^5,6

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3145-3163, 2023, DOI:10.32604/csse.2023.041061

Abstract Security systems are the need of the hour to protect data from unauthorized access. The dissemination of confidential information over the public network requires a high level of security. The security approach such as steganography ensures confidentiality, authentication, integrity, and non-repudiation. Steganography helps in hiding the secret data inside the cover media so that the attacker can be confused during the transmission process of secret data between sender and receiver. Therefore, we present an efficient hybrid security model that provides multifold security assurance. To this end, a rectified Advanced Encryption Standard (AES) algorithm is proposed to overcome the problems existing… More >

R. Ani^1,*, O. S. Deepa², B. R. Manju¹

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3033-3048, 2023, DOI:10.32604/csse.2023.033807

Abstract The drug development process takes a long time since it requires sorting through a large number of inactive compounds from a large collection of compounds chosen for study and choosing just the most pertinent compounds that can bind to a disease protein. The use of virtual screening in pharmaceutical research is growing in popularity. During the early phases of medication research and development, it is crucial. Chemical compound searches are now more narrowly targeted. Because the databases contain more and more ligands, this method needs to be quick and exact. Neural network fingerprints were created more effectively than the well-known… More >

Haodong Li¹, Huiling Du^1,*, Le Kang¹, Yewen Zhang¹, Tong Lu¹, Yuchan Zhang¹, Lan Yang², Shijie Song²

Journal of Renewable Materials, Vol.11, No.12, pp. 4161-4174, 2023, DOI:10.32604/jrm.2023.028877

Abstract The large accumulation of coal gangue, a common industrial solid waste, causes severe environmental problems, and green development strategies are required to transform this waste into high-value-added products. In this study, low-cost ceramsites adsorbents were prepared from waste gangue, silt coal, and peanut shells and applied to remove the organic dye methylene blue from wastewater. We investigated the microstructure of ceramsites and the effects of the sintering atmosphere, sintering temperature, and solution pH on their adsorption performance. The ceramsites sintered at 800°C under a nitrogen atmosphere exhibited the largest three-dimensional-interconnected hierarchical porous structure among the prepared ceramsites; further, it exhibited… More > Graphic Abstract

Bio Chéïssou Koto Tamou^1,2,3, Jean-Michel Mechling², Crespin Prudence Yabi^1,*, Gildas Edjrossè F. Godonou³, Edmond Codjo Adjovi¹, Mohamed Gibigaye³, André Lecomte², Nicolas Brosse⁴

Journal of Renewable Materials, Vol.11, No.12, pp. 4143-4160, 2023, DOI:10.32604/jrm.2023.030509

Abstract The housing sector today uses elaborate materials such as cement, iron, sand, often prohibitively expensive and whose production generates a strong environmental impact (scarcity of resources, transport, greenhouse gas greenhouse, etc.). In order to meet the challenges of sustainable development, earth construction is experiencing a resurgence of interest these days. Despite its many advantages, raw earth material has drawbacks, in particular its low mechanical resistance and its loss of geometric characteristics in the face of water, which slow down its development. As part of this study, the mechanical characteristics and durability of raw earth were improved by using residual water… More > Graphic Abstract

Hu Shi, Wei Cai, Xin Wang^*, Lei Song, Yuan Hu^*

Journal of Renewable Materials, Vol.11, No.12, pp. 3991-4006, 2023, DOI:10.32604/jrm.2023.029888

Abstract To solve the fire accidents caused by coal combustion, this work prepared four hybrid hydrogel materials using bio-based polymers, flame retardants, and inorganic materials. Compared to pure water and 3.5 wt% MgCl₂ solution, the as-prepared hydrogel presents good fire prevention performance. In addition, it is found that CO and CO₂ are not produced by coal when the pyrolysis temperature is lower than 200°C. During low-temperature pyrolysis, CO is more likely to be produced than CO₂, indicating inadequate pyrolysis behavior. At the same time, the addition of fire-preventing hydrogel can not only decrease the maximum CO₂ concentration before the critical temperature… More > Graphic Abstract