Jongwook Si¹, Sungyoung Kim^2,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 2893-2908, 2024, DOI:10.32604/cmc.2023.046081

Abstract In the context of high compression rates applied to Joint Photographic Experts Group (JPEG) images through lossy compression techniques, image-blocking artifacts may manifest. This necessitates the restoration of the image to its original quality. The challenge lies in regenerating significantly compressed images into a state in which these become identifiable. Therefore, this study focuses on the restoration of JPEG images subjected to substantial degradation caused by maximum lossy compression using Generative Adversarial Networks (GAN). The generator in this network is based on the U-Net architecture. It features a new hourglass structure that preserves the characteristics of the deep layers. In… More >

Keqiang Wang¹, Pengyang Zhao¹, Changjian Wang², Zimeng Zhang¹, Yu Zhang¹, Jia Lu¹, Zedong Yang^2,*

Energy Engineering, Vol.121, No.4, pp. 1091-1108, 2024, DOI:10.32604/ee.2023.044016

Abstract The rising frequency of extreme disaster events seriously threatens the safe and secure operation of the regional integrated electricity-natural gas system (RIENGS). With the growing level of coupling between electric and natural gas systems, it is critical to enhance the load restoration capability of both systems. This paper proposes a coordinated optimization strategy for resilience-enhanced RIENGS load restoration and repair scheduling and transforms it into a mixed integer second-order cone programming (MISOCP) model. The proposed model considers the distribution network reconfiguration and the coordinated repair strategy between the two systems, minimizing the total system load loss cost and repair time.… More >

Linlin Zhu, Yu Han, Xiaoqi Xi, Zhicun Zhang, Mengnan Liu, Lei Li, Siyu Tan, Bin Yan^*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3367-3386, 2023, DOI:10.32604/cmc.2023.045878

Abstract Deep learning techniques have significantly improved image restoration tasks in recent years. As a crucial component of deep learning, the loss function plays a key role in network optimization and performance enhancement. However, the currently prevalent loss functions assign equal weight to each pixel point during loss calculation, which hampers the ability to reflect the roles of different pixel points and fails to exploit the image’s characteristics fully. To address this issue, this study proposes an asymmetric loss function based on the image and data characteristics of the image recovery task. This novel loss function can adjust the weight of… More >

Turki M. Alanazi^*

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1553-1568, 2023, DOI:10.32604/iasc.2023.039686

Abstract Image processing is becoming more popular because images are being used increasingly in medical diagnosis, biometric monitoring, and character recognition. But these images are frequently contaminated with noise, which can corrupt subsequent image processing stages. Therefore, in this paper, we propose a novel nonlinear filter for removing “salt and pepper” impulsive noise from a complex color image. The new filter is called the Modified Vector Directional Filter (MVDF). The suggested method is based on the traditional Vector Directional Filter (VDF). However, before the candidate pixel is processed by the VDF, the MVDF employs a threshold and the neighboring pixels of… More >

Babangida Isyaku^1,2,*, Kamalrulnizam Bin Abu Bakar¹, Wamda Nagmeldin³, Abdelzahir Abdelmaboud⁴, Faisal Saeed^5,6, Fuad A. Ghaleb¹

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3729-3748, 2023, DOI:10.32604/csse.2023.034509

Abstract Software Defined Networks (SDN) introduced better network management by decoupling control and data plane. However, communication reliability is the desired property in computer networks. The frequency of communication link failure degrades network performance, and service disruptions are likely to occur. Emerging network applications, such as delay-sensitive applications, suffer packet loss with higher Round Trip Time (RTT). Several failure recovery schemes have been proposed to address link failure recovery issues in SDN. However, these schemes have various weaknesses, which may not always guarantee service availability. Communication paths differ in their roles; some paths are critical because of the higher frequency usage.… More >

Cong Lin¹, Chenghao Qiu¹, Can Wu¹, Siling Feng^1,*, Mengxing Huang^1,2,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4317-4340, 2023, DOI:10.32604/cmc.2023.036249

Abstract The random-value impulse noise (RVIN) detection approach in image denoising, which is dependent on manually defined detection thresholds or local window information, does not have strong generalization performance and cannot successfully cope with damaged pictures with high noise levels. The fusion of the K-means clustering approach in the noise detection stage is reviewed in this research, and the internal relationship between the flat region and the detail area of the damaged picture is thoroughly explored to suggest an unique two-stage method for gray image denoising. Based on the concept of pixel clustering and grouping, all pixels in the damaged picture… More >

Yawei Dong¹, Ziyue Guo¹, Qun Ma², Zhiming Xin³, Jin Tao¹, Jiatai Tian¹, Jinlei Zhu³, Zhiming Zhang^1,*, Jianqiang Qian^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.5, pp. 1301-1309, 2023, DOI:10.32604/phyton.2023.027043

Abstract In arid and semi-arid sand dune ecosystems, belowground bud bank plays an important role in population regeneration and vegetation restoration. However, the responses of belowground bud bank size and composition to sand burial and its induced changes in soil environmental factors have been rarely studied. In arid sand dunes of Northwestern China, we investigated belowground bud bank size and composition of the typical rhizomatous psammophyte Psammochloa villosa as well as three key soil environmental factors (soil moisture, total carbon and total nitrogen) under different depths of sand burial. Total buds and rhizome buds increased significantly with increasing burial depth, whereas… More >

Jiayu Ren^1,*, Yoshihisa Fujita², Susumu Nakata²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2111-2125, 2023, DOI:10.32604/cmes.2023.025970

Abstract Implicit surface generation based on the interpolation of surface points is one of the well-known modeling methods in the area of computer graphics. Several methods for the implicit surface reconstruction from surface points have been proposed on the basis of radial basis functions, a weighted sum of local functions, splines, wavelets, and combinations of them. However, if the surface points contain errors or are sparsely distributed, irregular components, such as curvature-shaped redundant bulges and unexpectedly generated high-frequency components, are commonly seen. This paper presents a framework for restoring irregular components generated on and around surfaces. Users are assumed to specify… More >

Shengchun Wang¹, Baoxuan Huang¹, Tsz Ho Wong², Jingui Huang^1,*, Hong Deng¹

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4667-4684, 2023, DOI:10.32604/cmc.2023.031444

Abstract In this paper, we propose an end-to-end cross-layer gated attention network (CLGA-Net) to directly restore fog-free images. Compared with the previous dehazing network, the dehazing model presented in this paper uses the smooth cavity convolution and local residual module as the feature extractor, combined with the channel attention mechanism, to better extract the restored features. A large amount of experimental data proves that the defogging model proposed in this paper is superior to previous defogging technologies in terms of structure similarity index (SSIM), peak signal to noise ratio (PSNR) and subjective visual quality. In order to improve the efficiency of… More >

S. Girirajan, A. Pandian^*

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1987-2001, 2023, DOI:10.32604/iasc.2023.028090

Abstract Speech enhancement is the task of taking a noisy speech input and producing an enhanced speech output. In recent years, the need for speech enhancement has been increased due to challenges that occurred in various applications such as hearing aids, Automatic Speech Recognition (ASR), and mobile speech communication systems. Most of the Speech Enhancement research work has been carried out for English, Chinese, and other European languages. Only a few research works involve speech enhancement in Indian regional Languages. In this paper, we propose a two-fold architecture to perform speech enhancement for Tamil speech signal based on convolutional recurrent neural… More >