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 - 03 April 2023

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… 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 - 31 March 2023

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… 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 - 09 March 2023

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… 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 - 09 March 2023

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. 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 - 28 December 2022

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… More >

S. Girirajan, A. Pandian^*

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1987-2001, 2023, DOI:10.32604/iasc.2023.028090 - 19 July 2022

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… More >

P. Rahul^*, B. Kaarthick

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1595-1609, 2023, DOI:10.32604/iasc.2023.025762 - 19 July 2022

Abstract In Mobile Ad Hoc Networks (MANET), Quality of Service (QoS) is an important factor that must be analysed for the showing the better performance. The Node Quality-based Clustering Algorithm using Fuzzy-Fruit Fly Optimization for Cluster Head and Gateway Selection (NQCAFFFOCHGS) has the best network performance because it uses the Improved Weighted Clustering Algorithm (IWCA) to cluster the network and the FFO algorithm, which uses fuzzy-based network metrics to select the best CH and entryway. However, the major drawback of the fuzzy system was to appropriately select the membership functions. Also, the network metrics related to… More >

Aodi Fu¹, Mingxuan Zhu², Wenzheng Yu^1,*, Xin Yao¹, Hanxiaoya Zhang³

Journal on Big Data, Vol.4, No.1, pp. 77-86, 2022, DOI:10.32604/jbd.2022.027477 - 04 May 2022

Abstract In 2014, Typhoon Rammasun invaded Qinzhou, Guangxi, causing damage to the wind tower sensor at 80 m in Qinzhou. In order to restore the wind speed at 80 m at that time, this paper was based on the hourly average wind speed data of the wind tower and meteorological station from 2017–2019, and constructed the wind speed related model of Meteorological Station and the wind measuring tower in Qinzhou, Moreover, this paper Based on the hourly average wind speed data of Qinzhou Meteorological Station in 2014, Restored the hourly average wind speed of the anemometer tower during More >

M. Nuthal Srinivasan^1,*, M. Chinnadurai²

Computer Systems Science and Engineering, Vol.43, No.2, pp. 515-529, 2022, DOI:10.32604/csse.2022.023109 - 20 April 2022

Abstract The video inpainting process helps in several video editing and restoration processes like unwanted object removal, scratch or damage rebuilding, and retargeting. It intends to fill spatio-temporal holes with reasonable content in the video. Inspite of the recent advancements of deep learning for image inpainting, it is challenging to outspread the techniques into the videos owing to the extra time dimensions. In this view, this paper presents an efficient video inpainting approach using beetle antenna search with deep belief network (VIA-BASDBN). The proposed VIA-BASDBN technique initially converts the videos into a set of frames and… More >

Kazim Ali^1,*, Adnan N. Qureshi¹, Ahmad Alauddin Bin Arifin², Muhammad Shahid Bhatti³, Abid Sohail³, Rohail Hassan⁴

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2209-2224, 2022, DOI:10.32604/cmc.2022.020111 - 07 December 2021

Abstract These days, deep learning and computer vision are much-growing fields in this modern world of information technology. Deep learning algorithms and computer vision have achieved great success in different applications like image classification, speech recognition, self-driving vehicles, disease diagnostics, and many more. Despite success in various applications, it is found that these learning algorithms face severe threats due to adversarial attacks. Adversarial examples are inputs like images in the computer vision field, which are intentionally slightly changed or perturbed. These changes are humanly imperceptible. But are misclassified by a model with high probability and severely More >