Kunjian Wang¹, Ruibin He¹, Qianhua Liao¹, Kun Xu¹, Wen Wang¹, Kan Chen^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.3, pp. 563-578, 2024, DOI:10.32604/fdmp.2023.030152

Abstract Fault fractures usually have large openings and considerable extension. Accordingly, cross-linked gel materials are generally considered more suitable plugging agents than water-based gels because the latter often undergo contamination via formation water, which prevents them from being effective over long times. Hence, in this study, a set of oil-based composite gels based on waste grease and epoxy resin has been developed. These materials have been observed to possess high compressive strength and resistance to the aforementioned contamination, thereby leading to notable increase in plugging success rate. The compressive strength, thickening time, and resistance to formation water pollution of these gels… 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 >

Songmei Liu, Yuheng Wu, Hongmei Li, Dongli Cai, Huiling Liang, Changchun Ye, Shenggen He^*

Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3267-3290, 2023, DOI:10.32604/phyton.2023.045453

Abstract

The consumption of cut roses (Rosa hybrida) has always ranked first in the world. However, it is vulnerable to rapid petal and leaf wilting due to leaf stomatal water loss, which seriously affects its ornamental quality and economic value. Stomatal movement, a key in plant physiological processes, is influenced by potassium and nitrate. Advancing comprehension of its physiological and molecular mechanism holds promise for preserving the freshness of cut roses. This study observed the impacts of different concentrations of KNO₃ vase treatments on stomatal opening and water loss in cut rose ‘Carola’ leaves, as well as their transcriptional responses to… More >

Caixia Tao, Shize Yang^*, Taiguo Li

Energy Engineering, Vol.121, No.1, pp. 187-201, 2024, DOI:10.32604/ee.2023.042421

Abstract With the current integration of distributed energy resources into the grid, the structure of distribution networks is becoming more complex. This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms. Consequently, traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima. To tackle this issue, a more advanced particle swarm optimization algorithm is proposed. To address the varying emphases at different stages of the optimization process, a dynamic strategy is implemented to regulate the social and self-learning factors. The Metropolis criterion is introduced into the simulated annealing algorithm to… More >

Ali Alshahrani¹, Ahmad Adel Abu-Shareha^2,*, Qusai Y. Shambour², Basil Al-Kasasbeh¹

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1679-1698, 2023, DOI:10.32604/cmc.2023.043545

Abstract Active queue management (AQM) methods manage the queued packets at the router buffer, prevent buffer congestion, and stabilize the network performance. The bursty nature of the traffic passing by the network routers and the slake behavior of the existing AQM methods leads to unnecessary packet dropping. This paper proposes a fully adaptive active queue management (AAQM) method to maintain stable network performance, avoid congestion and packet loss, and eliminate unnecessary packet dropping. The proposed AAQM method is based on load and queue length indicators and uses an adaptive mechanism to adjust the dropping probability based on the buffer status. The… More >

Wei Wang¹, Xinyao Tang^2,*, Kai Zhou¹, Chunhui Zhao¹, Changfa Liu³

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1911-1928, 2023, DOI:10.32604/cmc.2023.043233

Abstract Data Matrix (DM) codes have been widely used in industrial production. The reading of DM code usually includes positioning and decoding. Accurate positioning is a prerequisite for successful decoding. Traditional image processing methods have poor adaptability to pollution and complex backgrounds. Although deep learning-based methods can automatically extract features, the bounding boxes cannot entirely fit the contour of the code. Further image processing methods are required for precise positioning, which will reduce efficiency. Because of the above problems, a CenterNet-based DM code key point detection network is proposed, which can directly obtain the four key points of the DM code.… More >

Lisang Liu¹, Chengyang Ke^1,*, He Lin²

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2443-2461, 2023, DOI:10.32604/cmc.2023.042582

Abstract Aiming at the problems of inaccurate edge segmentation, the hole phenomenon of segmenting large-scale targets, and the slow segmentation speed of printed circuit boards (PCB) in the image segmentation process, a PCB image segmentation model Mobile-Deep based on DeepLabv3+ semantic segmentation framework is proposed. Firstly, the DeepLabv3+ feature extraction network is replaced by the lightweight model MobileNetv2, which effectively reduces the number of model parameters; secondly, for the problem of positive and negative sample imbalance, a new loss function is composed of Focal Loss combined with Dice Loss to solve the category imbalance and improve the model discriminative ability; in… More >

Fufang Li, Manlin Luo^*, Ming Hu, Guobin Wang, Yan Chen

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2835-2850, 2023, DOI:10.32604/csse.2023.039765

Abstract Liver cancer has the second highest incidence rate among all types of malignant tumors, and currently, its diagnosis heavily depends on doctors’ manual labeling of CT scan images, a process that is time-consuming and susceptible to subjective errors. To address the aforementioned issues, we propose an automatic segmentation model for liver and tumors called Res2Swin Unet, which is based on the Unet architecture. The model combines Attention-Res2 and Swin Transformer modules for liver and tumor segmentation, respectively. Attention-Res2 merges multiple feature map parts with an Attention gate via skip connections, while Swin Transformer captures long-range dependencies and models the input… More >

Shadi Al-Sarawi¹, Mohammed Anbar^1,*, Basim Ahmad Alabsi², Mohammad Adnan Aladaileh³, Shaza Dawood Ahmed Rihan²

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 491-515, 2023, DOI:10.32604/cmc.2023.041108

Abstract The Internet of Things (IoT) consists of interconnected smart devices communicating and collecting data. The Routing Protocol for Low-Power and Lossy Networks (RPL) is the standard protocol for Internet Protocol Version 6 (IPv6) in the IoT. However, RPL is vulnerable to various attacks, including the sinkhole attack, which disrupts the network by manipulating routing information. This paper proposes the Unweighted Voting Method (UVM) for sinkhole node identification, utilizing three key behavioral indicators: DODAG Information Object (DIO) Transaction Frequency, Rank Harmony, and Power Consumption. These indicators have been carefully selected based on their contribution to sinkhole attack detection and other relevant… More >

Liuhuo Wang¹, Qingcui Liu², Wenwei Zhu³, Yanru Wang⁴, Yi Tian^4,*, Long Zhao⁴

Energy Engineering, Vol.120, No.11, pp. 2651-2666, 2023, DOI:10.32604/ee.2023.027791

Abstract The electromagnetic losses of submarine cables are mainly caused by the metal shielding layer to prevent the water tree effect and the armor layer that strengthens the strength of the submarine cables. While these losses cause the temperature of submarine cable to rise, and temperature variation will in turn change the conductivity of its metal layer material. In this paper, the electric-magnetic-thermal multi-physical field coupling of the electromagnetic loss variation of the submarine cable is realized by establishing a full coupling system containing Fourier’s law and Maxwell-Ampère’s Law for the photoelectric composite submarine cable. The multi-physical field coupling model is… More > Graphic Abstract