Lijun Mu, Xiaojia Xue, Jie Bai^*, Xiaoyan Li, Xueliang Han

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1365-1379, 2024, DOI:10.32604/fdmp.2024.049013

Abstract Following large-scale volume fracturing in shale oil reservoirs, well shut-in measures are generally employed. Laboratory tests and field trials have underscored the efficacy of fracturing fluid imbibition during the shut-in phase in augmenting shale oil productivity. Unlike conventional reservoirs, shale oil reservoirs exhibit characteristics such as low porosity, low permeability, and rich content of organic matter and clay minerals. Notably, the osmotic pressure effects occurring between high-salinity formation water and low-salinity fracturing fluids are significant. The current understanding of the mobilization patterns of crude oil in micro-pores during the imbibition process remains nebulous, and the… More >

Mahatir Ahmed Tusher¹, Saket Choudary Kongara¹, Sagar Dhanraj Pande², SeongKi Kim^3,*, Salil Bharany^4,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4063-4080, 2024, DOI:10.32604/cmc.2024.049007

Abstract The challenging task of handwriting style synthesis requires capturing the individuality and diversity of human handwriting. The majority of currently available methods use either a generative adversarial network (GAN) or a recurrent neural network (RNN) to generate new handwriting styles. This is why these techniques frequently fall short of producing diverse and realistic text pictures, particularly for terms that are not commonly used. To resolve that, this research proposes a novel deep learning model that consists of a style encoder and a text generator to synthesize different handwriting styles. This network excels in generating conditional… More >

Bo Zhu^*, Xiaona Jing, Lan Qiu, Runbo Li

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3977-3999, 2024, DOI:10.32604/cmc.2024.048062

Abstract When building a classification model, the scenario where the samples of one class are significantly more than those of the other class is called data imbalance. Data imbalance causes the trained classification model to be in favor of the majority class (usually defined as the negative class), which may do harm to the accuracy of the minority class (usually defined as the positive class), and then lead to poor overall performance of the model. A method called MSHR-FCSSVM for solving imbalanced data classification is proposed in this article, which is based on a new hybrid… More >

Kristamtini¹, Sugeng Widodo², Heni Purwaningsih³, Arlyna Budi Pustika¹, Setyorini Widyayanti¹, Arif Muazam¹, Arini Putri Hanifa^1,*, Joko Triastono², Dewi Sahara², Heni Sulistyawati Purwaning Rahayu², Pandu Laksono², Diah Arina Fahmi², Sutardi¹, Joko Pramono⁴, Rachmiwati Yusuf¹

Phyton-International Journal of Experimental Botany, Vol.93, No.5, pp. 1007-1021, 2024, DOI:10.32604/phyton.2024.048770

Abstract Sorghum (Sorghum bicolor L. Moench) is an essential food crop for more than 750 million people in tropical and sub-tropical dry climates of Africa, India, and Latin America. The domestic sorghum market in Indonesia is still limited to the eastern region (East Nusa Tenggara, West Nusa Tenggara, Java, and South Sulawesi). Therefore, it is crucial to carry out sorghum research on drylands. This research aimed to investigate the effect of sorghum genotype and planting distance and their interaction toward growth and sorghum’s productivity in the Gunungkidul dryland, Yogyakarta, Indonesia. In addition, the farm business analysis, including… More >

Qirui Zhong¹, Xiaogang Cheng^2,*, Yuxin Song³, Han Wang²

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3417-3433, 2024, DOI:10.32604/cmc.2024.049992

Abstract This paper introduces an intelligent computational approach for extracting salient objects from images and estimating their distance information with PTZ (Pan-Tilt-Zoom) cameras. PTZ cameras have found wide applications in numerous public places, serving various purposes such as public security management, natural disaster monitoring, and crisis alarms, particularly with the rapid development of Artificial Intelligence and global infrastructural projects. In this paper, we combine Gauss optical principles with the PTZ camera’s capabilities of horizontal and pitch rotation, as well as optical zoom, to estimate the distance of the object. We present a novel monocular object distance… More >

Cyril Enault^*

Revue Internationale de Géomatique, Vol.33, pp. 77-92, 2024, DOI:10.32604/rig.2024.046591

Abstract La théorie égocentrée est aujourd’hui bien connue des éthologues et des psychologues mais moins diffusée chez les géographes car elle reste encore à l’état de théorie abstraite. Ce papier se propose dans un premier temps de rendre opérationnel cette approche dans le cadre de travaux géographiques à l’échelle de l’individu. Puis, elle envisage d’établir le lien entre l’échelle individu et l’échelle de la ville avec comme objectif de produire des cartes déformées de la ville. More > Graphic Abstract

Jungpil Shin^1,*, Md. Al Mehedi Hasan², Abu Saleh Musa Miah¹, Kota Suzuki¹, Koki Hirooka¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2605-2625, 2024, DOI:10.32604/cmes.2023.046334

Abstract Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing communities. In Japan, approximately 360,000 individuals with hearing and speech disabilities rely on Japanese Sign Language (JSL) for communication. However, existing JSL recognition systems have faced significant performance limitations due to inherent complexities. In response to these challenges, we present a novel JSL recognition system that employs a strategic fusion approach, combining joint skeleton-based handcrafted features and pixel-based deep learning features. Our system incorporates two distinct streams: the first stream extracts crucial handcrafted features, emphasizing the capture of hand and body… More >

Murugan Palanikumar¹, Nasreen Kausar^2,*, Dragan Pamucar^3,4, Seifedine Kadry^5,6,7,*, Chomyong Kim⁸, Yunyoung Nam⁹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3353-3385, 2024, DOI:10.32604/cmes.2024.031439

Abstract In this article, multiple attribute decision-making problems are solved using the vague normal set (VNS). It is possible to generalize the vague set (VS) and q-rung fuzzy set (FS) into the q-rung vague set (VS). A log q-rung normal vague weighted averaging (log q-rung NVWA), a log q-rung normal vague weighted geometric (log q-rung NVWG), a log generalized q-rung normal vague weighted averaging (log Gq-rung NVWA), and a log generalized q-rung normal vague weighted geometric (log Gq-rung NVWG) operator are discussed in this article. A description is provided of the scoring function, accuracy function and operational laws of the log q-rung… More >

Wei Wang¹, Yang Yu¹, Simin Luo^2,*, Wenlin Liu², Wei Tang¹, Yuanbo Ye¹

Energy Engineering, Vol.121, No.2, pp. 315-337, 2024, DOI:10.32604/ee.2023.042082

Abstract As an effective approach to achieve the “dual-carbon” goal, the grid-connected capacity of renewable energy increases constantly. Photovoltaics are the most widely used renewable energy sources and have been applied on various occasions. However, the inherent randomness, intermittency, and weak support of grid-connected equipment not only cause changes in the original flow characteristics of the grid but also result in complex fault characteristics. Traditional overcurrent and differential protection methods cannot respond accurately due to the effects of unknown renewable energy sources. Therefore, a longitudinal protection method based on virtual measurement of current restraint is proposed More >

Hong Qian^1,2, Haixin Wang^1,*, Guangji Wang³, Qingyun Yan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 679-698, 2024, DOI:10.32604/cmes.2023.043377

Abstract This study presents a proposed method for assessing the condition and predicting the future status of condensers operating in seawater over an extended period. The aim is to address the problems of scaling and corrosion, which lead to increased loss of cold resources. The method involves utilising a set of multivariate feature parameters associated with the condenser as input for evaluation and trend prediction. This methodology offers a precise means of determining the optimal timing for condenser cleaning, with the ultimate goal of improving its overall performance. The proposed approach involves the integration of the… More >