Kai Gao¹, Chin-Chen Chang^1,*, Chia-Chen Lin^2,*

Computer Systems Science and Engineering, Vol., , DOI:10.32604/csse.2024.038308

Abstract Reversible data hiding is a confidential communication technique that takes advantage of image file characteristics, which allows us to hide sensitive data in image files. In this paper, we propose a novel high-fidelity reversible data hiding scheme. Based on the advantage of the multipredictor mechanism, we combine two effective prediction schemes to improve prediction accuracy. In addition, the multihistogram technique is utilized to further improve the image quality of the stego image. Moreover, a model of the grouped knapsack problem is used to speed up the search for the suitable embedding bin in each sub-histogram. Experimental results show that the… More >

Xin Zou¹, Jieyu Zhang¹, Ting Cheng¹, Yangyang Guo¹, Xiao Han¹, Han Liu¹, Yuxing Qin¹, Jie Li², Dabing Xiang^1,*

Phyton-International Journal of Experimental Botany, Vol., , DOI:10.32604/phyton.2024.048469

Abstract To mitigate the wastage of seed resources and reduce the usage of pesticides and fertilizers, seed coating agents have gained popularity. This study employs single-factor and multi-index orthogonal experimental design methods to investigate the seed coating formula and physical properties of Tartary buckwheat. The specific effects of each component on Tartary buckwheat seed germination are analyzed. The findings reveal that the seed coating agent formulated with 1.5% polyvinyl alcohol, 0.15% sodium alginate, 0.2% op-10, 0.1% polyacrylamide, 8% colorant, 3% ammonium sulfate, 1% potassium dihydrogen phosphate, and 0.15% carbendazim exhibits the most effective coating. It demonstrates optimal physical properties and promotes… More >

Hao Bai¹, Beiyuan Liu^2,*, Hongwen Liu³, Jupeng Zeng², Jian Ouyang⁴, Yipeng Liu¹

Energy Engineering, Vol., , DOI:10.32604/ee.2024.049848

Abstract Most ground faults in distribution network are caused by insulation deterioration of power equipment. It is difficult to find the insulation deterioration of the distribution network in time, and the development trend of the initial insulation fault is unknown, which brings difficulties to the distribution inspection. In order to solve the above problems, a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed. Firstly, the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network, and the relational database of the distribution… More >

Jie Ma¹, Pengcheng Yue², Haozheng Yu¹, Yuqing Zhang³, Youwen Zhang¹, Cuiping Li³, Junhui Li^3,*, Wenwen Qin³, Yong Guo¹

Energy Engineering, Vol., , DOI:10.32604/ee.2024.048225

Abstract In recent years, the proportion of installed wind power in the three north regions where wind power bases are concentrated is increasing, but the peak regulation capacity of the power grid in the three north regions of China is limited, resulting in insufficient local wind power consumption capacity. Therefore, this paper proposes a two-layer optimal scheduling strategy based on wind power consumption benefits to improve the power grid's wind power consumption capacity. The objective of the upper model is to minimize the peak-valley difference of the system load, which is mainly to optimize the system load by using the demand… More >

Xiaoqin Ma^1,2, Jun Wang¹, Wenchang Yu¹, Qinli Zhang^1,2,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.049147

Abstract The presence of numerous uncertainties in hybrid decision information systems (HDISs) renders attribute reduction a formidable task. Currently available attribute reduction algorithms, including those based on Pawlak attribute importance, Skowron discernibility matrix, and information entropy, struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values, and attributes with fuzzy boundaries and abnormal values. In order to address the aforementioned issues, this paper delves into the study of attribute reduction within HDISs. First of all, a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring… More >

Haoan Gu¹, Kai Zhu¹, Alfred Strauss², Yehui Shi^3,4, Dragoslav Sumarac⁵, Maosen Cao^1,*

Structural Durability & Health Monitoring, Vol., , DOI:10.32604/sdhm.2024.042388

Abstract Concrete materials and structures are extensively used in transformation infrastructure and they usually bear cracks during their long-term operation. Detecting cracks using deep-learning algorithms like YOLOv3 (You Only Look Once version 3) is a new trend to pursue intelligent detection of concrete surface cracks. YOLOv3 is a typical deep-learning algorithm used for object detection. Owing to its generality, YOLOv3 lacks specific effi- ciency and accuracy in identifying concrete surface cracks. An improved algorithm based on YOLOv3, specialized in the rapid and accurate identification of concrete surface cracks is worthy of investigation. This study proposes a tailored deep-learning algorithm, termed MDN-YOLOv3… More >

R. Sangeetha, Usha Devi Gandhi^*

Computer Systems Science and Engineering, Vol., , DOI:10.32604/csse.2024.052487

Abstract This article has no abstract. More >

Wissal Saadellaoui¹, Samiha Kahlaoui¹, Kheiria Hcini¹, Abir Haddada¹, Noomene Sleimi^2,*, Roberta Ascrizzi³, Guido Flamini³, Fethia Harzallah-Skhiri⁴, Sondes Stambouli-Essassi¹

Phyton-International Journal of Experimental Botany, Vol., , DOI:10.32604/phyton.2024.048110

Abstract In this work, we investigated aroma volatiles emanated by dry roots, stems, leaves, flowers, and fruits of Cardaria draba (L.) Desv. growing wild in Tunisia and its aerial part essential oils (EOs) composition. A total of 37 volatile organic compounds (96.7%–98.9%) were identified; 4 esters, 4 alcohols, 7 hydrocarbons, 12 aldehydes, 5 ketones, 1 lactone, 1 organosulfur compound, 2 organonitrogen compounds, and 1 acid. The hydrocarbons form the main group, representing 49.5%–84.6% of the total detected volatiles. The main constituent was 2,2,4,6,6-pentamethylheptane (44.5%–76.2%) reaching the highest relative percentages. Forty-two compounds were determined in the two fractions of EOs, representing 98.8%… More >

Silvia C. Ramírez-Rodríguez¹, Pablo Preciado-Rangel¹, Marcelino Cabrera-De La Fuente², Susana González-Morales², Hortensia Ortega-Ortiz^3,*

Phyton-International Journal of Experimental Botany, Vol., , DOI:10.32604/phyton.2024.048096

Abstract

Biodegradable nanoparticles such as chitosan nanoparticles (CSNPs) are used in sustainable agriculture since they avoid damage to the environment; CSNPs have positive effects such as the accumulation of bioactive compounds and increased productivity in plants. This study aimed to investigate the impact of applying CSNPs on lettuce, specifically focusing on enzymatic activity, bioactive compounds, and yield. The trial was conducted using a completely randomized design, incorporating CSNPs: 0, 0.05, 0.1, 0.2, 0.4, and 0.8 mg mL⁻¹. The doses of 0.4 mg mL⁻¹ improve yields up to 24.6% increases and 0.1 mg mL⁻¹ of CSNPs increases total phenols by 31.2% and… More >

Chuandong Qin^1,2, Yu Cao^1,*, Liqun Meng¹

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.049228

Abstract Brain tumors come in various types, each with distinct characteristics and treatment approaches, making manual detection a time-consuming and potentially ambiguous process. Brain tumor detection is a valuable tool for gaining a deeper understanding of tumors and improving treatment outcomes. Machine learning models have become key players in automating brain tumor detection. Gradient descent methods are the mainstream algorithms for solving machine learning models. In this paper, we propose a novel distributed proximal stochastic gradient descent approach to solve the L₁-Smooth Support Vector Machine (SVM) classifier for brain tumor detection. Firstly, the smooth hinge loss is introduced to be used… More >