Abraham Lamboro^1,3,*, Songnan Yang¹, Xueying Li¹, Dan Yao², Jun Zhang^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.9, pp. 2489-2501, 2023, DOI:10.32604/phyton.2023.029492

Abstract The effect of beta-lactam antibiotics on shoot induction and plantlet regeneration from cotyledonary nodes was tested using two peanut cultivars. The culture media contained 4 mg/L 6-benzylaminopurine (BAP) as the main growth regulator. Various concentrations (100–600 mg/L) of cefotaxime, carbenicillin, and timentin were applied in the culture media. In all the tested media, there were no significant differences in the shoot induction as compared to the control. However, little phytotoxic effect was observed at higher concentrations of these antibiotics in the shoot elongation media. Under shoot elongation medium, shoots turned brownish and partly died at higher concentrations where shooting rates… More >

Jintao Fu¹, Yong Zhou^1,*, Qian Qiu², Guangwei Xu³, Neng Wan³

Journal of Quantum Computing, Vol.4, No.3, pp. 147-163, 2022, DOI:10.32604/jqc.2022.038358

Abstract In the field of computer research, the increase of data in result of societal progress has been remarkable, and the management of this data and the analysis of linked businesses have grown in popularity. There are numerous practical uses for the capability to extract key characteristics from secondary property data and utilize these characteristics to forecast home prices. Using regression methods in machine learning to segment the data set, examine the major factors affecting it, and forecast home prices is the most popular method for examining pricing information. It is challenging to generate precise forecasts since many of the regression… More >

Yuyan Luo^1,2, Xiaoxu Zhang^1,*, Tao Tong¹, Yong Qin^3,*, Zheng Yang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 2049-2076, 2023, DOI:10.32604/cmes.2023.025413

Abstract Graduate education is the main way to train high-level innovative talents, the basic layout to cope with the global talent competition, and the important cornerstone for implementing the innovation-driven development strategy and building an innovation-driven country. Therefore, graduate education is of great remarkably to the development of national education. As an important manifestation of graduate education, the quality of a graduate thesis should receive more attention. It is conducive to promoting the quality of graduates by supervising and examining the quality of the graduate thesis. For this purpose, this work is based on text mining, expert interviews, and questionnaire surveys… More >

Yue Liang, Wenxuan Dai, Wei Chen^*

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.10, pp. 2639-2659, 2023, DOI:10.32604/fdmp.2023.027622

Abstract Glass powder of various particle sizes (2, 5, 10 and 15 μm) has been assessed as a possible cement substitute for mortars. Different replacement rates of cement (5%, 10%, 15%, and 20%) have been considered for all particle sizes. The accessible porosity, compressive strength, gas permeability and microstructure have been investigated accordingly. The results have shown that adding glass powder up to 20% has a significantly negative effect on the porosity and compressive strength of mortar. The compressive strength initially rises with a 5% replacement and then decreases. Similarly, the gas permeability of the mortar displays a non-monotonic behavior; first, it… More >

S. Priya¹, R. S. Ponmagal^2,*

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1895-1907, 2023, DOI:10.32604/iasc.2023.039814

Abstract Handling service access in a cloud environment has been identified as a critical challenge in the modern internet world due to the increased rate of intrusion attacks. To address such threats towards cloud services, numerous techniques exist that mitigate the service threats according to different metrics. The rule-based approaches are unsuitable for new threats, whereas trust-based systems estimate trust value based on behavior, flow, and other features. However, the methods suffer from mitigating intrusion attacks at a higher rate. This article presents a novel Multi Fractal Trust Evaluation Model (MFTEM) to overcome these deficiencies. The method involves analyzing service growth,… More >

Narit Hnoohom¹, Sakorn Mekruksavanich², Anuchit Jitpattanakul^3,4,*

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1275-1291, 2023, DOI:10.32604/iasc.2023.038584

Abstract In recent years, as intelligent transportation systems (ITS) such as autonomous driving and advanced driver-assistance systems have become more popular, there has been a rise in the need for different sources of traffic situation data. The classification of the road surface type, also known as the RST, is among the most essential of these situational data and can be utilized across the entirety of the ITS domain. Recently, the benefits of deep learning (DL) approaches for sensor-based RST classification have been demonstrated by automatic feature extraction without manual methods. The ability to extract important features is vital in making RST… More >

Yasushi Koito^a,*

Frontiers in Heat and Mass Transfer, Vol.13, pp. 1-6, 2019, DOI:10.5098/hmt.13.26

Abstract This paper describes extended numerical analyses on vapor pressure distribution in a centered-wick ultra-thin heat pipe. Analyses were conducted by using a three-dimensional model developed by the author. Numerical results were obtained changing design parameters and operating conditions of the heat pipe. Discussion was made on the heat transfer limit as well as the vapor pressure drop. Moreover, a simple method was also presented to evaluate the vapor pressure drop in the ultra-thin heat pipe. Calculated results with the simple method agreed in 10 % with the three-dimensional numerical results. More >

Niharika Gupta¹, Baijnath Kaushik¹, Mohammad Khalid Imam Rahmani^2,*, Saima Anwar Lashari^2,*

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 347-366, 2023, DOI:10.32604/cmc.2023.038864

Abstract Diabetes is one of the fastest-growing human diseases worldwide and poses a significant threat to the population’s longer lives. Early prediction of diabetes is crucial to taking precautionary steps to avoid or delay its onset. In this study, we proposed a Deep Dense Layer Neural Network (DDLNN) for diabetes prediction using a dataset with 768 instances and nine variables. We also applied a combination of classical machine learning (ML) algorithms and ensemble learning algorithms for the effective prediction of the disease. The classical ML algorithms used were Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbor (KNN),… More >

Jingang Kim, Suengbum Lim, Taejin Lee^*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 471-490, 2023, DOI:10.32604/csse.2023.038413

Abstract AI-related research is conducted in various ways, but the reliability of AI prediction results is currently insufficient, so expert decisions are indispensable for tasks that require essential decision-making. XAI (eXplainable AI) is studied to improve the reliability of AI. However, each XAI methodology shows different results in the same data set and exact model. This means that XAI results must be given meaning, and a lot of noise value emerges. This paper proposes the HFD (Hybrid Feature Dropout)-based XAI and evaluation methodology. The proposed XAI methodology can mitigate shortcomings, such as incorrect feature weights and impractical feature selection. There are… More >

Jiangyuan Yao¹, Weiping Yang¹, Shuhua Weng¹, Minrui Wang¹, Zheng Jiang², Deshun Li^1,*, Yahui Li³, Xingcan Cao⁴

Computer Systems Science and Engineering, Vol.47, No.1, pp. 741-755, 2023, DOI:10.32604/csse.2023.031531

Abstract Software-defined networking (SDN) is widely used in multiple types of data center networks, and these distributed data center networks can be integrated into a multi-domain SDN by utilizing multiple controllers. However, the network topology of each control domain of SDN will affect the performance of the multi-domain network, so performance evaluation is required before the deployment of the multi-domain SDN. Besides, there is a high cost to build real multi-domain SDN networks with different topologies, so it is necessary to use simulation testing methods to evaluate the topological performance of the multi-domain SDN network. As there is a lack of… More >