Abdullrahman A. Al-Shamma’a¹, Hassan M. Hussein Farh^1,*, Ridwan Taiwo², Al-Wesabi Ibrahim³, Abdulrhman Alshaabani¹, Saad Mekhilef ⁴, Mohamed A. Mohamed^5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1303-1347, 2025, DOI:10.32604/cmes.2025.071302 - 26 November 2025

Abstract Optimal sizing and allocation of distributed generators (DGs) have become essential computational challenges in improving the performance, efficiency, and reliability of electrical distribution networks. Despite extensive research, existing approaches often face algorithmic limitations such as slow convergence, premature stagnation in local minima, or suboptimal accuracy in determining optimal DG placement and capacity. This study presents a comprehensive scientometric and systematic review of global research focused on computer-based modelling and algorithmic optimization for renewable DG sizing and placement. It integrates both quantitative and qualitative analyses of the scholarly landscape, mapping influential research domains, co-authorship structures, the More >

Vicky Anand¹, Priyadarshani Rajput¹, Tatiana Minkina¹, Saglara Mandzhieva¹, Santosh Kumar², Avnish Chauhan³, Vishnu D. Rajput^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.5, pp. 1339-1365, 2025, DOI:10.32604/phyton.2025.063927 - 29 May 2025

Abstract The digital revolution in agriculture has introduced data-driven decision-making, where artificial intelligence, especially machine learning (ML), helps analyze large and varied data sources to improve soil quality and crop growth indices. Thus, a thorough evaluation of scientific publications from 2007 to 2024 was conducted via the Scopus and Web of Science databases with the PRISMA guidelines to determine the realistic role of ML in soil health and crop improvement under the SDGs. In addition, the present review focused to identify and analyze the trends, challenges, and opportunities associated with the successful implementation of ML in… More >

Petrayuna Dian Omega¹, Joniarto Parung^1,*, Listyo Yuwanto¹, Yuh-Shan Ho^2,*

International Journal of Mental Health Promotion, Vol.26, No.10, pp. 817-836, 2024, DOI:10.32604/ijmhp.2024.056501 - 31 October 2024

Abstract Background: This study aimed to conduct a bibliometric analysis of positive mental health, focusing on citation performance, article title, abstract, author keywords, Keyword Plus, and their development trends. The novelty of this study is a pioneer within the field of positive mental health. Therefore, it delivered new ideas for researchers and practitioners who had concerns about positive mental health in terms of trends research which covered recommended articles and the research focus in recent years. Methods: The data were retrieved on 30 April 2024 from the Social Sciences Citation Index (SSCI) of Clarivate Analytics’ Web of… More >

Shirley Qi-Yu Sun¹, Anson Chiu-Yan Tang², Qing Wang¹, Loretta Yuet-Foon Chung^1,*, Regina Lai-Tong Lee^3,4,*

International Journal of Mental Health Promotion, Vol.24, No.6, pp. 795-810, 2022, DOI:10.32604/ijmhp.2022.024841 - 28 September 2022

Abstract There are increasing concerns about internet gaming disorder (IGD). No review of existing studies has systematically analyzed and visualized the trends of IGD and those early identification of symptoms related to IGD behaviors. This critical review focuses on the emerging trends for early identification of symptoms related to IGD behaviors in papers published in Web of Science Core Collection from 2009 to 2021 by scientometric analysis and critical review. Scientometric data analysis technique includes co-occurrence analysis, cluster analysis and burst analysis of authors, countries, keywords and co-citation to visualize those contributing and associated factors to… More >

Meixiang Chen¹, Hong Yang¹, Zhengda Song¹, Yonghua Gu^1,#,*, Yuhong Zheng^1,2, Jiangwei Zhu³, Aiwu Wang⁴, Li Fu^5,#,*

Phyton-International Journal of Experimental Botany, Vol.90, No.5, pp. 1507-1518, 2021, DOI:10.32604/phyton.2021.015723 - 27 May 2021

Abstract Opuntia Milpa Alta is a cactus cultivated, domesticated, hybridized and selected from the plant Opuntia ficus-indica by Mexican agricultural experts, which can be used as fruit and vegetable. Opuntia Milpa Alta leaves and fruit are superior to wild varieties and suitable for storage and transportation. In 1998, Opuntia Milpa Alta was introduced to China from Mexico by the Quality Product Development Center of the Ministry of Agriculture of China. Up to now, the Opuntia Milpa Alta has been cultivated on a certain scale in China. This study aims to identify the research progress and development trends… More >

Muhammad Shaheen^1,*, Ali Ahsan², Saeed Iqbal³

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 873-885, 2021, DOI:10.32604/iasc.2021.016622 - 20 April 2021

Abstract While there are several Scientometrics that can be used to assess the quality of the scientific work published in journals and conferences, yet; their validity and suitability is a great concern for stakeholders from both academia and industry. Different organizations have a different set of criteria for assessing the journals publishing scientific content. This is mostly based on the information generated from Scientometrics. A unified journal ranking system is therefore required that is acceptable to all concerned. This paper, collects data concerning Scientometrics for unified assessment of journals and proposes a mechanism of assessment using… More >

Asaph Armando Jacinto*, Márcia Aparecida da Silva Spinacé*

Journal of Renewable Materials, Vol.7, No.5, pp. 429-440, 2019, DOI:10.32604/jrm.2019.04427

Abstract The nanocellulose is a material that has gained much attention in the recent years. So, the relevance of Brazil in this field was evaluated concerning the scientific publications in Web of Science. Next, the Brazilian groups were mapped using a bibliometric procedure on these data. Then, more factors were analyzed from them too. They were the sources to extract the nanocellulose in Brazil, the methods to do it, the characterizations to determine its dimensions and the funding agencies of these researches. The results identified 69 Brazilian groups. Besides, the bacterial cellulose was the most common More >