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 in this paper. The positive… More >

Abid Sohail¹, Ammar Haseeb¹, Mobashar Rehman^2,*, Dhanapal Durai Dominic³, Muhammad Arif Butt⁴

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3603-3618, 2021, DOI:10.32604/cmc.2021.017795

Abstract There are numerous application areas of computing similarity between process models. It includes finding similar models from a repository, controlling redundancy of process models, and finding corresponding activities between a pair of process models. The similarity between two process models is computed based on their similarity between labels, structures, and execution behaviors. Several attempts have been made to develop similarity techniques between activity labels, as well as their execution behavior. However, a notable problem with the process model similarity is that two process models can also be similar if there is a structural variation between them. However, neither a benchmark… More >

Shazia Saqib¹, Allah Ditta², Muhammad Adnan Khan^1,*, Syed Asad Raza Kazmi³, Hani Alquhayz⁴

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2061-2076, 2021, DOI:10.32604/cmc.2020.013905

Abstract Human activity detection and recognition is a challenging task. Video surveillance can benefit greatly by advances in Internet of Things (IoT) and cloud computing. Artificial intelligence IoT (AIoT) based devices form the basis of a smart city. The research presents Intelligent dynamic gesture recognition (IDGR) using a Convolutional neural network (CNN) empowered by edit distance for video recognition. The proposed system has been evaluated using AIoT enabled devices for static and dynamic gestures of Pakistani sign language (PSL). However, the proposed methodology can work efficiently for any type of video. The proposed research concludes that deep learning and convolutional neural… More >