Computers & Graphics celebrates its golden anniversary in 2025. Motivated by this special event, this study presents a comprehensive bibliometric analysis of the journal, identifying key research trends, frequently cited authors, institutions, countries, and major citation patterns. The work retrieves data from the Web of Science (WoS) core collection and Scopus databases and utilizes bibliometric tools such as VOS viewer and bibliometrix software. We analyse the keyword evolution; co-citation networks and bibliographic coupling of the documents published in Computers & Graphics . The distribution of topics indicates increased attention to artificial intelligence–based methods, including deep learning, point cloud processing, and virtual reality, alongside established rendering and simulation techniques. Additionally, the bibliometric analysis of productive authors, institutions and countries, indicate increased publication and citation activity associated with institutions in Asian countries, especially China. Beyond broader trends, this study also highlights Computers & Graphics’ recent initiatives that emphasize transparency and reproducibility, such as the graphics replicability stamp and the special sections, which bridge academic conferences and high-quality journal publications. This study serves as a reference for researchers seeking to understand the historical trajectory, emerging trends, and evolving editorial priorities in computer graphics research.

This article presents an improved Hamiltonian control law (HCL) with load current sensorless ability for multiphase parallel converters in electric vehicle applications. On one hand, the proposed control approach has a significant advantage in handling constant power load (CPL) that occurs in the situation of the vehicle, which is a dangerous situation that can cause oscillations and uncertainty. On the other hand, the load current observer is applied with HCL to improve the efficiency and reliability of the converter system. In addition, by eliminating the need for current sensors, the cost and size of the converter system are reduced, while maintaining accurate current control. Moreover, the difference flatness approach has been applied to generate the current reference resulting in regulating the DC bus voltage. Finally, the multiphase two-quadrant converter driving by the proposed control law has been evaluated through experimental tests. The obtained experimental results demonstrate the excellent performance of the multiphase two-quadrant converter with CPL thereby confirming the efficacy of the proposed approach.

The compromise solution of the multi-criteria decision-making (MCDM) problem by the existing VIKOR method for Pythagorean fuzzy sets (PyFSs) is not closest to the positive ideal solution. This is because the defining function for VIKOR does not obey the axioms for a dissimilarity measure. Thus in this context, the existing notion of dissimilarity measures and the VIKOR method are controversial. This study aims to provide a new dissimilarity measure and refine the VIKOR method for PyFSs accordingly. We define a new dissimilarity measure for PyFSs and refine the existing VIKOR method. We discuss the additional properties of dissimilarity measures and improve the ideas of remoteness and ranking indexes. We provide numerical examples to support the analysis and findings of our study. Finally, we solve the MCDM problems to illustrate the proposed method.

Despite the importance of divergence measures, the literature has not provided a satisfactory formulation for the case of q-rung orthopair fuzzy set. This paper criticizes the existing attempts in terms of respect of the basic axioms of a divergence measure. Then new improved, axiomatically supported divergence measures for qROFSs are proposed. Additional properties of the new divergence measures are discussed to guarantee their good performance. The transformation relationships with entropy and dissimilarity measures are debated. The multiattribute border approximation area comparison decision method is extended based on the suggested divergence measures, and it is applied to the selection of all-rounder cricketer for a team.

The q-rung orthopair fuzzy set (qROFS) defined by Yager is a generalization of Atanassov intuitionistic fuzzy set and Pythagorean fuzzy sets. In this paper, we define the knowledge measure for qROFS by using the tangent inverse function. This is the first approach to quantify the knowledge associated with qROFS. The membership and nonmembership functions as well as the hesitancy margin are used to define the knowledge measure which makes it capable of considering both knowledge and fuzziness. The entropy measure which is the dual of the knowledge measure is also defined. The properties of the proposed knowledge measure with graphical explanations are discussed. An application of the proposed knowledge measure in multiattribute group decision making problem under confidence level approach is given.