Academic literature on the topic 'Citation manipulation'

Twenty two science Russian periodicals in informatics and library studies are selected for the bibliometrical analysis of key journal indicators, including publication activity of the same journals’ editorial staff. For the first time for domestic journals, the study reveals hidden self-citation when editorial members include links to their journal from other publications. The available instruments of scientometrical databases, including Web of Science and Scopus, and the national system Russian Science Citation Index do not enable to identify this form of self-citation. The mentioned manipulations are aimed at boosting journal rating. In several cases, intensive and unjustified citation by journals’ editorial staff in other periodicals which we consider the violation of publication ethical principles, is revealed.

In today's digital era, user-computer interface experiences are increasingly intuitive and immersive. Tangible User Interface (TUI) enables users to interact with digital content through physical manipulation. This design paradigm, emphasizing interaction with physical objects, garners significant attention from academia and industry. Literature review helps to strengthen the knowledge framework of research topics by reviewing relevant literature, and it aids in summarizing the current research status. Although this field has achieved certain research results and practical applications after years of development, the extensive and interdisciplinary nature of the literature makes it difficult to systematically analyze the research hotspots and trends through traditional literature review methods alone. Therefore, this study utilizes relevant literature collected from the Web of Science database as the data source. Through bibliometric analysis, it systematically reviews and visually analyzes the field of TUI to identify the progress and future trends over the past two decades.Method: This paper employs bibliometrics, content analysis, and information visualization. Bibliometrics, first proposed by Pritchard in 1969, quantitatively analyzes diverse literature data to uncover patterns and insights. To obtain more rigorous and comprehensive data indicators, this study integrates the use of CiteSpace and VOSviewer. CiteSpace and VOSviewer are bibliometric analysis tools that run on JAVA programs and can effectively establish mapping relationships between literature knowledge units. Visual analysis and research lineage sorting are conducted across the distribution of literature outputs by year, country, research organization, keyword clustering, and co-citation of literature entries in this study. This study selects the Web of Science core database for retrieval. The search strategy is set as TS=((tangible user interface design OR TUI design OR physical user interface design)). The five major citation indexes in the WOS database, including SSCI, SCI-Expanded, A&HCI, CPCI-S, and CPCI-SSH, are selected as retrieval sources. To avoid the loss of interdisciplinary literature, no reduction is made to the literature sources. The retrieved literature is exported to a txt file in the format of "full records and cited references". Irrelevant articles, such as those deviating from the research topic or containing duplicate data, are removed. In the end, a total of 3994 articles were obtained (from 2004 to 2023).Conclusion： The output of literature related to TUI peaked in 2019 and has since exhibited a declining trend. Few institutions are highly productive in this field, with Massachusetts Institute of Technology, Carnegie Mellon University, University of Washington, Tsinghua University, University of Tokyo being core institutions in academia. Through keyword clustering analysis, TUI research content can be classified into four categories: #1 Physical Interaction Technology, #2 Sensory Simulation, #3 Intelligent IoT, #4 User Behavior Study. Analysis of the evolution of TUI hotspots reveals that the current focus of most scholars is on enhancing TUI's application in virtual reality and augmented reality environments, as well as innovative applications in education and entertainment. Future research may concentrate on the integration of TUI with artificial intelligence technology, human-centered computing, and human-robot interaction.

<title>ABSTRACT</title> <p>Off-road mobility for an individual autonomous ground vehicle (AGV) can be severely limited by extreme environments (such as muddy patches or steep cliffs in off-road terrain). However, when operating as a group, cooperation between the AGVs can be leveraged to overcome such limitations. Traditionally cooperation has been achieved through information sharing, enabling the AGVs to “avoid” the extreme environments. In this paper we propose to achieve such cooperation through physical energy sharing, where the AGVs can “recover” from these environment scenarios. Specifically, we propose the use of a robotic manipulator (RM) that connects a disabled or degraded AGV with an operational AGV. A fleet level controller is proposed. The AGVs and the RM are modeled in Modelica, and integrated with the controller to perform simulations. We demonstrate collaborative movement in two scenarios, namely crossing a muddy patch and climbing a steep cliff. In each scenario the individual vehicle fails to complete the mission when degraded, however the cooperative fleet succeeds, while also enabling the degraded AGV to regain operational status.</p> <p><bold>Citation:</bold> M. Ashley, D. McMullan, S. Gopalswamy, “Physically Cooperating Autonomous Ground Vehicles,” In <italic>Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium</italic> (GVSETS), NDIA, Novi, MI, Aug. 15-17, 2023.</p>