Article
Computer Science, Artificial Intelligence
Jean-Rassaire Fouefack, Bhushan Borotikar, Marcel Luthi, Tania S. Douglas, Valerie Burdin, Tinashe E. M. Mutsvangwa
Summary: In model-based medical image analysis, the shape of structures, relative pose, and image intensity profiles are important features that can be modeled separately through statistical models. This study presents a statistical modeling method called Dynamic multi feature-class Gaussian process models (DMFCGPM) that combines shape, pose, and intensity features in a continuous domain using deformation fields. The method is validated using synthetic data and experiments on CT images, and shows robust and accurate performance.
MEDICAL IMAGE ANALYSIS
(2023)
Article
Engineering, Electrical & Electronic
Zihan Meng, Shouxiang Wang, Qianyu Zhao, Zhijie Zheng, Liang Feng
Summary: Reliability evaluation is crucial for electricity-gas-heat integrated energy systems. This paper focuses on user experience, introducing reliability modeling and evaluation indexes for energy consumption, highlighting the importance of considering user perspective in the evaluation process. The proposed method aims to improve the effectiveness of reliability evaluation for multi-energy consumption systems.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Automation & Control Systems
Yuping Wang, Miaoxin Chang, Xianzhen Huang, Yuxiong Li, Jiwu Tang
Summary: This paper studies the method for tool wear prediction in CNC machining systems. A new model based on a multi-stage Wiener process is proposed and validated. The results show that the proposed model enables us to make more economical maintenance by delaying the tool replacement time with fewer degradation data.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Transportation Science & Technology
Georges Sfeir, Filipe Rodrigues, Maya Abou-Zeid
Summary: The study introduces a method that integrates Gaussian Processes into latent class choice models to improve discrete representations of unobserved heterogeneity. By probabilistically assigning individuals to behaviorally homogeneous clusters and simultaneously estimating class-specific choice models, it achieves a more complex and flexible representation of heterogeneity.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Green & Sustainable Science & Technology
Jie Yang, Wenya Xu, Kai Ma, Conghui Li
Summary: This paper proposes a three-stage multi-energy sharing strategy to address the multi-energy imbalance problem among energy hubs using a peer-to-peer trading mode. The strategy determines the shareable energy quantity for participating energy hubs and employs multi-bilateral negotiations to determine the optimal energy trading price. The buyer and seller agents design the optimal energy sharing trading strategy for all energy hubs. Experimental results demonstrate that the pricing mechanism improves fairness and enhances social welfare, validating the effectiveness of the three-stage multi-energy sharing trading strategy.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Engineering, Manufacturing
Jiaying Deng, Hossein Ghasemkhani, Yong Tan, Arvind K. Tripathi
Summary: The choice of market mechanism is crucial for the success of an online marketplace. In the case of peer-to-peer (P2P) lending platforms, the auction lending model has been found to be more socially beneficial compared to the fixed price lending model. To improve allocative efficiency in P2P lending markets, the authors propose an artifact that dynamically estimates borrower reputation using transactional data. They show that accounting for reputation enhances the model's explanatory power and allows for empirical modeling of reputation evolution and impact in online platforms.
PRODUCTION AND OPERATIONS MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Fahad Mazaed Alotaibi, Israr Ullah, Shakeel Ahmad
Summary: This study investigates a Markov chain based analytical model for a multi-class queuing system, where users are categorized and serviced based on strict QoS and priority constraints. The developed model can guide the development of advanced connection admission control, efficient resource dimensioning, and capacity planning for queuing systems.
Article
Energy & Fuels
Cephas Samende, Jun Cao, Zhong Fan
Summary: This paper investigates the energy cost minimization problem for prosumers participating in peer-to-peer energy trading. A multi-agent deep deterministic policy gradient algorithm is proposed to learn optimal energy trading decisions, while distribution network tariffs are introduced to satisfy the distribution network constraints.
Article
Mathematics
Shengli Lv
Summary: This paper analyzed a multi-machine repairable system with one unreliable server and one repairman. The study focused on the steady-state availability and transient reliability of the machines and server, as well as the mean time to the first breakdown and failure. The effects of system parameters on various performance indices were visualized through case analysis and numerical illustration.
Article
Energy & Fuels
Peyman Bayat, Hossein Afrakhte, Pezhman Bayat
Summary: This paper introduces a comprehensive energy management system (CEMS) to enhance the resilience of microgrid and distribution network in a multi-microgrid system against unexpected events. The CEMS includes networked operation mode (NOM) and individual operation mode (IOM) to improve the overall system's reliability and ensure reliable power supply for consumers during emergency periods.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2021)
Article
Automation & Control Systems
Carlos Villacampa-Calvo, Bryan Zaldivar, Eduardo C. Garrido-Merchan, Daniel Hernandez-Lobato
Summary: This paper focuses on multi-class classification problems and uses Gaussian processes as the underlying classifier. It investigates the impact of considering noise in input attributes on the performance of machine learning methods, and evaluates the proposed methods through several experiments on synthetic and real data sets.
JOURNAL OF MACHINE LEARNING RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Bo Li, Zeshui Xu, Yixin Zhang
Summary: This paper presents a multi-stage medical scheme selection process, introducing preference relations under the probabilistic linguistic term environment, checking and repairing inconsistent relations to obtain comprehensive assessment, and combining historical data and evaluations using BM operator and Choquet integral to select suitable medical schemes.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Engineering, Industrial
Xi Gu
Summary: This paper focuses on the study of Reconfigurable Manufacturing Systems (RMSs) and develops methods to analyze their performance, using models such as discrete-time Markov chains and decomposition methods to provide accurate results in production rate calculations.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Review
Education, Scientific Disciplines
Emerald Jenkins, Rita D'Aoust, Sabrina Elias, Hae Ra Han, Phyllis Sharps, Carmen Alvarez
Summary: Peer review of teaching is crucial for enhancing faculty confidence, improving teaching quality, and fostering discussion among colleagues. The development of a peer review process using a Five-Step Design for Six Sigma methodology could serve as a model for other higher education institutions to enhance teaching excellence and student experience in the face of evolving teaching platforms and student demographics.
NURSE EDUCATION TODAY
(2021)
Review
Psychology, Multidisciplinary
Dana Strauss, Sophia Gran-Ruaz, Muna Osman, Monnica T. Williams, Sonya C. Faber
Summary: This article proposes key mechanisms underlying racial bias and censorship in the editorial and peer review process, using compelling case study examples from APA and other leading international journals. It highlights the need for more diverse researchers, perspectives, and topics in the field of psychology to meet the mental health needs of communities of colour. The article calls for several recommendations to ensure the APA can prioritize racial equity throughout the editorial and review process.
FRONTIERS IN PSYCHOLOGY
(2023)
Article
Computer Science, Interdisciplinary Applications
Ruediger Mutz
Summary: Diversity is a central concept in ecology, social sciences, and bibliometrics. This study proposes a probability-based diversity indicator that reconceptualizes the components of diversity as entropy masses, addressing an inconsistency issue in existing indicators. The overall diversity of research projects in terms of entropy is estimated, with journal articles being the most balanced output type across research areas.
Article
Multidisciplinary Sciences
Lutz Bornmann, Robin Haunschild, Kevin Boyack, Werner Marx, Jan C. Minx
Summary: This study examines the connection between climate change research and policy-making. It found that climate change papers cited in policy documents receive more citations on average. The study also observed an impact of international climate policy cycles on policy document publication and identified similar research fields between the scientific and policy communities.
Article
Multidisciplinary Sciences
Alexander Tekles, Katrin Auspurg, Lutz Bornmann
Summary: Previous studies have shown that papers written by male scientists receive more citations than those written by female scientists, and this could be explained by a gender homophily bias, where scientists tend to cite others of the same gender. However, this bias may have been overestimated as previous studies have overlooked structural aspects, such as the gender composition of research topics. When controlling for research topics at a detailed level, there is little evidence to support a gender homophily bias in citation decisions. This study highlights the importance of controlling for gendered specialization in research topics when investigating gender bias in science.
Review
Computer Science, Interdisciplinary Applications
Hamdi A. Al-Jamimi, Galal M. BinMakhashen, Lutz Bornmann
Summary: The governments of emerging market countries have invested significantly in scientific research, resulting in high research volume, impact, and international collaboration. It is important to evaluate their research performance using indicators such as productivity, impact, and collaboration. These indicators are crucial for developing research directions, policies, and meeting management needs.
Article
Communication
Iman Tahamtan, Lutz Bornmann
Summary: The normative theory of citing views citations as rewarding tools, while the social constructivist theory sees them as persuasion tools. However, existing theories fail to fully explain all citation motives, leading to the proposal of a new theory called social systems citation theory (SSCT). SSCT integrates previous theories and models, distinguishing authors' motives as belonging to psychological systems and publications with citation links as belonging to social science systems. The theory explains the autonomous operation of these systems and their interaction, offering a framework for empirical bibliometric studies.
PROFESIONAL DE LA INFORMACION
(2022)
Article
Computer Science, Information Systems
Lutz Bornmann, Robin Haunschild, Werner Marx
Summary: Reference Publication Year Spectroscopy (RPYS) is a bibliometric method used to reveal the historical roots of research topics or fields. It identifies the most frequently referenced publications within a specific reference publication year, instead of the most highly cited papers. This study demonstrates how RPYS can be applied to identify important researchers, institutions, and countries in breakthrough research, using the example of climate modeling and global warming prediction.
JOURNAL OF INFORMATION SCIENCE
(2023)
Article
Multidisciplinary Sciences
Lutz Bornmann, Christian Ganser, Alexander Tekles
Summary: In this study, we empirically investigated the influence of numerical information as anchors, such as citation impact, on the assessment of cited papers. We conducted a survey among corresponding authors and assigned them to different treatment groups receiving various additional numerical information. Our results suggest that the assessment of paper quality is influenced by the citation impact information, but not by other numerical information like an access code or journal impact.
Article
Computer Science, Interdisciplinary Applications
Anton Gruber, Alexander Tekles, Lutz Bornmann
Summary: This paper aims to analyze the academic roots of political scientist John J. Mearsheimer using the method of Reference Publication Year Spectroscopy (RPYS). By compiling a list of his most cited works and examining temporal peaks, the study reveals both the foundation of his theory of International Relations and his focus on current events and conflicts.
Article
Computer Science, Interdisciplinary Applications
Robin Haunschild, Lutz Bornmann
Summary: Many altmetric studies have examined the frequency of paper mentions on Twitter. This study investigates the citations of tweets in papers to assess their potential relevance. However, the findings suggest a low number of citations and indicate that tweets are more often used as study objects rather than influential content. The subject areas with the most citations of tweets are Social Sciences, Arts and Humanities, and Medicine, with COVID-19/corona pandemic being the dominant topic.
JOURNAL OF INFORMETRICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Lutz Bornmann, Sabine Gralka, Felix de Moya Anegon, Klaus Wohlrabe
Summary: One of the core indicators in scientometrics is the number of papers published by a unit within a given period. To properly assess such indicators, it is necessary to consider the unit's available resources. This study introduces a new input indicator, the number of unique authors mentioned on the institutions' papers, and calculates efficiency scores for over 3100 institutions from the higher education sector using this new indicator and output indicators. The results show a strong correlation between the new input indicator and institutional staff numbers.
JOURNAL OF INFORMETRICS
(2023)
Article
Multidisciplinary Sciences
Lutz Bornmann, Christian Ganser
Summary: This study aims to empirically examine the assessment of scientific papers using the anchoring-and-adjustment heuristic. By surveying corresponding authors and analyzing their adjustments to the anchor value, the research investigates whether the evaluation can be influenced by both quality-related information and unrelated numerical factors. The study seeks to shed light on whether bibliometrics or other numerical measures create the social order they intend to measure.
Article
Computer Science, Interdisciplinary Applications
Robin Haunschild, Lutz Bornmann
Summary: This study proposes a citation-free method for identifying potential young talented individuals based on their early publication performance. Three different indicators and their combinations were used to define potential talent. The best performing indicator combination was applied to identify young potentially talented individuals who published their first paper between 2007-2011, resulting in a set of 46,200 individuals that can be downloaded for free.
JOURNAL OF INFORMETRICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Christian Leibel, Lutz Bornmann
Summary: The paper provides a comprehensive review of the original disruption index (DI1) and its variants in scientometrics. It explains the technical and theoretical properties of these indices and examines their validity and limitations. The review highlights the higher convergent validity of modified index variants compared to DI1 and emphasizes the need for further research on the validity of disruption scores.
Article
Information Science & Library Science
Felix Bittmann, Alexander Tekles, Lutz Bornmann
Summary: The paper discusses the use of statistical matching as an alternative to linear regression models in bibliometrics to estimate effects and remove bias. Through analyzing milestone papers and nonmilestone papers, the study examines disruption indicators and evaluates the performance of different matching algorithms in terms of covariate balancing and disruptiveness assessment. Results show that coarsened exact matching (CEM) and entropy balancing (EB) perform well in balancing covariates, while DI5 and DEP are effective in evaluating disruptiveness of published papers.
QUANTITATIVE SCIENCE STUDIES
(2022)
Article
Information Science & Library Science
Robin Haunschild, Lutz Bornmann, Devendra Potnis, Iman Tahamtan
Summary: This study investigates public attention to opioid scholarly publications on Twitter using topic networks. The results show that Twitter users mainly discuss opioid publications using generic terms, and there is a significant presence of bot accounts in the discussion. The study also finds that topic networks generated by bot and nonbot accounts overlap, indicating that excluding bot accounts may not be necessary for generating topic networks.
QUANTITATIVE SCIENCE STUDIES
(2022)
Article
Computer Science, Interdisciplinary Applications
Hao Teng, Nan Wang, Hongyu Zhao, Yingtong Hu, Haitao Jin
Summary: In this paper, a new method based on functional semantic knowledge (FOP) is proposed for patent similarity calculation. Furthermore, patent STS datasets are processed and released as benchmarks. Preliminary results show that FOP-based methods are more suitable for STS tasks when combined with IPC codes, weights' assignments, and patent pre-trained vectors.
JOURNAL OF INFORMETRICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Cristina Urdiales, Eduardo Guzman
Summary: Subject categorization of scientific publications is important for evaluating paper quality. Traditional mechanisms for categorization have been questioned, and a new method based on association rules is proposed. The method automatically defines publication categories based on the repetition or absence of relevant descriptors. The empirical study in the field of Physical Sciences and Engineering shows that the proposed method produces consistent and suitable categorization results.
JOURNAL OF INFORMETRICS
(2024)
