Article
Mathematics
Leslie Hogben, Mark Hunnell, Kevin Liu, Houston Schuerger, Ben Small, Yaqi Zhang
Summary: The paper establishes the upper bound for the positive semidefinite propagation time of a graph in terms of its positive semidefinite zero forcing number. Two methods and algorithms for transforming one positive semidefinite zero forcing set into another are presented to prove this bound. Consequences of the bound, including a tight Nordhaus-Gaddum sum upper bound on positive semidefinite propagation time, are established.
DISCRETE MATHEMATICS
(2022)
Article
Chemistry, Multidisciplinary
Wei-Chang Yeh, Wenbo Zhu, Chia-Ling Huang, Tzu-Yun Hsu, Zhenyao Liu, Shi-Yi Tan
Summary: Social networks have become increasingly important and popular in modern times, playing a vital role in various organizations. This study proposes a new algorithm to improve the efficiency of information propagation in social networks by evaluating the propagation probability. The experimental results show that this algorithm effectively increases the efficiency of information propagation in social networks.
APPLIED SCIENCES-BASEL
(2022)
Article
Optics
Kurt Schab, Lukas Jelinek, Miloslav Capek, Mats Gustafsson
Summary: Upper bounds on the focusing efficiency of aperture fields and lens systems are proposed using integral equation representations of Maxwell's equations and Lagrangian duality. Two forms of focusing efficiency based on lens exit plane fields and optimal polarization currents are considered. The bounds are compared with classical prescriptions and inverse design lenses, showing that unbounded focusing efficiency can be achieved with lens exit plane fields. Additionally, aperture fields based on time-reversal do not necessarily yield optimal lens focusing efficiency in near-field focusing.
Article
Computer Science, Artificial Intelligence
Yuhua Li, Ruixuan Li, Xiaoqing Xiong, Xiwu Gu, Tianan Liang, Mingli Xu, Yumeng Yuan
Summary: In this study, a new Multi-Topical Authority sensitive Independent Cascade model is proposed and compared with other algorithms on real-world datasets, demonstrating its effectiveness.
APPLIED INTELLIGENCE
(2021)
Article
Mathematics, Applied
Neil Jiuyu Fan, Peter Long Guo
Summary: This paper explores the relationship between permutations and composition patterns, determining lower and upper bounding polynomials for different permutations and composition patterns. The results show that under specific conditions of avoiding certain permutation and composition patterns, the minimum and maximum values of key polynomials can be determined.
SCIENCE CHINA-MATHEMATICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Dejian Yu, Anran Fang
Summary: This study developed an effective topic ranking model, 4EFRRank, which takes into account the reinforcing effect of academic entities on topic influence. Experimental results show that the 4ER-Rank model successfully combines classic co-word metrics and effectively reflects high citation topics.
JOURNAL OF INFORMETRICS
(2023)
Article
Physics, Multidisciplinary
P. Helander, G. G. Plunk
Summary: Rigorous upper bounds on the growth rate of local gyrokinetic instabilities in magnetized plasmas are derived from the evolution equation for the Helmholtz free energy. These bounds apply to both electrostatic and electromagnetic instabilities, regardless of the number of particle species, their collision frequency, and the geometry of the magnetic field. These bounds not only apply to linear instabilities, but also set an upper limit on the nonlinear growth of the free energy.
PHYSICAL REVIEW LETTERS
(2021)
Article
Physics, Multidisciplinary
Matthias Christandl, Roberto Ferrara, Karol Horodecki
Summary: Quantum key distribution (QKD) and device-independent quantum key distribution (DIQKD) are methods of distributing keys using quantum particles, with DIQKD having a stronger security concept than QKD. Studies show that the achievable rate of DIQKD may exceed the upper bounds possible for QKD in specific quantum states or channels, and in some cases, the QKD rate is significant while the DIQKD rate is negligible.
PHYSICAL REVIEW LETTERS
(2021)
Article
Computer Science, Artificial Intelligence
Yu Shao, Ling Chen, Yixin Chen, Wei Liu
Summary: With the rapid growth of the internet, social networks have become an important platform for information exchange and propagation. However, negative information also spreads in social networks, causing a lot of problems. This study proposes a method that combines network sparsification and stratification to effectively locate the sources of negative influence using information from a few observed nodes. Experimental results demonstrate that this method can accurately identify the sources of influence in social networks, outperforming other algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Qisong Wu, Yin Fu, Yimin D. Zhang, Moeness G. Amin
Summary: This paper proposes a structured and clustered multi-task compressive sensing framework that exploits the inner sparse pattern and statistical dependence between tasks. By adopting a signal model with spike-and-slab priors and Dirichlet Process priors, the method achieves enhanced sparse reconstruction performance.
Article
Computer Science, Information Systems
WeiMin Li, Zheng Li, Alex Munyole Luvembe, Chao Yang
Summary: The paper proposes an influence maximization algorithm based on the Gaussian propagation model, which improves effectiveness and efficiency through multidimensional space modeling and parameter control.
INFORMATION SCIENCES
(2021)
Article
Optics
Miklos Ronto, Peter Jeszenszki, Edit Matyus, Eli Pollak
Summary: The development of computational resources allows us to determine the upper bounds of atomic and molecular energies accurately. However, the error bounds for computed energies are only available as estimates. In this paper, the Pollak-Martinazzo lower-bound theory combined with correlated Gaussian basis sets is used to achieve subparts-per-million convergence of ground and excited-state energies for He, Li, and Be atoms. The quality of these lower bounds is comparable to the upper bounds obtained from the Ritz method. These results demonstrate the power of lower bounds in providing precise estimates of atomic energies.
Article
Physics, Mathematical
Benjamin Landon, Philippe Sosoe
Summary: We provide a proof of an upper tail bound in two classes of stationary models in the KPZ universality class, which is of the correct order up to a constant factor in the exponent. The proof is based on an exponential identity derived by Rains for last passage percolation with exponential weights, and recently re-derived by Emrah-Janjigian-Seppailainen (EJS). Our proof follows a similar approach for both classes of models, utilizing only general properties of monotonicity and convexity, suggesting its applicability to other stationary models.
COMMUNICATIONS IN MATHEMATICAL PHYSICS
(2023)
Article
Environmental Sciences
Grant R. McDermott
Summary: The study shows that most climate skeptics tend to update their beliefs about climate sensitivity based on available evidence from instrumental climate data and scientific literature. However, belief convergence among skeptics is influenced by the strength of prior beliefs, making it increasingly difficult to convince remaining dissenters. Despite this, deviations from the Bayesian ideal can be accommodated within the same conceptual framework, providing insights into climate skepticism as a social phenomenon.
Article
Engineering, Chemical
Ali Hayek, Yasser A. Shalabi, Abdulkarim Alsamah
Summary: This paper discusses the trade-off relationship between permeability and selectivity of polymeric membranes prepared from glassy polymers, as well as the evaluation methods and standards for the performance in pure-gas and mixed-gas separations. New upper bounds for CO2/CH4, H2S/CH4, and combined acid gas sour mixed-gas separations based on experimental data are proposed for potential future industrial applications.
SEPARATION AND PURIFICATION TECHNOLOGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Xiang Zhu, Zhefeng Wang, Yu Yang, Bin Zhou, Yan Jia
JOURNAL OF COMPUTATIONAL SCIENCE
(2018)
Article
Computer Science, Information Systems
Yu Yang, Xiangbo Mao, Jian Pei, Xiaofei He
ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA
(2020)
Article
Computer Science, Interdisciplinary Applications
Hongbin Zhang, Yu Yang, Feng Wu
Summary: In this paper, we study a single-batch-processing machine scheduling problem by considering a just-in-time criterion. We propose a mixed-integer linear model to model the problem and design two priority rules for job sorting. We also propose two heuristic algorithms and a lower bound method for constructing and improving near-optimal schedules. The extensive numerical experiments demonstrate the effectiveness and efficiency of our approaches.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Engineering, Industrial
Yang Hu, Feng Wu, Yu Yang, Yongkui Liu
Summary: This paper proposes a hybrid two-stage approach to address the temporal dynamic service composition problem in cloud manufacturing by incorporating tensor factorization and many-objective evolutionary optimization. Experimental results demonstrate the superior performance of the proposed approach over other benchmarks.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Engineering, Industrial
Yang Hu, Yu Yang, Feng Wu
Summary: Cloud manufacturing is a promising paradigm for manufacturing, but existing studies ignore its dynamic nature and the complexity of revenue management caused by re-entrant services.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Management
Hongbin Zhang, Yu Yang, Feng Wu
Summary: We investigate a general single-batch-processing machine scheduling problem and propose a 3-step method to solve the NP-hard problem. We first find the optimal and near-optimal schedules for a given job sequence, and then iteratively improve the schedules. For the restricted problem, we use a dynamic programming algorithm and span-limit tree search approach to obtain the optimal schedule.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2024)
Article
Computer Science, Cybernetics
Jun Wang, Yu Yang, Qi Liu, Zheng Fang, Shujuan Sun, Yabo Xu
Summary: Understanding user engagement in social media is crucial for successful influencer marketing campaigns. This article focuses on studying the factors that impact user engagement with opinion leaders' blogs on two popular social media platforms in China. By analyzing characteristics and semantics, the study uncovers common and different factors that influence user engagement on the two platforms. The findings provide valuable insights for advertisers planning influencer marketing campaigns on these platforms.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Tongwen Wu, Yu Yang, Yanzhi Li, Huiqiang Mao, Liming Li, Xiaoqing Wang, Yuming Deng
Summary: The paper discusses the importance of predicting future customer orders for retailers and introduces a generative model to capture order distribution, utilizing representation learning and SGD algorithm to optimize prediction performance.
KDD '21: PROCEEDINGS OF THE 27TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING
(2021)
Article
Computer Science, Information Systems
Tianyuan Jin, Yu Yang, Renchi Yang, Jieming Shi, Keke Huang, Xiaokui Xiao
Summary: This paper introduces ROI-Greedy, an algorithm for solving the unconstrained submodular maximization with modular costs problem, which provides a strong approximation guarantee and outperforms competing methods in terms of efficiency and solution quality. Extensive experiments on benchmark datasets demonstrate the efficacy of ROI-Greedy in finding near-optimal solutions.
PROCEEDINGS OF THE VLDB ENDOWMENT
(2021)
Article
Computer Science, Information Systems
Zicun Cong, Lingyang Chu, Yu Yang, Jian Pei
Summary: The paper addresses the issue of generating counterfactual explanations for test data failing the KS test. It introduces the concept of most comprehensible counterfactual explanations and develops an algorithm called MOCHE to efficiently tackle the problem. Empirical studies demonstrate the effectiveness, efficiency, and scalability of the proposed approach.
PROCEEDINGS OF THE VLDB ENDOWMENT
(2021)
Article
Computer Science, Artificial Intelligence
Yu Yang, Jian Pei
Summary: Influence analysis aims at detecting influential vertices in networks and utilizing them in cost-effective strategies. As networks evolve, incorporating network evolution into influence analysis presents new challenges. Researchers need to consider the rapid changes in networks and the incomplete understanding of network evolution by people.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2021)
Proceedings Paper
Computer Science, Theory & Methods
Yu Yang, Zhefeng Wang, Tianyuan Jin, Jian Pei, Enhong Chen
PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM '19)
(2019)
Article
Computer Science, Information Systems
Lingyang Chu, Zhefeng Wang, Jian Pei, Yanyan Zhang, Yu Yang, Enhong Chen
PROCEEDINGS OF THE VLDB ENDOWMENT
(2019)
Article
Computer Science, Information Systems
Lingyang Chu, Yanyan Zhang, Yu Yang, Lanjun Wang, Jian Pei
PROCEEDINGS OF THE VLDB ENDOWMENT
(2019)
Proceedings Paper
Computer Science, Information Systems
Yu Yang, Lingyang Chu, Yanyan Zhang, Zhefeng Wang, Jian Pei, Enhong Chen
2018 IEEE 34TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE)
(2018)