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Utilizing Multipath Effects for Mobile Charging

IEEE Transactions on Mobile computing 2025年

作者： Gao, Jing Wu, Die Zhang, Linglin Li, Jingwen Yang, Jin Peng, Jian Liu, Tang Sichuan Normal University College of Computer Science Sichuan Chengdu610101 China Sichuan University School of Cyber Science and Engineering Chengdu610065 China Sichuan University College of Computer Science Chengdu610065 China Sichuan Normal University Visual Computing and Virtual Reality Key Laboratory of Sichuan Province Sichuan Chengdu610068 China

Recently, Wireless Rechargeable Sensor Networks (WRSNs) have emerged as a promising solution to address the energy limitations of wireless sensor networks. In practical applications of WRSNs, environmental objects are ubiquitous, reflecting radio waves and causing them to reach sensors via multiple paths. These multipath effects significantly impact the power intensity received by sensors. In this paper, we study a fundamental issue of charGing schEduling with mulTipath effectS (GETS), that is, how to schedule a mobile charger by comprehensively considering the multipath effects to maximize the overall charging utility. To this end, we first establish a charging model with environmental objects to investigate the impact of multipath effects on power distribution. Then, we propose a charging scheduling scheme that not only selects a series of sojourn locations for the MC (Mobile Charger) to maximize the total power received by nearby sensors but also construct a charging path that avoids environmental objects. We conduct extensive simulations as well as indoor and outdoor field experiments to evaluate the performance of our scheme. The results demonstrate that, on average, our scheme outperforms baseline algorithms by 48.87%. © 2002-2012 IEEE.

关键词： Charging stations

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Multi-Disease-Aware Training Strategy for Cardiac MR Image Segmentation

arXiv

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arXiv 2025年

作者： Zheng, Hong Chen, Yucheng Mu, Nan Li, Xiaoning College of Computer Science Sichuan Normal University Chengdu610101 China School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu611756 China Department of Cardiology West China Hospital Sichuan University Chengdu610041 China Visual Computing and Virtual Reality Key Laboratory of Sichuan Province Chengdu610066 China Sichuan 2011 Collaborative Innovation Center for Educational Big Data Chengdu610066 China

Accurate segmentation of the ventricles from cardiac magnetic resonance images (CMRIs) is crucial for enhancing the diagnosis and analysis of heart conditions. Deep learning-based segmentation methods have recently garnered significant attention due to their impressive performance. However, these segmentation methods are typically good at partitioning regularly shaped organs, such as the left ventricle (LV) and the myocardium (MYO), whereas they perform poorly on irregularly shaped organs, such as the right ventricle (RV). In this study, we argue that this limitation of segmentation models stems from their insufficient generalization ability to address the distribution shift of segmentation targets across slices, cardiac phases, and disease conditions. To overcome this issue, we present a Multi-Disease-Aware Training Strategy (MTS) and restructure the introduced CMRI datasets into multi-disease datasets. Additionally, we propose a specialized data processing technique for preprocessing input images to support the MTS. To validate the effectiveness of our method, we performed control group experiments and cross-validation tests. The experimental results show that (1) network models trained using our proposed strategy achieved superior segmentation performance, particularly in RV segmentation, and (2) these networks exhibited robust performance even when applied to data from unknown diseases. Copyright © 2025, The Authors. All rights reserved.

关键词： Image segmentation

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ON THE CONCENTRATION PROPERTIES FOR THE NONLINEAR SCHRDINGER EQUATION WITH A STARK POTENTIAL

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Acta Mathematica Scientia 2011年第5期31卷 1923-1938页

作者：朱世辉张健 Visual Computing and Virtual Reality Key Laboratory Sichuan Normal University College of Mathematics Sichuan University

In this paper, we study blow-up solutions of the Cauchy problem to the L2 critical nonlinear Schrdinger equation with a Stark potential. Using the variational characterization of the ground state for nonlinear Schrdinger equation without any potential, we obtain some concentration properties of blow-up solutions, including that the origin is the blow-up point of the radial blow-up solutions, the phenomenon of L2-concentration and rate of L2-concentration of blow-up solutions.

关键词： nonlinear Schrdinger equation blow-up solution blow-up point L2-concentration concentration compact principle

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LIMITING BEHAVIOR OF BLOW-UP SOLUTIONS OF THE NLSE WITH A STARK POTENTIAL

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Acta Mathematica Scientia 2012年第3期32卷 1181-1192页

作者：朱世辉张健 College of Mathematics and Software Science Sichuan Normal University Visual Computing and Virtual Reality Key Laboratory Sichuan Normal University

This article is concerned with blow-up solutions of the Cauchy problem of critical nonlinear SchrSdinger equation with a Stark potential. By using the variational characterization of corresponding ground state, the limiting behavior of blow-up solutions with critical and small super-critical mass are obtained in the natural energy space ∑ = {u ∈ H^1; fRN ｜x｜^2｜u｜^2dx 〈＋∞）}. Moreover, an interesting concentration property of the blow-up solutions with critical mass is gotten, which reads that ｜u（t, x）｜^2→ ｜｜Q｜｜L^2 2 δx=x1 as t → T.

关键词： Nonlinear Schroedinger equation Stark potential blow-up solution limiting behavior mass concentration

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VARIATIONAL ANALYSIS FOR THE MAXIMAL TIME FUNCTION IN NORMED SPACES

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Acta Mathematica Scientia 2024年第5期44卷 1696-1706页

作者： Ziyi ZHOU Yi JIANG School of Mathematical Sciences Visual Computing and Virtual Reality Key LaboratorySichuan Normal UniversityChengdu610066China

For a general normed vector space,a special optimal value function called a maximal time function is *** covers the farthest distance function as a special case,and has a close relationship with the smallest enclosing ball *** properties of the maximal time function are proven,including the convexity,the lower semicontinuity,and the exact characterizations of its subdifferential formulas.

关键词： maximal time function subdifferential normal cone nonsmooth analysis

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Instability of Standing Wave for the Klein–Gordon–Hartree Equation

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Acta Mathematica Sinica,English Series 2014年第5期30卷 861-871页

作者： Xiao Guang LI Jian ZHANG Yong Hong WU Visual Computing and Virtual Reality Key Laboratory of Sichuan Province Sichuan Normal University College of Mathematics and Software Science Sichuan Normal University Department of Mathematics and Statistics Curtin University of Technology

The instability property of the standing wave uω（t, x） = eiωtφ（x） for the Klein–Gordon– Hartree equation is investigated. For the case N≥3 and w2 〈2/N＋4-γ,it is shown that the standing wave eiwtφ（x） is... 详细信息

关键词： Klein–Gordon–Hartree equation standing waves strong instability

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Real-time controlling of crowd paths via distance propagating

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Journal of Computational Information Systems 2012年第19期8卷 8009-8016页

作者： Wu, He Qi, Li Gang, Lei Chen, Weilong Visual Computing and Virtual Reality Key Laboratory of Sichuan Province Sichuan Normal University Chengdu 610068 China Digital Media Department of Sichuan Normal University Chengdu 610068 China

In this paper, we propose a novel approach for controlling of crowd paths in real-time virtual environments. The proposed algorithm focus on addressing two problems: (1) the grid-based distance propagating for controlling of crowd paths. We propose a grid-based distance propagating algorithm for controlling of crowd paths, which requires no prior knowledge of crowd and obstacles. (2) the penalty function for collision-free. We propose using the penalty function to collision-free, which incorporates safety margins around obstacle using local information. Experimental results show that the proposed algorithm could be used for real-time navigation of many moving crowd in complicated virtual environments. © 2012 Binary Information Press.

关键词： virtual reality

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New characterizations of partial orders induced by a class of non-divisible t-norms

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Soft computing 2024年第17-18期28卷 9107-9114页

作者： Liu, Zhi-Qiang Wang, Xue-Ping School of Mathematical Sciences Sichuan Normal University Chengdu610066 China Visual Computing and Virtual Reality Key Laboratory of Sichuan Province Sichuan Normal University Chengdu610066 China

In this article, we deal with the algebraic structures of the partial orders induced by non-divisible t-norms. We first give a condition for the partial orders induced by non-divisible t-norms being a meet semi-lattice. Then, we show the condition for the partial orders induced by right-continuous t-norms being a lattice, which is very useful for constructing new lattice structures. Finally, an illustrative example is presented. Our results go a further step towards answering the first open problem raised by Karaçal and Kesicioğlu (Kybernetika 47:300-314, 2011). © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Fuzzy logic

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Optimal Control Policy of M/G/1 Queueing System with Delayed Randomized Multiple Vacations Under the Modified Min(N,D)-Policy Control

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Journal of the Operations Research Society of China 2023年第4期11卷 857-874页

作者： Le Luo Ying-Hui Tang Miao-Miao Yu Wen-Qing Wu School of Mathematical Sciences Sichuan Normal UniversityChengdu610068SichuanChina Nanchong Vocational and Technical College Nanchong637000JiangsuChina Visual Computing and Virtual Reality Key Laboratory of Sichuan Province Sichuan Normal UniversityChengdu610068SichuanChina

Based on the number of customers and the server’s workload,this paper proposes a modified Min(N,D)-policy and discusses an M/G/1 queueing model with delayed randomized multiple vacations under such a *** the well-known stochastic decomposition property of the steady-state queue size,the probability generating function of the steady-state queue length distribution is ***,the explicit expressions of the expected queue length and the additional queue length distribution are derived by some algebraic ***,employing the renewal reward theorem,the explicit expression of the long-run expected cost per unit time is ***,we analyze the optimal policy for economizing the expected cost and compare the optimal Min(N,D)-policy with the optimal N-policy and the optimal D-policy by using numerical examples.

关键词： M/G/1 queue Modified Min(N,D)-policy Randomized multiple vacations Queue length generating function Optimal joint control policy

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Unraveling the neural dynamics of mathematical interference in english reading: A novel approach with deep learning and fNIRS data

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Brain Research Bulletin 2025年 227卷 111398-111398页

作者： Zhijie Liang Ling Wang Jianyu Su Bo Sun Daifa Wang Juan Yang School of Computer Science Sichuan Normal UniversityChengdu 610066 China Visual Computing and Virtual Reality Key Laboratory of Sichuan Province Chengdu 610066 China College of Foreign Languages Sichuan Normal UniversityChengdu 610066 China School of Biological Science and Medical Engineering Beihang University Beijing 100083 China

English has emerged as the predominant global language, driving efforts to optimize its acquisition through interdisciplinary cognitive research. While behavioral studies suggest a link between English learning and mathematical cognition, the neural mechanisms underlying this relationship remain poorly understood. To bridge this gap, the present study employs functional near-infrared spectroscopy (fNIRS) to construct a novel dataset on mathematical interference in English acquisition. Utilizing this dataset, a novel deep learning model named AC-LSTM is proposed, amalgamating Transformer and LSTM architectures to identify residual mathematical cognition during the English learning process. The AC-LSTM model achieves an exceptional accuracy rate of 99.8 %, surpassing other machine learning and deep learning models. Moreover, a multi-class classification experiment is conducted to discern algebra, geometry, and quantitative reasoning interference, with the AC-LSTM model achieving the highest accuracy of 75.9 % in this classification task. Furthermore, crucial brain channels for interference detection are pinpointed through grid search, and alterations in vital brain regions (R-Broca and L-Broca) are unveiled via association rule analysis. By integrating fNIRS, deep learning, and data mining techniques, this study delves into cognitive interference in English learning, providing valuable insights for educational neuroscience and data mining research.

关键词： Deep Learning FNIRS English Language Learners Mathematical Interference Data Mining

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