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Journal of Advanced Ceramics 2024年第1期13卷 44-52页

作者： Zheng Wu Taosheng Xu Luohong Zhang Tingting Liu Zhansheng Wu Gangqiang Zhu Yanmin Jia school of Environmental and Chemical Engineering Xi’an Key Laboratory of Textile Chemical Engineering AuxiliariesXi’an Polytechnic UniversityXi’an 710048China school of Physics and Information Technology Shaanxi Normal UniversityXi’an 710062China

The strong pyrocatalytic dye decomposition of the BaTiO_(3)/Pr_(2)O_(3) heterojunction catalyst under cold–hot alternation conditions has been demonstrated in this *** pure BaTiO_(3) nanofibers,~54%rhodamine B(RhB)dye is decomposed under the cold–hot alternation of 29–57℃.With the loading content of Pr_(2)O_(3) increases from 0 to 4 wt%,the pyrocatalytic decomposition ratio of RhB solution increases first and then decreases,eventually achieving a maximum of 91%at 3 wt%.The enhanced pyrocatalytic performance after loading Pr_(2)O_(3) can be attributed to an internal electric field of the heterojunction,which effectively separates positive and negative *** strongly pyrocatalytic performance of BaTiO_(3)/Pr_(2)O_(3) makes it hopeful for applications in the dye wastewater treatment through harvesting the environmental cold–hot temperature alternation thermal energy in future.

关键词： pyroelectric materials BaTiO_(3) pyrocatalysis BaTiO_(3)/Pr_(2)O_(3)heterojunction dye decomposition

A Real-Time Small Target Vehicle Detection Algorithm with an Improved YOLOv5m Network Model

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Computers, Materials & Continua 2024年第1期78卷 303-327页

作者： Yaoyao Du xiangkui Jiang school of Automation Xi’an University of Posts and TelecommunicationsXi’an710121China

To address the challenges of high complexity,poor real-time performance,and low detection rates for small target vehicles in existing vehicle object detection algorithms,this paper proposes a real-time lightweight architecture based on You Only Look Once(YOLO)***,a lightweight upsampling operator called Content-Aware Reassembly of Features(CARAFE)is introduced in the feature fusion layer of the network to maximize the extraction of deep-level features for small target vehicles,reducing the missed detection rate and false detection ***,a new prediction layer for tiny targets is added,and the feature fusion network is redesigned to enhance the detection capability for small ***,this paper applies L1 regularization to train the improved network,followed by pruning and fine-tuning operations to remove redundant channels,reducing computational and parameter complexity and enhancing the detection efficiency of the *** is conducted on the VisDrone2019-DET *** experimental results show that the proposed algorithmreduces parameters and computation by 63.8% and 65.8%,*** average detection accuracy improves by 5.15%,and the detection speed reaches 47 images per second,satisfying real-time *** with existing approaches,including YOLOv5m and classical vehicle detection algorithms,our method achieves higher accuracy and faster speed for real-time detection of small target vehicles in edge computing.

关键词： Vehicle detection YOLOv5m small target channel pruning CARAFE

Study on carbon emission calculation method and carbon reduction indexes of urban building stock

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Science China(Technological Sciences) 2024年第9期67卷 2706-2726页

作者： YANG Liu ZHANG Nan LU Mei LUO Zhixing DOU Mei State Key Laboratory of Green Building Xi’an University of Architecture and TechnologyXi’an 710055China school of Architecture Xi’an University of Architecture and TechnologyXi’an 710055China school of Language Literature and LawXi’an University of Architecture and TechnologyXi’an 710055China school of Management Xi’an University of Architecture and TechnologyXi’an 710055China China Southwest Architectural Design and Research Institute Corp.Ltd. Chengdu 610041China

Carbon emissions associated with buildings are a major source of urban emissions. To put forward the methods and strategies to curb carbon emissions from urban building stock, it is not only necessary to establish a carbon emission calculation method for fine statistical analysis, but also to evaluate carbon emissions of urban planning schemes with applicable indexes. Currently,researches mainly focus on carbon emissions of individual buildings. When expanded to urban building stock, the calculation faces the lack of basic data, inadequate spatial analysis and unspecific carbon reduction indexes. Therefore, this study proposes a bottom-up calculation method for urban building stock, conducts spatial analysis based on carbon balance of urban grids, reveals the coupling mechanism between urban carbon reduction indexes and grid carbon emissions, and systematically establishes a carbon-reduction-oriented urban planning method that comprises calculation, analysis and evaluation, which is applied to xi'an,China. This study provides a theoretical reference for cities to formulate carbon reduction targets and implement planning strategies by evaluating and predicting carbon emissions from urban building stock.

关键词： carbon emissions urban building stock calculation method carbon reduction index

Deep-reinforcement-learning-based UAV autonomous navigation and collision avoidance in unknown environments

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Chinese Journal of Aeronautics 2024年第3期37卷 237-257页

作者： Fei WANG xiaoping ZHU Zhou ZHOU Yang TANG school of Astronautics Northwestern Polytechnical UniversityXi’an 710072China school of Aeronautics Northwestern Polytechnical UniversityXi’an 710072China

In some military application scenarios,Unmanned Aerial Vehicles(UAVs)need to perform missions with the assistance of on-board cameras when radar is not available and communication is interrupted,which brings challenges for UAV autonomous navigation and collision *** this paper,an improved deep-reinforcement-learning algorithm,Deep Q-Network with a Faster R-CNN model and a Data Deposit Mechanism(FRDDM-DQN),is proposed.A Faster R-CNN model(FR)is introduced and optimized to obtain the ability to extract obstacle information from images,and a new replay memory Data Deposit Mechanism(DDM)is designed to train an agent with a better *** training,a two-part training approach is used to reduce the time spent on training as well as retraining when the scenario *** order to verify the performance of the proposed method,a series of experiments,including training experiments,test experiments,and typical episodes experiments,is conducted in a 3D simulation *** results show that the agent trained by the proposed FRDDM-DQN has the ability to navigate autonomously and avoid collisions,and performs better compared to the FRDQN,FR-DDQN,FR-Dueling DQN,YOLO-based YDDM-DQN,and original FR outputbased FR-ODQN.

关键词： Faster R-CNN model Replay memory Data Deposit Mechanism(DDM) Two-part training approach Image-based Autonomous Navigation and Collision Avoidance(ANCA) Unmanned Aerial Vehicle(UAV)

Self-powered and self-sensing devices based on piezoelectric energy harvesting

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Science China(Technological Sciences) 2024年第6期67卷 1631-1667页

作者： CHEN GanTong ZHU Yue HUANG DongMei ZHOU Shengxi school of Aeronautics Northwestern Polytechnical UniversityXi’an710072China school of Mathematics and Statistics Xidian UniversityXi’an710071China

Wearable devices,interactive human-machine interface equipment,wireless sensors,and small-scale cleaning devices play crucial roles in biomedical implantation,disease treatment,health monitoring,environmental purification,*** devices require a sustainable energy source to work *** the consideration of the global energy crisis and environmental pollution,researchers are exploring new,stable,and environmentally friendly methods to power these low-powered *** energy is one of the most abundant natural energy *** mechanical energy from the ambient environment or host structures into electrical energy via the direct piezoelectric effect is an efficient energy harvesting *** paper reviews the application of advanced piezoelectric materials,and small-scale self-powered and self-sensing piezoelectric devices at the cubic centimeter scale in energy harvesting and health monitoring of human,animal,machinery,roads,bridges,as well as the pollutant degradation of the *** of these devices have the capability to not only harvest mechanical energy but also enable real-time monitoring and analysis of the electrical signals generated by the direct piezoelectric effect,facilitating prompt decision-making and appropriate *** addition,potential challenges and future prospects of small-scale self-powered and self-sensing piezoelectric devices are discussed.

关键词： piezoelectric energy harvesting self-powered self-sensing wearable devices implantable devices

Optimization of ferroelectricity and endurance of hafnium zirconium oxide thin films by controlling element inhomogeneity

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Journal of Advanced Ceramics 2024年第7期13卷 1023-1031页

作者： Fei Yan Ke Cao Yang Chen Jiajia Liao Min Liao yichun Zhou Shaanxi Key Laboratory of high-Orbits-Electron Materials and Protection Technology for Aerospace School of Advanced Materials and NanotechnologyXidian UniversityXi’an 710126China xi’an Key Laboratory of Reconfigurable Chip and Materials School of Advanced Materials and NanotechnologyXidian UniversityXi’an 710126China Frontier Research Center of Thin Films and Coatings for Device Applications Academy of Advanced Interdisciplinary ResearchXidian UniversityXi’an 710126China

Ferroelectric thin films based on HfO_(2) have garnered increasing attention worldwide,primarily due to their remarkable compatibility with silicon and scalability,in contrast to traditional perovskite-structured ferroelectric ***,significant challenges remain in their widespread commercial utilization,particularly concerning their notable wake-up effect and limited *** address these challenges,we propose a novel strategy involving the inhomogeneous distribution of Hf/Zr elements within thin films and explore its effects on the ferroelectricity and endurance of Hf_(0.5)Zr_(0.5)O_(2) thin *** techniques such as grazing incidence X-ray diffraction,transmission electron microscopy,and piezoresponse force microscopy,we investigated the structural characteristics and domain switching behaviors of these *** experimental results indicate that the inhomogeneous distribution of Hf/Zr contributes to improving the frequency stability and endurance while maintaining a large remnant polarization in Hf_(0.5)Zr_(0.5)O_(2) ferroelectric thin *** adjusting the distribution of Zr/Hf within the Hf_(0.5)Zr_(0.5)O_(2) thin films,significant enhancements in the remnant polarization(2P_(r)>35μC/cm2)and endurance(>109)along with a reduced coercive voltage can be ***,the fabricated ferroelectric thin films also exhibit high dielectric tunability(≥26%)under a low operating voltage of 2.5 V,whether in the wake-up state or *** study offers a promising approach to optimize both the ferroelectricity and endurance of HfO_(2)-based thin films.

关键词： ferroelectric capacitors thin films ferroelectricity hafnium zirconium oxide

New low-rank optimization model and algorithms for spectral compressed sensing

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Science China Mathematics 2024年第10期67卷 2409-2432页

作者： Zai Yang Xunmeng Wu Zongben Xu school of Mathematics and Statistics Xi'an Jiaotong UniversityXi'an 710049China

In this paper, we investigate the recovery of an undamped spectrally sparse signal and its spectral components from a set of regularly spaced samples within the framework of spectral compressed sensing and super-resolution. We show that the existing Hankel-based optimization methods suffer from the fundamental limitation that the prior knowledge of undampedness cannot be exploited. We propose a new low-rank optimization model partially inspired by forward-backward processing for line spectral estimation and show its capability to restrict the spectral poles to the unit circle. We present convex relaxation approaches with the model and show their provable accuracy and robustness to bounded and sparse noise. All our results are generalized from one-dimensional to arbitrary-dimensional spectral compressed sensing. Numerical simulations are provided to corroborate our analysis and show the efficiency of our model and the advantageous performance of our approach in terms of accuracy and resolution compared with the state-of-the-art Hankel and atomic norm methods.

关键词： low-rank double Hankel model doubly enhanced matrix completion line spectral estimation spectral compressed sensing Kronecker's theorem

A dynamical neural network approach for distributionally robust chance-constrained Markov decision process

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Science China Mathematics 2024年第6期67卷 1395-1418页

作者： Tian xia Jia Liu Zhiping Chen school of Mathematics and Statistics Xi’an Jiaotong UniversityXi’an710049China

In this paper,we study the distributionally robust joint chance-constrained Markov decision *** the logarithmic transformation technique,we derive its deterministic reformulation with bi-convex terms under the moment-based uncertainty *** cope with the non-convexity and improve the robustness of the solution,we propose a dynamical neural network approach to solve the reformulated optimization *** results on a machine replacement problem demonstrate the efficiency of the proposed dynamical neural network approach when compared with the sequential convex approximation approach.

关键词： Markov decision process chance constraints distributionally robust optimization moment-based ambiguity set dynamical neural network

Regulating the conductance of tungsten diselenide by oxygen plasma and improving its electrical stability by encapsulation

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Nano Research 2024年第4期17卷 3253-3260页

作者： Zhaofang Cheng Shaodan He Shimin Zhang Shijun Duan Min Wang Ziyu Liu Rong Zhang Wenya Qiang Xudong Zhang Minggang xia MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter School of PhysicsXi’an Jiaotong UniversityXi’an 710049China Department of Applied Physics School of PhysicsXi’an Jiaotong UniversityXi’an 710049China Shaanxi Province Key Laboratory of Quantum Information and Optoelectronic Quantum Devices School of PhysicsXi’an Jiaotong UniversityXi’an 710049China

Two-dimensional(2D)tungsten selenide(WSe_(2))is promising candidate material for future electronic applications,owing to its potential for ultimate device *** improving the electronic performance of WSe_(2)-based field-effect transistors(FETs),the modification of surface properties is *** this study,the seamless structural phase transition in WSe_(2) lattice is achieved by soft oxygen plasma,regulating the electrical conductance of WSe_(2)-based *** found that during the soft oxygen plasma treatment with optimal processing time,the generated oxygen ions can substitute some selenium atoms and thus locally modify the bond length,inducing 2H→1T phase transition in WSe_(2) with seamless *** mosaic structures have been proven to tailor the electronic structure and increase the hole carrier concentration inside WSe_(2),significantly increasing the channel conductance of WSe_(2) *** the further increase of the oxygen plasma treatment time,the creation of more selenium vacancy defects leads to the electronic doping,resulting in the reduction of *** from the hexagonal boron nitride(h-BN)encapsulation to interrupt the partial structural relaxation from 1T to 2H phase,our WSe_(2) FET exhibits high electronic stability with conductance of 6.8×10^(-4) S,which is about four orders of magnitude higher than 2H WSe_(2)(5.8×10^(-8) S).This study could further broaden the WSe_(2) FETs in applications for functionalization and integration in electronics.

关键词： tungsten selenide(WSe2) structural phase transition oxygen plasma conductance hexagonal boron nitride(h-BN)encapsulation

Learning to sample initial solution for solving 0-1 discrete optimization problem by local search

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Science China Mathematics 2024年第6期67卷 1317-1340页

作者： xin Liu Jianyong Sun Zongben Xu school of Mathematics and Statistics Xi’an Jiaotong UniversityXi’an710049China

Local search methods are convenient alternatives for solving discrete optimization problems(DOPs).These easy-to-implement methods are able to find approximate optimal solutions within a tolerable time *** is known that the quality of the initial solution greatly affects the quality of the approximated solution found by a local search *** this paper,we propose to take the initial solution as a random variable and learn its preferable probability *** aim is to sample a good initial solution from the learned distribution so that the local search can find a high-quality *** develop two different deep network models to deal with DOPs established on set(the knapsack problem)and graph(the maximum clique problem),*** deep neural network learns the representation of an optimization problem instance and transforms the representation to its probability *** results show that given the initial solution sampled from the learned probability distribution,a local search method can acquire much better approximate solutions than the randomly-sampled initial solution on the synthesized knapsack instances and the Erd?s-Rényi random graph ***,with sampled initial solutions,a classical genetic algorithm can achieve better solutions than a random initialized population in solving the maximum clique problems on DIMACS ***,we emphasize that the developed models can generalize in dimensions and across graphs with various densities,which is an important advantage on generalizing deep-learning-based optimization algorithms.

关键词： discrete optimization deep learning graph convolutional network local search