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Optimization of microstructure design for enhanced sensing performance in flexible piezoresistive sensors

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Journal of Advanced Ceramics 2024年第6期13卷 711-728页

作者： Xinghao Fan Hailong Hu Bin Liao Yaqi zhang Fan zhang school of Minerals Processing and Bioengineering Central South UniversityChangsha 410083China Research Institute of Aerospace technology Central South UniversityChangsha 410083China

Flexible piezoresistive strain sensors have received significant attention due to their diverse applications in monitoring human activities and health,as well as in robotics,prosthetics,and human–computer interaction *** the various flexible sensor types,those with microstructure designs are considered promising for strain sensing due to their simple structure,high sensitivity,extensive operational range,rapid response time,and robust *** review provides a concise overview of recent advancements in flexible piezoresistive sensors based on microstructure design for enhanced strain sensing performance,including the impact of microstructure on sensing mechanisms,classification of microstructure designs,fabrication methods,and practical ***,this review delves into the analysis of piezoresistive sensor sensing mechanisms and performance parameters,exploring the relationship between microstructure design and performance ***,an in-depth discussion is presented,focusing on the primary themes of microstructure design classification,process selection,performance characteristics,and specific *** review employs mathematical modeling and hierarchical analysis to emphasize the directionality of different microstructures on performance enhancement and to highlight the performance advantages and applicable features of various microstructure *** conclusion,this review examines the multifunctionality of flexible piezoresistive sensors based on microstructure design and addresses the challenges that still need to be overcome and improved,such as achieving a wide range of stretchability,high sensitivity,and robust *** review summarizes the research directions for enhancing sensing performance through microstructure design,aiming to assist in the advancement of flexible piezoresistive sensors.

关键词： microstructure design sensing performance flexible piezoresistive strain sensors microsensing mechanism

GP‐FMLNet:A feature matrix learning network enhanced by glyph and phonetic information for Chinese sentiment analysis

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CAAI Transactions on Intelligence technology 2024年第4期9卷 960-972页

作者： Jing Li Dezheng zhang Yonghong Xie Aziguli Wulamu Yao zhang school of computer and Communication Engineering University of Science and Technology BeijingBeijingChina Beijing Key Laboratory of Knowledge Engineering for Materials science University of Science and Technology BeijingBeijingChina University of Alberta EdmontonAlbertaCanada

Sentiment analysis is a fine‐grained analysis task that aims to identify the sentiment polarity of a specified *** methods in Chinese sentiment analysis tasks only consider sentiment features from a single pole and scale and thus cannot fully exploit and utilise sentiment feature information,making their performance less than *** resolve the problem,the authors propose a new method,GP‐FMLNet,that integrates both glyph and phonetic information and design a novel feature matrix learning process for phonetic features with which to model words that have the same pinyin information but different glyph *** method solves the problem of misspelling words influencing sentiment polarity prediction ***,the authors iteratively mine character,glyph,and pinyin features from the input comments ***,the authors use soft attention and matrix compound modules to model the phonetic features,which empowers their model to keep on zeroing in on the dynamic‐setting words in various positions and to dispense with the impacts of the deceptive‐setting ***-periments on six public datasets prove that the proposed model fully utilises the glyph and phonetic information and improves on the performance of existing Chinese senti-ment analysis algorithms.

关键词： aspect‐level sentiment analysis deep learning feature extraction glyph and phonetic feature matrix compound learning

Oxygen‑Coordinated Single Mn Sites for Efficient Electrocatalytic Nitrate Reduction to Ammonia

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Nano-Micro Letters 2024年第1期16卷 147-159页

作者： Shengbo zhang Yuankang Zha Yixing Ye Ke Li Yue Lin Lirong Zheng Guozhong Wang Yunxia zhang Huajie Yin Tongfei Shi Haimin zhang Laboratory of Materials Physics Centre for Environmental and Energy NanomaterialsAnhui Key Laboratory of Nanomaterials and NanotechnologyCAS Center for Excellence in NanoscienceInstitute of Solid State PhysicsHFIPSChinese Academy of SciencesHefei 230031People’s Republic of China University of science and technology of china Hefei 230026People’s Republic of China Key Laboratory of Agricultural Sensors Ministry of AgricultureSchool of Information and ComputerAnhui Agricultural UniversityHefei 230026People’s Republic of China Hefei National Research Center for Physical sciences at the Microscale University of Science and Technology of ChinaHefei 230026People’s Republic of China Beijing Synchrotron Radiation Facility Institute of High Energy PhysicsChinese Academy of Sciences19B Yuquan RoadBeijing 100049People’s Republic of China

Electrocatalytic nitrate reduction reaction has attracted increasing attention due to its goal of low carbon emission and environmental ***,we report an efficient NitRR catalyst composed of single Mn sites with atomically dispersed oxygen(O)coordination on bacterial cellulose-converted graphitic carbon(Mn-O-C).Evidence of the atomically dispersed Mn-(O-C_(2))_(4)moieties embedding in the exposed basal plane of carbon surface is confirmed by X-ray absorption *** a result,the as-synthesized Mn-O-C catalyst exhibits superior NitRR activity with an NH_(3)yield rate(RNH_(3))of 1476.9±62.6μg h^(−1)cm^(−2)at−0.7 V(*** hydrogen electrode,RHE)and a faradaic efficiency(FE)of 89.0±3.8%at−0.5 V(***)under ambient ***,when evaluated with a practical flow cell,Mn-O-C shows a high RNH_(3)of 3706.7±552.0μg h^(−1)cm^(−2)at a current density of 100 mA cm−2,2.5 times of that in the H *** in situ FT-IR and Raman spectroscopic studies combined with theoretical calculations indicate that the Mn-(O-C_(2))_(4)sites not only effectively inhibit the competitive hydrogen evolution reaction,but also greatly promote the adsorption and activation of nitrate(NO_(3)^(−)),thus boosting both the FE and selectivity of NH_(3)over Mn-(O-C_(2))_(4)sites.

关键词： Atomically dispersed Oxygen coordination Nitrate reduction reaction In situ spectroscopic studies Hydrogen evolution reaction

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A dual-kernel-based tracking approach for visual target

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science china(Information sciences) 2012年第3期55卷 566-576页

作者： zhang CanLong1,2 , JING ZhongLiang1, JIN Bo1 & LI ZhiXin2 1school of Aeronautics & Astronautics, Shanghai Jiao Tong University, Shanghai 200240, china 2College of computer science & Information technology , Guangxi Normal University, Guilin 541004, china 1. school of Aeronautics & Astronautics Shanghai Jiao Tong University Shanghai 200240 China2. College of Computer Science & Information Technology Guangxi Normal University Guilin 541004 China

A dual-kernel-based tracking approach for visual target is proposed in this paper. The similarity between candidate and target model, and the contrast between candidate and its neighboring background are considered simultaneously when evaluating a target candidate. The similarity is measured by Bhattacharyya coefficient while the contrast is calculated with Jensen-Shannon divergence, and they are adaptively fused into a novel objective function. By maximizing the linear approximation of objective function, a dual-kernel target location-shift relation from current location to a new location is induced. According to the location-shift relation, the optimal target location can be recursively gained in the mean shift procedure. Experimental evaluations on several image sequences demonstrate that the proposed algorithm can gain more accurate target location and better identification power to false target, and it is also robust to deformation and partial occlusion.

关键词： dual-kernel-based tracking mean shift Jensen-Shannon divergence Bhattacharyya coefficient

An Opposition-Based Learning-Based Search Mechanism for Flying Foxes Optimization Algorithm

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computers, Materials & Continua 2024年第6期79卷 5201-5223页

作者： Chen zhang Liming Liu Yufei Yang Yu Sun Jiaxu Ning Yu zhang Changsheng zhang Ying Guo Software College Northeastern UniversityShenyang110169China school of Information science and Engineering Shenyang Ligong UniversityShenyang110159China china Telecom Digital Intelligence technology Co. Ltd.Beijing100035China College of computer science and Engineering Ningxia Institute of Science and TechnologyShizuishan753000China

The flying foxes optimization(FFO)algorithm,as a newly introduced metaheuristic algorithm,is inspired by the survival tactics of flying foxes in heat wave *** preferentially selects the best-performing *** tendency will cause the newly generated solution to remain closely tied to the candidate optimal in the search *** address this issue,the paper introduces an opposition-based learning-based search mechanism for FFO algorithm(IFFO).Firstly,this paper introduces niching techniques to improve the survival list method,which not only focuses on the adaptability of individuals but also considers the population’s crowding degree to enhance the global search ***,an initialization strategy of opposition-based learning is used to perturb the initial population and elevate its ***,to verify the superiority of the improved search mechanism,IFFO,FFO and the cutting-edge metaheuristic algorithms are compared and analyzed using a set of test *** results prove that compared with other algorithms,IFFO is characterized by its rapid convergence,precise results and robust stability.

关键词： Flying foxes optimization(FFO)algorithm opposition-based learning niching techniques swarm intelligence metaheuristics evolutionary algorithms

Numerical Analysis of Perforation during Hydraulic Fracture Initiation Based on Continuous-Discontinuous Element Method

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computer Modeling in Engineering & sciences 2024年第8期140卷 2103-2129页

作者： Rui zhang Lixiang Wang Jing Li Chun Feng Yiming zhang school of Civil and Transportation Engineering Hebei University of TechnologyTianjin300401China Key Laboratory for Mechanics in Fluid Solid Coupling Systems Institute of MechanicsChinese Academy of SciencesBeijing100190China school of Civil Engineering and Architecture Zhejiang Sci-Tech UniversityHangzhou310018China Jinyun Institute Zhejiang Sci-Tech UniversityLishui321400China

Perforation is a pivotal technique employed to establish main flow channels within the reservoir formation at the outset of hydraulic fracturing *** perforation designs is critical for augmenting the efficacy of hydraulic fracturing and boosting oil or gas *** this study,we employ a hybrid finite-discrete element method,known as the continuous–discontinuous element method(CDEM),to simulate the initiation of post-perforation hydraulic fractures and to derive enhanced design *** model incorporates the four most prevalent perforation geometries,as delineated in an engineering technical ***-world perforations deviate from the ideal cylindrical shape,exhibiting variable cross-sectional profiles that typically manifest as an initial constriction followed by an expansion,a feature consistent across all four perforation *** simulations take into account variations in perforation hole geometries,cross-sectional diameters,and perforation *** findings show that perforations generated by the 39g DP3 HMX perforating bullet yield the lowest breakdown pressure,which inversely correlates with increases in sectional diameter and perforation ***,this study reveals the relationship between breakdown pressure and fracture degree,providing valuable insights for engineers and designers to refine perforation strategies.

关键词： Hydraulic fracturing real perforation shape breakdown pressure perforation layout design CDEM

YOLO-MFD:Remote Sensing Image Object Detection with Multi-Scale Fusion Dynamic Head

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computers, Materials & Continua 2024年第5期79卷 2547-2563页

作者： Zhongyuan zhang Wenqiu Zhu school of computer science Hunan University of TechnologyZhuzhou412007China

Remote sensing imagery,due to its high altitude,presents inherent challenges characterized by multiple scales,limited target areas,and intricate *** inherent traits often lead to increased miss and false detection rates when applying object recognition algorithms tailored for remote sensing ***,these complexities contribute to inaccuracies in target localization and hinder precise target *** paper addresses these challenges by proposing a solution:The YOLO-MFD model(YOLO-MFD:Remote Sensing Image Object Detection withMulti-scale Fusion Dynamic Head).Before presenting our method,we delve into the prevalent issues faced in remote sensing imagery ***,we emphasize the struggles of existing object recognition algorithms in comprehensively capturing critical image features amidst varying scales and complex *** resolve these issues,we introduce a novel ***,we propose the implementation of a lightweight multi-scale module called *** module significantly improves the model’s ability to comprehensively capture important image features by merging multi-scale feature *** effectively addresses the issues of missed detection and mistaken alarms that are common in remote sensing ***,an additional layer of small target detection heads is added,and a residual link is established with the higher-level feature extraction module in the backbone *** allows the model to incorporate shallower information,significantly improving the accuracy of target localization in remotely sensed ***,a dynamic head attentionmechanism is *** allows themodel to exhibit greater flexibility and accuracy in recognizing shapes and targets of different ***,the precision of object detection is significantly *** trial results show that the YOLO-MFD model shows improvements of 6.3%,3.5%,and 2.5%over the original YOLOv8 model in Precision,map@0.5 a

关键词： Object detection YOLOv8 multi-scale attention mechanism dynamic detection head

A Case Study of 3D Protein Structure Prediction with Genetic Algorithm and Tabu Search

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Wuhan University Journal of Natural sciences 2011年第2期16卷 125-129页

作者： WANG Ting1,2, zhang Xiaolong1, 3 1. school of computer science and technology, Wuhan University of science and technology, Wuhan 430065, Hubei, china 2. College of Mobile Telecommunications, Chongqing University of Posts and Telecommunications, Chongqing 400065, china 3. State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, china school of computer science and technology Wuhan University of Science and Technology Wuhan Hubei China College of Mobile Telecommunications Chongqing University of Posts and Telecommunications Chongqing China State Key Laboratory of Bioelectronics Southeast University Nanjing China

This paper describes a case study of 3D protein structure prediction of six sequences from protein data bank （PDB） by genetic algorithm and tabu search （GATS）, where off-lattice AB model is considered as a simplified model of protein structure. The lowest-energy values required for forming the native conformation of proteins are searched by GATS, and then the coarse structures （i.e., simplified structure） of the proteins are obtained according to the multiple angle parameters corresponding to the lowest energies. All the coarse structures form single hydrophobic cores surrounded by hydrophilic residues, which stay on the right side of the actual characteristic of protein structure. It demonstrates that this approach can predict the 3D protein structure effectively.

关键词： 3D protein structure off-lattice AB model genetic algorithm and tabu search (GATS)

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Variational Neural Inference Enhanced Text Semantic Communication System

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china Communications 2024年第7期21卷 50-64页

作者： zhang Xi zhang Yiqian Li Congduan Ma Xiao school of Electronics and Communication Engineering Sun Yat-Sen UniversityShenzhen 518107China Guizhou University State Key Laboratory of Public Big Data Guiyang 550025China Shenzhen Key Laboratory of Navigation and Communication Integration Shenzhen 518107China school of computer science and Engineering Sun Yat-Sen UniversityGuangzhou 510006China

Recently,deep learning-based semantic communication has garnered widespread attention,with numerous systems designed for transmitting diverse data sources,including text,image,and speech,*** efforts have been directed toward improving system performance,many studies have concentrated on enhancing the structure of the encoder and ***,this often overlooks the resulting increase in model complexity,imposing additional storage and computational burdens on smart ***,existing work tends to prioritize explicit semantics,neglecting the potential of implicit *** paper aims to easily and effectively enhance the receiver's decoding capability without modifying the encoder and decoder *** propose a novel semantic communication system with variational neural inference for text ***,we introduce a simple but effective variational neural inferer at the receiver to infer the latent semantic information within the received *** information is then utilized to assist in the decoding *** simulation results show a significant enhancement in system performance and improved robustness.

关键词： deep learning semantic communication variational neural inference

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