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Formidable females redux:male social integration into female networks and the value of dynamic multilayer networks 认领
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作者 Tyler R.BONNELL ChloéVILETTE +2 位作者 Christopher YOUNG Stephanus Peter HENZI ouise BARRETT 《动物学报:英文版》 SCIE CAS CSCD 2021年第1期49-57,共9页
The development of multilayer network techniques is a boon for researchers who wish to understand how different interaction layers might influence each other,and how these in turn might influence group dynamics.Here,w... The development of multilayer network techniques is a boon for researchers who wish to understand how different interaction layers might influence each other,and how these in turn might influence group dynamics.Here,we investigate how integration between male and female grooming and aggression interaction networks influences male power trajectories in vervet monkeys Chlorocebus pygerythrus.Our previous analyses of this phenomenon used a monolayer approach,and our aim here is to extend these analyses using a dynamic multilayer approach.To do so,we constructed a temporal series of male and female interaction layers.We then used a multivariate multilevel autoregression model to compare cross-lagged associations between a male's centrality in the female grooming layer and changes in male Elo ratings.Our results confirmed our original findings:changes in male centrality within the female grooming network were weakly but positively tied to changes in their Elo ratings.However,the multilayer network approach offered additional insights into this social process,identifying how changes in a male's centrality cascade through the other network layers.This dynamic view indicates that the changes in Elo ratings are likely to be short-lived,but that male centrality within the female network had a much stronger impact throughout the multilayer network as a whole,especially on reducing intermale aggression(i.e.,aggression directed by males toward other males).We suggest that multilayer social network approaches can take advantage of increased amounts of social data that are more commonly collected these days,using a variety of methods.Such data are inherently multilevel and multilayered,and thus offer the ability to quantify more precisely the dynamics of animal social behaviors. 展开更多
关键词 multilayer networks multilevel multivariate autoregressive model primate social dynamics social networks SOCIALITY time-aggregated networks vervet monkeys
文章速递POI Neural-Rec Model via Graph Embedding Representation 认领
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作者 Kang Yang Jinghua Zhu Xu Guo 《清华大学学报:自然科学版(英文版)》 SCIE EI CAS CSCD 2021年第2期208-218,共11页
With the booming of the Internet of Things(Io T)and the speedy advancement of Location-Based Social Networks(LBSNs),Point-Of-Interest(POI)recommendation has become a vital strategy for supporting people’s ability to ... With the booming of the Internet of Things(Io T)and the speedy advancement of Location-Based Social Networks(LBSNs),Point-Of-Interest(POI)recommendation has become a vital strategy for supporting people’s ability to mine their POIs.However,classical recommendation models,such as collaborative filtering,are not effective for structuring POI recommendations due to the sparseness of user check-ins.Furthermore,LBSN recommendations are distinct from other recommendation scenarios.With respect to user data,a user’s check-in record sequence requires rich social and geographic information.In this paper,we propose two different neural-network models,structural deep network Graph embedding Neural-network Recommendation system(SG-Neu Rec)and Deepwalk on Graph Neural-network Recommendation system(DG-Neu Rec)to improve POI recommendation.combined with embedding representation from social and geographical graph information(called SG-Neu Rec and DG-Neu Rec).Our model naturally combines the embedding representations of social and geographical graph information with user-POI interaction representation and captures the potential user-POI interactions under the framework of the neural network.Finally,we compare the performances of these two models and analyze the reasons for their differences.Results from comprehensive experiments on two real LBSNs datasets indicate the effective performance of our model. 展开更多
关键词 Point-Of-Interest(POI)recommendation graph embedding neural networks Deepwalk deep learning Location-Based Social Networks(LBSNs)
Interpreting Nestedness and Modularity Structures in Affiliation Networks: An Application in Knowledge Networks Formed by Software Project Teams 认领
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作者 Jorge Luiz dos Santos Renelson Ribeiro Sampaio 《社交网络(英文)》 2021年第1期1-18,共18页
An understanding of the knowledge creation and diffusion process in the organizational context is extremely relevant. Because from this understanding, organizations can restructure processes, reorient teams and implem... An understanding of the knowledge creation and diffusion process in the organizational context is extremely relevant. Because from this understanding, organizations can restructure processes, reorient teams and implement methodologies to assist in the construction of an evolutionary process of knowledge creation and diffusion aimed at sustainable growth and innovation. The theory of complex social networks has been applied in several fields to help understand organizational cognitive processes. However, these approaches still insipiently consider the analysis of the nestedness and modularity of the studied networks. In this article, we presented an approach that sought to identify patterns of nestedness and modularity in networks of affiliation of people in projects in the organizational context. The study sought to identify these patterns in affiliation networks in a public organization providing information technology services in the period from 2006 to 2013. The detection of these patterns was performed using the NODF (Nestedness metric based on Overlap and Decreasing Fill) algorithm described by <a href="#ref1">[1]</a>. The nestedness and modularity metrics can influence patterns of knowledge creation and diffusion in formal and informal networks constituted for the execution of projects in organizations. This study showed that the network structures of the organization during the study period presented a high degree of nestedness, and it was possible to identify combined structures of nestedness and modularity. 展开更多
关键词 Social Network Analysis Affiliation Networks MODULARITY NESTEDNESS
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Deep Neural Network Based Behavioral Model of Nonlinear Circuits 认领
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作者 Zhe Jin Sekouba Kaba 《应用数学与应用物理(英文)》 2021年第3期403-412,共10页
With the rapid growth of complexity and functionality of modern electronic systems, creating precise behavioral models of nonlinear circuits has become an attractive topic. Deep neural networks (DNNs) have been recogn... With the rapid growth of complexity and functionality of modern electronic systems, creating precise behavioral models of nonlinear circuits has become an attractive topic. Deep neural networks (DNNs) have been recognized as a powerful tool for nonlinear system modeling. To characterize the behavior of nonlinear circuits, a DNN based modeling approach is proposed in this paper. The procedure is illustrated by modeling a power amplifier (PA), which is a typical nonlinear circuit in electronic systems. The PA model is constructed based on a feedforward neural network with three hidden layers, and then Multisim circuit simulator is applied to generating the raw training data. Training and validation are carried out in Tensorflow deep learning framework. Compared with the commonly used polynomial model, the proposed DNN model exhibits a faster convergence rate and improves the mean squared error by 13 dB. The results demonstrate that the proposed DNN model can accurately depict the input-output characteristics of nonlinear circuits in both training and validation data sets. 展开更多
关键词 Nonlinear Circuits Deep Neural Networks Behavioral Model Power Amplifier
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Multilayer network analyses as a toolkit for measuring social structure 认领
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作者 Kelly R.FINN 《动物学报:英文版》 SCIE CAS CSCD 2021年第1期81-99,共19页
The formalization of multilayer networks allows for new ways to measure sociality in complex social systems,including groups of animals.The same mathematical representation and methods are widely applicable across fie... The formalization of multilayer networks allows for new ways to measure sociality in complex social systems,including groups of animals.The same mathematical representation and methods are widely applicable across fields and study systems,and a network can represent drastically different types of data.As such,in order to apply analyses and interpret the results in a meaningful way the researcher must have a deep understanding of what their network is representing and what parts of it are being measured by a given analysis.Multilayer social networks can represent social structure with more detail than is often present in single layer networks,including multiple"types"of individuals,interactions,or relationships,and the extent to which these types are interdependent.Multilayer networks can also encompass a wider range of social scales,which can help overcome complications that are inherent to measuring sociality.In this paper,I dissect multilayer networks into the parts that correspond to different components of social structures.I then discuss common pitfalls to avoid across different stages of multilayer network analyses-some novel and some that always exist in social network analysis but are magnified in multi-layer representations.This paper serves as a primer for building a customized toolkit of multilayer network analyses,to probe components of social structure in animal social systems. 展开更多
关键词 animal behavior multilayer networks RELATIONSHIPS SOCIALITY social networks social structure SUBGROUPS
Wideband Reconfigurable Millimeter-Wave Linear Array Antenna Using Liquid Crystal for 5G Networks 认领
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作者 Ali El Hajj Hassan Najib Fadlallah +2 位作者 Mohammad Rammal Georges Zakka El Nashef Elias Rachid 《无线工程与技术(英文)》 2021年第1期1-14,共14页
The advanced design of a 10 × 1 linear antenna array system with the capa-bility of frequency tunability using GT3-23001 liquid crystal (LC) is pro-posed. The design for this reconfigurable wideband antenna array... The advanced design of a 10 × 1 linear antenna array system with the capa-bility of frequency tunability using GT3-23001 liquid crystal (LC) is pro-posed. The design for this reconfigurable wideband antenna array for 5G ap-plications at Ka-band millimeter-wave (mmw) consists of a double layer of stacked patch antenna with aperture coupled feeding. The bias voltage over LC varies from 0 V to 10.6 V to achieve a frequency tunability of 1.18 GHz. The array operates from 25.3 GHz to 33.8 GHz with a peak gain of 19.2 dB and a beamwidth of 5.2<span style="white-space:nowrap;">&#176</span> at 30 GHz. The proposed reconfigurable antenna ar-ray represents a real and efficient solution for the recent and future mmw 5G networks. The proposed antenna is suitable for 5G base stations in stadiums, malls and convention centers. It is proper for satellite communications and radars at mmw. 展开更多
关键词 5G Networks Liquid Antenna Liquid Crystal Frequency Reconfigurability Antenna Array MILLIMETER-WAVE
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Performance of MIMO Systems Using Space Time Block Codes (STBC) 认领
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作者 Christopher M. Lau 《应用科学(英文)》 2021年第3期273-286,共14页
Digital Communications, in relation to wireless networks, have taken off in recent years due to the expanding need to communicate faster and more efficiently. A popular way to achieve this is by using wireless Multipl... Digital Communications, in relation to wireless networks, have taken off in recent years due to the expanding need to communicate faster and more efficiently. A popular way to achieve this is by using wireless Multiple Input Multiple Output (MIMO) communication systems. MIMO systems utilize Space Time Block Codes (STBC) as one of the leading ways to obtain higher data rates with limited bandwidth and power. With several STBC methods currently available, this paper analyzes simulations using Orthogonal Space Time Block Codes (OSTBC) in Rayleigh fading channels to evaluate the performance of MIMO systems. The selection to use a Rayleigh fading channel as a model for a non-line-of-sight (nLOS) environment is selected to mimic installations where a large number of signal paths and reflections are expected. All simulations are coded, generated and plotted using MATLAB resulting in graphical data representing the bit-error rate (BER) to signal-to-noise ratio (Eb/N<sub>0</sub>) or SNR. Each simulation captures how different configurations of key variables including code rate, diversity and antenna count can impact system performance. Four modulation schemes (BPSK, QPSK, 16-QAM and 64-QAM) are included in each simulation. Conclusive evidence based upon these simulations suggests higher diversity gains were achieved with a greater number of antennas. The most significant factor for increasing system performance was using a lower count of transmit antennas with a higher count of receive antennas. 展开更多
关键词 Computer Analysis Digital Communications MATLAB MIMO Modulation Techniques Multiple Input Multiple Output Systems Orthogonal Space Time Block Codes OSTBC Rayleigh Fading Channels Space Time Block Codes STBC Wireless Communications Wireless Networks
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Investigation and Technological Comparison of 4G and 5G Networks 认领
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作者 Yunman Hao 《电脑和通信(英文)》 2021年第1期36-43,共8页
Mobile cellular data networks have allowed users to access the Internet whilst on the move. Many companies use this technology in their products. Examples of this would be Smart Meters in the home and Tesla cars havin... Mobile cellular data networks have allowed users to access the Internet whilst on the move. Many companies use this technology in their products. Examples of this would be Smart Meters in the home and Tesla cars having their “over the air updates”. Both of these two companies use the 4G and 5G technology. So this report will include a technical overview of the technology and protocols (LTE Advanced) used in 4G and 5G networks and how they provide services to the user and how data is transferred within the networks. And there are lots of different parts about the network architecture between the 4G and 5G systems. This report will talk about some different parts between these two systems and some challenges in them. 展开更多
关键词 4G 5G Protocols NETWORKS Mobile Communication
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文章速递Evaluation of the situational awareness effects for smart distribution networks under the novel design of indicator framework and hybrid weighting method 认领
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作者 Leijiao GE Yuanliang LI +2 位作者 Suxuan LI Jiebei ZHU Jun YAN 《能源前沿:英文版》 SCIE CSCD 2021年第1期143-158,共16页
As a key application of smart grid technologies,the smart distribution network(SDN)is expected to have a high diversity of equipment and complexity of operation patterns.Situational awareness(SA),which aims to provide... As a key application of smart grid technologies,the smart distribution network(SDN)is expected to have a high diversity of equipment and complexity of operation patterns.Situational awareness(SA),which aims to provide a critical visibility of the SDN,will enable a significant assurance for stable SDN operations.However,the lack of systematic evaluation through the three stages of perception,comprehensive,and prediction may prevent the SA technique from effectively achieving the performance necessary to monitor and respond to events in SDN.To analyze the feasibility and effectiveness of the SA technique for the SDN,a comprehensive evaluation framework with specific performance indicators and systematic weighting methods is proposed in this paper.Besides,to implement the indicator framework while addressing the key issues of human expert scoring ambiguity and the lack of data in specific SDN areas,an improved interval-based analytic hierarchy process-based subjective weighting and a multi-objective programming method-based objective weighting are developed to evaluate the SDN SA performance.In addition,a case study in a real distribution network of Tianjin,China is conducted whose outcomes verify the practicality and effectiveness of the proposed SA technique for SDN operating security. 展开更多
关键词 distribution networks operation and maintenance expert systems
文章速递Regression model for civil aero-engine gas path parameter deviation based on deep domainadaptation with Res-BP neural network 认领
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作者 Xingjie ZHOU Xuyun FU +1 位作者 Minghang ZHAO Shisheng ZHONG 《中国航空学报:英文版》 SCIE EI CAS CSCD 2021年第1期79-90,共12页
The variations in gas path parameter deviations can fully reflect the healthy state of aeroengine gas path components and units;therefore,airlines usually take them as key parameters for monitoring the aero-engine gas... The variations in gas path parameter deviations can fully reflect the healthy state of aeroengine gas path components and units;therefore,airlines usually take them as key parameters for monitoring the aero-engine gas path performance state and conducting fault diagnosis.In the past,the airlines could not obtain deviations autonomously.At present,a data-driven method based on an aero-engine dataset with a large sample size can be utilized to obtain the deviations.However,it is still difficult to utilize aero-engine datasets with small sample sizes to establish regression models for deviations based on deep neural networks.To obtain monitoring autonomy of each aero-engine model,it is crucial to transfer and reuse the relevant knowledge of deviation modelling learned from different aero-engine models.This paper adopts the Residual-Back Propagation Neural Network(Res-BPNN)to deeply extract high-level features and stacks multi-layer Multi-Kernel Maximum Mean Discrepancy(MK-MMD)adaptation layers to map the extracted high-level features to the Reproduce Kernel Hilbert Space(RKHS)for discrepancy measurement.To further reduce the distribution discrepancy of each aero-engine model,the method of maximizing domain-confusion loss based on an adversarial mechanism is introduced to make the features learned from different domains as close as possible,and then the learned features can be confused.Through the above methods,domain-invariant features can be extracted,and the optimal adaptation effect can be achieved.Finally,the effectiveness of the proposed method is verified by using cruise data from different civil aero-engine models and compared with other transfer learning algorithms. 展开更多
关键词 Civil aero-engine Deep domain adaptation Domain confusion Neural networks Transfer learning
文章速递Unmanned aerial vehicle swarm mission reliability modeling and evaluation method oriented to systematic and networked mission 认领
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作者 Lizhi WANG Xuejiao ZHAO +3 位作者 Yuan ZHANG Xiaohong WANG Tielin MA Xia GAO 《中国航空学报:英文版》 SCIE EI CAS CSCD 2021年第2期466-478,共13页
With the development of Unmanned Aerial Vehicle(UAV) system autonomy, network communication technology and group intelligence theory, mission execution in the form of a UAV swarm will be an important realization of fu... With the development of Unmanned Aerial Vehicle(UAV) system autonomy, network communication technology and group intelligence theory, mission execution in the form of a UAV swarm will be an important realization of future applications. Traditional single-UAV mission reliability modeling methods have been unable to meet the requirements of UAV swarm mission reliability modeling. Therefore, the UAV swarm mission reliability modeling and evaluation method is proposed. First, aimed at the interdependence among the multiple layers, a multi-layer network model of a UAV swarm is established. At the same time, based on the system having the following characteristics—using a mission chain to complete the mission and applying the connectivity of the mission network—the mission network model of a UAV swarm is established. Second, vulnerability and connectivity are selected as two indicators to reflect the reliability of the mission, and aimed at random attack and deliberate attack, vulnerability and connectivity evaluation methods are proposed. Finally, the validity and accuracy of the constructed model are verified through simulations,and the model and selected indicators can meet the reliability requirements of the UAV swarm mission. In this way, this study provides quantitative reference for UAV-swarm-related decisionmaking work and supports the development of UAV-swarm-related work. 展开更多
关键词 Complex networks Connectivity Mission reliability Unmanned Aerial Vehicles(UAV) Vulnerability
文章速递Reliable Data Storage in Heterogeneous Wireless Sensor Networks by Jointly Optimizing Routing and Storage Node Deployment 认领
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作者 Huan Yang Feng Li +2 位作者 Dongxiao Yu Yifei Zou Jiguo Yu 《清华大学学报:自然科学版(英文版)》 SCIE EI CAS CSCD 2021年第2期230-238,共9页
In the era of big data,sensor networks have been pervasively deployed,producing a large amount of data for various applications.However,because sensor networks are usually placed in hostile environments,managing the h... In the era of big data,sensor networks have been pervasively deployed,producing a large amount of data for various applications.However,because sensor networks are usually placed in hostile environments,managing the huge volume of data is a very challenging issue.In this study,we mainly focus on the data storage reliability problem in heterogeneous wireless sensor networks where robust storage nodes are deployed in sensor networks and data redundancy is utilized through coding techniques.To minimize data delivery and data storage costs,we design an algorithm to jointly optimize data routing and storage node deployment.The problem can be formulated as a binary nonlinear combinatorial optimization problem,and due to its NP-hardness,designing approximation algorithms is highly nontrivial.By leveraging the Markov approximation framework,we elaborately design an efficient algorithm driven by a continuous-time Markov chain to schedule the deployment of the storage node and corresponding routing strategy.We also perform extensive simulations to verify the efficacy of our algorithm. 展开更多
关键词 reliable data storage routing node deployment heterogeneous sensor networks
文章速递Pathological tissue segmentation by using deep neural networks 认领
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作者 Bo Pang Jianyong Wang +1 位作者 Wei Zhang Zhang Yi 《TMR现代中药》 2021年第2期29-36,共8页
Objective:The process of manually recognize the lesion tissue in pathological images is a key,laborious and subjective step in tumor diagnosis.An automatic segmentation method is proposed to segment lesion tissue in p... Objective:The process of manually recognize the lesion tissue in pathological images is a key,laborious and subjective step in tumor diagnosis.An automatic segmentation method is proposed to segment lesion tissue in pathological images.Methods:We present a region of interest(ROI)method to generate a new pre-training dataset for training initial weights on DNNs to solve the overfitting problem.To improve the segmentation performance,a multiscale and multi-resolution ensemble strategy is proposed.Our methods are validated on a public segmentation dataset of colonoscopy images.Results:By using the ROI pre-training method,the Dice score of DeepLabV3 and ResUNet increases from 0.607 to 0.739 and from 0.572 to 0.741,respectively.The ensemble method is used in the testing phase,the Dice score of DeepLabV3 and ResUNet increased to 0.760 and 0.786.Conclusion:The ROI pre-training method and ensemble strategy can be applied to DeepLabV3 and ResUNet to improve the segmentation performance of colonoscopy images. 展开更多
关键词 Pathological images segmentation Deep neural networks Pre-training method Ensemble method
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文章速递5G mobile communication applications for surgery:An overview of the latest literature 认领
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作者 Leandra Börner Valdez Rabi R Datta +3 位作者 Benjamin Babic Dolores T Müller Christiane J Bruns Hans F Fuchs 《胃肠道内窥镜检查中的人工智能(英文)》 2021年第1期1-11,共11页
Fifth-generation wireless network,5G,is expected to bring surgery to a next level.Remote surgery and telementoring could be enabled and be brought into routine medical care due to 5G characteristics,such as extreme hi... Fifth-generation wireless network,5G,is expected to bring surgery to a next level.Remote surgery and telementoring could be enabled and be brought into routine medical care due to 5G characteristics,such as extreme high bandwidth,ultrashort latency,multiconnectivity,high mobility,high availability,and high reliability.This work explores the benefits,applications and demands of 5G for surgery.Therefore,the development of previous surgical procedures from using older networks to 5G is outlined.The current state of 5G in surgical research studies is discussed,as well as future aspects and requirements of 5G in surgery are presented. 展开更多
关键词 5G Wireless networks Remote surgery Telesurgery Telementoring Robotic surgery
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A Game-Theoretic Perspective on Resource Management for Large-Scale UAV Communication Networks 认领
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作者 Jiaxin Chen Ping Chen +3 位作者 Qihui Wu Yuhua Xu Nan Qi Tao Fang 《中国通信:英文版》 SCIE CSCD 2021年第1期70-87,共18页
As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerou... As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerous advantages,resource management among various domains in large-scale UAV communication networks is the key challenge to be solved urgently.Specifically,due to the inherent requirements and future development trend,distributed resource management is suitable.In this article,we investigate the resource management problem for large-scale UAV communication networks from game-theoretic perspective which are exactly coincident with the distributed and autonomous manner.By exploring the inherent features,the distinctive challenges are discussed.Then,we explore several gametheoretic models that not only combat the challenges but also have broad application prospects.We provide the basics of each game-theoretic model and discuss the potential applications for resource management in large-scale UAV communication networks.Specifically,mean-field game,graphical game,Stackelberg game,coalition game and potential game are included.After that,we propose two innovative case studies to highlight the feasibility of such novel game-theoretic models.Finally,we give some future research directions to shed light on future opportunities and applications. 展开更多
关键词 large-scale UAV communication networks resource management game-theoretic model
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Surface-tailored PtPdCu ultrathin nanowires as advanced electrocatalysts for ethanol oxidation and oxygen reduction reaction in direct ethanol fuel cell 认领
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作者 Kaili Wang Fei Wang +1 位作者 Yunfeng Zhao Weiqing Zhang 《能源化学:英文版》 SCIE EI CAS CSCD 2021年第1期251-261,I0008,共12页
The development of advanced electrocatalysts for efficient catalyzing ethanol oxidation reaction(EOR)and oxygen reduction reaction(ORR) is significant for direct ethanol fuel cells(DEFCs).However,in many previous stud... The development of advanced electrocatalysts for efficient catalyzing ethanol oxidation reaction(EOR)and oxygen reduction reaction(ORR) is significant for direct ethanol fuel cells(DEFCs).However,in many previous studies,the major difficulties including lower utilization efficiency and weaker anti-CO-poison ability of Pt hamper the practical testing of such DEFCs,Herein,ternary Pt22Pd27C51 ultrathin(~5 nm)NWs are fabricated via a facile surfactant-free strategy.The surface and electronic structures of Pt22Pd27Cu51 NWs are further tailored via acid-etching treatment.The resulted PtPdCu NWs with an optimal atomic Pt/Pd/Cu ratio of 36:41:23 display excellent specific activities towards EOR(4.38 mA/cm2)and ORR(1.16 mA/cm2),which are 19.8-and 5.7-folds larger than that of Pt/C,respectively.A singlecell was fabricated using Pt36Pd41Cu23 NWs as electrocatalyst in both anode and cathode with Pt loading of 1.2 mgpt/cm2.The power density measured at 80 ℃ is 21.7 mW/cm2,which is ~3.9 folds enhancement relative to that fabricated by using Pt/C(2 mgPt/cm2).The enhanced catalytic performance of Pt36Pd41Cu23NWs could be attributed to that synergistic effect between Pt,Pd and Cu enhances CO anti-poisoning ability and promotes the C-C bond cleavage.This work provides a promising strategy for developing efficient electrocatalysts for DEFCs. 展开更多
关键词 Acidic DEFCs Nanowire networks materials Platinum-palladium-copper Surface-component tailoring
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Landslide identification using machine learning 认领
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作者 Haojie Wang Limin Zhang +2 位作者 Kesheng Yin Hongyu Luo Jinhui Li 《地学前缘:英文版》 SCIE CAS CSCD 2021年第1期351-364,共14页
Landslide identification is critical for risk assessment and mitigation.This paper proposes a novel machinelearning and deep-learning method to identify natural-terrain landslides using integrated geodatabases.First,l... Landslide identification is critical for risk assessment and mitigation.This paper proposes a novel machinelearning and deep-learning method to identify natural-terrain landslides using integrated geodatabases.First,landslide-related data are compiled,including topographic data,geological data and rainfall-related data.Then,three integrated geodatabases are established;namely,Recent Landslide Database(Rec LD),Relict Landslide Database(Rel LD)and Joint Landslide Database(JLD).After that,five machine learning and deep learning algorithms,including logistic regression(LR),support vector machine(SVM),random forest(RF),boosting methods and convolutional neural network(CNN),are utilized and evaluated on each database.A case study in Lantau,Hong Kong,is conducted to demonstrate the application of the proposed method.From the results of the case study,CNN achieves an identification accuracy of 92.5%on Rec LD,and outperforms other algorithms due to its strengths in feature extraction and multi dimensional data processing.Boosting methods come second in terms of accuracy,followed by RF,LR and SVM.By using machine learning and deep learning techniques,the proposed landslide identification method shows outstanding robustness and great potential in tackling the landslide identification problem. 展开更多
关键词 Landslide risk Landslide identification Machine learning Deep learning Big data Convolutional neural networks
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Biogeographic distribution patterns of algal community in different urban lakes in China: Insights into the dynamics and co-existence 认领
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作者 Haihan Zhang Rongrong Zong +5 位作者 Huiyan He Kaiwen Liu Miaomiao Yan Yutian Miao Ben Ma Xin Huang 《环境科学学报:英文版》 SCIE EI CAS CSCD 2021年第2期216-227,共12页
Urban lake ecosystems are significant for social development,but currently we know little about the geographical distribution of algal community in urban lakes at a large-scale.In this study,we investigated the algal ... Urban lake ecosystems are significant for social development,but currently we know little about the geographical distribution of algal community in urban lakes at a large-scale.In this study,we investigated the algal community structure in different areas of urban lakes in China and evaluated the influence of water quality parameters and geographical location on the algal community.The results showed that obvious differences in water quality and algal communities were observed among urban lakes in different geographical areas.Chlorophyta was the dominant phylum,followed by cyanobacteria in all areas.The network analysis indicated that algal community composition in urban lakes of the western and southern area showed more variations than the eastern and northern areas,respectively.Redundancy analysis and structural equation model revealed that nutrients and p H were dominant environmental factors that affected the algal community,and they showed higher influence than that of iron,manganese and COD Mn concentration.Importantly,algal community and density exhibited longitude and latitude relationship.In general,these results provided an ecological insight into large-scale geographical distributions of algal community in urban lakes,thereby having potential applications for management of the lakes. 展开更多
关键词 Algal community structure Biogeographic pattern Ecological networks Urban lakes Structural equation model
Power law decay of stored pattern stability in sparse Hopfield neural networks 认领
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作者 Fei Fang Zhou Yang Sheng-Jun Wang 《理论物理通讯:英文版》 SCIE CAS CSCD 2021年第2期108-116,共9页
Hopfield neural networks on scale-free networks display the power law relation between the stability of patterns and the number of patterns.The stability is measured by the overlap between the output state and the sto... Hopfield neural networks on scale-free networks display the power law relation between the stability of patterns and the number of patterns.The stability is measured by the overlap between the output state and the stored pattern which is presented to a neural network.In simulations the overlap declines to a constant by a power law decay.Here we provide the explanation for the power law behavior through the signal-to-noise ratio analysis.We show that on sparse networks storing a plenty of patterns the stability of stored patterns can be approached by a power law function with the exponent-0.5.There is a difference between analytic and simulation results that the analytic results of overlap decay to 0.The difference exists because the signal and noise term of nodes diverge from the mean-field approach in the sparse finite size networks. 展开更多
关键词 Hopfield neural network attractor neural networks associative memory
Detection of Multiscale Center Point Objects Based on Parallel Network 认领
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作者 Hao Chen Hong Zheng Xiaolong Li 《人工智能技术学报(英文)》 2021年第1期68-73,共6页
Anchor-based detectors are widely used in object detection.To improve the accuracy of object detection,multiple anchor boxes are intensively placed on the input image,yet.Most of which are invalid.Although the anchor-... Anchor-based detectors are widely used in object detection.To improve the accuracy of object detection,multiple anchor boxes are intensively placed on the input image,yet.Most of which are invalid.Although the anchor-free method can reduce the number of useless anchor boxes,the invalid ones still occupy a high proportion.On this basis,this paper proposes a multiscale center point object detection method based on parallel network to further reduce the number of useless anchor boxes.This study adopts the parallel network architecture of hourglass-104 and darknet-53 of which the first one outputs heatmaps to generate the center point for object feature location on the output attribute feature map of darknet-53.Combining feature pyramid and CIoU loss function,this algorithm is trained and tested on MSCOCO dataset,increasing the detection rate of target location and the accuracy rate of small object detection.Though resembling the state-of-the-art two-stage detectors in overall object detection accuracy,this algorithm is superior in speed. 展开更多
关键词 deep learning heatmap feature pyramid networks object detection center point
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