Dear Editor,This letter focuses on the distributed optimal containment control of continuous-time multi-agent systems(CTMASs)with respect to the minimum-energy performance index over fixed *** achieve this,we firstly ...
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Dear Editor,This letter focuses on the distributed optimal containment control of continuous-time multi-agent systems(CTMASs)with respect to the minimum-energy performance index over fixed *** achieve this,we firstly investigate the optimal containment control problem using the inverse optimal control method,where all states of followers asymptotically converge to the convex hull spanned by the leaders while some quadratic performance indexes get minimized.A sufficient condition for existence of the distributed optimal containment control protocol is *** introducing the parametric algebraic Riccati equation(PARE),it is strictly proved that the global performance index can be used to approximate the standard minimumenergy performance index as the parameters tends to *** consequence,the standard minimum-energy cooperative containment control can be solved by local steady state feedback protocols.
In order to meet the needs of new materials gradually developing towards miniaturization,integration,and light weight,multifunctional BaNb_(2)O_(6):Yb^(3+)/Er^(3+)/Tm^(3+)transparent glass-ceramics were success-fully ...
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In order to meet the needs of new materials gradually developing towards miniaturization,integration,and light weight,multifunctional BaNb_(2)O_(6):Yb^(3+)/Er^(3+)/Tm^(3+)transparent glass-ceramics were success-fully prepared by melt quenching and controllable *** structure,luminescence,and en-ergy transmission were *** the opposite temperature dependence of the Tm^(3+)emission band and the corresponding large energy level gap,a maximum relative sensitivity of 2.3%K^(-1)based on thermal coupling levels(TCLs)is obtained in a wide temperature range(298-673 K).The multi-ratio optical thermometry based on TCLs and non-TCLs is successfully realized by using the different emission bands of double emission centers,which makes it possible for self-reference optical temperature measurement *** addition,the transparent glass-ceramic exhibits excellent electrical properties under 700 kV cm^(-1)electric field:high discharge energy density(W_(d)=0.99 J cm^(-3)),huge instantaneous power density(225.3 MW cm^(-3)),and ultra-fast discharge rate(T_(0.9)≤15.8 ns).The prepared glass-ceramic is expected to be a new type of lead-free multifunctional photoelectric material for temperature sensors and transparent electronic devices.
P-type Mg_(3)Sb_(2)-based Zintls have attracted considerable interest in the thermoelectric(TE)field due to their environmental friendliness and low ***,compared to their n-type counterparts,they show relatively low T...
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P-type Mg_(3)Sb_(2)-based Zintls have attracted considerable interest in the thermoelectric(TE)field due to their environmental friendliness and low ***,compared to their n-type counterparts,they show relatively low TE performance,limiting their application in TE *** this work,we simultaneously introduce Bi alloying at Sb sites and Ag doping at Mg sites into the Mg_(3)Sb_(2)to coopera-tively optimize the electrical and thermal properties for the first time,acquiring the highest ZT value of∼0.85 at 723 K and a high average ZT of 0.39 in the temperature range of 323-723 K in sample Mg_(2.94)Ag_(0.06)Sb_(1.9)Bi_(0.1).The first-principle calculations show that the codoping of Ag and Bi can shift the Fermi level into the valence band and narrow the band gap,resulting in the increased carrier concentration from 3.50×10^(17)cm^(-3)in the reference Mg 3 Sb 0.9 Bi 0.1 to∼7.88×10^(19)cm^(-3)in sample Mg 2.94 Ag 0.06 Sb 0.9 Bi *** a result,a remarkable power factor of∼778.9μW m^(-1)K^(-2)at 723 K is achieved in sample Mg 2.94 Ag 0.06 Sb 0.9 Bi ***,a low lattice thermal conductivity of∼0.48 W m^(-1)K^(-1)at 723 K is also obtained with the help of phonon scattering at the distorted lattice,point defects,and nano-precipitates in sample Mg 2.94 Ag 0.06 Sb 0.9 Bi *** synergistic effect of using the multi-element co-doping/-alloying to optimize electrical properties in Mg_(3)Sb_(2)holds promise for further improving the TE performance of Zintl phase materials or even others.
Within the thriving e-commerce landscape,some unscrupulous merchants hire spammer groups to post misleading reviews or ratings,aiming to manipulate public perception and disrupt fair market *** phenomenon has prompted...
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Within the thriving e-commerce landscape,some unscrupulous merchants hire spammer groups to post misleading reviews or ratings,aiming to manipulate public perception and disrupt fair market *** phenomenon has prompted a heightened research focus on spammer groups *** the e-commerce domain,current spammer group detection algorithms can be classified into three categories,i.e.,Frequent Item Mining-based,graph-based,and burst-based ***,existing graph-based algorithms have limitations in that they did not adequately consider the redundant relationships within co-review graphs and neglected to detect overlapping members within spammer *** address these issues,we introduce an overlapping spammer group detection algorithm based on deep reinforcement learning named ***,the algorithm filters out highly suspicious products and gets the set of reviewers who have reviewed these ***,taking these reviewers as nodes and their co-reviewing relationships as edges,we construct a homogeneous co-reviewing ***,to efficiently identify and handle the redundant relationships that are accidentally formed between ordinary users and spammer group members,we propose the Auto-Sim algorithm,which is a specifically tailored algorithm for dynamic optimization of the co-reviewing graph,allowing for adjustments to the reviewers’relationship network within the ***,candidate spammer groups are discovered by using the Ego-Splitting overlapping clustering algorithm,allowing overlapping members to exist in these ***,these groups are refined and ranked to derive the final list of spammer *** results based on real-life datasets show that our proposed DRL-OSG algorithm performs better than the baseline algorithms in Precision.
Measuring the transverse velocity field in high-resolution solar images is essential for understanding solar *** paper introduces an innovative unsupervised deep learning optical flow model designed to calculate the t...
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Measuring the transverse velocity field in high-resolution solar images is essential for understanding solar *** paper introduces an innovative unsupervised deep learning optical flow model designed to calculate the transverse velocity field,addressing the challenges of missing optical flow labels and the limited accuracy of velocity field measurements in high-resolution solar *** proposed method converts the transverse velocity field computation problem into an optical flow computation problem,using two forward propagations of features to get rid of the reliance on optical flow ***,it reduces the impact of the“Brightness Consistency”constraint on optical flow accuracy by identifying and handling optical flow *** apply this method to compute the transverse velocity fields of high-resolution solar image sequences from the Hαand TiO bands,observed by the New Vacuum Solar *** experiments with several wellestablished optical flow methods,including those based on supervised deep learning models,show that our approach outperforms the comparison methods according to key evaluation metrics such as Residual Map Mean,Residual Map Variance,Cross Correlation,and Structural Similarity Index ***,since optical flow captures the fundamental motion information in image sequences,the proposed method can be applied to a variety of research areas,including solar image registration,sequence alignment,image super-resolution,magnetic field calibration,and solar activity *** code is available at https://***/jackie-willianm/Transverse-Velocity-Field-Measurement-of-Solar-High-Resolution-Images.
An adaptive polarization controller (APC) is crucial in mitigating carrier fading in a self-homodyne coherent detection (SHCD) system. In this paper, we propose a simplified APC design based on the X-cut, Y-propagatin...
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Molecular property depends on the property, the number of the elements, and the interaction between elements(such as chemical bonds). Based on the above-mentioned idea, two methods to estimate the isobaric heat capaci...
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Molecular property depends on the property, the number of the elements, and the interaction between elements(such as chemical bonds). Based on the above-mentioned idea, two methods to estimate the isobaric heat capacity of liquids organic compounds were developed. Ten elements groups and 32 chemical bond groups were defined by considering the structure of organic compounds. The group contribution values and correlation parameters were regressed by the ridge regression method with the experiment data of 1137 compounds. The heat capacity can be calculated by summating the contributions of the elements and chemical bond groups. The two methods were compared with existing group contribution methods, such as Chickos, Zabransky-Ruzicka, and Zdenka Kolska. The results show that those new estimation methods' overall average relative deviations were 5.81% and 5.71%, which were lower than the other three methods. Those methods were more straightforward in compound *** new methods can be used to estimate the liquid heat capacity of silicon-containing compounds,which the other three methods cannot estimate. The new methods are more accessible, broader, and more accurate. Therefore, this research has important scientific significance and vast application prospects.
Process parameter configuration needs to respond quickly in the customized manufacturing environment. A multi-objective optimization method based on antlion algorithm for product process configuration design is propos...
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In information Centric Networking(ICN)where content is the object of exchange,in-network caching is a unique functional feature with the ability to handle data storage and distribution in remote sensing satellite *** ...
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In information Centric Networking(ICN)where content is the object of exchange,in-network caching is a unique functional feature with the ability to handle data storage and distribution in remote sensing satellite *** up cache space at any node enables users to access data nearby,thus relieving the processing pressure on the ***,the existing caching strategies still suffer from the lack of global planning of cache contents and low utilization of cache resources due to the lack of fine-grained division of cache *** address the issues mentioned,a cooperative caching strategy(CSTL)for remote sensing satellite networks based on a two-layer caching model is *** two-layer caching model is constructed by setting up separate cache spaces in the satellite network and the ground *** caching of popular contents in the region at the ground station to reduce the access delay of users.A content classification method based on hierarchical division is proposed in the satellite network,and differential probabilistic caching is employed for different levels of *** cached content is also dynamically adjusted by analyzing the subsequent changes in the popularity of the cached *** the two-layer caching model,ground stations and satellite networks collaboratively cache to achieve global planning of cache contents,rationalize the utilization of cache resources,and reduce the propagation delay of remote sensing *** results show that the CSTL strategy not only has a high cache hit ratio compared with other caching strategies but also effectively reduces user request delay and server load,which satisfies the timeliness requirement of remote sensing data transmission.
Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that h...
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Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that has been deliberately or accidentally polluted with *** presents a challenge in learning robust GNNs under noisy *** address this issue,we propose a novel framework called Soft-GNN,which mitigates the influence of label noise by adapting the data utilized in *** approach employs a dynamic data utilization strategy that estimates adaptive weights based on prediction deviation,local deviation,and global *** better utilizing significant training samples and reducing the impact of label noise through dynamic data selection,GNNs are trained to be more *** evaluate the performance,robustness,generality,and complexity of our model on five real-world datasets,and our experimental results demonstrate the superiority of our approach over existing methods.
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