Aiming at the problem that the traditional collaborative filtering recommendation algorithm does not fully consider the influence of correlation between projects on recommendation accuracy,this paper introduces projec...Aiming at the problem that the traditional collaborative filtering recommendation algorithm does not fully consider the influence of correlation between projects on recommendation accuracy,this paper introduces project attribute fuzzy matrix,measures the project relevance through fuzzy clustering method,and classifies all project attributes.Then,the weight of the project relevance is introduced in the user similarity calculation,so that the nearest neighbor search is more accurate.In the prediction scoring section,considering the change of user interest with time,it is proposed to use the time weighting function to improve the influence of the time effect of the evaluation,so that the newer evaluation information in the system has a relatively large weight.The experimental results show that the improved algorithm improves the recommendation accuracy and improves the recommendation quality.展开更多
The process of ranking scientific publications in dynamic citation networks plays a crucial rule in a variety of applications. Despite the availability of a number of ranking algorithms, most of them use common popula...The process of ranking scientific publications in dynamic citation networks plays a crucial rule in a variety of applications. Despite the availability of a number of ranking algorithms, most of them use common popularity metrics such as the citation count, h-index, and Impact Factor (IF). These adopted metrics cause a problem of bias in favor of older publications that took enough time to collect as many citations as possible. This paper focuses on solving the problem of bias by proposing a new ranking algorithm based on the PageRank (PR) algorithm;it is one of the main page ranking algorithms being widely used. The developed algorithm considers a newly suggested metric called the Citation Average rate of Change (CAC). Time information such as publication date and the citation occurrence’s time are used along with citation data to calculate the new metric. The proposed ranking algorithm was tested on a dataset of scientific papers in the field of medical physics published in the Dimensions database from years 2005 to 2017. The experimental results have shown that the proposed ranking algorithm outperforms the PageRank algorithm in ranking scientific publications where 26 papers instead of only 14 were ranked among the top 100 papers of this dataset. In addition, there were no radical changes or unreasonable jump in the ranking process, i.e., the correlation rate between the results of the proposed ranking method and the original PageRank algorithm was 92% based on the Spearman correlation coefficient.展开更多
A knowledge graph is a structured graph in which data obtained from multiple sources are standardized to acquire and integrate human knowledge.Research is being actively conducted to cover a wide variety of knowledge,...A knowledge graph is a structured graph in which data obtained from multiple sources are standardized to acquire and integrate human knowledge.Research is being actively conducted to cover a wide variety of knowledge,as it can be applied to applications that help humans.However,existing researches are constructing knowledge graphs without the time information that knowledge implies.Knowledge stored without time information becomes outdated over time,and in the future,the possibility of knowledge being false or meaningful changes is excluded.As a result,they can’t reect information that changes dynamically,and they can’t accept information that has newly emerged.To solve this problem,this paper proposes Time-Aware PolarisX,an automatically extended knowledge graph including time information.TimeAware PolarisX constructed a BERT model with a relation extractor and an ensemble NER model including a time tag with an entity extractor to extract knowledge consisting of subject,relation,and object from unstructured text.Through two application experiments,it shows that the proposed system overcomes the limitations of existing systems that do not consider time information when applied to an application such as a chatbot.Also,we verify that the accuracy of the extraction model is improved through a comparative experiment with the existing model.展开更多
In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenario...In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.展开更多
As location-based social network (LBSN) services become more popular in people’s lives, Point of Interest (POI) recommendation has become an important research topic.POI recommendation is to recommend places where us...As location-based social network (LBSN) services become more popular in people’s lives, Point of Interest (POI) recommendation has become an important research topic.POI recommendation is to recommend places where users have not visited before. There are two problems in POI recommendation: sparsity and precision. Most users only check-in a few POIs in an LBSN. To tackle the sparse problem in a certain extent, we compute the similarity between the check-in datasets of different times. For the precision problem, we incorporate temporal information and geographical information. The temporal information will influence how the user chooses and allow the user to visit different distance point on different day. The geographical information is also used as a control for points which are too far away from the user’s check-in data. Our experimental results on real life LBSN datasets show that the proposed approach outperforms the other POI recommendation methods substantially.展开更多
The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single react...The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single reactor,thus effectively reducing the cost and operational difficulties associated with flue gas treatment.In this study,Mn-Ce-Sm-Sn(MCSS)catalysts were prepared and loaded onto hightemperature resistant polyimide(P84)filter through ultrasonic impregnation to create composite catalytic filter.The results demonstrate that the NO conversion rates of the composite catalytic filter consistently achieve above 95%within the temperature range of 160-260℃,with a chlorobenzene T_(90)value of 230℃.The ultrasonic impregnation method effectively loaded the catalyst onto the filter,ensuring high dispersion both on the surface and inside the filter.This increased exposure of catalyst active sites enhances the catalytic activity of the composite catalytic filter.Additionally,increasing the catalyst loading leads to a gradual decrease in permeability,an increase in pressure drops and the long residence time of the flue gas,thereby improving catalytic activity.Compared to ordinary impregnation methods,ultrasonic impregnation improves the bonding strength between the catalyst and filter,as well as the permeability of the composite catalytic filter under the same loading conditions.Overall,this study presents a novel approach to prepare composite catalytic filter for the simultaneous removal of NO and chlorobenzene at low temperatures.展开更多
A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,whic...A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,which is used for the scrambling,substitution and diffusion processes.The three-dimensional Fisher-Yates scrambling,S-box substitution and diffusion are employed for the first round of encryption.The chaotic sequence is adopted for secondary encryption to scramble the ciphertext obtained in the first round.Then,three-dimensional filter is applied to diffusion for further useful information hiding.The key to the algorithm is generated by the combination of hash value of plaintext image and the input parameters.It improves resisting ability of plaintext attacks.The security analysis shows that the algorithm is effective and efficient.It can resist common attacks.In addition,the good diffusion effect shows that the scheme can solve the differential attacks encountered in the transmission of medical images and has positive implications for future research.展开更多
The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses ...The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.展开更多
Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively r...Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.展开更多
In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utili...In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.展开更多
A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,a...A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,and this new structure enables a planar integrated transition from microstrip lines to ultra-thin cavity filters,thereby reducing the size of the transition structure and achieving miniaturization.The structure includes a conventional tapered microstrip transition structure,which guides the electromagnetic field from the microstrip line to the reduced-height dielectric-filled waveguide,and an air-filled matching cavity which is placed between the dielectric-filled waveguide and the ultra-thin cavity filter.The heights of the microstrip line,the dielectric-filled waveguide and the ultra-thin cavity filter are the same,enabling seamless integration within a planar radio-frequency(RF)circuit.To facilitate testing,mature finline transition structures are integrated at both ends of the microstrip line during fabrications.The simulation results of the fabricated microstrip to ultra-thin cavity filter transition with the finline transition structure,with a passband of 91.5-96.5 GHz,has an insertion loss of less than 1.9 dB and a return loss lower than-20 dB.And the whole structure has also been measured which achieves an insertion loss less than 2.6 dB and a return loss lower than-15 dB within the filter's passband,including the additional insertion loss introduced by the finline transitions.Finally,a W-band compact up-conversion module is designed,and the test results show that after using the proposed structure,the module achieves 95 dBc suppression of the 84 GHz local oscillator.It is also demonstrated that the structure proposed in this letter achieves miniaturization of the system integration without compromising the filter performance.展开更多
Filter capacitors play an important role in altern-ating current(AC)-line filtering for stabilizing voltage,sup-pressing harmonics,and improving power quality.However,traditional aluminum electrolytic capacitors(AECs)...Filter capacitors play an important role in altern-ating current(AC)-line filtering for stabilizing voltage,sup-pressing harmonics,and improving power quality.However,traditional aluminum electrolytic capacitors(AECs)suffer from a large size,short lifespan,low power density,and poor reliability,which limits their use.In contrast,ultrafast supercapacitors(SCs)are ideal for replacing commercial AECs because of their extremely high power densities,fast charging and discharging,and excellent high-frequency re-sponse.We review the design principles and key parameters for ultrafast supercapacitors and summarize research pro-gress in recent years from the aspects of electrode materials,electrolytes,and device configurations.The preparation,structures,and frequency response performance of electrode materials mainly consisting of carbon materials such as graphene and carbon nanotubes,conductive polymers,and transition metal compounds,are focused on.Finally,future research directions for ultrafast SCs are suggested.展开更多
Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter us...Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.展开更多
High-selectivity common-mode(CM)and differential-mode(DM)reflectionless balanced bandpass filters(BBPFs)are proposed in this article.By loading absorption networks at single/both ends of the basic ring resonator,input...High-selectivity common-mode(CM)and differential-mode(DM)reflectionless balanced bandpass filters(BBPFs)are proposed in this article.By loading absorption networks at single/both ends of the basic ring resonator,input-/two-port wideband CM and DM reflectionless performance,wideband filtering performance and all-stop CM suppression are obtained.The absorption network composed of K-sections of coupled-lines(CLs)terminated with grounded resistors can not only extend the filtering performance to high order,but also realize wideband absorption of CM noise and out-of-band DM signals.Absorptive stubs are loaded at ports to increase the design flexibility and enhance the absorption.As for the input-reflectionless type,multiple independently controlled transmission zeros(TZs)are obtained by the TZ control network to improves the selectivity and out-of-band rejection.A set of 2 GHz micro-strip BBPFs are designed and measured,which shows simultaneous CM and DM absorption performance.展开更多
The surge of large-scale models in recent years has led to breakthroughs in numerous fields,but it has also introduced higher computational costs and more complex network architectures.These increasingly large and int...The surge of large-scale models in recent years has led to breakthroughs in numerous fields,but it has also introduced higher computational costs and more complex network architectures.These increasingly large and intricate networks pose challenges for deployment and execution while also exacerbating the issue of network over-parameterization.To address this issue,various network compression techniques have been developed,such as network pruning.A typical pruning algorithm follows a three-step pipeline involving training,pruning,and retraining.Existing methods often directly set the pruned filters to zero during retraining,significantly reducing the parameter space.However,this direct pruning strategy frequently results in irreversible information loss.In the early stages of training,a network still contains much uncertainty,and evaluating filter importance may not be sufficiently rigorous.To manage the pruning process effectively,this paper proposes a flexible neural network pruning algorithm based on the logistic growth differential equation,considering the characteristics of network training.Unlike other pruning algorithms that directly reduce filter weights,this algorithm introduces a three-stage adaptive weight decay strategy inspired by the logistic growth differential equation.It employs a gentle decay rate in the initial training stage,a rapid decay rate during the intermediate stage,and a slower decay rate in the network convergence stage.Additionally,the decay rate is adjusted adaptively based on the filter weights at each stage.By controlling the adaptive decay rate at each stage,the pruning of neural network filters can be effectively managed.In experiments conducted on the CIFAR-10 and ILSVRC-2012 datasets,the pruning of neural networks significantly reduces the floating-point operations while maintaining the same pruning rate.Specifically,when implementing a 30%pruning rate on the ResNet-110 network,the pruned neural network not only decreases floating-point operations by 40.8%but also enhances the classification accuracy by 0.49%compared to the original network.展开更多
With the rapid development of wireless techniques,the bandpass filter(BPF)is required to cover microwave and millimeter-wave frequency bands simultaneously with good mid-band suppression.However,it is difficult to imp...With the rapid development of wireless techniques,the bandpass filter(BPF)is required to cover microwave and millimeter-wave frequency bands simultaneously with good mid-band suppression.However,it is difficult to implement such BPF due to the large frequency ratio and wideband rejection.This paper presents a superior method to realize a dual-band BPF with a large frequency ratio maintaining compact size and low design complexity.This is contributed by an ultra-wide stopband BPF with inherent discriminating excited degree at spurious frequencies.By properly arranging the feeding position and electrical length ratio of stepped impedance resonator(SIR),the excited degree at specific spurious frequencies can be flexibly adjusted to achieve desired suppression level without affecting characteristics at the fundamental passband.For validation,two BPFs were simulated,fabricated and measured,exhibiting suppression levels of 20.3 dB and 35 dB up to 18f0 and 10.53f0 respectively.Based on this,a dual-band BPF with a large frequency ratio can be easily constructed.For demonstration,a dual-band BPF operating at 3.55 GHz and 43.15 GHz is implemented.A frequency ratio up to 12.15 and mid-band suppression level better than 28 dB had been achieved.Advantages of compactness,simplicity and excellent performance of the proposed work can be observed.展开更多
In-loop filters have been comprehensively explored during the development of video coding standards due to their remarkable noise-reduction capabilities.In the early stage of video coding,in-loop filters,such as the d...In-loop filters have been comprehensively explored during the development of video coding standards due to their remarkable noise-reduction capabilities.In the early stage of video coding,in-loop filters,such as the deblocking filter,sample adaptive offset,and adaptive loop filter,were performed separately for each component.Recently,cross-component filters have been studied to improve chroma fidelity by exploiting correlations between the luma and chroma channels.This paper introduces the cross-component filters used in the state-ofthe-art video coding standards,including the cross-component adaptive loop filter and cross-component sample adaptive offset.Crosscomponent filters aim to reduce compression artifacts based on the correlation between different components and provide more accurate pixel reconstruction values.We present their origin,development,and status in the current video coding standards.Finally,we conduct discussions on the further evolution of cross-component filters.展开更多
In this paper,the newly-derived maximum correntropy Kalman filter(MCKF)is re-derived from the M-estimation perspective,where the MCKF can be viewed as a special case of the M-estimations and the Gaussian kernel functi...In this paper,the newly-derived maximum correntropy Kalman filter(MCKF)is re-derived from the M-estimation perspective,where the MCKF can be viewed as a special case of the M-estimations and the Gaussian kernel function is a special case of many robust cost functions.Based on the derivation process,a unified form for the robust Gaussian filters(RGF)based on M-estimation is proposed to suppress the outliers and non-Gaussian noise in the measurement.The RGF provides a unified form for one Gaussian filter with different cost functions and a unified form for one robust filter with different approximating methods for the involved Gaussian integrals.Simulation results show that RGF with different weighting functions and different Gaussian integral approximation methods has robust antijamming performance.展开更多
Pure magnesia filter and periclase-spinel filter were prepared using porous MgO powder and Al2O3 micro-powder as raw materials.The filtration efficiency and purification mechanism of the two sets of filters on molten ...Pure magnesia filter and periclase-spinel filter were prepared using porous MgO powder and Al2O3 micro-powder as raw materials.The filtration efficiency and purification mechanism of the two sets of filters on molten steel were investigated through steel casting tests.The results show that on the basis of surviving the thermal shock of molten steel,both filters can significantly reduce the number of non-metallic inclusions and total oxygen content of steel,thereby improving the cleanliness of the molten steel.After the thermal shock of molten steel,cracks were found in the microstructure of pure magnesia filter.Via the diffusion of non-metallic inclusions from steel into MgO grains of the filter to form solid solution,the inclusions were adsorbed to the internal and external surfaces of the pure magnesia filter.The number of inclusions was reduced by 62.5%,and the total oxygen content decreased from 0.892 to 0.265 wt.%after filtration,achieving a filtration efficiency of 70.3%.Compared with the pure magnesia filter,no cracks were found in the microstructure of the periclase-spinel filter.The mass transfer rate was accelerated due to the diffusion of inclusions from steel into MgO and MgAl2O4 grains of the filter,as well as the higher high-temperature liquid content and smaller pore structure of the filter.More non-metallic inclusions were able to enter the interior of the filter,which made the periclase-spinel filter more capable of adsorbing inclusions from steel and reducing total oxygen content.The periclase-spinel filter reduced the number of inclusions in steel by 84.4%and decreased the total oxygen content of the steel from 0.892 to 0.119 wt.%,with a filtration efficiency of 86.7%,demonstrating excellent comprehensive performance.展开更多
This work proposes a novel design for a narrowband filter operating in the mid-wave infrared(MWIR)spectrum.The filter is designed with a single layer of slab waveguide decorated with a layer of gold grating arrays.Thi...This work proposes a novel design for a narrowband filter operating in the mid-wave infrared(MWIR)spectrum.The filter is designed with a single layer of slab waveguide decorated with a layer of gold grating arrays.This design demonstrates superior narrowband transmission properties within the MWIR range,which can be explained in the framework of guided-mode resonance(GMR).Since MWIR spectral data is crucial for identifying the chemical fingerprint of man-made objects and natural materials,the GMR filters hold great potential in integration with commercial MWIR photodetectors and focal plane arrays(FPAs)and addressing the market’s demand for ultra-compact spectral detection solutions.Theoretical studies have investigated the influential parameters in the GMR filter design and provided the methods towards optimal filtering performance.The center wavelength of these transmission filters exhibits significant tunability,spanning from 3μm to 5μm across the MWIR spectrum,while the full width at half maximum(FWHM)exhibits remarkable variability,ranging from 5.7 nm to 101.0 nm,enabling the attainment of desired filter performance contingent upon judicious waveguide material selection and optimized structural design.This work forges a path toward integrating multifunctional capabilities into ultra-compact MWIR sensors.展开更多
基金supported by the National Natural Science Foundation of China(61772196,61472136)the Hunan Provincial Focus Social Science Fund(2016ZDB006)+2 种基金Hunan Provincial Social Science Achievement Review Committee results appraisal identification project(Xiang social assessment 2016JD05)Key Project of Hunan Provincial Social Science Achievement Review Committee(XSP 19ZD1005)the financial support provided by the Key Laboratory of Hunan Province for New Retail Virtual Reality Technology(2017TP1026).
文摘Aiming at the problem that the traditional collaborative filtering recommendation algorithm does not fully consider the influence of correlation between projects on recommendation accuracy,this paper introduces project attribute fuzzy matrix,measures the project relevance through fuzzy clustering method,and classifies all project attributes.Then,the weight of the project relevance is introduced in the user similarity calculation,so that the nearest neighbor search is more accurate.In the prediction scoring section,considering the change of user interest with time,it is proposed to use the time weighting function to improve the influence of the time effect of the evaluation,so that the newer evaluation information in the system has a relatively large weight.The experimental results show that the improved algorithm improves the recommendation accuracy and improves the recommendation quality.
文摘The process of ranking scientific publications in dynamic citation networks plays a crucial rule in a variety of applications. Despite the availability of a number of ranking algorithms, most of them use common popularity metrics such as the citation count, h-index, and Impact Factor (IF). These adopted metrics cause a problem of bias in favor of older publications that took enough time to collect as many citations as possible. This paper focuses on solving the problem of bias by proposing a new ranking algorithm based on the PageRank (PR) algorithm;it is one of the main page ranking algorithms being widely used. The developed algorithm considers a newly suggested metric called the Citation Average rate of Change (CAC). Time information such as publication date and the citation occurrence’s time are used along with citation data to calculate the new metric. The proposed ranking algorithm was tested on a dataset of scientific papers in the field of medical physics published in the Dimensions database from years 2005 to 2017. The experimental results have shown that the proposed ranking algorithm outperforms the PageRank algorithm in ranking scientific publications where 26 papers instead of only 14 were ranked among the top 100 papers of this dataset. In addition, there were no radical changes or unreasonable jump in the ranking process, i.e., the correlation rate between the results of the proposed ranking method and the original PageRank algorithm was 92% based on the Spearman correlation coefficient.
基金supported by Basic Science Research Program through the NRF(National Research Foundation of Korea)the MSIT(Ministry of Science and ICT),Korea,under the National Program for Excellence in SW supervised by the IITP(Institute for Information&communications Technology Promotion)the Gachon University research fund of 2019(Nos.NRF2019R1A2C1008412,2015-0-00932,GCU-2019-0773)。
文摘A knowledge graph is a structured graph in which data obtained from multiple sources are standardized to acquire and integrate human knowledge.Research is being actively conducted to cover a wide variety of knowledge,as it can be applied to applications that help humans.However,existing researches are constructing knowledge graphs without the time information that knowledge implies.Knowledge stored without time information becomes outdated over time,and in the future,the possibility of knowledge being false or meaningful changes is excluded.As a result,they can’t reect information that changes dynamically,and they can’t accept information that has newly emerged.To solve this problem,this paper proposes Time-Aware PolarisX,an automatically extended knowledge graph including time information.TimeAware PolarisX constructed a BERT model with a relation extractor and an ensemble NER model including a time tag with an entity extractor to extract knowledge consisting of subject,relation,and object from unstructured text.Through two application experiments,it shows that the proposed system overcomes the limitations of existing systems that do not consider time information when applied to an application such as a chatbot.Also,we verify that the accuracy of the extraction model is improved through a comparative experiment with the existing model.
基金supported by the National Science and Technology Council,Taiwan under grants NSTC 111-2221-E-019-047 and NSTC 112-2221-E-019-030.
文摘In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.
文摘As location-based social network (LBSN) services become more popular in people’s lives, Point of Interest (POI) recommendation has become an important research topic.POI recommendation is to recommend places where users have not visited before. There are two problems in POI recommendation: sparsity and precision. Most users only check-in a few POIs in an LBSN. To tackle the sparse problem in a certain extent, we compute the similarity between the check-in datasets of different times. For the precision problem, we incorporate temporal information and geographical information. The temporal information will influence how the user chooses and allow the user to visit different distance point on different day. The geographical information is also used as a control for points which are too far away from the user’s check-in data. Our experimental results on real life LBSN datasets show that the proposed approach outperforms the other POI recommendation methods substantially.
基金Project supported by the National Key Research and Development Program of China(2021YFB3500600,2021YFB3500605)Natural Science Foundation of Jiangsu Province(BK20220365)+5 种基金Key R&D Program of Jiangsu Province(BE2022142)Natural Science Foundation of the Jiangsu Higher Education Institutions of China(22KJB610002)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23_1419)Science and Technology Plan of Yangzhou(YZ2022030,YZ2023020)the State Key Laboratory of Clean and Efficient Coal-fired Power Generation and Pollution Control(D2022FK098)。
文摘The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single reactor,thus effectively reducing the cost and operational difficulties associated with flue gas treatment.In this study,Mn-Ce-Sm-Sn(MCSS)catalysts were prepared and loaded onto hightemperature resistant polyimide(P84)filter through ultrasonic impregnation to create composite catalytic filter.The results demonstrate that the NO conversion rates of the composite catalytic filter consistently achieve above 95%within the temperature range of 160-260℃,with a chlorobenzene T_(90)value of 230℃.The ultrasonic impregnation method effectively loaded the catalyst onto the filter,ensuring high dispersion both on the surface and inside the filter.This increased exposure of catalyst active sites enhances the catalytic activity of the composite catalytic filter.Additionally,increasing the catalyst loading leads to a gradual decrease in permeability,an increase in pressure drops and the long residence time of the flue gas,thereby improving catalytic activity.Compared to ordinary impregnation methods,ultrasonic impregnation improves the bonding strength between the catalyst and filter,as well as the permeability of the composite catalytic filter under the same loading conditions.Overall,this study presents a novel approach to prepare composite catalytic filter for the simultaneous removal of NO and chlorobenzene at low temperatures.
文摘A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,which is used for the scrambling,substitution and diffusion processes.The three-dimensional Fisher-Yates scrambling,S-box substitution and diffusion are employed for the first round of encryption.The chaotic sequence is adopted for secondary encryption to scramble the ciphertext obtained in the first round.Then,three-dimensional filter is applied to diffusion for further useful information hiding.The key to the algorithm is generated by the combination of hash value of plaintext image and the input parameters.It improves resisting ability of plaintext attacks.The security analysis shows that the algorithm is effective and efficient.It can resist common attacks.In addition,the good diffusion effect shows that the scheme can solve the differential attacks encountered in the transmission of medical images and has positive implications for future research.
基金supported by the National Key R&D Program of China(No.2021YFB2011300)the Special Funds Project for the Transformation of Scientific and Technological Achievements of Jiangsu Province,China(No.BA2023039)+1 种基金the National Natural Science Foundation of China(No.52075262)the Fundamental Research Funds for the Central Universities,China(No.30922010706).
文摘The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.
文摘Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.
基金supported in part by the National Natural Science Foundation of China(12171124,61933007)the Natural Science Foundation of Heilongjiang Province of China(ZD2022F003)+2 种基金the National High-End Foreign Experts Recruitment Plan of China(G2023012004L)the Royal Society of UKthe Alexander von Humboldt Foundation of Germany
文摘In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.
基金Supported by the Fundamental Research Funds for the Central Universities(ZYGX2021J008)。
文摘A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,and this new structure enables a planar integrated transition from microstrip lines to ultra-thin cavity filters,thereby reducing the size of the transition structure and achieving miniaturization.The structure includes a conventional tapered microstrip transition structure,which guides the electromagnetic field from the microstrip line to the reduced-height dielectric-filled waveguide,and an air-filled matching cavity which is placed between the dielectric-filled waveguide and the ultra-thin cavity filter.The heights of the microstrip line,the dielectric-filled waveguide and the ultra-thin cavity filter are the same,enabling seamless integration within a planar radio-frequency(RF)circuit.To facilitate testing,mature finline transition structures are integrated at both ends of the microstrip line during fabrications.The simulation results of the fabricated microstrip to ultra-thin cavity filter transition with the finline transition structure,with a passband of 91.5-96.5 GHz,has an insertion loss of less than 1.9 dB and a return loss lower than-20 dB.And the whole structure has also been measured which achieves an insertion loss less than 2.6 dB and a return loss lower than-15 dB within the filter's passband,including the additional insertion loss introduced by the finline transitions.Finally,a W-band compact up-conversion module is designed,and the test results show that after using the proposed structure,the module achieves 95 dBc suppression of the 84 GHz local oscillator.It is also demonstrated that the structure proposed in this letter achieves miniaturization of the system integration without compromising the filter performance.
文摘Filter capacitors play an important role in altern-ating current(AC)-line filtering for stabilizing voltage,sup-pressing harmonics,and improving power quality.However,traditional aluminum electrolytic capacitors(AECs)suffer from a large size,short lifespan,low power density,and poor reliability,which limits their use.In contrast,ultrafast supercapacitors(SCs)are ideal for replacing commercial AECs because of their extremely high power densities,fast charging and discharging,and excellent high-frequency re-sponse.We review the design principles and key parameters for ultrafast supercapacitors and summarize research pro-gress in recent years from the aspects of electrode materials,electrolytes,and device configurations.The preparation,structures,and frequency response performance of electrode materials mainly consisting of carbon materials such as graphene and carbon nanotubes,conductive polymers,and transition metal compounds,are focused on.Finally,future research directions for ultrafast SCs are suggested.
基金supported in part by the National Natural Science Foundation of China(61873348,6230 3266,62273200)JSPS(Japan Society for the Promotion of Science) KAKENHI(22H03998,23K25252)
文摘Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.
文摘High-selectivity common-mode(CM)and differential-mode(DM)reflectionless balanced bandpass filters(BBPFs)are proposed in this article.By loading absorption networks at single/both ends of the basic ring resonator,input-/two-port wideband CM and DM reflectionless performance,wideband filtering performance and all-stop CM suppression are obtained.The absorption network composed of K-sections of coupled-lines(CLs)terminated with grounded resistors can not only extend the filtering performance to high order,but also realize wideband absorption of CM noise and out-of-band DM signals.Absorptive stubs are loaded at ports to increase the design flexibility and enhance the absorption.As for the input-reflectionless type,multiple independently controlled transmission zeros(TZs)are obtained by the TZ control network to improves the selectivity and out-of-band rejection.A set of 2 GHz micro-strip BBPFs are designed and measured,which shows simultaneous CM and DM absorption performance.
基金supported by the National Natural Science Foundation of China under Grant No.62172132.
文摘The surge of large-scale models in recent years has led to breakthroughs in numerous fields,but it has also introduced higher computational costs and more complex network architectures.These increasingly large and intricate networks pose challenges for deployment and execution while also exacerbating the issue of network over-parameterization.To address this issue,various network compression techniques have been developed,such as network pruning.A typical pruning algorithm follows a three-step pipeline involving training,pruning,and retraining.Existing methods often directly set the pruned filters to zero during retraining,significantly reducing the parameter space.However,this direct pruning strategy frequently results in irreversible information loss.In the early stages of training,a network still contains much uncertainty,and evaluating filter importance may not be sufficiently rigorous.To manage the pruning process effectively,this paper proposes a flexible neural network pruning algorithm based on the logistic growth differential equation,considering the characteristics of network training.Unlike other pruning algorithms that directly reduce filter weights,this algorithm introduces a three-stage adaptive weight decay strategy inspired by the logistic growth differential equation.It employs a gentle decay rate in the initial training stage,a rapid decay rate during the intermediate stage,and a slower decay rate in the network convergence stage.Additionally,the decay rate is adjusted adaptively based on the filter weights at each stage.By controlling the adaptive decay rate at each stage,the pruning of neural network filters can be effectively managed.In experiments conducted on the CIFAR-10 and ILSVRC-2012 datasets,the pruning of neural networks significantly reduces the floating-point operations while maintaining the same pruning rate.Specifically,when implementing a 30%pruning rate on the ResNet-110 network,the pruned neural network not only decreases floating-point operations by 40.8%but also enhances the classification accuracy by 0.49%compared to the original network.
基金supported by the National Natural Science Foundation of China(No.61671485).
文摘With the rapid development of wireless techniques,the bandpass filter(BPF)is required to cover microwave and millimeter-wave frequency bands simultaneously with good mid-band suppression.However,it is difficult to implement such BPF due to the large frequency ratio and wideband rejection.This paper presents a superior method to realize a dual-band BPF with a large frequency ratio maintaining compact size and low design complexity.This is contributed by an ultra-wide stopband BPF with inherent discriminating excited degree at spurious frequencies.By properly arranging the feeding position and electrical length ratio of stepped impedance resonator(SIR),the excited degree at specific spurious frequencies can be flexibly adjusted to achieve desired suppression level without affecting characteristics at the fundamental passband.For validation,two BPFs were simulated,fabricated and measured,exhibiting suppression levels of 20.3 dB and 35 dB up to 18f0 and 10.53f0 respectively.Based on this,a dual-band BPF with a large frequency ratio can be easily constructed.For demonstration,a dual-band BPF operating at 3.55 GHz and 43.15 GHz is implemented.A frequency ratio up to 12.15 and mid-band suppression level better than 28 dB had been achieved.Advantages of compactness,simplicity and excellent performance of the proposed work can be observed.
基金supported in part by National Science Foundation of China under Grant No.62031013PCL-CMCC Foundation for Science and Innovation under Grant No.2024ZY1C0040+1 种基金New Cornerstone Science Foundation for the Xplorer PrizeHigh performance Computing Platform of Peking University。
文摘In-loop filters have been comprehensively explored during the development of video coding standards due to their remarkable noise-reduction capabilities.In the early stage of video coding,in-loop filters,such as the deblocking filter,sample adaptive offset,and adaptive loop filter,were performed separately for each component.Recently,cross-component filters have been studied to improve chroma fidelity by exploiting correlations between the luma and chroma channels.This paper introduces the cross-component filters used in the state-ofthe-art video coding standards,including the cross-component adaptive loop filter and cross-component sample adaptive offset.Crosscomponent filters aim to reduce compression artifacts based on the correlation between different components and provide more accurate pixel reconstruction values.We present their origin,development,and status in the current video coding standards.Finally,we conduct discussions on the further evolution of cross-component filters.
基金supported by the Basic Science Center Program of the National Natural Science Foundation of China(62388101)the National Natural Science Foundation of China(61873275).
文摘In this paper,the newly-derived maximum correntropy Kalman filter(MCKF)is re-derived from the M-estimation perspective,where the MCKF can be viewed as a special case of the M-estimations and the Gaussian kernel function is a special case of many robust cost functions.Based on the derivation process,a unified form for the robust Gaussian filters(RGF)based on M-estimation is proposed to suppress the outliers and non-Gaussian noise in the measurement.The RGF provides a unified form for one Gaussian filter with different cost functions and a unified form for one robust filter with different approximating methods for the involved Gaussian integrals.Simulation results show that RGF with different weighting functions and different Gaussian integral approximation methods has robust antijamming performance.
基金supported by the Key Project of the National Natural Science Foundation of China(Grant No.U21A2058 and U1860205)the Natural Science Funds of Hubei Province for Distinguished Young Scholars(Grant No.2020CFA088).
文摘Pure magnesia filter and periclase-spinel filter were prepared using porous MgO powder and Al2O3 micro-powder as raw materials.The filtration efficiency and purification mechanism of the two sets of filters on molten steel were investigated through steel casting tests.The results show that on the basis of surviving the thermal shock of molten steel,both filters can significantly reduce the number of non-metallic inclusions and total oxygen content of steel,thereby improving the cleanliness of the molten steel.After the thermal shock of molten steel,cracks were found in the microstructure of pure magnesia filter.Via the diffusion of non-metallic inclusions from steel into MgO grains of the filter to form solid solution,the inclusions were adsorbed to the internal and external surfaces of the pure magnesia filter.The number of inclusions was reduced by 62.5%,and the total oxygen content decreased from 0.892 to 0.265 wt.%after filtration,achieving a filtration efficiency of 70.3%.Compared with the pure magnesia filter,no cracks were found in the microstructure of the periclase-spinel filter.The mass transfer rate was accelerated due to the diffusion of inclusions from steel into MgO and MgAl2O4 grains of the filter,as well as the higher high-temperature liquid content and smaller pore structure of the filter.More non-metallic inclusions were able to enter the interior of the filter,which made the periclase-spinel filter more capable of adsorbing inclusions from steel and reducing total oxygen content.The periclase-spinel filter reduced the number of inclusions in steel by 84.4%and decreased the total oxygen content of the steel from 0.892 to 0.119 wt.%,with a filtration efficiency of 86.7%,demonstrating excellent comprehensive performance.
基金supported by the National Key Research and Development Program of China under Grant No.2019YFB2203400the National Natural Science Foundation of China under Grant No.61974014.
文摘This work proposes a novel design for a narrowband filter operating in the mid-wave infrared(MWIR)spectrum.The filter is designed with a single layer of slab waveguide decorated with a layer of gold grating arrays.This design demonstrates superior narrowband transmission properties within the MWIR range,which can be explained in the framework of guided-mode resonance(GMR).Since MWIR spectral data is crucial for identifying the chemical fingerprint of man-made objects and natural materials,the GMR filters hold great potential in integration with commercial MWIR photodetectors and focal plane arrays(FPAs)and addressing the market’s demand for ultra-compact spectral detection solutions.Theoretical studies have investigated the influential parameters in the GMR filter design and provided the methods towards optimal filtering performance.The center wavelength of these transmission filters exhibits significant tunability,spanning from 3μm to 5μm across the MWIR spectrum,while the full width at half maximum(FWHM)exhibits remarkable variability,ranging from 5.7 nm to 101.0 nm,enabling the attainment of desired filter performance contingent upon judicious waveguide material selection and optimized structural design.This work forges a path toward integrating multifunctional capabilities into ultra-compact MWIR sensors.
