One of the elementary operations in computing systems is multiplication.Therefore,high-speed and low-power multipliers design is mandatory for efficient computing systems.In designing low-energy dissipation circuits,r...One of the elementary operations in computing systems is multiplication.Therefore,high-speed and low-power multipliers design is mandatory for efficient computing systems.In designing low-energy dissipation circuits,reversible logic is more efficient than irreversible logic circuits but at the cost of higher complexity.This paper introduces an efficient signed/unsigned 4×4 reversible Vedic multiplier with minimum quantum cost.The Vedic multiplier is considered fast as it generates all partial product and their sum in one step.This paper proposes two reversible Vedic multipliers with optimized quantum cost and garbage output.First,the unsigned Vedic multiplier is designed based on the Urdhava Tiryakbhyam(UT)Sutra.This multiplier consists of bitwise multiplication and adder compressors.Compared with Vedic multipliers in the literature,the proposed design has a quantum cost of 111 with a reduction of 94%compared to the previous design.It has a garbage output of 30 with optimization of the best-compared design.Second,the proposed unsigned multiplier is expanded to allow the multiplication of signed numbers as well as unsigned numbers.Two signed Vedic multipliers are presented with the aim of obtaining more optimization in performance parameters.DesignI has separate binary two’s complement(B2C)and MUX circuits,while DesignII combines binary two’s complement and MUX circuits in one circuit.DesignI shows the lowest quantum cost,231,regarding state-ofthe-art.DesignII has a quantum cost of 199,reducing to 86.14%of DesignI.The functionality of the proposed multiplier is simulated and verified using XILINX ISE 14.2.展开更多
A graph whose edges are labeled either as positive or negative is called a signed graph.Hameed et al.introduced signed distance and distance compatibility in 2021,initially to characterize balanced signed graphs which...A graph whose edges are labeled either as positive or negative is called a signed graph.Hameed et al.introduced signed distance and distance compatibility in 2021,initially to characterize balanced signed graphs which have nice spectral properties.This article mainly studies the conjecture proposed by Shijin et al.on the distance compatibility of the direct product of signed graphs,and provides necessary and sufficient conditions for the distance compatibility of the direct product of signed graphs.Some further questions regarding distance compatibility are also posed.展开更多
The unique structure of signed networks,characterized by positive and negative edges,poses significant challenges for analyzing network topology.In recent years,various statistical algorithms have been developed to ad...The unique structure of signed networks,characterized by positive and negative edges,poses significant challenges for analyzing network topology.In recent years,various statistical algorithms have been developed to address this issue.However,there remains a lack of a unified framework to uncover the nontrivial properties inherent in signed network structures.To support developers,researchers,and practitioners in this field,we introduce a Python library named SNSAlib(Signed Network Structure Analysis),specifically designed to meet these analytical requirements.This library encompasses empirical signed network datasets,signed null model algorithms,signed statistics algorithms,and evaluation indicators.The primary objective of SNSAlib is to facilitate the systematic analysis of micro-and meso-structure features within signed networks,including node popularity,clustering,assortativity,embeddedness,and community structure by employing more accurate signed null models.Ultimately,it provides a robust paradigm for structure analysis of signed networks that enhances our understanding and application of signed networks.展开更多
Unsignalized intersections pose a challenge for autonomous vehicles that must decide how to navigate them safely and efficiently.This paper proposes a reinforcement learning(RL)method for autonomous vehicles to naviga...Unsignalized intersections pose a challenge for autonomous vehicles that must decide how to navigate them safely and efficiently.This paper proposes a reinforcement learning(RL)method for autonomous vehicles to navigate unsignalized intersections safely and efficiently.The method uses a semantic scene representation to handle variable numbers of vehicles and a universal reward function to facilitate stable learning.A collision risk function is designed to penalize unsafe actions and guide the agent to avoid them.A scalable policy optimization algorithm is introduced to improve data efficiency and safety for vehicle learning at intersections.The algorithm employs experience replay to overcome the on-policy limitation of proximal policy optimization and incorporates the collision risk constraint into the policy optimization problem.The proposed safe RL algorithm can balance the trade-off between vehicle traffic safety and policy learning efficiency.Simulated intersection scenarios with different traffic situations are used to test the algorithm and demonstrate its high success rates and low collision rates under different traffic conditions.The algorithm shows the potential of RL for enhancing the safety and reliability of autonomous driving systems at unsignalized intersections.展开更多
A signed graph S=(S^(u),σ)has an underlying graph Suand a functionσ:E(S^(u))-→{+,-}.Let E^(-)(S)denote the set of negative edges of S.Then S is eulerian signed graph(or subeulerian signed graph,or balanced eulerian...A signed graph S=(S^(u),σ)has an underlying graph Suand a functionσ:E(S^(u))-→{+,-}.Let E^(-)(S)denote the set of negative edges of S.Then S is eulerian signed graph(or subeulerian signed graph,or balanced eulerian signed graph,respectively)if Suis eulerian(or subeulerian,or eulerian and|E-(S)|is even,respectively).We say that S is balanced subeulerian signed graph if there exists a balanced eulerian signed graph S′such that S′is spanned by S.The signed line graph L(S)of a signed graph S is a signed graph with the vertices of L(S)being the edges of S,where an edge eiej is in L(S)if and only if the edges e_(i)and e_(j)of S have a vertex in common in S such that an edge eiej in L(S)is negative if and only if both edges ei and ej are negative in S.In this paper,two families of signed graphs S and S′are identified,which are applied to characterize balanced subeulerian signed graphs and balanced subeulerian signed line graphs.In particular,it is proved that a signed graph S is balanced subeulerian if and only if S∈S,and that a signed line graph of signed graph S is balanced subeulerian if and only if S∈S′.展开更多
While progress has been made in information source localization,it has overlooked the prevalent friend and adversarial relationships in social networks.This paper addresses this gap by focusing on source localization ...While progress has been made in information source localization,it has overlooked the prevalent friend and adversarial relationships in social networks.This paper addresses this gap by focusing on source localization in signed network models.Leveraging the topological characteristics of signed networks and transforming the propagation probability into effective distance,we propose an optimization method for observer selection.Additionally,by using the reverse propagation algorithm we present a method for information source localization in signed networks.Extensive experimental results demonstrate that a higher proportion of positive edges within signed networks contributes to more favorable source localization,and the higher the ratio of propagation rates between positive and negative edges,the more accurate the source localization becomes.Interestingly,this aligns with our observation that,in reality,the number of friends tends to be greater than the number of adversaries,and the likelihood of information propagation among friends is often higher than among adversaries.In addition,the source located at the periphery of the network is not easy to identify.Furthermore,our proposed observer selection method based on effective distance achieves higher operational efficiency and exhibits higher accuracy in information source localization,compared with three strategies for observer selection based on the classical full-order neighbor coverage.展开更多
With the support of Vehicle-to-Everything(V2X)technology and computing power networks,the existing intersection traffic order is expected to benefit from efficiency improvements and energy savings by new schemes such ...With the support of Vehicle-to-Everything(V2X)technology and computing power networks,the existing intersection traffic order is expected to benefit from efficiency improvements and energy savings by new schemes such as de-signalization.How to effectively manage autonomous vehicles for traffic control with high throughput at unsignalized intersections while ensuring safety has been a research hotspot.This paper proposes a collision-free autonomous vehicle scheduling framework based on edge-cloud computing power networks for unsignalized intersections where the lanes entering the intersections are undirectional,and designs an efficient communication system and protocol.First,by analyzing the collision point occupation time,this paper formulates an absolute value programming problem.Second,this problem is solved with low complexity by the Edge Intelligence Optimal Entry Time(EI-OET)algorithm based on edge-cloud computing power support.Then,the communication system and protocol are designed for the proposed scheduling scheme to realize efficient and low-latency vehicular communications.Finally,simulation experiments compare the proposed scheduling framework with directional and traditional traffic light scheduling mechanisms,and the experimental results demonstrate its high efficiency,low latency,and low complexity.展开更多
Sign language dataset is essential in sign language recognition and translation(SLRT). Current public sign language datasets are small and lack diversity, which does not meet the practical application requirements for...Sign language dataset is essential in sign language recognition and translation(SLRT). Current public sign language datasets are small and lack diversity, which does not meet the practical application requirements for SLRT. However, making a large-scale and diverse sign language dataset is difficult as sign language data on the Internet is scarce. In making a large-scale and diverse sign language dataset, some sign language data qualities are not up to standard. This paper proposes a two information streams transformer(TIST) model to judge whether the quality of sign language data is qualified. To verify that TIST effectively improves sign language recognition(SLR), we make two datasets, the screened dataset and the unscreened dataset. In this experiment, this paper uses visual alignment constraint(VAC) as the baseline model. The experimental results show that the screened dataset can achieve better word error rate(WER) than the unscreened dataset.展开更多
Convolutional neural networks(CNNs)exhibit superior performance in image feature extraction,making them extensively used in the area of traffic sign recognition.However,the design of existing traffic sign recognition ...Convolutional neural networks(CNNs)exhibit superior performance in image feature extraction,making them extensively used in the area of traffic sign recognition.However,the design of existing traffic sign recognition algorithms often relies on expert knowledge to enhance the image feature extraction networks,necessitating image preprocessing and model parameter tuning.This increases the complexity of the model design process.This study introduces an evolutionary neural architecture search(ENAS)algorithm for the automatic design of neural network models tailored for traffic sign recognition.By integrating the construction parameters of residual network(ResNet)into evolutionary algorithms(EAs),we automatically generate lightweight networks for traffic sign recognition,utilizing blocks as the fundamental building units.Experimental evaluations on the German traffic sign recognition benchmark(GTSRB)dataset reveal that the algorithm attains a recognition accuracy of 99.32%,with a mere 2.8×10^(6)parameters.Experimental results comparing the proposed method with other traffic sign recognition algorithms demonstrate that the method can more efficiently discover neural network architectures,significantly reducing the number of network parameters while maintaining recognition accuracy.展开更多
Dynamic sign language recognition holds significant importance, particularly with the application of deep learning to address its complexity. However, existing methods face several challenges. Firstly, recognizing dyn...Dynamic sign language recognition holds significant importance, particularly with the application of deep learning to address its complexity. However, existing methods face several challenges. Firstly, recognizing dynamic sign language requires identifying keyframes that best represent the signs, and missing these keyframes reduces accuracy. Secondly, some methods do not focus enough on hand regions, which are small within the overall frame, leading to information loss. To address these challenges, we propose a novel Video Transformer Attention-based Network (VTAN) for dynamic sign language recognition. Our approach prioritizes informative frames and hand regions effectively. To tackle the first issue, we designed a keyframe extraction module enhanced by a convolutional autoencoder, which focuses on selecting information-rich frames and eliminating redundant ones from the video sequences. For the second issue, we developed a soft attention-based transformer module that emphasizes extracting features from hand regions, ensuring that the network pays more attention to hand information within sequences. This dual-focus approach improves effective dynamic sign language recognition by addressing the key challenges of identifying critical frames and emphasizing hand regions. Experimental results on two public benchmark datasets demonstrate the effectiveness of our network, outperforming most of the typical methods in sign language recognition tasks.展开更多
Once a train stops in a tunnel section and requires emergency evacuation,the large distance between stations and long walking distances in the underground spaces of suburban railway systems pose potential risks to the...Once a train stops in a tunnel section and requires emergency evacuation,the large distance between stations and long walking distances in the underground spaces of suburban railway systems pose potential risks to the evacuation process on tunnel platforms,especially in complex environments.This study utilized Virtual Reality(VR)technology to construct a virtual experimental platform for tunnel evacuation in suburban railway systems,simulating different combinations of smoke and obstacle conditions.By requiring participants to wear VR glasses and walk on an omnidirectional treadmill for moving,as well as complete psychological questionnaires,the study reveals the influences of No Guiding(NG)signs,Wall-Guided(WG)signs,and Central axis Guidance(CG)signs on the movement abilities and psychological behaviors of participants contrastively.The results show that either smoke conditions or obstacle positions affect the mental stress of participants,and the guidance sign has a positive effect on reducing the mental stress.There is an inverse relationship between mental stress and movement abilities.WG and CG signs respectively lead participants to walk closer to walls and along the central axis,which is conducive to reducing the variation in participants’behavior characteristics when circumventing obstacles on the wall side or track side under smoke conditions,respectively.Additionally,CG signs reduce the speed fluctuations of participants before circumventing obstacles,improving the stability of the distance from the wall and speed under smoke conditions,compared to NG and WG signs.These findings contribute to understanding the evacuation psychological-behavioral-movement characteristics of pedestrians on evacuation platforms in suburban railway tunnels and provide a basis for improving the safety design of evacuation guidance signs.展开更多
The arterial pulse tapping artifact,known as Aslanger’s sign,is an electrocardiographic artifact resulting from the transmission of arterial pulsation onto the limb electrodes of the standard 12-lead electrocardiogra...The arterial pulse tapping artifact,known as Aslanger’s sign,is an electrocardiographic artifact resulting from the transmission of arterial pulsation onto the limb electrodes of the standard 12-lead electrocardiograph(ECG)which are placed near the radial or posterior tibial arteries.[1-16]This electromechanical artifact is of cardiac origin and is synchronous with the cardiac cycle.[17]Nearly all reported cases of Aslanger’s sign exhibit an unusual waveform morphology in all 12 leads except one limb lead.[1-14,16]However,we previously reported a case of Aslanger’s sign that showed distorted waveforms from the ST to TP segments observed only in five limb leads among 12 leads.展开更多
This paper presents a predefined-time controller for Multiple Space transportation Robots System (MSRS), which can be applied in on-orbit assembly tasks to transport modules to pre-assembly configuration quickly. Firs...This paper presents a predefined-time controller for Multiple Space transportation Robots System (MSRS), which can be applied in on-orbit assembly tasks to transport modules to pre-assembly configuration quickly. Firstly, to simplify the analysis and design of predefined-time controller, a Predefined-time Stability Criterion is proposed in the form of Composite Lyapunov Function (CLF-PSC). Besides simplicity, the CLF-PSC also has the advantage of less conservativeness due to utilization of initial state information. Secondly, a concept of Lp-Norm-Normalized Sign Function (LPNNSF) is proposed based on the CLF-PSC. Different from traditional norm-normalized sign function, the Lp-norm of LPNNSF can be selected arbitrarily according to practical control task requirements, which means that the proposed LPNNSF is more generalized and more convenient for calculation. Thirdly, a predefined-time disturbance observer and predefined-time controller are designed based on the LPNNSF. The observer has the property of predefined-time convergence to achieve quicker and more accurate estimation of the lumped disturbance. The controller has less control input and chattering phenomenon than traditional predefined-time controller. In addition, by introducing the observer into the controller, the closed-loop system enjoys high precision and strong robustness. Finally, the effectiveness of the proposed controller is verified by numerical simulations. By employing the controller, the MSRS can carry assembly modules to the desired pre-assembly configuration accurately within predefined time.展开更多
Arabic Sign Language(ArSL)recognition plays a vital role in enhancing the communication for the Deaf and Hard of Hearing(DHH)community.Researchers have proposed multiple methods for automated recognition of ArSL;howev...Arabic Sign Language(ArSL)recognition plays a vital role in enhancing the communication for the Deaf and Hard of Hearing(DHH)community.Researchers have proposed multiple methods for automated recognition of ArSL;however,these methods face multiple challenges that include high gesture variability,occlusions,limited signer diversity,and the scarcity of large annotated datasets.Existing methods,often relying solely on either skeletal data or video-based features,struggle with generalization and robustness,especially in dynamic and real-world conditions.This paper proposes a novel multimodal ensemble classification framework that integrates geometric features derived from 3D skeletal joint distances and angles with temporal features extracted from RGB videos using the Inflated 3D ConvNet(I3D).By fusing these complementary modalities at the feature level and applying a majority-voting ensemble of XGBoost,Random Forest,and Support Vector Machine classifiers,the framework robustly captures both spatial configurations and motion dynamics of sign gestures.Feature selection using the Pearson Correlation Coefficient further enhances efficiency by reducing redundancy.Extensive experiments on the ArabSign dataset,which includes RGB videos and corresponding skeletal data,demonstrate that the proposed approach significantly outperforms state-of-the-art methods,achieving an average F1-score of 97%using a majority-voting ensemble of XGBoost,Random Forest,and SVM classifiers,and improving recognition accuracy by more than 7%over previous best methods.This work not only advances the technical stateof-the-art in ArSL recognition but also provides a scalable,real-time solution for practical deployment in educational,social,and assistive communication technologies.Even though this study is about Arabic Sign Language,the framework proposed here can be extended to different sign languages,creating possibilities for potentially worldwide applicability in sign language recognition tasks.展开更多
This paper proposes a lightweight traffic sign detection system based on you only look once(YOLO).Firstly,the classification to fusion(C2f)structure is integrated into the backbone network,employing deformable convolu...This paper proposes a lightweight traffic sign detection system based on you only look once(YOLO).Firstly,the classification to fusion(C2f)structure is integrated into the backbone network,employing deformable convolution and bi-directional feature pyramid network(BiFPN)_Concat to improve the adaptability of the network.Secondly,the simple attention module(SimAm)is embedded to prioritize key features and reduce the complexity of the model after the C2f layer at the end of the backbone network.Next,the focal efficient intersection over union(EloU)is introduced to adjust the weights of challenging samples.Finally,we accomplish the design and deployment for the mobile app.The results demonstrate improvements,with the F1 score of 0.8987,mean average precision(mAP)@0.5 of 98.8%,mAP@0.5:0.95 of 75.6%,and the detection speed of 50 frames per second(FPS).展开更多
To explore the influence of emergency evacuation signs on passenger behavior during subway fires and improve evacuation efficiency in emergencies,this paper proposes a dynamic emergency evacuation sign system.A simula...To explore the influence of emergency evacuation signs on passenger behavior during subway fires and improve evacuation efficiency in emergencies,this paper proposes a dynamic emergency evacuation sign system.A simulation platform integrating building information modeling(BIM)and virtual reality(VR)technologies was em-ployed to create subway fire evacuation scenarios using both the current and proposed dynamic emergency evacuation signage systems.Through simulation experiments,fine-grained microscopic data on passenger behavior was collected.Seven indicators were selected to assess evacuation efficiency and wayfinding difficulty.The analysis explored the influence of evacuation signs on passenger behavior in both overall and decision-making areas,thereby validating the effectiveness of the new emergency evacuation signage system.The results show that the dynamic evacuation signage system significantly improves overall passenger evacuation efficiency and reduces decision-making errors.It also improves wayfinding efficiency in critical decision areas by reducing the need for direction identification,minimizing stopping times,and lowering the frequency of decision errors.The method for evaluating the effects of emergency evacuation signs on passenger evacuation behavior proposed in this study provides a robust theoretical basis for the design and optimization of emergency-oriented signs.展开更多
This is subsequent of , by using the theory of additive fuzzy measure and signed additive fuzzy measure , we prove the Radon_Nikodym Theorem and Lebesgue decomposition Theorem of signed additive fuzzy measure.
文摘One of the elementary operations in computing systems is multiplication.Therefore,high-speed and low-power multipliers design is mandatory for efficient computing systems.In designing low-energy dissipation circuits,reversible logic is more efficient than irreversible logic circuits but at the cost of higher complexity.This paper introduces an efficient signed/unsigned 4×4 reversible Vedic multiplier with minimum quantum cost.The Vedic multiplier is considered fast as it generates all partial product and their sum in one step.This paper proposes two reversible Vedic multipliers with optimized quantum cost and garbage output.First,the unsigned Vedic multiplier is designed based on the Urdhava Tiryakbhyam(UT)Sutra.This multiplier consists of bitwise multiplication and adder compressors.Compared with Vedic multipliers in the literature,the proposed design has a quantum cost of 111 with a reduction of 94%compared to the previous design.It has a garbage output of 30 with optimization of the best-compared design.Second,the proposed unsigned multiplier is expanded to allow the multiplication of signed numbers as well as unsigned numbers.Two signed Vedic multipliers are presented with the aim of obtaining more optimization in performance parameters.DesignI has separate binary two’s complement(B2C)and MUX circuits,while DesignII combines binary two’s complement and MUX circuits in one circuit.DesignI shows the lowest quantum cost,231,regarding state-ofthe-art.DesignII has a quantum cost of 199,reducing to 86.14%of DesignI.The functionality of the proposed multiplier is simulated and verified using XILINX ISE 14.2.
基金Supported by the National Natural Science Foundation of China(Grant No.12071260)。
文摘A graph whose edges are labeled either as positive or negative is called a signed graph.Hameed et al.introduced signed distance and distance compatibility in 2021,initially to characterize balanced signed graphs which have nice spectral properties.This article mainly studies the conjecture proposed by Shijin et al.on the distance compatibility of the direct product of signed graphs,and provides necessary and sufficient conditions for the distance compatibility of the direct product of signed graphs.Some further questions regarding distance compatibility are also posed.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.72371031,62173065,62476045)Fundamental Research Funds for the Central Universities(Grant No.124330008)。
文摘The unique structure of signed networks,characterized by positive and negative edges,poses significant challenges for analyzing network topology.In recent years,various statistical algorithms have been developed to address this issue.However,there remains a lack of a unified framework to uncover the nontrivial properties inherent in signed network structures.To support developers,researchers,and practitioners in this field,we introduce a Python library named SNSAlib(Signed Network Structure Analysis),specifically designed to meet these analytical requirements.This library encompasses empirical signed network datasets,signed null model algorithms,signed statistics algorithms,and evaluation indicators.The primary objective of SNSAlib is to facilitate the systematic analysis of micro-and meso-structure features within signed networks,including node popularity,clustering,assortativity,embeddedness,and community structure by employing more accurate signed null models.Ultimately,it provides a robust paradigm for structure analysis of signed networks that enhances our understanding and application of signed networks.
基金supported by the National Natural Science Foundation of China (52102394,52172384)Hunan Provincial Natural Science Foundation of China (2023JJ10008)Young Elite Scientists Sponsorship Program by CAST (2022QNRC001)。
文摘Unsignalized intersections pose a challenge for autonomous vehicles that must decide how to navigate them safely and efficiently.This paper proposes a reinforcement learning(RL)method for autonomous vehicles to navigate unsignalized intersections safely and efficiently.The method uses a semantic scene representation to handle variable numbers of vehicles and a universal reward function to facilitate stable learning.A collision risk function is designed to penalize unsafe actions and guide the agent to avoid them.A scalable policy optimization algorithm is introduced to improve data efficiency and safety for vehicle learning at intersections.The algorithm employs experience replay to overcome the on-policy limitation of proximal policy optimization and incorporates the collision risk constraint into the policy optimization problem.The proposed safe RL algorithm can balance the trade-off between vehicle traffic safety and policy learning efficiency.Simulated intersection scenarios with different traffic situations are used to test the algorithm and demonstrate its high success rates and low collision rates under different traffic conditions.The algorithm shows the potential of RL for enhancing the safety and reliability of autonomous driving systems at unsignalized intersections.
基金Supported by the National Natural Science Foundation of China(Grant No.12261016)。
文摘A signed graph S=(S^(u),σ)has an underlying graph Suand a functionσ:E(S^(u))-→{+,-}.Let E^(-)(S)denote the set of negative edges of S.Then S is eulerian signed graph(or subeulerian signed graph,or balanced eulerian signed graph,respectively)if Suis eulerian(or subeulerian,or eulerian and|E-(S)|is even,respectively).We say that S is balanced subeulerian signed graph if there exists a balanced eulerian signed graph S′such that S′is spanned by S.The signed line graph L(S)of a signed graph S is a signed graph with the vertices of L(S)being the edges of S,where an edge eiej is in L(S)if and only if the edges e_(i)and e_(j)of S have a vertex in common in S such that an edge eiej in L(S)is negative if and only if both edges ei and ej are negative in S.In this paper,two families of signed graphs S and S′are identified,which are applied to characterize balanced subeulerian signed graphs and balanced subeulerian signed line graphs.In particular,it is proved that a signed graph S is balanced subeulerian if and only if S∈S,and that a signed line graph of signed graph S is balanced subeulerian if and only if S∈S′.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62103375 and 62006106)the Zhejiang Provincial Philosophy and Social Science Planning Project(Grant No.22NDJC009Z)+1 种基金the Education Ministry Humanities and Social Science Foundation of China(Grant Nos.19YJCZH056 and 21YJC630120)the Natural Science Foundation of Zhejiang Province of China(Grant Nos.LY23F030003 and LQ21F020005).
文摘While progress has been made in information source localization,it has overlooked the prevalent friend and adversarial relationships in social networks.This paper addresses this gap by focusing on source localization in signed network models.Leveraging the topological characteristics of signed networks and transforming the propagation probability into effective distance,we propose an optimization method for observer selection.Additionally,by using the reverse propagation algorithm we present a method for information source localization in signed networks.Extensive experimental results demonstrate that a higher proportion of positive edges within signed networks contributes to more favorable source localization,and the higher the ratio of propagation rates between positive and negative edges,the more accurate the source localization becomes.Interestingly,this aligns with our observation that,in reality,the number of friends tends to be greater than the number of adversaries,and the likelihood of information propagation among friends is often higher than among adversaries.In addition,the source located at the periphery of the network is not easy to identify.Furthermore,our proposed observer selection method based on effective distance achieves higher operational efficiency and exhibits higher accuracy in information source localization,compared with three strategies for observer selection based on the classical full-order neighbor coverage.
基金supported by the Natural Science Fund for Distinguished Young Scholars of Jiangsu Province under Grant BK20220067。
文摘With the support of Vehicle-to-Everything(V2X)technology and computing power networks,the existing intersection traffic order is expected to benefit from efficiency improvements and energy savings by new schemes such as de-signalization.How to effectively manage autonomous vehicles for traffic control with high throughput at unsignalized intersections while ensuring safety has been a research hotspot.This paper proposes a collision-free autonomous vehicle scheduling framework based on edge-cloud computing power networks for unsignalized intersections where the lanes entering the intersections are undirectional,and designs an efficient communication system and protocol.First,by analyzing the collision point occupation time,this paper formulates an absolute value programming problem.Second,this problem is solved with low complexity by the Edge Intelligence Optimal Entry Time(EI-OET)algorithm based on edge-cloud computing power support.Then,the communication system and protocol are designed for the proposed scheduling scheme to realize efficient and low-latency vehicular communications.Finally,simulation experiments compare the proposed scheduling framework with directional and traditional traffic light scheduling mechanisms,and the experimental results demonstrate its high efficiency,low latency,and low complexity.
基金supported by the National Language Commission to research on sign language data specifications for artificial intelligence applications and test standards for language service translation systems (No.ZDI145-70)。
文摘Sign language dataset is essential in sign language recognition and translation(SLRT). Current public sign language datasets are small and lack diversity, which does not meet the practical application requirements for SLRT. However, making a large-scale and diverse sign language dataset is difficult as sign language data on the Internet is scarce. In making a large-scale and diverse sign language dataset, some sign language data qualities are not up to standard. This paper proposes a two information streams transformer(TIST) model to judge whether the quality of sign language data is qualified. To verify that TIST effectively improves sign language recognition(SLR), we make two datasets, the screened dataset and the unscreened dataset. In this experiment, this paper uses visual alignment constraint(VAC) as the baseline model. The experimental results show that the screened dataset can achieve better word error rate(WER) than the unscreened dataset.
基金supported by the National Natural Science Foundation of China(No.62066041).
文摘Convolutional neural networks(CNNs)exhibit superior performance in image feature extraction,making them extensively used in the area of traffic sign recognition.However,the design of existing traffic sign recognition algorithms often relies on expert knowledge to enhance the image feature extraction networks,necessitating image preprocessing and model parameter tuning.This increases the complexity of the model design process.This study introduces an evolutionary neural architecture search(ENAS)algorithm for the automatic design of neural network models tailored for traffic sign recognition.By integrating the construction parameters of residual network(ResNet)into evolutionary algorithms(EAs),we automatically generate lightweight networks for traffic sign recognition,utilizing blocks as the fundamental building units.Experimental evaluations on the German traffic sign recognition benchmark(GTSRB)dataset reveal that the algorithm attains a recognition accuracy of 99.32%,with a mere 2.8×10^(6)parameters.Experimental results comparing the proposed method with other traffic sign recognition algorithms demonstrate that the method can more efficiently discover neural network architectures,significantly reducing the number of network parameters while maintaining recognition accuracy.
基金supported by the National Natural Science Foundation of China under Grant Nos.62076117 and 62166026the Jiangxi Provincial Key Laboratory of Virtual Reality under Grant No.2024SSY03151.
文摘Dynamic sign language recognition holds significant importance, particularly with the application of deep learning to address its complexity. However, existing methods face several challenges. Firstly, recognizing dynamic sign language requires identifying keyframes that best represent the signs, and missing these keyframes reduces accuracy. Secondly, some methods do not focus enough on hand regions, which are small within the overall frame, leading to information loss. To address these challenges, we propose a novel Video Transformer Attention-based Network (VTAN) for dynamic sign language recognition. Our approach prioritizes informative frames and hand regions effectively. To tackle the first issue, we designed a keyframe extraction module enhanced by a convolutional autoencoder, which focuses on selecting information-rich frames and eliminating redundant ones from the video sequences. For the second issue, we developed a soft attention-based transformer module that emphasizes extracting features from hand regions, ensuring that the network pays more attention to hand information within sequences. This dual-focus approach improves effective dynamic sign language recognition by addressing the key challenges of identifying critical frames and emphasizing hand regions. Experimental results on two public benchmark datasets demonstrate the effectiveness of our network, outperforming most of the typical methods in sign language recognition tasks.
基金supported by the National Natural Science Foundation of China(Grant Number 52472322)the Shanghai Sailing Program(Grant Number 21YF1415800)+1 种基金the Open Project of Key Laboratory of Advanced Public Transportation Science(Grant Number 2023-APTS-05)the Shanghai SASAC Enterprise Innovation and Capability Enhancement Project(Grant Number 2022016,2023020).
文摘Once a train stops in a tunnel section and requires emergency evacuation,the large distance between stations and long walking distances in the underground spaces of suburban railway systems pose potential risks to the evacuation process on tunnel platforms,especially in complex environments.This study utilized Virtual Reality(VR)technology to construct a virtual experimental platform for tunnel evacuation in suburban railway systems,simulating different combinations of smoke and obstacle conditions.By requiring participants to wear VR glasses and walk on an omnidirectional treadmill for moving,as well as complete psychological questionnaires,the study reveals the influences of No Guiding(NG)signs,Wall-Guided(WG)signs,and Central axis Guidance(CG)signs on the movement abilities and psychological behaviors of participants contrastively.The results show that either smoke conditions or obstacle positions affect the mental stress of participants,and the guidance sign has a positive effect on reducing the mental stress.There is an inverse relationship between mental stress and movement abilities.WG and CG signs respectively lead participants to walk closer to walls and along the central axis,which is conducive to reducing the variation in participants’behavior characteristics when circumventing obstacles on the wall side or track side under smoke conditions,respectively.Additionally,CG signs reduce the speed fluctuations of participants before circumventing obstacles,improving the stability of the distance from the wall and speed under smoke conditions,compared to NG and WG signs.These findings contribute to understanding the evacuation psychological-behavioral-movement characteristics of pedestrians on evacuation platforms in suburban railway tunnels and provide a basis for improving the safety design of evacuation guidance signs.
文摘The arterial pulse tapping artifact,known as Aslanger’s sign,is an electrocardiographic artifact resulting from the transmission of arterial pulsation onto the limb electrodes of the standard 12-lead electrocardiograph(ECG)which are placed near the radial or posterior tibial arteries.[1-16]This electromechanical artifact is of cardiac origin and is synchronous with the cardiac cycle.[17]Nearly all reported cases of Aslanger’s sign exhibit an unusual waveform morphology in all 12 leads except one limb lead.[1-14,16]However,we previously reported a case of Aslanger’s sign that showed distorted waveforms from the ST to TP segments observed only in five limb leads among 12 leads.
基金co-supported by the National Natural Science Foundation of China(Nos.12372048,12102343)the Key Program of the National Natural Science Foundation of China(No.U2013206)+1 种基金the China Postdoctoral Science Foundation(No.2023M742835)the Guangdong Basic and Applied Basic Research Foundation,China(No.2023A1515011421).
文摘This paper presents a predefined-time controller for Multiple Space transportation Robots System (MSRS), which can be applied in on-orbit assembly tasks to transport modules to pre-assembly configuration quickly. Firstly, to simplify the analysis and design of predefined-time controller, a Predefined-time Stability Criterion is proposed in the form of Composite Lyapunov Function (CLF-PSC). Besides simplicity, the CLF-PSC also has the advantage of less conservativeness due to utilization of initial state information. Secondly, a concept of Lp-Norm-Normalized Sign Function (LPNNSF) is proposed based on the CLF-PSC. Different from traditional norm-normalized sign function, the Lp-norm of LPNNSF can be selected arbitrarily according to practical control task requirements, which means that the proposed LPNNSF is more generalized and more convenient for calculation. Thirdly, a predefined-time disturbance observer and predefined-time controller are designed based on the LPNNSF. The observer has the property of predefined-time convergence to achieve quicker and more accurate estimation of the lumped disturbance. The controller has less control input and chattering phenomenon than traditional predefined-time controller. In addition, by introducing the observer into the controller, the closed-loop system enjoys high precision and strong robustness. Finally, the effectiveness of the proposed controller is verified by numerical simulations. By employing the controller, the MSRS can carry assembly modules to the desired pre-assembly configuration accurately within predefined time.
基金funding this work through Research Group No.KS-2024-376.
文摘Arabic Sign Language(ArSL)recognition plays a vital role in enhancing the communication for the Deaf and Hard of Hearing(DHH)community.Researchers have proposed multiple methods for automated recognition of ArSL;however,these methods face multiple challenges that include high gesture variability,occlusions,limited signer diversity,and the scarcity of large annotated datasets.Existing methods,often relying solely on either skeletal data or video-based features,struggle with generalization and robustness,especially in dynamic and real-world conditions.This paper proposes a novel multimodal ensemble classification framework that integrates geometric features derived from 3D skeletal joint distances and angles with temporal features extracted from RGB videos using the Inflated 3D ConvNet(I3D).By fusing these complementary modalities at the feature level and applying a majority-voting ensemble of XGBoost,Random Forest,and Support Vector Machine classifiers,the framework robustly captures both spatial configurations and motion dynamics of sign gestures.Feature selection using the Pearson Correlation Coefficient further enhances efficiency by reducing redundancy.Extensive experiments on the ArabSign dataset,which includes RGB videos and corresponding skeletal data,demonstrate that the proposed approach significantly outperforms state-of-the-art methods,achieving an average F1-score of 97%using a majority-voting ensemble of XGBoost,Random Forest,and SVM classifiers,and improving recognition accuracy by more than 7%over previous best methods.This work not only advances the technical stateof-the-art in ArSL recognition but also provides a scalable,real-time solution for practical deployment in educational,social,and assistive communication technologies.Even though this study is about Arabic Sign Language,the framework proposed here can be extended to different sign languages,creating possibilities for potentially worldwide applicability in sign language recognition tasks.
基金supported by the Shanxi Agricultural University Science and Technology Innovation Enhancement Project。
文摘This paper proposes a lightweight traffic sign detection system based on you only look once(YOLO).Firstly,the classification to fusion(C2f)structure is integrated into the backbone network,employing deformable convolution and bi-directional feature pyramid network(BiFPN)_Concat to improve the adaptability of the network.Secondly,the simple attention module(SimAm)is embedded to prioritize key features and reduce the complexity of the model after the C2f layer at the end of the backbone network.Next,the focal efficient intersection over union(EloU)is introduced to adjust the weights of challenging samples.Finally,we accomplish the design and deployment for the mobile app.The results demonstrate improvements,with the F1 score of 0.8987,mean average precision(mAP)@0.5 of 98.8%,mAP@0.5:0.95 of 75.6%,and the detection speed of 50 frames per second(FPS).
基金Beijing Natural Science Foundation-Fengtai Rail Transit Frontier Research Joint Foundation(No.L211024),the National Natural Science Foundation of China(No.52072012).
文摘To explore the influence of emergency evacuation signs on passenger behavior during subway fires and improve evacuation efficiency in emergencies,this paper proposes a dynamic emergency evacuation sign system.A simulation platform integrating building information modeling(BIM)and virtual reality(VR)technologies was em-ployed to create subway fire evacuation scenarios using both the current and proposed dynamic emergency evacuation signage systems.Through simulation experiments,fine-grained microscopic data on passenger behavior was collected.Seven indicators were selected to assess evacuation efficiency and wayfinding difficulty.The analysis explored the influence of evacuation signs on passenger behavior in both overall and decision-making areas,thereby validating the effectiveness of the new emergency evacuation signage system.The results show that the dynamic evacuation signage system significantly improves overall passenger evacuation efficiency and reduces decision-making errors.It also improves wayfinding efficiency in critical decision areas by reducing the need for direction identification,minimizing stopping times,and lowering the frequency of decision errors.The method for evaluating the effects of emergency evacuation signs on passenger evacuation behavior proposed in this study provides a robust theoretical basis for the design and optimization of emergency-oriented signs.
文摘This is subsequent of , by using the theory of additive fuzzy measure and signed additive fuzzy measure , we prove the Radon_Nikodym Theorem and Lebesgue decomposition Theorem of signed additive fuzzy measure.
