With China's rapid development of the construction of modern campus,the school's increasing popularity and status as well as the growing number of foreign exchange.Current campus information,human development ...With China's rapid development of the construction of modern campus,the school's increasing popularity and status as well as the growing number of foreign exchange.Current campus information,human development has gradually become a new issue on the development and construction of schools.The article through the analyzing on design features of the modern Campus Sign System to meet the needs of different groups,and the information can be effective used through the modern Campus Sign System between peoples and campus.So that in their daily life,work and other needs are fully met.展开更多
Reliable detection of traffic signs and lights(TSLs)at long range and under varying illumination is essen-tial for improving the perception and safety of autonomous driving systems(ADS).Traditional object detection mo...Reliable detection of traffic signs and lights(TSLs)at long range and under varying illumination is essen-tial for improving the perception and safety of autonomous driving systems(ADS).Traditional object detection models often exhibit significant performance degradation in real-world environments characterized by high dynamic range and complex lighting conditions.To overcome these limitations,this research presents FED-YOLOv10s,an improved and lightweight object detection framework based on You Only look Once v10(YOLOv10).The proposed model integrates a C2f-Faster block derived from FasterNet to reduce parameters and floating-point operations,an Efficient Multiscale Attention(EMA)mechanism to improve TSL-invariant feature extraction,and a deformable Convolution Networks v4(DCNv4)module to enhance multiscale spatial adaptability.Experimental findings demonstrate that the proposed architecture achieves an optimal balance between computational efficiency and detection accuracy,attaining an F1-score of 91.8%,and mAP@0.5 of 95.1%,while reducing parameters to 8.13 million.Comparative analyses across multiple traffic sign detection benchmarks demonstrate that FED-YOLOv10s outperforms state-of-the-art models in precision,recall,and mAP.These results highlight FED-YOLOv10s as a robust,efficient,and deployable solution for intelligent traffic perception in ADS.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
This paper proposes a model-based control framework for vehicle platooning systems with secondorder nonlinear dynamics operating over switching signed networks,time-varying delays,and deception attacks.The study inclu...This paper proposes a model-based control framework for vehicle platooning systems with secondorder nonlinear dynamics operating over switching signed networks,time-varying delays,and deception attacks.The study includes two configurations:a leaderless structure using Finite-Time Non-Singular Terminal Bipartite Consensus(FNTBC)and Fixed-Time Bipartite Consensus(FXTBC),and a leader—follower structure ensuring structural balance and robustness against deceptive signals.In the leaderless model,a bipartite controller based on impulsive control theory,gauge transformation,and Markovian switching Lyapunov functions ensures mean-square stability and coordination under deception attacks and communication delays.The FNTBC achieves finite-time convergence depending on initial conditions,while the FXTBC guarantees fixed-time convergence independent of them,providing adaptability to different operating states.In the leader—follower case,a discontinuous impulsive control law synchronizes all followers with the leader despite deceptive attacks and switching topologies,maintaining robust coordination through nonlinear corrective mechanisms.To validate the approach,simulations are conducted on systems of five and seventeen vehicles in both leaderless and leader—follower configurations.The results demonstrate that the proposed framework achieves rapid consensus,strong robustness,and high resistance to deception attacks,offering a secure and scalable model-based control solution for modern vehicular communication networks.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
Traffic sign detection is a critical component of driving systems.Single-stage network-based traffic sign detection algorithms,renowned for their fast detection speeds and high accuracy,have become the dominant approa...Traffic sign detection is a critical component of driving systems.Single-stage network-based traffic sign detection algorithms,renowned for their fast detection speeds and high accuracy,have become the dominant approach in current practices.However,in complex and dynamic traffic scenes,particularly with smaller traffic sign objects,challenges such as missed and false detections can lead to reduced overall detection accuracy.To address this issue,this paper proposes a detection algorithm that integrates edge and shape information.Recognizing that traffic signs have specific shapes and distinct edge contours,this paper introduces an edge feature extraction branch within the backbone network,enabling adaptive fusion with features of the same hierarchical level.Additionally,a shape prior convolution module is designed to replaces the first two convolutional modules of the backbone network,aimed at enhancing the model's perception ability for specific shape objects and reducing its sensitivity to background noise.The algorithm was evaluated on the CCTSDB and TT100k datasets,and compared to YOLOv8s,the mAP50 values increased by 3.0%and 10.4%,respectively,demonstrating the effectiveness of the proposed method in improving the accuracy of traffic sign detection.展开更多
Traffic sign detection is an important part of autonomous driving,and its recognition accuracy and speed are directly related to road traffic safety.Although convolutional neural networks(CNNs)have made certain breakt...Traffic sign detection is an important part of autonomous driving,and its recognition accuracy and speed are directly related to road traffic safety.Although convolutional neural networks(CNNs)have made certain breakthroughs in this field,in the face of complex scenes,such as image blur and target occlusion,the traffic sign detection continues to exhibit limited accuracy,accompanied by false positives and missed detections.To address the above problems,a traffic sign detection algorithm,You Only Look Once-based Skip Dynamic Way(YOLO-SDW)based on You Only Look Once version 8 small(YOLOv8s),is proposed.Firstly,a Skip Connection Reconstruction(SCR)module is introduced to efficiently integrate fine-grained feature information and enhance the detection accuracy of the algorithm in complex scenes.Secondly,a C2f module based on Dynamic Snake Convolution(C2f-DySnake)is proposed to dynamically adjust the receptive field information,improve the algorithm’s feature extraction ability for blurred or occluded targets,and reduce the occurrence of false detections and missed detections.Finally,the Wise Powerful IoU v2(WPIoUv2)loss function is proposed to further improve the detection accuracy of the algorithm.Experimental results show that the average precision mAP@0.5 of YOLO-SDW on the TT100K dataset is 89.2%,and mAP@0.5:0.95 is 68.5%,which is 4%and 3.3%higher than the YOLOv8s baseline,respectively.YOLO-SDW ensures real-time performance while having higher accuracy.展开更多
Fault diagnosis of various systems on rolling stock has drawn the attention of many researchers. However, obtaining an optimized sensor set of these systems, which is a prerequisite for fault diagnosis, remains a majo...Fault diagnosis of various systems on rolling stock has drawn the attention of many researchers. However, obtaining an optimized sensor set of these systems, which is a prerequisite for fault diagnosis, remains a major challenge. Available literature suggests that the configuration of sensors in these systems is presently dependent on the knowledge and engineering experiences of designers, which may lead to insufficient or redundant development of various sensors. In this paper, the optimization of sensor sets is addressed by using the signed digraph （SDG） method. The method is modified for use in braking systems by the introduction of an effect-function method to replace the traditional quantitative methods. Two criteria are adopted to evaluate the capability of the sensor sets, namely, observability and resolution. The sensors configuration method of braking system is proposed. It consists of generating bipartite graphs from SDG models and then solving the set cover problem using a greedy algorithm. To demonstrate the improvement, the sensor configuration of the HP2008 braking system is investigated and fault diagnosis on a test bench is performed. The test results show that SDG algorithm can improve single-fault resolution from 6 faults to 10 faults, and with additional four brake cylinder pressure （BCP） sensors it can cover up to 67 double faults which were not considered by traditional fault diagnosis system. SDG methods are suitable for reducing redundant sensors and that the sensor sets thereby obtained are capable of detecting typical faults, such as the failure of a release valve. This study investigates the formal extension of the SDG method to the sensor configuration of braking system, as well as the adaptation supported by the effect-function method.展开更多
In this paper, an adaptive fuzzy robust feedback control approach is proposed for a class of single-input and singleoutput （SISO） strict-feedback nonlinear systems with unknown nonlinear functions, time delays, unkn...In this paper, an adaptive fuzzy robust feedback control approach is proposed for a class of single-input and singleoutput （SISO） strict-feedback nonlinear systems with unknown nonlinear functions, time delays, unknown high-frequency gain sign, and without the measurements of the states. In the backstepping recursive design, fuzzy logic systems are employed to approximate the unknown smooth nonlinear functions, K-filters is designed to estimate the unmeasured states, and Nussbaum gain functions are introduced to solve the problem of unknown sign of high-frequency gain. By combining adaptive fuzzy control theory and adaptive backstepping design, a stable adaptive fuzzy output feedback control scheme is developed. It has been proven that the proposed adaptive fuzzy robust control approach can guarantee that all the signals of the closed-loop system are uniformly ultimately bounded and the tracking error can converge to a small neighborhood of the origin by appropriately choosing design parameters. Simulation results have shown the effectiveness of the proposed method.展开更多
This paper presents the implementation of an embedded automotive system that detects and recognizes traffic signs within a video stream. In addition, it discusses the recent advances in driver assistance technologies ...This paper presents the implementation of an embedded automotive system that detects and recognizes traffic signs within a video stream. In addition, it discusses the recent advances in driver assistance technologies and highlights the safety motivations for smart in-car embedded systems. An algorithm is presented that processes RGB image data, extracts relevant pixels, filters the image, labels prospective traffic signs and evaluates them against template traffic sign images. A reconfigurable hardware system is described which uses the Virtex-5 Xilinx FPGA and hardware/software co-design tools in order to create an embedded processor and the necessary hardware IP peripherals. The implementation is shown to have robust performance results, both in terms of timing and accuracy.展开更多
In this paper we discuss the topological structure near the singular point O (0,0) of the plane cubic system in the undetermined sign case, and give their coefficient conditions.
Objective: Influenza is a highly infectious viral disease, which occurs epidemically almost every winter in Japan. Rapid screening of patients with suspected influenza in places of mass gathering is important to delay...Objective: Influenza is a highly infectious viral disease, which occurs epidemically almost every winter in Japan. Rapid screening of patients with suspected influenza in places of mass gathering is important to delay or prevent transmission of the infection. The aim of this study was to assess the effectiveness of our newly developed infection screening system that employed vital signs and percutaneous oxygen saturation (SpO2) as parameters in a clinical setting. Methods: Since SpO2 accurately reflects respiratory status during influenza virus infection, we upgraded our previous system by adding SpO2 as a new parameter to improve the screening accuracy. This system instantly measures SpO2 and vital signs (i.e., heart rate, respiration rate, and facial temperature), which automatically detects infected individuals via a neural network-based nonlinear discriminant function using these derived parameters. We tested the system on 45 patients with seasonal influenza (35.8℃ < body temperature < 40.0℃, 18-35 years) and 64 normal control subjects (35.0℃ < body temperature < 37.5℃, 18-30 years) at Japan Self-Defense Central Hospital in 2012. Results: The system identified 40/45 patients with influenza and 60/64 normal control subjects, and provided sensitivity, specificity, and positive and negative predictive value (PPV, NPV) of 88.8%, 93.8%, 90.9%, and 92.3%, respectively. By including SpO2 as a screening parameter, we achieved superior sensitivity and NPV compared to that reported in our previous paper (sensitivity = 88%;NPV = 82%). Conclusions: Our results suggest that SpO2 is a good screening parameter that improves the accuracy of infection screening. The proposed system has the potential to efficiently identify infected individuals, thereby delaying or preventing the spread of infection during epidemic seasons.展开更多
For direct sequence spread spectrum (DSSS) communication systems suffering interference, it is known that code-aided interference suppression technique outperforms all of the previous linear or nonlinear methods. In t...For direct sequence spread spectrum (DSSS) communication systems suffering interference, it is known that code-aided interference suppression technique outperforms all of the previous linear or nonlinear methods. In this paper, we proposed an improved code-aided technique which can improve the system performance greatly by using the eigenvector sign (EVS) spreading sequence which depends on the statistical characteristics of the interference and the thermal noise.展开更多
Information Accessibility for disabled people is one of the most important design criteria for the China National Digital Library (CNDL) development. Sign language synthesis systems are effective to provide informatio...Information Accessibility for disabled people is one of the most important design criteria for the China National Digital Library (CNDL) development. Sign language synthesis systems are effective to provide information services for people with hearing and speech impairments. This paper presents a framework of a sign language synthesis system application in CNDL, as well as discusses the relevant technologies applied in the system. CNDL has been a real practice area for the sign language synthesis research.展开更多
This paper describes an approximated-scalar-sign-function-based anti-windup digital control design for analog nonlinear systems subject to input constraints. As input saturation occurs, the non-smooth saturation const...This paper describes an approximated-scalar-sign-function-based anti-windup digital control design for analog nonlinear systems subject to input constraints. As input saturation occurs, the non-smooth saturation constraint is modeled with the approximated scalar sign function which is a smooth nonlinear function. The resulting nonlinear model is further linearized at any operating point with the optimal linearization technique, and Linear Quadratic Regulator (LQR) is then applied for a state-feedback controller optimal for each operating point. As input saturation is encountered, an iterative procedure is developed to adjust control gains by systematically updating LQR weighting matrices until the inputs lie within the saturation limits. Through global digital redesign, the analog LQR controller is converted to an equivalent digital one for keeping the essential control performance, and moreover, delay compensation is taken into account during digital redesign for compensating the potential time delays in a control loop. The swing-up and stabilization control of single rotary inverted pendulum system is used to illustrate and verify the proposed method.展开更多
Arabic Sign Language (ArSL) is the native language for the Arab deaf community. ArSL allows deaf people to communicate among themselves and with non-deaf people around them to express their needs, thoughts and feeling...Arabic Sign Language (ArSL) is the native language for the Arab deaf community. ArSL allows deaf people to communicate among themselves and with non-deaf people around them to express their needs, thoughts and feelings. Opposite to spoken languages, Sign Language (SL) depends on hands and facial expression to express the thought instead of sounds. In recent years, interest in translating sign language automatically for different languages has increased. However, a small set of these works are specialized in ArSL. Basically, these works translate word by word without taking care of the semantics of the translated sentence or the translation rules of Arabic text to Arabic sign language. In this paper we present a proposed system for semantically translating Arabic text to Arabic SignWriting in the jurisprudence of prayer domain. The system is designed to translate Arabic text by applying Arabic Sign Language (ArSL) grammatical rules as well as semantically looking up the words in domain ontology. The results of qualitatively evaluating the system based on a SignWriting expert judgment proved the correctness of the translation results.展开更多
A multidisciplinary approach for developing an intelligent sign multi-language recognition system to greatly enhance deaf-mute communication will be discussed and implemented. This involves designing a low-cost glove-...A multidisciplinary approach for developing an intelligent sign multi-language recognition system to greatly enhance deaf-mute communication will be discussed and implemented. This involves designing a low-cost glove-based sensing system, collecting large and diverse datasets, preprocessing the data, and using efficient machine learning models. Furthermore, the glove is integrated with a user-friendly mobile application called “Life-sign” for this system. The main goal of this work is to minimize the processing time of machine learning classifiers while maintaining higher accuracy performance. This is achieved by using effective preprocessing algorithms to handle noisy and inconsistent data. Testing and iterating approaches have been applied to various classifiers to refine and improve their accuracy in the recognition process. Additionally, the Extra Trees (ET) classifier has been identified as the best algorithm, with results proving successful gesture prediction at an average accuracy of about 99.54%. A smart optimization feature has been implemented to control the size of data transferred via Bluetooth, allowing for fast recognition of consecutive gestures. Real-time performance has been measured through extensive experimental testing on various consecutive gestures, specifically referring to Arabic Sign Language (ArSL). The results have demonstrated that the system guarantees consecutive gesture recognition with a lower delay of 50 milliseconds.展开更多
Designing accurate and time-efficient real-time traffic sign recognition systems is a crucial part of developing the intelligent vehicle which is the main agent in the intelligent transportation system.Traffic sign re...Designing accurate and time-efficient real-time traffic sign recognition systems is a crucial part of developing the intelligent vehicle which is the main agent in the intelligent transportation system.Traffic sign recognition systems consist of an initial detection phase where images transportaand colors are segmented and fed to the recognition phase.The most challenging process in such systems in terms of time consumption is the detection phase.The trade off in previous studies,which proposed different methods for detecting traffic signs,is between accuracy and computation time,Therefore,this paper presents a novel accurate and time-efficient color segmentation approach based on logistic regression.We used RGB color space as the domain to extract the features of our hypothesis;this has boosted the speed of our approach since no color conversion is needed.Our trained segmentation classifier was tested on 1000 traffic sign images taken in different lighting conditions.The results show that our approach segmented 974 of these images correctly and in a time less than one-fifth of the time needed by any other robust segmentation method.展开更多
On May 8,2015,under the witness of Chinese President XI Jinping and Russian Federation President Vladimir Putin,on behalf of two countries,China Satellite Navigation System Committee Chairman WANG Li and Russian Feder...On May 8,2015,under the witness of Chinese President XI Jinping and Russian Federation President Vladimir Putin,on behalf of two countries,China Satellite Navigation System Committee Chairman WANG Li and Russian Federal Space Agency Chief Igor Komarov signed the"China’s Bei Dou System and Russian Glonass System Compatibility and Interoperability Cooperation Joint Statement".It indicates that the navigation cooperation be-展开更多
文摘With China's rapid development of the construction of modern campus,the school's increasing popularity and status as well as the growing number of foreign exchange.Current campus information,human development has gradually become a new issue on the development and construction of schools.The article through the analyzing on design features of the modern Campus Sign System to meet the needs of different groups,and the information can be effective used through the modern Campus Sign System between peoples and campus.So that in their daily life,work and other needs are fully met.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,Saudi Arabia under Grant No.IPP:172-830-2025.
文摘Reliable detection of traffic signs and lights(TSLs)at long range and under varying illumination is essen-tial for improving the perception and safety of autonomous driving systems(ADS).Traditional object detection models often exhibit significant performance degradation in real-world environments characterized by high dynamic range and complex lighting conditions.To overcome these limitations,this research presents FED-YOLOv10s,an improved and lightweight object detection framework based on You Only look Once v10(YOLOv10).The proposed model integrates a C2f-Faster block derived from FasterNet to reduce parameters and floating-point operations,an Efficient Multiscale Attention(EMA)mechanism to improve TSL-invariant feature extraction,and a deformable Convolution Networks v4(DCNv4)module to enhance multiscale spatial adaptability.Experimental findings demonstrate that the proposed architecture achieves an optimal balance between computational efficiency and detection accuracy,attaining an F1-score of 91.8%,and mAP@0.5 of 95.1%,while reducing parameters to 8.13 million.Comparative analyses across multiple traffic sign detection benchmarks demonstrate that FED-YOLOv10s outperforms state-of-the-art models in precision,recall,and mAP.These results highlight FED-YOLOv10s as a robust,efficient,and deployable solution for intelligent traffic perception in ADS.
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Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under grant number RGP.2/103/46”Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia for funding this research work through project number“NBU-FFR-2025-871-15”funding from Prince Sattam bin Abdulaziz University project number(PSAU/2025/R/1447).
文摘This paper proposes a model-based control framework for vehicle platooning systems with secondorder nonlinear dynamics operating over switching signed networks,time-varying delays,and deception attacks.The study includes two configurations:a leaderless structure using Finite-Time Non-Singular Terminal Bipartite Consensus(FNTBC)and Fixed-Time Bipartite Consensus(FXTBC),and a leader—follower structure ensuring structural balance and robustness against deceptive signals.In the leaderless model,a bipartite controller based on impulsive control theory,gauge transformation,and Markovian switching Lyapunov functions ensures mean-square stability and coordination under deception attacks and communication delays.The FNTBC achieves finite-time convergence depending on initial conditions,while the FXTBC guarantees fixed-time convergence independent of them,providing adaptability to different operating states.In the leader—follower case,a discontinuous impulsive control law synchronizes all followers with the leader despite deceptive attacks and switching topologies,maintaining robust coordination through nonlinear corrective mechanisms.To validate the approach,simulations are conducted on systems of five and seventeen vehicles in both leaderless and leader—follower configurations.The results demonstrate that the proposed framework achieves rapid consensus,strong robustness,and high resistance to deception attacks,offering a secure and scalable model-based control solution for modern vehicular communication networks.
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.
基金supported by the National Natural Science Foundation of China(Grant Nos.62572057,62272049,U24A20331)Beijing Natural Science Foundation(Grant Nos.4232026,4242020)Academic Research Projects of Beijing Union University(Grant No.ZK10202404).
文摘Traffic sign detection is a critical component of driving systems.Single-stage network-based traffic sign detection algorithms,renowned for their fast detection speeds and high accuracy,have become the dominant approach in current practices.However,in complex and dynamic traffic scenes,particularly with smaller traffic sign objects,challenges such as missed and false detections can lead to reduced overall detection accuracy.To address this issue,this paper proposes a detection algorithm that integrates edge and shape information.Recognizing that traffic signs have specific shapes and distinct edge contours,this paper introduces an edge feature extraction branch within the backbone network,enabling adaptive fusion with features of the same hierarchical level.Additionally,a shape prior convolution module is designed to replaces the first two convolutional modules of the backbone network,aimed at enhancing the model's perception ability for specific shape objects and reducing its sensitivity to background noise.The algorithm was evaluated on the CCTSDB and TT100k datasets,and compared to YOLOv8s,the mAP50 values increased by 3.0%and 10.4%,respectively,demonstrating the effectiveness of the proposed method in improving the accuracy of traffic sign detection.
基金funded by Key research and development Program of Henan Province(No.251111211200)National Natural Science Foundation of China(Grant No.U2004163).
文摘Traffic sign detection is an important part of autonomous driving,and its recognition accuracy and speed are directly related to road traffic safety.Although convolutional neural networks(CNNs)have made certain breakthroughs in this field,in the face of complex scenes,such as image blur and target occlusion,the traffic sign detection continues to exhibit limited accuracy,accompanied by false positives and missed detections.To address the above problems,a traffic sign detection algorithm,You Only Look Once-based Skip Dynamic Way(YOLO-SDW)based on You Only Look Once version 8 small(YOLOv8s),is proposed.Firstly,a Skip Connection Reconstruction(SCR)module is introduced to efficiently integrate fine-grained feature information and enhance the detection accuracy of the algorithm in complex scenes.Secondly,a C2f module based on Dynamic Snake Convolution(C2f-DySnake)is proposed to dynamically adjust the receptive field information,improve the algorithm’s feature extraction ability for blurred or occluded targets,and reduce the occurrence of false detections and missed detections.Finally,the Wise Powerful IoU v2(WPIoUv2)loss function is proposed to further improve the detection accuracy of the algorithm.Experimental results show that the average precision mAP@0.5 of YOLO-SDW on the TT100K dataset is 89.2%,and mAP@0.5:0.95 is 68.5%,which is 4%and 3.3%higher than the YOLOv8s baseline,respectively.YOLO-SDW ensures real-time performance while having higher accuracy.
基金Supported by National Hi-tech Research and Development Program of China(863 Program,Grant No.2011AA110503-3)Fundamental Research Funds for the Central Universities of China(Grant No.2860219030)Foundation of Traction Power State Key Laboratory of Southwest Jiaotong University,China(Grant No.TPL1308)
文摘Fault diagnosis of various systems on rolling stock has drawn the attention of many researchers. However, obtaining an optimized sensor set of these systems, which is a prerequisite for fault diagnosis, remains a major challenge. Available literature suggests that the configuration of sensors in these systems is presently dependent on the knowledge and engineering experiences of designers, which may lead to insufficient or redundant development of various sensors. In this paper, the optimization of sensor sets is addressed by using the signed digraph （SDG） method. The method is modified for use in braking systems by the introduction of an effect-function method to replace the traditional quantitative methods. Two criteria are adopted to evaluate the capability of the sensor sets, namely, observability and resolution. The sensors configuration method of braking system is proposed. It consists of generating bipartite graphs from SDG models and then solving the set cover problem using a greedy algorithm. To demonstrate the improvement, the sensor configuration of the HP2008 braking system is investigated and fault diagnosis on a test bench is performed. The test results show that SDG algorithm can improve single-fault resolution from 6 faults to 10 faults, and with additional four brake cylinder pressure （BCP） sensors it can cover up to 67 double faults which were not considered by traditional fault diagnosis system. SDG methods are suitable for reducing redundant sensors and that the sensor sets thereby obtained are capable of detecting typical faults, such as the failure of a release valve. This study investigates the formal extension of the SDG method to the sensor configuration of braking system, as well as the adaptation supported by the effect-function method.
基金supported by National Natural Science Foundation of China (No. 61074014)the Outstanding Youth Funds of Liaoning Province (No. 2005219001)Educational Department of Liaoning Province (No. 2006R29, No. 2007T80)
文摘In this paper, an adaptive fuzzy robust feedback control approach is proposed for a class of single-input and singleoutput （SISO） strict-feedback nonlinear systems with unknown nonlinear functions, time delays, unknown high-frequency gain sign, and without the measurements of the states. In the backstepping recursive design, fuzzy logic systems are employed to approximate the unknown smooth nonlinear functions, K-filters is designed to estimate the unmeasured states, and Nussbaum gain functions are introduced to solve the problem of unknown sign of high-frequency gain. By combining adaptive fuzzy control theory and adaptive backstepping design, a stable adaptive fuzzy output feedback control scheme is developed. It has been proven that the proposed adaptive fuzzy robust control approach can guarantee that all the signals of the closed-loop system are uniformly ultimately bounded and the tracking error can converge to a small neighborhood of the origin by appropriately choosing design parameters. Simulation results have shown the effectiveness of the proposed method.
文摘This paper presents the implementation of an embedded automotive system that detects and recognizes traffic signs within a video stream. In addition, it discusses the recent advances in driver assistance technologies and highlights the safety motivations for smart in-car embedded systems. An algorithm is presented that processes RGB image data, extracts relevant pixels, filters the image, labels prospective traffic signs and evaluates them against template traffic sign images. A reconfigurable hardware system is described which uses the Virtex-5 Xilinx FPGA and hardware/software co-design tools in order to create an embedded processor and the necessary hardware IP peripherals. The implementation is shown to have robust performance results, both in terms of timing and accuracy.
文摘In this paper we discuss the topological structure near the singular point O (0,0) of the plane cubic system in the undetermined sign case, and give their coefficient conditions.
文摘Objective: Influenza is a highly infectious viral disease, which occurs epidemically almost every winter in Japan. Rapid screening of patients with suspected influenza in places of mass gathering is important to delay or prevent transmission of the infection. The aim of this study was to assess the effectiveness of our newly developed infection screening system that employed vital signs and percutaneous oxygen saturation (SpO2) as parameters in a clinical setting. Methods: Since SpO2 accurately reflects respiratory status during influenza virus infection, we upgraded our previous system by adding SpO2 as a new parameter to improve the screening accuracy. This system instantly measures SpO2 and vital signs (i.e., heart rate, respiration rate, and facial temperature), which automatically detects infected individuals via a neural network-based nonlinear discriminant function using these derived parameters. We tested the system on 45 patients with seasonal influenza (35.8℃ < body temperature < 40.0℃, 18-35 years) and 64 normal control subjects (35.0℃ < body temperature < 37.5℃, 18-30 years) at Japan Self-Defense Central Hospital in 2012. Results: The system identified 40/45 patients with influenza and 60/64 normal control subjects, and provided sensitivity, specificity, and positive and negative predictive value (PPV, NPV) of 88.8%, 93.8%, 90.9%, and 92.3%, respectively. By including SpO2 as a screening parameter, we achieved superior sensitivity and NPV compared to that reported in our previous paper (sensitivity = 88%;NPV = 82%). Conclusions: Our results suggest that SpO2 is a good screening parameter that improves the accuracy of infection screening. The proposed system has the potential to efficiently identify infected individuals, thereby delaying or preventing the spread of infection during epidemic seasons.
基金the National Natural Science Foundation of China (No. 60772100)
文摘For direct sequence spread spectrum (DSSS) communication systems suffering interference, it is known that code-aided interference suppression technique outperforms all of the previous linear or nonlinear methods. In this paper, we proposed an improved code-aided technique which can improve the system performance greatly by using the eigenvector sign (EVS) spreading sequence which depends on the statistical characteristics of the interference and the thermal noise.
文摘Information Accessibility for disabled people is one of the most important design criteria for the China National Digital Library (CNDL) development. Sign language synthesis systems are effective to provide information services for people with hearing and speech impairments. This paper presents a framework of a sign language synthesis system application in CNDL, as well as discusses the relevant technologies applied in the system. CNDL has been a real practice area for the sign language synthesis research.
文摘This paper describes an approximated-scalar-sign-function-based anti-windup digital control design for analog nonlinear systems subject to input constraints. As input saturation occurs, the non-smooth saturation constraint is modeled with the approximated scalar sign function which is a smooth nonlinear function. The resulting nonlinear model is further linearized at any operating point with the optimal linearization technique, and Linear Quadratic Regulator (LQR) is then applied for a state-feedback controller optimal for each operating point. As input saturation is encountered, an iterative procedure is developed to adjust control gains by systematically updating LQR weighting matrices until the inputs lie within the saturation limits. Through global digital redesign, the analog LQR controller is converted to an equivalent digital one for keeping the essential control performance, and moreover, delay compensation is taken into account during digital redesign for compensating the potential time delays in a control loop. The swing-up and stabilization control of single rotary inverted pendulum system is used to illustrate and verify the proposed method.
文摘Arabic Sign Language (ArSL) is the native language for the Arab deaf community. ArSL allows deaf people to communicate among themselves and with non-deaf people around them to express their needs, thoughts and feelings. Opposite to spoken languages, Sign Language (SL) depends on hands and facial expression to express the thought instead of sounds. In recent years, interest in translating sign language automatically for different languages has increased. However, a small set of these works are specialized in ArSL. Basically, these works translate word by word without taking care of the semantics of the translated sentence or the translation rules of Arabic text to Arabic sign language. In this paper we present a proposed system for semantically translating Arabic text to Arabic SignWriting in the jurisprudence of prayer domain. The system is designed to translate Arabic text by applying Arabic Sign Language (ArSL) grammatical rules as well as semantically looking up the words in domain ontology. The results of qualitatively evaluating the system based on a SignWriting expert judgment proved the correctness of the translation results.
文摘A multidisciplinary approach for developing an intelligent sign multi-language recognition system to greatly enhance deaf-mute communication will be discussed and implemented. This involves designing a low-cost glove-based sensing system, collecting large and diverse datasets, preprocessing the data, and using efficient machine learning models. Furthermore, the glove is integrated with a user-friendly mobile application called “Life-sign” for this system. The main goal of this work is to minimize the processing time of machine learning classifiers while maintaining higher accuracy performance. This is achieved by using effective preprocessing algorithms to handle noisy and inconsistent data. Testing and iterating approaches have been applied to various classifiers to refine and improve their accuracy in the recognition process. Additionally, the Extra Trees (ET) classifier has been identified as the best algorithm, with results proving successful gesture prediction at an average accuracy of about 99.54%. A smart optimization feature has been implemented to control the size of data transferred via Bluetooth, allowing for fast recognition of consecutive gestures. Real-time performance has been measured through extensive experimental testing on various consecutive gestures, specifically referring to Arabic Sign Language (ArSL). The results have demonstrated that the system guarantees consecutive gesture recognition with a lower delay of 50 milliseconds.
文摘Designing accurate and time-efficient real-time traffic sign recognition systems is a crucial part of developing the intelligent vehicle which is the main agent in the intelligent transportation system.Traffic sign recognition systems consist of an initial detection phase where images transportaand colors are segmented and fed to the recognition phase.The most challenging process in such systems in terms of time consumption is the detection phase.The trade off in previous studies,which proposed different methods for detecting traffic signs,is between accuracy and computation time,Therefore,this paper presents a novel accurate and time-efficient color segmentation approach based on logistic regression.We used RGB color space as the domain to extract the features of our hypothesis;this has boosted the speed of our approach since no color conversion is needed.Our trained segmentation classifier was tested on 1000 traffic sign images taken in different lighting conditions.The results show that our approach segmented 974 of these images correctly and in a time less than one-fifth of the time needed by any other robust segmentation method.
文摘On May 8,2015,under the witness of Chinese President XI Jinping and Russian Federation President Vladimir Putin,on behalf of two countries,China Satellite Navigation System Committee Chairman WANG Li and Russian Federal Space Agency Chief Igor Komarov signed the"China’s Bei Dou System and Russian Glonass System Compatibility and Interoperability Cooperation Joint Statement".It indicates that the navigation cooperation be-
