In this paper,we propose a random access scheme termed sign-compute diversity slotted ALOHA(SCDSA).The SCDSA scheme combines diversity transmission with compute-and-forward.Without considering the capture effect and m...In this paper,we propose a random access scheme termed sign-compute diversity slotted ALOHA(SCDSA).The SCDSA scheme combines diversity transmission with compute-and-forward.Without considering the capture effect and multiple user detection techniques,our scheme can reach a high throughput of 0.98 without feedback under finite frame size settings,where the upper bound on performance is 1.Moreover,a lower bound on throughput performance is derived,which is tight in some parameter settings and can be used to approximate theoretical performance.Simulation results validate our analysis and confirm the advantages of our proposed scheme.展开更多
Container transportation is pivotal in global trade due to its efficiency,safety,and cost-effectiveness.However,structural defects—particularly in grapple slots—can result in cargo damage,financial loss,and elevated...Container transportation is pivotal in global trade due to its efficiency,safety,and cost-effectiveness.However,structural defects—particularly in grapple slots—can result in cargo damage,financial loss,and elevated safety risks,including container drops during lifting operations.Timely and accurate inspection before and after transit is therefore essential.Traditional inspection methods rely heavily on manual observation of internal and external surfaces,which are time-consuming,resource-intensive,and prone to subjective errors.Container roofs pose additional challenges due to limited visibility,while grapple slots are especially vulnerable to wear from frequent use.This study proposes a two-stage automated detection framework targeting defects in container roof grapple slots.In the first stage,YOLOv7 is employed to localize grapple slot regions with high precision.In the second stage,ResNet50 classifies the extracted slots as either intact or defective.The results from both stages are integrated into a human-machine interface for real-time visualization and user verification.Experimental evaluations demonstrate that YOLOv7 achieves a 99%detection rate at 100 frames per second(FPS),while ResNet50 attains 87%classification accuracy at 34 FPS.Compared to some state of the arts,the proposed system offers significant speed,reliability,and usability improvements,enabling efficient defect identification and visual reconfirmation via the interface.展开更多
As the proportion of composite materials used in aircraft continues to increase, the electromagnetic Shielding Effectiveness (SE) of these materials becomes a critical factor in the electromagnetic safety design of ai...As the proportion of composite materials used in aircraft continues to increase, the electromagnetic Shielding Effectiveness (SE) of these materials becomes a critical factor in the electromagnetic safety design of aircraft structures. The assessment of electromagnetic SE for Slotted Composite Structures(SCSs) is particularly challenging due to their complex geometries and there remains a lack of suitable models for accurately predicting the SE performance of these intricate configurations. To address this issue, this paper introduces SCS-Net, a Deep Neural Network (DNN) method designed to accurately predict the SE of SCS. This method considers the impacts of various structural parameters, material properties and incident wave parameters on the SE of SCSs. In order to better model the SCS, an improved Nicolson-Ross-Weir (NRW) method is introduced in this paper to provide an equivalent flat structure for the SCS and to calculate the electromagnetic parameters of the equivalent structure. Additionally, the prediction of SE via DNNs is limited by insufficient test data, which hinders support for large-sample training. To address the issue of limited measured data, this paper develops a Measurement-Computation Fusion (MCF) dataset construction method. The predictions based on the simulation results show that the proposed method maintains an error of less than 0.07 dB within the 8–10 GHz frequency range. Furthermore, a new loss function based on the weighted L1-norm is established to improve the prediction accuracy for these parameters. Compared with traditional loss functions, the new loss function reduces the maximum prediction error for equivalent electromagnetic parameters by 47%. This method significantly improves the prediction accuracy of SCS-Net for measured data, with a maximum improvement of 23.88%. These findings demonstrate that the proposed method enables precise SE prediction and design for composite structures while reducing the number of test samples needed.展开更多
Mitigating tag collisions is paramount for enhancing throughput in Radio Frequency Identification(RFID)systems.However,traditional algorithms encounter challenges like slot wastage and inefficient frame length adjustm...Mitigating tag collisions is paramount for enhancing throughput in Radio Frequency Identification(RFID)systems.However,traditional algorithms encounter challenges like slot wastage and inefficient frame length adjustments.To tackle these challenges,the Slot Prediction Q(SPQ)algorithm was introduced,integrating the VogtII prediction algorithm and slot grouping to improve the initial Q value by predicting the first frame.This method quickly estimates the number of tags based on slot utilization,accelerating Q value adjustments when slot utilization is low.Furthermore,a Markov decision chain is used to optimize the relationship between the number of slot groupings(x)and the Q value.The Whale Optimization Algorithm(WOA)is applied to fine-tune the learning rate(C)and Q value in the traditional Q algorithm.Simulation results demonstrate that SPQ significantly reduces the total slots used during the reading process and improves RFID system throughput compared to traditional Q,FastQ,Subset Enhanced Performance-Q(SUBEP-Q),and Threshold Grouping Dynamic Q(TGDQ)algorithms.Specifically,compared to the traditional Q algorithm,SPQ increases the average Identification Speed by 7.20%,System Efficiency by 11.08%,and Time Efficiency by 5.69%.展开更多
Intent detection and slot filling are two important components of natural language understanding.Because their relevance,joint training is often performed to improve performance.Existing studies mostly use a joint mod...Intent detection and slot filling are two important components of natural language understanding.Because their relevance,joint training is often performed to improve performance.Existing studies mostly use a joint model of multi-intent detection and slot-filling with unidirectional interaction,which improves the overall performance of the model by fusing the intent information in the slot-filling part.On this basis,in order to further improve the overall performance of the model by exploiting the correlation between the two,this paper proposes a joint multi-intent detection and slot-filling model based on a bidirectional interaction structure,which fuses the intent encoding information in the encoding part of slot filling and fuses the slot decoding information in the decoding part of intent detection.Experimental results on two public multi-intent joint training datasets,MixATIS and MixSNIPS,show that the bidirectional interaction structure proposed in this paper can effectively improve the performance of the joint model.In addition,in order to verify the generalization of the bidirectional interaction structure between intent and slot,a joint model for single-intent scenarios is proposed on the basis of the model in this paper.This model also achieves excellent performance on two public single-intent joint training datasets,CAIS and SNIPS.展开更多
To enhance the quality factor and sensitivity of refractive index sensors,a feedback waveguide slot grating micro-ring resonator was proposed.An air-hole grating structure was introduced based on the slot micro-ring,u...To enhance the quality factor and sensitivity of refractive index sensors,a feedback waveguide slot grating micro-ring resonator was proposed.An air-hole grating structure was introduced based on the slot micro-ring,utilizing the reflection of the grating to achieve the electromagnetic-like induced transparency effect at different wavelengths.The high slope characteristics of the EIT-like effect enabled a higher quality factor and sensitivity.The transmission principle of the structure was analyzed using the transmission matrix method,and the transmission spectrum and mode field distribution were simulated using the finite-difference time-domain(FDTD)method,and the device structure parameters were adjusted for optimization.Simulation results show that the proposed structure achieves an EIT-like effect with a quality factor of 59267.5.In the analysis of refractive index sensing characteristics,the structure exhibits a sensitivity of 408.57 nm/RIU and a detection limit of 6.23×10^(-5) RIU.Therefore,the proposed structure achieved both a high quality factor and refractive index sensitivity,demonstrating excellent sensing performance for applications in environmental monitoring,biomedical fields,and other areas with broad market potential.展开更多
Airports around the world commonly face challenges in managing airport slot allocation.Effective management of limited slot resources by civil aviation authority often requires redistributing requested slots among air...Airports around the world commonly face challenges in managing airport slot allocation.Effective management of limited slot resources by civil aviation authority often requires redistributing requested slots among airlines.The allocation process must operate within the prescribed capacity limits of the airport while adhering to established priorities and regulations.Additionally,ensuring market fairness is a key objective,as the value of airport slots plays a significant role in the adjustment process.This transforms the traditional time-shift-based problem into a complex multi-objective optimization problem.Addressing such complications is of significant importance to airlines,airports,and passengers alike.Due to the complexity of fairness metrics,traditional integer programming models encounter difficulties in finding effective solutions.This study proposes a neighborhood search strategy to tackle the single airport slot allocation,making it adaptable to both static and rolling capacity scenarios.Two Genetic Algorithms(GAs)are introduced,corresponding to time adjustment and sequence adjustment strategies,respectively.The GA based on the time adjustment strategy demonstrates high robustness,while the sequence adjustment strategy builds upon this GA to develop a simple heuristic algorithm that offers rapid convergence.Case studies conducted at seven airports in China confirm that all three algorithms yield high-quality adjustment solutions suitable for the majority of applications.Further,Pareto analysis reveals that these algorithms effectively balance the adjustment shifts and fairness metrics,demonstrating high practical value and broad applicability.展开更多
In this paper,a terahertz slotted waveguide array antenna is designed based on photonic crystal,which can realize efficient radiation of terahertz waves.The electromagnetic wave is fed from the rectangular waveguide a...In this paper,a terahertz slotted waveguide array antenna is designed based on photonic crystal,which can realize efficient radiation of terahertz waves.The electromagnetic wave is fed from the rectangular waveguide at the bottom of the antenna,coupled to photonic crystal waveguide through photonic crystal cavity,and radiated outward through slots at the top layer of antenna.The simulation results show that the antenna achieves a peak gain of 13.45 dBi at 360 GHz,a half-power beam width of 10.9°,and a side lobe level of−13.9 dB.The antenna based on photonic crystal has the advantages of low profile,low loss,and high radiation efficiency,which can be applied to terahertz wireless communication systems.展开更多
文摘In this paper,we propose a random access scheme termed sign-compute diversity slotted ALOHA(SCDSA).The SCDSA scheme combines diversity transmission with compute-and-forward.Without considering the capture effect and multiple user detection techniques,our scheme can reach a high throughput of 0.98 without feedback under finite frame size settings,where the upper bound on performance is 1.Moreover,a lower bound on throughput performance is derived,which is tight in some parameter settings and can be used to approximate theoretical performance.Simulation results validate our analysis and confirm the advantages of our proposed scheme.
文摘Container transportation is pivotal in global trade due to its efficiency,safety,and cost-effectiveness.However,structural defects—particularly in grapple slots—can result in cargo damage,financial loss,and elevated safety risks,including container drops during lifting operations.Timely and accurate inspection before and after transit is therefore essential.Traditional inspection methods rely heavily on manual observation of internal and external surfaces,which are time-consuming,resource-intensive,and prone to subjective errors.Container roofs pose additional challenges due to limited visibility,while grapple slots are especially vulnerable to wear from frequent use.This study proposes a two-stage automated detection framework targeting defects in container roof grapple slots.In the first stage,YOLOv7 is employed to localize grapple slot regions with high precision.In the second stage,ResNet50 classifies the extracted slots as either intact or defective.The results from both stages are integrated into a human-machine interface for real-time visualization and user verification.Experimental evaluations demonstrate that YOLOv7 achieves a 99%detection rate at 100 frames per second(FPS),while ResNet50 attains 87%classification accuracy at 34 FPS.Compared to some state of the arts,the proposed system offers significant speed,reliability,and usability improvements,enabling efficient defect identification and visual reconfirmation via the interface.
基金supported by the National Natural Science Foundation of China(Nos.62101020 and 62141405)the Special Scientific Research Project of Civil Aircraft,China(No.MJZ5-2N22).
文摘As the proportion of composite materials used in aircraft continues to increase, the electromagnetic Shielding Effectiveness (SE) of these materials becomes a critical factor in the electromagnetic safety design of aircraft structures. The assessment of electromagnetic SE for Slotted Composite Structures(SCSs) is particularly challenging due to their complex geometries and there remains a lack of suitable models for accurately predicting the SE performance of these intricate configurations. To address this issue, this paper introduces SCS-Net, a Deep Neural Network (DNN) method designed to accurately predict the SE of SCS. This method considers the impacts of various structural parameters, material properties and incident wave parameters on the SE of SCSs. In order to better model the SCS, an improved Nicolson-Ross-Weir (NRW) method is introduced in this paper to provide an equivalent flat structure for the SCS and to calculate the electromagnetic parameters of the equivalent structure. Additionally, the prediction of SE via DNNs is limited by insufficient test data, which hinders support for large-sample training. To address the issue of limited measured data, this paper develops a Measurement-Computation Fusion (MCF) dataset construction method. The predictions based on the simulation results show that the proposed method maintains an error of less than 0.07 dB within the 8–10 GHz frequency range. Furthermore, a new loss function based on the weighted L1-norm is established to improve the prediction accuracy for these parameters. Compared with traditional loss functions, the new loss function reduces the maximum prediction error for equivalent electromagnetic parameters by 47%. This method significantly improves the prediction accuracy of SCS-Net for measured data, with a maximum improvement of 23.88%. These findings demonstrate that the proposed method enables precise SE prediction and design for composite structures while reducing the number of test samples needed.
基金supported by National Key Research and Development Program of China(2022YFB4703102)National Natural Science Foundation of China(62273105).
文摘Mitigating tag collisions is paramount for enhancing throughput in Radio Frequency Identification(RFID)systems.However,traditional algorithms encounter challenges like slot wastage and inefficient frame length adjustments.To tackle these challenges,the Slot Prediction Q(SPQ)algorithm was introduced,integrating the VogtII prediction algorithm and slot grouping to improve the initial Q value by predicting the first frame.This method quickly estimates the number of tags based on slot utilization,accelerating Q value adjustments when slot utilization is low.Furthermore,a Markov decision chain is used to optimize the relationship between the number of slot groupings(x)and the Q value.The Whale Optimization Algorithm(WOA)is applied to fine-tune the learning rate(C)and Q value in the traditional Q algorithm.Simulation results demonstrate that SPQ significantly reduces the total slots used during the reading process and improves RFID system throughput compared to traditional Q,FastQ,Subset Enhanced Performance-Q(SUBEP-Q),and Threshold Grouping Dynamic Q(TGDQ)algorithms.Specifically,compared to the traditional Q algorithm,SPQ increases the average Identification Speed by 7.20%,System Efficiency by 11.08%,and Time Efficiency by 5.69%.
基金Supported by the National Nature Science Foundation of China(62462037,62462036)Project for Academic and Technical Leader in Major Disciplines in Jiangxi Province(20232BCJ22013)+1 种基金Jiangxi Provincial Natural Science Foundation(20242BAB26017,20232BAB202010)Jiangxi Province Graduate Innovation Fund Project(YC2023-S320)。
文摘Intent detection and slot filling are two important components of natural language understanding.Because their relevance,joint training is often performed to improve performance.Existing studies mostly use a joint model of multi-intent detection and slot-filling with unidirectional interaction,which improves the overall performance of the model by fusing the intent information in the slot-filling part.On this basis,in order to further improve the overall performance of the model by exploiting the correlation between the two,this paper proposes a joint multi-intent detection and slot-filling model based on a bidirectional interaction structure,which fuses the intent encoding information in the encoding part of slot filling and fuses the slot decoding information in the decoding part of intent detection.Experimental results on two public multi-intent joint training datasets,MixATIS and MixSNIPS,show that the bidirectional interaction structure proposed in this paper can effectively improve the performance of the joint model.In addition,in order to verify the generalization of the bidirectional interaction structure between intent and slot,a joint model for single-intent scenarios is proposed on the basis of the model in this paper.This model also achieves excellent performance on two public single-intent joint training datasets,CAIS and SNIPS.
基金supported by Natural Science Foundation of Gansu Province(NO.21JR7RA289)。
文摘To enhance the quality factor and sensitivity of refractive index sensors,a feedback waveguide slot grating micro-ring resonator was proposed.An air-hole grating structure was introduced based on the slot micro-ring,utilizing the reflection of the grating to achieve the electromagnetic-like induced transparency effect at different wavelengths.The high slope characteristics of the EIT-like effect enabled a higher quality factor and sensitivity.The transmission principle of the structure was analyzed using the transmission matrix method,and the transmission spectrum and mode field distribution were simulated using the finite-difference time-domain(FDTD)method,and the device structure parameters were adjusted for optimization.Simulation results show that the proposed structure achieves an EIT-like effect with a quality factor of 59267.5.In the analysis of refractive index sensing characteristics,the structure exhibits a sensitivity of 408.57 nm/RIU and a detection limit of 6.23×10^(-5) RIU.Therefore,the proposed structure achieved both a high quality factor and refractive index sensitivity,demonstrating excellent sensing performance for applications in environmental monitoring,biomedical fields,and other areas with broad market potential.
基金supported in part by the National Natural Science Foundation of China(Nos.62167003,52302421)in part by the Diversified Investment Fund of Tianjin,China(No.23JCQNJC00210)。
文摘Airports around the world commonly face challenges in managing airport slot allocation.Effective management of limited slot resources by civil aviation authority often requires redistributing requested slots among airlines.The allocation process must operate within the prescribed capacity limits of the airport while adhering to established priorities and regulations.Additionally,ensuring market fairness is a key objective,as the value of airport slots plays a significant role in the adjustment process.This transforms the traditional time-shift-based problem into a complex multi-objective optimization problem.Addressing such complications is of significant importance to airlines,airports,and passengers alike.Due to the complexity of fairness metrics,traditional integer programming models encounter difficulties in finding effective solutions.This study proposes a neighborhood search strategy to tackle the single airport slot allocation,making it adaptable to both static and rolling capacity scenarios.Two Genetic Algorithms(GAs)are introduced,corresponding to time adjustment and sequence adjustment strategies,respectively.The GA based on the time adjustment strategy demonstrates high robustness,while the sequence adjustment strategy builds upon this GA to develop a simple heuristic algorithm that offers rapid convergence.Case studies conducted at seven airports in China confirm that all three algorithms yield high-quality adjustment solutions suitable for the majority of applications.Further,Pareto analysis reveals that these algorithms effectively balance the adjustment shifts and fairness metrics,demonstrating high practical value and broad applicability.
基金supported by the National Natural Science Foundation of China(No.62375031)the Basic Research Project of Chongqing Science and Technology Commission(No.CSTC-2021jcyj-bsh0194)the Science and Technology Research Program of Chongqing Municipal Education Commission(No.KJQN202200602)。
文摘In this paper,a terahertz slotted waveguide array antenna is designed based on photonic crystal,which can realize efficient radiation of terahertz waves.The electromagnetic wave is fed from the rectangular waveguide at the bottom of the antenna,coupled to photonic crystal waveguide through photonic crystal cavity,and radiated outward through slots at the top layer of antenna.The simulation results show that the antenna achieves a peak gain of 13.45 dBi at 360 GHz,a half-power beam width of 10.9°,and a side lobe level of−13.9 dB.The antenna based on photonic crystal has the advantages of low profile,low loss,and high radiation efficiency,which can be applied to terahertz wireless communication systems.
