The Total Coloring Conjecture (TCC) proposes that every simple graph G is (Δ + 2)-totally-colorable, where Δ is the maximum degree of G. For planar graph, TCC is open only in case Δ = 6. In this paper, we prove tha...The Total Coloring Conjecture (TCC) proposes that every simple graph G is (Δ + 2)-totally-colorable, where Δ is the maximum degree of G. For planar graph, TCC is open only in case Δ = 6. In this paper, we prove that TCC holds for planar graph with Δ = 6 and every 7-cycle contains at most two chords.展开更多
Plant diseases pose a significant challenge to global agricultural productivity,necessitating efficient and precise diagnostic systems for early intervention and mitigation.In this study,we propose a novel hybrid fram...Plant diseases pose a significant challenge to global agricultural productivity,necessitating efficient and precise diagnostic systems for early intervention and mitigation.In this study,we propose a novel hybrid framework that integrates EfficientNet-B8,Vision Transformer(ViT),and Knowledge Graph Fusion(KGF)to enhance plant disease classification across 38 distinct disease categories.The proposed framework leverages deep learning and semantic enrichment to improve classification accuracy and interpretability.EfficientNet-B8,a convolutional neural network(CNN)with optimized depth and width scaling,captures fine-grained spatial details in high-resolution plant images,aiding in the detection of subtle disease symptoms.In parallel,ViT,a transformer-based architecture,effectively models long-range dependencies and global structural patterns within the images,ensuring robust disease pattern recognition.Furthermore,KGF incorporates domain-specific metadata,such as crop type,environmental conditions,and disease relationships,to provide contextual intelligence and improve classification accuracy.The proposed model was rigorously evaluated on a large-scale dataset containing diverse plant disease images,achieving outstanding performance with a 99.7%training accuracy and 99.3%testing accuracy.The precision and F1-score were consistently high across all disease classes,demonstrating the framework’s ability to minimize false positives and false negatives.Compared to conventional deep learning approaches,this hybrid method offers a more comprehensive and interpretable solution by integrating self-attention mechanisms and domain knowledge.Beyond its superior classification performance,this model opens avenues for optimizing metadata dependency and reducing computational complexity,making it more feasible for real-world deployment in resource-constrained agricultural settings.The proposed framework represents an advancement in precision agriculture,providing scalable,intelligent disease diagnosis that enhances crop protection and food security.展开更多
It is difficult to characterize graphs which contain no a 2-connected graph as a minor in graph theory.Let V_(8)be a graph constructed from an 8-cycle by connecting the antipodal vertices.There are thirteen 2-connecte...It is difficult to characterize graphs which contain no a 2-connected graph as a minor in graph theory.Let V_(8)be a graph constructed from an 8-cycle by connecting the antipodal vertices.There are thirteen 2-connected spanning subgraphs of V_(8).In particular,one of them is obtained from the Petersen graph by deleting two vertices and it is also a hard problem to characterize Petersen-minor-free graphs.In this paper,we characterize internally 4-connected graphs which contain a 2-connected spanning subgraph of V_(8)as a forbidden minor.展开更多
Lumped element lowpass filter(LPF)for ultra-high frequency(UHF)radio frequency(RF)front-end system is presented based on multilayer liquid crystal polymer(LCP).The lumped element LPF can achieve miniaturization and on...Lumped element lowpass filter(LPF)for ultra-high frequency(UHF)radio frequency(RF)front-end system is presented based on multilayer liquid crystal polymer(LCP).The lumped element LPF can achieve miniaturization and one transmission zero on the stopband by the 8-shaped inductor.The lumped element LPF is fabricated on a 4-layer LCP substrate with a compact size of 9 mm×14 mm×0.193 mm.The measured cut off frequency of the lumped element LPF is 0.5 GHz with insertion loss(IL)less than 0.37 dB.Both measured and simulated results suggest that it is a possible candidate for the application of UHF RF front-end system.展开更多
文摘The Total Coloring Conjecture (TCC) proposes that every simple graph G is (Δ + 2)-totally-colorable, where Δ is the maximum degree of G. For planar graph, TCC is open only in case Δ = 6. In this paper, we prove that TCC holds for planar graph with Δ = 6 and every 7-cycle contains at most two chords.
文摘Plant diseases pose a significant challenge to global agricultural productivity,necessitating efficient and precise diagnostic systems for early intervention and mitigation.In this study,we propose a novel hybrid framework that integrates EfficientNet-B8,Vision Transformer(ViT),and Knowledge Graph Fusion(KGF)to enhance plant disease classification across 38 distinct disease categories.The proposed framework leverages deep learning and semantic enrichment to improve classification accuracy and interpretability.EfficientNet-B8,a convolutional neural network(CNN)with optimized depth and width scaling,captures fine-grained spatial details in high-resolution plant images,aiding in the detection of subtle disease symptoms.In parallel,ViT,a transformer-based architecture,effectively models long-range dependencies and global structural patterns within the images,ensuring robust disease pattern recognition.Furthermore,KGF incorporates domain-specific metadata,such as crop type,environmental conditions,and disease relationships,to provide contextual intelligence and improve classification accuracy.The proposed model was rigorously evaluated on a large-scale dataset containing diverse plant disease images,achieving outstanding performance with a 99.7%training accuracy and 99.3%testing accuracy.The precision and F1-score were consistently high across all disease classes,demonstrating the framework’s ability to minimize false positives and false negatives.Compared to conventional deep learning approaches,this hybrid method offers a more comprehensive and interpretable solution by integrating self-attention mechanisms and domain knowledge.Beyond its superior classification performance,this model opens avenues for optimizing metadata dependency and reducing computational complexity,making it more feasible for real-world deployment in resource-constrained agricultural settings.The proposed framework represents an advancement in precision agriculture,providing scalable,intelligent disease diagnosis that enhances crop protection and food security.
基金Research Project supported by the National Natural Science Foundation of China(No.11961051)Provincial Natural Science Foundation of Shanxi(20210302123097)Shanxi Scholarship Council of China。
文摘It is difficult to characterize graphs which contain no a 2-connected graph as a minor in graph theory.Let V_(8)be a graph constructed from an 8-cycle by connecting the antipodal vertices.There are thirteen 2-connected spanning subgraphs of V_(8).In particular,one of them is obtained from the Petersen graph by deleting two vertices and it is also a hard problem to characterize Petersen-minor-free graphs.In this paper,we characterize internally 4-connected graphs which contain a 2-connected spanning subgraph of V_(8)as a forbidden minor.
基金Supported by the Shaanxi Provincial Innovation Team Project(2020TD-019)the Xi'an Sciences Plan Project(21XJZZ0075)。
文摘Lumped element lowpass filter(LPF)for ultra-high frequency(UHF)radio frequency(RF)front-end system is presented based on multilayer liquid crystal polymer(LCP).The lumped element LPF can achieve miniaturization and one transmission zero on the stopband by the 8-shaped inductor.The lumped element LPF is fabricated on a 4-layer LCP substrate with a compact size of 9 mm×14 mm×0.193 mm.The measured cut off frequency of the lumped element LPF is 0.5 GHz with insertion loss(IL)less than 0.37 dB.Both measured and simulated results suggest that it is a possible candidate for the application of UHF RF front-end system.
