In this paper,we propose a novel secure image communication system that integrates quantum key distribution and hyperchaotic encryption techniques to ensure enhanced security for both key distribution and plaintext en...In this paper,we propose a novel secure image communication system that integrates quantum key distribution and hyperchaotic encryption techniques to ensure enhanced security for both key distribution and plaintext encryption.Specifically,we leverage the B92 Quantum Key Distribution(QKD)protocol to secure the distribution of encryption keys,which are further processed through Galois Field(GF(28))operations for increased security.The encrypted plaintext is secured using a newly developed Hyper 3D Logistic Map(H3LM),a chaotic system that generates complex and unpredictable sequences,thereby ensuring strong confusion and diffusion in the encryption process.This hybrid approach offers a robust defense against quantum and classical cryptographic attacks,combining the advantages of quantum-level key distribution with the unpredictability of hyperchaos-based encryption.The proposed method demonstrates high sensitivity to key changes and resilience to noise,compression,and cropping attacks,ensuring both secure key transmission and robust image encryption.展开更多
With the rapid development of internet technology,security protection of information has become more and more prominent,especially information encryption.Considering the great advantages of chaotic encryption,we propo...With the rapid development of internet technology,security protection of information has become more and more prominent,especially information encryption.Considering the great advantages of chaotic encryption,we propose a 2D-lag complex logistic map with complex parameters(2D-LCLMCP)and corresponding encryption schemes.Firstly,we present the model of the 2D-LCLMCP and analyze its chaotic properties and system stability through fixed points,Lyapunov exponent,bifurcation diagram,phase diagram,etc.Secondly,a block cipher algorithm based on the 2D-LCLMCP is proposed,the plaintext data is preprocessed using a pseudorandom sequence generated by the 2D-LCLMCP.Based on the generalized Feistel cipher structure,a round function F is constructed using dynamic S-box and DNA encoding rules as the core of the block cipher algorithm.The generalized Feistel cipher structure consists of two F functions,four XOR operations,and one permutation operation per round.The symmetric dynamic round keys that change with the plaintext are generated by the 2D-LCLMCP.Finally,experimental simulation and performance analysis tests are conducted.The results show that the block cipher algorithm has low complexit,good diffusion and a large key space.When the block length is 64 bits,only six rounds of encryption are required to provide sufficient security and robustness against cryptographic attacks.展开更多
This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble lear...This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.展开更多
This paper highlights the crucial role of Indonesia’s GNSS receiver network in advancing Equatorial Plasma Bubble(EPB)studies in Southeast and East Asia,as ionospheric irregularities within EPB can disrupt GNSS signa...This paper highlights the crucial role of Indonesia’s GNSS receiver network in advancing Equatorial Plasma Bubble(EPB)studies in Southeast and East Asia,as ionospheric irregularities within EPB can disrupt GNSS signals and degrade positioning accuracy.Managed by the Indonesian Geospatial Information Agency(BIG),the Indonesia Continuously Operating Reference Station(Ina-CORS)network comprises over 300 GNSS receivers spanning equatorial to southern low-latitude regions.Ina-CORS is uniquely situated to monitor EPB generation,zonal drift,and dissipation across Southeast Asia.We provide a practical tool for EPB research,by sharing two-dimensional rate of Total Electron Content(TEC)change index(ROTI)derived from this network.We generate ROTI maps with a 10-minute resolution,and samples from May 2024 are publicly available for further scientific research.Two preliminary findings from the ROTI maps of Ina-CORS are noteworthy.First,the Ina-CORS ROTI maps reveal that the irregularities within a broader EPB structure persist longer,increasing the potential for these irregularities to migrate farther eastward.Second,we demonstrate that combined ROTI maps from Ina-CORS and GNSS receivers in East Asia and Australia can be used to monitor the development of ionospheric irregularities in Southeast and East Asia.We have demonstrated the combined ROTI maps to capture the development of ionospheric irregularities in the Southeast/East Asian sector during the G5 Geomagnetic Storm on May 11,2024.We observed simultaneous ionospheric irregularities in Japan and Australia,respectively propagating northwestward and southwestward,before midnight,whereas Southeast Asia’s equatorial and low-latitude regions exhibited irregularities post-midnight.By sharing ROTI maps from Indonesia and integrating them with regional GNSS networks,researchers can conduct comprehensive EPB studies,enhancing the understanding of EPB behavior across Southeast and East Asia and contributing significantly to ionospheric research.展开更多
目的:比较决策树和Logistic回归模型对体外受精-胚胎移植(in vitro fertilization and embryo transfer,IVF-ET)患者妊娠结局的预测价值。方法:纳入2021年1月至2022年10月在长治医学院附属和平医院接受IVF-ET的患者350例为研究对象,根...目的:比较决策树和Logistic回归模型对体外受精-胚胎移植(in vitro fertilization and embryo transfer,IVF-ET)患者妊娠结局的预测价值。方法:纳入2021年1月至2022年10月在长治医学院附属和平医院接受IVF-ET的患者350例为研究对象,根据妊娠结局分为妊娠成功组(215例)和妊娠失败组(135例)。收集患者临床资料,建立IVF-ET患者妊娠结局Logistic回归和决策树预测模型,并在是否基于Logistic回归结果条件下建立决策树分析模型(决策树1和决策树2),采用受试者工作特征(receiver operating characteristic,ROC)曲线对模型预测效果进行评价。结果:350例患者中,妊娠成功患者占61.43%,妊娠失败者占38.57%。妊娠失败组年龄≥35岁、不孕年限≥5年、周期次数≥1次、有心理精神障碍的患者比例及HCG日血清孕酮水平均高于妊娠成功组,获卵数≥10枚、受精率≥75%的患者比例及HCG日子宫内膜厚度、优质胚胎数小于妊娠成功组(P<0.05)。多因素Logistic回归分析结果显示,年龄、HCG日血清孕酮水平、优质胚胎数及心理精神障碍均是IVF-ET患者妊娠结局的影响因素(P<0.05)。决策树模型显示,年龄、HCG日血清孕酮水平、优质胚胎数为IVF-ET患者妊娠结局的影响因素。Logistic回归模型曲线下面积(area under curve,AUC)为0.832,预测敏感度、特异度和准确度分别为87.3%、71.4%、83.5%;决策树1的AUC为0.859,预测敏感度、特异度和准确度分别为85.1%、76.8%、85.6%;决策树2的AUC为0.820,预测敏感度、特异度和准确度分别为83.7%、73.2%、82.4%。决策树1的AUC大于决策树2(P<0.05),但与Logistic回归模型的AUC比较差异无统计学意义(P>0.05)。结论:Logistic回归模型和决策树模型对于IVF-ET患者妊娠结局均有一定的预测价值。展开更多
文摘In this paper,we propose a novel secure image communication system that integrates quantum key distribution and hyperchaotic encryption techniques to ensure enhanced security for both key distribution and plaintext encryption.Specifically,we leverage the B92 Quantum Key Distribution(QKD)protocol to secure the distribution of encryption keys,which are further processed through Galois Field(GF(28))operations for increased security.The encrypted plaintext is secured using a newly developed Hyper 3D Logistic Map(H3LM),a chaotic system that generates complex and unpredictable sequences,thereby ensuring strong confusion and diffusion in the encryption process.This hybrid approach offers a robust defense against quantum and classical cryptographic attacks,combining the advantages of quantum-level key distribution with the unpredictability of hyperchaos-based encryption.The proposed method demonstrates high sensitivity to key changes and resilience to noise,compression,and cropping attacks,ensuring both secure key transmission and robust image encryption.
基金Project supported by the Shandong Province Natural Science Foundation(Grant Nos.ZR2023MF089,R2023QF036,and ZR2021MF073)the Industry-University-Research Collaborative Innovation Fund Project of Qilu University of Technology(Shandong Academy of Sciences)(Grant Nos.2021CXY-13 and 2021CXY-14)+2 种基金the Major Scientific and Technological Innovation Projects of Shandong Province(Grant No.2020CXGC010901)the Talent Research Project of Qilu University of Technology(Shandong Academy of Sciences)(Grant No.2023RCKY054)the Basic Research Projects of Science,Education and Industry Integration Pilot Project of Qilu University of Technology(Shandong Academy of Sciences)(Grant No.2023PX081)。
文摘With the rapid development of internet technology,security protection of information has become more and more prominent,especially information encryption.Considering the great advantages of chaotic encryption,we propose a 2D-lag complex logistic map with complex parameters(2D-LCLMCP)and corresponding encryption schemes.Firstly,we present the model of the 2D-LCLMCP and analyze its chaotic properties and system stability through fixed points,Lyapunov exponent,bifurcation diagram,phase diagram,etc.Secondly,a block cipher algorithm based on the 2D-LCLMCP is proposed,the plaintext data is preprocessed using a pseudorandom sequence generated by the 2D-LCLMCP.Based on the generalized Feistel cipher structure,a round function F is constructed using dynamic S-box and DNA encoding rules as the core of the block cipher algorithm.The generalized Feistel cipher structure consists of two F functions,four XOR operations,and one permutation operation per round.The symmetric dynamic round keys that change with the plaintext are generated by the 2D-LCLMCP.Finally,experimental simulation and performance analysis tests are conducted.The results show that the block cipher algorithm has low complexit,good diffusion and a large key space.When the block length is 64 bits,only six rounds of encryption are required to provide sufficient security and robustness against cryptographic attacks.
基金the University of Transport Technology under the project entitled“Application of Machine Learning Algorithms in Landslide Susceptibility Mapping in Mountainous Areas”with grant number DTTD2022-16.
文摘This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.
基金support received from Telkom University under the“Skema Penelitian Terapan Periode I Tahun Anggaran 2024”and the Memorandum of Understanding for Research Collaboration on Regional Ionospheric Observation(No:092/SAM3/TEDEK/2021)along with colleagues UAA and WPT.INM sincerely thanks the National Institute of Information and Communications Technology(NICT)International Exchange Program 2024−2025(No.2024−007)for their invaluable support for a one-year visiting research at Hokkaido University.
文摘This paper highlights the crucial role of Indonesia’s GNSS receiver network in advancing Equatorial Plasma Bubble(EPB)studies in Southeast and East Asia,as ionospheric irregularities within EPB can disrupt GNSS signals and degrade positioning accuracy.Managed by the Indonesian Geospatial Information Agency(BIG),the Indonesia Continuously Operating Reference Station(Ina-CORS)network comprises over 300 GNSS receivers spanning equatorial to southern low-latitude regions.Ina-CORS is uniquely situated to monitor EPB generation,zonal drift,and dissipation across Southeast Asia.We provide a practical tool for EPB research,by sharing two-dimensional rate of Total Electron Content(TEC)change index(ROTI)derived from this network.We generate ROTI maps with a 10-minute resolution,and samples from May 2024 are publicly available for further scientific research.Two preliminary findings from the ROTI maps of Ina-CORS are noteworthy.First,the Ina-CORS ROTI maps reveal that the irregularities within a broader EPB structure persist longer,increasing the potential for these irregularities to migrate farther eastward.Second,we demonstrate that combined ROTI maps from Ina-CORS and GNSS receivers in East Asia and Australia can be used to monitor the development of ionospheric irregularities in Southeast and East Asia.We have demonstrated the combined ROTI maps to capture the development of ionospheric irregularities in the Southeast/East Asian sector during the G5 Geomagnetic Storm on May 11,2024.We observed simultaneous ionospheric irregularities in Japan and Australia,respectively propagating northwestward and southwestward,before midnight,whereas Southeast Asia’s equatorial and low-latitude regions exhibited irregularities post-midnight.By sharing ROTI maps from Indonesia and integrating them with regional GNSS networks,researchers can conduct comprehensive EPB studies,enhancing the understanding of EPB behavior across Southeast and East Asia and contributing significantly to ionospheric research.
文摘背景:腰椎小关节炎是引起下腰痛的一个主要原因,目前主要依靠MRI进行初步定性诊断,但仍有一定漏诊、误诊的概率发生,因此MR T2^(*)mapping成像技术有望成为定量检查腰椎小关节炎软骨损伤的重要检测手段。目的:探讨MR T2^(*)mapping成像技术在定量分析腰椎小关节炎软骨损伤退变中的应用价值。方法:收集南京医科大学第四附属医院2020年4月至2022年3月门诊或住院合并下腰痛共110例患者,设为病例组;同时招募无症状志愿者80例,设为对照组。对所有纳入对象L1-S1的小关节行3.0 T MR扫描,获取T2^(*)mapping横断位图像和T2WI图像,分别对所有小关节软骨进行Weishaupt分级及T2^(*)值测量,收集数据并行统计学分析。不同小关节Weishaupt分级之间小关节软骨T2^(*)值比较采用单因素方差分析。结果与结论:①经统计分析发现,病例组腰椎小关节软骨T2^(*)值(17.6±1.5)ms明显较对照组(21.4±1.3)ms降低,差异有显著性意义(P<0.05);②在病例组中,随着腰椎小关节Weishaupt分级增加,小关节软骨T2^(*)值也呈逐渐下降趋势,且这种差异有显著性意义(P<0.05);③提示T2^(*)mapping能够较好地显示腰椎小关节软骨损伤的早期病理变化,腰椎小关节软骨的T2^(*)值能够定量评估腰椎小关节的软骨损伤程度;T2^(*)mapping成像技术能为影像学诊断腰椎小关节炎软骨早期损伤提供很好的理论依据,具有重要的临床应用价值。
文摘目的:比较决策树和Logistic回归模型对体外受精-胚胎移植(in vitro fertilization and embryo transfer,IVF-ET)患者妊娠结局的预测价值。方法:纳入2021年1月至2022年10月在长治医学院附属和平医院接受IVF-ET的患者350例为研究对象,根据妊娠结局分为妊娠成功组(215例)和妊娠失败组(135例)。收集患者临床资料,建立IVF-ET患者妊娠结局Logistic回归和决策树预测模型,并在是否基于Logistic回归结果条件下建立决策树分析模型(决策树1和决策树2),采用受试者工作特征(receiver operating characteristic,ROC)曲线对模型预测效果进行评价。结果:350例患者中,妊娠成功患者占61.43%,妊娠失败者占38.57%。妊娠失败组年龄≥35岁、不孕年限≥5年、周期次数≥1次、有心理精神障碍的患者比例及HCG日血清孕酮水平均高于妊娠成功组,获卵数≥10枚、受精率≥75%的患者比例及HCG日子宫内膜厚度、优质胚胎数小于妊娠成功组(P<0.05)。多因素Logistic回归分析结果显示,年龄、HCG日血清孕酮水平、优质胚胎数及心理精神障碍均是IVF-ET患者妊娠结局的影响因素(P<0.05)。决策树模型显示,年龄、HCG日血清孕酮水平、优质胚胎数为IVF-ET患者妊娠结局的影响因素。Logistic回归模型曲线下面积(area under curve,AUC)为0.832,预测敏感度、特异度和准确度分别为87.3%、71.4%、83.5%;决策树1的AUC为0.859,预测敏感度、特异度和准确度分别为85.1%、76.8%、85.6%;决策树2的AUC为0.820,预测敏感度、特异度和准确度分别为83.7%、73.2%、82.4%。决策树1的AUC大于决策树2(P<0.05),但与Logistic回归模型的AUC比较差异无统计学意义(P>0.05)。结论:Logistic回归模型和决策树模型对于IVF-ET患者妊娠结局均有一定的预测价值。
