Constructing multi-dimensional hydrogen bond(H-bond)regulated single-molecule systems with multiemission remains a challenge.Herein,we report the design of a new excited-state intramolecular proton transfer(ESIPT)feat...Constructing multi-dimensional hydrogen bond(H-bond)regulated single-molecule systems with multiemission remains a challenge.Herein,we report the design of a new excited-state intramolecular proton transfer(ESIPT)featured chromophore(HBT-DPI)that shows flexible emission tunability via the multidimensional regulation of intra-and intermolecular H-bonds.The feature of switchable intramolecular Hbonds is induced via incorporating several hydrogen bond acceptors and donors into one single HBT-DPI molecule,allowing the“turn on/off”of ESIPT process by forming isomers with distinct intramolecular Hbonds configurations.In response to different external H-bonding environments,the obtained four types of crystal/cocrystals vary in the contents of isomers and the molecular packing modes,which are mainly guided by the intermolecular H-bonds,exhibiting non-emissive features or emissions ranging from green to orange.Utilizing the feature of intermolecular H-bond guided molecular packing,we demonstrate the utility of this fluorescent material for visualizing hydrophobic/hydrophilic areas on large-scale heterogeneous surfaces of modified poly(1,1-difluoroethylene)(PVDF)membranes and quantitatively estimating the surface hydrophobicity,providing a new approach for hydrophobicity/hydrophilicity monitoring and measurement.Overall,this study represents a new design strategy for constructing multi-dimensional hydrogen bond regulated ESIPT-based fluorescent materials that enable multiple emissions and unique applications.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
Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environ...Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.展开更多
Ensuring information security in the quantum era is a growing challenge due to advancements in cryptographic attacks and the emergence of quantum computing.To address these concerns,this paper presents the mathematica...Ensuring information security in the quantum era is a growing challenge due to advancements in cryptographic attacks and the emergence of quantum computing.To address these concerns,this paper presents the mathematical and computer modeling of a novel two-dimensional(2D)chaotic system for secure key generation in quantum image encryption(QIE).The proposed map employs trigonometric perturbations in conjunction with rational-saturation functions and hence,named as Trigonometric-Rational-Saturation(TRS)map.Through rigorous mathematical analysis and computational simulations,the map is extensively evaluated for bifurcation behaviour,chaotic trajectories,and Lyapunov exponents.The security evaluation validates the map’s non-linearity,unpredictability,and sensitive dependence on initial conditions.In addition,the proposed TRS map has further been tested by integrating it in a QIE scheme.The QIE scheme first quantum-encodes the classic image using the Novel Enhanced Quantum Representation(NEQR)technique,the TRS map is used for the generation of secure diffusion key,which is XOR-ed with the quantum-ready image to obtain the encrypted images.The security evaluation of the QIE scheme demonstrates superior security of the encrypted images in terms of statistical security attacks and also against Differential attacks.The encrypted images exhibit zero correlation and maximum entropy with demonstrating strong resilience due to 99.62%and 33.47%results for Number of Pixels Change Rate(NPCR)and Unified Average Changing Intensity(UACI).The results validate the effectiveness of TRS-based quantum encryption scheme in securing digital images against emerging quantum threats,making it suitable for secure image encryption in IoT and edge-based applications.展开更多
Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,th...Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,the existing generative image steganography methods generally have good steganography performance,but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information extraction.Therefore,this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping rule.Firstly,the reference image is disentangled by a content and an attribute encoder to obtain content features and attribute features,respectively.Then,a mean mapping rule is introduced to map the binary secret information into a noise vector,conforming to the distribution of attribute features.This noise vector is input into the generator to produce the attribute transformed stego image with the content feature of the reference image.Additionally,we design an adversarial loss,a reconstruction loss,and an image diversity loss to train the proposed model.Experimental results demonstrate that the stego images generated by the proposed method are of high quality,with an average extraction accuracy of 99.4%for the hidden information.Furthermore,since the stego image has a uniform distribution similar to the attribute-transformed image without secret information,it effectively resists both subjective and objective steganalysis.展开更多
Information on Land Use and Land Cover Map(LULCM)is essential for environment and socioeconomic applications.Such maps are generally derived from Multispectral Remote Sensing Images(MRSI)via classification.The classif...Information on Land Use and Land Cover Map(LULCM)is essential for environment and socioeconomic applications.Such maps are generally derived from Multispectral Remote Sensing Images(MRSI)via classification.The classification process can be described as information flow from images to maps through a trained classifier.Characterizing the information flow is essential for understanding the classification mechanism,providing solutions that address such theoretical issues as“what is the maximum number of classes that can be classified from a given MRSI?”and“how much information gain can be obtained?”Consequently,two interesting questions naturally arise,i.e.(i)How can we characterize the information flow?and(ii)What is the mathematical form of the information flow?To answer these two questions,this study first hypothesizes that thermodynamic entropy is the appropriate measure of information for both MRSI and LULCM.This hypothesis is then supported by kinetic-theory-based experiments.Thereafter,upon such an entropy,a generalized Jarzynski equation is formulated to mathematically model the information flow,which contains such parameters as thermodynamic entropy of MRSI,thermodynamic entropy of LULCM,weighted F1-score(classification accuracy),and total number of classes.This generalized Jarzynski equation has been successfully validated by hypothesis-driven experiments where 694 Sentinel-2 images are classified into 10 classes by four classical classifiers.This study provides a way for linking thermodynamic laws and concepts to the characterization and understanding of information flow in land cover classification,opening a new door for constructing domain knowledge.展开更多
This work was to generate landslide susceptibility maps for the Three Gorges Reservoir(TGR) area, China by using different machine learning models. Three advanced machine learning methods, namely, gradient boosting de...This work was to generate landslide susceptibility maps for the Three Gorges Reservoir(TGR) area, China by using different machine learning models. Three advanced machine learning methods, namely, gradient boosting decision tree(GBDT), random forest(RF) and information value(InV) models, were used, and the performances were assessed and compared. In total, 202 landslides were mapped by using a series of field surveys, aerial photographs, and reviews of historical and bibliographical data. Nine causative factors were then considered in landslide susceptibility map generation by using the GBDT, RF and InV models. All of the maps of the causative factors were resampled to a resolution of 28.5 m. Of the 486289 pixels in the area,28526 pixels were landslide pixels, and 457763 pixels were non-landslide pixels. Finally, landslide susceptibility maps were generated by using the three machine learning models, and their performances were assessed through receiver operating characteristic(ROC) curves, the sensitivity, specificity,overall accuracy(OA), and kappa coefficient(KAPPA). The results showed that the GBDT, RF and In V models in overall produced reasonable accurate landslide susceptibility maps. Among these three methods, the GBDT method outperforms the other two machine learning methods, which can provide strong technical support for producing landslide susceptibility maps in TGR.展开更多
Intelligence and perception are two operative technologies in 6G scenarios.The intelligent wireless network and information perception require a deep fusion of artificial intelligence(AI)and wireless communications in...Intelligence and perception are two operative technologies in 6G scenarios.The intelligent wireless network and information perception require a deep fusion of artificial intelligence(AI)and wireless communications in 6G systems.Therefore,fusion is becoming a typical feature and key challenge of 6G wireless communication systems.In this paper,we focus on the critical issues and propose three application scenarios in 6G wireless systems.Specifically,we first discuss the fusion of AI and 6G networks for the enhancement of 5G-advanced technology and future wireless communication systems.Then,we introduce the wireless AI technology architecture with 6G multidimensional information perception,which includes the physical layer technology of multi-dimensional feature information perception,full spectrum fusion technology,and intelligent wireless resource management.The discussion of key technologies for intelligent 6G wireless network networks is expected to provide a guideline for future research.展开更多
Average credit scores for people in the United States （US） differ from state to state. Some states have high, and some states have low average credit scores. Since lenders and employers use credit scores to make loa...Average credit scores for people in the United States （US） differ from state to state. Some states have high, and some states have low average credit scores. Since lenders and employers use credit scores to make loan and employment decisions, people living in states where average credit scores are high should experience the benefits of living where credit scores tend to allow more favorable loan and employment decisions. Although credit scores are the direct result of credit histories, credit histories may be impacted by demographic factors. If the demographic factors that impact credit histories are identified, ways to improve credit scores are likely to be discovered and available to people and state government policymakers. This study looks for demographic factors to indirectly explain the average credit scores for people living in each state of the US. The methodology includes statistical analyses and geographic information systems （GIS） mapping. Statistical analyses provide evidence to suggest that state average credit scores are explained by the demographic factors of education, family, income, and health. GIS mapping reveals clusters of states with similar demographics and credit scores.展开更多
This paper analyzes the semantics structure of enterprise process metric and gives guidelines to describe the semantics of metric for collecting metric data automatically. Based on domain ontology, a structure called ...This paper analyzes the semantics structure of enterprise process metric and gives guidelines to describe the semantics of metric for collecting metric data automatically. Based on domain ontology, a structure called semantic tree is defined to de- scribe the semantics relationships among measured entity, meas- urable attribute and constraints, which provides the same method to define semantics of process metrics and data elements in enterprise information model. The arithmetic to map process metrics to enterprise information model is put forward, which can compute the query conditions to retrieve process metrics data from enterprise information systems accurately. This arithmetic has been applied in an information project.展开更多
With the rapid development of digital and intelligent information systems, display of radar situation interface has become an important challenge in the field of human-computer interaction. We propose a method for the...With the rapid development of digital and intelligent information systems, display of radar situation interface has become an important challenge in the field of human-computer interaction. We propose a method for the optimization of radar situation interface from error-cognition through the mapping of information characteristics. A mapping method of matrix description is adopted to analyze the association properties between error-cognition sets and design information sets. Based on the mapping relationship between the domain of error-cognition and the domain of design information, a cross-correlational analysis is carried out between error-cognition and design information.We obtain the relationship matrix between the error-cognition of correlation between design information and the degree of importance among design information. Taking the task interface of a warfare navigation display as an example, error factors and the features of design information are extracted. Based on the results, we also propose an optimization design scheme for the radar situation interface.展开更多
Local featured program in Indonesia cannot be separated entirely from commodity strategic bases. Until in 2006, agricultural development formulation showed indicative targets for featured crops commodity production. T...Local featured program in Indonesia cannot be separated entirely from commodity strategic bases. Until in 2006, agricultural development formulation showed indicative targets for featured crops commodity production. The problem of food security is forming of farmer’s independence to protect local resources in efficiently and optimally, so these resources can be more utilized. It can be achieved by assist of information technologies and communication in forming of Geographic Information System (GIS) to support consistency of food security in Indonesia. This research designs prototype geographic information system in order to conduct the accurate mapping and to know the local featured crops production in Indonesia. This level is conducted for documentation and mapping of agricultural products which is the local featured production. This documentation requires the usage of potential physical, economic, social and cultural environment by the utilization of information technology and communication, which have the ability of relevancy and accessibility of reliable information.展开更多
During the pandemic, technological innovation provided a platform with a range of uses, including in the healthcare industry. Technology is currently being used in vaccination drives run by many governments across the...During the pandemic, technological innovation provided a platform with a range of uses, including in the healthcare industry. Technology is currently being used in vaccination drives run by many governments across the world to help spread vaccines quickly and efficiently. The technology makes healthcare personnel more effective at their professions and greatly raises the standard of service in the industry. The researchers undertook this study to create a suitable and long-lasting immunization database with a mapping method to give a better perspective of the immunization status. To gather essential information for this study, the researchers spoke with the local health officer in the targeted area. The obtained data then served as the basis for the system’s capabilities and features, becoming the target problems addressed by the developers. The investigation found that the majority of procedures and interactions are carried out manually and recorded on an unprotected, antiquated Excel spreadsheet. The researchers’ technology also shows to be a superior way to deal with the problems and difficulties while making their health-related transactions and operations quicker, safer, and much more effective.展开更多
Carrying out land and real estate survey is a prerequisite for land and real estate construction. However, land and real estate survey itself is a complex and systematic project, involving a wide range of measurement ...Carrying out land and real estate survey is a prerequisite for land and real estate construction. However, land and real estate survey itself is a complex and systematic project, involving a wide range of measurement and more content, which will lead to greater difficulty in the measurement work. In the past, people often use manual surveying and mapping to measure, which not only costs a lot of time and energy, but also is difficult to achieve good measurement results. With the rapid development of information technology in China, modern people have developed information-based surveying and mapping technology. Applying this technology to land and real estate surveying can not only improve the quality and efficiency of land and real estate surveying, but also realize the automation of land and real estate surveying and the diversification of land and real estate surveying results. At present, there are still many surveyors in our country have insufficient understanding of information-based surveying and mapping technology, which can not be well applied to land and real estate surveying. Based on this, this paper summarizes the problems related to land and real estate surveying and information-based surveying and mapping technology.展开更多
In mine production, using reasonable method to complete the measurement process is helpful for subsequent mining exploration and mining design. In actual measurement, adopting diversified information and surveying and...In mine production, using reasonable method to complete the measurement process is helpful for subsequent mining exploration and mining design. In actual measurement, adopting diversified information and surveying and mapping technology is conducive to further improve the quality and precision of measurement. In this paper, the role of the impact on mine survey is introduced. Moreover, the present situation of using geographic information, surveying and mapping technology and its future development prospect are discussed.展开更多
Visual information processing is not only an important research direction in fields of psychology,neuroscience and artificial intelligence etc,but also the research base on biological recognition theory and technology...Visual information processing is not only an important research direction in fields of psychology,neuroscience and artificial intelligence etc,but also the research base on biological recognition theory and technology realization.Visual information processing in existence,e.g.visual information processing facing to nerve calculation,visual information processing using substance shape distilling and wavelet under high yawp,ANN visual information processing and etc,are very complex in comparison.Using qualitative Mapping,this text describes the specific attributes in the course of visual information processing and the results are more brief and straightforward.So the software program of vision recognition is probably easier to realize.展开更多
In order to cater to the period of the era of big data development, China's surveying and mapping industry should accurately base on the frontier development trends of big data technology, use scientific and reaso...In order to cater to the period of the era of big data development, China's surveying and mapping industry should accurately base on the frontier development trends of big data technology, use scientific and reasonable surveying and mapping technical means, and achieve high quality surveying and mapping process. Among them, for the mine surveying and mapping work, it can take the initiative to combine the surveying and mapping geographic information service to realize the surveying and mapping analysis of the mine data and relevant data, and provide good decision-making data for the mine surveying and mapping work. In view of this, this paper mainly based on the development background of the period of big data, mining surveying and mapping geographic information service issues are studied and analyzed for reference.展开更多
With large scale topographic map charted in accordance with Topographic Map Symbols of 1:500 1:1 000 1:2 000(GB/T 20257.1-2007) as the base map of land survey,the land use status information was collected from the map...With large scale topographic map charted in accordance with Topographic Map Symbols of 1:500 1:1 000 1:2 000(GB/T 20257.1-2007) as the base map of land survey,the land use status information was collected from the map based on the standard in Present Status Classification of Land Utilization(GB/T 21010-2007).The study discussed in details the information of some land types including water system,residential sites,facilities,transportation,pipeline,vegetation,soils and so on,and pointed out problems on extracting land use status information from large scale topographic map.In order to share resources and save social costs,it suggested unifying the standard to classify land types and define all kinds of land types by quantitative values.展开更多
Machine learning(ML)-based prediction models for mapping hazard(e.g.,landslide and debris flow)susceptibility have been widely developed in recent research.However,in some specific areas,ML models have limited applica...Machine learning(ML)-based prediction models for mapping hazard(e.g.,landslide and debris flow)susceptibility have been widely developed in recent research.However,in some specific areas,ML models have limited application because of the uncertainties in identifying negative samples.The Parlung Tsangpo Basin exemplifies a region prone to recurrent glacial debris flows(GDFs)and is characterized by a prominent landform featuring deep gullies.Considering the limitations of the ML model,we developed and compared two combined statistical models(FA-WE and FA-IC)based on factor analysis(FA),weight of evidence(WE),and the information content(IC)method.The final GDF susceptibility maps were generated by selecting 8 most important static factors and considering the influence of precipitation.The results show that the FA-IC model has the best performance.The areas with a very high susceptibility to GDFs are primarily located in the narrow valley section upstream,on both sides of the valley in the middle and downstream of the Parlung Tsangpo River,and in the narrow valley section of each tributary.These areas encompass 86 gullies and are characterized as"narrow and steep".展开更多
ABSTRACT: This paper generalizes the makeup and forming dynamic mechanism of natural disaster systems, principles and methods of comprehensive division of natural disasters, as well as structure, function and up-build...ABSTRACT: This paper generalizes the makeup and forming dynamic mechanism of natural disaster systems, principles and methods of comprehensive division of natural disasters, as well as structure, function and up-build routes of map and file information visualization system (MFIVS). Taking the Changjiang(Yangtze) Valley as an example, on the basis of revealing up the integrated mechanism on the formations of its natural disasters and its distributing law, thereafter, the paper relies on the MFIVS technique, adopts two top-down and bottom-up approaches to study a comprehensive division of natural disasters. It is relatively objective and precise that the required division results include three natural disaster sections and nine natural disaster sub-sections, which can not only provide a scientific basis for utilizing natural resources and controlling natural disaster and environmental degradation, but also be illuminated to a concise, practical and effective technique on comprehensive division.展开更多
基金supported by the National Key R&D Program of China(No.2021YFC2103600)the National Natural Science Foundation of China(Nos.21878156,21978131,22275085,and 22278224)+2 种基金the Natural Science Foundation of Jiangsu Province(Nos.BK20200089 and BK20200691)the Project of Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the State Key Laboratory of Materials-Oriented Chemical Engineering(No.KL21-08).
文摘Constructing multi-dimensional hydrogen bond(H-bond)regulated single-molecule systems with multiemission remains a challenge.Herein,we report the design of a new excited-state intramolecular proton transfer(ESIPT)featured chromophore(HBT-DPI)that shows flexible emission tunability via the multidimensional regulation of intra-and intermolecular H-bonds.The feature of switchable intramolecular Hbonds is induced via incorporating several hydrogen bond acceptors and donors into one single HBT-DPI molecule,allowing the“turn on/off”of ESIPT process by forming isomers with distinct intramolecular Hbonds configurations.In response to different external H-bonding environments,the obtained four types of crystal/cocrystals vary in the contents of isomers and the molecular packing modes,which are mainly guided by the intermolecular H-bonds,exhibiting non-emissive features or emissions ranging from green to orange.Utilizing the feature of intermolecular H-bond guided molecular packing,we demonstrate the utility of this fluorescent material for visualizing hydrophobic/hydrophilic areas on large-scale heterogeneous surfaces of modified poly(1,1-difluoroethylene)(PVDF)membranes and quantitatively estimating the surface hydrophobicity,providing a new approach for hydrophobicity/hydrophilicity monitoring and measurement.Overall,this study represents a new design strategy for constructing multi-dimensional hydrogen bond regulated ESIPT-based fluorescent materials that enable multiple emissions and unique applications.
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supported by the project“GEF9874:Strengthening Coordinated Approaches to Reduce Invasive Alien Species(lAS)Threats to Globally Significant Agrobiodiversity and Agroecosystems in China”funding from the Excellent Talent Training Funding Project in Dongcheng District,Beijing,with project number 2024-dchrcpyzz-9.
文摘Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.
基金funded by Deanship of Research and Graduate Studies at King Khalid University.The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Group Project under grant number(RGP.2/556/45).
文摘Ensuring information security in the quantum era is a growing challenge due to advancements in cryptographic attacks and the emergence of quantum computing.To address these concerns,this paper presents the mathematical and computer modeling of a novel two-dimensional(2D)chaotic system for secure key generation in quantum image encryption(QIE).The proposed map employs trigonometric perturbations in conjunction with rational-saturation functions and hence,named as Trigonometric-Rational-Saturation(TRS)map.Through rigorous mathematical analysis and computational simulations,the map is extensively evaluated for bifurcation behaviour,chaotic trajectories,and Lyapunov exponents.The security evaluation validates the map’s non-linearity,unpredictability,and sensitive dependence on initial conditions.In addition,the proposed TRS map has further been tested by integrating it in a QIE scheme.The QIE scheme first quantum-encodes the classic image using the Novel Enhanced Quantum Representation(NEQR)technique,the TRS map is used for the generation of secure diffusion key,which is XOR-ed with the quantum-ready image to obtain the encrypted images.The security evaluation of the QIE scheme demonstrates superior security of the encrypted images in terms of statistical security attacks and also against Differential attacks.The encrypted images exhibit zero correlation and maximum entropy with demonstrating strong resilience due to 99.62%and 33.47%results for Number of Pixels Change Rate(NPCR)and Unified Average Changing Intensity(UACI).The results validate the effectiveness of TRS-based quantum encryption scheme in securing digital images against emerging quantum threats,making it suitable for secure image encryption in IoT and edge-based applications.
基金supported in part by the National Natural Science Foundation of China(Nos.62202234,62401270)the China Postdoctoral Science Foundation(No.2023M741778)the Natural Science Foundation of Jiangsu Province(Nos.BK20240706,BK20240694).
文摘Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,the existing generative image steganography methods generally have good steganography performance,but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information extraction.Therefore,this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping rule.Firstly,the reference image is disentangled by a content and an attribute encoder to obtain content features and attribute features,respectively.Then,a mean mapping rule is introduced to map the binary secret information into a noise vector,conforming to the distribution of attribute features.This noise vector is input into the generator to produce the attribute transformed stego image with the content feature of the reference image.Additionally,we design an adversarial loss,a reconstruction loss,and an image diversity loss to train the proposed model.Experimental results demonstrate that the stego images generated by the proposed method are of high quality,with an average extraction accuracy of 99.4%for the hidden information.Furthermore,since the stego image has a uniform distribution similar to the attribute-transformed image without secret information,it effectively resists both subjective and objective steganalysis.
基金supported by the National Natural Science Foundation of China[grant number 41930104]by the Research Grants Council of Hong Kong[grant number PolyU 152219/18E].
文摘Information on Land Use and Land Cover Map(LULCM)is essential for environment and socioeconomic applications.Such maps are generally derived from Multispectral Remote Sensing Images(MRSI)via classification.The classification process can be described as information flow from images to maps through a trained classifier.Characterizing the information flow is essential for understanding the classification mechanism,providing solutions that address such theoretical issues as“what is the maximum number of classes that can be classified from a given MRSI?”and“how much information gain can be obtained?”Consequently,two interesting questions naturally arise,i.e.(i)How can we characterize the information flow?and(ii)What is the mathematical form of the information flow?To answer these two questions,this study first hypothesizes that thermodynamic entropy is the appropriate measure of information for both MRSI and LULCM.This hypothesis is then supported by kinetic-theory-based experiments.Thereafter,upon such an entropy,a generalized Jarzynski equation is formulated to mathematically model the information flow,which contains such parameters as thermodynamic entropy of MRSI,thermodynamic entropy of LULCM,weighted F1-score(classification accuracy),and total number of classes.This generalized Jarzynski equation has been successfully validated by hypothesis-driven experiments where 694 Sentinel-2 images are classified into 10 classes by four classical classifiers.This study provides a way for linking thermodynamic laws and concepts to the characterization and understanding of information flow in land cover classification,opening a new door for constructing domain knowledge.
基金This work was supported in part by the National Natural Science Foundation of China(61601418,41602362,61871259)in part by the Opening Foundation of Hunan Engineering and Research Center of Natural Resource Investigation and Monitoring(2020-5)+1 种基金in part by the Qilian Mountain National Park Research Center(Qinghai)(grant number:GKQ2019-01)in part by the Geomatics Technology and Application Key Laboratory of Qinghai Province,Grant No.QHDX-2019-01.
文摘This work was to generate landslide susceptibility maps for the Three Gorges Reservoir(TGR) area, China by using different machine learning models. Three advanced machine learning methods, namely, gradient boosting decision tree(GBDT), random forest(RF) and information value(InV) models, were used, and the performances were assessed and compared. In total, 202 landslides were mapped by using a series of field surveys, aerial photographs, and reviews of historical and bibliographical data. Nine causative factors were then considered in landslide susceptibility map generation by using the GBDT, RF and InV models. All of the maps of the causative factors were resampled to a resolution of 28.5 m. Of the 486289 pixels in the area,28526 pixels were landslide pixels, and 457763 pixels were non-landslide pixels. Finally, landslide susceptibility maps were generated by using the three machine learning models, and their performances were assessed through receiver operating characteristic(ROC) curves, the sensitivity, specificity,overall accuracy(OA), and kappa coefficient(KAPPA). The results showed that the GBDT, RF and In V models in overall produced reasonable accurate landslide susceptibility maps. Among these three methods, the GBDT method outperforms the other two machine learning methods, which can provide strong technical support for producing landslide susceptibility maps in TGR.
文摘Intelligence and perception are two operative technologies in 6G scenarios.The intelligent wireless network and information perception require a deep fusion of artificial intelligence(AI)and wireless communications in 6G systems.Therefore,fusion is becoming a typical feature and key challenge of 6G wireless communication systems.In this paper,we focus on the critical issues and propose three application scenarios in 6G wireless systems.Specifically,we first discuss the fusion of AI and 6G networks for the enhancement of 5G-advanced technology and future wireless communication systems.Then,we introduce the wireless AI technology architecture with 6G multidimensional information perception,which includes the physical layer technology of multi-dimensional feature information perception,full spectrum fusion technology,and intelligent wireless resource management.The discussion of key technologies for intelligent 6G wireless network networks is expected to provide a guideline for future research.
文摘Average credit scores for people in the United States （US） differ from state to state. Some states have high, and some states have low average credit scores. Since lenders and employers use credit scores to make loan and employment decisions, people living in states where average credit scores are high should experience the benefits of living where credit scores tend to allow more favorable loan and employment decisions. Although credit scores are the direct result of credit histories, credit histories may be impacted by demographic factors. If the demographic factors that impact credit histories are identified, ways to improve credit scores are likely to be discovered and available to people and state government policymakers. This study looks for demographic factors to indirectly explain the average credit scores for people living in each state of the US. The methodology includes statistical analyses and geographic information systems （GIS） mapping. Statistical analyses provide evidence to suggest that state average credit scores are explained by the demographic factors of education, family, income, and health. GIS mapping reveals clusters of states with similar demographics and credit scores.
基金Supported by the National High Technology Research and Development Program of China (863 Progam) (2006AA09A102-15)the National Major Project of Science and Technology of China (2008ZX05023-05-05)
文摘This paper analyzes the semantics structure of enterprise process metric and gives guidelines to describe the semantics of metric for collecting metric data automatically. Based on domain ontology, a structure called semantic tree is defined to de- scribe the semantics relationships among measured entity, meas- urable attribute and constraints, which provides the same method to define semantics of process metrics and data elements in enterprise information model. The arithmetic to map process metrics to enterprise information model is put forward, which can compute the query conditions to retrieve process metrics data from enterprise information systems accurately. This arithmetic has been applied in an information project.
基金supported by Jiangsu Province Nature Science Foundation of China (BK20221490)the Key Fundamental Research Funds for the Central Universities (30920041114)+2 种基金the National Natural Science Foundation of China (52175469,71601068)the Key Research and Development (Social Development) Project of Jiangsu Province(BE2019647)Jiangsu Province Social Science Foundation of China (20YSB013)。
文摘With the rapid development of digital and intelligent information systems, display of radar situation interface has become an important challenge in the field of human-computer interaction. We propose a method for the optimization of radar situation interface from error-cognition through the mapping of information characteristics. A mapping method of matrix description is adopted to analyze the association properties between error-cognition sets and design information sets. Based on the mapping relationship between the domain of error-cognition and the domain of design information, a cross-correlational analysis is carried out between error-cognition and design information.We obtain the relationship matrix between the error-cognition of correlation between design information and the degree of importance among design information. Taking the task interface of a warfare navigation display as an example, error factors and the features of design information are extracted. Based on the results, we also propose an optimization design scheme for the radar situation interface.
文摘Local featured program in Indonesia cannot be separated entirely from commodity strategic bases. Until in 2006, agricultural development formulation showed indicative targets for featured crops commodity production. The problem of food security is forming of farmer’s independence to protect local resources in efficiently and optimally, so these resources can be more utilized. It can be achieved by assist of information technologies and communication in forming of Geographic Information System (GIS) to support consistency of food security in Indonesia. This research designs prototype geographic information system in order to conduct the accurate mapping and to know the local featured crops production in Indonesia. This level is conducted for documentation and mapping of agricultural products which is the local featured production. This documentation requires the usage of potential physical, economic, social and cultural environment by the utilization of information technology and communication, which have the ability of relevancy and accessibility of reliable information.
文摘During the pandemic, technological innovation provided a platform with a range of uses, including in the healthcare industry. Technology is currently being used in vaccination drives run by many governments across the world to help spread vaccines quickly and efficiently. The technology makes healthcare personnel more effective at their professions and greatly raises the standard of service in the industry. The researchers undertook this study to create a suitable and long-lasting immunization database with a mapping method to give a better perspective of the immunization status. To gather essential information for this study, the researchers spoke with the local health officer in the targeted area. The obtained data then served as the basis for the system’s capabilities and features, becoming the target problems addressed by the developers. The investigation found that the majority of procedures and interactions are carried out manually and recorded on an unprotected, antiquated Excel spreadsheet. The researchers’ technology also shows to be a superior way to deal with the problems and difficulties while making their health-related transactions and operations quicker, safer, and much more effective.
文摘Carrying out land and real estate survey is a prerequisite for land and real estate construction. However, land and real estate survey itself is a complex and systematic project, involving a wide range of measurement and more content, which will lead to greater difficulty in the measurement work. In the past, people often use manual surveying and mapping to measure, which not only costs a lot of time and energy, but also is difficult to achieve good measurement results. With the rapid development of information technology in China, modern people have developed information-based surveying and mapping technology. Applying this technology to land and real estate surveying can not only improve the quality and efficiency of land and real estate surveying, but also realize the automation of land and real estate surveying and the diversification of land and real estate surveying results. At present, there are still many surveyors in our country have insufficient understanding of information-based surveying and mapping technology, which can not be well applied to land and real estate surveying. Based on this, this paper summarizes the problems related to land and real estate surveying and information-based surveying and mapping technology.
文摘In mine production, using reasonable method to complete the measurement process is helpful for subsequent mining exploration and mining design. In actual measurement, adopting diversified information and surveying and mapping technology is conducive to further improve the quality and precision of measurement. In this paper, the role of the impact on mine survey is introduced. Moreover, the present situation of using geographic information, surveying and mapping technology and its future development prospect are discussed.
文摘Visual information processing is not only an important research direction in fields of psychology,neuroscience and artificial intelligence etc,but also the research base on biological recognition theory and technology realization.Visual information processing in existence,e.g.visual information processing facing to nerve calculation,visual information processing using substance shape distilling and wavelet under high yawp,ANN visual information processing and etc,are very complex in comparison.Using qualitative Mapping,this text describes the specific attributes in the course of visual information processing and the results are more brief and straightforward.So the software program of vision recognition is probably easier to realize.
文摘In order to cater to the period of the era of big data development, China's surveying and mapping industry should accurately base on the frontier development trends of big data technology, use scientific and reasonable surveying and mapping technical means, and achieve high quality surveying and mapping process. Among them, for the mine surveying and mapping work, it can take the initiative to combine the surveying and mapping geographic information service to realize the surveying and mapping analysis of the mine data and relevant data, and provide good decision-making data for the mine surveying and mapping work. In view of this, this paper mainly based on the development background of the period of big data, mining surveying and mapping geographic information service issues are studied and analyzed for reference.
基金Supported by Programs of Scientific and Technological Foundation of Nanjing Forestry University (X09-050-2)~~
文摘With large scale topographic map charted in accordance with Topographic Map Symbols of 1:500 1:1 000 1:2 000(GB/T 20257.1-2007) as the base map of land survey,the land use status information was collected from the map based on the standard in Present Status Classification of Land Utilization(GB/T 21010-2007).The study discussed in details the information of some land types including water system,residential sites,facilities,transportation,pipeline,vegetation,soils and so on,and pointed out problems on extracting land use status information from large scale topographic map.In order to share resources and save social costs,it suggested unifying the standard to classify land types and define all kinds of land types by quantitative values.
基金funded by the National Natural Science Foundation of China(Grant Nos.42377170).
文摘Machine learning(ML)-based prediction models for mapping hazard(e.g.,landslide and debris flow)susceptibility have been widely developed in recent research.However,in some specific areas,ML models have limited application because of the uncertainties in identifying negative samples.The Parlung Tsangpo Basin exemplifies a region prone to recurrent glacial debris flows(GDFs)and is characterized by a prominent landform featuring deep gullies.Considering the limitations of the ML model,we developed and compared two combined statistical models(FA-WE and FA-IC)based on factor analysis(FA),weight of evidence(WE),and the information content(IC)method.The final GDF susceptibility maps were generated by selecting 8 most important static factors and considering the influence of precipitation.The results show that the FA-IC model has the best performance.The areas with a very high susceptibility to GDFs are primarily located in the narrow valley section upstream,on both sides of the valley in the middle and downstream of the Parlung Tsangpo River,and in the narrow valley section of each tributary.These areas encompass 86 gullies and are characterized as"narrow and steep".
基金Under the auspices of President Foundation of the Chinese Academy of Sciences(1999).
文摘ABSTRACT: This paper generalizes the makeup and forming dynamic mechanism of natural disaster systems, principles and methods of comprehensive division of natural disasters, as well as structure, function and up-build routes of map and file information visualization system (MFIVS). Taking the Changjiang(Yangtze) Valley as an example, on the basis of revealing up the integrated mechanism on the formations of its natural disasters and its distributing law, thereafter, the paper relies on the MFIVS technique, adopts two top-down and bottom-up approaches to study a comprehensive division of natural disasters. It is relatively objective and precise that the required division results include three natural disaster sections and nine natural disaster sub-sections, which can not only provide a scientific basis for utilizing natural resources and controlling natural disaster and environmental degradation, but also be illuminated to a concise, practical and effective technique on comprehensive division.
