Aims ENGINEERING Information Technology&Electronic Engineering(EITEE),formerly known as Frontiers of Information Technology&Electronic Engineering(2015-2025)and Journal of Zhejiang University SCIENCE C(Compute...Aims ENGINEERING Information Technology&Electronic Engineering(EITEE),formerly known as Frontiers of Information Technology&Electronic Engineering(2015-2025)and Journal of Zhejiang University SCIENCE C(Computers&Electronics)(2010-2014),is a peer-reviewed scientific journal launched by the Chinese Academy of Engineering and Zhejiang University that aims to present the latest developments and achievements in information technology and electronic engineering to stimulate and promote academic exchanges between Chinese and foreign scientists.展开更多
Large-scale complex systems are integral to the functioning of various organizations within the national economy.Despite their significance,the lengthy construction cycles and the involvement of multiple entities ofte...Large-scale complex systems are integral to the functioning of various organizations within the national economy.Despite their significance,the lengthy construction cycles and the involvement of multiple entities often result in the deprioritization of standardized management practices,as they do not yield immediate benefits.The implementation of such systems typically encompasses the integrated phases of "development,construction,utiliz ation,and operation and maintenance".To enhance the overall delivery quality of these systems,it is imperative to dismantle the management barriers among these phases and adopt a holistic approach to standardized management.This paper takes a specific system project as a research object to identify common challenges,and proposes improvement strategies in the implementation of standar dized management.Empirical results indicate a substantial reduction in the system s full-lifecycle costs.展开更多
High-dimensional data causes difficulties in machine learning due to high time consumption and large memory requirements.In particular,in amulti-label environment,higher complexity is required asmuch as the number of ...High-dimensional data causes difficulties in machine learning due to high time consumption and large memory requirements.In particular,in amulti-label environment,higher complexity is required asmuch as the number of labels.Moreover,an optimization problem that fully considers all dependencies between features and labels is difficult to solve.In this study,we propose a novel regression-basedmulti-label feature selectionmethod that integrates mutual information to better exploit the underlying data structure.By incorporating mutual information into the regression formulation,the model captures not only linear relationships but also complex non-linear dependencies.The proposed objective function simultaneously considers three types of relationships:(1)feature redundancy,(2)featurelabel relevance,and(3)inter-label dependency.These three quantities are computed usingmutual information,allowing the proposed formulation to capture nonlinear dependencies among variables.These three types of relationships are key factors in multi-label feature selection,and our method expresses them within a unified formulation,enabling efficient optimization while simultaneously accounting for all of them.To efficiently solve the proposed optimization problem under non-negativity constraints,we develop a gradient-based optimization algorithm with fast convergence.Theexperimental results on sevenmulti-label datasets show that the proposed method outperforms existingmulti-label feature selection techniques.展开更多
Single Image Super-Resolution(SISR)seeks to reconstruct high-resolution(HR)images from lowresolution(LR)inputs,thereby enhancing visual fidelity and the perception of fine details.While Transformer-based models—such ...Single Image Super-Resolution(SISR)seeks to reconstruct high-resolution(HR)images from lowresolution(LR)inputs,thereby enhancing visual fidelity and the perception of fine details.While Transformer-based models—such as SwinIR,Restormer,and HAT—have recently achieved impressive results in super-resolution tasks by capturing global contextual information,these methods often suffer from substantial computational and memory overhead,which limits their deployment on resource-constrained edge devices.To address these challenges,we propose a novel lightweight super-resolution network,termed Binary Attention-Guided Information Distillation(BAID),which integrates frequency-aware modeling with a binary attention mechanism to significantly reduce computational complexity and parameter count whilemaintaining strong reconstruction performance.The network combines a high–low frequency decoupling strategy with a local–global attention sharing mechanism,enabling efficient compression of redundant computations through binary attention guidance.At the core of the architecture lies the Attention-Guided Distillation Block(AGDB),which retains the strengths of the information distillation framework while introducing a sparse binary attention module to enhance both inference efficiency and feature representation.Extensive×4 superresolution experiments on four standard benchmarks—Set5,Set14,BSD100,and Urban100—demonstrate that BAID achieves Peak Signal-to-Noise Ratio(PSNR)values of 32.13,28.51,27.47,and 26.15,respectively,with only 1.22 million parameters and 26.1 G Floating-Point Operations(FLOPs),outperforming other state-of-the-art lightweight methods such as Information Multi-Distillation Network(IMDN)and Residual Feature Distillation Network(RFDN).These results highlight the proposed model’s ability to deliver high-quality image reconstruction while offering strong deployment efficiency,making it well-suited for image restoration tasks in resource-limited environments.展开更多
1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography, natural resources, environmental sciences, geographic inf...1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography, natural resources, environmental sciences, geographic information sciences, remote sensing and cartography. Manuscripts come from different parts of the world.展开更多
Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automaticall...Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automatically and manually corrected hydrological slope unit division,the Longhua District,Shenzhen City,Guangdong Province,was selected as the study area.A total of 15 influencing factors,namely Fluctuation,slope,slope aspect,curvature,topographic witness index(TWI),stream power index(SPI),topographic roughness index(TRI),annual average rainfall,distance to water system,engineering rock group,distance to fault,land use,normalized difference vegetation index(NDVI),nighttime light,and distance to road,were selected as evaluation indicators.The information volume model(IV)and random points were used to select non-geological disaster units,and then the random forest model(RF)was used to evaluate the susceptibility to geological disasters.The automatic slope unit and the hydrological slope unit were compared and analyzed in the random forest and information volume random forest models.The results show that the area under the curve(AUC)values of the automatic slope unit evaluation results are 0.931 for the IV-RF model and 0.716 for the RF model,which are 0.6%(IV-RF model)and 1.9%(RF model)higher than those for the hydrological slope unit.Based on a comparison of the evaluation methods based on the two types of slope units,the hydrological slope unit evaluation method based on manual correction is highly subjective,is complicated to operate,and has a low evaluation accuracy,whereas the evaluation method based on automatic slope unit division is efficient and accurate,is suitable for large-scale efficient geological disaster evaluation,and can better deal with the problem of geological disaster susceptibility evaluation.展开更多
Modern business information systems face significant challenges in managing heterogeneous data sources,integrating disparate systems,and providing real-time decision support in complex enterprise environments.Contempo...Modern business information systems face significant challenges in managing heterogeneous data sources,integrating disparate systems,and providing real-time decision support in complex enterprise environments.Contemporary enterprises typically operate 200+interconnected systems,with research indicating that 52% of organizations manage three or more enterprise content management systems,creating information silos that reduce operational efficiency by up to 35%.While attention mechanisms have demonstrated remarkable success in natural language processing and computer vision,their systematic application to business information systems remains largely unexplored.This paper presents the theoretical foundation for a Hierarchical Attention-Based Business Information System(HABIS)framework that applies multi-level attention mechanisms to enterprise environments.We provide a comprehensive mathematical formulation of the framework,analyze its computational complexity,and present a proof-of-concept implementation with simulation-based validation that demonstrates a 42% reduction in crosssystem query latency compared to legacy ERP modules and 70% improvement in prediction accuracy over baseline methods.The theoretical framework introduces four hierarchical attention levels:system-level attention for dynamic weighting of business systems,process-level attention for business process prioritization,data-level attention for critical information selection,and temporal attention for time-sensitive pattern recognition.Our complexity analysis demonstrates that the framework achieves O(n log n)computational complexity for attention computation,making it scalable to large enterprise environments including retail supply chains with 200+system-scale deployments.The proof-of-concept implementation validates the theoretical framework’s feasibility withMSE loss of 0.439 and response times of 0.000120 s per query,demonstrating its potential for addressing key challenges in business information systems.This work establishes a foundation for future empirical research and practical implementation of attention-driven enterprise systems.展开更多
With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State I...With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing.展开更多
The internal flow fields within a three-dimensional inward-tunning combined inlet are extremely complex,especially during the engine mode transition,where the tunnel changes may impact the flow fields significantly.To...The internal flow fields within a three-dimensional inward-tunning combined inlet are extremely complex,especially during the engine mode transition,where the tunnel changes may impact the flow fields significantly.To develop an efficient flow field reconstruction model for this,we present an Improved Conditional Denoising Diffusion Generative Adversarial Network(ICDDGAN),which integrates Conditional Denoising Diffusion Probabilistic Models(CDDPMs)with Style GAN,and introduce a reconstruction discrimination mechanism and dynamic loss weight learning strategy.We establish the Mach number flow field dataset by numerical simulation at various backpressures for the mode transition process from turbine mode to ejector ramjet mode at Mach number 2.5.The proposed ICDDGAN model,given only sparse parameter information,can rapidly generate high-quality Mach number flow fields without a large number of samples for training.The results show that ICDDGAN is superior to CDDGAN in terms of training convergence and stability.Moreover,the interpolation and extrapolation test results during backpressure conditions show that ICDDGAN can accurately and quickly reconstruct Mach number fields at various tunnel slice shapes,with a Structural Similarity Index Measure(SSIM)of over 0.96 and a Mean-Square Error(MSE)of 0.035%to actual flow fields,reducing time costs by 7-8 orders of magnitude compared to Computational Fluid Dynamics(CFD)calculations.This can provide an efficient means for rapid computation of complex flow fields.展开更多
This study attempts to understand the role of ICTs on adoption of climate change adaption options among the Nepalese rice farmers, using data from 773 households from seven districts—3 from Terai region and 4 from hi...This study attempts to understand the role of ICTs on adoption of climate change adaption options among the Nepalese rice farmers, using data from 773 households from seven districts—3 from Terai region and 4 from hilly region. Individual Farmer’s Awareness Index was developed to categorize the respondent knowledge of climate change adaptation and Ordered Logit Model was used to examine the factors influencing their adaptation options in present of ICTs. The result revealed that 65% farmers perceived knowledge about temperature, rainfall and other relative information from various ICT devices that they pose. Farmers received such information mostly from Radio (71%), TV (69%) and mobile phone (62.5%) and argued these three devices are the most prominent, easy access and practical devices to receive such information. 86% farmers used such devices on the daily basis and 90% and more users opined that the information provided from such devices is in their own language and fully understandable. From ICT devices they pose, 71% of the farmers are receiving climate change information and 61% received agro-related information and the majority of them argued that such available information is very much informative and supportive of their resilience to climate change and use of available adaptation options. From the Farmers Awareness Index, this study found 19.8% farmers are high aware, 65.1% medium aware and 15.1% were less aware of the changing climate and its anomalies. Similarly, result from Ordered Logit Model shows that age (0.45***), gender (0.48**), market center (0.32*), bank access (0.54***), availability of subsidy (1.0***), agro-extension services (0.71**), access to TV (0.67***) and membership to a social network (3.20**) played a significant role in increasing farmers’ awareness of climate change which in turn lead to increased adoption of adaptation options available to the farmers. The findings suggest the need for further improvement on ICT devices and publicity of such ICT devices and proper investment to boost rice farmers’ adaptation to climate change, which will in turn help to improve their livelihoods and well-being.展开更多
There is a widespread belief that information and knowledge are vital for rural and agricultural development. Today, generation of new and various information and knowledge sources need new information and communicati...There is a widespread belief that information and knowledge are vital for rural and agricultural development. Today, generation of new and various information and knowledge sources need new information and communication channels. New information and communication technologies can decrease poverty by promotion rural people access to education, health, government and financial services; overall, they can improve livelihood. The purpose of this study was to identify potentials of new information and communications technologies （ICTs） in agricultural and rural sector. Documentary research and literature review were used as research method. Findings revealed that the most applications for these ICTs in rural and agricultural sector were： E-trade of inputs and outputs, extension and training activities for rural dwellers, advertisement of rural tourism products, knowledge transfer from urban to rural and vice versa, official procedures and geographic information system （GIS） for management of natural resources.展开更多
The study investigated constraints of women farmers access to ICTs for agricultural information in Oyo State.A total of 120 respondents were sampled.Data were retrieved using interview schedule and were analysed using...The study investigated constraints of women farmers access to ICTs for agricultural information in Oyo State.A total of 120 respondents were sampled.Data were retrieved using interview schedule and were analysed using descriptive and inferential statistics.Statistics reveal respondents average age,average household size and average monthly income as x=45.8,x=10.6 and x=₦7,800.34 respectively,majority(86.7%)were married,58.3%representing respondents with primary education.Mobile phone(x=0.98)was the most available among the respondents while poor ICTs infrastructure(x=1.55)and difficulty in the utilization of ICTs gadgets(x=1.62)ranked highest as constraints access to ICTs for agricultural information.Significant relationship existed between respondents average monthly income(r=0.492,p=0.000),educational level(χ^(2)=4.726,p=0.021)and the constraints access to ICTs for agricultural information.Scaling up the ICTs infrastructure base around farming clusters and capacity building like training on ICTs to access agricultural information retrieval is advocated for women farmers.展开更多
Electronic commerce which denotes the process of electronic transaction via internet has led to a very significant improvement in the level of growth, development, efficiency and productivity of global economies. In o...Electronic commerce which denotes the process of electronic transaction via internet has led to a very significant improvement in the level of growth, development, efficiency and productivity of global economies. In order to benefit from the economic opportunities offered by electronic commerce, Nigerian government and business organizations needs to effectively integrate Information and Communication Technologies (ICTs) as the major component of e-commerce campaign initiatives. The discussion in the paper is centered on e-commerce and ICTs and their resultant effect on Nigeria’s economic growth and development. This paper has presented an in-depth discussion of the various types of e-commerce, the major contributions of e-commerce to the economic growth of Nigeria and finally the challenges that impede the growth of e-commerce in Nigeria were identified and the possible recommendations for solutions to those challenges were provided.展开更多
With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration wi...With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.展开更多
This article analyzes the concentration of production and distribution of information, from the analysis of the news in major international news agencies.The biopolitics is more and more interconnected to social, cult...This article analyzes the concentration of production and distribution of information, from the analysis of the news in major international news agencies.The biopolitics is more and more interconnected to social, cultural, economical, and political matters, which led us to see in the contemporary scenario the creation of new forms of social organization which will determine how we interact with each other and how we face the world. Additionally, questions emerge about the usage of the means of communication, particularly those related to Technology of Communication and Information （TICs）. The influence of the media over the social-cultural activities tends to create homogenizations of senses, aiming a planetary visibility in a process that can not only disfigure but destroy many symbolic representations and cultural forms. On the other hand, globalization tends to, instead of minimize the differences in the world, ended up creating new conflicts that, through the usage of new technologies of communication, expresses and articulate themselves.展开更多
This paper introduced first a conceptual framework of 'information literacy training of farmers' based on the widely recognized understanding of the term 'information literacy(IL).' It then followed wi...This paper introduced first a conceptual framework of 'information literacy training of farmers' based on the widely recognized understanding of the term 'information literacy(IL).' It then followed with a discussion based on these three authors' field investigation regarding to Hubei peasants' current information literacy training in such perspectives as information consciousness,information ability and ways and means of information access.It concluded by pointing out some of the more apparent factors that had adverse impacts on the farmers' information literacy training in central China and suggested a few possible remedial measures to guide the course for those who are involved in such undertakings.展开更多
There is curiosity and awareness throughout the world regarding the role of Information and Communication technologies. This is felt in each and every section of society. Several studies have confirmed and considered ...There is curiosity and awareness throughout the world regarding the role of Information and Communication technologies. This is felt in each and every section of society. Several studies have confirmed and considered information and communication technology’s significance in the field of education. It has not only affected learners but also to the teachers. This paper explores how ICT-based projects affect teachers’ and students’ attitudes. The data was collected through self-prepared attitude scale. It was distributed among the teachers and students of various schools. Two hundred students and one hundred twenty teachers responded to the questionnaire. Analysis was done through the data collected from the teachers as well as from students. The study’s conclusions demonstrated that while there was no significant variation in the attitudes of teachers utilizing different ICT-based programs, there was a substantial difference in the students’ attitude toward learning with different ICT-based programs.展开更多
Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the con...Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the context of fewshot and zero-shot scenarios remains highly challenging due to the scarcity of training data.Large language models(LLMs),on the other hand,can generalize well to unseen tasks with few-shot demonstrations or even zero-shot instructions and have demonstrated impressive ability for a wide range of natural language understanding or generation tasks.Nevertheless,it is unclear,whether such effectiveness can be replicated in the task of IE,where the target tasks involve specialized schema and quite abstractive entity or relation concepts.In this paper,we first examine the validity of LLMs in executing IE tasks with an established prompting strategy and further propose multiple types of augmented prompting methods,including the structured fundamental prompt(SFP),the structured interactive reasoning prompt(SIRP),and the voting-enabled structured interactive reasoning prompt(VESIRP).The experimental results demonstrate that while directly promotes inferior performance,the proposed augmented prompt methods significantly improve the extraction accuracy,achieving comparable or even better performance(e.g.,zero-shot FewNERD,FewNERD-INTRA)than state-of-theart methods that require large-scale training samples.This study represents a systematic exploration of employing instruction-following LLM for the task of IE.It not only establishes a performance benchmark for this novel paradigm but,more importantly,validates a practical technical pathway through the proposed prompt enhancement method,offering a viable solution for efficient IE in low-resource settings.展开更多
文摘Aims ENGINEERING Information Technology&Electronic Engineering(EITEE),formerly known as Frontiers of Information Technology&Electronic Engineering(2015-2025)and Journal of Zhejiang University SCIENCE C(Computers&Electronics)(2010-2014),is a peer-reviewed scientific journal launched by the Chinese Academy of Engineering and Zhejiang University that aims to present the latest developments and achievements in information technology and electronic engineering to stimulate and promote academic exchanges between Chinese and foreign scientists.
文摘Large-scale complex systems are integral to the functioning of various organizations within the national economy.Despite their significance,the lengthy construction cycles and the involvement of multiple entities often result in the deprioritization of standardized management practices,as they do not yield immediate benefits.The implementation of such systems typically encompasses the integrated phases of "development,construction,utiliz ation,and operation and maintenance".To enhance the overall delivery quality of these systems,it is imperative to dismantle the management barriers among these phases and adopt a holistic approach to standardized management.This paper takes a specific system project as a research object to identify common challenges,and proposes improvement strategies in the implementation of standar dized management.Empirical results indicate a substantial reduction in the system s full-lifecycle costs.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(RS-2020-NR049579).
文摘High-dimensional data causes difficulties in machine learning due to high time consumption and large memory requirements.In particular,in amulti-label environment,higher complexity is required asmuch as the number of labels.Moreover,an optimization problem that fully considers all dependencies between features and labels is difficult to solve.In this study,we propose a novel regression-basedmulti-label feature selectionmethod that integrates mutual information to better exploit the underlying data structure.By incorporating mutual information into the regression formulation,the model captures not only linear relationships but also complex non-linear dependencies.The proposed objective function simultaneously considers three types of relationships:(1)feature redundancy,(2)featurelabel relevance,and(3)inter-label dependency.These three quantities are computed usingmutual information,allowing the proposed formulation to capture nonlinear dependencies among variables.These three types of relationships are key factors in multi-label feature selection,and our method expresses them within a unified formulation,enabling efficient optimization while simultaneously accounting for all of them.To efficiently solve the proposed optimization problem under non-negativity constraints,we develop a gradient-based optimization algorithm with fast convergence.Theexperimental results on sevenmulti-label datasets show that the proposed method outperforms existingmulti-label feature selection techniques.
基金funded by Project of Sichuan Provincial Department of Science and Technology under 2025JDKP0150the Fundamental Research Funds for the Central Universities under 25CAFUC03093.
文摘Single Image Super-Resolution(SISR)seeks to reconstruct high-resolution(HR)images from lowresolution(LR)inputs,thereby enhancing visual fidelity and the perception of fine details.While Transformer-based models—such as SwinIR,Restormer,and HAT—have recently achieved impressive results in super-resolution tasks by capturing global contextual information,these methods often suffer from substantial computational and memory overhead,which limits their deployment on resource-constrained edge devices.To address these challenges,we propose a novel lightweight super-resolution network,termed Binary Attention-Guided Information Distillation(BAID),which integrates frequency-aware modeling with a binary attention mechanism to significantly reduce computational complexity and parameter count whilemaintaining strong reconstruction performance.The network combines a high–low frequency decoupling strategy with a local–global attention sharing mechanism,enabling efficient compression of redundant computations through binary attention guidance.At the core of the architecture lies the Attention-Guided Distillation Block(AGDB),which retains the strengths of the information distillation framework while introducing a sparse binary attention module to enhance both inference efficiency and feature representation.Extensive×4 superresolution experiments on four standard benchmarks—Set5,Set14,BSD100,and Urban100—demonstrate that BAID achieves Peak Signal-to-Noise Ratio(PSNR)values of 32.13,28.51,27.47,and 26.15,respectively,with only 1.22 million parameters and 26.1 G Floating-Point Operations(FLOPs),outperforming other state-of-the-art lightweight methods such as Information Multi-Distillation Network(IMDN)and Residual Feature Distillation Network(RFDN).These results highlight the proposed model’s ability to deliver high-quality image reconstruction while offering strong deployment efficiency,making it well-suited for image restoration tasks in resource-limited environments.
文摘1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography, natural resources, environmental sciences, geographic information sciences, remote sensing and cartography. Manuscripts come from different parts of the world.
文摘Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automatically and manually corrected hydrological slope unit division,the Longhua District,Shenzhen City,Guangdong Province,was selected as the study area.A total of 15 influencing factors,namely Fluctuation,slope,slope aspect,curvature,topographic witness index(TWI),stream power index(SPI),topographic roughness index(TRI),annual average rainfall,distance to water system,engineering rock group,distance to fault,land use,normalized difference vegetation index(NDVI),nighttime light,and distance to road,were selected as evaluation indicators.The information volume model(IV)and random points were used to select non-geological disaster units,and then the random forest model(RF)was used to evaluate the susceptibility to geological disasters.The automatic slope unit and the hydrological slope unit were compared and analyzed in the random forest and information volume random forest models.The results show that the area under the curve(AUC)values of the automatic slope unit evaluation results are 0.931 for the IV-RF model and 0.716 for the RF model,which are 0.6%(IV-RF model)and 1.9%(RF model)higher than those for the hydrological slope unit.Based on a comparison of the evaluation methods based on the two types of slope units,the hydrological slope unit evaluation method based on manual correction is highly subjective,is complicated to operate,and has a low evaluation accuracy,whereas the evaluation method based on automatic slope unit division is efficient and accurate,is suitable for large-scale efficient geological disaster evaluation,and can better deal with the problem of geological disaster susceptibility evaluation.
文摘Modern business information systems face significant challenges in managing heterogeneous data sources,integrating disparate systems,and providing real-time decision support in complex enterprise environments.Contemporary enterprises typically operate 200+interconnected systems,with research indicating that 52% of organizations manage three or more enterprise content management systems,creating information silos that reduce operational efficiency by up to 35%.While attention mechanisms have demonstrated remarkable success in natural language processing and computer vision,their systematic application to business information systems remains largely unexplored.This paper presents the theoretical foundation for a Hierarchical Attention-Based Business Information System(HABIS)framework that applies multi-level attention mechanisms to enterprise environments.We provide a comprehensive mathematical formulation of the framework,analyze its computational complexity,and present a proof-of-concept implementation with simulation-based validation that demonstrates a 42% reduction in crosssystem query latency compared to legacy ERP modules and 70% improvement in prediction accuracy over baseline methods.The theoretical framework introduces four hierarchical attention levels:system-level attention for dynamic weighting of business systems,process-level attention for business process prioritization,data-level attention for critical information selection,and temporal attention for time-sensitive pattern recognition.Our complexity analysis demonstrates that the framework achieves O(n log n)computational complexity for attention computation,making it scalable to large enterprise environments including retail supply chains with 200+system-scale deployments.The proof-of-concept implementation validates the theoretical framework’s feasibility withMSE loss of 0.439 and response times of 0.000120 s per query,demonstrating its potential for addressing key challenges in business information systems.This work establishes a foundation for future empirical research and practical implementation of attention-driven enterprise systems.
基金supported by National Natural Science Foundation of China(NSFC)under grant U23A20310.
文摘With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing.
文摘The internal flow fields within a three-dimensional inward-tunning combined inlet are extremely complex,especially during the engine mode transition,where the tunnel changes may impact the flow fields significantly.To develop an efficient flow field reconstruction model for this,we present an Improved Conditional Denoising Diffusion Generative Adversarial Network(ICDDGAN),which integrates Conditional Denoising Diffusion Probabilistic Models(CDDPMs)with Style GAN,and introduce a reconstruction discrimination mechanism and dynamic loss weight learning strategy.We establish the Mach number flow field dataset by numerical simulation at various backpressures for the mode transition process from turbine mode to ejector ramjet mode at Mach number 2.5.The proposed ICDDGAN model,given only sparse parameter information,can rapidly generate high-quality Mach number flow fields without a large number of samples for training.The results show that ICDDGAN is superior to CDDGAN in terms of training convergence and stability.Moreover,the interpolation and extrapolation test results during backpressure conditions show that ICDDGAN can accurately and quickly reconstruct Mach number fields at various tunnel slice shapes,with a Structural Similarity Index Measure(SSIM)of over 0.96 and a Mean-Square Error(MSE)of 0.035%to actual flow fields,reducing time costs by 7-8 orders of magnitude compared to Computational Fluid Dynamics(CFD)calculations.This can provide an efficient means for rapid computation of complex flow fields.
文摘This study attempts to understand the role of ICTs on adoption of climate change adaption options among the Nepalese rice farmers, using data from 773 households from seven districts—3 from Terai region and 4 from hilly region. Individual Farmer’s Awareness Index was developed to categorize the respondent knowledge of climate change adaptation and Ordered Logit Model was used to examine the factors influencing their adaptation options in present of ICTs. The result revealed that 65% farmers perceived knowledge about temperature, rainfall and other relative information from various ICT devices that they pose. Farmers received such information mostly from Radio (71%), TV (69%) and mobile phone (62.5%) and argued these three devices are the most prominent, easy access and practical devices to receive such information. 86% farmers used such devices on the daily basis and 90% and more users opined that the information provided from such devices is in their own language and fully understandable. From ICT devices they pose, 71% of the farmers are receiving climate change information and 61% received agro-related information and the majority of them argued that such available information is very much informative and supportive of their resilience to climate change and use of available adaptation options. From the Farmers Awareness Index, this study found 19.8% farmers are high aware, 65.1% medium aware and 15.1% were less aware of the changing climate and its anomalies. Similarly, result from Ordered Logit Model shows that age (0.45***), gender (0.48**), market center (0.32*), bank access (0.54***), availability of subsidy (1.0***), agro-extension services (0.71**), access to TV (0.67***) and membership to a social network (3.20**) played a significant role in increasing farmers’ awareness of climate change which in turn lead to increased adoption of adaptation options available to the farmers. The findings suggest the need for further improvement on ICT devices and publicity of such ICT devices and proper investment to boost rice farmers’ adaptation to climate change, which will in turn help to improve their livelihoods and well-being.
文摘There is a widespread belief that information and knowledge are vital for rural and agricultural development. Today, generation of new and various information and knowledge sources need new information and communication channels. New information and communication technologies can decrease poverty by promotion rural people access to education, health, government and financial services; overall, they can improve livelihood. The purpose of this study was to identify potentials of new information and communications technologies （ICTs） in agricultural and rural sector. Documentary research and literature review were used as research method. Findings revealed that the most applications for these ICTs in rural and agricultural sector were： E-trade of inputs and outputs, extension and training activities for rural dwellers, advertisement of rural tourism products, knowledge transfer from urban to rural and vice versa, official procedures and geographic information system （GIS） for management of natural resources.
文摘The study investigated constraints of women farmers access to ICTs for agricultural information in Oyo State.A total of 120 respondents were sampled.Data were retrieved using interview schedule and were analysed using descriptive and inferential statistics.Statistics reveal respondents average age,average household size and average monthly income as x=45.8,x=10.6 and x=₦7,800.34 respectively,majority(86.7%)were married,58.3%representing respondents with primary education.Mobile phone(x=0.98)was the most available among the respondents while poor ICTs infrastructure(x=1.55)and difficulty in the utilization of ICTs gadgets(x=1.62)ranked highest as constraints access to ICTs for agricultural information.Significant relationship existed between respondents average monthly income(r=0.492,p=0.000),educational level(χ^(2)=4.726,p=0.021)and the constraints access to ICTs for agricultural information.Scaling up the ICTs infrastructure base around farming clusters and capacity building like training on ICTs to access agricultural information retrieval is advocated for women farmers.
文摘Electronic commerce which denotes the process of electronic transaction via internet has led to a very significant improvement in the level of growth, development, efficiency and productivity of global economies. In order to benefit from the economic opportunities offered by electronic commerce, Nigerian government and business organizations needs to effectively integrate Information and Communication Technologies (ICTs) as the major component of e-commerce campaign initiatives. The discussion in the paper is centered on e-commerce and ICTs and their resultant effect on Nigeria’s economic growth and development. This paper has presented an in-depth discussion of the various types of e-commerce, the major contributions of e-commerce to the economic growth of Nigeria and finally the challenges that impede the growth of e-commerce in Nigeria were identified and the possible recommendations for solutions to those challenges were provided.
基金Under the auspices of National Natural Science Foundation of China(No.42330510)。
文摘With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.
文摘This article analyzes the concentration of production and distribution of information, from the analysis of the news in major international news agencies.The biopolitics is more and more interconnected to social, cultural, economical, and political matters, which led us to see in the contemporary scenario the creation of new forms of social organization which will determine how we interact with each other and how we face the world. Additionally, questions emerge about the usage of the means of communication, particularly those related to Technology of Communication and Information （TICs）. The influence of the media over the social-cultural activities tends to create homogenizations of senses, aiming a planetary visibility in a process that can not only disfigure but destroy many symbolic representations and cultural forms. On the other hand, globalization tends to, instead of minimize the differences in the world, ended up creating new conflicts that, through the usage of new technologies of communication, expresses and articulate themselves.
文摘This paper introduced first a conceptual framework of 'information literacy training of farmers' based on the widely recognized understanding of the term 'information literacy(IL).' It then followed with a discussion based on these three authors' field investigation regarding to Hubei peasants' current information literacy training in such perspectives as information consciousness,information ability and ways and means of information access.It concluded by pointing out some of the more apparent factors that had adverse impacts on the farmers' information literacy training in central China and suggested a few possible remedial measures to guide the course for those who are involved in such undertakings.
文摘There is curiosity and awareness throughout the world regarding the role of Information and Communication technologies. This is felt in each and every section of society. Several studies have confirmed and considered information and communication technology’s significance in the field of education. It has not only affected learners but also to the teachers. This paper explores how ICT-based projects affect teachers’ and students’ attitudes. The data was collected through self-prepared attitude scale. It was distributed among the teachers and students of various schools. Two hundred students and one hundred twenty teachers responded to the questionnaire. Analysis was done through the data collected from the teachers as well as from students. The study’s conclusions demonstrated that while there was no significant variation in the attitudes of teachers utilizing different ICT-based programs, there was a substantial difference in the students’ attitude toward learning with different ICT-based programs.
基金supported by the National Natural Science Foundation of China(62222212).
文摘Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the context of fewshot and zero-shot scenarios remains highly challenging due to the scarcity of training data.Large language models(LLMs),on the other hand,can generalize well to unseen tasks with few-shot demonstrations or even zero-shot instructions and have demonstrated impressive ability for a wide range of natural language understanding or generation tasks.Nevertheless,it is unclear,whether such effectiveness can be replicated in the task of IE,where the target tasks involve specialized schema and quite abstractive entity or relation concepts.In this paper,we first examine the validity of LLMs in executing IE tasks with an established prompting strategy and further propose multiple types of augmented prompting methods,including the structured fundamental prompt(SFP),the structured interactive reasoning prompt(SIRP),and the voting-enabled structured interactive reasoning prompt(VESIRP).The experimental results demonstrate that while directly promotes inferior performance,the proposed augmented prompt methods significantly improve the extraction accuracy,achieving comparable or even better performance(e.g.,zero-shot FewNERD,FewNERD-INTRA)than state-of-theart methods that require large-scale training samples.This study represents a systematic exploration of employing instruction-following LLM for the task of IE.It not only establishes a performance benchmark for this novel paradigm but,more importantly,validates a practical technical pathway through the proposed prompt enhancement method,offering a viable solution for efficient IE in low-resource settings.
