This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends t...This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].展开更多
As global climate change intensifies,the power industry-a major source of carbon emissions-plays a pivotal role in achieving carbon peaking and neutrality goals through its low-carbon transition.Traditional power pla...As global climate change intensifies,the power industry-a major source of carbon emissions-plays a pivotal role in achieving carbon peaking and neutrality goals through its low-carbon transition.Traditional power plants’carbon management systems can no longer meet the demands of high-precision,real-time monitoring.Smart power plants now offer innovative solutions for carbon emission tracking and intelligent analysis by integrating IoT,big data,and AI technologies.Current research predominantly focuses on optimizing individual processes,lacking systematic exploration of comprehensive dynamic monitoring and intelligent decision-making across the entire workflow.To address this gap,we propose a smart carbon emission monitoring and analysis platform for power plants that integrates IoT sensing,multimodal data analytics,and AI-driven decision-making.The platform establishes a multi-source sensor network to collect emissions data throughout the fuel combustion,auxiliary equipment operation,and waste treatment processes.Combining carbon emission factor analysis with machine learning models enables real-time emission calculations and utilizes long short-term memory networks to predict future emission trends.展开更多
The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT...The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT environments to the Adversarial Tactics,Techniques,and Common Knowledge(ATT&CK)framework by MITRE and introduces a lightweight,data-driven scoring model that enables rapid identification and prioritization of attacks.Inspired by the Factor Analysis of Information Risk model,our proposed scoring model integrates four key metrics:Common Vulnerability Scoring System(CVSS)-based severity scoring,Cyber Kill Chain–based difficulty estimation,Deep Neural Networks-driven detection scoring,and frequency analysis based on dataset prevalence.By aggregating these indicators,the model generates comprehensive risk profiles,facilitating actionable prioritization of threats.Robustness and stability of the scoring model are validated through non-parametric correlation analysis using Spearman’s and Kendall’s rank correlation coefficients,demonstrating consistent performance across diverse scenarios.The approach culminates in a prioritized attack ranking that provides actionable guidance for risk mitigation and resource allocation in Edge-IoT/IIoT security operations.By leveraging real-world data to align MITRE ATT&CK techniques with CVSS metrics,the framework offers a standardized and practically applicable solution for consistent threat assessment in operational settings.The proposed lightweight scoring model delivers rapid and reliable results under dynamic cyber conditions,facilitating timely identification of attack scenarios and prioritization of response strategies.Our systematic integration of established taxonomies with data-driven indicators strengthens practical risk management and supports strategic planning in next-generation IoT deployments.Ultimately,this work advances adaptive threat modeling for Edge/IIoT ecosystems and establishes a robust foundation for evidence-based prioritization in emerging cyber-physical infrastructures.展开更多
Inflammatory bowel disease(IBD),encompassing Crohn’s disease and ulcerative colitis,manifests as a chronic,recurrent,and refractory intestinal inflammatory condition significantly impacting patients’quality of life....Inflammatory bowel disease(IBD),encompassing Crohn’s disease and ulcerative colitis,manifests as a chronic,recurrent,and refractory intestinal inflammatory condition significantly impacting patients’quality of life.Despite ongoing research,its etiology and pathogenesis remain incompletely understood.Recent advancements in medical research highlight the critical role of drug combination therapies in managing IBD.This paper employs the strengths,weaknesses,opportunities,and threats framework to evaluate the four strategic elements(strengths,weaknesses,opportunities,and threats)pertaining to combination therapies for IBD.Among the strengths,the paper underscores the efficacy of multi-targeted strategies,the advancement of personalized medicine,and the mitigation of drug resistance.Nonetheless,the analysis identifies significant weaknesses,including the prohibitive cost of treatment,issues with patient compliance,and the necessity for comprehensive long-term safety data.The paper also delineates opportunities to augment therapeutic success through the incorporation of biomarkers,the application of artificial intelligence,and extensive international collaborative efforts.In contrast,the paper does not shy away from addressing the threats,which include the potential for therapeutic resistance and the logistical challenges inherent in global therapy deployment.These initiatives aim to refine future therapeutic practices,fostering safer,more effective,and personalized treatment paradigms for IBD patients.展开更多
The application and development of a wide-area measurement system(WAMS)has enabled many applications and led to several requirements based on dynamic measurement data.Such data are transmitted as big data information ...The application and development of a wide-area measurement system(WAMS)has enabled many applications and led to several requirements based on dynamic measurement data.Such data are transmitted as big data information flow.To ensure effective transmission of wide-frequency electrical information by the communication protocol of a WAMS,this study performs real-time traffic monitoring and analysis of the data network of a power information system,and establishes corresponding network optimization strategies to solve existing transmission problems.This study utilizes the traffic analysis results obtained using the current real-time dynamic monitoring system to design an optimization strategy,covering the optimization in three progressive levels:the underlying communication protocol,source data,and transmission process.Optimization of the system structure and scheduling optimization of data information are validated to be feasible and practical via tests.展开更多
Chlorine, chlorine dioxide, and ozone are widely used as disinfectants in drinking water treatments. However, the combined use of different disinfectants can result in the formation of various organic and inorganic di...Chlorine, chlorine dioxide, and ozone are widely used as disinfectants in drinking water treatments. However, the combined use of different disinfectants can result in the formation of various organic and inorganic disinfection byproducts(DBPs). The toxic interactions, including synergism, addition, and antagonism, among the complex DBPs are still unclear. In this study, we established and verified a real-time cell analysis(RTCA) method for cytotoxicity measurement on Chinese hamster ovary(CHO) cell. Using this convenient and accurate method, we assessed the cytotoxicity of a series of binary combinations consisting of one of the 3 inorganic DBPs(chlorite, chlorate, and bromate) and one of the 32 regulated and emerging organic DBPs. The combination index(CI) of each combination was calculated and evaluated by isobolographic analysis to reflect the toxic interactions. The results confirmed the synergistic effect on cytotoxicity in the binary combinations consisting of chlorite and one of the 5 organic DBPs(2 iodinated DBPs(I-DBPs) and 3 brominated DBPs(Br-DBPs)), chlorate and one of the 4 organic DBPs(3 aromatic DBPs and dibromoacetonitrile), and bromate and one of the 3 organic DBPs(2 I-DBPs and dibromoacetic acid). The possible synergism mechanism of organic DBPs on the inorganic ones may be attributed to the influence of organic DBPs on cell membrane and cell antioxidant system. This study revealed the toxic interactions among organic and inorganic DBPs, and emphasized the latent adverse outcomes in the combined use of different disinfectants.展开更多
In order to optimize the embedded system implementation for Ethernet-based computer numerical control （CNC） system, it is very necessary to establish the performance analysis model and further adopt the codesign met...In order to optimize the embedded system implementation for Ethernet-based computer numerical control （CNC） system, it is very necessary to establish the performance analysis model and further adopt the codesign method from the control, communication and computing perspectives. On the basis of analyzing real-time Ethemet, system architecture, time characteristic parameters of control-loop ere, a performance analysis model for real-time Ethemet-based CNC system was proposed, which is able to include the timing effects caused by the implementation platform in the simulation. The key for establishing the model is accomplished by designing the error analysis module and the controller nodes. Under the restraint of CPU resource and communication bandwidth, the experiment with a case study was conducted, and the results show that if the deadline miss ratio of data packets is 0.2%, then the percentage error is 1.105%. The proposed model can be used at several stages of CNC system development.展开更多
As multimedia data sharing increases,data security in mobile devices and its mechanism can be seen as critical.Biometrics combines the physiological and behavioral qualities of an individual to validate their characte...As multimedia data sharing increases,data security in mobile devices and its mechanism can be seen as critical.Biometrics combines the physiological and behavioral qualities of an individual to validate their character in real-time.Humans incorporate physiological attributes like a fingerprint,face,iris,palm print,finger knuckle print,Deoxyribonucleic Acid(DNA),and behavioral qualities like walk,voice,mark,or keystroke.The main goal of this paper is to design a robust framework for automatic face recognition.Scale Invariant Feature Transform(SIFT)and Speeded-up Robust Features(SURF)are employed for face recognition.Also,we propose a modified Gabor Wavelet Transform for SIFT/SURF(GWT-SIFT/GWT-SURF)to increase the recognition accuracy of human faces.The proposed scheme is composed of three steps.First,the entropy of the image is removed using Discrete Wavelet Transform(DWT).Second,the computational complexity of the SIFT/SURF is reduced.Third,the accuracy is increased for authentication by the proposed GWT-SIFT/GWT-SURF algorithm.A comparative analysis of the proposed scheme is done on real-time Olivetti Research Laboratory(ORL)and Poznan University of Technology(PUT)databases.When compared to the traditional SIFT/SURF methods,we verify that the GWT-SIFT achieves the better accuracy of 99.32%and the better approach is the GWT-SURF as the run time of the GWT-SURF for 100 images is 3.4 seconds when compared to the GWT-SIFT which has a run time of 4.9 seconds for 100 images.展开更多
In this paper, a mathematical model of real-time simulation is given, and the problem of convergence on real-time Runge-Kutta algorithms is analysed. At last a theorem on the relation between the order of compensation...In this paper, a mathematical model of real-time simulation is given, and the problem of convergence on real-time Runge-Kutta algorithms is analysed. At last a theorem on the relation between the order of compensation and the convergent order of real-time algorithm is proved.展开更多
Flood control operation,a non-engineering measure,can efficiently manage flood disasters within a river basin.However,numerous uncertainties exit in the real-time operation of flood control systems,creating risks in d...Flood control operation,a non-engineering measure,can efficiently manage flood disasters within a river basin.However,numerous uncertainties exit in the real-time operation of flood control systems,creating risks in decision-making.As an efficient tool to mitigate these risks,risk management has garnered increasing attention in real-time flood control operation.This communication offers a series of suggestions for future research concerning risk management in real-time flood control operation,including risk assessment,risk diagnosis,and risk control methods.展开更多
Opinion (sentiment) analysis on big data streams from the constantly generated text streams on social media networks to hundreds of millions of online consumer reviews provides many organizations in every field with o...Opinion (sentiment) analysis on big data streams from the constantly generated text streams on social media networks to hundreds of millions of online consumer reviews provides many organizations in every field with opportunities to discover valuable intelligence from the massive user generated text streams. However, the traditional content analysis frameworks are inefficient to handle the unprecedentedly big volume of unstructured text streams and the complexity of text analysis tasks for the real time opinion analysis on the big data streams. In this paper, we propose a parallel real time sentiment analysis system: Social Media Data Stream Sentiment Analysis Service (SMDSSAS) that performs multiple phases of sentiment analysis of social media text streams effectively in real time with two fully analytic opinion mining models to combat the scale of text data streams and the complexity of sentiment analysis processing on unstructured text streams. We propose two aspect based opinion mining models: Deterministic and Probabilistic sentiment models for a real time sentiment analysis on the user given topic related data streams. Experiments on the social media Twitter stream traffic captured during the pre-election weeks of the 2016 Presidential election for real-time analysis of public opinions toward two presidential candidates showed that the proposed system was able to predict correctly Donald Trump as the winner of the 2016 Presidential election. The cross validation results showed that the proposed sentiment models with the real-time streaming components in our proposed framework delivered effectively the analysis of the opinions on two presidential candidates with average 81% accuracy for the Deterministic model and 80% for the Probabilistic model, which are 1% - 22% improvements from the results of the existing literature.展开更多
A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and...A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.展开更多
Real-time electricity price(RTEP)influence factor extraction is essential to forecasting accurate power system electricity prices.At present,new electricity price forecasting models have been studied to improve predic...Real-time electricity price(RTEP)influence factor extraction is essential to forecasting accurate power system electricity prices.At present,new electricity price forecasting models have been studied to improve predictive accuracy,ignoring the extraction and analysis of RTEP influence factors.In this study,a correlation analysis method is proposed based on stochastic matrix theory.Firstly,an augmented matrix is formulated,including RTEP influence factor data and RTEP state data.Secondly,data correlation analysis results are obtained given the statistical characteristics of source data based on stochastic matrix theory.Mean spectral radius(MSR)is used as the measure of correlativity.Finally,the proposed method is evaluated in New England electricity markets and compared with the BP neural network forecasting method.Experimental results show that the extracted index system comprehensively generalizes RTEP influence factors,which play a significant role in improving RTEP forecasting accuracy.展开更多
Today with certainty, the petroleum industry is fostering sanguinely the fields’ development programs for the optimization of reservoir characterization through worth-full appliances of computer analysis techniques. ...Today with certainty, the petroleum industry is fostering sanguinely the fields’ development programs for the optimization of reservoir characterization through worth-full appliances of computer analysis techniques. The time element is of prime importance for optimistic petroleum development projects. Therefore, the frontline of “Real-time Analysis” is added into the applications of computer solving techniques for achieving and sketching up the real-time cost effectiveness in analyzing field development programs. It focuses on the phases of real-time well test data acquisition system, real-time secure access to the well test data either on field or in office and real-time data interpretation unit. This interface will yield the productive results for the field of reservoir’s pressure transient analysis and wells’ systems analysis by following the up-to-date preferred, accurate and effective well test analytical principles with modern real-time computer applications and techniques. It also lays emphasis for the comfort and reliability of data in creating best interpersonal working modes within a reputable and esteemed petroleum development organization.展开更多
A real-time monitoring and 3D visualization analysis system is proposed for dam foundation curtain grouting. Based on the real-time control technology, the optimization method and the set theory, a mathematical model ...A real-time monitoring and 3D visualization analysis system is proposed for dam foundation curtain grouting. Based on the real-time control technology, the optimization method and the set theory, a mathematical model of the system is established. The real-time collection and transmission technology of the grouting data provides a data foundation for the system. The real-time grouting monitoring and dynamic alarming method helps the system control the grouting quality during the grouting process, thus, the abnormalities of grouting, such as jacking and hydraulic uplift, can be effectively controlled. In addition, the 3D grouting visualization analysis technology is proposed to establish the grouting information model(GIM). The GIM provides a platform to visualize and analyze the grouting process and results. The system has been applied to a hydraulic project of China as a case study, and the application results indicate that the real-time grouting monitoring and 3D visualization analysis for the grouting process can help engineers control the grouting quality more efficiently.展开更多
With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This...With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This study aims to explore the development strategies of real-time data analysis and decision-support systems,and analyze their application status and future development trends in various industries.The article first reviews the basic concepts and importance of real-time data analysis and decision-support systems,and then discusses in detail the key technical aspects such as system architecture,data collection and processing,analysis methods,and visualization techniques.展开更多
The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challe...The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.展开更多
The belt and road initiative strategy is proposed based on the stable and sustainable cooperation on economy and development between China and neighboring countries.The development of economy can affect every aspect o...The belt and road initiative strategy is proposed based on the stable and sustainable cooperation on economy and development between China and neighboring countries.The development of economy can affect every aspect of vocational education development.Therefore,vocational education in China must be moved toward internationalization to achieve sustainable development in the face of the implementation of the belt and road initiative strategy.The analysis data obtained through the strengths,weaknesses,opportunities,and threats analysis method on the internationalization of China’s vocational education under the background of the belt and road initiative strategy were the advantages analysis(strengths)of continuous maturity in developing of vocational education,which drives by economic development and the foreign employment and entrepreneurship guidance mechanism;the disadvantages analysis(weaknesses)of lack talent cultivation and weak branding of vocational education;analysis of support opportunities given by national policy;and threats analysis of social culture in the involved countries along the route.To further develop and expand China’s vocational education under the background of the belt and road initiative strategy,some countermeasures were proposed such as improves cultivation or training of talents,to build strong branding of China vocational education,and faces cultural challenges to facilitate the international development of China vocational education.展开更多
Training of preschool teachers in Sichuan Province brings advantages in increasing government support for the preschool education industry.The society attaches an important role to the preschool education industry as ...Training of preschool teachers in Sichuan Province brings advantages in increasing government support for the preschool education industry.The society attaches an important role to the preschool education industry as well as the rapid development of preschool education in Sichuan Province.However,problem exists in large flows of preschool teachers and imbalanced gender ratios.By viewing from the new situation,the comprehensive liberalization of the second-child policy and the development of educational informatization as well as the implementation of the one belt and one road strategy have created great opportunities in training of preschool teachers.At the same time,the increase in external impact of high-quality graduates in the east also poses a great threat to the development of preschool teachers in Sichuan Province.Through the strategic combination of strengths,weaknesses,opportunities,and threats analysis,the paper explores effective countermeasure ways to improve the quality of training of the preschool teachers in Sichuan Province and the construction of an excellent team of preschool teachers in Sichuan Province.展开更多
Advanced intelligent or ＂smart＂ meters are being deployed in Asia. A result of deployment of smart meters, with associated equipment, is the electric power industry faced with new and changing threats, vulnerabiliti...Advanced intelligent or ＂smart＂ meters are being deployed in Asia. A result of deployment of smart meters, with associated equipment, is the electric power industry faced with new and changing threats, vulnerabilities and re-evaluate traditional approaches to cyber security. Protection against emerging cyber-security threats targeting smart meter infrastructures will increase risk to both the utility and customer if not addressed within initial rollouts. This paper will discuss the issues in SMI （smart meter infrastructures） deployments that pertain to cyber security. It will cover topics such as the threats to operations, infrastructure, network and people and organization and their associated risks. SMI deployments include not only the smart meter, but also the interfaces for home energy management systems as well as communication interfaces back to the utility. Utilities must recognize and anticipate the new threat landscape that can attack and compromise the meter and the associated field network collectors. They must also include threats to the WAN （wide-area-network） backhaul networks, smart meter headends, MDMS （meter data management systems） and their interfaces to CIS （customer information systems） and billing and OMS （outage management systems）. Lessons learned from SMI implementations from North America, Europe and recently, Japan, will be discussed. How white-box and black-box testing techniques are applied to determine the threat impact to the SMI. Finally, organizational change risk will be discussed and how utilities have responded to re-organizing and developing a security governance structure for the SMI and other smart grid applications.展开更多
文摘This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].
文摘As global climate change intensifies,the power industry-a major source of carbon emissions-plays a pivotal role in achieving carbon peaking and neutrality goals through its low-carbon transition.Traditional power plants’carbon management systems can no longer meet the demands of high-precision,real-time monitoring.Smart power plants now offer innovative solutions for carbon emission tracking and intelligent analysis by integrating IoT,big data,and AI technologies.Current research predominantly focuses on optimizing individual processes,lacking systematic exploration of comprehensive dynamic monitoring and intelligent decision-making across the entire workflow.To address this gap,we propose a smart carbon emission monitoring and analysis platform for power plants that integrates IoT sensing,multimodal data analytics,and AI-driven decision-making.The platform establishes a multi-source sensor network to collect emissions data throughout the fuel combustion,auxiliary equipment operation,and waste treatment processes.Combining carbon emission factor analysis with machine learning models enables real-time emission calculations and utilizes long short-term memory networks to predict future emission trends.
基金supported by the“Regional Innovation System&Education(RISE)”through the Seoul RISE Center,funded by the Ministry of Education(MOE)and the Seoul Metropolitan Government(2025-RISE-01-018-05)supported by Quad Miners Corp。
文摘The dynamic,heterogeneous nature of Edge computing in the Internet of Things(Edge-IoT)and Industrial IoT(IIoT)networks brings unique and evolving cybersecurity challenges.This study maps cyber threats in Edge-IoT/IIoT environments to the Adversarial Tactics,Techniques,and Common Knowledge(ATT&CK)framework by MITRE and introduces a lightweight,data-driven scoring model that enables rapid identification and prioritization of attacks.Inspired by the Factor Analysis of Information Risk model,our proposed scoring model integrates four key metrics:Common Vulnerability Scoring System(CVSS)-based severity scoring,Cyber Kill Chain–based difficulty estimation,Deep Neural Networks-driven detection scoring,and frequency analysis based on dataset prevalence.By aggregating these indicators,the model generates comprehensive risk profiles,facilitating actionable prioritization of threats.Robustness and stability of the scoring model are validated through non-parametric correlation analysis using Spearman’s and Kendall’s rank correlation coefficients,demonstrating consistent performance across diverse scenarios.The approach culminates in a prioritized attack ranking that provides actionable guidance for risk mitigation and resource allocation in Edge-IoT/IIoT security operations.By leveraging real-world data to align MITRE ATT&CK techniques with CVSS metrics,the framework offers a standardized and practically applicable solution for consistent threat assessment in operational settings.The proposed lightweight scoring model delivers rapid and reliable results under dynamic cyber conditions,facilitating timely identification of attack scenarios and prioritization of response strategies.Our systematic integration of established taxonomies with data-driven indicators strengthens practical risk management and supports strategic planning in next-generation IoT deployments.Ultimately,this work advances adaptive threat modeling for Edge/IIoT ecosystems and establishes a robust foundation for evidence-based prioritization in emerging cyber-physical infrastructures.
文摘Inflammatory bowel disease(IBD),encompassing Crohn’s disease and ulcerative colitis,manifests as a chronic,recurrent,and refractory intestinal inflammatory condition significantly impacting patients’quality of life.Despite ongoing research,its etiology and pathogenesis remain incompletely understood.Recent advancements in medical research highlight the critical role of drug combination therapies in managing IBD.This paper employs the strengths,weaknesses,opportunities,and threats framework to evaluate the four strategic elements(strengths,weaknesses,opportunities,and threats)pertaining to combination therapies for IBD.Among the strengths,the paper underscores the efficacy of multi-targeted strategies,the advancement of personalized medicine,and the mitigation of drug resistance.Nonetheless,the analysis identifies significant weaknesses,including the prohibitive cost of treatment,issues with patient compliance,and the necessity for comprehensive long-term safety data.The paper also delineates opportunities to augment therapeutic success through the incorporation of biomarkers,the application of artificial intelligence,and extensive international collaborative efforts.In contrast,the paper does not shy away from addressing the threats,which include the potential for therapeutic resistance and the logistical challenges inherent in global therapy deployment.These initiatives aim to refine future therapeutic practices,fostering safer,more effective,and personalized treatment paradigms for IBD patients.
文摘The application and development of a wide-area measurement system(WAMS)has enabled many applications and led to several requirements based on dynamic measurement data.Such data are transmitted as big data information flow.To ensure effective transmission of wide-frequency electrical information by the communication protocol of a WAMS,this study performs real-time traffic monitoring and analysis of the data network of a power information system,and establishes corresponding network optimization strategies to solve existing transmission problems.This study utilizes the traffic analysis results obtained using the current real-time dynamic monitoring system to design an optimization strategy,covering the optimization in three progressive levels:the underlying communication protocol,source data,and transmission process.Optimization of the system structure and scheduling optimization of data information are validated to be feasible and practical via tests.
基金supported by the National Natural Science Foundation of China (No. 21876210)。
文摘Chlorine, chlorine dioxide, and ozone are widely used as disinfectants in drinking water treatments. However, the combined use of different disinfectants can result in the formation of various organic and inorganic disinfection byproducts(DBPs). The toxic interactions, including synergism, addition, and antagonism, among the complex DBPs are still unclear. In this study, we established and verified a real-time cell analysis(RTCA) method for cytotoxicity measurement on Chinese hamster ovary(CHO) cell. Using this convenient and accurate method, we assessed the cytotoxicity of a series of binary combinations consisting of one of the 3 inorganic DBPs(chlorite, chlorate, and bromate) and one of the 32 regulated and emerging organic DBPs. The combination index(CI) of each combination was calculated and evaluated by isobolographic analysis to reflect the toxic interactions. The results confirmed the synergistic effect on cytotoxicity in the binary combinations consisting of chlorite and one of the 5 organic DBPs(2 iodinated DBPs(I-DBPs) and 3 brominated DBPs(Br-DBPs)), chlorate and one of the 4 organic DBPs(3 aromatic DBPs and dibromoacetonitrile), and bromate and one of the 3 organic DBPs(2 I-DBPs and dibromoacetic acid). The possible synergism mechanism of organic DBPs on the inorganic ones may be attributed to the influence of organic DBPs on cell membrane and cell antioxidant system. This study revealed the toxic interactions among organic and inorganic DBPs, and emphasized the latent adverse outcomes in the combined use of different disinfectants.
基金Projects(50875090,50905063) supported by the National Natural Science Foundation of ChinaProject(2009AA04Z111) supported by the National High Technology Research and Development Program of China+2 种基金Project(20090460769) supported by China Postdoctoral Science FoundationProject(2011ZM0070) supported by the Fundamental Research Funds for the Central Universities in ChinaProject(S2011010001155) supported by the Natural Science Foundation of Guangdong Province,China
文摘In order to optimize the embedded system implementation for Ethernet-based computer numerical control （CNC） system, it is very necessary to establish the performance analysis model and further adopt the codesign method from the control, communication and computing perspectives. On the basis of analyzing real-time Ethemet, system architecture, time characteristic parameters of control-loop ere, a performance analysis model for real-time Ethemet-based CNC system was proposed, which is able to include the timing effects caused by the implementation platform in the simulation. The key for establishing the model is accomplished by designing the error analysis module and the controller nodes. Under the restraint of CPU resource and communication bandwidth, the experiment with a case study was conducted, and the results show that if the deadline miss ratio of data packets is 0.2%, then the percentage error is 1.105%. The proposed model can be used at several stages of CNC system development.
文摘As multimedia data sharing increases,data security in mobile devices and its mechanism can be seen as critical.Biometrics combines the physiological and behavioral qualities of an individual to validate their character in real-time.Humans incorporate physiological attributes like a fingerprint,face,iris,palm print,finger knuckle print,Deoxyribonucleic Acid(DNA),and behavioral qualities like walk,voice,mark,or keystroke.The main goal of this paper is to design a robust framework for automatic face recognition.Scale Invariant Feature Transform(SIFT)and Speeded-up Robust Features(SURF)are employed for face recognition.Also,we propose a modified Gabor Wavelet Transform for SIFT/SURF(GWT-SIFT/GWT-SURF)to increase the recognition accuracy of human faces.The proposed scheme is composed of three steps.First,the entropy of the image is removed using Discrete Wavelet Transform(DWT).Second,the computational complexity of the SIFT/SURF is reduced.Third,the accuracy is increased for authentication by the proposed GWT-SIFT/GWT-SURF algorithm.A comparative analysis of the proposed scheme is done on real-time Olivetti Research Laboratory(ORL)and Poznan University of Technology(PUT)databases.When compared to the traditional SIFT/SURF methods,we verify that the GWT-SIFT achieves the better accuracy of 99.32%and the better approach is the GWT-SURF as the run time of the GWT-SURF for 100 images is 3.4 seconds when compared to the GWT-SIFT which has a run time of 4.9 seconds for 100 images.
文摘In this paper, a mathematical model of real-time simulation is given, and the problem of convergence on real-time Runge-Kutta algorithms is analysed. At last a theorem on the relation between the order of compensation and the convergent order of real-time algorithm is proved.
基金supported by the National Natural Science Foundation of China(Grant No.51909062)the National Key R&D Program(Grant No.2022YFC3202801).
文摘Flood control operation,a non-engineering measure,can efficiently manage flood disasters within a river basin.However,numerous uncertainties exit in the real-time operation of flood control systems,creating risks in decision-making.As an efficient tool to mitigate these risks,risk management has garnered increasing attention in real-time flood control operation.This communication offers a series of suggestions for future research concerning risk management in real-time flood control operation,including risk assessment,risk diagnosis,and risk control methods.
文摘Opinion (sentiment) analysis on big data streams from the constantly generated text streams on social media networks to hundreds of millions of online consumer reviews provides many organizations in every field with opportunities to discover valuable intelligence from the massive user generated text streams. However, the traditional content analysis frameworks are inefficient to handle the unprecedentedly big volume of unstructured text streams and the complexity of text analysis tasks for the real time opinion analysis on the big data streams. In this paper, we propose a parallel real time sentiment analysis system: Social Media Data Stream Sentiment Analysis Service (SMDSSAS) that performs multiple phases of sentiment analysis of social media text streams effectively in real time with two fully analytic opinion mining models to combat the scale of text data streams and the complexity of sentiment analysis processing on unstructured text streams. We propose two aspect based opinion mining models: Deterministic and Probabilistic sentiment models for a real time sentiment analysis on the user given topic related data streams. Experiments on the social media Twitter stream traffic captured during the pre-election weeks of the 2016 Presidential election for real-time analysis of public opinions toward two presidential candidates showed that the proposed system was able to predict correctly Donald Trump as the winner of the 2016 Presidential election. The cross validation results showed that the proposed sentiment models with the real-time streaming components in our proposed framework delivered effectively the analysis of the opinions on two presidential candidates with average 81% accuracy for the Deterministic model and 80% for the Probabilistic model, which are 1% - 22% improvements from the results of the existing literature.
基金Project(51175159)supported by the National Natural Science Foundation of ChinaProject(2013WK3024)supported by the Science andTechnology Planning Program of Hunan Province,ChinaProject(CX2013B146)supported by the Hunan Provincial InnovationFoundation for Postgraduate,China
文摘A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.
基金National Natural Science Foundation of China(No.61701104)the “13th Five Year Plan” Research Foundation of Jilin Provincial Department of Education,China(No.JJKH2017018KJ)
文摘Real-time electricity price(RTEP)influence factor extraction is essential to forecasting accurate power system electricity prices.At present,new electricity price forecasting models have been studied to improve predictive accuracy,ignoring the extraction and analysis of RTEP influence factors.In this study,a correlation analysis method is proposed based on stochastic matrix theory.Firstly,an augmented matrix is formulated,including RTEP influence factor data and RTEP state data.Secondly,data correlation analysis results are obtained given the statistical characteristics of source data based on stochastic matrix theory.Mean spectral radius(MSR)is used as the measure of correlativity.Finally,the proposed method is evaluated in New England electricity markets and compared with the BP neural network forecasting method.Experimental results show that the extracted index system comprehensively generalizes RTEP influence factors,which play a significant role in improving RTEP forecasting accuracy.
文摘Today with certainty, the petroleum industry is fostering sanguinely the fields’ development programs for the optimization of reservoir characterization through worth-full appliances of computer analysis techniques. The time element is of prime importance for optimistic petroleum development projects. Therefore, the frontline of “Real-time Analysis” is added into the applications of computer solving techniques for achieving and sketching up the real-time cost effectiveness in analyzing field development programs. It focuses on the phases of real-time well test data acquisition system, real-time secure access to the well test data either on field or in office and real-time data interpretation unit. This interface will yield the productive results for the field of reservoir’s pressure transient analysis and wells’ systems analysis by following the up-to-date preferred, accurate and effective well test analytical principles with modern real-time computer applications and techniques. It also lays emphasis for the comfort and reliability of data in creating best interpersonal working modes within a reputable and esteemed petroleum development organization.
基金Supported by the Innovative Research Groups of the National Natural Science Foundation of China(No.51321065)the National Natural Science Foundation of China(No.51339003 and No.51439005)
文摘A real-time monitoring and 3D visualization analysis system is proposed for dam foundation curtain grouting. Based on the real-time control technology, the optimization method and the set theory, a mathematical model of the system is established. The real-time collection and transmission technology of the grouting data provides a data foundation for the system. The real-time grouting monitoring and dynamic alarming method helps the system control the grouting quality during the grouting process, thus, the abnormalities of grouting, such as jacking and hydraulic uplift, can be effectively controlled. In addition, the 3D grouting visualization analysis technology is proposed to establish the grouting information model(GIM). The GIM provides a platform to visualize and analyze the grouting process and results. The system has been applied to a hydraulic project of China as a case study, and the application results indicate that the real-time grouting monitoring and 3D visualization analysis for the grouting process can help engineers control the grouting quality more efficiently.
文摘With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This study aims to explore the development strategies of real-time data analysis and decision-support systems,and analyze their application status and future development trends in various industries.The article first reviews the basic concepts and importance of real-time data analysis and decision-support systems,and then discusses in detail the key technical aspects such as system architecture,data collection and processing,analysis methods,and visualization techniques.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00242528,50%)supported by a grant from the Korea Electric Power Corporation(R24XO01-4,50%)for basic research and development projects starting in 2024.
文摘The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.
文摘The belt and road initiative strategy is proposed based on the stable and sustainable cooperation on economy and development between China and neighboring countries.The development of economy can affect every aspect of vocational education development.Therefore,vocational education in China must be moved toward internationalization to achieve sustainable development in the face of the implementation of the belt and road initiative strategy.The analysis data obtained through the strengths,weaknesses,opportunities,and threats analysis method on the internationalization of China’s vocational education under the background of the belt and road initiative strategy were the advantages analysis(strengths)of continuous maturity in developing of vocational education,which drives by economic development and the foreign employment and entrepreneurship guidance mechanism;the disadvantages analysis(weaknesses)of lack talent cultivation and weak branding of vocational education;analysis of support opportunities given by national policy;and threats analysis of social culture in the involved countries along the route.To further develop and expand China’s vocational education under the background of the belt and road initiative strategy,some countermeasures were proposed such as improves cultivation or training of talents,to build strong branding of China vocational education,and faces cultural challenges to facilitate the international development of China vocational education.
文摘Training of preschool teachers in Sichuan Province brings advantages in increasing government support for the preschool education industry.The society attaches an important role to the preschool education industry as well as the rapid development of preschool education in Sichuan Province.However,problem exists in large flows of preschool teachers and imbalanced gender ratios.By viewing from the new situation,the comprehensive liberalization of the second-child policy and the development of educational informatization as well as the implementation of the one belt and one road strategy have created great opportunities in training of preschool teachers.At the same time,the increase in external impact of high-quality graduates in the east also poses a great threat to the development of preschool teachers in Sichuan Province.Through the strategic combination of strengths,weaknesses,opportunities,and threats analysis,the paper explores effective countermeasure ways to improve the quality of training of the preschool teachers in Sichuan Province and the construction of an excellent team of preschool teachers in Sichuan Province.
文摘Advanced intelligent or ＂smart＂ meters are being deployed in Asia. A result of deployment of smart meters, with associated equipment, is the electric power industry faced with new and changing threats, vulnerabilities and re-evaluate traditional approaches to cyber security. Protection against emerging cyber-security threats targeting smart meter infrastructures will increase risk to both the utility and customer if not addressed within initial rollouts. This paper will discuss the issues in SMI （smart meter infrastructures） deployments that pertain to cyber security. It will cover topics such as the threats to operations, infrastructure, network and people and organization and their associated risks. SMI deployments include not only the smart meter, but also the interfaces for home energy management systems as well as communication interfaces back to the utility. Utilities must recognize and anticipate the new threat landscape that can attack and compromise the meter and the associated field network collectors. They must also include threats to the WAN （wide-area-network） backhaul networks, smart meter headends, MDMS （meter data management systems） and their interfaces to CIS （customer information systems） and billing and OMS （outage management systems）. Lessons learned from SMI implementations from North America, Europe and recently, Japan, will be discussed. How white-box and black-box testing techniques are applied to determine the threat impact to the SMI. Finally, organizational change risk will be discussed and how utilities have responded to re-organizing and developing a security governance structure for the SMI and other smart grid applications.
