In recent years,with the frequent occurrence of cyber security incidents,people have paid more attention to it.Information security risk assessment is a very important research topic.This paper gives a brief overview ...In recent years,with the frequent occurrence of cyber security incidents,people have paid more attention to it.Information security risk assessment is a very important research topic.This paper gives a brief overview of the theory of cybersecurity risk assessment,focuses on the description of the current mainstream cybersecurity risk assessment methods,classifies and compares the existing methods according to the nature of the methods,and analyses the advantages,disadvantages,and application scope of each method.Finally,the main factors affecting the evaluation results are summarized and refined,and future research hotspots in this field are proposed.Through the empirical analysis of the three factors,the influence of the correlation of the three factors,the uncertainty of the evaluation indexes,and the timeliness of the evaluation on the evaluation results are concluded,which provides a reference for future research on evaluation methods.展开更多
A new method for submarine pipeline routing risk quantitative analysis was provided, and the study was developed from qualitative analysis to quantitative analysis.The characteristics of the potential risk of the subm...A new method for submarine pipeline routing risk quantitative analysis was provided, and the study was developed from qualitative analysis to quantitative analysis.The characteristics of the potential risk of the submarine pipeline system were considered, and grey-mode identification theory was used. The study process was composed of three parts: establishing the indexes system of routing risk quantitative analysis, establishing the model of grey-mode identification for routing risk quantitative analysis, and establishing the standard of mode identification result. It is shown that this model can directly and concisely reflect the hazard degree of the routing through computing example, and prepares the routing selection for the future.展开更多
With the scale and cost of geotechnical engineering projects increasing rapidly over the past few decades,there is a clear need for the careful consideration of calculated risks in design.While risk is typically dealt...With the scale and cost of geotechnical engineering projects increasing rapidly over the past few decades,there is a clear need for the careful consideration of calculated risks in design.While risk is typically dealt with subjectively through the use of conservative design parameters,with the advent of reliability-based methods,this no longer needs to be the case.Instead,a quantitative risk approach can be considered that incorporates uncertainty in ground conditions directly into the design process to determine the variable ground response and support loads.This allows for the optimization of support on the basis of both worker safety and economic risk.This paper presents the application of such an approach to review the design of the initial lining system along a section of the Driskos twin tunnels as part of the Egnatia Odos highway in northern Greece.Along this section of tunnel,weak rock masses were encountered as well as high in situ stress conditions,which led to excessive deformations and failure of the as built temporary support.Monitoring data were used to validate the rock mass parameters selected in this area and a risk approach was used to determine,in hindsight,the most appropriate support category with respect to the cost of installation and expected cost of failure.Different construction sequences were also considered in the context of both convenience and risk cost.展开更多
In order to develop precision or personalized medicine,identifying new quantitative imaging markers and building machine learning models to predict cancer risk and prognosis has been attracting broad research interest...In order to develop precision or personalized medicine,identifying new quantitative imaging markers and building machine learning models to predict cancer risk and prognosis has been attracting broad research interest recently.Most of these research approaches use the similar concepts of the conventional computer-aided detection schemes of medical images,which include steps in detecting and segmenting suspicious regions or tumors,followed by training machine learning models based on the fusion of multiple image features computed from the segmented regions or tumors.However,due to the heterogeneity and boundary fuzziness of the suspicious regions or tumors,segmenting subtle regions is often difficult and unreliable.Additionally,ignoring global and/or background parenchymal tissue characteristics may also be a limitation of the conventional approaches.In our recent studies,we investigated the feasibility of developing new computer-aided schemes implemented with the machine learning models that are trained by global image features to predict cancer risk and prognosis.We trained and tested several models using images obtained from full-field digital mammography,magnetic resonance imaging,and computed tomography of breast,lung,and ovarian cancers.Study results showed that many of these new models yielded higher performance than other approaches used in current clinical practice.Furthermore,the computed global image features also contain complementary information from the features computed from the segmented regions or tumors in predicting cancer prognosis.Therefore,the global image features can be used alone to develop new case-based prediction models or can be added to current tumor-based models to increase their discriminatory power.展开更多
文摘In recent years,with the frequent occurrence of cyber security incidents,people have paid more attention to it.Information security risk assessment is a very important research topic.This paper gives a brief overview of the theory of cybersecurity risk assessment,focuses on the description of the current mainstream cybersecurity risk assessment methods,classifies and compares the existing methods according to the nature of the methods,and analyses the advantages,disadvantages,and application scope of each method.Finally,the main factors affecting the evaluation results are summarized and refined,and future research hotspots in this field are proposed.Through the empirical analysis of the three factors,the influence of the correlation of the three factors,the uncertainty of the evaluation indexes,and the timeliness of the evaluation on the evaluation results are concluded,which provides a reference for future research on evaluation methods.
文摘A new method for submarine pipeline routing risk quantitative analysis was provided, and the study was developed from qualitative analysis to quantitative analysis.The characteristics of the potential risk of the submarine pipeline system were considered, and grey-mode identification theory was used. The study process was composed of three parts: establishing the indexes system of routing risk quantitative analysis, establishing the model of grey-mode identification for routing risk quantitative analysis, and establishing the standard of mode identification result. It is shown that this model can directly and concisely reflect the hazard degree of the routing through computing example, and prepares the routing selection for the future.
文摘With the scale and cost of geotechnical engineering projects increasing rapidly over the past few decades,there is a clear need for the careful consideration of calculated risks in design.While risk is typically dealt with subjectively through the use of conservative design parameters,with the advent of reliability-based methods,this no longer needs to be the case.Instead,a quantitative risk approach can be considered that incorporates uncertainty in ground conditions directly into the design process to determine the variable ground response and support loads.This allows for the optimization of support on the basis of both worker safety and economic risk.This paper presents the application of such an approach to review the design of the initial lining system along a section of the Driskos twin tunnels as part of the Egnatia Odos highway in northern Greece.Along this section of tunnel,weak rock masses were encountered as well as high in situ stress conditions,which led to excessive deformations and failure of the as built temporary support.Monitoring data were used to validate the rock mass parameters selected in this area and a risk approach was used to determine,in hindsight,the most appropriate support category with respect to the cost of installation and expected cost of failure.Different construction sequences were also considered in the context of both convenience and risk cost.
基金The studies mentioned in this paper were supported in part by Grants R01 CA160205 and R01 CA197150 from the National Cancer Institute,National Institutes of Health,USAGrant HR15-016 from Oklahoma Center for the Advancement of Science and Technology,USA.
文摘In order to develop precision or personalized medicine,identifying new quantitative imaging markers and building machine learning models to predict cancer risk and prognosis has been attracting broad research interest recently.Most of these research approaches use the similar concepts of the conventional computer-aided detection schemes of medical images,which include steps in detecting and segmenting suspicious regions or tumors,followed by training machine learning models based on the fusion of multiple image features computed from the segmented regions or tumors.However,due to the heterogeneity and boundary fuzziness of the suspicious regions or tumors,segmenting subtle regions is often difficult and unreliable.Additionally,ignoring global and/or background parenchymal tissue characteristics may also be a limitation of the conventional approaches.In our recent studies,we investigated the feasibility of developing new computer-aided schemes implemented with the machine learning models that are trained by global image features to predict cancer risk and prognosis.We trained and tested several models using images obtained from full-field digital mammography,magnetic resonance imaging,and computed tomography of breast,lung,and ovarian cancers.Study results showed that many of these new models yielded higher performance than other approaches used in current clinical practice.Furthermore,the computed global image features also contain complementary information from the features computed from the segmented regions or tumors in predicting cancer prognosis.Therefore,the global image features can be used alone to develop new case-based prediction models or can be added to current tumor-based models to increase their discriminatory power.