Cyberattacks are difficult to prevent because the targeted companies and organizations are often relying on new and fundamentally insecure cloudbased technologies,such as the Internet of Things.With increasing industr...Cyberattacks are difficult to prevent because the targeted companies and organizations are often relying on new and fundamentally insecure cloudbased technologies,such as the Internet of Things.With increasing industry adoption and migration of traditional computing services to the cloud,one of the main challenges in cybersecurity is to provide mechanisms to secure these technologies.This work proposes a Data Security Framework for cloud computing services(CCS)that evaluates and improves CCS data security from a software engineering perspective by evaluating the levels of security within the cloud computing paradigm using engineering methods and techniques applied to CCS.This framework is developed by means of a methodology based on a heuristic theory that incorporates knowledge generated by existing works as well as the experience of their implementation.The paper presents the design details of the framework,which consists of three stages:identification of data security requirements,management of data security risks and evaluation of data security performance in CCS.展开更多
This research uses our previously-developed smartphone camera-based heart rate change analysis system to survey the correlation between weather patterns and the autonomic nervous activity across a big data set of appr...This research uses our previously-developed smartphone camera-based heart rate change analysis system to survey the correlation between weather patterns and the autonomic nervous activity across a big data set of approximately 200,000 entries. The results showed a trend in which a significant decrease was seen in sympathetic nervous activity in both males and females—the higher the temperature. In addition, a significant increase was seen in the sympathetic nervous system in both males and females—the higher the atmospheric pressure. Lastly, a significant decrease was seen in the sympathetic nervous system in both males and females—the more precipitation there was. These results accord with prior research and with human biological phenomena, and we were able to use a data set of approximately 200,000 entries to statistically demonstrate our hypothesis. We believe this represents a valuable set of reference data for use in the health care.展开更多
This research uses a large amount of autonomic nervous system data (approximately 100,000 entries) to investigate the relationship between human autonomic nervous activity and behaviors, daily and regional changes. Da...This research uses a large amount of autonomic nervous system data (approximately 100,000 entries) to investigate the relationship between human autonomic nervous activity and behaviors, daily and regional changes. Data were measured via a heart rate variability analysis system that utilizes the camera of smartphones. This system was developed by the authors during previous research. The relations between autonomic nervous system and behaviors, total power and sympathetic nervous activity were found to rise after waking, while during leisure time, the total power rises and sympathetic nervous activity is inhibited. Concerning the relationship between autonomic nervous system and day of the week, it was found that total power decreases from the middle through the latter part of the week (namely, Wednesday, Thursday, and Friday), while it rises on Saturday, while the sympathetic nervous activity is suppressed on Saturday. Regarding the relationship between autonomic nervous system and region, it was found that total power is lower in the Kanto region of Japan than in others. This study also shows statistical proof (using a large amount of measurement data) to ideas held by the public for years. Thus, the data can be considered meaningful to the society, and the authors hope that it helps to improve work-life balance.展开更多
Based on the arrangement of the across-fault measurement data along the northern edge of the Qinghai-Xizang block,we divide the deformation into different types and probe the nature of various fault movements based on...Based on the arrangement of the across-fault measurement data along the northern edge of the Qinghai-Xizang block,we divide the deformation into different types and probe the nature of various fault movements based on these types.The recent situation of tectonic movement of main structural belts and seismicity in this area are expounded.From the above,it is concluded that across-fault measurement can reflect not only the conditions of fault movement nearby but also the change of regional stress fields; not only is this a method to obtain regional seismogenic information and to conduct short-term prediction but it is also involved with large scale space-time prediction of moderate and strong earthquakes on the basis of the macro characteristics of fractures.展开更多
To investigate the influence of real leading-edge manufacturing error on aerodynamic performance of high subsonic compressor blades,a family of leading-edge manufacturing error data were obtained from measured compres...To investigate the influence of real leading-edge manufacturing error on aerodynamic performance of high subsonic compressor blades,a family of leading-edge manufacturing error data were obtained from measured compressor cascades.Considering the limited samples,the leadingedge angle and leading-edge radius distribution forms were evaluated by Shapiro-Wilk test and quantile–quantile plot.Their statistical characteristics provided can be introduced to later related researches.The parameterization design method B-spline and Bezier are adopted to create geometry models with manufacturing error based on leading-edge angle and leading-edge radius.The influence of real manufacturing error is quantified and analyzed by self-developed non-intrusive polynomial chaos and Sobol’indices.The mechanism of leading-edge manufacturing error on aerodynamic performance is discussed.The results show that the total pressure loss coefficient is sensitive to the leading-edge manufacturing error compared with the static pressure ratio,especially at high incidence.Specifically,manufacturing error of the leading edge will influence the local flow acceleration and subsequently cause fluctuation of the downstream flow.The aerodynamic performance is sensitive to the manufacturing error of leading-edge radius at the design and negative incidences,while it is sensitive to the manufacturing error of leading-edge angle under the operation conditions with high incidences.展开更多
The state of charge(SOC)estimation of lithium-ion battery is an important function in the battery management system(BMS)of electric vehicles.The long short term memory(LSTM)model can be employed for SOC estimation,whi...The state of charge(SOC)estimation of lithium-ion battery is an important function in the battery management system(BMS)of electric vehicles.The long short term memory(LSTM)model can be employed for SOC estimation,which is capable of estimating the future changing states of a nonlinear system.Since the BMS usually works under complicated operating conditions,i.e the real measurement data used for model training may be corrupted by non-Gaussian noise,and thus the performance of the original LSTM with the mean square error(MSE)loss may deteriorate.Therefore,a novel LSTM with mixture kernel mean p-power error(MKMPE)loss,called MKMPE-LSTM,is developed by using the MKMPE loss to replace the MSE as the learning criterion in LSTM framework,which can achieve robust SOC estimation under the measurement data contaminated with non-Gaussian noises(or outliers)because of the MKMPE containing the p-order moments of the error distribution.In addition,a meta-heuristic algorithm,called heap-based-optimizer(HBO),is employed to optimize the hyper-parameters(mainly including learning rate,number of hidden layer neuron and value of p in MKMPE)of the proposed MKMPE-LSTM model to further improve its flexibility and generalization performance,and a novel hybrid model(HBO-MKMPE-LSTM)is established for SOC estimation under non-Gaussian noise cases.Finally,several tests are performed under various cases through a benchmark to evaluate the performance of the proposed HBO-MKMPE-LSTM model,and the results demonstrate that the proposed hybrid method can provide a good robustness and accuracy under different non-Gaussian measurement noises,and the SOC estimation results in terms of mean square error(MSE),root MSE(RMSE),mean absolute relative error(MARE),and determination coefficient R2are less than 0.05%,3%,3%,and above 99.8%at 25℃,respectively.展开更多
The main function of Internet of Things is to collect and transmit data.At present,the data transmission in Internet of Things lacks effective trust attestation mechanism and trust traceability mechanism of data sourc...The main function of Internet of Things is to collect and transmit data.At present,the data transmission in Internet of Things lacks effective trust attestation mechanism and trust traceability mechanism of data source.To solve the above problems,a trust attestation mechanism for sensing layer nodes is presented.First a trusted group is established,and the node which is going to join the group needs to attest its identity and key attributes to the higher level node.Then the dynamic trust measurement value of the node can be obtained by measuring the node data transmission behavior.Finally the node encapsulates the key attributes and trust measurement value to use short message group signature to attest its trust to the challenger.This mechanism can measure the data sending and receiving behaviors of sensing nodes and track the data source,and it does not expose the privacy information of nodes and the sensing nodes can be traced effectively.The trust measurement for sensing nodes and verification is applicable to Internet of Things and the simulation experiment shows the trust attestation mechanism is flexible,practical and efficient.Besides,it can accurately and quickly identify the malicious nodes at the same time.The impact on the system performance is negligible.展开更多
In this paper, the measurement method of calorimetric power for an electron cyclotron resonance heating（ECRH） system for EAST is presented. This method requires measurements of the water flow through the cooling cir...In this paper, the measurement method of calorimetric power for an electron cyclotron resonance heating（ECRH） system for EAST is presented. This method requires measurements of the water flow through the cooling circuits and the input and output water temperatures in each cooling circuit. Usually, the inlet water temperature stability is controlled to obtain more accurate results.The influence of the inlet water temperature change on the measurement results is analyzed for the first time in this paper. Also, a novel temperature calibration method is proposed. This kind of calibration method is accurate and effective, and can be easily implemented.展开更多
The exponential advancement witnessed in 5G communication and quantum computing has presented unparalleled prospects for safeguarding sensitive data within healthcare infrastructures.This study proposes a novel framew...The exponential advancement witnessed in 5G communication and quantum computing has presented unparalleled prospects for safeguarding sensitive data within healthcare infrastructures.This study proposes a novel framework for healthcare applications that integrates 5G communication,quantum computing,and sensitive data measurement to address the challenges of measuring and securely transmitting sensitive medical data.The framework includes a quantum-inspired method for quantifying data sensitivity based on quantum superposition and entanglement principles and a delegated quantum computing protocol for secure data transmission in 5G-enabled healthcare systems,ensuring user anonymity and data confidentiality.The framework is applied to innovative healthcare scenarios,such as secure 5G voice communication,data transmission,and short message services.Experimental results demonstrate the framework’s high accuracy in sensitive data measurement and enhanced security for data transmission in 5G healthcare systems,surpassing existing approaches.展开更多
Smart grids are increasingly dependent on data with the rapid development of communication and measurement.As one of the important data sources of smart grids,phasor measurement unit(PMU)is facing the high risk from a...Smart grids are increasingly dependent on data with the rapid development of communication and measurement.As one of the important data sources of smart grids,phasor measurement unit(PMU)is facing the high risk from attacks.Compared with cyber attacks,global position system(GPS)spoofing attacks(GSAs)are easier to implement because they can be exploited by portable devices,without the need to access the physical system.Therefore,this paper proposes a novel method for pattern recognition of GSA and an additional function of the proposed method is the data correction to the phase angle difference(PAD)deviation.Specifically,this paper analyzes the effect of GSA on PMU measurement and gives two common patterns of GSA,i.e.,the step attack and the ramp attack.Then,the method of estimating the PAD deviation across a transmission line introduced by GSA is proposed,which does not require the line parameters.After obtaining the estimated PAD deviations,the pattern of GSA can be recognized by hypothesis tests and correlation coefficients according to the statistical characteristics of the estimated PAD deviations.Finally,with the case studies,the effectiveness of the proposed method is demonstrated,and the success rate of the pattern recognition and the online performance of the proposed method are analyzed.展开更多
In repeated measurement data, the variables are not independent, and a certain auto- correlation typically exists between different levels of repeated measurement factors. The random error is composed of at least two ...In repeated measurement data, the variables are not independent, and a certain auto- correlation typically exists between different levels of repeated measurement factors. The random error is composed of at least two parts, i.e. the individual random effect and the intra-individual multi-repeated measurement effect. Traditional statistical analysis methods （such as the t-test and the one-way analysis of variance） are not applicable. The linear mixed model has been widely applied for the analysis and design of repeated measurement data. This paper focuses on medical examples and describes the selection of a covariance structure for the linear mixed model of repeated measurement in the modeling of different variance-eovariance structures. By selecting different covariance structures, we can perform the parameter estimation and statistical test for the fixed effect of repeated measurement data, the parameters of random effects, and the covari- ance matrix. The results are analyzed and compared to provide a reference for applying the linear mixed model of repeated measurement to medical research.展开更多
In this paper, recent measurements of tip vortex flow with and without cavitation carried out in Cavitation Mechanism Tunnel of China Ship Scientific Research Center（CSSRC） are presented. The elliptic hydrofoil with...In this paper, recent measurements of tip vortex flow with and without cavitation carried out in Cavitation Mechanism Tunnel of China Ship Scientific Research Center（CSSRC） are presented. The elliptic hydrofoil with section NACA 662-415 was adopted as test model. High-speed video（HSV） camera was used to visualize the trajectory of tip vortex core and the form of tip vortex cavitation（TVC） in different cavitation situations. Laser Doppler velocimetry（LDV） was employed to measure the tip vortex flow field in some typical sections along the vortex trajectory with the case of cavitation free. Stereo particle image velocimetry（SPIV） system was used to measure the velocity and vorticity distributions with and without cavitation. Series measurement results such as velocity and vorticity distributions, the trajectory of tip vortex core, the vortex core radius, cavity size and cavitation inception number were obtained. The results demonstrated that the minimum pressure coefficient in the vortex core obtained by flow field measurement was quite coincident with the tip vortex cavitation inception number obtained under the condition of high incoming velocity and low air content. And TVC would decrease the vortex strength comparing with the case without cavitation.展开更多
文摘Cyberattacks are difficult to prevent because the targeted companies and organizations are often relying on new and fundamentally insecure cloudbased technologies,such as the Internet of Things.With increasing industry adoption and migration of traditional computing services to the cloud,one of the main challenges in cybersecurity is to provide mechanisms to secure these technologies.This work proposes a Data Security Framework for cloud computing services(CCS)that evaluates and improves CCS data security from a software engineering perspective by evaluating the levels of security within the cloud computing paradigm using engineering methods and techniques applied to CCS.This framework is developed by means of a methodology based on a heuristic theory that incorporates knowledge generated by existing works as well as the experience of their implementation.The paper presents the design details of the framework,which consists of three stages:identification of data security requirements,management of data security risks and evaluation of data security performance in CCS.
文摘This research uses our previously-developed smartphone camera-based heart rate change analysis system to survey the correlation between weather patterns and the autonomic nervous activity across a big data set of approximately 200,000 entries. The results showed a trend in which a significant decrease was seen in sympathetic nervous activity in both males and females—the higher the temperature. In addition, a significant increase was seen in the sympathetic nervous system in both males and females—the higher the atmospheric pressure. Lastly, a significant decrease was seen in the sympathetic nervous system in both males and females—the more precipitation there was. These results accord with prior research and with human biological phenomena, and we were able to use a data set of approximately 200,000 entries to statistically demonstrate our hypothesis. We believe this represents a valuable set of reference data for use in the health care.
文摘This research uses a large amount of autonomic nervous system data (approximately 100,000 entries) to investigate the relationship between human autonomic nervous activity and behaviors, daily and regional changes. Data were measured via a heart rate variability analysis system that utilizes the camera of smartphones. This system was developed by the authors during previous research. The relations between autonomic nervous system and behaviors, total power and sympathetic nervous activity were found to rise after waking, while during leisure time, the total power rises and sympathetic nervous activity is inhibited. Concerning the relationship between autonomic nervous system and day of the week, it was found that total power decreases from the middle through the latter part of the week (namely, Wednesday, Thursday, and Friday), while it rises on Saturday, while the sympathetic nervous activity is suppressed on Saturday. Regarding the relationship between autonomic nervous system and region, it was found that total power is lower in the Kanto region of Japan than in others. This study also shows statistical proof (using a large amount of measurement data) to ideas held by the public for years. Thus, the data can be considered meaningful to the society, and the authors hope that it helps to improve work-life balance.
文摘Based on the arrangement of the across-fault measurement data along the northern edge of the Qinghai-Xizang block,we divide the deformation into different types and probe the nature of various fault movements based on these types.The recent situation of tectonic movement of main structural belts and seismicity in this area are expounded.From the above,it is concluded that across-fault measurement can reflect not only the conditions of fault movement nearby but also the change of regional stress fields; not only is this a method to obtain regional seismogenic information and to conduct short-term prediction but it is also involved with large scale space-time prediction of moderate and strong earthquakes on the basis of the macro characteristics of fractures.
基金the National Natural Science Foundation of China(No.51790512)the 111 Project(No.B17037)the National Key Laboratory Foundation,Industry-Academia-Research Collaboration Project of Aero Engine Corporation of China(No.HFZL2018CXY011-1)and MIIT。
文摘To investigate the influence of real leading-edge manufacturing error on aerodynamic performance of high subsonic compressor blades,a family of leading-edge manufacturing error data were obtained from measured compressor cascades.Considering the limited samples,the leadingedge angle and leading-edge radius distribution forms were evaluated by Shapiro-Wilk test and quantile–quantile plot.Their statistical characteristics provided can be introduced to later related researches.The parameterization design method B-spline and Bezier are adopted to create geometry models with manufacturing error based on leading-edge angle and leading-edge radius.The influence of real manufacturing error is quantified and analyzed by self-developed non-intrusive polynomial chaos and Sobol’indices.The mechanism of leading-edge manufacturing error on aerodynamic performance is discussed.The results show that the total pressure loss coefficient is sensitive to the leading-edge manufacturing error compared with the static pressure ratio,especially at high incidence.Specifically,manufacturing error of the leading edge will influence the local flow acceleration and subsequently cause fluctuation of the downstream flow.The aerodynamic performance is sensitive to the manufacturing error of leading-edge radius at the design and negative incidences,while it is sensitive to the manufacturing error of leading-edge angle under the operation conditions with high incidences.
基金supported by the National Key R.D Program of China(2021YFB2401904)the Joint Fund project of the National Natural Science Foundation of China(U21A20485)+1 种基金the National Natural Science Foundation of China(61976175)the Key Laboratory Project of Shaanxi Provincial Education Department Scientific Research Projects(20JS109)。
文摘The state of charge(SOC)estimation of lithium-ion battery is an important function in the battery management system(BMS)of electric vehicles.The long short term memory(LSTM)model can be employed for SOC estimation,which is capable of estimating the future changing states of a nonlinear system.Since the BMS usually works under complicated operating conditions,i.e the real measurement data used for model training may be corrupted by non-Gaussian noise,and thus the performance of the original LSTM with the mean square error(MSE)loss may deteriorate.Therefore,a novel LSTM with mixture kernel mean p-power error(MKMPE)loss,called MKMPE-LSTM,is developed by using the MKMPE loss to replace the MSE as the learning criterion in LSTM framework,which can achieve robust SOC estimation under the measurement data contaminated with non-Gaussian noises(or outliers)because of the MKMPE containing the p-order moments of the error distribution.In addition,a meta-heuristic algorithm,called heap-based-optimizer(HBO),is employed to optimize the hyper-parameters(mainly including learning rate,number of hidden layer neuron and value of p in MKMPE)of the proposed MKMPE-LSTM model to further improve its flexibility and generalization performance,and a novel hybrid model(HBO-MKMPE-LSTM)is established for SOC estimation under non-Gaussian noise cases.Finally,several tests are performed under various cases through a benchmark to evaluate the performance of the proposed HBO-MKMPE-LSTM model,and the results demonstrate that the proposed hybrid method can provide a good robustness and accuracy under different non-Gaussian measurement noises,and the SOC estimation results in terms of mean square error(MSE),root MSE(RMSE),mean absolute relative error(MARE),and determination coefficient R2are less than 0.05%,3%,3%,and above 99.8%at 25℃,respectively.
基金Supported by the National Natural Science Foundation of China(61501007)General Project of Science and Technology Project of Beijing Municipal Education Commission(KM201610005023)
文摘The main function of Internet of Things is to collect and transmit data.At present,the data transmission in Internet of Things lacks effective trust attestation mechanism and trust traceability mechanism of data source.To solve the above problems,a trust attestation mechanism for sensing layer nodes is presented.First a trusted group is established,and the node which is going to join the group needs to attest its identity and key attributes to the higher level node.Then the dynamic trust measurement value of the node can be obtained by measuring the node data transmission behavior.Finally the node encapsulates the key attributes and trust measurement value to use short message group signature to attest its trust to the challenger.This mechanism can measure the data sending and receiving behaviors of sensing nodes and track the data source,and it does not expose the privacy information of nodes and the sensing nodes can be traced effectively.The trust measurement for sensing nodes and verification is applicable to Internet of Things and the simulation experiment shows the trust attestation mechanism is flexible,practical and efficient.Besides,it can accurately and quickly identify the malicious nodes at the same time.The impact on the system performance is negligible.
基金supported by the National Magnetic Confinement Fusion Science Program of China (Grant Nos.2011GB102000, 2015GB103000)
文摘In this paper, the measurement method of calorimetric power for an electron cyclotron resonance heating（ECRH） system for EAST is presented. This method requires measurements of the water flow through the cooling circuits and the input and output water temperatures in each cooling circuit. Usually, the inlet water temperature stability is controlled to obtain more accurate results.The influence of the inlet water temperature change on the measurement results is analyzed for the first time in this paper. Also, a novel temperature calibration method is proposed. This kind of calibration method is accurate and effective, and can be easily implemented.
文摘The exponential advancement witnessed in 5G communication and quantum computing has presented unparalleled prospects for safeguarding sensitive data within healthcare infrastructures.This study proposes a novel framework for healthcare applications that integrates 5G communication,quantum computing,and sensitive data measurement to address the challenges of measuring and securely transmitting sensitive medical data.The framework includes a quantum-inspired method for quantifying data sensitivity based on quantum superposition and entanglement principles and a delegated quantum computing protocol for secure data transmission in 5G-enabled healthcare systems,ensuring user anonymity and data confidentiality.The framework is applied to innovative healthcare scenarios,such as secure 5G voice communication,data transmission,and short message services.Experimental results demonstrate the framework’s high accuracy in sensitive data measurement and enhanced security for data transmission in 5G healthcare systems,surpassing existing approaches.
基金supported by the National Key Research and Development Program of China(No.2017YFB0902900,No.2017YFB0902901)National Natural Science Foundation of China(No.51627811,No.51725702)the Fundamental Research Funds for the Central Universities(No.2018ZD01)
文摘Smart grids are increasingly dependent on data with the rapid development of communication and measurement.As one of the important data sources of smart grids,phasor measurement unit(PMU)is facing the high risk from attacks.Compared with cyber attacks,global position system(GPS)spoofing attacks(GSAs)are easier to implement because they can be exploited by portable devices,without the need to access the physical system.Therefore,this paper proposes a novel method for pattern recognition of GSA and an additional function of the proposed method is the data correction to the phase angle difference(PAD)deviation.Specifically,this paper analyzes the effect of GSA on PMU measurement and gives two common patterns of GSA,i.e.,the step attack and the ramp attack.Then,the method of estimating the PAD deviation across a transmission line introduced by GSA is proposed,which does not require the line parameters.After obtaining the estimated PAD deviations,the pattern of GSA can be recognized by hypothesis tests and correlation coefficients according to the statistical characteristics of the estimated PAD deviations.Finally,with the case studies,the effectiveness of the proposed method is demonstrated,and the success rate of the pattern recognition and the online performance of the proposed method are analyzed.
文摘In repeated measurement data, the variables are not independent, and a certain auto- correlation typically exists between different levels of repeated measurement factors. The random error is composed of at least two parts, i.e. the individual random effect and the intra-individual multi-repeated measurement effect. Traditional statistical analysis methods （such as the t-test and the one-way analysis of variance） are not applicable. The linear mixed model has been widely applied for the analysis and design of repeated measurement data. This paper focuses on medical examples and describes the selection of a covariance structure for the linear mixed model of repeated measurement in the modeling of different variance-eovariance structures. By selecting different covariance structures, we can perform the parameter estimation and statistical test for the fixed effect of repeated measurement data, the parameters of random effects, and the covari- ance matrix. The results are analyzed and compared to provide a reference for applying the linear mixed model of repeated measurement to medical research.
基金Project supported by the Key Project of National Natural Science Foundation of China(Grant No.11332009)
文摘In this paper, recent measurements of tip vortex flow with and without cavitation carried out in Cavitation Mechanism Tunnel of China Ship Scientific Research Center（CSSRC） are presented. The elliptic hydrofoil with section NACA 662-415 was adopted as test model. High-speed video（HSV） camera was used to visualize the trajectory of tip vortex core and the form of tip vortex cavitation（TVC） in different cavitation situations. Laser Doppler velocimetry（LDV） was employed to measure the tip vortex flow field in some typical sections along the vortex trajectory with the case of cavitation free. Stereo particle image velocimetry（SPIV） system was used to measure the velocity and vorticity distributions with and without cavitation. Series measurement results such as velocity and vorticity distributions, the trajectory of tip vortex core, the vortex core radius, cavity size and cavitation inception number were obtained. The results demonstrated that the minimum pressure coefficient in the vortex core obtained by flow field measurement was quite coincident with the tip vortex cavitation inception number obtained under the condition of high incoming velocity and low air content. And TVC would decrease the vortex strength comparing with the case without cavitation.
