Based on the investigation data of 12 Haloxylon ammodendron plots in the south edge of Gurbantunggut Desert, Fuzzy distribution was introduced into the study of Haloxylon ammodendron base diameter structure fitting ac...Based on the investigation data of 12 Haloxylon ammodendron plots in the south edge of Gurbantunggut Desert, Fuzzy distribution was introduced into the study of Haloxylon ammodendron base diameter structure fitting according to the consistency between the characteristics of Fuzzy distribution function and the distribution series of cumulative percentage of stand base diameter, and the fitting precision and effect of Fuzzy distribution function were discussed. The root mean square error RMSE and determination coefficient R<sup>2</sup> values showed that Fuzzy-Γ<sub>1</sub>, Fuzzy-Γ<sub>2</sub>, Fuzzy-Γ<sub>3</sub>, Fuzzy-Γ<sub>4</sub> had good fitting performance, among which Fuzzy-Γ<sub>1</sub> had relatively high fitting precision, and its parameters were closely related to stand age and density, Fuzzy-Γ<sub>2</sub> distribution function was the second, and Fuzzy-Γ<sub>4</sub> distribution function had the worst fitting effect. By introducing a parameter c from the similarity of four distribution function formulas, a generalized Fuzzy distribution function Fuzzy-Γ<sub>5</sub> is obtained. This function shows the highest fitting accuracy. Most of the values of parameter c are near 1 or 2, which shows that the diameter distribution is mainly approximate to Fuzzy-Γ<sub>1</sub> and Fuzzy-Γ<sub>2</sub>.展开更多
Quantum key distribution(QKD) generates information-theoretical secret keys between two parties based on the physical laws of quantum mechanics. Following the advancement in quantum communication networks, it becomes ...Quantum key distribution(QKD) generates information-theoretical secret keys between two parties based on the physical laws of quantum mechanics. Following the advancement in quantum communication networks, it becomes feasible and economical to combine QKD with classical optical communication through the same fiber using dense wavelength division multiplexing(DWDM) technology. This study proposes a detailed scheme of TF-QKD protocol with DWDM technology and analyzes its performance, considering the influence of quantum channel number and adjacent quantum crosstalk on the secret key rates. The simulation results show that the scheme further increases the secret key rate of TF-QKD and its variants. Therefore, this scheme provides a method for improving the secret key rate for practical quantum networks.展开更多
随着可再生能源占比的提升,气电联合配网(integrated electricity-gas distribution systems,IEGDS)发展迅速,其研究的必要性也随之凸显。为解决IEGDS考虑可再生能源接入后的多设施规划及可靠性评估问题,提出了考虑可靠性约束的IEGDS分...随着可再生能源占比的提升,气电联合配网(integrated electricity-gas distribution systems,IEGDS)发展迅速,其研究的必要性也随之凸显。为解决IEGDS考虑可再生能源接入后的多设施规划及可靠性评估问题,提出了考虑可靠性约束的IEGDS分布鲁棒优化(distributionally robust optimization,DRO)规划模型。可靠性评估通过系统平均中断频率指标(system average interruption frequency index,SAIFI)与预期能源未供应指标(expectation energy not supplied,EENS)量化,给出一种显式可靠性评估模型。利用Wasserstein距离衡量的DRO规划模型来处理可再生能源出力、电与气负荷的随机性。最后经过案例分析得出,投建设施种类的增加不仅能降低总成本,还能提高系统运行可靠性与灵活性,可再生能源出力与气电负荷的不确定性导致总成本提升60%以上。随着可靠性要求提升总成本也随之提高,但得到的方案在实际应用中更具价值与参考性。展开更多
Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic...Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic,and hydrogeological models are operationally exploited.This holistic approach was adopted for the development of the AquaVar DSS,used for water resource management in the French Mediterranean Var watershed.The year 2019 marked the initial use of the DSS in its operational environment.Over the next 5 years,multiple hydrological events allowed to test the performance of the DSS.The results show that the tool is capable of simulating peak flows associated with two extreme rainfall events(storms Alex and Aline).For a moderate flood,the real-time functionality was able to simulate forecast discharges 26 h before the flood peak,with a maximum local error of 30%.Finally,simulations for the drought period 2022-2023 highlighted the essential need for DSS to evolve in line with changing climatic conditions,which give rise to unprecedented hydrological processes.The lessons learned from these first 5 years of AquaVar use under operational conditions are synthesized,addressing various topics such as DSS modularity,evolution,data positioning,technology,and governance.展开更多
The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this wor...The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.展开更多
In this paper, a distributed muting strategy based on simplified topology （DRBST） was proposed for LEO satellite networks. The topology of LEO satellite networks was simplified aiming at minimizing intersatellite li...In this paper, a distributed muting strategy based on simplified topology （DRBST） was proposed for LEO satellite networks. The topology of LEO satellite networks was simplified aiming at minimizing intersatellite links handover number. To optimize the route based on the simplified topology, we considered not only the transmission delay but also the queuing delay and the processing delay, which were analyzed using Markov chain and determined using a novel methodology. The DRBST algorithm was simulated in a LEO satellite networks model built using OPNET. The simulation results demonstrate that the low complexity DRBST algorithm can guarantee end-to-end delay bound. Moreover, the muting protocol cost is much less than traditional algorithms.展开更多
Surface properties （viz. surface area, basicity/base strength distribution, and crystal phases） of alkali metal doped CaO （alkali metal/Ca= 0.1 and 0.4） catalysts and their catalytic activity/selectivity in oxidat...Surface properties （viz. surface area, basicity/base strength distribution, and crystal phases） of alkali metal doped CaO （alkali metal/Ca= 0.1 and 0.4） catalysts and their catalytic activity/selectivity in oxidative coupling of methane （OCM） to higher hydrocarbons at different reaction conditions （viz. temperature, 700 and 750 ℃; CH4/O2 ratio, 4.0 and 8.0 and space velocity, 5140-20550 cm^3 ·g^-1·h^-1） have been investigated. The influence of catalyst calcination temperature on the activity/selectivity has also been investigated. The surface properties （viz. surface area, basicity/base strength distribution） and catalytic activity/selectivity of the alkali metal doped CaO catalysts are strongly influenced by the alkali metal promoter and its concentration in the alkali metal doped CaO catalysts. An addition of alkali metal promoter to CaO results in a large decrease in the surface area but a large increase in the surface basicity （strong basic sites） and the C2＋ selectivity and yield of the catalysts in the OCM process. The activity and selectivity are strongly influenced by the catalyst calcination temperature. No direct relationship between surface basicity and catalytic activity/selectivity has been observed. Among the alkali metal doped CaO catalysts, Na-CaO （Na/Ca = 0.1, before calcination） catalyst （calcined at 750 ℃）, showed best performance （C2＋ selectivity of 68.8% with 24.7% methane conversion）, whereas the poorest performance was shown by the Rb-CaO catalyst in the OCM process.展开更多
An algorithm for underwater target feature recognition is proposed using its highlights distribution.For an underwater target with large size and slender body,it is assumed that the heading course and the length of th...An algorithm for underwater target feature recognition is proposed using its highlights distribution.For an underwater target with large size and slender body,it is assumed that the heading course and the length of the target are both determined by the distribution of its highlights.By supposing that these highlights obey Gaussian mixture distribution,the feature recognition problem can be transformed into a clustering problem.Therefore,using the collinearly constrained expectation maximization algorithm,the clustering centers of these highlights can be calculated and then the estimation of the heading and length of the target can be obtained with high accuracy.The effectiveness of the proposed method is demonstrated using simulations.展开更多
Measurement of light distribution in biological tissue contributes to selecting strategy and optimizing dose for biomedical application. In this letter, a photoacoustic method combined with Monte Carlo simulation was ...Measurement of light distribution in biological tissue contributes to selecting strategy and optimizing dose for biomedical application. In this letter, a photoacoustic method combined with Monte Carlo simulation was used to estimate the three-dimensional light distribution in biological tissue. The light distribution was produced by a cylindrical diffuser which interposed into tissues. The light profiles obtained by the method were compared to those detected by photo diodes. The experimental results demonstrate the feasibility of this method. The approach can play a significant role for photo-dosimetry in biomedical phototherapy.展开更多
This study evaluated the application of the European flood forecasting operational real time system （EFFORTS） to the Yellow River. An automatic data pre-processing program was developed to provide real-time hydromet...This study evaluated the application of the European flood forecasting operational real time system （EFFORTS） to the Yellow River. An automatic data pre-processing program was developed to provide real-time hydrometeorological data. Various GIS layers were collected and developed to meet the demands of the distributed hydrological model in the EFFORTS. The model parameters were calibrated and validated based on more than ten years of historical hydrometeorological data from the study area. The San-Hua Basin （from the Sanmenxia Reservoir to the Huayuankou Hydrological Station）, the most geographically important area of the Yellow River, was chosen as the study area. The analysis indicates that the EFFORTS enhances the work efficiency, extends the flood forecasting lead time, and attains an acceptable level of forecasting accuracy in the San-Hua Basin, with a mean deterministic coefficient at Huayuankou Station, the basin outlet, of 0.90 in calibration and 0.96 in validation. The analysis also shows that the ;simulation accuracy is better for the southern part than for the northern part of the San-Hua Basin. This implies that, along with the characteristics of the basin and the mechanisms of runoff generation of the hydrological model, the hydrometeorological data play an important role in simulation of hydrological behavior.展开更多
Cloud storage is widely used in massive data outsourcing, but how to efficiently query encrypted multidimensional data stored in an untrusted cloud environment remains a research challenge. We propose a high performan...Cloud storage is widely used in massive data outsourcing, but how to efficiently query encrypted multidimensional data stored in an untrusted cloud environment remains a research challenge. We propose a high performance and privacy-preserving query（p LSH-PPQ） scheme over encrypted multidimensional data to address this challenge. In our scheme, for a given query, the proxy server will return K top similar data object identifiers. An enhanced Ciphertext-Policy Attribute-Based Encryption（CP-ABE）policy is used to control access to the search results. Therefore, only the requester with the permission attribute can obtain correct secret keys to decrypt the data. Security analysis proves that the p LSH-PPQ scheme achieves data confidentiality and reserves the data owner＇s privacy in a semi-trusted cloud. In addition, evaluations demonstrate that the p LSH-PPQ scheme can significantly reduce response time and provide high search efficiency without compromising on search quality.展开更多
Based on the properties of wideband source’s spatial spread,an algorithm for reverberation suppression in beams domain is proposed.In an effective observation range,a compact bank of receiving spatial beams is operat...Based on the properties of wideband source’s spatial spread,an algorithm for reverberation suppression in beams domain is proposed.In an effective observation range,a compact bank of receiving spatial beams is operated to transform the data from element domain to beam domain.Angular Distribution Index(ADI) is obtained by comparing to a reference value which is computed by Monte Carlo Integration.ADI decreases with a stronger target echo.Hence,choosing an appropriate threshold of ADI,the target echo can be separated from reverberation by cutting off the high AD components.The filter is compatible with the procedures of beamforming and detection for the current sonar.The computation complexity of the filter is low.The relationships between ADI and frequency,bandwidth,signal-reverberation ratio,are illustrated by a simulation example.The processing results based on the lake-trial and sea-trial data show that reverberation can be significantly suppressed,and threshold choosing for wideband ADI filter is fault tolerant.展开更多
Intrusion detection is critical to guaranteeing the safety of the data in the network.Even though,since Internet commerce has grown at a breakneck pace,network traffic kinds are rising daily,and network behavior chara...Intrusion detection is critical to guaranteeing the safety of the data in the network.Even though,since Internet commerce has grown at a breakneck pace,network traffic kinds are rising daily,and network behavior characteristics are becoming increasingly complicated,posing significant hurdles to intrusion detection.The challenges in terms of false positives,false negatives,low detection accuracy,high running time,adversarial attacks,uncertain attacks,etc.lead to insecure Intrusion Detection System(IDS).To offset the existing challenge,the work has developed a secure Data Mining Intrusion detection system(DataMIDS)framework using Functional Perturbation(FP)feature selection and Bengio Nesterov Momentum-based Tuned Generative Adversarial Network(BNM-tGAN)attack detection technique.The data mining-based framework provides shallow learning of features and emphasizes feature engineering as well as selection.Initially,the IDS data are analyzed for missing values based on the Marginal Likelihood Fisher Information Matrix technique(MLFIMT)that identifies the relationship among the missing values and attack classes.Based on the analysis,the missing values are classified as Missing Completely at Random(MCAR),Missing at random(MAR),Missing Not at Random(MNAR),and handled according to the types.Thereafter,categorical features are handled followed by feature scaling using Absolute Median Division based Robust Scalar(AMDRS)and the Handling of the imbalanced dataset.The selection of relevant features is initiated using FP that uses‘3’Feature Selection(FS)techniques i.e.,Inverse Chi Square based Flamingo Search(ICS-FSO)wrapper method,Hyperparameter Tuned Threshold based Decision Tree(HpTT-DT)embedded method,and Xavier Normal Distribution based Relief(XavND-Relief)filter method.Finally,the selected features are trained and tested for detecting attacks using BNM-tGAN.The Experimental analysis demonstrates that the introduced DataMIDS framework produces an accurate diagnosis about the attack with low computation time.The work avoids false alarm rate of attacks and remains to be relatively robust against malicious attacks as compared to existing methods.展开更多
The recent growth of communication and sensor technology results in the enlargement of a new attractive and challenging area-wireless sensor networks (WSNs). A network comprising of several minute wireless sensor node...The recent growth of communication and sensor technology results in the enlargement of a new attractive and challenging area-wireless sensor networks (WSNs). A network comprising of several minute wireless sensor nodes which are organized in a dense manner is called as a Wireless Sensor Network (WSN). Every node estimates the state of its surroundings in this network. The estimated results are then converted into the signal form in order to determine the features related to this technique after the processing of the signals. It’s high computational environment with limited and controlled broadcast range, processing, as well as limited energy. The embedded soft computing approach in wireless sensor networks is suggested. This approach means a grouping of embedded fuzzy logic and neural networks models for information processing in complex environment with unsure, rough, fuzzy measuring data. It is generalization of soft computing concept for the embedded, distributed, adaptive systems.展开更多
文摘Based on the investigation data of 12 Haloxylon ammodendron plots in the south edge of Gurbantunggut Desert, Fuzzy distribution was introduced into the study of Haloxylon ammodendron base diameter structure fitting according to the consistency between the characteristics of Fuzzy distribution function and the distribution series of cumulative percentage of stand base diameter, and the fitting precision and effect of Fuzzy distribution function were discussed. The root mean square error RMSE and determination coefficient R<sup>2</sup> values showed that Fuzzy-Γ<sub>1</sub>, Fuzzy-Γ<sub>2</sub>, Fuzzy-Γ<sub>3</sub>, Fuzzy-Γ<sub>4</sub> had good fitting performance, among which Fuzzy-Γ<sub>1</sub> had relatively high fitting precision, and its parameters were closely related to stand age and density, Fuzzy-Γ<sub>2</sub> distribution function was the second, and Fuzzy-Γ<sub>4</sub> distribution function had the worst fitting effect. By introducing a parameter c from the similarity of four distribution function formulas, a generalized Fuzzy distribution function Fuzzy-Γ<sub>5</sub> is obtained. This function shows the highest fitting accuracy. Most of the values of parameter c are near 1 or 2, which shows that the diameter distribution is mainly approximate to Fuzzy-Γ<sub>1</sub> and Fuzzy-Γ<sub>2</sub>.
基金supported by the State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications (Grant No. IPOC2021ZT10)the National Natural Science Foundation of China (Grant No. 11904333)+1 种基金the Fundamental Research Funds for the Central Universities (Grant No. 2019XD-A02)BUPT Innovation and Entrepreneurship Support Program (Grant No. 2022YC-T051)。
文摘Quantum key distribution(QKD) generates information-theoretical secret keys between two parties based on the physical laws of quantum mechanics. Following the advancement in quantum communication networks, it becomes feasible and economical to combine QKD with classical optical communication through the same fiber using dense wavelength division multiplexing(DWDM) technology. This study proposes a detailed scheme of TF-QKD protocol with DWDM technology and analyzes its performance, considering the influence of quantum channel number and adjacent quantum crosstalk on the secret key rates. The simulation results show that the scheme further increases the secret key rate of TF-QKD and its variants. Therefore, this scheme provides a method for improving the secret key rate for practical quantum networks.
文摘随着可再生能源占比的提升,气电联合配网(integrated electricity-gas distribution systems,IEGDS)发展迅速,其研究的必要性也随之凸显。为解决IEGDS考虑可再生能源接入后的多设施规划及可靠性评估问题,提出了考虑可靠性约束的IEGDS分布鲁棒优化(distributionally robust optimization,DRO)规划模型。可靠性评估通过系统平均中断频率指标(system average interruption frequency index,SAIFI)与预期能源未供应指标(expectation energy not supplied,EENS)量化,给出一种显式可靠性评估模型。利用Wasserstein距离衡量的DRO规划模型来处理可再生能源出力、电与气负荷的随机性。最后经过案例分析得出,投建设施种类的增加不仅能降低总成本,还能提高系统运行可靠性与灵活性,可再生能源出力与气电负荷的不确定性导致总成本提升60%以上。随着可靠性要求提升总成本也随之提高,但得到的方案在实际应用中更具价值与参考性。
文摘Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic,and hydrogeological models are operationally exploited.This holistic approach was adopted for the development of the AquaVar DSS,used for water resource management in the French Mediterranean Var watershed.The year 2019 marked the initial use of the DSS in its operational environment.Over the next 5 years,multiple hydrological events allowed to test the performance of the DSS.The results show that the tool is capable of simulating peak flows associated with two extreme rainfall events(storms Alex and Aline).For a moderate flood,the real-time functionality was able to simulate forecast discharges 26 h before the flood peak,with a maximum local error of 30%.Finally,simulations for the drought period 2022-2023 highlighted the essential need for DSS to evolve in line with changing climatic conditions,which give rise to unprecedented hydrological processes.The lessons learned from these first 5 years of AquaVar use under operational conditions are synthesized,addressing various topics such as DSS modularity,evolution,data positioning,technology,and governance.
基金Projects(61573144,61773165,61673175,61174040)supported by the National Natural Science Foundation of ChinaProject(222201717006)supported by the Fundamental Research Funds for the Central Universities,China
文摘The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.
基金Supported by the National Science Foundation of China （No. 60873219）.
文摘In this paper, a distributed muting strategy based on simplified topology （DRBST） was proposed for LEO satellite networks. The topology of LEO satellite networks was simplified aiming at minimizing intersatellite links handover number. To optimize the route based on the simplified topology, we considered not only the transmission delay but also the queuing delay and the processing delay, which were analyzed using Markov chain and determined using a novel methodology. The DRBST algorithm was simulated in a LEO satellite networks model built using OPNET. The simulation results demonstrate that the low complexity DRBST algorithm can guarantee end-to-end delay bound. Moreover, the muting protocol cost is much less than traditional algorithms.
文摘Surface properties （viz. surface area, basicity/base strength distribution, and crystal phases） of alkali metal doped CaO （alkali metal/Ca= 0.1 and 0.4） catalysts and their catalytic activity/selectivity in oxidative coupling of methane （OCM） to higher hydrocarbons at different reaction conditions （viz. temperature, 700 and 750 ℃; CH4/O2 ratio, 4.0 and 8.0 and space velocity, 5140-20550 cm^3 ·g^-1·h^-1） have been investigated. The influence of catalyst calcination temperature on the activity/selectivity has also been investigated. The surface properties （viz. surface area, basicity/base strength distribution） and catalytic activity/selectivity of the alkali metal doped CaO catalysts are strongly influenced by the alkali metal promoter and its concentration in the alkali metal doped CaO catalysts. An addition of alkali metal promoter to CaO results in a large decrease in the surface area but a large increase in the surface basicity （strong basic sites） and the C2＋ selectivity and yield of the catalysts in the OCM process. The activity and selectivity are strongly influenced by the catalyst calcination temperature. No direct relationship between surface basicity and catalytic activity/selectivity has been observed. Among the alkali metal doped CaO catalysts, Na-CaO （Na/Ca = 0.1, before calcination） catalyst （calcined at 750 ℃）, showed best performance （C2＋ selectivity of 68.8% with 24.7% methane conversion）, whereas the poorest performance was shown by the Rb-CaO catalyst in the OCM process.
基金supported by the National Natural Science Foundation of China(61471352,61531018,61372181)the Key Lab Foundation of CAS(CXJJ-16S061)
文摘An algorithm for underwater target feature recognition is proposed using its highlights distribution.For an underwater target with large size and slender body,it is assumed that the heading course and the length of the target are both determined by the distribution of its highlights.By supposing that these highlights obey Gaussian mixture distribution,the feature recognition problem can be transformed into a clustering problem.Therefore,using the collinearly constrained expectation maximization algorithm,the clustering centers of these highlights can be calculated and then the estimation of the heading and length of the target can be obtained with high accuracy.The effectiveness of the proposed method is demonstrated using simulations.
基金supported by the National Natural Science Foundation of China(No.61178089/81201124)in part by the Natural Science Foundation of Fujian Province(No.2011Y0019)
文摘Measurement of light distribution in biological tissue contributes to selecting strategy and optimizing dose for biomedical application. In this letter, a photoacoustic method combined with Monte Carlo simulation was used to estimate the three-dimensional light distribution in biological tissue. The light distribution was produced by a cylindrical diffuser which interposed into tissues. The light profiles obtained by the method were compared to those detected by photo diodes. The experimental results demonstrate the feasibility of this method. The approach can play a significant role for photo-dosimetry in biomedical phototherapy.
基金supported by the ADB Loan for Flood Management Project in the Yellow River Basin (Grant No. YH-SW-XH-02)
文摘This study evaluated the application of the European flood forecasting operational real time system （EFFORTS） to the Yellow River. An automatic data pre-processing program was developed to provide real-time hydrometeorological data. Various GIS layers were collected and developed to meet the demands of the distributed hydrological model in the EFFORTS. The model parameters were calibrated and validated based on more than ten years of historical hydrometeorological data from the study area. The San-Hua Basin （from the Sanmenxia Reservoir to the Huayuankou Hydrological Station）, the most geographically important area of the Yellow River, was chosen as the study area. The analysis indicates that the EFFORTS enhances the work efficiency, extends the flood forecasting lead time, and attains an acceptable level of forecasting accuracy in the San-Hua Basin, with a mean deterministic coefficient at Huayuankou Station, the basin outlet, of 0.90 in calibration and 0.96 in validation. The analysis also shows that the ;simulation accuracy is better for the southern part than for the northern part of the San-Hua Basin. This implies that, along with the characteristics of the basin and the mechanisms of runoff generation of the hydrological model, the hydrometeorological data play an important role in simulation of hydrological behavior.
基金Supported by the National Natural Science Foundation of China(61303029)
文摘Cloud storage is widely used in massive data outsourcing, but how to efficiently query encrypted multidimensional data stored in an untrusted cloud environment remains a research challenge. We propose a high performance and privacy-preserving query（p LSH-PPQ） scheme over encrypted multidimensional data to address this challenge. In our scheme, for a given query, the proxy server will return K top similar data object identifiers. An enhanced Ciphertext-Policy Attribute-Based Encryption（CP-ABE）policy is used to control access to the search results. Therefore, only the requester with the permission attribute can obtain correct secret keys to decrypt the data. Security analysis proves that the p LSH-PPQ scheme achieves data confidentiality and reserves the data owner＇s privacy in a semi-trusted cloud. In addition, evaluations demonstrate that the p LSH-PPQ scheme can significantly reduce response time and provide high search efficiency without compromising on search quality.
基金supported by the National Natural Science Foundation of China(61302169)
文摘Based on the properties of wideband source’s spatial spread,an algorithm for reverberation suppression in beams domain is proposed.In an effective observation range,a compact bank of receiving spatial beams is operated to transform the data from element domain to beam domain.Angular Distribution Index(ADI) is obtained by comparing to a reference value which is computed by Monte Carlo Integration.ADI decreases with a stronger target echo.Hence,choosing an appropriate threshold of ADI,the target echo can be separated from reverberation by cutting off the high AD components.The filter is compatible with the procedures of beamforming and detection for the current sonar.The computation complexity of the filter is low.The relationships between ADI and frequency,bandwidth,signal-reverberation ratio,are illustrated by a simulation example.The processing results based on the lake-trial and sea-trial data show that reverberation can be significantly suppressed,and threshold choosing for wideband ADI filter is fault tolerant.
文摘Intrusion detection is critical to guaranteeing the safety of the data in the network.Even though,since Internet commerce has grown at a breakneck pace,network traffic kinds are rising daily,and network behavior characteristics are becoming increasingly complicated,posing significant hurdles to intrusion detection.The challenges in terms of false positives,false negatives,low detection accuracy,high running time,adversarial attacks,uncertain attacks,etc.lead to insecure Intrusion Detection System(IDS).To offset the existing challenge,the work has developed a secure Data Mining Intrusion detection system(DataMIDS)framework using Functional Perturbation(FP)feature selection and Bengio Nesterov Momentum-based Tuned Generative Adversarial Network(BNM-tGAN)attack detection technique.The data mining-based framework provides shallow learning of features and emphasizes feature engineering as well as selection.Initially,the IDS data are analyzed for missing values based on the Marginal Likelihood Fisher Information Matrix technique(MLFIMT)that identifies the relationship among the missing values and attack classes.Based on the analysis,the missing values are classified as Missing Completely at Random(MCAR),Missing at random(MAR),Missing Not at Random(MNAR),and handled according to the types.Thereafter,categorical features are handled followed by feature scaling using Absolute Median Division based Robust Scalar(AMDRS)and the Handling of the imbalanced dataset.The selection of relevant features is initiated using FP that uses‘3’Feature Selection(FS)techniques i.e.,Inverse Chi Square based Flamingo Search(ICS-FSO)wrapper method,Hyperparameter Tuned Threshold based Decision Tree(HpTT-DT)embedded method,and Xavier Normal Distribution based Relief(XavND-Relief)filter method.Finally,the selected features are trained and tested for detecting attacks using BNM-tGAN.The Experimental analysis demonstrates that the introduced DataMIDS framework produces an accurate diagnosis about the attack with low computation time.The work avoids false alarm rate of attacks and remains to be relatively robust against malicious attacks as compared to existing methods.
文摘The recent growth of communication and sensor technology results in the enlargement of a new attractive and challenging area-wireless sensor networks (WSNs). A network comprising of several minute wireless sensor nodes which are organized in a dense manner is called as a Wireless Sensor Network (WSN). Every node estimates the state of its surroundings in this network. The estimated results are then converted into the signal form in order to determine the features related to this technique after the processing of the signals. It’s high computational environment with limited and controlled broadcast range, processing, as well as limited energy. The embedded soft computing approach in wireless sensor networks is suggested. This approach means a grouping of embedded fuzzy logic and neural networks models for information processing in complex environment with unsure, rough, fuzzy measuring data. It is generalization of soft computing concept for the embedded, distributed, adaptive systems.
