The ammonia synthesis reactor is the core unit in the whole ammonia synthesis production. The ammonia concentration at the ammonia converter outlet is a significant process variable, which reflects directly the produc...The ammonia synthesis reactor is the core unit in the whole ammonia synthesis production. The ammonia concentration at the ammonia converter outlet is a significant process variable, which reflects directly the production efficiency. However, it is hard to be measured reliably online in real applications. In this paper, a soft sensor based on BP neural network (BPNN) is applied to estimate the ammonia concentration. A modified group search optimization with nearest neighborhood (GSO-NH) is proposed to optimize the weights and thresholds of BPNN. GSO-NH is integrated with BPNN to build a soft sensor model. Finally, the soft sensor model based on BPNN and GSO-NH (GSO-NH-NN) is used to infer the outlet ammonia concentration in a real-world application. Three other modeling methods are applied for comparison with GSO-NH-NN. The results show that the soft sensor based on GSO-NH-NN has a good prediction performance with high accuracy. Moreover, the GSO-NH-NN also provides good generalization ability to other modeling problems in ammonia synthesis production.展开更多
Based on the reaction between the azido group and hydrogen sulfide (H2S), BTN, an ofT-on fluorescent sensor was synthesized, which exhibited a 20-fold fluorescence enhancement upon addition of H2S, and a 5.6×10...Based on the reaction between the azido group and hydrogen sulfide (H2S), BTN, an ofT-on fluorescent sensor was synthesized, which exhibited a 20-fold fluorescence enhancement upon addition of H2S, and a 5.6×10 8 mol/L detection limit can be reached in 10 min. To check its applicability, an easy prepared test paper strip of BTN was made for rapid and selective detection of hydrogen sulfide in red-wine samples, the detection limit is as low as 1 μmol/L.展开更多
When a mass of individual targets move closely, it is unpractical or unnecessary to localize and track every specific target in wireless sensor networks (WSN). However, they can be tracked as a whole by view of group ...When a mass of individual targets move closely, it is unpractical or unnecessary to localize and track every specific target in wireless sensor networks (WSN). However, they can be tracked as a whole by view of group target. In order to decrease the amount of energy spent on active sensing and communications, a flexible boundary detecting model for group target tracking in WSN is proposed, in which, the number of sensors involved in target tracking is adjustable. Unlike traditional one or multiple individual targets, the group target usually occupies a large area. To obtain global estimated position of group target, a divide-merge algorithm using convex hull is designed. In this algorithm, group target’s boundary is divided into several small pieces, and each one is enclosed by a convex hull which is constructed by a cluster of boundary sensors. Then, the information of these small convex hulls is sent back to a sink. Finally, big convex hull merged from these small ones is considered as the group target’s contour. According to our metric of precision evaluation, the simulation experiments confirm the efficiency and accuracy of this algorithm.展开更多
The Wireless Sensor Network(WSN)is a promising technology that could be used to monitor rivers’water levels for early warning flood detection in the 5G context.However,during a flood,sensor nodes may be washed up or ...The Wireless Sensor Network(WSN)is a promising technology that could be used to monitor rivers’water levels for early warning flood detection in the 5G context.However,during a flood,sensor nodes may be washed up or become faulty,which seriously affects network connectivity.To address this issue,Unmanned Aerial Vehicles(UAVs)could be integrated with WSN as routers or data mules to provide reliable data collection and flood prediction.In light of this,we propose a fault-tolerant multi-level framework comprised of a WSN and a UAV to monitor river levels.The framework is capable to provide seamless data collection by handling the disconnections caused by the failed nodes during a flood.Besides,an algorithm hybridized with Group Method Data Handling(GMDH)and Particle Swarm Optimization(PSO)is proposed to predict forthcoming floods in an intelligent collaborative environment.The proposed water-level prediction model is trained based on the real dataset obtained fromthe Selangor River inMalaysia.The performance of the work in comparison with other models has been also evaluated and numerical results based on different metrics such as coefficient of determination(R2),correlation coefficient(R),RootMean Square Error(RMSE),Mean Absolute Percentage Error(MAPE),and BIAS are provided.展开更多
The key exposure problem is a practical threat for many security applications. In wireless sensor networks (WSNs), keys could be compromised easily due to its limited hardware protections. A secure group key managemen...The key exposure problem is a practical threat for many security applications. In wireless sensor networks (WSNs), keys could be compromised easily due to its limited hardware protections. A secure group key management scheme is responsible for secure distributing group keys among valid nodes of the group. Based on the key-insulated encryption (KIE), we propose a group key management scheme (KIE-GKMS), which integrates the pair-wise key pre-distribution for WSN. The KIE-GKMS scheme updates group keys dynamically when adding or removing nodes. Moreover, the security analysis proves that the KIE-GKMS scheme not only obtains the semantic security, but also provides the forward and backward security. Finally, the theoretical analysis shows that the KIE-GKMS scheme has constant performance on both communication and storage costs in sensor nodes.展开更多
密钥预分配方案关乎无线传感器网络节点间协同的安全问题.现有的密钥预分配方案大多存在连通率低,抗捕获性差,灵活性差等缺点.该文在分析现有密钥预分配方案的基础之上,对TD(k,n)模型作出了适当的改进,设计出一种均匀分布TD(k,n)模型,引...密钥预分配方案关乎无线传感器网络节点间协同的安全问题.现有的密钥预分配方案大多存在连通率低,抗捕获性差,灵活性差等缺点.该文在分析现有密钥预分配方案的基础之上,对TD(k,n)模型作出了适当的改进,设计出一种均匀分布TD(k,n)模型,引入Blundo二元对称多项式加密方法,并结合提出的均匀分配TD(k,n)模型,进一步提出了一种改进的分组密钥预分配方案IGDKPS(improved key-predistribution scheme based on group deployment).理论分析和仿真结果表明:IGDKPS方案在安全连通率、抗捕获性、灵活性等方面均有良好表现.展开更多
Localization is fundamental component for many critical applicationsin wireless sensor networks (WSNs). However, DV-Hop localization algorithmand its improved ones cannot meet the requirement of positioning accuracy f...Localization is fundamental component for many critical applicationsin wireless sensor networks (WSNs). However, DV-Hop localization algorithmand its improved ones cannot meet the requirement of positioning accuracy fortheir high localization errors. This paper proposes a localization algorithm basedon positioning group quality (LA-PGQ). The average estimate hop size was firstcorrected by link singularity and difference between the estimation hop lengthand true hop length among beacons, the best positioning group was constitutedfor unknown node by using node trust function and positioning group qualityevaluation function to choose three beacons with best topological distribution.Third, LA-PGQ algorithm uses two-dimensional hyperbolic algorithm instead ofthe classical three-side method/least square method to determine the coordinates ofnodes, which are more accurate. Simulation results show the positioning accuracyof LA-PGQ algorithm is obviously improved in WSNs, and the average localizationerror of LA-PGQ algorithm is remarkable lower than those of the DV-Hopalgorithm and its improved algorithm and Amorphous, under both the isotropyand anisotropy distributions.展开更多
基金Supported by the National Natural Science Foundation of China (61074079)Shanghai Leading Academic Discipline Project(B504)+1 种基金Specialized Research Fund for the Doctoral Program of Higher Education of China (20100074120010)the Natural Science Foundation of Shanghai City (11ZR1409700)
文摘The ammonia synthesis reactor is the core unit in the whole ammonia synthesis production. The ammonia concentration at the ammonia converter outlet is a significant process variable, which reflects directly the production efficiency. However, it is hard to be measured reliably online in real applications. In this paper, a soft sensor based on BP neural network (BPNN) is applied to estimate the ammonia concentration. A modified group search optimization with nearest neighborhood (GSO-NH) is proposed to optimize the weights and thresholds of BPNN. GSO-NH is integrated with BPNN to build a soft sensor model. Finally, the soft sensor model based on BPNN and GSO-NH (GSO-NH-NN) is used to infer the outlet ammonia concentration in a real-world application. Three other modeling methods are applied for comparison with GSO-NH-NN. The results show that the soft sensor based on GSO-NH-NN has a good prediction performance with high accuracy. Moreover, the GSO-NH-NN also provides good generalization ability to other modeling problems in ammonia synthesis production.
基金This work was financially supported by the Scien- tific Research Foundation of Northwest A&F University (Nos. Z111021103 and Z111021107), the National Nat- ural Science Foundation of China (Nos. 21206137, 21272030, 201205095, 21472016), and Shaanxi Prov- ince Science and Technology (No. 2013K12-03-23).
文摘Based on the reaction between the azido group and hydrogen sulfide (H2S), BTN, an ofT-on fluorescent sensor was synthesized, which exhibited a 20-fold fluorescence enhancement upon addition of H2S, and a 5.6×10 8 mol/L detection limit can be reached in 10 min. To check its applicability, an easy prepared test paper strip of BTN was made for rapid and selective detection of hydrogen sulfide in red-wine samples, the detection limit is as low as 1 μmol/L.
文摘When a mass of individual targets move closely, it is unpractical or unnecessary to localize and track every specific target in wireless sensor networks (WSN). However, they can be tracked as a whole by view of group target. In order to decrease the amount of energy spent on active sensing and communications, a flexible boundary detecting model for group target tracking in WSN is proposed, in which, the number of sensors involved in target tracking is adjustable. Unlike traditional one or multiple individual targets, the group target usually occupies a large area. To obtain global estimated position of group target, a divide-merge algorithm using convex hull is designed. In this algorithm, group target’s boundary is divided into several small pieces, and each one is enclosed by a convex hull which is constructed by a cluster of boundary sensors. Then, the information of these small convex hulls is sent back to a sink. Finally, big convex hull merged from these small ones is considered as the group target’s contour. According to our metric of precision evaluation, the simulation experiments confirm the efficiency and accuracy of this algorithm.
基金This work was supported by Ministry of Higher Education,Fundamental Research Grant Scheme,Vote Number 21H14,and Faculty of Information Science and Technology,Universiti Kebangsaan Malaysia(Grant ID:GGPM-2020-029 and Grant ID:PPFTSM-2020).
文摘The Wireless Sensor Network(WSN)is a promising technology that could be used to monitor rivers’water levels for early warning flood detection in the 5G context.However,during a flood,sensor nodes may be washed up or become faulty,which seriously affects network connectivity.To address this issue,Unmanned Aerial Vehicles(UAVs)could be integrated with WSN as routers or data mules to provide reliable data collection and flood prediction.In light of this,we propose a fault-tolerant multi-level framework comprised of a WSN and a UAV to monitor river levels.The framework is capable to provide seamless data collection by handling the disconnections caused by the failed nodes during a flood.Besides,an algorithm hybridized with Group Method Data Handling(GMDH)and Particle Swarm Optimization(PSO)is proposed to predict forthcoming floods in an intelligent collaborative environment.The proposed water-level prediction model is trained based on the real dataset obtained fromthe Selangor River inMalaysia.The performance of the work in comparison with other models has been also evaluated and numerical results based on different metrics such as coefficient of determination(R2),correlation coefficient(R),RootMean Square Error(RMSE),Mean Absolute Percentage Error(MAPE),and BIAS are provided.
基金Project(61100201) supported by National Natural Science Foundation of ChinaProject(12ZZ019) supported by Technology Innovation Research Program,Shang Municipal Education Commission,China+1 种基金Project(LYM11053) supported by the Foundation for Distinguished Young Talents in Higher Education of Guangdong Province,ChinaProject(NCET-12-0358) supported by New Century Excellent Talentsin University,Ministry of Education,China
文摘The key exposure problem is a practical threat for many security applications. In wireless sensor networks (WSNs), keys could be compromised easily due to its limited hardware protections. A secure group key management scheme is responsible for secure distributing group keys among valid nodes of the group. Based on the key-insulated encryption (KIE), we propose a group key management scheme (KIE-GKMS), which integrates the pair-wise key pre-distribution for WSN. The KIE-GKMS scheme updates group keys dynamically when adding or removing nodes. Moreover, the security analysis proves that the KIE-GKMS scheme not only obtains the semantic security, but also provides the forward and backward security. Finally, the theoretical analysis shows that the KIE-GKMS scheme has constant performance on both communication and storage costs in sensor nodes.
文摘密钥预分配方案关乎无线传感器网络节点间协同的安全问题.现有的密钥预分配方案大多存在连通率低,抗捕获性差,灵活性差等缺点.该文在分析现有密钥预分配方案的基础之上,对TD(k,n)模型作出了适当的改进,设计出一种均匀分布TD(k,n)模型,引入Blundo二元对称多项式加密方法,并结合提出的均匀分配TD(k,n)模型,进一步提出了一种改进的分组密钥预分配方案IGDKPS(improved key-predistribution scheme based on group deployment).理论分析和仿真结果表明:IGDKPS方案在安全连通率、抗捕获性、灵活性等方面均有良好表现.
基金This work was supported by the Yunnan Local Colleges Applied BasicResearch Projects(2017FH001-059,2018FH001-010,2018FH001-061)National Natural Science Foundation of China(61962033).
文摘Localization is fundamental component for many critical applicationsin wireless sensor networks (WSNs). However, DV-Hop localization algorithmand its improved ones cannot meet the requirement of positioning accuracy fortheir high localization errors. This paper proposes a localization algorithm basedon positioning group quality (LA-PGQ). The average estimate hop size was firstcorrected by link singularity and difference between the estimation hop lengthand true hop length among beacons, the best positioning group was constitutedfor unknown node by using node trust function and positioning group qualityevaluation function to choose three beacons with best topological distribution.Third, LA-PGQ algorithm uses two-dimensional hyperbolic algorithm instead ofthe classical three-side method/least square method to determine the coordinates ofnodes, which are more accurate. Simulation results show the positioning accuracyof LA-PGQ algorithm is obviously improved in WSNs, and the average localizationerror of LA-PGQ algorithm is remarkable lower than those of the DV-Hopalgorithm and its improved algorithm and Amorphous, under both the isotropyand anisotropy distributions.