Due to the enormous usage of the internet for transmission of data over a network,security and authenticity become major risks.Major challenges encountered in biometric system are the misuse of enrolled biometric temp...Due to the enormous usage of the internet for transmission of data over a network,security and authenticity become major risks.Major challenges encountered in biometric system are the misuse of enrolled biometric templates stored in database server.To describe these issues various algorithms are implemented to deliver better protection to biometric traits such as physical(Face,fingerprint,Ear etc.)and behavioural(Gesture,Voice,tying etc.)by means of matching and verification process.In this work,biometric security system with fuzzy extractor and convolutional neural networks using face attribute is proposed which provides different choices for supporting cryptographic processes to the confidential data.The proposed system not only offers security but also enhances the system execution by discrepancy conservation of binary templates.Here Face Attribute Convolutional Neural Network(FACNN)is used to generate binary codes from nodal points which act as a key to encrypt and decrypt the entire data for further processing.Implementing Artificial Intelligence(AI)into the proposed system,automatically upgrades and replaces the previously stored biometric template after certain time period to reduce the risk of ageing difference while processing.Binary codes generated from face templates are used not only for cryptographic approach is also used for biometric process of enrolment and verification.Three main face data sets are taken into the evaluation to attain system performance by improving the efficiency of matching performance to verify authenticity.This system enhances the system performance by 8%matching and verification and minimizes the False Acceptance Rate(FAR),False Rejection Rate(FRR)and Equal Error Rate(EER)by 6 times and increases the data privacy through the biometric cryptosystem by 98.2%while compared to other work.展开更多
地源热泵技术属于可再生能源利用技术。地源热泵是利用地球表面浅层地热资源作为冷热源进行能量转换的供暖空调系统。以A高校教学楼地源热泵系统为研究对象,介绍了该系统的工程概况,并对地源热泵系统的运行制冷工况进行了测试分析。结...地源热泵技术属于可再生能源利用技术。地源热泵是利用地球表面浅层地热资源作为冷热源进行能量转换的供暖空调系统。以A高校教学楼地源热泵系统为研究对象,介绍了该系统的工程概况,并对地源热泵系统的运行制冷工况进行了测试分析。结果表明:地源热泵运行稳定,该建筑地源热泵实测机组性能系数(Coefficient of Performance,COP)可达4.4以上,地源热泵实测系统制冷能效比(Energy Efficiency Ratio,EER)可达3.5以上,地源热泵机组的负载率为62%;夏季运行时,与普通空调相比可节约运行费用约1.3×104元,经济效益和环境效益显著。展开更多
文摘Due to the enormous usage of the internet for transmission of data over a network,security and authenticity become major risks.Major challenges encountered in biometric system are the misuse of enrolled biometric templates stored in database server.To describe these issues various algorithms are implemented to deliver better protection to biometric traits such as physical(Face,fingerprint,Ear etc.)and behavioural(Gesture,Voice,tying etc.)by means of matching and verification process.In this work,biometric security system with fuzzy extractor and convolutional neural networks using face attribute is proposed which provides different choices for supporting cryptographic processes to the confidential data.The proposed system not only offers security but also enhances the system execution by discrepancy conservation of binary templates.Here Face Attribute Convolutional Neural Network(FACNN)is used to generate binary codes from nodal points which act as a key to encrypt and decrypt the entire data for further processing.Implementing Artificial Intelligence(AI)into the proposed system,automatically upgrades and replaces the previously stored biometric template after certain time period to reduce the risk of ageing difference while processing.Binary codes generated from face templates are used not only for cryptographic approach is also used for biometric process of enrolment and verification.Three main face data sets are taken into the evaluation to attain system performance by improving the efficiency of matching performance to verify authenticity.This system enhances the system performance by 8%matching and verification and minimizes the False Acceptance Rate(FAR),False Rejection Rate(FRR)and Equal Error Rate(EER)by 6 times and increases the data privacy through the biometric cryptosystem by 98.2%while compared to other work.
文摘地源热泵技术属于可再生能源利用技术。地源热泵是利用地球表面浅层地热资源作为冷热源进行能量转换的供暖空调系统。以A高校教学楼地源热泵系统为研究对象,介绍了该系统的工程概况,并对地源热泵系统的运行制冷工况进行了测试分析。结果表明:地源热泵运行稳定,该建筑地源热泵实测机组性能系数(Coefficient of Performance,COP)可达4.4以上,地源热泵实测系统制冷能效比(Energy Efficiency Ratio,EER)可达3.5以上,地源热泵机组的负载率为62%;夏季运行时,与普通空调相比可节约运行费用约1.3×104元,经济效益和环境效益显著。
