In object detection,spatial knowledge assisted systems are effective.Object detection is a main and challenging issue to analyze object-related information.Several existing object detection techniques were developed t...In object detection,spatial knowledge assisted systems are effective.Object detection is a main and challenging issue to analyze object-related information.Several existing object detection techniques were developed to consider the object detection problem as a classification problem to perform feature selection and classification.But these techniques still face,less computational efficiency and high time consumption.This paper resolves the above limitations using the Fuzzy Tversky index Ontology-based Multi-Layer Perception method which improves the accuracy of object detection with minimum time.The proposed method uses a multilayer forfinding the similarity score.A fuzzy membership function is used to validate the score for predicting the burned and non-burned zone.Experimental assessment is performed with different factors such as classification rate,time complexity,error rate,space complexity,and precision by using the forestfire dataset.The results show that this novel technique can help to improve the classification rate and reduce the time and space complexity as well as error rate than the conventional methods.展开更多
Different efforts have been undertaken to customizing a security and privacy concern in clouddata access. Therefore, the security measures are reliable and the data access was verified as themajor problem in the cloud...Different efforts have been undertaken to customizing a security and privacy concern in clouddata access. Therefore, the security measures are reliable and the data access was verified as themajor problem in the cloud environment. To overcome this problem, we proposed an efficientdata access control using optimized homomorphic encryption (HE). Because users outsourcetheir sensitive information to cloud providers, data security and access control is one of themost difficult ongoing cloud computing research projects. Existing solutions that rely on cryptographictechnologies to address these security issues result in significant complexity for bothdata and cloud service providers. The experimental results show that the key generation is 7.6%decreased by HE and 14.14% less than the proposed method. The encryption time is 11.34% lessthan the optimized HE and 23.28% decreased by ECC. The decryption time is 13.18% and 24.07%when compared with HE and ECC respectively.展开更多
文摘In object detection,spatial knowledge assisted systems are effective.Object detection is a main and challenging issue to analyze object-related information.Several existing object detection techniques were developed to consider the object detection problem as a classification problem to perform feature selection and classification.But these techniques still face,less computational efficiency and high time consumption.This paper resolves the above limitations using the Fuzzy Tversky index Ontology-based Multi-Layer Perception method which improves the accuracy of object detection with minimum time.The proposed method uses a multilayer forfinding the similarity score.A fuzzy membership function is used to validate the score for predicting the burned and non-burned zone.Experimental assessment is performed with different factors such as classification rate,time complexity,error rate,space complexity,and precision by using the forestfire dataset.The results show that this novel technique can help to improve the classification rate and reduce the time and space complexity as well as error rate than the conventional methods.
文摘Different efforts have been undertaken to customizing a security and privacy concern in clouddata access. Therefore, the security measures are reliable and the data access was verified as themajor problem in the cloud environment. To overcome this problem, we proposed an efficientdata access control using optimized homomorphic encryption (HE). Because users outsourcetheir sensitive information to cloud providers, data security and access control is one of themost difficult ongoing cloud computing research projects. Existing solutions that rely on cryptographictechnologies to address these security issues result in significant complexity for bothdata and cloud service providers. The experimental results show that the key generation is 7.6%decreased by HE and 14.14% less than the proposed method. The encryption time is 11.34% lessthan the optimized HE and 23.28% decreased by ECC. The decryption time is 13.18% and 24.07%when compared with HE and ECC respectively.
