Pub Date : 1900-01-01DOI: 10.55011/staiqc.2021.1205
V. K
{"title":"Critical Solution to Power Grid Problems Using Smart Grid –A Case Study on Karnataka Power Transmission Control Limited (KPTCL)","authors":"V. K","doi":"10.55011/staiqc.2021.1205","DOIUrl":"https://doi.org/10.55011/staiqc.2021.1205","url":null,"abstract":"","PeriodicalId":231409,"journal":{"name":"Sparklinglight Transactions on Artificial Intelligence and Quantum Computing","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122811556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.55011/staiqc.2022.2103
Bishwas Mishra, Abhishek Samanta
Deepfake image manipulation has achieved great attention in the previous year’s owing to brings solemn challenges from the public self-confidence. Forgery detection in face imaging has made considerable developments in detecting manipulated images. However, there is still a need for an efficient deepfake detection approach in complex background environments. This paper applies the state-of-the-art quantum transfer learning approach for classifying deepfake images from original face images. The proposed model comprises classical pre-trained ResNet-18 and quantum neural network layers that provide efficient features extraction to learn the different patterns of the deepfake face images. The proposed model is validated on a real-world deepfake dataset created using commercial software. An accuracy of 96.1 % was obtained.
{"title":"Quantum Transfer Learning Approach for Deepfake Detection","authors":"Bishwas Mishra, Abhishek Samanta","doi":"10.55011/staiqc.2022.2103","DOIUrl":"https://doi.org/10.55011/staiqc.2022.2103","url":null,"abstract":"Deepfake image manipulation has achieved great attention in the previous year’s owing to brings solemn challenges from the public self-confidence. Forgery detection in face imaging has made considerable developments in detecting manipulated images. However, there is still a need for an efficient deepfake detection approach in complex background environments. This paper applies the state-of-the-art quantum transfer learning approach for classifying deepfake images from original face images. The proposed model comprises classical pre-trained ResNet-18 and quantum neural network layers that provide efficient features extraction to learn the different patterns of the deepfake face images. The proposed model is validated on a real-world deepfake dataset created using commercial software. An accuracy of 96.1 % was obtained.","PeriodicalId":231409,"journal":{"name":"Sparklinglight Transactions on Artificial Intelligence and Quantum Computing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121451834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.55011/staiqc.2022.2105
Sourav Kumar Bhoi, K. Prasad. K, Rajermani Thinakaran
Rice is an important food in our day-to-day life. It has rich sources of carbohydrates that are highly essential for body growth and development. Rice is an important crop in agriculture, where it enhances a country’s economy. However, if rice plants arediseased and not monitored regularly then the crop in the field is wasted and it reduces the proper production rate. Therefore, there should be a mechanism which regularly monitors the crop in a field to detect any disease to rice plant. In this paper, a framework is proposed for identification of rice leaf disease using IoT based Unmanned Aerial Vehicle (UAV) system. Here, the UAV monitors an entire field, capture the images and sends the images to the machine intelligent cloud for detection of rice leaf diseases. The cloud is installed with a proposed stacking classifier that classify the diseased rice plant images received from UAV into different categories. The dataset of these rice leaf diseases is collected from Kaggle source. The performance of the stacking classifier installed at the cloud is evaluated using Python based Orange 3.26 tool. It is observed form the results that stacking classifier outperforms the conventional machine learning models in detecting the actual disease with a classification accuracy (CA) of 86.7%.
{"title":"A Machine Intelligent Framework for Detection of Rice Leaf Diseases in Field Using IoT Based Unmanned Aerial Vehicle System","authors":"Sourav Kumar Bhoi, K. Prasad. K, Rajermani Thinakaran","doi":"10.55011/staiqc.2022.2105","DOIUrl":"https://doi.org/10.55011/staiqc.2022.2105","url":null,"abstract":"Rice is an important food in our day-to-day life. It has rich sources of carbohydrates that are highly essential for body growth and development. Rice is an important crop in agriculture, where it enhances a country’s economy. However, if rice plants arediseased and not monitored regularly then the crop in the field is wasted and it reduces the proper production rate. Therefore, there should be a mechanism which regularly monitors the crop in a field to detect any disease to rice plant. In this paper, a framework is proposed for identification of rice leaf disease using IoT based Unmanned Aerial Vehicle (UAV) system. Here, the UAV monitors an entire field, capture the images and sends the images to the machine intelligent cloud for detection of rice leaf diseases. The cloud is installed with a proposed stacking classifier that classify the diseased rice plant images received from UAV into different categories. The dataset of these rice leaf diseases is collected from Kaggle source. The performance of the stacking classifier installed at the cloud is evaluated using Python based Orange 3.26 tool. It is observed form the results that stacking classifier outperforms the conventional machine learning models in detecting the actual disease with a classification accuracy (CA) of 86.7%.","PeriodicalId":231409,"journal":{"name":"Sparklinglight Transactions on Artificial Intelligence and Quantum Computing","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134159906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.55011/staiqc.2021.1204
Ashwaq Mahfoodh Alrawahi
{"title":"A Systematic Study on Role of Big Data in Education","authors":"Ashwaq Mahfoodh Alrawahi","doi":"10.55011/staiqc.2021.1204","DOIUrl":"https://doi.org/10.55011/staiqc.2021.1204","url":null,"abstract":"","PeriodicalId":231409,"journal":{"name":"Sparklinglight Transactions on Artificial Intelligence and Quantum Computing","volume":"660 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132160582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.55011/staiqc.2022.2201
Vyshak R, Abdul Shareef Pallivalappil
We are living in the world of technology where we share our messages to the sender via several messaging applications. While we share the information, we are not aware about how secure our messages are and whether any person can hack the private messages or not. It is obvious when the messaging applications with no security pose great risk to our private information. Cryptography is a technique which is used to hide the information in the form of encryption. This preserves confidentiality, integrity and availability and also provides security and privacy of data to the users. In this study, wehave developed a simple approach with an additional layer of security to be added over the Caesar Cipher to enhance the security that can be incorporated with messaging applications.
{"title":"A Novel Approach to Strengthen Additional Layer of Security to Caesar Cipher","authors":"Vyshak R, Abdul Shareef Pallivalappil","doi":"10.55011/staiqc.2022.2201","DOIUrl":"https://doi.org/10.55011/staiqc.2022.2201","url":null,"abstract":"We are living in the world of technology where we share our messages to the sender via several messaging applications. While we share the information, we are not aware about how secure our messages are and whether any person can hack the private messages or not. It is obvious when the messaging applications with no security pose great risk to our private information. Cryptography is a technique which is used to hide the information in the form of encryption. This preserves confidentiality, integrity and availability and also provides security and privacy of data to the users. In this study, wehave developed a simple approach with an additional layer of security to be added over the Caesar Cipher to enhance the security that can be incorporated with messaging applications.","PeriodicalId":231409,"journal":{"name":"Sparklinglight Transactions on Artificial Intelligence and Quantum Computing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126340371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.55011/staiqc.2022.2101
S. S
{"title":"Comparative Analysis of AODV and Optimal Residual Energy Selection AODV Protocol for MANET","authors":"S. S","doi":"10.55011/staiqc.2022.2101","DOIUrl":"https://doi.org/10.55011/staiqc.2022.2101","url":null,"abstract":"","PeriodicalId":231409,"journal":{"name":"Sparklinglight Transactions on Artificial Intelligence and Quantum Computing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130462484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.55011/staiqc.2021.1101
Taheya AliSalim Al Habsi, Vishal Dattana
{"title":"A Study on Future Perspectives of Healthcare Data Analytics Using Internet of Things","authors":"Taheya AliSalim Al Habsi, Vishal Dattana","doi":"10.55011/staiqc.2021.1101","DOIUrl":"https://doi.org/10.55011/staiqc.2021.1101","url":null,"abstract":"","PeriodicalId":231409,"journal":{"name":"Sparklinglight Transactions on Artificial Intelligence and Quantum Computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130344607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.55011/staiqc.2021.1201
Geetha Poornima K, Vinayachandra, R. M., Bishwas Mishra
{"title":"Use of Supervised Learning Algorithms in Predictive Analytics","authors":"Geetha Poornima K, Vinayachandra, R. M., Bishwas Mishra","doi":"10.55011/staiqc.2021.1201","DOIUrl":"https://doi.org/10.55011/staiqc.2021.1201","url":null,"abstract":"","PeriodicalId":231409,"journal":{"name":"Sparklinglight Transactions on Artificial Intelligence and Quantum Computing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125067955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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