Pub Date : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193280
Aravind Karrothu, B. Brindavathi, Chunduru Anilkumar
Till date, all the fuzzy identity-based encryption (IBE) cryptosystems for generating public keys used biometrics namely finger print, iris biometric identification, voice-based identification, and other set of identification types. This work is a concept for combining both fuzzy IBE system with human odor thresholds as identities. Naturally human body develops a one-inch layer of odor on skin, which will be used as identity for public keys generation and by using sample-left algorithm the size of public keys is minimized.
{"title":"New Fuzzy IBE System using Odor Detection","authors":"Aravind Karrothu, B. Brindavathi, Chunduru Anilkumar","doi":"10.1109/ICESC57686.2023.10193280","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193280","url":null,"abstract":"Till date, all the fuzzy identity-based encryption (IBE) cryptosystems for generating public keys used biometrics namely finger print, iris biometric identification, voice-based identification, and other set of identification types. This work is a concept for combining both fuzzy IBE system with human odor thresholds as identities. Naturally human body develops a one-inch layer of odor on skin, which will be used as identity for public keys generation and by using sample-left algorithm the size of public keys is minimized.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122717373","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}
The objective of this work is to propose the use of FarmO’Cart, a cutting-edge online marketing platform, as an effective solution to modernize conventional agricultural trading practices by facilitating an electronic exchange that links farmers, retailers, and consumers. The platform provides an option to directly sell or buy agricultural products without the involvement of any middlemen, thus allowing farmers to benefit from their crop production by generating 15-20% returns and reducing the debt ratio among farmers and their suicide rate. This proposed solution, FarmO'Cart, integrates a range of innovative features designed like a multilingual voice assistant, powered by advanced ALAN AI (Actionable Artificial Intelligence) technology, enabling farmers to interact with the platform in their native language and revolutionize traditional agricultural trading practices. Farmers can put their queries or ask for assistance by simply speaking out in their native languages. The platform is also accessible in 130+ languages through the integration of the Google Translate API (Application Programming Interface), ensuring a truly global reach. These features make the proposed solution more usable for the farmer community who may not be able to understand international languages or English in general. The Bcrypt’s hashing algorithm was leveraged to provide enhanced security for user data and passwords and the incorporation of salted hashing and a variable cost factor adds robustness to thwart brute-force attacks and password-cracking attempts. By employing these cryptographic techniques, the platform ensures effective protection of sensitive information. The FarmO’Cart also offers a community platform for farmers to connect and collaborate with Agri-experts & fellow farmers to improve productivity and profitability.
{"title":"FarmO’Cart: Multilingual Voice-Assisted Machine Learning Based real-time price Prediction to Enhance Agricultural Income","authors":"Aastha Patel, Lina Khedikar, Manasi Lokakshi, Sarika Khandelwal","doi":"10.1109/ICESC57686.2023.10193010","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193010","url":null,"abstract":"The objective of this work is to propose the use of FarmO’Cart, a cutting-edge online marketing platform, as an effective solution to modernize conventional agricultural trading practices by facilitating an electronic exchange that links farmers, retailers, and consumers. The platform provides an option to directly sell or buy agricultural products without the involvement of any middlemen, thus allowing farmers to benefit from their crop production by generating 15-20% returns and reducing the debt ratio among farmers and their suicide rate. This proposed solution, FarmO'Cart, integrates a range of innovative features designed like a multilingual voice assistant, powered by advanced ALAN AI (Actionable Artificial Intelligence) technology, enabling farmers to interact with the platform in their native language and revolutionize traditional agricultural trading practices. Farmers can put their queries or ask for assistance by simply speaking out in their native languages. The platform is also accessible in 130+ languages through the integration of the Google Translate API (Application Programming Interface), ensuring a truly global reach. These features make the proposed solution more usable for the farmer community who may not be able to understand international languages or English in general. The Bcrypt’s hashing algorithm was leveraged to provide enhanced security for user data and passwords and the incorporation of salted hashing and a variable cost factor adds robustness to thwart brute-force attacks and password-cracking attempts. By employing these cryptographic techniques, the platform ensures effective protection of sensitive information. The FarmO’Cart also offers a community platform for farmers to connect and collaborate with Agri-experts & fellow farmers to improve productivity and profitability.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125172077","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193333
S. Ramya, Dr T. Vijayaraghavan, D. Kalaivani
In low- and middle-income nations today, diabetes affects the majority of the population, according to a World Health organization (WHO) research. The WHO report suggested that 80% of the deaths would be due to the diabetes from 2016 to 2030. However, the current method continues to provide findings that are erroneous, which has a substantial negative impact on performance. To overcome the abovementioned issue, in this work, Random Forest (RF) algorithm and Fine tuned K-Nearest Neighbor (FKNN) classifier algorithm is proposed. Pre-processing, feature selection, and classification are the three primary stages of this project. Initially, preprocessing is performing for improving the final dataset results more accurately. Preprocessing is the process of cleaning the database into correct format. In order to choose more relevant and useful data from the dataset, the feature selection is then carried out utilizing the RF algorithm. It also minimizes the risk of over fitting with minimum features. Finally, diabetic prediction and classification is done by using FKNN classifier algorithm is used for categorizing items in the feature space based on training samples that are the most similar to the objects being classified. According to the experimental results, the suggested RF+FKNN method outperforms the current algorithms in accuracy, precision, recall, and f-measure.
{"title":"Diabetic Prediction using Feature Selection based Random Forest and Fine Tuned K-Nearest Neighbor Classifier Algorithm-A Design Thinking Approach","authors":"S. Ramya, Dr T. Vijayaraghavan, D. Kalaivani","doi":"10.1109/ICESC57686.2023.10193333","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193333","url":null,"abstract":"In low- and middle-income nations today, diabetes affects the majority of the population, according to a World Health organization (WHO) research. The WHO report suggested that 80% of the deaths would be due to the diabetes from 2016 to 2030. However, the current method continues to provide findings that are erroneous, which has a substantial negative impact on performance. To overcome the abovementioned issue, in this work, Random Forest (RF) algorithm and Fine tuned K-Nearest Neighbor (FKNN) classifier algorithm is proposed. Pre-processing, feature selection, and classification are the three primary stages of this project. Initially, preprocessing is performing for improving the final dataset results more accurately. Preprocessing is the process of cleaning the database into correct format. In order to choose more relevant and useful data from the dataset, the feature selection is then carried out utilizing the RF algorithm. It also minimizes the risk of over fitting with minimum features. Finally, diabetic prediction and classification is done by using FKNN classifier algorithm is used for categorizing items in the feature space based on training samples that are the most similar to the objects being classified. According to the experimental results, the suggested RF+FKNN method outperforms the current algorithms in accuracy, precision, recall, and f-measure.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125315138","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193521
K. Rajeshwaran, S. S. Keertanaa, S. Lidharshana, S. Madhumitha
Every year, traffic accidents involving vehicles result in hundreds of fatalities, serious injuries, and significant material losses. The primary causes of vehicular traffic accidents are infractions of traffic laws. Hence, having a reliable method of identifying violations will result in a decrease in traffic accidents and a reliable traffic control system. The vehicle environment has become one of the hottest study topics for the communications sector as a result of recent developments in telecommunications, computing, and sensor technologies. Computer networking researchers have proposed a new wireless networking concept called Vehicular Ad hoc Network (VANET), which can increase passenger safety and provide “efficient” road and policy monitoring. This concept aims to reduce the high number of vehicular traffic accidents, improve safety, and manage traffic control systems with high and reliable efficiency. Future VANET-based vehicle applications will include everything from transport automation systems to entertainment and comfort-based ones, making roads safer and better structured.
{"title":"Vehicle-to-Vehicle Communication using VANET","authors":"K. Rajeshwaran, S. S. Keertanaa, S. Lidharshana, S. Madhumitha","doi":"10.1109/ICESC57686.2023.10193521","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193521","url":null,"abstract":"Every year, traffic accidents involving vehicles result in hundreds of fatalities, serious injuries, and significant material losses. The primary causes of vehicular traffic accidents are infractions of traffic laws. Hence, having a reliable method of identifying violations will result in a decrease in traffic accidents and a reliable traffic control system. The vehicle environment has become one of the hottest study topics for the communications sector as a result of recent developments in telecommunications, computing, and sensor technologies. Computer networking researchers have proposed a new wireless networking concept called Vehicular Ad hoc Network (VANET), which can increase passenger safety and provide “efficient” road and policy monitoring. This concept aims to reduce the high number of vehicular traffic accidents, improve safety, and manage traffic control systems with high and reliable efficiency. Future VANET-based vehicle applications will include everything from transport automation systems to entertainment and comfort-based ones, making roads safer and better structured.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129697758","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10192933
Angel Swastik Duggal, A. Gehlot, P. Malik, Nitasha Bisht, Rajesh Singh
Galvanic taste modulation is the practice of altering the sensation of taste using electrical stimuli of a low magnitude. This research study describes the procedure of building a signal generator that specifically targets low-power signal generation for application over an individual’s buccal peripheries. Using this custom system, it would be feasible to study the correlation between taste profile and wave shape of the continuous electro stimulus. Additionally, it would also be possible to cross-quantize the stimulus of taste using VI units. Upon implementation of this technology within the domain of Augmented Reality and biomedical systems, the use cases include dietary salt reduction, experimental treatment of Ageusia etc. If explored in depth, galvanic taste modulation could essentially extrapolate itself into a subdomain of food technology as an electroculinary extension.
{"title":"A Signal Generation System for Galvanic Taste Modulation using ATmega328p Microcontroller","authors":"Angel Swastik Duggal, A. Gehlot, P. Malik, Nitasha Bisht, Rajesh Singh","doi":"10.1109/ICESC57686.2023.10192933","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10192933","url":null,"abstract":"Galvanic taste modulation is the practice of altering the sensation of taste using electrical stimuli of a low magnitude. This research study describes the procedure of building a signal generator that specifically targets low-power signal generation for application over an individual’s buccal peripheries. Using this custom system, it would be feasible to study the correlation between taste profile and wave shape of the continuous electro stimulus. Additionally, it would also be possible to cross-quantize the stimulus of taste using VI units. Upon implementation of this technology within the domain of Augmented Reality and biomedical systems, the use cases include dietary salt reduction, experimental treatment of Ageusia etc. If explored in depth, galvanic taste modulation could essentially extrapolate itself into a subdomain of food technology as an electroculinary extension.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128254107","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193561
Dr Jai Kishan Karahyla, Neelam Sharma, Sushant Chamoli, Dr Anil Shirgire, Ravi Kant, Amit Chauhan
Bitcoin is a rapidly growing but extremely risky cryptocurrency. It marks a watershed moment in the history of cash. These days, digital currency is preferred to actual money. Bitcoin has decentralized authority and placed it in the hands of its users. Many people are joining the largest and most well-known Bitcoin mining pools as the risk of working alone is too great. In order to enhance their chances of creating the next block in the Bitcoins blockchain and decrease the mining reward volatility, users can band together to form Bitcoin pools. This tendency toward consolidation may also be seen in the rise of large-scale mining farms equipped with powerful mining resources and speedy processing capability. Because of the risk of a 51% assault, this pattern shows that Bitcoin’s pure, decentralized protocol is moving toward greater centralization in its distribution network. Not to be overlooked is the resulting centralization of the bitcoin network as a result of cloud wallets making it simple for new users to join. Because of the easily hackable nature of Bitcoin technologies, this could lead to a wide range of security vulnerabilities. The proposed approach uses normalization and filling missing values in preprocessing, PCA for feature Extraction and finally training the model using LSTM-DNN Models. The proposed approach outperforms other two models such as CNN and DNN.
{"title":"Predicting Price Direction of Bitcoin based on Hybrid Model of LSTM and Dense Neural Network Approach","authors":"Dr Jai Kishan Karahyla, Neelam Sharma, Sushant Chamoli, Dr Anil Shirgire, Ravi Kant, Amit Chauhan","doi":"10.1109/ICESC57686.2023.10193561","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193561","url":null,"abstract":"Bitcoin is a rapidly growing but extremely risky cryptocurrency. It marks a watershed moment in the history of cash. These days, digital currency is preferred to actual money. Bitcoin has decentralized authority and placed it in the hands of its users. Many people are joining the largest and most well-known Bitcoin mining pools as the risk of working alone is too great. In order to enhance their chances of creating the next block in the Bitcoins blockchain and decrease the mining reward volatility, users can band together to form Bitcoin pools. This tendency toward consolidation may also be seen in the rise of large-scale mining farms equipped with powerful mining resources and speedy processing capability. Because of the risk of a 51% assault, this pattern shows that Bitcoin’s pure, decentralized protocol is moving toward greater centralization in its distribution network. Not to be overlooked is the resulting centralization of the bitcoin network as a result of cloud wallets making it simple for new users to join. Because of the easily hackable nature of Bitcoin technologies, this could lead to a wide range of security vulnerabilities. The proposed approach uses normalization and filling missing values in preprocessing, PCA for feature Extraction and finally training the model using LSTM-DNN Models. The proposed approach outperforms other two models such as CNN and DNN.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128645311","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10192978
A. Joshi, V. Subedha
Distributed computing through topology control involves making changes to the underlying network (modeled as a graph) to decrease the cost of distributed algorithms when executed across the modified networks. Topology construction builds reduced topology and topology maintenance adopts the reduced topology when the current topology is no longer optimal. This study makes major contributions to topology control by constructing new topologies named sparkle topologies using a ring topology, structured web topology, sun topology, and star topology. The efficiency of the sparkle topologies is checked by calculating the reliability using Wiener Index and data transfer using Cisco packet simulation. Data transmission times, the number of hops required, and the number of potential failure points are all reduced in sparkle topologies compared to ring topologies.
{"title":"Reliability and Packet Transfer Efficiency of Sparkle Topologies","authors":"A. Joshi, V. Subedha","doi":"10.1109/ICESC57686.2023.10192978","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10192978","url":null,"abstract":"Distributed computing through topology control involves making changes to the underlying network (modeled as a graph) to decrease the cost of distributed algorithms when executed across the modified networks. Topology construction builds reduced topology and topology maintenance adopts the reduced topology when the current topology is no longer optimal. This study makes major contributions to topology control by constructing new topologies named sparkle topologies using a ring topology, structured web topology, sun topology, and star topology. The efficiency of the sparkle topologies is checked by calculating the reliability using Wiener Index and data transfer using Cisco packet simulation. Data transmission times, the number of hops required, and the number of potential failure points are all reduced in sparkle topologies compared to ring topologies.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125078737","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193384
Kaligotla Ravi Kumar, C. Sivakumar
the capacity optimization framework for mobile nodes in ultra dense cloud networks is a process that aims to optimize the capacity of devices deployed in areas with a high concentration of cloud resources. The objective is to maximize the total throughput and connection quality of the mobile node connections. To achieve this, a thorough analysis of the current configuration and usage patterns of the mobile nodes must be undertaken. This involves a comprehensive review of the physical, application, and network layer parameters. From there, capacity optimization techniques such as load balancing, system optimization, and bandwidth estimation can be applied. These techniques foster the efficient use of available resources, reduce latency, and address shortcomings of current approaches to mobile node throughput. Optimizing the mobile node capacity in ultra dense clouds will result in improved user experience, better access quality, and higher industry adoption of cloud technologies.
{"title":"An Improved Capacity Optimization Framework for Mobile Nodes in Ultra Dense Cloud Networks","authors":"Kaligotla Ravi Kumar, C. Sivakumar","doi":"10.1109/ICESC57686.2023.10193384","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193384","url":null,"abstract":"the capacity optimization framework for mobile nodes in ultra dense cloud networks is a process that aims to optimize the capacity of devices deployed in areas with a high concentration of cloud resources. The objective is to maximize the total throughput and connection quality of the mobile node connections. To achieve this, a thorough analysis of the current configuration and usage patterns of the mobile nodes must be undertaken. This involves a comprehensive review of the physical, application, and network layer parameters. From there, capacity optimization techniques such as load balancing, system optimization, and bandwidth estimation can be applied. These techniques foster the efficient use of available resources, reduce latency, and address shortcomings of current approaches to mobile node throughput. Optimizing the mobile node capacity in ultra dense clouds will result in improved user experience, better access quality, and higher industry adoption of cloud technologies.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127275791","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193438
Zarif Khudoykulov, Abdukodir Karimov, R. Abdurakhmanov, Mirkomil Mirzabekov
An authentication mechanism plays an essential role in access control. Authentication methods vary depending on the environment used, and many authentication methods are designed for cloud computing systems. This research paper examines the current authentication techniques employed in cloud computing systems and highlights unresolved issues and challenges that exist in this domain.
{"title":"Authentication in Cloud Computing: Open Problems","authors":"Zarif Khudoykulov, Abdukodir Karimov, R. Abdurakhmanov, Mirkomil Mirzabekov","doi":"10.1109/ICESC57686.2023.10193438","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193438","url":null,"abstract":"An authentication mechanism plays an essential role in access control. Authentication methods vary depending on the environment used, and many authentication methods are designed for cloud computing systems. This research paper examines the current authentication techniques employed in cloud computing systems and highlights unresolved issues and challenges that exist in this domain.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122390803","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10192582
A.Naveen Kumaar, J. Akilandeswari, P. R. Mathangi, P. Kavya, S. Dhanush Prabhu, V. Ashwin Kumar
Computers are now considered as the daily necessities for both mankind and medical science. A doctor examines a patient, with the physical interaction and then with all the reports like scans, X-rays, blood reports, and so on. In case of Radiologist, they can’t frequently touch the screen or buttons while browsing the radiology report images, this may lead to radioactive contamination. A gesture-based browsing method is developed to overcome this issue by making the radiologist to browse the images without any close interactions with the device. An interface is provided for the surgeon where their hand-gestures are used for safe browsing of radiology report images using recent hand-gesture recognition methodologies. Further the accuracy of the system is increased by the proposed modified Convolutional Neural Network technique which uses De-noising Auto Encoder based CNN (DAECNN) to identify the hand-gesture made by the radiologist. A detailed study is made on the recent hand-gesture recognition methodologies used on secure browsing of radiology images based on accuracy. The proposed technique is compared with the existing deep learning methodologies such as CNN, Adaline (Adaptive Linear Neuron), DAE (Denoising Autoencoder) and the performances are examined. The findings of the research show that the DAECNN methodology outperforms the currently used classification techniques.
{"title":"Secure radiology image browsing tool improvised using Denoising Autoencoder with Convolutional Neural Network (DAECNN)","authors":"A.Naveen Kumaar, J. Akilandeswari, P. R. Mathangi, P. Kavya, S. Dhanush Prabhu, V. Ashwin Kumar","doi":"10.1109/ICESC57686.2023.10192582","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10192582","url":null,"abstract":"Computers are now considered as the daily necessities for both mankind and medical science. A doctor examines a patient, with the physical interaction and then with all the reports like scans, X-rays, blood reports, and so on. In case of Radiologist, they can’t frequently touch the screen or buttons while browsing the radiology report images, this may lead to radioactive contamination. A gesture-based browsing method is developed to overcome this issue by making the radiologist to browse the images without any close interactions with the device. An interface is provided for the surgeon where their hand-gestures are used for safe browsing of radiology report images using recent hand-gesture recognition methodologies. Further the accuracy of the system is increased by the proposed modified Convolutional Neural Network technique which uses De-noising Auto Encoder based CNN (DAECNN) to identify the hand-gesture made by the radiologist. A detailed study is made on the recent hand-gesture recognition methodologies used on secure browsing of radiology images based on accuracy. The proposed technique is compared with the existing deep learning methodologies such as CNN, Adaline (Adaptive Linear Neuron), DAE (Denoising Autoencoder) and the performances are examined. The findings of the research show that the DAECNN methodology outperforms the currently used classification techniques.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126695754","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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