Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544802
V. Shoba, R. Parameswari
The process of Big data storage has become challenging due to the expansion of extensive data; data providers will offer encrypted data and upload to Big data. However, the data exchange mechanism is unable to accommodate encrypted data. Particularly when a large number of users share the scalable data, the scalability becomes extremely limited. Using a contemporary privacy protection system to solve this issue and ensure the security of encrypted data, as well as partially homomorphic re-encryption and decryption (PHRED). This scheme has the flexibility to share data by ensuring user's privacy with partially trusted Big Data. It can access to strong unforgeable scheme it make the transmuted cipher text have public and private key verification combined identity based Augmented Homomorphic Re Encryption Decryption(AHRED) on paillier crypto System with Laplacian noise filter the performance of the data provider for privacy preserving big data.
{"title":"Data Security and Privacy Preserving with Augmented Homomorphic Re-Encryption Decryption (AHRED) Algorithm in Big Data Analytics","authors":"V. Shoba, R. Parameswari","doi":"10.1109/ICIRCA51532.2021.9544802","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544802","url":null,"abstract":"The process of Big data storage has become challenging due to the expansion of extensive data; data providers will offer encrypted data and upload to Big data. However, the data exchange mechanism is unable to accommodate encrypted data. Particularly when a large number of users share the scalable data, the scalability becomes extremely limited. Using a contemporary privacy protection system to solve this issue and ensure the security of encrypted data, as well as partially homomorphic re-encryption and decryption (PHRED). This scheme has the flexibility to share data by ensuring user's privacy with partially trusted Big Data. It can access to strong unforgeable scheme it make the transmuted cipher text have public and private key verification combined identity based Augmented Homomorphic Re Encryption Decryption(AHRED) on paillier crypto System with Laplacian noise filter the performance of the data provider for privacy preserving big data.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115027148","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9545082
Rakesh Kumar, Meenu Gupta, Suyash Shukla, R. Yadav
Diligent Traffic Enforcement is a major problem throughout India, often focusing on corruption and abuse; is the subject of major changes initiated by senior management of all traffic police institutions in India. Therefore, this paper proposes an effective e-challan production strategy using OCR (Optical Character recognition) where the challan ends using the online application. Scanning different number plates and downloading facts from the database and producing E-Challan. The E-Challan is a web platform that provides various types of support for monitoring and managing the traffic penalties and it also helps the users to overcome the problems that they face while paying for their challan during the traffic time. The E-challan Application is the interaction between HD Cameras and drivers with the use of an online platform. The driver who will breach the traffic rule, vehicle's number plate snapshot is captured automatically by the HD Camera located near a traffic light and traffic area through Image Processing technology and Artificial Intelligence, the software will automatically detect the vehicle owner for the penalty and then apply the suitable penalty against the vehicle owner in their account. With the help of this online prototype, the challan system becomes easy for the users by keeping it online.
{"title":"E-Challan Automation for RTO using OCR","authors":"Rakesh Kumar, Meenu Gupta, Suyash Shukla, R. Yadav","doi":"10.1109/ICIRCA51532.2021.9545082","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9545082","url":null,"abstract":"Diligent Traffic Enforcement is a major problem throughout India, often focusing on corruption and abuse; is the subject of major changes initiated by senior management of all traffic police institutions in India. Therefore, this paper proposes an effective e-challan production strategy using OCR (Optical Character recognition) where the challan ends using the online application. Scanning different number plates and downloading facts from the database and producing E-Challan. The E-Challan is a web platform that provides various types of support for monitoring and managing the traffic penalties and it also helps the users to overcome the problems that they face while paying for their challan during the traffic time. The E-challan Application is the interaction between HD Cameras and drivers with the use of an online platform. The driver who will breach the traffic rule, vehicle's number plate snapshot is captured automatically by the HD Camera located near a traffic light and traffic area through Image Processing technology and Artificial Intelligence, the software will automatically detect the vehicle owner for the penalty and then apply the suitable penalty against the vehicle owner in their account. With the help of this online prototype, the challan system becomes easy for the users by keeping it online.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115623868","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544792
C. Z. Basha, D. P. K. Reddy, S. Chand, Azmira Krishna
Augmented reality experience enables us to view real-world objects in 3D by overlapping real-world objects with digital 3d objects to provide a much-enhanced user experience. This paper explains and presents the ways to construct a 3D (3 Dimension) asset of the real world like cities, monuments, and other objects using blender and then the3D digital asset will be incorporated into our application. So that whenever our marker scans the object i.e., the 3D asset gets overlayed. The main idea of this concept is to experience real-world objects in the absence of real-world objects. Let us say that, a person wants to see the Eiffel tower and he/she searches it on Google. Now, the person could only see the images of Eiffel tower. To experience it in 3D he/she can use Google earth but it does not provide an original 3D experience. So, this is the point where augmented reality enters into the scene. The proposed research work has created a 3D asset by using a blender tool. Now, that asset will be imported and applied it to a marker. Whenever, this marker is scanned by using our application, the 3D effect of Eiffel tower will be overlayed on the screen. Augmented Reality is overlapping real-world objects with 3d objects. The main objective of augmented reality is that users cannot notice the discrepancy between augmented objects and real-world objects. AR is a wholly distinct technology, which helps our daily living and many other experiences so improved. It uses our most common hardware such as mobiles, cameras, etc. This makes this technology very beneficial and effortless to use. It is also a lot more different from VR in terms of hardware. But most of the purpose is the same.
{"title":"Augmented Reality Experience for Real-World Objects, Monuments, and Cities","authors":"C. Z. Basha, D. P. K. Reddy, S. Chand, Azmira Krishna","doi":"10.1109/ICIRCA51532.2021.9544792","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544792","url":null,"abstract":"Augmented reality experience enables us to view real-world objects in 3D by overlapping real-world objects with digital 3d objects to provide a much-enhanced user experience. This paper explains and presents the ways to construct a 3D (3 Dimension) asset of the real world like cities, monuments, and other objects using blender and then the3D digital asset will be incorporated into our application. So that whenever our marker scans the object i.e., the 3D asset gets overlayed. The main idea of this concept is to experience real-world objects in the absence of real-world objects. Let us say that, a person wants to see the Eiffel tower and he/she searches it on Google. Now, the person could only see the images of Eiffel tower. To experience it in 3D he/she can use Google earth but it does not provide an original 3D experience. So, this is the point where augmented reality enters into the scene. The proposed research work has created a 3D asset by using a blender tool. Now, that asset will be imported and applied it to a marker. Whenever, this marker is scanned by using our application, the 3D effect of Eiffel tower will be overlayed on the screen. Augmented Reality is overlapping real-world objects with 3d objects. The main objective of augmented reality is that users cannot notice the discrepancy between augmented objects and real-world objects. AR is a wholly distinct technology, which helps our daily living and many other experiences so improved. It uses our most common hardware such as mobiles, cameras, etc. This makes this technology very beneficial and effortless to use. It is also a lot more different from VR in terms of hardware. But most of the purpose is the same.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115643015","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544100
Ashutosh Upadhyay, K. S.
Computer vision mainly focuses on the automatic extraction, analysis, and understanding of useful information from a single image or video. On the other hand, authenticity is emerging as one of the primary requirements in today's world by developing a system for computer vision complexity. Generally, two robust techniques such as age estimation and face recognition are required to maintain authenticity. In reality, fraud and scams are getting increased, so here this paper has proposed a new combined model for face recognition and age prediction. Face recognition has been implemented and presented in this paper by using a Deep Neural Network. The authenticity problem can be handled by using either facial recognition or age prediction alone; this study has presented a method that employs both of them together to enhance the system's robustness. So, first, this model detects the person's face, and then it predicts the person's age. If the individual is eligible to view the information or perform a task, their access will be limited; otherwise, their access will be restricted. So it helps to solve two difficulties in this case: the person's identification cannot be faked, and their age is also confirmed by the system. (CNN for the face, and mention technique for the age.)
{"title":"AI-based content filtering system using an age prediction algorithm","authors":"Ashutosh Upadhyay, K. S.","doi":"10.1109/ICIRCA51532.2021.9544100","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544100","url":null,"abstract":"Computer vision mainly focuses on the automatic extraction, analysis, and understanding of useful information from a single image or video. On the other hand, authenticity is emerging as one of the primary requirements in today's world by developing a system for computer vision complexity. Generally, two robust techniques such as age estimation and face recognition are required to maintain authenticity. In reality, fraud and scams are getting increased, so here this paper has proposed a new combined model for face recognition and age prediction. Face recognition has been implemented and presented in this paper by using a Deep Neural Network. The authenticity problem can be handled by using either facial recognition or age prediction alone; this study has presented a method that employs both of them together to enhance the system's robustness. So, first, this model detects the person's face, and then it predicts the person's age. If the individual is eligible to view the information or perform a task, their access will be limited; otherwise, their access will be restricted. So it helps to solve two difficulties in this case: the person's identification cannot be faked, and their age is also confirmed by the system. (CNN for the face, and mention technique for the age.)","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"22 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114105171","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9545009
Yashvi Desai, Naisha Shah, Vrushali Shah, P. Bhavathankar, Kaisar Katchi
Augmented reality has three principal features: combining the real world environment with the virtual world, real-time interaction for users, and accurate representation of 3D objects. Augmented Reality in E-commerce allows customers to view products or experience services in their physical space before purchasing the required items. Current online shopping services only allow customers to see 2D images of the products they are buying. This type of experience is not personalized and sometimes leads to bad shopping choices choices; the customers find it difficult to shop only with a static image view available. Customers cannot accurately predict whether the product they purchase will fit their home environment. This results in a lot of people returning or exchanging the things their purchases. AR resolves these issues. Thus, a method has been proposed for adding a virtual object in the real world by just using a real-time camera. The main aim of this paper is to provide user visualization of high resolution E-commerce products in a real environment.
{"title":"Markerless Augmented Reality based application for E-Commerce to Visualise 3D Content","authors":"Yashvi Desai, Naisha Shah, Vrushali Shah, P. Bhavathankar, Kaisar Katchi","doi":"10.1109/ICIRCA51532.2021.9545009","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9545009","url":null,"abstract":"Augmented reality has three principal features: combining the real world environment with the virtual world, real-time interaction for users, and accurate representation of 3D objects. Augmented Reality in E-commerce allows customers to view products or experience services in their physical space before purchasing the required items. Current online shopping services only allow customers to see 2D images of the products they are buying. This type of experience is not personalized and sometimes leads to bad shopping choices choices; the customers find it difficult to shop only with a static image view available. Customers cannot accurately predict whether the product they purchase will fit their home environment. This results in a lot of people returning or exchanging the things their purchases. AR resolves these issues. Thus, a method has been proposed for adding a virtual object in the real world by just using a real-time camera. The main aim of this paper is to provide user visualization of high resolution E-commerce products in a real environment.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114247802","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544701
Hejuan Chen
The proposed research study focuses on the leakage location system of the electric vehicle battery pack based on the Wavelet transform. Under the same equalization time, the equalization efficiency of the method that has been tested from the battery pack to the cell to the battery pack is 91.4%, and the overall equalization efficiency of this method is 93.8%. When the battery pack is in a discharging state, the equalization circuit module can complete the migration of the battery pack's power to the battery with the lowest terminal voltage or SOC. With the considerations of the mentioned features, this paper applies the wavelet model to construct the efficient location system. The proposed model is tested on the different scenarios with different data sets. The performance guides us that the accuracy of proposed model is much higher.
{"title":"Leakage Location System of Electric Vehicle Battery Pack Based on Wavelet Transform","authors":"Hejuan Chen","doi":"10.1109/ICIRCA51532.2021.9544701","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544701","url":null,"abstract":"The proposed research study focuses on the leakage location system of the electric vehicle battery pack based on the Wavelet transform. Under the same equalization time, the equalization efficiency of the method that has been tested from the battery pack to the cell to the battery pack is 91.4%, and the overall equalization efficiency of this method is 93.8%. When the battery pack is in a discharging state, the equalization circuit module can complete the migration of the battery pack's power to the battery with the lowest terminal voltage or SOC. With the considerations of the mentioned features, this paper applies the wavelet model to construct the efficient location system. The proposed model is tested on the different scenarios with different data sets. The performance guides us that the accuracy of proposed model is much higher.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116707253","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9545052
J. Ananthi, P. S. H. Jose
Recently, Wireless Body Area Networks (WBAN) have been increasingly significant in healthcare applications. It is derived from the wireless sensor network with biomedical sensors. The Internet of Things (IoT) has a huge impact on how medical data is received and transmitted to the right systems in healthcare applications. Security, fastest delivery, and energy consumption are major concerns in wireless body area networks. This research work focuses on the rapid data transmission between the patient and doctor using Unmanned Aerial Vehicles (UAV). There are five sensors that are analyzed as Heart rate monitoring sensor, Temperature sensor, Human motion sensor, Oximeter sensor, and Blood pressure sensor. For the fastest delivery, the sensed medical data was delivered utilizing unmanned aerial vehicles. This helps the patients in critical/emergencies to communicate the medical information to the doctor safely and securely. The experimental result examines various sensors attached to the Arduino IDE. The obtained results will be transmitted to the patients using unmanned aerial vehicles. These techniques help to improve the fastest communication for emergency condition patients.
{"title":"Implementation of IoT and UAV Based WBAN for healthcare applications","authors":"J. Ananthi, P. S. H. Jose","doi":"10.1109/ICIRCA51532.2021.9545052","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9545052","url":null,"abstract":"Recently, Wireless Body Area Networks (WBAN) have been increasingly significant in healthcare applications. It is derived from the wireless sensor network with biomedical sensors. The Internet of Things (IoT) has a huge impact on how medical data is received and transmitted to the right systems in healthcare applications. Security, fastest delivery, and energy consumption are major concerns in wireless body area networks. This research work focuses on the rapid data transmission between the patient and doctor using Unmanned Aerial Vehicles (UAV). There are five sensors that are analyzed as Heart rate monitoring sensor, Temperature sensor, Human motion sensor, Oximeter sensor, and Blood pressure sensor. For the fastest delivery, the sensed medical data was delivered utilizing unmanned aerial vehicles. This helps the patients in critical/emergencies to communicate the medical information to the doctor safely and securely. The experimental result examines various sensors attached to the Arduino IDE. The obtained results will be transmitted to the patients using unmanned aerial vehicles. These techniques help to improve the fastest communication for emergency condition patients.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116977443","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9545077
M. Ahmed, Rafeed Rahman, Shahriar Hossain, Shahnewaz Ali Mohammad
The brain tumor is a lethal illness that has endured innumerable individuals. Brain tumor causes abnormal growth of brain tissues, the tissues can be either malignant or non-malignant, but both are capable of causing long term harm and in about 95% cases can cause demise. Utilizing MRI (Magnetic resonance imaging) scans has become one of the meaningful techniques for identifying its existence in the human brain. Subsequent to getting the MRI filters these are physically investigated by experts to determine the presence of a brain tumor in a patient. Various specialists assessing MRI scans may result in outcomes that are not same; this happens because of the variance in forming evaluations from one professional to the next. Furthermore, because MRI scan analysis is a manual procedure, various people might make different mistakes. Based on the interpretations of the experts, two distinct MRI scans performed on the same patient may yield different findings. To make things simpler, reliable, and obtaining acquiring predictable outcomes for both specialists and non-specialists while performing assessment of MRI scans, this research work has presented deep learning strategies in the context of transfer learning models such as ResNet 50, ResNet 152 inception v3, VGG16 and also proposed Conv2d+SVM model to analyze MRI scans and determine the presence of a brain tumor. Also, this research work has utilized a dataset consisting of 253 images and then performed augmentation to increase the amount of data. After training, our model portrayed accuracy of 87.17% and 76.62% for ResNet 50, 99.28% and 88.24% for ResNet 152, 99.28% and 96.08% for inception v3, 99.78 and 86.27% for VGG16 and 92% and 78.3% for Conv2D+SVM in terms of training and validation respectively
{"title":"Brain Tumor Prediction by analyzing MRI using deep learning architectures","authors":"M. Ahmed, Rafeed Rahman, Shahriar Hossain, Shahnewaz Ali Mohammad","doi":"10.1109/ICIRCA51532.2021.9545077","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9545077","url":null,"abstract":"The brain tumor is a lethal illness that has endured innumerable individuals. Brain tumor causes abnormal growth of brain tissues, the tissues can be either malignant or non-malignant, but both are capable of causing long term harm and in about 95% cases can cause demise. Utilizing MRI (Magnetic resonance imaging) scans has become one of the meaningful techniques for identifying its existence in the human brain. Subsequent to getting the MRI filters these are physically investigated by experts to determine the presence of a brain tumor in a patient. Various specialists assessing MRI scans may result in outcomes that are not same; this happens because of the variance in forming evaluations from one professional to the next. Furthermore, because MRI scan analysis is a manual procedure, various people might make different mistakes. Based on the interpretations of the experts, two distinct MRI scans performed on the same patient may yield different findings. To make things simpler, reliable, and obtaining acquiring predictable outcomes for both specialists and non-specialists while performing assessment of MRI scans, this research work has presented deep learning strategies in the context of transfer learning models such as ResNet 50, ResNet 152 inception v3, VGG16 and also proposed Conv2d+SVM model to analyze MRI scans and determine the presence of a brain tumor. Also, this research work has utilized a dataset consisting of 253 images and then performed augmentation to increase the amount of data. After training, our model portrayed accuracy of 87.17% and 76.62% for ResNet 50, 99.28% and 88.24% for ResNet 152, 99.28% and 96.08% for inception v3, 99.78 and 86.27% for VGG16 and 92% and 78.3% for Conv2D+SVM in terms of training and validation respectively","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117142844","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544800
E. Zhang
Uterine fibroids are the most common benign tumors in gynecology, with high incidence rate and showing an increasing trend. Some uterine fibroids can lead to patients with prolonged menstrual cycle, increased menstrual volume, more severe cases will appear hemorrhagic anemia. Larger uterine fibroids will oppress the patient's pelvic cavity, so that patients have frequent urination, fecal discomfort, etc. This disease seriously affects women's life and health. This paper completes the requirement analysis and overall design of the disease data mining system. After that, the system is divided into data processing subsystem, algorithm calling subsystem, knowledge display subsystem, user management subsystem, as well as the realization technology, function modules and main process of the main functions of the system.
{"title":"Clinical Study on Fast Rehabilitation Program of Integrated Traditional Chinese and Western Medicine after Laparoscopic Hysterectomy based on Data Mining","authors":"E. Zhang","doi":"10.1109/ICIRCA51532.2021.9544800","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544800","url":null,"abstract":"Uterine fibroids are the most common benign tumors in gynecology, with high incidence rate and showing an increasing trend. Some uterine fibroids can lead to patients with prolonged menstrual cycle, increased menstrual volume, more severe cases will appear hemorrhagic anemia. Larger uterine fibroids will oppress the patient's pelvic cavity, so that patients have frequent urination, fecal discomfort, etc. This disease seriously affects women's life and health. This paper completes the requirement analysis and overall design of the disease data mining system. After that, the system is divided into data processing subsystem, algorithm calling subsystem, knowledge display subsystem, user management subsystem, as well as the realization technology, function modules and main process of the main functions of the system.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123184628","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 : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544607
Manojkumar. K, L. Sujihelen
Crowd behavioural analysis is an interesting and emerging domain in research, with incomplete set of activities, tasks and lack of intermediate cub-processes which are mandated for productive analysis. Since the domain is untapped to a major extent, the research carried out in the domain needs proper stages of operations. A proper taxonomy will direct the futuristic domains in the right track of processes and organization of intermediate tasks. This review paper intends to document the list of stages and processes, data collection, pipelining the sub-tasks, pre-emptive identification of supposed problems during the later stages in detection of crowd emotions and behavioural analysis. Deep learning techniques have been widely deployed to investigate the models of crowd analysis, anomaly detection, and look for meaningful insights and patterns from datasets. The Different models are investigated thoroughly for their respective understanding about the emotional aspects considered in the studies. Emotional characteristics when powered with crowd behavioural analysis and real world entities will deliver a promising solution for crime detections, anomaly detection and ensure a safer environment for nations. Video surveillance tools, datasets from crime datasets and various other factors contributed to the previous research works, models are now being designed to incorporate the best features of these models into one and thus achieve one fruitful model for continuous video analytics.
{"title":"Behavioural Analysis For Prospects In Crowd Emotion Sensing: A Survey","authors":"Manojkumar. K, L. Sujihelen","doi":"10.1109/ICIRCA51532.2021.9544607","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544607","url":null,"abstract":"Crowd behavioural analysis is an interesting and emerging domain in research, with incomplete set of activities, tasks and lack of intermediate cub-processes which are mandated for productive analysis. Since the domain is untapped to a major extent, the research carried out in the domain needs proper stages of operations. A proper taxonomy will direct the futuristic domains in the right track of processes and organization of intermediate tasks. This review paper intends to document the list of stages and processes, data collection, pipelining the sub-tasks, pre-emptive identification of supposed problems during the later stages in detection of crowd emotions and behavioural analysis. Deep learning techniques have been widely deployed to investigate the models of crowd analysis, anomaly detection, and look for meaningful insights and patterns from datasets. The Different models are investigated thoroughly for their respective understanding about the emotional aspects considered in the studies. Emotional characteristics when powered with crowd behavioural analysis and real world entities will deliver a promising solution for crime detections, anomaly detection and ensure a safer environment for nations. Video surveillance tools, datasets from crime datasets and various other factors contributed to the previous research works, models are now being designed to incorporate the best features of these models into one and thus achieve one fruitful model for continuous video analytics.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121561779","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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