Pub Date : 2023-05-18DOI: 10.1109/ACCESS57397.2023.10200876
S. Sreeja, Pooja Yadav, V. Asha, Prabhu Chodnekar, Sammit Prashant, Binju Saju, Arpana Prasad
Female anopheles mosquitoes transmit the highly contagious parasitical diseases. Animals as well as humans are harmed by this sickness. In the worst-case scenario, this illness could result in the patient's death if it is not adequately diagnosed in the early stages. It is exceedingly difficultly in confirming 0 the presence of ailment in industry owing towards a deficiency of exceedingly methodological competence. Cutting-edge this situation, data retrieval assistance is required for accurate and quick disease identification. With the aid of IT division buzzword know-hows like Machine Learning, Deep Learning, and Non-natural Acumen, modern IT sectors are working tirelessly to combat this sickness. If appropriately applied, these technologies will continue to be the backbone of healthcare as they have been in recent years. In order to determine if an organism is infected with a parasite or not, this study applies the Convolutional Neural Network (CNN) algorithm to a minuscule carbon copy of the contaminated blood cells. 15 out of 16 random photos can be accurately predicted by our suggested model, which achieved an accuracy of 95.23 percent.
{"title":"Parasitical Disease Prediction Model – a Deep Learning Based Approach","authors":"S. Sreeja, Pooja Yadav, V. Asha, Prabhu Chodnekar, Sammit Prashant, Binju Saju, Arpana Prasad","doi":"10.1109/ACCESS57397.2023.10200876","DOIUrl":"https://doi.org/10.1109/ACCESS57397.2023.10200876","url":null,"abstract":"Female anopheles mosquitoes transmit the highly contagious parasitical diseases. Animals as well as humans are harmed by this sickness. In the worst-case scenario, this illness could result in the patient's death if it is not adequately diagnosed in the early stages. It is exceedingly difficultly in confirming 0 the presence of ailment in industry owing towards a deficiency of exceedingly methodological competence. Cutting-edge this situation, data retrieval assistance is required for accurate and quick disease identification. With the aid of IT division buzzword know-hows like Machine Learning, Deep Learning, and Non-natural Acumen, modern IT sectors are working tirelessly to combat this sickness. If appropriately applied, these technologies will continue to be the backbone of healthcare as they have been in recent years. In order to determine if an organism is infected with a parasite or not, this study applies the Convolutional Neural Network (CNN) algorithm to a minuscule carbon copy of the contaminated blood cells. 15 out of 16 random photos can be accurately predicted by our suggested model, which achieved an accuracy of 95.23 percent.","PeriodicalId":345351,"journal":{"name":"2023 3rd International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128242400","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 : 2023-05-18DOI: 10.1109/ACCESS57397.2023.10200020
Anagha Prabhakaran, D. S. kumar
Structural vibrations have a great impact on civil structures. Most of the damage happening to structures that lead to a reduction in their life span is due to vibration. This vibration can be natural or man-made. This paper explains the importance of SHM(Structural health monitoring) and proposes a system for continuously monitoring the structural health status. The prototype consists of an ADXL-335 accelerometer, Arduino Uno, GPS (Global positioning system) and GSM (Global system for mobile communication). The functionalities of the system include detection of variation in the structural parameters, locating the position of the structure by means of GPS and sending the health status of the structure to authority where the GSM consists of a prioritized list of numbers. The paper also focuses on analyzing the dynamic parameters like acceleration and tilt angle in three modes: no vibration mode, normal vibration mode and collapse mode. Also analysis of time-domain features of vibration data in three modes are also analyzed.
{"title":"A Wireless Multifunctional Structural Health Monitoring System","authors":"Anagha Prabhakaran, D. S. kumar","doi":"10.1109/ACCESS57397.2023.10200020","DOIUrl":"https://doi.org/10.1109/ACCESS57397.2023.10200020","url":null,"abstract":"Structural vibrations have a great impact on civil structures. Most of the damage happening to structures that lead to a reduction in their life span is due to vibration. This vibration can be natural or man-made. This paper explains the importance of SHM(Structural health monitoring) and proposes a system for continuously monitoring the structural health status. The prototype consists of an ADXL-335 accelerometer, Arduino Uno, GPS (Global positioning system) and GSM (Global system for mobile communication). The functionalities of the system include detection of variation in the structural parameters, locating the position of the structure by means of GPS and sending the health status of the structure to authority where the GSM consists of a prioritized list of numbers. The paper also focuses on analyzing the dynamic parameters like acceleration and tilt angle in three modes: no vibration mode, normal vibration mode and collapse mode. Also analysis of time-domain features of vibration data in three modes are also analyzed.","PeriodicalId":345351,"journal":{"name":"2023 3rd International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS)","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132889610","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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