Medical imaging plays an important role in medical diagnosis and treatment. It is also useful in medical applications. The proposed concept's goal is to understand the importance of data balancing, data augmentation, and segmentation in the clinical field, to improve image data balancing using data augmentation and edge detection techniques, to improve radiology image preprocessing to locate regions of interest (ROI), and to construct custom-built Deep Neural Networks (DNN) in diagnosing respiratory illness using Machine Learning approaches. Images of varying quality from multiple machine types are frequently included in different datasets. This study used four datasets, three of which are online datasets from Kaggle and the fourth is real-time radiology pictures of COVID and Pneumonia-infected persons from neighboring local hospitals. We proposed RESP_DATA_BALANCE for image data balance in dataset construction, and RDD_ROI (Respiratory Disease Detection Region of Interest) algorithm, which combines improved image feature extraction technique using a GLCM and unsupervised K-means clustering for segmentation to identify the region of interest in the detection of respiratory diseases. Our suggested custom-built 28-layer Respiratory Disease Detection Deep Neural Network (RDD_DNN) is used for further training, testing, and validation. Furthermore, experimental results focus on performance characteristics using various data augmentation, edge detection, and preprocessing strategies. The experimental purpose of our research study is to aid in the classification and early diagnosis of respiratory disorders.
{"title":"Radiology Image Data Augmentation and Image Enhancement in Respiratory Disease Infection Detection Using Machine Learning Approach","authors":"Prita Patil, Vaibhav Narawade","doi":"10.54392/irjmt24211","DOIUrl":"https://doi.org/10.54392/irjmt24211","url":null,"abstract":"Medical imaging plays an important role in medical diagnosis and treatment. It is also useful in medical applications. The proposed concept's goal is to understand the importance of data balancing, data augmentation, and segmentation in the clinical field, to improve image data balancing using data augmentation and edge detection techniques, to improve radiology image preprocessing to locate regions of interest (ROI), and to construct custom-built Deep Neural Networks (DNN) in diagnosing respiratory illness using Machine Learning approaches. Images of varying quality from multiple machine types are frequently included in different datasets. This study used four datasets, three of which are online datasets from Kaggle and the fourth is real-time radiology pictures of COVID and Pneumonia-infected persons from neighboring local hospitals. We proposed RESP_DATA_BALANCE for image data balance in dataset construction, and RDD_ROI (Respiratory Disease Detection Region of Interest) algorithm, which combines improved image feature extraction technique using a GLCM and unsupervised K-means clustering for segmentation to identify the region of interest in the detection of respiratory diseases. Our suggested custom-built 28-layer Respiratory Disease Detection Deep Neural Network (RDD_DNN) is used for further training, testing, and validation. Furthermore, experimental results focus on performance characteristics using various data augmentation, edge detection, and preprocessing strategies. The experimental purpose of our research study is to aid in the classification and early diagnosis of respiratory disorders.","PeriodicalId":507794,"journal":{"name":"International Research Journal of Multidisciplinary Technovation","volume":"117 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140250748","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}
This study explores the potential of PANI-GO:MnO2/MoO3 nanocomposites as high-performance supercapacitors, addressing the increasing energy storage demands in portable electronics devices. By varying the amount of polyaniline (PANI) alongside a ternary composite of GO/MnO2/MoO3, the present study investigates their combined influence on electrochemical performance. XRD analysis confirmed the hexagonal phase with an average particle size of 19 nm, and FTIR analysis showed the functional groups associated with the title compound. FESEM images demonstrated the leaf-like structures, and the EDAX spectrum confirmed the presence of Mn and Mo elements in the as-prepared samples. Electrochemical analysis showed a maximum capacitance of 596 F/g. The unique blend of graphene, polyaniline, and ternary metal oxides in these nanocomposites holds great promise for advanced supercapacitors. The research aims to understand how different levels of polyaniline impact the overall composition, providing insights into the synergies between these components and their effects on energy storage capabilities.
{"title":"Synergistic Analysis of Hydrothermally Synthesized PANI-GO: MnO2/MoO3 Nanocomposites for Enhanced Structural and Supercapacitor Performance","authors":"K. R, Subbramaniyan P","doi":"10.54392/irjmt2424","DOIUrl":"https://doi.org/10.54392/irjmt2424","url":null,"abstract":"This study explores the potential of PANI-GO:MnO2/MoO3 nanocomposites as high-performance supercapacitors, addressing the increasing energy storage demands in portable electronics devices. By varying the amount of polyaniline (PANI) alongside a ternary composite of GO/MnO2/MoO3, the present study investigates their combined influence on electrochemical performance. XRD analysis confirmed the hexagonal phase with an average particle size of 19 nm, and FTIR analysis showed the functional groups associated with the title compound. FESEM images demonstrated the leaf-like structures, and the EDAX spectrum confirmed the presence of Mn and Mo elements in the as-prepared samples. Electrochemical analysis showed a maximum capacitance of 596 F/g. The unique blend of graphene, polyaniline, and ternary metal oxides in these nanocomposites holds great promise for advanced supercapacitors. The research aims to understand how different levels of polyaniline impact the overall composition, providing insights into the synergies between these components and their effects on energy storage capabilities.","PeriodicalId":507794,"journal":{"name":"International Research Journal of Multidisciplinary Technovation","volume":"51 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139775524","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}
This study explores the potential of PANI-GO:MnO2/MoO3 nanocomposites as high-performance supercapacitors, addressing the increasing energy storage demands in portable electronics devices. By varying the amount of polyaniline (PANI) alongside a ternary composite of GO/MnO2/MoO3, the present study investigates their combined influence on electrochemical performance. XRD analysis confirmed the hexagonal phase with an average particle size of 19 nm, and FTIR analysis showed the functional groups associated with the title compound. FESEM images demonstrated the leaf-like structures, and the EDAX spectrum confirmed the presence of Mn and Mo elements in the as-prepared samples. Electrochemical analysis showed a maximum capacitance of 596 F/g. The unique blend of graphene, polyaniline, and ternary metal oxides in these nanocomposites holds great promise for advanced supercapacitors. The research aims to understand how different levels of polyaniline impact the overall composition, providing insights into the synergies between these components and their effects on energy storage capabilities.
{"title":"Synergistic Analysis of Hydrothermally Synthesized PANI-GO: MnO2/MoO3 Nanocomposites for Enhanced Structural and Supercapacitor Performance","authors":"K. R, Subbramaniyan P","doi":"10.54392/irjmt2424","DOIUrl":"https://doi.org/10.54392/irjmt2424","url":null,"abstract":"This study explores the potential of PANI-GO:MnO2/MoO3 nanocomposites as high-performance supercapacitors, addressing the increasing energy storage demands in portable electronics devices. By varying the amount of polyaniline (PANI) alongside a ternary composite of GO/MnO2/MoO3, the present study investigates their combined influence on electrochemical performance. XRD analysis confirmed the hexagonal phase with an average particle size of 19 nm, and FTIR analysis showed the functional groups associated with the title compound. FESEM images demonstrated the leaf-like structures, and the EDAX spectrum confirmed the presence of Mn and Mo elements in the as-prepared samples. Electrochemical analysis showed a maximum capacitance of 596 F/g. The unique blend of graphene, polyaniline, and ternary metal oxides in these nanocomposites holds great promise for advanced supercapacitors. The research aims to understand how different levels of polyaniline impact the overall composition, providing insights into the synergies between these components and their effects on energy storage capabilities.","PeriodicalId":507794,"journal":{"name":"International Research Journal of Multidisciplinary Technovation","volume":"327 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139835341","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 Information centric networks (ICN) transforms the focal point of current Internet paradigm to data centric approach from host centric approach by allowing content driven forwarding and in-network caching mechanisms. Though NDN (Named data networking) paradigm of ICN assures a secure content communication, it is vulnerable to different attacks by the malicious nodes. To minimize the hazards from compromised nodes and to improve the network security, the remaining nodes should transparently receive information about such nodes. This will restrict the forwarding strategy to exploit these malicious nodes for forwarding interest and content as well. Our protocol introduces a dynamic model for prediction of trust in order to evaluate the node trust. Proposed approach observes the historical behaviors of node and uses extended fuzzy logic rules for the prediction of future behaviors to evaluate the node’s trust value. This prediction model is incorporated within the trust based forwarding mechanism that aims to forward interest through secure and shortest path. The extensive simulation study has been carried out to analyze the protocol performance in ns-3 driven ndnSIM-2.0 simulator for performance metrics such as data discovery latency, packet delivery ratio, network overhead, detection ratio and cache hit ratio. When we integrate our trust joint forwarding strategy to state-of-the-art protocols, their performance is significantly improved up to approximately 10-35% against stated performance measures for realistic network topology.
{"title":"CTJIF-ICN: A Coadjuvant Trust Joint Interest Forwarding Mechanism in Information Centric Networks","authors":"Krishna Delvadia, N. Dutta","doi":"10.54392/irjmt2422","DOIUrl":"https://doi.org/10.54392/irjmt2422","url":null,"abstract":"The Information centric networks (ICN) transforms the focal point of current Internet paradigm to data centric approach from host centric approach by allowing content driven forwarding and in-network caching mechanisms. Though NDN (Named data networking) paradigm of ICN assures a secure content communication, it is vulnerable to different attacks by the malicious nodes. To minimize the hazards from compromised nodes and to improve the network security, the remaining nodes should transparently receive information about such nodes. This will restrict the forwarding strategy to exploit these malicious nodes for forwarding interest and content as well. Our protocol introduces a dynamic model for prediction of trust in order to evaluate the node trust. Proposed approach observes the historical behaviors of node and uses extended fuzzy logic rules for the prediction of future behaviors to evaluate the node’s trust value. This prediction model is incorporated within the trust based forwarding mechanism that aims to forward interest through secure and shortest path. The extensive simulation study has been carried out to analyze the protocol performance in ns-3 driven ndnSIM-2.0 simulator for performance metrics such as data discovery latency, packet delivery ratio, network overhead, detection ratio and cache hit ratio. When we integrate our trust joint forwarding strategy to state-of-the-art protocols, their performance is significantly improved up to approximately 10-35% against stated performance measures for realistic network topology.","PeriodicalId":507794,"journal":{"name":"International Research Journal of Multidisciplinary Technovation","volume":"8 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139847074","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}
M. Panigrahi, Adiraj Behera, Ratan Indu Ganguly, Radha Raman Dash
Hollow microcubes with nanorods of Indium oxide (In2O3) are synthesized using hydrothermal followed by decomposition process. Synthesized materials are characterized with XRD, SEM, and FTIR spectroscopy for esteeming phase compositions and morphologies. The photocatalytic performances of two materials are evaluated by the degradation of crystal violet dye in an aqueous solution under UV light. The photocatalytic activity of prepared In(OH)3 shows ~60% degradation of crystal violet after 5 h reaction, whereas In2O3 shows ~92% degradation under same conditions.
{"title":"A Photocatalysis of CV Dye Under UV Light Degradation using Laboratory Prepared In(OH)3 And In2O3 By Hydrothermal Method: Nano-Matrrials For Dye Sensitive Solar Cell","authors":"M. Panigrahi, Adiraj Behera, Ratan Indu Ganguly, Radha Raman Dash","doi":"10.54392/irjmt2423","DOIUrl":"https://doi.org/10.54392/irjmt2423","url":null,"abstract":"Hollow microcubes with nanorods of Indium oxide (In2O3) are synthesized using hydrothermal followed by decomposition process. Synthesized materials are characterized with XRD, SEM, and FTIR spectroscopy for esteeming phase compositions and morphologies. The photocatalytic performances of two materials are evaluated by the degradation of crystal violet dye in an aqueous solution under UV light. The photocatalytic activity of prepared In(OH)3 shows ~60% degradation of crystal violet after 5 h reaction, whereas In2O3 shows ~92% degradation under same conditions.","PeriodicalId":507794,"journal":{"name":"International Research Journal of Multidisciplinary Technovation","volume":" January","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139787654","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}
M. Panigrahi, Adiraj Behera, Ratan Indu Ganguly, Radha Raman Dash
Hollow microcubes with nanorods of Indium oxide (In2O3) are synthesized using hydrothermal followed by decomposition process. Synthesized materials are characterized with XRD, SEM, and FTIR spectroscopy for esteeming phase compositions and morphologies. The photocatalytic performances of two materials are evaluated by the degradation of crystal violet dye in an aqueous solution under UV light. The photocatalytic activity of prepared In(OH)3 shows ~60% degradation of crystal violet after 5 h reaction, whereas In2O3 shows ~92% degradation under same conditions.
{"title":"A Photocatalysis of CV Dye Under UV Light Degradation using Laboratory Prepared In(OH)3 And In2O3 By Hydrothermal Method: Nano-Matrrials For Dye Sensitive Solar Cell","authors":"M. Panigrahi, Adiraj Behera, Ratan Indu Ganguly, Radha Raman Dash","doi":"10.54392/irjmt2423","DOIUrl":"https://doi.org/10.54392/irjmt2423","url":null,"abstract":"Hollow microcubes with nanorods of Indium oxide (In2O3) are synthesized using hydrothermal followed by decomposition process. Synthesized materials are characterized with XRD, SEM, and FTIR spectroscopy for esteeming phase compositions and morphologies. The photocatalytic performances of two materials are evaluated by the degradation of crystal violet dye in an aqueous solution under UV light. The photocatalytic activity of prepared In(OH)3 shows ~60% degradation of crystal violet after 5 h reaction, whereas In2O3 shows ~92% degradation under same conditions.","PeriodicalId":507794,"journal":{"name":"International Research Journal of Multidisciplinary Technovation","volume":"210 1-2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139847230","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 Information centric networks (ICN) transforms the focal point of current Internet paradigm to data centric approach from host centric approach by allowing content driven forwarding and in-network caching mechanisms. Though NDN (Named data networking) paradigm of ICN assures a secure content communication, it is vulnerable to different attacks by the malicious nodes. To minimize the hazards from compromised nodes and to improve the network security, the remaining nodes should transparently receive information about such nodes. This will restrict the forwarding strategy to exploit these malicious nodes for forwarding interest and content as well. Our protocol introduces a dynamic model for prediction of trust in order to evaluate the node trust. Proposed approach observes the historical behaviors of node and uses extended fuzzy logic rules for the prediction of future behaviors to evaluate the node’s trust value. This prediction model is incorporated within the trust based forwarding mechanism that aims to forward interest through secure and shortest path. The extensive simulation study has been carried out to analyze the protocol performance in ns-3 driven ndnSIM-2.0 simulator for performance metrics such as data discovery latency, packet delivery ratio, network overhead, detection ratio and cache hit ratio. When we integrate our trust joint forwarding strategy to state-of-the-art protocols, their performance is significantly improved up to approximately 10-35% against stated performance measures for realistic network topology.
{"title":"CTJIF-ICN: A Coadjuvant Trust Joint Interest Forwarding Mechanism in Information Centric Networks","authors":"Krishna Delvadia, N. Dutta","doi":"10.54392/irjmt2422","DOIUrl":"https://doi.org/10.54392/irjmt2422","url":null,"abstract":"The Information centric networks (ICN) transforms the focal point of current Internet paradigm to data centric approach from host centric approach by allowing content driven forwarding and in-network caching mechanisms. Though NDN (Named data networking) paradigm of ICN assures a secure content communication, it is vulnerable to different attacks by the malicious nodes. To minimize the hazards from compromised nodes and to improve the network security, the remaining nodes should transparently receive information about such nodes. This will restrict the forwarding strategy to exploit these malicious nodes for forwarding interest and content as well. Our protocol introduces a dynamic model for prediction of trust in order to evaluate the node trust. Proposed approach observes the historical behaviors of node and uses extended fuzzy logic rules for the prediction of future behaviors to evaluate the node’s trust value. This prediction model is incorporated within the trust based forwarding mechanism that aims to forward interest through secure and shortest path. The extensive simulation study has been carried out to analyze the protocol performance in ns-3 driven ndnSIM-2.0 simulator for performance metrics such as data discovery latency, packet delivery ratio, network overhead, detection ratio and cache hit ratio. When we integrate our trust joint forwarding strategy to state-of-the-art protocols, their performance is significantly improved up to approximately 10-35% against stated performance measures for realistic network topology.","PeriodicalId":507794,"journal":{"name":"International Research Journal of Multidisciplinary Technovation","volume":" 1021","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139787131","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}
Sankar K, Gokula Krishnan V, V. S, Kaviarasan S, Arockia Abins A
Effective trash management has become a top environmental priority, especially in urban areas with significant population growth where garbage output is on the rise. As cities work to manage garbage properly, innovative waste management programmes have the potential to increase effectiveness, cut costs, and improve the aesthetic appeal of public places. This article introduces SCM-RIAN, a powerful "Smart City Management and Classification System" built on the Internet of Things (IoT) and deep learning (DL) technologies. Convolutional neural networks are used in the garbage classification model that is implemented within this smart city management and classification framework. This system for classifying waste is intended to categorise rubbish into several classes at waste collection sites, encouraging recycling. The Rotation-Invariant Attention Network (RIAN) is a unique approach presented for the categorization process to address a prevalent problem in smart city management (SCM). A Centre Spectral Attention (CSpeA) module built within RIAN isolates spectral bands from other categories of pixels' influence, reducing redundancy. As an alternative to the conventional 3 3 convolution, to obtain rotation-invariant spectral-spatial data contained in SCM patches, the Rectified Spatial Attention (RSpaA) module is also introduced. The suggested RIAN for SCM classification is built on the integration of the CSpeA, 11 convolution, and RSpaA modules. The Ladybird Beetle Optimisation Algorithm (LBBOA) is used to optimise hyperparameters. With improved results compared to other current models, this suggested SCM-RIAN achieved 98.12% accuracy (ACC) with high sensitivity (SEN), specificity (SPEC), and kappa index (KI) using the garbage classification dataset.
{"title":"Enhancing Smart City Waste Management through LBBOA based RIAN Classification","authors":"Sankar K, Gokula Krishnan V, V. S, Kaviarasan S, Arockia Abins A","doi":"10.54392/irjmt2365","DOIUrl":"https://doi.org/10.54392/irjmt2365","url":null,"abstract":"Effective trash management has become a top environmental priority, especially in urban areas with significant population growth where garbage output is on the rise. As cities work to manage garbage properly, innovative waste management programmes have the potential to increase effectiveness, cut costs, and improve the aesthetic appeal of public places. This article introduces SCM-RIAN, a powerful \"Smart City Management and Classification System\" built on the Internet of Things (IoT) and deep learning (DL) technologies. Convolutional neural networks are used in the garbage classification model that is implemented within this smart city management and classification framework. This system for classifying waste is intended to categorise rubbish into several classes at waste collection sites, encouraging recycling. The Rotation-Invariant Attention Network (RIAN) is a unique approach presented for the categorization process to address a prevalent problem in smart city management (SCM). A Centre Spectral Attention (CSpeA) module built within RIAN isolates spectral bands from other categories of pixels' influence, reducing redundancy. As an alternative to the conventional 3 3 convolution, to obtain rotation-invariant spectral-spatial data contained in SCM patches, the Rectified Spatial Attention (RSpaA) module is also introduced. The suggested RIAN for SCM classification is built on the integration of the CSpeA, 11 convolution, and RSpaA modules. The Ladybird Beetle Optimisation Algorithm (LBBOA) is used to optimise hyperparameters. With improved results compared to other current models, this suggested SCM-RIAN achieved 98.12% accuracy (ACC) with high sensitivity (SEN), specificity (SPEC), and kappa index (KI) using the garbage classification dataset.","PeriodicalId":507794,"journal":{"name":"International Research Journal of Multidisciplinary Technovation","volume":"37 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139261808","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}
Sarita Jibhau Wagh, Pradip M. Paithane, M. D. Sangale, Pondhe G.M
One of the natural resources having the latent for home, agrarian, and engineering use is surface and groundwater. Due to humanoid and certain natural reasons, the eminence of the groundwater serving Baramati City and Tehsil has deteriorated. Agriculture is using more pesticides and fertilizer, therefore this supply is being affected. Municipal water pollution can be caused by “septic boilers”, “bathe sewage”, “polluted aquatic”, “improper discarded management”, “public excretion”, “improper waste structure”, “public sewage discharges”, and “unorganized solid waste disposal”. The current study will improve the accuracy of the water quality index for areas in Baramati Tehsil that are affected by industry and drinking water supplies. The groundwater zones were created using a weighted index overlay analysis, which assigned weights based on several classes of individual water quality metrics and drinking water standards. Based on few observations, fuzzy logic offers an effective and practical tool for categorizing drinking water quality. This study's objective is to provide a fuzzy logic-based water quality indicator for basin-wide reservoirs. For a weight-based fuzzy quality index, a minimum of 6 physico-chemicals are needed.
{"title":"Computation of Groundwater Quality of Baramati with the help of Fuzzy Water Quality Index (FWQI)","authors":"Sarita Jibhau Wagh, Pradip M. Paithane, M. D. Sangale, Pondhe G.M","doi":"10.54392/irjmt2364","DOIUrl":"https://doi.org/10.54392/irjmt2364","url":null,"abstract":"One of the natural resources having the latent for home, agrarian, and engineering use is surface and groundwater. Due to humanoid and certain natural reasons, the eminence of the groundwater serving Baramati City and Tehsil has deteriorated. Agriculture is using more pesticides and fertilizer, therefore this supply is being affected. Municipal water pollution can be caused by “septic boilers”, “bathe sewage”, “polluted aquatic”, “improper discarded management”, “public excretion”, “improper waste structure”, “public sewage discharges”, and “unorganized solid waste disposal”. The current study will improve the accuracy of the water quality index for areas in Baramati Tehsil that are affected by industry and drinking water supplies. The groundwater zones were created using a weighted index overlay analysis, which assigned weights based on several classes of individual water quality metrics and drinking water standards. Based on few observations, fuzzy logic offers an effective and practical tool for categorizing drinking water quality. This study's objective is to provide a fuzzy logic-based water quality indicator for basin-wide reservoirs. For a weight-based fuzzy quality index, a minimum of 6 physico-chemicals are needed.","PeriodicalId":507794,"journal":{"name":"International Research Journal of Multidisciplinary Technovation","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139282481","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 main objective of our project “Blood leakage detection during self-dialysis” is, the patient can do their treatment by themselves whenever he/she feels comfortable and free. The IOT device is also designed as a warning tool for detection of blood leakage/loss. It can indicate the risk level in both end-sensing units and remote monitor devices via a wireless network and cloud.
{"title":"Blood Leakage Detection During Self-Dialysis","authors":"Suresh Kumar M, Vanmathi V, Poornima S","doi":"10.34256/irjmt2025","DOIUrl":"https://doi.org/10.34256/irjmt2025","url":null,"abstract":"The main objective of our project “Blood leakage detection during self-dialysis” is, the patient can do their treatment by themselves whenever he/she feels comfortable and free. The IOT device is also designed as a warning tool for detection of blood leakage/loss. It can indicate the risk level in both end-sensing units and remote monitor devices via a wireless network and cloud.","PeriodicalId":507794,"journal":{"name":"International Research Journal of Multidisciplinary Technovation","volume":" 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141220055","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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