Pub Date : 2023-08-05DOI: 10.59544/tdpo3323/ngcesi23p43
Nanda Jayalakshmi P, Revathy V
Water quality parameter is of much importance in our day to day lives. Prediction of water quality will help to reduce water pollution and guard our human health. This work has advanced an “Machine Learning based real-time water quality monitoring system” pertaining to lakes is being used in rural areas. All the organisms that use it are affected by the waste generated in this water. Water quality monitoring system is to identify the level of water and finding ways to correct the problems in it. Water quality refers to the chemical, physical and biological characteristics of water. It is a measure of the condition of water relative to the requirements of one or more biotic species and or to any human need or purpose. It is most frequently used by reference to a set of standards against which compliance can be assessed. The most common standards used to assess water quality relate to health of ecosystems, safety of human contact and drinking water. An intelligent process of monitoring the quality of water automatically detects the condition of water through Machine Learning by processing sensors data and instantly provides notification to water analyst when the quality of water is abnormal. The structure uses Determination of pH, Color, Temperature, Carbon monoxide, Conductivity, Fecal coliform. Likewise, ANN, Adaptive filter algorithm, Support Vector Machine, Naïve Bayes, Random forest calculation has been utilized for anticipating the nature of water, with the assistance of prepared informational collection from various water tests.
{"title":"Machine Learning Based Realtime Water Quality Monitoring System","authors":"Nanda Jayalakshmi P, Revathy V","doi":"10.59544/tdpo3323/ngcesi23p43","DOIUrl":"https://doi.org/10.59544/tdpo3323/ngcesi23p43","url":null,"abstract":"Water quality parameter is of much importance in our day to day lives. Prediction of water quality will help to reduce water pollution and guard our human health. This work has advanced an “Machine Learning based real-time water quality monitoring system” pertaining to lakes is being used in rural areas. All the organisms that use it are affected by the waste generated in this water. Water quality monitoring system is to identify the level of water and finding ways to correct the problems in it. Water quality refers to the chemical, physical and biological characteristics of water. It is a measure of the condition of water relative to the requirements of one or more biotic species and or to any human need or purpose. It is most frequently used by reference to a set of standards against which compliance can be assessed. The most common standards used to assess water quality relate to health of ecosystems, safety of human contact and drinking water. An intelligent process of monitoring the quality of water automatically detects the condition of water through Machine Learning by processing sensors data and instantly provides notification to water analyst when the quality of water is abnormal. The structure uses Determination of pH, Color, Temperature, Carbon monoxide, Conductivity, Fecal coliform. Likewise, ANN, Adaptive filter algorithm, Support Vector Machine, Naïve Bayes, Random forest calculation has been utilized for anticipating the nature of water, with the assistance of prepared informational collection from various water tests.","PeriodicalId":315694,"journal":{"name":"The International Conference on scientific innovations in Science, Technology, and Management","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127168255","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 : 2023-08-05DOI: 10.59544/jaad9174/ngcesi23p46
Ganga M, Gini R
Fake News creates erroneous suspense information that can be identified. This spreads dishonesty about a country’s status or overstates the expense of special functions for a government, destroying democracy in certain countries. The project proposes an Multi Support Vector Machine (MSVM) -based approach for detecting fake news. The proposed model will be used to classify or detect the news as fake or real. Principal Component Analysis (PCA) is used for Feature Extraction. Principal Component Analysis (PCA) reduces the dimension of the data set comprising many related variables and recalls the maximum change in actual data. The proposed work will select the essential features with a Firefly-Optimized Algorithm (FA). The Firefly Optimized Algorithm (FA) is one of the various Evolutionary Algorithms (EAs) with various purposes. For the classification of fake news, an Multi Support Vector Machine (MSVM) classifier algorithm is implemented.
{"title":"Optimized Multi Support Vector Machine Based Approach for Fake News Detection","authors":"Ganga M, Gini R","doi":"10.59544/jaad9174/ngcesi23p46","DOIUrl":"https://doi.org/10.59544/jaad9174/ngcesi23p46","url":null,"abstract":"Fake News creates erroneous suspense information that can be identified. This spreads dishonesty about a country’s status or overstates the expense of special functions for a government, destroying democracy in certain countries. The project proposes an Multi Support Vector Machine (MSVM) -based approach for detecting fake news. The proposed model will be used to classify or detect the news as fake or real. Principal Component Analysis (PCA) is used for Feature Extraction. Principal Component Analysis (PCA) reduces the dimension of the data set comprising many related variables and recalls the maximum change in actual data. The proposed work will select the essential features with a Firefly-Optimized Algorithm (FA). The Firefly Optimized Algorithm (FA) is one of the various Evolutionary Algorithms (EAs) with various purposes. For the classification of fake news, an Multi Support Vector Machine (MSVM) classifier algorithm is implemented.","PeriodicalId":315694,"journal":{"name":"The International Conference on scientific innovations in Science, Technology, and Management","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125726464","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 : 2023-08-05DOI: 10.59544/cugn6440/ngcesi23p20
Dins K S
Sandwich beams are composite systems that have properties such as high rigidity, high strength and low weight. The sandwich system include glass fiber reinforced polymer (GFRP) skins and phenolic cores, and several layers of sandwich panels are bonded with an epoxy polymer matrix to manufacture the packages. In sandwich beam (LSB) layers, four horizontally oriented layers and the other four vertically oriented layers were tested. To understand the basic behavior of a multilayer sandwich beam, a 3D finite element model was developed using ANSYS. To explore the suitability of this new concept for structural applications, the flexural behavior of the layered sandwich beam is validated using data available in the literature, and the numerical model can be improved by incorporating shear and fatigue behavior which increases confidence in using this novel concept of beam in the civil construction sector.
{"title":"Strength Analysis of Layered Sandwich Beam","authors":"Dins K S","doi":"10.59544/cugn6440/ngcesi23p20","DOIUrl":"https://doi.org/10.59544/cugn6440/ngcesi23p20","url":null,"abstract":"Sandwich beams are composite systems that have properties such as high rigidity, high strength and low weight. The sandwich system include glass fiber reinforced polymer (GFRP) skins and phenolic cores, and several layers of sandwich panels are bonded with an epoxy polymer matrix to manufacture the packages. In sandwich beam (LSB) layers, four horizontally oriented layers and the other four vertically oriented layers were tested. To understand the basic behavior of a multilayer sandwich beam, a 3D finite element model was developed using ANSYS. To explore the suitability of this new concept for structural applications, the flexural behavior of the layered sandwich beam is validated using data available in the literature, and the numerical model can be improved by incorporating shear and fatigue behavior which increases confidence in using this novel concept of beam in the civil construction sector.","PeriodicalId":315694,"journal":{"name":"The International Conference on scientific innovations in Science, Technology, and Management","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125886846","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 : 2023-08-05DOI: 10.59544/sgkg8201/ngcesi23p54
Now days the use of nanoparticles in the construction field will increase. The nanoparticles help to improve the physical and mechanical properties of the concrete. Nano powder can improve the mechanical properties of cement paste due to accelerating the formation of small sized crystals. The study focus on the structural changes of cement paste when adding Sic and Tic nanoparticles as admixtures in different proportion. Scanning Electron Microscopy and energy dispactive spectroscopy have been employed in identifying the structural changes in nanoparticles modified paste. Silicon carbide (SiC), also known as carborundum. It is hard chemical a compound containing silicon and carbon. A semiconductor, it occurs in nature as the extremely rare mineral moissanite. SiC also has a very low coefficient of thermal expansion (4.0 × 10-6/K) and experiences X no phase transitions that would cause discontinuities in thermal expansion. Which accessories the strength of concrete. Titanium carbide, TiC, is an extremely hard (Mohs 9-9.5) refractory ceramic material, similar to tungsten carbide. It has the appearance of black powder with the sodium chloride (face-centered cubic) crystal structure. Its crystals as found in nature range in size from 0.1 to 0.3 m. Titanium carbide is used in preparation of cermets, which are frequently used to machine steel materials at high cutting speed.Increase the strength of cement paste, Enhance the mechanical properties,Enhance the physical properties.
{"title":"Experimental and Analysis of Adding Silicon and Titanium Carbide Nanoparticles to the Cement PasteExperimental and Analysis of Adding Silicon and Titanium Carbide Nanoparticles to the Cement Paste","authors":"","doi":"10.59544/sgkg8201/ngcesi23p54","DOIUrl":"https://doi.org/10.59544/sgkg8201/ngcesi23p54","url":null,"abstract":"Now days the use of nanoparticles in the construction field will increase. The nanoparticles help to improve the physical and mechanical properties of the concrete. Nano powder can improve the mechanical properties of cement paste due to accelerating the formation of small sized crystals. The study focus on the structural changes of cement paste when adding Sic and Tic nanoparticles as admixtures in different proportion. Scanning Electron Microscopy and energy dispactive spectroscopy have been employed in identifying the structural changes in nanoparticles modified paste. Silicon carbide (SiC), also known as carborundum. It is hard chemical a compound containing silicon and carbon. A semiconductor, it occurs in nature as the extremely rare mineral moissanite. SiC also has a very low coefficient of thermal expansion (4.0 × 10-6/K) and experiences X no phase transitions that would cause discontinuities in thermal expansion. Which accessories the strength of concrete. Titanium carbide, TiC, is an extremely hard (Mohs 9-9.5) refractory ceramic material, similar to tungsten carbide. It has the appearance of black powder with the sodium chloride (face-centered cubic) crystal structure. Its crystals as found in nature range in size from 0.1 to 0.3 m. Titanium carbide is used in preparation of cermets, which are frequently used to machine steel materials at high cutting speed.Increase the strength of cement paste, Enhance the mechanical properties,Enhance the physical properties.","PeriodicalId":315694,"journal":{"name":"The International Conference on scientific innovations in Science, Technology, and Management","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125997254","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 : 2023-08-05DOI: 10.59544/dpaz6258/ngcesi23p29
Abilash S. B, Sujitha R
Fake engagement is one of the significant problems in Online Social Networks (OSNs) which is used to increase the popularity of an account in an inorganic manner. The detection of fake engagement is crucial because it leads to loss of money for businesses, wrong audience targeting in advertising, wrong product predictions systems, and unhealthy social network environment. This study is related with the detection of fake and automated accounts which leads to fake engagement on Instagram. Prior to this work, there were no publicly available dataset for fake and automated accounts. For this purpose, two datasets have been published for the detection of fake and automated accounts. For the detection of these accounts, machine learning algorithms like Naive Bayes, Logistic Regression, Support Vector Machines and Neural Networks are applied. Additionally, for the detection of automated accounts, cost sensitive genetic algorithm is proposed to handle the unnatural bias in the dataset. To deal with the unevenness problem in the fake dataset, Smote-nc algorithm is implemented. In this paper investigating various methods used in the existing work for the Instagram fake account detection.
虚假参与是在线社交网络(Online Social Networks，简称OSNs)的一个重要问题，它被用来以无机的方式增加一个账户的受欢迎程度。检测虚假参与是至关重要的，因为它会导致企业损失资金，广告中的错误受众定位，错误的产品预测系统以及不健康的社交网络环境。这项研究与检测虚假账户和自动账户有关，这些账户会导致Instagram上的虚假参与度。在这项工作之前，没有公开的假账户和自动账户数据集。为此，已经发布了两个数据集，用于检测虚假账户和自动账户。为了检测这些账户，使用了朴素贝叶斯、逻辑回归、支持向量机和神经网络等机器学习算法。此外，对于自动账户的检测，提出了成本敏感遗传算法来处理数据集中的非自然偏差。为了解决假数据集的不均匀性问题，实现了Smote-nc算法。本文对现有工作中用于Instagram虚假账户检测的各种方法进行了研究。
{"title":"Instagram Fake and Automated Account Detection: A Review","authors":"Abilash S. B, Sujitha R","doi":"10.59544/dpaz6258/ngcesi23p29","DOIUrl":"https://doi.org/10.59544/dpaz6258/ngcesi23p29","url":null,"abstract":"Fake engagement is one of the significant problems in Online Social Networks (OSNs) which is used to increase the popularity of an account in an inorganic manner. The detection of fake engagement is crucial because it leads to loss of money for businesses, wrong audience targeting in advertising, wrong product predictions systems, and unhealthy social network environment. This study is related with the detection of fake and automated accounts which leads to fake engagement on Instagram. Prior to this work, there were no publicly available dataset for fake and automated accounts. For this purpose, two datasets have been published for the detection of fake and automated accounts. For the detection of these accounts, machine learning algorithms like Naive Bayes, Logistic Regression, Support Vector Machines and Neural Networks are applied. Additionally, for the detection of automated accounts, cost sensitive genetic algorithm is proposed to handle the unnatural bias in the dataset. To deal with the unevenness problem in the fake dataset, Smote-nc algorithm is implemented. In this paper investigating various methods used in the existing work for the Instagram fake account detection.","PeriodicalId":315694,"journal":{"name":"The International Conference on scientific innovations in Science, Technology, and Management","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126379909","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 : 2023-08-05DOI: 10.59544/vnmj1833/ngcesi23p27
Abishek D, Sujitha R
Cancer has identified a diverse condition of several various subtypes. The timely screening and course of treatment of a cancer form is now a requirement in early cancer research because it supports the medical treatment of patients. Many research teams studied the application of ML and Deep Learning methods in the field of biomedicine and bioinformatics in the classification of people with cancer across high or low-risk categories. These techniques have therefore been used as a model for the development and treatment of cancer. A sit is important that ML instruments are capable of detecting key features from complex datasets. Many of these methods are widely used for the development of predictive models for predicating a cure for cancer, some of the methods are artificial neural networks (ANNs), support vector machine (SVMs) and decision trees (DTs). While we can understand cancer progression with the use of ML methods, an adequate validity level is needed to take these methods into consideration in clinical practice every day .In this study the ML & DL approaches used in cancer progression modeling are reviewed. The predictions addressed are mostly linked to specific ML, input, and data samples supervision. 2021ElsevierLtd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Virtual Conference one Advanced Nano materials and Applications. This is an open access article under the CCBY-NC-ND license.
{"title":"Prediction of Cancer Disease Using Machine Learning Approach: A Review","authors":"Abishek D, Sujitha R","doi":"10.59544/vnmj1833/ngcesi23p27","DOIUrl":"https://doi.org/10.59544/vnmj1833/ngcesi23p27","url":null,"abstract":"Cancer has identified a diverse condition of several various subtypes. The timely screening and course of treatment of a cancer form is now a requirement in early cancer research because it supports the medical treatment of patients. Many research teams studied the application of ML and Deep Learning methods in the field of biomedicine and bioinformatics in the classification of people with cancer across high or low-risk categories. These techniques have therefore been used as a model for the development and treatment of cancer. A sit is important that ML instruments are capable of detecting key features from complex datasets. Many of these methods are widely used for the development of predictive models for predicating a cure for cancer, some of the methods are artificial neural networks (ANNs), support vector machine (SVMs) and decision trees (DTs). While we can understand cancer progression with the use of ML methods, an adequate validity level is needed to take these methods into consideration in clinical practice every day .In this study the ML & DL approaches used in cancer progression modeling are reviewed. The predictions addressed are mostly linked to specific ML, input, and data samples supervision. 2021ElsevierLtd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Virtual Conference one Advanced Nano materials and Applications. This is an open access article under the CCBY-NC-ND license.","PeriodicalId":315694,"journal":{"name":"The International Conference on scientific innovations in Science, Technology, and Management","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123817026","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 : 2023-08-05DOI: 10.59544/ivww3534/ngcesi23p65
M. Larisch, B. Perry
Embedded retaining walls are a well-established method to construct retention systems fordeep excavations and to create a barrier against the inflow of groundwater. Several factorsneed to be considered when selecting the most suitable wall type to achieve compliance with the project requirements and specifications. The selection of there taining wall type provides a direct link to the expected grade of water proofing performance which is the focus of this paper. It should be noted that embedded retaining walls in general should not be assumed to beabsolutely water tight as complete water tightness is neither practical nor economical. Even cast in-place concrete diaphragm walls with very low permeability can’t be considered completely water tight despite having the least number of vertical construction joints of all embedded retaining wall systems. British Standard BS 8102:1990 clearly highlights therequirement of additional water proofing elements and methods to meet the relevant waterproofing levels for such walls and basements in general. However, unless the diaphragm wall (or other wall type) itself provides adequate and realistic water retention performance, the performance of the additional tanking can be put at risk, too. The required performance criteria for fresh tremie concrete to be used for the construction of diaphragm walls, must be selected to achieve optimal concrete density to fully comply with the expected structural, durability and water proofing performance criteria of the entire basement.
{"title":"Modern Concrete Technology and Placement Methods and Their Influence on Water Proofing Performance of Diaphragm Walls","authors":"M. Larisch, B. Perry","doi":"10.59544/ivww3534/ngcesi23p65","DOIUrl":"https://doi.org/10.59544/ivww3534/ngcesi23p65","url":null,"abstract":"Embedded retaining walls are a well-established method to construct retention systems fordeep excavations and to create a barrier against the inflow of groundwater. Several factorsneed to be considered when selecting the most suitable wall type to achieve compliance with the project requirements and specifications. The selection of there taining wall type provides a direct link to the expected grade of water proofing performance which is the focus of this paper. It should be noted that embedded retaining walls in general should not be assumed to beabsolutely water tight as complete water tightness is neither practical nor economical. Even cast in-place concrete diaphragm walls with very low permeability can’t be considered completely water tight despite having the least number of vertical construction joints of all embedded retaining wall systems. British Standard BS 8102:1990 clearly highlights therequirement of additional water proofing elements and methods to meet the relevant waterproofing levels for such walls and basements in general. However, unless the diaphragm wall (or other wall type) itself provides adequate and realistic water retention performance, the performance of the additional tanking can be put at risk, too. The required performance criteria for fresh tremie concrete to be used for the construction of diaphragm walls, must be selected to achieve optimal concrete density to fully comply with the expected structural, durability and water proofing performance criteria of the entire basement.","PeriodicalId":315694,"journal":{"name":"The International Conference on scientific innovations in Science, Technology, and Management","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133077749","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 : 2023-08-05DOI: 10.59544/tnnw2034/ngcesi23p49
Ganga M.V
Basically, engineering structures are required to satisfy predefined performance targets such as successfully resisting external load actions. Due to the randomness nature of both the structure l property and the external attacks, however, the “absolute safety” of a structure cannot be achieved in engineering practice. Rather, the practical strategy is to control the probability of violating the performance requirements (e.g., structural safety) under an acceptable level. To that end, some probability based approaches are essentially needed to quantify the occurrence possibility of such undesired consequences. Under this context, the mathematical formulation of analytical tools for structural reliability assessment is the topic of this book.
{"title":"Structural Reliability Assessment of Bridges","authors":"Ganga M.V","doi":"10.59544/tnnw2034/ngcesi23p49","DOIUrl":"https://doi.org/10.59544/tnnw2034/ngcesi23p49","url":null,"abstract":"Basically, engineering structures are required to satisfy predefined performance targets such as successfully resisting external load actions. Due to the randomness nature of both the structure l property and the external attacks, however, the “absolute safety” of a structure cannot be achieved in engineering practice. Rather, the practical strategy is to control the probability of violating the performance requirements (e.g., structural safety) under an acceptable level. To that end, some probability based approaches are essentially needed to quantify the occurrence possibility of such undesired consequences. Under this context, the mathematical formulation of analytical tools for structural reliability assessment is the topic of this book.","PeriodicalId":315694,"journal":{"name":"The International Conference on scientific innovations in Science, Technology, and Management","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123850040","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 : 2023-08-05DOI: 10.59544/zejk7531/ngcesi23p24
Abisha R, Merry Guisa J
A Maximum Power Point Tracking or Tracker (MPPT) is a high efficiency system that extracts the maximum power output from a solar cell or an array of photovoltaic (PV) cells. Normally the solar power systems efficiency is less. To improve its efficiency, solar power systems are usually equipped with the function of MPPT. The work presented in this paper concerns the designing and implementation of a photovoltaic system (PV) provided with an MPPT control. More particularly, the utilization of a buck converter for controlling photovoltaic power using Maximum Power Point Tracking (MPPT) mechanism was presented. First the photovoltaic module is analyzed using SIMULINK software. In this project the buck converter was used along with a MPPT control. The MPPT is responsible for extracting the maximum possible power from the photovoltaic and feed it to the load via the buck converter which steps down the voltage to the required magnitude. The algorithm utilized for MPPT was the three-point weighting that incorporates mid-point tracking. The system was designed and simulated in MATLAB. Both the buck converter and the solar cell are modelled using Sim- Power Systems blocks. Especially, the waveforms of MPPT and Photo voltaic have been presented.
{"title":"MPPT of Solar Using Mid-Point Tracking Method","authors":"Abisha R, Merry Guisa J","doi":"10.59544/zejk7531/ngcesi23p24","DOIUrl":"https://doi.org/10.59544/zejk7531/ngcesi23p24","url":null,"abstract":"A Maximum Power Point Tracking or Tracker (MPPT) is a high efficiency system that extracts the maximum power output from a solar cell or an array of photovoltaic (PV) cells. Normally the solar power systems efficiency is less. To improve its efficiency, solar power systems are usually equipped with the function of MPPT. The work presented in this paper concerns the designing and implementation of a photovoltaic system (PV) provided with an MPPT control. More particularly, the utilization of a buck converter for controlling photovoltaic power using Maximum Power Point Tracking (MPPT) mechanism was presented. First the photovoltaic module is analyzed using SIMULINK software. In this project the buck converter was used along with a MPPT control. The MPPT is responsible for extracting the maximum possible power from the photovoltaic and feed it to the load via the buck converter which steps down the voltage to the required magnitude. The algorithm utilized for MPPT was the three-point weighting that incorporates mid-point tracking. The system was designed and simulated in MATLAB. Both the buck converter and the solar cell are modelled using Sim- Power Systems blocks. Especially, the waveforms of MPPT and Photo voltaic have been presented.","PeriodicalId":315694,"journal":{"name":"The International Conference on scientific innovations in Science, Technology, and Management","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131295830","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 : 2023-08-05DOI: 10.59544/lurb3625/ngcesi23p64
Harish K. R., Edwin Sahayaraj M., Stanly Jones Retnam B.
A vast array of plating processes, the substances through which different plating can be applied with the natural intention of saving the component, shape and the outer layer that are left unprotected to any kind of physical, chemical and also mechanical adversities. Thus, Spray pyrolysis is very efficient, cost effective, and utilizes simple equipment. Spray pyrolysis is an important technique in which a thin film is deposited on the dielectric matrix by spraying a precursor solution on a heated surface. Spray pyrolysis has been applied to deposit a wide variety of thin films. These films were used in various devices such as solar cells, carbon solar cells, sensors, and solid oxide fuel cells, etc. It is observed that often the properties of deposited thin films depend on the preparation conditions. An extensive investigation of the effects of spray parameters on film quality is given to demonstrate the importance of the process of optimization. However, spray pyrolysis seems not useful due to poor quality of thin film, thermal decomposition, and vapor convection. The vapors are generated due to temperature difference, which restricts the source from binding with the substrate. In this paper, briefly study the spray pyrolysis techniques and using the same for metal coating done over polymers. Also, this study highlighted many research obstacles and presented future direction for research in developing new methodology using the inadequacies of the existing approaches.
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