Pub Date : 2024-07-03DOI: 10.15406/mseij.2024.08.00239
Al-Mahmud Al Mamun, Md Rasel Hossain, Mst Mahfuza Sharmin
Quality control in metal product manufacturing relies heavily on accurately detecting and classifying surface defects through visual inspection. Recently, convolutional neural networks (CNNs) have shown promising results in automating this process with high accuracy. This research paper proposes a new (experimental version) Lite Convolutional Neural Network (LCNN) designed to analyze image data to detect and classify surface defects on metallic surfaces. Our model was trained on a metal surface defects dataset comprising 1800 images of six different types of surface defects. Despite using relatively small datasets, the proposed LCNN version achieves a classification accuracy of 91.67%, highlighting its effectiveness in real-world defect detection scenarios.
{"title":"Detection and classification of metal surface defects using lite convolutional neural network (LCNN)","authors":"Al-Mahmud Al Mamun, Md Rasel Hossain, Mst Mahfuza Sharmin","doi":"10.15406/mseij.2024.08.00239","DOIUrl":"https://doi.org/10.15406/mseij.2024.08.00239","url":null,"abstract":"Quality control in metal product manufacturing relies heavily on accurately detecting and classifying surface defects through visual inspection. Recently, convolutional neural networks (CNNs) have shown promising results in automating this process with high accuracy. This research paper proposes a new (experimental version) Lite Convolutional Neural Network (LCNN) designed to analyze image data to detect and classify surface defects on metallic surfaces. Our model was trained on a metal surface defects dataset comprising 1800 images of six different types of surface defects. Despite using relatively small datasets, the proposed LCNN version achieves a classification accuracy of 91.67%, highlighting its effectiveness in real-world defect detection scenarios.","PeriodicalId":435904,"journal":{"name":"Material Science & Engineering International Journal","volume":"118 s1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141682069","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 : 2024-04-02DOI: 10.15406/mseij.2024.08.00231
Al Mahmud Al Mamun, Md. Ashik Iqbal, Md Rasel Hossain, Mst. Mahfuza Sharmin, Md Ziaul Haque
Near-Earth asteroids (NEAs) are celestial bodies that orbit within close to Earth, offering valuable insights into the early solar system's formation and posing potential hazards due to impact events. This work presents a comprehensive overview of NEAs, encompassing their historical significance, characteristics, impact hazards, and prospects. The study outlines the NASA Asteroids Classification Dataset and discusses its importance for research on asteroid classification and risk assessment. Furthermore, the methodology section delineates the utilization of the NGBoost classifier for predictive modeling tasks, detailing data collection, preprocessing, model training, evaluation, and result interpretation. Results from the NGBoost classifier demonstrate high accuracy and performance metrics in classifying asteroids, underscoring its efficacy in advancing asteroid classification efforts and informing planetary defense strategies. NEAs pose a potential threat to our planet, and their classification is essential for understanding their properties and predicting their trajectories accurately. In this research, we explore the application of NGBoost, a powerful gradient-boosting framework, for classifying NEAs based on their orbital and physical characteristics. We present a dataset comprising features extracted from known NEAs and non-NEAs and demonstrate the efficacy of NGBoost in accurately distinguishing between these classes. Our results indicate promising performance metrics with 99.22% accuracy, suggesting that NGBoost holds potential as a valuable tool in asteroid classification.
{"title":"Near-earth asteroids classification using NGBoost classifier","authors":"Al Mahmud Al Mamun, Md. Ashik Iqbal, Md Rasel Hossain, Mst. Mahfuza Sharmin, Md Ziaul Haque","doi":"10.15406/mseij.2024.08.00231","DOIUrl":"https://doi.org/10.15406/mseij.2024.08.00231","url":null,"abstract":"Near-Earth asteroids (NEAs) are celestial bodies that orbit within close to Earth, offering valuable insights into the early solar system's formation and posing potential hazards due to impact events. This work presents a comprehensive overview of NEAs, encompassing their historical significance, characteristics, impact hazards, and prospects. The study outlines the NASA Asteroids Classification Dataset and discusses its importance for research on asteroid classification and risk assessment. Furthermore, the methodology section delineates the utilization of the NGBoost classifier for predictive modeling tasks, detailing data collection, preprocessing, model training, evaluation, and result interpretation. Results from the NGBoost classifier demonstrate high accuracy and performance metrics in classifying asteroids, underscoring its efficacy in advancing asteroid classification efforts and informing planetary defense strategies. NEAs pose a potential threat to our planet, and their classification is essential for understanding their properties and predicting their trajectories accurately. In this research, we explore the application of NGBoost, a powerful gradient-boosting framework, for classifying NEAs based on their orbital and physical characteristics. We present a dataset comprising features extracted from known NEAs and non-NEAs and demonstrate the efficacy of NGBoost in accurately distinguishing between these classes. Our results indicate promising performance metrics with 99.22% accuracy, suggesting that NGBoost holds potential as a valuable tool in asteroid classification.","PeriodicalId":435904,"journal":{"name":"Material Science & Engineering International Journal","volume":"41 27","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140752292","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 : 2024-01-22DOI: 10.15406/mseij.2024.08.00229
Syed Talat Ali, Annmette Riis, Raine Mikael Larsen
The crevice corrosion propagation modes and repassivation potential of stainless steel AISI 316 in chloride solution were compared using cyclic potentiodynamic polarization (CPP), potentiodynamic-galvanostatic-potentiodynamic (PD-GS-PD) and Tsujikawa– Hisamatsu electrochemical (THE) methods. The PD-GS-PD method was found to be the most conservative electrochemical technique which delivered the lowest repassivation potential value in a relatively short time. The crevice corrosion propagation modes in these three electrochemical methods were also compared with crevice corrosion propagation mode in galvanically coupled small area stainless steel AISI 316 anode with large area titanium cathode. The crevice corrosion propagation mode achieved in galvanically coupled AISI 316 anode at open circuit potential simulated the crevice corrosion propagation mode in real systems. The crevice corrosion propagation modes achieved in PD-GS-PD and THE methods mimicked the crevice corrosion propagation in real systems.
{"title":"Comparison of test methods for crevice corrosion propagation and repassivation potential of stainless steel AISI 316","authors":"Syed Talat Ali, Annmette Riis, Raine Mikael Larsen","doi":"10.15406/mseij.2024.08.00229","DOIUrl":"https://doi.org/10.15406/mseij.2024.08.00229","url":null,"abstract":"The crevice corrosion propagation modes and repassivation potential of stainless steel AISI 316 in chloride solution were compared using cyclic potentiodynamic polarization (CPP), potentiodynamic-galvanostatic-potentiodynamic (PD-GS-PD) and Tsujikawa– Hisamatsu electrochemical (THE) methods. The PD-GS-PD method was found to be the most conservative electrochemical technique which delivered the lowest repassivation potential value in a relatively short time. The crevice corrosion propagation modes in these three electrochemical methods were also compared with crevice corrosion propagation mode in galvanically coupled small area stainless steel AISI 316 anode with large area titanium cathode. The crevice corrosion propagation mode achieved in galvanically coupled AISI 316 anode at open circuit potential simulated the crevice corrosion propagation mode in real systems. The crevice corrosion propagation modes achieved in PD-GS-PD and THE methods mimicked the crevice corrosion propagation in real systems.","PeriodicalId":435904,"journal":{"name":"Material Science & Engineering International Journal","volume":"4 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140499433","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 : 2024-01-19DOI: 10.15406/mseij.2024.08.00228
Frank Edward Tadeo Espinoza, Marco Antonio Coral Ygnacio
This paper deals with the development of a credit risk assessment system using multilayer neural networks. The main objective of this work is to provide a decision support tool for risk assessment, considering relevant variables in the process. To achieve this objective, the backpropagation algorithm and the Adam optimizer were used to train the model. In terms of materials and methods, a training and validation data set including relevant financial information of credit applicants was used. A multilayer neural network was implemented that made predictions and calculated the loss using the categorical cross-entropy function. The results obtained during the development of the system showed a favorable performance and a satisfactory level of accuracy in identifying and classifying different levels of credit risk. However, it is emphasized that the system does not provide absolute results; human intervention is recommended as a last resort for decision making
{"title":"Development of a credit risk evaluation system using multilayer neural networks","authors":"Frank Edward Tadeo Espinoza, Marco Antonio Coral Ygnacio","doi":"10.15406/mseij.2024.08.00228","DOIUrl":"https://doi.org/10.15406/mseij.2024.08.00228","url":null,"abstract":"This paper deals with the development of a credit risk assessment system using multilayer neural networks. The main objective of this work is to provide a decision support tool for risk assessment, considering relevant variables in the process. To achieve this objective, the backpropagation algorithm and the Adam optimizer were used to train the model. In terms of materials and methods, a training and validation data set including relevant financial information of credit applicants was used. A multilayer neural network was implemented that made predictions and calculated the loss using the categorical cross-entropy function. The results obtained during the development of the system showed a favorable performance and a satisfactory level of accuracy in identifying and classifying different levels of credit risk. However, it is emphasized that the system does not provide absolute results; human intervention is recommended as a last resort for decision making","PeriodicalId":435904,"journal":{"name":"Material Science & Engineering International Journal","volume":"56 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140502905","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 : 2023-08-23DOI: 10.15406/mseij.2023.07.00218
N. Ravindra, S. Hossain, Airefetalo Sadoh
The unique temperature-induced color changing properties of thermochromic materials make them of significant interest for applications in aerospace, anti-counterfeiting technology, construction, defense, drugs & pharmaceuticals, electronics, energy, food & agriculture, maintenance of infrastructure, materials processing & storage, military technology, optoelectronics, packaging, sensors, smart displays, textiles, thermal storage and transportation. Thermochromism occurs due to the following characteristics: (a) phase transitions in a compound (e.g. leuco dyes); (b) changes in ligand geometry or the number of solvent molecules in the coordination sphere (e.g. transition metal complex that derives its color from crystal field effects) and (c) complex factors in multicomponent mixtures. Thermochromic materials can be divided into several categories depending on their material properties and operating conditions. In recent years, numerous techniques have been used to synthesize thermochromic materials for a variety of purposes and applications. This review summarizes the various mechanisms of thermochromism, their classification, preparation and applications and discusses future development trends.
{"title":"Principles, properties and preparation of thermochromic materials","authors":"N. Ravindra, S. Hossain, Airefetalo Sadoh","doi":"10.15406/mseij.2023.07.00218","DOIUrl":"https://doi.org/10.15406/mseij.2023.07.00218","url":null,"abstract":"The unique temperature-induced color changing properties of thermochromic materials make them of significant interest for applications in aerospace, anti-counterfeiting technology, construction, defense, drugs & pharmaceuticals, electronics, energy, food & agriculture, maintenance of infrastructure, materials processing & storage, military technology, optoelectronics, packaging, sensors, smart displays, textiles, thermal storage and transportation. Thermochromism occurs due to the following characteristics: (a) phase transitions in a compound (e.g. leuco dyes); (b) changes in ligand geometry or the number of solvent molecules in the coordination sphere (e.g. transition metal complex that derives its color from crystal field effects) and (c) complex factors in multicomponent mixtures. Thermochromic materials can be divided into several categories depending on their material properties and operating conditions. In recent years, numerous techniques have been used to synthesize thermochromic materials for a variety of purposes and applications. This review summarizes the various mechanisms of thermochromism, their classification, preparation and applications and discusses future development trends.","PeriodicalId":435904,"journal":{"name":"Material Science & Engineering International Journal","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132744006","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 : 2023-06-06DOI: 10.15406/mseij.2023.07.00212
Jinwu Kang
{"title":"Materials research in artificial intelligence era","authors":"Jinwu Kang","doi":"10.15406/mseij.2023.07.00212","DOIUrl":"https://doi.org/10.15406/mseij.2023.07.00212","url":null,"abstract":"","PeriodicalId":435904,"journal":{"name":"Material Science & Engineering International Journal","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139370798","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 : 2023-05-19DOI: 10.15406/mseij.2023.07.00210
N. Ravindra, Leqi Lin, B. Bora, B. Prasad, OS Sastry, S. Mondal
The utilization of renewable sources of energy is of significant interest today. This is particularly the case due to the growing interest in addressing global warming, carbon footprint and the associated challenges for the environment. In this context, the enhanced use of solar panels is relevant and timely. With a view to understand and appreciate the fundamentals of the workings of the solar panels and the influence of the outdoor weather-related parameters on their operational characteristics, a study is presented in this paper. A detailed procedure for performance measurement of PV modules in outdoor conditions is reported. Improvement in the precision of outdoor performance measurements of photovoltaic (PV) modules is investigated for a wide range of outdoor conditions. A comparative performance evaluation of the currently available PV modules under the influence of humidity, irradiance and particle radiation is presented. PV parameters show strong dependence on these outdoor conditions. The instability in solar cell modules when reacting with water or under high humidity inhibits the high performance of solar cell modules. Irradiation results depict that the silicon-based PV modules show a decreasing trend of power conversion efficiency with increasing solar irradiance. The efficiency increases with increased solar irradiance for CdTe, GaAs and CIGS solar cells in the irradiance range of 200 to 1000 W•m-2. Tandem and multi-junction solar cells exhibit a high-power conversion efficiency when the solar irradiance increases from 0 - 70 suns. Perovskite solar cells have better particle radiation tolerance than silicon, III-V and CIGS solar cells. The shading problem is discussed briefly for solar cell modules. This study is aimed to provide valuable and comparable information on the degradation performance of solar cells as function of humidity, irradiance and particle radiation, and serves as the basis for future development.
{"title":"Influence of outdoor conditions on PV module performance – an overview","authors":"N. Ravindra, Leqi Lin, B. Bora, B. Prasad, OS Sastry, S. Mondal","doi":"10.15406/mseij.2023.07.00210","DOIUrl":"https://doi.org/10.15406/mseij.2023.07.00210","url":null,"abstract":"The utilization of renewable sources of energy is of significant interest today. This is particularly the case due to the growing interest in addressing global warming, carbon footprint and the associated challenges for the environment. In this context, the enhanced use of solar panels is relevant and timely. With a view to understand and appreciate the fundamentals of the workings of the solar panels and the influence of the outdoor weather-related parameters on their operational characteristics, a study is presented in this paper. A detailed procedure for performance measurement of PV modules in outdoor conditions is reported. Improvement in the precision of outdoor performance measurements of photovoltaic (PV) modules is investigated for a wide range of outdoor conditions. A comparative performance evaluation of the currently available PV modules under the influence of humidity, irradiance and particle radiation is presented. PV parameters show strong dependence on these outdoor conditions. The instability in solar cell modules when reacting with water or under high humidity inhibits the high performance of solar cell modules. Irradiation results depict that the silicon-based PV modules show a decreasing trend of power conversion efficiency with increasing solar irradiance. The efficiency increases with increased solar irradiance for CdTe, GaAs and CIGS solar cells in the irradiance range of 200 to 1000 W•m-2. Tandem and multi-junction solar cells exhibit a high-power conversion efficiency when the solar irradiance increases from 0 - 70 suns. Perovskite solar cells have better particle radiation tolerance than silicon, III-V and CIGS solar cells. The shading problem is discussed briefly for solar cell modules. This study is aimed to provide valuable and comparable information on the degradation performance of solar cells as function of humidity, irradiance and particle radiation, and serves as the basis for future development.","PeriodicalId":435904,"journal":{"name":"Material Science & Engineering International Journal","volume":"202 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125733553","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 : 2023-05-15DOI: 10.15406/mseij.2023.07.00209
PK Vishwakarma, P. Jaget, M. Parte, V.S. Lodhi, R. Maurya
We report here the experimental and theoretical investigation of the bis(4-furoyl-3-methyl-1-phenyl-2-pyrazolin-5-one)oxoperoxomolybdenum(VI) complex molecule. It was prepared by the reaction of (2:1) 4-furoyl-3-methyl-1-phenyl-2-pyrazolin-5-one and [MoO(O)2]2+ in an aqueous ethanol medium. Characterization was performed by elemental analysis, molar conductivity, magnetic measurements, electrochemical analysis, and infrared and electronic spectral studies. Theoretical validation was performed by density functional theory calculations using B3LYP as the LANL2DZ function. The molecular geometry results show a distorted pseudo-pentagonal bipyramidal geometry together with the O7 coordination mode around the Mo(VI) center. The FMO energies allow the determination of the atomic and molecular parameters and also represent the charge transfer across the molecule.
{"title":"Material of oxo-peroxo-molybdenum (VI) complex involving 4-Furoyl-3-methyl-1-phenyl-2-pyrazoline-5- one: experimental cum theoretical observations","authors":"PK Vishwakarma, P. Jaget, M. Parte, V.S. Lodhi, R. Maurya","doi":"10.15406/mseij.2023.07.00209","DOIUrl":"https://doi.org/10.15406/mseij.2023.07.00209","url":null,"abstract":"We report here the experimental and theoretical investigation of the bis(4-furoyl-3-methyl-1-phenyl-2-pyrazolin-5-one)oxoperoxomolybdenum(VI) complex molecule. It was prepared by the reaction of (2:1) 4-furoyl-3-methyl-1-phenyl-2-pyrazolin-5-one and [MoO(O)2]2+ in an aqueous ethanol medium. Characterization was performed by elemental analysis, molar conductivity, magnetic measurements, electrochemical analysis, and infrared and electronic spectral studies. Theoretical validation was performed by density functional theory calculations using B3LYP as the LANL2DZ function. The molecular geometry results show a distorted pseudo-pentagonal bipyramidal geometry together with the O7 coordination mode around the Mo(VI) center. The FMO energies allow the determination of the atomic and molecular parameters and also represent the charge transfer across the molecule.","PeriodicalId":435904,"journal":{"name":"Material Science & Engineering International Journal","volume":"7 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132738491","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 : 2023-05-12DOI: 10.15406/mseij.2023.07.00208
Ottávio Carmignano, Paulo Roberto G Brandao
The serpentinite rock is formed by minerals of the serpentine group, such as antigorite and lizardite, and can be found in several countries around the world. It has several commercial applications, among them its use as an ornamental rock. It can be found in numerous constructions, such as churches, houses and buildings. However, trade names are adopted for ornamental rocks, making it difficult to identify and confirm the existence of the specific rock in buildings. Using bibliographical research, the present work aims to study the use of serpentinite as an ornamental rock, identifying its first applications in the world and presenting commercial names adopted for this rock, allowing a better understanding of the relevance of this rock in world architecture. More than sixty commercial names of serpentinites used as ornamental rocks, in different applications, throughout different civilizations, were found.
{"title":"Employment of serpentinite rock in architecture","authors":"Ottávio Carmignano, Paulo Roberto G Brandao","doi":"10.15406/mseij.2023.07.00208","DOIUrl":"https://doi.org/10.15406/mseij.2023.07.00208","url":null,"abstract":"The serpentinite rock is formed by minerals of the serpentine group, such as antigorite and lizardite, and can be found in several countries around the world. It has several commercial applications, among them its use as an ornamental rock. It can be found in numerous constructions, such as churches, houses and buildings. However, trade names are adopted for ornamental rocks, making it difficult to identify and confirm the existence of the specific rock in buildings. Using bibliographical research, the present work aims to study the use of serpentinite as an ornamental rock, identifying its first applications in the world and presenting commercial names adopted for this rock, allowing a better understanding of the relevance of this rock in world architecture. More than sixty commercial names of serpentinites used as ornamental rocks, in different applications, throughout different civilizations, were found.","PeriodicalId":435904,"journal":{"name":"Material Science & Engineering International Journal","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133607120","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 : 2023-05-11DOI: 10.15406/mseij.2023.07.00207
Sunil Sharma, L. Tharani
Pancreatic cancer (PC) is a lethal disease that is difficult to diagnose in its early stages. This is the reason it is deadly known as “The silent killer”. Traditional diagnostic methods are often invasive and can lead to misdiagnosis. The purpose of this manuscript is to propose photonic crystal fibers (PCFs) based artificial intelligence (AI) systems to materialize it as a promising tool for diagnosing pancreatic cancer. PCFs are optical fibers (OFs) that allow for the detection of light at high resolution and used to analyze the biochemical composition of tissues samples and feed the resulting data into an AI algorithm. The proposed system has the potential to significantly improve the early detection and diagnosis of pancreatic cancer, which lead to better outcomes. The Decision Tree (DT) model achieved an accuracy of 86.8%, a sensitivity of 81.6%, and a specificity of 90.3%. The Support Vector Machine (SVM) model achieved an accuracy of 90.9%, a sensitivity of 95.7%, and a specificity of 86.0%. The K-nearest neighbor (KNN) model achieved an accuracy of 90.8%, a sensitivity of 91.7%, and a specificity of 89.1%.
{"title":"Photonic crystal fiber based automated system to diagnose silent killer","authors":"Sunil Sharma, L. Tharani","doi":"10.15406/mseij.2023.07.00207","DOIUrl":"https://doi.org/10.15406/mseij.2023.07.00207","url":null,"abstract":"Pancreatic cancer (PC) is a lethal disease that is difficult to diagnose in its early stages. This is the reason it is deadly known as “The silent killer”. Traditional diagnostic methods are often invasive and can lead to misdiagnosis. The purpose of this manuscript is to propose photonic crystal fibers (PCFs) based artificial intelligence (AI) systems to materialize it as a promising tool for diagnosing pancreatic cancer. PCFs are optical fibers (OFs) that allow for the detection of light at high resolution and used to analyze the biochemical composition of tissues samples and feed the resulting data into an AI algorithm. The proposed system has the potential to significantly improve the early detection and diagnosis of pancreatic cancer, which lead to better outcomes. The Decision Tree (DT) model achieved an accuracy of 86.8%, a sensitivity of 81.6%, and a specificity of 90.3%. The Support Vector Machine (SVM) model achieved an accuracy of 90.9%, a sensitivity of 95.7%, and a specificity of 86.0%. The K-nearest neighbor (KNN) model achieved an accuracy of 90.8%, a sensitivity of 91.7%, and a specificity of 89.1%.","PeriodicalId":435904,"journal":{"name":"Material Science & Engineering International Journal","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121925611","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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