Pub Date : 2023-01-01DOI: 10.18535/ijecs/v12i01.4710
T. Khan
Customer satisfaction has become the primary target for each successful running business currently. They have the true potential in uplifting a tiny business overnight to completely shutting down a brand. Real time analysis of customer opinion (sentiment) is the backbone of this success. Thus this piece of research tries to focus light on the challenges encountered by businesses in four categories of opinion mining. Natural Language Processing with machine learning algorithms works wonders for opinion mining. What is important is the correct choice of opinion mining for a specific type of business as each one of them demands an idiosyncratic approach. The research indeed shares a quick infusion for businesses to safeguard. Countless advice is beared by businesses to have real time analysis, but this research endeavor by showcasing its ideal infusion.
{"title":"Addressing Challenges of Opinion Mining in Businesses","authors":"T. Khan","doi":"10.18535/ijecs/v12i01.4710","DOIUrl":"https://doi.org/10.18535/ijecs/v12i01.4710","url":null,"abstract":"Customer satisfaction has become the primary target for each successful running business currently. They have the true potential in uplifting a tiny business overnight to completely shutting down a brand. Real time analysis of customer opinion (sentiment) is the backbone of this success. Thus this piece of research tries to focus light on the challenges encountered by businesses in four categories of opinion mining. Natural Language Processing with machine learning algorithms works wonders for opinion mining. What is important is the correct choice of opinion mining for a specific type of business as each one of them demands an idiosyncratic approach. The research indeed shares a quick infusion for businesses to safeguard. Countless advice is beared by businesses to have real time analysis, but this research endeavor by showcasing its ideal infusion.","PeriodicalId":231371,"journal":{"name":"International Journal of Engineering and Computer Science","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122133087","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}
Online user data is crucial to the marketing process since it affects consumers' daily lives. False product reviews have a negative impact on the enterprise's capacity to analyse data and make decisions with confidence. Some users have a propensity todisseminate unconfirmed fake news on internet sites.Today, it is crucial to be able to recognise fake reviews.Many websites provide things for sale to consumers online. Purchasing decisions can be made based on product reviews and market demand. On the basis of reviews, consumers determine whether a product is acceptable for use or not. There will be hundreds of comments about the product, some of which may be false. We provide a mechanism to identify fake reviews of items and indicate whether they are reliable or not in order to distinguish between them. This approach for identifying false reviews describes the use of supervised machine learning. This methodology was devised in response to gaps because traditional fake review detection methods classified reviews as authentic or false using either sentiment polarity scores or categorical datasets. By taking into account both polarity ratings and classifiers for false review identification, our method contributes to closing this gap. A survey of already published articles was conducted as part of our effort. Support Vector Machine[2], a machine learning technique, used in our system produced accuracy of 80%.
{"title":"Amazon’s Fake Review Detection using Support Vector Machine","authors":"Om Dhamdhere, Mansi Singh, Abhijeet Dhanwate, Atharva Kumbhar, , Pranali Lokhande","doi":"10.18535/ijecs/v11i12.4708","DOIUrl":"https://doi.org/10.18535/ijecs/v11i12.4708","url":null,"abstract":"Online user data is crucial to the marketing process since it affects consumers' daily lives. False product reviews have a negative impact on the enterprise's capacity to analyse data and make decisions with confidence. Some users have a propensity todisseminate unconfirmed fake news on internet sites.Today, it is crucial to be able to recognise fake reviews.Many websites provide things for sale to consumers online. Purchasing decisions can be made based on product reviews and market demand. On the basis of reviews, consumers determine whether a product is acceptable for use or not. There will be hundreds of comments about the product, some of which may be false. We provide a mechanism to identify fake reviews of items and indicate whether they are reliable or not in order to distinguish between them. This approach for identifying false reviews describes the use of supervised machine learning. This methodology was devised in response to gaps because traditional fake review detection methods classified reviews as authentic or false using either sentiment polarity scores or categorical datasets. By taking into account both polarity ratings and classifiers for false review identification, our method contributes to closing this gap. A survey of already published articles was conducted as part of our effort. Support Vector Machine[2], a machine learning technique, used in our system produced accuracy of 80%.","PeriodicalId":231371,"journal":{"name":"International Journal of Engineering and Computer Science","volume":"64 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133868994","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 : 2022-11-30DOI: 10.18535/ijecs/v11i11.4706
A. Hannan
One of the most recent technological developments, block chain technology has the potential to help a lot of organizations. In order to give readers a better understanding of what block chain technology is and how it works, this paper's main goal is to give an overview of it. The questions that should be asked to determine whether Block chain Technology is the best option for organizations are included in another section of this paper. This section will also provide a summary of how Block chain Technology can benefit businesses. The discussion that follows demonstrates how various industries are currently mastering the technology in order to dominate their fields. This essay will also look at the findings of a study that was done to gauge public awareness of block chain technology.
{"title":"An Examination of the Blockchain Technology: Challenges and Future Opportunities","authors":"A. Hannan","doi":"10.18535/ijecs/v11i11.4706","DOIUrl":"https://doi.org/10.18535/ijecs/v11i11.4706","url":null,"abstract":"One of the most recent technological developments, block chain technology has the potential to help a lot of organizations. In order to give readers a better understanding of what block chain technology is and how it works, this paper's main goal is to give an overview of it. The questions that should be asked to determine whether Block chain Technology is the best option for organizations are included in another section of this paper. This section will also provide a summary of how Block chain Technology can benefit businesses. The discussion that follows demonstrates how various industries are currently mastering the technology in order to dominate their fields. This essay will also look at the findings of a study that was done to gauge public awareness of block chain technology.","PeriodicalId":231371,"journal":{"name":"International Journal of Engineering and Computer Science","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115176949","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 : 2022-11-22DOI: 10.18535/ijecs/v11i11.4701
Carlos Soria, Víctor Rangel R, M. Edwards
This article presents the analysis, design and optimization of a normal radiation helical antenna with medium gain (2dB) and circular polarization as a proposal for use in a network with LoRa technology. The diameter of this antenna for the UHF frequency band would be 10.5cm, for which a parametric study is carried out to miniaturize the dimensions of the helix without losing its characteristics. The parameters and simulation results for a frequency of 915 MHz are presented.
{"title":"Miniaturized helical antenna design for network with LoRa technology","authors":"Carlos Soria, Víctor Rangel R, M. Edwards","doi":"10.18535/ijecs/v11i11.4701","DOIUrl":"https://doi.org/10.18535/ijecs/v11i11.4701","url":null,"abstract":"This article presents the analysis, design and optimization of a normal radiation helical antenna with medium gain (2dB) and circular polarization as a proposal for use in a network with LoRa technology. The diameter of this antenna for the UHF frequency band would be 10.5cm, for which a parametric study is carried out to miniaturize the dimensions of the helix without losing its characteristics. The parameters and simulation results for a frequency of 915 MHz are presented.","PeriodicalId":231371,"journal":{"name":"International Journal of Engineering and Computer Science","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131178019","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 : 2022-09-22DOI: 10.18535/ijecs/v11i09.4699
Carlos Soria, Víctor Rangel R, R. Edwards
This article presents the analysis, design, simulation, construction and characterization of an axial radiation helical antenna with medium gain (11dBi) and circular polarization as a proposed use for the emergency water information network. Due to its application in the earth station, there are no dimensional limits. The parameters and results for an operating frequency of 915 MHz are presented.
{"title":"Helicoidal antenna in RIVERcore device for the Emergency Water Information Network","authors":"Carlos Soria, Víctor Rangel R, R. Edwards","doi":"10.18535/ijecs/v11i09.4699","DOIUrl":"https://doi.org/10.18535/ijecs/v11i09.4699","url":null,"abstract":"This article presents the analysis, design, simulation, construction and characterization of an axial radiation helical antenna with medium gain (11dBi) and circular polarization as a proposed use for the emergency water information network. Due to its application in the earth station, there are no dimensional limits. The parameters and results for an operating frequency of 915 MHz are presented.","PeriodicalId":231371,"journal":{"name":"International Journal of Engineering and Computer Science","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123695804","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 : 2022-09-17DOI: 10.18535/ijecs/v11i09.4696
Johnson Kannepamula
{"title":"conversion of flowchart to C program(Source code )","authors":"Johnson Kannepamula","doi":"10.18535/ijecs/v11i09.4696","DOIUrl":"https://doi.org/10.18535/ijecs/v11i09.4696","url":null,"abstract":"<jats:p />","PeriodicalId":231371,"journal":{"name":"International Journal of Engineering and Computer Science","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115922502","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 : 2022-09-08DOI: 10.18535/ijecs/v11i09.4656
Mehboob Ali, Vinod Sharma, M. Ali
With the advent of deep neural networks, application of machine learning in multidisciplinary problems enhanced many folds. Many unsolvable problems previously sought as complex to compute are now made solvable by deep neural network techniques. Problems like protein folding by Alpha-fold and Alpha-Go are prime examples. In this study six well known convolutional neural networks are applied for the classification of uterine cervix cancer cases for both seven class and two class classification. A primary dataset was also created by collecting raw slide samples form the leading medical institutes. The machine learning techniques do require set of well-crafted feature values representing the ground truth. Many times, these features fail to represent the ground truth. The deep neural networks can extract all the relevant features itself and those extracted features are used for final classification. In this work the convolutional neural networks are used for extraction of features which are the used for training shallow neural networks. The shallow neural networks used are Levenberg Marquardt neural network, One Step Secant and Scaled Conjugate gradient descent. The results indicated that among the 6 convolutional neural networks the ResNet50 is best and among the three shallow neural network Levenberg Marquardt is best for both seven and two class classification. The duo (ResNet50 and Levenberg Marquardt) produced a classification accuracy of 82.92%. Among all the classes of diagnosis, class 7 has the best F-value followed by class 1, whereas class 4 has the lowest F- value followed by class 5 and class 2. Lowest F-value indicates maximum misclassification. For two-class classification, duo (ResNet50 and Levenberg Marquardt) produced classification accuracy is 94.77%. The F-value of both the classes is above 92% for all the combination of CNN and shallow neural network. The results do conclude that the deep neural networks can easily classify the cases of cervical cancer with notable accuracy, without feature extraction.
{"title":"Deep-Neural Networks as feature extractors and monolithic neural networks as classifiers, for classification of uterine cervix cancer cases","authors":"Mehboob Ali, Vinod Sharma, M. Ali","doi":"10.18535/ijecs/v11i09.4656","DOIUrl":"https://doi.org/10.18535/ijecs/v11i09.4656","url":null,"abstract":"With the advent of deep neural networks, application of machine learning in multidisciplinary problems enhanced many folds. Many unsolvable problems previously sought as complex to compute are now made solvable by deep neural network techniques. Problems like protein folding by Alpha-fold and Alpha-Go are prime examples. \u0000In this study six well known convolutional neural networks are applied for the classification of uterine cervix cancer cases for both seven class and two class classification. A primary dataset was also created by collecting raw slide samples form the leading medical institutes. The machine learning techniques do require set of well-crafted feature values representing the ground truth. Many times, these features fail to represent the ground truth. The deep neural networks can extract all the relevant features itself and those extracted features are used for final classification. In this work the convolutional neural networks are used for extraction of features which are the used for training shallow neural networks. The shallow neural networks used are Levenberg Marquardt neural network, One Step Secant and Scaled Conjugate gradient descent. The results indicated that among the 6 convolutional neural networks the ResNet50 is best and among the three shallow neural network Levenberg Marquardt is best for both seven and two class classification. The duo (ResNet50 and Levenberg Marquardt) produced a classification accuracy of 82.92%. Among all the classes of diagnosis, class 7 has the best F-value followed by class 1, whereas class 4 has the lowest F- value followed by class 5 and class 2. Lowest F-value indicates maximum misclassification. For two-class classification, duo (ResNet50 and Levenberg Marquardt) produced classification accuracy is 94.77%. The F-value of both the classes is above 92% for all the combination of CNN and shallow neural network. \u0000The results do conclude that the deep neural networks can easily classify the cases of cervical cancer with notable accuracy, without feature extraction.","PeriodicalId":231371,"journal":{"name":"International Journal of Engineering and Computer Science","volume":"265 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116048733","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 : 2022-08-29DOI: 10.18535/ijecs/v11i08.4695
Dnyaneshwari P.Wagh, Fadewar H.S, S. G. N., Santosh P. Shrikhande
Every person has a unique finger vein pattern existing within each finger. Unlike facial features or fingerprints, finger vein authentication systems aren’t vulnerable to forgery. Finger vein authentication systems are more secure and reliable, and less expensive, than biometric security systems using fingerprint. This paper presents a novel security framework based on finger vein pattern. Finger Vein pattern in used in ID based cryptography to generate the keys for data encryption. These keys are combined with generator of Elliptic Curve Cryptography (ECC) to exchange the keys using Diffie Hellman key exchange algorithm. Once the keys are exchanged, the data is encrypted using Advance Encryption Standard (AES). This framework is tested in Internet of Things (IoT) environment for enhancing the security. The IoT based security systems implemented in the banks and other organizations can be enhanced considerably using the proposed security model.
{"title":"A Finger Vein Pattern based Key GenerationExchange and Security framework for IoT using ID based cryptography, ECDH and AES","authors":"Dnyaneshwari P.Wagh, Fadewar H.S, S. G. N., Santosh P. Shrikhande","doi":"10.18535/ijecs/v11i08.4695","DOIUrl":"https://doi.org/10.18535/ijecs/v11i08.4695","url":null,"abstract":"Every person has a unique finger vein pattern existing within each finger. Unlike facial features or fingerprints, finger vein authentication systems aren’t vulnerable to forgery. Finger vein authentication systems are more secure and reliable, and less expensive, than biometric security systems using fingerprint. This paper presents a novel security framework based on finger vein pattern. Finger Vein pattern in used in ID based cryptography to generate the keys for data encryption. These keys are combined with generator of Elliptic Curve Cryptography (ECC) to exchange the keys using Diffie Hellman key exchange algorithm. Once the keys are exchanged, the data is encrypted using Advance Encryption Standard (AES). This framework is tested in Internet of Things (IoT) environment for enhancing the security. The IoT based security systems implemented in the banks and other organizations can be enhanced considerably using the proposed security model.","PeriodicalId":231371,"journal":{"name":"International Journal of Engineering and Computer Science","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132878413","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 : 2022-07-22DOI: 10.18535/ijecs/v11i07.4682
PAGALLA BHAVANI SHANKAR, P L N PRAKASH KUMAR, Lakshmi Prasanna Pulipaka
Data is a word plays a vital role in every kind of aspects. In earlier days data can be expressed manually through communication channels. Day by day technology is enhanced in various etiquette. As per trends, technology is directly proportional to the data. Data will be transmitted from source to destination by using communication channel at wide range massively. The massive data is produced at the moment by using social media, as per today’s technology. Data communication will be passing through internet by adopting various kinds of several media platforms (Face book, twitter, snap chat). Raw data is in the form of unstructured where it moves to social media platforms. Unstructured data is unreadable in nature. To overcome this factor Social Media Analytics (SMA) is a weapon to organize the unstructured data into the manner of structured. To perform the analysis on the unstructured data, need to adopt different analytics tools. Among the different analytical tools, Tanagra is the best optimized tool to organized and analyzed the unstructured data and produces the users concerned data. Keywords: Structured Data, Unstructured Data, Social Media, Social Media Analytics
{"title":"Era of Social Media Analytic Tools: A New Approach","authors":"PAGALLA BHAVANI SHANKAR, P L N PRAKASH KUMAR, Lakshmi Prasanna Pulipaka","doi":"10.18535/ijecs/v11i07.4682","DOIUrl":"https://doi.org/10.18535/ijecs/v11i07.4682","url":null,"abstract":"Data is a word plays a vital role in every kind of aspects. In earlier days data can be expressed manually through communication channels. Day by day technology is enhanced in various etiquette. As per trends, technology is directly proportional to the data. Data will be transmitted from source to destination by using communication channel at wide range massively. The massive data is produced at the moment by using social media, as per today’s technology. Data communication will be passing through internet by adopting various kinds of several media platforms (Face book, twitter, snap chat). Raw data is in the form of unstructured where it moves to social media platforms. Unstructured data is unreadable in nature. To overcome this factor Social Media Analytics (SMA) is a weapon to organize the unstructured data into the manner of structured. To perform the analysis on the unstructured data, need to adopt different analytics tools. Among the different analytical tools, Tanagra is the best optimized tool to organized and analyzed the unstructured data and produces the users concerned data. \u0000Keywords: Structured Data, Unstructured Data, Social Media, Social Media Analytics","PeriodicalId":231371,"journal":{"name":"International Journal of Engineering and Computer Science","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130005363","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 : 2022-07-18DOI: 10.18535/ijecs/v11i07.4679
R. Regan, Jayashree J, Kurmitha M
The Internet of Objects (IoT) could be a new paradigm for the linked, data-exchanging nature of things and their parts through a network supported by nodes. IoT has risen to the forefront of emerging technologies in a very type of applications, including peer-to-peer networks, smart energy grids, home and building automation, vehicle-to-vehicle communication, and wearable computing devices, because of the widespread use of small devices and embedded sensor frameworks. thanks to its tremendous expansion and widespread use, it's posed security issues that may prevent it from getting used during a style of new applications. The growing number of networked gadgets creates several access points for attackers, also as security issues. due to the fragile nature of IoT applications including health, automation, and energy grids, security concerns can't be tolerated. DLT (Distributed Ledger Technology) is one such technology which will help to mitigate IoT security threats. The vulnerability of a central node, which can compromise the whole system, are often reduced by adopting a distributed ledger to eliminate the necessity for one node. Blockchain, a distributed ledger technology, has sparked plenty of interest and generated real-world value. Here we construct a distributed multi ledger construction algorithm for peer-to-peer data transaction which involves key generation for each transaction.
{"title":"Smart Distributed Multi-Ledger Construction Algorithm for Internet of things (IoT)","authors":"R. Regan, Jayashree J, Kurmitha M","doi":"10.18535/ijecs/v11i07.4679","DOIUrl":"https://doi.org/10.18535/ijecs/v11i07.4679","url":null,"abstract":"The Internet of Objects (IoT) could be a new paradigm for the linked, data-exchanging nature of things and their parts through a network supported by nodes. IoT has risen to the forefront of emerging technologies in a very type of applications, including peer-to-peer networks, smart energy grids, home and building automation, vehicle-to-vehicle communication, and wearable computing devices, because of the widespread use of small devices and embedded sensor frameworks. thanks to its tremendous expansion and widespread use, it's posed security issues that may prevent it from getting used during a style of new applications. The growing number of networked gadgets creates several access points for attackers, also as security issues. due to the fragile nature of IoT applications including health, automation, and energy grids, security concerns can't be tolerated. DLT (Distributed Ledger Technology) is one such technology which will help to mitigate IoT security threats. The vulnerability of a central node, which can compromise the whole system, are often reduced by adopting a distributed ledger to eliminate the necessity for one node. Blockchain, a distributed ledger technology, has sparked plenty of interest and generated real-world value. Here we construct a distributed multi ledger construction algorithm for peer-to-peer data transaction which involves key generation for each transaction.","PeriodicalId":231371,"journal":{"name":"International Journal of Engineering and Computer Science","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130697179","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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