Pub Date : 2021-11-29DOI: 10.1142/s1793962322500246
A. Sedelnikov, S. Glushkov, V. Serdakova, M. Evtushenko, E. Khnyryova
The paper is devoted to simulating the impact of a thermal shock on a thin homogeneous plate in the ANSYS package. The assessment of the stress–strain state is carried out and the dynamics of changes in the temperature field of the plate is determined. The obtained results were compared with the data of other authors and can be used when taking into account the thermal shock of large elastic elements of spacecraft.
{"title":"Simulating the stress-strain state of a thin plate after a thermal shock","authors":"A. Sedelnikov, S. Glushkov, V. Serdakova, M. Evtushenko, E. Khnyryova","doi":"10.1142/s1793962322500246","DOIUrl":"https://doi.org/10.1142/s1793962322500246","url":null,"abstract":"The paper is devoted to simulating the impact of a thermal shock on a thin homogeneous plate in the ANSYS package. The assessment of the stress–strain state is carried out and the dynamics of changes in the temperature field of the plate is determined. The obtained results were compared with the data of other authors and can be used when taking into account the thermal shock of large elastic elements of spacecraft.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73126119","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 : 2021-11-29DOI: 10.1142/s1793962323410052
Yan Chen
{"title":"Design and simulation of AI remote terminal user identity recognition system based on reinforcement learning","authors":"Yan Chen","doi":"10.1142/s1793962323410052","DOIUrl":"https://doi.org/10.1142/s1793962323410052","url":null,"abstract":"","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78257373","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 : 2021-11-29DOI: 10.1142/s1793962322500386
Leila Esmaeili, M. Niaparast
{"title":"New compounding lifetime distributions with applications to real data","authors":"Leila Esmaeili, M. Niaparast","doi":"10.1142/s1793962322500386","DOIUrl":"https://doi.org/10.1142/s1793962322500386","url":null,"abstract":"","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91382748","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 : 2021-11-24DOI: 10.1142/s1793962323410027
N. Khan, R. Mahalakshmi
Recommendation systems are shrewd applications for knowledge mining that profoundly handle the problem of data overload. Various literature explores different philosophies to create ideas and recommends different strategies according to the needs of customers. Most of the work in the suggested structure space focuses on extending the accuracy of the recommendation by using a few possible methods where the principle purpose remains to improve the accuracy of suggestions while avoiding other plan objectives, such as the particular situation of a client. By using appropriate customer rating data, the biggest test for a suggested system is to generate substantial proposals. A setting is an enormous concept that can think of numerous points of view: for example, the community of friends of a client, time, mindset, environment, organization, type of day, classification of an item, description of the object, place, and language. The rating behavior of customers typically varies in different environments. We have proposed a new review-based contextual recommender (RBCR) system application from this line of analysis, in particular a novel recommender system, which is an adaptable, quick, and accurate piece planning framework that perceives the significance of setting and fuses the logical data using piece stunt while making expectations. We have contrasted our suggested calculation with pre- and post-sifting methods as they have been the most common methodologies in writing to illuminate the issue of setting conscious suggestion. Our studies show that considering the logical data, the display of a system will increase and provide better, appropriate and important results on various evaluation measurements.
{"title":"A novel user review-based contextual recommender system","authors":"N. Khan, R. Mahalakshmi","doi":"10.1142/s1793962323410027","DOIUrl":"https://doi.org/10.1142/s1793962323410027","url":null,"abstract":"Recommendation systems are shrewd applications for knowledge mining that profoundly handle the problem of data overload. Various literature explores different philosophies to create ideas and recommends different strategies according to the needs of customers. Most of the work in the suggested structure space focuses on extending the accuracy of the recommendation by using a few possible methods where the principle purpose remains to improve the accuracy of suggestions while avoiding other plan objectives, such as the particular situation of a client. By using appropriate customer rating data, the biggest test for a suggested system is to generate substantial proposals. A setting is an enormous concept that can think of numerous points of view: for example, the community of friends of a client, time, mindset, environment, organization, type of day, classification of an item, description of the object, place, and language. The rating behavior of customers typically varies in different environments. We have proposed a new review-based contextual recommender (RBCR) system application from this line of analysis, in particular a novel recommender system, which is an adaptable, quick, and accurate piece planning framework that perceives the significance of setting and fuses the logical data using piece stunt while making expectations. We have contrasted our suggested calculation with pre- and post-sifting methods as they have been the most common methodologies in writing to illuminate the issue of setting conscious suggestion. Our studies show that considering the logical data, the display of a system will increase and provide better, appropriate and important results on various evaluation measurements.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89444717","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 : 2021-11-13DOI: 10.1142/s1793962322500209
K. Al-Utaibi, Alessandro Nutini, A. Sohail, Robia Arif, Sümeyye Tunç, S. M. Sait
Background: CAR-T cells are chimeric antigen receptor (CAR)-T cells; they are target-specific engineered cells on tumor cells and produce T cell-mediated antitumor responses. CAR-T cell therapy is the “first-line” therapy in immunotherapy for the treatment of highly clonal neoplasms such as lymphoma and leukemia. This adoptive therapy is currently being studied and tested even in the case of solid tumors such as osteosarcoma since, precisely for this type of tumor, the use of immune checkpoint inhibitors remained disappointing. Although CAR-T is a promising therapeutic technique, there are therapeutic limits linked to the persistence of these cells and to the tumor’s immune escape. CAR-T cell engineering techniques are allowed to express interleukin IL-36, and seem to be much more efficient in antitumoral action. IL-36 is involved in the long-term antitumor action, allowing CAR-T cells to be more efficient in their antitumor action due to a “cross-talk” action between the “IL-36/dendritic cells” axis and the adaptive immunity. Methods: This analysis makes the model useful for evaluating cell dynamics in the case of tumor relapses or specific understanding of the action of CAR-T cells in certain types of tumor. The model proposed here seeks to quantify the action and interaction between the three fundamental elements of this antitumor activity induced by this type of adoptive immunotherapy: IL-36, “armored” CAR-T cells (i.e., engineered to produce IL-36) and the tumor cell population, focusing exclusively on the action of this interleukin and on the antitumor consequences of the so modified CAR-T cells. Mathematical model was developed and numerical simulations were carried out during this research. The development of the model with stability analysis by conditions of Routh–Hurwitz shows how IL-36 makes CAR-T cells more efficient and persistent over time and more effective in the antitumoral treatment, making therapy more effective against the “solid tumor”. Findings: Primary malignant bone tumors are quite rare (about 3% of all tumors) and the vast majority consist of osteosarcomas and Ewing’s sarcoma and, approximately, the 20% of patients undergo metastasis situations that is the most likely cause of death. Interpretation: In bone tumor like osteosarcoma, there is a variation of the cellular mechanical characteristics that can influence the efficacy of chemotherapy and increase the metastatic capacity; an approach related to adoptive immunotherapy with CAR-T cells may be a possible solution because this type of therapy is not influenced by the biomechanics of cancer cells which show peculiar characteristics.
{"title":"Modeling and simulation of the \"IL-36 cytokine\" and CAR-T cells interplay in cancer onset","authors":"K. Al-Utaibi, Alessandro Nutini, A. Sohail, Robia Arif, Sümeyye Tunç, S. M. Sait","doi":"10.1142/s1793962322500209","DOIUrl":"https://doi.org/10.1142/s1793962322500209","url":null,"abstract":"Background: CAR-T cells are chimeric antigen receptor (CAR)-T cells; they are target-specific engineered cells on tumor cells and produce T cell-mediated antitumor responses. CAR-T cell therapy is the “first-line” therapy in immunotherapy for the treatment of highly clonal neoplasms such as lymphoma and leukemia. This adoptive therapy is currently being studied and tested even in the case of solid tumors such as osteosarcoma since, precisely for this type of tumor, the use of immune checkpoint inhibitors remained disappointing. Although CAR-T is a promising therapeutic technique, there are therapeutic limits linked to the persistence of these cells and to the tumor’s immune escape. CAR-T cell engineering techniques are allowed to express interleukin IL-36, and seem to be much more efficient in antitumoral action. IL-36 is involved in the long-term antitumor action, allowing CAR-T cells to be more efficient in their antitumor action due to a “cross-talk” action between the “IL-36/dendritic cells” axis and the adaptive immunity. Methods: This analysis makes the model useful for evaluating cell dynamics in the case of tumor relapses or specific understanding of the action of CAR-T cells in certain types of tumor. The model proposed here seeks to quantify the action and interaction between the three fundamental elements of this antitumor activity induced by this type of adoptive immunotherapy: IL-36, “armored” CAR-T cells (i.e., engineered to produce IL-36) and the tumor cell population, focusing exclusively on the action of this interleukin and on the antitumor consequences of the so modified CAR-T cells. Mathematical model was developed and numerical simulations were carried out during this research. The development of the model with stability analysis by conditions of Routh–Hurwitz shows how IL-36 makes CAR-T cells more efficient and persistent over time and more effective in the antitumoral treatment, making therapy more effective against the “solid tumor”. Findings: Primary malignant bone tumors are quite rare (about 3% of all tumors) and the vast majority consist of osteosarcomas and Ewing’s sarcoma and, approximately, the 20% of patients undergo metastasis situations that is the most likely cause of death. Interpretation: In bone tumor like osteosarcoma, there is a variation of the cellular mechanical characteristics that can influence the efficacy of chemotherapy and increase the metastatic capacity; an approach related to adoptive immunotherapy with CAR-T cells may be a possible solution because this type of therapy is not influenced by the biomechanics of cancer cells which show peculiar characteristics.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72640746","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 : 2021-11-01DOI: 10.1142/s1793962322500301
Maisnam Niranjan Singh, Samitha Khaiyum
{"title":"Reducing catastrophic forgetting problem in streaming data by Hybrid Shark Smell with Jaya Optimization-based Deep Neural Networks","authors":"Maisnam Niranjan Singh, Samitha Khaiyum","doi":"10.1142/s1793962322500301","DOIUrl":"https://doi.org/10.1142/s1793962322500301","url":null,"abstract":"","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73290791","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 : 2021-10-27DOI: 10.1142/s1793962322410021
Honglei Zhang, Zhenbo Zang, BalaAnand Muthu
Today, artificial intelligence (AI) can use the most powerful edge computing systems in the Internet of Things (IoT) for finding the information extracted from vast sensory data such as cyber effects or models in physical environments for classification, identification, and prediction. Heterogeneous IoT devices produce isolated and dispersed information parts, and knowledge sharing and exchange in IoT intelligent applications with several selfish nodes are necessary for complex tasks. In both academia and business, IoT is driving a digital revolution. However, protection and IoT privacy problems are challenged. It offers comfort for everyday lives. Blockchain, a shared cryptographic database, is a promising IoT encryption solution for several manufacturing, finance, and trade sectors. The IoT-based blockchain architecture is an interesting contrast to the conventional, centralized paradigm that struggles to fulfill specific IoT requirements. New concepts for applying data and resources management protection procedures in distributed networks and cloud computing are introduced. Cloud management services can be linked to the application through blockchain technology and distributed leader, a stable cognitive information system that facilitates management operations and securing data. This document provides many ideas for applying personal and behavioral characteristics to security and cryptography protocols, blockchain based on the cognitive cloud computing (BC-CCC) pattern. The simulation result shows that the proposed strategy can significantly enhance data transmission rate (96.2%), security ratio (94.5%), throughput ratio (92.4%), scalability ratio (91.5%), trust rate (93.8%), data trading ratio (96.2%), and reduce storage cost rate (25.1%) compared to other existing methods.
{"title":"Knowledge-based systems for blockchain-based cognitive cloud computing model for security purposes","authors":"Honglei Zhang, Zhenbo Zang, BalaAnand Muthu","doi":"10.1142/s1793962322410021","DOIUrl":"https://doi.org/10.1142/s1793962322410021","url":null,"abstract":"Today, artificial intelligence (AI) can use the most powerful edge computing systems in the Internet of Things (IoT) for finding the information extracted from vast sensory data such as cyber effects or models in physical environments for classification, identification, and prediction. Heterogeneous IoT devices produce isolated and dispersed information parts, and knowledge sharing and exchange in IoT intelligent applications with several selfish nodes are necessary for complex tasks. In both academia and business, IoT is driving a digital revolution. However, protection and IoT privacy problems are challenged. It offers comfort for everyday lives. Blockchain, a shared cryptographic database, is a promising IoT encryption solution for several manufacturing, finance, and trade sectors. The IoT-based blockchain architecture is an interesting contrast to the conventional, centralized paradigm that struggles to fulfill specific IoT requirements. New concepts for applying data and resources management protection procedures in distributed networks and cloud computing are introduced. Cloud management services can be linked to the application through blockchain technology and distributed leader, a stable cognitive information system that facilitates management operations and securing data. This document provides many ideas for applying personal and behavioral characteristics to security and cryptography protocols, blockchain based on the cognitive cloud computing (BC-CCC) pattern. The simulation result shows that the proposed strategy can significantly enhance data transmission rate (96.2%), security ratio (94.5%), throughput ratio (92.4%), scalability ratio (91.5%), trust rate (93.8%), data trading ratio (96.2%), and reduce storage cost rate (25.1%) compared to other existing methods.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87957009","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 : 2021-10-27DOI: 10.1142/s1793962322500192
K. Al-Utaibi, M. Idrees, A. Sohail, Fatima Arif, Alessandro Nutini, S. M. Sait
Our endocrine system is not only complex, but is also enormously sensitive to the imbalances caused by the environmental stressors, extreme weather situation, and other geographical factors. The endocrine disruptions are associated with the bone diseases. Osteoporosis is a bone disorder that occurs when bone mineral density and bone mass decrease. It affects women and men of all races and ethnic groups, causing bone weakness and the risk of fractures. Environmental stresses are referred to physical, chemical, and biological factors that can impact species productivity. This research aims to examine the impact of environmental stresses on bone diseases like osteoporosis and low bone mass (LBM) in the United States (US). For this purpose, we use an artificial neural network model to evaluate the correlation between the data. A multilayer neural network model is constructed using the Levenberg–Marquardt training algorithm, and its performance is evaluated by mean absolute error and coefficient of correlation. The data of osteoporosis and LBM cases in the US are divided into three groups, including gender group, age group, and race/ethnicity group. Each group shows a positive correlation with environmental stresses and thus the endocrinology.
{"title":"Artificial intelligence to link environmental endocrine disruptors (EEDs) with bone diseases","authors":"K. Al-Utaibi, M. Idrees, A. Sohail, Fatima Arif, Alessandro Nutini, S. M. Sait","doi":"10.1142/s1793962322500192","DOIUrl":"https://doi.org/10.1142/s1793962322500192","url":null,"abstract":"Our endocrine system is not only complex, but is also enormously sensitive to the imbalances caused by the environmental stressors, extreme weather situation, and other geographical factors. The endocrine disruptions are associated with the bone diseases. Osteoporosis is a bone disorder that occurs when bone mineral density and bone mass decrease. It affects women and men of all races and ethnic groups, causing bone weakness and the risk of fractures. Environmental stresses are referred to physical, chemical, and biological factors that can impact species productivity. This research aims to examine the impact of environmental stresses on bone diseases like osteoporosis and low bone mass (LBM) in the United States (US). For this purpose, we use an artificial neural network model to evaluate the correlation between the data. A multilayer neural network model is constructed using the Levenberg–Marquardt training algorithm, and its performance is evaluated by mean absolute error and coefficient of correlation. The data of osteoporosis and LBM cases in the US are divided into three groups, including gender group, age group, and race/ethnicity group. Each group shows a positive correlation with environmental stresses and thus the endocrinology.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75891422","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 : 2021-10-23DOI: 10.1142/s1793962322500210
Adhiyaman Manickam, Pushpendra Kumar, K. Dasunaidu, Govindaraj Venkatesan, D. Joshi
A stochastic SIR influenza vertical transmission model is examined in this paper where vaccination and an incidence rate that is not linear are considered. To determine whether testosterone regulates lower sintering HPA axis function in males, we used a stochastic SIR epidemic procedure with divergent influences on ACTH and cortisol. The suppressive effects on cortisol can be attributed to a peripheral (adrenal) locus. Following that, we came to the conclusion that experimental solutions have been discovered and the requisite statistical findings have been examined. Finally, we deduce that the given mathematical model and the results are relevant to medical research. In the future, this research can be further extended to simulate more results in the medical field.
{"title":"A stochastic SIR model for analysis of testosterone suppression of CRH-stimulated cortisol in men","authors":"Adhiyaman Manickam, Pushpendra Kumar, K. Dasunaidu, Govindaraj Venkatesan, D. Joshi","doi":"10.1142/s1793962322500210","DOIUrl":"https://doi.org/10.1142/s1793962322500210","url":null,"abstract":"A stochastic SIR influenza vertical transmission model is examined in this paper where vaccination and an incidence rate that is not linear are considered. To determine whether testosterone regulates lower sintering HPA axis function in males, we used a stochastic SIR epidemic procedure with divergent influences on ACTH and cortisol. The suppressive effects on cortisol can be attributed to a peripheral (adrenal) locus. Following that, we came to the conclusion that experimental solutions have been discovered and the requisite statistical findings have been examined. Finally, we deduce that the given mathematical model and the results are relevant to medical research. In the future, this research can be further extended to simulate more results in the medical field.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86080310","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 : 2021-10-20DOI: 10.1142/s1793962322500015
Mandar Kundan Keakde, A. Muddana
In large-scale social media, sentiment classification is a significant one for connecting gaps among social media contents as well as real-world actions, including public emotional status monitoring, political election prediction, and so on. On the other hand, textual sentiment classification is well studied by various platforms, like Instagram, Twitter, etc. Sentiment classification has many advantages in various fields, like opinion polls, education, and e-commerce. Sentiment classification is an interesting and progressing research area due to its applications in several areas. The information is collected from various people about social, products, and social events by web in sentiment analysis. This review provides a detailed survey of 50 research papers presenting sentiment classification schemes such as active learning-based approach, aspect learning-based method, and machine learning-based approach. The analysis is presented based on the categorization of sentiment classification schemes, the dataset used, software tools utilized, published year, and the performance metrics. Finally, the issues of existing methods considering conventional sentiment classification strategies are elaborated to obtain improved contribution in devising significant sentiment classification strategies. Moreover, the probable future research directions in attaining efficient sentiment classification are provided.
{"title":"Study and analysis of various sentiment classification strategies: A challenging overview","authors":"Mandar Kundan Keakde, A. Muddana","doi":"10.1142/s1793962322500015","DOIUrl":"https://doi.org/10.1142/s1793962322500015","url":null,"abstract":"In large-scale social media, sentiment classification is a significant one for connecting gaps among social media contents as well as real-world actions, including public emotional status monitoring, political election prediction, and so on. On the other hand, textual sentiment classification is well studied by various platforms, like Instagram, Twitter, etc. Sentiment classification has many advantages in various fields, like opinion polls, education, and e-commerce. Sentiment classification is an interesting and progressing research area due to its applications in several areas. The information is collected from various people about social, products, and social events by web in sentiment analysis. This review provides a detailed survey of 50 research papers presenting sentiment classification schemes such as active learning-based approach, aspect learning-based method, and machine learning-based approach. The analysis is presented based on the categorization of sentiment classification schemes, the dataset used, software tools utilized, published year, and the performance metrics. Finally, the issues of existing methods considering conventional sentiment classification strategies are elaborated to obtain improved contribution in devising significant sentiment classification strategies. Moreover, the probable future research directions in attaining efficient sentiment classification are provided.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81351506","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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