Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677647
Marwan B. Mohammed, W. Al-Hameed
Increasing growth in the volume of digital data from documents performed the difficulty of accessing important information. The solution is using automatic summarization systems that aim to extract important information in a short time. Usually, these systems work to extract a single summary from a single document or multi-documents. However, extracting a summary from a multi-document may encounter some obstacles. This work focuses on how to overcome these obstacles and extract an appropriate and cohesion summary by presenting and suggesting four important contributions with a qualitative leap in the process of extracting the important information that seeks to extract a candidate summary that matches the sentences of the golden summary. The first suggestion is a set of features to extract important sentences and easy to understand, the second, build a Backpropagation Multi-layer Perceptron Neural Network (BMPNN) based on these features input to extract the score for each sentence, the third, using the Random oversampling method and its effective role in rebalancing the data during the training process in BMPNN, and finally, solving the problem of reordering sentences in the candidate summary according to the importance of the sentence depending on one of the features. The results of the evaluation Rouge-1, Rouge-2, and Rouge-L measures showed that the candidate's summary is very close to the golden summary in terms of matching sentences, and it achieved very good results.
{"title":"Cohesive Summary Extraction From Multi-Document Based On Artificial Neural Network","authors":"Marwan B. Mohammed, W. Al-Hameed","doi":"10.1109/ICCITM53167.2021.9677647","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677647","url":null,"abstract":"Increasing growth in the volume of digital data from documents performed the difficulty of accessing important information. The solution is using automatic summarization systems that aim to extract important information in a short time. Usually, these systems work to extract a single summary from a single document or multi-documents. However, extracting a summary from a multi-document may encounter some obstacles. This work focuses on how to overcome these obstacles and extract an appropriate and cohesion summary by presenting and suggesting four important contributions with a qualitative leap in the process of extracting the important information that seeks to extract a candidate summary that matches the sentences of the golden summary. The first suggestion is a set of features to extract important sentences and easy to understand, the second, build a Backpropagation Multi-layer Perceptron Neural Network (BMPNN) based on these features input to extract the score for each sentence, the third, using the Random oversampling method and its effective role in rebalancing the data during the training process in BMPNN, and finally, solving the problem of reordering sentences in the candidate summary according to the importance of the sentence depending on one of the features. The results of the evaluation Rouge-1, Rouge-2, and Rouge-L measures showed that the candidate's summary is very close to the golden summary in terms of matching sentences, and it achieved very good results.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124808415","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 : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677682
Zeena Abdul Aziz Khudhair, Muhammad Taha Ahmed
The Box Cox Rlstić-Balakrishnan Odd Burr III-G Family is a new family of distributions introduced in this paper. It can be conceived of as a natural extension of the useful RB-G family of distributions. The key tool for this generalization is the use of Box-Cox transformation. The exponential distribution was used as a sub-distribution. Some mathematical properties of the new sub-family were derived. Then, a specific member with four parameters was studied with various statistical features and viewed as a statistical model. Finally, the novel model's power of adjustment was compared to six current competitive models using real data.
{"title":"Box-Cox Ristić—Balakrishnan Odd Burr III-G Family of distribution: Properties and applications","authors":"Zeena Abdul Aziz Khudhair, Muhammad Taha Ahmed","doi":"10.1109/ICCITM53167.2021.9677682","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677682","url":null,"abstract":"The Box Cox Rlstić-Balakrishnan Odd Burr III-G Family is a new family of distributions introduced in this paper. It can be conceived of as a natural extension of the useful RB-G family of distributions. The key tool for this generalization is the use of Box-Cox transformation. The exponential distribution was used as a sub-distribution. Some mathematical properties of the new sub-family were derived. Then, a specific member with four parameters was studied with various statistical features and viewed as a statistical model. Finally, the novel model's power of adjustment was compared to six current competitive models using real data.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125264134","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 : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677705
Noor Al-Huda Hamed Olewy, A. K. Hadi
Many web services on the internet have sprung up as a result of the rapid advancement of technology and the deployment of computing. Since users need many web services to achieve their requests, there are many web services that share the same functionality at different qualities. This requires the identification of the quality of web services. Using cloud computing, this paper proposes a model of multi-classification to predict the quality of web services by using machine learning techniques. There are four algorithms of machine learning applied in this work: Multiclass Logistic Regression, Multiclass Decision Forest (DF), Multiclass Decision Jungle (DJ), and Multiclass Neural Network (NN), After comparing the results, it has been found that the Multiclass Neural Network obtained the highest overall accuracy and average accuracy. By using features selection and normalization in this work and compare the algorithms. The selection of the best model is followed by the creation of a web service for the prediction of quality using Azure ML studio.
{"title":"Multiclass Model for Quality of Service Using Machine Learning and Cloud Computing","authors":"Noor Al-Huda Hamed Olewy, A. K. Hadi","doi":"10.1109/ICCITM53167.2021.9677705","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677705","url":null,"abstract":"Many web services on the internet have sprung up as a result of the rapid advancement of technology and the deployment of computing. Since users need many web services to achieve their requests, there are many web services that share the same functionality at different qualities. This requires the identification of the quality of web services. Using cloud computing, this paper proposes a model of multi-classification to predict the quality of web services by using machine learning techniques. There are four algorithms of machine learning applied in this work: Multiclass Logistic Regression, Multiclass Decision Forest (DF), Multiclass Decision Jungle (DJ), and Multiclass Neural Network (NN), After comparing the results, it has been found that the Multiclass Neural Network obtained the highest overall accuracy and average accuracy. By using features selection and normalization in this work and compare the algorithms. The selection of the best model is followed by the creation of a web service for the prediction of quality using Azure ML studio.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114588393","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 : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677874
E. H. Salman, I. Zayer, Shayma Naif Hassan
The engineering systems of robotics, communication networks, and electronics status, require a software effort estimation to decrease the error of effort and cost estimation since huge sizes of datasets are used in these systems. It supports the different tasks in scheduling, planning, and so on yet it is difficult to estimate the necessary duration to fix a required task. However, the computational complexity level is increased with improving of abovementioned systems. In this paper, several software effort estimation techniques are considered for mechatronics and communications systems. These techniques are artificial neural networks, Fuzzy logic rule, genetic algorithm, and others. The analyses and investigations revealed that the hybrid technique is the best one, which is described as the statistical representations cascaded to artificial neural networks. the hybrid technique has a higher accuracy with desirable complexity.
{"title":"A Comparative Study of Algorithms of Software Effort Estimation for the Robotic and Communication Systems Based on Improved Accuracy","authors":"E. H. Salman, I. Zayer, Shayma Naif Hassan","doi":"10.1109/ICCITM53167.2021.9677874","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677874","url":null,"abstract":"The engineering systems of robotics, communication networks, and electronics status, require a software effort estimation to decrease the error of effort and cost estimation since huge sizes of datasets are used in these systems. It supports the different tasks in scheduling, planning, and so on yet it is difficult to estimate the necessary duration to fix a required task. However, the computational complexity level is increased with improving of abovementioned systems. In this paper, several software effort estimation techniques are considered for mechatronics and communications systems. These techniques are artificial neural networks, Fuzzy logic rule, genetic algorithm, and others. The analyses and investigations revealed that the hybrid technique is the best one, which is described as the statistical representations cascaded to artificial neural networks. the hybrid technique has a higher accuracy with desirable complexity.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129611048","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 : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677716
N. Al-Thanoon, O. Qasim, Z. Algamal
The Multidimensional Knapsack Problem (MKP) is an important issue in the class of knapsack problem with a wide range of applications in management and engineering. It is a combinatory optimization problem and it is also an NP-hard problem. To solve MKP, several traditional and nature-inspired search algorithms are available in the literature. In this study, a new hybrid pigeon-inspired optimization algorithm is proposed. The proposed hybridization can, efficiently, exploit the strong points of pigeon optimization algorithm in terms of solving MKP. Extensive experiments are conducted based on benchmark datasets for evaluating the performance of the proposed hybridization. The results verify that the proposed hybridization is significantly superior over the other nature-inspired algorithms used for solving MKP.
{"title":"A New Hybrid Pigeon-Inspired Optimization Algorithm for Solving Multidimensional Knapsack Problems","authors":"N. Al-Thanoon, O. Qasim, Z. Algamal","doi":"10.1109/ICCITM53167.2021.9677716","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677716","url":null,"abstract":"The Multidimensional Knapsack Problem (MKP) is an important issue in the class of knapsack problem with a wide range of applications in management and engineering. It is a combinatory optimization problem and it is also an NP-hard problem. To solve MKP, several traditional and nature-inspired search algorithms are available in the literature. In this study, a new hybrid pigeon-inspired optimization algorithm is proposed. The proposed hybridization can, efficiently, exploit the strong points of pigeon optimization algorithm in terms of solving MKP. Extensive experiments are conducted based on benchmark datasets for evaluating the performance of the proposed hybridization. The results verify that the proposed hybridization is significantly superior over the other nature-inspired algorithms used for solving MKP.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128508963","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 : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677651
Hamsa Th. Seaad, Elaf Suliman Khaleel, Huda I. Ahmed, Eman T. Hamed
We developed a new three-term conjugate gradient method (C.G.M)in this study. Under certain conditions, this approach achieves the desired descent direction while also being globally convergent. On the basis of the Dolan-More performance profile, these results show that this method outperforms the alternative standard method
{"title":"A Modified Sufficient Descent Spectral Conjugate Gradient Method for Minimization","authors":"Hamsa Th. Seaad, Elaf Suliman Khaleel, Huda I. Ahmed, Eman T. Hamed","doi":"10.1109/ICCITM53167.2021.9677651","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677651","url":null,"abstract":"We developed a new three-term conjugate gradient method (C.G.M)in this study. Under certain conditions, this approach achieves the desired descent direction while also being globally convergent. On the basis of the Dolan-More performance profile, these results show that this method outperforms the alternative standard method","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130565746","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 : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677853
Husam Yaseen, Raya Salim Al Rassam
The Weibull regression model is one of the most important parametric regression models. Because of the knowledge of the probability distribution of the response variable following the Weibull distribution, which facilities the possibility of estimating the regression parameters based on the baseline hazard function. It is estimated by estimating the parameters of the Weibull distribution using the maximum likelihood estimation method. The R software was used for the purpose of estimating the regression coefficients and identifying the most significant features that model the outcome. In this paper, we investigate the factors affecting the progression of Corona virus patients from Al-Shiffa Hospital in the city of Mosul. In addition, this study focused on patients who were in a critical condition, and whose cases necessitated their monitoring during their stay under the artificial respiration machine Continues Positive Airway Pressure (CPAP). The six variables were taken as the most influential on the injury case and it was found that the most influential variables were Remdesivir and O2 using some statistical criteria.
{"title":"Study of the Factors Affecting the Incidence of COVID-19 Infection Using an Accelerrated Weibull Regression Model","authors":"Husam Yaseen, Raya Salim Al Rassam","doi":"10.1109/ICCITM53167.2021.9677853","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677853","url":null,"abstract":"The Weibull regression model is one of the most important parametric regression models. Because of the knowledge of the probability distribution of the response variable following the Weibull distribution, which facilities the possibility of estimating the regression parameters based on the baseline hazard function. It is estimated by estimating the parameters of the Weibull distribution using the maximum likelihood estimation method. The R software was used for the purpose of estimating the regression coefficients and identifying the most significant features that model the outcome. In this paper, we investigate the factors affecting the progression of Corona virus patients from Al-Shiffa Hospital in the city of Mosul. In addition, this study focused on patients who were in a critical condition, and whose cases necessitated their monitoring during their stay under the artificial respiration machine Continues Positive Airway Pressure (CPAP). The six variables were taken as the most influential on the injury case and it was found that the most influential variables were Remdesivir and O2 using some statistical criteria.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"27 23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114806068","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 : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677653
S. T. Hasson, Salar Essa Hasan
This paper clarifies the implementation of the leach protocol in wireless sensor networks (WSN) and developing an enhanced approach to select the cluster head. The performance of the suggested wireless sensor network is evaluated by implementing and running a leach protocol. NS 2.35 as a simulator is used in this evaluation to evaluate 100 deployed sensors on a certain area of 100 m∧ 2. The evaluation is based on the packet sent, packet receives, start time, stop time, throughput, Packet Delivery Ratio, delay, and jitter as performance metrics. The network performance is improved with less energy consumed in transmission and processing of data with leach protocol
{"title":"An Improvement on Leach Protocol for Wireless Sensor Network","authors":"S. T. Hasson, Salar Essa Hasan","doi":"10.1109/ICCITM53167.2021.9677653","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677653","url":null,"abstract":"This paper clarifies the implementation of the leach protocol in wireless sensor networks (WSN) and developing an enhanced approach to select the cluster head. The performance of the suggested wireless sensor network is evaluated by implementing and running a leach protocol. NS 2.35 as a simulator is used in this evaluation to evaluate 100 deployed sensors on a certain area of 100 m∧ 2. The evaluation is based on the packet sent, packet receives, start time, stop time, throughput, Packet Delivery Ratio, delay, and jitter as performance metrics. The network performance is improved with less energy consumed in transmission and processing of data with leach protocol","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129394762","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 : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677681
A. Fares, M. Alanezi
As the Covid-19 outbreak spreads across the globe and has killed many lives, many applications have been created to track patients and fight this pandemic. However, several applications lack safety and privacy. This paper designs and develops a mobile app to track patients with the Covid-19 or any other pandemic disease through using GPS in Iraq. Moreover, the app maintains a privacy for users by encrypting their personal data before sending them to the cloud using a MODE CBC AES block encryption algorithm. The app keeps the identity and location of the users, supports two language interfaces English and Arabic, and works in Android and iOS environments. Only the health care providers can decrypt these data and know about the patient's location. Also, to make the patient trusts the application, his/her information will be deleted after sending his/her negative test after 21 days. In addition, the app provides users with information regarding healthcare places in the case of emergency. For the evaluation of this app, a data was collected from 20 users, including males and females and their ages were between (20–50) in Mosul city. The results showed that the app works properly and the users are notified when they are in close with other registered infected people. In addition, the users found that the app was simple, easy to use, and useful to do contact safely. To convince the users to utilize this app, the app is provided with button trial option to try it.
{"title":"Contagious Patient Tracking Application Spotlight: Privacy and Security Rights","authors":"A. Fares, M. Alanezi","doi":"10.1109/ICCITM53167.2021.9677681","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677681","url":null,"abstract":"As the Covid-19 outbreak spreads across the globe and has killed many lives, many applications have been created to track patients and fight this pandemic. However, several applications lack safety and privacy. This paper designs and develops a mobile app to track patients with the Covid-19 or any other pandemic disease through using GPS in Iraq. Moreover, the app maintains a privacy for users by encrypting their personal data before sending them to the cloud using a MODE CBC AES block encryption algorithm. The app keeps the identity and location of the users, supports two language interfaces English and Arabic, and works in Android and iOS environments. Only the health care providers can decrypt these data and know about the patient's location. Also, to make the patient trusts the application, his/her information will be deleted after sending his/her negative test after 21 days. In addition, the app provides users with information regarding healthcare places in the case of emergency. For the evaluation of this app, a data was collected from 20 users, including males and females and their ages were between (20–50) in Mosul city. The results showed that the app works properly and the users are notified when they are in close with other registered infected people. In addition, the users found that the app was simple, easy to use, and useful to do contact safely. To convince the users to utilize this app, the app is provided with button trial option to try it.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114857225","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 : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677635
Eman A. Mansour, Emad A. Kuffi, Sadiq A. Mehdi
In this paper, complex SEE (Sadiq-Emad-Eman) integral transform is going to be used to find the exact solution for the first order ordinary differential equations of population growth and decay problems, some growth and decay problems are going to be solved using complex SEE transform to prove the transform capability and efficiency in finding the exact solution for these problems, using the simplest and smallest number of possible calculations.
{"title":"Solving Population Growth and Decay Problems Using Complex SEE Transform","authors":"Eman A. Mansour, Emad A. Kuffi, Sadiq A. Mehdi","doi":"10.1109/ICCITM53167.2021.9677635","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677635","url":null,"abstract":"In this paper, complex SEE (Sadiq-Emad-Eman) integral transform is going to be used to find the exact solution for the first order ordinary differential equations of population growth and decay problems, some growth and decay problems are going to be solved using complex SEE transform to prove the transform capability and efficiency in finding the exact solution for these problems, using the simplest and smallest number of possible calculations.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115022402","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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