Pub Date : 2021-12-18DOI: 10.31181/jdaic1001202222b
I. Badi, Ali M. Abdulshahed
The iron and steel industry plays a major role in Libyan urbanization. Iron and steel products are the main driving forces in the construction manufacturing sector in Libya. This research suggested a set of indicators to evaluate the sustainability of the iron and steel industry in Libya using a rough AHP model. Rough AHP analyses the relative importance of the criteria based on their preferences given by experts. The research results show that the most important criterion is costs followed by emission and waste. We have found that the rough AHP model can play an important role in improving indicators that quantify the advance towards sustainable development, especially when it is in a situation where complex environments (i.e., Libya) exist.
{"title":"Sustainability performance measurement for Libyan Iron and Steel Company using Rough AHP","authors":"I. Badi, Ali M. Abdulshahed","doi":"10.31181/jdaic1001202222b","DOIUrl":"https://doi.org/10.31181/jdaic1001202222b","url":null,"abstract":"The iron and steel industry plays a major role in Libyan urbanization. Iron and steel products are the main driving forces in the construction manufacturing sector in Libya. This research suggested a set of indicators to evaluate the sustainability of the iron and steel industry in Libya using a rough AHP model. Rough AHP analyses the relative importance of the criteria based on their preferences given by experts. The research results show that the most important criterion is costs followed by emission and waste. We have found that the rough AHP model can play an important role in improving indicators that quantify the advance towards sustainable development, especially when it is in a situation where complex environments (i.e., Libya) exist.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128705918","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 : 2021-05-18DOI: 10.1101/2021.05.14.21257209
Arvanitis Athanasios, Furxhi Irini, Thomas Tasioulis, Karatzas Konstantinos
This paper demonstrates how a short-term prediction of the effective reproduction number (Rt) of COVID-19 in regions of Greece is achieved based on online mobility data. Various machine learning methods are applied to predict Rt and attribute importance analysis is performed to reveal the most important variables that affect the accurate prediction of Rt. Our results are based on an ensemble of diverse Rt methodologies to provide non-precautious and non-indulgent predictions. The model demonstrates robust results and the methodology overall represents a promising approach towards COVID-19 outbreak prediction. This paper can help health related authorities when deciding non-nosocomial interventions to prevent the spread of COVID-19.
{"title":"Prediction of the effective reproduction number of COVID-19 in Greece. A machine learning approach using Google mobility data.","authors":"Arvanitis Athanasios, Furxhi Irini, Thomas Tasioulis, Karatzas Konstantinos","doi":"10.1101/2021.05.14.21257209","DOIUrl":"https://doi.org/10.1101/2021.05.14.21257209","url":null,"abstract":"This paper demonstrates how a short-term prediction of the effective reproduction number (Rt) of COVID-19 in regions of Greece is achieved based on online mobility data. Various machine learning methods are applied to predict Rt and attribute importance analysis is performed to reveal the most important variables that affect the accurate prediction of Rt. Our results are based on an ensemble of diverse Rt methodologies to provide non-precautious and non-indulgent predictions. The model demonstrates robust results and the methodology overall represents a promising approach towards COVID-19 outbreak prediction. This paper can help health related authorities when deciding non-nosocomial interventions to prevent the spread of COVID-19.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128955493","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 : 1900-01-01DOI: 10.31181/jdaic10017022023p
A. Puška, Anđelka Štilić, Ilija Stojanović
Understanding the level of economic freedom is an important indicator for investors and policymakers. The index of economic freedom, which the Heritage Foundation releases annually, is the most significant of the methods used to measure this indicator in practice, as this index evaluates the degree of market openness over the degree of fiscal and regulatory restraint. The research presented in this paper was conducted in order to establish the level of economic freedom in the Balkan countries. For this purpose, a multi-criteria ranking of Balkan countries based on economic freedom criteria was used. The weight of the criteria was determined using the Entropy method, and the countries were ranked using the CRADIS (Compromise Ranking of Alternatives from Distance to ideal Solution) method. These methods employed a double normalisation approach, and according to the results of this application, Bulgaria has the best indicators of economic freedom, while Montenegro has the worst, with sensitivity analysis and validation of the results confirming these findings. The approach of using double normalisation contributes to decision-making stability since the results of different methods are uniform when compared to the use of the classical approach in the case of multi-criteria analysis methods.
{"title":"Approach for multi-criteria ranking of Balkan countries based on the index of economic freedom","authors":"A. Puška, Anđelka Štilić, Ilija Stojanović","doi":"10.31181/jdaic10017022023p","DOIUrl":"https://doi.org/10.31181/jdaic10017022023p","url":null,"abstract":"Understanding the level of economic freedom is an important indicator for investors and policymakers. The index of economic freedom, which the Heritage Foundation releases annually, is the most significant of the methods used to measure this indicator in practice, as this index evaluates the degree of market openness over the degree of fiscal and regulatory restraint. The research presented in this paper was conducted in order to establish the level of economic freedom in the Balkan countries. For this purpose, a multi-criteria ranking of Balkan countries based on economic freedom criteria was used. The weight of the criteria was determined using the Entropy method, and the countries were ranked using the CRADIS (Compromise Ranking of Alternatives from Distance to ideal Solution) method. These methods employed a double normalisation approach, and according to the results of this application, Bulgaria has the best indicators of economic freedom, while Montenegro has the worst, with sensitivity analysis and validation of the results confirming these findings. The approach of using double normalisation contributes to decision-making stability since the results of different methods are uniform when compared to the use of the classical approach in the case of multi-criteria analysis methods.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123504920","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 : 1900-01-01DOI: 10.31181/jdaic10006062023a
Amir Ali, K. Ullah, Amir Hussain
The intuitionistic fuzzy soft set (IFSS) is a vital technique for tackling uncertainty while the collection of information with the help of the membership function having values from unit interval. Moreover, the Aczel-Alsina t-norm (AATNRM) and Aczel-Alsina t-conorm (AATCRM) are the most generalized and flexible operational laws to operate the information which is the part of the unit intervals. The purpose of this article is to provide a number of aggregation operations (AOs) for information represented by intuitionistic fuzzy soft values (IFSVs) based on AATRM and AATCRM. Therefore, some new operational laws are developed by using on the AATRM and AATCRM for the development of the sum and product laws for IFSVs. Then, intuitionistic fuzzy soft Aczel-Alsina weighted averaging (IFSAAWA) and geometric (IFSAAWG) operators are purposed based on these operational laws. Additionally, some of their characteristics are examined, and the difference of the proposed and existing operators is investigated. Moreover, the proposed approach is applied to the problem of multi-attribute decision-making (MADM) for significance.
{"title":"An approach to multi-attribute decision-making based on intuitionistic fuzzy soft information and Aczel-Alsina operational laws","authors":"Amir Ali, K. Ullah, Amir Hussain","doi":"10.31181/jdaic10006062023a","DOIUrl":"https://doi.org/10.31181/jdaic10006062023a","url":null,"abstract":"The intuitionistic fuzzy soft set (IFSS) is a vital technique for tackling uncertainty while the collection of information with the help of the membership function having values from unit interval. Moreover, the Aczel-Alsina t-norm (AATNRM) and Aczel-Alsina t-conorm (AATCRM) are the most generalized and flexible operational laws to operate the information which is the part of the unit intervals. The purpose of this article is to provide a number of aggregation operations (AOs) for information represented by intuitionistic fuzzy soft values (IFSVs) based on AATRM and AATCRM. Therefore, some new operational laws are developed by using on the AATRM and AATCRM for the development of the sum and product laws for IFSVs. Then, intuitionistic fuzzy soft Aczel-Alsina weighted averaging (IFSAAWA) and geometric (IFSAAWG) operators are purposed based on these operational laws. Additionally, some of their characteristics are examined, and the difference of the proposed and existing operators is investigated. Moreover, the proposed approach is applied to the problem of multi-attribute decision-making (MADM) for significance.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115305895","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 : 1900-01-01DOI: 10.31181/jdaic10010052023a
K. Adegbola
This paper addresses the long-standing stochastic single-vendor, multi-manufacturer inventory control problem, using simulation optimization. It is assumed that Manufacturers producing similar goods experience very high random demand; hence, safety stock of raw materials is held in reserve in their warehouses. The vendor supplying this raw material (principal ingredients) as a policy restricts shipments to multiples of full truck load. Thus, it is necessary to take replenishment decision and coordinate delivery among these manufacturers. To solve this problem, we modeled the single vendor, single manufacturer version of the problem (AlDurgam et al., 2017) using simulation optimization techniques, which was validated numerically using parameters and results from AlDurgam et al. (2017). The simulation model was modified systematically to relax the single manufacturer assumption under two distribution policies namely, joint reorder point and vendor managed inventory. These policies were evidently modeled with stringent conditions in literature. A numerical example was provided to compare the performances of the two proposed policies, and the VMI policy was found to performed better in terms of financial savings. Lastly, we investigate the robustness of the famous continuous review (Q, R) inventory policy which is widely used in the mathematical modeling of this problem, against the common cycle assumption. The coefficient of variation is thus suggested as a judgment criterion of when to embrace simulation modeling ahead of other modeling techniques.
本文采用仿真优化方法解决了长期存在的单厂商多厂商随机库存控制问题。假设生产类似商品的制造商经历非常高的随机需求;因此，原材料的安全库存是在仓库中储备的。作为一项政策，供应这种原材料(主要成分)的供应商限制装运数量为满载卡车的数倍。因此，有必要在这些制造商之间做出补充决策并协调交付。为了解决这个问题，我们使用仿真优化技术对单一供应商、单一制造商版本的问题(AlDurgam et al.， 2017)进行了建模，并使用AlDurgam et al.(2017)的参数和结果进行了数值验证。在联合再订货点和供应商管理库存两种分销策略下，对仿真模型进行了系统修正，放宽了单一制造商的假设。这些政策在文献中显然是用严格的条件来模拟的。提供了一个数值示例来比较两种建议策略的性能，并发现VMI策略在财务节省方面表现更好。最后，我们研究了在此问题的数学模型中广泛使用的著名的连续回顾(Q, R)库存策略在共同周期假设下的鲁棒性。因此，变异系数被认为是在其他建模技术之前何时采用仿真建模的判断标准。
{"title":"A simulation study of single-vendor, single and multiple-manufacturers supply chain system, with stochastic demand and two distribution policies","authors":"K. Adegbola","doi":"10.31181/jdaic10010052023a","DOIUrl":"https://doi.org/10.31181/jdaic10010052023a","url":null,"abstract":"This paper addresses the long-standing stochastic single-vendor, multi-manufacturer inventory control problem, using simulation optimization. It is assumed that Manufacturers producing similar goods experience very high random demand; hence, safety stock of raw materials is held in reserve in their warehouses. The vendor supplying this raw material (principal ingredients) as a policy restricts shipments to multiples of full truck load. Thus, it is necessary to take replenishment decision and coordinate delivery among these manufacturers. To solve this problem, we modeled the single vendor, single manufacturer version of the problem (AlDurgam et al., 2017) using simulation optimization techniques, which was validated numerically using parameters and results from AlDurgam et al. (2017). The simulation model was modified systematically to relax the single manufacturer assumption under two distribution policies namely, joint reorder point and vendor managed inventory. These policies were evidently modeled with stringent conditions in literature. A numerical example was provided to compare the performances of the two proposed policies, and the VMI policy was found to performed better in terms of financial savings. Lastly, we investigate the robustness of the famous continuous review (Q, R) inventory policy which is widely used in the mathematical modeling of this problem, against the common cycle assumption. The coefficient of variation is thus suggested as a judgment criterion of when to embrace simulation modeling ahead of other modeling techniques.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122428194","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}
In recent research, it has been found that an enormous amount of the population is involved in agriculture. The farmers are increasingly exposed to income risks from the effects of volatility in many factors directly or indirectly related to farming. The prediction of the farmer’s income can be used to manage the income risks by assisting the farmer. This paper proposes an ARIMA-based framework to forecast the income from a crop for the next consecutive years. A detailed analysis of the proposed work on best suitable ARIMA framework is discussed. It is shown that the proposed work obtains a higher accuracy in predicting the income in future over other alternative methods
{"title":"Automated prediction of income from farming of a commodity: An ARIMA based framework","authors":"Soumyadipta Kar, Manas Kumar Mohanty, Parag Kumar Guha Thakurta","doi":"10.31181/jdaic10021072023k","DOIUrl":"https://doi.org/10.31181/jdaic10021072023k","url":null,"abstract":"In recent research, it has been found that an enormous amount of the population is involved in agriculture. The farmers are increasingly exposed to income risks from the effects of volatility in many factors directly or indirectly related to farming. The prediction of the farmer’s income can be used to manage the income risks by assisting the farmer. This paper proposes an ARIMA-based framework to forecast the income from a crop for the next consecutive years. A detailed analysis of the proposed work on best suitable ARIMA framework is discussed. It is shown that the proposed work obtains a higher accuracy in predicting the income in future over other alternative methods","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129268163","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 : 1900-01-01DOI: 10.31181/jdaic10029042022k
R. Divakar, Bijendra K. Singh, A. Bajpai, Anil Kumar
Edge is the high-frequency part of an image and represents location where abrupt change takes place in the intensity of luminescence. Edge detection is the basic step of the feature extraction and pattern recognition of any image. Wavelet transforms extract low and high-frequency information of any signal separately. In two-dimensional wavelet transforms, an image is decomposed into four sub-images the one approximation image and three different images (horizontal, vertical, and diagonal images) in each decomposition level. The differences’ images show how the neighboring pixels differ in the horizontal, vertical and diagonal directions. The approximation coefficients are forced to zero and differences’ coefficients are inverse wavelet transformed. As the reconstructed image shows the edges of the image and describes its pattern. Using Haar wavelet at decomposition level 1, 2 and 3, the image pattern recognition by edge detection is performed and discussed.
{"title":"Image pattern recognition by edge detection using discrete wavelet transforms","authors":"R. Divakar, Bijendra K. Singh, A. Bajpai, Anil Kumar","doi":"10.31181/jdaic10029042022k","DOIUrl":"https://doi.org/10.31181/jdaic10029042022k","url":null,"abstract":"Edge is the high-frequency part of an image and represents location where abrupt change takes place in the intensity of luminescence. Edge detection is the basic step of the feature extraction and pattern recognition of any image. Wavelet transforms extract low and high-frequency information of any signal separately. In two-dimensional wavelet transforms, an image is decomposed into four sub-images the one approximation image and three different images (horizontal, vertical, and diagonal images) in each decomposition level. The differences’ images show how the neighboring pixels differ in the horizontal, vertical and diagonal directions. The approximation coefficients are forced to zero and differences’ coefficients are inverse wavelet transformed. As the reconstructed image shows the edges of the image and describes its pattern. Using Haar wavelet at decomposition level 1, 2 and 3, the image pattern recognition by edge detection is performed and discussed.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133909000","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 : 1900-01-01DOI: 10.31181/jdaic10028042022c
S. Chakraborty, B. Mallick, Santonab Chakraborty
A prior knowledge regarding the effectiveness of each of the medicines prescribed by a physician would be quite helpful to a patient for rapid recovery from a particular disease. In this paper, an attempt is put forward to develop the related association rules for understanding the roles of different types of medicines prescribed for treatment of dental diseases, especially tooth pain (odontalgia/dentalgia) and swelling of tooth (pericoronitis). 75 patient cases from a dentist are analyzed to determine the average number of different types of medicines prescribed, average number of medicines and average cost of treatment, and to mine the corresponding association rules. It is observed from 1-item dataset that antibiotic#1 is the most preferred medicine, followed by antiseptic. Similarly, the 2-item dataset shows that the most preferred combination on medicines is {antibiotic#1, antiseptic}, followed by {antibiotic#1, anti-reflux}. Among all the association rules developed, the rule (If antibiotic#1 and antibiotic#2 and antiseptic, then anti-reflux) appears with the maximum strength.
{"title":"Mining of association rules for treatment of dental diseases","authors":"S. Chakraborty, B. Mallick, Santonab Chakraborty","doi":"10.31181/jdaic10028042022c","DOIUrl":"https://doi.org/10.31181/jdaic10028042022c","url":null,"abstract":"A prior knowledge regarding the effectiveness of each of the medicines prescribed by a physician would be quite helpful to a patient for rapid recovery from a particular disease. In this paper, an attempt is put forward to develop the related association rules for understanding the roles of different types of medicines prescribed for treatment of dental diseases, especially tooth pain (odontalgia/dentalgia) and swelling of tooth (pericoronitis). 75 patient cases from a dentist are analyzed to determine the average number of different types of medicines prescribed, average number of medicines and average cost of treatment, and to mine the corresponding association rules. It is observed from 1-item dataset that antibiotic#1 is the most preferred medicine, followed by antiseptic. Similarly, the 2-item dataset shows that the most preferred combination on medicines is {antibiotic#1, antiseptic}, followed by {antibiotic#1, anti-reflux}. Among all the association rules developed, the rule (If antibiotic#1 and antibiotic#2 and antiseptic, then anti-reflux) appears with the maximum strength.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127052493","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 : 1900-01-01DOI: 10.31181/jdaic10015072023s
Deepanjali Sahoo, A. Tripathy, J. K. Pati, P. K. Parida
In this work, authors discuss the way of selecting level of supplier by using the concept of binary coded genetic algorithm. For the best solution due to involvement of multi objective functions, the process of Tournament selection is widely discussed. In addition to this, authors involve fuzzy parameters due to the aspiration levels of Decision maker in analysis part for more clarity towards optimality. As a case study towards pareto optimality, the theory of non-dominance of solutions is properly discussed with the help of Pareto frontier. At last the values of objective functions based on quality, cost and service levels following an example are being analyzed with a significant view towards optimality. Based on the optimal solutions, the level of supplier selection is properly discussed.
{"title":"A selection of level of supplier in supply chain management using binary coded genetic algorithm with a case study towards Pareto optimality","authors":"Deepanjali Sahoo, A. Tripathy, J. K. Pati, P. K. Parida","doi":"10.31181/jdaic10015072023s","DOIUrl":"https://doi.org/10.31181/jdaic10015072023s","url":null,"abstract":"In this work, authors discuss the way of selecting level of supplier by using the concept of binary coded genetic algorithm. For the best solution due to involvement of multi objective functions, the process of Tournament selection is widely discussed. In addition to this, authors involve fuzzy parameters due to the aspiration levels of Decision maker in analysis part for more clarity towards optimality. As a case study towards pareto optimality, the theory of non-dominance of solutions is properly discussed with the help of Pareto frontier. At last the values of objective functions based on quality, cost and service levels following an example are being analyzed with a significant view towards optimality. Based on the optimal solutions, the level of supplier selection is properly discussed.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122264995","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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