We use optimal control theory to determine the optimal rate of change in the subscription fee and the optimal ratio of ad space to the total web page space for a web content provider. An optimal solution is obtained using the maximum principle approach and the model predictive control approach. Numerical experiments show that it is preferable to use the first approach when the planning horizon is short and the second approach when the planning horizon is long
{"title":"Internet digital content pricing and subscribers control","authors":"Sobhi Mejjouali, Lotfi Tadj","doi":"10.37190/ord230304","DOIUrl":"https://doi.org/10.37190/ord230304","url":null,"abstract":"We use optimal control theory to determine the optimal rate of change in the subscription fee and the optimal ratio of ad space to the total web page space for a web content provider. An optimal solution is obtained using the maximum principle approach and the model predictive control approach. Numerical experiments show that it is preferable to use the first approach when the planning horizon is short and the second approach when the planning horizon is long","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":"36 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":"135599653","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}
The characterisation of probability distribution plays an important role in statistical studies. There are various methods of characterisation available in the literature. The characterisation using truncated moments limits the observations; hence, researchers may save time and cost. In this paper, the characterisation of three general forms of continuous distributions based on doubly truncated moments has been studied. The results are given simply and explicitly. Further, the results have been applied to some well-known continuous distributions.
{"title":"Characterisation of some generalized continuous distributions by doubly truncated moments","authors":"Haseeb Athar, M. Ahsanullah, Mohd. Almech Ali","doi":"10.37190/ord230101","DOIUrl":"https://doi.org/10.37190/ord230101","url":null,"abstract":"The characterisation of probability distribution plays an important role in statistical studies. There are various methods of characterisation available in the literature. The characterisation using truncated moments limits the observations; hence, researchers may save time and cost. In this paper, the characterisation of three general forms of continuous distributions based on doubly truncated moments has been studied. The results are given simply and explicitly. Further, the results have been applied to some well-known continuous distributions.","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":"688 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76280112","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}
Countries’ defence industries are the leading indicator of their global power. The warehouse is the place where the materials are kept until the customer order arrives so that the companies are viable and can respond appropriately to internal/external customer demands. In this regard, warehouse location plays a vital role in the defence industry in terms of storage options with increased flexibility, a simplified supply chain with cost management and optimal positioning according to deployment locations. In this study, the decision on the location of warehouses for logistic support during the warranty period of military vehicles manufactured and supplied to the armed forces by a defence company was made. It is aimed to propose the best solution to a real-life problem with high complexity, containing many data and constraints. In this context, the criteria that are thought to be most relevant to this problem have been determined by taking expert opinions. Having determined the order of importance of the requirements by the analytical hierarchy process (AHP) with the Super Decisions V 2.10, their weights were included as a coefficient of the objective function in the goal programming (GP) model. As a result of solving the GP model using GAMS (general algebraic modelling system), it was decided to select the warehouses that provided the optimal results among the alternative warehouse locations in 9 different locations. Furthermore, to see the impact of changes in criterion weights, sensitivity analysis has also been included. The significance of this research lies within the integrated usage of AHP and GP in the defence industry when determining warehouse locations by the experts’ opinions. With this study, not only a solution strategy was developed, but also a basis for the warehouse location decision in the defence industry projects already signed or to be signed was given.
一个国家的国防工业是其全球实力的主要指标。仓库是在客户订单到达之前保存材料的地方，以便公司能够生存并能够适当地响应内部/外部客户的需求。在这方面，仓库位置在国防工业的存储选择方面发挥着至关重要的作用，具有更高的灵活性，简化的供应链，成本管理和根据部署位置的最佳定位。在这项研究中，决定了一家防务公司制造和供应给武装部队的军用车辆在保证期内后勤支助仓库的地点。它旨在为现实生活中具有高复杂性、包含许多数据和约束的问题提出最佳解决方案。在这方面，被认为与这个问题最相关的标准是通过听取专家意见来确定的。利用Super Decisions V 2.10，通过层次分析法(AHP)确定需求的重要顺序，将其权重作为目标规划(GP)模型中目标函数的系数。利用GAMS(通用代数建模系统)求解GP模型，决定在9个不同地点的备选仓库位置中选择提供最优结果的仓库。此外，为了看到标准权重变化的影响，还包括敏感性分析。本研究的意义在于结合AHP和GP在国防工业中根据专家意见确定仓库位置的应用。通过本研究，不仅制定了解决方案策略，而且为国防工业项目中已经签署或即将签署的仓库选址决策提供了依据。
{"title":"An integrated modelling approach for an optimal location of warehouses in the defence industry organisation","authors":"Melda Gelibolu Bayrakcı, Ö. Baykoç","doi":"10.37190/ord230203","DOIUrl":"https://doi.org/10.37190/ord230203","url":null,"abstract":"Countries’ defence industries are the leading indicator of their global power. The warehouse is the place where the materials are kept until the customer order arrives so that the companies are viable and can respond appropriately to internal/external customer demands. In this regard, warehouse location plays a vital role in the defence industry in terms of storage options with increased flexibility, a simplified supply chain with cost management and optimal positioning according to deployment locations. In this study, the decision on the location of warehouses for logistic support during the warranty period of military vehicles manufactured and supplied to the armed forces by a defence company was made. It is aimed to propose the best solution to a real-life problem with high complexity, containing many data and constraints. In this context, the criteria that are thought to be most relevant to this problem have been determined by taking expert opinions. Having determined the order of importance of the requirements by the analytical hierarchy process (AHP) with the Super Decisions V 2.10, their weights were included as a coefficient of the objective function in the goal programming (GP) model. As a result of solving the GP model using GAMS (general algebraic modelling system), it was decided to select the warehouses that provided the optimal results among the alternative warehouse locations in 9 different locations. Furthermore, to see the impact of changes in criterion weights, sensitivity analysis has also been included. The significance of this research lies within the integrated usage of AHP and GP in the defence industry when determining warehouse locations by the experts’ opinions. With this study, not only a solution strategy was developed, but also a basis for the warehouse location decision in the defence industry projects already signed or to be signed was given.","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":"89 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82142871","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}
Today’s world is characterised by competitive environments, optimal resource utilization, and cost reduction, which has resulted in an increasing role for metaheuristic algorithms in solving complex modern problems. As a result, this paper introduces the gold rush optimizer (GRO), a population-based metaheuristic algorithm that simulates how gold-seekers prospected for gold during the Gold Rush Era using three key concepts of gold prospecting: migration, collaboration, and panning. The GRO algorithm is compared to twelve well-known metaheuristic algorithms on 29 benchmark test cases to assess the proposed approach’s performance. For scientific evaluation, the Friedman and Wilcoxon signed-rank tests are used. In addition to these test cases, the GRO algorithm is evaluated using three real-world engineering problems. The results indicated that the proposed algorithm was more capable than other algorithms in proposing qualitative and competitive solutions.
{"title":"Gold rush optimizer: A new population-based metaheuristic algorithm","authors":"Kamran Zolfi","doi":"10.37190/ord230108","DOIUrl":"https://doi.org/10.37190/ord230108","url":null,"abstract":"Today’s world is characterised by competitive environments, optimal resource utilization, and cost reduction, which has resulted in an increasing role for metaheuristic algorithms in solving complex modern problems. As a result, this paper introduces the gold rush optimizer (GRO), a population-based metaheuristic algorithm that simulates how gold-seekers prospected for gold during the Gold Rush Era using three key concepts of gold prospecting: migration, collaboration, and panning. The GRO algorithm is compared to twelve well-known metaheuristic algorithms on 29 benchmark test cases to assess the proposed approach’s performance. For scientific evaluation, the Friedman and Wilcoxon signed-rank tests are used. In addition to these test cases, the GRO algorithm is evaluated using three real-world engineering problems. The results indicated that the proposed algorithm was more capable than other algorithms in proposing qualitative and competitive solutions.","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":"42 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91281367","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}
Nur Ain Mohd Hassan, K. Zakaria, Kamalrudin Mohamed Salleh, Siti Mashani Ahmad
The paper explores the long-term causal relationships of Malaysian palm oil exports with the real effective exchange rate of the respective importing countries, palm oil consumption, vegetable oil production, and GDP growth. The study applied panel cointegration and causality approaches based on data from 10 main palm oil importing countries between 2004 and 2018. The impacts of economic growth, the effective real exchange rate, and the production of other vegetable oils by the main palm oil importing countries on Malaysian palm oil exports were found to be negative. However, palm oil consumption by the main palm oil importers was found to be a statistically significant positive determinant of Malaysian palm oil exports. This finding indicates that consumption has a direct positive effect on the demand for exports. A panel Granger causality analysis revealed a unidirectional causality between importing countries’ production of other vegetable oils and Malaysian exports of palm oil.
{"title":"An empirical analysis of Malaysian palm oil export to world major palm oil importing countries: evidence from a panel cointegration model","authors":"Nur Ain Mohd Hassan, K. Zakaria, Kamalrudin Mohamed Salleh, Siti Mashani Ahmad","doi":"10.37190/ord230105","DOIUrl":"https://doi.org/10.37190/ord230105","url":null,"abstract":"The paper explores the long-term causal relationships of Malaysian palm oil exports with the real effective exchange rate of the respective importing countries, palm oil consumption, vegetable oil production, and GDP growth. The study applied panel cointegration and causality approaches based on data from 10 main palm oil importing countries between 2004 and 2018. The impacts of economic growth, the effective real exchange rate, and the production of other vegetable oils by the main palm oil importing countries on Malaysian palm oil exports were found to be negative. However, palm oil consumption by the main palm oil importers was found to be a statistically significant positive determinant of Malaysian palm oil exports. This finding indicates that consumption has a direct positive effect on the demand for exports. A panel Granger causality analysis revealed a unidirectional causality between importing countries’ production of other vegetable oils and Malaysian exports of palm oil.","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":"43 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78561042","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}
Probabilistic price forecasting has recently gained attention in power trading because decisions based on such predictions can yield significantly higher profits than those made with point forecasts alone. At the same time, methods are being developed to combine predictive distributions, since no model is perfect and averaging generally improves forecasting performance. In this article, we address the question of whether using CRPS learning, a novel weighting technique minimizing the continuous ranked probability score (CRPS), leads to optimal decisions in day-ahead bidding. To this end, we conduct an empirical study using hourly day-ahead electricity prices from the German EPEX market. We find that increasing the diversity of an ensemble can have a positive impact on accuracy. At the same time, the higher computational cost of using CRPS learning compared to an equal-weighted aggregation of distributions is not offset by higher profits, despite significantly more accurate predictions.
{"title":"Combining predictive distributions of electricity prices. Does minimizing the CRPS lead to optimal decisions in day-ahead bidding?","authors":"Weronika Nitka, Rafał Weron","doi":"10.37190/ord230307","DOIUrl":"https://doi.org/10.37190/ord230307","url":null,"abstract":"Probabilistic price forecasting has recently gained attention in power trading because decisions based on such predictions can yield significantly higher profits than those made with point forecasts alone. At the same time, methods are being developed to combine predictive distributions, since no model is perfect and averaging generally improves forecasting performance. In this article, we address the question of whether using CRPS learning, a novel weighting technique minimizing the continuous ranked probability score (CRPS), leads to optimal decisions in day-ahead bidding. To this end, we conduct an empirical study using hourly day-ahead electricity prices from the German EPEX market. We find that increasing the diversity of an ensemble can have a positive impact on accuracy. At the same time, the higher computational cost of using CRPS learning compared to an equal-weighted aggregation of distributions is not offset by higher profits, despite significantly more accurate predictions.","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":"120 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":"135599318","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}
This paper aims to develop an inventory model considering discrete demand, coordinated pricing, and multiple delivery policy in a single-buyer single-supplier production-inventory system. The shortage is not allowed and the planning horizon is considered to be infinite. The main objective of the framework is to equip the decision-maker with optimal order, pricing, and shipment quantities to maximize the total profit of the system. The results obtained from the numerical example reveal that the proposed approach with an average selling price equal to about 94% of the classical model, has resulted in an average profit increase of about 16% and an average order increase of about 34% compared to the classical approach
{"title":"Pricing-inventory model with discrete demand and delivery orders","authors":"Heibatolah Sadeghi, Hêriş Golpîra, Faicel Hnaien, Cosimo Magazzino","doi":"10.37190/ord230308","DOIUrl":"https://doi.org/10.37190/ord230308","url":null,"abstract":"This paper aims to develop an inventory model considering discrete demand, coordinated pricing, and multiple delivery policy in a single-buyer single-supplier production-inventory system. The shortage is not allowed and the planning horizon is considered to be infinite. The main objective of the framework is to equip the decision-maker with optimal order, pricing, and shipment quantities to maximize the total profit of the system. The results obtained from the numerical example reveal that the proposed approach with an average selling price equal to about 94% of the classical model, has resulted in an average profit increase of about 16% and an average order increase of about 34% compared to the classical approach","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":"7 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":"135599347","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}
Because of the COVID-19 situation, selection for a teaching assistant position to get a TA scholarship in a university in Thailand needs to be performed online by the formed committee. Due to the online process and the limited number of scholarships offered by the university, beyond the face-to-face interview, multiple-criteria decision analysis can help to select a proper student. In this study, we use the extended VIKOR method with fuzzy numbers to help committees to select the students from the applicants. The criteria and the weights of the criteria are provided with the help of committees. Both trapezoidal and triangular linguistic variables are used to find the solution and to observe the range of the possible result. The different weights supporting the strategy of maximum group utility are varied to detect the potential alternatives. The ranking results are also compared with the one obtained from the TODIM approach to illustrate the appropriate alternative.
{"title":"Teaching assistant selection in Thailand by using an extended VIKOR based on piecewise linear approximation of fuzzy numbers","authors":"Akan Narabin, Phairoj Samutrak","doi":"10.37190/ord230306","DOIUrl":"https://doi.org/10.37190/ord230306","url":null,"abstract":"Because of the COVID-19 situation, selection for a teaching assistant position to get a TA scholarship in a university in Thailand needs to be performed online by the formed committee. Due to the online process and the limited number of scholarships offered by the university, beyond the face-to-face interview, multiple-criteria decision analysis can help to select a proper student. In this study, we use the extended VIKOR method with fuzzy numbers to help committees to select the students from the applicants. The criteria and the weights of the criteria are provided with the help of committees. Both trapezoidal and triangular linguistic variables are used to find the solution and to observe the range of the possible result. The different weights supporting the strategy of maximum group utility are varied to detect the potential alternatives. The ranking results are also compared with the one obtained from the TODIM approach to illustrate the appropriate alternative.","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":"21 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":"135599930","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}
Pick-and-pass systems are a part of picker-to-parts order-picking systems and constitute a very common storage solution in cases where customer orders are usually small and need to be completed very quickly. As workers pick items in the zones connected by conveyor, their work needs to be coordinated. The paper presents MILP models that optimize the order-picking process. The first model uses information about expected demand for items to solve the storage location problem and balance the workload across zones. The task of the next model is order-batching and sequencing – two concepts are presented that meet different assumptions. The results of the exemplary tasks solved with the use of the proposed MILP models show that the total picking time of a set of orders can be reduced by about 35-45% in comparison with random policies. The paper presents an equation for the lower bound of a makespan. Recommendations about the number of zones that guarantee the required system efficiency are also introduced.
{"title":"Linear programming models for optimal workload and batching in pick-and-pass warehousing systems","authors":"Grzegorz Tarczyński","doi":"10.37190/ord230309","DOIUrl":"https://doi.org/10.37190/ord230309","url":null,"abstract":"Pick-and-pass systems are a part of picker-to-parts order-picking systems and constitute a very common storage solution in cases where customer orders are usually small and need to be completed very quickly. As workers pick items in the zones connected by conveyor, their work needs to be coordinated. The paper presents MILP models that optimize the order-picking process. The first model uses information about expected demand for items to solve the storage location problem and balance the workload across zones. The task of the next model is order-batching and sequencing – two concepts are presented that meet different assumptions. The results of the exemplary tasks solved with the use of the proposed MILP models show that the total picking time of a set of orders can be reduced by about 35-45% in comparison with random policies. The paper presents an equation for the lower bound of a makespan. Recommendations about the number of zones that guarantee the required system efficiency are also introduced.","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":"120 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":"135599348","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}
Seminars are offered to students for education in various disciplines. The seminars may be limited in terms of the maximum number of participants, e.g., to have lively interactions. Due to capacity limitations, those seminars are often offered several times to serve the students’ demands. Still, some seminars are more popular than others and it may not be possible to grant access to all interested students due to capacity limitations. In this paper, a simple, but efficient random selection using key objectives (SEKO) assignment strategy is proposed which achieves the following goals: (i) efficiency by utilizing all available seminar places, (ii) satisfying all students by trying to assign at least one seminar to each student, and (iii) fairness by considering the number of assigned seminars per student. We formulate various theoretical optimization models using integer linear programming (ILP) and compare their solutions to the SEKO assignment based on a real-world data set. The real-world data set is also used as the basis for generating large data sets to investigate the scalability in terms of demand and number of seminars. Furthermore, the first-in first-out (FIFO) assignment, as a typical implementation of fair assignments in practice, is compared to SEKO in terms of utilization and fairness. The results show that the FIFO assignment suffers in real world situations regarding fairness, while the SEKO assignment is close to the optimum and scales regarding computational time in contrast to the ILP.
{"title":"The SEKO assignment. Efficient and fair assignment of students to multiple seminars","authors":"Tobias Hoßfeld _","doi":"10.37190/ord230301","DOIUrl":"https://doi.org/10.37190/ord230301","url":null,"abstract":"Seminars are offered to students for education in various disciplines. The seminars may be limited in terms of the maximum number of participants, e.g., to have lively interactions. Due to capacity limitations, those seminars are often offered several times to serve the students’ demands. Still, some seminars are more popular than others and it may not be possible to grant access to all interested students due to capacity limitations. In this paper, a simple, but efficient random selection using key objectives (SEKO) assignment strategy is proposed which achieves the following goals: (i) efficiency by utilizing all available seminar places, (ii) satisfying all students by trying to assign at least one seminar to each student, and (iii) fairness by considering the number of assigned seminars per student. We formulate various theoretical optimization models using integer linear programming (ILP) and compare their solutions to the SEKO assignment based on a real-world data set. The real-world data set is also used as the basis for generating large data sets to investigate the scalability in terms of demand and number of seminars. Furthermore, the first-in first-out (FIFO) assignment, as a typical implementation of fair assignments in practice, is compared to SEKO in terms of utilization and fairness. The results show that the FIFO assignment suffers in real world situations regarding fairness, while the SEKO assignment is close to the optimum and scales regarding computational time in contrast to the ILP.","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":"117 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":"135599932","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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